Delete qa
Browse files- qa/README.md +0 -55
- qa/all_results.json +0 -15
- qa/config.json +0 -26
- qa/eval_nbest_predictions.json +0 -3
- qa/eval_predictions.json +0 -0
- qa/eval_results.json +0 -9
- qa/model.safetensors +0 -3
- qa/runs/May15_03-24-14_cs-Precision-7960-Tower/events.out.tfevents.1747293859.cs-Precision-7960-Tower.147971.0 +0 -3
- qa/runs/May15_03-24-14_cs-Precision-7960-Tower/events.out.tfevents.1747297197.cs-Precision-7960-Tower.147971.1 +0 -3
- qa/special_tokens_map.json +0 -7
- qa/tokenizer.json +0 -0
- qa/tokenizer_config.json +0 -56
- qa/train_results.json +0 -9
- qa/trainer_state.json +0 -245
- qa/training_args.bin +0 -3
- qa/vocab.txt +0 -0
qa/README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google-bert/bert-base-uncased
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tags:
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- generated_from_trainer
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datasets:
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- squad
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model-index:
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- name: baseline
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# baseline
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the squad dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 12
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 2.0
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### Training results
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.6.0+cu118
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- Datasets 3.3.1
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- Tokenizers 0.21.0
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qa/all_results.json
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{
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"epoch": 2.0,
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"eval_exact_match": 81.49479659413434,
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"eval_f1": 88.62945564424126,
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"eval_runtime": 61.0301,
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"eval_samples": 10784,
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"eval_samples_per_second": 176.7,
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"eval_steps_per_second": 22.087,
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"total_flos": 3.541929151120589e+16,
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"train_loss": 1.148573803161563,
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"train_runtime": 3245.3985,
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"train_samples": 88524,
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"train_samples_per_second": 54.554,
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"train_steps_per_second": 4.546
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}
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qa/config.json
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{
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"_name_or_path": "google-bert/bert-base-uncased",
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"architectures": [
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"BertForQuestionAnswering"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.49.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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qa/eval_nbest_predictions.json
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qa/eval_predictions.json
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qa/eval_results.json
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qa/model.safetensors
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qa/special_tokens_map.json
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qa/tokenizer.json
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