DIGITS-CNN/cars/lr-investigations/fixed/5e-3/caffe_output.log

I0406 13:51:49.506356 23057 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210406-124546-3359/solver.prototxt
I0406 13:51:49.506525 23057 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string).
W0406 13:51:49.506529 23057 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type.
I0406 13:51:49.506597 23057 caffe.cpp:218] Using GPUs 1
I0406 13:51:49.526320 23057 caffe.cpp:223] GPU 1: GeForce GTX TITAN X
I0406 13:51:49.732375 23057 solver.cpp:44] Initializing solver from parameters:
test_iter: 51
test_interval: 102
base_lr: 0.005
display: 12
max_iter: 20400
lr_policy: "fixed"
momentum: 0.9
weight_decay: 5e-05
snapshot: 102
snapshot_prefix: "snapshot"
solver_mode: GPU
device_id: 1
net: "train_val.prototxt"
train_state {
level: 0
stage: ""
}
type: "SGD"
I0406 13:51:49.733369 23057 solver.cpp:87] Creating training net from net file: train_val.prototxt
I0406 13:51:49.734033 23057 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data
I0406 13:51:49.734047 23057 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy
I0406 13:51:49.734171 23057 net.cpp:51] Initializing net from parameters:
state {
phase: TRAIN
level: 0
stage: ""
}
layer {
name: "train-data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 227
mean_file: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto"
}
data_param {
source: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/train_db"
batch_size: 128
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "norm1"
type: "LRN"
bottom: "conv1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "norm1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "norm2"
type: "LRN"
bottom: "conv2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "norm2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "fc7"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 196
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8"
bottom: "label"
top: "loss"
}
I0406 13:51:49.734251 23057 layer_factory.hpp:77] Creating layer train-data
I0406 13:51:49.757519 23057 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/train_db
I0406 13:51:49.757766 23057 net.cpp:84] Creating Layer train-data
I0406 13:51:49.757781 23057 net.cpp:380] train-data -> data
I0406 13:51:49.757800 23057 net.cpp:380] train-data -> label
I0406 13:51:49.757812 23057 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0406 13:51:49.764586 23057 data_layer.cpp:45] output data size: 128,3,227,227
I0406 13:51:49.898903 23057 net.cpp:122] Setting up train-data
I0406 13:51:49.898926 23057 net.cpp:129] Top shape: 128 3 227 227 (19787136)
I0406 13:51:49.898931 23057 net.cpp:129] Top shape: 128 (128)
I0406 13:51:49.898932 23057 net.cpp:137] Memory required for data: 79149056
I0406 13:51:49.898941 23057 layer_factory.hpp:77] Creating layer conv1
I0406 13:51:49.898959 23057 net.cpp:84] Creating Layer conv1
I0406 13:51:49.898963 23057 net.cpp:406] conv1 <- data
I0406 13:51:49.898974 23057 net.cpp:380] conv1 -> conv1
I0406 13:51:50.357398 23057 net.cpp:122] Setting up conv1
I0406 13:51:50.357421 23057 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0406 13:51:50.357426 23057 net.cpp:137] Memory required for data: 227833856
I0406 13:51:50.357450 23057 layer_factory.hpp:77] Creating layer relu1
I0406 13:51:50.357463 23057 net.cpp:84] Creating Layer relu1
I0406 13:51:50.357468 23057 net.cpp:406] relu1 <- conv1
I0406 13:51:50.357476 23057 net.cpp:367] relu1 -> conv1 (in-place)
I0406 13:51:50.357862 23057 net.cpp:122] Setting up relu1
I0406 13:51:50.357872 23057 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0406 13:51:50.357877 23057 net.cpp:137] Memory required for data: 376518656
I0406 13:51:50.357880 23057 layer_factory.hpp:77] Creating layer norm1
I0406 13:51:50.357890 23057 net.cpp:84] Creating Layer norm1
I0406 13:51:50.357894 23057 net.cpp:406] norm1 <- conv1
I0406 13:51:50.357930 23057 net.cpp:380] norm1 -> norm1
I0406 13:51:50.358530 23057 net.cpp:122] Setting up norm1
I0406 13:51:50.358541 23057 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0406 13:51:50.358546 23057 net.cpp:137] Memory required for data: 525203456
I0406 13:51:50.358549 23057 layer_factory.hpp:77] Creating layer pool1
I0406 13:51:50.358558 23057 net.cpp:84] Creating Layer pool1
I0406 13:51:50.358562 23057 net.cpp:406] pool1 <- norm1
I0406 13:51:50.358568 23057 net.cpp:380] pool1 -> pool1
I0406 13:51:50.358613 23057 net.cpp:122] Setting up pool1
I0406 13:51:50.358620 23057 net.cpp:129] Top shape: 128 96 27 27 (8957952)
I0406 13:51:50.358624 23057 net.cpp:137] Memory required for data: 561035264
I0406 13:51:50.358628 23057 layer_factory.hpp:77] Creating layer conv2
I0406 13:51:50.358640 23057 net.cpp:84] Creating Layer conv2
I0406 13:51:50.358644 23057 net.cpp:406] conv2 <- pool1
I0406 13:51:50.358649 23057 net.cpp:380] conv2 -> conv2
I0406 13:51:50.367098 23057 net.cpp:122] Setting up conv2
I0406 13:51:50.367125 23057 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0406 13:51:50.367128 23057 net.cpp:137] Memory required for data: 656586752
I0406 13:51:50.367143 23057 layer_factory.hpp:77] Creating layer relu2
I0406 13:51:50.367153 23057 net.cpp:84] Creating Layer relu2
I0406 13:51:50.367158 23057 net.cpp:406] relu2 <- conv2
I0406 13:51:50.367166 23057 net.cpp:367] relu2 -> conv2 (in-place)
I0406 13:51:50.367725 23057 net.cpp:122] Setting up relu2
I0406 13:51:50.367738 23057 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0406 13:51:50.367743 23057 net.cpp:137] Memory required for data: 752138240
I0406 13:51:50.367746 23057 layer_factory.hpp:77] Creating layer norm2
I0406 13:51:50.367755 23057 net.cpp:84] Creating Layer norm2
I0406 13:51:50.367758 23057 net.cpp:406] norm2 <- conv2
I0406 13:51:50.367765 23057 net.cpp:380] norm2 -> norm2
I0406 13:51:50.368533 23057 net.cpp:122] Setting up norm2
I0406 13:51:50.368544 23057 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0406 13:51:50.368548 23057 net.cpp:137] Memory required for data: 847689728
I0406 13:51:50.368552 23057 layer_factory.hpp:77] Creating layer pool2
I0406 13:51:50.368561 23057 net.cpp:84] Creating Layer pool2
I0406 13:51:50.368566 23057 net.cpp:406] pool2 <- norm2
I0406 13:51:50.368571 23057 net.cpp:380] pool2 -> pool2
I0406 13:51:50.368607 23057 net.cpp:122] Setting up pool2
I0406 13:51:50.368614 23057 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0406 13:51:50.368618 23057 net.cpp:137] Memory required for data: 869840896
I0406 13:51:50.368620 23057 layer_factory.hpp:77] Creating layer conv3
I0406 13:51:50.368633 23057 net.cpp:84] Creating Layer conv3
I0406 13:51:50.368636 23057 net.cpp:406] conv3 <- pool2
I0406 13:51:50.368643 23057 net.cpp:380] conv3 -> conv3
I0406 13:51:50.381891 23057 net.cpp:122] Setting up conv3
I0406 13:51:50.381913 23057 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0406 13:51:50.381916 23057 net.cpp:137] Memory required for data: 903067648
I0406 13:51:50.381927 23057 layer_factory.hpp:77] Creating layer relu3
I0406 13:51:50.381935 23057 net.cpp:84] Creating Layer relu3
I0406 13:51:50.381938 23057 net.cpp:406] relu3 <- conv3
I0406 13:51:50.381943 23057 net.cpp:367] relu3 -> conv3 (in-place)
I0406 13:51:50.382341 23057 net.cpp:122] Setting up relu3
I0406 13:51:50.382350 23057 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0406 13:51:50.382352 23057 net.cpp:137] Memory required for data: 936294400
I0406 13:51:50.382355 23057 layer_factory.hpp:77] Creating layer conv4
I0406 13:51:50.382364 23057 net.cpp:84] Creating Layer conv4
I0406 13:51:50.382366 23057 net.cpp:406] conv4 <- conv3
I0406 13:51:50.382371 23057 net.cpp:380] conv4 -> conv4
I0406 13:51:50.393712 23057 net.cpp:122] Setting up conv4
I0406 13:51:50.393736 23057 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0406 13:51:50.393740 23057 net.cpp:137] Memory required for data: 969521152
I0406 13:51:50.393752 23057 layer_factory.hpp:77] Creating layer relu4
I0406 13:51:50.393766 23057 net.cpp:84] Creating Layer relu4
I0406 13:51:50.393771 23057 net.cpp:406] relu4 <- conv4
I0406 13:51:50.393802 23057 net.cpp:367] relu4 -> conv4 (in-place)
I0406 13:51:50.394281 23057 net.cpp:122] Setting up relu4
I0406 13:51:50.394291 23057 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0406 13:51:50.394295 23057 net.cpp:137] Memory required for data: 1002747904
I0406 13:51:50.394299 23057 layer_factory.hpp:77] Creating layer conv5
I0406 13:51:50.394312 23057 net.cpp:84] Creating Layer conv5
I0406 13:51:50.394316 23057 net.cpp:406] conv5 <- conv4
I0406 13:51:50.394325 23057 net.cpp:380] conv5 -> conv5
I0406 13:51:50.405966 23057 net.cpp:122] Setting up conv5
I0406 13:51:50.405995 23057 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0406 13:51:50.406002 23057 net.cpp:137] Memory required for data: 1024899072
I0406 13:51:50.406019 23057 layer_factory.hpp:77] Creating layer relu5
I0406 13:51:50.406033 23057 net.cpp:84] Creating Layer relu5
I0406 13:51:50.406038 23057 net.cpp:406] relu5 <- conv5
I0406 13:51:50.406046 23057 net.cpp:367] relu5 -> conv5 (in-place)
I0406 13:51:50.406710 23057 net.cpp:122] Setting up relu5
I0406 13:51:50.406723 23057 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0406 13:51:50.406726 23057 net.cpp:137] Memory required for data: 1047050240
I0406 13:51:50.406730 23057 layer_factory.hpp:77] Creating layer pool5
I0406 13:51:50.406739 23057 net.cpp:84] Creating Layer pool5
I0406 13:51:50.406744 23057 net.cpp:406] pool5 <- conv5
I0406 13:51:50.406749 23057 net.cpp:380] pool5 -> pool5
I0406 13:51:50.406798 23057 net.cpp:122] Setting up pool5
I0406 13:51:50.406805 23057 net.cpp:129] Top shape: 128 256 6 6 (1179648)
I0406 13:51:50.406808 23057 net.cpp:137] Memory required for data: 1051768832
I0406 13:51:50.406811 23057 layer_factory.hpp:77] Creating layer fc6
I0406 13:51:50.406823 23057 net.cpp:84] Creating Layer fc6
I0406 13:51:50.406827 23057 net.cpp:406] fc6 <- pool5
I0406 13:51:50.406834 23057 net.cpp:380] fc6 -> fc6
I0406 13:51:50.862350 23057 net.cpp:122] Setting up fc6
I0406 13:51:50.862377 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:50.862381 23057 net.cpp:137] Memory required for data: 1053865984
I0406 13:51:50.862392 23057 layer_factory.hpp:77] Creating layer relu6
I0406 13:51:50.862403 23057 net.cpp:84] Creating Layer relu6
I0406 13:51:50.862408 23057 net.cpp:406] relu6 <- fc6
I0406 13:51:50.862416 23057 net.cpp:367] relu6 -> fc6 (in-place)
I0406 13:51:50.865869 23057 net.cpp:122] Setting up relu6
I0406 13:51:50.865887 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:50.865891 23057 net.cpp:137] Memory required for data: 1055963136
I0406 13:51:50.865895 23057 layer_factory.hpp:77] Creating layer drop6
I0406 13:51:50.865907 23057 net.cpp:84] Creating Layer drop6
I0406 13:51:50.865911 23057 net.cpp:406] drop6 <- fc6
I0406 13:51:50.865918 23057 net.cpp:367] drop6 -> fc6 (in-place)
I0406 13:51:50.865957 23057 net.cpp:122] Setting up drop6
I0406 13:51:50.865963 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:50.865967 23057 net.cpp:137] Memory required for data: 1058060288
I0406 13:51:50.865969 23057 layer_factory.hpp:77] Creating layer fc7
I0406 13:51:50.865978 23057 net.cpp:84] Creating Layer fc7
I0406 13:51:50.865981 23057 net.cpp:406] fc7 <- fc6
I0406 13:51:50.865989 23057 net.cpp:380] fc7 -> fc7
I0406 13:51:51.049242 23057 net.cpp:122] Setting up fc7
I0406 13:51:51.049263 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:51.049265 23057 net.cpp:137] Memory required for data: 1060157440
I0406 13:51:51.049273 23057 layer_factory.hpp:77] Creating layer relu7
I0406 13:51:51.049281 23057 net.cpp:84] Creating Layer relu7
I0406 13:51:51.049285 23057 net.cpp:406] relu7 <- fc7
I0406 13:51:51.049290 23057 net.cpp:367] relu7 -> fc7 (in-place)
I0406 13:51:51.049667 23057 net.cpp:122] Setting up relu7
I0406 13:51:51.049675 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:51.049679 23057 net.cpp:137] Memory required for data: 1062254592
I0406 13:51:51.049680 23057 layer_factory.hpp:77] Creating layer drop7
I0406 13:51:51.049685 23057 net.cpp:84] Creating Layer drop7
I0406 13:51:51.049688 23057 net.cpp:406] drop7 <- fc7
I0406 13:51:51.049715 23057 net.cpp:367] drop7 -> fc7 (in-place)
I0406 13:51:51.049736 23057 net.cpp:122] Setting up drop7
I0406 13:51:51.049741 23057 net.cpp:129] Top shape: 128 4096 (524288)
I0406 13:51:51.049743 23057 net.cpp:137] Memory required for data: 1064351744
I0406 13:51:51.049746 23057 layer_factory.hpp:77] Creating layer fc8
I0406 13:51:51.049753 23057 net.cpp:84] Creating Layer fc8
I0406 13:51:51.049755 23057 net.cpp:406] fc8 <- fc7
I0406 13:51:51.049760 23057 net.cpp:380] fc8 -> fc8
I0406 13:51:51.057101 23057 net.cpp:122] Setting up fc8
I0406 13:51:51.057122 23057 net.cpp:129] Top shape: 128 196 (25088)
I0406 13:51:51.057124 23057 net.cpp:137] Memory required for data: 1064452096
I0406 13:51:51.057132 23057 layer_factory.hpp:77] Creating layer loss
I0406 13:51:51.057142 23057 net.cpp:84] Creating Layer loss
I0406 13:51:51.057145 23057 net.cpp:406] loss <- fc8
I0406 13:51:51.057149 23057 net.cpp:406] loss <- label
I0406 13:51:51.057155 23057 net.cpp:380] loss -> loss
I0406 13:51:51.057164 23057 layer_factory.hpp:77] Creating layer loss
I0406 13:51:51.057893 23057 net.cpp:122] Setting up loss
I0406 13:51:51.057902 23057 net.cpp:129] Top shape: (1)
I0406 13:51:51.057904 23057 net.cpp:132]     with loss weight 1
I0406 13:51:51.057926 23057 net.cpp:137] Memory required for data: 1064452100
I0406 13:51:51.057929 23057 net.cpp:198] loss needs backward computation.
I0406 13:51:51.057934 23057 net.cpp:198] fc8 needs backward computation.
I0406 13:51:51.057936 23057 net.cpp:198] drop7 needs backward computation.
I0406 13:51:51.057940 23057 net.cpp:198] relu7 needs backward computation.
I0406 13:51:51.057941 23057 net.cpp:198] fc7 needs backward computation.
I0406 13:51:51.057943 23057 net.cpp:198] drop6 needs backward computation.
I0406 13:51:51.057945 23057 net.cpp:198] relu6 needs backward computation.
I0406 13:51:51.057947 23057 net.cpp:198] fc6 needs backward computation.
I0406 13:51:51.057950 23057 net.cpp:198] pool5 needs backward computation.
I0406 13:51:51.057952 23057 net.cpp:198] relu5 needs backward computation.
I0406 13:51:51.057955 23057 net.cpp:198] conv5 needs backward computation.
I0406 13:51:51.057957 23057 net.cpp:198] relu4 needs backward computation.
I0406 13:51:51.057960 23057 net.cpp:198] conv4 needs backward computation.
I0406 13:51:51.057961 23057 net.cpp:198] relu3 needs backward computation.
I0406 13:51:51.057963 23057 net.cpp:198] conv3 needs backward computation.
I0406 13:51:51.057966 23057 net.cpp:198] pool2 needs backward computation.
I0406 13:51:51.057969 23057 net.cpp:198] norm2 needs backward computation.
I0406 13:51:51.057972 23057 net.cpp:198] relu2 needs backward computation.
I0406 13:51:51.057974 23057 net.cpp:198] conv2 needs backward computation.
I0406 13:51:51.057977 23057 net.cpp:198] pool1 needs backward computation.
I0406 13:51:51.057979 23057 net.cpp:198] norm1 needs backward computation.
I0406 13:51:51.057981 23057 net.cpp:198] relu1 needs backward computation.
I0406 13:51:51.057983 23057 net.cpp:198] conv1 needs backward computation.
I0406 13:51:51.057986 23057 net.cpp:200] train-data does not need backward computation.
I0406 13:51:51.057989 23057 net.cpp:242] This network produces output loss
I0406 13:51:51.058001 23057 net.cpp:255] Network initialization done.
I0406 13:51:51.058554 23057 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt
I0406 13:51:51.058583 23057 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data
I0406 13:51:51.058712 23057 net.cpp:51] Initializing net from parameters:
state {
phase: TEST
}
layer {
name: "val-data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
crop_size: 227
mean_file: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto"
}
data_param {
source: "/mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/val_db"
batch_size: 32
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "norm1"
type: "LRN"
bottom: "conv1"
top: "norm1"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "norm1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "norm2"
type: "LRN"
bottom: "conv2"
top: "norm2"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "norm2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "pool2"
top: "conv3"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "pool5"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "fc7"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 196
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "accuracy"
type: "Accuracy"
bottom: "fc8"
bottom: "label"
top: "accuracy"
include {
phase: TEST
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "fc8"
bottom: "label"
top: "loss"
}
I0406 13:51:51.058812 23057 layer_factory.hpp:77] Creating layer val-data
I0406 13:51:51.061672 23057 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/val_db
I0406 13:51:51.061879 23057 net.cpp:84] Creating Layer val-data
I0406 13:51:51.061888 23057 net.cpp:380] val-data -> data
I0406 13:51:51.061897 23057 net.cpp:380] val-data -> label
I0406 13:51:51.061904 23057 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0406 13:51:51.065662 23057 data_layer.cpp:45] output data size: 32,3,227,227
I0406 13:51:51.103117 23057 net.cpp:122] Setting up val-data
I0406 13:51:51.103142 23057 net.cpp:129] Top shape: 32 3 227 227 (4946784)
I0406 13:51:51.103147 23057 net.cpp:129] Top shape: 32 (32)
I0406 13:51:51.103150 23057 net.cpp:137] Memory required for data: 19787264
I0406 13:51:51.103157 23057 layer_factory.hpp:77] Creating layer label_val-data_1_split
I0406 13:51:51.103170 23057 net.cpp:84] Creating Layer label_val-data_1_split
I0406 13:51:51.103175 23057 net.cpp:406] label_val-data_1_split <- label
I0406 13:51:51.103183 23057 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0
I0406 13:51:51.103194 23057 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1
I0406 13:51:51.103252 23057 net.cpp:122] Setting up label_val-data_1_split
I0406 13:51:51.103260 23057 net.cpp:129] Top shape: 32 (32)
I0406 13:51:51.103263 23057 net.cpp:129] Top shape: 32 (32)
I0406 13:51:51.103266 23057 net.cpp:137] Memory required for data: 19787520
I0406 13:51:51.103271 23057 layer_factory.hpp:77] Creating layer conv1
I0406 13:51:51.103283 23057 net.cpp:84] Creating Layer conv1
I0406 13:51:51.103287 23057 net.cpp:406] conv1 <- data
I0406 13:51:51.103293 23057 net.cpp:380] conv1 -> conv1
I0406 13:51:51.112589 23057 net.cpp:122] Setting up conv1
I0406 13:51:51.112614 23057 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0406 13:51:51.112618 23057 net.cpp:137] Memory required for data: 56958720
I0406 13:51:51.112633 23057 layer_factory.hpp:77] Creating layer relu1
I0406 13:51:51.112644 23057 net.cpp:84] Creating Layer relu1
I0406 13:51:51.112648 23057 net.cpp:406] relu1 <- conv1
I0406 13:51:51.112655 23057 net.cpp:367] relu1 -> conv1 (in-place)
I0406 13:51:51.113054 23057 net.cpp:122] Setting up relu1
I0406 13:51:51.113065 23057 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0406 13:51:51.113068 23057 net.cpp:137] Memory required for data: 94129920
I0406 13:51:51.113072 23057 layer_factory.hpp:77] Creating layer norm1
I0406 13:51:51.113082 23057 net.cpp:84] Creating Layer norm1
I0406 13:51:51.113086 23057 net.cpp:406] norm1 <- conv1
I0406 13:51:51.113092 23057 net.cpp:380] norm1 -> norm1
I0406 13:51:51.113718 23057 net.cpp:122] Setting up norm1
I0406 13:51:51.113729 23057 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0406 13:51:51.113734 23057 net.cpp:137] Memory required for data: 131301120
I0406 13:51:51.113736 23057 layer_factory.hpp:77] Creating layer pool1
I0406 13:51:51.113744 23057 net.cpp:84] Creating Layer pool1
I0406 13:51:51.113749 23057 net.cpp:406] pool1 <- norm1
I0406 13:51:51.113754 23057 net.cpp:380] pool1 -> pool1
I0406 13:51:51.113788 23057 net.cpp:122] Setting up pool1
I0406 13:51:51.113795 23057 net.cpp:129] Top shape: 32 96 27 27 (2239488)
I0406 13:51:51.113797 23057 net.cpp:137] Memory required for data: 140259072
I0406 13:51:51.113801 23057 layer_factory.hpp:77] Creating layer conv2
I0406 13:51:51.113812 23057 net.cpp:84] Creating Layer conv2
I0406 13:51:51.113816 23057 net.cpp:406] conv2 <- pool1
I0406 13:51:51.113847 23057 net.cpp:380] conv2 -> conv2
I0406 13:51:51.122893 23057 net.cpp:122] Setting up conv2
I0406 13:51:51.122917 23057 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0406 13:51:51.122921 23057 net.cpp:137] Memory required for data: 164146944
I0406 13:51:51.122937 23057 layer_factory.hpp:77] Creating layer relu2
I0406 13:51:51.122947 23057 net.cpp:84] Creating Layer relu2
I0406 13:51:51.122952 23057 net.cpp:406] relu2 <- conv2
I0406 13:51:51.122961 23057 net.cpp:367] relu2 -> conv2 (in-place)
I0406 13:51:51.123623 23057 net.cpp:122] Setting up relu2
I0406 13:51:51.123636 23057 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0406 13:51:51.123639 23057 net.cpp:137] Memory required for data: 188034816
I0406 13:51:51.123643 23057 layer_factory.hpp:77] Creating layer norm2
I0406 13:51:51.123656 23057 net.cpp:84] Creating Layer norm2
I0406 13:51:51.123659 23057 net.cpp:406] norm2 <- conv2
I0406 13:51:51.123665 23057 net.cpp:380] norm2 -> norm2
I0406 13:51:51.124349 23057 net.cpp:122] Setting up norm2
I0406 13:51:51.124361 23057 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0406 13:51:51.124363 23057 net.cpp:137] Memory required for data: 211922688
I0406 13:51:51.124367 23057 layer_factory.hpp:77] Creating layer pool2
I0406 13:51:51.124377 23057 net.cpp:84] Creating Layer pool2
I0406 13:51:51.124380 23057 net.cpp:406] pool2 <- norm2
I0406 13:51:51.124385 23057 net.cpp:380] pool2 -> pool2
I0406 13:51:51.124424 23057 net.cpp:122] Setting up pool2
I0406 13:51:51.124430 23057 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0406 13:51:51.124434 23057 net.cpp:137] Memory required for data: 217460480
I0406 13:51:51.124437 23057 layer_factory.hpp:77] Creating layer conv3
I0406 13:51:51.124450 23057 net.cpp:84] Creating Layer conv3
I0406 13:51:51.124454 23057 net.cpp:406] conv3 <- pool2
I0406 13:51:51.124461 23057 net.cpp:380] conv3 -> conv3
I0406 13:51:51.137672 23057 net.cpp:122] Setting up conv3
I0406 13:51:51.137696 23057 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0406 13:51:51.137698 23057 net.cpp:137] Memory required for data: 225767168
I0406 13:51:51.137710 23057 layer_factory.hpp:77] Creating layer relu3
I0406 13:51:51.137719 23057 net.cpp:84] Creating Layer relu3
I0406 13:51:51.137722 23057 net.cpp:406] relu3 <- conv3
I0406 13:51:51.137730 23057 net.cpp:367] relu3 -> conv3 (in-place)
I0406 13:51:51.138237 23057 net.cpp:122] Setting up relu3
I0406 13:51:51.138248 23057 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0406 13:51:51.138250 23057 net.cpp:137] Memory required for data: 234073856
I0406 13:51:51.138253 23057 layer_factory.hpp:77] Creating layer conv4
I0406 13:51:51.138265 23057 net.cpp:84] Creating Layer conv4
I0406 13:51:51.138267 23057 net.cpp:406] conv4 <- conv3
I0406 13:51:51.138274 23057 net.cpp:380] conv4 -> conv4
I0406 13:51:51.147555 23057 net.cpp:122] Setting up conv4
I0406 13:51:51.147576 23057 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0406 13:51:51.147579 23057 net.cpp:137] Memory required for data: 242380544
I0406 13:51:51.147588 23057 layer_factory.hpp:77] Creating layer relu4
I0406 13:51:51.147596 23057 net.cpp:84] Creating Layer relu4
I0406 13:51:51.147600 23057 net.cpp:406] relu4 <- conv4
I0406 13:51:51.147605 23057 net.cpp:367] relu4 -> conv4 (in-place)
I0406 13:51:51.147929 23057 net.cpp:122] Setting up relu4
I0406 13:51:51.147938 23057 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0406 13:51:51.147939 23057 net.cpp:137] Memory required for data: 250687232
I0406 13:51:51.147941 23057 layer_factory.hpp:77] Creating layer conv5
I0406 13:51:51.147951 23057 net.cpp:84] Creating Layer conv5
I0406 13:51:51.147954 23057 net.cpp:406] conv5 <- conv4
I0406 13:51:51.147959 23057 net.cpp:380] conv5 -> conv5
I0406 13:51:51.158699 23057 net.cpp:122] Setting up conv5
I0406 13:51:51.158725 23057 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0406 13:51:51.158731 23057 net.cpp:137] Memory required for data: 256225024
I0406 13:51:51.158748 23057 layer_factory.hpp:77] Creating layer relu5
I0406 13:51:51.158763 23057 net.cpp:84] Creating Layer relu5
I0406 13:51:51.158769 23057 net.cpp:406] relu5 <- conv5
I0406 13:51:51.158804 23057 net.cpp:367] relu5 -> conv5 (in-place)
I0406 13:51:51.159531 23057 net.cpp:122] Setting up relu5
I0406 13:51:51.159544 23057 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0406 13:51:51.159549 23057 net.cpp:137] Memory required for data: 261762816
I0406 13:51:51.159554 23057 layer_factory.hpp:77] Creating layer pool5
I0406 13:51:51.159569 23057 net.cpp:84] Creating Layer pool5
I0406 13:51:51.159574 23057 net.cpp:406] pool5 <- conv5
I0406 13:51:51.159584 23057 net.cpp:380] pool5 -> pool5
I0406 13:51:51.159641 23057 net.cpp:122] Setting up pool5
I0406 13:51:51.159651 23057 net.cpp:129] Top shape: 32 256 6 6 (294912)
I0406 13:51:51.159654 23057 net.cpp:137] Memory required for data: 262942464
I0406 13:51:51.159658 23057 layer_factory.hpp:77] Creating layer fc6
I0406 13:51:51.159670 23057 net.cpp:84] Creating Layer fc6
I0406 13:51:51.159675 23057 net.cpp:406] fc6 <- pool5
I0406 13:51:51.159684 23057 net.cpp:380] fc6 -> fc6
I0406 13:51:51.505182 23057 net.cpp:122] Setting up fc6
I0406 13:51:51.505203 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.505204 23057 net.cpp:137] Memory required for data: 263466752
I0406 13:51:51.505213 23057 layer_factory.hpp:77] Creating layer relu6
I0406 13:51:51.505220 23057 net.cpp:84] Creating Layer relu6
I0406 13:51:51.505225 23057 net.cpp:406] relu6 <- fc6
I0406 13:51:51.505230 23057 net.cpp:367] relu6 -> fc6 (in-place)
I0406 13:51:51.505908 23057 net.cpp:122] Setting up relu6
I0406 13:51:51.505918 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.505919 23057 net.cpp:137] Memory required for data: 263991040
I0406 13:51:51.505923 23057 layer_factory.hpp:77] Creating layer drop6
I0406 13:51:51.505928 23057 net.cpp:84] Creating Layer drop6
I0406 13:51:51.505930 23057 net.cpp:406] drop6 <- fc6
I0406 13:51:51.505934 23057 net.cpp:367] drop6 -> fc6 (in-place)
I0406 13:51:51.505960 23057 net.cpp:122] Setting up drop6
I0406 13:51:51.505964 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.505966 23057 net.cpp:137] Memory required for data: 264515328
I0406 13:51:51.505968 23057 layer_factory.hpp:77] Creating layer fc7
I0406 13:51:51.505975 23057 net.cpp:84] Creating Layer fc7
I0406 13:51:51.505977 23057 net.cpp:406] fc7 <- fc6
I0406 13:51:51.505980 23057 net.cpp:380] fc7 -> fc7
I0406 13:51:51.653981 23057 net.cpp:122] Setting up fc7
I0406 13:51:51.654000 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.654001 23057 net.cpp:137] Memory required for data: 265039616
I0406 13:51:51.654011 23057 layer_factory.hpp:77] Creating layer relu7
I0406 13:51:51.654019 23057 net.cpp:84] Creating Layer relu7
I0406 13:51:51.654022 23057 net.cpp:406] relu7 <- fc7
I0406 13:51:51.654027 23057 net.cpp:367] relu7 -> fc7 (in-place)
I0406 13:51:51.654412 23057 net.cpp:122] Setting up relu7
I0406 13:51:51.654420 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.654422 23057 net.cpp:137] Memory required for data: 265563904
I0406 13:51:51.654424 23057 layer_factory.hpp:77] Creating layer drop7
I0406 13:51:51.654429 23057 net.cpp:84] Creating Layer drop7
I0406 13:51:51.654433 23057 net.cpp:406] drop7 <- fc7
I0406 13:51:51.654438 23057 net.cpp:367] drop7 -> fc7 (in-place)
I0406 13:51:51.654458 23057 net.cpp:122] Setting up drop7
I0406 13:51:51.654466 23057 net.cpp:129] Top shape: 32 4096 (131072)
I0406 13:51:51.654469 23057 net.cpp:137] Memory required for data: 266088192
I0406 13:51:51.654470 23057 layer_factory.hpp:77] Creating layer fc8
I0406 13:51:51.654476 23057 net.cpp:84] Creating Layer fc8
I0406 13:51:51.654479 23057 net.cpp:406] fc8 <- fc7
I0406 13:51:51.654484 23057 net.cpp:380] fc8 -> fc8
I0406 13:51:51.662026 23057 net.cpp:122] Setting up fc8
I0406 13:51:51.662042 23057 net.cpp:129] Top shape: 32 196 (6272)
I0406 13:51:51.662045 23057 net.cpp:137] Memory required for data: 266113280
I0406 13:51:51.662052 23057 layer_factory.hpp:77] Creating layer fc8_fc8_0_split
I0406 13:51:51.662060 23057 net.cpp:84] Creating Layer fc8_fc8_0_split
I0406 13:51:51.662065 23057 net.cpp:406] fc8_fc8_0_split <- fc8
I0406 13:51:51.662087 23057 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0
I0406 13:51:51.662094 23057 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1
I0406 13:51:51.662128 23057 net.cpp:122] Setting up fc8_fc8_0_split
I0406 13:51:51.662132 23057 net.cpp:129] Top shape: 32 196 (6272)
I0406 13:51:51.662135 23057 net.cpp:129] Top shape: 32 196 (6272)
I0406 13:51:51.662137 23057 net.cpp:137] Memory required for data: 266163456
I0406 13:51:51.662138 23057 layer_factory.hpp:77] Creating layer accuracy
I0406 13:51:51.662144 23057 net.cpp:84] Creating Layer accuracy
I0406 13:51:51.662147 23057 net.cpp:406] accuracy <- fc8_fc8_0_split_0
I0406 13:51:51.662149 23057 net.cpp:406] accuracy <- label_val-data_1_split_0
I0406 13:51:51.662154 23057 net.cpp:380] accuracy -> accuracy
I0406 13:51:51.662159 23057 net.cpp:122] Setting up accuracy
I0406 13:51:51.662163 23057 net.cpp:129] Top shape: (1)
I0406 13:51:51.662164 23057 net.cpp:137] Memory required for data: 266163460
I0406 13:51:51.662166 23057 layer_factory.hpp:77] Creating layer loss
I0406 13:51:51.662170 23057 net.cpp:84] Creating Layer loss
I0406 13:51:51.662173 23057 net.cpp:406] loss <- fc8_fc8_0_split_1
I0406 13:51:51.662175 23057 net.cpp:406] loss <- label_val-data_1_split_1
I0406 13:51:51.662178 23057 net.cpp:380] loss -> loss
I0406 13:51:51.662184 23057 layer_factory.hpp:77] Creating layer loss
I0406 13:51:51.662833 23057 net.cpp:122] Setting up loss
I0406 13:51:51.662842 23057 net.cpp:129] Top shape: (1)
I0406 13:51:51.662843 23057 net.cpp:132]     with loss weight 1
I0406 13:51:51.662851 23057 net.cpp:137] Memory required for data: 266163464
I0406 13:51:51.662853 23057 net.cpp:198] loss needs backward computation.
