tmvar_5e-05_ES2
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0189
- Precision: 0.8469
- Recall: 0.8973
- F1: 0.8714
- Accuracy: 0.9971
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.3852 | 1.47 | 25 | 0.1019 | 0.0 | 0.0 | 0.0 | 0.9843 |
0.0775 | 2.94 | 50 | 0.0398 | 0.2812 | 0.3892 | 0.3265 | 0.9863 |
0.0327 | 4.41 | 75 | 0.0243 | 0.4740 | 0.4919 | 0.4828 | 0.9910 |
0.02 | 5.88 | 100 | 0.0191 | 0.7656 | 0.7946 | 0.7798 | 0.9954 |
0.0084 | 7.35 | 125 | 0.0229 | 0.7766 | 0.7892 | 0.7828 | 0.9952 |
0.0045 | 8.82 | 150 | 0.0172 | 0.8351 | 0.8486 | 0.8418 | 0.9964 |
0.0023 | 10.29 | 175 | 0.0190 | 0.9148 | 0.8703 | 0.8920 | 0.9968 |
0.0015 | 11.76 | 200 | 0.0189 | 0.8469 | 0.8973 | 0.8714 | 0.9971 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
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