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distilbert-base-uncased__sst2__train-16-6
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: 0.8356
- Accuracy: 0.6480
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 |
|---|---|---|---|---|
| 0.6978 | 1.0 | 7 | 0.6807 | 0.4286 |
| 0.6482 | 2.0 | 14 | 0.6775 | 0.4286 |
| 0.6051 | 3.0 | 21 | 0.6623 | 0.5714 |
| 0.486 | 4.0 | 28 | 0.6710 | 0.5714 |
| 0.4612 | 5.0 | 35 | 0.5325 | 0.7143 |
| 0.2233 | 6.0 | 42 | 0.4992 | 0.7143 |
| 0.1328 | 7.0 | 49 | 0.4753 | 0.7143 |
| 0.0905 | 8.0 | 56 | 0.2416 | 1.0 |
| 0.0413 | 9.0 | 63 | 0.2079 | 1.0 |
| 0.0356 | 10.0 | 70 | 0.2234 | 0.8571 |
| 0.0217 | 11.0 | 77 | 0.2639 | 0.8571 |
| 0.0121 | 12.0 | 84 | 0.2977 | 0.8571 |
| 0.0105 | 13.0 | 91 | 0.3468 | 0.8571 |
| 0.0085 | 14.0 | 98 | 0.3912 | 0.8571 |
| 0.0077 | 15.0 | 105 | 0.4000 | 0.8571 |
| 0.0071 | 16.0 | 112 | 0.4015 | 0.8571 |
| 0.0078 | 17.0 | 119 | 0.3865 | 0.8571 |
| 0.0059 | 18.0 | 126 | 0.3603 | 0.8571 |
| 0.0051 | 19.0 | 133 | 0.3231 | 0.8571 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
