post-training-eval-report

Community

Concisely interpret and report on post-training model evaluations.

AuthorKirillKlem
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill solves the challenge of effectively interpreting and summarizing post-training model evaluation results. It helps users discern the significance of changes in model performance metrics and identifies actionable insights from experimental comparisons.

Core Features & Use Cases

  • Metric Interpretation: Analyze changes in model performance metrics to discern signal from noise.
  • Result Comparison: Compare and contrast multiple training runs, checkpoints, or ablations.
  • Evaluation Reports: Prepare structured reports outlining model evaluation outcomes and recommended next steps.
  • Use Case: Suppose you have several checkpoints from a model training process, and you need to analyze the impact of various ablations on model performance.

Quick Start

Analyze and interpret the results of the experiment by running 'analyze-results -r /path/to/experiment/folder'.

Dependency Matrix

Required Modules

None required

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: post-training-eval-report
Download link: https://github.com/KirillKlem/codex-skills/archive/main.zip#post-training-eval-report

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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