Validation and train sets are equal?

When I train this net:

net = feedforwardnet(20,'trainlm');
net.inputs{1}.processFcns = {};
net.outputs{2}.processFcns = {}; 
net.trainParam.epochs = 200;

It looks like, that I have the exactly same train and validation sets during training, so it never ends until max epoch is reached. I have tried to change ratio manually, but it doesnt work as well.

My input data set is unique.

I've tried another input data set and it works. I have also tried to specific range for validation and train set by divideint and it works as well:

net.divideFcn = 'divideind';
net.divideParam.trainInd = 89:584;
net.divideParam.valInd = 1:88;

So what am I missing?

[Greg Heath]

It would help if you posted your commented code operating on one of the MATLAB example data sets.

 help nndatasets
 doc nndatasets

Greg

PS: What is wrong with using the example code in

 help feedforwardnet
 doc feedforwardnet

?