student-run-experiment

name	student-run-experiment
description	Execute experiments reproducibly and publish usable results instead of private logs.

Student Run Experiment

Student-specific extensions

• Record artifact destinations before the run starts.
• Separate observations from interpretation in the results write-up.
• Summarize failures, not just wins.
• Update the Research task board task with the real artifact list after publishing results.

Purpose

Execute an experiment according to a published experiment plan, ensuring reproducibility and proper logging.

Workflow

1. Read plan: Load the experiment plan from your canonical shared artifact directory: {artifact_dir}/{student}/experiment_plan_{id}.md
2. Set up environment: Install dependencies, configure GPU, set seeds
3. Implement: Write code in workspace/
4. Execute: Run training/evaluation with full logging
5. Collect results: Gather metrics, generate figures
6. Publish: Write results to your canonical shared artifact directory: {artifact_dir}/{your-name}/experiment_results_{id}.md
7. Export reviewable evidence: Copy logs, figures, and any code/config snapshot needed for review into {artifact_dir}/{your-name}/support/{id}/
8. Update the Research task board: bash ../../scripts/lab-kanban.sh -caller <your-name> -submit -id <ID> -artifacts "..."

Reproducibility Checklist

Before running, verify:

• Random seeds are fixed (Python, NumPy, PyTorch/TF)
• Dependencies are locked (requirements.txt or environment.yml)
• Hyperparameters are logged (config file or command-line args)
• Data loading is deterministic
• Git hash of code is recorded
• GPU/hardware info is logged

Results Format

# Experiment Results: {title}

## Setup
- **Plan**: {artifact_dir}/{student}/experiment_plan_{id}.md
- **Code snapshot**: {artifact_dir}/{your-name}/support/{id}/code/
- **Environment**: Python X.Y, PyTorch X.Y, CUDA X.Y
- **Hardware**: GPU type, count
- **Seeds**: [42, 123, 456]
- **Git hash**: ...

## Results

### Main Results
| Method | Metric1 | Metric2 | Metric3 |
|---|---|---|---|

### Ablation Results
| Variant | Metric1 | Metric2 |
|---|---|---|

## Analysis
Key observations and interpretation.

## Figures
- `figures/main_comparison.png`
- `figures/ablation.png`

## Logs
- `{artifact_dir}/{your-name}/support/{id}/run_001.log`

## Issues
Any problems encountered during execution.

Error Handling

• If an experiment fails, log the error and notify the requesting student via the canonical shared message directory from your AGENTS/CLAUDE instructions
• Partial results are valuable — publish what you have with clear notes on what's missing
• If resource limits are hit, report to supervisor with a message of type question