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Purpose of an Eyeball Dev Set for Human-Level Tasks
Question: For a task that people already do well, such as sorting customer support emails into topics, what should a manually reviewed dev set be large enough to accomplish?
Sample answer: It should be large enough to expose the model's main failure patterns so you can see which kinds of mistakes happen most often.
Key points:
- Make the dominant mistake patterns visible.
- Include enough examples to judge those patterns reliably.
Rubric: The student response should clearly say that the Eyeball dev set must be large enough to reveal the system's main error patterns or failure modes.
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A Small Sample of Dev Errors Can Reveal Major Failure Patterns
Reviewing About 50 Mistakes Reveals Main Error Sources
Reviewing About 100 Eyeball Dev Errors Usually Reveals the Main Failure Patterns
Lower Error Rates Require Larger Review Sets
Why should the manually reviewed dev subset be large enough?
The rough sizing guidance for an eyeball development set is meant for tasks that people can evaluate reliably.
A validation sample should be large enough to reveal the system's main _____.
Match each example count to the amount of insight it typically provides when reviewing errors by hand.
Order the steps for reviewing a validation set to find the most common model mistakes.
Which example task is used to illustrate a rough Eyeball dev set size recommendation?
A tiny validation sample is enough to uncover every major failure mode in a model.
When manual error review is practical
Match each concept to the best description in a model error-analysis setting.
Decide Whether a Human Review Set Is Large Enough
How should an Eyeball dev set be sized to reveal the main error patterns?
Choose the right size for a review set in an image recognition project.
Purpose of an Eyeball Dev Set for Human-Level Tasks