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deberta-v3-large__sst2__train-16-0
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9917
- Accuracy: 0.7705
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 |
|---|---|---|---|---|
| 0.7001 | 1.0 | 7 | 0.7327 | 0.2857 |
| 0.6326 | 2.0 | 14 | 0.6479 | 0.5714 |
| 0.5232 | 3.0 | 21 | 0.5714 | 0.5714 |
| 0.3313 | 4.0 | 28 | 0.6340 | 0.7143 |
| 0.3161 | 5.0 | 35 | 0.6304 | 0.7143 |
| 0.0943 | 6.0 | 42 | 0.4719 | 0.8571 |
| 0.0593 | 7.0 | 49 | 0.5000 | 0.7143 |
| 0.0402 | 8.0 | 56 | 0.3530 | 0.8571 |
| 0.0307 | 9.0 | 63 | 0.3499 | 0.8571 |
| 0.0033 | 10.0 | 70 | 0.3258 | 0.8571 |
| 0.0021 | 11.0 | 77 | 0.3362 | 0.8571 |
| 0.0012 | 12.0 | 84 | 0.4591 | 0.8571 |
| 0.0036 | 13.0 | 91 | 0.4661 | 0.8571 |
| 0.001 | 14.0 | 98 | 0.5084 | 0.8571 |
| 0.0017 | 15.0 | 105 | 0.5844 | 0.8571 |
| 0.0005 | 16.0 | 112 | 0.6645 | 0.8571 |
| 0.002 | 17.0 | 119 | 0.7422 | 0.8571 |
| 0.0006 | 18.0 | 126 | 0.7354 | 0.8571 |
| 0.0005 | 19.0 | 133 | 0.7265 | 0.8571 |
| 0.0005 | 20.0 | 140 | 0.7207 | 0.8571 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
