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SS_model
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: 0.3980
- Accuracy: 0.9587
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.153 | 1.0 | 4301 | 0.1472 | 0.9526 |
0.1165 | 2.0 | 8602 | 0.1376 | 0.9562 |
0.0951 | 3.0 | 12903 | 0.1462 | 0.9596 |
0.0851 | 4.0 | 17204 | 0.1550 | 0.9602 |
0.0709 | 5.0 | 21505 | 0.1848 | 0.9596 |
0.069 | 6.0 | 25806 | 0.2027 | 0.9586 |
0.0591 | 7.0 | 30107 | 0.2266 | 0.9582 |
0.047 | 8.0 | 34408 | 0.2110 | 0.9573 |
0.0391 | 9.0 | 38709 | 0.2405 | 0.9577 |
0.0333 | 10.0 | 43010 | 0.2865 | 0.9566 |
0.0336 | 11.0 | 47311 | 0.2671 | 0.9588 |
0.0226 | 12.0 | 51612 | 0.2743 | 0.9567 |
0.0266 | 13.0 | 55913 | 0.3281 | 0.9577 |
0.0191 | 14.0 | 60214 | 0.3062 | 0.9572 |
0.0232 | 15.0 | 64515 | 0.3479 | 0.9585 |
0.0149 | 16.0 | 68816 | 0.3542 | 0.9587 |
0.0099 | 17.0 | 73117 | 0.3646 | 0.9587 |
0.0123 | 18.0 | 77418 | 0.3721 | 0.9584 |
0.0091 | 19.0 | 81719 | 0.3896 | 0.9590 |
0.0086 | 20.0 | 86020 | 0.3980 | 0.9587 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3