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Compare training and development data properties after a mismatch is found
When you detect a mismatch between the training set and the development set, a good first step is to determine which properties of the examples differ between the two distributions.
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Compare training and development data properties after a mismatch is found
What best describes a mismatch between training data and evaluation data?
A data mismatch problem means the model performs poorly on both training-like data and the development/test data.
Data mismatch and distribution fit
Match each data-distribution term with its description.
Put the diagnostic workflow for dataset shift in the correct order.
What most directly causes a mismatch between training data and evaluation data?
A voice-to-text system can perform well on the training set and training-dev set but still do poorly on the dev set if the dev data comes from a different distribution.
Training Distribution and Evaluation Distribution
Match each performance pattern to the most likely diagnosis of the model's problem.
Put the steps in order for diagnosing a distribution mismatch from model performance.
Explain what a performance gap across two data distributions suggests
Explain why a voice-command model looks strong on one split but weak on another.
Why is this called data mismatch?
Learn After
Using Error Analysis to Investigate Dataset Mismatch
What Should You Do First When Training and Development Data Do Not Match?
True or false: If a model performs well on the training set but poorly on the dev set, a useful next step is to compare how the two datasets differ.
What should you compare when diagnosing a data mismatch?
When a training set and a validation set look different, what should you examine first?
When a model performs differently on two datasets from different populations, a useful first step is to identify which properties of the examples differ between the two sets.
When a train-dev mismatch is suspected, the key diagnostic is to compare which _____ differ across the two datasets.
Match each data-split term to its meaning in diagnosing distribution shift.
Put the steps for identifying a training-development mismatch in order.
Why compare training-set properties with dev-set properties when a model shows a mismatch problem?
True or False: A model that scores well on training data but much worse on dev data is probably underfitting.
A gap between _____ performance and dev-set performance can signal data mismatch.
Match each observation or action to its correct interpretation in a data mismatch diagnosis.
Order the reasoning for diagnosing a training-dev mismatch
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