| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: phibert-finetuned-ner | |
| results: [] | |
| <!-- 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. --> | |
| # phibert-finetuned-ner | |
| 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: 0.0293 | |
| - Precision: 0.9238 | |
| - Recall: 0.9213 | |
| - F1: 0.9226 | |
| - Accuracy: 0.9950 | |
| ## 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: 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: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.0309 | 1.0 | 5728 | 0.0305 | 0.8977 | 0.9042 | 0.9009 | 0.9939 | | |
| | 0.0131 | 2.0 | 11456 | 0.0308 | 0.9089 | 0.9114 | 0.9102 | 0.9939 | | |
| | 0.008 | 3.0 | 17184 | 0.0293 | 0.9238 | 0.9213 | 0.9226 | 0.9950 | | |
| ### Framework versions | |
| - Transformers 4.26.0 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.9.0 | |
| - Tokenizers 0.13.2 | |