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Assign the best “possible action” to exactly one training curve. Use a possible explanation at most once. Assume these are learning curves for a model trained to classify CIFAR images using PyTorch trained with a typical cross entropy loss.

Assign the best “possible action” to exactly one training curve. Use a possible explanation at most once. Assume these are learning curves for a model trained to classify CIFAR images using PyTorch trained with a typical cross entropy loss.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Assign the best “possible action” to exactly one training curve.

Use a possible explanation at most once.

Assume these are learning curves for a model trained to classify CIFAR images using PyTorch trained with a typical cross entropy loss.

Choose the most fitting answer.

Loss Steps O Use the squared loss instead of the cross entropy loss Shuffle your batches Set the batch size to one O Set the batch size to the size of the training set Use data augmentation O Check for division by zero or logarithms of small numbers O Use a loss like the area under the curve which is threshold-invariant Decrease the learning rate Train Test
Transcribed Image Text:Loss Steps O Use the squared loss instead of the cross entropy loss Shuffle your batches Set the batch size to one O Set the batch size to the size of the training set Use data augmentation O Check for division by zero or logarithms of small numbers O Use a loss like the area under the curve which is threshold-invariant Decrease the learning rate Train Test
Loss Steps O Use the squared loss instead of the cross entropy loss O Shuffle your batches O Set the batch size to one O Set the batch size to the size of the training set O Use data augmentation MW O Check for division by zero or logarithms of small numbers O Use a loss like the area under the curve which is threshold-invariant O Decrease the learning rate
Transcribed Image Text:Loss Steps O Use the squared loss instead of the cross entropy loss O Shuffle your batches O Set the batch size to one O Set the batch size to the size of the training set O Use data augmentation MW O Check for division by zero or logarithms of small numbers O Use a loss like the area under the curve which is threshold-invariant O Decrease the learning rate
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