Reward Models Surface Odd Gemma SFT Outputs
A researcher scans Gemma supervised fine-tuning outputs with experimental reward models to surface the lowest-scoring samples.
kalomaze, a research engineer at Prime Intellect focused on reinforcement learning for LLMs, posted about building experimental reward models. These models scan samples of Gemma SFT outputs to locate the worst-scored results, which the post describes as immaculate gemeralds at the tail. The approach is presented as a way to identify unusual generations. A reply from xlr8harder called the idea amazing. Visible posts show the method highlights repetitive or surreal outputs among the lowest-scoring items in the scanned set.
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Reward Models Surface Odd Gemma SFT Outputs
A researcher scans Gemma supervised fine-tuning outputs with experimental reward models to surface the lowest-scoring samples.
kalomaze, a research engineer at Prime Intellect focused on reinforcement learning for LLMs, posted about building experimental reward models. These models scan samples of Gemma SFT outputs to locate the worst-scored results, which the post describes as immaculate gemeralds at the tail. The approach is presented as a way to identify unusual generations. A reply from xlr8harder called the idea amazing. Visible posts show the method highlights repetitive or surreal outputs among the lowest-scoring items in the scanned set.
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building experimental reward models and searching samples of gemma SFT outputs for "worst scored"... this process locates some immaculate gemeralds at the tail
@kalomaze honestly an amazing idea