Practice vocabulary for communicating model evaluation results: benchmark statements, practical vs. benchmark significance, caveats, and presenting results to non-technical stakeholders.
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In the report you write: 'The model ___ 91.4% on the SQuAD benchmark.' What verb is standard here?
'The model achieves X on Y benchmark' is the standard phrasing. 'Achieves' communicates a measured score without over-claiming; alternatives like 'wins' or 'dominates' add editorial bias.
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A colleague asks about the gap between ___ significance and benchmark score. What distinction are they raising?
Practical significance asks: does this benchmark improvement translate to better real-world outcomes? A 0.3% gain on a benchmark may be statistically significant but practically irrelevant if users cannot perceive or benefit from it.
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You tell stakeholders: 'This result has ___.' What are you preparing them for?
'This result has caveats' signals that the number should not be taken at face value — for example, the test set may not match production distribution, the metric may not capture what matters, or the evaluation was run under favourable conditions.
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When presenting to non-technical stakeholders you translate F1 score into ___ terms they can act on.
Non-technical stakeholders need to understand what a metric means for their goals. Translating F1 into business terms means explaining: 'In practice, this means 1 in 10 recommendations will be wrong,' or similar actionable framing.
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The evaluation memo states: 'Results are ___ to the conditions of our internal test set.' What does this caveat mean?
'Results are specific to our internal test set' warns that the evaluation was conducted under particular conditions (domain, language, time period, user base) and the scores may not hold in different deployment contexts.