| --- |
| library_name: transformers |
| license: mit |
| base_model: emilyalsentzer/Bio_ClinicalBERT |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: clinicalbert-medical-doc-classifier |
| 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. --> |
|
|
| # clinicalbert-medical-doc-classifier |
|
|
| This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0252 |
| - Accuracy: 0.9953 |
| - F1: 0.9948 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | 0.1238 | 0.1582 | 100 | 0.1158 | 0.9757 | 0.9679 | |
| | 0.0966 | 0.3165 | 200 | 0.0470 | 0.9924 | 0.9912 | |
| | 0.0269 | 0.4747 | 300 | 0.0364 | 0.9942 | 0.9931 | |
| | 0.0178 | 0.6329 | 400 | 0.0336 | 0.9947 | 0.9935 | |
| | 0.0428 | 0.7911 | 500 | 0.0327 | 0.9940 | 0.9933 | |
| | 0.0062 | 0.9494 | 600 | 0.0296 | 0.9949 | 0.9937 | |
| | 0.0370 | 1.1076 | 700 | 0.0262 | 0.9947 | 0.9935 | |
| | 0.0201 | 1.2658 | 800 | 0.0279 | 0.9947 | 0.9935 | |
| | 0.0231 | 1.4241 | 900 | 0.0252 | 0.9953 | 0.9948 | |
| | 0.0193 | 1.5823 | 1000 | 0.0249 | 0.9953 | 0.9942 | |
| | 0.0189 | 1.7405 | 1100 | 0.0263 | 0.9951 | 0.9941 | |
| | 0.0201 | 1.8987 | 1200 | 0.0256 | 0.9953 | 0.9947 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.4.0 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.4 |
| - Tokenizers 0.22.2 |
| |
