Low training accuracy on cityscape data set

[guantinglin]

Hi,

I am training the caffe version of ENet. When training on the cityscape fine annotated dataset, my training accuracy seems not to be converged. Do you have any suggestion about how to solve it?
All parameters are the default one except for the batch is set as 2 due to the memory capacity.

Thanks for your help.

I1203 11:35:57.409646 12188 solver.cpp:228] Iteration 173240, loss = 1.04035
I1203 11:35:57.409780 12188 solver.cpp:244] Train net output #0: accuracy = 0.609447
I1203 11:35:57.409791 12188 solver.cpp:244] Train net output #1: loss = 1.04036 (* 1 = 1.04036 loss)
I1203 11:35:57.409796 12188 solver.cpp:244] Train net output #2: per_class_accuracy = 0.799779
I1203 11:35:57.409801 12188 solver.cpp:244] Train net output #3: per_class_accuracy = 0.729202
I1203 11:35:57.409806 12188 solver.cpp:244] Train net output #4: per_class_accuracy = 0.754431
I1203 11:35:57.409809 12188 solver.cpp:244] Train net output #5: per_class_accuracy = 0
I1203 11:35:57.409813 12188 solver.cpp:244] Train net output #6: per_class_accuracy = 0.298023
I1203 11:35:57.409817 12188 solver.cpp:244] Train net output #7: per_class_accuracy = 0.747144
I1203 11:35:57.409821 12188 solver.cpp:244] Train net output #8: per_class_accuracy = 0.841352
I1203 11:35:57.409826 12188 solver.cpp:244] Train net output #9: per_class_accuracy = 0.406868
I1203 11:35:57.409828 12188 solver.cpp:244] Train net output #10: per_class_accuracy = 0.627141
I1203 11:35:57.409832 12188 solver.cpp:244] Train net output #11: per_class_accuracy = 0.809035
I1203 11:35:57.409837 12188 solver.cpp:244] Train net output #12: per_class_accuracy = 0.98963
I1203 11:35:57.409842 12188 solver.cpp:244] Train net output #13: per_class_accuracy = 0.215297
I1203 11:35:57.409845 12188 solver.cpp:244] Train net output #14: per_class_accuracy = 0
I1203 11:35:57.409849 12188 solver.cpp:244] Train net output #15: per_class_accuracy = 0.578774
I1203 11:35:57.409853 12188 solver.cpp:244] Train net output #16: per_class_accuracy = 0
I1203 11:35:57.409857 12188 solver.cpp:244] Train net output #17: per_class_accuracy = 0
I1203 11:35:57.409862 12188 solver.cpp:244] Train net output #18: per_class_accuracy = 0
I1203 11:35:57.409865 12188 solver.cpp:244] Train net output #19: per_class_accuracy = 0
I1203 11:35:57.409869 12188 solver.cpp:244] Train net output #20: per_class_accuracy = 0

[changlinzhang]

@guantinglin Have your solved this problem? I ran into a similar situation.

[lingchaoa]

@changlinzhang @guantinglin i have a similar situation.