model
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: 0.2138
- Precision: 0.5538
- Recall: 0.6313
- F1: 0.5900
- Accuracy: 0.9586
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: 0.0001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2962 | 1.0 | 679 | 0.1463 | 0.4864 | 0.5010 | 0.4936 | 0.9532 |
| 0.1321 | 2.0 | 1358 | 0.1482 | 0.4794 | 0.5946 | 0.5308 | 0.9549 |
| 0.0649 | 3.0 | 2037 | 0.1570 | 0.5307 | 0.6168 | 0.5705 | 0.9577 |
| 0.0414 | 4.0 | 2716 | 0.1799 | 0.5050 | 0.6390 | 0.5641 | 0.9564 |
| 0.0316 | 5.0 | 3395 | 0.2138 | 0.5538 | 0.6313 | 0.5900 | 0.9586 |
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 rduan6/model
Evaluation results
- Precision on ncbi_diseasevalidation set self-reported0.554
- Recall on ncbi_diseasevalidation set self-reported0.631
- F1 on ncbi_diseasevalidation set self-reported0.590
- Accuracy on ncbi_diseasevalidation set self-reported0.959