orig_net_log.txt

I1112 18:26:20.476073 22658 solver.cpp:337] Iteration 0, Testing net (#0)
I1112 18:26:20.486620 22658 net.cpp:693] Ignoring source layer prob
I1112 18:26:22.844864 22658 solver.cpp:404]     Test net output #0: accuracy = 0.02416
I1112 18:26:22.862859 22658 solver.cpp:228] Iteration 0, loss = 38.3147
I1112 18:26:22.862937 22658 solver.cpp:244]     Train net output #0: loss = 38.3147 (* 1 = 38.3147 loss)
I1112 18:26:22.862980 22658 sgd_solver.cpp:106] Iteration 0, lr = 0.01
I1112 18:27:25.690100 22658 solver.cpp:228] Iteration 1000, loss = 4.31486
I1112 18:27:25.690229 22658 solver.cpp:244]     Train net output #0: loss = 4.31486 (* 1 = 4.31486 loss)
I1112 18:27:25.690245 22658 sgd_solver.cpp:106] Iteration 1000, lr = 0.01
I1112 18:28:28.546875 22658 solver.cpp:228] Iteration 2000, loss = 4.29191
I1112 18:28:28.546974 22658 solver.cpp:244]     Train net output #0: loss = 4.2919 (* 1 = 4.2919 loss)
I1112 18:28:28.546993 22658 sgd_solver.cpp:106] Iteration 2000, lr = 0.01
I1112 18:29:31.232525 22658 solver.cpp:228] Iteration 3000, loss = 4.80188
I1112 18:29:31.232632 22658 solver.cpp:244]     Train net output #0: loss = 4.80188 (* 1 = 4.80188 loss)
I1112 18:29:31.232650 22658 sgd_solver.cpp:106] Iteration 3000, lr = 0.01
I1112 18:30:33.989977 22658 solver.cpp:228] Iteration 4000, loss = 4.457
I1112 18:30:33.990145 22658 solver.cpp:244]     Train net output #0: loss = 4.45701 (* 1 = 4.45701 loss)
I1112 18:30:33.990164 22658 sgd_solver.cpp:106] Iteration 4000, lr = 0.01
I1112 18:31:34.120241 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_5000.caffemodel
I1112 18:31:45.499259 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_5000.solverstate
I1112 18:31:45.625067 22658 solver.cpp:337] Iteration 5000, Testing net (#0)
I1112 18:31:45.625108 22658 net.cpp:693] Ignoring source layer prob
I1112 18:31:47.635975 22658 solver.cpp:404]     Test net output #0: accuracy = 0.01264
I1112 18:31:47.644444 22658 solver.cpp:228] Iteration 5000, loss = 4.42241
I1112 18:31:47.644482 22658 solver.cpp:244]     Train net output #0: loss = 4.42241 (* 1 = 4.42241 loss)
I1112 18:31:47.644495 22658 sgd_solver.cpp:106] Iteration 5000, lr = 0.01
I1112 18:32:44.463510 22658 solver.cpp:228] Iteration 6000, loss = 4.40137
I1112 18:32:44.463692 22658 solver.cpp:244]     Train net output #0: loss = 4.40137 (* 1 = 4.40137 loss)
I1112 18:32:44.463706 22658 sgd_solver.cpp:106] Iteration 6000, lr = 0.01
I1112 18:33:41.274355 22658 solver.cpp:228] Iteration 7000, loss = 4.40615
I1112 18:33:41.274456 22658 solver.cpp:244]     Train net output #0: loss = 4.40616 (* 1 = 4.40616 loss)
I1112 18:33:41.274471 22658 sgd_solver.cpp:106] Iteration 7000, lr = 0.01
I1112 18:34:38.108649 22658 solver.cpp:228] Iteration 8000, loss = 4.40302
I1112 18:34:38.108717 22658 solver.cpp:244]     Train net output #0: loss = 4.40302 (* 1 = 4.40302 loss)
I1112 18:34:38.108727 22658 sgd_solver.cpp:106] Iteration 8000, lr = 0.01
I1112 18:35:34.911927 22658 solver.cpp:228] Iteration 9000, loss = 4.37814
I1112 18:35:34.912045 22658 solver.cpp:244]     Train net output #0: loss = 4.37815 (* 1 = 4.37815 loss)
I1112 18:35:34.912055 22658 sgd_solver.cpp:106] Iteration 9000, lr = 0.01
I1112 18:36:31.676822 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_10000.caffemodel
I1112 18:36:40.288696 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_10000.solverstate
I1112 18:36:40.412233 22658 solver.cpp:337] Iteration 10000, Testing net (#0)
I1112 18:36:40.412267 22658 net.cpp:693] Ignoring source layer prob
I1112 18:36:42.409515 22658 solver.cpp:404]     Test net output #0: accuracy = 0.012
I1112 18:36:42.417625 22658 solver.cpp:228] Iteration 10000, loss = 4.42412
I1112 18:36:42.417649 22658 solver.cpp:244]     Train net output #0: loss = 4.42413 (* 1 = 4.42413 loss)
I1112 18:36:42.417671 22658 sgd_solver.cpp:46] MultiStep Status: Iteration 10000, step = 1
I1112 18:36:42.417678 22658 sgd_solver.cpp:106] Iteration 10000, lr = 0.001
I1112 18:36:42.482101 22658 sgd_solver.cpp:46] MultiStep Status: Iteration 10001, step = 2
I1112 18:37:39.221137 22658 solver.cpp:228] Iteration 11000, loss = 4.31903
I1112 18:37:39.221312 22658 solver.cpp:244]     Train net output #0: loss = 4.31903 (* 1 = 4.31903 loss)
I1112 18:37:39.221324 22658 sgd_solver.cpp:106] Iteration 11000, lr = 0.0001
I1112 18:38:36.019762 22658 solver.cpp:228] Iteration 12000, loss = 3.91513
I1112 18:38:36.019883 22658 solver.cpp:244]     Train net output #0: loss = 3.91514 (* 1 = 3.91514 loss)
I1112 18:38:36.019896 22658 sgd_solver.cpp:106] Iteration 12000, lr = 0.0001
I1112 18:39:33.037860 22658 solver.cpp:228] Iteration 13000, loss = 3.72487
I1112 18:39:33.037981 22658 solver.cpp:244]     Train net output #0: loss = 3.72487 (* 1 = 3.72487 loss)
I1112 18:39:33.037994 22658 sgd_solver.cpp:106] Iteration 13000, lr = 0.0001
I1112 18:40:29.859546 22658 solver.cpp:228] Iteration 14000, loss = 3.62126
I1112 18:40:29.859616 22658 solver.cpp:244]     Train net output #0: loss = 3.62126 (* 1 = 3.62126 loss)
I1112 18:40:29.859627 22658 sgd_solver.cpp:106] Iteration 14000, lr = 0.0001
I1112 18:41:26.609722 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_15000.caffemodel
I1112 18:41:35.204751 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_15000.solverstate
I1112 18:41:35.328637 22658 solver.cpp:337] Iteration 15000, Testing net (#0)
I1112 18:41:35.328675 22658 net.cpp:693] Ignoring source layer prob
I1112 18:41:37.328809 22658 solver.cpp:404]     Test net output #0: accuracy = 0.05672
I1112 18:41:37.337193 22658 solver.cpp:228] Iteration 15000, loss = 3.65662
I1112 18:41:37.337230 22658 solver.cpp:244]     Train net output #0: loss = 3.65663 (* 1 = 3.65663 loss)
I1112 18:41:37.337241 22658 sgd_solver.cpp:106] Iteration 15000, lr = 0.0001
I1112 18:42:34.164156 22658 solver.cpp:228] Iteration 16000, loss = 3.56069
I1112 18:42:34.164304 22658 solver.cpp:244]     Train net output #0: loss = 3.5607 (* 1 = 3.5607 loss)
I1112 18:42:34.164317 22658 sgd_solver.cpp:106] Iteration 16000, lr = 0.0001
I1112 18:43:30.983141 22658 solver.cpp:228] Iteration 17000, loss = 2.98757
I1112 18:43:30.983266 22658 solver.cpp:244]     Train net output #0: loss = 2.98757 (* 1 = 2.98757 loss)
I1112 18:43:30.983279 22658 sgd_solver.cpp:106] Iteration 17000, lr = 0.0001
I1112 18:44:27.784482 22658 solver.cpp:228] Iteration 18000, loss = 2.45038
I1112 18:44:27.784574 22658 solver.cpp:244]     Train net output #0: loss = 2.45039 (* 1 = 2.45039 loss)
I1112 18:44:27.784587 22658 sgd_solver.cpp:106] Iteration 18000, lr = 0.0001
I1112 18:45:24.585693 22658 solver.cpp:228] Iteration 19000, loss = 1.55374
I1112 18:45:24.585820 22658 solver.cpp:244]     Train net output #0: loss = 1.55374 (* 1 = 1.55374 loss)
I1112 18:45:24.585834 22658 sgd_solver.cpp:106] Iteration 19000, lr = 0.0001
I1112 18:46:21.339321 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_20000.caffemodel
I1112 18:46:21.771287 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_20000.solverstate
I1112 18:46:21.901027 22658 solver.cpp:337] Iteration 20000, Testing net (#0)
I1112 18:46:21.901064 22658 net.cpp:693] Ignoring source layer prob
I1112 18:46:23.897691 22658 solver.cpp:404]     Test net output #0: accuracy = 0.57368
I1112 18:46:23.905828 22658 solver.cpp:228] Iteration 20000, loss = 1.49738
I1112 18:46:23.905860 22658 solver.cpp:244]     Train net output #0: loss = 1.49739 (* 1 = 1.49739 loss)
I1112 18:46:23.905872 22658 sgd_solver.cpp:106] Iteration 20000, lr = 0.0001
I1112 18:47:20.712563 22658 solver.cpp:228] Iteration 21000, loss = 1.19933
I1112 18:47:20.712707 22658 solver.cpp:244]     Train net output #0: loss = 1.19933 (* 1 = 1.19933 loss)
I1112 18:47:20.712718 22658 sgd_solver.cpp:106] Iteration 21000, lr = 0.0001
I1112 18:48:17.504933 22658 solver.cpp:228] Iteration 22000, loss = 0.947277
I1112 18:48:17.505053 22658 solver.cpp:244]     Train net output #0: loss = 0.947283 (* 1 = 0.947283 loss)
I1112 18:48:17.505066 22658 sgd_solver.cpp:106] Iteration 22000, lr = 0.0001
I1112 18:49:14.303673 22658 solver.cpp:228] Iteration 23000, loss = 1.26126
I1112 18:49:14.303793 22658 solver.cpp:244]     Train net output #0: loss = 1.26127 (* 1 = 1.26127 loss)
I1112 18:49:14.303807 22658 sgd_solver.cpp:106] Iteration 23000, lr = 0.0001
I1112 18:50:11.098644 22658 solver.cpp:228] Iteration 24000, loss = 0.403298
I1112 18:50:11.098762 22658 solver.cpp:244]     Train net output #0: loss = 0.403304 (* 1 = 0.403304 loss)
I1112 18:50:11.098774 22658 sgd_solver.cpp:106] Iteration 24000, lr = 0.0001
I1112 18:51:07.845607 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_25000.caffemodel
I1112 18:51:25.874099 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_25000.solverstate
