--- base_model: dmis-lab/biobert-v1.1 tags: - generated_from_trainer metrics: - accuracy model-index: - name: contrast_classifier_biobert_v2 results: [] --- # 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