I’m not exactly sure why that might happen. However, what you could try is,

Verify that the loss decreases during training.
Normalizing or Standardizing the data.
Does it give the same value if you feed in the training data as well? If it does, it may be an error in your code or the network is getting “stuck” at a point.

Could you post a snippet of the training/validation loop as well?