--- base_model: dmis-lab/biobert-base-cased-v1.1 tags: - generated_from_trainer model-index: - name: ontochem_biobert_v2 results: [] --- # ontochem_biobert_v2 This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0345 ## 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: 1e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | No log | 1.0 | 96 | 0.5601 | | No log | 2.0 | 192 | 0.0588 | | No log | 3.0 | 288 | 0.0361 | | No log | 4.0 | 384 | 0.0325 | | No log | 5.0 | 480 | 0.0297 | | 0.2391 | 6.0 | 576 | 0.0320 | | 0.2391 | 7.0 | 672 | 0.0322 | | 0.2391 | 8.0 | 768 | 0.0319 | | 0.2391 | 9.0 | 864 | 0.0338 | | 0.2391 | 10.0 | 960 | 0.0345 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2