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Email-Phising-Detection
iexploreaiml/Email-Phising-Detection
Email-Phising-Detection is a text classification model from iexploreaiml. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Oct 6, 2025
- Updated
- Oct 6, 2025
- SHA
- 4227583e
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
results
This model is a fine-tuned version of bert-base-uncased on the zefang-liu/phishing-email-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0992
- Accuracy: 0.9775
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0634 | 1.0 | 1863 | 0.0950 | 0.9713 |
| 0.0336 | 2.0 | 3726 | 0.0842 | 0.9785 |
| 0.0269 | 3.0 | 5589 | 0.0835 | 0.9785 |
| 0.0452 | 4.0 | 7452 | 0.1083 | 0.9777 |
| 0.0233 | 5.0 | 9315 | 0.0992 | 0.9775 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 6, 2025
- Updated
- Oct 6, 2025