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Question 5 - HPE2-N69 discussion

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Refer to the exhibit.

You are demonstrating HPE Machine Learning Development Environment, and you show details about an experiment, as shown in the exhibits. The customer asks about what "validation loss' means. What should you respond?

A.
Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.
Answers
A.
Validation refers to testing how well the current model performs on new data; file lower the loss the better the performance.
B.
Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.
Answers
B.
Validation refers to an assessment of how efficient the model code is; the lower the loss the lower the demand on GPU memory resources.
C.
Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.
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C.
Validation loss refers to the loss detected during the backward pass of training, while training loss refers to loss during the forward pass.
D.
Validation loss is metadata that indicates how many updates were lost between the conductor and agents.
Answers
D.
Validation loss is metadata that indicates how many updates were lost between the conductor and agents.
Suggested answer: C
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asked 16/09/2024
Xiaoyi Wu
38 questions
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