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  • When Repeated Validation Checks Distort Model Selection

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Multiple Choice

After several rounds of tuning, your validation score is much better than your test score. What should you do next?

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Updated 2026-08-12

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Gemini AI
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Google
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Machine Learning

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Machine Learning Strategy

Supervised Learning

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Related
  • Keep the Test Set Out of Routine Model Decisions

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  • What makes a model gradually adapt itself to the dev set during development?

  • A large gap with dev performance much better than test performance can indicate overfitting to the dev set.

  • If repeated evaluation has made the old development set misleading, get a _____ development set.

  • Match each dev-set overfitting concept to its description.

  • Put the dev-set overfitting process in the correct order.

  • After several rounds of tuning, your validation score is much better than your test score. What should you do next?

  • It is a good practice to keep checking the test set after every major training change so you can choose the best model.

  • Repeatedly choosing models based on dev-set results can cause the system to gradually _____ to the dev set.

  • Match each development-set practice or signal with what it means in model selection.

  • Order the steps for investigating a validation-versus-test performance gap.

  • How Repeated Tuning Can Distort the Development Set

  • Evaluating a Model That Fits the Development Set Too Closely

  • Sign That the Development Set Has Been Overused

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