I1112 18:51:26.576740 22658 solver.cpp:337] Iteration 25000, Testing net (#0)
I1112 18:51:26.576786 22658 net.cpp:693] Ignoring source layer prob
I1112 18:51:28.575407 22658 solver.cpp:404]     Test net output #0: accuracy = 0.84624
I1112 18:51:28.583638 22658 solver.cpp:228] Iteration 25000, loss = 0.566215
I1112 18:51:28.583675 22658 solver.cpp:244]     Train net output #0: loss = 0.56622 (* 1 = 0.56622 loss)
I1112 18:51:28.583689 22658 sgd_solver.cpp:106] Iteration 25000, lr = 0.0001
I1112 18:52:25.389371 22658 solver.cpp:228] Iteration 26000, loss = 0.756037
I1112 18:52:25.389480 22658 solver.cpp:244]     Train net output #0: loss = 0.756043 (* 1 = 0.756043 loss)
I1112 18:52:25.389492 22658 sgd_solver.cpp:106] Iteration 26000, lr = 0.0001
I1112 18:53:22.199970 22658 solver.cpp:228] Iteration 27000, loss = 0.34899
I1112 18:53:22.200064 22658 solver.cpp:244]     Train net output #0: loss = 0.348995 (* 1 = 0.348995 loss)
I1112 18:53:22.200078 22658 sgd_solver.cpp:106] Iteration 27000, lr = 0.0001
I1112 18:54:19.018688 22658 solver.cpp:228] Iteration 28000, loss = 0.415251
I1112 18:54:19.018795 22658 solver.cpp:244]     Train net output #0: loss = 0.415257 (* 1 = 0.415257 loss)
I1112 18:54:19.018810 22658 sgd_solver.cpp:106] Iteration 28000, lr = 0.0001
I1112 18:55:15.819617 22658 solver.cpp:228] Iteration 29000, loss = 0.362996
I1112 18:55:15.819782 22658 solver.cpp:244]     Train net output #0: loss = 0.363002 (* 1 = 0.363002 loss)
I1112 18:55:15.819795 22658 sgd_solver.cpp:106] Iteration 29000, lr = 0.0001
I1112 18:56:12.563169 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_30000.caffemodel
I1112 18:56:31.634881 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_30000.solverstate
I1112 18:56:31.764564 22658 solver.cpp:337] Iteration 30000, Testing net (#0)
I1112 18:56:31.764607 22658 net.cpp:693] Ignoring source layer prob
I1112 18:56:33.762115 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9088
I1112 18:56:33.770154 22658 solver.cpp:228] Iteration 30000, loss = 0.529891
I1112 18:56:33.770190 22658 solver.cpp:244]     Train net output #0: loss = 0.529897 (* 1 = 0.529897 loss)
I1112 18:56:33.770201 22658 sgd_solver.cpp:46] MultiStep Status: Iteration 30000, step = 3
I1112 18:56:33.770216 22658 sgd_solver.cpp:106] Iteration 30000, lr = 1e-05
I1112 18:57:30.582237 22658 solver.cpp:228] Iteration 31000, loss = 0.250642
I1112 18:57:30.582331 22658 solver.cpp:244]     Train net output #0: loss = 0.250648 (* 1 = 0.250648 loss)
I1112 18:57:30.582343 22658 sgd_solver.cpp:106] Iteration 31000, lr = 1e-05
I1112 18:58:27.409876 22658 solver.cpp:228] Iteration 32000, loss = 0.311913
I1112 18:58:27.409950 22658 solver.cpp:244]     Train net output #0: loss = 0.311919 (* 1 = 0.311919 loss)
I1112 18:58:27.409961 22658 sgd_solver.cpp:106] Iteration 32000, lr = 1e-05
I1112 18:59:24.238893 22658 solver.cpp:228] Iteration 33000, loss = 0.310523
I1112 18:59:24.239007 22658 solver.cpp:244]     Train net output #0: loss = 0.310529 (* 1 = 0.310529 loss)
I1112 18:59:24.239022 22658 sgd_solver.cpp:106] Iteration 33000, lr = 1e-05
I1112 19:00:21.052326 22658 solver.cpp:228] Iteration 34000, loss = 0.295812
I1112 19:00:21.052418 22658 solver.cpp:244]     Train net output #0: loss = 0.295818 (* 1 = 0.295818 loss)
I1112 19:00:21.052430 22658 sgd_solver.cpp:106] Iteration 34000, lr = 1e-05
I1112 19:01:17.810945 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_35000.caffemodel
I1112 19:01:36.075402 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_35000.solverstate
I1112 19:01:36.203660 22658 solver.cpp:337] Iteration 35000, Testing net (#0)
I1112 19:01:36.203698 22658 net.cpp:693] Ignoring source layer prob
I1112 19:01:38.207485 22658 solver.cpp:404]     Test net output #0: accuracy = 0.92592
I1112 19:01:38.214996 22658 solver.cpp:228] Iteration 35000, loss = 0.435165
I1112 19:01:38.215032 22658 solver.cpp:244]     Train net output #0: loss = 0.43517 (* 1 = 0.43517 loss)
I1112 19:01:38.215045 22658 sgd_solver.cpp:106] Iteration 35000, lr = 1e-05
I1112 19:02:35.013890 22658 solver.cpp:228] Iteration 36000, loss = 0.227602
I1112 19:02:35.013986 22658 solver.cpp:244]     Train net output #0: loss = 0.227607 (* 1 = 0.227607 loss)
I1112 19:02:35.013998 22658 sgd_solver.cpp:106] Iteration 36000, lr = 1e-05
I1112 19:03:31.896461 22658 solver.cpp:228] Iteration 37000, loss = 0.492891
I1112 19:03:31.896539 22658 solver.cpp:244]     Train net output #0: loss = 0.492896 (* 1 = 0.492896 loss)
I1112 19:03:31.896553 22658 sgd_solver.cpp:106] Iteration 37000, lr = 1e-05
I1112 19:04:28.688140 22658 solver.cpp:228] Iteration 38000, loss = 0.135153
I1112 19:04:28.688277 22658 solver.cpp:244]     Train net output #0: loss = 0.135158 (* 1 = 0.135158 loss)
I1112 19:04:28.688292 22658 sgd_solver.cpp:106] Iteration 38000, lr = 1e-05
I1112 19:05:25.490181 22658 solver.cpp:228] Iteration 39000, loss = 0.214336
I1112 19:05:25.490299 22658 solver.cpp:244]     Train net output #0: loss = 0.214341 (* 1 = 0.214341 loss)
I1112 19:05:25.490314 22658 sgd_solver.cpp:106] Iteration 39000, lr = 1e-05
I1112 19:06:22.210944 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_40000.caffemodel
I1112 19:06:49.326015 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_40000.solverstate
I1112 19:06:49.458456 22658 solver.cpp:337] Iteration 40000, Testing net (#0)
I1112 19:06:49.458500 22658 net.cpp:693] Ignoring source layer prob
I1112 19:06:51.459578 22658 solver.cpp:404]     Test net output #0: accuracy = 0.92928
I1112 19:06:51.467869 22658 solver.cpp:228] Iteration 40000, loss = 0.340649
I1112 19:06:51.467903 22658 solver.cpp:244]     Train net output #0: loss = 0.340654 (* 1 = 0.340654 loss)
I1112 19:06:51.467916 22658 sgd_solver.cpp:106] Iteration 40000, lr = 1e-05
I1112 19:07:48.291949 22658 solver.cpp:228] Iteration 41000, loss = 0.500416
I1112 19:07:48.292021 22658 solver.cpp:244]     Train net output #0: loss = 0.500421 (* 1 = 0.500421 loss)
I1112 19:07:48.292032 22658 sgd_solver.cpp:106] Iteration 41000, lr = 1e-05
I1112 19:08:45.074378 22658 solver.cpp:228] Iteration 42000, loss = 0.233963
I1112 19:08:45.074527 22658 solver.cpp:244]     Train net output #0: loss = 0.233968 (* 1 = 0.233968 loss)
I1112 19:08:45.074539 22658 sgd_solver.cpp:106] Iteration 42000, lr = 1e-05
I1112 19:09:41.881499 22658 solver.cpp:228] Iteration 43000, loss = 0.441027
I1112 19:09:41.881615 22658 solver.cpp:244]     Train net output #0: loss = 0.441032 (* 1 = 0.441032 loss)
I1112 19:09:41.881628 22658 sgd_solver.cpp:106] Iteration 43000, lr = 1e-05
I1112 19:10:38.658195 22658 solver.cpp:228] Iteration 44000, loss = 0.297593
I1112 19:10:38.658335 22658 solver.cpp:244]     Train net output #0: loss = 0.297597 (* 1 = 0.297597 loss)
I1112 19:10:38.658347 22658 sgd_solver.cpp:106] Iteration 44000, lr = 1e-05
I1112 19:11:35.405364 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_45000.caffemodel
I1112 19:11:57.657634 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_45000.solverstate
I1112 19:11:57.787525 22658 solver.cpp:337] Iteration 45000, Testing net (#0)
I1112 19:11:57.787578 22658 net.cpp:693] Ignoring source layer prob
I1112 19:11:59.784309 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9324
I1112 19:11:59.792515 22658 solver.cpp:228] Iteration 45000, loss = 0.333901
I1112 19:11:59.792549 22658 solver.cpp:244]     Train net output #0: loss = 0.333906 (* 1 = 0.333906 loss)
I1112 19:11:59.792562 22658 sgd_solver.cpp:106] Iteration 45000, lr = 1e-05
I1112 19:12:56.636240 22658 solver.cpp:228] Iteration 46000, loss = 0.175954
I1112 19:12:56.636330 22658 solver.cpp:244]     Train net output #0: loss = 0.175959 (* 1 = 0.175959 loss)
I1112 19:12:56.636343 22658 sgd_solver.cpp:106] Iteration 46000, lr = 1e-05
I1112 19:13:53.450371 22658 solver.cpp:228] Iteration 47000, loss = 0.158882
I1112 19:13:53.450441 22658 solver.cpp:244]     Train net output #0: loss = 0.158887 (* 1 = 0.158887 loss)
I1112 19:13:53.450453 22658 sgd_solver.cpp:106] Iteration 47000, lr = 1e-05
I1112 19:14:51.430449 22658 solver.cpp:228] Iteration 48000, loss = 0.31462
I1112 19:14:51.430548 22658 solver.cpp:244]     Train net output #0: loss = 0.314625 (* 1 = 0.314625 loss)
I1112 19:14:51.430572 22658 sgd_solver.cpp:106] Iteration 48000, lr = 1e-05
I1112 19:15:50.208830 22658 solver.cpp:228] Iteration 49000, loss = 0.16152
I1112 19:15:50.208914 22658 solver.cpp:244]     Train net output #0: loss = 0.161525 (* 1 = 0.161525 loss)
I1112 19:15:50.208938 22658 sgd_solver.cpp:106] Iteration 49000, lr = 1e-05
I1112 19:16:48.458546 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_50000.caffemodel
I1112 19:17:06.910661 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_50000.solverstate
I1112 19:17:07.037364 22658 solver.cpp:337] Iteration 50000, Testing net (#0)
