iter 3700 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5781 loss_s: 2.8997 loss_mse: 0.0280 losses: 3.4793
iter 3800 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5784 loss_s: 2.9005 loss_mse: 0.0281 losses: 3.4805
iter 3900 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5783 loss_s: 2.8970 loss_mse: 0.0281 losses: 3.4768
iter 4000 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5776 loss_s: 2.8929 loss_mse: 0.0281 losses: 3.4721
iter 4100 time/iter: 0.49 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5773 loss_s: 2.8916 loss_mse: 0.0281 losses: 3.4705
iter 4200 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5775 loss_s: 2.8877 loss_mse: 0.0281 losses: 3.4668
iter 4300 time/iter: 0.50 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5779 loss_s: 2.8855 loss_mse: 0.0281 losses: 3.4649
iter 4400 time/iter: 0.49 lr: 0.000100 loss_mn: 0.0016 loss_c: 0.5782 loss_s: 2.8828 loss_mse: 0.0282 losses: 3.4626
iter 4500 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 4600 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 4700 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 4800 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 4900 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 5000 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan
iter 5100 time/iter: 0.49 lr: 0.000100 loss_mn: nan loss_c: nan loss_s: nan loss_mse: nan losses: nan