Fine-tuning large language models (LLMs) using solution fine-tuning, solution-cluster re-ranking, and multi-task sequential fine-tuning improves their performance in solving math problems, achieving 58.8% accuracy on the MATH dataset.

https://arxiv.org/abs//2310.10047

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