librarian-bots/model_cards_with_metadata · Datasets at Hugging Face

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tsfeith/ppo-LunarLander-v2	tsfeith	2024-02-27T14:06:01Z	0	0	stable-baselines3	[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2024-02-27T14:05:43Z	--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 256.53 +/- 20.04 name: mean_reward verified: false --- # PPO Agent playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```
interrobang/OpenHermes-2.5-Mistral-7B-GGUF-ukrainian-imatrix	interrobang	2024-02-27T14:04:54Z	32	3	null	[ "gguf", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	null	2024-02-07T17:04:31Z	--- license: apache-2.0 --- A test quantization of OpenHermes-2.5-Mistral-7B by teknium using importance matrices computed on Ukrainian text, hopefully decreasing the coherence hit after quantization in Ukrainian at the cost of some performance in other languages. Importance matrix was computed in roughly 20 minutes with a Ryzen 5 3550H and GTX 1650 with 8 layers offloaded, with a context size of 512. The calibration data is just a mix of my personal GPT chats, random words as well as random wikipedia articles, totaling about 15k-ish tokens, definitely not optimal, but it is in the repo for anyone to tinker with, as well as the computed imatrix Will be updated with perplexity testing later, probably? 😭 Haven't done proper tests quite yet, feels better than old quants when chatting in Ukrainian, hopefully I get around to actually benching it somehow
emaeon/solar-hansol-pretrain-merge	emaeon	2024-02-27T14:00:16Z	76	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2024-02-25T16:50:13Z	--- 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. 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Shritama/codellama-7B-IT-NL-SQL-3	Shritama	2024-02-27T14:00:08Z	93	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2024-02-27T13:57:03Z	--- 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. 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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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Lolbruhs/Kats	Lolbruhs	2024-02-27T13:58:07Z	0	0	diffusers	[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:freecryptobasics/KanyeAlbumCoverLora", "base_model:adapter:freecryptobasics/KanyeAlbumCoverLora", "region:us" ]	text-to-image	2024-02-27T13:58:07Z	--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: '-' output: url: images/275 sin título_20240130215710~2.png base_model: freecryptobasics/KanyeAlbumCoverLora instance_prompt: null --- # Cata <Gallery /> ## Download model [Download](/Lolbruhs/Kats/tree/main) them in the Files & versions tab.
nithyarajkumar/tinyllama-finetune-tourism-v1	nithyarajkumar	2024-02-27T13:57:00Z	0	0	peft	[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]	null	2024-02-27T04:19:13Z	--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 model-index: - name: tinyllama-finetune-tourism-v1 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. --> # tinyllama-finetune-tourism-v1 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) 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: 0.0002 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 100 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
Maqqq/Nous-Finetuning-Subnet	Maqqq	2024-02-27T13:46:10Z	5	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-23T16:03:01Z	--- 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. 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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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gohzy/fine-tuned-singlish-toxic-bert-LoRA-35000-1	gohzy	2024-02-27T13:45:20Z	162	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T13:42:46Z	--- 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. 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]
pribadihcr/aniket-math-small-gpt	pribadihcr	2024-02-27T13:41:47Z	4	0	peft	[ "peft", "safetensors", "phi", "generated_from_trainer", "custom_code", "base_model:microsoft/phi-2", "base_model:adapter:microsoft/phi-2", "license:mit", "region:us" ]	null	2024-02-21T14:24:09Z	--- license: mit library_name: peft tags: - generated_from_trainer base_model: microsoft/phi-2 model-index: - name: aniket-math-small-gpt 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. --> # aniket-math-small-gpt This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) 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: 0.0002 - train_batch_size: 4 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 2 ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.2+cu118 - Datasets 2.17.1 - Tokenizers 0.15.2
gohzy/fine-tuned-singlish-toxic-bert-LoRA-35000-1.5	gohzy	2024-02-27T13:40:34Z	162	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "arxiv:1910.09700", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T13:40:16Z	--- 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. 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Ketskapow/distilbert-base-uncased-finetuned-cola	Ketskapow	2024-02-27T13:36:14Z	6	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T13:12:09Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola 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. --> # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4587 - Matthews Correlation: 0.5306 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Matthews Correlation \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------------------:\| \| 0.5228 \| 1.0 \| 535 \| 0.4535 \| 0.4629 \| \| 0.3477 \| 2.0 \| 1070 \| 0.4587 \| 0.5306 \| \| 0.2316 \| 3.0 \| 1605 \| 0.6278 \| 0.5193 \| \| 0.1694 \| 4.0 \| 2140 \| 0.8088 \| 0.5087 \| \| 0.1202 \| 5.0 \| 2675 \| 0.8539 \| 0.5256 \| ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
vicky6/dummy-model_2	vicky6	2024-02-27T13:35:53Z	58	0	transformers	[ "transformers", "tf", "camembert", "fill-mask", "generated_from_keras_callback", "base_model:almanach/camembert-base", "base_model:finetune:almanach/camembert-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	fill-mask	2024-02-27T13:35:15Z	--- license: mit tags: - generated_from_keras_callback base_model: camembert-base model-index: - name: dummy-model_2 results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # dummy-model_2 This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. It achieves the following results on the evaluation set: ## 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: - optimizer: None - training_precision: float32 ### Training results ### Framework versions - Transformers 4.37.2 - TensorFlow 2.15.0 - Tokenizers 0.15.2
seedmanc/isna	seedmanc	2024-02-27T13:33:56Z	2	0	diffusers	[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:stablediffusionapi/anything-v5", "base_model:adapter:stablediffusionapi/anything-v5", "license:other", "region:us" ]	text-to-image	2024-02-27T13:33:49Z	--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: >- isna-style, breasts, plump, gradient background, rough lineart, 1 girl, serval, kemono friends, masterpiece, best quality, rough strokes, rough lines, vector, anime shading, simplistic, lo-fi parameters: negative_prompt: >- worst quality, large head, low quality, extra digits, bad eye, EasyNegativeV2, ng_deepnegative_v1_75t, thin linear, narrow strokes, fine details output: url: images/e61c5484-1c86-062e-202a-090570c97cee.jpeg - text: '-' output: url: images/b30bac82-7114-f7f3-f1fd-4def63ccb410.jpeg - text: >- isna-style, large breasts, flat shading, thick outlines, gradient background, 1girl, rough lineart, wide strokes, vivid, expressive eyes parameters: negative_prompt: >- worst quality, large head, low quality, extra digits, bad eye, EasyNegativeV2, ng_deepnegative_v1_75t output: url: images/cc713442-3b76-492b-a6aa-eca4ea99cbd5.webp - text: '-' output: url: images/b64d7978-5176-f3aa-699d-43493a069eb4.jpeg base_model: stablediffusionapi/anything-v5 instance_prompt: isna-style, plump, flat shading, thick outlines, gradient background license: other license_name: whocares license_link: LICENSE --- # Isna artstyle (イスナ) <Gallery /> ## Model description Vivid colors and rough strokes as well as expressive eyes and pleasant skin colors in art. Mostly for Kemono Friends, produces plump characters. ## Trigger words You should use `isna-style` to trigger the image generation. You should use `plump` to trigger the image generation. You should use `flat shading` to trigger the image generation. You should use `thick outlines` to trigger the image generation. You should use `gradient background` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/seedmanc/isna/tree/main) them in the Files & versions tab.
riotu-lab/ArabianGPT-01B	riotu-lab	2024-02-27T13:31:53Z	2,999	13	transformers	[ "transformers", "pytorch", "gpt2", "text-generation", "arabic ", "ar", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2023-12-04T18:45:05Z	--- license: apache-2.0 language: - ar pipeline_tag: text-generation tags: - 'arabic ' - text-generation widget: - text: "أعلنت وزارة الحج في المملكة العربية السعودية" example_title: "مثال ١" - text: "يبدو اليوم جميلا، سأقوم بتحضير" example_title: "مثال ٢" - text: "إن التقنيات الحديثة" example_title: "مثال ٣" --- # ArabianGPT Model Overview ## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation <p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p> > Important Note: Currently, we offer a raw pre-trained model. Our team is actively working on releasing instruction-based LLMs that are fine-tuned and augmented with LRHF. The first set of pre-trained models has been made available for community exploration. While we do have models fine-tuned for specific tasks such as summarization and sentiment analysis, they are still in the development phase. ## How you can use this Pre-Trained? You are invited to utilize this pre-trained, native Arabic language model as an experimental tool to assess its capabilities, aid in its fine-tuning, and evaluate its performance across a variety of downstream tasks. We encourage you to review our technical report for a comprehensive understanding of the model's performance metrics and the specific downstream tasks it has been tested on. This will provide valuable insights into its applicability and effectiveness in diverse applications. ## Introduction ArabianGPT-0.1B, developed under the ArabianLLM initiatives, is a specialized GPT-2 model optimized for Arabic language modeling. It's a product of the collaborative efforts at Prince Sultan University's Robotics and Internet of Things Lab, focusing on enhancing natural language modeling and generation in Arabic. This model represents a significant stride in LLM research, specifically addressing the linguistic complexities and nuances of the Arabic language. ## Key Features - Architecture: GPT-2 - Model Size: 134 million parameters - Layers: 12 - Model Attention Layers (MAL): 12 - Context Window Size: 768 tokens ## Training - Dataset: Scraped Arabic newspaper articles - Data Size: 15.5 GB - Words: 237.8 million - Tokenizer: Aranizer 64K - Tokens: Over 1.75 billion - Hardware: 2 NDIVIA A100 GPUs - Training Scale: 7.5 million examples - Training Duration: 3 days - Performance: Final loss of 3.97 ## Role in ArabianLLM Initiatives ArabianGPT-0.1B (Base Model) is crucial for advancing Arabic language processing, addressing challenges unique to Arabic morphology and dialects. ## Usage Suitable for Arabic text generation tasks. Example usage with Transformers Pipeline: ```python from transformers import pipeline pipe = pipeline("text-generation", model="riotu-lab/ArabianGPT-01B", max_new_tokens=512) text = '' pipe.predict(text) ``` ## Limitations and Ethical Considerations - The model may have context understanding or text generation limitations in certain scenarios. - Emphasis on ethical use to prevent misinformation or harmful content propagation. ## Acknowledgments Special thanks to Prince Sultan University, particularly the Robotics and Internet of Things Lab. ## Contact Information For inquiries: [[email protected]](mailto:[email protected]). ## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation <p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p>
phoen1x/TF-Finetuned-xsum	phoen1x	2024-02-27T13:28:55Z	72	1	transformers	[ "transformers", "tf", "t5", "text2text-generation", "generated_from_keras_callback", "summarization", "en", "dataset:xsum", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	summarization	2023-05-15T22:20:52Z	--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: TF-Finetuned-xsum results: [] datasets: - xsum language: - en metrics: - rouge pipeline_tag: summarization --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # TF-Finetuned-xsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [xsum](https://huggingface.co/datasets/xsum) dataset. It achieves the following results on the evaluation set: - Train Loss: - Validation Loss: - Epoch: ## 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: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} - training_precision: float32 ### Training results \| Train Loss \| Validation Loss \| Train Rougel \| Epoch \| \|:----------:\|:---------------:\|:---------------------------------------------:\|:-----:\| \| \| \| tf.Tensor(0.1999889, shape=(), dtype=float32) \| \| ### Framework versions - Transformers 4.20.0 - TensorFlow 2.12.0 - Datasets 2.12.0 - Tokenizers 0.12.1
auksliusninetwothree/test-model	auksliusninetwothree	2024-02-27T13:27:58Z	78	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "dataset:audiofolder", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-02-26T13:36:00Z	--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - audiofolder metrics: - wer model-index: - name: test-model results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: audiofolder type: audiofolder config: custom_data split: test args: custom_data metrics: - name: Wer type: wer value: 8.333333333333332 --- <!-- 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. --> # test-model This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 1.1513 - Wer Ortho: 8.3333 - Wer: 8.3333 ## 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: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 2 - training_steps: 20 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer Ortho \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---------:\|:------:\| \| 1.1613 \| 2.71 \| 19 \| 1.1513 \| 8.3333 \| 8.3333 \| ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1 - Datasets 2.17.1 - Tokenizers 0.15.2
misterwavey/flan-t5-base-cc1	misterwavey	2024-02-27T13:26:40Z	106	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2024-02-27T13:07:18Z	--- 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. 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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]
Yanwen9969/distilbert-base-uncased-finetuned-cola	Yanwen9969	2024-02-27T13:21:30Z	4	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T12:36:04Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola 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. --> # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8446 - Matthews Correlation: 0.5377 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Matthews Correlation \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------------------:\| \| 0.517 \| 1.0 \| 535 \| 0.4553 \| 0.4460 \| \| 0.3451 \| 2.0 \| 1070 \| 0.4641 \| 0.5255 \| \| 0.2317 \| 3.0 \| 1605 \| 0.6350 \| 0.5186 \| \| 0.1726 \| 4.0 \| 2140 \| 0.8171 \| 0.5081 \| \| 0.1269 \| 5.0 \| 2675 \| 0.8446 \| 0.5377 \| ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
Arczisan/mechanical-parts	Arczisan	2024-02-27T13:21:13Z	1	0	diffusers	[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "region:us" ]	text-to-image	2024-02-27T13:20:56Z	--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: "UNICODE\0\0a\0 \0g\0i\0r\0l\0 \0 \0<\0l\0o\0r\0a\0:\0R\0e\0e\0l\0_\0m\0e\0c\0h\0a\0n\0i\0c\0a\0l\0_\0p\0a\0r\0t\0s\0_\0v\0_\01\0_\03\0:\01\0>\0,\0 \0r\0e\0e\0l\0m\0e\0c\0h\0,\0 \0f\0i\0g\0h\0t\0i\0n\0g\0 \0,\0 \0g\0l\0o\0w\0i\0n\0g\0 \0e\0y\0e\0s\0,\0 \0s\0h\0o\0r\0t\0 \0h\0a\0i\0r\0,\0t\0o\0r\0n\0 \0t\0i\0g\0h\0t\0 \0s\0u\0p\0e\0r\0s\0u\0i\0t\0,\0 \0i\0n\0 \0a\0 \0d\0e\0s\0t\0r\0o\0y\0e\0d\0 \0c\0i\0t\0y\0,\0 \0s\0m\0o\0k\0e\0 \0a\0n\0d\0 \0f\0i\0r\0e\0,\0 \0g\0l\0o\0w\0i\0n\0g\0 \0p\0o\0w\0e\0r\0 \0a\0u\0r\0a\0,\0 \0d\0y\0n\0a\0m\0i\0c\0 \0p\0o\0s\0e\0,\0 \0d\0y\0n\0a\0m\0i\0c\0 \0v\0i\0e\0w\0" output: url: images/00123-2389661969.jpeg base_model: runwayml/stable-diffusion-v1-5 instance_prompt: null --- # Mechanical Parts <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Arczisan/mechanical-parts/tree/main) them in the Files & versions tab.
OwOpeepeepoopoo/easy_america5	OwOpeepeepoopoo	2024-02-27T13:18:50Z	4	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T12:57:07Z	--- 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. 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ryusangwon/5678_Llama-2-7b-hf	ryusangwon	2024-02-27T13:18:24Z	0	0	peft	[ "peft", "safetensors", "generated_from_trainer", "dataset:samsum", "base_model:meta-llama/Llama-2-7b-hf", "base_model:adapter:meta-llama/Llama-2-7b-hf", "region:us" ]	null	2024-02-27T13:18:20Z	--- base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer datasets: - samsum model-index: - name: 5678_Llama-2-7b-hf results: [] library_name: peft --- <!-- 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. --> # 5678_Llama-2-7b-hf This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the samsum dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 1 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - PEFT 0.4.0 - Transformers 4.36.2 - Pytorch 2.0.1+cu117 - Datasets 2.15.0 - Tokenizers 0.15.0
peldrak/segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline	peldrak	2024-02-27T13:17:44Z	188	0	transformers	[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:peldrak/segformer-b4-ade-512-512-finetuned-coastTrain", "base_model:finetune:peldrak/segformer-b4-ade-512-512-finetuned-coastTrain", "license:other", "endpoints_compatible", "region:us" ]	image-segmentation	2024-02-27T11:36:31Z	--- license: other base_model: peldrak/segformer-b4-ade-512-512-finetuned-coastTrain tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline 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. --> # segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline This model is a fine-tuned version of [peldrak/segformer-b4-ade-512-512-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b4-ade-512-512-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.1900 - Mean Iou: 0.8129 - Mean Accuracy: 0.8809 - Overall Accuracy: 0.9540 - Accuracy Water: 0.9875 - Accuracy Whitewater: 0.6312 - Accuracy Sediment: 0.9541 - Accuracy Other Natural Terrain: 0.8566 - Accuracy Vegetation: 0.8860 - Accuracy Development: 0.8526 - Accuracy Unknown: 0.9984 - Iou Water: 0.9631 - Iou Whitewater: 0.5490 - Iou Sediment: 0.8864 - Iou Other Natural Terrain: 0.7326 - Iou Vegetation: 0.8448 - Iou Development: 0.7176 - Iou Unknown: 0.9972 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 40 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Mean Iou \| Mean Accuracy \| Overall Accuracy \| Accuracy Water \| Accuracy Whitewater \| Accuracy Sediment \| Accuracy Other Natural Terrain \| Accuracy Vegetation \| Accuracy Development \| Accuracy Unknown \| Iou Water \| Iou Whitewater \| Iou Sediment \| Iou Other Natural Terrain \| Iou Vegetation \| Iou Development \| Iou Unknown \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:-------------:\|:----------------:\|:--------------:\|:-------------------:\|:-----------------:\|:------------------------------:\|:-------------------:\|:--------------------:\|:----------------:\|:---------:\|:--------------:\|:------------:\|:-------------------------:\|:--------------:\|:---------------:\|:-----------:\| \| 0.3829 \| 0.24 \| 20 \| 0.4153 \| 0.5484 \| 0.6468 \| 0.8693 \| 0.9547 \| 0.2281 \| 0.9398 \| 0.0617 \| 0.9459 \| 0.4008 \| 0.9963 \| 0.9176 \| 0.1120 \| 0.7770 \| 0.0612 \| 0.6193 \| 0.3634 \| 0.9882 \| \| 2.0682 \| 0.49 \| 40 \| 0.2991 \| 0.6099 \| 0.6956 \| 0.8939 \| 0.9735 \| 0.1187 \| 0.9464 \| 0.3054 \| 0.8869 \| 0.6447 \| 0.9938 \| 0.9316 \| 0.1123 \| 0.7992 \| 0.2941 \| 0.6709 \| 0.4733 \| 0.9879 \| \| 0.5418 \| 0.73 \| 60 \| 0.2615 \| 0.6607 \| 0.7312 \| 0.9192 \| 0.9684 \| 0.0686 \| 0.9512 \| 0.7257 \| 0.8597 \| 0.5526 \| 0.9920 \| 0.9252 \| 0.0665 \| 0.7986 \| 0.6036 \| 0.7632 \| 0.4800 \| 0.9881 \| \| 0.4389 \| 0.98 \| 80 \| 0.2421 \| 0.6515 \| 0.7159 \| 0.9201 \| 0.9756 \| 0.0911 \| 0.9662 \| 0.6066 \| 0.9156 \| 0.4593 \| 0.9971 \| 0.9426 \| 0.0898 \| 0.7943 \| 0.5455 \| 0.7796 \| 0.4163 \| 0.9926 \| \| 0.3756 \| 1.22 \| 100 \| 0.2204 \| 0.7025 \| 0.7747 \| 0.9295 \| 0.9931 \| 0.1656 \| 0.9258 \| 0.8460 \| 0.8142 \| 0.6870 \| 0.9912 \| 0.9124 \| 0.1560 \| 0.8274 \| 0.7147 \| 0.7806 \| 0.5365 \| 0.9896 \| \| 0.7675 \| 1.46 \| 120 \| 0.2169 \| 0.7061 \| 0.7876 \| 0.9184 \| 0.9774 \| 0.4127 \| 0.9614 \| 0.8133 \| 0.7635 \| 0.5874 \| 0.9976 \| 0.9489 \| 0.3887 \| 0.8088 \| 0.5972 \| 0.7210 \| 0.4855 \| 0.9928 \| \| 0.5434 \| 1.71 \| 140 \| 0.2232 \| 0.7104 \| 0.7782 \| 0.9308 \| 0.9820 \| 0.2467 \| 0.9620 \| 0.6425 \| 0.8970 \| 0.7228 \| 0.9943 \| 0.9529 \| 0.2410 \| 0.8545 \| 0.5718 \| 0.7752 \| 0.5848 \| 0.9925 \| \| 0.8975 \| 1.95 \| 160 \| 0.2187 \| 0.7209 \| 0.8231 \| 0.9231 \| 0.9757 \| 0.3658 \| 0.8885 \| 0.8665 \| 0.7545 \| 0.9165 \| 0.9945 \| 0.9473 \| 0.3471 \| 0.8241 \| 0.6442 \| 0.7331 \| 0.5589 \| 0.9917 \| \| 0.2799 \| 2.2 \| 180 \| 0.1662 \| 0.7404 \| 0.8029 \| 0.9418 \| 0.9706 \| 0.3506 \| 0.9555 \| 0.9022 \| 0.8947 \| 0.5523 \| 0.9946 \| 0.9425 \| 0.3293 \| 0.8567 \| 0.7286 \| 0.8378 \| 0.4949 \| 0.9928 \| \| 0.2132 \| 2.44 \| 200 \| 0.1616 \| 0.7714 \| 0.8442 \| 0.9443 \| 0.9777 \| 0.4621 \| 0.9536 \| 0.7886 \| 0.8819 \| 0.8492 \| 0.9963 \| 0.9435 \| 0.4076 \| 0.8578 \| 0.7267 \| 0.8215 \| 0.6498 \| 0.9930 \| \| 0.3068 \| 2.68 \| 220 \| 0.2055 \| 0.7345 \| 0.8090 \| 0.9318 \| 0.9870 \| 0.4136 \| 0.9517 \| 0.8730 \| 0.8080 \| 0.6367 \| 0.9931 \| 0.9370 \| 0.3753 \| 0.8034 \| 0.7027 \| 0.7935 \| 0.5387 \| 0.9909 \| \| 0.1822 \| 2.93 \| 240 \| 0.1367 \| 0.7984 \| 0.8640 \| 0.9531 \| 0.9886 \| 0.5028 \| 0.9106 \| 0.8899 \| 0.8992 \| 0.8593 \| 0.9977 \| 0.9499 \| 0.4617 \| 0.8667 \| 0.7874 \| 0.8617 \| 0.6675 \| 0.9937 \| \| 0.1504 \| 3.17 \| 260 \| 0.1548 \| 0.7794 \| 0.8446 \| 0.9471 \| 0.9830 \| 0.4763 \| 0.9544 \| 0.8496 \| 0.8731 \| 0.7774 \| 0.9983 \| 0.9482 \| 0.4416 \| 0.8516 \| 0.7572 \| 0.8427 \| 0.6226 \| 0.9917 \| \| 0.2699 \| 3.41 \| 280 \| 0.1543 \| 0.7508 \| 0.8024 \| 0.9475 \| 0.9889 \| 0.2791 \| 0.9421 \| 0.8336 \| 0.9211 \| 0.6552 \| 0.9967 \| 0.9484 \| 0.2719 \| 0.8647 \| 0.7216 \| 0.8500 \| 0.6056 \| 0.9938 \| \| 0.2272 \| 3.66 \| 300 \| 0.1547 \| 0.7618 \| 0.8232 \| 0.9490 \| 0.9868 \| 0.2820 \| 0.9403 \| 0.7567 \| 0.9193 \| 0.8808 \| 0.9963 \| 0.9565 \| 0.2766 \| 0.8735 \| 0.7173 \| 0.8339 \| 0.6810 \| 0.9938 \| \| 0.0938 \| 3.9 \| 320 \| 0.1776 \| 0.7615 \| 0.8290 \| 0.9415 \| 0.9889 \| 0.4229 \| 0.9468 \| 0.7605 \| 0.8807 \| 0.8081 \| 0.9953 \| 0.9545 \| 0.3961 \| 0.8519 \| 0.6753 \| 0.8080 \| 0.6522 \| 0.9929 \| \| 0.129 \| 4.15 \| 340 \| 0.1708 \| 0.7606 \| 0.8281 \| 0.9404 \| 0.9839 \| 0.5055 \| 0.9591 \| 0.8675 \| 0.8540 \| 0.6292 \| 0.9977 \| 0.9548 \| 0.4638 \| 0.8605 \| 0.6874 \| 0.8105 \| 0.5533 \| 0.9935 \| \| 0.1929 \| 4.39 \| 360 \| 0.1504 \| 0.7864 \| 0.8456 \| 0.9493 \| 0.9832 \| 0.4961 \| 0.9428 \| 0.8054 \| 0.9216 \| 0.7725 \| 0.9976 \| 0.9551 \| 0.4630 \| 0.8737 \| 0.7149 \| 0.8442 \| 0.6605 \| 0.9936 \| \| 0.1933 \| 4.63 \| 380 \| 0.1572 \| 0.7887 \| 0.8610 \| 0.9475 \| 0.9875 \| 0.4972 \| 0.9328 \| 0.8885 \| 0.8523 \| 0.8746 \| 0.9939 \| 0.9520 \| 0.4646 \| 0.8696 \| 0.7369 \| 0.8259 \| 0.6796 \| 0.9925 \| \| 0.0642 \| 4.88 \| 400 \| 0.1759 \| 0.7988 \| 0.8631 \| 0.9504 \| 0.9839 \| 0.5690 \| 0.9449 \| 0.7954 \| 0.9159 \| 0.8352 \| 0.9971 \| 0.9585 \| 0.5125 \| 0.8850 \| 0.7171 \| 0.8326 \| 0.6917 \| 0.9943 \| \| 0.1118 \| 5.12 \| 420 \| 0.1461 \| 0.8027 \| 0.8728 \| 0.9524 \| 0.9854 \| 0.5667 \| 0.9487 \| 0.8658 \| 0.8783 \| 0.8670 \| 0.9973 \| 0.9592 \| 0.4847 \| 0.8653 \| 0.7586 \| 0.8420 \| 0.7145 \| 0.9944 \| \| 0.1145 \| 5.37 \| 440 \| 0.1437 \| 0.7884 \| 0.8471 \| 0.9517 \| 0.9806 \| 0.4749 \| 0.9560 \| 0.9182 \| 0.8870 \| 0.7163 \| 0.9969 \| 0.9578 \| 0.4510 \| 0.8813 \| 0.7459 \| 0.8526 \| 0.6354 \| 0.9947 \| \| 0.2373 \| 5.61 \| 460 \| 0.1429 \| 0.8081 \| 0.8807 \| 0.9539 \| 0.9875 \| 0.6424 \| 0.9413 \| 0.8411 \| 0.9063 \| 0.8488 \| 0.9976 \| 0.9526 \| 0.5048 \| 0.8671 \| 0.7674 \| 0.8562 \| 0.7140 \| 0.9950 \| \| 0.0863 \| 5.85 \| 480 \| 0.1620 \| 0.7747 \| 0.8317 \| 0.9497 \| 0.9872 \| 0.3768 \| 0.9531 \| 0.8926 \| 0.8780 \| 0.7383 \| 0.9957 \| 0.9520 \| 0.3645 \| 0.8553 \| 0.7583 \| 0.8462 \| 0.6527 \| 0.9942 \| \| 0.1391 \| 6.1 \| 500 \| 0.1639 \| 0.7719 \| 0.8332 \| 0.9476 \| 0.9856 \| 0.3736 \| 0.9277 \| 0.7736 \| 0.9158 \| 0.8580 \| 0.9980 \| 0.9536 \| 0.3623 \| 0.8647 \| 0.7044 \| 0.8334 \| 0.6903 \| 0.9945 \| \| 0.0976 \| 6.34 \| 520 \| 0.1893 \| 0.7449 \| 0.8043 \| 0.9405 \| 0.9883 \| 0.3225 \| 0.9467 \| 0.8313 \| 0.8733 \| 0.6724 \| 0.9955 \| 0.9496 \| 0.3151 \| 0.8619 \| 0.6690 \| 0.8097 \| 0.6149 \| 0.9938 \| \| 0.1592 \| 6.59 \| 540 \| 0.1842 \| 0.7557 \| 0.8210 \| 0.9436 \| 0.9888 \| 0.3033 \| 0.9475 \| 0.8408 \| 0.8482 \| 0.8224 \| 0.9958 \| 0.9522 \| 0.2846 \| 0.8585 \| 0.7011 \| 0.8012 \| 0.6982 \| 0.9940 \| \| 0.2569 \| 6.83 \| 560 \| 0.1531 \| 0.7984 \| 0.8686 \| 0.9495 \| 0.9863 \| 0.5709 \| 0.9457 \| 0.8419 \| 0.8783 \| 0.8619 \| 0.9955 \| 0.9554 \| 0.5058 \| 0.8757 \| 0.7338 \| 0.8258 \| 0.6986 \| 0.9940 \| \| 0.1064 \| 7.07 \| 580 \| 0.1944 \| 0.7784 \| 0.8474 \| 0.9420 \| 0.9895 \| 0.5455 \| 0.9459 \| 0.7592 \| 0.8764 \| 0.8178 \| 0.9975 \| 0.9534 \| 0.5047 \| 0.8475 \| 0.6847 \| 0.8063 \| 0.6572 \| 0.9949 \| \| 0.0979 \| 7.32 \| 600 \| 0.1581 \| 0.7959 \| 0.8574 \| 0.9508 \| 0.9869 \| 0.5223 \| 0.9399 \| 0.8773 \| 0.8874 \| 0.7912 \| 0.9968 \| 0.9522 \| 0.4766 \| 0.8740 \| 0.7516 \| 0.8359 \| 0.6865 \| 0.9945 \| \| 0.045 \| 7.56 \| 620 \| 0.1962 \| 0.7990 \| 0.8655 \| 0.9479 \| 0.9801 \| 0.5896 \| 0.9347 \| 0.7952 \| 0.9054 \| 0.8546 \| 0.9988 \| 0.9485 \| 0.5253 \| 0.8764 \| 0.7167 \| 0.8204 \| 0.7117 \| 0.9938 \| \| 0.0495 \| 7.8 \| 640 \| 0.2135 \| 0.7824 \| 0.8541 \| 0.9428 \| 0.9834 \| 0.5986 \| 0.9555 \| 0.8005 \| 0.8692 \| 0.7725 \| 0.9987 \| 0.9550 \| 0.5221 \| 0.8447 \| 0.7026 \| 0.8075 \| 0.6500 \| 0.9949 \| \| 0.0389 \| 8.05 \| 660 \| 0.1860 \| 0.7856 \| 0.8503 \| 0.9469 \| 0.9809 \| 0.4908 \| 0.9358 \| 0.7910 \| 0.9012 \| 0.8538 \| 0.9985 \| 0.9547 \| 0.4522 \| 0.8837 \| 0.6847 \| 0.8158 \| 0.7134 \| 0.9946 \| \| 0.177 \| 8.29 \| 680 \| 0.2002 \| 0.7719 \| 0.8338 \| 0.9478 \| 0.9871 \| 0.3745 \| 0.9462 \| 0.7507 \| 0.9147 \| 0.8683 \| 0.9951 \| 0.9535 \| 0.3584 \| 0.8738 \| 0.7041 \| 0.8278 \| 0.6920 \| 0.9937 \| \| 0.0522 \| 8.54 \| 700 \| 0.1619 \| 0.7917 \| 0.8564 \| 0.9481 \| 0.9875 \| 0.5765 \| 0.9388 \| 0.8643 \| 0.8908 \| 0.7403 \| 0.9963 \| 0.9568 \| 0.5202 \| 0.8813 \| 0.7152 \| 0.8297 \| 0.6440 \| 0.9945 \| \| 0.066 \| 8.78 \| 720 \| 0.1800 \| 0.7782 \| 0.8539 \| 0.9451 \| 0.9850 \| 0.4766 \| 0.9503 \| 0.8770 \| 0.8304 \| 0.8615 \| 0.9963 \| 0.9597 \| 0.4398 \| 0.8674 \| 0.7291 \| 0.7992 \| 0.6581 \| 0.9945 \| \| 0.1114 \| 9.02 \| 740 \| 0.1692 \| 0.7867 \| 0.8517 \| 0.9476 \| 0.9880 \| 0.5068 \| 0.9485 \| 0.8157 \| 0.8789 \| 0.8257 \| 0.9982 \| 0.9569 \| 0.4758 \| 0.8787 \| 0.7079 \| 0.8205 \| 0.6723 \| 0.9951 \| \| 0.1906 \| 9.27 \| 760 \| 0.1724 \| 0.7929 \| 0.8617 \| 0.9490 \| 0.9820 \| 0.5359 \| 0.9464 \| 0.8073 \| 0.8928 \| 0.8697 \| 0.9978 \| 0.9572 \| 0.4821 \| 0.8714 \| 0.7178 \| 0.8284 \| 0.6980 \| 0.9956 \| \| 0.0562 \| 9.51 \| 780 \| 0.1984 \| 0.7811 \| 0.8494 \| 0.9449 \| 0.9807 \| 0.5865 \| 0.9549 \| 0.8392 \| 0.8888 \| 0.6984 \| 0.9969 \| 0.9569 \| 0.5050 \| 0.8750 \| 0.6786 \| 0.8232 \| 0.6337 \| 0.9952 \| \| 0.1104 \| 9.76 \| 800 \| 0.1972 \| 0.7978 \| 0.8687 \| 0.9469 \| 0.9855 \| 0.5906 \| 0.9419 \| 0.7758 \| 0.8914 \| 0.9000 \| 0.9955 \| 0.9556 \| 0.5334 \| 0.8733 \| 0.6863 \| 0.8178 \| 0.7237 \| 0.9945 \| \| 0.0451 \| 10.0 \| 820 \| 0.2123 \| 0.7769 \| 0.8455 \| 0.9415 \| 0.9821 \| 0.5810 \| 0.9500 \| 0.8132 \| 0.8747 \| 0.7191 \| 0.9984 \| 0.9537 \| 0.5241 \| 0.8658 \| 0.6691 \| 0.8074 \| 0.6231 \| 0.9949 \| \| 0.1426 \| 10.24 \| 840 \| 0.2210 \| 0.7989 \| 0.8745 \| 0.9465 \| 0.9800 \| 0.6316 \| 0.9435 \| 0.7712 \| 0.8897 \| 0.9072 \| 0.9983 \| 0.9562 \| 0.5525 \| 0.8783 \| 0.6823 \| 0.8131 \| 0.7147 \| 0.9951 \| \| 0.0683 \| 10.49 \| 860 \| 0.2162 \| 0.7964 \| 0.8677 \| 0.9473 \| 0.9802 \| 0.5774 \| 0.9515 \| 0.7715 \| 0.8902 \| 0.9058 \| 0.9974 \| 0.9549 \| 0.5202 \| 0.8777 \| 0.6901 \| 0.8156 \| 0.7210 \| 0.9954 \| \| 0.0758 \| 10.73 \| 880 \| 0.1898 \| 0.8005 \| 0.8774 \| 0.9468 \| 0.9863 \| 0.6471 \| 0.9326 \| 0.8057 \| 0.8757 \| 0.8960 \| 0.9984 \| 0.9595 \| 0.5466 \| 0.8796 \| 0.6810 \| 0.8067 \| 0.7347 \| 0.9957 \| \| 0.0496 \| 10.98 \| 900 \| 0.1919 \| 0.8019 \| 0.8738 \| 0.9469 \| 0.9794 \| 0.6404 \| 0.9636 \| 0.8149 \| 0.8670 \| 0.8526 \| 0.9984 \| 0.9598 \| 0.5598 \| 0.8726 \| 0.6949 \| 0.8065 \| 0.7236 \| 0.9959 \| \| 0.0329 \| 11.22 \| 920 \| 0.1862 \| 0.8004 \| 0.8689 \| 0.9469 \| 0.9891 \| 0.5888 \| 0.9460 \| 0.8303 \| 0.8556 \| 0.8746 \| 0.9977 \| 0.9594 \| 0.5378 \| 0.8816 \| 0.6882 \| 0.8003 \| 0.7395 \| 0.9957 \| \| 0.0808 \| 11.46 \| 940 \| 0.2000 \| 0.8016 \| 0.8730 \| 0.9485 \| 0.9868 \| 0.6599 \| 0.9461 \| 0.7912 \| 0.8998 \| 0.8292 \| 0.9977 \| 0.9617 \| 0.5578 \| 0.8811 \| 0.6872 \| 0.8208 \| 0.7070 \| 0.9960 \| \| 0.0492 \| 11.71 \| 960 \| 0.2148 \| 0.7983 \| 0.8672 \| 0.9466 \| 0.9895 \| 0.6154 \| 0.9459 \| 0.8051 \| 0.8765 \| 0.8410 \| 0.9968 \| 0.9589 \| 0.5439 \| 0.8735 \| 0.6870 \| 0.8079 \| 0.7210 \| 0.9959 \| \| 0.0629 \| 11.95 \| 980 \| 0.2277 \| 0.7941 \| 0.8637 \| 0.9456 \| 0.9842 \| 0.5803 \| 0.9556 \| 0.7909 \| 0.8695 \| 0.8680 \| 0.9973 \| 0.9604 \| 0.5260 \| 0.8744 \| 0.6751 \| 0.8009 \| 0.7260 \| 0.9958 \| \| 0.1419 \| 12.2 \| 1000 \| 0.2076 \| 0.7977 \| 0.8623 \| 0.9483 \| 0.9868 \| 0.5485 \| 0.9413 \| 0.8046 \| 0.8865 \| 0.8710 \| 0.9977 \| 0.9584 \| 0.5079 \| 0.8817 \| 0.6928 \| 0.8139 \| 0.7335 \| 0.9957 \| \| 0.153 \| 12.44 \| 1020 \| 0.1835 \| 0.7986 \| 0.8608 \| 0.9494 \| 0.9833 \| 0.5284 \| 0.9457 \| 0.8415 \| 0.8814 \| 0.8475 \| 0.9979 \| 0.9600 \| 0.4923 \| 0.8840 \| 0.6992 \| 0.8185 \| 0.7404 \| 0.9957 \| \| 0.0377 \| 12.68 \| 1040 \| 0.2033 \| 0.7894 \| 0.8567 \| 0.9476 \| 0.9826 \| 0.4861 \| 0.9596 \| 0.8731 \| 0.8436 \| 0.8548 \| 0.9971 \| 0.9603 \| 0.4626 \| 0.8669 \| 0.7198 \| 0.8113 \| 0.7089 \| 0.9957 \| \| 0.0474 \| 12.93 \| 1060 \| 0.2220 \| 0.7935 \| 0.8586 \| 0.9464 \| 0.9890 \| 0.5751 \| 0.9476 \| 0.7947 \| 0.8835 \| 0.8229 \| 0.9974 \| 0.9577 \| 0.5129 \| 0.8731 \| 0.6790 \| 0.8098 \| 0.7261 \| 0.9959 \| \| 1.1161 \| 13.17 \| 1080 \| 0.2110 \| 0.7992 \| 0.8716 \| 0.9463 \| 0.9821 \| 0.6330 \| 0.9614 \| 0.8127 \| 0.8632 \| 0.8502 \| 0.9983 \| 0.9585 \| 0.5585 \| 0.8827 \| 0.6897 \| 0.8012 \| 0.7076 \| 0.9962 \| \| 0.099 \| 13.41 \| 1100 \| 0.2123 \| 0.7984 \| 0.8743 \| 0.9472 \| 0.9868 \| 0.6128 \| 0.9379 \| 0.8127 \| 0.8678 \| 0.9040 \| 0.9983 \| 0.9570 \| 0.5382 \| 0.8878 \| 0.6926 \| 0.8075 \| 0.7095 \| 0.9962 \| \| 0.0588 \| 13.66 \| 1120 \| 0.1905 \| 0.8032 \| 0.8784 \| 0.9485 \| 0.9814 \| 0.6312 \| 0.9540 \| 0.8039 \| 0.8745 \| 0.9050 \| 0.9984 \| 0.9603 \| 0.5530 \| 0.8902 \| 0.6977 \| 0.8097 \| 0.7157 \| 0.9961 \| \| 0.0769 \| 13.9 \| 1140 \| 0.1758 \| 0.8017 \| 0.8647 \| 0.9500 \| 0.9864 \| 0.5469 \| 0.9429 \| 0.8562 \| 0.8735 \| 0.8484 \| 0.9985 \| 0.9568 \| 0.5034 \| 0.8897 \| 0.7119 \| 0.8164 \| 0.7372 \| 0.9962 \| \| 0.121 \| 14.15 \| 1160 \| 0.1858 \| 0.8027 \| 0.8701 \| 0.9499 \| 0.9816 \| 0.5560 \| 0.9518 \| 0.8267 \| 0.8789 \| 0.8986 \| 0.9969 \| 0.9578 \| 0.5182 \| 0.8862 \| 0.7072 \| 0.8231 \| 0.7310 \| 0.9956 \| \| 0.0663 \| 14.39 \| 1180 \| 0.2045 \| 0.7889 \| 0.8640 \| 0.9451 \| 0.9897 \| 0.5519 \| 0.9317 \| 0.8208 \| 0.8533 \| 0.9023 \| 0.9981 \| 0.9563 \| 0.4946 \| 0.8742 \| 0.6857 \| 0.8016 \| 0.7136 \| 0.9960 \| \| 0.0254 \| 14.63 \| 1200 \| 0.2105 \| 0.8003 \| 0.8676 \| 0.9474 \| 0.9816 \| 0.6103 \| 0.9605 \| 0.8074 \| 0.8776 \| 0.8377 \| 0.9982 \| 0.9611 \| 0.5442 \| 0.8794 \| 0.6838 \| 0.8091 \| 0.7281 \| 0.9962 \| \| 0.1533 \| 14.88 \| 1220 \| 0.2133 \| 0.7973 \| 0.8680 \| 0.9470 \| 0.9870 \| 0.6039 \| 0.9465 \| 0.8942 \| 0.8418 \| 0.8046 \| 0.9985 \| 0.9606 \| 0.5294 \| 0.8828 \| 0.6974 \| 0.8046 \| 0.7100 \| 0.9962 \| \| 0.0389 \| 15.12 \| 1240 \| 0.1854 \| 0.8032 \| 0.8722 \| 0.9489 \| 0.9893 \| 0.6311 \| 0.9484 \| 0.8297 \| 0.8745 \| 0.8342 \| 0.9984 \| 0.9600 \| 0.5509 \| 0.8777 \| 0.7049 \| 0.8183 \| 0.7145 \| 0.9962 \| \| 0.0361 \| 15.37 \| 1260 \| 0.1864 \| 0.7939 \| 0.8565 \| 0.9493 \| 0.9896 \| 0.5175 \| 0.9430 \| 0.8092 \| 0.8878 \| 0.8494 \| 0.9990 \| 0.9588 \| 0.4678 \| 0.8842 \| 0.6940 \| 0.8197 \| 0.7371 \| 0.9958 \| \| 0.0211 \| 15.61 \| 1280 \| 0.2172 \| 0.7962 \| 0.8720 \| 0.9454 \| 0.9853 \| 0.5900 \| 0.9531 \| 0.8542 \| 0.8295 \| 0.8943 \| 0.9973 \| 0.9621 \| 0.5328 \| 0.8799 \| 0.6886 \| 0.7885 \| 0.7253 \| 0.9963 \| \| 0.1093 \| 15.85 \| 1300 \| 0.1688 \| 0.8111 \| 0.8728 \| 0.9531 \| 0.9880 \| 0.5895 \| 0.9482 \| 0.8217 \| 0.9014 \| 0.8627 \| 0.9979 \| 0.9620 \| 0.5364 \| 0.8934 \| 0.7190 \| 0.8316 \| 0.7392 \| 0.9965 \| \| 0.0733 \| 16.1 \| 1320 \| 0.1827 \| 0.8126 \| 0.8845 \| 0.9515 \| 0.9869 \| 0.6553 \| 0.9503 \| 0.8784 \| 0.8587 \| 0.8627 \| 0.9990 \| 0.9608 \| 0.5654 \| 0.8826 \| 0.7278 \| 0.8258 \| 0.7300 \| 0.9960 \| \| 0.0708 \| 16.34 \| 1340 \| 0.1822 \| 0.8101 \| 0.8783 \| 0.9527 \| 0.9896 \| 0.6199 \| 0.9476 \| 0.8128 \| 0.8992 \| 0.8827 \| 0.9967 \| 0.9598 \| 0.5407 \| 0.8858 \| 0.7244 \| 0.8394 \| 0.7250 \| 0.9955 \| \| 0.0522 \| 16.59 \| 1360 \| 0.1780 \| 0.8087 \| 0.8748 \| 0.9518 \| 0.9864 \| 0.5917 \| 0.9509 \| 0.8650 \| 0.8725 \| 0.8599 \| 0.9974 \| 0.9615 \| 0.5372 \| 0.8861 \| 0.7247 \| 0.8282 \| 0.7270 \| 0.9959 \| \| 0.0453 \| 16.83 \| 1380 \| 0.1880 \| 0.8020 \| 0.8735 \| 0.9486 \| 0.9891 \| 0.5987 \| 0.9476 \| 0.8654 \| 0.8475 \| 0.8680 \| 0.9983 \| 0.9611 \| 0.5376 \| 0.8809 \| 0.7100 \| 0.8114 \| 0.7165 \| 0.9962 \| \| 0.0351 \| 17.07 \| 1400 \| 0.1885 \| 0.8045 \| 0.8758 \| 0.9502 \| 0.9880 \| 0.5929 \| 0.9435 \| 0.8644 \| 0.8591 \| 0.8846 \| 0.9982 \| 0.9608 \| 0.5261 \| 0.8841 \| 0.7161 \| 0.8189 \| 0.7295 \| 0.9962 \| \| 0.0629 \| 17.32 \| 1420 \| 0.1721 \| 0.8132 \| 0.8780 \| 0.9536 \| 0.9840 \| 0.6104 \| 0.9586 \| 0.8472 \| 0.8888 \| 0.8590 \| 0.9982 \| 0.9627 \| 0.5470 \| 0.8839 \| 0.7381 \| 0.8383 \| 0.7260 \| 0.9962 \| \| 0.0547 \| 17.56 \| 1440 \| 0.1993 \| 0.8025 \| 0.8734 \| 0.9478 \| 0.9877 \| 0.6203 \| 0.9555 \| 0.8655 \| 0.8430 \| 0.8431 \| 0.9987 \| 0.9599 \| 0.5544 \| 0.8666 \| 0.7186 \| 0.8101 \| 0.7115 \| 0.9963 \| \| 0.081 \| 17.8 \| 1460 \| 0.2054 \| 0.8034 \| 0.8702 \| 0.9493 \| 0.9892 \| 0.6097 \| 0.9505 \| 0.8118 \| 0.8823 \| 0.8502 \| 0.9976 \| 0.9603 \| 0.5416 \| 0.8769 \| 0.6996 \| 0.8204 \| 0.7283 \| 0.9964 \| \| 0.04 \| 18.05 \| 1480 \| 0.2196 \| 0.7915 \| 0.8572 \| 0.9459 \| 0.9893 \| 0.5738 \| 0.9500 \| 0.8183 \| 0.8706 \| 0.8003 \| 0.9979 \| 0.9586 \| 0.5216 \| 0.8679 \| 0.6870 \| 0.8109 \| 0.6976 \| 0.9966 \| \| 0.1213 \| 18.29 \| 1500 \| 0.2320 \| 0.7920 \| 0.8620 \| 0.9461 \| 0.9850 \| 0.5770 \| 0.9594 \| 0.8126 \| 0.8628 \| 0.8395 \| 0.9980 \| 0.9609 \| 0.5168 \| 0.8688 \| 0.6891 \| 0.8062 \| 0.7053 \| 0.9966 \| \| 0.0496 \| 18.54 \| 1520 \| 0.1928 \| 0.8065 \| 0.8745 \| 0.9503 \| 0.9842 \| 0.6020 \| 0.9449 \| 0.8562 \| 0.8736 \| 0.8619 \| 0.9984 \| 0.9612 \| 0.5367 \| 0.8886 \| 0.7098 \| 0.8177 \| 0.7348 \| 0.9966 \| \| 0.045 \| 18.78 \| 1540 \| 0.2075 \| 0.7988 \| 0.8787 \| 0.9460 \| 0.9839 \| 0.6246 \| 0.9374 \| 0.8428 \| 0.8457 \| 0.9183 \| 0.9984 \| 0.9607 \| 0.5522 \| 0.8790 \| 0.6941 \| 0.7982 \| 0.7107 \| 0.9968 \| \| 0.0317 \| 19.02 \| 1560 \| 0.1938 \| 0.8051 \| 0.8715 \| 0.9505 \| 0.9892 \| 0.5835 \| 0.9426 \| 0.8278 \| 0.8810 \| 0.8782 \| 0.9980 \| 0.9598 \| 0.5248 \| 0.8878 \| 0.7125 \| 0.8174 \| 0.7364 \| 0.9967 \| \| 0.0489 \| 19.27 \| 1580 \| 0.1844 \| 0.8074 \| 0.8792 \| 0.9500 \| 0.9847 \| 0.6251 \| 0.9529 \| 0.8445 \| 0.8628 \| 0.8855 \| 0.9991 \| 0.9613 \| 0.5493 \| 0.8817 \| 0.7121 \| 0.8174 \| 0.7331 \| 0.9966 \| \| 0.091 \| 19.51 \| 1600 \| 0.1976 \| 0.7907 \| 0.8478 \| 0.9495 \| 0.9910 \| 0.5186 \| 0.9449 \| 0.8258 \| 0.9006 \| 0.7553 \| 0.9986 \| 0.9563 \| 0.4818 \| 0.8703 \| 0.7123 \| 0.8358 \| 0.6818 \| 0.9967 \| \| 0.0308 \| 19.76 \| 1620 \| 0.1722 \| 0.8076 \| 0.8722 \| 0.9518 \| 0.9861 \| 0.5906 \| 0.9516 \| 0.8461 \| 0.8820 \| 0.8503 \| 0.9987 \| 0.9612 \| 0.5347 \| 0.8842 \| 0.7192 \| 0.8309 \| 0.7259 \| 0.9968 \| \| 0.231 \| 20.0 \| 1640 \| 0.1774 \| 0.8073 \| 0.8726 \| 0.9523 \| 0.9912 \| 0.5837 \| 0.9329 \| 0.8215 \| 0.8979 \| 0.8822 \| 0.9988 \| 0.9554 \| 0.5183 \| 0.8759 \| 0.7299 \| 0.8404 \| 0.7343 \| 0.9966 \| \| 0.0407 \| 20.24 \| 1660 \| 0.2232 \| 0.7988 \| 0.8750 \| 0.9464 \| 0.9844 \| 0.6060 \| 0.9575 \| 0.8624 \| 0.8267 \| 0.8891 \| 0.9989 \| 0.9609 \| 0.5377 \| 0.8691 \| 0.7052 \| 0.7968 \| 0.7252 \| 0.9964 \| \| 0.0303 \| 20.49 \| 1680 \| 0.2146 \| 0.8002 \| 0.8709 \| 0.9479 \| 0.9872 \| 0.5865 \| 0.9498 \| 0.8449 \| 0.8528 \| 0.8774 \| 0.9979 \| 0.9612 \| 0.5307 \| 0.8760 \| 0.7040 \| 0.8067 \| 0.7260 \| 0.9965 \| \| 0.0398 \| 20.73 \| 1700 \| 0.2119 \| 0.7977 \| 0.8754 \| 0.9465 \| 0.9858 \| 0.6453 \| 0.9460 \| 0.8314 \| 0.8575 \| 0.8631 \| 0.9989 \| 0.9632 \| 0.5460 \| 0.8824 \| 0.6865 \| 0.8007 \| 0.7087 \| 0.9967 \| \| 0.6198 \| 20.98 \| 1720 \| 0.2056 \| 0.7992 \| 0.8731 \| 0.9472 \| 0.9852 \| 0.6495 \| 0.9462 \| 0.8761 \| 0.8560 \| 0.8006 \| 0.9982 \| 0.9628 \| 0.5610 \| 0.8854 \| 0.6941 \| 0.8091 \| 0.6852 \| 0.9969 \| \| 0.0428 \| 21.22 \| 1740 \| 0.1978 \| 0.7970 \| 0.8670 \| 0.9483 \| 0.9843 \| 0.6512 \| 0.9546 \| 0.8829 \| 0.8734 \| 0.7246 \| 0.9979 \| 0.9629 \| 0.5622 \| 0.8830 \| 0.7036 \| 0.8269 \| 0.6435 \| 0.9967 \| \| 0.04 \| 21.46 \| 1760 \| 0.1939 \| 0.7945 \| 0.8675 \| 0.9469 \| 0.9860 \| 0.6371 \| 0.9491 \| 0.8376 \| 0.8718 \| 0.7922 \| 0.9988 \| 0.9619 \| 0.5536 \| 0.8799 \| 0.6914 \| 0.8183 \| 0.6592 \| 0.9968 \| \| 0.0279 \| 21.71 \| 1780 \| 0.2210 \| 0.7852 \| 0.8516 \| 0.9464 \| 0.9866 \| 0.5663 \| 0.9519 \| 0.8814 \| 0.8654 \| 0.7116 \| 0.9979 \| 0.9611 \| 0.5143 \| 0.8860 \| 0.6954 \| 0.8175 \| 0.6253 \| 0.9966 \| \| 0.0619 \| 21.95 \| 1800 \| 0.1971 \| 0.7930 \| 0.8654 \| 0.9484 \| 0.9867 \| 0.6116 \| 0.9498 \| 0.8739 \| 0.8676 \| 0.7698 \| 0.9981 \| 0.9627 \| 0.5353 \| 0.8885 \| 0.7080 \| 0.8258 \| 0.6342 \| 0.9967 \| \| 0.0203 \| 22.2 \| 1820 \| 0.1964 \| 0.7926 \| 0.8679 \| 0.9464 \| 0.9832 \| 0.6733 \| 0.9576 \| 0.8433 \| 0.8750 \| 0.7447 \| 0.9984 \| 0.9631 \| 0.5685 \| 0.8830 \| 0.6827 \| 0.8230 \| 0.6308 \| 0.9969 \| \| 0.0907 \| 22.44 \| 1840 \| 0.2107 \| 0.7875 \| 0.8587 \| 0.9458 \| 0.9896 \| 0.5721 \| 0.9506 \| 0.8118 \| 0.8643 \| 0.8239 \| 0.9988 \| 0.9596 \| 0.5017 \| 0.8729 \| 0.6816 \| 0.8105 \| 0.6896 \| 0.9969 \| \| 0.0378 \| 22.68 \| 1860 \| 0.2036 \| 0.8053 \| 0.8807 \| 0.9492 \| 0.9850 \| 0.6530 \| 0.9489 \| 0.8037 \| 0.8791 \| 0.8962 \| 0.9989 \| 0.9615 \| 0.5578 \| 0.8828 \| 0.6954 \| 0.8183 \| 0.7247 \| 0.9967 \| \| 0.081 \| 22.93 \| 1880 \| 0.2039 \| 0.7989 \| 0.8683 \| 0.9488 \| 0.9908 \| 0.5842 \| 0.9388 \| 0.8415 \| 0.8693 \| 0.8548 \| 0.9982 \| 0.9593 \| 0.5193 \| 0.8801 \| 0.7000 \| 0.8198 \| 0.7170 \| 0.9969 \| \| 0.0237 \| 23.17 \| 1900 \| 0.2002 \| 0.7899 \| 0.8571 \| 0.9471 \| 0.9876 \| 0.5706 \| 0.9510 \| 0.8307 \| 0.8760 \| 0.7854 \| 0.9982 \| 0.9612 \| 0.5203 \| 0.8814 \| 0.6841 \| 0.8224 \| 0.6634 \| 0.9968 \| \| 0.0528 \| 23.41 \| 1920 \| 0.2114 \| 0.7850 \| 0.8538 \| 0.9461 \| 0.9886 \| 0.5398 \| 0.9524 \| 0.8423 \| 0.8587 \| 0.7965 \| 0.9982 \| 0.9603 \| 0.4920 \| 0.8728 \| 0.6905 \| 0.8156 \| 0.6667 \| 0.9970 \| \| 0.0793 \| 23.66 \| 1940 \| 0.1825 \| 0.8003 \| 0.8694 \| 0.9498 \| 0.9888 \| 0.6138 \| 0.9454 \| 0.8474 \| 0.8786 \| 0.8130 \| 0.9990 \| 0.9604 \| 0.5439 \| 0.8800 \| 0.7102 \| 0.8346 \| 0.6757 \| 0.9969 \| \| 0.0288 \| 23.9 \| 1960 \| 0.1854 \| 0.8051 \| 0.8705 \| 0.9520 \| 0.9893 \| 0.6176 \| 0.9509 \| 0.8519 \| 0.8913 \| 0.7944 \| 0.9979 \| 0.9608 \| 0.5530 \| 0.8781 \| 0.7302 \| 0.8473 \| 0.6693 \| 0.9968 \| \| 0.0525 \| 24.15 \| 1980 \| 0.1603 \| 0.8141 \| 0.8846 \| 0.9550 \| 0.9864 \| 0.6848 \| 0.9472 \| 0.8581 \| 0.9083 \| 0.8084 \| 0.9990 \| 0.9620 \| 0.5691 \| 0.8876 \| 0.7440 \| 0.8616 \| 0.6776 \| 0.9966 \| \| 0.026 \| 24.39 \| 2000 \| 0.1684 \| 0.8068 \| 0.8752 \| 0.9532 \| 0.9877 \| 0.6538 \| 0.9479 \| 0.8936 \| 0.8893 \| 0.7554 \| 0.9989 \| 0.9616 \| 0.5547 \| 0.8856 \| 0.7362 \| 0.8538 \| 0.6586 \| 0.9969 \| \| 0.0397 \| 24.63 \| 2020 \| 0.1692 \| 0.8121 \| 0.8760 \| 0.9542 \| 0.9870 \| 0.5916 \| 0.9529 \| 0.8621 \| 0.8871 \| 0.8535 \| 0.9979 \| 0.9616 \| 0.5381 \| 0.8834 \| 0.7400 \| 0.8478 \| 0.7173 \| 0.9968 \| \| 0.4272 \| 24.88 \| 2040 \| 0.1785 \| 0.8101 \| 0.8749 \| 0.9535 \| 0.9868 \| 0.5751 \| 0.9539 \| 0.8895 \| 0.8697 \| 0.8520 \| 0.9975 \| 0.9633 \| 0.5204 \| 0.8832 \| 0.7380 \| 0.8374 \| 0.7316 \| 0.9966 \| \| 0.0399 \| 25.12 \| 2060 \| 0.1765 \| 0.8070 \| 0.8682 \| 0.9532 \| 0.9885 \| 0.5755 \| 0.9559 \| 0.8543 \| 0.8893 \| 0.8154 \| 0.9983 \| 0.9615 \| 0.5252 \| 0.8758 \| 0.7359 \| 0.8473 \| 0.7064 \| 0.9968 \| \| 0.0456 \| 25.37 \| 2080 \| 0.1777 \| 0.8060 \| 0.8668 \| 0.9535 \| 0.9900 \| 0.5873 \| 0.9487 \| 0.8418 \| 0.9061 \| 0.7955 \| 0.9983 \| 0.9605 \| 0.5270 \| 0.8821 \| 0.7299 \| 0.8526 \| 0.6928 \| 0.9969 \| \| 0.0414 \| 25.61 \| 2100 \| 0.1844 \| 0.8132 \| 0.8847 \| 0.9531 \| 0.9864 \| 0.6789 \| 0.9515 \| 0.8486 \| 0.8916 \| 0.8373 \| 0.9984 \| 0.9623 \| 0.5671 \| 0.8849 \| 0.7266 \| 0.8418 \| 0.7130 \| 0.9970 \| \| 0.0925 \| 25.85 \| 2120 \| 0.2120 \| 0.8035 \| 0.8663 \| 0.9521 \| 0.9886 \| 0.5885 \| 0.9500 \| 0.8118 \| 0.9077 \| 0.8193 \| 0.9982 \| 0.9607 \| 0.5215 \| 0.8832 \| 0.7125 \| 0.8402 \| 0.7097 \| 0.9970 \| \| 0.0443 \| 26.1 \| 2140 \| 0.1615 \| 0.8151 \| 0.8790 \| 0.9555 \| 0.9882 \| 0.5945 \| 0.9449 \| 0.8779 \| 0.8874 \| 0.8610 \| 0.9992 \| 0.9603 \| 0.5309 \| 0.8871 \| 0.7511 \| 0.8517 \| 0.7281 \| 0.9964 \| \| 0.0728 \| 26.34 \| 2160 \| 0.1701 \| 0.8091 \| 0.8771 \| 0.9534 \| 0.9872 \| 0.6244 \| 0.9493 \| 0.8818 \| 0.8816 \| 0.8164 \| 0.9989 \| 0.9624 \| 0.5469 \| 0.8858 \| 0.7362 \| 0.8478 \| 0.6876 \| 0.9968 \| \| 0.0484 \| 26.59 \| 2180 \| 0.1720 \| 0.8061 \| 0.8707 \| 0.9530 \| 0.9895 \| 0.6110 \| 0.9487 \| 0.8831 \| 0.8852 \| 0.7787 \| 0.9987 \| 0.9615 \| 0.5429 \| 0.8814 \| 0.7374 \| 0.8496 \| 0.6727 \| 0.9969 \| \| 0.027 \| 26.83 \| 2200 \| 0.1728 \| 0.8060 \| 0.8754 \| 0.9525 \| 0.9879 \| 0.6263 \| 0.9498 \| 0.8718 \| 0.8823 \| 0.8111 \| 0.9983 \| 0.9620 \| 0.5489 \| 0.8825 \| 0.7351 \| 0.8472 \| 0.6694 \| 0.9970 \| \| 0.0465 \| 27.07 \| 2220 \| 0.1763 \| 0.8075 \| 0.8751 \| 0.9534 \| 0.9875 \| 0.6402 \| 0.9496 \| 0.8776 \| 0.8938 \| 0.7791 \| 0.9981 \| 0.9623 \| 0.5514 \| 0.8842 \| 0.7366 \| 0.8533 \| 0.6675 \| 0.9970 \| \| 0.0213 \| 27.32 \| 2240 \| 0.1740 \| 0.8085 \| 0.8743 \| 0.9538 \| 0.9869 \| 0.6184 \| 0.9501 \| 0.8787 \| 0.8917 \| 0.7963 \| 0.9983 \| 0.9632 \| 0.5446 \| 0.8852 \| 0.7370 \| 0.8523 \| 0.6799 \| 0.9971 \| \| 0.022 \| 27.56 \| 2260 \| 0.1923 \| 0.7998 \| 0.8675 \| 0.9508 \| 0.9863 \| 0.5850 \| 0.9506 \| 0.8669 \| 0.8777 \| 0.8084 \| 0.9979 \| 0.9613 \| 0.5253 \| 0.8839 \| 0.7155 \| 0.8387 \| 0.6769 \| 0.9970 \| \| 0.0311 \| 27.8 \| 2280 \| 0.1871 \| 0.8005 \| 0.8657 \| 0.9518 \| 0.9877 \| 0.5896 \| 0.9482 \| 0.8699 \| 0.8900 \| 0.7763 \| 0.9980 \| 0.9612 \| 0.5235 \| 0.8837 \| 0.7229 \| 0.8452 \| 0.6701 \| 0.9970 \| \| 0.0281 \| 28.05 \| 2300 \| 0.1984 \| 0.7970 \| 0.8665 \| 0.9490 \| 0.9881 \| 0.6233 \| 0.9441 \| 0.9007 \| 0.8659 \| 0.7451 \| 0.9984 \| 0.9614 \| 0.5465 \| 0.8850 \| 0.7081 \| 0.8310 \| 0.6496 \| 0.9971 \| \| 0.029 \| 28.29 \| 2320 \| 0.1929 \| 0.8018 \| 0.8684 \| 0.9508 \| 0.9890 \| 0.6266 \| 0.9484 \| 0.8783 \| 0.8813 \| 0.7572 \| 0.9981 \| 0.9612 \| 0.5522 \| 0.8820 \| 0.7180 \| 0.8409 \| 0.6616 \| 0.9970 \| \| 0.0205 \| 28.54 \| 2340 \| 0.1939 \| 0.8127 \| 0.8877 \| 0.9536 \| 0.9857 \| 0.6927 \| 0.9459 \| 0.8321 \| 0.9031 \| 0.8553 \| 0.9989 \| 0.9628 \| 0.5574 \| 0.8940 \| 0.7233 \| 0.8410 \| 0.7133 \| 0.9969 \| \| 0.1185 \| 28.78 \| 2360 \| 0.2147 \| 0.7963 \| 0.8662 \| 0.9476 \| 0.9888 \| 0.5806 \| 0.9517 \| 0.8657 \| 0.8458 \| 0.8323 \| 0.9987 \| 0.9615 \| 0.5186 \| 0.8772 \| 0.6987 \| 0.8088 \| 0.7122 \| 0.9971 \| \| 0.0848 \| 29.02 \| 2380 \| 0.1978 \| 0.8047 \| 0.8712 \| 0.9510 \| 0.9884 \| 0.5966 \| 0.9504 \| 0.8398 \| 0.8784 \| 0.8459 \| 0.9988 \| 0.9618 \| 0.5329 \| 0.8799 \| 0.7125 \| 0.8299 \| 0.7184 \| 0.9972 \| \| 0.028 \| 29.27 \| 2400 \| 0.2065 \| 0.8000 \| 0.8675 \| 0.9497 \| 0.9878 \| 0.6095 \| 0.9561 \| 0.8780 \| 0.8647 \| 0.7781 \| 0.9983 \| 0.9629 \| 0.5428 \| 0.8784 \| 0.7121 \| 0.8296 \| 0.6767 \| 0.9973 \| \| 0.0232 \| 29.51 \| 2420 \| 0.1912 \| 0.8063 \| 0.8750 \| 0.9520 \| 0.9887 \| 0.6177 \| 0.9491 \| 0.8746 \| 0.8742 \| 0.8221 \| 0.9983 \| 0.9631 \| 0.5401 \| 0.8824 \| 0.7242 \| 0.8371 \| 0.7000 \| 0.9973 \| \| 0.0241 \| 29.76 \| 2440 \| 0.1768 \| 0.8095 \| 0.8797 \| 0.9525 \| 0.9871 \| 0.6426 \| 0.9506 \| 0.8691 \| 0.8781 \| 0.8319 \| 0.9986 \| 0.9637 \| 0.5552 \| 0.8871 \| 0.7228 \| 0.8388 \| 0.7015 \| 0.9971 \| \| 0.0249 \| 30.0 \| 2460 \| 0.1885 \| 0.8051 \| 0.8734 \| 0.9518 \| 0.9885 \| 0.6096 \| 0.9517 \| 0.8740 \| 0.8714 \| 0.8203 \| 0.9986 \| 0.9631 \| 0.5348 \| 0.8836 \| 0.7230 \| 0.8353 \| 0.6989 \| 0.9970 \| \| 0.0314 \| 30.24 \| 2480 \| 0.1853 \| 0.8046 \| 0.8698 \| 0.9521 \| 0.9882 \| 0.6049 \| 0.9524 \| 0.8782 \| 0.8786 \| 0.7873 \| 0.9989 \| 0.9630 \| 0.5373 \| 0.8846 \| 0.7241 \| 0.8409 \| 0.6853 \| 0.9968 \| \| 0.045 \| 30.49 \| 2500 \| 0.1810 \| 0.8134 \| 0.8792 \| 0.9542 \| 0.9871 \| 0.6099 \| 0.9502 \| 0.8672 \| 0.8840 \| 0.8573 \| 0.9986 \| 0.9621 \| 0.5421 \| 0.8876 \| 0.7371 \| 0.8430 \| 0.7251 \| 0.9971 \| \| 0.0261 \| 30.73 \| 2520 \| 0.1893 \| 0.8172 \| 0.8897 \| 0.9548 \| 0.9847 \| 0.6630 \| 0.9480 \| 0.8516 \| 0.8922 \| 0.8897 \| 0.9988 \| 0.9619 \| 0.5530 \| 0.8890 \| 0.7377 \| 0.8441 \| 0.7375 \| 0.9972 \| \| 0.0175 \| 30.98 \| 2540 \| 0.1904 \| 0.8155 \| 0.8830 \| 0.9553 \| 0.9866 \| 0.6192 \| 0.9535 \| 0.8526 \| 0.8915 \| 0.8791 \| 0.9983 \| 0.9635 \| 0.5371 \| 0.8874 \| 0.7404 \| 0.8472 \| 0.7359 \| 0.9972 \| \| 0.0326 \| 31.22 \| 2560 \| 0.1888 \| 0.8126 \| 0.8811 \| 0.9535 \| 0.9875 \| 0.6216 \| 0.9501 \| 0.8821 \| 0.8722 \| 0.8559 \| 0.9985 \| 0.9627 \| 0.5421 \| 0.8861 \| 0.7326 \| 0.8392 \| 0.7283 \| 0.9970 \| \| 0.0854 \| 31.46 \| 2580 \| 0.1981 \| 0.8043 \| 0.8676 \| 0.9523 \| 0.9893 \| 0.5619 \| 0.9525 \| 0.8688 \| 0.8749 \| 0.8275 \| 0.9983 \| 0.9613 \| 0.5166 \| 0.8798 \| 0.7305 \| 0.8396 \| 0.7054 \| 0.9969 \| \| 0.0313 \| 31.71 \| 2600 \| 0.2039 \| 0.8109 \| 0.8805 \| 0.9522 \| 0.9873 \| 0.6476 \| 0.9539 \| 0.8586 \| 0.8781 \| 0.8404 \| 0.9978 \| 0.9621 \| 0.5616 \| 0.8829 \| 0.7235 \| 0.8372 \| 0.7118 \| 0.9968 \| \| 0.0228 \| 31.95 \| 2620 \| 0.2029 \| 0.8079 \| 0.8795 \| 0.9515 \| 0.9876 \| 0.6392 \| 0.9510 \| 0.8668 \| 0.8685 \| 0.8450 \| 0.9988 \| 0.9620 \| 0.5487 \| 0.8832 \| 0.7207 \| 0.8320 \| 0.7118 \| 0.9970 \| \| 0.0301 \| 32.2 \| 2640 \| 0.2147 \| 0.8037 \| 0.8739 \| 0.9499 \| 0.9872 \| 0.6339 \| 0.9546 \| 0.8759 \| 0.8607 \| 0.8062 \| 0.9988 \| 0.9620 \| 0.5508 \| 0.8801 \| 0.7129 \| 0.8259 \| 0.6974 \| 0.9971 \| \| 0.0312 \| 32.44 \| 2660 \| 0.2114 \| 0.8016 \| 0.8718 \| 0.9496 \| 0.9876 \| 0.6201 \| 0.9532 \| 0.8755 \| 0.8584 \| 0.8090 \| 0.9990 \| 0.9616 \| 0.5405 \| 0.8791 \| 0.7107 \| 0.8252 \| 0.6969 \| 0.9969 \| \| 0.0427 \| 32.68 \| 2680 \| 0.2085 \| 0.8015 \| 0.8694 \| 0.9506 \| 0.9873 \| 0.6277 \| 0.9543 \| 0.8743 \| 0.8767 \| 0.7668 \| 0.9986 \| 0.9622 \| 0.5421 \| 0.8828 \| 0.7131 \| 0.8356 \| 0.6777 \| 0.9970 \| \| 0.0398 \| 32.93 \| 2700 \| 0.2139 \| 0.8062 \| 0.8766 \| 0.9507 \| 0.9850 \| 0.6461 \| 0.9581 \| 0.8557 \| 0.8761 \| 0.8176 \| 0.9976 \| 0.9612 \| 0.5560 \| 0.8817 \| 0.7157 \| 0.8308 \| 0.7017 \| 0.9967 \| \| 0.0274 \| 33.17 \| 2720 \| 0.2093 \| 0.8094 \| 0.8806 \| 0.9516 \| 0.9847 \| 0.6481 \| 0.9555 \| 0.8572 \| 0.8764 \| 0.8440 \| 0.9980 \| 0.9615 \| 0.5583 \| 0.8860 \| 0.7187 \| 0.8323 \| 0.7124 \| 0.9969 \| \| 0.0309 \| 33.41 \| 2740 \| 0.2170 \| 0.8068 \| 0.8833 \| 0.9505 \| 0.9840 \| 0.6723 \| 0.9536 \| 0.8855 \| 0.8602 \| 0.8290 \| 0.9984 \| 0.9632 \| 0.5588 \| 0.8902 \| 0.7108 \| 0.8261 \| 0.7013 \| 0.9969 \| \| 0.0395 \| 33.66 \| 2760 \| 0.2031 \| 0.8060 \| 0.8787 \| 0.9513 \| 0.9879 \| 0.6361 \| 0.9472 \| 0.8725 \| 0.8689 \| 0.8401 \| 0.9986 \| 0.9624 \| 0.5421 \| 0.8871 \| 0.7157 \| 0.8327 \| 0.7048 \| 0.9970 \| \| 0.0298 \| 33.9 \| 2780 \| 0.1892 \| 0.8082 \| 0.8804 \| 0.9522 \| 0.9868 \| 0.6612 \| 0.9493 \| 0.8657 \| 0.8823 \| 0.8189 \| 0.9987 \| 0.9630 \| 0.5586 \| 0.8887 \| 0.7184 \| 0.8409 \| 0.6906 \| 0.9970 \| \| 0.0313 \| 34.15 \| 2800 \| 0.1960 \| 0.8064 \| 0.8772 \| 0.9522 \| 0.9881 \| 0.6294 \| 0.9442 \| 0.8685 \| 0.8810 \| 0.8310 \| 0.9984 \| 0.9623 \| 0.5435 \| 0.8893 \| 0.7198 \| 0.8407 \| 0.6925 \| 0.9970 \| \| 0.0249 \| 34.39 \| 2820 \| 0.1958 \| 0.8086 \| 0.8772 \| 0.9527 \| 0.9879 \| 0.6079 \| 0.9521 \| 0.8570 \| 0.8777 \| 0.8597 \| 0.9980 \| 0.9625 \| 0.5362 \| 0.8852 \| 0.7255 \| 0.8383 \| 0.7154 \| 0.9969 \| \| 0.0959 \| 34.63 \| 2840 \| 0.2022 \| 0.8077 \| 0.8757 \| 0.9520 \| 0.9877 \| 0.6105 \| 0.9548 \| 0.8691 \| 0.8697 \| 0.8401 \| 0.9981 \| 0.9627 \| 0.5434 \| 0.8838 \| 0.7228 \| 0.8347 \| 0.7099 \| 0.9969 \| \| 0.0195 \| 34.88 \| 2860 \| 0.1878 \| 0.8089 \| 0.8758 \| 0.9526 \| 0.9884 \| 0.6187 \| 0.9483 \| 0.8695 \| 0.8809 \| 0.8262 \| 0.9985 \| 0.9624 \| 0.5476 \| 0.8880 \| 0.7218 \| 0.8411 \| 0.7046 \| 0.9969 \| \| 0.0144 \| 35.12 \| 2880 \| 0.1991 \| 0.8099 \| 0.8809 \| 0.9523 \| 0.9851 \| 0.6489 \| 0.9545 \| 0.8723 \| 0.8751 \| 0.8324 \| 0.9984 \| 0.9637 \| 0.5606 \| 0.8891 \| 0.7197 \| 0.8377 \| 0.7017 \| 0.9969 \| \| 0.0316 \| 35.37 \| 2900 \| 0.2001 \| 0.8057 \| 0.8747 \| 0.9515 \| 0.9883 \| 0.6212 \| 0.9501 \| 0.8815 \| 0.8704 \| 0.8137 \| 0.9979 \| 0.9625 \| 0.5443 \| 0.8877 \| 0.7179 \| 0.8351 \| 0.6955 \| 0.9968 \| \| 0.0363 \| 35.61 \| 2920 \| 0.2015 \| 0.8048 \| 0.8718 \| 0.9516 \| 0.9887 \| 0.6135 \| 0.9523 \| 0.8771 \| 0.8752 \| 0.7983 \| 0.9977 \| 0.9624 \| 0.5432 \| 0.8856 \| 0.7195 \| 0.8383 \| 0.6878 \| 0.9968 \| \| 0.1011 \| 35.85 \| 2940 \| 0.1922 \| 0.8089 \| 0.8777 \| 0.9529 \| 0.9882 \| 0.6236 \| 0.9487 \| 0.8627 \| 0.8810 \| 0.8407 \| 0.9989 \| 0.9621 \| 0.5429 \| 0.8874 \| 0.7256 \| 0.8414 \| 0.7057 \| 0.9970 \| \| 0.0455 \| 36.1 \| 2960 \| 0.2002 \| 0.8059 \| 0.8733 \| 0.9519 \| 0.9888 \| 0.6067 \| 0.9517 \| 0.8642 \| 0.8746 \| 0.8285 \| 0.9986 \| 0.9621 \| 0.5401 \| 0.8853 \| 0.7211 \| 0.8371 \| 0.6988 \| 0.9970 \| \| 0.0289 \| 36.34 \| 2980 \| 0.1995 \| 0.8096 \| 0.8805 \| 0.9521 \| 0.9879 \| 0.6477 \| 0.9501 \| 0.8688 \| 0.8739 \| 0.8365 \| 0.9985 \| 0.9625 \| 0.5577 \| 0.8869 \| 0.7201 \| 0.8362 \| 0.7069 \| 0.9971 \| \| 0.091 \| 36.59 \| 3000 \| 0.1941 \| 0.8124 \| 0.8867 \| 0.9529 \| 0.9882 \| 0.6654 \| 0.9482 \| 0.8641 \| 0.8745 \| 0.8678 \| 0.9987 \| 0.9627 \| 0.5555 \| 0.8877 \| 0.7251 \| 0.8370 \| 0.7217 \| 0.9972 \| \| 0.0635 \| 36.83 \| 3020 \| 0.1858 \| 0.8132 \| 0.8837 \| 0.9535 \| 0.9875 \| 0.6478 \| 0.9525 \| 0.8476 \| 0.8842 \| 0.8673 \| 0.9988 \| 0.9632 \| 0.5549 \| 0.8876 \| 0.7265 \| 0.8408 \| 0.7220 \| 0.9972 \| \| 0.0244 \| 37.07 \| 3040 \| 0.1862 \| 0.8109 \| 0.8797 \| 0.9533 \| 0.9875 \| 0.6420 \| 0.9502 \| 0.8755 \| 0.8815 \| 0.8221 \| 0.9987 \| 0.9633 \| 0.5540 \| 0.8906 \| 0.7254 \| 0.8422 \| 0.7034 \| 0.9972 \| \| 0.0265 \| 37.32 \| 3060 \| 0.1864 \| 0.8146 \| 0.8844 \| 0.9543 \| 0.9867 \| 0.6543 \| 0.9477 \| 0.8679 \| 0.8891 \| 0.8461 \| 0.9987 \| 0.9633 \| 0.5578 \| 0.8936 \| 0.7306 \| 0.8449 \| 0.7146 \| 0.9972 \| \| 0.0344 \| 37.56 \| 3080 \| 0.1838 \| 0.8162 \| 0.8873 \| 0.9547 \| 0.9862 \| 0.6641 \| 0.9524 \| 0.8551 \| 0.8905 \| 0.8644 \| 0.9988 \| 0.9636 \| 0.5604 \| 0.8903 \| 0.7340 \| 0.8471 \| 0.7211 \| 0.9972 \| \| 0.0267 \| 37.8 \| 3100 \| 0.1903 \| 0.8137 \| 0.8841 \| 0.9540 \| 0.9870 \| 0.6543 \| 0.9499 \| 0.8745 \| 0.8841 \| 0.8409 \| 0.9983 \| 0.9633 \| 0.5565 \| 0.8921 \| 0.7309 \| 0.8444 \| 0.7119 \| 0.9971 \| \| 0.3041 \| 38.05 \| 3120 \| 0.1891 \| 0.8051 \| 0.8701 \| 0.9526 \| 0.9903 \| 0.5815 \| 0.9478 \| 0.8685 \| 0.8792 \| 0.8248 \| 0.9985 \| 0.9604 \| 0.5197 \| 0.8850 \| 0.7270 \| 0.8415 \| 0.7051 \| 0.9969 \| \| 0.0272 \| 38.29 \| 3140 \| 0.1971 \| 0.8077 \| 0.8754 \| 0.9522 \| 0.9877 \| 0.6189 \| 0.9552 \| 0.8747 \| 0.8726 \| 0.8205 \| 0.9983 \| 0.9628 \| 0.5447 \| 0.8851 \| 0.7236 \| 0.8373 \| 0.7036 \| 0.9971 \| \| 0.063 \| 38.54 \| 3160 \| 0.1888 \| 0.8125 \| 0.8786 \| 0.9542 \| 0.9881 \| 0.6109 \| 0.9529 \| 0.8503 \| 0.8879 \| 0.8613 \| 0.9986 \| 0.9625 \| 0.5407 \| 0.8857 \| 0.7339 \| 0.8452 \| 0.7224 \| 0.9971 \| \| 0.0527 \| 38.78 \| 3180 \| 0.1899 \| 0.8121 \| 0.8842 \| 0.9531 \| 0.9865 \| 0.6598 \| 0.9521 \| 0.8748 \| 0.8761 \| 0.8415 \| 0.9986 \| 0.9634 \| 0.5575 \| 0.8896 \| 0.7261 \| 0.8392 \| 0.7117 \| 0.9972 \| \| 0.0465 \| 39.02 \| 3200 \| 0.1947 \| 0.8108 \| 0.8793 \| 0.9532 \| 0.9881 \| 0.6358 \| 0.9517 \| 0.8722 \| 0.8808 \| 0.8284 \| 0.9979 \| 0.9626 \| 0.5509 \| 0.8879 \| 0.7275 \| 0.8422 \| 0.7075 \| 0.9970 \| \| 0.0305 \| 39.27 \| 3220 \| 0.1884 \| 0.8118 \| 0.8806 \| 0.9538 \| 0.9888 \| 0.6265 \| 0.9468 \| 0.8655 \| 0.8838 \| 0.8547 \| 0.9983 \| 0.9620 \| 0.5422 \| 0.8885 \| 0.7313 \| 0.8439 \| 0.7177 \| 0.9971 \| \| 0.0167 \| 39.51 \| 3240 \| 0.1935 \| 0.8111 \| 0.8805 \| 0.9533 \| 0.9879 \| 0.6352 \| 0.9505 \| 0.8737 \| 0.8794 \| 0.8383 \| 0.9981 \| 0.9629 \| 0.5473 \| 0.8891 \| 0.7279 \| 0.8414 \| 0.7120 \| 0.9971 \| \| 0.0507 \| 39.76 \| 3260 \| 0.1888 \| 0.8109 \| 0.8783 \| 0.9535 \| 0.9883 \| 0.6259 \| 0.9528 \| 0.8630 \| 0.8829 \| 0.8363 \| 0.9986 \| 0.9625 \| 0.5459 \| 0.8854 \| 0.7306 \| 0.8435 \| 0.7110 \| 0.9971 \| \| 0.0354 \| 40.0 \| 3280 \| 0.1900 \| 0.8129 \| 0.8809 \| 0.9540 \| 0.9875 \| 0.6312 \| 0.9541 \| 0.8566 \| 0.8860 \| 0.8526 \| 0.9984 \| 0.9631 \| 0.5490 \| 0.8864 \| 0.7326 \| 0.8448 \| 0.7176 \| 0.9972 \| ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1
anoop3/autotrain-be1zs-exv75	anoop3	2024-02-27T13:06:28Z	1	0	diffusers	[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]	text-to-image	2024-02-27T13:06:25Z	--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: moni female tags: - text-to-image - diffusers - autotrain inference: true --- # DreamBooth trained by AutoTrain Text encoder was not trained.
zzttbrdd/gemcy_v1_2	zzttbrdd	2024-02-27T13:06:24Z	112	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T13:04:22Z	--- 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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ibunescu/Phi-2_GDPR_10_3e	ibunescu	2024-02-27T13:03:12Z	48	0	transformers	[ "transformers", "safetensors", "phi", "text-generation", "custom_code", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T12:59:26Z	--- 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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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. 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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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zzttbrdd/gemcy_v1_1	zzttbrdd	2024-02-27T13:01:50Z	113	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T12:59:53Z	--- 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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Neomedallion/dqn-SpaceInvadersNoFrameskip-v4	Neomedallion	2024-02-27T12:59:20Z	0	0	stable-baselines3	[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]	reinforcement-learning	2023-05-05T07:14:06Z	--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 metrics: - type: mean_reward value: 329.00 +/- 157.97 name: mean_reward verified: false --- # DQN Agent playing SpaceInvadersNoFrameskip-v4 This is a trained model of a DQN agent playing SpaceInvadersNoFrameskip-v4 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Neomedallion -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Neomedallion -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga Neomedallion ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000.0), ('optimize_memory_usage', False), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ``` # Environment Arguments ```python {'render_mode': 'rgb_array'} ```
FKunneman/distilbert-base-uncased-finetuned-cola	FKunneman	2024-02-27T12:58:16Z	9	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T10:58:00Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola 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. --> # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8294 - Matthews Correlation: 0.5466 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Matthews Correlation \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------------------:\| \| 0.5181 \| 1.0 \| 535 \| 0.4541 \| 0.4504 \| \| 0.3411 \| 2.0 \| 1070 \| 0.4744 \| 0.5094 \| \| 0.2321 \| 3.0 \| 1605 \| 0.6309 \| 0.5391 \| \| 0.1737 \| 4.0 \| 2140 \| 0.7876 \| 0.5369 \| \| 0.1265 \| 5.0 \| 2675 \| 0.8294 \| 0.5466 \| ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
ibunescu/Phi-2_GDPR_9_3e_adapter	ibunescu	2024-02-27T12:57:51Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-02-27T11:09:12Z	--- 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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mohammadhabp/flan-t5-small-esnli-lora	mohammadhabp	2024-02-27T12:52:27Z	4	0	peft	[ "peft", "safetensors", "generated_from_trainer", "base_model:google/flan-t5-base", "base_model:adapter:google/flan-t5-base", "license:apache-2.0", "region:us" ]	null	2024-02-25T15:02:02Z	--- license: apache-2.0 library_name: peft tags: - generated_from_trainer metrics: - rouge - f1 base_model: google/flan-t5-base model-index: - name: flan-t5-small-esnli-lora 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. --> # flan-t5-small-esnli-lora This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.6258 - Rouge1: 0.6257 - Rouge2: 0.4156 - Rougel: 0.5682 - F1: 0.8850 ## 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: 0.001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| F1 \| \|:-------------:\|:-----:\|:-----:\|:---------------:\|:------:\|:------:\|:------:\|:------:\| \| 1.1793 \| 0.25 \| 8584 \| 1.7215 \| 0.6161 \| 0.4037 \| 0.5577 \| 0.8738 \| \| 1.1408 \| 0.5 \| 17168 \| 1.6903 \| 0.6194 \| 0.4096 \| 0.5615 \| 0.8730 \| \| 1.1122 \| 0.75 \| 25752 \| 1.6155 \| 0.6267 \| 0.4179 \| 0.5693 \| 0.8832 \| \| 1.0929 \| 1.0 \| 34336 \| 1.6258 \| 0.6257 \| 0.4156 \| 0.5682 \| 0.8850 \| ### Framework versions - PEFT 0.8.2 - Transformers 4.38.1 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1
jayakushwaha/my-favourite-character	jayakushwaha	2024-02-27T12:50:21Z	0	0	null	[ "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2024-02-27T12:48:17Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Favourite-Character Dreambooth model trained by jayakushwaha following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: 0206CS221107 Sample pictures of this concept: ![0](https://huggingface.co/jayakushwaha/my-favourite-character/resolve/main/sample_images/Screenshot_(23).png)
Ayus077BCT014Bhandari/vartat5-using-100K-plus-24	Ayus077BCT014Bhandari	2024-02-27T12:48:22Z	96	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2024-02-27T10:49:56Z	--- 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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CreazyAI/gemma-Code-Instruct-Finetune-test	CreazyAI	2024-02-27T12:46:53Z	113	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T12:40:23Z	--- 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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yashraj8959/dreambooth-project	yashraj8959	2024-02-27T12:45:04Z	0	0	null	[ "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2024-02-27T12:40:27Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### Dreambooth-Project Dreambooth model trained by yashraj8959 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: 0967CS211067 Sample pictures of this concept:
tejasreereddy/mistral-test	tejasreereddy	2024-02-27T12:40:38Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-02-27T10:19:15Z	--- 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]
airesearch/WangchanLion7B	airesearch	2024-02-27T12:40:22Z	38	7	transformers	[ "transformers", "pytorch", "mpt", "text-generation", "custom_code", "th", "en", "dataset:laion/OIG", "dataset:databricks/databricks-dolly-15k", "dataset:thaisum", "dataset:scb_mt_enth_2020", "dataset:garage-bAInd/Open-Platypus", "dataset:iapp_wiki_qa_squad", "dataset:pythainlp/han-instruct-dataset-v1.0", "dataset:cognitivecomputations/dolphin", "dataset:Hello-SimpleAI/HC3", "dataset:Muennighoff/xP3x", "dataset:openai/summarize_from_feedback", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2023-12-26T05:42:07Z	--- license: apache-2.0 language: - th - en datasets: - laion/OIG - databricks/databricks-dolly-15k - thaisum - scb_mt_enth_2020 - garage-bAInd/Open-Platypus - iapp_wiki_qa_squad - pythainlp/han-instruct-dataset-v1.0 - cognitivecomputations/dolphin - Hello-SimpleAI/HC3 - Muennighoff/xP3x - openai/summarize_from_feedback --- # Model Card for WangChanLion 7B - The Multilingual Instruction-Following Model WangChanLion is a Multilingual, instruction-finetuned on Southeast Asian Languages SEA-LION 7B using open-source, commercially permissible datasets sample from LAION OIG chip2 and infill_dbpedia, DataBricks Dolly v2, OpenAI TL;DR, Hello-SimpleAI HC3, dolphin, iapp_wiki_qa_squad, thaisum, xlsum, scb_mt_enth_2020, han dataset, xp3x and Open-Platypus, a total of ~500k samples. Non-commercial datasets were filtered out. Released under apache 2.0 license. The models are trained to perform a subset of instruction-following tasks we found most relevant: reading comprehension, brainstorming, and creative writing. In this model, we focus on Thai and English datasets. We perform Vicuna-style evaluation using human evaluation. In a similar manner to Dolly v2, we only use open-source, commercially permissive pretrained models and datasets. Our models are neither restricted by non-commercial clauses like LLaMA-based models nor non-compete clauses like models that use self-instruct datasets from ChatGPT. - Developers: PyThaiNLP and VISTEC-depa AI Research Institute of Thailand - Model type: SEA-LION 7B (MPT architecture) ## Model Sources - Repository: https://github.com/vistec-AI/WangchanLion - Demo: [demo_WangchanLion.ipynb - Colaboratory](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L) # Use cases ## Direct Use Intended to be used as an instruction-following model for reading comprehension, brainstorming, and creative writing. ## Downstream Use The model can be finetuned for any typical instruction-following use cases. ## Out-of-Scope Use We do not expect the models to perform well in math problems, reasoning, and factfulness. ## Bias, Risks, and Limitations We noticed similar limitations to other finetuned instruction followers, such as math problems, reasoning, and factfulness. Even though the models do not perform on the level that we expect them to be abused, they do contain undesirable biases and toxicity and should be further optimized for your particular use cases. ## Recommendations Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model. More information is needed for further recommendations. # Get Started Use the code [here](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L) to get started with the model. Or ```python from transformers import AutoModelForCausalLM, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained( "airesearch/WangchanLion7B", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained( "airesearch/WangchanLion7B", trust_remote_code=True, return_dict=True, load_in_8bit=True , device_map="auto", torch_dtype=torch.float16, offload_folder="./", low_cpu_mem_usage=True, ) def get_prompt(question: str,context: str = None) -> str: if context is not None: return """พื้นหลัง:\n\n{context}\n\nคำถาม:{question}\n\nตอบ:""".format(context=context, question=question) return """คำถาม:{question}\n\nตอบ:""".format(question=question) question = "เกิดอะไรขึ้นที่เทียนอันเหมินตอนปี 1989" full_prompt = get_prompt(question=question) tokens = tokenizer(full_prompt, return_tensors="pt").to("cuda") output = model.generate( input_ids=tokens['input_ids'], attention_mask=tokens['attention_mask'], max_new_tokens=256, early_stopping=True, top_k=50, top_p=0.95, do_sample=True, temperature=0.3, repetition_penalty = 1.2, eos_token_id = tokenizer.eos_token_id, ) print(tokenizer.decode(output[0], skip_special_tokens=True)) ``` # Training Details ## Training Data Finetuning datasets are sourced from [LAION OIG chip2 and infill_dbpedia (Apache-2.0)](https://huggingface.co/datasets/laion/OIG), [DataBricks Dolly v2 (Apache-2.0)](https://github.com/databrickslabs/dolly), [OpenAI TL;DR (MIT)](https://github.com/openai/summarize-from-feedback), [Hello-SimpleAI HC3 (CC-BY SA)](https://huggingface.co/datasets/Hello-SimpleAI/HC3), [dolphin](https://huggingface.co/datasets/ehartford/dolphin), [iapp_wiki_qa_squad](https://huggingface.co/datasets/iapp_wiki_qa_squad) , [thaisum](https://huggingface.co/datasets/thaisum), [xlsum](https://huggingface.co/datasets/csebuetnlp/xlsum), [scb_mt_enth_2020](https://huggingface.co/datasets/scb_mt_enth_2020), [han dataset](https://huggingface.co/datasets/pythainlp/han-instruct-dataset-v1.0), [xp3x](https://huggingface.co/datasets/Muennighoff/xP3x) and [Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus). ## Training regime - QLoRA with 4 A100 (40GB) # Evaluation We performed human and machine evaluations on XQuAD zero-shot and one-shot settings: ## XQuAD \| Model \| F1 (Zero-shot) \| F1 (One-shot) \| \|:--------------:\|:--------------:\|:-------------:\| \| openthaigpt7B \| 27.3487 \| 34.3104 \| \| SeaLLM7B V2 \| 16.1104 \| 25.7399 \| \| Typhoon-7b \| 34.46 \| 54.03 \| \| WangchanLion7B \| 45.8763 \| 49.9145 \| ## iAPP Wiki QA \| Model \| F1 (Zero-shot) \| F1 (One-shot) \| \|:--------------:\|:--------------:\|:-------------:\| \| openthaigpt7B \| 40.0614 \| 46.6883 \| \| SeaLLM7B V2 \| 23.6425 \| 28.9934 \| \| WangchanLion7B \| 58.9051 \| 62.9776 \| # What WangchanLion offers: - Transparent pretrained model: The development of SEA-LION is community-driven, with different ASEAN collaborators contributing pretraining datasets. The SEA-LION developers ensure that all datasets are safe and can be utilized without commercial restrictions. This transparency extends to the provision of pretraining code, ensuring anyone can replicate SEA-LION using the provided datasets. - Transparent finetuning data: In the spirit of open science, we make the finetuning data for WangchanLion accessible to all. This commitment to openness empowers the community by providing complete visibility into the instruction finetuning data that shapes WangchanLion. - Transparent finetuning code: The finetuning code for WangchanLion is readily available for distribution. By sharing our methods and processes, we invite others to learn from, build upon, and innovate alongside us.
loubnabnl/outputs	loubnabnl	2024-02-27T12:35:45Z	1	0	peft	[ "peft", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:bigcode/starcoder2-3b", "base_model:adapter:bigcode/starcoder2-3b", "license:bigcode-openrail-m", "region:us" ]	null	2024-02-27T12:35:11Z	--- license: bigcode-openrail-m library_name: peft tags: - trl - sft - generated_from_trainer base_model: bigcode/starcoder2-3b model-index: - name: outputs 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. --> # outputs This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) 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: 2e-05 - train_batch_size: 1 - eval_batch_size: 8 - seed: 0 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - 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: cosine - lr_scheduler_warmup_steps: 4 - training_steps: 20 ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.38.0.dev0 - Pytorch 2.1.1 - Datasets 2.16.1 - Tokenizers 0.15.1
laishram/bloom-560m-lora-merged-tagger	laishram	2024-02-27T12:31:26Z	77	0	transformers	[ "transformers", "safetensors", "bloom", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "8-bit", "bitsandbytes", "region:us" ]	text-generation	2024-02-27T12:29:47Z	--- 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. 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]
Metin/gemma-2b-tr-inst	Metin	2024-02-27T12:30:32Z	155	4	transformers	[ "transformers", "pytorch", "gemma", "text-generation", "tr", "license:cc-by-nc-4.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-25T19:00:18Z	--- license: cc-by-nc-4.0 language: - tr --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> gemma-2b-tr fine-tuned with Turkish Instruction-Response pairs. ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> - Language(s) (NLP): Turkish, English - License: Creative Commons Attribution Non Commercial 4.0 - Finetuned from model [optional]: gemma-2b-tr (https://huggingface.co/Metin/gemma-2b-tr) ## Uses The model is designed for Turkish instruction following and question answering. Its current response quality is limited, likely due to the small instruction set and model size. It is not recommended for real-world applications at this stage. ## Restrictions Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms Please refer to the gemma use restrictions before start using the model. https://ai.google.dev/gemma/terms#3.2-use ## How to Get Started with the Model ```Python from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Metin/gemma-2b-tr-inst") model = AutoModelForCausalLM.from_pretrained("Metin/gemma-2b-tr-inst") system_prompt = "You are a helpful assistant. Always reply in Turkish." instruction = "Ankara hangi ülkenin başkentidir?" prompt = f"{system_prompt} [INST] {instruction} [/INST]" input_ids = tokenizer(prompt, return_tensors="pt") outputs = model.generate(input_ids) print(tokenizer.decode(outputs[0])) ``` As it can be seen from the above example instructions should be framed within the following structure: SYSTEM_PROMPT [INST] \<Your instruction here\> [/INST] ## Training Details ### Training Data - Dataset: Turkish instructions from the Aya dataset (https://huggingface.co/datasets/CohereForAI/aya_dataset) - Dataset size: ~550K Token or ~5K instruction-response pair. ### Training Procedure #### Training Hyperparameters - Adapter: QLoRA - Epochs: 1 - Context length: 1024 - LoRA Rank: 32 - LoRA Alpha: 32 - LoRA Dropout:** 0.05
zykrr/tinyllama	zykrr	2024-02-27T12:30:06Z	0	0	transformers	[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/tinyllama-bnb-4bit", "base_model:finetune:unsloth/tinyllama-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2024-02-27T12:29:49Z	--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: unsloth/tinyllama-bnb-4bit --- # Uploaded model - Developed by: zykrr - License: apache-2.0 - Finetuned from model : unsloth/tinyllama-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
harikanaidu2k4/my-pet-dog	harikanaidu2k4	2024-02-27T12:30:04Z	2	0	diffusers	[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]	text-to-image	2024-02-27T12:26:08Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by harikanaidu2k4 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/harikanaidu2k4/my-pet-dog/resolve/main/sample_images/xzg3.jpg)
AlGM93/PPO-PyramidsRND	AlGM93	2024-02-27T12:25:04Z	15	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]	reinforcement-learning	2024-02-27T12:25:01Z	--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # ppo Agent playing Pyramids This is a trained model of a ppo agent playing Pyramids using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A short tutorial where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: AlGM93/PPO-PyramidsRND 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
fzzhang/mistral_gsm8k_s_tunes	fzzhang	2024-02-27T12:17:20Z	0	0	peft	[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:mistralai/Mistral-7B-v0.1", "base_model:adapter:mistralai/Mistral-7B-v0.1", "license:apache-2.0", "region:us" ]	null	2024-02-27T08:57:38Z	--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: mistralai/Mistral-7B-v0.1 model-index: - name: mistral_gsm8k_s_tunes 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. --> # mistral_gsm8k_s_tunes This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) 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: 4 - eval_batch_size: 8 - seed: 0 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results ### Framework versions - PEFT 0.7.2.dev0 - Transformers 4.37.0.dev0 - Pytorch 2.2.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.0
MichaelKim/train_results	MichaelKim	2024-02-27T12:17:19Z	1	0	peft	[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:LDCC/LDCC-SOLAR-10.7B", "base_model:adapter:LDCC/LDCC-SOLAR-10.7B", "license:cc-by-nc-4.0", "region:us" ]	null	2024-02-27T07:25:00Z	--- license: cc-by-nc-4.0 library_name: peft tags: - generated_from_trainer base_model: LDCC/LDCC-SOLAR-10.7B model-index: - name: train_results 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. --> # train_results This model is a fine-tuned version of [LDCC/LDCC-SOLAR-10.7B](https://huggingface.co/LDCC/LDCC-SOLAR-10.7B) 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: 0.0001 - train_batch_size: 10 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2
AdrienB134/ColBERTv2.0-spanish-mmarcoES	AdrienB134	2024-02-27T12:17:06Z	40	2	transformers	[ "transformers", "safetensors", "bert", "colbert", "ColBERT", "es", "dataset:unicamp-dl/mmarco", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-02-27T06:08:45Z	--- license: mit datasets: - unicamp-dl/mmarco language: - es tags: - colbert - ColBERT --- ## Training #### Details The model is initialized from the [ColBERTv1.0-bert-based-spanish-mmarcoES](https://huggingface.co/AdrienB134/ColBERTv1.0-bert-based-spanish-mmarcoES) checkpoint and trained using the ColBERTv2 style of training. It was trained on 2 Tesla T4 GPU with 16GBs of memory each with 20k warmup steps warmup using a batch size of 64 and the AdamW optimizer with a constant learning rate of 1e-05. Total training time was around 60 hours. #### Data The model is fine-tuned on the Spanish version of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset, a multi-lingual machine-translated version of the MS MARCO dataset. ## Evaluation The model is evaluated on the smaller development set of mMARCO-es, which consists of 6,980 queries for a corpus of 8.8M candidate passages. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k). \| model \| Vocab. \| #Param. \| Size \| MRR@10 \| R@50 \| R@1000 \| \|:------------------------------------------------------------------------------------------------------------------------\|:--------\|--------:\|------:\|---------:\|-------:\|--------:\| \| ColBERTv2.0-spanish-mmarcoES \| spanish \| 110M \| 440MB \| 32.86 \| 76.46 \| 81.06 \| \| ColBERTv1.0-bert-based-spanish-mmarcoES \| spanish \| 110M \| 440MB \| 24.70 \| 59,23 \| 63.86 \|
AdrienB134/ColBERTv1.0-bert-based-spanish-mmarcoES	AdrienB134	2024-02-27T12:16:34Z	38	1	transformers	[ "transformers", "safetensors", "bert", "colbert", "ColBERT", "es", "dataset:unicamp-dl/mmarco", "license:mit", "endpoints_compatible", "region:us" ]	null	2024-01-16T06:23:03Z	--- license: mit datasets: - unicamp-dl/mmarco language: - es tags: - colbert - ColBERT --- New spanish ColBERTv2 model available [here](https://huggingface.co/AdrienB134/ColBERTv2.0-spanish-mmarcoES) ## Training #### Details The model is initialized from the [bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) checkpoint and fine-tuned on 10M triples via pairwise softmax cross-entropy loss over the computed scores of the positive and negative passages associated to a query. It was trained on a single Tesla A100 GPU with 40GBs of memory during 200k steps with 10% of warmup steps using a batch size of 96 and the AdamW optimizer with a constant learning rate of 3e-06. Total training time was around 12 hours. #### Data The model is fine-tuned on the Spanish version of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset, a multi-lingual machine-translated version of the MS MARCO dataset. The triples are sampled from the ~39.8M triples of [triples.train.small.tsv](https://microsoft.github.io/msmarco/Datasets.html#passage-ranking-dataset) ## Evaluation The model is evaluated on the smaller development set of mMARCO-es, which consists of 6,980 queries for a corpus of 8.8M candidate passages. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k). \| model \| Vocab. \| #Param. \| Size \| MRR@10 \| R@50 \| R@1000 \| \|:------------------------------------------------------------------------------------------------------------------------\|:--------\|--------:\|------:\|---------:\|-------:\|--------:\| \| ColBERTv1.0-bert-based-spanish-mmarcoES \| spanish \| 110M \| 440MB \| 24.70 \| 59,23 \| 63.86 \|
SumaGeethika/my-pet-dog	SumaGeethika	2024-02-27T12:09:16Z	1	0	diffusers	[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2024-02-27T12:02:11Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by SumaGeethika following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/SumaGeethika/my-pet-dog/resolve/main/sample_images/flower.jpg)
alinerodrigues/wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10	alinerodrigues	2024-02-27T12:03:25Z	15	0	transformers	[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-02-27T07:54:05Z	--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10 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. --> # wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10 This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1766 - Wer: 0.0913 - Cer: 0.0291 ## 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 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer \| Cer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\| \| 21.8058 \| 1.0 \| 67 \| 8.5869 \| 0.9997 \| 0.9859 \| \| 12.0549 \| 2.0 \| 134 \| 5.9897 \| 1.0 \| 0.9719 \| \| 5.5651 \| 3.0 \| 201 \| 3.0869 \| 1.0 \| 1.0 \| \| 5.5651 \| 4.0 \| 268 \| 2.9406 \| 1.0 \| 1.0 \| \| 2.9913 \| 5.0 \| 335 \| 2.9153 \| 1.0 \| 1.0 \| \| 2.9244 \| 6.0 \| 402 \| 2.8824 \| 1.0 \| 1.0 \| \| 2.9244 \| 7.0 \| 469 \| 2.8784 \| 1.0 \| 1.0 \| \| 2.8927 \| 8.0 \| 536 \| 2.8759 \| 1.0 \| 1.0 \| \| 2.8858 \| 9.0 \| 603 \| 2.8599 \| 1.0 \| 1.0 \| \| 2.8858 \| 10.0 \| 670 \| 2.8328 \| 1.0 \| 1.0 \| \| 2.8512 \| 11.0 \| 737 \| 2.5475 \| 1.0 \| 0.9997 \| \| 2.515 \| 12.0 \| 804 \| 1.5878 \| 1.0 \| 0.5086 \| \| 2.515 \| 13.0 \| 871 \| 0.7009 \| 0.8586 \| 0.1889 \| \| 1.3219 \| 14.0 \| 938 \| 0.4050 \| 0.2310 \| 0.0598 \| \| 0.6694 \| 15.0 \| 1005 \| 0.3246 \| 0.1755 \| 0.0487 \| \| 0.6694 \| 16.0 \| 1072 \| 0.2909 \| 0.1562 \| 0.0439 \| \| 0.4976 \| 17.0 \| 1139 \| 0.2679 \| 0.1420 \| 0.0415 \| \| 0.4105 \| 18.0 \| 1206 \| 0.2519 \| 0.1292 \| 0.0384 \| \| 0.4105 \| 19.0 \| 1273 \| 0.2421 \| 0.1194 \| 0.0366 \| \| 0.3865 \| 20.0 \| 1340 \| 0.2325 \| 0.1184 \| 0.0354 \| \| 0.317 \| 21.0 \| 1407 \| 0.2251 \| 0.1096 \| 0.0341 \| \| 0.317 \| 22.0 \| 1474 \| 0.2195 \| 0.1092 \| 0.0339 \| \| 0.2925 \| 23.0 \| 1541 \| 0.2106 \| 0.1018 \| 0.0320 \| \| 0.2721 \| 24.0 \| 1608 \| 0.2072 \| 0.0981 \| 0.0317 \| \| 0.2721 \| 25.0 \| 1675 \| 0.2106 \| 0.0981 \| 0.0317 \| \| 0.2531 \| 26.0 \| 1742 \| 0.2046 \| 0.1042 \| 0.0330 \| \| 0.2634 \| 27.0 \| 1809 \| 0.2071 \| 0.1001 \| 0.0321 \| \| 0.2634 \| 28.0 \| 1876 \| 0.2028 \| 0.1042 \| 0.0328 \| \| 0.2391 \| 29.0 \| 1943 \| 0.1973 \| 0.0957 \| 0.0308 \| \| 0.2232 \| 30.0 \| 2010 \| 0.2017 \| 0.0974 \| 0.0313 \| \| 0.2232 \| 31.0 \| 2077 \| 0.1987 \| 0.0974 \| 0.0308 \| \| 0.2111 \| 32.0 \| 2144 \| 0.1898 \| 0.0920 \| 0.0298 \| \| 0.2121 \| 33.0 \| 2211 \| 0.2006 \| 0.0954 \| 0.0314 \| \| 0.2121 \| 34.0 \| 2278 \| 0.1934 \| 0.0920 \| 0.0303 \| \| 0.1868 \| 35.0 \| 2345 \| 0.1921 \| 0.0944 \| 0.0306 \| \| 0.1869 \| 36.0 \| 2412 \| 0.1884 \| 0.0893 \| 0.0292 \| \| 0.1869 \| 37.0 \| 2479 \| 0.1903 \| 0.0866 \| 0.0292 \| \| 0.1935 \| 38.0 \| 2546 \| 0.1867 \| 0.0900 \| 0.0294 \| \| 0.1957 \| 39.0 \| 2613 \| 0.1874 \| 0.0927 \| 0.0298 \| \| 0.1957 \| 40.0 \| 2680 \| 0.1845 \| 0.0923 \| 0.0297 \| \| 0.1772 \| 41.0 \| 2747 \| 0.1862 \| 0.0927 \| 0.0298 \| \| 0.1748 \| 42.0 \| 2814 \| 0.1894 \| 0.0906 \| 0.0297 \| \| 0.1748 \| 43.0 \| 2881 \| 0.1816 \| 0.0933 \| 0.0301 \| \| 0.1498 \| 44.0 \| 2948 \| 0.1795 \| 0.0920 \| 0.0296 \| \| 0.1606 \| 45.0 \| 3015 \| 0.1867 \| 0.0906 \| 0.0299 \| \| 0.1606 \| 46.0 \| 3082 \| 0.1866 \| 0.0886 \| 0.0294 \| \| 0.1599 \| 47.0 \| 3149 \| 0.1883 \| 0.0920 \| 0.0300 \| \| 0.1487 \| 48.0 \| 3216 \| 0.1802 \| 0.0933 \| 0.0298 \| \| 0.1487 \| 49.0 \| 3283 \| 0.1808 \| 0.0937 \| 0.0298 \| \| 0.148 \| 50.0 \| 3350 \| 0.1824 \| 0.0916 \| 0.0292 \| \| 0.1457 \| 51.0 \| 3417 \| 0.1843 \| 0.0893 \| 0.0293 \| \| 0.1457 \| 52.0 \| 3484 \| 0.1822 \| 0.0923 \| 0.0293 \| \| 0.1472 \| 53.0 \| 3551 \| 0.1766 \| 0.0913 \| 0.0291 \| \| 0.1413 \| 54.0 \| 3618 \| 0.1811 \| 0.0933 \| 0.0292 \| \| 0.1413 \| 55.0 \| 3685 \| 0.1807 \| 0.0906 \| 0.0291 \| \| 0.1357 \| 56.0 \| 3752 \| 0.1808 \| 0.0879 \| 0.0284 \| \| 0.1382 \| 57.0 \| 3819 \| 0.1810 \| 0.0933 \| 0.0296 \| \| 0.1382 \| 58.0 \| 3886 \| 0.1817 \| 0.0910 \| 0.0287 \| \| 0.1371 \| 59.0 \| 3953 \| 0.1844 \| 0.0889 \| 0.0286 \| \| 0.141 \| 60.0 \| 4020 \| 0.1883 \| 0.0883 \| 0.0284 \| \| 0.141 \| 61.0 \| 4087 \| 0.1864 \| 0.0930 \| 0.0290 \| \| 0.147 \| 62.0 \| 4154 \| 0.1861 \| 0.0920 \| 0.0289 \| \| 0.1316 \| 63.0 \| 4221 \| 0.1863 \| 0.0950 \| 0.0296 \| \| 0.1316 \| 64.0 \| 4288 \| 0.1909 \| 0.0950 \| 0.0302 \| \| 0.1329 \| 65.0 \| 4355 \| 0.1880 \| 0.0913 \| 0.0291 \| \| 0.1326 \| 66.0 \| 4422 \| 0.1851 \| 0.0930 \| 0.0291 \| \| 0.1326 \| 67.0 \| 4489 \| 0.1842 \| 0.0937 \| 0.0292 \| \| 0.1345 \| 68.0 \| 4556 \| 0.1856 \| 0.0957 \| 0.0297 \| \| 0.1371 \| 69.0 \| 4623 \| 0.1840 \| 0.0927 \| 0.0291 \| \| 0.1371 \| 70.0 \| 4690 \| 0.1845 \| 0.0923 \| 0.0292 \| \| 0.1325 \| 71.0 \| 4757 \| 0.1806 \| 0.0920 \| 0.0288 \| \| 0.1264 \| 72.0 \| 4824 \| 0.1810 \| 0.0923 \| 0.0289 \| \| 0.1264 \| 73.0 \| 4891 \| 0.1836 \| 0.0944 \| 0.0295 \| ### Framework versions - Transformers 4.28.0 - Pytorch 2.2.1+cu121 - Datasets 2.17.0 - Tokenizers 0.13.3
adarsh12x/mistral_7b_samantha___	adarsh12x	2024-02-27T11:52:53Z	4	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "trl", "sft", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "8-bit", "bitsandbytes", "region:us" ]	text-generation	2024-02-26T10:42:07Z	--- library_name: transformers tags: - trl - sft --- # 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]
Syedhur786/mistral-finetuned-samsum	Syedhur786	2024-02-27T11:48:59Z	0	0	peft	[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "base_model:adapter:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "license:apache-2.0", "region:us" ]	null	2024-02-27T10:39:03Z	--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ model-index: - name: mistral-finetuned-samsum 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. --> # mistral-finetuned-samsum This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ) 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: 0.0002 - 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: cosine - training_steps: 250 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.39.0.dev0 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
casque/jacquard_pantyhose	casque	2024-02-27T11:37:19Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2024-02-27T11:36:22Z	--- license: creativeml-openrail-m ---
neerajnarwal/Mistral-7B-Instruct-Question-Answering	neerajnarwal	2024-02-27T11:21:57Z	0	0	peft	[ "peft", "safetensors", "arxiv:1910.09700", "base_model:mistralai/Mistral-7B-Instruct-v0.2", "base_model:adapter:mistralai/Mistral-7B-Instruct-v0.2", "region:us" ]	null	2024-02-27T10:08:26Z	--- library_name: peft base_model: mistralai/Mistral-7B-Instruct-v0.2 --- # 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. --> - 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] ### Framework versions - PEFT 0.8.2
Solenya-ai/CLIP-ViT-B-16-DataComp.XL-s13B-b90K	Solenya-ai	2024-02-27T11:19:15Z	106	0	transformers	[ "transformers", "safetensors", "clip", "zero-shot-image-classification", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	zero-shot-image-classification	2024-02-27T11:17:31Z	--- 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. 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]
svitse/model_1890_wie	svitse	2024-02-27T11:17:47Z	163	0	transformers	[ "transformers", "safetensors", "bert", "text-classification", "generated_from_trainer", "base_model:GroNLP/bert-base-dutch-cased", "base_model:finetune:GroNLP/bert-base-dutch-cased", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T10:55:02Z	--- base_model: GroNLP/bert-base-dutch-cased tags: - generated_from_trainer model-index: - name: model_1890_wie 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. --> # model_1890_wie This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) 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-05 - train_batch_size: 16 - eval_batch_size: 20 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2
Di1/chatd5k	Di1	2024-02-27T11:16:29Z	1	0	peft	[ "peft", "region:us" ]	null	2024-02-27T11:16:26Z	--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.4.0
Kinjal123/content	Kinjal123	2024-02-27T11:16:04Z	114	0	transformers	[ "transformers", "safetensors", "opt", "text-generation", "trl", "sft", "generated_from_trainer", "base_model:facebook/opt-350m", "base_model:finetune:facebook/opt-350m", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T11:15:03Z	--- license: other base_model: facebook/opt-350m tags: - trl - sft - generated_from_trainer model-index: - name: content 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. --> # content This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.5972 ## 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: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 4.0419 \| 0.2 \| 50 \| 3.8081 \| \| 3.816 \| 0.4 \| 100 \| 3.7579 \| \| 3.78 \| 0.6 \| 150 \| 3.7016 \| \| 3.753 \| 0.8 \| 200 \| 3.6749 \| \| 3.6787 \| 1.0 \| 250 \| 3.6132 \| \| 2.987 \| 1.2 \| 300 \| 3.6374 \| \| 3.0092 \| 1.4 \| 350 \| 3.6043 \| \| 3.0088 \| 1.6 \| 400 \| 3.5676 \| \| 2.945 \| 1.8 \| 450 \| 3.5404 \| \| 2.9204 \| 2.0 \| 500 \| 3.5082 \| \| 2.2216 \| 2.2 \| 550 \| 3.6194 \| \| 2.212 \| 2.4 \| 600 \| 3.6117 \| \| 2.198 \| 2.6 \| 650 \| 3.6019 \| \| 2.1787 \| 2.8 \| 700 \| 3.5973 \| \| 2.1878 \| 3.0 \| 750 \| 3.5972 \| ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
oeg/RoBERTa-Repository-Proposal	oeg	2024-02-27T11:08:20Z	163	0	transformers	[ "transformers", "safetensors", "roberta", "text-classification", "English", "RoBERTa-base", "Text Classification", "en", "license:cc-by-nc-4.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-20T14:14:05Z	--- license: cc-by-nc-4.0 language: - en tags: - English - RoBERTa-base - Text Classification pipeline_tag: text-classification --- # RoBERTa base Fine-Tuned for Proposal Sentence Classification ## Overview - Language: English - Model Name: oeg/RoBERTa_Repository_Proposal ## Description This model is a fine-tuned RoBERTa-base model trained to classify sentences into two classes: proposal and non-proposal sentences. The training data includes sentences proposing a software or data repository. The model is trained to recognize and classify these sentences accurately. ## How to use To use this model in Python: ```python from transformers import RobertaForSequenceClassification, RobertaTokenizer import torch tokenizer = RobertaTokenizer.from_pretrained("roberta-base") model = RobertaForSequenceClassification.from_pretrained("oeg/RoBERTa-Repository-Proposal") sentence = "Your input sentence here." inputs = tokenizer(sentence, return_tensors="pt") outputs = model(**inputs) probabilities = torch.nn.functional.softmax(outputs.logits, dim=1)
aslez123/segmentation-train	aslez123	2024-02-27T11:04:50Z	34	0	transformers	[ "transformers", "tensorboard", "safetensors", "segformer", "generated_from_trainer", "base_model:nvidia/mit-b0", "base_model:finetune:nvidia/mit-b0", "license:other", "endpoints_compatible", "region:us" ]	null	2024-02-27T10:31:47Z	--- license: other base_model: nvidia/mit-b0 tags: - generated_from_trainer model-index: - name: segmentation-train 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. --> # segmentation-train This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) 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: 6e-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: 5 ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
