librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

modelId string	author string	last_modified timestamp[us, tz=UTC]	downloads int64	likes int64	library_name string	tags list	pipeline_tag string	createdAt timestamp[us, tz=UTC]	card string
lesso10/dbaf1184-5899-4d20-964a-33ecb54ce416	lesso10	2025-01-15T16:22:26Z	14	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "custom_code", "base_model:NovaSearch/stella_en_1.5B_v5", "base_model:adapter:NovaSearch/stella_en_1.5B_v5", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T16:12:57Z	--- library_name: peft license: mit base_model: dunzhang/stella_en_1.5B_v5 tags: - axolotl - generated_from_trainer model-index: - name: dbaf1184-5899-4d20-964a-33ecb54ce416 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: dunzhang/stella_en_1.5B_v5 bf16: true chat_template: llama3 datasets: - data_files: - c17c59740c4fc07c_train_data.json ds_type: json format: custom path: /workspace/input_data/c17c59740c4fc07c_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso10/dbaf1184-5899-4d20-964a-33ecb54ce416 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/c17c59740c4fc07c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21989a9f-7539-4956-94ad-ee9bd5631eb8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21989a9f-7539-4956-94ad-ee9bd5631eb8 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # dbaf1184-5899-4d20-964a-33ecb54ce416 This model is a fine-tuned version of [dunzhang/stella_en_1.5B_v5](https://huggingface.co/dunzhang/stella_en_1.5B_v5) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0017 \| 5 \| nan \| \| 0.0 \| 0.0034 \| 10 \| nan \| \| 0.0 \| 0.0051 \| 15 \| nan \| \| 0.0 \| 0.0068 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
JacksonBrune/9d3840b2-d488-4fbf-97e3-b030d9e3517c	JacksonBrune	2025-01-15T16:19:37Z	9	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "region:us" ]	null	2025-01-15T15:50:19Z	--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: 9d3840b2-d488-4fbf-97e3-b030d9e3517c results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: JacksonBrune/9d3840b2-d488-4fbf-97e3-b030d9e3517c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|eot_id\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: birthdya-sn56-18-Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 9d3840b2-d488-4fbf-97e3-b030d9e3517c This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8708 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.145 \| 0.0001 \| 1 \| 2.5498 \| \| 2.7497 \| 0.0002 \| 3 \| 2.5405 \| \| 1.9838 \| 0.0003 \| 6 \| 2.3407 \| \| 2.057 \| 0.0005 \| 9 \| 1.8708 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
antonvinny/whisper-tiny-gs	antonvinny	2025-01-15T16:18:37Z	32	0	transformers	[ "transformers", "tensorboard", "onnx", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "en", "base_model:openai/whisper-small", "base_model:quantized:openai/whisper-small", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2025-01-15T15:02:21Z	--- library_name: transformers language: - en license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-tiny-gs results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # whisper-tiny-gs This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0001 - Wer: 2.4950 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 600 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| \|:-------------:\|:--------:\|:----:\|:---------------:\|:------:\| \| 0.0002 \| 66.6667 \| 200 \| 0.0003 \| 2.4950 \| \| 0.0001 \| 133.3333 \| 400 \| 0.0001 \| 2.4950 \| \| 0.0001 \| 200.0 \| 600 \| 0.0001 \| 2.4950 \| ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
dimasik2987/77bfbadf-495d-408a-be33-a01f7dedab05	dimasik2987	2025-01-15T16:17:23Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "custom_code", "base_model:NovaSearch/stella_en_1.5B_v5", "base_model:adapter:NovaSearch/stella_en_1.5B_v5", "license:mit", "region:us" ]	null	2025-01-15T16:13:05Z	--- library_name: peft license: mit base_model: dunzhang/stella_en_1.5B_v5 tags: - axolotl - generated_from_trainer model-index: - name: 77bfbadf-495d-408a-be33-a01f7dedab05 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: dunzhang/stella_en_1.5B_v5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - c17c59740c4fc07c_train_data.json ds_type: json format: custom path: /workspace/input_data/c17c59740c4fc07c_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik2987/77bfbadf-495d-408a-be33-a01f7dedab05 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/c17c59740c4fc07c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21989a9f-7539-4956-94ad-ee9bd5631eb8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21989a9f-7539-4956-94ad-ee9bd5631eb8 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 77bfbadf-495d-408a-be33-a01f7dedab05 This model is a fine-tuned version of [dunzhang/stella_en_1.5B_v5](https://huggingface.co/dunzhang/stella_en_1.5B_v5) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0017 \| 5 \| nan \| \| 0.0 \| 0.0034 \| 10 \| nan \| \| 0.0 \| 0.0051 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Error410/JVCGPT-Mini-beta-GGUF	Error410	2025-01-15T16:17:14Z	34	0	null	[ "gguf", "jvc", "issou", "aya", "fr", "dataset:Error410/sharegpt", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:quantized:meta-llama/Llama-3.2-3B-Instruct", "endpoints_compatible", "region:us" ]	null	2025-01-12T02:14:23Z	--- datasets: - Error410/sharegpt language: - fr base_model: - meta-llama/Llama-3.2-3B-Instruct tags: - jvc - issou - aya --- # Error410/JVCGPT-Mini-beta ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/R0ZRrgMITvprcoXajAnPi.png) ## Description Ce modèle est une version fine-tunée de Llama 3.2 3B ayant pour objectif de reproduire les styles d’écriture et les posts des utilisateurs du forum jeuxvideo.com. Entraîné sur une fraction des données publiques de JVArchive, ce modèle est conçu pour capturer le ton, l’humour et les références propres à cette communauté en ligne. ## Détails du modèle - Base : Llama 3.2 (3B paramètres) - Dataset utilisé : 2% de JVArchive (public et accessible librement) - Entraînement : 3 heures pour 2 epoch sur un cluster de 8 NVIDIA L40S sur un contexte de 4096 tokens. - Objectif : Générer des messages imitant le style des utilisateurs de jeuxvideo.com - Accès : Dataset et modèles disponibles gratuitement sur notre repo [Error410](https://huggingface.co/Error410/). ## Format du prompt ``` <\|begin_of_text\|><\|start_header_id\|>system<\|end_header_id\|> Réponds comme un membre actif du forum, en respectant le style, les références et le ton typiques du topic en cours. Topic: <TOPIC>\|eot_id\|><\|start_header_id\|>user<\|end_header_id\|> <\|im_pseudo\|>PSEUDO<\|end_pseudo\|> <\|im_date\|>DATE<\|end_date\|> <\|begin_of_post\|>POST<\|end_of_post\|><\|eot_id\|><\|start_header_id\|>assistant<\|end_header_id\|> <\|im_pseudo\|>PSEUDO<\|end_pseudo\|> <\|im_date\|>DATE<\|end_date\|> <\|begin_of_post\|>POST<\|end_of_post\|><\|eot_id\|> ``` Template SillyTavern: https://huggingface.co/Error410/JVCGPT-Mini-beta/blob/main/SillyTavern%20Prompt%20Format.json ## Performances - Style : Captures efficacement les références, expressions, et styles d’écriture caractéristiques des forums jeuxvideo.com. - Légèreté : Adapté pour tout grâce à sa petit taille de 3B de paramètres. - Temps de réponse : Optimisé pour des générations rapides à faible coût. ## Dataset Le modèle a été entraîné sur une sélection de 2% des archives de JVArchive (100 000 topics). Ces données ont été traitées et filtrées pour garantir une qualité et une diversité optimales. ## Licence Le modèle, le dataset, et tous les fichiers associés sont mis à disposition gratuitement sous la même license (PUBLIC) que JVArchive, dans notre repo. ## Remerciements Un grand merci à JVArchive pour l’accès aux données publiques et à la communauté jeuxvideo.com pour son inspiration. Ce projet est dédié aux passionnés de l’histoire du forum et à la culture internet. ## Auteurs - [Greums](https://huggingface.co/Greums/) : Pro des datasets bordelent cimer chef - [Undi](https://huggingface.co/Undi95/)
Error410/JVCGPT-Mini-beta	Error410	2025-01-15T16:16:22Z	17	0	null	[ "safetensors", "llama", "jvc", "issou", "aya", "fr", "dataset:Error410/sharegpt", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:finetune:meta-llama/Llama-3.2-3B-Instruct", "region:us" ]	null	2025-01-12T01:45:03Z	--- datasets: - Error410/sharegpt language: - fr base_model: - meta-llama/Llama-3.2-3B-Instruct tags: - jvc - issou - aya --- # Error410/JVCGPT-Mini-beta ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/R0ZRrgMITvprcoXajAnPi.png) ## Description Ce modèle est une version fine-tunée de Llama 3.2 3B ayant pour objectif de reproduire les styles d’écriture et les posts des utilisateurs du forum jeuxvideo.com. Entraîné sur une fraction des données publiques de JVArchive, ce modèle est conçu pour capturer le ton, l’humour et les références propres à cette communauté en ligne. ## Détails du modèle - Base : Llama 3.2 (3B paramètres) - Dataset utilisé : 2% de JVArchive (public et accessible librement) - Entraînement : 3 heures pour 2 epoch sur un cluster de 8 NVIDIA L40S sur un contexte de 4096 tokens. - Objectif : Générer des messages imitant le style des utilisateurs de jeuxvideo.com - Accès : Dataset et modèles disponibles gratuitement sur notre repo [Error410](https://huggingface.co/Error410/). ## Format du prompt ``` <\|begin_of_text\|><\|start_header_id\|>system<\|end_header_id\|> Réponds comme un membre actif du forum, en respectant le style, les références et le ton typiques du topic en cours. Topic: <TOPIC>\|eot_id\|><\|start_header_id\|>user<\|end_header_id\|> <\|im_pseudo\|>PSEUDO<\|end_pseudo\|> <\|im_date\|>DATE<\|end_date\|> <\|begin_of_post\|>POST<\|end_of_post\|><\|eot_id\|><\|start_header_id\|>assistant<\|end_header_id\|> <\|im_pseudo\|>PSEUDO<\|end_pseudo\|> <\|im_date\|>DATE<\|end_date\|> <\|begin_of_post\|>POST<\|end_of_post\|><\|eot_id\|> ``` Template SillyTavern: https://huggingface.co/Error410/JVCGPT-Mini-beta/blob/main/SillyTavern%20Prompt%20Format.json ## Performances - Style : Captures efficacement les références, expressions, et styles d’écriture caractéristiques des forums jeuxvideo.com. - Légèreté : Adapté pour tout grâce à sa petit taille de 3B de paramètres. - Temps de réponse : Optimisé pour des générations rapides à faible coût. ## Dataset Le modèle a été entraîné sur une sélection de 2% des archives de JVArchive (100 000 topics). Ces données ont été traitées et filtrées pour garantir une qualité et une diversité optimales. ## Licence Le modèle, le dataset, et tous les fichiers associés sont mis à disposition gratuitement sous la même license (PUBLIC) que JVArchive, dans notre repo. ## Remerciements Un grand merci à JVArchive pour l’accès aux données publiques et à la communauté jeuxvideo.com pour son inspiration. Ce projet est dédié aux passionnés de l’histoire du forum et à la culture internet. ## Auteurs - [Greums](https://huggingface.co/Greums/) : Pro des datasets bordelent cimer chef - [Undi](https://huggingface.co/Undi95/)
lesso13/6d237b86-7931-4795-b258-7cf41ed07b45	lesso13	2025-01-15T16:16:06Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-1.5B-Instruct", "base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:49:16Z	--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 6d237b86-7931-4795-b258-7cf41ed07b45 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-1.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 756452db934ae1d1_train_data.json ds_type: json format: custom path: /workspace/input_data/756452db934ae1d1_train_data.json type: field_instruction: question field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso13/6d237b86-7931-4795-b258-7cf41ed07b45 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/756452db934ae1d1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 74979543-06fb-451f-b2f1-4786823d5776 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 74979543-06fb-451f-b2f1-4786823d5776 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 6d237b86-7931-4795-b258-7cf41ed07b45 This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9857 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0001 \| 1 \| 1.0872 \| \| 1.1047 \| 0.0008 \| 8 \| 1.0565 \| \| 1.0449 \| 0.0016 \| 16 \| 1.0030 \| \| 1.04 \| 0.0023 \| 24 \| 0.9857 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
bbytxt/99b7be35-ecb0-4251-93fd-0b9840307a9c	bbytxt	2025-01-15T16:16:03Z	7	0	peft	[ "peft", "safetensors", "phi", "axolotl", "generated_from_trainer", "base_model:echarlaix/tiny-random-PhiForCausalLM", "base_model:adapter:echarlaix/tiny-random-PhiForCausalLM", "license:apache-2.0", "region:us" ]	null	2025-01-15T16:15:04Z	--- library_name: peft license: apache-2.0 base_model: echarlaix/tiny-random-PhiForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 99b7be35-ecb0-4251-93fd-0b9840307a9c results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: echarlaix/tiny-random-PhiForCausalLM bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - a036efca81d0f95e_train_data.json ds_type: json format: custom path: /workspace/input_data/a036efca81d0f95e_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/99b7be35-ecb0-4251-93fd-0b9840307a9c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/a036efca81d0f95e_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 special_tokens: pad_token: <\|endoftext\|> strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21b208df-454c-48c3-9b23-520ad94bb3d4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21b208df-454c-48c3-9b23-520ad94bb3d4 warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 99b7be35-ecb0-4251-93fd-0b9840307a9c This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 6.7069 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 6.9344 \| 0.0019 \| 1 \| 6.9199 \| \| 6.6524 \| 0.0970 \| 50 \| 6.7949 \| \| 6.5216 \| 0.1941 \| 100 \| 6.7281 \| \| 6.4882 \| 0.2911 \| 150 \| 6.7088 \| \| 6.4793 \| 0.3882 \| 200 \| 6.7069 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
roleplaiapp/Llama-3.3-70B-Instruct-Q4_K_M-GGUF	roleplaiapp	2025-01-15T16:15:35Z	49	0	transformers	[ "transformers", "gguf", "llama-cpp", "Llama-3.3-70B-Instruct", "Q4_K_M", "meta-llama", "code", "math", "chat", "roleplay", "text-generation", "safetensors", "nlp", "en", "fr", "it", "pt", "hi", "es", "th", "de", "base_model:meta-llama/Llama-3.1-70B", "base_model:quantized:meta-llama/Llama-3.1-70B", "endpoints_compatible", "region:us", "conversational" ]	text-generation	2025-01-15T13:28:50Z	--- library_name: transformers language: - en - fr - it - pt - hi - es - th - de base_model: - meta-llama/Llama-3.1-70B tags: - llama-cpp - Llama-3.3-70B-Instruct - gguf - Q4_K_M - llama-cpp - gguf - meta-llama - code - math - chat - roleplay - text-generation - safetensors - nlp - code pipeline_tag: text-generation --- # Llama-3.3-70B-Instruct-Q4_K_M-GGUF Repo: `roleplaiapp/Llama-3.3-70B-Instruct-Q4_K_M -GGUF` Original Model: `Llama-3.3-70B-Instruct` Organization: `meta-llama` Quantized File: `llama-3.3-70b-instruct-q3_k_m.gguf` Quantization: `GGUF` Quantization Method: `Q4_K_M ` Use Imatrix: `False` Split Model: `False` ## Overview This is an GGUF Q4_K_M quantized version of [Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct). ## Quantization By I often have idle A100 GPUs while building/testing and training the RP app, so I put them to use quantizing models. I hope the community finds these quantizations useful. Andrew Webby @ [RolePlai](https://roleplai.app/)
exala/db_aca2_7.2.1	exala	2025-01-15T16:14:07Z	17	0	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T16:13:53Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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(2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
Oscar2384/intime-sosten-copa-B-con-soft-algodon-elasticad-surtido	Oscar2384	2025-01-15T16:13:34Z	20	0	diffusers	[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	2025-01-15T15:52:08Z	--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: COPASOSELAS --- # Intime Sosten Copa B Con Soft Algodon Elasticad Surtido <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `COPASOSELAS` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Oscar2384/intime-sosten-copa-B-con-soft-algodon-elasticad-surtido', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF	paultimothymooney	2025-01-15T16:13:33Z	40	0	transformers	[ "transformers", "gguf", "code", "codeqwen", "chat", "qwen", "qwen-coder", "llama-cpp", "gguf-my-repo", "text-generation", "en", "base_model:Qwen/Qwen2.5-Coder-0.5B-Instruct", "base_model:quantized:Qwen/Qwen2.5-Coder-0.5B-Instruct", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	text-generation	2025-01-15T16:13:27Z	--- license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct/blob/main/LICENSE language: - en base_model: Qwen/Qwen2.5-Coder-0.5B-Instruct pipeline_tag: text-generation library_name: transformers tags: - code - codeqwen - chat - qwen - qwen-coder - llama-cpp - gguf-my-repo --- # paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF This model was converted to GGUF format from [`Qwen/Qwen2.5-Coder-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -c 2048 ```
phonemetransformers/CHILDES-Indonesian-phoneme-tokenizer	phonemetransformers	2025-01-15T16:12:07Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:54Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
oldiday/27f6fcb8-4599-455c-bbaf-98396a85a925	oldiday	2025-01-15T16:10:02Z	13	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-135M", "base_model:adapter:unsloth/SmolLM2-135M", "license:apache-2.0", "region:us" ]	null	2025-01-15T16:00:20Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-135M tags: - axolotl - generated_from_trainer model-index: - name: 27f6fcb8-4599-455c-bbaf-98396a85a925 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-135M bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e5fba043d1f22bc2_train_data.json ds_type: json format: custom path: /workspace/input_data/e5fba043d1f22bc2_train_data.json type: field_instruction: prompt field_output: reference_response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: oldiday/27f6fcb8-4599-455c-bbaf-98396a85a925 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 5.0e-05 load_in_4bit: false load_in_8bit: false local_rank: 0 logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 100 micro_batch_size: 8 mlflow_experiment_name: /tmp/e5fba043d1f22bc2_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: techspear-hub wandb_mode: online wandb_name: 15e5c164-e834-4f75-975b-0d306607a752 wandb_project: Gradients-On-Six wandb_run: your_name wandb_runid: 15e5c164-e834-4f75-975b-0d306607a752 warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details><br> # 27f6fcb8-4599-455c-bbaf-98396a85a925 This model is a fine-tuned version of [unsloth/SmolLM2-135M](https://huggingface.co/unsloth/SmolLM2-135M) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3658 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0007 \| 1 \| 1.4431 \| \| 1.4342 \| 0.0059 \| 9 \| 1.4399 \| \| 1.4666 \| 0.0117 \| 18 \| 1.4246 \| \| 1.4174 \| 0.0176 \| 27 \| 1.4081 \| \| 1.4487 \| 0.0235 \| 36 \| 1.3942 \| \| 1.3878 \| 0.0293 \| 45 \| 1.3837 \| \| 1.3904 \| 0.0352 \| 54 \| 1.3762 \| \| 1.2992 \| 0.0411 \| 63 \| 1.3713 \| \| 1.3923 \| 0.0470 \| 72 \| 1.3683 \| \| 1.3503 \| 0.0528 \| 81 \| 1.3666 \| \| 1.4249 \| 0.0587 \| 90 \| 1.3660 \| \| 1.3777 \| 0.0646 \| 99 \| 1.3658 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
tarabukinivan/a0bf2150-f712-41d2-9b98-6973dcf1c843	tarabukinivan	2025-01-15T16:09:25Z	9	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-3B", "base_model:adapter:Qwen/Qwen2.5-3B", "license:other", "region:us" ]	null	2025-01-15T15:39:26Z	--- library_name: peft license: other base_model: Qwen/Qwen2.5-3B tags: - axolotl - generated_from_trainer model-index: - name: a0bf2150-f712-41d2-9b98-6973dcf1c843 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-3B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 21f641ae0efcd8d6_train_data.json ds_type: json format: custom path: /workspace/input_data/21f641ae0efcd8d6_train_data.json type: field_instruction: prompt field_output: chosen format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: tarabukinivan/a0bf2150-f712-41d2-9b98-6973dcf1c843 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/21f641ae0efcd8d6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 9e2f882e-8f4c-4fd9-b3f6-e92c5704a050 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 9e2f882e-8f4c-4fd9-b3f6-e92c5704a050 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # a0bf2150-f712-41d2-9b98-6973dcf1c843 This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0546 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0001 \| 1 \| 1.8047 \| \| 1.2561 \| 0.0007 \| 13 \| 1.1174 \| \| 1.1405 \| 0.0013 \| 26 \| 1.0613 \| \| 1.116 \| 0.0020 \| 39 \| 1.0546 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization	MayBashendy	2025-01-15T16:09:17Z	7	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T14:57:24Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5617 - Qwk: 0.4874 - Mse: 0.5617 - Rmse: 0.7495 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0339 \| 2 \| 4.2196 \| -0.0288 \| 4.2196 \| 2.0542 \| \| No log \| 0.0678 \| 4 \| 2.2233 \| 0.0640 \| 2.2233 \| 1.4911 \| \| No log \| 0.1017 \| 6 \| 1.2161 \| 0.0258 \| 1.2161 \| 1.1028 \| \| No log \| 0.1356 \| 8 \| 0.9924 \| 0.0330 \| 0.9924 \| 0.9962 \| \| No log \| 0.1695 \| 10 \| 0.8343 \| 0.1465 \| 0.8343 \| 0.9134 \| \| No log \| 0.2034 \| 12 \| 0.8470 \| 0.1648 \| 0.8470 \| 0.9203 \| \| No log \| 0.2373 \| 14 \| 0.8884 \| 0.0983 \| 0.8884 \| 0.9425 \| \| No log \| 0.2712 \| 16 \| 1.0015 \| -0.0066 \| 1.0015 \| 1.0008 \| \| No log \| 0.3051 \| 18 \| 0.9798 \| 0.0851 \| 0.9798 \| 0.9898 \| \| No log \| 0.3390 \| 20 \| 1.0506 \| -0.0377 \| 1.0506 \| 1.0250 \| \| No log \| 0.3729 \| 22 \| 1.3475 \| 0.0262 \| 1.3475 \| 1.1608 \| \| No log \| 0.4068 \| 24 \| 1.4195 \| 0.0262 \| 1.4195 \| 1.1914 \| \| No log \| 0.4407 \| 26 \| 1.1388 \| 0.0363 \| 1.1388 \| 1.0671 \| \| No log \| 0.4746 \| 28 \| 0.9469 \| 0.0456 \| 0.9469 \| 0.9731 \| \| No log \| 0.5085 \| 30 \| 0.7915 \| 0.0932 \| 0.7915 \| 0.8897 \| \| No log \| 0.5424 \| 32 \| 0.7764 \| 0.0797 \| 0.7764 \| 0.8812 \| \| No log \| 0.5763 \| 34 \| 0.7658 \| 0.1505 \| 0.7658 \| 0.8751 \| \| No log \| 0.6102 \| 36 \| 0.7574 \| 0.1281 \| 0.7574 \| 0.8703 \| \| No log \| 0.6441 \| 38 \| 0.7671 \| 0.2713 \| 0.7671 \| 0.8759 \| \| No log \| 0.6780 \| 40 \| 0.7597 \| 0.2883 \| 0.7597 \| 0.8716 \| \| No log \| 0.7119 \| 42 \| 0.7352 \| 0.3097 \| 0.7352 \| 0.8575 \| \| No log \| 0.7458 \| 44 \| 0.7179 \| 0.2723 \| 0.7179 \| 0.8473 \| \| No log \| 0.7797 \| 46 \| 0.8210 \| 0.2453 \| 0.8210 \| 0.9061 \| \| No log \| 0.8136 \| 48 \| 0.8228 \| 0.2687 \| 0.8228 \| 0.9071 \| \| No log \| 0.8475 \| 50 \| 0.7828 \| 0.2687 \| 0.7828 \| 0.8848 \| \| No log \| 0.8814 \| 52 \| 0.7498 \| 0.3427 \| 0.7498 \| 0.8659 \| \| No log \| 0.9153 \| 54 \| 0.7103 \| 0.3392 \| 0.7103 \| 0.8428 \| \| No log \| 0.9492 \| 56 \| 0.7264 \| 0.3468 \| 0.7264 \| 0.8523 \| \| No log \| 0.9831 \| 58 \| 0.7145 \| 0.4157 \| 0.7145 \| 0.8453 \| \| No log \| 1.0169 \| 60 \| 0.6964 \| 0.3647 \| 0.6964 \| 0.8345 \| \| No log \| 1.0508 \| 62 \| 0.6822 \| 0.3708 \| 0.6822 \| 0.8259 \| \| No log \| 1.0847 \| 64 \| 0.6574 \| 0.4099 \| 0.6574 \| 0.8108 \| \| No log \| 1.1186 \| 66 \| 0.6465 \| 0.4529 \| 0.6465 \| 0.8040 \| \| No log \| 1.1525 \| 68 \| 0.6532 \| 0.4700 \| 0.6532 \| 0.8082 \| \| No log \| 1.1864 \| 70 \| 0.6603 \| 0.4298 \| 0.6603 \| 0.8126 \| \| No log \| 1.2203 \| 72 \| 0.7369 \| 0.4176 \| 0.7369 \| 0.8584 \| \| No log \| 1.2542 \| 74 \| 0.6974 \| 0.4337 \| 0.6974 \| 0.8351 \| \| No log \| 1.2881 \| 76 \| 0.6845 \| 0.4749 \| 0.6845 \| 0.8274 \| \| No log \| 1.3220 \| 78 \| 0.6924 \| 0.4749 \| 0.6924 \| 0.8321 \| \| No log \| 1.3559 \| 80 \| 0.6937 \| 0.4781 \| 0.6937 \| 0.8329 \| \| No log \| 1.3898 \| 82 \| 0.7165 \| 0.4589 \| 0.7165 \| 0.8465 \| \| No log \| 1.4237 \| 84 \| 0.7688 \| 0.4315 \| 0.7688 \| 0.8768 \| \| No log \| 1.4576 \| 86 \| 0.9003 \| 0.3983 \| 0.9003 \| 0.9488 \| \| No log \| 1.4915 \| 88 \| 0.8929 \| 0.4161 \| 0.8929 \| 0.9449 \| \| No log \| 1.5254 \| 90 \| 0.7462 \| 0.4357 \| 0.7462 \| 0.8638 \| \| No log \| 1.5593 \| 92 \| 0.7201 \| 0.4550 \| 0.7201 \| 0.8486 \| \| No log \| 1.5932 \| 94 \| 0.7240 \| 0.4899 \| 0.7240 \| 0.8509 \| \| No log \| 1.6271 \| 96 \| 0.8073 \| 0.4730 \| 0.8073 \| 0.8985 \| \| No log \| 1.6610 \| 98 \| 0.8365 \| 0.4393 \| 0.8365 \| 0.9146 \| \| No log \| 1.6949 \| 100 \| 0.8551 \| 0.4769 \| 0.8551 \| 0.9247 \| \| No log \| 1.7288 \| 102 \| 0.7937 \| 0.4260 \| 0.7937 \| 0.8909 \| \| No log \| 1.7627 \| 104 \| 0.8459 \| 0.4352 \| 0.8459 \| 0.9197 \| \| No log \| 1.7966 \| 106 \| 0.7920 \| 0.4484 \| 0.7920 \| 0.8899 \| \| No log \| 1.8305 \| 108 \| 0.8247 \| 0.4463 \| 0.8247 \| 0.9081 \| \| No log \| 1.8644 \| 110 \| 1.1376 \| 0.3577 \| 1.1376 \| 1.0666 \| \| No log \| 1.8983 \| 112 \| 1.0599 \| 0.3574 \| 1.0599 \| 1.0295 \| \| No log \| 1.9322 \| 114 \| 0.7327 \| 0.4837 \| 0.7327 \| 0.8560 \| \| No log \| 1.9661 \| 116 \| 0.8170 \| 0.3834 \| 0.8170 \| 0.9039 \| \| No log \| 2.0 \| 118 \| 0.8166 \| 0.3846 \| 0.8166 \| 0.9037 \| \| No log \| 2.0339 \| 120 \| 0.7262 \| 0.5192 \| 0.7262 \| 0.8522 \| \| No log \| 2.0678 \| 122 \| 0.8005 \| 0.4277 \| 0.8005 \| 0.8947 \| \| No log \| 2.1017 \| 124 \| 0.9027 \| 0.2983 \| 0.9027 \| 0.9501 \| \| No log \| 2.1356 \| 126 \| 0.7849 \| 0.4046 \| 0.7849 \| 0.8859 \| \| No log \| 2.1695 \| 128 \| 0.7066 \| 0.3798 \| 0.7066 \| 0.8406 \| \| No log \| 2.2034 \| 130 \| 0.6268 \| 0.4572 \| 0.6268 \| 0.7917 \| \| No log \| 2.2373 \| 132 \| 0.6235 \| 0.4659 \| 0.6235 \| 0.7896 \| \| No log \| 2.2712 \| 134 \| 0.6538 \| 0.4459 \| 0.6538 \| 0.8086 \| \| No log \| 2.3051 \| 136 \| 0.8376 \| 0.4329 \| 0.8376 \| 0.9152 \| \| No log \| 2.3390 \| 138 \| 0.7967 \| 0.4363 \| 0.7967 \| 0.8926 \| \| No log \| 2.3729 \| 140 \| 0.6376 \| 0.4274 \| 0.6376 \| 0.7985 \| \| No log \| 2.4068 \| 142 \| 0.6585 \| 0.4542 \| 0.6585 \| 0.8115 \| \| No log \| 2.4407 \| 144 \| 0.6457 \| 0.4321 \| 0.6457 \| 0.8035 \| \| No log \| 2.4746 \| 146 \| 0.6707 \| 0.4785 \| 0.6707 \| 0.8189 \| \| No log \| 2.5085 \| 148 \| 0.6931 \| 0.4606 \| 0.6931 \| 0.8325 \| \| No log \| 2.5424 \| 150 \| 0.6635 \| 0.4477 \| 0.6635 \| 0.8145 \| \| No log \| 2.5763 \| 152 \| 0.6945 \| 0.4744 \| 0.6945 \| 0.8334 \| \| No log \| 2.6102 \| 154 \| 0.6745 \| 0.4655 \| 0.6745 \| 0.8213 \| \| No log \| 2.6441 \| 156 \| 0.6559 \| 0.4746 \| 0.6559 \| 0.8099 \| \| No log \| 2.6780 \| 158 \| 0.6424 \| 0.4958 \| 0.6424 \| 0.8015 \| \| No log \| 2.7119 \| 160 \| 0.6542 \| 0.5039 \| 0.6542 \| 0.8088 \| \| No log \| 2.7458 \| 162 \| 0.6594 \| 0.5213 \| 0.6594 \| 0.8120 \| \| No log \| 2.7797 \| 164 \| 0.7149 \| 0.5015 \| 0.7149 \| 0.8455 \| \| No log \| 2.8136 \| 166 \| 0.7718 \| 0.5442 \| 0.7718 \| 0.8785 \| \| No log \| 2.8475 \| 168 \| 0.7848 \| 0.5622 \| 0.7848 \| 0.8859 \| \| No log \| 2.8814 \| 170 \| 0.7685 \| 0.5126 \| 0.7685 \| 0.8766 \| \| No log \| 2.9153 \| 172 \| 0.8633 \| 0.4963 \| 0.8633 \| 0.9291 \| \| No log \| 2.9492 \| 174 \| 0.8201 \| 0.5117 \| 0.8201 \| 0.9056 \| \| No log \| 2.9831 \| 176 \| 0.7117 \| 0.5364 \| 0.7117 \| 0.8436 \| \| No log \| 3.0169 \| 178 \| 0.8802 \| 0.4675 \| 0.8802 \| 0.9382 \| \| No log \| 3.0508 \| 180 \| 0.7990 \| 0.4734 \| 0.7990 \| 0.8939 \| \| No log \| 3.0847 \| 182 \| 0.6686 \| 0.4847 \| 0.6686 \| 0.8176 \| \| No log \| 3.1186 \| 184 \| 0.6372 \| 0.4211 \| 0.6372 \| 0.7983 \| \| No log \| 3.1525 \| 186 \| 0.6420 \| 0.3830 \| 0.6420 \| 0.8013 \| \| No log \| 3.1864 \| 188 \| 0.7457 \| 0.4332 \| 0.7457 \| 0.8636 \| \| No log \| 3.2203 \| 190 \| 0.7242 \| 0.4210 \| 0.7242 \| 0.8510 \| \| No log \| 3.2542 \| 192 \| 0.6703 \| 0.4150 \| 0.6703 \| 0.8187 \| \| No log \| 3.2881 \| 194 \| 0.6770 \| 0.3859 \| 0.6770 \| 0.8228 \| \| No log \| 3.3220 \| 196 \| 0.6892 \| 0.4199 \| 0.6892 \| 0.8302 \| \| No log \| 3.3559 \| 198 \| 0.7007 \| 0.4433 \| 0.7007 \| 0.8371 \| \| No log \| 3.3898 \| 200 \| 0.7016 \| 0.4348 \| 0.7016 \| 0.8376 \| \| No log \| 3.4237 \| 202 \| 0.7239 \| 0.4275 \| 0.7239 \| 0.8508 \| \| No log \| 3.4576 \| 204 \| 0.7045 \| 0.4275 \| 0.7045 \| 0.8394 \| \| No log \| 3.4915 \| 206 \| 0.6639 \| 0.4249 \| 0.6639 \| 0.8148 \| \| No log \| 3.5254 \| 208 \| 0.6430 \| 0.3490 \| 0.6430 \| 0.8019 \| \| No log \| 3.5593 \| 210 \| 0.6838 \| 0.3809 \| 0.6838 \| 0.8269 \| \| No log \| 3.5932 \| 212 \| 0.6554 \| 0.3574 \| 0.6554 \| 0.8096 \| \| No log \| 3.6271 \| 214 \| 0.6941 \| 0.3643 \| 0.6941 \| 0.8331 \| \| No log \| 3.6610 \| 216 \| 0.9193 \| 0.3782 \| 0.9193 \| 0.9588 \| \| No log \| 3.6949 \| 218 \| 0.8658 \| 0.3735 \| 0.8658 \| 0.9305 \| \| No log \| 3.7288 \| 220 \| 0.6616 \| 0.3662 \| 0.6616 \| 0.8134 \| \| No log \| 3.7627 \| 222 \| 0.6164 \| 0.3456 \| 0.6164 \| 0.7851 \| \| No log \| 3.7966 \| 224 \| 0.6183 \| 0.4331 \| 0.6183 \| 0.7863 \| \| No log \| 3.8305 \| 226 \| 0.6271 \| 0.3885 \| 0.6271 \| 0.7919 \| \| No log \| 3.8644 \| 228 \| 0.6795 \| 0.3969 \| 0.6795 \| 0.8243 \| \| No log \| 3.8983 \| 230 \| 0.7252 \| 0.4442 \| 0.7252 \| 0.8516 \| \| No log \| 3.9322 \| 232 \| 0.7638 \| 0.4587 \| 0.7638 \| 0.8739 \| \| No log \| 3.9661 \| 234 \| 0.6737 \| 0.4424 \| 0.6737 \| 0.8208 \| \| No log \| 4.0 \| 236 \| 0.6828 \| 0.4186 \| 0.6828 \| 0.8263 \| \| No log \| 4.0339 \| 238 \| 0.6647 \| 0.4051 \| 0.6647 \| 0.8153 \| \| No log \| 4.0678 \| 240 \| 0.6187 \| 0.3669 \| 0.6187 \| 0.7866 \| \| No log \| 4.1017 \| 242 \| 0.6409 \| 0.4165 \| 0.6409 \| 0.8006 \| \| No log \| 4.1356 \| 244 \| 0.7363 \| 0.4767 \| 0.7363 \| 0.8581 \| \| No log \| 4.1695 \| 246 \| 1.0628 \| 0.3801 \| 1.0628 \| 1.0309 \| \| No log \| 4.2034 \| 248 \| 1.1978 \| 0.3578 \| 1.1978 \| 1.0944 \| \| No log \| 4.2373 \| 250 \| 0.9836 \| 0.4115 \| 0.9836 \| 0.9918 \| \| No log \| 4.2712 \| 252 \| 0.7441 \| 0.4461 \| 0.7441 \| 0.8626 \| \| No log \| 4.3051 \| 254 \| 0.6874 \| 0.4652 \| 0.6874 \| 0.8291 \| \| No log \| 4.3390 \| 256 \| 0.6894 \| 0.4741 \| 0.6894 \| 0.8303 \| \| No log \| 4.3729 \| 258 \| 0.7296 \| 0.4072 \| 0.7296 \| 0.8542 \| \| No log \| 4.4068 \| 260 \| 0.7426 \| 0.4467 \| 0.7426 \| 0.8618 \| \| No log \| 4.4407 \| 262 \| 0.8213 \| 0.4579 \| 0.8213 \| 0.9062 \| \| No log \| 4.4746 \| 264 \| 0.7700 \| 0.4579 \| 0.7700 \| 0.8775 \| \| No log \| 4.5085 \| 266 \| 0.7815 \| 0.4523 \| 0.7815 \| 0.8840 \| \| No log \| 4.5424 \| 268 \| 0.6997 \| 0.4531 \| 0.6997 \| 0.8365 \| \| No log \| 4.5763 \| 270 \| 0.6442 \| 0.4227 \| 0.6442 \| 0.8026 \| \| No log \| 4.6102 \| 272 \| 0.5964 \| 0.4278 \| 0.5964 \| 0.7723 \| \| No log \| 4.6441 \| 274 \| 0.6215 \| 0.4015 \| 0.6215 \| 0.7884 \| \| No log \| 4.6780 \| 276 \| 0.6080 \| 0.3765 \| 0.6080 \| 0.7798 \| \| No log \| 4.7119 \| 278 \| 0.5863 \| 0.3998 \| 0.5863 \| 0.7657 \| \| No log \| 4.7458 \| 280 \| 0.5943 \| 0.4679 \| 0.5943 \| 0.7709 \| \| No log \| 4.7797 \| 282 \| 0.6017 \| 0.4383 \| 0.6017 \| 0.7757 \| \| No log \| 4.8136 \| 284 \| 0.6141 \| 0.4176 \| 0.6141 \| 0.7837 \| \| No log \| 4.8475 \| 286 \| 0.6245 \| 0.4499 \| 0.6245 \| 0.7902 \| \| No log \| 4.8814 \| 288 \| 0.6176 \| 0.4807 \| 0.6176 \| 0.7859 \| \| No log \| 4.9153 \| 290 \| 0.6299 \| 0.4458 \| 0.6299 \| 0.7936 \| \| No log \| 4.9492 \| 292 \| 0.7054 \| 0.4557 \| 0.7054 \| 0.8399 \| \| No log \| 4.9831 \| 294 \| 0.7136 \| 0.4664 \| 0.7136 \| 0.8448 \| \| No log \| 5.0169 \| 296 \| 0.6757 \| 0.4381 \| 0.6757 \| 0.8220 \| \| No log \| 5.0508 \| 298 \| 0.6509 \| 0.4846 \| 0.6509 \| 0.8068 \| \| No log \| 5.0847 \| 300 \| 0.6313 \| 0.4673 \| 0.6313 \| 0.7945 \| \| No log \| 5.1186 \| 302 \| 0.6295 \| 0.4693 \| 0.6295 \| 0.7934 \| \| No log \| 5.1525 \| 304 \| 0.6293 \| 0.4578 \| 0.6293 \| 0.7933 \| \| No log \| 5.1864 \| 306 \| 0.6420 \| 0.4416 \| 0.6420 \| 0.8012 \| \| No log \| 5.2203 \| 308 \| 0.7168 \| 0.4810 \| 0.7168 \| 0.8466 \| \| No log \| 5.2542 \| 310 \| 0.7265 \| 0.4579 \| 0.7265 \| 0.8524 \| \| No log \| 5.2881 \| 312 \| 0.6593 \| 0.4516 \| 0.6593 \| 0.8120 \| \| No log \| 5.3220 \| 314 \| 0.6216 \| 0.4036 \| 0.6216 \| 0.7884 \| \| No log \| 5.3559 \| 316 \| 0.6288 \| 0.4029 \| 0.6288 \| 0.7930 \| \| No log \| 5.3898 \| 318 \| 0.6443 \| 0.4682 \| 0.6443 \| 0.8027 \| \| No log \| 5.4237 \| 320 \| 0.6501 \| 0.4578 \| 0.6501 \| 0.8063 \| \| No log \| 5.4576 \| 322 \| 0.6482 \| 0.4740 \| 0.6482 \| 0.8051 \| \| No log \| 5.4915 \| 324 \| 0.6157 \| 0.4134 \| 0.6157 \| 0.7847 \| \| No log \| 5.5254 \| 326 \| 0.6020 \| 0.4150 \| 0.6020 \| 0.7759 \| \| No log \| 5.5593 \| 328 \| 0.5992 \| 0.3806 \| 0.5992 \| 0.7741 \| \| No log \| 5.5932 \| 330 \| 0.5935 \| 0.4808 \| 0.5935 \| 0.7704 \| \| No log \| 5.6271 \| 332 \| 0.5974 \| 0.4925 \| 0.5974 \| 0.7729 \| \| No log \| 5.6610 \| 334 \| 0.6415 \| 0.5098 \| 0.6415 \| 0.8010 \| \| No log \| 5.6949 \| 336 \| 0.6185 \| 0.4956 \| 0.6185 \| 0.7865 \| \| No log \| 5.7288 \| 338 \| 0.5939 \| 0.4842 \| 0.5939 \| 0.7706 \| \| No log \| 5.7627 \| 340 \| 0.5816 \| 0.4157 \| 0.5816 \| 0.7626 \| \| No log \| 5.7966 \| 342 \| 0.6050 \| 0.3829 \| 0.6050 \| 0.7778 \| \| No log \| 5.8305 \| 344 \| 0.5903 \| 0.4521 \| 0.5903 \| 0.7683 \| \| No log \| 5.8644 \| 346 \| 0.6224 \| 0.5026 \| 0.6224 \| 0.7889 \| \| No log \| 5.8983 \| 348 \| 0.6256 \| 0.5039 \| 0.6256 \| 0.7910 \| \| No log \| 5.9322 \| 350 \| 0.6195 \| 0.4572 \| 0.6195 \| 0.7871 \| \| No log \| 5.9661 \| 352 \| 0.6777 \| 0.4649 \| 0.6777 \| 0.8232 \| \| No log \| 6.0 \| 354 \| 0.8010 \| 0.4884 \| 0.8010 \| 0.8950 \| \| No log \| 6.0339 \| 356 \| 0.8134 \| 0.4784 \| 0.8134 \| 0.9019 \| \| No log \| 6.0678 \| 358 \| 0.7095 \| 0.4522 \| 0.7095 \| 0.8423 \| \| No log \| 6.1017 \| 360 \| 0.6367 \| 0.4440 \| 0.6367 \| 0.7979 \| \| No log \| 6.1356 \| 362 \| 0.6759 \| 0.5220 \| 0.6759 \| 0.8221 \| \| No log \| 6.1695 \| 364 \| 0.6883 \| 0.5230 \| 0.6883 \| 0.8297 \| \| No log \| 6.2034 \| 366 \| 0.6466 \| 0.4729 \| 0.6466 \| 0.8041 \| \| No log \| 6.2373 \| 368 \| 0.6219 \| 0.4422 \| 0.6219 \| 0.7886 \| \| No log \| 6.2712 \| 370 \| 0.6174 \| 0.4460 \| 0.6174 \| 0.7858 \| \| No log \| 6.3051 \| 372 \| 0.6144 \| 0.4398 \| 0.6144 \| 0.7838 \| \| No log \| 6.3390 \| 374 \| 0.6120 \| 0.4521 \| 0.6120 \| 0.7823 \| \| No log \| 6.3729 \| 376 \| 0.6093 \| 0.4570 \| 0.6093 \| 0.7806 \| \| No log \| 6.4068 \| 378 \| 0.6226 \| 0.4540 \| 0.6226 \| 0.7890 \| \| No log \| 6.4407 \| 380 \| 0.6624 \| 0.4716 \| 0.6624 \| 0.8139 \| \| No log \| 6.4746 \| 382 \| 0.6675 \| 0.4270 \| 0.6675 \| 0.8170 \| \| No log \| 6.5085 \| 384 \| 0.6181 \| 0.3848 \| 0.6181 \| 0.7862 \| \| No log \| 6.5424 \| 386 \| 0.5847 \| 0.3426 \| 0.5847 \| 0.7647 \| \| No log \| 6.5763 \| 388 \| 0.5801 \| 0.4841 \| 0.5801 \| 0.7616 \| \| No log \| 6.6102 \| 390 \| 0.5851 \| 0.4906 \| 0.5851 \| 0.7649 \| \| No log \| 6.6441 \| 392 \| 0.6153 \| 0.4866 \| 0.6153 \| 0.7844 \| \| No log \| 6.6780 \| 394 \| 0.6139 \| 0.5018 \| 0.6139 \| 0.7835 \| \| No log \| 6.7119 \| 396 \| 0.6068 \| 0.5290 \| 0.6068 \| 0.7790 \| \| No log \| 6.7458 \| 398 \| 0.6110 \| 0.4687 \| 0.6110 \| 0.7817 \| \| No log \| 6.7797 \| 400 \| 0.6028 \| 0.4284 \| 0.6028 \| 0.7764 \| \| No log \| 6.8136 \| 402 \| 0.5944 \| 0.4042 \| 0.5944 \| 0.7710 \| \| No log \| 6.8475 \| 404 \| 0.5969 \| 0.4319 \| 0.5969 \| 0.7726 \| \| No log \| 6.8814 \| 406 \| 0.6161 \| 0.4480 \| 0.6161 \| 0.7849 \| \| No log \| 6.9153 \| 408 \| 0.6922 \| 0.4825 \| 0.6922 \| 0.8320 \| \| No log \| 6.9492 \| 410 \| 0.6787 \| 0.4948 \| 0.6787 \| 0.8239 \| \| No log \| 6.9831 \| 412 \| 0.6222 \| 0.4482 \| 0.6222 \| 0.7888 \| \| No log \| 7.0169 \| 414 \| 0.6365 \| 0.4706 \| 0.6365 \| 0.7978 \| \| No log \| 7.0508 \| 416 \| 0.7240 \| 0.4915 \| 0.7240 \| 0.8509 \| \| No log \| 7.0847 \| 418 \| 0.7256 \| 0.5048 \| 0.7256 \| 0.8518 \| \| No log \| 7.1186 \| 420 \| 0.6445 \| 0.4816 \| 0.6445 \| 0.8028 \| \| No log \| 7.1525 \| 422 \| 0.6172 \| 0.4788 \| 0.6172 \| 0.7856 \| \| No log \| 7.1864 \| 424 \| 0.6290 \| 0.4921 \| 0.6290 \| 0.7931 \| \| No log \| 7.2203 \| 426 \| 0.6963 \| 0.5303 \| 0.6963 \| 0.8345 \| \| No log \| 7.2542 \| 428 \| 0.8245 \| 0.3773 \| 0.8245 \| 0.9080 \| \| No log \| 7.2881 \| 430 \| 0.8196 \| 0.3773 \| 0.8196 \| 0.9053 \| \| No log \| 7.3220 \| 432 \| 0.7598 \| 0.4345 \| 0.7598 \| 0.8717 \| \| No log \| 7.3559 \| 434 \| 0.6501 \| 0.5567 \| 0.6501 \| 0.8063 \| \| No log \| 7.3898 \| 436 \| 0.5816 \| 0.5299 \| 0.5816 \| 0.7626 \| \| No log \| 7.4237 \| 438 \| 0.5829 \| 0.5409 \| 0.5829 \| 0.7635 \| \| No log \| 7.4576 \| 440 \| 0.6012 \| 0.5314 \| 0.6012 \| 0.7754 \| \| No log \| 7.4915 \| 442 \| 0.6652 \| 0.5143 \| 0.6652 \| 0.8156 \| \| No log \| 7.5254 \| 444 \| 0.6704 \| 0.5143 \| 0.6704 \| 0.8188 \| \| No log \| 7.5593 \| 446 \| 0.6131 \| 0.5514 \| 0.6131 \| 0.7830 \| \| No log \| 7.5932 \| 448 \| 0.5898 \| 0.4963 \| 0.5898 \| 0.7680 \| \| No log \| 7.6271 \| 450 \| 0.6421 \| 0.4221 \| 0.6421 \| 0.8013 \| \| No log \| 7.6610 \| 452 \| 0.6541 \| 0.4131 \| 0.6541 \| 0.8087 \| \| No log \| 7.6949 \| 454 \| 0.6077 \| 0.4619 \| 0.6077 \| 0.7796 \| \| No log \| 7.7288 \| 456 \| 0.5903 \| 0.4783 \| 0.5903 \| 0.7683 \| \| No log \| 7.7627 \| 458 \| 0.7189 \| 0.4959 \| 0.7189 \| 0.8479 \| \| No log \| 7.7966 \| 460 \| 0.8165 \| 0.4250 \| 0.8165 \| 0.9036 \| \| No log \| 7.8305 \| 462 \| 0.7612 \| 0.4290 \| 0.7612 \| 0.8725 \| \| No log \| 7.8644 \| 464 \| 0.6345 \| 0.5071 \| 0.6345 \| 0.7965 \| \| No log \| 7.8983 \| 466 \| 0.5708 \| 0.5136 \| 0.5708 \| 0.7555 \| \| No log \| 7.9322 \| 468 \| 0.5614 \| 0.4876 \| 0.5614 \| 0.7493 \| \| No log \| 7.9661 \| 470 \| 0.5710 \| 0.5131 \| 0.5710 \| 0.7556 \| \| No log \| 8.0 \| 472 \| 0.6259 \| 0.5158 \| 0.6259 \| 0.7911 \| \| No log \| 8.0339 \| 474 \| 0.7018 \| 0.5192 \| 0.7018 \| 0.8377 \| \| No log \| 8.0678 \| 476 \| 0.6813 \| 0.5302 \| 0.6813 \| 0.8254 \| \| No log \| 8.1017 \| 478 \| 0.6114 \| 0.4985 \| 0.6114 \| 0.7819 \| \| No log \| 8.1356 \| 480 \| 0.5791 \| 0.5447 \| 0.5791 \| 0.7610 \| \| No log \| 8.1695 \| 482 \| 0.5797 \| 0.5357 \| 0.5797 \| 0.7614 \| \| No log \| 8.2034 \| 484 \| 0.6036 \| 0.4828 \| 0.6036 \| 0.7769 \| \| No log \| 8.2373 \| 486 \| 0.6574 \| 0.5173 \| 0.6574 \| 0.8108 \| \| No log \| 8.2712 \| 488 \| 0.6894 \| 0.5158 \| 0.6894 \| 0.8303 \| \| No log \| 8.3051 \| 490 \| 0.7148 \| 0.5177 \| 0.7148 \| 0.8454 \| \| No log \| 8.3390 \| 492 \| 0.6801 \| 0.5158 \| 0.6801 \| 0.8247 \| \| No log \| 8.3729 \| 494 \| 0.6156 \| 0.4833 \| 0.6156 \| 0.7846 \| \| No log \| 8.4068 \| 496 \| 0.5827 \| 0.4948 \| 0.5827 \| 0.7633 \| \| No log \| 8.4407 \| 498 \| 0.5896 \| 0.3781 \| 0.5896 \| 0.7679 \| \| 0.3742 \| 8.4746 \| 500 \| 0.5902 \| 0.3905 \| 0.5902 \| 0.7683 \| \| 0.3742 \| 8.5085 \| 502 \| 0.5993 \| 0.4837 \| 0.5993 \| 0.7742 \| \| 0.3742 \| 8.5424 \| 504 \| 0.6062 \| 0.4998 \| 0.6062 \| 0.7786 \| \| 0.3742 \| 8.5763 \| 506 \| 0.6092 \| 0.5123 \| 0.6092 \| 0.7805 \| \| 0.3742 \| 8.6102 \| 508 \| 0.6054 \| 0.4489 \| 0.6054 \| 0.7781 \| \| 0.3742 \| 8.6441 \| 510 \| 0.6295 \| 0.4877 \| 0.6295 \| 0.7934 \| \| 0.3742 \| 8.6780 \| 512 \| 0.6631 \| 0.4187 \| 0.6631 \| 0.8143 \| \| 0.3742 \| 8.7119 \| 514 \| 0.6665 \| 0.4214 \| 0.6665 \| 0.8164 \| \| 0.3742 \| 8.7458 \| 516 \| 0.6354 \| 0.4539 \| 0.6354 \| 0.7971 \| \| 0.3742 \| 8.7797 \| 518 \| 0.6137 \| 0.4711 \| 0.6137 \| 0.7834 \| \| 0.3742 \| 8.8136 \| 520 \| 0.5911 \| 0.5396 \| 0.5911 \| 0.7688 \| \| 0.3742 \| 8.8475 \| 522 \| 0.6211 \| 0.5035 \| 0.6211 \| 0.7881 \| \| 0.3742 \| 8.8814 \| 524 \| 0.7404 \| 0.4629 \| 0.7404 \| 0.8605 \| \| 0.3742 \| 8.9153 \| 526 \| 0.7928 \| 0.4108 \| 0.7928 \| 0.8904 \| \| 0.3742 \| 8.9492 \| 528 \| 0.7446 \| 0.4538 \| 0.7446 \| 0.8629 \| \| 0.3742 \| 8.9831 \| 530 \| 0.6457 \| 0.5147 \| 0.6457 \| 0.8036 \| \| 0.3742 \| 9.0169 \| 532 \| 0.5852 \| 0.5248 \| 0.5852 \| 0.7650 \| \| 0.3742 \| 9.0508 \| 534 \| 0.5808 \| 0.4884 \| 0.5808 \| 0.7621 \| \| 0.3742 \| 9.0847 \| 536 \| 0.5865 \| 0.5155 \| 0.5865 \| 0.7658 \| \| 0.3742 \| 9.1186 \| 538 \| 0.6318 \| 0.5237 \| 0.6318 \| 0.7949 \| \| 0.3742 \| 9.1525 \| 540 \| 0.6793 \| 0.4758 \| 0.6793 \| 0.8242 \| \| 0.3742 \| 9.1864 \| 542 \| 0.7238 \| 0.4568 \| 0.7238 \| 0.8508 \| \| 0.3742 \| 9.2203 \| 544 \| 0.6955 \| 0.4444 \| 0.6955 \| 0.8340 \| \| 0.3742 \| 9.2542 \| 546 \| 0.6120 \| 0.4930 \| 0.6120 \| 0.7823 \| \| 0.3742 \| 9.2881 \| 548 \| 0.5883 \| 0.5198 \| 0.5883 \| 0.7670 \| \| 0.3742 \| 9.3220 \| 550 \| 0.5969 \| 0.5334 \| 0.5969 \| 0.7726 \| \| 0.3742 \| 9.3559 \| 552 \| 0.6477 \| 0.5118 \| 0.6477 \| 0.8048 \| \| 0.3742 \| 9.3898 \| 554 \| 0.6999 \| 0.4560 \| 0.6999 \| 0.8366 \| \| 0.3742 \| 9.4237 \| 556 \| 0.6612 \| 0.5329 \| 0.6612 \| 0.8131 \| \| 0.3742 \| 9.4576 \| 558 \| 0.5937 \| 0.5487 \| 0.5937 \| 0.7705 \| \| 0.3742 \| 9.4915 \| 560 \| 0.5724 \| 0.4827 \| 0.5724 \| 0.7566 \| \| 0.3742 \| 9.5254 \| 562 \| 0.5785 \| 0.4910 \| 0.5785 \| 0.7606 \| \| 0.3742 \| 9.5593 \| 564 \| 0.5883 \| 0.4611 \| 0.5883 \| 0.7670 \| \| 0.3742 \| 9.5932 \| 566 \| 0.5856 \| 0.4747 \| 0.5856 \| 0.7652 \| \| 0.3742 \| 9.6271 \| 568 \| 0.6184 \| 0.5233 \| 0.6184 \| 0.7864 \| \| 0.3742 \| 9.6610 \| 570 \| 0.6614 \| 0.5189 \| 0.6614 \| 0.8133 \| \| 0.3742 \| 9.6949 \| 572 \| 0.6453 \| 0.4999 \| 0.6453 \| 0.8033 \| \| 0.3742 \| 9.7288 \| 574 \| 0.6140 \| 0.5434 \| 0.6140 \| 0.7836 \| \| 0.3742 \| 9.7627 \| 576 \| 0.6231 \| 0.4926 \| 0.6231 \| 0.7893 \| \| 0.3742 \| 9.7966 \| 578 \| 0.6571 \| 0.4916 \| 0.6571 \| 0.8106 \| \| 0.3742 \| 9.8305 \| 580 \| 0.6343 \| 0.4722 \| 0.6343 \| 0.7964 \| \| 0.3742 \| 9.8644 \| 582 \| 0.6065 \| 0.4923 \| 0.6065 \| 0.7788 \| \| 0.3742 \| 9.8983 \| 584 \| 0.6180 \| 0.4742 \| 0.6180 \| 0.7861 \| \| 0.3742 \| 9.9322 \| 586 \| 0.6712 \| 0.4695 \| 0.6712 \| 0.8193 \| \| 0.3742 \| 9.9661 \| 588 \| 0.7290 \| 0.4787 \| 0.7290 \| 0.8538 \| \| 0.3742 \| 10.0 \| 590 \| 0.7491 \| 0.4650 \| 0.7491 \| 0.8655 \| \| 0.3742 \| 10.0339 \| 592 \| 0.7263 \| 0.4659 \| 0.7263 \| 0.8522 \| \| 0.3742 \| 10.0678 \| 594 \| 0.6702 \| 0.5251 \| 0.6702 \| 0.8187 \| \| 0.3742 \| 10.1017 \| 596 \| 0.6595 \| 0.5351 \| 0.6595 \| 0.8121 \| \| 0.3742 \| 10.1356 \| 598 \| 0.6585 \| 0.4904 \| 0.6585 \| 0.8115 \| \| 0.3742 \| 10.1695 \| 600 \| 0.6765 \| 0.4783 \| 0.6765 \| 0.8225 \| \| 0.3742 \| 10.2034 \| 602 \| 0.6808 \| 0.4394 \| 0.6808 \| 0.8251 \| \| 0.3742 \| 10.2373 \| 604 \| 0.6815 \| 0.4096 \| 0.6815 \| 0.8255 \| \| 0.3742 \| 10.2712 \| 606 \| 0.6668 \| 0.4283 \| 0.6668 \| 0.8166 \| \| 0.3742 \| 10.3051 \| 608 \| 0.6261 \| 0.4877 \| 0.6261 \| 0.7912 \| \| 0.3742 \| 10.3390 \| 610 \| 0.6318 \| 0.4413 \| 0.6318 \| 0.7948 \| \| 0.3742 \| 10.3729 \| 612 \| 0.6476 \| 0.4626 \| 0.6476 \| 0.8048 \| \| 0.3742 \| 10.4068 \| 614 \| 0.6388 \| 0.4407 \| 0.6388 \| 0.7992 \| \| 0.3742 \| 10.4407 \| 616 \| 0.6333 \| 0.4539 \| 0.6333 \| 0.7958 \| \| 0.3742 \| 10.4746 \| 618 \| 0.6294 \| 0.4416 \| 0.6294 \| 0.7934 \| \| 0.3742 \| 10.5085 \| 620 \| 0.6251 \| 0.4438 \| 0.6251 \| 0.7906 \| \| 0.3742 \| 10.5424 \| 622 \| 0.6119 \| 0.3935 \| 0.6119 \| 0.7822 \| \| 0.3742 \| 10.5763 \| 624 \| 0.6131 \| 0.4082 \| 0.6131 \| 0.7830 \| \| 0.3742 \| 10.6102 \| 626 \| 0.6237 \| 0.3958 \| 0.6237 \| 0.7898 \| \| 0.3742 \| 10.6441 \| 628 \| 0.6435 \| 0.4252 \| 0.6435 \| 0.8022 \| \| 0.3742 \| 10.6780 \| 630 \| 0.6649 \| 0.4222 \| 0.6649 \| 0.8154 \| \| 0.3742 \| 10.7119 \| 632 \| 0.6542 \| 0.4579 \| 0.6542 \| 0.8088 \| \| 0.3742 \| 10.7458 \| 634 \| 0.6224 \| 0.4349 \| 0.6224 \| 0.7889 \| \| 0.3742 \| 10.7797 \| 636 \| 0.6125 \| 0.4549 \| 0.6125 \| 0.7826 \| \| 0.3742 \| 10.8136 \| 638 \| 0.6063 \| 0.4004 \| 0.6063 \| 0.7786 \| \| 0.3742 \| 10.8475 \| 640 \| 0.6026 \| 0.4412 \| 0.6026 \| 0.7763 \| \| 0.3742 \| 10.8814 \| 642 \| 0.5971 \| 0.4454 \| 0.5971 \| 0.7727 \| \| 0.3742 \| 10.9153 \| 644 \| 0.5979 \| 0.4541 \| 0.5979 \| 0.7733 \| \| 0.3742 \| 10.9492 \| 646 \| 0.5891 \| 0.4398 \| 0.5891 \| 0.7675 \| \| 0.3742 \| 10.9831 \| 648 \| 0.5801 \| 0.4844 \| 0.5801 \| 0.7617 \| \| 0.3742 \| 11.0169 \| 650 \| 0.5838 \| 0.5122 \| 0.5838 \| 0.7641 \| \| 0.3742 \| 11.0508 \| 652 \| 0.6248 \| 0.5615 \| 0.6248 \| 0.7904 \| \| 0.3742 \| 11.0847 \| 654 \| 0.7645 \| 0.4710 \| 0.7645 \| 0.8744 \| \| 0.3742 \| 11.1186 \| 656 \| 0.9152 \| 0.3868 \| 0.9152 \| 0.9567 \| \| 0.3742 \| 11.1525 \| 658 \| 0.9535 \| 0.3497 \| 0.9535 \| 0.9765 \| \| 0.3742 \| 11.1864 \| 660 \| 0.8803 \| 0.3921 \| 0.8803 \| 0.9382 \| \| 0.3742 \| 11.2203 \| 662 \| 0.7806 \| 0.4437 \| 0.7806 \| 0.8835 \| \| 0.3742 \| 11.2542 \| 664 \| 0.6500 \| 0.5398 \| 0.6500 \| 0.8062 \| \| 0.3742 \| 11.2881 \| 666 \| 0.5876 \| 0.5625 \| 0.5876 \| 0.7665 \| \| 0.3742 \| 11.3220 \| 668 \| 0.5857 \| 0.5625 \| 0.5857 \| 0.7653 \| \| 0.3742 \| 11.3559 \| 670 \| 0.6102 \| 0.5683 \| 0.6102 \| 0.7812 \| \| 0.3742 \| 11.3898 \| 672 \| 0.6804 \| 0.5423 \| 0.6804 \| 0.8249 \| \| 0.3742 \| 11.4237 \| 674 \| 0.7725 \| 0.4654 \| 0.7725 \| 0.8789 \| \| 0.3742 \| 11.4576 \| 676 \| 0.8085 \| 0.4392 \| 0.8085 \| 0.8991 \| \| 0.3742 \| 11.4915 \| 678 \| 0.7631 \| 0.4239 \| 0.7631 \| 0.8736 \| \| 0.3742 \| 11.5254 \| 680 \| 0.6930 \| 0.4136 \| 0.6930 \| 0.8325 \| \| 0.3742 \| 11.5593 \| 682 \| 0.6677 \| 0.4598 \| 0.6677 \| 0.8171 \| \| 0.3742 \| 11.5932 \| 684 \| 0.6682 \| 0.4685 \| 0.6682 \| 0.8174 \| \| 0.3742 \| 11.6271 \| 686 \| 0.7061 \| 0.4925 \| 0.7061 \| 0.8403 \| \| 0.3742 \| 11.6610 \| 688 \| 0.7086 \| 0.4793 \| 0.7086 \| 0.8418 \| \| 0.3742 \| 11.6949 \| 690 \| 0.6720 \| 0.5200 \| 0.6720 \| 0.8197 \| \| 0.3742 \| 11.7288 \| 692 \| 0.6325 \| 0.5019 \| 0.6325 \| 0.7953 \| \| 0.3742 \| 11.7627 \| 694 \| 0.6226 \| 0.4998 \| 0.6226 \| 0.7890 \| \| 0.3742 \| 11.7966 \| 696 \| 0.6334 \| 0.5347 \| 0.6334 \| 0.7959 \| \| 0.3742 \| 11.8305 \| 698 \| 0.6461 \| 0.5006 \| 0.6461 \| 0.8038 \| \| 0.3742 \| 11.8644 \| 700 \| 0.6405 \| 0.5336 \| 0.6405 \| 0.8003 \| \| 0.3742 \| 11.8983 \| 702 \| 0.6450 \| 0.4781 \| 0.6450 \| 0.8031 \| \| 0.3742 \| 11.9322 \| 704 \| 0.6486 \| 0.4519 \| 0.6486 \| 0.8054 \| \| 0.3742 \| 11.9661 \| 706 \| 0.6481 \| 0.4878 \| 0.6481 \| 0.8051 \| \| 0.3742 \| 12.0 \| 708 \| 0.6390 \| 0.5206 \| 0.6390 \| 0.7994 \| \| 0.3742 \| 12.0339 \| 710 \| 0.6954 \| 0.5230 \| 0.6954 \| 0.8339 \| \| 0.3742 \| 12.0678 \| 712 \| 0.7365 \| 0.4913 \| 0.7365 \| 0.8582 \| \| 0.3742 \| 12.1017 \| 714 \| 0.7072 \| 0.4726 \| 0.7072 \| 0.8409 \| \| 0.3742 \| 12.1356 \| 716 \| 0.6519 \| 0.4459 \| 0.6519 \| 0.8074 \| \| 0.3742 \| 12.1695 \| 718 \| 0.6112 \| 0.4714 \| 0.6112 \| 0.7818 \| \| 0.3742 \| 12.2034 \| 720 \| 0.6113 \| 0.4781 \| 0.6113 \| 0.7819 \| \| 0.3742 \| 12.2373 \| 722 \| 0.6359 \| 0.4375 \| 0.6359 \| 0.7974 \| \| 0.3742 \| 12.2712 \| 724 \| 0.6797 \| 0.4674 \| 0.6797 \| 0.8244 \| \| 0.3742 \| 12.3051 \| 726 \| 0.7603 \| 0.3992 \| 0.7603 \| 0.8719 \| \| 0.3742 \| 12.3390 \| 728 \| 0.7811 \| 0.4862 \| 0.7811 \| 0.8838 \| \| 0.3742 \| 12.3729 \| 730 \| 0.7230 \| 0.4618 \| 0.7230 \| 0.8503 \| \| 0.3742 \| 12.4068 \| 732 \| 0.6736 \| 0.4575 \| 0.6736 \| 0.8207 \| \| 0.3742 \| 12.4407 \| 734 \| 0.6627 \| 0.5083 \| 0.6627 \| 0.8140 \| \| 0.3742 \| 12.4746 \| 736 \| 0.6226 \| 0.5014 \| 0.6226 \| 0.7891 \| \| 0.3742 \| 12.5085 \| 738 \| 0.6193 \| 0.5362 \| 0.6193 \| 0.7870 \| \| 0.3742 \| 12.5424 \| 740 \| 0.6673 \| 0.5083 \| 0.6673 \| 0.8169 \| \| 0.3742 \| 12.5763 \| 742 \| 0.7748 \| 0.4346 \| 0.7748 \| 0.8802 \| \| 0.3742 \| 12.6102 \| 744 \| 0.8359 \| 0.4813 \| 0.8359 \| 0.9143 \| \| 0.3742 \| 12.6441 \| 746 \| 0.7885 \| 0.4116 \| 0.7885 \| 0.8880 \| \| 0.3742 \| 12.6780 \| 748 \| 0.7043 \| 0.4074 \| 0.7043 \| 0.8392 \| \| 0.3742 \| 12.7119 \| 750 \| 0.6857 \| 0.3907 \| 0.6857 \| 0.8280 \| \| 0.3742 \| 12.7458 \| 752 \| 0.6625 \| 0.3733 \| 0.6625 \| 0.8140 \| \| 0.3742 \| 12.7797 \| 754 \| 0.6589 \| 0.3733 \| 0.6589 \| 0.8118 \| \| 0.3742 \| 12.8136 \| 756 \| 0.6701 \| 0.4074 \| 0.6701 \| 0.8186 \| \| 0.3742 \| 12.8475 \| 758 \| 0.6657 \| 0.3907 \| 0.6657 \| 0.8159 \| \| 0.3742 \| 12.8814 \| 760 \| 0.6350 \| 0.4112 \| 0.6350 \| 0.7969 \| \| 0.3742 \| 12.9153 \| 762 \| 0.6341 \| 0.4101 \| 0.6341 \| 0.7963 \| \| 0.3742 \| 12.9492 \| 764 \| 0.6836 \| 0.4522 \| 0.6836 \| 0.8268 \| \| 0.3742 \| 12.9831 \| 766 \| 0.6856 \| 0.4935 \| 0.6856 \| 0.8280 \| \| 0.3742 \| 13.0169 \| 768 \| 0.6397 \| 0.4842 \| 0.6397 \| 0.7998 \| \| 0.3742 \| 13.0508 \| 770 \| 0.5950 \| 0.4874 \| 0.5950 \| 0.7713 \| \| 0.3742 \| 13.0847 \| 772 \| 0.5875 \| 0.5503 \| 0.5875 \| 0.7665 \| \| 0.3742 \| 13.1186 \| 774 \| 0.5872 \| 0.5484 \| 0.5872 \| 0.7663 \| \| 0.3742 \| 13.1525 \| 776 \| 0.5959 \| 0.5323 \| 0.5959 \| 0.7719 \| \| 0.3742 \| 13.1864 \| 778 \| 0.6663 \| 0.5007 \| 0.6663 \| 0.8163 \| \| 0.3742 \| 13.2203 \| 780 \| 0.7393 \| 0.4969 \| 0.7393 \| 0.8598 \| \| 0.3742 \| 13.2542 \| 782 \| 0.7082 \| 0.4969 \| 0.7082 \| 0.8415 \| \| 0.3742 \| 13.2881 \| 784 \| 0.6598 \| 0.4589 \| 0.6598 \| 0.8123 \| \| 0.3742 \| 13.3220 \| 786 \| 0.6112 \| 0.4261 \| 0.6112 \| 0.7818 \| \| 0.3742 \| 13.3559 \| 788 \| 0.5781 \| 0.4533 \| 0.5781 \| 0.7603 \| \| 0.3742 \| 13.3898 \| 790 \| 0.5725 \| 0.4668 \| 0.5725 \| 0.7566 \| \| 0.3742 \| 13.4237 \| 792 \| 0.5823 \| 0.4712 \| 0.5823 \| 0.7631 \| \| 0.3742 \| 13.4576 \| 794 \| 0.5983 \| 0.5122 \| 0.5983 \| 0.7735 \| \| 0.3742 \| 13.4915 \| 796 \| 0.5988 \| 0.5122 \| 0.5988 \| 0.7738 \| \| 0.3742 \| 13.5254 \| 798 \| 0.6210 \| 0.4783 \| 0.6210 \| 0.7881 \| \| 0.3742 \| 13.5593 \| 800 \| 0.6163 \| 0.4794 \| 0.6163 \| 0.7850 \| \| 0.3742 \| 13.5932 \| 802 \| 0.5988 \| 0.4531 \| 0.5988 \| 0.7738 \| \| 0.3742 \| 13.6271 \| 804 \| 0.5855 \| 0.4531 \| 0.5855 \| 0.7652 \| \| 0.3742 \| 13.6610 \| 806 \| 0.5785 \| 0.4842 \| 0.5785 \| 0.7606 \| \| 0.3742 \| 13.6949 \| 808 \| 0.5831 \| 0.4442 \| 0.5831 \| 0.7636 \| \| 0.3742 \| 13.7288 \| 810 \| 0.5992 \| 0.4839 \| 0.5992 \| 0.7741 \| \| 0.3742 \| 13.7627 \| 812 \| 0.6030 \| 0.4839 \| 0.6030 \| 0.7766 \| \| 0.3742 \| 13.7966 \| 814 \| 0.5894 \| 0.4490 \| 0.5894 \| 0.7677 \| \| 0.3742 \| 13.8305 \| 816 \| 0.5914 \| 0.4490 \| 0.5914 \| 0.7690 \| \| 0.3742 \| 13.8644 \| 818 \| 0.5950 \| 0.4490 \| 0.5950 \| 0.7714 \| \| 0.3742 \| 13.8983 \| 820 \| 0.6106 \| 0.4746 \| 0.6106 \| 0.7814 \| \| 0.3742 \| 13.9322 \| 822 \| 0.6293 \| 0.4754 \| 0.6293 \| 0.7933 \| \| 0.3742 \| 13.9661 \| 824 \| 0.6451 \| 0.4611 \| 0.6451 \| 0.8032 \| \| 0.3742 \| 14.0 \| 826 \| 0.6494 \| 0.4578 \| 0.6494 \| 0.8059 \| \| 0.3742 \| 14.0339 \| 828 \| 0.6249 \| 0.4187 \| 0.6249 \| 0.7905 \| \| 0.3742 \| 14.0678 \| 830 \| 0.6007 \| 0.4815 \| 0.6007 \| 0.7751 \| \| 0.3742 \| 14.1017 \| 832 \| 0.6217 \| 0.4193 \| 0.6217 \| 0.7885 \| \| 0.3742 \| 14.1356 \| 834 \| 0.6424 \| 0.4374 \| 0.6424 \| 0.8015 \| \| 0.3742 \| 14.1695 \| 836 \| 0.6151 \| 0.4528 \| 0.6151 \| 0.7843 \| \| 0.3742 \| 14.2034 \| 838 \| 0.5923 \| 0.5188 \| 0.5923 \| 0.7696 \| \| 0.3742 \| 14.2373 \| 840 \| 0.6380 \| 0.4634 \| 0.6380 \| 0.7988 \| \| 0.3742 \| 14.2712 \| 842 \| 0.6802 \| 0.4987 \| 0.6802 \| 0.8247 \| \| 0.3742 \| 14.3051 \| 844 \| 0.6805 \| 0.5084 \| 0.6805 \| 0.8249 \| \| 0.3742 \| 14.3390 \| 846 \| 0.6955 \| 0.4987 \| 0.6955 \| 0.8340 \| \| 0.3742 \| 14.3729 \| 848 \| 0.6434 \| 0.4605 \| 0.6434 \| 0.8021 \| \| 0.3742 \| 14.4068 \| 850 \| 0.5940 \| 0.4357 \| 0.5940 \| 0.7707 \| \| 0.3742 \| 14.4407 \| 852 \| 0.5861 \| 0.4783 \| 0.5861 \| 0.7655 \| \| 0.3742 \| 14.4746 \| 854 \| 0.5856 \| 0.4424 \| 0.5856 \| 0.7652 \| \| 0.3742 \| 14.5085 \| 856 \| 0.6035 \| 0.4516 \| 0.6035 \| 0.7769 \| \| 0.3742 \| 14.5424 \| 858 \| 0.6451 \| 0.4469 \| 0.6451 \| 0.8032 \| \| 0.3742 \| 14.5763 \| 860 \| 0.6481 \| 0.4469 \| 0.6481 \| 0.8051 \| \| 0.3742 \| 14.6102 \| 862 \| 0.6175 \| 0.4695 \| 0.6175 \| 0.7858 \| \| 0.3742 \| 14.6441 \| 864 \| 0.5913 \| 0.4909 \| 0.5913 \| 0.7690 \| \| 0.3742 \| 14.6780 \| 866 \| 0.5823 \| 0.4644 \| 0.5823 \| 0.7631 \| \| 0.3742 \| 14.7119 \| 868 \| 0.5905 \| 0.5006 \| 0.5905 \| 0.7684 \| \| 0.3742 \| 14.7458 \| 870 \| 0.5986 \| 0.4712 \| 0.5986 \| 0.7737 \| \| 0.3742 \| 14.7797 \| 872 \| 0.5790 \| 0.5181 \| 0.5790 \| 0.7609 \| \| 0.3742 \| 14.8136 \| 874 \| 0.5746 \| 0.5282 \| 0.5746 \| 0.7581 \| \| 0.3742 \| 14.8475 \| 876 \| 0.5925 \| 0.5321 \| 0.5925 \| 0.7697 \| \| 0.3742 \| 14.8814 \| 878 \| 0.6330 \| 0.4714 \| 0.6330 \| 0.7956 \| \| 0.3742 \| 14.9153 \| 880 \| 0.6533 \| 0.4895 \| 0.6533 \| 0.8083 \| \| 0.3742 \| 14.9492 \| 882 \| 0.6274 \| 0.4850 \| 0.6274 \| 0.7921 \| \| 0.3742 \| 14.9831 \| 884 \| 0.6142 \| 0.5117 \| 0.6142 \| 0.7837 \| \| 0.3742 \| 15.0169 \| 886 \| 0.6155 \| 0.5190 \| 0.6155 \| 0.7845 \| \| 0.3742 \| 15.0508 \| 888 \| 0.6017 \| 0.5472 \| 0.6017 \| 0.7757 \| \| 0.3742 \| 15.0847 \| 890 \| 0.6124 \| 0.5397 \| 0.6124 \| 0.7825 \| \| 0.3742 \| 15.1186 \| 892 \| 0.6208 \| 0.5307 \| 0.6208 \| 0.7879 \| \| 0.3742 \| 15.1525 \| 894 \| 0.6130 \| 0.5307 \| 0.6130 \| 0.7829 \| \| 0.3742 \| 15.1864 \| 896 \| 0.6133 \| 0.5307 \| 0.6133 \| 0.7832 \| \| 0.3742 \| 15.2203 \| 898 \| 0.6103 \| 0.5253 \| 0.6103 \| 0.7812 \| \| 0.3742 \| 15.2542 \| 900 \| 0.6169 \| 0.5261 \| 0.6169 \| 0.7854 \| \| 0.3742 \| 15.2881 \| 902 \| 0.6092 \| 0.5261 \| 0.6092 \| 0.7805 \| \| 0.3742 \| 15.3220 \| 904 \| 0.6049 \| 0.5144 \| 0.6049 \| 0.7777 \| \| 0.3742 \| 15.3559 \| 906 \| 0.6190 \| 0.5077 \| 0.6190 \| 0.7867 \| \| 0.3742 \| 15.3898 \| 908 \| 0.6285 \| 0.5243 \| 0.6285 \| 0.7928 \| \| 0.3742 \| 15.4237 \| 910 \| 0.6431 \| 0.5620 \| 0.6431 \| 0.8019 \| \| 0.3742 \| 15.4576 \| 912 \| 0.6844 \| 0.5057 \| 0.6844 \| 0.8273 \| \| 0.3742 \| 15.4915 \| 914 \| 0.7018 \| 0.5043 \| 0.7018 \| 0.8377 \| \| 0.3742 \| 15.5254 \| 916 \| 0.6662 \| 0.5068 \| 0.6662 \| 0.8162 \| \| 0.3742 \| 15.5593 \| 918 \| 0.6597 \| 0.5068 \| 0.6597 \| 0.8122 \| \| 0.3742 \| 15.5932 \| 920 \| 0.6547 \| 0.4884 \| 0.6547 \| 0.8091 \| \| 0.3742 \| 15.6271 \| 922 \| 0.6340 \| 0.4930 \| 0.6340 \| 0.7962 \| \| 0.3742 \| 15.6610 \| 924 \| 0.6111 \| 0.4724 \| 0.6111 \| 0.7817 \| \| 0.3742 \| 15.6949 \| 926 \| 0.5918 \| 0.4578 \| 0.5918 \| 0.7693 \| \| 0.3742 \| 15.7288 \| 928 \| 0.5899 \| 0.4816 \| 0.5899 \| 0.7680 \| \| 0.3742 \| 15.7627 \| 930 \| 0.5993 \| 0.5096 \| 0.5993 \| 0.7741 \| \| 0.3742 \| 15.7966 \| 932 \| 0.6248 \| 0.5113 \| 0.6248 \| 0.7904 \| \| 0.3742 \| 15.8305 \| 934 \| 0.6389 \| 0.5128 \| 0.6389 \| 0.7993 \| \| 0.3742 \| 15.8644 \| 936 \| 0.6344 \| 0.4857 \| 0.6344 \| 0.7965 \| \| 0.3742 \| 15.8983 \| 938 \| 0.6210 \| 0.5162 \| 0.6210 \| 0.7881 \| \| 0.3742 \| 15.9322 \| 940 \| 0.6144 \| 0.4728 \| 0.6144 \| 0.7838 \| \| 0.3742 \| 15.9661 \| 942 \| 0.5873 \| 0.3982 \| 0.5873 \| 0.7664 \| \| 0.3742 \| 16.0 \| 944 \| 0.5795 \| 0.3878 \| 0.5795 \| 0.7612 \| \| 0.3742 \| 16.0339 \| 946 \| 0.5782 \| 0.3916 \| 0.5782 \| 0.7604 \| \| 0.3742 \| 16.0678 \| 948 \| 0.5850 \| 0.4273 \| 0.5850 \| 0.7648 \| \| 0.3742 \| 16.1017 \| 950 \| 0.5998 \| 0.4724 \| 0.5998 \| 0.7745 \| \| 0.3742 \| 16.1356 \| 952 \| 0.6271 \| 0.4907 \| 0.6271 \| 0.7919 \| \| 0.3742 \| 16.1695 \| 954 \| 0.6676 \| 0.4799 \| 0.6676 \| 0.8171 \| \| 0.3742 \| 16.2034 \| 956 \| 0.6535 \| 0.4912 \| 0.6535 \| 0.8084 \| \| 0.3742 \| 16.2373 \| 958 \| 0.6461 \| 0.4924 \| 0.6461 \| 0.8038 \| \| 0.3742 \| 16.2712 \| 960 \| 0.6468 \| 0.5076 \| 0.6468 \| 0.8042 \| \| 0.3742 \| 16.3051 \| 962 \| 0.6233 \| 0.4960 \| 0.6233 \| 0.7895 \| \| 0.3742 \| 16.3390 \| 964 \| 0.6155 \| 0.4390 \| 0.6155 \| 0.7845 \| \| 0.3742 \| 16.3729 \| 966 \| 0.6053 \| 0.4183 \| 0.6053 \| 0.7780 \| \| 0.3742 \| 16.4068 \| 968 \| 0.5959 \| 0.4289 \| 0.5959 \| 0.7720 \| \| 0.3742 \| 16.4407 \| 970 \| 0.5892 \| 0.3992 \| 0.5892 \| 0.7676 \| \| 0.3742 \| 16.4746 \| 972 \| 0.5878 \| 0.3750 \| 0.5878 \| 0.7667 \| \| 0.3742 \| 16.5085 \| 974 \| 0.5987 \| 0.4088 \| 0.5987 \| 0.7737 \| \| 0.3742 \| 16.5424 \| 976 \| 0.6297 \| 0.4046 \| 0.6297 \| 0.7936 \| \| 0.3742 \| 16.5763 \| 978 \| 0.7015 \| 0.4426 \| 0.7015 \| 0.8376 \| \| 0.3742 \| 16.6102 \| 980 \| 0.7986 \| 0.4345 \| 0.7986 \| 0.8936 \| \| 0.3742 \| 16.6441 \| 982 \| 0.8505 \| 0.4530 \| 0.8505 \| 0.9223 \| \| 0.3742 \| 16.6780 \| 984 \| 0.8661 \| 0.4522 \| 0.8661 \| 0.9307 \| \| 0.3742 \| 16.7119 \| 986 \| 0.8286 \| 0.4633 \| 0.8286 \| 0.9103 \| \| 0.3742 \| 16.7458 \| 988 \| 0.7841 \| 0.4441 \| 0.7841 \| 0.8855 \| \| 0.3742 \| 16.7797 \| 990 \| 0.7511 \| 0.4337 \| 0.7511 \| 0.8666 \| \| 0.3742 \| 16.8136 \| 992 \| 0.6991 \| 0.4381 \| 0.6991 \| 0.8361 \| \| 0.3742 \| 16.8475 \| 994 \| 0.6421 \| 0.4324 \| 0.6421 \| 0.8013 \| \| 0.3742 \| 16.8814 \| 996 \| 0.6367 \| 0.4515 \| 0.6367 \| 0.7980 \| \| 0.3742 \| 16.9153 \| 998 \| 0.6562 \| 0.4381 \| 0.6562 \| 0.8101 \| \| 0.0688 \| 16.9492 \| 1000 \| 0.6999 \| 0.4568 \| 0.6999 \| 0.8366 \| \| 0.0688 \| 16.9831 \| 1002 \| 0.7397 \| 0.4731 \| 0.7397 \| 0.8600 \| \| 0.0688 \| 17.0169 \| 1004 \| 0.7376 \| 0.4731 \| 0.7376 \| 0.8589 \| \| 0.0688 \| 17.0508 \| 1006 \| 0.6975 \| 0.4690 \| 0.6975 \| 0.8352 \| \| 0.0688 \| 17.0847 \| 1008 \| 0.6399 \| 0.4837 \| 0.6399 \| 0.7999 \| \| 0.0688 \| 17.1186 \| 1010 \| 0.6059 \| 0.4539 \| 0.6059 \| 0.7784 \| \| 0.0688 \| 17.1525 \| 1012 \| 0.6169 \| 0.4515 \| 0.6169 \| 0.7855 \| \| 0.0688 \| 17.1864 \| 1014 \| 0.6328 \| 0.4548 \| 0.6328 \| 0.7955 \| \| 0.0688 \| 17.2203 \| 1016 \| 0.6471 \| 0.4668 \| 0.6471 \| 0.8044 \| \| 0.0688 \| 17.2542 \| 1018 \| 0.6186 \| 0.4455 \| 0.6186 \| 0.7865 \| \| 0.0688 \| 17.2881 \| 1020 \| 0.5951 \| 0.4805 \| 0.5951 \| 0.7714 \| \| 0.0688 \| 17.3220 \| 1022 \| 0.6025 \| 0.4704 \| 0.6025 \| 0.7762 \| \| 0.0688 \| 17.3559 \| 1024 \| 0.6019 \| 0.4794 \| 0.6019 \| 0.7758 \| \| 0.0688 \| 17.3898 \| 1026 \| 0.5891 \| 0.4857 \| 0.5891 \| 0.7676 \| \| 0.0688 \| 17.4237 \| 1028 \| 0.5924 \| 0.4857 \| 0.5924 \| 0.7697 \| \| 0.0688 \| 17.4576 \| 1030 \| 0.6075 \| 0.4921 \| 0.6075 \| 0.7794 \| \| 0.0688 \| 17.4915 \| 1032 \| 0.6063 \| 0.4857 \| 0.6063 \| 0.7786 \| \| 0.0688 \| 17.5254 \| 1034 \| 0.6025 \| 0.4950 \| 0.6025 \| 0.7762 \| \| 0.0688 \| 17.5593 \| 1036 \| 0.6076 \| 0.5289 \| 0.6076 \| 0.7795 \| \| 0.0688 \| 17.5932 \| 1038 \| 0.6015 \| 0.5006 \| 0.6015 \| 0.7755 \| \| 0.0688 \| 17.6271 \| 1040 \| 0.5847 \| 0.4514 \| 0.5847 \| 0.7647 \| \| 0.0688 \| 17.6610 \| 1042 \| 0.5782 \| 0.4614 \| 0.5782 \| 0.7604 \| \| 0.0688 \| 17.6949 \| 1044 \| 0.5890 \| 0.4603 \| 0.5890 \| 0.7675 \| \| 0.0688 \| 17.7288 \| 1046 \| 0.6114 \| 0.4637 \| 0.6114 \| 0.7820 \| \| 0.0688 \| 17.7627 \| 1048 \| 0.6075 \| 0.4637 \| 0.6075 \| 0.7794 \| \| 0.0688 \| 17.7966 \| 1050 \| 0.5894 \| 0.4521 \| 0.5894 \| 0.7677 \| \| 0.0688 \| 17.8305 \| 1052 \| 0.5982 \| 0.5384 \| 0.5982 \| 0.7734 \| \| 0.0688 \| 17.8644 \| 1054 \| 0.6251 \| 0.4824 \| 0.6251 \| 0.7907 \| \| 0.0688 \| 17.8983 \| 1056 \| 0.6211 \| 0.5060 \| 0.6211 \| 0.7881 \| \| 0.0688 \| 17.9322 \| 1058 \| 0.6035 \| 0.5103 \| 0.6035 \| 0.7769 \| \| 0.0688 \| 17.9661 \| 1060 \| 0.5846 \| 0.5630 \| 0.5846 \| 0.7646 \| \| 0.0688 \| 18.0 \| 1062 \| 0.5784 \| 0.5507 \| 0.5784 \| 0.7605 \| \| 0.0688 \| 18.0339 \| 1064 \| 0.5922 \| 0.4958 \| 0.5922 \| 0.7695 \| \| 0.0688 \| 18.0678 \| 1066 \| 0.5961 \| 0.4779 \| 0.5961 \| 0.7721 \| \| 0.0688 \| 18.1017 \| 1068 \| 0.5831 \| 0.5146 \| 0.5831 \| 0.7636 \| \| 0.0688 \| 18.1356 \| 1070 \| 0.5780 \| 0.5843 \| 0.5780 \| 0.7602 \| \| 0.0688 \| 18.1695 \| 1072 \| 0.5770 \| 0.5842 \| 0.5770 \| 0.7596 \| \| 0.0688 \| 18.2034 \| 1074 \| 0.5695 \| 0.5493 \| 0.5695 \| 0.7547 \| \| 0.0688 \| 18.2373 \| 1076 \| 0.5642 \| 0.5012 \| 0.5642 \| 0.7511 \| \| 0.0688 \| 18.2712 \| 1078 \| 0.5862 \| 0.4769 \| 0.5862 \| 0.7657 \| \| 0.0688 \| 18.3051 \| 1080 \| 0.6085 \| 0.4507 \| 0.6085 \| 0.7800 \| \| 0.0688 \| 18.3390 \| 1082 \| 0.6239 \| 0.4434 \| 0.6239 \| 0.7898 \| \| 0.0688 \| 18.3729 \| 1084 \| 0.6444 \| 0.4427 \| 0.6444 \| 0.8028 \| \| 0.0688 \| 18.4068 \| 1086 \| 0.6201 \| 0.4787 \| 0.6200 \| 0.7874 \| \| 0.0688 \| 18.4407 \| 1088 \| 0.5929 \| 0.4999 \| 0.5929 \| 0.7700 \| \| 0.0688 \| 18.4746 \| 1090 \| 0.5672 \| 0.5347 \| 0.5672 \| 0.7531 \| \| 0.0688 \| 18.5085 \| 1092 \| 0.5631 \| 0.5718 \| 0.5631 \| 0.7504 \| \| 0.0688 \| 18.5424 \| 1094 \| 0.5755 \| 0.5815 \| 0.5755 \| 0.7586 \| \| 0.0688 \| 18.5763 \| 1096 \| 0.5859 \| 0.5676 \| 0.5859 \| 0.7654 \| \| 0.0688 \| 18.6102 \| 1098 \| 0.6115 \| 0.5712 \| 0.6115 \| 0.7820 \| \| 0.0688 \| 18.6441 \| 1100 \| 0.6229 \| 0.5640 \| 0.6229 \| 0.7892 \| \| 0.0688 \| 18.6780 \| 1102 \| 0.6227 \| 0.5860 \| 0.6227 \| 0.7891 \| \| 0.0688 \| 18.7119 \| 1104 \| 0.6254 \| 0.624 \| 0.6254 \| 0.7908 \| \| 0.0688 \| 18.7458 \| 1106 \| 0.6341 \| 0.5816 \| 0.6341 \| 0.7963 \| \| 0.0688 \| 18.7797 \| 1108 \| 0.6333 \| 0.5816 \| 0.6333 \| 0.7958 \| \| 0.0688 \| 18.8136 \| 1110 \| 0.6140 \| 0.5953 \| 0.6140 \| 0.7836 \| \| 0.0688 \| 18.8475 \| 1112 \| 0.6343 \| 0.5281 \| 0.6343 \| 0.7964 \| \| 0.0688 \| 18.8814 \| 1114 \| 0.7013 \| 0.5125 \| 0.7013 \| 0.8374 \| \| 0.0688 \| 18.9153 \| 1116 \| 0.7885 \| 0.4590 \| 0.7885 \| 0.8880 \| \| 0.0688 \| 18.9492 \| 1118 \| 0.7920 \| 0.4267 \| 0.7920 \| 0.8899 \| \| 0.0688 \| 18.9831 \| 1120 \| 0.7500 \| 0.4846 \| 0.7500 \| 0.8660 \| \| 0.0688 \| 19.0169 \| 1122 \| 0.6853 \| 0.4687 \| 0.6853 \| 0.8278 \| \| 0.0688 \| 19.0508 \| 1124 \| 0.6170 \| 0.4815 \| 0.6170 \| 0.7855 \| \| 0.0688 \| 19.0847 \| 1126 \| 0.5854 \| 0.5642 \| 0.5854 \| 0.7651 \| \| 0.0688 \| 19.1186 \| 1128 \| 0.5962 \| 0.5682 \| 0.5962 \| 0.7722 \| \| 0.0688 \| 19.1525 \| 1130 \| 0.6283 \| 0.5178 \| 0.6283 \| 0.7927 \| \| 0.0688 \| 19.1864 \| 1132 \| 0.7183 \| 0.4982 \| 0.7183 \| 0.8475 \| \| 0.0688 \| 19.2203 \| 1134 \| 0.7741 \| 0.5055 \| 0.7741 \| 0.8798 \| \| 0.0688 \| 19.2542 \| 1136 \| 0.7745 \| 0.5055 \| 0.7745 \| 0.8801 \| \| 0.0688 \| 19.2881 \| 1138 \| 0.7280 \| 0.5296 \| 0.7280 \| 0.8532 \| \| 0.0688 \| 19.3220 \| 1140 \| 0.6471 \| 0.5198 \| 0.6471 \| 0.8044 \| \| 0.0688 \| 19.3559 \| 1142 \| 0.6004 \| 0.4655 \| 0.6004 \| 0.7748 \| \| 0.0688 \| 19.3898 \| 1144 \| 0.5858 \| 0.4641 \| 0.5858 \| 0.7654 \| \| 0.0688 \| 19.4237 \| 1146 \| 0.6048 \| 0.4508 \| 0.6048 \| 0.7777 \| \| 0.0688 \| 19.4576 \| 1148 \| 0.6611 \| 0.5034 \| 0.6611 \| 0.8131 \| \| 0.0688 \| 19.4915 \| 1150 \| 0.7651 \| 0.4846 \| 0.7651 \| 0.8747 \| \| 0.0688 \| 19.5254 \| 1152 \| 0.8086 \| 0.4871 \| 0.8086 \| 0.8992 \| \| 0.0688 \| 19.5593 \| 1154 \| 0.7747 \| 0.4835 \| 0.7747 \| 0.8802 \| \| 0.0688 \| 19.5932 \| 1156 \| 0.7153 \| 0.5034 \| 0.7153 \| 0.8458 \| \| 0.0688 \| 19.6271 \| 1158 \| 0.6538 \| 0.4515 \| 0.6538 \| 0.8086 \| \| 0.0688 \| 19.6610 \| 1160 \| 0.6188 \| 0.5033 \| 0.6188 \| 0.7866 \| \| 0.0688 \| 19.6949 \| 1162 \| 0.5943 \| 0.5434 \| 0.5943 \| 0.7709 \| \| 0.0688 \| 19.7288 \| 1164 \| 0.5820 \| 0.5768 \| 0.5820 \| 0.7629 \| \| 0.0688 \| 19.7627 \| 1166 \| 0.5688 \| 0.5165 \| 0.5688 \| 0.7542 \| \| 0.0688 \| 19.7966 \| 1168 \| 0.5513 \| 0.5440 \| 0.5513 \| 0.7425 \| \| 0.0688 \| 19.8305 \| 1170 \| 0.5548 \| 0.5284 \| 0.5548 \| 0.7449 \| \| 0.0688 \| 19.8644 \| 1172 \| 0.5588 \| 0.5148 \| 0.5588 \| 0.7475 \| \| 0.0688 \| 19.8983 \| 1174 \| 0.5786 \| 0.4564 \| 0.5786 \| 0.7607 \| \| 0.0688 \| 19.9322 \| 1176 \| 0.5941 \| 0.4434 \| 0.5941 \| 0.7708 \| \| 0.0688 \| 19.9661 \| 1178 \| 0.6011 \| 0.4434 \| 0.6011 \| 0.7753 \| \| 0.0688 \| 20.0 \| 1180 \| 0.5806 \| 0.4630 \| 0.5806 \| 0.7620 \| \| 0.0688 \| 20.0339 \| 1182 \| 0.5661 \| 0.4409 \| 0.5661 \| 0.7524 \| \| 0.0688 \| 20.0678 \| 1184 \| 0.5504 \| 0.4853 \| 0.5504 \| 0.7419 \| \| 0.0688 \| 20.1017 \| 1186 \| 0.5375 \| 0.5291 \| 0.5375 \| 0.7332 \| \| 0.0688 \| 20.1356 \| 1188 \| 0.5358 \| 0.5697 \| 0.5358 \| 0.7320 \| \| 0.0688 \| 20.1695 \| 1190 \| 0.5576 \| 0.4783 \| 0.5576 \| 0.7467 \| \| 0.0688 \| 20.2034 \| 1192 \| 0.5614 \| 0.4691 \| 0.5614 \| 0.7493 \| \| 0.0688 \| 20.2373 \| 1194 \| 0.5652 \| 0.5397 \| 0.5652 \| 0.7518 \| \| 0.0688 \| 20.2712 \| 1196 \| 0.5930 \| 0.4932 \| 0.5930 \| 0.7701 \| \| 0.0688 \| 20.3051 \| 1198 \| 0.6207 \| 0.5158 \| 0.6207 \| 0.7879 \| \| 0.0688 \| 20.3390 \| 1200 \| 0.6107 \| 0.4754 \| 0.6107 \| 0.7815 \| \| 0.0688 \| 20.3729 \| 1202 \| 0.5663 \| 0.5121 \| 0.5663 \| 0.7526 \| \| 0.0688 \| 20.4068 \| 1204 \| 0.5480 \| 0.4630 \| 0.5480 \| 0.7403 \| \| 0.0688 \| 20.4407 \| 1206 \| 0.5471 \| 0.4723 \| 0.5471 \| 0.7397 \| \| 0.0688 \| 20.4746 \| 1208 \| 0.5466 \| 0.4900 \| 0.5466 \| 0.7394 \| \| 0.0688 \| 20.5085 \| 1210 \| 0.5494 \| 0.5188 \| 0.5494 \| 0.7412 \| \| 0.0688 \| 20.5424 \| 1212 \| 0.5928 \| 0.4833 \| 0.5928 \| 0.7700 \| \| 0.0688 \| 20.5763 \| 1214 \| 0.7070 \| 0.4776 \| 0.7070 \| 0.8408 \| \| 0.0688 \| 20.6102 \| 1216 \| 0.8177 \| 0.4908 \| 0.8177 \| 0.9043 \| \| 0.0688 \| 20.6441 \| 1218 \| 0.8847 \| 0.4728 \| 0.8847 \| 0.9406 \| \| 0.0688 \| 20.6780 \| 1220 \| 0.8832 \| 0.4851 \| 0.8832 \| 0.9398 \| \| 0.0688 \| 20.7119 \| 1222 \| 0.8152 \| 0.4701 \| 0.8152 \| 0.9029 \| \| 0.0688 \| 20.7458 \| 1224 \| 0.7643 \| 0.4739 \| 0.7643 \| 0.8743 \| \| 0.0688 \| 20.7797 \| 1226 \| 0.7091 \| 0.4809 \| 0.7091 \| 0.8421 \| \| 0.0688 \| 20.8136 \| 1228 \| 0.6890 \| 0.5062 \| 0.6890 \| 0.8300 \| \| 0.0688 \| 20.8475 \| 1230 \| 0.6909 \| 0.5046 \| 0.6909 \| 0.8312 \| \| 0.0688 \| 20.8814 \| 1232 \| 0.6553 \| 0.5362 \| 0.6553 \| 0.8095 \| \| 0.0688 \| 20.9153 \| 1234 \| 0.6212 \| 0.5441 \| 0.6212 \| 0.7882 \| \| 0.0688 \| 20.9492 \| 1236 \| 0.5811 \| 0.5663 \| 0.5811 \| 0.7623 \| \| 0.0688 \| 20.9831 \| 1238 \| 0.5607 \| 0.5851 \| 0.5607 \| 0.7488 \| \| 0.0688 \| 21.0169 \| 1240 \| 0.5425 \| 0.5547 \| 0.5425 \| 0.7366 \| \| 0.0688 \| 21.0508 \| 1242 \| 0.5343 \| 0.5506 \| 0.5343 \| 0.7309 \| \| 0.0688 \| 21.0847 \| 1244 \| 0.5425 \| 0.5668 \| 0.5425 \| 0.7365 \| \| 0.0688 \| 21.1186 \| 1246 \| 0.5700 \| 0.5725 \| 0.5700 \| 0.7550 \| \| 0.0688 \| 21.1525 \| 1248 \| 0.5868 \| 0.5463 \| 0.5868 \| 0.7660 \| \| 0.0688 \| 21.1864 \| 1250 \| 0.6167 \| 0.5310 \| 0.6167 \| 0.7853 \| \| 0.0688 \| 21.2203 \| 1252 \| 0.6533 \| 0.5103 \| 0.6533 \| 0.8083 \| \| 0.0688 \| 21.2542 \| 1254 \| 0.6629 \| 0.5020 \| 0.6629 \| 0.8142 \| \| 0.0688 \| 21.2881 \| 1256 \| 0.6226 \| 0.5072 \| 0.6226 \| 0.7890 \| \| 0.0688 \| 21.3220 \| 1258 \| 0.5886 \| 0.4794 \| 0.5886 \| 0.7672 \| \| 0.0688 \| 21.3559 \| 1260 \| 0.5911 \| 0.4552 \| 0.5911 \| 0.7688 \| \| 0.0688 \| 21.3898 \| 1262 \| 0.6194 \| 0.5087 \| 0.6194 \| 0.7870 \| \| 0.0688 \| 21.4237 \| 1264 \| 0.6461 \| 0.4987 \| 0.6461 \| 0.8038 \| \| 0.0688 \| 21.4576 \| 1266 \| 0.6607 \| 0.4901 \| 0.6607 \| 0.8128 \| \| 0.0688 \| 21.4915 \| 1268 \| 0.6342 \| 0.5242 \| 0.6342 \| 0.7964 \| \| 0.0688 \| 21.5254 \| 1270 \| 0.5914 \| 0.4973 \| 0.5914 \| 0.7690 \| \| 0.0688 \| 21.5593 \| 1272 \| 0.5663 \| 0.5539 \| 0.5663 \| 0.7525 \| \| 0.0688 \| 21.5932 \| 1274 \| 0.5573 \| 0.5610 \| 0.5573 \| 0.7465 \| \| 0.0688 \| 21.6271 \| 1276 \| 0.5555 \| 0.5717 \| 0.5555 \| 0.7453 \| \| 0.0688 \| 21.6610 \| 1278 \| 0.5593 \| 0.5378 \| 0.5593 \| 0.7479 \| \| 0.0688 \| 21.6949 \| 1280 \| 0.5734 \| 0.4978 \| 0.5734 \| 0.7572 \| \| 0.0688 \| 21.7288 \| 1282 \| 0.5807 \| 0.4721 \| 0.5807 \| 0.7620 \| \| 0.0688 \| 21.7627 \| 1284 \| 0.5672 \| 0.4709 \| 0.5672 \| 0.7531 \| \| 0.0688 \| 21.7966 \| 1286 \| 0.5683 \| 0.4320 \| 0.5683 \| 0.7539 \| \| 0.0688 \| 21.8305 \| 1288 \| 0.5905 \| 0.4662 \| 0.5905 \| 0.7685 \| \| 0.0688 \| 21.8644 \| 1290 \| 0.6337 \| 0.4665 \| 0.6337 \| 0.7960 \| \| 0.0688 \| 21.8983 \| 1292 \| 0.6521 \| 0.4804 \| 0.6521 \| 0.8075 \| \| 0.0688 \| 21.9322 \| 1294 \| 0.6474 \| 0.4804 \| 0.6474 \| 0.8046 \| \| 0.0688 \| 21.9661 \| 1296 \| 0.6005 \| 0.4733 \| 0.6005 \| 0.7749 \| \| 0.0688 \| 22.0 \| 1298 \| 0.5691 \| 0.5216 \| 0.5691 \| 0.7544 \| \| 0.0688 \| 22.0339 \| 1300 \| 0.5630 \| 0.5403 \| 0.5630 \| 0.7503 \| \| 0.0688 \| 22.0678 \| 1302 \| 0.5609 \| 0.5100 \| 0.5609 \| 0.7490 \| \| 0.0688 \| 22.1017 \| 1304 \| 0.5585 \| 0.5293 \| 0.5585 \| 0.7473 \| \| 0.0688 \| 22.1356 \| 1306 \| 0.5707 \| 0.5064 \| 0.5707 \| 0.7554 \| \| 0.0688 \| 22.1695 \| 1308 \| 0.5908 \| 0.4787 \| 0.5908 \| 0.7686 \| \| 0.0688 \| 22.2034 \| 1310 \| 0.5947 \| 0.4539 \| 0.5947 \| 0.7712 \| \| 0.0688 \| 22.2373 \| 1312 \| 0.6004 \| 0.4684 \| 0.6004 \| 0.7748 \| \| 0.0688 \| 22.2712 \| 1314 \| 0.5847 \| 0.4705 \| 0.5847 \| 0.7646 \| \| 0.0688 \| 22.3051 \| 1316 \| 0.5579 \| 0.5486 \| 0.5579 \| 0.7470 \| \| 0.0688 \| 22.3390 \| 1318 \| 0.5393 \| 0.5650 \| 0.5393 \| 0.7344 \| \| 0.0688 \| 22.3729 \| 1320 \| 0.5435 \| 0.5733 \| 0.5435 \| 0.7373 \| \| 0.0688 \| 22.4068 \| 1322 \| 0.5754 \| 0.5351 \| 0.5754 \| 0.7586 \| \| 0.0688 \| 22.4407 \| 1324 \| 0.6354 \| 0.5072 \| 0.6354 \| 0.7971 \| \| 0.0688 \| 22.4746 \| 1326 \| 0.6615 \| 0.5405 \| 0.6615 \| 0.8133 \| \| 0.0688 \| 22.5085 \| 1328 \| 0.6477 \| 0.5132 \| 0.6477 \| 0.8048 \| \| 0.0688 \| 22.5424 \| 1330 \| 0.6418 \| 0.5087 \| 0.6418 \| 0.8011 \| \| 0.0688 \| 22.5763 \| 1332 \| 0.6095 \| 0.4804 \| 0.6095 \| 0.7807 \| \| 0.0688 \| 22.6102 \| 1334 \| 0.5686 \| 0.5027 \| 0.5686 \| 0.7540 \| \| 0.0688 \| 22.6441 \| 1336 \| 0.5534 \| 0.5537 \| 0.5534 \| 0.7439 \| \| 0.0688 \| 22.6780 \| 1338 \| 0.5521 \| 0.5605 \| 0.5521 \| 0.7430 \| \| 0.0688 \| 22.7119 \| 1340 \| 0.5485 \| 0.5288 \| 0.5485 \| 0.7406 \| \| 0.0688 \| 22.7458 \| 1342 \| 0.5557 \| 0.5943 \| 0.5557 \| 0.7454 \| \| 0.0688 \| 22.7797 \| 1344 \| 0.5639 \| 0.5943 \| 0.5639 \| 0.7509 \| \| 0.0688 \| 22.8136 \| 1346 \| 0.5736 \| 0.5879 \| 0.5736 \| 0.7574 \| \| 0.0688 \| 22.8475 \| 1348 \| 0.5728 \| 0.5881 \| 0.5728 \| 0.7568 \| \| 0.0688 \| 22.8814 \| 1350 \| 0.5684 \| 0.5602 \| 0.5684 \| 0.7539 \| \| 0.0688 \| 22.9153 \| 1352 \| 0.5604 \| 0.5692 \| 0.5604 \| 0.7486 \| \| 0.0688 \| 22.9492 \| 1354 \| 0.5632 \| 0.5428 \| 0.5632 \| 0.7504 \| \| 0.0688 \| 22.9831 \| 1356 \| 0.5759 \| 0.5333 \| 0.5759 \| 0.7589 \| \| 0.0688 \| 23.0169 \| 1358 \| 0.5763 \| 0.5121 \| 0.5763 \| 0.7592 \| \| 0.0688 \| 23.0508 \| 1360 \| 0.5853 \| 0.5048 \| 0.5853 \| 0.7650 \| \| 0.0688 \| 23.0847 \| 1362 \| 0.5941 \| 0.5048 \| 0.5941 \| 0.7708 \| \| 0.0688 \| 23.1186 \| 1364 \| 0.6011 \| 0.5048 \| 0.6011 \| 0.7753 \| \| 0.0688 \| 23.1525 \| 1366 \| 0.5912 \| 0.4788 \| 0.5912 \| 0.7689 \| \| 0.0688 \| 23.1864 \| 1368 \| 0.5868 \| 0.5056 \| 0.5868 \| 0.7660 \| \| 0.0688 \| 23.2203 \| 1370 \| 0.5868 \| 0.5006 \| 0.5868 \| 0.7660 \| \| 0.0688 \| 23.2542 \| 1372 \| 0.5740 \| 0.5130 \| 0.5740 \| 0.7576 \| \| 0.0688 \| 23.2881 \| 1374 \| 0.5735 \| 0.5570 \| 0.5735 \| 0.7573 \| \| 0.0688 \| 23.3220 \| 1376 \| 0.5803 \| 0.5866 \| 0.5803 \| 0.7618 \| \| 0.0688 \| 23.3559 \| 1378 \| 0.5817 \| 0.5751 \| 0.5817 \| 0.7627 \| \| 0.0688 \| 23.3898 \| 1380 \| 0.5733 \| 0.6093 \| 0.5733 \| 0.7572 \| \| 0.0688 \| 23.4237 \| 1382 \| 0.5714 \| 0.5628 \| 0.5714 \| 0.7559 \| \| 0.0688 \| 23.4576 \| 1384 \| 0.5765 \| 0.5693 \| 0.5765 \| 0.7593 \| \| 0.0688 \| 23.4915 \| 1386 \| 0.5940 \| 0.5312 \| 0.5940 \| 0.7707 \| \| 0.0688 \| 23.5254 \| 1388 \| 0.5898 \| 0.5391 \| 0.5898 \| 0.7680 \| \| 0.0688 \| 23.5593 \| 1390 \| 0.5604 \| 0.5536 \| 0.5604 \| 0.7486 \| \| 0.0688 \| 23.5932 \| 1392 \| 0.5415 \| 0.5122 \| 0.5415 \| 0.7359 \| \| 0.0688 \| 23.6271 \| 1394 \| 0.5371 \| 0.5524 \| 0.5371 \| 0.7329 \| \| 0.0688 \| 23.6610 \| 1396 \| 0.5521 \| 0.5409 \| 0.5521 \| 0.7430 \| \| 0.0688 \| 23.6949 \| 1398 \| 0.5866 \| 0.4890 \| 0.5866 \| 0.7659 \| \| 0.0688 \| 23.7288 \| 1400 \| 0.5892 \| 0.4928 \| 0.5892 \| 0.7676 \| \| 0.0688 \| 23.7627 \| 1402 \| 0.5736 \| 0.5161 \| 0.5736 \| 0.7574 \| \| 0.0688 \| 23.7966 \| 1404 \| 0.5752 \| 0.5025 \| 0.5752 \| 0.7584 \| \| 0.0688 \| 23.8305 \| 1406 \| 0.5832 \| 0.4822 \| 0.5832 \| 0.7637 \| \| 0.0688 \| 23.8644 \| 1408 \| 0.5855 \| 0.4984 \| 0.5855 \| 0.7652 \| \| 0.0688 \| 23.8983 \| 1410 \| 0.5871 \| 0.5427 \| 0.5871 \| 0.7662 \| \| 0.0688 \| 23.9322 \| 1412 \| 0.5939 \| 0.5655 \| 0.5939 \| 0.7706 \| \| 0.0688 \| 23.9661 \| 1414 \| 0.6054 \| 0.5867 \| 0.6054 \| 0.7781 \| \| 0.0688 \| 24.0 \| 1416 \| 0.6241 \| 0.5416 \| 0.6241 \| 0.7900 \| \| 0.0688 \| 24.0339 \| 1418 \| 0.6045 \| 0.5512 \| 0.6045 \| 0.7775 \| \| 0.0688 \| 24.0678 \| 1420 \| 0.5856 \| 0.5666 \| 0.5856 \| 0.7652 \| \| 0.0688 \| 24.1017 \| 1422 \| 0.5793 \| 0.5323 \| 0.5793 \| 0.7611 \| \| 0.0688 \| 24.1356 \| 1424 \| 0.5948 \| 0.4985 \| 0.5948 \| 0.7712 \| \| 0.0688 \| 24.1695 \| 1426 \| 0.6258 \| 0.4787 \| 0.6258 \| 0.7911 \| \| 0.0688 \| 24.2034 \| 1428 \| 0.6753 \| 0.4585 \| 0.6753 \| 0.8217 \| \| 0.0688 \| 24.2373 \| 1430 \| 0.7012 \| 0.4585 \| 0.7012 \| 0.8374 \| \| 0.0688 \| 24.2712 \| 1432 \| 0.7137 \| 0.4337 \| 0.7137 \| 0.8448 \| \| 0.0688 \| 24.3051 \| 1434 \| 0.7110 \| 0.4337 \| 0.7110 \| 0.8432 \| \| 0.0688 \| 24.3390 \| 1436 \| 0.7173 \| 0.4337 \| 0.7173 \| 0.8470 \| \| 0.0688 \| 24.3729 \| 1438 \| 0.7320 \| 0.4780 \| 0.7320 \| 0.8556 \| \| 0.0688 \| 24.4068 \| 1440 \| 0.7503 \| 0.4620 \| 0.7503 \| 0.8662 \| \| 0.0688 \| 24.4407 \| 1442 \| 0.7398 \| 0.4824 \| 0.7398 \| 0.8601 \| \| 0.0688 \| 24.4746 \| 1444 \| 0.7525 \| 0.4813 \| 0.7525 \| 0.8674 \| \| 0.0688 \| 24.5085 \| 1446 \| 0.7133 \| 0.4668 \| 0.7133 \| 0.8446 \| \| 0.0688 \| 24.5424 \| 1448 \| 0.6904 \| 0.4707 \| 0.6904 \| 0.8309 \| \| 0.0688 \| 24.5763 \| 1450 \| 0.6765 \| 0.4798 \| 0.6765 \| 0.8225 \| \| 0.0688 \| 24.6102 \| 1452 \| 0.6908 \| 0.4798 \| 0.6908 \| 0.8312 \| \| 0.0688 \| 24.6441 \| 1454 \| 0.7249 \| 0.4898 \| 0.7249 \| 0.8514 \| \| 0.0688 \| 24.6780 \| 1456 \| 0.7405 \| 0.4772 \| 0.7405 \| 0.8605 \| \| 0.0688 \| 24.7119 \| 1458 \| 0.7419 \| 0.4581 \| 0.7419 \| 0.8613 \| \| 0.0688 \| 24.7458 \| 1460 \| 0.7254 \| 0.4749 \| 0.7254 \| 0.8517 \| \| 0.0688 \| 24.7797 \| 1462 \| 0.6696 \| 0.5260 \| 0.6696 \| 0.8183 \| \| 0.0688 \| 24.8136 \| 1464 \| 0.6295 \| 0.5377 \| 0.6295 \| 0.7934 \| \| 0.0688 \| 24.8475 \| 1466 \| 0.6306 \| 0.5589 \| 0.6306 \| 0.7941 \| \| 0.0688 \| 24.8814 \| 1468 \| 0.6366 \| 0.5589 \| 0.6366 \| 0.7979 \| \| 0.0688 \| 24.9153 \| 1470 \| 0.6203 \| 0.5798 \| 0.6203 \| 0.7876 \| \| 0.0688 \| 24.9492 \| 1472 \| 0.6111 \| 0.5838 \| 0.6111 \| 0.7817 \| \| 0.0688 \| 24.9831 \| 1474 \| 0.5983 \| 0.5991 \| 0.5983 \| 0.7735 \| \| 0.0688 \| 25.0169 \| 1476 \| 0.5922 \| 0.5768 \| 0.5922 \| 0.7695 \| \| 0.0688 \| 25.0508 \| 1478 \| 0.6087 \| 0.5650 \| 0.6087 \| 0.7802 \| \| 0.0688 \| 25.0847 \| 1480 \| 0.6378 \| 0.5006 \| 0.6378 \| 0.7986 \| \| 0.0688 \| 25.1186 \| 1482 \| 0.6557 \| 0.5090 \| 0.6557 \| 0.8097 \| \| 0.0688 \| 25.1525 \| 1484 \| 0.6557 \| 0.5238 \| 0.6557 \| 0.8098 \| \| 0.0688 \| 25.1864 \| 1486 \| 0.6671 \| 0.5388 \| 0.6671 \| 0.8167 \| \| 0.0688 \| 25.2203 \| 1488 \| 0.6794 \| 0.5512 \| 0.6794 \| 0.8243 \| \| 0.0688 \| 25.2542 \| 1490 \| 0.6946 \| 0.4657 \| 0.6946 \| 0.8334 \| \| 0.0688 \| 25.2881 \| 1492 \| 0.6945 \| 0.4412 \| 0.6945 \| 0.8334 \| \| 0.0688 \| 25.3220 \| 1494 \| 0.6800 \| 0.4257 \| 0.6800 \| 0.8246 \| \| 0.0688 \| 25.3559 \| 1496 \| 0.6585 \| 0.4452 \| 0.6585 \| 0.8115 \| \| 0.0688 \| 25.3898 \| 1498 \| 0.6735 \| 0.4751 \| 0.6735 \| 0.8207 \| \| 0.051 \| 25.4237 \| 1500 \| 0.7019 \| 0.5156 \| 0.7019 \| 0.8378 \| \| 0.051 \| 25.4576 \| 1502 \| 0.7023 \| 0.5465 \| 0.7023 \| 0.8380 \| \| 0.051 \| 25.4915 \| 1504 \| 0.6540 \| 0.5178 \| 0.6540 \| 0.8087 \| \| 0.051 \| 25.5254 \| 1506 \| 0.5986 \| 0.5472 \| 0.5986 \| 0.7737 \| \| 0.051 \| 25.5593 \| 1508 \| 0.5904 \| 0.6104 \| 0.5904 \| 0.7684 \| \| 0.051 \| 25.5932 \| 1510 \| 0.5842 \| 0.6043 \| 0.5842 \| 0.7644 \| \| 0.051 \| 25.6271 \| 1512 \| 0.5952 \| 0.6099 \| 0.5952 \| 0.7715 \| \| 0.051 \| 25.6610 \| 1514 \| 0.6068 \| 0.5820 \| 0.6068 \| 0.7790 \| \| 0.051 \| 25.6949 \| 1516 \| 0.6090 \| 0.5472 \| 0.6090 \| 0.7804 \| \| 0.051 \| 25.7288 \| 1518 \| 0.5929 \| 0.5490 \| 0.5929 \| 0.7700 \| \| 0.051 \| 25.7627 \| 1520 \| 0.5754 \| 0.5605 \| 0.5754 \| 0.7585 \| \| 0.051 \| 25.7966 \| 1522 \| 0.5611 \| 0.5487 \| 0.5611 \| 0.7491 \| \| 0.051 \| 25.8305 \| 1524 \| 0.5637 \| 0.5397 \| 0.5637 \| 0.7508 \| \| 0.051 \| 25.8644 \| 1526 \| 0.5930 \| 0.5563 \| 0.5930 \| 0.7701 \| \| 0.051 \| 25.8983 \| 1528 \| 0.6057 \| 0.5521 \| 0.6057 \| 0.7783 \| \| 0.051 \| 25.9322 \| 1530 \| 0.6095 \| 0.5440 \| 0.6095 \| 0.7807 \| \| 0.051 \| 25.9661 \| 1532 \| 0.5898 \| 0.5536 \| 0.5898 \| 0.7680 \| \| 0.051 \| 26.0 \| 1534 \| 0.5781 \| 0.5428 \| 0.5781 \| 0.7604 \| \| 0.051 \| 26.0339 \| 1536 \| 0.5740 \| 0.4951 \| 0.5740 \| 0.7577 \| \| 0.051 \| 26.0678 \| 1538 \| 0.5802 \| 0.5013 \| 0.5802 \| 0.7617 \| \| 0.051 \| 26.1017 \| 1540 \| 0.5976 \| 0.5069 \| 0.5976 \| 0.7730 \| \| 0.051 \| 26.1356 \| 1542 \| 0.6146 \| 0.5257 \| 0.6146 \| 0.7839 \| \| 0.051 \| 26.1695 \| 1544 \| 0.6260 \| 0.5303 \| 0.6260 \| 0.7912 \| \| 0.051 \| 26.2034 \| 1546 \| 0.6064 \| 0.5257 \| 0.6064 \| 0.7787 \| \| 0.051 \| 26.2373 \| 1548 \| 0.5797 \| 0.5048 \| 0.5797 \| 0.7614 \| \| 0.051 \| 26.2712 \| 1550 \| 0.5579 \| 0.4658 \| 0.5579 \| 0.7469 \| \| 0.051 \| 26.3051 \| 1552 \| 0.5481 \| 0.4807 \| 0.5481 \| 0.7403 \| \| 0.051 \| 26.3390 \| 1554 \| 0.5522 \| 0.4847 \| 0.5522 \| 0.7431 \| \| 0.051 \| 26.3729 \| 1556 \| 0.5617 \| 0.4874 \| 0.5617 \| 0.7495 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
pepijn223/phrivi-finetuned	pepijn223	2025-01-15T16:08:49Z	53	0	transformers	[ "transformers", "tensorboard", "safetensors", "paligemma", "image-text-to-text", "generated_from_trainer", "base_model:google/paligemma-3b-pt-224", "base_model:finetune:google/paligemma-3b-pt-224", "license:gemma", "text-generation-inference", "endpoints_compatible", "region:us" ]	image-text-to-text	2025-01-09T16:54:17Z	--- library_name: transformers license: gemma base_model: google/paligemma-3b-pt-224 tags: - generated_from_trainer model-index: - name: phrivi-finetuned results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # phrivi-finetuned This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2 - num_epochs: 1 ### Training results ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
nbninh/fbc7e776-e353-4000-a7aa-e8927900b5ed	nbninh	2025-01-15T16:08:41Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:09:23Z	--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: fbc7e776-e353-4000-a7aa-e8927900b5ed results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nbninh/fbc7e776-e353-4000-a7aa-e8927900b5ed hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <\|eot_id\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # fbc7e776-e353-4000-a7aa-e8927900b5ed This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1869 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.1759 \| 0.0109 \| 200 \| 1.1869 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
akhooli/setfit_ar_hs_mb	akhooli	2025-01-15T16:07:49Z	9	0	setfit	[ "setfit", "safetensors", "modernbert", "sentence-transformers", "text-classification", "generated_from_setfit_trainer", "arxiv:2209.11055", "base_model:akhooli/sbert-nli-500k-triplets-MB", "base_model:finetune:akhooli/sbert-nli-500k-triplets-MB", "model-index", "region:us" ]	text-classification	2025-01-15T16:07:32Z	--- tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: يا حاقد ع الاسلام السياسي - text: 'بلد مخيف، صار القتل بحجه الشرف متل قتل بعوضة، واللي بيخوف اكتر من اللي واقف مكتف ايديه ومش مساعد. وين كنآ، ووين وصلنآ، لمتى حنضل عايشين وساكتين! ' - text: "من خلال المتابعة ..يتضح أن أكثر اللاعبين الذين يتم تسويقهم هم لاعبي امريكا\ \ الجنوبية وأقلهم الافارقة. \nمن خلال الواقع ..أكثر اللاعبين تهاونا ولعب على\ \ الواقف في آخر ٦ شهور من عقودهم هم لاعبي امريكا الجنوبية ." - text: ' علم الحزب يا فهمانه ما حطوا لانه عم يحكي وطنيا ومشان ماحدا متلك يعترض. اذا حطوا بتعترضي واذا ما حطوا كمان بتعترضي.' - text: "شيوعي \nعلماني \nمسيحي\nانصار سنه \nصوفي \nيمثلك التجمع \nلا يمثلك التجمع\ \ \nاهلا بكم جميعا فنحن نريد بناء وطن ❤" metrics: - accuracy pipeline_tag: text-classification library_name: setfit inference: true base_model: akhooli/sbert-nli-500k-triplets-MB model-index: - name: SetFit with akhooli/sbert-nli-500k-triplets-MB results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 0.7956709956709956 name: Accuracy --- # SetFit with akhooli/sbert-nli-500k-triplets-MB This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [akhooli/sbert-nli-500k-triplets-MB](https://huggingface.co/akhooli/sbert-nli-500k-triplets-MB) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - Model Type: SetFit - Sentence Transformer body: [akhooli/sbert-nli-500k-triplets-MB](https://huggingface.co/akhooli/sbert-nli-500k-triplets-MB) - Classification head: a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - Maximum Sequence Length: 8192 tokens - Number of Classes: 2 classes <!-- - Training Dataset: [Unknown](https://huggingface.co/datasets/unknown) --> <!-- - Language: Unknown --> <!-- - License: Unknown --> ### Model Sources - Repository: [SetFit on GitHub](https://github.com/huggingface/setfit) - Paper: [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - Blogpost: [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels \| Label \| Examples \| \|:---------\|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\| \| positive \| <ul><li>' سبحان الله الفلسطينيين شعب خاين في كل مكان \nلاحول ولا قوة إلا بالله'</li><li>'يا بيك عّم تخبرنا عن شي ما فينا تعملو نحن ماًعندنا نواب ولا وزراء بمثلونا بالدولة الا اذا زهقان وعبالك ليك'</li><li>'جوز كذابين منافقين…'</li></ul> \| \| negative \| <ul><li>'ربي لا تجعلني أسيء الظن بأحد ولا تجعل في قلبي شيئا على أحد ، اللهم أسألك قلباً نقياً صافيا'</li><li>'هشام حداد عامل فيها جون ستيوارت'</li><li>' بحياة اختك من وين بتجيبي اخبارك؟؟ من صغري وانا عبالي كون… LINK'</li></ul> \| ## Evaluation ### Metrics \| Label \| Accuracy \| \|:--------\|:---------\| \| all \| 0.7957 \| ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("akhooli/setfit_ar_hs_mb") # Run inference preds = model("يا حاقد ع الاسلام السياسي") ``` <!-- ### Downstream Use List how someone could finetune this model on their own dataset. --> <!-- ### Out-of-Scope Use List how the model may foreseeably be misused and address what users ought not to do with the model. --> <!-- ## Bias, Risks and Limitations What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model. --> <!-- ### Recommendations What are recommendations with respect to the foreseeable issues? For example, filtering explicit content. --> ## Training Details ### Training Set Metrics \| Training set \| Min \| Median \| Max \| \|:-------------\|:----\|:--------\|:----\| \| Word count \| 1 \| 18.8388 \| 185 \| \| Label \| Training Sample Count \| \|:---------\|:----------------------\| \| negative \| 5200 \| \| positive \| 4943 \| ### Training Hyperparameters - batch_size: (16, 16) - num_epochs: (1, 1) - max_steps: 6000 - sampling_strategy: undersampling - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - l2_weight: 0.01 - seed: 42 - run_name: setfit_hate_52k_mb_6k - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results \| Epoch \| Step \| Training Loss \| Validation Loss \| \|:------:\|:----:\|:-------------:\|:---------------:\| \| 0.0003 \| 1 \| 0.3373 \| - \| \| 0.0333 \| 100 \| 0.2955 \| - \| \| 0.0667 \| 200 \| 0.2535 \| - \| \| 0.1 \| 300 \| 0.2373 \| - \| \| 0.1333 \| 400 \| 0.2228 \| - \| \| 0.1667 \| 500 \| 0.1956 \| - \| \| 0.2 \| 600 \| 0.1768 \| - \| \| 0.2333 \| 700 \| 0.1489 \| - \| \| 0.2667 \| 800 \| 0.122 \| - \| \| 0.3 \| 900 \| 0.1045 \| - \| \| 0.3333 \| 1000 \| 0.086 \| - \| \| 0.3667 \| 1100 \| 0.0681 \| - \| \| 0.4 \| 1200 \| 0.067 \| - \| \| 0.4333 \| 1300 \| 0.0477 \| - \| \| 0.4667 \| 1400 \| 0.043 \| - \| \| 0.5 \| 1500 \| 0.0316 \| - \| \| 0.5333 \| 1600 \| 0.0251 \| - \| \| 0.5667 \| 1700 \| 0.0236 \| - \| \| 0.6 \| 1800 \| 0.0163 \| - \| \| 0.6333 \| 1900 \| 0.0148 \| - \| \| 0.6667 \| 2000 \| 0.0105 \| - \| \| 0.7 \| 2100 \| 0.018 \| - \| \| 0.7333 \| 2200 \| 0.013 \| - \| \| 0.7667 \| 2300 \| 0.0103 \| - \| \| 0.8 \| 2400 \| 0.0107 \| - \| \| 0.8333 \| 2500 \| 0.0115 \| - \| \| 0.8667 \| 2600 \| 0.0069 \| - \| \| 0.9 \| 2700 \| 0.0062 \| - \| \| 0.9333 \| 2800 \| 0.0074 \| - \| \| 0.9667 \| 2900 \| 0.0063 \| - \| \| 1.0 \| 3000 \| 0.0068 \| - \| \| 1.0333 \| 3100 \| 0.0048 \| - \| \| 1.0667 \| 3200 \| 0.0055 \| - \| \| 1.1 \| 3300 \| 0.0047 \| - \| \| 1.1333 \| 3400 \| 0.0043 \| - \| \| 1.1667 \| 3500 \| 0.0029 \| - \| \| 1.2 \| 3600 \| 0.0036 \| - \| \| 1.2333 \| 3700 \| 0.0034 \| - \| \| 1.2667 \| 3800 \| 0.0024 \| - \| \| 1.3 \| 3900 \| 0.0033 \| - \| \| 1.3333 \| 4000 \| 0.0042 \| - \| \| 1.3667 \| 4100 \| 0.0039 \| - \| \| 1.4 \| 4200 \| 0.0019 \| - \| \| 1.4333 \| 4300 \| 0.0022 \| - \| \| 1.4667 \| 4400 \| 0.0031 \| - \| \| 1.5 \| 4500 \| 0.0019 \| - \| \| 1.5333 \| 4600 \| 0.0036 \| - \| \| 1.5667 \| 4700 \| 0.0017 \| - \| \| 1.6 \| 4800 \| 0.0007 \| - \| \| 1.6333 \| 4900 \| 0.0006 \| - \| \| 1.6667 \| 5000 \| 0.0019 \| - \| \| 1.7 \| 5100 \| 0.0022 \| - \| \| 1.7333 \| 5200 \| 0.0013 \| - \| \| 1.7667 \| 5300 \| 0.0025 \| - \| \| 1.8 \| 5400 \| 0.0024 \| - \| \| 1.8333 \| 5500 \| 0.0013 \| - \| \| 1.8667 \| 5600 \| 0.0022 \| - \| \| 1.9 \| 5700 \| 0.0022 \| - \| \| 1.9333 \| 5800 \| 0.0019 \| - \| \| 1.9667 \| 5900 \| 0.0019 \| - \| \| 2.0 \| 6000 \| 0.0031 \| - \| ### Framework Versions - Python: 3.10.12 - SetFit: 1.2.0.dev0 - Sentence Transformers: 3.3.1 - Transformers: 4.48.0 - PyTorch: 2.5.1+cu121 - Datasets: 3.2.0 - Tokenizers: 0.21.0 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ``` <!-- ## Glossary Clearly define terms in order to be accessible across audiences. --> <!-- ## Model Card Authors Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction. --> <!-- ## Model Card Contact Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors. -->
nhungphammmmm/f4dd682c-79ff-4237-a141-c43695838f85	nhungphammmmm	2025-01-15T16:07:31Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-1.5B-Instruct", "base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:51:51Z	--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: f4dd682c-79ff-4237-a141-c43695838f85 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-1.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 756452db934ae1d1_train_data.json ds_type: json format: custom path: /workspace/input_data/756452db934ae1d1_train_data.json type: field_instruction: question field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhungphammmmm/f4dd682c-79ff-4237-a141-c43695838f85 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/756452db934ae1d1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 74979543-06fb-451f-b2f1-4786823d5776 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 74979543-06fb-451f-b2f1-4786823d5776 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # f4dd682c-79ff-4237-a141-c43695838f85 This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9338 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.8583 \| 0.0195 \| 200 \| 0.9338 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso11/91645d6e-af35-438f-a2bb-ad7694222576	lesso11	2025-01-15T16:06:53Z	8	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:36:02Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: 91645d6e-af35-438f-a2bb-ad7694222576 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: true chat_template: llama3 datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso11/91645d6e-af35-438f-a2bb-ad7694222576 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 91645d6e-af35-438f-a2bb-ad7694222576 This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0001 \| 1 \| nan \| \| 0.0 \| 0.0003 \| 5 \| nan \| \| 0.0 \| 0.0005 \| 10 \| nan \| \| 0.0 \| 0.0008 \| 15 \| nan \| \| 0.0 \| 0.0010 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
phonemetransformers/CHILDES-Icelandic-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:28Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:52Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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phonemetransformers/CHILDES-Farsi-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:27Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:51Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
