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clinical-finetuned-data10
This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5795
- Accuracy: 0.8
- Precision: 0.8507
- Recall: 0.8507
- F1: 0.8507
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: 1e-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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4903 | 1.0 | 50 | 0.5799 | 0.65 | 0.8810 | 0.5522 | 0.6789 |
| 0.4553 | 2.0 | 100 | 0.5528 | 0.71 | 0.8958 | 0.6418 | 0.7478 |
| 0.3538 | 3.0 | 150 | 0.5463 | 0.76 | 0.8644 | 0.7612 | 0.8095 |
| 0.2954 | 4.0 | 200 | 0.5511 | 0.78 | 0.8462 | 0.8209 | 0.8333 |
| 0.2644 | 5.0 | 250 | 0.5869 | 0.79 | 0.8485 | 0.8358 | 0.8421 |
| 0.2108 | 6.0 | 300 | 0.5418 | 0.79 | 0.8594 | 0.8209 | 0.8397 |
| 0.1881 | 7.0 | 350 | 0.5622 | 0.81 | 0.8636 | 0.8507 | 0.8571 |
| 0.1602 | 8.0 | 400 | 0.5796 | 0.8 | 0.8507 | 0.8507 | 0.8507 |
| 0.1617 | 9.0 | 450 | 0.5795 | 0.8 | 0.8507 | 0.8507 | 0.8507 |
| 0.1561 | 10.0 | 500 | 0.5795 | 0.8 | 0.8507 | 0.8507 | 0.8507 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
