I'm carrying out a project of predicting time series data with an LSTM. I tried out the experiment three times with randomly sampled data(about 920,000 lines each)
I've stacked 3 layers of LSTM cells, used l1(0.01) regularization, used dropout, tried shuffling the dataset for every epoch, used ADAM optimizer..
but I get the error curve as follows, which seems to signify overfitting
x-axis : epochs
y-axis : error in terms of mean squared error
the blue line indicates the test set, and the orange train set
Can somebody give suggestions on what I should try? Maybe it's a matter on the dataset itself?