distilbert-base-uncased-finetuned-cola
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: 0.4733
- Matthews Correlation: 0.5490
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 | Matthews Correlation |
|---|---|---|---|---|
| 0.5168 | 1.0 | 535 | 0.4561 | 0.4500 |
| 0.3493 | 2.0 | 1070 | 0.4733 | 0.5490 |
| 0.2368 | 3.0 | 1605 | 0.6126 | 0.5368 |
| 0.1707 | 4.0 | 2140 | 0.7476 | 0.5444 |
| 0.1288 | 5.0 | 2675 | 0.7890 | 0.5472 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1