phonemetransformers/CHILDES-Turkish-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:26Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:50Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-Basque-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:24Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:48Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-Danish-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:23Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:47Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-Japanese-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:18Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-Spanish-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:10Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:38Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-German-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:08Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:36Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-French-phoneme-tokenizer	phonemetransformers	2025-01-15T16:05:03Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:33Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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phonemetransformers/CHILDES-English-phoneme-tokenizer	phonemetransformers	2025-01-15T16:04:55Z	0	0	transformers	[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-06-03T13:23:31Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization	MayBashendy	2025-01-15T16:04:43Z	7	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T15:46:57Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8110 - Qwk: 0.2754 - Mse: 1.8110 - Rmse: 1.3457 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0270 \| 2 \| 7.2082 \| -0.0162 \| 7.2082 \| 2.6848 \| \| No log \| 0.0541 \| 4 \| 4.4178 \| 0.0833 \| 4.4178 \| 2.1018 \| \| No log \| 0.0811 \| 6 \| 3.6012 \| -0.0423 \| 3.6012 \| 1.8977 \| \| No log \| 0.1081 \| 8 \| 3.9013 \| -0.0796 \| 3.9013 \| 1.9752 \| \| No log \| 0.1351 \| 10 \| 2.2566 \| 0.1194 \| 2.2566 \| 1.5022 \| \| No log \| 0.1622 \| 12 \| 1.8780 \| 0.1593 \| 1.8780 \| 1.3704 \| \| No log \| 0.1892 \| 14 \| 2.1948 \| -0.0625 \| 2.1948 \| 1.4815 \| \| No log \| 0.2162 \| 16 \| 2.2320 \| -0.0472 \| 2.2320 \| 1.4940 \| \| No log \| 0.2432 \| 18 \| 2.2639 \| 0.0305 \| 2.2639 \| 1.5046 \| \| No log \| 0.2703 \| 20 \| 2.2500 \| 0.0606 \| 2.2500 \| 1.5000 \| \| No log \| 0.2973 \| 22 \| 2.1048 \| 0.1157 \| 2.1048 \| 1.4508 \| \| No log \| 0.3243 \| 24 \| 2.0103 \| 0.2018 \| 2.0103 \| 1.4179 \| \| No log \| 0.3514 \| 26 \| 1.9807 \| 0.1869 \| 1.9807 \| 1.4074 \| \| No log \| 0.3784 \| 28 \| 1.9049 \| 0.1698 \| 1.9049 \| 1.3802 \| \| No log \| 0.4054 \| 30 \| 1.8210 \| 0.1714 \| 1.8210 \| 1.3494 \| \| No log \| 0.4324 \| 32 \| 1.7544 \| 0.1714 \| 1.7544 \| 1.3245 \| \| No log \| 0.4595 \| 34 \| 1.6969 \| 0.1154 \| 1.6969 \| 1.3027 \| \| No log \| 0.4865 \| 36 \| 1.6768 \| 0.2569 \| 1.6768 \| 1.2949 \| \| No log \| 0.5135 \| 38 \| 1.8115 \| 0.2459 \| 1.8115 \| 1.3459 \| \| No log \| 0.5405 \| 40 \| 1.8102 \| 0.2459 \| 1.8102 \| 1.3454 \| \| No log \| 0.5676 \| 42 \| 1.8407 \| 0.3465 \| 1.8407 \| 1.3567 \| \| No log \| 0.5946 \| 44 \| 1.6912 \| 0.2735 \| 1.6912 \| 1.3005 \| \| No log \| 0.6216 \| 46 \| 1.5411 \| 0.1682 \| 1.5411 \| 1.2414 \| \| No log \| 0.6486 \| 48 \| 1.4974 \| 0.1524 \| 1.4974 \| 1.2237 \| \| No log \| 0.6757 \| 50 \| 1.5038 \| 0.2243 \| 1.5038 \| 1.2263 \| \| No log \| 0.7027 \| 52 \| 1.5548 \| 0.2202 \| 1.5548 \| 1.2469 \| \| No log \| 0.7297 \| 54 \| 1.5638 \| 0.2321 \| 1.5638 \| 1.2505 \| \| No log \| 0.7568 \| 56 \| 1.5255 \| 0.2301 \| 1.5255 \| 1.2351 \| \| No log \| 0.7838 \| 58 \| 1.4802 \| 0.2182 \| 1.4802 \| 1.2166 \| \| No log \| 0.8108 \| 60 \| 1.4783 \| 0.2056 \| 1.4783 \| 1.2159 \| \| No log \| 0.8378 \| 62 \| 1.5381 \| 0.2407 \| 1.5381 \| 1.2402 \| \| No log \| 0.8649 \| 64 \| 1.5067 \| 0.2545 \| 1.5067 \| 1.2275 \| \| No log \| 0.8919 \| 66 \| 1.4023 \| 0.3509 \| 1.4023 \| 1.1842 \| \| No log \| 0.9189 \| 68 \| 1.2808 \| 0.3966 \| 1.2808 \| 1.1317 \| \| No log \| 0.9459 \| 70 \| 1.1520 \| 0.5116 \| 1.1520 \| 1.0733 \| \| No log \| 0.9730 \| 72 \| 1.1067 \| 0.5238 \| 1.1067 \| 1.0520 \| \| No log \| 1.0 \| 74 \| 1.1387 \| 0.5167 \| 1.1387 \| 1.0671 \| \| No log \| 1.0270 \| 76 \| 1.2173 \| 0.5366 \| 1.2173 \| 1.1033 \| \| No log \| 1.0541 \| 78 \| 1.3335 \| 0.4500 \| 1.3335 \| 1.1548 \| \| No log \| 1.0811 \| 80 \| 1.3091 \| 0.5082 \| 1.3091 \| 1.1442 \| \| No log \| 1.1081 \| 82 \| 1.2611 \| 0.5124 \| 1.2611 \| 1.1230 \| \| No log \| 1.1351 \| 84 \| 1.3162 \| 0.4370 \| 1.3162 \| 1.1473 \| \| No log \| 1.1622 \| 86 \| 1.2898 \| 0.4667 \| 1.2898 \| 1.1357 \| \| No log \| 1.1892 \| 88 \| 1.2614 \| 0.4715 \| 1.2614 \| 1.1231 \| \| No log \| 1.2162 \| 90 \| 1.5039 \| 0.3636 \| 1.5039 \| 1.2263 \| \| No log \| 1.2432 \| 92 \| 1.7922 \| 0.2581 \| 1.7922 \| 1.3387 \| \| No log \| 1.2703 \| 94 \| 1.6562 \| 0.2812 \| 1.6562 \| 1.2869 \| \| No log \| 1.2973 \| 96 \| 1.6710 \| 0.2879 \| 1.6710 \| 1.2927 \| \| No log \| 1.3243 \| 98 \| 1.6769 \| 0.2899 \| 1.6769 \| 1.2950 \| \| No log \| 1.3514 \| 100 \| 1.7390 \| 0.3022 \| 1.7390 \| 1.3187 \| \| No log \| 1.3784 \| 102 \| 1.6659 \| 0.3022 \| 1.6659 \| 1.2907 \| \| No log \| 1.4054 \| 104 \| 1.6323 \| 0.3212 \| 1.6323 \| 1.2776 \| \| No log \| 1.4324 \| 106 \| 1.5980 \| 0.3636 \| 1.5980 \| 1.2641 \| \| No log \| 1.4595 \| 108 \| 1.4648 \| 0.4427 \| 1.4648 \| 1.2103 \| \| No log \| 1.4865 \| 110 \| 1.4642 \| 0.5203 \| 1.4642 \| 1.2100 \| \| No log \| 1.5135 \| 112 \| 1.5540 \| 0.3016 \| 1.5540 \| 1.2466 \| \| No log \| 1.5405 \| 114 \| 1.7152 \| 0.2344 \| 1.7152 \| 1.3096 \| \| No log \| 1.5676 \| 116 \| 1.6887 \| 0.3030 \| 1.6887 \| 1.2995 \| \| No log \| 1.5946 \| 118 \| 1.6345 \| 0.3478 \| 1.6345 \| 1.2785 \| \| No log \| 1.6216 \| 120 \| 1.5541 \| 0.3889 \| 1.5541 \| 1.2466 \| \| No log \| 1.6486 \| 122 \| 1.7321 \| 0.3429 \| 1.7321 \| 1.3161 \| \| No log \| 1.6757 \| 124 \| 1.7849 \| 0.3429 \| 1.7849 \| 1.3360 \| \| No log \| 1.7027 \| 126 \| 1.7942 \| 0.3212 \| 1.7942 \| 1.3395 \| \| No log \| 1.7297 \| 128 \| 1.6782 \| 0.3478 \| 1.6782 \| 1.2954 \| \| No log \| 1.7568 \| 130 \| 1.6333 \| 0.2791 \| 1.6333 \| 1.2780 \| \| No log \| 1.7838 \| 132 \| 1.6812 \| 0.2764 \| 1.6812 \| 1.2966 \| \| No log \| 1.8108 \| 134 \| 1.6148 \| 0.2759 \| 1.6148 \| 1.2707 \| \| No log \| 1.8378 \| 136 \| 1.5928 \| 0.3306 \| 1.5928 \| 1.2621 \| \| No log \| 1.8649 \| 138 \| 1.5961 \| 0.3252 \| 1.5961 \| 1.2634 \| \| No log \| 1.8919 \| 140 \| 1.6132 \| 0.2951 \| 1.6132 \| 1.2701 \| \| No log \| 1.9189 \| 142 \| 1.6740 \| 0.3876 \| 1.6740 \| 1.2938 \| \| No log \| 1.9459 \| 144 \| 1.5854 \| 0.3281 \| 1.5854 \| 1.2591 \| \| No log \| 1.9730 \| 146 \| 1.5721 \| 0.3492 \| 1.5721 \| 1.2538 \| \| No log \| 2.0 \| 148 \| 1.5770 \| 0.3759 \| 1.5770 \| 1.2558 \| \| No log \| 2.0270 \| 150 \| 1.4834 \| 0.3360 \| 1.4834 \| 1.2179 \| \| No log \| 2.0541 \| 152 \| 1.3675 \| 0.3871 \| 1.3675 \| 1.1694 \| \| No log \| 2.0811 \| 154 \| 1.3421 \| 0.3577 \| 1.3421 \| 1.1585 \| \| No log \| 2.1081 \| 156 \| 1.5974 \| 0.3942 \| 1.5974 \| 1.2639 \| \| No log \| 2.1351 \| 158 \| 1.7204 \| 0.3597 \| 1.7204 \| 1.3117 \| \| No log \| 2.1622 \| 160 \| 1.5333 \| 0.3852 \| 1.5333 \| 1.2382 \| \| No log \| 2.1892 \| 162 \| 1.4891 \| 0.3622 \| 1.4891 \| 1.2203 \| \| No log \| 2.2162 \| 164 \| 1.6118 \| 0.3459 \| 1.6118 \| 1.2696 \| \| No log \| 2.2432 \| 166 \| 1.8269 \| 0.3358 \| 1.8269 \| 1.3516 \| \| No log \| 2.2703 \| 168 \| 1.6298 \| 0.3259 \| 1.6298 \| 1.2766 \| \| No log \| 2.2973 \| 170 \| 1.5699 \| 0.3134 \| 1.5699 \| 1.2530 \| \| No log \| 2.3243 \| 172 \| 1.5849 \| 0.3529 \| 1.5849 \| 1.2589 \| \| No log \| 2.3514 \| 174 \| 1.6959 \| 0.3478 \| 1.6959 \| 1.3023 \| \| No log \| 2.3784 \| 176 \| 1.8324 \| 0.2857 \| 1.8324 \| 1.3537 \| \| No log \| 2.4054 \| 178 \| 1.6801 \| 0.3741 \| 1.6801 \| 1.2962 \| \| No log \| 2.4324 \| 180 \| 1.6340 \| 0.3623 \| 1.6340 \| 1.2783 \| \| No log \| 2.4595 \| 182 \| 1.5266 \| 0.4427 \| 1.5266 \| 1.2355 \| \| No log \| 2.4865 \| 184 \| 1.4815 \| 0.3770 \| 1.4815 \| 1.2172 \| \| No log \| 2.5135 \| 186 \| 1.4268 \| 0.3130 \| 1.4268 \| 1.1945 \| \| No log \| 2.5405 \| 188 \| 1.3539 \| 0.3478 \| 1.3539 \| 1.1636 \| \| No log \| 2.5676 \| 190 \| 1.4250 \| 0.4545 \| 1.4250 \| 1.1937 \| \| No log \| 2.5946 \| 192 \| 1.6666 \| 0.3768 \| 1.6666 \| 1.2910 \| \| No log \| 2.6216 \| 194 \| 1.8661 \| 0.2878 \| 1.8661 \| 1.3661 \| \| No log \| 2.6486 \| 196 \| 1.8096 \| 0.3121 \| 1.8096 \| 1.3452 \| \| No log \| 2.6757 \| 198 \| 1.5584 \| 0.3942 \| 1.5584 \| 1.2484 \| \| No log \| 2.7027 \| 200 \| 1.3693 \| 0.5481 \| 1.3693 \| 1.1702 \| \| No log \| 2.7297 \| 202 \| 1.3817 \| 0.5185 \| 1.3817 \| 1.1755 \| \| No log \| 2.7568 \| 204 \| 1.4770 \| 0.4478 \| 1.4770 \| 1.2153 \| \| No log \| 2.7838 \| 206 \| 1.6677 \| 0.3597 \| 1.6677 \| 1.2914 \| \| No log \| 2.8108 \| 208 \| 1.7582 \| 0.3453 \| 1.7582 \| 1.3260 \| \| No log \| 2.8378 \| 210 \| 1.6186 \| 0.4060 \| 1.6186 \| 1.2722 \| \| No log \| 2.8649 \| 212 \| 1.4199 \| 0.4286 \| 1.4199 \| 1.1916 \| \| No log \| 2.8919 \| 214 \| 1.3802 \| 0.4567 \| 1.3802 \| 1.1748 \| \| No log \| 2.9189 \| 216 \| 1.5417 \| 0.4380 \| 1.5417 \| 1.2416 \| \| No log \| 2.9459 \| 218 \| 2.0088 \| 0.2207 \| 2.0088 \| 1.4173 \| \| No log \| 2.9730 \| 220 \| 2.2277 \| 0.1408 \| 2.2277 \| 1.4925 \| \| No log \| 3.0 \| 222 \| 2.1407 \| 0.0597 \| 2.1407 \| 1.4631 \| \| No log \| 3.0270 \| 224 \| 1.8514 \| 0.1951 \| 1.8514 \| 1.3607 \| \| No log \| 3.0541 \| 226 \| 1.6430 \| 0.3740 \| 1.6430 \| 1.2818 \| \| No log \| 3.0811 \| 228 \| 1.5615 \| 0.4127 \| 1.5615 \| 1.2496 \| \| No log \| 3.1081 \| 230 \| 1.5855 \| 0.4627 \| 1.5855 \| 1.2592 \| \| No log \| 3.1351 \| 232 \| 1.6564 \| 0.3429 \| 1.6564 \| 1.2870 \| \| No log \| 3.1622 \| 234 \| 1.5814 \| 0.4203 \| 1.5814 \| 1.2576 \| \| No log \| 3.1892 \| 236 \| 1.4123 \| 0.4923 \| 1.4123 \| 1.1884 \| \| No log \| 3.2162 \| 238 \| 1.4214 \| 0.4961 \| 1.4214 \| 1.1922 \| \| No log \| 3.2432 \| 240 \| 1.5848 \| 0.3971 \| 1.5848 \| 1.2589 \| \| No log \| 3.2703 \| 242 \| 1.7020 \| 0.3885 \| 1.7020 \| 1.3046 \| \| No log \| 3.2973 \| 244 \| 1.8595 \| 0.2483 \| 1.8595 \| 1.3636 \| \| No log \| 3.3243 \| 246 \| 2.0443 \| 0.1806 \| 2.0443 \| 1.4298 \| \| No log \| 3.3514 \| 248 \| 2.0324 \| 0.1806 \| 2.0324 \| 1.4256 \| \| No log \| 3.3784 \| 250 \| 1.8233 \| 0.2254 \| 1.8233 \| 1.3503 \| \| No log \| 3.4054 \| 252 \| 1.6159 \| 0.3910 \| 1.6159 \| 1.2712 \| \| No log \| 3.4324 \| 254 \| 1.5849 \| 0.3759 \| 1.5849 \| 1.2589 \| \| No log \| 3.4595 \| 256 \| 1.6667 \| 0.3876 \| 1.6667 \| 1.2910 \| \| No log \| 3.4865 \| 258 \| 1.8424 \| 0.2590 \| 1.8424 \| 1.3574 \| \| No log \| 3.5135 \| 260 \| 1.9403 \| 0.1958 \| 1.9403 \| 1.3929 \| \| No log \| 3.5405 \| 262 \| 2.0503 \| 0.1655 \| 2.0502 \| 1.4319 \| \| No log \| 3.5676 \| 264 \| 1.8608 \| 0.2817 \| 1.8608 \| 1.3641 \| \| No log \| 3.5946 \| 266 \| 1.7975 \| 0.3077 \| 1.7975 \| 1.3407 \| \| No log \| 3.6216 \| 268 \| 1.8322 \| 0.2254 \| 1.8322 \| 1.3536 \| \| No log \| 3.6486 \| 270 \| 1.9213 \| 0.2254 \| 1.9213 \| 1.3861 \| \| No log \| 3.6757 \| 272 \| 1.9880 \| 0.2254 \| 1.9880 \| 1.4100 \| \| No log \| 3.7027 \| 274 \| 1.9393 \| 0.2254 \| 1.9393 \| 1.3926 \| \| No log \| 3.7297 \| 276 \| 1.8321 \| 0.2270 \| 1.8321 \| 1.3536 \| \| No log \| 3.7568 \| 278 \| 1.8982 \| 0.2254 \| 1.8982 \| 1.3778 \| \| No log \| 3.7838 \| 280 \| 1.9421 \| 0.2254 \| 1.9421 \| 1.3936 \| \| No log \| 3.8108 \| 282 \| 2.0218 \| 0.2254 \| 2.0218 \| 1.4219 \| \| No log \| 3.8378 \| 284 \| 1.9314 \| 0.2553 \| 1.9314 \| 1.3898 \| \| No log \| 3.8649 \| 286 \| 1.8592 \| 0.2571 \| 1.8592 \| 1.3635 \| \| No log \| 3.8919 \| 288 \| 1.6958 \| 0.2963 \| 1.6958 \| 1.3022 \| \| No log \| 3.9189 \| 290 \| 1.6157 \| 0.3840 \| 1.6157 \| 1.2711 \| \| No log \| 3.9459 \| 292 \| 1.6598 \| 0.3101 \| 1.6598 \| 1.2883 \| \| No log \| 3.9730 \| 294 \| 1.5943 \| 0.4394 \| 1.5943 \| 1.2626 \| \| No log \| 4.0 \| 296 \| 1.4468 \| 0.4615 \| 1.4468 \| 1.2028 \| \| No log \| 4.0270 \| 298 \| 1.3742 \| 0.4567 \| 1.3742 \| 1.1723 \| \| No log \| 4.0541 \| 300 \| 1.3576 \| 0.4531 \| 1.3576 \| 1.1651 \| \| No log \| 4.0811 \| 302 \| 1.5542 \| 0.3881 \| 1.5542 \| 1.2467 \| \| No log \| 4.1081 \| 304 \| 1.7148 \| 0.2979 \| 1.7148 \| 1.3095 \| \| No log \| 4.1351 \| 306 \| 1.7422 \| 0.3099 \| 1.7422 \| 1.3199 \| \| No log \| 4.1622 \| 308 \| 1.8653 \| 0.2817 \| 1.8653 \| 1.3658 \| \| No log \| 4.1892 \| 310 \| 1.8779 \| 0.2817 \| 1.8779 \| 1.3704 \| \| No log \| 4.2162 \| 312 \| 1.9154 \| 0.2517 \| 1.9154 \| 1.3840 \| \| No log \| 4.2432 \| 314 \| 1.8347 \| 0.2817 \| 1.8347 \| 1.3545 \| \| No log \| 4.2703 \| 316 \| 1.7254 \| 0.2937 \| 1.7254 \| 1.3135 \| \| No log \| 4.2973 \| 318 \| 1.7849 \| 0.2937 \| 1.7849 \| 1.3360 \| \| No log \| 4.3243 \| 320 \| 2.0441 \| 0.2207 \| 2.0441 \| 1.4297 \| \| No log \| 4.3514 \| 322 \| 2.0704 \| 0.2207 \| 2.0704 \| 1.4389 \| \| No log \| 4.3784 \| 324 \| 2.0644 \| 0.2222 \| 2.0644 \| 1.4368 \| \| No log \| 4.4054 \| 326 \| 1.8950 \| 0.2817 \| 1.8950 \| 1.3766 \| \| No log \| 4.4324 \| 328 \| 1.6892 \| 0.3088 \| 1.6892 \| 1.2997 \| \| No log \| 4.4595 \| 330 \| 1.6061 \| 0.3284 \| 1.6061 \| 1.2673 \| \| No log \| 4.4865 \| 332 \| 1.6050 \| 0.3284 \| 1.6050 \| 1.2669 \| \| No log \| 4.5135 \| 334 \| 1.6380 \| 0.2707 \| 1.6380 \| 1.2798 \| \| No log \| 4.5405 \| 336 \| 1.6928 \| 0.2628 \| 1.6928 \| 1.3011 \| \| No log \| 4.5676 \| 338 \| 1.6034 \| 0.3088 \| 1.6034 \| 1.2662 \| \| No log \| 4.5946 \| 340 \| 1.5406 \| 0.3704 \| 1.5406 \| 1.2412 \| \| No log \| 4.6216 \| 342 \| 1.6825 \| 0.2899 \| 1.6825 \| 1.2971 \| \| No log \| 4.6486 \| 344 \| 1.7879 \| 0.2553 \| 1.7879 \| 1.3371 \| \| No log \| 4.6757 \| 346 \| 1.7188 \| 0.3000 \| 1.7188 \| 1.3110 \| \| No log \| 4.7027 \| 348 \| 1.6851 \| 0.2794 \| 1.6851 \| 1.2981 \| \| No log \| 4.7297 \| 350 \| 1.7611 \| 0.2256 \| 1.7611 \| 1.3271 \| \| No log \| 4.7568 \| 352 \| 1.9253 \| 0.2090 \| 1.9253 \| 1.3875 \| \| No log \| 4.7838 \| 354 \| 2.0759 \| 0.1515 \| 2.0759 \| 1.4408 \| \| No log \| 4.8108 \| 356 \| 2.0925 \| 0.1571 \| 2.0925 \| 1.4465 \| \| No log \| 4.8378 \| 358 \| 2.0788 \| 0.1944 \| 2.0788 \| 1.4418 \| \| No log \| 4.8649 \| 360 \| 1.9254 \| 0.2553 \| 1.9254 \| 1.3876 \| \| No log \| 4.8919 \| 362 \| 1.6860 \| 0.3088 \| 1.6860 \| 1.2985 \| \| No log \| 4.9189 \| 364 \| 1.6780 \| 0.3459 \| 1.6780 \| 1.2954 \| \| No log \| 4.9459 \| 366 \| 1.6791 \| 0.3459 \| 1.6791 \| 1.2958 \| \| No log \| 4.9730 \| 368 \| 1.6670 \| 0.4242 \| 1.6670 \| 1.2911 \| \| No log \| 5.0 \| 370 \| 1.5885 \| 0.4122 \| 1.5885 \| 1.2604 \| \| No log \| 5.0270 \| 372 \| 1.5051 \| 0.3906 \| 1.5051 \| 1.2268 \| \| No log \| 5.0541 \| 374 \| 1.4867 \| 0.3810 \| 1.4867 \| 1.2193 \| \| No log \| 5.0811 \| 376 \| 1.5628 \| 0.4 \| 1.5628 \| 1.2501 \| \| No log \| 5.1081 \| 378 \| 1.6585 \| 0.3731 \| 1.6585 \| 1.2878 \| \| No log \| 5.1351 \| 380 \| 1.8380 \| 0.2734 \| 1.8380 \| 1.3557 \| \| No log \| 5.1622 \| 382 \| 1.9378 \| 0.2270 \| 1.9378 \| 1.3920 \| \| No log \| 5.1892 \| 384 \| 1.9140 \| 0.2270 \| 1.9140 \| 1.3835 \| \| No log \| 5.2162 \| 386 \| 1.7157 \| 0.3066 \| 1.7157 \| 1.3099 \| \| No log \| 5.2432 \| 388 \| 1.5721 \| 0.3910 \| 1.5721 \| 1.2538 \| \| No log \| 5.2703 \| 390 \| 1.5407 \| 0.4375 \| 1.5407 \| 1.2413 \| \| No log \| 5.2973 \| 392 \| 1.4930 \| 0.4375 \| 1.4930 \| 1.2219 \| \| No log \| 5.3243 \| 394 \| 1.4746 \| 0.4375 \| 1.4746 \| 1.2143 \| \| No log \| 5.3514 \| 396 \| 1.4671 \| 0.4308 \| 1.4671 \| 1.2113 \| \| No log \| 5.3784 \| 398 \| 1.4099 \| 0.4341 \| 1.4099 \| 1.1874 \| \| No log \| 5.4054 \| 400 \| 1.4354 \| 0.4394 \| 1.4354 \| 1.1981 \| \| No log \| 5.4324 \| 402 \| 1.5180 \| 0.3881 \| 1.5180 \| 1.2321 \| \| No log \| 5.4595 \| 404 \| 1.6601 \| 0.3433 \| 1.6601 \| 1.2885 \| \| No log \| 5.4865 \| 406 \| 1.7180 \| 0.3043 \| 1.7180 \| 1.3107 \| \| No log \| 5.5135 \| 408 \| 1.6135 \| 0.3556 \| 1.6135 \| 1.2702 \| \| No log \| 5.5405 \| 410 \| 1.5487 \| 0.4328 \| 1.5487 \| 1.2445 \| \| No log \| 5.5676 \| 412 \| 1.6277 \| 0.3731 \| 1.6277 \| 1.2758 \| \| No log \| 5.5946 \| 414 \| 1.7122 \| 0.3235 \| 1.7122 \| 1.3085 \| \| No log \| 5.6216 \| 416 \| 1.8522 \| 0.2734 \| 1.8522 \| 1.3610 \| \| No log \| 5.6486 \| 418 \| 1.9405 \| 0.2553 \| 1.9405 \| 1.3930 \| \| No log \| 5.6757 \| 420 \| 1.9563 \| 0.2553 \| 1.9563 \| 1.3987 \| \| No log \| 5.7027 \| 422 \| 1.8105 \| 0.2734 \| 1.8105 \| 1.3455 \| \| No log \| 5.7297 \| 424 \| 1.6032 \| 0.4242 \| 1.6032 \| 1.2662 \| \| No log \| 5.7568 \| 426 \| 1.4874 \| 0.3968 \| 1.4874 \| 1.2196 \| \| No log \| 5.7838 \| 428 \| 1.5161 \| 0.368 \| 1.5161 \| 1.2313 \| \| No log \| 5.8108 \| 430 \| 1.7124 \| 0.4091 \| 1.7124 \| 1.3086 \| \| No log \| 5.8378 \| 432 \| 1.8787 \| 0.2734 \| 1.8787 \| 1.3706 \| \| No log \| 5.8649 \| 434 \| 1.9319 \| 0.2553 \| 1.9319 \| 1.3899 \| \| No log \| 5.8919 \| 436 \| 1.8562 \| 0.2734 \| 1.8562 \| 1.3624 \| \| No log \| 5.9189 \| 438 \| 1.7858 \| 0.2899 \| 1.7858 \| 1.3363 \| \| No log \| 5.9459 \| 440 \| 1.9567 \| 0.2254 \| 1.9567 \| 1.3988 \| \| No log \| 5.9730 \| 442 \| 2.0003 \| 0.2254 \| 2.0003 \| 1.4143 \| \| No log \| 6.0 \| 444 \| 1.9405 \| 0.2254 \| 1.9405 \| 1.3930 \| \| No log \| 6.0270 \| 446 \| 1.7613 \| 0.2899 \| 1.7613 \| 1.3271 \| \| No log \| 6.0541 \| 448 \| 1.6111 \| 0.4242 \| 1.6111 \| 1.2693 \| \| No log \| 6.0811 \| 450 \| 1.6096 \| 0.3731 \| 1.6096 \| 1.2687 \| \| No log \| 6.1081 \| 452 \| 1.8084 \| 0.2734 \| 1.8084 \| 1.3447 \| \| No log \| 6.1351 \| 454 \| 2.0332 \| 0.2254 \| 2.0332 \| 1.4259 \| \| No log \| 6.1622 \| 456 \| 2.0020 \| 0.2254 \| 2.0020 \| 1.4149 \| \| No log \| 6.1892 \| 458 \| 1.8074 \| 0.2734 \| 1.8074 \| 1.3444 \| \| No log \| 6.2162 \| 460 \| 1.5295 \| 0.4265 \| 1.5295 \| 1.2367 \| \| No log \| 6.2432 \| 462 \| 1.4173 \| 0.5191 \| 1.4173 \| 1.1905 \| \| No log \| 6.2703 \| 464 \| 1.4113 \| 0.4882 \| 1.4113 \| 1.1880 \| \| No log \| 6.2973 \| 466 \| 1.5022 \| 0.4580 \| 1.5022 \| 1.2256 \| \| No log \| 6.3243 \| 468 \| 1.6681 \| 0.3731 \| 1.6681 \| 1.2915 \| \| No log \| 6.3514 \| 470 \| 1.7982 \| 0.3407 \| 1.7982 \| 1.3410 \| \| No log \| 6.3784 \| 472 \| 1.7536 \| 0.3284 \| 1.7536 \| 1.3242 \| \| No log \| 6.4054 \| 474 \| 1.5888 \| 0.4179 \| 1.5888 \| 1.2605 \| \| No log \| 6.4324 \| 476 \| 1.4139 \| 0.5303 \| 1.4139 \| 1.1891 \| \| No log \| 6.4595 \| 478 \| 1.4145 \| 0.4962 \| 1.4145 \| 1.1893 \| \| No log \| 6.4865 \| 480 \| 1.5579 \| 0.4242 \| 1.5579 \| 1.2481 \| \| No log \| 6.5135 \| 482 \| 1.7630 \| 0.2754 \| 1.7630 \| 1.3278 \| \| No log \| 6.5405 \| 484 \| 1.8474 \| 0.2411 \| 1.8474 \| 1.3592 \| \| No log \| 6.5676 \| 486 \| 1.7922 \| 0.2446 \| 1.7922 \| 1.3387 \| \| No log \| 6.5946 \| 488 \| 1.6658 \| 0.4242 \| 1.6658 \| 1.2907 \| \| No log \| 6.6216 \| 490 \| 1.5592 \| 0.4098 \| 1.5592 \| 1.2487 \| \| No log \| 6.6486 \| 492 \| 1.5511 \| 0.3761 \| 1.5511 \| 1.2454 \| \| No log \| 6.6757 \| 494 \| 1.5523 \| 0.4500 \| 1.5523 \| 1.2459 \| \| No log \| 6.7027 \| 496 \| 1.6037 \| 0.4031 \| 1.6037 \| 1.2664 \| \| No log \| 6.7297 \| 498 \| 1.6611 \| 0.3731 \| 1.6611 \| 1.2888 \| \| 0.3936 \| 6.7568 \| 500 \| 1.6958 \| 0.3235 \| 1.6958 \| 1.3022 \| \| 0.3936 \| 6.7838 \| 502 \| 1.6762 \| 0.3235 \| 1.6762 \| 1.2947 \| \| 0.3936 \| 6.8108 \| 504 \| 1.6236 \| 0.3852 \| 1.6236 \| 1.2742 \| \| 0.3936 \| 6.8378 \| 506 \| 1.5538 \| 0.3852 \| 1.5538 \| 1.2465 \| \| 0.3936 \| 6.8649 \| 508 \| 1.5990 \| 0.3852 \| 1.5990 \| 1.2645 \| \| 0.3936 \| 6.8919 \| 510 \| 1.6781 \| 0.3407 \| 1.6781 \| 1.2954 \| \| 0.3936 \| 6.9189 \| 512 \| 1.7600 \| 0.2920 \| 1.7600 \| 1.3267 \| \| 0.3936 \| 6.9459 \| 514 \| 1.7322 \| 0.2920 \| 1.7322 \| 1.3161 \| \| 0.3936 \| 6.9730 \| 516 \| 1.6869 \| 0.3556 \| 1.6869 \| 1.2988 \| \| 0.3936 \| 7.0 \| 518 \| 1.6151 \| 0.3609 \| 1.6151 \| 1.2709 \| \| 0.3936 \| 7.0270 \| 520 \| 1.5323 \| 0.4478 \| 1.5323 \| 1.2378 \| \| 0.3936 \| 7.0541 \| 522 \| 1.4406 \| 0.4603 \| 1.4406 \| 1.2003 \| \| 0.3936 \| 7.0811 \| 524 \| 1.4687 \| 0.4662 \| 1.4687 \| 1.2119 \| \| 0.3936 \| 7.1081 \| 526 \| 1.5421 \| 0.4179 \| 1.5421 \| 1.2418 \| \| 0.3936 \| 7.1351 \| 528 \| 1.6858 \| 0.2920 \| 1.6858 \| 1.2984 \| \| 0.3936 \| 7.1622 \| 530 \| 1.8141 \| 0.2754 \| 1.8141 \| 1.3469 \| \| 0.3936 \| 7.1892 \| 532 \| 2.0164 \| 0.1690 \| 2.0164 \| 1.4200 \| \| 0.3936 \| 7.2162 \| 534 \| 2.0350 \| 0.1690 \| 2.0350 \| 1.4265 \| \| 0.3936 \| 7.2432 \| 536 \| 1.8110 \| 0.2754 \| 1.8110 \| 1.3457 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
sahandrez/rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811	sahandrez	2025-01-15T16:03:40Z	6	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "generated_from_trainer", "trl", "rloo", "conversational", "arxiv:2402.14740", "base_model:sahandrez/Qwen2.5-1.5B-sft-uf", "base_model:finetune:sahandrez/Qwen2.5-1.5B-sft-uf", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-14T19:28:22Z	--- base_model: sahandrez/Qwen2.5-1.5B-sft-uf library_name: transformers model_name: rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811 tags: - generated_from_trainer - trl - rloo licence: license --- # Model Card for rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811 This model is a fine-tuned version of [sahandrez/Qwen2.5-1.5B-sft-uf](https://huggingface.co/sahandrez/Qwen2.5-1.5B-sft-uf). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="sahandrez/rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/unpaired_rlhf/sahand/runs/w2hc91ea) This model was trained with RLOO, a method introduced in [Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs](https://huggingface.co/papers/2402.14740). ### Framework versions - TRL: 0.13.0 - Transformers: 4.48.0 - Pytorch: 2.4.0 - Datasets: 3.1.0 - Tokenizers: 0.21.0 ## Citations Cite RLOO as: ```bibtex @inproceedings{ahmadian2024back, title = {{Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs}}, author = {Arash Ahmadian and Chris Cremer and Matthias Gall{'{e}} and Marzieh Fadaee and Julia Kreutzer and Olivier Pietquin and Ahmet {"{U}}st{"{u}}n and Sara Hooker}, year = 2024, booktitle = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2024, Bangkok, Thailand, August 11-16, 2024}, publisher = {Association for Computational Linguistics}, pages = {12248--12267}, editor = {Lun{-}Wei Ku and Andre Martins and Vivek Srikumar}, } ``` Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF	itlwas	2025-01-15T16:00:26Z	19	0	transformers	[ "transformers", "gguf", "llama-cpp", "gguf-my-repo", "text-generation", "ko", "dataset:kyujinpy/KOR-OpenOrca-Platypus-v3", "base_model:PracticeLLM/Custom-KoLLM-13B-v1", "base_model:quantized:PracticeLLM/Custom-KoLLM-13B-v1", "license:cc-by-nc-sa-4.0", "endpoints_compatible", "region:us" ]	text-generation	2025-01-15T15:59:53Z	--- language: - ko datasets: - kyujinpy/KOR-OpenOrca-Platypus-v3 library_name: transformers pipeline_tag: text-generation license: cc-by-nc-sa-4.0 tags: - llama-cpp - gguf-my-repo base_model: PracticeLLM/Custom-KoLLM-13B-v1 --- # itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF This model was converted to GGUF format from [`PracticeLLM/Custom-KoLLM-13B-v1`](https://huggingface.co/PracticeLLM/Custom-KoLLM-13B-v1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/PracticeLLM/Custom-KoLLM-13B-v1) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -c 2048 ```
ivangrapher/f067d804-cf60-45c6-8409-593a1c2e69c0	ivangrapher	2025-01-15T16:00:17Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-0.5B-Instruct", "base_model:adapter:unsloth/Qwen2-0.5B-Instruct", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:56:57Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-0.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: f067d804-cf60-45c6-8409-593a1c2e69c0 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-0.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - cb0c735aa9ecc20c_train_data.json ds_type: json format: custom path: /workspace/input_data/cb0c735aa9ecc20c_train_data.json type: field_input: init_response field_instruction: critic_prompt field_output: revision_response format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 8 gradient_checkpointing: false group_by_length: false hub_model_id: ivangrapher/f067d804-cf60-45c6-8409-593a1c2e69c0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 70GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/cb0c735aa9ecc20c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 53e19756-9979-4666-a32e-c3622fab4ea4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 53e19756-9979-4666-a32e-c3622fab4ea4 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # f067d804-cf60-45c6-8409-593a1c2e69c0 This model is a fine-tuned version of [unsloth/Qwen2-0.5B-Instruct](https://huggingface.co/unsloth/Qwen2-0.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0008 \| 1 \| nan \| \| 0.0 \| 0.0060 \| 8 \| nan \| \| 0.0 \| 0.0121 \| 16 \| nan \| \| 0.0 \| 0.0181 \| 24 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhoxinh/1d537965-820c-4214-8f76-78946dc4e7c2	nhoxinh	2025-01-15T15:57:48Z	9	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:42:56Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 1d537965-820c-4214-8f76-78946dc4e7c2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhoxinh/1d537965-820c-4214-8f76-78946dc4e7c2 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 1d537965-820c-4214-8f76-78946dc4e7c2 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0409 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.081 \| 0.0376 \| 200 \| 0.0409 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Patnev71/floorplanv3	Patnev71	2025-01-15T15:57:47Z	5	0	transformers	[ "transformers", "safetensors", "segformer", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2025-01-15T15:57:45Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. 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bbytxt/d94c1346-5615-4f88-b572-e185e31c489a	bbytxt	2025-01-15T15:57:38Z	10	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Mistral-7b-64k", "base_model:adapter:NousResearch/Yarn-Mistral-7b-64k", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:04:40Z	--- library_name: peft license: apache-2.0 base_model: NousResearch/Yarn-Mistral-7b-64k tags: - axolotl - generated_from_trainer model-index: - name: d94c1346-5615-4f88-b572-e185e31c489a results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Mistral-7b-64k bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - 7708f8a044b2986d_train_data.json ds_type: json format: custom path: /workspace/input_data/7708f8a044b2986d_train_data.json type: field_instruction: prompt field_output: chosen format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/d94c1346-5615-4f88-b572-e185e31c489a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/7708f8a044b2986d_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 0a956f4b-2530-421e-9d67-9975bdd289dc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 0a956f4b-2530-421e-9d67-9975bdd289dc warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details><br> # d94c1346-5615-4f88-b572-e185e31c489a This model is a fine-tuned version of [NousResearch/Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3177 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 8.4345 \| 0.0008 \| 1 \| 2.2083 \| \| 2.7382 \| 0.0377 \| 50 \| 1.6734 \| \| 1.6323 \| 0.0754 \| 100 \| 1.5817 \| \| 2.5445 \| 0.1132 \| 150 \| 1.4006 \| \| 1.7847 \| 0.1509 \| 200 \| 1.3177 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso10/7f7eaa0f-17d1-424f-922a-7f1286dfe318	lesso10	2025-01-15T15:56:07Z	13	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:42:41Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 7f7eaa0f-17d1-424f-922a-7f1286dfe318 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: true chat_template: llama3 datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso10/7f7eaa0f-17d1-424f-922a-7f1286dfe318 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 7f7eaa0f-17d1-424f-922a-7f1286dfe318 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0002 \| 1 \| nan \| \| 0.0 \| 0.0009 \| 5 \| nan \| \| 0.0 \| 0.0019 \| 10 \| nan \| \| 0.0 \| 0.0028 \| 15 \| nan \| \| 0.0 \| 0.0038 \| 20 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nadejdatarabukina/fffd188d-8ff3-46b8-a154-566ea0e51a69	nadejdatarabukina	2025-01-15T15:50:51Z	16	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:42:45Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: fffd188d-8ff3-46b8-a154-566ea0e51a69 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 6 gradient_checkpointing: false group_by_length: false hub_model_id: nadejdatarabukina/fffd188d-8ff3-46b8-a154-566ea0e51a69 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # fffd188d-8ff3-46b8-a154-566ea0e51a69 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 6 - total_train_batch_size: 12 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0003 \| 1 \| nan \| \| 0.0 \| 0.0023 \| 8 \| nan \| \| 0.0 \| 0.0045 \| 16 \| nan \| \| 0.0 \| 0.0068 \| 24 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
VerbACxSS/sempl-it-gpt2-small-italian	VerbACxSS	2025-01-15T15:50:42Z	48	0	transformers	[ "transformers", "safetensors", "gpt2", "text-generation", "legal", "it", "base_model:GroNLP/gpt2-small-italian", "base_model:finetune:GroNLP/gpt2-small-italian", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-12-27T08:58:19Z	--- license: mit language: - it base_model: - GroNLP/gpt2-small-italian pipeline_tag: text-generation tags: - legal library_name: transformers --- ## Usage ``` from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian", model_max_length=1024) model = AutoModelForCausalLM.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian") model.eval() text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva' prompt = f'### [Input]:\n{text_to_simplify}\n\n###[Output]:\n' x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids y = model.generate(x, max_length=1024)[0] y_dec = tokenizer.decode(y, max_length=1024, truncation=True) output = y_dec.split('###[Output]:\n')[1].split('<\|endoftext\|>')[0].strip() print(output) ``` ## Acknowledgements This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) "VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility" (Prot. 2020BJKB9M), funded by the Italian Ministero dell'Università e della Ricerca.
dimasik2987/3c9903ab-f11a-4346-b33b-53331b56f77d	dimasik2987	2025-01-15T15:50:29Z	12	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:42:50Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 3c9903ab-f11a-4346-b33b-53331b56f77d results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik2987/3c9903ab-f11a-4346-b33b-53331b56f77d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 3c9903ab-f11a-4346-b33b-53331b56f77d This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0002 \| 1 \| nan \| \| 0.0 \| 0.0009 \| 5 \| nan \| \| 0.0 \| 0.0019 \| 10 \| nan \| \| 0.0 \| 0.0028 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
VerbACxSS/sempl-it-mt5-small	VerbACxSS	2025-01-15T15:50:21Z	68	0	transformers	[ "transformers", "safetensors", "mt5", "text2text-generation", "legal", "it", "base_model:google/mt5-small", "base_model:finetune:google/mt5-small", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2024-12-27T08:58:49Z	--- license: mit language: - it base_model: - google/mt5-small pipeline_tag: text2text-generation tags: - legal library_name: transformers --- ## Usage ``` from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-mt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("VerbACxSS/sempl-it-mt5-small") model.eval() text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva' prompt = f'semplifica: {text_to_simplify}' x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids y = model.generate(x, max_length=1024)[0] output = tokenizer.decode(y, max_length=1024, truncation=True, skip_special_tokens=True, clean_up_tokenization_spaces=True) print(output) ``` ## Acknowledgements This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) "VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility" (Prot. 2020BJKB9M), funded by the Italian Ministero dell'Università e della Ricerca.
laquythang/49668481-8ea3-4632-b312-cd2956370777	laquythang	2025-01-15T15:50:05Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:32:51Z	--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 49668481-8ea3-4632-b312-cd2956370777 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: laquythang/49668481-8ea3-4632-b312-cd2956370777 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 49668481-8ea3-4632-b312-cd2956370777 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0637 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.8976 \| 0.7073 \| 200 \| 1.0637 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
aurelvu/bert-bibtex-classifier	aurelvu	2025-01-15T15:49:15Z	171	0	transformers	[ "transformers", "tensorboard", "safetensors", "bert", "token-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-multilingual-cased", "base_model:finetune:distilbert/distilbert-base-multilingual-cased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	token-classification	2025-01-12T22:59:50Z	--- library_name: transformers license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer model-index: - name: tmp_trainer results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # tmp_trainer This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3.0 ### Training results ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
nhung01/73decf8f-573c-4ede-a607-775c7da77ed4	nhung01	2025-01-15T15:48:40Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:32:43Z	--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 73decf8f-573c-4ede-a607-775c7da77ed4 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/73decf8f-573c-4ede-a607-775c7da77ed4 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 73decf8f-573c-4ede-a607-775c7da77ed4 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0612 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.8979 \| 0.7073 \| 200 \| 1.0612 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization	MayBashendy	2025-01-15T15:46:25Z	7	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T15:28:55Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3764 - Qwk: 0.4593 - Mse: 1.3764 - Rmse: 1.1732 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0286 \| 2 \| 6.8337 \| 0.0242 \| 6.8337 \| 2.6141 \| \| No log \| 0.0571 \| 4 \| 4.4891 \| 0.0928 \| 4.4891 \| 2.1187 \| \| No log \| 0.0857 \| 6 \| 3.6095 \| -0.0417 \| 3.6095 \| 1.8999 \| \| No log \| 0.1143 \| 8 \| 2.6066 \| 0.0805 \| 2.6066 \| 1.6145 \| \| No log \| 0.1429 \| 10 \| 2.3240 \| 0.0833 \| 2.3240 \| 1.5245 \| \| No log \| 0.1714 \| 12 \| 2.4556 \| 0.0946 \| 2.4556 \| 1.5670 \| \| No log \| 0.2 \| 14 \| 2.0410 \| 0.0960 \| 2.0410 \| 1.4286 \| \| No log \| 0.2286 \| 16 \| 1.8799 \| 0.2931 \| 1.8799 \| 1.3711 \| \| No log \| 0.2571 \| 18 \| 1.7234 \| 0.2957 \| 1.7234 \| 1.3128 \| \| No log \| 0.2857 \| 20 \| 1.5811 \| 0.3036 \| 1.5811 \| 1.2574 \| \| No log \| 0.3143 \| 22 \| 1.4460 \| 0.1869 \| 1.4460 \| 1.2025 \| \| No log \| 0.3429 \| 24 \| 1.5540 \| 0.1321 \| 1.5540 \| 1.2466 \| \| No log \| 0.3714 \| 26 \| 1.4213 \| 0.2222 \| 1.4213 \| 1.1922 \| \| No log \| 0.4 \| 28 \| 1.5136 \| 0.3193 \| 1.5136 \| 1.2303 \| \| No log \| 0.4286 \| 30 \| 1.9478 \| 0.2105 \| 1.9478 \| 1.3956 \| \| No log \| 0.4571 \| 32 \| 2.0764 \| 0.2014 \| 2.0764 \| 1.4410 \| \| No log \| 0.4857 \| 34 \| 1.5700 \| 0.3281 \| 1.5700 \| 1.2530 \| \| No log \| 0.5143 \| 36 \| 1.2381 \| 0.3826 \| 1.2381 \| 1.1127 \| \| No log \| 0.5429 \| 38 \| 1.2643 \| 0.3423 \| 1.2643 \| 1.1244 \| \| No log \| 0.5714 \| 40 \| 1.2574 \| 0.4068 \| 1.2574 \| 1.1213 \| \| No log \| 0.6 \| 42 \| 1.2750 \| 0.4298 \| 1.2750 \| 1.1291 \| \| No log \| 0.6286 \| 44 \| 1.6089 \| 0.3220 \| 1.6089 \| 1.2684 \| \| No log \| 0.6571 \| 46 \| 1.6026 \| 0.3636 \| 1.6026 \| 1.2659 \| \| No log \| 0.6857 \| 48 \| 1.0863 \| 0.5156 \| 1.0863 \| 1.0423 \| \| No log \| 0.7143 \| 50 \| 0.9043 \| 0.6809 \| 0.9043 \| 0.9509 \| \| No log \| 0.7429 \| 52 \| 1.0416 \| 0.5538 \| 1.0416 \| 1.0206 \| \| No log \| 0.7714 \| 54 \| 1.5162 \| 0.3200 \| 1.5162 \| 1.2313 \| \| No log \| 0.8 \| 56 \| 1.3478 \| 0.4580 \| 1.3478 \| 1.1610 \| \| No log \| 0.8286 \| 58 \| 0.9924 \| 0.6269 \| 0.9924 \| 0.9962 \| \| No log \| 0.8571 \| 60 \| 0.9594 \| 0.6763 \| 0.9594 \| 0.9795 \| \| No log \| 0.8857 \| 62 \| 1.1393 \| 0.5481 \| 1.1393 \| 1.0674 \| \| No log \| 0.9143 \| 64 \| 1.1885 \| 0.5255 \| 1.1885 \| 1.0902 \| \| No log \| 0.9429 \| 66 \| 1.0726 \| 0.6222 \| 1.0726 \| 1.0357 \| \| No log \| 0.9714 \| 68 \| 1.0284 \| 0.5649 \| 1.0284 \| 1.0141 \| \| No log \| 1.0 \| 70 \| 1.0905 \| 0.6324 \| 1.0905 \| 1.0443 \| \| No log \| 1.0286 \| 72 \| 1.0872 \| 0.6131 \| 1.0872 \| 1.0427 \| \| No log \| 1.0571 \| 74 \| 1.1639 \| 0.5493 \| 1.1639 \| 1.0788 \| \| No log \| 1.0857 \| 76 \| 1.4816 \| 0.4965 \| 1.4816 \| 1.2172 \| \| No log \| 1.1143 \| 78 \| 1.4626 \| 0.5143 \| 1.4626 \| 1.2094 \| \| No log \| 1.1429 \| 80 \| 1.4851 \| 0.5180 \| 1.4851 \| 1.2186 \| \| No log \| 1.1714 \| 82 \| 1.3317 \| 0.4889 \| 1.3317 \| 1.1540 \| \| No log \| 1.2 \| 84 \| 1.2976 \| 0.4062 \| 1.2976 \| 1.1391 \| \| No log \| 1.2286 \| 86 \| 1.4304 \| 0.4032 \| 1.4304 \| 1.1960 \| \| No log \| 1.2571 \| 88 \| 1.7350 \| 0.3333 \| 1.7350 \| 1.3172 \| \| No log \| 1.2857 \| 90 \| 1.8839 \| 0.2880 \| 1.8839 \| 1.3725 \| \| No log \| 1.3143 \| 92 \| 1.8076 \| 0.2326 \| 1.8076 \| 1.3445 \| \| No log \| 1.3429 \| 94 \| 1.2636 \| 0.5109 \| 1.2636 \| 1.1241 \| \| No log \| 1.3714 \| 96 \| 1.0193 \| 0.5857 \| 1.0193 \| 1.0096 \| \| No log \| 1.4 \| 98 \| 1.2112 \| 0.5674 \| 1.2112 \| 1.1005 \| \| No log \| 1.4286 \| 100 \| 1.5935 \| 0.4113 \| 1.5935 \| 1.2623 \| \| No log \| 1.4571 \| 102 \| 1.3159 \| 0.5217 \| 1.3159 \| 1.1471 \| \| No log \| 1.4857 \| 104 \| 0.8062 \| 0.7050 \| 0.8062 \| 0.8979 \| \| No log \| 1.5143 \| 106 \| 0.7865 \| 0.7391 \| 0.7865 \| 0.8869 \| \| No log \| 1.5429 \| 108 \| 0.9035 \| 0.6418 \| 0.9035 \| 0.9505 \| \| No log \| 1.5714 \| 110 \| 1.2976 \| 0.4964 \| 1.2976 \| 1.1391 \| \| No log \| 1.6 \| 112 \| 1.3322 \| 0.4964 \| 1.3322 \| 1.1542 \| \| No log \| 1.6286 \| 114 \| 1.0269 \| 0.6074 \| 1.0269 \| 1.0134 \| \| No log \| 1.6571 \| 116 \| 0.8800 \| 0.6377 \| 0.8800 \| 0.9381 \| \| No log \| 1.6857 \| 118 \| 0.9260 \| 0.6331 \| 0.9260 \| 0.9623 \| \| No log \| 1.7143 \| 120 \| 1.1650 \| 0.5315 \| 1.1650 \| 1.0794 \| \| No log \| 1.7429 \| 122 \| 1.4832 \| 0.4895 \| 1.4832 \| 1.2179 \| \| No log \| 1.7714 \| 124 \| 1.4908 \| 0.4615 \| 1.4908 \| 1.2210 \| \| No log \| 1.8 \| 126 \| 1.4700 \| 0.4476 \| 1.4700 \| 1.2124 \| \| No log \| 1.8286 \| 128 \| 1.2040 \| 0.5468 \| 1.2040 \| 1.0972 \| \| No log \| 1.8571 \| 130 \| 1.0580 \| 0.6615 \| 1.0580 \| 1.0286 \| \| No log \| 1.8857 \| 132 \| 1.0125 \| 0.4959 \| 1.0125 \| 1.0062 \| \| No log \| 1.9143 \| 134 \| 1.0953 \| 0.6299 \| 1.0953 \| 1.0466 \| \| No log \| 1.9429 \| 136 \| 1.3044 \| 0.5075 \| 1.3044 \| 1.1421 \| \| No log \| 1.9714 \| 138 \| 1.4761 \| 0.4265 \| 1.4761 \| 1.2150 \| \| No log \| 2.0 \| 140 \| 1.4946 \| 0.4265 \| 1.4946 \| 1.2225 \| \| No log \| 2.0286 \| 142 \| 1.3233 \| 0.5263 \| 1.3233 \| 1.1504 \| \| No log \| 2.0571 \| 144 \| 1.2769 \| 0.5926 \| 1.2769 \| 1.1300 \| \| No log \| 2.0857 \| 146 \| 1.5574 \| 0.3942 \| 1.5574 \| 1.2480 \| \| No log \| 2.1143 \| 148 \| 1.7650 \| 0.2222 \| 1.7650 \| 1.3285 \| \| No log \| 2.1429 \| 150 \| 1.6343 \| 0.3333 \| 1.6343 \| 1.2784 \| \| No log \| 2.1714 \| 152 \| 1.4845 \| 0.3971 \| 1.4845 \| 1.2184 \| \| No log \| 2.2 \| 154 \| 1.2324 \| 0.5152 \| 1.2324 \| 1.1101 \| \| No log \| 2.2286 \| 156 \| 1.0931 \| 0.5938 \| 1.0931 \| 1.0455 \| \| No log \| 2.2571 \| 158 \| 1.0929 \| 0.5645 \| 1.0929 \| 1.0454 \| \| No log \| 2.2857 \| 160 \| 1.2566 \| 0.4812 \| 1.2566 \| 1.1210 \| \| No log \| 2.3143 \| 162 \| 1.2894 \| 0.4812 \| 1.2894 \| 1.1355 \| \| No log \| 2.3429 \| 164 \| 1.2423 \| 0.5075 \| 1.2423 \| 1.1146 \| \| No log \| 2.3714 \| 166 \| 1.1305 \| 0.5758 \| 1.1305 \| 1.0633 \| \| No log \| 2.4 \| 168 \| 0.9736 \| 0.6471 \| 0.9736 \| 0.9867 \| \| No log \| 2.4286 \| 170 \| 0.9289 \| 0.6567 \| 0.9289 \| 0.9638 \| \| No log \| 2.4571 \| 172 \| 1.0946 \| 0.6232 \| 1.0946 \| 1.0462 \| \| No log \| 2.4857 \| 174 \| 1.4287 \| 0.4593 \| 1.4287 \| 1.1953 \| \| No log \| 2.5143 \| 176 \| 1.3580 \| 0.4706 \| 1.3580 \| 1.1653 \| \| No log \| 2.5429 \| 178 \| 1.0219 \| 0.6232 \| 1.0219 \| 1.0109 \| \| No log \| 2.5714 \| 180 \| 0.9143 \| 0.6277 \| 0.9143 \| 0.9562 \| \| No log \| 2.6 \| 182 \| 0.9552 \| 0.6232 \| 0.9552 \| 0.9773 \| \| No log \| 2.6286 \| 184 \| 1.0716 \| 0.5857 \| 1.0716 \| 1.0352 \| \| No log \| 2.6571 \| 186 \| 0.9842 \| 0.6232 \| 0.9842 \| 0.9921 \| \| No log \| 2.6857 \| 188 \| 0.8826 \| 0.6471 \| 0.8826 \| 0.9395 \| \| No log \| 2.7143 \| 190 \| 1.0422 \| 0.6176 \| 1.0422 \| 1.0209 \| \| No log \| 2.7429 \| 192 \| 1.2937 \| 0.4889 \| 1.2937 \| 1.1374 \| \| No log \| 2.7714 \| 194 \| 1.3087 \| 0.4889 \| 1.3087 \| 1.1440 \| \| No log \| 2.8 \| 196 \| 1.0811 \| 0.6087 \| 1.0811 \| 1.0398 \| \| No log \| 2.8286 \| 198 \| 0.8948 \| 0.6418 \| 0.8948 \| 0.9459 \| \| No log \| 2.8571 \| 200 \| 0.9906 \| 0.6187 \| 0.9906 \| 0.9953 \| \| No log \| 2.8857 \| 202 \| 1.3906 \| 0.4593 \| 1.3906 \| 1.1792 \| \| No log \| 2.9143 \| 204 \| 1.5787 \| 0.3429 \| 1.5787 \| 1.2564 \| \| No log \| 2.9429 \| 206 \| 1.3830 \| 0.4662 \| 1.3830 \| 1.1760 \| \| No log \| 2.9714 \| 208 \| 1.1465 \| 0.5385 \| 1.1465 \| 1.0707 \| \| No log \| 3.0 \| 210 \| 1.0218 \| 0.6129 \| 1.0218 \| 1.0108 \| \| No log \| 3.0286 \| 212 \| 1.0315 \| 0.5246 \| 1.0315 \| 1.0156 \| \| No log \| 3.0571 \| 214 \| 1.1276 \| 0.6032 \| 1.1276 \| 1.0619 \| \| No log \| 3.0857 \| 216 \| 1.4077 \| 0.4320 \| 1.4077 \| 1.1865 \| \| No log \| 3.1143 \| 218 \| 1.5440 \| 0.4531 \| 1.5440 \| 1.2426 \| \| No log \| 3.1429 \| 220 \| 1.5291 \| 0.4531 \| 1.5291 \| 1.2365 \| \| No log \| 3.1714 \| 222 \| 1.3984 \| 0.5039 \| 1.3984 \| 1.1825 \| \| No log \| 3.2 \| 224 \| 1.4500 \| 0.4341 \| 1.4500 \| 1.2041 \| \| No log \| 3.2286 \| 226 \| 1.6216 \| 0.2923 \| 1.6216 \| 1.2734 \| \| No log \| 3.2571 \| 228 \| 1.5246 \| 0.3556 \| 1.5246 \| 1.2347 \| \| No log \| 3.2857 \| 230 \| 1.3671 \| 0.4783 \| 1.3671 \| 1.1692 \| \| No log \| 3.3143 \| 232 \| 1.4404 \| 0.4265 \| 1.4404 \| 1.2001 \| \| No log \| 3.3429 \| 234 \| 1.7448 \| 0.2609 \| 1.7448 \| 1.3209 \| \| No log \| 3.3714 \| 236 \| 1.8269 \| 0.2774 \| 1.8269 \| 1.3516 \| \| No log \| 3.4 \| 238 \| 1.5437 \| 0.3582 \| 1.5437 \| 1.2425 \| \| No log \| 3.4286 \| 240 \| 1.2087 \| 0.5191 \| 1.2087 \| 1.0994 \| \| No log \| 3.4571 \| 242 \| 1.0510 \| 0.6212 \| 1.0510 \| 1.0252 \| \| No log \| 3.4857 \| 244 \| 1.0694 \| 0.5954 \| 1.0694 \| 1.0341 \| \| No log \| 3.5143 \| 246 \| 1.2784 \| 0.5263 \| 1.2784 \| 1.1307 \| \| No log \| 3.5429 \| 248 \| 1.4112 \| 0.4925 \| 1.4112 \| 1.1879 \| \| No log \| 3.5714 \| 250 \| 1.5436 \| 0.4058 \| 1.5436 \| 1.2424 \| \| No log \| 3.6 \| 252 \| 1.4830 \| 0.4234 \| 1.4830 \| 1.2178 \| \| No log \| 3.6286 \| 254 \| 1.5739 \| 0.3571 \| 1.5739 \| 1.2546 \| \| No log \| 3.6571 \| 256 \| 1.5217 \| 0.4058 \| 1.5217 \| 1.2336 \| \| No log \| 3.6857 \| 258 \| 1.4990 \| 0.4148 \| 1.4990 \| 1.2243 \| \| No log \| 3.7143 \| 260 \| 1.4782 \| 0.4030 \| 1.4782 \| 1.2158 \| \| No log \| 3.7429 \| 262 \| 1.4390 \| 0.4545 \| 1.4390 \| 1.1996 \| \| No log \| 3.7714 \| 264 \| 1.4553 \| 0.4545 \| 1.4553 \| 1.2064 \| \| No log \| 3.8 \| 266 \| 1.3295 \| 0.5191 \| 1.3295 \| 1.1531 \| \| No log \| 3.8286 \| 268 \| 1.2024 \| 0.5564 \| 1.2024 \| 1.0965 \| \| No log \| 3.8571 \| 270 \| 1.1636 \| 0.5735 \| 1.1636 \| 1.0787 \| \| No log \| 3.8857 \| 272 \| 1.2539 \| 0.5 \| 1.2539 \| 1.1198 \| \| No log \| 3.9143 \| 274 \| 1.3901 \| 0.4559 \| 1.3901 \| 1.1790 \| \| No log \| 3.9429 \| 276 \| 1.3526 \| 0.4818 \| 1.3526 \| 1.1630 \| \| No log \| 3.9714 \| 278 \| 1.4592 \| 0.4511 \| 1.4592 \| 1.2080 \| \| No log \| 4.0 \| 280 \| 1.8012 \| 0.2774 \| 1.8012 \| 1.3421 \| \| No log \| 4.0286 \| 282 \| 2.0166 \| 0.2014 \| 2.0166 \| 1.4201 \| \| No log \| 4.0571 \| 284 \| 1.7866 \| 0.3066 \| 1.7866 \| 1.3366 \| \| No log \| 4.0857 \| 286 \| 1.3599 \| 0.4627 \| 1.3599 \| 1.1662 \| \| No log \| 4.1143 \| 288 \| 1.0635 \| 0.5865 \| 1.0635 \| 1.0313 \| \| No log \| 4.1429 \| 290 \| 1.0123 \| 0.6119 \| 1.0123 \| 1.0061 \| \| No log \| 4.1714 \| 292 \| 1.1615 \| 0.5693 \| 1.1615 \| 1.0777 \| \| No log \| 4.2 \| 294 \| 1.3948 \| 0.4593 \| 1.3948 \| 1.1810 \| \| No log \| 4.2286 \| 296 \| 1.3104 \| 0.4889 \| 1.3104 \| 1.1447 \| \| No log \| 4.2571 \| 298 \| 1.0651 \| 0.5778 \| 1.0651 \| 1.0320 \| \| No log \| 4.2857 \| 300 \| 0.9699 \| 0.6519 \| 0.9699 \| 0.9849 \| \| No log \| 4.3143 \| 302 \| 1.0309 \| 0.6176 \| 1.0309 \| 1.0153 \| \| No log \| 4.3429 \| 304 \| 1.3110 \| 0.4706 \| 1.3110 \| 1.1450 \| \| No log \| 4.3714 \| 306 \| 1.7069 \| 0.3478 \| 1.7069 \| 1.3065 \| \| No log \| 4.4 \| 308 \| 1.7723 \| 0.2899 \| 1.7723 \| 1.3313 \| \| No log \| 4.4286 \| 310 \| 1.5822 \| 0.4088 \| 1.5822 \| 1.2578 \| \| No log \| 4.4571 \| 312 \| 1.3861 \| 0.5 \| 1.3861 \| 1.1773 \| \| No log \| 4.4857 \| 314 \| 1.3641 \| 0.5 \| 1.3641 \| 1.1679 \| \| No log \| 4.5143 \| 316 \| 1.4717 \| 0.4203 \| 1.4717 \| 1.2131 \| \| No log \| 4.5429 \| 318 \| 1.6087 \| 0.3768 \| 1.6087 \| 1.2683 \| \| No log \| 4.5714 \| 320 \| 1.6747 \| 0.3453 \| 1.6747 \| 1.2941 \| \| No log \| 4.6 \| 322 \| 1.5752 \| 0.3942 \| 1.5752 \| 1.2551 \| \| No log \| 4.6286 \| 324 \| 1.4327 \| 0.4203 \| 1.4327 \| 1.1970 \| \| No log \| 4.6571 \| 326 \| 1.2610 \| 0.5496 \| 1.2610 \| 1.1230 \| \| No log \| 4.6857 \| 328 \| 1.1840 \| 0.5758 \| 1.1840 \| 1.0881 \| \| No log \| 4.7143 \| 330 \| 1.2157 \| 0.5496 \| 1.2157 \| 1.1026 \| \| No log \| 4.7429 \| 332 \| 1.3424 \| 0.5075 \| 1.3424 \| 1.1586 \| \| No log \| 4.7714 \| 334 \| 1.5371 \| 0.3407 \| 1.5371 \| 1.2398 \| \| No log \| 4.8 \| 336 \| 1.6706 \| 0.2878 \| 1.6706 \| 1.2925 \| \| No log \| 4.8286 \| 338 \| 1.6747 \| 0.2714 \| 1.6747 \| 1.2941 \| \| No log \| 4.8571 \| 340 \| 1.5275 \| 0.3731 \| 1.5275 \| 1.2359 \| \| No log \| 4.8857 \| 342 \| 1.3610 \| 0.5414 \| 1.3610 \| 1.1666 \| \| No log \| 4.9143 \| 344 \| 1.3677 \| 0.5075 \| 1.3677 \| 1.1695 \| \| No log \| 4.9429 \| 346 \| 1.4244 \| 0.4889 \| 1.4244 \| 1.1935 \| \| No log \| 4.9714 \| 348 \| 1.4352 \| 0.4380 \| 1.4352 \| 1.1980 \| \| No log \| 5.0 \| 350 \| 1.4374 \| 0.4380 \| 1.4374 \| 1.1989 \| \| No log \| 5.0286 \| 352 \| 1.2030 \| 0.5333 \| 1.2030 \| 1.0968 \| \| No log \| 5.0571 \| 354 \| 1.1369 \| 0.5821 \| 1.1369 \| 1.0662 \| \| No log \| 5.0857 \| 356 \| 1.2578 \| 0.5333 \| 1.2578 \| 1.1215 \| \| No log \| 5.1143 \| 358 \| 1.5682 \| 0.3623 \| 1.5682 \| 1.2523 \| \| No log \| 5.1429 \| 360 \| 1.7093 \| 0.3212 \| 1.7093 \| 1.3074 \| \| No log \| 5.1714 \| 362 \| 1.6142 \| 0.3286 \| 1.6142 \| 1.2705 \| \| No log \| 5.2 \| 364 \| 1.4060 \| 0.4706 \| 1.4060 \| 1.1858 \| \| No log \| 5.2286 \| 366 \| 1.2391 \| 0.5414 \| 1.2391 \| 1.1131 \| \| No log \| 5.2571 \| 368 \| 1.1590 \| 0.5426 \| 1.1590 \| 1.0766 \| \| No log \| 5.2857 \| 370 \| 1.1743 \| 0.5426 \| 1.1743 \| 1.0837 \| \| No log \| 5.3143 \| 372 \| 1.1697 \| 0.5692 \| 1.1697 \| 1.0815 \| \| No log \| 5.3429 \| 374 \| 1.2521 \| 0.5714 \| 1.2521 \| 1.1190 \| \| No log \| 5.3714 \| 376 \| 1.4472 \| 0.4706 \| 1.4472 \| 1.2030 \| \| No log \| 5.4 \| 378 \| 1.4903 \| 0.4706 \| 1.4903 \| 1.2208 \| \| No log \| 5.4286 \| 380 \| 1.4069 \| 0.4706 \| 1.4069 \| 1.1861 \| \| No log \| 5.4571 \| 382 \| 1.3369 \| 0.5075 \| 1.3369 \| 1.1563 \| \| No log \| 5.4857 \| 384 \| 1.3297 \| 0.5075 \| 1.3297 \| 1.1531 \| \| No log \| 5.5143 \| 386 \| 1.2427 \| 0.5455 \| 1.2427 \| 1.1148 \| \| No log \| 5.5429 \| 388 \| 1.0827 \| 0.5649 \| 1.0827 \| 1.0405 \| \| No log \| 5.5714 \| 390 \| 0.9922 \| 0.5692 \| 0.9922 \| 0.9961 \| \| No log \| 5.6 \| 392 \| 0.9703 \| 0.6015 \| 0.9703 \| 0.9851 \| \| No log \| 5.6286 \| 394 \| 1.0948 \| 0.5821 \| 1.0948 \| 1.0463 \| \| No log \| 5.6571 \| 396 \| 1.3265 \| 0.5147 \| 1.3265 \| 1.1517 \| \| No log \| 5.6857 \| 398 \| 1.3873 \| 0.4889 \| 1.3873 \| 1.1778 \| \| No log \| 5.7143 \| 400 \| 1.2730 \| 0.5373 \| 1.2730 \| 1.1283 \| \| No log \| 5.7429 \| 402 \| 1.2221 \| 0.5481 \| 1.2221 \| 1.1055 \| \| No log \| 5.7714 \| 404 \| 1.1536 \| 0.5649 \| 1.1536 \| 1.0741 \| \| No log \| 5.8 \| 406 \| 1.1435 \| 0.6015 \| 1.1435 \| 1.0694 \| \| No log \| 5.8286 \| 408 \| 1.0895 \| 0.6 \| 1.0895 \| 1.0438 \| \| No log \| 5.8571 \| 410 \| 1.1584 \| 0.5891 \| 1.1584 \| 1.0763 \| \| No log \| 5.8857 \| 412 \| 1.2302 \| 0.5846 \| 1.2302 \| 1.1091 \| \| No log \| 5.9143 \| 414 \| 1.2604 \| 0.5606 \| 1.2604 \| 1.1227 \| \| No log \| 5.9429 \| 416 \| 1.2379 \| 0.5714 \| 1.2379 \| 1.1126 \| \| No log \| 5.9714 \| 418 \| 1.0615 \| 0.5649 \| 1.0615 \| 1.0303 \| \| No log \| 6.0 \| 420 \| 0.9040 \| 0.6015 \| 0.9040 \| 0.9508 \| \| No log \| 6.0286 \| 422 \| 0.8775 \| 0.5970 \| 0.8775 \| 0.9367 \| \| No log \| 6.0571 \| 424 \| 1.0238 \| 0.5714 \| 1.0238 \| 1.0118 \| \| No log \| 6.0857 \| 426 \| 1.2761 \| 0.4889 \| 1.2761 \| 1.1297 \| \| No log \| 6.1143 \| 428 \| 1.3554 \| 0.5072 \| 1.3554 \| 1.1642 \| \| No log \| 6.1429 \| 430 \| 1.2540 \| 0.4885 \| 1.2540 \| 1.1198 \| \| No log \| 6.1714 \| 432 \| 1.0339 \| 0.5231 \| 1.0339 \| 1.0168 \| \| No log \| 6.2 \| 434 \| 0.9861 \| 0.5736 \| 0.9861 \| 0.9930 \| \| No log \| 6.2286 \| 436 \| 1.1010 \| 0.5385 \| 1.1010 \| 1.0493 \| \| No log \| 6.2571 \| 438 \| 1.2149 \| 0.5455 \| 1.2149 \| 1.1022 \| \| No log \| 6.2857 \| 440 \| 1.3697 \| 0.5077 \| 1.3697 \| 1.1703 \| \| No log \| 6.3143 \| 442 \| 1.3210 \| 0.5970 \| 1.3210 \| 1.1494 \| \| No log \| 6.3429 \| 444 \| 1.2623 \| 0.5985 \| 1.2623 \| 1.1235 \| \| No log \| 6.3714 \| 446 \| 1.2335 \| 0.5821 \| 1.2335 \| 1.1106 \| \| No log \| 6.4 \| 448 \| 1.2572 \| 0.5564 \| 1.2572 \| 1.1213 \| \| No log \| 6.4286 \| 450 \| 1.2073 \| 0.5564 \| 1.2073 \| 1.0988 \| \| No log \| 6.4571 \| 452 \| 1.1963 \| 0.5303 \| 1.1963 \| 1.0938 \| \| No log \| 6.4857 \| 454 \| 1.2310 \| 0.5564 \| 1.2310 \| 1.1095 \| \| No log \| 6.5143 \| 456 \| 1.2620 \| 0.5778 \| 1.2620 \| 1.1234 \| \| No log \| 6.5429 \| 458 \| 1.2205 \| 0.5714 \| 1.2205 \| 1.1048 \| \| No log \| 6.5714 \| 460 \| 1.1813 \| 0.5758 \| 1.1813 \| 1.0869 \| \| No log \| 6.6 \| 462 \| 1.1858 \| 0.5758 \| 1.1858 \| 1.0890 \| \| No log \| 6.6286 \| 464 \| 1.2509 \| 0.5758 \| 1.2509 \| 1.1184 \| \| No log \| 6.6571 \| 466 \| 1.3665 \| 0.4593 \| 1.3665 \| 1.1690 \| \| No log \| 6.6857 \| 468 \| 1.3494 \| 0.4706 \| 1.3494 \| 1.1616 \| \| No log \| 6.7143 \| 470 \| 1.3706 \| 0.4818 \| 1.3706 \| 1.1707 \| \| No log \| 6.7429 \| 472 \| 1.2916 \| 0.5072 \| 1.2916 \| 1.1365 \| \| No log \| 6.7714 \| 474 \| 1.1484 \| 0.5985 \| 1.1484 \| 1.0716 \| \| No log \| 6.8 \| 476 \| 1.1952 \| 0.5985 \| 1.1952 \| 1.0932 \| \| No log \| 6.8286 \| 478 \| 1.2637 \| 0.5441 \| 1.2637 \| 1.1241 \| \| No log \| 6.8571 \| 480 \| 1.2950 \| 0.5441 \| 1.2950 \| 1.1380 \| \| No log \| 6.8857 \| 482 \| 1.2568 \| 0.5778 \| 1.2568 \| 1.1211 \| \| No log \| 6.9143 \| 484 \| 1.2612 \| 0.5778 \| 1.2612 \| 1.1230 \| \| No log \| 6.9429 \| 486 \| 1.1672 \| 0.5821 \| 1.1672 \| 1.0804 \| \| No log \| 6.9714 \| 488 \| 1.1548 \| 0.5649 \| 1.1548 \| 1.0746 \| \| No log \| 7.0 \| 490 \| 1.2945 \| 0.5522 \| 1.2945 \| 1.1378 \| \| No log \| 7.0286 \| 492 \| 1.4219 \| 0.4812 \| 1.4219 \| 1.1924 \| \| No log \| 7.0571 \| 494 \| 1.3554 \| 0.5152 \| 1.3554 \| 1.1642 \| \| No log \| 7.0857 \| 496 \| 1.2111 \| 0.5197 \| 1.2111 \| 1.1005 \| \| No log \| 7.1143 \| 498 \| 1.2144 \| 0.4793 \| 1.2144 \| 1.1020 \| \| 0.3532 \| 7.1429 \| 500 \| 1.2226 \| 0.5323 \| 1.2226 \| 1.1057 \| \| 0.3532 \| 7.1714 \| 502 \| 1.2471 \| 0.5385 \| 1.2471 \| 1.1167 \| \| 0.3532 \| 7.2 \| 504 \| 1.3811 \| 0.4925 \| 1.3811 \| 1.1752 \| \| 0.3532 \| 7.2286 \| 506 \| 1.4908 \| 0.3971 \| 1.4908 \| 1.2210 \| \| 0.3532 \| 7.2571 \| 508 \| 1.4098 \| 0.5 \| 1.4098 \| 1.1874 \| \| 0.3532 \| 7.2857 \| 510 \| 1.3510 \| 0.5 \| 1.3510 \| 1.1623 \| \| 0.3532 \| 7.3143 \| 512 \| 1.3337 \| 0.5373 \| 1.3337 \| 1.1549 \| \| 0.3532 \| 7.3429 \| 514 \| 1.2646 \| 0.5649 \| 1.2646 \| 1.1245 \| \| 0.3532 \| 7.3714 \| 516 \| 1.2132 \| 0.5938 \| 1.2132 \| 1.1015 \| \| 0.3532 \| 7.4 \| 518 \| 1.2061 \| 0.5938 \| 1.2061 \| 1.0982 \| \| 0.3532 \| 7.4286 \| 520 \| 1.2082 \| 0.5649 \| 1.2082 \| 1.0992 \| \| 0.3532 \| 7.4571 \| 522 \| 1.2063 \| 0.5649 \| 1.2063 \| 1.0983 \| \| 0.3532 \| 7.4857 \| 524 \| 1.2944 \| 0.5373 \| 1.2944 \| 1.1377 \| \| 0.3532 \| 7.5143 \| 526 \| 1.3583 \| 0.4672 \| 1.3583 \| 1.1654 \| \| 0.3532 \| 7.5429 \| 528 \| 1.3764 \| 0.4783 \| 1.3764 \| 1.1732 \| \| 0.3532 \| 7.5714 \| 530 \| 1.4234 \| 0.4853 \| 1.4234 \| 1.1931 \| \| 0.3532 \| 7.6 \| 532 \| 1.5196 \| 0.4234 \| 1.5196 \| 1.2327 \| \| 0.3532 \| 7.6286 \| 534 \| 1.3764 \| 0.4593 \| 1.3764 \| 1.1732 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
ClarenceDan/fb4700b3-f04a-48ac-b7f7-8b018fb175ac	ClarenceDan	2025-01-15T15:45:10Z	8	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:20:36Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: fb4700b3-f04a-48ac-b7f7-8b018fb175ac results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/fb4700b3-f04a-48ac-b7f7-8b018fb175ac hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # fb4700b3-f04a-48ac-b7f7-8b018fb175ac This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0001 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 3 \| nan \| \| 0.0 \| 0.0003 \| 6 \| nan \| \| 0.0 \| 0.0005 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Keltezaa/Katie_Thomas_Actress	Keltezaa	2025-01-15T15:44:56Z	39	0	diffusers	[ "diffusers", "text-to-image", "lora", "template:diffusion-lora", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:cc-by-nc-nd-4.0", "region:us" ]	text-to-image	2025-01-15T15:40:47Z	--- tags: - text-to-image - lora - diffusers - template:diffusion-lora widget: - text: >- 35mm photograph of a young woman, (wearing a jacket:1.5),having a coffee in a vintage cafe, smile, professional, atmospheric haze, excellent dynamic range, masterpiece, excellent quality, ultra detailed, subtle lighting, soft focus, detailed shadows output: url: images/example_9nxcl3qpv.png base_model: black-forest-labs/FLUX.1-dev instance_prompt: null license: cc-by-nc-nd-4.0 --- # Katie Thomas Actress <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Keltezaa/Katie_Thomas_Actress/tree/main) them in the Files & versions tab.
Patnev71/floorplanv2	Patnev71	2025-01-15T15:44:45Z	5	0	transformers	[ "transformers", "safetensors", "segformer", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2025-01-15T15:44:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
dzanbek/cc00dfb0-c695-416a-8916-6686f2159be0	dzanbek	2025-01-15T15:44:05Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]	null	2025-01-15T14:15:45Z	--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: cc00dfb0-c695-416a-8916-6686f2159be0 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dzanbek/cc00dfb0-c695-416a-8916-6686f2159be0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # cc00dfb0-c695-416a-8916-6686f2159be0 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0005 \| 10 \| nan \| \| 0.0 \| 0.0007 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
kk-aivio/fe65bf08-5d51-4a1f-a7a4-29850ba83120	kk-aivio	2025-01-15T15:42:14Z	10	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "region:us" ]	null	2025-01-15T15:12:58Z	--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: fe65bf08-5d51-4a1f-a7a4-29850ba83120 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kk-aivio/fe65bf08-5d51-4a1f-a7a4-29850ba83120 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <\|eot_id\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: birthday-sn56-17-Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # fe65bf08-5d51-4a1f-a7a4-29850ba83120 This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8674 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 2.145 \| 0.0001 \| 1 \| 2.5498 \| \| 2.7495 \| 0.0002 \| 3 \| 2.5397 \| \| 1.9831 \| 0.0003 \| 6 \| 2.3370 \| \| 2.0553 \| 0.0005 \| 9 \| 1.8674 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF	itlwas	2025-01-15T15:42:05Z	25	0	transformers	[ "transformers", "gguf", "ROC", "Taiwan", "zh-tw", "llama-factory", "llama-cpp", "gguf-my-repo", "text-generation", "zh", "en", "dataset:lianghsun/tw-novel-1.1B", "dataset:lianghsun/tw-finance-159M", "dataset:lianghsun/tw-legal-news-24M", "dataset:lianghsun/tw-gov-news-90M", "dataset:lianghsun/tw-gov-556k", "dataset:lianghsun/tw-news-551M", "dataset:lianghsun/tw-health-43M", "dataset:lianghsun/tw-science-24M", "dataset:lianghsun/tw-book-43M", "dataset:lianghsun/tw-society-88M", "dataset:lianghsun/tw-law-article-evolution", "dataset:lianghsun/tw-processed-judgments", "dataset:lianghsun/tw-legal-methodology", "dataset:lianghsun/tw-legal-qa", "dataset:lianghsun/tw-judgment-gist", "dataset:lianghsun/reasoning-base-20k", "dataset:lianghsun/wikipedia-zh-filtered", "dataset:AWeirdDev/zh-tw-pts-articles-sm", "dataset:bhxiang/c4_calibrate_mini", "dataset:benchang1110/pretrainedtw", "dataset:benchang1110/sciencetw", "dataset:intfloat/multilingual_cc_news", "base_model:lianghsun/Llama-3.2-Taiwan-3B", "base_model:quantized:lianghsun/Llama-3.2-Taiwan-3B", "license:llama3.2", "endpoints_compatible", "region:us", "conversational" ]	text-generation	2025-01-15T15:41:53Z	--- base_model: lianghsun/Llama-3.2-Taiwan-3B library_name: transformers datasets: - lianghsun/tw-novel-1.1B - lianghsun/tw-finance-159M - lianghsun/tw-legal-news-24M - lianghsun/tw-gov-news-90M - lianghsun/tw-gov-556k - lianghsun/tw-news-551M - lianghsun/tw-health-43M - lianghsun/tw-science-24M - lianghsun/tw-book-43M - lianghsun/tw-society-88M - lianghsun/tw-law-article-evolution - lianghsun/tw-processed-judgments - lianghsun/tw-legal-methodology - lianghsun/tw-legal-qa - lianghsun/tw-judgment-gist - lianghsun/reasoning-base-20k - lianghsun/wikipedia-zh-filtered - AWeirdDev/zh-tw-pts-articles-sm - bhxiang/c4_calibrate_mini - benchang1110/pretrainedtw - benchang1110/sciencetw - intfloat/multilingual_cc_news language: - zh - en license: llama3.2 tags: - ROC - Taiwan - zh-tw - llama-factory - llama-cpp - gguf-my-repo new_version: lianghsun/Llama-3.2-Taiwan-3B-Instruct pipeline_tag: text-generation widget: - text: 中華民國憲法第一條 --- # itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF This model was converted to GGUF format from [`lianghsun/Llama-3.2-Taiwan-3B`](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -c 2048 ```
thaffggg/a02adaab-00b1-4220-a9a9-154dea3495b5	thaffggg	2025-01-15T15:39:09Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-4k-instruct", "base_model:adapter:microsoft/Phi-3-mini-4k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:20:01Z	--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-4k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a02adaab-00b1-4220-a9a9-154dea3495b5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-4k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 80c99709830fd48a_train_data.json ds_type: json format: custom path: /workspace/input_data/80c99709830fd48a_train_data.json type: field_instruction: input field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/a02adaab-00b1-4220-a9a9-154dea3495b5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/80c99709830fd48a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # a02adaab-00b1-4220-a9a9-154dea3495b5 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4311 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.7407 \| 0.1206 \| 200 \| 0.4311 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
asafd60/HebQwen-json-2025-meta	asafd60	2025-01-15T15:38:37Z	84	0	transformers	[ "transformers", "safetensors", "qwen2_vl", "image-text-to-text", "conversational", "arxiv:1910.09700", "text-generation-inference", "endpoints_compatible", "region:us" ]	image-text-to-text	2025-01-15T15:32:36Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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cunghoctienganh/a4f8f6b7-473d-44a0-ad19-9c32ae368864	cunghoctienganh	2025-01-15T15:38:30Z	6	0	peft	[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-4k-instruct", "base_model:adapter:microsoft/Phi-3-mini-4k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:19:21Z	--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-4k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a4f8f6b7-473d-44a0-ad19-9c32ae368864 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-4k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 80c99709830fd48a_train_data.json ds_type: json format: custom path: /workspace/input_data/80c99709830fd48a_train_data.json type: field_instruction: input field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: cunghoctienganh/a4f8f6b7-473d-44a0-ad19-9c32ae368864 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/80c99709830fd48a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # a4f8f6b7-473d-44a0-ad19-9c32ae368864 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4312 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.7471 \| 0.1206 \| 200 \| 0.4312 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thangla01/cc2b4a23-f3b3-4c69-aaa5-14746b129c9c	thangla01	2025-01-15T15:38:26Z	8	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:35:58Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: cc2b4a23-f3b3-4c69-aaa5-14746b129c9c results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thangla01/cc2b4a23-f3b3-4c69-aaa5-14746b129c9c hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # cc2b4a23-f3b3-4c69-aaa5-14746b129c9c This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6362 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 6.8421 \| 0.0105 \| 200 \| 1.6362 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization	MayBashendy	2025-01-15T15:38:20Z	6	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T14:51:41Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6404 - Qwk: 0.5029 - Mse: 0.6404 - Rmse: 0.8003 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0377 \| 2 \| 4.2473 \| -0.0228 \| 4.2473 \| 2.0609 \| \| No log \| 0.0755 \| 4 \| 2.3310 \| 0.0238 \| 2.3310 \| 1.5268 \| \| No log \| 0.1132 \| 6 \| 1.3560 \| 0.0205 \| 1.3560 \| 1.1645 \| \| No log \| 0.1509 \| 8 \| 0.9130 \| 0.0383 \| 0.9130 \| 0.9555 \| \| No log \| 0.1887 \| 10 \| 0.8565 \| 0.1596 \| 0.8565 \| 0.9255 \| \| No log \| 0.2264 \| 12 \| 1.0357 \| 0.0713 \| 1.0357 \| 1.0177 \| \| No log \| 0.2642 \| 14 \| 1.0549 \| 0.1234 \| 1.0549 \| 1.0271 \| \| No log \| 0.3019 \| 16 \| 0.8566 \| 0.1477 \| 0.8566 \| 0.9255 \| \| No log \| 0.3396 \| 18 \| 1.1207 \| 0.1474 \| 1.1207 \| 1.0587 \| \| No log \| 0.3774 \| 20 \| 1.6261 \| 0.0643 \| 1.6261 \| 1.2752 \| \| No log \| 0.4151 \| 22 \| 1.5250 \| 0.0550 \| 1.5250 \| 1.2349 \| \| No log \| 0.4528 \| 24 \| 1.2243 \| 0.0677 \| 1.2243 \| 1.1065 \| \| No log \| 0.4906 \| 26 \| 0.9723 \| 0.1509 \| 0.9723 \| 0.9860 \| \| No log \| 0.5283 \| 28 \| 0.9085 \| 0.1681 \| 0.9085 \| 0.9532 \| \| No log \| 0.5660 \| 30 \| 0.8029 \| 0.2499 \| 0.8029 \| 0.8961 \| \| No log \| 0.6038 \| 32 \| 0.8286 \| 0.1573 \| 0.8286 \| 0.9103 \| \| No log \| 0.6415 \| 34 \| 0.8689 \| 0.1731 \| 0.8689 \| 0.9322 \| \| No log \| 0.6792 \| 36 \| 1.1002 \| 0.0847 \| 1.1002 \| 1.0489 \| \| No log \| 0.7170 \| 38 \| 1.4252 \| 0.0868 \| 1.4252 \| 1.1938 \| \| No log \| 0.7547 \| 40 \| 1.8930 \| 0.1372 \| 1.8930 \| 1.3759 \| \| No log \| 0.7925 \| 42 \| 1.7148 \| 0.1316 \| 1.7148 \| 1.3095 \| \| No log \| 0.8302 \| 44 \| 1.2532 \| 0.2452 \| 1.2532 \| 1.1195 \| \| No log \| 0.8679 \| 46 \| 0.9984 \| 0.2395 \| 0.9984 \| 0.9992 \| \| No log \| 0.9057 \| 48 \| 1.0085 \| 0.2069 \| 1.0085 \| 1.0042 \| \| No log \| 0.9434 \| 50 \| 0.8329 \| 0.3641 \| 0.8329 \| 0.9126 \| \| No log \| 0.9811 \| 52 \| 0.6157 \| 0.3959 \| 0.6157 \| 0.7846 \| \| No log \| 1.0189 \| 54 \| 0.6081 \| 0.4061 \| 0.6081 \| 0.7798 \| \| No log \| 1.0566 \| 56 \| 0.6818 \| 0.3701 \| 0.6818 \| 0.8257 \| \| No log \| 1.0943 \| 58 \| 0.9277 \| 0.2847 \| 0.9277 \| 0.9632 \| \| No log \| 1.1321 \| 60 \| 1.0415 \| 0.3412 \| 1.0415 \| 1.0205 \| \| No log \| 1.1698 \| 62 \| 0.9216 \| 0.3506 \| 0.9216 \| 0.9600 \| \| No log \| 1.2075 \| 64 \| 0.6502 \| 0.4398 \| 0.6502 \| 0.8063 \| \| No log \| 1.2453 \| 66 \| 0.7747 \| 0.2631 \| 0.7747 \| 0.8802 \| \| No log \| 1.2830 \| 68 \| 0.9121 \| 0.1402 \| 0.9121 \| 0.9550 \| \| No log \| 1.3208 \| 70 \| 0.7329 \| 0.2601 \| 0.7329 \| 0.8561 \| \| No log \| 1.3585 \| 72 \| 0.6610 \| 0.5366 \| 0.6610 \| 0.8130 \| \| No log \| 1.3962 \| 74 \| 0.9865 \| 0.4573 \| 0.9865 \| 0.9932 \| \| No log \| 1.4340 \| 76 \| 1.1531 \| 0.3424 \| 1.1531 \| 1.0738 \| \| No log \| 1.4717 \| 78 \| 0.9473 \| 0.4736 \| 0.9473 \| 0.9733 \| \| No log \| 1.5094 \| 80 \| 0.9756 \| 0.4506 \| 0.9756 \| 0.9877 \| \| No log \| 1.5472 \| 82 \| 0.9997 \| 0.4460 \| 0.9997 \| 0.9999 \| \| No log \| 1.5849 \| 84 \| 1.2514 \| 0.2979 \| 1.2514 \| 1.1187 \| \| No log \| 1.6226 \| 86 \| 1.2607 \| 0.3124 \| 1.2607 \| 1.1228 \| \| No log \| 1.6604 \| 88 \| 1.3783 \| 0.2598 \| 1.3783 \| 1.1740 \| \| No log \| 1.6981 \| 90 \| 1.3063 \| 0.2830 \| 1.3063 \| 1.1429 \| \| No log \| 1.7358 \| 92 \| 0.9235 \| 0.4575 \| 0.9235 \| 0.9610 \| \| No log \| 1.7736 \| 94 \| 0.5829 \| 0.4552 \| 0.5829 \| 0.7635 \| \| No log \| 1.8113 \| 96 \| 0.6093 \| 0.4342 \| 0.6093 \| 0.7805 \| \| No log \| 1.8491 \| 98 \| 0.5742 \| 0.3628 \| 0.5742 \| 0.7578 \| \| No log \| 1.8868 \| 100 \| 0.6228 \| 0.4603 \| 0.6228 \| 0.7892 \| \| No log \| 1.9245 \| 102 \| 0.6994 \| 0.5053 \| 0.6994 \| 0.8363 \| \| No log \| 1.9623 \| 104 \| 0.5974 \| 0.4997 \| 0.5974 \| 0.7729 \| \| No log \| 2.0 \| 106 \| 0.5891 \| 0.5375 \| 0.5891 \| 0.7675 \| \| No log \| 2.0377 \| 108 \| 0.6116 \| 0.5281 \| 0.6116 \| 0.7821 \| \| No log \| 2.0755 \| 110 \| 0.6222 \| 0.6008 \| 0.6222 \| 0.7888 \| \| No log \| 2.1132 \| 112 \| 0.7781 \| 0.5635 \| 0.7781 \| 0.8821 \| \| No log \| 2.1509 \| 114 \| 1.1884 \| 0.3373 \| 1.1884 \| 1.0902 \| \| No log \| 2.1887 \| 116 \| 1.5178 \| 0.2919 \| 1.5178 \| 1.2320 \| \| No log \| 2.2264 \| 118 \| 1.2534 \| 0.3059 \| 1.2534 \| 1.1195 \| \| No log \| 2.2642 \| 120 \| 0.7709 \| 0.5254 \| 0.7709 \| 0.8780 \| \| No log \| 2.3019 \| 122 \| 0.5978 \| 0.5234 \| 0.5978 \| 0.7732 \| \| No log \| 2.3396 \| 124 \| 0.6255 \| 0.4921 \| 0.6255 \| 0.7909 \| \| No log \| 2.3774 \| 126 \| 0.5841 \| 0.5536 \| 0.5841 \| 0.7643 \| \| No log \| 2.4151 \| 128 \| 0.7852 \| 0.5560 \| 0.7852 \| 0.8861 \| \| No log \| 2.4528 \| 130 \| 0.9215 \| 0.3990 \| 0.9215 \| 0.9599 \| \| No log \| 2.4906 \| 132 \| 0.7816 \| 0.5569 \| 0.7816 \| 0.8841 \| \| No log \| 2.5283 \| 134 \| 0.5990 \| 0.5452 \| 0.5990 \| 0.7739 \| \| No log \| 2.5660 \| 136 \| 0.5412 \| 0.4919 \| 0.5412 \| 0.7357 \| \| No log \| 2.6038 \| 138 \| 0.5472 \| 0.4689 \| 0.5472 \| 0.7397 \| \| No log \| 2.6415 \| 140 \| 0.7115 \| 0.5535 \| 0.7115 \| 0.8435 \| \| No log \| 2.6792 \| 142 \| 1.3119 \| 0.3421 \| 1.3119 \| 1.1454 \| \| No log \| 2.7170 \| 144 \| 1.5224 \| 0.2856 \| 1.5224 \| 1.2338 \| \| No log \| 2.7547 \| 146 \| 1.1841 \| 0.4041 \| 1.1841 \| 1.0882 \| \| No log \| 2.7925 \| 148 \| 0.9617 \| 0.4544 \| 0.9617 \| 0.9807 \| \| No log \| 2.8302 \| 150 \| 0.8756 \| 0.4804 \| 0.8756 \| 0.9358 \| \| No log \| 2.8679 \| 152 \| 0.9670 \| 0.4648 \| 0.9670 \| 0.9834 \| \| No log \| 2.9057 \| 154 \| 1.1254 \| 0.3595 \| 1.1254 \| 1.0609 \| \| No log \| 2.9434 \| 156 \| 0.9562 \| 0.4757 \| 0.9562 \| 0.9779 \| \| No log \| 2.9811 \| 158 \| 0.7437 \| 0.5500 \| 0.7437 \| 0.8624 \| \| No log \| 3.0189 \| 160 \| 0.6462 \| 0.5414 \| 0.6462 \| 0.8039 \| \| No log \| 3.0566 \| 162 \| 0.6470 \| 0.5277 \| 0.6470 \| 0.8044 \| \| No log \| 3.0943 \| 164 \| 0.7120 \| 0.5137 \| 0.7120 \| 0.8438 \| \| No log \| 3.1321 \| 166 \| 0.8192 \| 0.5071 \| 0.8192 \| 0.9051 \| \| No log \| 3.1698 \| 168 \| 0.9236 \| 0.4534 \| 0.9236 \| 0.9610 \| \| No log \| 3.2075 \| 170 \| 0.8508 \| 0.5040 \| 0.8508 \| 0.9224 \| \| No log \| 3.2453 \| 172 \| 0.7356 \| 0.5419 \| 0.7356 \| 0.8577 \| \| No log \| 3.2830 \| 174 \| 0.6803 \| 0.5183 \| 0.6803 \| 0.8248 \| \| No log \| 3.3208 \| 176 \| 0.6747 \| 0.5787 \| 0.6747 \| 0.8214 \| \| No log \| 3.3585 \| 178 \| 0.6850 \| 0.5714 \| 0.6850 \| 0.8277 \| \| No log \| 3.3962 \| 180 \| 0.7099 \| 0.5388 \| 0.7099 \| 0.8426 \| \| No log \| 3.4340 \| 182 \| 0.7962 \| 0.5214 \| 0.7962 \| 0.8923 \| \| No log \| 3.4717 \| 184 \| 0.7702 \| 0.5532 \| 0.7702 \| 0.8776 \| \| No log \| 3.5094 \| 186 \| 0.6431 \| 0.5696 \| 0.6431 \| 0.8019 \| \| No log \| 3.5472 \| 188 \| 0.6170 \| 0.5693 \| 0.6170 \| 0.7855 \| \| No log \| 3.5849 \| 190 \| 0.7147 \| 0.5322 \| 0.7147 \| 0.8454 \| \| No log \| 3.6226 \| 192 \| 0.9754 \| 0.4538 \| 0.9754 \| 0.9876 \| \| No log \| 3.6604 \| 194 \| 1.0223 \| 0.4284 \| 1.0223 \| 1.0111 \| \| No log \| 3.6981 \| 196 \| 0.8039 \| 0.5049 \| 0.8039 \| 0.8966 \| \| No log \| 3.7358 \| 198 \| 0.6262 \| 0.5378 \| 0.6262 \| 0.7913 \| \| No log \| 3.7736 \| 200 \| 0.5897 \| 0.544 \| 0.5897 \| 0.7679 \| \| No log \| 3.8113 \| 202 \| 0.5879 \| 0.4848 \| 0.5879 \| 0.7667 \| \| No log \| 3.8491 \| 204 \| 0.6732 \| 0.5162 \| 0.6732 \| 0.8205 \| \| No log \| 3.8868 \| 206 \| 0.7012 \| 0.5104 \| 0.7012 \| 0.8374 \| \| No log \| 3.9245 \| 208 \| 0.7607 \| 0.5141 \| 0.7607 \| 0.8722 \| \| No log \| 3.9623 \| 210 \| 0.7177 \| 0.4838 \| 0.7177 \| 0.8472 \| \| No log \| 4.0 \| 212 \| 0.7243 \| 0.4587 \| 0.7243 \| 0.8511 \| \| No log \| 4.0377 \| 214 \| 0.7986 \| 0.4752 \| 0.7986 \| 0.8937 \| \| No log \| 4.0755 \| 216 \| 0.8368 \| 0.4465 \| 0.8368 \| 0.9147 \| \| No log \| 4.1132 \| 218 \| 0.7661 \| 0.4456 \| 0.7661 \| 0.8753 \| \| No log \| 4.1509 \| 220 \| 0.6834 \| 0.4762 \| 0.6834 \| 0.8267 \| \| No log \| 4.1887 \| 222 \| 0.6034 \| 0.5200 \| 0.6034 \| 0.7768 \| \| No log \| 4.2264 \| 224 \| 0.5829 \| 0.5026 \| 0.5829 \| 0.7635 \| \| No log \| 4.2642 \| 226 \| 0.5522 \| 0.5046 \| 0.5522 \| 0.7431 \| \| No log \| 4.3019 \| 228 \| 0.6732 \| 0.5143 \| 0.6732 \| 0.8205 \| \| No log \| 4.3396 \| 230 \| 0.8137 \| 0.5024 \| 0.8137 \| 0.9020 \| \| No log \| 4.3774 \| 232 \| 0.7688 \| 0.5289 \| 0.7688 \| 0.8768 \| \| No log \| 4.4151 \| 234 \| 0.6635 \| 0.5474 \| 0.6635 \| 0.8146 \| \| No log \| 4.4528 \| 236 \| 0.5890 \| 0.5847 \| 0.5890 \| 0.7675 \| \| No log \| 4.4906 \| 238 \| 0.5520 \| 0.5296 \| 0.5520 \| 0.7430 \| \| No log \| 4.5283 \| 240 \| 0.5479 \| 0.4513 \| 0.5479 \| 0.7402 \| \| No log \| 4.5660 \| 242 \| 0.5546 \| 0.4287 \| 0.5546 \| 0.7447 \| \| No log \| 4.6038 \| 244 \| 0.6018 \| 0.4705 \| 0.6018 \| 0.7758 \| \| No log \| 4.6415 \| 246 \| 0.8159 \| 0.4863 \| 0.8159 \| 0.9033 \| \| No log \| 4.6792 \| 248 \| 0.9919 \| 0.3930 \| 0.9919 \| 0.9959 \| \| No log \| 4.7170 \| 250 \| 0.8988 \| 0.4560 \| 0.8988 \| 0.9480 \| \| No log \| 4.7547 \| 252 \| 0.7981 \| 0.5224 \| 0.7981 \| 0.8934 \| \| No log \| 4.7925 \| 254 \| 0.7082 \| 0.5429 \| 0.7082 \| 0.8416 \| \| No log \| 4.8302 \| 256 \| 0.6740 \| 0.5810 \| 0.6740 \| 0.8210 \| \| No log \| 4.8679 \| 258 \| 0.6624 \| 0.5910 \| 0.6624 \| 0.8139 \| \| No log \| 4.9057 \| 260 \| 0.6916 \| 0.5185 \| 0.6916 \| 0.8316 \| \| No log \| 4.9434 \| 262 \| 0.8107 \| 0.4617 \| 0.8107 \| 0.9004 \| \| No log \| 4.9811 \| 264 \| 0.9351 \| 0.4061 \| 0.9351 \| 0.9670 \| \| No log \| 5.0189 \| 266 \| 0.9234 \| 0.4039 \| 0.9234 \| 0.9609 \| \| No log \| 5.0566 \| 268 \| 0.7650 \| 0.5064 \| 0.7650 \| 0.8746 \| \| No log \| 5.0943 \| 270 \| 0.6317 \| 0.5487 \| 0.6317 \| 0.7948 \| \| No log \| 5.1321 \| 272 \| 0.5789 \| 0.4779 \| 0.5789 \| 0.7609 \| \| No log \| 5.1698 \| 274 \| 0.6494 \| 0.4821 \| 0.6494 \| 0.8058 \| \| No log \| 5.2075 \| 276 \| 0.6298 \| 0.4959 \| 0.6298 \| 0.7936 \| \| No log \| 5.2453 \| 278 \| 0.5982 \| 0.5173 \| 0.5981 \| 0.7734 \| \| No log \| 5.2830 \| 280 \| 0.8517 \| 0.4940 \| 0.8517 \| 0.9229 \| \| No log \| 5.3208 \| 282 \| 1.2323 \| 0.2818 \| 1.2323 \| 1.1101 \| \| No log \| 5.3585 \| 284 \| 1.2627 \| 0.2595 \| 1.2627 \| 1.1237 \| \| No log \| 5.3962 \| 286 \| 0.9694 \| 0.4360 \| 0.9694 \| 0.9846 \| \| No log \| 5.4340 \| 288 \| 0.6580 \| 0.5133 \| 0.6580 \| 0.8112 \| \| No log \| 5.4717 \| 290 \| 0.5646 \| 0.5791 \| 0.5646 \| 0.7514 \| \| No log \| 5.5094 \| 292 \| 0.5872 \| 0.4476 \| 0.5872 \| 0.7663 \| \| No log \| 5.5472 \| 294 \| 0.5897 \| 0.4657 \| 0.5897 \| 0.7679 \| \| No log \| 5.5849 \| 296 \| 0.5925 \| 0.5642 \| 0.5925 \| 0.7697 \| \| No log \| 5.6226 \| 298 \| 0.6847 \| 0.5382 \| 0.6847 \| 0.8275 \| \| No log \| 5.6604 \| 300 \| 0.9729 \| 0.4245 \| 0.9729 \| 0.9864 \| \| No log \| 5.6981 \| 302 \| 1.3748 \| 0.3148 \| 1.3748 \| 1.1725 \| \| No log \| 5.7358 \| 304 \| 1.6679 \| 0.2424 \| 1.6679 \| 1.2915 \| \| No log \| 5.7736 \| 306 \| 1.5423 \| 0.2462 \| 1.5423 \| 1.2419 \| \| No log \| 5.8113 \| 308 \| 1.1594 \| 0.3335 \| 1.1594 \| 1.0767 \| \| No log \| 5.8491 \| 310 \| 0.8002 \| 0.4709 \| 0.8002 \| 0.8945 \| \| No log \| 5.8868 \| 312 \| 0.5973 \| 0.5889 \| 0.5973 \| 0.7729 \| \| No log \| 5.9245 \| 314 \| 0.5677 \| 0.6079 \| 0.5677 \| 0.7535 \| \| No log \| 5.9623 \| 316 \| 0.5561 \| 0.6258 \| 0.5561 \| 0.7457 \| \| No log \| 6.0 \| 318 \| 0.5507 \| 0.6429 \| 0.5507 \| 0.7421 \| \| No log \| 6.0377 \| 320 \| 0.5508 \| 0.6175 \| 0.5508 \| 0.7422 \| \| No log \| 6.0755 \| 322 \| 0.5591 \| 0.6309 \| 0.5591 \| 0.7478 \| \| No log \| 6.1132 \| 324 \| 0.5875 \| 0.6441 \| 0.5875 \| 0.7665 \| \| No log \| 6.1509 \| 326 \| 0.6572 \| 0.5946 \| 0.6572 \| 0.8107 \| \| No log \| 6.1887 \| 328 \| 0.7346 \| 0.5047 \| 0.7346 \| 0.8571 \| \| No log \| 6.2264 \| 330 \| 0.7883 \| 0.4531 \| 0.7883 \| 0.8879 \| \| No log \| 6.2642 \| 332 \| 0.7583 \| 0.4830 \| 0.7583 \| 0.8708 \| \| No log \| 6.3019 \| 334 \| 0.6975 \| 0.5044 \| 0.6975 \| 0.8352 \| \| No log \| 6.3396 \| 336 \| 0.6328 \| 0.5577 \| 0.6328 \| 0.7955 \| \| No log \| 6.3774 \| 338 \| 0.6077 \| 0.6084 \| 0.6077 \| 0.7796 \| \| No log \| 6.4151 \| 340 \| 0.6454 \| 0.6105 \| 0.6454 \| 0.8034 \| \| No log \| 6.4528 \| 342 \| 0.6772 \| 0.6293 \| 0.6772 \| 0.8229 \| \| No log \| 6.4906 \| 344 \| 0.7261 \| 0.5732 \| 0.7261 \| 0.8521 \| \| No log \| 6.5283 \| 346 \| 0.8307 \| 0.4926 \| 0.8307 \| 0.9115 \| \| No log \| 6.5660 \| 348 \| 0.8205 \| 0.4750 \| 0.8205 \| 0.9058 \| \| No log \| 6.6038 \| 350 \| 0.7000 \| 0.5564 \| 0.7000 \| 0.8367 \| \| No log \| 6.6415 \| 352 \| 0.5884 \| 0.5860 \| 0.5884 \| 0.7670 \| \| No log \| 6.6792 \| 354 \| 0.5588 \| 0.6040 \| 0.5588 \| 0.7475 \| \| No log \| 6.7170 \| 356 \| 0.5540 \| 0.5842 \| 0.5540 \| 0.7443 \| \| No log \| 6.7547 \| 358 \| 0.5684 \| 0.5746 \| 0.5684 \| 0.7540 \| \| No log \| 6.7925 \| 360 \| 0.5849 \| 0.5558 \| 0.5849 \| 0.7648 \| \| No log \| 6.8302 \| 362 \| 0.5776 \| 0.5804 \| 0.5776 \| 0.7600 \| \| No log \| 6.8679 \| 364 \| 0.5644 \| 0.5859 \| 0.5644 \| 0.7512 \| \| No log \| 6.9057 \| 366 \| 0.5538 \| 0.5618 \| 0.5538 \| 0.7442 \| \| No log \| 6.9434 \| 368 \| 0.5417 \| 0.5377 \| 0.5417 \| 0.7360 \| \| No log \| 6.9811 \| 370 \| 0.5460 \| 0.4654 \| 0.5460 \| 0.7389 \| \| No log \| 7.0189 \| 372 \| 0.5722 \| 0.4889 \| 0.5722 \| 0.7565 \| \| No log \| 7.0566 \| 374 \| 0.5693 \| 0.4889 \| 0.5693 \| 0.7545 \| \| No log \| 7.0943 \| 376 \| 0.6087 \| 0.5328 \| 0.6087 \| 0.7802 \| \| No log \| 7.1321 \| 378 \| 0.5971 \| 0.5242 \| 0.5971 \| 0.7727 \| \| No log \| 7.1698 \| 380 \| 0.5952 \| 0.5262 \| 0.5952 \| 0.7715 \| \| No log \| 7.2075 \| 382 \| 0.5716 \| 0.5724 \| 0.5716 \| 0.7560 \| \| No log \| 7.2453 \| 384 \| 0.5663 \| 0.5643 \| 0.5663 \| 0.7525 \| \| No log \| 7.2830 \| 386 \| 0.5560 \| 0.5641 \| 0.5560 \| 0.7456 \| \| No log \| 7.3208 \| 388 \| 0.5432 \| 0.4990 \| 0.5432 \| 0.7370 \| \| No log \| 7.3585 \| 390 \| 0.5355 \| 0.5048 \| 0.5355 \| 0.7318 \| \| No log \| 7.3962 \| 392 \| 0.5335 \| 0.4804 \| 0.5335 \| 0.7304 \| \| No log \| 7.4340 \| 394 \| 0.5408 \| 0.5046 \| 0.5408 \| 0.7354 \| \| No log \| 7.4717 \| 396 \| 0.5895 \| 0.5395 \| 0.5895 \| 0.7678 \| \| No log \| 7.5094 \| 398 \| 0.6544 \| 0.5187 \| 0.6544 \| 0.8089 \| \| No log \| 7.5472 \| 400 \| 0.6710 \| 0.5369 \| 0.6710 \| 0.8192 \| \| No log \| 7.5849 \| 402 \| 0.6784 \| 0.5301 \| 0.6784 \| 0.8236 \| \| No log \| 7.6226 \| 404 \| 0.6731 \| 0.5271 \| 0.6731 \| 0.8204 \| \| No log \| 7.6604 \| 406 \| 0.7178 \| 0.5552 \| 0.7178 \| 0.8472 \| \| No log \| 7.6981 \| 408 \| 0.7901 \| 0.5554 \| 0.7901 \| 0.8889 \| \| No log \| 7.7358 \| 410 \| 0.9238 \| 0.4669 \| 0.9238 \| 0.9611 \| \| No log \| 7.7736 \| 412 \| 0.9980 \| 0.4031 \| 0.9980 \| 0.9990 \| \| No log \| 7.8113 \| 414 \| 0.9183 \| 0.4453 \| 0.9183 \| 0.9583 \| \| No log \| 7.8491 \| 416 \| 0.7103 \| 0.5337 \| 0.7103 \| 0.8428 \| \| No log \| 7.8868 \| 418 \| 0.6005 \| 0.5762 \| 0.6005 \| 0.7749 \| \| No log \| 7.9245 \| 420 \| 0.5906 \| 0.4772 \| 0.5906 \| 0.7685 \| \| No log \| 7.9623 \| 422 \| 0.5679 \| 0.4024 \| 0.5679 \| 0.7536 \| \| No log \| 8.0 \| 424 \| 0.5324 \| 0.3755 \| 0.5324 \| 0.7296 \| \| No log \| 8.0377 \| 426 \| 0.5280 \| 0.4100 \| 0.5280 \| 0.7266 \| \| No log \| 8.0755 \| 428 \| 0.5301 \| 0.4996 \| 0.5301 \| 0.7281 \| \| No log \| 8.1132 \| 430 \| 0.5226 \| 0.4621 \| 0.5226 \| 0.7229 \| \| No log \| 8.1509 \| 432 \| 0.5423 \| 0.5516 \| 0.5423 \| 0.7364 \| \| No log \| 8.1887 \| 434 \| 0.5498 \| 0.6100 \| 0.5498 \| 0.7415 \| \| No log \| 8.2264 \| 436 \| 0.5586 \| 0.6482 \| 0.5586 \| 0.7474 \| \| No log \| 8.2642 \| 438 \| 0.6275 \| 0.5434 \| 0.6275 \| 0.7922 \| \| No log \| 8.3019 \| 440 \| 0.6392 \| 0.5291 \| 0.6392 \| 0.7995 \| \| No log \| 8.3396 \| 442 \| 0.5715 \| 0.5607 \| 0.5715 \| 0.7560 \| \| No log \| 8.3774 \| 444 \| 0.5203 \| 0.5805 \| 0.5203 \| 0.7213 \| \| No log \| 8.4151 \| 446 \| 0.5551 \| 0.5067 \| 0.5551 \| 0.7451 \| \| No log \| 8.4528 \| 448 \| 0.5769 \| 0.4789 \| 0.5769 \| 0.7596 \| \| No log \| 8.4906 \| 450 \| 0.5339 \| 0.5006 \| 0.5339 \| 0.7307 \| \| No log \| 8.5283 \| 452 \| 0.5035 \| 0.4897 \| 0.5035 \| 0.7096 \| \| No log \| 8.5660 \| 454 \| 0.5923 \| 0.5489 \| 0.5923 \| 0.7696 \| \| No log \| 8.6038 \| 456 \| 0.6918 \| 0.5313 \| 0.6918 \| 0.8318 \| \| No log \| 8.6415 \| 458 \| 0.7063 \| 0.5126 \| 0.7063 \| 0.8404 \| \| No log \| 8.6792 \| 460 \| 0.6414 \| 0.5401 \| 0.6414 \| 0.8009 \| \| No log \| 8.7170 \| 462 \| 0.5628 \| 0.6358 \| 0.5628 \| 0.7502 \| \| No log \| 8.7547 \| 464 \| 0.5601 \| 0.6314 \| 0.5601 \| 0.7484 \| \| No log \| 8.7925 \| 466 \| 0.5738 \| 0.6288 \| 0.5738 \| 0.7575 \| \| No log \| 8.8302 \| 468 \| 0.6672 \| 0.5434 \| 0.6672 \| 0.8169 \| \| No log \| 8.8679 \| 470 \| 0.8416 \| 0.4655 \| 0.8416 \| 0.9174 \| \| No log \| 8.9057 \| 472 \| 0.8374 \| 0.4467 \| 0.8374 \| 0.9151 \| \| No log \| 8.9434 \| 474 \| 0.6751 \| 0.4961 \| 0.6751 \| 0.8216 \| \| No log \| 8.9811 \| 476 \| 0.5743 \| 0.5342 \| 0.5743 \| 0.7578 \| \| No log \| 9.0189 \| 478 \| 0.5423 \| 0.5137 \| 0.5423 \| 0.7364 \| \| No log \| 9.0566 \| 480 \| 0.5473 \| 0.5446 \| 0.5473 \| 0.7398 \| \| No log \| 9.0943 \| 482 \| 0.5612 \| 0.5665 \| 0.5612 \| 0.7491 \| \| No log \| 9.1321 \| 484 \| 0.5746 \| 0.5318 \| 0.5747 \| 0.7581 \| \| No log \| 9.1698 \| 486 \| 0.6079 \| 0.5389 \| 0.6079 \| 0.7797 \| \| No log \| 9.2075 \| 488 \| 0.6587 \| 0.5355 \| 0.6587 \| 0.8116 \| \| No log \| 9.2453 \| 490 \| 0.6466 \| 0.5158 \| 0.6466 \| 0.8041 \| \| No log \| 9.2830 \| 492 \| 0.5998 \| 0.5187 \| 0.5998 \| 0.7744 \| \| No log \| 9.3208 \| 494 \| 0.5841 \| 0.4931 \| 0.5841 \| 0.7643 \| \| No log \| 9.3585 \| 496 \| 0.5826 \| 0.4931 \| 0.5826 \| 0.7633 \| \| No log \| 9.3962 \| 498 \| 0.6094 \| 0.5269 \| 0.6094 \| 0.7806 \| \| 0.4026 \| 9.4340 \| 500 \| 0.6498 \| 0.4771 \| 0.6498 \| 0.8061 \| \| 0.4026 \| 9.4717 \| 502 \| 0.7081 \| 0.4931 \| 0.7081 \| 0.8415 \| \| 0.4026 \| 9.5094 \| 504 \| 0.6831 \| 0.4858 \| 0.6831 \| 0.8265 \| \| 0.4026 \| 9.5472 \| 506 \| 0.6339 \| 0.5921 \| 0.6339 \| 0.7962 \| \| 0.4026 \| 9.5849 \| 508 \| 0.6050 \| 0.5660 \| 0.6050 \| 0.7778 \| \| 0.4026 \| 9.6226 \| 510 \| 0.6029 \| 0.5348 \| 0.6029 \| 0.7765 \| \| 0.4026 \| 9.6604 \| 512 \| 0.5805 \| 0.5531 \| 0.5805 \| 0.7619 \| \| 0.4026 \| 9.6981 \| 514 \| 0.5793 \| 0.4448 \| 0.5793 \| 0.7611 \| \| 0.4026 \| 9.7358 \| 516 \| 0.6128 \| 0.4777 \| 0.6128 \| 0.7828 \| \| 0.4026 \| 9.7736 \| 518 \| 0.6073 \| 0.4777 \| 0.6073 \| 0.7793 \| \| 0.4026 \| 9.8113 \| 520 \| 0.5890 \| 0.4941 \| 0.5890 \| 0.7674 \| \| 0.4026 \| 9.8491 \| 522 \| 0.6008 \| 0.5494 \| 0.6008 \| 0.7751 \| \| 0.4026 \| 9.8868 \| 524 \| 0.6307 \| 0.6296 \| 0.6307 \| 0.7942 \| \| 0.4026 \| 9.9245 \| 526 \| 0.6690 \| 0.5738 \| 0.6690 \| 0.8179 \| \| 0.4026 \| 9.9623 \| 528 \| 0.7104 \| 0.4782 \| 0.7104 \| 0.8429 \| \| 0.4026 \| 10.0 \| 530 \| 0.7745 \| 0.4514 \| 0.7745 \| 0.8801 \| \| 0.4026 \| 10.0377 \| 532 \| 0.7810 \| 0.4642 \| 0.7810 \| 0.8837 \| \| 0.4026 \| 10.0755 \| 534 \| 0.6887 \| 0.4742 \| 0.6887 \| 0.8299 \| \| 0.4026 \| 10.1132 \| 536 \| 0.6139 \| 0.5396 \| 0.6139 \| 0.7835 \| \| 0.4026 \| 10.1509 \| 538 \| 0.5841 \| 0.5476 \| 0.5841 \| 0.7643 \| \| 0.4026 \| 10.1887 \| 540 \| 0.5686 \| 0.5402 \| 0.5686 \| 0.7541 \| \| 0.4026 \| 10.2264 \| 542 \| 0.5925 \| 0.5269 \| 0.5925 \| 0.7698 \| \| 0.4026 \| 10.2642 \| 544 \| 0.5995 \| 0.4816 \| 0.5995 \| 0.7743 \| \| 0.4026 \| 10.3019 \| 546 \| 0.5616 \| 0.4984 \| 0.5616 \| 0.7494 \| \| 0.4026 \| 10.3396 \| 548 \| 0.5623 \| 0.5271 \| 0.5623 \| 0.7499 \| \| 0.4026 \| 10.3774 \| 550 \| 0.6186 \| 0.5229 \| 0.6186 \| 0.7865 \| \| 0.4026 \| 10.4151 \| 552 \| 0.6444 \| 0.5453 \| 0.6444 \| 0.8027 \| \| 0.4026 \| 10.4528 \| 554 \| 0.6285 \| 0.5237 \| 0.6285 \| 0.7928 \| \| 0.4026 \| 10.4906 \| 556 \| 0.6011 \| 0.5447 \| 0.6011 \| 0.7753 \| \| 0.4026 \| 10.5283 \| 558 \| 0.5841 \| 0.5861 \| 0.5841 \| 0.7643 \| \| 0.4026 \| 10.5660 \| 560 \| 0.5949 \| 0.5238 \| 0.5949 \| 0.7713 \| \| 0.4026 \| 10.6038 \| 562 \| 0.5829 \| 0.5649 \| 0.5829 \| 0.7635 \| \| 0.4026 \| 10.6415 \| 564 \| 0.5605 \| 0.5341 \| 0.5605 \| 0.7486 \| \| 0.4026 \| 10.6792 \| 566 \| 0.5942 \| 0.5437 \| 0.5942 \| 0.7708 \| \| 0.4026 \| 10.7170 \| 568 \| 0.6717 \| 0.4899 \| 0.6717 \| 0.8196 \| \| 0.4026 \| 10.7547 \| 570 \| 0.6902 \| 0.4899 \| 0.6902 \| 0.8308 \| \| 0.4026 \| 10.7925 \| 572 \| 0.6270 \| 0.5578 \| 0.6270 \| 0.7918 \| \| 0.4026 \| 10.8302 \| 574 \| 0.5758 \| 0.5919 \| 0.5758 \| 0.7588 \| \| 0.4026 \| 10.8679 \| 576 \| 0.5609 \| 0.5746 \| 0.5609 \| 0.7489 \| \| 0.4026 \| 10.9057 \| 578 \| 0.5661 \| 0.5514 \| 0.5661 \| 0.7524 \| \| 0.4026 \| 10.9434 \| 580 \| 0.5552 \| 0.5593 \| 0.5552 \| 0.7451 \| \| 0.4026 \| 10.9811 \| 582 \| 0.5368 \| 0.5970 \| 0.5368 \| 0.7326 \| \| 0.4026 \| 11.0189 \| 584 \| 0.5309 \| 0.5560 \| 0.5309 \| 0.7286 \| \| 0.4026 \| 11.0566 \| 586 \| 0.5418 \| 0.5589 \| 0.5418 \| 0.7361 \| \| 0.4026 \| 11.0943 \| 588 \| 0.5484 \| 0.5777 \| 0.5484 \| 0.7406 \| \| 0.4026 \| 11.1321 \| 590 \| 0.5748 \| 0.5442 \| 0.5748 \| 0.7582 \| \| 0.4026 \| 11.1698 \| 592 \| 0.5988 \| 0.5629 \| 0.5988 \| 0.7738 \| \| 0.4026 \| 11.2075 \| 594 \| 0.5828 \| 0.5570 \| 0.5828 \| 0.7634 \| \| 0.4026 \| 11.2453 \| 596 \| 0.5513 \| 0.6214 \| 0.5513 \| 0.7425 \| \| 0.4026 \| 11.2830 \| 598 \| 0.5608 \| 0.5872 \| 0.5608 \| 0.7489 \| \| 0.4026 \| 11.3208 \| 600 \| 0.5678 \| 0.6336 \| 0.5678 \| 0.7535 \| \| 0.4026 \| 11.3585 \| 602 \| 0.5578 \| 0.6292 \| 0.5578 \| 0.7469 \| \| 0.4026 \| 11.3962 \| 604 \| 0.5570 \| 0.6111 \| 0.5570 \| 0.7463 \| \| 0.4026 \| 11.4340 \| 606 \| 0.6239 \| 0.5537 \| 0.6239 \| 0.7899 \| \| 0.4026 \| 11.4717 \| 608 \| 0.6865 \| 0.5001 \| 0.6865 \| 0.8285 \| \| 0.4026 \| 11.5094 \| 610 \| 0.6768 \| 0.5178 \| 0.6768 \| 0.8227 \| \| 0.4026 \| 11.5472 \| 612 \| 0.5969 \| 0.5299 \| 0.5969 \| 0.7726 \| \| 0.4026 \| 11.5849 \| 614 \| 0.5379 \| 0.6202 \| 0.5379 \| 0.7334 \| \| 0.4026 \| 11.6226 \| 616 \| 0.5269 \| 0.5943 \| 0.5269 \| 0.7259 \| \| 0.4026 \| 11.6604 \| 618 \| 0.5273 \| 0.5522 \| 0.5273 \| 0.7262 \| \| 0.4026 \| 11.6981 \| 620 \| 0.5315 \| 0.4704 \| 0.5315 \| 0.7290 \| \| 0.4026 \| 11.7358 \| 622 \| 0.5357 \| 0.4693 \| 0.5357 \| 0.7319 \| \| 0.4026 \| 11.7736 \| 624 \| 0.5408 \| 0.4763 \| 0.5408 \| 0.7354 \| \| 0.4026 \| 11.8113 \| 626 \| 0.5448 \| 0.5294 \| 0.5448 \| 0.7381 \| \| 0.4026 \| 11.8491 \| 628 \| 0.5527 \| 0.5948 \| 0.5527 \| 0.7434 \| \| 0.4026 \| 11.8868 \| 630 \| 0.5598 \| 0.6508 \| 0.5598 \| 0.7482 \| \| 0.4026 \| 11.9245 \| 632 \| 0.5630 \| 0.6100 \| 0.5630 \| 0.7504 \| \| 0.4026 \| 11.9623 \| 634 \| 0.5638 \| 0.5968 \| 0.5638 \| 0.7509 \| \| 0.4026 \| 12.0 \| 636 \| 0.5580 \| 0.6151 \| 0.5580 \| 0.7470 \| \| 0.4026 \| 12.0377 \| 638 \| 0.5523 \| 0.6151 \| 0.5523 \| 0.7432 \| \| 0.4026 \| 12.0755 \| 640 \| 0.5518 \| 0.5886 \| 0.5518 \| 0.7428 \| \| 0.4026 \| 12.1132 \| 642 \| 0.5606 \| 0.5969 \| 0.5606 \| 0.7487 \| \| 0.4026 \| 12.1509 \| 644 \| 0.5594 \| 0.5722 \| 0.5594 \| 0.7479 \| \| 0.4026 \| 12.1887 \| 646 \| 0.5685 \| 0.53 \| 0.5685 \| 0.7540 \| \| 0.4026 \| 12.2264 \| 648 \| 0.5943 \| 0.5674 \| 0.5943 \| 0.7709 \| \| 0.4026 \| 12.2642 \| 650 \| 0.6236 \| 0.6040 \| 0.6236 \| 0.7897 \| \| 0.4026 \| 12.3019 \| 652 \| 0.6388 \| 0.6125 \| 0.6388 \| 0.7992 \| \| 0.4026 \| 12.3396 \| 654 \| 0.6041 \| 0.6178 \| 0.6041 \| 0.7772 \| \| 0.4026 \| 12.3774 \| 656 \| 0.5825 \| 0.6264 \| 0.5825 \| 0.7632 \| \| 0.4026 \| 12.4151 \| 658 \| 0.5679 \| 0.5762 \| 0.5679 \| 0.7536 \| \| 0.4026 \| 12.4528 \| 660 \| 0.5633 \| 0.5067 \| 0.5633 \| 0.7505 \| \| 0.4026 \| 12.4906 \| 662 \| 0.5971 \| 0.4847 \| 0.5971 \| 0.7727 \| \| 0.4026 \| 12.5283 \| 664 \| 0.6482 \| 0.4899 \| 0.6482 \| 0.8051 \| \| 0.4026 \| 12.5660 \| 666 \| 0.6779 \| 0.5240 \| 0.6779 \| 0.8234 \| \| 0.4026 \| 12.6038 \| 668 \| 0.6705 \| 0.5282 \| 0.6705 \| 0.8189 \| \| 0.4026 \| 12.6415 \| 670 \| 0.6883 \| 0.5501 \| 0.6883 \| 0.8296 \| \| 0.4026 \| 12.6792 \| 672 \| 0.7226 \| 0.5104 \| 0.7226 \| 0.8501 \| \| 0.4026 \| 12.7170 \| 674 \| 0.6862 \| 0.5238 \| 0.6862 \| 0.8284 \| \| 0.4026 \| 12.7547 \| 676 \| 0.6551 \| 0.5396 \| 0.6551 \| 0.8094 \| \| 0.4026 \| 12.7925 \| 678 \| 0.6419 \| 0.5340 \| 0.6419 \| 0.8012 \| \| 0.4026 \| 12.8302 \| 680 \| 0.5884 \| 0.5355 \| 0.5884 \| 0.7671 \| \| 0.4026 \| 12.8679 \| 682 \| 0.5400 \| 0.5896 \| 0.5400 \| 0.7349 \| \| 0.4026 \| 12.9057 \| 684 \| 0.5287 \| 0.5767 \| 0.5287 \| 0.7271 \| \| 0.4026 \| 12.9434 \| 686 \| 0.5255 \| 0.4666 \| 0.5255 \| 0.7249 \| \| 0.4026 \| 12.9811 \| 688 \| 0.5244 \| 0.4816 \| 0.5244 \| 0.7241 \| \| 0.4026 \| 13.0189 \| 690 \| 0.5278 \| 0.5004 \| 0.5278 \| 0.7265 \| \| 0.4026 \| 13.0566 \| 692 \| 0.5362 \| 0.5856 \| 0.5362 \| 0.7322 \| \| 0.4026 \| 13.0943 \| 694 \| 0.5394 \| 0.5211 \| 0.5394 \| 0.7345 \| \| 0.4026 \| 13.1321 \| 696 \| 0.5516 \| 0.5197 \| 0.5516 \| 0.7427 \| \| 0.4026 \| 13.1698 \| 698 \| 0.5498 \| 0.5197 \| 0.5498 \| 0.7415 \| \| 0.4026 \| 13.2075 \| 700 \| 0.5545 \| 0.5197 \| 0.5545 \| 0.7447 \| \| 0.4026 \| 13.2453 \| 702 \| 0.5731 \| 0.5223 \| 0.5731 \| 0.7570 \| \| 0.4026 \| 13.2830 \| 704 \| 0.5552 \| 0.5197 \| 0.5552 \| 0.7451 \| \| 0.4026 \| 13.3208 \| 706 \| 0.5549 \| 0.5197 \| 0.5549 \| 0.7449 \| \| 0.4026 \| 13.3585 \| 708 \| 0.5819 \| 0.5010 \| 0.5819 \| 0.7628 \| \| 0.4026 \| 13.3962 \| 710 \| 0.5824 \| 0.4920 \| 0.5824 \| 0.7632 \| \| 0.4026 \| 13.4340 \| 712 \| 0.5841 \| 0.5010 \| 0.5841 \| 0.7643 \| \| 0.4026 \| 13.4717 \| 714 \| 0.5661 \| 0.4740 \| 0.5661 \| 0.7524 \| \| 0.4026 \| 13.5094 \| 716 \| 0.5719 \| 0.5130 \| 0.5719 \| 0.7562 \| \| 0.4026 \| 13.5472 \| 718 \| 0.5917 \| 0.5262 \| 0.5917 \| 0.7692 \| \| 0.4026 \| 13.5849 \| 720 \| 0.6151 \| 0.5205 \| 0.6151 \| 0.7843 \| \| 0.4026 \| 13.6226 \| 722 \| 0.6434 \| 0.5072 \| 0.6434 \| 0.8021 \| \| 0.4026 \| 13.6604 \| 724 \| 0.6276 \| 0.4949 \| 0.6276 \| 0.7922 \| \| 0.4026 \| 13.6981 \| 726 \| 0.5934 \| 0.4935 \| 0.5934 \| 0.7703 \| \| 0.4026 \| 13.7358 \| 728 \| 0.5870 \| 0.4908 \| 0.5870 \| 0.7661 \| \| 0.4026 \| 13.7736 \| 730 \| 0.5700 \| 0.5524 \| 0.5700 \| 0.7550 \| \| 0.4026 \| 13.8113 \| 732 \| 0.5656 \| 0.6182 \| 0.5656 \| 0.7520 \| \| 0.4026 \| 13.8491 \| 734 \| 0.5804 \| 0.6054 \| 0.5804 \| 0.7619 \| \| 0.4026 \| 13.8868 \| 736 \| 0.6192 \| 0.5462 \| 0.6192 \| 0.7869 \| \| 0.4026 \| 13.9245 \| 738 \| 0.6436 \| 0.5109 \| 0.6436 \| 0.8022 \| \| 0.4026 \| 13.9623 \| 740 \| 0.6516 \| 0.5066 \| 0.6516 \| 0.8072 \| \| 0.4026 \| 14.0 \| 742 \| 0.6361 \| 0.5176 \| 0.6361 \| 0.7976 \| \| 0.4026 \| 14.0377 \| 744 \| 0.6154 \| 0.5101 \| 0.6154 \| 0.7845 \| \| 0.4026 \| 14.0755 \| 746 \| 0.5645 \| 0.5878 \| 0.5645 \| 0.7513 \| \| 0.4026 \| 14.1132 \| 748 \| 0.5596 \| 0.6190 \| 0.5596 \| 0.7480 \| \| 0.4026 \| 14.1509 \| 750 \| 0.5807 \| 0.5571 \| 0.5807 \| 0.7621 \| \| 0.4026 \| 14.1887 \| 752 \| 0.5913 \| 0.5840 \| 0.5913 \| 0.7689 \| \| 0.4026 \| 14.2264 \| 754 \| 0.5706 \| 0.6046 \| 0.5706 \| 0.7554 \| \| 0.4026 \| 14.2642 \| 756 \| 0.5529 \| 0.6461 \| 0.5529 \| 0.7436 \| \| 0.4026 \| 14.3019 \| 758 \| 0.5776 \| 0.5482 \| 0.5776 \| 0.7600 \| \| 0.4026 \| 14.3396 \| 760 \| 0.6419 \| 0.5207 \| 0.6419 \| 0.8012 \| \| 0.4026 \| 14.3774 \| 762 \| 0.6703 \| 0.4790 \| 0.6703 \| 0.8187 \| \| 0.4026 \| 14.4151 \| 764 \| 0.6680 \| 0.4916 \| 0.6680 \| 0.8173 \| \| 0.4026 \| 14.4528 \| 766 \| 0.6454 \| 0.5284 \| 0.6454 \| 0.8034 \| \| 0.4026 \| 14.4906 \| 768 \| 0.5906 \| 0.5660 \| 0.5906 \| 0.7685 \| \| 0.4026 \| 14.5283 \| 770 \| 0.5657 \| 0.6221 \| 0.5657 \| 0.7521 \| \| 0.4026 \| 14.5660 \| 772 \| 0.5493 \| 0.6707 \| 0.5493 \| 0.7411 \| \| 0.4026 \| 14.6038 \| 774 \| 0.5489 \| 0.6429 \| 0.5489 \| 0.7409 \| \| 0.4026 \| 14.6415 \| 776 \| 0.5699 \| 0.5510 \| 0.5699 \| 0.7549 \| \| 0.4026 \| 14.6792 \| 778 \| 0.5806 \| 0.5425 \| 0.5806 \| 0.7619 \| \| 0.4026 \| 14.7170 \| 780 \| 0.5693 \| 0.5514 \| 0.5693 \| 0.7545 \| \| 0.4026 \| 14.7547 \| 782 \| 0.5407 \| 0.6059 \| 0.5407 \| 0.7354 \| \| 0.4026 \| 14.7925 \| 784 \| 0.5329 \| 0.6322 \| 0.5329 \| 0.7300 \| \| 0.4026 \| 14.8302 \| 786 \| 0.5516 \| 0.6479 \| 0.5516 \| 0.7427 \| \| 0.4026 \| 14.8679 \| 788 \| 0.6065 \| 0.5923 \| 0.6065 \| 0.7788 \| \| 0.4026 \| 14.9057 \| 790 \| 0.6305 \| 0.5952 \| 0.6305 \| 0.7941 \| \| 0.4026 \| 14.9434 \| 792 \| 0.6533 \| 0.5898 \| 0.6533 \| 0.8082 \| \| 0.4026 \| 14.9811 \| 794 \| 0.7234 \| 0.4894 \| 0.7234 \| 0.8505 \| \| 0.4026 \| 15.0189 \| 796 \| 0.7686 \| 0.4736 \| 0.7686 \| 0.8767 \| \| 0.4026 \| 15.0566 \| 798 \| 0.7126 \| 0.4996 \| 0.7126 \| 0.8441 \| \| 0.4026 \| 15.0943 \| 800 \| 0.6281 \| 0.5070 \| 0.6281 \| 0.7925 \| \| 0.4026 \| 15.1321 \| 802 \| 0.5525 \| 0.6103 \| 0.5525 \| 0.7433 \| \| 0.4026 \| 15.1698 \| 804 \| 0.5437 \| 0.6582 \| 0.5437 \| 0.7373 \| \| 0.4026 \| 15.2075 \| 806 \| 0.5752 \| 0.6160 \| 0.5752 \| 0.7584 \| \| 0.4026 \| 15.2453 \| 808 \| 0.5765 \| 0.6462 \| 0.5765 \| 0.7593 \| \| 0.4026 \| 15.2830 \| 810 \| 0.5650 \| 0.6936 \| 0.5650 \| 0.7517 \| \| 0.4026 \| 15.3208 \| 812 \| 0.5896 \| 0.6098 \| 0.5896 \| 0.7679 \| \| 0.4026 \| 15.3585 \| 814 \| 0.6334 \| 0.5324 \| 0.6334 \| 0.7958 \| \| 0.4026 \| 15.3962 \| 816 \| 0.6662 \| 0.5117 \| 0.6662 \| 0.8162 \| \| 0.4026 \| 15.4340 \| 818 \| 0.6409 \| 0.4959 \| 0.6409 \| 0.8006 \| \| 0.4026 \| 15.4717 \| 820 \| 0.5866 \| 0.5220 \| 0.5866 \| 0.7659 \| \| 0.4026 \| 15.5094 \| 822 \| 0.5443 \| 0.5510 \| 0.5443 \| 0.7378 \| \| 0.4026 \| 15.5472 \| 824 \| 0.5345 \| 0.5723 \| 0.5345 \| 0.7311 \| \| 0.4026 \| 15.5849 \| 826 \| 0.5417 \| 0.5702 \| 0.5417 \| 0.7360 \| \| 0.4026 \| 15.6226 \| 828 \| 0.5403 \| 0.6262 \| 0.5403 \| 0.7350 \| \| 0.4026 \| 15.6604 \| 830 \| 0.5824 \| 0.5425 \| 0.5824 \| 0.7631 \| \| 0.4026 \| 15.6981 \| 832 \| 0.6294 \| 0.5107 \| 0.6294 \| 0.7933 \| \| 0.4026 \| 15.7358 \| 834 \| 0.6359 \| 0.5107 \| 0.6359 \| 0.7974 \| \| 0.4026 \| 15.7736 \| 836 \| 0.5840 \| 0.5226 \| 0.5840 \| 0.7642 \| \| 0.4026 \| 15.8113 \| 838 \| 0.5516 \| 0.5326 \| 0.5516 \| 0.7427 \| \| 0.4026 \| 15.8491 \| 840 \| 0.5465 \| 0.4654 \| 0.5465 \| 0.7392 \| \| 0.4026 \| 15.8868 \| 842 \| 0.5452 \| 0.5185 \| 0.5452 \| 0.7384 \| \| 0.4026 \| 15.9245 \| 844 \| 0.5479 \| 0.5540 \| 0.5479 \| 0.7402 \| \| 0.4026 \| 15.9623 \| 846 \| 0.5709 \| 0.5478 \| 0.5709 \| 0.7556 \| \| 0.4026 \| 16.0 \| 848 \| 0.5965 \| 0.5244 \| 0.5965 \| 0.7723 \| \| 0.4026 \| 16.0377 \| 850 \| 0.5855 \| 0.5244 \| 0.5855 \| 0.7652 \| \| 0.4026 \| 16.0755 \| 852 \| 0.5563 \| 0.5236 \| 0.5563 \| 0.7458 \| \| 0.4026 \| 16.1132 \| 854 \| 0.5512 \| 0.5236 \| 0.5512 \| 0.7425 \| \| 0.4026 \| 16.1509 \| 856 \| 0.5425 \| 0.5236 \| 0.5425 \| 0.7366 \| \| 0.4026 \| 16.1887 \| 858 \| 0.5488 \| 0.5236 \| 0.5488 \| 0.7408 \| \| 0.4026 \| 16.2264 \| 860 \| 0.5559 \| 0.4886 \| 0.5559 \| 0.7456 \| \| 0.4026 \| 16.2642 \| 862 \| 0.5384 \| 0.5155 \| 0.5384 \| 0.7338 \| \| 0.4026 \| 16.3019 \| 864 \| 0.5216 \| 0.4828 \| 0.5216 \| 0.7222 \| \| 0.4026 \| 16.3396 \| 866 \| 0.5268 \| 0.5323 \| 0.5268 \| 0.7258 \| \| 0.4026 \| 16.3774 \| 868 \| 0.5287 \| 0.5185 \| 0.5287 \| 0.7271 \| \| 0.4026 \| 16.4151 \| 870 \| 0.5528 \| 0.5339 \| 0.5528 \| 0.7435 \| \| 0.4026 \| 16.4528 \| 872 \| 0.6222 \| 0.5080 \| 0.6222 \| 0.7888 \| \| 0.4026 \| 16.4906 \| 874 \| 0.7171 \| 0.5038 \| 0.7171 \| 0.8468 \| \| 0.4026 \| 16.5283 \| 876 \| 0.7497 \| 0.4812 \| 0.7497 \| 0.8658 \| \| 0.4026 \| 16.5660 \| 878 \| 0.6911 \| 0.4845 \| 0.6911 \| 0.8313 \| \| 0.4026 \| 16.6038 \| 880 \| 0.6496 \| 0.5364 \| 0.6496 \| 0.8060 \| \| 0.4026 \| 16.6415 \| 882 \| 0.6414 \| 0.5208 \| 0.6414 \| 0.8009 \| \| 0.4026 \| 16.6792 \| 884 \| 0.5922 \| 0.5420 \| 0.5922 \| 0.7695 \| \| 0.4026 \| 16.7170 \| 886 \| 0.5651 \| 0.6104 \| 0.5651 \| 0.7517 \| \| 0.4026 \| 16.7547 \| 888 \| 0.5588 \| 0.5669 \| 0.5588 \| 0.7475 \| \| 0.4026 \| 16.7925 \| 890 \| 0.5557 \| 0.5481 \| 0.5557 \| 0.7455 \| \| 0.4026 \| 16.8302 \| 892 \| 0.5771 \| 0.4740 \| 0.5771 \| 0.7597 \| \| 0.4026 \| 16.8679 \| 894 \| 0.5899 \| 0.4550 \| 0.5899 \| 0.7680 \| \| 0.4026 \| 16.9057 \| 896 \| 0.5709 \| 0.4102 \| 0.5709 \| 0.7556 \| \| 0.4026 \| 16.9434 \| 898 \| 0.5444 \| 0.4642 \| 0.5444 \| 0.7378 \| \| 0.4026 \| 16.9811 \| 900 \| 0.5414 \| 0.5285 \| 0.5414 \| 0.7358 \| \| 0.4026 \| 17.0189 \| 902 \| 0.5508 \| 0.5601 \| 0.5508 \| 0.7422 \| \| 0.4026 \| 17.0566 \| 904 \| 0.5689 \| 0.5713 \| 0.5689 \| 0.7543 \| \| 0.4026 \| 17.0943 \| 906 \| 0.6032 \| 0.5619 \| 0.6032 \| 0.7766 \| \| 0.4026 \| 17.1321 \| 908 \| 0.6153 \| 0.5504 \| 0.6153 \| 0.7844 \| \| 0.4026 \| 17.1698 \| 910 \| 0.6342 \| 0.5334 \| 0.6342 \| 0.7964 \| \| 0.4026 \| 17.2075 \| 912 \| 0.6339 \| 0.5214 \| 0.6339 \| 0.7962 \| \| 0.4026 \| 17.2453 \| 914 \| 0.6112 \| 0.5437 \| 0.6112 \| 0.7818 \| \| 0.4026 \| 17.2830 \| 916 \| 0.5990 \| 0.5355 \| 0.5990 \| 0.7739 \| \| 0.4026 \| 17.3208 \| 918 \| 0.6068 \| 0.5536 \| 0.6068 \| 0.7789 \| \| 0.4026 \| 17.3585 \| 920 \| 0.6082 \| 0.6025 \| 0.6082 \| 0.7799 \| \| 0.4026 \| 17.3962 \| 922 \| 0.6076 \| 0.5941 \| 0.6076 \| 0.7795 \| \| 0.4026 \| 17.4340 \| 924 \| 0.5976 \| 0.5650 \| 0.5976 \| 0.7731 \| \| 0.4026 \| 17.4717 \| 926 \| 0.5777 \| 0.5848 \| 0.5777 \| 0.7601 \| \| 0.4026 \| 17.5094 \| 928 \| 0.5699 \| 0.5968 \| 0.5699 \| 0.7549 \| \| 0.4026 \| 17.5472 \| 930 \| 0.5633 \| 0.5972 \| 0.5633 \| 0.7505 \| \| 0.4026 \| 17.5849 \| 932 \| 0.5612 \| 0.5489 \| 0.5612 \| 0.7491 \| \| 0.4026 \| 17.6226 \| 934 \| 0.5579 \| 0.5320 \| 0.5579 \| 0.7469 \| \| 0.4026 \| 17.6604 \| 936 \| 0.5655 \| 0.5476 \| 0.5655 \| 0.7520 \| \| 0.4026 \| 17.6981 \| 938 \| 0.5781 \| 0.5565 \| 0.5781 \| 0.7603 \| \| 0.4026 \| 17.7358 \| 940 \| 0.5921 \| 0.5649 \| 0.5921 \| 0.7695 \| \| 0.4026 \| 17.7736 \| 942 \| 0.5825 \| 0.5811 \| 0.5825 \| 0.7632 \| \| 0.4026 \| 17.8113 \| 944 \| 0.5678 \| 0.5728 \| 0.5678 \| 0.7535 \| \| 0.4026 \| 17.8491 \| 946 \| 0.5673 \| 0.5684 \| 0.5673 \| 0.7532 \| \| 0.4026 \| 17.8868 \| 948 \| 0.5647 \| 0.5402 \| 0.5647 \| 0.7514 \| \| 0.4026 \| 17.9245 \| 950 \| 0.5597 \| 0.5323 \| 0.5597 \| 0.7481 \| \| 0.4026 \| 17.9623 \| 952 \| 0.5595 \| 0.4975 \| 0.5595 \| 0.7480 \| \| 0.4026 \| 18.0 \| 954 \| 0.5616 \| 0.5131 \| 0.5616 \| 0.7494 \| \| 0.4026 \| 18.0377 \| 956 \| 0.5634 \| 0.5323 \| 0.5634 \| 0.7506 \| \| 0.4026 \| 18.0755 \| 958 \| 0.5776 \| 0.5176 \| 0.5776 \| 0.7600 \| \| 0.4026 \| 18.1132 \| 960 \| 0.5828 \| 0.5176 \| 0.5828 \| 0.7634 \| \| 0.4026 \| 18.1509 \| 962 \| 0.5774 \| 0.4913 \| 0.5774 \| 0.7599 \| \| 0.4026 \| 18.1887 \| 964 \| 0.5772 \| 0.4913 \| 0.5772 \| 0.7598 \| \| 0.4026 \| 18.2264 \| 966 \| 0.5806 \| 0.4913 \| 0.5806 \| 0.7620 \| \| 0.4026 \| 18.2642 \| 968 \| 0.5831 \| 0.4928 \| 0.5831 \| 0.7636 \| \| 0.4026 \| 18.3019 \| 970 \| 0.5795 \| 0.5019 \| 0.5795 \| 0.7612 \| \| 0.4026 \| 18.3396 \| 972 \| 0.5723 \| 0.5312 \| 0.5723 \| 0.7565 \| \| 0.4026 \| 18.3774 \| 974 \| 0.5806 \| 0.5500 \| 0.5806 \| 0.7620 \| \| 0.4026 \| 18.4151 \| 976 \| 0.5773 \| 0.5500 \| 0.5773 \| 0.7598 \| \| 0.4026 \| 18.4528 \| 978 \| 0.5773 \| 0.5500 \| 0.5773 \| 0.7598 \| \| 0.4026 \| 18.4906 \| 980 \| 0.5722 \| 0.5164 \| 0.5722 \| 0.7565 \| \| 0.4026 \| 18.5283 \| 982 \| 0.5644 \| 0.4888 \| 0.5644 \| 0.7513 \| \| 0.4026 \| 18.5660 \| 984 \| 0.5568 \| 0.4864 \| 0.5568 \| 0.7462 \| \| 0.4026 \| 18.6038 \| 986 \| 0.5575 \| 0.5078 \| 0.5575 \| 0.7467 \| \| 0.4026 \| 18.6415 \| 988 \| 0.5570 \| 0.5078 \| 0.5570 \| 0.7463 \| \| 0.4026 \| 18.6792 \| 990 \| 0.5582 \| 0.5004 \| 0.5582 \| 0.7471 \| \| 0.4026 \| 18.7170 \| 992 \| 0.5635 \| 0.4835 \| 0.5635 \| 0.7506 \| \| 0.4026 \| 18.7547 \| 994 \| 0.5736 \| 0.4812 \| 0.5736 \| 0.7574 \| \| 0.4026 \| 18.7925 \| 996 \| 0.5634 \| 0.4904 \| 0.5634 \| 0.7506 \| \| 0.4026 \| 18.8302 \| 998 \| 0.5571 \| 0.5147 \| 0.5571 \| 0.7464 \| \| 0.0707 \| 18.8679 \| 1000 \| 0.5565 \| 0.5421 \| 0.5565 \| 0.7460 \| \| 0.0707 \| 18.9057 \| 1002 \| 0.5585 \| 0.4857 \| 0.5585 \| 0.7473 \| \| 0.0707 \| 18.9434 \| 1004 \| 0.5899 \| 0.5059 \| 0.5899 \| 0.7681 \| \| 0.0707 \| 18.9811 \| 1006 \| 0.6331 \| 0.4695 \| 0.6331 \| 0.7957 \| \| 0.0707 \| 19.0189 \| 1008 \| 0.6374 \| 0.5029 \| 0.6374 \| 0.7983 \| \| 0.0707 \| 19.0566 \| 1010 \| 0.6404 \| 0.5029 \| 0.6404 \| 0.8003 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
