Update README.md

## Overview
Arctic-Text2SQL-R1-7B is a 7-billion-parameter Text-to-SQL model fine-tuned using Group Relative Policy Optimization (GRPO) with a simple execution-based reward signal. It converts natural language questions into executable SQL queries.

## Key Features

- **Lightweight RL formulation**: Uses only execution correctness and syntax validity as rewards.
- **State-of-the-art performance**: Achieves 68.9% execution accuracy on BIRD-dev and 68.5% on BIRD-test, with an average of 57.2% across six benchmarks (BIRD, Spider, Spider2.0, Spider-DK, EHRSQL, ScienceBenchmark)
- **Efficiency**: Outperforms many 70B+ models with only 7B parameters.

## Intended Use

This model is designed for:

- Interactive natural language interfaces to relational databases.
- Data analytics tools enabling non-technical users to query databases.

### Not intended for:
- Generation of non-SQL text or free-form natural language tasks.
- Production systems without validation, especially in safety-critical domains.

| Benchmark | Dev/Test Accuracy |
| ---------------- | ----------------- |
| BIRD-dev | 68.9% |
| BIRD-test | 68.5% |
| Spider-test | 88.8% |
| Spider2.0-DK | 15.6% |
| EHRSQL | 36.7% |
| ScienceBenchmark | 51.8% |
| **Average** | **57.2%** |


## Ethical Considerations
- Avoid using for private or sensitive data without proper oversight.
- Validate generated SQL to prevent data leakage or unauthorized access.

README.md

@@ -2,4 +2,12 @@
 license: apache-2.0
 base_model:
 - Qwen/Qwen2.5-Coder-7B-Instruct
----
+---
+
+## Overview
+Arctic-Text2SQL-R1-7B is a 7-billion-parameter Text-to-SQL model fine-tuned using Group Relative Policy Optimization (GRPO) with a simple execution-based reward signal. It converts natural language questions into executable SQL queries.
+
+## Key Features
+
+- **Lightweight RL formulation**: Uses only execution correctness and syntax validity as rewards.
+- **State-of-the-art performance**: chieves 68.9% execution accuracy on BIRD-dev and 68.5% on BIRD-test, with an average of 57.2% across six benchmarks (BIRD, Spider, Spider2.0, Spider-DK, EHRSQL, ScienceBenchmark)