metadata

license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - fake-news
  - real-news
  - binary-classification
  - transformers
pretty_name: Fake New News Detection Dataset
size_categories:
  - 10K<n<100K

license: mit task_categories: - text-classification language: - en tags: - fake-news - real-news - binary-classification - transformers pretty_name: Fake New News Detection Dataset size_categories: - 10K<n<100K

NewsFineTuning

A combined dataset of fake and true news articles for binary classification.

Files

train.csv – 70% training data
val.csv – 15% validation data
test.csv – 15% test data

Each CSV contains:

title — Article title
text — Full article content
subject — Topic category
date — Published date
label — 0 = Real, 1 = Fake

Task

This dataset is ideal for:

Fake news detection
Binary classification
Fine-tuning transformers (e.g., DistilBERT)

Load with Datasets

from datasets import load_dataset

dataset = load_dataset("declan101/NewsFineTuning")