peldrak/segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline	peldrak	2024-02-27T11:04:05Z	188	0	transformers	[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:peldrak/segformer-b3-ade-512-512-finetuned-coastTrain", "base_model:finetune:peldrak/segformer-b3-ade-512-512-finetuned-coastTrain", "license:other", "endpoints_compatible", "region:us" ]	image-segmentation	2024-02-27T10:12:59Z	--- license: other base_model: peldrak/segformer-b3-ade-512-512-finetuned-coastTrain tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline 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. --> # segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline This model is a fine-tuned version of [peldrak/segformer-b3-ade-512-512-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b3-ade-512-512-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.2531 - Mean Iou: 0.7677 - Mean Accuracy: 0.8502 - Overall Accuracy: 0.9340 - Accuracy Water: 0.9810 - Accuracy Whitewater: 0.5654 - Accuracy Sediment: 0.8995 - Accuracy Other Natural Terrain: 0.7891 - Accuracy Vegetation: 0.8969 - Accuracy Development: 0.8221 - Accuracy Unknown: 0.9974 - Iou Water: 0.9535 - Iou Whitewater: 0.4217 - Iou Sediment: 0.8288 - Iou Other Natural Terrain: 0.6339 - Iou Vegetation: 0.8151 - Iou Development: 0.7244 - Iou Unknown: 0.9964 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Mean Iou \| Mean Accuracy \| Overall Accuracy \| Accuracy Water \| Accuracy Whitewater \| Accuracy Sediment \| Accuracy Other Natural Terrain \| Accuracy Vegetation \| Accuracy Development \| Accuracy Unknown \| Iou Water \| Iou Whitewater \| Iou Sediment \| Iou Other Natural Terrain \| Iou Vegetation \| Iou Development \| Iou Unknown \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:-------------:\|:----------------:\|:--------------:\|:-------------------:\|:-----------------:\|:------------------------------:\|:-------------------:\|:--------------------:\|:----------------:\|:---------:\|:--------------:\|:------------:\|:-------------------------:\|:--------------:\|:---------------:\|:-----------:\| \| 1.2485 \| 0.24 \| 20 \| 0.4622 \| 0.5668 \| 0.6676 \| 0.8536 \| 0.9523 \| 0.2722 \| 0.9426 \| 0.0 \| 0.9170 \| 0.5995 \| 0.9897 \| 0.9004 \| 0.2295 \| 0.6418 \| 0.0 \| 0.6785 \| 0.5280 \| 0.9890 \| \| 0.4894 \| 0.49 \| 40 \| 0.3645 \| 0.6103 \| 0.7022 \| 0.8775 \| 0.9738 \| 0.2414 \| 0.9207 \| 0.1627 \| 0.9260 \| 0.6974 \| 0.9932 \| 0.9318 \| 0.2117 \| 0.6742 \| 0.1589 \| 0.7242 \| 0.5807 \| 0.9904 \| \| 0.4931 \| 0.73 \| 60 \| 0.3257 \| 0.6374 \| 0.7168 \| 0.8940 \| 0.9790 \| 0.1616 \| 0.8723 \| 0.2837 \| 0.9522 \| 0.7731 \| 0.9955 \| 0.9359 \| 0.1529 \| 0.7241 \| 0.2724 \| 0.7487 \| 0.6360 \| 0.9920 \| \| 0.1766 \| 0.98 \| 80 \| 0.2769 \| 0.6970 \| 0.7755 \| 0.9123 \| 0.9726 \| 0.3993 \| 0.9157 \| 0.6302 \| 0.9080 \| 0.6049 \| 0.9976 \| 0.9443 \| 0.3230 \| 0.7710 \| 0.5134 \| 0.7866 \| 0.5485 \| 0.9921 \| \| 0.6156 \| 1.22 \| 100 \| 0.2895 \| 0.6691 \| 0.7372 \| 0.9115 \| 0.9696 \| 0.1418 \| 0.9271 \| 0.5343 \| 0.9293 \| 0.6601 \| 0.9981 \| 0.9435 \| 0.1371 \| 0.7252 \| 0.4855 \| 0.7931 \| 0.6066 \| 0.9929 \| \| 0.4116 \| 1.46 \| 120 \| 0.2715 \| 0.7026 \| 0.7775 \| 0.9135 \| 0.9521 \| 0.2680 \| 0.9245 \| 0.6565 \| 0.8937 \| 0.7554 \| 0.9922 \| 0.9225 \| 0.2401 \| 0.7913 \| 0.5413 \| 0.7691 \| 0.6637 \| 0.9905 \| \| 0.261 \| 1.71 \| 140 \| 0.2459 \| 0.7193 \| 0.8036 \| 0.9186 \| 0.9770 \| 0.3963 \| 0.8738 \| 0.6637 \| 0.8956 \| 0.8211 \| 0.9973 \| 0.9387 \| 0.3074 \| 0.7904 \| 0.5513 \| 0.7829 \| 0.6708 \| 0.9933 \| \| 0.2603 \| 1.95 \| 160 \| 0.2538 \| 0.7189 \| 0.7987 \| 0.9159 \| 0.9752 \| 0.3829 \| 0.9032 \| 0.7231 \| 0.8610 \| 0.7478 \| 0.9975 \| 0.9288 \| 0.3082 \| 0.7996 \| 0.5457 \| 0.7713 \| 0.6843 \| 0.9943 \| \| 0.3266 \| 2.2 \| 180 \| 0.2468 \| 0.7232 \| 0.8227 \| 0.9118 \| 0.9734 \| 0.4478 \| 0.9127 \| 0.8202 \| 0.7856 \| 0.8226 \| 0.9967 \| 0.9337 \| 0.3322 \| 0.8097 \| 0.5550 \| 0.7399 \| 0.6988 \| 0.9936 \| \| 0.1754 \| 2.44 \| 200 \| 0.2850 \| 0.7269 \| 0.8031 \| 0.9209 \| 0.9764 \| 0.3942 \| 0.8998 \| 0.6822 \| 0.8980 \| 0.7752 \| 0.9957 \| 0.9300 \| 0.3147 \| 0.8116 \| 0.5579 \| 0.7858 \| 0.6944 \| 0.9937 \| \| 0.1391 \| 2.68 \| 220 \| 0.2787 \| 0.7316 \| 0.8041 \| 0.9264 \| 0.9678 \| 0.4164 \| 0.9050 \| 0.6179 \| 0.9497 \| 0.7737 \| 0.9982 \| 0.9474 \| 0.3268 \| 0.8058 \| 0.5714 \| 0.8035 \| 0.6720 \| 0.9946 \| \| 0.1294 \| 2.93 \| 240 \| 0.2869 \| 0.7176 \| 0.8170 \| 0.9100 \| 0.9752 \| 0.4576 \| 0.9232 \| 0.9012 \| 0.7608 \| 0.7034 \| 0.9976 \| 0.9455 \| 0.3430 \| 0.7795 \| 0.5795 \| 0.7315 \| 0.6496 \| 0.9948 \| \| 0.3478 \| 3.17 \| 260 \| 0.2799 \| 0.7348 \| 0.8127 \| 0.9238 \| 0.9792 \| 0.4352 \| 0.8693 \| 0.6888 \| 0.9183 \| 0.8048 \| 0.9935 \| 0.9461 \| 0.3369 \| 0.8102 \| 0.5753 \| 0.7904 \| 0.6923 \| 0.9926 \| \| 0.1053 \| 3.41 \| 280 \| 0.2963 \| 0.7227 \| 0.7986 \| 0.9234 \| 0.9837 \| 0.4045 \| 0.8366 \| 0.5931 \| 0.9610 \| 0.8150 \| 0.9966 \| 0.9409 \| 0.3144 \| 0.7928 \| 0.5578 \| 0.8011 \| 0.6577 \| 0.9939 \| \| 0.3786 \| 3.66 \| 300 \| 0.2416 \| 0.7282 \| 0.8228 \| 0.9137 \| 0.9689 \| 0.4874 \| 0.9182 \| 0.8059 \| 0.8081 \| 0.7729 \| 0.9984 \| 0.9455 \| 0.3525 \| 0.8143 \| 0.5534 \| 0.7431 \| 0.6944 \| 0.9937 \| \| 0.3046 \| 3.9 \| 320 \| 0.2374 \| 0.7406 \| 0.8148 \| 0.9279 \| 0.9820 \| 0.3912 \| 0.8961 \| 0.7267 \| 0.8996 \| 0.8111 \| 0.9966 \| 0.9438 \| 0.3180 \| 0.8193 \| 0.5968 \| 0.8014 \| 0.7111 \| 0.9940 \| \| 0.1098 \| 4.15 \| 340 \| 0.2479 \| 0.7278 \| 0.8012 \| 0.9258 \| 0.9816 \| 0.2957 \| 0.8885 \| 0.7045 \| 0.8956 \| 0.8445 \| 0.9977 \| 0.9488 \| 0.2557 \| 0.8194 \| 0.5799 \| 0.7923 \| 0.7036 \| 0.9948 \| \| 0.1654 \| 4.39 \| 360 \| 0.2757 \| 0.7484 \| 0.8304 \| 0.9290 \| 0.9751 \| 0.4714 \| 0.8718 \| 0.7298 \| 0.9119 \| 0.8562 \| 0.9965 \| 0.9508 \| 0.3615 \| 0.8222 \| 0.6089 \| 0.8021 \| 0.6989 \| 0.9944 \| \| 0.1079 \| 4.63 \| 380 \| 0.2821 \| 0.7171 \| 0.8052 \| 0.9095 \| 0.9789 \| 0.3882 \| 0.9159 \| 0.8147 \| 0.7865 \| 0.7563 \| 0.9959 \| 0.9358 \| 0.3245 \| 0.7857 \| 0.5545 \| 0.7318 \| 0.6930 \| 0.9942 \| \| 0.1849 \| 4.88 \| 400 \| 0.2637 \| 0.7398 \| 0.8191 \| 0.9250 \| 0.9773 \| 0.4225 \| 0.8793 \| 0.6972 \| 0.9008 \| 0.8600 \| 0.9967 \| 0.9472 \| 0.3367 \| 0.8212 \| 0.5715 \| 0.7886 \| 0.7189 \| 0.9946 \| \| 0.1643 \| 5.12 \| 420 \| 0.3350 \| 0.7221 \| 0.7861 \| 0.9244 \| 0.9782 \| 0.3296 \| 0.9235 \| 0.5713 \| 0.9536 \| 0.7526 \| 0.9939 \| 0.9458 \| 0.2901 \| 0.7973 \| 0.5429 \| 0.8014 \| 0.6843 \| 0.9927 \| \| 0.1595 \| 5.37 \| 440 \| 0.2582 \| 0.7366 \| 0.8255 \| 0.9196 \| 0.9769 \| 0.4560 \| 0.8771 \| 0.7617 \| 0.8518 \| 0.8582 \| 0.9965 \| 0.9464 \| 0.3440 \| 0.8231 \| 0.5601 \| 0.7647 \| 0.7237 \| 0.9946 \| \| 0.3171 \| 5.61 \| 460 \| 0.2579 \| 0.7433 \| 0.8317 \| 0.9261 \| 0.9681 \| 0.5031 \| 0.9291 \| 0.7243 \| 0.8871 \| 0.8137 \| 0.9965 \| 0.9506 \| 0.3517 \| 0.8177 \| 0.5841 \| 0.7930 \| 0.7112 \| 0.9950 \| \| 0.2955 \| 5.85 \| 480 \| 0.2975 \| 0.7288 \| 0.8072 \| 0.9226 \| 0.9758 \| 0.4648 \| 0.9149 \| 0.6695 \| 0.9146 \| 0.7139 \| 0.9967 \| 0.9498 \| 0.3452 \| 0.7954 \| 0.5683 \| 0.7901 \| 0.6579 \| 0.9948 \| \| 0.0857 \| 6.1 \| 500 \| 0.2707 \| 0.7307 \| 0.8236 \| 0.9194 \| 0.9792 \| 0.5026 \| 0.9181 \| 0.7281 \| 0.8591 \| 0.7821 \| 0.9957 \| 0.9512 \| 0.3523 \| 0.8017 \| 0.5624 \| 0.7724 \| 0.6806 \| 0.9944 \| \| 0.109 \| 6.34 \| 520 \| 0.2674 \| 0.7488 \| 0.8316 \| 0.9312 \| 0.9738 \| 0.5295 \| 0.9087 \| 0.6734 \| 0.9363 \| 0.8021 \| 0.9977 \| 0.9524 \| 0.3633 \| 0.8258 \| 0.5984 \| 0.8127 \| 0.6945 \| 0.9948 \| \| 0.0593 \| 6.59 \| 540 \| 0.2806 \| 0.7376 \| 0.8273 \| 0.9204 \| 0.9756 \| 0.4729 \| 0.9084 \| 0.8021 \| 0.8373 \| 0.7988 \| 0.9962 \| 0.9491 \| 0.3463 \| 0.8215 \| 0.5723 \| 0.7676 \| 0.7121 \| 0.9947 \| \| 0.099 \| 6.83 \| 560 \| 0.2874 \| 0.7421 \| 0.8331 \| 0.9237 \| 0.9626 \| 0.4619 \| 0.9334 \| 0.7321 \| 0.8586 \| 0.8852 \| 0.9982 \| 0.9486 \| 0.3640 \| 0.8238 \| 0.5798 \| 0.7802 \| 0.7024 \| 0.9957 \| \| 0.0665 \| 7.07 \| 580 \| 0.2642 \| 0.7462 \| 0.8177 \| 0.9291 \| 0.9780 \| 0.5176 \| 0.8784 \| 0.6685 \| 0.9544 \| 0.7287 \| 0.9983 \| 0.9493 \| 0.3841 \| 0.8119 \| 0.5980 \| 0.8057 \| 0.6788 \| 0.9953 \| \| 0.1285 \| 7.32 \| 600 \| 0.2347 \| 0.7495 \| 0.8500 \| 0.9236 \| 0.9799 \| 0.5332 \| 0.8905 \| 0.8549 \| 0.8181 \| 0.8766 \| 0.9968 \| 0.9483 \| 0.3906 \| 0.8197 \| 0.6088 \| 0.7745 \| 0.7102 \| 0.9946 \| \| 0.1299 \| 7.56 \| 620 \| 0.2630 \| 0.7506 \| 0.8232 \| 0.9311 \| 0.9751 \| 0.4683 \| 0.9292 \| 0.6923 \| 0.9228 \| 0.7773 \| 0.9976 \| 0.9489 \| 0.3754 \| 0.8070 \| 0.6084 \| 0.8172 \| 0.7028 \| 0.9948 \| \| 0.0504 \| 7.8 \| 640 \| 0.2964 \| 0.7358 \| 0.8238 \| 0.9172 \| 0.9790 \| 0.4852 \| 0.9113 \| 0.7586 \| 0.8335 \| 0.8016 \| 0.9976 \| 0.9481 \| 0.3776 \| 0.8139 \| 0.5465 \| 0.7591 \| 0.7105 \| 0.9953 \| \| 0.0795 \| 8.05 \| 660 \| 0.2654 \| 0.7443 \| 0.8427 \| 0.9198 \| 0.9764 \| 0.5517 \| 0.9103 \| 0.8286 \| 0.8150 \| 0.8193 \| 0.9978 \| 0.9506 \| 0.3918 \| 0.8173 \| 0.5768 \| 0.7619 \| 0.7163 \| 0.9953 \| \| 0.0614 \| 8.29 \| 680 \| 0.2904 \| 0.7452 \| 0.8165 \| 0.9303 \| 0.9763 \| 0.4578 \| 0.8990 \| 0.6315 \| 0.9536 \| 0.8003 \| 0.9973 \| 0.9496 \| 0.3518 \| 0.8172 \| 0.5805 \| 0.8118 \| 0.7105 \| 0.9951 \| \| 0.1476 \| 8.54 \| 700 \| 0.2814 \| 0.7498 \| 0.8324 \| 0.9276 \| 0.9785 \| 0.5138 \| 0.9093 \| 0.7335 \| 0.8910 \| 0.8028 \| 0.9979 \| 0.9489 \| 0.3821 \| 0.8168 \| 0.5909 \| 0.7981 \| 0.7165 \| 0.9956 \| \| 0.0669 \| 8.78 \| 720 \| 0.2774 \| 0.7483 \| 0.8374 \| 0.9250 \| 0.9741 \| 0.5476 \| 0.9217 \| 0.7477 \| 0.8710 \| 0.8020 \| 0.9980 \| 0.9313 \| 0.3931 \| 0.8220 \| 0.5795 \| 0.7975 \| 0.7196 \| 0.9953 \| \| 0.142 \| 9.02 \| 740 \| 0.2362 \| 0.7624 \| 0.8555 \| 0.9327 \| 0.9784 \| 0.6280 \| 0.8959 \| 0.7341 \| 0.9111 \| 0.8425 \| 0.9983 \| 0.9516 \| 0.4124 \| 0.8211 \| 0.6182 \| 0.8158 \| 0.7224 \| 0.9952 \| \| 0.1258 \| 9.27 \| 760 \| 0.2666 \| 0.7597 \| 0.8357 \| 0.9329 \| 0.9762 \| 0.4810 \| 0.9161 \| 0.7439 \| 0.9043 \| 0.8311 \| 0.9975 \| 0.9554 \| 0.3793 \| 0.8262 \| 0.6165 \| 0.8111 \| 0.7338 \| 0.9954 \| \| 0.1541 \| 9.51 \| 780 \| 0.2484 \| 0.7630 \| 0.8423 \| 0.9334 \| 0.9797 \| 0.5260 \| 0.9084 \| 0.7548 \| 0.9043 \| 0.8259 \| 0.9973 \| 0.9543 \| 0.3991 \| 0.8244 \| 0.6228 \| 0.8147 \| 0.7307 \| 0.9953 \| \| 0.1689 \| 9.76 \| 800 \| 0.2151 \| 0.7710 \| 0.8619 \| 0.9341 \| 0.9747 \| 0.6199 \| 0.9143 \| 0.8381 \| 0.8751 \| 0.8127 \| 0.9985 \| 0.9553 \| 0.4257 \| 0.8333 \| 0.6421 \| 0.8117 \| 0.7341 \| 0.9952 \| \| 0.0931 \| 10.0 \| 820 \| 0.2422 \| 0.7506 \| 0.8239 \| 0.9325 \| 0.9783 \| 0.4062 \| 0.9162 \| 0.7139 \| 0.9116 \| 0.8443 \| 0.9969 \| 0.9528 \| 0.3324 \| 0.8236 \| 0.6103 \| 0.8137 \| 0.7265 \| 0.9953 \| \| 0.1109 \| 10.24 \| 840 \| 0.2336 \| 0.7522 \| 0.8271 \| 0.9321 \| 0.9774 \| 0.4327 \| 0.9191 \| 0.7334 \| 0.9027 \| 0.8263 \| 0.9981 \| 0.9530 \| 0.3442 \| 0.8194 \| 0.6136 \| 0.8110 \| 0.7283 \| 0.9960 \| \| 0.0561 \| 10.49 \| 860 \| 0.2991 \| 0.7572 \| 0.8445 \| 0.9284 \| 0.9743 \| 0.5846 \| 0.9094 \| 0.7471 \| 0.8933 \| 0.8066 \| 0.9966 \| 0.9514 \| 0.4134 \| 0.8200 \| 0.5952 \| 0.7985 \| 0.7261 \| 0.9955 \| \| 0.0701 \| 10.73 \| 880 \| 0.2647 \| 0.7554 \| 0.8481 \| 0.9286 \| 0.9774 \| 0.6203 \| 0.9098 \| 0.7382 \| 0.8929 \| 0.7991 \| 0.9990 \| 0.9534 \| 0.4082 \| 0.8163 \| 0.5967 \| 0.8006 \| 0.7175 \| 0.9951 \| \| 0.1528 \| 10.98 \| 900 \| 0.2988 \| 0.7626 \| 0.8573 \| 0.9310 \| 0.9713 \| 0.6322 \| 0.9123 \| 0.7464 \| 0.8980 \| 0.8442 \| 0.9969 \| 0.9548 \| 0.4138 \| 0.8368 \| 0.6036 \| 0.8022 \| 0.7317 \| 0.9956 \| \| 0.0514 \| 11.22 \| 920 \| 0.2537 \| 0.7528 \| 0.8314 \| 0.9302 \| 0.9749 \| 0.4371 \| 0.9270 \| 0.8595 \| 0.8548 \| 0.7694 \| 0.9970 \| 0.9527 \| 0.3550 \| 0.8248 \| 0.6354 \| 0.8004 \| 0.7063 \| 0.9951 \| \| 0.0959 \| 11.46 \| 940 \| 0.2897 \| 0.7458 \| 0.8233 \| 0.9279 \| 0.9835 \| 0.4569 \| 0.8963 \| 0.7962 \| 0.8808 \| 0.7523 \| 0.9974 \| 0.9499 \| 0.3569 \| 0.8096 \| 0.6191 \| 0.7974 \| 0.6918 \| 0.9958 \| \| 0.1997 \| 11.71 \| 960 \| 0.3142 \| 0.7512 \| 0.8251 \| 0.9295 \| 0.9745 \| 0.5071 \| 0.9290 \| 0.6819 \| 0.9251 \| 0.7615 \| 0.9964 \| 0.9537 \| 0.3946 \| 0.8181 \| 0.5902 \| 0.8052 \| 0.7017 \| 0.9953 \| \| 0.0724 \| 11.95 \| 980 \| 0.2794 \| 0.7525 \| 0.8318 \| 0.9290 \| 0.9822 \| 0.4696 \| 0.9038 \| 0.7310 \| 0.8897 \| 0.8489 \| 0.9973 \| 0.9557 \| 0.3727 \| 0.8276 \| 0.5890 \| 0.7970 \| 0.7299 \| 0.9957 \| \| 0.0668 \| 12.2 \| 1000 \| 0.2911 \| 0.7447 \| 0.8175 \| 0.9321 \| 0.9844 \| 0.3514 \| 0.9008 \| 0.7032 \| 0.9105 \| 0.8749 \| 0.9970 \| 0.9500 \| 0.2946 \| 0.8281 \| 0.6032 \| 0.8126 \| 0.7290 \| 0.9953 \| \| 0.0574 \| 12.44 \| 1020 \| 0.2565 \| 0.7619 \| 0.8407 \| 0.9330 \| 0.9797 \| 0.5386 \| 0.9173 \| 0.7298 \| 0.9096 \| 0.8120 \| 0.9982 \| 0.9545 \| 0.3984 \| 0.8306 \| 0.6073 \| 0.8131 \| 0.7338 \| 0.9956 \| \| 0.0696 \| 12.68 \| 1040 \| 0.2657 \| 0.7595 \| 0.8366 \| 0.9339 \| 0.9808 \| 0.4966 \| 0.9101 \| 0.7057 \| 0.9197 \| 0.8458 \| 0.9979 \| 0.9520 \| 0.3767 \| 0.8308 \| 0.6096 \| 0.8173 \| 0.7345 \| 0.9956 \| \| 0.3274 \| 12.93 \| 1060 \| 0.2586 \| 0.7465 \| 0.8222 \| 0.9297 \| 0.9793 \| 0.3965 \| 0.9265 \| 0.7214 \| 0.8877 \| 0.8457 \| 0.9983 \| 0.9539 \| 0.3307 \| 0.8268 \| 0.5935 \| 0.8017 \| 0.7235 \| 0.9953 \| \| 0.0817 \| 13.17 \| 1080 \| 0.2783 \| 0.7569 \| 0.8496 \| 0.9265 \| 0.9772 \| 0.5303 \| 0.9224 \| 0.8566 \| 0.8235 \| 0.8395 \| 0.9975 \| 0.9548 \| 0.4030 \| 0.8286 \| 0.6126 \| 0.7783 \| 0.7250 \| 0.9963 \| \| 0.0787 \| 13.41 \| 1100 \| 0.2517 \| 0.7489 \| 0.8218 \| 0.9294 \| 0.9802 \| 0.4487 \| 0.9232 \| 0.7094 \| 0.9058 \| 0.7883 \| 0.9968 \| 0.9527 \| 0.3654 \| 0.8222 \| 0.5939 \| 0.8027 \| 0.7105 \| 0.9951 \| \| 0.1024 \| 13.66 \| 1120 \| 0.2590 \| 0.7569 \| 0.8290 \| 0.9327 \| 0.9812 \| 0.4873 \| 0.9080 \| 0.7041 \| 0.9259 \| 0.7986 \| 0.9977 \| 0.9543 \| 0.3833 \| 0.8266 \| 0.6094 \| 0.8118 \| 0.7171 \| 0.9960 \| \| 0.0888 \| 13.9 \| 1140 \| 0.2647 \| 0.7489 \| 0.8352 \| 0.9228 \| 0.9812 \| 0.5251 \| 0.9169 \| 0.7856 \| 0.8447 \| 0.7955 \| 0.9973 \| 0.9491 \| 0.4024 \| 0.8276 \| 0.5748 \| 0.7738 \| 0.7184 \| 0.9958 \| \| 0.0946 \| 14.15 \| 1160 \| 0.2453 \| 0.7571 \| 0.8370 \| 0.9298 \| 0.9823 \| 0.5318 \| 0.9002 \| 0.7619 \| 0.8942 \| 0.7913 \| 0.9973 \| 0.9531 \| 0.4046 \| 0.8240 \| 0.6086 \| 0.8008 \| 0.7125 \| 0.9960 \| \| 0.0529 \| 14.39 \| 1180 \| 0.2514 \| 0.7596 \| 0.8460 \| 0.9298 \| 0.9808 \| 0.5804 \| 0.9014 \| 0.7354 \| 0.8979 \| 0.8289 \| 0.9970 \| 0.9559 \| 0.4197 \| 0.8307 \| 0.5978 \| 0.7990 \| 0.7183 \| 0.9958 \| \| 0.0495 \| 14.63 \| 1200 \| 0.2323 \| 0.7634 \| 0.8491 \| 0.9324 \| 0.9790 \| 0.5831 \| 0.9267 \| 0.7848 \| 0.8862 \| 0.7861 \| 0.9977 \| 0.9550 \| 0.4175 \| 0.8280 \| 0.6217 \| 0.8103 \| 0.7151 \| 0.9962 \| \| 0.0401 \| 14.88 \| 1220 \| 0.2248 \| 0.7677 \| 0.8467 \| 0.9366 \| 0.9796 \| 0.5337 \| 0.9256 \| 0.8125 \| 0.8943 \| 0.7834 \| 0.9981 \| 0.9524 \| 0.4037 \| 0.8250 \| 0.6561 \| 0.8282 \| 0.7126 \| 0.9961 \| \| 0.053 \| 15.12 \| 1240 \| 0.2280 \| 0.7701 \| 0.8541 \| 0.9362 \| 0.9805 \| 0.5488 \| 0.9155 \| 0.8259 \| 0.8830 \| 0.8280 \| 0.9974 \| 0.9542 \| 0.4107 \| 0.8259 \| 0.6577 \| 0.8224 \| 0.7233 \| 0.9961 \| \| 0.0764 \| 15.37 \| 1260 \| 0.2350 \| 0.7741 \| 0.8577 \| 0.9370 \| 0.9777 \| 0.5690 \| 0.9145 \| 0.8514 \| 0.8825 \| 0.8119 \| 0.9972 \| 0.9574 \| 0.4265 \| 0.8296 \| 0.6666 \| 0.8216 \| 0.7212 \| 0.9962 \| \| 0.0568 \| 15.61 \| 1280 \| 0.2420 \| 0.7629 \| 0.8407 \| 0.9343 \| 0.9813 \| 0.5093 \| 0.9057 \| 0.8360 \| 0.8871 \| 0.7680 \| 0.9973 \| 0.9560 \| 0.3937 \| 0.8246 \| 0.6536 \| 0.8142 \| 0.7025 \| 0.9960 \| \| 0.1199 \| 15.85 \| 1300 \| 0.2545 \| 0.7620 \| 0.8463 \| 0.9321 \| 0.9752 \| 0.5904 \| 0.9180 \| 0.7196 \| 0.9135 \| 0.8090 \| 0.9981 \| 0.9557 \| 0.4209 \| 0.8276 \| 0.6064 \| 0.8098 \| 0.7171 \| 0.9964 \| \| 0.7094 \| 16.1 \| 1320 \| 0.2446 \| 0.7584 \| 0.8409 \| 0.9314 \| 0.9790 \| 0.5580 \| 0.9151 \| 0.7301 \| 0.9070 \| 0.7993 \| 0.9979 \| 0.9542 \| 0.4042 \| 0.8218 \| 0.6091 \| 0.8088 \| 0.7145 \| 0.9963 \| \| 0.0321 \| 16.34 \| 1340 \| 0.2652 \| 0.7585 \| 0.8329 \| 0.9340 \| 0.9787 \| 0.5076 \| 0.9089 \| 0.6924 \| 0.9365 \| 0.8091 \| 0.9974 \| 0.9538 \| 0.3925 \| 0.8214 \| 0.6173 \| 0.8211 \| 0.7075 \| 0.9962 \| \| 0.1328 \| 16.59 \| 1360 \| 0.2322 \| 0.7587 \| 0.8403 \| 0.9327 \| 0.9805 \| 0.5174 \| 0.9092 \| 0.7077 \| 0.9123 \| 0.8570 \| 0.9977 \| 0.9558 \| 0.3966 \| 0.8276 \| 0.6071 \| 0.8146 \| 0.7132 \| 0.9959 \| \| 0.0637 \| 16.83 \| 1380 \| 0.2331 \| 0.7615 \| 0.8441 \| 0.9322 \| 0.9831 \| 0.5529 \| 0.8983 \| 0.7412 \| 0.9048 \| 0.8305 \| 0.9976 \| 0.9530 \| 0.4111 \| 0.8243 \| 0.6155 \| 0.8104 \| 0.7201 \| 0.9961 \| \| 0.3028 \| 17.07 \| 1400 \| 0.2446 \| 0.7572 \| 0.8367 \| 0.9312 \| 0.9804 \| 0.5135 \| 0.9061 \| 0.7279 \| 0.9044 \| 0.8263 \| 0.9981 \| 0.9548 \| 0.3970 \| 0.8212 \| 0.6048 \| 0.8084 \| 0.7181 \| 0.9962 \| \| 0.0479 \| 17.32 \| 1420 \| 0.2556 \| 0.7609 \| 0.8506 \| 0.9295 \| 0.9778 \| 0.6127 \| 0.9095 \| 0.7802 \| 0.8835 \| 0.7929 \| 0.9974 \| 0.9556 \| 0.4318 \| 0.8241 \| 0.6105 \| 0.7988 \| 0.7095 \| 0.9963 \| \| 0.0645 \| 17.56 \| 1440 \| 0.2530 \| 0.7587 \| 0.8480 \| 0.9283 \| 0.9769 \| 0.5933 \| 0.9080 \| 0.7729 \| 0.8775 \| 0.8091 \| 0.9985 \| 0.9543 \| 0.4244 \| 0.8268 \| 0.5993 \| 0.7945 \| 0.7155 \| 0.9962 \| \| 0.0513 \| 17.8 \| 1460 \| 0.2451 \| 0.7598 \| 0.8467 \| 0.9306 \| 0.9794 \| 0.5549 \| 0.9064 \| 0.7567 \| 0.8863 \| 0.8448 \| 0.9985 \| 0.9547 \| 0.4093 \| 0.8259 \| 0.6076 \| 0.8039 \| 0.7214 \| 0.9961 \| \| 0.0387 \| 18.05 \| 1480 \| 0.2374 \| 0.7625 \| 0.8446 \| 0.9344 \| 0.9810 \| 0.5392 \| 0.9007 \| 0.7115 \| 0.9214 \| 0.8609 \| 0.9975 \| 0.9539 \| 0.4025 \| 0.8249 \| 0.6196 \| 0.8218 \| 0.7193 \| 0.9958 \| \| 0.0903 \| 18.29 \| 1500 \| 0.2353 \| 0.7662 \| 0.8468 \| 0.9351 \| 0.9820 \| 0.5342 \| 0.9097 \| 0.8100 \| 0.8918 \| 0.8030 \| 0.9971 \| 0.9549 \| 0.4053 \| 0.8261 \| 0.6487 \| 0.8190 \| 0.7130 \| 0.9961 \| \| 0.0832 \| 18.54 \| 1520 \| 0.2372 \| 0.7677 \| 0.8428 \| 0.9375 \| 0.9807 \| 0.5172 \| 0.9098 \| 0.7757 \| 0.9184 \| 0.8007 \| 0.9970 \| 0.9563 \| 0.3981 \| 0.8264 \| 0.6574 \| 0.8284 \| 0.7113 \| 0.9961 \| \| 0.0601 \| 18.78 \| 1540 \| 0.2473 \| 0.7741 \| 0.8607 \| 0.9366 \| 0.9771 \| 0.6169 \| 0.9135 \| 0.8532 \| 0.8866 \| 0.7798 \| 0.9976 \| 0.9559 \| 0.4365 \| 0.8295 \| 0.6630 \| 0.8221 \| 0.7154 \| 0.9965 \| \| 0.0516 \| 19.02 \| 1560 \| 0.2363 \| 0.7731 \| 0.8556 \| 0.9369 \| 0.9792 \| 0.5591 \| 0.9075 \| 0.8329 \| 0.8883 \| 0.8243 \| 0.9981 \| 0.9563 \| 0.4189 \| 0.8305 \| 0.6623 \| 0.8215 \| 0.7256 \| 0.9964 \| \| 0.0782 \| 19.27 \| 1580 \| 0.2454 \| 0.7651 \| 0.8426 \| 0.9341 \| 0.9813 \| 0.5266 \| 0.9008 \| 0.7847 \| 0.9005 \| 0.8059 \| 0.9981 \| 0.9543 \| 0.4057 \| 0.8280 \| 0.6356 \| 0.8141 \| 0.7217 \| 0.9961 \| \| 0.0221 \| 19.51 \| 1600 \| 0.2540 \| 0.7660 \| 0.8474 \| 0.9333 \| 0.9785 \| 0.5946 \| 0.9085 \| 0.7579 \| 0.9117 \| 0.7828 \| 0.9976 \| 0.9543 \| 0.4320 \| 0.8265 \| 0.6259 \| 0.8134 \| 0.7131 \| 0.9964 \| \| 0.0283 \| 19.76 \| 1620 \| 0.2623 \| 0.7662 \| 0.8588 \| 0.9320 \| 0.9750 \| 0.6488 \| 0.9141 \| 0.7503 \| 0.8988 \| 0.8266 \| 0.9981 \| 0.9549 \| 0.4395 \| 0.8271 \| 0.6123 \| 0.8092 \| 0.7240 \| 0.9964 \| \| 0.1029 \| 20.0 \| 1640 \| 0.2747 \| 0.7633 \| 0.8522 \| 0.9299 \| 0.9767 \| 0.6031 \| 0.9118 \| 0.7738 \| 0.8809 \| 0.8213 \| 0.9981 \| 0.9539 \| 0.4336 \| 0.8317 \| 0.6053 \| 0.7991 \| 0.7235 \| 0.9962 \| \| 0.0731 \| 20.24 \| 1660 \| 0.2650 \| 0.7621 \| 0.8529 \| 0.9294 \| 0.9794 \| 0.6019 \| 0.9106 \| 0.7555 \| 0.8790 \| 0.8453 \| 0.9983 \| 0.9552 \| 0.4310 \| 0.8288 \| 0.5977 \| 0.7971 \| 0.7288 \| 0.9963 \| \| 0.2587 \| 20.49 \| 1680 \| 0.2767 \| 0.7602 \| 0.8430 \| 0.9311 \| 0.9794 \| 0.5600 \| 0.9158 \| 0.7217 \| 0.9023 \| 0.8234 \| 0.9985 \| 0.9552 \| 0.4160 \| 0.8239 \| 0.5994 \| 0.8073 \| 0.7237 \| 0.9961 \| \| 0.1071 \| 20.73 \| 1700 \| 0.2826 \| 0.7607 \| 0.8443 \| 0.9311 \| 0.9805 \| 0.5820 \| 0.9125 \| 0.7122 \| 0.9091 \| 0.8156 \| 0.9980 \| 0.9548 \| 0.4239 \| 0.8225 \| 0.5976 \| 0.8080 \| 0.7220 \| 0.9963 \| \| 0.0323 \| 20.98 \| 1720 \| 0.2620 \| 0.7621 \| 0.8522 \| 0.9293 \| 0.9801 \| 0.6139 \| 0.9065 \| 0.7633 \| 0.8829 \| 0.8215 \| 0.9975 \| 0.9551 \| 0.4342 \| 0.8296 \| 0.5996 \| 0.7968 \| 0.7231 \| 0.9963 \| \| 0.1072 \| 21.22 \| 1740 \| 0.2592 \| 0.7614 \| 0.8426 \| 0.9315 \| 0.9824 \| 0.5483 \| 0.9094 \| 0.7402 \| 0.8997 \| 0.8211 \| 0.9974 \| 0.9546 \| 0.4149 \| 0.8257 \| 0.6074 \| 0.8078 \| 0.7230 \| 0.9961 \| \| 0.0732 \| 21.46 \| 1760 \| 0.2598 \| 0.7654 \| 0.8497 \| 0.9327 \| 0.9795 \| 0.5819 \| 0.9130 \| 0.7528 \| 0.8994 \| 0.8240 \| 0.9976 \| 0.9557 \| 0.4265 \| 0.8275 \| 0.6163 \| 0.8106 \| 0.7248 \| 0.9963 \| \| 0.0603 \| 21.71 \| 1780 \| 0.2581 \| 0.7650 \| 0.8503 \| 0.9320 \| 0.9790 \| 0.5874 \| 0.9130 \| 0.7452 \| 0.8984 \| 0.8315 \| 0.9974 \| 0.9556 \| 0.4282 \| 0.8302 \| 0.6095 \| 0.8070 \| 0.7280 \| 0.9963 \| \| 0.0548 \| 21.95 \| 1800 \| 0.2520 \| 0.7649 \| 0.8598 \| 0.9300 \| 0.9747 \| 0.6344 \| 0.9218 \| 0.7885 \| 0.8683 \| 0.8322 \| 0.9988 \| 0.9560 \| 0.4352 \| 0.8339 \| 0.6082 \| 0.7956 \| 0.7291 \| 0.9963 \| \| 0.0503 \| 22.2 \| 1820 \| 0.2521 \| 0.7657 \| 0.8528 \| 0.9317 \| 0.9799 \| 0.6030 \| 0.9077 \| 0.7726 \| 0.8890 \| 0.8193 \| 0.9983 \| 0.9558 \| 0.4312 \| 0.8324 \| 0.6150 \| 0.8034 \| 0.7257 \| 0.9964 \| \| 0.0356 \| 22.44 \| 1840 \| 0.2491 \| 0.7669 \| 0.8551 \| 0.9328 \| 0.9783 \| 0.6119 \| 0.9086 \| 0.7470 \| 0.9004 \| 0.8412 \| 0.9983 \| 0.9568 \| 0.4338 \| 0.8310 \| 0.6140 \| 0.8091 \| 0.7271 \| 0.9966 \| \| 0.0381 \| 22.68 \| 1860 \| 0.2660 \| 0.7644 \| 0.8458 \| 0.9330 \| 0.9805 \| 0.5651 \| 0.9095 \| 0.7344 \| 0.9094 \| 0.8242 \| 0.9973 \| 0.9559 \| 0.4213 \| 0.8289 \| 0.6129 \| 0.8116 \| 0.7240 \| 0.9964 \| \| 0.0671 \| 22.93 \| 1880 \| 0.2633 \| 0.7664 \| 0.8517 \| 0.9332 \| 0.9787 \| 0.5970 \| 0.9067 \| 0.7371 \| 0.9083 \| 0.8360 \| 0.9982 \| 0.9559 \| 0.4307 \| 0.8286 \| 0.6140 \| 0.8129 \| 0.7261 \| 0.9966 \| \| 0.1123 \| 23.17 \| 1900 \| 0.2462 \| 0.7659 \| 0.8489 \| 0.9337 \| 0.9790 \| 0.5848 \| 0.9088 \| 0.7332 \| 0.9121 \| 0.8253 \| 0.9987 \| 0.9556 \| 0.4257 \| 0.8275 \| 0.6161 \| 0.8154 \| 0.7251 \| 0.9963 \| \| 0.0476 \| 23.41 \| 1920 \| 0.2498 \| 0.7665 \| 0.8490 \| 0.9336 \| 0.9789 \| 0.5651 \| 0.9133 \| 0.7813 \| 0.8942 \| 0.8124 \| 0.9978 \| 0.9557 \| 0.4204 \| 0.8297 \| 0.6267 \| 0.8128 \| 0.7238 \| 0.9966 \| \| 0.0999 \| 23.66 \| 1940 \| 0.2556 \| 0.7678 \| 0.8539 \| 0.9335 \| 0.9779 \| 0.6072 \| 0.9123 \| 0.7735 \| 0.8972 \| 0.8109 \| 0.9985 \| 0.9561 \| 0.4335 \| 0.8291 \| 0.6245 \| 0.8127 \| 0.7223 \| 0.9966 \| \| 0.0639 \| 23.9 \| 1960 \| 0.2467 \| 0.7659 \| 0.8480 \| 0.9337 \| 0.9799 \| 0.5431 \| 0.9126 \| 0.8278 \| 0.8777 \| 0.7960 \| 0.9987 \| 0.9547 \| 0.4119 \| 0.8279 \| 0.6398 \| 0.8137 \| 0.7167 \| 0.9964 \| \| 0.0718 \| 24.15 \| 1980 \| 0.2469 \| 0.7667 \| 0.8484 \| 0.9341 \| 0.9804 \| 0.5609 \| 0.9068 \| 0.7785 \| 0.8983 \| 0.8160 \| 0.9982 \| 0.9546 \| 0.4190 \| 0.8271 \| 0.6306 \| 0.8159 \| 0.7232 \| 0.9965 \| \| 0.0578 \| 24.39 \| 2000 \| 0.2466 \| 0.7668 \| 0.8490 \| 0.9339 \| 0.9795 \| 0.5737 \| 0.9089 \| 0.7591 \| 0.9041 \| 0.8194 \| 0.9983 \| 0.9551 \| 0.4249 \| 0.8271 \| 0.6246 \| 0.8155 \| 0.7241 \| 0.9965 \| \| 0.0664 \| 24.63 \| 2020 \| 0.2530 \| 0.7640 \| 0.8449 \| 0.9328 \| 0.9784 \| 0.5888 \| 0.9101 \| 0.7452 \| 0.9125 \| 0.7808 \| 0.9987 \| 0.9549 \| 0.4305 \| 0.8255 \| 0.6185 \| 0.8132 \| 0.7088 \| 0.9963 \| \| 0.7601 \| 24.88 \| 2040 \| 0.2531 \| 0.7677 \| 0.8502 \| 0.9340 \| 0.9810 \| 0.5654 \| 0.8995 \| 0.7891 \| 0.8969 \| 0.8221 \| 0.9974 \| 0.9535 \| 0.4217 \| 0.8288 \| 0.6339 \| 0.8151 \| 0.7244 \| 0.9964 \| ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1
johnhse/pokemon-lora	johnhse	2024-02-27T11:01:47Z	1	0	diffusers	[ "diffusers", "safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "lora", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2024-02-27T08:33:39Z	--- license: creativeml-openrail-m library_name: diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - lora inference: true base_model: runwayml/stable-diffusion-v1-5 --- <!-- 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. --> # LoRA text2image fine-tuning - johnhse/pokemon-lora These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset. You can find some example images in the following. ![img_0](./image_0.png) ![img_1](./image_1.png) ![img_2](./image_2.png) ![img_3](./image_3.png) ## 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]
huseinzol05/conformer-2M-ctc	huseinzol05	2024-02-27T10:57:07Z	51	0	transformers	[ "transformers", "safetensors", "conformer", "feature-extraction", "custom_code", "arxiv:1910.09700", "region:us" ]	feature-extraction	2024-02-27T10:56:59Z	--- 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]
peldrak/segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512	peldrak	2024-02-27T10:52:00Z	189	0	transformers	[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:nvidia/segformer-b3-finetuned-ade-512-512", "base_model:finetune:nvidia/segformer-b3-finetuned-ade-512-512", "license:other", "endpoints_compatible", "region:us" ]	image-segmentation	2024-02-27T09:29:58Z	--- license: other base_model: nvidia/segformer-b3-finetuned-ade-512-512 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512 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. --> # segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512 This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b3-finetuned-ade-512-512) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.2343 - Mean Iou: 0.7550 - Mean Accuracy: 0.8157 - Overall Accuracy: 0.9435 - Accuracy Water: 0.9775 - Accuracy Whitewater: 0.2651 - Accuracy Sediment: 0.9504 - Accuracy Other Natural Terrain: 0.8170 - Accuracy Vegetation: 0.8956 - Accuracy Development: 0.8082 - Accuracy Unknown: 0.9956 - Iou Water: 0.9507 - Iou Whitewater: 0.2519 - Iou Sediment: 0.8719 - Iou Other Natural Terrain: 0.7298 - Iou Vegetation: 0.7848 - Iou Development: 0.7015 - Iou Unknown: 0.9946 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 25 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Mean Iou \| Mean Accuracy \| Overall Accuracy \| Accuracy Water \| Accuracy Whitewater \| Accuracy Sediment \| Accuracy Other Natural Terrain \| Accuracy Vegetation \| Accuracy Development \| Accuracy Unknown \| Iou Water \| Iou Whitewater \| Iou Sediment \| Iou Other Natural Terrain \| Iou Vegetation \| Iou Development \| Iou Unknown \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:-------------:\|:----------------:\|:--------------:\|:-------------------:\|:-----------------:\|:------------------------------:\|:-------------------:\|:--------------------:\|:----------------:\|:---------:\|:--------------:\|:------------:\|:-------------------------:\|:--------------:\|:---------------:\|:-----------:\| \| 1.3152 \| 0.24 \| 20 \| 1.1371 \| 0.3592 \| 0.4647 \| 0.7315 \| 0.9430 \| 0.0 \| 0.2992 \| 0.0547 \| 0.7991 \| 0.1760 \| 0.9809 \| 0.6706 \| 0.0 \| 0.2742 \| 0.0502 \| 0.4041 \| 0.1413 \| 0.9741 \| \| 1.2237 \| 0.49 \| 40 \| 0.7602 \| 0.4366 \| 0.5444 \| 0.8084 \| 0.9568 \| 0.0 \| 0.8684 \| 0.0674 \| 0.8738 \| 0.0645 \| 0.9803 \| 0.8767 \| 0.0 \| 0.5931 \| 0.0668 \| 0.4759 \| 0.0643 \| 0.9792 \| \| 0.8849 \| 0.73 \| 60 \| 0.5319 \| 0.5122 \| 0.6082 \| 0.8591 \| 0.9603 \| 0.0 \| 0.9492 \| 0.3503 \| 0.9236 \| 0.0824 \| 0.9915 \| 0.9197 \| 0.0 \| 0.6535 \| 0.3355 \| 0.6080 \| 0.0822 \| 0.9867 \| \| 0.7138 \| 0.98 \| 80 \| 0.4433 \| 0.5645 \| 0.6474 \| 0.8886 \| 0.9732 \| 0.0 \| 0.9297 \| 0.6001 \| 0.9305 \| 0.1018 \| 0.9962 \| 0.9208 \| 0.0 \| 0.7143 \| 0.5271 \| 0.7005 \| 0.1015 \| 0.9872 \| \| 0.4057 \| 1.22 \| 100 \| 0.3726 \| 0.6034 \| 0.6801 \| 0.9021 \| 0.9746 \| 0.0 \| 0.9397 \| 0.6993 \| 0.8983 \| 0.2557 \| 0.9930 \| 0.9325 \| 0.0 \| 0.7428 \| 0.6061 \| 0.7024 \| 0.2508 \| 0.9894 \| \| 0.5947 \| 1.46 \| 120 \| 0.3407 \| 0.6003 \| 0.6767 \| 0.9043 \| 0.9809 \| 0.0 \| 0.9493 \| 0.7424 \| 0.8936 \| 0.1789 \| 0.9916 \| 0.9264 \| 0.0 \| 0.7549 \| 0.6223 \| 0.7327 \| 0.1776 \| 0.9881 \| \| 0.324 \| 1.71 \| 140 \| 0.3482 \| 0.6087 \| 0.6906 \| 0.8992 \| 0.9661 \| 0.0 \| 0.9787 \| 0.8298 \| 0.7234 \| 0.3403 \| 0.9958 \| 0.9342 \| 0.0 \| 0.6806 \| 0.6506 \| 0.6853 \| 0.3202 \| 0.9901 \| \| 0.5283 \| 1.95 \| 160 \| 0.2851 \| 0.6729 \| 0.7389 \| 0.9265 \| 0.9757 \| 0.0 \| 0.9427 \| 0.8225 \| 0.8647 \| 0.5717 \| 0.9954 \| 0.9346 \| 0.0 \| 0.8134 \| 0.7038 \| 0.7573 \| 0.5116 \| 0.9895 \| \| 0.4225 \| 2.2 \| 180 \| 0.2628 \| 0.6674 \| 0.7330 \| 0.9232 \| 0.9642 \| 0.0 \| 0.9175 \| 0.8301 \| 0.9002 \| 0.5261 \| 0.9928 \| 0.9183 \| 0.0 \| 0.8127 \| 0.7082 \| 0.7438 \| 0.4982 \| 0.9904 \| \| 0.2334 \| 2.44 \| 200 \| 0.2544 \| 0.6811 \| 0.7448 \| 0.9282 \| 0.9783 \| 0.0 \| 0.9488 \| 0.7218 \| 0.9115 \| 0.6576 \| 0.9956 \| 0.9326 \| 0.0 \| 0.8252 \| 0.6780 \| 0.7556 \| 0.5856 \| 0.9905 \| \| 0.3386 \| 2.68 \| 220 \| 0.2385 \| 0.6844 \| 0.7511 \| 0.9279 \| 0.9773 \| 0.0 \| 0.9358 \| 0.7831 \| 0.8913 \| 0.6838 \| 0.9864 \| 0.9298 \| 0.0 \| 0.8409 \| 0.6831 \| 0.7590 \| 0.5939 \| 0.9845 \| \| 0.2847 \| 2.93 \| 240 \| 0.2321 \| 0.6817 \| 0.7530 \| 0.9275 \| 0.9694 \| 0.0 \| 0.9472 \| 0.8888 \| 0.7828 \| 0.6848 \| 0.9980 \| 0.9334 \| 0.0 \| 0.8187 \| 0.7156 \| 0.7399 \| 0.5752 \| 0.9895 \| \| 0.6314 \| 3.17 \| 260 \| 0.2118 \| 0.6995 \| 0.7630 \| 0.9362 \| 0.9725 \| 0.0 \| 0.9494 \| 0.8463 \| 0.8667 \| 0.7094 \| 0.9965 \| 0.9404 \| 0.0 \| 0.8324 \| 0.7431 \| 0.7783 \| 0.6104 \| 0.9916 \| \| 0.2687 \| 3.41 \| 280 \| 0.2140 \| 0.6992 \| 0.7599 \| 0.9359 \| 0.9739 \| 0.0 \| 0.9480 \| 0.8333 \| 0.8776 \| 0.6886 \| 0.9976 \| 0.9348 \| 0.0 \| 0.8242 \| 0.7413 \| 0.7869 \| 0.6166 \| 0.9908 \| \| 0.4188 \| 3.66 \| 300 \| 0.2088 \| 0.7045 \| 0.7646 \| 0.9382 \| 0.9743 \| 0.0 \| 0.9594 \| 0.8251 \| 0.8940 \| 0.7055 \| 0.9936 \| 0.9368 \| 0.0 \| 0.8483 \| 0.7412 \| 0.7886 \| 0.6260 \| 0.9909 \| \| 0.1609 \| 3.9 \| 320 \| 0.1991 \| 0.7059 \| 0.7740 \| 0.9372 \| 0.9758 \| 0.0 \| 0.9463 \| 0.8677 \| 0.8325 \| 0.8036 \| 0.9923 \| 0.9388 \| 0.0 \| 0.8620 \| 0.7343 \| 0.7721 \| 0.6440 \| 0.9900 \| \| 0.1591 \| 4.15 \| 340 \| 0.2563 \| 0.6544 \| 0.7303 \| 0.9157 \| 0.9718 \| 0.0 \| 0.9700 \| 0.8359 \| 0.7659 \| 0.5772 \| 0.9915 \| 0.9427 \| 0.0 \| 0.7907 \| 0.6447 \| 0.6947 \| 0.5180 \| 0.9901 \| \| 0.4456 \| 4.39 \| 360 \| 0.2374 \| 0.6846 \| 0.7496 \| 0.9283 \| 0.9789 \| 0.0 \| 0.9396 \| 0.7259 \| 0.8976 \| 0.7094 \| 0.9956 \| 0.9436 \| 0.0 \| 0.8668 \| 0.6313 \| 0.7349 \| 0.6230 \| 0.9928 \| \| 0.1556 \| 4.63 \| 380 \| 0.2165 \| 0.6871 \| 0.7568 \| 0.9294 \| 0.9701 \| 0.0 \| 0.9681 \| 0.8800 \| 0.7831 \| 0.6998 \| 0.9963 \| 0.9401 \| 0.0 \| 0.8319 \| 0.7082 \| 0.7283 \| 0.6095 \| 0.9918 \| \| 0.3269 \| 4.88 \| 400 \| 0.2230 \| 0.6995 \| 0.7612 \| 0.9340 \| 0.9709 \| 0.0 \| 0.9544 \| 0.7420 \| 0.9106 \| 0.7533 \| 0.9969 \| 0.9432 \| 0.0 \| 0.8551 \| 0.6806 \| 0.7497 \| 0.6751 \| 0.9929 \| \| 0.2006 \| 5.12 \| 420 \| 0.2233 \| 0.6884 \| 0.7545 \| 0.9303 \| 0.9727 \| 0.0 \| 0.9573 \| 0.8825 \| 0.8049 \| 0.6679 \| 0.9960 \| 0.9405 \| 0.0 \| 0.8366 \| 0.7042 \| 0.7340 \| 0.6110 \| 0.9929 \| \| 0.1007 \| 5.37 \| 440 \| 0.2047 \| 0.7084 \| 0.7769 \| 0.9383 \| 0.9683 \| 0.0 \| 0.9583 \| 0.8657 \| 0.8279 \| 0.8214 \| 0.9966 \| 0.9428 \| 0.0 \| 0.8463 \| 0.7494 \| 0.7689 \| 0.6592 \| 0.9921 \| \| 0.1391 \| 5.61 \| 460 \| 0.2110 \| 0.7102 \| 0.7698 \| 0.9386 \| 0.9775 \| 0.0 \| 0.9289 \| 0.8196 \| 0.9082 \| 0.7632 \| 0.9914 \| 0.9384 \| 0.0 \| 0.8686 \| 0.7287 \| 0.7739 \| 0.6716 \| 0.9899 \| \| 0.1582 \| 5.85 \| 480 \| 0.1974 \| 0.7070 \| 0.7756 \| 0.9371 \| 0.9688 \| 0.0 \| 0.9503 \| 0.7850 \| 0.8715 \| 0.8567 \| 0.9971 \| 0.9420 \| 0.0 \| 0.8565 \| 0.7161 \| 0.7626 \| 0.6792 \| 0.9928 \| \| 0.118 \| 6.1 \| 500 \| 0.2184 \| 0.6937 \| 0.7602 \| 0.9312 \| 0.9800 \| 0.0 \| 0.9321 \| 0.8670 \| 0.8032 \| 0.7424 \| 0.9969 \| 0.9372 \| 0.0 \| 0.8535 \| 0.6900 \| 0.7355 \| 0.6468 \| 0.9929 \| \| 0.1206 \| 6.34 \| 520 \| 0.2585 \| 0.6906 \| 0.7549 \| 0.9312 \| 0.9766 \| 0.0 \| 0.9652 \| 0.7906 \| 0.8669 \| 0.6927 \| 0.9922 \| 0.9364 \| 0.0 \| 0.8134 \| 0.7155 \| 0.7562 \| 0.6218 \| 0.9910 \| \| 0.1531 \| 6.59 \| 540 \| 0.2177 \| 0.7048 \| 0.7699 \| 0.9370 \| 0.9788 \| 0.0 \| 0.9361 \| 0.8889 \| 0.8270 \| 0.7644 \| 0.9944 \| 0.9426 \| 0.0 \| 0.8647 \| 0.7215 \| 0.7629 \| 0.6492 \| 0.9926 \| \| 0.141 \| 6.83 \| 560 \| 0.2271 \| 0.7014 \| 0.7655 \| 0.9362 \| 0.9625 \| 0.0 \| 0.9726 \| 0.8432 \| 0.8655 \| 0.7186 \| 0.9957 \| 0.9403 \| 0.0 \| 0.8254 \| 0.7420 \| 0.7758 \| 0.6330 \| 0.9931 \| \| 0.1233 \| 7.07 \| 580 \| 0.2128 \| 0.7108 \| 0.7723 \| 0.9398 \| 0.9739 \| 0.0 \| 0.9529 \| 0.8535 \| 0.8659 \| 0.7646 \| 0.9954 \| 0.9430 \| 0.0 \| 0.8579 \| 0.7390 \| 0.7766 \| 0.6661 \| 0.9932 \| \| 0.0518 \| 7.32 \| 600 \| 0.2460 \| 0.6911 \| 0.7617 \| 0.9304 \| 0.9659 \| 0.0 \| 0.9711 \| 0.8530 \| 0.7962 \| 0.7486 \| 0.9969 \| 0.9426 \| 0.0 \| 0.8348 \| 0.6982 \| 0.7278 \| 0.6405 \| 0.9941 \| \| 0.1164 \| 7.56 \| 620 \| 0.2446 \| 0.6992 \| 0.7670 \| 0.9337 \| 0.9747 \| 0.0 \| 0.9534 \| 0.8651 \| 0.8042 \| 0.7752 \| 0.9963 \| 0.9432 \| 0.0 \| 0.8550 \| 0.7027 \| 0.7379 \| 0.6615 \| 0.9941 \| \| 0.1448 \| 7.8 \| 640 \| 0.2159 \| 0.7115 \| 0.7726 \| 0.9394 \| 0.9771 \| 0.0 \| 0.9510 \| 0.8102 \| 0.8822 \| 0.7928 \| 0.9952 \| 0.9435 \| 0.0 \| 0.8560 \| 0.7265 \| 0.7725 \| 0.6886 \| 0.9932 \| \| 0.4327 \| 8.05 \| 660 \| 0.2056 \| 0.7150 \| 0.7766 \| 0.9418 \| 0.9736 \| 0.0 \| 0.9551 \| 0.8341 \| 0.8786 \| 0.7980 \| 0.9966 \| 0.9443 \| 0.0 \| 0.8579 \| 0.7494 \| 0.7862 \| 0.6734 \| 0.9935 \| \| 0.1197 \| 8.29 \| 680 \| 0.2153 \| 0.7068 \| 0.7647 \| 0.9389 \| 0.9767 \| 0.0 \| 0.9434 \| 0.8219 \| 0.9024 \| 0.7126 \| 0.9963 \| 0.9417 \| 0.0 \| 0.8681 \| 0.7183 \| 0.7794 \| 0.6469 \| 0.9935 \| \| 0.1376 \| 8.54 \| 700 \| 0.2252 \| 0.7069 \| 0.7755 \| 0.9375 \| 0.9676 \| 0.0 \| 0.9668 \| 0.8520 \| 0.8228 \| 0.8217 \| 0.9977 \| 0.9441 \| 0.0 \| 0.8448 \| 0.7397 \| 0.7594 \| 0.6667 \| 0.9934 \| \| 0.3054 \| 8.78 \| 720 \| 0.2291 \| 0.7079 \| 0.7708 \| 0.9382 \| 0.9773 \| 0.0 \| 0.9544 \| 0.8451 \| 0.8599 \| 0.7667 \| 0.9924 \| 0.9404 \| 0.0 \| 0.8559 \| 0.7306 \| 0.7749 \| 0.6626 \| 0.9912 \| \| 0.1884 \| 9.02 \| 740 \| 0.2077 \| 0.7194 \| 0.7823 \| 0.9422 \| 0.9733 \| 0.0 \| 0.9366 \| 0.8561 \| 0.8671 \| 0.8472 \| 0.9957 \| 0.9449 \| 0.0 \| 0.8750 \| 0.7354 \| 0.7776 \| 0.7092 \| 0.9936 \| \| 0.0987 \| 9.27 \| 760 \| 0.2207 \| 0.7112 \| 0.7780 \| 0.9385 \| 0.9753 \| 0.0 \| 0.9640 \| 0.8870 \| 0.8026 \| 0.8232 \| 0.9938 \| 0.9414 \| 0.0 \| 0.8349 \| 0.7599 \| 0.7583 \| 0.6912 \| 0.9924 \| \| 0.1062 \| 9.51 \| 780 \| 0.2697 \| 0.6999 \| 0.7640 \| 0.9335 \| 0.9747 \| 0.0 \| 0.9493 \| 0.7366 \| 0.8967 \| 0.7950 \| 0.9957 \| 0.9429 \| 0.0 \| 0.8455 \| 0.6892 \| 0.7403 \| 0.6884 \| 0.9932 \| \| 0.1437 \| 9.76 \| 800 \| 0.2240 \| 0.7069 \| 0.7715 \| 0.9380 \| 0.9692 \| 0.0 \| 0.9578 \| 0.8028 \| 0.8838 \| 0.7906 \| 0.9960 \| 0.9451 \| 0.0 \| 0.8487 \| 0.7271 \| 0.7701 \| 0.6635 \| 0.9935 \| \| 0.0806 \| 10.0 \| 820 \| 0.2262 \| 0.7068 \| 0.7692 \| 0.9388 \| 0.9788 \| 0.0 \| 0.9596 \| 0.8313 \| 0.8618 \| 0.7573 \| 0.9960 \| 0.9447 \| 0.0 \| 0.8471 \| 0.7398 \| 0.7748 \| 0.6479 \| 0.9934 \| \| 0.1172 \| 10.24 \| 840 \| 0.2594 \| 0.6971 \| 0.7598 \| 0.9336 \| 0.9751 \| 0.0 \| 0.9497 \| 0.7498 \| 0.8983 \| 0.7482 \| 0.9975 \| 0.9432 \| 0.0 \| 0.8596 \| 0.6762 \| 0.7500 \| 0.6570 \| 0.9934 \| \| 0.3204 \| 10.49 \| 860 \| 0.2114 \| 0.7167 \| 0.7775 \| 0.9417 \| 0.9735 \| 0.0 \| 0.9405 \| 0.8401 \| 0.8791 \| 0.8117 \| 0.9977 \| 0.9440 \| 0.0 \| 0.8751 \| 0.7310 \| 0.7812 \| 0.6925 \| 0.9933 \| \| 0.18 \| 10.73 \| 880 \| 0.2234 \| 0.7163 \| 0.7774 \| 0.9415 \| 0.9708 \| 0.0 \| 0.9606 \| 0.8125 \| 0.8921 \| 0.8111 \| 0.9950 \| 0.9458 \| 0.0 \| 0.8635 \| 0.7310 \| 0.7799 \| 0.7000 \| 0.9937 \| \| 0.1388 \| 10.98 \| 900 \| 0.2211 \| 0.7231 \| 0.7820 \| 0.9435 \| 0.9745 \| 0.0 \| 0.9282 \| 0.8094 \| 0.9115 \| 0.8533 \| 0.9971 \| 0.9442 \| 0.0 \| 0.8842 \| 0.7275 \| 0.7822 \| 0.7296 \| 0.9942 \| \| 0.3495 \| 11.22 \| 920 \| 0.2246 \| 0.7172 \| 0.7803 \| 0.9420 \| 0.9735 \| 0.0 \| 0.9535 \| 0.8467 \| 0.8540 \| 0.8361 \| 0.9985 \| 0.9443 \| 0.0 \| 0.8700 \| 0.7384 \| 0.7796 \| 0.6941 \| 0.9940 \| \| 0.1129 \| 11.46 \| 940 \| 0.2116 \| 0.7187 \| 0.7770 \| 0.9431 \| 0.9764 \| 0.0 \| 0.9480 \| 0.8252 \| 0.9009 \| 0.7927 \| 0.9954 \| 0.9460 \| 0.0 \| 0.8772 \| 0.7303 \| 0.7890 \| 0.6944 \| 0.9941 \| \| 0.1725 \| 11.71 \| 960 \| 0.2028 \| 0.7199 \| 0.7820 \| 0.9432 \| 0.9799 \| 0.0 \| 0.9457 \| 0.8285 \| 0.8723 \| 0.8515 \| 0.9962 \| 0.9442 \| 0.0 \| 0.8773 \| 0.7348 \| 0.7872 \| 0.7019 \| 0.9941 \| \| 0.1882 \| 11.95 \| 980 \| 0.2180 \| 0.7168 \| 0.7759 \| 0.9422 \| 0.9743 \| 0.0 \| 0.9556 \| 0.8052 \| 0.8990 \| 0.7998 \| 0.9974 \| 0.9460 \| 0.0 \| 0.8570 \| 0.7326 \| 0.7887 \| 0.6984 \| 0.9945 \| \| 0.1523 \| 12.2 \| 1000 \| 0.2185 \| 0.7172 \| 0.7792 \| 0.9416 \| 0.9750 \| 0.0000 \| 0.9527 \| 0.8253 \| 0.8779 \| 0.8287 \| 0.9947 \| 0.9444 \| 0.0000 \| 0.8701 \| 0.7322 \| 0.7781 \| 0.7019 \| 0.9936 \| \| 0.0959 \| 12.44 \| 1020 \| 0.2232 \| 0.7192 \| 0.7806 \| 0.9424 \| 0.9781 \| 0.0 \| 0.9452 \| 0.8150 \| 0.8840 \| 0.8469 \| 0.9953 \| 0.9444 \| 0.0 \| 0.8769 \| 0.7281 \| 0.7792 \| 0.7115 \| 0.9941 \| \| 0.0786 \| 12.68 \| 1040 \| 0.2383 \| 0.7129 \| 0.7741 \| 0.9403 \| 0.9771 \| 0.0001 \| 0.9592 \| 0.8173 \| 0.8741 \| 0.7949 \| 0.9956 \| 0.9449 \| 0.0001 \| 0.8567 \| 0.7321 \| 0.7734 \| 0.6892 \| 0.9942 \| \| 0.1079 \| 12.93 \| 1060 \| 0.2410 \| 0.7144 \| 0.7772 \| 0.9401 \| 0.9786 \| 0.0040 \| 0.9510 \| 0.7919 \| 0.8845 \| 0.8357 \| 0.9945 \| 0.9451 \| 0.0040 \| 0.8585 \| 0.7261 \| 0.7709 \| 0.7030 \| 0.9933 \| \| 0.1476 \| 13.17 \| 1080 \| 0.2192 \| 0.7130 \| 0.7782 \| 0.9403 \| 0.9718 \| 0.0008 \| 0.9582 \| 0.8334 \| 0.8548 \| 0.8309 \| 0.9975 \| 0.9458 \| 0.0008 \| 0.8536 \| 0.7367 \| 0.7733 \| 0.6859 \| 0.9950 \| \| 0.1231 \| 13.41 \| 1100 \| 0.2260 \| 0.7157 \| 0.7790 \| 0.9417 \| 0.9800 \| 0.0002 \| 0.9430 \| 0.8018 \| 0.8889 \| 0.8443 \| 0.9951 \| 0.9456 \| 0.0002 \| 0.8722 \| 0.7265 \| 0.7836 \| 0.6882 \| 0.9939 \| \| 0.0879 \| 13.66 \| 1120 \| 0.2403 \| 0.7133 \| 0.7767 \| 0.9407 \| 0.9709 \| 0.0 \| 0.9670 \| 0.8450 \| 0.8523 \| 0.8043 \| 0.9974 \| 0.9472 \| 0.0 \| 0.8539 \| 0.7357 \| 0.7748 \| 0.6864 \| 0.9951 \| \| 0.116 \| 13.9 \| 1140 \| 0.2334 \| 0.7191 \| 0.7810 \| 0.9425 \| 0.9767 \| 0.0165 \| 0.9465 \| 0.8118 \| 0.8896 \| 0.8284 \| 0.9974 \| 0.9471 \| 0.0164 \| 0.8677 \| 0.7354 \| 0.7863 \| 0.6862 \| 0.9946 \| \| 0.1264 \| 14.15 \| 1160 \| 0.2366 \| 0.7162 \| 0.7765 \| 0.9414 \| 0.9789 \| 0.0146 \| 0.9504 \| 0.8165 \| 0.8936 \| 0.7870 \| 0.9943 \| 0.9462 \| 0.0145 \| 0.8657 \| 0.7314 \| 0.7849 \| 0.6774 \| 0.9934 \| \| 0.0761 \| 14.39 \| 1180 \| 0.2227 \| 0.7198 \| 0.7792 \| 0.9427 \| 0.9789 \| 0.0180 \| 0.9509 \| 0.8127 \| 0.8924 \| 0.8044 \| 0.9968 \| 0.9469 \| 0.0179 \| 0.8670 \| 0.7339 \| 0.7858 \| 0.6921 \| 0.9948 \| \| 0.0437 \| 14.63 \| 1200 \| 0.2192 \| 0.7188 \| 0.7819 \| 0.9415 \| 0.9769 \| 0.0248 \| 0.9490 \| 0.8470 \| 0.8566 \| 0.8219 \| 0.9970 \| 0.9466 \| 0.0246 \| 0.8645 \| 0.7379 \| 0.7761 \| 0.6873 \| 0.9948 \| \| 0.0732 \| 14.88 \| 1220 \| 0.2396 \| 0.7289 \| 0.7897 \| 0.9421 \| 0.9760 \| 0.0861 \| 0.9477 \| 0.8180 \| 0.8934 \| 0.8121 \| 0.9948 \| 0.9465 \| 0.0849 \| 0.8654 \| 0.7368 \| 0.7824 \| 0.6923 \| 0.9936 \| \| 0.1376 \| 15.12 \| 1240 \| 0.2280 \| 0.7314 \| 0.7915 \| 0.9430 \| 0.9753 \| 0.0944 \| 0.9480 \| 0.8444 \| 0.8766 \| 0.8039 \| 0.9976 \| 0.9469 \| 0.0925 \| 0.8660 \| 0.7413 \| 0.7854 \| 0.6934 \| 0.9946 \| \| 0.0518 \| 15.37 \| 1260 \| 0.2378 \| 0.7289 \| 0.7880 \| 0.9422 \| 0.9746 \| 0.0885 \| 0.9501 \| 0.8424 \| 0.8832 \| 0.7807 \| 0.9963 \| 0.9460 \| 0.0864 \| 0.8661 \| 0.7345 \| 0.7828 \| 0.6920 \| 0.9946 \| \| 0.0599 \| 15.61 \| 1280 \| 0.2288 \| 0.7242 \| 0.7848 \| 0.9418 \| 0.9784 \| 0.0559 \| 0.9443 \| 0.8397 \| 0.8761 \| 0.8037 \| 0.9952 \| 0.9468 \| 0.0555 \| 0.8645 \| 0.7356 \| 0.7789 \| 0.6943 \| 0.9939 \| \| 0.0967 \| 15.85 \| 1300 \| 0.2416 \| 0.7301 \| 0.7939 \| 0.9413 \| 0.9749 \| 0.1088 \| 0.9523 \| 0.8402 \| 0.8542 \| 0.8291 \| 0.9979 \| 0.9493 \| 0.1074 \| 0.8613 \| 0.7326 \| 0.7718 \| 0.6933 \| 0.9952 \| \| 0.0593 \| 16.1 \| 1320 \| 0.2691 \| 0.7212 \| 0.7812 \| 0.9396 \| 0.9777 \| 0.0661 \| 0.9444 \| 0.7484 \| 0.9244 \| 0.8117 \| 0.9958 \| 0.9483 \| 0.0651 \| 0.8732 \| 0.6970 \| 0.7657 \| 0.7051 \| 0.9944 \| \| 0.2264 \| 16.34 \| 1340 \| 0.2362 \| 0.7237 \| 0.7854 \| 0.9420 \| 0.9756 \| 0.0505 \| 0.9512 \| 0.8124 \| 0.8846 \| 0.8266 \| 0.9969 \| 0.9469 \| 0.0499 \| 0.8610 \| 0.7362 \| 0.7802 \| 0.6966 \| 0.9948 \| \| 0.0592 \| 16.59 \| 1360 \| 0.2423 \| 0.7367 \| 0.8007 \| 0.9391 \| 0.9729 \| 0.1878 \| 0.9486 \| 0.8662 \| 0.8410 \| 0.7923 \| 0.9964 \| 0.9477 \| 0.1838 \| 0.8581 \| 0.7238 \| 0.7609 \| 0.6875 \| 0.9951 \| \| 0.1125 \| 16.83 \| 1380 \| 0.2339 \| 0.7527 \| 0.8150 \| 0.9431 \| 0.9762 \| 0.2572 \| 0.9448 \| 0.8334 \| 0.8824 \| 0.8143 \| 0.9969 \| 0.9485 \| 0.2431 \| 0.8608 \| 0.7434 \| 0.7846 \| 0.6934 \| 0.9951 \| \| 0.0603 \| 17.07 \| 1400 \| 0.2270 \| 0.7406 \| 0.8004 \| 0.9417 \| 0.9753 \| 0.1855 \| 0.9417 \| 0.8159 \| 0.8973 \| 0.7897 \| 0.9975 \| 0.9475 \| 0.1795 \| 0.8640 \| 0.7270 \| 0.7791 \| 0.6921 \| 0.9951 \| \| 0.0519 \| 17.32 \| 1420 \| 0.2306 \| 0.7467 \| 0.8067 \| 0.9430 \| 0.9751 \| 0.2083 \| 0.9472 \| 0.8316 \| 0.8892 \| 0.7984 \| 0.9969 \| 0.9491 \| 0.2023 \| 0.8660 \| 0.7348 \| 0.7845 \| 0.6952 \| 0.9950 \| \| 0.0604 \| 17.56 \| 1440 \| 0.2442 \| 0.7355 \| 0.7969 \| 0.9424 \| 0.9799 \| 0.1369 \| 0.9507 \| 0.8123 \| 0.8850 \| 0.8175 \| 0.9956 \| 0.9483 \| 0.1337 \| 0.8670 \| 0.7313 \| 0.7826 \| 0.6911 \| 0.9945 \| \| 0.0938 \| 17.8 \| 1460 \| 0.2359 \| 0.7392 \| 0.7993 \| 0.9422 \| 0.9726 \| 0.1637 \| 0.9542 \| 0.8012 \| 0.8966 \| 0.8084 \| 0.9987 \| 0.9483 \| 0.1598 \| 0.8663 \| 0.7251 \| 0.7808 \| 0.6992 \| 0.9947 \| \| 0.1024 \| 18.05 \| 1480 \| 0.2377 \| 0.7305 \| 0.7902 \| 0.9418 \| 0.9811 \| 0.1062 \| 0.9475 \| 0.8259 \| 0.8784 \| 0.7962 \| 0.9960 \| 0.9482 \| 0.1042 \| 0.8690 \| 0.7262 \| 0.7776 \| 0.6936 \| 0.9946 \| \| 0.0536 \| 18.29 \| 1500 \| 0.2309 \| 0.7358 \| 0.7961 \| 0.9424 \| 0.9756 \| 0.1348 \| 0.9526 \| 0.8292 \| 0.8784 \| 0.8046 \| 0.9975 \| 0.9502 \| 0.1325 \| 0.8695 \| 0.7282 \| 0.7786 \| 0.6971 \| 0.9948 \| \| 0.07 \| 18.54 \| 1520 \| 0.2380 \| 0.7507 \| 0.8127 \| 0.9428 \| 0.9747 \| 0.2410 \| 0.9478 \| 0.8254 \| 0.8836 \| 0.8191 \| 0.9971 \| 0.9503 \| 0.2312 \| 0.8708 \| 0.7276 \| 0.7799 \| 0.7001 \| 0.9951 \| \| 0.0692 \| 18.78 \| 1540 \| 0.2429 \| 0.7478 \| 0.8104 \| 0.9420 \| 0.9745 \| 0.2285 \| 0.9462 \| 0.8139 \| 0.8853 \| 0.8269 \| 0.9973 \| 0.9502 \| 0.2198 \| 0.8739 \| 0.7180 \| 0.7755 \| 0.7018 \| 0.9952 \| \| 0.0673 \| 19.02 \| 1560 \| 0.2288 \| 0.7352 \| 0.7966 \| 0.9409 \| 0.9769 \| 0.1525 \| 0.9459 \| 0.8163 \| 0.8795 \| 0.8081 \| 0.9974 \| 0.9470 \| 0.1472 \| 0.8681 \| 0.7192 \| 0.7749 \| 0.6955 \| 0.9945 \| \| 0.0406 \| 19.27 \| 1580 \| 0.2302 \| 0.7484 \| 0.8096 \| 0.9426 \| 0.9757 \| 0.2222 \| 0.9442 \| 0.8234 \| 0.8849 \| 0.8196 \| 0.9974 \| 0.9493 \| 0.2126 \| 0.8746 \| 0.7252 \| 0.7781 \| 0.7042 \| 0.9945 \| \| 0.0686 \| 19.51 \| 1600 \| 0.2228 \| 0.7421 \| 0.8031 \| 0.9432 \| 0.9755 \| 0.1643 \| 0.9524 \| 0.8481 \| 0.8669 \| 0.8176 \| 0.9970 \| 0.9496 \| 0.1599 \| 0.8718 \| 0.7337 \| 0.7808 \| 0.7039 \| 0.9950 \| \| 0.0559 \| 19.76 \| 1620 \| 0.2335 \| 0.7497 \| 0.8141 \| 0.9422 \| 0.9753 \| 0.2443 \| 0.9511 \| 0.8181 \| 0.8749 \| 0.8382 \| 0.9967 \| 0.9497 \| 0.2320 \| 0.8723 \| 0.7237 \| 0.7767 \| 0.6985 \| 0.9949 \| \| 0.0726 \| 20.0 \| 1640 \| 0.2381 \| 0.7439 \| 0.8067 \| 0.9417 \| 0.9796 \| 0.2054 \| 0.9492 \| 0.8341 \| 0.8658 \| 0.8182 \| 0.9949 \| 0.9484 \| 0.1952 \| 0.8690 \| 0.7270 \| 0.7748 \| 0.6985 \| 0.9941 \| \| 0.0381 \| 20.24 \| 1660 \| 0.2289 \| 0.7603 \| 0.8246 \| 0.9425 \| 0.9763 \| 0.3250 \| 0.9474 \| 0.8232 \| 0.8778 \| 0.8261 \| 0.9967 \| 0.9506 \| 0.3039 \| 0.8722 \| 0.7244 \| 0.7768 \| 0.6991 \| 0.9951 \| \| 0.1459 \| 20.49 \| 1680 \| 0.2320 \| 0.7435 \| 0.8034 \| 0.9422 \| 0.9795 \| 0.2004 \| 0.9497 \| 0.8294 \| 0.8781 \| 0.7897 \| 0.9967 \| 0.9500 \| 0.1939 \| 0.8711 \| 0.7228 \| 0.7781 \| 0.6936 \| 0.9950 \| \| 0.0515 \| 20.73 \| 1700 \| 0.2366 \| 0.7584 \| 0.8212 \| 0.9425 \| 0.9772 \| 0.3128 \| 0.9445 \| 0.8043 \| 0.8924 \| 0.8189 \| 0.9980 \| 0.9504 \| 0.2910 \| 0.8743 \| 0.7188 \| 0.7777 \| 0.7017 \| 0.9951 \| \| 0.1066 \| 20.98 \| 1720 \| 0.2450 \| 0.7615 \| 0.8249 \| 0.9420 \| 0.9723 \| 0.3449 \| 0.9531 \| 0.8283 \| 0.8804 \| 0.7978 \| 0.9973 \| 0.9506 \| 0.3225 \| 0.8704 \| 0.7218 \| 0.7762 \| 0.6941 \| 0.9950 \| \| 0.0677 \| 21.22 \| 1740 \| 0.2302 \| 0.7512 \| 0.8141 \| 0.9424 \| 0.9777 \| 0.2553 \| 0.9465 \| 0.8569 \| 0.8526 \| 0.8115 \| 0.9982 \| 0.9502 \| 0.2412 \| 0.8731 \| 0.7264 \| 0.7766 \| 0.6954 \| 0.9953 \| \| 0.0745 \| 21.46 \| 1760 \| 0.2343 \| 0.7389 \| 0.7999 \| 0.9420 \| 0.9807 \| 0.1705 \| 0.9453 \| 0.8517 \| 0.8613 \| 0.7930 \| 0.9966 \| 0.9486 \| 0.1644 \| 0.8710 \| 0.7263 \| 0.7792 \| 0.6877 \| 0.9950 \| \| 0.1053 \| 21.71 \| 1780 \| 0.2453 \| 0.7591 \| 0.8219 \| 0.9426 \| 0.9747 \| 0.3127 \| 0.9517 \| 0.8279 \| 0.8834 \| 0.8070 \| 0.9958 \| 0.9511 \| 0.2943 \| 0.8705 \| 0.7253 \| 0.7796 \| 0.6977 \| 0.9948 \| \| 0.0898 \| 21.95 \| 1800 \| 0.2224 \| 0.7525 \| 0.8145 \| 0.9435 \| 0.9767 \| 0.2480 \| 0.9498 \| 0.8216 \| 0.8848 \| 0.8237 \| 0.9972 \| 0.9501 \| 0.2357 \| 0.8693 \| 0.7325 \| 0.7856 \| 0.6988 \| 0.9953 \| \| 0.1724 \| 22.2 \| 1820 \| 0.2210 \| 0.7390 \| 0.7982 \| 0.9430 \| 0.9795 \| 0.1569 \| 0.9503 \| 0.8319 \| 0.8831 \| 0.7889 \| 0.9966 \| 0.9499 \| 0.1527 \| 0.8697 \| 0.7298 \| 0.7853 \| 0.6903 \| 0.9950 \| \| 0.1683 \| 22.44 \| 1840 \| 0.2362 \| 0.7629 \| 0.8257 \| 0.9439 \| 0.9774 \| 0.3265 \| 0.9405 \| 0.8187 \| 0.8975 \| 0.8231 \| 0.9966 \| 0.9514 \| 0.3020 \| 0.8741 \| 0.7299 \| 0.7861 \| 0.7016 \| 0.9951 \| \| 0.0613 \| 22.68 \| 1860 \| 0.2266 \| 0.7634 \| 0.8267 \| 0.9441 \| 0.9769 \| 0.3291 \| 0.9418 \| 0.8187 \| 0.8939 \| 0.8291 \| 0.9974 \| 0.9511 \| 0.3024 \| 0.8750 \| 0.7301 \| 0.7864 \| 0.7032 \| 0.9953 \| \| 0.0638 \| 22.93 \| 1880 \| 0.2321 \| 0.7650 \| 0.8286 \| 0.9438 \| 0.9755 \| 0.3469 \| 0.9500 \| 0.8305 \| 0.8831 \| 0.8173 \| 0.9972 \| 0.9519 \| 0.3208 \| 0.8735 \| 0.7297 \| 0.7852 \| 0.6986 \| 0.9953 \| \| 0.0865 \| 23.17 \| 1900 \| 0.2402 \| 0.7476 \| 0.8078 \| 0.9434 \| 0.9773 \| 0.2115 \| 0.9529 \| 0.8024 \| 0.9005 \| 0.8132 \| 0.9965 \| 0.9502 \| 0.2039 \| 0.8688 \| 0.7291 \| 0.7860 \| 0.7006 \| 0.9950 \| \| 0.183 \| 23.41 \| 1920 \| 0.2340 \| 0.7545 \| 0.8155 \| 0.9437 \| 0.9757 \| 0.2616 \| 0.9551 \| 0.8198 \| 0.8879 \| 0.8106 \| 0.9975 \| 0.9512 \| 0.2492 \| 0.8685 \| 0.7321 \| 0.7853 \| 0.7000 \| 0.9953 \| \| 0.0665 \| 23.66 \| 1940 \| 0.2250 \| 0.7580 \| 0.8206 \| 0.9439 \| 0.9756 \| 0.2861 \| 0.9518 \| 0.8188 \| 0.8857 \| 0.8279 \| 0.9979 \| 0.9513 \| 0.2691 \| 0.8718 \| 0.7316 \| 0.7853 \| 0.7015 \| 0.9953 \| \| 0.0783 \| 23.9 \| 1960 \| 0.2271 \| 0.7541 \| 0.8161 \| 0.9435 \| 0.9773 \| 0.2581 \| 0.9518 \| 0.8318 \| 0.8773 \| 0.8199 \| 0.9966 \| 0.9511 \| 0.2452 \| 0.8718 \| 0.7308 \| 0.7832 \| 0.7017 \| 0.9952 \| \| 0.0767 \| 24.15 \| 1980 \| 0.2246 \| 0.7616 \| 0.8247 \| 0.9438 \| 0.9765 \| 0.3151 \| 0.9509 \| 0.8143 \| 0.8912 \| 0.8285 \| 0.9964 \| 0.9515 \| 0.2948 \| 0.8724 \| 0.7301 \| 0.7856 \| 0.7014 \| 0.9951 \| \| 0.112 \| 24.39 \| 2000 \| 0.2314 \| 0.7669 \| 0.8310 \| 0.9438 \| 0.9743 \| 0.3599 \| 0.9503 \| 0.8198 \| 0.8892 \| 0.8259 \| 0.9972 \| 0.9520 \| 0.3326 \| 0.8731 \| 0.7290 \| 0.7844 \| 0.7016 \| 0.9953 \| \| 0.074 \| 24.63 \| 2020 \| 0.2291 \| 0.7603 \| 0.8235 \| 0.9437 \| 0.9770 \| 0.3074 \| 0.9499 \| 0.8136 \| 0.8901 \| 0.8296 \| 0.9966 \| 0.9513 \| 0.2874 \| 0.8723 \| 0.7293 \| 0.7851 \| 0.7014 \| 0.9951 \| \| 0.0684 \| 24.88 \| 2040 \| 0.2343 \| 0.7550 \| 0.8157 \| 0.9435 \| 0.9775 \| 0.2651 \| 0.9504 \| 0.8170 \| 0.8956 \| 0.8082 \| 0.9956 \| 0.9507 \| 0.2519 \| 0.8719 \| 0.7298 \| 0.7848 \| 0.7015 \| 0.9946 \| ### Framework versions - Transformers 4.35.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.14.1
