Model Overview

The Omaratef3221/Qwen2-0.5B-Instruct-SQL-query-generator is a specialized 0.5 billion parameter model, fine-tuned from Qwen/Qwen2-0.5B-Instruct. Its core function is to convert natural language text into SQL queries. The model was trained on the first 10,000 rows of the motherduckdb/duckdb-text2sql-25k dataset, focusing on text-to-SQL generation.

Key Capabilities

• Natural Language to SQL Conversion: Translates text prompts into executable SQL queries.
• Database Interaction: Facilitates data retrieval from databases using natural language commands.
• Interface Building: Supports the development of natural language interfaces for database systems.

Training Details

The model was fine-tuned with a learning rate of 1e-4, a batch size of 8, and 5 epochs. While specific performance metrics like accuracy, precision, recall, and F1-score were used for evaluation, their values are not explicitly provided in the README. Users should review generated SQL queries for accuracy and security before execution.

Good For

• Developers needing to integrate natural language query capabilities into database applications.
• Prototyping text-to-SQL features where a compact, specialized model is beneficial.
• Educational purposes to understand fine-tuning for specific NLP tasks.