How big should batch size and number of epochs be when fitting a model?
I used Keras to perform non linear regression for market mix modelling. I got best results with a batch size of 32 and epochs = 100 while training a Sequential model in Keras with 3 hidden layers. Generally batch size of 32 or 25 is good, with epochs = 100 unless you have large dataset. in case of large dataset you can go with batch size of 10 with epochs b/w 50 to 100.
Again the above mentioned figures have worked fine for me.
My training set has 970 samples and validation set has 243 samples.
How big should batch size and number of epochs be when fitting a model to optimize the val_acc? Is there any sort of rule of thumb to use based on data input size?