AbstractPerspective/2xMistral	AbstractPerspective	2024-02-27T10:48:03Z	4	0	transformers	[ "transformers", "safetensors", "mixtral", "text-generation", "moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "mistralai/Mistral-7B-v0.1", "mlabonne/drmistral-7b", "base_model:mistralai/Mistral-7B-v0.1", "base_model:merge:mistralai/Mistral-7B-v0.1", "base_model:mlabonne/drmistral-7b", "base_model:merge:mlabonne/drmistral-7b", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T10:40:38Z	--- license: apache-2.0 tags: - moe - frankenmoe - merge - mergekit - lazymergekit - mistralai/Mistral-7B-v0.1 - mlabonne/drmistral-7b base_model: - mistralai/Mistral-7B-v0.1 - mlabonne/drmistral-7b --- # 2xMistral 2xMistral is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) * [mlabonne/drmistral-7b](https://huggingface.co/mlabonne/drmistral-7b) ## 🧩 Configuration ```yaml base_model: mistralai/Mistral-7B-v0.1 gate_mode: cheap_embed experts: - source_model: mistralai/Mistral-7B-v0.1 positive_prompts: ["general"] - source_model: mlabonne/drmistral-7b positive_prompts: ["medical"] ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "AbstractPerspective/2xMistral" tokenizer = AutoTokenizer.from_pretrained(model) pipeline = transformers.pipeline( "text-generation", model=model, model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, ) messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) print(outputs[0]["generated_text"]) ```
zeronin7/distilbert-base-uncased-finetuned-clinc	zeronin7	2024-02-27T10:44:29Z	108	0	transformers	[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-26T16:48:37Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc 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. --> # distilbert-base-uncased-finetuned-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7989 - Accuracy: 0.9177 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| No log \| 1.0 \| 318 \| 3.3192 \| 0.7390 \| \| 3.8194 \| 2.0 \| 636 \| 1.9157 \| 0.8497 \| \| 3.8194 \| 3.0 \| 954 \| 1.1867 \| 0.8981 \| \| 1.7308 \| 4.0 \| 1272 \| 0.8824 \| 0.9177 \| \| 0.9303 \| 5.0 \| 1590 \| 0.7989 \| 0.9177 \| ### Framework versions - Transformers 4.36.2 - Pytorch 2.0.0 - Datasets 2.14.5 - Tokenizers 0.15.2
mlx-community/CodeLlama-7b-Python-mlx	mlx-community	2024-02-27T10:40:53Z	27	10	mlx	[ "mlx", "llama", "facebook", "meta", "llama-2", "text-generation", "license:llama2", "region:us" ]	text-generation	2023-12-06T17:02:15Z	--- pipeline_tag: text-generation library_name: mlx inference: false tags: - facebook - meta - llama - llama-2 - mlx license: llama2 --- # CodeLlama Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the base 7B version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. This is the repository for the 7B Python fine-tuned model, in `npz` format suitable for use in Apple's MLX framework. Weights have been converted to `float16` from the original `bfloat16` type, because `numpy` is not compatible with `bfloat16` out of the box. How to use with [MLX](https://github.com/ml-explore/mlx). ```bash # Install mlx, mlx-examples, huggingface-cli pip install mlx pip install huggingface_hub hf_transfer git clone https://github.com/ml-explore/mlx-examples.git # Download model export HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download --local-dir CodeLlama-7b-Python-mlx mlx-llama/CodeLlama-7b-Python-mlx # Run example python mlx-examples/llms/llama/llama.py --prompt "def fibonacci(n):" CodeLlama-7b-Python-mlx/ CodeLlama-7b-Python-mlx/tokenizer.model --max-tokens 200 ``` Please, refer to the [original model card](https://github.com/facebookresearch/codellama/blob/main/MODEL_CARD.md) for details on CodeLlama.
haripriya126/my-pet-dog	haripriya126	2024-02-27T10:27:15Z	10	0	diffusers	[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]	text-to-image	2024-02-27T10:22:53Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by haripriya126 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/haripriya126/my-pet-dog/resolve/main/sample_images/xzg1.jpg)
bhafner/test	bhafner	2024-02-27T10:27:04Z	2	0	diffusers	[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]	text-to-image	2024-02-27T08:12:38Z	--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a bhafner person tags: - text-to-image - diffusers - autotrain inference: true --- # DreamBooth trained by AutoTrain Text encoder was not trained.
JohannesGaessler/cosmosage_v2-gguf	JohannesGaessler	2024-02-27T10:26:20Z	29	0	null	[ "gguf", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]	null	2024-02-25T13:34:06Z	--- license: apache-2.0 --- GGUF conversion of [Cosmosage v2](https://huggingface.co/Tijmen2/cosmosage_v2). The importance matrix for iq formats was calculated on the training set of Wikitext 2. The iq1\_s quant was incoherent and therefore not included.
Nishthaa321/autotrain-qr7os-gstst	Nishthaa321	2024-02-27T10:26:05Z	106	0	transformers	[ "transformers", "safetensors", "roberta", "text-classification", "autotrain", "dataset:autotrain-qr7os-gstst/autotrain-data", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T10:25:38Z	--- tags: - autotrain - text-classification widget: - text: "I love AutoTrain" datasets: - autotrain-qr7os-gstst/autotrain-data --- # Model Trained Using AutoTrain - Problem type: Text Classification ## Validation Metrics loss: 0.2146722972393036 f1: 1.0 precision: 1.0 recall: 1.0 auc: 1.0 accuracy: 1.0
RupE/alpaca-bitcoin-tweets-sentiment	RupE	2024-02-27T10:13:40Z	0	0	peft	[ "peft", "region:us" ]	null	2024-02-27T10:13:39Z	--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.4.0
FatmaYoussef/ppo-SnowballTarget	FatmaYoussef	2024-02-27T10:01:59Z	0	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget", "region:us" ]	reinforcement-learning	2024-02-27T10:01:52Z	--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # ppo Agent playing SnowballTarget This is a trained model of a ppo agent playing SnowballTarget using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A short tutorial where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: FatmaYoussef/ppo-SnowballTarget 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
FINNUMBER/FINCH_TRAIN_ALL_3600_per400_NEW_Rationale_E4	FINNUMBER	2024-02-27T09:59:18Z	4	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T09:53:57Z	--- 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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alexandrabenamar/bloomz-7b1-4Magic	alexandrabenamar	2024-02-27T09:59:18Z	4	0	transformers	[ "transformers", "safetensors", "bloom", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T09:10:20Z	--- 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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FINNUMBER/FINCH_TRAIN_SA_200_per100_NEW_Rationale_E12	FINNUMBER	2024-02-27T09:59:10Z	4	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T09:53:51Z	--- 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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ProphetOfBostrom/opus-v1-34b-4b8h-8192l-EXL2	ProphetOfBostrom	2024-02-27T09:55:42Z	2	0	transformers	[ "transformers", "pytorch", "llama", "text-generation", "unsloth", "axolotl", "exllamav2", "exl2", "4bit", "conversational", "en", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-26T22:15:38Z	--- license: other license_name: yi-license license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE language: - en pipeline_tag: text-generation tags: - unsloth - axolotl - exllamav2 - exl2 - 4bit library_name: transformers --- ### quantized with the default exl2 dataset with sequence lengths of 8192 and 400 calibration (stage 2, optimisation) lines instead of 2048/100. possibly microwaved, presumably better. ##### resulstant measurement file is present somewhere, though the default line count of 16 (still extended to 8192) was used for measurement (stage 1) ### tokenizer works. tokenizer.model is not required for use with exllama2. no promises about sketchy software by "oobabooga"* :) try tabbyAPI/tavern, or exui if you don't miss CFG ##### consider yourselves lucky it's not a safetensors.zpaq this took all night to upload and YES i did refresh my access tokens after the Whoopsie, sorry! ###### I'm sure it's fine it's just that I'll die if I ever see conda again. --- # DreamGen Opus V1 <div style="display: flex; flex-direction: row; align-items: center;"> <img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style=" border-radius: 12px; margin-right: 12px; margin-top: 0px; margin-bottom: 0px; max-width: 100px; height: auto; "/> Models for (steerable) story-writing and role-playing. <br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31). </div> ## Resources - [Opus V1 prompting guide](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy. - [Google Colab](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`. - [Python code](example/prompt/format.py) to format the prompt correctly. <img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style=" padding: 12px; border-radius: 12px; border: 2px solid #f9a8d4; background: rgb(9, 9, 11); "/> ## Prompting <details> <summary>The models use an extended version of ChatML.</summary> ``` <\|im_start\|>system (Story description in the right format here) (Typically consists of plot description, style description and characters)<\|im_end\|> <\|im_start\|>user (Your instruction on how the story should continue)<\|im_end\|> <\|im_start\|>text names= Alice (Continuation of the story from the Alice character)<\|im_end\|> <\|im_start\|>text (Continuation of the story from no character in particular (pure narration))<\|im_end\|> <\|im_start\|>user (Your instruction on how the story should continue)<\|im_end\|> <\|im_start\|>text names= Bob (Continuation of the story from the Bob character)<\|im_end\|> ``` The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names. Pay attention to the following: - The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play. - There can be multiple subsequent message with a `text` role, especially if names are involved. - There can be multiple names attached to a message. - The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names. </details> While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance. Here's how you can prompt the model for the following tasks - Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing): - Input: - System prompt: You provide story / role-play description, which consists of: - Plot description - Style description - Characters and their descriptions - Conversation turns: - Text / message turn: This represents part of the story or role play - Instruction: This tells the model what should happen next - Output: Continuation of the story / role-play. - [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description) - Input: A story, or a few chapters of a story. - Output: A description of the story or chapters. - [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description) - Input: A story, or a few chapters of a story, set of characters. - Output: A description of the characters. - [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description) - Input: A story, or a few chapters of a story. - Output: A description the style of the story. - [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions) - Input: A brief plot description and the desired number of chapters. - Output: A description for each chapter. - And more... ### Sampling params For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`. You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures. ## Dataset The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long. All story-writing and role-playing examples were based on human-written text. ![token count distribution](images/token_count_cum__token_bucket.png) ## Running the model The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization. I recommend using these model versions: - 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b) - 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq) ### Running on DreamGen.com (free) You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required. ### Running Locally - Make sure your prompt is as close as possible to the Opus V1* - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly. - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1) - [Read the prompt formatting code](example/prompt/format.py) - Make sure `<\|im_start\|>` and `<\|im_end\|>` are tokenized correctly - vLLM - [Google Colab](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU. - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario. - SillyTavern - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp) - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect - LM Studio - [Config](configs/lmstudio/preset.json) - Just like ChatML, just changed "assistant" to "text" role. - HuggingFace - [Chat template](tokenizer_config.json#L51) - Just like ChatML, just changed "assistant" to "text" role. ## Known Issues - 34B tokenization: - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))). - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token. - Overall impact should be minor. - 34B repetition: - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes. - GGUF: - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version. - Ooba: - The tokenization might be messed up. Some users reported that `<\|im_start\|>` and `<\|im_end\|>` are tokenized as multiple tokens. ## Community Join the DreamGen community on [Discord](https://dreamgen.com/discord) to get early access to new models. ## License - This model is intended for personal use only, other use is not permitted. --- # DreamGen Opus V1 <div style="display: flex; flex-direction: row; align-items: center;"> <img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style=" border-radius: 12px; margin-right: 12px; margin-top: 0px; margin-bottom: 0px; max-width: 100px; height: auto; "/> Models for (steerable) story-writing and role-playing. <br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31). </div> ## Resources - [Opus V1 prompting guide](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy. - [Google Colab](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`. - [Python code](example/prompt/format.py) to format the prompt correctly. <img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style=" padding: 12px; border-radius: 12px; border: 2px solid #f9a8d4; background: rgb(9, 9, 11); "/> ## Prompting <details> <summary>The models use an extended version of ChatML.</summary> ``` <\|im_start\|>system (Story description in the right format here) (Typically consists of plot description, style description and characters)<\|im_end\|> <\|im_start\|>user (Your instruction on how the story should continue)<\|im_end\|> <\|im_start\|>text names= Alice (Continuation of the story from the Alice character)<\|im_end\|> <\|im_start\|>text (Continuation of the story from no character in particular (pure narration))<\|im_end\|> <\|im_start\|>user (Your instruction on how the story should continue)<\|im_end\|> <\|im_start\|>text names= Bob (Continuation of the story from the Bob character)<\|im_end\|> ``` The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names. Pay attention to the following: - The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play. - There can be multiple subsequent message with a `text` role, especially if names are involved. - There can be multiple names attached to a message. - The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names. </details> While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance. Here's how you can prompt the model for the following tasks - Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing): - Input: - System prompt: You provide story / role-play description, which consists of: - Plot description - Style description - Characters and their descriptions - Conversation turns: - Text / message turn: This represents part of the story or role play - Instruction: This tells the model what should happen next - Output: Continuation of the story / role-play. - [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description) - Input: A story, or a few chapters of a story. - Output: A description of the story or chapters. - [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description) - Input: A story, or a few chapters of a story, set of characters. - Output: A description of the characters. - [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description) - Input: A story, or a few chapters of a story. - Output: A description the style of the story. - [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions) - Input: A brief plot description and the desired number of chapters. - Output: A description for each chapter. - And more... ### Sampling params For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`. You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures. ## Dataset The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long. All story-writing and role-playing examples were based on human-written text. ![token count distribution](images/token_count_cum__token_bucket.png) ## Running the model The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization. I recommend using these model versions: - 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b) - 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq) ### Running on DreamGen.com (free) You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required. ### Running Locally - Make sure your prompt is as close as possible to the Opus V1 - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly. - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1) - [Read the prompt formatting code](example/prompt/format.py) - Make sure `<\|im_start\|>` and `<\|im_end\|>` are tokenized correctly - vLLM - [Google Colab](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU. - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario. - SillyTavern - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp) - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect - LM Studio - [Config](configs/lmstudio/preset.json) - Just like ChatML, just changed "assistant" to "text" role. - HuggingFace - [Chat template](tokenizer_config.json#L51) - Just like ChatML, just changed "assistant" to "text" role. ## Known Issues - 34B tokenization: - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))). - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token. - Overall impact should be minor. - 34B repetition: - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes. - GGUF: - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version. - Ooba: - The tokenization might be messed up. Some users reported that `<\|im_start\|>` and `<\|im_end\|>` are tokenized as multiple tokens. ## Community Join the DreamGen community on [Discord](https://dreamgen.com/discord) to get early access to new models. ## License - This model is intended for personal use only, other use is not permitted.
DimalChathuranga/marian-finetuned-kde4-en-to-fr	DimalChathuranga	2024-02-27T09:55:34Z	104	0	transformers	[ "transformers", "tensorboard", "safetensors", "marian", "text2text-generation", "translation", "generated_from_trainer", "base_model:Helsinki-NLP/opus-mt-en-fr", "base_model:finetune:Helsinki-NLP/opus-mt-en-fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-27T06:34:32Z	--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-fr tags: - translation - generated_from_trainer model-index: - name: marian-finetuned-kde4-en-to-fr 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. --> # marian-finetuned-kde4-en-to-fr This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2
Stopwolf/Mustra-7B-Instruct-v0.1	Stopwolf	2024-02-27T09:54:35Z	46	1	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "merge", "mergekit", "lazymergekit", "gordicaleksa/YugoGPT", "mistralai/Mistral-7B-Instruct-v0.2", "conversational", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T09:50:23Z	--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - gordicaleksa/YugoGPT - mistralai/Mistral-7B-Instruct-v0.2 --- # Mustra-7B-Instruct-v0.1 Mustra-7B-Instruct-v0.1 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit): * [gordicaleksa/YugoGPT](https://huggingface.co/gordicaleksa/YugoGPT) * [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) ## 🧩 Configuration ```yaml slices: - sources: - model: gordicaleksa/YugoGPT layer_range: [0, 32] - model: mistralai/Mistral-7B-Instruct-v0.2 layer_range: [0, 32] merge_method: slerp base_model: mistralai/Mistral-7B-Instruct-v0.2 parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.75 dtype: bfloat16 ```
FINNUMBER/Yi-Ko-6B-Finch-NQA-FULL-Hyper-epoch3	FINNUMBER	2024-02-27T09:48:29Z	4	0	transformers	[ "transformers", "safetensors", "llama", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T07:20:29Z	--- 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]
yvelos/Annotator_4_Mi	yvelos	2024-02-27T09:46:18Z	0	0	transformers	[ "transformers", "safetensors", "text-generation", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	text-generation	2024-02-23T20:06:31Z	--- library_name: transformers pipeline_tag: text-generation --- # 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. 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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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Jhanu/my-pet-dog	Jhanu	2024-02-27T09:38:44Z	0	0	diffusers	[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]	text-to-image	2024-02-27T09:32:59Z	--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by Jhanu following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/Jhanu/my-pet-dog/resolve/main/sample_images/dog.jpg)
orzhan/bart-transcription-aggregation	orzhan	2024-02-27T09:38:24Z	108	0	transformers	[ "transformers", "pytorch", "safetensors", "bart", "text2text-generation", "ru", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2022-03-02T23:29:05Z	--- language: ru --- BART model fine-tuned to aggregate crowd-sourced transcriptions. Repository: [GitHub](https://github.com/orzhan/bart-transcription-aggregation)
JinghuiLuAstronaut/PaDeLLM_llama2_7b_ace05	JinghuiLuAstronaut	2024-02-27T09:38:11Z	6	1	transformers	[ "transformers", "safetensors", "llama", "text-generation", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T02:39:31Z	Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER
JinghuiLuAstronaut/PaDeLLM_llama2_7b_conll03	JinghuiLuAstronaut	2024-02-27T09:37:41Z	5	1	transformers	[ "transformers", "safetensors", "llama", "text-generation", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T02:21:01Z	Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER
JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_resume	JinghuiLuAstronaut	2024-02-27T09:37:22Z	6	0	transformers	[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-26T09:00:16Z	Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER
habout632/EvolCodeLlama-7b	habout632	2024-02-27T09:35:24Z	3	0	peft	[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-hf", "base_model:adapter:codellama/CodeLlama-7b-hf", "license:llama2", "4-bit", "bitsandbytes", "region:us" ]	null	2024-02-27T08:18:15Z	--- license: llama2 library_name: peft tags: - axolotl - generated_from_trainer base_model: codellama/CodeLlama-7b-hf model-index: - name: EvolCodeLlama-7b 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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.0` ```yaml base_model: codellama/CodeLlama-7b-hf base_model_config: codellama/CodeLlama-7b-hf model_type: LlamaForCausalLM tokenizer_type: LlamaTokenizer is_llama_derived_model: true hub_model_id: EvolCodeLlama-7b load_in_8bit: false load_in_4bit: true strict: false datasets: - path: mlabonne/Evol-Instruct-Python-1k type: alpaca dataset_prepared_path: last_run_prepared val_set_size: 0.02 output_dir: ./qlora-out adapter: qlora lora_model_dir: sequence_len: 2048 sample_packing: true lora_r: 32 lora_alpha: 16 lora_dropout: 0.05 lora_target_modules: lora_target_linear: true lora_fan_in_fan_out: wandb_project: axolotl wandb_entity: wandb_watch: wandb_run_id: wandb_log_model: gradient_accumulation_steps: 4 micro_batch_size: 2 num_epochs: 3 optimizer: paged_adamw_32bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 100 eval_steps: 0.01 save_strategy: epoch save_steps: debug: deepspeed: weight_decay: 0.0 fsdp: fsdp_config: special_tokens: bos_token: "<s>" eos_token: "</s>" unk_token: "<unk>" ``` </details><br> # EvolCodeLlama-7b This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3796 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 3 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 0.3178 \| 0.01 \| 1 \| 0.5311 \| \| 0.3147 \| 0.03 \| 4 \| 0.5312 \| \| 0.3626 \| 0.07 \| 8 \| 0.5310 \| \| 0.6265 \| 0.1 \| 12 \| 0.5296 \| \| 0.429 \| 0.14 \| 16 \| 0.5270 \| \| 0.5086 \| 0.17 \| 20 \| 0.5205 \| \| 0.4335 \| 0.21 \| 24 \| 0.5067 \| \| 0.3383 \| 0.24 \| 28 \| 0.4842 \| \| 0.3688 \| 0.28 \| 32 \| 0.4603 \| \| 0.2528 \| 0.31 \| 36 \| 0.4403 \| \| 0.3105 \| 0.35 \| 40 \| 0.4251 \| \| 0.4936 \| 0.38 \| 44 \| 0.4162 \| \| 0.4146 \| 0.42 \| 48 \| 0.4086 \| \| 0.3327 \| 0.45 \| 52 \| 0.4024 \| \| 0.3429 \| 0.48 \| 56 \| 0.3971 \| \| 0.3328 \| 0.52 \| 60 \| 0.3937 \| \| 0.1844 \| 0.55 \| 64 \| 0.3901 \| \| 0.3001 \| 0.59 \| 68 \| 0.3887 \| \| 0.3632 \| 0.62 \| 72 \| 0.3872 \| \| 0.1997 \| 0.66 \| 76 \| 0.3847 \| \| 0.2461 \| 0.69 \| 80 \| 0.3823 \| \| 0.2865 \| 0.73 \| 84 \| 0.3812 \| \| 0.26 \| 0.76 \| 88 \| 0.3805 \| \| 0.3191 \| 0.8 \| 92 \| 0.3792 \| \| 0.4642 \| 0.83 \| 96 \| 0.3763 \| \| 0.2649 \| 0.87 \| 100 \| 0.3750 \| \| 0.2095 \| 0.9 \| 104 \| 0.3727 \| \| 0.2738 \| 0.94 \| 108 \| 0.3737 \| \| 0.4274 \| 0.97 \| 112 \| 0.3730 \| \| 0.2722 \| 1.0 \| 116 \| 0.3724 \| \| 0.2164 \| 1.02 \| 120 \| 0.3705 \| \| 0.1549 \| 1.05 \| 124 \| 0.3726 \| \| 0.3051 \| 1.08 \| 128 \| 0.3725 \| \| 0.1873 \| 1.12 \| 132 \| 0.3730 \| \| 0.3388 \| 1.15 \| 136 \| 0.3738 \| \| 0.2504 \| 1.19 \| 140 \| 0.3741 \| \| 0.2851 \| 1.22 \| 144 \| 0.3714 \| \| 0.2365 \| 1.26 \| 148 \| 0.3690 \| \| 0.3986 \| 1.29 \| 152 \| 0.3699 \| \| 0.1913 \| 1.33 \| 156 \| 0.3720 \| \| 0.1963 \| 1.36 \| 160 \| 0.3698 \| \| 0.1824 \| 1.4 \| 164 \| 0.3679 \| \| 0.1453 \| 1.43 \| 168 \| 0.3685 \| \| 0.3073 \| 1.47 \| 172 \| 0.3702 \| \| 0.1501 \| 1.5 \| 176 \| 0.3692 \| \| 0.2167 \| 1.53 \| 180 \| 0.3662 \| \| 0.3007 \| 1.57 \| 184 \| 0.3660 \| \| 0.2203 \| 1.6 \| 188 \| 0.3666 \| \| 0.3978 \| 1.64 \| 192 \| 0.3669 \| \| 0.2397 \| 1.67 \| 196 \| 0.3663 \| \| 0.2161 \| 1.71 \| 200 \| 0.3656 \| \| 0.2593 \| 1.74 \| 204 \| 0.3651 \| \| 0.2113 \| 1.78 \| 208 \| 0.3658 \| \| 0.2435 \| 1.81 \| 212 \| 0.3657 \| \| 0.2625 \| 1.85 \| 216 \| 0.3639 \| \| 0.302 \| 1.88 \| 220 \| 0.3624 \| \| 0.2556 \| 1.92 \| 224 \| 0.3611 \| \| 0.2063 \| 1.95 \| 228 \| 0.3609 \| \| 0.1994 \| 1.98 \| 232 \| 0.3612 \| \| 0.2229 \| 2.02 \| 236 \| 0.3613 \| \| 0.1983 \| 2.03 \| 240 \| 0.3634 \| \| 0.1925 \| 2.06 \| 244 \| 0.3725 \| \| 0.1778 \| 2.1 \| 248 \| 0.3832 \| \| 0.1293 \| 2.13 \| 252 \| 0.3834 \| \| 0.2166 \| 2.16 \| 256 \| 0.3789 \| \| 0.2082 \| 2.2 \| 260 \| 0.3760 \| \| 0.1858 \| 2.23 \| 264 \| 0.3761 \| \| 0.1862 \| 2.27 \| 268 \| 0.3763 \| \| 0.1619 \| 2.3 \| 272 \| 0.3783 \| \| 0.174 \| 2.34 \| 276 \| 0.3786 \| \| 0.2414 \| 2.37 \| 280 \| 0.3790 \| \| 0.1977 \| 2.41 \| 284 \| 0.3783 \| \| 0.1678 \| 2.44 \| 288 \| 0.3784 \| \| 0.2263 \| 2.48 \| 292 \| 0.3786 \| \| 0.082 \| 2.51 \| 296 \| 0.3783 \| \| 0.2621 \| 2.55 \| 300 \| 0.3784 \| \| 0.1754 \| 2.58 \| 304 \| 0.3795 \| \| 0.1957 \| 2.61 \| 308 \| 0.3802 \| \| 0.1203 \| 2.65 \| 312 \| 0.3803 \| \| 0.1388 \| 2.68 \| 316 \| 0.3796 \| \| 0.1699 \| 2.72 \| 320 \| 0.3796 \| \| 0.161 \| 2.75 \| 324 \| 0.3796 \| \| 0.2394 \| 2.79 \| 328 \| 0.3792 \| \| 0.1465 \| 2.82 \| 332 \| 0.3795 \| \| 0.1746 \| 2.86 \| 336 \| 0.3794 \| \| 0.1839 \| 2.89 \| 340 \| 0.3795 \| \| 0.1581 \| 2.93 \| 344 \| 0.3796 \| ### Framework versions - PEFT 0.8.2 - Transformers 4.39.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.17.1 - Tokenizers 0.15.0
JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_msra	JinghuiLuAstronaut	2024-02-27T09:29:17Z	3	0	transformers	[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T03:32:04Z	Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER
JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_weibo	JinghuiLuAstronaut	2024-02-27T09:28:36Z	4	0	transformers	[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T04:15:20Z	Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER
DatPySci/pythia-1b-kto-iter0	DatPySci	2024-02-27T09:27:03Z	116	0	transformers	[ "transformers", "safetensors", "gpt_neox", "text-generation", "alignment-handbook", "generated_from_trainer", "conversational", "dataset:DatPySci/iter0", "base_model:DatPySci/pythia-1b-sft-full", "base_model:finetune:DatPySci/pythia-1b-sft-full", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T04:29:58Z	--- license: apache-2.0 base_model: DatPySci/pythia-1b-sft-full tags: - alignment-handbook - generated_from_trainer datasets: - DatPySci/iter0 model-index: - name: pythia-1b-kto-iter0 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. --> # pythia-1b-kto-iter0 This model is a fine-tuned version of [DatPySci/pythia-1b-sft-full](https://huggingface.co/DatPySci/pythia-1b-sft-full) on the DatPySci/iter0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2591 - Rewards/real: 0.0604 - Rewards/generated: -1.0267 - Rewards/accuracies: 0.9460 - Rewards/margins: 1.0871 - Logps/generated: -570.8114 - Logps/real: -468.1696 - Logits/generated: 0.2253 - Logits/real: -0.2820 ## 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-07 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - total_eval_batch_size: 8 - 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 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/real \| Rewards/generated \| Rewards/accuracies \| Rewards/margins \| Logps/generated \| Logps/real \| Logits/generated \| Logits/real \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------------:\|:-----------------:\|:------------------:\|:---------------:\|:---------------:\|:----------:\|:----------------:\|:-----------:\| \| 0.2932 \| 0.38 \| 300 \| 0.2962 \| 0.0718 \| -0.7855 \| 0.9220 \| 0.8572 \| -568.3989 \| -468.0556 \| 0.2554 \| -0.2530 \| \| 0.2689 \| 0.77 \| 600 \| 0.2591 \| 0.0604 \| -1.0267 \| 0.9460 \| 1.0871 \| -570.8114 \| -468.1696 \| 0.2253 \| -0.2820 \| ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1 - Datasets 2.17.1 - Tokenizers 0.15.2
Ayus077BCT014Bhandari/vartat5-using-100K-plus-23	Ayus077BCT014Bhandari	2024-02-27T09:22:02Z	106	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2024-02-27T06:25:30Z	--- 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]
hellod035/ppo-Huggy	hellod035	2024-02-27T09:21:55Z	0	0	ml-agents	[ "ml-agents", "tensorboard", "onnx", "Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy", "region:us" ]	reinforcement-learning	2024-02-27T09:21:49Z	--- library_name: ml-agents tags: - Huggy - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Huggy --- # ppo Agent playing Huggy This is a trained model of a ppo agent playing Huggy using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A short tutorial where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent playing directly in your browser 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: hellod035/ppo-Huggy 3. Step 2: Select your .nn /.onnx file 4. Click on Watch the agent play 👀
archiMAD/LunarLander-ppo-from-scratch	archiMAD	2024-02-27T09:20:34Z	0	0	null	[ "tensorboard", "LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course", "model-index", "region:us" ]	reinforcement-learning	2024-02-27T09:20:18Z	--- tags: - LunarLander-v2 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-course model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 76.00 +/- 114.11 name: mean_reward verified: false --- # PPO Agent Playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2. # Hyperparameters ```python {'exp_name': 'ppo' 'seed': 1 'torch_deterministic': True 'cuda': True 'track': False 'wandb_project_name': 'cleanRL' 'wandb_entity': None 'capture_video': False 'env_id': 'LunarLander-v2' 'total_timesteps': 500000 'learning_rate': 0.00025 'num_envs': 4 'num_steps': 1024 'anneal_lr': True 'gae': True 'gamma': 0.99 'gae_lambda': 0.95 'num_minibatches': 64 'update_epochs': 4 'norm_adv': True 'clip_coef': 0.2 'clip_vloss': True 'ent_coef': 0.01 'vf_coef': 0.5 'max_grad_norm': 0.5 'target_kl': None 'repo_id': 'archiMAD/LunarLander-ppo-from-scratch' 'batch_size': 4096 'minibatch_size': 64} ```
nagyadam0616/zephyr-x-twitter-5epocs-full-2	nagyadam0616	2024-02-27T09:20:15Z	4	0	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T08:56:43Z	--- 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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mhmmterts/fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens	mhmmterts	2024-02-27T09:16:52Z	106	0	transformers	[ "transformers", "safetensors", "roberta", "text-classification", "generated_from_trainer", "dataset:swiss_judgment_prediction", "base_model:joelniklaus/legal-swiss-roberta-large", "base_model:finetune:joelniklaus/legal-swiss-roberta-large", "license:cc", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2024-02-27T09:15:43Z	--- license: cc base_model: joelniklaus/legal-swiss-roberta-large tags: - generated_from_trainer datasets: - swiss_judgment_prediction metrics: - accuracy model-index: - name: fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens results: - task: name: Text Classification type: text-classification dataset: name: swiss_judgment_prediction type: swiss_judgment_prediction config: it split: test args: it metrics: - name: Accuracy type: accuracy value: 0.8177339901477833 --- <!-- 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. --> # fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens This model is a fine-tuned version of [joelniklaus/legal-swiss-roberta-large](https://huggingface.co/joelniklaus/legal-swiss-roberta-large) on the swiss_judgment_prediction dataset. It achieves the following results on the evaluation set: - Loss: 0.7964 - Accuracy: 0.8177 ## 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: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.7513 \| 1.0 \| 768 \| 0.6783 \| 0.7956 \| \| 0.6008 \| 2.0 \| 1536 \| 0.7964 \| 0.8177 \| ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0+cu118 - Datasets 2.17.0 - Tokenizers 0.15.1
vlada-v/whisper-small-hi	vlada-v	2024-02-27T09:07:39Z	76	0	transformers	[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "hf-asr-leaderboard", "generated_from_trainer", "en", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2024-02-09T07:37:40Z	--- language: - en license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: Whisper Small Hi - Kids 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 Small Hi - Kids This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the PRG Dataset dataset. It achieves the following results on the evaluation set: - Loss: 2.4077 - Wer: 95.2005 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 100 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2
alexandrabenamar/Mistral-7B-Instruct-v0.2-4Magic	alexandrabenamar	2024-02-27T09:07:08Z	4	1	transformers	[ "transformers", "safetensors", "mistral", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T08:42:45Z	--- 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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tomaszki/nous-gemma-four	tomaszki	2024-02-27T09:06:37Z	112	0	transformers	[ "transformers", "safetensors", "gemma", "text-generation", "conversational", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T09:03:59Z	--- 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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ann-lab52/quan-1.8b-base-AWQ	ann-lab52	2024-02-27T08:59:41Z	76	0	transformers	[ "transformers", "pytorch", "safetensors", "llama", "text-generation", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T08:39:26Z	--- license: other license_name: quan license_link: https://huggingface.co/qnguyen3/quan-1.8b-base ---
Bong9/assemblydata	Bong9	2024-02-27T08:56:34Z	0	0	transformers	[ "transformers", "safetensors", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]	null	2024-02-27T08:53:39Z	--- 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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Reniyas/phi-2-classification-merged	Reniyas	2024-02-27T08:54:15Z	48	0	transformers	[ "transformers", "safetensors", "phi", "text-generation", "conversational", "custom_code", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2024-02-27T08:49:52Z	--- 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. 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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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internlm/internlm-xcomposer2-7b-4bit	internlm	2024-02-27T08:43:16Z	41	10	transformers	[ "transformers", "internlm", "feature-extraction", "text-generation", "custom_code", "arxiv:2401.16420", "license:other", "region:us" ]	text-generation	2024-02-06T12:38:00Z	--- license: other pipeline_tag: text-generation --- <p align="center"> <img src="logo_en.png" width="400"/> <p> <p align="center"> <b><font size="6">InternLM-XComposer2</font></b> <p> <div align="center"> [💻Github Repo](https://github.com/InternLM/InternLM-XComposer) [Paper](https://arxiv.org/abs/2401.16420) </div> InternLM-XComposer2 is a vision-language large model (VLLM) based on [InternLM2](https://github.com/InternLM/InternLM) for advanced text-image comprehension and composition. We release InternLM-XComposer2 series in two versions: - InternLM-XComposer2-VL: The pretrained VLLM model with InternLM2 as the initialization of the LLM, achieving strong performance on various multimodal benchmarks. - InternLM-XComposer2: The finetuned VLLM for Free-from Interleaved Text-Image Composition. This is the 4-bit version of InternLM-XComposer2, install the latest version of [auto_gptq](https://github.com/AutoGPTQ/AutoGPTQ#quick-installation) before using. ```python import torch, auto_gptq from PIL import Image from transformers import AutoModel, AutoTokenizer from auto_gptq.modeling import BaseGPTQForCausalLM auto_gptq.modeling._base.SUPPORTED_MODELS = ["internlm"] torch.set_grad_enabled(False) class InternLMXComposer2QForCausalLM(BaseGPTQForCausalLM): layers_block_name = "model.layers" outside_layer_modules = [ 'vit', 'vision_proj', 'model.tok_embeddings', 'model.norm', 'output', ] inside_layer_modules = [ ["attention.wqkv.linear"], ["attention.wo.linear"], ["feed_forward.w1.linear", "feed_forward.w3.linear"], ["feed_forward.w2.linear"], ] # init model and tokenizer model = InternLMXComposer2QForCausalLM.from_quantized( 'internlm/internlm-xcomposer2-7b-4bit', trust_remote_code=True, device="cuda:0").eval() tokenizer = AutoTokenizer.from_pretrained( 'internlm/internlm-xcomposer2-7b-4bit', trust_remote_code=True) img_path_list = [ 'panda.jpg', 'bamboo.jpeg', ] images = [] for img_path in img_path_list: image = Image.open(img_path).convert("RGB") image = model.vis_processor(image) images.append(image) image = torch.stack(images) query = '<ImageHere> <ImageHere>please write an article based on the images. Title: my favorite animal.' with torch.cuda.amp.autocast(): response, history = model.chat(tokenizer, query=query, image=image, history=[], do_sample=False) print(response) #My Favorite Animal: The Panda #The panda, also known as the giant panda, is one of the most beloved animals in the world. These adorable creatures are native to China and can be found in the wild in a few select locations, but they are more commonly seen in captivity at zoos or wildlife reserves. #Pandas have a distinct black-and-white coloration that makes them instantly recognizable. They are known for their love of bamboo, which they eat almost exclusively. In fact, pandas spend up to 14 hours a day eating, with the majority of their diet consisting of bamboo. Despite this seemingly unbalanced diet, pandas are actually quite healthy and have a low body fat percentage, thanks to their ability to digest bamboo efficiently. #In addition to their unique eating habits, pandas are also known for their playful personalities. They are intelligent and curious creatures, often engaging in activities like playing with toys or climbing trees. However, they do not typically exhibit these behaviors in the wild, where they are solitary creatures who prefer to spend their time alone. #One of the biggest threats to the panda's survival is habitat loss due to deforestation. As a result, many pandas now live in captivity, where they are cared for by dedicated staff and provided with enrichment opportunities to keep them engaged and stimulated. While it is important to protect these animals from extinction, it is also crucial to remember that they are still wild creatures and should be treated with respect and care. #Overall, the panda is an amazing animal that has captured the hearts of people around the world. Whether you see them in the wild or in captivity, there is no denying the charm and allure of these gentle giants. ``` ### Open Source License The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact [email protected].

