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SQL-R1 is a new NL2SQL reasoning model trained using reinforcement learning, designed to convert natural language queries into structured SQL statements. The model overcomes limitations of supervised fine-tuning, particularly in complex scenarios with multi-table joins and nested queries. SQL-R1 achieves high accuracy rates on benchmark datasets Spider and BIRD using a small amount of synthetic data. The innovative training strategies include a specialized RL-based reward function and effective cold start processes, which enhance the model's learning and performance in various database applications.

SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning

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