How deeply does Deep Learning with PyTorch, Second Edition cover epoch?

Explains epochs through dataset coverage, batch-step relationships, loop code, stopping choices, and metric interpretation.

Epoch

As explained in Deep Learning with PyTorch, Second Edition

One complete pass through the entire training dataset used in training, after which each sample has been used once.

An epoch is one complete pass through the entire training dataset. During that pass, every sample is used once to update the model parameters. section 5.4.3

An epoch is not the same as a training iteration or step. A step usually processes one batch through forward and backward passes; multiple batch steps make up one epoch. When the entire dataset is used in each step, one step equals one epoch. section 5.4.3

Epochs organize the training process:

Set a number of epochs or another stopping criterion before running the training loop. section 5.4.3 section 5.4.4
Inspect loss and class-specific results across epochs rather than trusting overall accuracy alone. section 13.8

Choosing the number of epochs

A normalized temperature model is trained for 5,000 epochs. Its loss falls from 80.36 initially to about 2.93 by epoch 5,000, while the learned parameters approach the expected Fahrenheit-to-Celsius relationship. The choice of 5,000 is a hyperparameter rather than a universal rule. section 5.4.4

How Deep Learning with PyTorch, Second Edition covers it

Cover of Deep Learning with PyTorch, Second Edition

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Related concepts

traininghas part · Training is a process of developing or improving a person’s or model’s capabilities through instruction, experience, or adjustment using data.
objective functionuses · An objective function assigns values to candidate solutions, predictions, or parameter settings according to a criterion to be minimized or maximized.
similarity searchused by · Similarity search is a retrieval technique that finds or ranks items by comparing their representations with a query according to a similarity or distance measure.
accuracycontrasts with · Accuracy is the degree to which an output, prediction, or measurement agrees with a correct or reference outcome under a specified criterion.
training datasethas part · A collection of examples or observations supplied to a learning procedure to fit or adapt a model or learn its patterns or parameters.

This explainer was generated by Manning's knowledge graph from the text of Deep Learning with PyTorch, Second Edition. The section links point to the parts of the book it draws on.