MMR1/MMR1-Math-v0-7B
MMR1/MMR1-Math-v0-7B is a 7 billion parameter multimodal model developed by MMR1, specialized in mathematical tasks. It achieves state-of-the-art performance among open-source 7B multimodal models on math-related benchmarks, competing with larger proprietary models despite being trained on only 6k high-quality data instances. This model is optimized for complex mathematical reasoning and problem-solving, making it suitable for applications requiring advanced numerical and logical understanding from multimodal inputs.
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MMR1-Math-v0-7B: Multimodal Mathematical Reasoning Model
MMR1-Math-v0-7B is a 7 billion parameter Large Multimodal Model (LMM) specifically designed for advanced mathematical tasks. Developed by MMR1, this model demonstrates state-of-the-art performance among open-source 7B multimodal models in mathematical reasoning, even rivaling larger proprietary models.
Key Capabilities
- SOTA Performance: Achieves leading results on math-related multimodal benchmarks such as MathVista, MathVision, LogicVista, and MathVerse.
- Data Efficiency: Remarkably trained on only 6k carefully curated, high-quality data instances from public datasets, showcasing significant efficiency.
- Balanced Data Strategy: Utilizes a balanced data sampling approach, considering both task difficulty and the diversity of mathematical problem types.
- Efficient Training: Leverages GRPO for efficient reinforcement learning training.
Good For
- Applications requiring multimodal mathematical reasoning and problem-solving.
- Research and development in efficient LMM training with minimal data.
- Benchmarking and comparison against other open-source and proprietary multimodal models in mathematical domains.