Epoch-based training in PyTorch - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is an epoch in machine learning training?

An epoch is one complete pass through the entire training dataset during model training.

beginner

Why do we use multiple epochs in training a model?

Multiple epochs help the model learn better by repeatedly adjusting weights based on the data, improving accuracy over time.

intermediate

In PyTorch, what is the typical structure inside an epoch during training?

Inside an epoch, the model processes batches of data, computes predictions, calculates loss, backpropagates errors, and updates weights.

beginner

What is the difference between an epoch and a batch?

A batch is a small subset of the dataset processed at once; an epoch is when the model has seen all batches covering the entire dataset once.

intermediate

How can you monitor training progress during epochs in PyTorch?

You can track training loss and accuracy after each epoch to see if the model is improving or needs adjustments.

What does one epoch represent in training?

A One pass through the entire training dataset

B One batch of data processed

C One update of model weights

D One evaluation on the test set

An epoch means the model has seen all training data once.

Why do we split data into batches during training?

A To avoid using epochs

B To increase the size of the dataset

C To reduce memory usage and speed up training

D To test the model

Batches help manage memory and make training faster by processing smaller chunks.

What happens after each batch is processed in an epoch?

A The model is saved to disk

B Model weights are updated using backpropagation

C The training stops

D The test data is evaluated

Weights update after each batch to improve the model.

If you train for 5 epochs, how many times does the model see the full dataset?

A 5 times

B 1 time

C Number of batches times 5

D Depends on batch size

Each epoch is one full pass through the dataset, so 5 epochs means 5 passes.

Which metric is commonly checked after each epoch?

A Learning rate

B Batch size

C Number of epochs

D Training loss

Training loss shows how well the model is learning after each epoch.

Explain what an epoch is and why it is important in training machine learning models.

Think about how the model learns from data repeatedly.

Describe the steps that happen inside one epoch during training with PyTorch.

Consider what the model does with each batch in the epoch.