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Browse files- README (8).md +67 -0
- config (3).json +48 -0
- gitattributes (8) +34 -0
- gitignore (1) +1 -0
- pytorch_model (3).bin +3 -0
- special_tokens_map (2).json +7 -0
- tokenizer (1).json +0 -0
- tokenizer_config (2).json +16 -0
- training_args (1).bin +3 -0
- vocab (1).txt +0 -0
README (8).md
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---
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license: mit
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tags:
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- generated_from_trainer
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model-index:
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- name: Bio_ClinicalBERT-finetuned-medicalcondition
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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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# Bio_ClinicalBERT-finetuned-medicalcondition
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This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7201
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- F1 Score: 0.8254
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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: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.8002 | 1.0 | 1772 | 0.6327 | 0.7759 |
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| 0.5933 | 2.0 | 3544 | 0.5906 | 0.7934 |
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| 0.5015 | 3.0 | 5316 | 0.5768 | 0.8033 |
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| 0.4265 | 4.0 | 7088 | 0.5792 | 0.8099 |
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| 0.3698 | 5.0 | 8860 | 0.6030 | 0.8109 |
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| 0.3229 | 6.0 | 10632 | 0.6366 | 0.8167 |
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| 0.2907 | 7.0 | 12404 | 0.6671 | 0.8198 |
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| 0.2649 | 8.0 | 14176 | 0.6850 | 0.8237 |
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| 0.2477 | 9.0 | 15948 | 0.7072 | 0.8247 |
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| 0.2348 | 10.0 | 17720 | 0.7201 | 0.8254 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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config (3).json
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{
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"_name_or_path": "emilyalsentzer/Bio_ClinicalBERT",
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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": "Pain",
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"1": "Depression",
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"2": "High Blood Pressure",
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"3": "Anxiety",
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"4": "Migraine",
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"5": "Diabetes, Type 2",
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"6": "Weight Loss",
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"7": "Insomnia",
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"8": "Obesity"
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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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"Anxiety": 3,
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"Depression": 1,
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"Diabetes, Type 2": 5,
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"High Blood Pressure": 2,
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"Insomnia": 7,
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"Migraine": 4,
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"Obesity": 8,
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"Pain": 0,
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"Weight Loss": 6
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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": "4.25.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 28996
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}
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gitattributes (8)
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gitignore (1)
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checkpoint-*/
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pytorch_model (3).bin
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special_tokens_map (2).json
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"mask_token": "[MASK]",
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tokenizer (1).json
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tokenizer_config (2).json
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training_args (1).bin
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vocab (1).txt
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