README.md

---
license: apache-2.0
datasets:
- shawhin/phishing-site-classification
metrics:
- accuracy
- recall
- precision
- f1
base_model: shawhin/bert-phishing-classifier_student
library_name: transformers
---


# bert-phishing-classifier_student

This model is a quantized version of [shawhin/bert-phishing-classifier_student](https://huggingface.co/shawhin/bert-phishing-classifier_student) trained via knowledge distillation from [shawhin/bert-phishing-classifier_teacher](https://huggingface.co/shawhin/bert-phishing-classifier_teacher) using the [shawhin/phishing-site-classification](https://huggingface.co/datasets/shawhin/phishing-site-classification) dataset. 
It achieves the following results on the validation set:

- Accuracy: 0.9356
- Precision: 0.9757
- Recall: 0.8933
- F1 Score: 0.9327

## Model description

Quantized student model for model compression example.

[Video](https://youtu.be/FLkUOkeMd5M) | [Blog](https://towardsdatascience.com/compressing-large-language-models-llms-9f406eea5b5e) | [Example code](https://github.com/ShawhinT/YouTube-Blog/tree/main/LLMs/model-compression)

## Intended uses & limitations

This model was created for educational purposes.

## Training and evaluation data

The Training, Testing, and Validation data are available here: [shawhin/phishing-site-classification](https://huggingface.co/datasets/shawhin/phishing-site-classification).