keras validation mean squared error always similar to 1
It could be very close to 1 (or for that matter, changing very slowly) for many reasons:


Maybe your learning rate is very small.
Maybe the network has reached its learning capacity. Since we do not know anything about the network architecture, we can't rule this out.


This does not mean there is nothing to learn from the data. In the worst case, there is nothing to learn from data, with the given architecture,  hyperparameters and the time you are willing to let the network learn.