when-debugging-ml-training-use-ml-training-debugger
CommunityDiagnose and fix ML training quickly.
AuthorDNYoussef
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Systematic workflow for debugging ML training, covering loss divergence, NaN losses, overfitting, and slow convergence, with phase-based execution and actionable feedback.
Core Features & Use Cases
- 5-Phase Process: Diagnose, analyze root cause, apply fixes, validate, and optimize performance.
- Diagnostic Outputs: Generates diagnostic reports and before/after comparisons.
- Actionable Fixes: Recommendations for learning rate, regularization, and data handling.
Quick Start
Run the ML Training Debugger on your training script to get a diagnostic report, apply fixes, and compare performance.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 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: when-debugging-ml-training-use-ml-training-debugger Download link: https://github.com/DNYoussef/ai-chrome-extension/archive/main.zip#when-debugging-ml-training-use-ml-training-debugger Please download this .zip file, extract it, and install it in the .claude/skills/ directory.