I0406 13:51:51.662858 23057 net.cpp:200] accuracy does not need backward computation.
I0406 13:51:51.662859 23057 net.cpp:198] fc8_fc8_0_split needs backward computation.
I0406 13:51:51.662863 23057 net.cpp:198] fc8 needs backward computation.
I0406 13:51:51.662864 23057 net.cpp:198] drop7 needs backward computation.
I0406 13:51:51.662866 23057 net.cpp:198] relu7 needs backward computation.
I0406 13:51:51.662868 23057 net.cpp:198] fc7 needs backward computation.
I0406 13:51:51.662870 23057 net.cpp:198] drop6 needs backward computation.
I0406 13:51:51.662873 23057 net.cpp:198] relu6 needs backward computation.
I0406 13:51:51.662874 23057 net.cpp:198] fc6 needs backward computation.
I0406 13:51:51.662876 23057 net.cpp:198] pool5 needs backward computation.
I0406 13:51:51.662878 23057 net.cpp:198] relu5 needs backward computation.
I0406 13:51:51.662881 23057 net.cpp:198] conv5 needs backward computation.
I0406 13:51:51.662883 23057 net.cpp:198] relu4 needs backward computation.
I0406 13:51:51.662885 23057 net.cpp:198] conv4 needs backward computation.
I0406 13:51:51.662887 23057 net.cpp:198] relu3 needs backward computation.
I0406 13:51:51.662889 23057 net.cpp:198] conv3 needs backward computation.
I0406 13:51:51.662891 23057 net.cpp:198] pool2 needs backward computation.
I0406 13:51:51.662894 23057 net.cpp:198] norm2 needs backward computation.
I0406 13:51:51.662896 23057 net.cpp:198] relu2 needs backward computation.
I0406 13:51:51.662899 23057 net.cpp:198] conv2 needs backward computation.
I0406 13:51:51.662900 23057 net.cpp:198] pool1 needs backward computation.
I0406 13:51:51.662904 23057 net.cpp:198] norm1 needs backward computation.
I0406 13:51:51.662905 23057 net.cpp:198] relu1 needs backward computation.
I0406 13:51:51.662907 23057 net.cpp:198] conv1 needs backward computation.
I0406 13:51:51.662909 23057 net.cpp:200] label_val-data_1_split does not need backward computation.
I0406 13:51:51.662912 23057 net.cpp:200] val-data does not need backward computation.
I0406 13:51:51.662914 23057 net.cpp:242] This network produces output accuracy
I0406 13:51:51.662916 23057 net.cpp:242] This network produces output loss
I0406 13:51:51.662931 23057 net.cpp:255] Network initialization done.
I0406 13:51:51.662997 23057 solver.cpp:56] Solver scaffolding done.
I0406 13:51:51.663383 23057 caffe.cpp:248] Starting Optimization
I0406 13:51:51.663390 23057 solver.cpp:272] Solving
I0406 13:51:51.663401 23057 solver.cpp:273] Learning Rate Policy: fixed
I0406 13:51:51.665064 23057 solver.cpp:330] Iteration 0, Testing net (#0)
I0406 13:51:51.665074 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:51:51.769924 23057 blocking_queue.cpp:49] Waiting for data
I0406 13:51:55.853785 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:51:55.901361 23057 solver.cpp:397]     Test net output #0: accuracy = 0.00306373
I0406 13:51:55.901396 23057 solver.cpp:397]     Test net output #1: loss = 5.27785 (* 1 = 5.27785 loss)
I0406 13:51:56.057250 23057 solver.cpp:218] Iteration 0 (-8.51873e-36 iter/s, 4.39377s/12 iters), loss = 5.28247
I0406 13:51:56.058801 23057 solver.cpp:237]     Train net output #0: loss = 5.28247 (* 1 = 5.28247 loss)
I0406 13:51:56.058815 23057 sgd_solver.cpp:105] Iteration 0, lr = 0.005
I0406 13:52:00.221863 23057 solver.cpp:218] Iteration 12 (2.88252 iter/s, 4.16302s/12 iters), loss = 5.28697
I0406 13:52:00.221900 23057 solver.cpp:237]     Train net output #0: loss = 5.28697 (* 1 = 5.28697 loss)
I0406 13:52:00.221906 23057 sgd_solver.cpp:105] Iteration 12, lr = 0.005
I0406 13:52:05.627818 23057 solver.cpp:218] Iteration 24 (2.21981 iter/s, 5.40586s/12 iters), loss = 5.27495
I0406 13:52:05.627863 23057 solver.cpp:237]     Train net output #0: loss = 5.27495 (* 1 = 5.27495 loss)
I0406 13:52:05.627869 23057 sgd_solver.cpp:105] Iteration 24, lr = 0.005
I0406 13:52:11.008800 23057 solver.cpp:218] Iteration 36 (2.23012 iter/s, 5.38088s/12 iters), loss = 5.28846
I0406 13:52:11.008848 23057 solver.cpp:237]     Train net output #0: loss = 5.28846 (* 1 = 5.28846 loss)
I0406 13:52:11.008857 23057 sgd_solver.cpp:105] Iteration 36, lr = 0.005
I0406 13:52:16.285089 23057 solver.cpp:218] Iteration 48 (2.27437 iter/s, 5.27619s/12 iters), loss = 5.30759
I0406 13:52:16.285130 23057 solver.cpp:237]     Train net output #0: loss = 5.30759 (* 1 = 5.30759 loss)
I0406 13:52:16.285137 23057 sgd_solver.cpp:105] Iteration 48, lr = 0.005
I0406 13:52:21.544539 23057 solver.cpp:218] Iteration 60 (2.28165 iter/s, 5.25936s/12 iters), loss = 5.27333
I0406 13:52:21.544620 23057 solver.cpp:237]     Train net output #0: loss = 5.27333 (* 1 = 5.27333 loss)
I0406 13:52:21.544626 23057 sgd_solver.cpp:105] Iteration 60, lr = 0.005
I0406 13:52:26.791960 23057 solver.cpp:218] Iteration 72 (2.2869 iter/s, 5.24728s/12 iters), loss = 5.3122
I0406 13:52:26.792019 23057 solver.cpp:237]     Train net output #0: loss = 5.3122 (* 1 = 5.3122 loss)
I0406 13:52:26.792030 23057 sgd_solver.cpp:105] Iteration 72, lr = 0.005
I0406 13:52:31.947937 23057 solver.cpp:218] Iteration 84 (2.32745 iter/s, 5.15587s/12 iters), loss = 5.29336
I0406 13:52:31.947981 23057 solver.cpp:237]     Train net output #0: loss = 5.29336 (* 1 = 5.29336 loss)
I0406 13:52:31.947988 23057 sgd_solver.cpp:105] Iteration 84, lr = 0.005
I0406 13:52:37.229655 23057 solver.cpp:218] Iteration 96 (2.27203 iter/s, 5.28162s/12 iters), loss = 5.29056
I0406 13:52:37.229692 23057 solver.cpp:237]     Train net output #0: loss = 5.29056 (* 1 = 5.29056 loss)
I0406 13:52:37.229697 23057 sgd_solver.cpp:105] Iteration 96, lr = 0.005
I0406 13:52:38.995041 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:52:39.301358 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel
I0406 13:52:42.381744 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate
I0406 13:52:44.709318 23057 solver.cpp:330] Iteration 102, Testing net (#0)
I0406 13:52:44.709344 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:52:49.100764 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:52:49.178618 23057 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0406 13:52:49.178656 23057 solver.cpp:397]     Test net output #1: loss = 5.28636 (* 1 = 5.28636 loss)
I0406 13:52:51.277335 23057 solver.cpp:218] Iteration 108 (0.854243 iter/s, 14.0475s/12 iters), loss = 5.28648
I0406 13:52:51.277381 23057 solver.cpp:237]     Train net output #0: loss = 5.28648 (* 1 = 5.28648 loss)
I0406 13:52:51.277387 23057 sgd_solver.cpp:105] Iteration 108, lr = 0.005
I0406 13:52:56.405025 23057 solver.cpp:218] Iteration 120 (2.34029 iter/s, 5.12758s/12 iters), loss = 5.27105
I0406 13:52:56.405143 23057 solver.cpp:237]     Train net output #0: loss = 5.27105 (* 1 = 5.27105 loss)
I0406 13:52:56.405149 23057 sgd_solver.cpp:105] Iteration 120, lr = 0.005
I0406 13:53:01.759603 23057 solver.cpp:218] Iteration 132 (2.24114 iter/s, 5.35441s/12 iters), loss = 5.26616
I0406 13:53:01.759649 23057 solver.cpp:237]     Train net output #0: loss = 5.26616 (* 1 = 5.26616 loss)
I0406 13:53:01.759655 23057 sgd_solver.cpp:105] Iteration 132, lr = 0.005
I0406 13:53:06.966497 23057 solver.cpp:218] Iteration 144 (2.30468 iter/s, 5.20679s/12 iters), loss = 5.27741
I0406 13:53:06.966540 23057 solver.cpp:237]     Train net output #0: loss = 5.27741 (* 1 = 5.27741 loss)
I0406 13:53:06.966547 23057 sgd_solver.cpp:105] Iteration 144, lr = 0.005
I0406 13:53:12.304245 23057 solver.cpp:218] Iteration 156 (2.24818 iter/s, 5.33765s/12 iters), loss = 5.2882
I0406 13:53:12.304286 23057 solver.cpp:237]     Train net output #0: loss = 5.2882 (* 1 = 5.2882 loss)
I0406 13:53:12.304291 23057 sgd_solver.cpp:105] Iteration 156, lr = 0.005
I0406 13:53:17.849577 23057 solver.cpp:218] Iteration 168 (2.16402 iter/s, 5.54523s/12 iters), loss = 5.2739
I0406 13:53:17.849627 23057 solver.cpp:237]     Train net output #0: loss = 5.2739 (* 1 = 5.2739 loss)
I0406 13:53:17.849635 23057 sgd_solver.cpp:105] Iteration 168, lr = 0.005
I0406 13:53:22.999207 23057 solver.cpp:218] Iteration 180 (2.33031 iter/s, 5.14952s/12 iters), loss = 5.29221
I0406 13:53:22.999272 23057 solver.cpp:237]     Train net output #0: loss = 5.29221 (* 1 = 5.29221 loss)
I0406 13:53:22.999280 23057 sgd_solver.cpp:105] Iteration 180, lr = 0.005
I0406 13:53:28.208371 23057 solver.cpp:218] Iteration 192 (2.30368 iter/s, 5.20905s/12 iters), loss = 5.24362
I0406 13:53:28.208475 23057 solver.cpp:237]     Train net output #0: loss = 5.24362 (* 1 = 5.24362 loss)
I0406 13:53:28.208482 23057 sgd_solver.cpp:105] Iteration 192, lr = 0.005
I0406 13:53:32.506343 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:53:33.215956 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel
I0406 13:53:36.348297 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate
I0406 13:53:38.692373 23057 solver.cpp:330] Iteration 204, Testing net (#0)
I0406 13:53:38.692397 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:53:42.983845 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:53:43.112948 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0067402
I0406 13:53:43.112984 23057 solver.cpp:397]     Test net output #1: loss = 5.25979 (* 1 = 5.25979 loss)
I0406 13:53:43.253309 23057 solver.cpp:218] Iteration 204 (0.797622 iter/s, 15.0447s/12 iters), loss = 5.24558
I0406 13:53:43.253360 23057 solver.cpp:237]     Train net output #0: loss = 5.24558 (* 1 = 5.24558 loss)
I0406 13:53:43.253367 23057 sgd_solver.cpp:105] Iteration 204, lr = 0.005
I0406 13:53:47.787158 23057 solver.cpp:218] Iteration 216 (2.64682 iter/s, 4.53375s/12 iters), loss = 5.24076
I0406 13:53:47.787210 23057 solver.cpp:237]     Train net output #0: loss = 5.24076 (* 1 = 5.24076 loss)
I0406 13:53:47.787218 23057 sgd_solver.cpp:105] Iteration 216, lr = 0.005
I0406 13:53:53.358618 23057 solver.cpp:218] Iteration 228 (2.15388 iter/s, 5.57135s/12 iters), loss = 5.23817
I0406 13:53:53.358664 23057 solver.cpp:237]     Train net output #0: loss = 5.23817 (* 1 = 5.23817 loss)
I0406 13:53:53.358671 23057 sgd_solver.cpp:105] Iteration 228, lr = 0.005
I0406 13:53:58.709556 23057 solver.cpp:218] Iteration 240 (2.24264 iter/s, 5.35083s/12 iters), loss = 5.17827
I0406 13:53:58.709686 23057 solver.cpp:237]     Train net output #0: loss = 5.17827 (* 1 = 5.17827 loss)
I0406 13:53:58.709693 23057 sgd_solver.cpp:105] Iteration 240, lr = 0.005
I0406 13:54:04.185555 23057 solver.cpp:218] Iteration 252 (2.19145 iter/s, 5.47582s/12 iters), loss = 5.23539
I0406 13:54:04.185608 23057 solver.cpp:237]     Train net output #0: loss = 5.23539 (* 1 = 5.23539 loss)
I0406 13:54:04.185616 23057 sgd_solver.cpp:105] Iteration 252, lr = 0.005
I0406 13:54:09.354972 23057 solver.cpp:218] Iteration 264 (2.32139 iter/s, 5.16931s/12 iters), loss = 5.16745
I0406 13:54:09.355016 23057 solver.cpp:237]     Train net output #0: loss = 5.16745 (* 1 = 5.16745 loss)
I0406 13:54:09.355024 23057 sgd_solver.cpp:105] Iteration 264, lr = 0.005
I0406 13:54:14.640758 23057 solver.cpp:218] Iteration 276 (2.27028 iter/s, 5.28568s/12 iters), loss = 5.14995
I0406 13:54:14.640812 23057 solver.cpp:237]     Train net output #0: loss = 5.14995 (* 1 = 5.14995 loss)
I0406 13:54:14.640822 23057 sgd_solver.cpp:105] Iteration 276, lr = 0.005
I0406 13:54:20.061926 23057 solver.cpp:218] Iteration 288 (2.21359 iter/s, 5.42106s/12 iters), loss = 5.17283
I0406 13:54:20.061973 23057 solver.cpp:237]     Train net output #0: loss = 5.17283 (* 1 = 5.17283 loss)
I0406 13:54:20.061980 23057 sgd_solver.cpp:105] Iteration 288, lr = 0.005
I0406 13:54:25.220806 23057 solver.cpp:218] Iteration 300 (2.32613 iter/s, 5.15878s/12 iters), loss = 5.24152
I0406 13:54:25.220854 23057 solver.cpp:237]     Train net output #0: loss = 5.24152 (* 1 = 5.24152 loss)
I0406 13:54:25.220860 23057 sgd_solver.cpp:105] Iteration 300, lr = 0.005
I0406 13:54:26.239033 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:54:27.527395 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel
I0406 13:54:30.489410 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate
I0406 13:54:32.793016 23057 solver.cpp:330] Iteration 306, Testing net (#0)
I0406 13:54:32.793037 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:54:37.293889 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:54:37.450770 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0104167
I0406 13:54:37.450803 23057 solver.cpp:397]     Test net output #1: loss = 5.1618 (* 1 = 5.1618 loss)
I0406 13:54:39.440737 23057 solver.cpp:218] Iteration 312 (0.843896 iter/s, 14.2198s/12 iters), loss = 5.15951
I0406 13:54:39.440783 23057 solver.cpp:237]     Train net output #0: loss = 5.15951 (* 1 = 5.15951 loss)
I0406 13:54:39.440788 23057 sgd_solver.cpp:105] Iteration 312, lr = 0.005
I0406 13:54:44.741572 23057 solver.cpp:218] Iteration 324 (2.26384 iter/s, 5.30073s/12 iters), loss = 5.25745
I0406 13:54:44.741633 23057 solver.cpp:237]     Train net output #0: loss = 5.25745 (* 1 = 5.25745 loss)
I0406 13:54:44.741642 23057 sgd_solver.cpp:105] Iteration 324, lr = 0.005
I0406 13:54:50.051563 23057 solver.cpp:218] Iteration 336 (2.25994 iter/s, 5.30987s/12 iters), loss = 5.16706
I0406 13:54:50.051618 23057 solver.cpp:237]     Train net output #0: loss = 5.16706 (* 1 = 5.16706 loss)
I0406 13:54:50.051628 23057 sgd_solver.cpp:105] Iteration 336, lr = 0.005
I0406 13:54:55.245596 23057 solver.cpp:218] Iteration 348 (2.31039 iter/s, 5.19393s/12 iters), loss = 5.11073
I0406 13:54:55.245635 23057 solver.cpp:237]     Train net output #0: loss = 5.11073 (* 1 = 5.11073 loss)
I0406 13:54:55.245641 23057 sgd_solver.cpp:105] Iteration 348, lr = 0.005
I0406 13:55:00.621722 23057 solver.cpp:218] Iteration 360 (2.23213 iter/s, 5.37603s/12 iters), loss = 5.17961
I0406 13:55:00.622014 23057 solver.cpp:237]     Train net output #0: loss = 5.17961 (* 1 = 5.17961 loss)
I0406 13:55:00.622021 23057 sgd_solver.cpp:105] Iteration 360, lr = 0.005
I0406 13:55:06.119263 23057 solver.cpp:218] Iteration 372 (2.18293 iter/s, 5.4972s/12 iters), loss = 5.14532
I0406 13:55:06.119321 23057 solver.cpp:237]     Train net output #0: loss = 5.14532 (* 1 = 5.14532 loss)
I0406 13:55:06.119329 23057 sgd_solver.cpp:105] Iteration 372, lr = 0.005
I0406 13:55:11.697010 23057 solver.cpp:218] Iteration 384 (2.15145 iter/s, 5.57763s/12 iters), loss = 5.21631
I0406 13:55:11.697053 23057 solver.cpp:237]     Train net output #0: loss = 5.21631 (* 1 = 5.21631 loss)
I0406 13:55:11.697059 23057 sgd_solver.cpp:105] Iteration 384, lr = 0.005
I0406 13:55:17.134433 23057 solver.cpp:218] Iteration 396 (2.20697 iter/s, 5.43732s/12 iters), loss = 5.14937
I0406 13:55:17.134475 23057 solver.cpp:237]     Train net output #0: loss = 5.14937 (* 1 = 5.14937 loss)
I0406 13:55:17.134481 23057 sgd_solver.cpp:105] Iteration 396, lr = 0.005
I0406 13:55:20.426765 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:55:21.950333 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel
I0406 13:55:25.087574 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate
I0406 13:55:28.449717 23057 solver.cpp:330] Iteration 408, Testing net (#0)
I0406 13:55:28.449745 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:55:32.758553 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:55:33.007144 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0110294
I0406 13:55:33.007177 23057 solver.cpp:397]     Test net output #1: loss = 5.12789 (* 1 = 5.12789 loss)
I0406 13:55:33.147867 23057 solver.cpp:218] Iteration 408 (0.749379 iter/s, 16.0133s/12 iters), loss = 5.13249
I0406 13:55:33.147930 23057 solver.cpp:237]     Train net output #0: loss = 5.13249 (* 1 = 5.13249 loss)
I0406 13:55:33.147938 23057 sgd_solver.cpp:105] Iteration 408, lr = 0.005
I0406 13:55:37.580523 23057 solver.cpp:218] Iteration 420 (2.70725 iter/s, 4.43254s/12 iters), loss = 5.11791
I0406 13:55:37.580587 23057 solver.cpp:237]     Train net output #0: loss = 5.11791 (* 1 = 5.11791 loss)
I0406 13:55:37.580596 23057 sgd_solver.cpp:105] Iteration 420, lr = 0.005
I0406 13:55:42.980630 23057 solver.cpp:218] Iteration 432 (2.22223 iter/s, 5.39999s/12 iters), loss = 5.07629
I0406 13:55:42.980676 23057 solver.cpp:237]     Train net output #0: loss = 5.07629 (* 1 = 5.07629 loss)
I0406 13:55:42.980681 23057 sgd_solver.cpp:105] Iteration 432, lr = 0.005
I0406 13:55:48.375478 23057 solver.cpp:218] Iteration 444 (2.22439 iter/s, 5.39474s/12 iters), loss = 5.08007
I0406 13:55:48.375530 23057 solver.cpp:237]     Train net output #0: loss = 5.08007 (* 1 = 5.08007 loss)
I0406 13:55:48.375537 23057 sgd_solver.cpp:105] Iteration 444, lr = 0.005
I0406 13:55:53.602250 23057 solver.cpp:218] Iteration 456 (2.29592 iter/s, 5.22666s/12 iters), loss = 5.1689
I0406 13:55:53.602313 23057 solver.cpp:237]     Train net output #0: loss = 5.1689 (* 1 = 5.1689 loss)
I0406 13:55:53.602321 23057 sgd_solver.cpp:105] Iteration 456, lr = 0.005
I0406 13:55:59.065997 23057 solver.cpp:218] Iteration 468 (2.19634 iter/s, 5.46363s/12 iters), loss = 5.10212
I0406 13:55:59.066053 23057 solver.cpp:237]     Train net output #0: loss = 5.10212 (* 1 = 5.10212 loss)
I0406 13:55:59.066061 23057 sgd_solver.cpp:105] Iteration 468, lr = 0.005
I0406 13:56:04.478720 23057 solver.cpp:218] Iteration 480 (2.21704 iter/s, 5.41262s/12 iters), loss = 5.05703
I0406 13:56:04.478806 23057 solver.cpp:237]     Train net output #0: loss = 5.05703 (* 1 = 5.05703 loss)
I0406 13:56:04.478812 23057 sgd_solver.cpp:105] Iteration 480, lr = 0.005
I0406 13:56:10.003414 23057 solver.cpp:218] Iteration 492 (2.17212 iter/s, 5.52455s/12 iters), loss = 5.09798
I0406 13:56:10.003464 23057 solver.cpp:237]     Train net output #0: loss = 5.09798 (* 1 = 5.09798 loss)
I0406 13:56:10.003473 23057 sgd_solver.cpp:105] Iteration 492, lr = 0.005
I0406 13:56:15.254084 23057 solver.cpp:218] Iteration 504 (2.28547 iter/s, 5.25057s/12 iters), loss = 5.06192
I0406 13:56:15.254122 23057 solver.cpp:237]     Train net output #0: loss = 5.06192 (* 1 = 5.06192 loss)
I0406 13:56:15.254127 23057 sgd_solver.cpp:105] Iteration 504, lr = 0.005
I0406 13:56:15.484360 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:56:17.262809 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel
I0406 13:56:21.989414 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate
I0406 13:56:24.313133 23057 solver.cpp:330] Iteration 510, Testing net (#0)
I0406 13:56:24.313153 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:56:28.641719 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:56:28.881891 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0171569
I0406 13:56:28.881925 23057 solver.cpp:397]     Test net output #1: loss = 5.08036 (* 1 = 5.08036 loss)
I0406 13:56:30.899859 23057 solver.cpp:218] Iteration 516 (0.766989 iter/s, 15.6456s/12 iters), loss = 5.08369
I0406 13:56:30.899909 23057 solver.cpp:237]     Train net output #0: loss = 5.08369 (* 1 = 5.08369 loss)
I0406 13:56:30.899916 23057 sgd_solver.cpp:105] Iteration 516, lr = 0.005
I0406 13:56:36.134727 23057 solver.cpp:218] Iteration 528 (2.29236 iter/s, 5.23477s/12 iters), loss = 5.18669
I0406 13:56:36.134845 23057 solver.cpp:237]     Train net output #0: loss = 5.18669 (* 1 = 5.18669 loss)
I0406 13:56:36.134852 23057 sgd_solver.cpp:105] Iteration 528, lr = 0.005
I0406 13:56:41.467839 23057 solver.cpp:218] Iteration 540 (2.25017 iter/s, 5.33293s/12 iters), loss = 5.03513
I0406 13:56:41.467898 23057 solver.cpp:237]     Train net output #0: loss = 5.03513 (* 1 = 5.03513 loss)
I0406 13:56:41.467907 23057 sgd_solver.cpp:105] Iteration 540, lr = 0.005
I0406 13:56:46.571336 23057 solver.cpp:218] Iteration 552 (2.35138 iter/s, 5.10338s/12 iters), loss = 5.08915
I0406 13:56:46.571378 23057 solver.cpp:237]     Train net output #0: loss = 5.08915 (* 1 = 5.08915 loss)
I0406 13:56:46.571383 23057 sgd_solver.cpp:105] Iteration 552, lr = 0.005
I0406 13:56:51.976027 23057 solver.cpp:218] Iteration 564 (2.22033 iter/s, 5.40459s/12 iters), loss = 5.04001
I0406 13:56:51.976075 23057 solver.cpp:237]     Train net output #0: loss = 5.04001 (* 1 = 5.04001 loss)
I0406 13:56:51.976083 23057 sgd_solver.cpp:105] Iteration 564, lr = 0.005
I0406 13:56:57.103580 23057 solver.cpp:218] Iteration 576 (2.34034 iter/s, 5.12745s/12 iters), loss = 4.96357
I0406 13:56:57.103617 23057 solver.cpp:237]     Train net output #0: loss = 4.96357 (* 1 = 4.96357 loss)
I0406 13:56:57.103623 23057 sgd_solver.cpp:105] Iteration 576, lr = 0.005
I0406 13:57:02.431309 23057 solver.cpp:218] Iteration 588 (2.25241 iter/s, 5.32764s/12 iters), loss = 5.05372
I0406 13:57:02.431350 23057 solver.cpp:237]     Train net output #0: loss = 5.05372 (* 1 = 5.05372 loss)
I0406 13:57:02.431355 23057 sgd_solver.cpp:105] Iteration 588, lr = 0.005
I0406 13:57:07.766580 23057 solver.cpp:218] Iteration 600 (2.24922 iter/s, 5.33517s/12 iters), loss = 5.06518
I0406 13:57:07.766691 23057 solver.cpp:237]     Train net output #0: loss = 5.06518 (* 1 = 5.06518 loss)
I0406 13:57:07.766698 23057 sgd_solver.cpp:105] Iteration 600, lr = 0.005
I0406 13:57:10.348444 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:57:12.780153 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel
I0406 13:57:15.864734 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate
I0406 13:57:18.186931 23057 solver.cpp:330] Iteration 612, Testing net (#0)
I0406 13:57:18.186954 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:57:22.501075 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:57:22.834012 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0245098
I0406 13:57:22.834049 23057 solver.cpp:397]     Test net output #1: loss = 5.04202 (* 1 = 5.04202 loss)
I0406 13:57:22.974709 23057 solver.cpp:218] Iteration 612 (0.789064 iter/s, 15.2079s/12 iters), loss = 5.01982
I0406 13:57:22.974767 23057 solver.cpp:237]     Train net output #0: loss = 5.01982 (* 1 = 5.01982 loss)
I0406 13:57:22.974776 23057 sgd_solver.cpp:105] Iteration 612, lr = 0.005
I0406 13:57:27.524101 23057 solver.cpp:218] Iteration 624 (2.63778 iter/s, 4.54928s/12 iters), loss = 5.01705
I0406 13:57:27.524152 23057 solver.cpp:237]     Train net output #0: loss = 5.01705 (* 1 = 5.01705 loss)
I0406 13:57:27.524161 23057 sgd_solver.cpp:105] Iteration 624, lr = 0.005
