bioBERT-finrtuned-ner
This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on the bc2gm_corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.0887
- Precision: 0.7933
- Recall: 0.8373
- F1: 0.8147
- Accuracy: 0.9750
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 |
---|---|---|---|---|---|---|---|
0.0893 | 1.0 | 1563 | 0.0748 | 0.7447 | 0.8063 | 0.7743 | 0.9722 |
0.0507 | 2.0 | 3126 | 0.0773 | 0.7928 | 0.8275 | 0.8098 | 0.9739 |
0.0286 | 3.0 | 4689 | 0.0887 | 0.7933 | 0.8373 | 0.8147 | 0.9750 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6
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Dataset used to train drAbreu/bioBERT-NER-BC2GM_corpus
Evaluation results
- Precision on bc2gm_corpusself-reported0.793
- Recall on bc2gm_corpusself-reported0.837
- F1 on bc2gm_corpusself-reported0.815
- Accuracy on bc2gm_corpusself-reported0.975