--- base_model: medicalai/ClinicalBERT tags: - generated_from_trainer model-index: - name: JNLPBA_ClinicalBERT_NER results: [] --- # JNLPBA_ClinicalBERT_NER This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1723 - Seqeval classification report: precision recall f1-score support DNA 0.72 0.81 0.77 1351 RNA 0.71 0.86 0.78 723 cell_line 0.84 0.74 0.78 582 cell_type 0.72 0.75 0.73 5623 protein 0.85 0.85 0.85 3501 micro avg 0.76 0.79 0.78 11780 macro avg 0.77 0.80 0.78 11780 weighted avg 0.76 0.79 0.78 11780 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | 0.336 | 1.0 | 582 | 0.1930 | precision recall f1-score support DNA 0.72 0.77 0.75 1351 RNA 0.70 0.84 0.77 723 cell_line 0.85 0.70 0.77 582 cell_type 0.71 0.68 0.69 5623 protein 0.85 0.80 0.83 3501 micro avg 0.76 0.74 0.75 11780 macro avg 0.77 0.76 0.76 11780 weighted avg 0.76 0.74 0.75 11780 | | 0.1841 | 2.0 | 1164 | 0.1762 | precision recall f1-score support DNA 0.73 0.78 0.76 1351 RNA 0.70 0.87 0.78 723 cell_line 0.86 0.71 0.78 582 cell_type 0.71 0.73 0.72 5623 protein 0.86 0.83 0.84 3501 micro avg 0.76 0.77 0.77 11780 macro avg 0.77 0.78 0.78 11780 weighted avg 0.77 0.77 0.77 11780 | | 0.1582 | 3.0 | 1746 | 0.1723 | precision recall f1-score support DNA 0.72 0.81 0.77 1351 RNA 0.71 0.86 0.78 723 cell_line 0.84 0.74 0.78 582 cell_type 0.72 0.75 0.73 5623 protein 0.85 0.85 0.85 3501 micro avg 0.76 0.79 0.78 11780 macro avg 0.77 0.80 0.78 11780 weighted avg 0.76 0.79 0.78 11780 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0