I0406 13:57:32.850201 23057 solver.cpp:218] Iteration 636 (2.2531 iter/s, 5.326s/12 iters), loss = 5.04373
I0406 13:57:32.850241 23057 solver.cpp:237]     Train net output #0: loss = 5.04373 (* 1 = 5.04373 loss)
I0406 13:57:32.850247 23057 sgd_solver.cpp:105] Iteration 636, lr = 0.005
I0406 13:57:38.200574 23057 solver.cpp:218] Iteration 648 (2.24288 iter/s, 5.35028s/12 iters), loss = 4.95534
I0406 13:57:38.200736 23057 solver.cpp:237]     Train net output #0: loss = 4.95534 (* 1 = 4.95534 loss)
I0406 13:57:38.200744 23057 sgd_solver.cpp:105] Iteration 648, lr = 0.005
I0406 13:57:43.594156 23057 solver.cpp:218] Iteration 660 (2.22496 iter/s, 5.39337s/12 iters), loss = 4.97252
I0406 13:57:43.594208 23057 solver.cpp:237]     Train net output #0: loss = 4.97252 (* 1 = 4.97252 loss)
I0406 13:57:43.594218 23057 sgd_solver.cpp:105] Iteration 660, lr = 0.005
I0406 13:57:49.049083 23057 solver.cpp:218] Iteration 672 (2.19989 iter/s, 5.45482s/12 iters), loss = 4.99621
I0406 13:57:49.049124 23057 solver.cpp:237]     Train net output #0: loss = 4.99621 (* 1 = 4.99621 loss)
I0406 13:57:49.049129 23057 sgd_solver.cpp:105] Iteration 672, lr = 0.005
I0406 13:57:54.459712 23057 solver.cpp:218] Iteration 684 (2.2179 iter/s, 5.41053s/12 iters), loss = 4.94276
I0406 13:57:54.459751 23057 solver.cpp:237]     Train net output #0: loss = 4.94276 (* 1 = 4.94276 loss)
I0406 13:57:54.459758 23057 sgd_solver.cpp:105] Iteration 684, lr = 0.005
I0406 13:57:55.363554 23057 blocking_queue.cpp:49] Waiting for data
I0406 13:57:59.754465 23057 solver.cpp:218] Iteration 696 (2.26643 iter/s, 5.29466s/12 iters), loss = 4.94622
I0406 13:57:59.754504 23057 solver.cpp:237]     Train net output #0: loss = 4.94622 (* 1 = 4.94622 loss)
I0406 13:57:59.754510 23057 sgd_solver.cpp:105] Iteration 696, lr = 0.005
I0406 13:58:04.622293 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:58:05.036391 23057 solver.cpp:218] Iteration 708 (2.27194 iter/s, 5.28183s/12 iters), loss = 5.02376
I0406 13:58:05.036428 23057 solver.cpp:237]     Train net output #0: loss = 5.02376 (* 1 = 5.02376 loss)
I0406 13:58:05.036434 23057 sgd_solver.cpp:105] Iteration 708, lr = 0.005
I0406 13:58:07.291110 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel
I0406 13:58:10.675235 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate
I0406 13:58:13.073688 23057 solver.cpp:330] Iteration 714, Testing net (#0)
I0406 13:58:13.073712 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:58:17.205730 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:58:17.518996 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0300245
I0406 13:58:17.519037 23057 solver.cpp:397]     Test net output #1: loss = 4.98438 (* 1 = 4.98438 loss)
I0406 13:58:19.523622 23057 solver.cpp:218] Iteration 720 (0.828325 iter/s, 14.4871s/12 iters), loss = 5.03049
I0406 13:58:19.523674 23057 solver.cpp:237]     Train net output #0: loss = 5.03049 (* 1 = 5.03049 loss)
I0406 13:58:19.523680 23057 sgd_solver.cpp:105] Iteration 720, lr = 0.005
I0406 13:58:24.804234 23057 solver.cpp:218] Iteration 732 (2.27251 iter/s, 5.28051s/12 iters), loss = 4.89275
I0406 13:58:24.804288 23057 solver.cpp:237]     Train net output #0: loss = 4.89275 (* 1 = 4.89275 loss)
I0406 13:58:24.804298 23057 sgd_solver.cpp:105] Iteration 732, lr = 0.005
I0406 13:58:30.309206 23057 solver.cpp:218] Iteration 744 (2.17989 iter/s, 5.50486s/12 iters), loss = 4.94464
I0406 13:58:30.309247 23057 solver.cpp:237]     Train net output #0: loss = 4.94464 (* 1 = 4.94464 loss)
I0406 13:58:30.309253 23057 sgd_solver.cpp:105] Iteration 744, lr = 0.005
I0406 13:58:35.769476 23057 solver.cpp:218] Iteration 756 (2.19773 iter/s, 5.46017s/12 iters), loss = 4.8223
I0406 13:58:35.769523 23057 solver.cpp:237]     Train net output #0: loss = 4.8223 (* 1 = 4.8223 loss)
I0406 13:58:35.769529 23057 sgd_solver.cpp:105] Iteration 756, lr = 0.005
I0406 13:58:41.164598 23057 solver.cpp:218] Iteration 768 (2.22427 iter/s, 5.39502s/12 iters), loss = 5.01041
I0406 13:58:41.164727 23057 solver.cpp:237]     Train net output #0: loss = 5.01041 (* 1 = 5.01041 loss)
I0406 13:58:41.164734 23057 sgd_solver.cpp:105] Iteration 768, lr = 0.005
I0406 13:58:46.766677 23057 solver.cpp:218] Iteration 780 (2.14213 iter/s, 5.60189s/12 iters), loss = 4.92019
I0406 13:58:46.766722 23057 solver.cpp:237]     Train net output #0: loss = 4.92019 (* 1 = 4.92019 loss)
I0406 13:58:46.766728 23057 sgd_solver.cpp:105] Iteration 780, lr = 0.005
I0406 13:58:52.155540 23057 solver.cpp:218] Iteration 792 (2.22686 iter/s, 5.38876s/12 iters), loss = 5.024
I0406 13:58:52.155576 23057 solver.cpp:237]     Train net output #0: loss = 5.024 (* 1 = 5.024 loss)
I0406 13:58:52.155582 23057 sgd_solver.cpp:105] Iteration 792, lr = 0.005
I0406 13:58:57.558398 23057 solver.cpp:218] Iteration 804 (2.22109 iter/s, 5.40276s/12 iters), loss = 4.91367
I0406 13:58:57.558451 23057 solver.cpp:237]     Train net output #0: loss = 4.91367 (* 1 = 4.91367 loss)
I0406 13:58:57.558459 23057 sgd_solver.cpp:105] Iteration 804, lr = 0.005
I0406 13:58:59.438732 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:59:02.466653 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel
I0406 13:59:05.614557 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate
I0406 13:59:07.943717 23057 solver.cpp:330] Iteration 816, Testing net (#0)
I0406 13:59:07.943737 23057 net.cpp:676] Ignoring source layer train-data
I0406 13:59:12.087708 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:59:12.464226 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0373775
I0406 13:59:12.464253 23057 solver.cpp:397]     Test net output #1: loss = 4.93501 (* 1 = 4.93501 loss)
I0406 13:59:12.604557 23057 solver.cpp:218] Iteration 816 (0.797555 iter/s, 15.046s/12 iters), loss = 4.94203
I0406 13:59:12.604598 23057 solver.cpp:237]     Train net output #0: loss = 4.94203 (* 1 = 4.94203 loss)
I0406 13:59:12.604602 23057 sgd_solver.cpp:105] Iteration 816, lr = 0.005
I0406 13:59:17.193802 23057 solver.cpp:218] Iteration 828 (2.61486 iter/s, 4.58916s/12 iters), loss = 4.86771
I0406 13:59:17.193840 23057 solver.cpp:237]     Train net output #0: loss = 4.86771 (* 1 = 4.86771 loss)
I0406 13:59:17.193846 23057 sgd_solver.cpp:105] Iteration 828, lr = 0.005
I0406 13:59:22.566571 23057 solver.cpp:218] Iteration 840 (2.23353 iter/s, 5.37267s/12 iters), loss = 4.79574
I0406 13:59:22.566632 23057 solver.cpp:237]     Train net output #0: loss = 4.79574 (* 1 = 4.79574 loss)
I0406 13:59:22.566640 23057 sgd_solver.cpp:105] Iteration 840, lr = 0.005
I0406 13:59:27.775399 23057 solver.cpp:218] Iteration 852 (2.30383 iter/s, 5.20872s/12 iters), loss = 4.85746
I0406 13:59:27.775439 23057 solver.cpp:237]     Train net output #0: loss = 4.85746 (* 1 = 4.85746 loss)
I0406 13:59:27.775444 23057 sgd_solver.cpp:105] Iteration 852, lr = 0.005
I0406 13:59:33.180310 23057 solver.cpp:218] Iteration 864 (2.22024 iter/s, 5.40481s/12 iters), loss = 4.87767
I0406 13:59:33.180356 23057 solver.cpp:237]     Train net output #0: loss = 4.87767 (* 1 = 4.87767 loss)
I0406 13:59:33.180362 23057 sgd_solver.cpp:105] Iteration 864, lr = 0.005
I0406 13:59:38.583714 23057 solver.cpp:218] Iteration 876 (2.22086 iter/s, 5.4033s/12 iters), loss = 4.85057
I0406 13:59:38.583765 23057 solver.cpp:237]     Train net output #0: loss = 4.85057 (* 1 = 4.85057 loss)
I0406 13:59:38.583775 23057 sgd_solver.cpp:105] Iteration 876, lr = 0.005
I0406 13:59:44.162343 23057 solver.cpp:218] Iteration 888 (2.15111 iter/s, 5.57852s/12 iters), loss = 4.84689
I0406 13:59:44.162452 23057 solver.cpp:237]     Train net output #0: loss = 4.84689 (* 1 = 4.84689 loss)
I0406 13:59:44.162461 23057 sgd_solver.cpp:105] Iteration 888, lr = 0.005
I0406 13:59:49.384686 23057 solver.cpp:218] Iteration 900 (2.29789 iter/s, 5.22218s/12 iters), loss = 4.78219
I0406 13:59:49.384735 23057 solver.cpp:237]     Train net output #0: loss = 4.78219 (* 1 = 4.78219 loss)
I0406 13:59:49.384743 23057 sgd_solver.cpp:105] Iteration 900, lr = 0.005
I0406 13:59:53.522805 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 13:59:54.852938 23057 solver.cpp:218] Iteration 912 (2.19453 iter/s, 5.46814s/12 iters), loss = 4.87394
I0406 13:59:54.852994 23057 solver.cpp:237]     Train net output #0: loss = 4.87394 (* 1 = 4.87394 loss)
I0406 13:59:54.853003 23057 sgd_solver.cpp:105] Iteration 912, lr = 0.005
I0406 13:59:56.956529 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel
I0406 13:59:59.972731 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate
I0406 14:00:02.274992 23057 solver.cpp:330] Iteration 918, Testing net (#0)
I0406 14:00:02.275012 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:00:06.406797 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:00:06.822199 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0545343
I0406 14:00:06.822234 23057 solver.cpp:397]     Test net output #1: loss = 4.84229 (* 1 = 4.84229 loss)
I0406 14:00:08.672410 23057 solver.cpp:218] Iteration 924 (0.868351 iter/s, 13.8193s/12 iters), loss = 4.81478
I0406 14:00:08.672461 23057 solver.cpp:237]     Train net output #0: loss = 4.81478 (* 1 = 4.81478 loss)
I0406 14:00:08.672468 23057 sgd_solver.cpp:105] Iteration 924, lr = 0.005
I0406 14:00:13.797094 23057 solver.cpp:218] Iteration 936 (2.34165 iter/s, 5.12458s/12 iters), loss = 4.86367
I0406 14:00:13.797133 23057 solver.cpp:237]     Train net output #0: loss = 4.86367 (* 1 = 4.86367 loss)
I0406 14:00:13.797139 23057 sgd_solver.cpp:105] Iteration 936, lr = 0.005
I0406 14:00:19.122738 23057 solver.cpp:218] Iteration 948 (2.25329 iter/s, 5.32555s/12 iters), loss = 4.72567
I0406 14:00:19.122891 23057 solver.cpp:237]     Train net output #0: loss = 4.72567 (* 1 = 4.72567 loss)
I0406 14:00:19.122900 23057 sgd_solver.cpp:105] Iteration 948, lr = 0.005
I0406 14:00:24.669330 23057 solver.cpp:218] Iteration 960 (2.16357 iter/s, 5.54638s/12 iters), loss = 4.85778
I0406 14:00:24.669384 23057 solver.cpp:237]     Train net output #0: loss = 4.85778 (* 1 = 4.85778 loss)
I0406 14:00:24.669392 23057 sgd_solver.cpp:105] Iteration 960, lr = 0.005
I0406 14:00:30.064524 23057 solver.cpp:218] Iteration 972 (2.22424 iter/s, 5.39509s/12 iters), loss = 4.64043
I0406 14:00:30.064566 23057 solver.cpp:237]     Train net output #0: loss = 4.64043 (* 1 = 4.64043 loss)
I0406 14:00:30.064571 23057 sgd_solver.cpp:105] Iteration 972, lr = 0.005
I0406 14:00:35.645079 23057 solver.cpp:218] Iteration 984 (2.15036 iter/s, 5.58045s/12 iters), loss = 4.78499
I0406 14:00:35.645120 23057 solver.cpp:237]     Train net output #0: loss = 4.78499 (* 1 = 4.78499 loss)
I0406 14:00:35.645126 23057 sgd_solver.cpp:105] Iteration 984, lr = 0.005
I0406 14:00:41.045197 23057 solver.cpp:218] Iteration 996 (2.22221 iter/s, 5.40002s/12 iters), loss = 4.71432
I0406 14:00:41.045248 23057 solver.cpp:237]     Train net output #0: loss = 4.71432 (* 1 = 4.71432 loss)
I0406 14:00:41.045258 23057 sgd_solver.cpp:105] Iteration 996, lr = 0.005
I0406 14:00:46.339434 23057 solver.cpp:218] Iteration 1008 (2.26666 iter/s, 5.29413s/12 iters), loss = 4.71875
I0406 14:00:46.339483 23057 solver.cpp:237]     Train net output #0: loss = 4.71875 (* 1 = 4.71875 loss)
I0406 14:00:46.339490 23057 sgd_solver.cpp:105] Iteration 1008, lr = 0.005
I0406 14:00:47.501577 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:00:51.142514 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel
I0406 14:00:54.204527 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate
I0406 14:00:56.512199 23057 solver.cpp:330] Iteration 1020, Testing net (#0)
I0406 14:00:56.512220 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:01:00.594486 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:01:01.041415 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0582108
I0406 14:01:01.041451 23057 solver.cpp:397]     Test net output #1: loss = 4.75656 (* 1 = 4.75656 loss)
I0406 14:01:01.182160 23057 solver.cpp:218] Iteration 1020 (0.808486 iter/s, 14.8426s/12 iters), loss = 4.76229
I0406 14:01:01.182212 23057 solver.cpp:237]     Train net output #0: loss = 4.76229 (* 1 = 4.76229 loss)
I0406 14:01:01.182219 23057 sgd_solver.cpp:105] Iteration 1020, lr = 0.005
I0406 14:01:05.761957 23057 solver.cpp:218] Iteration 1032 (2.62026 iter/s, 4.57969s/12 iters), loss = 5.02156
I0406 14:01:05.762010 23057 solver.cpp:237]     Train net output #0: loss = 5.02156 (* 1 = 5.02156 loss)
I0406 14:01:05.762018 23057 sgd_solver.cpp:105] Iteration 1032, lr = 0.005
I0406 14:01:11.261276 23057 solver.cpp:218] Iteration 1044 (2.18213 iter/s, 5.49921s/12 iters), loss = 4.72423
I0406 14:01:11.261322 23057 solver.cpp:237]     Train net output #0: loss = 4.72423 (* 1 = 4.72423 loss)
I0406 14:01:11.261328 23057 sgd_solver.cpp:105] Iteration 1044, lr = 0.005
I0406 14:01:16.519773 23057 solver.cpp:218] Iteration 1056 (2.28206 iter/s, 5.2584s/12 iters), loss = 4.75628
I0406 14:01:16.519810 23057 solver.cpp:237]     Train net output #0: loss = 4.75628 (* 1 = 4.75628 loss)
I0406 14:01:16.519816 23057 sgd_solver.cpp:105] Iteration 1056, lr = 0.005
I0406 14:01:21.792299 23057 solver.cpp:218] Iteration 1068 (2.27599 iter/s, 5.27243s/12 iters), loss = 4.54986
I0406 14:01:21.792464 23057 solver.cpp:237]     Train net output #0: loss = 4.54986 (* 1 = 4.54986 loss)
I0406 14:01:21.792471 23057 sgd_solver.cpp:105] Iteration 1068, lr = 0.005
I0406 14:01:27.221695 23057 solver.cpp:218] Iteration 1080 (2.21028 iter/s, 5.42918s/12 iters), loss = 4.58022
I0406 14:01:27.221747 23057 solver.cpp:237]     Train net output #0: loss = 4.58022 (* 1 = 4.58022 loss)
I0406 14:01:27.221755 23057 sgd_solver.cpp:105] Iteration 1080, lr = 0.005
I0406 14:01:32.682585 23057 solver.cpp:218] Iteration 1092 (2.19749 iter/s, 5.46078s/12 iters), loss = 4.69124
I0406 14:01:32.682621 23057 solver.cpp:237]     Train net output #0: loss = 4.69124 (* 1 = 4.69124 loss)
I0406 14:01:32.682626 23057 sgd_solver.cpp:105] Iteration 1092, lr = 0.005
I0406 14:01:38.187789 23057 solver.cpp:218] Iteration 1104 (2.17979 iter/s, 5.50511s/12 iters), loss = 4.68415
I0406 14:01:38.187837 23057 solver.cpp:237]     Train net output #0: loss = 4.68415 (* 1 = 4.68415 loss)
I0406 14:01:38.187842 23057 sgd_solver.cpp:105] Iteration 1104, lr = 0.005
I0406 14:01:41.577100 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:01:43.619524 23057 solver.cpp:218] Iteration 1116 (2.20928 iter/s, 5.43163s/12 iters), loss = 4.55389
I0406 14:01:43.619563 23057 solver.cpp:237]     Train net output #0: loss = 4.55389 (* 1 = 4.55389 loss)
I0406 14:01:43.619568 23057 sgd_solver.cpp:105] Iteration 1116, lr = 0.005
I0406 14:01:45.717559 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel
I0406 14:01:49.563778 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate
I0406 14:01:51.870664 23057 solver.cpp:330] Iteration 1122, Testing net (#0)
I0406 14:01:51.870723 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:01:55.988037 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:01:56.462502 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0637255
I0406 14:01:56.462538 23057 solver.cpp:397]     Test net output #1: loss = 4.66434 (* 1 = 4.66434 loss)
I0406 14:01:58.324334 23057 solver.cpp:218] Iteration 1128 (0.816069 iter/s, 14.7046s/12 iters), loss = 4.6255
I0406 14:01:58.324391 23057 solver.cpp:237]     Train net output #0: loss = 4.6255 (* 1 = 4.6255 loss)
I0406 14:01:58.324399 23057 sgd_solver.cpp:105] Iteration 1128, lr = 0.005
I0406 14:02:03.917445 23057 solver.cpp:218] Iteration 1140 (2.14554 iter/s, 5.593s/12 iters), loss = 4.4205
I0406 14:02:03.917488 23057 solver.cpp:237]     Train net output #0: loss = 4.4205 (* 1 = 4.4205 loss)
I0406 14:02:03.917495 23057 sgd_solver.cpp:105] Iteration 1140, lr = 0.005
I0406 14:02:09.012677 23057 solver.cpp:218] Iteration 1152 (2.35519 iter/s, 5.09514s/12 iters), loss = 4.63471
I0406 14:02:09.012722 23057 solver.cpp:237]     Train net output #0: loss = 4.63471 (* 1 = 4.63471 loss)
I0406 14:02:09.012729 23057 sgd_solver.cpp:105] Iteration 1152, lr = 0.005
I0406 14:02:14.236263 23057 solver.cpp:218] Iteration 1164 (2.29732 iter/s, 5.22349s/12 iters), loss = 4.8191
I0406 14:02:14.236304 23057 solver.cpp:237]     Train net output #0: loss = 4.8191 (* 1 = 4.8191 loss)
I0406 14:02:14.236310 23057 sgd_solver.cpp:105] Iteration 1164, lr = 0.005
I0406 14:02:19.601487 23057 solver.cpp:218] Iteration 1176 (2.23667 iter/s, 5.36512s/12 iters), loss = 4.55722
I0406 14:02:19.601538 23057 solver.cpp:237]     Train net output #0: loss = 4.55722 (* 1 = 4.55722 loss)
I0406 14:02:19.601547 23057 sgd_solver.cpp:105] Iteration 1176, lr = 0.005
I0406 14:02:24.973975 23057 solver.cpp:218] Iteration 1188 (2.23365 iter/s, 5.37238s/12 iters), loss = 4.54555
I0406 14:02:24.974202 23057 solver.cpp:237]     Train net output #0: loss = 4.54555 (* 1 = 4.54555 loss)
I0406 14:02:24.974211 23057 sgd_solver.cpp:105] Iteration 1188, lr = 0.005
I0406 14:02:30.336419 23057 solver.cpp:218] Iteration 1200 (2.2379 iter/s, 5.36216s/12 iters), loss = 4.59281
I0406 14:02:30.336477 23057 solver.cpp:237]     Train net output #0: loss = 4.59281 (* 1 = 4.59281 loss)
I0406 14:02:30.336484 23057 sgd_solver.cpp:105] Iteration 1200, lr = 0.005
I0406 14:02:35.743351 23057 solver.cpp:218] Iteration 1212 (2.21942 iter/s, 5.40682s/12 iters), loss = 4.51892
I0406 14:02:35.743403 23057 solver.cpp:237]     Train net output #0: loss = 4.51892 (* 1 = 4.51892 loss)
I0406 14:02:35.743412 23057 sgd_solver.cpp:105] Iteration 1212, lr = 0.005
I0406 14:02:36.000774 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:02:40.683183 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel
I0406 14:02:43.722841 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate
I0406 14:02:46.014073 23057 solver.cpp:330] Iteration 1224, Testing net (#0)
I0406 14:02:46.014092 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:02:50.001497 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:02:50.607080 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0857843
I0406 14:02:50.607117 23057 solver.cpp:397]     Test net output #1: loss = 4.48376 (* 1 = 4.48376 loss)
I0406 14:02:50.758376 23057 solver.cpp:218] Iteration 1224 (0.799209 iter/s, 15.0148s/12 iters), loss = 4.45078
I0406 14:02:50.759948 23057 solver.cpp:237]     Train net output #0: loss = 4.45078 (* 1 = 4.45078 loss)
I0406 14:02:50.759968 23057 sgd_solver.cpp:105] Iteration 1224, lr = 0.005
I0406 14:02:55.290060 23057 solver.cpp:218] Iteration 1236 (2.64896 iter/s, 4.53008s/12 iters), loss = 4.65878
I0406 14:02:55.290170 23057 solver.cpp:237]     Train net output #0: loss = 4.65878 (* 1 = 4.65878 loss)
I0406 14:02:55.290179 23057 sgd_solver.cpp:105] Iteration 1236, lr = 0.005
I0406 14:03:00.822185 23057 solver.cpp:218] Iteration 1248 (2.16921 iter/s, 5.53196s/12 iters), loss = 4.49454
I0406 14:03:00.822237 23057 solver.cpp:237]     Train net output #0: loss = 4.49454 (* 1 = 4.49454 loss)
I0406 14:03:00.822245 23057 sgd_solver.cpp:105] Iteration 1248, lr = 0.005
I0406 14:03:05.896378 23057 solver.cpp:218] Iteration 1260 (2.36496 iter/s, 5.07408s/12 iters), loss = 4.50607
I0406 14:03:05.896430 23057 solver.cpp:237]     Train net output #0: loss = 4.50607 (* 1 = 4.50607 loss)
I0406 14:03:05.896438 23057 sgd_solver.cpp:105] Iteration 1260, lr = 0.005
I0406 14:03:11.210633 23057 solver.cpp:218] Iteration 1272 (2.25812 iter/s, 5.31415s/12 iters), loss = 4.50513
I0406 14:03:11.210678 23057 solver.cpp:237]     Train net output #0: loss = 4.50513 (* 1 = 4.50513 loss)
I0406 14:03:11.210686 23057 sgd_solver.cpp:105] Iteration 1272, lr = 0.005
I0406 14:03:16.462927 23057 solver.cpp:218] Iteration 1284 (2.28476 iter/s, 5.25219s/12 iters), loss = 4.43645
I0406 14:03:16.462983 23057 solver.cpp:237]     Train net output #0: loss = 4.43645 (* 1 = 4.43645 loss)
I0406 14:03:16.462992 23057 sgd_solver.cpp:105] Iteration 1284, lr = 0.005
I0406 14:03:21.851038 23057 solver.cpp:218] Iteration 1296 (2.22717 iter/s, 5.388s/12 iters), loss = 4.51979
I0406 14:03:21.851087 23057 solver.cpp:237]     Train net output #0: loss = 4.51979 (* 1 = 4.51979 loss)
I0406 14:03:21.851095 23057 sgd_solver.cpp:105] Iteration 1296, lr = 0.005
I0406 14:03:27.036686 23057 solver.cpp:218] Iteration 1308 (2.31413 iter/s, 5.18554s/12 iters), loss = 4.45555
I0406 14:03:27.036832 23057 solver.cpp:237]     Train net output #0: loss = 4.45555 (* 1 = 4.45555 loss)
I0406 14:03:27.036839 23057 sgd_solver.cpp:105] Iteration 1308, lr = 0.005
I0406 14:03:29.469203 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:03:32.338575 23057 solver.cpp:218] Iteration 1320 (2.26343 iter/s, 5.30168s/12 iters), loss = 4.48191
I0406 14:03:32.338635 23057 solver.cpp:237]     Train net output #0: loss = 4.48191 (* 1 = 4.48191 loss)
I0406 14:03:32.338644 23057 sgd_solver.cpp:105] Iteration 1320, lr = 0.005
I0406 14:03:34.576685 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel
I0406 14:03:37.617835 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate
I0406 14:03:39.952082 23057 solver.cpp:330] Iteration 1326, Testing net (#0)
I0406 14:03:39.952103 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:03:43.862807 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:03:44.450771 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0784314
I0406 14:03:44.450806 23057 solver.cpp:397]     Test net output #1: loss = 4.41039 (* 1 = 4.41039 loss)
I0406 14:03:46.330881 23057 solver.cpp:218] Iteration 1332 (0.857625 iter/s, 13.9921s/12 iters), loss = 4.30237
I0406 14:03:46.330943 23057 solver.cpp:237]     Train net output #0: loss = 4.30237 (* 1 = 4.30237 loss)
I0406 14:03:46.330952 23057 sgd_solver.cpp:105] Iteration 1332, lr = 0.005
I0406 14:03:51.596462 23057 solver.cpp:218] Iteration 1344 (2.279 iter/s, 5.26546s/12 iters), loss = 4.37089
I0406 14:03:51.596513 23057 solver.cpp:237]     Train net output #0: loss = 4.37089 (* 1 = 4.37089 loss)
I0406 14:03:51.596521 23057 sgd_solver.cpp:105] Iteration 1344, lr = 0.005
I0406 14:03:56.599076 23057 solver.cpp:218] Iteration 1356 (2.3988 iter/s, 5.00251s/12 iters), loss = 4.15091
I0406 14:03:56.599123 23057 solver.cpp:237]     Train net output #0: loss = 4.15091 (* 1 = 4.15091 loss)
