Why network overfits too early?

I want to train a neural network model, which basicly does binary classification. I can't understand why my network overfits too early. I thought my network is too big and it memorizes the dataset, but when I make it smaller, it does not learn at all. How avoid this situation? dropout didn't work, augmentation techniques helped a bit, obviously regularizations didn't change anything. Can you guys explain the reasons, and how I can avoid it?

overfitneural-networkclassification
4 votesLP185.00
1 Answers
sK2.00
0

Have you tried early stopping ?

Reply
LP185.00
0

I have not tried it, because it takes 3-4 epoches and the networks starts to overfit. I thought learning rate is too big or small. changed them, it didn't work as well.

Couldn't find what you were looking for?and we will find an expert to answer.
How helpful was this page?