问题
I'm getting the problem of non-converged training loss. (batchsize: 16, average loss:10). I have tried with the following methods + Vary the learning rate lr (initial lr = 0.002 cause very high loss, around e+10). Then with lr = e-6, the loss seem to small but do not converge. + Add initialization for bias + Add regularization for bias and weight
This is the network structure and the training loss log
Hope to hear from you Best regards
来源：https://stackoverflow.com/questions/41234297/caffe-training-loss-does-not-converge