I0406 14:03:56.599133 23057 sgd_solver.cpp:105] Iteration 1356, lr = 0.005
I0406 14:04:02.285970 23057 solver.cpp:218] Iteration 1368 (2.11015 iter/s, 5.68679s/12 iters), loss = 4.2064
I0406 14:04:02.286084 23057 solver.cpp:237]     Train net output #0: loss = 4.2064 (* 1 = 4.2064 loss)
I0406 14:04:02.286093 23057 sgd_solver.cpp:105] Iteration 1368, lr = 0.005
I0406 14:04:03.632027 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:04:07.682024 23057 solver.cpp:218] Iteration 1380 (2.22392 iter/s, 5.39588s/12 iters), loss = 4.22966
I0406 14:04:07.682066 23057 solver.cpp:237]     Train net output #0: loss = 4.22966 (* 1 = 4.22966 loss)
I0406 14:04:07.682072 23057 sgd_solver.cpp:105] Iteration 1380, lr = 0.005
I0406 14:04:13.000222 23057 solver.cpp:218] Iteration 1392 (2.25644 iter/s, 5.3181s/12 iters), loss = 4.27374
I0406 14:04:13.000260 23057 solver.cpp:237]     Train net output #0: loss = 4.27374 (* 1 = 4.27374 loss)
I0406 14:04:13.000265 23057 sgd_solver.cpp:105] Iteration 1392, lr = 0.005
I0406 14:04:18.308043 23057 solver.cpp:218] Iteration 1404 (2.26086 iter/s, 5.30772s/12 iters), loss = 4.30458
I0406 14:04:18.308096 23057 solver.cpp:237]     Train net output #0: loss = 4.30458 (* 1 = 4.30458 loss)
I0406 14:04:18.308106 23057 sgd_solver.cpp:105] Iteration 1404, lr = 0.005
I0406 14:04:23.135944 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:04:23.519533 23057 solver.cpp:218] Iteration 1416 (2.30265 iter/s, 5.21139s/12 iters), loss = 4.40241
I0406 14:04:23.519573 23057 solver.cpp:237]     Train net output #0: loss = 4.40241 (* 1 = 4.40241 loss)
I0406 14:04:23.519580 23057 sgd_solver.cpp:105] Iteration 1416, lr = 0.005
I0406 14:04:28.292225 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel
I0406 14:04:31.349720 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate
I0406 14:04:33.673712 23057 solver.cpp:330] Iteration 1428, Testing net (#0)
I0406 14:04:33.673825 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:04:37.478762 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:04:38.062700 23057 solver.cpp:397]     Test net output #0: accuracy = 0.0876225
I0406 14:04:38.062734 23057 solver.cpp:397]     Test net output #1: loss = 4.32228 (* 1 = 4.32228 loss)
I0406 14:04:38.203136 23057 solver.cpp:218] Iteration 1428 (0.817247 iter/s, 14.6834s/12 iters), loss = 4.23541
I0406 14:04:38.203192 23057 solver.cpp:237]     Train net output #0: loss = 4.23541 (* 1 = 4.23541 loss)
I0406 14:04:38.203200 23057 sgd_solver.cpp:105] Iteration 1428, lr = 0.005
I0406 14:04:42.720387 23057 solver.cpp:218] Iteration 1440 (2.65654 iter/s, 4.51715s/12 iters), loss = 4.26518
I0406 14:04:42.720449 23057 solver.cpp:237]     Train net output #0: loss = 4.26518 (* 1 = 4.26518 loss)
I0406 14:04:42.720458 23057 sgd_solver.cpp:105] Iteration 1440, lr = 0.005
I0406 14:04:47.943397 23057 solver.cpp:218] Iteration 1452 (2.29758 iter/s, 5.22289s/12 iters), loss = 4.0028
I0406 14:04:47.943462 23057 solver.cpp:237]     Train net output #0: loss = 4.0028 (* 1 = 4.0028 loss)
I0406 14:04:47.943471 23057 sgd_solver.cpp:105] Iteration 1452, lr = 0.005
I0406 14:04:53.222827 23057 solver.cpp:218] Iteration 1464 (2.27302 iter/s, 5.27931s/12 iters), loss = 4.17895
I0406 14:04:53.222875 23057 solver.cpp:237]     Train net output #0: loss = 4.17895 (* 1 = 4.17895 loss)
I0406 14:04:53.222883 23057 sgd_solver.cpp:105] Iteration 1464, lr = 0.005
I0406 14:04:58.629765 23057 solver.cpp:218] Iteration 1476 (2.21941 iter/s, 5.40683s/12 iters), loss = 4.30401
I0406 14:04:58.629806 23057 solver.cpp:237]     Train net output #0: loss = 4.30401 (* 1 = 4.30401 loss)
I0406 14:04:58.629812 23057 sgd_solver.cpp:105] Iteration 1476, lr = 0.005
I0406 14:05:04.131816 23057 solver.cpp:218] Iteration 1488 (2.18104 iter/s, 5.50195s/12 iters), loss = 4.11966
I0406 14:05:04.131925 23057 solver.cpp:237]     Train net output #0: loss = 4.11966 (* 1 = 4.11966 loss)
I0406 14:05:04.131934 23057 sgd_solver.cpp:105] Iteration 1488, lr = 0.005
I0406 14:05:09.407114 23057 solver.cpp:218] Iteration 1500 (2.27482 iter/s, 5.27514s/12 iters), loss = 4.11121
I0406 14:05:09.407164 23057 solver.cpp:237]     Train net output #0: loss = 4.11121 (* 1 = 4.11121 loss)
I0406 14:05:09.407173 23057 sgd_solver.cpp:105] Iteration 1500, lr = 0.005
I0406 14:05:14.575278 23057 solver.cpp:218] Iteration 1512 (2.32196 iter/s, 5.16806s/12 iters), loss = 4.23089
I0406 14:05:14.575328 23057 solver.cpp:237]     Train net output #0: loss = 4.23089 (* 1 = 4.23089 loss)
I0406 14:05:14.575336 23057 sgd_solver.cpp:105] Iteration 1512, lr = 0.005
I0406 14:05:16.570961 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:05:19.980517 23057 solver.cpp:218] Iteration 1524 (2.22011 iter/s, 5.40513s/12 iters), loss = 4.10397
I0406 14:05:19.980567 23057 solver.cpp:237]     Train net output #0: loss = 4.10397 (* 1 = 4.10397 loss)
I0406 14:05:19.980576 23057 sgd_solver.cpp:105] Iteration 1524, lr = 0.005
I0406 14:05:22.137415 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel
I0406 14:05:25.258409 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate
I0406 14:05:27.564183 23057 solver.cpp:330] Iteration 1530, Testing net (#0)
I0406 14:05:27.564205 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:05:31.417845 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:05:32.076593 23057 solver.cpp:397]     Test net output #0: accuracy = 0.096201
I0406 14:05:32.076622 23057 solver.cpp:397]     Test net output #1: loss = 4.17986 (* 1 = 4.17986 loss)
I0406 14:05:33.973167 23057 solver.cpp:218] Iteration 1536 (0.857603 iter/s, 13.9925s/12 iters), loss = 3.8975
I0406 14:05:33.973213 23057 solver.cpp:237]     Train net output #0: loss = 3.8975 (* 1 = 3.8975 loss)
I0406 14:05:33.973219 23057 sgd_solver.cpp:105] Iteration 1536, lr = 0.005
I0406 14:05:39.429659 23057 solver.cpp:218] Iteration 1548 (2.19926 iter/s, 5.45639s/12 iters), loss = 3.86038
I0406 14:05:39.429781 23057 solver.cpp:237]     Train net output #0: loss = 3.86038 (* 1 = 3.86038 loss)
I0406 14:05:39.429788 23057 sgd_solver.cpp:105] Iteration 1548, lr = 0.005
I0406 14:05:44.786731 23057 solver.cpp:218] Iteration 1560 (2.2401 iter/s, 5.35689s/12 iters), loss = 4.13122
I0406 14:05:44.786792 23057 solver.cpp:237]     Train net output #0: loss = 4.13122 (* 1 = 4.13122 loss)
I0406 14:05:44.786800 23057 sgd_solver.cpp:105] Iteration 1560, lr = 0.005
I0406 14:05:50.078871 23057 solver.cpp:218] Iteration 1572 (2.26756 iter/s, 5.29203s/12 iters), loss = 4.02743
I0406 14:05:50.078912 23057 solver.cpp:237]     Train net output #0: loss = 4.02743 (* 1 = 4.02743 loss)
I0406 14:05:50.078917 23057 sgd_solver.cpp:105] Iteration 1572, lr = 0.005
I0406 14:05:55.330843 23057 solver.cpp:218] Iteration 1584 (2.2849 iter/s, 5.25188s/12 iters), loss = 4.35342
I0406 14:05:55.330883 23057 solver.cpp:237]     Train net output #0: loss = 4.35342 (* 1 = 4.35342 loss)
I0406 14:05:55.330888 23057 sgd_solver.cpp:105] Iteration 1584, lr = 0.005
I0406 14:06:00.483976 23057 solver.cpp:218] Iteration 1596 (2.32872 iter/s, 5.15304s/12 iters), loss = 4.0029
I0406 14:06:00.484014 23057 solver.cpp:237]     Train net output #0: loss = 4.0029 (* 1 = 4.0029 loss)
I0406 14:06:00.484019 23057 sgd_solver.cpp:105] Iteration 1596, lr = 0.005
I0406 14:06:05.750787 23057 solver.cpp:218] Iteration 1608 (2.27846 iter/s, 5.26671s/12 iters), loss = 4.01003
I0406 14:06:05.750841 23057 solver.cpp:237]     Train net output #0: loss = 4.01003 (* 1 = 4.01003 loss)
I0406 14:06:05.750851 23057 sgd_solver.cpp:105] Iteration 1608, lr = 0.005
I0406 14:06:09.745713 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:06:10.940706 23057 solver.cpp:218] Iteration 1620 (2.31222 iter/s, 5.18981s/12 iters), loss = 3.94143
I0406 14:06:10.940762 23057 solver.cpp:237]     Train net output #0: loss = 3.94143 (* 1 = 3.94143 loss)
I0406 14:06:10.940769 23057 sgd_solver.cpp:105] Iteration 1620, lr = 0.005
I0406 14:06:15.271761 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel
I0406 14:06:18.326347 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate
I0406 14:06:20.635152 23057 solver.cpp:330] Iteration 1632, Testing net (#0)
I0406 14:06:20.635170 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:06:24.317847 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:06:24.980104 23057 solver.cpp:397]     Test net output #0: accuracy = 0.117034
I0406 14:06:24.980137 23057 solver.cpp:397]     Test net output #1: loss = 4.03268 (* 1 = 4.03268 loss)
I0406 14:06:25.120762 23057 solver.cpp:218] Iteration 1632 (0.846269 iter/s, 14.1799s/12 iters), loss = 3.89221
I0406 14:06:25.120807 23057 solver.cpp:237]     Train net output #0: loss = 3.89221 (* 1 = 3.89221 loss)
I0406 14:06:25.120813 23057 sgd_solver.cpp:105] Iteration 1632, lr = 0.005
I0406 14:06:29.576203 23057 solver.cpp:218] Iteration 1644 (2.69339 iter/s, 4.45535s/12 iters), loss = 3.98923
I0406 14:06:29.576248 23057 solver.cpp:237]     Train net output #0: loss = 3.98923 (* 1 = 3.98923 loss)
I0406 14:06:29.576254 23057 sgd_solver.cpp:105] Iteration 1644, lr = 0.005
I0406 14:06:34.859581 23057 solver.cpp:218] Iteration 1656 (2.27132 iter/s, 5.28328s/12 iters), loss = 4.03198
I0406 14:06:34.859666 23057 solver.cpp:237]     Train net output #0: loss = 4.03198 (* 1 = 4.03198 loss)
I0406 14:06:34.859673 23057 sgd_solver.cpp:105] Iteration 1656, lr = 0.005
I0406 14:06:40.070832 23057 solver.cpp:218] Iteration 1668 (2.30277 iter/s, 5.21111s/12 iters), loss = 3.91803
I0406 14:06:40.070999 23057 solver.cpp:237]     Train net output #0: loss = 3.91803 (* 1 = 3.91803 loss)
I0406 14:06:40.071009 23057 sgd_solver.cpp:105] Iteration 1668, lr = 0.005
I0406 14:06:45.057569 23057 solver.cpp:218] Iteration 1680 (2.40649 iter/s, 4.98652s/12 iters), loss = 3.87551
I0406 14:06:45.057615 23057 solver.cpp:237]     Train net output #0: loss = 3.87551 (* 1 = 3.87551 loss)
I0406 14:06:45.057621 23057 sgd_solver.cpp:105] Iteration 1680, lr = 0.005
I0406 14:06:50.306239 23057 solver.cpp:218] Iteration 1692 (2.28634 iter/s, 5.24857s/12 iters), loss = 3.83606
I0406 14:06:50.306290 23057 solver.cpp:237]     Train net output #0: loss = 3.83606 (* 1 = 3.83606 loss)
I0406 14:06:50.306298 23057 sgd_solver.cpp:105] Iteration 1692, lr = 0.005
I0406 14:06:55.587206 23057 solver.cpp:218] Iteration 1704 (2.27235 iter/s, 5.28087s/12 iters), loss = 3.76683
I0406 14:06:55.587246 23057 solver.cpp:237]     Train net output #0: loss = 3.76683 (* 1 = 3.76683 loss)
I0406 14:06:55.587251 23057 sgd_solver.cpp:105] Iteration 1704, lr = 0.005
I0406 14:07:01.039917 23057 solver.cpp:218] Iteration 1716 (2.20078 iter/s, 5.45262s/12 iters), loss = 4.11025
I0406 14:07:01.039963 23057 solver.cpp:237]     Train net output #0: loss = 4.11025 (* 1 = 4.11025 loss)
I0406 14:07:01.039970 23057 sgd_solver.cpp:105] Iteration 1716, lr = 0.005
I0406 14:07:02.114580 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:07:06.237614 23057 solver.cpp:218] Iteration 1728 (2.30876 iter/s, 5.1976s/12 iters), loss = 4.03916
I0406 14:07:06.237671 23057 solver.cpp:237]     Train net output #0: loss = 4.03916 (* 1 = 4.03916 loss)
I0406 14:07:06.237679 23057 sgd_solver.cpp:105] Iteration 1728, lr = 0.005
I0406 14:07:08.351055 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel
I0406 14:07:11.758674 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate
I0406 14:07:14.065542 23057 solver.cpp:330] Iteration 1734, Testing net (#0)
I0406 14:07:14.065570 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:07:17.896675 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:07:18.670986 23057 solver.cpp:397]     Test net output #0: accuracy = 0.126838
I0406 14:07:18.671020 23057 solver.cpp:397]     Test net output #1: loss = 3.99757 (* 1 = 3.99757 loss)
I0406 14:07:20.496546 23057 solver.cpp:218] Iteration 1740 (0.841588 iter/s, 14.2588s/12 iters), loss = 3.94955
I0406 14:07:20.496592 23057 solver.cpp:237]     Train net output #0: loss = 3.94955 (* 1 = 3.94955 loss)
I0406 14:07:20.496596 23057 sgd_solver.cpp:105] Iteration 1740, lr = 0.005
I0406 14:07:25.922189 23057 solver.cpp:218] Iteration 1752 (2.21176 iter/s, 5.42554s/12 iters), loss = 3.93792
I0406 14:07:25.922235 23057 solver.cpp:237]     Train net output #0: loss = 3.93792 (* 1 = 3.93792 loss)
I0406 14:07:25.922242 23057 sgd_solver.cpp:105] Iteration 1752, lr = 0.005
I0406 14:07:31.261606 23057 solver.cpp:218] Iteration 1764 (2.24748 iter/s, 5.33931s/12 iters), loss = 3.89151
I0406 14:07:31.261662 23057 solver.cpp:237]     Train net output #0: loss = 3.89151 (* 1 = 3.89151 loss)
I0406 14:07:31.261672 23057 sgd_solver.cpp:105] Iteration 1764, lr = 0.005
I0406 14:07:36.515470 23057 solver.cpp:218] Iteration 1776 (2.28408 iter/s, 5.25376s/12 iters), loss = 3.73072
I0406 14:07:36.515512 23057 solver.cpp:237]     Train net output #0: loss = 3.73072 (* 1 = 3.73072 loss)
I0406 14:07:36.515518 23057 sgd_solver.cpp:105] Iteration 1776, lr = 0.005
I0406 14:07:41.636292 23057 solver.cpp:218] Iteration 1788 (2.34342 iter/s, 5.12072s/12 iters), loss = 3.57947
I0406 14:07:41.636334 23057 solver.cpp:237]     Train net output #0: loss = 3.57947 (* 1 = 3.57947 loss)
I0406 14:07:41.636340 23057 sgd_solver.cpp:105] Iteration 1788, lr = 0.005
I0406 14:07:46.970374 23057 solver.cpp:218] Iteration 1800 (2.24973 iter/s, 5.33398s/12 iters), loss = 3.6278
I0406 14:07:46.970515 23057 solver.cpp:237]     Train net output #0: loss = 3.6278 (* 1 = 3.6278 loss)
I0406 14:07:46.970522 23057 sgd_solver.cpp:105] Iteration 1800, lr = 0.005
I0406 14:07:52.319902 23057 solver.cpp:218] Iteration 1812 (2.24327 iter/s, 5.34933s/12 iters), loss = 3.91122
I0406 14:07:52.319949 23057 solver.cpp:237]     Train net output #0: loss = 3.91122 (* 1 = 3.91122 loss)
I0406 14:07:52.319955 23057 sgd_solver.cpp:105] Iteration 1812, lr = 0.005
I0406 14:07:55.685243 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:07:57.592010 23057 solver.cpp:218] Iteration 1824 (2.27617 iter/s, 5.272s/12 iters), loss = 3.60076
I0406 14:07:57.592051 23057 solver.cpp:237]     Train net output #0: loss = 3.60076 (* 1 = 3.60076 loss)
I0406 14:07:57.592057 23057 sgd_solver.cpp:105] Iteration 1824, lr = 0.005
I0406 14:08:02.240111 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel
I0406 14:08:05.289559 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate
I0406 14:08:07.736586 23057 solver.cpp:330] Iteration 1836, Testing net (#0)
I0406 14:08:07.736613 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:08:11.309338 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:08:12.076527 23057 solver.cpp:397]     Test net output #0: accuracy = 0.137255
I0406 14:08:12.076563 23057 solver.cpp:397]     Test net output #1: loss = 3.92023 (* 1 = 3.92023 loss)
I0406 14:08:12.217509 23057 solver.cpp:218] Iteration 1836 (0.820494 iter/s, 14.6253s/12 iters), loss = 3.47825
I0406 14:08:12.217554 23057 solver.cpp:237]     Train net output #0: loss = 3.47825 (* 1 = 3.47825 loss)
I0406 14:08:12.217561 23057 sgd_solver.cpp:105] Iteration 1836, lr = 0.005
I0406 14:08:16.342365 23057 solver.cpp:218] Iteration 1848 (2.90926 iter/s, 4.12476s/12 iters), loss = 3.54765
I0406 14:08:16.342422 23057 solver.cpp:237]     Train net output #0: loss = 3.54765 (* 1 = 3.54765 loss)
I0406 14:08:16.342430 23057 sgd_solver.cpp:105] Iteration 1848, lr = 0.005
I0406 14:08:21.517933 23057 solver.cpp:218] Iteration 1860 (2.31863 iter/s, 5.17546s/12 iters), loss = 3.62013
I0406 14:08:21.518026 23057 solver.cpp:237]     Train net output #0: loss = 3.62013 (* 1 = 3.62013 loss)
I0406 14:08:21.518033 23057 sgd_solver.cpp:105] Iteration 1860, lr = 0.005
I0406 14:08:26.732856 23057 solver.cpp:218] Iteration 1872 (2.30115 iter/s, 5.21478s/12 iters), loss = 3.76055
I0406 14:08:26.732923 23057 solver.cpp:237]     Train net output #0: loss = 3.76055 (* 1 = 3.76055 loss)
I0406 14:08:26.732931 23057 sgd_solver.cpp:105] Iteration 1872, lr = 0.005
I0406 14:08:31.944165 23057 solver.cpp:218] Iteration 1884 (2.30274 iter/s, 5.21119s/12 iters), loss = 3.57448
I0406 14:08:31.944214 23057 solver.cpp:237]     Train net output #0: loss = 3.57448 (* 1 = 3.57448 loss)
I0406 14:08:31.944222 23057 sgd_solver.cpp:105] Iteration 1884, lr = 0.005
I0406 14:08:37.239076 23057 solver.cpp:218] Iteration 1896 (2.26637 iter/s, 5.2948s/12 iters), loss = 3.72121
I0406 14:08:37.239125 23057 solver.cpp:237]     Train net output #0: loss = 3.72121 (* 1 = 3.72121 loss)
I0406 14:08:37.239133 23057 sgd_solver.cpp:105] Iteration 1896, lr = 0.005
I0406 14:08:42.632000 23057 solver.cpp:218] Iteration 1908 (2.22518 iter/s, 5.39282s/12 iters), loss = 3.62734
I0406 14:08:42.632040 23057 solver.cpp:237]     Train net output #0: loss = 3.62734 (* 1 = 3.62734 loss)
I0406 14:08:42.632047 23057 sgd_solver.cpp:105] Iteration 1908, lr = 0.005
I0406 14:08:47.856979 23057 solver.cpp:218] Iteration 1920 (2.2967 iter/s, 5.22488s/12 iters), loss = 3.45097
I0406 14:08:47.857028 23057 solver.cpp:237]     Train net output #0: loss = 3.45097 (* 1 = 3.45097 loss)
I0406 14:08:47.857035 23057 sgd_solver.cpp:105] Iteration 1920, lr = 0.005
I0406 14:08:48.107589 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:08:53.019989 23057 solver.cpp:218] Iteration 1932 (2.32427 iter/s, 5.16291s/12 iters), loss = 3.45109
I0406 14:08:53.020077 23057 solver.cpp:237]     Train net output #0: loss = 3.45109 (* 1 = 3.45109 loss)
I0406 14:08:53.020083 23057 sgd_solver.cpp:105] Iteration 1932, lr = 0.005
I0406 14:08:55.133507 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel
I0406 14:08:58.142104 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate
I0406 14:09:02.226822 23057 solver.cpp:330] Iteration 1938, Testing net (#0)
I0406 14:09:02.226841 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:09:05.772351 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:09:06.657905 23057 solver.cpp:397]     Test net output #0: accuracy = 0.159314
I0406 14:09:06.657943 23057 solver.cpp:397]     Test net output #1: loss = 3.72807 (* 1 = 3.72807 loss)
I0406 14:09:08.469877 23057 solver.cpp:218] Iteration 1944 (0.776715 iter/s, 15.4497s/12 iters), loss = 3.62627
I0406 14:09:08.469921 23057 solver.cpp:237]     Train net output #0: loss = 3.62627 (* 1 = 3.62627 loss)
I0406 14:09:08.469926 23057 sgd_solver.cpp:105] Iteration 1944, lr = 0.005
I0406 14:09:13.804961 23057 solver.cpp:218] Iteration 1956 (2.2493 iter/s, 5.33498s/12 iters), loss = 3.51797
I0406 14:09:13.805003 23057 solver.cpp:237]     Train net output #0: loss = 3.51797 (* 1 = 3.51797 loss)
I0406 14:09:13.805011 23057 sgd_solver.cpp:105] Iteration 1956, lr = 0.005
I0406 14:09:18.951084 23057 solver.cpp:218] Iteration 1968 (2.3319 iter/s, 5.14602s/12 iters), loss = 3.57931
I0406 14:09:18.951138 23057 solver.cpp:237]     Train net output #0: loss = 3.57931 (* 1 = 3.57931 loss)
I0406 14:09:18.951148 23057 sgd_solver.cpp:105] Iteration 1968, lr = 0.005
I0406 14:09:24.240811 23057 solver.cpp:218] Iteration 1980 (2.26859 iter/s, 5.28962s/12 iters), loss = 3.31969
I0406 14:09:24.240944 23057 solver.cpp:237]     Train net output #0: loss = 3.31969 (* 1 = 3.31969 loss)
I0406 14:09:24.240950 23057 sgd_solver.cpp:105] Iteration 1980, lr = 0.005
I0406 14:09:29.392755 23057 solver.cpp:218] Iteration 1992 (2.3293 iter/s, 5.15176s/12 iters), loss = 3.53569
I0406 14:09:29.392808 23057 solver.cpp:237]     Train net output #0: loss = 3.53569 (* 1 = 3.53569 loss)
I0406 14:09:29.392818 23057 sgd_solver.cpp:105] Iteration 1992, lr = 0.005
I0406 14:09:34.732451 23057 solver.cpp:218] Iteration 2004 (2.24737 iter/s, 5.33958s/12 iters), loss = 3.48022
I0406 14:09:34.732508 23057 solver.cpp:237]     Train net output #0: loss = 3.48022 (* 1 = 3.48022 loss)
I0406 14:09:34.732517 23057 sgd_solver.cpp:105] Iteration 2004, lr = 0.005
I0406 14:09:40.160408 23057 solver.cpp:218] Iteration 2016 (2.21082 iter/s, 5.42784s/12 iters), loss = 3.61108
I0406 14:09:40.160460 23057 solver.cpp:237]     Train net output #0: loss = 3.61108 (* 1 = 3.61108 loss)
I0406 14:09:40.160470 23057 sgd_solver.cpp:105] Iteration 2016, lr = 0.005
I0406 14:09:42.760150 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:09:45.336907 23057 solver.cpp:218] Iteration 2028 (2.31822 iter/s, 5.17639s/12 iters), loss = 3.49716
I0406 14:09:45.336948 23057 solver.cpp:237]     Train net output #0: loss = 3.49716 (* 1 = 3.49716 loss)
I0406 14:09:45.336954 23057 sgd_solver.cpp:105] Iteration 2028, lr = 0.005
I0406 14:09:50.134796 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel
I0406 14:09:54.512302 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate
I0406 14:09:56.822948 23057 solver.cpp:330] Iteration 2040, Testing net (#0)
I0406 14:09:56.822965 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:10:00.492027 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:10:01.332674 23057 solver.cpp:397]     Test net output #0: accuracy = 0.166054
I0406 14:10:01.332708 23057 solver.cpp:397]     Test net output #1: loss = 3.62277 (* 1 = 3.62277 loss)
I0406 14:10:01.469156 23057 solver.cpp:218] Iteration 2040 (0.743859 iter/s, 16.1321s/12 iters), loss = 3.28717
I0406 14:10:01.469198 23057 solver.cpp:237]     Train net output #0: loss = 3.28717 (* 1 = 3.28717 loss)
I0406 14:10:01.469204 23057 sgd_solver.cpp:105] Iteration 2040, lr = 0.005
I0406 14:10:05.630640 23057 solver.cpp:218] Iteration 2052 (2.88365 iter/s, 4.16139s/12 iters), loss = 3.45048
I0406 14:10:05.630684 23057 solver.cpp:237]     Train net output #0: loss = 3.45048 (* 1 = 3.45048 loss)
I0406 14:10:05.630690 23057 sgd_solver.cpp:105] Iteration 2052, lr = 0.005
I0406 14:10:07.280800 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:10:10.717084 23057 solver.cpp:218] Iteration 2064 (2.35926 iter/s, 5.08635s/12 iters), loss = 3.32729
I0406 14:10:10.717130 23057 solver.cpp:237]     Train net output #0: loss = 3.32729 (* 1 = 3.32729 loss)
I0406 14:10:10.717136 23057 sgd_solver.cpp:105] Iteration 2064, lr = 0.005
I0406 14:10:15.988513 23057 solver.cpp:218] Iteration 2076 (2.27647 iter/s, 5.27132s/12 iters), loss = 3.256
I0406 14:10:15.988576 23057 solver.cpp:237]     Train net output #0: loss = 3.256 (* 1 = 3.256 loss)
I0406 14:10:15.988585 23057 sgd_solver.cpp:105] Iteration 2076, lr = 0.005
