Fake / True News Detection

In this notebook I conduct an exploratory data analysis on the text data. Then, I train three models for fake news detection. Data is taken from this kaggle competition.

The models are:

• The pretrained DistilBERT and ALBERT Base v1 models using implementations from the Hugging Face framework. I used transfer learning to retrain these two models for fake news detection.
• XGBoost Classifier from the XGBoost library with TF-IDF features.

Results

Model	Dataset	Accuracy	F1-Score
DistilBERT	Validation	0.9996	0.9996
	Test	0.9998	0.9998
ALBERT Base v1	Validation	0.999	0.999
	Test	0.9998	0.9998
XGBClassifier	Validation	0.975	0.975
	Test	0.973	0.973