--- base_model: medicalai/ClinicalBERT tags: - generated_from_trainer model-index: - name: BC5CDR_ClinicalBERT_NER results: [] --- # BC5CDR_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: 0.1107 - Seqeval classification report: precision recall f1-score support Chemical 0.71 0.73 0.72 10493 Disease 0.82 0.82 0.82 6944 micro avg 0.75 0.77 0.76 17437 macro avg 0.76 0.78 0.77 17437 weighted avg 0.75 0.77 0.76 17437 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | No log | 1.0 | 143 | 0.1255 | precision recall f1-score support Chemical 0.67 0.68 0.68 10493 Disease 0.79 0.78 0.78 6944 micro avg 0.72 0.72 0.72 17437 macro avg 0.73 0.73 0.73 17437 weighted avg 0.72 0.72 0.72 17437 | | No log | 2.0 | 286 | 0.1160 | precision recall f1-score support Chemical 0.69 0.71 0.70 10493 Disease 0.77 0.83 0.80 6944 micro avg 0.72 0.76 0.74 17437 macro avg 0.73 0.77 0.75 17437 weighted avg 0.72 0.76 0.74 17437 | | No log | 3.0 | 429 | 0.1107 | precision recall f1-score support Chemical 0.71 0.73 0.72 10493 Disease 0.82 0.82 0.82 6944 micro avg 0.75 0.77 0.76 17437 macro avg 0.76 0.78 0.77 17437 weighted avg 0.75 0.77 0.76 17437 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0