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distilbert-base-uncased__sst2__train-16-1
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: 0.6012
- Accuracy: 0.6766
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 |
|---|---|---|---|---|
| 0.6983 | 1.0 | 7 | 0.7036 | 0.2857 |
| 0.6836 | 2.0 | 14 | 0.7181 | 0.2857 |
| 0.645 | 3.0 | 21 | 0.7381 | 0.2857 |
| 0.5902 | 4.0 | 28 | 0.7746 | 0.2857 |
| 0.5799 | 5.0 | 35 | 0.7242 | 0.5714 |
| 0.3584 | 6.0 | 42 | 0.6935 | 0.5714 |
| 0.2596 | 7.0 | 49 | 0.7041 | 0.5714 |
| 0.1815 | 8.0 | 56 | 0.5930 | 0.7143 |
| 0.0827 | 9.0 | 63 | 0.6976 | 0.7143 |
| 0.0613 | 10.0 | 70 | 0.7346 | 0.7143 |
| 0.0356 | 11.0 | 77 | 0.6992 | 0.5714 |
| 0.0158 | 12.0 | 84 | 0.7328 | 0.5714 |
| 0.013 | 13.0 | 91 | 0.7819 | 0.5714 |
| 0.0103 | 14.0 | 98 | 0.8589 | 0.5714 |
| 0.0087 | 15.0 | 105 | 0.9177 | 0.5714 |
| 0.0076 | 16.0 | 112 | 0.9519 | 0.5714 |
| 0.0078 | 17.0 | 119 | 0.9556 | 0.5714 |
| 0.006 | 18.0 | 126 | 0.9542 | 0.5714 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