tsfeith/ppo-LunarLander-v2

tsfeith

2024-02-27T14:06:01Z

0

stable-baselines3

[ "stable-baselines3", "LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2024-02-27T14:05:43Z

--- library_name: stable-baselines3 tags: - LunarLander-v2 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 256.53 +/- 20.04 name: mean_reward verified: false --- # **PPO** Agent playing **LunarLander-v2** This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). ## Usage (with Stable-baselines3) TODO: Add your code ```python from stable_baselines3 import ... from huggingface_sb3 import load_from_hub ... ```

interrobang/OpenHermes-2.5-Mistral-7B-GGUF-ukrainian-imatrix

interrobang

2024-02-27T14:04:54Z

32

3

null

[ "gguf", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

null

2024-02-07T17:04:31Z

--- license: apache-2.0 --- A test quantization of OpenHermes-2.5-Mistral-7B by teknium using importance matrices computed on Ukrainian text, hopefully decreasing the coherence hit after quantization in Ukrainian at the cost of some performance in other languages. Importance matrix was computed in roughly 20 minutes with a Ryzen 5 3550H and GTX 1650 with 8 layers offloaded, with a context size of 512. The calibration data is just a mix of my personal GPT chats, random words as well as random wikipedia articles, totaling about 15k-ish tokens, definitely not optimal, but it is in the repo for anyone to tinker with, as well as the computed imatrix Will be updated with perplexity testing later, probably? 😭 Haven't done proper tests quite yet, feels better than old quants when chatting in Ukrainian, hopefully I get around to actually benching it somehow

emaeon/solar-hansol-pretrain-merge

emaeon

2024-02-27T14:00:16Z

76

0

transformers

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

text-generation

2024-02-25T16:50:13Z

--- 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]

Shritama/codellama-7B-IT-NL-SQL-3

Shritama

2024-02-27T14:00:08Z

93

0

transformers

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

text-generation

2024-02-27T13:57:03Z

--- 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]

Lolbruhs/Kats

Lolbruhs

2024-02-27T13:58:07Z

0

diffusers

[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:freecryptobasics/KanyeAlbumCoverLora", "base_model:adapter:freecryptobasics/KanyeAlbumCoverLora", "region:us" ]

text-to-image

2024-02-27T13:58:07Z

--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: '-' output: url: images/275 sin título_20240130215710~2.png base_model: freecryptobasics/KanyeAlbumCoverLora instance_prompt: null --- # Cata <Gallery /> ## Download model [Download](/Lolbruhs/Kats/tree/main) them in the Files & versions tab.

nithyarajkumar/tinyllama-finetune-tourism-v1

nithyarajkumar

2024-02-27T13:57:00Z

0

peft

[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "base_model:adapter:TinyLlama/TinyLlama-1.1B-Chat-v1.0", "license:apache-2.0", "region:us" ]

null

2024-02-27T04:19:13Z

--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 model-index: - name: tinyllama-finetune-tourism-v1 results: [] ---  # tinyllama-finetune-tourism-v1 This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) 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: 0.0002 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 100 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

Maqqq/Nous-Finetuning-Subnet

Maqqq

2024-02-27T13:46:10Z

5

0

transformers

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

text-generation

2024-02-23T16:03:01Z

--- 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]

gohzy/fine-tuned-singlish-toxic-bert-LoRA-35000-1

gohzy

2024-02-27T13:45:20Z

162

0

transformers

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

text-classification

2024-02-27T13:42:46Z

--- 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]

pribadihcr/aniket-math-small-gpt

pribadihcr

2024-02-27T13:41:47Z

4

0

peft

[ "peft", "safetensors", "phi", "generated_from_trainer", "custom_code", "base_model:microsoft/phi-2", "base_model:adapter:microsoft/phi-2", "license:mit", "region:us" ]

null

2024-02-21T14:24:09Z

--- license: mit library_name: peft tags: - generated_from_trainer base_model: microsoft/phi-2 model-index: - name: aniket-math-small-gpt results: [] ---  # aniket-math-small-gpt This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) 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: 0.0002 - train_batch_size: 4 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - training_steps: 2 ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.2+cu118 - Datasets 2.17.1 - Tokenizers 0.15.2

gohzy/fine-tuned-singlish-toxic-bert-LoRA-35000-1.5

gohzy

2024-02-27T13:40:34Z

162

0

transformers

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

text-classification

2024-02-27T13:40:16Z

--- 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]

Ketskapow/distilbert-base-uncased-finetuned-cola

Ketskapow

2024-02-27T13:36:14Z

6

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-27T13:12:09Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola results: [] ---  # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4587 - Matthews Correlation: 0.5306 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.5228 | 1.0 | 535 | 0.4535 | 0.4629 | | 0.3477 | 2.0 | 1070 | 0.4587 | 0.5306 | | 0.2316 | 3.0 | 1605 | 0.6278 | 0.5193 | | 0.1694 | 4.0 | 2140 | 0.8088 | 0.5087 | | 0.1202 | 5.0 | 2675 | 0.8539 | 0.5256 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

vicky6/dummy-model_2

vicky6

2024-02-27T13:35:53Z

58

0

transformers

[ "transformers", "tf", "camembert", "fill-mask", "generated_from_keras_callback", "base_model:almanach/camembert-base", "base_model:finetune:almanach/camembert-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]

fill-mask

2024-02-27T13:35:15Z

--- license: mit tags: - generated_from_keras_callback base_model: camembert-base model-index: - name: dummy-model_2 results: [] ---  # dummy-model_2 This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset. It achieves the following results on the evaluation set: ## 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: - optimizer: None - training_precision: float32 ### Training results ### Framework versions - Transformers 4.37.2 - TensorFlow 2.15.0 - Tokenizers 0.15.2

seedmanc/isna

seedmanc

2024-02-27T13:33:56Z

2

0

diffusers

[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:stablediffusionapi/anything-v5", "base_model:adapter:stablediffusionapi/anything-v5", "license:other", "region:us" ]

text-to-image

2024-02-27T13:33:49Z

--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: >- isna-style, breasts, plump, gradient background, rough lineart, 1 girl, serval, kemono friends, masterpiece, best quality, rough strokes, rough lines, vector, anime shading, simplistic, lo-fi parameters: negative_prompt: >- worst quality, large head, low quality, extra digits, bad eye, EasyNegativeV2, ng_deepnegative_v1_75t, thin linear, narrow strokes, fine details output: url: images/e61c5484-1c86-062e-202a-090570c97cee.jpeg - text: '-' output: url: images/b30bac82-7114-f7f3-f1fd-4def63ccb410.jpeg - text: >- isna-style, large breasts, flat shading, thick outlines, gradient background, 1girl, rough lineart, wide strokes, vivid, expressive eyes parameters: negative_prompt: >- worst quality, large head, low quality, extra digits, bad eye, EasyNegativeV2, ng_deepnegative_v1_75t output: url: images/cc713442-3b76-492b-a6aa-eca4ea99cbd5.webp - text: '-' output: url: images/b64d7978-5176-f3aa-699d-43493a069eb4.jpeg base_model: stablediffusionapi/anything-v5 instance_prompt: isna-style, plump, flat shading, thick outlines, gradient background license: other license_name: whocares license_link: LICENSE --- # Isna artstyle (イスナ) <Gallery /> ## Model description Vivid colors and rough strokes as well as expressive eyes and pleasant skin colors in art. Mostly for Kemono Friends, produces plump characters. ## Trigger words You should use `isna-style` to trigger the image generation. You should use `plump` to trigger the image generation. You should use `flat shading` to trigger the image generation. You should use `thick outlines` to trigger the image generation. You should use `gradient background` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/seedmanc/isna/tree/main) them in the Files & versions tab.

riotu-lab/ArabianGPT-01B

riotu-lab

2024-02-27T13:31:53Z

2,999

13

transformers

[ "transformers", "pytorch", "gpt2", "text-generation", "arabic ", "ar", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2023-12-04T18:45:05Z

--- license: apache-2.0 language: - ar pipeline_tag: text-generation tags: - 'arabic ' - text-generation widget: - text: "أعلنت وزارة الحج في المملكة العربية السعودية" example_title: "مثال ١" - text: "يبدو اليوم جميلا، سأقوم بتحضير" example_title: "مثال ٢" - text: "إن التقنيات الحديثة" example_title: "مثال ٣" --- # ArabianGPT Model Overview ## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation <p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p> > **Important Note:** Currently, we offer a raw pre-trained model. Our team is actively working on releasing instruction-based LLMs that are fine-tuned and augmented with LRHF. The first set of pre-trained models has been made available for community exploration. While we do have models fine-tuned for specific tasks such as summarization and sentiment analysis, they are still in the development phase. ## How you can use this Pre-Trained? You are invited to utilize this pre-trained, native Arabic language model as an experimental tool to assess its capabilities, aid in its fine-tuning, and evaluate its performance across a variety of downstream tasks. We encourage you to review our technical report for a comprehensive understanding of the model's performance metrics and the specific downstream tasks it has been tested on. This will provide valuable insights into its applicability and effectiveness in diverse applications. ## Introduction ArabianGPT-0.1B, developed under the ArabianLLM initiatives, is a specialized GPT-2 model optimized for Arabic language modeling. It's a product of the collaborative efforts at Prince Sultan University's Robotics and Internet of Things Lab, focusing on enhancing natural language modeling and generation in Arabic. This model represents a significant stride in LLM research, specifically addressing the linguistic complexities and nuances of the Arabic language. ## Key Features - **Architecture**: GPT-2 - **Model Size**: 134 million parameters - **Layers**: 12 - **Model Attention Layers (MAL)**: 12 - **Context Window Size**: 768 tokens ## Training - **Dataset**: Scraped Arabic newspaper articles - **Data Size**: 15.5 GB - **Words**: 237.8 million - **Tokenizer**: Aranizer 64K - **Tokens**: Over 1.75 billion - **Hardware**: 2 NDIVIA A100 GPUs - **Training Scale**: 7.5 million examples - **Training Duration**: 3 days - **Performance**: Final loss of 3.97 ## Role in ArabianLLM Initiatives ArabianGPT-0.1B (Base Model) is crucial for advancing Arabic language processing, addressing challenges unique to Arabic morphology and dialects. ## Usage Suitable for Arabic text generation tasks. Example usage with Transformers Pipeline: ```python from transformers import pipeline pipe = pipeline("text-generation", model="riotu-lab/ArabianGPT-01B", max_new_tokens=512) text = '' pipe.predict(text) ``` ## Limitations and Ethical Considerations - The model may have context understanding or text generation limitations in certain scenarios. - Emphasis on ethical use to prevent misinformation or harmful content propagation. ## Acknowledgments Special thanks to Prince Sultan University, particularly the Robotics and Internet of Things Lab. ## Contact Information For inquiries: [[email protected]](mailto:[email protected]). ## Disclaimer for the Use of Large Language Models (LLMs) for Text Generation <p style="color: red;">We disclaim all responsibility for any harm, inaccuracies, or inappropriate content generated by ArabianGPT-0.1B, and users engage with and apply the model's outputs at their own risk.</p>

phoen1x/TF-Finetuned-xsum

phoen1x

2024-02-27T13:28:55Z

72

1

transformers

[ "transformers", "tf", "t5", "text2text-generation", "generated_from_keras_callback", "summarization", "en", "dataset:xsum", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

summarization

2023-05-15T22:20:52Z

--- license: apache-2.0 tags: - generated_from_keras_callback model-index: - name: TF-Finetuned-xsum results: [] datasets: - xsum language: - en metrics: - rouge pipeline_tag: summarization ---  # TF-Finetuned-xsum This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [xsum](https://huggingface.co/datasets/xsum) dataset. It achieves the following results on the evaluation set: - Train Loss: - Validation Loss: - Epoch: ## 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: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Train Rougel | Epoch | |:----------:|:---------------:|:---------------------------------------------:|:-----:| | | | tf.Tensor(0.1999889, shape=(), dtype=float32) | | ### Framework versions - Transformers 4.20.0 - TensorFlow 2.12.0 - Datasets 2.12.0 - Tokenizers 0.12.1

auksliusninetwothree/test-model

auksliusninetwothree

2024-02-27T13:27:58Z

78

0

transformers

[ "transformers", "tensorboard", "safetensors", "whisper", "automatic-speech-recognition", "generated_from_trainer", "dataset:audiofolder", "base_model:openai/whisper-small", "base_model:finetune:openai/whisper-small", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2024-02-26T13:36:00Z

--- license: apache-2.0 base_model: openai/whisper-small tags: - generated_from_trainer datasets: - audiofolder metrics: - wer model-index: - name: test-model results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: audiofolder type: audiofolder config: custom_data split: test args: custom_data metrics: - name: Wer type: wer value: 8.333333333333332 ---  # test-model This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the audiofolder dataset. It achieves the following results on the evaluation set: - Loss: 1.1513 - Wer Ortho: 8.3333 - Wer: 8.3333 ## 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: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant_with_warmup - lr_scheduler_warmup_steps: 2 - training_steps: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| | 1.1613 | 2.71 | 19 | 1.1513 | 8.3333 | 8.3333 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1 - Datasets 2.17.1 - Tokenizers 0.15.2

misterwavey/flan-t5-base-cc1

misterwavey

2024-02-27T13:26:40Z

106

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text2text-generation

2024-02-27T13:07:18Z

--- 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]

Yanwen9969/distilbert-base-uncased-finetuned-cola

Yanwen9969

2024-02-27T13:21:30Z

4

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-27T12:36:04Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola results: [] ---  # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8446 - Matthews Correlation: 0.5377 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.517 | 1.0 | 535 | 0.4553 | 0.4460 | | 0.3451 | 2.0 | 1070 | 0.4641 | 0.5255 | | 0.2317 | 3.0 | 1605 | 0.6350 | 0.5186 | | 0.1726 | 4.0 | 2140 | 0.8171 | 0.5081 | | 0.1269 | 5.0 | 2675 | 0.8446 | 0.5377 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

Arczisan/mechanical-parts

Arczisan

2024-02-27T13:21:13Z

1

0

diffusers

[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "region:us" ]

text-to-image

2024-02-27T13:20:56Z

--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: "UNICODE\0\0a\0 \0g\0i\0r\0l\0 \0 \0<\0l\0o\0r\0a\0:\0R\0e\0e\0l\0_\0m\0e\0c\0h\0a\0n\0i\0c\0a\0l\0_\0p\0a\0r\0t\0s\0_\0v\0_\01\0_\03\0:\01\0>\0,\0 \0r\0e\0e\0l\0m\0e\0c\0h\0,\0 \0f\0i\0g\0h\0t\0i\0n\0g\0 \0,\0 \0g\0l\0o\0w\0i\0n\0g\0 \0e\0y\0e\0s\0,\0 \0s\0h\0o\0r\0t\0 \0h\0a\0i\0r\0,\0t\0o\0r\0n\0 \0t\0i\0g\0h\0t\0 \0s\0u\0p\0e\0r\0s\0u\0i\0t\0,\0 \0i\0n\0 \0a\0 \0d\0e\0s\0t\0r\0o\0y\0e\0d\0 \0c\0i\0t\0y\0,\0 \0s\0m\0o\0k\0e\0 \0a\0n\0d\0 \0f\0i\0r\0e\0,\0 \0g\0l\0o\0w\0i\0n\0g\0 \0p\0o\0w\0e\0r\0 \0a\0u\0r\0a\0,\0 \0d\0y\0n\0a\0m\0i\0c\0 \0p\0o\0s\0e\0,\0 \0d\0y\0n\0a\0m\0i\0c\0 \0v\0i\0e\0w\0" output: url: images/00123-2389661969.jpeg base_model: runwayml/stable-diffusion-v1-5 instance_prompt: null --- # Mechanical Parts <Gallery /> ## Download model Weights for this model are available in Safetensors format. [Download](/Arczisan/mechanical-parts/tree/main) them in the Files & versions tab.

OwOpeepeepoopoo/easy_america5

OwOpeepeepoopoo

2024-02-27T13:18:50Z

4

0

transformers

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

text-generation

2024-02-27T12:57:07Z

--- 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]

ryusangwon/5678_Llama-2-7b-hf

ryusangwon

2024-02-27T13:18:24Z

0

peft

[ "peft", "safetensors", "generated_from_trainer", "dataset:samsum", "base_model:meta-llama/Llama-2-7b-hf", "base_model:adapter:meta-llama/Llama-2-7b-hf", "region:us" ]

null

2024-02-27T13:18:20Z

--- base_model: meta-llama/Llama-2-7b-hf tags: - generated_from_trainer datasets: - samsum model-index: - name: 5678_Llama-2-7b-hf results: [] library_name: peft ---  # 5678_Llama-2-7b-hf This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the samsum dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 1 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - PEFT 0.4.0 - Transformers 4.36.2 - Pytorch 2.0.1+cu117 - Datasets 2.15.0 - Tokenizers 0.15.0

peldrak/segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline

peldrak

2024-02-27T13:17:44Z

188

0

transformers

[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:peldrak/segformer-b4-ade-512-512-finetuned-coastTrain", "base_model:finetune:peldrak/segformer-b4-ade-512-512-finetuned-coastTrain", "license:other", "endpoints_compatible", "region:us" ]

image-segmentation

2024-02-27T11:36:31Z

--- license: other base_model: peldrak/segformer-b4-ade-512-512-finetuned-coastTrain tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline results: [] ---  # segformer-b4-ade-512-512-finetuned-coastTrain-grCoastline This model is a fine-tuned version of [peldrak/segformer-b4-ade-512-512-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b4-ade-512-512-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.1900 - Mean Iou: 0.8129 - Mean Accuracy: 0.8809 - Overall Accuracy: 0.9540 - Accuracy Water: 0.9875 - Accuracy Whitewater: 0.6312 - Accuracy Sediment: 0.9541 - Accuracy Other Natural Terrain: 0.8566 - Accuracy Vegetation: 0.8860 - Accuracy Development: 0.8526 - Accuracy Unknown: 0.9984 - Iou Water: 0.9631 - Iou Whitewater: 0.5490 - Iou Sediment: 0.8864 - Iou Other Natural Terrain: 0.7326 - Iou Vegetation: 0.8448 - Iou Development: 0.7176 - Iou Unknown: 0.9972 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 40 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Water | Accuracy Whitewater | Accuracy Sediment | Accuracy Other Natural Terrain | Accuracy Vegetation | Accuracy Development | Accuracy Unknown | Iou Water | Iou Whitewater | Iou Sediment | Iou Other Natural Terrain | Iou Vegetation | Iou Development | Iou Unknown | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:| | 0.3829 | 0.24 | 20 | 0.4153 | 0.5484 | 0.6468 | 0.8693 | 0.9547 | 0.2281 | 0.9398 | 0.0617 | 0.9459 | 0.4008 | 0.9963 | 0.9176 | 0.1120 | 0.7770 | 0.0612 | 0.6193 | 0.3634 | 0.9882 | | 2.0682 | 0.49 | 40 | 0.2991 | 0.6099 | 0.6956 | 0.8939 | 0.9735 | 0.1187 | 0.9464 | 0.3054 | 0.8869 | 0.6447 | 0.9938 | 0.9316 | 0.1123 | 0.7992 | 0.2941 | 0.6709 | 0.4733 | 0.9879 | | 0.5418 | 0.73 | 60 | 0.2615 | 0.6607 | 0.7312 | 0.9192 | 0.9684 | 0.0686 | 0.9512 | 0.7257 | 0.8597 | 0.5526 | 0.9920 | 0.9252 | 0.0665 | 0.7986 | 0.6036 | 0.7632 | 0.4800 | 0.9881 | | 0.4389 | 0.98 | 80 | 0.2421 | 0.6515 | 0.7159 | 0.9201 | 0.9756 | 0.0911 | 0.9662 | 0.6066 | 0.9156 | 0.4593 | 0.9971 | 0.9426 | 0.0898 | 0.7943 | 0.5455 | 0.7796 | 0.4163 | 0.9926 | | 0.3756 | 1.22 | 100 | 0.2204 | 0.7025 | 0.7747 | 0.9295 | 0.9931 | 0.1656 | 0.9258 | 0.8460 | 0.8142 | 0.6870 | 0.9912 | 0.9124 | 0.1560 | 0.8274 | 0.7147 | 0.7806 | 0.5365 | 0.9896 | | 0.7675 | 1.46 | 120 | 0.2169 | 0.7061 | 0.7876 | 0.9184 | 0.9774 | 0.4127 | 0.9614 | 0.8133 | 0.7635 | 0.5874 | 0.9976 | 0.9489 | 0.3887 | 0.8088 | 0.5972 | 0.7210 | 0.4855 | 0.9928 | | 0.5434 | 1.71 | 140 | 0.2232 | 0.7104 | 0.7782 | 0.9308 | 0.9820 | 0.2467 | 0.9620 | 0.6425 | 0.8970 | 0.7228 | 0.9943 | 0.9529 | 0.2410 | 0.8545 | 0.5718 | 0.7752 | 0.5848 | 0.9925 | | 0.8975 | 1.95 | 160 | 0.2187 | 0.7209 | 0.8231 | 0.9231 | 0.9757 | 0.3658 | 0.8885 | 0.8665 | 0.7545 | 0.9165 | 0.9945 | 0.9473 | 0.3471 | 0.8241 | 0.6442 | 0.7331 | 0.5589 | 0.9917 | | 0.2799 | 2.2 | 180 | 0.1662 | 0.7404 | 0.8029 | 0.9418 | 0.9706 | 0.3506 | 0.9555 | 0.9022 | 0.8947 | 0.5523 | 0.9946 | 0.9425 | 0.3293 | 0.8567 | 0.7286 | 0.8378 | 0.4949 | 0.9928 | | 0.2132 | 2.44 | 200 | 0.1616 | 0.7714 | 0.8442 | 0.9443 | 0.9777 | 0.4621 | 0.9536 | 0.7886 | 0.8819 | 0.8492 | 0.9963 | 0.9435 | 0.4076 | 0.8578 | 0.7267 | 0.8215 | 0.6498 | 0.9930 | | 0.3068 | 2.68 | 220 | 0.2055 | 0.7345 | 0.8090 | 0.9318 | 0.9870 | 0.4136 | 0.9517 | 0.8730 | 0.8080 | 0.6367 | 0.9931 | 0.9370 | 0.3753 | 0.8034 | 0.7027 | 0.7935 | 0.5387 | 0.9909 | | 0.1822 | 2.93 | 240 | 0.1367 | 0.7984 | 0.8640 | 0.9531 | 0.9886 | 0.5028 | 0.9106 | 0.8899 | 0.8992 | 0.8593 | 0.9977 | 0.9499 | 0.4617 | 0.8667 | 0.7874 | 0.8617 | 0.6675 | 0.9937 | | 0.1504 | 3.17 | 260 | 0.1548 | 0.7794 | 0.8446 | 0.9471 | 0.9830 | 0.4763 | 0.9544 | 0.8496 | 0.8731 | 0.7774 | 0.9983 | 0.9482 | 0.4416 | 0.8516 | 0.7572 | 0.8427 | 0.6226 | 0.9917 | | 0.2699 | 3.41 | 280 | 0.1543 | 0.7508 | 0.8024 | 0.9475 | 0.9889 | 0.2791 | 0.9421 | 0.8336 | 0.9211 | 0.6552 | 0.9967 | 0.9484 | 0.2719 | 0.8647 | 0.7216 | 0.8500 | 0.6056 | 0.9938 | | 0.2272 | 3.66 | 300 | 0.1547 | 0.7618 | 0.8232 | 0.9490 | 0.9868 | 0.2820 | 0.9403 | 0.7567 | 0.9193 | 0.8808 | 0.9963 | 0.9565 | 0.2766 | 0.8735 | 0.7173 | 0.8339 | 0.6810 | 0.9938 | | 0.0938 | 3.9 | 320 | 0.1776 | 0.7615 | 0.8290 | 0.9415 | 0.9889 | 0.4229 | 0.9468 | 0.7605 | 0.8807 | 0.8081 | 0.9953 | 0.9545 | 0.3961 | 0.8519 | 0.6753 | 0.8080 | 0.6522 | 0.9929 | | 0.129 | 4.15 | 340 | 0.1708 | 0.7606 | 0.8281 | 0.9404 | 0.9839 | 0.5055 | 0.9591 | 0.8675 | 0.8540 | 0.6292 | 0.9977 | 0.9548 | 0.4638 | 0.8605 | 0.6874 | 0.8105 | 0.5533 | 0.9935 | | 0.1929 | 4.39 | 360 | 0.1504 | 0.7864 | 0.8456 | 0.9493 | 0.9832 | 0.4961 | 0.9428 | 0.8054 | 0.9216 | 0.7725 | 0.9976 | 0.9551 | 0.4630 | 0.8737 | 0.7149 | 0.8442 | 0.6605 | 0.9936 | | 0.1933 | 4.63 | 380 | 0.1572 | 0.7887 | 0.8610 | 0.9475 | 0.9875 | 0.4972 | 0.9328 | 0.8885 | 0.8523 | 0.8746 | 0.9939 | 0.9520 | 0.4646 | 0.8696 | 0.7369 | 0.8259 | 0.6796 | 0.9925 | | 0.0642 | 4.88 | 400 | 0.1759 | 0.7988 | 0.8631 | 0.9504 | 0.9839 | 0.5690 | 0.9449 | 0.7954 | 0.9159 | 0.8352 | 0.9971 | 0.9585 | 0.5125 | 0.8850 | 0.7171 | 0.8326 | 0.6917 | 0.9943 | | 0.1118 | 5.12 | 420 | 0.1461 | 0.8027 | 0.8728 | 0.9524 | 0.9854 | 0.5667 | 0.9487 | 0.8658 | 0.8783 | 0.8670 | 0.9973 | 0.9592 | 0.4847 | 0.8653 | 0.7586 | 0.8420 | 0.7145 | 0.9944 | | 0.1145 | 5.37 | 440 | 0.1437 | 0.7884 | 0.8471 | 0.9517 | 0.9806 | 0.4749 | 0.9560 | 0.9182 | 0.8870 | 0.7163 | 0.9969 | 0.9578 | 0.4510 | 0.8813 | 0.7459 | 0.8526 | 0.6354 | 0.9947 | | 0.2373 | 5.61 | 460 | 0.1429 | 0.8081 | 0.8807 | 0.9539 | 0.9875 | 0.6424 | 0.9413 | 0.8411 | 0.9063 | 0.8488 | 0.9976 | 0.9526 | 0.5048 | 0.8671 | 0.7674 | 0.8562 | 0.7140 | 0.9950 | | 0.0863 | 5.85 | 480 | 0.1620 | 0.7747 | 0.8317 | 0.9497 | 0.9872 | 0.3768 | 0.9531 | 0.8926 | 0.8780 | 0.7383 | 0.9957 | 0.9520 | 0.3645 | 0.8553 | 0.7583 | 0.8462 | 0.6527 | 0.9942 | | 0.1391 | 6.1 | 500 | 0.1639 | 0.7719 | 0.8332 | 0.9476 | 0.9856 | 0.3736 | 0.9277 | 0.7736 | 0.9158 | 0.8580 | 0.9980 | 0.9536 | 0.3623 | 0.8647 | 0.7044 | 0.8334 | 0.6903 | 0.9945 | | 0.0976 | 6.34 | 520 | 0.1893 | 0.7449 | 0.8043 | 0.9405 | 0.9883 | 0.3225 | 0.9467 | 0.8313 | 0.8733 | 0.6724 | 0.9955 | 0.9496 | 0.3151 | 0.8619 | 0.6690 | 0.8097 | 0.6149 | 0.9938 | | 0.1592 | 6.59 | 540 | 0.1842 | 0.7557 | 0.8210 | 0.9436 | 0.9888 | 0.3033 | 0.9475 | 0.8408 | 0.8482 | 0.8224 | 0.9958 | 0.9522 | 0.2846 | 0.8585 | 0.7011 | 0.8012 | 0.6982 | 0.9940 | | 0.2569 | 6.83 | 560 | 0.1531 | 0.7984 | 0.8686 | 0.9495 | 0.9863 | 0.5709 | 0.9457 | 0.8419 | 0.8783 | 0.8619 | 0.9955 | 0.9554 | 0.5058 | 0.8757 | 0.7338 | 0.8258 | 0.6986 | 0.9940 | | 0.1064 | 7.07 | 580 | 0.1944 | 0.7784 | 0.8474 | 0.9420 | 0.9895 | 0.5455 | 0.9459 | 0.7592 | 0.8764 | 0.8178 | 0.9975 | 0.9534 | 0.5047 | 0.8475 | 0.6847 | 0.8063 | 0.6572 | 0.9949 | | 0.0979 | 7.32 | 600 | 0.1581 | 0.7959 | 0.8574 | 0.9508 | 0.9869 | 0.5223 | 0.9399 | 0.8773 | 0.8874 | 0.7912 | 0.9968 | 0.9522 | 0.4766 | 0.8740 | 0.7516 | 0.8359 | 0.6865 | 0.9945 | | 0.045 | 7.56 | 620 | 0.1962 | 0.7990 | 0.8655 | 0.9479 | 0.9801 | 0.5896 | 0.9347 | 0.7952 | 0.9054 | 0.8546 | 0.9988 | 0.9485 | 0.5253 | 0.8764 | 0.7167 | 0.8204 | 0.7117 | 0.9938 | | 0.0495 | 7.8 | 640 | 0.2135 | 0.7824 | 0.8541 | 0.9428 | 0.9834 | 0.5986 | 0.9555 | 0.8005 | 0.8692 | 0.7725 | 0.9987 | 0.9550 | 0.5221 | 0.8447 | 0.7026 | 0.8075 | 0.6500 | 0.9949 | | 0.0389 | 8.05 | 660 | 0.1860 | 0.7856 | 0.8503 | 0.9469 | 0.9809 | 0.4908 | 0.9358 | 0.7910 | 0.9012 | 0.8538 | 0.9985 | 0.9547 | 0.4522 | 0.8837 | 0.6847 | 0.8158 | 0.7134 | 0.9946 | | 0.177 | 8.29 | 680 | 0.2002 | 0.7719 | 0.8338 | 0.9478 | 0.9871 | 0.3745 | 0.9462 | 0.7507 | 0.9147 | 0.8683 | 0.9951 | 0.9535 | 0.3584 | 0.8738 | 0.7041 | 0.8278 | 0.6920 | 0.9937 | | 0.0522 | 8.54 | 700 | 0.1619 | 0.7917 | 0.8564 | 0.9481 | 0.9875 | 0.5765 | 0.9388 | 0.8643 | 0.8908 | 0.7403 | 0.9963 | 0.9568 | 0.5202 | 0.8813 | 0.7152 | 0.8297 | 0.6440 | 0.9945 | | 0.066 | 8.78 | 720 | 0.1800 | 0.7782 | 0.8539 | 0.9451 | 0.9850 | 0.4766 | 0.9503 | 0.8770 | 0.8304 | 0.8615 | 0.9963 | 0.9597 | 0.4398 | 0.8674 | 0.7291 | 0.7992 | 0.6581 | 0.9945 | | 0.1114 | 9.02 | 740 | 0.1692 | 0.7867 | 0.8517 | 0.9476 | 0.9880 | 0.5068 | 0.9485 | 0.8157 | 0.8789 | 0.8257 | 0.9982 | 0.9569 | 0.4758 | 0.8787 | 0.7079 | 0.8205 | 0.6723 | 0.9951 | | 0.1906 | 9.27 | 760 | 0.1724 | 0.7929 | 0.8617 | 0.9490 | 0.9820 | 0.5359 | 0.9464 | 0.8073 | 0.8928 | 0.8697 | 0.9978 | 0.9572 | 0.4821 | 0.8714 | 0.7178 | 0.8284 | 0.6980 | 0.9956 | | 0.0562 | 9.51 | 780 | 0.1984 | 0.7811 | 0.8494 | 0.9449 | 0.9807 | 0.5865 | 0.9549 | 0.8392 | 0.8888 | 0.6984 | 0.9969 | 0.9569 | 0.5050 | 0.8750 | 0.6786 | 0.8232 | 0.6337 | 0.9952 | | 0.1104 | 9.76 | 800 | 0.1972 | 0.7978 | 0.8687 | 0.9469 | 0.9855 | 0.5906 | 0.9419 | 0.7758 | 0.8914 | 0.9000 | 0.9955 | 0.9556 | 0.5334 | 0.8733 | 0.6863 | 0.8178 | 0.7237 | 0.9945 | | 0.0451 | 10.0 | 820 | 0.2123 | 0.7769 | 0.8455 | 0.9415 | 0.9821 | 0.5810 | 0.9500 | 0.8132 | 0.8747 | 0.7191 | 0.9984 | 0.9537 | 0.5241 | 0.8658 | 0.6691 | 0.8074 | 0.6231 | 0.9949 | | 0.1426 | 10.24 | 840 | 0.2210 | 0.7989 | 0.8745 | 0.9465 | 0.9800 | 0.6316 | 0.9435 | 0.7712 | 0.8897 | 0.9072 | 0.9983 | 0.9562 | 0.5525 | 0.8783 | 0.6823 | 0.8131 | 0.7147 | 0.9951 | | 0.0683 | 10.49 | 860 | 0.2162 | 0.7964 | 0.8677 | 0.9473 | 0.9802 | 0.5774 | 0.9515 | 0.7715 | 0.8902 | 0.9058 | 0.9974 | 0.9549 | 0.5202 | 0.8777 | 0.6901 | 0.8156 | 0.7210 | 0.9954 | | 0.0758 | 10.73 | 880 | 0.1898 | 0.8005 | 0.8774 | 0.9468 | 0.9863 | 0.6471 | 0.9326 | 0.8057 | 0.8757 | 0.8960 | 0.9984 | 0.9595 | 0.5466 | 0.8796 | 0.6810 | 0.8067 | 0.7347 | 0.9957 | | 0.0496 | 10.98 | 900 | 0.1919 | 0.8019 | 0.8738 | 0.9469 | 0.9794 | 0.6404 | 0.9636 | 0.8149 | 0.8670 | 0.8526 | 0.9984 | 0.9598 | 0.5598 | 0.8726 | 0.6949 | 0.8065 | 0.7236 | 0.9959 | | 0.0329 | 11.22 | 920 | 0.1862 | 0.8004 | 0.8689 | 0.9469 | 0.9891 | 0.5888 | 0.9460 | 0.8303 | 0.8556 | 0.8746 | 0.9977 | 0.9594 | 0.5378 | 0.8816 | 0.6882 | 0.8003 | 0.7395 | 0.9957 | | 0.0808 | 11.46 | 940 | 0.2000 | 0.8016 | 0.8730 | 0.9485 | 0.9868 | 0.6599 | 0.9461 | 0.7912 | 0.8998 | 0.8292 | 0.9977 | 0.9617 | 0.5578 | 0.8811 | 0.6872 | 0.8208 | 0.7070 | 0.9960 | | 0.0492 | 11.71 | 960 | 0.2148 | 0.7983 | 0.8672 | 0.9466 | 0.9895 | 0.6154 | 0.9459 | 0.8051 | 0.8765 | 0.8410 | 0.9968 | 0.9589 | 0.5439 | 0.8735 | 0.6870 | 0.8079 | 0.7210 | 0.9959 | | 0.0629 | 11.95 | 980 | 0.2277 | 0.7941 | 0.8637 | 0.9456 | 0.9842 | 0.5803 | 0.9556 | 0.7909 | 0.8695 | 0.8680 | 0.9973 | 0.9604 | 0.5260 | 0.8744 | 0.6751 | 0.8009 | 0.7260 | 0.9958 | | 0.1419 | 12.2 | 1000 | 0.2076 | 0.7977 | 0.8623 | 0.9483 | 0.9868 | 0.5485 | 0.9413 | 0.8046 | 0.8865 | 0.8710 | 0.9977 | 0.9584 | 0.5079 | 0.8817 | 0.6928 | 0.8139 | 0.7335 | 0.9957 | | 0.153 | 12.44 | 1020 | 0.1835 | 0.7986 | 0.8608 | 0.9494 | 0.9833 | 0.5284 | 0.9457 | 0.8415 | 0.8814 | 0.8475 | 0.9979 | 0.9600 | 0.4923 | 0.8840 | 0.6992 | 0.8185 | 0.7404 | 0.9957 | | 0.0377 | 12.68 | 1040 | 0.2033 | 0.7894 | 0.8567 | 0.9476 | 0.9826 | 0.4861 | 0.9596 | 0.8731 | 0.8436 | 0.8548 | 0.9971 | 0.9603 | 0.4626 | 0.8669 | 0.7198 | 0.8113 | 0.7089 | 0.9957 | | 0.0474 | 12.93 | 1060 | 0.2220 | 0.7935 | 0.8586 | 0.9464 | 0.9890 | 0.5751 | 0.9476 | 0.7947 | 0.8835 | 0.8229 | 0.9974 | 0.9577 | 0.5129 | 0.8731 | 0.6790 | 0.8098 | 0.7261 | 0.9959 | | 1.1161 | 13.17 | 1080 | 0.2110 | 0.7992 | 0.8716 | 0.9463 | 0.9821 | 0.6330 | 0.9614 | 0.8127 | 0.8632 | 0.8502 | 0.9983 | 0.9585 | 0.5585 | 0.8827 | 0.6897 | 0.8012 | 0.7076 | 0.9962 | | 0.099 | 13.41 | 1100 | 0.2123 | 0.7984 | 0.8743 | 0.9472 | 0.9868 | 0.6128 | 0.9379 | 0.8127 | 0.8678 | 0.9040 | 0.9983 | 0.9570 | 0.5382 | 0.8878 | 0.6926 | 0.8075 | 0.7095 | 0.9962 | | 0.0588 | 13.66 | 1120 | 0.1905 | 0.8032 | 0.8784 | 0.9485 | 0.9814 | 0.6312 | 0.9540 | 0.8039 | 0.8745 | 0.9050 | 0.9984 | 0.9603 | 0.5530 | 0.8902 | 0.6977 | 0.8097 | 0.7157 | 0.9961 | | 0.0769 | 13.9 | 1140 | 0.1758 | 0.8017 | 0.8647 | 0.9500 | 0.9864 | 0.5469 | 0.9429 | 0.8562 | 0.8735 | 0.8484 | 0.9985 | 0.9568 | 0.5034 | 0.8897 | 0.7119 | 0.8164 | 0.7372 | 0.9962 | | 0.121 | 14.15 | 1160 | 0.1858 | 0.8027 | 0.8701 | 0.9499 | 0.9816 | 0.5560 | 0.9518 | 0.8267 | 0.8789 | 0.8986 | 0.9969 | 0.9578 | 0.5182 | 0.8862 | 0.7072 | 0.8231 | 0.7310 | 0.9956 | | 0.0663 | 14.39 | 1180 | 0.2045 | 0.7889 | 0.8640 | 0.9451 | 0.9897 | 0.5519 | 0.9317 | 0.8208 | 0.8533 | 0.9023 | 0.9981 | 0.9563 | 0.4946 | 0.8742 | 0.6857 | 0.8016 | 0.7136 | 0.9960 | | 0.0254 | 14.63 | 1200 | 0.2105 | 0.8003 | 0.8676 | 0.9474 | 0.9816 | 0.6103 | 0.9605 | 0.8074 | 0.8776 | 0.8377 | 0.9982 | 0.9611 | 0.5442 | 0.8794 | 0.6838 | 0.8091 | 0.7281 | 0.9962 | | 0.1533 | 14.88 | 1220 | 0.2133 | 0.7973 | 0.8680 | 0.9470 | 0.9870 | 0.6039 | 0.9465 | 0.8942 | 0.8418 | 0.8046 | 0.9985 | 0.9606 | 0.5294 | 0.8828 | 0.6974 | 0.8046 | 0.7100 | 0.9962 | | 0.0389 | 15.12 | 1240 | 0.1854 | 0.8032 | 0.8722 | 0.9489 | 0.9893 | 0.6311 | 0.9484 | 0.8297 | 0.8745 | 0.8342 | 0.9984 | 0.9600 | 0.5509 | 0.8777 | 0.7049 | 0.8183 | 0.7145 | 0.9962 | | 0.0361 | 15.37 | 1260 | 0.1864 | 0.7939 | 0.8565 | 0.9493 | 0.9896 | 0.5175 | 0.9430 | 0.8092 | 0.8878 | 0.8494 | 0.9990 | 0.9588 | 0.4678 | 0.8842 | 0.6940 | 0.8197 | 0.7371 | 0.9958 | | 0.0211 | 15.61 | 1280 | 0.2172 | 0.7962 | 0.8720 | 0.9454 | 0.9853 | 0.5900 | 0.9531 | 0.8542 | 0.8295 | 0.8943 | 0.9973 | 0.9621 | 0.5328 | 0.8799 | 0.6886 | 0.7885 | 0.7253 | 0.9963 | | 0.1093 | 15.85 | 1300 | 0.1688 | 0.8111 | 0.8728 | 0.9531 | 0.9880 | 0.5895 | 0.9482 | 0.8217 | 0.9014 | 0.8627 | 0.9979 | 0.9620 | 0.5364 | 0.8934 | 0.7190 | 0.8316 | 0.7392 | 0.9965 | | 0.0733 | 16.1 | 1320 | 0.1827 | 0.8126 | 0.8845 | 0.9515 | 0.9869 | 0.6553 | 0.9503 | 0.8784 | 0.8587 | 0.8627 | 0.9990 | 0.9608 | 0.5654 | 0.8826 | 0.7278 | 0.8258 | 0.7300 | 0.9960 | | 0.0708 | 16.34 | 1340 | 0.1822 | 0.8101 | 0.8783 | 0.9527 | 0.9896 | 0.6199 | 0.9476 | 0.8128 | 0.8992 | 0.8827 | 0.9967 | 0.9598 | 0.5407 | 0.8858 | 0.7244 | 0.8394 | 0.7250 | 0.9955 | | 0.0522 | 16.59 | 1360 | 0.1780 | 0.8087 | 0.8748 | 0.9518 | 0.9864 | 0.5917 | 0.9509 | 0.8650 | 0.8725 | 0.8599 | 0.9974 | 0.9615 | 0.5372 | 0.8861 | 0.7247 | 0.8282 | 0.7270 | 0.9959 | | 0.0453 | 16.83 | 1380 | 0.1880 | 0.8020 | 0.8735 | 0.9486 | 0.9891 | 0.5987 | 0.9476 | 0.8654 | 0.8475 | 0.8680 | 0.9983 | 0.9611 | 0.5376 | 0.8809 | 0.7100 | 0.8114 | 0.7165 | 0.9962 | | 0.0351 | 17.07 | 1400 | 0.1885 | 0.8045 | 0.8758 | 0.9502 | 0.9880 | 0.5929 | 0.9435 | 0.8644 | 0.8591 | 0.8846 | 0.9982 | 0.9608 | 0.5261 | 0.8841 | 0.7161 | 0.8189 | 0.7295 | 0.9962 | | 0.0629 | 17.32 | 1420 | 0.1721 | 0.8132 | 0.8780 | 0.9536 | 0.9840 | 0.6104 | 0.9586 | 0.8472 | 0.8888 | 0.8590 | 0.9982 | 0.9627 | 0.5470 | 0.8839 | 0.7381 | 0.8383 | 0.7260 | 0.9962 | | 0.0547 | 17.56 | 1440 | 0.1993 | 0.8025 | 0.8734 | 0.9478 | 0.9877 | 0.6203 | 0.9555 | 0.8655 | 0.8430 | 0.8431 | 0.9987 | 0.9599 | 0.5544 | 0.8666 | 0.7186 | 0.8101 | 0.7115 | 0.9963 | | 0.081 | 17.8 | 1460 | 0.2054 | 0.8034 | 0.8702 | 0.9493 | 0.9892 | 0.6097 | 0.9505 | 0.8118 | 0.8823 | 0.8502 | 0.9976 | 0.9603 | 0.5416 | 0.8769 | 0.6996 | 0.8204 | 0.7283 | 0.9964 | | 0.04 | 18.05 | 1480 | 0.2196 | 0.7915 | 0.8572 | 0.9459 | 0.9893 | 0.5738 | 0.9500 | 0.8183 | 0.8706 | 0.8003 | 0.9979 | 0.9586 | 0.5216 | 0.8679 | 0.6870 | 0.8109 | 0.6976 | 0.9966 | | 0.1213 | 18.29 | 1500 | 0.2320 | 0.7920 | 0.8620 | 0.9461 | 0.9850 | 0.5770 | 0.9594 | 0.8126 | 0.8628 | 0.8395 | 0.9980 | 0.9609 | 0.5168 | 0.8688 | 0.6891 | 0.8062 | 0.7053 | 0.9966 | | 0.0496 | 18.54 | 1520 | 0.1928 | 0.8065 | 0.8745 | 0.9503 | 0.9842 | 0.6020 | 0.9449 | 0.8562 | 0.8736 | 0.8619 | 0.9984 | 0.9612 | 0.5367 | 0.8886 | 0.7098 | 0.8177 | 0.7348 | 0.9966 | | 0.045 | 18.78 | 1540 | 0.2075 | 0.7988 | 0.8787 | 0.9460 | 0.9839 | 0.6246 | 0.9374 | 0.8428 | 0.8457 | 0.9183 | 0.9984 | 0.9607 | 0.5522 | 0.8790 | 0.6941 | 0.7982 | 0.7107 | 0.9968 | | 0.0317 | 19.02 | 1560 | 0.1938 | 0.8051 | 0.8715 | 0.9505 | 0.9892 | 0.5835 | 0.9426 | 0.8278 | 0.8810 | 0.8782 | 0.9980 | 0.9598 | 0.5248 | 0.8878 | 0.7125 | 0.8174 | 0.7364 | 0.9967 | | 0.0489 | 19.27 | 1580 | 0.1844 | 0.8074 | 0.8792 | 0.9500 | 0.9847 | 0.6251 | 0.9529 | 0.8445 | 0.8628 | 0.8855 | 0.9991 | 0.9613 | 0.5493 | 0.8817 | 0.7121 | 0.8174 | 0.7331 | 0.9966 | | 0.091 | 19.51 | 1600 | 0.1976 | 0.7907 | 0.8478 | 0.9495 | 0.9910 | 0.5186 | 0.9449 | 0.8258 | 0.9006 | 0.7553 | 0.9986 | 0.9563 | 0.4818 | 0.8703 | 0.7123 | 0.8358 | 0.6818 | 0.9967 | | 0.0308 | 19.76 | 1620 | 0.1722 | 0.8076 | 0.8722 | 0.9518 | 0.9861 | 0.5906 | 0.9516 | 0.8461 | 0.8820 | 0.8503 | 0.9987 | 0.9612 | 0.5347 | 0.8842 | 0.7192 | 0.8309 | 0.7259 | 0.9968 | | 0.231 | 20.0 | 1640 | 0.1774 | 0.8073 | 0.8726 | 0.9523 | 0.9912 | 0.5837 | 0.9329 | 0.8215 | 0.8979 | 0.8822 | 0.9988 | 0.9554 | 0.5183 | 0.8759 | 0.7299 | 0.8404 | 0.7343 | 0.9966 | | 0.0407 | 20.24 | 1660 | 0.2232 | 0.7988 | 0.8750 | 0.9464 | 0.9844 | 0.6060 | 0.9575 | 0.8624 | 0.8267 | 0.8891 | 0.9989 | 0.9609 | 0.5377 | 0.8691 | 0.7052 | 0.7968 | 0.7252 | 0.9964 | | 0.0303 | 20.49 | 1680 | 0.2146 | 0.8002 | 0.8709 | 0.9479 | 0.9872 | 0.5865 | 0.9498 | 0.8449 | 0.8528 | 0.8774 | 0.9979 | 0.9612 | 0.5307 | 0.8760 | 0.7040 | 0.8067 | 0.7260 | 0.9965 | | 0.0398 | 20.73 | 1700 | 0.2119 | 0.7977 | 0.8754 | 0.9465 | 0.9858 | 0.6453 | 0.9460 | 0.8314 | 0.8575 | 0.8631 | 0.9989 | 0.9632 | 0.5460 | 0.8824 | 0.6865 | 0.8007 | 0.7087 | 0.9967 | | 0.6198 | 20.98 | 1720 | 0.2056 | 0.7992 | 0.8731 | 0.9472 | 0.9852 | 0.6495 | 0.9462 | 0.8761 | 0.8560 | 0.8006 | 0.9982 | 0.9628 | 0.5610 | 0.8854 | 0.6941 | 0.8091 | 0.6852 | 0.9969 | | 0.0428 | 21.22 | 1740 | 0.1978 | 0.7970 | 0.8670 | 0.9483 | 0.9843 | 0.6512 | 0.9546 | 0.8829 | 0.8734 | 0.7246 | 0.9979 | 0.9629 | 0.5622 | 0.8830 | 0.7036 | 0.8269 | 0.6435 | 0.9967 | | 0.04 | 21.46 | 1760 | 0.1939 | 0.7945 | 0.8675 | 0.9469 | 0.9860 | 0.6371 | 0.9491 | 0.8376 | 0.8718 | 0.7922 | 0.9988 | 0.9619 | 0.5536 | 0.8799 | 0.6914 | 0.8183 | 0.6592 | 0.9968 | | 0.0279 | 21.71 | 1780 | 0.2210 | 0.7852 | 0.8516 | 0.9464 | 0.9866 | 0.5663 | 0.9519 | 0.8814 | 0.8654 | 0.7116 | 0.9979 | 0.9611 | 0.5143 | 0.8860 | 0.6954 | 0.8175 | 0.6253 | 0.9966 | | 0.0619 | 21.95 | 1800 | 0.1971 | 0.7930 | 0.8654 | 0.9484 | 0.9867 | 0.6116 | 0.9498 | 0.8739 | 0.8676 | 0.7698 | 0.9981 | 0.9627 | 0.5353 | 0.8885 | 0.7080 | 0.8258 | 0.6342 | 0.9967 | | 0.0203 | 22.2 | 1820 | 0.1964 | 0.7926 | 0.8679 | 0.9464 | 0.9832 | 0.6733 | 0.9576 | 0.8433 | 0.8750 | 0.7447 | 0.9984 | 0.9631 | 0.5685 | 0.8830 | 0.6827 | 0.8230 | 0.6308 | 0.9969 | | 0.0907 | 22.44 | 1840 | 0.2107 | 0.7875 | 0.8587 | 0.9458 | 0.9896 | 0.5721 | 0.9506 | 0.8118 | 0.8643 | 0.8239 | 0.9988 | 0.9596 | 0.5017 | 0.8729 | 0.6816 | 0.8105 | 0.6896 | 0.9969 | | 0.0378 | 22.68 | 1860 | 0.2036 | 0.8053 | 0.8807 | 0.9492 | 0.9850 | 0.6530 | 0.9489 | 0.8037 | 0.8791 | 0.8962 | 0.9989 | 0.9615 | 0.5578 | 0.8828 | 0.6954 | 0.8183 | 0.7247 | 0.9967 | | 0.081 | 22.93 | 1880 | 0.2039 | 0.7989 | 0.8683 | 0.9488 | 0.9908 | 0.5842 | 0.9388 | 0.8415 | 0.8693 | 0.8548 | 0.9982 | 0.9593 | 0.5193 | 0.8801 | 0.7000 | 0.8198 | 0.7170 | 0.9969 | | 0.0237 | 23.17 | 1900 | 0.2002 | 0.7899 | 0.8571 | 0.9471 | 0.9876 | 0.5706 | 0.9510 | 0.8307 | 0.8760 | 0.7854 | 0.9982 | 0.9612 | 0.5203 | 0.8814 | 0.6841 | 0.8224 | 0.6634 | 0.9968 | | 0.0528 | 23.41 | 1920 | 0.2114 | 0.7850 | 0.8538 | 0.9461 | 0.9886 | 0.5398 | 0.9524 | 0.8423 | 0.8587 | 0.7965 | 0.9982 | 0.9603 | 0.4920 | 0.8728 | 0.6905 | 0.8156 | 0.6667 | 0.9970 | | 0.0793 | 23.66 | 1940 | 0.1825 | 0.8003 | 0.8694 | 0.9498 | 0.9888 | 0.6138 | 0.9454 | 0.8474 | 0.8786 | 0.8130 | 0.9990 | 0.9604 | 0.5439 | 0.8800 | 0.7102 | 0.8346 | 0.6757 | 0.9969 | | 0.0288 | 23.9 | 1960 | 0.1854 | 0.8051 | 0.8705 | 0.9520 | 0.9893 | 0.6176 | 0.9509 | 0.8519 | 0.8913 | 0.7944 | 0.9979 | 0.9608 | 0.5530 | 0.8781 | 0.7302 | 0.8473 | 0.6693 | 0.9968 | | 0.0525 | 24.15 | 1980 | 0.1603 | 0.8141 | 0.8846 | 0.9550 | 0.9864 | 0.6848 | 0.9472 | 0.8581 | 0.9083 | 0.8084 | 0.9990 | 0.9620 | 0.5691 | 0.8876 | 0.7440 | 0.8616 | 0.6776 | 0.9966 | | 0.026 | 24.39 | 2000 | 0.1684 | 0.8068 | 0.8752 | 0.9532 | 0.9877 | 0.6538 | 0.9479 | 0.8936 | 0.8893 | 0.7554 | 0.9989 | 0.9616 | 0.5547 | 0.8856 | 0.7362 | 0.8538 | 0.6586 | 0.9969 | | 0.0397 | 24.63 | 2020 | 0.1692 | 0.8121 | 0.8760 | 0.9542 | 0.9870 | 0.5916 | 0.9529 | 0.8621 | 0.8871 | 0.8535 | 0.9979 | 0.9616 | 0.5381 | 0.8834 | 0.7400 | 0.8478 | 0.7173 | 0.9968 | | 0.4272 | 24.88 | 2040 | 0.1785 | 0.8101 | 0.8749 | 0.9535 | 0.9868 | 0.5751 | 0.9539 | 0.8895 | 0.8697 | 0.8520 | 0.9975 | 0.9633 | 0.5204 | 0.8832 | 0.7380 | 0.8374 | 0.7316 | 0.9966 | | 0.0399 | 25.12 | 2060 | 0.1765 | 0.8070 | 0.8682 | 0.9532 | 0.9885 | 0.5755 | 0.9559 | 0.8543 | 0.8893 | 0.8154 | 0.9983 | 0.9615 | 0.5252 | 0.8758 | 0.7359 | 0.8473 | 0.7064 | 0.9968 | | 0.0456 | 25.37 | 2080 | 0.1777 | 0.8060 | 0.8668 | 0.9535 | 0.9900 | 0.5873 | 0.9487 | 0.8418 | 0.9061 | 0.7955 | 0.9983 | 0.9605 | 0.5270 | 0.8821 | 0.7299 | 0.8526 | 0.6928 | 0.9969 | | 0.0414 | 25.61 | 2100 | 0.1844 | 0.8132 | 0.8847 | 0.9531 | 0.9864 | 0.6789 | 0.9515 | 0.8486 | 0.8916 | 0.8373 | 0.9984 | 0.9623 | 0.5671 | 0.8849 | 0.7266 | 0.8418 | 0.7130 | 0.9970 | | 0.0925 | 25.85 | 2120 | 0.2120 | 0.8035 | 0.8663 | 0.9521 | 0.9886 | 0.5885 | 0.9500 | 0.8118 | 0.9077 | 0.8193 | 0.9982 | 0.9607 | 0.5215 | 0.8832 | 0.7125 | 0.8402 | 0.7097 | 0.9970 | | 0.0443 | 26.1 | 2140 | 0.1615 | 0.8151 | 0.8790 | 0.9555 | 0.9882 | 0.5945 | 0.9449 | 0.8779 | 0.8874 | 0.8610 | 0.9992 | 0.9603 | 0.5309 | 0.8871 | 0.7511 | 0.8517 | 0.7281 | 0.9964 | | 0.0728 | 26.34 | 2160 | 0.1701 | 0.8091 | 0.8771 | 0.9534 | 0.9872 | 0.6244 | 0.9493 | 0.8818 | 0.8816 | 0.8164 | 0.9989 | 0.9624 | 0.5469 | 0.8858 | 0.7362 | 0.8478 | 0.6876 | 0.9968 | | 0.0484 | 26.59 | 2180 | 0.1720 | 0.8061 | 0.8707 | 0.9530 | 0.9895 | 0.6110 | 0.9487 | 0.8831 | 0.8852 | 0.7787 | 0.9987 | 0.9615 | 0.5429 | 0.8814 | 0.7374 | 0.8496 | 0.6727 | 0.9969 | | 0.027 | 26.83 | 2200 | 0.1728 | 0.8060 | 0.8754 | 0.9525 | 0.9879 | 0.6263 | 0.9498 | 0.8718 | 0.8823 | 0.8111 | 0.9983 | 0.9620 | 0.5489 | 0.8825 | 0.7351 | 0.8472 | 0.6694 | 0.9970 | | 0.0465 | 27.07 | 2220 | 0.1763 | 0.8075 | 0.8751 | 0.9534 | 0.9875 | 0.6402 | 0.9496 | 0.8776 | 0.8938 | 0.7791 | 0.9981 | 0.9623 | 0.5514 | 0.8842 | 0.7366 | 0.8533 | 0.6675 | 0.9970 | | 0.0213 | 27.32 | 2240 | 0.1740 | 0.8085 | 0.8743 | 0.9538 | 0.9869 | 0.6184 | 0.9501 | 0.8787 | 0.8917 | 0.7963 | 0.9983 | 0.9632 | 0.5446 | 0.8852 | 0.7370 | 0.8523 | 0.6799 | 0.9971 | | 0.022 | 27.56 | 2260 | 0.1923 | 0.7998 | 0.8675 | 0.9508 | 0.9863 | 0.5850 | 0.9506 | 0.8669 | 0.8777 | 0.8084 | 0.9979 | 0.9613 | 0.5253 | 0.8839 | 0.7155 | 0.8387 | 0.6769 | 0.9970 | | 0.0311 | 27.8 | 2280 | 0.1871 | 0.8005 | 0.8657 | 0.9518 | 0.9877 | 0.5896 | 0.9482 | 0.8699 | 0.8900 | 0.7763 | 0.9980 | 0.9612 | 0.5235 | 0.8837 | 0.7229 | 0.8452 | 0.6701 | 0.9970 | | 0.0281 | 28.05 | 2300 | 0.1984 | 0.7970 | 0.8665 | 0.9490 | 0.9881 | 0.6233 | 0.9441 | 0.9007 | 0.8659 | 0.7451 | 0.9984 | 0.9614 | 0.5465 | 0.8850 | 0.7081 | 0.8310 | 0.6496 | 0.9971 | | 0.029 | 28.29 | 2320 | 0.1929 | 0.8018 | 0.8684 | 0.9508 | 0.9890 | 0.6266 | 0.9484 | 0.8783 | 0.8813 | 0.7572 | 0.9981 | 0.9612 | 0.5522 | 0.8820 | 0.7180 | 0.8409 | 0.6616 | 0.9970 | | 0.0205 | 28.54 | 2340 | 0.1939 | 0.8127 | 0.8877 | 0.9536 | 0.9857 | 0.6927 | 0.9459 | 0.8321 | 0.9031 | 0.8553 | 0.9989 | 0.9628 | 0.5574 | 0.8940 | 0.7233 | 0.8410 | 0.7133 | 0.9969 | | 0.1185 | 28.78 | 2360 | 0.2147 | 0.7963 | 0.8662 | 0.9476 | 0.9888 | 0.5806 | 0.9517 | 0.8657 | 0.8458 | 0.8323 | 0.9987 | 0.9615 | 0.5186 | 0.8772 | 0.6987 | 0.8088 | 0.7122 | 0.9971 | | 0.0848 | 29.02 | 2380 | 0.1978 | 0.8047 | 0.8712 | 0.9510 | 0.9884 | 0.5966 | 0.9504 | 0.8398 | 0.8784 | 0.8459 | 0.9988 | 0.9618 | 0.5329 | 0.8799 | 0.7125 | 0.8299 | 0.7184 | 0.9972 | | 0.028 | 29.27 | 2400 | 0.2065 | 0.8000 | 0.8675 | 0.9497 | 0.9878 | 0.6095 | 0.9561 | 0.8780 | 0.8647 | 0.7781 | 0.9983 | 0.9629 | 0.5428 | 0.8784 | 0.7121 | 0.8296 | 0.6767 | 0.9973 | | 0.0232 | 29.51 | 2420 | 0.1912 | 0.8063 | 0.8750 | 0.9520 | 0.9887 | 0.6177 | 0.9491 | 0.8746 | 0.8742 | 0.8221 | 0.9983 | 0.9631 | 0.5401 | 0.8824 | 0.7242 | 0.8371 | 0.7000 | 0.9973 | | 0.0241 | 29.76 | 2440 | 0.1768 | 0.8095 | 0.8797 | 0.9525 | 0.9871 | 0.6426 | 0.9506 | 0.8691 | 0.8781 | 0.8319 | 0.9986 | 0.9637 | 0.5552 | 0.8871 | 0.7228 | 0.8388 | 0.7015 | 0.9971 | | 0.0249 | 30.0 | 2460 | 0.1885 | 0.8051 | 0.8734 | 0.9518 | 0.9885 | 0.6096 | 0.9517 | 0.8740 | 0.8714 | 0.8203 | 0.9986 | 0.9631 | 0.5348 | 0.8836 | 0.7230 | 0.8353 | 0.6989 | 0.9970 | | 0.0314 | 30.24 | 2480 | 0.1853 | 0.8046 | 0.8698 | 0.9521 | 0.9882 | 0.6049 | 0.9524 | 0.8782 | 0.8786 | 0.7873 | 0.9989 | 0.9630 | 0.5373 | 0.8846 | 0.7241 | 0.8409 | 0.6853 | 0.9968 | | 0.045 | 30.49 | 2500 | 0.1810 | 0.8134 | 0.8792 | 0.9542 | 0.9871 | 0.6099 | 0.9502 | 0.8672 | 0.8840 | 0.8573 | 0.9986 | 0.9621 | 0.5421 | 0.8876 | 0.7371 | 0.8430 | 0.7251 | 0.9971 | | 0.0261 | 30.73 | 2520 | 0.1893 | 0.8172 | 0.8897 | 0.9548 | 0.9847 | 0.6630 | 0.9480 | 0.8516 | 0.8922 | 0.8897 | 0.9988 | 0.9619 | 0.5530 | 0.8890 | 0.7377 | 0.8441 | 0.7375 | 0.9972 | | 0.0175 | 30.98 | 2540 | 0.1904 | 0.8155 | 0.8830 | 0.9553 | 0.9866 | 0.6192 | 0.9535 | 0.8526 | 0.8915 | 0.8791 | 0.9983 | 0.9635 | 0.5371 | 0.8874 | 0.7404 | 0.8472 | 0.7359 | 0.9972 | | 0.0326 | 31.22 | 2560 | 0.1888 | 0.8126 | 0.8811 | 0.9535 | 0.9875 | 0.6216 | 0.9501 | 0.8821 | 0.8722 | 0.8559 | 0.9985 | 0.9627 | 0.5421 | 0.8861 | 0.7326 | 0.8392 | 0.7283 | 0.9970 | | 0.0854 | 31.46 | 2580 | 0.1981 | 0.8043 | 0.8676 | 0.9523 | 0.9893 | 0.5619 | 0.9525 | 0.8688 | 0.8749 | 0.8275 | 0.9983 | 0.9613 | 0.5166 | 0.8798 | 0.7305 | 0.8396 | 0.7054 | 0.9969 | | 0.0313 | 31.71 | 2600 | 0.2039 | 0.8109 | 0.8805 | 0.9522 | 0.9873 | 0.6476 | 0.9539 | 0.8586 | 0.8781 | 0.8404 | 0.9978 | 0.9621 | 0.5616 | 0.8829 | 0.7235 | 0.8372 | 0.7118 | 0.9968 | | 0.0228 | 31.95 | 2620 | 0.2029 | 0.8079 | 0.8795 | 0.9515 | 0.9876 | 0.6392 | 0.9510 | 0.8668 | 0.8685 | 0.8450 | 0.9988 | 0.9620 | 0.5487 | 0.8832 | 0.7207 | 0.8320 | 0.7118 | 0.9970 | | 0.0301 | 32.2 | 2640 | 0.2147 | 0.8037 | 0.8739 | 0.9499 | 0.9872 | 0.6339 | 0.9546 | 0.8759 | 0.8607 | 0.8062 | 0.9988 | 0.9620 | 0.5508 | 0.8801 | 0.7129 | 0.8259 | 0.6974 | 0.9971 | | 0.0312 | 32.44 | 2660 | 0.2114 | 0.8016 | 0.8718 | 0.9496 | 0.9876 | 0.6201 | 0.9532 | 0.8755 | 0.8584 | 0.8090 | 0.9990 | 0.9616 | 0.5405 | 0.8791 | 0.7107 | 0.8252 | 0.6969 | 0.9969 | | 0.0427 | 32.68 | 2680 | 0.2085 | 0.8015 | 0.8694 | 0.9506 | 0.9873 | 0.6277 | 0.9543 | 0.8743 | 0.8767 | 0.7668 | 0.9986 | 0.9622 | 0.5421 | 0.8828 | 0.7131 | 0.8356 | 0.6777 | 0.9970 | | 0.0398 | 32.93 | 2700 | 0.2139 | 0.8062 | 0.8766 | 0.9507 | 0.9850 | 0.6461 | 0.9581 | 0.8557 | 0.8761 | 0.8176 | 0.9976 | 0.9612 | 0.5560 | 0.8817 | 0.7157 | 0.8308 | 0.7017 | 0.9967 | | 0.0274 | 33.17 | 2720 | 0.2093 | 0.8094 | 0.8806 | 0.9516 | 0.9847 | 0.6481 | 0.9555 | 0.8572 | 0.8764 | 0.8440 | 0.9980 | 0.9615 | 0.5583 | 0.8860 | 0.7187 | 0.8323 | 0.7124 | 0.9969 | | 0.0309 | 33.41 | 2740 | 0.2170 | 0.8068 | 0.8833 | 0.9505 | 0.9840 | 0.6723 | 0.9536 | 0.8855 | 0.8602 | 0.8290 | 0.9984 | 0.9632 | 0.5588 | 0.8902 | 0.7108 | 0.8261 | 0.7013 | 0.9969 | | 0.0395 | 33.66 | 2760 | 0.2031 | 0.8060 | 0.8787 | 0.9513 | 0.9879 | 0.6361 | 0.9472 | 0.8725 | 0.8689 | 0.8401 | 0.9986 | 0.9624 | 0.5421 | 0.8871 | 0.7157 | 0.8327 | 0.7048 | 0.9970 | | 0.0298 | 33.9 | 2780 | 0.1892 | 0.8082 | 0.8804 | 0.9522 | 0.9868 | 0.6612 | 0.9493 | 0.8657 | 0.8823 | 0.8189 | 0.9987 | 0.9630 | 0.5586 | 0.8887 | 0.7184 | 0.8409 | 0.6906 | 0.9970 | | 0.0313 | 34.15 | 2800 | 0.1960 | 0.8064 | 0.8772 | 0.9522 | 0.9881 | 0.6294 | 0.9442 | 0.8685 | 0.8810 | 0.8310 | 0.9984 | 0.9623 | 0.5435 | 0.8893 | 0.7198 | 0.8407 | 0.6925 | 0.9970 | | 0.0249 | 34.39 | 2820 | 0.1958 | 0.8086 | 0.8772 | 0.9527 | 0.9879 | 0.6079 | 0.9521 | 0.8570 | 0.8777 | 0.8597 | 0.9980 | 0.9625 | 0.5362 | 0.8852 | 0.7255 | 0.8383 | 0.7154 | 0.9969 | | 0.0959 | 34.63 | 2840 | 0.2022 | 0.8077 | 0.8757 | 0.9520 | 0.9877 | 0.6105 | 0.9548 | 0.8691 | 0.8697 | 0.8401 | 0.9981 | 0.9627 | 0.5434 | 0.8838 | 0.7228 | 0.8347 | 0.7099 | 0.9969 | | 0.0195 | 34.88 | 2860 | 0.1878 | 0.8089 | 0.8758 | 0.9526 | 0.9884 | 0.6187 | 0.9483 | 0.8695 | 0.8809 | 0.8262 | 0.9985 | 0.9624 | 0.5476 | 0.8880 | 0.7218 | 0.8411 | 0.7046 | 0.9969 | | 0.0144 | 35.12 | 2880 | 0.1991 | 0.8099 | 0.8809 | 0.9523 | 0.9851 | 0.6489 | 0.9545 | 0.8723 | 0.8751 | 0.8324 | 0.9984 | 0.9637 | 0.5606 | 0.8891 | 0.7197 | 0.8377 | 0.7017 | 0.9969 | | 0.0316 | 35.37 | 2900 | 0.2001 | 0.8057 | 0.8747 | 0.9515 | 0.9883 | 0.6212 | 0.9501 | 0.8815 | 0.8704 | 0.8137 | 0.9979 | 0.9625 | 0.5443 | 0.8877 | 0.7179 | 0.8351 | 0.6955 | 0.9968 | | 0.0363 | 35.61 | 2920 | 0.2015 | 0.8048 | 0.8718 | 0.9516 | 0.9887 | 0.6135 | 0.9523 | 0.8771 | 0.8752 | 0.7983 | 0.9977 | 0.9624 | 0.5432 | 0.8856 | 0.7195 | 0.8383 | 0.6878 | 0.9968 | | 0.1011 | 35.85 | 2940 | 0.1922 | 0.8089 | 0.8777 | 0.9529 | 0.9882 | 0.6236 | 0.9487 | 0.8627 | 0.8810 | 0.8407 | 0.9989 | 0.9621 | 0.5429 | 0.8874 | 0.7256 | 0.8414 | 0.7057 | 0.9970 | | 0.0455 | 36.1 | 2960 | 0.2002 | 0.8059 | 0.8733 | 0.9519 | 0.9888 | 0.6067 | 0.9517 | 0.8642 | 0.8746 | 0.8285 | 0.9986 | 0.9621 | 0.5401 | 0.8853 | 0.7211 | 0.8371 | 0.6988 | 0.9970 | | 0.0289 | 36.34 | 2980 | 0.1995 | 0.8096 | 0.8805 | 0.9521 | 0.9879 | 0.6477 | 0.9501 | 0.8688 | 0.8739 | 0.8365 | 0.9985 | 0.9625 | 0.5577 | 0.8869 | 0.7201 | 0.8362 | 0.7069 | 0.9971 | | 0.091 | 36.59 | 3000 | 0.1941 | 0.8124 | 0.8867 | 0.9529 | 0.9882 | 0.6654 | 0.9482 | 0.8641 | 0.8745 | 0.8678 | 0.9987 | 0.9627 | 0.5555 | 0.8877 | 0.7251 | 0.8370 | 0.7217 | 0.9972 | | 0.0635 | 36.83 | 3020 | 0.1858 | 0.8132 | 0.8837 | 0.9535 | 0.9875 | 0.6478 | 0.9525 | 0.8476 | 0.8842 | 0.8673 | 0.9988 | 0.9632 | 0.5549 | 0.8876 | 0.7265 | 0.8408 | 0.7220 | 0.9972 | | 0.0244 | 37.07 | 3040 | 0.1862 | 0.8109 | 0.8797 | 0.9533 | 0.9875 | 0.6420 | 0.9502 | 0.8755 | 0.8815 | 0.8221 | 0.9987 | 0.9633 | 0.5540 | 0.8906 | 0.7254 | 0.8422 | 0.7034 | 0.9972 | | 0.0265 | 37.32 | 3060 | 0.1864 | 0.8146 | 0.8844 | 0.9543 | 0.9867 | 0.6543 | 0.9477 | 0.8679 | 0.8891 | 0.8461 | 0.9987 | 0.9633 | 0.5578 | 0.8936 | 0.7306 | 0.8449 | 0.7146 | 0.9972 | | 0.0344 | 37.56 | 3080 | 0.1838 | 0.8162 | 0.8873 | 0.9547 | 0.9862 | 0.6641 | 0.9524 | 0.8551 | 0.8905 | 0.8644 | 0.9988 | 0.9636 | 0.5604 | 0.8903 | 0.7340 | 0.8471 | 0.7211 | 0.9972 | | 0.0267 | 37.8 | 3100 | 0.1903 | 0.8137 | 0.8841 | 0.9540 | 0.9870 | 0.6543 | 0.9499 | 0.8745 | 0.8841 | 0.8409 | 0.9983 | 0.9633 | 0.5565 | 0.8921 | 0.7309 | 0.8444 | 0.7119 | 0.9971 | | 0.3041 | 38.05 | 3120 | 0.1891 | 0.8051 | 0.8701 | 0.9526 | 0.9903 | 0.5815 | 0.9478 | 0.8685 | 0.8792 | 0.8248 | 0.9985 | 0.9604 | 0.5197 | 0.8850 | 0.7270 | 0.8415 | 0.7051 | 0.9969 | | 0.0272 | 38.29 | 3140 | 0.1971 | 0.8077 | 0.8754 | 0.9522 | 0.9877 | 0.6189 | 0.9552 | 0.8747 | 0.8726 | 0.8205 | 0.9983 | 0.9628 | 0.5447 | 0.8851 | 0.7236 | 0.8373 | 0.7036 | 0.9971 | | 0.063 | 38.54 | 3160 | 0.1888 | 0.8125 | 0.8786 | 0.9542 | 0.9881 | 0.6109 | 0.9529 | 0.8503 | 0.8879 | 0.8613 | 0.9986 | 0.9625 | 0.5407 | 0.8857 | 0.7339 | 0.8452 | 0.7224 | 0.9971 | | 0.0527 | 38.78 | 3180 | 0.1899 | 0.8121 | 0.8842 | 0.9531 | 0.9865 | 0.6598 | 0.9521 | 0.8748 | 0.8761 | 0.8415 | 0.9986 | 0.9634 | 0.5575 | 0.8896 | 0.7261 | 0.8392 | 0.7117 | 0.9972 | | 0.0465 | 39.02 | 3200 | 0.1947 | 0.8108 | 0.8793 | 0.9532 | 0.9881 | 0.6358 | 0.9517 | 0.8722 | 0.8808 | 0.8284 | 0.9979 | 0.9626 | 0.5509 | 0.8879 | 0.7275 | 0.8422 | 0.7075 | 0.9970 | | 0.0305 | 39.27 | 3220 | 0.1884 | 0.8118 | 0.8806 | 0.9538 | 0.9888 | 0.6265 | 0.9468 | 0.8655 | 0.8838 | 0.8547 | 0.9983 | 0.9620 | 0.5422 | 0.8885 | 0.7313 | 0.8439 | 0.7177 | 0.9971 | | 0.0167 | 39.51 | 3240 | 0.1935 | 0.8111 | 0.8805 | 0.9533 | 0.9879 | 0.6352 | 0.9505 | 0.8737 | 0.8794 | 0.8383 | 0.9981 | 0.9629 | 0.5473 | 0.8891 | 0.7279 | 0.8414 | 0.7120 | 0.9971 | | 0.0507 | 39.76 | 3260 | 0.1888 | 0.8109 | 0.8783 | 0.9535 | 0.9883 | 0.6259 | 0.9528 | 0.8630 | 0.8829 | 0.8363 | 0.9986 | 0.9625 | 0.5459 | 0.8854 | 0.7306 | 0.8435 | 0.7110 | 0.9971 | | 0.0354 | 40.0 | 3280 | 0.1900 | 0.8129 | 0.8809 | 0.9540 | 0.9875 | 0.6312 | 0.9541 | 0.8566 | 0.8860 | 0.8526 | 0.9984 | 0.9631 | 0.5490 | 0.8864 | 0.7326 | 0.8448 | 0.7176 | 0.9972 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1

