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MixGPT2_Domain_100KP_BFall_fromB_100K_topP_0.75_ratio2.5
This model is a fine-tuned version of bert-base-uncased on the Train benign: Fall,Test Benign: Fall, Train phish: Fall, Test phish: Fall, generated url dataset: generated_phish_MixGPT2_using_benign_100K_top_p_0.75_domain dataset. It achieves the following results on the evaluation set:
- Loss: 0.0232
- Accuracy: 0.9972
- F1: 0.9700
- Precision: 0.9778
- Recall: 0.9622
- Roc Auc Score: 0.9806
- Tpr At Fpr 0.01: 0.0
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc Score | Tpr At Fpr 0.01 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0202 | 1.0 | 21875 | 0.0244 | 0.9938 | 0.9365 | 0.9148 | 0.9594 | 0.9775 | 0.0 |
| 0.0108 | 2.0 | 43750 | 0.0146 | 0.9970 | 0.9684 | 0.9782 | 0.9588 | 0.9789 | 0.8886 |
| 0.0078 | 3.0 | 65625 | 0.0195 | 0.9966 | 0.9640 | 0.9731 | 0.955 | 0.9768 | 0.0 |
| 0.0019 | 4.0 | 87500 | 0.0245 | 0.9964 | 0.9628 | 0.9608 | 0.9648 | 0.9814 | 0.0 |
| 0.0007 | 5.0 | 109375 | 0.0232 | 0.9972 | 0.9700 | 0.9778 | 0.9622 | 0.9806 | 0.0 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
