Shubhamsaboo/Qwen3-Coder
Mar 2025 – Mar 2025
1 Month active
Languages Used
Python
Technical Skills
Code RefactoringData EvaluationMachine LearningNatural Language ProcessingSQL
lfy79001
PROFILE
Lfy79001
In March 2025, Shubhamsaboo developed the Bird-Spider SQL Generation Evaluation Framework within the Qwen3-Coder repository, creating a unified benchmarking solution for SQL generation models across the Bird and Spider datasets. Leveraging Python and SQL, Shubhamsaboo implemented components for data preprocessing, model generation, and execution-based evaluation of SQL queries, enabling reproducible and transparent model assessment. The work included code refactoring to remove legacy evaluation files, which streamlined the framework and reduced maintenance complexity. This project demonstrated depth in data evaluation and natural language processing, establishing a foundation for faster iteration and clearer visibility into model performance for future development cycles.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
3,142
Activity Months1
Your Network
15 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered the Bird-Spider SQL Generation Evaluation Framework for Qwen3-Coder, establishing a unified benchmarking approach for SQL generation across Bird and Spider datasets. Included components for data preprocessing, model generation, and execution-based evaluation of SQL queries, plus cleanup/refactor removing legacy evaluation files to streamline maintenance. This work enables reproducible benchmarking, faster iteration, and clearer visibility into model performance.
2 Commits • 1 Features
Mar 1, 2025March 2025: Delivered the Bird-Spider SQL Generation Evaluation Framework for Qwen3-Coder, establishing a unified benchmarking approach for SQL generation across Bird and Spider datasets. Included components for data preprocessing, model generation, and execution-based evaluation of SQL queries, plus cleanup/refactor removing legacy evaluation files to streamline maintenance. This work enables reproducible benchmarking, faster iteration, and clearer visibility into model performance.
March 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture85.0%
Performance75.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Code RefactoringData EvaluationMachine LearningNatural Language ProcessingSQL
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