Create README.md

README.md

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+---
+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
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("declan101/NewsFineTuning")