I1112 19:17:07.037407 22658 net.cpp:693] Ignoring source layer prob
I1112 19:17:09.204952 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9372
I1112 19:17:09.214370 22658 solver.cpp:228] Iteration 50000, loss = 0.201067
I1112 19:17:09.214418 22658 solver.cpp:244]     Train net output #0: loss = 0.201072 (* 1 = 0.201072 loss)
I1112 19:17:09.214438 22658 sgd_solver.cpp:106] Iteration 50000, lr = 1e-05
I1112 19:18:06.051889 22658 solver.cpp:228] Iteration 51000, loss = 0.409416
I1112 19:18:06.051991 22658 solver.cpp:244]     Train net output #0: loss = 0.40942 (* 1 = 0.40942 loss)
I1112 19:18:06.052003 22658 sgd_solver.cpp:106] Iteration 51000, lr = 1e-05
I1112 19:19:04.081697 22658 solver.cpp:228] Iteration 52000, loss = 0.213628
I1112 19:19:04.081885 22658 solver.cpp:244]     Train net output #0: loss = 0.213633 (* 1 = 0.213633 loss)
I1112 19:19:04.081913 22658 sgd_solver.cpp:106] Iteration 52000, lr = 1e-05
I1112 19:20:05.657680 22658 solver.cpp:228] Iteration 53000, loss = 0.317465
I1112 19:20:05.657795 22658 solver.cpp:244]     Train net output #0: loss = 0.31747 (* 1 = 0.31747 loss)
I1112 19:20:05.657814 22658 sgd_solver.cpp:106] Iteration 53000, lr = 1e-05
I1112 19:21:07.480934 22658 solver.cpp:228] Iteration 54000, loss = 0.206105
I1112 19:21:07.481036 22658 solver.cpp:244]     Train net output #0: loss = 0.20611 (* 1 = 0.20611 loss)
I1112 19:21:07.481050 22658 sgd_solver.cpp:106] Iteration 54000, lr = 1e-05
I1112 19:22:09.246300 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_55000.caffemodel
I1112 19:22:09.624891 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_55000.solverstate
I1112 19:22:10.080413 22658 solver.cpp:337] Iteration 55000, Testing net (#0)
I1112 19:22:10.080472 22658 net.cpp:693] Ignoring source layer prob
I1112 19:22:12.240922 22658 solver.cpp:404]     Test net output #0: accuracy = 0.94464
I1112 19:22:12.250411 22658 solver.cpp:228] Iteration 55000, loss = 0.170576
I1112 19:22:12.250458 22658 solver.cpp:244]     Train net output #0: loss = 0.170581 (* 1 = 0.170581 loss)
I1112 19:22:12.250478 22658 sgd_solver.cpp:106] Iteration 55000, lr = 1e-05
I1112 19:23:14.137468 22658 solver.cpp:228] Iteration 56000, loss = 0.151233
I1112 19:23:14.155560 22658 solver.cpp:244]     Train net output #0: loss = 0.151238 (* 1 = 0.151238 loss)
I1112 19:23:14.155589 22658 sgd_solver.cpp:106] Iteration 56000, lr = 1e-05
I1112 19:24:16.004221 22658 solver.cpp:228] Iteration 57000, loss = 0.21465
I1112 19:24:16.004348 22658 solver.cpp:244]     Train net output #0: loss = 0.214655 (* 1 = 0.214655 loss)
I1112 19:24:16.004367 22658 sgd_solver.cpp:106] Iteration 57000, lr = 1e-05
I1112 19:25:17.862640 22658 solver.cpp:228] Iteration 58000, loss = 0.17141
I1112 19:25:17.862752 22658 solver.cpp:244]     Train net output #0: loss = 0.171415 (* 1 = 0.171415 loss)
I1112 19:25:17.862769 22658 sgd_solver.cpp:106] Iteration 58000, lr = 1e-05
I1112 19:26:19.762698 22658 solver.cpp:228] Iteration 59000, loss = 0.0759664
I1112 19:26:19.762820 22658 solver.cpp:244]     Train net output #0: loss = 0.0759713 (* 1 = 0.0759713 loss)
I1112 19:26:19.762843 22658 sgd_solver.cpp:106] Iteration 59000, lr = 1e-05
I1112 19:27:21.479202 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_60000.caffemodel
I1112 19:27:46.666872 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_60000.solverstate
I1112 19:27:47.027364 22658 solver.cpp:337] Iteration 60000, Testing net (#0)
I1112 19:27:47.027434 22658 net.cpp:693] Ignoring source layer prob
I1112 19:27:49.150846 22658 solver.cpp:404]     Test net output #0: accuracy = 0.94944
I1112 19:27:49.161859 22658 solver.cpp:228] Iteration 60000, loss = 0.174202
I1112 19:27:49.161924 22658 solver.cpp:244]     Train net output #0: loss = 0.174206 (* 1 = 0.174206 loss)
I1112 19:27:49.161942 22658 sgd_solver.cpp:106] Iteration 60000, lr = 1e-05
I1112 19:28:51.676625 22658 solver.cpp:228] Iteration 61000, loss = 0.40184
I1112 19:28:51.676774 22658 solver.cpp:244]     Train net output #0: loss = 0.401845 (* 1 = 0.401845 loss)
I1112 19:28:51.676791 22658 sgd_solver.cpp:106] Iteration 61000, lr = 1e-05
I1112 19:29:53.929725 22658 solver.cpp:228] Iteration 62000, loss = 0.115392
I1112 19:29:53.929865 22658 solver.cpp:244]     Train net output #0: loss = 0.115397 (* 1 = 0.115397 loss)
I1112 19:29:53.929883 22658 sgd_solver.cpp:106] Iteration 62000, lr = 1e-05
I1112 19:30:56.340014 22658 solver.cpp:228] Iteration 63000, loss = 0.263272
I1112 19:30:56.340117 22658 solver.cpp:244]     Train net output #0: loss = 0.263277 (* 1 = 0.263277 loss)
I1112 19:30:56.340136 22658 sgd_solver.cpp:106] Iteration 63000, lr = 1e-05
I1112 19:31:58.303515 22658 solver.cpp:228] Iteration 64000, loss = 0.213521
I1112 19:31:58.303620 22658 solver.cpp:244]     Train net output #0: loss = 0.213526 (* 1 = 0.213526 loss)
I1112 19:31:58.303637 22658 sgd_solver.cpp:106] Iteration 64000, lr = 1e-05
I1112 19:33:00.141191 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_65000.caffemodel
I1112 19:33:27.978409 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_65000.solverstate
I1112 19:33:28.233078 22658 solver.cpp:337] Iteration 65000, Testing net (#0)
I1112 19:33:28.233115 22658 net.cpp:693] Ignoring source layer prob
I1112 19:33:30.367952 22658 solver.cpp:404]     Test net output #0: accuracy = 0.952721
I1112 19:33:30.376317 22658 solver.cpp:228] Iteration 65000, loss = 0.205211
I1112 19:33:30.376348 22658 solver.cpp:244]     Train net output #0: loss = 0.205216 (* 1 = 0.205216 loss)
I1112 19:33:30.376366 22658 sgd_solver.cpp:106] Iteration 65000, lr = 1e-05
I1112 19:34:32.288730 22658 solver.cpp:228] Iteration 66000, loss = 0.151429
I1112 19:34:32.295740 22658 solver.cpp:244]     Train net output #0: loss = 0.151434 (* 1 = 0.151434 loss)
I1112 19:34:32.295763 22658 sgd_solver.cpp:106] Iteration 66000, lr = 1e-05
I1112 19:35:32.291749 22658 solver.cpp:228] Iteration 67000, loss = 0.162783
I1112 19:35:32.291898 22658 solver.cpp:244]     Train net output #0: loss = 0.162788 (* 1 = 0.162788 loss)
I1112 19:35:32.291913 22658 sgd_solver.cpp:106] Iteration 67000, lr = 1e-05
I1112 19:36:29.091657 22658 solver.cpp:228] Iteration 68000, loss = 0.213127
I1112 19:36:29.091732 22658 solver.cpp:244]     Train net output #0: loss = 0.213132 (* 1 = 0.213132 loss)
I1112 19:36:29.091742 22658 sgd_solver.cpp:106] Iteration 68000, lr = 1e-05
I1112 19:37:25.881470 22658 solver.cpp:228] Iteration 69000, loss = 0.27647
I1112 19:37:25.881615 22658 solver.cpp:244]     Train net output #0: loss = 0.276474 (* 1 = 0.276474 loss)
I1112 19:37:25.881630 22658 sgd_solver.cpp:106] Iteration 69000, lr = 1e-05
I1112 19:38:22.621273 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_70000.caffemodel
I1112 19:38:56.720160 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_70000.solverstate
I1112 19:38:57.018792 22658 solver.cpp:337] Iteration 70000, Testing net (#0)
I1112 19:38:57.018859 22658 net.cpp:693] Ignoring source layer prob
I1112 19:38:59.010864 22658 solver.cpp:404]     Test net output #0: accuracy = 0.953361
I1112 19:38:59.019218 22658 solver.cpp:228] Iteration 70000, loss = 0.258355
I1112 19:38:59.019254 22658 solver.cpp:244]     Train net output #0: loss = 0.25836 (* 1 = 0.25836 loss)
I1112 19:38:59.019269 22658 sgd_solver.cpp:106] Iteration 70000, lr = 1e-05
I1112 19:39:55.825551 22658 solver.cpp:228] Iteration 71000, loss = 0.333374
I1112 19:39:55.825637 22658 solver.cpp:244]     Train net output #0: loss = 0.333378 (* 1 = 0.333378 loss)
I1112 19:39:55.825651 22658 sgd_solver.cpp:106] Iteration 71000, lr = 1e-05
I1112 19:40:52.618973 22658 solver.cpp:228] Iteration 72000, loss = 0.232436
I1112 19:40:52.619112 22658 solver.cpp:244]     Train net output #0: loss = 0.232441 (* 1 = 0.232441 loss)
I1112 19:40:52.619127 22658 sgd_solver.cpp:106] Iteration 72000, lr = 1e-05
I1112 19:41:49.410068 22658 solver.cpp:228] Iteration 73000, loss = 0.142638
I1112 19:41:49.410157 22658 solver.cpp:244]     Train net output #0: loss = 0.142642 (* 1 = 0.142642 loss)
I1112 19:41:49.410171 22658 sgd_solver.cpp:106] Iteration 73000, lr = 1e-05
I1112 19:42:46.196192 22658 solver.cpp:228] Iteration 74000, loss = 0.115871
I1112 19:42:46.196353 22658 solver.cpp:244]     Train net output #0: loss = 0.115875 (* 1 = 0.115875 loss)
I1112 19:42:46.196367 22658 sgd_solver.cpp:106] Iteration 74000, lr = 1e-05
I1112 19:43:42.922078 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_75000.caffemodel
I1112 19:44:41.740746 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_75000.solverstate
I1112 19:44:41.867322 22658 solver.cpp:337] Iteration 75000, Testing net (#0)
I1112 19:44:41.867360 22658 net.cpp:693] Ignoring source layer prob
I1112 19:44:43.867844 22658 solver.cpp:404]     Test net output #0: accuracy = 0.95824
