# Evidence: Masked image modeling: reconstruct missing patches

Copy this template into your own portfolio and fill it after running your modified exercise.

## Evidence required

Keep patch-order slices, visible-only feature shapes, hidden-patch counts, independent MSE and held-amplitude reconstruction results.

- Command: `python3 phases/17-pretraining/02-mim/code/main.py`
- Working directory: repository root
- Python / JAX / NumPy versions: 
- Hardware and device: 
- My prediction before running: 
- My change to the exercise: 
- Exit code and meaningful output: 
- Why the result supports or contradicts my prediction: 
- Checkpoint result: 
- Artifact link or saved filename: 
- Portfolio status: saved in local workspace