metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Variome_5e-05_29_03
results: []
Variome_5e-05_29_03
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: 0.1054
- Precision: 0.5304
- Recall: 0.4586
- F1: 0.4919
- Accuracy: 0.9843
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: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.5733 | 5.0 | 25 | 0.1581 | 0.0 | 0.0 | 0.0 | 0.9794 |
0.1685 | 10.0 | 50 | 0.1553 | 0.0 | 0.0 | 0.0 | 0.9794 |
0.1691 | 15.0 | 75 | 0.1547 | 0.0 | 0.0 | 0.0 | 0.9794 |
0.1606 | 20.0 | 100 | 0.1335 | 0.0 | 0.0 | 0.0 | 0.9794 |
0.1144 | 25.0 | 125 | 0.1044 | 0.2151 | 0.1504 | 0.1770 | 0.9802 |
0.0795 | 30.0 | 150 | 0.1023 | 0.2 | 0.1504 | 0.1717 | 0.9804 |
0.0612 | 35.0 | 175 | 0.1102 | 0.4118 | 0.2105 | 0.2786 | 0.9831 |
0.0465 | 40.0 | 200 | 0.0991 | 0.4158 | 0.3158 | 0.3590 | 0.9840 |
0.0352 | 45.0 | 225 | 0.0995 | 0.4653 | 0.3534 | 0.4017 | 0.9838 |
0.0281 | 50.0 | 250 | 0.0969 | 0.4685 | 0.3910 | 0.4262 | 0.9838 |
0.0223 | 55.0 | 275 | 0.0976 | 0.5684 | 0.4060 | 0.4737 | 0.9853 |
0.0183 | 60.0 | 300 | 0.0992 | 0.5093 | 0.4135 | 0.4564 | 0.9848 |
0.0154 | 65.0 | 325 | 0.0996 | 0.5816 | 0.4286 | 0.4935 | 0.9858 |
0.0131 | 70.0 | 350 | 0.1007 | 0.5221 | 0.4436 | 0.4797 | 0.9842 |
0.0109 | 75.0 | 375 | 0.1023 | 0.5130 | 0.4436 | 0.4758 | 0.9842 |
0.0094 | 80.0 | 400 | 0.1037 | 0.5566 | 0.4436 | 0.4937 | 0.9851 |
0.0085 | 85.0 | 425 | 0.1054 | 0.5304 | 0.4586 | 0.4919 | 0.9843 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2