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Software Engineering vocabulary · Machine Learning and Data Processing

Batch size

Meaning in software engineering, with examples

nounCommon term

In software engineering, batch size means: The number of training examples a model processes together before it updates its parameters once.

In Turkish: batch boyutu, yığın boyutu

How it is used

Limited mainly by GPU memory. Bigger batches use the hardware more efficiently but may need a different learning rate. When memory runs out, engineers reduce the batch size or use gradient accumulation.

Example sentences

  1. We got an out-of-memory error, so I cut the batch size from 64 to 32.

  2. With a larger batch size, each epoch finishes faster.

Common collocations

  • increase the batch size
  • effective batch size
  • mini-batch
  • batch size of 32
  • epochOne complete pass of the training process through the whole training dataset. Models are usually trained for several epochs.
  • learning rateA hyperparameter that controls how big a step the model takes each time it updates its parameters. Too high makes training unstable; too low makes it very slow.
  • GPUShort for graphics processing unit: the chip that renders a game's images by running shaders and drawing millions of pixels every frame. The CPU handles most of the game logic.
  • hyperparameterA setting chosen by engineers before training rather than learned from data, such as the learning rate, the batch size or the number of layers.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Machine Learning and Data Processing

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