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MixGPT2_subdomain_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_95K_top_p_0.75subdomain dataset. It achieves the following results on the evaluation set:
- Loss: 0.0273
- Accuracy: 0.9976
- F1: 0.9738
- Precision: 0.9989
- Recall: 0.9498
- Roc Auc Score: 0.9749
- Tpr At Fpr 0.01: 0.9544
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0052 | 1.0 | 21554 | 0.0150 | 0.9972 | 0.9692 | 0.9979 | 0.9422 | 0.9711 | 0.9408 |
| 0.0046 | 2.0 | 43108 | 0.0107 | 0.9979 | 0.9778 | 0.9954 | 0.9608 | 0.9803 | 0.9458 |
| 0.002 | 3.0 | 64662 | 0.0198 | 0.9973 | 0.9708 | 0.9983 | 0.9448 | 0.9724 | 0.9488 |
| 0.0005 | 4.0 | 86216 | 0.0243 | 0.9974 | 0.9721 | 0.9977 | 0.9478 | 0.9738 | 0.947 |
| 0.0 | 5.0 | 107770 | 0.0273 | 0.9976 | 0.9738 | 0.9989 | 0.9498 | 0.9749 | 0.9544 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
