The batch size is usually set between 64 and 256.
The batch size does have an effect on the final test accuracy. One way to think about it is that smaller batches means that the number of parameter updates per epoch is greater. Inherently, this update will be much more noisy as the loss is computed over a smaller subset of the data. However, this noise seems to help the generalization of the model.
Refer to: https://arxiv.org/abs/1609.04836 438 and https://arxiv.org/abs/1703.04933 258 for two recent studies on this subject