deepnet111/sn9-3b-018	deepnet111	2025-01-15T15:37:50Z	178	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-15T15:35:47Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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cabustillo13/roberta-base-bne-platzi-project-nlp	cabustillo13	2025-01-15T15:37:14Z	14	0	transformers	[ "transformers", "tensorboard", "safetensors", "roberta", "text-classification", "generated_from_trainer", "base_model:BSC-LT/roberta-base-bne", "base_model:finetune:BSC-LT/roberta-base-bne", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T04:08:44Z	--- library_name: transformers license: apache-2.0 base_model: BSC-TeMU/roberta-base-bne tags: - generated_from_trainer metrics: - accuracy model-index: - name: roberta-base-bne-platzi-project-nlp results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # roberta-base-bne-platzi-project-nlp This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4563 - Accuracy: 0.8538 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.3594 \| 1.0 \| 2500 \| 0.3971 \| 0.8436 \| \| 0.2582 \| 2.0 \| 5000 \| 0.4563 \| 0.8538 \| ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Tokenizers 0.21.0
mradermacher/WiNGPT-Babel-GGUF	mradermacher	2025-01-15T15:36:52Z	262	0	transformers	[ "transformers", "gguf", "translation", "multilingual", "en", "zh", "base_model:winninghealth/WiNGPT-Babel", "base_model:quantized:winninghealth/WiNGPT-Babel", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	translation	2025-01-15T15:23:35Z	--- base_model: winninghealth/WiNGPT-Babel language: - en - zh library_name: transformers license: apache-2.0 quantized_by: mradermacher tags: - translation - multilingual --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> static quants of https://huggingface.co/winninghealth/WiNGPT-Babel <!-- provided-files --> weighted/imatrix quants are available at https://huggingface.co/mradermacher/WiNGPT-Babel-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q2_K.gguf) \| Q2_K \| 0.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_S.gguf) \| Q3_K_S \| 0.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_M.gguf) \| Q3_K_M \| 0.9 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_L.gguf) \| Q3_K_L \| 1.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.IQ4_XS.gguf) \| IQ4_XS \| 1.0 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q4_K_S.gguf) \| Q4_K_S \| 1.0 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q4_K_M.gguf) \| Q4_K_M \| 1.1 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q5_K_S.gguf) \| Q5_K_S \| 1.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q5_K_M.gguf) \| Q5_K_M \| 1.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q6_K.gguf) \| Q6_K \| 1.4 \| very good quality \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q8_0.gguf) \| Q8_0 \| 1.7 \| fast, best quality \| \| [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.f16.gguf) \| f16 \| 3.2 \| 16 bpw, overkill \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->
lesso06/933a3df0-e8dc-4b5f-808c-5edc7e3ea567	lesso06	2025-01-15T15:35:57Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:32:36Z	--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 933a3df0-e8dc-4b5f-808c-5edc7e3ea567 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: true chat_template: llama3 datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso06/933a3df0-e8dc-4b5f-808c-5edc7e3ea567 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 933a3df0-e8dc-4b5f-808c-5edc7e3ea567 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6562 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 3.5612 \| 0.0035 \| 1 \| 3.7545 \| \| 3.549 \| 0.0177 \| 5 \| 3.5143 \| \| 2.8654 \| 0.0354 \| 10 \| 2.2111 \| \| 1.9689 \| 0.0531 \| 15 \| 1.8258 \| \| 1.7188 \| 0.0707 \| 20 \| 1.6879 \| \| 1.7133 \| 0.0884 \| 25 \| 1.6562 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
August4293/Llama3.1-8B-PRM-Deepseek-Data-4bit	August4293	2025-01-15T15:35:53Z	16	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2025-01-15T15:33:26Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
MayBashendy/ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization	MayBashendy	2025-01-15T15:35:39Z	7	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T15:17:34Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8239 - Qwk: 0.6567 - Mse: 0.8239 - Rmse: 0.9077 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:------:\|:----:\|:---------------:\|:------:\|:------:\|:------:\| \| No log \| 0.0206 \| 2 \| 6.6386 \| 0.0308 \| 6.6386 \| 2.5766 \| \| No log \| 0.0412 \| 4 \| 4.3409 \| 0.0894 \| 4.3409 \| 2.0835 \| \| No log \| 0.0619 \| 6 \| 2.9340 \| 0.1149 \| 2.9340 \| 1.7129 \| \| No log \| 0.0825 \| 8 \| 2.5329 \| 0.0970 \| 2.5329 \| 1.5915 \| \| No log \| 0.1031 \| 10 \| 2.0854 \| 0.1260 \| 2.0854 \| 1.4441 \| \| No log \| 0.1237 \| 12 \| 1.7133 \| 0.2655 \| 1.7133 \| 1.3089 \| \| No log \| 0.1443 \| 14 \| 1.5473 \| 0.1852 \| 1.5473 \| 1.2439 \| \| No log \| 0.1649 \| 16 \| 1.5422 \| 0.2832 \| 1.5422 \| 1.2419 \| \| No log \| 0.1856 \| 18 \| 1.8395 \| 0.2333 \| 1.8395 \| 1.3563 \| \| No log \| 0.2062 \| 20 \| 2.4245 \| 0.0541 \| 2.4245 \| 1.5571 \| \| No log \| 0.2268 \| 22 \| 2.2319 \| 0.0699 \| 2.2319 \| 1.4940 \| \| No log \| 0.2474 \| 24 \| 1.6828 \| 0.2951 \| 1.6828 \| 1.2972 \| \| No log \| 0.2680 \| 26 \| 1.1992 \| 0.4874 \| 1.1992 \| 1.0951 \| \| No log \| 0.2887 \| 28 \| 1.5225 \| 0.2000 \| 1.5225 \| 1.2339 \| \| No log \| 0.3093 \| 30 \| 1.3550 \| 0.3966 \| 1.3550 \| 1.1641 \| \| No log \| 0.3299 \| 32 \| 1.0281 \| 0.6015 \| 1.0281 \| 1.0139 \| \| No log \| 0.3505 \| 34 \| 1.1542 \| 0.5037 \| 1.1542 \| 1.0743 \| \| No log \| 0.3711 \| 36 \| 1.2467 \| 0.5211 \| 1.2467 \| 1.1166 \| \| No log \| 0.3918 \| 38 \| 1.0146 \| 0.6197 \| 1.0146 \| 1.0073 \| \| No log \| 0.4124 \| 40 \| 0.9003 \| 0.64 \| 0.9003 \| 0.9489 \| \| No log \| 0.4330 \| 42 \| 0.8324 \| 0.6918 \| 0.8324 \| 0.9123 \| \| No log \| 0.4536 \| 44 \| 0.8800 \| 0.7329 \| 0.8800 \| 0.9381 \| \| No log \| 0.4742 \| 46 \| 1.3931 \| 0.5829 \| 1.3931 \| 1.1803 \| \| No log \| 0.4948 \| 48 \| 1.2730 \| 0.6036 \| 1.2730 \| 1.1283 \| \| No log \| 0.5155 \| 50 \| 0.9855 \| 0.6667 \| 0.9855 \| 0.9927 \| \| No log \| 0.5361 \| 52 \| 1.0368 \| 0.5946 \| 1.0368 \| 1.0182 \| \| No log \| 0.5567 \| 54 \| 1.1082 \| 0.5517 \| 1.1082 \| 1.0527 \| \| No log \| 0.5773 \| 56 \| 1.0923 \| 0.5882 \| 1.0923 \| 1.0451 \| \| No log \| 0.5979 \| 58 \| 1.0331 \| 0.6 \| 1.0331 \| 1.0164 \| \| No log \| 0.6186 \| 60 \| 0.9837 \| 0.6225 \| 0.9837 \| 0.9918 \| \| No log \| 0.6392 \| 62 \| 0.9091 \| 0.6323 \| 0.9091 \| 0.9535 \| \| No log \| 0.6598 \| 64 \| 0.8918 \| 0.6582 \| 0.8918 \| 0.9444 \| \| No log \| 0.6804 \| 66 \| 1.0270 \| 0.6471 \| 1.0270 \| 1.0134 \| \| No log \| 0.7010 \| 68 \| 0.9795 \| 0.6282 \| 0.9795 \| 0.9897 \| \| No log \| 0.7216 \| 70 \| 0.8182 \| 0.7059 \| 0.8182 \| 0.9046 \| \| No log \| 0.7423 \| 72 \| 0.8577 \| 0.7105 \| 0.8577 \| 0.9261 \| \| No log \| 0.7629 \| 74 \| 1.1304 \| 0.5769 \| 1.1304 \| 1.0632 \| \| No log \| 0.7835 \| 76 \| 1.3418 \| 0.5093 \| 1.3418 \| 1.1584 \| \| No log \| 0.8041 \| 78 \| 1.1096 \| 0.6125 \| 1.1096 \| 1.0534 \| \| No log \| 0.8247 \| 80 \| 0.9768 \| 0.6835 \| 0.9768 \| 0.9883 \| \| No log \| 0.8454 \| 82 \| 0.9448 \| 0.6800 \| 0.9448 \| 0.9720 \| \| No log \| 0.8660 \| 84 \| 1.1318 \| 0.5844 \| 1.1318 \| 1.0639 \| \| No log \| 0.8866 \| 86 \| 1.1446 \| 0.5503 \| 1.1446 \| 1.0699 \| \| No log \| 0.9072 \| 88 \| 1.0225 \| 0.6081 \| 1.0225 \| 1.0112 \| \| No log \| 0.9278 \| 90 \| 0.9466 \| 0.6494 \| 0.9466 \| 0.9729 \| \| No log \| 0.9485 \| 92 \| 0.9471 \| 0.6410 \| 0.9471 \| 0.9732 \| \| No log \| 0.9691 \| 94 \| 0.9464 \| 0.6369 \| 0.9464 \| 0.9728 \| \| No log \| 0.9897 \| 96 \| 0.9880 \| 0.6832 \| 0.9880 \| 0.9940 \| \| No log \| 1.0103 \| 98 \| 1.0383 \| 0.6220 \| 1.0383 \| 1.0190 \| \| No log \| 1.0309 \| 100 \| 0.9291 \| 0.6708 \| 0.9291 \| 0.9639 \| \| No log \| 1.0515 \| 102 \| 0.8811 \| 0.7051 \| 0.8811 \| 0.9387 \| \| No log \| 1.0722 \| 104 \| 0.8661 \| 0.6933 \| 0.8661 \| 0.9306 \| \| No log \| 1.0928 \| 106 \| 0.8505 \| 0.7320 \| 0.8505 \| 0.9222 \| \| No log \| 1.1134 \| 108 \| 0.9108 \| 0.6835 \| 0.9108 \| 0.9544 \| \| No log \| 1.1340 \| 110 \| 0.9671 \| 0.6545 \| 0.9671 \| 0.9834 \| \| No log \| 1.1546 \| 112 \| 0.8803 \| 0.7143 \| 0.8803 \| 0.9382 \| \| No log \| 1.1753 \| 114 \| 0.7077 \| 0.7927 \| 0.7077 \| 0.8412 \| \| No log \| 1.1959 \| 116 \| 0.6499 \| 0.7907 \| 0.6499 \| 0.8062 \| \| No log \| 1.2165 \| 118 \| 0.6344 \| 0.7977 \| 0.6344 \| 0.7965 \| \| No log \| 1.2371 \| 120 \| 0.7094 \| 0.7602 \| 0.7094 \| 0.8422 \| \| No log \| 1.2577 \| 122 \| 0.8116 \| 0.7425 \| 0.8116 \| 0.9009 \| \| No log \| 1.2784 \| 124 \| 0.8744 \| 0.6962 \| 0.8744 \| 0.9351 \| \| No log \| 1.2990 \| 126 \| 0.7462 \| 0.7407 \| 0.7462 \| 0.8638 \| \| No log \| 1.3196 \| 128 \| 0.5628 \| 0.8070 \| 0.5628 \| 0.7502 \| \| No log \| 1.3402 \| 130 \| 0.6567 \| 0.7831 \| 0.6567 \| 0.8103 \| \| No log \| 1.3608 \| 132 \| 0.9735 \| 0.6748 \| 0.9735 \| 0.9867 \| \| No log \| 1.3814 \| 134 \| 0.6423 \| 0.8024 \| 0.6423 \| 0.8014 \| \| No log \| 1.4021 \| 136 \| 0.6233 \| 0.8128 \| 0.6233 \| 0.7895 \| \| No log \| 1.4227 \| 138 \| 0.9567 \| 0.7437 \| 0.9567 \| 0.9781 \| \| No log \| 1.4433 \| 140 \| 0.9548 \| 0.7111 \| 0.9548 \| 0.9771 \| \| No log \| 1.4639 \| 142 \| 1.0082 \| 0.6144 \| 1.0082 \| 1.0041 \| \| No log \| 1.4845 \| 144 \| 0.9656 \| 0.6234 \| 0.9656 \| 0.9827 \| \| No log \| 1.5052 \| 146 \| 0.9097 \| 0.6941 \| 0.9097 \| 0.9538 \| \| No log \| 1.5258 \| 148 \| 0.8018 \| 0.6918 \| 0.8018 \| 0.8954 \| \| No log \| 1.5464 \| 150 \| 0.7871 \| 0.6918 \| 0.7871 \| 0.8872 \| \| No log \| 1.5670 \| 152 \| 0.8130 \| 0.6923 \| 0.8130 \| 0.9017 \| \| No log \| 1.5876 \| 154 \| 0.8739 \| 0.6883 \| 0.8739 \| 0.9348 \| \| No log \| 1.6082 \| 156 \| 0.9073 \| 0.6883 \| 0.9073 \| 0.9525 \| \| No log \| 1.6289 \| 158 \| 0.8979 \| 0.6797 \| 0.8979 \| 0.9476 \| \| No log \| 1.6495 \| 160 \| 0.9202 \| 0.7020 \| 0.9202 \| 0.9593 \| \| No log \| 1.6701 \| 162 \| 0.9533 \| 0.6933 \| 0.9533 \| 0.9764 \| \| No log \| 1.6907 \| 164 \| 1.0495 \| 0.6323 \| 1.0495 \| 1.0244 \| \| No log \| 1.7113 \| 166 \| 0.9693 \| 0.6667 \| 0.9693 \| 0.9845 \| \| No log \| 1.7320 \| 168 \| 0.9011 \| 0.7059 \| 0.9011 \| 0.9493 \| \| No log \| 1.7526 \| 170 \| 0.8788 \| 0.6914 \| 0.8788 \| 0.9375 \| \| No log \| 1.7732 \| 172 \| 0.8192 \| 0.7152 \| 0.8192 \| 0.9051 \| \| No log \| 1.7938 \| 174 \| 0.7623 \| 0.7738 \| 0.7623 \| 0.8731 \| \| No log \| 1.8144 \| 176 \| 0.6998 \| 0.7436 \| 0.6998 \| 0.8365 \| \| No log \| 1.8351 \| 178 \| 0.6744 \| 0.775 \| 0.6744 \| 0.8212 \| \| No log \| 1.8557 \| 180 \| 0.6923 \| 0.7882 \| 0.6923 \| 0.8321 \| \| No log \| 1.8763 \| 182 \| 1.0034 \| 0.6889 \| 1.0034 \| 1.0017 \| \| No log \| 1.8969 \| 184 \| 1.1008 \| 0.6243 \| 1.1008 \| 1.0492 \| \| No log \| 1.9175 \| 186 \| 0.8802 \| 0.6962 \| 0.8802 \| 0.9382 \| \| No log \| 1.9381 \| 188 \| 0.6508 \| 0.7432 \| 0.6508 \| 0.8067 \| \| No log \| 1.9588 \| 190 \| 0.6284 \| 0.7821 \| 0.6284 \| 0.7927 \| \| No log \| 1.9794 \| 192 \| 0.6294 \| 0.7547 \| 0.6294 \| 0.7933 \| \| No log \| 2.0 \| 194 \| 0.5511 \| 0.8187 \| 0.5511 \| 0.7424 \| \| No log \| 2.0206 \| 196 \| 0.6162 \| 0.8105 \| 0.6162 \| 0.7850 \| \| No log \| 2.0412 \| 198 \| 0.9315 \| 0.7263 \| 0.9315 \| 0.9651 \| \| No log \| 2.0619 \| 200 \| 1.2573 \| 0.6597 \| 1.2573 \| 1.1213 \| \| No log \| 2.0825 \| 202 \| 1.2732 \| 0.6136 \| 1.2732 \| 1.1283 \| \| No log \| 2.1031 \| 204 \| 1.0180 \| 0.6581 \| 1.0180 \| 1.0090 \| \| No log \| 2.1237 \| 206 \| 0.7410 \| 0.6803 \| 0.7410 \| 0.8608 \| \| No log \| 2.1443 \| 208 \| 0.5425 \| 0.7975 \| 0.5425 \| 0.7366 \| \| No log \| 2.1649 \| 210 \| 0.4957 \| 0.7879 \| 0.4957 \| 0.7041 \| \| No log \| 2.1856 \| 212 \| 0.5009 \| 0.8235 \| 0.5009 \| 0.7077 \| \| No log \| 2.2062 \| 214 \| 0.6764 \| 0.7727 \| 0.6764 \| 0.8225 \| \| No log \| 2.2268 \| 216 \| 0.8855 \| 0.7368 \| 0.8855 \| 0.9410 \| \| No log \| 2.2474 \| 218 \| 0.8688 \| 0.7018 \| 0.8688 \| 0.9321 \| \| No log \| 2.2680 \| 220 \| 0.7828 \| 0.7389 \| 0.7828 \| 0.8847 \| \| No log \| 2.2887 \| 222 \| 0.7133 \| 0.7285 \| 0.7133 \| 0.8446 \| \| No log \| 2.3093 \| 224 \| 0.7029 \| 0.7403 \| 0.7029 \| 0.8384 \| \| No log \| 2.3299 \| 226 \| 0.7274 \| 0.7468 \| 0.7274 \| 0.8529 \| \| No log \| 2.3505 \| 228 \| 0.7905 \| 0.7024 \| 0.7905 \| 0.8891 \| \| No log \| 2.3711 \| 230 \| 0.8163 \| 0.7024 \| 0.8163 \| 0.9035 \| \| No log \| 2.3918 \| 232 \| 0.6817 \| 0.7407 \| 0.6817 \| 0.8257 \| \| No log \| 2.4124 \| 234 \| 0.6279 \| 0.7898 \| 0.6279 \| 0.7924 \| \| No log \| 2.4330 \| 236 \| 0.6566 \| 0.7285 \| 0.6566 \| 0.8103 \| \| No log \| 2.4536 \| 238 \| 0.6737 \| 0.7432 \| 0.6737 \| 0.8208 \| \| No log \| 2.4742 \| 240 \| 0.6652 \| 0.7586 \| 0.6652 \| 0.8156 \| \| No log \| 2.4948 \| 242 \| 0.6573 \| 0.7133 \| 0.6573 \| 0.8108 \| \| No log \| 2.5155 \| 244 \| 0.6947 \| 0.7376 \| 0.6947 \| 0.8335 \| \| No log \| 2.5361 \| 246 \| 0.6919 \| 0.7532 \| 0.6919 \| 0.8318 \| \| No log \| 2.5567 \| 248 \| 0.7783 \| 0.7634 \| 0.7783 \| 0.8822 \| \| No log \| 2.5773 \| 250 \| 0.9080 \| 0.7725 \| 0.9080 \| 0.9529 \| \| No log \| 2.5979 \| 252 \| 0.7760 \| 0.7789 \| 0.7760 \| 0.8809 \| \| No log \| 2.6186 \| 254 \| 0.5427 \| 0.8046 \| 0.5427 \| 0.7367 \| \| No log \| 2.6392 \| 256 \| 0.5157 \| 0.8395 \| 0.5157 \| 0.7181 \| \| No log \| 2.6598 \| 258 \| 0.5074 \| 0.8199 \| 0.5074 \| 0.7123 \| \| No log \| 2.6804 \| 260 \| 0.5683 \| 0.7879 \| 0.5683 \| 0.7539 \| \| No log \| 2.7010 \| 262 \| 0.7725 \| 0.6994 \| 0.7725 \| 0.8789 \| \| No log \| 2.7216 \| 264 \| 0.9238 \| 0.6790 \| 0.9238 \| 0.9612 \| \| No log \| 2.7423 \| 266 \| 0.8716 \| 0.7152 \| 0.8716 \| 0.9336 \| \| No log \| 2.7629 \| 268 \| 0.7049 \| 0.7123 \| 0.7049 \| 0.8396 \| \| No log \| 2.7835 \| 270 \| 0.5827 \| 0.8280 \| 0.5827 \| 0.7634 \| \| No log \| 2.8041 \| 272 \| 0.5649 \| 0.8101 \| 0.5649 \| 0.7516 \| \| No log \| 2.8247 \| 274 \| 0.5398 \| 0.8323 \| 0.5398 \| 0.7347 \| \| No log \| 2.8454 \| 276 \| 0.5942 \| 0.8098 \| 0.5942 \| 0.7708 \| \| No log \| 2.8660 \| 278 \| 0.8162 \| 0.7 \| 0.8162 \| 0.9035 \| \| No log \| 2.8866 \| 280 \| 1.0026 \| 0.6341 \| 1.0026 \| 1.0013 \| \| No log \| 2.9072 \| 282 \| 1.0403 \| 0.6174 \| 1.0403 \| 1.0199 \| \| No log \| 2.9278 \| 284 \| 0.9378 \| 0.6968 \| 0.9378 \| 0.9684 \| \| No log \| 2.9485 \| 286 \| 0.7710 \| 0.7273 \| 0.7710 \| 0.8781 \| \| No log \| 2.9691 \| 288 \| 0.6648 \| 0.7758 \| 0.6648 \| 0.8153 \| \| No log \| 2.9897 \| 290 \| 0.6411 \| 0.7952 \| 0.6411 \| 0.8007 \| \| No log \| 3.0103 \| 292 \| 0.6512 \| 0.7719 \| 0.6512 \| 0.8070 \| \| No log \| 3.0309 \| 294 \| 0.6983 \| 0.7273 \| 0.6983 \| 0.8356 \| \| No log \| 3.0515 \| 296 \| 0.7335 \| 0.7051 \| 0.7335 \| 0.8565 \| \| No log \| 3.0722 \| 298 \| 0.7403 \| 0.7179 \| 0.7403 \| 0.8604 \| \| No log \| 3.0928 \| 300 \| 0.6836 \| 0.7179 \| 0.6836 \| 0.8268 \| \| No log \| 3.1134 \| 302 \| 0.6452 \| 0.7296 \| 0.6452 \| 0.8033 \| \| No log \| 3.1340 \| 304 \| 0.6395 \| 0.7297 \| 0.6395 \| 0.7997 \| \| No log \| 3.1546 \| 306 \| 0.6961 \| 0.7 \| 0.6961 \| 0.8343 \| \| No log \| 3.1753 \| 308 \| 0.7678 \| 0.6567 \| 0.7678 \| 0.8762 \| \| No log \| 3.1959 \| 310 \| 0.7398 \| 0.6912 \| 0.7398 \| 0.8601 \| \| No log \| 3.2165 \| 312 \| 0.7046 \| 0.7123 \| 0.7046 \| 0.8394 \| \| No log \| 3.2371 \| 314 \| 0.8046 \| 0.7037 \| 0.8046 \| 0.8970 \| \| No log \| 3.2577 \| 316 \| 0.9462 \| 0.7273 \| 0.9462 \| 0.9727 \| \| No log \| 3.2784 \| 318 \| 0.8458 \| 0.7135 \| 0.8458 \| 0.9197 \| \| No log \| 3.2990 \| 320 \| 0.6890 \| 0.7160 \| 0.6890 \| 0.8300 \| \| No log \| 3.3196 \| 322 \| 0.6354 \| 0.7654 \| 0.6354 \| 0.7971 \| \| No log \| 3.3402 \| 324 \| 0.6535 \| 0.7403 \| 0.6535 \| 0.8084 \| \| No log \| 3.3608 \| 326 \| 0.6979 \| 0.7237 \| 0.6979 \| 0.8354 \| \| No log \| 3.3814 \| 328 \| 0.8189 \| 0.72 \| 0.8189 \| 0.9049 \| \| No log \| 3.4021 \| 330 \| 0.8727 \| 0.6714 \| 0.8727 \| 0.9342 \| \| No log \| 3.4227 \| 332 \| 0.8652 \| 0.7059 \| 0.8652 \| 0.9302 \| \| No log \| 3.4433 \| 334 \| 0.7842 \| 0.7286 \| 0.7842 \| 0.8856 \| \| No log \| 3.4639 \| 336 \| 0.7216 \| 0.7517 \| 0.7216 \| 0.8495 \| \| No log \| 3.4845 \| 338 \| 0.7338 \| 0.7215 \| 0.7338 \| 0.8566 \| \| No log \| 3.5052 \| 340 \| 0.7771 \| 0.6957 \| 0.7771 \| 0.8815 \| \| No log \| 3.5258 \| 342 \| 0.7209 \| 0.7305 \| 0.7209 \| 0.8490 \| \| No log \| 3.5464 \| 344 \| 0.6624 \| 0.7262 \| 0.6624 \| 0.8139 \| \| No log \| 3.5670 \| 346 \| 0.6127 \| 0.7879 \| 0.6127 \| 0.7828 \| \| No log \| 3.5876 \| 348 \| 0.6189 \| 0.7665 \| 0.6189 \| 0.7867 \| \| No log \| 3.6082 \| 350 \| 0.6325 \| 0.7456 \| 0.6325 \| 0.7953 \| \| No log \| 3.6289 \| 352 \| 0.6053 \| 0.7952 \| 0.6053 \| 0.7780 \| \| No log \| 3.6495 \| 354 \| 0.5672 \| 0.8323 \| 0.5672 \| 0.7531 \| \| No log \| 3.6701 \| 356 \| 0.5962 \| 0.7719 \| 0.5962 \| 0.7721 \| \| No log \| 3.6907 \| 358 \| 0.6806 \| 0.7650 \| 0.6806 \| 0.8250 \| \| No log \| 3.7113 \| 360 \| 0.7369 \| 0.7701 \| 0.7369 \| 0.8585 \| \| No log \| 3.7320 \| 362 \| 0.7234 \| 0.7514 \| 0.7234 \| 0.8505 \| \| No log \| 3.7526 \| 364 \| 0.6946 \| 0.7262 \| 0.6946 \| 0.8334 \| \| No log \| 3.7732 \| 366 \| 0.7153 \| 0.7375 \| 0.7153 \| 0.8457 \| \| No log \| 3.7938 \| 368 \| 0.8381 \| 0.6795 \| 0.8381 \| 0.9155 \| \| No log \| 3.8144 \| 370 \| 0.9907 \| 0.6467 \| 0.9907 \| 0.9953 \| \| No log \| 3.8351 \| 372 \| 0.9842 \| 0.6588 \| 0.9842 \| 0.9921 \| \| No log \| 3.8557 \| 374 \| 0.8263 \| 0.7030 \| 0.8263 \| 0.9090 \| \| No log \| 3.8763 \| 376 \| 0.6364 \| 0.7826 \| 0.6364 \| 0.7978 \| \| No log \| 3.8969 \| 378 \| 0.5979 \| 0.8129 \| 0.5979 \| 0.7733 \| \| No log \| 3.9175 \| 380 \| 0.6032 \| 0.8129 \| 0.6032 \| 0.7766 \| \| No log \| 3.9381 \| 382 \| 0.6340 \| 0.7821 \| 0.6340 \| 0.7963 \| \| No log \| 3.9588 \| 384 \| 0.6742 \| 0.7515 \| 0.6742 \| 0.8211 \| \| No log \| 3.9794 \| 386 \| 0.7577 \| 0.7066 \| 0.7577 \| 0.8705 \| \| No log \| 4.0 \| 388 \| 0.7956 \| 0.6918 \| 0.7956 \| 0.8920 \| \| No log \| 4.0206 \| 390 \| 0.8222 \| 0.6623 \| 0.8222 \| 0.9068 \| \| No log \| 4.0412 \| 392 \| 0.7831 \| 0.6835 \| 0.7831 \| 0.8849 \| \| No log \| 4.0619 \| 394 \| 0.7014 \| 0.7453 \| 0.7014 \| 0.8375 \| \| No log \| 4.0825 \| 396 \| 0.6360 \| 0.7595 \| 0.6360 \| 0.7975 \| \| No log \| 4.1031 \| 398 \| 0.6268 \| 0.7848 \| 0.6268 \| 0.7917 \| \| No log \| 4.1237 \| 400 \| 0.6348 \| 0.7853 \| 0.6348 \| 0.7968 \| \| No log \| 4.1443 \| 402 \| 0.7172 \| 0.7337 \| 0.7172 \| 0.8469 \| \| No log \| 4.1649 \| 404 \| 0.8698 \| 0.7262 \| 0.8698 \| 0.9327 \| \| No log \| 4.1856 \| 406 \| 0.9461 \| 0.6909 \| 0.9461 \| 0.9727 \| \| No log \| 4.2062 \| 408 \| 0.8941 \| 0.6795 \| 0.8941 \| 0.9456 \| \| No log \| 4.2268 \| 410 \| 0.8287 \| 0.7123 \| 0.8287 \| 0.9103 \| \| No log \| 4.2474 \| 412 \| 0.8115 \| 0.7123 \| 0.8115 \| 0.9008 \| \| No log \| 4.2680 \| 414 \| 0.8251 \| 0.6994 \| 0.8251 \| 0.9084 \| \| No log \| 4.2887 \| 416 \| 0.9469 \| 0.7396 \| 0.9469 \| 0.9731 \| \| No log \| 4.3093 \| 418 \| 0.9229 \| 0.7437 \| 0.9229 \| 0.9607 \| \| No log \| 4.3299 \| 420 \| 0.7387 \| 0.7668 \| 0.7387 \| 0.8595 \| \| No log \| 4.3505 \| 422 \| 0.6246 \| 0.7294 \| 0.6246 \| 0.7903 \| \| No log \| 4.3711 \| 424 \| 0.6276 \| 0.7355 \| 0.6276 \| 0.7922 \| \| No log \| 4.3918 \| 426 \| 0.6380 \| 0.7368 \| 0.6380 \| 0.7987 \| \| No log \| 4.4124 \| 428 \| 0.6312 \| 0.7651 \| 0.6312 \| 0.7945 \| \| No log \| 4.4330 \| 430 \| 0.6137 \| 0.7651 \| 0.6137 \| 0.7834 \| \| No log \| 4.4536 \| 432 \| 0.5521 \| 0.8182 \| 0.5521 \| 0.7430 \| \| No log \| 4.4742 \| 434 \| 0.5049 \| 0.8354 \| 0.5049 \| 0.7106 \| \| No log \| 4.4948 \| 436 \| 0.4706 \| 0.8415 \| 0.4706 \| 0.6860 \| \| No log \| 4.5155 \| 438 \| 0.4786 \| 0.8276 \| 0.4786 \| 0.6918 \| \| No log \| 4.5361 \| 440 \| 0.5208 \| 0.8161 \| 0.5208 \| 0.7217 \| \| No log \| 4.5567 \| 442 \| 0.5843 \| 0.7758 \| 0.5843 \| 0.7644 \| \| No log \| 4.5773 \| 444 \| 0.6199 \| 0.7451 \| 0.6199 \| 0.7874 \| \| No log \| 4.5979 \| 446 \| 0.6672 \| 0.7397 \| 0.6672 \| 0.8168 \| \| No log \| 4.6186 \| 448 \| 0.6637 \| 0.7465 \| 0.6637 \| 0.8147 \| \| No log \| 4.6392 \| 450 \| 0.6270 \| 0.7361 \| 0.6270 \| 0.7918 \| \| No log \| 4.6598 \| 452 \| 0.6211 \| 0.7467 \| 0.6211 \| 0.7881 \| \| No log \| 4.6804 \| 454 \| 0.6129 \| 0.7595 \| 0.6129 \| 0.7829 \| \| No log \| 4.7010 \| 456 \| 0.6952 \| 0.7375 \| 0.6952 \| 0.8338 \| \| No log \| 4.7216 \| 458 \| 0.8275 \| 0.7487 \| 0.8275 \| 0.9097 \| \| No log \| 4.7423 \| 460 \| 0.8799 \| 0.7391 \| 0.8799 \| 0.9381 \| \| No log \| 4.7629 \| 462 \| 0.7715 \| 0.7143 \| 0.7715 \| 0.8784 \| \| No log \| 4.7835 \| 464 \| 0.6494 \| 0.7451 \| 0.6494 \| 0.8059 \| \| No log \| 4.8041 \| 466 \| 0.6108 \| 0.7792 \| 0.6108 \| 0.7815 \| \| No log \| 4.8247 \| 468 \| 0.5989 \| 0.8 \| 0.5989 \| 0.7739 \| \| No log \| 4.8454 \| 470 \| 0.5888 \| 0.8101 \| 0.5888 \| 0.7673 \| \| No log \| 4.8660 \| 472 \| 0.6099 \| 0.7643 \| 0.6099 \| 0.7809 \| \| No log \| 4.8866 \| 474 \| 0.6723 \| 0.7485 \| 0.6723 \| 0.8199 \| \| No log \| 4.9072 \| 476 \| 0.6485 \| 0.7826 \| 0.6485 \| 0.8053 \| \| No log \| 4.9278 \| 478 \| 0.5903 \| 0.8 \| 0.5903 \| 0.7683 \| \| No log \| 4.9485 \| 480 \| 0.5514 \| 0.8068 \| 0.5514 \| 0.7426 \| \| No log \| 4.9691 \| 482 \| 0.5580 \| 0.8298 \| 0.5580 \| 0.7470 \| \| No log \| 4.9897 \| 484 \| 0.5587 \| 0.8046 \| 0.5587 \| 0.7475 \| \| No log \| 5.0103 \| 486 \| 0.5812 \| 0.7976 \| 0.5812 \| 0.7624 \| \| No log \| 5.0309 \| 488 \| 0.6220 \| 0.8182 \| 0.6220 \| 0.7887 \| \| No log \| 5.0515 \| 490 \| 0.6713 \| 0.7465 \| 0.6713 \| 0.8194 \| \| No log \| 5.0722 \| 492 \| 0.7329 \| 0.6883 \| 0.7329 \| 0.8561 \| \| No log \| 5.0928 \| 494 \| 0.8174 \| 0.7195 \| 0.8174 \| 0.9041 \| \| No log \| 5.1134 \| 496 \| 0.8007 \| 0.7253 \| 0.8007 \| 0.8948 \| \| No log \| 5.1340 \| 498 \| 0.7276 \| 0.7429 \| 0.7276 \| 0.8530 \| \| 0.3973 \| 5.1546 \| 500 \| 0.6351 \| 0.7717 \| 0.6351 \| 0.7969 \| \| 0.3973 \| 5.1753 \| 502 \| 0.6046 \| 0.8222 \| 0.6046 \| 0.7775 \| \| 0.3973 \| 5.1959 \| 504 \| 0.5989 \| 0.8161 \| 0.5989 \| 0.7739 \| \| 0.3973 \| 5.2165 \| 506 \| 0.5907 \| 0.8 \| 0.5907 \| 0.7686 \| \| 0.3973 \| 5.2371 \| 508 \| 0.6053 \| 0.7746 \| 0.6053 \| 0.7780 \| \| 0.3973 \| 5.2577 \| 510 \| 0.5994 \| 0.7929 \| 0.5994 \| 0.7742 \| \| 0.3973 \| 5.2784 \| 512 \| 0.6174 \| 0.7927 \| 0.6174 \| 0.7858 \| \| 0.3973 \| 5.2990 \| 514 \| 0.5979 \| 0.8121 \| 0.5979 \| 0.7732 \| \| 0.3973 \| 5.3196 \| 516 \| 0.5881 \| 0.8049 \| 0.5881 \| 0.7669 \| \| 0.3973 \| 5.3402 \| 518 \| 0.5806 \| 0.8199 \| 0.5806 \| 0.7619 \| \| 0.3973 \| 5.3608 \| 520 \| 0.5868 \| 0.8228 \| 0.5868 \| 0.7660 \| \| 0.3973 \| 5.3814 \| 522 \| 0.5853 \| 0.8302 \| 0.5853 \| 0.7651 \| \| 0.3973 \| 5.4021 \| 524 \| 0.6008 \| 0.7826 \| 0.6008 \| 0.7751 \| \| 0.3973 \| 5.4227 \| 526 \| 0.6094 \| 0.7826 \| 0.6094 \| 0.7807 \| \| 0.3973 \| 5.4433 \| 528 \| 0.5773 \| 0.7853 \| 0.5773 \| 0.7598 \| \| 0.3973 \| 5.4639 \| 530 \| 0.5429 \| 0.8050 \| 0.5429 \| 0.7368 \| \| 0.3973 \| 5.4845 \| 532 \| 0.5545 \| 0.8050 \| 0.5545 \| 0.7446 \| \| 0.3973 \| 5.5052 \| 534 \| 0.6134 \| 0.7925 \| 0.6134 \| 0.7832 \| \| 0.3973 \| 5.5258 \| 536 \| 0.7517 \| 0.7067 \| 0.7517 \| 0.8670 \| \| 0.3973 \| 5.5464 \| 538 \| 0.8842 \| 0.6621 \| 0.8842 \| 0.9403 \| \| 0.3973 \| 5.5670 \| 540 \| 0.9498 \| 0.6377 \| 0.9498 \| 0.9746 \| \| 0.3973 \| 5.5876 \| 542 \| 0.9129 \| 0.6569 \| 0.9129 \| 0.9555 \| \| 0.3973 \| 5.6082 \| 544 \| 0.8239 \| 0.6567 \| 0.8239 \| 0.9077 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
MayBashendy/ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization	MayBashendy	2025-01-15T15:35:36Z	184	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-12-31T16:45:16Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8235 - Qwk: 0.6980 - Mse: 0.8235 - Rmse: 0.9075 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:------:\|:------:\|:------:\| \| No log \| 0.0225 \| 2 \| 6.7499 \| 0.0239 \| 6.7499 \| 2.5981 \| \| No log \| 0.0449 \| 4 \| 3.9448 \| 0.0779 \| 3.9448 \| 1.9862 \| \| No log \| 0.0674 \| 6 \| 3.2132 \| 0.0119 \| 3.2132 \| 1.7925 \| \| No log \| 0.0899 \| 8 \| 2.8634 \| 0.0759 \| 2.8634 \| 1.6921 \| \| No log \| 0.1124 \| 10 \| 2.4238 \| 0.1399 \| 2.4238 \| 1.5569 \| \| No log \| 0.1348 \| 12 \| 2.4654 \| 0.1678 \| 2.4654 \| 1.5702 \| \| No log \| 0.1573 \| 14 \| 2.3670 \| 0.1644 \| 2.3670 \| 1.5385 \| \| No log \| 0.1798 \| 16 \| 2.0761 \| 0.2121 \| 2.0761 \| 1.4409 \| \| No log \| 0.2022 \| 18 \| 3.0611 \| 0.0256 \| 3.0611 \| 1.7496 \| \| No log \| 0.2247 \| 20 \| 3.0347 \| 0.0261 \| 3.0347 \| 1.7420 \| \| No log \| 0.2472 \| 22 \| 2.9350 \| 0.0261 \| 2.9350 \| 1.7132 \| \| No log \| 0.2697 \| 24 \| 2.3165 \| 0.1127 \| 2.3165 \| 1.5220 \| \| No log \| 0.2921 \| 26 \| 2.0376 \| 0.2105 \| 2.0376 \| 1.4275 \| \| No log \| 0.3146 \| 28 \| 1.7324 \| 0.2087 \| 1.7324 \| 1.3162 \| \| No log \| 0.3371 \| 30 \| 1.6030 \| 0.1835 \| 1.6030 \| 1.2661 \| \| No log \| 0.3596 \| 32 \| 1.6510 \| 0.1897 \| 1.6510 \| 1.2849 \| \| No log \| 0.3820 \| 34 \| 2.1315 \| 0.2302 \| 2.1315 \| 1.4600 \| \| No log \| 0.4045 \| 36 \| 2.9023 \| 0.0914 \| 2.9023 \| 1.7036 \| \| No log \| 0.4270 \| 38 \| 3.1944 \| 0.0978 \| 3.1944 \| 1.7873 \| \| No log \| 0.4494 \| 40 \| 2.9683 \| 0.1163 \| 2.9683 \| 1.7229 \| \| No log \| 0.4719 \| 42 \| 2.3236 \| 0.2125 \| 2.3236 \| 1.5243 \| \| No log \| 0.4944 \| 44 \| 1.7125 \| 0.3704 \| 1.7125 \| 1.3086 \| \| No log \| 0.5169 \| 46 \| 1.4584 \| 0.4394 \| 1.4584 \| 1.2076 \| \| No log \| 0.5393 \| 48 \| 1.5439 \| 0.4317 \| 1.5439 \| 1.2425 \| \| No log \| 0.5618 \| 50 \| 2.0450 \| 0.2420 \| 2.0450 \| 1.4300 \| \| No log \| 0.5843 \| 52 \| 2.1974 \| 0.2375 \| 2.1974 \| 1.4824 \| \| No log \| 0.6067 \| 54 \| 2.1522 \| 0.2420 \| 2.1522 \| 1.4670 \| \| No log \| 0.6292 \| 56 \| 2.2223 \| 0.2420 \| 2.2223 \| 1.4908 \| \| No log \| 0.6517 \| 58 \| 2.0063 \| 0.3289 \| 2.0063 \| 1.4164 \| \| No log \| 0.6742 \| 60 \| 1.9971 \| 0.3333 \| 1.9971 \| 1.4132 \| \| No log \| 0.6966 \| 62 \| 1.7158 \| 0.3889 \| 1.7158 \| 1.3099 \| \| No log \| 0.7191 \| 64 \| 1.3191 \| 0.5248 \| 1.3191 \| 1.1485 \| \| No log \| 0.7416 \| 66 \| 1.2559 \| 0.5362 \| 1.2559 \| 1.1207 \| \| No log \| 0.7640 \| 68 \| 1.3554 \| 0.5616 \| 1.3554 \| 1.1642 \| \| No log \| 0.7865 \| 70 \| 1.6083 \| 0.4940 \| 1.6083 \| 1.2682 \| \| No log \| 0.8090 \| 72 \| 1.7086 \| 0.5111 \| 1.7086 \| 1.3071 \| \| No log \| 0.8315 \| 74 \| 1.4948 \| 0.5444 \| 1.4948 \| 1.2226 \| \| No log \| 0.8539 \| 76 \| 1.3163 \| 0.5479 \| 1.3163 \| 1.1473 \| \| No log \| 0.8764 \| 78 \| 1.3710 \| 0.5235 \| 1.3710 \| 1.1709 \| \| No log \| 0.8989 \| 80 \| 1.2650 \| 0.5405 \| 1.2650 \| 1.1247 \| \| No log \| 0.9213 \| 82 \| 1.1409 \| 0.6234 \| 1.1409 \| 1.0681 \| \| No log \| 0.9438 \| 84 \| 0.9831 \| 0.6351 \| 0.9831 \| 0.9915 \| \| No log \| 0.9663 \| 86 \| 0.9026 \| 0.6809 \| 0.9026 \| 0.9501 \| \| No log \| 0.9888 \| 88 \| 0.8614 \| 0.6853 \| 0.8614 \| 0.9281 \| \| No log \| 1.0112 \| 90 \| 0.9918 \| 0.6099 \| 0.9918 \| 0.9959 \| \| No log \| 1.0337 \| 92 \| 1.1130 \| 0.5634 \| 1.1130 \| 1.0550 \| \| No log \| 1.0562 \| 94 \| 0.9977 \| 0.6056 \| 0.9977 \| 0.9988 \| \| No log \| 1.0787 \| 96 \| 1.0509 \| 0.6065 \| 1.0509 \| 1.0251 \| \| No log \| 1.1011 \| 98 \| 1.3156 \| 0.6145 \| 1.3156 \| 1.1470 \| \| No log \| 1.1236 \| 100 \| 1.4242 \| 0.5780 \| 1.4242 \| 1.1934 \| \| No log \| 1.1461 \| 102 \| 1.2445 \| 0.6380 \| 1.2445 \| 1.1156 \| \| No log \| 1.1685 \| 104 \| 1.1225 \| 0.5772 \| 1.1225 \| 1.0595 \| \| No log \| 1.1910 \| 106 \| 1.0577 \| 0.5571 \| 1.0577 \| 1.0284 \| \| No log \| 1.2135 \| 108 \| 1.0190 \| 0.6029 \| 1.0190 \| 1.0095 \| \| No log \| 1.2360 \| 110 \| 1.0296 \| 0.5693 \| 1.0296 \| 1.0147 \| \| No log \| 1.2584 \| 112 \| 1.1317 \| 0.5833 \| 1.1317 \| 1.0638 \| \| No log \| 1.2809 \| 114 \| 1.1935 \| 0.5850 \| 1.1935 \| 1.0925 \| \| No log \| 1.3034 \| 116 \| 1.0900 \| 0.6143 \| 1.0900 \| 1.0440 \| \| No log \| 1.3258 \| 118 \| 1.0439 \| 0.6143 \| 1.0439 \| 1.0217 \| \| No log \| 1.3483 \| 120 \| 1.1155 \| 0.5906 \| 1.1155 \| 1.0562 \| \| No log \| 1.3708 \| 122 \| 1.0796 \| 0.6081 \| 1.0796 \| 1.0391 \| \| No log \| 1.3933 \| 124 \| 0.9929 \| 0.6267 \| 0.9929 \| 0.9965 \| \| No log \| 1.4157 \| 126 \| 0.8937 \| 0.6759 \| 0.8937 \| 0.9454 \| \| No log \| 1.4382 \| 128 \| 0.8898 \| 0.6528 \| 0.8898 \| 0.9433 \| \| No log \| 1.4607 \| 130 \| 1.0211 \| 0.6410 \| 1.0211 \| 1.0105 \| \| No log \| 1.4831 \| 132 \| 1.4143 \| 0.5294 \| 1.4143 \| 1.1893 \| \| No log \| 1.5056 \| 134 \| 1.5741 \| 0.5172 \| 1.5741 \| 1.2546 \| \| No log \| 1.5281 \| 136 \| 1.2332 \| 0.6203 \| 1.2332 \| 1.1105 \| \| No log \| 1.5506 \| 138 \| 0.8877 \| 0.6056 \| 0.8877 \| 0.9422 \| \| No log \| 1.5730 \| 140 \| 0.8260 \| 0.6853 \| 0.8260 \| 0.9089 \| \| No log \| 1.5955 \| 142 \| 0.8399 \| 0.7083 \| 0.8399 \| 0.9164 \| \| No log \| 1.6180 \| 144 \| 0.9279 \| 0.6494 \| 0.9279 \| 0.9633 \| \| No log \| 1.6404 \| 146 \| 1.1181 \| 0.6047 \| 1.1181 \| 1.0574 \| \| No log \| 1.6629 \| 148 \| 1.0097 \| 0.6584 \| 1.0097 \| 1.0048 \| \| No log \| 1.6854 \| 150 \| 0.9732 \| 0.6456 \| 0.9732 \| 0.9865 \| \| No log \| 1.7079 \| 152 \| 1.1485 \| 0.5698 \| 1.1485 \| 1.0717 \| \| No log \| 1.7303 \| 154 \| 1.2391 \| 0.5663 \| 1.2391 \| 1.1131 \| \| No log \| 1.7528 \| 156 \| 1.4465 \| 0.5909 \| 1.4465 \| 1.2027 \| \| No log \| 1.7753 \| 158 \| 1.1367 \| 0.6013 \| 1.1367 \| 1.0661 \| \| No log \| 1.7978 \| 160 \| 0.8003 \| 0.6712 \| 0.8003 \| 0.8946 \| \| No log \| 1.8202 \| 162 \| 0.7855 \| 0.7123 \| 0.7855 \| 0.8863 \| \| No log \| 1.8427 \| 164 \| 0.8127 \| 0.7248 \| 0.8127 \| 0.9015 \| \| No log \| 1.8652 \| 166 \| 0.9137 \| 0.6490 \| 0.9137 \| 0.9559 \| \| No log \| 1.8876 \| 168 \| 1.2149 \| 0.5697 \| 1.2149 \| 1.1022 \| \| No log \| 1.9101 \| 170 \| 1.3223 \| 0.5731 \| 1.3223 \| 1.1499 \| \| No log \| 1.9326 \| 172 \| 1.2370 \| 0.6057 \| 1.2370 \| 1.1122 \| \| No log \| 1.9551 \| 174 \| 1.0690 \| 0.6235 \| 1.0690 \| 1.0339 \| \| No log \| 1.9775 \| 176 \| 0.8758 \| 0.6800 \| 0.8758 \| 0.9359 \| \| No log \| 2.0 \| 178 \| 0.8399 \| 0.6974 \| 0.8399 \| 0.9165 \| \| No log \| 2.0225 \| 180 \| 0.7908 \| 0.7273 \| 0.7908 \| 0.8893 \| \| No log \| 2.0449 \| 182 \| 0.7553 \| 0.7368 \| 0.7553 \| 0.8691 \| \| No log \| 2.0674 \| 184 \| 0.9469 \| 0.6875 \| 0.9469 \| 0.9731 \| \| No log \| 2.0899 \| 186 \| 1.0288 \| 0.6582 \| 1.0288 \| 1.0143 \| \| No log \| 2.1124 \| 188 \| 0.9775 \| 0.6582 \| 0.9775 \| 0.9887 \| \| No log \| 2.1348 \| 190 \| 0.9110 \| 0.6625 \| 0.9110 \| 0.9545 \| \| No log \| 2.1573 \| 192 \| 0.9113 \| 0.6905 \| 0.9113 \| 0.9546 \| \| No log \| 2.1798 \| 194 \| 0.8910 \| 0.7093 \| 0.8910 \| 0.9439 \| \| No log \| 2.2022 \| 196 \| 0.9157 \| 0.6901 \| 0.9157 \| 0.9569 \| \| No log \| 2.2247 \| 198 \| 0.9856 \| 0.7079 \| 0.9856 \| 0.9928 \| \| No log \| 2.2472 \| 200 \| 0.9730 \| 0.6936 \| 0.9730 \| 0.9864 \| \| No log \| 2.2697 \| 202 \| 0.8251 \| 0.7237 \| 0.8251 \| 0.9084 \| \| No log \| 2.2921 \| 204 \| 0.8114 \| 0.6939 \| 0.8114 \| 0.9008 \| \| No log \| 2.3146 \| 206 \| 0.8341 \| 0.7190 \| 0.8341 \| 0.9133 \| \| No log \| 2.3371 \| 208 \| 0.8705 \| 0.6131 \| 0.8705 \| 0.9330 \| \| No log \| 2.3596 \| 210 \| 0.9179 \| 0.6331 \| 0.9179 \| 0.9581 \| \| No log \| 2.3820 \| 212 \| 0.9431 \| 0.6429 \| 0.9431 \| 0.9711 \| \| No log \| 2.4045 \| 214 \| 1.0174 \| 0.6122 \| 1.0174 \| 1.0087 \| \| No log \| 2.4270 \| 216 \| 1.2815 \| 0.5732 \| 1.2815 \| 1.1320 \| \| No log \| 2.4494 \| 218 \| 1.4477 \| 0.5650 \| 1.4477 \| 1.2032 \| \| No log \| 2.4719 \| 220 \| 1.1777 \| 0.6433 \| 1.1777 \| 1.0852 \| \| No log \| 2.4944 \| 222 \| 0.8770 \| 0.7229 \| 0.8770 \| 0.9365 \| \| No log \| 2.5169 \| 224 \| 0.7887 \| 0.7317 \| 0.7887 \| 0.8881 \| \| No log \| 2.5393 \| 226 \| 0.8828 \| 0.7011 \| 0.8828 \| 0.9396 \| \| No log \| 2.5618 \| 228 \| 0.9417 \| 0.6821 \| 0.9417 \| 0.9704 \| \| No log \| 2.5843 \| 230 \| 0.8212 \| 0.7093 \| 0.8212 \| 0.9062 \| \| No log \| 2.6067 \| 232 \| 0.7767 \| 0.7436 \| 0.7767 \| 0.8813 \| \| No log \| 2.6292 \| 234 \| 0.8518 \| 0.7162 \| 0.8518 \| 0.9229 \| \| No log \| 2.6517 \| 236 \| 0.8481 \| 0.7162 \| 0.8481 \| 0.9209 \| \| No log \| 2.6742 \| 238 \| 0.8264 \| 0.7261 \| 0.8264 \| 0.9091 \| \| No log \| 2.6966 \| 240 \| 0.9441 \| 0.6893 \| 0.9441 \| 0.9716 \| \| No log \| 2.7191 \| 242 \| 1.0546 \| 0.6704 \| 1.0546 \| 1.0269 \| \| No log \| 2.7416 \| 244 \| 0.9842 \| 0.6816 \| 0.9842 \| 0.9921 \| \| No log \| 2.7640 \| 246 \| 0.8624 \| 0.7453 \| 0.8624 \| 0.9286 \| \| No log \| 2.7865 \| 248 \| 0.8618 \| 0.6803 \| 0.8618 \| 0.9283 \| \| No log \| 2.8090 \| 250 \| 0.8531 \| 0.6667 \| 0.8531 \| 0.9236 \| \| No log \| 2.8315 \| 252 \| 0.8015 \| 0.7368 \| 0.8015 \| 0.8953 \| \| No log \| 2.8539 \| 254 \| 0.8789 \| 0.6962 \| 0.8789 \| 0.9375 \| \| No log \| 2.8764 \| 256 \| 0.9868 \| 0.6824 \| 0.9868 \| 0.9934 \| \| No log \| 2.8989 \| 258 \| 0.9168 \| 0.6667 \| 0.9168 \| 0.9575 \| \| No log \| 2.9213 \| 260 \| 0.7860 \| 0.6968 \| 0.7860 \| 0.8866 \| \| No log \| 2.9438 \| 262 \| 0.7684 \| 0.7320 \| 0.7684 \| 0.8766 \| \| No log \| 2.9663 \| 264 \| 0.8350 \| 0.7273 \| 0.8350 \| 0.9138 \| \| No log \| 2.9888 \| 266 \| 0.9936 \| 0.6497 \| 0.9936 \| 0.9968 \| \| No log \| 3.0112 \| 268 \| 1.1765 \| 0.6420 \| 1.1765 \| 1.0847 \| \| No log \| 3.0337 \| 270 \| 1.3074 \| 0.6127 \| 1.3074 \| 1.1434 \| \| No log \| 3.0562 \| 272 \| 1.1744 \| 0.6627 \| 1.1744 \| 1.0837 \| \| No log \| 3.0787 \| 274 \| 0.8994 \| 0.6711 \| 0.8994 \| 0.9484 \| \| No log \| 3.1011 \| 276 \| 0.7643 \| 0.6980 \| 0.7643 \| 0.8743 \| \| No log \| 3.1236 \| 278 \| 0.7656 \| 0.6901 \| 0.7656 \| 0.8750 \| \| No log \| 3.1461 \| 280 \| 0.7889 \| 0.6621 \| 0.7889 \| 0.8882 \| \| No log \| 3.1685 \| 282 \| 0.9606 \| 0.6928 \| 0.9606 \| 0.9801 \| \| No log \| 3.1910 \| 284 \| 1.1225 \| 0.6667 \| 1.1225 \| 1.0595 \| \| No log \| 3.2135 \| 286 \| 1.2142 \| 0.6463 \| 1.2142 \| 1.1019 \| \| No log \| 3.2360 \| 288 \| 1.0268 \| 0.6923 \| 1.0268 \| 1.0133 \| \| No log \| 3.2584 \| 290 \| 0.7790 \| 0.6928 \| 0.7790 \| 0.8826 \| \| No log \| 3.2809 \| 292 \| 0.7135 \| 0.7368 \| 0.7135 \| 0.8447 \| \| No log \| 3.3034 \| 294 \| 0.7415 \| 0.7484 \| 0.7415 \| 0.8611 \| \| No log \| 3.3258 \| 296 \| 0.8153 \| 0.7317 \| 0.8153 \| 0.9030 \| \| No log \| 3.3483 \| 298 \| 0.9019 \| 0.7337 \| 0.9019 \| 0.9497 \| \| No log \| 3.3708 \| 300 \| 0.8978 \| 0.7305 \| 0.8978 \| 0.9475 \| \| No log \| 3.3933 \| 302 \| 0.8980 \| 0.7229 \| 0.8980 \| 0.9476 \| \| No log \| 3.4157 \| 304 \| 0.9298 \| 0.7030 \| 0.9298 \| 0.9643 \| \| No log \| 3.4382 \| 306 \| 0.8938 \| 0.7117 \| 0.8938 \| 0.9454 \| \| No log \| 3.4607 \| 308 \| 0.7981 \| 0.7097 \| 0.7981 \| 0.8933 \| \| No log \| 3.4831 \| 310 \| 0.7560 \| 0.6853 \| 0.7560 \| 0.8695 \| \| No log \| 3.5056 \| 312 \| 0.7667 \| 0.7361 \| 0.7667 \| 0.8756 \| \| No log \| 3.5281 \| 314 \| 0.7564 \| 0.7133 \| 0.7564 \| 0.8697 \| \| No log \| 3.5506 \| 316 \| 0.7166 \| 0.7333 \| 0.7166 \| 0.8465 \| \| No log \| 3.5730 \| 318 \| 0.8723 \| 0.7195 \| 0.8723 \| 0.9340 \| \| No log \| 3.5955 \| 320 \| 1.1398 \| 0.6556 \| 1.1398 \| 1.0676 \| \| No log \| 3.6180 \| 322 \| 1.1866 \| 0.6145 \| 1.1866 \| 1.0893 \| \| No log \| 3.6404 \| 324 \| 1.0065 \| 0.6420 \| 1.0065 \| 1.0032 \| \| No log \| 3.6629 \| 326 \| 0.7958 \| 0.7059 \| 0.7958 \| 0.8921 \| \| No log \| 3.6854 \| 328 \| 0.7029 \| 0.7586 \| 0.7029 \| 0.8384 \| \| No log \| 3.7079 \| 330 \| 0.6871 \| 0.7361 \| 0.6871 \| 0.8289 \| \| No log \| 3.7303 \| 332 \| 0.6626 \| 0.7671 \| 0.6626 \| 0.8140 \| \| No log \| 3.7528 \| 334 \| 0.6622 \| 0.7871 \| 0.6622 \| 0.8137 \| \| No log \| 3.7753 \| 336 \| 0.7631 \| 0.7515 \| 0.7631 \| 0.8736 \| \| No log \| 3.7978 \| 338 \| 0.8749 \| 0.7052 \| 0.8749 \| 0.9354 \| \| No log \| 3.8202 \| 340 \| 0.8515 \| 0.7126 \| 0.8515 \| 0.9228 \| \| No log \| 3.8427 \| 342 \| 0.7951 \| 0.7647 \| 0.7951 \| 0.8917 \| \| No log \| 3.8652 \| 344 \| 0.8031 \| 0.7389 \| 0.8031 \| 0.8962 \| \| No log \| 3.8876 \| 346 \| 0.8594 \| 0.6901 \| 0.8594 \| 0.9270 \| \| No log \| 3.9101 \| 348 \| 0.8294 \| 0.6809 \| 0.8294 \| 0.9107 \| \| No log \| 3.9326 \| 350 \| 0.7983 \| 0.7162 \| 0.7983 \| 0.8935 \| \| No log \| 3.9551 \| 352 \| 0.8242 \| 0.7362 \| 0.8242 \| 0.9078 \| \| No log \| 3.9775 \| 354 \| 0.8498 \| 0.7305 \| 0.8498 \| 0.9218 \| \| No log \| 4.0 \| 356 \| 0.9308 \| 0.7030 \| 0.9308 \| 0.9648 \| \| No log \| 4.0225 \| 358 \| 0.9551 \| 0.7030 \| 0.9551 \| 0.9773 \| \| No log \| 4.0449 \| 360 \| 0.8899 \| 0.6914 \| 0.8899 \| 0.9433 \| \| No log \| 4.0674 \| 362 \| 0.8509 \| 0.6951 \| 0.8509 \| 0.9224 \| \| No log \| 4.0899 \| 364 \| 0.7797 \| 0.7229 \| 0.7797 \| 0.8830 \| \| No log \| 4.1124 \| 366 \| 0.7379 \| 0.75 \| 0.7379 \| 0.8590 \| \| No log \| 4.1348 \| 368 \| 0.7696 \| 0.75 \| 0.7696 \| 0.8773 \| \| No log \| 4.1573 \| 370 \| 0.8279 \| 0.6909 \| 0.8279 \| 0.9099 \| \| No log \| 4.1798 \| 372 \| 0.8621 \| 0.7317 \| 0.8621 \| 0.9285 \| \| No log \| 4.2022 \| 374 \| 0.9652 \| 0.6747 \| 0.9652 \| 0.9825 \| \| No log \| 4.2247 \| 376 \| 0.9987 \| 0.6296 \| 0.9987 \| 0.9994 \| \| No log \| 4.2472 \| 378 \| 1.0098 \| 0.6883 \| 1.0098 \| 1.0049 \| \| No log \| 4.2697 \| 380 \| 1.0363 \| 0.625 \| 1.0363 \| 1.0180 \| \| No log \| 4.2921 \| 382 \| 0.9867 \| 0.5899 \| 0.9867 \| 0.9933 \| \| No log \| 4.3146 \| 384 \| 0.9271 \| 0.6846 \| 0.9271 \| 0.9629 \| \| No log \| 4.3371 \| 386 \| 0.9243 \| 0.6452 \| 0.9243 \| 0.9614 \| \| No log \| 4.3596 \| 388 \| 1.0277 \| 0.6258 \| 1.0277 \| 1.0138 \| \| No log \| 4.3820 \| 390 \| 1.1102 \| 0.6310 \| 1.1102 \| 1.0537 \| \| No log \| 4.4045 \| 392 \| 0.8984 \| 0.6420 \| 0.8984 \| 0.9478 \| \| No log \| 4.4270 \| 394 \| 0.6753 \| 0.8125 \| 0.6753 \| 0.8218 \| \| No log \| 4.4494 \| 396 \| 0.6416 \| 0.7785 \| 0.6416 \| 0.8010 \| \| No log \| 4.4719 \| 398 \| 0.6401 \| 0.7785 \| 0.6401 \| 0.8001 \| \| No log \| 4.4944 \| 400 \| 0.6687 \| 0.7785 \| 0.6687 \| 0.8178 \| \| No log \| 4.5169 \| 402 \| 0.7273 \| 0.7075 \| 0.7273 \| 0.8528 \| \| No log \| 4.5393 \| 404 \| 0.7722 \| 0.7020 \| 0.7722 \| 0.8787 \| \| No log \| 4.5618 \| 406 \| 0.7629 \| 0.7105 \| 0.7629 \| 0.8734 \| \| No log \| 4.5843 \| 408 \| 0.7780 \| 0.6974 \| 0.7780 \| 0.8820 \| \| No log \| 4.6067 \| 410 \| 0.7689 \| 0.6974 \| 0.7689 \| 0.8769 \| \| No log \| 4.6292 \| 412 \| 0.7241 \| 0.75 \| 0.7241 \| 0.8510 \| \| No log \| 4.6517 \| 414 \| 0.6443 \| 0.7785 \| 0.6443 \| 0.8027 \| \| No log \| 4.6742 \| 416 \| 0.6238 \| 0.7785 \| 0.6238 \| 0.7898 \| \| No log \| 4.6966 \| 418 \| 0.6294 \| 0.7867 \| 0.6294 \| 0.7934 \| \| No log \| 4.7191 \| 420 \| 0.6906 \| 0.7925 \| 0.6906 \| 0.8310 \| \| No log \| 4.7416 \| 422 \| 0.8316 \| 0.7284 \| 0.8316 \| 0.9119 \| \| No log \| 4.7640 \| 424 \| 0.7839 \| 0.7425 \| 0.7839 \| 0.8854 \| \| No log \| 4.7865 \| 426 \| 0.6938 \| 0.7904 \| 0.6938 \| 0.8330 \| \| No log \| 4.8090 \| 428 \| 0.6855 \| 0.7904 \| 0.6855 \| 0.8280 \| \| No log \| 4.8315 \| 430 \| 0.6866 \| 0.7952 \| 0.6866 \| 0.8286 \| \| No log \| 4.8539 \| 432 \| 0.7095 \| 0.8125 \| 0.7095 \| 0.8423 \| \| No log \| 4.8764 \| 434 \| 0.7935 \| 0.7654 \| 0.7935 \| 0.8908 \| \| No log \| 4.8989 \| 436 \| 0.9087 \| 0.6829 \| 0.9087 \| 0.9533 \| \| No log \| 4.9213 \| 438 \| 0.9127 \| 0.6667 \| 0.9127 \| 0.9553 \| \| No log \| 4.9438 \| 440 \| 0.8895 \| 0.6627 \| 0.8895 \| 0.9431 \| \| No log \| 4.9663 \| 442 \| 0.7709 \| 0.7619 \| 0.7709 \| 0.8780 \| \| No log \| 4.9888 \| 444 \| 0.6746 \| 0.7904 \| 0.6746 \| 0.8213 \| \| No log \| 5.0112 \| 446 \| 0.6282 \| 0.7662 \| 0.6282 \| 0.7926 \| \| No log \| 5.0337 \| 448 \| 0.6500 \| 0.75 \| 0.6500 \| 0.8062 \| \| No log \| 5.0562 \| 450 \| 0.6861 \| 0.7550 \| 0.6861 \| 0.8283 \| \| No log \| 5.0787 \| 452 \| 0.7197 \| 0.7417 \| 0.7197 \| 0.8483 \| \| No log \| 5.1011 \| 454 \| 0.7811 \| 0.7123 \| 0.7811 \| 0.8838 \| \| No log \| 5.1236 \| 456 \| 0.8052 \| 0.6713 \| 0.8052 \| 0.8973 \| \| No log \| 5.1461 \| 458 \| 0.7841 \| 0.6806 \| 0.7841 \| 0.8855 \| \| No log \| 5.1685 \| 460 \| 0.7582 \| 0.6986 \| 0.7582 \| 0.8708 \| \| No log \| 5.1910 \| 462 \| 0.7210 \| 0.7383 \| 0.7210 \| 0.8491 \| \| No log \| 5.2135 \| 464 \| 0.6827 \| 0.7432 \| 0.6827 \| 0.8262 \| \| No log \| 5.2360 \| 466 \| 0.6956 \| 0.7383 \| 0.6956 \| 0.8340 \| \| No log \| 5.2584 \| 468 \| 0.7954 \| 0.72 \| 0.7954 \| 0.8919 \| \| No log \| 5.2809 \| 470 \| 0.8401 \| 0.7355 \| 0.8401 \| 0.9166 \| \| No log \| 5.3034 \| 472 \| 0.7855 \| 0.7564 \| 0.7855 \| 0.8863 \| \| No log \| 5.3258 \| 474 \| 0.7808 \| 0.7643 \| 0.7808 \| 0.8836 \| \| No log \| 5.3483 \| 476 \| 0.7830 \| 0.7485 \| 0.7830 \| 0.8849 \| \| No log \| 5.3708 \| 478 \| 0.6540 \| 0.7636 \| 0.6540 \| 0.8087 \| \| No log \| 5.3933 \| 480 \| 0.6426 \| 0.8171 \| 0.6426 \| 0.8016 \| \| No log \| 5.4157 \| 482 \| 0.7162 \| 0.7561 \| 0.7162 \| 0.8463 \| \| No log \| 5.4382 \| 484 \| 0.8179 \| 0.7470 \| 0.8179 \| 0.9044 \| \| No log \| 5.4607 \| 486 \| 0.8560 \| 0.6871 \| 0.8560 \| 0.9252 \| \| No log \| 5.4831 \| 488 \| 0.8279 \| 0.7044 \| 0.8279 \| 0.9099 \| \| No log \| 5.5056 \| 490 \| 0.7908 \| 0.7692 \| 0.7908 \| 0.8892 \| \| No log \| 5.5281 \| 492 \| 0.8189 \| 0.72 \| 0.8189 \| 0.9049 \| \| No log \| 5.5506 \| 494 \| 0.8573 \| 0.6712 \| 0.8573 \| 0.9259 \| \| No log \| 5.5730 \| 496 \| 0.9023 \| 0.6622 \| 0.9023 \| 0.9499 \| \| No log \| 5.5955 \| 498 \| 0.9562 \| 0.6395 \| 0.9562 \| 0.9779 \| \| 0.4108 \| 5.6180 \| 500 \| 0.9236 \| 0.6154 \| 0.9236 \| 0.9610 \| \| 0.4108 \| 5.6404 \| 502 \| 0.8723 \| 0.6429 \| 0.8723 \| 0.9340 \| \| 0.4108 \| 5.6629 \| 504 \| 0.8019 \| 0.7211 \| 0.8019 \| 0.8955 \| \| 0.4108 \| 5.6854 \| 506 \| 0.7450 \| 0.7662 \| 0.7450 \| 0.8631 \| \| 0.4108 \| 5.7079 \| 508 \| 0.7097 \| 0.7848 \| 0.7097 \| 0.8424 \| \| 0.4108 \| 5.7303 \| 510 \| 0.7363 \| 0.7831 \| 0.7363 \| 0.8581 \| \| 0.4108 \| 5.7528 \| 512 \| 0.7654 \| 0.75 \| 0.7654 \| 0.8749 \| \| 0.4108 \| 5.7753 \| 514 \| 0.7439 \| 0.75 \| 0.7439 \| 0.8625 \| \| 0.4108 \| 5.7978 \| 516 \| 0.6668 \| 0.7853 \| 0.6668 \| 0.8166 \| \| 0.4108 \| 5.8202 \| 518 \| 0.6113 \| 0.8125 \| 0.6113 \| 0.7819 \| \| 0.4108 \| 5.8427 \| 520 \| 0.6067 \| 0.8050 \| 0.6067 \| 0.7789 \| \| 0.4108 \| 5.8652 \| 522 \| 0.6229 \| 0.8125 \| 0.6229 \| 0.7893 \| \| 0.4108 \| 5.8876 \| 524 \| 0.6233 \| 0.7848 \| 0.6233 \| 0.7895 \| \| 0.4108 \| 5.9101 \| 526 \| 0.6430 \| 0.7925 \| 0.6430 \| 0.8019 \| \| 0.4108 \| 5.9326 \| 528 \| 0.6314 \| 0.7925 \| 0.6314 \| 0.7946 \| \| 0.4108 \| 5.9551 \| 530 \| 0.6136 \| 0.8 \| 0.6136 \| 0.7833 \| \| 0.4108 \| 5.9775 \| 532 \| 0.6032 \| 0.8125 \| 0.6032 \| 0.7766 \| \| 0.4108 \| 6.0 \| 534 \| 0.6027 \| 0.8025 \| 0.6027 \| 0.7764 \| \| 0.4108 \| 6.0225 \| 536 \| 0.6238 \| 0.8025 \| 0.6238 \| 0.7898 \| \| 0.4108 \| 6.0449 \| 538 \| 0.6663 \| 0.8121 \| 0.6663 \| 0.8163 \| \| 0.4108 \| 6.0674 \| 540 \| 0.6986 \| 0.8047 \| 0.6986 \| 0.8358 \| \| 0.4108 \| 6.0899 \| 542 \| 0.7147 \| 0.7886 \| 0.7147 \| 0.8454 \| \| 0.4108 \| 6.1124 \| 544 \| 0.7203 \| 0.7953 \| 0.7203 \| 0.8487 \| \| 0.4108 \| 6.1348 \| 546 \| 0.7287 \| 0.7904 \| 0.7287 \| 0.8536 \| \| 0.4108 \| 6.1573 \| 548 \| 0.7130 \| 0.7925 \| 0.7130 \| 0.8444 \| \| 0.4108 \| 6.1798 \| 550 \| 0.6790 \| 0.7949 \| 0.6790 \| 0.8240 \| \| 0.4108 \| 6.2022 \| 552 \| 0.6462 \| 0.7949 \| 0.6462 \| 0.8039 \| \| 0.4108 \| 6.2247 \| 554 \| 0.6340 \| 0.7949 \| 0.6340 \| 0.7963 \| \| 0.4108 \| 6.2472 \| 556 \| 0.6552 \| 0.7901 \| 0.6552 \| 0.8094 \| \| 0.4108 \| 6.2697 \| 558 \| 0.6958 \| 0.7879 \| 0.6958 \| 0.8342 \| \| 0.4108 \| 6.2921 \| 560 \| 0.7199 \| 0.7784 \| 0.7199 \| 0.8485 \| \| 0.4108 \| 6.3146 \| 562 \| 0.7557 \| 0.7590 \| 0.7557 \| 0.8693 \| \| 0.4108 \| 6.3371 \| 564 \| 0.7634 \| 0.7848 \| 0.7634 \| 0.8738 \| \| 0.4108 \| 6.3596 \| 566 \| 0.7853 \| 0.7564 \| 0.7853 \| 0.8862 \| \| 0.4108 \| 6.3820 \| 568 \| 0.8368 \| 0.6788 \| 0.8368 \| 0.9148 \| \| 0.4108 \| 6.4045 \| 570 \| 0.9209 \| 0.6941 \| 0.9209 \| 0.9596 \| \| 0.4108 \| 6.4270 \| 572 \| 1.0415 \| 0.6630 \| 1.0415 \| 1.0205 \| \| 0.4108 \| 6.4494 \| 574 \| 0.9611 \| 0.6952 \| 0.9611 \| 0.9804 \| \| 0.4108 \| 6.4719 \| 576 \| 0.8231 \| 0.7667 \| 0.8231 \| 0.9073 \| \| 0.4108 \| 6.4944 \| 578 \| 0.7428 \| 0.7701 \| 0.7428 \| 0.8619 \| \| 0.4108 \| 6.5169 \| 580 \| 0.6969 \| 0.7952 \| 0.6969 \| 0.8348 \| \| 0.4108 \| 6.5393 \| 582 \| 0.7073 \| 0.8050 \| 0.7073 \| 0.8410 \| \| 0.4108 \| 6.5618 \| 584 \| 0.7410 \| 0.7564 \| 0.7410 \| 0.8608 \| \| 0.4108 \| 6.5843 \| 586 \| 0.7670 \| 0.6993 \| 0.7670 \| 0.8758 \| \| 0.4108 \| 6.6067 \| 588 \| 0.7922 \| 0.6763 \| 0.7922 \| 0.8900 \| \| 0.4108 \| 6.6292 \| 590 \| 0.8097 \| 0.6763 \| 0.8097 \| 0.8998 \| \| 0.4108 \| 6.6517 \| 592 \| 0.8084 \| 0.6667 \| 0.8084 \| 0.8991 \| \| 0.4108 \| 6.6742 \| 594 \| 0.8051 \| 0.6423 \| 0.8051 \| 0.8973 \| \| 0.4108 \| 6.6966 \| 596 \| 0.7751 \| 0.6761 \| 0.7751 \| 0.8804 \| \| 0.4108 \| 6.7191 \| 598 \| 0.7358 \| 0.7248 \| 0.7358 \| 0.8578 \| \| 0.4108 \| 6.7416 \| 600 \| 0.7432 \| 0.7484 \| 0.7432 \| 0.8621 \| \| 0.4108 \| 6.7640 \| 602 \| 0.7627 \| 0.7329 \| 0.7627 \| 0.8733 \| \| 0.4108 \| 6.7865 \| 604 \| 0.8505 \| 0.7101 \| 0.8505 \| 0.9222 \| \| 0.4108 \| 6.8090 \| 606 \| 0.9321 \| 0.7052 \| 0.9321 \| 0.9655 \| \| 0.4108 \| 6.8315 \| 608 \| 0.9064 \| 0.6977 \| 0.9064 \| 0.9521 \| \| 0.4108 \| 6.8539 \| 610 \| 0.8078 \| 0.7368 \| 0.8078 \| 0.8988 \| \| 0.4108 \| 6.8764 \| 612 \| 0.7928 \| 0.7561 \| 0.7928 \| 0.8904 \| \| 0.4108 \| 6.8989 \| 614 \| 0.8223 \| 0.7485 \| 0.8223 \| 0.9068 \| \| 0.4108 \| 6.9213 \| 616 \| 0.8761 \| 0.6988 \| 0.8761 \| 0.9360 \| \| 0.4108 \| 6.9438 \| 618 \| 0.9445 \| 0.6258 \| 0.9445 \| 0.9719 \| \| 0.4108 \| 6.9663 \| 620 \| 0.9800 \| 0.6258 \| 0.9800 \| 0.9900 \| \| 0.4108 \| 6.9888 \| 622 \| 0.9661 \| 0.6258 \| 0.9661 \| 0.9829 \| \| 0.4108 \| 7.0112 \| 624 \| 0.8560 \| 0.6709 \| 0.8560 \| 0.9252 \| \| 0.4108 \| 7.0337 \| 626 \| 0.7641 \| 0.7871 \| 0.7641 \| 0.8741 \| \| 0.4108 \| 7.0562 \| 628 \| 0.7324 \| 0.7949 \| 0.7324 \| 0.8558 \| \| 0.4108 \| 7.0787 \| 630 \| 0.7149 \| 0.7949 \| 0.7149 \| 0.8455 \| \| 0.4108 \| 7.1011 \| 632 \| 0.7211 \| 0.8025 \| 0.7211 \| 0.8492 \| \| 0.4108 \| 7.1236 \| 634 \| 0.8127 \| 0.7105 \| 0.8127 \| 0.9015 \| \| 0.4108 \| 7.1461 \| 636 \| 0.9362 \| 0.6538 \| 0.9362 \| 0.9675 \| \| 0.4108 \| 7.1685 \| 638 \| 1.0110 \| 0.6364 \| 1.0110 \| 1.0055 \| \| 0.4108 \| 7.1910 \| 640 \| 0.9426 \| 0.6216 \| 0.9426 \| 0.9709 \| \| 0.4108 \| 7.2135 \| 642 \| 0.8219 \| 0.6667 \| 0.8219 \| 0.9066 \| \| 0.4108 \| 7.2360 \| 644 \| 0.7717 \| 0.7368 \| 0.7717 \| 0.8784 \| \| 0.4108 \| 7.2584 \| 646 \| 0.7557 \| 0.7949 \| 0.7557 \| 0.8693 \| \| 0.4108 \| 7.2809 \| 648 \| 0.7469 \| 0.7662 \| 0.7469 \| 0.8642 \| \| 0.4108 \| 7.3034 \| 650 \| 0.7613 \| 0.7484 \| 0.7613 \| 0.8725 \| \| 0.4108 \| 7.3258 \| 652 \| 0.7972 \| 0.6842 \| 0.7972 \| 0.8929 \| \| 0.4108 \| 7.3483 \| 654 \| 0.8835 \| 0.6667 \| 0.8835 \| 0.9399 \| \| 0.4108 \| 7.3708 \| 656 \| 0.9643 \| 0.6627 \| 0.9643 \| 0.9820 \| \| 0.4108 \| 7.3933 \| 658 \| 0.9340 \| 0.7006 \| 0.9340 \| 0.9664 \| \| 0.4108 \| 7.4157 \| 660 \| 0.8235 \| 0.6797 \| 0.8235 \| 0.9075 \| \| 0.4108 \| 7.4382 \| 662 \| 0.7339 \| 0.7742 \| 0.7339 \| 0.8567 \| \| 0.4108 \| 7.4607 \| 664 \| 0.7120 \| 0.7871 \| 0.7120 \| 0.8438 \| \| 0.4108 \| 7.4831 \| 666 \| 0.7130 \| 0.76 \| 0.7130 \| 0.8444 \| \| 0.4108 \| 7.5056 \| 668 \| 0.7107 \| 0.7871 \| 0.7107 \| 0.8430 \| \| 0.4108 \| 7.5281 \| 670 \| 0.7281 \| 0.7949 \| 0.7281 \| 0.8533 \| \| 0.4108 \| 7.5506 \| 672 \| 0.7606 \| 0.7742 \| 0.7606 \| 0.8721 \| \| 0.4108 \| 7.5730 \| 674 \| 0.8003 \| 0.7179 \| 0.8003 \| 0.8946 \| \| 0.4108 \| 7.5955 \| 676 \| 0.8399 \| 0.6709 \| 0.8399 \| 0.9165 \| \| 0.4108 \| 7.6180 \| 678 \| 0.8613 \| 0.6463 \| 0.8613 \| 0.9281 \| \| 0.4108 \| 7.6404 \| 680 \| 0.8270 \| 0.6871 \| 0.8270 \| 0.9094 \| \| 0.4108 \| 7.6629 \| 682 \| 0.7780 \| 0.7215 \| 0.7780 \| 0.8820 \| \| 0.4108 \| 7.6854 \| 684 \| 0.7576 \| 0.7742 \| 0.7576 \| 0.8704 \| \| 0.4108 \| 7.7079 \| 686 \| 0.7672 \| 0.7742 \| 0.7672 \| 0.8759 \| \| 0.4108 \| 7.7303 \| 688 \| 0.7841 \| 0.7451 \| 0.7841 \| 0.8855 \| \| 0.4108 \| 7.7528 \| 690 \| 0.7796 \| 0.7421 \| 0.7796 \| 0.8829 \| \| 0.4108 \| 7.7753 \| 692 \| 0.8324 \| 0.6709 \| 0.8324 \| 0.9124 \| \| 0.4108 \| 7.7978 \| 694 \| 0.8602 \| 0.6871 \| 0.8602 \| 0.9275 \| \| 0.4108 \| 7.8202 \| 696 \| 0.8447 \| 0.7073 \| 0.8447 \| 0.9191 \| \| 0.4108 \| 7.8427 \| 698 \| 0.7853 \| 0.7273 \| 0.7853 \| 0.8862 \| \| 0.4108 \| 7.8652 \| 700 \| 0.7673 \| 0.75 \| 0.7673 \| 0.8760 \| \| 0.4108 \| 7.8876 \| 702 \| 0.7676 \| 0.7574 \| 0.7676 \| 0.8762 \| \| 0.4108 \| 7.9101 \| 704 \| 0.7984 \| 0.7152 \| 0.7984 \| 0.8935 \| \| 0.4108 \| 7.9326 \| 706 \| 0.8097 \| 0.6790 \| 0.8097 \| 0.8998 \| \| 0.4108 \| 7.9551 \| 708 \| 0.8056 \| 0.6923 \| 0.8056 \| 0.8975 \| \| 0.4108 \| 7.9775 \| 710 \| 0.7782 \| 0.6933 \| 0.7782 \| 0.8821 \| \| 0.4108 \| 8.0 \| 712 \| 0.7368 \| 0.7582 \| 0.7368 \| 0.8583 \| \| 0.4108 \| 8.0225 \| 714 \| 0.7258 \| 0.7682 \| 0.7258 \| 0.8520 \| \| 0.4108 \| 8.0449 \| 716 \| 0.7294 \| 0.7682 \| 0.7294 \| 0.8541 \| \| 0.4108 \| 8.0674 \| 718 \| 0.7498 \| 0.7162 \| 0.7498 \| 0.8659 \| \| 0.4108 \| 8.0899 \| 720 \| 0.8073 \| 0.6667 \| 0.8073 \| 0.8985 \| \| 0.4108 \| 8.1124 \| 722 \| 0.8861 \| 0.6395 \| 0.8861 \| 0.9413 \| \| 0.4108 \| 8.1348 \| 724 \| 0.8883 \| 0.6438 \| 0.8883 \| 0.9425 \| \| 0.4108 \| 8.1573 \| 726 \| 0.8196 \| 0.6338 \| 0.8196 \| 0.9053 \| \| 0.4108 \| 8.1798 \| 728 \| 0.7533 \| 0.6950 \| 0.7533 \| 0.8679 \| \| 0.4108 \| 8.2022 \| 730 \| 0.7504 \| 0.7234 \| 0.7504 \| 0.8662 \| \| 0.4108 \| 8.2247 \| 732 \| 0.7668 \| 0.7234 \| 0.7668 \| 0.8757 \| \| 0.4108 \| 8.2472 \| 734 \| 0.7634 \| 0.7234 \| 0.7634 \| 0.8737 \| \| 0.4108 \| 8.2697 \| 736 \| 0.7420 \| 0.7143 \| 0.7420 \| 0.8614 \| \| 0.4108 \| 8.2921 \| 738 \| 0.7211 \| 0.7586 \| 0.7211 \| 0.8492 \| \| 0.4108 \| 8.3146 \| 740 \| 0.7228 \| 0.7534 \| 0.7228 \| 0.8502 \| \| 0.4108 \| 8.3371 \| 742 \| 0.7666 \| 0.6944 \| 0.7666 \| 0.8756 \| \| 0.4108 \| 8.3596 \| 744 \| 0.7875 \| 0.6286 \| 0.7875 \| 0.8874 \| \| 0.4108 \| 8.3820 \| 746 \| 0.7802 \| 0.6475 \| 0.7802 \| 0.8833 \| \| 0.4108 \| 8.4045 \| 748 \| 0.7427 \| 0.7092 \| 0.7427 \| 0.8618 \| \| 0.4108 \| 8.4270 \| 750 \| 0.7343 \| 0.7234 \| 0.7343 \| 0.8569 \| \| 0.4108 \| 8.4494 \| 752 \| 0.7432 \| 0.7234 \| 0.7432 \| 0.8621 \| \| 0.4108 \| 8.4719 \| 754 \| 0.7555 \| 0.7310 \| 0.7555 \| 0.8692 \| \| 0.4108 \| 8.4944 \| 756 \| 0.7775 \| 0.7467 \| 0.7775 \| 0.8818 \| \| 0.4108 \| 8.5169 \| 758 \| 0.7997 \| 0.7582 \| 0.7997 \| 0.8943 \| \| 0.4108 \| 8.5393 \| 760 \| 0.8284 \| 0.6923 \| 0.8284 \| 0.9102 \| \| 0.4108 \| 8.5618 \| 762 \| 0.8917 \| 0.6875 \| 0.8917 \| 0.9443 \| \| 0.4108 \| 8.5843 \| 764 \| 0.9260 \| 0.6624 \| 0.9260 \| 0.9623 \| \| 0.4108 \| 8.6067 \| 766 \| 0.8834 \| 0.6711 \| 0.8834 \| 0.9399 \| \| 0.4108 \| 8.6292 \| 768 \| 0.7681 \| 0.7152 \| 0.7681 \| 0.8764 \| \| 0.4108 \| 8.6517 \| 770 \| 0.6925 \| 0.7843 \| 0.6925 \| 0.8322 \| \| 0.4108 \| 8.6742 \| 772 \| 0.6811 \| 0.7733 \| 0.6811 \| 0.8253 \| \| 0.4108 \| 8.6966 \| 774 \| 0.6814 \| 0.7949 \| 0.6814 \| 0.8255 \| \| 0.4108 \| 8.7191 \| 776 \| 0.6917 \| 0.7949 \| 0.6917 \| 0.8317 \| \| 0.4108 \| 8.7416 \| 778 \| 0.7070 \| 0.7742 \| 0.7070 \| 0.8408 \| \| 0.4108 \| 8.7640 \| 780 \| 0.7199 \| 0.8 \| 0.7199 \| 0.8484 \| \| 0.4108 \| 8.7865 \| 782 \| 0.7148 \| 0.8 \| 0.7148 \| 0.8454 \| \| 0.4108 \| 8.8090 \| 784 \| 0.7058 \| 0.7949 \| 0.7058 \| 0.8401 \| \| 0.4108 \| 8.8315 \| 786 \| 0.7053 \| 0.8050 \| 0.7053 \| 0.8398 \| \| 0.4108 \| 8.8539 \| 788 \| 0.7390 \| 0.7853 \| 0.7390 \| 0.8596 \| \| 0.4108 \| 8.8764 \| 790 \| 0.7897 \| 0.7407 \| 0.7897 \| 0.8887 \| \| 0.4108 \| 8.8989 \| 792 \| 0.8494 \| 0.6941 \| 0.8494 \| 0.9216 \| \| 0.4108 \| 8.9213 \| 794 \| 0.8960 \| 0.6667 \| 0.8960 \| 0.9466 \| \| 0.4108 \| 8.9438 \| 796 \| 0.9026 \| 0.6746 \| 0.9026 \| 0.9501 \| \| 0.4108 \| 8.9663 \| 798 \| 0.8892 \| 0.7018 \| 0.8892 \| 0.9430 \| \| 0.4108 \| 8.9888 \| 800 \| 0.8590 \| 0.7135 \| 0.8590 \| 0.9268 \| \| 0.4108 \| 9.0112 \| 802 \| 0.8189 \| 0.7024 \| 0.8189 \| 0.9049 \| \| 0.4108 \| 9.0337 \| 804 \| 0.8683 \| 0.6941 \| 0.8683 \| 0.9318 \| \| 0.4108 \| 9.0562 \| 806 \| 0.8950 \| 0.6747 \| 0.8950 \| 0.9461 \| \| 0.4108 \| 9.0787 \| 808 \| 0.9466 \| 0.6386 \| 0.9466 \| 0.9729 \| \| 0.4108 \| 9.1011 \| 810 \| 0.8961 \| 0.6709 \| 0.8961 \| 0.9466 \| \| 0.4108 \| 9.1236 \| 812 \| 0.7832 \| 0.7190 \| 0.7832 \| 0.8850 \| \| 0.4108 \| 9.1461 \| 814 \| 0.7159 \| 0.7451 \| 0.7159 \| 0.8461 \| \| 0.4108 \| 9.1685 \| 816 \| 0.7033 \| 0.7582 \| 0.7033 \| 0.8386 \| \| 0.4108 \| 9.1910 \| 818 \| 0.7130 \| 0.7582 \| 0.7130 \| 0.8444 \| \| 0.4108 \| 9.2135 \| 820 \| 0.7455 \| 0.7237 \| 0.7455 \| 0.8634 \| \| 0.4108 \| 9.2360 \| 822 \| 0.7779 \| 0.7190 \| 0.7779 \| 0.8820 \| \| 0.4108 \| 9.2584 \| 824 \| 0.7932 \| 0.7237 \| 0.7932 \| 0.8906 \| \| 0.4108 \| 9.2809 \| 826 \| 0.7900 \| 0.7237 \| 0.7900 \| 0.8888 \| \| 0.4108 \| 9.3034 \| 828 \| 0.7522 \| 0.7105 \| 0.7522 \| 0.8673 \| \| 0.4108 \| 9.3258 \| 830 \| 0.7069 \| 0.7333 \| 0.7069 \| 0.8408 \| \| 0.4108 \| 9.3483 \| 832 \| 0.7039 \| 0.7467 \| 0.7039 \| 0.8390 \| \| 0.4108 \| 9.3708 \| 834 \| 0.7188 \| 0.7361 \| 0.7188 \| 0.8478 \| \| 0.4108 \| 9.3933 \| 836 \| 0.7636 \| 0.6950 \| 0.7636 \| 0.8738 \| \| 0.4108 \| 9.4157 \| 838 \| 0.7806 \| 0.6812 \| 0.7806 \| 0.8835 \| \| 0.4108 \| 9.4382 \| 840 \| 0.7602 \| 0.6667 \| 0.7602 \| 0.8719 \| \| 0.4108 \| 9.4607 \| 842 \| 0.7421 \| 0.7133 \| 0.7421 \| 0.8614 \| \| 0.4108 \| 9.4831 \| 844 \| 0.7280 \| 0.7248 \| 0.7280 \| 0.8532 \| \| 0.4108 \| 9.5056 \| 846 \| 0.7300 \| 0.7248 \| 0.7300 \| 0.8544 \| \| 0.4108 \| 9.5281 \| 848 \| 0.7692 \| 0.7190 \| 0.7692 \| 0.8770 \| \| 0.4108 \| 9.5506 \| 850 \| 0.7942 \| 0.7190 \| 0.7942 \| 0.8912 \| \| 0.4108 \| 9.5730 \| 852 \| 0.7760 \| 0.7075 \| 0.7760 \| 0.8809 \| \| 0.4108 \| 9.5955 \| 854 \| 0.7386 \| 0.7248 \| 0.7386 \| 0.8594 \| \| 0.4108 \| 9.6180 \| 856 \| 0.7129 \| 0.7248 \| 0.7129 \| 0.8444 \| \| 0.4108 \| 9.6404 \| 858 \| 0.7050 \| 0.7333 \| 0.7050 \| 0.8396 \| \| 0.4108 \| 9.6629 \| 860 \| 0.7291 \| 0.7368 \| 0.7291 \| 0.8539 \| \| 0.4108 \| 9.6854 \| 862 \| 0.7425 \| 0.7451 \| 0.7425 \| 0.8617 \| \| 0.4108 \| 9.7079 \| 864 \| 0.7430 \| 0.7368 \| 0.7430 \| 0.8620 \| \| 0.4108 \| 9.7303 \| 866 \| 0.7808 \| 0.7368 \| 0.7808 \| 0.8837 \| \| 0.4108 \| 9.7528 \| 868 \| 0.9250 \| 0.6429 \| 0.9250 \| 0.9618 \| \| 0.4108 \| 9.7753 \| 870 \| 0.9775 \| 0.6347 \| 0.9775 \| 0.9887 \| \| 0.4108 \| 9.7978 \| 872 \| 0.8964 \| 0.6503 \| 0.8964 \| 0.9468 \| \| 0.4108 \| 9.8202 \| 874 \| 0.7878 \| 0.7436 \| 0.7878 \| 0.8876 \| \| 0.4108 \| 9.8427 \| 876 \| 0.7188 \| 0.7662 \| 0.7188 \| 0.8478 \| \| 0.4108 \| 9.8652 \| 878 \| 0.6850 \| 0.7871 \| 0.6850 \| 0.8276 \| \| 0.4108 \| 9.8876 \| 880 \| 0.6926 \| 0.7662 \| 0.6926 \| 0.8322 \| \| 0.4108 \| 9.9101 \| 882 \| 0.7107 \| 0.7550 \| 0.7107 \| 0.8430 \| \| 0.4108 \| 9.9326 \| 884 \| 0.7245 \| 0.7432 \| 0.7245 \| 0.8512 \| \| 0.4108 \| 9.9551 \| 886 \| 0.7322 \| 0.7310 \| 0.7322 \| 0.8557 \| \| 0.4108 \| 9.9775 \| 888 \| 0.7489 \| 0.7361 \| 0.7489 \| 0.8654 \| \| 0.4108 \| 10.0 \| 890 \| 0.7577 \| 0.7361 \| 0.7577 \| 0.8705 \| \| 0.4108 \| 10.0225 \| 892 \| 0.7513 \| 0.7361 \| 0.7513 \| 0.8668 \| \| 0.4108 \| 10.0449 \| 894 \| 0.7598 \| 0.7133 \| 0.7598 \| 0.8717 \| \| 0.4108 \| 10.0674 \| 896 \| 0.7931 \| 0.6522 \| 0.7931 \| 0.8906 \| \| 0.4108 \| 10.0899 \| 898 \| 0.8341 \| 0.6423 \| 0.8341 \| 0.9133 \| \| 0.4108 \| 10.1124 \| 900 \| 0.8211 \| 0.6522 \| 0.8211 \| 0.9061 \| \| 0.4108 \| 10.1348 \| 902 \| 0.7625 \| 0.6763 \| 0.7625 \| 0.8732 \| \| 0.4108 \| 10.1573 \| 904 \| 0.7206 \| 0.7234 \| 0.7206 \| 0.8489 \| \| 0.4108 \| 10.1798 \| 906 \| 0.6887 \| 0.7234 \| 0.6887 \| 0.8299 \| \| 0.4108 \| 10.2022 \| 908 \| 0.6599 \| 0.7448 \| 0.6599 \| 0.8124 \| \| 0.4108 \| 10.2247 \| 910 \| 0.6414 \| 0.7671 \| 0.6414 \| 0.8009 \| \| 0.4108 \| 10.2472 \| 912 \| 0.6461 \| 0.7586 \| 0.6461 \| 0.8038 \| \| 0.4108 \| 10.2697 \| 914 \| 0.6742 \| 0.7413 \| 0.6742 \| 0.8211 \| \| 0.4108 \| 10.2921 \| 916 \| 0.7835 \| 0.6809 \| 0.7835 \| 0.8851 \| \| 0.4108 \| 10.3146 \| 918 \| 0.8354 \| 0.6475 \| 0.8354 \| 0.9140 \| \| 0.4108 \| 10.3371 \| 920 \| 0.7677 \| 0.6761 \| 0.7677 \| 0.8762 \| \| 0.4108 \| 10.3596 \| 922 \| 0.6541 \| 0.7222 \| 0.6541 \| 0.8088 \| \| 0.4108 \| 10.3820 \| 924 \| 0.6368 \| 0.7733 \| 0.6368 \| 0.7980 \| \| 0.4108 \| 10.4045 \| 926 \| 0.6619 \| 0.7949 \| 0.6619 \| 0.8136 \| \| 0.4108 \| 10.4270 \| 928 \| 0.7138 \| 0.7975 \| 0.7138 \| 0.8449 \| \| 0.4108 \| 10.4494 \| 930 \| 0.7559 \| 0.7692 \| 0.7559 \| 0.8694 \| \| 0.4108 \| 10.4719 \| 932 \| 0.7835 \| 0.75 \| 0.7836 \| 0.8852 \| \| 0.4108 \| 10.4944 \| 934 \| 0.7897 \| 0.7425 \| 0.7897 \| 0.8887 \| \| 0.4108 \| 10.5169 \| 936 \| 0.8144 \| 0.7349 \| 0.8144 \| 0.9024 \| \| 0.4108 \| 10.5393 \| 938 \| 0.8365 \| 0.7051 \| 0.8365 \| 0.9146 \| \| 0.4108 \| 10.5618 \| 940 \| 0.8405 \| 0.6928 \| 0.8405 \| 0.9168 \| \| 0.4108 \| 10.5843 \| 942 \| 0.8292 \| 0.6579 \| 0.8292 \| 0.9106 \| \| 0.4108 \| 10.6067 \| 944 \| 0.7814 \| 0.7143 \| 0.7814 \| 0.8840 \| \| 0.4108 \| 10.6292 \| 946 \| 0.7252 \| 0.7516 \| 0.7252 \| 0.8516 \| \| 0.4108 \| 10.6517 \| 948 \| 0.6647 \| 0.7722 \| 0.6647 \| 0.8153 \| \| 0.4108 \| 10.6742 \| 950 \| 0.6261 \| 0.7843 \| 0.6261 \| 0.7913 \| \| 0.4108 \| 10.6966 \| 952 \| 0.6143 \| 0.7517 \| 0.6143 \| 0.7838 \| \| 0.4108 \| 10.7191 \| 954 \| 0.6057 \| 0.7733 \| 0.6057 \| 0.7783 \| \| 0.4108 \| 10.7416 \| 956 \| 0.5955 \| 0.7799 \| 0.5955 \| 0.7717 \| \| 0.4108 \| 10.7640 \| 958 \| 0.6243 \| 0.7975 \| 0.6243 \| 0.7901 \| \| 0.4108 \| 10.7865 \| 960 \| 0.7047 \| 0.7453 \| 0.7047 \| 0.8395 \| \| 0.4108 \| 10.8090 \| 962 \| 0.8036 \| 0.725 \| 0.8036 \| 0.8964 \| \| 0.4108 \| 10.8315 \| 964 \| 0.8204 \| 0.7006 \| 0.8204 \| 0.9058 \| \| 0.4108 \| 10.8539 \| 966 \| 0.7663 \| 0.6974 \| 0.7663 \| 0.8754 \| \| 0.4108 \| 10.8764 \| 968 \| 0.6950 \| 0.7397 \| 0.6950 \| 0.8336 \| \| 0.4108 \| 10.8989 \| 970 \| 0.6610 \| 0.7397 \| 0.6610 \| 0.8130 \| \| 0.4108 \| 10.9213 \| 972 \| 0.6401 \| 0.7733 \| 0.6401 \| 0.8001 \| \| 0.4108 \| 10.9438 \| 974 \| 0.6417 \| 0.8050 \| 0.6417 \| 0.8011 \| \| 0.4108 \| 10.9663 \| 976 \| 0.7302 \| 0.7362 \| 0.7302 \| 0.8545 \| \| 0.4108 \| 10.9888 \| 978 \| 0.8548 \| 0.7186 \| 0.8548 \| 0.9245 \| \| 0.4108 \| 11.0112 \| 980 \| 0.9575 \| 0.6747 \| 0.9575 \| 0.9785 \| \| 0.4108 \| 11.0337 \| 982 \| 0.9180 \| 0.6875 \| 0.9180 \| 0.9581 \| \| 0.4108 \| 11.0562 \| 984 \| 0.8190 \| 0.7308 \| 0.8190 \| 0.9050 \| \| 0.4108 \| 11.0787 \| 986 \| 0.7186 \| 0.7226 \| 0.7186 \| 0.8477 \| \| 0.4108 \| 11.1011 \| 988 \| 0.6561 \| 0.7534 \| 0.6561 \| 0.8100 \| \| 0.4108 \| 11.1236 \| 990 \| 0.6681 \| 0.7586 \| 0.6681 \| 0.8174 \| \| 0.4108 \| 11.1461 \| 992 \| 0.6943 \| 0.7234 \| 0.6943 \| 0.8332 \| \| 0.4108 \| 11.1685 \| 994 \| 0.7027 \| 0.7234 \| 0.7027 \| 0.8383 \| \| 0.4108 \| 11.1910 \| 996 \| 0.7129 \| 0.75 \| 0.7129 \| 0.8444 \| \| 0.4108 \| 11.2135 \| 998 \| 0.7362 \| 0.7133 \| 0.7362 \| 0.8580 \| \| 0.0902 \| 11.2360 \| 1000 \| 0.7913 \| 0.6331 \| 0.7913 \| 0.8895 \| \| 0.0902 \| 11.2584 \| 1002 \| 0.8354 \| 0.6197 \| 0.8354 \| 0.9140 \| \| 0.0902 \| 11.2809 \| 1004 \| 0.8424 \| 0.6438 \| 0.8424 \| 0.9178 \| \| 0.0902 \| 11.3034 \| 1006 \| 0.7741 \| 0.6846 \| 0.7741 \| 0.8798 \| \| 0.0902 \| 11.3258 \| 1008 \| 0.6986 \| 0.7222 \| 0.6986 \| 0.8358 \| \| 0.0902 \| 11.3483 \| 1010 \| 0.6959 \| 0.7222 \| 0.6959 \| 0.8342 \| \| 0.0902 \| 11.3708 \| 1012 \| 0.7097 \| 0.7222 \| 0.7097 \| 0.8424 \| \| 0.0902 \| 11.3933 \| 1014 \| 0.7227 \| 0.7222 \| 0.7227 \| 0.8501 \| \| 0.0902 \| 11.4157 \| 1016 \| 0.7240 \| 0.7222 \| 0.7240 \| 0.8509 \| \| 0.0902 \| 11.4382 \| 1018 \| 0.7231 \| 0.7183 \| 0.7231 \| 0.8504 \| \| 0.0902 \| 11.4607 \| 1020 \| 0.7425 \| 0.7183 \| 0.7425 \| 0.8617 \| \| 0.0902 \| 11.4831 \| 1022 \| 0.7399 \| 0.6857 \| 0.7399 \| 0.8602 \| \| 0.0902 \| 11.5056 \| 1024 \| 0.7269 \| 0.6950 \| 0.7269 \| 0.8526 \| \| 0.0902 \| 11.5281 \| 1026 \| 0.7119 \| 0.6901 \| 0.7119 \| 0.8437 \| \| 0.0902 \| 11.5506 \| 1028 \| 0.7208 \| 0.6939 \| 0.7208 \| 0.8490 \| \| 0.0902 \| 11.5730 \| 1030 \| 0.7919 \| 0.6839 \| 0.7919 \| 0.8899 \| \| 0.0902 \| 11.5955 \| 1032 \| 0.8472 \| 0.6753 \| 0.8472 \| 0.9204 \| \| 0.0902 \| 11.6180 \| 1034 \| 0.8890 \| 0.6623 \| 0.8890 \| 0.9428 \| \| 0.0902 \| 11.6404 \| 1036 \| 0.8065 \| 0.6839 \| 0.8065 \| 0.8980 \| \| 0.0902 \| 11.6629 \| 1038 \| 0.7126 \| 0.7403 \| 0.7126 \| 0.8442 \| \| 0.0902 \| 11.6854 \| 1040 \| 0.6552 \| 0.7742 \| 0.6552 \| 0.8095 \| \| 0.0902 \| 11.7079 \| 1042 \| 0.6468 \| 0.7949 \| 0.6468 \| 0.8043 \| \| 0.0902 \| 11.7303 \| 1044 \| 0.6622 \| 0.7949 \| 0.6622 \| 0.8137 \| \| 0.0902 \| 11.7528 \| 1046 \| 0.6878 \| 0.7692 \| 0.6878 \| 0.8294 \| \| 0.0902 \| 11.7753 \| 1048 \| 0.6873 \| 0.7742 \| 0.6873 \| 0.8290 \| \| 0.0902 \| 11.7978 \| 1050 \| 0.6694 \| 0.7662 \| 0.6694 \| 0.8182 \| \| 0.0902 \| 11.8202 \| 1052 \| 0.6394 \| 0.7843 \| 0.6394 \| 0.7996 \| \| 0.0902 \| 11.8427 \| 1054 \| 0.6176 \| 0.7843 \| 0.6176 \| 0.7859 \| \| 0.0902 \| 11.8652 \| 1056 \| 0.6236 \| 0.7763 \| 0.6236 \| 0.7897 \| \| 0.0902 \| 11.8876 \| 1058 \| 0.6418 \| 0.7792 \| 0.6418 \| 0.8011 \| \| 0.0902 \| 11.9101 \| 1060 \| 0.6360 \| 0.7722 \| 0.6360 \| 0.7975 \| \| 0.0902 \| 11.9326 \| 1062 \| 0.6413 \| 0.775 \| 0.6413 \| 0.8008 \| \| 0.0902 \| 11.9551 \| 1064 \| 0.6599 \| 0.775 \| 0.6599 \| 0.8123 \| \| 0.0902 \| 11.9775 \| 1066 \| 0.6832 \| 0.775 \| 0.6832 \| 0.8266 \| \| 0.0902 \| 12.0 \| 1068 \| 0.7074 \| 0.7799 \| 0.7074 \| 0.8411 \| \| 0.0902 \| 12.0225 \| 1070 \| 0.7394 \| 0.7703 \| 0.7394 \| 0.8599 \| \| 0.0902 \| 12.0449 \| 1072 \| 0.7905 \| 0.6944 \| 0.7905 \| 0.8891 \| \| 0.0902 \| 12.0674 \| 1074 \| 0.8131 \| 0.7133 \| 0.8131 \| 0.9017 \| \| 0.0902 \| 12.0899 \| 1076 \| 0.7863 \| 0.7273 \| 0.7863 \| 0.8867 \| \| 0.0902 \| 12.1124 \| 1078 \| 0.7514 \| 0.7534 \| 0.7514 \| 0.8668 \| \| 0.0902 \| 12.1348 \| 1080 \| 0.7385 \| 0.6667 \| 0.7385 \| 0.8594 \| \| 0.0902 \| 12.1573 \| 1082 \| 0.7411 \| 0.6667 \| 0.7411 \| 0.8609 \| \| 0.0902 \| 12.1798 \| 1084 \| 0.7129 \| 0.6757 \| 0.7129 \| 0.8443 \| \| 0.0902 \| 12.2022 \| 1086 \| 0.6768 \| 0.6892 \| 0.6768 \| 0.8227 \| \| 0.0902 \| 12.2247 \| 1088 \| 0.6493 \| 0.7413 \| 0.6493 \| 0.8058 \| \| 0.0902 \| 12.2472 \| 1090 \| 0.6430 \| 0.7671 \| 0.6430 \| 0.8019 \| \| 0.0902 \| 12.2697 \| 1092 \| 0.6493 \| 0.7586 \| 0.6493 \| 0.8058 \| \| 0.0902 \| 12.2921 \| 1094 \| 0.6675 \| 0.7413 \| 0.6675 \| 0.8170 \| \| 0.0902 \| 12.3146 \| 1096 \| 0.7245 \| 0.6901 \| 0.7245 \| 0.8512 \| \| 0.0902 \| 12.3371 \| 1098 \| 0.8463 \| 0.6575 \| 0.8463 \| 0.9199 \| \| 0.0902 \| 12.3596 \| 1100 \| 0.9309 \| 0.6483 \| 0.9309 \| 0.9648 \| \| 0.0902 \| 12.3820 \| 1102 \| 0.9031 \| 0.6667 \| 0.9031 \| 0.9503 \| \| 0.0902 \| 12.4045 \| 1104 \| 0.7976 \| 0.6761 \| 0.7976 \| 0.8931 \| \| 0.0902 \| 12.4270 \| 1106 \| 0.6976 \| 0.7448 \| 0.6976 \| 0.8352 \| \| 0.0902 \| 12.4494 \| 1108 \| 0.6741 \| 0.7671 \| 0.6741 \| 0.8210 \| \| 0.0902 \| 12.4719 \| 1110 \| 0.6870 \| 0.7050 \| 0.6870 \| 0.8289 \| \| 0.0902 \| 12.4944 \| 1112 \| 0.6879 \| 0.7413 \| 0.6879 \| 0.8294 \| \| 0.0902 \| 12.5169 \| 1114 \| 0.6805 \| 0.75 \| 0.6805 \| 0.8249 \| \| 0.0902 \| 12.5393 \| 1116 \| 0.6757 \| 0.7586 \| 0.6757 \| 0.8220 \| \| 0.0902 \| 12.5618 \| 1118 \| 0.6882 \| 0.7534 \| 0.6882 \| 0.8296 \| \| 0.0902 \| 12.5843 \| 1120 \| 0.7040 \| 0.7123 \| 0.7040 \| 0.8391 \| \| 0.0902 \| 12.6067 \| 1122 \| 0.6870 \| 0.7432 \| 0.6870 \| 0.8289 \| \| 0.0902 \| 12.6292 \| 1124 \| 0.6693 \| 0.7619 \| 0.6693 \| 0.8181 \| \| 0.0902 \| 12.6517 \| 1126 \| 0.6815 \| 0.7361 \| 0.6815 \| 0.8256 \| \| 0.0902 \| 12.6742 \| 1128 \| 0.7148 \| 0.7133 \| 0.7148 \| 0.8455 \| \| 0.0902 \| 12.6966 \| 1130 \| 0.7334 \| 0.6901 \| 0.7334 \| 0.8564 \| \| 0.0902 \| 12.7191 \| 1132 \| 0.7092 \| 0.6944 \| 0.7092 \| 0.8421 \| \| 0.0902 \| 12.7416 \| 1134 \| 0.6664 \| 0.7361 \| 0.6664 \| 0.8164 \| \| 0.0902 \| 12.7640 \| 1136 \| 0.6453 \| 0.7703 \| 0.6453 \| 0.8033 \| \| 0.0902 \| 12.7865 \| 1138 \| 0.6592 \| 0.7682 \| 0.6592 \| 0.8119 \| \| 0.0902 \| 12.8090 \| 1140 \| 0.6804 \| 0.7448 \| 0.6804 \| 0.8249 \| \| 0.0902 \| 12.8315 \| 1142 \| 0.7077 \| 0.75 \| 0.7077 \| 0.8413 \| \| 0.0902 \| 12.8539 \| 1144 \| 0.7501 \| 0.6950 \| 0.7501 \| 0.8661 \| \| 0.0902 \| 12.8764 \| 1146 \| 0.7861 \| 0.6620 \| 0.7861 \| 0.8866 \| \| 0.0902 \| 12.8989 \| 1148 \| 0.7880 \| 0.6620 \| 0.7880 \| 0.8877 \| \| 0.0902 \| 12.9213 \| 1150 \| 0.7739 \| 0.6986 \| 0.7739 \| 0.8797 \| \| 0.0902 \| 12.9438 \| 1152 \| 0.7630 \| 0.7114 \| 0.7630 \| 0.8735 \| \| 0.0902 \| 12.9663 \| 1154 \| 0.7492 \| 0.7067 \| 0.7492 \| 0.8656 \| \| 0.0902 \| 12.9888 \| 1156 \| 0.7518 \| 0.7105 \| 0.7518 \| 0.8670 \| \| 0.0902 \| 13.0112 \| 1158 \| 0.7827 \| 0.6968 \| 0.7827 \| 0.8847 \| \| 0.0902 \| 13.0337 \| 1160 \| 0.7917 \| 0.7037 \| 0.7917 \| 0.8898 \| \| 0.0902 \| 13.0562 \| 1162 \| 0.7680 \| 0.7108 \| 0.7680 \| 0.8764 \| \| 0.0902 \| 13.0787 \| 1164 \| 0.7283 \| 0.7545 \| 0.7283 \| 0.8534 \| \| 0.0902 \| 13.1011 \| 1166 \| 0.6815 \| 0.7619 \| 0.6815 \| 0.8255 \| \| 0.0902 \| 13.1236 \| 1168 \| 0.6469 \| 0.7799 \| 0.6469 \| 0.8043 \| \| 0.0902 \| 13.1461 \| 1170 \| 0.6309 \| 0.7949 \| 0.6309 \| 0.7943 \| \| 0.0902 \| 13.1685 \| 1172 \| 0.6314 \| 0.7949 \| 0.6314 \| 0.7946 \| \| 0.0902 \| 13.1910 \| 1174 \| 0.6307 \| 0.7949 \| 0.6307 \| 0.7942 \| \| 0.0902 \| 13.2135 \| 1176 \| 0.6444 \| 0.7871 \| 0.6444 \| 0.8028 \| \| 0.0902 \| 13.2360 \| 1178 \| 0.6747 \| 0.7792 \| 0.6747 \| 0.8214 \| \| 0.0902 \| 13.2584 \| 1180 \| 0.6891 \| 0.7712 \| 0.6891 \| 0.8301 \| \| 0.0902 \| 13.2809 \| 1182 \| 0.6867 \| 0.7712 \| 0.6867 \| 0.8287 \| \| 0.0902 \| 13.3034 \| 1184 \| 0.6621 \| 0.76 \| 0.6621 \| 0.8137 \| \| 0.0902 \| 13.3258 \| 1186 \| 0.6470 \| 0.7682 \| 0.6470 \| 0.8043 \| \| 0.0902 \| 13.3483 \| 1188 \| 0.6416 \| 0.7763 \| 0.6416 \| 0.8010 \| \| 0.0902 \| 13.3708 \| 1190 \| 0.6360 \| 0.7763 \| 0.6360 \| 0.7975 \| \| 0.0902 \| 13.3933 \| 1192 \| 0.6297 \| 0.7682 \| 0.6297 \| 0.7936 \| \| 0.0902 \| 13.4157 \| 1194 \| 0.6456 \| 0.7682 \| 0.6456 \| 0.8035 \| \| 0.0902 \| 13.4382 \| 1196 \| 0.6563 \| 0.7771 \| 0.6563 \| 0.8101 \| \| 0.0902 \| 13.4607 \| 1198 \| 0.6641 \| 0.7692 \| 0.6641 \| 0.8149 \| \| 0.0902 \| 13.4831 \| 1200 \| 0.6807 \| 0.7484 \| 0.6807 \| 0.8251 \| \| 0.0902 \| 13.5056 \| 1202 \| 0.6735 \| 0.7692 \| 0.6735 \| 0.8207 \| \| 0.0902 \| 13.5281 \| 1204 \| 0.6445 \| 0.7582 \| 0.6445 \| 0.8028 \| \| 0.0902 \| 13.5506 \| 1206 \| 0.6326 \| 0.7792 \| 0.6326 \| 0.7953 \| \| 0.0902 \| 13.5730 \| 1208 \| 0.6318 \| 0.7792 \| 0.6318 \| 0.7948 \| \| 0.0902 \| 13.5955 \| 1210 \| 0.6403 \| 0.7692 \| 0.6403 \| 0.8002 \| \| 0.0902 \| 13.6180 \| 1212 \| 0.6905 \| 0.7547 \| 0.6905 \| 0.8310 \| \| 0.0902 \| 13.6404 \| 1214 \| 0.7628 \| 0.7425 \| 0.7628 \| 0.8734 \| \| 0.0902 \| 13.6629 \| 1216 \| 0.8088 \| 0.7045 \| 0.8088 \| 0.8994 \| \| 0.0902 \| 13.6854 \| 1218 \| 0.8127 \| 0.7293 \| 0.8127 \| 0.9015 \| \| 0.0902 \| 13.7079 \| 1220 \| 0.8216 \| 0.7363 \| 0.8216 \| 0.9064 \| \| 0.0902 \| 13.7303 \| 1222 \| 0.8397 \| 0.7363 \| 0.8397 \| 0.9164 \| \| 0.0902 \| 13.7528 \| 1224 \| 0.8094 \| 0.7541 \| 0.8094 \| 0.8997 \| \| 0.0902 \| 13.7753 \| 1226 \| 0.7963 \| 0.7444 \| 0.7963 \| 0.8923 \| \| 0.0902 \| 13.7978 \| 1228 \| 0.8017 \| 0.7444 \| 0.8017 \| 0.8954 \| \| 0.0902 \| 13.8202 \| 1230 \| 0.8622 \| 0.7263 \| 0.8622 \| 0.9286 \| \| 0.0902 \| 13.8427 \| 1232 \| 0.9431 \| 0.6742 \| 0.9431 \| 0.9711 \| \| 0.0902 \| 13.8652 \| 1234 \| 0.9269 \| 0.6857 \| 0.9269 \| 0.9628 \| \| 0.0902 \| 13.8876 \| 1236 \| 0.8206 \| 0.7093 \| 0.8206 \| 0.9059 \| \| 0.0902 \| 13.9101 \| 1238 \| 0.7411 \| 0.7468 \| 0.7411 \| 0.8609 \| \| 0.0902 \| 13.9326 \| 1240 \| 0.7126 \| 0.7368 \| 0.7126 \| 0.8442 \| \| 0.0902 \| 13.9551 \| 1242 \| 0.7678 \| 0.6713 \| 0.7678 \| 0.8762 \| \| 0.0902 \| 13.9775 \| 1244 \| 0.8350 \| 0.6475 \| 0.8350 \| 0.9138 \| \| 0.0902 \| 14.0 \| 1246 \| 0.8394 \| 0.6475 \| 0.8394 \| 0.9162 \| \| 0.0902 \| 14.0225 \| 1248 \| 0.8266 \| 0.5985 \| 0.8266 \| 0.9092 \| \| 0.0902 \| 14.0449 \| 1250 \| 0.7328 \| 0.6618 \| 0.7328 \| 0.8561 \| \| 0.0902 \| 14.0674 \| 1252 \| 0.6881 \| 0.7 \| 0.6881 \| 0.8295 \| \| 0.0902 \| 14.0899 \| 1254 \| 0.6485 \| 0.6993 \| 0.6485 \| 0.8053 \| \| 0.0902 \| 14.1124 \| 1256 \| 0.6188 \| 0.7568 \| 0.6188 \| 0.7867 \| \| 0.0902 \| 14.1348 \| 1258 \| 0.6284 \| 0.7763 \| 0.6284 \| 0.7927 \| \| 0.0902 \| 14.1573 \| 1260 \| 0.6399 \| 0.7763 \| 0.6399 \| 0.8000 \| \| 0.0902 \| 14.1798 \| 1262 \| 0.6428 \| 0.7843 \| 0.6428 \| 0.8017 \| \| 0.0902 \| 14.2022 \| 1264 \| 0.6348 \| 0.7843 \| 0.6348 \| 0.7967 \| \| 0.0902 \| 14.2247 \| 1266 \| 0.6232 \| 0.7733 \| 0.6232 \| 0.7894 \| \| 0.0902 \| 14.2472 \| 1268 \| 0.6153 \| 0.7534 \| 0.6153 \| 0.7844 \| \| 0.0902 \| 14.2697 \| 1270 \| 0.6003 \| 0.7534 \| 0.6003 \| 0.7748 \| \| 0.0902 \| 14.2921 \| 1272 \| 0.5946 \| 0.7619 \| 0.5946 \| 0.7711 \| \| 0.0902 \| 14.3146 \| 1274 \| 0.5945 \| 0.7619 \| 0.5945 \| 0.7711 \| \| 0.0902 \| 14.3371 \| 1276 \| 0.5865 \| 0.7619 \| 0.5865 \| 0.7658 \| \| 0.0902 \| 14.3596 \| 1278 \| 0.5915 \| 0.7534 \| 0.5915 \| 0.7691 \| \| 0.0902 \| 14.3820 \| 1280 \| 0.6255 \| 0.7534 \| 0.6255 \| 0.7909 \| \| 0.0902 \| 14.4045 \| 1282 \| 0.6337 \| 0.7534 \| 0.6337 \| 0.7961 \| \| 0.0902 \| 14.4270 \| 1284 \| 0.6298 \| 0.7534 \| 0.6298 \| 0.7936 \| \| 0.0902 \| 14.4494 \| 1286 \| 0.6248 \| 0.7651 \| 0.6248 \| 0.7905 \| \| 0.0902 \| 14.4719 \| 1288 \| 0.6185 \| 0.7871 \| 0.6185 \| 0.7865 \| \| 0.0902 \| 14.4944 \| 1290 \| 0.6037 \| 0.7949 \| 0.6037 \| 0.7770 \| \| 0.0902 \| 14.5169 \| 1292 \| 0.5979 \| 0.7949 \| 0.5979 \| 0.7733 \| \| 0.0902 \| 14.5393 \| 1294 \| 0.6044 \| 0.7949 \| 0.6044 \| 0.7774 \| \| 0.0902 \| 14.5618 \| 1296 \| 0.6157 \| 0.8050 \| 0.6157 \| 0.7846 \| \| 0.0902 \| 14.5843 \| 1298 \| 0.6444 \| 0.7879 \| 0.6444 \| 0.8028 \| \| 0.0902 \| 14.6067 \| 1300 \| 0.6733 \| 0.7738 \| 0.6733 \| 0.8205 \| \| 0.0902 \| 14.6292 \| 1302 \| 0.7218 \| 0.7674 \| 0.7218 \| 0.8496 \| \| 0.0902 \| 14.6517 \| 1304 \| 0.7525 \| 0.7543 \| 0.7525 \| 0.8675 \| \| 0.0902 \| 14.6742 \| 1306 \| 0.7656 \| 0.7640 \| 0.7656 \| 0.8750 \| \| 0.0902 \| 14.6966 \| 1308 \| 0.7987 \| 0.7086 \| 0.7987 \| 0.8937 \| \| 0.0902 \| 14.7191 \| 1310 \| 0.8112 \| 0.7045 \| 0.8112 \| 0.9007 \| \| 0.0902 \| 14.7416 \| 1312 \| 0.8417 \| 0.6932 \| 0.8417 \| 0.9174 \| \| 0.0902 \| 14.7640 \| 1314 \| 0.7978 \| 0.6941 \| 0.7978 \| 0.8932 \| \| 0.0902 \| 14.7865 \| 1316 \| 0.7087 \| 0.7179 \| 0.7087 \| 0.8419 \| \| 0.0902 \| 14.8090 \| 1318 \| 0.6274 \| 0.7792 \| 0.6274 \| 0.7921 \| \| 0.0902 \| 14.8315 \| 1320 \| 0.6026 \| 0.7733 \| 0.6026 \| 0.7762 \| \| 0.0902 \| 14.8539 \| 1322 \| 0.6035 \| 0.7651 \| 0.6035 \| 0.7769 \| \| 0.0902 \| 14.8764 \| 1324 \| 0.6007 \| 0.7651 \| 0.6007 \| 0.7751 \| \| 0.0902 \| 14.8989 \| 1326 \| 0.5988 \| 0.7534 \| 0.5988 \| 0.7738 \| \| 0.0902 \| 14.9213 \| 1328 \| 0.6025 \| 0.7534 \| 0.6025 \| 0.7762 \| \| 0.0902 \| 14.9438 \| 1330 \| 0.6074 \| 0.7534 \| 0.6074 \| 0.7794 \| \| 0.0902 \| 14.9663 \| 1332 \| 0.6149 \| 0.7534 \| 0.6149 \| 0.7842 \| \| 0.0902 \| 14.9888 \| 1334 \| 0.6369 \| 0.7534 \| 0.6369 \| 0.7981 \| \| 0.0902 \| 15.0112 \| 1336 \| 0.6929 \| 0.6901 \| 0.6929 \| 0.8324 \| \| 0.0902 \| 15.0337 \| 1338 \| 0.7589 \| 0.6429 \| 0.7589 \| 0.8712 \| \| 0.0902 \| 15.0562 \| 1340 \| 0.8354 \| 0.6429 \| 0.8354 \| 0.9140 \| \| 0.0902 \| 15.0787 \| 1342 \| 0.8459 \| 0.6429 \| 0.8459 \| 0.9197 \| \| 0.0902 \| 15.1011 \| 1344 \| 0.7767 \| 0.6429 \| 0.7767 \| 0.8813 \| \| 0.0902 \| 15.1236 \| 1346 \| 0.6776 \| 0.7133 \| 0.6776 \| 0.8232 \| \| 0.0902 \| 15.1461 \| 1348 \| 0.6352 \| 0.7534 \| 0.6352 \| 0.7970 \| \| 0.0902 \| 15.1685 \| 1350 \| 0.6148 \| 0.7534 \| 0.6148 \| 0.7841 \| \| 0.0902 \| 15.1910 \| 1352 \| 0.6157 \| 0.7651 \| 0.6157 \| 0.7847 \| \| 0.0902 \| 15.2135 \| 1354 \| 0.6375 \| 0.7448 \| 0.6375 \| 0.7984 \| \| 0.0902 \| 15.2360 \| 1356 \| 0.6892 \| 0.6993 \| 0.6892 \| 0.8302 \| \| 0.0902 \| 15.2584 \| 1358 \| 0.7375 \| 0.6429 \| 0.7375 \| 0.8588 \| \| 0.0902 \| 15.2809 \| 1360 \| 0.7440 \| 0.6277 \| 0.7440 \| 0.8626 \| \| 0.0902 \| 15.3034 \| 1362 \| 0.7051 \| 0.6857 \| 0.7051 \| 0.8397 \| \| 0.0902 \| 15.3258 \| 1364 \| 0.6784 \| 0.7324 \| 0.6784 \| 0.8236 \| \| 0.0902 \| 15.3483 \| 1366 \| 0.6693 \| 0.7413 \| 0.6693 \| 0.8181 \| \| 0.0902 \| 15.3708 \| 1368 \| 0.6865 \| 0.7092 \| 0.6865 \| 0.8285 \| \| 0.0902 \| 15.3933 \| 1370 \| 0.7129 \| 0.7034 \| 0.7129 \| 0.8443 \| \| 0.0902 \| 15.4157 \| 1372 \| 0.7180 \| 0.6806 \| 0.7180 \| 0.8473 \| \| 0.0902 \| 15.4382 \| 1374 \| 0.7093 \| 0.6713 \| 0.7093 \| 0.8422 \| \| 0.0902 \| 15.4607 \| 1376 \| 0.7080 \| 0.6939 \| 0.7080 \| 0.8414 \| \| 0.0902 \| 15.4831 \| 1378 \| 0.7029 \| 0.6939 \| 0.7029 \| 0.8384 \| \| 0.0902 \| 15.5056 \| 1380 \| 0.6650 \| 0.7467 \| 0.6650 \| 0.8155 \| \| 0.0902 \| 15.5281 \| 1382 \| 0.6446 \| 0.7792 \| 0.6446 \| 0.8029 \| \| 0.0902 \| 15.5506 \| 1384 \| 0.6390 \| 0.7871 \| 0.6390 \| 0.7994 \| \| 0.0902 \| 15.5730 \| 1386 \| 0.6562 \| 0.7975 \| 0.6562 \| 0.8100 \| \| 0.0902 \| 15.5955 \| 1388 \| 0.6837 \| 0.7771 \| 0.6837 \| 0.8269 \| \| 0.0902 \| 15.6180 \| 1390 \| 0.7191 \| 0.7342 \| 0.7191 \| 0.8480 \| \| 0.0902 \| 15.6404 \| 1392 \| 0.7462 \| 0.6957 \| 0.7462 \| 0.8638 \| \| 0.0902 \| 15.6629 \| 1394 \| 0.7638 \| 0.6957 \| 0.7638 \| 0.8740 \| \| 0.0902 \| 15.6854 \| 1396 \| 0.7883 \| 0.6914 \| 0.7883 \| 0.8879 \| \| 0.0902 \| 15.7079 \| 1398 \| 0.7537 \| 0.7073 \| 0.7537 \| 0.8682 \| \| 0.0902 \| 15.7303 \| 1400 \| 0.6628 \| 0.7561 \| 0.6628 \| 0.8141 \| \| 0.0902 \| 15.7528 \| 1402 \| 0.5868 \| 0.7901 \| 0.5868 \| 0.7660 \| \| 0.0902 \| 15.7753 \| 1404 \| 0.5742 \| 0.7853 \| 0.5742 \| 0.7577 \| \| 0.0902 \| 15.7978 \| 1406 \| 0.5841 \| 0.8 \| 0.5841 \| 0.7642 \| \| 0.0902 \| 15.8202 \| 1408 \| 0.5942 \| 0.7853 \| 0.5942 \| 0.7709 \| \| 0.0902 \| 15.8427 \| 1410 \| 0.6140 \| 0.7647 \| 0.6140 \| 0.7836 \| \| 0.0902 \| 15.8652 \| 1412 \| 0.6513 \| 0.7836 \| 0.6513 \| 0.8070 \| \| 0.0902 \| 15.8876 \| 1414 \| 0.6937 \| 0.7791 \| 0.6937 \| 0.8329 \| \| 0.0902 \| 15.9101 \| 1416 \| 0.7189 \| 0.7791 \| 0.7189 \| 0.8479 \| \| 0.0902 \| 15.9326 \| 1418 \| 0.7041 \| 0.7619 \| 0.7041 \| 0.8391 \| \| 0.0902 \| 15.9551 \| 1420 \| 0.6912 \| 0.7619 \| 0.6912 \| 0.8314 \| \| 0.0902 \| 15.9775 \| 1422 \| 0.6785 \| 0.7654 \| 0.6785 \| 0.8237 \| \| 0.0902 \| 16.0 \| 1424 \| 0.6705 \| 0.7898 \| 0.6705 \| 0.8188 \| \| 0.0902 \| 16.0225 \| 1426 \| 0.6644 \| 0.7975 \| 0.6644 \| 0.8151 \| \| 0.0902 \| 16.0449 \| 1428 \| 0.6601 \| 0.7654 \| 0.6601 \| 0.8125 \| \| 0.0902 \| 16.0674 \| 1430 \| 0.6674 \| 0.7470 \| 0.6674 \| 0.8169 \| \| 0.0902 \| 16.0899 \| 1432 \| 0.6789 \| 0.7317 \| 0.6789 \| 0.8240 \| \| 0.0902 \| 16.1124 \| 1434 \| 0.7078 \| 0.6957 \| 0.7078 \| 0.8413 \| \| 0.0902 \| 16.1348 \| 1436 \| 0.7160 \| 0.6957 \| 0.7160 \| 0.8462 \| \| 0.0902 \| 16.1573 \| 1438 \| 0.7170 \| 0.6957 \| 0.7170 \| 0.8468 \| \| 0.0902 \| 16.1798 \| 1440 \| 0.6967 \| 0.75 \| 0.6967 \| 0.8347 \| \| 0.0902 \| 16.2022 \| 1442 \| 0.6968 \| 0.7643 \| 0.6968 \| 0.8348 \| \| 0.0902 \| 16.2247 \| 1444 \| 0.6936 \| 0.7792 \| 0.6936 \| 0.8328 \| \| 0.0902 \| 16.2472 \| 1446 \| 0.7068 \| 0.7792 \| 0.7068 \| 0.8407 \| \| 0.0902 \| 16.2697 \| 1448 \| 0.7058 \| 0.7582 \| 0.7058 \| 0.8401 \| \| 0.0902 \| 16.2921 \| 1450 \| 0.7087 \| 0.7582 \| 0.7087 \| 0.8418 \| \| 0.0902 \| 16.3146 \| 1452 \| 0.7318 \| 0.7582 \| 0.7318 \| 0.8554 \| \| 0.0902 \| 16.3371 \| 1454 \| 0.7466 \| 0.7417 \| 0.7466 \| 0.8641 \| \| 0.0902 \| 16.3596 \| 1456 \| 0.7406 \| 0.7417 \| 0.7406 \| 0.8606 \| \| 0.0902 \| 16.3820 \| 1458 \| 0.7358 \| 0.75 \| 0.7358 \| 0.8578 \| \| 0.0902 \| 16.4045 \| 1460 \| 0.7026 \| 0.7285 \| 0.7026 \| 0.8382 \| \| 0.0902 \| 16.4270 \| 1462 \| 0.6924 \| 0.7162 \| 0.6923 \| 0.8321 \| \| 0.0902 \| 16.4494 \| 1464 \| 0.7048 \| 0.7285 \| 0.7048 \| 0.8395 \| \| 0.0902 \| 16.4719 \| 1466 \| 0.7310 \| 0.7285 \| 0.7310 \| 0.8550 \| \| 0.0902 \| 16.4944 \| 1468 \| 0.7694 \| 0.75 \| 0.7694 \| 0.8772 \| \| 0.0902 \| 16.5169 \| 1470 \| 0.8124 \| 0.7067 \| 0.8124 \| 0.9013 \| \| 0.0902 \| 16.5393 \| 1472 \| 0.8399 \| 0.6839 \| 0.8399 \| 0.9165 \| \| 0.0902 \| 16.5618 \| 1474 \| 0.8193 \| 0.725 \| 0.8193 \| 0.9051 \| \| 0.0902 \| 16.5843 \| 1476 \| 0.7882 \| 0.75 \| 0.7882 \| 0.8878 \| \| 0.0902 \| 16.6067 \| 1478 \| 0.7818 \| 0.75 \| 0.7818 \| 0.8842 \| \| 0.0902 \| 16.6292 \| 1480 \| 0.7713 \| 0.75 \| 0.7713 \| 0.8782 \| \| 0.0902 \| 16.6517 \| 1482 \| 0.7593 \| 0.75 \| 0.7593 \| 0.8714 \| \| 0.0902 \| 16.6742 \| 1484 \| 0.7528 \| 0.75 \| 0.7528 \| 0.8676 \| \| 0.0902 \| 16.6966 \| 1486 \| 0.7568 \| 0.7582 \| 0.7568 \| 0.8699 \| \| 0.0902 \| 16.7191 \| 1488 \| 0.7323 \| 0.7582 \| 0.7323 \| 0.8558 \| \| 0.0902 \| 16.7416 \| 1490 \| 0.7138 \| 0.7662 \| 0.7138 \| 0.8449 \| \| 0.0902 \| 16.7640 \| 1492 \| 0.7014 \| 0.7662 \| 0.7014 \| 0.8375 \| \| 0.0902 \| 16.7865 \| 1494 \| 0.6971 \| 0.7368 \| 0.6971 \| 0.8349 \| \| 0.0902 \| 16.8090 \| 1496 \| 0.6984 \| 0.7451 \| 0.6984 \| 0.8357 \| \| 0.0902 \| 16.8315 \| 1498 \| 0.7058 \| 0.7368 \| 0.7058 \| 0.8401 \| \| 0.054 \| 16.8539 \| 1500 \| 0.7201 \| 0.7368 \| 0.7201 \| 0.8486 \| \| 0.054 \| 16.8764 \| 1502 \| 0.7380 \| 0.7285 \| 0.7380 \| 0.8591 \| \| 0.054 \| 16.8989 \| 1504 \| 0.7601 \| 0.7285 \| 0.7601 \| 0.8718 \| \| 0.054 \| 16.9213 \| 1506 \| 0.7823 \| 0.7285 \| 0.7823 \| 0.8845 \| \| 0.054 \| 16.9438 \| 1508 \| 0.8008 \| 0.7285 \| 0.8008 \| 0.8949 \| \| 0.054 \| 16.9663 \| 1510 \| 0.8235 \| 0.6980 \| 0.8235 \| 0.9075 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
shopitalic/fragance-set-roomspray-rafael	shopitalic	2025-01-15T15:33:20Z	35	0	diffusers	[ "diffusers", "flux", "text-to-image", "lora", "fal", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	2025-01-15T15:33:09Z	--- tags: - flux - text-to-image - lora - diffusers - fal base_model: black-forest-labs/FLUX.1-dev instance_prompt: license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md --- # fragance set roomspray rafael <Gallery /> ## Model description ## Trigger words You should use `` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/shopitalic/fragance-set-roomspray-rafael/tree/main) them in the Files & versions tab. ## Training at fal.ai Training was done using [fal.ai/models/fal-ai/flux-lora-fast-training](https://fal.ai/models/fal-ai/flux-lora-fast-training).
nhung03/26927434-adaa-4a69-bc76-b2ea296c9bfc	nhung03	2025-01-15T15:32:22Z	10	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/OpenHermes-2.5-Mistral-7B", "base_model:adapter:unsloth/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T15:09:24Z	--- library_name: peft license: apache-2.0 base_model: unsloth/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: 26927434-adaa-4a69-bc76-b2ea296c9bfc results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 87f5261f601511ad_train_data.json ds_type: json format: custom path: /workspace/input_data/87f5261f601511ad_train_data.json type: field_input: HS field_instruction: prefix field_output: CN format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/26927434-adaa-4a69-bc76-b2ea296c9bfc hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/87f5261f601511ad_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cefa18a5-e417-4b7f-b50e-7cfa90696def wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cefa18a5-e417-4b7f-b50e-7cfa90696def warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 26927434-adaa-4a69-bc76-b2ea296c9bfc This model is a fine-tuned version of [unsloth/OpenHermes-2.5-Mistral-7B](https://huggingface.co/unsloth/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.8336 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 12.0856 \| 0.1287 \| 200 \| 2.8336 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
ell-hol/FTR170-flux-dbth-lr	ell-hol	2025-01-15T15:32:08Z	8	0	diffusers	[ "diffusers", "text-to-image", "diffusers-training", "lora", "replicate", "flux", "flux-diffusers", "template:sd-lora", "license:other", "region:us" ]	text-to-image	2025-01-15T14:43:46Z	--- license: other library_name: diffusers tags: - text-to-image - diffusers-training - diffusers - lora - replicate - flux - flux-diffusers - template:sd-lora base_model: FLUX.1-dev instance_prompt: a photo of the FTR170 building widget: [] --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # Flux DreamBooth LoRA - ell-hol/FTR170-flux-dbth-lr <Gallery /> ## Model description These are ell-hol/FTR170-flux-dbth-lr DreamBooth LoRA weights for FLUX.1-dev. The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [Flux diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_flux.md) on [Replicate](https://replicate.com/lucataco/diffusers-dreambooth-lora). Was LoRA for the text encoder enabled? False. ## Trigger words You should use `a photo of the FTR170 building` to trigger the image generation. ## Download model [Download the *.safetensors LoRA](ell-hol/FTR170-flux-dbth-lr/tree/main) in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda') pipeline.load_lora_weights('ell-hol/FTR170-flux-dbth-lr', weight_name='pytorch_lora_weights.safetensors') image = pipeline('a photo of the FTR170 building').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) ## License Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md). ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]
AntonioTH/Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2	AntonioTH	2025-01-15T15:29:57Z	8	0	transformers	[ "transformers", "tensorboard", "safetensors", "layoutlmv2", "document-question-answering", "generated_from_trainer", "base_model:microsoft/layoutxlm-base", "base_model:finetune:microsoft/layoutxlm-base", "license:cc-by-nc-sa-4.0", "endpoints_compatible", "region:us" ]	document-question-answering	2025-01-15T14:35:02Z	--- library_name: transformers license: cc-by-nc-sa-4.0 base_model: microsoft/layoutxlm-base tags: - generated_from_trainer model-index: - name: Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2 This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: reduce_lr_on_plateau - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 3.2231 \| 0.7692 \| 10 \| 0.7135 \| \| 0.1961 \| 1.5385 \| 20 \| 0.0019 \| \| 0.002 \| 2.3077 \| 30 \| 0.0004 \| \| 0.0005 \| 3.0769 \| 40 \| 0.0002 \| \| 0.0003 \| 3.8462 \| 50 \| 0.0001 \| \| 0.0003 \| 4.6154 \| 60 \| 0.0001 \| \| 0.0002 \| 5.3846 \| 70 \| 0.0001 \| \| 0.0002 \| 6.1538 \| 80 \| 0.0001 \| \| 0.0002 \| 6.9231 \| 90 \| 0.0001 \| \| 0.0002 \| 7.6923 \| 100 \| 0.0001 \| \| 0.0002 \| 8.4615 \| 110 \| 0.0001 \| \| 0.0001 \| 9.2308 \| 120 \| 0.0001 \| \| 0.0001 \| 10.0 \| 130 \| 0.0001 \| ### Framework versions - Transformers 4.48.0 - Pytorch 2.4.1.post100 - Datasets 3.2.0 - Tokenizers 0.21.0
