Hi, I tend to learn a model that can map X=[400,100] to y=[400,180], in which each row of y has just one non-zero element = 1. A model with binary cross-entropy loss and adam optimizer could map that, but when I replace y by y=0.5*y, the model does not train at all and just returns a zero output (output=> zeros([400,180]) ).
Could you mind helping me fix this problem?