hdong0/Qwen3-8B-base-Open-R1-GRPO_dapo_acc_16384_nokl
hdong0/Qwen3-8B-base-Open-R1-GRPO_dapo_acc_16384_nokl is an 8 billion parameter language model, fine-tuned from the Qwen3-8B-Base architecture. Developed by hdong0, this model specializes in mathematical reasoning, having been trained with the GRPO method on the DAPO-Math-17k-Processed dataset. It is optimized for tasks requiring advanced mathematical problem-solving capabilities, leveraging a 32768 token context length.
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Model Overview
This model, hdong0/Qwen3-8B-base-Open-R1-GRPO_dapo_acc_16384_nokl, is an 8 billion parameter language model derived from the Qwen3-8B-Base architecture. It has been specifically fine-tuned to enhance its mathematical reasoning abilities.
Key Capabilities & Training
- Mathematical Reasoning: The model's primary strength lies in mathematical problem-solving, achieved through fine-tuning on the open-r1/DAPO-Math-17k-Processed dataset.
- GRPO Method: Training incorporated the GRPO (Gradient-based Reward Policy Optimization) method, as detailed in the research paper "DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models" (arXiv:2402.03300). This method is designed to improve mathematical reasoning performance.
- Context Length: It supports a substantial context length of 32768 tokens, allowing for processing longer and more complex mathematical problems or discussions.
- Framework: The fine-tuning process utilized the TRL library from Hugging Face.
Use Cases
This model is particularly well-suited for applications requiring robust mathematical reasoning, such as:
- Solving complex math problems.
- Assisting in educational contexts for mathematical explanations.
- Developing tools for scientific computation and analysis.