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BioBERT-finetuned-ner-S800
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0693
- Precision: 0.6727
- Recall: 0.7767
- F1: 0.7210
- Accuracy: 0.9773
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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 55 | 0.0689 | 0.5835 | 0.6573 | 0.6182 | 0.9739 |
No log | 2.0 | 110 | 0.0687 | 0.6524 | 0.7514 | 0.6984 | 0.9766 |
No log | 3.0 | 165 | 0.0693 | 0.6727 | 0.7767 | 0.7210 | 0.9773 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3