exala/db_aca2_7.2	exala	2025-01-15T15:28:55Z	6	0	transformers	[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T15:28:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization	MayBashendy	2025-01-15T15:28:24Z	7	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T15:10:59Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7167 - Qwk: 0.3022 - Mse: 1.7167 - Rmse: 1.3102 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0303 \| 2 \| 6.9944 \| 0.0057 \| 6.9944 \| 2.6447 \| \| No log \| 0.0606 \| 4 \| 4.5153 \| 0.0407 \| 4.5153 \| 2.1249 \| \| No log \| 0.0909 \| 6 \| 3.7162 \| -0.0635 \| 3.7162 \| 1.9278 \| \| No log \| 0.1212 \| 8 \| 3.7143 \| -0.1047 \| 3.7143 \| 1.9273 \| \| No log \| 0.1515 \| 10 \| 3.2285 \| 0.0118 \| 3.2285 \| 1.7968 \| \| No log \| 0.1818 \| 12 \| 2.4530 \| 0.0930 \| 2.4530 \| 1.5662 \| \| No log \| 0.2121 \| 14 \| 2.2921 \| 0.1538 \| 2.2921 \| 1.5140 \| \| No log \| 0.2424 \| 16 \| 2.2405 \| 0.2628 \| 2.2405 \| 1.4968 \| \| No log \| 0.2727 \| 18 \| 2.3051 \| 0.1497 \| 2.3051 \| 1.5183 \| \| No log \| 0.3030 \| 20 \| 2.3160 \| 0.1208 \| 2.3160 \| 1.5219 \| \| No log \| 0.3333 \| 22 \| 2.3371 \| 0.1208 \| 2.3371 \| 1.5288 \| \| No log \| 0.3636 \| 24 \| 2.3923 \| 0.0933 \| 2.3923 \| 1.5467 \| \| No log \| 0.3939 \| 26 \| 2.3991 \| 0.0933 \| 2.3991 \| 1.5489 \| \| No log \| 0.4242 \| 28 \| 2.4278 \| 0.1224 \| 2.4278 \| 1.5581 \| \| No log \| 0.4545 \| 30 \| 2.2243 \| 0.2464 \| 2.2243 \| 1.4914 \| \| No log \| 0.4848 \| 32 \| 1.9640 \| 0.2080 \| 1.9640 \| 1.4014 \| \| No log \| 0.5152 \| 34 \| 1.7294 \| 0.0708 \| 1.7294 \| 1.3151 \| \| No log \| 0.5455 \| 36 \| 1.6212 \| 0.1714 \| 1.6212 \| 1.2732 \| \| No log \| 0.5758 \| 38 \| 1.5596 \| 0.1887 \| 1.5596 \| 1.2488 \| \| No log \| 0.6061 \| 40 \| 1.5678 \| 0.2385 \| 1.5678 \| 1.2521 \| \| No log \| 0.6364 \| 42 \| 1.6246 \| 0.2385 \| 1.6246 \| 1.2746 \| \| No log \| 0.6667 \| 44 \| 1.7130 \| 0.2807 \| 1.7130 \| 1.3088 \| \| No log \| 0.6970 \| 46 \| 1.8307 \| 0.2185 \| 1.8307 \| 1.3530 \| \| No log \| 0.7273 \| 48 \| 1.8662 \| 0.1008 \| 1.8662 \| 1.3661 \| \| No log \| 0.7576 \| 50 \| 2.2266 \| 0.0167 \| 2.2266 \| 1.4922 \| \| No log \| 0.7879 \| 52 \| 2.3084 \| -0.0164 \| 2.3084 \| 1.5194 \| \| No log \| 0.8182 \| 54 \| 2.4142 \| -0.0813 \| 2.4142 \| 1.5538 \| \| No log \| 0.8485 \| 56 \| 1.8711 \| 0.0536 \| 1.8711 \| 1.3679 \| \| No log \| 0.8788 \| 58 \| 1.4019 \| 0.2593 \| 1.4019 \| 1.1840 \| \| No log \| 0.9091 \| 60 \| 1.3756 \| 0.3361 \| 1.3756 \| 1.1729 \| \| No log \| 0.9394 \| 62 \| 1.3331 \| 0.3248 \| 1.3331 \| 1.1546 \| \| No log \| 0.9697 \| 64 \| 1.4205 \| 0.4071 \| 1.4205 \| 1.1918 \| \| No log \| 1.0 \| 66 \| 1.7671 \| 0.2679 \| 1.7671 \| 1.3293 \| \| No log \| 1.0303 \| 68 \| 1.8373 \| 0.2364 \| 1.8373 \| 1.3555 \| \| No log \| 1.0606 \| 70 \| 1.5523 \| 0.3393 \| 1.5523 \| 1.2459 \| \| No log \| 1.0909 \| 72 \| 1.3863 \| 0.3243 \| 1.3863 \| 1.1774 \| \| No log \| 1.1212 \| 74 \| 1.3750 \| 0.3540 \| 1.3750 \| 1.1726 \| \| No log \| 1.1515 \| 76 \| 1.3629 \| 0.3860 \| 1.3629 \| 1.1674 \| \| No log \| 1.1818 \| 78 \| 1.4439 \| 0.3393 \| 1.4439 \| 1.2016 \| \| No log \| 1.2121 \| 80 \| 1.5159 \| 0.3604 \| 1.5159 \| 1.2312 \| \| No log \| 1.2424 \| 82 \| 1.7802 \| 0.2321 \| 1.7802 \| 1.3342 \| \| No log \| 1.2727 \| 84 \| 1.8063 \| 0.2456 \| 1.8063 \| 1.3440 \| \| No log \| 1.3030 \| 86 \| 1.5623 \| 0.3793 \| 1.5623 \| 1.2499 \| \| No log \| 1.3333 \| 88 \| 1.4173 \| 0.3478 \| 1.4173 \| 1.1905 \| \| No log \| 1.3636 \| 90 \| 1.2854 \| 0.3684 \| 1.2854 \| 1.1338 \| \| No log \| 1.3939 \| 92 \| 1.3589 \| 0.2936 \| 1.3589 \| 1.1657 \| \| No log \| 1.4242 \| 94 \| 1.3796 \| 0.3393 \| 1.3796 \| 1.1745 \| \| No log \| 1.4545 \| 96 \| 1.4248 \| 0.3966 \| 1.4248 \| 1.1937 \| \| No log \| 1.4848 \| 98 \| 1.4145 \| 0.4035 \| 1.4145 \| 1.1893 \| \| No log \| 1.5152 \| 100 \| 1.5414 \| 0.4068 \| 1.5414 \| 1.2415 \| \| No log \| 1.5455 \| 102 \| 1.6869 \| 0.3051 \| 1.6869 \| 1.2988 \| \| No log \| 1.5758 \| 104 \| 1.6587 \| 0.3115 \| 1.6587 \| 1.2879 \| \| No log \| 1.6061 \| 106 \| 1.7339 \| 0.2810 \| 1.7339 \| 1.3168 \| \| No log \| 1.6364 \| 108 \| 1.6304 \| 0.3415 \| 1.6304 \| 1.2769 \| \| No log \| 1.6667 \| 110 \| 1.7599 \| 0.2835 \| 1.7599 \| 1.3266 \| \| No log \| 1.6970 \| 112 \| 1.8480 \| 0.2258 \| 1.8480 \| 1.3594 \| \| No log \| 1.7273 \| 114 \| 1.5999 \| 0.3333 \| 1.5999 \| 1.2649 \| \| No log \| 1.7576 \| 116 \| 1.4627 \| 0.5079 \| 1.4627 \| 1.2094 \| \| No log \| 1.7879 \| 118 \| 1.4149 \| 0.4 \| 1.4149 \| 1.1895 \| \| No log \| 1.8182 \| 120 \| 1.5311 \| 0.5077 \| 1.5311 \| 1.2374 \| \| No log \| 1.8485 \| 122 \| 1.8821 \| 0.2609 \| 1.8821 \| 1.3719 \| \| No log \| 1.8788 \| 124 \| 1.9892 \| 0.1630 \| 1.9892 \| 1.4104 \| \| No log \| 1.9091 \| 126 \| 1.8187 \| 0.3088 \| 1.8187 \| 1.3486 \| \| No log \| 1.9394 \| 128 \| 1.4761 \| 0.4715 \| 1.4761 \| 1.2149 \| \| No log \| 1.9697 \| 130 \| 1.3188 \| 0.4068 \| 1.3188 \| 1.1484 \| \| No log \| 2.0 \| 132 \| 1.3135 \| 0.5082 \| 1.3135 \| 1.1461 \| \| No log \| 2.0303 \| 134 \| 1.4589 \| 0.4733 \| 1.4589 \| 1.2079 \| \| No log \| 2.0606 \| 136 \| 1.6805 \| 0.3284 \| 1.6805 \| 1.2963 \| \| No log \| 2.0909 \| 138 \| 2.0007 \| 0.0916 \| 2.0007 \| 1.4144 \| \| No log \| 2.1212 \| 140 \| 1.9180 \| 0.1493 \| 1.9180 \| 1.3849 \| \| No log \| 2.1515 \| 142 \| 1.5706 \| 0.3556 \| 1.5706 \| 1.2532 \| \| No log \| 2.1818 \| 144 \| 1.2024 \| 0.5873 \| 1.2024 \| 1.0965 \| \| No log \| 2.2121 \| 146 \| 1.0618 \| 0.4370 \| 1.0618 \| 1.0305 \| \| No log \| 2.2424 \| 148 \| 1.0357 \| 0.5484 \| 1.0357 \| 1.0177 \| \| No log \| 2.2727 \| 150 \| 1.1690 \| 0.5512 \| 1.1690 \| 1.0812 \| \| No log \| 2.3030 \| 152 \| 1.3789 \| 0.4496 \| 1.3789 \| 1.1743 \| \| No log \| 2.3333 \| 154 \| 1.2727 \| 0.5197 \| 1.2727 \| 1.1282 \| \| No log \| 2.3636 \| 156 \| 1.1478 \| 0.5528 \| 1.1478 \| 1.0713 \| \| No log \| 2.3939 \| 158 \| 1.1685 \| 0.5323 \| 1.1685 \| 1.0810 \| \| No log \| 2.4242 \| 160 \| 1.2396 \| 0.5161 \| 1.2396 \| 1.1134 \| \| No log \| 2.4545 \| 162 \| 1.3491 \| 0.5039 \| 1.3491 \| 1.1615 \| \| No log \| 2.4848 \| 164 \| 1.3579 \| 0.5156 \| 1.3579 \| 1.1653 \| \| No log \| 2.5152 \| 166 \| 1.4688 \| 0.3721 \| 1.4688 \| 1.2119 \| \| No log \| 2.5455 \| 168 \| 1.4561 \| 0.4127 \| 1.4561 \| 1.2067 \| \| No log \| 2.5758 \| 170 \| 1.4176 \| 0.5 \| 1.4176 \| 1.1906 \| \| No log \| 2.6061 \| 172 \| 1.4266 \| 0.4754 \| 1.4266 \| 1.1944 \| \| No log \| 2.6364 \| 174 \| 1.6812 \| 0.2835 \| 1.6812 \| 1.2966 \| \| No log \| 2.6667 \| 176 \| 1.9125 \| 0.2114 \| 1.9125 \| 1.3829 \| \| No log \| 2.6970 \| 178 \| 2.0021 \| 0.1667 \| 2.0021 \| 1.4150 \| \| No log \| 2.7273 \| 180 \| 1.8599 \| 0.2131 \| 1.8599 \| 1.3638 \| \| No log \| 2.7576 \| 182 \| 1.5087 \| 0.4496 \| 1.5087 \| 1.2283 \| \| No log \| 2.7879 \| 184 \| 1.3008 \| 0.5385 \| 1.3008 \| 1.1405 \| \| No log \| 2.8182 \| 186 \| 1.2706 \| 0.5271 \| 1.2706 \| 1.1272 \| \| No log \| 2.8485 \| 188 \| 1.3617 \| 0.5116 \| 1.3617 \| 1.1669 \| \| No log \| 2.8788 \| 190 \| 1.3683 \| 0.4844 \| 1.3683 \| 1.1697 \| \| No log \| 2.9091 \| 192 \| 1.4496 \| 0.4361 \| 1.4496 \| 1.2040 \| \| No log \| 2.9394 \| 194 \| 1.4260 \| 0.4462 \| 1.4260 \| 1.1942 \| \| No log \| 2.9697 \| 196 \| 1.3760 \| 0.5197 \| 1.3760 \| 1.1730 \| \| No log \| 3.0 \| 198 \| 1.3927 \| 0.5156 \| 1.3927 \| 1.1801 \| \| No log \| 3.0303 \| 200 \| 1.4339 \| 0.4844 \| 1.4339 \| 1.1974 \| \| No log \| 3.0606 \| 202 \| 1.4469 \| 0.4961 \| 1.4469 \| 1.2029 \| \| No log \| 3.0909 \| 204 \| 1.4224 \| 0.5344 \| 1.4224 \| 1.1926 \| \| No log \| 3.1212 \| 206 \| 1.4897 \| 0.4179 \| 1.4897 \| 1.2205 \| \| No log \| 3.1515 \| 208 \| 1.5812 \| 0.3485 \| 1.5812 \| 1.2575 \| \| No log \| 3.1818 \| 210 \| 1.6296 \| 0.3256 \| 1.6296 \| 1.2766 \| \| No log \| 3.2121 \| 212 \| 1.4779 \| 0.4252 \| 1.4779 \| 1.2157 \| \| No log \| 3.2424 \| 214 \| 1.3430 \| 0.496 \| 1.3430 \| 1.1589 \| \| No log \| 3.2727 \| 216 \| 1.2147 \| 0.528 \| 1.2147 \| 1.1021 \| \| No log \| 3.3030 \| 218 \| 1.3675 \| 0.4844 \| 1.3675 \| 1.1694 \| \| No log \| 3.3333 \| 220 \| 1.5121 \| 0.4 \| 1.5121 \| 1.2297 \| \| No log \| 3.3636 \| 222 \| 1.3824 \| 0.4878 \| 1.3824 \| 1.1757 \| \| No log \| 3.3939 \| 224 \| 1.1374 \| 0.4957 \| 1.1374 \| 1.0665 \| \| No log \| 3.4242 \| 226 \| 1.1127 \| 0.4696 \| 1.1127 \| 1.0548 \| \| No log \| 3.4545 \| 228 \| 1.1710 \| 0.4522 \| 1.1710 \| 1.0821 \| \| No log \| 3.4848 \| 230 \| 1.3114 \| 0.4522 \| 1.3114 \| 1.1452 \| \| No log \| 3.5152 \| 232 \| 1.3567 \| 0.4667 \| 1.3567 \| 1.1648 \| \| No log \| 3.5455 \| 234 \| 1.3247 \| 0.4921 \| 1.3247 \| 1.1510 \| \| No log \| 3.5758 \| 236 \| 1.2507 \| 0.5312 \| 1.2507 \| 1.1183 \| \| No log \| 3.6061 \| 238 \| 1.1976 \| 0.5714 \| 1.1976 \| 1.0944 \| \| No log \| 3.6364 \| 240 \| 1.1839 \| 0.5736 \| 1.1839 \| 1.0881 \| \| No log \| 3.6667 \| 242 \| 1.3254 \| 0.5255 \| 1.3254 \| 1.1513 \| \| No log \| 3.6970 \| 244 \| 1.3419 \| 0.4889 \| 1.3419 \| 1.1584 \| \| No log \| 3.7273 \| 246 \| 1.4214 \| 0.4148 \| 1.4214 \| 1.1922 \| \| No log \| 3.7576 \| 248 \| 1.5377 \| 0.3704 \| 1.5377 \| 1.2400 \| \| No log \| 3.7879 \| 250 \| 1.5166 \| 0.3359 \| 1.5166 \| 1.2315 \| \| No log \| 3.8182 \| 252 \| 1.5304 \| 0.368 \| 1.5304 \| 1.2371 \| \| No log \| 3.8485 \| 254 \| 1.5101 \| 0.4034 \| 1.5101 \| 1.2289 \| \| No log \| 3.8788 \| 256 \| 1.4454 \| 0.4202 \| 1.4454 \| 1.2022 \| \| No log \| 3.9091 \| 258 \| 1.5006 \| 0.4034 \| 1.5006 \| 1.2250 \| \| No log \| 3.9394 \| 260 \| 1.6493 \| 0.2581 \| 1.6493 \| 1.2843 \| \| No log \| 3.9697 \| 262 \| 1.8253 \| 0.1760 \| 1.8253 \| 1.3510 \| \| No log \| 4.0 \| 264 \| 1.8408 \| 0.2047 \| 1.8408 \| 1.3568 \| \| No log \| 4.0303 \| 266 \| 1.7825 \| 0.2308 \| 1.7825 \| 1.3351 \| \| No log \| 4.0606 \| 268 \| 1.6237 \| 0.3008 \| 1.6237 \| 1.2742 \| \| No log \| 4.0909 \| 270 \| 1.5478 \| 0.4211 \| 1.5478 \| 1.2441 \| \| No log \| 4.1212 \| 272 \| 1.4616 \| 0.4242 \| 1.4616 \| 1.2089 \| \| No log \| 4.1515 \| 274 \| 1.4935 \| 0.4361 \| 1.4935 \| 1.2221 \| \| No log \| 4.1818 \| 276 \| 1.6308 \| 0.3664 \| 1.6308 \| 1.2770 \| \| No log \| 4.2121 \| 278 \| 1.7634 \| 0.2462 \| 1.7634 \| 1.3279 \| \| No log \| 4.2424 \| 280 \| 1.8587 \| 0.2406 \| 1.8587 \| 1.3633 \| \| No log \| 4.2727 \| 282 \| 1.8221 \| 0.2836 \| 1.8221 \| 1.3499 \| \| No log \| 4.3030 \| 284 \| 1.5922 \| 0.3158 \| 1.5922 \| 1.2618 \| \| No log \| 4.3333 \| 286 \| 1.3365 \| 0.5039 \| 1.3365 \| 1.1561 \| \| No log \| 4.3636 \| 288 \| 1.3022 \| 0.5039 \| 1.3022 \| 1.1411 \| \| No log \| 4.3939 \| 290 \| 1.4342 \| 0.4444 \| 1.4342 \| 1.1976 \| \| No log \| 4.4242 \| 292 \| 1.6800 \| 0.3212 \| 1.6800 \| 1.2961 \| \| No log \| 4.4545 \| 294 \| 1.8339 \| 0.2482 \| 1.8339 \| 1.3542 \| \| No log \| 4.4848 \| 296 \| 2.0354 \| 0.1176 \| 2.0354 \| 1.4267 \| \| No log \| 4.5152 \| 298 \| 2.0186 \| 0.0746 \| 2.0186 \| 1.4208 \| \| No log \| 4.5455 \| 300 \| 1.7992 \| 0.2556 \| 1.7992 \| 1.3413 \| \| No log \| 4.5758 \| 302 \| 1.5955 \| 0.3411 \| 1.5955 \| 1.2631 \| \| No log \| 4.6061 \| 304 \| 1.4671 \| 0.3810 \| 1.4671 \| 1.2113 \| \| No log \| 4.6364 \| 306 \| 1.3656 \| 0.5041 \| 1.3656 \| 1.1686 \| \| No log \| 4.6667 \| 308 \| 1.3630 \| 0.5397 \| 1.3630 \| 1.1675 \| \| No log \| 4.6970 \| 310 \| 1.4873 \| 0.4296 \| 1.4873 \| 1.2196 \| \| No log \| 4.7273 \| 312 \| 1.7610 \| 0.2446 \| 1.7610 \| 1.3270 \| \| No log \| 4.7576 \| 314 \| 2.0182 \| 0.1460 \| 2.0182 \| 1.4207 \| \| No log \| 4.7879 \| 316 \| 2.1348 \| 0.1714 \| 2.1348 \| 1.4611 \| \| No log \| 4.8182 \| 318 \| 2.1244 \| 0.1831 \| 2.1244 \| 1.4575 \| \| No log \| 4.8485 \| 320 \| 1.9065 \| 0.2857 \| 1.9065 \| 1.3808 \| \| No log \| 4.8788 \| 322 \| 1.5997 \| 0.3597 \| 1.5997 \| 1.2648 \| \| No log \| 4.9091 \| 324 \| 1.4691 \| 0.4925 \| 1.4691 \| 1.2121 \| \| No log \| 4.9394 \| 326 \| 1.5112 \| 0.4328 \| 1.5112 \| 1.2293 \| \| No log \| 4.9697 \| 328 \| 1.6980 \| 0.3333 \| 1.6980 \| 1.3031 \| \| No log \| 5.0 \| 330 \| 1.9604 \| 0.2286 \| 1.9604 \| 1.4001 \| \| No log \| 5.0303 \| 332 \| 1.9863 \| 0.1986 \| 1.9863 \| 1.4094 \| \| No log \| 5.0606 \| 334 \| 1.9663 \| 0.1986 \| 1.9663 \| 1.4022 \| \| No log \| 5.0909 \| 336 \| 1.9781 \| 0.1986 \| 1.9781 \| 1.4064 \| \| No log \| 5.1212 \| 338 \| 2.0225 \| 0.2000 \| 2.0225 \| 1.4221 \| \| No log \| 5.1515 \| 340 \| 2.0287 \| 0.2000 \| 2.0287 \| 1.4243 \| \| No log \| 5.1818 \| 342 \| 2.0276 \| 0.2000 \| 2.0276 \| 1.4239 \| \| No log \| 5.2121 \| 344 \| 1.9562 \| 0.1844 \| 1.9562 \| 1.3986 \| \| No log \| 5.2424 \| 346 \| 1.7553 \| 0.3333 \| 1.7553 \| 1.3249 \| \| No log \| 5.2727 \| 348 \| 1.6211 \| 0.4058 \| 1.6211 \| 1.2732 \| \| No log \| 5.3030 \| 350 \| 1.6287 \| 0.3796 \| 1.6287 \| 1.2762 \| \| No log \| 5.3333 \| 352 \| 1.5323 \| 0.3676 \| 1.5323 \| 1.2378 \| \| No log \| 5.3636 \| 354 \| 1.4494 \| 0.4328 \| 1.4494 \| 1.2039 \| \| No log \| 5.3939 \| 356 \| 1.4895 \| 0.4148 \| 1.4895 \| 1.2204 \| \| No log \| 5.4242 \| 358 \| 1.7277 \| 0.3143 \| 1.7277 \| 1.3144 \| \| No log \| 5.4545 \| 360 \| 2.0436 \| 0.2098 \| 2.0436 \| 1.4295 \| \| No log \| 5.4848 \| 362 \| 2.0502 \| 0.2222 \| 2.0502 \| 1.4319 \| \| No log \| 5.5152 \| 364 \| 1.9849 \| 0.2778 \| 1.9849 \| 1.4089 \| \| No log \| 5.5455 \| 366 \| 1.7435 \| 0.3497 \| 1.7435 \| 1.3204 \| \| No log \| 5.5758 \| 368 \| 1.5414 \| 0.3597 \| 1.5414 \| 1.2415 \| \| No log \| 5.6061 \| 370 \| 1.4444 \| 0.4328 \| 1.4444 \| 1.2018 \| \| No log \| 5.6364 \| 372 \| 1.5102 \| 0.4203 \| 1.5102 \| 1.2289 \| \| No log \| 5.6667 \| 374 \| 1.7301 \| 0.2878 \| 1.7301 \| 1.3153 \| \| No log \| 5.6970 \| 376 \| 1.8386 \| 0.2754 \| 1.8386 \| 1.3559 \| \| No log \| 5.7273 \| 378 \| 1.7688 \| 0.2590 \| 1.7688 \| 1.3299 \| \| No log \| 5.7576 \| 380 \| 1.6764 \| 0.3333 \| 1.6764 \| 1.2948 \| \| No log \| 5.7879 \| 382 \| 1.6558 \| 0.3212 \| 1.6558 \| 1.2868 \| \| No log \| 5.8182 \| 384 \| 1.6592 \| 0.3212 \| 1.6592 \| 1.2881 \| \| No log \| 5.8485 \| 386 \| 1.8444 \| 0.3022 \| 1.8444 \| 1.3581 \| \| No log \| 5.8788 \| 388 \| 2.0224 \| 0.2695 \| 2.0224 \| 1.4221 \| \| No log \| 5.9091 \| 390 \| 1.9895 \| 0.2695 \| 1.9895 \| 1.4105 \| \| No log \| 5.9394 \| 392 \| 1.7949 \| 0.3022 \| 1.7949 \| 1.3397 \| \| No log \| 5.9697 \| 394 \| 1.5034 \| 0.4029 \| 1.5034 \| 1.2261 \| \| No log \| 6.0 \| 396 \| 1.3198 \| 0.4672 \| 1.3198 \| 1.1488 \| \| No log \| 6.0303 \| 398 \| 1.2589 \| 0.4925 \| 1.2589 \| 1.1220 \| \| No log \| 6.0606 \| 400 \| 1.2109 \| 0.5231 \| 1.2109 \| 1.1004 \| \| No log \| 6.0909 \| 402 \| 1.2751 \| 0.4848 \| 1.2751 \| 1.1292 \| \| No log \| 6.1212 \| 404 \| 1.4672 \| 0.4088 \| 1.4672 \| 1.2113 \| \| No log \| 6.1515 \| 406 \| 1.7512 \| 0.3066 \| 1.7512 \| 1.3233 \| \| No log \| 6.1818 \| 408 \| 1.8199 \| 0.2899 \| 1.8199 \| 1.3490 \| \| No log \| 6.2121 \| 410 \| 1.8737 \| 0.2286 \| 1.8737 \| 1.3688 \| \| No log \| 6.2424 \| 412 \| 1.7951 \| 0.3022 \| 1.7951 \| 1.3398 \| \| No log \| 6.2727 \| 414 \| 1.6056 \| 0.3913 \| 1.6056 \| 1.2671 \| \| No log \| 6.3030 \| 416 \| 1.5029 \| 0.4234 \| 1.5029 \| 1.2259 \| \| No log \| 6.3333 \| 418 \| 1.4873 \| 0.4526 \| 1.4873 \| 1.2196 \| \| No log \| 6.3636 \| 420 \| 1.5242 \| 0.4444 \| 1.5242 \| 1.2346 \| \| No log \| 6.3939 \| 422 \| 1.5626 \| 0.4627 \| 1.5626 \| 1.2501 \| \| No log \| 6.4242 \| 424 \| 1.5605 \| 0.4122 \| 1.5605 \| 1.2492 \| \| No log \| 6.4545 \| 426 \| 1.5478 \| 0.4122 \| 1.5478 \| 1.2441 \| \| No log \| 6.4848 \| 428 \| 1.5280 \| 0.4122 \| 1.5280 \| 1.2361 \| \| No log \| 6.5152 \| 430 \| 1.5320 \| 0.4122 \| 1.5320 \| 1.2378 \| \| No log \| 6.5455 \| 432 \| 1.5495 \| 0.4122 \| 1.5495 \| 1.2448 \| \| No log \| 6.5758 \| 434 \| 1.6572 \| 0.3788 \| 1.6571 \| 1.2873 \| \| No log \| 6.6061 \| 436 \| 1.7076 \| 0.3382 \| 1.7076 \| 1.3068 \| \| No log \| 6.6364 \| 438 \| 1.6395 \| 0.4148 \| 1.6395 \| 1.2804 \| \| No log \| 6.6667 \| 440 \| 1.5910 \| 0.4148 \| 1.5910 \| 1.2614 \| \| No log \| 6.6970 \| 442 \| 1.5514 \| 0.4148 \| 1.5514 \| 1.2456 \| \| No log \| 6.7273 \| 444 \| 1.5695 \| 0.3971 \| 1.5695 \| 1.2528 \| \| No log \| 6.7576 \| 446 \| 1.6529 \| 0.3478 \| 1.6529 \| 1.2856 \| \| No log \| 6.7879 \| 448 \| 1.6667 \| 0.3478 \| 1.6667 \| 1.2910 \| \| No log \| 6.8182 \| 450 \| 1.5943 \| 0.3529 \| 1.5943 \| 1.2626 \| \| No log \| 6.8485 \| 452 \| 1.6232 \| 0.3358 \| 1.6232 \| 1.2741 \| \| No log \| 6.8788 \| 454 \| 1.7026 \| 0.3143 \| 1.7026 \| 1.3048 \| \| No log \| 6.9091 \| 456 \| 1.8190 \| 0.2553 \| 1.8190 \| 1.3487 \| \| No log \| 6.9394 \| 458 \| 1.8363 \| 0.2553 \| 1.8363 \| 1.3551 \| \| No log \| 6.9697 \| 460 \| 1.6069 \| 0.3478 \| 1.6069 \| 1.2676 \| \| No log \| 7.0 \| 462 \| 1.3671 \| 0.4662 \| 1.3671 \| 1.1692 \| \| No log \| 7.0303 \| 464 \| 1.2786 \| 0.5736 \| 1.2786 \| 1.1308 \| \| No log \| 7.0606 \| 466 \| 1.3161 \| 0.5469 \| 1.3161 \| 1.1472 \| \| No log \| 7.0909 \| 468 \| 1.4248 \| 0.4427 \| 1.4248 \| 1.1937 \| \| No log \| 7.1212 \| 470 \| 1.6490 \| 0.3212 \| 1.6490 \| 1.2841 \| \| No log \| 7.1515 \| 472 \| 1.8276 \| 0.2553 \| 1.8276 \| 1.3519 \| \| No log \| 7.1818 \| 474 \| 1.8325 \| 0.2014 \| 1.8325 \| 1.3537 \| \| No log \| 7.2121 \| 476 \| 1.7131 \| 0.2687 \| 1.7131 \| 1.3089 \| \| No log \| 7.2424 \| 478 \| 1.6029 \| 0.3840 \| 1.6029 \| 1.2660 \| \| No log \| 7.2727 \| 480 \| 1.6119 \| 0.35 \| 1.6119 \| 1.2696 \| \| No log \| 7.3030 \| 482 \| 1.6414 \| 0.3802 \| 1.6414 \| 1.2812 \| \| No log \| 7.3333 \| 484 \| 1.7304 \| 0.3226 \| 1.7304 \| 1.3154 \| \| No log \| 7.3636 \| 486 \| 1.7827 \| 0.2370 \| 1.7827 \| 1.3352 \| \| No log \| 7.3939 \| 488 \| 1.6803 \| 0.3556 \| 1.6803 \| 1.2963 \| \| No log \| 7.4242 \| 490 \| 1.5603 \| 0.3609 \| 1.5603 \| 1.2491 \| \| No log \| 7.4545 \| 492 \| 1.4283 \| 0.4531 \| 1.4283 \| 1.1951 \| \| No log \| 7.4848 \| 494 \| 1.3342 \| 0.4160 \| 1.3342 \| 1.1551 \| \| No log \| 7.5152 \| 496 \| 1.3632 \| 0.4409 \| 1.3632 \| 1.1675 \| \| No log \| 7.5455 \| 498 \| 1.5263 \| 0.4091 \| 1.5263 \| 1.2354 \| \| 0.4132 \| 7.5758 \| 500 \| 1.7767 \| 0.3066 \| 1.7767 \| 1.3329 \| \| 0.4132 \| 7.6061 \| 502 \| 1.8679 \| 0.2899 \| 1.8679 \| 1.3667 \| \| 0.4132 \| 7.6364 \| 504 \| 1.7845 \| 0.2899 \| 1.7845 \| 1.3359 \| \| 0.4132 \| 7.6667 \| 506 \| 1.6449 \| 0.3759 \| 1.6449 \| 1.2825 \| \| 0.4132 \| 7.6970 \| 508 \| 1.5565 \| 0.4091 \| 1.5565 \| 1.2476 \| \| 0.4132 \| 7.7273 \| 510 \| 1.4505 \| 0.4462 \| 1.4505 \| 1.2044 \| \| 0.4132 \| 7.7576 \| 512 \| 1.4850 \| 0.4462 \| 1.4850 \| 1.2186 \| \| 0.4132 \| 7.7879 \| 514 \| 1.6438 \| 0.3529 \| 1.6438 \| 1.2821 \| \| 0.4132 \| 7.8182 \| 516 \| 1.8453 \| 0.2734 \| 1.8453 \| 1.3584 \| \| 0.4132 \| 7.8485 \| 518 \| 1.9250 \| 0.2128 \| 1.9250 \| 1.3874 \| \| 0.4132 \| 7.8788 \| 520 \| 1.9368 \| 0.2254 \| 1.9368 \| 1.3917 \| \| 0.4132 \| 7.9091 \| 522 \| 1.8844 \| 0.2571 \| 1.8844 \| 1.3727 \| \| 0.4132 \| 7.9394 \| 524 \| 1.7167 \| 0.3022 \| 1.7167 \| 1.3102 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
pvduy/Qwen2.7-7B-Instruct-QwQ	pvduy	2025-01-15T15:27:50Z	1,626	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-15T15:22:24Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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lesso07/5f8a3450-51fd-403d-9d1a-57a04bedf50c	lesso07	2025-01-15T15:22:59Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2-0.5B", "base_model:adapter:Qwen/Qwen2-0.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T10:31:19Z	--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2-0.5B tags: - axolotl - generated_from_trainer model-index: - name: 5f8a3450-51fd-403d-9d1a-57a04bedf50c results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2-0.5B bf16: true chat_template: llama3 datasets: - data_files: - a54dfbc141335bb5_train_data.json ds_type: json format: custom path: /workspace/input_data/a54dfbc141335bb5_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso07/5f8a3450-51fd-403d-9d1a-57a04bedf50c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/a54dfbc141335bb5_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e302ed25-6563-4139-a251-885ddd901a8d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e302ed25-6563-4139-a251-885ddd901a8d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 5f8a3450-51fd-403d-9d1a-57a04bedf50c This model is a fine-tuned version of [Qwen/Qwen2-0.5B](https://huggingface.co/Qwen/Qwen2-0.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.4338 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 1.7504 \| 0.0000 \| 1 \| 2.8080 \| \| 2.5122 \| 0.0001 \| 5 \| 2.7556 \| \| 2.3674 \| 0.0002 \| 10 \| 2.5045 \| \| 2.6639 \| 0.0002 \| 15 \| 2.4447 \| \| 1.8371 \| 0.0003 \| 20 \| 2.4358 \| \| 2.2204 \| 0.0004 \| 25 \| 2.4338 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
chauhoang/5d7d72f6-1494-4bc7-888a-74bf6c08aad0	chauhoang	2025-01-15T15:21:55Z	11	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "region:us" ]	null	2025-01-15T15:16:00Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 5d7d72f6-1494-4bc7-888a-74bf6c08aad0 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 5 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: chauhoang/5d7d72f6-1494-4bc7-888a-74bf6c08aad0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 5 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 5d7d72f6-1494-4bc7-888a-74bf6c08aad0 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0008 \| 1 \| nan \| \| 0.0 \| 0.0082 \| 10 \| nan \| \| 0.0 \| 0.0163 \| 20 \| nan \| \| 0.0 \| 0.0245 \| 30 \| nan \| \| 0.0 \| 0.0327 \| 40 \| nan \| \| 0.0 \| 0.0408 \| 50 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thakkkkkk/ac914070-92e4-4882-aab1-2dae1cc8f023	thakkkkkk	2025-01-15T15:17:26Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:elyza/Llama-3-ELYZA-JP-8B", "base_model:adapter:elyza/Llama-3-ELYZA-JP-8B", "license:llama3", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:23:23Z	--- library_name: peft license: llama3 base_model: elyza/Llama-3-ELYZA-JP-8B tags: - axolotl - generated_from_trainer model-index: - name: ac914070-92e4-4882-aab1-2dae1cc8f023 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: elyza/Llama-3-ELYZA-JP-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fda69805a6ba006d_train_data.json ds_type: json format: custom path: /workspace/input_data/fda69805a6ba006d_train_data.json type: field_instruction: prompt field_output: solution format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thakkkkkk/ac914070-92e4-4882-aab1-2dae1cc8f023 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 4 mlflow_experiment_name: /tmp/fda69805a6ba006d_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <\|eot_id\|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f2e1c4d6-26a9-4626-844d-fb1f5d0379e3 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f2e1c4d6-26a9-4626-844d-fb1f5d0379e3 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # ac914070-92e4-4882-aab1-2dae1cc8f023 This model is a fine-tuned version of [elyza/Llama-3-ELYZA-JP-8B](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7168 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.7364 \| 0.0187 \| 200 \| 0.7168 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
hollmann/andre-dev	hollmann	2025-01-15T15:15:11Z	12	0	diffusers	[ "diffusers", "flux", "text-to-image", "lora", "fal", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	2025-01-15T15:15:04Z	--- tags: - flux - text-to-image - lora - diffusers - fal base_model: black-forest-labs/FLUX.1-dev instance_prompt: foo license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md --- # andre dev <Gallery /> ## Model description ## Trigger words You should use `foo` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/hollmann/andre-dev/tree/main) them in the Files & versions tab. ## Training at fal.ai Training was done using [fal.ai/models/fal-ai/flux-lora-fast-training](https://fal.ai/models/fal-ai/flux-lora-fast-training).
tarabukinivan/b421da53-ff70-4e6d-b92e-a790e19e8999	tarabukinivan	2025-01-15T15:13:31Z	6	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]	null	2025-01-15T14:14:08Z	--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: b421da53-ff70-4e6d-b92e-a790e19e8999 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: tarabukinivan/b421da53-ff70-4e6d-b92e-a790e19e8999 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # b421da53-ff70-4e6d-b92e-a790e19e8999 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0006 \| 13 \| nan \| \| 0.0 \| 0.0012 \| 26 \| nan \| \| 0.0 \| 0.0018 \| 39 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
lesso05/cb24c657-616f-497d-82aa-f52913f3c89f	lesso05	2025-01-15T15:13:11Z	9	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0", "base_model:adapter:WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0", "license:llama3", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T13:24:13Z	--- library_name: peft license: llama3 base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 tags: - axolotl - generated_from_trainer model-index: - name: cb24c657-616f-497d-82aa-f52913f3c89f results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 bf16: true chat_template: llama3 datasets: - data_files: - 3c33873967a336a3_train_data.json ds_type: json format: custom path: /workspace/input_data/3c33873967a336a3_train_data.json type: field_input: context field_instruction: question field_output: answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso05/cb24c657-616f-497d-82aa-f52913f3c89f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/3c33873967a336a3_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fd5b49f1-57e4-4c15-bca0-7eed58aadb30 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fd5b49f1-57e4-4c15-bca0-7eed58aadb30 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # cb24c657-616f-497d-82aa-f52913f3c89f This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4272 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 3.0196 \| 0.0001 \| 1 \| 3.4767 \| \| 2.5522 \| 0.0003 \| 5 \| 2.9957 \| \| 1.1031 \| 0.0006 \| 10 \| 1.1841 \| \| 0.323 \| 0.0009 \| 15 \| 0.3350 \| \| 0.3152 \| 0.0012 \| 20 \| 0.4184 \| \| 0.359 \| 0.0015 \| 25 \| 0.4272 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
fedovtt/b8cd5a6b-26c8-44b2-bfd1-a975c77263d2	fedovtt	2025-01-15T15:10:48Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]	null	2025-01-15T14:12:47Z	--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: fedovtt/b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0005 \| 10 \| nan \| \| 0.0 \| 0.0007 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
Nekuromento/watt-tool-8B-Q6_K-GGUF	Nekuromento	2025-01-15T15:10:37Z	23	0	null	[ "gguf", "function-calling", "tool-use", "llama", "bfcl", "llama-cpp", "gguf-my-repo", "en", "base_model:watt-ai/watt-tool-8B", "base_model:quantized:watt-ai/watt-tool-8B", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	null	2025-01-15T15:10:06Z	--- license: apache-2.0 language: - en base_model: watt-ai/watt-tool-8B tags: - function-calling - tool-use - llama - bfcl - llama-cpp - gguf-my-repo --- # Nekuromento/watt-tool-8B-Q6_K-GGUF This model was converted to GGUF format from [`watt-ai/watt-tool-8B`](https://huggingface.co/watt-ai/watt-tool-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/watt-ai/watt-tool-8B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -c 2048 ```
Keltezaa/Shione_Cooper_Actress	Keltezaa	2025-01-15T15:10:32Z	71	0	diffusers	[ "diffusers", "text-to-image", "lora", "template:diffusion-lora", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:cc-by-nc-sa-4.0", "region:us" ]	text-to-image	2025-01-15T14:32:12Z	--- tags: - text-to-image - lora - diffusers - template:diffusion-lora widget: - text: >- A glamour Breathtaking medium shot photography of a young woman with a friendly and calm expression, dressed in a turtleneck. Her style reflects effortless sophistication, blending laid-back comfort with subtle refinement. She is smiling warmly, radiating confidence and approachability. The background is solid and softly lit, enhancing the natural tones and textures of the image. The lighting is diffused and flattering, emphasizing her features while creating a professional and polished aesthetic, she is a natural redhead with pale skin and freckles, standing naked in a lush forest output: url: images/example_ndl7kpc55.png - text: >- A glamour Breathtaking medium shot photography of a young woman with a friendly and calm expression, dressed in a turtleneck. Her style reflects effortless sophistication, blending laid-back comfort with subtle refinement. She is smiling warmly, radiating confidence and approachability. The background is solid and softly lit, enhancing the natural tones and textures of the image. The lighting is diffused and flattering, emphasizing her features while creating a professional and polished aesthetic, output: url: images/example_rdnlqg3w5.png base_model: black-forest-labs/FLUX.1-dev instance_prompt: null license: cc-by-nc-sa-4.0 --- # Shione_Cooper_ Actress <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Keltezaa/Shione_Cooper_Actress/tree/main) them in the Files & versions tab.
ClarenceDan/93993d99-8ea8-47e0-849f-d360c7481cb7	ClarenceDan	2025-01-15T15:09:54Z	32	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:lmsys/vicuna-13b-v1.5", "base_model:adapter:lmsys/vicuna-13b-v1.5", "license:llama2", "region:us" ]	null	2025-01-15T14:21:24Z	--- library_name: peft license: llama2 base_model: lmsys/vicuna-13b-v1.5 tags: - axolotl - generated_from_trainer model-index: - name: 93993d99-8ea8-47e0-849f-d360c7481cb7 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: lmsys/vicuna-13b-v1.5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4a8c0890df315567_train_data.json ds_type: json format: custom path: /workspace/input_data/4a8c0890df315567_train_data.json type: field_instruction: original_text field_output: correct_text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/93993d99-8ea8-47e0-849f-d360c7481cb7 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/4a8c0890df315567_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a6ac3cc6-bcf7-42ba-814a-539ed29d5e1d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a6ac3cc6-bcf7-42ba-814a-539ed29d5e1d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 93993d99-8ea8-47e0-849f-d360c7481cb7 This model is a fine-tuned version of [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2676 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.4302 \| 0.0000 \| 1 \| 0.4490 \| \| 0.448 \| 0.0001 \| 3 \| 0.4463 \| \| 0.4044 \| 0.0002 \| 6 \| 0.4110 \| \| 0.2998 \| 0.0003 \| 9 \| 0.2676 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
thaffggg/47549b63-3cef-4fdc-babf-e37cc823fc95	thaffggg	2025-01-15T15:03:52Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:50:54Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 47549b63-3cef-4fdc-babf-e37cc823fc95 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/47549b63-3cef-4fdc-babf-e37cc823fc95 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 47549b63-3cef-4fdc-babf-e37cc823fc95 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2828 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.3918 \| 0.1633 \| 200 \| 0.2828 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
nhung01/99cbf546-cfba-4383-aa91-9122d9181457	nhung01	2025-01-15T15:03:48Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:51:04Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 99cbf546-cfba-4383-aa91-9122d9181457 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/99cbf546-cfba-4383-aa91-9122d9181457 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 99cbf546-cfba-4383-aa91-9122d9181457 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2814 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.3922 \| 0.1633 \| 200 \| 0.2814 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
cunghoctienganh/a798d10d-dee8-4bf8-a46e-6c45dbb791b5	cunghoctienganh	2025-01-15T15:03:18Z	8	0	peft	[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]	null	2025-01-15T14:50:50Z	--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: a798d10d-dee8-4bf8-a46e-6c45dbb791b5 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: cunghoctienganh/a798d10d-dee8-4bf8-a46e-6c45dbb791b5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details><br> # a798d10d-dee8-4bf8-a46e-6c45dbb791b5 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2802 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.3897 \| 0.1633 \| 200 \| 0.2802 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
augustinjianu/whisper-tiny-ro	augustinjianu	2025-01-15T15:00:52Z	21	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "ro", "dataset:mozilla-foundation/common_voice_17_0", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2025-01-14T22:58:36Z	--- library_name: transformers language: - ro license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Tiny Ro (local) - Augustin Jianu results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: ro split: test args: 'config: ro, split: test' metrics: - name: Wer type: wer value: 37.48352861569144 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Whisper Tiny Ro (local) - Augustin Jianu This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5978 - Wer: 37.4835 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| \|:-------------:\|:-------:\|:-----:\|:---------------:\|:-------:\| \| 0.4417 \| 1.7730 \| 1000 \| 0.5327 \| 43.8513 \| \| 0.1813 \| 3.5461 \| 2000 \| 0.4666 \| 38.8689 \| \| 0.0751 \| 5.3191 \| 3000 \| 0.4645 \| 36.5006 \| \| 0.0326 \| 7.0922 \| 4000 \| 0.4803 \| 36.4614 \| \| 0.0234 \| 8.8652 \| 5000 \| 0.5087 \| 36.5148 \| \| 0.0082 \| 10.6383 \| 6000 \| 0.5424 \| 36.6252 \| \| 0.0042 \| 12.4113 \| 7000 \| 0.5650 \| 37.6509 \| \| 0.0029 \| 14.1844 \| 8000 \| 0.5809 \| 36.8710 \| \| 0.0025 \| 15.9574 \| 9000 \| 0.5922 \| 38.1495 \| \| 0.0021 \| 17.7305 \| 10000 \| 0.5978 \| 37.4835 \| ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0
mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF	mradermacher	2025-01-15T15:00:04Z	555	0	transformers	[ "transformers", "gguf", "chat", "abliterated", "uncensored", "mergekit", "merge", "en", "base_model:pipihand01/QwQ-32B-Preview-abliterated-linear25", "base_model:quantized:pipihand01/QwQ-32B-Preview-abliterated-linear25", "license:apache-2.0", "endpoints_compatible", "region:us", "imatrix", "conversational" ]	null	2025-01-15T10:23:55Z	--- base_model: pipihand01/QwQ-32B-Preview-abliterated-linear25 language: - en library_name: transformers license: apache-2.0 license_link: https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-linear25/blob/main/LICENSE quantized_by: mradermacher tags: - chat - abliterated - uncensored - mergekit - merge --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: nicoboss --> weighted/imatrix quants of https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-linear25 <!-- provided-files --> static quants are available at https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ1_S.gguf) \| i1-IQ1_S \| 7.4 \| for the desperate \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ1_M.gguf) \| i1-IQ1_M \| 8.0 \| mostly desperate \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_XXS.gguf) \| i1-IQ2_XXS \| 9.1 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_XS.gguf) \| i1-IQ2_XS \| 10.1 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_S.gguf) \| i1-IQ2_S \| 10.5 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_M.gguf) \| i1-IQ2_M \| 11.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q2_K_S.gguf) \| i1-Q2_K_S \| 11.6 \| very low quality \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q2_K.gguf) \| i1-Q2_K \| 12.4 \| IQ3_XXS probably better \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_XXS.gguf) \| i1-IQ3_XXS \| 12.9 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_XS.gguf) \| i1-IQ3_XS \| 13.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_S.gguf) \| i1-Q3_K_S \| 14.5 \| IQ3_XS probably better \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_S.gguf) \| i1-IQ3_S \| 14.5 \| beats Q3_K* \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_M.gguf) \| i1-IQ3_M \| 14.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_M.gguf) \| i1-Q3_K_M \| 16.0 \| IQ3_S probably better \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_L.gguf) \| i1-Q3_K_L \| 17.3 \| IQ3_M probably better \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ4_XS.gguf) \| i1-IQ4_XS \| 17.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_0.gguf) \| i1-Q4_0 \| 18.8 \| fast, low quality \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_K_S.gguf) \| i1-Q4_K_S \| 18.9 \| optimal size/speed/quality \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_K_M.gguf) \| i1-Q4_K_M \| 20.0 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_1.gguf) \| i1-Q4_1 \| 20.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q5_K_S.gguf) \| i1-Q5_K_S \| 22.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q5_K_M.gguf) \| i1-Q5_K_M \| 23.4 \| \| \| [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q6_K.gguf) \| i1-Q6_K \| 27.0 \| practically like static Q6_K \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. <!-- end -->
hendrydong/ckpt-m-1115-1	hendrydong	2025-01-15T14:59:58Z	47	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-15T14:54:46Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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LocaleNLP/English_bambara	LocaleNLP	2025-01-15T14:59:17Z	263	0	transformers	[ "transformers", "safetensors", "marian", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2025-01-15T14:28:35Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
kokovova/1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7	kokovova	2025-01-15T14:58:59Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:trl-internal-testing/tiny-random-LlamaForCausalLM", "base_model:adapter:trl-internal-testing/tiny-random-LlamaForCausalLM", "region:us" ]	null	2025-01-15T14:58:05Z	--- library_name: peft base_model: trl-internal-testing/tiny-random-LlamaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: trl-internal-testing/tiny-random-LlamaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 986b94c9dc58c18c_train_data.json ds_type: json format: custom path: /workspace/input_data/986b94c9dc58c18c_train_data.json type: field_instruction: prompt field_output: response_a format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kokovova/1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/986b94c9dc58c18c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 69e5af40-c6f1-445f-a934-e367beed4132 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 69e5af40-c6f1-445f-a934-e367beed4132 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 This model is a fine-tuned version of [trl-internal-testing/tiny-random-LlamaForCausalLM](https://huggingface.co/trl-internal-testing/tiny-random-LlamaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.3785 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0001 \| 1 \| 10.3803 \| \| 10.3806 \| 0.0012 \| 8 \| 10.3800 \| \| 10.3797 \| 0.0024 \| 16 \| 10.3791 \| \| 10.3786 \| 0.0035 \| 24 \| 10.3785 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
minsangK/20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1	minsangK	2025-01-15T14:58:53Z	23	0	transformers	[ "transformers", "safetensors", "xlm-roberta", "feature-extraction", "generated_from_trainer", "text-embeddings-inference", "endpoints_compatible", "region:us" ]	feature-extraction	2025-01-15T11:06:31Z	--- library_name: transformers tags: - generated_from_trainer model-index: - name: 20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # 20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1 This model was trained from scratch on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.2 - Datasets 2.19.0 - Tokenizers 0.19.1
bbytxt/11002e5d-55bc-4350-a995-08db41105f07	bbytxt	2025-01-15T14:58:20Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM-1.7B-Instruct", "base_model:adapter:unsloth/SmolLM-1.7B-Instruct", "license:apache-2.0", "region:us" ]	null	2025-01-15T14:32:11Z	--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM-1.7B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 11002e5d-55bc-4350-a995-08db41105f07 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM-1.7B-Instruct bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - 19944eee78b6e7aa_train_data.json ds_type: json format: custom path: /workspace/input_data/19944eee78b6e7aa_train_data.json type: field_input: background field_instruction: context field_output: question format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/11002e5d-55bc-4350-a995-08db41105f07 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/19944eee78b6e7aa_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 3d13b11f-b0e7-4077-be87-c28a4188a998 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 3d13b11f-b0e7-4077-be87-c28a4188a998 warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 11002e5d-55bc-4350-a995-08db41105f07 This model is a fine-tuned version of [unsloth/SmolLM-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM-1.7B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7661 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 4.078 \| 0.0004 \| 1 \| 4.2947 \| \| 2.1366 \| 0.0186 \| 50 \| 2.0422 \| \| 2.0896 \| 0.0371 \| 100 \| 1.8271 \| \| 1.8261 \| 0.0557 \| 150 \| 1.7759 \| \| 2.0419 \| 0.0743 \| 200 \| 1.7661 \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
visdata/bc15	visdata	2025-01-15T14:58:14Z	57	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-01-15T14:46:23Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
youssefguessous/hautdela-lora-flux-dev	youssefguessous	2025-01-15T14:57:17Z	44	1	diffusers	[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]	text-to-image	2025-01-15T12:54:04Z	--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: HAUTDELA --- # Hautdela Lora Flux Dev <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `HAUTDELA` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('youssefguessous/hautdela-lora-flux-dev', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
dimasik87/388f1eb7-1d9e-47b8-9fb1-dcead681c9df	dimasik87	2025-01-15T14:57:06Z	8	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]	null	2025-01-15T14:15:12Z	--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 388f1eb7-1d9e-47b8-9fb1-dcead681c9df results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik87/388f1eb7-1d9e-47b8-9fb1-dcead681c9df hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details><br> # 388f1eb7-1d9e-47b8-9fb1-dcead681c9df This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| No log \| 0.0000 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 5 \| nan \| \| 0.0 \| 0.0005 \| 10 \| nan \| \| 0.0 \| 0.0007 \| 15 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1
MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization	MayBashendy	2025-01-15T14:56:51Z	5	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T14:08:55Z	--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6956 - Qwk: 0.4065 - Mse: 0.6956 - Rmse: 0.8340 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Qwk \| Mse \| Rmse \| \|:-------------:\|:-------:\|:----:\|:---------------:\|:-------:\|:------:\|:------:\| \| No log \| 0.0370 \| 2 \| 4.2649 \| -0.0228 \| 4.2649 \| 2.0652 \| \| No log \| 0.0741 \| 4 \| 2.4048 \| 0.0659 \| 2.4048 \| 1.5507 \| \| No log \| 0.1111 \| 6 \| 1.2037 \| 0.0258 \| 1.2037 \| 1.0971 \| \| No log \| 0.1481 \| 8 \| 0.8782 \| 0.1424 \| 0.8782 \| 0.9371 \| \| No log \| 0.1852 \| 10 \| 0.8781 \| 0.1210 \| 0.8781 \| 0.9371 \| \| No log \| 0.2222 \| 12 \| 0.9623 \| 0.0461 \| 0.9623 \| 0.9810 \| \| No log \| 0.2593 \| 14 \| 1.1572 \| -0.0959 \| 1.1572 \| 1.0757 \| \| No log \| 0.2963 \| 16 \| 1.0446 \| -0.0058 \| 1.0446 \| 1.0221 \| \| No log \| 0.3333 \| 18 \| 0.8847 \| 0.0712 \| 0.8847 \| 0.9406 \| \| No log \| 0.3704 \| 20 \| 0.9010 \| 0.0447 \| 0.9010 \| 0.9492 \| \| No log \| 0.4074 \| 22 \| 0.8834 \| 0.1596 \| 0.8834 \| 0.9399 \| \| No log \| 0.4444 \| 24 \| 0.9201 \| 0.1204 \| 0.9201 \| 0.9592 \| \| No log \| 0.4815 \| 26 \| 0.9268 \| 0.1865 \| 0.9268 \| 0.9627 \| \| No log \| 0.5185 \| 28 \| 1.0286 \| 0.0219 \| 1.0286 \| 1.0142 \| \| No log \| 0.5556 \| 30 \| 1.0217 \| 0.0724 \| 1.0217 \| 1.0108 \| \| No log \| 0.5926 \| 32 \| 1.0320 \| 0.0384 \| 1.0320 \| 1.0159 \| \| No log \| 0.6296 \| 34 \| 0.9380 \| 0.2221 \| 0.9380 \| 0.9685 \| \| No log \| 0.6667 \| 36 \| 0.8912 \| 0.2712 \| 0.8912 \| 0.9441 \| \| No log \| 0.7037 \| 38 \| 0.8365 \| 0.2929 \| 0.8365 \| 0.9146 \| \| No log \| 0.7407 \| 40 \| 0.8275 \| 0.2618 \| 0.8275 \| 0.9096 \| \| No log \| 0.7778 \| 42 \| 0.8612 \| 0.2517 \| 0.8612 \| 0.9280 \| \| No log \| 0.8148 \| 44 \| 0.9083 \| 0.1655 \| 0.9083 \| 0.9530 \| \| No log \| 0.8519 \| 46 \| 0.9579 \| 0.0189 \| 0.9579 \| 0.9787 \| \| No log \| 0.8889 \| 48 \| 0.8705 \| 0.2135 \| 0.8705 \| 0.9330 \| \| No log \| 0.9259 \| 50 \| 0.8026 \| 0.2723 \| 0.8026 \| 0.8959 \| \| No log \| 0.9630 \| 52 \| 0.8513 \| 0.1171 \| 0.8513 \| 0.9227 \| \| No log \| 1.0 \| 54 \| 0.8504 \| 0.1725 \| 0.8504 \| 0.9222 \| \| No log \| 1.0370 \| 56 \| 0.8050 \| 0.2772 \| 0.8050 \| 0.8972 \| \| No log \| 1.0741 \| 58 \| 0.7881 \| 0.3398 \| 0.7881 \| 0.8877 \| \| No log \| 1.1111 \| 60 \| 0.8618 \| 0.3128 \| 0.8618 \| 0.9283 \| \| No log \| 1.1481 \| 62 \| 1.0342 \| 0.3109 \| 1.0342 \| 1.0169 \| \| No log \| 1.1852 \| 64 \| 0.8242 \| 0.2916 \| 0.8242 \| 0.9078 \| \| No log \| 1.2222 \| 66 \| 0.7361 \| 0.2098 \| 0.7361 \| 0.8580 \| \| No log \| 1.2593 \| 68 \| 0.7477 \| 0.2240 \| 0.7477 \| 0.8647 \| \| No log \| 1.2963 \| 70 \| 0.8031 \| 0.2975 \| 0.8031 \| 0.8962 \| \| No log \| 1.3333 \| 72 \| 1.0369 \| 0.2641 \| 1.0369 \| 1.0183 \| \| No log \| 1.3704 \| 74 \| 0.8289 \| 0.3314 \| 0.8289 \| 0.9104 \| \| No log \| 1.4074 \| 76 \| 0.7565 \| 0.2932 \| 0.7565 \| 0.8698 \| \| No log \| 1.4444 \| 78 \| 0.7453 \| 0.3283 \| 0.7453 \| 0.8633 \| \| No log \| 1.4815 \| 80 \| 0.9273 \| 0.2649 \| 0.9273 \| 0.9630 \| \| No log \| 1.5185 \| 82 \| 0.9151 \| 0.2909 \| 0.9151 \| 0.9566 \| \| No log \| 1.5556 \| 84 \| 0.7353 \| 0.2598 \| 0.7353 \| 0.8575 \| \| No log \| 1.5926 \| 86 \| 0.7402 \| 0.2537 \| 0.7402 \| 0.8603 \| \| No log \| 1.6296 \| 88 \| 0.7210 \| 0.3183 \| 0.7210 \| 0.8491 \| \| No log \| 1.6667 \| 90 \| 0.7265 \| 0.2319 \| 0.7265 \| 0.8523 \| \| No log \| 1.7037 \| 92 \| 0.9780 \| 0.1547 \| 0.9780 \| 0.9890 \| \| No log \| 1.7407 \| 94 \| 1.1386 \| 0.1581 \| 1.1386 \| 1.0670 \| \| No log \| 1.7778 \| 96 \| 0.9872 \| 0.1703 \| 0.9872 \| 0.9936 \| \| No log \| 1.8148 \| 98 \| 0.7693 \| 0.2500 \| 0.7693 \| 0.8771 \| \| No log \| 1.8519 \| 100 \| 0.6808 \| 0.3121 \| 0.6808 \| 0.8251 \| \| No log \| 1.8889 \| 102 \| 0.7115 \| 0.2345 \| 0.7115 \| 0.8435 \| \| No log \| 1.9259 \| 104 \| 0.7080 \| 0.3626 \| 0.7080 \| 0.8414 \| \| No log \| 1.9630 \| 106 \| 0.7251 \| 0.3840 \| 0.7251 \| 0.8515 \| \| No log \| 2.0 \| 108 \| 0.8961 \| 0.3583 \| 0.8961 \| 0.9466 \| \| No log \| 2.0370 \| 110 \| 0.8678 \| 0.3421 \| 0.8678 \| 0.9315 \| \| No log \| 2.0741 \| 112 \| 0.7853 \| 0.4160 \| 0.7853 \| 0.8862 \| \| No log \| 2.1111 \| 114 \| 0.7847 \| 0.3450 \| 0.7847 \| 0.8858 \| \| No log \| 2.1481 \| 116 \| 0.7820 \| 0.2879 \| 0.7820 \| 0.8843 \| \| No log \| 2.1852 \| 118 \| 0.7886 \| 0.2819 \| 0.7886 \| 0.8880 \| \| No log \| 2.2222 \| 120 \| 0.8080 \| 0.3674 \| 0.8080 \| 0.8989 \| \| No log \| 2.2593 \| 122 \| 0.7933 \| 0.3608 \| 0.7933 \| 0.8907 \| \| No log \| 2.2963 \| 124 \| 0.8356 \| 0.1799 \| 0.8356 \| 0.9141 \| \| No log \| 2.3333 \| 126 \| 0.7891 \| 0.3746 \| 0.7891 \| 0.8883 \| \| No log \| 2.3704 \| 128 \| 1.0069 \| 0.2719 \| 1.0069 \| 1.0034 \| \| No log \| 2.4074 \| 130 \| 1.1976 \| 0.2507 \| 1.1976 \| 1.0944 \| \| No log \| 2.4444 \| 132 \| 0.9833 \| 0.2422 \| 0.9833 \| 0.9916 \| \| No log \| 2.4815 \| 134 \| 0.7235 \| 0.3557 \| 0.7235 \| 0.8506 \| \| No log \| 2.5185 \| 136 \| 0.7984 \| 0.2655 \| 0.7984 \| 0.8935 \| \| No log \| 2.5556 \| 138 \| 0.7571 \| 0.2872 \| 0.7571 \| 0.8701 \| \| No log \| 2.5926 \| 140 \| 0.6836 \| 0.3905 \| 0.6836 \| 0.8268 \| \| No log \| 2.6296 \| 142 \| 0.7576 \| 0.2694 \| 0.7576 \| 0.8704 \| \| No log \| 2.6667 \| 144 \| 0.8193 \| 0.2553 \| 0.8193 \| 0.9052 \| \| No log \| 2.7037 \| 146 \| 0.7582 \| 0.3387 \| 0.7582 \| 0.8708 \| \| No log \| 2.7407 \| 148 \| 0.6818 \| 0.4172 \| 0.6818 \| 0.8257 \| \| No log \| 2.7778 \| 150 \| 0.6817 \| 0.3847 \| 0.6817 \| 0.8256 \| \| No log \| 2.8148 \| 152 \| 0.6857 \| 0.4001 \| 0.6857 \| 0.8280 \| \| No log \| 2.8519 \| 154 \| 0.6964 \| 0.3905 \| 0.6964 \| 0.8345 \| \| No log \| 2.8889 \| 156 \| 0.7135 \| 0.3795 \| 0.7135 \| 0.8447 \| \| No log \| 2.9259 \| 158 \| 0.7874 \| 0.3589 \| 0.7874 \| 0.8874 \| \| No log \| 2.9630 \| 160 \| 0.8083 \| 0.3097 \| 0.8083 \| 0.8990 \| \| No log \| 3.0 \| 162 \| 0.7531 \| 0.3002 \| 0.7531 \| 0.8678 \| \| No log \| 3.0370 \| 164 \| 0.7420 \| 0.3057 \| 0.7420 \| 0.8614 \| \| No log \| 3.0741 \| 166 \| 0.7428 \| 0.2769 \| 0.7428 \| 0.8619 \| \| No log \| 3.1111 \| 168 \| 0.7424 \| 0.2735 \| 0.7424 \| 0.8616 \| \| No log \| 3.1481 \| 170 \| 0.6882 \| 0.3449 \| 0.6882 \| 0.8296 \| \| No log \| 3.1852 \| 172 \| 0.7197 \| 0.4562 \| 0.7197 \| 0.8484 \| \| No log \| 3.2222 \| 174 \| 0.7287 \| 0.4128 \| 0.7287 \| 0.8536 \| \| No log \| 3.2593 \| 176 \| 0.7444 \| 0.4239 \| 0.7444 \| 0.8628 \| \| No log \| 3.2963 \| 178 \| 0.7850 \| 0.3941 \| 0.7850 \| 0.8860 \| \| No log \| 3.3333 \| 180 \| 0.7861 \| 0.4062 \| 0.7861 \| 0.8866 \| \| No log \| 3.3704 \| 182 \| 0.7008 \| 0.4332 \| 0.7008 \| 0.8371 \| \| No log \| 3.4074 \| 184 \| 0.6862 \| 0.4233 \| 0.6862 \| 0.8284 \| \| No log \| 3.4444 \| 186 \| 0.6707 \| 0.3905 \| 0.6707 \| 0.8189 \| \| No log \| 3.4815 \| 188 \| 0.6858 \| 0.3590 \| 0.6858 \| 0.8281 \| \| No log \| 3.5185 \| 190 \| 0.8277 \| 0.3560 \| 0.8277 \| 0.9098 \| \| No log \| 3.5556 \| 192 \| 0.8980 \| 0.3155 \| 0.8980 \| 0.9476 \| \| No log \| 3.5926 \| 194 \| 0.7492 \| 0.3088 \| 0.7492 \| 0.8655 \| \| No log \| 3.6296 \| 196 \| 0.6773 \| 0.3358 \| 0.6773 \| 0.8230 \| \| No log \| 3.6667 \| 198 \| 0.7539 \| 0.3898 \| 0.7539 \| 0.8683 \| \| No log \| 3.7037 \| 200 \| 0.7836 \| 0.3404 \| 0.7836 \| 0.8852 \| \| No log \| 3.7407 \| 202 \| 0.7252 \| 0.4127 \| 0.7252 \| 0.8516 \| \| No log \| 3.7778 \| 204 \| 0.7269 \| 0.3153 \| 0.7269 \| 0.8526 \| \| No log \| 3.8148 \| 206 \| 0.8672 \| 0.2295 \| 0.8672 \| 0.9312 \| \| No log \| 3.8519 \| 208 \| 0.8732 \| 0.2705 \| 0.8732 \| 0.9345 \| \| No log \| 3.8889 \| 210 \| 0.7278 \| 0.3419 \| 0.7278 \| 0.8531 \| \| No log \| 3.9259 \| 212 \| 0.6975 \| 0.4351 \| 0.6975 \| 0.8351 \| \| No log \| 3.9630 \| 214 \| 0.7183 \| 0.4552 \| 0.7183 \| 0.8476 \| \| No log \| 4.0 \| 216 \| 0.7031 \| 0.4728 \| 0.7031 \| 0.8385 \| \| No log \| 4.0370 \| 218 \| 0.7066 \| 0.3930 \| 0.7066 \| 0.8406 \| \| No log \| 4.0741 \| 220 \| 0.7424 \| 0.3812 \| 0.7424 \| 0.8617 \| \| No log \| 4.1111 \| 222 \| 0.7145 \| 0.3401 \| 0.7145 \| 0.8453 \| \| No log \| 4.1481 \| 224 \| 0.7027 \| 0.3419 \| 0.7027 \| 0.8382 \| \| No log \| 4.1852 \| 226 \| 0.6740 \| 0.3789 \| 0.6740 \| 0.8210 \| \| No log \| 4.2222 \| 228 \| 0.6646 \| 0.3990 \| 0.6646 \| 0.8152 \| \| No log \| 4.2593 \| 230 \| 0.6643 \| 0.4154 \| 0.6643 \| 0.8151 \| \| No log \| 4.2963 \| 232 \| 0.6807 \| 0.4047 \| 0.6807 \| 0.8250 \| \| No log \| 4.3333 \| 234 \| 0.7314 \| 0.4496 \| 0.7314 \| 0.8552 \| \| No log \| 4.3704 \| 236 \| 0.7605 \| 0.4808 \| 0.7605 \| 0.8721 \| \| No log \| 4.4074 \| 238 \| 0.7136 \| 0.4234 \| 0.7136 \| 0.8447 \| \| No log \| 4.4444 \| 240 \| 0.7071 \| 0.4520 \| 0.7071 \| 0.8409 \| \| No log \| 4.4815 \| 242 \| 0.7238 \| 0.4571 \| 0.7238 \| 0.8508 \| \| No log \| 4.5185 \| 244 \| 0.7134 \| 0.4346 \| 0.7134 \| 0.8446 \| \| No log \| 4.5556 \| 246 \| 0.7427 \| 0.4241 \| 0.7427 \| 0.8618 \| \| No log \| 4.5926 \| 248 \| 0.7480 \| 0.4094 \| 0.7480 \| 0.8648 \| \| No log \| 4.6296 \| 250 \| 0.7522 \| 0.4079 \| 0.7522 \| 0.8673 \| \| No log \| 4.6667 \| 252 \| 0.7522 \| 0.4296 \| 0.7522 \| 0.8673 \| \| No log \| 4.7037 \| 254 \| 0.7353 \| 0.3845 \| 0.7353 \| 0.8575 \| \| No log \| 4.7407 \| 256 \| 0.7388 \| 0.3514 \| 0.7388 \| 0.8595 \| \| No log \| 4.7778 \| 258 \| 0.7709 \| 0.3659 \| 0.7709 \| 0.8780 \| \| No log \| 4.8148 \| 260 \| 0.7823 \| 0.3613 \| 0.7823 \| 0.8845 \| \| No log \| 4.8519 \| 262 \| 0.7626 \| 0.3703 \| 0.7626 \| 0.8733 \| \| No log \| 4.8889 \| 264 \| 0.7646 \| 0.4058 \| 0.7646 \| 0.8744 \| \| No log \| 4.9259 \| 266 \| 0.7517 \| 0.4111 \| 0.7517 \| 0.8670 \| \| No log \| 4.9630 \| 268 \| 0.7591 \| 0.3921 \| 0.7591 \| 0.8713 \| \| No log \| 5.0 \| 270 \| 0.7818 \| 0.4122 \| 0.7818 \| 0.8842 \| \| No log \| 5.0370 \| 272 \| 0.7745 \| 0.4303 \| 0.7745 \| 0.8800 \| \| No log \| 5.0741 \| 274 \| 0.7880 \| 0.4521 \| 0.7880 \| 0.8877 \| \| No log \| 5.1111 \| 276 \| 0.8725 \| 0.3928 \| 0.8725 \| 0.9341 \| \| No log \| 5.1481 \| 278 \| 0.8682 \| 0.3761 \| 0.8682 \| 0.9318 \| \| No log \| 5.1852 \| 280 \| 0.7397 \| 0.4129 \| 0.7397 \| 0.8600 \| \| No log \| 5.2222 \| 282 \| 0.7005 \| 0.3669 \| 0.7005 \| 0.8370 \| \| No log \| 5.2593 \| 284 \| 0.7074 \| 0.3585 \| 0.7074 \| 0.8410 \| \| No log \| 5.2963 \| 286 \| 0.7026 \| 0.3227 \| 0.7026 \| 0.8382 \| \| No log \| 5.3333 \| 288 \| 0.7122 \| 0.3655 \| 0.7122 \| 0.8439 \| \| No log \| 5.3704 \| 290 \| 0.7270 \| 0.3693 \| 0.7270 \| 0.8526 \| \| No log \| 5.4074 \| 292 \| 0.7674 \| 0.4339 \| 0.7674 \| 0.8760 \| \| No log \| 5.4444 \| 294 \| 0.7428 \| 0.3853 \| 0.7428 \| 0.8618 \| \| No log \| 5.4815 \| 296 \| 0.7304 \| 0.3568 \| 0.7304 \| 0.8546 \| \| No log \| 5.5185 \| 298 \| 0.7671 \| 0.2821 \| 0.7671 \| 0.8758 \| \| No log \| 5.5556 \| 300 \| 0.7282 \| 0.3860 \| 0.7282 \| 0.8534 \| \| No log \| 5.5926 \| 302 \| 0.7099 \| 0.3877 \| 0.7099 \| 0.8426 \| \| No log \| 5.6296 \| 304 \| 0.7235 \| 0.3827 \| 0.7235 \| 0.8506 \| \| No log \| 5.6667 \| 306 \| 0.7305 \| 0.4462 \| 0.7305 \| 0.8547 \| \| No log \| 5.7037 \| 308 \| 0.6874 \| 0.4306 \| 0.6874 \| 0.8291 \| \| No log \| 5.7407 \| 310 \| 0.7730 \| 0.4009 \| 0.7730 \| 0.8792 \| \| No log \| 5.7778 \| 312 \| 0.8971 \| 0.3048 \| 0.8971 \| 0.9472 \| \| No log \| 5.8148 \| 314 \| 0.8102 \| 0.3699 \| 0.8102 \| 0.9001 \| \| No log \| 5.8519 \| 316 \| 0.6982 \| 0.4026 \| 0.6982 \| 0.8356 \| \| No log \| 5.8889 \| 318 \| 0.6854 \| 0.3977 \| 0.6854 \| 0.8279 \| \| No log \| 5.9259 \| 320 \| 0.6907 \| 0.4542 \| 0.6907 \| 0.8311 \| \| No log \| 5.9630 \| 322 \| 0.7088 \| 0.4649 \| 0.7088 \| 0.8419 \| \| No log \| 6.0 \| 324 \| 0.7319 \| 0.4862 \| 0.7319 \| 0.8555 \| \| No log \| 6.0370 \| 326 \| 0.7332 \| 0.4812 \| 0.7332 \| 0.8563 \| \| No log \| 6.0741 \| 328 \| 0.7223 \| 0.4940 \| 0.7223 \| 0.8499 \| \| No log \| 6.1111 \| 330 \| 0.7190 \| 0.3858 \| 0.7190 \| 0.8479 \| \| No log \| 6.1481 \| 332 \| 0.7488 \| 0.3590 \| 0.7488 \| 0.8653 \| \| No log \| 6.1852 \| 334 \| 0.7076 \| 0.2821 \| 0.7076 \| 0.8412 \| \| No log \| 6.2222 \| 336 \| 0.6852 \| 0.2982 \| 0.6852 \| 0.8278 \| \| No log \| 6.2593 \| 338 \| 0.7207 \| 0.2521 \| 0.7207 \| 0.8490 \| \| No log \| 6.2963 \| 340 \| 0.7623 \| 0.2642 \| 0.7623 \| 0.8731 \| \| No log \| 6.3333 \| 342 \| 0.7289 \| 0.3507 \| 0.7289 \| 0.8538 \| \| No log \| 6.3704 \| 344 \| 0.6978 \| 0.3791 \| 0.6978 \| 0.8353 \| \| No log \| 6.4074 \| 346 \| 0.6939 \| 0.3435 \| 0.6939 \| 0.8330 \| \| No log \| 6.4444 \| 348 \| 0.7328 \| 0.3696 \| 0.7328 \| 0.8561 \| \| No log \| 6.4815 \| 350 \| 0.7141 \| 0.384 \| 0.7141 \| 0.8450 \| \| No log \| 6.5185 \| 352 \| 0.6893 \| 0.3894 \| 0.6893 \| 0.8302 \| \| No log \| 6.5556 \| 354 \| 0.6849 \| 0.3443 \| 0.6849 \| 0.8276 \| \| No log \| 6.5926 \| 356 \| 0.7324 \| 0.3791 \| 0.7324 \| 0.8558 \| \| No log \| 6.6296 \| 358 \| 0.7436 \| 0.3755 \| 0.7436 \| 0.8623 \| \| No log \| 6.6667 \| 360 \| 0.7026 \| 0.3604 \| 0.7026 \| 0.8382 \| \| No log \| 6.7037 \| 362 \| 0.7192 \| 0.3814 \| 0.7192 \| 0.8481 \| \| No log \| 6.7407 \| 364 \| 0.7593 \| 0.3607 \| 0.7593 \| 0.8714 \| \| No log \| 6.7778 \| 366 \| 0.7241 \| 0.3776 \| 0.7241 \| 0.8509 \| \| No log \| 6.8148 \| 368 \| 0.7035 \| 0.3373 \| 0.7035 \| 0.8388 \| \| No log \| 6.8519 \| 370 \| 0.7332 \| 0.3985 \| 0.7332 \| 0.8563 \| \| No log \| 6.8889 \| 372 \| 0.7415 \| 0.3983 \| 0.7415 \| 0.8611 \| \| No log \| 6.9259 \| 374 \| 0.7157 \| 0.3970 \| 0.7157 \| 0.8460 \| \| No log \| 6.9630 \| 376 \| 0.7331 \| 0.3808 \| 0.7331 \| 0.8562 \| \| No log \| 7.0 \| 378 \| 0.7475 \| 0.4068 \| 0.7475 \| 0.8646 \| \| No log \| 7.0370 \| 380 \| 0.7260 \| 0.3782 \| 0.7260 \| 0.8521 \| \| No log \| 7.0741 \| 382 \| 0.7003 \| 0.3363 \| 0.7003 \| 0.8369 \| \| No log \| 7.1111 \| 384 \| 0.7012 \| 0.4209 \| 0.7012 \| 0.8374 \| \| No log \| 7.1481 \| 386 \| 0.7126 \| 0.4273 \| 0.7126 \| 0.8442 \| \| No log \| 7.1852 \| 388 \| 0.7068 \| 0.4146 \| 0.7068 \| 0.8407 \| \| No log \| 7.2222 \| 390 \| 0.6893 \| 0.3976 \| 0.6893 \| 0.8302 \| \| No log \| 7.2593 \| 392 \| 0.7194 \| 0.3353 \| 0.7194 \| 0.8482 \| \| No log \| 7.2963 \| 394 \| 0.7559 \| 0.3323 \| 0.7559 \| 0.8694 \| \| No log \| 7.3333 \| 396 \| 0.7225 \| 0.3618 \| 0.7225 \| 0.8500 \| \| No log \| 7.3704 \| 398 \| 0.7170 \| 0.3776 \| 0.7170 \| 0.8468 \| \| No log \| 7.4074 \| 400 \| 0.7965 \| 0.3963 \| 0.7965 \| 0.8925 \| \| No log \| 7.4444 \| 402 \| 0.9136 \| 0.3449 \| 0.9136 \| 0.9558 \| \| No log \| 7.4815 \| 404 \| 0.8872 \| 0.3363 \| 0.8872 \| 0.9419 \| \| No log \| 7.5185 \| 406 \| 0.7623 \| 0.3967 \| 0.7623 \| 0.8731 \| \| No log \| 7.5556 \| 408 \| 0.7050 \| 0.3184 \| 0.7050 \| 0.8396 \| \| No log \| 7.5926 \| 410 \| 0.6974 \| 0.3655 \| 0.6974 \| 0.8351 \| \| No log \| 7.6296 \| 412 \| 0.7093 \| 0.2859 \| 0.7093 \| 0.8422 \| \| No log \| 7.6667 \| 414 \| 0.6987 \| 0.3212 \| 0.6987 \| 0.8359 \| \| No log \| 7.7037 \| 416 \| 0.6966 \| 0.3645 \| 0.6966 \| 0.8346 \| \| No log \| 7.7407 \| 418 \| 0.6930 \| 0.3961 \| 0.6930 \| 0.8324 \| \| No log \| 7.7778 \| 420 \| 0.6835 \| 0.4450 \| 0.6835 \| 0.8267 \| \| No log \| 7.8148 \| 422 \| 0.6783 \| 0.4712 \| 0.6783 \| 0.8236 \| \| No log \| 7.8519 \| 424 \| 0.7015 \| 0.4629 \| 0.7015 \| 0.8376 \| \| No log \| 7.8889 \| 426 \| 0.6753 \| 0.4621 \| 0.6753 \| 0.8218 \| \| No log \| 7.9259 \| 428 \| 0.6774 \| 0.3902 \| 0.6774 \| 0.8230 \| \| No log \| 7.9630 \| 430 \| 0.7012 \| 0.4128 \| 0.7012 \| 0.8374 \| \| No log \| 8.0 \| 432 \| 0.6767 \| 0.4186 \| 0.6767 \| 0.8226 \| \| No log \| 8.0370 \| 434 \| 0.6702 \| 0.4079 \| 0.6702 \| 0.8187 \| \| No log \| 8.0741 \| 436 \| 0.6775 \| 0.4211 \| 0.6775 \| 0.8231 \| \| No log \| 8.1111 \| 438 \| 0.6938 \| 0.4465 \| 0.6938 \| 0.8330 \| \| No log \| 8.1481 \| 440 \| 0.7008 \| 0.4403 \| 0.7008 \| 0.8372 \| \| No log \| 8.1852 \| 442 \| 0.6938 \| 0.4465 \| 0.6938 \| 0.8329 \| \| No log \| 8.2222 \| 444 \| 0.7169 \| 0.4451 \| 0.7169 \| 0.8467 \| \| No log \| 8.2593 \| 446 \| 0.7140 \| 0.4504 \| 0.7140 \| 0.8450 \| \| No log \| 8.2963 \| 448 \| 0.7267 \| 0.4444 \| 0.7267 \| 0.8525 \| \| No log \| 8.3333 \| 450 \| 0.7111 \| 0.4713 \| 0.7111 \| 0.8433 \| \| No log \| 8.3704 \| 452 \| 0.7098 \| 0.4960 \| 0.7098 \| 0.8425 \| \| No log \| 8.4074 \| 454 \| 0.7196 \| 0.4569 \| 0.7196 \| 0.8483 \| \| No log \| 8.4444 \| 456 \| 0.7759 \| 0.4233 \| 0.7759 \| 0.8808 \| \| No log \| 8.4815 \| 458 \| 0.7809 \| 0.4237 \| 0.7809 \| 0.8837 \| \| No log \| 8.5185 \| 460 \| 0.7744 \| 0.4066 \| 0.7744 \| 0.8800 \| \| No log \| 8.5556 \| 462 \| 0.7148 \| 0.3988 \| 0.7148 \| 0.8455 \| \| No log \| 8.5926 \| 464 \| 0.7066 \| 0.4181 \| 0.7066 \| 0.8406 \| \| No log \| 8.6296 \| 466 \| 0.7049 \| 0.3904 \| 0.7049 \| 0.8396 \| \| No log \| 8.6667 \| 468 \| 0.7050 \| 0.4147 \| 0.7050 \| 0.8397 \| \| No log \| 8.7037 \| 470 \| 0.7628 \| 0.3665 \| 0.7628 \| 0.8734 \| \| No log \| 8.7407 \| 472 \| 0.8046 \| 0.2797 \| 0.8046 \| 0.8970 \| \| No log \| 8.7778 \| 474 \| 0.7751 \| 0.3621 \| 0.7751 \| 0.8804 \| \| No log \| 8.8148 \| 476 \| 0.7161 \| 0.3629 \| 0.7161 \| 0.8462 \| \| No log \| 8.8519 \| 478 \| 0.7246 \| 0.3481 \| 0.7246 \| 0.8512 \| \| No log \| 8.8889 \| 480 \| 0.7615 \| 0.4345 \| 0.7615 \| 0.8727 \| \| No log \| 8.9259 \| 482 \| 0.7338 \| 0.3665 \| 0.7338 \| 0.8566 \| \| No log \| 8.9630 \| 484 \| 0.7104 \| 0.4143 \| 0.7104 \| 0.8428 \| \| No log \| 9.0 \| 486 \| 0.7510 \| 0.3212 \| 0.7510 \| 0.8666 \| \| No log \| 9.0370 \| 488 \| 0.7680 \| 0.3347 \| 0.7680 \| 0.8764 \| \| No log \| 9.0741 \| 490 \| 0.7204 \| 0.3338 \| 0.7204 \| 0.8488 \| \| No log \| 9.1111 \| 492 \| 0.6770 \| 0.3475 \| 0.6770 \| 0.8228 \| \| No log \| 9.1481 \| 494 \| 0.6943 \| 0.3249 \| 0.6943 \| 0.8332 \| \| No log \| 9.1852 \| 496 \| 0.6981 \| 0.3090 \| 0.6981 \| 0.8356 \| \| No log \| 9.2222 \| 498 \| 0.6866 \| 0.3215 \| 0.6866 \| 0.8286 \| \| 0.3989 \| 9.2593 \| 500 \| 0.6787 \| 0.2617 \| 0.6787 \| 0.8238 \| \| 0.3989 \| 9.2963 \| 502 \| 0.7103 \| 0.3806 \| 0.7103 \| 0.8428 \| \| 0.3989 \| 9.3333 \| 504 \| 0.7781 \| 0.3991 \| 0.7781 \| 0.8821 \| \| 0.3989 \| 9.3704 \| 506 \| 0.7649 \| 0.4175 \| 0.7649 \| 0.8746 \| \| 0.3989 \| 9.4074 \| 508 \| 0.7344 \| 0.3725 \| 0.7344 \| 0.8570 \| \| 0.3989 \| 9.4444 \| 510 \| 0.6900 \| 0.2849 \| 0.6900 \| 0.8306 \| \| 0.3989 \| 9.4815 \| 512 \| 0.6813 \| 0.2647 \| 0.6813 \| 0.8254 \| \| 0.3989 \| 9.5185 \| 514 \| 0.6820 \| 0.2647 \| 0.6820 \| 0.8258 \| \| 0.3989 \| 9.5556 \| 516 \| 0.6890 \| 0.2912 \| 0.6890 \| 0.8300 \| \| 0.3989 \| 9.5926 \| 518 \| 0.6841 \| 0.2912 \| 0.6841 \| 0.8271 \| \| 0.3989 \| 9.6296 \| 520 \| 0.6673 \| 0.3036 \| 0.6673 \| 0.8169 \| \| 0.3989 \| 9.6667 \| 522 \| 0.6629 \| 0.3024 \| 0.6629 \| 0.8142 \| \| 0.3989 \| 9.7037 \| 524 \| 0.6666 \| 0.3090 \| 0.6666 \| 0.8165 \| \| 0.3989 \| 9.7407 \| 526 \| 0.6590 \| 0.3307 \| 0.6590 \| 0.8118 \| \| 0.3989 \| 9.7778 \| 528 \| 0.6633 \| 0.3598 \| 0.6633 \| 0.8144 \| \| 0.3989 \| 9.8148 \| 530 \| 0.6790 \| 0.3652 \| 0.6790 \| 0.8240 \| \| 0.3989 \| 9.8519 \| 532 \| 0.6762 \| 0.3866 \| 0.6762 \| 0.8223 \| \| 0.3989 \| 9.8889 \| 534 \| 0.6872 \| 0.4164 \| 0.6872 \| 0.8290 \| \| 0.3989 \| 9.9259 \| 536 \| 0.6703 \| 0.4307 \| 0.6703 \| 0.8187 \| \| 0.3989 \| 9.9630 \| 538 \| 0.6707 \| 0.4018 \| 0.6707 \| 0.8190 \| \| 0.3989 \| 10.0 \| 540 \| 0.6676 \| 0.3584 \| 0.6676 \| 0.8171 \| \| 0.3989 \| 10.0370 \| 542 \| 0.6725 \| 0.4244 \| 0.6725 \| 0.8201 \| \| 0.3989 \| 10.0741 \| 544 \| 0.7166 \| 0.3911 \| 0.7166 \| 0.8465 \| \| 0.3989 \| 10.1111 \| 546 \| 0.6942 \| 0.3875 \| 0.6942 \| 0.8332 \| \| 0.3989 \| 10.1481 \| 548 \| 0.6521 \| 0.3847 \| 0.6521 \| 0.8076 \| \| 0.3989 \| 10.1852 \| 550 \| 0.6613 \| 0.3423 \| 0.6613 \| 0.8132 \| \| 0.3989 \| 10.2222 \| 552 \| 0.6784 \| 0.3811 \| 0.6784 \| 0.8236 \| \| 0.3989 \| 10.2593 \| 554 \| 0.6593 \| 0.3961 \| 0.6593 \| 0.8120 \| \| 0.3989 \| 10.2963 \| 556 \| 0.6501 \| 0.3639 \| 0.6501 \| 0.8063 \| \| 0.3989 \| 10.3333 \| 558 \| 0.6681 \| 0.3637 \| 0.6681 \| 0.8174 \| \| 0.3989 \| 10.3704 \| 560 \| 0.7092 \| 0.4351 \| 0.7092 \| 0.8421 \| \| 0.3989 \| 10.4074 \| 562 \| 0.6952 \| 0.4476 \| 0.6952 \| 0.8338 \| \| 0.3989 \| 10.4444 \| 564 \| 0.6861 \| 0.3861 \| 0.6861 \| 0.8283 \| \| 0.3989 \| 10.4815 \| 566 \| 0.7003 \| 0.4138 \| 0.7003 \| 0.8368 \| \| 0.3989 \| 10.5185 \| 568 \| 0.6967 \| 0.3646 \| 0.6967 \| 0.8347 \| \| 0.3989 \| 10.5556 \| 570 \| 0.6775 \| 0.3455 \| 0.6775 \| 0.8231 \| \| 0.3989 \| 10.5926 \| 572 \| 0.6778 \| 0.3455 \| 0.6778 \| 0.8233 \| \| 0.3989 \| 10.6296 \| 574 \| 0.6976 \| 0.3124 \| 0.6976 \| 0.8352 \| \| 0.3989 \| 10.6667 \| 576 \| 0.7550 \| 0.3738 \| 0.7550 \| 0.8689 \| \| 0.3989 \| 10.7037 \| 578 \| 0.7780 \| 0.4051 \| 0.7780 \| 0.8820 \| \| 0.3989 \| 10.7407 \| 580 \| 0.7216 \| 0.3524 \| 0.7216 \| 0.8495 \| \| 0.3989 \| 10.7778 \| 582 \| 0.6932 \| 0.3696 \| 0.6932 \| 0.8326 \| \| 0.3989 \| 10.8148 \| 584 \| 0.6912 \| 0.4042 \| 0.6912 \| 0.8314 \| \| 0.3989 \| 10.8519 \| 586 \| 0.6984 \| 0.3805 \| 0.6984 \| 0.8357 \| \| 0.3989 \| 10.8889 \| 588 \| 0.7320 \| 0.3074 \| 0.7320 \| 0.8556 \| \| 0.3989 \| 10.9259 \| 590 \| 0.7950 \| 0.4049 \| 0.7950 \| 0.8916 \| \| 0.3989 \| 10.9630 \| 592 \| 0.8450 \| 0.3658 \| 0.8450 \| 0.9192 \| \| 0.3989 \| 11.0 \| 594 \| 0.8332 \| 0.3711 \| 0.8332 \| 0.9128 \| \| 0.3989 \| 11.0370 \| 596 \| 0.7693 \| 0.3146 \| 0.7693 \| 0.8771 \| \| 0.3989 \| 11.0741 \| 598 \| 0.7161 \| 0.2683 \| 0.7161 \| 0.8462 \| \| 0.3989 \| 11.1111 \| 600 \| 0.7131 \| 0.2764 \| 0.7131 \| 0.8445 \| \| 0.3989 \| 11.1481 \| 602 \| 0.7296 \| 0.2635 \| 0.7296 \| 0.8542 \| \| 0.3989 \| 11.1852 \| 604 \| 0.7695 \| 0.2883 \| 0.7695 \| 0.8772 \| \| 0.3989 \| 11.2222 \| 606 \| 0.7810 \| 0.3082 \| 0.7810 \| 0.8837 \| \| 0.3989 \| 11.2593 \| 608 \| 0.7489 \| 0.3211 \| 0.7489 \| 0.8654 \| \| 0.3989 \| 11.2963 \| 610 \| 0.6990 \| 0.3722 \| 0.6990 \| 0.8361 \| \| 0.3989 \| 11.3333 \| 612 \| 0.6908 \| 0.3637 \| 0.6908 \| 0.8312 \| \| 0.3989 \| 11.3704 \| 614 \| 0.6900 \| 0.4327 \| 0.6900 \| 0.8307 \| \| 0.3989 \| 11.4074 \| 616 \| 0.6778 \| 0.3593 \| 0.6778 \| 0.8233 \| \| 0.3989 \| 11.4444 \| 618 \| 0.6911 \| 0.3123 \| 0.6911 \| 0.8313 \| \| 0.3989 \| 11.4815 \| 620 \| 0.7727 \| 0.3614 \| 0.7727 \| 0.8790 \| \| 0.3989 \| 11.5185 \| 622 \| 0.8277 \| 0.3627 \| 0.8277 \| 0.9098 \| \| 0.3989 \| 11.5556 \| 624 \| 0.7816 \| 0.3516 \| 0.7816 \| 0.8841 \| \| 0.3989 \| 11.5926 \| 626 \| 0.6957 \| 0.3840 \| 0.6957 \| 0.8341 \| \| 0.3989 \| 11.6296 \| 628 \| 0.6688 \| 0.2742 \| 0.6688 \| 0.8178 \| \| 0.3989 \| 11.6667 \| 630 \| 0.6807 \| 0.3720 \| 0.6807 \| 0.8250 \| \| 0.3989 \| 11.7037 \| 632 \| 0.6776 \| 0.3833 \| 0.6776 \| 0.8232 \| \| 0.3989 \| 11.7407 \| 634 \| 0.6928 \| 0.3954 \| 0.6928 \| 0.8324 \| \| 0.3989 \| 11.7778 \| 636 \| 0.7114 \| 0.3921 \| 0.7114 \| 0.8434 \| \| 0.3989 \| 11.8148 \| 638 \| 0.6843 \| 0.4111 \| 0.6843 \| 0.8272 \| \| 0.3989 \| 11.8519 \| 640 \| 0.6685 \| 0.4915 \| 0.6685 \| 0.8176 \| \| 0.3989 \| 11.8889 \| 642 \| 0.6649 \| 0.4915 \| 0.6649 \| 0.8154 \| \| 0.3989 \| 11.9259 \| 644 \| 0.6607 \| 0.4582 \| 0.6607 \| 0.8128 \| \| 0.3989 \| 11.9630 \| 646 \| 0.6603 \| 0.4367 \| 0.6603 \| 0.8126 \| \| 0.3989 \| 12.0 \| 648 \| 0.6609 \| 0.3799 \| 0.6609 \| 0.8130 \| \| 0.3989 \| 12.0370 \| 650 \| 0.6551 \| 0.3786 \| 0.6551 \| 0.8094 \| \| 0.3989 \| 12.0741 \| 652 \| 0.6515 \| 0.3552 \| 0.6515 \| 0.8072 \| \| 0.3989 \| 12.1111 \| 654 \| 0.6478 \| 0.3962 \| 0.6478 \| 0.8048 \| \| 0.3989 \| 12.1481 \| 656 \| 0.6561 \| 0.3962 \| 0.6561 \| 0.8100 \| \| 0.3989 \| 12.1852 \| 658 \| 0.6658 \| 0.3795 \| 0.6658 \| 0.8159 \| \| 0.3989 \| 12.2222 \| 660 \| 0.6709 \| 0.3794 \| 0.6709 \| 0.8191 \| \| 0.3989 \| 12.2593 \| 662 \| 0.7029 \| 0.4209 \| 0.7029 \| 0.8384 \| \| 0.3989 \| 12.2963 \| 664 \| 0.7678 \| 0.4051 \| 0.7678 \| 0.8763 \| \| 0.3989 \| 12.3333 \| 666 \| 0.7786 \| 0.4165 \| 0.7786 \| 0.8824 \| \| 0.3989 \| 12.3704 \| 668 \| 0.7494 \| 0.4387 \| 0.7494 \| 0.8657 \| \| 0.3989 \| 12.4074 \| 670 \| 0.6842 \| 0.3376 \| 0.6842 \| 0.8272 \| \| 0.3989 \| 12.4444 \| 672 \| 0.6557 \| 0.4136 \| 0.6557 \| 0.8098 \| \| 0.3989 \| 12.4815 \| 674 \| 0.6543 \| 0.4013 \| 0.6543 \| 0.8089 \| \| 0.3989 \| 12.5185 \| 676 \| 0.6561 \| 0.4185 \| 0.6561 \| 0.8100 \| \| 0.3989 \| 12.5556 \| 678 \| 0.6593 \| 0.4337 \| 0.6593 \| 0.8120 \| \| 0.3989 \| 12.5926 \| 680 \| 0.6632 \| 0.3989 \| 0.6632 \| 0.8144 \| \| 0.3989 \| 12.6296 \| 682 \| 0.6686 \| 0.3850 \| 0.6686 \| 0.8177 \| \| 0.3989 \| 12.6667 \| 684 \| 0.6555 \| 0.3717 \| 0.6555 \| 0.8096 \| \| 0.3989 \| 12.7037 \| 686 \| 0.6537 \| 0.3961 \| 0.6537 \| 0.8085 \| \| 0.3989 \| 12.7407 \| 688 \| 0.6672 \| 0.3931 \| 0.6672 \| 0.8168 \| \| 0.3989 \| 12.7778 \| 690 \| 0.6930 \| 0.4439 \| 0.6930 \| 0.8325 \| \| 0.3989 \| 12.8148 \| 692 \| 0.7478 \| 0.4464 \| 0.7478 \| 0.8647 \| \| 0.3989 \| 12.8519 \| 694 \| 0.7656 \| 0.4464 \| 0.7656 \| 0.8750 \| \| 0.3989 \| 12.8889 \| 696 \| 0.7161 \| 0.4330 \| 0.7161 \| 0.8462 \| \| 0.3989 \| 12.9259 \| 698 \| 0.6732 \| 0.4321 \| 0.6732 \| 0.8205 \| \| 0.3989 \| 12.9630 \| 700 \| 0.6765 \| 0.3894 \| 0.6765 \| 0.8225 \| \| 0.3989 \| 13.0 \| 702 \| 0.6678 \| 0.3949 \| 0.6678 \| 0.8172 \| \| 0.3989 \| 13.0370 \| 704 \| 0.6724 \| 0.4450 \| 0.6724 \| 0.8200 \| \| 0.3989 \| 13.0741 \| 706 \| 0.6971 \| 0.4169 \| 0.6971 \| 0.8349 \| \| 0.3989 \| 13.1111 \| 708 \| 0.6941 \| 0.4017 \| 0.6941 \| 0.8331 \| \| 0.3989 \| 13.1481 \| 710 \| 0.6841 \| 0.4369 \| 0.6841 \| 0.8271 \| \| 0.3989 \| 13.1852 \| 712 \| 0.7099 \| 0.4153 \| 0.7099 \| 0.8426 \| \| 0.3989 \| 13.2222 \| 714 \| 0.7661 \| 0.4165 \| 0.7661 \| 0.8753 \| \| 0.3989 \| 13.2593 \| 716 \| 0.7600 \| 0.4194 \| 0.7600 \| 0.8718 \| \| 0.3989 \| 13.2963 \| 718 \| 0.7098 \| 0.4773 \| 0.7098 \| 0.8425 \| \| 0.3989 \| 13.3333 \| 720 \| 0.6987 \| 0.4060 \| 0.6987 \| 0.8359 \| \| 0.3989 \| 13.3704 \| 722 \| 0.7065 \| 0.3861 \| 0.7065 \| 0.8405 \| \| 0.3989 \| 13.4074 \| 724 \| 0.6807 \| 0.3993 \| 0.6807 \| 0.8250 \| \| 0.3989 \| 13.4444 \| 726 \| 0.6681 \| 0.3951 \| 0.6681 \| 0.8174 \| \| 0.3989 \| 13.4815 \| 728 \| 0.6905 \| 0.4164 \| 0.6905 \| 0.8309 \| \| 0.3989 \| 13.5185 \| 730 \| 0.6999 \| 0.4100 \| 0.6999 \| 0.8366 \| \| 0.3989 \| 13.5556 \| 732 \| 0.6771 \| 0.3959 \| 0.6771 \| 0.8228 \| \| 0.3989 \| 13.5926 \| 734 \| 0.6639 \| 0.3849 \| 0.6639 \| 0.8148 \| \| 0.3989 \| 13.6296 \| 736 \| 0.6664 \| 0.4125 \| 0.6664 \| 0.8163 \| \| 0.3989 \| 13.6667 \| 738 \| 0.6685 \| 0.4125 \| 0.6685 \| 0.8176 \| \| 0.3989 \| 13.7037 \| 740 \| 0.6685 \| 0.4514 \| 0.6685 \| 0.8176 \| \| 0.3989 \| 13.7407 \| 742 \| 0.6763 \| 0.3486 \| 0.6763 \| 0.8224 \| \| 0.3989 \| 13.7778 \| 744 \| 0.6774 \| 0.3447 \| 0.6774 \| 0.8230 \| \| 0.3989 \| 13.8148 \| 746 \| 0.6772 \| 0.4196 \| 0.6772 \| 0.8229 \| \| 0.3989 \| 13.8519 \| 748 \| 0.7201 \| 0.3721 \| 0.7201 \| 0.8486 \| \| 0.3989 \| 13.8889 \| 750 \| 0.7478 \| 0.3967 \| 0.7478 \| 0.8647 \| \| 0.3989 \| 13.9259 \| 752 \| 0.7129 \| 0.3842 \| 0.7129 \| 0.8443 \| \| 0.3989 \| 13.9630 \| 754 \| 0.6736 \| 0.3720 \| 0.6736 \| 0.8207 \| \| 0.3989 \| 14.0 \| 756 \| 0.6597 \| 0.3260 \| 0.6597 \| 0.8122 \| \| 0.3989 \| 14.0370 \| 758 \| 0.6661 \| 0.3535 \| 0.6661 \| 0.8161 \| \| 0.3989 \| 14.0741 \| 760 \| 0.6634 \| 0.3261 \| 0.6634 \| 0.8145 \| \| 0.3989 \| 14.1111 \| 762 \| 0.6619 \| 0.3932 \| 0.6619 \| 0.8135 \| \| 0.3989 \| 14.1481 \| 764 \| 0.7034 \| 0.3979 \| 0.7034 \| 0.8387 \| \| 0.3989 \| 14.1852 \| 766 \| 0.7503 \| 0.4186 \| 0.7503 \| 0.8662 \| \| 0.3989 \| 14.2222 \| 768 \| 0.7448 \| 0.4291 \| 0.7448 \| 0.8630 \| \| 0.3989 \| 14.2593 \| 770 \| 0.7038 \| 0.3582 \| 0.7038 \| 0.8390 \| \| 0.3989 \| 14.2963 \| 772 \| 0.6633 \| 0.3481 \| 0.6633 \| 0.8145 \| \| 0.3989 \| 14.3333 \| 774 \| 0.6669 \| 0.3535 \| 0.6669 \| 0.8166 \| \| 0.3989 \| 14.3704 \| 776 \| 0.6649 \| 0.3427 \| 0.6649 \| 0.8154 \| \| 0.3989 \| 14.4074 \| 778 \| 0.6675 \| 0.3868 \| 0.6675 \| 0.8170 \| \| 0.3989 \| 14.4444 \| 780 \| 0.6906 \| 0.3825 \| 0.6906 \| 0.8310 \| \| 0.3989 \| 14.4815 \| 782 \| 0.6904 \| 0.3923 \| 0.6904 \| 0.8309 \| \| 0.3989 \| 14.5185 \| 784 \| 0.6962 \| 0.4358 \| 0.6962 \| 0.8344 \| \| 0.3989 \| 14.5556 \| 786 \| 0.6914 \| 0.4262 \| 0.6914 \| 0.8315 \| \| 0.3989 \| 14.5926 \| 788 \| 0.6870 \| 0.4385 \| 0.6870 \| 0.8288 \| \| 0.3989 \| 14.6296 \| 790 \| 0.6940 \| 0.4323 \| 0.6940 \| 0.8331 \| \| 0.3989 \| 14.6667 \| 792 \| 0.6840 \| 0.4330 \| 0.6840 \| 0.8270 \| \| 0.3989 \| 14.7037 \| 794 \| 0.6704 \| 0.3710 \| 0.6704 \| 0.8188 \| \| 0.3989 \| 14.7407 \| 796 \| 0.6604 \| 0.4066 \| 0.6604 \| 0.8127 \| \| 0.3989 \| 14.7778 \| 798 \| 0.6668 \| 0.3904 \| 0.6668 \| 0.8166 \| \| 0.3989 \| 14.8148 \| 800 \| 0.6755 \| 0.4607 \| 0.6755 \| 0.8219 \| \| 0.3989 \| 14.8519 \| 802 \| 0.6829 \| 0.4445 \| 0.6829 \| 0.8264 \| \| 0.3989 \| 14.8889 \| 804 \| 0.6616 \| 0.4246 \| 0.6616 \| 0.8134 \| \| 0.3989 \| 14.9259 \| 806 \| 0.6458 \| 0.4192 \| 0.6458 \| 0.8036 \| \| 0.3989 \| 14.9630 \| 808 \| 0.6336 \| 0.4225 \| 0.6336 \| 0.7960 \| \| 0.3989 \| 15.0 \| 810 \| 0.6256 \| 0.4268 \| 0.6256 \| 0.7909 \| \| 0.3989 \| 15.0370 \| 812 \| 0.6270 \| 0.4053 \| 0.6270 \| 0.7919 \| \| 0.3989 \| 15.0741 \| 814 \| 0.6710 \| 0.3810 \| 0.6710 \| 0.8191 \| \| 0.3989 \| 15.1111 \| 816 \| 0.6770 \| 0.3746 \| 0.6770 \| 0.8228 \| \| 0.3989 \| 15.1481 \| 818 \| 0.6395 \| 0.4224 \| 0.6395 \| 0.7997 \| \| 0.3989 \| 15.1852 \| 820 \| 0.6250 \| 0.4482 \| 0.6250 \| 0.7905 \| \| 0.3989 \| 15.2222 \| 822 \| 0.6428 \| 0.4607 \| 0.6428 \| 0.8017 \| \| 0.3989 \| 15.2593 \| 824 \| 0.6432 \| 0.4553 \| 0.6432 \| 0.8020 \| \| 0.3989 \| 15.2963 \| 826 \| 0.6369 \| 0.4203 \| 0.6369 \| 0.7981 \| \| 0.3989 \| 15.3333 \| 828 \| 0.6731 \| 0.4489 \| 0.6731 \| 0.8205 \| \| 0.3989 \| 15.3704 \| 830 \| 0.7253 \| 0.4014 \| 0.7253 \| 0.8517 \| \| 0.3989 \| 15.4074 \| 832 \| 0.7206 \| 0.3982 \| 0.7206 \| 0.8489 \| \| 0.3989 \| 15.4444 \| 834 \| 0.6697 \| 0.4266 \| 0.6697 \| 0.8183 \| \| 0.3989 \| 15.4815 \| 836 \| 0.6468 \| 0.4696 \| 0.6468 \| 0.8042 \| \| 0.3989 \| 15.5185 \| 838 \| 0.6553 \| 0.4499 \| 0.6553 \| 0.8095 \| \| 0.3989 \| 15.5556 \| 840 \| 0.6369 \| 0.4286 \| 0.6369 \| 0.7980 \| \| 0.3989 \| 15.5926 \| 842 \| 0.6288 \| 0.4072 \| 0.6288 \| 0.7930 \| \| 0.3989 \| 15.6296 \| 844 \| 0.6593 \| 0.4202 \| 0.6593 \| 0.8120 \| \| 0.3989 \| 15.6667 \| 846 \| 0.7051 \| 0.4073 \| 0.7051 \| 0.8397 \| \| 0.3989 \| 15.7037 \| 848 \| 0.7109 \| 0.3975 \| 0.7109 \| 0.8432 \| \| 0.3989 \| 15.7407 \| 850 \| 0.6783 \| 0.4004 \| 0.6783 \| 0.8236 \| \| 0.3989 \| 15.7778 \| 852 \| 0.6444 \| 0.4189 \| 0.6444 \| 0.8028 \| \| 0.3989 \| 15.8148 \| 854 \| 0.6317 \| 0.4308 \| 0.6317 \| 0.7948 \| \| 0.3989 \| 15.8519 \| 856 \| 0.6378 \| 0.4386 \| 0.6378 \| 0.7986 \| \| 0.3989 \| 15.8889 \| 858 \| 0.6511 \| 0.4498 \| 0.6511 \| 0.8069 \| \| 0.3989 \| 15.9259 \| 860 \| 0.6488 \| 0.4529 \| 0.6488 \| 0.8055 \| \| 0.3989 \| 15.9630 \| 862 \| 0.6421 \| 0.4538 \| 0.6421 \| 0.8013 \| \| 0.3989 \| 16.0 \| 864 \| 0.6372 \| 0.4544 \| 0.6372 \| 0.7982 \| \| 0.3989 \| 16.0370 \| 866 \| 0.6646 \| 0.4705 \| 0.6646 \| 0.8152 \| \| 0.3989 \| 16.0741 \| 868 \| 0.6611 \| 0.4567 \| 0.6611 \| 0.8131 \| \| 0.3989 \| 16.1111 \| 870 \| 0.6353 \| 0.4394 \| 0.6353 \| 0.7970 \| \| 0.3989 \| 16.1481 \| 872 \| 0.6305 \| 0.4618 \| 0.6305 \| 0.7941 \| \| 0.3989 \| 16.1852 \| 874 \| 0.6310 \| 0.4587 \| 0.6310 \| 0.7943 \| \| 0.3989 \| 16.2222 \| 876 \| 0.6236 \| 0.4335 \| 0.6236 \| 0.7897 \| \| 0.3989 \| 16.2593 \| 878 \| 0.6222 \| 0.4613 \| 0.6222 \| 0.7888 \| \| 0.3989 \| 16.2963 \| 880 \| 0.6210 \| 0.4623 \| 0.6210 \| 0.7880 \| \| 0.3989 \| 16.3333 \| 882 \| 0.6215 \| 0.4505 \| 0.6215 \| 0.7884 \| \| 0.3989 \| 16.3704 \| 884 \| 0.6234 \| 0.4530 \| 0.6234 \| 0.7896 \| \| 0.3989 \| 16.4074 \| 886 \| 0.6229 \| 0.4273 \| 0.6229 \| 0.7892 \| \| 0.3989 \| 16.4444 \| 888 \| 0.6284 \| 0.4365 \| 0.6284 \| 0.7927 \| \| 0.3989 \| 16.4815 \| 890 \| 0.6267 \| 0.4345 \| 0.6267 \| 0.7917 \| \| 0.3989 \| 16.5185 \| 892 \| 0.6296 \| 0.4368 \| 0.6296 \| 0.7935 \| \| 0.3989 \| 16.5556 \| 894 \| 0.6307 \| 0.4368 \| 0.6307 \| 0.7942 \| \| 0.3989 \| 16.5926 \| 896 \| 0.6319 \| 0.4328 \| 0.6319 \| 0.7949 \| \| 0.3989 \| 16.6296 \| 898 \| 0.6265 \| 0.4433 \| 0.6265 \| 0.7915 \| \| 0.3989 \| 16.6667 \| 900 \| 0.6221 \| 0.4341 \| 0.6221 \| 0.7887 \| \| 0.3989 \| 16.7037 \| 902 \| 0.6184 \| 0.4380 \| 0.6184 \| 0.7864 \| \| 0.3989 \| 16.7407 \| 904 \| 0.6211 \| 0.4331 \| 0.6211 \| 0.7881 \| \| 0.3989 \| 16.7778 \| 906 \| 0.6329 \| 0.3923 \| 0.6329 \| 0.7956 \| \| 0.3989 \| 16.8148 \| 908 \| 0.6370 \| 0.3923 \| 0.6370 \| 0.7981 \| \| 0.3989 \| 16.8519 \| 910 \| 0.6440 \| 0.4124 \| 0.6440 \| 0.8025 \| \| 0.3989 \| 16.8889 \| 912 \| 0.6364 \| 0.4415 \| 0.6364 \| 0.7978 \| \| 0.3989 \| 16.9259 \| 914 \| 0.6324 \| 0.4827 \| 0.6324 \| 0.7952 \| \| 0.3989 \| 16.9630 \| 916 \| 0.6367 \| 0.4712 \| 0.6367 \| 0.7980 \| \| 0.3989 \| 17.0 \| 918 \| 0.6374 \| 0.4868 \| 0.6374 \| 0.7984 \| \| 0.3989 \| 17.0370 \| 920 \| 0.6298 \| 0.4433 \| 0.6298 \| 0.7936 \| \| 0.3989 \| 17.0741 \| 922 \| 0.6262 \| 0.4212 \| 0.6262 \| 0.7913 \| \| 0.3989 \| 17.1111 \| 924 \| 0.6226 \| 0.4212 \| 0.6226 \| 0.7891 \| \| 0.3989 \| 17.1481 \| 926 \| 0.6201 \| 0.4569 \| 0.6201 \| 0.7875 \| \| 0.3989 \| 17.1852 \| 928 \| 0.6240 \| 0.4614 \| 0.6240 \| 0.7899 \| \| 0.3989 \| 17.2222 \| 930 \| 0.6161 \| 0.4693 \| 0.6161 \| 0.7849 \| \| 0.3989 \| 17.2593 \| 932 \| 0.6410 \| 0.4292 \| 0.6410 \| 0.8006 \| \| 0.3989 \| 17.2963 \| 934 \| 0.6465 \| 0.4488 \| 0.6465 \| 0.8041 \| \| 0.3989 \| 17.3333 \| 936 \| 0.6256 \| 0.4163 \| 0.6256 \| 0.7909 \| \| 0.3989 \| 17.3704 \| 938 \| 0.6211 \| 0.4322 \| 0.6211 \| 0.7881 \| \| 0.3989 \| 17.4074 \| 940 \| 0.6531 \| 0.4476 \| 0.6531 \| 0.8081 \| \| 0.3989 \| 17.4444 \| 942 \| 0.6888 \| 0.4726 \| 0.6888 \| 0.8299 \| \| 0.3989 \| 17.4815 \| 944 \| 0.6918 \| 0.4726 \| 0.6918 \| 0.8318 \| \| 0.3989 \| 17.5185 \| 946 \| 0.6702 \| 0.4946 \| 0.6702 \| 0.8186 \| \| 0.3989 \| 17.5556 \| 948 \| 0.6504 \| 0.4861 \| 0.6504 \| 0.8065 \| \| 0.3989 \| 17.5926 \| 950 \| 0.6541 \| 0.4818 \| 0.6541 \| 0.8088 \| \| 0.3989 \| 17.6296 \| 952 \| 0.6489 \| 0.4783 \| 0.6489 \| 0.8056 \| \| 0.3989 \| 17.6667 \| 954 \| 0.6567 \| 0.4948 \| 0.6567 \| 0.8104 \| \| 0.3989 \| 17.7037 \| 956 \| 0.6684 \| 0.5438 \| 0.6684 \| 0.8175 \| \| 0.3989 \| 17.7407 \| 958 \| 0.6579 \| 0.4967 \| 0.6579 \| 0.8111 \| \| 0.3989 \| 17.7778 \| 960 \| 0.6376 \| 0.4900 \| 0.6376 \| 0.7985 \| \| 0.3989 \| 17.8148 \| 962 \| 0.6296 \| 0.4788 \| 0.6296 \| 0.7935 \| \| 0.3989 \| 17.8519 \| 964 \| 0.6319 \| 0.4193 \| 0.6319 \| 0.7949 \| \| 0.3989 \| 17.8889 \| 966 \| 0.6270 \| 0.4440 \| 0.6270 \| 0.7918 \| \| 0.3989 \| 17.9259 \| 968 \| 0.6294 \| 0.4592 \| 0.6294 \| 0.7934 \| \| 0.3989 \| 17.9630 \| 970 \| 0.6303 \| 0.4614 \| 0.6303 \| 0.7939 \| \| 0.3989 \| 18.0 \| 972 \| 0.6321 \| 0.4614 \| 0.6321 \| 0.7951 \| \| 0.3989 \| 18.0370 \| 974 \| 0.6270 \| 0.4474 \| 0.6270 \| 0.7918 \| \| 0.3989 \| 18.0741 \| 976 \| 0.6202 \| 0.4815 \| 0.6202 \| 0.7875 \| \| 0.3989 \| 18.1111 \| 978 \| 0.6292 \| 0.5075 \| 0.6292 \| 0.7932 \| \| 0.3989 \| 18.1481 \| 980 \| 0.6572 \| 0.4963 \| 0.6572 \| 0.8107 \| \| 0.3989 \| 18.1852 \| 982 \| 0.6353 \| 0.4780 \| 0.6353 \| 0.7971 \| \| 0.3989 \| 18.2222 \| 984 \| 0.6217 \| 0.4474 \| 0.6217 \| 0.7885 \| \| 0.3989 \| 18.2593 \| 986 \| 0.6191 \| 0.4556 \| 0.6191 \| 0.7868 \| \| 0.3989 \| 18.2963 \| 988 \| 0.6139 \| 0.4196 \| 0.6139 \| 0.7835 \| \| 0.3989 \| 18.3333 \| 990 \| 0.6329 \| 0.4905 \| 0.6329 \| 0.7956 \| \| 0.3989 \| 18.3704 \| 992 \| 0.6486 \| 0.5086 \| 0.6486 \| 0.8053 \| \| 0.3989 \| 18.4074 \| 994 \| 0.6243 \| 0.4934 \| 0.6243 \| 0.7901 \| \| 0.3989 \| 18.4444 \| 996 \| 0.6024 \| 0.4497 \| 0.6024 \| 0.7761 \| \| 0.3989 \| 18.4815 \| 998 \| 0.6024 \| 0.4433 \| 0.6024 \| 0.7761 \| \| 0.0722 \| 18.5185 \| 1000 \| 0.6044 \| 0.4539 \| 0.6044 \| 0.7774 \| \| 0.0722 \| 18.5556 \| 1002 \| 0.6345 \| 0.4999 \| 0.6345 \| 0.7966 \| \| 0.0722 \| 18.5926 \| 1004 \| 0.6415 \| 0.4876 \| 0.6415 \| 0.8009 \| \| 0.0722 \| 18.6296 \| 1006 \| 0.6148 \| 0.4063 \| 0.6148 \| 0.7841 \| \| 0.0722 \| 18.6667 \| 1008 \| 0.6138 \| 0.4063 \| 0.6138 \| 0.7835 \| \| 0.0722 \| 18.7037 \| 1010 \| 0.6392 \| 0.4840 \| 0.6392 \| 0.7995 \| \| 0.0722 \| 18.7407 \| 1012 \| 0.6662 \| 0.4804 \| 0.6662 \| 0.8162 \| \| 0.0722 \| 18.7778 \| 1014 \| 0.6590 \| 0.4739 \| 0.6590 \| 0.8118 \| \| 0.0722 \| 18.8148 \| 1016 \| 0.6394 \| 0.4921 \| 0.6394 \| 0.7996 \| \| 0.0722 \| 18.8519 \| 1018 \| 0.6215 \| 0.4457 \| 0.6215 \| 0.7884 \| \| 0.0722 \| 18.8889 \| 1020 \| 0.6133 \| 0.4446 \| 0.6133 \| 0.7832 \| \| 0.0722 \| 18.9259 \| 1022 \| 0.6121 \| 0.4354 \| 0.6121 \| 0.7824 \| \| 0.0722 \| 18.9630 \| 1024 \| 0.6167 \| 0.4623 \| 0.6167 \| 0.7853 \| \| 0.0722 \| 19.0 \| 1026 \| 0.6212 \| 0.4352 \| 0.6212 \| 0.7882 \| \| 0.0722 \| 19.0370 \| 1028 \| 0.6566 \| 0.3747 \| 0.6566 \| 0.8103 \| \| 0.0722 \| 19.0741 \| 1030 \| 0.7234 \| 0.4190 \| 0.7234 \| 0.8505 \| \| 0.0722 \| 19.1111 \| 1032 \| 0.7400 \| 0.4149 \| 0.7400 \| 0.8602 \| \| 0.0722 \| 19.1481 \| 1034 \| 0.6956 \| 0.4065 \| 0.6956 \| 0.8340 \| ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1
Kuongan/CS221-mdeberta-v3-base-randomdrop	Kuongan	2025-01-15T14:56:47Z	24	0	transformers	[ "transformers", "safetensors", "deberta-v2", "text-classification", "generated_from_trainer", "base_model:microsoft/mdeberta-v3-base", "base_model:finetune:microsoft/mdeberta-v3-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T14:08:24Z	--- library_name: transformers license: mit base_model: microsoft/mdeberta-v3-base tags: - generated_from_trainer metrics: - f1 - accuracy model-index: - name: CS221-mdeberta-v3-base-randomdrop results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # CS221-mdeberta-v3-base-randomdrop This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5440 - F1: 0.6741 - Roc Auc: 0.7756 - Accuracy: 0.4071 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 20 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| F1 \| Roc Auc \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:-------:\|:--------:\| \| 0.5661 \| 1.0 \| 99 \| 0.5434 \| 0.0 \| 0.5 \| 0.1425 \| \| 0.5054 \| 2.0 \| 198 \| 0.4744 \| 0.4852 \| 0.6560 \| 0.2621 \| \| 0.4409 \| 3.0 \| 297 \| 0.4436 \| 0.5766 \| 0.7104 \| 0.3308 \| \| 0.3975 \| 4.0 \| 396 \| 0.4284 \| 0.6071 \| 0.7316 \| 0.3588 \| \| 0.2827 \| 5.0 \| 495 \| 0.4228 \| 0.6095 \| 0.7296 \| 0.3562 \| \| 0.2831 \| 6.0 \| 594 \| 0.4540 \| 0.6467 \| 0.7642 \| 0.3715 \| \| 0.1846 \| 7.0 \| 693 \| 0.4519 \| 0.6325 \| 0.7459 \| 0.3893 \| \| 0.1752 \| 8.0 \| 792 \| 0.4538 \| 0.6426 \| 0.7535 \| 0.3740 \| \| 0.1547 \| 9.0 \| 891 \| 0.4799 \| 0.6541 \| 0.7642 \| 0.3791 \| \| 0.1046 \| 10.0 \| 990 \| 0.4793 \| 0.6667 \| 0.7687 \| 0.4020 \| \| 0.1052 \| 11.0 \| 1089 \| 0.5001 \| 0.6593 \| 0.7658 \| 0.4046 \| \| 0.0843 \| 12.0 \| 1188 \| 0.5069 \| 0.6647 \| 0.7705 \| 0.3893 \| \| 0.0653 \| 13.0 \| 1287 \| 0.5275 \| 0.6681 \| 0.7669 \| 0.4097 \| \| 0.0575 \| 14.0 \| 1386 \| 0.5455 \| 0.6617 \| 0.7632 \| 0.3944 \| \| 0.0503 \| 15.0 \| 1485 \| 0.5440 \| 0.6741 \| 0.7756 \| 0.4071 \| \| 0.0499 \| 16.0 \| 1584 \| 0.5555 \| 0.6653 \| 0.7660 \| 0.4097 \| \| 0.0431 \| 17.0 \| 1683 \| 0.5557 \| 0.6660 \| 0.7675 \| 0.4020 \| \| 0.0422 \| 18.0 \| 1782 \| 0.5599 \| 0.6632 \| 0.7664 \| 0.3944 \| ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
rsicproject/mnasnet-GPT-UCM-captioning	rsicproject	2025-01-15T14:55:57Z	39	0	transformers	[ "transformers", "tensorboard", "safetensors", "vision-encoder-decoder", "generated_from_trainer", "endpoints_compatible", "region:us" ]	null	2025-01-15T14:54:18Z	--- library_name: transformers tags: - generated_from_trainer metrics: - rouge model-index: - name: mnasnet-GPT-UCM-captioning results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # mnasnet-GPT-UCM-captioning This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1599 - Rouge: 0.7565 - Bleu1: 0.8056 - Bleu2: 0.7427 - Bleu3: 0.6876 - Bleu4: 0.6411 - Meteor: 0.7599 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1024 - num_epochs: 128 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge \| Bleu1 \| Bleu2 \| Bleu3 \| Bleu4 \| Meteor \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\|:------:\|:------:\|:------:\|:------:\| \| No log \| 1.0 \| 132 \| 1.9151 \| 0.4839 \| 0.5481 \| 0.4544 \| 0.3734 \| 0.3128 \| 0.4642 \| \| No log \| 2.0 \| 264 \| 1.5925 \| 0.5534 \| 0.5757 \| 0.4913 \| 0.4205 \| 0.3644 \| 0.5538 \| \| No log \| 3.0 \| 396 \| 1.3495 \| 0.5927 \| 0.6183 \| 0.5338 \| 0.4640 \| 0.4116 \| 0.5908 \| \| No log \| 4.0 \| 528 \| 1.2230 \| 0.5476 \| 0.6251 \| 0.5351 \| 0.4665 \| 0.4141 \| 0.5342 \| \| No log \| 5.0 \| 660 \| 1.0534 \| 0.6380 \| 0.6833 \| 0.6038 \| 0.5417 \| 0.4909 \| 0.6387 \| \| No log \| 6.0 \| 792 \| 1.1554 \| 0.6127 \| 0.6740 \| 0.5783 \| 0.5065 \| 0.4487 \| 0.5980 \| \| No log \| 7.0 \| 924 \| 1.0466 \| 0.5886 \| 0.6646 \| 0.5867 \| 0.5250 \| 0.4784 \| 0.5726 \| \| 0.8231 \| 8.0 \| 1056 \| 1.0427 \| 0.6528 \| 0.7305 \| 0.6468 \| 0.5849 \| 0.5415 \| 0.6299 \| \| 0.8231 \| 9.0 \| 1188 \| 0.9752 \| 0.6546 \| 0.7104 \| 0.6276 \| 0.5647 \| 0.5149 \| 0.6534 \| \| 0.8231 \| 10.0 \| 1320 \| 0.9692 \| 0.6850 \| 0.7409 \| 0.6665 \| 0.6060 \| 0.5589 \| 0.7002 \| \| 0.8231 \| 11.0 \| 1452 \| 1.0092 \| 0.6708 \| 0.7441 \| 0.6592 \| 0.5922 \| 0.5382 \| 0.6744 \| \| 0.8231 \| 12.0 \| 1584 \| 0.9588 \| 0.7100 \| 0.7872 \| 0.7174 \| 0.6573 \| 0.6057 \| 0.7064 \| \| 0.8231 \| 13.0 \| 1716 \| 1.0117 \| 0.6975 \| 0.7612 \| 0.6820 \| 0.6170 \| 0.5607 \| 0.6904 \| \| 0.8231 \| 14.0 \| 1848 \| 0.9922 \| 0.7642 \| 0.8057 \| 0.7403 \| 0.6830 \| 0.6321 \| 0.7646 \| \| 0.8231 \| 15.0 \| 1980 \| 1.0432 \| 0.7051 \| 0.7689 \| 0.6954 \| 0.6346 \| 0.5875 \| 0.6945 \| \| 0.2276 \| 16.0 \| 2112 \| 1.0168 \| 0.7263 \| 0.7839 \| 0.7197 \| 0.6627 \| 0.6130 \| 0.7216 \| \| 0.2276 \| 17.0 \| 2244 \| 0.9891 \| 0.7684 \| 0.8315 \| 0.7710 \| 0.7150 \| 0.6689 \| 0.7671 \| \| 0.2276 \| 18.0 \| 2376 \| 0.9994 \| 0.7563 \| 0.8113 \| 0.7474 \| 0.6967 \| 0.6514 \| 0.7514 \| \| 0.2276 \| 19.0 \| 2508 \| 1.0163 \| 0.7709 \| 0.8105 \| 0.7480 \| 0.6924 \| 0.6433 \| 0.7779 \| \| 0.2276 \| 20.0 \| 2640 \| 1.0252 \| 0.7643 \| 0.8030 \| 0.7419 \| 0.6868 \| 0.6379 \| 0.7782 \| \| 0.2276 \| 21.0 \| 2772 \| 1.0315 \| 0.7764 \| 0.8350 \| 0.7695 \| 0.7125 \| 0.6612 \| 0.7814 \| \| 0.2276 \| 22.0 \| 2904 \| 1.0395 \| 0.7695 \| 0.8167 \| 0.7632 \| 0.7180 \| 0.6781 \| 0.7768 \| \| 0.2276 \| 23.0 \| 3036 \| 1.0521 \| 0.7353 \| 0.7927 \| 0.7278 \| 0.6731 \| 0.6262 \| 0.7424 \| \| 0.1659 \| 24.0 \| 3168 \| 1.0567 \| 0.7760 \| 0.8122 \| 0.7512 \| 0.7009 \| 0.6583 \| 0.7793 \| \| 0.1659 \| 25.0 \| 3300 \| 1.0346 \| 0.7586 \| 0.8060 \| 0.7456 \| 0.6933 \| 0.6520 \| 0.7633 \| \| 0.1659 \| 26.0 \| 3432 \| 1.0450 \| 0.7731 \| 0.8191 \| 0.7544 \| 0.7031 \| 0.6597 \| 0.7738 \| \| 0.1659 \| 27.0 \| 3564 \| 1.0612 \| 0.7768 \| 0.8142 \| 0.7523 \| 0.6951 \| 0.6423 \| 0.7883 \| \| 0.1659 \| 28.0 \| 3696 \| 1.0530 \| 0.7643 \| 0.8098 \| 0.7543 \| 0.7066 \| 0.6671 \| 0.7639 \| \| 0.1659 \| 29.0 \| 3828 \| 1.0286 \| 0.7877 \| 0.8337 \| 0.7801 \| 0.7344 \| 0.6944 \| 0.7977 \| \| 0.1659 \| 30.0 \| 3960 \| 1.0435 \| 0.7741 \| 0.8154 \| 0.7506 \| 0.6967 \| 0.6483 \| 0.7790 \| \| 0.1659 \| 31.0 \| 4092 \| 1.0730 \| 0.7393 \| 0.7980 \| 0.7362 \| 0.6846 \| 0.6403 \| 0.7382 \| \| 0.1503 \| 32.0 \| 4224 \| 1.0879 \| 0.7519 \| 0.7933 \| 0.7289 \| 0.6759 \| 0.6291 \| 0.7550 \| \| 0.1503 \| 33.0 \| 4356 \| 1.0987 \| 0.7719 \| 0.8107 \| 0.7470 \| 0.6948 \| 0.6498 \| 0.7759 \| \| 0.1503 \| 34.0 \| 4488 \| 1.0784 \| 0.7725 \| 0.8143 \| 0.7475 \| 0.6920 \| 0.6443 \| 0.7743 \| \| 0.1503 \| 35.0 \| 4620 \| 1.0775 \| 0.7863 \| 0.8176 \| 0.7646 \| 0.7201 \| 0.6807 \| 0.7955 \| \| 0.1503 \| 36.0 \| 4752 \| 1.1081 \| 0.7746 \| 0.8070 \| 0.7499 \| 0.7004 \| 0.6576 \| 0.7832 \| \| 0.1503 \| 37.0 \| 4884 \| 1.1177 \| 0.7682 \| 0.8246 \| 0.7658 \| 0.7128 \| 0.6665 \| 0.7746 \| \| 0.1503 \| 38.0 \| 5016 \| 1.1341 \| 0.7608 \| 0.8068 \| 0.7442 \| 0.6927 \| 0.6477 \| 0.7603 \| \| 0.1427 \| 39.0 \| 5148 \| 1.1599 \| 0.7565 \| 0.8056 \| 0.7427 \| 0.6876 \| 0.6411 \| 0.7599 \| ### Framework versions - Transformers 4.45.2 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.20.3
SenhorDasMoscas/acho-classification-15-01-2025	SenhorDasMoscas	2025-01-15T14:54:48Z	38	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-01-15T14:53:48Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a	kk-aivio	2025-01-15T14:53:21Z	8	0	peft	[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:echarlaix/tiny-random-mistral", "base_model:adapter:echarlaix/tiny-random-mistral", "license:apache-2.0", "region:us" ]	null	2025-01-15T14:51:47Z	--- library_name: peft license: apache-2.0 base_model: echarlaix/tiny-random-mistral tags: - axolotl - generated_from_trainer model-index: - name: 4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: echarlaix/tiny-random-mistral bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 960a93b2c47c666b_train_data.json ds_type: json format: custom path: /workspace/input_data/960a93b2c47c666b_train_data.json type: field_instruction: prompt field_output: model_completion format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/960a93b2c47c666b_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b43660c7-01f6-4d83-9a12-686ad5ff81c2 wandb_project: birthday-sn56-17-Gradients-On-Demand wandb_run: your_name wandb_runid: b43660c7-01f6-4d83-9a12-686ad5ff81c2 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details><br> # 4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a This model is a fine-tuned version of [echarlaix/tiny-random-mistral](https://huggingface.co/echarlaix/tiny-random-mistral) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:------:\|:----:\|:---------------:\| \| 0.0 \| 0.0001 \| 1 \| nan \| \| 0.0 \| 0.0002 \| 3 \| nan \| \| 0.0 \| 0.0004 \| 6 \| nan \| \| 0.0 \| 0.0006 \| 9 \| nan \| ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso10/dbaf1184-5899-4d20-964a-33ecb54ce416

