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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: 0.2719
- Accuracy: 0.9197
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.11 | 100 | 0.3326 | 0.903 |
| No log | 0.21 | 200 | 0.3056 | 0.9087 |
| No log | 0.32 | 300 | 0.2854 | 0.9153 |
| No log | 0.43 | 400 | 0.2846 | 0.9153 |
| 0.3712 | 0.53 | 500 | 0.2808 | 0.9177 |
| 0.3712 | 0.64 | 600 | 0.2769 | 0.9187 |
| 0.3712 | 0.75 | 700 | 0.2781 | 0.9187 |
| 0.3712 | 0.85 | 800 | 0.2740 | 0.9197 |
| 0.3712 | 0.96 | 900 | 0.2719 | 0.9197 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
