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distilbert-base-uncased__sst2__train-32-1
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: 0.6492
- Accuracy: 0.6551
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 |
|---|---|---|---|---|
| 0.7106 | 1.0 | 13 | 0.6850 | 0.6154 |
| 0.631 | 2.0 | 26 | 0.6632 | 0.6923 |
| 0.5643 | 3.0 | 39 | 0.6247 | 0.7692 |
| 0.3992 | 4.0 | 52 | 0.5948 | 0.7692 |
| 0.1928 | 5.0 | 65 | 0.5803 | 0.7692 |
| 0.0821 | 6.0 | 78 | 0.6404 | 0.6923 |
| 0.0294 | 7.0 | 91 | 0.7387 | 0.6923 |
| 0.0141 | 8.0 | 104 | 0.8270 | 0.6923 |
| 0.0082 | 9.0 | 117 | 0.8496 | 0.6923 |
| 0.0064 | 10.0 | 130 | 0.8679 | 0.6923 |
| 0.005 | 11.0 | 143 | 0.8914 | 0.6923 |
| 0.0036 | 12.0 | 156 | 0.9278 | 0.6923 |
| 0.0031 | 13.0 | 169 | 0.9552 | 0.6923 |
| 0.0029 | 14.0 | 182 | 0.9745 | 0.6923 |
| 0.0028 | 15.0 | 195 | 0.9785 | 0.6923 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
