--- base_model: dmis-lab/biobert-v1.1 tags: - generated_from_trainer model-index: - name: JNLPBA_bioBERT_NER results: [] --- # JNLPBA_bioBERT_NER This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1445 - Seqeval classification report: precision recall f1-score support DNA 0.72 0.80 0.76 507 RNA 0.81 0.83 0.82 1593 cell_line 0.76 0.78 0.77 5750 cell_type 0.76 0.81 0.79 618 protein 0.81 0.81 0.81 1452 micro avg 0.77 0.80 0.78 9920 macro avg 0.77 0.81 0.79 9920 weighted avg 0.77 0.80 0.78 9920 ## 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 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Seqeval classification report | |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | 0.2687 | 1.0 | 582 | 0.1504 | precision recall f1-score support DNA 0.72 0.81 0.76 507 RNA 0.78 0.82 0.80 1593 cell_line 0.75 0.77 0.76 5750 cell_type 0.76 0.81 0.78 618 protein 0.80 0.81 0.80 1452 micro avg 0.76 0.79 0.77 9920 macro avg 0.76 0.80 0.78 9920 weighted avg 0.76 0.79 0.77 9920 | | 0.1412 | 2.0 | 1164 | 0.1461 | precision recall f1-score support DNA 0.72 0.81 0.76 507 RNA 0.83 0.79 0.81 1593 cell_line 0.75 0.77 0.76 5750 cell_type 0.75 0.82 0.78 618 protein 0.85 0.75 0.80 1452 micro avg 0.78 0.78 0.78 9920 macro avg 0.78 0.79 0.78 9920 weighted avg 0.78 0.78 0.78 9920 | | 0.1251 | 3.0 | 1746 | 0.1445 | precision recall f1-score support DNA 0.72 0.80 0.76 507 RNA 0.81 0.83 0.82 1593 cell_line 0.76 0.78 0.77 5750 cell_type 0.76 0.81 0.79 618 protein 0.81 0.81 0.81 1452 micro avg 0.77 0.80 0.78 9920 macro avg 0.77 0.81 0.79 9920 weighted avg 0.77 0.80 0.78 9920 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0