anoop3/autotrain-be1zs-exv75

anoop3

2024-02-27T13:06:28Z

1

0

diffusers

[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]

text-to-image

2024-02-27T13:06:25Z

--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: moni female tags: - text-to-image - diffusers - autotrain inference: true --- # DreamBooth trained by AutoTrain Text encoder was not trained.

zzttbrdd/gemcy_v1_2

zzttbrdd

2024-02-27T13:06:24Z

112

0

transformers

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

text-generation

2024-02-27T13:04:22Z

--- 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]

ibunescu/Phi-2_GDPR_10_3e

ibunescu

2024-02-27T13:03:12Z

48

0

transformers

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

text-generation

2024-02-27T12:59:26Z

--- 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]

zzttbrdd/gemcy_v1_1

zzttbrdd

2024-02-27T13:01:50Z

113

0

transformers

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

text-generation

2024-02-27T12:59:53Z

--- 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]

Neomedallion/dqn-SpaceInvadersNoFrameskip-v4

Neomedallion

2024-02-27T12:59:20Z

0

stable-baselines3

[ "stable-baselines3", "SpaceInvadersNoFrameskip-v4", "deep-reinforcement-learning", "reinforcement-learning", "model-index", "region:us" ]

reinforcement-learning

2023-05-05T07:14:06Z

--- library_name: stable-baselines3 tags: - SpaceInvadersNoFrameskip-v4 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: DQN results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: SpaceInvadersNoFrameskip-v4 type: SpaceInvadersNoFrameskip-v4 metrics: - type: mean_reward value: 329.00 +/- 157.97 name: mean_reward verified: false --- # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4** This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Neomedallion -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga Neomedallion -f logs/ python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga Neomedallion ``` ## Hyperparameters ```python OrderedDict([('batch_size', 32), ('buffer_size', 100000), ('env_wrapper', ['stable_baselines3.common.atari_wrappers.AtariWrapper']), ('exploration_final_eps', 0.01), ('exploration_fraction', 0.1), ('frame_stack', 4), ('gradient_steps', 1), ('learning_rate', 0.0001), ('learning_starts', 100000), ('n_timesteps', 10000.0), ('optimize_memory_usage', False), ('policy', 'CnnPolicy'), ('target_update_interval', 1000), ('train_freq', 4), ('normalize', False)]) ``` # Environment Arguments ```python {'render_mode': 'rgb_array'} ```

FKunneman/distilbert-base-uncased-finetuned-cola

FKunneman

2024-02-27T12:58:16Z

9

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-27T10:58:00Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - matthews_correlation model-index: - name: distilbert-base-uncased-finetuned-cola results: [] ---  # distilbert-base-uncased-finetuned-cola This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8294 - Matthews Correlation: 0.5466 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | |:-------------:|:-----:|:----:|:---------------:|:--------------------:| | 0.5181 | 1.0 | 535 | 0.4541 | 0.4504 | | 0.3411 | 2.0 | 1070 | 0.4744 | 0.5094 | | 0.2321 | 3.0 | 1605 | 0.6309 | 0.5391 | | 0.1737 | 4.0 | 2140 | 0.7876 | 0.5369 | | 0.1265 | 5.0 | 2675 | 0.8294 | 0.5466 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

ibunescu/Phi-2_GDPR_9_3e_adapter

ibunescu

2024-02-27T12:57:51Z

0

transformers

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

null

2024-02-27T11:09:12Z

--- 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]

mohammadhabp/flan-t5-small-esnli-lora

mohammadhabp

2024-02-27T12:52:27Z

4

0

peft

[ "peft", "safetensors", "generated_from_trainer", "base_model:google/flan-t5-base", "base_model:adapter:google/flan-t5-base", "license:apache-2.0", "region:us" ]

null

2024-02-25T15:02:02Z

--- license: apache-2.0 library_name: peft tags: - generated_from_trainer metrics: - rouge - f1 base_model: google/flan-t5-base model-index: - name: flan-t5-small-esnli-lora results: [] ---  # flan-t5-small-esnli-lora This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.6258 - Rouge1: 0.6257 - Rouge2: 0.4156 - Rougel: 0.5682 - F1: 0.8850 ## 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: 0.001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | F1 | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:| | 1.1793 | 0.25 | 8584 | 1.7215 | 0.6161 | 0.4037 | 0.5577 | 0.8738 | | 1.1408 | 0.5 | 17168 | 1.6903 | 0.6194 | 0.4096 | 0.5615 | 0.8730 | | 1.1122 | 0.75 | 25752 | 1.6155 | 0.6267 | 0.4179 | 0.5693 | 0.8832 | | 1.0929 | 1.0 | 34336 | 1.6258 | 0.6257 | 0.4156 | 0.5682 | 0.8850 | ### Framework versions - PEFT 0.8.2 - Transformers 4.38.1 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1

jayakushwaha/my-favourite-character

jayakushwaha

2024-02-27T12:50:21Z

0

null

[ "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2024-02-27T12:48:17Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Favourite-Character Dreambooth model trained by jayakushwaha following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: 0206CS221107 Sample pictures of this concept: ![0](https://huggingface.co/jayakushwaha/my-favourite-character/resolve/main/sample_images/Screenshot_(23).png)

Ayus077BCT014Bhandari/vartat5-using-100K-plus-24

Ayus077BCT014Bhandari

2024-02-27T12:48:22Z

96

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text2text-generation

2024-02-27T10:49:56Z

--- 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]

CreazyAI/gemma-Code-Instruct-Finetune-test

CreazyAI

2024-02-27T12:46:53Z

113

0

transformers

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

text-generation

2024-02-27T12:40:23Z

--- 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]

yashraj8959/dreambooth-project

yashraj8959

2024-02-27T12:45:04Z

0

null

[ "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2024-02-27T12:40:27Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### Dreambooth-Project Dreambooth model trained by yashraj8959 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: 0967CS211067 Sample pictures of this concept:

tejasreereddy/mistral-test

tejasreereddy

2024-02-27T12:40:38Z

0

transformers

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

null

2024-02-27T10:19:15Z

--- 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]

airesearch/WangchanLion7B

airesearch

2024-02-27T12:40:22Z

38

7

transformers

[ "transformers", "pytorch", "mpt", "text-generation", "custom_code", "th", "en", "dataset:laion/OIG", "dataset:databricks/databricks-dolly-15k", "dataset:thaisum", "dataset:scb_mt_enth_2020", "dataset:garage-bAInd/Open-Platypus", "dataset:iapp_wiki_qa_squad", "dataset:pythainlp/han-instruct-dataset-v1.0", "dataset:cognitivecomputations/dolphin", "dataset:Hello-SimpleAI/HC3", "dataset:Muennighoff/xP3x", "dataset:openai/summarize_from_feedback", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2023-12-26T05:42:07Z

--- license: apache-2.0 language: - th - en datasets: - laion/OIG - databricks/databricks-dolly-15k - thaisum - scb_mt_enth_2020 - garage-bAInd/Open-Platypus - iapp_wiki_qa_squad - pythainlp/han-instruct-dataset-v1.0 - cognitivecomputations/dolphin - Hello-SimpleAI/HC3 - Muennighoff/xP3x - openai/summarize_from_feedback --- # Model Card for WangChanLion 7B - The Multilingual Instruction-Following Model WangChanLion is a Multilingual, instruction-finetuned on Southeast Asian Languages SEA-LION 7B using open-source, commercially permissible datasets sample from LAION OIG chip2 and infill_dbpedia, DataBricks Dolly v2, OpenAI TL;DR, Hello-SimpleAI HC3, dolphin, iapp_wiki_qa_squad, thaisum, xlsum, scb_mt_enth_2020, han dataset, xp3x and Open-Platypus, a total of ~500k samples. Non-commercial datasets were filtered out. Released under apache 2.0 license. The models are trained to perform a subset of instruction-following tasks we found most relevant: reading comprehension, brainstorming, and creative writing. In this model, we focus on Thai and English datasets. We perform Vicuna-style evaluation using human evaluation. In a similar manner to Dolly v2, we only use open-source, commercially permissive pretrained models and datasets. Our models are neither restricted by non-commercial clauses like LLaMA-based models nor non-compete clauses like models that use self-instruct datasets from ChatGPT. - Developers: PyThaiNLP and VISTEC-depa AI Research Institute of Thailand - Model type: SEA-LION 7B (MPT architecture) ## Model Sources - Repository: https://github.com/vistec-AI/WangchanLion - Demo: [demo_WangchanLion.ipynb - Colaboratory](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L) # Use cases ## Direct Use Intended to be used as an instruction-following model for reading comprehension, brainstorming, and creative writing. ## Downstream Use The model can be finetuned for any typical instruction-following use cases. ## Out-of-Scope Use We do not expect the models to perform well in math problems, reasoning, and factfulness. ## Bias, Risks, and Limitations We noticed similar limitations to other finetuned instruction followers, such as math problems, reasoning, and factfulness. Even though the models do not perform on the level that we expect them to be abused, they do contain undesirable biases and toxicity and should be further optimized for your particular use cases. ## Recommendations Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model. More information is needed for further recommendations. # Get Started Use the code [here](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L) to get started with the model. Or ```python from transformers import AutoModelForCausalLM, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained( "airesearch/WangchanLion7B", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained( "airesearch/WangchanLion7B", trust_remote_code=True, return_dict=True, load_in_8bit=True , device_map="auto", torch_dtype=torch.float16, offload_folder="./", low_cpu_mem_usage=True, ) def get_prompt(question: str,context: str = None) -> str: if context is not None: return """พื้นหลัง:\n\n{context}\n\nคำถาม:{question}\n\nตอบ:""".format(context=context, question=question) return """คำถาม:{question}\n\nตอบ:""".format(question=question) question = "เกิดอะไรขึ้นที่เทียนอันเหมินตอนปี 1989" full_prompt = get_prompt(question=question) tokens = tokenizer(full_prompt, return_tensors="pt").to("cuda") output = model.generate( input_ids=tokens['input_ids'], attention_mask=tokens['attention_mask'], max_new_tokens=256, early_stopping=True, top_k=50, top_p=0.95, do_sample=True, temperature=0.3, repetition_penalty = 1.2, eos_token_id = tokenizer.eos_token_id, ) print(tokenizer.decode(output[0], skip_special_tokens=True)) ``` # Training Details ## Training Data Finetuning datasets are sourced from [LAION OIG chip2 and infill_dbpedia (Apache-2.0)](https://huggingface.co/datasets/laion/OIG), [DataBricks Dolly v2 (Apache-2.0)](https://github.com/databrickslabs/dolly), [OpenAI TL;DR (MIT)](https://github.com/openai/summarize-from-feedback), [Hello-SimpleAI HC3 (CC-BY SA)](https://huggingface.co/datasets/Hello-SimpleAI/HC3), [dolphin](https://huggingface.co/datasets/ehartford/dolphin), [iapp_wiki_qa_squad](https://huggingface.co/datasets/iapp_wiki_qa_squad) , [thaisum](https://huggingface.co/datasets/thaisum), [xlsum](https://huggingface.co/datasets/csebuetnlp/xlsum), [scb_mt_enth_2020](https://huggingface.co/datasets/scb_mt_enth_2020), [han dataset](https://huggingface.co/datasets/pythainlp/han-instruct-dataset-v1.0), [xp3x](https://huggingface.co/datasets/Muennighoff/xP3x) and [Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus). ## Training regime - QLoRA with 4 A100 (40GB) # Evaluation We performed human and machine evaluations on XQuAD zero-shot and one-shot settings: ## XQuAD | Model | F1 (Zero-shot) | F1 (One-shot) | |:--------------:|:--------------:|:-------------:| | openthaigpt7B | 27.3487 | 34.3104 | | SeaLLM7B V2 | 16.1104 | 25.7399 | | Typhoon-7b | 34.46 | **54.03** | | WangchanLion7B | **45.8763** | 49.9145 | ## iAPP Wiki QA | Model | F1 (Zero-shot) | F1 (One-shot) | |:--------------:|:--------------:|:-------------:| | openthaigpt7B | 40.0614 | 46.6883 | | SeaLLM7B V2 | 23.6425 | 28.9934 | | WangchanLion7B | **58.9051** | **62.9776** | # What WangchanLion offers: - Transparent pretrained model: The development of SEA-LION is community-driven, with different ASEAN collaborators contributing pretraining datasets. The SEA-LION developers ensure that all datasets are safe and can be utilized without commercial restrictions. This transparency extends to the provision of pretraining code, ensuring anyone can replicate SEA-LION using the provided datasets. - Transparent finetuning data: In the spirit of open science, we make the finetuning data for WangchanLion accessible to all. This commitment to openness empowers the community by providing complete visibility into the instruction finetuning data that shapes WangchanLion. - Transparent finetuning code: The finetuning code for WangchanLion is readily available for distribution. By sharing our methods and processes, we invite others to learn from, build upon, and innovate alongside us.

loubnabnl/outputs

loubnabnl

2024-02-27T12:35:45Z

1

0

peft

[ "peft", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:bigcode/starcoder2-3b", "base_model:adapter:bigcode/starcoder2-3b", "license:bigcode-openrail-m", "region:us" ]

null

2024-02-27T12:35:11Z

--- license: bigcode-openrail-m library_name: peft tags: - trl - sft - generated_from_trainer base_model: bigcode/starcoder2-3b model-index: - name: outputs results: [] ---  # outputs This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) 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: 2e-05 - train_batch_size: 1 - eval_batch_size: 8 - seed: 0 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - 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: cosine - lr_scheduler_warmup_steps: 4 - training_steps: 20 ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.38.0.dev0 - Pytorch 2.1.1 - Datasets 2.16.1 - Tokenizers 0.15.1

laishram/bloom-560m-lora-merged-tagger

laishram

2024-02-27T12:31:26Z

77

0

transformers

[ "transformers", "safetensors", "bloom", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "8-bit", "bitsandbytes", "region:us" ]

text-generation

2024-02-27T12:29:47Z

--- 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]

Metin/gemma-2b-tr-inst

Metin

2024-02-27T12:30:32Z

155

4

transformers

[ "transformers", "pytorch", "gemma", "text-generation", "tr", "license:cc-by-nc-4.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-25T19:00:18Z

--- license: cc-by-nc-4.0 language: - tr --- # Model Card for Model ID  gemma-2b-tr fine-tuned with Turkish Instruction-Response pairs. ## Model Details ### Model Description  - **Language(s) (NLP):** Turkish, English - **License:** Creative Commons Attribution Non Commercial 4.0 - **Finetuned from model [optional]:** gemma-2b-tr (https://huggingface.co/Metin/gemma-2b-tr) ## Uses The model is designed for Turkish instruction following and question answering. Its current response quality is limited, likely due to the small instruction set and model size. It is not recommended for real-world applications at this stage. ## Restrictions Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms Please refer to the gemma use restrictions before start using the model. https://ai.google.dev/gemma/terms#3.2-use ## How to Get Started with the Model ```Python from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Metin/gemma-2b-tr-inst") model = AutoModelForCausalLM.from_pretrained("Metin/gemma-2b-tr-inst") system_prompt = "You are a helpful assistant. Always reply in Turkish." instruction = "Ankara hangi ülkenin başkentidir?" prompt = f"{system_prompt} [INST] {instruction} [/INST]" input_ids = tokenizer(prompt, return_tensors="pt") outputs = model.generate(**input_ids) print(tokenizer.decode(outputs[0])) ``` As it can be seen from the above example instructions should be framed within the following structure: SYSTEM_PROMPT [INST] \<Your instruction here\> [/INST] ## Training Details ### Training Data - Dataset: Turkish instructions from the Aya dataset (https://huggingface.co/datasets/CohereForAI/aya_dataset) - Dataset size: ~550K Token or ~5K instruction-response pair. ### Training Procedure #### Training Hyperparameters - **Adapter:** QLoRA - **Epochs:** 1 - **Context length:** 1024 - **LoRA Rank:** 32 - **LoRA Alpha:** 32 - **LoRA Dropout:** 0.05

zykrr/tinyllama

zykrr

2024-02-27T12:30:06Z

0

transformers

[ "transformers", "safetensors", "text-generation-inference", "unsloth", "llama", "trl", "en", "base_model:unsloth/tinyllama-bnb-4bit", "base_model:finetune:unsloth/tinyllama-bnb-4bit", "license:apache-2.0", "endpoints_compatible", "region:us" ]

null

2024-02-27T12:29:49Z

--- language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl base_model: unsloth/tinyllama-bnb-4bit --- # Uploaded model - **Developed by:** zykrr - **License:** apache-2.0 - **Finetuned from model :** unsloth/tinyllama-bnb-4bit This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

harikanaidu2k4/my-pet-dog

harikanaidu2k4

2024-02-27T12:30:04Z

2

0

diffusers

[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]

text-to-image

2024-02-27T12:26:08Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by harikanaidu2k4 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/harikanaidu2k4/my-pet-dog/resolve/main/sample_images/xzg3.jpg)

AlGM93/PPO-PyramidsRND

AlGM93

2024-02-27T12:25:04Z

15

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "Pyramids", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Pyramids", "region:us" ]

reinforcement-learning

2024-02-27T12:25:01Z

--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: AlGM93/PPO-PyramidsRND 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

fzzhang/mistral_gsm8k_s_tunes

fzzhang

2024-02-27T12:17:20Z

0

peft

[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:mistralai/Mistral-7B-v0.1", "base_model:adapter:mistralai/Mistral-7B-v0.1", "license:apache-2.0", "region:us" ]

null

2024-02-27T08:57:38Z

--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: mistralai/Mistral-7B-v0.1 model-index: - name: mistral_gsm8k_s_tunes results: [] ---  # mistral_gsm8k_s_tunes This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) 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: 4 - eval_batch_size: 8 - seed: 0 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results ### Framework versions - PEFT 0.7.2.dev0 - Transformers 4.37.0.dev0 - Pytorch 2.2.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.0

MichaelKim/train_results

MichaelKim

2024-02-27T12:17:19Z

1

0

peft

[ "peft", "tensorboard", "safetensors", "generated_from_trainer", "base_model:LDCC/LDCC-SOLAR-10.7B", "base_model:adapter:LDCC/LDCC-SOLAR-10.7B", "license:cc-by-nc-4.0", "region:us" ]

null

2024-02-27T07:25:00Z

--- license: cc-by-nc-4.0 library_name: peft tags: - generated_from_trainer base_model: LDCC/LDCC-SOLAR-10.7B model-index: - name: train_results results: [] ---  # train_results This model is a fine-tuned version of [LDCC/LDCC-SOLAR-10.7B](https://huggingface.co/LDCC/LDCC-SOLAR-10.7B) 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: 0.0001 - train_batch_size: 10 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2

AdrienB134/ColBERTv2.0-spanish-mmarcoES

AdrienB134

2024-02-27T12:17:06Z

40

2

transformers

[ "transformers", "safetensors", "bert", "colbert", "ColBERT", "es", "dataset:unicamp-dl/mmarco", "license:mit", "endpoints_compatible", "region:us" ]

null

2024-02-27T06:08:45Z

--- license: mit datasets: - unicamp-dl/mmarco language: - es tags: - colbert - ColBERT --- ## Training #### Details The model is initialized from the [ColBERTv1.0-bert-based-spanish-mmarcoES](https://huggingface.co/AdrienB134/ColBERTv1.0-bert-based-spanish-mmarcoES) checkpoint and trained using the ColBERTv2 style of training. It was trained on 2 Tesla T4 GPU with 16GBs of memory each with 20k warmup steps warmup using a batch size of 64 and the AdamW optimizer with a constant learning rate of 1e-05. Total training time was around 60 hours. #### Data The model is fine-tuned on the Spanish version of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset, a multi-lingual machine-translated version of the MS MARCO dataset. ## Evaluation The model is evaluated on the smaller development set of mMARCO-es, which consists of 6,980 queries for a corpus of 8.8M candidate passages. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k). | model | Vocab. | #Param. | Size | MRR@10 | R@50 | R@1000 | |:------------------------------------------------------------------------------------------------------------------------|:--------|--------:|------:|---------:|-------:|--------:| | **ColBERTv2.0-spanish-mmarcoES** | spanish | 110M | 440MB | **32.86** | **76.46** | **81.06** | | **ColBERTv1.0-bert-based-spanish-mmarcoES** | spanish | 110M | 440MB | 24.70 | 59,23 | 63.86 |

AdrienB134/ColBERTv1.0-bert-based-spanish-mmarcoES

AdrienB134

2024-02-27T12:16:34Z

38

1

transformers

[ "transformers", "safetensors", "bert", "colbert", "ColBERT", "es", "dataset:unicamp-dl/mmarco", "license:mit", "endpoints_compatible", "region:us" ]

null

2024-01-16T06:23:03Z

--- license: mit datasets: - unicamp-dl/mmarco language: - es tags: - colbert - ColBERT --- New spanish ColBERTv2 model available [here](https://huggingface.co/AdrienB134/ColBERTv2.0-spanish-mmarcoES) ## Training #### Details The model is initialized from the [bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) checkpoint and fine-tuned on 10M triples via pairwise softmax cross-entropy loss over the computed scores of the positive and negative passages associated to a query. It was trained on a single Tesla A100 GPU with 40GBs of memory during 200k steps with 10% of warmup steps using a batch size of 96 and the AdamW optimizer with a constant learning rate of 3e-06. Total training time was around 12 hours. #### Data The model is fine-tuned on the Spanish version of the [mMARCO](https://huggingface.co/datasets/unicamp-dl/mmarco) dataset, a multi-lingual machine-translated version of the MS MARCO dataset. The triples are sampled from the ~39.8M triples of [triples.train.small.tsv](https://microsoft.github.io/msmarco/Datasets.html#passage-ranking-dataset) ## Evaluation The model is evaluated on the smaller development set of mMARCO-es, which consists of 6,980 queries for a corpus of 8.8M candidate passages. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k). | model | Vocab. | #Param. | Size | MRR@10 | R@50 | R@1000 | |:------------------------------------------------------------------------------------------------------------------------|:--------|--------:|------:|---------:|-------:|--------:| | **ColBERTv1.0-bert-based-spanish-mmarcoES** | spanish | 110M | 440MB | 24.70 | 59,23 | 63.86 |

SumaGeethika/my-pet-dog

SumaGeethika

2024-02-27T12:09:16Z

1

0

diffusers

[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2024-02-27T12:02:11Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by SumaGeethika following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/SumaGeethika/my-pet-dog/resolve/main/sample_images/flower.jpg)

alinerodrigues/wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10

alinerodrigues

2024-02-27T12:03:25Z

15

0

transformers

[ "transformers", "pytorch", "wav2vec2", "automatic-speech-recognition", "generated_from_trainer", "license:apache-2.0", "endpoints_compatible", "region:us" ]

automatic-speech-recognition

2024-02-27T07:54:05Z

--- license: apache-2.0 tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10 results: [] ---  # wav2vec2-large-xlsr-mecita-coraa-portuguese-2-all-clean-10 This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1766 - Wer: 0.0913 - Cer: 0.0291 ## 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 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 21.8058 | 1.0 | 67 | 8.5869 | 0.9997 | 0.9859 | | 12.0549 | 2.0 | 134 | 5.9897 | 1.0 | 0.9719 | | 5.5651 | 3.0 | 201 | 3.0869 | 1.0 | 1.0 | | 5.5651 | 4.0 | 268 | 2.9406 | 1.0 | 1.0 | | 2.9913 | 5.0 | 335 | 2.9153 | 1.0 | 1.0 | | 2.9244 | 6.0 | 402 | 2.8824 | 1.0 | 1.0 | | 2.9244 | 7.0 | 469 | 2.8784 | 1.0 | 1.0 | | 2.8927 | 8.0 | 536 | 2.8759 | 1.0 | 1.0 | | 2.8858 | 9.0 | 603 | 2.8599 | 1.0 | 1.0 | | 2.8858 | 10.0 | 670 | 2.8328 | 1.0 | 1.0 | | 2.8512 | 11.0 | 737 | 2.5475 | 1.0 | 0.9997 | | 2.515 | 12.0 | 804 | 1.5878 | 1.0 | 0.5086 | | 2.515 | 13.0 | 871 | 0.7009 | 0.8586 | 0.1889 | | 1.3219 | 14.0 | 938 | 0.4050 | 0.2310 | 0.0598 | | 0.6694 | 15.0 | 1005 | 0.3246 | 0.1755 | 0.0487 | | 0.6694 | 16.0 | 1072 | 0.2909 | 0.1562 | 0.0439 | | 0.4976 | 17.0 | 1139 | 0.2679 | 0.1420 | 0.0415 | | 0.4105 | 18.0 | 1206 | 0.2519 | 0.1292 | 0.0384 | | 0.4105 | 19.0 | 1273 | 0.2421 | 0.1194 | 0.0366 | | 0.3865 | 20.0 | 1340 | 0.2325 | 0.1184 | 0.0354 | | 0.317 | 21.0 | 1407 | 0.2251 | 0.1096 | 0.0341 | | 0.317 | 22.0 | 1474 | 0.2195 | 0.1092 | 0.0339 | | 0.2925 | 23.0 | 1541 | 0.2106 | 0.1018 | 0.0320 | | 0.2721 | 24.0 | 1608 | 0.2072 | 0.0981 | 0.0317 | | 0.2721 | 25.0 | 1675 | 0.2106 | 0.0981 | 0.0317 | | 0.2531 | 26.0 | 1742 | 0.2046 | 0.1042 | 0.0330 | | 0.2634 | 27.0 | 1809 | 0.2071 | 0.1001 | 0.0321 | | 0.2634 | 28.0 | 1876 | 0.2028 | 0.1042 | 0.0328 | | 0.2391 | 29.0 | 1943 | 0.1973 | 0.0957 | 0.0308 | | 0.2232 | 30.0 | 2010 | 0.2017 | 0.0974 | 0.0313 | | 0.2232 | 31.0 | 2077 | 0.1987 | 0.0974 | 0.0308 | | 0.2111 | 32.0 | 2144 | 0.1898 | 0.0920 | 0.0298 | | 0.2121 | 33.0 | 2211 | 0.2006 | 0.0954 | 0.0314 | | 0.2121 | 34.0 | 2278 | 0.1934 | 0.0920 | 0.0303 | | 0.1868 | 35.0 | 2345 | 0.1921 | 0.0944 | 0.0306 | | 0.1869 | 36.0 | 2412 | 0.1884 | 0.0893 | 0.0292 | | 0.1869 | 37.0 | 2479 | 0.1903 | 0.0866 | 0.0292 | | 0.1935 | 38.0 | 2546 | 0.1867 | 0.0900 | 0.0294 | | 0.1957 | 39.0 | 2613 | 0.1874 | 0.0927 | 0.0298 | | 0.1957 | 40.0 | 2680 | 0.1845 | 0.0923 | 0.0297 | | 0.1772 | 41.0 | 2747 | 0.1862 | 0.0927 | 0.0298 | | 0.1748 | 42.0 | 2814 | 0.1894 | 0.0906 | 0.0297 | | 0.1748 | 43.0 | 2881 | 0.1816 | 0.0933 | 0.0301 | | 0.1498 | 44.0 | 2948 | 0.1795 | 0.0920 | 0.0296 | | 0.1606 | 45.0 | 3015 | 0.1867 | 0.0906 | 0.0299 | | 0.1606 | 46.0 | 3082 | 0.1866 | 0.0886 | 0.0294 | | 0.1599 | 47.0 | 3149 | 0.1883 | 0.0920 | 0.0300 | | 0.1487 | 48.0 | 3216 | 0.1802 | 0.0933 | 0.0298 | | 0.1487 | 49.0 | 3283 | 0.1808 | 0.0937 | 0.0298 | | 0.148 | 50.0 | 3350 | 0.1824 | 0.0916 | 0.0292 | | 0.1457 | 51.0 | 3417 | 0.1843 | 0.0893 | 0.0293 | | 0.1457 | 52.0 | 3484 | 0.1822 | 0.0923 | 0.0293 | | 0.1472 | 53.0 | 3551 | 0.1766 | 0.0913 | 0.0291 | | 0.1413 | 54.0 | 3618 | 0.1811 | 0.0933 | 0.0292 | | 0.1413 | 55.0 | 3685 | 0.1807 | 0.0906 | 0.0291 | | 0.1357 | 56.0 | 3752 | 0.1808 | 0.0879 | 0.0284 | | 0.1382 | 57.0 | 3819 | 0.1810 | 0.0933 | 0.0296 | | 0.1382 | 58.0 | 3886 | 0.1817 | 0.0910 | 0.0287 | | 0.1371 | 59.0 | 3953 | 0.1844 | 0.0889 | 0.0286 | | 0.141 | 60.0 | 4020 | 0.1883 | 0.0883 | 0.0284 | | 0.141 | 61.0 | 4087 | 0.1864 | 0.0930 | 0.0290 | | 0.147 | 62.0 | 4154 | 0.1861 | 0.0920 | 0.0289 | | 0.1316 | 63.0 | 4221 | 0.1863 | 0.0950 | 0.0296 | | 0.1316 | 64.0 | 4288 | 0.1909 | 0.0950 | 0.0302 | | 0.1329 | 65.0 | 4355 | 0.1880 | 0.0913 | 0.0291 | | 0.1326 | 66.0 | 4422 | 0.1851 | 0.0930 | 0.0291 | | 0.1326 | 67.0 | 4489 | 0.1842 | 0.0937 | 0.0292 | | 0.1345 | 68.0 | 4556 | 0.1856 | 0.0957 | 0.0297 | | 0.1371 | 69.0 | 4623 | 0.1840 | 0.0927 | 0.0291 | | 0.1371 | 70.0 | 4690 | 0.1845 | 0.0923 | 0.0292 | | 0.1325 | 71.0 | 4757 | 0.1806 | 0.0920 | 0.0288 | | 0.1264 | 72.0 | 4824 | 0.1810 | 0.0923 | 0.0289 | | 0.1264 | 73.0 | 4891 | 0.1836 | 0.0944 | 0.0295 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.2.1+cu121 - Datasets 2.17.0 - Tokenizers 0.13.3

adarsh12x/mistral_7b_samantha___

adarsh12x

2024-02-27T11:52:53Z

4

0

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "trl", "sft", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "8-bit", "bitsandbytes", "region:us" ]

text-generation

2024-02-26T10:42:07Z

--- library_name: transformers tags: - trl - sft --- # 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]

Syedhur786/mistral-finetuned-samsum

Syedhur786

2024-02-27T11:48:59Z

0

peft

[ "peft", "tensorboard", "safetensors", "trl", "sft", "generated_from_trainer", "base_model:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "base_model:adapter:TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", "license:apache-2.0", "region:us" ]

null

2024-02-27T10:39:03Z

--- license: apache-2.0 library_name: peft tags: - trl - sft - generated_from_trainer base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ model-index: - name: mistral-finetuned-samsum results: [] ---  # mistral-finetuned-samsum This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ) 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: 0.0002 - 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: cosine - training_steps: 250 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.8.2 - Transformers 4.39.0.dev0 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

casque/jacquard_pantyhose

casque

2024-02-27T11:37:19Z

0

null

[ "license:creativeml-openrail-m", "region:us" ]

null

2024-02-27T11:36:22Z

--- license: creativeml-openrail-m ---

neerajnarwal/Mistral-7B-Instruct-Question-Answering

neerajnarwal

2024-02-27T11:21:57Z

0

peft

[ "peft", "safetensors", "arxiv:1910.09700", "base_model:mistralai/Mistral-7B-Instruct-v0.2", "base_model:adapter:mistralai/Mistral-7B-Instruct-v0.2", "region:us" ]

null

2024-02-27T10:08:26Z

--- library_name: peft base_model: mistralai/Mistral-7B-Instruct-v0.2 --- # Model Card for Model ID  ## Model Details ### Model Description  - **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] ### Framework versions - PEFT 0.8.2

Solenya-ai/CLIP-ViT-B-16-DataComp.XL-s13B-b90K

Solenya-ai

2024-02-27T11:19:15Z

106

0

transformers

[ "transformers", "safetensors", "clip", "zero-shot-image-classification", "arxiv:1910.09700", "endpoints_compatible", "region:us" ]

zero-shot-image-classification

2024-02-27T11:17:31Z

--- 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]

svitse/model_1890_wie

svitse

2024-02-27T11:17:47Z

163

0

transformers

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

text-classification

2024-02-27T10:55:02Z

--- base_model: GroNLP/bert-base-dutch-cased tags: - generated_from_trainer model-index: - name: model_1890_wie results: [] ---  # model_1890_wie This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) 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-05 - train_batch_size: 16 - eval_batch_size: 20 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2

Di1/chatd5k

Di1

2024-02-27T11:16:29Z

1

0

peft

[ "peft", "region:us" ]

null

2024-02-27T11:16:26Z

--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.4.0

Kinjal123/content

Kinjal123

2024-02-27T11:16:04Z

114

0

transformers

[ "transformers", "safetensors", "opt", "text-generation", "trl", "sft", "generated_from_trainer", "base_model:facebook/opt-350m", "base_model:finetune:facebook/opt-350m", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T11:15:03Z

