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MixGPT2V2_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_MixGPT2V2_using_phish_95K_top_p_0.75domain dataset. It achieves the following results on the evaluation set:
- Loss: 0.0218
- Accuracy: 0.9979
- F1: 0.9779
- Precision: 0.9983
- Recall: 0.9582
- Roc Auc Score: 0.9791
- Tpr At Fpr 0.01: 0.959
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0061 | 1.0 | 21554 | 0.0175 | 0.9967 | 0.9646 | 0.9947 | 0.9362 | 0.9680 | 0.8936 |
| 0.0031 | 2.0 | 43108 | 0.0122 | 0.9980 | 0.9786 | 0.9876 | 0.9698 | 0.9846 | 0.9328 |
| 0.0021 | 3.0 | 64662 | 0.0128 | 0.9978 | 0.9760 | 0.9946 | 0.958 | 0.9789 | 0.945 |
| 0.0009 | 4.0 | 86216 | 0.0178 | 0.9980 | 0.9782 | 0.9971 | 0.96 | 0.9799 | 0.9588 |
| 0.0004 | 5.0 | 107770 | 0.0218 | 0.9979 | 0.9779 | 0.9983 | 0.9582 | 0.9791 | 0.959 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
