phishing-url-bert-tiny-v1
This model is a fine-tuned version of CrabInHoney/urlbert-tiny-v4-phishing-classifier on combination of multiple datasets. It achieves the following results on the evaluation set:
- Loss: 0.0809
- Accuracy: 0.9884
- F1: 0.9741
- Precision: 0.9829
- Recall: 0.9655
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0378 | 1.0 | 6023 | 0.0959 | 0.9873 | 0.9715 | 0.9857 | 0.9577 |
| 0.0353 | 2.0 | 12046 | 0.0853 | 0.9882 | 0.9737 | 0.9819 | 0.9656 |
| 0.0432 | 3.0 | 18069 | 0.0809 | 0.9884 | 0.9741 | 0.9829 | 0.9655 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2