BioBERT_CRAFT_NER_new
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1158
- Precision: 0.9737
- Recall: 0.9752
- F1: 0.9745
- Accuracy: 0.9738
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: 3
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Precision |
Recall |
F1 |
Accuracy |
| 0.1991 |
1.0 |
695 |
0.1160 |
0.9713 |
0.9727 |
0.9720 |
0.9713 |
| 0.0529 |
2.0 |
1390 |
0.1123 |
0.9726 |
0.9744 |
0.9735 |
0.9729 |
| 0.0254 |
3.0 |
2085 |
0.1158 |
0.9737 |
0.9752 |
0.9745 |
0.9738 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
