Thank you. But since my batch size is set to the whole training data set, it shouldn’t matter if the records are shuffled. Surely if the data is shuffled, each row will only be used once in each epoch. So shuffling would change how the network weights are updated each time the algorithm is run, but its not like we are excluding any rows or using some rows more than others. Do you agree?
Also turning shuffle to false did not change the loss. The loss still never goes below 0.7. when using dataloader. Also increasing to 1000 epochs did not decrease the loss.