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Onlyphish_10K_fromB_BFall_40KGen_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: 0.0500
- Accuracy: 0.9943
- F1: 0.9371
- Precision: 0.9955
- Recall: 0.8852
- Roc Auc Score: 0.9425
- Tpr At Fpr 0.01: 0.8404
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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.0145 | 1.0 | 7813 | 0.0237 | 0.9946 | 0.9415 | 0.9760 | 0.9094 | 0.9541 | 0.8006 |
| 0.007 | 2.0 | 15626 | 0.0356 | 0.9943 | 0.9365 | 0.9953 | 0.8842 | 0.9420 | 0.8444 |
| 0.0023 | 3.0 | 23439 | 0.0402 | 0.9949 | 0.9435 | 0.9927 | 0.899 | 0.9493 | 0.8434 |
| 0.0019 | 4.0 | 31252 | 0.0453 | 0.9947 | 0.9412 | 0.9955 | 0.8924 | 0.9461 | 0.8592 |
| 0.0 | 5.0 | 39065 | 0.0500 | 0.9943 | 0.9371 | 0.9955 | 0.8852 | 0.9425 | 0.8404 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.9.0+cu111
- Datasets 2.10.1
- Tokenizers 0.13.2
