---
library_name: transformers
datasets:
- shawhin/phishing-site-classification
base_model:
- google-bert/bert-base-uncased
---

# Model Card for Model ID

<!-- 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](https://huggingface.co/google-bert/bert-base-uncased) on the [phishing-site-classification dataset](https://huggingface.co/datasets/shawhin/phishing-site-classification)


### Model Sources

<!-- Provide the basic links for the model. -->

- **Repository:** [GitHub](https://github.com/dhruvyadav89300/BERT-Phishing-Classifier)



## 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)