abnormality_classifier_biobert_v1_3_epochs
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2835
- Accuracy: 0.957
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0099 | 1.0 | 1125 | 0.2986 | 0.952 |
| 0.0048 | 2.0 | 2250 | 0.2623 | 0.961 |
| 0.0063 | 3.0 | 3375 | 0.2835 | 0.957 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Granoladata/abnormality_classifier_biobert_v1_3_epochs
Base model
dmis-lab/biobert-v1.1