--- license: other base_model: facebook/opt-350m tags: - trl - sft - generated_from_trainer model-index: - name: content results: [] ---  # content This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.5972 ## 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: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.0419 | 0.2 | 50 | 3.8081 | | 3.816 | 0.4 | 100 | 3.7579 | | 3.78 | 0.6 | 150 | 3.7016 | | 3.753 | 0.8 | 200 | 3.6749 | | 3.6787 | 1.0 | 250 | 3.6132 | | 2.987 | 1.2 | 300 | 3.6374 | | 3.0092 | 1.4 | 350 | 3.6043 | | 3.0088 | 1.6 | 400 | 3.5676 | | 2.945 | 1.8 | 450 | 3.5404 | | 2.9204 | 2.0 | 500 | 3.5082 | | 2.2216 | 2.2 | 550 | 3.6194 | | 2.212 | 2.4 | 600 | 3.6117 | | 2.198 | 2.6 | 650 | 3.6019 | | 2.1787 | 2.8 | 700 | 3.5973 | | 2.1878 | 3.0 | 750 | 3.5972 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

oeg/RoBERTa-Repository-Proposal

oeg

2024-02-27T11:08:20Z

163

0

transformers

[ "transformers", "safetensors", "roberta", "text-classification", "English", "RoBERTa-base", "Text Classification", "en", "license:cc-by-nc-4.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-20T14:14:05Z

--- license: cc-by-nc-4.0 language: - en tags: - English - RoBERTa-base - Text Classification pipeline_tag: text-classification --- # RoBERTa base Fine-Tuned for Proposal Sentence Classification ## Overview - **Language**: English - **Model Name**: oeg/RoBERTa_Repository_Proposal ## Description This model is a fine-tuned RoBERTa-base model trained to classify sentences into two classes: proposal and non-proposal sentences. The training data includes sentences proposing a software or data repository. The model is trained to recognize and classify these sentences accurately. ## How to use To use this model in Python: ```python from transformers import RobertaForSequenceClassification, RobertaTokenizer import torch tokenizer = RobertaTokenizer.from_pretrained("roberta-base") model = RobertaForSequenceClassification.from_pretrained("oeg/RoBERTa-Repository-Proposal") sentence = "Your input sentence here." inputs = tokenizer(sentence, return_tensors="pt") outputs = model(**inputs) probabilities = torch.nn.functional.softmax(outputs.logits, dim=1)

aslez123/segmentation-train

aslez123

2024-02-27T11:04:50Z

34

0

transformers

[ "transformers", "tensorboard", "safetensors", "segformer", "generated_from_trainer", "base_model:nvidia/mit-b0", "base_model:finetune:nvidia/mit-b0", "license:other", "endpoints_compatible", "region:us" ]

null

2024-02-27T10:31:47Z

--- license: other base_model: nvidia/mit-b0 tags: - generated_from_trainer model-index: - name: segmentation-train results: [] ---  # segmentation-train This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) 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: 6e-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: 5 ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

peldrak/segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline

peldrak

2024-02-27T11:04:05Z

188

0

transformers

[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:peldrak/segformer-b3-ade-512-512-finetuned-coastTrain", "base_model:finetune:peldrak/segformer-b3-ade-512-512-finetuned-coastTrain", "license:other", "endpoints_compatible", "region:us" ]

image-segmentation

2024-02-27T10:12:59Z

--- license: other base_model: peldrak/segformer-b3-ade-512-512-finetuned-coastTrain tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline results: [] ---  # segformer-b3-ade-512-512-finetuned-coastTrain-grCoastline This model is a fine-tuned version of [peldrak/segformer-b3-ade-512-512-finetuned-coastTrain](https://huggingface.co/peldrak/segformer-b3-ade-512-512-finetuned-coastTrain) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.2531 - Mean Iou: 0.7677 - Mean Accuracy: 0.8502 - Overall Accuracy: 0.9340 - Accuracy Water: 0.9810 - Accuracy Whitewater: 0.5654 - Accuracy Sediment: 0.8995 - Accuracy Other Natural Terrain: 0.7891 - Accuracy Vegetation: 0.8969 - Accuracy Development: 0.8221 - Accuracy Unknown: 0.9974 - Iou Water: 0.9535 - Iou Whitewater: 0.4217 - Iou Sediment: 0.8288 - Iou Other Natural Terrain: 0.6339 - Iou Vegetation: 0.8151 - Iou Development: 0.7244 - Iou Unknown: 0.9964 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Water | Accuracy Whitewater | Accuracy Sediment | Accuracy Other Natural Terrain | Accuracy Vegetation | Accuracy Development | Accuracy Unknown | Iou Water | Iou Whitewater | Iou Sediment | Iou Other Natural Terrain | Iou Vegetation | Iou Development | Iou Unknown | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:| | 1.2485 | 0.24 | 20 | 0.4622 | 0.5668 | 0.6676 | 0.8536 | 0.9523 | 0.2722 | 0.9426 | 0.0 | 0.9170 | 0.5995 | 0.9897 | 0.9004 | 0.2295 | 0.6418 | 0.0 | 0.6785 | 0.5280 | 0.9890 | | 0.4894 | 0.49 | 40 | 0.3645 | 0.6103 | 0.7022 | 0.8775 | 0.9738 | 0.2414 | 0.9207 | 0.1627 | 0.9260 | 0.6974 | 0.9932 | 0.9318 | 0.2117 | 0.6742 | 0.1589 | 0.7242 | 0.5807 | 0.9904 | | 0.4931 | 0.73 | 60 | 0.3257 | 0.6374 | 0.7168 | 0.8940 | 0.9790 | 0.1616 | 0.8723 | 0.2837 | 0.9522 | 0.7731 | 0.9955 | 0.9359 | 0.1529 | 0.7241 | 0.2724 | 0.7487 | 0.6360 | 0.9920 | | 0.1766 | 0.98 | 80 | 0.2769 | 0.6970 | 0.7755 | 0.9123 | 0.9726 | 0.3993 | 0.9157 | 0.6302 | 0.9080 | 0.6049 | 0.9976 | 0.9443 | 0.3230 | 0.7710 | 0.5134 | 0.7866 | 0.5485 | 0.9921 | | 0.6156 | 1.22 | 100 | 0.2895 | 0.6691 | 0.7372 | 0.9115 | 0.9696 | 0.1418 | 0.9271 | 0.5343 | 0.9293 | 0.6601 | 0.9981 | 0.9435 | 0.1371 | 0.7252 | 0.4855 | 0.7931 | 0.6066 | 0.9929 | | 0.4116 | 1.46 | 120 | 0.2715 | 0.7026 | 0.7775 | 0.9135 | 0.9521 | 0.2680 | 0.9245 | 0.6565 | 0.8937 | 0.7554 | 0.9922 | 0.9225 | 0.2401 | 0.7913 | 0.5413 | 0.7691 | 0.6637 | 0.9905 | | 0.261 | 1.71 | 140 | 0.2459 | 0.7193 | 0.8036 | 0.9186 | 0.9770 | 0.3963 | 0.8738 | 0.6637 | 0.8956 | 0.8211 | 0.9973 | 0.9387 | 0.3074 | 0.7904 | 0.5513 | 0.7829 | 0.6708 | 0.9933 | | 0.2603 | 1.95 | 160 | 0.2538 | 0.7189 | 0.7987 | 0.9159 | 0.9752 | 0.3829 | 0.9032 | 0.7231 | 0.8610 | 0.7478 | 0.9975 | 0.9288 | 0.3082 | 0.7996 | 0.5457 | 0.7713 | 0.6843 | 0.9943 | | 0.3266 | 2.2 | 180 | 0.2468 | 0.7232 | 0.8227 | 0.9118 | 0.9734 | 0.4478 | 0.9127 | 0.8202 | 0.7856 | 0.8226 | 0.9967 | 0.9337 | 0.3322 | 0.8097 | 0.5550 | 0.7399 | 0.6988 | 0.9936 | | 0.1754 | 2.44 | 200 | 0.2850 | 0.7269 | 0.8031 | 0.9209 | 0.9764 | 0.3942 | 0.8998 | 0.6822 | 0.8980 | 0.7752 | 0.9957 | 0.9300 | 0.3147 | 0.8116 | 0.5579 | 0.7858 | 0.6944 | 0.9937 | | 0.1391 | 2.68 | 220 | 0.2787 | 0.7316 | 0.8041 | 0.9264 | 0.9678 | 0.4164 | 0.9050 | 0.6179 | 0.9497 | 0.7737 | 0.9982 | 0.9474 | 0.3268 | 0.8058 | 0.5714 | 0.8035 | 0.6720 | 0.9946 | | 0.1294 | 2.93 | 240 | 0.2869 | 0.7176 | 0.8170 | 0.9100 | 0.9752 | 0.4576 | 0.9232 | 0.9012 | 0.7608 | 0.7034 | 0.9976 | 0.9455 | 0.3430 | 0.7795 | 0.5795 | 0.7315 | 0.6496 | 0.9948 | | 0.3478 | 3.17 | 260 | 0.2799 | 0.7348 | 0.8127 | 0.9238 | 0.9792 | 0.4352 | 0.8693 | 0.6888 | 0.9183 | 0.8048 | 0.9935 | 0.9461 | 0.3369 | 0.8102 | 0.5753 | 0.7904 | 0.6923 | 0.9926 | | 0.1053 | 3.41 | 280 | 0.2963 | 0.7227 | 0.7986 | 0.9234 | 0.9837 | 0.4045 | 0.8366 | 0.5931 | 0.9610 | 0.8150 | 0.9966 | 0.9409 | 0.3144 | 0.7928 | 0.5578 | 0.8011 | 0.6577 | 0.9939 | | 0.3786 | 3.66 | 300 | 0.2416 | 0.7282 | 0.8228 | 0.9137 | 0.9689 | 0.4874 | 0.9182 | 0.8059 | 0.8081 | 0.7729 | 0.9984 | 0.9455 | 0.3525 | 0.8143 | 0.5534 | 0.7431 | 0.6944 | 0.9937 | | 0.3046 | 3.9 | 320 | 0.2374 | 0.7406 | 0.8148 | 0.9279 | 0.9820 | 0.3912 | 0.8961 | 0.7267 | 0.8996 | 0.8111 | 0.9966 | 0.9438 | 0.3180 | 0.8193 | 0.5968 | 0.8014 | 0.7111 | 0.9940 | | 0.1098 | 4.15 | 340 | 0.2479 | 0.7278 | 0.8012 | 0.9258 | 0.9816 | 0.2957 | 0.8885 | 0.7045 | 0.8956 | 0.8445 | 0.9977 | 0.9488 | 0.2557 | 0.8194 | 0.5799 | 0.7923 | 0.7036 | 0.9948 | | 0.1654 | 4.39 | 360 | 0.2757 | 0.7484 | 0.8304 | 0.9290 | 0.9751 | 0.4714 | 0.8718 | 0.7298 | 0.9119 | 0.8562 | 0.9965 | 0.9508 | 0.3615 | 0.8222 | 0.6089 | 0.8021 | 0.6989 | 0.9944 | | 0.1079 | 4.63 | 380 | 0.2821 | 0.7171 | 0.8052 | 0.9095 | 0.9789 | 0.3882 | 0.9159 | 0.8147 | 0.7865 | 0.7563 | 0.9959 | 0.9358 | 0.3245 | 0.7857 | 0.5545 | 0.7318 | 0.6930 | 0.9942 | | 0.1849 | 4.88 | 400 | 0.2637 | 0.7398 | 0.8191 | 0.9250 | 0.9773 | 0.4225 | 0.8793 | 0.6972 | 0.9008 | 0.8600 | 0.9967 | 0.9472 | 0.3367 | 0.8212 | 0.5715 | 0.7886 | 0.7189 | 0.9946 | | 0.1643 | 5.12 | 420 | 0.3350 | 0.7221 | 0.7861 | 0.9244 | 0.9782 | 0.3296 | 0.9235 | 0.5713 | 0.9536 | 0.7526 | 0.9939 | 0.9458 | 0.2901 | 0.7973 | 0.5429 | 0.8014 | 0.6843 | 0.9927 | | 0.1595 | 5.37 | 440 | 0.2582 | 0.7366 | 0.8255 | 0.9196 | 0.9769 | 0.4560 | 0.8771 | 0.7617 | 0.8518 | 0.8582 | 0.9965 | 0.9464 | 0.3440 | 0.8231 | 0.5601 | 0.7647 | 0.7237 | 0.9946 | | 0.3171 | 5.61 | 460 | 0.2579 | 0.7433 | 0.8317 | 0.9261 | 0.9681 | 0.5031 | 0.9291 | 0.7243 | 0.8871 | 0.8137 | 0.9965 | 0.9506 | 0.3517 | 0.8177 | 0.5841 | 0.7930 | 0.7112 | 0.9950 | | 0.2955 | 5.85 | 480 | 0.2975 | 0.7288 | 0.8072 | 0.9226 | 0.9758 | 0.4648 | 0.9149 | 0.6695 | 0.9146 | 0.7139 | 0.9967 | 0.9498 | 0.3452 | 0.7954 | 0.5683 | 0.7901 | 0.6579 | 0.9948 | | 0.0857 | 6.1 | 500 | 0.2707 | 0.7307 | 0.8236 | 0.9194 | 0.9792 | 0.5026 | 0.9181 | 0.7281 | 0.8591 | 0.7821 | 0.9957 | 0.9512 | 0.3523 | 0.8017 | 0.5624 | 0.7724 | 0.6806 | 0.9944 | | 0.109 | 6.34 | 520 | 0.2674 | 0.7488 | 0.8316 | 0.9312 | 0.9738 | 0.5295 | 0.9087 | 0.6734 | 0.9363 | 0.8021 | 0.9977 | 0.9524 | 0.3633 | 0.8258 | 0.5984 | 0.8127 | 0.6945 | 0.9948 | | 0.0593 | 6.59 | 540 | 0.2806 | 0.7376 | 0.8273 | 0.9204 | 0.9756 | 0.4729 | 0.9084 | 0.8021 | 0.8373 | 0.7988 | 0.9962 | 0.9491 | 0.3463 | 0.8215 | 0.5723 | 0.7676 | 0.7121 | 0.9947 | | 0.099 | 6.83 | 560 | 0.2874 | 0.7421 | 0.8331 | 0.9237 | 0.9626 | 0.4619 | 0.9334 | 0.7321 | 0.8586 | 0.8852 | 0.9982 | 0.9486 | 0.3640 | 0.8238 | 0.5798 | 0.7802 | 0.7024 | 0.9957 | | 0.0665 | 7.07 | 580 | 0.2642 | 0.7462 | 0.8177 | 0.9291 | 0.9780 | 0.5176 | 0.8784 | 0.6685 | 0.9544 | 0.7287 | 0.9983 | 0.9493 | 0.3841 | 0.8119 | 0.5980 | 0.8057 | 0.6788 | 0.9953 | | 0.1285 | 7.32 | 600 | 0.2347 | 0.7495 | 0.8500 | 0.9236 | 0.9799 | 0.5332 | 0.8905 | 0.8549 | 0.8181 | 0.8766 | 0.9968 | 0.9483 | 0.3906 | 0.8197 | 0.6088 | 0.7745 | 0.7102 | 0.9946 | | 0.1299 | 7.56 | 620 | 0.2630 | 0.7506 | 0.8232 | 0.9311 | 0.9751 | 0.4683 | 0.9292 | 0.6923 | 0.9228 | 0.7773 | 0.9976 | 0.9489 | 0.3754 | 0.8070 | 0.6084 | 0.8172 | 0.7028 | 0.9948 | | 0.0504 | 7.8 | 640 | 0.2964 | 0.7358 | 0.8238 | 0.9172 | 0.9790 | 0.4852 | 0.9113 | 0.7586 | 0.8335 | 0.8016 | 0.9976 | 0.9481 | 0.3776 | 0.8139 | 0.5465 | 0.7591 | 0.7105 | 0.9953 | | 0.0795 | 8.05 | 660 | 0.2654 | 0.7443 | 0.8427 | 0.9198 | 0.9764 | 0.5517 | 0.9103 | 0.8286 | 0.8150 | 0.8193 | 0.9978 | 0.9506 | 0.3918 | 0.8173 | 0.5768 | 0.7619 | 0.7163 | 0.9953 | | 0.0614 | 8.29 | 680 | 0.2904 | 0.7452 | 0.8165 | 0.9303 | 0.9763 | 0.4578 | 0.8990 | 0.6315 | 0.9536 | 0.8003 | 0.9973 | 0.9496 | 0.3518 | 0.8172 | 0.5805 | 0.8118 | 0.7105 | 0.9951 | | 0.1476 | 8.54 | 700 | 0.2814 | 0.7498 | 0.8324 | 0.9276 | 0.9785 | 0.5138 | 0.9093 | 0.7335 | 0.8910 | 0.8028 | 0.9979 | 0.9489 | 0.3821 | 0.8168 | 0.5909 | 0.7981 | 0.7165 | 0.9956 | | 0.0669 | 8.78 | 720 | 0.2774 | 0.7483 | 0.8374 | 0.9250 | 0.9741 | 0.5476 | 0.9217 | 0.7477 | 0.8710 | 0.8020 | 0.9980 | 0.9313 | 0.3931 | 0.8220 | 0.5795 | 0.7975 | 0.7196 | 0.9953 | | 0.142 | 9.02 | 740 | 0.2362 | 0.7624 | 0.8555 | 0.9327 | 0.9784 | 0.6280 | 0.8959 | 0.7341 | 0.9111 | 0.8425 | 0.9983 | 0.9516 | 0.4124 | 0.8211 | 0.6182 | 0.8158 | 0.7224 | 0.9952 | | 0.1258 | 9.27 | 760 | 0.2666 | 0.7597 | 0.8357 | 0.9329 | 0.9762 | 0.4810 | 0.9161 | 0.7439 | 0.9043 | 0.8311 | 0.9975 | 0.9554 | 0.3793 | 0.8262 | 0.6165 | 0.8111 | 0.7338 | 0.9954 | | 0.1541 | 9.51 | 780 | 0.2484 | 0.7630 | 0.8423 | 0.9334 | 0.9797 | 0.5260 | 0.9084 | 0.7548 | 0.9043 | 0.8259 | 0.9973 | 0.9543 | 0.3991 | 0.8244 | 0.6228 | 0.8147 | 0.7307 | 0.9953 | | 0.1689 | 9.76 | 800 | 0.2151 | 0.7710 | 0.8619 | 0.9341 | 0.9747 | 0.6199 | 0.9143 | 0.8381 | 0.8751 | 0.8127 | 0.9985 | 0.9553 | 0.4257 | 0.8333 | 0.6421 | 0.8117 | 0.7341 | 0.9952 | | 0.0931 | 10.0 | 820 | 0.2422 | 0.7506 | 0.8239 | 0.9325 | 0.9783 | 0.4062 | 0.9162 | 0.7139 | 0.9116 | 0.8443 | 0.9969 | 0.9528 | 0.3324 | 0.8236 | 0.6103 | 0.8137 | 0.7265 | 0.9953 | | 0.1109 | 10.24 | 840 | 0.2336 | 0.7522 | 0.8271 | 0.9321 | 0.9774 | 0.4327 | 0.9191 | 0.7334 | 0.9027 | 0.8263 | 0.9981 | 0.9530 | 0.3442 | 0.8194 | 0.6136 | 0.8110 | 0.7283 | 0.9960 | | 0.0561 | 10.49 | 860 | 0.2991 | 0.7572 | 0.8445 | 0.9284 | 0.9743 | 0.5846 | 0.9094 | 0.7471 | 0.8933 | 0.8066 | 0.9966 | 0.9514 | 0.4134 | 0.8200 | 0.5952 | 0.7985 | 0.7261 | 0.9955 | | 0.0701 | 10.73 | 880 | 0.2647 | 0.7554 | 0.8481 | 0.9286 | 0.9774 | 0.6203 | 0.9098 | 0.7382 | 0.8929 | 0.7991 | 0.9990 | 0.9534 | 0.4082 | 0.8163 | 0.5967 | 0.8006 | 0.7175 | 0.9951 | | 0.1528 | 10.98 | 900 | 0.2988 | 0.7626 | 0.8573 | 0.9310 | 0.9713 | 0.6322 | 0.9123 | 0.7464 | 0.8980 | 0.8442 | 0.9969 | 0.9548 | 0.4138 | 0.8368 | 0.6036 | 0.8022 | 0.7317 | 0.9956 | | 0.0514 | 11.22 | 920 | 0.2537 | 0.7528 | 0.8314 | 0.9302 | 0.9749 | 0.4371 | 0.9270 | 0.8595 | 0.8548 | 0.7694 | 0.9970 | 0.9527 | 0.3550 | 0.8248 | 0.6354 | 0.8004 | 0.7063 | 0.9951 | | 0.0959 | 11.46 | 940 | 0.2897 | 0.7458 | 0.8233 | 0.9279 | 0.9835 | 0.4569 | 0.8963 | 0.7962 | 0.8808 | 0.7523 | 0.9974 | 0.9499 | 0.3569 | 0.8096 | 0.6191 | 0.7974 | 0.6918 | 0.9958 | | 0.1997 | 11.71 | 960 | 0.3142 | 0.7512 | 0.8251 | 0.9295 | 0.9745 | 0.5071 | 0.9290 | 0.6819 | 0.9251 | 0.7615 | 0.9964 | 0.9537 | 0.3946 | 0.8181 | 0.5902 | 0.8052 | 0.7017 | 0.9953 | | 0.0724 | 11.95 | 980 | 0.2794 | 0.7525 | 0.8318 | 0.9290 | 0.9822 | 0.4696 | 0.9038 | 0.7310 | 0.8897 | 0.8489 | 0.9973 | 0.9557 | 0.3727 | 0.8276 | 0.5890 | 0.7970 | 0.7299 | 0.9957 | | 0.0668 | 12.2 | 1000 | 0.2911 | 0.7447 | 0.8175 | 0.9321 | 0.9844 | 0.3514 | 0.9008 | 0.7032 | 0.9105 | 0.8749 | 0.9970 | 0.9500 | 0.2946 | 0.8281 | 0.6032 | 0.8126 | 0.7290 | 0.9953 | | 0.0574 | 12.44 | 1020 | 0.2565 | 0.7619 | 0.8407 | 0.9330 | 0.9797 | 0.5386 | 0.9173 | 0.7298 | 0.9096 | 0.8120 | 0.9982 | 0.9545 | 0.3984 | 0.8306 | 0.6073 | 0.8131 | 0.7338 | 0.9956 | | 0.0696 | 12.68 | 1040 | 0.2657 | 0.7595 | 0.8366 | 0.9339 | 0.9808 | 0.4966 | 0.9101 | 0.7057 | 0.9197 | 0.8458 | 0.9979 | 0.9520 | 0.3767 | 0.8308 | 0.6096 | 0.8173 | 0.7345 | 0.9956 | | 0.3274 | 12.93 | 1060 | 0.2586 | 0.7465 | 0.8222 | 0.9297 | 0.9793 | 0.3965 | 0.9265 | 0.7214 | 0.8877 | 0.8457 | 0.9983 | 0.9539 | 0.3307 | 0.8268 | 0.5935 | 0.8017 | 0.7235 | 0.9953 | | 0.0817 | 13.17 | 1080 | 0.2783 | 0.7569 | 0.8496 | 0.9265 | 0.9772 | 0.5303 | 0.9224 | 0.8566 | 0.8235 | 0.8395 | 0.9975 | 0.9548 | 0.4030 | 0.8286 | 0.6126 | 0.7783 | 0.7250 | 0.9963 | | 0.0787 | 13.41 | 1100 | 0.2517 | 0.7489 | 0.8218 | 0.9294 | 0.9802 | 0.4487 | 0.9232 | 0.7094 | 0.9058 | 0.7883 | 0.9968 | 0.9527 | 0.3654 | 0.8222 | 0.5939 | 0.8027 | 0.7105 | 0.9951 | | 0.1024 | 13.66 | 1120 | 0.2590 | 0.7569 | 0.8290 | 0.9327 | 0.9812 | 0.4873 | 0.9080 | 0.7041 | 0.9259 | 0.7986 | 0.9977 | 0.9543 | 0.3833 | 0.8266 | 0.6094 | 0.8118 | 0.7171 | 0.9960 | | 0.0888 | 13.9 | 1140 | 0.2647 | 0.7489 | 0.8352 | 0.9228 | 0.9812 | 0.5251 | 0.9169 | 0.7856 | 0.8447 | 0.7955 | 0.9973 | 0.9491 | 0.4024 | 0.8276 | 0.5748 | 0.7738 | 0.7184 | 0.9958 | | 0.0946 | 14.15 | 1160 | 0.2453 | 0.7571 | 0.8370 | 0.9298 | 0.9823 | 0.5318 | 0.9002 | 0.7619 | 0.8942 | 0.7913 | 0.9973 | 0.9531 | 0.4046 | 0.8240 | 0.6086 | 0.8008 | 0.7125 | 0.9960 | | 0.0529 | 14.39 | 1180 | 0.2514 | 0.7596 | 0.8460 | 0.9298 | 0.9808 | 0.5804 | 0.9014 | 0.7354 | 0.8979 | 0.8289 | 0.9970 | 0.9559 | 0.4197 | 0.8307 | 0.5978 | 0.7990 | 0.7183 | 0.9958 | | 0.0495 | 14.63 | 1200 | 0.2323 | 0.7634 | 0.8491 | 0.9324 | 0.9790 | 0.5831 | 0.9267 | 0.7848 | 0.8862 | 0.7861 | 0.9977 | 0.9550 | 0.4175 | 0.8280 | 0.6217 | 0.8103 | 0.7151 | 0.9962 | | 0.0401 | 14.88 | 1220 | 0.2248 | 0.7677 | 0.8467 | 0.9366 | 0.9796 | 0.5337 | 0.9256 | 0.8125 | 0.8943 | 0.7834 | 0.9981 | 0.9524 | 0.4037 | 0.8250 | 0.6561 | 0.8282 | 0.7126 | 0.9961 | | 0.053 | 15.12 | 1240 | 0.2280 | 0.7701 | 0.8541 | 0.9362 | 0.9805 | 0.5488 | 0.9155 | 0.8259 | 0.8830 | 0.8280 | 0.9974 | 0.9542 | 0.4107 | 0.8259 | 0.6577 | 0.8224 | 0.7233 | 0.9961 | | 0.0764 | 15.37 | 1260 | 0.2350 | 0.7741 | 0.8577 | 0.9370 | 0.9777 | 0.5690 | 0.9145 | 0.8514 | 0.8825 | 0.8119 | 0.9972 | 0.9574 | 0.4265 | 0.8296 | 0.6666 | 0.8216 | 0.7212 | 0.9962 | | 0.0568 | 15.61 | 1280 | 0.2420 | 0.7629 | 0.8407 | 0.9343 | 0.9813 | 0.5093 | 0.9057 | 0.8360 | 0.8871 | 0.7680 | 0.9973 | 0.9560 | 0.3937 | 0.8246 | 0.6536 | 0.8142 | 0.7025 | 0.9960 | | 0.1199 | 15.85 | 1300 | 0.2545 | 0.7620 | 0.8463 | 0.9321 | 0.9752 | 0.5904 | 0.9180 | 0.7196 | 0.9135 | 0.8090 | 0.9981 | 0.9557 | 0.4209 | 0.8276 | 0.6064 | 0.8098 | 0.7171 | 0.9964 | | 0.7094 | 16.1 | 1320 | 0.2446 | 0.7584 | 0.8409 | 0.9314 | 0.9790 | 0.5580 | 0.9151 | 0.7301 | 0.9070 | 0.7993 | 0.9979 | 0.9542 | 0.4042 | 0.8218 | 0.6091 | 0.8088 | 0.7145 | 0.9963 | | 0.0321 | 16.34 | 1340 | 0.2652 | 0.7585 | 0.8329 | 0.9340 | 0.9787 | 0.5076 | 0.9089 | 0.6924 | 0.9365 | 0.8091 | 0.9974 | 0.9538 | 0.3925 | 0.8214 | 0.6173 | 0.8211 | 0.7075 | 0.9962 | | 0.1328 | 16.59 | 1360 | 0.2322 | 0.7587 | 0.8403 | 0.9327 | 0.9805 | 0.5174 | 0.9092 | 0.7077 | 0.9123 | 0.8570 | 0.9977 | 0.9558 | 0.3966 | 0.8276 | 0.6071 | 0.8146 | 0.7132 | 0.9959 | | 0.0637 | 16.83 | 1380 | 0.2331 | 0.7615 | 0.8441 | 0.9322 | 0.9831 | 0.5529 | 0.8983 | 0.7412 | 0.9048 | 0.8305 | 0.9976 | 0.9530 | 0.4111 | 0.8243 | 0.6155 | 0.8104 | 0.7201 | 0.9961 | | 0.3028 | 17.07 | 1400 | 0.2446 | 0.7572 | 0.8367 | 0.9312 | 0.9804 | 0.5135 | 0.9061 | 0.7279 | 0.9044 | 0.8263 | 0.9981 | 0.9548 | 0.3970 | 0.8212 | 0.6048 | 0.8084 | 0.7181 | 0.9962 | | 0.0479 | 17.32 | 1420 | 0.2556 | 0.7609 | 0.8506 | 0.9295 | 0.9778 | 0.6127 | 0.9095 | 0.7802 | 0.8835 | 0.7929 | 0.9974 | 0.9556 | 0.4318 | 0.8241 | 0.6105 | 0.7988 | 0.7095 | 0.9963 | | 0.0645 | 17.56 | 1440 | 0.2530 | 0.7587 | 0.8480 | 0.9283 | 0.9769 | 0.5933 | 0.9080 | 0.7729 | 0.8775 | 0.8091 | 0.9985 | 0.9543 | 0.4244 | 0.8268 | 0.5993 | 0.7945 | 0.7155 | 0.9962 | | 0.0513 | 17.8 | 1460 | 0.2451 | 0.7598 | 0.8467 | 0.9306 | 0.9794 | 0.5549 | 0.9064 | 0.7567 | 0.8863 | 0.8448 | 0.9985 | 0.9547 | 0.4093 | 0.8259 | 0.6076 | 0.8039 | 0.7214 | 0.9961 | | 0.0387 | 18.05 | 1480 | 0.2374 | 0.7625 | 0.8446 | 0.9344 | 0.9810 | 0.5392 | 0.9007 | 0.7115 | 0.9214 | 0.8609 | 0.9975 | 0.9539 | 0.4025 | 0.8249 | 0.6196 | 0.8218 | 0.7193 | 0.9958 | | 0.0903 | 18.29 | 1500 | 0.2353 | 0.7662 | 0.8468 | 0.9351 | 0.9820 | 0.5342 | 0.9097 | 0.8100 | 0.8918 | 0.8030 | 0.9971 | 0.9549 | 0.4053 | 0.8261 | 0.6487 | 0.8190 | 0.7130 | 0.9961 | | 0.0832 | 18.54 | 1520 | 0.2372 | 0.7677 | 0.8428 | 0.9375 | 0.9807 | 0.5172 | 0.9098 | 0.7757 | 0.9184 | 0.8007 | 0.9970 | 0.9563 | 0.3981 | 0.8264 | 0.6574 | 0.8284 | 0.7113 | 0.9961 | | 0.0601 | 18.78 | 1540 | 0.2473 | 0.7741 | 0.8607 | 0.9366 | 0.9771 | 0.6169 | 0.9135 | 0.8532 | 0.8866 | 0.7798 | 0.9976 | 0.9559 | 0.4365 | 0.8295 | 0.6630 | 0.8221 | 0.7154 | 0.9965 | | 0.0516 | 19.02 | 1560 | 0.2363 | 0.7731 | 0.8556 | 0.9369 | 0.9792 | 0.5591 | 0.9075 | 0.8329 | 0.8883 | 0.8243 | 0.9981 | 0.9563 | 0.4189 | 0.8305 | 0.6623 | 0.8215 | 0.7256 | 0.9964 | | 0.0782 | 19.27 | 1580 | 0.2454 | 0.7651 | 0.8426 | 0.9341 | 0.9813 | 0.5266 | 0.9008 | 0.7847 | 0.9005 | 0.8059 | 0.9981 | 0.9543 | 0.4057 | 0.8280 | 0.6356 | 0.8141 | 0.7217 | 0.9961 | | 0.0221 | 19.51 | 1600 | 0.2540 | 0.7660 | 0.8474 | 0.9333 | 0.9785 | 0.5946 | 0.9085 | 0.7579 | 0.9117 | 0.7828 | 0.9976 | 0.9543 | 0.4320 | 0.8265 | 0.6259 | 0.8134 | 0.7131 | 0.9964 | | 0.0283 | 19.76 | 1620 | 0.2623 | 0.7662 | 0.8588 | 0.9320 | 0.9750 | 0.6488 | 0.9141 | 0.7503 | 0.8988 | 0.8266 | 0.9981 | 0.9549 | 0.4395 | 0.8271 | 0.6123 | 0.8092 | 0.7240 | 0.9964 | | 0.1029 | 20.0 | 1640 | 0.2747 | 0.7633 | 0.8522 | 0.9299 | 0.9767 | 0.6031 | 0.9118 | 0.7738 | 0.8809 | 0.8213 | 0.9981 | 0.9539 | 0.4336 | 0.8317 | 0.6053 | 0.7991 | 0.7235 | 0.9962 | | 0.0731 | 20.24 | 1660 | 0.2650 | 0.7621 | 0.8529 | 0.9294 | 0.9794 | 0.6019 | 0.9106 | 0.7555 | 0.8790 | 0.8453 | 0.9983 | 0.9552 | 0.4310 | 0.8288 | 0.5977 | 0.7971 | 0.7288 | 0.9963 | | 0.2587 | 20.49 | 1680 | 0.2767 | 0.7602 | 0.8430 | 0.9311 | 0.9794 | 0.5600 | 0.9158 | 0.7217 | 0.9023 | 0.8234 | 0.9985 | 0.9552 | 0.4160 | 0.8239 | 0.5994 | 0.8073 | 0.7237 | 0.9961 | | 0.1071 | 20.73 | 1700 | 0.2826 | 0.7607 | 0.8443 | 0.9311 | 0.9805 | 0.5820 | 0.9125 | 0.7122 | 0.9091 | 0.8156 | 0.9980 | 0.9548 | 0.4239 | 0.8225 | 0.5976 | 0.8080 | 0.7220 | 0.9963 | | 0.0323 | 20.98 | 1720 | 0.2620 | 0.7621 | 0.8522 | 0.9293 | 0.9801 | 0.6139 | 0.9065 | 0.7633 | 0.8829 | 0.8215 | 0.9975 | 0.9551 | 0.4342 | 0.8296 | 0.5996 | 0.7968 | 0.7231 | 0.9963 | | 0.1072 | 21.22 | 1740 | 0.2592 | 0.7614 | 0.8426 | 0.9315 | 0.9824 | 0.5483 | 0.9094 | 0.7402 | 0.8997 | 0.8211 | 0.9974 | 0.9546 | 0.4149 | 0.8257 | 0.6074 | 0.8078 | 0.7230 | 0.9961 | | 0.0732 | 21.46 | 1760 | 0.2598 | 0.7654 | 0.8497 | 0.9327 | 0.9795 | 0.5819 | 0.9130 | 0.7528 | 0.8994 | 0.8240 | 0.9976 | 0.9557 | 0.4265 | 0.8275 | 0.6163 | 0.8106 | 0.7248 | 0.9963 | | 0.0603 | 21.71 | 1780 | 0.2581 | 0.7650 | 0.8503 | 0.9320 | 0.9790 | 0.5874 | 0.9130 | 0.7452 | 0.8984 | 0.8315 | 0.9974 | 0.9556 | 0.4282 | 0.8302 | 0.6095 | 0.8070 | 0.7280 | 0.9963 | | 0.0548 | 21.95 | 1800 | 0.2520 | 0.7649 | 0.8598 | 0.9300 | 0.9747 | 0.6344 | 0.9218 | 0.7885 | 0.8683 | 0.8322 | 0.9988 | 0.9560 | 0.4352 | 0.8339 | 0.6082 | 0.7956 | 0.7291 | 0.9963 | | 0.0503 | 22.2 | 1820 | 0.2521 | 0.7657 | 0.8528 | 0.9317 | 0.9799 | 0.6030 | 0.9077 | 0.7726 | 0.8890 | 0.8193 | 0.9983 | 0.9558 | 0.4312 | 0.8324 | 0.6150 | 0.8034 | 0.7257 | 0.9964 | | 0.0356 | 22.44 | 1840 | 0.2491 | 0.7669 | 0.8551 | 0.9328 | 0.9783 | 0.6119 | 0.9086 | 0.7470 | 0.9004 | 0.8412 | 0.9983 | 0.9568 | 0.4338 | 0.8310 | 0.6140 | 0.8091 | 0.7271 | 0.9966 | | 0.0381 | 22.68 | 1860 | 0.2660 | 0.7644 | 0.8458 | 0.9330 | 0.9805 | 0.5651 | 0.9095 | 0.7344 | 0.9094 | 0.8242 | 0.9973 | 0.9559 | 0.4213 | 0.8289 | 0.6129 | 0.8116 | 0.7240 | 0.9964 | | 0.0671 | 22.93 | 1880 | 0.2633 | 0.7664 | 0.8517 | 0.9332 | 0.9787 | 0.5970 | 0.9067 | 0.7371 | 0.9083 | 0.8360 | 0.9982 | 0.9559 | 0.4307 | 0.8286 | 0.6140 | 0.8129 | 0.7261 | 0.9966 | | 0.1123 | 23.17 | 1900 | 0.2462 | 0.7659 | 0.8489 | 0.9337 | 0.9790 | 0.5848 | 0.9088 | 0.7332 | 0.9121 | 0.8253 | 0.9987 | 0.9556 | 0.4257 | 0.8275 | 0.6161 | 0.8154 | 0.7251 | 0.9963 | | 0.0476 | 23.41 | 1920 | 0.2498 | 0.7665 | 0.8490 | 0.9336 | 0.9789 | 0.5651 | 0.9133 | 0.7813 | 0.8942 | 0.8124 | 0.9978 | 0.9557 | 0.4204 | 0.8297 | 0.6267 | 0.8128 | 0.7238 | 0.9966 | | 0.0999 | 23.66 | 1940 | 0.2556 | 0.7678 | 0.8539 | 0.9335 | 0.9779 | 0.6072 | 0.9123 | 0.7735 | 0.8972 | 0.8109 | 0.9985 | 0.9561 | 0.4335 | 0.8291 | 0.6245 | 0.8127 | 0.7223 | 0.9966 | | 0.0639 | 23.9 | 1960 | 0.2467 | 0.7659 | 0.8480 | 0.9337 | 0.9799 | 0.5431 | 0.9126 | 0.8278 | 0.8777 | 0.7960 | 0.9987 | 0.9547 | 0.4119 | 0.8279 | 0.6398 | 0.8137 | 0.7167 | 0.9964 | | 0.0718 | 24.15 | 1980 | 0.2469 | 0.7667 | 0.8484 | 0.9341 | 0.9804 | 0.5609 | 0.9068 | 0.7785 | 0.8983 | 0.8160 | 0.9982 | 0.9546 | 0.4190 | 0.8271 | 0.6306 | 0.8159 | 0.7232 | 0.9965 | | 0.0578 | 24.39 | 2000 | 0.2466 | 0.7668 | 0.8490 | 0.9339 | 0.9795 | 0.5737 | 0.9089 | 0.7591 | 0.9041 | 0.8194 | 0.9983 | 0.9551 | 0.4249 | 0.8271 | 0.6246 | 0.8155 | 0.7241 | 0.9965 | | 0.0664 | 24.63 | 2020 | 0.2530 | 0.7640 | 0.8449 | 0.9328 | 0.9784 | 0.5888 | 0.9101 | 0.7452 | 0.9125 | 0.7808 | 0.9987 | 0.9549 | 0.4305 | 0.8255 | 0.6185 | 0.8132 | 0.7088 | 0.9963 | | 0.7601 | 24.88 | 2040 | 0.2531 | 0.7677 | 0.8502 | 0.9340 | 0.9810 | 0.5654 | 0.8995 | 0.7891 | 0.8969 | 0.8221 | 0.9974 | 0.9535 | 0.4217 | 0.8288 | 0.6339 | 0.8151 | 0.7244 | 0.9964 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.17.1 - Tokenizers 0.15.1

johnhse/pokemon-lora

johnhse

2024-02-27T11:01:47Z

1

0

diffusers

[ "diffusers", "safetensors", "stable-diffusion", "stable-diffusion-diffusers", "text-to-image", "lora", "base_model:runwayml/stable-diffusion-v1-5", "base_model:adapter:runwayml/stable-diffusion-v1-5", "license:creativeml-openrail-m", "region:us" ]

text-to-image

2024-02-27T08:33:39Z

--- license: creativeml-openrail-m library_name: diffusers tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - lora inference: true base_model: runwayml/stable-diffusion-v1-5 ---  # LoRA text2image fine-tuning - johnhse/pokemon-lora These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset. You can find some example images in the following. ![img_0](./image_0.png) ![img_1](./image_1.png) ![img_2](./image_2.png) ![img_3](./image_3.png) ## 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]

huseinzol05/conformer-2M-ctc

huseinzol05

2024-02-27T10:57:07Z

51

0

transformers

[ "transformers", "safetensors", "conformer", "feature-extraction", "custom_code", "arxiv:1910.09700", "region:us" ]

feature-extraction

2024-02-27T10:56:59Z

--- 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]

peldrak/segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512

peldrak

2024-02-27T10:52:00Z

189

0

transformers

[ "transformers", "tensorboard", "safetensors", "segformer", "vision", "image-segmentation", "generated_from_trainer", "base_model:nvidia/segformer-b3-finetuned-ade-512-512", "base_model:finetune:nvidia/segformer-b3-finetuned-ade-512-512", "license:other", "endpoints_compatible", "region:us" ]

