This is a starter post. Replace it with a real write-up when you are ready.
Key Principles
For experiment-heavy work, the basics matter: fixed seeds, versioned data, committed config files, clear metrics, and a short note explaining what changed between runs.
Checklist
- Fix random seeds in PyTorch/NumPy.
- Log exact data hash / git commit.
- Track metrics using standard logs.