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Base_10Kphish_benignFall_IL_10K_OnlyPhish_10K_from_benign_top_p_0.75
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1123
- Accuracy: 0.9899
- F1: 0.8810
- Precision: 0.9985
- Recall: 0.7882
- Roc Auc Score: 0.8941
- Tpr At Fpr 0.01: 0.8132
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0068 | 1.0 | 6563 | 0.0531 | 0.9894 | 0.8756 | 0.9934 | 0.7828 | 0.8913 | 0.7264 |
| 0.0042 | 2.0 | 13126 | 0.0747 | 0.9894 | 0.8754 | 0.9962 | 0.7808 | 0.8903 | 0.7666 |
| 0.0015 | 3.0 | 19689 | 0.0648 | 0.9904 | 0.8887 | 0.9983 | 0.8008 | 0.9004 | 0.8088 |
| 0.0008 | 4.0 | 26252 | 0.0861 | 0.9912 | 0.8983 | 0.9980 | 0.8166 | 0.9083 | 0.831 |
| 0.0 | 5.0 | 32815 | 0.1123 | 0.9899 | 0.8810 | 0.9985 | 0.7882 | 0.8941 | 0.8132 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
