results
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7867
- Accuracy: 0.8396
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3562 | 1.0 | 534 | 0.4267 | 0.8143 |
| 0.2547 | 2.0 | 1068 | 0.4353 | 0.8452 |
| 0.1287 | 3.0 | 1602 | 0.5904 | 0.8537 |
| 0.0847 | 4.0 | 2136 | 0.7506 | 0.8358 |
| 0.0225 | 5.0 | 2670 | 0.7867 | 0.8396 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1