| library_name: transformers | |
| base_model: medicalai/ClinicalBERT | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| model-index: | |
| - name: 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. --> | |
| # results | |
| This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.8614 | |
| - Accuracy: 0.6145 | |
| - Precision: 0.6243 | |
| - Recall: 0.6145 | |
| - F1: 0.5971 | |
| - Roc Auc: 0.8073 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Use adamw_torch 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 | Precision | Recall | F1 | Roc Auc | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:| | |
| | No log | 1.0 | 42 | 1.0433 | 0.4458 | 0.4351 | 0.4458 | 0.3685 | 0.7162 | | |
| | No log | 2.0 | 84 | 0.8946 | 0.5663 | 0.5641 | 0.5663 | 0.5559 | 0.7823 | | |
| | No log | 3.0 | 126 | 0.9142 | 0.5783 | 0.6385 | 0.5783 | 0.5332 | 0.7896 | | |
| | No log | 4.0 | 168 | 0.8497 | 0.6386 | 0.6434 | 0.6386 | 0.6299 | 0.8084 | | |
| | No log | 5.0 | 210 | 0.8614 | 0.6145 | 0.6243 | 0.6145 | 0.5971 | 0.8073 | | |
| ### Framework versions | |
| - Transformers 4.46.3 | |
| - Pytorch 2.5.1+cu121 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.20.3 | |