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distilbert-base-uncased__sst2__train-16-2
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: 0.6748
- Accuracy: 0.6315
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 |
|---|---|---|---|---|
| 0.7043 | 1.0 | 7 | 0.7054 | 0.2857 |
| 0.6711 | 2.0 | 14 | 0.7208 | 0.2857 |
| 0.6311 | 3.0 | 21 | 0.7365 | 0.2857 |
| 0.551 | 4.0 | 28 | 0.7657 | 0.5714 |
| 0.5599 | 5.0 | 35 | 0.6915 | 0.5714 |
| 0.3167 | 6.0 | 42 | 0.7134 | 0.5714 |
| 0.2489 | 7.0 | 49 | 0.7892 | 0.5714 |
| 0.1985 | 8.0 | 56 | 0.6756 | 0.7143 |
| 0.0864 | 9.0 | 63 | 0.8059 | 0.5714 |
| 0.0903 | 10.0 | 70 | 0.8165 | 0.7143 |
| 0.0429 | 11.0 | 77 | 0.7947 | 0.7143 |
| 0.0186 | 12.0 | 84 | 0.8570 | 0.7143 |
| 0.0146 | 13.0 | 91 | 0.9346 | 0.7143 |
| 0.011 | 14.0 | 98 | 0.9804 | 0.7143 |
| 0.0098 | 15.0 | 105 | 1.0136 | 0.7143 |
| 0.0086 | 16.0 | 112 | 1.0424 | 0.7143 |
| 0.0089 | 17.0 | 119 | 1.0736 | 0.7143 |
| 0.0068 | 18.0 | 126 | 1.0808 | 0.7143 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
