PV-Bio_clinicalBERT-superset
This model is a fine-tuned version of giacomomiolo/electramed_base_scivocab_1M on the pv_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2082
- Precision: 0.7056
- Recall: 0.7474
- F1: 0.7259
- Accuracy: 0.9657
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.063 | 1.0 | 1813 | 0.1061 | 0.6453 | 0.7306 | 0.6853 | 0.9623 |
| 0.0086 | 2.0 | 3626 | 0.1068 | 0.6620 | 0.7516 | 0.7040 | 0.9647 |
| 0.0089 | 3.0 | 5439 | 0.1265 | 0.7026 | 0.7300 | 0.7160 | 0.9657 |
| 0.004 | 4.0 | 7252 | 0.1369 | 0.6820 | 0.7601 | 0.7189 | 0.9638 |
| 0.0004 | 5.0 | 9065 | 0.1573 | 0.6937 | 0.7602 | 0.7254 | 0.9656 |
| 0.0184 | 6.0 | 10878 | 0.1707 | 0.7078 | 0.7475 | 0.7271 | 0.9662 |
| 0.0009 | 7.0 | 12691 | 0.1787 | 0.7116 | 0.7398 | 0.7254 | 0.9662 |
| 0.0006 | 8.0 | 14504 | 0.1874 | 0.6979 | 0.7576 | 0.7265 | 0.9655 |
| 0.0008 | 9.0 | 16317 | 0.1970 | 0.7083 | 0.7475 | 0.7273 | 0.9660 |
| 0.0003 | 10.0 | 18130 | 0.2082 | 0.7056 | 0.7474 | 0.7259 | 0.9657 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1