distilbert-base-uncased-finetuned-PubmedQA
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2957
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 21 | 4.6513 |
No log | 2.0 | 42 | 4.1809 |
No log | 3.0 | 63 | 4.1888 |
No log | 4.0 | 84 | 4.0779 |
No log | 5.0 | 105 | 4.1221 |
No log | 6.0 | 126 | 4.1381 |
No log | 7.0 | 147 | 4.0619 |
No log | 8.0 | 168 | 4.1242 |
No log | 9.0 | 189 | 4.1044 |
No log | 10.0 | 210 | 4.1699 |
No log | 11.0 | 231 | 4.1761 |
No log | 12.0 | 252 | 4.3132 |
No log | 13.0 | 273 | 4.2233 |
No log | 14.0 | 294 | 4.3036 |
No log | 15.0 | 315 | 4.2894 |
No log | 16.0 | 336 | 4.3075 |
No log | 17.0 | 357 | 4.3120 |
No log | 18.0 | 378 | 4.2841 |
No log | 19.0 | 399 | 4.3161 |
No log | 20.0 | 420 | 4.2957 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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