I1112 19:44:43.876091 22658 solver.cpp:228] Iteration 75000, loss = 0.115801
I1112 19:44:43.876127 22658 solver.cpp:244]     Train net output #0: loss = 0.115806 (* 1 = 0.115806 loss)
I1112 19:44:43.876142 22658 sgd_solver.cpp:106] Iteration 75000, lr = 1e-05
I1112 19:45:42.837433 22658 solver.cpp:228] Iteration 76000, loss = 0.195798
I1112 19:45:42.837625 22658 solver.cpp:244]     Train net output #0: loss = 0.195803 (* 1 = 0.195803 loss)
I1112 19:45:42.837682 22658 sgd_solver.cpp:106] Iteration 76000, lr = 1e-05
I1112 19:46:44.494390 22658 solver.cpp:228] Iteration 77000, loss = 0.249234
I1112 19:46:44.494503 22658 solver.cpp:244]     Train net output #0: loss = 0.249239 (* 1 = 0.249239 loss)
I1112 19:46:44.494520 22658 sgd_solver.cpp:106] Iteration 77000, lr = 1e-05
I1112 19:47:46.349251 22658 solver.cpp:228] Iteration 78000, loss = 0.131885
I1112 19:47:46.349364 22658 solver.cpp:244]     Train net output #0: loss = 0.13189 (* 1 = 0.13189 loss)
I1112 19:47:46.349380 22658 sgd_solver.cpp:106] Iteration 78000, lr = 1e-05
I1112 19:48:48.242525 22658 solver.cpp:228] Iteration 79000, loss = 0.200348
I1112 19:48:48.242629 22658 solver.cpp:244]     Train net output #0: loss = 0.200353 (* 1 = 0.200353 loss)
I1112 19:48:48.242645 22658 sgd_solver.cpp:106] Iteration 79000, lr = 1e-05
I1112 19:49:50.070878 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_80000.caffemodel
I1112 19:49:52.752486 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_80000.solverstate
I1112 19:49:52.962076 22658 solver.cpp:337] Iteration 80000, Testing net (#0)
I1112 19:49:52.962122 22658 net.cpp:693] Ignoring source layer prob
I1112 19:49:55.144073 22658 solver.cpp:404]     Test net output #0: accuracy = 0.96208
I1112 19:49:55.152392 22658 solver.cpp:228] Iteration 80000, loss = 0.125659
I1112 19:49:55.152451 22658 solver.cpp:244]     Train net output #0: loss = 0.125664 (* 1 = 0.125664 loss)
I1112 19:49:55.152470 22658 sgd_solver.cpp:106] Iteration 80000, lr = 1e-05
I1112 19:50:57.283330 22658 solver.cpp:228] Iteration 81000, loss = 0.0925115
I1112 19:50:57.283447 22658 solver.cpp:244]     Train net output #0: loss = 0.0925162 (* 1 = 0.0925162 loss)
I1112 19:50:57.283484 22658 sgd_solver.cpp:106] Iteration 81000, lr = 1e-05
I1112 19:51:59.300597 22658 solver.cpp:228] Iteration 82000, loss = 0.0821938
I1112 19:51:59.300739 22658 solver.cpp:244]     Train net output #0: loss = 0.0821984 (* 1 = 0.0821984 loss)
I1112 19:51:59.300765 22658 sgd_solver.cpp:106] Iteration 82000, lr = 1e-05
I1112 19:53:01.273134 22658 solver.cpp:228] Iteration 83000, loss = 0.189682
I1112 19:53:01.273252 22658 solver.cpp:244]     Train net output #0: loss = 0.189687 (* 1 = 0.189687 loss)
I1112 19:53:01.273274 22658 sgd_solver.cpp:106] Iteration 83000, lr = 1e-05
I1112 19:54:03.106796 22658 solver.cpp:228] Iteration 84000, loss = 0.102762
I1112 19:54:03.106925 22658 solver.cpp:244]     Train net output #0: loss = 0.102766 (* 1 = 0.102766 loss)
I1112 19:54:03.106948 22658 sgd_solver.cpp:106] Iteration 84000, lr = 1e-05
I1112 19:55:04.932348 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_85000.caffemodel
I1112 19:55:46.258229 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_85000.solverstate
I1112 19:55:46.476588 22658 solver.cpp:337] Iteration 85000, Testing net (#0)
I1112 19:55:46.476624 22658 net.cpp:693] Ignoring source layer prob
I1112 19:55:48.617943 22658 solver.cpp:404]     Test net output #0: accuracy = 0.962081
I1112 19:55:48.625572 22658 solver.cpp:228] Iteration 85000, loss = 0.435795
I1112 19:55:48.625623 22658 solver.cpp:244]     Train net output #0: loss = 0.4358 (* 1 = 0.4358 loss)
I1112 19:55:48.625640 22658 sgd_solver.cpp:106] Iteration 85000, lr = 1e-05
I1112 19:56:49.912412 22658 solver.cpp:228] Iteration 86000, loss = 0.066838
I1112 19:56:49.912678 22658 solver.cpp:244]     Train net output #0: loss = 0.0668425 (* 1 = 0.0668425 loss)
I1112 19:56:49.912716 22658 sgd_solver.cpp:106] Iteration 86000, lr = 1e-05
I1112 19:57:51.256547 22658 solver.cpp:228] Iteration 87000, loss = 0.117711
I1112 19:57:51.256656 22658 solver.cpp:244]     Train net output #0: loss = 0.117716 (* 1 = 0.117716 loss)
I1112 19:57:51.256671 22658 sgd_solver.cpp:106] Iteration 87000, lr = 1e-05
I1112 19:58:52.546135 22658 solver.cpp:228] Iteration 88000, loss = 0.160661
I1112 19:58:52.546254 22658 solver.cpp:244]     Train net output #0: loss = 0.160665 (* 1 = 0.160665 loss)
I1112 19:58:52.546279 22658 sgd_solver.cpp:106] Iteration 88000, lr = 1e-05
I1112 19:59:53.822619 22658 solver.cpp:228] Iteration 89000, loss = 0.160484
I1112 19:59:53.822769 22658 solver.cpp:244]     Train net output #0: loss = 0.160489 (* 1 = 0.160489 loss)
I1112 19:59:53.822791 22658 sgd_solver.cpp:106] Iteration 89000, lr = 1e-05
I1112 20:00:55.987571 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_90000.caffemodel
I1112 20:01:32.902271 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_90000.solverstate
I1112 20:01:33.673023 22658 solver.cpp:337] Iteration 90000, Testing net (#0)
I1112 20:01:33.673081 22658 net.cpp:693] Ignoring source layer prob
I1112 20:01:35.671552 22658 solver.cpp:404]     Test net output #0: accuracy = 0.96512
I1112 20:01:35.679663 22658 solver.cpp:228] Iteration 90000, loss = 0.126786
I1112 20:01:35.679702 22658 solver.cpp:244]     Train net output #0: loss = 0.126791 (* 1 = 0.126791 loss)
I1112 20:01:35.679714 22658 sgd_solver.cpp:106] Iteration 90000, lr = 1e-05
I1112 20:02:32.486924 22658 solver.cpp:228] Iteration 91000, loss = 0.0327956
I1112 20:02:32.487010 22658 solver.cpp:244]     Train net output #0: loss = 0.0328 (* 1 = 0.0328 loss)
I1112 20:02:32.487022 22658 sgd_solver.cpp:106] Iteration 91000, lr = 1e-05
I1112 20:03:30.307323 22658 solver.cpp:228] Iteration 92000, loss = 0.123311
I1112 20:03:30.307476 22658 solver.cpp:244]     Train net output #0: loss = 0.123316 (* 1 = 0.123316 loss)
I1112 20:03:30.307497 22658 sgd_solver.cpp:106] Iteration 92000, lr = 1e-05
I1112 20:04:31.698539 22658 solver.cpp:228] Iteration 93000, loss = 0.0829564
I1112 20:04:31.698624 22658 solver.cpp:244]     Train net output #0: loss = 0.0829604 (* 1 = 0.0829604 loss)
I1112 20:04:31.698645 22658 sgd_solver.cpp:106] Iteration 93000, lr = 1e-05
I1112 20:05:33.697173 22658 solver.cpp:228] Iteration 94000, loss = 0.0586053
I1112 20:05:33.697298 22658 solver.cpp:244]     Train net output #0: loss = 0.0586092 (* 1 = 0.0586092 loss)
I1112 20:05:33.697319 22658 sgd_solver.cpp:106] Iteration 94000, lr = 1e-05
I1112 20:06:35.535065 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_95000.caffemodel
I1112 20:06:35.904137 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_95000.solverstate
I1112 20:06:36.114198 22658 solver.cpp:337] Iteration 95000, Testing net (#0)
I1112 20:06:36.114246 22658 net.cpp:693] Ignoring source layer prob
I1112 20:06:39.077673 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97136
I1112 20:06:39.092667 22658 solver.cpp:228] Iteration 95000, loss = 0.0855998
I1112 20:06:39.092720 22658 solver.cpp:244]     Train net output #0: loss = 0.0856037 (* 1 = 0.0856037 loss)
I1112 20:06:39.092742 22658 sgd_solver.cpp:106] Iteration 95000, lr = 1e-05
I1112 20:07:40.883407 22658 solver.cpp:228] Iteration 96000, loss = 0.133367
I1112 20:07:40.883632 22658 solver.cpp:244]     Train net output #0: loss = 0.13337 (* 1 = 0.13337 loss)
I1112 20:07:40.883649 22658 sgd_solver.cpp:106] Iteration 96000, lr = 1e-05
I1112 20:08:43.165920 22658 solver.cpp:228] Iteration 97000, loss = 0.143691
I1112 20:08:43.166043 22658 solver.cpp:244]     Train net output #0: loss = 0.143695 (* 1 = 0.143695 loss)
I1112 20:08:43.166064 22658 sgd_solver.cpp:106] Iteration 97000, lr = 1e-05
I1112 20:09:44.938036 22658 solver.cpp:228] Iteration 98000, loss = 0.147147
I1112 20:09:44.938148 22658 solver.cpp:244]     Train net output #0: loss = 0.147151 (* 1 = 0.147151 loss)
I1112 20:09:44.938166 22658 sgd_solver.cpp:106] Iteration 98000, lr = 1e-05
I1112 20:10:46.746414 22658 solver.cpp:228] Iteration 99000, loss = 0.0681359
I1112 20:10:46.746507 22658 solver.cpp:244]     Train net output #0: loss = 0.0681399 (* 1 = 0.0681399 loss)
I1112 20:10:46.746526 22658 sgd_solver.cpp:106] Iteration 99000, lr = 1e-05
I1112 20:11:48.528170 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_100000.caffemodel
I1112 20:12:29.172730 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_100000.solverstate
I1112 20:12:29.412004 22658 solver.cpp:337] Iteration 100000, Testing net (#0)
I1112 20:12:29.412040 22658 net.cpp:693] Ignoring source layer prob
I1112 20:12:32.239064 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97408
I1112 20:12:32.250768 22658 solver.cpp:228] Iteration 100000, loss = 0.0466952
