nn.MSELoss might not be the best suitable criterion for a sigmoid output and you could try to use nn.BCELoss. I would generally recommend to remove the sigmoid at the end of your model and use nn.BCEWithLogitsLoss for more numerical stability.
Did you check the model predictions for the training and validation datasets?
The losses look a bit weird as they are not changing at all for 10 epochs?