An evaluation collection should expose the conditions your team wants to measure. Start with the model task and the deployment questions that remain unresolved. Fiund can discuss sourcing or collection requirements for a proposed evaluation set, with availability, annotation scope, and use permissions assessed for that project.
Define the evaluation target
Specify whether the model recognizes actions, localizes events, follows objects, or answers questions. Decide what evidence the evaluator may inspect and how incomplete observations affect scoring. A useful brief includes representative correct outputs and boundary cases rather than relying on a category name alone.
Choose meaningful held-out conditions
Reserve participants, locations, objects, or task variants according to the generalization question. Avoid calling footage independent merely because it has different filenames. Track sessions and derived clips so neighboring segments from one recording cannot quietly enter both training and evaluation collections.
Separate difficulty from corruption
Natural occlusion and changing viewpoints may be intentional test conditions. Missing files, broken timestamps, and labels attached to the wrong clip are integrity problems. Record these separately so a difficult benchmark is not simply an inconsistent one. Define exclusions before reviewing model outputs.
Make the review reproducible
Keep an evaluation manifest, annotation guidance, and a version identifier. Record corrections with affected examples and reasons. If answers depend on subjective interpretation, establish a resolution process and retain uncertain cases explicitly. This makes later comparisons easier to interpret when the collection evolves. Keep model-assisted annotation provenance visible and arrange independent review of answer evidence where required. Do not silently redefine labels after seeing one model’s mistakes; record any correction and its effect on earlier results.
Include in your inquiry
- Task outputs and scoring interpretation
- Held-out participants or environments
- Difficulty categories and integrity checks
- Versioning and annotation review process