I have this problem when i train my data by caffe .
F1107 12:42:42.507861 2369 net.cpp:774] Cannot copy param 0 weights from layer 'conv4_3_norm_mbox_conf'; shape mismatch. Source param shape is 40 512 3 5 (307200); target param shape is 180 512 3 5 (1382400). To learn this layer's parameters from scratch rather than copying from a saved net, rename the layer.
这是由于预训练网络的参数与当前模型架构对不上，只要把出现错误的层名字改了就ok了！！之前识别的是两类（background和text），然后源码每个点是有20个priorbox，所以num_output是40，现在我要识别11类，输出应该是220才对。
I have solved this problem by delete the file like "VGG_text_text_polygon_precise_fix_order_384x384_iter_120000.solverstate"
Delete all solverstate file and problem have solved .
Later, I realize that the true reason is that I have altered another caffemodel to train my data , so I can solve this problem!
The latest solvement is to rename the layer's name which you add, or you can change the layers'name in "model_libs.py". It works!
But the train val is very low so I think this is a bad solvement ?Oh my god ~I don't know what I can do !