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Onlyphish_10K_fromP_BFall_10KGen_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: 0.0759
- Accuracy: 0.9929
- F1: 0.9193
- Precision: 1.0
- Recall: 0.8506
- Roc Auc Score: 0.9253
- Tpr At Fpr 0.01: 0.8776
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0055 | 1.0 | 13125 | 0.0436 | 0.9901 | 0.8844 | 0.9933 | 0.797 | 0.8984 | 0.7488 |
| 0.0032 | 2.0 | 26250 | 0.1145 | 0.9853 | 0.8171 | 0.9994 | 0.691 | 0.8455 | 0.756 |
| 0.0025 | 3.0 | 39375 | 0.0705 | 0.9919 | 0.9076 | 0.9978 | 0.8324 | 0.9162 | 0.8332 |
| 0.0018 | 4.0 | 52500 | 0.0848 | 0.9919 | 0.9065 | 0.9998 | 0.8292 | 0.9146 | 0.8506 |
| 0.0008 | 5.0 | 65625 | 0.0759 | 0.9929 | 0.9193 | 1.0 | 0.8506 | 0.9253 | 0.8776 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
