--- tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: biobert-base-cased-v1.2-finetuned-ner-CRAFT_English results: [] --- # biobert-base-cased-v1.2-finetuned-ner-CRAFT_English This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1614 - Precision: 0.8585 - Recall: 0.8623 - F1: 0.8604 - Accuracy: 0.9724 ## 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: 3e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.0725 | 1.0 | 1360 | 0.1242 | 0.8090 | 0.8698 | 0.8383 | 0.9681 | | 0.0281 | 2.0 | 2720 | 0.1541 | 0.8497 | 0.8549 | 0.8523 | 0.9705 | | 0.0162 | 3.0 | 4080 | 0.1510 | 0.8390 | 0.8681 | 0.8533 | 0.9711 | | 0.0053 | 4.0 | 5440 | 0.1614 | 0.8585 | 0.8623 | 0.8604 | 0.9724 | ### Framework versions - Transformers 4.17.0 - Pytorch 1.10.0+cu111 - Datasets 1.18.4 - Tokenizers 0.11.6