# Evidence: Adapt a pretrained model and choose a post-training objective

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

## Evidence required

Source/checkpoint hashes, independent loss and gradient, disjoint evaluation results and teacher-failure diagnosis. Keep the environment, observed outputs and your explanation of the figure.

- Command: `python3 phases/15-deployment/02-adapt-a-pretrained-model-and-choose-a-post-training-objective/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