I1112 20:12:32.250824 22658 solver.cpp:244]     Train net output #0: loss = 0.0466992 (* 1 = 0.0466992 loss)
I1112 20:12:32.250843 22658 sgd_solver.cpp:106] Iteration 100000, lr = 1e-05
I1112 20:13:34.100131 22658 solver.cpp:228] Iteration 101000, loss = 0.0544607
I1112 20:13:34.100242 22658 solver.cpp:244]     Train net output #0: loss = 0.0544646 (* 1 = 0.0544646 loss)
I1112 20:13:34.100263 22658 sgd_solver.cpp:106] Iteration 101000, lr = 1e-05
I1112 20:14:35.946539 22658 solver.cpp:228] Iteration 102000, loss = 0.0891605
I1112 20:14:35.946676 22658 solver.cpp:244]     Train net output #0: loss = 0.0891643 (* 1 = 0.0891643 loss)
I1112 20:14:35.946696 22658 sgd_solver.cpp:106] Iteration 102000, lr = 1e-05
I1112 20:15:37.780402 22658 solver.cpp:228] Iteration 103000, loss = 0.167639
I1112 20:15:37.780505 22658 solver.cpp:244]     Train net output #0: loss = 0.167642 (* 1 = 0.167642 loss)
I1112 20:15:37.780521 22658 sgd_solver.cpp:106] Iteration 103000, lr = 1e-05
I1112 20:16:39.580974 22658 solver.cpp:228] Iteration 104000, loss = 0.0958053
I1112 20:16:39.581087 22658 solver.cpp:244]     Train net output #0: loss = 0.0958088 (* 1 = 0.0958088 loss)
I1112 20:16:39.581105 22658 sgd_solver.cpp:106] Iteration 104000, lr = 1e-05
I1112 20:17:41.370409 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_105000.caffemodel
I1112 20:18:11.945446 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_105000.solverstate
I1112 20:18:12.129034 22658 solver.cpp:337] Iteration 105000, Testing net (#0)
I1112 20:18:12.129073 22658 net.cpp:693] Ignoring source layer prob
I1112 20:18:14.292526 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97432
I1112 20:18:14.305968 22658 solver.cpp:228] Iteration 105000, loss = 0.154738
I1112 20:18:14.306018 22658 solver.cpp:244]     Train net output #0: loss = 0.154742 (* 1 = 0.154742 loss)
I1112 20:18:14.306037 22658 sgd_solver.cpp:106] Iteration 105000, lr = 1e-05
I1112 20:19:16.141335 22658 solver.cpp:228] Iteration 106000, loss = 0.101075
I1112 20:19:16.141461 22658 solver.cpp:244]     Train net output #0: loss = 0.101079 (* 1 = 0.101079 loss)
I1112 20:19:16.141484 22658 sgd_solver.cpp:106] Iteration 106000, lr = 1e-05
I1112 20:20:13.729354 22658 solver.cpp:228] Iteration 107000, loss = 0.0655306
I1112 20:20:13.729431 22658 solver.cpp:244]     Train net output #0: loss = 0.0655344 (* 1 = 0.0655344 loss)
I1112 20:20:13.729444 22658 sgd_solver.cpp:106] Iteration 107000, lr = 1e-05
I1112 20:21:10.525743 22658 solver.cpp:228] Iteration 108000, loss = 0.101923
I1112 20:21:10.525858 22658 solver.cpp:244]     Train net output #0: loss = 0.101927 (* 1 = 0.101927 loss)
I1112 20:21:10.525873 22658 sgd_solver.cpp:106] Iteration 108000, lr = 1e-05
I1112 20:22:08.373420 22658 solver.cpp:228] Iteration 109000, loss = 0.117532
I1112 20:22:08.373569 22658 solver.cpp:244]     Train net output #0: loss = 0.117536 (* 1 = 0.117536 loss)
I1112 20:22:08.373582 22658 sgd_solver.cpp:106] Iteration 109000, lr = 1e-05
I1112 20:23:07.134135 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_110000.caffemodel
I1112 20:23:51.191522 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_110000.solverstate
I1112 20:23:51.343245 22658 solver.cpp:337] Iteration 110000, Testing net (#0)
I1112 20:23:51.343291 22658 net.cpp:693] Ignoring source layer prob
I1112 20:23:53.363507 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97576
I1112 20:23:53.371456 22658 solver.cpp:228] Iteration 110000, loss = 0.122511
I1112 20:23:53.371500 22658 solver.cpp:244]     Train net output #0: loss = 0.122515 (* 1 = 0.122515 loss)
I1112 20:23:53.371515 22658 sgd_solver.cpp:106] Iteration 110000, lr = 1e-05
I1112 20:24:52.679515 22658 solver.cpp:228] Iteration 111000, loss = 0.0543763
I1112 20:24:52.679682 22658 solver.cpp:244]     Train net output #0: loss = 0.0543801 (* 1 = 0.0543801 loss)
I1112 20:24:52.679724 22658 sgd_solver.cpp:106] Iteration 111000, lr = 1e-05
I1112 20:25:54.750475 22658 solver.cpp:228] Iteration 112000, loss = 0.198809
I1112 20:25:54.750602 22658 solver.cpp:244]     Train net output #0: loss = 0.198813 (* 1 = 0.198813 loss)
I1112 20:25:54.750618 22658 sgd_solver.cpp:106] Iteration 112000, lr = 1e-05
I1112 20:26:56.155791 22658 solver.cpp:228] Iteration 113000, loss = 0.142874
I1112 20:26:56.155928 22658 solver.cpp:244]     Train net output #0: loss = 0.142878 (* 1 = 0.142878 loss)
I1112 20:26:56.155951 22658 sgd_solver.cpp:106] Iteration 113000, lr = 1e-05
I1112 20:27:57.844512 22658 solver.cpp:228] Iteration 114000, loss = 0.047025
I1112 20:27:57.844641 22658 solver.cpp:244]     Train net output #0: loss = 0.0470288 (* 1 = 0.0470288 loss)
I1112 20:27:57.844665 22658 sgd_solver.cpp:106] Iteration 114000, lr = 1e-05
I1112 20:28:59.399060 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_115000.caffemodel
I1112 20:29:22.528756 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_115000.solverstate
I1112 20:29:22.789378 22658 solver.cpp:337] Iteration 115000, Testing net (#0)
I1112 20:29:22.789469 22658 net.cpp:693] Ignoring source layer prob
I1112 20:29:25.553201 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9756
I1112 20:29:25.563071 22658 solver.cpp:228] Iteration 115000, loss = 0.0537564
I1112 20:29:25.563115 22658 solver.cpp:244]     Train net output #0: loss = 0.0537601 (* 1 = 0.0537601 loss)
I1112 20:29:25.563136 22658 sgd_solver.cpp:106] Iteration 115000, lr = 1e-05
I1112 20:30:27.299278 22658 solver.cpp:228] Iteration 116000, loss = 0.108332
I1112 20:30:27.299401 22658 solver.cpp:244]     Train net output #0: loss = 0.108336 (* 1 = 0.108336 loss)
I1112 20:30:27.299417 22658 sgd_solver.cpp:106] Iteration 116000, lr = 1e-05
I1112 20:31:29.699971 22658 solver.cpp:228] Iteration 117000, loss = 0.060675
I1112 20:31:29.700057 22658 solver.cpp:244]     Train net output #0: loss = 0.0606787 (* 1 = 0.0606787 loss)
I1112 20:31:29.700081 22658 sgd_solver.cpp:106] Iteration 117000, lr = 1e-05
I1112 20:32:28.665735 22658 solver.cpp:228] Iteration 118000, loss = 0.0649171
I1112 20:32:28.665837 22658 solver.cpp:244]     Train net output #0: loss = 0.0649207 (* 1 = 0.0649207 loss)
I1112 20:32:28.665850 22658 sgd_solver.cpp:106] Iteration 118000, lr = 1e-05
I1112 20:33:26.140462 22658 solver.cpp:228] Iteration 119000, loss = 0.0960095
I1112 20:33:26.140583 22658 solver.cpp:244]     Train net output #0: loss = 0.0960131 (* 1 = 0.0960131 loss)
I1112 20:33:26.140594 22658 sgd_solver.cpp:106] Iteration 119000, lr = 1e-05
I1112 20:34:22.865619 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_120000.caffemodel
I1112 20:35:08.784278 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_120000.solverstate
I1112 20:35:08.910511 22658 solver.cpp:337] Iteration 120000, Testing net (#0)
I1112 20:35:08.910557 22658 net.cpp:693] Ignoring source layer prob
I1112 20:35:11.138779 22658 solver.cpp:404]     Test net output #0: accuracy = 0.978
I1112 20:35:11.147047 22658 solver.cpp:228] Iteration 120000, loss = 0.0960212
I1112 20:35:11.147080 22658 solver.cpp:244]     Train net output #0: loss = 0.096025 (* 1 = 0.096025 loss)
I1112 20:35:11.147094 22658 sgd_solver.cpp:106] Iteration 120000, lr = 1e-05
I1112 20:36:07.987220 22658 solver.cpp:228] Iteration 121000, loss = 0.0251692
I1112 20:36:07.987339 22658 solver.cpp:244]     Train net output #0: loss = 0.0251731 (* 1 = 0.0251731 loss)
I1112 20:36:07.987352 22658 sgd_solver.cpp:106] Iteration 121000, lr = 1e-05
I1112 20:37:04.847000 22658 solver.cpp:228] Iteration 122000, loss = 0.0701337
I1112 20:37:04.847103 22658 solver.cpp:244]     Train net output #0: loss = 0.0701378 (* 1 = 0.0701378 loss)
I1112 20:37:04.847128 22658 sgd_solver.cpp:106] Iteration 122000, lr = 1e-05
I1112 20:38:01.648829 22658 solver.cpp:228] Iteration 123000, loss = 0.107311
I1112 20:38:01.648972 22658 solver.cpp:244]     Train net output #0: loss = 0.107315 (* 1 = 0.107315 loss)
I1112 20:38:01.648988 22658 sgd_solver.cpp:106] Iteration 123000, lr = 1e-05
I1112 20:38:58.887368 22658 solver.cpp:228] Iteration 124000, loss = 0.184254
I1112 20:38:58.887464 22658 solver.cpp:244]     Train net output #0: loss = 0.184258 (* 1 = 0.184258 loss)
I1112 20:38:58.887490 22658 sgd_solver.cpp:106] Iteration 124000, lr = 1e-05
I1112 20:39:55.657119 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_125000.caffemodel
I1112 20:40:21.821209 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_125000.solverstate
I1112 20:40:22.111798 22658 solver.cpp:337] Iteration 125000, Testing net (#0)
I1112 20:40:22.111871 22658 net.cpp:693] Ignoring source layer prob
I1112 20:40:24.140230 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97792
I1112 20:40:24.148254 22658 solver.cpp:228] Iteration 125000, loss = 0.100383
I1112 20:40:24.148286 22658 solver.cpp:244]     Train net output #0: loss = 0.100387 (* 1 = 0.100387 loss)
