distilbert-base-uncased-finetuned-clinc
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: 0.7894
- Accuracy: 0.9184
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: 48
- eval_batch_size: 48
- 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 |
|---|---|---|---|---|
| 4.3122 | 1.0 | 318 | 3.3058 | 0.7274 |
| 2.6526 | 2.0 | 636 | 1.8966 | 0.8429 |
| 1.5702 | 3.0 | 954 | 1.1748 | 0.8923 |
| 1.0315 | 4.0 | 1272 | 0.8752 | 0.9129 |
| 0.8129 | 5.0 | 1590 | 0.7894 | 0.9184 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.9.0+cu130
- Datasets 4.1.0
- Tokenizers 0.22.2