A new era for AI maths whizzes
Alibaba Cloud’s Qwen team has unveiled Qwen2-Math, a series of large language models specifically designed to tackle complex mathematical problems.
These new models – built upon the existing Qwen2 foundation – demonstrate remarkable proficiency in solving arithmetic and mathematical challenges, and outperform former industry leaders.
The Qwen team crafted Qwen2-Math using a vast and diverse Mathematics-specific Corpus. This corpus comprises a rich tapestry of high-quality resources, including web texts, books, code, exam questions, and synthetic data generated by Qwen2 itself.
Rigorous evaluation on both English and Chinese mathematical benchmarks – including GSM8K, Math, MMLU-STEM, CMATH, and GaoKao Math – revealed the exceptional capabilities of Qwen2-Math. Notably, the flagship model, Qwen2-Math-72B-Instruct, surpassed the performance of proprietary models such as GPT-4o and Claude 3.5 in various mathematical tasks.
“Qwen2-Math-Instruct achieves the best performance among models of the same size, with RM@8 outperforming Maj@8, particularly in the 1.5B and 7B models,” the Qwen team noted.
This superior performance is attributed to the effective implementation of a math-specific reward model during the development process.
Further showcasing its prowess, Qwen2-Math demonstrated impressive results in challenging mathematical competitions like the American Invitational Mathematics Examination (AIME) 2024 and the American Mathematics Contest (AMC) 2023.
To ensure the model’s integrity and prevent contamination, the Qwen team implemented robust decontamination methods during both the pre-training and post-training phases. This rigorous approach involved removing duplicate samples and identifying overlaps with test sets to maintain the model’s accuracy and reliability.
Looking ahead, the Qwen team plans to expand Qwen2-Math’s capabilities beyond English, with bilingual and multilingual models in the pipeline. This commitment to inclusivity aims to make advanced mathematical problem-solving accessible to a global audience.
“We will continue to enhance our models’ ability to solve complex and challenging mathematical problems,” affirmed the Qwen team.
You can find the Qwen2 models on Hugging Face here.
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