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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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### Performance on the BIRD Development Set |
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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**. |
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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. |
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