DataGpt-SQL-7B: An Open-Source Language Model for Text-to-SQL
Lixia Wu, Peng Li, Junhong Lou, Lei Fu
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/cainiaotechai/datagpt-sql-7bOfficialIn paper★ 7
Abstract
In addressing the pivotal role of translating natural language queries into SQL commands, we propose a suite of compact, fine-tuned models and self-refine mechanisms to democratize data access and analysis for non-expert users, mitigating risks associated with closed-source Large Language Models. Specifically, we constructed a dataset of over 20K sample for Text-to-SQL as well as the preference dateset, to improve the efficiency in the domain of SQL generation. To further ensure code validity, a code corrector was integrated into the model. Our system, DataGpt-sql, achieved 87.2\% accuracy on the spider-dev, respectively, showcasing the effectiveness of our solution in text-to-SQL conversion tasks. Our code, data, and models are available at https://github.com/CainiaoTechAi/datagpt-sql-7b
Tasks
Benchmark Results
| Dataset | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| spider | datagpt-sql-7B + InvalidSQL-Feedback | Execution Accuracy (Dev) | 87.2 | — | Unverified |
| spider | datagpt-sql-7B | Execution Accuracy (Dev) | 84.8 | — | Unverified |