I1112 20:40:24.148300 22658 sgd_solver.cpp:106] Iteration 125000, lr = 1e-05
I1112 20:41:20.953330 22658 solver.cpp:228] Iteration 126000, loss = 0.0422435
I1112 20:41:20.953464 22658 solver.cpp:244]     Train net output #0: loss = 0.0422477 (* 1 = 0.0422477 loss)
I1112 20:41:20.953480 22658 sgd_solver.cpp:106] Iteration 126000, lr = 1e-05
I1112 20:42:17.834780 22658 solver.cpp:228] Iteration 127000, loss = 0.0932531
I1112 20:42:17.834868 22658 solver.cpp:244]     Train net output #0: loss = 0.0932573 (* 1 = 0.0932573 loss)
I1112 20:42:17.834887 22658 sgd_solver.cpp:106] Iteration 127000, lr = 1e-05
I1112 20:43:14.825450 22658 solver.cpp:228] Iteration 128000, loss = 0.0894153
I1112 20:43:14.825526 22658 solver.cpp:244]     Train net output #0: loss = 0.0894195 (* 1 = 0.0894195 loss)
I1112 20:43:14.825539 22658 sgd_solver.cpp:106] Iteration 128000, lr = 1e-05
I1112 20:44:11.616441 22658 solver.cpp:228] Iteration 129000, loss = 0.134308
I1112 20:44:11.616569 22658 solver.cpp:244]     Train net output #0: loss = 0.134312 (* 1 = 0.134312 loss)
I1112 20:44:11.616582 22658 sgd_solver.cpp:106] Iteration 129000, lr = 1e-05
I1112 20:45:08.342778 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_130000.caffemodel
I1112 20:45:19.069383 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_130000.solverstate
I1112 20:45:19.199450 22658 solver.cpp:337] Iteration 130000, Testing net (#0)
I1112 20:45:19.199512 22658 net.cpp:693] Ignoring source layer prob
I1112 20:45:21.219424 22658 solver.cpp:404]     Test net output #0: accuracy = 0.97872
I1112 20:45:21.227772 22658 solver.cpp:228] Iteration 130000, loss = 0.0929341
I1112 20:45:21.227804 22658 solver.cpp:244]     Train net output #0: loss = 0.0929383 (* 1 = 0.0929383 loss)
I1112 20:45:21.227816 22658 sgd_solver.cpp:106] Iteration 130000, lr = 1e-05
I1112 20:46:18.003451 22658 solver.cpp:228] Iteration 131000, loss = 0.039815
I1112 20:46:18.003612 22658 solver.cpp:244]     Train net output #0: loss = 0.0398192 (* 1 = 0.0398192 loss)
I1112 20:46:18.003626 22658 sgd_solver.cpp:106] Iteration 131000, lr = 1e-05
I1112 20:47:14.805690 22658 solver.cpp:228] Iteration 132000, loss = 0.0769318
I1112 20:47:14.805773 22658 solver.cpp:244]     Train net output #0: loss = 0.076936 (* 1 = 0.076936 loss)
I1112 20:47:14.805791 22658 sgd_solver.cpp:106] Iteration 132000, lr = 1e-05
I1112 20:48:11.565834 22658 solver.cpp:228] Iteration 133000, loss = 0.107856
I1112 20:48:11.565904 22658 solver.cpp:244]     Train net output #0: loss = 0.107861 (* 1 = 0.107861 loss)
I1112 20:48:11.565917 22658 sgd_solver.cpp:106] Iteration 133000, lr = 1e-05
I1112 20:49:08.336546 22658 solver.cpp:228] Iteration 134000, loss = 0.0771949
I1112 20:49:08.336621 22658 solver.cpp:244]     Train net output #0: loss = 0.0771992 (* 1 = 0.0771992 loss)
I1112 20:49:08.336634 22658 sgd_solver.cpp:106] Iteration 134000, lr = 1e-05
I1112 20:50:05.072194 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_135000.caffemodel
I1112 20:50:43.558310 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_135000.solverstate
I1112 20:50:43.683404 22658 solver.cpp:337] Iteration 135000, Testing net (#0)
I1112 20:50:43.683449 22658 net.cpp:693] Ignoring source layer prob
I1112 20:50:45.701880 22658 solver.cpp:404]     Test net output #0: accuracy = 0.978721
I1112 20:50:45.710172 22658 solver.cpp:228] Iteration 135000, loss = 0.0763671
I1112 20:50:45.710209 22658 solver.cpp:244]     Train net output #0: loss = 0.0763713 (* 1 = 0.0763713 loss)
I1112 20:50:45.710222 22658 sgd_solver.cpp:106] Iteration 135000, lr = 1e-05
I1112 20:51:42.504884 22658 solver.cpp:228] Iteration 136000, loss = 0.0927074
I1112 20:51:42.505026 22658 solver.cpp:244]     Train net output #0: loss = 0.0927116 (* 1 = 0.0927116 loss)
I1112 20:51:42.505039 22658 sgd_solver.cpp:106] Iteration 136000, lr = 1e-05
I1112 20:52:39.317550 22658 solver.cpp:228] Iteration 137000, loss = 0.157865
I1112 20:52:39.317636 22658 solver.cpp:244]     Train net output #0: loss = 0.157869 (* 1 = 0.157869 loss)
I1112 20:52:39.317647 22658 sgd_solver.cpp:106] Iteration 137000, lr = 1e-05
I1112 20:53:36.129366 22658 solver.cpp:228] Iteration 138000, loss = 0.0406279
I1112 20:53:36.129439 22658 solver.cpp:244]     Train net output #0: loss = 0.0406323 (* 1 = 0.0406323 loss)
I1112 20:53:36.129451 22658 sgd_solver.cpp:106] Iteration 138000, lr = 1e-05
I1112 20:54:32.971813 22658 solver.cpp:228] Iteration 139000, loss = 0.258542
I1112 20:54:32.971945 22658 solver.cpp:244]     Train net output #0: loss = 0.258547 (* 1 = 0.258547 loss)
I1112 20:54:32.971958 22658 sgd_solver.cpp:106] Iteration 139000, lr = 1e-05
I1112 20:55:29.720185 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_140000.caffemodel
I1112 20:55:58.576355 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_140000.solverstate
I1112 20:55:59.344419 22658 solver.cpp:337] Iteration 140000, Testing net (#0)
I1112 20:55:59.344465 22658 net.cpp:693] Ignoring source layer prob
I1112 20:56:01.373252 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98304
I1112 20:56:01.381248 22658 solver.cpp:228] Iteration 140000, loss = 0.118582
I1112 20:56:01.381281 22658 solver.cpp:244]     Train net output #0: loss = 0.118586 (* 1 = 0.118586 loss)
I1112 20:56:01.381304 22658 sgd_solver.cpp:106] Iteration 140000, lr = 1e-05
I1112 20:56:58.185081 22658 solver.cpp:228] Iteration 141000, loss = 0.125344
I1112 20:56:58.185220 22658 solver.cpp:244]     Train net output #0: loss = 0.125348 (* 1 = 0.125348 loss)
I1112 20:56:58.185231 22658 sgd_solver.cpp:106] Iteration 141000, lr = 1e-05
I1112 20:57:54.970682 22658 solver.cpp:228] Iteration 142000, loss = 0.039972
I1112 20:57:54.970834 22658 solver.cpp:244]     Train net output #0: loss = 0.0399764 (* 1 = 0.0399764 loss)
I1112 20:57:54.970846 22658 sgd_solver.cpp:106] Iteration 142000, lr = 1e-05
I1112 20:58:51.752876 22658 solver.cpp:228] Iteration 143000, loss = 0.0324312
I1112 20:58:51.753010 22658 solver.cpp:244]     Train net output #0: loss = 0.0324357 (* 1 = 0.0324357 loss)
I1112 20:58:51.753024 22658 sgd_solver.cpp:106] Iteration 143000, lr = 1e-05
I1112 20:59:48.538215 22658 solver.cpp:228] Iteration 144000, loss = 0.0268269
I1112 20:59:48.538359 22658 solver.cpp:244]     Train net output #0: loss = 0.0268315 (* 1 = 0.0268315 loss)
I1112 20:59:48.538373 22658 sgd_solver.cpp:106] Iteration 144000, lr = 1e-05
I1112 21:00:45.275162 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_145000.caffemodel
I1112 21:00:45.599586 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_145000.solverstate
I1112 21:00:45.794607 22658 solver.cpp:337] Iteration 145000, Testing net (#0)
I1112 21:00:45.794646 22658 net.cpp:693] Ignoring source layer prob
I1112 21:00:47.787456 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9808
I1112 21:00:47.795586 22658 solver.cpp:228] Iteration 145000, loss = 0.0730953
I1112 21:00:47.795627 22658 solver.cpp:244]     Train net output #0: loss = 0.0730998 (* 1 = 0.0730998 loss)
I1112 21:00:47.795640 22658 sgd_solver.cpp:106] Iteration 145000, lr = 1e-05
I1112 21:01:44.572578 22658 solver.cpp:228] Iteration 146000, loss = 0.0418733
I1112 21:01:44.572706 22658 solver.cpp:244]     Train net output #0: loss = 0.0418779 (* 1 = 0.0418779 loss)
I1112 21:01:44.572721 22658 sgd_solver.cpp:106] Iteration 146000, lr = 1e-05
I1112 21:02:41.334988 22658 solver.cpp:228] Iteration 147000, loss = 0.0956071
I1112 21:02:41.335063 22658 solver.cpp:244]     Train net output #0: loss = 0.0956117 (* 1 = 0.0956117 loss)
I1112 21:02:41.335077 22658 sgd_solver.cpp:106] Iteration 147000, lr = 1e-05
I1112 21:03:38.118713 22658 solver.cpp:228] Iteration 148000, loss = 0.112924
I1112 21:03:38.118857 22658 solver.cpp:244]     Train net output #0: loss = 0.112929 (* 1 = 0.112929 loss)
I1112 21:03:38.118871 22658 sgd_solver.cpp:106] Iteration 148000, lr = 1e-05
I1112 21:04:34.884706 22658 solver.cpp:228] Iteration 149000, loss = 0.103558
I1112 21:04:34.884781 22658 solver.cpp:244]     Train net output #0: loss = 0.103563 (* 1 = 0.103563 loss)
I1112 21:04:34.884794 22658 sgd_solver.cpp:106] Iteration 149000, lr = 1e-05
I1112 21:05:31.597337 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_150000.caffemodel
I1112 21:05:38.080971 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_150000.solverstate
I1112 21:05:38.206790 22658 solver.cpp:337] Iteration 150000, Testing net (#0)
I1112 21:05:38.206835 22658 net.cpp:693] Ignoring source layer prob
I1112 21:05:40.256230 22658 solver.cpp:404]     Test net output #0: accuracy = 0.9836
I1112 21:05:40.264143 22658 solver.cpp:228] Iteration 150000, loss = 0.0545443
I1112 21:05:40.264175 22658 solver.cpp:244]     Train net output #0: loss = 0.0545491 (* 1 = 0.0545491 loss)
