Minibatch size
时间: 2023-12-27 12:05:17 浏览: 58
Minibatch size refers to the number of examples or instances of data that are processed together in a single iteration or batch during training of a machine learning model. The size of the minibatch is typically smaller than the total size of the training dataset, and is chosen to balance the computational efficiency and the quality of the model's optimization. A larger minibatch size can lead to faster convergence, but may also require more memory and computational resources, while a smaller minibatch size may result in slower convergence and may require more training iterations to reach the same level of performance. The choice of minibatch size depends on the specific problem and the characteristics of the data and the model being trained.
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