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Onlyphish_100KP_BFall_fromB_20KGen_topP_0.75
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: 0.0187
- Accuracy: 0.9974
- F1: 0.9714
- Precision: 0.9987
- Recall: 0.9456
- Roc Auc Score: 0.9728
- Tpr At Fpr 0.01: 0.9596
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0036 | 1.0 | 78750 | 0.0305 | 0.9963 | 0.9593 | 0.9991 | 0.9226 | 0.9613 | 0.9348 |
| 0.0074 | 2.0 | 157500 | 0.0234 | 0.9967 | 0.9643 | 0.9947 | 0.9358 | 0.9678 | 0.0 |
| 0.0038 | 3.0 | 236250 | 0.0244 | 0.9967 | 0.9637 | 0.9987 | 0.931 | 0.9655 | 0.9352 |
| 0.0009 | 4.0 | 315000 | 0.0223 | 0.9970 | 0.9678 | 0.9991 | 0.9384 | 0.9692 | 0.9632 |
| 0.0011 | 5.0 | 393750 | 0.0187 | 0.9974 | 0.9714 | 0.9987 | 0.9456 | 0.9728 | 0.9596 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
