Supplying movie reviews translated into Urdu across two sentiment categories: positive and negative. It structures data into sentence and sentiment fields to facilitate supervised learning for Urdu natural language processing.
Use Cases
- Train a sentiment analysis model for Urdu using the sentence and sentiment columns
- Evaluate the accuracy of Urdu language models on binary classification tasks
- Fine-tune multilingual BERT or similar architectures on the sentence field for domain-specific Urdu understanding
Strengths
- Includes a sentence column containing Urdu-translated movie reviews
- Features a sentiment column with binary labels for positive and negative reviews
- Provides a direct Urdu mapping of the standard IMDb sentiment analysis benchmark