sentence-classifier
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: 0.3291
- Precision: 0.9236
- Recall: 0.9217
- Accuracy: 0.9219
- F1: 0.9221
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Precision |
Recall |
Accuracy |
F1 |
| No log |
1.0 |
154 |
0.3536 |
0.8783 |
0.8745 |
0.8747 |
0.8753 |
| No log |
2.0 |
308 |
0.2784 |
0.9132 |
0.9105 |
0.9105 |
0.9109 |
| No log |
3.0 |
462 |
0.2928 |
0.9189 |
0.9160 |
0.9162 |
0.9165 |
| 0.3402 |
4.0 |
616 |
0.3098 |
0.9239 |
0.9223 |
0.9227 |
0.9228 |
| 0.3402 |
5.0 |
770 |
0.3291 |
0.9236 |
0.9217 |
0.9219 |
0.9221 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
