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distilbert-base-uncased__sst2__train-32-0
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8558
- Accuracy: 0.7183
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7088 | 1.0 | 13 | 0.6819 | 0.6154 |
| 0.635 | 2.0 | 26 | 0.6318 | 0.7692 |
| 0.547 | 3.0 | 39 | 0.5356 | 0.7692 |
| 0.3497 | 4.0 | 52 | 0.4456 | 0.6923 |
| 0.1979 | 5.0 | 65 | 0.3993 | 0.7692 |
| 0.098 | 6.0 | 78 | 0.3613 | 0.7692 |
| 0.0268 | 7.0 | 91 | 0.3561 | 0.9231 |
| 0.0137 | 8.0 | 104 | 0.3755 | 0.9231 |
| 0.0083 | 9.0 | 117 | 0.4194 | 0.7692 |
| 0.0065 | 10.0 | 130 | 0.4446 | 0.7692 |
| 0.005 | 11.0 | 143 | 0.4527 | 0.7692 |
| 0.0038 | 12.0 | 156 | 0.4645 | 0.7692 |
| 0.0033 | 13.0 | 169 | 0.4735 | 0.7692 |
| 0.0033 | 14.0 | 182 | 0.4874 | 0.7692 |
| 0.0029 | 15.0 | 195 | 0.5041 | 0.7692 |
| 0.0025 | 16.0 | 208 | 0.5148 | 0.7692 |
| 0.0024 | 17.0 | 221 | 0.5228 | 0.7692 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
