Closed rainsoulsrx closed 6 years ago
Thanks for Ur question.
Actually, the base_lr do change smaller as the training process goes on.
Please see details at: https://github.com/syfafterzy/SVDNet-for-Pedestrian-Retrieval/blob/master/SVDNet/resnet/base_lr.txt.
Thx, but the caffenet solver_restraint.prototxt, base_lr: 0.001, lr_policy: "step", stepsize: 2000, max_iter: 2000, that is to say, the lr keeps to be 0.01 during the restraint stage, right?
Yes, you are right. For CaffeNet, we only fine-tune the network to good convergence during the last RRI, to reduce training time.
Thank you~~
I notice that base_lr is set to be 0.001 in all solver_restraint.prototxt, normally, base_lr should change smaller as the training process goes on, but the given code keep on using 0.001. will it converg very well in the end?