xss-classifier
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0131
- Accuracy: 0.9984
- Precision: 0.9977
- Recall: 0.9977
- F1: 0.9977
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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.0124 | 1.0 | 4322 | 0.0090 | 0.9971 | 0.9934 | 0.9983 | 0.9959 |
| 0.0075 | 2.0 | 8644 | 0.0112 | 0.9981 | 0.9970 | 0.9977 | 0.9974 |
| 0.0077 | 3.0 | 12966 | 0.0132 | 0.9983 | 0.9974 | 0.9977 | 0.9975 |
| 0.0020 | 4.0 | 17288 | 0.0105 | 0.9981 | 0.9977 | 0.9970 | 0.9974 |
| 0.0000 | 5.0 | 21610 | 0.0131 | 0.9984 | 0.9977 | 0.9977 | 0.9977 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2