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Baseline_100Kphish_benignFall_20_20_20
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0206
- Accuracy: 0.9973
- F1: 0.9713
- Precision: 0.9998
- Recall: 0.9444
- Roc Auc Score: 0.9722
- Tpr At Fpr 0.01: 0.962
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0021 | 1.0 | 65625 | 0.0198 | 0.9974 | 0.9721 | 0.9966 | 0.9488 | 0.9743 | 0.9436 |
| 0.0013 | 2.0 | 131250 | 0.0251 | 0.9969 | 0.9664 | 0.9996 | 0.9354 | 0.9677 | 0.9416 |
| 0.0025 | 3.0 | 196875 | 0.0284 | 0.9966 | 0.9625 | 0.9996 | 0.928 | 0.9640 | 0.953 |
| 0.0 | 4.0 | 262500 | 0.0187 | 0.9974 | 0.9717 | 0.9994 | 0.9456 | 0.9728 | 0.965 |
| 0.0011 | 5.0 | 328125 | 0.0206 | 0.9973 | 0.9713 | 0.9998 | 0.9444 | 0.9722 | 0.962 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
