| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - epi_classify4_gard | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| base_model: dmis-lab/biobert-base-cased-v1.2 | |
| model-index: | |
| - name: results | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: epi_classify4_gard | |
| type: epi_classify4_gard | |
| args: default | |
| metrics: | |
| - type: precision | |
| value: 0.875 | |
| name: Precision | |
| - type: recall | |
| value: 0.9032258064516129 | |
| name: Recall | |
| - type: f1 | |
| value: 0.8888888888888888 | |
| name: F1 | |
| - type: accuracy | |
| value: 0.986 | |
| name: Accuracy | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # results | |
| 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 epi_classify4_gard dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0541 | |
| - Precision: 0.875 | |
| - Recall: 0.9032 | |
| - F1: 0.8889 | |
| - Accuracy: 0.986 | |
| ## 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: 16 | |
| - eval_batch_size: 8 | |
| - seed: 2 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4.0 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.12.5 | |
| - Pytorch 1.9.0+cu102 | |
| - Datasets 1.12.1 | |
| - Tokenizers 0.10.3 | |