sms-spam-distilbert
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: 0.0594
- Accuracy: 0.9881
- Precision: 0.9815
- Recall: 0.9298
- F1: 0.9550
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0448 | 1.0 | 244 | 0.0256 | 0.9964 | 1.0 | 0.9739 | 0.9868 |
| 0.0174 | 2.0 | 488 | 0.0253 | 0.9964 | 1.0 | 0.9739 | 0.9868 |
| 0.0075 | 3.0 | 732 | 0.0269 | 0.9964 | 1.0 | 0.9739 | 0.9868 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2