I assumed the problem was a classification one and obtained a probability of approx 1/3 for each class with the same values for each sample. That is to be expected (albeit exactly the same maybe down to the no. of significant digits after decimal) at the start, since the network hasn’t learned anything yet and by pure chance, you get 1/3. If you continue to get the same values a few epochs into training, it may be a problem.
Out of curiosity, could you try manually initializing the linear layer weights using a different distribution? I believe the default is uniform in [-1/sqrt(1/(no.of columns in weight matrix),  1/sqrt(1/(no.of columns in weight matrix)]