Increasing errors with MultiLayerNetworkExternalErrors.java Example

[Saurabh7]

Hi,

I am trying to using train a simple 2 layer network on a simple synthetic dataset.
With two features X1 and X2.
and lables: y = X1^2 + X2^2

I am calculating the error for each epoch manually and using the errors to call backprop, similar to the MultiLayerNetworkExternalErrors.java example

The prediction error is increasing with each epoch, I would have expected decreasing errors with on this simple dataset.
Could someone help me with if the issue is with how I am using dl4j methods ?

Code: https://gist.github.com/Saurabh7/9b5ea7def2a167903e7d206e272e2662
Data: https://gist.github.com/Saurabh7/982fb4ddfbd58bd866782ea31b95aef1

[saudet]

http://deeplearning4j.org/docs/latest/deeplearning4j-troubleshooting-training