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Onlyphish_100KP_BFall_fromP_10KGen_topP_0.75_noaddedB
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: 0.0211
- Accuracy: 0.9975
- F1: 0.9730
- Precision: 0.9994
- Recall: 0.948
- Roc Auc Score: 0.9740
- Tpr At Fpr 0.01: 0.9576
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.004 | 1.0 | 65938 | 0.0210 | 0.9964 | 0.9613 | 0.9966 | 0.9284 | 0.9641 | 0.9244 |
| 0.003 | 2.0 | 131876 | 0.0195 | 0.9966 | 0.9630 | 0.9970 | 0.9312 | 0.9655 | 0.9268 |
| 0.0016 | 3.0 | 197814 | 0.0148 | 0.9977 | 0.9757 | 0.9983 | 0.954 | 0.9770 | 0.9554 |
| 0.0011 | 4.0 | 263752 | 0.0202 | 0.9970 | 0.9677 | 0.9989 | 0.9384 | 0.9692 | 0.9438 |
| 0.0005 | 5.0 | 329690 | 0.0211 | 0.9975 | 0.9730 | 0.9994 | 0.948 | 0.9740 | 0.9576 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
