| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: bert-phishing-classifier |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # bert-phishing-classifier |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2994 |
| - Accuracy: 0.871 |
| - Auc: 0.951 |
|
|
| ## 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: 0.0002 |
| - 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: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:| |
| | 0.4954 | 1.0 | 263 | 0.4188 | 0.791 | 0.913 | |
| | 0.3914 | 2.0 | 526 | 0.3616 | 0.818 | 0.931 | |
| | 0.3813 | 3.0 | 789 | 0.3164 | 0.86 | 0.938 | |
| | 0.3589 | 4.0 | 1052 | 0.4471 | 0.811 | 0.942 | |
| | 0.3513 | 5.0 | 1315 | 0.3300 | 0.862 | 0.946 | |
| | 0.3547 | 6.0 | 1578 | 0.3082 | 0.867 | 0.948 | |
| | 0.3224 | 7.0 | 1841 | 0.2914 | 0.864 | 0.949 | |
| | 0.3301 | 8.0 | 2104 | 0.2986 | 0.876 | 0.949 | |
| | 0.3165 | 9.0 | 2367 | 0.2901 | 0.862 | 0.95 | |
| | 0.3061 | 10.0 | 2630 | 0.2994 | 0.871 | 0.951 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.9.0 |
| - Pytorch 2.11.0 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