lesso10

2025-01-15T16:22:26Z

14

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "custom_code", "base_model:NovaSearch/stella_en_1.5B_v5", "base_model:adapter:NovaSearch/stella_en_1.5B_v5", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T16:12:57Z

--- library_name: peft license: mit base_model: dunzhang/stella_en_1.5B_v5 tags: - axolotl - generated_from_trainer model-index: - name: dbaf1184-5899-4d20-964a-33ecb54ce416 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: dunzhang/stella_en_1.5B_v5 bf16: true chat_template: llama3 datasets: - data_files: - c17c59740c4fc07c_train_data.json ds_type: json format: custom path: /workspace/input_data/c17c59740c4fc07c_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso10/dbaf1184-5899-4d20-964a-33ecb54ce416 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/c17c59740c4fc07c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21989a9f-7539-4956-94ad-ee9bd5631eb8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21989a9f-7539-4956-94ad-ee9bd5631eb8 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # dbaf1184-5899-4d20-964a-33ecb54ce416 This model is a fine-tuned version of [dunzhang/stella_en_1.5B_v5](https://huggingface.co/dunzhang/stella_en_1.5B_v5) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0003 | 1 | nan | | 0.0 | 0.0017 | 5 | nan | | 0.0 | 0.0034 | 10 | nan | | 0.0 | 0.0051 | 15 | nan | | 0.0 | 0.0068 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

JacksonBrune/9d3840b2-d488-4fbf-97e3-b030d9e3517c

JacksonBrune

2025-01-15T16:19:37Z

9

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "region:us" ]

null

2025-01-15T15:50:19Z

--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: 9d3840b2-d488-4fbf-97e3-b030d9e3517c results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: JacksonBrune/9d3840b2-d488-4fbf-97e3-b030d9e3517c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|eot_id|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: birthdya-sn56-18-Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 9d3840b2-d488-4fbf-97e3-b030d9e3517c This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8708 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.145 | 0.0001 | 1 | 2.5498 | | 2.7497 | 0.0002 | 3 | 2.5405 | | 1.9838 | 0.0003 | 6 | 2.3407 | | 2.057 | 0.0005 | 9 | 1.8708 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

antonvinny/whisper-tiny-gs

antonvinny

2025-01-15T16:18:37Z

32

0

transformers

[ "transformers", "tensorboard", "onnx", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "en", "base_model:openai/whisper-small", "base_model:quantized:openai/whisper-small", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2025-01-15T15:02:21Z

--- library_name: transformers language: - en license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer metrics: - wer model-index: - name: whisper-tiny-gs results: [] ---  # whisper-tiny-gs This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0001 - Wer: 2.4950 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 3e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - training_steps: 600 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:--------:|:----:|:---------------:|:------:| | 0.0002 | 66.6667 | 200 | 0.0003 | 2.4950 | | 0.0001 | 133.3333 | 400 | 0.0001 | 2.4950 | | 0.0001 | 200.0 | 600 | 0.0001 | 2.4950 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0

dimasik2987/77bfbadf-495d-408a-be33-a01f7dedab05

dimasik2987

2025-01-15T16:17:23Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "custom_code", "base_model:NovaSearch/stella_en_1.5B_v5", "base_model:adapter:NovaSearch/stella_en_1.5B_v5", "license:mit", "region:us" ]

null

2025-01-15T16:13:05Z

--- library_name: peft license: mit base_model: dunzhang/stella_en_1.5B_v5 tags: - axolotl - generated_from_trainer model-index: - name: 77bfbadf-495d-408a-be33-a01f7dedab05 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: dunzhang/stella_en_1.5B_v5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - c17c59740c4fc07c_train_data.json ds_type: json format: custom path: /workspace/input_data/c17c59740c4fc07c_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik2987/77bfbadf-495d-408a-be33-a01f7dedab05 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/c17c59740c4fc07c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21989a9f-7539-4956-94ad-ee9bd5631eb8 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21989a9f-7539-4956-94ad-ee9bd5631eb8 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 77bfbadf-495d-408a-be33-a01f7dedab05 This model is a fine-tuned version of [dunzhang/stella_en_1.5B_v5](https://huggingface.co/dunzhang/stella_en_1.5B_v5) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0003 | 1 | nan | | 0.0 | 0.0017 | 5 | nan | | 0.0 | 0.0034 | 10 | nan | | 0.0 | 0.0051 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Error410/JVCGPT-Mini-beta-GGUF

Error410

2025-01-15T16:17:14Z

34

0

null

[ "gguf", "jvc", "issou", "aya", "fr", "dataset:Error410/sharegpt", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:quantized:meta-llama/Llama-3.2-3B-Instruct", "endpoints_compatible", "region:us" ]

null

2025-01-12T02:14:23Z

--- datasets: - Error410/sharegpt language: - fr base_model: - meta-llama/Llama-3.2-3B-Instruct tags: - jvc - issou - aya --- # Error410/JVCGPT-Mini-beta ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/R0ZRrgMITvprcoXajAnPi.png) ## Description Ce modèle est une version fine-tunée de **Llama 3.2 3B** ayant pour objectif de reproduire les styles d’écriture et les posts des utilisateurs du forum **jeuxvideo.com**. Entraîné sur une fraction des données publiques de **JVArchive**, ce modèle est conçu pour capturer le ton, l’humour et les références propres à cette communauté en ligne. ## Détails du modèle - **Base** : Llama 3.2 (3B paramètres) - **Dataset utilisé** : 2% de JVArchive (public et accessible librement) - **Entraînement** : 3 heures pour 2 epoch sur un cluster de 8 NVIDIA L40S sur un contexte de 4096 tokens. - **Objectif** : Générer des messages imitant le style des utilisateurs de jeuxvideo.com - **Accès** : Dataset et modèles disponibles gratuitement sur notre repo [Error410](https://huggingface.co/Error410/). ## Format du prompt ``` <|begin_of_text|><|start_header_id|>system<|end_header_id|> Réponds comme un membre actif du forum, en respectant le style, les références et le ton typiques du topic en cours. Topic: <TOPIC>|eot_id|><|start_header_id|>user<|end_header_id|> <|im_pseudo|>PSEUDO<|end_pseudo|> <|im_date|>DATE<|end_date|> <|begin_of_post|>POST<|end_of_post|><|eot_id|><|start_header_id|>assistant<|end_header_id|> <|im_pseudo|>PSEUDO<|end_pseudo|> <|im_date|>DATE<|end_date|> <|begin_of_post|>POST<|end_of_post|><|eot_id|> ``` Template SillyTavern: https://huggingface.co/Error410/JVCGPT-Mini-beta/blob/main/SillyTavern%20Prompt%20Format.json ## Performances - **Style** : Captures efficacement les références, expressions, et styles d’écriture caractéristiques des forums jeuxvideo.com. - **Légèreté** : Adapté pour tout grâce à sa petit taille de 3B de paramètres. - **Temps de réponse** : Optimisé pour des générations rapides à faible coût. ## Dataset Le modèle a été entraîné sur une sélection de **2% des archives de JVArchive** (100 000 topics). Ces données ont été traitées et filtrées pour garantir une qualité et une diversité optimales. ## Licence Le modèle, le dataset, et tous les fichiers associés sont mis à disposition gratuitement sous la même license (PUBLIC) que JVArchive, dans notre repo. ## Remerciements Un grand merci à **JVArchive** pour l’accès aux données publiques et à la communauté jeuxvideo.com pour son inspiration. Ce projet est dédié aux passionnés de l’histoire du forum et à la culture internet. ## Auteurs - [Greums](https://huggingface.co/Greums/) : Pro des datasets bordelent cimer chef - [Undi](https://huggingface.co/Undi95/)

Error410/JVCGPT-Mini-beta

Error410

2025-01-15T16:16:22Z

17

0

null

[ "safetensors", "llama", "jvc", "issou", "aya", "fr", "dataset:Error410/sharegpt", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:finetune:meta-llama/Llama-3.2-3B-Instruct", "region:us" ]

null

2025-01-12T01:45:03Z

--- datasets: - Error410/sharegpt language: - fr base_model: - meta-llama/Llama-3.2-3B-Instruct tags: - jvc - issou - aya --- # Error410/JVCGPT-Mini-beta ![image/png](https://cdn-uploads.huggingface.co/production/uploads/63ab1241ad514ca8d1430003/R0ZRrgMITvprcoXajAnPi.png) ## Description Ce modèle est une version fine-tunée de **Llama 3.2 3B** ayant pour objectif de reproduire les styles d’écriture et les posts des utilisateurs du forum **jeuxvideo.com**. Entraîné sur une fraction des données publiques de **JVArchive**, ce modèle est conçu pour capturer le ton, l’humour et les références propres à cette communauté en ligne. ## Détails du modèle - **Base** : Llama 3.2 (3B paramètres) - **Dataset utilisé** : 2% de JVArchive (public et accessible librement) - **Entraînement** : 3 heures pour 2 epoch sur un cluster de 8 NVIDIA L40S sur un contexte de 4096 tokens. - **Objectif** : Générer des messages imitant le style des utilisateurs de jeuxvideo.com - **Accès** : Dataset et modèles disponibles gratuitement sur notre repo [Error410](https://huggingface.co/Error410/). ## Format du prompt ``` <|begin_of_text|><|start_header_id|>system<|end_header_id|> Réponds comme un membre actif du forum, en respectant le style, les références et le ton typiques du topic en cours. Topic: <TOPIC>|eot_id|><|start_header_id|>user<|end_header_id|> <|im_pseudo|>PSEUDO<|end_pseudo|> <|im_date|>DATE<|end_date|> <|begin_of_post|>POST<|end_of_post|><|eot_id|><|start_header_id|>assistant<|end_header_id|> <|im_pseudo|>PSEUDO<|end_pseudo|> <|im_date|>DATE<|end_date|> <|begin_of_post|>POST<|end_of_post|><|eot_id|> ``` Template SillyTavern: https://huggingface.co/Error410/JVCGPT-Mini-beta/blob/main/SillyTavern%20Prompt%20Format.json ## Performances - **Style** : Captures efficacement les références, expressions, et styles d’écriture caractéristiques des forums jeuxvideo.com. - **Légèreté** : Adapté pour tout grâce à sa petit taille de 3B de paramètres. - **Temps de réponse** : Optimisé pour des générations rapides à faible coût. ## Dataset Le modèle a été entraîné sur une sélection de **2% des archives de JVArchive** (100 000 topics). Ces données ont été traitées et filtrées pour garantir une qualité et une diversité optimales. ## Licence Le modèle, le dataset, et tous les fichiers associés sont mis à disposition gratuitement sous la même license (PUBLIC) que JVArchive, dans notre repo. ## Remerciements Un grand merci à **JVArchive** pour l’accès aux données publiques et à la communauté jeuxvideo.com pour son inspiration. Ce projet est dédié aux passionnés de l’histoire du forum et à la culture internet. ## Auteurs - [Greums](https://huggingface.co/Greums/) : Pro des datasets bordelent cimer chef - [Undi](https://huggingface.co/Undi95/)

lesso13/6d237b86-7931-4795-b258-7cf41ed07b45

lesso13

2025-01-15T16:16:06Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-1.5B-Instruct", "base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:49:16Z

--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 6d237b86-7931-4795-b258-7cf41ed07b45 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-1.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 756452db934ae1d1_train_data.json ds_type: json format: custom path: /workspace/input_data/756452db934ae1d1_train_data.json type: field_instruction: question field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso13/6d237b86-7931-4795-b258-7cf41ed07b45 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/756452db934ae1d1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_hf output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 74979543-06fb-451f-b2f1-4786823d5776 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 74979543-06fb-451f-b2f1-4786823d5776 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 6d237b86-7931-4795-b258-7cf41ed07b45 This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9857 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 1.0872 | | 1.1047 | 0.0008 | 8 | 1.0565 | | 1.0449 | 0.0016 | 16 | 1.0030 | | 1.04 | 0.0023 | 24 | 0.9857 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

bbytxt/99b7be35-ecb0-4251-93fd-0b9840307a9c

bbytxt

2025-01-15T16:16:03Z

7

0

peft

[ "peft", "safetensors", "phi", "axolotl", "generated_from_trainer", "base_model:echarlaix/tiny-random-PhiForCausalLM", "base_model:adapter:echarlaix/tiny-random-PhiForCausalLM", "license:apache-2.0", "region:us" ]

null

2025-01-15T16:15:04Z

--- library_name: peft license: apache-2.0 base_model: echarlaix/tiny-random-PhiForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 99b7be35-ecb0-4251-93fd-0b9840307a9c results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: echarlaix/tiny-random-PhiForCausalLM bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - a036efca81d0f95e_train_data.json ds_type: json format: custom path: /workspace/input_data/a036efca81d0f95e_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/99b7be35-ecb0-4251-93fd-0b9840307a9c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/a036efca81d0f95e_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 special_tokens: pad_token: <|endoftext|> strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21b208df-454c-48c3-9b23-520ad94bb3d4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21b208df-454c-48c3-9b23-520ad94bb3d4 warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details> # 99b7be35-ecb0-4251-93fd-0b9840307a9c This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 6.7069 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 6.9344 | 0.0019 | 1 | 6.9199 | | 6.6524 | 0.0970 | 50 | 6.7949 | | 6.5216 | 0.1941 | 100 | 6.7281 | | 6.4882 | 0.2911 | 150 | 6.7088 | | 6.4793 | 0.3882 | 200 | 6.7069 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

roleplaiapp/Llama-3.3-70B-Instruct-Q4_K_M-GGUF

roleplaiapp

2025-01-15T16:15:35Z

49

0

transformers

[ "transformers", "gguf", "llama-cpp", "Llama-3.3-70B-Instruct", "Q4_K_M", "meta-llama", "code", "math", "chat", "roleplay", "text-generation", "safetensors", "nlp", "en", "fr", "it", "pt", "hi", "es", "th", "de", "base_model:meta-llama/Llama-3.1-70B", "base_model:quantized:meta-llama/Llama-3.1-70B", "endpoints_compatible", "region:us", "conversational" ]

text-generation

2025-01-15T13:28:50Z

--- library_name: transformers language: - en - fr - it - pt - hi - es - th - de base_model: - meta-llama/Llama-3.1-70B tags: - llama-cpp - Llama-3.3-70B-Instruct - gguf - Q4_K_M - llama-cpp - gguf - meta-llama - code - math - chat - roleplay - text-generation - safetensors - nlp - code pipeline_tag: text-generation --- # Llama-3.3-70B-Instruct-Q4_K_M-GGUF **Repo:** `roleplaiapp/Llama-3.3-70B-Instruct-Q4_K_M -GGUF` **Original Model:** `Llama-3.3-70B-Instruct` **Organization:** `meta-llama` **Quantized File:** `llama-3.3-70b-instruct-q3_k_m.gguf` **Quantization:** `GGUF` **Quantization Method:** `Q4_K_M ` **Use Imatrix:** `False` **Split Model:** `False` ## Overview This is an GGUF Q4_K_M quantized version of [Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct). ## Quantization By I often have idle A100 GPUs while building/testing and training the RP app, so I put them to use quantizing models. I hope the community finds these quantizations useful. Andrew Webby @ [RolePlai](https://roleplai.app/)

exala/db_aca2_7.2.1

exala

2025-01-15T16:14:07Z

17

0

transformers

[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T16:13:53Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

Oscar2384/intime-sosten-copa-B-con-soft-algodon-elasticad-surtido

Oscar2384

2025-01-15T16:13:34Z

20

0

diffusers

[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]

text-to-image

2025-01-15T15:52:08Z

--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: COPASOSELAS --- # Intime Sosten Copa B Con Soft Algodon Elasticad Surtido <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `COPASOSELAS` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('Oscar2384/intime-sosten-copa-B-con-soft-algodon-elasticad-surtido', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF

paultimothymooney

2025-01-15T16:13:33Z

40

0

transformers

[ "transformers", "gguf", "code", "codeqwen", "chat", "qwen", "qwen-coder", "llama-cpp", "gguf-my-repo", "text-generation", "en", "base_model:Qwen/Qwen2.5-Coder-0.5B-Instruct", "base_model:quantized:Qwen/Qwen2.5-Coder-0.5B-Instruct", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

text-generation

2025-01-15T16:13:27Z

--- license: apache-2.0 license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct/blob/main/LICENSE language: - en base_model: Qwen/Qwen2.5-Coder-0.5B-Instruct pipeline_tag: text-generation library_name: transformers tags: - code - codeqwen - chat - qwen - qwen-coder - llama-cpp - gguf-my-repo --- # paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF This model was converted to GGUF format from [`Qwen/Qwen2.5-Coder-0.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B-Instruct) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo paultimothymooney/Qwen2.5-Coder-0.5B-Instruct-Q8_0-GGUF --hf-file qwen2.5-coder-0.5b-instruct-q8_0.gguf -c 2048 ```

phonemetransformers/CHILDES-Indonesian-phoneme-tokenizer

phonemetransformers

2025-01-15T16:12:07Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:54Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

oldiday/27f6fcb8-4599-455c-bbaf-98396a85a925

oldiday

2025-01-15T16:10:02Z

13

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-135M", "base_model:adapter:unsloth/SmolLM2-135M", "license:apache-2.0", "region:us" ]

null

2025-01-15T16:00:20Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-135M tags: - axolotl - generated_from_trainer model-index: - name: 27f6fcb8-4599-455c-bbaf-98396a85a925 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-135M bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - e5fba043d1f22bc2_train_data.json ds_type: json format: custom path: /workspace/input_data/e5fba043d1f22bc2_train_data.json type: field_instruction: prompt field_output: reference_response format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: oldiday/27f6fcb8-4599-455c-bbaf-98396a85a925 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 5.0e-05 load_in_4bit: false load_in_8bit: false local_rank: 0 logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_steps: 100 micro_batch_size: 8 mlflow_experiment_name: /tmp/e5fba043d1f22bc2_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: techspear-hub wandb_mode: online wandb_name: 15e5c164-e834-4f75-975b-0d306607a752 wandb_project: Gradients-On-Six wandb_run: your_name wandb_runid: 15e5c164-e834-4f75-975b-0d306607a752 warmup_steps: 10 weight_decay: 0.01 xformers_attention: null ``` </details> # 27f6fcb8-4599-455c-bbaf-98396a85a925 This model is a fine-tuned version of [unsloth/SmolLM2-135M](https://huggingface.co/unsloth/SmolLM2-135M) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3658 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0007 | 1 | 1.4431 | | 1.4342 | 0.0059 | 9 | 1.4399 | | 1.4666 | 0.0117 | 18 | 1.4246 | | 1.4174 | 0.0176 | 27 | 1.4081 | | 1.4487 | 0.0235 | 36 | 1.3942 | | 1.3878 | 0.0293 | 45 | 1.3837 | | 1.3904 | 0.0352 | 54 | 1.3762 | | 1.2992 | 0.0411 | 63 | 1.3713 | | 1.3923 | 0.0470 | 72 | 1.3683 | | 1.3503 | 0.0528 | 81 | 1.3666 | | 1.4249 | 0.0587 | 90 | 1.3660 | | 1.3777 | 0.0646 | 99 | 1.3658 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

tarabukinivan/a0bf2150-f712-41d2-9b98-6973dcf1c843

tarabukinivan

2025-01-15T16:09:25Z

9

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-3B", "base_model:adapter:Qwen/Qwen2.5-3B", "license:other", "region:us" ]

null

2025-01-15T15:39:26Z

--- library_name: peft license: other base_model: Qwen/Qwen2.5-3B tags: - axolotl - generated_from_trainer model-index: - name: a0bf2150-f712-41d2-9b98-6973dcf1c843 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-3B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 21f641ae0efcd8d6_train_data.json ds_type: json format: custom path: /workspace/input_data/21f641ae0efcd8d6_train_data.json type: field_instruction: prompt field_output: chosen format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: tarabukinivan/a0bf2150-f712-41d2-9b98-6973dcf1c843 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/21f641ae0efcd8d6_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 9e2f882e-8f4c-4fd9-b3f6-e92c5704a050 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 9e2f882e-8f4c-4fd9-b3f6-e92c5704a050 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # a0bf2150-f712-41d2-9b98-6973dcf1c843 This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0546 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 1.8047 | | 1.2561 | 0.0007 | 13 | 1.1174 | | 1.1405 | 0.0013 | 26 | 1.0613 | | 1.116 | 0.0020 | 39 | 1.0546 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization

MayBashendy

2025-01-15T16:09:17Z

7

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T14:57:24Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization results: [] ---  # ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k11_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5617 - Qwk: 0.4874 - Mse: 0.5617 - Rmse: 0.7495 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0339 | 2 | 4.2196 | -0.0288 | 4.2196 | 2.0542 | | No log | 0.0678 | 4 | 2.2233 | 0.0640 | 2.2233 | 1.4911 | | No log | 0.1017 | 6 | 1.2161 | 0.0258 | 1.2161 | 1.1028 | | No log | 0.1356 | 8 | 0.9924 | 0.0330 | 0.9924 | 0.9962 | | No log | 0.1695 | 10 | 0.8343 | 0.1465 | 0.8343 | 0.9134 | | No log | 0.2034 | 12 | 0.8470 | 0.1648 | 0.8470 | 0.9203 | | No log | 0.2373 | 14 | 0.8884 | 0.0983 | 0.8884 | 0.9425 | | No log | 0.2712 | 16 | 1.0015 | -0.0066 | 1.0015 | 1.0008 | | No log | 0.3051 | 18 | 0.9798 | 0.0851 | 0.9798 | 0.9898 | | No log | 0.3390 | 20 | 1.0506 | -0.0377 | 1.0506 | 1.0250 | | No log | 0.3729 | 22 | 1.3475 | 0.0262 | 1.3475 | 1.1608 | | No log | 0.4068 | 24 | 1.4195 | 0.0262 | 1.4195 | 1.1914 | | No log | 0.4407 | 26 | 1.1388 | 0.0363 | 1.1388 | 1.0671 | | No log | 0.4746 | 28 | 0.9469 | 0.0456 | 0.9469 | 0.9731 | | No log | 0.5085 | 30 | 0.7915 | 0.0932 | 0.7915 | 0.8897 | | No log | 0.5424 | 32 | 0.7764 | 0.0797 | 0.7764 | 0.8812 | | No log | 0.5763 | 34 | 0.7658 | 0.1505 | 0.7658 | 0.8751 | | No log | 0.6102 | 36 | 0.7574 | 0.1281 | 0.7574 | 0.8703 | | No log | 0.6441 | 38 | 0.7671 | 0.2713 | 0.7671 | 0.8759 | | No log | 0.6780 | 40 | 0.7597 | 0.2883 | 0.7597 | 0.8716 | | No log | 0.7119 | 42 | 0.7352 | 0.3097 | 0.7352 | 0.8575 | | No log | 0.7458 | 44 | 0.7179 | 0.2723 | 0.7179 | 0.8473 | | No log | 0.7797 | 46 | 0.8210 | 0.2453 | 0.8210 | 0.9061 | | No log | 0.8136 | 48 | 0.8228 | 0.2687 | 0.8228 | 0.9071 | | No log | 0.8475 | 50 | 0.7828 | 0.2687 | 0.7828 | 0.8848 | | No log | 0.8814 | 52 | 0.7498 | 0.3427 | 0.7498 | 0.8659 | | No log | 0.9153 | 54 | 0.7103 | 0.3392 | 0.7103 | 0.8428 | | No log | 0.9492 | 56 | 0.7264 | 0.3468 | 0.7264 | 0.8523 | | No log | 0.9831 | 58 | 0.7145 | 0.4157 | 0.7145 | 0.8453 | | No log | 1.0169 | 60 | 0.6964 | 0.3647 | 0.6964 | 0.8345 | | No log | 1.0508 | 62 | 0.6822 | 0.3708 | 0.6822 | 0.8259 | | No log | 1.0847 | 64 | 0.6574 | 0.4099 | 0.6574 | 0.8108 | | No log | 1.1186 | 66 | 0.6465 | 0.4529 | 0.6465 | 0.8040 | | No log | 1.1525 | 68 | 0.6532 | 0.4700 | 0.6532 | 0.8082 | | No log | 1.1864 | 70 | 0.6603 | 0.4298 | 0.6603 | 0.8126 | | No log | 1.2203 | 72 | 0.7369 | 0.4176 | 0.7369 | 0.8584 | | No log | 1.2542 | 74 | 0.6974 | 0.4337 | 0.6974 | 0.8351 | | No log | 1.2881 | 76 | 0.6845 | 0.4749 | 0.6845 | 0.8274 | | No log | 1.3220 | 78 | 0.6924 | 0.4749 | 0.6924 | 0.8321 | | No log | 1.3559 | 80 | 0.6937 | 0.4781 | 0.6937 | 0.8329 | | No log | 1.3898 | 82 | 0.7165 | 0.4589 | 0.7165 | 0.8465 | | No log | 1.4237 | 84 | 0.7688 | 0.4315 | 0.7688 | 0.8768 | | No log | 1.4576 | 86 | 0.9003 | 0.3983 | 0.9003 | 0.9488 | | No log | 1.4915 | 88 | 0.8929 | 0.4161 | 0.8929 | 0.9449 | | No log | 1.5254 | 90 | 0.7462 | 0.4357 | 0.7462 | 0.8638 | | No log | 1.5593 | 92 | 0.7201 | 0.4550 | 0.7201 | 0.8486 | | No log | 1.5932 | 94 | 0.7240 | 0.4899 | 0.7240 | 0.8509 | | No log | 1.6271 | 96 | 0.8073 | 0.4730 | 0.8073 | 0.8985 | | No log | 1.6610 | 98 | 0.8365 | 0.4393 | 0.8365 | 0.9146 | | No log | 1.6949 | 100 | 0.8551 | 0.4769 | 0.8551 | 0.9247 | | No log | 1.7288 | 102 | 0.7937 | 0.4260 | 0.7937 | 0.8909 | | No log | 1.7627 | 104 | 0.8459 | 0.4352 | 0.8459 | 0.9197 | | No log | 1.7966 | 106 | 0.7920 | 0.4484 | 0.7920 | 0.8899 | | No log | 1.8305 | 108 | 0.8247 | 0.4463 | 0.8247 | 0.9081 | | No log | 1.8644 | 110 | 1.1376 | 0.3577 | 1.1376 | 1.0666 | | No log | 1.8983 | 112 | 1.0599 | 0.3574 | 1.0599 | 1.0295 | | No log | 1.9322 | 114 | 0.7327 | 0.4837 | 0.7327 | 0.8560 | | No log | 1.9661 | 116 | 0.8170 | 0.3834 | 0.8170 | 0.9039 | | No log | 2.0 | 118 | 0.8166 | 0.3846 | 0.8166 | 0.9037 | | No log | 2.0339 | 120 | 0.7262 | 0.5192 | 0.7262 | 0.8522 | | No log | 2.0678 | 122 | 0.8005 | 0.4277 | 0.8005 | 0.8947 | | No log | 2.1017 | 124 | 0.9027 | 0.2983 | 0.9027 | 0.9501 | | No log | 2.1356 | 126 | 0.7849 | 0.4046 | 0.7849 | 0.8859 | | No log | 2.1695 | 128 | 0.7066 | 0.3798 | 0.7066 | 0.8406 | | No log | 2.2034 | 130 | 0.6268 | 0.4572 | 0.6268 | 0.7917 | | No log | 2.2373 | 132 | 0.6235 | 0.4659 | 0.6235 | 0.7896 | | No log | 2.2712 | 134 | 0.6538 | 0.4459 | 0.6538 | 0.8086 | | No log | 2.3051 | 136 | 0.8376 | 0.4329 | 0.8376 | 0.9152 | | No log | 2.3390 | 138 | 0.7967 | 0.4363 | 0.7967 | 0.8926 | | No log | 2.3729 | 140 | 0.6376 | 0.4274 | 0.6376 | 0.7985 | | No log | 2.4068 | 142 | 0.6585 | 0.4542 | 0.6585 | 0.8115 | | No log | 2.4407 | 144 | 0.6457 | 0.4321 | 0.6457 | 0.8035 | | No log | 2.4746 | 146 | 0.6707 | 0.4785 | 0.6707 | 0.8189 | | No log | 2.5085 | 148 | 0.6931 | 0.4606 | 0.6931 | 0.8325 | | No log | 2.5424 | 150 | 0.6635 | 0.4477 | 0.6635 | 0.8145 | | No log | 2.5763 | 152 | 0.6945 | 0.4744 | 0.6945 | 0.8334 | | No log | 2.6102 | 154 | 0.6745 | 0.4655 | 0.6745 | 0.8213 | | No log | 2.6441 | 156 | 0.6559 | 0.4746 | 0.6559 | 0.8099 | | No log | 2.6780 | 158 | 0.6424 | 0.4958 | 0.6424 | 0.8015 | | No log | 2.7119 | 160 | 0.6542 | 0.5039 | 0.6542 | 0.8088 | | No log | 2.7458 | 162 | 0.6594 | 0.5213 | 0.6594 | 0.8120 | | No log | 2.7797 | 164 | 0.7149 | 0.5015 | 0.7149 | 0.8455 | | No log | 2.8136 | 166 | 0.7718 | 0.5442 | 0.7718 | 0.8785 | | No log | 2.8475 | 168 | 0.7848 | 0.5622 | 0.7848 | 0.8859 | | No log | 2.8814 | 170 | 0.7685 | 0.5126 | 0.7685 | 0.8766 | | No log | 2.9153 | 172 | 0.8633 | 0.4963 | 0.8633 | 0.9291 | | No log | 2.9492 | 174 | 0.8201 | 0.5117 | 0.8201 | 0.9056 | | No log | 2.9831 | 176 | 0.7117 | 0.5364 | 0.7117 | 0.8436 | | No log | 3.0169 | 178 | 0.8802 | 0.4675 | 0.8802 | 0.9382 | | No log | 3.0508 | 180 | 0.7990 | 0.4734 | 0.7990 | 0.8939 | | No log | 3.0847 | 182 | 0.6686 | 0.4847 | 0.6686 | 0.8176 | | No log | 3.1186 | 184 | 0.6372 | 0.4211 | 0.6372 | 0.7983 | | No log | 3.1525 | 186 | 0.6420 | 0.3830 | 0.6420 | 0.8013 | | No log | 3.1864 | 188 | 0.7457 | 0.4332 | 0.7457 | 0.8636 | | No log | 3.2203 | 190 | 0.7242 | 0.4210 | 0.7242 | 0.8510 | | No log | 3.2542 | 192 | 0.6703 | 0.4150 | 0.6703 | 0.8187 | | No log | 3.2881 | 194 | 0.6770 | 0.3859 | 0.6770 | 0.8228 | | No log | 3.3220 | 196 | 0.6892 | 0.4199 | 0.6892 | 0.8302 | | No log | 3.3559 | 198 | 0.7007 | 0.4433 | 0.7007 | 0.8371 | | No log | 3.3898 | 200 | 0.7016 | 0.4348 | 0.7016 | 0.8376 | | No log | 3.4237 | 202 | 0.7239 | 0.4275 | 0.7239 | 0.8508 | | No log | 3.4576 | 204 | 0.7045 | 0.4275 | 0.7045 | 0.8394 | | No log | 3.4915 | 206 | 0.6639 | 0.4249 | 0.6639 | 0.8148 | | No log | 3.5254 | 208 | 0.6430 | 0.3490 | 0.6430 | 0.8019 | | No log | 3.5593 | 210 | 0.6838 | 0.3809 | 0.6838 | 0.8269 | | No log | 3.5932 | 212 | 0.6554 | 0.3574 | 0.6554 | 0.8096 | | No log | 3.6271 | 214 | 0.6941 | 0.3643 | 0.6941 | 0.8331 | | No log | 3.6610 | 216 | 0.9193 | 0.3782 | 0.9193 | 0.9588 | | No log | 3.6949 | 218 | 0.8658 | 0.3735 | 0.8658 | 0.9305 | | No log | 3.7288 | 220 | 0.6616 | 0.3662 | 0.6616 | 0.8134 | | No log | 3.7627 | 222 | 0.6164 | 0.3456 | 0.6164 | 0.7851 | | No log | 3.7966 | 224 | 0.6183 | 0.4331 | 0.6183 | 0.7863 | | No log | 3.8305 | 226 | 0.6271 | 0.3885 | 0.6271 | 0.7919 | | No log | 3.8644 | 228 | 0.6795 | 0.3969 | 0.6795 | 0.8243 | | No log | 3.8983 | 230 | 0.7252 | 0.4442 | 0.7252 | 0.8516 | | No log | 3.9322 | 232 | 0.7638 | 0.4587 | 0.7638 | 0.8739 | | No log | 3.9661 | 234 | 0.6737 | 0.4424 | 0.6737 | 0.8208 | | No log | 4.0 | 236 | 0.6828 | 0.4186 | 0.6828 | 0.8263 | | No log | 4.0339 | 238 | 0.6647 | 0.4051 | 0.6647 | 0.8153 | | No log | 4.0678 | 240 | 0.6187 | 0.3669 | 0.6187 | 0.7866 | | No log | 4.1017 | 242 | 0.6409 | 0.4165 | 0.6409 | 0.8006 | | No log | 4.1356 | 244 | 0.7363 | 0.4767 | 0.7363 | 0.8581 | | No log | 4.1695 | 246 | 1.0628 | 0.3801 | 1.0628 | 1.0309 | | No log | 4.2034 | 248 | 1.1978 | 0.3578 | 1.1978 | 1.0944 | | No log | 4.2373 | 250 | 0.9836 | 0.4115 | 0.9836 | 0.9918 | | No log | 4.2712 | 252 | 0.7441 | 0.4461 | 0.7441 | 0.8626 | | No log | 4.3051 | 254 | 0.6874 | 0.4652 | 0.6874 | 0.8291 | | No log | 4.3390 | 256 | 0.6894 | 0.4741 | 0.6894 | 0.8303 | | No log | 4.3729 | 258 | 0.7296 | 0.4072 | 0.7296 | 0.8542 | | No log | 4.4068 | 260 | 0.7426 | 0.4467 | 0.7426 | 0.8618 | | No log | 4.4407 | 262 | 0.8213 | 0.4579 | 0.8213 | 0.9062 | | No log | 4.4746 | 264 | 0.7700 | 0.4579 | 0.7700 | 0.8775 | | No log | 4.5085 | 266 | 0.7815 | 0.4523 | 0.7815 | 0.8840 | | No log | 4.5424 | 268 | 0.6997 | 0.4531 | 0.6997 | 0.8365 | | No log | 4.5763 | 270 | 0.6442 | 0.4227 | 0.6442 | 0.8026 | | No log | 4.6102 | 272 | 0.5964 | 0.4278 | 0.5964 | 0.7723 | | No log | 4.6441 | 274 | 0.6215 | 0.4015 | 0.6215 | 0.7884 | | No log | 4.6780 | 276 | 0.6080 | 0.3765 | 0.6080 | 0.7798 | | No log | 4.7119 | 278 | 0.5863 | 0.3998 | 0.5863 | 0.7657 | | No log | 4.7458 | 280 | 0.5943 | 0.4679 | 0.5943 | 0.7709 | | No log | 4.7797 | 282 | 0.6017 | 0.4383 | 0.6017 | 0.7757 | | No log | 4.8136 | 284 | 0.6141 | 0.4176 | 0.6141 | 0.7837 | | No log | 4.8475 | 286 | 0.6245 | 0.4499 | 0.6245 | 0.7902 | | No log | 4.8814 | 288 | 0.6176 | 0.4807 | 0.6176 | 0.7859 | | No log | 4.9153 | 290 | 0.6299 | 0.4458 | 0.6299 | 0.7936 | | No log | 4.9492 | 292 | 0.7054 | 0.4557 | 0.7054 | 0.8399 | | No log | 4.9831 | 294 | 0.7136 | 0.4664 | 0.7136 | 0.8448 | | No log | 5.0169 | 296 | 0.6757 | 0.4381 | 0.6757 | 0.8220 | | No log | 5.0508 | 298 | 0.6509 | 0.4846 | 0.6509 | 0.8068 | | No log | 5.0847 | 300 | 0.6313 | 0.4673 | 0.6313 | 0.7945 | | No log | 5.1186 | 302 | 0.6295 | 0.4693 | 0.6295 | 0.7934 | | No log | 5.1525 | 304 | 0.6293 | 0.4578 | 0.6293 | 0.7933 | | No log | 5.1864 | 306 | 0.6420 | 0.4416 | 0.6420 | 0.8012 | | No log | 5.2203 | 308 | 0.7168 | 0.4810 | 0.7168 | 0.8466 | | No log | 5.2542 | 310 | 0.7265 | 0.4579 | 0.7265 | 0.8524 | | No log | 5.2881 | 312 | 0.6593 | 0.4516 | 0.6593 | 0.8120 | | No log | 5.3220 | 314 | 0.6216 | 0.4036 | 0.6216 | 0.7884 | | No log | 5.3559 | 316 | 0.6288 | 0.4029 | 0.6288 | 0.7930 | | No log | 5.3898 | 318 | 0.6443 | 0.4682 | 0.6443 | 0.8027 | | No log | 5.4237 | 320 | 0.6501 | 0.4578 | 0.6501 | 0.8063 | | No log | 5.4576 | 322 | 0.6482 | 0.4740 | 0.6482 | 0.8051 | | No log | 5.4915 | 324 | 0.6157 | 0.4134 | 0.6157 | 0.7847 | | No log | 5.5254 | 326 | 0.6020 | 0.4150 | 0.6020 | 0.7759 | | No log | 5.5593 | 328 | 0.5992 | 0.3806 | 0.5992 | 0.7741 | | No log | 5.5932 | 330 | 0.5935 | 0.4808 | 0.5935 | 0.7704 | | No log | 5.6271 | 332 | 0.5974 | 0.4925 | 0.5974 | 0.7729 | | No log | 5.6610 | 334 | 0.6415 | 0.5098 | 0.6415 | 0.8010 | | No log | 5.6949 | 336 | 0.6185 | 0.4956 | 0.6185 | 0.7865 | | No log | 5.7288 | 338 | 0.5939 | 0.4842 | 0.5939 | 0.7706 | | No log | 5.7627 | 340 | 0.5816 | 0.4157 | 0.5816 | 0.7626 | | No log | 5.7966 | 342 | 0.6050 | 0.3829 | 0.6050 | 0.7778 | | No log | 5.8305 | 344 | 0.5903 | 0.4521 | 0.5903 | 0.7683 | | No log | 5.8644 | 346 | 0.6224 | 0.5026 | 0.6224 | 0.7889 | | No log | 5.8983 | 348 | 0.6256 | 0.5039 | 0.6256 | 0.7910 | | No log | 5.9322 | 350 | 0.6195 | 0.4572 | 0.6195 | 0.7871 | | No log | 5.9661 | 352 | 0.6777 | 0.4649 | 0.6777 | 0.8232 | | No log | 6.0 | 354 | 0.8010 | 0.4884 | 0.8010 | 0.8950 | | No log | 6.0339 | 356 | 0.8134 | 0.4784 | 0.8134 | 0.9019 | | No log | 6.0678 | 358 | 0.7095 | 0.4522 | 0.7095 | 0.8423 | | No log | 6.1017 | 360 | 0.6367 | 0.4440 | 0.6367 | 0.7979 | | No log | 6.1356 | 362 | 0.6759 | 0.5220 | 0.6759 | 0.8221 | | No log | 6.1695 | 364 | 0.6883 | 0.5230 | 0.6883 | 0.8297 | | No log | 6.2034 | 366 | 0.6466 | 0.4729 | 0.6466 | 0.8041 | | No log | 6.2373 | 368 | 0.6219 | 0.4422 | 0.6219 | 0.7886 | | No log | 6.2712 | 370 | 0.6174 | 0.4460 | 0.6174 | 0.7858 | | No log | 6.3051 | 372 | 0.6144 | 0.4398 | 0.6144 | 0.7838 | | No log | 6.3390 | 374 | 0.6120 | 0.4521 | 0.6120 | 0.7823 | | No log | 6.3729 | 376 | 0.6093 | 0.4570 | 0.6093 | 0.7806 | | No log | 6.4068 | 378 | 0.6226 | 0.4540 | 0.6226 | 0.7890 | | No log | 6.4407 | 380 | 0.6624 | 0.4716 | 0.6624 | 0.8139 | | No log | 6.4746 | 382 | 0.6675 | 0.4270 | 0.6675 | 0.8170 | | No log | 6.5085 | 384 | 0.6181 | 0.3848 | 0.6181 | 0.7862 | | No log | 6.5424 | 386 | 0.5847 | 0.3426 | 0.5847 | 0.7647 | | No log | 6.5763 | 388 | 0.5801 | 0.4841 | 0.5801 | 0.7616 | | No log | 6.6102 | 390 | 0.5851 | 0.4906 | 0.5851 | 0.7649 | | No log | 6.6441 | 392 | 0.6153 | 0.4866 | 0.6153 | 0.7844 | | No log | 6.6780 | 394 | 0.6139 | 0.5018 | 0.6139 | 0.7835 | | No log | 6.7119 | 396 | 0.6068 | 0.5290 | 0.6068 | 0.7790 | | No log | 6.7458 | 398 | 0.6110 | 0.4687 | 0.6110 | 0.7817 | | No log | 6.7797 | 400 | 0.6028 | 0.4284 | 0.6028 | 0.7764 | | No log | 6.8136 | 402 | 0.5944 | 0.4042 | 0.5944 | 0.7710 | | No log | 6.8475 | 404 | 0.5969 | 0.4319 | 0.5969 | 0.7726 | | No log | 6.8814 | 406 | 0.6161 | 0.4480 | 0.6161 | 0.7849 | | No log | 6.9153 | 408 | 0.6922 | 0.4825 | 0.6922 | 0.8320 | | No log | 6.9492 | 410 | 0.6787 | 0.4948 | 0.6787 | 0.8239 | | No log | 6.9831 | 412 | 0.6222 | 0.4482 | 0.6222 | 0.7888 | | No log | 7.0169 | 414 | 0.6365 | 0.4706 | 0.6365 | 0.7978 | | No log | 7.0508 | 416 | 0.7240 | 0.4915 | 0.7240 | 0.8509 | | No log | 7.0847 | 418 | 0.7256 | 0.5048 | 0.7256 | 0.8518 | | No log | 7.1186 | 420 | 0.6445 | 0.4816 | 0.6445 | 0.8028 | | No log | 7.1525 | 422 | 0.6172 | 0.4788 | 0.6172 | 0.7856 | | No log | 7.1864 | 424 | 0.6290 | 0.4921 | 0.6290 | 0.7931 | | No log | 7.2203 | 426 | 0.6963 | 0.5303 | 0.6963 | 0.8345 | | No log | 7.2542 | 428 | 0.8245 | 0.3773 | 0.8245 | 0.9080 | | No log | 7.2881 | 430 | 0.8196 | 0.3773 | 0.8196 | 0.9053 | | No log | 7.3220 | 432 | 0.7598 | 0.4345 | 0.7598 | 0.8717 | | No log | 7.3559 | 434 | 0.6501 | 0.5567 | 0.6501 | 0.8063 | | No log | 7.3898 | 436 | 0.5816 | 0.5299 | 0.5816 | 0.7626 | | No log | 7.4237 | 438 | 0.5829 | 0.5409 | 0.5829 | 0.7635 | | No log | 7.4576 | 440 | 0.6012 | 0.5314 | 0.6012 | 0.7754 | | No log | 7.4915 | 442 | 0.6652 | 0.5143 | 0.6652 | 0.8156 | | No log | 7.5254 | 444 | 0.6704 | 0.5143 | 0.6704 | 0.8188 | | No log | 7.5593 | 446 | 0.6131 | 0.5514 | 0.6131 | 0.7830 | | No log | 7.5932 | 448 | 0.5898 | 0.4963 | 0.5898 | 0.7680 | | No log | 7.6271 | 450 | 0.6421 | 0.4221 | 0.6421 | 0.8013 | | No log | 7.6610 | 452 | 0.6541 | 0.4131 | 0.6541 | 0.8087 | | No log | 7.6949 | 454 | 0.6077 | 0.4619 | 0.6077 | 0.7796 | | No log | 7.7288 | 456 | 0.5903 | 0.4783 | 0.5903 | 0.7683 | | No log | 7.7627 | 458 | 0.7189 | 0.4959 | 0.7189 | 0.8479 | | No log | 7.7966 | 460 | 0.8165 | 0.4250 | 0.8165 | 0.9036 | | No log | 7.8305 | 462 | 0.7612 | 0.4290 | 0.7612 | 0.8725 | | No log | 7.8644 | 464 | 0.6345 | 0.5071 | 0.6345 | 0.7965 | | No log | 7.8983 | 466 | 0.5708 | 0.5136 | 0.5708 | 0.7555 | | No log | 7.9322 | 468 | 0.5614 | 0.4876 | 0.5614 | 0.7493 | | No log | 7.9661 | 470 | 0.5710 | 0.5131 | 0.5710 | 0.7556 | | No log | 8.0 | 472 | 0.6259 | 0.5158 | 0.6259 | 0.7911 | | No log | 8.0339 | 474 | 0.7018 | 0.5192 | 0.7018 | 0.8377 | | No log | 8.0678 | 476 | 0.6813 | 0.5302 | 0.6813 | 0.8254 | | No log | 8.1017 | 478 | 0.6114 | 0.4985 | 0.6114 | 0.7819 | | No log | 8.1356 | 480 | 0.5791 | 0.5447 | 0.5791 | 0.7610 | | No log | 8.1695 | 482 | 0.5797 | 0.5357 | 0.5797 | 0.7614 | | No log | 8.2034 | 484 | 0.6036 | 0.4828 | 0.6036 | 0.7769 | | No log | 8.2373 | 486 | 0.6574 | 0.5173 | 0.6574 | 0.8108 | | No log | 8.2712 | 488 | 0.6894 | 0.5158 | 0.6894 | 0.8303 | | No log | 8.3051 | 490 | 0.7148 | 0.5177 | 0.7148 | 0.8454 | | No log | 8.3390 | 492 | 0.6801 | 0.5158 | 0.6801 | 0.8247 | | No log | 8.3729 | 494 | 0.6156 | 0.4833 | 0.6156 | 0.7846 | | No log | 8.4068 | 496 | 0.5827 | 0.4948 | 0.5827 | 0.7633 | | No log | 8.4407 | 498 | 0.5896 | 0.3781 | 0.5896 | 0.7679 | | 0.3742 | 8.4746 | 500 | 0.5902 | 0.3905 | 0.5902 | 0.7683 | | 0.3742 | 8.5085 | 502 | 0.5993 | 0.4837 | 0.5993 | 0.7742 | | 0.3742 | 8.5424 | 504 | 0.6062 | 0.4998 | 0.6062 | 0.7786 | | 0.3742 | 8.5763 | 506 | 0.6092 | 0.5123 | 0.6092 | 0.7805 | | 0.3742 | 8.6102 | 508 | 0.6054 | 0.4489 | 0.6054 | 0.7781 | | 0.3742 | 8.6441 | 510 | 0.6295 | 0.4877 | 0.6295 | 0.7934 | | 0.3742 | 8.6780 | 512 | 0.6631 | 0.4187 | 0.6631 | 0.8143 | | 0.3742 | 8.7119 | 514 | 0.6665 | 0.4214 | 0.6665 | 0.8164 | | 0.3742 | 8.7458 | 516 | 0.6354 | 0.4539 | 0.6354 | 0.7971 | | 0.3742 | 8.7797 | 518 | 0.6137 | 0.4711 | 0.6137 | 0.7834 | | 0.3742 | 8.8136 | 520 | 0.5911 | 0.5396 | 0.5911 | 0.7688 | | 0.3742 | 8.8475 | 522 | 0.6211 | 0.5035 | 0.6211 | 0.7881 | | 0.3742 | 8.8814 | 524 | 0.7404 | 0.4629 | 0.7404 | 0.8605 | | 0.3742 | 8.9153 | 526 | 0.7928 | 0.4108 | 0.7928 | 0.8904 | | 0.3742 | 8.9492 | 528 | 0.7446 | 0.4538 | 0.7446 | 0.8629 | | 0.3742 | 8.9831 | 530 | 0.6457 | 0.5147 | 0.6457 | 0.8036 | | 0.3742 | 9.0169 | 532 | 0.5852 | 0.5248 | 0.5852 | 0.7650 | | 0.3742 | 9.0508 | 534 | 0.5808 | 0.4884 | 0.5808 | 0.7621 | | 0.3742 | 9.0847 | 536 | 0.5865 | 0.5155 | 0.5865 | 0.7658 | | 0.3742 | 9.1186 | 538 | 0.6318 | 0.5237 | 0.6318 | 0.7949 | | 0.3742 | 9.1525 | 540 | 0.6793 | 0.4758 | 0.6793 | 0.8242 | | 0.3742 | 9.1864 | 542 | 0.7238 | 0.4568 | 0.7238 | 0.8508 | | 0.3742 | 9.2203 | 544 | 0.6955 | 0.4444 | 0.6955 | 0.8340 | | 0.3742 | 9.2542 | 546 | 0.6120 | 0.4930 | 0.6120 | 0.7823 | | 0.3742 | 9.2881 | 548 | 0.5883 | 0.5198 | 0.5883 | 0.7670 | | 0.3742 | 9.3220 | 550 | 0.5969 | 0.5334 | 0.5969 | 0.7726 | | 0.3742 | 9.3559 | 552 | 0.6477 | 0.5118 | 0.6477 | 0.8048 | | 0.3742 | 9.3898 | 554 | 0.6999 | 0.4560 | 0.6999 | 0.8366 | | 0.3742 | 9.4237 | 556 | 0.6612 | 0.5329 | 0.6612 | 0.8131 | | 0.3742 | 9.4576 | 558 | 0.5937 | 0.5487 | 0.5937 | 0.7705 | | 0.3742 | 9.4915 | 560 | 0.5724 | 0.4827 | 0.5724 | 0.7566 | | 0.3742 | 9.5254 | 562 | 0.5785 | 0.4910 | 0.5785 | 0.7606 | | 0.3742 | 9.5593 | 564 | 0.5883 | 0.4611 | 0.5883 | 0.7670 | | 0.3742 | 9.5932 | 566 | 0.5856 | 0.4747 | 0.5856 | 0.7652 | | 0.3742 | 9.6271 | 568 | 0.6184 | 0.5233 | 0.6184 | 0.7864 | | 0.3742 | 9.6610 | 570 | 0.6614 | 0.5189 | 0.6614 | 0.8133 | | 0.3742 | 9.6949 | 572 | 0.6453 | 0.4999 | 0.6453 | 0.8033 | | 0.3742 | 9.7288 | 574 | 0.6140 | 0.5434 | 0.6140 | 0.7836 | | 0.3742 | 9.7627 | 576 | 0.6231 | 0.4926 | 0.6231 | 0.7893 | | 0.3742 | 9.7966 | 578 | 0.6571 | 0.4916 | 0.6571 | 0.8106 | | 0.3742 | 9.8305 | 580 | 0.6343 | 0.4722 | 0.6343 | 0.7964 | | 0.3742 | 9.8644 | 582 | 0.6065 | 0.4923 | 0.6065 | 0.7788 | | 0.3742 | 9.8983 | 584 | 0.6180 | 0.4742 | 0.6180 | 0.7861 | | 0.3742 | 9.9322 | 586 | 0.6712 | 0.4695 | 0.6712 | 0.8193 | | 0.3742 | 9.9661 | 588 | 0.7290 | 0.4787 | 0.7290 | 0.8538 | | 0.3742 | 10.0 | 590 | 0.7491 | 0.4650 | 0.7491 | 0.8655 | | 0.3742 | 10.0339 | 592 | 0.7263 | 0.4659 | 0.7263 | 0.8522 | | 0.3742 | 10.0678 | 594 | 0.6702 | 0.5251 | 0.6702 | 0.8187 | | 0.3742 | 10.1017 | 596 | 0.6595 | 0.5351 | 0.6595 | 0.8121 | | 0.3742 | 10.1356 | 598 | 0.6585 | 0.4904 | 0.6585 | 0.8115 | | 0.3742 | 10.1695 | 600 | 0.6765 | 0.4783 | 0.6765 | 0.8225 | | 0.3742 | 10.2034 | 602 | 0.6808 | 0.4394 | 0.6808 | 0.8251 | | 0.3742 | 10.2373 | 604 | 0.6815 | 0.4096 | 0.6815 | 0.8255 | | 0.3742 | 10.2712 | 606 | 0.6668 | 0.4283 | 0.6668 | 0.8166 | | 0.3742 | 10.3051 | 608 | 0.6261 | 0.4877 | 0.6261 | 0.7912 | | 0.3742 | 10.3390 | 610 | 0.6318 | 0.4413 | 0.6318 | 0.7948 | | 0.3742 | 10.3729 | 612 | 0.6476 | 0.4626 | 0.6476 | 0.8048 | | 0.3742 | 10.4068 | 614 | 0.6388 | 0.4407 | 0.6388 | 0.7992 | | 0.3742 | 10.4407 | 616 | 0.6333 | 0.4539 | 0.6333 | 0.7958 | | 0.3742 | 10.4746 | 618 | 0.6294 | 0.4416 | 0.6294 | 0.7934 | | 0.3742 | 10.5085 | 620 | 0.6251 | 0.4438 | 0.6251 | 0.7906 | | 0.3742 | 10.5424 | 622 | 0.6119 | 0.3935 | 0.6119 | 0.7822 | | 0.3742 | 10.5763 | 624 | 0.6131 | 0.4082 | 0.6131 | 0.7830 | | 0.3742 | 10.6102 | 626 | 0.6237 | 0.3958 | 0.6237 | 0.7898 | | 0.3742 | 10.6441 | 628 | 0.6435 | 0.4252 | 0.6435 | 0.8022 | | 0.3742 | 10.6780 | 630 | 0.6649 | 0.4222 | 0.6649 | 0.8154 | | 0.3742 | 10.7119 | 632 | 0.6542 | 0.4579 | 0.6542 | 0.8088 | | 0.3742 | 10.7458 | 634 | 0.6224 | 0.4349 | 0.6224 | 0.7889 | | 0.3742 | 10.7797 | 636 | 0.6125 | 0.4549 | 0.6125 | 0.7826 | | 0.3742 | 10.8136 | 638 | 0.6063 | 0.4004 | 0.6063 | 0.7786 | | 0.3742 | 10.8475 | 640 | 0.6026 | 0.4412 | 0.6026 | 0.7763 | | 0.3742 | 10.8814 | 642 | 0.5971 | 0.4454 | 0.5971 | 0.7727 | | 0.3742 | 10.9153 | 644 | 0.5979 | 0.4541 | 0.5979 | 0.7733 | | 0.3742 | 10.9492 | 646 | 0.5891 | 0.4398 | 0.5891 | 0.7675 | | 0.3742 | 10.9831 | 648 | 0.5801 | 0.4844 | 0.5801 | 0.7617 | | 0.3742 | 11.0169 | 650 | 0.5838 | 0.5122 | 0.5838 | 0.7641 | | 0.3742 | 11.0508 | 652 | 0.6248 | 0.5615 | 0.6248 | 0.7904 | | 0.3742 | 11.0847 | 654 | 0.7645 | 0.4710 | 0.7645 | 0.8744 | | 0.3742 | 11.1186 | 656 | 0.9152 | 0.3868 | 0.9152 | 0.9567 | | 0.3742 | 11.1525 | 658 | 0.9535 | 0.3497 | 0.9535 | 0.9765 | | 0.3742 | 11.1864 | 660 | 0.8803 | 0.3921 | 0.8803 | 0.9382 | | 0.3742 | 11.2203 | 662 | 0.7806 | 0.4437 | 0.7806 | 0.8835 | | 0.3742 | 11.2542 | 664 | 0.6500 | 0.5398 | 0.6500 | 0.8062 | | 0.3742 | 11.2881 | 666 | 0.5876 | 0.5625 | 0.5876 | 0.7665 | | 0.3742 | 11.3220 | 668 | 0.5857 | 0.5625 | 0.5857 | 0.7653 | | 0.3742 | 11.3559 | 670 | 0.6102 | 0.5683 | 0.6102 | 0.7812 | | 0.3742 | 11.3898 | 672 | 0.6804 | 0.5423 | 0.6804 | 0.8249 | | 0.3742 | 11.4237 | 674 | 0.7725 | 0.4654 | 0.7725 | 0.8789 | | 0.3742 | 11.4576 | 676 | 0.8085 | 0.4392 | 0.8085 | 0.8991 | | 0.3742 | 11.4915 | 678 | 0.7631 | 0.4239 | 0.7631 | 0.8736 | | 0.3742 | 11.5254 | 680 | 0.6930 | 0.4136 | 0.6930 | 0.8325 | | 0.3742 | 11.5593 | 682 | 0.6677 | 0.4598 | 0.6677 | 0.8171 | | 0.3742 | 11.5932 | 684 | 0.6682 | 0.4685 | 0.6682 | 0.8174 | | 0.3742 | 11.6271 | 686 | 0.7061 | 0.4925 | 0.7061 | 0.8403 | | 0.3742 | 11.6610 | 688 | 0.7086 | 0.4793 | 0.7086 | 0.8418 | | 0.3742 | 11.6949 | 690 | 0.6720 | 0.5200 | 0.6720 | 0.8197 | | 0.3742 | 11.7288 | 692 | 0.6325 | 0.5019 | 0.6325 | 0.7953 | | 0.3742 | 11.7627 | 694 | 0.6226 | 0.4998 | 0.6226 | 0.7890 | | 0.3742 | 11.7966 | 696 | 0.6334 | 0.5347 | 0.6334 | 0.7959 | | 0.3742 | 11.8305 | 698 | 0.6461 | 0.5006 | 0.6461 | 0.8038 | | 0.3742 | 11.8644 | 700 | 0.6405 | 0.5336 | 0.6405 | 0.8003 | | 0.3742 | 11.8983 | 702 | 0.6450 | 0.4781 | 0.6450 | 0.8031 | | 0.3742 | 11.9322 | 704 | 0.6486 | 0.4519 | 0.6486 | 0.8054 | | 0.3742 | 11.9661 | 706 | 0.6481 | 0.4878 | 0.6481 | 0.8051 | | 0.3742 | 12.0 | 708 | 0.6390 | 0.5206 | 0.6390 | 0.7994 | | 0.3742 | 12.0339 | 710 | 0.6954 | 0.5230 | 0.6954 | 0.8339 | | 0.3742 | 12.0678 | 712 | 0.7365 | 0.4913 | 0.7365 | 0.8582 | | 0.3742 | 12.1017 | 714 | 0.7072 | 0.4726 | 0.7072 | 0.8409 | | 0.3742 | 12.1356 | 716 | 0.6519 | 0.4459 | 0.6519 | 0.8074 | | 0.3742 | 12.1695 | 718 | 0.6112 | 0.4714 | 0.6112 | 0.7818 | | 0.3742 | 12.2034 | 720 | 0.6113 | 0.4781 | 0.6113 | 0.7819 | | 0.3742 | 12.2373 | 722 | 0.6359 | 0.4375 | 0.6359 | 0.7974 | | 0.3742 | 12.2712 | 724 | 0.6797 | 0.4674 | 0.6797 | 0.8244 | | 0.3742 | 12.3051 | 726 | 0.7603 | 0.3992 | 0.7603 | 0.8719 | | 0.3742 | 12.3390 | 728 | 0.7811 | 0.4862 | 0.7811 | 0.8838 | | 0.3742 | 12.3729 | 730 | 0.7230 | 0.4618 | 0.7230 | 0.8503 | | 0.3742 | 12.4068 | 732 | 0.6736 | 0.4575 | 0.6736 | 0.8207 | | 0.3742 | 12.4407 | 734 | 0.6627 | 0.5083 | 0.6627 | 0.8140 | | 0.3742 | 12.4746 | 736 | 0.6226 | 0.5014 | 0.6226 | 0.7891 | | 0.3742 | 12.5085 | 738 | 0.6193 | 0.5362 | 0.6193 | 0.7870 | | 0.3742 | 12.5424 | 740 | 0.6673 | 0.5083 | 0.6673 | 0.8169 | | 0.3742 | 12.5763 | 742 | 0.7748 | 0.4346 | 0.7748 | 0.8802 | | 0.3742 | 12.6102 | 744 | 0.8359 | 0.4813 | 0.8359 | 0.9143 | | 0.3742 | 12.6441 | 746 | 0.7885 | 0.4116 | 0.7885 | 0.8880 | | 0.3742 | 12.6780 | 748 | 0.7043 | 0.4074 | 0.7043 | 0.8392 | | 0.3742 | 12.7119 | 750 | 0.6857 | 0.3907 | 0.6857 | 0.8280 | | 0.3742 | 12.7458 | 752 | 0.6625 | 0.3733 | 0.6625 | 0.8140 | | 0.3742 | 12.7797 | 754 | 0.6589 | 0.3733 | 0.6589 | 0.8118 | | 0.3742 | 12.8136 | 756 | 0.6701 | 0.4074 | 0.6701 | 0.8186 | | 0.3742 | 12.8475 | 758 | 0.6657 | 0.3907 | 0.6657 | 0.8159 | | 0.3742 | 12.8814 | 760 | 0.6350 | 0.4112 | 0.6350 | 0.7969 | | 0.3742 | 12.9153 | 762 | 0.6341 | 0.4101 | 0.6341 | 0.7963 | | 0.3742 | 12.9492 | 764 | 0.6836 | 0.4522 | 0.6836 | 0.8268 | | 0.3742 | 12.9831 | 766 | 0.6856 | 0.4935 | 0.6856 | 0.8280 | | 0.3742 | 13.0169 | 768 | 0.6397 | 0.4842 | 0.6397 | 0.7998 | | 0.3742 | 13.0508 | 770 | 0.5950 | 0.4874 | 0.5950 | 0.7713 | | 0.3742 | 13.0847 | 772 | 0.5875 | 0.5503 | 0.5875 | 0.7665 | | 0.3742 | 13.1186 | 774 | 0.5872 | 0.5484 | 0.5872 | 0.7663 | | 0.3742 | 13.1525 | 776 | 0.5959 | 0.5323 | 0.5959 | 0.7719 | | 0.3742 | 13.1864 | 778 | 0.6663 | 0.5007 | 0.6663 | 0.8163 | | 0.3742 | 13.2203 | 780 | 0.7393 | 0.4969 | 0.7393 | 0.8598 | | 0.3742 | 13.2542 | 782 | 0.7082 | 0.4969 | 0.7082 | 0.8415 | | 0.3742 | 13.2881 | 784 | 0.6598 | 0.4589 | 0.6598 | 0.8123 | | 0.3742 | 13.3220 | 786 | 0.6112 | 0.4261 | 0.6112 | 0.7818 | | 0.3742 | 13.3559 | 788 | 0.5781 | 0.4533 | 0.5781 | 0.7603 | | 0.3742 | 13.3898 | 790 | 0.5725 | 0.4668 | 0.5725 | 0.7566 | | 0.3742 | 13.4237 | 792 | 0.5823 | 0.4712 | 0.5823 | 0.7631 | | 0.3742 | 13.4576 | 794 | 0.5983 | 0.5122 | 0.5983 | 0.7735 | | 0.3742 | 13.4915 | 796 | 0.5988 | 0.5122 | 0.5988 | 0.7738 | | 0.3742 | 13.5254 | 798 | 0.6210 | 0.4783 | 0.6210 | 0.7881 | | 0.3742 | 13.5593 | 800 | 0.6163 | 0.4794 | 0.6163 | 0.7850 | | 0.3742 | 13.5932 | 802 | 0.5988 | 0.4531 | 0.5988 | 0.7738 | | 0.3742 | 13.6271 | 804 | 0.5855 | 0.4531 | 0.5855 | 0.7652 | | 0.3742 | 13.6610 | 806 | 0.5785 | 0.4842 | 0.5785 | 0.7606 | | 0.3742 | 13.6949 | 808 | 0.5831 | 0.4442 | 0.5831 | 0.7636 | | 0.3742 | 13.7288 | 810 | 0.5992 | 0.4839 | 0.5992 | 0.7741 | | 0.3742 | 13.7627 | 812 | 0.6030 | 0.4839 | 0.6030 | 0.7766 | | 0.3742 | 13.7966 | 814 | 0.5894 | 0.4490 | 0.5894 | 0.7677 | | 0.3742 | 13.8305 | 816 | 0.5914 | 0.4490 | 0.5914 | 0.7690 | | 0.3742 | 13.8644 | 818 | 0.5950 | 0.4490 | 0.5950 | 0.7714 | | 0.3742 | 13.8983 | 820 | 0.6106 | 0.4746 | 0.6106 | 0.7814 | | 0.3742 | 13.9322 | 822 | 0.6293 | 0.4754 | 0.6293 | 0.7933 | | 0.3742 | 13.9661 | 824 | 0.6451 | 0.4611 | 0.6451 | 0.8032 | | 0.3742 | 14.0 | 826 | 0.6494 | 0.4578 | 0.6494 | 0.8059 | | 0.3742 | 14.0339 | 828 | 0.6249 | 0.4187 | 0.6249 | 0.7905 | | 0.3742 | 14.0678 | 830 | 0.6007 | 0.4815 | 0.6007 | 0.7751 | | 0.3742 | 14.1017 | 832 | 0.6217 | 0.4193 | 0.6217 | 0.7885 | | 0.3742 | 14.1356 | 834 | 0.6424 | 0.4374 | 0.6424 | 0.8015 | | 0.3742 | 14.1695 | 836 | 0.6151 | 0.4528 | 0.6151 | 0.7843 | | 0.3742 | 14.2034 | 838 | 0.5923 | 0.5188 | 0.5923 | 0.7696 | | 0.3742 | 14.2373 | 840 | 0.6380 | 0.4634 | 0.6380 | 0.7988 | | 0.3742 | 14.2712 | 842 | 0.6802 | 0.4987 | 0.6802 | 0.8247 | | 0.3742 | 14.3051 | 844 | 0.6805 | 0.5084 | 0.6805 | 0.8249 | | 0.3742 | 14.3390 | 846 | 0.6955 | 0.4987 | 0.6955 | 0.8340 | | 0.3742 | 14.3729 | 848 | 0.6434 | 0.4605 | 0.6434 | 0.8021 | | 0.3742 | 14.4068 | 850 | 0.5940 | 0.4357 | 0.5940 | 0.7707 | | 0.3742 | 14.4407 | 852 | 0.5861 | 0.4783 | 0.5861 | 0.7655 | | 0.3742 | 14.4746 | 854 | 0.5856 | 0.4424 | 0.5856 | 0.7652 | | 0.3742 | 14.5085 | 856 | 0.6035 | 0.4516 | 0.6035 | 0.7769 | | 0.3742 | 14.5424 | 858 | 0.6451 | 0.4469 | 0.6451 | 0.8032 | | 0.3742 | 14.5763 | 860 | 0.6481 | 0.4469 | 0.6481 | 0.8051 | | 0.3742 | 14.6102 | 862 | 0.6175 | 0.4695 | 0.6175 | 0.7858 | | 0.3742 | 14.6441 | 864 | 0.5913 | 0.4909 | 0.5913 | 0.7690 | | 0.3742 | 14.6780 | 866 | 0.5823 | 0.4644 | 0.5823 | 0.7631 | | 0.3742 | 14.7119 | 868 | 0.5905 | 0.5006 | 0.5905 | 0.7684 | | 0.3742 | 14.7458 | 870 | 0.5986 | 0.4712 | 0.5986 | 0.7737 | | 0.3742 | 14.7797 | 872 | 0.5790 | 0.5181 | 0.5790 | 0.7609 | | 0.3742 | 14.8136 | 874 | 0.5746 | 0.5282 | 0.5746 | 0.7581 | | 0.3742 | 14.8475 | 876 | 0.5925 | 0.5321 | 0.5925 | 0.7697 | | 0.3742 | 14.8814 | 878 | 0.6330 | 0.4714 | 0.6330 | 0.7956 | | 0.3742 | 14.9153 | 880 | 0.6533 | 0.4895 | 0.6533 | 0.8083 | | 0.3742 | 14.9492 | 882 | 0.6274 | 0.4850 | 0.6274 | 0.7921 | | 0.3742 | 14.9831 | 884 | 0.6142 | 0.5117 | 0.6142 | 0.7837 | | 0.3742 | 15.0169 | 886 | 0.6155 | 0.5190 | 0.6155 | 0.7845 | | 0.3742 | 15.0508 | 888 | 0.6017 | 0.5472 | 0.6017 | 0.7757 | | 0.3742 | 15.0847 | 890 | 0.6124 | 0.5397 | 0.6124 | 0.7825 | | 0.3742 | 15.1186 | 892 | 0.6208 | 0.5307 | 0.6208 | 0.7879 | | 0.3742 | 15.1525 | 894 | 0.6130 | 0.5307 | 0.6130 | 0.7829 | | 0.3742 | 15.1864 | 896 | 0.6133 | 0.5307 | 0.6133 | 0.7832 | | 0.3742 | 15.2203 | 898 | 0.6103 | 0.5253 | 0.6103 | 0.7812 | | 0.3742 | 15.2542 | 900 | 0.6169 | 0.5261 | 0.6169 | 0.7854 | | 0.3742 | 15.2881 | 902 | 0.6092 | 0.5261 | 0.6092 | 0.7805 | | 0.3742 | 15.3220 | 904 | 0.6049 | 0.5144 | 0.6049 | 0.7777 | | 0.3742 | 15.3559 | 906 | 0.6190 | 0.5077 | 0.6190 | 0.7867 | | 0.3742 | 15.3898 | 908 | 0.6285 | 0.5243 | 0.6285 | 0.7928 | | 0.3742 | 15.4237 | 910 | 0.6431 | 0.5620 | 0.6431 | 0.8019 | | 0.3742 | 15.4576 | 912 | 0.6844 | 0.5057 | 0.6844 | 0.8273 | | 0.3742 | 15.4915 | 914 | 0.7018 | 0.5043 | 0.7018 | 0.8377 | | 0.3742 | 15.5254 | 916 | 0.6662 | 0.5068 | 0.6662 | 0.8162 | | 0.3742 | 15.5593 | 918 | 0.6597 | 0.5068 | 0.6597 | 0.8122 | | 0.3742 | 15.5932 | 920 | 0.6547 | 0.4884 | 0.6547 | 0.8091 | | 0.3742 | 15.6271 | 922 | 0.6340 | 0.4930 | 0.6340 | 0.7962 | | 0.3742 | 15.6610 | 924 | 0.6111 | 0.4724 | 0.6111 | 0.7817 | | 0.3742 | 15.6949 | 926 | 0.5918 | 0.4578 | 0.5918 | 0.7693 | | 0.3742 | 15.7288 | 928 | 0.5899 | 0.4816 | 0.5899 | 0.7680 | | 0.3742 | 15.7627 | 930 | 0.5993 | 0.5096 | 0.5993 | 0.7741 | | 0.3742 | 15.7966 | 932 | 0.6248 | 0.5113 | 0.6248 | 0.7904 | | 0.3742 | 15.8305 | 934 | 0.6389 | 0.5128 | 0.6389 | 0.7993 | | 0.3742 | 15.8644 | 936 | 0.6344 | 0.4857 | 0.6344 | 0.7965 | | 0.3742 | 15.8983 | 938 | 0.6210 | 0.5162 | 0.6210 | 0.7881 | | 0.3742 | 15.9322 | 940 | 0.6144 | 0.4728 | 0.6144 | 0.7838 | | 0.3742 | 15.9661 | 942 | 0.5873 | 0.3982 | 0.5873 | 0.7664 | | 0.3742 | 16.0 | 944 | 0.5795 | 0.3878 | 0.5795 | 0.7612 | | 0.3742 | 16.0339 | 946 | 0.5782 | 0.3916 | 0.5782 | 0.7604 | | 0.3742 | 16.0678 | 948 | 0.5850 | 0.4273 | 0.5850 | 0.7648 | | 0.3742 | 16.1017 | 950 | 0.5998 | 0.4724 | 0.5998 | 0.7745 | | 0.3742 | 16.1356 | 952 | 0.6271 | 0.4907 | 0.6271 | 0.7919 | | 0.3742 | 16.1695 | 954 | 0.6676 | 0.4799 | 0.6676 | 0.8171 | | 0.3742 | 16.2034 | 956 | 0.6535 | 0.4912 | 0.6535 | 0.8084 | | 0.3742 | 16.2373 | 958 | 0.6461 | 0.4924 | 0.6461 | 0.8038 | | 0.3742 | 16.2712 | 960 | 0.6468 | 0.5076 | 0.6468 | 0.8042 | | 0.3742 | 16.3051 | 962 | 0.6233 | 0.4960 | 0.6233 | 0.7895 | | 0.3742 | 16.3390 | 964 | 0.6155 | 0.4390 | 0.6155 | 0.7845 | | 0.3742 | 16.3729 | 966 | 0.6053 | 0.4183 | 0.6053 | 0.7780 | | 0.3742 | 16.4068 | 968 | 0.5959 | 0.4289 | 0.5959 | 0.7720 | | 0.3742 | 16.4407 | 970 | 0.5892 | 0.3992 | 0.5892 | 0.7676 | | 0.3742 | 16.4746 | 972 | 0.5878 | 0.3750 | 0.5878 | 0.7667 | | 0.3742 | 16.5085 | 974 | 0.5987 | 0.4088 | 0.5987 | 0.7737 | | 0.3742 | 16.5424 | 976 | 0.6297 | 0.4046 | 0.6297 | 0.7936 | | 0.3742 | 16.5763 | 978 | 0.7015 | 0.4426 | 0.7015 | 0.8376 | | 0.3742 | 16.6102 | 980 | 0.7986 | 0.4345 | 0.7986 | 0.8936 | | 0.3742 | 16.6441 | 982 | 0.8505 | 0.4530 | 0.8505 | 0.9223 | | 0.3742 | 16.6780 | 984 | 0.8661 | 0.4522 | 0.8661 | 0.9307 | | 0.3742 | 16.7119 | 986 | 0.8286 | 0.4633 | 0.8286 | 0.9103 | | 0.3742 | 16.7458 | 988 | 0.7841 | 0.4441 | 0.7841 | 0.8855 | | 0.3742 | 16.7797 | 990 | 0.7511 | 0.4337 | 0.7511 | 0.8666 | | 0.3742 | 16.8136 | 992 | 0.6991 | 0.4381 | 0.6991 | 0.8361 | | 0.3742 | 16.8475 | 994 | 0.6421 | 0.4324 | 0.6421 | 0.8013 | | 0.3742 | 16.8814 | 996 | 0.6367 | 0.4515 | 0.6367 | 0.7980 | | 0.3742 | 16.9153 | 998 | 0.6562 | 0.4381 | 0.6562 | 0.8101 | | 0.0688 | 16.9492 | 1000 | 0.6999 | 0.4568 | 0.6999 | 0.8366 | | 0.0688 | 16.9831 | 1002 | 0.7397 | 0.4731 | 0.7397 | 0.8600 | | 0.0688 | 17.0169 | 1004 | 0.7376 | 0.4731 | 0.7376 | 0.8589 | | 0.0688 | 17.0508 | 1006 | 0.6975 | 0.4690 | 0.6975 | 0.8352 | | 0.0688 | 17.0847 | 1008 | 0.6399 | 0.4837 | 0.6399 | 0.7999 | | 0.0688 | 17.1186 | 1010 | 0.6059 | 0.4539 | 0.6059 | 0.7784 | | 0.0688 | 17.1525 | 1012 | 0.6169 | 0.4515 | 0.6169 | 0.7855 | | 0.0688 | 17.1864 | 1014 | 0.6328 | 0.4548 | 0.6328 | 0.7955 | | 0.0688 | 17.2203 | 1016 | 0.6471 | 0.4668 | 0.6471 | 0.8044 | | 0.0688 | 17.2542 | 1018 | 0.6186 | 0.4455 | 0.6186 | 0.7865 | | 0.0688 | 17.2881 | 1020 | 0.5951 | 0.4805 | 0.5951 | 0.7714 | | 0.0688 | 17.3220 | 1022 | 0.6025 | 0.4704 | 0.6025 | 0.7762 | | 0.0688 | 17.3559 | 1024 | 0.6019 | 0.4794 | 0.6019 | 0.7758 | | 0.0688 | 17.3898 | 1026 | 0.5891 | 0.4857 | 0.5891 | 0.7676 | | 0.0688 | 17.4237 | 1028 | 0.5924 | 0.4857 | 0.5924 | 0.7697 | | 0.0688 | 17.4576 | 1030 | 0.6075 | 0.4921 | 0.6075 | 0.7794 | | 0.0688 | 17.4915 | 1032 | 0.6063 | 0.4857 | 0.6063 | 0.7786 | | 0.0688 | 17.5254 | 1034 | 0.6025 | 0.4950 | 0.6025 | 0.7762 | | 0.0688 | 17.5593 | 1036 | 0.6076 | 0.5289 | 0.6076 | 0.7795 | | 0.0688 | 17.5932 | 1038 | 0.6015 | 0.5006 | 0.6015 | 0.7755 | | 0.0688 | 17.6271 | 1040 | 0.5847 | 0.4514 | 0.5847 | 0.7647 | | 0.0688 | 17.6610 | 1042 | 0.5782 | 0.4614 | 0.5782 | 0.7604 | | 0.0688 | 17.6949 | 1044 | 0.5890 | 0.4603 | 0.5890 | 0.7675 | | 0.0688 | 17.7288 | 1046 | 0.6114 | 0.4637 | 0.6114 | 0.7820 | | 0.0688 | 17.7627 | 1048 | 0.6075 | 0.4637 | 0.6075 | 0.7794 | | 0.0688 | 17.7966 | 1050 | 0.5894 | 0.4521 | 0.5894 | 0.7677 | | 0.0688 | 17.8305 | 1052 | 0.5982 | 0.5384 | 0.5982 | 0.7734 | | 0.0688 | 17.8644 | 1054 | 0.6251 | 0.4824 | 0.6251 | 0.7907 | | 0.0688 | 17.8983 | 1056 | 0.6211 | 0.5060 | 0.6211 | 0.7881 | | 0.0688 | 17.9322 | 1058 | 0.6035 | 0.5103 | 0.6035 | 0.7769 | | 0.0688 | 17.9661 | 1060 | 0.5846 | 0.5630 | 0.5846 | 0.7646 | | 0.0688 | 18.0 | 1062 | 0.5784 | 0.5507 | 0.5784 | 0.7605 | | 0.0688 | 18.0339 | 1064 | 0.5922 | 0.4958 | 0.5922 | 0.7695 | | 0.0688 | 18.0678 | 1066 | 0.5961 | 0.4779 | 0.5961 | 0.7721 | | 0.0688 | 18.1017 | 1068 | 0.5831 | 0.5146 | 0.5831 | 0.7636 | | 0.0688 | 18.1356 | 1070 | 0.5780 | 0.5843 | 0.5780 | 0.7602 | | 0.0688 | 18.1695 | 1072 | 0.5770 | 0.5842 | 0.5770 | 0.7596 | | 0.0688 | 18.2034 | 1074 | 0.5695 | 0.5493 | 0.5695 | 0.7547 | | 0.0688 | 18.2373 | 1076 | 0.5642 | 0.5012 | 0.5642 | 0.7511 | | 0.0688 | 18.2712 | 1078 | 0.5862 | 0.4769 | 0.5862 | 0.7657 | | 0.0688 | 18.3051 | 1080 | 0.6085 | 0.4507 | 0.6085 | 0.7800 | | 0.0688 | 18.3390 | 1082 | 0.6239 | 0.4434 | 0.6239 | 0.7898 | | 0.0688 | 18.3729 | 1084 | 0.6444 | 0.4427 | 0.6444 | 0.8028 | | 0.0688 | 18.4068 | 1086 | 0.6201 | 0.4787 | 0.6200 | 0.7874 | | 0.0688 | 18.4407 | 1088 | 0.5929 | 0.4999 | 0.5929 | 0.7700 | | 0.0688 | 18.4746 | 1090 | 0.5672 | 0.5347 | 0.5672 | 0.7531 | | 0.0688 | 18.5085 | 1092 | 0.5631 | 0.5718 | 0.5631 | 0.7504 | | 0.0688 | 18.5424 | 1094 | 0.5755 | 0.5815 | 0.5755 | 0.7586 | | 0.0688 | 18.5763 | 1096 | 0.5859 | 0.5676 | 0.5859 | 0.7654 | | 0.0688 | 18.6102 | 1098 | 0.6115 | 0.5712 | 0.6115 | 0.7820 | | 0.0688 | 18.6441 | 1100 | 0.6229 | 0.5640 | 0.6229 | 0.7892 | | 0.0688 | 18.6780 | 1102 | 0.6227 | 0.5860 | 0.6227 | 0.7891 | | 0.0688 | 18.7119 | 1104 | 0.6254 | 0.624 | 0.6254 | 0.7908 | | 0.0688 | 18.7458 | 1106 | 0.6341 | 0.5816 | 0.6341 | 0.7963 | | 0.0688 | 18.7797 | 1108 | 0.6333 | 0.5816 | 0.6333 | 0.7958 | | 0.0688 | 18.8136 | 1110 | 0.6140 | 0.5953 | 0.6140 | 0.7836 | | 0.0688 | 18.8475 | 1112 | 0.6343 | 0.5281 | 0.6343 | 0.7964 | | 0.0688 | 18.8814 | 1114 | 0.7013 | 0.5125 | 0.7013 | 0.8374 | | 0.0688 | 18.9153 | 1116 | 0.7885 | 0.4590 | 0.7885 | 0.8880 | | 0.0688 | 18.9492 | 1118 | 0.7920 | 0.4267 | 0.7920 | 0.8899 | | 0.0688 | 18.9831 | 1120 | 0.7500 | 0.4846 | 0.7500 | 0.8660 | | 0.0688 | 19.0169 | 1122 | 0.6853 | 0.4687 | 0.6853 | 0.8278 | | 0.0688 | 19.0508 | 1124 | 0.6170 | 0.4815 | 0.6170 | 0.7855 | | 0.0688 | 19.0847 | 1126 | 0.5854 | 0.5642 | 0.5854 | 0.7651 | | 0.0688 | 19.1186 | 1128 | 0.5962 | 0.5682 | 0.5962 | 0.7722 | | 0.0688 | 19.1525 | 1130 | 0.6283 | 0.5178 | 0.6283 | 0.7927 | | 0.0688 | 19.1864 | 1132 | 0.7183 | 0.4982 | 0.7183 | 0.8475 | | 0.0688 | 19.2203 | 1134 | 0.7741 | 0.5055 | 0.7741 | 0.8798 | | 0.0688 | 19.2542 | 1136 | 0.7745 | 0.5055 | 0.7745 | 0.8801 | | 0.0688 | 19.2881 | 1138 | 0.7280 | 0.5296 | 0.7280 | 0.8532 | | 0.0688 | 19.3220 | 1140 | 0.6471 | 0.5198 | 0.6471 | 0.8044 | | 0.0688 | 19.3559 | 1142 | 0.6004 | 0.4655 | 0.6004 | 0.7748 | | 0.0688 | 19.3898 | 1144 | 0.5858 | 0.4641 | 0.5858 | 0.7654 | | 0.0688 | 19.4237 | 1146 | 0.6048 | 0.4508 | 0.6048 | 0.7777 | | 0.0688 | 19.4576 | 1148 | 0.6611 | 0.5034 | 0.6611 | 0.8131 | | 0.0688 | 19.4915 | 1150 | 0.7651 | 0.4846 | 0.7651 | 0.8747 | | 0.0688 | 19.5254 | 1152 | 0.8086 | 0.4871 | 0.8086 | 0.8992 | | 0.0688 | 19.5593 | 1154 | 0.7747 | 0.4835 | 0.7747 | 0.8802 | | 0.0688 | 19.5932 | 1156 | 0.7153 | 0.5034 | 0.7153 | 0.8458 | | 0.0688 | 19.6271 | 1158 | 0.6538 | 0.4515 | 0.6538 | 0.8086 | | 0.0688 | 19.6610 | 1160 | 0.6188 | 0.5033 | 0.6188 | 0.7866 | | 0.0688 | 19.6949 | 1162 | 0.5943 | 0.5434 | 0.5943 | 0.7709 | | 0.0688 | 19.7288 | 1164 | 0.5820 | 0.5768 | 0.5820 | 0.7629 | | 0.0688 | 19.7627 | 1166 | 0.5688 | 0.5165 | 0.5688 | 0.7542 | | 0.0688 | 19.7966 | 1168 | 0.5513 | 0.5440 | 0.5513 | 0.7425 | | 0.0688 | 19.8305 | 1170 | 0.5548 | 0.5284 | 0.5548 | 0.7449 | | 0.0688 | 19.8644 | 1172 | 0.5588 | 0.5148 | 0.5588 | 0.7475 | | 0.0688 | 19.8983 | 1174 | 0.5786 | 0.4564 | 0.5786 | 0.7607 | | 0.0688 | 19.9322 | 1176 | 0.5941 | 0.4434 | 0.5941 | 0.7708 | | 0.0688 | 19.9661 | 1178 | 0.6011 | 0.4434 | 0.6011 | 0.7753 | | 0.0688 | 20.0 | 1180 | 0.5806 | 0.4630 | 0.5806 | 0.7620 | | 0.0688 | 20.0339 | 1182 | 0.5661 | 0.4409 | 0.5661 | 0.7524 | | 0.0688 | 20.0678 | 1184 | 0.5504 | 0.4853 | 0.5504 | 0.7419 | | 0.0688 | 20.1017 | 1186 | 0.5375 | 0.5291 | 0.5375 | 0.7332 | | 0.0688 | 20.1356 | 1188 | 0.5358 | 0.5697 | 0.5358 | 0.7320 | | 0.0688 | 20.1695 | 1190 | 0.5576 | 0.4783 | 0.5576 | 0.7467 | | 0.0688 | 20.2034 | 1192 | 0.5614 | 0.4691 | 0.5614 | 0.7493 | | 0.0688 | 20.2373 | 1194 | 0.5652 | 0.5397 | 0.5652 | 0.7518 | | 0.0688 | 20.2712 | 1196 | 0.5930 | 0.4932 | 0.5930 | 0.7701 | | 0.0688 | 20.3051 | 1198 | 0.6207 | 0.5158 | 0.6207 | 0.7879 | | 0.0688 | 20.3390 | 1200 | 0.6107 | 0.4754 | 0.6107 | 0.7815 | | 0.0688 | 20.3729 | 1202 | 0.5663 | 0.5121 | 0.5663 | 0.7526 | | 0.0688 | 20.4068 | 1204 | 0.5480 | 0.4630 | 0.5480 | 0.7403 | | 0.0688 | 20.4407 | 1206 | 0.5471 | 0.4723 | 0.5471 | 0.7397 | | 0.0688 | 20.4746 | 1208 | 0.5466 | 0.4900 | 0.5466 | 0.7394 | | 0.0688 | 20.5085 | 1210 | 0.5494 | 0.5188 | 0.5494 | 0.7412 | | 0.0688 | 20.5424 | 1212 | 0.5928 | 0.4833 | 0.5928 | 0.7700 | | 0.0688 | 20.5763 | 1214 | 0.7070 | 0.4776 | 0.7070 | 0.8408 | | 0.0688 | 20.6102 | 1216 | 0.8177 | 0.4908 | 0.8177 | 0.9043 | | 0.0688 | 20.6441 | 1218 | 0.8847 | 0.4728 | 0.8847 | 0.9406 | | 0.0688 | 20.6780 | 1220 | 0.8832 | 0.4851 | 0.8832 | 0.9398 | | 0.0688 | 20.7119 | 1222 | 0.8152 | 0.4701 | 0.8152 | 0.9029 | | 0.0688 | 20.7458 | 1224 | 0.7643 | 0.4739 | 0.7643 | 0.8743 | | 0.0688 | 20.7797 | 1226 | 0.7091 | 0.4809 | 0.7091 | 0.8421 | | 0.0688 | 20.8136 | 1228 | 0.6890 | 0.5062 | 0.6890 | 0.8300 | | 0.0688 | 20.8475 | 1230 | 0.6909 | 0.5046 | 0.6909 | 0.8312 | | 0.0688 | 20.8814 | 1232 | 0.6553 | 0.5362 | 0.6553 | 0.8095 | | 0.0688 | 20.9153 | 1234 | 0.6212 | 0.5441 | 0.6212 | 0.7882 | | 0.0688 | 20.9492 | 1236 | 0.5811 | 0.5663 | 0.5811 | 0.7623 | | 0.0688 | 20.9831 | 1238 | 0.5607 | 0.5851 | 0.5607 | 0.7488 | | 0.0688 | 21.0169 | 1240 | 0.5425 | 0.5547 | 0.5425 | 0.7366 | | 0.0688 | 21.0508 | 1242 | 0.5343 | 0.5506 | 0.5343 | 0.7309 | | 0.0688 | 21.0847 | 1244 | 0.5425 | 0.5668 | 0.5425 | 0.7365 | | 0.0688 | 21.1186 | 1246 | 0.5700 | 0.5725 | 0.5700 | 0.7550 | | 0.0688 | 21.1525 | 1248 | 0.5868 | 0.5463 | 0.5868 | 0.7660 | | 0.0688 | 21.1864 | 1250 | 0.6167 | 0.5310 | 0.6167 | 0.7853 | | 0.0688 | 21.2203 | 1252 | 0.6533 | 0.5103 | 0.6533 | 0.8083 | | 0.0688 | 21.2542 | 1254 | 0.6629 | 0.5020 | 0.6629 | 0.8142 | | 0.0688 | 21.2881 | 1256 | 0.6226 | 0.5072 | 0.6226 | 0.7890 | | 0.0688 | 21.3220 | 1258 | 0.5886 | 0.4794 | 0.5886 | 0.7672 | | 0.0688 | 21.3559 | 1260 | 0.5911 | 0.4552 | 0.5911 | 0.7688 | | 0.0688 | 21.3898 | 1262 | 0.6194 | 0.5087 | 0.6194 | 0.7870 | | 0.0688 | 21.4237 | 1264 | 0.6461 | 0.4987 | 0.6461 | 0.8038 | | 0.0688 | 21.4576 | 1266 | 0.6607 | 0.4901 | 0.6607 | 0.8128 | | 0.0688 | 21.4915 | 1268 | 0.6342 | 0.5242 | 0.6342 | 0.7964 | | 0.0688 | 21.5254 | 1270 | 0.5914 | 0.4973 | 0.5914 | 0.7690 | | 0.0688 | 21.5593 | 1272 | 0.5663 | 0.5539 | 0.5663 | 0.7525 | | 0.0688 | 21.5932 | 1274 | 0.5573 | 0.5610 | 0.5573 | 0.7465 | | 0.0688 | 21.6271 | 1276 | 0.5555 | 0.5717 | 0.5555 | 0.7453 | | 0.0688 | 21.6610 | 1278 | 0.5593 | 0.5378 | 0.5593 | 0.7479 | | 0.0688 | 21.6949 | 1280 | 0.5734 | 0.4978 | 0.5734 | 0.7572 | | 0.0688 | 21.7288 | 1282 | 0.5807 | 0.4721 | 0.5807 | 0.7620 | | 0.0688 | 21.7627 | 1284 | 0.5672 | 0.4709 | 0.5672 | 0.7531 | | 0.0688 | 21.7966 | 1286 | 0.5683 | 0.4320 | 0.5683 | 0.7539 | | 0.0688 | 21.8305 | 1288 | 0.5905 | 0.4662 | 0.5905 | 0.7685 | | 0.0688 | 21.8644 | 1290 | 0.6337 | 0.4665 | 0.6337 | 0.7960 | | 0.0688 | 21.8983 | 1292 | 0.6521 | 0.4804 | 0.6521 | 0.8075 | | 0.0688 | 21.9322 | 1294 | 0.6474 | 0.4804 | 0.6474 | 0.8046 | | 0.0688 | 21.9661 | 1296 | 0.6005 | 0.4733 | 0.6005 | 0.7749 | | 0.0688 | 22.0 | 1298 | 0.5691 | 0.5216 | 0.5691 | 0.7544 | | 0.0688 | 22.0339 | 1300 | 0.5630 | 0.5403 | 0.5630 | 0.7503 | | 0.0688 | 22.0678 | 1302 | 0.5609 | 0.5100 | 0.5609 | 0.7490 | | 0.0688 | 22.1017 | 1304 | 0.5585 | 0.5293 | 0.5585 | 0.7473 | | 0.0688 | 22.1356 | 1306 | 0.5707 | 0.5064 | 0.5707 | 0.7554 | | 0.0688 | 22.1695 | 1308 | 0.5908 | 0.4787 | 0.5908 | 0.7686 | | 0.0688 | 22.2034 | 1310 | 0.5947 | 0.4539 | 0.5947 | 0.7712 | | 0.0688 | 22.2373 | 1312 | 0.6004 | 0.4684 | 0.6004 | 0.7748 | | 0.0688 | 22.2712 | 1314 | 0.5847 | 0.4705 | 0.5847 | 0.7646 | | 0.0688 | 22.3051 | 1316 | 0.5579 | 0.5486 | 0.5579 | 0.7470 | | 0.0688 | 22.3390 | 1318 | 0.5393 | 0.5650 | 0.5393 | 0.7344 | | 0.0688 | 22.3729 | 1320 | 0.5435 | 0.5733 | 0.5435 | 0.7373 | | 0.0688 | 22.4068 | 1322 | 0.5754 | 0.5351 | 0.5754 | 0.7586 | | 0.0688 | 22.4407 | 1324 | 0.6354 | 0.5072 | 0.6354 | 0.7971 | | 0.0688 | 22.4746 | 1326 | 0.6615 | 0.5405 | 0.6615 | 0.8133 | | 0.0688 | 22.5085 | 1328 | 0.6477 | 0.5132 | 0.6477 | 0.8048 | | 0.0688 | 22.5424 | 1330 | 0.6418 | 0.5087 | 0.6418 | 0.8011 | | 0.0688 | 22.5763 | 1332 | 0.6095 | 0.4804 | 0.6095 | 0.7807 | | 0.0688 | 22.6102 | 1334 | 0.5686 | 0.5027 | 0.5686 | 0.7540 | | 0.0688 | 22.6441 | 1336 | 0.5534 | 0.5537 | 0.5534 | 0.7439 | | 0.0688 | 22.6780 | 1338 | 0.5521 | 0.5605 | 0.5521 | 0.7430 | | 0.0688 | 22.7119 | 1340 | 0.5485 | 0.5288 | 0.5485 | 0.7406 | | 0.0688 | 22.7458 | 1342 | 0.5557 | 0.5943 | 0.5557 | 0.7454 | | 0.0688 | 22.7797 | 1344 | 0.5639 | 0.5943 | 0.5639 | 0.7509 | | 0.0688 | 22.8136 | 1346 | 0.5736 | 0.5879 | 0.5736 | 0.7574 | | 0.0688 | 22.8475 | 1348 | 0.5728 | 0.5881 | 0.5728 | 0.7568 | | 0.0688 | 22.8814 | 1350 | 0.5684 | 0.5602 | 0.5684 | 0.7539 | | 0.0688 | 22.9153 | 1352 | 0.5604 | 0.5692 | 0.5604 | 0.7486 | | 0.0688 | 22.9492 | 1354 | 0.5632 | 0.5428 | 0.5632 | 0.7504 | | 0.0688 | 22.9831 | 1356 | 0.5759 | 0.5333 | 0.5759 | 0.7589 | | 0.0688 | 23.0169 | 1358 | 0.5763 | 0.5121 | 0.5763 | 0.7592 | | 0.0688 | 23.0508 | 1360 | 0.5853 | 0.5048 | 0.5853 | 0.7650 | | 0.0688 | 23.0847 | 1362 | 0.5941 | 0.5048 | 0.5941 | 0.7708 | | 0.0688 | 23.1186 | 1364 | 0.6011 | 0.5048 | 0.6011 | 0.7753 | | 0.0688 | 23.1525 | 1366 | 0.5912 | 0.4788 | 0.5912 | 0.7689 | | 0.0688 | 23.1864 | 1368 | 0.5868 | 0.5056 | 0.5868 | 0.7660 | | 0.0688 | 23.2203 | 1370 | 0.5868 | 0.5006 | 0.5868 | 0.7660 | | 0.0688 | 23.2542 | 1372 | 0.5740 | 0.5130 | 0.5740 | 0.7576 | | 0.0688 | 23.2881 | 1374 | 0.5735 | 0.5570 | 0.5735 | 0.7573 | | 0.0688 | 23.3220 | 1376 | 0.5803 | 0.5866 | 0.5803 | 0.7618 | | 0.0688 | 23.3559 | 1378 | 0.5817 | 0.5751 | 0.5817 | 0.7627 | | 0.0688 | 23.3898 | 1380 | 0.5733 | 0.6093 | 0.5733 | 0.7572 | | 0.0688 | 23.4237 | 1382 | 0.5714 | 0.5628 | 0.5714 | 0.7559 | | 0.0688 | 23.4576 | 1384 | 0.5765 | 0.5693 | 0.5765 | 0.7593 | | 0.0688 | 23.4915 | 1386 | 0.5940 | 0.5312 | 0.5940 | 0.7707 | | 0.0688 | 23.5254 | 1388 | 0.5898 | 0.5391 | 0.5898 | 0.7680 | | 0.0688 | 23.5593 | 1390 | 0.5604 | 0.5536 | 0.5604 | 0.7486 | | 0.0688 | 23.5932 | 1392 | 0.5415 | 0.5122 | 0.5415 | 0.7359 | | 0.0688 | 23.6271 | 1394 | 0.5371 | 0.5524 | 0.5371 | 0.7329 | | 0.0688 | 23.6610 | 1396 | 0.5521 | 0.5409 | 0.5521 | 0.7430 | | 0.0688 | 23.6949 | 1398 | 0.5866 | 0.4890 | 0.5866 | 0.7659 | | 0.0688 | 23.7288 | 1400 | 0.5892 | 0.4928 | 0.5892 | 0.7676 | | 0.0688 | 23.7627 | 1402 | 0.5736 | 0.5161 | 0.5736 | 0.7574 | | 0.0688 | 23.7966 | 1404 | 0.5752 | 0.5025 | 0.5752 | 0.7584 | | 0.0688 | 23.8305 | 1406 | 0.5832 | 0.4822 | 0.5832 | 0.7637 | | 0.0688 | 23.8644 | 1408 | 0.5855 | 0.4984 | 0.5855 | 0.7652 | | 0.0688 | 23.8983 | 1410 | 0.5871 | 0.5427 | 0.5871 | 0.7662 | | 0.0688 | 23.9322 | 1412 | 0.5939 | 0.5655 | 0.5939 | 0.7706 | | 0.0688 | 23.9661 | 1414 | 0.6054 | 0.5867 | 0.6054 | 0.7781 | | 0.0688 | 24.0 | 1416 | 0.6241 | 0.5416 | 0.6241 | 0.7900 | | 0.0688 | 24.0339 | 1418 | 0.6045 | 0.5512 | 0.6045 | 0.7775 | | 0.0688 | 24.0678 | 1420 | 0.5856 | 0.5666 | 0.5856 | 0.7652 | | 0.0688 | 24.1017 | 1422 | 0.5793 | 0.5323 | 0.5793 | 0.7611 | | 0.0688 | 24.1356 | 1424 | 0.5948 | 0.4985 | 0.5948 | 0.7712 | | 0.0688 | 24.1695 | 1426 | 0.6258 | 0.4787 | 0.6258 | 0.7911 | | 0.0688 | 24.2034 | 1428 | 0.6753 | 0.4585 | 0.6753 | 0.8217 | | 0.0688 | 24.2373 | 1430 | 0.7012 | 0.4585 | 0.7012 | 0.8374 | | 0.0688 | 24.2712 | 1432 | 0.7137 | 0.4337 | 0.7137 | 0.8448 | | 0.0688 | 24.3051 | 1434 | 0.7110 | 0.4337 | 0.7110 | 0.8432 | | 0.0688 | 24.3390 | 1436 | 0.7173 | 0.4337 | 0.7173 | 0.8470 | | 0.0688 | 24.3729 | 1438 | 0.7320 | 0.4780 | 0.7320 | 0.8556 | | 0.0688 | 24.4068 | 1440 | 0.7503 | 0.4620 | 0.7503 | 0.8662 | | 0.0688 | 24.4407 | 1442 | 0.7398 | 0.4824 | 0.7398 | 0.8601 | | 0.0688 | 24.4746 | 1444 | 0.7525 | 0.4813 | 0.7525 | 0.8674 | | 0.0688 | 24.5085 | 1446 | 0.7133 | 0.4668 | 0.7133 | 0.8446 | | 0.0688 | 24.5424 | 1448 | 0.6904 | 0.4707 | 0.6904 | 0.8309 | | 0.0688 | 24.5763 | 1450 | 0.6765 | 0.4798 | 0.6765 | 0.8225 | | 0.0688 | 24.6102 | 1452 | 0.6908 | 0.4798 | 0.6908 | 0.8312 | | 0.0688 | 24.6441 | 1454 | 0.7249 | 0.4898 | 0.7249 | 0.8514 | | 0.0688 | 24.6780 | 1456 | 0.7405 | 0.4772 | 0.7405 | 0.8605 | | 0.0688 | 24.7119 | 1458 | 0.7419 | 0.4581 | 0.7419 | 0.8613 | | 0.0688 | 24.7458 | 1460 | 0.7254 | 0.4749 | 0.7254 | 0.8517 | | 0.0688 | 24.7797 | 1462 | 0.6696 | 0.5260 | 0.6696 | 0.8183 | | 0.0688 | 24.8136 | 1464 | 0.6295 | 0.5377 | 0.6295 | 0.7934 | | 0.0688 | 24.8475 | 1466 | 0.6306 | 0.5589 | 0.6306 | 0.7941 | | 0.0688 | 24.8814 | 1468 | 0.6366 | 0.5589 | 0.6366 | 0.7979 | | 0.0688 | 24.9153 | 1470 | 0.6203 | 0.5798 | 0.6203 | 0.7876 | | 0.0688 | 24.9492 | 1472 | 0.6111 | 0.5838 | 0.6111 | 0.7817 | | 0.0688 | 24.9831 | 1474 | 0.5983 | 0.5991 | 0.5983 | 0.7735 | | 0.0688 | 25.0169 | 1476 | 0.5922 | 0.5768 | 0.5922 | 0.7695 | | 0.0688 | 25.0508 | 1478 | 0.6087 | 0.5650 | 0.6087 | 0.7802 | | 0.0688 | 25.0847 | 1480 | 0.6378 | 0.5006 | 0.6378 | 0.7986 | | 0.0688 | 25.1186 | 1482 | 0.6557 | 0.5090 | 0.6557 | 0.8097 | | 0.0688 | 25.1525 | 1484 | 0.6557 | 0.5238 | 0.6557 | 0.8098 | | 0.0688 | 25.1864 | 1486 | 0.6671 | 0.5388 | 0.6671 | 0.8167 | | 0.0688 | 25.2203 | 1488 | 0.6794 | 0.5512 | 0.6794 | 0.8243 | | 0.0688 | 25.2542 | 1490 | 0.6946 | 0.4657 | 0.6946 | 0.8334 | | 0.0688 | 25.2881 | 1492 | 0.6945 | 0.4412 | 0.6945 | 0.8334 | | 0.0688 | 25.3220 | 1494 | 0.6800 | 0.4257 | 0.6800 | 0.8246 | | 0.0688 | 25.3559 | 1496 | 0.6585 | 0.4452 | 0.6585 | 0.8115 | | 0.0688 | 25.3898 | 1498 | 0.6735 | 0.4751 | 0.6735 | 0.8207 | | 0.051 | 25.4237 | 1500 | 0.7019 | 0.5156 | 0.7019 | 0.8378 | | 0.051 | 25.4576 | 1502 | 0.7023 | 0.5465 | 0.7023 | 0.8380 | | 0.051 | 25.4915 | 1504 | 0.6540 | 0.5178 | 0.6540 | 0.8087 | | 0.051 | 25.5254 | 1506 | 0.5986 | 0.5472 | 0.5986 | 0.7737 | | 0.051 | 25.5593 | 1508 | 0.5904 | 0.6104 | 0.5904 | 0.7684 | | 0.051 | 25.5932 | 1510 | 0.5842 | 0.6043 | 0.5842 | 0.7644 | | 0.051 | 25.6271 | 1512 | 0.5952 | 0.6099 | 0.5952 | 0.7715 | | 0.051 | 25.6610 | 1514 | 0.6068 | 0.5820 | 0.6068 | 0.7790 | | 0.051 | 25.6949 | 1516 | 0.6090 | 0.5472 | 0.6090 | 0.7804 | | 0.051 | 25.7288 | 1518 | 0.5929 | 0.5490 | 0.5929 | 0.7700 | | 0.051 | 25.7627 | 1520 | 0.5754 | 0.5605 | 0.5754 | 0.7585 | | 0.051 | 25.7966 | 1522 | 0.5611 | 0.5487 | 0.5611 | 0.7491 | | 0.051 | 25.8305 | 1524 | 0.5637 | 0.5397 | 0.5637 | 0.7508 | | 0.051 | 25.8644 | 1526 | 0.5930 | 0.5563 | 0.5930 | 0.7701 | | 0.051 | 25.8983 | 1528 | 0.6057 | 0.5521 | 0.6057 | 0.7783 | | 0.051 | 25.9322 | 1530 | 0.6095 | 0.5440 | 0.6095 | 0.7807 | | 0.051 | 25.9661 | 1532 | 0.5898 | 0.5536 | 0.5898 | 0.7680 | | 0.051 | 26.0 | 1534 | 0.5781 | 0.5428 | 0.5781 | 0.7604 | | 0.051 | 26.0339 | 1536 | 0.5740 | 0.4951 | 0.5740 | 0.7577 | | 0.051 | 26.0678 | 1538 | 0.5802 | 0.5013 | 0.5802 | 0.7617 | | 0.051 | 26.1017 | 1540 | 0.5976 | 0.5069 | 0.5976 | 0.7730 | | 0.051 | 26.1356 | 1542 | 0.6146 | 0.5257 | 0.6146 | 0.7839 | | 0.051 | 26.1695 | 1544 | 0.6260 | 0.5303 | 0.6260 | 0.7912 | | 0.051 | 26.2034 | 1546 | 0.6064 | 0.5257 | 0.6064 | 0.7787 | | 0.051 | 26.2373 | 1548 | 0.5797 | 0.5048 | 0.5797 | 0.7614 | | 0.051 | 26.2712 | 1550 | 0.5579 | 0.4658 | 0.5579 | 0.7469 | | 0.051 | 26.3051 | 1552 | 0.5481 | 0.4807 | 0.5481 | 0.7403 | | 0.051 | 26.3390 | 1554 | 0.5522 | 0.4847 | 0.5522 | 0.7431 | | 0.051 | 26.3729 | 1556 | 0.5617 | 0.4874 | 0.5617 | 0.7495 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

pepijn223/phrivi-finetuned

pepijn223

2025-01-15T16:08:49Z

53

0

transformers

[ "transformers", "tensorboard", "safetensors", "paligemma", "image-text-to-text", "generated_from_trainer", "base_model:google/paligemma-3b-pt-224", "base_model:finetune:google/paligemma-3b-pt-224", "license:gemma", "text-generation-inference", "endpoints_compatible", "region:us" ]

image-text-to-text

2025-01-09T16:54:17Z

--- library_name: transformers license: gemma base_model: google/paligemma-3b-pt-224 tags: - generated_from_trainer model-index: - name: phrivi-finetuned results: [] ---  # phrivi-finetuned This model is a fine-tuned version of [google/paligemma-3b-pt-224](https://huggingface.co/google/paligemma-3b-pt-224) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 2 - num_epochs: 1 ### Training results ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0

nbninh/fbc7e776-e353-4000-a7aa-e8927900b5ed

nbninh

2025-01-15T16:08:41Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:09:23Z

--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: fbc7e776-e353-4000-a7aa-e8927900b5ed results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nbninh/fbc7e776-e353-4000-a7aa-e8927900b5ed hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <|eot_id|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # fbc7e776-e353-4000-a7aa-e8927900b5ed This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1869 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.1759 | 0.0109 | 200 | 1.1869 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

akhooli/setfit_ar_hs_mb

akhooli

2025-01-15T16:07:49Z

9

0

setfit

[ "setfit", "safetensors", "modernbert", "sentence-transformers", "text-classification", "generated_from_setfit_trainer", "arxiv:2209.11055", "base_model:akhooli/sbert-nli-500k-triplets-MB", "base_model:finetune:akhooli/sbert-nli-500k-triplets-MB", "model-index", "region:us" ]

text-classification

2025-01-15T16:07:32Z

--- tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer widget: - text: يا حاقد ع الاسلام السياسي - text: 'بلد مخيف، صار القتل بحجه الشرف متل قتل بعوضة، واللي بيخوف اكتر من اللي واقف مكتف ايديه ومش مساعد. وين كنآ، ووين وصلنآ، لمتى حنضل عايشين وساكتين! ' - text: "من خلال المتابعة ..يتضح أن أكثر اللاعبين الذين يتم تسويقهم هم لاعبي امريكا\ \ الجنوبية وأقلهم الافارقة. \nمن خلال الواقع ..أكثر اللاعبين تهاونا ولعب على\ \ الواقف في آخر ٦ شهور من عقودهم هم لاعبي امريكا الجنوبية ." - text: ' علم الحزب يا فهمانه ما حطوا لانه عم يحكي وطنيا ومشان ماحدا متلك يعترض. اذا حطوا بتعترضي واذا ما حطوا كمان بتعترضي.' - text: "شيوعي \nعلماني \nمسيحي\nانصار سنه \nصوفي \nيمثلك التجمع \nلا يمثلك التجمع\ \ \nاهلا بكم جميعا فنحن نريد بناء وطن ❤" metrics: - accuracy pipeline_tag: text-classification library_name: setfit inference: true base_model: akhooli/sbert-nli-500k-triplets-MB model-index: - name: SetFit with akhooli/sbert-nli-500k-triplets-MB results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 0.7956709956709956 name: Accuracy --- # SetFit with akhooli/sbert-nli-500k-triplets-MB This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [akhooli/sbert-nli-500k-triplets-MB](https://huggingface.co/akhooli/sbert-nli-500k-triplets-MB) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - **Model Type:** SetFit - **Sentence Transformer body:** [akhooli/sbert-nli-500k-triplets-MB](https://huggingface.co/akhooli/sbert-nli-500k-triplets-MB) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 8192 tokens - **Number of Classes:** 2 classes    ### Model Sources - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels | Label | Examples | |:---------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | positive | <ul><li>' سبحان الله الفلسطينيين شعب خاين في كل مكان \nلاحول ولا قوة إلا بالله'</li><li>'يا بيك عّم تخبرنا عن شي ما فينا تعملو نحن ماًعندنا نواب ولا وزراء بمثلونا بالدولة الا اذا زهقان وعبالك ليك'</li><li>'جوز كذابين منافقين…'</li></ul> | | negative | <ul><li>'ربي لا تجعلني أسيء الظن بأحد ولا تجعل في قلبي شيئا على أحد ، اللهم أسألك قلباً نقياً صافيا'</li><li>'هشام حداد عامل فيها جون ستيوارت'</li><li>' بحياة اختك من وين بتجيبي اخبارك؟؟ من صغري وانا عبالي كون… LINK'</li></ul> | ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 0.7957 | ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("akhooli/setfit_ar_hs_mb") # Run inference preds = model("يا حاقد ع الاسلام السياسي") ```     ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:--------|:----| | Word count | 1 | 18.8388 | 185 | | Label | Training Sample Count | |:---------|:----------------------| | negative | 5200 | | positive | 4943 | ### Training Hyperparameters - batch_size: (16, 16) - num_epochs: (1, 1) - max_steps: 6000 - sampling_strategy: undersampling - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - l2_weight: 0.01 - seed: 42 - run_name: setfit_hate_52k_mb_6k - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:------:|:----:|:-------------:|:---------------:| | 0.0003 | 1 | 0.3373 | - | | 0.0333 | 100 | 0.2955 | - | | 0.0667 | 200 | 0.2535 | - | | 0.1 | 300 | 0.2373 | - | | 0.1333 | 400 | 0.2228 | - | | 0.1667 | 500 | 0.1956 | - | | 0.2 | 600 | 0.1768 | - | | 0.2333 | 700 | 0.1489 | - | | 0.2667 | 800 | 0.122 | - | | 0.3 | 900 | 0.1045 | - | | 0.3333 | 1000 | 0.086 | - | | 0.3667 | 1100 | 0.0681 | - | | 0.4 | 1200 | 0.067 | - | | 0.4333 | 1300 | 0.0477 | - | | 0.4667 | 1400 | 0.043 | - | | 0.5 | 1500 | 0.0316 | - | | 0.5333 | 1600 | 0.0251 | - | | 0.5667 | 1700 | 0.0236 | - | | 0.6 | 1800 | 0.0163 | - | | 0.6333 | 1900 | 0.0148 | - | | 0.6667 | 2000 | 0.0105 | - | | 0.7 | 2100 | 0.018 | - | | 0.7333 | 2200 | 0.013 | - | | 0.7667 | 2300 | 0.0103 | - | | 0.8 | 2400 | 0.0107 | - | | 0.8333 | 2500 | 0.0115 | - | | 0.8667 | 2600 | 0.0069 | - | | 0.9 | 2700 | 0.0062 | - | | 0.9333 | 2800 | 0.0074 | - | | 0.9667 | 2900 | 0.0063 | - | | 1.0 | 3000 | 0.0068 | - | | 1.0333 | 3100 | 0.0048 | - | | 1.0667 | 3200 | 0.0055 | - | | 1.1 | 3300 | 0.0047 | - | | 1.1333 | 3400 | 0.0043 | - | | 1.1667 | 3500 | 0.0029 | - | | 1.2 | 3600 | 0.0036 | - | | 1.2333 | 3700 | 0.0034 | - | | 1.2667 | 3800 | 0.0024 | - | | 1.3 | 3900 | 0.0033 | - | | 1.3333 | 4000 | 0.0042 | - | | 1.3667 | 4100 | 0.0039 | - | | 1.4 | 4200 | 0.0019 | - | | 1.4333 | 4300 | 0.0022 | - | | 1.4667 | 4400 | 0.0031 | - | | 1.5 | 4500 | 0.0019 | - | | 1.5333 | 4600 | 0.0036 | - | | 1.5667 | 4700 | 0.0017 | - | | 1.6 | 4800 | 0.0007 | - | | 1.6333 | 4900 | 0.0006 | - | | 1.6667 | 5000 | 0.0019 | - | | 1.7 | 5100 | 0.0022 | - | | 1.7333 | 5200 | 0.0013 | - | | 1.7667 | 5300 | 0.0025 | - | | 1.8 | 5400 | 0.0024 | - | | 1.8333 | 5500 | 0.0013 | - | | 1.8667 | 5600 | 0.0022 | - | | 1.9 | 5700 | 0.0022 | - | | 1.9333 | 5800 | 0.0019 | - | | 1.9667 | 5900 | 0.0019 | - | | 2.0 | 6000 | 0.0031 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.2.0.dev0 - Sentence Transformers: 3.3.1 - Transformers: 4.48.0 - PyTorch: 2.5.1+cu121 - Datasets: 3.2.0 - Tokenizers: 0.21.0 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```

nhungphammmmm/f4dd682c-79ff-4237-a141-c43695838f85

nhungphammmmm

2025-01-15T16:07:31Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2.5-1.5B-Instruct", "base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:51:51Z

