If you normalize the output during training (and the target of course, too), you might “denormalize” both to get the expected prediction ranges.
E.g. if you’ve standardized them by subtracting the mean and dividing with the stddev:
x_norm = (x - mean) / std

you might undo it via:
x = x_norm * std + mean