run ./train.sh loss is too big

[xcj-github]

when i run the ./train.sh , the log output like fllowing: .......... 0302 19:12:14.613809 31026 sgd_solver.cpp:106] Iteration 6340, lr = 1e-06 I0302 19:12:38.769260 31026 solver.cpp:228] Iteration 6360, loss = 10621.1 I0302 19:12:38.769335 31026 solver.cpp:244] Train net output #0: dsn1_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769345 31026 solver.cpp:244] Train net output #1: dsn2_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769351 31026 solver.cpp:244] Train net output #2: dsn3_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769356 31026 solver.cpp:244] Train net output #3: dsn4_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769361 31026 solver.cpp:244] Train net output #4: dsn5_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769366 31026 solver.cpp:244] Train net output #5: fuse_loss = 0 ( 1 = 0 loss) I0302 19:12:38.769388 31026 sgd_solver.cpp:106] Iteration 6360, lr = 1e-06 I0302 19:13:03.462623 31026 solver.cpp:228] Iteration 6380, loss = 11332.3 I0302 19:13:03.462703 31026 solver.cpp:244] Train net output #0: dsn1_loss = 7039.19 ( 1 = 7039.19 loss) I0302 19:13:03.462718 31026 solver.cpp:244] Train net output #1: dsn2_loss = 5792.09 ( 1 = 5792.09 loss) I0302 19:13:03.462725 31026 solver.cpp:244] Train net output #2: dsn3_loss = 4685.93 ( 1 = 4685.93 loss) I0302 19:13:03.462733 31026 solver.cpp:244] Train net output #3: dsn4_loss = 4729.02 ( 1 = 4729.02 loss) I0302 19:13:03.462740 31026 solver.cpp:244] Train net output #4: dsn5_loss = 4076.09 ( 1 = 4076.09 loss) I0302 19:13:03.462749 31026 solver.cpp:244] Train net output #5: fuse_loss = 4297.43 ( 1 = 4297.43 loss) I0302 19:13:03.462755 31026 sgd_solver.cpp:106] Iteration 6380, lr = 1e-06 I0302 19:13:27.423714 31026 solver.cpp:228] Iteration 6400, loss = 11654.9 I0302 19:13:27.423781 31026 solver.cpp:244] Train net output #0: dsn1_loss = 323.811 ( 1 = 323.811 loss) I0302 19:13:27.423807 31026 solver.cpp:244] Train net output #1: dsn2_loss = 309.62 ( 1 = 309.62 loss) I0302 19:13:27.423815 31026 solver.cpp:244] Train net output #2: dsn3_loss = 266.862 ( 1 = 266.862 loss) I0302 19:13:27.423821 31026 solver.cpp:244] Train net output #3: dsn4_loss = 225.52 ( 1 = 225.52 loss) I0302 19:13:27.423842 31026 solver.cpp:244] Train net output #4: dsn5_loss = 224.127 ( 1 = 224.127 loss) I0302 19:13:27.423864 31026 solver.cpp:244] Train net output #5: fuse_loss = 218.551 ( 1 = 218.551 loss) I0302 19:13:27.423871 31026 sgd_solver.cpp:106] Iteration 6400, lr = 1e-06 I0302 19:13:52.708914 31026 solver.cpp:228] Iteration 6420, loss = 11339.1 I0302 19:13:52.708992 31026 solver.cpp:244] Train net output #0: dsn1_loss = 8.48727 ( 1 = 8.48727 loss) I0302 19:13:52.709002 31026 solver.cpp:244] Train net output #1: dsn2_loss = 3.91735 ( 1 = 3.91735 loss) I0302 19:13:52.709007 31026 solver.cpp:244] Train net output #2: dsn3_loss = 3.22385 ( 1 = 3.22385 loss) I0302 19:13:52.709013 31026 solver.cpp:244] Train net output #3: dsn4_loss = 3.65278 ( 1 = 3.65278 loss) I0302 19:13:52.709018 31026 solver.cpp:244] Train net output #4: dsn5_loss = 3.51696 ( 1 = 3.51696 loss) I0302 19:13:52.709024 31026 solver.cpp:244] Train net output #5: fuse_loss = 2.89571 ( 1 = 2.89571 loss) ......... Is there something wrong?

i did not set loss parameters η and λ . where should i set these parameters ? thx

[yun-liu]

In fact, the output seems normal. You can test the trained model to see if the training process is right.