I1112 21:05:40.264188 22658 sgd_solver.cpp:106] Iteration 150000, lr = 1e-05
I1112 21:06:37.068620 22658 solver.cpp:228] Iteration 151000, loss = 0.0471437
I1112 21:06:37.068709 22658 solver.cpp:244]     Train net output #0: loss = 0.0471486 (* 1 = 0.0471486 loss)
I1112 21:06:37.068722 22658 sgd_solver.cpp:106] Iteration 151000, lr = 1e-05
I1112 21:07:33.869997 22658 solver.cpp:228] Iteration 152000, loss = 0.0694555
I1112 21:07:33.870139 22658 solver.cpp:244]     Train net output #0: loss = 0.0694603 (* 1 = 0.0694603 loss)
I1112 21:07:33.870152 22658 sgd_solver.cpp:106] Iteration 152000, lr = 1e-05
I1112 21:08:30.662034 22658 solver.cpp:228] Iteration 153000, loss = 0.0944737
I1112 21:08:30.662245 22658 solver.cpp:244]     Train net output #0: loss = 0.0944786 (* 1 = 0.0944786 loss)
I1112 21:08:30.662261 22658 sgd_solver.cpp:106] Iteration 153000, lr = 1e-05
I1112 21:09:27.494827 22658 solver.cpp:228] Iteration 154000, loss = 0.0622184
I1112 21:09:27.494956 22658 solver.cpp:244]     Train net output #0: loss = 0.0622233 (* 1 = 0.0622233 loss)
I1112 21:09:27.494971 22658 sgd_solver.cpp:106] Iteration 154000, lr = 1e-05
I1112 21:10:24.193181 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_155000.caffemodel
I1112 21:11:14.876988 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_155000.solverstate
I1112 21:11:15.005151 22658 solver.cpp:337] Iteration 155000, Testing net (#0)
I1112 21:11:15.005190 22658 net.cpp:693] Ignoring source layer prob
I1112 21:11:17.043164 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98544
I1112 21:11:17.051352 22658 solver.cpp:228] Iteration 155000, loss = 0.031915
I1112 21:11:17.051384 22658 solver.cpp:244]     Train net output #0: loss = 0.03192 (* 1 = 0.03192 loss)
I1112 21:11:17.051396 22658 sgd_solver.cpp:106] Iteration 155000, lr = 1e-05
I1112 21:12:13.795614 22658 solver.cpp:228] Iteration 156000, loss = 0.0468683
I1112 21:12:13.795775 22658 solver.cpp:244]     Train net output #0: loss = 0.0468732 (* 1 = 0.0468732 loss)
I1112 21:12:13.795789 22658 sgd_solver.cpp:106] Iteration 156000, lr = 1e-05
I1112 21:13:10.567159 22658 solver.cpp:228] Iteration 157000, loss = 0.0911628
I1112 21:13:10.567245 22658 solver.cpp:244]     Train net output #0: loss = 0.0911678 (* 1 = 0.0911678 loss)
I1112 21:13:10.567260 22658 sgd_solver.cpp:106] Iteration 157000, lr = 1e-05
I1112 21:14:07.315346 22658 solver.cpp:228] Iteration 158000, loss = 0.205191
I1112 21:14:07.315421 22658 solver.cpp:244]     Train net output #0: loss = 0.205196 (* 1 = 0.205196 loss)
I1112 21:14:07.315433 22658 sgd_solver.cpp:106] Iteration 158000, lr = 1e-05
I1112 21:15:04.061944 22658 solver.cpp:228] Iteration 159000, loss = 0.109404
I1112 21:15:04.062016 22658 solver.cpp:244]     Train net output #0: loss = 0.109409 (* 1 = 0.109409 loss)
I1112 21:15:04.062026 22658 sgd_solver.cpp:106] Iteration 159000, lr = 1e-05
I1112 21:16:00.834239 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_160000.caffemodel
I1112 21:16:56.652683 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_160000.solverstate
I1112 21:16:56.778071 22658 solver.cpp:337] Iteration 160000, Testing net (#0)
I1112 21:16:56.778105 22658 net.cpp:693] Ignoring source layer prob
I1112 21:16:58.773280 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98592
I1112 21:16:58.781839 22658 solver.cpp:228] Iteration 160000, loss = 0.0335857
I1112 21:16:58.781875 22658 solver.cpp:244]     Train net output #0: loss = 0.0335906 (* 1 = 0.0335906 loss)
I1112 21:16:58.781888 22658 sgd_solver.cpp:106] Iteration 160000, lr = 1e-05
I1112 21:17:55.590939 22658 solver.cpp:228] Iteration 161000, loss = 0.0730014
I1112 21:17:55.591030 22658 solver.cpp:244]     Train net output #0: loss = 0.0730062 (* 1 = 0.0730062 loss)
I1112 21:17:55.591044 22658 sgd_solver.cpp:106] Iteration 161000, lr = 1e-05
I1112 21:18:52.460878 22658 solver.cpp:228] Iteration 162000, loss = 0.0866657
I1112 21:18:52.461024 22658 solver.cpp:244]     Train net output #0: loss = 0.0866705 (* 1 = 0.0866705 loss)
I1112 21:18:52.461040 22658 sgd_solver.cpp:106] Iteration 162000, lr = 1e-05
I1112 21:19:50.006188 22658 solver.cpp:228] Iteration 163000, loss = 0.041264
I1112 21:19:50.006311 22658 solver.cpp:244]     Train net output #0: loss = 0.0412688 (* 1 = 0.0412688 loss)
I1112 21:19:50.006328 22658 sgd_solver.cpp:106] Iteration 163000, lr = 1e-05
I1112 21:20:46.780594 22658 solver.cpp:228] Iteration 164000, loss = 0.0465584
I1112 21:20:46.780668 22658 solver.cpp:244]     Train net output #0: loss = 0.0465633 (* 1 = 0.0465633 loss)
I1112 21:20:46.780678 22658 sgd_solver.cpp:106] Iteration 164000, lr = 1e-05
I1112 21:21:43.487491 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_165000.caffemodel
I1112 21:22:06.030360 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_165000.solverstate
I1112 21:22:06.160189 22658 solver.cpp:337] Iteration 165000, Testing net (#0)
I1112 21:22:06.160243 22658 net.cpp:693] Ignoring source layer prob
I1112 21:22:08.153568 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98344
I1112 21:22:08.161983 22658 solver.cpp:228] Iteration 165000, loss = 0.0570027
I1112 21:22:08.162020 22658 solver.cpp:244]     Train net output #0: loss = 0.0570076 (* 1 = 0.0570076 loss)
I1112 21:22:08.162035 22658 sgd_solver.cpp:106] Iteration 165000, lr = 1e-05
I1112 21:23:04.954463 22658 solver.cpp:228] Iteration 166000, loss = 0.0834248
I1112 21:23:04.954540 22658 solver.cpp:244]     Train net output #0: loss = 0.0834297 (* 1 = 0.0834297 loss)
I1112 21:23:04.954552 22658 sgd_solver.cpp:106] Iteration 166000, lr = 1e-05
I1112 21:24:01.738023 22658 solver.cpp:228] Iteration 167000, loss = 0.057301
I1112 21:24:01.738106 22658 solver.cpp:244]     Train net output #0: loss = 0.0573059 (* 1 = 0.0573059 loss)
I1112 21:24:01.738122 22658 sgd_solver.cpp:106] Iteration 167000, lr = 1e-05
I1112 21:24:58.541908 22658 solver.cpp:228] Iteration 168000, loss = 0.0160937
I1112 21:24:58.542031 22658 solver.cpp:244]     Train net output #0: loss = 0.0160985 (* 1 = 0.0160985 loss)
I1112 21:24:58.542043 22658 sgd_solver.cpp:106] Iteration 168000, lr = 1e-05
I1112 21:25:55.365742 22658 solver.cpp:228] Iteration 169000, loss = 0.0715471
I1112 21:25:55.365865 22658 solver.cpp:244]     Train net output #0: loss = 0.0715521 (* 1 = 0.0715521 loss)
I1112 21:25:55.365880 22658 sgd_solver.cpp:106] Iteration 169000, lr = 1e-05
I1112 21:26:52.124804 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_170000.caffemodel
I1112 21:27:46.149219 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_170000.solverstate
I1112 21:27:46.310220 22658 solver.cpp:337] Iteration 170000, Testing net (#0)
I1112 21:27:46.310264 22658 net.cpp:693] Ignoring source layer prob
I1112 21:27:48.307837 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98408
I1112 21:27:48.315819 22658 solver.cpp:228] Iteration 170000, loss = 0.0211924
I1112 21:27:48.315856 22658 solver.cpp:244]     Train net output #0: loss = 0.0211973 (* 1 = 0.0211973 loss)
I1112 21:27:48.315871 22658 sgd_solver.cpp:106] Iteration 170000, lr = 1e-05
I1112 21:28:45.113427 22658 solver.cpp:228] Iteration 171000, loss = 0.0401826
I1112 21:28:45.113559 22658 solver.cpp:244]     Train net output #0: loss = 0.0401874 (* 1 = 0.0401874 loss)
I1112 21:28:45.113572 22658 sgd_solver.cpp:106] Iteration 171000, lr = 1e-05
I1112 21:29:41.908344 22658 solver.cpp:228] Iteration 172000, loss = 0.0562365
I1112 21:29:41.908470 22658 solver.cpp:244]     Train net output #0: loss = 0.0562415 (* 1 = 0.0562415 loss)
I1112 21:29:41.908484 22658 sgd_solver.cpp:106] Iteration 172000, lr = 1e-05
I1112 21:30:38.663069 22658 solver.cpp:228] Iteration 173000, loss = 0.0314199
I1112 21:30:38.663143 22658 solver.cpp:244]     Train net output #0: loss = 0.0314249 (* 1 = 0.0314249 loss)
I1112 21:30:38.663156 22658 sgd_solver.cpp:106] Iteration 173000, lr = 1e-05
I1112 21:31:35.461849 22658 solver.cpp:228] Iteration 174000, loss = 0.0655912
I1112 21:31:35.461925 22658 solver.cpp:244]     Train net output #0: loss = 0.0655962 (* 1 = 0.0655962 loss)
I1112 21:31:35.461938 22658 sgd_solver.cpp:106] Iteration 174000, lr = 1e-05
I1112 21:32:32.189601 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_175000.caffemodel
I1112 21:33:11.661753 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_175000.solverstate
I1112 21:33:11.788835 22658 solver.cpp:337] Iteration 175000, Testing net (#0)
I1112 21:33:11.788877 22658 net.cpp:693] Ignoring source layer prob
I1112 21:33:13.803560 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98744
I1112 21:33:13.811833 22658 solver.cpp:228] Iteration 175000, loss = 0.0588413
I1112 21:33:13.811872 22658 solver.cpp:244]     Train net output #0: loss = 0.0588464 (* 1 = 0.0588464 loss)
I1112 21:33:13.811885 22658 sgd_solver.cpp:106] Iteration 175000, lr = 1e-05
