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Benign10MGPT2_subdomain_100KP_BFall_fromB_90K_topP_0.75_ratio5
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_Benign10MGPT2_using_benign_95K_top_p_0.75subdomain dataset. It achieves the following results on the evaluation set:
- Loss: 0.0583
- Accuracy: 0.9898
- F1: 0.8963
- Precision: 0.8692
- Recall: 0.9252
- Roc Auc Score: 0.9591
- Tpr At Fpr 0.01: 0.7684
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc Score | Tpr At Fpr 0.01 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0918 | 1.0 | 35625 | 0.0388 | 0.9897 | 0.8926 | 0.8852 | 0.9002 | 0.9472 | 0.731 |
| 0.0757 | 2.0 | 71250 | 0.0341 | 0.9909 | 0.9067 | 0.8838 | 0.9308 | 0.9623 | 0.791 |
| 0.0537 | 3.0 | 106875 | 0.0493 | 0.9882 | 0.8808 | 0.8503 | 0.9136 | 0.9528 | 0.7598 |
| 0.034 | 4.0 | 142500 | 0.0478 | 0.9910 | 0.9068 | 0.8971 | 0.9168 | 0.9558 | 0.7692 |
| 0.0234 | 5.0 | 178125 | 0.0583 | 0.9898 | 0.8963 | 0.8692 | 0.9252 | 0.9591 | 0.7684 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
