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BERT-phishing-classifier
dhruvyadav89300/BERT-phishing-classifier
BERT-phishing-classifier is a text classification model from dhruvyadav89300. Use it when you need a label for a piece of text. It is set up for transformers.
This is the model is a fine-tuned version of google-bert/bert-base-uncased on the phishing-site-classification dataset
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Nov 2, 2024
- Updated
- Nov 2, 2024
- SHA
- e9573398
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<!-- Provide a quick summary of what the model is/does. -->Model Details
Model Description
<!-- Provide a longer summary of what this model is. -->This is the model is a fine-tuned version of google-bert/bert-base-uncased on the phishing-site-classification dataset
Model Sources
<!-- Provide the basic links for the model. -->- Repository: GitHub
Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->Training Results
| Epoch | Training Loss | Step | Validation Loss | Accuracy | AUC | Learning Rate |
|---|---|---|---|---|---|---|
| 1 | 0.4932 | 263 | 0.4237 | 0.789 | 0.912 | 0.00019 |
| 2 | 0.3908 | 526 | 0.3761 | 0.824 | 0.932 | 0.00018 |
| 3 | 0.3787 | 789 | 0.3136 | 0.860 | 0.941 | 0.00017 |
| 4 | 0.3606 | 1052 | 0.4401 | 0.818 | 0.944 | 0.00016 |
| 5 | 0.3545 | 1315 | 0.2928 | 0.864 | 0.947 | 0.00015 |
| 6 | 0.3600 | 1578 | 0.3406 | 0.867 | 0.949 | 0.00014 |
| 7 | 0.3233 | 1841 | 0.2897 | 0.869 | 0.950 | 0.00013 |
| 8 | 0.3411 | 2104 | 0.3328 | 0.871 | 0.949 | 0.00012 |
| 9 | 0.3292 | 2367 | 0.3189 | 0.876 | 0.954 | 0.00011 |
| 10 | 0.3239 | 2630 | 0.3685 | 0.849 | 0.956 | 0.00010 |
| 11 | 0.3201 | 2893 | 0.3317 | 0.862 | 0.956 | 0.00009 |
| 12 | 0.3335 | 3156 | 0.2725 | 0.869 | 0.957 | 0.00008 |
| 13 | 0.3230 | 3419 | 0.2856 | 0.882 | 0.955 | 0.00007 |
| 14 | 0.3087 | 3682 | 0.2900 | 0.882 | 0.957 | 0.00006 |
| 15 | 0.3050 | 3945 | 0.2704 | 0.893 | 0.957 | 0.00005 |
| 16 | 0.3032 | 4208 | 0.2662 | 0.878 | 0.957 | 0.00004 |
| 17 | 0.3027 | 4471 | 0.2930 | 0.882 | 0.956 | 0.00003 |
| 18 | 0.2950 | 4734 | 0.2707 | 0.880 | 0.957 | 0.00002 |
| 19 | 0.2998 | 4997 | 0.2782 | 0.884 | 0.957 | 0.00001 |
| 20 | 0.2971 | 5260 | 0.2792 | 0.882 | 0.957 | 0.00000 |
Final Training Summary
- Total Training Runtime: 555.4381 seconds
- Final Training Loss: 0.3372
- Train Samples per Second: 75.616
- Eval Accuracy (Best Epoch): 0.893 (Epoch 15)
- Eval AUC (Best Epoch): 0.957 (Multiple Epochs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 2, 2024
- Updated
- Nov 2, 2024