AI2sql
AI2sql is a state-of-the-art LLM for converting natural language questions to SQL queries.
Model Card: Fine-tuning Llama 2 for AI2SQL Query Generation
This model card outlines the fine-tuning of the Llama 2 model to generate SQL queries for AI2SQL tasks.
Model Details
- Original Model: NousResearch/Llama-2-7b-chat-hf
- Model Type: Large Language Model
- Fine-tuning Task: AI2SQL (SQL Query Generation)
- Fine-tuned Model Name: llama-2-7b-miniguanaco
Implementation
- Environment Requirement: GPU-supported platform with minimum 20GB RAM.
- Dependencies: accelerate==0.21.0, peft==0.4.0, bitsandbytes==0.40.2, transformers==4.31.0, trl==0.4.7
- GPU Specification: T4 or equivalent (as of 24 Aug 2023)
Training Details
- Dataset: WikiSQL
- Method: Supervised Fine-Tuning (SFT)
- Epochs: 1
- Batch Size: 4 per GPU
- Optimization: AdamW with cosine learning rate schedule
- Learning Rate: 2e-4
- Special Features:
- LoRA for efficient parameter adjustment.
- 4-bit precision model loading with BitsAndBytes.
- Gradient checkpointing and clipping.
Performance Metrics
- Accuracy: 85% (on a held-out test set from WikiSQL)
- Query Generation Time: Average of 0.5 seconds per query
- Resource Efficiency: Demonstrates 30% reduced memory usage compared to the base model
Usage and Applications
TBD
Note: The performance metrics provided here are hypothetical and for illustrative purposes only. Actual performance would depend on various factors, including the specifics of the dataset and training regimen.
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