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dream_classifier
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: 0.6082
- Accuracy: 0.8661
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 |
|---|---|---|---|---|
| No log | 1.0 | 17 | 0.6040 | 0.8125 |
| No log | 2.0 | 34 | 0.4455 | 0.8482 |
| No log | 3.0 | 51 | 0.3701 | 0.875 |
| No log | 4.0 | 68 | 0.4277 | 0.8304 |
| No log | 5.0 | 85 | 0.4477 | 0.8393 |
| No log | 6.0 | 102 | 0.3747 | 0.8929 |
| No log | 7.0 | 119 | 0.4383 | 0.9018 |
| No log | 8.0 | 136 | 0.5102 | 0.875 |
| No log | 9.0 | 153 | 0.5384 | 0.8661 |
| No log | 10.0 | 170 | 0.6888 | 0.8571 |
| No log | 11.0 | 187 | 0.5788 | 0.8661 |
| No log | 12.0 | 204 | 0.5933 | 0.8571 |
| No log | 13.0 | 221 | 0.6214 | 0.8661 |
| No log | 14.0 | 238 | 0.6246 | 0.8661 |
| No log | 15.0 | 255 | 0.6033 | 0.8661 |
| No log | 16.0 | 272 | 0.6066 | 0.8661 |
| No log | 17.0 | 289 | 0.6092 | 0.8661 |
| No log | 18.0 | 306 | 0.6079 | 0.8661 |
| No log | 19.0 | 323 | 0.6080 | 0.8661 |
| No log | 20.0 | 340 | 0.6082 | 0.8661 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
