<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilbert-base-uncased__sst2__train-16-5
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: 0.6537
- Accuracy: 0.6332
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 |
|---|---|---|---|---|
| 0.6925 | 1.0 | 7 | 0.6966 | 0.2857 |
| 0.6703 | 2.0 | 14 | 0.7045 | 0.2857 |
| 0.6404 | 3.0 | 21 | 0.7205 | 0.2857 |
| 0.555 | 4.0 | 28 | 0.7548 | 0.2857 |
| 0.5179 | 5.0 | 35 | 0.6745 | 0.5714 |
| 0.3038 | 6.0 | 42 | 0.7260 | 0.5714 |
| 0.2089 | 7.0 | 49 | 0.8016 | 0.5714 |
| 0.1303 | 8.0 | 56 | 0.8202 | 0.5714 |
| 0.0899 | 9.0 | 63 | 0.9966 | 0.5714 |
| 0.0552 | 10.0 | 70 | 1.1887 | 0.5714 |
| 0.0333 | 11.0 | 77 | 1.2163 | 0.5714 |
| 0.0169 | 12.0 | 84 | 1.2874 | 0.5714 |
| 0.0136 | 13.0 | 91 | 1.3598 | 0.5714 |
| 0.0103 | 14.0 | 98 | 1.4237 | 0.5714 |
| 0.0089 | 15.0 | 105 | 1.4758 | 0.5714 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
