bio_gpt_ner
This model is a fine-tuned version of microsoft/biogpt on the ncbi_disease dataset. It achieves the following results on the evaluation set:
- Loss: 0.1558
- Precision: 0.8269
- Recall: 0.6463
- F1: 0.7255
- Accuracy: 0.9544
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: 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 |
---|---|---|---|---|---|---|---|
0.3027 | 1.0 | 680 | 0.1893 | 0.8417 | 0.4194 | 0.5598 | 0.9405 |
0.2037 | 2.0 | 1360 | 0.1562 | 0.8082 | 0.6388 | 0.7136 | 0.9517 |
0.1228 | 3.0 | 2040 | 0.1558 | 0.8269 | 0.6463 | 0.7255 | 0.9544 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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Dataset used to train westbrook/bio_gpt_ner
Evaluation results
- Precision on ncbi_diseasevalidation set self-reported0.827
- Recall on ncbi_diseasevalidation set self-reported0.646
- F1 on ncbi_diseasevalidation set self-reported0.726
- Accuracy on ncbi_diseasevalidation set self-reported0.954