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PubMedBERT-MNLI-MedNLI

Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
generated_from_trainer
Inference Endpoints
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  1. README.md +71 -0
  2. all_results.json +14 -0
  3. config.json +36 -0
  4. eval_results.json +9 -0
  5. predict_results_None.txt +1423 -0
  6. pytorch_model.bin +3 -0
  7. runs/Sep06_14-31-58_d62a17eebd0d/1662474745.8974035/events.out.tfevents.1662474745.d62a17eebd0d.419.1 +3 -0
  8. runs/Sep06_14-31-58_d62a17eebd0d/events.out.tfevents.1662474745.d62a17eebd0d.419.0 +3 -0
  9. runs/Sep06_14-31-58_d62a17eebd0d/events.out.tfevents.1662481494.d62a17eebd0d.419.2 +3 -0
  10. special_tokens_map.json +7 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +15 -0
  13. train_results.json +8 -0
  14. trainer_state.json +235 -0
  15. training_args.bin +3 -0
  16. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: best_model
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+ results: []
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+ ---
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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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+
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+ # best_model
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+
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+ This model is a fine-tuned version of [/content/drive/MyDrive/fine_tuned_models/pubmedbert_mnli_v3](https://huggingface.co//content/drive/MyDrive/fine_tuned_models/pubmedbert_mnli_v3) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9501
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+ - Accuracy: 0.8667
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5673 | 1.42 | 500 | 0.4358 | 0.8437 |
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+ | 0.2898 | 2.85 | 1000 | 0.4845 | 0.8523 |
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+ | 0.1669 | 4.27 | 1500 | 0.6233 | 0.8573 |
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+ | 0.1087 | 5.7 | 2000 | 0.7263 | 0.8573 |
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+ | 0.0728 | 7.12 | 2500 | 0.8841 | 0.8638 |
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+ | 0.0512 | 8.55 | 3000 | 0.9501 | 0.8667 |
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+ | 0.0372 | 9.97 | 3500 | 1.0440 | 0.8566 |
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+ | 0.0262 | 11.4 | 4000 | 1.0770 | 0.8609 |
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+ | 0.0243 | 12.82 | 4500 | 1.0931 | 0.8616 |
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+ | 0.023 | 14.25 | 5000 | 1.1088 | 0.8631 |
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+ | 0.0163 | 15.67 | 5500 | 1.1264 | 0.8581 |
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+ | 0.0111 | 17.09 | 6000 | 1.1541 | 0.8616 |
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+ | 0.0098 | 18.52 | 6500 | 1.1542 | 0.8631 |
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+ | 0.0074 | 19.94 | 7000 | 1.1653 | 0.8638 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.22.0.dev0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1
all_results.json ADDED
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+ {
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+ "epoch": 20.0,
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+ "eval_accuracy": 0.8666666746139526,
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+ "eval_loss": 0.9500740170478821,
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+ "eval_runtime": 13.4036,
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+ "eval_samples": 1395,
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+ "eval_samples_per_second": 104.076,
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+ "eval_steps_per_second": 3.283,
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+ "train_loss": 0.10057472327884626,
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+ "train_runtime": 6733.6679,
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+ "train_samples": 11232,
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+ "train_samples_per_second": 33.361,
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+ "train_steps_per_second": 1.043
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "/content/drive/MyDrive/fine_tuned_models/pubmedbert_mnli_v3",
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+ "architectures": [
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+ "BertForSequenceClassification"
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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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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "contradiction",
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+ "1": "entailment",
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+ "2": "neutral"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "contradiction": 0,
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+ "entailment": 1,
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+ "neutral": 2
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+ },
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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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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.22.0.dev0",
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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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+ }
eval_results.json ADDED
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+ {
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+ "epoch": 20.0,
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+ "eval_accuracy": 0.8666666746139526,
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+ "eval_loss": 0.9500740170478821,
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+ "eval_runtime": 13.4036,
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+ "eval_samples": 1395,
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+ "eval_samples_per_second": 104.076,
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+ "eval_steps_per_second": 3.283
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+ }
predict_results_None.txt ADDED
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