InfiniAILab/OpenR1-Qwen-7B-Math-Instruct
The InfiniAILab/OpenR1-Qwen-7B-Math-Instruct is a 7.6 billion parameter language model, fine-tuned from Qwen/Qwen2.5-Math-7B-Instruct. Developed by InfiniAILab, this model specializes in mathematical reasoning and problem-solving. It was trained on the OpenR1-Math-220k dataset, making it particularly adept at handling complex mathematical tasks. With a context length of 32768 tokens, it is designed for applications requiring robust mathematical instruction following.
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Model Overview
InfiniAILab/OpenR1-Qwen-7B-Math-Instruct is a 7.6 billion parameter language model, fine-tuned from the Qwen/Qwen2.5-Math-7B-Instruct base model. Its primary focus is on enhancing mathematical reasoning and instruction following capabilities. The model was specifically trained using the open-r1/OpenR1-Math-220k dataset, a specialized collection for mathematical problems.
Key Capabilities
- Specialized Mathematical Reasoning: Optimized for understanding and solving mathematical problems, building upon the Qwen2.5-Math-7B-Instruct foundation.
- Instruction Following: Designed to accurately follow mathematical instructions and generate relevant responses.
- Extended Context: Supports a context length of 32768 tokens, allowing for processing longer and more complex mathematical queries.
Training Details
The model was fine-tuned using the TRL library with an SFT (Supervised Fine-Tuning) approach. This training methodology leverages the OpenR1-Math-220k dataset to imbue the model with strong mathematical proficiency. The training process can be visualized via Weights & Biases, as linked in the original model card.