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--- |
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library_name: transformers |
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datasets: |
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- shawhin/phishing-site-classification |
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base_model: |
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- google-bert/bert-base-uncased |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the [phishing-site-classification dataset](https://huggingface.co/datasets/shawhin/phishing-site-classification) |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [GitHub](https://github.com/dhruvyadav89300/BERT-Phishing-Classifier) |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Training Results |
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| Epoch | Training Loss | Step | Validation Loss | Accuracy | AUC | Learning Rate | |
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|-------|---------------|------|-----------------|----------|------|---------------| |
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| 1 | 0.4932 | 263 | 0.4237 | 0.789 | 0.912| 0.00019 | |
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| 2 | 0.3908 | 526 | 0.3761 | 0.824 | 0.932| 0.00018 | |
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| 3 | 0.3787 | 789 | 0.3136 | 0.860 | 0.941| 0.00017 | |
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| 4 | 0.3606 | 1052 | 0.4401 | 0.818 | 0.944| 0.00016 | |
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| 5 | 0.3545 | 1315 | 0.2928 | 0.864 | 0.947| 0.00015 | |
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| 6 | 0.3600 | 1578 | 0.3406 | 0.867 | 0.949| 0.00014 | |
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| 7 | 0.3233 | 1841 | 0.2897 | 0.869 | 0.950| 0.00013 | |
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| 8 | 0.3411 | 2104 | 0.3328 | 0.871 | 0.949| 0.00012 | |
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| 9 | 0.3292 | 2367 | 0.3189 | 0.876 | 0.954| 0.00011 | |
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| 10 | 0.3239 | 2630 | 0.3685 | 0.849 | 0.956| 0.00010 | |
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| 11 | 0.3201 | 2893 | 0.3317 | 0.862 | 0.956| 0.00009 | |
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| 12 | 0.3335 | 3156 | 0.2725 | 0.869 | 0.957| 0.00008 | |
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| 13 | 0.3230 | 3419 | 0.2856 | 0.882 | 0.955| 0.00007 | |
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| 14 | 0.3087 | 3682 | 0.2900 | 0.882 | 0.957| 0.00006 | |
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| 15 | 0.3050 | 3945 | 0.2704 | 0.893 | 0.957| 0.00005 | |
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| 16 | 0.3032 | 4208 | 0.2662 | 0.878 | 0.957| 0.00004 | |
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| 17 | 0.3027 | 4471 | 0.2930 | 0.882 | 0.956| 0.00003 | |
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| 18 | 0.2950 | 4734 | 0.2707 | 0.880 | 0.957| 0.00002 | |
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| 19 | 0.2998 | 4997 | 0.2782 | 0.884 | 0.957| 0.00001 | |
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| 20 | 0.2971 | 5260 | 0.2792 | 0.882 | 0.957| 0.00000 | |
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#### Final Training Summary |
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- **Total Training Runtime:** 555.4381 seconds |
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- **Final Training Loss:** 0.3372 |
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- **Train Samples per Second:** 75.616 |
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- **Eval Accuracy (Best Epoch):** 0.893 (Epoch 15) |
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- **Eval AUC (Best Epoch):** 0.957 (Multiple Epochs) |
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