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AgitationTextV4
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: 0.5320
- Accuracy: 0.76
- Precision: 0.8507
- Recall: 0.8028
- F1: 0.8261
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 |
|---|---|---|---|---|---|---|---|
| 0.6223 | 1.0 | 50 | 0.6247 | 0.66 | 0.7403 | 0.8028 | 0.7703 |
| 0.5431 | 2.0 | 100 | 0.5636 | 0.66 | 0.9302 | 0.5634 | 0.7018 |
| 0.4361 | 3.0 | 150 | 0.5346 | 0.7 | 0.8475 | 0.7042 | 0.7692 |
| 0.3617 | 4.0 | 200 | 0.5255 | 0.72 | 0.8413 | 0.7465 | 0.7910 |
| 0.2878 | 5.0 | 250 | 0.5009 | 0.74 | 0.8358 | 0.7887 | 0.8116 |
| 0.2282 | 6.0 | 300 | 0.5116 | 0.76 | 0.8615 | 0.7887 | 0.8235 |
| 0.1747 | 7.0 | 350 | 0.5235 | 0.75 | 0.8966 | 0.7324 | 0.8062 |
| 0.1454 | 8.0 | 400 | 0.5663 | 0.79 | 0.8472 | 0.8592 | 0.8531 |
| 0.125 | 9.0 | 450 | 0.5371 | 0.77 | 0.8529 | 0.8169 | 0.8345 |
| 0.1188 | 10.0 | 500 | 0.5320 | 0.76 | 0.8507 | 0.8028 | 0.8261 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