--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: f4dd682c-79ff-4237-a141-c43695838f85 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2.5-1.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 756452db934ae1d1_train_data.json ds_type: json format: custom path: /workspace/input_data/756452db934ae1d1_train_data.json type: field_instruction: question field_output: answer format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhungphammmmm/f4dd682c-79ff-4237-a141-c43695838f85 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/756452db934ae1d1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 74979543-06fb-451f-b2f1-4786823d5776 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 74979543-06fb-451f-b2f1-4786823d5776 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # f4dd682c-79ff-4237-a141-c43695838f85 This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9338 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.8583 | 0.0195 | 200 | 0.9338 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso11/91645d6e-af35-438f-a2bb-ad7694222576

lesso11

2025-01-15T16:06:53Z

8

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:36:02Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: 91645d6e-af35-438f-a2bb-ad7694222576 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: true chat_template: llama3 datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso11/91645d6e-af35-438f-a2bb-ad7694222576 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 91645d6e-af35-438f-a2bb-ad7694222576 This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0001 | 1 | nan | | 0.0 | 0.0003 | 5 | nan | | 0.0 | 0.0005 | 10 | nan | | 0.0 | 0.0008 | 15 | nan | | 0.0 | 0.0010 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

phonemetransformers/CHILDES-Icelandic-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:28Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:52Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Farsi-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:27Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:51Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Turkish-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:26Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:50Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Basque-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:24Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:48Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Danish-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:23Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:47Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Japanese-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:18Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:43Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-Spanish-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:10Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:38Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-German-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:08Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:36Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-French-phoneme-tokenizer

phonemetransformers

2025-01-15T16:05:03Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:33Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

phonemetransformers/CHILDES-English-phoneme-tokenizer

phonemetransformers

2025-01-15T16:04:55Z

0

transformers

[ "transformers", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2024-06-03T13:23:31Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization

MayBashendy

2025-01-15T16:04:43Z

7

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T15:46:57Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8110 - Qwk: 0.2754 - Mse: 1.8110 - Rmse: 1.3457 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0270 | 2 | 7.2082 | -0.0162 | 7.2082 | 2.6848 | | No log | 0.0541 | 4 | 4.4178 | 0.0833 | 4.4178 | 2.1018 | | No log | 0.0811 | 6 | 3.6012 | -0.0423 | 3.6012 | 1.8977 | | No log | 0.1081 | 8 | 3.9013 | -0.0796 | 3.9013 | 1.9752 | | No log | 0.1351 | 10 | 2.2566 | 0.1194 | 2.2566 | 1.5022 | | No log | 0.1622 | 12 | 1.8780 | 0.1593 | 1.8780 | 1.3704 | | No log | 0.1892 | 14 | 2.1948 | -0.0625 | 2.1948 | 1.4815 | | No log | 0.2162 | 16 | 2.2320 | -0.0472 | 2.2320 | 1.4940 | | No log | 0.2432 | 18 | 2.2639 | 0.0305 | 2.2639 | 1.5046 | | No log | 0.2703 | 20 | 2.2500 | 0.0606 | 2.2500 | 1.5000 | | No log | 0.2973 | 22 | 2.1048 | 0.1157 | 2.1048 | 1.4508 | | No log | 0.3243 | 24 | 2.0103 | 0.2018 | 2.0103 | 1.4179 | | No log | 0.3514 | 26 | 1.9807 | 0.1869 | 1.9807 | 1.4074 | | No log | 0.3784 | 28 | 1.9049 | 0.1698 | 1.9049 | 1.3802 | | No log | 0.4054 | 30 | 1.8210 | 0.1714 | 1.8210 | 1.3494 | | No log | 0.4324 | 32 | 1.7544 | 0.1714 | 1.7544 | 1.3245 | | No log | 0.4595 | 34 | 1.6969 | 0.1154 | 1.6969 | 1.3027 | | No log | 0.4865 | 36 | 1.6768 | 0.2569 | 1.6768 | 1.2949 | | No log | 0.5135 | 38 | 1.8115 | 0.2459 | 1.8115 | 1.3459 | | No log | 0.5405 | 40 | 1.8102 | 0.2459 | 1.8102 | 1.3454 | | No log | 0.5676 | 42 | 1.8407 | 0.3465 | 1.8407 | 1.3567 | | No log | 0.5946 | 44 | 1.6912 | 0.2735 | 1.6912 | 1.3005 | | No log | 0.6216 | 46 | 1.5411 | 0.1682 | 1.5411 | 1.2414 | | No log | 0.6486 | 48 | 1.4974 | 0.1524 | 1.4974 | 1.2237 | | No log | 0.6757 | 50 | 1.5038 | 0.2243 | 1.5038 | 1.2263 | | No log | 0.7027 | 52 | 1.5548 | 0.2202 | 1.5548 | 1.2469 | | No log | 0.7297 | 54 | 1.5638 | 0.2321 | 1.5638 | 1.2505 | | No log | 0.7568 | 56 | 1.5255 | 0.2301 | 1.5255 | 1.2351 | | No log | 0.7838 | 58 | 1.4802 | 0.2182 | 1.4802 | 1.2166 | | No log | 0.8108 | 60 | 1.4783 | 0.2056 | 1.4783 | 1.2159 | | No log | 0.8378 | 62 | 1.5381 | 0.2407 | 1.5381 | 1.2402 | | No log | 0.8649 | 64 | 1.5067 | 0.2545 | 1.5067 | 1.2275 | | No log | 0.8919 | 66 | 1.4023 | 0.3509 | 1.4023 | 1.1842 | | No log | 0.9189 | 68 | 1.2808 | 0.3966 | 1.2808 | 1.1317 | | No log | 0.9459 | 70 | 1.1520 | 0.5116 | 1.1520 | 1.0733 | | No log | 0.9730 | 72 | 1.1067 | 0.5238 | 1.1067 | 1.0520 | | No log | 1.0 | 74 | 1.1387 | 0.5167 | 1.1387 | 1.0671 | | No log | 1.0270 | 76 | 1.2173 | 0.5366 | 1.2173 | 1.1033 | | No log | 1.0541 | 78 | 1.3335 | 0.4500 | 1.3335 | 1.1548 | | No log | 1.0811 | 80 | 1.3091 | 0.5082 | 1.3091 | 1.1442 | | No log | 1.1081 | 82 | 1.2611 | 0.5124 | 1.2611 | 1.1230 | | No log | 1.1351 | 84 | 1.3162 | 0.4370 | 1.3162 | 1.1473 | | No log | 1.1622 | 86 | 1.2898 | 0.4667 | 1.2898 | 1.1357 | | No log | 1.1892 | 88 | 1.2614 | 0.4715 | 1.2614 | 1.1231 | | No log | 1.2162 | 90 | 1.5039 | 0.3636 | 1.5039 | 1.2263 | | No log | 1.2432 | 92 | 1.7922 | 0.2581 | 1.7922 | 1.3387 | | No log | 1.2703 | 94 | 1.6562 | 0.2812 | 1.6562 | 1.2869 | | No log | 1.2973 | 96 | 1.6710 | 0.2879 | 1.6710 | 1.2927 | | No log | 1.3243 | 98 | 1.6769 | 0.2899 | 1.6769 | 1.2950 | | No log | 1.3514 | 100 | 1.7390 | 0.3022 | 1.7390 | 1.3187 | | No log | 1.3784 | 102 | 1.6659 | 0.3022 | 1.6659 | 1.2907 | | No log | 1.4054 | 104 | 1.6323 | 0.3212 | 1.6323 | 1.2776 | | No log | 1.4324 | 106 | 1.5980 | 0.3636 | 1.5980 | 1.2641 | | No log | 1.4595 | 108 | 1.4648 | 0.4427 | 1.4648 | 1.2103 | | No log | 1.4865 | 110 | 1.4642 | 0.5203 | 1.4642 | 1.2100 | | No log | 1.5135 | 112 | 1.5540 | 0.3016 | 1.5540 | 1.2466 | | No log | 1.5405 | 114 | 1.7152 | 0.2344 | 1.7152 | 1.3096 | | No log | 1.5676 | 116 | 1.6887 | 0.3030 | 1.6887 | 1.2995 | | No log | 1.5946 | 118 | 1.6345 | 0.3478 | 1.6345 | 1.2785 | | No log | 1.6216 | 120 | 1.5541 | 0.3889 | 1.5541 | 1.2466 | | No log | 1.6486 | 122 | 1.7321 | 0.3429 | 1.7321 | 1.3161 | | No log | 1.6757 | 124 | 1.7849 | 0.3429 | 1.7849 | 1.3360 | | No log | 1.7027 | 126 | 1.7942 | 0.3212 | 1.7942 | 1.3395 | | No log | 1.7297 | 128 | 1.6782 | 0.3478 | 1.6782 | 1.2954 | | No log | 1.7568 | 130 | 1.6333 | 0.2791 | 1.6333 | 1.2780 | | No log | 1.7838 | 132 | 1.6812 | 0.2764 | 1.6812 | 1.2966 | | No log | 1.8108 | 134 | 1.6148 | 0.2759 | 1.6148 | 1.2707 | | No log | 1.8378 | 136 | 1.5928 | 0.3306 | 1.5928 | 1.2621 | | No log | 1.8649 | 138 | 1.5961 | 0.3252 | 1.5961 | 1.2634 | | No log | 1.8919 | 140 | 1.6132 | 0.2951 | 1.6132 | 1.2701 | | No log | 1.9189 | 142 | 1.6740 | 0.3876 | 1.6740 | 1.2938 | | No log | 1.9459 | 144 | 1.5854 | 0.3281 | 1.5854 | 1.2591 | | No log | 1.9730 | 146 | 1.5721 | 0.3492 | 1.5721 | 1.2538 | | No log | 2.0 | 148 | 1.5770 | 0.3759 | 1.5770 | 1.2558 | | No log | 2.0270 | 150 | 1.4834 | 0.3360 | 1.4834 | 1.2179 | | No log | 2.0541 | 152 | 1.3675 | 0.3871 | 1.3675 | 1.1694 | | No log | 2.0811 | 154 | 1.3421 | 0.3577 | 1.3421 | 1.1585 | | No log | 2.1081 | 156 | 1.5974 | 0.3942 | 1.5974 | 1.2639 | | No log | 2.1351 | 158 | 1.7204 | 0.3597 | 1.7204 | 1.3117 | | No log | 2.1622 | 160 | 1.5333 | 0.3852 | 1.5333 | 1.2382 | | No log | 2.1892 | 162 | 1.4891 | 0.3622 | 1.4891 | 1.2203 | | No log | 2.2162 | 164 | 1.6118 | 0.3459 | 1.6118 | 1.2696 | | No log | 2.2432 | 166 | 1.8269 | 0.3358 | 1.8269 | 1.3516 | | No log | 2.2703 | 168 | 1.6298 | 0.3259 | 1.6298 | 1.2766 | | No log | 2.2973 | 170 | 1.5699 | 0.3134 | 1.5699 | 1.2530 | | No log | 2.3243 | 172 | 1.5849 | 0.3529 | 1.5849 | 1.2589 | | No log | 2.3514 | 174 | 1.6959 | 0.3478 | 1.6959 | 1.3023 | | No log | 2.3784 | 176 | 1.8324 | 0.2857 | 1.8324 | 1.3537 | | No log | 2.4054 | 178 | 1.6801 | 0.3741 | 1.6801 | 1.2962 | | No log | 2.4324 | 180 | 1.6340 | 0.3623 | 1.6340 | 1.2783 | | No log | 2.4595 | 182 | 1.5266 | 0.4427 | 1.5266 | 1.2355 | | No log | 2.4865 | 184 | 1.4815 | 0.3770 | 1.4815 | 1.2172 | | No log | 2.5135 | 186 | 1.4268 | 0.3130 | 1.4268 | 1.1945 | | No log | 2.5405 | 188 | 1.3539 | 0.3478 | 1.3539 | 1.1636 | | No log | 2.5676 | 190 | 1.4250 | 0.4545 | 1.4250 | 1.1937 | | No log | 2.5946 | 192 | 1.6666 | 0.3768 | 1.6666 | 1.2910 | | No log | 2.6216 | 194 | 1.8661 | 0.2878 | 1.8661 | 1.3661 | | No log | 2.6486 | 196 | 1.8096 | 0.3121 | 1.8096 | 1.3452 | | No log | 2.6757 | 198 | 1.5584 | 0.3942 | 1.5584 | 1.2484 | | No log | 2.7027 | 200 | 1.3693 | 0.5481 | 1.3693 | 1.1702 | | No log | 2.7297 | 202 | 1.3817 | 0.5185 | 1.3817 | 1.1755 | | No log | 2.7568 | 204 | 1.4770 | 0.4478 | 1.4770 | 1.2153 | | No log | 2.7838 | 206 | 1.6677 | 0.3597 | 1.6677 | 1.2914 | | No log | 2.8108 | 208 | 1.7582 | 0.3453 | 1.7582 | 1.3260 | | No log | 2.8378 | 210 | 1.6186 | 0.4060 | 1.6186 | 1.2722 | | No log | 2.8649 | 212 | 1.4199 | 0.4286 | 1.4199 | 1.1916 | | No log | 2.8919 | 214 | 1.3802 | 0.4567 | 1.3802 | 1.1748 | | No log | 2.9189 | 216 | 1.5417 | 0.4380 | 1.5417 | 1.2416 | | No log | 2.9459 | 218 | 2.0088 | 0.2207 | 2.0088 | 1.4173 | | No log | 2.9730 | 220 | 2.2277 | 0.1408 | 2.2277 | 1.4925 | | No log | 3.0 | 222 | 2.1407 | 0.0597 | 2.1407 | 1.4631 | | No log | 3.0270 | 224 | 1.8514 | 0.1951 | 1.8514 | 1.3607 | | No log | 3.0541 | 226 | 1.6430 | 0.3740 | 1.6430 | 1.2818 | | No log | 3.0811 | 228 | 1.5615 | 0.4127 | 1.5615 | 1.2496 | | No log | 3.1081 | 230 | 1.5855 | 0.4627 | 1.5855 | 1.2592 | | No log | 3.1351 | 232 | 1.6564 | 0.3429 | 1.6564 | 1.2870 | | No log | 3.1622 | 234 | 1.5814 | 0.4203 | 1.5814 | 1.2576 | | No log | 3.1892 | 236 | 1.4123 | 0.4923 | 1.4123 | 1.1884 | | No log | 3.2162 | 238 | 1.4214 | 0.4961 | 1.4214 | 1.1922 | | No log | 3.2432 | 240 | 1.5848 | 0.3971 | 1.5848 | 1.2589 | | No log | 3.2703 | 242 | 1.7020 | 0.3885 | 1.7020 | 1.3046 | | No log | 3.2973 | 244 | 1.8595 | 0.2483 | 1.8595 | 1.3636 | | No log | 3.3243 | 246 | 2.0443 | 0.1806 | 2.0443 | 1.4298 | | No log | 3.3514 | 248 | 2.0324 | 0.1806 | 2.0324 | 1.4256 | | No log | 3.3784 | 250 | 1.8233 | 0.2254 | 1.8233 | 1.3503 | | No log | 3.4054 | 252 | 1.6159 | 0.3910 | 1.6159 | 1.2712 | | No log | 3.4324 | 254 | 1.5849 | 0.3759 | 1.5849 | 1.2589 | | No log | 3.4595 | 256 | 1.6667 | 0.3876 | 1.6667 | 1.2910 | | No log | 3.4865 | 258 | 1.8424 | 0.2590 | 1.8424 | 1.3574 | | No log | 3.5135 | 260 | 1.9403 | 0.1958 | 1.9403 | 1.3929 | | No log | 3.5405 | 262 | 2.0503 | 0.1655 | 2.0502 | 1.4319 | | No log | 3.5676 | 264 | 1.8608 | 0.2817 | 1.8608 | 1.3641 | | No log | 3.5946 | 266 | 1.7975 | 0.3077 | 1.7975 | 1.3407 | | No log | 3.6216 | 268 | 1.8322 | 0.2254 | 1.8322 | 1.3536 | | No log | 3.6486 | 270 | 1.9213 | 0.2254 | 1.9213 | 1.3861 | | No log | 3.6757 | 272 | 1.9880 | 0.2254 | 1.9880 | 1.4100 | | No log | 3.7027 | 274 | 1.9393 | 0.2254 | 1.9393 | 1.3926 | | No log | 3.7297 | 276 | 1.8321 | 0.2270 | 1.8321 | 1.3536 | | No log | 3.7568 | 278 | 1.8982 | 0.2254 | 1.8982 | 1.3778 | | No log | 3.7838 | 280 | 1.9421 | 0.2254 | 1.9421 | 1.3936 | | No log | 3.8108 | 282 | 2.0218 | 0.2254 | 2.0218 | 1.4219 | | No log | 3.8378 | 284 | 1.9314 | 0.2553 | 1.9314 | 1.3898 | | No log | 3.8649 | 286 | 1.8592 | 0.2571 | 1.8592 | 1.3635 | | No log | 3.8919 | 288 | 1.6958 | 0.2963 | 1.6958 | 1.3022 | | No log | 3.9189 | 290 | 1.6157 | 0.3840 | 1.6157 | 1.2711 | | No log | 3.9459 | 292 | 1.6598 | 0.3101 | 1.6598 | 1.2883 | | No log | 3.9730 | 294 | 1.5943 | 0.4394 | 1.5943 | 1.2626 | | No log | 4.0 | 296 | 1.4468 | 0.4615 | 1.4468 | 1.2028 | | No log | 4.0270 | 298 | 1.3742 | 0.4567 | 1.3742 | 1.1723 | | No log | 4.0541 | 300 | 1.3576 | 0.4531 | 1.3576 | 1.1651 | | No log | 4.0811 | 302 | 1.5542 | 0.3881 | 1.5542 | 1.2467 | | No log | 4.1081 | 304 | 1.7148 | 0.2979 | 1.7148 | 1.3095 | | No log | 4.1351 | 306 | 1.7422 | 0.3099 | 1.7422 | 1.3199 | | No log | 4.1622 | 308 | 1.8653 | 0.2817 | 1.8653 | 1.3658 | | No log | 4.1892 | 310 | 1.8779 | 0.2817 | 1.8779 | 1.3704 | | No log | 4.2162 | 312 | 1.9154 | 0.2517 | 1.9154 | 1.3840 | | No log | 4.2432 | 314 | 1.8347 | 0.2817 | 1.8347 | 1.3545 | | No log | 4.2703 | 316 | 1.7254 | 0.2937 | 1.7254 | 1.3135 | | No log | 4.2973 | 318 | 1.7849 | 0.2937 | 1.7849 | 1.3360 | | No log | 4.3243 | 320 | 2.0441 | 0.2207 | 2.0441 | 1.4297 | | No log | 4.3514 | 322 | 2.0704 | 0.2207 | 2.0704 | 1.4389 | | No log | 4.3784 | 324 | 2.0644 | 0.2222 | 2.0644 | 1.4368 | | No log | 4.4054 | 326 | 1.8950 | 0.2817 | 1.8950 | 1.3766 | | No log | 4.4324 | 328 | 1.6892 | 0.3088 | 1.6892 | 1.2997 | | No log | 4.4595 | 330 | 1.6061 | 0.3284 | 1.6061 | 1.2673 | | No log | 4.4865 | 332 | 1.6050 | 0.3284 | 1.6050 | 1.2669 | | No log | 4.5135 | 334 | 1.6380 | 0.2707 | 1.6380 | 1.2798 | | No log | 4.5405 | 336 | 1.6928 | 0.2628 | 1.6928 | 1.3011 | | No log | 4.5676 | 338 | 1.6034 | 0.3088 | 1.6034 | 1.2662 | | No log | 4.5946 | 340 | 1.5406 | 0.3704 | 1.5406 | 1.2412 | | No log | 4.6216 | 342 | 1.6825 | 0.2899 | 1.6825 | 1.2971 | | No log | 4.6486 | 344 | 1.7879 | 0.2553 | 1.7879 | 1.3371 | | No log | 4.6757 | 346 | 1.7188 | 0.3000 | 1.7188 | 1.3110 | | No log | 4.7027 | 348 | 1.6851 | 0.2794 | 1.6851 | 1.2981 | | No log | 4.7297 | 350 | 1.7611 | 0.2256 | 1.7611 | 1.3271 | | No log | 4.7568 | 352 | 1.9253 | 0.2090 | 1.9253 | 1.3875 | | No log | 4.7838 | 354 | 2.0759 | 0.1515 | 2.0759 | 1.4408 | | No log | 4.8108 | 356 | 2.0925 | 0.1571 | 2.0925 | 1.4465 | | No log | 4.8378 | 358 | 2.0788 | 0.1944 | 2.0788 | 1.4418 | | No log | 4.8649 | 360 | 1.9254 | 0.2553 | 1.9254 | 1.3876 | | No log | 4.8919 | 362 | 1.6860 | 0.3088 | 1.6860 | 1.2985 | | No log | 4.9189 | 364 | 1.6780 | 0.3459 | 1.6780 | 1.2954 | | No log | 4.9459 | 366 | 1.6791 | 0.3459 | 1.6791 | 1.2958 | | No log | 4.9730 | 368 | 1.6670 | 0.4242 | 1.6670 | 1.2911 | | No log | 5.0 | 370 | 1.5885 | 0.4122 | 1.5885 | 1.2604 | | No log | 5.0270 | 372 | 1.5051 | 0.3906 | 1.5051 | 1.2268 | | No log | 5.0541 | 374 | 1.4867 | 0.3810 | 1.4867 | 1.2193 | | No log | 5.0811 | 376 | 1.5628 | 0.4 | 1.5628 | 1.2501 | | No log | 5.1081 | 378 | 1.6585 | 0.3731 | 1.6585 | 1.2878 | | No log | 5.1351 | 380 | 1.8380 | 0.2734 | 1.8380 | 1.3557 | | No log | 5.1622 | 382 | 1.9378 | 0.2270 | 1.9378 | 1.3920 | | No log | 5.1892 | 384 | 1.9140 | 0.2270 | 1.9140 | 1.3835 | | No log | 5.2162 | 386 | 1.7157 | 0.3066 | 1.7157 | 1.3099 | | No log | 5.2432 | 388 | 1.5721 | 0.3910 | 1.5721 | 1.2538 | | No log | 5.2703 | 390 | 1.5407 | 0.4375 | 1.5407 | 1.2413 | | No log | 5.2973 | 392 | 1.4930 | 0.4375 | 1.4930 | 1.2219 | | No log | 5.3243 | 394 | 1.4746 | 0.4375 | 1.4746 | 1.2143 | | No log | 5.3514 | 396 | 1.4671 | 0.4308 | 1.4671 | 1.2113 | | No log | 5.3784 | 398 | 1.4099 | 0.4341 | 1.4099 | 1.1874 | | No log | 5.4054 | 400 | 1.4354 | 0.4394 | 1.4354 | 1.1981 | | No log | 5.4324 | 402 | 1.5180 | 0.3881 | 1.5180 | 1.2321 | | No log | 5.4595 | 404 | 1.6601 | 0.3433 | 1.6601 | 1.2885 | | No log | 5.4865 | 406 | 1.7180 | 0.3043 | 1.7180 | 1.3107 | | No log | 5.5135 | 408 | 1.6135 | 0.3556 | 1.6135 | 1.2702 | | No log | 5.5405 | 410 | 1.5487 | 0.4328 | 1.5487 | 1.2445 | | No log | 5.5676 | 412 | 1.6277 | 0.3731 | 1.6277 | 1.2758 | | No log | 5.5946 | 414 | 1.7122 | 0.3235 | 1.7122 | 1.3085 | | No log | 5.6216 | 416 | 1.8522 | 0.2734 | 1.8522 | 1.3610 | | No log | 5.6486 | 418 | 1.9405 | 0.2553 | 1.9405 | 1.3930 | | No log | 5.6757 | 420 | 1.9563 | 0.2553 | 1.9563 | 1.3987 | | No log | 5.7027 | 422 | 1.8105 | 0.2734 | 1.8105 | 1.3455 | | No log | 5.7297 | 424 | 1.6032 | 0.4242 | 1.6032 | 1.2662 | | No log | 5.7568 | 426 | 1.4874 | 0.3968 | 1.4874 | 1.2196 | | No log | 5.7838 | 428 | 1.5161 | 0.368 | 1.5161 | 1.2313 | | No log | 5.8108 | 430 | 1.7124 | 0.4091 | 1.7124 | 1.3086 | | No log | 5.8378 | 432 | 1.8787 | 0.2734 | 1.8787 | 1.3706 | | No log | 5.8649 | 434 | 1.9319 | 0.2553 | 1.9319 | 1.3899 | | No log | 5.8919 | 436 | 1.8562 | 0.2734 | 1.8562 | 1.3624 | | No log | 5.9189 | 438 | 1.7858 | 0.2899 | 1.7858 | 1.3363 | | No log | 5.9459 | 440 | 1.9567 | 0.2254 | 1.9567 | 1.3988 | | No log | 5.9730 | 442 | 2.0003 | 0.2254 | 2.0003 | 1.4143 | | No log | 6.0 | 444 | 1.9405 | 0.2254 | 1.9405 | 1.3930 | | No log | 6.0270 | 446 | 1.7613 | 0.2899 | 1.7613 | 1.3271 | | No log | 6.0541 | 448 | 1.6111 | 0.4242 | 1.6111 | 1.2693 | | No log | 6.0811 | 450 | 1.6096 | 0.3731 | 1.6096 | 1.2687 | | No log | 6.1081 | 452 | 1.8084 | 0.2734 | 1.8084 | 1.3447 | | No log | 6.1351 | 454 | 2.0332 | 0.2254 | 2.0332 | 1.4259 | | No log | 6.1622 | 456 | 2.0020 | 0.2254 | 2.0020 | 1.4149 | | No log | 6.1892 | 458 | 1.8074 | 0.2734 | 1.8074 | 1.3444 | | No log | 6.2162 | 460 | 1.5295 | 0.4265 | 1.5295 | 1.2367 | | No log | 6.2432 | 462 | 1.4173 | 0.5191 | 1.4173 | 1.1905 | | No log | 6.2703 | 464 | 1.4113 | 0.4882 | 1.4113 | 1.1880 | | No log | 6.2973 | 466 | 1.5022 | 0.4580 | 1.5022 | 1.2256 | | No log | 6.3243 | 468 | 1.6681 | 0.3731 | 1.6681 | 1.2915 | | No log | 6.3514 | 470 | 1.7982 | 0.3407 | 1.7982 | 1.3410 | | No log | 6.3784 | 472 | 1.7536 | 0.3284 | 1.7536 | 1.3242 | | No log | 6.4054 | 474 | 1.5888 | 0.4179 | 1.5888 | 1.2605 | | No log | 6.4324 | 476 | 1.4139 | 0.5303 | 1.4139 | 1.1891 | | No log | 6.4595 | 478 | 1.4145 | 0.4962 | 1.4145 | 1.1893 | | No log | 6.4865 | 480 | 1.5579 | 0.4242 | 1.5579 | 1.2481 | | No log | 6.5135 | 482 | 1.7630 | 0.2754 | 1.7630 | 1.3278 | | No log | 6.5405 | 484 | 1.8474 | 0.2411 | 1.8474 | 1.3592 | | No log | 6.5676 | 486 | 1.7922 | 0.2446 | 1.7922 | 1.3387 | | No log | 6.5946 | 488 | 1.6658 | 0.4242 | 1.6658 | 1.2907 | | No log | 6.6216 | 490 | 1.5592 | 0.4098 | 1.5592 | 1.2487 | | No log | 6.6486 | 492 | 1.5511 | 0.3761 | 1.5511 | 1.2454 | | No log | 6.6757 | 494 | 1.5523 | 0.4500 | 1.5523 | 1.2459 | | No log | 6.7027 | 496 | 1.6037 | 0.4031 | 1.6037 | 1.2664 | | No log | 6.7297 | 498 | 1.6611 | 0.3731 | 1.6611 | 1.2888 | | 0.3936 | 6.7568 | 500 | 1.6958 | 0.3235 | 1.6958 | 1.3022 | | 0.3936 | 6.7838 | 502 | 1.6762 | 0.3235 | 1.6762 | 1.2947 | | 0.3936 | 6.8108 | 504 | 1.6236 | 0.3852 | 1.6236 | 1.2742 | | 0.3936 | 6.8378 | 506 | 1.5538 | 0.3852 | 1.5538 | 1.2465 | | 0.3936 | 6.8649 | 508 | 1.5990 | 0.3852 | 1.5990 | 1.2645 | | 0.3936 | 6.8919 | 510 | 1.6781 | 0.3407 | 1.6781 | 1.2954 | | 0.3936 | 6.9189 | 512 | 1.7600 | 0.2920 | 1.7600 | 1.3267 | | 0.3936 | 6.9459 | 514 | 1.7322 | 0.2920 | 1.7322 | 1.3161 | | 0.3936 | 6.9730 | 516 | 1.6869 | 0.3556 | 1.6869 | 1.2988 | | 0.3936 | 7.0 | 518 | 1.6151 | 0.3609 | 1.6151 | 1.2709 | | 0.3936 | 7.0270 | 520 | 1.5323 | 0.4478 | 1.5323 | 1.2378 | | 0.3936 | 7.0541 | 522 | 1.4406 | 0.4603 | 1.4406 | 1.2003 | | 0.3936 | 7.0811 | 524 | 1.4687 | 0.4662 | 1.4687 | 1.2119 | | 0.3936 | 7.1081 | 526 | 1.5421 | 0.4179 | 1.5421 | 1.2418 | | 0.3936 | 7.1351 | 528 | 1.6858 | 0.2920 | 1.6858 | 1.2984 | | 0.3936 | 7.1622 | 530 | 1.8141 | 0.2754 | 1.8141 | 1.3469 | | 0.3936 | 7.1892 | 532 | 2.0164 | 0.1690 | 2.0164 | 1.4200 | | 0.3936 | 7.2162 | 534 | 2.0350 | 0.1690 | 2.0350 | 1.4265 | | 0.3936 | 7.2432 | 536 | 1.8110 | 0.2754 | 1.8110 | 1.3457 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

sahandrez/rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811

sahandrez

2025-01-15T16:03:40Z

6

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "generated_from_trainer", "trl", "rloo", "conversational", "arxiv:2402.14740", "base_model:sahandrez/Qwen2.5-1.5B-sft-uf", "base_model:finetune:sahandrez/Qwen2.5-1.5B-sft-uf", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-14T19:28:22Z

--- base_model: sahandrez/Qwen2.5-1.5B-sft-uf library_name: transformers model_name: rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811 tags: - generated_from_trainer - trl - rloo licence: license --- # Model Card for rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811 This model is a fine-tuned version of [sahandrez/Qwen2.5-1.5B-sft-uf](https://huggingface.co/sahandrez/Qwen2.5-1.5B-sft-uf). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="sahandrez/rloo-unpaired-Qwen2.5-1.5B-ultrafeedback-binarized-20250114-142811", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/unpaired_rlhf/sahand/runs/w2hc91ea) This model was trained with RLOO, a method introduced in [Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs](https://huggingface.co/papers/2402.14740). ### Framework versions - TRL: 0.13.0 - Transformers: 4.48.0 - Pytorch: 2.4.0 - Datasets: 3.1.0 - Tokenizers: 0.21.0 ## Citations Cite RLOO as: ```bibtex @inproceedings{ahmadian2024back, title = {{Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs}}, author = {Arash Ahmadian and Chris Cremer and Matthias Gall{'{e}} and Marzieh Fadaee and Julia Kreutzer and Olivier Pietquin and Ahmet {"{U}}st{"{u}}n and Sara Hooker}, year = 2024, booktitle = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2024, Bangkok, Thailand, August 11-16, 2024}, publisher = {Association for Computational Linguistics}, pages = {12248--12267}, editor = {Lun{-}Wei Ku and Andre Martins and Vivek Srikumar}, } ``` Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```

itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF

itlwas

2025-01-15T16:00:26Z

19

0

transformers

[ "transformers", "gguf", "llama-cpp", "gguf-my-repo", "text-generation", "ko", "dataset:kyujinpy/KOR-OpenOrca-Platypus-v3", "base_model:PracticeLLM/Custom-KoLLM-13B-v1", "base_model:quantized:PracticeLLM/Custom-KoLLM-13B-v1", "license:cc-by-nc-sa-4.0", "endpoints_compatible", "region:us" ]

text-generation

2025-01-15T15:59:53Z

--- language: - ko datasets: - kyujinpy/KOR-OpenOrca-Platypus-v3 library_name: transformers pipeline_tag: text-generation license: cc-by-nc-sa-4.0 tags: - llama-cpp - gguf-my-repo base_model: PracticeLLM/Custom-KoLLM-13B-v1 --- # itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF This model was converted to GGUF format from [`PracticeLLM/Custom-KoLLM-13B-v1`](https://huggingface.co/PracticeLLM/Custom-KoLLM-13B-v1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/PracticeLLM/Custom-KoLLM-13B-v1) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo itlwas/Custom-KoLLM-13B-v1-Q4_K_M-GGUF --hf-file custom-kollm-13b-v1-q4_k_m.gguf -c 2048 ```

ivangrapher/f067d804-cf60-45c6-8409-593a1c2e69c0

ivangrapher

2025-01-15T16:00:17Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-0.5B-Instruct", "base_model:adapter:unsloth/Qwen2-0.5B-Instruct", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:56:57Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-0.5B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: f067d804-cf60-45c6-8409-593a1c2e69c0 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-0.5B-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - cb0c735aa9ecc20c_train_data.json ds_type: json format: custom path: /workspace/input_data/cb0c735aa9ecc20c_train_data.json type: field_input: init_response field_instruction: critic_prompt field_output: revision_response format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 8 gradient_checkpointing: false group_by_length: false hub_model_id: ivangrapher/f067d804-cf60-45c6-8409-593a1c2e69c0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 70GiB max_steps: 30 micro_batch_size: 4 mlflow_experiment_name: /tmp/cb0c735aa9ecc20c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 53e19756-9979-4666-a32e-c3622fab4ea4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 53e19756-9979-4666-a32e-c3622fab4ea4 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # f067d804-cf60-45c6-8409-593a1c2e69c0 This model is a fine-tuned version of [unsloth/Qwen2-0.5B-Instruct](https://huggingface.co/unsloth/Qwen2-0.5B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0008 | 1 | nan | | 0.0 | 0.0060 | 8 | nan | | 0.0 | 0.0121 | 16 | nan | | 0.0 | 0.0181 | 24 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhoxinh/1d537965-820c-4214-8f76-78946dc4e7c2

nhoxinh

2025-01-15T15:57:48Z

9

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:42:56Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 1d537965-820c-4214-8f76-78946dc4e7c2 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhoxinh/1d537965-820c-4214-8f76-78946dc4e7c2 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 1d537965-820c-4214-8f76-78946dc4e7c2 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0409 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.081 | 0.0376 | 200 | 0.0409 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Patnev71/floorplanv3

Patnev71

2025-01-15T15:57:47Z

5

0

transformers

[ "transformers", "safetensors", "segformer", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2025-01-15T15:57:45Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

bbytxt/d94c1346-5615-4f88-b572-e185e31c489a

bbytxt

2025-01-15T15:57:38Z

10

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "custom_code", "base_model:NousResearch/Yarn-Mistral-7b-64k", "base_model:adapter:NousResearch/Yarn-Mistral-7b-64k", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:04:40Z

--- library_name: peft license: apache-2.0 base_model: NousResearch/Yarn-Mistral-7b-64k tags: - axolotl - generated_from_trainer model-index: - name: d94c1346-5615-4f88-b572-e185e31c489a results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: NousResearch/Yarn-Mistral-7b-64k bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - 7708f8a044b2986d_train_data.json ds_type: json format: custom path: /workspace/input_data/7708f8a044b2986d_train_data.json type: field_instruction: prompt field_output: chosen format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/d94c1346-5615-4f88-b572-e185e31c489a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/7708f8a044b2986d_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 special_tokens: pad_token: </s> strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 0a956f4b-2530-421e-9d67-9975bdd289dc wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 0a956f4b-2530-421e-9d67-9975bdd289dc warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details> # d94c1346-5615-4f88-b572-e185e31c489a This model is a fine-tuned version of [NousResearch/Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3177 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 8.4345 | 0.0008 | 1 | 2.2083 | | 2.7382 | 0.0377 | 50 | 1.6734 | | 1.6323 | 0.0754 | 100 | 1.5817 | | 2.5445 | 0.1132 | 150 | 1.4006 | | 1.7847 | 0.1509 | 200 | 1.3177 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso10/7f7eaa0f-17d1-424f-922a-7f1286dfe318

lesso10

2025-01-15T15:56:07Z

13

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:42:41Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 7f7eaa0f-17d1-424f-922a-7f1286dfe318 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: true chat_template: llama3 datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso10/7f7eaa0f-17d1-424f-922a-7f1286dfe318 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 7f7eaa0f-17d1-424f-922a-7f1286dfe318 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0002 | 1 | nan | | 0.0 | 0.0009 | 5 | nan | | 0.0 | 0.0019 | 10 | nan | | 0.0 | 0.0028 | 15 | nan | | 0.0 | 0.0038 | 20 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nadejdatarabukina/fffd188d-8ff3-46b8-a154-566ea0e51a69

nadejdatarabukina

2025-01-15T15:50:51Z

16

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:42:45Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: fffd188d-8ff3-46b8-a154-566ea0e51a69 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 6 gradient_checkpointing: false group_by_length: false hub_model_id: nadejdatarabukina/fffd188d-8ff3-46b8-a154-566ea0e51a69 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # fffd188d-8ff3-46b8-a154-566ea0e51a69 This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 6 - total_train_batch_size: 12 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0003 | 1 | nan | | 0.0 | 0.0023 | 8 | nan | | 0.0 | 0.0045 | 16 | nan | | 0.0 | 0.0068 | 24 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

VerbACxSS/sempl-it-gpt2-small-italian

VerbACxSS

2025-01-15T15:50:42Z

48

0

transformers

[ "transformers", "safetensors", "gpt2", "text-generation", "legal", "it", "base_model:GroNLP/gpt2-small-italian", "base_model:finetune:GroNLP/gpt2-small-italian", "license:mit", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-12-27T08:58:19Z

--- license: mit language: - it base_model: - GroNLP/gpt2-small-italian pipeline_tag: text-generation tags: - legal library_name: transformers --- ## Usage ``` from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian", model_max_length=1024) model = AutoModelForCausalLM.from_pretrained("VerbACxSS/sempl-it-gpt2-small-italian") model.eval() text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva' prompt = f'### [Input]:\n{text_to_simplify}\n\n###[Output]:\n' x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids y = model.generate(x, max_length=1024)[0] y_dec = tokenizer.decode(y, max_length=1024, truncation=True) output = y_dec.split('###[Output]:\n')[1].split('<|endoftext|>')[0].strip() print(output) ``` ## Acknowledgements This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) "VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility" (Prot. 2020BJKB9M), funded by the Italian Ministero dell'Università e della Ricerca.

dimasik2987/3c9903ab-f11a-4346-b33b-53331b56f77d

dimasik2987

2025-01-15T15:50:29Z

12

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM2-1.7B", "base_model:adapter:unsloth/SmolLM2-1.7B", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:42:50Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM2-1.7B tags: - axolotl - generated_from_trainer model-index: - name: 3c9903ab-f11a-4346-b33b-53331b56f77d results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM2-1.7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0754f1f9a7257ab1_train_data.json ds_type: json format: custom path: /workspace/input_data/0754f1f9a7257ab1_train_data.json type: field_input: input field_instruction: instruction field_output: output format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik2987/3c9903ab-f11a-4346-b33b-53331b56f77d hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 79GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0754f1f9a7257ab1_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 5b623591-63a4-4fae-839a-cad854463700 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 5b623591-63a4-4fae-839a-cad854463700 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 3c9903ab-f11a-4346-b33b-53331b56f77d This model is a fine-tuned version of [unsloth/SmolLM2-1.7B](https://huggingface.co/unsloth/SmolLM2-1.7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0002 | 1 | nan | | 0.0 | 0.0009 | 5 | nan | | 0.0 | 0.0019 | 10 | nan | | 0.0 | 0.0028 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

VerbACxSS/sempl-it-mt5-small

VerbACxSS

2025-01-15T15:50:21Z

68

0

transformers

[ "transformers", "safetensors", "mt5", "text2text-generation", "legal", "it", "base_model:google/mt5-small", "base_model:finetune:google/mt5-small", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2024-12-27T08:58:49Z

--- license: mit language: - it base_model: - google/mt5-small pipeline_tag: text2text-generation tags: - legal library_name: transformers --- ## Usage ``` from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VerbACxSS/sempl-it-mt5-small") model = AutoModelForSeq2SeqLM.from_pretrained("VerbACxSS/sempl-it-mt5-small") model.eval() text_to_simplify = 'Nella fattispecie, questo documento è di natura prescrittiva' prompt = f'semplifica: {text_to_simplify}' x = tokenizer(prompt, max_length=1024, truncation=True, padding=True, return_tensors='pt').input_ids y = model.generate(x, max_length=1024)[0] output = tokenizer.decode(y, max_length=1024, truncation=True, skip_special_tokens=True, clean_up_tokenization_spaces=True) print(output) ``` ## Acknowledgements This contribution is a result of the research conducted within the framework of the PRIN 2020 (Progetti di Rilevante Interesse Nazionale) "VerbACxSS: on analytic verbs, complexity, synthetic verbs, and simplification. For accessibility" (Prot. 2020BJKB9M), funded by the Italian Ministero dell'Università e della Ricerca.

laquythang/49668481-8ea3-4632-b312-cd2956370777

laquythang

2025-01-15T15:50:05Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:32:51Z

--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 49668481-8ea3-4632-b312-cd2956370777 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: laquythang/49668481-8ea3-4632-b312-cd2956370777 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 49668481-8ea3-4632-b312-cd2956370777 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0637 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.8976 | 0.7073 | 200 | 1.0637 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

aurelvu/bert-bibtex-classifier

aurelvu

2025-01-15T15:49:15Z

171

0

transformers

[ "transformers", "tensorboard", "safetensors", "bert", "token-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-multilingual-cased", "base_model:finetune:distilbert/distilbert-base-multilingual-cased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

token-classification

2025-01-12T22:59:50Z

--- library_name: transformers license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer model-index: - name: tmp_trainer results: [] ---  # tmp_trainer This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3.0 ### Training results ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0

nhung01/73decf8f-573c-4ede-a607-775c7da77ed4

nhung01

2025-01-15T15:48:40Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:32:43Z

--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 73decf8f-573c-4ede-a607-775c7da77ed4 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/73decf8f-573c-4ede-a607-775c7da77ed4 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 73decf8f-573c-4ede-a607-775c7da77ed4 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.0612 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.8979 | 0.7073 | 200 | 1.0612 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization

MayBashendy

2025-01-15T15:46:25Z

7

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T15:28:55Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.3764 - Qwk: 0.4593 - Mse: 1.3764 - Rmse: 1.1732 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0286 | 2 | 6.8337 | 0.0242 | 6.8337 | 2.6141 | | No log | 0.0571 | 4 | 4.4891 | 0.0928 | 4.4891 | 2.1187 | | No log | 0.0857 | 6 | 3.6095 | -0.0417 | 3.6095 | 1.8999 | | No log | 0.1143 | 8 | 2.6066 | 0.0805 | 2.6066 | 1.6145 | | No log | 0.1429 | 10 | 2.3240 | 0.0833 | 2.3240 | 1.5245 | | No log | 0.1714 | 12 | 2.4556 | 0.0946 | 2.4556 | 1.5670 | | No log | 0.2 | 14 | 2.0410 | 0.0960 | 2.0410 | 1.4286 | | No log | 0.2286 | 16 | 1.8799 | 0.2931 | 1.8799 | 1.3711 | | No log | 0.2571 | 18 | 1.7234 | 0.2957 | 1.7234 | 1.3128 | | No log | 0.2857 | 20 | 1.5811 | 0.3036 | 1.5811 | 1.2574 | | No log | 0.3143 | 22 | 1.4460 | 0.1869 | 1.4460 | 1.2025 | | No log | 0.3429 | 24 | 1.5540 | 0.1321 | 1.5540 | 1.2466 | | No log | 0.3714 | 26 | 1.4213 | 0.2222 | 1.4213 | 1.1922 | | No log | 0.4 | 28 | 1.5136 | 0.3193 | 1.5136 | 1.2303 | | No log | 0.4286 | 30 | 1.9478 | 0.2105 | 1.9478 | 1.3956 | | No log | 0.4571 | 32 | 2.0764 | 0.2014 | 2.0764 | 1.4410 | | No log | 0.4857 | 34 | 1.5700 | 0.3281 | 1.5700 | 1.2530 | | No log | 0.5143 | 36 | 1.2381 | 0.3826 | 1.2381 | 1.1127 | | No log | 0.5429 | 38 | 1.2643 | 0.3423 | 1.2643 | 1.1244 | | No log | 0.5714 | 40 | 1.2574 | 0.4068 | 1.2574 | 1.1213 | | No log | 0.6 | 42 | 1.2750 | 0.4298 | 1.2750 | 1.1291 | | No log | 0.6286 | 44 | 1.6089 | 0.3220 | 1.6089 | 1.2684 | | No log | 0.6571 | 46 | 1.6026 | 0.3636 | 1.6026 | 1.2659 | | No log | 0.6857 | 48 | 1.0863 | 0.5156 | 1.0863 | 1.0423 | | No log | 0.7143 | 50 | 0.9043 | 0.6809 | 0.9043 | 0.9509 | | No log | 0.7429 | 52 | 1.0416 | 0.5538 | 1.0416 | 1.0206 | | No log | 0.7714 | 54 | 1.5162 | 0.3200 | 1.5162 | 1.2313 | | No log | 0.8 | 56 | 1.3478 | 0.4580 | 1.3478 | 1.1610 | | No log | 0.8286 | 58 | 0.9924 | 0.6269 | 0.9924 | 0.9962 | | No log | 0.8571 | 60 | 0.9594 | 0.6763 | 0.9594 | 0.9795 | | No log | 0.8857 | 62 | 1.1393 | 0.5481 | 1.1393 | 1.0674 | | No log | 0.9143 | 64 | 1.1885 | 0.5255 | 1.1885 | 1.0902 | | No log | 0.9429 | 66 | 1.0726 | 0.6222 | 1.0726 | 1.0357 | | No log | 0.9714 | 68 | 1.0284 | 0.5649 | 1.0284 | 1.0141 | | No log | 1.0 | 70 | 1.0905 | 0.6324 | 1.0905 | 1.0443 | | No log | 1.0286 | 72 | 1.0872 | 0.6131 | 1.0872 | 1.0427 | | No log | 1.0571 | 74 | 1.1639 | 0.5493 | 1.1639 | 1.0788 | | No log | 1.0857 | 76 | 1.4816 | 0.4965 | 1.4816 | 1.2172 | | No log | 1.1143 | 78 | 1.4626 | 0.5143 | 1.4626 | 1.2094 | | No log | 1.1429 | 80 | 1.4851 | 0.5180 | 1.4851 | 1.2186 | | No log | 1.1714 | 82 | 1.3317 | 0.4889 | 1.3317 | 1.1540 | | No log | 1.2 | 84 | 1.2976 | 0.4062 | 1.2976 | 1.1391 | | No log | 1.2286 | 86 | 1.4304 | 0.4032 | 1.4304 | 1.1960 | | No log | 1.2571 | 88 | 1.7350 | 0.3333 | 1.7350 | 1.3172 | | No log | 1.2857 | 90 | 1.8839 | 0.2880 | 1.8839 | 1.3725 | | No log | 1.3143 | 92 | 1.8076 | 0.2326 | 1.8076 | 1.3445 | | No log | 1.3429 | 94 | 1.2636 | 0.5109 | 1.2636 | 1.1241 | | No log | 1.3714 | 96 | 1.0193 | 0.5857 | 1.0193 | 1.0096 | | No log | 1.4 | 98 | 1.2112 | 0.5674 | 1.2112 | 1.1005 | | No log | 1.4286 | 100 | 1.5935 | 0.4113 | 1.5935 | 1.2623 | | No log | 1.4571 | 102 | 1.3159 | 0.5217 | 1.3159 | 1.1471 | | No log | 1.4857 | 104 | 0.8062 | 0.7050 | 0.8062 | 0.8979 | | No log | 1.5143 | 106 | 0.7865 | 0.7391 | 0.7865 | 0.8869 | | No log | 1.5429 | 108 | 0.9035 | 0.6418 | 0.9035 | 0.9505 | | No log | 1.5714 | 110 | 1.2976 | 0.4964 | 1.2976 | 1.1391 | | No log | 1.6 | 112 | 1.3322 | 0.4964 | 1.3322 | 1.1542 | | No log | 1.6286 | 114 | 1.0269 | 0.6074 | 1.0269 | 1.0134 | | No log | 1.6571 | 116 | 0.8800 | 0.6377 | 0.8800 | 0.9381 | | No log | 1.6857 | 118 | 0.9260 | 0.6331 | 0.9260 | 0.9623 | | No log | 1.7143 | 120 | 1.1650 | 0.5315 | 1.1650 | 1.0794 | | No log | 1.7429 | 122 | 1.4832 | 0.4895 | 1.4832 | 1.2179 | | No log | 1.7714 | 124 | 1.4908 | 0.4615 | 1.4908 | 1.2210 | | No log | 1.8 | 126 | 1.4700 | 0.4476 | 1.4700 | 1.2124 | | No log | 1.8286 | 128 | 1.2040 | 0.5468 | 1.2040 | 1.0972 | | No log | 1.8571 | 130 | 1.0580 | 0.6615 | 1.0580 | 1.0286 | | No log | 1.8857 | 132 | 1.0125 | 0.4959 | 1.0125 | 1.0062 | | No log | 1.9143 | 134 | 1.0953 | 0.6299 | 1.0953 | 1.0466 | | No log | 1.9429 | 136 | 1.3044 | 0.5075 | 1.3044 | 1.1421 | | No log | 1.9714 | 138 | 1.4761 | 0.4265 | 1.4761 | 1.2150 | | No log | 2.0 | 140 | 1.4946 | 0.4265 | 1.4946 | 1.2225 | | No log | 2.0286 | 142 | 1.3233 | 0.5263 | 1.3233 | 1.1504 | | No log | 2.0571 | 144 | 1.2769 | 0.5926 | 1.2769 | 1.1300 | | No log | 2.0857 | 146 | 1.5574 | 0.3942 | 1.5574 | 1.2480 | | No log | 2.1143 | 148 | 1.7650 | 0.2222 | 1.7650 | 1.3285 | | No log | 2.1429 | 150 | 1.6343 | 0.3333 | 1.6343 | 1.2784 | | No log | 2.1714 | 152 | 1.4845 | 0.3971 | 1.4845 | 1.2184 | | No log | 2.2 | 154 | 1.2324 | 0.5152 | 1.2324 | 1.1101 | | No log | 2.2286 | 156 | 1.0931 | 0.5938 | 1.0931 | 1.0455 | | No log | 2.2571 | 158 | 1.0929 | 0.5645 | 1.0929 | 1.0454 | | No log | 2.2857 | 160 | 1.2566 | 0.4812 | 1.2566 | 1.1210 | | No log | 2.3143 | 162 | 1.2894 | 0.4812 | 1.2894 | 1.1355 | | No log | 2.3429 | 164 | 1.2423 | 0.5075 | 1.2423 | 1.1146 | | No log | 2.3714 | 166 | 1.1305 | 0.5758 | 1.1305 | 1.0633 | | No log | 2.4 | 168 | 0.9736 | 0.6471 | 0.9736 | 0.9867 | | No log | 2.4286 | 170 | 0.9289 | 0.6567 | 0.9289 | 0.9638 | | No log | 2.4571 | 172 | 1.0946 | 0.6232 | 1.0946 | 1.0462 | | No log | 2.4857 | 174 | 1.4287 | 0.4593 | 1.4287 | 1.1953 | | No log | 2.5143 | 176 | 1.3580 | 0.4706 | 1.3580 | 1.1653 | | No log | 2.5429 | 178 | 1.0219 | 0.6232 | 1.0219 | 1.0109 | | No log | 2.5714 | 180 | 0.9143 | 0.6277 | 0.9143 | 0.9562 | | No log | 2.6 | 182 | 0.9552 | 0.6232 | 0.9552 | 0.9773 | | No log | 2.6286 | 184 | 1.0716 | 0.5857 | 1.0716 | 1.0352 | | No log | 2.6571 | 186 | 0.9842 | 0.6232 | 0.9842 | 0.9921 | | No log | 2.6857 | 188 | 0.8826 | 0.6471 | 0.8826 | 0.9395 | | No log | 2.7143 | 190 | 1.0422 | 0.6176 | 1.0422 | 1.0209 | | No log | 2.7429 | 192 | 1.2937 | 0.4889 | 1.2937 | 1.1374 | | No log | 2.7714 | 194 | 1.3087 | 0.4889 | 1.3087 | 1.1440 | | No log | 2.8 | 196 | 1.0811 | 0.6087 | 1.0811 | 1.0398 | | No log | 2.8286 | 198 | 0.8948 | 0.6418 | 0.8948 | 0.9459 | | No log | 2.8571 | 200 | 0.9906 | 0.6187 | 0.9906 | 0.9953 | | No log | 2.8857 | 202 | 1.3906 | 0.4593 | 1.3906 | 1.1792 | | No log | 2.9143 | 204 | 1.5787 | 0.3429 | 1.5787 | 1.2564 | | No log | 2.9429 | 206 | 1.3830 | 0.4662 | 1.3830 | 1.1760 | | No log | 2.9714 | 208 | 1.1465 | 0.5385 | 1.1465 | 1.0707 | | No log | 3.0 | 210 | 1.0218 | 0.6129 | 1.0218 | 1.0108 | | No log | 3.0286 | 212 | 1.0315 | 0.5246 | 1.0315 | 1.0156 | | No log | 3.0571 | 214 | 1.1276 | 0.6032 | 1.1276 | 1.0619 | | No log | 3.0857 | 216 | 1.4077 | 0.4320 | 1.4077 | 1.1865 | | No log | 3.1143 | 218 | 1.5440 | 0.4531 | 1.5440 | 1.2426 | | No log | 3.1429 | 220 | 1.5291 | 0.4531 | 1.5291 | 1.2365 | | No log | 3.1714 | 222 | 1.3984 | 0.5039 | 1.3984 | 1.1825 | | No log | 3.2 | 224 | 1.4500 | 0.4341 | 1.4500 | 1.2041 | | No log | 3.2286 | 226 | 1.6216 | 0.2923 | 1.6216 | 1.2734 | | No log | 3.2571 | 228 | 1.5246 | 0.3556 | 1.5246 | 1.2347 | | No log | 3.2857 | 230 | 1.3671 | 0.4783 | 1.3671 | 1.1692 | | No log | 3.3143 | 232 | 1.4404 | 0.4265 | 1.4404 | 1.2001 | | No log | 3.3429 | 234 | 1.7448 | 0.2609 | 1.7448 | 1.3209 | | No log | 3.3714 | 236 | 1.8269 | 0.2774 | 1.8269 | 1.3516 | | No log | 3.4 | 238 | 1.5437 | 0.3582 | 1.5437 | 1.2425 | | No log | 3.4286 | 240 | 1.2087 | 0.5191 | 1.2087 | 1.0994 | | No log | 3.4571 | 242 | 1.0510 | 0.6212 | 1.0510 | 1.0252 | | No log | 3.4857 | 244 | 1.0694 | 0.5954 | 1.0694 | 1.0341 | | No log | 3.5143 | 246 | 1.2784 | 0.5263 | 1.2784 | 1.1307 | | No log | 3.5429 | 248 | 1.4112 | 0.4925 | 1.4112 | 1.1879 | | No log | 3.5714 | 250 | 1.5436 | 0.4058 | 1.5436 | 1.2424 | | No log | 3.6 | 252 | 1.4830 | 0.4234 | 1.4830 | 1.2178 | | No log | 3.6286 | 254 | 1.5739 | 0.3571 | 1.5739 | 1.2546 | | No log | 3.6571 | 256 | 1.5217 | 0.4058 | 1.5217 | 1.2336 | | No log | 3.6857 | 258 | 1.4990 | 0.4148 | 1.4990 | 1.2243 | | No log | 3.7143 | 260 | 1.4782 | 0.4030 | 1.4782 | 1.2158 | | No log | 3.7429 | 262 | 1.4390 | 0.4545 | 1.4390 | 1.1996 | | No log | 3.7714 | 264 | 1.4553 | 0.4545 | 1.4553 | 1.2064 | | No log | 3.8 | 266 | 1.3295 | 0.5191 | 1.3295 | 1.1531 | | No log | 3.8286 | 268 | 1.2024 | 0.5564 | 1.2024 | 1.0965 | | No log | 3.8571 | 270 | 1.1636 | 0.5735 | 1.1636 | 1.0787 | | No log | 3.8857 | 272 | 1.2539 | 0.5 | 1.2539 | 1.1198 | | No log | 3.9143 | 274 | 1.3901 | 0.4559 | 1.3901 | 1.1790 | | No log | 3.9429 | 276 | 1.3526 | 0.4818 | 1.3526 | 1.1630 | | No log | 3.9714 | 278 | 1.4592 | 0.4511 | 1.4592 | 1.2080 | | No log | 4.0 | 280 | 1.8012 | 0.2774 | 1.8012 | 1.3421 | | No log | 4.0286 | 282 | 2.0166 | 0.2014 | 2.0166 | 1.4201 | | No log | 4.0571 | 284 | 1.7866 | 0.3066 | 1.7866 | 1.3366 | | No log | 4.0857 | 286 | 1.3599 | 0.4627 | 1.3599 | 1.1662 | | No log | 4.1143 | 288 | 1.0635 | 0.5865 | 1.0635 | 1.0313 | | No log | 4.1429 | 290 | 1.0123 | 0.6119 | 1.0123 | 1.0061 | | No log | 4.1714 | 292 | 1.1615 | 0.5693 | 1.1615 | 1.0777 | | No log | 4.2 | 294 | 1.3948 | 0.4593 | 1.3948 | 1.1810 | | No log | 4.2286 | 296 | 1.3104 | 0.4889 | 1.3104 | 1.1447 | | No log | 4.2571 | 298 | 1.0651 | 0.5778 | 1.0651 | 1.0320 | | No log | 4.2857 | 300 | 0.9699 | 0.6519 | 0.9699 | 0.9849 | | No log | 4.3143 | 302 | 1.0309 | 0.6176 | 1.0309 | 1.0153 | | No log | 4.3429 | 304 | 1.3110 | 0.4706 | 1.3110 | 1.1450 | | No log | 4.3714 | 306 | 1.7069 | 0.3478 | 1.7069 | 1.3065 | | No log | 4.4 | 308 | 1.7723 | 0.2899 | 1.7723 | 1.3313 | | No log | 4.4286 | 310 | 1.5822 | 0.4088 | 1.5822 | 1.2578 | | No log | 4.4571 | 312 | 1.3861 | 0.5 | 1.3861 | 1.1773 | | No log | 4.4857 | 314 | 1.3641 | 0.5 | 1.3641 | 1.1679 | | No log | 4.5143 | 316 | 1.4717 | 0.4203 | 1.4717 | 1.2131 | | No log | 4.5429 | 318 | 1.6087 | 0.3768 | 1.6087 | 1.2683 | | No log | 4.5714 | 320 | 1.6747 | 0.3453 | 1.6747 | 1.2941 | | No log | 4.6 | 322 | 1.5752 | 0.3942 | 1.5752 | 1.2551 | | No log | 4.6286 | 324 | 1.4327 | 0.4203 | 1.4327 | 1.1970 | | No log | 4.6571 | 326 | 1.2610 | 0.5496 | 1.2610 | 1.1230 | | No log | 4.6857 | 328 | 1.1840 | 0.5758 | 1.1840 | 1.0881 | | No log | 4.7143 | 330 | 1.2157 | 0.5496 | 1.2157 | 1.1026 | | No log | 4.7429 | 332 | 1.3424 | 0.5075 | 1.3424 | 1.1586 | | No log | 4.7714 | 334 | 1.5371 | 0.3407 | 1.5371 | 1.2398 | | No log | 4.8 | 336 | 1.6706 | 0.2878 | 1.6706 | 1.2925 | | No log | 4.8286 | 338 | 1.6747 | 0.2714 | 1.6747 | 1.2941 | | No log | 4.8571 | 340 | 1.5275 | 0.3731 | 1.5275 | 1.2359 | | No log | 4.8857 | 342 | 1.3610 | 0.5414 | 1.3610 | 1.1666 | | No log | 4.9143 | 344 | 1.3677 | 0.5075 | 1.3677 | 1.1695 | | No log | 4.9429 | 346 | 1.4244 | 0.4889 | 1.4244 | 1.1935 | | No log | 4.9714 | 348 | 1.4352 | 0.4380 | 1.4352 | 1.1980 | | No log | 5.0 | 350 | 1.4374 | 0.4380 | 1.4374 | 1.1989 | | No log | 5.0286 | 352 | 1.2030 | 0.5333 | 1.2030 | 1.0968 | | No log | 5.0571 | 354 | 1.1369 | 0.5821 | 1.1369 | 1.0662 | | No log | 5.0857 | 356 | 1.2578 | 0.5333 | 1.2578 | 1.1215 | | No log | 5.1143 | 358 | 1.5682 | 0.3623 | 1.5682 | 1.2523 | | No log | 5.1429 | 360 | 1.7093 | 0.3212 | 1.7093 | 1.3074 | | No log | 5.1714 | 362 | 1.6142 | 0.3286 | 1.6142 | 1.2705 | | No log | 5.2 | 364 | 1.4060 | 0.4706 | 1.4060 | 1.1858 | | No log | 5.2286 | 366 | 1.2391 | 0.5414 | 1.2391 | 1.1131 | | No log | 5.2571 | 368 | 1.1590 | 0.5426 | 1.1590 | 1.0766 | | No log | 5.2857 | 370 | 1.1743 | 0.5426 | 1.1743 | 1.0837 | | No log | 5.3143 | 372 | 1.1697 | 0.5692 | 1.1697 | 1.0815 | | No log | 5.3429 | 374 | 1.2521 | 0.5714 | 1.2521 | 1.1190 | | No log | 5.3714 | 376 | 1.4472 | 0.4706 | 1.4472 | 1.2030 | | No log | 5.4 | 378 | 1.4903 | 0.4706 | 1.4903 | 1.2208 | | No log | 5.4286 | 380 | 1.4069 | 0.4706 | 1.4069 | 1.1861 | | No log | 5.4571 | 382 | 1.3369 | 0.5075 | 1.3369 | 1.1563 | | No log | 5.4857 | 384 | 1.3297 | 0.5075 | 1.3297 | 1.1531 | | No log | 5.5143 | 386 | 1.2427 | 0.5455 | 1.2427 | 1.1148 | | No log | 5.5429 | 388 | 1.0827 | 0.5649 | 1.0827 | 1.0405 | | No log | 5.5714 | 390 | 0.9922 | 0.5692 | 0.9922 | 0.9961 | | No log | 5.6 | 392 | 0.9703 | 0.6015 | 0.9703 | 0.9851 | | No log | 5.6286 | 394 | 1.0948 | 0.5821 | 1.0948 | 1.0463 | | No log | 5.6571 | 396 | 1.3265 | 0.5147 | 1.3265 | 1.1517 | | No log | 5.6857 | 398 | 1.3873 | 0.4889 | 1.3873 | 1.1778 | | No log | 5.7143 | 400 | 1.2730 | 0.5373 | 1.2730 | 1.1283 | | No log | 5.7429 | 402 | 1.2221 | 0.5481 | 1.2221 | 1.1055 | | No log | 5.7714 | 404 | 1.1536 | 0.5649 | 1.1536 | 1.0741 | | No log | 5.8 | 406 | 1.1435 | 0.6015 | 1.1435 | 1.0694 | | No log | 5.8286 | 408 | 1.0895 | 0.6 | 1.0895 | 1.0438 | | No log | 5.8571 | 410 | 1.1584 | 0.5891 | 1.1584 | 1.0763 | | No log | 5.8857 | 412 | 1.2302 | 0.5846 | 1.2302 | 1.1091 | | No log | 5.9143 | 414 | 1.2604 | 0.5606 | 1.2604 | 1.1227 | | No log | 5.9429 | 416 | 1.2379 | 0.5714 | 1.2379 | 1.1126 | | No log | 5.9714 | 418 | 1.0615 | 0.5649 | 1.0615 | 1.0303 | | No log | 6.0 | 420 | 0.9040 | 0.6015 | 0.9040 | 0.9508 | | No log | 6.0286 | 422 | 0.8775 | 0.5970 | 0.8775 | 0.9367 | | No log | 6.0571 | 424 | 1.0238 | 0.5714 | 1.0238 | 1.0118 | | No log | 6.0857 | 426 | 1.2761 | 0.4889 | 1.2761 | 1.1297 | | No log | 6.1143 | 428 | 1.3554 | 0.5072 | 1.3554 | 1.1642 | | No log | 6.1429 | 430 | 1.2540 | 0.4885 | 1.2540 | 1.1198 | | No log | 6.1714 | 432 | 1.0339 | 0.5231 | 1.0339 | 1.0168 | | No log | 6.2 | 434 | 0.9861 | 0.5736 | 0.9861 | 0.9930 | | No log | 6.2286 | 436 | 1.1010 | 0.5385 | 1.1010 | 1.0493 | | No log | 6.2571 | 438 | 1.2149 | 0.5455 | 1.2149 | 1.1022 | | No log | 6.2857 | 440 | 1.3697 | 0.5077 | 1.3697 | 1.1703 | | No log | 6.3143 | 442 | 1.3210 | 0.5970 | 1.3210 | 1.1494 | | No log | 6.3429 | 444 | 1.2623 | 0.5985 | 1.2623 | 1.1235 | | No log | 6.3714 | 446 | 1.2335 | 0.5821 | 1.2335 | 1.1106 | | No log | 6.4 | 448 | 1.2572 | 0.5564 | 1.2572 | 1.1213 | | No log | 6.4286 | 450 | 1.2073 | 0.5564 | 1.2073 | 1.0988 | | No log | 6.4571 | 452 | 1.1963 | 0.5303 | 1.1963 | 1.0938 | | No log | 6.4857 | 454 | 1.2310 | 0.5564 | 1.2310 | 1.1095 | | No log | 6.5143 | 456 | 1.2620 | 0.5778 | 1.2620 | 1.1234 | | No log | 6.5429 | 458 | 1.2205 | 0.5714 | 1.2205 | 1.1048 | | No log | 6.5714 | 460 | 1.1813 | 0.5758 | 1.1813 | 1.0869 | | No log | 6.6 | 462 | 1.1858 | 0.5758 | 1.1858 | 1.0890 | | No log | 6.6286 | 464 | 1.2509 | 0.5758 | 1.2509 | 1.1184 | | No log | 6.6571 | 466 | 1.3665 | 0.4593 | 1.3665 | 1.1690 | | No log | 6.6857 | 468 | 1.3494 | 0.4706 | 1.3494 | 1.1616 | | No log | 6.7143 | 470 | 1.3706 | 0.4818 | 1.3706 | 1.1707 | | No log | 6.7429 | 472 | 1.2916 | 0.5072 | 1.2916 | 1.1365 | | No log | 6.7714 | 474 | 1.1484 | 0.5985 | 1.1484 | 1.0716 | | No log | 6.8 | 476 | 1.1952 | 0.5985 | 1.1952 | 1.0932 | | No log | 6.8286 | 478 | 1.2637 | 0.5441 | 1.2637 | 1.1241 | | No log | 6.8571 | 480 | 1.2950 | 0.5441 | 1.2950 | 1.1380 | | No log | 6.8857 | 482 | 1.2568 | 0.5778 | 1.2568 | 1.1211 | | No log | 6.9143 | 484 | 1.2612 | 0.5778 | 1.2612 | 1.1230 | | No log | 6.9429 | 486 | 1.1672 | 0.5821 | 1.1672 | 1.0804 | | No log | 6.9714 | 488 | 1.1548 | 0.5649 | 1.1548 | 1.0746 | | No log | 7.0 | 490 | 1.2945 | 0.5522 | 1.2945 | 1.1378 | | No log | 7.0286 | 492 | 1.4219 | 0.4812 | 1.4219 | 1.1924 | | No log | 7.0571 | 494 | 1.3554 | 0.5152 | 1.3554 | 1.1642 | | No log | 7.0857 | 496 | 1.2111 | 0.5197 | 1.2111 | 1.1005 | | No log | 7.1143 | 498 | 1.2144 | 0.4793 | 1.2144 | 1.1020 | | 0.3532 | 7.1429 | 500 | 1.2226 | 0.5323 | 1.2226 | 1.1057 | | 0.3532 | 7.1714 | 502 | 1.2471 | 0.5385 | 1.2471 | 1.1167 | | 0.3532 | 7.2 | 504 | 1.3811 | 0.4925 | 1.3811 | 1.1752 | | 0.3532 | 7.2286 | 506 | 1.4908 | 0.3971 | 1.4908 | 1.2210 | | 0.3532 | 7.2571 | 508 | 1.4098 | 0.5 | 1.4098 | 1.1874 | | 0.3532 | 7.2857 | 510 | 1.3510 | 0.5 | 1.3510 | 1.1623 | | 0.3532 | 7.3143 | 512 | 1.3337 | 0.5373 | 1.3337 | 1.1549 | | 0.3532 | 7.3429 | 514 | 1.2646 | 0.5649 | 1.2646 | 1.1245 | | 0.3532 | 7.3714 | 516 | 1.2132 | 0.5938 | 1.2132 | 1.1015 | | 0.3532 | 7.4 | 518 | 1.2061 | 0.5938 | 1.2061 | 1.0982 | | 0.3532 | 7.4286 | 520 | 1.2082 | 0.5649 | 1.2082 | 1.0992 | | 0.3532 | 7.4571 | 522 | 1.2063 | 0.5649 | 1.2063 | 1.0983 | | 0.3532 | 7.4857 | 524 | 1.2944 | 0.5373 | 1.2944 | 1.1377 | | 0.3532 | 7.5143 | 526 | 1.3583 | 0.4672 | 1.3583 | 1.1654 | | 0.3532 | 7.5429 | 528 | 1.3764 | 0.4783 | 1.3764 | 1.1732 | | 0.3532 | 7.5714 | 530 | 1.4234 | 0.4853 | 1.4234 | 1.1931 | | 0.3532 | 7.6 | 532 | 1.5196 | 0.4234 | 1.5196 | 1.2327 | | 0.3532 | 7.6286 | 534 | 1.3764 | 0.4593 | 1.3764 | 1.1732 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

ClarenceDan/fb4700b3-f04a-48ac-b7f7-8b018fb175ac

ClarenceDan

2025-01-15T15:45:10Z

8

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:20:36Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: fb4700b3-f04a-48ac-b7f7-8b018fb175ac results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/fb4700b3-f04a-48ac-b7f7-8b018fb175ac hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # fb4700b3-f04a-48ac-b7f7-8b018fb175ac This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0001 | 1 | nan | | 0.0 | 0.0002 | 3 | nan | | 0.0 | 0.0003 | 6 | nan | | 0.0 | 0.0005 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Keltezaa/Katie_Thomas_Actress

Keltezaa

2025-01-15T15:44:56Z

39

0

diffusers

[ "diffusers", "text-to-image", "lora", "template:diffusion-lora", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:cc-by-nc-nd-4.0", "region:us" ]

text-to-image

2025-01-15T15:40:47Z

--- tags: - text-to-image - lora - diffusers - template:diffusion-lora widget: - text: >- 35mm photograph of a young woman, (wearing a jacket:1.5),having a coffee in a vintage cafe, smile, professional, atmospheric haze, excellent dynamic range, masterpiece, excellent quality, ultra detailed, subtle lighting, soft focus, detailed shadows output: url: images/example_9nxcl3qpv.png base_model: black-forest-labs/FLUX.1-dev instance_prompt: null license: cc-by-nc-nd-4.0 --- # Katie Thomas Actress <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Keltezaa/Katie_Thomas_Actress/tree/main) them in the Files & versions tab.

Patnev71/floorplanv2

Patnev71

2025-01-15T15:44:45Z

5

0

transformers

[ "transformers", "safetensors", "segformer", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

null

2025-01-15T15:44:43Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

dzanbek/cc00dfb0-c695-416a-8916-6686f2159be0

dzanbek

2025-01-15T15:44:05Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]

null

2025-01-15T14:15:45Z

--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: cc00dfb0-c695-416a-8916-6686f2159be0 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dzanbek/cc00dfb0-c695-416a-8916-6686f2159be0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # cc00dfb0-c695-416a-8916-6686f2159be0 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0005 | 10 | nan | | 0.0 | 0.0007 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

kk-aivio/fe65bf08-5d51-4a1f-a7a4-29850ba83120

kk-aivio

2025-01-15T15:42:14Z

10

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "base_model:adapter:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B", "region:us" ]

null

2025-01-15T15:12:58Z

--- library_name: peft base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B tags: - axolotl - generated_from_trainer model-index: - name: fe65bf08-5d51-4a1f-a7a4-29850ba83120 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 6e6190eb26c4eb66_train_data.json ds_type: json format: custom path: /workspace/input_data/6e6190eb26c4eb66_train_data.json type: field_input: user_input field_instruction: prompt field_output: chosen format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kk-aivio/fe65bf08-5d51-4a1f-a7a4-29850ba83120 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/6e6190eb26c4eb66_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: <|eot_id|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 wandb_project: birthday-sn56-17-Gradients-On-Demand wandb_run: your_name wandb_runid: 22a7e7a8-f3c8-4b2e-bae8-382fa9d6d294 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # fe65bf08-5d51-4a1f-a7a4-29850ba83120 This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.8674 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 2.145 | 0.0001 | 1 | 2.5498 | | 2.7495 | 0.0002 | 3 | 2.5397 | | 1.9831 | 0.0003 | 6 | 2.3370 | | 2.0553 | 0.0005 | 9 | 1.8674 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF

itlwas

2025-01-15T15:42:05Z

25

0

transformers

[ "transformers", "gguf", "ROC", "Taiwan", "zh-tw", "llama-factory", "llama-cpp", "gguf-my-repo", "text-generation", "zh", "en", "dataset:lianghsun/tw-novel-1.1B", "dataset:lianghsun/tw-finance-159M", "dataset:lianghsun/tw-legal-news-24M", "dataset:lianghsun/tw-gov-news-90M", "dataset:lianghsun/tw-gov-556k", "dataset:lianghsun/tw-news-551M", "dataset:lianghsun/tw-health-43M", "dataset:lianghsun/tw-science-24M", "dataset:lianghsun/tw-book-43M", "dataset:lianghsun/tw-society-88M", "dataset:lianghsun/tw-law-article-evolution", "dataset:lianghsun/tw-processed-judgments", "dataset:lianghsun/tw-legal-methodology", "dataset:lianghsun/tw-legal-qa", "dataset:lianghsun/tw-judgment-gist", "dataset:lianghsun/reasoning-base-20k", "dataset:lianghsun/wikipedia-zh-filtered", "dataset:AWeirdDev/zh-tw-pts-articles-sm", "dataset:bhxiang/c4_calibrate_mini", "dataset:benchang1110/pretrainedtw", "dataset:benchang1110/sciencetw", "dataset:intfloat/multilingual_cc_news", "base_model:lianghsun/Llama-3.2-Taiwan-3B", "base_model:quantized:lianghsun/Llama-3.2-Taiwan-3B", "license:llama3.2", "endpoints_compatible", "region:us", "conversational" ]

text-generation

2025-01-15T15:41:53Z

--- base_model: lianghsun/Llama-3.2-Taiwan-3B library_name: transformers datasets: - lianghsun/tw-novel-1.1B - lianghsun/tw-finance-159M - lianghsun/tw-legal-news-24M - lianghsun/tw-gov-news-90M - lianghsun/tw-gov-556k - lianghsun/tw-news-551M - lianghsun/tw-health-43M - lianghsun/tw-science-24M - lianghsun/tw-book-43M - lianghsun/tw-society-88M - lianghsun/tw-law-article-evolution - lianghsun/tw-processed-judgments - lianghsun/tw-legal-methodology - lianghsun/tw-legal-qa - lianghsun/tw-judgment-gist - lianghsun/reasoning-base-20k - lianghsun/wikipedia-zh-filtered - AWeirdDev/zh-tw-pts-articles-sm - bhxiang/c4_calibrate_mini - benchang1110/pretrainedtw - benchang1110/sciencetw - intfloat/multilingual_cc_news language: - zh - en license: llama3.2 tags: - ROC - Taiwan - zh-tw - llama-factory - llama-cpp - gguf-my-repo new_version: lianghsun/Llama-3.2-Taiwan-3B-Instruct pipeline_tag: text-generation widget: - text: 中華民國憲法第一條 --- # itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF This model was converted to GGUF format from [`lianghsun/Llama-3.2-Taiwan-3B`](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/lianghsun/Llama-3.2-Taiwan-3B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo itlwas/Llama-3.2-Taiwan-3B-Q4_K_M-GGUF --hf-file llama-3.2-taiwan-3b-q4_k_m.gguf -c 2048 ```

thaffggg/a02adaab-00b1-4220-a9a9-154dea3495b5

thaffggg

2025-01-15T15:39:09Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-4k-instruct", "base_model:adapter:microsoft/Phi-3-mini-4k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:20:01Z

--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-4k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a02adaab-00b1-4220-a9a9-154dea3495b5 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-4k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 80c99709830fd48a_train_data.json ds_type: json format: custom path: /workspace/input_data/80c99709830fd48a_train_data.json type: field_instruction: input field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/a02adaab-00b1-4220-a9a9-154dea3495b5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/80c99709830fd48a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # a02adaab-00b1-4220-a9a9-154dea3495b5 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4311 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.7407 | 0.1206 | 200 | 0.4311 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

asafd60/HebQwen-json-2025-meta

asafd60

2025-01-15T15:38:37Z

84

0

transformers

[ "transformers", "safetensors", "qwen2_vl", "image-text-to-text", "conversational", "arxiv:1910.09700", "text-generation-inference", "endpoints_compatible", "region:us" ]

image-text-to-text

2025-01-15T15:32:36Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

cunghoctienganh/a4f8f6b7-473d-44a0-ad19-9c32ae368864

cunghoctienganh

2025-01-15T15:38:30Z

6

0

peft

[ "peft", "safetensors", "phi3", "axolotl", "generated_from_trainer", "custom_code", "base_model:microsoft/Phi-3-mini-4k-instruct", "base_model:adapter:microsoft/Phi-3-mini-4k-instruct", "license:mit", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:19:21Z

--- library_name: peft license: mit base_model: microsoft/Phi-3-mini-4k-instruct tags: - axolotl - generated_from_trainer model-index: - name: a4f8f6b7-473d-44a0-ad19-9c32ae368864 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: microsoft/Phi-3-mini-4k-instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 80c99709830fd48a_train_data.json ds_type: json format: custom path: /workspace/input_data/80c99709830fd48a_train_data.json type: field_instruction: input field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: cunghoctienganh/a4f8f6b7-473d-44a0-ad19-9c32ae368864 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/80c99709830fd48a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e24b6a86-83f1-40ca-ac06-bdb6e674fa7c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # a4f8f6b7-473d-44a0-ad19-9c32ae368864 This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4312 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.7471 | 0.1206 | 200 | 0.4312 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thangla01/cc2b4a23-f3b3-4c69-aaa5-14746b129c9c

thangla01

2025-01-15T15:38:26Z

8

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/Mistral-Nemo-Base-2407", "base_model:adapter:unsloth/Mistral-Nemo-Base-2407", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:35:58Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Mistral-Nemo-Base-2407 tags: - axolotl - generated_from_trainer model-index: - name: cc2b4a23-f3b3-4c69-aaa5-14746b129c9c results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Mistral-Nemo-Base-2407 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - a807bb88794a6c5a_train_data.json ds_type: json format: custom path: /workspace/input_data/a807bb88794a6c5a_train_data.json type: field_instruction: prompt field_output: label format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thangla01/cc2b4a23-f3b3-4c69-aaa5-14746b129c9c hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/a807bb88794a6c5a_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f19c28d2-bbf3-4c64-b448-7d3ff5c4b03c warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # cc2b4a23-f3b3-4c69-aaa5-14746b129c9c This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6362 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 6.8421 | 0.0105 | 200 | 1.6362 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization

MayBashendy

2025-01-15T15:38:20Z

6

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T14:51:41Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization results: [] ---  # ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6404 - Qwk: 0.5029 - Mse: 0.6404 - Rmse: 0.8003 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0377 | 2 | 4.2473 | -0.0228 | 4.2473 | 2.0609 | | No log | 0.0755 | 4 | 2.3310 | 0.0238 | 2.3310 | 1.5268 | | No log | 0.1132 | 6 | 1.3560 | 0.0205 | 1.3560 | 1.1645 | | No log | 0.1509 | 8 | 0.9130 | 0.0383 | 0.9130 | 0.9555 | | No log | 0.1887 | 10 | 0.8565 | 0.1596 | 0.8565 | 0.9255 | | No log | 0.2264 | 12 | 1.0357 | 0.0713 | 1.0357 | 1.0177 | | No log | 0.2642 | 14 | 1.0549 | 0.1234 | 1.0549 | 1.0271 | | No log | 0.3019 | 16 | 0.8566 | 0.1477 | 0.8566 | 0.9255 | | No log | 0.3396 | 18 | 1.1207 | 0.1474 | 1.1207 | 1.0587 | | No log | 0.3774 | 20 | 1.6261 | 0.0643 | 1.6261 | 1.2752 | | No log | 0.4151 | 22 | 1.5250 | 0.0550 | 1.5250 | 1.2349 | | No log | 0.4528 | 24 | 1.2243 | 0.0677 | 1.2243 | 1.1065 | | No log | 0.4906 | 26 | 0.9723 | 0.1509 | 0.9723 | 0.9860 | | No log | 0.5283 | 28 | 0.9085 | 0.1681 | 0.9085 | 0.9532 | | No log | 0.5660 | 30 | 0.8029 | 0.2499 | 0.8029 | 0.8961 | | No log | 0.6038 | 32 | 0.8286 | 0.1573 | 0.8286 | 0.9103 | | No log | 0.6415 | 34 | 0.8689 | 0.1731 | 0.8689 | 0.9322 | | No log | 0.6792 | 36 | 1.1002 | 0.0847 | 1.1002 | 1.0489 | | No log | 0.7170 | 38 | 1.4252 | 0.0868 | 1.4252 | 1.1938 | | No log | 0.7547 | 40 | 1.8930 | 0.1372 | 1.8930 | 1.3759 | | No log | 0.7925 | 42 | 1.7148 | 0.1316 | 1.7148 | 1.3095 | | No log | 0.8302 | 44 | 1.2532 | 0.2452 | 1.2532 | 1.1195 | | No log | 0.8679 | 46 | 0.9984 | 0.2395 | 0.9984 | 0.9992 | | No log | 0.9057 | 48 | 1.0085 | 0.2069 | 1.0085 | 1.0042 | | No log | 0.9434 | 50 | 0.8329 | 0.3641 | 0.8329 | 0.9126 | | No log | 0.9811 | 52 | 0.6157 | 0.3959 | 0.6157 | 0.7846 | | No log | 1.0189 | 54 | 0.6081 | 0.4061 | 0.6081 | 0.7798 | | No log | 1.0566 | 56 | 0.6818 | 0.3701 | 0.6818 | 0.8257 | | No log | 1.0943 | 58 | 0.9277 | 0.2847 | 0.9277 | 0.9632 | | No log | 1.1321 | 60 | 1.0415 | 0.3412 | 1.0415 | 1.0205 | | No log | 1.1698 | 62 | 0.9216 | 0.3506 | 0.9216 | 0.9600 | | No log | 1.2075 | 64 | 0.6502 | 0.4398 | 0.6502 | 0.8063 | | No log | 1.2453 | 66 | 0.7747 | 0.2631 | 0.7747 | 0.8802 | | No log | 1.2830 | 68 | 0.9121 | 0.1402 | 0.9121 | 0.9550 | | No log | 1.3208 | 70 | 0.7329 | 0.2601 | 0.7329 | 0.8561 | | No log | 1.3585 | 72 | 0.6610 | 0.5366 | 0.6610 | 0.8130 | | No log | 1.3962 | 74 | 0.9865 | 0.4573 | 0.9865 | 0.9932 | | No log | 1.4340 | 76 | 1.1531 | 0.3424 | 1.1531 | 1.0738 | | No log | 1.4717 | 78 | 0.9473 | 0.4736 | 0.9473 | 0.9733 | | No log | 1.5094 | 80 | 0.9756 | 0.4506 | 0.9756 | 0.9877 | | No log | 1.5472 | 82 | 0.9997 | 0.4460 | 0.9997 | 0.9999 | | No log | 1.5849 | 84 | 1.2514 | 0.2979 | 1.2514 | 1.1187 | | No log | 1.6226 | 86 | 1.2607 | 0.3124 | 1.2607 | 1.1228 | | No log | 1.6604 | 88 | 1.3783 | 0.2598 | 1.3783 | 1.1740 | | No log | 1.6981 | 90 | 1.3063 | 0.2830 | 1.3063 | 1.1429 | | No log | 1.7358 | 92 | 0.9235 | 0.4575 | 0.9235 | 0.9610 | | No log | 1.7736 | 94 | 0.5829 | 0.4552 | 0.5829 | 0.7635 | | No log | 1.8113 | 96 | 0.6093 | 0.4342 | 0.6093 | 0.7805 | | No log | 1.8491 | 98 | 0.5742 | 0.3628 | 0.5742 | 0.7578 | | No log | 1.8868 | 100 | 0.6228 | 0.4603 | 0.6228 | 0.7892 | | No log | 1.9245 | 102 | 0.6994 | 0.5053 | 0.6994 | 0.8363 | | No log | 1.9623 | 104 | 0.5974 | 0.4997 | 0.5974 | 0.7729 | | No log | 2.0 | 106 | 0.5891 | 0.5375 | 0.5891 | 0.7675 | | No log | 2.0377 | 108 | 0.6116 | 0.5281 | 0.6116 | 0.7821 | | No log | 2.0755 | 110 | 0.6222 | 0.6008 | 0.6222 | 0.7888 | | No log | 2.1132 | 112 | 0.7781 | 0.5635 | 0.7781 | 0.8821 | | No log | 2.1509 | 114 | 1.1884 | 0.3373 | 1.1884 | 1.0902 | | No log | 2.1887 | 116 | 1.5178 | 0.2919 | 1.5178 | 1.2320 | | No log | 2.2264 | 118 | 1.2534 | 0.3059 | 1.2534 | 1.1195 | | No log | 2.2642 | 120 | 0.7709 | 0.5254 | 0.7709 | 0.8780 | | No log | 2.3019 | 122 | 0.5978 | 0.5234 | 0.5978 | 0.7732 | | No log | 2.3396 | 124 | 0.6255 | 0.4921 | 0.6255 | 0.7909 | | No log | 2.3774 | 126 | 0.5841 | 0.5536 | 0.5841 | 0.7643 | | No log | 2.4151 | 128 | 0.7852 | 0.5560 | 0.7852 | 0.8861 | | No log | 2.4528 | 130 | 0.9215 | 0.3990 | 0.9215 | 0.9599 | | No log | 2.4906 | 132 | 0.7816 | 0.5569 | 0.7816 | 0.8841 | | No log | 2.5283 | 134 | 0.5990 | 0.5452 | 0.5990 | 0.7739 | | No log | 2.5660 | 136 | 0.5412 | 0.4919 | 0.5412 | 0.7357 | | No log | 2.6038 | 138 | 0.5472 | 0.4689 | 0.5472 | 0.7397 | | No log | 2.6415 | 140 | 0.7115 | 0.5535 | 0.7115 | 0.8435 | | No log | 2.6792 | 142 | 1.3119 | 0.3421 | 1.3119 | 1.1454 | | No log | 2.7170 | 144 | 1.5224 | 0.2856 | 1.5224 | 1.2338 | | No log | 2.7547 | 146 | 1.1841 | 0.4041 | 1.1841 | 1.0882 | | No log | 2.7925 | 148 | 0.9617 | 0.4544 | 0.9617 | 0.9807 | | No log | 2.8302 | 150 | 0.8756 | 0.4804 | 0.8756 | 0.9358 | | No log | 2.8679 | 152 | 0.9670 | 0.4648 | 0.9670 | 0.9834 | | No log | 2.9057 | 154 | 1.1254 | 0.3595 | 1.1254 | 1.0609 | | No log | 2.9434 | 156 | 0.9562 | 0.4757 | 0.9562 | 0.9779 | | No log | 2.9811 | 158 | 0.7437 | 0.5500 | 0.7437 | 0.8624 | | No log | 3.0189 | 160 | 0.6462 | 0.5414 | 0.6462 | 0.8039 | | No log | 3.0566 | 162 | 0.6470 | 0.5277 | 0.6470 | 0.8044 | | No log | 3.0943 | 164 | 0.7120 | 0.5137 | 0.7120 | 0.8438 | | No log | 3.1321 | 166 | 0.8192 | 0.5071 | 0.8192 | 0.9051 | | No log | 3.1698 | 168 | 0.9236 | 0.4534 | 0.9236 | 0.9610 | | No log | 3.2075 | 170 | 0.8508 | 0.5040 | 0.8508 | 0.9224 | | No log | 3.2453 | 172 | 0.7356 | 0.5419 | 0.7356 | 0.8577 | | No log | 3.2830 | 174 | 0.6803 | 0.5183 | 0.6803 | 0.8248 | | No log | 3.3208 | 176 | 0.6747 | 0.5787 | 0.6747 | 0.8214 | | No log | 3.3585 | 178 | 0.6850 | 0.5714 | 0.6850 | 0.8277 | | No log | 3.3962 | 180 | 0.7099 | 0.5388 | 0.7099 | 0.8426 | | No log | 3.4340 | 182 | 0.7962 | 0.5214 | 0.7962 | 0.8923 | | No log | 3.4717 | 184 | 0.7702 | 0.5532 | 0.7702 | 0.8776 | | No log | 3.5094 | 186 | 0.6431 | 0.5696 | 0.6431 | 0.8019 | | No log | 3.5472 | 188 | 0.6170 | 0.5693 | 0.6170 | 0.7855 | | No log | 3.5849 | 190 | 0.7147 | 0.5322 | 0.7147 | 0.8454 | | No log | 3.6226 | 192 | 0.9754 | 0.4538 | 0.9754 | 0.9876 | | No log | 3.6604 | 194 | 1.0223 | 0.4284 | 1.0223 | 1.0111 | | No log | 3.6981 | 196 | 0.8039 | 0.5049 | 0.8039 | 0.8966 | | No log | 3.7358 | 198 | 0.6262 | 0.5378 | 0.6262 | 0.7913 | | No log | 3.7736 | 200 | 0.5897 | 0.544 | 0.5897 | 0.7679 | | No log | 3.8113 | 202 | 0.5879 | 0.4848 | 0.5879 | 0.7667 | | No log | 3.8491 | 204 | 0.6732 | 0.5162 | 0.6732 | 0.8205 | | No log | 3.8868 | 206 | 0.7012 | 0.5104 | 0.7012 | 0.8374 | | No log | 3.9245 | 208 | 0.7607 | 0.5141 | 0.7607 | 0.8722 | | No log | 3.9623 | 210 | 0.7177 | 0.4838 | 0.7177 | 0.8472 | | No log | 4.0 | 212 | 0.7243 | 0.4587 | 0.7243 | 0.8511 | | No log | 4.0377 | 214 | 0.7986 | 0.4752 | 0.7986 | 0.8937 | | No log | 4.0755 | 216 | 0.8368 | 0.4465 | 0.8368 | 0.9147 | | No log | 4.1132 | 218 | 0.7661 | 0.4456 | 0.7661 | 0.8753 | | No log | 4.1509 | 220 | 0.6834 | 0.4762 | 0.6834 | 0.8267 | | No log | 4.1887 | 222 | 0.6034 | 0.5200 | 0.6034 | 0.7768 | | No log | 4.2264 | 224 | 0.5829 | 0.5026 | 0.5829 | 0.7635 | | No log | 4.2642 | 226 | 0.5522 | 0.5046 | 0.5522 | 0.7431 | | No log | 4.3019 | 228 | 0.6732 | 0.5143 | 0.6732 | 0.8205 | | No log | 4.3396 | 230 | 0.8137 | 0.5024 | 0.8137 | 0.9020 | | No log | 4.3774 | 232 | 0.7688 | 0.5289 | 0.7688 | 0.8768 | | No log | 4.4151 | 234 | 0.6635 | 0.5474 | 0.6635 | 0.8146 | | No log | 4.4528 | 236 | 0.5890 | 0.5847 | 0.5890 | 0.7675 | | No log | 4.4906 | 238 | 0.5520 | 0.5296 | 0.5520 | 0.7430 | | No log | 4.5283 | 240 | 0.5479 | 0.4513 | 0.5479 | 0.7402 | | No log | 4.5660 | 242 | 0.5546 | 0.4287 | 0.5546 | 0.7447 | | No log | 4.6038 | 244 | 0.6018 | 0.4705 | 0.6018 | 0.7758 | | No log | 4.6415 | 246 | 0.8159 | 0.4863 | 0.8159 | 0.9033 | | No log | 4.6792 | 248 | 0.9919 | 0.3930 | 0.9919 | 0.9959 | | No log | 4.7170 | 250 | 0.8988 | 0.4560 | 0.8988 | 0.9480 | | No log | 4.7547 | 252 | 0.7981 | 0.5224 | 0.7981 | 0.8934 | | No log | 4.7925 | 254 | 0.7082 | 0.5429 | 0.7082 | 0.8416 | | No log | 4.8302 | 256 | 0.6740 | 0.5810 | 0.6740 | 0.8210 | | No log | 4.8679 | 258 | 0.6624 | 0.5910 | 0.6624 | 0.8139 | | No log | 4.9057 | 260 | 0.6916 | 0.5185 | 0.6916 | 0.8316 | | No log | 4.9434 | 262 | 0.8107 | 0.4617 | 0.8107 | 0.9004 | | No log | 4.9811 | 264 | 0.9351 | 0.4061 | 0.9351 | 0.9670 | | No log | 5.0189 | 266 | 0.9234 | 0.4039 | 0.9234 | 0.9609 | | No log | 5.0566 | 268 | 0.7650 | 0.5064 | 0.7650 | 0.8746 | | No log | 5.0943 | 270 | 0.6317 | 0.5487 | 0.6317 | 0.7948 | | No log | 5.1321 | 272 | 0.5789 | 0.4779 | 0.5789 | 0.7609 | | No log | 5.1698 | 274 | 0.6494 | 0.4821 | 0.6494 | 0.8058 | | No log | 5.2075 | 276 | 0.6298 | 0.4959 | 0.6298 | 0.7936 | | No log | 5.2453 | 278 | 0.5982 | 0.5173 | 0.5981 | 0.7734 | | No log | 5.2830 | 280 | 0.8517 | 0.4940 | 0.8517 | 0.9229 | | No log | 5.3208 | 282 | 1.2323 | 0.2818 | 1.2323 | 1.1101 | | No log | 5.3585 | 284 | 1.2627 | 0.2595 | 1.2627 | 1.1237 | | No log | 5.3962 | 286 | 0.9694 | 0.4360 | 0.9694 | 0.9846 | | No log | 5.4340 | 288 | 0.6580 | 0.5133 | 0.6580 | 0.8112 | | No log | 5.4717 | 290 | 0.5646 | 0.5791 | 0.5646 | 0.7514 | | No log | 5.5094 | 292 | 0.5872 | 0.4476 | 0.5872 | 0.7663 | | No log | 5.5472 | 294 | 0.5897 | 0.4657 | 0.5897 | 0.7679 | | No log | 5.5849 | 296 | 0.5925 | 0.5642 | 0.5925 | 0.7697 | | No log | 5.6226 | 298 | 0.6847 | 0.5382 | 0.6847 | 0.8275 | | No log | 5.6604 | 300 | 0.9729 | 0.4245 | 0.9729 | 0.9864 | | No log | 5.6981 | 302 | 1.3748 | 0.3148 | 1.3748 | 1.1725 | | No log | 5.7358 | 304 | 1.6679 | 0.2424 | 1.6679 | 1.2915 | | No log | 5.7736 | 306 | 1.5423 | 0.2462 | 1.5423 | 1.2419 | | No log | 5.8113 | 308 | 1.1594 | 0.3335 | 1.1594 | 1.0767 | | No log | 5.8491 | 310 | 0.8002 | 0.4709 | 0.8002 | 0.8945 | | No log | 5.8868 | 312 | 0.5973 | 0.5889 | 0.5973 | 0.7729 | | No log | 5.9245 | 314 | 0.5677 | 0.6079 | 0.5677 | 0.7535 | | No log | 5.9623 | 316 | 0.5561 | 0.6258 | 0.5561 | 0.7457 | | No log | 6.0 | 318 | 0.5507 | 0.6429 | 0.5507 | 0.7421 | | No log | 6.0377 | 320 | 0.5508 | 0.6175 | 0.5508 | 0.7422 | | No log | 6.0755 | 322 | 0.5591 | 0.6309 | 0.5591 | 0.7478 | | No log | 6.1132 | 324 | 0.5875 | 0.6441 | 0.5875 | 0.7665 | | No log | 6.1509 | 326 | 0.6572 | 0.5946 | 0.6572 | 0.8107 | | No log | 6.1887 | 328 | 0.7346 | 0.5047 | 0.7346 | 0.8571 | | No log | 6.2264 | 330 | 0.7883 | 0.4531 | 0.7883 | 0.8879 | | No log | 6.2642 | 332 | 0.7583 | 0.4830 | 0.7583 | 0.8708 | | No log | 6.3019 | 334 | 0.6975 | 0.5044 | 0.6975 | 0.8352 | | No log | 6.3396 | 336 | 0.6328 | 0.5577 | 0.6328 | 0.7955 | | No log | 6.3774 | 338 | 0.6077 | 0.6084 | 0.6077 | 0.7796 | | No log | 6.4151 | 340 | 0.6454 | 0.6105 | 0.6454 | 0.8034 | | No log | 6.4528 | 342 | 0.6772 | 0.6293 | 0.6772 | 0.8229 | | No log | 6.4906 | 344 | 0.7261 | 0.5732 | 0.7261 | 0.8521 | | No log | 6.5283 | 346 | 0.8307 | 0.4926 | 0.8307 | 0.9115 | | No log | 6.5660 | 348 | 0.8205 | 0.4750 | 0.8205 | 0.9058 | | No log | 6.6038 | 350 | 0.7000 | 0.5564 | 0.7000 | 0.8367 | | No log | 6.6415 | 352 | 0.5884 | 0.5860 | 0.5884 | 0.7670 | | No log | 6.6792 | 354 | 0.5588 | 0.6040 | 0.5588 | 0.7475 | | No log | 6.7170 | 356 | 0.5540 | 0.5842 | 0.5540 | 0.7443 | | No log | 6.7547 | 358 | 0.5684 | 0.5746 | 0.5684 | 0.7540 | | No log | 6.7925 | 360 | 0.5849 | 0.5558 | 0.5849 | 0.7648 | | No log | 6.8302 | 362 | 0.5776 | 0.5804 | 0.5776 | 0.7600 | | No log | 6.8679 | 364 | 0.5644 | 0.5859 | 0.5644 | 0.7512 | | No log | 6.9057 | 366 | 0.5538 | 0.5618 | 0.5538 | 0.7442 | | No log | 6.9434 | 368 | 0.5417 | 0.5377 | 0.5417 | 0.7360 | | No log | 6.9811 | 370 | 0.5460 | 0.4654 | 0.5460 | 0.7389 | | No log | 7.0189 | 372 | 0.5722 | 0.4889 | 0.5722 | 0.7565 | | No log | 7.0566 | 374 | 0.5693 | 0.4889 | 0.5693 | 0.7545 | | No log | 7.0943 | 376 | 0.6087 | 0.5328 | 0.6087 | 0.7802 | | No log | 7.1321 | 378 | 0.5971 | 0.5242 | 0.5971 | 0.7727 | | No log | 7.1698 | 380 | 0.5952 | 0.5262 | 0.5952 | 0.7715 | | No log | 7.2075 | 382 | 0.5716 | 0.5724 | 0.5716 | 0.7560 | | No log | 7.2453 | 384 | 0.5663 | 0.5643 | 0.5663 | 0.7525 | | No log | 7.2830 | 386 | 0.5560 | 0.5641 | 0.5560 | 0.7456 | | No log | 7.3208 | 388 | 0.5432 | 0.4990 | 0.5432 | 0.7370 | | No log | 7.3585 | 390 | 0.5355 | 0.5048 | 0.5355 | 0.7318 | | No log | 7.3962 | 392 | 0.5335 | 0.4804 | 0.5335 | 0.7304 | | No log | 7.4340 | 394 | 0.5408 | 0.5046 | 0.5408 | 0.7354 | | No log | 7.4717 | 396 | 0.5895 | 0.5395 | 0.5895 | 0.7678 | | No log | 7.5094 | 398 | 0.6544 | 0.5187 | 0.6544 | 0.8089 | | No log | 7.5472 | 400 | 0.6710 | 0.5369 | 0.6710 | 0.8192 | | No log | 7.5849 | 402 | 0.6784 | 0.5301 | 0.6784 | 0.8236 | | No log | 7.6226 | 404 | 0.6731 | 0.5271 | 0.6731 | 0.8204 | | No log | 7.6604 | 406 | 0.7178 | 0.5552 | 0.7178 | 0.8472 | | No log | 7.6981 | 408 | 0.7901 | 0.5554 | 0.7901 | 0.8889 | | No log | 7.7358 | 410 | 0.9238 | 0.4669 | 0.9238 | 0.9611 | | No log | 7.7736 | 412 | 0.9980 | 0.4031 | 0.9980 | 0.9990 | | No log | 7.8113 | 414 | 0.9183 | 0.4453 | 0.9183 | 0.9583 | | No log | 7.8491 | 416 | 0.7103 | 0.5337 | 0.7103 | 0.8428 | | No log | 7.8868 | 418 | 0.6005 | 0.5762 | 0.6005 | 0.7749 | | No log | 7.9245 | 420 | 0.5906 | 0.4772 | 0.5906 | 0.7685 | | No log | 7.9623 | 422 | 0.5679 | 0.4024 | 0.5679 | 0.7536 | | No log | 8.0 | 424 | 0.5324 | 0.3755 | 0.5324 | 0.7296 | | No log | 8.0377 | 426 | 0.5280 | 0.4100 | 0.5280 | 0.7266 | | No log | 8.0755 | 428 | 0.5301 | 0.4996 | 0.5301 | 0.7281 | | No log | 8.1132 | 430 | 0.5226 | 0.4621 | 0.5226 | 0.7229 | | No log | 8.1509 | 432 | 0.5423 | 0.5516 | 0.5423 | 0.7364 | | No log | 8.1887 | 434 | 0.5498 | 0.6100 | 0.5498 | 0.7415 | | No log | 8.2264 | 436 | 0.5586 | 0.6482 | 0.5586 | 0.7474 | | No log | 8.2642 | 438 | 0.6275 | 0.5434 | 0.6275 | 0.7922 | | No log | 8.3019 | 440 | 0.6392 | 0.5291 | 0.6392 | 0.7995 | | No log | 8.3396 | 442 | 0.5715 | 0.5607 | 0.5715 | 0.7560 | | No log | 8.3774 | 444 | 0.5203 | 0.5805 | 0.5203 | 0.7213 | | No log | 8.4151 | 446 | 0.5551 | 0.5067 | 0.5551 | 0.7451 | | No log | 8.4528 | 448 | 0.5769 | 0.4789 | 0.5769 | 0.7596 | | No log | 8.4906 | 450 | 0.5339 | 0.5006 | 0.5339 | 0.7307 | | No log | 8.5283 | 452 | 0.5035 | 0.4897 | 0.5035 | 0.7096 | | No log | 8.5660 | 454 | 0.5923 | 0.5489 | 0.5923 | 0.7696 | | No log | 8.6038 | 456 | 0.6918 | 0.5313 | 0.6918 | 0.8318 | | No log | 8.6415 | 458 | 0.7063 | 0.5126 | 0.7063 | 0.8404 | | No log | 8.6792 | 460 | 0.6414 | 0.5401 | 0.6414 | 0.8009 | | No log | 8.7170 | 462 | 0.5628 | 0.6358 | 0.5628 | 0.7502 | | No log | 8.7547 | 464 | 0.5601 | 0.6314 | 0.5601 | 0.7484 | | No log | 8.7925 | 466 | 0.5738 | 0.6288 | 0.5738 | 0.7575 | | No log | 8.8302 | 468 | 0.6672 | 0.5434 | 0.6672 | 0.8169 | | No log | 8.8679 | 470 | 0.8416 | 0.4655 | 0.8416 | 0.9174 | | No log | 8.9057 | 472 | 0.8374 | 0.4467 | 0.8374 | 0.9151 | | No log | 8.9434 | 474 | 0.6751 | 0.4961 | 0.6751 | 0.8216 | | No log | 8.9811 | 476 | 0.5743 | 0.5342 | 0.5743 | 0.7578 | | No log | 9.0189 | 478 | 0.5423 | 0.5137 | 0.5423 | 0.7364 | | No log | 9.0566 | 480 | 0.5473 | 0.5446 | 0.5473 | 0.7398 | | No log | 9.0943 | 482 | 0.5612 | 0.5665 | 0.5612 | 0.7491 | | No log | 9.1321 | 484 | 0.5746 | 0.5318 | 0.5747 | 0.7581 | | No log | 9.1698 | 486 | 0.6079 | 0.5389 | 0.6079 | 0.7797 | | No log | 9.2075 | 488 | 0.6587 | 0.5355 | 0.6587 | 0.8116 | | No log | 9.2453 | 490 | 0.6466 | 0.5158 | 0.6466 | 0.8041 | | No log | 9.2830 | 492 | 0.5998 | 0.5187 | 0.5998 | 0.7744 | | No log | 9.3208 | 494 | 0.5841 | 0.4931 | 0.5841 | 0.7643 | | No log | 9.3585 | 496 | 0.5826 | 0.4931 | 0.5826 | 0.7633 | | No log | 9.3962 | 498 | 0.6094 | 0.5269 | 0.6094 | 0.7806 | | 0.4026 | 9.4340 | 500 | 0.6498 | 0.4771 | 0.6498 | 0.8061 | | 0.4026 | 9.4717 | 502 | 0.7081 | 0.4931 | 0.7081 | 0.8415 | | 0.4026 | 9.5094 | 504 | 0.6831 | 0.4858 | 0.6831 | 0.8265 | | 0.4026 | 9.5472 | 506 | 0.6339 | 0.5921 | 0.6339 | 0.7962 | | 0.4026 | 9.5849 | 508 | 0.6050 | 0.5660 | 0.6050 | 0.7778 | | 0.4026 | 9.6226 | 510 | 0.6029 | 0.5348 | 0.6029 | 0.7765 | | 0.4026 | 9.6604 | 512 | 0.5805 | 0.5531 | 0.5805 | 0.7619 | | 0.4026 | 9.6981 | 514 | 0.5793 | 0.4448 | 0.5793 | 0.7611 | | 0.4026 | 9.7358 | 516 | 0.6128 | 0.4777 | 0.6128 | 0.7828 | | 0.4026 | 9.7736 | 518 | 0.6073 | 0.4777 | 0.6073 | 0.7793 | | 0.4026 | 9.8113 | 520 | 0.5890 | 0.4941 | 0.5890 | 0.7674 | | 0.4026 | 9.8491 | 522 | 0.6008 | 0.5494 | 0.6008 | 0.7751 | | 0.4026 | 9.8868 | 524 | 0.6307 | 0.6296 | 0.6307 | 0.7942 | | 0.4026 | 9.9245 | 526 | 0.6690 | 0.5738 | 0.6690 | 0.8179 | | 0.4026 | 9.9623 | 528 | 0.7104 | 0.4782 | 0.7104 | 0.8429 | | 0.4026 | 10.0 | 530 | 0.7745 | 0.4514 | 0.7745 | 0.8801 | | 0.4026 | 10.0377 | 532 | 0.7810 | 0.4642 | 0.7810 | 0.8837 | | 0.4026 | 10.0755 | 534 | 0.6887 | 0.4742 | 0.6887 | 0.8299 | | 0.4026 | 10.1132 | 536 | 0.6139 | 0.5396 | 0.6139 | 0.7835 | | 0.4026 | 10.1509 | 538 | 0.5841 | 0.5476 | 0.5841 | 0.7643 | | 0.4026 | 10.1887 | 540 | 0.5686 | 0.5402 | 0.5686 | 0.7541 | | 0.4026 | 10.2264 | 542 | 0.5925 | 0.5269 | 0.5925 | 0.7698 | | 0.4026 | 10.2642 | 544 | 0.5995 | 0.4816 | 0.5995 | 0.7743 | | 0.4026 | 10.3019 | 546 | 0.5616 | 0.4984 | 0.5616 | 0.7494 | | 0.4026 | 10.3396 | 548 | 0.5623 | 0.5271 | 0.5623 | 0.7499 | | 0.4026 | 10.3774 | 550 | 0.6186 | 0.5229 | 0.6186 | 0.7865 | | 0.4026 | 10.4151 | 552 | 0.6444 | 0.5453 | 0.6444 | 0.8027 | | 0.4026 | 10.4528 | 554 | 0.6285 | 0.5237 | 0.6285 | 0.7928 | | 0.4026 | 10.4906 | 556 | 0.6011 | 0.5447 | 0.6011 | 0.7753 | | 0.4026 | 10.5283 | 558 | 0.5841 | 0.5861 | 0.5841 | 0.7643 | | 0.4026 | 10.5660 | 560 | 0.5949 | 0.5238 | 0.5949 | 0.7713 | | 0.4026 | 10.6038 | 562 | 0.5829 | 0.5649 | 0.5829 | 0.7635 | | 0.4026 | 10.6415 | 564 | 0.5605 | 0.5341 | 0.5605 | 0.7486 | | 0.4026 | 10.6792 | 566 | 0.5942 | 0.5437 | 0.5942 | 0.7708 | | 0.4026 | 10.7170 | 568 | 0.6717 | 0.4899 | 0.6717 | 0.8196 | | 0.4026 | 10.7547 | 570 | 0.6902 | 0.4899 | 0.6902 | 0.8308 | | 0.4026 | 10.7925 | 572 | 0.6270 | 0.5578 | 0.6270 | 0.7918 | | 0.4026 | 10.8302 | 574 | 0.5758 | 0.5919 | 0.5758 | 0.7588 | | 0.4026 | 10.8679 | 576 | 0.5609 | 0.5746 | 0.5609 | 0.7489 | | 0.4026 | 10.9057 | 578 | 0.5661 | 0.5514 | 0.5661 | 0.7524 | | 0.4026 | 10.9434 | 580 | 0.5552 | 0.5593 | 0.5552 | 0.7451 | | 0.4026 | 10.9811 | 582 | 0.5368 | 0.5970 | 0.5368 | 0.7326 | | 0.4026 | 11.0189 | 584 | 0.5309 | 0.5560 | 0.5309 | 0.7286 | | 0.4026 | 11.0566 | 586 | 0.5418 | 0.5589 | 0.5418 | 0.7361 | | 0.4026 | 11.0943 | 588 | 0.5484 | 0.5777 | 0.5484 | 0.7406 | | 0.4026 | 11.1321 | 590 | 0.5748 | 0.5442 | 0.5748 | 0.7582 | | 0.4026 | 11.1698 | 592 | 0.5988 | 0.5629 | 0.5988 | 0.7738 | | 0.4026 | 11.2075 | 594 | 0.5828 | 0.5570 | 0.5828 | 0.7634 | | 0.4026 | 11.2453 | 596 | 0.5513 | 0.6214 | 0.5513 | 0.7425 | | 0.4026 | 11.2830 | 598 | 0.5608 | 0.5872 | 0.5608 | 0.7489 | | 0.4026 | 11.3208 | 600 | 0.5678 | 0.6336 | 0.5678 | 0.7535 | | 0.4026 | 11.3585 | 602 | 0.5578 | 0.6292 | 0.5578 | 0.7469 | | 0.4026 | 11.3962 | 604 | 0.5570 | 0.6111 | 0.5570 | 0.7463 | | 0.4026 | 11.4340 | 606 | 0.6239 | 0.5537 | 0.6239 | 0.7899 | | 0.4026 | 11.4717 | 608 | 0.6865 | 0.5001 | 0.6865 | 0.8285 | | 0.4026 | 11.5094 | 610 | 0.6768 | 0.5178 | 0.6768 | 0.8227 | | 0.4026 | 11.5472 | 612 | 0.5969 | 0.5299 | 0.5969 | 0.7726 | | 0.4026 | 11.5849 | 614 | 0.5379 | 0.6202 | 0.5379 | 0.7334 | | 0.4026 | 11.6226 | 616 | 0.5269 | 0.5943 | 0.5269 | 0.7259 | | 0.4026 | 11.6604 | 618 | 0.5273 | 0.5522 | 0.5273 | 0.7262 | | 0.4026 | 11.6981 | 620 | 0.5315 | 0.4704 | 0.5315 | 0.7290 | | 0.4026 | 11.7358 | 622 | 0.5357 | 0.4693 | 0.5357 | 0.7319 | | 0.4026 | 11.7736 | 624 | 0.5408 | 0.4763 | 0.5408 | 0.7354 | | 0.4026 | 11.8113 | 626 | 0.5448 | 0.5294 | 0.5448 | 0.7381 | | 0.4026 | 11.8491 | 628 | 0.5527 | 0.5948 | 0.5527 | 0.7434 | | 0.4026 | 11.8868 | 630 | 0.5598 | 0.6508 | 0.5598 | 0.7482 | | 0.4026 | 11.9245 | 632 | 0.5630 | 0.6100 | 0.5630 | 0.7504 | | 0.4026 | 11.9623 | 634 | 0.5638 | 0.5968 | 0.5638 | 0.7509 | | 0.4026 | 12.0 | 636 | 0.5580 | 0.6151 | 0.5580 | 0.7470 | | 0.4026 | 12.0377 | 638 | 0.5523 | 0.6151 | 0.5523 | 0.7432 | | 0.4026 | 12.0755 | 640 | 0.5518 | 0.5886 | 0.5518 | 0.7428 | | 0.4026 | 12.1132 | 642 | 0.5606 | 0.5969 | 0.5606 | 0.7487 | | 0.4026 | 12.1509 | 644 | 0.5594 | 0.5722 | 0.5594 | 0.7479 | | 0.4026 | 12.1887 | 646 | 0.5685 | 0.53 | 0.5685 | 0.7540 | | 0.4026 | 12.2264 | 648 | 0.5943 | 0.5674 | 0.5943 | 0.7709 | | 0.4026 | 12.2642 | 650 | 0.6236 | 0.6040 | 0.6236 | 0.7897 | | 0.4026 | 12.3019 | 652 | 0.6388 | 0.6125 | 0.6388 | 0.7992 | | 0.4026 | 12.3396 | 654 | 0.6041 | 0.6178 | 0.6041 | 0.7772 | | 0.4026 | 12.3774 | 656 | 0.5825 | 0.6264 | 0.5825 | 0.7632 | | 0.4026 | 12.4151 | 658 | 0.5679 | 0.5762 | 0.5679 | 0.7536 | | 0.4026 | 12.4528 | 660 | 0.5633 | 0.5067 | 0.5633 | 0.7505 | | 0.4026 | 12.4906 | 662 | 0.5971 | 0.4847 | 0.5971 | 0.7727 | | 0.4026 | 12.5283 | 664 | 0.6482 | 0.4899 | 0.6482 | 0.8051 | | 0.4026 | 12.5660 | 666 | 0.6779 | 0.5240 | 0.6779 | 0.8234 | | 0.4026 | 12.6038 | 668 | 0.6705 | 0.5282 | 0.6705 | 0.8189 | | 0.4026 | 12.6415 | 670 | 0.6883 | 0.5501 | 0.6883 | 0.8296 | | 0.4026 | 12.6792 | 672 | 0.7226 | 0.5104 | 0.7226 | 0.8501 | | 0.4026 | 12.7170 | 674 | 0.6862 | 0.5238 | 0.6862 | 0.8284 | | 0.4026 | 12.7547 | 676 | 0.6551 | 0.5396 | 0.6551 | 0.8094 | | 0.4026 | 12.7925 | 678 | 0.6419 | 0.5340 | 0.6419 | 0.8012 | | 0.4026 | 12.8302 | 680 | 0.5884 | 0.5355 | 0.5884 | 0.7671 | | 0.4026 | 12.8679 | 682 | 0.5400 | 0.5896 | 0.5400 | 0.7349 | | 0.4026 | 12.9057 | 684 | 0.5287 | 0.5767 | 0.5287 | 0.7271 | | 0.4026 | 12.9434 | 686 | 0.5255 | 0.4666 | 0.5255 | 0.7249 | | 0.4026 | 12.9811 | 688 | 0.5244 | 0.4816 | 0.5244 | 0.7241 | | 0.4026 | 13.0189 | 690 | 0.5278 | 0.5004 | 0.5278 | 0.7265 | | 0.4026 | 13.0566 | 692 | 0.5362 | 0.5856 | 0.5362 | 0.7322 | | 0.4026 | 13.0943 | 694 | 0.5394 | 0.5211 | 0.5394 | 0.7345 | | 0.4026 | 13.1321 | 696 | 0.5516 | 0.5197 | 0.5516 | 0.7427 | | 0.4026 | 13.1698 | 698 | 0.5498 | 0.5197 | 0.5498 | 0.7415 | | 0.4026 | 13.2075 | 700 | 0.5545 | 0.5197 | 0.5545 | 0.7447 | | 0.4026 | 13.2453 | 702 | 0.5731 | 0.5223 | 0.5731 | 0.7570 | | 0.4026 | 13.2830 | 704 | 0.5552 | 0.5197 | 0.5552 | 0.7451 | | 0.4026 | 13.3208 | 706 | 0.5549 | 0.5197 | 0.5549 | 0.7449 | | 0.4026 | 13.3585 | 708 | 0.5819 | 0.5010 | 0.5819 | 0.7628 | | 0.4026 | 13.3962 | 710 | 0.5824 | 0.4920 | 0.5824 | 0.7632 | | 0.4026 | 13.4340 | 712 | 0.5841 | 0.5010 | 0.5841 | 0.7643 | | 0.4026 | 13.4717 | 714 | 0.5661 | 0.4740 | 0.5661 | 0.7524 | | 0.4026 | 13.5094 | 716 | 0.5719 | 0.5130 | 0.5719 | 0.7562 | | 0.4026 | 13.5472 | 718 | 0.5917 | 0.5262 | 0.5917 | 0.7692 | | 0.4026 | 13.5849 | 720 | 0.6151 | 0.5205 | 0.6151 | 0.7843 | | 0.4026 | 13.6226 | 722 | 0.6434 | 0.5072 | 0.6434 | 0.8021 | | 0.4026 | 13.6604 | 724 | 0.6276 | 0.4949 | 0.6276 | 0.7922 | | 0.4026 | 13.6981 | 726 | 0.5934 | 0.4935 | 0.5934 | 0.7703 | | 0.4026 | 13.7358 | 728 | 0.5870 | 0.4908 | 0.5870 | 0.7661 | | 0.4026 | 13.7736 | 730 | 0.5700 | 0.5524 | 0.5700 | 0.7550 | | 0.4026 | 13.8113 | 732 | 0.5656 | 0.6182 | 0.5656 | 0.7520 | | 0.4026 | 13.8491 | 734 | 0.5804 | 0.6054 | 0.5804 | 0.7619 | | 0.4026 | 13.8868 | 736 | 0.6192 | 0.5462 | 0.6192 | 0.7869 | | 0.4026 | 13.9245 | 738 | 0.6436 | 0.5109 | 0.6436 | 0.8022 | | 0.4026 | 13.9623 | 740 | 0.6516 | 0.5066 | 0.6516 | 0.8072 | | 0.4026 | 14.0 | 742 | 0.6361 | 0.5176 | 0.6361 | 0.7976 | | 0.4026 | 14.0377 | 744 | 0.6154 | 0.5101 | 0.6154 | 0.7845 | | 0.4026 | 14.0755 | 746 | 0.5645 | 0.5878 | 0.5645 | 0.7513 | | 0.4026 | 14.1132 | 748 | 0.5596 | 0.6190 | 0.5596 | 0.7480 | | 0.4026 | 14.1509 | 750 | 0.5807 | 0.5571 | 0.5807 | 0.7621 | | 0.4026 | 14.1887 | 752 | 0.5913 | 0.5840 | 0.5913 | 0.7689 | | 0.4026 | 14.2264 | 754 | 0.5706 | 0.6046 | 0.5706 | 0.7554 | | 0.4026 | 14.2642 | 756 | 0.5529 | 0.6461 | 0.5529 | 0.7436 | | 0.4026 | 14.3019 | 758 | 0.5776 | 0.5482 | 0.5776 | 0.7600 | | 0.4026 | 14.3396 | 760 | 0.6419 | 0.5207 | 0.6419 | 0.8012 | | 0.4026 | 14.3774 | 762 | 0.6703 | 0.4790 | 0.6703 | 0.8187 | | 0.4026 | 14.4151 | 764 | 0.6680 | 0.4916 | 0.6680 | 0.8173 | | 0.4026 | 14.4528 | 766 | 0.6454 | 0.5284 | 0.6454 | 0.8034 | | 0.4026 | 14.4906 | 768 | 0.5906 | 0.5660 | 0.5906 | 0.7685 | | 0.4026 | 14.5283 | 770 | 0.5657 | 0.6221 | 0.5657 | 0.7521 | | 0.4026 | 14.5660 | 772 | 0.5493 | 0.6707 | 0.5493 | 0.7411 | | 0.4026 | 14.6038 | 774 | 0.5489 | 0.6429 | 0.5489 | 0.7409 | | 0.4026 | 14.6415 | 776 | 0.5699 | 0.5510 | 0.5699 | 0.7549 | | 0.4026 | 14.6792 | 778 | 0.5806 | 0.5425 | 0.5806 | 0.7619 | | 0.4026 | 14.7170 | 780 | 0.5693 | 0.5514 | 0.5693 | 0.7545 | | 0.4026 | 14.7547 | 782 | 0.5407 | 0.6059 | 0.5407 | 0.7354 | | 0.4026 | 14.7925 | 784 | 0.5329 | 0.6322 | 0.5329 | 0.7300 | | 0.4026 | 14.8302 | 786 | 0.5516 | 0.6479 | 0.5516 | 0.7427 | | 0.4026 | 14.8679 | 788 | 0.6065 | 0.5923 | 0.6065 | 0.7788 | | 0.4026 | 14.9057 | 790 | 0.6305 | 0.5952 | 0.6305 | 0.7941 | | 0.4026 | 14.9434 | 792 | 0.6533 | 0.5898 | 0.6533 | 0.8082 | | 0.4026 | 14.9811 | 794 | 0.7234 | 0.4894 | 0.7234 | 0.8505 | | 0.4026 | 15.0189 | 796 | 0.7686 | 0.4736 | 0.7686 | 0.8767 | | 0.4026 | 15.0566 | 798 | 0.7126 | 0.4996 | 0.7126 | 0.8441 | | 0.4026 | 15.0943 | 800 | 0.6281 | 0.5070 | 0.6281 | 0.7925 | | 0.4026 | 15.1321 | 802 | 0.5525 | 0.6103 | 0.5525 | 0.7433 | | 0.4026 | 15.1698 | 804 | 0.5437 | 0.6582 | 0.5437 | 0.7373 | | 0.4026 | 15.2075 | 806 | 0.5752 | 0.6160 | 0.5752 | 0.7584 | | 0.4026 | 15.2453 | 808 | 0.5765 | 0.6462 | 0.5765 | 0.7593 | | 0.4026 | 15.2830 | 810 | 0.5650 | 0.6936 | 0.5650 | 0.7517 | | 0.4026 | 15.3208 | 812 | 0.5896 | 0.6098 | 0.5896 | 0.7679 | | 0.4026 | 15.3585 | 814 | 0.6334 | 0.5324 | 0.6334 | 0.7958 | | 0.4026 | 15.3962 | 816 | 0.6662 | 0.5117 | 0.6662 | 0.8162 | | 0.4026 | 15.4340 | 818 | 0.6409 | 0.4959 | 0.6409 | 0.8006 | | 0.4026 | 15.4717 | 820 | 0.5866 | 0.5220 | 0.5866 | 0.7659 | | 0.4026 | 15.5094 | 822 | 0.5443 | 0.5510 | 0.5443 | 0.7378 | | 0.4026 | 15.5472 | 824 | 0.5345 | 0.5723 | 0.5345 | 0.7311 | | 0.4026 | 15.5849 | 826 | 0.5417 | 0.5702 | 0.5417 | 0.7360 | | 0.4026 | 15.6226 | 828 | 0.5403 | 0.6262 | 0.5403 | 0.7350 | | 0.4026 | 15.6604 | 830 | 0.5824 | 0.5425 | 0.5824 | 0.7631 | | 0.4026 | 15.6981 | 832 | 0.6294 | 0.5107 | 0.6294 | 0.7933 | | 0.4026 | 15.7358 | 834 | 0.6359 | 0.5107 | 0.6359 | 0.7974 | | 0.4026 | 15.7736 | 836 | 0.5840 | 0.5226 | 0.5840 | 0.7642 | | 0.4026 | 15.8113 | 838 | 0.5516 | 0.5326 | 0.5516 | 0.7427 | | 0.4026 | 15.8491 | 840 | 0.5465 | 0.4654 | 0.5465 | 0.7392 | | 0.4026 | 15.8868 | 842 | 0.5452 | 0.5185 | 0.5452 | 0.7384 | | 0.4026 | 15.9245 | 844 | 0.5479 | 0.5540 | 0.5479 | 0.7402 | | 0.4026 | 15.9623 | 846 | 0.5709 | 0.5478 | 0.5709 | 0.7556 | | 0.4026 | 16.0 | 848 | 0.5965 | 0.5244 | 0.5965 | 0.7723 | | 0.4026 | 16.0377 | 850 | 0.5855 | 0.5244 | 0.5855 | 0.7652 | | 0.4026 | 16.0755 | 852 | 0.5563 | 0.5236 | 0.5563 | 0.7458 | | 0.4026 | 16.1132 | 854 | 0.5512 | 0.5236 | 0.5512 | 0.7425 | | 0.4026 | 16.1509 | 856 | 0.5425 | 0.5236 | 0.5425 | 0.7366 | | 0.4026 | 16.1887 | 858 | 0.5488 | 0.5236 | 0.5488 | 0.7408 | | 0.4026 | 16.2264 | 860 | 0.5559 | 0.4886 | 0.5559 | 0.7456 | | 0.4026 | 16.2642 | 862 | 0.5384 | 0.5155 | 0.5384 | 0.7338 | | 0.4026 | 16.3019 | 864 | 0.5216 | 0.4828 | 0.5216 | 0.7222 | | 0.4026 | 16.3396 | 866 | 0.5268 | 0.5323 | 0.5268 | 0.7258 | | 0.4026 | 16.3774 | 868 | 0.5287 | 0.5185 | 0.5287 | 0.7271 | | 0.4026 | 16.4151 | 870 | 0.5528 | 0.5339 | 0.5528 | 0.7435 | | 0.4026 | 16.4528 | 872 | 0.6222 | 0.5080 | 0.6222 | 0.7888 | | 0.4026 | 16.4906 | 874 | 0.7171 | 0.5038 | 0.7171 | 0.8468 | | 0.4026 | 16.5283 | 876 | 0.7497 | 0.4812 | 0.7497 | 0.8658 | | 0.4026 | 16.5660 | 878 | 0.6911 | 0.4845 | 0.6911 | 0.8313 | | 0.4026 | 16.6038 | 880 | 0.6496 | 0.5364 | 0.6496 | 0.8060 | | 0.4026 | 16.6415 | 882 | 0.6414 | 0.5208 | 0.6414 | 0.8009 | | 0.4026 | 16.6792 | 884 | 0.5922 | 0.5420 | 0.5922 | 0.7695 | | 0.4026 | 16.7170 | 886 | 0.5651 | 0.6104 | 0.5651 | 0.7517 | | 0.4026 | 16.7547 | 888 | 0.5588 | 0.5669 | 0.5588 | 0.7475 | | 0.4026 | 16.7925 | 890 | 0.5557 | 0.5481 | 0.5557 | 0.7455 | | 0.4026 | 16.8302 | 892 | 0.5771 | 0.4740 | 0.5771 | 0.7597 | | 0.4026 | 16.8679 | 894 | 0.5899 | 0.4550 | 0.5899 | 0.7680 | | 0.4026 | 16.9057 | 896 | 0.5709 | 0.4102 | 0.5709 | 0.7556 | | 0.4026 | 16.9434 | 898 | 0.5444 | 0.4642 | 0.5444 | 0.7378 | | 0.4026 | 16.9811 | 900 | 0.5414 | 0.5285 | 0.5414 | 0.7358 | | 0.4026 | 17.0189 | 902 | 0.5508 | 0.5601 | 0.5508 | 0.7422 | | 0.4026 | 17.0566 | 904 | 0.5689 | 0.5713 | 0.5689 | 0.7543 | | 0.4026 | 17.0943 | 906 | 0.6032 | 0.5619 | 0.6032 | 0.7766 | | 0.4026 | 17.1321 | 908 | 0.6153 | 0.5504 | 0.6153 | 0.7844 | | 0.4026 | 17.1698 | 910 | 0.6342 | 0.5334 | 0.6342 | 0.7964 | | 0.4026 | 17.2075 | 912 | 0.6339 | 0.5214 | 0.6339 | 0.7962 | | 0.4026 | 17.2453 | 914 | 0.6112 | 0.5437 | 0.6112 | 0.7818 | | 0.4026 | 17.2830 | 916 | 0.5990 | 0.5355 | 0.5990 | 0.7739 | | 0.4026 | 17.3208 | 918 | 0.6068 | 0.5536 | 0.6068 | 0.7789 | | 0.4026 | 17.3585 | 920 | 0.6082 | 0.6025 | 0.6082 | 0.7799 | | 0.4026 | 17.3962 | 922 | 0.6076 | 0.5941 | 0.6076 | 0.7795 | | 0.4026 | 17.4340 | 924 | 0.5976 | 0.5650 | 0.5976 | 0.7731 | | 0.4026 | 17.4717 | 926 | 0.5777 | 0.5848 | 0.5777 | 0.7601 | | 0.4026 | 17.5094 | 928 | 0.5699 | 0.5968 | 0.5699 | 0.7549 | | 0.4026 | 17.5472 | 930 | 0.5633 | 0.5972 | 0.5633 | 0.7505 | | 0.4026 | 17.5849 | 932 | 0.5612 | 0.5489 | 0.5612 | 0.7491 | | 0.4026 | 17.6226 | 934 | 0.5579 | 0.5320 | 0.5579 | 0.7469 | | 0.4026 | 17.6604 | 936 | 0.5655 | 0.5476 | 0.5655 | 0.7520 | | 0.4026 | 17.6981 | 938 | 0.5781 | 0.5565 | 0.5781 | 0.7603 | | 0.4026 | 17.7358 | 940 | 0.5921 | 0.5649 | 0.5921 | 0.7695 | | 0.4026 | 17.7736 | 942 | 0.5825 | 0.5811 | 0.5825 | 0.7632 | | 0.4026 | 17.8113 | 944 | 0.5678 | 0.5728 | 0.5678 | 0.7535 | | 0.4026 | 17.8491 | 946 | 0.5673 | 0.5684 | 0.5673 | 0.7532 | | 0.4026 | 17.8868 | 948 | 0.5647 | 0.5402 | 0.5647 | 0.7514 | | 0.4026 | 17.9245 | 950 | 0.5597 | 0.5323 | 0.5597 | 0.7481 | | 0.4026 | 17.9623 | 952 | 0.5595 | 0.4975 | 0.5595 | 0.7480 | | 0.4026 | 18.0 | 954 | 0.5616 | 0.5131 | 0.5616 | 0.7494 | | 0.4026 | 18.0377 | 956 | 0.5634 | 0.5323 | 0.5634 | 0.7506 | | 0.4026 | 18.0755 | 958 | 0.5776 | 0.5176 | 0.5776 | 0.7600 | | 0.4026 | 18.1132 | 960 | 0.5828 | 0.5176 | 0.5828 | 0.7634 | | 0.4026 | 18.1509 | 962 | 0.5774 | 0.4913 | 0.5774 | 0.7599 | | 0.4026 | 18.1887 | 964 | 0.5772 | 0.4913 | 0.5772 | 0.7598 | | 0.4026 | 18.2264 | 966 | 0.5806 | 0.4913 | 0.5806 | 0.7620 | | 0.4026 | 18.2642 | 968 | 0.5831 | 0.4928 | 0.5831 | 0.7636 | | 0.4026 | 18.3019 | 970 | 0.5795 | 0.5019 | 0.5795 | 0.7612 | | 0.4026 | 18.3396 | 972 | 0.5723 | 0.5312 | 0.5723 | 0.7565 | | 0.4026 | 18.3774 | 974 | 0.5806 | 0.5500 | 0.5806 | 0.7620 | | 0.4026 | 18.4151 | 976 | 0.5773 | 0.5500 | 0.5773 | 0.7598 | | 0.4026 | 18.4528 | 978 | 0.5773 | 0.5500 | 0.5773 | 0.7598 | | 0.4026 | 18.4906 | 980 | 0.5722 | 0.5164 | 0.5722 | 0.7565 | | 0.4026 | 18.5283 | 982 | 0.5644 | 0.4888 | 0.5644 | 0.7513 | | 0.4026 | 18.5660 | 984 | 0.5568 | 0.4864 | 0.5568 | 0.7462 | | 0.4026 | 18.6038 | 986 | 0.5575 | 0.5078 | 0.5575 | 0.7467 | | 0.4026 | 18.6415 | 988 | 0.5570 | 0.5078 | 0.5570 | 0.7463 | | 0.4026 | 18.6792 | 990 | 0.5582 | 0.5004 | 0.5582 | 0.7471 | | 0.4026 | 18.7170 | 992 | 0.5635 | 0.4835 | 0.5635 | 0.7506 | | 0.4026 | 18.7547 | 994 | 0.5736 | 0.4812 | 0.5736 | 0.7574 | | 0.4026 | 18.7925 | 996 | 0.5634 | 0.4904 | 0.5634 | 0.7506 | | 0.4026 | 18.8302 | 998 | 0.5571 | 0.5147 | 0.5571 | 0.7464 | | 0.0707 | 18.8679 | 1000 | 0.5565 | 0.5421 | 0.5565 | 0.7460 | | 0.0707 | 18.9057 | 1002 | 0.5585 | 0.4857 | 0.5585 | 0.7473 | | 0.0707 | 18.9434 | 1004 | 0.5899 | 0.5059 | 0.5899 | 0.7681 | | 0.0707 | 18.9811 | 1006 | 0.6331 | 0.4695 | 0.6331 | 0.7957 | | 0.0707 | 19.0189 | 1008 | 0.6374 | 0.5029 | 0.6374 | 0.7983 | | 0.0707 | 19.0566 | 1010 | 0.6404 | 0.5029 | 0.6404 | 0.8003 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

deepnet111/sn9-3b-018

deepnet111

2025-01-15T15:37:50Z

178

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-15T15:35:47Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

cabustillo13/roberta-base-bne-platzi-project-nlp

cabustillo13

2025-01-15T15:37:14Z

14

0

transformers

[ "transformers", "tensorboard", "safetensors", "roberta", "text-classification", "generated_from_trainer", "base_model:BSC-LT/roberta-base-bne", "base_model:finetune:BSC-LT/roberta-base-bne", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T04:08:44Z