I1112 21:34:10.585845 22658 solver.cpp:228] Iteration 176000, loss = 0.0498035
I1112 21:34:10.585952 22658 solver.cpp:244]     Train net output #0: loss = 0.0498084 (* 1 = 0.0498084 loss)
I1112 21:34:10.585969 22658 sgd_solver.cpp:106] Iteration 176000, lr = 1e-05
I1112 21:35:07.384919 22658 solver.cpp:228] Iteration 177000, loss = 0.0515311
I1112 21:35:07.384996 22658 solver.cpp:244]     Train net output #0: loss = 0.051536 (* 1 = 0.051536 loss)
I1112 21:35:07.385007 22658 sgd_solver.cpp:106] Iteration 177000, lr = 1e-05
I1112 21:36:04.149585 22658 solver.cpp:228] Iteration 178000, loss = 0.0272203
I1112 21:36:04.149669 22658 solver.cpp:244]     Train net output #0: loss = 0.027225 (* 1 = 0.027225 loss)
I1112 21:36:04.149682 22658 sgd_solver.cpp:106] Iteration 178000, lr = 1e-05
I1112 21:37:00.908612 22658 solver.cpp:228] Iteration 179000, loss = 0.135542
I1112 21:37:00.908684 22658 solver.cpp:244]     Train net output #0: loss = 0.135547 (* 1 = 0.135547 loss)
I1112 21:37:00.908694 22658 sgd_solver.cpp:106] Iteration 179000, lr = 1e-05
I1112 21:37:57.616582 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_180000.caffemodel
I1112 21:38:40.744658 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_180000.solverstate
I1112 21:38:40.868038 22658 solver.cpp:337] Iteration 180000, Testing net (#0)
I1112 21:38:40.868072 22658 net.cpp:693] Ignoring source layer prob
I1112 21:38:42.874202 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98864
I1112 21:38:42.882356 22658 solver.cpp:228] Iteration 180000, loss = 0.0295726
I1112 21:38:42.882393 22658 solver.cpp:244]     Train net output #0: loss = 0.0295773 (* 1 = 0.0295773 loss)
I1112 21:38:42.882408 22658 sgd_solver.cpp:106] Iteration 180000, lr = 1e-05
I1112 21:39:39.667399 22658 solver.cpp:228] Iteration 181000, loss = 0.0600494
I1112 21:39:39.667495 22658 solver.cpp:244]     Train net output #0: loss = 0.060054 (* 1 = 0.060054 loss)
I1112 21:39:39.667510 22658 sgd_solver.cpp:106] Iteration 181000, lr = 1e-05
I1112 21:40:36.507742 22658 solver.cpp:228] Iteration 182000, loss = 0.0243624
I1112 21:40:36.507817 22658 solver.cpp:244]     Train net output #0: loss = 0.0243671 (* 1 = 0.0243671 loss)
I1112 21:40:36.507828 22658 sgd_solver.cpp:106] Iteration 182000, lr = 1e-05
I1112 21:41:33.306901 22658 solver.cpp:228] Iteration 183000, loss = 0.0555625
I1112 21:41:33.306973 22658 solver.cpp:244]     Train net output #0: loss = 0.0555673 (* 1 = 0.0555673 loss)
I1112 21:41:33.306984 22658 sgd_solver.cpp:106] Iteration 183000, lr = 1e-05
I1112 21:42:30.088368 22658 solver.cpp:228] Iteration 184000, loss = 0.0496629
I1112 21:42:30.088539 22658 solver.cpp:244]     Train net output #0: loss = 0.0496676 (* 1 = 0.0496676 loss)
I1112 21:42:30.088569 22658 sgd_solver.cpp:106] Iteration 184000, lr = 1e-05
I1112 21:43:26.837252 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_185000.caffemodel
I1112 21:43:52.452572 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_185000.solverstate
I1112 21:43:52.575176 22658 solver.cpp:337] Iteration 185000, Testing net (#0)
I1112 21:43:52.575218 22658 net.cpp:693] Ignoring source layer prob
I1112 21:43:54.601177 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98672
I1112 21:43:54.610512 22658 solver.cpp:228] Iteration 185000, loss = 0.0480283
I1112 21:43:54.610581 22658 solver.cpp:244]     Train net output #0: loss = 0.048033 (* 1 = 0.048033 loss)
I1112 21:43:54.610635 22658 sgd_solver.cpp:106] Iteration 185000, lr = 1e-05
I1112 21:44:51.382313 22658 solver.cpp:228] Iteration 186000, loss = 0.021458
I1112 21:44:51.382436 22658 solver.cpp:244]     Train net output #0: loss = 0.0214627 (* 1 = 0.0214627 loss)
I1112 21:44:51.382450 22658 sgd_solver.cpp:106] Iteration 186000, lr = 1e-05
I1112 21:45:48.145872 22658 solver.cpp:228] Iteration 187000, loss = 0.0661592
I1112 21:45:48.146028 22658 solver.cpp:244]     Train net output #0: loss = 0.066164 (* 1 = 0.066164 loss)
I1112 21:45:48.146042 22658 sgd_solver.cpp:106] Iteration 187000, lr = 1e-05
I1112 21:46:44.919323 22658 solver.cpp:228] Iteration 188000, loss = 0.0476509
I1112 21:46:44.919484 22658 solver.cpp:244]     Train net output #0: loss = 0.0476558 (* 1 = 0.0476558 loss)
I1112 21:46:44.919497 22658 sgd_solver.cpp:106] Iteration 188000, lr = 1e-05
I1112 21:47:41.713317 22658 solver.cpp:228] Iteration 189000, loss = 0.0306991
I1112 21:47:41.713392 22658 solver.cpp:244]     Train net output #0: loss = 0.0307039 (* 1 = 0.0307039 loss)
I1112 21:47:41.713405 22658 sgd_solver.cpp:106] Iteration 189000, lr = 1e-05
I1112 21:48:38.430124 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_190000.caffemodel
I1112 21:48:58.883813 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_190000.solverstate
I1112 21:48:59.007131 22658 solver.cpp:337] Iteration 190000, Testing net (#0)
I1112 21:48:59.007166 22658 net.cpp:693] Ignoring source layer prob
I1112 21:49:01.017141 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98688
I1112 21:49:01.025030 22658 solver.cpp:228] Iteration 190000, loss = 0.0643359
I1112 21:49:01.025068 22658 solver.cpp:244]     Train net output #0: loss = 0.0643408 (* 1 = 0.0643408 loss)
I1112 21:49:01.025080 22658 sgd_solver.cpp:106] Iteration 190000, lr = 1e-05
I1112 21:49:57.796241 22658 solver.cpp:228] Iteration 191000, loss = 0.0644197
I1112 21:49:57.796362 22658 solver.cpp:244]     Train net output #0: loss = 0.0644246 (* 1 = 0.0644246 loss)
I1112 21:49:57.796376 22658 sgd_solver.cpp:106] Iteration 191000, lr = 1e-05
I1112 21:50:54.576442 22658 solver.cpp:228] Iteration 192000, loss = 0.0308325
I1112 21:50:54.576562 22658 solver.cpp:244]     Train net output #0: loss = 0.0308375 (* 1 = 0.0308375 loss)
I1112 21:50:54.576575 22658 sgd_solver.cpp:106] Iteration 192000, lr = 1e-05
I1112 21:51:51.356675 22658 solver.cpp:228] Iteration 193000, loss = 0.0416236
I1112 21:51:51.356817 22658 solver.cpp:244]     Train net output #0: loss = 0.0416287 (* 1 = 0.0416287 loss)
I1112 21:51:51.356829 22658 sgd_solver.cpp:106] Iteration 193000, lr = 1e-05
I1112 21:52:48.130861 22658 solver.cpp:228] Iteration 194000, loss = 0.0204529
I1112 21:52:48.130934 22658 solver.cpp:244]     Train net output #0: loss = 0.0204579 (* 1 = 0.0204579 loss)
I1112 21:52:48.130944 22658 sgd_solver.cpp:106] Iteration 194000, lr = 1e-05
I1112 21:53:44.838289 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_195000.caffemodel
I1112 21:54:10.010563 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_195000.solverstate
I1112 21:54:10.135151 22658 solver.cpp:337] Iteration 195000, Testing net (#0)
I1112 21:54:10.135187 22658 net.cpp:693] Ignoring source layer prob
I1112 21:54:12.135428 22658 solver.cpp:404]     Test net output #0: accuracy = 0.988
I1112 21:54:12.143792 22658 solver.cpp:228] Iteration 195000, loss = 0.0315241
I1112 21:54:12.143831 22658 solver.cpp:244]     Train net output #0: loss = 0.0315291 (* 1 = 0.0315291 loss)
I1112 21:54:12.143846 22658 sgd_solver.cpp:106] Iteration 195000, lr = 1e-05
I1112 21:55:08.936801 22658 solver.cpp:228] Iteration 196000, loss = 0.0422908
I1112 21:55:08.936893 22658 solver.cpp:244]     Train net output #0: loss = 0.0422958 (* 1 = 0.0422958 loss)
I1112 21:55:08.936908 22658 sgd_solver.cpp:106] Iteration 196000, lr = 1e-05
I1112 21:56:05.730690 22658 solver.cpp:228] Iteration 197000, loss = 0.0458275
I1112 21:56:05.730809 22658 solver.cpp:244]     Train net output #0: loss = 0.0458326 (* 1 = 0.0458326 loss)
I1112 21:56:05.730823 22658 sgd_solver.cpp:106] Iteration 197000, lr = 1e-05
I1112 21:57:02.556721 22658 solver.cpp:228] Iteration 198000, loss = 0.0726431
I1112 21:57:02.556840 22658 solver.cpp:244]     Train net output #0: loss = 0.0726481 (* 1 = 0.0726481 loss)
I1112 21:57:02.556854 22658 sgd_solver.cpp:106] Iteration 198000, lr = 1e-05
I1112 21:57:59.328810 22658 solver.cpp:228] Iteration 199000, loss = 0.0257422
I1112 21:57:59.328915 22658 solver.cpp:244]     Train net output #0: loss = 0.0257472 (* 1 = 0.0257472 loss)
I1112 21:57:59.328927 22658 sgd_solver.cpp:106] Iteration 199000, lr = 1e-05
I1112 21:58:56.048578 22658 solver.cpp:454] Snapshotting to binary proto file snapshots/snap__iter_200000.caffemodel
I1112 21:59:19.801123 22658 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshots/snap__iter_200000.solverstate
I1112 21:59:19.935370 22658 solver.cpp:317] Iteration 200000, loss = 0.0253112
I1112 21:59:19.935418 22658 solver.cpp:337] Iteration 200000, Testing net (#0)
I1112 21:59:19.935427 22658 net.cpp:693] Ignoring source layer prob
I1112 21:59:21.925748 22658 solver.cpp:404]     Test net output #0: accuracy = 0.98792
I1112 21:59:21.925791 22658 solver.cpp:322] Optimization Done.
I1112 21:59:21.943846 22658 caffe.cpp:254] Optimization Done.