Multi-output regression problem with Keras
Accuracy is a metric for classification, not regression. 

$$Accuracy = \frac{\text{Correct classification}}{\text{Number of classifications}}$$

So when you use accuracy for regression only the values where actual_label == predicted_label are evaluated as true are counted as correct classifications. That will happen quite rarely when you are doing regression, resulting in an accuracy that is close to zero.

Instead you should use something like mean absolute error or mean squared error as validation metrics for regression.