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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ base_model:
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+ - Qwen/Qwen2.5-Coder-1.5B-Instruct
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+ pipeline_tag: translation
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+ ---
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+
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+ ### Performance on the BIRD Development Set
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+
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+ We further evaluate **DatA-SQL-1.5B** on the **BIRD** development set using self-consistency voting.
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+ Under **Vote@8**, our model achieves an **execution accuracy (EX) of 55.86 %**, establishing a new state of the art among open-source Text-to-SQL systems at the 1.5 B scale.
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+ This result demonstrates that even compact models can acquire strong reasoning and SQL generation abilities when trained with our **reasoning-guided data augmentation** and **execution-aware multi-agent framework**.
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+ The lightweight design ensures low training and inference costs while maintaining high execution robustness.
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+ Overall, **DatA-SQL-1.5B** achieves competitive accuracy compared with much larger GPT-based pipelines, highlighting the efficiency and practicality of our approach.