Adapt a model with internal classification data.
Measure performance independently after adaptation.
Choose two appropriate practices.
Separate adaptation and evaluation data without entity overlap, and include production boundary and safety examples in the held-out set.
Detailed explanation
The evaluation reflects real risks.
The held-out set is no longer independent.
Generalization cannot be measured if the same data is reused.
Overfitting is hidden.
Check official documentation
Compare the following points with the official documentation.
Amazon Bedrock公式モデルカスタマイズとAIF-C01 Domain 3.1・3.3を確認する。
Official references
What to confirm
適応データと独立評価データの分離理由を説明できる。
Key points
- Adaptation
- Independent evaluation
- Boundary cases
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Independent evaluation
Testing on data not used to adapt or select a model, providing less biased evidence.
Boundary case
An example near a decision or safety boundary where errors are more likely.