Update README.md

README.md

@@ -1,3 +1,40 @@
----
-license: mit
----
+---
+license: cc-by-4.0
+language:
+  - en
+tags:
+  - summarization
+  - text-generation
+  - NLP
+  - transformers
+datasets:
+  - your-dataset-name
+---
+
+# BART Fine-Tuned Summarization Model
+
+This repository hosts a **BART-based model fine-tuned for text summarization** on a custom dataset of articles and highlights. The model is suitable for **generating concise summaries from long-form text**.
+
+---
+
+## Model Overview
+
+- **Base Model:** `facebook/bart-large-cnn`
+- **Task:** Text Summarization
+- **Fine-Tuning Dataset:** Custom CSV dataset containing `document` and `summary` columns
+- **Dataset Size:** Varies depending on your CSV file
+- **Framework:** Hugging Face Transformers
+- **Language:** English
+
+---
+
+## Dataset Preparation
+
+1. Load your CSV dataset containing columns: `article` (renamed to `document`) and `highlights` (renamed to `summary`).  
+2. Clean the dataset by removing missing or non-string entries.  
+3. Split the dataset into **train** and **validation** sets (80/20 split).  
+
+```python
+from datasets import Dataset
+dataset = Dataset.from_pandas(df)
+dataset = dataset.train_test_split(test_size=0.2, seed=42)