I am currently studying LSTM and RNNs.
I have used Stacked LSTM and it gives me a better performance than single LSTM. As per my understanding, if I increase the depth of LSTM, the number of hidden units also increases. It means overfitting, right? Then why am I getting better results?
[Note: I have used
Dropout after every stack of LSTM ]