| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: answerdotai/ModernBERT-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: modernbert-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. --> |
| |
|
| | # modernbert-phishing-classifier |
| |
|
| | This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3066 |
| | - Accuracy: 0.9 |
| | - Auc: 0.965 |
| |
|
| | ## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 15 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:| |
| | | 0.3714 | 1.0 | 263 | 0.2936 | 0.869 | 0.949 | |
| | | 0.2622 | 2.0 | 526 | 0.2681 | 0.884 | 0.96 | |
| | | 0.2405 | 3.0 | 789 | 0.2642 | 0.898 | 0.961 | |
| | | 0.2091 | 4.0 | 1052 | 0.2688 | 0.893 | 0.963 | |
| | | 0.2078 | 5.0 | 1315 | 0.3813 | 0.882 | 0.962 | |
| | | 0.1887 | 6.0 | 1578 | 0.2667 | 0.9 | 0.965 | |
| | | 0.1695 | 7.0 | 1841 | 0.2851 | 0.902 | 0.964 | |
| | | 0.1654 | 8.0 | 2104 | 0.2935 | 0.902 | 0.964 | |
| | | 0.157 | 9.0 | 2367 | 0.3169 | 0.904 | 0.966 | |
| | | 0.158 | 10.0 | 2630 | 0.3190 | 0.896 | 0.964 | |
| | | 0.149 | 11.0 | 2893 | 0.3019 | 0.893 | 0.965 | |
| | | 0.1437 | 12.0 | 3156 | 0.2995 | 0.9 | 0.965 | |
| | | 0.1365 | 13.0 | 3419 | 0.3048 | 0.9 | 0.965 | |
| | | 0.1312 | 14.0 | 3682 | 0.3090 | 0.898 | 0.965 | |
| | | 0.1304 | 15.0 | 3945 | 0.3066 | 0.9 | 0.965 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.48.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.21.0 |
| |
|
