An adaptation dataset consists mostly of long boilerplate with a small number of useful instructions. What should the team do before a costly training run?

1. Duplicate all boilerplate until the dataset is ten times larger.
2. Discard the useful instructions and keep only file names.
3. Assume any larger corpus always produces a better task model.
4. Inspect, filter, and validate representative examples for the target behavior.