ClinicalTextV4
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: 0.5609
- Accuracy: 0.8658
- Precision: 0.8371
- Recall: 0.8939
- F1: 0.8646
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 |
---|---|---|---|---|---|---|---|
0.4824 | 1.0 | 600 | 0.3630 | 0.8458 | 0.825 | 0.8609 | 0.8426 |
0.3314 | 2.0 | 1200 | 0.3583 | 0.8558 | 0.8252 | 0.8870 | 0.8550 |
0.2673 | 3.0 | 1800 | 0.3437 | 0.8583 | 0.8189 | 0.9043 | 0.8595 |
0.2255 | 4.0 | 2400 | 0.3678 | 0.8675 | 0.8302 | 0.9096 | 0.8680 |
0.1883 | 5.0 | 3000 | 0.4002 | 0.8642 | 0.8259 | 0.9078 | 0.8650 |
0.1562 | 6.0 | 3600 | 0.4695 | 0.8633 | 0.8352 | 0.8904 | 0.8620 |
0.1372 | 7.0 | 4200 | 0.4940 | 0.8658 | 0.8371 | 0.8939 | 0.8646 |
0.1269 | 8.0 | 4800 | 0.5376 | 0.865 | 0.8402 | 0.8870 | 0.8629 |
0.1097 | 9.0 | 5400 | 0.5539 | 0.8633 | 0.8397 | 0.8835 | 0.8610 |
0.0997 | 10.0 | 6000 | 0.5609 | 0.8658 | 0.8371 | 0.8939 | 0.8646 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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