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MixGPT2_Domain_100KP_BFall_fromP_90K_topP_0.75_ratio2.63
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_phish_94K_top_p_0.75_domain dataset. It achieves the following results on the evaluation set:
- Loss: 0.0244
- Accuracy: 0.9979
- F1: 0.9770
- Precision: 0.9981
- Recall: 0.9568
- Roc Auc Score: 0.9784
- Tpr At Fpr 0.01: 0.9584
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0065 | 1.0 | 21554 | 0.0158 | 0.9966 | 0.9633 | 0.9962 | 0.9326 | 0.9662 | 0.9092 |
| 0.0024 | 2.0 | 43108 | 0.0111 | 0.9976 | 0.9741 | 0.9962 | 0.953 | 0.9764 | 0.9462 |
| 0.0024 | 3.0 | 64662 | 0.0178 | 0.9978 | 0.9769 | 0.9952 | 0.9592 | 0.9795 | 0.9468 |
| 0.0007 | 4.0 | 86216 | 0.0194 | 0.9978 | 0.9766 | 0.9971 | 0.957 | 0.9784 | 0.9508 |
| 0.0 | 5.0 | 107770 | 0.0244 | 0.9979 | 0.9770 | 0.9981 | 0.9568 | 0.9784 | 0.9584 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
