Model Overview

Jason-hu/Qwen2.5-3B-GSM8K-SFT is a specialized 3.1 billion parameter language model derived from the Qwen2.5-3B-Instruct base. It has been specifically fine-tuned to enhance its capabilities in mathematical reasoning.

Key Capabilities

• Mathematical Reasoning: Optimized for solving grade school mathematics problems.
• Fine-tuned Performance: Utilizes LoRA SFT (Supervised Fine-Tuning) on the GSM8K dataset to improve accuracy in math-related tasks.
• Base Architecture: Built on the robust Qwen2.5-3B-Instruct model, providing a strong foundation for language understanding.
• Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer problem descriptions or multi-step reasoning.

Good For

• Educational Applications: Ideal for systems requiring automated solutions or explanations for grade school math problems.
• Research in Mathematical LLMs: Useful for researchers exploring the effectiveness of fine-tuning smaller models for specific reasoning domains.
• Benchmarking: Can serve as a baseline or comparison model for evaluating performance on mathematical datasets like GSM8K.