--- base_model: dmis-lab/biobert-v1.1 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: cer_model results: [] --- # cer_model 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: nan - Precision: 0.0 - Recall: 0.0 - F1: 0.0 - Accuracy: 0.5235 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:| | 0.0 | 1.0 | 5178 | nan | 0.0 | 0.0 | 0.0 | 0.5235 | ### Framework versions - Transformers 4.37.0 - Pytorch 2.1.2 - Datasets 2.1.0 - Tokenizers 0.15.1