| --- |
| base_model: dmis-lab/biobert-v1.1 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: contrast_classifier_biobert_v2 |
| 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_biobert_v2 |
| |
| 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: 0.0010 |
| - Accuracy: 1.0 |
| |
| ## 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.653 | 1.0 | 37 | 0.6146 | 0.7273 | |
| | 0.4263 | 2.0 | 74 | 0.2425 | 0.9697 | |
| | 0.1128 | 3.0 | 111 | 0.0098 | 1.0 | |
| | 0.0275 | 4.0 | 148 | 0.0031 | 1.0 | |
| | 0.003 | 5.0 | 185 | 0.0023 | 1.0 | |
| | 0.0023 | 6.0 | 222 | 0.0015 | 1.0 | |
| | 0.0018 | 7.0 | 259 | 0.0011 | 1.0 | |
| | 0.0015 | 8.0 | 296 | 0.0011 | 1.0 | |
| | 0.0016 | 9.0 | 333 | 0.0011 | 1.0 | |
| | 0.0222 | 10.0 | 370 | 0.0010 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
| |