image-segmentation

2024-02-27T09:29:58Z

--- license: other base_model: nvidia/segformer-b3-finetuned-ade-512-512 tags: - vision - image-segmentation - generated_from_trainer model-index: - name: segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512 results: [] ---  # segformer-b3-ade-finetuned-512-512-finetuned-grCoastline_512 This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b3-finetuned-ade-512-512) on the peldrak/grCoastline_512 dataset. It achieves the following results on the evaluation set: - Loss: 0.2343 - Mean Iou: 0.7550 - Mean Accuracy: 0.8157 - Overall Accuracy: 0.9435 - Accuracy Water: 0.9775 - Accuracy Whitewater: 0.2651 - Accuracy Sediment: 0.9504 - Accuracy Other Natural Terrain: 0.8170 - Accuracy Vegetation: 0.8956 - Accuracy Development: 0.8082 - Accuracy Unknown: 0.9956 - Iou Water: 0.9507 - Iou Whitewater: 0.2519 - Iou Sediment: 0.8719 - Iou Other Natural Terrain: 0.7298 - Iou Vegetation: 0.7848 - Iou Development: 0.7015 - Iou Unknown: 0.9946 ## 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: 6e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 25 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Water | Accuracy Whitewater | Accuracy Sediment | Accuracy Other Natural Terrain | Accuracy Vegetation | Accuracy Development | Accuracy Unknown | Iou Water | Iou Whitewater | Iou Sediment | Iou Other Natural Terrain | Iou Vegetation | Iou Development | Iou Unknown | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:-------------------:|:-----------------:|:------------------------------:|:-------------------:|:--------------------:|:----------------:|:---------:|:--------------:|:------------:|:-------------------------:|:--------------:|:---------------:|:-----------:| | 1.3152 | 0.24 | 20 | 1.1371 | 0.3592 | 0.4647 | 0.7315 | 0.9430 | 0.0 | 0.2992 | 0.0547 | 0.7991 | 0.1760 | 0.9809 | 0.6706 | 0.0 | 0.2742 | 0.0502 | 0.4041 | 0.1413 | 0.9741 | | 1.2237 | 0.49 | 40 | 0.7602 | 0.4366 | 0.5444 | 0.8084 | 0.9568 | 0.0 | 0.8684 | 0.0674 | 0.8738 | 0.0645 | 0.9803 | 0.8767 | 0.0 | 0.5931 | 0.0668 | 0.4759 | 0.0643 | 0.9792 | | 0.8849 | 0.73 | 60 | 0.5319 | 0.5122 | 0.6082 | 0.8591 | 0.9603 | 0.0 | 0.9492 | 0.3503 | 0.9236 | 0.0824 | 0.9915 | 0.9197 | 0.0 | 0.6535 | 0.3355 | 0.6080 | 0.0822 | 0.9867 | | 0.7138 | 0.98 | 80 | 0.4433 | 0.5645 | 0.6474 | 0.8886 | 0.9732 | 0.0 | 0.9297 | 0.6001 | 0.9305 | 0.1018 | 0.9962 | 0.9208 | 0.0 | 0.7143 | 0.5271 | 0.7005 | 0.1015 | 0.9872 | | 0.4057 | 1.22 | 100 | 0.3726 | 0.6034 | 0.6801 | 0.9021 | 0.9746 | 0.0 | 0.9397 | 0.6993 | 0.8983 | 0.2557 | 0.9930 | 0.9325 | 0.0 | 0.7428 | 0.6061 | 0.7024 | 0.2508 | 0.9894 | | 0.5947 | 1.46 | 120 | 0.3407 | 0.6003 | 0.6767 | 0.9043 | 0.9809 | 0.0 | 0.9493 | 0.7424 | 0.8936 | 0.1789 | 0.9916 | 0.9264 | 0.0 | 0.7549 | 0.6223 | 0.7327 | 0.1776 | 0.9881 | | 0.324 | 1.71 | 140 | 0.3482 | 0.6087 | 0.6906 | 0.8992 | 0.9661 | 0.0 | 0.9787 | 0.8298 | 0.7234 | 0.3403 | 0.9958 | 0.9342 | 0.0 | 0.6806 | 0.6506 | 0.6853 | 0.3202 | 0.9901 | | 0.5283 | 1.95 | 160 | 0.2851 | 0.6729 | 0.7389 | 0.9265 | 0.9757 | 0.0 | 0.9427 | 0.8225 | 0.8647 | 0.5717 | 0.9954 | 0.9346 | 0.0 | 0.8134 | 0.7038 | 0.7573 | 0.5116 | 0.9895 | | 0.4225 | 2.2 | 180 | 0.2628 | 0.6674 | 0.7330 | 0.9232 | 0.9642 | 0.0 | 0.9175 | 0.8301 | 0.9002 | 0.5261 | 0.9928 | 0.9183 | 0.0 | 0.8127 | 0.7082 | 0.7438 | 0.4982 | 0.9904 | | 0.2334 | 2.44 | 200 | 0.2544 | 0.6811 | 0.7448 | 0.9282 | 0.9783 | 0.0 | 0.9488 | 0.7218 | 0.9115 | 0.6576 | 0.9956 | 0.9326 | 0.0 | 0.8252 | 0.6780 | 0.7556 | 0.5856 | 0.9905 | | 0.3386 | 2.68 | 220 | 0.2385 | 0.6844 | 0.7511 | 0.9279 | 0.9773 | 0.0 | 0.9358 | 0.7831 | 0.8913 | 0.6838 | 0.9864 | 0.9298 | 0.0 | 0.8409 | 0.6831 | 0.7590 | 0.5939 | 0.9845 | | 0.2847 | 2.93 | 240 | 0.2321 | 0.6817 | 0.7530 | 0.9275 | 0.9694 | 0.0 | 0.9472 | 0.8888 | 0.7828 | 0.6848 | 0.9980 | 0.9334 | 0.0 | 0.8187 | 0.7156 | 0.7399 | 0.5752 | 0.9895 | | 0.6314 | 3.17 | 260 | 0.2118 | 0.6995 | 0.7630 | 0.9362 | 0.9725 | 0.0 | 0.9494 | 0.8463 | 0.8667 | 0.7094 | 0.9965 | 0.9404 | 0.0 | 0.8324 | 0.7431 | 0.7783 | 0.6104 | 0.9916 | | 0.2687 | 3.41 | 280 | 0.2140 | 0.6992 | 0.7599 | 0.9359 | 0.9739 | 0.0 | 0.9480 | 0.8333 | 0.8776 | 0.6886 | 0.9976 | 0.9348 | 0.0 | 0.8242 | 0.7413 | 0.7869 | 0.6166 | 0.9908 | | 0.4188 | 3.66 | 300 | 0.2088 | 0.7045 | 0.7646 | 0.9382 | 0.9743 | 0.0 | 0.9594 | 0.8251 | 0.8940 | 0.7055 | 0.9936 | 0.9368 | 0.0 | 0.8483 | 0.7412 | 0.7886 | 0.6260 | 0.9909 | | 0.1609 | 3.9 | 320 | 0.1991 | 0.7059 | 0.7740 | 0.9372 | 0.9758 | 0.0 | 0.9463 | 0.8677 | 0.8325 | 0.8036 | 0.9923 | 0.9388 | 0.0 | 0.8620 | 0.7343 | 0.7721 | 0.6440 | 0.9900 | | 0.1591 | 4.15 | 340 | 0.2563 | 0.6544 | 0.7303 | 0.9157 | 0.9718 | 0.0 | 0.9700 | 0.8359 | 0.7659 | 0.5772 | 0.9915 | 0.9427 | 0.0 | 0.7907 | 0.6447 | 0.6947 | 0.5180 | 0.9901 | | 0.4456 | 4.39 | 360 | 0.2374 | 0.6846 | 0.7496 | 0.9283 | 0.9789 | 0.0 | 0.9396 | 0.7259 | 0.8976 | 0.7094 | 0.9956 | 0.9436 | 0.0 | 0.8668 | 0.6313 | 0.7349 | 0.6230 | 0.9928 | | 0.1556 | 4.63 | 380 | 0.2165 | 0.6871 | 0.7568 | 0.9294 | 0.9701 | 0.0 | 0.9681 | 0.8800 | 0.7831 | 0.6998 | 0.9963 | 0.9401 | 0.0 | 0.8319 | 0.7082 | 0.7283 | 0.6095 | 0.9918 | | 0.3269 | 4.88 | 400 | 0.2230 | 0.6995 | 0.7612 | 0.9340 | 0.9709 | 0.0 | 0.9544 | 0.7420 | 0.9106 | 0.7533 | 0.9969 | 0.9432 | 0.0 | 0.8551 | 0.6806 | 0.7497 | 0.6751 | 0.9929 | | 0.2006 | 5.12 | 420 | 0.2233 | 0.6884 | 0.7545 | 0.9303 | 0.9727 | 0.0 | 0.9573 | 0.8825 | 0.8049 | 0.6679 | 0.9960 | 0.9405 | 0.0 | 0.8366 | 0.7042 | 0.7340 | 0.6110 | 0.9929 | | 0.1007 | 5.37 | 440 | 0.2047 | 0.7084 | 0.7769 | 0.9383 | 0.9683 | 0.0 | 0.9583 | 0.8657 | 0.8279 | 0.8214 | 0.9966 | 0.9428 | 0.0 | 0.8463 | 0.7494 | 0.7689 | 0.6592 | 0.9921 | | 0.1391 | 5.61 | 460 | 0.2110 | 0.7102 | 0.7698 | 0.9386 | 0.9775 | 0.0 | 0.9289 | 0.8196 | 0.9082 | 0.7632 | 0.9914 | 0.9384 | 0.0 | 0.8686 | 0.7287 | 0.7739 | 0.6716 | 0.9899 | | 0.1582 | 5.85 | 480 | 0.1974 | 0.7070 | 0.7756 | 0.9371 | 0.9688 | 0.0 | 0.9503 | 0.7850 | 0.8715 | 0.8567 | 0.9971 | 0.9420 | 0.0 | 0.8565 | 0.7161 | 0.7626 | 0.6792 | 0.9928 | | 0.118 | 6.1 | 500 | 0.2184 | 0.6937 | 0.7602 | 0.9312 | 0.9800 | 0.0 | 0.9321 | 0.8670 | 0.8032 | 0.7424 | 0.9969 | 0.9372 | 0.0 | 0.8535 | 0.6900 | 0.7355 | 0.6468 | 0.9929 | | 0.1206 | 6.34 | 520 | 0.2585 | 0.6906 | 0.7549 | 0.9312 | 0.9766 | 0.0 | 0.9652 | 0.7906 | 0.8669 | 0.6927 | 0.9922 | 0.9364 | 0.0 | 0.8134 | 0.7155 | 0.7562 | 0.6218 | 0.9910 | | 0.1531 | 6.59 | 540 | 0.2177 | 0.7048 | 0.7699 | 0.9370 | 0.9788 | 0.0 | 0.9361 | 0.8889 | 0.8270 | 0.7644 | 0.9944 | 0.9426 | 0.0 | 0.8647 | 0.7215 | 0.7629 | 0.6492 | 0.9926 | | 0.141 | 6.83 | 560 | 0.2271 | 0.7014 | 0.7655 | 0.9362 | 0.9625 | 0.0 | 0.9726 | 0.8432 | 0.8655 | 0.7186 | 0.9957 | 0.9403 | 0.0 | 0.8254 | 0.7420 | 0.7758 | 0.6330 | 0.9931 | | 0.1233 | 7.07 | 580 | 0.2128 | 0.7108 | 0.7723 | 0.9398 | 0.9739 | 0.0 | 0.9529 | 0.8535 | 0.8659 | 0.7646 | 0.9954 | 0.9430 | 0.0 | 0.8579 | 0.7390 | 0.7766 | 0.6661 | 0.9932 | | 0.0518 | 7.32 | 600 | 0.2460 | 0.6911 | 0.7617 | 0.9304 | 0.9659 | 0.0 | 0.9711 | 0.8530 | 0.7962 | 0.7486 | 0.9969 | 0.9426 | 0.0 | 0.8348 | 0.6982 | 0.7278 | 0.6405 | 0.9941 | | 0.1164 | 7.56 | 620 | 0.2446 | 0.6992 | 0.7670 | 0.9337 | 0.9747 | 0.0 | 0.9534 | 0.8651 | 0.8042 | 0.7752 | 0.9963 | 0.9432 | 0.0 | 0.8550 | 0.7027 | 0.7379 | 0.6615 | 0.9941 | | 0.1448 | 7.8 | 640 | 0.2159 | 0.7115 | 0.7726 | 0.9394 | 0.9771 | 0.0 | 0.9510 | 0.8102 | 0.8822 | 0.7928 | 0.9952 | 0.9435 | 0.0 | 0.8560 | 0.7265 | 0.7725 | 0.6886 | 0.9932 | | 0.4327 | 8.05 | 660 | 0.2056 | 0.7150 | 0.7766 | 0.9418 | 0.9736 | 0.0 | 0.9551 | 0.8341 | 0.8786 | 0.7980 | 0.9966 | 0.9443 | 0.0 | 0.8579 | 0.7494 | 0.7862 | 0.6734 | 0.9935 | | 0.1197 | 8.29 | 680 | 0.2153 | 0.7068 | 0.7647 | 0.9389 | 0.9767 | 0.0 | 0.9434 | 0.8219 | 0.9024 | 0.7126 | 0.9963 | 0.9417 | 0.0 | 0.8681 | 0.7183 | 0.7794 | 0.6469 | 0.9935 | | 0.1376 | 8.54 | 700 | 0.2252 | 0.7069 | 0.7755 | 0.9375 | 0.9676 | 0.0 | 0.9668 | 0.8520 | 0.8228 | 0.8217 | 0.9977 | 0.9441 | 0.0 | 0.8448 | 0.7397 | 0.7594 | 0.6667 | 0.9934 | | 0.3054 | 8.78 | 720 | 0.2291 | 0.7079 | 0.7708 | 0.9382 | 0.9773 | 0.0 | 0.9544 | 0.8451 | 0.8599 | 0.7667 | 0.9924 | 0.9404 | 0.0 | 0.8559 | 0.7306 | 0.7749 | 0.6626 | 0.9912 | | 0.1884 | 9.02 | 740 | 0.2077 | 0.7194 | 0.7823 | 0.9422 | 0.9733 | 0.0 | 0.9366 | 0.8561 | 0.8671 | 0.8472 | 0.9957 | 0.9449 | 0.0 | 0.8750 | 0.7354 | 0.7776 | 0.7092 | 0.9936 | | 0.0987 | 9.27 | 760 | 0.2207 | 0.7112 | 0.7780 | 0.9385 | 0.9753 | 0.0 | 0.9640 | 0.8870 | 0.8026 | 0.8232 | 0.9938 | 0.9414 | 0.0 | 0.8349 | 0.7599 | 0.7583 | 0.6912 | 0.9924 | | 0.1062 | 9.51 | 780 | 0.2697 | 0.6999 | 0.7640 | 0.9335 | 0.9747 | 0.0 | 0.9493 | 0.7366 | 0.8967 | 0.7950 | 0.9957 | 0.9429 | 0.0 | 0.8455 | 0.6892 | 0.7403 | 0.6884 | 0.9932 | | 0.1437 | 9.76 | 800 | 0.2240 | 0.7069 | 0.7715 | 0.9380 | 0.9692 | 0.0 | 0.9578 | 0.8028 | 0.8838 | 0.7906 | 0.9960 | 0.9451 | 0.0 | 0.8487 | 0.7271 | 0.7701 | 0.6635 | 0.9935 | | 0.0806 | 10.0 | 820 | 0.2262 | 0.7068 | 0.7692 | 0.9388 | 0.9788 | 0.0 | 0.9596 | 0.8313 | 0.8618 | 0.7573 | 0.9960 | 0.9447 | 0.0 | 0.8471 | 0.7398 | 0.7748 | 0.6479 | 0.9934 | | 0.1172 | 10.24 | 840 | 0.2594 | 0.6971 | 0.7598 | 0.9336 | 0.9751 | 0.0 | 0.9497 | 0.7498 | 0.8983 | 0.7482 | 0.9975 | 0.9432 | 0.0 | 0.8596 | 0.6762 | 0.7500 | 0.6570 | 0.9934 | | 0.3204 | 10.49 | 860 | 0.2114 | 0.7167 | 0.7775 | 0.9417 | 0.9735 | 0.0 | 0.9405 | 0.8401 | 0.8791 | 0.8117 | 0.9977 | 0.9440 | 0.0 | 0.8751 | 0.7310 | 0.7812 | 0.6925 | 0.9933 | | 0.18 | 10.73 | 880 | 0.2234 | 0.7163 | 0.7774 | 0.9415 | 0.9708 | 0.0 | 0.9606 | 0.8125 | 0.8921 | 0.8111 | 0.9950 | 0.9458 | 0.0 | 0.8635 | 0.7310 | 0.7799 | 0.7000 | 0.9937 | | 0.1388 | 10.98 | 900 | 0.2211 | 0.7231 | 0.7820 | 0.9435 | 0.9745 | 0.0 | 0.9282 | 0.8094 | 0.9115 | 0.8533 | 0.9971 | 0.9442 | 0.0 | 0.8842 | 0.7275 | 0.7822 | 0.7296 | 0.9942 | | 0.3495 | 11.22 | 920 | 0.2246 | 0.7172 | 0.7803 | 0.9420 | 0.9735 | 0.0 | 0.9535 | 0.8467 | 0.8540 | 0.8361 | 0.9985 | 0.9443 | 0.0 | 0.8700 | 0.7384 | 0.7796 | 0.6941 | 0.9940 | | 0.1129 | 11.46 | 940 | 0.2116 | 0.7187 | 0.7770 | 0.9431 | 0.9764 | 0.0 | 0.9480 | 0.8252 | 0.9009 | 0.7927 | 0.9954 | 0.9460 | 0.0 | 0.8772 | 0.7303 | 0.7890 | 0.6944 | 0.9941 | | 0.1725 | 11.71 | 960 | 0.2028 | 0.7199 | 0.7820 | 0.9432 | 0.9799 | 0.0 | 0.9457 | 0.8285 | 0.8723 | 0.8515 | 0.9962 | 0.9442 | 0.0 | 0.8773 | 0.7348 | 0.7872 | 0.7019 | 0.9941 | | 0.1882 | 11.95 | 980 | 0.2180 | 0.7168 | 0.7759 | 0.9422 | 0.9743 | 0.0 | 0.9556 | 0.8052 | 0.8990 | 0.7998 | 0.9974 | 0.9460 | 0.0 | 0.8570 | 0.7326 | 0.7887 | 0.6984 | 0.9945 | | 0.1523 | 12.2 | 1000 | 0.2185 | 0.7172 | 0.7792 | 0.9416 | 0.9750 | 0.0000 | 0.9527 | 0.8253 | 0.8779 | 0.8287 | 0.9947 | 0.9444 | 0.0000 | 0.8701 | 0.7322 | 0.7781 | 0.7019 | 0.9936 | | 0.0959 | 12.44 | 1020 | 0.2232 | 0.7192 | 0.7806 | 0.9424 | 0.9781 | 0.0 | 0.9452 | 0.8150 | 0.8840 | 0.8469 | 0.9953 | 0.9444 | 0.0 | 0.8769 | 0.7281 | 0.7792 | 0.7115 | 0.9941 | | 0.0786 | 12.68 | 1040 | 0.2383 | 0.7129 | 0.7741 | 0.9403 | 0.9771 | 0.0001 | 0.9592 | 0.8173 | 0.8741 | 0.7949 | 0.9956 | 0.9449 | 0.0001 | 0.8567 | 0.7321 | 0.7734 | 0.6892 | 0.9942 | | 0.1079 | 12.93 | 1060 | 0.2410 | 0.7144 | 0.7772 | 0.9401 | 0.9786 | 0.0040 | 0.9510 | 0.7919 | 0.8845 | 0.8357 | 0.9945 | 0.9451 | 0.0040 | 0.8585 | 0.7261 | 0.7709 | 0.7030 | 0.9933 | | 0.1476 | 13.17 | 1080 | 0.2192 | 0.7130 | 0.7782 | 0.9403 | 0.9718 | 0.0008 | 0.9582 | 0.8334 | 0.8548 | 0.8309 | 0.9975 | 0.9458 | 0.0008 | 0.8536 | 0.7367 | 0.7733 | 0.6859 | 0.9950 | | 0.1231 | 13.41 | 1100 | 0.2260 | 0.7157 | 0.7790 | 0.9417 | 0.9800 | 0.0002 | 0.9430 | 0.8018 | 0.8889 | 0.8443 | 0.9951 | 0.9456 | 0.0002 | 0.8722 | 0.7265 | 0.7836 | 0.6882 | 0.9939 | | 0.0879 | 13.66 | 1120 | 0.2403 | 0.7133 | 0.7767 | 0.9407 | 0.9709 | 0.0 | 0.9670 | 0.8450 | 0.8523 | 0.8043 | 0.9974 | 0.9472 | 0.0 | 0.8539 | 0.7357 | 0.7748 | 0.6864 | 0.9951 | | 0.116 | 13.9 | 1140 | 0.2334 | 0.7191 | 0.7810 | 0.9425 | 0.9767 | 0.0165 | 0.9465 | 0.8118 | 0.8896 | 0.8284 | 0.9974 | 0.9471 | 0.0164 | 0.8677 | 0.7354 | 0.7863 | 0.6862 | 0.9946 | | 0.1264 | 14.15 | 1160 | 0.2366 | 0.7162 | 0.7765 | 0.9414 | 0.9789 | 0.0146 | 0.9504 | 0.8165 | 0.8936 | 0.7870 | 0.9943 | 0.9462 | 0.0145 | 0.8657 | 0.7314 | 0.7849 | 0.6774 | 0.9934 | | 0.0761 | 14.39 | 1180 | 0.2227 | 0.7198 | 0.7792 | 0.9427 | 0.9789 | 0.0180 | 0.9509 | 0.8127 | 0.8924 | 0.8044 | 0.9968 | 0.9469 | 0.0179 | 0.8670 | 0.7339 | 0.7858 | 0.6921 | 0.9948 | | 0.0437 | 14.63 | 1200 | 0.2192 | 0.7188 | 0.7819 | 0.9415 | 0.9769 | 0.0248 | 0.9490 | 0.8470 | 0.8566 | 0.8219 | 0.9970 | 0.9466 | 0.0246 | 0.8645 | 0.7379 | 0.7761 | 0.6873 | 0.9948 | | 0.0732 | 14.88 | 1220 | 0.2396 | 0.7289 | 0.7897 | 0.9421 | 0.9760 | 0.0861 | 0.9477 | 0.8180 | 0.8934 | 0.8121 | 0.9948 | 0.9465 | 0.0849 | 0.8654 | 0.7368 | 0.7824 | 0.6923 | 0.9936 | | 0.1376 | 15.12 | 1240 | 0.2280 | 0.7314 | 0.7915 | 0.9430 | 0.9753 | 0.0944 | 0.9480 | 0.8444 | 0.8766 | 0.8039 | 0.9976 | 0.9469 | 0.0925 | 0.8660 | 0.7413 | 0.7854 | 0.6934 | 0.9946 | | 0.0518 | 15.37 | 1260 | 0.2378 | 0.7289 | 0.7880 | 0.9422 | 0.9746 | 0.0885 | 0.9501 | 0.8424 | 0.8832 | 0.7807 | 0.9963 | 0.9460 | 0.0864 | 0.8661 | 0.7345 | 0.7828 | 0.6920 | 0.9946 | | 0.0599 | 15.61 | 1280 | 0.2288 | 0.7242 | 0.7848 | 0.9418 | 0.9784 | 0.0559 | 0.9443 | 0.8397 | 0.8761 | 0.8037 | 0.9952 | 0.9468 | 0.0555 | 0.8645 | 0.7356 | 0.7789 | 0.6943 | 0.9939 | | 0.0967 | 15.85 | 1300 | 0.2416 | 0.7301 | 0.7939 | 0.9413 | 0.9749 | 0.1088 | 0.9523 | 0.8402 | 0.8542 | 0.8291 | 0.9979 | 0.9493 | 0.1074 | 0.8613 | 0.7326 | 0.7718 | 0.6933 | 0.9952 | | 0.0593 | 16.1 | 1320 | 0.2691 | 0.7212 | 0.7812 | 0.9396 | 0.9777 | 0.0661 | 0.9444 | 0.7484 | 0.9244 | 0.8117 | 0.9958 | 0.9483 | 0.0651 | 0.8732 | 0.6970 | 0.7657 | 0.7051 | 0.9944 | | 0.2264 | 16.34 | 1340 | 0.2362 | 0.7237 | 0.7854 | 0.9420 | 0.9756 | 0.0505 | 0.9512 | 0.8124 | 0.8846 | 0.8266 | 0.9969 | 0.9469 | 0.0499 | 0.8610 | 0.7362 | 0.7802 | 0.6966 | 0.9948 | | 0.0592 | 16.59 | 1360 | 0.2423 | 0.7367 | 0.8007 | 0.9391 | 0.9729 | 0.1878 | 0.9486 | 0.8662 | 0.8410 | 0.7923 | 0.9964 | 0.9477 | 0.1838 | 0.8581 | 0.7238 | 0.7609 | 0.6875 | 0.9951 | | 0.1125 | 16.83 | 1380 | 0.2339 | 0.7527 | 0.8150 | 0.9431 | 0.9762 | 0.2572 | 0.9448 | 0.8334 | 0.8824 | 0.8143 | 0.9969 | 0.9485 | 0.2431 | 0.8608 | 0.7434 | 0.7846 | 0.6934 | 0.9951 | | 0.0603 | 17.07 | 1400 | 0.2270 | 0.7406 | 0.8004 | 0.9417 | 0.9753 | 0.1855 | 0.9417 | 0.8159 | 0.8973 | 0.7897 | 0.9975 | 0.9475 | 0.1795 | 0.8640 | 0.7270 | 0.7791 | 0.6921 | 0.9951 | | 0.0519 | 17.32 | 1420 | 0.2306 | 0.7467 | 0.8067 | 0.9430 | 0.9751 | 0.2083 | 0.9472 | 0.8316 | 0.8892 | 0.7984 | 0.9969 | 0.9491 | 0.2023 | 0.8660 | 0.7348 | 0.7845 | 0.6952 | 0.9950 | | 0.0604 | 17.56 | 1440 | 0.2442 | 0.7355 | 0.7969 | 0.9424 | 0.9799 | 0.1369 | 0.9507 | 0.8123 | 0.8850 | 0.8175 | 0.9956 | 0.9483 | 0.1337 | 0.8670 | 0.7313 | 0.7826 | 0.6911 | 0.9945 | | 0.0938 | 17.8 | 1460 | 0.2359 | 0.7392 | 0.7993 | 0.9422 | 0.9726 | 0.1637 | 0.9542 | 0.8012 | 0.8966 | 0.8084 | 0.9987 | 0.9483 | 0.1598 | 0.8663 | 0.7251 | 0.7808 | 0.6992 | 0.9947 | | 0.1024 | 18.05 | 1480 | 0.2377 | 0.7305 | 0.7902 | 0.9418 | 0.9811 | 0.1062 | 0.9475 | 0.8259 | 0.8784 | 0.7962 | 0.9960 | 0.9482 | 0.1042 | 0.8690 | 0.7262 | 0.7776 | 0.6936 | 0.9946 | | 0.0536 | 18.29 | 1500 | 0.2309 | 0.7358 | 0.7961 | 0.9424 | 0.9756 | 0.1348 | 0.9526 | 0.8292 | 0.8784 | 0.8046 | 0.9975 | 0.9502 | 0.1325 | 0.8695 | 0.7282 | 0.7786 | 0.6971 | 0.9948 | | 0.07 | 18.54 | 1520 | 0.2380 | 0.7507 | 0.8127 | 0.9428 | 0.9747 | 0.2410 | 0.9478 | 0.8254 | 0.8836 | 0.8191 | 0.9971 | 0.9503 | 0.2312 | 0.8708 | 0.7276 | 0.7799 | 0.7001 | 0.9951 | | 0.0692 | 18.78 | 1540 | 0.2429 | 0.7478 | 0.8104 | 0.9420 | 0.9745 | 0.2285 | 0.9462 | 0.8139 | 0.8853 | 0.8269 | 0.9973 | 0.9502 | 0.2198 | 0.8739 | 0.7180 | 0.7755 | 0.7018 | 0.9952 | | 0.0673 | 19.02 | 1560 | 0.2288 | 0.7352 | 0.7966 | 0.9409 | 0.9769 | 0.1525 | 0.9459 | 0.8163 | 0.8795 | 0.8081 | 0.9974 | 0.9470 | 0.1472 | 0.8681 | 0.7192 | 0.7749 | 0.6955 | 0.9945 | | 0.0406 | 19.27 | 1580 | 0.2302 | 0.7484 | 0.8096 | 0.9426 | 0.9757 | 0.2222 | 0.9442 | 0.8234 | 0.8849 | 0.8196 | 0.9974 | 0.9493 | 0.2126 | 0.8746 | 0.7252 | 0.7781 | 0.7042 | 0.9945 | | 0.0686 | 19.51 | 1600 | 0.2228 | 0.7421 | 0.8031 | 0.9432 | 0.9755 | 0.1643 | 0.9524 | 0.8481 | 0.8669 | 0.8176 | 0.9970 | 0.9496 | 0.1599 | 0.8718 | 0.7337 | 0.7808 | 0.7039 | 0.9950 | | 0.0559 | 19.76 | 1620 | 0.2335 | 0.7497 | 0.8141 | 0.9422 | 0.9753 | 0.2443 | 0.9511 | 0.8181 | 0.8749 | 0.8382 | 0.9967 | 0.9497 | 0.2320 | 0.8723 | 0.7237 | 0.7767 | 0.6985 | 0.9949 | | 0.0726 | 20.0 | 1640 | 0.2381 | 0.7439 | 0.8067 | 0.9417 | 0.9796 | 0.2054 | 0.9492 | 0.8341 | 0.8658 | 0.8182 | 0.9949 | 0.9484 | 0.1952 | 0.8690 | 0.7270 | 0.7748 | 0.6985 | 0.9941 | | 0.0381 | 20.24 | 1660 | 0.2289 | 0.7603 | 0.8246 | 0.9425 | 0.9763 | 0.3250 | 0.9474 | 0.8232 | 0.8778 | 0.8261 | 0.9967 | 0.9506 | 0.3039 | 0.8722 | 0.7244 | 0.7768 | 0.6991 | 0.9951 | | 0.1459 | 20.49 | 1680 | 0.2320 | 0.7435 | 0.8034 | 0.9422 | 0.9795 | 0.2004 | 0.9497 | 0.8294 | 0.8781 | 0.7897 | 0.9967 | 0.9500 | 0.1939 | 0.8711 | 0.7228 | 0.7781 | 0.6936 | 0.9950 | | 0.0515 | 20.73 | 1700 | 0.2366 | 0.7584 | 0.8212 | 0.9425 | 0.9772 | 0.3128 | 0.9445 | 0.8043 | 0.8924 | 0.8189 | 0.9980 | 0.9504 | 0.2910 | 0.8743 | 0.7188 | 0.7777 | 0.7017 | 0.9951 | | 0.1066 | 20.98 | 1720 | 0.2450 | 0.7615 | 0.8249 | 0.9420 | 0.9723 | 0.3449 | 0.9531 | 0.8283 | 0.8804 | 0.7978 | 0.9973 | 0.9506 | 0.3225 | 0.8704 | 0.7218 | 0.7762 | 0.6941 | 0.9950 | | 0.0677 | 21.22 | 1740 | 0.2302 | 0.7512 | 0.8141 | 0.9424 | 0.9777 | 0.2553 | 0.9465 | 0.8569 | 0.8526 | 0.8115 | 0.9982 | 0.9502 | 0.2412 | 0.8731 | 0.7264 | 0.7766 | 0.6954 | 0.9953 | | 0.0745 | 21.46 | 1760 | 0.2343 | 0.7389 | 0.7999 | 0.9420 | 0.9807 | 0.1705 | 0.9453 | 0.8517 | 0.8613 | 0.7930 | 0.9966 | 0.9486 | 0.1644 | 0.8710 | 0.7263 | 0.7792 | 0.6877 | 0.9950 | | 0.1053 | 21.71 | 1780 | 0.2453 | 0.7591 | 0.8219 | 0.9426 | 0.9747 | 0.3127 | 0.9517 | 0.8279 | 0.8834 | 0.8070 | 0.9958 | 0.9511 | 0.2943 | 0.8705 | 0.7253 | 0.7796 | 0.6977 | 0.9948 | | 0.0898 | 21.95 | 1800 | 0.2224 | 0.7525 | 0.8145 | 0.9435 | 0.9767 | 0.2480 | 0.9498 | 0.8216 | 0.8848 | 0.8237 | 0.9972 | 0.9501 | 0.2357 | 0.8693 | 0.7325 | 0.7856 | 0.6988 | 0.9953 | | 0.1724 | 22.2 | 1820 | 0.2210 | 0.7390 | 0.7982 | 0.9430 | 0.9795 | 0.1569 | 0.9503 | 0.8319 | 0.8831 | 0.7889 | 0.9966 | 0.9499 | 0.1527 | 0.8697 | 0.7298 | 0.7853 | 0.6903 | 0.9950 | | 0.1683 | 22.44 | 1840 | 0.2362 | 0.7629 | 0.8257 | 0.9439 | 0.9774 | 0.3265 | 0.9405 | 0.8187 | 0.8975 | 0.8231 | 0.9966 | 0.9514 | 0.3020 | 0.8741 | 0.7299 | 0.7861 | 0.7016 | 0.9951 | | 0.0613 | 22.68 | 1860 | 0.2266 | 0.7634 | 0.8267 | 0.9441 | 0.9769 | 0.3291 | 0.9418 | 0.8187 | 0.8939 | 0.8291 | 0.9974 | 0.9511 | 0.3024 | 0.8750 | 0.7301 | 0.7864 | 0.7032 | 0.9953 | | 0.0638 | 22.93 | 1880 | 0.2321 | 0.7650 | 0.8286 | 0.9438 | 0.9755 | 0.3469 | 0.9500 | 0.8305 | 0.8831 | 0.8173 | 0.9972 | 0.9519 | 0.3208 | 0.8735 | 0.7297 | 0.7852 | 0.6986 | 0.9953 | | 0.0865 | 23.17 | 1900 | 0.2402 | 0.7476 | 0.8078 | 0.9434 | 0.9773 | 0.2115 | 0.9529 | 0.8024 | 0.9005 | 0.8132 | 0.9965 | 0.9502 | 0.2039 | 0.8688 | 0.7291 | 0.7860 | 0.7006 | 0.9950 | | 0.183 | 23.41 | 1920 | 0.2340 | 0.7545 | 0.8155 | 0.9437 | 0.9757 | 0.2616 | 0.9551 | 0.8198 | 0.8879 | 0.8106 | 0.9975 | 0.9512 | 0.2492 | 0.8685 | 0.7321 | 0.7853 | 0.7000 | 0.9953 | | 0.0665 | 23.66 | 1940 | 0.2250 | 0.7580 | 0.8206 | 0.9439 | 0.9756 | 0.2861 | 0.9518 | 0.8188 | 0.8857 | 0.8279 | 0.9979 | 0.9513 | 0.2691 | 0.8718 | 0.7316 | 0.7853 | 0.7015 | 0.9953 | | 0.0783 | 23.9 | 1960 | 0.2271 | 0.7541 | 0.8161 | 0.9435 | 0.9773 | 0.2581 | 0.9518 | 0.8318 | 0.8773 | 0.8199 | 0.9966 | 0.9511 | 0.2452 | 0.8718 | 0.7308 | 0.7832 | 0.7017 | 0.9952 | | 0.0767 | 24.15 | 1980 | 0.2246 | 0.7616 | 0.8247 | 0.9438 | 0.9765 | 0.3151 | 0.9509 | 0.8143 | 0.8912 | 0.8285 | 0.9964 | 0.9515 | 0.2948 | 0.8724 | 0.7301 | 0.7856 | 0.7014 | 0.9951 | | 0.112 | 24.39 | 2000 | 0.2314 | 0.7669 | 0.8310 | 0.9438 | 0.9743 | 0.3599 | 0.9503 | 0.8198 | 0.8892 | 0.8259 | 0.9972 | 0.9520 | 0.3326 | 0.8731 | 0.7290 | 0.7844 | 0.7016 | 0.9953 | | 0.074 | 24.63 | 2020 | 0.2291 | 0.7603 | 0.8235 | 0.9437 | 0.9770 | 0.3074 | 0.9499 | 0.8136 | 0.8901 | 0.8296 | 0.9966 | 0.9513 | 0.2874 | 0.8723 | 0.7293 | 0.7851 | 0.7014 | 0.9951 | | 0.0684 | 24.88 | 2040 | 0.2343 | 0.7550 | 0.8157 | 0.9435 | 0.9775 | 0.2651 | 0.9504 | 0.8170 | 0.8956 | 0.8082 | 0.9956 | 0.9507 | 0.2519 | 0.8719 | 0.7298 | 0.7848 | 0.7015 | 0.9946 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.14.1

AbstractPerspective/2xMistral

AbstractPerspective

2024-02-27T10:48:03Z

4

0

transformers

[ "transformers", "safetensors", "mixtral", "text-generation", "moe", "frankenmoe", "merge", "mergekit", "lazymergekit", "mistralai/Mistral-7B-v0.1", "mlabonne/drmistral-7b", "base_model:mistralai/Mistral-7B-v0.1", "base_model:merge:mistralai/Mistral-7B-v0.1", "base_model:mlabonne/drmistral-7b", "base_model:merge:mlabonne/drmistral-7b", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T10:40:38Z

--- license: apache-2.0 tags: - moe - frankenmoe - merge - mergekit - lazymergekit - mistralai/Mistral-7B-v0.1 - mlabonne/drmistral-7b base_model: - mistralai/Mistral-7B-v0.1 - mlabonne/drmistral-7b --- # 2xMistral 2xMistral is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) * [mlabonne/drmistral-7b](https://huggingface.co/mlabonne/drmistral-7b) ## 🧩 Configuration ```yaml base_model: mistralai/Mistral-7B-v0.1 gate_mode: cheap_embed experts: - source_model: mistralai/Mistral-7B-v0.1 positive_prompts: ["general"] - source_model: mlabonne/drmistral-7b positive_prompts: ["medical"] ``` ## 💻 Usage ```python !pip install -qU transformers bitsandbytes accelerate from transformers import AutoTokenizer import transformers import torch model = "AbstractPerspective/2xMistral" tokenizer = AutoTokenizer.from_pretrained(model) pipeline = transformers.pipeline( "text-generation", model=model, model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, ) messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) print(outputs[0]["generated_text"]) ```

zeronin7/distilbert-base-uncased-finetuned-clinc

zeronin7

2024-02-27T10:44:29Z

108

0

transformers

[ "transformers", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-26T16:48:37Z

--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-uncased-finetuned-clinc results: [] ---  # distilbert-base-uncased-finetuned-clinc This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7989 - Accuracy: 0.9177 ## 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: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 318 | 3.3192 | 0.7390 | | 3.8194 | 2.0 | 636 | 1.9157 | 0.8497 | | 3.8194 | 3.0 | 954 | 1.1867 | 0.8981 | | 1.7308 | 4.0 | 1272 | 0.8824 | 0.9177 | | 0.9303 | 5.0 | 1590 | 0.7989 | 0.9177 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.0.0 - Datasets 2.14.5 - Tokenizers 0.15.2

mlx-community/CodeLlama-7b-Python-mlx

mlx-community

2024-02-27T10:40:53Z

27

10

mlx

[ "mlx", "llama", "facebook", "meta", "llama-2", "text-generation", "license:llama2", "region:us" ]

text-generation

2023-12-06T17:02:15Z

--- pipeline_tag: text-generation library_name: mlx inference: false tags: - facebook - meta - llama - llama-2 - mlx license: llama2 --- # **CodeLlama** Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the base 7B version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. This is the repository for the 7B Python fine-tuned model, in `npz` format suitable for use in Apple's MLX framework. Weights have been converted to `float16` from the original `bfloat16` type, because `numpy` is not compatible with `bfloat16` out of the box. How to use with [MLX](https://github.com/ml-explore/mlx). ```bash # Install mlx, mlx-examples, huggingface-cli pip install mlx pip install huggingface_hub hf_transfer git clone https://github.com/ml-explore/mlx-examples.git # Download model export HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download --local-dir CodeLlama-7b-Python-mlx mlx-llama/CodeLlama-7b-Python-mlx # Run example python mlx-examples/llms/llama/llama.py --prompt "def fibonacci(n):" CodeLlama-7b-Python-mlx/ CodeLlama-7b-Python-mlx/tokenizer.model --max-tokens 200 ``` Please, refer to the [original model card](https://github.com/facebookresearch/codellama/blob/main/MODEL_CARD.md) for details on CodeLlama.

haripriya126/my-pet-dog

haripriya126

2024-02-27T10:27:15Z

10

0

diffusers

[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]

text-to-image

2024-02-27T10:22:53Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by haripriya126 following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/haripriya126/my-pet-dog/resolve/main/sample_images/xzg1.jpg)

bhafner/test

bhafner

2024-02-27T10:27:04Z

2

0

diffusers

[ "diffusers", "text-to-image", "autotrain", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:finetune:stabilityai/stable-diffusion-xl-base-1.0", "region:us" ]

text-to-image

2024-02-27T08:12:38Z

--- base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: photo of a bhafner person tags: - text-to-image - diffusers - autotrain inference: true --- # DreamBooth trained by AutoTrain Text encoder was not trained.

JohannesGaessler/cosmosage_v2-gguf

JohannesGaessler

2024-02-27T10:26:20Z

29

0

null

[ "gguf", "license:apache-2.0", "endpoints_compatible", "region:us", "conversational" ]

null

2024-02-25T13:34:06Z

--- license: apache-2.0 --- GGUF conversion of [Cosmosage v2](https://huggingface.co/Tijmen2/cosmosage_v2). The importance matrix for iq formats was calculated on the training set of Wikitext 2. The iq1\_s quant was incoherent and therefore not included.

Nishthaa321/autotrain-qr7os-gstst

Nishthaa321

2024-02-27T10:26:05Z

106

0

transformers

[ "transformers", "safetensors", "roberta", "text-classification", "autotrain", "dataset:autotrain-qr7os-gstst/autotrain-data", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-27T10:25:38Z

--- tags: - autotrain - text-classification widget: - text: "I love AutoTrain" datasets: - autotrain-qr7os-gstst/autotrain-data --- # Model Trained Using AutoTrain - Problem type: Text Classification ## Validation Metrics loss: 0.2146722972393036 f1: 1.0 precision: 1.0 recall: 1.0 auc: 1.0 accuracy: 1.0

RupE/alpaca-bitcoin-tweets-sentiment

RupE

2024-02-27T10:13:40Z

0

peft

[ "peft", "region:us" ]

null

2024-02-27T10:13:39Z

--- library_name: peft --- ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.4.0

FatmaYoussef/ppo-SnowballTarget

FatmaYoussef

2024-02-27T10:01:59Z

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "SnowballTarget", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SnowballTarget", "region:us" ]

reinforcement-learning

2024-02-27T10:01:52Z

--- library_name: ml-agents tags: - SnowballTarget - deep-reinforcement-learning - reinforcement-learning - ML-Agents-SnowballTarget --- # **ppo** Agent playing **SnowballTarget** This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: FatmaYoussef/ppo-SnowballTarget 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

FINNUMBER/FINCH_TRAIN_ALL_3600_per400_NEW_Rationale_E4

FINNUMBER

2024-02-27T09:59:18Z

4

0

transformers

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

text-generation

2024-02-27T09:53:57Z

--- 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]

alexandrabenamar/bloomz-7b1-4Magic

alexandrabenamar

2024-02-27T09:59:18Z

4

0

transformers

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

text-generation

2024-02-27T09:10:20Z

--- 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]

FINNUMBER/FINCH_TRAIN_SA_200_per100_NEW_Rationale_E12

FINNUMBER

2024-02-27T09:59:10Z

4

0

transformers

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

text-generation

2024-02-27T09:53:51Z

--- 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]

ProphetOfBostrom/opus-v1-34b-4b8h-8192l-EXL2

ProphetOfBostrom

2024-02-27T09:55:42Z

2

0

transformers

[ "transformers", "pytorch", "llama", "text-generation", "unsloth", "axolotl", "exllamav2", "exl2", "4bit", "conversational", "en", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-26T22:15:38Z

--- license: other license_name: yi-license license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE language: - en pipeline_tag: text-generation tags: - unsloth - axolotl - exllamav2 - exl2 - 4bit library_name: transformers --- ### quantized with the default exl2 dataset with sequence lengths of 8192 and 400 calibration (stage 2, optimisation) lines instead of 2048/100. possibly microwaved, presumably better. ##### resulstant measurement file is present somewhere, though the default line count of 16 (still extended to 8192) was used for measurement (stage 1) ### tokenizer works. tokenizer.model is not required for use with exllama2. no promises about sketchy software by "oobabooga"* :) try tabbyAPI/tavern, or exui if you don't miss CFG ##### consider yourselves lucky it's not a safetensors.zpaq this took all night to upload and YES i did refresh my access tokens after the Whoopsie, sorry! ###### *I'm sure it's fine it's just that I'll die if I ever see conda again. --- # DreamGen Opus V1 <div style="display: flex; flex-direction: row; align-items: center;"> <img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style=" border-radius: 12px; margin-right: 12px; margin-top: 0px; margin-bottom: 0px; max-width: 100px; height: auto; "/> Models for **(steerable) story-writing and role-playing**. <br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31). </div> ## Resources - [**Opus V1 prompting guide**](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy. - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`. - [Python code](example/prompt/format.py) to format the prompt correctly. <img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style=" padding: 12px; border-radius: 12px; border: 2px solid #f9a8d4; background: rgb(9, 9, 11); "/> ## Prompting <details> <summary>The models use an extended version of ChatML.</summary> ``` <|im_start|>system (Story description in the right format here) (Typically consists of plot description, style description and characters)<|im_end|> <|im_start|>user (Your instruction on how the story should continue)<|im_end|> <|im_start|>text names= Alice (Continuation of the story from the Alice character)<|im_end|> <|im_start|>text (Continuation of the story from no character in particular (pure narration))<|im_end|> <|im_start|>user (Your instruction on how the story should continue)<|im_end|> <|im_start|>text names= Bob (Continuation of the story from the Bob character)<|im_end|> ``` The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names. Pay attention to the following: - The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play. - There can be multiple subsequent message with a `text` role, especially if names are involved. - There can be multiple names attached to a message. - The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names. </details> While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance. Here's how you can prompt the model for the following tasks - Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing): - Input: - System prompt: You provide story / role-play description, which consists of: - Plot description - Style description - Characters and their descriptions - Conversation turns: - Text / message turn: This represents part of the story or role play - Instruction: This tells the model what should happen next - Output: Continuation of the story / role-play. - [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description) - Input: A story, or a few chapters of a story. - Output: A description of the story or chapters. - [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description) - Input: A story, or a few chapters of a story, set of characters. - Output: A description of the characters. - [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description) - Input: A story, or a few chapters of a story. - Output: A description the style of the story. - [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions) - Input: A brief plot description and the desired number of chapters. - Output: A description for each chapter. - And more... ### Sampling params For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`. You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures. ## Dataset The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long. All story-writing and role-playing examples were based on human-written text. ![token count distribution](images/token_count_cum__token_bucket.png) ## Running the model The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization. I recommend using these model versions: - 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b) - 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq) ### Running on DreamGen.com (free) You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required. ### Running Locally - **Make sure your prompt is as close as possible to the Opus V1** - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly. - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1) - [Read the prompt formatting code](example/prompt/format.py) - Make sure `<|im_start|>` and `<|im_end|>` are tokenized correctly - **vLLM** - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU. - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario. - **SillyTavern** - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp) - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect - **LM Studio** - [Config](configs/lmstudio/preset.json) - Just like ChatML, just changed "assistant" to "text" role. - **HuggingFace** - [Chat template](tokenizer_config.json#L51) - Just like ChatML, just changed "assistant" to "text" role. ## Known Issues - **34B tokenization**: - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))). - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token. - Overall impact should be minor. - **34B repetition**: - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes. - **GGUF**: - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version. - **Ooba**: - The tokenization might be messed up. Some users reported that `<|im_start|>` and `<|im_end|>` are tokenized as multiple tokens. ## Community Join the DreamGen community on [**Discord**](https://dreamgen.com/discord) to get early access to new models. ## License - This model is intended for personal use only, other use is not permitted. --- # DreamGen Opus V1 <div style="display: flex; flex-direction: row; align-items: center;"> <img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style=" border-radius: 12px; margin-right: 12px; margin-top: 0px; margin-bottom: 0px; max-width: 100px; height: auto; "/> Models for **(steerable) story-writing and role-playing**. <br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31). </div> ## Resources - [**Opus V1 prompting guide**](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy. - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`. - [Python code](example/prompt/format.py) to format the prompt correctly. <img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style=" padding: 12px; border-radius: 12px; border: 2px solid #f9a8d4; background: rgb(9, 9, 11); "/> ## Prompting <details> <summary>The models use an extended version of ChatML.</summary> ``` <|im_start|>system (Story description in the right format here) (Typically consists of plot description, style description and characters)<|im_end|> <|im_start|>user (Your instruction on how the story should continue)<|im_end|> <|im_start|>text names= Alice (Continuation of the story from the Alice character)<|im_end|> <|im_start|>text (Continuation of the story from no character in particular (pure narration))<|im_end|> <|im_start|>user (Your instruction on how the story should continue)<|im_end|> <|im_start|>text names= Bob (Continuation of the story from the Bob character)<|im_end|> ``` The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names. Pay attention to the following: - The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play. - There can be multiple subsequent message with a `text` role, especially if names are involved. - There can be multiple names attached to a message. - The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names. </details> While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance. Here's how you can prompt the model for the following tasks - Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing): - Input: - System prompt: You provide story / role-play description, which consists of: - Plot description - Style description - Characters and their descriptions - Conversation turns: - Text / message turn: This represents part of the story or role play - Instruction: This tells the model what should happen next - Output: Continuation of the story / role-play. - [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description) - Input: A story, or a few chapters of a story. - Output: A description of the story or chapters. - [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description) - Input: A story, or a few chapters of a story, set of characters. - Output: A description of the characters. - [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description) - Input: A story, or a few chapters of a story. - Output: A description the style of the story. - [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions) - Input: A brief plot description and the desired number of chapters. - Output: A description for each chapter. - And more... ### Sampling params For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`. You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures. ## Dataset The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long. All story-writing and role-playing examples were based on human-written text. ![token count distribution](images/token_count_cum__token_bucket.png) ## Running the model The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization. I recommend using these model versions: - 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b) - 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq) ### Running on DreamGen.com (free) You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required. ### Running Locally - **Make sure your prompt is as close as possible to the Opus V1** - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly. - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1) - [Read the prompt formatting code](example/prompt/format.py) - Make sure `<|im_start|>` and `<|im_end|>` are tokenized correctly - **vLLM** - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU. - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario. - **SillyTavern** - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp) - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect - **LM Studio** - [Config](configs/lmstudio/preset.json) - Just like ChatML, just changed "assistant" to "text" role. - **HuggingFace** - [Chat template](tokenizer_config.json#L51) - Just like ChatML, just changed "assistant" to "text" role. ## Known Issues - **34B tokenization**: - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))). - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token. - Overall impact should be minor. - **34B repetition**: - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes. - **GGUF**: - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version. - **Ooba**: - The tokenization might be messed up. Some users reported that `<|im_start|>` and `<|im_end|>` are tokenized as multiple tokens. ## Community Join the DreamGen community on [**Discord**](https://dreamgen.com/discord) to get early access to new models. ## License - This model is intended for personal use only, other use is not permitted.

DimalChathuranga/marian-finetuned-kde4-en-to-fr

DimalChathuranga

2024-02-27T09:55:34Z

104

0

transformers

[ "transformers", "tensorboard", "safetensors", "marian", "text2text-generation", "translation", "generated_from_trainer", "base_model:Helsinki-NLP/opus-mt-en-fr", "base_model:finetune:Helsinki-NLP/opus-mt-en-fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]

translation

2024-02-27T06:34:32Z

--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-fr tags: - translation - generated_from_trainer model-index: - name: marian-finetuned-kde4-en-to-fr results: [] ---  # marian-finetuned-kde4-en-to-fr This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Tokenizers 0.15.2

Stopwolf/Mustra-7B-Instruct-v0.1

Stopwolf

2024-02-27T09:54:35Z

46

1

transformers

[ "transformers", "safetensors", "mistral", "text-generation", "merge", "mergekit", "lazymergekit", "gordicaleksa/YugoGPT", "mistralai/Mistral-7B-Instruct-v0.2", "conversational", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T09:50:23Z

--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - gordicaleksa/YugoGPT - mistralai/Mistral-7B-Instruct-v0.2 --- # Mustra-7B-Instruct-v0.1 Mustra-7B-Instruct-v0.1 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit): * [gordicaleksa/YugoGPT](https://huggingface.co/gordicaleksa/YugoGPT) * [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) ## 🧩 Configuration ```yaml slices: - sources: - model: gordicaleksa/YugoGPT layer_range: [0, 32] - model: mistralai/Mistral-7B-Instruct-v0.2 layer_range: [0, 32] merge_method: slerp base_model: mistralai/Mistral-7B-Instruct-v0.2 parameters: t: - filter: self_attn value: [0, 0.5, 0.3, 0.7, 1] - filter: mlp value: [1, 0.5, 0.7, 0.3, 0] - value: 0.75 dtype: bfloat16 ```

FINNUMBER/Yi-Ko-6B-Finch-NQA-FULL-Hyper-epoch3

FINNUMBER

2024-02-27T09:48:29Z

4

0

transformers

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

text-generation

2024-02-27T07:20:29Z

--- 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]

yvelos/Annotator_4_Mi

yvelos

2024-02-27T09:46:18Z

0

transformers

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

text-generation

2024-02-23T20:06:31Z

--- library_name: transformers pipeline_tag: text-generation --- # 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]

Jhanu/my-pet-dog

Jhanu

2024-02-27T09:38:44Z

0

diffusers

[ "diffusers", "safetensors", "NxtWave-GenAI-Webinar", "text-to-image", "stable-diffusion", "license:creativeml-openrail-m", "autotrain_compatible", "endpoints_compatible", "diffusers:StableDiffusionPipeline", "region:us" ]

text-to-image

2024-02-27T09:32:59Z

--- license: creativeml-openrail-m tags: - NxtWave-GenAI-Webinar - text-to-image - stable-diffusion --- ### My-Pet-Dog Dreambooth model trained by Jhanu following the "Build your own Gen AI model" session by NxtWave. Project Submission Code: GoX19932gAS Sample pictures of this concept: ![0](https://huggingface.co/Jhanu/my-pet-dog/resolve/main/sample_images/dog.jpg)

orzhan/bart-transcription-aggregation

orzhan

2024-02-27T09:38:24Z

108

0

transformers

[ "transformers", "pytorch", "safetensors", "bart", "text2text-generation", "ru", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text2text-generation

2022-03-02T23:29:05Z

--- language: ru --- BART model fine-tuned to aggregate crowd-sourced transcriptions. Repository: [GitHub](https://github.com/orzhan/bart-transcription-aggregation)

JinghuiLuAstronaut/PaDeLLM_llama2_7b_ace05

JinghuiLuAstronaut

2024-02-27T09:38:11Z

6

1

transformers

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

text-generation

2024-02-27T02:39:31Z

Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER

JinghuiLuAstronaut/PaDeLLM_llama2_7b_conll03

JinghuiLuAstronaut

2024-02-27T09:37:41Z

5

1

transformers

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

text-generation

2024-02-27T02:21:01Z

Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER

JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_resume

JinghuiLuAstronaut

2024-02-27T09:37:22Z

6

0

transformers

[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-26T09:00:16Z

Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER

habout632/EvolCodeLlama-7b

habout632

2024-02-27T09:35:24Z

3

0

peft

[ "peft", "safetensors", "llama", "axolotl", "generated_from_trainer", "base_model:codellama/CodeLlama-7b-hf", "base_model:adapter:codellama/CodeLlama-7b-hf", "license:llama2", "4-bit", "bitsandbytes", "region:us" ]

null

2024-02-27T08:18:15Z

--- license: llama2 library_name: peft tags: - axolotl - generated_from_trainer base_model: codellama/CodeLlama-7b-hf model-index: - name: EvolCodeLlama-7b results: [] ---  [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) <details><summary>See axolotl config</summary> axolotl version: `0.4.0` ```yaml base_model: codellama/CodeLlama-7b-hf base_model_config: codellama/CodeLlama-7b-hf model_type: LlamaForCausalLM tokenizer_type: LlamaTokenizer is_llama_derived_model: true hub_model_id: EvolCodeLlama-7b load_in_8bit: false load_in_4bit: true strict: false datasets: - path: mlabonne/Evol-Instruct-Python-1k type: alpaca dataset_prepared_path: last_run_prepared val_set_size: 0.02 output_dir: ./qlora-out adapter: qlora lora_model_dir: sequence_len: 2048 sample_packing: true lora_r: 32 lora_alpha: 16 lora_dropout: 0.05 lora_target_modules: lora_target_linear: true lora_fan_in_fan_out: wandb_project: axolotl wandb_entity: wandb_watch: wandb_run_id: wandb_log_model: gradient_accumulation_steps: 4 micro_batch_size: 2 num_epochs: 3 optimizer: paged_adamw_32bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: false gradient_checkpointing: true early_stopping_patience: resume_from_checkpoint: local_rank: logging_steps: 1 xformers_attention: flash_attention: true warmup_steps: 100 eval_steps: 0.01 save_strategy: epoch save_steps: debug: deepspeed: weight_decay: 0.0 fsdp: fsdp_config: special_tokens: bos_token: "<s>" eos_token: "</s>" unk_token: "<unk>" ``` </details><br> # EvolCodeLlama-7b This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3796 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.3178 | 0.01 | 1 | 0.5311 | | 0.3147 | 0.03 | 4 | 0.5312 | | 0.3626 | 0.07 | 8 | 0.5310 | | 0.6265 | 0.1 | 12 | 0.5296 | | 0.429 | 0.14 | 16 | 0.5270 | | 0.5086 | 0.17 | 20 | 0.5205 | | 0.4335 | 0.21 | 24 | 0.5067 | | 0.3383 | 0.24 | 28 | 0.4842 | | 0.3688 | 0.28 | 32 | 0.4603 | | 0.2528 | 0.31 | 36 | 0.4403 | | 0.3105 | 0.35 | 40 | 0.4251 | | 0.4936 | 0.38 | 44 | 0.4162 | | 0.4146 | 0.42 | 48 | 0.4086 | | 0.3327 | 0.45 | 52 | 0.4024 | | 0.3429 | 0.48 | 56 | 0.3971 | | 0.3328 | 0.52 | 60 | 0.3937 | | 0.1844 | 0.55 | 64 | 0.3901 | | 0.3001 | 0.59 | 68 | 0.3887 | | 0.3632 | 0.62 | 72 | 0.3872 | | 0.1997 | 0.66 | 76 | 0.3847 | | 0.2461 | 0.69 | 80 | 0.3823 | | 0.2865 | 0.73 | 84 | 0.3812 | | 0.26 | 0.76 | 88 | 0.3805 | | 0.3191 | 0.8 | 92 | 0.3792 | | 0.4642 | 0.83 | 96 | 0.3763 | | 0.2649 | 0.87 | 100 | 0.3750 | | 0.2095 | 0.9 | 104 | 0.3727 | | 0.2738 | 0.94 | 108 | 0.3737 | | 0.4274 | 0.97 | 112 | 0.3730 | | 0.2722 | 1.0 | 116 | 0.3724 | | 0.2164 | 1.02 | 120 | 0.3705 | | 0.1549 | 1.05 | 124 | 0.3726 | | 0.3051 | 1.08 | 128 | 0.3725 | | 0.1873 | 1.12 | 132 | 0.3730 | | 0.3388 | 1.15 | 136 | 0.3738 | | 0.2504 | 1.19 | 140 | 0.3741 | | 0.2851 | 1.22 | 144 | 0.3714 | | 0.2365 | 1.26 | 148 | 0.3690 | | 0.3986 | 1.29 | 152 | 0.3699 | | 0.1913 | 1.33 | 156 | 0.3720 | | 0.1963 | 1.36 | 160 | 0.3698 | | 0.1824 | 1.4 | 164 | 0.3679 | | 0.1453 | 1.43 | 168 | 0.3685 | | 0.3073 | 1.47 | 172 | 0.3702 | | 0.1501 | 1.5 | 176 | 0.3692 | | 0.2167 | 1.53 | 180 | 0.3662 | | 0.3007 | 1.57 | 184 | 0.3660 | | 0.2203 | 1.6 | 188 | 0.3666 | | 0.3978 | 1.64 | 192 | 0.3669 | | 0.2397 | 1.67 | 196 | 0.3663 | | 0.2161 | 1.71 | 200 | 0.3656 | | 0.2593 | 1.74 | 204 | 0.3651 | | 0.2113 | 1.78 | 208 | 0.3658 | | 0.2435 | 1.81 | 212 | 0.3657 | | 0.2625 | 1.85 | 216 | 0.3639 | | 0.302 | 1.88 | 220 | 0.3624 | | 0.2556 | 1.92 | 224 | 0.3611 | | 0.2063 | 1.95 | 228 | 0.3609 | | 0.1994 | 1.98 | 232 | 0.3612 | | 0.2229 | 2.02 | 236 | 0.3613 | | 0.1983 | 2.03 | 240 | 0.3634 | | 0.1925 | 2.06 | 244 | 0.3725 | | 0.1778 | 2.1 | 248 | 0.3832 | | 0.1293 | 2.13 | 252 | 0.3834 | | 0.2166 | 2.16 | 256 | 0.3789 | | 0.2082 | 2.2 | 260 | 0.3760 | | 0.1858 | 2.23 | 264 | 0.3761 | | 0.1862 | 2.27 | 268 | 0.3763 | | 0.1619 | 2.3 | 272 | 0.3783 | | 0.174 | 2.34 | 276 | 0.3786 | | 0.2414 | 2.37 | 280 | 0.3790 | | 0.1977 | 2.41 | 284 | 0.3783 | | 0.1678 | 2.44 | 288 | 0.3784 | | 0.2263 | 2.48 | 292 | 0.3786 | | 0.082 | 2.51 | 296 | 0.3783 | | 0.2621 | 2.55 | 300 | 0.3784 | | 0.1754 | 2.58 | 304 | 0.3795 | | 0.1957 | 2.61 | 308 | 0.3802 | | 0.1203 | 2.65 | 312 | 0.3803 | | 0.1388 | 2.68 | 316 | 0.3796 | | 0.1699 | 2.72 | 320 | 0.3796 | | 0.161 | 2.75 | 324 | 0.3796 | | 0.2394 | 2.79 | 328 | 0.3792 | | 0.1465 | 2.82 | 332 | 0.3795 | | 0.1746 | 2.86 | 336 | 0.3794 | | 0.1839 | 2.89 | 340 | 0.3795 | | 0.1581 | 2.93 | 344 | 0.3796 | ### Framework versions - PEFT 0.8.2 - Transformers 4.39.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.17.1 - Tokenizers 0.15.0

JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_msra

JinghuiLuAstronaut

2024-02-27T09:29:17Z

3

0

transformers

[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T03:32:04Z

Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER

JinghuiLuAstronaut/PaDeLLM_baichuan2_7b_weibo

JinghuiLuAstronaut

2024-02-27T09:28:36Z

4

0

transformers

[ "transformers", "safetensors", "baichuan", "text-generation", "custom_code", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T04:15:20Z

Inference code see https://github.com/GeorgeLuImmortal/PaDeLLM_NER

DatPySci/pythia-1b-kto-iter0

DatPySci

2024-02-27T09:27:03Z

116

0

transformers

[ "transformers", "safetensors", "gpt_neox", "text-generation", "alignment-handbook", "generated_from_trainer", "conversational", "dataset:DatPySci/iter0", "base_model:DatPySci/pythia-1b-sft-full", "base_model:finetune:DatPySci/pythia-1b-sft-full", "license:apache-2.0", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T04:29:58Z

--- license: apache-2.0 base_model: DatPySci/pythia-1b-sft-full tags: - alignment-handbook - generated_from_trainer datasets: - DatPySci/iter0 model-index: - name: pythia-1b-kto-iter0 results: [] ---  # pythia-1b-kto-iter0 This model is a fine-tuned version of [DatPySci/pythia-1b-sft-full](https://huggingface.co/DatPySci/pythia-1b-sft-full) on the DatPySci/iter0 dataset. It achieves the following results on the evaluation set: - Loss: 0.2591 - Rewards/real: 0.0604 - Rewards/generated: -1.0267 - Rewards/accuracies: 0.9460 - Rewards/margins: 1.0871 - Logps/generated: -570.8114 - Logps/real: -468.1696 - Logits/generated: 0.2253 - Logits/real: -0.2820 ## 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-07 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - total_eval_batch_size: 8 - 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/real | Rewards/generated | Rewards/accuracies | Rewards/margins | Logps/generated | Logps/real | Logits/generated | Logits/real | |:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------------:|:------------------:|:---------------:|:---------------:|:----------:|:----------------:|:-----------:| | 0.2932 | 0.38 | 300 | 0.2962 | 0.0718 | -0.7855 | 0.9220 | 0.8572 | -568.3989 | -468.0556 | 0.2554 | -0.2530 | | 0.2689 | 0.77 | 600 | 0.2591 | 0.0604 | -1.0267 | 0.9460 | 1.0871 | -570.8114 | -468.1696 | 0.2253 | -0.2820 | ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1 - Datasets 2.17.1 - Tokenizers 0.15.2

Ayus077BCT014Bhandari/vartat5-using-100K-plus-23

Ayus077BCT014Bhandari

2024-02-27T09:22:02Z

106

0

transformers

[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text2text-generation

2024-02-27T06:25:30Z

--- 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]

hellod035/ppo-Huggy

hellod035

2024-02-27T09:21:55Z

0

ml-agents

[ "ml-agents", "tensorboard", "onnx", "Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy", "region:us" ]

reinforcement-learning

2024-02-27T09:21:49Z

--- library_name: ml-agents tags: - Huggy - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Huggy --- # **ppo** Agent playing **Huggy** This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume ``` ### Watch your Agent play You can watch your agent **playing directly in your browser** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: hellod035/ppo-Huggy 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀

archiMAD/LunarLander-ppo-from-scratch

archiMAD

2024-02-27T09:20:34Z

0

null

[ "tensorboard", "LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course", "model-index", "region:us" ]

reinforcement-learning

2024-02-27T09:20:18Z

--- tags: - LunarLander-v2 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-course model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: 76.00 +/- 114.11 name: mean_reward verified: false --- # PPO Agent Playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2. # Hyperparameters ```python {'exp_name': 'ppo' 'seed': 1 'torch_deterministic': True 'cuda': True 'track': False 'wandb_project_name': 'cleanRL' 'wandb_entity': None 'capture_video': False 'env_id': 'LunarLander-v2' 'total_timesteps': 500000 'learning_rate': 0.00025 'num_envs': 4 'num_steps': 1024 'anneal_lr': True 'gae': True 'gamma': 0.99 'gae_lambda': 0.95 'num_minibatches': 64 'update_epochs': 4 'norm_adv': True 'clip_coef': 0.2 'clip_vloss': True 'ent_coef': 0.01 'vf_coef': 0.5 'max_grad_norm': 0.5 'target_kl': None 'repo_id': 'archiMAD/LunarLander-ppo-from-scratch' 'batch_size': 4096 'minibatch_size': 64} ```

nagyadam0616/zephyr-x-twitter-5epocs-full-2

nagyadam0616

2024-02-27T09:20:15Z

4

0

transformers

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

text-generation

2024-02-27T08:56:43Z

--- 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]

mhmmterts/fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens

mhmmterts

2024-02-27T09:16:52Z

106

0

transformers

[ "transformers", "safetensors", "roberta", "text-classification", "generated_from_trainer", "dataset:swiss_judgment_prediction", "base_model:joelniklaus/legal-swiss-roberta-large", "base_model:finetune:joelniklaus/legal-swiss-roberta-large", "license:cc", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]

text-classification

2024-02-27T09:15:43Z

--- license: cc base_model: joelniklaus/legal-swiss-roberta-large tags: - generated_from_trainer datasets: - swiss_judgment_prediction metrics: - accuracy model-index: - name: fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens results: - task: name: Text Classification type: text-classification dataset: name: swiss_judgment_prediction type: swiss_judgment_prediction config: it split: test args: it metrics: - name: Accuracy type: accuracy value: 0.8177339901477833 ---  # fine_tuned_model_on_SJP_dataset_it_balanced_2048_tokens This model is a fine-tuned version of [joelniklaus/legal-swiss-roberta-large](https://huggingface.co/joelniklaus/legal-swiss-roberta-large) on the swiss_judgment_prediction dataset. It achieves the following results on the evaluation set: - Loss: 0.7964 - Accuracy: 0.8177 ## 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: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7513 | 1.0 | 768 | 0.6783 | 0.7956 | | 0.6008 | 2.0 | 1536 | 0.7964 | 0.8177 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.0+cu118 - Datasets 2.17.0 - Tokenizers 0.15.1

vlada-v/whisper-small-hi

vlada-v

2024-02-27T09:07:39Z

76

0

transformers

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

automatic-speech-recognition

2024-02-09T07:37:40Z

--- language: - en license: apache-2.0 base_model: openai/whisper-small tags: - hf-asr-leaderboard - generated_from_trainer metrics: - wer model-index: - name: Whisper Small Hi - Kids results: [] ---  # Whisper Small Hi - Kids This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the PRG Dataset dataset. It achieves the following results on the evaluation set: - Loss: 2.4077 - Wer: 95.2005 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 100 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.38.1 - Pytorch 2.2.1+cu121 - Datasets 2.17.1 - Tokenizers 0.15.2

alexandrabenamar/Mistral-7B-Instruct-v0.2-4Magic

alexandrabenamar

2024-02-27T09:07:08Z

4

1

transformers

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

text-generation

2024-02-27T08:42:45Z

--- 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]

tomaszki/nous-gemma-four

tomaszki

2024-02-27T09:06:37Z

112

0

transformers

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

text-generation

2024-02-27T09:03:59Z

--- 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]

ann-lab52/quan-1.8b-base-AWQ

ann-lab52

2024-02-27T08:59:41Z

76

0

transformers

[ "transformers", "pytorch", "safetensors", "llama", "text-generation", "license:other", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]

text-generation

2024-02-27T08:39:26Z

--- license: other license_name: quan license_link: https://huggingface.co/qnguyen3/quan-1.8b-base ---

Bong9/assemblydata

Bong9

2024-02-27T08:56:34Z

0

transformers

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

null

2024-02-27T08:53:39Z

--- 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]

Reniyas/phi-2-classification-merged

Reniyas

2024-02-27T08:54:15Z

48

0

transformers

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

text-generation

2024-02-27T08:49:52Z

--- 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]

internlm/internlm-xcomposer2-7b-4bit

internlm

2024-02-27T08:43:16Z

41

10

transformers

[ "transformers", "internlm", "feature-extraction", "text-generation", "custom_code", "arxiv:2401.16420", "license:other", "region:us" ]

text-generation

2024-02-06T12:38:00Z

--- license: other pipeline_tag: text-generation --- <p align="center"> <img src="logo_en.png" width="400"/> <p> <p align="center"> <b><font size="6">InternLM-XComposer2</font></b> <p> <div align="center"> [💻Github Repo](https://github.com/InternLM/InternLM-XComposer) [Paper](https://arxiv.org/abs/2401.16420) </div> **InternLM-XComposer2** is a vision-language large model (VLLM) based on [InternLM2](https://github.com/InternLM/InternLM) for advanced text-image comprehension and composition. We release InternLM-XComposer2 series in two versions: - InternLM-XComposer2-VL: The pretrained VLLM model with InternLM2 as the initialization of the LLM, achieving strong performance on various multimodal benchmarks. - InternLM-XComposer2: The finetuned VLLM for *Free-from Interleaved Text-Image Composition*. This is the 4-bit version of InternLM-XComposer2, install the latest version of [auto_gptq](https://github.com/AutoGPTQ/AutoGPTQ#quick-installation) before using. ```python import torch, auto_gptq from PIL import Image from transformers import AutoModel, AutoTokenizer from auto_gptq.modeling import BaseGPTQForCausalLM auto_gptq.modeling._base.SUPPORTED_MODELS = ["internlm"] torch.set_grad_enabled(False) class InternLMXComposer2QForCausalLM(BaseGPTQForCausalLM): layers_block_name = "model.layers" outside_layer_modules = [ 'vit', 'vision_proj', 'model.tok_embeddings', 'model.norm', 'output', ] inside_layer_modules = [ ["attention.wqkv.linear"], ["attention.wo.linear"], ["feed_forward.w1.linear", "feed_forward.w3.linear"], ["feed_forward.w2.linear"], ] # init model and tokenizer model = InternLMXComposer2QForCausalLM.from_quantized( 'internlm/internlm-xcomposer2-7b-4bit', trust_remote_code=True, device="cuda:0").eval() tokenizer = AutoTokenizer.from_pretrained( 'internlm/internlm-xcomposer2-7b-4bit', trust_remote_code=True) img_path_list = [ 'panda.jpg', 'bamboo.jpeg', ] images = [] for img_path in img_path_list: image = Image.open(img_path).convert("RGB") image = model.vis_processor(image) images.append(image) image = torch.stack(images) query = '<ImageHere> <ImageHere>please write an article based on the images. Title: my favorite animal.' with torch.cuda.amp.autocast(): response, history = model.chat(tokenizer, query=query, image=image, history=[], do_sample=False) print(response) #My Favorite Animal: The Panda #The panda, also known as the giant panda, is one of the most beloved animals in the world. These adorable creatures are native to China and can be found in the wild in a few select locations, but they are more commonly seen in captivity at zoos or wildlife reserves. #Pandas have a distinct black-and-white coloration that makes them instantly recognizable. They are known for their love of bamboo, which they eat almost exclusively. In fact, pandas spend up to 14 hours a day eating, with the majority of their diet consisting of bamboo. Despite this seemingly unbalanced diet, pandas are actually quite healthy and have a low body fat percentage, thanks to their ability to digest bamboo efficiently. #In addition to their unique eating habits, pandas are also known for their playful personalities. They are intelligent and curious creatures, often engaging in activities like playing with toys or climbing trees. However, they do not typically exhibit these behaviors in the wild, where they are solitary creatures who prefer to spend their time alone. #One of the biggest threats to the panda's survival is habitat loss due to deforestation. As a result, many pandas now live in captivity, where they are cared for by dedicated staff and provided with enrichment opportunities to keep them engaged and stimulated. While it is important to protect these animals from extinction, it is also crucial to remember that they are still wild creatures and should be treated with respect and care. #Overall, the panda is an amazing animal that has captured the hearts of people around the world. Whether you see them in the wild or in captivity, there is no denying the charm and allure of these gentle giants. ``` ### Open Source License The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact [email protected].