- Add 60 new agents across all 10 categories (75 -> 135) - Add 95 new plugins with command files (25 -> 120) - Update all agents to use model: opus - Update README with complete plugin/agent tables - Update marketplace.json with all 120 plugins
664 B
664 B
Track an ML experiment by logging parameters, metrics, and artifacts for comparison.
Steps
- Define the experiment metadata:
- Log hyperparameters:
- Log metrics during and after training:
- Save artifacts:
- Record environment details:
- Tag the experiment with status (running, completed, failed).
- Store results in a structured format for later comparison.
Format
Experiment: <name>
Date: <timestamp>
Hypothesis: <what is being tested>
Params: { learning_rate: X, batch_size: Y, ... }
Rules
- Always log random seeds for reproducibility.
- Record the exact dataset version used.
- Never overwrite previous experiment results.