I've noticed that the performance of my models vary quite a bit as a function of the batch size, both in terms of the time to converge and (possibly) the amount of overfitting.I thought batch size was simply controlling the number of images sent to the gpu / cpu at any given time, but I can't match that up with this behavior. Can someone explain what batch size controls in the model? Why the variation in performance? Any good resources?
Sorry for the naive question. This is my first time using these sorts of models, and in the background reading I've done, I've still not fully grasped what this parameter is doing.