DeepSeek R1: Open-Source Model Challenges OpenAI in Complex Reasoning
DeepSeek R1, an open-source model, is challenging OpenAI's models in complex reasoning tasks. Utilizing Group Relative Policy Optimization (GRPO) and an RL-focused multi-stage training approach, the creators released not only the model but also a research paper detailing its development. The paper describes an "aha moment" during training where the model learned to allocate more thinking time to a problem by reevaluating its initial approach, without human feedback. This blog post recreates this "aha moment" using GRPO and the Countdown game, training an open model to learn self-verification and search abilities. An interactive Jupyter Notebook code, along with scripts and instructions for distributed training on multi-GPU nodes or SLURM clusters, is provided to facilitate learning GRPO and TRL.
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