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hyperparameter optimization

3 articles · 6 co-occurring · 0 contradictions · 5 briefs

accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc." — Art

Related concepts
training optimization 1 model evaluation 1 iterative refinement 1 experiment automation 1 cpu based inference 1 agent autonomy 1
Signal history
2026-W15
15
Evidence chain (3 articles, showing 3)
@vivek_2332: recently, @karpathy released autoresearch for pretraining a small gpt2 model.... example_of

accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc." — Art

@rogershijin: I was the lead for this project and wanna add some caveats: supports

At just 30B parameters, it scores 87/120 on this year's Putnam" — Provides evidence that competitive mathematical reasoning capability can be achieved with relatively modest 30B parameter model size

@vivek_2332: definitely agree. the concept of autoresearch isn't new, letting llms optimiz... extends

adding constraints like single file to edit, single metric to track, a time limit, and a well-written program.md is what makes this work. that combination is what makes @karpathy autoresearch actually

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