dbert-review-classification
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3117
- Accuracy: 0.5217
- Mse: 1.1363
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse |
|---|---|---|---|---|---|
| No log | 1.0 | 438 | 1.1416 | 0.5107 | 1.2943 |
| 1.2437 | 2.0 | 876 | 1.1698 | 0.5047 | 1.3863 |
| 0.9888 | 3.0 | 1314 | 1.1890 | 0.515 | 1.2217 |
| 0.787 | 4.0 | 1752 | 1.3117 | 0.5217 | 1.1363 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1