To me it seems strange you are using softmax + mse loss.
You are computing some sort of probabilities but then you use a cartesian distance? Strange
Are you using the same dataset or a different one? You have convolutions with 512 filters which leads to a huge amount of a parameters for a 3D nn. Be sure you have the proper amount of parameters given the size of your dataset as 3D convolutions tend to overfit.
Despite the scale of the plot is not proper, it seems even the training is not learning much if it can converge in 10 epochs.
Lastly it would be nice if you use any other metric to measure “overfitting”. Some sort of accuracy would be nice as you can measure if it better than by chance.
Lastly, just random suggestion, are you using a validation set extracted from the same type of data? If you use 2 different datasets (rather than splitting one into train and val) you may find this.