--- library_name: transformers license: apache-2.0 base_model: BSC-TeMU/roberta-base-bne tags: - generated_from_trainer metrics: - accuracy model-index: - name: roberta-base-bne-platzi-project-nlp results: [] ---  # roberta-base-bne-platzi-project-nlp This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4563 - Accuracy: 0.8538 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3594 | 1.0 | 2500 | 0.3971 | 0.8436 | | 0.2582 | 2.0 | 5000 | 0.4563 | 0.8538 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Tokenizers 0.21.0

mradermacher/WiNGPT-Babel-GGUF

mradermacher

2025-01-15T15:36:52Z

262

0

transformers

[ "transformers", "gguf", "translation", "multilingual", "en", "zh", "base_model:winninghealth/WiNGPT-Babel", "base_model:quantized:winninghealth/WiNGPT-Babel", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

translation

2025-01-15T15:23:35Z

--- base_model: winninghealth/WiNGPT-Babel language: - en - zh library_name: transformers license: apache-2.0 quantized_by: mradermacher tags: - translation - multilingual --- ## About      static quants of https://huggingface.co/winninghealth/WiNGPT-Babel  weighted/imatrix quants are available at https://huggingface.co/mradermacher/WiNGPT-Babel-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q2_K.gguf) | Q2_K | 0.8 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_S.gguf) | Q3_K_S | 0.9 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q3_K_L.gguf) | Q3_K_L | 1.0 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.IQ4_XS.gguf) | IQ4_XS | 1.0 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q5_K_S.gguf) | Q5_K_S | 1.2 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q5_K_M.gguf) | Q5_K_M | 1.2 | | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q6_K.gguf) | Q6_K | 1.4 | very good quality | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality | | [GGUF](https://huggingface.co/mradermacher/WiNGPT-Babel-GGUF/resolve/main/WiNGPT-Babel.f16.gguf) | f16 | 3.2 | 16 bpw, overkill | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.

lesso06/933a3df0-e8dc-4b5f-808c-5edc7e3ea567

lesso06

2025-01-15T15:35:57Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen1.5-7B", "base_model:adapter:Qwen/Qwen1.5-7B", "license:other", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:32:36Z

--- library_name: peft license: other base_model: Qwen/Qwen1.5-7B tags: - axolotl - generated_from_trainer model-index: - name: 933a3df0-e8dc-4b5f-808c-5edc7e3ea567 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen1.5-7B bf16: true chat_template: llama3 datasets: - data_files: - 59ee0b6235c26daa_train_data.json ds_type: json format: custom path: /workspace/input_data/59ee0b6235c26daa_train_data.json type: field_input: pronoun field_instruction: sentence field_output: definition format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso06/933a3df0-e8dc-4b5f-808c-5edc7e3ea567 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/59ee0b6235c26daa_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cac36870-8e18-426e-9717-ca6857936964 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cac36870-8e18-426e-9717-ca6857936964 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 933a3df0-e8dc-4b5f-808c-5edc7e3ea567 This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6562 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.5612 | 0.0035 | 1 | 3.7545 | | 3.549 | 0.0177 | 5 | 3.5143 | | 2.8654 | 0.0354 | 10 | 2.2111 | | 1.9689 | 0.0531 | 15 | 1.8258 | | 1.7188 | 0.0707 | 20 | 1.6879 | | 1.7133 | 0.0884 | 25 | 1.6562 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

August4293/Llama3.1-8B-PRM-Deepseek-Data-4bit

August4293

2025-01-15T15:35:53Z

16

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]

text-generation

2025-01-15T15:33:26Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

MayBashendy/ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization

MayBashendy

2025-01-15T15:35:39Z

7

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T15:17:34Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization results: [] ---  # ArabicNewSplits7_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k13_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8239 - Qwk: 0.6567 - Mse: 0.8239 - Rmse: 0.9077 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:| | No log | 0.0206 | 2 | 6.6386 | 0.0308 | 6.6386 | 2.5766 | | No log | 0.0412 | 4 | 4.3409 | 0.0894 | 4.3409 | 2.0835 | | No log | 0.0619 | 6 | 2.9340 | 0.1149 | 2.9340 | 1.7129 | | No log | 0.0825 | 8 | 2.5329 | 0.0970 | 2.5329 | 1.5915 | | No log | 0.1031 | 10 | 2.0854 | 0.1260 | 2.0854 | 1.4441 | | No log | 0.1237 | 12 | 1.7133 | 0.2655 | 1.7133 | 1.3089 | | No log | 0.1443 | 14 | 1.5473 | 0.1852 | 1.5473 | 1.2439 | | No log | 0.1649 | 16 | 1.5422 | 0.2832 | 1.5422 | 1.2419 | | No log | 0.1856 | 18 | 1.8395 | 0.2333 | 1.8395 | 1.3563 | | No log | 0.2062 | 20 | 2.4245 | 0.0541 | 2.4245 | 1.5571 | | No log | 0.2268 | 22 | 2.2319 | 0.0699 | 2.2319 | 1.4940 | | No log | 0.2474 | 24 | 1.6828 | 0.2951 | 1.6828 | 1.2972 | | No log | 0.2680 | 26 | 1.1992 | 0.4874 | 1.1992 | 1.0951 | | No log | 0.2887 | 28 | 1.5225 | 0.2000 | 1.5225 | 1.2339 | | No log | 0.3093 | 30 | 1.3550 | 0.3966 | 1.3550 | 1.1641 | | No log | 0.3299 | 32 | 1.0281 | 0.6015 | 1.0281 | 1.0139 | | No log | 0.3505 | 34 | 1.1542 | 0.5037 | 1.1542 | 1.0743 | | No log | 0.3711 | 36 | 1.2467 | 0.5211 | 1.2467 | 1.1166 | | No log | 0.3918 | 38 | 1.0146 | 0.6197 | 1.0146 | 1.0073 | | No log | 0.4124 | 40 | 0.9003 | 0.64 | 0.9003 | 0.9489 | | No log | 0.4330 | 42 | 0.8324 | 0.6918 | 0.8324 | 0.9123 | | No log | 0.4536 | 44 | 0.8800 | 0.7329 | 0.8800 | 0.9381 | | No log | 0.4742 | 46 | 1.3931 | 0.5829 | 1.3931 | 1.1803 | | No log | 0.4948 | 48 | 1.2730 | 0.6036 | 1.2730 | 1.1283 | | No log | 0.5155 | 50 | 0.9855 | 0.6667 | 0.9855 | 0.9927 | | No log | 0.5361 | 52 | 1.0368 | 0.5946 | 1.0368 | 1.0182 | | No log | 0.5567 | 54 | 1.1082 | 0.5517 | 1.1082 | 1.0527 | | No log | 0.5773 | 56 | 1.0923 | 0.5882 | 1.0923 | 1.0451 | | No log | 0.5979 | 58 | 1.0331 | 0.6 | 1.0331 | 1.0164 | | No log | 0.6186 | 60 | 0.9837 | 0.6225 | 0.9837 | 0.9918 | | No log | 0.6392 | 62 | 0.9091 | 0.6323 | 0.9091 | 0.9535 | | No log | 0.6598 | 64 | 0.8918 | 0.6582 | 0.8918 | 0.9444 | | No log | 0.6804 | 66 | 1.0270 | 0.6471 | 1.0270 | 1.0134 | | No log | 0.7010 | 68 | 0.9795 | 0.6282 | 0.9795 | 0.9897 | | No log | 0.7216 | 70 | 0.8182 | 0.7059 | 0.8182 | 0.9046 | | No log | 0.7423 | 72 | 0.8577 | 0.7105 | 0.8577 | 0.9261 | | No log | 0.7629 | 74 | 1.1304 | 0.5769 | 1.1304 | 1.0632 | | No log | 0.7835 | 76 | 1.3418 | 0.5093 | 1.3418 | 1.1584 | | No log | 0.8041 | 78 | 1.1096 | 0.6125 | 1.1096 | 1.0534 | | No log | 0.8247 | 80 | 0.9768 | 0.6835 | 0.9768 | 0.9883 | | No log | 0.8454 | 82 | 0.9448 | 0.6800 | 0.9448 | 0.9720 | | No log | 0.8660 | 84 | 1.1318 | 0.5844 | 1.1318 | 1.0639 | | No log | 0.8866 | 86 | 1.1446 | 0.5503 | 1.1446 | 1.0699 | | No log | 0.9072 | 88 | 1.0225 | 0.6081 | 1.0225 | 1.0112 | | No log | 0.9278 | 90 | 0.9466 | 0.6494 | 0.9466 | 0.9729 | | No log | 0.9485 | 92 | 0.9471 | 0.6410 | 0.9471 | 0.9732 | | No log | 0.9691 | 94 | 0.9464 | 0.6369 | 0.9464 | 0.9728 | | No log | 0.9897 | 96 | 0.9880 | 0.6832 | 0.9880 | 0.9940 | | No log | 1.0103 | 98 | 1.0383 | 0.6220 | 1.0383 | 1.0190 | | No log | 1.0309 | 100 | 0.9291 | 0.6708 | 0.9291 | 0.9639 | | No log | 1.0515 | 102 | 0.8811 | 0.7051 | 0.8811 | 0.9387 | | No log | 1.0722 | 104 | 0.8661 | 0.6933 | 0.8661 | 0.9306 | | No log | 1.0928 | 106 | 0.8505 | 0.7320 | 0.8505 | 0.9222 | | No log | 1.1134 | 108 | 0.9108 | 0.6835 | 0.9108 | 0.9544 | | No log | 1.1340 | 110 | 0.9671 | 0.6545 | 0.9671 | 0.9834 | | No log | 1.1546 | 112 | 0.8803 | 0.7143 | 0.8803 | 0.9382 | | No log | 1.1753 | 114 | 0.7077 | 0.7927 | 0.7077 | 0.8412 | | No log | 1.1959 | 116 | 0.6499 | 0.7907 | 0.6499 | 0.8062 | | No log | 1.2165 | 118 | 0.6344 | 0.7977 | 0.6344 | 0.7965 | | No log | 1.2371 | 120 | 0.7094 | 0.7602 | 0.7094 | 0.8422 | | No log | 1.2577 | 122 | 0.8116 | 0.7425 | 0.8116 | 0.9009 | | No log | 1.2784 | 124 | 0.8744 | 0.6962 | 0.8744 | 0.9351 | | No log | 1.2990 | 126 | 0.7462 | 0.7407 | 0.7462 | 0.8638 | | No log | 1.3196 | 128 | 0.5628 | 0.8070 | 0.5628 | 0.7502 | | No log | 1.3402 | 130 | 0.6567 | 0.7831 | 0.6567 | 0.8103 | | No log | 1.3608 | 132 | 0.9735 | 0.6748 | 0.9735 | 0.9867 | | No log | 1.3814 | 134 | 0.6423 | 0.8024 | 0.6423 | 0.8014 | | No log | 1.4021 | 136 | 0.6233 | 0.8128 | 0.6233 | 0.7895 | | No log | 1.4227 | 138 | 0.9567 | 0.7437 | 0.9567 | 0.9781 | | No log | 1.4433 | 140 | 0.9548 | 0.7111 | 0.9548 | 0.9771 | | No log | 1.4639 | 142 | 1.0082 | 0.6144 | 1.0082 | 1.0041 | | No log | 1.4845 | 144 | 0.9656 | 0.6234 | 0.9656 | 0.9827 | | No log | 1.5052 | 146 | 0.9097 | 0.6941 | 0.9097 | 0.9538 | | No log | 1.5258 | 148 | 0.8018 | 0.6918 | 0.8018 | 0.8954 | | No log | 1.5464 | 150 | 0.7871 | 0.6918 | 0.7871 | 0.8872 | | No log | 1.5670 | 152 | 0.8130 | 0.6923 | 0.8130 | 0.9017 | | No log | 1.5876 | 154 | 0.8739 | 0.6883 | 0.8739 | 0.9348 | | No log | 1.6082 | 156 | 0.9073 | 0.6883 | 0.9073 | 0.9525 | | No log | 1.6289 | 158 | 0.8979 | 0.6797 | 0.8979 | 0.9476 | | No log | 1.6495 | 160 | 0.9202 | 0.7020 | 0.9202 | 0.9593 | | No log | 1.6701 | 162 | 0.9533 | 0.6933 | 0.9533 | 0.9764 | | No log | 1.6907 | 164 | 1.0495 | 0.6323 | 1.0495 | 1.0244 | | No log | 1.7113 | 166 | 0.9693 | 0.6667 | 0.9693 | 0.9845 | | No log | 1.7320 | 168 | 0.9011 | 0.7059 | 0.9011 | 0.9493 | | No log | 1.7526 | 170 | 0.8788 | 0.6914 | 0.8788 | 0.9375 | | No log | 1.7732 | 172 | 0.8192 | 0.7152 | 0.8192 | 0.9051 | | No log | 1.7938 | 174 | 0.7623 | 0.7738 | 0.7623 | 0.8731 | | No log | 1.8144 | 176 | 0.6998 | 0.7436 | 0.6998 | 0.8365 | | No log | 1.8351 | 178 | 0.6744 | 0.775 | 0.6744 | 0.8212 | | No log | 1.8557 | 180 | 0.6923 | 0.7882 | 0.6923 | 0.8321 | | No log | 1.8763 | 182 | 1.0034 | 0.6889 | 1.0034 | 1.0017 | | No log | 1.8969 | 184 | 1.1008 | 0.6243 | 1.1008 | 1.0492 | | No log | 1.9175 | 186 | 0.8802 | 0.6962 | 0.8802 | 0.9382 | | No log | 1.9381 | 188 | 0.6508 | 0.7432 | 0.6508 | 0.8067 | | No log | 1.9588 | 190 | 0.6284 | 0.7821 | 0.6284 | 0.7927 | | No log | 1.9794 | 192 | 0.6294 | 0.7547 | 0.6294 | 0.7933 | | No log | 2.0 | 194 | 0.5511 | 0.8187 | 0.5511 | 0.7424 | | No log | 2.0206 | 196 | 0.6162 | 0.8105 | 0.6162 | 0.7850 | | No log | 2.0412 | 198 | 0.9315 | 0.7263 | 0.9315 | 0.9651 | | No log | 2.0619 | 200 | 1.2573 | 0.6597 | 1.2573 | 1.1213 | | No log | 2.0825 | 202 | 1.2732 | 0.6136 | 1.2732 | 1.1283 | | No log | 2.1031 | 204 | 1.0180 | 0.6581 | 1.0180 | 1.0090 | | No log | 2.1237 | 206 | 0.7410 | 0.6803 | 0.7410 | 0.8608 | | No log | 2.1443 | 208 | 0.5425 | 0.7975 | 0.5425 | 0.7366 | | No log | 2.1649 | 210 | 0.4957 | 0.7879 | 0.4957 | 0.7041 | | No log | 2.1856 | 212 | 0.5009 | 0.8235 | 0.5009 | 0.7077 | | No log | 2.2062 | 214 | 0.6764 | 0.7727 | 0.6764 | 0.8225 | | No log | 2.2268 | 216 | 0.8855 | 0.7368 | 0.8855 | 0.9410 | | No log | 2.2474 | 218 | 0.8688 | 0.7018 | 0.8688 | 0.9321 | | No log | 2.2680 | 220 | 0.7828 | 0.7389 | 0.7828 | 0.8847 | | No log | 2.2887 | 222 | 0.7133 | 0.7285 | 0.7133 | 0.8446 | | No log | 2.3093 | 224 | 0.7029 | 0.7403 | 0.7029 | 0.8384 | | No log | 2.3299 | 226 | 0.7274 | 0.7468 | 0.7274 | 0.8529 | | No log | 2.3505 | 228 | 0.7905 | 0.7024 | 0.7905 | 0.8891 | | No log | 2.3711 | 230 | 0.8163 | 0.7024 | 0.8163 | 0.9035 | | No log | 2.3918 | 232 | 0.6817 | 0.7407 | 0.6817 | 0.8257 | | No log | 2.4124 | 234 | 0.6279 | 0.7898 | 0.6279 | 0.7924 | | No log | 2.4330 | 236 | 0.6566 | 0.7285 | 0.6566 | 0.8103 | | No log | 2.4536 | 238 | 0.6737 | 0.7432 | 0.6737 | 0.8208 | | No log | 2.4742 | 240 | 0.6652 | 0.7586 | 0.6652 | 0.8156 | | No log | 2.4948 | 242 | 0.6573 | 0.7133 | 0.6573 | 0.8108 | | No log | 2.5155 | 244 | 0.6947 | 0.7376 | 0.6947 | 0.8335 | | No log | 2.5361 | 246 | 0.6919 | 0.7532 | 0.6919 | 0.8318 | | No log | 2.5567 | 248 | 0.7783 | 0.7634 | 0.7783 | 0.8822 | | No log | 2.5773 | 250 | 0.9080 | 0.7725 | 0.9080 | 0.9529 | | No log | 2.5979 | 252 | 0.7760 | 0.7789 | 0.7760 | 0.8809 | | No log | 2.6186 | 254 | 0.5427 | 0.8046 | 0.5427 | 0.7367 | | No log | 2.6392 | 256 | 0.5157 | 0.8395 | 0.5157 | 0.7181 | | No log | 2.6598 | 258 | 0.5074 | 0.8199 | 0.5074 | 0.7123 | | No log | 2.6804 | 260 | 0.5683 | 0.7879 | 0.5683 | 0.7539 | | No log | 2.7010 | 262 | 0.7725 | 0.6994 | 0.7725 | 0.8789 | | No log | 2.7216 | 264 | 0.9238 | 0.6790 | 0.9238 | 0.9612 | | No log | 2.7423 | 266 | 0.8716 | 0.7152 | 0.8716 | 0.9336 | | No log | 2.7629 | 268 | 0.7049 | 0.7123 | 0.7049 | 0.8396 | | No log | 2.7835 | 270 | 0.5827 | 0.8280 | 0.5827 | 0.7634 | | No log | 2.8041 | 272 | 0.5649 | 0.8101 | 0.5649 | 0.7516 | | No log | 2.8247 | 274 | 0.5398 | 0.8323 | 0.5398 | 0.7347 | | No log | 2.8454 | 276 | 0.5942 | 0.8098 | 0.5942 | 0.7708 | | No log | 2.8660 | 278 | 0.8162 | 0.7 | 0.8162 | 0.9035 | | No log | 2.8866 | 280 | 1.0026 | 0.6341 | 1.0026 | 1.0013 | | No log | 2.9072 | 282 | 1.0403 | 0.6174 | 1.0403 | 1.0199 | | No log | 2.9278 | 284 | 0.9378 | 0.6968 | 0.9378 | 0.9684 | | No log | 2.9485 | 286 | 0.7710 | 0.7273 | 0.7710 | 0.8781 | | No log | 2.9691 | 288 | 0.6648 | 0.7758 | 0.6648 | 0.8153 | | No log | 2.9897 | 290 | 0.6411 | 0.7952 | 0.6411 | 0.8007 | | No log | 3.0103 | 292 | 0.6512 | 0.7719 | 0.6512 | 0.8070 | | No log | 3.0309 | 294 | 0.6983 | 0.7273 | 0.6983 | 0.8356 | | No log | 3.0515 | 296 | 0.7335 | 0.7051 | 0.7335 | 0.8565 | | No log | 3.0722 | 298 | 0.7403 | 0.7179 | 0.7403 | 0.8604 | | No log | 3.0928 | 300 | 0.6836 | 0.7179 | 0.6836 | 0.8268 | | No log | 3.1134 | 302 | 0.6452 | 0.7296 | 0.6452 | 0.8033 | | No log | 3.1340 | 304 | 0.6395 | 0.7297 | 0.6395 | 0.7997 | | No log | 3.1546 | 306 | 0.6961 | 0.7 | 0.6961 | 0.8343 | | No log | 3.1753 | 308 | 0.7678 | 0.6567 | 0.7678 | 0.8762 | | No log | 3.1959 | 310 | 0.7398 | 0.6912 | 0.7398 | 0.8601 | | No log | 3.2165 | 312 | 0.7046 | 0.7123 | 0.7046 | 0.8394 | | No log | 3.2371 | 314 | 0.8046 | 0.7037 | 0.8046 | 0.8970 | | No log | 3.2577 | 316 | 0.9462 | 0.7273 | 0.9462 | 0.9727 | | No log | 3.2784 | 318 | 0.8458 | 0.7135 | 0.8458 | 0.9197 | | No log | 3.2990 | 320 | 0.6890 | 0.7160 | 0.6890 | 0.8300 | | No log | 3.3196 | 322 | 0.6354 | 0.7654 | 0.6354 | 0.7971 | | No log | 3.3402 | 324 | 0.6535 | 0.7403 | 0.6535 | 0.8084 | | No log | 3.3608 | 326 | 0.6979 | 0.7237 | 0.6979 | 0.8354 | | No log | 3.3814 | 328 | 0.8189 | 0.72 | 0.8189 | 0.9049 | | No log | 3.4021 | 330 | 0.8727 | 0.6714 | 0.8727 | 0.9342 | | No log | 3.4227 | 332 | 0.8652 | 0.7059 | 0.8652 | 0.9302 | | No log | 3.4433 | 334 | 0.7842 | 0.7286 | 0.7842 | 0.8856 | | No log | 3.4639 | 336 | 0.7216 | 0.7517 | 0.7216 | 0.8495 | | No log | 3.4845 | 338 | 0.7338 | 0.7215 | 0.7338 | 0.8566 | | No log | 3.5052 | 340 | 0.7771 | 0.6957 | 0.7771 | 0.8815 | | No log | 3.5258 | 342 | 0.7209 | 0.7305 | 0.7209 | 0.8490 | | No log | 3.5464 | 344 | 0.6624 | 0.7262 | 0.6624 | 0.8139 | | No log | 3.5670 | 346 | 0.6127 | 0.7879 | 0.6127 | 0.7828 | | No log | 3.5876 | 348 | 0.6189 | 0.7665 | 0.6189 | 0.7867 | | No log | 3.6082 | 350 | 0.6325 | 0.7456 | 0.6325 | 0.7953 | | No log | 3.6289 | 352 | 0.6053 | 0.7952 | 0.6053 | 0.7780 | | No log | 3.6495 | 354 | 0.5672 | 0.8323 | 0.5672 | 0.7531 | | No log | 3.6701 | 356 | 0.5962 | 0.7719 | 0.5962 | 0.7721 | | No log | 3.6907 | 358 | 0.6806 | 0.7650 | 0.6806 | 0.8250 | | No log | 3.7113 | 360 | 0.7369 | 0.7701 | 0.7369 | 0.8585 | | No log | 3.7320 | 362 | 0.7234 | 0.7514 | 0.7234 | 0.8505 | | No log | 3.7526 | 364 | 0.6946 | 0.7262 | 0.6946 | 0.8334 | | No log | 3.7732 | 366 | 0.7153 | 0.7375 | 0.7153 | 0.8457 | | No log | 3.7938 | 368 | 0.8381 | 0.6795 | 0.8381 | 0.9155 | | No log | 3.8144 | 370 | 0.9907 | 0.6467 | 0.9907 | 0.9953 | | No log | 3.8351 | 372 | 0.9842 | 0.6588 | 0.9842 | 0.9921 | | No log | 3.8557 | 374 | 0.8263 | 0.7030 | 0.8263 | 0.9090 | | No log | 3.8763 | 376 | 0.6364 | 0.7826 | 0.6364 | 0.7978 | | No log | 3.8969 | 378 | 0.5979 | 0.8129 | 0.5979 | 0.7733 | | No log | 3.9175 | 380 | 0.6032 | 0.8129 | 0.6032 | 0.7766 | | No log | 3.9381 | 382 | 0.6340 | 0.7821 | 0.6340 | 0.7963 | | No log | 3.9588 | 384 | 0.6742 | 0.7515 | 0.6742 | 0.8211 | | No log | 3.9794 | 386 | 0.7577 | 0.7066 | 0.7577 | 0.8705 | | No log | 4.0 | 388 | 0.7956 | 0.6918 | 0.7956 | 0.8920 | | No log | 4.0206 | 390 | 0.8222 | 0.6623 | 0.8222 | 0.9068 | | No log | 4.0412 | 392 | 0.7831 | 0.6835 | 0.7831 | 0.8849 | | No log | 4.0619 | 394 | 0.7014 | 0.7453 | 0.7014 | 0.8375 | | No log | 4.0825 | 396 | 0.6360 | 0.7595 | 0.6360 | 0.7975 | | No log | 4.1031 | 398 | 0.6268 | 0.7848 | 0.6268 | 0.7917 | | No log | 4.1237 | 400 | 0.6348 | 0.7853 | 0.6348 | 0.7968 | | No log | 4.1443 | 402 | 0.7172 | 0.7337 | 0.7172 | 0.8469 | | No log | 4.1649 | 404 | 0.8698 | 0.7262 | 0.8698 | 0.9327 | | No log | 4.1856 | 406 | 0.9461 | 0.6909 | 0.9461 | 0.9727 | | No log | 4.2062 | 408 | 0.8941 | 0.6795 | 0.8941 | 0.9456 | | No log | 4.2268 | 410 | 0.8287 | 0.7123 | 0.8287 | 0.9103 | | No log | 4.2474 | 412 | 0.8115 | 0.7123 | 0.8115 | 0.9008 | | No log | 4.2680 | 414 | 0.8251 | 0.6994 | 0.8251 | 0.9084 | | No log | 4.2887 | 416 | 0.9469 | 0.7396 | 0.9469 | 0.9731 | | No log | 4.3093 | 418 | 0.9229 | 0.7437 | 0.9229 | 0.9607 | | No log | 4.3299 | 420 | 0.7387 | 0.7668 | 0.7387 | 0.8595 | | No log | 4.3505 | 422 | 0.6246 | 0.7294 | 0.6246 | 0.7903 | | No log | 4.3711 | 424 | 0.6276 | 0.7355 | 0.6276 | 0.7922 | | No log | 4.3918 | 426 | 0.6380 | 0.7368 | 0.6380 | 0.7987 | | No log | 4.4124 | 428 | 0.6312 | 0.7651 | 0.6312 | 0.7945 | | No log | 4.4330 | 430 | 0.6137 | 0.7651 | 0.6137 | 0.7834 | | No log | 4.4536 | 432 | 0.5521 | 0.8182 | 0.5521 | 0.7430 | | No log | 4.4742 | 434 | 0.5049 | 0.8354 | 0.5049 | 0.7106 | | No log | 4.4948 | 436 | 0.4706 | 0.8415 | 0.4706 | 0.6860 | | No log | 4.5155 | 438 | 0.4786 | 0.8276 | 0.4786 | 0.6918 | | No log | 4.5361 | 440 | 0.5208 | 0.8161 | 0.5208 | 0.7217 | | No log | 4.5567 | 442 | 0.5843 | 0.7758 | 0.5843 | 0.7644 | | No log | 4.5773 | 444 | 0.6199 | 0.7451 | 0.6199 | 0.7874 | | No log | 4.5979 | 446 | 0.6672 | 0.7397 | 0.6672 | 0.8168 | | No log | 4.6186 | 448 | 0.6637 | 0.7465 | 0.6637 | 0.8147 | | No log | 4.6392 | 450 | 0.6270 | 0.7361 | 0.6270 | 0.7918 | | No log | 4.6598 | 452 | 0.6211 | 0.7467 | 0.6211 | 0.7881 | | No log | 4.6804 | 454 | 0.6129 | 0.7595 | 0.6129 | 0.7829 | | No log | 4.7010 | 456 | 0.6952 | 0.7375 | 0.6952 | 0.8338 | | No log | 4.7216 | 458 | 0.8275 | 0.7487 | 0.8275 | 0.9097 | | No log | 4.7423 | 460 | 0.8799 | 0.7391 | 0.8799 | 0.9381 | | No log | 4.7629 | 462 | 0.7715 | 0.7143 | 0.7715 | 0.8784 | | No log | 4.7835 | 464 | 0.6494 | 0.7451 | 0.6494 | 0.8059 | | No log | 4.8041 | 466 | 0.6108 | 0.7792 | 0.6108 | 0.7815 | | No log | 4.8247 | 468 | 0.5989 | 0.8 | 0.5989 | 0.7739 | | No log | 4.8454 | 470 | 0.5888 | 0.8101 | 0.5888 | 0.7673 | | No log | 4.8660 | 472 | 0.6099 | 0.7643 | 0.6099 | 0.7809 | | No log | 4.8866 | 474 | 0.6723 | 0.7485 | 0.6723 | 0.8199 | | No log | 4.9072 | 476 | 0.6485 | 0.7826 | 0.6485 | 0.8053 | | No log | 4.9278 | 478 | 0.5903 | 0.8 | 0.5903 | 0.7683 | | No log | 4.9485 | 480 | 0.5514 | 0.8068 | 0.5514 | 0.7426 | | No log | 4.9691 | 482 | 0.5580 | 0.8298 | 0.5580 | 0.7470 | | No log | 4.9897 | 484 | 0.5587 | 0.8046 | 0.5587 | 0.7475 | | No log | 5.0103 | 486 | 0.5812 | 0.7976 | 0.5812 | 0.7624 | | No log | 5.0309 | 488 | 0.6220 | 0.8182 | 0.6220 | 0.7887 | | No log | 5.0515 | 490 | 0.6713 | 0.7465 | 0.6713 | 0.8194 | | No log | 5.0722 | 492 | 0.7329 | 0.6883 | 0.7329 | 0.8561 | | No log | 5.0928 | 494 | 0.8174 | 0.7195 | 0.8174 | 0.9041 | | No log | 5.1134 | 496 | 0.8007 | 0.7253 | 0.8007 | 0.8948 | | No log | 5.1340 | 498 | 0.7276 | 0.7429 | 0.7276 | 0.8530 | | 0.3973 | 5.1546 | 500 | 0.6351 | 0.7717 | 0.6351 | 0.7969 | | 0.3973 | 5.1753 | 502 | 0.6046 | 0.8222 | 0.6046 | 0.7775 | | 0.3973 | 5.1959 | 504 | 0.5989 | 0.8161 | 0.5989 | 0.7739 | | 0.3973 | 5.2165 | 506 | 0.5907 | 0.8 | 0.5907 | 0.7686 | | 0.3973 | 5.2371 | 508 | 0.6053 | 0.7746 | 0.6053 | 0.7780 | | 0.3973 | 5.2577 | 510 | 0.5994 | 0.7929 | 0.5994 | 0.7742 | | 0.3973 | 5.2784 | 512 | 0.6174 | 0.7927 | 0.6174 | 0.7858 | | 0.3973 | 5.2990 | 514 | 0.5979 | 0.8121 | 0.5979 | 0.7732 | | 0.3973 | 5.3196 | 516 | 0.5881 | 0.8049 | 0.5881 | 0.7669 | | 0.3973 | 5.3402 | 518 | 0.5806 | 0.8199 | 0.5806 | 0.7619 | | 0.3973 | 5.3608 | 520 | 0.5868 | 0.8228 | 0.5868 | 0.7660 | | 0.3973 | 5.3814 | 522 | 0.5853 | 0.8302 | 0.5853 | 0.7651 | | 0.3973 | 5.4021 | 524 | 0.6008 | 0.7826 | 0.6008 | 0.7751 | | 0.3973 | 5.4227 | 526 | 0.6094 | 0.7826 | 0.6094 | 0.7807 | | 0.3973 | 5.4433 | 528 | 0.5773 | 0.7853 | 0.5773 | 0.7598 | | 0.3973 | 5.4639 | 530 | 0.5429 | 0.8050 | 0.5429 | 0.7368 | | 0.3973 | 5.4845 | 532 | 0.5545 | 0.8050 | 0.5545 | 0.7446 | | 0.3973 | 5.5052 | 534 | 0.6134 | 0.7925 | 0.6134 | 0.7832 | | 0.3973 | 5.5258 | 536 | 0.7517 | 0.7067 | 0.7517 | 0.8670 | | 0.3973 | 5.5464 | 538 | 0.8842 | 0.6621 | 0.8842 | 0.9403 | | 0.3973 | 5.5670 | 540 | 0.9498 | 0.6377 | 0.9498 | 0.9746 | | 0.3973 | 5.5876 | 542 | 0.9129 | 0.6569 | 0.9129 | 0.9555 | | 0.3973 | 5.6082 | 544 | 0.8239 | 0.6567 | 0.8239 | 0.9077 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

MayBashendy/ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization

MayBashendy

2025-01-15T15:35:36Z

184

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-12-31T16:45:16Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization results: [] ---  # ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run1_AugV5_k19_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8235 - Qwk: 0.6980 - Mse: 0.8235 - Rmse: 0.9075 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:| | No log | 0.0225 | 2 | 6.7499 | 0.0239 | 6.7499 | 2.5981 | | No log | 0.0449 | 4 | 3.9448 | 0.0779 | 3.9448 | 1.9862 | | No log | 0.0674 | 6 | 3.2132 | 0.0119 | 3.2132 | 1.7925 | | No log | 0.0899 | 8 | 2.8634 | 0.0759 | 2.8634 | 1.6921 | | No log | 0.1124 | 10 | 2.4238 | 0.1399 | 2.4238 | 1.5569 | | No log | 0.1348 | 12 | 2.4654 | 0.1678 | 2.4654 | 1.5702 | | No log | 0.1573 | 14 | 2.3670 | 0.1644 | 2.3670 | 1.5385 | | No log | 0.1798 | 16 | 2.0761 | 0.2121 | 2.0761 | 1.4409 | | No log | 0.2022 | 18 | 3.0611 | 0.0256 | 3.0611 | 1.7496 | | No log | 0.2247 | 20 | 3.0347 | 0.0261 | 3.0347 | 1.7420 | | No log | 0.2472 | 22 | 2.9350 | 0.0261 | 2.9350 | 1.7132 | | No log | 0.2697 | 24 | 2.3165 | 0.1127 | 2.3165 | 1.5220 | | No log | 0.2921 | 26 | 2.0376 | 0.2105 | 2.0376 | 1.4275 | | No log | 0.3146 | 28 | 1.7324 | 0.2087 | 1.7324 | 1.3162 | | No log | 0.3371 | 30 | 1.6030 | 0.1835 | 1.6030 | 1.2661 | | No log | 0.3596 | 32 | 1.6510 | 0.1897 | 1.6510 | 1.2849 | | No log | 0.3820 | 34 | 2.1315 | 0.2302 | 2.1315 | 1.4600 | | No log | 0.4045 | 36 | 2.9023 | 0.0914 | 2.9023 | 1.7036 | | No log | 0.4270 | 38 | 3.1944 | 0.0978 | 3.1944 | 1.7873 | | No log | 0.4494 | 40 | 2.9683 | 0.1163 | 2.9683 | 1.7229 | | No log | 0.4719 | 42 | 2.3236 | 0.2125 | 2.3236 | 1.5243 | | No log | 0.4944 | 44 | 1.7125 | 0.3704 | 1.7125 | 1.3086 | | No log | 0.5169 | 46 | 1.4584 | 0.4394 | 1.4584 | 1.2076 | | No log | 0.5393 | 48 | 1.5439 | 0.4317 | 1.5439 | 1.2425 | | No log | 0.5618 | 50 | 2.0450 | 0.2420 | 2.0450 | 1.4300 | | No log | 0.5843 | 52 | 2.1974 | 0.2375 | 2.1974 | 1.4824 | | No log | 0.6067 | 54 | 2.1522 | 0.2420 | 2.1522 | 1.4670 | | No log | 0.6292 | 56 | 2.2223 | 0.2420 | 2.2223 | 1.4908 | | No log | 0.6517 | 58 | 2.0063 | 0.3289 | 2.0063 | 1.4164 | | No log | 0.6742 | 60 | 1.9971 | 0.3333 | 1.9971 | 1.4132 | | No log | 0.6966 | 62 | 1.7158 | 0.3889 | 1.7158 | 1.3099 | | No log | 0.7191 | 64 | 1.3191 | 0.5248 | 1.3191 | 1.1485 | | No log | 0.7416 | 66 | 1.2559 | 0.5362 | 1.2559 | 1.1207 | | No log | 0.7640 | 68 | 1.3554 | 0.5616 | 1.3554 | 1.1642 | | No log | 0.7865 | 70 | 1.6083 | 0.4940 | 1.6083 | 1.2682 | | No log | 0.8090 | 72 | 1.7086 | 0.5111 | 1.7086 | 1.3071 | | No log | 0.8315 | 74 | 1.4948 | 0.5444 | 1.4948 | 1.2226 | | No log | 0.8539 | 76 | 1.3163 | 0.5479 | 1.3163 | 1.1473 | | No log | 0.8764 | 78 | 1.3710 | 0.5235 | 1.3710 | 1.1709 | | No log | 0.8989 | 80 | 1.2650 | 0.5405 | 1.2650 | 1.1247 | | No log | 0.9213 | 82 | 1.1409 | 0.6234 | 1.1409 | 1.0681 | | No log | 0.9438 | 84 | 0.9831 | 0.6351 | 0.9831 | 0.9915 | | No log | 0.9663 | 86 | 0.9026 | 0.6809 | 0.9026 | 0.9501 | | No log | 0.9888 | 88 | 0.8614 | 0.6853 | 0.8614 | 0.9281 | | No log | 1.0112 | 90 | 0.9918 | 0.6099 | 0.9918 | 0.9959 | | No log | 1.0337 | 92 | 1.1130 | 0.5634 | 1.1130 | 1.0550 | | No log | 1.0562 | 94 | 0.9977 | 0.6056 | 0.9977 | 0.9988 | | No log | 1.0787 | 96 | 1.0509 | 0.6065 | 1.0509 | 1.0251 | | No log | 1.1011 | 98 | 1.3156 | 0.6145 | 1.3156 | 1.1470 | | No log | 1.1236 | 100 | 1.4242 | 0.5780 | 1.4242 | 1.1934 | | No log | 1.1461 | 102 | 1.2445 | 0.6380 | 1.2445 | 1.1156 | | No log | 1.1685 | 104 | 1.1225 | 0.5772 | 1.1225 | 1.0595 | | No log | 1.1910 | 106 | 1.0577 | 0.5571 | 1.0577 | 1.0284 | | No log | 1.2135 | 108 | 1.0190 | 0.6029 | 1.0190 | 1.0095 | | No log | 1.2360 | 110 | 1.0296 | 0.5693 | 1.0296 | 1.0147 | | No log | 1.2584 | 112 | 1.1317 | 0.5833 | 1.1317 | 1.0638 | | No log | 1.2809 | 114 | 1.1935 | 0.5850 | 1.1935 | 1.0925 | | No log | 1.3034 | 116 | 1.0900 | 0.6143 | 1.0900 | 1.0440 | | No log | 1.3258 | 118 | 1.0439 | 0.6143 | 1.0439 | 1.0217 | | No log | 1.3483 | 120 | 1.1155 | 0.5906 | 1.1155 | 1.0562 | | No log | 1.3708 | 122 | 1.0796 | 0.6081 | 1.0796 | 1.0391 | | No log | 1.3933 | 124 | 0.9929 | 0.6267 | 0.9929 | 0.9965 | | No log | 1.4157 | 126 | 0.8937 | 0.6759 | 0.8937 | 0.9454 | | No log | 1.4382 | 128 | 0.8898 | 0.6528 | 0.8898 | 0.9433 | | No log | 1.4607 | 130 | 1.0211 | 0.6410 | 1.0211 | 1.0105 | | No log | 1.4831 | 132 | 1.4143 | 0.5294 | 1.4143 | 1.1893 | | No log | 1.5056 | 134 | 1.5741 | 0.5172 | 1.5741 | 1.2546 | | No log | 1.5281 | 136 | 1.2332 | 0.6203 | 1.2332 | 1.1105 | | No log | 1.5506 | 138 | 0.8877 | 0.6056 | 0.8877 | 0.9422 | | No log | 1.5730 | 140 | 0.8260 | 0.6853 | 0.8260 | 0.9089 | | No log | 1.5955 | 142 | 0.8399 | 0.7083 | 0.8399 | 0.9164 | | No log | 1.6180 | 144 | 0.9279 | 0.6494 | 0.9279 | 0.9633 | | No log | 1.6404 | 146 | 1.1181 | 0.6047 | 1.1181 | 1.0574 | | No log | 1.6629 | 148 | 1.0097 | 0.6584 | 1.0097 | 1.0048 | | No log | 1.6854 | 150 | 0.9732 | 0.6456 | 0.9732 | 0.9865 | | No log | 1.7079 | 152 | 1.1485 | 0.5698 | 1.1485 | 1.0717 | | No log | 1.7303 | 154 | 1.2391 | 0.5663 | 1.2391 | 1.1131 | | No log | 1.7528 | 156 | 1.4465 | 0.5909 | 1.4465 | 1.2027 | | No log | 1.7753 | 158 | 1.1367 | 0.6013 | 1.1367 | 1.0661 | | No log | 1.7978 | 160 | 0.8003 | 0.6712 | 0.8003 | 0.8946 | | No log | 1.8202 | 162 | 0.7855 | 0.7123 | 0.7855 | 0.8863 | | No log | 1.8427 | 164 | 0.8127 | 0.7248 | 0.8127 | 0.9015 | | No log | 1.8652 | 166 | 0.9137 | 0.6490 | 0.9137 | 0.9559 | | No log | 1.8876 | 168 | 1.2149 | 0.5697 | 1.2149 | 1.1022 | | No log | 1.9101 | 170 | 1.3223 | 0.5731 | 1.3223 | 1.1499 | | No log | 1.9326 | 172 | 1.2370 | 0.6057 | 1.2370 | 1.1122 | | No log | 1.9551 | 174 | 1.0690 | 0.6235 | 1.0690 | 1.0339 | | No log | 1.9775 | 176 | 0.8758 | 0.6800 | 0.8758 | 0.9359 | | No log | 2.0 | 178 | 0.8399 | 0.6974 | 0.8399 | 0.9165 | | No log | 2.0225 | 180 | 0.7908 | 0.7273 | 0.7908 | 0.8893 | | No log | 2.0449 | 182 | 0.7553 | 0.7368 | 0.7553 | 0.8691 | | No log | 2.0674 | 184 | 0.9469 | 0.6875 | 0.9469 | 0.9731 | | No log | 2.0899 | 186 | 1.0288 | 0.6582 | 1.0288 | 1.0143 | | No log | 2.1124 | 188 | 0.9775 | 0.6582 | 0.9775 | 0.9887 | | No log | 2.1348 | 190 | 0.9110 | 0.6625 | 0.9110 | 0.9545 | | No log | 2.1573 | 192 | 0.9113 | 0.6905 | 0.9113 | 0.9546 | | No log | 2.1798 | 194 | 0.8910 | 0.7093 | 0.8910 | 0.9439 | | No log | 2.2022 | 196 | 0.9157 | 0.6901 | 0.9157 | 0.9569 | | No log | 2.2247 | 198 | 0.9856 | 0.7079 | 0.9856 | 0.9928 | | No log | 2.2472 | 200 | 0.9730 | 0.6936 | 0.9730 | 0.9864 | | No log | 2.2697 | 202 | 0.8251 | 0.7237 | 0.8251 | 0.9084 | | No log | 2.2921 | 204 | 0.8114 | 0.6939 | 0.8114 | 0.9008 | | No log | 2.3146 | 206 | 0.8341 | 0.7190 | 0.8341 | 0.9133 | | No log | 2.3371 | 208 | 0.8705 | 0.6131 | 0.8705 | 0.9330 | | No log | 2.3596 | 210 | 0.9179 | 0.6331 | 0.9179 | 0.9581 | | No log | 2.3820 | 212 | 0.9431 | 0.6429 | 0.9431 | 0.9711 | | No log | 2.4045 | 214 | 1.0174 | 0.6122 | 1.0174 | 1.0087 | | No log | 2.4270 | 216 | 1.2815 | 0.5732 | 1.2815 | 1.1320 | | No log | 2.4494 | 218 | 1.4477 | 0.5650 | 1.4477 | 1.2032 | | No log | 2.4719 | 220 | 1.1777 | 0.6433 | 1.1777 | 1.0852 | | No log | 2.4944 | 222 | 0.8770 | 0.7229 | 0.8770 | 0.9365 | | No log | 2.5169 | 224 | 0.7887 | 0.7317 | 0.7887 | 0.8881 | | No log | 2.5393 | 226 | 0.8828 | 0.7011 | 0.8828 | 0.9396 | | No log | 2.5618 | 228 | 0.9417 | 0.6821 | 0.9417 | 0.9704 | | No log | 2.5843 | 230 | 0.8212 | 0.7093 | 0.8212 | 0.9062 | | No log | 2.6067 | 232 | 0.7767 | 0.7436 | 0.7767 | 0.8813 | | No log | 2.6292 | 234 | 0.8518 | 0.7162 | 0.8518 | 0.9229 | | No log | 2.6517 | 236 | 0.8481 | 0.7162 | 0.8481 | 0.9209 | | No log | 2.6742 | 238 | 0.8264 | 0.7261 | 0.8264 | 0.9091 | | No log | 2.6966 | 240 | 0.9441 | 0.6893 | 0.9441 | 0.9716 | | No log | 2.7191 | 242 | 1.0546 | 0.6704 | 1.0546 | 1.0269 | | No log | 2.7416 | 244 | 0.9842 | 0.6816 | 0.9842 | 0.9921 | | No log | 2.7640 | 246 | 0.8624 | 0.7453 | 0.8624 | 0.9286 | | No log | 2.7865 | 248 | 0.8618 | 0.6803 | 0.8618 | 0.9283 | | No log | 2.8090 | 250 | 0.8531 | 0.6667 | 0.8531 | 0.9236 | | No log | 2.8315 | 252 | 0.8015 | 0.7368 | 0.8015 | 0.8953 | | No log | 2.8539 | 254 | 0.8789 | 0.6962 | 0.8789 | 0.9375 | | No log | 2.8764 | 256 | 0.9868 | 0.6824 | 0.9868 | 0.9934 | | No log | 2.8989 | 258 | 0.9168 | 0.6667 | 0.9168 | 0.9575 | | No log | 2.9213 | 260 | 0.7860 | 0.6968 | 0.7860 | 0.8866 | | No log | 2.9438 | 262 | 0.7684 | 0.7320 | 0.7684 | 0.8766 | | No log | 2.9663 | 264 | 0.8350 | 0.7273 | 0.8350 | 0.9138 | | No log | 2.9888 | 266 | 0.9936 | 0.6497 | 0.9936 | 0.9968 | | No log | 3.0112 | 268 | 1.1765 | 0.6420 | 1.1765 | 1.0847 | | No log | 3.0337 | 270 | 1.3074 | 0.6127 | 1.3074 | 1.1434 | | No log | 3.0562 | 272 | 1.1744 | 0.6627 | 1.1744 | 1.0837 | | No log | 3.0787 | 274 | 0.8994 | 0.6711 | 0.8994 | 0.9484 | | No log | 3.1011 | 276 | 0.7643 | 0.6980 | 0.7643 | 0.8743 | | No log | 3.1236 | 278 | 0.7656 | 0.6901 | 0.7656 | 0.8750 | | No log | 3.1461 | 280 | 0.7889 | 0.6621 | 0.7889 | 0.8882 | | No log | 3.1685 | 282 | 0.9606 | 0.6928 | 0.9606 | 0.9801 | | No log | 3.1910 | 284 | 1.1225 | 0.6667 | 1.1225 | 1.0595 | | No log | 3.2135 | 286 | 1.2142 | 0.6463 | 1.2142 | 1.1019 | | No log | 3.2360 | 288 | 1.0268 | 0.6923 | 1.0268 | 1.0133 | | No log | 3.2584 | 290 | 0.7790 | 0.6928 | 0.7790 | 0.8826 | | No log | 3.2809 | 292 | 0.7135 | 0.7368 | 0.7135 | 0.8447 | | No log | 3.3034 | 294 | 0.7415 | 0.7484 | 0.7415 | 0.8611 | | No log | 3.3258 | 296 | 0.8153 | 0.7317 | 0.8153 | 0.9030 | | No log | 3.3483 | 298 | 0.9019 | 0.7337 | 0.9019 | 0.9497 | | No log | 3.3708 | 300 | 0.8978 | 0.7305 | 0.8978 | 0.9475 | | No log | 3.3933 | 302 | 0.8980 | 0.7229 | 0.8980 | 0.9476 | | No log | 3.4157 | 304 | 0.9298 | 0.7030 | 0.9298 | 0.9643 | | No log | 3.4382 | 306 | 0.8938 | 0.7117 | 0.8938 | 0.9454 | | No log | 3.4607 | 308 | 0.7981 | 0.7097 | 0.7981 | 0.8933 | | No log | 3.4831 | 310 | 0.7560 | 0.6853 | 0.7560 | 0.8695 | | No log | 3.5056 | 312 | 0.7667 | 0.7361 | 0.7667 | 0.8756 | | No log | 3.5281 | 314 | 0.7564 | 0.7133 | 0.7564 | 0.8697 | | No log | 3.5506 | 316 | 0.7166 | 0.7333 | 0.7166 | 0.8465 | | No log | 3.5730 | 318 | 0.8723 | 0.7195 | 0.8723 | 0.9340 | | No log | 3.5955 | 320 | 1.1398 | 0.6556 | 1.1398 | 1.0676 | | No log | 3.6180 | 322 | 1.1866 | 0.6145 | 1.1866 | 1.0893 | | No log | 3.6404 | 324 | 1.0065 | 0.6420 | 1.0065 | 1.0032 | | No log | 3.6629 | 326 | 0.7958 | 0.7059 | 0.7958 | 0.8921 | | No log | 3.6854 | 328 | 0.7029 | 0.7586 | 0.7029 | 0.8384 | | No log | 3.7079 | 330 | 0.6871 | 0.7361 | 0.6871 | 0.8289 | | No log | 3.7303 | 332 | 0.6626 | 0.7671 | 0.6626 | 0.8140 | | No log | 3.7528 | 334 | 0.6622 | 0.7871 | 0.6622 | 0.8137 | | No log | 3.7753 | 336 | 0.7631 | 0.7515 | 0.7631 | 0.8736 | | No log | 3.7978 | 338 | 0.8749 | 0.7052 | 0.8749 | 0.9354 | | No log | 3.8202 | 340 | 0.8515 | 0.7126 | 0.8515 | 0.9228 | | No log | 3.8427 | 342 | 0.7951 | 0.7647 | 0.7951 | 0.8917 | | No log | 3.8652 | 344 | 0.8031 | 0.7389 | 0.8031 | 0.8962 | | No log | 3.8876 | 346 | 0.8594 | 0.6901 | 0.8594 | 0.9270 | | No log | 3.9101 | 348 | 0.8294 | 0.6809 | 0.8294 | 0.9107 | | No log | 3.9326 | 350 | 0.7983 | 0.7162 | 0.7983 | 0.8935 | | No log | 3.9551 | 352 | 0.8242 | 0.7362 | 0.8242 | 0.9078 | | No log | 3.9775 | 354 | 0.8498 | 0.7305 | 0.8498 | 0.9218 | | No log | 4.0 | 356 | 0.9308 | 0.7030 | 0.9308 | 0.9648 | | No log | 4.0225 | 358 | 0.9551 | 0.7030 | 0.9551 | 0.9773 | | No log | 4.0449 | 360 | 0.8899 | 0.6914 | 0.8899 | 0.9433 | | No log | 4.0674 | 362 | 0.8509 | 0.6951 | 0.8509 | 0.9224 | | No log | 4.0899 | 364 | 0.7797 | 0.7229 | 0.7797 | 0.8830 | | No log | 4.1124 | 366 | 0.7379 | 0.75 | 0.7379 | 0.8590 | | No log | 4.1348 | 368 | 0.7696 | 0.75 | 0.7696 | 0.8773 | | No log | 4.1573 | 370 | 0.8279 | 0.6909 | 0.8279 | 0.9099 | | No log | 4.1798 | 372 | 0.8621 | 0.7317 | 0.8621 | 0.9285 | | No log | 4.2022 | 374 | 0.9652 | 0.6747 | 0.9652 | 0.9825 | | No log | 4.2247 | 376 | 0.9987 | 0.6296 | 0.9987 | 0.9994 | | No log | 4.2472 | 378 | 1.0098 | 0.6883 | 1.0098 | 1.0049 | | No log | 4.2697 | 380 | 1.0363 | 0.625 | 1.0363 | 1.0180 | | No log | 4.2921 | 382 | 0.9867 | 0.5899 | 0.9867 | 0.9933 | | No log | 4.3146 | 384 | 0.9271 | 0.6846 | 0.9271 | 0.9629 | | No log | 4.3371 | 386 | 0.9243 | 0.6452 | 0.9243 | 0.9614 | | No log | 4.3596 | 388 | 1.0277 | 0.6258 | 1.0277 | 1.0138 | | No log | 4.3820 | 390 | 1.1102 | 0.6310 | 1.1102 | 1.0537 | | No log | 4.4045 | 392 | 0.8984 | 0.6420 | 0.8984 | 0.9478 | | No log | 4.4270 | 394 | 0.6753 | 0.8125 | 0.6753 | 0.8218 | | No log | 4.4494 | 396 | 0.6416 | 0.7785 | 0.6416 | 0.8010 | | No log | 4.4719 | 398 | 0.6401 | 0.7785 | 0.6401 | 0.8001 | | No log | 4.4944 | 400 | 0.6687 | 0.7785 | 0.6687 | 0.8178 | | No log | 4.5169 | 402 | 0.7273 | 0.7075 | 0.7273 | 0.8528 | | No log | 4.5393 | 404 | 0.7722 | 0.7020 | 0.7722 | 0.8787 | | No log | 4.5618 | 406 | 0.7629 | 0.7105 | 0.7629 | 0.8734 | | No log | 4.5843 | 408 | 0.7780 | 0.6974 | 0.7780 | 0.8820 | | No log | 4.6067 | 410 | 0.7689 | 0.6974 | 0.7689 | 0.8769 | | No log | 4.6292 | 412 | 0.7241 | 0.75 | 0.7241 | 0.8510 | | No log | 4.6517 | 414 | 0.6443 | 0.7785 | 0.6443 | 0.8027 | | No log | 4.6742 | 416 | 0.6238 | 0.7785 | 0.6238 | 0.7898 | | No log | 4.6966 | 418 | 0.6294 | 0.7867 | 0.6294 | 0.7934 | | No log | 4.7191 | 420 | 0.6906 | 0.7925 | 0.6906 | 0.8310 | | No log | 4.7416 | 422 | 0.8316 | 0.7284 | 0.8316 | 0.9119 | | No log | 4.7640 | 424 | 0.7839 | 0.7425 | 0.7839 | 0.8854 | | No log | 4.7865 | 426 | 0.6938 | 0.7904 | 0.6938 | 0.8330 | | No log | 4.8090 | 428 | 0.6855 | 0.7904 | 0.6855 | 0.8280 | | No log | 4.8315 | 430 | 0.6866 | 0.7952 | 0.6866 | 0.8286 | | No log | 4.8539 | 432 | 0.7095 | 0.8125 | 0.7095 | 0.8423 | | No log | 4.8764 | 434 | 0.7935 | 0.7654 | 0.7935 | 0.8908 | | No log | 4.8989 | 436 | 0.9087 | 0.6829 | 0.9087 | 0.9533 | | No log | 4.9213 | 438 | 0.9127 | 0.6667 | 0.9127 | 0.9553 | | No log | 4.9438 | 440 | 0.8895 | 0.6627 | 0.8895 | 0.9431 | | No log | 4.9663 | 442 | 0.7709 | 0.7619 | 0.7709 | 0.8780 | | No log | 4.9888 | 444 | 0.6746 | 0.7904 | 0.6746 | 0.8213 | | No log | 5.0112 | 446 | 0.6282 | 0.7662 | 0.6282 | 0.7926 | | No log | 5.0337 | 448 | 0.6500 | 0.75 | 0.6500 | 0.8062 | | No log | 5.0562 | 450 | 0.6861 | 0.7550 | 0.6861 | 0.8283 | | No log | 5.0787 | 452 | 0.7197 | 0.7417 | 0.7197 | 0.8483 | | No log | 5.1011 | 454 | 0.7811 | 0.7123 | 0.7811 | 0.8838 | | No log | 5.1236 | 456 | 0.8052 | 0.6713 | 0.8052 | 0.8973 | | No log | 5.1461 | 458 | 0.7841 | 0.6806 | 0.7841 | 0.8855 | | No log | 5.1685 | 460 | 0.7582 | 0.6986 | 0.7582 | 0.8708 | | No log | 5.1910 | 462 | 0.7210 | 0.7383 | 0.7210 | 0.8491 | | No log | 5.2135 | 464 | 0.6827 | 0.7432 | 0.6827 | 0.8262 | | No log | 5.2360 | 466 | 0.6956 | 0.7383 | 0.6956 | 0.8340 | | No log | 5.2584 | 468 | 0.7954 | 0.72 | 0.7954 | 0.8919 | | No log | 5.2809 | 470 | 0.8401 | 0.7355 | 0.8401 | 0.9166 | | No log | 5.3034 | 472 | 0.7855 | 0.7564 | 0.7855 | 0.8863 | | No log | 5.3258 | 474 | 0.7808 | 0.7643 | 0.7808 | 0.8836 | | No log | 5.3483 | 476 | 0.7830 | 0.7485 | 0.7830 | 0.8849 | | No log | 5.3708 | 478 | 0.6540 | 0.7636 | 0.6540 | 0.8087 | | No log | 5.3933 | 480 | 0.6426 | 0.8171 | 0.6426 | 0.8016 | | No log | 5.4157 | 482 | 0.7162 | 0.7561 | 0.7162 | 0.8463 | | No log | 5.4382 | 484 | 0.8179 | 0.7470 | 0.8179 | 0.9044 | | No log | 5.4607 | 486 | 0.8560 | 0.6871 | 0.8560 | 0.9252 | | No log | 5.4831 | 488 | 0.8279 | 0.7044 | 0.8279 | 0.9099 | | No log | 5.5056 | 490 | 0.7908 | 0.7692 | 0.7908 | 0.8892 | | No log | 5.5281 | 492 | 0.8189 | 0.72 | 0.8189 | 0.9049 | | No log | 5.5506 | 494 | 0.8573 | 0.6712 | 0.8573 | 0.9259 | | No log | 5.5730 | 496 | 0.9023 | 0.6622 | 0.9023 | 0.9499 | | No log | 5.5955 | 498 | 0.9562 | 0.6395 | 0.9562 | 0.9779 | | 0.4108 | 5.6180 | 500 | 0.9236 | 0.6154 | 0.9236 | 0.9610 | | 0.4108 | 5.6404 | 502 | 0.8723 | 0.6429 | 0.8723 | 0.9340 | | 0.4108 | 5.6629 | 504 | 0.8019 | 0.7211 | 0.8019 | 0.8955 | | 0.4108 | 5.6854 | 506 | 0.7450 | 0.7662 | 0.7450 | 0.8631 | | 0.4108 | 5.7079 | 508 | 0.7097 | 0.7848 | 0.7097 | 0.8424 | | 0.4108 | 5.7303 | 510 | 0.7363 | 0.7831 | 0.7363 | 0.8581 | | 0.4108 | 5.7528 | 512 | 0.7654 | 0.75 | 0.7654 | 0.8749 | | 0.4108 | 5.7753 | 514 | 0.7439 | 0.75 | 0.7439 | 0.8625 | | 0.4108 | 5.7978 | 516 | 0.6668 | 0.7853 | 0.6668 | 0.8166 | | 0.4108 | 5.8202 | 518 | 0.6113 | 0.8125 | 0.6113 | 0.7819 | | 0.4108 | 5.8427 | 520 | 0.6067 | 0.8050 | 0.6067 | 0.7789 | | 0.4108 | 5.8652 | 522 | 0.6229 | 0.8125 | 0.6229 | 0.7893 | | 0.4108 | 5.8876 | 524 | 0.6233 | 0.7848 | 0.6233 | 0.7895 | | 0.4108 | 5.9101 | 526 | 0.6430 | 0.7925 | 0.6430 | 0.8019 | | 0.4108 | 5.9326 | 528 | 0.6314 | 0.7925 | 0.6314 | 0.7946 | | 0.4108 | 5.9551 | 530 | 0.6136 | 0.8 | 0.6136 | 0.7833 | | 0.4108 | 5.9775 | 532 | 0.6032 | 0.8125 | 0.6032 | 0.7766 | | 0.4108 | 6.0 | 534 | 0.6027 | 0.8025 | 0.6027 | 0.7764 | | 0.4108 | 6.0225 | 536 | 0.6238 | 0.8025 | 0.6238 | 0.7898 | | 0.4108 | 6.0449 | 538 | 0.6663 | 0.8121 | 0.6663 | 0.8163 | | 0.4108 | 6.0674 | 540 | 0.6986 | 0.8047 | 0.6986 | 0.8358 | | 0.4108 | 6.0899 | 542 | 0.7147 | 0.7886 | 0.7147 | 0.8454 | | 0.4108 | 6.1124 | 544 | 0.7203 | 0.7953 | 0.7203 | 0.8487 | | 0.4108 | 6.1348 | 546 | 0.7287 | 0.7904 | 0.7287 | 0.8536 | | 0.4108 | 6.1573 | 548 | 0.7130 | 0.7925 | 0.7130 | 0.8444 | | 0.4108 | 6.1798 | 550 | 0.6790 | 0.7949 | 0.6790 | 0.8240 | | 0.4108 | 6.2022 | 552 | 0.6462 | 0.7949 | 0.6462 | 0.8039 | | 0.4108 | 6.2247 | 554 | 0.6340 | 0.7949 | 0.6340 | 0.7963 | | 0.4108 | 6.2472 | 556 | 0.6552 | 0.7901 | 0.6552 | 0.8094 | | 0.4108 | 6.2697 | 558 | 0.6958 | 0.7879 | 0.6958 | 0.8342 | | 0.4108 | 6.2921 | 560 | 0.7199 | 0.7784 | 0.7199 | 0.8485 | | 0.4108 | 6.3146 | 562 | 0.7557 | 0.7590 | 0.7557 | 0.8693 | | 0.4108 | 6.3371 | 564 | 0.7634 | 0.7848 | 0.7634 | 0.8738 | | 0.4108 | 6.3596 | 566 | 0.7853 | 0.7564 | 0.7853 | 0.8862 | | 0.4108 | 6.3820 | 568 | 0.8368 | 0.6788 | 0.8368 | 0.9148 | | 0.4108 | 6.4045 | 570 | 0.9209 | 0.6941 | 0.9209 | 0.9596 | | 0.4108 | 6.4270 | 572 | 1.0415 | 0.6630 | 1.0415 | 1.0205 | | 0.4108 | 6.4494 | 574 | 0.9611 | 0.6952 | 0.9611 | 0.9804 | | 0.4108 | 6.4719 | 576 | 0.8231 | 0.7667 | 0.8231 | 0.9073 | | 0.4108 | 6.4944 | 578 | 0.7428 | 0.7701 | 0.7428 | 0.8619 | | 0.4108 | 6.5169 | 580 | 0.6969 | 0.7952 | 0.6969 | 0.8348 | | 0.4108 | 6.5393 | 582 | 0.7073 | 0.8050 | 0.7073 | 0.8410 | | 0.4108 | 6.5618 | 584 | 0.7410 | 0.7564 | 0.7410 | 0.8608 | | 0.4108 | 6.5843 | 586 | 0.7670 | 0.6993 | 0.7670 | 0.8758 | | 0.4108 | 6.6067 | 588 | 0.7922 | 0.6763 | 0.7922 | 0.8900 | | 0.4108 | 6.6292 | 590 | 0.8097 | 0.6763 | 0.8097 | 0.8998 | | 0.4108 | 6.6517 | 592 | 0.8084 | 0.6667 | 0.8084 | 0.8991 | | 0.4108 | 6.6742 | 594 | 0.8051 | 0.6423 | 0.8051 | 0.8973 | | 0.4108 | 6.6966 | 596 | 0.7751 | 0.6761 | 0.7751 | 0.8804 | | 0.4108 | 6.7191 | 598 | 0.7358 | 0.7248 | 0.7358 | 0.8578 | | 0.4108 | 6.7416 | 600 | 0.7432 | 0.7484 | 0.7432 | 0.8621 | | 0.4108 | 6.7640 | 602 | 0.7627 | 0.7329 | 0.7627 | 0.8733 | | 0.4108 | 6.7865 | 604 | 0.8505 | 0.7101 | 0.8505 | 0.9222 | | 0.4108 | 6.8090 | 606 | 0.9321 | 0.7052 | 0.9321 | 0.9655 | | 0.4108 | 6.8315 | 608 | 0.9064 | 0.6977 | 0.9064 | 0.9521 | | 0.4108 | 6.8539 | 610 | 0.8078 | 0.7368 | 0.8078 | 0.8988 | | 0.4108 | 6.8764 | 612 | 0.7928 | 0.7561 | 0.7928 | 0.8904 | | 0.4108 | 6.8989 | 614 | 0.8223 | 0.7485 | 0.8223 | 0.9068 | | 0.4108 | 6.9213 | 616 | 0.8761 | 0.6988 | 0.8761 | 0.9360 | | 0.4108 | 6.9438 | 618 | 0.9445 | 0.6258 | 0.9445 | 0.9719 | | 0.4108 | 6.9663 | 620 | 0.9800 | 0.6258 | 0.9800 | 0.9900 | | 0.4108 | 6.9888 | 622 | 0.9661 | 0.6258 | 0.9661 | 0.9829 | | 0.4108 | 7.0112 | 624 | 0.8560 | 0.6709 | 0.8560 | 0.9252 | | 0.4108 | 7.0337 | 626 | 0.7641 | 0.7871 | 0.7641 | 0.8741 | | 0.4108 | 7.0562 | 628 | 0.7324 | 0.7949 | 0.7324 | 0.8558 | | 0.4108 | 7.0787 | 630 | 0.7149 | 0.7949 | 0.7149 | 0.8455 | | 0.4108 | 7.1011 | 632 | 0.7211 | 0.8025 | 0.7211 | 0.8492 | | 0.4108 | 7.1236 | 634 | 0.8127 | 0.7105 | 0.8127 | 0.9015 | | 0.4108 | 7.1461 | 636 | 0.9362 | 0.6538 | 0.9362 | 0.9675 | | 0.4108 | 7.1685 | 638 | 1.0110 | 0.6364 | 1.0110 | 1.0055 | | 0.4108 | 7.1910 | 640 | 0.9426 | 0.6216 | 0.9426 | 0.9709 | | 0.4108 | 7.2135 | 642 | 0.8219 | 0.6667 | 0.8219 | 0.9066 | | 0.4108 | 7.2360 | 644 | 0.7717 | 0.7368 | 0.7717 | 0.8784 | | 0.4108 | 7.2584 | 646 | 0.7557 | 0.7949 | 0.7557 | 0.8693 | | 0.4108 | 7.2809 | 648 | 0.7469 | 0.7662 | 0.7469 | 0.8642 | | 0.4108 | 7.3034 | 650 | 0.7613 | 0.7484 | 0.7613 | 0.8725 | | 0.4108 | 7.3258 | 652 | 0.7972 | 0.6842 | 0.7972 | 0.8929 | | 0.4108 | 7.3483 | 654 | 0.8835 | 0.6667 | 0.8835 | 0.9399 | | 0.4108 | 7.3708 | 656 | 0.9643 | 0.6627 | 0.9643 | 0.9820 | | 0.4108 | 7.3933 | 658 | 0.9340 | 0.7006 | 0.9340 | 0.9664 | | 0.4108 | 7.4157 | 660 | 0.8235 | 0.6797 | 0.8235 | 0.9075 | | 0.4108 | 7.4382 | 662 | 0.7339 | 0.7742 | 0.7339 | 0.8567 | | 0.4108 | 7.4607 | 664 | 0.7120 | 0.7871 | 0.7120 | 0.8438 | | 0.4108 | 7.4831 | 666 | 0.7130 | 0.76 | 0.7130 | 0.8444 | | 0.4108 | 7.5056 | 668 | 0.7107 | 0.7871 | 0.7107 | 0.8430 | | 0.4108 | 7.5281 | 670 | 0.7281 | 0.7949 | 0.7281 | 0.8533 | | 0.4108 | 7.5506 | 672 | 0.7606 | 0.7742 | 0.7606 | 0.8721 | | 0.4108 | 7.5730 | 674 | 0.8003 | 0.7179 | 0.8003 | 0.8946 | | 0.4108 | 7.5955 | 676 | 0.8399 | 0.6709 | 0.8399 | 0.9165 | | 0.4108 | 7.6180 | 678 | 0.8613 | 0.6463 | 0.8613 | 0.9281 | | 0.4108 | 7.6404 | 680 | 0.8270 | 0.6871 | 0.8270 | 0.9094 | | 0.4108 | 7.6629 | 682 | 0.7780 | 0.7215 | 0.7780 | 0.8820 | | 0.4108 | 7.6854 | 684 | 0.7576 | 0.7742 | 0.7576 | 0.8704 | | 0.4108 | 7.7079 | 686 | 0.7672 | 0.7742 | 0.7672 | 0.8759 | | 0.4108 | 7.7303 | 688 | 0.7841 | 0.7451 | 0.7841 | 0.8855 | | 0.4108 | 7.7528 | 690 | 0.7796 | 0.7421 | 0.7796 | 0.8829 | | 0.4108 | 7.7753 | 692 | 0.8324 | 0.6709 | 0.8324 | 0.9124 | | 0.4108 | 7.7978 | 694 | 0.8602 | 0.6871 | 0.8602 | 0.9275 | | 0.4108 | 7.8202 | 696 | 0.8447 | 0.7073 | 0.8447 | 0.9191 | | 0.4108 | 7.8427 | 698 | 0.7853 | 0.7273 | 0.7853 | 0.8862 | | 0.4108 | 7.8652 | 700 | 0.7673 | 0.75 | 0.7673 | 0.8760 | | 0.4108 | 7.8876 | 702 | 0.7676 | 0.7574 | 0.7676 | 0.8762 | | 0.4108 | 7.9101 | 704 | 0.7984 | 0.7152 | 0.7984 | 0.8935 | | 0.4108 | 7.9326 | 706 | 0.8097 | 0.6790 | 0.8097 | 0.8998 | | 0.4108 | 7.9551 | 708 | 0.8056 | 0.6923 | 0.8056 | 0.8975 | | 0.4108 | 7.9775 | 710 | 0.7782 | 0.6933 | 0.7782 | 0.8821 | | 0.4108 | 8.0 | 712 | 0.7368 | 0.7582 | 0.7368 | 0.8583 | | 0.4108 | 8.0225 | 714 | 0.7258 | 0.7682 | 0.7258 | 0.8520 | | 0.4108 | 8.0449 | 716 | 0.7294 | 0.7682 | 0.7294 | 0.8541 | | 0.4108 | 8.0674 | 718 | 0.7498 | 0.7162 | 0.7498 | 0.8659 | | 0.4108 | 8.0899 | 720 | 0.8073 | 0.6667 | 0.8073 | 0.8985 | | 0.4108 | 8.1124 | 722 | 0.8861 | 0.6395 | 0.8861 | 0.9413 | | 0.4108 | 8.1348 | 724 | 0.8883 | 0.6438 | 0.8883 | 0.9425 | | 0.4108 | 8.1573 | 726 | 0.8196 | 0.6338 | 0.8196 | 0.9053 | | 0.4108 | 8.1798 | 728 | 0.7533 | 0.6950 | 0.7533 | 0.8679 | | 0.4108 | 8.2022 | 730 | 0.7504 | 0.7234 | 0.7504 | 0.8662 | | 0.4108 | 8.2247 | 732 | 0.7668 | 0.7234 | 0.7668 | 0.8757 | | 0.4108 | 8.2472 | 734 | 0.7634 | 0.7234 | 0.7634 | 0.8737 | | 0.4108 | 8.2697 | 736 | 0.7420 | 0.7143 | 0.7420 | 0.8614 | | 0.4108 | 8.2921 | 738 | 0.7211 | 0.7586 | 0.7211 | 0.8492 | | 0.4108 | 8.3146 | 740 | 0.7228 | 0.7534 | 0.7228 | 0.8502 | | 0.4108 | 8.3371 | 742 | 0.7666 | 0.6944 | 0.7666 | 0.8756 | | 0.4108 | 8.3596 | 744 | 0.7875 | 0.6286 | 0.7875 | 0.8874 | | 0.4108 | 8.3820 | 746 | 0.7802 | 0.6475 | 0.7802 | 0.8833 | | 0.4108 | 8.4045 | 748 | 0.7427 | 0.7092 | 0.7427 | 0.8618 | | 0.4108 | 8.4270 | 750 | 0.7343 | 0.7234 | 0.7343 | 0.8569 | | 0.4108 | 8.4494 | 752 | 0.7432 | 0.7234 | 0.7432 | 0.8621 | | 0.4108 | 8.4719 | 754 | 0.7555 | 0.7310 | 0.7555 | 0.8692 | | 0.4108 | 8.4944 | 756 | 0.7775 | 0.7467 | 0.7775 | 0.8818 | | 0.4108 | 8.5169 | 758 | 0.7997 | 0.7582 | 0.7997 | 0.8943 | | 0.4108 | 8.5393 | 760 | 0.8284 | 0.6923 | 0.8284 | 0.9102 | | 0.4108 | 8.5618 | 762 | 0.8917 | 0.6875 | 0.8917 | 0.9443 | | 0.4108 | 8.5843 | 764 | 0.9260 | 0.6624 | 0.9260 | 0.9623 | | 0.4108 | 8.6067 | 766 | 0.8834 | 0.6711 | 0.8834 | 0.9399 | | 0.4108 | 8.6292 | 768 | 0.7681 | 0.7152 | 0.7681 | 0.8764 | | 0.4108 | 8.6517 | 770 | 0.6925 | 0.7843 | 0.6925 | 0.8322 | | 0.4108 | 8.6742 | 772 | 0.6811 | 0.7733 | 0.6811 | 0.8253 | | 0.4108 | 8.6966 | 774 | 0.6814 | 0.7949 | 0.6814 | 0.8255 | | 0.4108 | 8.7191 | 776 | 0.6917 | 0.7949 | 0.6917 | 0.8317 | | 0.4108 | 8.7416 | 778 | 0.7070 | 0.7742 | 0.7070 | 0.8408 | | 0.4108 | 8.7640 | 780 | 0.7199 | 0.8 | 0.7199 | 0.8484 | | 0.4108 | 8.7865 | 782 | 0.7148 | 0.8 | 0.7148 | 0.8454 | | 0.4108 | 8.8090 | 784 | 0.7058 | 0.7949 | 0.7058 | 0.8401 | | 0.4108 | 8.8315 | 786 | 0.7053 | 0.8050 | 0.7053 | 0.8398 | | 0.4108 | 8.8539 | 788 | 0.7390 | 0.7853 | 0.7390 | 0.8596 | | 0.4108 | 8.8764 | 790 | 0.7897 | 0.7407 | 0.7897 | 0.8887 | | 0.4108 | 8.8989 | 792 | 0.8494 | 0.6941 | 0.8494 | 0.9216 | | 0.4108 | 8.9213 | 794 | 0.8960 | 0.6667 | 0.8960 | 0.9466 | | 0.4108 | 8.9438 | 796 | 0.9026 | 0.6746 | 0.9026 | 0.9501 | | 0.4108 | 8.9663 | 798 | 0.8892 | 0.7018 | 0.8892 | 0.9430 | | 0.4108 | 8.9888 | 800 | 0.8590 | 0.7135 | 0.8590 | 0.9268 | | 0.4108 | 9.0112 | 802 | 0.8189 | 0.7024 | 0.8189 | 0.9049 | | 0.4108 | 9.0337 | 804 | 0.8683 | 0.6941 | 0.8683 | 0.9318 | | 0.4108 | 9.0562 | 806 | 0.8950 | 0.6747 | 0.8950 | 0.9461 | | 0.4108 | 9.0787 | 808 | 0.9466 | 0.6386 | 0.9466 | 0.9729 | | 0.4108 | 9.1011 | 810 | 0.8961 | 0.6709 | 0.8961 | 0.9466 | | 0.4108 | 9.1236 | 812 | 0.7832 | 0.7190 | 0.7832 | 0.8850 | | 0.4108 | 9.1461 | 814 | 0.7159 | 0.7451 | 0.7159 | 0.8461 | | 0.4108 | 9.1685 | 816 | 0.7033 | 0.7582 | 0.7033 | 0.8386 | | 0.4108 | 9.1910 | 818 | 0.7130 | 0.7582 | 0.7130 | 0.8444 | | 0.4108 | 9.2135 | 820 | 0.7455 | 0.7237 | 0.7455 | 0.8634 | | 0.4108 | 9.2360 | 822 | 0.7779 | 0.7190 | 0.7779 | 0.8820 | | 0.4108 | 9.2584 | 824 | 0.7932 | 0.7237 | 0.7932 | 0.8906 | | 0.4108 | 9.2809 | 826 | 0.7900 | 0.7237 | 0.7900 | 0.8888 | | 0.4108 | 9.3034 | 828 | 0.7522 | 0.7105 | 0.7522 | 0.8673 | | 0.4108 | 9.3258 | 830 | 0.7069 | 0.7333 | 0.7069 | 0.8408 | | 0.4108 | 9.3483 | 832 | 0.7039 | 0.7467 | 0.7039 | 0.8390 | | 0.4108 | 9.3708 | 834 | 0.7188 | 0.7361 | 0.7188 | 0.8478 | | 0.4108 | 9.3933 | 836 | 0.7636 | 0.6950 | 0.7636 | 0.8738 | | 0.4108 | 9.4157 | 838 | 0.7806 | 0.6812 | 0.7806 | 0.8835 | | 0.4108 | 9.4382 | 840 | 0.7602 | 0.6667 | 0.7602 | 0.8719 | | 0.4108 | 9.4607 | 842 | 0.7421 | 0.7133 | 0.7421 | 0.8614 | | 0.4108 | 9.4831 | 844 | 0.7280 | 0.7248 | 0.7280 | 0.8532 | | 0.4108 | 9.5056 | 846 | 0.7300 | 0.7248 | 0.7300 | 0.8544 | | 0.4108 | 9.5281 | 848 | 0.7692 | 0.7190 | 0.7692 | 0.8770 | | 0.4108 | 9.5506 | 850 | 0.7942 | 0.7190 | 0.7942 | 0.8912 | | 0.4108 | 9.5730 | 852 | 0.7760 | 0.7075 | 0.7760 | 0.8809 | | 0.4108 | 9.5955 | 854 | 0.7386 | 0.7248 | 0.7386 | 0.8594 | | 0.4108 | 9.6180 | 856 | 0.7129 | 0.7248 | 0.7129 | 0.8444 | | 0.4108 | 9.6404 | 858 | 0.7050 | 0.7333 | 0.7050 | 0.8396 | | 0.4108 | 9.6629 | 860 | 0.7291 | 0.7368 | 0.7291 | 0.8539 | | 0.4108 | 9.6854 | 862 | 0.7425 | 0.7451 | 0.7425 | 0.8617 | | 0.4108 | 9.7079 | 864 | 0.7430 | 0.7368 | 0.7430 | 0.8620 | | 0.4108 | 9.7303 | 866 | 0.7808 | 0.7368 | 0.7808 | 0.8837 | | 0.4108 | 9.7528 | 868 | 0.9250 | 0.6429 | 0.9250 | 0.9618 | | 0.4108 | 9.7753 | 870 | 0.9775 | 0.6347 | 0.9775 | 0.9887 | | 0.4108 | 9.7978 | 872 | 0.8964 | 0.6503 | 0.8964 | 0.9468 | | 0.4108 | 9.8202 | 874 | 0.7878 | 0.7436 | 0.7878 | 0.8876 | | 0.4108 | 9.8427 | 876 | 0.7188 | 0.7662 | 0.7188 | 0.8478 | | 0.4108 | 9.8652 | 878 | 0.6850 | 0.7871 | 0.6850 | 0.8276 | | 0.4108 | 9.8876 | 880 | 0.6926 | 0.7662 | 0.6926 | 0.8322 | | 0.4108 | 9.9101 | 882 | 0.7107 | 0.7550 | 0.7107 | 0.8430 | | 0.4108 | 9.9326 | 884 | 0.7245 | 0.7432 | 0.7245 | 0.8512 | | 0.4108 | 9.9551 | 886 | 0.7322 | 0.7310 | 0.7322 | 0.8557 | | 0.4108 | 9.9775 | 888 | 0.7489 | 0.7361 | 0.7489 | 0.8654 | | 0.4108 | 10.0 | 890 | 0.7577 | 0.7361 | 0.7577 | 0.8705 | | 0.4108 | 10.0225 | 892 | 0.7513 | 0.7361 | 0.7513 | 0.8668 | | 0.4108 | 10.0449 | 894 | 0.7598 | 0.7133 | 0.7598 | 0.8717 | | 0.4108 | 10.0674 | 896 | 0.7931 | 0.6522 | 0.7931 | 0.8906 | | 0.4108 | 10.0899 | 898 | 0.8341 | 0.6423 | 0.8341 | 0.9133 | | 0.4108 | 10.1124 | 900 | 0.8211 | 0.6522 | 0.8211 | 0.9061 | | 0.4108 | 10.1348 | 902 | 0.7625 | 0.6763 | 0.7625 | 0.8732 | | 0.4108 | 10.1573 | 904 | 0.7206 | 0.7234 | 0.7206 | 0.8489 | | 0.4108 | 10.1798 | 906 | 0.6887 | 0.7234 | 0.6887 | 0.8299 | | 0.4108 | 10.2022 | 908 | 0.6599 | 0.7448 | 0.6599 | 0.8124 | | 0.4108 | 10.2247 | 910 | 0.6414 | 0.7671 | 0.6414 | 0.8009 | | 0.4108 | 10.2472 | 912 | 0.6461 | 0.7586 | 0.6461 | 0.8038 | | 0.4108 | 10.2697 | 914 | 0.6742 | 0.7413 | 0.6742 | 0.8211 | | 0.4108 | 10.2921 | 916 | 0.7835 | 0.6809 | 0.7835 | 0.8851 | | 0.4108 | 10.3146 | 918 | 0.8354 | 0.6475 | 0.8354 | 0.9140 | | 0.4108 | 10.3371 | 920 | 0.7677 | 0.6761 | 0.7677 | 0.8762 | | 0.4108 | 10.3596 | 922 | 0.6541 | 0.7222 | 0.6541 | 0.8088 | | 0.4108 | 10.3820 | 924 | 0.6368 | 0.7733 | 0.6368 | 0.7980 | | 0.4108 | 10.4045 | 926 | 0.6619 | 0.7949 | 0.6619 | 0.8136 | | 0.4108 | 10.4270 | 928 | 0.7138 | 0.7975 | 0.7138 | 0.8449 | | 0.4108 | 10.4494 | 930 | 0.7559 | 0.7692 | 0.7559 | 0.8694 | | 0.4108 | 10.4719 | 932 | 0.7835 | 0.75 | 0.7836 | 0.8852 | | 0.4108 | 10.4944 | 934 | 0.7897 | 0.7425 | 0.7897 | 0.8887 | | 0.4108 | 10.5169 | 936 | 0.8144 | 0.7349 | 0.8144 | 0.9024 | | 0.4108 | 10.5393 | 938 | 0.8365 | 0.7051 | 0.8365 | 0.9146 | | 0.4108 | 10.5618 | 940 | 0.8405 | 0.6928 | 0.8405 | 0.9168 | | 0.4108 | 10.5843 | 942 | 0.8292 | 0.6579 | 0.8292 | 0.9106 | | 0.4108 | 10.6067 | 944 | 0.7814 | 0.7143 | 0.7814 | 0.8840 | | 0.4108 | 10.6292 | 946 | 0.7252 | 0.7516 | 0.7252 | 0.8516 | | 0.4108 | 10.6517 | 948 | 0.6647 | 0.7722 | 0.6647 | 0.8153 | | 0.4108 | 10.6742 | 950 | 0.6261 | 0.7843 | 0.6261 | 0.7913 | | 0.4108 | 10.6966 | 952 | 0.6143 | 0.7517 | 0.6143 | 0.7838 | | 0.4108 | 10.7191 | 954 | 0.6057 | 0.7733 | 0.6057 | 0.7783 | | 0.4108 | 10.7416 | 956 | 0.5955 | 0.7799 | 0.5955 | 0.7717 | | 0.4108 | 10.7640 | 958 | 0.6243 | 0.7975 | 0.6243 | 0.7901 | | 0.4108 | 10.7865 | 960 | 0.7047 | 0.7453 | 0.7047 | 0.8395 | | 0.4108 | 10.8090 | 962 | 0.8036 | 0.725 | 0.8036 | 0.8964 | | 0.4108 | 10.8315 | 964 | 0.8204 | 0.7006 | 0.8204 | 0.9058 | | 0.4108 | 10.8539 | 966 | 0.7663 | 0.6974 | 0.7663 | 0.8754 | | 0.4108 | 10.8764 | 968 | 0.6950 | 0.7397 | 0.6950 | 0.8336 | | 0.4108 | 10.8989 | 970 | 0.6610 | 0.7397 | 0.6610 | 0.8130 | | 0.4108 | 10.9213 | 972 | 0.6401 | 0.7733 | 0.6401 | 0.8001 | | 0.4108 | 10.9438 | 974 | 0.6417 | 0.8050 | 0.6417 | 0.8011 | | 0.4108 | 10.9663 | 976 | 0.7302 | 0.7362 | 0.7302 | 0.8545 | | 0.4108 | 10.9888 | 978 | 0.8548 | 0.7186 | 0.8548 | 0.9245 | | 0.4108 | 11.0112 | 980 | 0.9575 | 0.6747 | 0.9575 | 0.9785 | | 0.4108 | 11.0337 | 982 | 0.9180 | 0.6875 | 0.9180 | 0.9581 | | 0.4108 | 11.0562 | 984 | 0.8190 | 0.7308 | 0.8190 | 0.9050 | | 0.4108 | 11.0787 | 986 | 0.7186 | 0.7226 | 0.7186 | 0.8477 | | 0.4108 | 11.1011 | 988 | 0.6561 | 0.7534 | 0.6561 | 0.8100 | | 0.4108 | 11.1236 | 990 | 0.6681 | 0.7586 | 0.6681 | 0.8174 | | 0.4108 | 11.1461 | 992 | 0.6943 | 0.7234 | 0.6943 | 0.8332 | | 0.4108 | 11.1685 | 994 | 0.7027 | 0.7234 | 0.7027 | 0.8383 | | 0.4108 | 11.1910 | 996 | 0.7129 | 0.75 | 0.7129 | 0.8444 | | 0.4108 | 11.2135 | 998 | 0.7362 | 0.7133 | 0.7362 | 0.8580 | | 0.0902 | 11.2360 | 1000 | 0.7913 | 0.6331 | 0.7913 | 0.8895 | | 0.0902 | 11.2584 | 1002 | 0.8354 | 0.6197 | 0.8354 | 0.9140 | | 0.0902 | 11.2809 | 1004 | 0.8424 | 0.6438 | 0.8424 | 0.9178 | | 0.0902 | 11.3034 | 1006 | 0.7741 | 0.6846 | 0.7741 | 0.8798 | | 0.0902 | 11.3258 | 1008 | 0.6986 | 0.7222 | 0.6986 | 0.8358 | | 0.0902 | 11.3483 | 1010 | 0.6959 | 0.7222 | 0.6959 | 0.8342 | | 0.0902 | 11.3708 | 1012 | 0.7097 | 0.7222 | 0.7097 | 0.8424 | | 0.0902 | 11.3933 | 1014 | 0.7227 | 0.7222 | 0.7227 | 0.8501 | | 0.0902 | 11.4157 | 1016 | 0.7240 | 0.7222 | 0.7240 | 0.8509 | | 0.0902 | 11.4382 | 1018 | 0.7231 | 0.7183 | 0.7231 | 0.8504 | | 0.0902 | 11.4607 | 1020 | 0.7425 | 0.7183 | 0.7425 | 0.8617 | | 0.0902 | 11.4831 | 1022 | 0.7399 | 0.6857 | 0.7399 | 0.8602 | | 0.0902 | 11.5056 | 1024 | 0.7269 | 0.6950 | 0.7269 | 0.8526 | | 0.0902 | 11.5281 | 1026 | 0.7119 | 0.6901 | 0.7119 | 0.8437 | | 0.0902 | 11.5506 | 1028 | 0.7208 | 0.6939 | 0.7208 | 0.8490 | | 0.0902 | 11.5730 | 1030 | 0.7919 | 0.6839 | 0.7919 | 0.8899 | | 0.0902 | 11.5955 | 1032 | 0.8472 | 0.6753 | 0.8472 | 0.9204 | | 0.0902 | 11.6180 | 1034 | 0.8890 | 0.6623 | 0.8890 | 0.9428 | | 0.0902 | 11.6404 | 1036 | 0.8065 | 0.6839 | 0.8065 | 0.8980 | | 0.0902 | 11.6629 | 1038 | 0.7126 | 0.7403 | 0.7126 | 0.8442 | | 0.0902 | 11.6854 | 1040 | 0.6552 | 0.7742 | 0.6552 | 0.8095 | | 0.0902 | 11.7079 | 1042 | 0.6468 | 0.7949 | 0.6468 | 0.8043 | | 0.0902 | 11.7303 | 1044 | 0.6622 | 0.7949 | 0.6622 | 0.8137 | | 0.0902 | 11.7528 | 1046 | 0.6878 | 0.7692 | 0.6878 | 0.8294 | | 0.0902 | 11.7753 | 1048 | 0.6873 | 0.7742 | 0.6873 | 0.8290 | | 0.0902 | 11.7978 | 1050 | 0.6694 | 0.7662 | 0.6694 | 0.8182 | | 0.0902 | 11.8202 | 1052 | 0.6394 | 0.7843 | 0.6394 | 0.7996 | | 0.0902 | 11.8427 | 1054 | 0.6176 | 0.7843 | 0.6176 | 0.7859 | | 0.0902 | 11.8652 | 1056 | 0.6236 | 0.7763 | 0.6236 | 0.7897 | | 0.0902 | 11.8876 | 1058 | 0.6418 | 0.7792 | 0.6418 | 0.8011 | | 0.0902 | 11.9101 | 1060 | 0.6360 | 0.7722 | 0.6360 | 0.7975 | | 0.0902 | 11.9326 | 1062 | 0.6413 | 0.775 | 0.6413 | 0.8008 | | 0.0902 | 11.9551 | 1064 | 0.6599 | 0.775 | 0.6599 | 0.8123 | | 0.0902 | 11.9775 | 1066 | 0.6832 | 0.775 | 0.6832 | 0.8266 | | 0.0902 | 12.0 | 1068 | 0.7074 | 0.7799 | 0.7074 | 0.8411 | | 0.0902 | 12.0225 | 1070 | 0.7394 | 0.7703 | 0.7394 | 0.8599 | | 0.0902 | 12.0449 | 1072 | 0.7905 | 0.6944 | 0.7905 | 0.8891 | | 0.0902 | 12.0674 | 1074 | 0.8131 | 0.7133 | 0.8131 | 0.9017 | | 0.0902 | 12.0899 | 1076 | 0.7863 | 0.7273 | 0.7863 | 0.8867 | | 0.0902 | 12.1124 | 1078 | 0.7514 | 0.7534 | 0.7514 | 0.8668 | | 0.0902 | 12.1348 | 1080 | 0.7385 | 0.6667 | 0.7385 | 0.8594 | | 0.0902 | 12.1573 | 1082 | 0.7411 | 0.6667 | 0.7411 | 0.8609 | | 0.0902 | 12.1798 | 1084 | 0.7129 | 0.6757 | 0.7129 | 0.8443 | | 0.0902 | 12.2022 | 1086 | 0.6768 | 0.6892 | 0.6768 | 0.8227 | | 0.0902 | 12.2247 | 1088 | 0.6493 | 0.7413 | 0.6493 | 0.8058 | | 0.0902 | 12.2472 | 1090 | 0.6430 | 0.7671 | 0.6430 | 0.8019 | | 0.0902 | 12.2697 | 1092 | 0.6493 | 0.7586 | 0.6493 | 0.8058 | | 0.0902 | 12.2921 | 1094 | 0.6675 | 0.7413 | 0.6675 | 0.8170 | | 0.0902 | 12.3146 | 1096 | 0.7245 | 0.6901 | 0.7245 | 0.8512 | | 0.0902 | 12.3371 | 1098 | 0.8463 | 0.6575 | 0.8463 | 0.9199 | | 0.0902 | 12.3596 | 1100 | 0.9309 | 0.6483 | 0.9309 | 0.9648 | | 0.0902 | 12.3820 | 1102 | 0.9031 | 0.6667 | 0.9031 | 0.9503 | | 0.0902 | 12.4045 | 1104 | 0.7976 | 0.6761 | 0.7976 | 0.8931 | | 0.0902 | 12.4270 | 1106 | 0.6976 | 0.7448 | 0.6976 | 0.8352 | | 0.0902 | 12.4494 | 1108 | 0.6741 | 0.7671 | 0.6741 | 0.8210 | | 0.0902 | 12.4719 | 1110 | 0.6870 | 0.7050 | 0.6870 | 0.8289 | | 0.0902 | 12.4944 | 1112 | 0.6879 | 0.7413 | 0.6879 | 0.8294 | | 0.0902 | 12.5169 | 1114 | 0.6805 | 0.75 | 0.6805 | 0.8249 | | 0.0902 | 12.5393 | 1116 | 0.6757 | 0.7586 | 0.6757 | 0.8220 | | 0.0902 | 12.5618 | 1118 | 0.6882 | 0.7534 | 0.6882 | 0.8296 | | 0.0902 | 12.5843 | 1120 | 0.7040 | 0.7123 | 0.7040 | 0.8391 | | 0.0902 | 12.6067 | 1122 | 0.6870 | 0.7432 | 0.6870 | 0.8289 | | 0.0902 | 12.6292 | 1124 | 0.6693 | 0.7619 | 0.6693 | 0.8181 | | 0.0902 | 12.6517 | 1126 | 0.6815 | 0.7361 | 0.6815 | 0.8256 | | 0.0902 | 12.6742 | 1128 | 0.7148 | 0.7133 | 0.7148 | 0.8455 | | 0.0902 | 12.6966 | 1130 | 0.7334 | 0.6901 | 0.7334 | 0.8564 | | 0.0902 | 12.7191 | 1132 | 0.7092 | 0.6944 | 0.7092 | 0.8421 | | 0.0902 | 12.7416 | 1134 | 0.6664 | 0.7361 | 0.6664 | 0.8164 | | 0.0902 | 12.7640 | 1136 | 0.6453 | 0.7703 | 0.6453 | 0.8033 | | 0.0902 | 12.7865 | 1138 | 0.6592 | 0.7682 | 0.6592 | 0.8119 | | 0.0902 | 12.8090 | 1140 | 0.6804 | 0.7448 | 0.6804 | 0.8249 | | 0.0902 | 12.8315 | 1142 | 0.7077 | 0.75 | 0.7077 | 0.8413 | | 0.0902 | 12.8539 | 1144 | 0.7501 | 0.6950 | 0.7501 | 0.8661 | | 0.0902 | 12.8764 | 1146 | 0.7861 | 0.6620 | 0.7861 | 0.8866 | | 0.0902 | 12.8989 | 1148 | 0.7880 | 0.6620 | 0.7880 | 0.8877 | | 0.0902 | 12.9213 | 1150 | 0.7739 | 0.6986 | 0.7739 | 0.8797 | | 0.0902 | 12.9438 | 1152 | 0.7630 | 0.7114 | 0.7630 | 0.8735 | | 0.0902 | 12.9663 | 1154 | 0.7492 | 0.7067 | 0.7492 | 0.8656 | | 0.0902 | 12.9888 | 1156 | 0.7518 | 0.7105 | 0.7518 | 0.8670 | | 0.0902 | 13.0112 | 1158 | 0.7827 | 0.6968 | 0.7827 | 0.8847 | | 0.0902 | 13.0337 | 1160 | 0.7917 | 0.7037 | 0.7917 | 0.8898 | | 0.0902 | 13.0562 | 1162 | 0.7680 | 0.7108 | 0.7680 | 0.8764 | | 0.0902 | 13.0787 | 1164 | 0.7283 | 0.7545 | 0.7283 | 0.8534 | | 0.0902 | 13.1011 | 1166 | 0.6815 | 0.7619 | 0.6815 | 0.8255 | | 0.0902 | 13.1236 | 1168 | 0.6469 | 0.7799 | 0.6469 | 0.8043 | | 0.0902 | 13.1461 | 1170 | 0.6309 | 0.7949 | 0.6309 | 0.7943 | | 0.0902 | 13.1685 | 1172 | 0.6314 | 0.7949 | 0.6314 | 0.7946 | | 0.0902 | 13.1910 | 1174 | 0.6307 | 0.7949 | 0.6307 | 0.7942 | | 0.0902 | 13.2135 | 1176 | 0.6444 | 0.7871 | 0.6444 | 0.8028 | | 0.0902 | 13.2360 | 1178 | 0.6747 | 0.7792 | 0.6747 | 0.8214 | | 0.0902 | 13.2584 | 1180 | 0.6891 | 0.7712 | 0.6891 | 0.8301 | | 0.0902 | 13.2809 | 1182 | 0.6867 | 0.7712 | 0.6867 | 0.8287 | | 0.0902 | 13.3034 | 1184 | 0.6621 | 0.76 | 0.6621 | 0.8137 | | 0.0902 | 13.3258 | 1186 | 0.6470 | 0.7682 | 0.6470 | 0.8043 | | 0.0902 | 13.3483 | 1188 | 0.6416 | 0.7763 | 0.6416 | 0.8010 | | 0.0902 | 13.3708 | 1190 | 0.6360 | 0.7763 | 0.6360 | 0.7975 | | 0.0902 | 13.3933 | 1192 | 0.6297 | 0.7682 | 0.6297 | 0.7936 | | 0.0902 | 13.4157 | 1194 | 0.6456 | 0.7682 | 0.6456 | 0.8035 | | 0.0902 | 13.4382 | 1196 | 0.6563 | 0.7771 | 0.6563 | 0.8101 | | 0.0902 | 13.4607 | 1198 | 0.6641 | 0.7692 | 0.6641 | 0.8149 | | 0.0902 | 13.4831 | 1200 | 0.6807 | 0.7484 | 0.6807 | 0.8251 | | 0.0902 | 13.5056 | 1202 | 0.6735 | 0.7692 | 0.6735 | 0.8207 | | 0.0902 | 13.5281 | 1204 | 0.6445 | 0.7582 | 0.6445 | 0.8028 | | 0.0902 | 13.5506 | 1206 | 0.6326 | 0.7792 | 0.6326 | 0.7953 | | 0.0902 | 13.5730 | 1208 | 0.6318 | 0.7792 | 0.6318 | 0.7948 | | 0.0902 | 13.5955 | 1210 | 0.6403 | 0.7692 | 0.6403 | 0.8002 | | 0.0902 | 13.6180 | 1212 | 0.6905 | 0.7547 | 0.6905 | 0.8310 | | 0.0902 | 13.6404 | 1214 | 0.7628 | 0.7425 | 0.7628 | 0.8734 | | 0.0902 | 13.6629 | 1216 | 0.8088 | 0.7045 | 0.8088 | 0.8994 | | 0.0902 | 13.6854 | 1218 | 0.8127 | 0.7293 | 0.8127 | 0.9015 | | 0.0902 | 13.7079 | 1220 | 0.8216 | 0.7363 | 0.8216 | 0.9064 | | 0.0902 | 13.7303 | 1222 | 0.8397 | 0.7363 | 0.8397 | 0.9164 | | 0.0902 | 13.7528 | 1224 | 0.8094 | 0.7541 | 0.8094 | 0.8997 | | 0.0902 | 13.7753 | 1226 | 0.7963 | 0.7444 | 0.7963 | 0.8923 | | 0.0902 | 13.7978 | 1228 | 0.8017 | 0.7444 | 0.8017 | 0.8954 | | 0.0902 | 13.8202 | 1230 | 0.8622 | 0.7263 | 0.8622 | 0.9286 | | 0.0902 | 13.8427 | 1232 | 0.9431 | 0.6742 | 0.9431 | 0.9711 | | 0.0902 | 13.8652 | 1234 | 0.9269 | 0.6857 | 0.9269 | 0.9628 | | 0.0902 | 13.8876 | 1236 | 0.8206 | 0.7093 | 0.8206 | 0.9059 | | 0.0902 | 13.9101 | 1238 | 0.7411 | 0.7468 | 0.7411 | 0.8609 | | 0.0902 | 13.9326 | 1240 | 0.7126 | 0.7368 | 0.7126 | 0.8442 | | 0.0902 | 13.9551 | 1242 | 0.7678 | 0.6713 | 0.7678 | 0.8762 | | 0.0902 | 13.9775 | 1244 | 0.8350 | 0.6475 | 0.8350 | 0.9138 | | 0.0902 | 14.0 | 1246 | 0.8394 | 0.6475 | 0.8394 | 0.9162 | | 0.0902 | 14.0225 | 1248 | 0.8266 | 0.5985 | 0.8266 | 0.9092 | | 0.0902 | 14.0449 | 1250 | 0.7328 | 0.6618 | 0.7328 | 0.8561 | | 0.0902 | 14.0674 | 1252 | 0.6881 | 0.7 | 0.6881 | 0.8295 | | 0.0902 | 14.0899 | 1254 | 0.6485 | 0.6993 | 0.6485 | 0.8053 | | 0.0902 | 14.1124 | 1256 | 0.6188 | 0.7568 | 0.6188 | 0.7867 | | 0.0902 | 14.1348 | 1258 | 0.6284 | 0.7763 | 0.6284 | 0.7927 | | 0.0902 | 14.1573 | 1260 | 0.6399 | 0.7763 | 0.6399 | 0.8000 | | 0.0902 | 14.1798 | 1262 | 0.6428 | 0.7843 | 0.6428 | 0.8017 | | 0.0902 | 14.2022 | 1264 | 0.6348 | 0.7843 | 0.6348 | 0.7967 | | 0.0902 | 14.2247 | 1266 | 0.6232 | 0.7733 | 0.6232 | 0.7894 | | 0.0902 | 14.2472 | 1268 | 0.6153 | 0.7534 | 0.6153 | 0.7844 | | 0.0902 | 14.2697 | 1270 | 0.6003 | 0.7534 | 0.6003 | 0.7748 | | 0.0902 | 14.2921 | 1272 | 0.5946 | 0.7619 | 0.5946 | 0.7711 | | 0.0902 | 14.3146 | 1274 | 0.5945 | 0.7619 | 0.5945 | 0.7711 | | 0.0902 | 14.3371 | 1276 | 0.5865 | 0.7619 | 0.5865 | 0.7658 | | 0.0902 | 14.3596 | 1278 | 0.5915 | 0.7534 | 0.5915 | 0.7691 | | 0.0902 | 14.3820 | 1280 | 0.6255 | 0.7534 | 0.6255 | 0.7909 | | 0.0902 | 14.4045 | 1282 | 0.6337 | 0.7534 | 0.6337 | 0.7961 | | 0.0902 | 14.4270 | 1284 | 0.6298 | 0.7534 | 0.6298 | 0.7936 | | 0.0902 | 14.4494 | 1286 | 0.6248 | 0.7651 | 0.6248 | 0.7905 | | 0.0902 | 14.4719 | 1288 | 0.6185 | 0.7871 | 0.6185 | 0.7865 | | 0.0902 | 14.4944 | 1290 | 0.6037 | 0.7949 | 0.6037 | 0.7770 | | 0.0902 | 14.5169 | 1292 | 0.5979 | 0.7949 | 0.5979 | 0.7733 | | 0.0902 | 14.5393 | 1294 | 0.6044 | 0.7949 | 0.6044 | 0.7774 | | 0.0902 | 14.5618 | 1296 | 0.6157 | 0.8050 | 0.6157 | 0.7846 | | 0.0902 | 14.5843 | 1298 | 0.6444 | 0.7879 | 0.6444 | 0.8028 | | 0.0902 | 14.6067 | 1300 | 0.6733 | 0.7738 | 0.6733 | 0.8205 | | 0.0902 | 14.6292 | 1302 | 0.7218 | 0.7674 | 0.7218 | 0.8496 | | 0.0902 | 14.6517 | 1304 | 0.7525 | 0.7543 | 0.7525 | 0.8675 | | 0.0902 | 14.6742 | 1306 | 0.7656 | 0.7640 | 0.7656 | 0.8750 | | 0.0902 | 14.6966 | 1308 | 0.7987 | 0.7086 | 0.7987 | 0.8937 | | 0.0902 | 14.7191 | 1310 | 0.8112 | 0.7045 | 0.8112 | 0.9007 | | 0.0902 | 14.7416 | 1312 | 0.8417 | 0.6932 | 0.8417 | 0.9174 | | 0.0902 | 14.7640 | 1314 | 0.7978 | 0.6941 | 0.7978 | 0.8932 | | 0.0902 | 14.7865 | 1316 | 0.7087 | 0.7179 | 0.7087 | 0.8419 | | 0.0902 | 14.8090 | 1318 | 0.6274 | 0.7792 | 0.6274 | 0.7921 | | 0.0902 | 14.8315 | 1320 | 0.6026 | 0.7733 | 0.6026 | 0.7762 | | 0.0902 | 14.8539 | 1322 | 0.6035 | 0.7651 | 0.6035 | 0.7769 | | 0.0902 | 14.8764 | 1324 | 0.6007 | 0.7651 | 0.6007 | 0.7751 | | 0.0902 | 14.8989 | 1326 | 0.5988 | 0.7534 | 0.5988 | 0.7738 | | 0.0902 | 14.9213 | 1328 | 0.6025 | 0.7534 | 0.6025 | 0.7762 | | 0.0902 | 14.9438 | 1330 | 0.6074 | 0.7534 | 0.6074 | 0.7794 | | 0.0902 | 14.9663 | 1332 | 0.6149 | 0.7534 | 0.6149 | 0.7842 | | 0.0902 | 14.9888 | 1334 | 0.6369 | 0.7534 | 0.6369 | 0.7981 | | 0.0902 | 15.0112 | 1336 | 0.6929 | 0.6901 | 0.6929 | 0.8324 | | 0.0902 | 15.0337 | 1338 | 0.7589 | 0.6429 | 0.7589 | 0.8712 | | 0.0902 | 15.0562 | 1340 | 0.8354 | 0.6429 | 0.8354 | 0.9140 | | 0.0902 | 15.0787 | 1342 | 0.8459 | 0.6429 | 0.8459 | 0.9197 | | 0.0902 | 15.1011 | 1344 | 0.7767 | 0.6429 | 0.7767 | 0.8813 | | 0.0902 | 15.1236 | 1346 | 0.6776 | 0.7133 | 0.6776 | 0.8232 | | 0.0902 | 15.1461 | 1348 | 0.6352 | 0.7534 | 0.6352 | 0.7970 | | 0.0902 | 15.1685 | 1350 | 0.6148 | 0.7534 | 0.6148 | 0.7841 | | 0.0902 | 15.1910 | 1352 | 0.6157 | 0.7651 | 0.6157 | 0.7847 | | 0.0902 | 15.2135 | 1354 | 0.6375 | 0.7448 | 0.6375 | 0.7984 | | 0.0902 | 15.2360 | 1356 | 0.6892 | 0.6993 | 0.6892 | 0.8302 | | 0.0902 | 15.2584 | 1358 | 0.7375 | 0.6429 | 0.7375 | 0.8588 | | 0.0902 | 15.2809 | 1360 | 0.7440 | 0.6277 | 0.7440 | 0.8626 | | 0.0902 | 15.3034 | 1362 | 0.7051 | 0.6857 | 0.7051 | 0.8397 | | 0.0902 | 15.3258 | 1364 | 0.6784 | 0.7324 | 0.6784 | 0.8236 | | 0.0902 | 15.3483 | 1366 | 0.6693 | 0.7413 | 0.6693 | 0.8181 | | 0.0902 | 15.3708 | 1368 | 0.6865 | 0.7092 | 0.6865 | 0.8285 | | 0.0902 | 15.3933 | 1370 | 0.7129 | 0.7034 | 0.7129 | 0.8443 | | 0.0902 | 15.4157 | 1372 | 0.7180 | 0.6806 | 0.7180 | 0.8473 | | 0.0902 | 15.4382 | 1374 | 0.7093 | 0.6713 | 0.7093 | 0.8422 | | 0.0902 | 15.4607 | 1376 | 0.7080 | 0.6939 | 0.7080 | 0.8414 | | 0.0902 | 15.4831 | 1378 | 0.7029 | 0.6939 | 0.7029 | 0.8384 | | 0.0902 | 15.5056 | 1380 | 0.6650 | 0.7467 | 0.6650 | 0.8155 | | 0.0902 | 15.5281 | 1382 | 0.6446 | 0.7792 | 0.6446 | 0.8029 | | 0.0902 | 15.5506 | 1384 | 0.6390 | 0.7871 | 0.6390 | 0.7994 | | 0.0902 | 15.5730 | 1386 | 0.6562 | 0.7975 | 0.6562 | 0.8100 | | 0.0902 | 15.5955 | 1388 | 0.6837 | 0.7771 | 0.6837 | 0.8269 | | 0.0902 | 15.6180 | 1390 | 0.7191 | 0.7342 | 0.7191 | 0.8480 | | 0.0902 | 15.6404 | 1392 | 0.7462 | 0.6957 | 0.7462 | 0.8638 | | 0.0902 | 15.6629 | 1394 | 0.7638 | 0.6957 | 0.7638 | 0.8740 | | 0.0902 | 15.6854 | 1396 | 0.7883 | 0.6914 | 0.7883 | 0.8879 | | 0.0902 | 15.7079 | 1398 | 0.7537 | 0.7073 | 0.7537 | 0.8682 | | 0.0902 | 15.7303 | 1400 | 0.6628 | 0.7561 | 0.6628 | 0.8141 | | 0.0902 | 15.7528 | 1402 | 0.5868 | 0.7901 | 0.5868 | 0.7660 | | 0.0902 | 15.7753 | 1404 | 0.5742 | 0.7853 | 0.5742 | 0.7577 | | 0.0902 | 15.7978 | 1406 | 0.5841 | 0.8 | 0.5841 | 0.7642 | | 0.0902 | 15.8202 | 1408 | 0.5942 | 0.7853 | 0.5942 | 0.7709 | | 0.0902 | 15.8427 | 1410 | 0.6140 | 0.7647 | 0.6140 | 0.7836 | | 0.0902 | 15.8652 | 1412 | 0.6513 | 0.7836 | 0.6513 | 0.8070 | | 0.0902 | 15.8876 | 1414 | 0.6937 | 0.7791 | 0.6937 | 0.8329 | | 0.0902 | 15.9101 | 1416 | 0.7189 | 0.7791 | 0.7189 | 0.8479 | | 0.0902 | 15.9326 | 1418 | 0.7041 | 0.7619 | 0.7041 | 0.8391 | | 0.0902 | 15.9551 | 1420 | 0.6912 | 0.7619 | 0.6912 | 0.8314 | | 0.0902 | 15.9775 | 1422 | 0.6785 | 0.7654 | 0.6785 | 0.8237 | | 0.0902 | 16.0 | 1424 | 0.6705 | 0.7898 | 0.6705 | 0.8188 | | 0.0902 | 16.0225 | 1426 | 0.6644 | 0.7975 | 0.6644 | 0.8151 | | 0.0902 | 16.0449 | 1428 | 0.6601 | 0.7654 | 0.6601 | 0.8125 | | 0.0902 | 16.0674 | 1430 | 0.6674 | 0.7470 | 0.6674 | 0.8169 | | 0.0902 | 16.0899 | 1432 | 0.6789 | 0.7317 | 0.6789 | 0.8240 | | 0.0902 | 16.1124 | 1434 | 0.7078 | 0.6957 | 0.7078 | 0.8413 | | 0.0902 | 16.1348 | 1436 | 0.7160 | 0.6957 | 0.7160 | 0.8462 | | 0.0902 | 16.1573 | 1438 | 0.7170 | 0.6957 | 0.7170 | 0.8468 | | 0.0902 | 16.1798 | 1440 | 0.6967 | 0.75 | 0.6967 | 0.8347 | | 0.0902 | 16.2022 | 1442 | 0.6968 | 0.7643 | 0.6968 | 0.8348 | | 0.0902 | 16.2247 | 1444 | 0.6936 | 0.7792 | 0.6936 | 0.8328 | | 0.0902 | 16.2472 | 1446 | 0.7068 | 0.7792 | 0.7068 | 0.8407 | | 0.0902 | 16.2697 | 1448 | 0.7058 | 0.7582 | 0.7058 | 0.8401 | | 0.0902 | 16.2921 | 1450 | 0.7087 | 0.7582 | 0.7087 | 0.8418 | | 0.0902 | 16.3146 | 1452 | 0.7318 | 0.7582 | 0.7318 | 0.8554 | | 0.0902 | 16.3371 | 1454 | 0.7466 | 0.7417 | 0.7466 | 0.8641 | | 0.0902 | 16.3596 | 1456 | 0.7406 | 0.7417 | 0.7406 | 0.8606 | | 0.0902 | 16.3820 | 1458 | 0.7358 | 0.75 | 0.7358 | 0.8578 | | 0.0902 | 16.4045 | 1460 | 0.7026 | 0.7285 | 0.7026 | 0.8382 | | 0.0902 | 16.4270 | 1462 | 0.6924 | 0.7162 | 0.6923 | 0.8321 | | 0.0902 | 16.4494 | 1464 | 0.7048 | 0.7285 | 0.7048 | 0.8395 | | 0.0902 | 16.4719 | 1466 | 0.7310 | 0.7285 | 0.7310 | 0.8550 | | 0.0902 | 16.4944 | 1468 | 0.7694 | 0.75 | 0.7694 | 0.8772 | | 0.0902 | 16.5169 | 1470 | 0.8124 | 0.7067 | 0.8124 | 0.9013 | | 0.0902 | 16.5393 | 1472 | 0.8399 | 0.6839 | 0.8399 | 0.9165 | | 0.0902 | 16.5618 | 1474 | 0.8193 | 0.725 | 0.8193 | 0.9051 | | 0.0902 | 16.5843 | 1476 | 0.7882 | 0.75 | 0.7882 | 0.8878 | | 0.0902 | 16.6067 | 1478 | 0.7818 | 0.75 | 0.7818 | 0.8842 | | 0.0902 | 16.6292 | 1480 | 0.7713 | 0.75 | 0.7713 | 0.8782 | | 0.0902 | 16.6517 | 1482 | 0.7593 | 0.75 | 0.7593 | 0.8714 | | 0.0902 | 16.6742 | 1484 | 0.7528 | 0.75 | 0.7528 | 0.8676 | | 0.0902 | 16.6966 | 1486 | 0.7568 | 0.7582 | 0.7568 | 0.8699 | | 0.0902 | 16.7191 | 1488 | 0.7323 | 0.7582 | 0.7323 | 0.8558 | | 0.0902 | 16.7416 | 1490 | 0.7138 | 0.7662 | 0.7138 | 0.8449 | | 0.0902 | 16.7640 | 1492 | 0.7014 | 0.7662 | 0.7014 | 0.8375 | | 0.0902 | 16.7865 | 1494 | 0.6971 | 0.7368 | 0.6971 | 0.8349 | | 0.0902 | 16.8090 | 1496 | 0.6984 | 0.7451 | 0.6984 | 0.8357 | | 0.0902 | 16.8315 | 1498 | 0.7058 | 0.7368 | 0.7058 | 0.8401 | | 0.054 | 16.8539 | 1500 | 0.7201 | 0.7368 | 0.7201 | 0.8486 | | 0.054 | 16.8764 | 1502 | 0.7380 | 0.7285 | 0.7380 | 0.8591 | | 0.054 | 16.8989 | 1504 | 0.7601 | 0.7285 | 0.7601 | 0.8718 | | 0.054 | 16.9213 | 1506 | 0.7823 | 0.7285 | 0.7823 | 0.8845 | | 0.054 | 16.9438 | 1508 | 0.8008 | 0.7285 | 0.8008 | 0.8949 | | 0.054 | 16.9663 | 1510 | 0.8235 | 0.6980 | 0.8235 | 0.9075 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

shopitalic/fragance-set-roomspray-rafael

shopitalic

2025-01-15T15:33:20Z

35

0

diffusers

[ "diffusers", "flux", "text-to-image", "lora", "fal", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]

text-to-image

2025-01-15T15:33:09Z

--- tags: - flux - text-to-image - lora - diffusers - fal base_model: black-forest-labs/FLUX.1-dev instance_prompt: license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md --- # fragance set roomspray rafael <Gallery /> ## Model description ## Trigger words You should use `` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/shopitalic/fragance-set-roomspray-rafael/tree/main) them in the Files & versions tab. ## Training at fal.ai Training was done using [fal.ai/models/fal-ai/flux-lora-fast-training](https://fal.ai/models/fal-ai/flux-lora-fast-training).

