results
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9272
- Accuracy: 0.6419
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2263 | 1.0 | 283 | 1.1019 | 0.5686 |
| 0.9798 | 2.0 | 566 | 0.9540 | 0.6264 |
| 0.7406 | 3.0 | 849 | 0.9522 | 0.6378 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.4.0
- Tokenizers 0.21.1