# Is it always better to using stacked LSTM than single LSTM?

I am currently studying LSTM and RNNs.

I came across several concepts like Multidimensional LSTM and Stacked LSTM.

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 BatchNorm and Dropout after every stack of LSTM ]