Batch Size

Batch size refers to the number of training examples utilized in one iteration. In other words, batch size is the number of samples that will be propagated through the neural network during a single forward/backward pass. The batch size is a hyperparameter that defines the number of samples to work through before updating the internal model parameters. The larger the batch size, the more memory space you'll need. A batch size of 32 is a good starting point, and you should increase or decrease this number depending on your memory resources.

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Batch Size

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