nhung03/26927434-adaa-4a69-bc76-b2ea296c9bfc

nhung03

2025-01-15T15:32:22Z

10

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:unsloth/OpenHermes-2.5-Mistral-7B", "base_model:adapter:unsloth/OpenHermes-2.5-Mistral-7B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T15:09:24Z

--- library_name: peft license: apache-2.0 base_model: unsloth/OpenHermes-2.5-Mistral-7B tags: - axolotl - generated_from_trainer model-index: - name: 26927434-adaa-4a69-bc76-b2ea296c9bfc results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/OpenHermes-2.5-Mistral-7B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 87f5261f601511ad_train_data.json ds_type: json format: custom path: /workspace/input_data/87f5261f601511ad_train_data.json type: field_input: HS field_instruction: prefix field_output: CN format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung03/26927434-adaa-4a69-bc76-b2ea296c9bfc hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/87f5261f601511ad_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: cefa18a5-e417-4b7f-b50e-7cfa90696def wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: cefa18a5-e417-4b7f-b50e-7cfa90696def warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 26927434-adaa-4a69-bc76-b2ea296c9bfc This model is a fine-tuned version of [unsloth/OpenHermes-2.5-Mistral-7B](https://huggingface.co/unsloth/OpenHermes-2.5-Mistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.8336 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 12.0856 | 0.1287 | 200 | 2.8336 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

ell-hol/FTR170-flux-dbth-lr

ell-hol

2025-01-15T15:32:08Z

8

0

diffusers

[ "diffusers", "text-to-image", "diffusers-training", "lora", "replicate", "flux", "flux-diffusers", "template:sd-lora", "license:other", "region:us" ]

text-to-image

2025-01-15T14:43:46Z

--- license: other library_name: diffusers tags: - text-to-image - diffusers-training - diffusers - lora - replicate - flux - flux-diffusers - template:sd-lora base_model: FLUX.1-dev instance_prompt: a photo of the FTR170 building widget: [] ---  # Flux DreamBooth LoRA - ell-hol/FTR170-flux-dbth-lr <Gallery /> ## Model description These are ell-hol/FTR170-flux-dbth-lr DreamBooth LoRA weights for FLUX.1-dev. The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [Flux diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_flux.md) on [Replicate](https://replicate.com/lucataco/diffusers-dreambooth-lora). Was LoRA for the text encoder enabled? False. ## Trigger words You should use `a photo of the FTR170 building` to trigger the image generation. ## Download model [Download the *.safetensors LoRA](ell-hol/FTR170-flux-dbth-lr/tree/main) in the Files & versions tab. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda') pipeline.load_lora_weights('ell-hol/FTR170-flux-dbth-lr', weight_name='pytorch_lora_weights.safetensors') image = pipeline('a photo of the FTR170 building').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) ## License Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md). ## Intended uses & limitations #### How to use ```python # TODO: add an example code snippet for running this diffusion pipeline ``` #### Limitations and bias [TODO: provide examples of latent issues and potential remediations] ## Training details [TODO: describe the data used to train the model]

AntonioTH/Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2

AntonioTH

2025-01-15T15:29:57Z

8

0

transformers

[ "transformers", "tensorboard", "safetensors", "layoutlmv2", "document-question-answering", "generated_from_trainer", "base_model:microsoft/layoutxlm-base", "base_model:finetune:microsoft/layoutxlm-base", "license:cc-by-nc-sa-4.0", "endpoints_compatible", "region:us" ]

document-question-answering

2025-01-15T14:35:02Z

--- library_name: transformers license: cc-by-nc-sa-4.0 base_model: microsoft/layoutxlm-base tags: - generated_from_trainer model-index: - name: Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2 results: [] ---  # Layout-finetuned-fr-model-50instances20-10epochs-5e-05lr-V2 This model is a fine-tuned version of [microsoft/layoutxlm-base](https://huggingface.co/microsoft/layoutxlm-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0001 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: reduce_lr_on_plateau - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.2231 | 0.7692 | 10 | 0.7135 | | 0.1961 | 1.5385 | 20 | 0.0019 | | 0.002 | 2.3077 | 30 | 0.0004 | | 0.0005 | 3.0769 | 40 | 0.0002 | | 0.0003 | 3.8462 | 50 | 0.0001 | | 0.0003 | 4.6154 | 60 | 0.0001 | | 0.0002 | 5.3846 | 70 | 0.0001 | | 0.0002 | 6.1538 | 80 | 0.0001 | | 0.0002 | 6.9231 | 90 | 0.0001 | | 0.0002 | 7.6923 | 100 | 0.0001 | | 0.0002 | 8.4615 | 110 | 0.0001 | | 0.0001 | 9.2308 | 120 | 0.0001 | | 0.0001 | 10.0 | 130 | 0.0001 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.4.1.post100 - Datasets 3.2.0 - Tokenizers 0.21.0

exala/db_aca2_7.2

exala

2025-01-15T15:28:55Z

6

0

transformers

[ "transformers", "safetensors", "distilbert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T15:28:43Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

MayBashendy/ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization

MayBashendy

2025-01-15T15:28:24Z

7

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T15:10:59Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization results: [] ---  # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7167 - Qwk: 0.3022 - Mse: 1.7167 - Rmse: 1.3102 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0303 | 2 | 6.9944 | 0.0057 | 6.9944 | 2.6447 | | No log | 0.0606 | 4 | 4.5153 | 0.0407 | 4.5153 | 2.1249 | | No log | 0.0909 | 6 | 3.7162 | -0.0635 | 3.7162 | 1.9278 | | No log | 0.1212 | 8 | 3.7143 | -0.1047 | 3.7143 | 1.9273 | | No log | 0.1515 | 10 | 3.2285 | 0.0118 | 3.2285 | 1.7968 | | No log | 0.1818 | 12 | 2.4530 | 0.0930 | 2.4530 | 1.5662 | | No log | 0.2121 | 14 | 2.2921 | 0.1538 | 2.2921 | 1.5140 | | No log | 0.2424 | 16 | 2.2405 | 0.2628 | 2.2405 | 1.4968 | | No log | 0.2727 | 18 | 2.3051 | 0.1497 | 2.3051 | 1.5183 | | No log | 0.3030 | 20 | 2.3160 | 0.1208 | 2.3160 | 1.5219 | | No log | 0.3333 | 22 | 2.3371 | 0.1208 | 2.3371 | 1.5288 | | No log | 0.3636 | 24 | 2.3923 | 0.0933 | 2.3923 | 1.5467 | | No log | 0.3939 | 26 | 2.3991 | 0.0933 | 2.3991 | 1.5489 | | No log | 0.4242 | 28 | 2.4278 | 0.1224 | 2.4278 | 1.5581 | | No log | 0.4545 | 30 | 2.2243 | 0.2464 | 2.2243 | 1.4914 | | No log | 0.4848 | 32 | 1.9640 | 0.2080 | 1.9640 | 1.4014 | | No log | 0.5152 | 34 | 1.7294 | 0.0708 | 1.7294 | 1.3151 | | No log | 0.5455 | 36 | 1.6212 | 0.1714 | 1.6212 | 1.2732 | | No log | 0.5758 | 38 | 1.5596 | 0.1887 | 1.5596 | 1.2488 | | No log | 0.6061 | 40 | 1.5678 | 0.2385 | 1.5678 | 1.2521 | | No log | 0.6364 | 42 | 1.6246 | 0.2385 | 1.6246 | 1.2746 | | No log | 0.6667 | 44 | 1.7130 | 0.2807 | 1.7130 | 1.3088 | | No log | 0.6970 | 46 | 1.8307 | 0.2185 | 1.8307 | 1.3530 | | No log | 0.7273 | 48 | 1.8662 | 0.1008 | 1.8662 | 1.3661 | | No log | 0.7576 | 50 | 2.2266 | 0.0167 | 2.2266 | 1.4922 | | No log | 0.7879 | 52 | 2.3084 | -0.0164 | 2.3084 | 1.5194 | | No log | 0.8182 | 54 | 2.4142 | -0.0813 | 2.4142 | 1.5538 | | No log | 0.8485 | 56 | 1.8711 | 0.0536 | 1.8711 | 1.3679 | | No log | 0.8788 | 58 | 1.4019 | 0.2593 | 1.4019 | 1.1840 | | No log | 0.9091 | 60 | 1.3756 | 0.3361 | 1.3756 | 1.1729 | | No log | 0.9394 | 62 | 1.3331 | 0.3248 | 1.3331 | 1.1546 | | No log | 0.9697 | 64 | 1.4205 | 0.4071 | 1.4205 | 1.1918 | | No log | 1.0 | 66 | 1.7671 | 0.2679 | 1.7671 | 1.3293 | | No log | 1.0303 | 68 | 1.8373 | 0.2364 | 1.8373 | 1.3555 | | No log | 1.0606 | 70 | 1.5523 | 0.3393 | 1.5523 | 1.2459 | | No log | 1.0909 | 72 | 1.3863 | 0.3243 | 1.3863 | 1.1774 | | No log | 1.1212 | 74 | 1.3750 | 0.3540 | 1.3750 | 1.1726 | | No log | 1.1515 | 76 | 1.3629 | 0.3860 | 1.3629 | 1.1674 | | No log | 1.1818 | 78 | 1.4439 | 0.3393 | 1.4439 | 1.2016 | | No log | 1.2121 | 80 | 1.5159 | 0.3604 | 1.5159 | 1.2312 | | No log | 1.2424 | 82 | 1.7802 | 0.2321 | 1.7802 | 1.3342 | | No log | 1.2727 | 84 | 1.8063 | 0.2456 | 1.8063 | 1.3440 | | No log | 1.3030 | 86 | 1.5623 | 0.3793 | 1.5623 | 1.2499 | | No log | 1.3333 | 88 | 1.4173 | 0.3478 | 1.4173 | 1.1905 | | No log | 1.3636 | 90 | 1.2854 | 0.3684 | 1.2854 | 1.1338 | | No log | 1.3939 | 92 | 1.3589 | 0.2936 | 1.3589 | 1.1657 | | No log | 1.4242 | 94 | 1.3796 | 0.3393 | 1.3796 | 1.1745 | | No log | 1.4545 | 96 | 1.4248 | 0.3966 | 1.4248 | 1.1937 | | No log | 1.4848 | 98 | 1.4145 | 0.4035 | 1.4145 | 1.1893 | | No log | 1.5152 | 100 | 1.5414 | 0.4068 | 1.5414 | 1.2415 | | No log | 1.5455 | 102 | 1.6869 | 0.3051 | 1.6869 | 1.2988 | | No log | 1.5758 | 104 | 1.6587 | 0.3115 | 1.6587 | 1.2879 | | No log | 1.6061 | 106 | 1.7339 | 0.2810 | 1.7339 | 1.3168 | | No log | 1.6364 | 108 | 1.6304 | 0.3415 | 1.6304 | 1.2769 | | No log | 1.6667 | 110 | 1.7599 | 0.2835 | 1.7599 | 1.3266 | | No log | 1.6970 | 112 | 1.8480 | 0.2258 | 1.8480 | 1.3594 | | No log | 1.7273 | 114 | 1.5999 | 0.3333 | 1.5999 | 1.2649 | | No log | 1.7576 | 116 | 1.4627 | 0.5079 | 1.4627 | 1.2094 | | No log | 1.7879 | 118 | 1.4149 | 0.4 | 1.4149 | 1.1895 | | No log | 1.8182 | 120 | 1.5311 | 0.5077 | 1.5311 | 1.2374 | | No log | 1.8485 | 122 | 1.8821 | 0.2609 | 1.8821 | 1.3719 | | No log | 1.8788 | 124 | 1.9892 | 0.1630 | 1.9892 | 1.4104 | | No log | 1.9091 | 126 | 1.8187 | 0.3088 | 1.8187 | 1.3486 | | No log | 1.9394 | 128 | 1.4761 | 0.4715 | 1.4761 | 1.2149 | | No log | 1.9697 | 130 | 1.3188 | 0.4068 | 1.3188 | 1.1484 | | No log | 2.0 | 132 | 1.3135 | 0.5082 | 1.3135 | 1.1461 | | No log | 2.0303 | 134 | 1.4589 | 0.4733 | 1.4589 | 1.2079 | | No log | 2.0606 | 136 | 1.6805 | 0.3284 | 1.6805 | 1.2963 | | No log | 2.0909 | 138 | 2.0007 | 0.0916 | 2.0007 | 1.4144 | | No log | 2.1212 | 140 | 1.9180 | 0.1493 | 1.9180 | 1.3849 | | No log | 2.1515 | 142 | 1.5706 | 0.3556 | 1.5706 | 1.2532 | | No log | 2.1818 | 144 | 1.2024 | 0.5873 | 1.2024 | 1.0965 | | No log | 2.2121 | 146 | 1.0618 | 0.4370 | 1.0618 | 1.0305 | | No log | 2.2424 | 148 | 1.0357 | 0.5484 | 1.0357 | 1.0177 | | No log | 2.2727 | 150 | 1.1690 | 0.5512 | 1.1690 | 1.0812 | | No log | 2.3030 | 152 | 1.3789 | 0.4496 | 1.3789 | 1.1743 | | No log | 2.3333 | 154 | 1.2727 | 0.5197 | 1.2727 | 1.1282 | | No log | 2.3636 | 156 | 1.1478 | 0.5528 | 1.1478 | 1.0713 | | No log | 2.3939 | 158 | 1.1685 | 0.5323 | 1.1685 | 1.0810 | | No log | 2.4242 | 160 | 1.2396 | 0.5161 | 1.2396 | 1.1134 | | No log | 2.4545 | 162 | 1.3491 | 0.5039 | 1.3491 | 1.1615 | | No log | 2.4848 | 164 | 1.3579 | 0.5156 | 1.3579 | 1.1653 | | No log | 2.5152 | 166 | 1.4688 | 0.3721 | 1.4688 | 1.2119 | | No log | 2.5455 | 168 | 1.4561 | 0.4127 | 1.4561 | 1.2067 | | No log | 2.5758 | 170 | 1.4176 | 0.5 | 1.4176 | 1.1906 | | No log | 2.6061 | 172 | 1.4266 | 0.4754 | 1.4266 | 1.1944 | | No log | 2.6364 | 174 | 1.6812 | 0.2835 | 1.6812 | 1.2966 | | No log | 2.6667 | 176 | 1.9125 | 0.2114 | 1.9125 | 1.3829 | | No log | 2.6970 | 178 | 2.0021 | 0.1667 | 2.0021 | 1.4150 | | No log | 2.7273 | 180 | 1.8599 | 0.2131 | 1.8599 | 1.3638 | | No log | 2.7576 | 182 | 1.5087 | 0.4496 | 1.5087 | 1.2283 | | No log | 2.7879 | 184 | 1.3008 | 0.5385 | 1.3008 | 1.1405 | | No log | 2.8182 | 186 | 1.2706 | 0.5271 | 1.2706 | 1.1272 | | No log | 2.8485 | 188 | 1.3617 | 0.5116 | 1.3617 | 1.1669 | | No log | 2.8788 | 190 | 1.3683 | 0.4844 | 1.3683 | 1.1697 | | No log | 2.9091 | 192 | 1.4496 | 0.4361 | 1.4496 | 1.2040 | | No log | 2.9394 | 194 | 1.4260 | 0.4462 | 1.4260 | 1.1942 | | No log | 2.9697 | 196 | 1.3760 | 0.5197 | 1.3760 | 1.1730 | | No log | 3.0 | 198 | 1.3927 | 0.5156 | 1.3927 | 1.1801 | | No log | 3.0303 | 200 | 1.4339 | 0.4844 | 1.4339 | 1.1974 | | No log | 3.0606 | 202 | 1.4469 | 0.4961 | 1.4469 | 1.2029 | | No log | 3.0909 | 204 | 1.4224 | 0.5344 | 1.4224 | 1.1926 | | No log | 3.1212 | 206 | 1.4897 | 0.4179 | 1.4897 | 1.2205 | | No log | 3.1515 | 208 | 1.5812 | 0.3485 | 1.5812 | 1.2575 | | No log | 3.1818 | 210 | 1.6296 | 0.3256 | 1.6296 | 1.2766 | | No log | 3.2121 | 212 | 1.4779 | 0.4252 | 1.4779 | 1.2157 | | No log | 3.2424 | 214 | 1.3430 | 0.496 | 1.3430 | 1.1589 | | No log | 3.2727 | 216 | 1.2147 | 0.528 | 1.2147 | 1.1021 | | No log | 3.3030 | 218 | 1.3675 | 0.4844 | 1.3675 | 1.1694 | | No log | 3.3333 | 220 | 1.5121 | 0.4 | 1.5121 | 1.2297 | | No log | 3.3636 | 222 | 1.3824 | 0.4878 | 1.3824 | 1.1757 | | No log | 3.3939 | 224 | 1.1374 | 0.4957 | 1.1374 | 1.0665 | | No log | 3.4242 | 226 | 1.1127 | 0.4696 | 1.1127 | 1.0548 | | No log | 3.4545 | 228 | 1.1710 | 0.4522 | 1.1710 | 1.0821 | | No log | 3.4848 | 230 | 1.3114 | 0.4522 | 1.3114 | 1.1452 | | No log | 3.5152 | 232 | 1.3567 | 0.4667 | 1.3567 | 1.1648 | | No log | 3.5455 | 234 | 1.3247 | 0.4921 | 1.3247 | 1.1510 | | No log | 3.5758 | 236 | 1.2507 | 0.5312 | 1.2507 | 1.1183 | | No log | 3.6061 | 238 | 1.1976 | 0.5714 | 1.1976 | 1.0944 | | No log | 3.6364 | 240 | 1.1839 | 0.5736 | 1.1839 | 1.0881 | | No log | 3.6667 | 242 | 1.3254 | 0.5255 | 1.3254 | 1.1513 | | No log | 3.6970 | 244 | 1.3419 | 0.4889 | 1.3419 | 1.1584 | | No log | 3.7273 | 246 | 1.4214 | 0.4148 | 1.4214 | 1.1922 | | No log | 3.7576 | 248 | 1.5377 | 0.3704 | 1.5377 | 1.2400 | | No log | 3.7879 | 250 | 1.5166 | 0.3359 | 1.5166 | 1.2315 | | No log | 3.8182 | 252 | 1.5304 | 0.368 | 1.5304 | 1.2371 | | No log | 3.8485 | 254 | 1.5101 | 0.4034 | 1.5101 | 1.2289 | | No log | 3.8788 | 256 | 1.4454 | 0.4202 | 1.4454 | 1.2022 | | No log | 3.9091 | 258 | 1.5006 | 0.4034 | 1.5006 | 1.2250 | | No log | 3.9394 | 260 | 1.6493 | 0.2581 | 1.6493 | 1.2843 | | No log | 3.9697 | 262 | 1.8253 | 0.1760 | 1.8253 | 1.3510 | | No log | 4.0 | 264 | 1.8408 | 0.2047 | 1.8408 | 1.3568 | | No log | 4.0303 | 266 | 1.7825 | 0.2308 | 1.7825 | 1.3351 | | No log | 4.0606 | 268 | 1.6237 | 0.3008 | 1.6237 | 1.2742 | | No log | 4.0909 | 270 | 1.5478 | 0.4211 | 1.5478 | 1.2441 | | No log | 4.1212 | 272 | 1.4616 | 0.4242 | 1.4616 | 1.2089 | | No log | 4.1515 | 274 | 1.4935 | 0.4361 | 1.4935 | 1.2221 | | No log | 4.1818 | 276 | 1.6308 | 0.3664 | 1.6308 | 1.2770 | | No log | 4.2121 | 278 | 1.7634 | 0.2462 | 1.7634 | 1.3279 | | No log | 4.2424 | 280 | 1.8587 | 0.2406 | 1.8587 | 1.3633 | | No log | 4.2727 | 282 | 1.8221 | 0.2836 | 1.8221 | 1.3499 | | No log | 4.3030 | 284 | 1.5922 | 0.3158 | 1.5922 | 1.2618 | | No log | 4.3333 | 286 | 1.3365 | 0.5039 | 1.3365 | 1.1561 | | No log | 4.3636 | 288 | 1.3022 | 0.5039 | 1.3022 | 1.1411 | | No log | 4.3939 | 290 | 1.4342 | 0.4444 | 1.4342 | 1.1976 | | No log | 4.4242 | 292 | 1.6800 | 0.3212 | 1.6800 | 1.2961 | | No log | 4.4545 | 294 | 1.8339 | 0.2482 | 1.8339 | 1.3542 | | No log | 4.4848 | 296 | 2.0354 | 0.1176 | 2.0354 | 1.4267 | | No log | 4.5152 | 298 | 2.0186 | 0.0746 | 2.0186 | 1.4208 | | No log | 4.5455 | 300 | 1.7992 | 0.2556 | 1.7992 | 1.3413 | | No log | 4.5758 | 302 | 1.5955 | 0.3411 | 1.5955 | 1.2631 | | No log | 4.6061 | 304 | 1.4671 | 0.3810 | 1.4671 | 1.2113 | | No log | 4.6364 | 306 | 1.3656 | 0.5041 | 1.3656 | 1.1686 | | No log | 4.6667 | 308 | 1.3630 | 0.5397 | 1.3630 | 1.1675 | | No log | 4.6970 | 310 | 1.4873 | 0.4296 | 1.4873 | 1.2196 | | No log | 4.7273 | 312 | 1.7610 | 0.2446 | 1.7610 | 1.3270 | | No log | 4.7576 | 314 | 2.0182 | 0.1460 | 2.0182 | 1.4207 | | No log | 4.7879 | 316 | 2.1348 | 0.1714 | 2.1348 | 1.4611 | | No log | 4.8182 | 318 | 2.1244 | 0.1831 | 2.1244 | 1.4575 | | No log | 4.8485 | 320 | 1.9065 | 0.2857 | 1.9065 | 1.3808 | | No log | 4.8788 | 322 | 1.5997 | 0.3597 | 1.5997 | 1.2648 | | No log | 4.9091 | 324 | 1.4691 | 0.4925 | 1.4691 | 1.2121 | | No log | 4.9394 | 326 | 1.5112 | 0.4328 | 1.5112 | 1.2293 | | No log | 4.9697 | 328 | 1.6980 | 0.3333 | 1.6980 | 1.3031 | | No log | 5.0 | 330 | 1.9604 | 0.2286 | 1.9604 | 1.4001 | | No log | 5.0303 | 332 | 1.9863 | 0.1986 | 1.9863 | 1.4094 | | No log | 5.0606 | 334 | 1.9663 | 0.1986 | 1.9663 | 1.4022 | | No log | 5.0909 | 336 | 1.9781 | 0.1986 | 1.9781 | 1.4064 | | No log | 5.1212 | 338 | 2.0225 | 0.2000 | 2.0225 | 1.4221 | | No log | 5.1515 | 340 | 2.0287 | 0.2000 | 2.0287 | 1.4243 | | No log | 5.1818 | 342 | 2.0276 | 0.2000 | 2.0276 | 1.4239 | | No log | 5.2121 | 344 | 1.9562 | 0.1844 | 1.9562 | 1.3986 | | No log | 5.2424 | 346 | 1.7553 | 0.3333 | 1.7553 | 1.3249 | | No log | 5.2727 | 348 | 1.6211 | 0.4058 | 1.6211 | 1.2732 | | No log | 5.3030 | 350 | 1.6287 | 0.3796 | 1.6287 | 1.2762 | | No log | 5.3333 | 352 | 1.5323 | 0.3676 | 1.5323 | 1.2378 | | No log | 5.3636 | 354 | 1.4494 | 0.4328 | 1.4494 | 1.2039 | | No log | 5.3939 | 356 | 1.4895 | 0.4148 | 1.4895 | 1.2204 | | No log | 5.4242 | 358 | 1.7277 | 0.3143 | 1.7277 | 1.3144 | | No log | 5.4545 | 360 | 2.0436 | 0.2098 | 2.0436 | 1.4295 | | No log | 5.4848 | 362 | 2.0502 | 0.2222 | 2.0502 | 1.4319 | | No log | 5.5152 | 364 | 1.9849 | 0.2778 | 1.9849 | 1.4089 | | No log | 5.5455 | 366 | 1.7435 | 0.3497 | 1.7435 | 1.3204 | | No log | 5.5758 | 368 | 1.5414 | 0.3597 | 1.5414 | 1.2415 | | No log | 5.6061 | 370 | 1.4444 | 0.4328 | 1.4444 | 1.2018 | | No log | 5.6364 | 372 | 1.5102 | 0.4203 | 1.5102 | 1.2289 | | No log | 5.6667 | 374 | 1.7301 | 0.2878 | 1.7301 | 1.3153 | | No log | 5.6970 | 376 | 1.8386 | 0.2754 | 1.8386 | 1.3559 | | No log | 5.7273 | 378 | 1.7688 | 0.2590 | 1.7688 | 1.3299 | | No log | 5.7576 | 380 | 1.6764 | 0.3333 | 1.6764 | 1.2948 | | No log | 5.7879 | 382 | 1.6558 | 0.3212 | 1.6558 | 1.2868 | | No log | 5.8182 | 384 | 1.6592 | 0.3212 | 1.6592 | 1.2881 | | No log | 5.8485 | 386 | 1.8444 | 0.3022 | 1.8444 | 1.3581 | | No log | 5.8788 | 388 | 2.0224 | 0.2695 | 2.0224 | 1.4221 | | No log | 5.9091 | 390 | 1.9895 | 0.2695 | 1.9895 | 1.4105 | | No log | 5.9394 | 392 | 1.7949 | 0.3022 | 1.7949 | 1.3397 | | No log | 5.9697 | 394 | 1.5034 | 0.4029 | 1.5034 | 1.2261 | | No log | 6.0 | 396 | 1.3198 | 0.4672 | 1.3198 | 1.1488 | | No log | 6.0303 | 398 | 1.2589 | 0.4925 | 1.2589 | 1.1220 | | No log | 6.0606 | 400 | 1.2109 | 0.5231 | 1.2109 | 1.1004 | | No log | 6.0909 | 402 | 1.2751 | 0.4848 | 1.2751 | 1.1292 | | No log | 6.1212 | 404 | 1.4672 | 0.4088 | 1.4672 | 1.2113 | | No log | 6.1515 | 406 | 1.7512 | 0.3066 | 1.7512 | 1.3233 | | No log | 6.1818 | 408 | 1.8199 | 0.2899 | 1.8199 | 1.3490 | | No log | 6.2121 | 410 | 1.8737 | 0.2286 | 1.8737 | 1.3688 | | No log | 6.2424 | 412 | 1.7951 | 0.3022 | 1.7951 | 1.3398 | | No log | 6.2727 | 414 | 1.6056 | 0.3913 | 1.6056 | 1.2671 | | No log | 6.3030 | 416 | 1.5029 | 0.4234 | 1.5029 | 1.2259 | | No log | 6.3333 | 418 | 1.4873 | 0.4526 | 1.4873 | 1.2196 | | No log | 6.3636 | 420 | 1.5242 | 0.4444 | 1.5242 | 1.2346 | | No log | 6.3939 | 422 | 1.5626 | 0.4627 | 1.5626 | 1.2501 | | No log | 6.4242 | 424 | 1.5605 | 0.4122 | 1.5605 | 1.2492 | | No log | 6.4545 | 426 | 1.5478 | 0.4122 | 1.5478 | 1.2441 | | No log | 6.4848 | 428 | 1.5280 | 0.4122 | 1.5280 | 1.2361 | | No log | 6.5152 | 430 | 1.5320 | 0.4122 | 1.5320 | 1.2378 | | No log | 6.5455 | 432 | 1.5495 | 0.4122 | 1.5495 | 1.2448 | | No log | 6.5758 | 434 | 1.6572 | 0.3788 | 1.6571 | 1.2873 | | No log | 6.6061 | 436 | 1.7076 | 0.3382 | 1.7076 | 1.3068 | | No log | 6.6364 | 438 | 1.6395 | 0.4148 | 1.6395 | 1.2804 | | No log | 6.6667 | 440 | 1.5910 | 0.4148 | 1.5910 | 1.2614 | | No log | 6.6970 | 442 | 1.5514 | 0.4148 | 1.5514 | 1.2456 | | No log | 6.7273 | 444 | 1.5695 | 0.3971 | 1.5695 | 1.2528 | | No log | 6.7576 | 446 | 1.6529 | 0.3478 | 1.6529 | 1.2856 | | No log | 6.7879 | 448 | 1.6667 | 0.3478 | 1.6667 | 1.2910 | | No log | 6.8182 | 450 | 1.5943 | 0.3529 | 1.5943 | 1.2626 | | No log | 6.8485 | 452 | 1.6232 | 0.3358 | 1.6232 | 1.2741 | | No log | 6.8788 | 454 | 1.7026 | 0.3143 | 1.7026 | 1.3048 | | No log | 6.9091 | 456 | 1.8190 | 0.2553 | 1.8190 | 1.3487 | | No log | 6.9394 | 458 | 1.8363 | 0.2553 | 1.8363 | 1.3551 | | No log | 6.9697 | 460 | 1.6069 | 0.3478 | 1.6069 | 1.2676 | | No log | 7.0 | 462 | 1.3671 | 0.4662 | 1.3671 | 1.1692 | | No log | 7.0303 | 464 | 1.2786 | 0.5736 | 1.2786 | 1.1308 | | No log | 7.0606 | 466 | 1.3161 | 0.5469 | 1.3161 | 1.1472 | | No log | 7.0909 | 468 | 1.4248 | 0.4427 | 1.4248 | 1.1937 | | No log | 7.1212 | 470 | 1.6490 | 0.3212 | 1.6490 | 1.2841 | | No log | 7.1515 | 472 | 1.8276 | 0.2553 | 1.8276 | 1.3519 | | No log | 7.1818 | 474 | 1.8325 | 0.2014 | 1.8325 | 1.3537 | | No log | 7.2121 | 476 | 1.7131 | 0.2687 | 1.7131 | 1.3089 | | No log | 7.2424 | 478 | 1.6029 | 0.3840 | 1.6029 | 1.2660 | | No log | 7.2727 | 480 | 1.6119 | 0.35 | 1.6119 | 1.2696 | | No log | 7.3030 | 482 | 1.6414 | 0.3802 | 1.6414 | 1.2812 | | No log | 7.3333 | 484 | 1.7304 | 0.3226 | 1.7304 | 1.3154 | | No log | 7.3636 | 486 | 1.7827 | 0.2370 | 1.7827 | 1.3352 | | No log | 7.3939 | 488 | 1.6803 | 0.3556 | 1.6803 | 1.2963 | | No log | 7.4242 | 490 | 1.5603 | 0.3609 | 1.5603 | 1.2491 | | No log | 7.4545 | 492 | 1.4283 | 0.4531 | 1.4283 | 1.1951 | | No log | 7.4848 | 494 | 1.3342 | 0.4160 | 1.3342 | 1.1551 | | No log | 7.5152 | 496 | 1.3632 | 0.4409 | 1.3632 | 1.1675 | | No log | 7.5455 | 498 | 1.5263 | 0.4091 | 1.5263 | 1.2354 | | 0.4132 | 7.5758 | 500 | 1.7767 | 0.3066 | 1.7767 | 1.3329 | | 0.4132 | 7.6061 | 502 | 1.8679 | 0.2899 | 1.8679 | 1.3667 | | 0.4132 | 7.6364 | 504 | 1.7845 | 0.2899 | 1.7845 | 1.3359 | | 0.4132 | 7.6667 | 506 | 1.6449 | 0.3759 | 1.6449 | 1.2825 | | 0.4132 | 7.6970 | 508 | 1.5565 | 0.4091 | 1.5565 | 1.2476 | | 0.4132 | 7.7273 | 510 | 1.4505 | 0.4462 | 1.4505 | 1.2044 | | 0.4132 | 7.7576 | 512 | 1.4850 | 0.4462 | 1.4850 | 1.2186 | | 0.4132 | 7.7879 | 514 | 1.6438 | 0.3529 | 1.6438 | 1.2821 | | 0.4132 | 7.8182 | 516 | 1.8453 | 0.2734 | 1.8453 | 1.3584 | | 0.4132 | 7.8485 | 518 | 1.9250 | 0.2128 | 1.9250 | 1.3874 | | 0.4132 | 7.8788 | 520 | 1.9368 | 0.2254 | 1.9368 | 1.3917 | | 0.4132 | 7.9091 | 522 | 1.8844 | 0.2571 | 1.8844 | 1.3727 | | 0.4132 | 7.9394 | 524 | 1.7167 | 0.3022 | 1.7167 | 1.3102 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

pvduy/Qwen2.7-7B-Instruct-QwQ

pvduy

2025-01-15T15:27:50Z

1,626

0

transformers

[ "transformers", "safetensors", "qwen2", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-15T15:22:24Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

lesso07/5f8a3450-51fd-403d-9d1a-57a04bedf50c

lesso07

2025-01-15T15:22:59Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:Qwen/Qwen2-0.5B", "base_model:adapter:Qwen/Qwen2-0.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T10:31:19Z

--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2-0.5B tags: - axolotl - generated_from_trainer model-index: - name: 5f8a3450-51fd-403d-9d1a-57a04bedf50c results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: Qwen/Qwen2-0.5B bf16: true chat_template: llama3 datasets: - data_files: - a54dfbc141335bb5_train_data.json ds_type: json format: custom path: /workspace/input_data/a54dfbc141335bb5_train_data.json type: field_instruction: instruction field_output: output format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso07/5f8a3450-51fd-403d-9d1a-57a04bedf50c hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/a54dfbc141335bb5_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: e302ed25-6563-4139-a251-885ddd901a8d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: e302ed25-6563-4139-a251-885ddd901a8d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 5f8a3450-51fd-403d-9d1a-57a04bedf50c This model is a fine-tuned version of [Qwen/Qwen2-0.5B](https://huggingface.co/Qwen/Qwen2-0.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.4338 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 1.7504 | 0.0000 | 1 | 2.8080 | | 2.5122 | 0.0001 | 5 | 2.7556 | | 2.3674 | 0.0002 | 10 | 2.5045 | | 2.6639 | 0.0002 | 15 | 2.4447 | | 1.8371 | 0.0003 | 20 | 2.4358 | | 2.2204 | 0.0004 | 25 | 2.4338 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

chauhoang/5d7d72f6-1494-4bc7-888a-74bf6c08aad0

chauhoang

2025-01-15T15:21:55Z

11

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "region:us" ]

null

2025-01-15T15:16:00Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 5d7d72f6-1494-4bc7-888a-74bf6c08aad0 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 5 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: chauhoang/5d7d72f6-1494-4bc7-888a-74bf6c08aad0 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 5 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 5d7d72f6-1494-4bc7-888a-74bf6c08aad0 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0008 | 1 | nan | | 0.0 | 0.0082 | 10 | nan | | 0.0 | 0.0163 | 20 | nan | | 0.0 | 0.0245 | 30 | nan | | 0.0 | 0.0327 | 40 | nan | | 0.0 | 0.0408 | 50 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thakkkkkk/ac914070-92e4-4882-aab1-2dae1cc8f023

thakkkkkk

2025-01-15T15:17:26Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:elyza/Llama-3-ELYZA-JP-8B", "base_model:adapter:elyza/Llama-3-ELYZA-JP-8B", "license:llama3", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:23:23Z

--- library_name: peft license: llama3 base_model: elyza/Llama-3-ELYZA-JP-8B tags: - axolotl - generated_from_trainer model-index: - name: ac914070-92e4-4882-aab1-2dae1cc8f023 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: elyza/Llama-3-ELYZA-JP-8B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - fda69805a6ba006d_train_data.json ds_type: json format: custom path: /workspace/input_data/fda69805a6ba006d_train_data.json type: field_instruction: prompt field_output: solution format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thakkkkkk/ac914070-92e4-4882-aab1-2dae1cc8f023 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 4 mlflow_experiment_name: /tmp/fda69805a6ba006d_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 special_tokens: pad_token: <|eot_id|> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: f2e1c4d6-26a9-4626-844d-fb1f5d0379e3 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: f2e1c4d6-26a9-4626-844d-fb1f5d0379e3 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # ac914070-92e4-4882-aab1-2dae1cc8f023 This model is a fine-tuned version of [elyza/Llama-3-ELYZA-JP-8B](https://huggingface.co/elyza/Llama-3-ELYZA-JP-8B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.7168 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.7364 | 0.0187 | 200 | 0.7168 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

hollmann/andre-dev

hollmann

2025-01-15T15:15:11Z

12

0

diffusers

[ "diffusers", "flux", "text-to-image", "lora", "fal", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]

text-to-image

2025-01-15T15:15:04Z

--- tags: - flux - text-to-image - lora - diffusers - fal base_model: black-forest-labs/FLUX.1-dev instance_prompt: foo license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md --- # andre dev <Gallery /> ## Model description ## Trigger words You should use `foo` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/hollmann/andre-dev/tree/main) them in the Files & versions tab. ## Training at fal.ai Training was done using [fal.ai/models/fal-ai/flux-lora-fast-training](https://fal.ai/models/fal-ai/flux-lora-fast-training).

tarabukinivan/b421da53-ff70-4e6d-b92e-a790e19e8999

tarabukinivan

2025-01-15T15:13:31Z

6

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]

null

2025-01-15T14:14:08Z

--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: b421da53-ff70-4e6d-b92e-a790e19e8999 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: tarabukinivan/b421da53-ff70-4e6d-b92e-a790e19e8999 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 50 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # b421da53-ff70-4e6d-b92e-a790e19e8999 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0006 | 13 | nan | | 0.0 | 0.0012 | 26 | nan | | 0.0 | 0.0018 | 39 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

lesso05/cb24c657-616f-497d-82aa-f52913f3c89f

lesso05

2025-01-15T15:13:11Z

9

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0", "base_model:adapter:WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0", "license:llama3", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T13:24:13Z

--- library_name: peft license: llama3 base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 tags: - axolotl - generated_from_trainer model-index: - name: cb24c657-616f-497d-82aa-f52913f3c89f results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 bf16: true chat_template: llama3 datasets: - data_files: - 3c33873967a336a3_train_data.json ds_type: json format: custom path: /workspace/input_data/3c33873967a336a3_train_data.json type: field_input: context field_instruction: question field_output: answers format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: 2 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null flash_attention: false fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: lesso05/cb24c657-616f-497d-82aa-f52913f3c89f hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 25 micro_batch_size: 2 mlflow_experiment_name: /tmp/3c33873967a336a3_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: fd5b49f1-57e4-4c15-bca0-7eed58aadb30 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: fd5b49f1-57e4-4c15-bca0-7eed58aadb30 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # cb24c657-616f-497d-82aa-f52913f3c89f This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4272 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 3.0196 | 0.0001 | 1 | 3.4767 | | 2.5522 | 0.0003 | 5 | 2.9957 | | 1.1031 | 0.0006 | 10 | 1.1841 | | 0.323 | 0.0009 | 15 | 0.3350 | | 0.3152 | 0.0012 | 20 | 0.4184 | | 0.359 | 0.0015 | 25 | 0.4272 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

fedovtt/b8cd5a6b-26c8-44b2-bfd1-a975c77263d2

fedovtt

2025-01-15T15:10:48Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]

null

2025-01-15T14:12:47Z

--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: fedovtt/b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # b8cd5a6b-26c8-44b2-bfd1-a975c77263d2 This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0005 | 10 | nan | | 0.0 | 0.0007 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

Nekuromento/watt-tool-8B-Q6_K-GGUF

Nekuromento

2025-01-15T15:10:37Z

23

0

null

[ "gguf", "function-calling", "tool-use", "llama", "bfcl", "llama-cpp", "gguf-my-repo", "en", "base_model:watt-ai/watt-tool-8B", "base_model:quantized:watt-ai/watt-tool-8B", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

null

2025-01-15T15:10:06Z

--- license: apache-2.0 language: - en base_model: watt-ai/watt-tool-8B tags: - function-calling - tool-use - llama - bfcl - llama-cpp - gguf-my-repo --- # Nekuromento/watt-tool-8B-Q6_K-GGUF This model was converted to GGUF format from [`watt-ai/watt-tool-8B`](https://huggingface.co/watt-ai/watt-tool-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/watt-ai/watt-tool-8B) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Nekuromento/watt-tool-8B-Q6_K-GGUF --hf-file watt-tool-8b-q6_k.gguf -c 2048 ```

Keltezaa/Shione_Cooper_Actress

Keltezaa

2025-01-15T15:10:32Z

71

0

diffusers

[ "diffusers", "text-to-image", "lora", "template:diffusion-lora", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:cc-by-nc-sa-4.0", "region:us" ]

text-to-image

2025-01-15T14:32:12Z

--- tags: - text-to-image - lora - diffusers - template:diffusion-lora widget: - text: >- A glamour Breathtaking medium shot photography of a young woman with a friendly and calm expression, dressed in a turtleneck. Her style reflects effortless sophistication, blending laid-back comfort with subtle refinement. She is smiling warmly, radiating confidence and approachability. The background is solid and softly lit, enhancing the natural tones and textures of the image. The lighting is diffused and flattering, emphasizing her features while creating a professional and polished aesthetic, she is a natural redhead with pale skin and freckles, standing naked in a lush forest output: url: images/example_ndl7kpc55.png - text: >- A glamour Breathtaking medium shot photography of a young woman with a friendly and calm expression, dressed in a turtleneck. Her style reflects effortless sophistication, blending laid-back comfort with subtle refinement. She is smiling warmly, radiating confidence and approachability. The background is solid and softly lit, enhancing the natural tones and textures of the image. The lighting is diffused and flattering, emphasizing her features while creating a professional and polished aesthetic, output: url: images/example_rdnlqg3w5.png base_model: black-forest-labs/FLUX.1-dev instance_prompt: null license: cc-by-nc-sa-4.0 --- # Shione_Cooper_ Actress <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Keltezaa/Shione_Cooper_Actress/tree/main) them in the Files & versions tab.

ClarenceDan/93993d99-8ea8-47e0-849f-d360c7481cb7

ClarenceDan

2025-01-15T15:09:54Z

32

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:lmsys/vicuna-13b-v1.5", "base_model:adapter:lmsys/vicuna-13b-v1.5", "license:llama2", "region:us" ]

null

2025-01-15T14:21:24Z

--- library_name: peft license: llama2 base_model: lmsys/vicuna-13b-v1.5 tags: - axolotl - generated_from_trainer model-index: - name: 93993d99-8ea8-47e0-849f-d360c7481cb7 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: lmsys/vicuna-13b-v1.5 bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 4a8c0890df315567_train_data.json ds_type: json format: custom path: /workspace/input_data/4a8c0890df315567_train_data.json type: field_instruction: original_text field_output: correct_text format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: ClarenceDan/93993d99-8ea8-47e0-849f-d360c7481cb7 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/4a8c0890df315567_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: a6ac3cc6-bcf7-42ba-814a-539ed29d5e1d wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: a6ac3cc6-bcf7-42ba-814a-539ed29d5e1d warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 93993d99-8ea8-47e0-849f-d360c7481cb7 This model is a fine-tuned version of [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2676 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.4302 | 0.0000 | 1 | 0.4490 | | 0.448 | 0.0001 | 3 | 0.4463 | | 0.4044 | 0.0002 | 6 | 0.4110 | | 0.2998 | 0.0003 | 9 | 0.2676 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

thaffggg/47549b63-3cef-4fdc-babf-e37cc823fc95

thaffggg

2025-01-15T15:03:52Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:50:54Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 47549b63-3cef-4fdc-babf-e37cc823fc95 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: thaffggg/47549b63-3cef-4fdc-babf-e37cc823fc95 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 47549b63-3cef-4fdc-babf-e37cc823fc95 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2828 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.3918 | 0.1633 | 200 | 0.2828 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

nhung01/99cbf546-cfba-4383-aa91-9122d9181457

nhung01

2025-01-15T15:03:48Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:51:04Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: 99cbf546-cfba-4383-aa91-9122d9181457 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: nhung01/99cbf546-cfba-4383-aa91-9122d9181457 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # 99cbf546-cfba-4383-aa91-9122d9181457 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2814 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.3922 | 0.1633 | 200 | 0.2814 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

cunghoctienganh/a798d10d-dee8-4bf8-a46e-6c45dbb791b5

cunghoctienganh

2025-01-15T15:03:18Z

8

0

peft

[ "peft", "safetensors", "qwen2", "axolotl", "generated_from_trainer", "base_model:unsloth/Qwen2-1.5B", "base_model:adapter:unsloth/Qwen2-1.5B", "license:apache-2.0", "8-bit", "bitsandbytes", "region:us" ]

null

2025-01-15T14:50:50Z

--- library_name: peft license: apache-2.0 base_model: unsloth/Qwen2-1.5B tags: - axolotl - generated_from_trainer model-index: - name: a798d10d-dee8-4bf8-a46e-6c45dbb791b5 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/Qwen2-1.5B bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - d01e93bb4785c31e_train_data.json ds_type: json format: custom path: /workspace/input_data/d01e93bb4785c31e_train_data.json type: field_input: domain field_instruction: question field_output: query format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 1 flash_attention: true fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true gradient_clipping: 1.0 group_by_length: false hub_model_id: cunghoctienganh/a798d10d-dee8-4bf8-a46e-6c45dbb791b5 hub_repo: null hub_strategy: end hub_token: null learning_rate: 5.0e-05 load_in_4bit: true load_in_8bit: true local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 200 micro_batch_size: 2 mlflow_experiment_name: /tmp/d01e93bb4785c31e_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 1 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: b42bd8e6-00f4-4388-b8c9-71f792e66bc4 warmup_steps: 5 weight_decay: 0.01 xformers_attention: true ``` </details> # a798d10d-dee8-4bf8-a46e-6c45dbb791b5 This model is a fine-tuned version of [unsloth/Qwen2-1.5B](https://huggingface.co/unsloth/Qwen2-1.5B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2802 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 5 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.3897 | 0.1633 | 200 | 0.2802 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

augustinjianu/whisper-tiny-ro

augustinjianu

2025-01-15T15:00:52Z

21

0

transformers

[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "ro", "dataset:mozilla-foundation/common_voice_17_0", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2025-01-14T22:58:36Z

--- library_name: transformers language: - ro license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - mozilla-foundation/common_voice_17_0 metrics: - wer model-index: - name: Whisper Tiny Ro (local) - Augustin Jianu results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 17.0 type: mozilla-foundation/common_voice_17_0 config: ro split: test args: 'config: ro, split: test' metrics: - name: Wer type: wer value: 37.48352861569144 ---  # Whisper Tiny Ro (local) - Augustin Jianu This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set: - Loss: 0.5978 - Wer: 37.4835 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 10000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:-----:|:---------------:|:-------:| | 0.4417 | 1.7730 | 1000 | 0.5327 | 43.8513 | | 0.1813 | 3.5461 | 2000 | 0.4666 | 38.8689 | | 0.0751 | 5.3191 | 3000 | 0.4645 | 36.5006 | | 0.0326 | 7.0922 | 4000 | 0.4803 | 36.4614 | | 0.0234 | 8.8652 | 5000 | 0.5087 | 36.5148 | | 0.0082 | 10.6383 | 6000 | 0.5424 | 36.6252 | | 0.0042 | 12.4113 | 7000 | 0.5650 | 37.6509 | | 0.0029 | 14.1844 | 8000 | 0.5809 | 36.8710 | | 0.0025 | 15.9574 | 9000 | 0.5922 | 38.1495 | | 0.0021 | 17.7305 | 10000 | 0.5978 | 37.4835 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0

mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF

mradermacher

2025-01-15T15:00:04Z

555

0

transformers

[ "transformers", "gguf", "chat", "abliterated", "uncensored", "mergekit", "merge", "en", "base_model:pipihand01/QwQ-32B-Preview-abliterated-linear25", "base_model:quantized:pipihand01/QwQ-32B-Preview-abliterated-linear25", "license:apache-2.0", "endpoints_compatible", "region:us", "imatrix", "conversational" ]

null

2025-01-15T10:23:55Z

--- base_model: pipihand01/QwQ-32B-Preview-abliterated-linear25 language: - en library_name: transformers license: apache-2.0 license_link: https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-linear25/blob/main/LICENSE quantized_by: mradermacher tags: - chat - abliterated - uncensored - mergekit - merge --- ## About      weighted/imatrix quants of https://huggingface.co/pipihand01/QwQ-32B-Preview-abliterated-linear25  static quants are available at https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) | Link | Type | Size/GB | Notes | |:-----|:-----|--------:|:------| | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ1_S.gguf) | i1-IQ1_S | 7.4 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ1_M.gguf) | i1-IQ1_M | 8.0 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.1 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.1 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_S.gguf) | i1-IQ2_S | 10.5 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ2_M.gguf) | i1-IQ2_M | 11.4 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q2_K_S.gguf) | i1-Q2_K_S | 11.6 | very low quality | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q2_K.gguf) | i1-Q2_K | 12.4 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 12.9 | lower quality | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_XS.gguf) | i1-IQ3_XS | 13.8 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_S.gguf) | i1-Q3_K_S | 14.5 | IQ3_XS probably better | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_S.gguf) | i1-IQ3_S | 14.5 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ3_M.gguf) | i1-IQ3_M | 14.9 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_M.gguf) | i1-Q3_K_M | 16.0 | IQ3_S probably better | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q3_K_L.gguf) | i1-Q3_K_L | 17.3 | IQ3_M probably better | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-IQ4_XS.gguf) | i1-IQ4_XS | 17.8 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_0.gguf) | i1-Q4_0 | 18.8 | fast, low quality | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_K_S.gguf) | i1-Q4_K_S | 18.9 | optimal size/speed/quality | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_K_M.gguf) | i1-Q4_K_M | 20.0 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q4_1.gguf) | i1-Q4_1 | 20.7 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q5_K_S.gguf) | i1-Q5_K_S | 22.7 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q5_K_M.gguf) | i1-Q5_K_M | 23.4 | | | [GGUF](https://huggingface.co/mradermacher/QwQ-32B-Preview-abliterated-linear25-i1-GGUF/resolve/main/QwQ-32B-Preview-abliterated-linear25.i1-Q6_K.gguf) | i1-Q6_K | 27.0 | practically like static Q6_K | Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

hendrydong/ckpt-m-1115-1

hendrydong

2025-01-15T14:59:58Z

47

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-15T14:54:46Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

LocaleNLP/English_bambara

LocaleNLP

2025-01-15T14:59:17Z

263

0

transformers

[ "transformers", "safetensors", "marian", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2025-01-15T14:28:35Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

kokovova/1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7

kokovova

2025-01-15T14:58:59Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:trl-internal-testing/tiny-random-LlamaForCausalLM", "base_model:adapter:trl-internal-testing/tiny-random-LlamaForCausalLM", "region:us" ]

null

2025-01-15T14:58:05Z

--- library_name: peft base_model: trl-internal-testing/tiny-random-LlamaForCausalLM tags: - axolotl - generated_from_trainer model-index: - name: 1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: trl-internal-testing/tiny-random-LlamaForCausalLM bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 986b94c9dc58c18c_train_data.json ds_type: json format: custom path: /workspace/input_data/986b94c9dc58c18c_train_data.json type: field_instruction: prompt field_output: response_a format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kokovova/1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 75GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/986b94c9dc58c18c_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 69e5af40-c6f1-445f-a934-e367beed4132 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 69e5af40-c6f1-445f-a934-e367beed4132 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 1f7a1df9-f33f-4437-9e3c-c5a5ac50d5c7 This model is a fine-tuned version of [trl-internal-testing/tiny-random-LlamaForCausalLM](https://huggingface.co/trl-internal-testing/tiny-random-LlamaForCausalLM) on the None dataset. It achieves the following results on the evaluation set: - Loss: 10.3785 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0001 | 1 | 10.3803 | | 10.3806 | 0.0012 | 8 | 10.3800 | | 10.3797 | 0.0024 | 16 | 10.3791 | | 10.3786 | 0.0035 | 24 | 10.3785 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

minsangK/20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1

minsangK

2025-01-15T14:58:53Z

23

0

transformers

[ "transformers", "safetensors", "xlm-roberta", "feature-extraction", "generated_from_trainer", "text-embeddings-inference", "endpoints_compatible", "region:us" ]

feature-extraction

2025-01-15T11:06:31Z

--- library_name: transformers tags: - generated_from_trainer model-index: - name: 20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1 results: [] ---  # 20250115-bge-m3-8192-bs-8-1-epoch-5e-6-hn-1 This model was trained from scratch on an unknown dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.2 - Datasets 2.19.0 - Tokenizers 0.19.1

bbytxt/11002e5d-55bc-4350-a995-08db41105f07

bbytxt

2025-01-15T14:58:20Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/SmolLM-1.7B-Instruct", "base_model:adapter:unsloth/SmolLM-1.7B-Instruct", "license:apache-2.0", "region:us" ]

null

2025-01-15T14:32:11Z

--- library_name: peft license: apache-2.0 base_model: unsloth/SmolLM-1.7B-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 11002e5d-55bc-4350-a995-08db41105f07 results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/SmolLM-1.7B-Instruct bf16: true chat_template: llama3 data_processes: 16 dataset_prepared_path: null datasets: - data_files: - 19944eee78b6e7aa_train_data.json ds_type: json format: custom path: /workspace/input_data/19944eee78b6e7aa_train_data.json type: field_input: background field_instruction: context field_output: question format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device_map: auto do_eval: true early_stopping_patience: 5 eval_batch_size: 2 eval_max_new_tokens: 128 eval_steps: 50 eval_table_size: null evals_per_epoch: null flash_attention: true fp16: false fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: true hub_model_id: bbytxt/11002e5d-55bc-4350-a995-08db41105f07 hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0001 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 128 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 64 lora_target_linear: true lr_scheduler: cosine max_grad_norm: 1.0 max_memory: 0: 75GB max_steps: 200 micro_batch_size: 8 mlflow_experiment_name: /tmp/19944eee78b6e7aa_train_data.json model_type: AutoModelForCausalLM num_epochs: 3 optim_args: adam_beta1: 0.9 adam_beta2: 0.95 adam_epsilon: 1e-5 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 50 saves_per_epoch: null sequence_len: 1024 strict: false tf32: true tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 3d13b11f-b0e7-4077-be87-c28a4188a998 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 3d13b11f-b0e7-4077-be87-c28a4188a998 warmup_steps: 30 weight_decay: 0.0 xformers_attention: null ``` </details> # 11002e5d-55bc-4350-a995-08db41105f07 This model is a fine-tuned version of [unsloth/SmolLM-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM-1.7B-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7661 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 30 - training_steps: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 4.078 | 0.0004 | 1 | 4.2947 | | 2.1366 | 0.0186 | 50 | 2.0422 | | 2.0896 | 0.0371 | 100 | 1.8271 | | 1.8261 | 0.0557 | 150 | 1.7759 | | 2.0419 | 0.0743 | 200 | 1.7661 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

visdata/bc15

visdata

2025-01-15T14:58:14Z

57

0

transformers

[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2025-01-15T14:46:23Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

youssefguessous/hautdela-lora-flux-dev

youssefguessous

2025-01-15T14:57:17Z

44

1

diffusers

[ "diffusers", "flux", "lora", "replicate", "text-to-image", "en", "base_model:black-forest-labs/FLUX.1-dev", "base_model:adapter:black-forest-labs/FLUX.1-dev", "license:other", "region:us" ]

text-to-image

2025-01-15T12:54:04Z

--- license: other license_name: flux-1-dev-non-commercial-license license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md language: - en tags: - flux - diffusers - lora - replicate base_model: "black-forest-labs/FLUX.1-dev" pipeline_tag: text-to-image # widget: # - text: >- # prompt # output: # url: https://... instance_prompt: HAUTDELA --- # Hautdela Lora Flux Dev <Gallery /> Trained on Replicate using: https://replicate.com/ostris/flux-dev-lora-trainer/train ## Trigger words You should use `HAUTDELA` to trigger the image generation. ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) ```py from diffusers import AutoPipelineForText2Image import torch pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') pipeline.load_lora_weights('youssefguessous/hautdela-lora-flux-dev', weight_name='lora.safetensors') image = pipeline('your prompt').images[0] ``` For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

dimasik87/388f1eb7-1d9e-47b8-9fb1-dcead681c9df

dimasik87

2025-01-15T14:57:06Z

8

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:unsloth/llama-3-8b-Instruct", "base_model:adapter:unsloth/llama-3-8b-Instruct", "license:llama3", "region:us" ]

null

2025-01-15T14:15:12Z

--- library_name: peft license: llama3 base_model: unsloth/llama-3-8b-Instruct tags: - axolotl - generated_from_trainer model-index: - name: 388f1eb7-1d9e-47b8-9fb1-dcead681c9df results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: unsloth/llama-3-8b-Instruct bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 0431498a24ad26e2_train_data.json ds_type: json format: custom path: /workspace/input_data/0431498a24ad26e2_train_data.json type: field_input: text field_instruction: prompt field_output: responseA format: '{instruction} {input}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null device: cuda early_stopping_patience: 1 eval_max_new_tokens: 128 eval_steps: 5 eval_table_size: null evals_per_epoch: null flash_attention: false fp16: null gradient_accumulation_steps: 4 gradient_checkpointing: true group_by_length: false hub_model_id: dimasik87/388f1eb7-1d9e-47b8-9fb1-dcead681c9df hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 3 lora_alpha: 32 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 16 lora_target_linear: true lr_scheduler: cosine max_memory: 0: 78GiB max_steps: 30 micro_batch_size: 2 mlflow_experiment_name: /tmp/0431498a24ad26e2_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_torch output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false save_steps: 10 sequence_len: 1024 strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: true trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: 21027872-1320-4917-9c1c-3ca7864e1be9 wandb_project: Gradients-On-Demand wandb_run: your_name wandb_runid: 21027872-1320-4917-9c1c-3ca7864e1be9 warmup_steps: 10 weight_decay: 0.01 xformers_attention: true ``` </details> # 388f1eb7-1d9e-47b8-9fb1-dcead681c9df This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | No log | 0.0000 | 1 | nan | | 0.0 | 0.0002 | 5 | nan | | 0.0 | 0.0005 | 10 | nan | | 0.0 | 0.0007 | 15 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1

MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization

MayBashendy

2025-01-15T14:56:51Z

5

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:aubmindlab/bert-base-arabertv02", "base_model:finetune:aubmindlab/bert-base-arabertv02", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T14:08:55Z

--- library_name: transformers base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization results: [] ---  # ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k10_task2_organization This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6956 - Qwk: 0.4065 - Mse: 0.6956 - Rmse: 0.8340 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse | |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:| | No log | 0.0370 | 2 | 4.2649 | -0.0228 | 4.2649 | 2.0652 | | No log | 0.0741 | 4 | 2.4048 | 0.0659 | 2.4048 | 1.5507 | | No log | 0.1111 | 6 | 1.2037 | 0.0258 | 1.2037 | 1.0971 | | No log | 0.1481 | 8 | 0.8782 | 0.1424 | 0.8782 | 0.9371 | | No log | 0.1852 | 10 | 0.8781 | 0.1210 | 0.8781 | 0.9371 | | No log | 0.2222 | 12 | 0.9623 | 0.0461 | 0.9623 | 0.9810 | | No log | 0.2593 | 14 | 1.1572 | -0.0959 | 1.1572 | 1.0757 | | No log | 0.2963 | 16 | 1.0446 | -0.0058 | 1.0446 | 1.0221 | | No log | 0.3333 | 18 | 0.8847 | 0.0712 | 0.8847 | 0.9406 | | No log | 0.3704 | 20 | 0.9010 | 0.0447 | 0.9010 | 0.9492 | | No log | 0.4074 | 22 | 0.8834 | 0.1596 | 0.8834 | 0.9399 | | No log | 0.4444 | 24 | 0.9201 | 0.1204 | 0.9201 | 0.9592 | | No log | 0.4815 | 26 | 0.9268 | 0.1865 | 0.9268 | 0.9627 | | No log | 0.5185 | 28 | 1.0286 | 0.0219 | 1.0286 | 1.0142 | | No log | 0.5556 | 30 | 1.0217 | 0.0724 | 1.0217 | 1.0108 | | No log | 0.5926 | 32 | 1.0320 | 0.0384 | 1.0320 | 1.0159 | | No log | 0.6296 | 34 | 0.9380 | 0.2221 | 0.9380 | 0.9685 | | No log | 0.6667 | 36 | 0.8912 | 0.2712 | 0.8912 | 0.9441 | | No log | 0.7037 | 38 | 0.8365 | 0.2929 | 0.8365 | 0.9146 | | No log | 0.7407 | 40 | 0.8275 | 0.2618 | 0.8275 | 0.9096 | | No log | 0.7778 | 42 | 0.8612 | 0.2517 | 0.8612 | 0.9280 | | No log | 0.8148 | 44 | 0.9083 | 0.1655 | 0.9083 | 0.9530 | | No log | 0.8519 | 46 | 0.9579 | 0.0189 | 0.9579 | 0.9787 | | No log | 0.8889 | 48 | 0.8705 | 0.2135 | 0.8705 | 0.9330 | | No log | 0.9259 | 50 | 0.8026 | 0.2723 | 0.8026 | 0.8959 | | No log | 0.9630 | 52 | 0.8513 | 0.1171 | 0.8513 | 0.9227 | | No log | 1.0 | 54 | 0.8504 | 0.1725 | 0.8504 | 0.9222 | | No log | 1.0370 | 56 | 0.8050 | 0.2772 | 0.8050 | 0.8972 | | No log | 1.0741 | 58 | 0.7881 | 0.3398 | 0.7881 | 0.8877 | | No log | 1.1111 | 60 | 0.8618 | 0.3128 | 0.8618 | 0.9283 | | No log | 1.1481 | 62 | 1.0342 | 0.3109 | 1.0342 | 1.0169 | | No log | 1.1852 | 64 | 0.8242 | 0.2916 | 0.8242 | 0.9078 | | No log | 1.2222 | 66 | 0.7361 | 0.2098 | 0.7361 | 0.8580 | | No log | 1.2593 | 68 | 0.7477 | 0.2240 | 0.7477 | 0.8647 | | No log | 1.2963 | 70 | 0.8031 | 0.2975 | 0.8031 | 0.8962 | | No log | 1.3333 | 72 | 1.0369 | 0.2641 | 1.0369 | 1.0183 | | No log | 1.3704 | 74 | 0.8289 | 0.3314 | 0.8289 | 0.9104 | | No log | 1.4074 | 76 | 0.7565 | 0.2932 | 0.7565 | 0.8698 | | No log | 1.4444 | 78 | 0.7453 | 0.3283 | 0.7453 | 0.8633 | | No log | 1.4815 | 80 | 0.9273 | 0.2649 | 0.9273 | 0.9630 | | No log | 1.5185 | 82 | 0.9151 | 0.2909 | 0.9151 | 0.9566 | | No log | 1.5556 | 84 | 0.7353 | 0.2598 | 0.7353 | 0.8575 | | No log | 1.5926 | 86 | 0.7402 | 0.2537 | 0.7402 | 0.8603 | | No log | 1.6296 | 88 | 0.7210 | 0.3183 | 0.7210 | 0.8491 | | No log | 1.6667 | 90 | 0.7265 | 0.2319 | 0.7265 | 0.8523 | | No log | 1.7037 | 92 | 0.9780 | 0.1547 | 0.9780 | 0.9890 | | No log | 1.7407 | 94 | 1.1386 | 0.1581 | 1.1386 | 1.0670 | | No log | 1.7778 | 96 | 0.9872 | 0.1703 | 0.9872 | 0.9936 | | No log | 1.8148 | 98 | 0.7693 | 0.2500 | 0.7693 | 0.8771 | | No log | 1.8519 | 100 | 0.6808 | 0.3121 | 0.6808 | 0.8251 | | No log | 1.8889 | 102 | 0.7115 | 0.2345 | 0.7115 | 0.8435 | | No log | 1.9259 | 104 | 0.7080 | 0.3626 | 0.7080 | 0.8414 | | No log | 1.9630 | 106 | 0.7251 | 0.3840 | 0.7251 | 0.8515 | | No log | 2.0 | 108 | 0.8961 | 0.3583 | 0.8961 | 0.9466 | | No log | 2.0370 | 110 | 0.8678 | 0.3421 | 0.8678 | 0.9315 | | No log | 2.0741 | 112 | 0.7853 | 0.4160 | 0.7853 | 0.8862 | | No log | 2.1111 | 114 | 0.7847 | 0.3450 | 0.7847 | 0.8858 | | No log | 2.1481 | 116 | 0.7820 | 0.2879 | 0.7820 | 0.8843 | | No log | 2.1852 | 118 | 0.7886 | 0.2819 | 0.7886 | 0.8880 | | No log | 2.2222 | 120 | 0.8080 | 0.3674 | 0.8080 | 0.8989 | | No log | 2.2593 | 122 | 0.7933 | 0.3608 | 0.7933 | 0.8907 | | No log | 2.2963 | 124 | 0.8356 | 0.1799 | 0.8356 | 0.9141 | | No log | 2.3333 | 126 | 0.7891 | 0.3746 | 0.7891 | 0.8883 | | No log | 2.3704 | 128 | 1.0069 | 0.2719 | 1.0069 | 1.0034 | | No log | 2.4074 | 130 | 1.1976 | 0.2507 | 1.1976 | 1.0944 | | No log | 2.4444 | 132 | 0.9833 | 0.2422 | 0.9833 | 0.9916 | | No log | 2.4815 | 134 | 0.7235 | 0.3557 | 0.7235 | 0.8506 | | No log | 2.5185 | 136 | 0.7984 | 0.2655 | 0.7984 | 0.8935 | | No log | 2.5556 | 138 | 0.7571 | 0.2872 | 0.7571 | 0.8701 | | No log | 2.5926 | 140 | 0.6836 | 0.3905 | 0.6836 | 0.8268 | | No log | 2.6296 | 142 | 0.7576 | 0.2694 | 0.7576 | 0.8704 | | No log | 2.6667 | 144 | 0.8193 | 0.2553 | 0.8193 | 0.9052 | | No log | 2.7037 | 146 | 0.7582 | 0.3387 | 0.7582 | 0.8708 | | No log | 2.7407 | 148 | 0.6818 | 0.4172 | 0.6818 | 0.8257 | | No log | 2.7778 | 150 | 0.6817 | 0.3847 | 0.6817 | 0.8256 | | No log | 2.8148 | 152 | 0.6857 | 0.4001 | 0.6857 | 0.8280 | | No log | 2.8519 | 154 | 0.6964 | 0.3905 | 0.6964 | 0.8345 | | No log | 2.8889 | 156 | 0.7135 | 0.3795 | 0.7135 | 0.8447 | | No log | 2.9259 | 158 | 0.7874 | 0.3589 | 0.7874 | 0.8874 | | No log | 2.9630 | 160 | 0.8083 | 0.3097 | 0.8083 | 0.8990 | | No log | 3.0 | 162 | 0.7531 | 0.3002 | 0.7531 | 0.8678 | | No log | 3.0370 | 164 | 0.7420 | 0.3057 | 0.7420 | 0.8614 | | No log | 3.0741 | 166 | 0.7428 | 0.2769 | 0.7428 | 0.8619 | | No log | 3.1111 | 168 | 0.7424 | 0.2735 | 0.7424 | 0.8616 | | No log | 3.1481 | 170 | 0.6882 | 0.3449 | 0.6882 | 0.8296 | | No log | 3.1852 | 172 | 0.7197 | 0.4562 | 0.7197 | 0.8484 | | No log | 3.2222 | 174 | 0.7287 | 0.4128 | 0.7287 | 0.8536 | | No log | 3.2593 | 176 | 0.7444 | 0.4239 | 0.7444 | 0.8628 | | No log | 3.2963 | 178 | 0.7850 | 0.3941 | 0.7850 | 0.8860 | | No log | 3.3333 | 180 | 0.7861 | 0.4062 | 0.7861 | 0.8866 | | No log | 3.3704 | 182 | 0.7008 | 0.4332 | 0.7008 | 0.8371 | | No log | 3.4074 | 184 | 0.6862 | 0.4233 | 0.6862 | 0.8284 | | No log | 3.4444 | 186 | 0.6707 | 0.3905 | 0.6707 | 0.8189 | | No log | 3.4815 | 188 | 0.6858 | 0.3590 | 0.6858 | 0.8281 | | No log | 3.5185 | 190 | 0.8277 | 0.3560 | 0.8277 | 0.9098 | | No log | 3.5556 | 192 | 0.8980 | 0.3155 | 0.8980 | 0.9476 | | No log | 3.5926 | 194 | 0.7492 | 0.3088 | 0.7492 | 0.8655 | | No log | 3.6296 | 196 | 0.6773 | 0.3358 | 0.6773 | 0.8230 | | No log | 3.6667 | 198 | 0.7539 | 0.3898 | 0.7539 | 0.8683 | | No log | 3.7037 | 200 | 0.7836 | 0.3404 | 0.7836 | 0.8852 | | No log | 3.7407 | 202 | 0.7252 | 0.4127 | 0.7252 | 0.8516 | | No log | 3.7778 | 204 | 0.7269 | 0.3153 | 0.7269 | 0.8526 | | No log | 3.8148 | 206 | 0.8672 | 0.2295 | 0.8672 | 0.9312 | | No log | 3.8519 | 208 | 0.8732 | 0.2705 | 0.8732 | 0.9345 | | No log | 3.8889 | 210 | 0.7278 | 0.3419 | 0.7278 | 0.8531 | | No log | 3.9259 | 212 | 0.6975 | 0.4351 | 0.6975 | 0.8351 | | No log | 3.9630 | 214 | 0.7183 | 0.4552 | 0.7183 | 0.8476 | | No log | 4.0 | 216 | 0.7031 | 0.4728 | 0.7031 | 0.8385 | | No log | 4.0370 | 218 | 0.7066 | 0.3930 | 0.7066 | 0.8406 | | No log | 4.0741 | 220 | 0.7424 | 0.3812 | 0.7424 | 0.8617 | | No log | 4.1111 | 222 | 0.7145 | 0.3401 | 0.7145 | 0.8453 | | No log | 4.1481 | 224 | 0.7027 | 0.3419 | 0.7027 | 0.8382 | | No log | 4.1852 | 226 | 0.6740 | 0.3789 | 0.6740 | 0.8210 | | No log | 4.2222 | 228 | 0.6646 | 0.3990 | 0.6646 | 0.8152 | | No log | 4.2593 | 230 | 0.6643 | 0.4154 | 0.6643 | 0.8151 | | No log | 4.2963 | 232 | 0.6807 | 0.4047 | 0.6807 | 0.8250 | | No log | 4.3333 | 234 | 0.7314 | 0.4496 | 0.7314 | 0.8552 | | No log | 4.3704 | 236 | 0.7605 | 0.4808 | 0.7605 | 0.8721 | | No log | 4.4074 | 238 | 0.7136 | 0.4234 | 0.7136 | 0.8447 | | No log | 4.4444 | 240 | 0.7071 | 0.4520 | 0.7071 | 0.8409 | | No log | 4.4815 | 242 | 0.7238 | 0.4571 | 0.7238 | 0.8508 | | No log | 4.5185 | 244 | 0.7134 | 0.4346 | 0.7134 | 0.8446 | | No log | 4.5556 | 246 | 0.7427 | 0.4241 | 0.7427 | 0.8618 | | No log | 4.5926 | 248 | 0.7480 | 0.4094 | 0.7480 | 0.8648 | | No log | 4.6296 | 250 | 0.7522 | 0.4079 | 0.7522 | 0.8673 | | No log | 4.6667 | 252 | 0.7522 | 0.4296 | 0.7522 | 0.8673 | | No log | 4.7037 | 254 | 0.7353 | 0.3845 | 0.7353 | 0.8575 | | No log | 4.7407 | 256 | 0.7388 | 0.3514 | 0.7388 | 0.8595 | | No log | 4.7778 | 258 | 0.7709 | 0.3659 | 0.7709 | 0.8780 | | No log | 4.8148 | 260 | 0.7823 | 0.3613 | 0.7823 | 0.8845 | | No log | 4.8519 | 262 | 0.7626 | 0.3703 | 0.7626 | 0.8733 | | No log | 4.8889 | 264 | 0.7646 | 0.4058 | 0.7646 | 0.8744 | | No log | 4.9259 | 266 | 0.7517 | 0.4111 | 0.7517 | 0.8670 | | No log | 4.9630 | 268 | 0.7591 | 0.3921 | 0.7591 | 0.8713 | | No log | 5.0 | 270 | 0.7818 | 0.4122 | 0.7818 | 0.8842 | | No log | 5.0370 | 272 | 0.7745 | 0.4303 | 0.7745 | 0.8800 | | No log | 5.0741 | 274 | 0.7880 | 0.4521 | 0.7880 | 0.8877 | | No log | 5.1111 | 276 | 0.8725 | 0.3928 | 0.8725 | 0.9341 | | No log | 5.1481 | 278 | 0.8682 | 0.3761 | 0.8682 | 0.9318 | | No log | 5.1852 | 280 | 0.7397 | 0.4129 | 0.7397 | 0.8600 | | No log | 5.2222 | 282 | 0.7005 | 0.3669 | 0.7005 | 0.8370 | | No log | 5.2593 | 284 | 0.7074 | 0.3585 | 0.7074 | 0.8410 | | No log | 5.2963 | 286 | 0.7026 | 0.3227 | 0.7026 | 0.8382 | | No log | 5.3333 | 288 | 0.7122 | 0.3655 | 0.7122 | 0.8439 | | No log | 5.3704 | 290 | 0.7270 | 0.3693 | 0.7270 | 0.8526 | | No log | 5.4074 | 292 | 0.7674 | 0.4339 | 0.7674 | 0.8760 | | No log | 5.4444 | 294 | 0.7428 | 0.3853 | 0.7428 | 0.8618 | | No log | 5.4815 | 296 | 0.7304 | 0.3568 | 0.7304 | 0.8546 | | No log | 5.5185 | 298 | 0.7671 | 0.2821 | 0.7671 | 0.8758 | | No log | 5.5556 | 300 | 0.7282 | 0.3860 | 0.7282 | 0.8534 | | No log | 5.5926 | 302 | 0.7099 | 0.3877 | 0.7099 | 0.8426 | | No log | 5.6296 | 304 | 0.7235 | 0.3827 | 0.7235 | 0.8506 | | No log | 5.6667 | 306 | 0.7305 | 0.4462 | 0.7305 | 0.8547 | | No log | 5.7037 | 308 | 0.6874 | 0.4306 | 0.6874 | 0.8291 | | No log | 5.7407 | 310 | 0.7730 | 0.4009 | 0.7730 | 0.8792 | | No log | 5.7778 | 312 | 0.8971 | 0.3048 | 0.8971 | 0.9472 | | No log | 5.8148 | 314 | 0.8102 | 0.3699 | 0.8102 | 0.9001 | | No log | 5.8519 | 316 | 0.6982 | 0.4026 | 0.6982 | 0.8356 | | No log | 5.8889 | 318 | 0.6854 | 0.3977 | 0.6854 | 0.8279 | | No log | 5.9259 | 320 | 0.6907 | 0.4542 | 0.6907 | 0.8311 | | No log | 5.9630 | 322 | 0.7088 | 0.4649 | 0.7088 | 0.8419 | | No log | 6.0 | 324 | 0.7319 | 0.4862 | 0.7319 | 0.8555 | | No log | 6.0370 | 326 | 0.7332 | 0.4812 | 0.7332 | 0.8563 | | No log | 6.0741 | 328 | 0.7223 | 0.4940 | 0.7223 | 0.8499 | | No log | 6.1111 | 330 | 0.7190 | 0.3858 | 0.7190 | 0.8479 | | No log | 6.1481 | 332 | 0.7488 | 0.3590 | 0.7488 | 0.8653 | | No log | 6.1852 | 334 | 0.7076 | 0.2821 | 0.7076 | 0.8412 | | No log | 6.2222 | 336 | 0.6852 | 0.2982 | 0.6852 | 0.8278 | | No log | 6.2593 | 338 | 0.7207 | 0.2521 | 0.7207 | 0.8490 | | No log | 6.2963 | 340 | 0.7623 | 0.2642 | 0.7623 | 0.8731 | | No log | 6.3333 | 342 | 0.7289 | 0.3507 | 0.7289 | 0.8538 | | No log | 6.3704 | 344 | 0.6978 | 0.3791 | 0.6978 | 0.8353 | | No log | 6.4074 | 346 | 0.6939 | 0.3435 | 0.6939 | 0.8330 | | No log | 6.4444 | 348 | 0.7328 | 0.3696 | 0.7328 | 0.8561 | | No log | 6.4815 | 350 | 0.7141 | 0.384 | 0.7141 | 0.8450 | | No log | 6.5185 | 352 | 0.6893 | 0.3894 | 0.6893 | 0.8302 | | No log | 6.5556 | 354 | 0.6849 | 0.3443 | 0.6849 | 0.8276 | | No log | 6.5926 | 356 | 0.7324 | 0.3791 | 0.7324 | 0.8558 | | No log | 6.6296 | 358 | 0.7436 | 0.3755 | 0.7436 | 0.8623 | | No log | 6.6667 | 360 | 0.7026 | 0.3604 | 0.7026 | 0.8382 | | No log | 6.7037 | 362 | 0.7192 | 0.3814 | 0.7192 | 0.8481 | | No log | 6.7407 | 364 | 0.7593 | 0.3607 | 0.7593 | 0.8714 | | No log | 6.7778 | 366 | 0.7241 | 0.3776 | 0.7241 | 0.8509 | | No log | 6.8148 | 368 | 0.7035 | 0.3373 | 0.7035 | 0.8388 | | No log | 6.8519 | 370 | 0.7332 | 0.3985 | 0.7332 | 0.8563 | | No log | 6.8889 | 372 | 0.7415 | 0.3983 | 0.7415 | 0.8611 | | No log | 6.9259 | 374 | 0.7157 | 0.3970 | 0.7157 | 0.8460 | | No log | 6.9630 | 376 | 0.7331 | 0.3808 | 0.7331 | 0.8562 | | No log | 7.0 | 378 | 0.7475 | 0.4068 | 0.7475 | 0.8646 | | No log | 7.0370 | 380 | 0.7260 | 0.3782 | 0.7260 | 0.8521 | | No log | 7.0741 | 382 | 0.7003 | 0.3363 | 0.7003 | 0.8369 | | No log | 7.1111 | 384 | 0.7012 | 0.4209 | 0.7012 | 0.8374 | | No log | 7.1481 | 386 | 0.7126 | 0.4273 | 0.7126 | 0.8442 | | No log | 7.1852 | 388 | 0.7068 | 0.4146 | 0.7068 | 0.8407 | | No log | 7.2222 | 390 | 0.6893 | 0.3976 | 0.6893 | 0.8302 | | No log | 7.2593 | 392 | 0.7194 | 0.3353 | 0.7194 | 0.8482 | | No log | 7.2963 | 394 | 0.7559 | 0.3323 | 0.7559 | 0.8694 | | No log | 7.3333 | 396 | 0.7225 | 0.3618 | 0.7225 | 0.8500 | | No log | 7.3704 | 398 | 0.7170 | 0.3776 | 0.7170 | 0.8468 | | No log | 7.4074 | 400 | 0.7965 | 0.3963 | 0.7965 | 0.8925 | | No log | 7.4444 | 402 | 0.9136 | 0.3449 | 0.9136 | 0.9558 | | No log | 7.4815 | 404 | 0.8872 | 0.3363 | 0.8872 | 0.9419 | | No log | 7.5185 | 406 | 0.7623 | 0.3967 | 0.7623 | 0.8731 | | No log | 7.5556 | 408 | 0.7050 | 0.3184 | 0.7050 | 0.8396 | | No log | 7.5926 | 410 | 0.6974 | 0.3655 | 0.6974 | 0.8351 | | No log | 7.6296 | 412 | 0.7093 | 0.2859 | 0.7093 | 0.8422 | | No log | 7.6667 | 414 | 0.6987 | 0.3212 | 0.6987 | 0.8359 | | No log | 7.7037 | 416 | 0.6966 | 0.3645 | 0.6966 | 0.8346 | | No log | 7.7407 | 418 | 0.6930 | 0.3961 | 0.6930 | 0.8324 | | No log | 7.7778 | 420 | 0.6835 | 0.4450 | 0.6835 | 0.8267 | | No log | 7.8148 | 422 | 0.6783 | 0.4712 | 0.6783 | 0.8236 | | No log | 7.8519 | 424 | 0.7015 | 0.4629 | 0.7015 | 0.8376 | | No log | 7.8889 | 426 | 0.6753 | 0.4621 | 0.6753 | 0.8218 | | No log | 7.9259 | 428 | 0.6774 | 0.3902 | 0.6774 | 0.8230 | | No log | 7.9630 | 430 | 0.7012 | 0.4128 | 0.7012 | 0.8374 | | No log | 8.0 | 432 | 0.6767 | 0.4186 | 0.6767 | 0.8226 | | No log | 8.0370 | 434 | 0.6702 | 0.4079 | 0.6702 | 0.8187 | | No log | 8.0741 | 436 | 0.6775 | 0.4211 | 0.6775 | 0.8231 | | No log | 8.1111 | 438 | 0.6938 | 0.4465 | 0.6938 | 0.8330 | | No log | 8.1481 | 440 | 0.7008 | 0.4403 | 0.7008 | 0.8372 | | No log | 8.1852 | 442 | 0.6938 | 0.4465 | 0.6938 | 0.8329 | | No log | 8.2222 | 444 | 0.7169 | 0.4451 | 0.7169 | 0.8467 | | No log | 8.2593 | 446 | 0.7140 | 0.4504 | 0.7140 | 0.8450 | | No log | 8.2963 | 448 | 0.7267 | 0.4444 | 0.7267 | 0.8525 | | No log | 8.3333 | 450 | 0.7111 | 0.4713 | 0.7111 | 0.8433 | | No log | 8.3704 | 452 | 0.7098 | 0.4960 | 0.7098 | 0.8425 | | No log | 8.4074 | 454 | 0.7196 | 0.4569 | 0.7196 | 0.8483 | | No log | 8.4444 | 456 | 0.7759 | 0.4233 | 0.7759 | 0.8808 | | No log | 8.4815 | 458 | 0.7809 | 0.4237 | 0.7809 | 0.8837 | | No log | 8.5185 | 460 | 0.7744 | 0.4066 | 0.7744 | 0.8800 | | No log | 8.5556 | 462 | 0.7148 | 0.3988 | 0.7148 | 0.8455 | | No log | 8.5926 | 464 | 0.7066 | 0.4181 | 0.7066 | 0.8406 | | No log | 8.6296 | 466 | 0.7049 | 0.3904 | 0.7049 | 0.8396 | | No log | 8.6667 | 468 | 0.7050 | 0.4147 | 0.7050 | 0.8397 | | No log | 8.7037 | 470 | 0.7628 | 0.3665 | 0.7628 | 0.8734 | | No log | 8.7407 | 472 | 0.8046 | 0.2797 | 0.8046 | 0.8970 | | No log | 8.7778 | 474 | 0.7751 | 0.3621 | 0.7751 | 0.8804 | | No log | 8.8148 | 476 | 0.7161 | 0.3629 | 0.7161 | 0.8462 | | No log | 8.8519 | 478 | 0.7246 | 0.3481 | 0.7246 | 0.8512 | | No log | 8.8889 | 480 | 0.7615 | 0.4345 | 0.7615 | 0.8727 | | No log | 8.9259 | 482 | 0.7338 | 0.3665 | 0.7338 | 0.8566 | | No log | 8.9630 | 484 | 0.7104 | 0.4143 | 0.7104 | 0.8428 | | No log | 9.0 | 486 | 0.7510 | 0.3212 | 0.7510 | 0.8666 | | No log | 9.0370 | 488 | 0.7680 | 0.3347 | 0.7680 | 0.8764 | | No log | 9.0741 | 490 | 0.7204 | 0.3338 | 0.7204 | 0.8488 | | No log | 9.1111 | 492 | 0.6770 | 0.3475 | 0.6770 | 0.8228 | | No log | 9.1481 | 494 | 0.6943 | 0.3249 | 0.6943 | 0.8332 | | No log | 9.1852 | 496 | 0.6981 | 0.3090 | 0.6981 | 0.8356 | | No log | 9.2222 | 498 | 0.6866 | 0.3215 | 0.6866 | 0.8286 | | 0.3989 | 9.2593 | 500 | 0.6787 | 0.2617 | 0.6787 | 0.8238 | | 0.3989 | 9.2963 | 502 | 0.7103 | 0.3806 | 0.7103 | 0.8428 | | 0.3989 | 9.3333 | 504 | 0.7781 | 0.3991 | 0.7781 | 0.8821 | | 0.3989 | 9.3704 | 506 | 0.7649 | 0.4175 | 0.7649 | 0.8746 | | 0.3989 | 9.4074 | 508 | 0.7344 | 0.3725 | 0.7344 | 0.8570 | | 0.3989 | 9.4444 | 510 | 0.6900 | 0.2849 | 0.6900 | 0.8306 | | 0.3989 | 9.4815 | 512 | 0.6813 | 0.2647 | 0.6813 | 0.8254 | | 0.3989 | 9.5185 | 514 | 0.6820 | 0.2647 | 0.6820 | 0.8258 | | 0.3989 | 9.5556 | 516 | 0.6890 | 0.2912 | 0.6890 | 0.8300 | | 0.3989 | 9.5926 | 518 | 0.6841 | 0.2912 | 0.6841 | 0.8271 | | 0.3989 | 9.6296 | 520 | 0.6673 | 0.3036 | 0.6673 | 0.8169 | | 0.3989 | 9.6667 | 522 | 0.6629 | 0.3024 | 0.6629 | 0.8142 | | 0.3989 | 9.7037 | 524 | 0.6666 | 0.3090 | 0.6666 | 0.8165 | | 0.3989 | 9.7407 | 526 | 0.6590 | 0.3307 | 0.6590 | 0.8118 | | 0.3989 | 9.7778 | 528 | 0.6633 | 0.3598 | 0.6633 | 0.8144 | | 0.3989 | 9.8148 | 530 | 0.6790 | 0.3652 | 0.6790 | 0.8240 | | 0.3989 | 9.8519 | 532 | 0.6762 | 0.3866 | 0.6762 | 0.8223 | | 0.3989 | 9.8889 | 534 | 0.6872 | 0.4164 | 0.6872 | 0.8290 | | 0.3989 | 9.9259 | 536 | 0.6703 | 0.4307 | 0.6703 | 0.8187 | | 0.3989 | 9.9630 | 538 | 0.6707 | 0.4018 | 0.6707 | 0.8190 | | 0.3989 | 10.0 | 540 | 0.6676 | 0.3584 | 0.6676 | 0.8171 | | 0.3989 | 10.0370 | 542 | 0.6725 | 0.4244 | 0.6725 | 0.8201 | | 0.3989 | 10.0741 | 544 | 0.7166 | 0.3911 | 0.7166 | 0.8465 | | 0.3989 | 10.1111 | 546 | 0.6942 | 0.3875 | 0.6942 | 0.8332 | | 0.3989 | 10.1481 | 548 | 0.6521 | 0.3847 | 0.6521 | 0.8076 | | 0.3989 | 10.1852 | 550 | 0.6613 | 0.3423 | 0.6613 | 0.8132 | | 0.3989 | 10.2222 | 552 | 0.6784 | 0.3811 | 0.6784 | 0.8236 | | 0.3989 | 10.2593 | 554 | 0.6593 | 0.3961 | 0.6593 | 0.8120 | | 0.3989 | 10.2963 | 556 | 0.6501 | 0.3639 | 0.6501 | 0.8063 | | 0.3989 | 10.3333 | 558 | 0.6681 | 0.3637 | 0.6681 | 0.8174 | | 0.3989 | 10.3704 | 560 | 0.7092 | 0.4351 | 0.7092 | 0.8421 | | 0.3989 | 10.4074 | 562 | 0.6952 | 0.4476 | 0.6952 | 0.8338 | | 0.3989 | 10.4444 | 564 | 0.6861 | 0.3861 | 0.6861 | 0.8283 | | 0.3989 | 10.4815 | 566 | 0.7003 | 0.4138 | 0.7003 | 0.8368 | | 0.3989 | 10.5185 | 568 | 0.6967 | 0.3646 | 0.6967 | 0.8347 | | 0.3989 | 10.5556 | 570 | 0.6775 | 0.3455 | 0.6775 | 0.8231 | | 0.3989 | 10.5926 | 572 | 0.6778 | 0.3455 | 0.6778 | 0.8233 | | 0.3989 | 10.6296 | 574 | 0.6976 | 0.3124 | 0.6976 | 0.8352 | | 0.3989 | 10.6667 | 576 | 0.7550 | 0.3738 | 0.7550 | 0.8689 | | 0.3989 | 10.7037 | 578 | 0.7780 | 0.4051 | 0.7780 | 0.8820 | | 0.3989 | 10.7407 | 580 | 0.7216 | 0.3524 | 0.7216 | 0.8495 | | 0.3989 | 10.7778 | 582 | 0.6932 | 0.3696 | 0.6932 | 0.8326 | | 0.3989 | 10.8148 | 584 | 0.6912 | 0.4042 | 0.6912 | 0.8314 | | 0.3989 | 10.8519 | 586 | 0.6984 | 0.3805 | 0.6984 | 0.8357 | | 0.3989 | 10.8889 | 588 | 0.7320 | 0.3074 | 0.7320 | 0.8556 | | 0.3989 | 10.9259 | 590 | 0.7950 | 0.4049 | 0.7950 | 0.8916 | | 0.3989 | 10.9630 | 592 | 0.8450 | 0.3658 | 0.8450 | 0.9192 | | 0.3989 | 11.0 | 594 | 0.8332 | 0.3711 | 0.8332 | 0.9128 | | 0.3989 | 11.0370 | 596 | 0.7693 | 0.3146 | 0.7693 | 0.8771 | | 0.3989 | 11.0741 | 598 | 0.7161 | 0.2683 | 0.7161 | 0.8462 | | 0.3989 | 11.1111 | 600 | 0.7131 | 0.2764 | 0.7131 | 0.8445 | | 0.3989 | 11.1481 | 602 | 0.7296 | 0.2635 | 0.7296 | 0.8542 | | 0.3989 | 11.1852 | 604 | 0.7695 | 0.2883 | 0.7695 | 0.8772 | | 0.3989 | 11.2222 | 606 | 0.7810 | 0.3082 | 0.7810 | 0.8837 | | 0.3989 | 11.2593 | 608 | 0.7489 | 0.3211 | 0.7489 | 0.8654 | | 0.3989 | 11.2963 | 610 | 0.6990 | 0.3722 | 0.6990 | 0.8361 | | 0.3989 | 11.3333 | 612 | 0.6908 | 0.3637 | 0.6908 | 0.8312 | | 0.3989 | 11.3704 | 614 | 0.6900 | 0.4327 | 0.6900 | 0.8307 | | 0.3989 | 11.4074 | 616 | 0.6778 | 0.3593 | 0.6778 | 0.8233 | | 0.3989 | 11.4444 | 618 | 0.6911 | 0.3123 | 0.6911 | 0.8313 | | 0.3989 | 11.4815 | 620 | 0.7727 | 0.3614 | 0.7727 | 0.8790 | | 0.3989 | 11.5185 | 622 | 0.8277 | 0.3627 | 0.8277 | 0.9098 | | 0.3989 | 11.5556 | 624 | 0.7816 | 0.3516 | 0.7816 | 0.8841 | | 0.3989 | 11.5926 | 626 | 0.6957 | 0.3840 | 0.6957 | 0.8341 | | 0.3989 | 11.6296 | 628 | 0.6688 | 0.2742 | 0.6688 | 0.8178 | | 0.3989 | 11.6667 | 630 | 0.6807 | 0.3720 | 0.6807 | 0.8250 | | 0.3989 | 11.7037 | 632 | 0.6776 | 0.3833 | 0.6776 | 0.8232 | | 0.3989 | 11.7407 | 634 | 0.6928 | 0.3954 | 0.6928 | 0.8324 | | 0.3989 | 11.7778 | 636 | 0.7114 | 0.3921 | 0.7114 | 0.8434 | | 0.3989 | 11.8148 | 638 | 0.6843 | 0.4111 | 0.6843 | 0.8272 | | 0.3989 | 11.8519 | 640 | 0.6685 | 0.4915 | 0.6685 | 0.8176 | | 0.3989 | 11.8889 | 642 | 0.6649 | 0.4915 | 0.6649 | 0.8154 | | 0.3989 | 11.9259 | 644 | 0.6607 | 0.4582 | 0.6607 | 0.8128 | | 0.3989 | 11.9630 | 646 | 0.6603 | 0.4367 | 0.6603 | 0.8126 | | 0.3989 | 12.0 | 648 | 0.6609 | 0.3799 | 0.6609 | 0.8130 | | 0.3989 | 12.0370 | 650 | 0.6551 | 0.3786 | 0.6551 | 0.8094 | | 0.3989 | 12.0741 | 652 | 0.6515 | 0.3552 | 0.6515 | 0.8072 | | 0.3989 | 12.1111 | 654 | 0.6478 | 0.3962 | 0.6478 | 0.8048 | | 0.3989 | 12.1481 | 656 | 0.6561 | 0.3962 | 0.6561 | 0.8100 | | 0.3989 | 12.1852 | 658 | 0.6658 | 0.3795 | 0.6658 | 0.8159 | | 0.3989 | 12.2222 | 660 | 0.6709 | 0.3794 | 0.6709 | 0.8191 | | 0.3989 | 12.2593 | 662 | 0.7029 | 0.4209 | 0.7029 | 0.8384 | | 0.3989 | 12.2963 | 664 | 0.7678 | 0.4051 | 0.7678 | 0.8763 | | 0.3989 | 12.3333 | 666 | 0.7786 | 0.4165 | 0.7786 | 0.8824 | | 0.3989 | 12.3704 | 668 | 0.7494 | 0.4387 | 0.7494 | 0.8657 | | 0.3989 | 12.4074 | 670 | 0.6842 | 0.3376 | 0.6842 | 0.8272 | | 0.3989 | 12.4444 | 672 | 0.6557 | 0.4136 | 0.6557 | 0.8098 | | 0.3989 | 12.4815 | 674 | 0.6543 | 0.4013 | 0.6543 | 0.8089 | | 0.3989 | 12.5185 | 676 | 0.6561 | 0.4185 | 0.6561 | 0.8100 | | 0.3989 | 12.5556 | 678 | 0.6593 | 0.4337 | 0.6593 | 0.8120 | | 0.3989 | 12.5926 | 680 | 0.6632 | 0.3989 | 0.6632 | 0.8144 | | 0.3989 | 12.6296 | 682 | 0.6686 | 0.3850 | 0.6686 | 0.8177 | | 0.3989 | 12.6667 | 684 | 0.6555 | 0.3717 | 0.6555 | 0.8096 | | 0.3989 | 12.7037 | 686 | 0.6537 | 0.3961 | 0.6537 | 0.8085 | | 0.3989 | 12.7407 | 688 | 0.6672 | 0.3931 | 0.6672 | 0.8168 | | 0.3989 | 12.7778 | 690 | 0.6930 | 0.4439 | 0.6930 | 0.8325 | | 0.3989 | 12.8148 | 692 | 0.7478 | 0.4464 | 0.7478 | 0.8647 | | 0.3989 | 12.8519 | 694 | 0.7656 | 0.4464 | 0.7656 | 0.8750 | | 0.3989 | 12.8889 | 696 | 0.7161 | 0.4330 | 0.7161 | 0.8462 | | 0.3989 | 12.9259 | 698 | 0.6732 | 0.4321 | 0.6732 | 0.8205 | | 0.3989 | 12.9630 | 700 | 0.6765 | 0.3894 | 0.6765 | 0.8225 | | 0.3989 | 13.0 | 702 | 0.6678 | 0.3949 | 0.6678 | 0.8172 | | 0.3989 | 13.0370 | 704 | 0.6724 | 0.4450 | 0.6724 | 0.8200 | | 0.3989 | 13.0741 | 706 | 0.6971 | 0.4169 | 0.6971 | 0.8349 | | 0.3989 | 13.1111 | 708 | 0.6941 | 0.4017 | 0.6941 | 0.8331 | | 0.3989 | 13.1481 | 710 | 0.6841 | 0.4369 | 0.6841 | 0.8271 | | 0.3989 | 13.1852 | 712 | 0.7099 | 0.4153 | 0.7099 | 0.8426 | | 0.3989 | 13.2222 | 714 | 0.7661 | 0.4165 | 0.7661 | 0.8753 | | 0.3989 | 13.2593 | 716 | 0.7600 | 0.4194 | 0.7600 | 0.8718 | | 0.3989 | 13.2963 | 718 | 0.7098 | 0.4773 | 0.7098 | 0.8425 | | 0.3989 | 13.3333 | 720 | 0.6987 | 0.4060 | 0.6987 | 0.8359 | | 0.3989 | 13.3704 | 722 | 0.7065 | 0.3861 | 0.7065 | 0.8405 | | 0.3989 | 13.4074 | 724 | 0.6807 | 0.3993 | 0.6807 | 0.8250 | | 0.3989 | 13.4444 | 726 | 0.6681 | 0.3951 | 0.6681 | 0.8174 | | 0.3989 | 13.4815 | 728 | 0.6905 | 0.4164 | 0.6905 | 0.8309 | | 0.3989 | 13.5185 | 730 | 0.6999 | 0.4100 | 0.6999 | 0.8366 | | 0.3989 | 13.5556 | 732 | 0.6771 | 0.3959 | 0.6771 | 0.8228 | | 0.3989 | 13.5926 | 734 | 0.6639 | 0.3849 | 0.6639 | 0.8148 | | 0.3989 | 13.6296 | 736 | 0.6664 | 0.4125 | 0.6664 | 0.8163 | | 0.3989 | 13.6667 | 738 | 0.6685 | 0.4125 | 0.6685 | 0.8176 | | 0.3989 | 13.7037 | 740 | 0.6685 | 0.4514 | 0.6685 | 0.8176 | | 0.3989 | 13.7407 | 742 | 0.6763 | 0.3486 | 0.6763 | 0.8224 | | 0.3989 | 13.7778 | 744 | 0.6774 | 0.3447 | 0.6774 | 0.8230 | | 0.3989 | 13.8148 | 746 | 0.6772 | 0.4196 | 0.6772 | 0.8229 | | 0.3989 | 13.8519 | 748 | 0.7201 | 0.3721 | 0.7201 | 0.8486 | | 0.3989 | 13.8889 | 750 | 0.7478 | 0.3967 | 0.7478 | 0.8647 | | 0.3989 | 13.9259 | 752 | 0.7129 | 0.3842 | 0.7129 | 0.8443 | | 0.3989 | 13.9630 | 754 | 0.6736 | 0.3720 | 0.6736 | 0.8207 | | 0.3989 | 14.0 | 756 | 0.6597 | 0.3260 | 0.6597 | 0.8122 | | 0.3989 | 14.0370 | 758 | 0.6661 | 0.3535 | 0.6661 | 0.8161 | | 0.3989 | 14.0741 | 760 | 0.6634 | 0.3261 | 0.6634 | 0.8145 | | 0.3989 | 14.1111 | 762 | 0.6619 | 0.3932 | 0.6619 | 0.8135 | | 0.3989 | 14.1481 | 764 | 0.7034 | 0.3979 | 0.7034 | 0.8387 | | 0.3989 | 14.1852 | 766 | 0.7503 | 0.4186 | 0.7503 | 0.8662 | | 0.3989 | 14.2222 | 768 | 0.7448 | 0.4291 | 0.7448 | 0.8630 | | 0.3989 | 14.2593 | 770 | 0.7038 | 0.3582 | 0.7038 | 0.8390 | | 0.3989 | 14.2963 | 772 | 0.6633 | 0.3481 | 0.6633 | 0.8145 | | 0.3989 | 14.3333 | 774 | 0.6669 | 0.3535 | 0.6669 | 0.8166 | | 0.3989 | 14.3704 | 776 | 0.6649 | 0.3427 | 0.6649 | 0.8154 | | 0.3989 | 14.4074 | 778 | 0.6675 | 0.3868 | 0.6675 | 0.8170 | | 0.3989 | 14.4444 | 780 | 0.6906 | 0.3825 | 0.6906 | 0.8310 | | 0.3989 | 14.4815 | 782 | 0.6904 | 0.3923 | 0.6904 | 0.8309 | | 0.3989 | 14.5185 | 784 | 0.6962 | 0.4358 | 0.6962 | 0.8344 | | 0.3989 | 14.5556 | 786 | 0.6914 | 0.4262 | 0.6914 | 0.8315 | | 0.3989 | 14.5926 | 788 | 0.6870 | 0.4385 | 0.6870 | 0.8288 | | 0.3989 | 14.6296 | 790 | 0.6940 | 0.4323 | 0.6940 | 0.8331 | | 0.3989 | 14.6667 | 792 | 0.6840 | 0.4330 | 0.6840 | 0.8270 | | 0.3989 | 14.7037 | 794 | 0.6704 | 0.3710 | 0.6704 | 0.8188 | | 0.3989 | 14.7407 | 796 | 0.6604 | 0.4066 | 0.6604 | 0.8127 | | 0.3989 | 14.7778 | 798 | 0.6668 | 0.3904 | 0.6668 | 0.8166 | | 0.3989 | 14.8148 | 800 | 0.6755 | 0.4607 | 0.6755 | 0.8219 | | 0.3989 | 14.8519 | 802 | 0.6829 | 0.4445 | 0.6829 | 0.8264 | | 0.3989 | 14.8889 | 804 | 0.6616 | 0.4246 | 0.6616 | 0.8134 | | 0.3989 | 14.9259 | 806 | 0.6458 | 0.4192 | 0.6458 | 0.8036 | | 0.3989 | 14.9630 | 808 | 0.6336 | 0.4225 | 0.6336 | 0.7960 | | 0.3989 | 15.0 | 810 | 0.6256 | 0.4268 | 0.6256 | 0.7909 | | 0.3989 | 15.0370 | 812 | 0.6270 | 0.4053 | 0.6270 | 0.7919 | | 0.3989 | 15.0741 | 814 | 0.6710 | 0.3810 | 0.6710 | 0.8191 | | 0.3989 | 15.1111 | 816 | 0.6770 | 0.3746 | 0.6770 | 0.8228 | | 0.3989 | 15.1481 | 818 | 0.6395 | 0.4224 | 0.6395 | 0.7997 | | 0.3989 | 15.1852 | 820 | 0.6250 | 0.4482 | 0.6250 | 0.7905 | | 0.3989 | 15.2222 | 822 | 0.6428 | 0.4607 | 0.6428 | 0.8017 | | 0.3989 | 15.2593 | 824 | 0.6432 | 0.4553 | 0.6432 | 0.8020 | | 0.3989 | 15.2963 | 826 | 0.6369 | 0.4203 | 0.6369 | 0.7981 | | 0.3989 | 15.3333 | 828 | 0.6731 | 0.4489 | 0.6731 | 0.8205 | | 0.3989 | 15.3704 | 830 | 0.7253 | 0.4014 | 0.7253 | 0.8517 | | 0.3989 | 15.4074 | 832 | 0.7206 | 0.3982 | 0.7206 | 0.8489 | | 0.3989 | 15.4444 | 834 | 0.6697 | 0.4266 | 0.6697 | 0.8183 | | 0.3989 | 15.4815 | 836 | 0.6468 | 0.4696 | 0.6468 | 0.8042 | | 0.3989 | 15.5185 | 838 | 0.6553 | 0.4499 | 0.6553 | 0.8095 | | 0.3989 | 15.5556 | 840 | 0.6369 | 0.4286 | 0.6369 | 0.7980 | | 0.3989 | 15.5926 | 842 | 0.6288 | 0.4072 | 0.6288 | 0.7930 | | 0.3989 | 15.6296 | 844 | 0.6593 | 0.4202 | 0.6593 | 0.8120 | | 0.3989 | 15.6667 | 846 | 0.7051 | 0.4073 | 0.7051 | 0.8397 | | 0.3989 | 15.7037 | 848 | 0.7109 | 0.3975 | 0.7109 | 0.8432 | | 0.3989 | 15.7407 | 850 | 0.6783 | 0.4004 | 0.6783 | 0.8236 | | 0.3989 | 15.7778 | 852 | 0.6444 | 0.4189 | 0.6444 | 0.8028 | | 0.3989 | 15.8148 | 854 | 0.6317 | 0.4308 | 0.6317 | 0.7948 | | 0.3989 | 15.8519 | 856 | 0.6378 | 0.4386 | 0.6378 | 0.7986 | | 0.3989 | 15.8889 | 858 | 0.6511 | 0.4498 | 0.6511 | 0.8069 | | 0.3989 | 15.9259 | 860 | 0.6488 | 0.4529 | 0.6488 | 0.8055 | | 0.3989 | 15.9630 | 862 | 0.6421 | 0.4538 | 0.6421 | 0.8013 | | 0.3989 | 16.0 | 864 | 0.6372 | 0.4544 | 0.6372 | 0.7982 | | 0.3989 | 16.0370 | 866 | 0.6646 | 0.4705 | 0.6646 | 0.8152 | | 0.3989 | 16.0741 | 868 | 0.6611 | 0.4567 | 0.6611 | 0.8131 | | 0.3989 | 16.1111 | 870 | 0.6353 | 0.4394 | 0.6353 | 0.7970 | | 0.3989 | 16.1481 | 872 | 0.6305 | 0.4618 | 0.6305 | 0.7941 | | 0.3989 | 16.1852 | 874 | 0.6310 | 0.4587 | 0.6310 | 0.7943 | | 0.3989 | 16.2222 | 876 | 0.6236 | 0.4335 | 0.6236 | 0.7897 | | 0.3989 | 16.2593 | 878 | 0.6222 | 0.4613 | 0.6222 | 0.7888 | | 0.3989 | 16.2963 | 880 | 0.6210 | 0.4623 | 0.6210 | 0.7880 | | 0.3989 | 16.3333 | 882 | 0.6215 | 0.4505 | 0.6215 | 0.7884 | | 0.3989 | 16.3704 | 884 | 0.6234 | 0.4530 | 0.6234 | 0.7896 | | 0.3989 | 16.4074 | 886 | 0.6229 | 0.4273 | 0.6229 | 0.7892 | | 0.3989 | 16.4444 | 888 | 0.6284 | 0.4365 | 0.6284 | 0.7927 | | 0.3989 | 16.4815 | 890 | 0.6267 | 0.4345 | 0.6267 | 0.7917 | | 0.3989 | 16.5185 | 892 | 0.6296 | 0.4368 | 0.6296 | 0.7935 | | 0.3989 | 16.5556 | 894 | 0.6307 | 0.4368 | 0.6307 | 0.7942 | | 0.3989 | 16.5926 | 896 | 0.6319 | 0.4328 | 0.6319 | 0.7949 | | 0.3989 | 16.6296 | 898 | 0.6265 | 0.4433 | 0.6265 | 0.7915 | | 0.3989 | 16.6667 | 900 | 0.6221 | 0.4341 | 0.6221 | 0.7887 | | 0.3989 | 16.7037 | 902 | 0.6184 | 0.4380 | 0.6184 | 0.7864 | | 0.3989 | 16.7407 | 904 | 0.6211 | 0.4331 | 0.6211 | 0.7881 | | 0.3989 | 16.7778 | 906 | 0.6329 | 0.3923 | 0.6329 | 0.7956 | | 0.3989 | 16.8148 | 908 | 0.6370 | 0.3923 | 0.6370 | 0.7981 | | 0.3989 | 16.8519 | 910 | 0.6440 | 0.4124 | 0.6440 | 0.8025 | | 0.3989 | 16.8889 | 912 | 0.6364 | 0.4415 | 0.6364 | 0.7978 | | 0.3989 | 16.9259 | 914 | 0.6324 | 0.4827 | 0.6324 | 0.7952 | | 0.3989 | 16.9630 | 916 | 0.6367 | 0.4712 | 0.6367 | 0.7980 | | 0.3989 | 17.0 | 918 | 0.6374 | 0.4868 | 0.6374 | 0.7984 | | 0.3989 | 17.0370 | 920 | 0.6298 | 0.4433 | 0.6298 | 0.7936 | | 0.3989 | 17.0741 | 922 | 0.6262 | 0.4212 | 0.6262 | 0.7913 | | 0.3989 | 17.1111 | 924 | 0.6226 | 0.4212 | 0.6226 | 0.7891 | | 0.3989 | 17.1481 | 926 | 0.6201 | 0.4569 | 0.6201 | 0.7875 | | 0.3989 | 17.1852 | 928 | 0.6240 | 0.4614 | 0.6240 | 0.7899 | | 0.3989 | 17.2222 | 930 | 0.6161 | 0.4693 | 0.6161 | 0.7849 | | 0.3989 | 17.2593 | 932 | 0.6410 | 0.4292 | 0.6410 | 0.8006 | | 0.3989 | 17.2963 | 934 | 0.6465 | 0.4488 | 0.6465 | 0.8041 | | 0.3989 | 17.3333 | 936 | 0.6256 | 0.4163 | 0.6256 | 0.7909 | | 0.3989 | 17.3704 | 938 | 0.6211 | 0.4322 | 0.6211 | 0.7881 | | 0.3989 | 17.4074 | 940 | 0.6531 | 0.4476 | 0.6531 | 0.8081 | | 0.3989 | 17.4444 | 942 | 0.6888 | 0.4726 | 0.6888 | 0.8299 | | 0.3989 | 17.4815 | 944 | 0.6918 | 0.4726 | 0.6918 | 0.8318 | | 0.3989 | 17.5185 | 946 | 0.6702 | 0.4946 | 0.6702 | 0.8186 | | 0.3989 | 17.5556 | 948 | 0.6504 | 0.4861 | 0.6504 | 0.8065 | | 0.3989 | 17.5926 | 950 | 0.6541 | 0.4818 | 0.6541 | 0.8088 | | 0.3989 | 17.6296 | 952 | 0.6489 | 0.4783 | 0.6489 | 0.8056 | | 0.3989 | 17.6667 | 954 | 0.6567 | 0.4948 | 0.6567 | 0.8104 | | 0.3989 | 17.7037 | 956 | 0.6684 | 0.5438 | 0.6684 | 0.8175 | | 0.3989 | 17.7407 | 958 | 0.6579 | 0.4967 | 0.6579 | 0.8111 | | 0.3989 | 17.7778 | 960 | 0.6376 | 0.4900 | 0.6376 | 0.7985 | | 0.3989 | 17.8148 | 962 | 0.6296 | 0.4788 | 0.6296 | 0.7935 | | 0.3989 | 17.8519 | 964 | 0.6319 | 0.4193 | 0.6319 | 0.7949 | | 0.3989 | 17.8889 | 966 | 0.6270 | 0.4440 | 0.6270 | 0.7918 | | 0.3989 | 17.9259 | 968 | 0.6294 | 0.4592 | 0.6294 | 0.7934 | | 0.3989 | 17.9630 | 970 | 0.6303 | 0.4614 | 0.6303 | 0.7939 | | 0.3989 | 18.0 | 972 | 0.6321 | 0.4614 | 0.6321 | 0.7951 | | 0.3989 | 18.0370 | 974 | 0.6270 | 0.4474 | 0.6270 | 0.7918 | | 0.3989 | 18.0741 | 976 | 0.6202 | 0.4815 | 0.6202 | 0.7875 | | 0.3989 | 18.1111 | 978 | 0.6292 | 0.5075 | 0.6292 | 0.7932 | | 0.3989 | 18.1481 | 980 | 0.6572 | 0.4963 | 0.6572 | 0.8107 | | 0.3989 | 18.1852 | 982 | 0.6353 | 0.4780 | 0.6353 | 0.7971 | | 0.3989 | 18.2222 | 984 | 0.6217 | 0.4474 | 0.6217 | 0.7885 | | 0.3989 | 18.2593 | 986 | 0.6191 | 0.4556 | 0.6191 | 0.7868 | | 0.3989 | 18.2963 | 988 | 0.6139 | 0.4196 | 0.6139 | 0.7835 | | 0.3989 | 18.3333 | 990 | 0.6329 | 0.4905 | 0.6329 | 0.7956 | | 0.3989 | 18.3704 | 992 | 0.6486 | 0.5086 | 0.6486 | 0.8053 | | 0.3989 | 18.4074 | 994 | 0.6243 | 0.4934 | 0.6243 | 0.7901 | | 0.3989 | 18.4444 | 996 | 0.6024 | 0.4497 | 0.6024 | 0.7761 | | 0.3989 | 18.4815 | 998 | 0.6024 | 0.4433 | 0.6024 | 0.7761 | | 0.0722 | 18.5185 | 1000 | 0.6044 | 0.4539 | 0.6044 | 0.7774 | | 0.0722 | 18.5556 | 1002 | 0.6345 | 0.4999 | 0.6345 | 0.7966 | | 0.0722 | 18.5926 | 1004 | 0.6415 | 0.4876 | 0.6415 | 0.8009 | | 0.0722 | 18.6296 | 1006 | 0.6148 | 0.4063 | 0.6148 | 0.7841 | | 0.0722 | 18.6667 | 1008 | 0.6138 | 0.4063 | 0.6138 | 0.7835 | | 0.0722 | 18.7037 | 1010 | 0.6392 | 0.4840 | 0.6392 | 0.7995 | | 0.0722 | 18.7407 | 1012 | 0.6662 | 0.4804 | 0.6662 | 0.8162 | | 0.0722 | 18.7778 | 1014 | 0.6590 | 0.4739 | 0.6590 | 0.8118 | | 0.0722 | 18.8148 | 1016 | 0.6394 | 0.4921 | 0.6394 | 0.7996 | | 0.0722 | 18.8519 | 1018 | 0.6215 | 0.4457 | 0.6215 | 0.7884 | | 0.0722 | 18.8889 | 1020 | 0.6133 | 0.4446 | 0.6133 | 0.7832 | | 0.0722 | 18.9259 | 1022 | 0.6121 | 0.4354 | 0.6121 | 0.7824 | | 0.0722 | 18.9630 | 1024 | 0.6167 | 0.4623 | 0.6167 | 0.7853 | | 0.0722 | 19.0 | 1026 | 0.6212 | 0.4352 | 0.6212 | 0.7882 | | 0.0722 | 19.0370 | 1028 | 0.6566 | 0.3747 | 0.6566 | 0.8103 | | 0.0722 | 19.0741 | 1030 | 0.7234 | 0.4190 | 0.7234 | 0.8505 | | 0.0722 | 19.1111 | 1032 | 0.7400 | 0.4149 | 0.7400 | 0.8602 | | 0.0722 | 19.1481 | 1034 | 0.6956 | 0.4065 | 0.6956 | 0.8340 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu118 - Datasets 2.21.0 - Tokenizers 0.19.1

Kuongan/CS221-mdeberta-v3-base-randomdrop

Kuongan

2025-01-15T14:56:47Z

24

0

transformers

[ "transformers", "safetensors", "deberta-v2", "text-classification", "generated_from_trainer", "base_model:microsoft/mdeberta-v3-base", "base_model:finetune:microsoft/mdeberta-v3-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T14:08:24Z

--- library_name: transformers license: mit base_model: microsoft/mdeberta-v3-base tags: - generated_from_trainer metrics: - f1 - accuracy model-index: - name: CS221-mdeberta-v3-base-randomdrop results: [] ---  # CS221-mdeberta-v3-base-randomdrop This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5440 - F1: 0.6741 - Roc Auc: 0.7756 - Accuracy: 0.4071 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| | 0.5661 | 1.0 | 99 | 0.5434 | 0.0 | 0.5 | 0.1425 | | 0.5054 | 2.0 | 198 | 0.4744 | 0.4852 | 0.6560 | 0.2621 | | 0.4409 | 3.0 | 297 | 0.4436 | 0.5766 | 0.7104 | 0.3308 | | 0.3975 | 4.0 | 396 | 0.4284 | 0.6071 | 0.7316 | 0.3588 | | 0.2827 | 5.0 | 495 | 0.4228 | 0.6095 | 0.7296 | 0.3562 | | 0.2831 | 6.0 | 594 | 0.4540 | 0.6467 | 0.7642 | 0.3715 | | 0.1846 | 7.0 | 693 | 0.4519 | 0.6325 | 0.7459 | 0.3893 | | 0.1752 | 8.0 | 792 | 0.4538 | 0.6426 | 0.7535 | 0.3740 | | 0.1547 | 9.0 | 891 | 0.4799 | 0.6541 | 0.7642 | 0.3791 | | 0.1046 | 10.0 | 990 | 0.4793 | 0.6667 | 0.7687 | 0.4020 | | 0.1052 | 11.0 | 1089 | 0.5001 | 0.6593 | 0.7658 | 0.4046 | | 0.0843 | 12.0 | 1188 | 0.5069 | 0.6647 | 0.7705 | 0.3893 | | 0.0653 | 13.0 | 1287 | 0.5275 | 0.6681 | 0.7669 | 0.4097 | | 0.0575 | 14.0 | 1386 | 0.5455 | 0.6617 | 0.7632 | 0.3944 | | 0.0503 | 15.0 | 1485 | 0.5440 | 0.6741 | 0.7756 | 0.4071 | | 0.0499 | 16.0 | 1584 | 0.5555 | 0.6653 | 0.7660 | 0.4097 | | 0.0431 | 17.0 | 1683 | 0.5557 | 0.6660 | 0.7675 | 0.4020 | | 0.0422 | 18.0 | 1782 | 0.5599 | 0.6632 | 0.7664 | 0.3944 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0

rsicproject/mnasnet-GPT-UCM-captioning

rsicproject

2025-01-15T14:55:57Z

39

0

transformers

[ "transformers", "tensorboard", "safetensors", "vision-encoder-decoder", "generated_from_trainer", "endpoints_compatible", "region:us" ]

null

2025-01-15T14:54:18Z

--- library_name: transformers tags: - generated_from_trainer metrics: - rouge model-index: - name: mnasnet-GPT-UCM-captioning results: [] ---  # mnasnet-GPT-UCM-captioning This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1599 - Rouge: 0.7565 - Bleu1: 0.8056 - Bleu2: 0.7427 - Bleu3: 0.6876 - Bleu4: 0.6411 - Meteor: 0.7599 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1024 - num_epochs: 128 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Meteor | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------:|:------:| | No log | 1.0 | 132 | 1.9151 | 0.4839 | 0.5481 | 0.4544 | 0.3734 | 0.3128 | 0.4642 | | No log | 2.0 | 264 | 1.5925 | 0.5534 | 0.5757 | 0.4913 | 0.4205 | 0.3644 | 0.5538 | | No log | 3.0 | 396 | 1.3495 | 0.5927 | 0.6183 | 0.5338 | 0.4640 | 0.4116 | 0.5908 | | No log | 4.0 | 528 | 1.2230 | 0.5476 | 0.6251 | 0.5351 | 0.4665 | 0.4141 | 0.5342 | | No log | 5.0 | 660 | 1.0534 | 0.6380 | 0.6833 | 0.6038 | 0.5417 | 0.4909 | 0.6387 | | No log | 6.0 | 792 | 1.1554 | 0.6127 | 0.6740 | 0.5783 | 0.5065 | 0.4487 | 0.5980 | | No log | 7.0 | 924 | 1.0466 | 0.5886 | 0.6646 | 0.5867 | 0.5250 | 0.4784 | 0.5726 | | 0.8231 | 8.0 | 1056 | 1.0427 | 0.6528 | 0.7305 | 0.6468 | 0.5849 | 0.5415 | 0.6299 | | 0.8231 | 9.0 | 1188 | 0.9752 | 0.6546 | 0.7104 | 0.6276 | 0.5647 | 0.5149 | 0.6534 | | 0.8231 | 10.0 | 1320 | 0.9692 | 0.6850 | 0.7409 | 0.6665 | 0.6060 | 0.5589 | 0.7002 | | 0.8231 | 11.0 | 1452 | 1.0092 | 0.6708 | 0.7441 | 0.6592 | 0.5922 | 0.5382 | 0.6744 | | 0.8231 | 12.0 | 1584 | 0.9588 | 0.7100 | 0.7872 | 0.7174 | 0.6573 | 0.6057 | 0.7064 | | 0.8231 | 13.0 | 1716 | 1.0117 | 0.6975 | 0.7612 | 0.6820 | 0.6170 | 0.5607 | 0.6904 | | 0.8231 | 14.0 | 1848 | 0.9922 | 0.7642 | 0.8057 | 0.7403 | 0.6830 | 0.6321 | 0.7646 | | 0.8231 | 15.0 | 1980 | 1.0432 | 0.7051 | 0.7689 | 0.6954 | 0.6346 | 0.5875 | 0.6945 | | 0.2276 | 16.0 | 2112 | 1.0168 | 0.7263 | 0.7839 | 0.7197 | 0.6627 | 0.6130 | 0.7216 | | 0.2276 | 17.0 | 2244 | 0.9891 | 0.7684 | 0.8315 | 0.7710 | 0.7150 | 0.6689 | 0.7671 | | 0.2276 | 18.0 | 2376 | 0.9994 | 0.7563 | 0.8113 | 0.7474 | 0.6967 | 0.6514 | 0.7514 | | 0.2276 | 19.0 | 2508 | 1.0163 | 0.7709 | 0.8105 | 0.7480 | 0.6924 | 0.6433 | 0.7779 | | 0.2276 | 20.0 | 2640 | 1.0252 | 0.7643 | 0.8030 | 0.7419 | 0.6868 | 0.6379 | 0.7782 | | 0.2276 | 21.0 | 2772 | 1.0315 | 0.7764 | 0.8350 | 0.7695 | 0.7125 | 0.6612 | 0.7814 | | 0.2276 | 22.0 | 2904 | 1.0395 | 0.7695 | 0.8167 | 0.7632 | 0.7180 | 0.6781 | 0.7768 | | 0.2276 | 23.0 | 3036 | 1.0521 | 0.7353 | 0.7927 | 0.7278 | 0.6731 | 0.6262 | 0.7424 | | 0.1659 | 24.0 | 3168 | 1.0567 | 0.7760 | 0.8122 | 0.7512 | 0.7009 | 0.6583 | 0.7793 | | 0.1659 | 25.0 | 3300 | 1.0346 | 0.7586 | 0.8060 | 0.7456 | 0.6933 | 0.6520 | 0.7633 | | 0.1659 | 26.0 | 3432 | 1.0450 | 0.7731 | 0.8191 | 0.7544 | 0.7031 | 0.6597 | 0.7738 | | 0.1659 | 27.0 | 3564 | 1.0612 | 0.7768 | 0.8142 | 0.7523 | 0.6951 | 0.6423 | 0.7883 | | 0.1659 | 28.0 | 3696 | 1.0530 | 0.7643 | 0.8098 | 0.7543 | 0.7066 | 0.6671 | 0.7639 | | 0.1659 | 29.0 | 3828 | 1.0286 | 0.7877 | 0.8337 | 0.7801 | 0.7344 | 0.6944 | 0.7977 | | 0.1659 | 30.0 | 3960 | 1.0435 | 0.7741 | 0.8154 | 0.7506 | 0.6967 | 0.6483 | 0.7790 | | 0.1659 | 31.0 | 4092 | 1.0730 | 0.7393 | 0.7980 | 0.7362 | 0.6846 | 0.6403 | 0.7382 | | 0.1503 | 32.0 | 4224 | 1.0879 | 0.7519 | 0.7933 | 0.7289 | 0.6759 | 0.6291 | 0.7550 | | 0.1503 | 33.0 | 4356 | 1.0987 | 0.7719 | 0.8107 | 0.7470 | 0.6948 | 0.6498 | 0.7759 | | 0.1503 | 34.0 | 4488 | 1.0784 | 0.7725 | 0.8143 | 0.7475 | 0.6920 | 0.6443 | 0.7743 | | 0.1503 | 35.0 | 4620 | 1.0775 | 0.7863 | 0.8176 | 0.7646 | 0.7201 | 0.6807 | 0.7955 | | 0.1503 | 36.0 | 4752 | 1.1081 | 0.7746 | 0.8070 | 0.7499 | 0.7004 | 0.6576 | 0.7832 | | 0.1503 | 37.0 | 4884 | 1.1177 | 0.7682 | 0.8246 | 0.7658 | 0.7128 | 0.6665 | 0.7746 | | 0.1503 | 38.0 | 5016 | 1.1341 | 0.7608 | 0.8068 | 0.7442 | 0.6927 | 0.6477 | 0.7603 | | 0.1427 | 39.0 | 5148 | 1.1599 | 0.7565 | 0.8056 | 0.7427 | 0.6876 | 0.6411 | 0.7599 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.20.3

SenhorDasMoscas/acho-classification-15-01-2025

SenhorDasMoscas

2025-01-15T14:54:48Z

38

0

transformers

[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2025-01-15T14:53:48Z

--- library_name: transformers tags: [] --- # Model Card for Model ID  ## Model Details ### Model Description  This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ### Model Sources [optional]  - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses  ### Direct Use  [More Information Needed] ### Downstream Use [optional]  [More Information Needed] ### Out-of-Scope Use  [More Information Needed] ## Bias, Risks, and Limitations  [More Information Needed] ### Recommendations  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data  [More Information Needed] ### Training Procedure  #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed]  #### Speeds, Sizes, Times [optional]  [More Information Needed] ## Evaluation  ### Testing Data, Factors & Metrics #### Testing Data  [More Information Needed] #### Factors  [More Information Needed] #### Metrics  [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional]  [More Information Needed] ## Environmental Impact  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [More Information Needed] - **Hours used:** [More Information Needed] - **Cloud Provider:** [More Information Needed] - **Compute Region:** [More Information Needed] - **Carbon Emitted:** [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional]  **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional]  [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]

kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a

kk-aivio

2025-01-15T14:53:21Z

8

0

peft

[ "peft", "safetensors", "mistral", "axolotl", "generated_from_trainer", "base_model:echarlaix/tiny-random-mistral", "base_model:adapter:echarlaix/tiny-random-mistral", "license:apache-2.0", "region:us" ]

null

2025-01-15T14:51:47Z

--- library_name: peft license: apache-2.0 base_model: echarlaix/tiny-random-mistral tags: - axolotl - generated_from_trainer model-index: - name: 4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a results: [] ---  [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.1` ```yaml adapter: lora base_model: echarlaix/tiny-random-mistral bf16: auto chat_template: llama3 dataset_prepared_path: null datasets: - data_files: - 960a93b2c47c666b_train_data.json ds_type: json format: custom path: /workspace/input_data/960a93b2c47c666b_train_data.json type: field_instruction: prompt field_output: model_completion format: '{instruction}' no_input_format: '{instruction}' system_format: '{system}' system_prompt: '' debug: null deepspeed: null early_stopping_patience: null eval_max_new_tokens: 128 eval_table_size: null evals_per_epoch: 4 flash_attention: false fp16: null fsdp: null fsdp_config: null gradient_accumulation_steps: 4 gradient_checkpointing: false group_by_length: false hub_model_id: kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a hub_repo: null hub_strategy: checkpoint hub_token: null learning_rate: 0.0002 load_in_4bit: false load_in_8bit: false local_rank: null logging_steps: 1 lora_alpha: 16 lora_dropout: 0.05 lora_fan_in_fan_out: null lora_model_dir: null lora_r: 8 lora_target_linear: true lr_scheduler: cosine max_steps: 10 micro_batch_size: 2 mlflow_experiment_name: /tmp/960a93b2c47c666b_train_data.json model_type: AutoModelForCausalLM num_epochs: 1 optimizer: adamw_bnb_8bit output_dir: miner_id_24 pad_to_sequence_len: true resume_from_checkpoint: null s2_attention: null sample_packing: false saves_per_epoch: 4 sequence_len: 512 special_tokens: pad_token: </s> strict: false tf32: false tokenizer_type: AutoTokenizer train_on_inputs: false trust_remote_code: true val_set_size: 0.05 wandb_entity: null wandb_mode: online wandb_name: b43660c7-01f6-4d83-9a12-686ad5ff81c2 wandb_project: birthday-sn56-17-Gradients-On-Demand wandb_run: your_name wandb_runid: b43660c7-01f6-4d83-9a12-686ad5ff81c2 warmup_steps: 10 weight_decay: 0.0 xformers_attention: null ``` </details> # 4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a This model is a fine-tuned version of [echarlaix/tiny-random-mistral](https://huggingface.co/echarlaix/tiny-random-mistral) on the None dataset. It achieves the following results on the evaluation set: - Loss: nan ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 10 - training_steps: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.0 | 0.0001 | 1 | nan | | 0.0 | 0.0002 | 3 | nan | | 0.0 | 0.0004 | 6 | nan | | 0.0 | 0.0006 | 9 | nan | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.0 - Pytorch 2.5.0+cu124 - Datasets 3.0.1 - Tokenizers 0.20.1