Hello everyone,
I am trying to train a multitask CNN nets which is used to both classification and regression.
When I trained it with 100000 iteration,the classification accuracy is still very low,and its loss is still high:
Test net output #0: accuracy = 0.001875
I1202 06:35:36.006667 7062 solver.cpp:408] Test net output #1: class_loss = 3.09879 (* 4 = 12.3952 loss)
I1202 06:35:36.006677 7062 solver.cpp:408] Test net output #2: reg_loss = 0.0493825 (* 1 = 0.0493825 loss)
I finetune my net with Caffenet. It takes about 10 hours for 100000 iters.
My solver is like this:
test_iter: 100
test_interval: 1000
base_lr: 0.0001
lr_policy: "step"
gamma: 0.1
stepsize: 20000
display: 20
max_iter: 200000
momentum: 0.9
weight_decay: 0.0005
Any advice for this problem?
Thanks,
Bill.