I0406 14:10:21.340157 23057 solver.cpp:218] Iteration 2088 (2.24235 iter/s, 5.35153s/12 iters), loss = 3.38349
I0406 14:10:21.340196 23057 solver.cpp:237]     Train net output #0: loss = 3.38349 (* 1 = 3.38349 loss)
I0406 14:10:21.340202 23057 sgd_solver.cpp:105] Iteration 2088, lr = 0.005
I0406 14:10:26.459483 23057 solver.cpp:218] Iteration 2100 (2.3441 iter/s, 5.11923s/12 iters), loss = 3.17823
I0406 14:10:26.459978 23057 solver.cpp:237]     Train net output #0: loss = 3.17823 (* 1 = 3.17823 loss)
I0406 14:10:26.459988 23057 sgd_solver.cpp:105] Iteration 2100, lr = 0.005
I0406 14:10:31.471252 23057 solver.cpp:218] Iteration 2112 (2.39462 iter/s, 5.01123s/12 iters), loss = 3.29893
I0406 14:10:31.471292 23057 solver.cpp:237]     Train net output #0: loss = 3.29893 (* 1 = 3.29893 loss)
I0406 14:10:31.471297 23057 sgd_solver.cpp:105] Iteration 2112, lr = 0.005
I0406 14:10:36.123762 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:10:36.479466 23057 solver.cpp:218] Iteration 2124 (2.39611 iter/s, 5.00812s/12 iters), loss = 3.46195
I0406 14:10:36.479506 23057 solver.cpp:237]     Train net output #0: loss = 3.46195 (* 1 = 3.46195 loss)
I0406 14:10:36.479511 23057 sgd_solver.cpp:105] Iteration 2124, lr = 0.005
I0406 14:10:41.919867 23057 solver.cpp:218] Iteration 2136 (2.20576 iter/s, 5.44031s/12 iters), loss = 3.18167
I0406 14:10:41.919909 23057 solver.cpp:237]     Train net output #0: loss = 3.18167 (* 1 = 3.18167 loss)
I0406 14:10:41.919915 23057 sgd_solver.cpp:105] Iteration 2136, lr = 0.005
I0406 14:10:43.926997 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel
I0406 14:10:46.940213 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate
I0406 14:10:49.242105 23057 solver.cpp:330] Iteration 2142, Testing net (#0)
I0406 14:10:49.242122 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:10:52.801826 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:10:53.654721 23057 solver.cpp:397]     Test net output #0: accuracy = 0.18076
I0406 14:10:53.654758 23057 solver.cpp:397]     Test net output #1: loss = 3.61433 (* 1 = 3.61433 loss)
I0406 14:10:55.564908 23057 solver.cpp:218] Iteration 2148 (0.87945 iter/s, 13.6449s/12 iters), loss = 3.24216
I0406 14:10:55.564960 23057 solver.cpp:237]     Train net output #0: loss = 3.24216 (* 1 = 3.24216 loss)
I0406 14:10:55.564970 23057 sgd_solver.cpp:105] Iteration 2148, lr = 0.005
I0406 14:11:00.732360 23057 solver.cpp:218] Iteration 2160 (2.32227 iter/s, 5.16735s/12 iters), loss = 3.06034
I0406 14:11:00.732462 23057 solver.cpp:237]     Train net output #0: loss = 3.06034 (* 1 = 3.06034 loss)
I0406 14:11:00.732470 23057 sgd_solver.cpp:105] Iteration 2160, lr = 0.005
I0406 14:11:05.940276 23057 solver.cpp:218] Iteration 2172 (2.30426 iter/s, 5.20776s/12 iters), loss = 2.96321
I0406 14:11:05.940328 23057 solver.cpp:237]     Train net output #0: loss = 2.96321 (* 1 = 2.96321 loss)
I0406 14:11:05.940335 23057 sgd_solver.cpp:105] Iteration 2172, lr = 0.005
I0406 14:11:11.104305 23057 solver.cpp:218] Iteration 2184 (2.32381 iter/s, 5.16392s/12 iters), loss = 3.36158
I0406 14:11:11.104367 23057 solver.cpp:237]     Train net output #0: loss = 3.36158 (* 1 = 3.36158 loss)
I0406 14:11:11.104374 23057 sgd_solver.cpp:105] Iteration 2184, lr = 0.005
I0406 14:11:16.435390 23057 solver.cpp:218] Iteration 2196 (2.251 iter/s, 5.33097s/12 iters), loss = 3.35988
I0406 14:11:16.435442 23057 solver.cpp:237]     Train net output #0: loss = 3.35988 (* 1 = 3.35988 loss)
I0406 14:11:16.435451 23057 sgd_solver.cpp:105] Iteration 2196, lr = 0.005
I0406 14:11:21.789162 23057 solver.cpp:218] Iteration 2208 (2.24145 iter/s, 5.35367s/12 iters), loss = 3.23808
I0406 14:11:21.789202 23057 solver.cpp:237]     Train net output #0: loss = 3.23808 (* 1 = 3.23808 loss)
I0406 14:11:21.789209 23057 sgd_solver.cpp:105] Iteration 2208, lr = 0.005
I0406 14:11:26.992048 23057 solver.cpp:218] Iteration 2220 (2.30646 iter/s, 5.20278s/12 iters), loss = 3.13383
I0406 14:11:26.992103 23057 solver.cpp:237]     Train net output #0: loss = 3.13383 (* 1 = 3.13383 loss)
I0406 14:11:26.992111 23057 sgd_solver.cpp:105] Iteration 2220, lr = 0.005
I0406 14:11:28.779793 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:11:32.404247 23057 solver.cpp:218] Iteration 2232 (2.21726 iter/s, 5.41209s/12 iters), loss = 2.94009
I0406 14:11:32.404364 23057 solver.cpp:237]     Train net output #0: loss = 2.94009 (* 1 = 2.94009 loss)
I0406 14:11:32.404371 23057 sgd_solver.cpp:105] Iteration 2232, lr = 0.005
I0406 14:11:37.257272 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel
I0406 14:11:40.287959 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate
I0406 14:11:42.604166 23057 solver.cpp:330] Iteration 2244, Testing net (#0)
I0406 14:11:42.604188 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:11:46.039804 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:11:47.009881 23057 solver.cpp:397]     Test net output #0: accuracy = 0.202206
I0406 14:11:47.009917 23057 solver.cpp:397]     Test net output #1: loss = 3.53061 (* 1 = 3.53061 loss)
I0406 14:11:47.153414 23057 solver.cpp:218] Iteration 2244 (0.813619 iter/s, 14.7489s/12 iters), loss = 2.82697
I0406 14:11:47.154978 23057 solver.cpp:237]     Train net output #0: loss = 2.82697 (* 1 = 2.82697 loss)
I0406 14:11:47.154990 23057 sgd_solver.cpp:105] Iteration 2244, lr = 0.005
I0406 14:11:51.575372 23057 solver.cpp:218] Iteration 2256 (2.71471 iter/s, 4.42035s/12 iters), loss = 2.96795
I0406 14:11:51.575413 23057 solver.cpp:237]     Train net output #0: loss = 2.96795 (* 1 = 2.96795 loss)
I0406 14:11:51.575420 23057 sgd_solver.cpp:105] Iteration 2256, lr = 0.005
I0406 14:11:56.950345 23057 solver.cpp:218] Iteration 2268 (2.23261 iter/s, 5.37487s/12 iters), loss = 2.89272
I0406 14:11:56.950402 23057 solver.cpp:237]     Train net output #0: loss = 2.89272 (* 1 = 2.89272 loss)
I0406 14:11:56.950412 23057 sgd_solver.cpp:105] Iteration 2268, lr = 0.005
I0406 14:12:02.314275 23057 solver.cpp:218] Iteration 2280 (2.23721 iter/s, 5.36382s/12 iters), loss = 2.88715
I0406 14:12:02.314332 23057 solver.cpp:237]     Train net output #0: loss = 2.88715 (* 1 = 2.88715 loss)
I0406 14:12:02.314338 23057 sgd_solver.cpp:105] Iteration 2280, lr = 0.005
I0406 14:12:07.616945 23057 solver.cpp:218] Iteration 2292 (2.26306 iter/s, 5.30256s/12 iters), loss = 3.18447
I0406 14:12:07.617049 23057 solver.cpp:237]     Train net output #0: loss = 3.18447 (* 1 = 3.18447 loss)
I0406 14:12:07.617056 23057 sgd_solver.cpp:105] Iteration 2292, lr = 0.005
I0406 14:12:12.888379 23057 solver.cpp:218] Iteration 2304 (2.27649 iter/s, 5.27127s/12 iters), loss = 2.89709
I0406 14:12:12.888428 23057 solver.cpp:237]     Train net output #0: loss = 2.89709 (* 1 = 2.89709 loss)
I0406 14:12:12.888435 23057 sgd_solver.cpp:105] Iteration 2304, lr = 0.005
I0406 14:12:18.146292 23057 solver.cpp:218] Iteration 2316 (2.28232 iter/s, 5.25781s/12 iters), loss = 2.9119
I0406 14:12:18.146353 23057 solver.cpp:237]     Train net output #0: loss = 2.9119 (* 1 = 2.9119 loss)
I0406 14:12:18.146363 23057 sgd_solver.cpp:105] Iteration 2316, lr = 0.005
I0406 14:12:22.184837 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:12:23.303711 23057 solver.cpp:218] Iteration 2328 (2.32679 iter/s, 5.15731s/12 iters), loss = 2.99083
I0406 14:12:23.303753 23057 solver.cpp:237]     Train net output #0: loss = 2.99083 (* 1 = 2.99083 loss)
I0406 14:12:23.303759 23057 sgd_solver.cpp:105] Iteration 2328, lr = 0.005
I0406 14:12:28.674430 23057 solver.cpp:218] Iteration 2340 (2.23438 iter/s, 5.37062s/12 iters), loss = 2.74181
I0406 14:12:28.674489 23057 solver.cpp:237]     Train net output #0: loss = 2.74181 (* 1 = 2.74181 loss)
I0406 14:12:28.674497 23057 sgd_solver.cpp:105] Iteration 2340, lr = 0.005
I0406 14:12:30.806103 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel
I0406 14:12:33.881579 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate
I0406 14:12:36.187825 23057 solver.cpp:330] Iteration 2346, Testing net (#0)
I0406 14:12:36.187849 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:12:39.584549 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:12:40.522246 23057 solver.cpp:397]     Test net output #0: accuracy = 0.215686
I0406 14:12:40.522274 23057 solver.cpp:397]     Test net output #1: loss = 3.48781 (* 1 = 3.48781 loss)
I0406 14:12:42.272804 23057 solver.cpp:218] Iteration 2352 (0.882469 iter/s, 13.5982s/12 iters), loss = 3.12472
I0406 14:12:42.272845 23057 solver.cpp:237]     Train net output #0: loss = 3.12472 (* 1 = 3.12472 loss)
I0406 14:12:42.272850 23057 sgd_solver.cpp:105] Iteration 2352, lr = 0.005
I0406 14:12:47.525646 23057 solver.cpp:218] Iteration 2364 (2.28452 iter/s, 5.25274s/12 iters), loss = 2.76
I0406 14:12:47.525696 23057 solver.cpp:237]     Train net output #0: loss = 2.76 (* 1 = 2.76 loss)
I0406 14:12:47.525703 23057 sgd_solver.cpp:105] Iteration 2364, lr = 0.005
I0406 14:12:52.817740 23057 solver.cpp:218] Iteration 2376 (2.26758 iter/s, 5.29199s/12 iters), loss = 2.9058
I0406 14:12:52.817790 23057 solver.cpp:237]     Train net output #0: loss = 2.9058 (* 1 = 2.9058 loss)
I0406 14:12:52.817800 23057 sgd_solver.cpp:105] Iteration 2376, lr = 0.005
I0406 14:12:58.256016 23057 solver.cpp:218] Iteration 2388 (2.20662 iter/s, 5.43817s/12 iters), loss = 2.68497
I0406 14:12:58.256062 23057 solver.cpp:237]     Train net output #0: loss = 2.68497 (* 1 = 2.68497 loss)
I0406 14:12:58.256069 23057 sgd_solver.cpp:105] Iteration 2388, lr = 0.005
I0406 14:13:03.577347 23057 solver.cpp:218] Iteration 2400 (2.25512 iter/s, 5.32123s/12 iters), loss = 2.54653
I0406 14:13:03.577387 23057 solver.cpp:237]     Train net output #0: loss = 2.54653 (* 1 = 2.54653 loss)
I0406 14:13:03.577392 23057 sgd_solver.cpp:105] Iteration 2400, lr = 0.005
I0406 14:13:08.957033 23057 solver.cpp:218] Iteration 2412 (2.23065 iter/s, 5.37959s/12 iters), loss = 2.75899
I0406 14:13:08.957073 23057 solver.cpp:237]     Train net output #0: loss = 2.75899 (* 1 = 2.75899 loss)
I0406 14:13:08.957079 23057 sgd_solver.cpp:105] Iteration 2412, lr = 0.005
I0406 14:13:14.424201 23057 solver.cpp:218] Iteration 2424 (2.19496 iter/s, 5.46707s/12 iters), loss = 2.68633
I0406 14:13:14.424305 23057 solver.cpp:237]     Train net output #0: loss = 2.68633 (* 1 = 2.68633 loss)
I0406 14:13:14.424312 23057 sgd_solver.cpp:105] Iteration 2424, lr = 0.005
I0406 14:13:15.620261 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:13:19.867234 23057 solver.cpp:218] Iteration 2436 (2.20472 iter/s, 5.44287s/12 iters), loss = 3.00557
I0406 14:13:19.867283 23057 solver.cpp:237]     Train net output #0: loss = 3.00557 (* 1 = 3.00557 loss)
I0406 14:13:19.867290 23057 sgd_solver.cpp:105] Iteration 2436, lr = 0.005
I0406 14:13:24.519529 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel
I0406 14:13:27.538908 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate
I0406 14:13:29.849265 23057 solver.cpp:330] Iteration 2448, Testing net (#0)
I0406 14:13:29.849287 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:13:33.186014 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:13:34.195891 23057 solver.cpp:397]     Test net output #0: accuracy = 0.210172
I0406 14:13:34.195927 23057 solver.cpp:397]     Test net output #1: loss = 3.47608 (* 1 = 3.47608 loss)
I0406 14:13:34.336145 23057 solver.cpp:218] Iteration 2448 (0.829374 iter/s, 14.4687s/12 iters), loss = 2.87553
I0406 14:13:34.336205 23057 solver.cpp:237]     Train net output #0: loss = 2.87553 (* 1 = 2.87553 loss)
I0406 14:13:34.336212 23057 sgd_solver.cpp:105] Iteration 2448, lr = 0.005
I0406 14:13:38.726863 23057 solver.cpp:218] Iteration 2460 (2.73311 iter/s, 4.39061s/12 iters), loss = 2.74822
I0406 14:13:38.726907 23057 solver.cpp:237]     Train net output #0: loss = 2.74822 (* 1 = 2.74822 loss)
I0406 14:13:38.726913 23057 sgd_solver.cpp:105] Iteration 2460, lr = 0.005
I0406 14:13:44.194310 23057 solver.cpp:218] Iteration 2472 (2.19485 iter/s, 5.46735s/12 iters), loss = 2.69194
I0406 14:13:44.194350 23057 solver.cpp:237]     Train net output #0: loss = 2.69194 (* 1 = 2.69194 loss)
I0406 14:13:44.194356 23057 sgd_solver.cpp:105] Iteration 2472, lr = 0.005
I0406 14:13:49.589418 23057 solver.cpp:218] Iteration 2484 (2.22428 iter/s, 5.39501s/12 iters), loss = 2.59842
I0406 14:13:49.589561 23057 solver.cpp:237]     Train net output #0: loss = 2.59842 (* 1 = 2.59842 loss)
I0406 14:13:49.589571 23057 sgd_solver.cpp:105] Iteration 2484, lr = 0.005
I0406 14:13:54.813740 23057 solver.cpp:218] Iteration 2496 (2.29704 iter/s, 5.22412s/12 iters), loss = 2.65351
I0406 14:13:54.813794 23057 solver.cpp:237]     Train net output #0: loss = 2.65351 (* 1 = 2.65351 loss)
I0406 14:13:54.813802 23057 sgd_solver.cpp:105] Iteration 2496, lr = 0.005
I0406 14:14:00.143448 23057 solver.cpp:218] Iteration 2508 (2.25157 iter/s, 5.3296s/12 iters), loss = 2.68481
I0406 14:14:00.143486 23057 solver.cpp:237]     Train net output #0: loss = 2.68481 (* 1 = 2.68481 loss)
I0406 14:14:00.143492 23057 sgd_solver.cpp:105] Iteration 2508, lr = 0.005
I0406 14:14:05.239862 23057 solver.cpp:218] Iteration 2520 (2.35464 iter/s, 5.09632s/12 iters), loss = 2.72918
I0406 14:14:05.239899 23057 solver.cpp:237]     Train net output #0: loss = 2.72918 (* 1 = 2.72918 loss)
I0406 14:14:05.239904 23057 sgd_solver.cpp:105] Iteration 2520, lr = 0.005
I0406 14:14:08.410547 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:14:10.418586 23057 solver.cpp:218] Iteration 2532 (2.31721 iter/s, 5.17863s/12 iters), loss = 2.56196
I0406 14:14:10.418635 23057 solver.cpp:237]     Train net output #0: loss = 2.56196 (* 1 = 2.56196 loss)
I0406 14:14:10.418643 23057 sgd_solver.cpp:105] Iteration 2532, lr = 0.005
I0406 14:14:15.694823 23057 solver.cpp:218] Iteration 2544 (2.27439 iter/s, 5.27613s/12 iters), loss = 2.40158
I0406 14:14:15.694864 23057 solver.cpp:237]     Train net output #0: loss = 2.40158 (* 1 = 2.40158 loss)
I0406 14:14:15.694870 23057 sgd_solver.cpp:105] Iteration 2544, lr = 0.005
I0406 14:14:17.789062 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel
I0406 14:14:20.790211 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate
I0406 14:14:23.090632 23057 solver.cpp:330] Iteration 2550, Testing net (#0)
I0406 14:14:23.090656 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:14:26.394590 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:14:27.410621 23057 solver.cpp:397]     Test net output #0: accuracy = 0.233456
I0406 14:14:27.410656 23057 solver.cpp:397]     Test net output #1: loss = 3.43096 (* 1 = 3.43096 loss)
I0406 14:14:29.300745 23057 solver.cpp:218] Iteration 2556 (0.881979 iter/s, 13.6058s/12 iters), loss = 2.77008
I0406 14:14:29.300792 23057 solver.cpp:237]     Train net output #0: loss = 2.77008 (* 1 = 2.77008 loss)
I0406 14:14:29.300798 23057 sgd_solver.cpp:105] Iteration 2556, lr = 0.005
I0406 14:14:34.440743 23057 solver.cpp:218] Iteration 2568 (2.33468 iter/s, 5.1399s/12 iters), loss = 2.49493
I0406 14:14:34.440804 23057 solver.cpp:237]     Train net output #0: loss = 2.49493 (* 1 = 2.49493 loss)
I0406 14:14:34.440811 23057 sgd_solver.cpp:105] Iteration 2568, lr = 0.005
I0406 14:14:39.505539 23057 solver.cpp:218] Iteration 2580 (2.36935 iter/s, 5.06468s/12 iters), loss = 2.46329
I0406 14:14:39.505586 23057 solver.cpp:237]     Train net output #0: loss = 2.46329 (* 1 = 2.46329 loss)
I0406 14:14:39.505592 23057 sgd_solver.cpp:105] Iteration 2580, lr = 0.005
I0406 14:14:44.639695 23057 solver.cpp:218] Iteration 2592 (2.33733 iter/s, 5.13406s/12 iters), loss = 2.42082
I0406 14:14:44.639731 23057 solver.cpp:237]     Train net output #0: loss = 2.42082 (* 1 = 2.42082 loss)
I0406 14:14:44.639737 23057 sgd_solver.cpp:105] Iteration 2592, lr = 0.005
I0406 14:14:49.911428 23057 solver.cpp:218] Iteration 2604 (2.27633 iter/s, 5.27164s/12 iters), loss = 2.50312
I0406 14:14:49.911478 23057 solver.cpp:237]     Train net output #0: loss = 2.50312 (* 1 = 2.50312 loss)
I0406 14:14:49.911485 23057 sgd_solver.cpp:105] Iteration 2604, lr = 0.005
I0406 14:14:55.051273 23057 solver.cpp:218] Iteration 2616 (2.33475 iter/s, 5.13974s/12 iters), loss = 2.39169
I0406 14:14:55.051928 23057 solver.cpp:237]     Train net output #0: loss = 2.39169 (* 1 = 2.39169 loss)
I0406 14:14:55.051939 23057 sgd_solver.cpp:105] Iteration 2616, lr = 0.005
I0406 14:15:00.103039 23057 solver.cpp:218] Iteration 2628 (2.37574 iter/s, 5.05106s/12 iters), loss = 2.38782
I0406 14:15:00.103075 23057 solver.cpp:237]     Train net output #0: loss = 2.38782 (* 1 = 2.38782 loss)
I0406 14:15:00.103081 23057 sgd_solver.cpp:105] Iteration 2628, lr = 0.005
I0406 14:15:00.565462 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:15:05.543545 23057 solver.cpp:218] Iteration 2640 (2.20572 iter/s, 5.44041s/12 iters), loss = 2.60898
I0406 14:15:05.543609 23057 solver.cpp:237]     Train net output #0: loss = 2.60898 (* 1 = 2.60898 loss)
I0406 14:15:05.543618 23057 sgd_solver.cpp:105] Iteration 2640, lr = 0.005
I0406 14:15:10.273877 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel
I0406 14:15:13.354785 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate
I0406 14:15:15.666162 23057 solver.cpp:330] Iteration 2652, Testing net (#0)
I0406 14:15:15.666185 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:15:18.902698 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:15:19.939344 23057 solver.cpp:397]     Test net output #0: accuracy = 0.229167
I0406 14:15:19.939378 23057 solver.cpp:397]     Test net output #1: loss = 3.48568 (* 1 = 3.48568 loss)
I0406 14:15:20.079730 23057 solver.cpp:218] Iteration 2652 (0.825536 iter/s, 14.536s/12 iters), loss = 2.68304
I0406 14:15:20.079782 23057 solver.cpp:237]     Train net output #0: loss = 2.68304 (* 1 = 2.68304 loss)
I0406 14:15:20.079790 23057 sgd_solver.cpp:105] Iteration 2652, lr = 0.005
I0406 14:15:24.431690 23057 solver.cpp:218] Iteration 2664 (2.75744 iter/s, 4.35186s/12 iters), loss = 2.49261
I0406 14:15:24.431735 23057 solver.cpp:237]     Train net output #0: loss = 2.49261 (* 1 = 2.49261 loss)
I0406 14:15:24.431740 23057 sgd_solver.cpp:105] Iteration 2664, lr = 0.005
I0406 14:15:29.819029 23057 solver.cpp:218] Iteration 2676 (2.22749 iter/s, 5.38724s/12 iters), loss = 2.35445
I0406 14:15:29.819141 23057 solver.cpp:237]     Train net output #0: loss = 2.35445 (* 1 = 2.35445 loss)
I0406 14:15:29.819150 23057 sgd_solver.cpp:105] Iteration 2676, lr = 0.005
I0406 14:15:35.308913 23057 solver.cpp:218] Iteration 2688 (2.18591 iter/s, 5.48972s/12 iters), loss = 2.46501
I0406 14:15:35.308964 23057 solver.cpp:237]     Train net output #0: loss = 2.46501 (* 1 = 2.46501 loss)
I0406 14:15:35.308971 23057 sgd_solver.cpp:105] Iteration 2688, lr = 0.005
I0406 14:15:40.653475 23057 solver.cpp:218] Iteration 2700 (2.24532 iter/s, 5.34446s/12 iters), loss = 2.29946
I0406 14:15:40.653515 23057 solver.cpp:237]     Train net output #0: loss = 2.29946 (* 1 = 2.29946 loss)
I0406 14:15:40.653522 23057 sgd_solver.cpp:105] Iteration 2700, lr = 0.005
I0406 14:15:45.916514 23057 solver.cpp:218] Iteration 2712 (2.28009 iter/s, 5.26295s/12 iters), loss = 2.51682
I0406 14:15:45.916565 23057 solver.cpp:237]     Train net output #0: loss = 2.51682 (* 1 = 2.51682 loss)
I0406 14:15:45.916574 23057 sgd_solver.cpp:105] Iteration 2712, lr = 0.005
I0406 14:15:51.222865 23057 solver.cpp:218] Iteration 2724 (2.26149 iter/s, 5.30624s/12 iters), loss = 2.72911
I0406 14:15:51.222913 23057 solver.cpp:237]     Train net output #0: loss = 2.72911 (* 1 = 2.72911 loss)
I0406 14:15:51.222921 23057 sgd_solver.cpp:105] Iteration 2724, lr = 0.005
I0406 14:15:53.970057 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:15:56.526201 23057 solver.cpp:218] Iteration 2736 (2.26277 iter/s, 5.30324s/12 iters), loss = 2.99692
I0406 14:15:56.526242 23057 solver.cpp:237]     Train net output #0: loss = 2.99692 (* 1 = 2.99692 loss)
I0406 14:15:56.526247 23057 sgd_solver.cpp:105] Iteration 2736, lr = 0.005
I0406 14:16:01.766604 23057 solver.cpp:218] Iteration 2748 (2.28994 iter/s, 5.2403s/12 iters), loss = 2.50739
I0406 14:16:01.766758 23057 solver.cpp:237]     Train net output #0: loss = 2.50739 (* 1 = 2.50739 loss)
I0406 14:16:01.766768 23057 sgd_solver.cpp:105] Iteration 2748, lr = 0.005
I0406 14:16:03.831889 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel
I0406 14:16:07.580619 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate
I0406 14:16:09.883821 23057 solver.cpp:330] Iteration 2754, Testing net (#0)
I0406 14:16:09.883843 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:16:12.906278 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:16:13.136446 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:16:14.224213 23057 solver.cpp:397]     Test net output #0: accuracy = 0.234681
I0406 14:16:14.224251 23057 solver.cpp:397]     Test net output #1: loss = 3.37232 (* 1 = 3.37232 loss)
I0406 14:16:16.179648 23057 solver.cpp:218] Iteration 2760 (0.832595 iter/s, 14.4128s/12 iters), loss = 2.39614
I0406 14:16:16.179697 23057 solver.cpp:237]     Train net output #0: loss = 2.39614 (* 1 = 2.39614 loss)
I0406 14:16:16.179703 23057 sgd_solver.cpp:105] Iteration 2760, lr = 0.005
I0406 14:16:21.368194 23057 solver.cpp:218] Iteration 2772 (2.31283 iter/s, 5.18844s/12 iters), loss = 2.41442
I0406 14:16:21.368237 23057 solver.cpp:237]     Train net output #0: loss = 2.41442 (* 1 = 2.41442 loss)
I0406 14:16:21.368242 23057 sgd_solver.cpp:105] Iteration 2772, lr = 0.005
I0406 14:16:26.553565 23057 solver.cpp:218] Iteration 2784 (2.31425 iter/s, 5.18527s/12 iters), loss = 2.1692
I0406 14:16:26.553620 23057 solver.cpp:237]     Train net output #0: loss = 2.1692 (* 1 = 2.1692 loss)
I0406 14:16:26.553629 23057 sgd_solver.cpp:105] Iteration 2784, lr = 0.005
I0406 14:16:31.700892 23057 solver.cpp:218] Iteration 2796 (2.33136 iter/s, 5.14722s/12 iters), loss = 2.27597
I0406 14:16:31.700947 23057 solver.cpp:237]     Train net output #0: loss = 2.27597 (* 1 = 2.27597 loss)
I0406 14:16:31.700956 23057 sgd_solver.cpp:105] Iteration 2796, lr = 0.005
I0406 14:16:37.057590 23057 solver.cpp:218] Iteration 2808 (2.24023 iter/s, 5.35659s/12 iters), loss = 2.37004
