tags: | |
- generated_from_trainer | |
metrics: | |
- precision | |
- recall | |
- f1 | |
- accuracy | |
model-index: | |
- name: medlid-identify | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# medlid-identify | |
This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.1617 | |
- Precision: 0.4085 | |
- Recall: 0.4551 | |
- F1: 0.4305 | |
- Accuracy: 0.9452 | |
## 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: 81 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 4 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| No log | 1.0 | 381 | 0.1447 | 0.3867 | 0.2215 | 0.2817 | 0.9440 | | |
| 0.1714 | 2.0 | 762 | 0.1410 | 0.3937 | 0.4513 | 0.4206 | 0.9457 | | |
| 0.107 | 3.0 | 1143 | 0.1487 | 0.4061 | 0.4347 | 0.4199 | 0.9456 | | |
| 0.0702 | 4.0 | 1524 | 0.1617 | 0.4085 | 0.4551 | 0.4305 | 0.9452 | | |
### Framework versions | |
- Transformers 4.30.2 | |
- Pytorch 1.11.0 | |
- Datasets 2.13.1 | |
- Tokenizers 0.13.3 | |