Batch size and epochs in TensorFlow - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the batch size when training a TensorFlow model.

TensorFlow

model.fit(x_train, y_train, epochs=5, batch_size=[1])

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A5

B1

C32

D100

Attempts:

3 left

💡 Hint

Common Mistakes

Using epochs value as batch size.

Setting batch size to 1 which can slow training.

Using a very large batch size that may not fit in memory.

The batch size controls how many samples are processed before the model updates its weights. 32 is a common batch size.

2fill in blank

medium

Complete the code to set the number of epochs for training a TensorFlow model.

TensorFlow

model.fit(x_train, y_train, epochs=[1], batch_size=32)

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A10

B0

C1000

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Setting epochs to zero or negative values.

Using an extremely large number causing long training times.

Epochs define how many times the model sees the entire training data. 10 is a reasonable number for many tasks.

3fill in blank

hard

Fix the error in the code by choosing the correct batch size value.

TensorFlow

model.fit(x_train, y_train, epochs=5, batch_size=[1])

Drag options to blanks, or click blank then click option'

A0

B32

C-10

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Using zero or negative batch size.

Passing None instead of an integer.

Batch size must be a positive integer. Zero, negative, or None values cause errors.

4fill in blank

hard

Fill both blanks to correctly set epochs and batch size in model training.

TensorFlow

model.fit(x_train, y_train, epochs=[1], batch_size=[2])

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A10

B32

C5

D64

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping epochs and batch size values.

Using batch size values that are too large.

Setting epochs to 5 and batch size to 32 is a common training setup.

5fill in blank

hard

Fill all three blanks to create a training call with epochs, batch size, and validation split.

TensorFlow

model.fit(x_train, y_train, epochs=[1], batch_size=[2], validation_split=[3])

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A20

B64

C0.2

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using validation split as an integer instead of decimal.

Setting batch size or epochs to zero or negative.

Using 10 epochs, batch size 64, and 0.2 validation split is a typical setup to train and validate the model.