I0406 14:16:37.057701 23057 solver.cpp:237]     Train net output #0: loss = 2.37004 (* 1 = 2.37004 loss)
I0406 14:16:37.057708 23057 sgd_solver.cpp:105] Iteration 2808, lr = 0.005
I0406 14:16:42.211352 23057 solver.cpp:218] Iteration 2820 (2.32847 iter/s, 5.1536s/12 iters), loss = 1.9372
I0406 14:16:42.211414 23057 solver.cpp:237]     Train net output #0: loss = 1.9372 (* 1 = 1.9372 loss)
I0406 14:16:42.211424 23057 sgd_solver.cpp:105] Iteration 2820, lr = 0.005
I0406 14:16:47.114187 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:16:47.443182 23057 solver.cpp:218] Iteration 2832 (2.2937 iter/s, 5.23172s/12 iters), loss = 2.57034
I0406 14:16:47.443222 23057 solver.cpp:237]     Train net output #0: loss = 2.57034 (* 1 = 2.57034 loss)
I0406 14:16:47.443228 23057 sgd_solver.cpp:105] Iteration 2832, lr = 0.005
I0406 14:16:52.288307 23057 solver.cpp:218] Iteration 2844 (2.47676 iter/s, 4.84504s/12 iters), loss = 2.27333
I0406 14:16:52.288347 23057 solver.cpp:237]     Train net output #0: loss = 2.27333 (* 1 = 2.27333 loss)
I0406 14:16:52.288352 23057 sgd_solver.cpp:105] Iteration 2844, lr = 0.005
I0406 14:16:56.920512 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel
I0406 14:16:59.943969 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate
I0406 14:17:02.290699 23057 solver.cpp:330] Iteration 2856, Testing net (#0)
I0406 14:17:02.290729 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:17:05.484099 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:17:06.600862 23057 solver.cpp:397]     Test net output #0: accuracy = 0.257966
I0406 14:17:06.600906 23057 solver.cpp:397]     Test net output #1: loss = 3.29781 (* 1 = 3.29781 loss)
I0406 14:17:06.744264 23057 solver.cpp:218] Iteration 2856 (0.830117 iter/s, 14.4558s/12 iters), loss = 2.46608
I0406 14:17:06.745855 23057 solver.cpp:237]     Train net output #0: loss = 2.46608 (* 1 = 2.46608 loss)
I0406 14:17:06.745869 23057 sgd_solver.cpp:105] Iteration 2856, lr = 0.005
I0406 14:17:11.149428 23057 solver.cpp:218] Iteration 2868 (2.72509 iter/s, 4.40353s/12 iters), loss = 2.21089
I0406 14:17:11.149577 23057 solver.cpp:237]     Train net output #0: loss = 2.21089 (* 1 = 2.21089 loss)
I0406 14:17:11.149587 23057 sgd_solver.cpp:105] Iteration 2868, lr = 0.005
I0406 14:17:16.393573 23057 solver.cpp:218] Iteration 2880 (2.28835 iter/s, 5.24396s/12 iters), loss = 1.90644
I0406 14:17:16.393605 23057 solver.cpp:237]     Train net output #0: loss = 1.90644 (* 1 = 1.90644 loss)
I0406 14:17:16.393610 23057 sgd_solver.cpp:105] Iteration 2880, lr = 0.005
I0406 14:17:21.345155 23057 solver.cpp:218] Iteration 2892 (2.42351 iter/s, 4.9515s/12 iters), loss = 2.10887
I0406 14:17:21.345193 23057 solver.cpp:237]     Train net output #0: loss = 2.10887 (* 1 = 2.10887 loss)
I0406 14:17:21.345198 23057 sgd_solver.cpp:105] Iteration 2892, lr = 0.005
I0406 14:17:26.697293 23057 solver.cpp:218] Iteration 2904 (2.24213 iter/s, 5.35205s/12 iters), loss = 2.05805
I0406 14:17:26.697335 23057 solver.cpp:237]     Train net output #0: loss = 2.05805 (* 1 = 2.05805 loss)
I0406 14:17:26.697341 23057 sgd_solver.cpp:105] Iteration 2904, lr = 0.005
I0406 14:17:31.840545 23057 solver.cpp:218] Iteration 2916 (2.3332 iter/s, 5.14315s/12 iters), loss = 2.07096
I0406 14:17:31.840603 23057 solver.cpp:237]     Train net output #0: loss = 2.07096 (* 1 = 2.07096 loss)
I0406 14:17:31.840611 23057 sgd_solver.cpp:105] Iteration 2916, lr = 0.005
I0406 14:17:37.137863 23057 solver.cpp:218] Iteration 2928 (2.26535 iter/s, 5.2972s/12 iters), loss = 2.15034
I0406 14:17:37.137918 23057 solver.cpp:237]     Train net output #0: loss = 2.15034 (* 1 = 2.15034 loss)
I0406 14:17:37.137926 23057 sgd_solver.cpp:105] Iteration 2928, lr = 0.005
I0406 14:17:39.085232 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:17:42.502753 23057 solver.cpp:218] Iteration 2940 (2.23681 iter/s, 5.36478s/12 iters), loss = 1.98288
I0406 14:17:42.502851 23057 solver.cpp:237]     Train net output #0: loss = 1.98288 (* 1 = 1.98288 loss)
I0406 14:17:42.502857 23057 sgd_solver.cpp:105] Iteration 2940, lr = 0.005
I0406 14:17:47.817893 23057 solver.cpp:218] Iteration 2952 (2.25777 iter/s, 5.31499s/12 iters), loss = 2.04753
I0406 14:17:47.817929 23057 solver.cpp:237]     Train net output #0: loss = 2.04753 (* 1 = 2.04753 loss)
I0406 14:17:47.817935 23057 sgd_solver.cpp:105] Iteration 2952, lr = 0.005
I0406 14:17:50.106135 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel
I0406 14:17:53.127110 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate
I0406 14:17:55.474794 23057 solver.cpp:330] Iteration 2958, Testing net (#0)
I0406 14:17:55.474815 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:17:58.687618 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:17:59.872942 23057 solver.cpp:397]     Test net output #0: accuracy = 0.264093
I0406 14:17:59.872977 23057 solver.cpp:397]     Test net output #1: loss = 3.19376 (* 1 = 3.19376 loss)
I0406 14:18:01.778404 23057 solver.cpp:218] Iteration 2964 (0.859577 iter/s, 13.9604s/12 iters), loss = 2.16205
I0406 14:18:01.778470 23057 solver.cpp:237]     Train net output #0: loss = 2.16205 (* 1 = 2.16205 loss)
I0406 14:18:01.778478 23057 sgd_solver.cpp:105] Iteration 2964, lr = 0.005
I0406 14:18:07.159734 23057 solver.cpp:218] Iteration 2976 (2.22998 iter/s, 5.38121s/12 iters), loss = 1.87166
I0406 14:18:07.159792 23057 solver.cpp:237]     Train net output #0: loss = 1.87166 (* 1 = 1.87166 loss)
I0406 14:18:07.159801 23057 sgd_solver.cpp:105] Iteration 2976, lr = 0.005
I0406 14:18:12.327090 23057 solver.cpp:218] Iteration 2988 (2.32232 iter/s, 5.16724s/12 iters), loss = 1.80617
I0406 14:18:12.327138 23057 solver.cpp:237]     Train net output #0: loss = 1.80617 (* 1 = 1.80617 loss)
I0406 14:18:12.327147 23057 sgd_solver.cpp:105] Iteration 2988, lr = 0.005
I0406 14:18:17.512248 23057 solver.cpp:218] Iteration 3000 (2.31435 iter/s, 5.18505s/12 iters), loss = 2.08914
I0406 14:18:17.512677 23057 solver.cpp:237]     Train net output #0: loss = 2.08914 (* 1 = 2.08914 loss)
I0406 14:18:17.512687 23057 sgd_solver.cpp:105] Iteration 3000, lr = 0.005
I0406 14:18:22.576622 23057 solver.cpp:218] Iteration 3012 (2.36972 iter/s, 5.06389s/12 iters), loss = 2.05657
I0406 14:18:22.576686 23057 solver.cpp:237]     Train net output #0: loss = 2.05657 (* 1 = 2.05657 loss)
I0406 14:18:22.576699 23057 sgd_solver.cpp:105] Iteration 3012, lr = 0.005
I0406 14:18:27.851819 23057 solver.cpp:218] Iteration 3024 (2.27485 iter/s, 5.27508s/12 iters), loss = 2.06416
I0406 14:18:27.851867 23057 solver.cpp:237]     Train net output #0: loss = 2.06416 (* 1 = 2.06416 loss)
I0406 14:18:27.851876 23057 sgd_solver.cpp:105] Iteration 3024, lr = 0.005
I0406 14:18:32.079161 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:18:33.213582 23057 solver.cpp:218] Iteration 3036 (2.23811 iter/s, 5.36166s/12 iters), loss = 2.00434
I0406 14:18:33.213635 23057 solver.cpp:237]     Train net output #0: loss = 2.00434 (* 1 = 2.00434 loss)
I0406 14:18:33.213644 23057 sgd_solver.cpp:105] Iteration 3036, lr = 0.005
I0406 14:18:38.514281 23057 solver.cpp:218] Iteration 3048 (2.2639 iter/s, 5.30059s/12 iters), loss = 2.00918
I0406 14:18:38.514339 23057 solver.cpp:237]     Train net output #0: loss = 2.00918 (* 1 = 2.00918 loss)
I0406 14:18:38.514348 23057 sgd_solver.cpp:105] Iteration 3048, lr = 0.005
I0406 14:18:43.028362 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel
I0406 14:18:46.038964 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate
I0406 14:18:48.356321 23057 solver.cpp:330] Iteration 3060, Testing net (#0)
I0406 14:18:48.356400 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:18:51.514029 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:18:52.741884 23057 solver.cpp:397]     Test net output #0: accuracy = 0.292279
I0406 14:18:52.741916 23057 solver.cpp:397]     Test net output #1: loss = 3.21776 (* 1 = 3.21776 loss)
I0406 14:18:52.882421 23057 solver.cpp:218] Iteration 3060 (0.835191 iter/s, 14.368s/12 iters), loss = 2.04399
I0406 14:18:52.883983 23057 solver.cpp:237]     Train net output #0: loss = 2.04399 (* 1 = 2.04399 loss)
I0406 14:18:52.883994 23057 sgd_solver.cpp:105] Iteration 3060, lr = 0.005
I0406 14:18:57.348026 23057 solver.cpp:218] Iteration 3072 (2.68817 iter/s, 4.464s/12 iters), loss = 1.92297
I0406 14:18:57.348083 23057 solver.cpp:237]     Train net output #0: loss = 1.92297 (* 1 = 1.92297 loss)
I0406 14:18:57.348093 23057 sgd_solver.cpp:105] Iteration 3072, lr = 0.005
I0406 14:19:02.634043 23057 solver.cpp:218] Iteration 3084 (2.27019 iter/s, 5.28591s/12 iters), loss = 1.82336
I0406 14:19:02.634085 23057 solver.cpp:237]     Train net output #0: loss = 1.82336 (* 1 = 1.82336 loss)
I0406 14:19:02.634091 23057 sgd_solver.cpp:105] Iteration 3084, lr = 0.005
I0406 14:19:08.086206 23057 solver.cpp:218] Iteration 3096 (2.201 iter/s, 5.45206s/12 iters), loss = 1.76157
I0406 14:19:08.086249 23057 solver.cpp:237]     Train net output #0: loss = 1.76157 (* 1 = 1.76157 loss)
I0406 14:19:08.086256 23057 sgd_solver.cpp:105] Iteration 3096, lr = 0.005
I0406 14:19:13.101709 23057 solver.cpp:218] Iteration 3108 (2.39263 iter/s, 5.01541s/12 iters), loss = 1.69686
I0406 14:19:13.101749 23057 solver.cpp:237]     Train net output #0: loss = 1.69686 (* 1 = 1.69686 loss)
I0406 14:19:13.101756 23057 sgd_solver.cpp:105] Iteration 3108, lr = 0.005
I0406 14:19:18.266944 23057 solver.cpp:218] Iteration 3120 (2.32327 iter/s, 5.16514s/12 iters), loss = 2.01751
I0406 14:19:18.266986 23057 solver.cpp:237]     Train net output #0: loss = 2.01751 (* 1 = 2.01751 loss)
I0406 14:19:18.266993 23057 sgd_solver.cpp:105] Iteration 3120, lr = 0.005
I0406 14:19:23.565176 23057 solver.cpp:218] Iteration 3132 (2.26495 iter/s, 5.29814s/12 iters), loss = 2.03541
I0406 14:19:23.565286 23057 solver.cpp:237]     Train net output #0: loss = 2.03541 (* 1 = 2.03541 loss)
I0406 14:19:23.565292 23057 sgd_solver.cpp:105] Iteration 3132, lr = 0.005
I0406 14:19:24.673162 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:19:28.919180 23057 solver.cpp:218] Iteration 3144 (2.24138 iter/s, 5.35384s/12 iters), loss = 1.54881
I0406 14:19:28.919231 23057 solver.cpp:237]     Train net output #0: loss = 1.54881 (* 1 = 1.54881 loss)
I0406 14:19:28.919240 23057 sgd_solver.cpp:105] Iteration 3144, lr = 0.005
I0406 14:19:34.085456 23057 solver.cpp:218] Iteration 3156 (2.3228 iter/s, 5.16617s/12 iters), loss = 2.0686
I0406 14:19:34.085507 23057 solver.cpp:237]     Train net output #0: loss = 2.0686 (* 1 = 2.0686 loss)
I0406 14:19:34.085513 23057 sgd_solver.cpp:105] Iteration 3156, lr = 0.005
I0406 14:19:36.129391 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel
I0406 14:19:39.134938 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate
I0406 14:19:42.486289 23057 solver.cpp:330] Iteration 3162, Testing net (#0)
I0406 14:19:42.486315 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:19:45.557735 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:19:46.842443 23057 solver.cpp:397]     Test net output #0: accuracy = 0.28125
I0406 14:19:46.842484 23057 solver.cpp:397]     Test net output #1: loss = 3.17817 (* 1 = 3.17817 loss)
I0406 14:19:48.689112 23057 solver.cpp:218] Iteration 3168 (0.821722 iter/s, 14.6035s/12 iters), loss = 1.94302
I0406 14:19:48.689182 23057 solver.cpp:237]     Train net output #0: loss = 1.94302 (* 1 = 1.94302 loss)
I0406 14:19:48.689193 23057 sgd_solver.cpp:105] Iteration 3168, lr = 0.005
I0406 14:19:53.946632 23057 solver.cpp:218] Iteration 3180 (2.2825 iter/s, 5.2574s/12 iters), loss = 1.65571
I0406 14:19:53.946722 23057 solver.cpp:237]     Train net output #0: loss = 1.65571 (* 1 = 1.65571 loss)
I0406 14:19:53.946728 23057 sgd_solver.cpp:105] Iteration 3180, lr = 0.005
I0406 14:19:59.310093 23057 solver.cpp:218] Iteration 3192 (2.23742 iter/s, 5.36332s/12 iters), loss = 1.44276
I0406 14:19:59.310134 23057 solver.cpp:237]     Train net output #0: loss = 1.44276 (* 1 = 1.44276 loss)
I0406 14:19:59.310140 23057 sgd_solver.cpp:105] Iteration 3192, lr = 0.005
I0406 14:20:04.452414 23057 solver.cpp:218] Iteration 3204 (2.33362 iter/s, 5.14223s/12 iters), loss = 1.66742
I0406 14:20:04.452455 23057 solver.cpp:237]     Train net output #0: loss = 1.66742 (* 1 = 1.66742 loss)
I0406 14:20:04.452461 23057 sgd_solver.cpp:105] Iteration 3204, lr = 0.005
I0406 14:20:09.899106 23057 solver.cpp:218] Iteration 3216 (2.20321 iter/s, 5.44659s/12 iters), loss = 2.13615
I0406 14:20:09.899147 23057 solver.cpp:237]     Train net output #0: loss = 2.13615 (* 1 = 2.13615 loss)
I0406 14:20:09.899152 23057 sgd_solver.cpp:105] Iteration 3216, lr = 0.005
I0406 14:20:15.250047 23057 solver.cpp:218] Iteration 3228 (2.24263 iter/s, 5.35085s/12 iters), loss = 1.63261
I0406 14:20:15.250085 23057 solver.cpp:237]     Train net output #0: loss = 1.63261 (* 1 = 1.63261 loss)
I0406 14:20:15.250092 23057 sgd_solver.cpp:105] Iteration 3228, lr = 0.005
I0406 14:20:18.511173 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:20:20.445669 23057 solver.cpp:218] Iteration 3240 (2.30968 iter/s, 5.19552s/12 iters), loss = 1.61134
I0406 14:20:20.445713 23057 solver.cpp:237]     Train net output #0: loss = 1.61134 (* 1 = 1.61134 loss)
I0406 14:20:20.445719 23057 sgd_solver.cpp:105] Iteration 3240, lr = 0.005
I0406 14:20:25.719460 23057 solver.cpp:218] Iteration 3252 (2.27545 iter/s, 5.27369s/12 iters), loss = 1.70344
I0406 14:20:25.719597 23057 solver.cpp:237]     Train net output #0: loss = 1.70344 (* 1 = 1.70344 loss)
I0406 14:20:25.719604 23057 sgd_solver.cpp:105] Iteration 3252, lr = 0.005
I0406 14:20:30.636979 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel
I0406 14:20:35.258064 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate
I0406 14:20:37.586431 23057 solver.cpp:330] Iteration 3264, Testing net (#0)
I0406 14:20:37.586452 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:20:40.659019 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:20:41.942912 23057 solver.cpp:397]     Test net output #0: accuracy = 0.286152
I0406 14:20:41.942939 23057 solver.cpp:397]     Test net output #1: loss = 3.24972 (* 1 = 3.24972 loss)
I0406 14:20:42.081851 23057 solver.cpp:218] Iteration 3264 (0.733401 iter/s, 16.3621s/12 iters), loss = 1.61228
I0406 14:20:42.083458 23057 solver.cpp:237]     Train net output #0: loss = 1.61228 (* 1 = 1.61228 loss)
I0406 14:20:42.083473 23057 sgd_solver.cpp:105] Iteration 3264, lr = 0.005
I0406 14:20:46.285138 23057 solver.cpp:218] Iteration 3276 (2.85603 iter/s, 4.20164s/12 iters), loss = 2.03475
I0406 14:20:46.285181 23057 solver.cpp:237]     Train net output #0: loss = 2.03475 (* 1 = 2.03475 loss)
I0406 14:20:46.285187 23057 sgd_solver.cpp:105] Iteration 3276, lr = 0.005
I0406 14:20:51.641921 23057 solver.cpp:218] Iteration 3288 (2.24019 iter/s, 5.35668s/12 iters), loss = 1.91407
I0406 14:20:51.641961 23057 solver.cpp:237]     Train net output #0: loss = 1.91407 (* 1 = 1.91407 loss)
I0406 14:20:51.641968 23057 sgd_solver.cpp:105] Iteration 3288, lr = 0.005
I0406 14:20:57.043735 23057 solver.cpp:218] Iteration 3300 (2.22152 iter/s, 5.40171s/12 iters), loss = 1.55277
I0406 14:20:57.043865 23057 solver.cpp:237]     Train net output #0: loss = 1.55277 (* 1 = 1.55277 loss)
I0406 14:20:57.043874 23057 sgd_solver.cpp:105] Iteration 3300, lr = 0.005
I0406 14:21:02.441066 23057 solver.cpp:218] Iteration 3312 (2.2234 iter/s, 5.39714s/12 iters), loss = 2.00954
I0406 14:21:02.441121 23057 solver.cpp:237]     Train net output #0: loss = 2.00954 (* 1 = 2.00954 loss)
I0406 14:21:02.441129 23057 sgd_solver.cpp:105] Iteration 3312, lr = 0.005
I0406 14:21:07.682643 23057 solver.cpp:218] Iteration 3324 (2.28944 iter/s, 5.24146s/12 iters), loss = 2.11673
I0406 14:21:07.682706 23057 solver.cpp:237]     Train net output #0: loss = 2.11673 (* 1 = 2.11673 loss)
I0406 14:21:07.682716 23057 sgd_solver.cpp:105] Iteration 3324, lr = 0.005
I0406 14:21:13.151278 23057 solver.cpp:218] Iteration 3336 (2.19438 iter/s, 5.46852s/12 iters), loss = 1.38865
I0406 14:21:13.151320 23057 solver.cpp:237]     Train net output #0: loss = 1.38865 (* 1 = 1.38865 loss)
I0406 14:21:13.151326 23057 sgd_solver.cpp:105] Iteration 3336, lr = 0.005
I0406 14:21:13.646456 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:21:18.541772 23057 solver.cpp:218] Iteration 3348 (2.22618 iter/s, 5.39039s/12 iters), loss = 1.93665
I0406 14:21:18.541824 23057 solver.cpp:237]     Train net output #0: loss = 1.93665 (* 1 = 1.93665 loss)
I0406 14:21:18.541832 23057 sgd_solver.cpp:105] Iteration 3348, lr = 0.005
I0406 14:21:23.784518 23057 solver.cpp:218] Iteration 3360 (2.28892 iter/s, 5.24264s/12 iters), loss = 1.65947
I0406 14:21:23.784554 23057 solver.cpp:237]     Train net output #0: loss = 1.65947 (* 1 = 1.65947 loss)
I0406 14:21:23.784559 23057 sgd_solver.cpp:105] Iteration 3360, lr = 0.005
I0406 14:21:25.931797 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel
I0406 14:21:28.966336 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate
I0406 14:21:31.260855 23057 solver.cpp:330] Iteration 3366, Testing net (#0)
I0406 14:21:31.260874 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:21:34.314613 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:21:35.667958 23057 solver.cpp:397]     Test net output #0: accuracy = 0.288603
I0406 14:21:35.668005 23057 solver.cpp:397]     Test net output #1: loss = 3.1768 (* 1 = 3.1768 loss)
I0406 14:21:37.534962 23057 solver.cpp:218] Iteration 3372 (0.872709 iter/s, 13.7503s/12 iters), loss = 1.52868
I0406 14:21:37.535027 23057 solver.cpp:237]     Train net output #0: loss = 1.52868 (* 1 = 1.52868 loss)
I0406 14:21:37.535035 23057 sgd_solver.cpp:105] Iteration 3372, lr = 0.005
I0406 14:21:42.829519 23057 solver.cpp:218] Iteration 3384 (2.26653 iter/s, 5.29443s/12 iters), loss = 1.42947
I0406 14:21:42.829578 23057 solver.cpp:237]     Train net output #0: loss = 1.42947 (* 1 = 1.42947 loss)
I0406 14:21:42.829587 23057 sgd_solver.cpp:105] Iteration 3384, lr = 0.005
I0406 14:21:48.053020 23057 solver.cpp:218] Iteration 3396 (2.29736 iter/s, 5.22339s/12 iters), loss = 1.78905
I0406 14:21:48.053061 23057 solver.cpp:237]     Train net output #0: loss = 1.78905 (* 1 = 1.78905 loss)
I0406 14:21:48.053066 23057 sgd_solver.cpp:105] Iteration 3396, lr = 0.005
I0406 14:21:53.287245 23057 solver.cpp:218] Iteration 3408 (2.29265 iter/s, 5.23413s/12 iters), loss = 1.51769
I0406 14:21:53.287300 23057 solver.cpp:237]     Train net output #0: loss = 1.51769 (* 1 = 1.51769 loss)
I0406 14:21:53.287310 23057 sgd_solver.cpp:105] Iteration 3408, lr = 0.005
I0406 14:21:58.599305 23057 solver.cpp:218] Iteration 3420 (2.25906 iter/s, 5.31195s/12 iters), loss = 1.70018
I0406 14:21:58.599356 23057 solver.cpp:237]     Train net output #0: loss = 1.70018 (* 1 = 1.70018 loss)
I0406 14:21:58.599364 23057 sgd_solver.cpp:105] Iteration 3420, lr = 0.005
I0406 14:22:03.862890 23057 solver.cpp:218] Iteration 3432 (2.27986 iter/s, 5.26348s/12 iters), loss = 1.87172
I0406 14:22:03.863016 23057 solver.cpp:237]     Train net output #0: loss = 1.87172 (* 1 = 1.87172 loss)
I0406 14:22:03.863025 23057 sgd_solver.cpp:105] Iteration 3432, lr = 0.005
I0406 14:22:06.633322 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:22:09.265525 23057 solver.cpp:218] Iteration 3444 (2.22121 iter/s, 5.40246s/12 iters), loss = 1.80599
I0406 14:22:09.265564 23057 solver.cpp:237]     Train net output #0: loss = 1.80599 (* 1 = 1.80599 loss)
I0406 14:22:09.265570 23057 sgd_solver.cpp:105] Iteration 3444, lr = 0.005
I0406 14:22:14.470988 23057 solver.cpp:218] Iteration 3456 (2.30531 iter/s, 5.20537s/12 iters), loss = 1.71338
I0406 14:22:14.471032 23057 solver.cpp:237]     Train net output #0: loss = 1.71338 (* 1 = 1.71338 loss)
I0406 14:22:14.471037 23057 sgd_solver.cpp:105] Iteration 3456, lr = 0.005
I0406 14:22:19.303028 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel
I0406 14:22:22.400468 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate
I0406 14:22:24.705502 23057 solver.cpp:330] Iteration 3468, Testing net (#0)
I0406 14:22:24.705528 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:22:25.100023 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:22:27.812834 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:22:29.186830 23057 solver.cpp:397]     Test net output #0: accuracy = 0.282476
I0406 14:22:29.186867 23057 solver.cpp:397]     Test net output #1: loss = 3.18699 (* 1 = 3.18699 loss)
I0406 14:22:29.329988 23057 solver.cpp:218] Iteration 3468 (0.8076 iter/s, 14.8588s/12 iters), loss = 1.76353
I0406 14:22:29.331552 23057 solver.cpp:237]     Train net output #0: loss = 1.76353 (* 1 = 1.76353 loss)
I0406 14:22:29.331562 23057 sgd_solver.cpp:105] Iteration 3468, lr = 0.005
I0406 14:22:33.655148 23057 solver.cpp:218] Iteration 3480 (2.7755 iter/s, 4.32355s/12 iters), loss = 1.34028
I0406 14:22:33.655194 23057 solver.cpp:237]     Train net output #0: loss = 1.34028 (* 1 = 1.34028 loss)
I0406 14:22:33.655202 23057 sgd_solver.cpp:105] Iteration 3480, lr = 0.005
I0406 14:22:39.049835 23057 solver.cpp:218] Iteration 3492 (2.22445 iter/s, 5.39459s/12 iters), loss = 1.47812
I0406 14:22:39.049973 23057 solver.cpp:237]     Train net output #0: loss = 1.47812 (* 1 = 1.47812 loss)
I0406 14:22:39.049983 23057 sgd_solver.cpp:105] Iteration 3492, lr = 0.005
I0406 14:22:44.087278 23057 solver.cpp:218] Iteration 3504 (2.38225 iter/s, 5.03725s/12 iters), loss = 1.3246
I0406 14:22:44.087319 23057 solver.cpp:237]     Train net output #0: loss = 1.3246 (* 1 = 1.3246 loss)
I0406 14:22:44.087325 23057 sgd_solver.cpp:105] Iteration 3504, lr = 0.005
I0406 14:22:49.351573 23057 solver.cpp:218] Iteration 3516 (2.27955 iter/s, 5.2642s/12 iters), loss = 1.44937
I0406 14:22:49.351626 23057 solver.cpp:237]     Train net output #0: loss = 1.44937 (* 1 = 1.44937 loss)
I0406 14:22:49.351635 23057 sgd_solver.cpp:105] Iteration 3516, lr = 0.005
I0406 14:22:54.541507 23057 solver.cpp:218] Iteration 3528 (2.31222 iter/s, 5.18983s/12 iters), loss = 2.02869
I0406 14:22:54.541558 23057 solver.cpp:237]     Train net output #0: loss = 2.02869 (* 1 = 2.02869 loss)
