| # Processed MultiSpider Dataset | |
| This is a processed version of the MultiSpider dataset with the following enhancements: | |
| - Combined questions from multiple languages (en, de, es, fr, ja, vi, zh) | |
| - Added complexity levels for each SQL query (easy, medium, hard) | |
| - Split into balanced train and test sets | |
| ## Dataset Statistics | |
| - Train set: 4248 examples | |
| - Test set: 1064 examples | |
| - Languages: English, German, Spanish, French, Japanese, Vietnamese, Chinese | |
| - Database files: 166 SQLite files | |
| ## Format | |
| Each example follows this structure: | |
| ```json | |
| { | |
| "db_id": "database_name", | |
| "query": "SELECT * FROM table WHERE condition", | |
| "complexity_level": "easy|medium|hard", | |
| "questions": { | |
| "en": "English natural language question", | |
| "de": "German natural language question", | |
| "es": "Spanish natural language question", | |
| "fr": "French natural language question", | |
| "ja": "Japanese natural language question", | |
| "vi": "Vietnamese natural language question", | |
| "zh": "Chinese natural language question" | |
| } | |
| } | |
| ``` | |
| ## Usage | |
| This dataset is ideal for: | |
| 1. Supervised Fine-Tuning (SFT) of text-to-SQL models | |
| 2. Curriculum learning (using complexity levels) | |
| 3. Cross-lingual training and evaluation | |
| 4. Guided Reinforcement Learning from Policy Optimization (GRPO) | |