metadata
license: apache-2.0
language:
- en
pretty_name: j
size_categories:
- n<1K
CenQuery: Indian Census Text-to-SQL Dataset
Project Overview
CenQuery is a specialized Text-to-SQL system designed for Indian Census Data. This dataset was used to fine-tune the defog/llama-3-sqlcoder-8b model using QLoRA to handle complex natural language queries related to demographics, healthcare, and regional statistics.
Dataset Composition
The dataset is split into two primary components to ensure a rigorous evaluation of the model's generalization capabilities:
- Training Set (
old_train_(Mixed).jsonl): 650 instruction-tuned examples covering diverse query patterns and schema joins. - Evaluation Set (
old_eval_(Mixed).jsonl): 150 unseen questions used for final benchmarking and metric calculation (Execution Accuracy and Exact Match).
Schema Information
The queries operate on a relational schema representing several key census sectors:
- Population Stats: Age-wise and gender-wise population data.
- Healthcare Stats: Vaccination and health infrastructure metrics.
- Religion/Language Stats: Distribution of religious groups and linguistic data.
- Crop Stats: Agricultural data including area sown and foodgrain statistics.
Full DDL definitions are provided in the database_schema.json file in this repository.
Prompt Format
The data follows the SQLCoder-8B instruction format:
### Task: The natural language question.### Database Schema: Relevant table DDLs.### SQL: The ground-truth SQL query.
Citation
If using this dataset for research, please cite the CenQuery Project.