I0406 14:22:54.541566 23057 sgd_solver.cpp:105] Iteration 3528, lr = 0.005
I0406 14:22:59.563627 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:22:59.865437 23057 solver.cpp:218] Iteration 3540 (2.25402 iter/s, 5.32382s/12 iters), loss = 1.34948
I0406 14:22:59.865492 23057 solver.cpp:237]     Train net output #0: loss = 1.34948 (* 1 = 1.34948 loss)
I0406 14:22:59.865501 23057 sgd_solver.cpp:105] Iteration 3540, lr = 0.005
I0406 14:23:05.084987 23057 solver.cpp:218] Iteration 3552 (2.2991 iter/s, 5.21944s/12 iters), loss = 1.66334
I0406 14:23:05.085026 23057 solver.cpp:237]     Train net output #0: loss = 1.66334 (* 1 = 1.66334 loss)
I0406 14:23:05.085032 23057 sgd_solver.cpp:105] Iteration 3552, lr = 0.005
I0406 14:23:10.395637 23057 solver.cpp:218] Iteration 3564 (2.25965 iter/s, 5.31055s/12 iters), loss = 1.4796
I0406 14:23:10.395731 23057 solver.cpp:237]     Train net output #0: loss = 1.4796 (* 1 = 1.4796 loss)
I0406 14:23:10.395737 23057 sgd_solver.cpp:105] Iteration 3564, lr = 0.005
I0406 14:23:12.497270 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel
I0406 14:23:15.521970 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate
I0406 14:23:17.824242 23057 solver.cpp:330] Iteration 3570, Testing net (#0)
I0406 14:23:17.824262 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:23:20.795387 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:23:22.250361 23057 solver.cpp:397]     Test net output #0: accuracy = 0.26348
I0406 14:23:22.250391 23057 solver.cpp:397]     Test net output #1: loss = 3.27115 (* 1 = 3.27115 loss)
I0406 14:23:24.311206 23057 solver.cpp:218] Iteration 3576 (0.862357 iter/s, 13.9154s/12 iters), loss = 1.53914
I0406 14:23:24.311251 23057 solver.cpp:237]     Train net output #0: loss = 1.53914 (* 1 = 1.53914 loss)
I0406 14:23:24.311257 23057 sgd_solver.cpp:105] Iteration 3576, lr = 0.005
I0406 14:23:29.402022 23057 solver.cpp:218] Iteration 3588 (2.35723 iter/s, 5.09072s/12 iters), loss = 1.35873
I0406 14:23:29.402061 23057 solver.cpp:237]     Train net output #0: loss = 1.35873 (* 1 = 1.35873 loss)
I0406 14:23:29.402068 23057 sgd_solver.cpp:105] Iteration 3588, lr = 0.005
I0406 14:23:34.619271 23057 solver.cpp:218] Iteration 3600 (2.30011 iter/s, 5.21715s/12 iters), loss = 1.38628
I0406 14:23:34.619331 23057 solver.cpp:237]     Train net output #0: loss = 1.38628 (* 1 = 1.38628 loss)
I0406 14:23:34.619341 23057 sgd_solver.cpp:105] Iteration 3600, lr = 0.005
I0406 14:23:40.016746 23057 solver.cpp:218] Iteration 3612 (2.22331 iter/s, 5.39736s/12 iters), loss = 1.46187
I0406 14:23:40.016785 23057 solver.cpp:237]     Train net output #0: loss = 1.46187 (* 1 = 1.46187 loss)
I0406 14:23:40.016791 23057 sgd_solver.cpp:105] Iteration 3612, lr = 0.005
I0406 14:23:45.464000 23057 solver.cpp:218] Iteration 3624 (2.20298 iter/s, 5.44716s/12 iters), loss = 1.35665
I0406 14:23:45.464130 23057 solver.cpp:237]     Train net output #0: loss = 1.35665 (* 1 = 1.35665 loss)
I0406 14:23:45.464136 23057 sgd_solver.cpp:105] Iteration 3624, lr = 0.005
I0406 14:23:50.727030 23057 solver.cpp:218] Iteration 3636 (2.28013 iter/s, 5.26285s/12 iters), loss = 1.71357
I0406 14:23:50.727070 23057 solver.cpp:237]     Train net output #0: loss = 1.71357 (* 1 = 1.71357 loss)
I0406 14:23:50.727077 23057 sgd_solver.cpp:105] Iteration 3636, lr = 0.005
I0406 14:23:52.718616 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:23:56.049612 23057 solver.cpp:218] Iteration 3648 (2.25459 iter/s, 5.32249s/12 iters), loss = 1.32084
I0406 14:23:56.049654 23057 solver.cpp:237]     Train net output #0: loss = 1.32084 (* 1 = 1.32084 loss)
I0406 14:23:56.049659 23057 sgd_solver.cpp:105] Iteration 3648, lr = 0.005
I0406 14:24:01.292791 23057 solver.cpp:218] Iteration 3660 (2.28873 iter/s, 5.24308s/12 iters), loss = 1.4592
I0406 14:24:01.292840 23057 solver.cpp:237]     Train net output #0: loss = 1.4592 (* 1 = 1.4592 loss)
I0406 14:24:01.292847 23057 sgd_solver.cpp:105] Iteration 3660, lr = 0.005
I0406 14:24:06.189200 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel
I0406 14:24:09.224547 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate
I0406 14:24:11.537329 23057 solver.cpp:330] Iteration 3672, Testing net (#0)
I0406 14:24:11.537345 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:24:14.487232 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:24:15.938418 23057 solver.cpp:397]     Test net output #0: accuracy = 0.281863
I0406 14:24:15.938519 23057 solver.cpp:397]     Test net output #1: loss = 3.25431 (* 1 = 3.25431 loss)
I0406 14:24:16.077984 23057 solver.cpp:218] Iteration 3672 (0.811632 iter/s, 14.785s/12 iters), loss = 1.39484
I0406 14:24:16.078042 23057 solver.cpp:237]     Train net output #0: loss = 1.39484 (* 1 = 1.39484 loss)
I0406 14:24:16.078047 23057 sgd_solver.cpp:105] Iteration 3672, lr = 0.005
I0406 14:24:20.439846 23057 solver.cpp:218] Iteration 3684 (2.75119 iter/s, 4.36175s/12 iters), loss = 1.27007
I0406 14:24:20.439904 23057 solver.cpp:237]     Train net output #0: loss = 1.27007 (* 1 = 1.27007 loss)
I0406 14:24:20.439913 23057 sgd_solver.cpp:105] Iteration 3684, lr = 0.005
I0406 14:24:25.792654 23057 solver.cpp:218] Iteration 3696 (2.24186 iter/s, 5.3527s/12 iters), loss = 1.51101
I0406 14:24:25.792697 23057 solver.cpp:237]     Train net output #0: loss = 1.51101 (* 1 = 1.51101 loss)
I0406 14:24:25.792703 23057 sgd_solver.cpp:105] Iteration 3696, lr = 0.005
I0406 14:24:31.054438 23057 solver.cpp:218] Iteration 3708 (2.28064 iter/s, 5.26168s/12 iters), loss = 1.23754
I0406 14:24:31.054499 23057 solver.cpp:237]     Train net output #0: loss = 1.23754 (* 1 = 1.23754 loss)
I0406 14:24:31.054509 23057 sgd_solver.cpp:105] Iteration 3708, lr = 0.005
I0406 14:24:36.183267 23057 solver.cpp:218] Iteration 3720 (2.33977 iter/s, 5.12872s/12 iters), loss = 1.21978
I0406 14:24:36.183312 23057 solver.cpp:237]     Train net output #0: loss = 1.21978 (* 1 = 1.21978 loss)
I0406 14:24:36.183320 23057 sgd_solver.cpp:105] Iteration 3720, lr = 0.005
I0406 14:24:41.343891 23057 solver.cpp:218] Iteration 3732 (2.32535 iter/s, 5.16052s/12 iters), loss = 1.67184
I0406 14:24:41.343936 23057 solver.cpp:237]     Train net output #0: loss = 1.67184 (* 1 = 1.67184 loss)
I0406 14:24:41.343943 23057 sgd_solver.cpp:105] Iteration 3732, lr = 0.005
I0406 14:24:45.536487 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:24:46.608319 23057 solver.cpp:218] Iteration 3744 (2.2795 iter/s, 5.26432s/12 iters), loss = 1.61407
I0406 14:24:46.609231 23057 solver.cpp:237]     Train net output #0: loss = 1.61407 (* 1 = 1.61407 loss)
I0406 14:24:46.609241 23057 sgd_solver.cpp:105] Iteration 3744, lr = 0.005
I0406 14:24:51.796741 23057 solver.cpp:218] Iteration 3756 (2.31327 iter/s, 5.18747s/12 iters), loss = 1.46747
I0406 14:24:51.796778 23057 solver.cpp:237]     Train net output #0: loss = 1.46747 (* 1 = 1.46747 loss)
I0406 14:24:51.796783 23057 sgd_solver.cpp:105] Iteration 3756, lr = 0.005
I0406 14:24:56.942703 23057 solver.cpp:218] Iteration 3768 (2.33205 iter/s, 5.14568s/12 iters), loss = 1.49039
I0406 14:24:56.942741 23057 solver.cpp:237]     Train net output #0: loss = 1.49039 (* 1 = 1.49039 loss)
I0406 14:24:56.942747 23057 sgd_solver.cpp:105] Iteration 3768, lr = 0.005
I0406 14:24:59.128144 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel
I0406 14:25:02.272878 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate
I0406 14:25:04.694366 23057 solver.cpp:330] Iteration 3774, Testing net (#0)
I0406 14:25:04.694386 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:25:07.540839 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:25:08.999316 23057 solver.cpp:397]     Test net output #0: accuracy = 0.291667
I0406 14:25:08.999349 23057 solver.cpp:397]     Test net output #1: loss = 3.26219 (* 1 = 3.26219 loss)
I0406 14:25:10.963124 23057 solver.cpp:218] Iteration 3780 (0.855904 iter/s, 14.0203s/12 iters), loss = 1.33924
I0406 14:25:10.963171 23057 solver.cpp:237]     Train net output #0: loss = 1.33924 (* 1 = 1.33924 loss)
I0406 14:25:10.963177 23057 sgd_solver.cpp:105] Iteration 3780, lr = 0.005
I0406 14:25:16.106179 23057 solver.cpp:218] Iteration 3792 (2.33329 iter/s, 5.14296s/12 iters), loss = 1.24487
I0406 14:25:16.106215 23057 solver.cpp:237]     Train net output #0: loss = 1.24487 (* 1 = 1.24487 loss)
I0406 14:25:16.106220 23057 sgd_solver.cpp:105] Iteration 3792, lr = 0.005
I0406 14:25:21.656932 23057 solver.cpp:218] Iteration 3804 (2.16191 iter/s, 5.55066s/12 iters), loss = 1.41398
I0406 14:25:21.657048 23057 solver.cpp:237]     Train net output #0: loss = 1.41398 (* 1 = 1.41398 loss)
I0406 14:25:21.657058 23057 sgd_solver.cpp:105] Iteration 3804, lr = 0.005
I0406 14:25:26.770483 23057 solver.cpp:218] Iteration 3816 (2.34678 iter/s, 5.11338s/12 iters), loss = 1.18146
I0406 14:25:26.770526 23057 solver.cpp:237]     Train net output #0: loss = 1.18146 (* 1 = 1.18146 loss)
I0406 14:25:26.770532 23057 sgd_solver.cpp:105] Iteration 3816, lr = 0.005
I0406 14:25:31.896592 23057 solver.cpp:218] Iteration 3828 (2.341 iter/s, 5.12601s/12 iters), loss = 1.19938
I0406 14:25:31.896646 23057 solver.cpp:237]     Train net output #0: loss = 1.19938 (* 1 = 1.19938 loss)
I0406 14:25:31.896656 23057 sgd_solver.cpp:105] Iteration 3828, lr = 0.005
I0406 14:25:37.255141 23057 solver.cpp:218] Iteration 3840 (2.23946 iter/s, 5.35844s/12 iters), loss = 1.49882
I0406 14:25:37.255182 23057 solver.cpp:237]     Train net output #0: loss = 1.49882 (* 1 = 1.49882 loss)
I0406 14:25:37.255187 23057 sgd_solver.cpp:105] Iteration 3840, lr = 0.005
I0406 14:25:38.391026 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:25:42.551328 23057 solver.cpp:218] Iteration 3852 (2.26583 iter/s, 5.29608s/12 iters), loss = 1.03603
I0406 14:25:42.551383 23057 solver.cpp:237]     Train net output #0: loss = 1.03603 (* 1 = 1.03603 loss)
I0406 14:25:42.551390 23057 sgd_solver.cpp:105] Iteration 3852, lr = 0.005
I0406 14:25:48.000921 23057 solver.cpp:218] Iteration 3864 (2.20204 iter/s, 5.44949s/12 iters), loss = 1.47606
I0406 14:25:48.000967 23057 solver.cpp:237]     Train net output #0: loss = 1.47606 (* 1 = 1.47606 loss)
I0406 14:25:48.000974 23057 sgd_solver.cpp:105] Iteration 3864, lr = 0.005
I0406 14:25:52.603999 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel
I0406 14:25:55.575480 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate
I0406 14:25:57.881482 23057 solver.cpp:330] Iteration 3876, Testing net (#0)
I0406 14:25:57.881506 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:26:00.681314 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:26:02.225425 23057 solver.cpp:397]     Test net output #0: accuracy = 0.291667
I0406 14:26:02.225461 23057 solver.cpp:397]     Test net output #1: loss = 3.31164 (* 1 = 3.31164 loss)
I0406 14:26:02.365774 23057 solver.cpp:218] Iteration 3876 (0.835382 iter/s, 14.3647s/12 iters), loss = 1.48014
I0406 14:26:02.365837 23057 solver.cpp:237]     Train net output #0: loss = 1.48014 (* 1 = 1.48014 loss)
I0406 14:26:02.365845 23057 sgd_solver.cpp:105] Iteration 3876, lr = 0.005
I0406 14:26:06.758992 23057 solver.cpp:218] Iteration 3888 (2.73155 iter/s, 4.39311s/12 iters), loss = 1.40883
I0406 14:26:06.759047 23057 solver.cpp:237]     Train net output #0: loss = 1.40883 (* 1 = 1.40883 loss)
I0406 14:26:06.759057 23057 sgd_solver.cpp:105] Iteration 3888, lr = 0.005
I0406 14:26:12.183064 23057 solver.cpp:218] Iteration 3900 (2.21241 iter/s, 5.42396s/12 iters), loss = 1.09819
I0406 14:26:12.183121 23057 solver.cpp:237]     Train net output #0: loss = 1.09819 (* 1 = 1.09819 loss)
I0406 14:26:12.183130 23057 sgd_solver.cpp:105] Iteration 3900, lr = 0.005
I0406 14:26:17.557982 23057 solver.cpp:218] Iteration 3912 (2.23264 iter/s, 5.3748s/12 iters), loss = 1.2868
I0406 14:26:17.558037 23057 solver.cpp:237]     Train net output #0: loss = 1.2868 (* 1 = 1.2868 loss)
I0406 14:26:17.558046 23057 sgd_solver.cpp:105] Iteration 3912, lr = 0.005
I0406 14:26:22.720083 23057 solver.cpp:218] Iteration 3924 (2.32468 iter/s, 5.16199s/12 iters), loss = 1.45986
I0406 14:26:22.720196 23057 solver.cpp:237]     Train net output #0: loss = 1.45986 (* 1 = 1.45986 loss)
I0406 14:26:22.720206 23057 sgd_solver.cpp:105] Iteration 3924, lr = 0.005
I0406 14:26:27.834486 23057 solver.cpp:218] Iteration 3936 (2.34639 iter/s, 5.11425s/12 iters), loss = 1.37952
I0406 14:26:27.834523 23057 solver.cpp:237]     Train net output #0: loss = 1.37952 (* 1 = 1.37952 loss)
I0406 14:26:27.834528 23057 sgd_solver.cpp:105] Iteration 3936, lr = 0.005
I0406 14:26:31.438587 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:26:33.100227 23057 solver.cpp:218] Iteration 3948 (2.27892 iter/s, 5.26566s/12 iters), loss = 1.31351
I0406 14:26:33.100260 23057 solver.cpp:237]     Train net output #0: loss = 1.31351 (* 1 = 1.31351 loss)
I0406 14:26:33.100266 23057 sgd_solver.cpp:105] Iteration 3948, lr = 0.005
I0406 14:26:38.233224 23057 solver.cpp:218] Iteration 3960 (2.33786 iter/s, 5.13291s/12 iters), loss = 1.39438
I0406 14:26:38.233274 23057 solver.cpp:237]     Train net output #0: loss = 1.39438 (* 1 = 1.39438 loss)
I0406 14:26:38.233281 23057 sgd_solver.cpp:105] Iteration 3960, lr = 0.005
I0406 14:26:43.448787 23057 solver.cpp:218] Iteration 3972 (2.30085 iter/s, 5.21546s/12 iters), loss = 1.15096
I0406 14:26:43.448824 23057 solver.cpp:237]     Train net output #0: loss = 1.15096 (* 1 = 1.15096 loss)
I0406 14:26:43.448830 23057 sgd_solver.cpp:105] Iteration 3972, lr = 0.005
I0406 14:26:45.612521 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel
I0406 14:26:48.617725 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate
I0406 14:26:51.572242 23057 solver.cpp:330] Iteration 3978, Testing net (#0)
I0406 14:26:51.572261 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:26:54.343248 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:26:55.886886 23057 solver.cpp:397]     Test net output #0: accuracy = 0.294118
I0406 14:26:55.886920 23057 solver.cpp:397]     Test net output #1: loss = 3.30565 (* 1 = 3.30565 loss)
I0406 14:26:57.842298 23057 solver.cpp:218] Iteration 3984 (0.833718 iter/s, 14.3934s/12 iters), loss = 1.25055
I0406 14:26:57.842345 23057 solver.cpp:237]     Train net output #0: loss = 1.25055 (* 1 = 1.25055 loss)
I0406 14:26:57.842352 23057 sgd_solver.cpp:105] Iteration 3984, lr = 0.005
I0406 14:27:02.945125 23057 solver.cpp:218] Iteration 3996 (2.35169 iter/s, 5.10272s/12 iters), loss = 1.14734
I0406 14:27:02.945169 23057 solver.cpp:237]     Train net output #0: loss = 1.14734 (* 1 = 1.14734 loss)
I0406 14:27:02.945174 23057 sgd_solver.cpp:105] Iteration 3996, lr = 0.005
I0406 14:27:08.274670 23057 solver.cpp:218] Iteration 4008 (2.25164 iter/s, 5.32944s/12 iters), loss = 0.912873
I0406 14:27:08.274711 23057 solver.cpp:237]     Train net output #0: loss = 0.912873 (* 1 = 0.912873 loss)
I0406 14:27:08.274716 23057 sgd_solver.cpp:105] Iteration 4008, lr = 0.005
I0406 14:27:13.624272 23057 solver.cpp:218] Iteration 4020 (2.2432 iter/s, 5.3495s/12 iters), loss = 1.22608
I0406 14:27:13.624315 23057 solver.cpp:237]     Train net output #0: loss = 1.22608 (* 1 = 1.22608 loss)
I0406 14:27:13.624321 23057 sgd_solver.cpp:105] Iteration 4020, lr = 0.005
I0406 14:27:19.068197 23057 solver.cpp:218] Iteration 4032 (2.20433 iter/s, 5.44382s/12 iters), loss = 1.22395
I0406 14:27:19.068256 23057 solver.cpp:237]     Train net output #0: loss = 1.22395 (* 1 = 1.22395 loss)
I0406 14:27:19.068266 23057 sgd_solver.cpp:105] Iteration 4032, lr = 0.005
I0406 14:27:24.201066 23057 solver.cpp:218] Iteration 4044 (2.33792 iter/s, 5.13276s/12 iters), loss = 1.01979
I0406 14:27:24.201103 23057 solver.cpp:237]     Train net output #0: loss = 1.01979 (* 1 = 1.01979 loss)
I0406 14:27:24.201109 23057 sgd_solver.cpp:105] Iteration 4044, lr = 0.005
I0406 14:27:24.724895 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:27:29.442786 23057 solver.cpp:218] Iteration 4056 (2.28936 iter/s, 5.24163s/12 iters), loss = 0.963844
I0406 14:27:29.442826 23057 solver.cpp:237]     Train net output #0: loss = 0.963844 (* 1 = 0.963844 loss)
I0406 14:27:29.442831 23057 sgd_solver.cpp:105] Iteration 4056, lr = 0.005
I0406 14:27:34.851212 23057 solver.cpp:218] Iteration 4068 (2.2188 iter/s, 5.40833s/12 iters), loss = 1.08921
I0406 14:27:34.851265 23057 solver.cpp:237]     Train net output #0: loss = 1.08921 (* 1 = 1.08921 loss)
I0406 14:27:34.851274 23057 sgd_solver.cpp:105] Iteration 4068, lr = 0.005
I0406 14:27:39.565723 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel
I0406 14:27:42.667739 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate
I0406 14:27:44.973820 23057 solver.cpp:330] Iteration 4080, Testing net (#0)
I0406 14:27:44.973839 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:27:47.683348 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:27:49.251969 23057 solver.cpp:397]     Test net output #0: accuracy = 0.293505
I0406 14:27:49.251996 23057 solver.cpp:397]     Test net output #1: loss = 3.3402 (* 1 = 3.3402 loss)
I0406 14:27:49.392341 23057 solver.cpp:218] Iteration 4080 (0.825255 iter/s, 14.541s/12 iters), loss = 1.26005
I0406 14:27:49.393920 23057 solver.cpp:237]     Train net output #0: loss = 1.26005 (* 1 = 1.26005 loss)
I0406 14:27:49.393931 23057 sgd_solver.cpp:105] Iteration 4080, lr = 0.005
I0406 14:27:53.824563 23057 solver.cpp:218] Iteration 4092 (2.70844 iter/s, 4.4306s/12 iters), loss = 1.22649
I0406 14:27:53.824616 23057 solver.cpp:237]     Train net output #0: loss = 1.22649 (* 1 = 1.22649 loss)
I0406 14:27:53.824625 23057 sgd_solver.cpp:105] Iteration 4092, lr = 0.005
I0406 14:27:58.900105 23057 solver.cpp:218] Iteration 4104 (2.36433 iter/s, 5.07544s/12 iters), loss = 1.08806
I0406 14:27:58.900209 23057 solver.cpp:237]     Train net output #0: loss = 1.08806 (* 1 = 1.08806 loss)
I0406 14:27:58.900218 23057 sgd_solver.cpp:105] Iteration 4104, lr = 0.005
I0406 14:28:04.238721 23057 solver.cpp:218] Iteration 4116 (2.24784 iter/s, 5.33846s/12 iters), loss = 0.972398
I0406 14:28:04.238761 23057 solver.cpp:237]     Train net output #0: loss = 0.972398 (* 1 = 0.972398 loss)
I0406 14:28:04.238770 23057 sgd_solver.cpp:105] Iteration 4116, lr = 0.005
I0406 14:28:09.558076 23057 solver.cpp:218] Iteration 4128 (2.25595 iter/s, 5.31926s/12 iters), loss = 0.900809
I0406 14:28:09.558117 23057 solver.cpp:237]     Train net output #0: loss = 0.900809 (* 1 = 0.900809 loss)
I0406 14:28:09.558123 23057 sgd_solver.cpp:105] Iteration 4128, lr = 0.005
I0406 14:28:14.626484 23057 solver.cpp:218] Iteration 4140 (2.36765 iter/s, 5.06831s/12 iters), loss = 1.05379
I0406 14:28:14.626536 23057 solver.cpp:237]     Train net output #0: loss = 1.05379 (* 1 = 1.05379 loss)
I0406 14:28:14.626543 23057 sgd_solver.cpp:105] Iteration 4140, lr = 0.005
I0406 14:28:17.458236 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:28:20.109617 23057 solver.cpp:218] Iteration 4152 (2.18857 iter/s, 5.48302s/12 iters), loss = 1.0113
I0406 14:28:20.109663 23057 solver.cpp:237]     Train net output #0: loss = 1.0113 (* 1 = 1.0113 loss)
I0406 14:28:20.109670 23057 sgd_solver.cpp:105] Iteration 4152, lr = 0.005
I0406 14:28:21.717559 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:28:25.314930 23057 solver.cpp:218] Iteration 4164 (2.30538 iter/s, 5.20521s/12 iters), loss = 0.954747
I0406 14:28:25.314971 23057 solver.cpp:237]     Train net output #0: loss = 0.954747 (* 1 = 0.954747 loss)
I0406 14:28:25.314976 23057 sgd_solver.cpp:105] Iteration 4164, lr = 0.005
I0406 14:28:30.533583 23057 solver.cpp:218] Iteration 4176 (2.29949 iter/s, 5.21855s/12 iters), loss = 1.24781
I0406 14:28:30.533705 23057 solver.cpp:237]     Train net output #0: loss = 1.24781 (* 1 = 1.24781 loss)
I0406 14:28:30.533712 23057 sgd_solver.cpp:105] Iteration 4176, lr = 0.005
I0406 14:28:32.682402 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel
I0406 14:28:35.675145 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate
I0406 14:28:37.985431 23057 solver.cpp:330] Iteration 4182, Testing net (#0)
I0406 14:28:37.985453 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:28:40.738335 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:28:42.517184 23057 solver.cpp:397]     Test net output #0: accuracy = 0.324755
I0406 14:28:42.517226 23057 solver.cpp:397]     Test net output #1: loss = 3.15451 (* 1 = 3.15451 loss)
I0406 14:28:44.508512 23057 solver.cpp:218] Iteration 4188 (0.858695 iter/s, 13.9747s/12 iters), loss = 1.26711
I0406 14:28:44.508559 23057 solver.cpp:237]     Train net output #0: loss = 1.26711 (* 1 = 1.26711 loss)
I0406 14:28:44.508564 23057 sgd_solver.cpp:105] Iteration 4188, lr = 0.005
I0406 14:28:49.707264 23057 solver.cpp:218] Iteration 4200 (2.30829 iter/s, 5.19865s/12 iters), loss = 0.978101
I0406 14:28:49.707329 23057 solver.cpp:237]     Train net output #0: loss = 0.978101 (* 1 = 0.978101 loss)
I0406 14:28:49.707337 23057 sgd_solver.cpp:105] Iteration 4200, lr = 0.005
I0406 14:28:55.057240 23057 solver.cpp:218] Iteration 4212 (2.24305 iter/s, 5.34986s/12 iters), loss = 0.832692
I0406 14:28:55.057296 23057 solver.cpp:237]     Train net output #0: loss = 0.832692 (* 1 = 0.832692 loss)
I0406 14:28:55.057305 23057 sgd_solver.cpp:105] Iteration 4212, lr = 0.005
I0406 14:29:00.321808 23057 solver.cpp:218] Iteration 4224 (2.27944 iter/s, 5.26446s/12 iters), loss = 1.106
I0406 14:29:00.321847 23057 solver.cpp:237]     Train net output #0: loss = 1.106 (* 1 = 1.106 loss)
I0406 14:29:00.321853 23057 sgd_solver.cpp:105] Iteration 4224, lr = 0.005
I0406 14:29:05.569002 23057 solver.cpp:218] Iteration 4236 (2.28698 iter/s, 5.2471s/12 iters), loss = 1.42167
I0406 14:29:05.569200 23057 solver.cpp:237]     Train net output #0: loss = 1.42167 (* 1 = 1.42167 loss)
I0406 14:29:05.569206 23057 sgd_solver.cpp:105] Iteration 4236, lr = 0.005
I0406 14:29:10.684808 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:29:10.960808 23057 solver.cpp:218] Iteration 4248 (2.2257 iter/s, 5.39155s/12 iters), loss = 1.0329
I0406 14:29:10.960861 23057 solver.cpp:237]     Train net output #0: loss = 1.0329 (* 1 = 1.0329 loss)
