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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-bert/bert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: phishing-binary-classification-bert |
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results: [] |
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datasets: |
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- aisuko/phishing-binary-classification |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# phishing-binary-classification-bert |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on [aisuko/phishing-binary-classification](https://huggingface.co/datasets/aisuko/phishing-binary-classification) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4878 |
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- Accuracy: 0.82 |
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- Auc: 0.919 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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[aisuko/phishing-binary-classification](https://huggingface.co/datasets/aisuko/phishing-binary-classification) dataset |
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## Training procedure |
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Please check Kaggle notbebook [FT Google Bert for Binary Classification](https://www.kaggle.com/code/aisuko/ft-google-bert-for-binary-classification) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----:| |
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| 0.6681 | 1.0 | 1250 | 0.6198 | 0.69 | 0.885 | |
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| 0.6185 | 2.0 | 2500 | 0.5813 | 0.712 | 0.897 | |
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| 0.5907 | 3.0 | 3750 | 0.5478 | 0.82 | 0.9 | |
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| 0.5693 | 4.0 | 5000 | 0.5267 | 0.815 | 0.908 | |
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| 0.5608 | 5.0 | 6250 | 0.5193 | 0.787 | 0.91 | |
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| 0.5486 | 6.0 | 7500 | 0.5168 | 0.769 | 0.915 | |
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| 0.5409 | 7.0 | 8750 | 0.5034 | 0.79 | 0.916 | |
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| 0.5338 | 8.0 | 10000 | 0.5016 | 0.784 | 0.918 | |
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| 0.5331 | 9.0 | 11250 | 0.4947 | 0.796 | 0.919 | |
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| 0.5308 | 10.0 | 12500 | 0.4878 | 0.82 | 0.919 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
