You are confused. The task is to find a local minimum that is sufficiently low. I use the goal
mse(target-output) <= 0.01*mean(var(target',1)).
This yields an Rsquare >= 0.99 % Look up Rsquare in wikipedia
Furthermore, because of the output's invariance to the shuffling of hidden node order and weight signs there are 2^H * H! equivalent nets with the same number of hidden nodes and weight absolute values. For the default value H = 10, 2^H *H! = 3.7159e+09
Furthermore there are often more than one set of orders and absolute values that will cause an acceptable Rsquare.
The differences you see can be caused by different initial random weight values.
Hope this helps.
Thank you for formally accepting my answer
Greg
