loss is too small

[valencebond]

the code weights[inds] = tot / num_in_bin
loss = F.binary_cross_entropy_with_logits( input, target, weights, reduction='sum') / tot
same as weights[inds] = 1 / num_in_bin ， and combination with weights = weights / n，
weighted logits may be one percent or one thousandths of origin weighted if there are many samples in one bins。
if there is something wrong with my understanding , please tell me.

[libuyu]

Your understanding is right, and our target is just making the weight of these samples small. The motivation and details can be seen in our paper https://arxiv.org/abs/1811.05181