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thistleknotthistleknot/skills/cross-hatch-sampling/SKILL.md

cross-hatch-sampling

Skill0 starsChanged 6 months agoNo licenceView on GitHub

Two-axis class-balanced batch construction that projects dataset source (Y) and answer type (X) simultaneously to express the full latent representation across training batches. Uses MMR-style deficit-driven selection: each draw goes to the (regime, source) cell furthest below its target ratio, ensuring convergence on both axes without maintaining separate trackers. Use when constructing RL/SFT batches that must cover all answer-type behaviors without lopsided F1, sizing HPO batches small enough for bounded trials while guaranteeing regime representation, or selecting few-shot exemplars that cover answer formats AND dataset diversity simultaneously. Trigger on "class balance my batch", "regime coverage", "answer type sampling", "two-axis MMR", "cross-hatch", or "lopsided F1 from unbalanced batches".

The file

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2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

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    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

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    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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