metadata

license: apache-2.0
datasets:
  - shawhin/phishing-site-classification
metrics:
  - accuracy
  - recall
  - precision
  - f1
base_model: distilbert/distilbert-base-uncased
pipeline_tag: text-classification
library_name: transformers

bert-phishing-classifier_student

This model is modified version of distilbert/distilbert-base-uncased trained via knowledge distillation from shawhin/bert-phishing-classifier_teacher using the shawhin/phishing-site-classification dataset. It achieves the following results on the testing set:

Loss (training): 0.0563
Accuracy: 0.9022
Precision: 0.9426
Recall: 0.8603
F1 Score: 0.8995

Model description

Student model for knowledge distillation example.

Video | Blog | Example code

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.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 32
eval_batch_size: 32
num_epochs: 5
temperature: 2.0
adam optimizer alpha: 0.5