Improving initial Cross Entropy in CNN
By increasing number of features in convolutional layers, you are actually increasing the number of learnable parameters which were initialized to random values. So, randomness increases and that's why the cross entropy loss increases.Hope this is satisfiable justification to your question.

Ex, Suppose convolution layer with : 

filter_size = (3, 3) and number_feature = 10 =&gt; number_parameters = 3*3*10 = 90
filter_size = (3, 3) and number_feature = 64 =&gt; number_parameters = 3*3*64 = 576