| --- |
| base_model: dmis-lab/biobert-v1.1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: contrast_classifier_bio_bert |
| 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. --> |
|
|
| # contrast_classifier_bio_bert |
| |
| This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1097 |
| - Accuracy: 0.9857 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 12 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0075 | 1.0 | 18 | 0.2757 | 0.9286 | |
| | 0.0024 | 2.0 | 36 | 0.5377 | 0.8429 | |
| | 0.0009 | 3.0 | 54 | 0.1979 | 0.9714 | |
| | 0.0006 | 4.0 | 72 | 0.1630 | 0.9714 | |
| | 0.0004 | 5.0 | 90 | 0.1114 | 0.9857 | |
| | 0.0004 | 6.0 | 108 | 0.1033 | 0.9857 | |
| | 0.0003 | 7.0 | 126 | 0.1036 | 0.9857 | |
| | 0.0003 | 8.0 | 144 | 0.1067 | 0.9857 | |
| | 0.0003 | 9.0 | 162 | 0.1095 | 0.9857 | |
| | 0.0003 | 10.0 | 180 | 0.1094 | 0.9857 | |
| | 0.0002 | 11.0 | 198 | 0.1096 | 0.9857 | |
| | 0.0002 | 12.0 | 216 | 0.1097 | 0.9857 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.0 |
| - Tokenizers 0.15.0 |
| |
