determining batch size and epoch size of neural network
Depends on many things. Batch size is how many instances will be accepted as input by your model, in order to make a complete forward pass and propagate the appropriate gradients backwards. Having a batch size too small could lead to gradients that derived from a batch which is not representative of the data distribution, thus these gradients could be harmful. Having a large batch size in a huge dataset could lead to memory issues. Having said that, use 128.