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Baseline_10Kphish_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: 0.0830
- Accuracy: 0.9916
- F1: 0.9039
- Precision: 0.9971
- Recall: 0.8266
- Roc Auc Score: 0.9132
- Tpr At Fpr 0.01: 0.8118
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0118 | 1.0 | 6563 | 0.0538 | 0.9889 | 0.8681 | 0.9948 | 0.77 | 0.8849 | 0.7234 |
| 0.0053 | 2.0 | 13126 | 0.0538 | 0.9915 | 0.9021 | 0.9945 | 0.8254 | 0.9126 | 0.7654 |
| 0.0018 | 3.0 | 19689 | 0.0639 | 0.9916 | 0.9040 | 0.9945 | 0.8286 | 0.9142 | 0.7782 |
| 0.0009 | 4.0 | 26252 | 0.0843 | 0.9905 | 0.8894 | 0.9978 | 0.8022 | 0.9011 | 0.8086 |
| 0.0 | 5.0 | 32815 | 0.0830 | 0.9916 | 0.9039 | 0.9971 | 0.8266 | 0.9132 | 0.8118 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
