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Onlyphish_10K_fromB_BFall_20KGen_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: 0.0515
- Accuracy: 0.9951
- F1: 0.9454
- Precision: 0.9973
- Recall: 0.8986
- Roc Auc Score: 0.9492
- Tpr At Fpr 0.01: 0.8868
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0132 | 1.0 | 7188 | 0.0420 | 0.9915 | 0.9029 | 0.9945 | 0.8268 | 0.9133 | 0.7952 |
| 0.0034 | 2.0 | 14376 | 0.0398 | 0.9939 | 0.9322 | 0.9950 | 0.8768 | 0.9383 | 0.8162 |
| 0.0022 | 3.0 | 21564 | 0.0348 | 0.9955 | 0.9512 | 0.9937 | 0.9122 | 0.9560 | 0.886 |
| 0.0 | 4.0 | 28752 | 0.0360 | 0.9955 | 0.9507 | 0.9840 | 0.9196 | 0.9594 | 0.0 |
| 0.0 | 5.0 | 35940 | 0.0515 | 0.9951 | 0.9454 | 0.9973 | 0.8986 | 0.9492 | 0.8868 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