I0406 14:29:10.960870 23057 sgd_solver.cpp:105] Iteration 4248, lr = 0.005
I0406 14:29:16.241698 23057 solver.cpp:218] Iteration 4260 (2.27239 iter/s, 5.28078s/12 iters), loss = 0.978547
I0406 14:29:16.241745 23057 solver.cpp:237]     Train net output #0: loss = 0.978547 (* 1 = 0.978547 loss)
I0406 14:29:16.241753 23057 sgd_solver.cpp:105] Iteration 4260, lr = 0.005
I0406 14:29:21.363610 23057 solver.cpp:218] Iteration 4272 (2.34292 iter/s, 5.12181s/12 iters), loss = 1.0451
I0406 14:29:21.363649 23057 solver.cpp:237]     Train net output #0: loss = 1.0451 (* 1 = 1.0451 loss)
I0406 14:29:21.363654 23057 sgd_solver.cpp:105] Iteration 4272, lr = 0.005
I0406 14:29:26.260532 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel
I0406 14:29:29.383152 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate
I0406 14:29:31.697831 23057 solver.cpp:330] Iteration 4284, Testing net (#0)
I0406 14:29:31.697854 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:29:34.448686 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:29:36.144105 23057 solver.cpp:397]     Test net output #0: accuracy = 0.326593
I0406 14:29:36.144223 23057 solver.cpp:397]     Test net output #1: loss = 3.084 (* 1 = 3.084 loss)
I0406 14:29:36.284317 23057 solver.cpp:218] Iteration 4284 (0.80426 iter/s, 14.9205s/12 iters), loss = 1.32268
I0406 14:29:36.284375 23057 solver.cpp:237]     Train net output #0: loss = 1.32268 (* 1 = 1.32268 loss)
I0406 14:29:36.284381 23057 sgd_solver.cpp:105] Iteration 4284, lr = 0.005
I0406 14:29:40.595618 23057 solver.cpp:218] Iteration 4296 (2.78345 iter/s, 4.3112s/12 iters), loss = 0.818676
I0406 14:29:40.595656 23057 solver.cpp:237]     Train net output #0: loss = 0.818676 (* 1 = 0.818676 loss)
I0406 14:29:40.595662 23057 sgd_solver.cpp:105] Iteration 4296, lr = 0.005
I0406 14:29:45.836864 23057 solver.cpp:218] Iteration 4308 (2.28957 iter/s, 5.24115s/12 iters), loss = 1.09541
I0406 14:29:45.836915 23057 solver.cpp:237]     Train net output #0: loss = 1.09541 (* 1 = 1.09541 loss)
I0406 14:29:45.836920 23057 sgd_solver.cpp:105] Iteration 4308, lr = 0.005
I0406 14:29:50.900924 23057 solver.cpp:218] Iteration 4320 (2.36969 iter/s, 5.06395s/12 iters), loss = 0.958374
I0406 14:29:50.900969 23057 solver.cpp:237]     Train net output #0: loss = 0.958374 (* 1 = 0.958374 loss)
I0406 14:29:50.900974 23057 sgd_solver.cpp:105] Iteration 4320, lr = 0.005
I0406 14:29:55.959046 23057 solver.cpp:218] Iteration 4332 (2.37247 iter/s, 5.05802s/12 iters), loss = 1.18777
I0406 14:29:55.959087 23057 solver.cpp:237]     Train net output #0: loss = 1.18777 (* 1 = 1.18777 loss)
I0406 14:29:55.959093 23057 sgd_solver.cpp:105] Iteration 4332, lr = 0.005
I0406 14:30:01.278694 23057 solver.cpp:218] Iteration 4344 (2.25583 iter/s, 5.31956s/12 iters), loss = 0.936174
I0406 14:30:01.278733 23057 solver.cpp:237]     Train net output #0: loss = 0.936174 (* 1 = 0.936174 loss)
I0406 14:30:01.278738 23057 sgd_solver.cpp:105] Iteration 4344, lr = 0.005
I0406 14:30:03.249944 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:30:06.582625 23057 solver.cpp:218] Iteration 4356 (2.26251 iter/s, 5.30384s/12 iters), loss = 0.82679
I0406 14:30:06.582726 23057 solver.cpp:237]     Train net output #0: loss = 0.82679 (* 1 = 0.82679 loss)
I0406 14:30:06.582732 23057 sgd_solver.cpp:105] Iteration 4356, lr = 0.005
I0406 14:30:11.816560 23057 solver.cpp:218] Iteration 4368 (2.2928 iter/s, 5.23378s/12 iters), loss = 1.01146
I0406 14:30:11.816604 23057 solver.cpp:237]     Train net output #0: loss = 1.01146 (* 1 = 1.01146 loss)
I0406 14:30:11.816610 23057 sgd_solver.cpp:105] Iteration 4368, lr = 0.005
I0406 14:30:17.248980 23057 solver.cpp:218] Iteration 4380 (2.209 iter/s, 5.43232s/12 iters), loss = 0.723539
I0406 14:30:17.249030 23057 solver.cpp:237]     Train net output #0: loss = 0.723539 (* 1 = 0.723539 loss)
I0406 14:30:17.249039 23057 sgd_solver.cpp:105] Iteration 4380, lr = 0.005
I0406 14:30:19.384263 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel
I0406 14:30:22.414178 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate
I0406 14:30:25.411005 23057 solver.cpp:330] Iteration 4386, Testing net (#0)
I0406 14:30:25.411026 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:30:28.135210 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:30:29.869722 23057 solver.cpp:397]     Test net output #0: accuracy = 0.314338
I0406 14:30:29.869756 23057 solver.cpp:397]     Test net output #1: loss = 3.23207 (* 1 = 3.23207 loss)
I0406 14:30:31.858850 23057 solver.cpp:218] Iteration 4392 (0.821372 iter/s, 14.6097s/12 iters), loss = 0.907524
I0406 14:30:31.858891 23057 solver.cpp:237]     Train net output #0: loss = 0.907524 (* 1 = 0.907524 loss)
I0406 14:30:31.858896 23057 sgd_solver.cpp:105] Iteration 4392, lr = 0.005
I0406 14:30:36.808207 23057 solver.cpp:218] Iteration 4404 (2.4246 iter/s, 4.94926s/12 iters), loss = 1.17988
I0406 14:30:36.808331 23057 solver.cpp:237]     Train net output #0: loss = 1.17988 (* 1 = 1.17988 loss)
I0406 14:30:36.808339 23057 sgd_solver.cpp:105] Iteration 4404, lr = 0.005
I0406 14:30:41.777384 23057 solver.cpp:218] Iteration 4416 (2.41497 iter/s, 4.969s/12 iters), loss = 1.06201
I0406 14:30:41.777428 23057 solver.cpp:237]     Train net output #0: loss = 1.06201 (* 1 = 1.06201 loss)
I0406 14:30:41.777434 23057 sgd_solver.cpp:105] Iteration 4416, lr = 0.005
I0406 14:30:46.842208 23057 solver.cpp:218] Iteration 4428 (2.36933 iter/s, 5.06473s/12 iters), loss = 0.937315
I0406 14:30:46.842248 23057 solver.cpp:237]     Train net output #0: loss = 0.937315 (* 1 = 0.937315 loss)
I0406 14:30:46.842254 23057 sgd_solver.cpp:105] Iteration 4428, lr = 0.005
I0406 14:30:51.804540 23057 solver.cpp:218] Iteration 4440 (2.41826 iter/s, 4.96224s/12 iters), loss = 1.02905
I0406 14:30:51.804581 23057 solver.cpp:237]     Train net output #0: loss = 1.02905 (* 1 = 1.02905 loss)
I0406 14:30:51.804586 23057 sgd_solver.cpp:105] Iteration 4440, lr = 0.005
I0406 14:30:56.167035 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:30:57.179749 23057 solver.cpp:218] Iteration 4452 (2.23251 iter/s, 5.37511s/12 iters), loss = 0.90448
I0406 14:30:57.179801 23057 solver.cpp:237]     Train net output #0: loss = 0.90448 (* 1 = 0.90448 loss)
I0406 14:30:57.179809 23057 sgd_solver.cpp:105] Iteration 4452, lr = 0.005
I0406 14:31:02.296908 23057 solver.cpp:218] Iteration 4464 (2.3451 iter/s, 5.11705s/12 iters), loss = 0.865006
I0406 14:31:02.296948 23057 solver.cpp:237]     Train net output #0: loss = 0.865006 (* 1 = 0.865006 loss)
I0406 14:31:02.296954 23057 sgd_solver.cpp:105] Iteration 4464, lr = 0.005
I0406 14:31:07.793637 23057 solver.cpp:218] Iteration 4476 (2.18316 iter/s, 5.49663s/12 iters), loss = 1.00027
I0406 14:31:07.793747 23057 solver.cpp:237]     Train net output #0: loss = 1.00027 (* 1 = 1.00027 loss)
I0406 14:31:07.793756 23057 sgd_solver.cpp:105] Iteration 4476, lr = 0.005
I0406 14:31:12.575162 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel
I0406 14:31:16.250638 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate
I0406 14:31:19.639003 23057 solver.cpp:330] Iteration 4488, Testing net (#0)
I0406 14:31:19.639022 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:31:22.211819 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:31:24.019521 23057 solver.cpp:397]     Test net output #0: accuracy = 0.333333
I0406 14:31:24.019562 23057 solver.cpp:397]     Test net output #1: loss = 3.14576 (* 1 = 3.14576 loss)
I0406 14:31:24.159993 23057 solver.cpp:218] Iteration 4488 (0.733222 iter/s, 16.3661s/12 iters), loss = 1.07473
I0406 14:31:24.160032 23057 solver.cpp:237]     Train net output #0: loss = 1.07473 (* 1 = 1.07473 loss)
I0406 14:31:24.160037 23057 sgd_solver.cpp:105] Iteration 4488, lr = 0.005
I0406 14:31:28.556267 23057 solver.cpp:218] Iteration 4500 (2.72964 iter/s, 4.39618s/12 iters), loss = 0.759467
I0406 14:31:28.556309 23057 solver.cpp:237]     Train net output #0: loss = 0.759467 (* 1 = 0.759467 loss)
I0406 14:31:28.556314 23057 sgd_solver.cpp:105] Iteration 4500, lr = 0.005
I0406 14:31:33.904053 23057 solver.cpp:218] Iteration 4512 (2.24396 iter/s, 5.34768s/12 iters), loss = 0.961172
I0406 14:31:33.904109 23057 solver.cpp:237]     Train net output #0: loss = 0.961172 (* 1 = 0.961172 loss)
I0406 14:31:33.904117 23057 sgd_solver.cpp:105] Iteration 4512, lr = 0.005
I0406 14:31:39.262228 23057 solver.cpp:218] Iteration 4524 (2.23961 iter/s, 5.35807s/12 iters), loss = 0.797482
I0406 14:31:39.262341 23057 solver.cpp:237]     Train net output #0: loss = 0.797482 (* 1 = 0.797482 loss)
I0406 14:31:39.262348 23057 sgd_solver.cpp:105] Iteration 4524, lr = 0.005
I0406 14:31:44.474267 23057 solver.cpp:218] Iteration 4536 (2.30244 iter/s, 5.21187s/12 iters), loss = 1.1042
I0406 14:31:44.474310 23057 solver.cpp:237]     Train net output #0: loss = 1.1042 (* 1 = 1.1042 loss)
I0406 14:31:44.474316 23057 sgd_solver.cpp:105] Iteration 4536, lr = 0.005
I0406 14:31:49.728634 23057 solver.cpp:218] Iteration 4548 (2.28386 iter/s, 5.25426s/12 iters), loss = 0.856841
I0406 14:31:49.728691 23057 solver.cpp:237]     Train net output #0: loss = 0.856841 (* 1 = 0.856841 loss)
I0406 14:31:49.728699 23057 sgd_solver.cpp:105] Iteration 4548, lr = 0.005
I0406 14:31:51.177314 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:31:55.291841 23057 solver.cpp:218] Iteration 4560 (2.15707 iter/s, 5.5631s/12 iters), loss = 0.748802
I0406 14:31:55.291882 23057 solver.cpp:237]     Train net output #0: loss = 0.748802 (* 1 = 0.748802 loss)
I0406 14:31:55.291888 23057 sgd_solver.cpp:105] Iteration 4560, lr = 0.005
I0406 14:32:00.605746 23057 solver.cpp:218] Iteration 4572 (2.25827 iter/s, 5.31381s/12 iters), loss = 1.07443
I0406 14:32:00.605784 23057 solver.cpp:237]     Train net output #0: loss = 1.07443 (* 1 = 1.07443 loss)
I0406 14:32:00.605792 23057 sgd_solver.cpp:105] Iteration 4572, lr = 0.005
I0406 14:32:05.830533 23057 solver.cpp:218] Iteration 4584 (2.29679 iter/s, 5.22469s/12 iters), loss = 0.924613
I0406 14:32:05.830595 23057 solver.cpp:237]     Train net output #0: loss = 0.924613 (* 1 = 0.924613 loss)
I0406 14:32:05.830603 23057 sgd_solver.cpp:105] Iteration 4584, lr = 0.005
I0406 14:32:07.964299 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel
I0406 14:32:11.008455 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate
I0406 14:32:13.316404 23057 solver.cpp:330] Iteration 4590, Testing net (#0)
I0406 14:32:13.316427 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:32:15.953650 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:32:17.736930 23057 solver.cpp:397]     Test net output #0: accuracy = 0.331495
I0406 14:32:17.736969 23057 solver.cpp:397]     Test net output #1: loss = 3.21846 (* 1 = 3.21846 loss)
I0406 14:32:19.612915 23057 solver.cpp:218] Iteration 4596 (0.870688 iter/s, 13.7822s/12 iters), loss = 1.01418
I0406 14:32:19.612951 23057 solver.cpp:237]     Train net output #0: loss = 1.01418 (* 1 = 1.01418 loss)
I0406 14:32:19.612957 23057 sgd_solver.cpp:105] Iteration 4596, lr = 0.005
I0406 14:32:24.937234 23057 solver.cpp:218] Iteration 4608 (2.25385 iter/s, 5.32423s/12 iters), loss = 0.877831
I0406 14:32:24.937276 23057 solver.cpp:237]     Train net output #0: loss = 0.877831 (* 1 = 0.877831 loss)
I0406 14:32:24.937283 23057 sgd_solver.cpp:105] Iteration 4608, lr = 0.005
I0406 14:32:29.999421 23057 solver.cpp:218] Iteration 4620 (2.37056 iter/s, 5.06209s/12 iters), loss = 1.00506
I0406 14:32:29.999464 23057 solver.cpp:237]     Train net output #0: loss = 1.00506 (* 1 = 1.00506 loss)
I0406 14:32:29.999469 23057 sgd_solver.cpp:105] Iteration 4620, lr = 0.005
I0406 14:32:35.150388 23057 solver.cpp:218] Iteration 4632 (2.3297 iter/s, 5.15087s/12 iters), loss = 0.93741
I0406 14:32:35.150427 23057 solver.cpp:237]     Train net output #0: loss = 0.93741 (* 1 = 0.93741 loss)
I0406 14:32:35.150434 23057 sgd_solver.cpp:105] Iteration 4632, lr = 0.005
I0406 14:32:40.294615 23057 solver.cpp:218] Iteration 4644 (2.33275 iter/s, 5.14414s/12 iters), loss = 0.754755
I0406 14:32:40.294652 23057 solver.cpp:237]     Train net output #0: loss = 0.754755 (* 1 = 0.754755 loss)
I0406 14:32:40.294658 23057 sgd_solver.cpp:105] Iteration 4644, lr = 0.005
I0406 14:32:43.803864 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:32:45.530650 23057 solver.cpp:218] Iteration 4656 (2.29185 iter/s, 5.23594s/12 iters), loss = 0.912999
I0406 14:32:45.530699 23057 solver.cpp:237]     Train net output #0: loss = 0.912999 (* 1 = 0.912999 loss)
I0406 14:32:45.530705 23057 sgd_solver.cpp:105] Iteration 4656, lr = 0.005
I0406 14:32:50.825197 23057 solver.cpp:218] Iteration 4668 (2.26653 iter/s, 5.29444s/12 iters), loss = 0.715799
I0406 14:32:50.825238 23057 solver.cpp:237]     Train net output #0: loss = 0.715799 (* 1 = 0.715799 loss)
I0406 14:32:50.825244 23057 sgd_solver.cpp:105] Iteration 4668, lr = 0.005
I0406 14:32:55.809607 23057 solver.cpp:218] Iteration 4680 (2.40755 iter/s, 4.98431s/12 iters), loss = 0.792032
I0406 14:32:55.809655 23057 solver.cpp:237]     Train net output #0: loss = 0.792032 (* 1 = 0.792032 loss)
I0406 14:32:55.809661 23057 sgd_solver.cpp:105] Iteration 4680, lr = 0.005
I0406 14:33:00.495829 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel
I0406 14:33:03.474138 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate
I0406 14:33:05.770484 23057 solver.cpp:330] Iteration 4692, Testing net (#0)
I0406 14:33:05.770504 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:33:08.207505 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:33:10.020141 23057 solver.cpp:397]     Test net output #0: accuracy = 0.331495
I0406 14:33:10.020177 23057 solver.cpp:397]     Test net output #1: loss = 3.21128 (* 1 = 3.21128 loss)
I0406 14:33:10.160621 23057 solver.cpp:218] Iteration 4692 (0.836187 iter/s, 14.3508s/12 iters), loss = 1.00007
I0406 14:33:10.160663 23057 solver.cpp:237]     Train net output #0: loss = 1.00007 (* 1 = 1.00007 loss)
I0406 14:33:10.160670 23057 sgd_solver.cpp:105] Iteration 4692, lr = 0.005
I0406 14:33:14.541589 23057 solver.cpp:218] Iteration 4704 (2.73918 iter/s, 4.38088s/12 iters), loss = 0.958903
I0406 14:33:14.541688 23057 solver.cpp:237]     Train net output #0: loss = 0.958903 (* 1 = 0.958903 loss)
I0406 14:33:14.541695 23057 sgd_solver.cpp:105] Iteration 4704, lr = 0.005
I0406 14:33:19.762640 23057 solver.cpp:218] Iteration 4716 (2.29845 iter/s, 5.2209s/12 iters), loss = 0.789263
I0406 14:33:19.762696 23057 solver.cpp:237]     Train net output #0: loss = 0.789263 (* 1 = 0.789263 loss)
I0406 14:33:19.762706 23057 sgd_solver.cpp:105] Iteration 4716, lr = 0.005
I0406 14:33:24.916205 23057 solver.cpp:218] Iteration 4728 (2.32854 iter/s, 5.15345s/12 iters), loss = 0.969595
I0406 14:33:24.916250 23057 solver.cpp:237]     Train net output #0: loss = 0.969595 (* 1 = 0.969595 loss)
I0406 14:33:24.916256 23057 sgd_solver.cpp:105] Iteration 4728, lr = 0.005
I0406 14:33:30.006219 23057 solver.cpp:218] Iteration 4740 (2.3576 iter/s, 5.08991s/12 iters), loss = 0.845005
I0406 14:33:30.006275 23057 solver.cpp:237]     Train net output #0: loss = 0.845005 (* 1 = 0.845005 loss)
I0406 14:33:30.006283 23057 sgd_solver.cpp:105] Iteration 4740, lr = 0.005
I0406 14:33:35.463843 23057 solver.cpp:218] Iteration 4752 (2.1988 iter/s, 5.45751s/12 iters), loss = 0.999
I0406 14:33:35.463882 23057 solver.cpp:237]     Train net output #0: loss = 0.999 (* 1 = 0.999 loss)
I0406 14:33:35.463888 23057 sgd_solver.cpp:105] Iteration 4752, lr = 0.005
I0406 14:33:36.024312 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:33:40.603291 23057 solver.cpp:218] Iteration 4764 (2.33492 iter/s, 5.13935s/12 iters), loss = 0.767104
I0406 14:33:40.603330 23057 solver.cpp:237]     Train net output #0: loss = 0.767104 (* 1 = 0.767104 loss)
I0406 14:33:40.603336 23057 sgd_solver.cpp:105] Iteration 4764, lr = 0.005
I0406 14:33:45.740367 23057 solver.cpp:218] Iteration 4776 (2.336 iter/s, 5.13698s/12 iters), loss = 0.600156
I0406 14:33:45.740487 23057 solver.cpp:237]     Train net output #0: loss = 0.600156 (* 1 = 0.600156 loss)
I0406 14:33:45.740494 23057 sgd_solver.cpp:105] Iteration 4776, lr = 0.005
I0406 14:33:50.942886 23057 solver.cpp:218] Iteration 4788 (2.30665 iter/s, 5.20234s/12 iters), loss = 0.400882
I0406 14:33:50.942941 23057 solver.cpp:237]     Train net output #0: loss = 0.400882 (* 1 = 0.400882 loss)
I0406 14:33:50.942950 23057 sgd_solver.cpp:105] Iteration 4788, lr = 0.005
I0406 14:33:53.009006 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel
I0406 14:33:55.946535 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate
I0406 14:33:58.837924 23057 solver.cpp:330] Iteration 4794, Testing net (#0)
I0406 14:33:58.837945 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:34:01.372138 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:34:03.296802 23057 solver.cpp:397]     Test net output #0: accuracy = 0.327819
I0406 14:34:03.296838 23057 solver.cpp:397]     Test net output #1: loss = 3.22804 (* 1 = 3.22804 loss)
I0406 14:34:05.107352 23057 solver.cpp:218] Iteration 4800 (0.847201 iter/s, 14.1643s/12 iters), loss = 0.83978
I0406 14:34:05.107398 23057 solver.cpp:237]     Train net output #0: loss = 0.83978 (* 1 = 0.83978 loss)
I0406 14:34:05.107404 23057 sgd_solver.cpp:105] Iteration 4800, lr = 0.005
I0406 14:34:10.167523 23057 solver.cpp:218] Iteration 4812 (2.37151 iter/s, 5.06007s/12 iters), loss = 0.681626
I0406 14:34:10.167565 23057 solver.cpp:237]     Train net output #0: loss = 0.681626 (* 1 = 0.681626 loss)
I0406 14:34:10.167570 23057 sgd_solver.cpp:105] Iteration 4812, lr = 0.005
I0406 14:34:15.486714 23057 solver.cpp:218] Iteration 4824 (2.25602 iter/s, 5.31909s/12 iters), loss = 0.658472
I0406 14:34:15.486754 23057 solver.cpp:237]     Train net output #0: loss = 0.658472 (* 1 = 0.658472 loss)
I0406 14:34:15.486760 23057 sgd_solver.cpp:105] Iteration 4824, lr = 0.005
I0406 14:34:20.736936 23057 solver.cpp:218] Iteration 4836 (2.28566 iter/s, 5.25013s/12 iters), loss = 0.902695
I0406 14:34:20.737040 23057 solver.cpp:237]     Train net output #0: loss = 0.902695 (* 1 = 0.902695 loss)
I0406 14:34:20.737048 23057 sgd_solver.cpp:105] Iteration 4836, lr = 0.005
I0406 14:34:22.773118 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:34:25.945382 23057 solver.cpp:218] Iteration 4848 (2.30402 iter/s, 5.20829s/12 iters), loss = 0.738787
I0406 14:34:25.945431 23057 solver.cpp:237]     Train net output #0: loss = 0.738787 (* 1 = 0.738787 loss)
I0406 14:34:25.945441 23057 sgd_solver.cpp:105] Iteration 4848, lr = 0.005
I0406 14:34:28.618216 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:34:30.995805 23057 solver.cpp:218] Iteration 4860 (2.37609 iter/s, 5.05032s/12 iters), loss = 0.729807
I0406 14:34:30.995849 23057 solver.cpp:237]     Train net output #0: loss = 0.729807 (* 1 = 0.729807 loss)
I0406 14:34:30.995855 23057 sgd_solver.cpp:105] Iteration 4860, lr = 0.005
I0406 14:34:36.267223 23057 solver.cpp:218] Iteration 4872 (2.27647 iter/s, 5.27132s/12 iters), loss = 0.858961
I0406 14:34:36.267261 23057 solver.cpp:237]     Train net output #0: loss = 0.858961 (* 1 = 0.858961 loss)
I0406 14:34:36.267267 23057 sgd_solver.cpp:105] Iteration 4872, lr = 0.005
I0406 14:34:41.311053 23057 solver.cpp:218] Iteration 4884 (2.37919 iter/s, 5.04373s/12 iters), loss = 0.75707
I0406 14:34:41.311115 23057 solver.cpp:237]     Train net output #0: loss = 0.75707 (* 1 = 0.75707 loss)
I0406 14:34:41.311127 23057 sgd_solver.cpp:105] Iteration 4884, lr = 0.005
I0406 14:34:45.980808 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel
I0406 14:34:49.097795 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate
I0406 14:34:51.731526 23057 solver.cpp:330] Iteration 4896, Testing net (#0)
I0406 14:34:51.731607 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:34:54.233419 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:34:56.136464 23057 solver.cpp:397]     Test net output #0: accuracy = 0.331495
I0406 14:34:56.136498 23057 solver.cpp:397]     Test net output #1: loss = 3.16692 (* 1 = 3.16692 loss)
I0406 14:34:56.276628 23057 solver.cpp:218] Iteration 4896 (0.80185 iter/s, 14.9654s/12 iters), loss = 0.72362
I0406 14:34:56.276710 23057 solver.cpp:237]     Train net output #0: loss = 0.72362 (* 1 = 0.72362 loss)
I0406 14:34:56.276721 23057 sgd_solver.cpp:105] Iteration 4896, lr = 0.005
I0406 14:35:00.741720 23057 solver.cpp:218] Iteration 4908 (2.68759 iter/s, 4.46497s/12 iters), loss = 0.729372
I0406 14:35:00.741763 23057 solver.cpp:237]     Train net output #0: loss = 0.729372 (* 1 = 0.729372 loss)
I0406 14:35:00.741770 23057 sgd_solver.cpp:105] Iteration 4908, lr = 0.005
I0406 14:35:06.038564 23057 solver.cpp:218] Iteration 4920 (2.26555 iter/s, 5.29674s/12 iters), loss = 0.803327
I0406 14:35:06.038627 23057 solver.cpp:237]     Train net output #0: loss = 0.803327 (* 1 = 0.803327 loss)
I0406 14:35:06.038636 23057 sgd_solver.cpp:105] Iteration 4920, lr = 0.005
I0406 14:35:11.279841 23057 solver.cpp:218] Iteration 4932 (2.28957 iter/s, 5.24116s/12 iters), loss = 0.701718
I0406 14:35:11.279888 23057 solver.cpp:237]     Train net output #0: loss = 0.701718 (* 1 = 0.701718 loss)
I0406 14:35:11.279894 23057 sgd_solver.cpp:105] Iteration 4932, lr = 0.005
I0406 14:35:16.755148 23057 solver.cpp:218] Iteration 4944 (2.1917 iter/s, 5.4752s/12 iters), loss = 0.823402
I0406 14:35:16.755187 23057 solver.cpp:237]     Train net output #0: loss = 0.823402 (* 1 = 0.823402 loss)
I0406 14:35:16.755193 23057 sgd_solver.cpp:105] Iteration 4944, lr = 0.005
I0406 14:35:21.887362 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:35:22.136299 23057 solver.cpp:218] Iteration 4956 (2.23005 iter/s, 5.38105s/12 iters), loss = 0.845943
I0406 14:35:22.136353 23057 solver.cpp:237]     Train net output #0: loss = 0.845943 (* 1 = 0.845943 loss)
I0406 14:35:22.136360 23057 sgd_solver.cpp:105] Iteration 4956, lr = 0.005
I0406 14:35:27.503901 23057 solver.cpp:218] Iteration 4968 (2.23568 iter/s, 5.36749s/12 iters), loss = 0.616182
I0406 14:35:27.503937 23057 solver.cpp:237]     Train net output #0: loss = 0.616182 (* 1 = 0.616182 loss)
I0406 14:35:27.503943 23057 sgd_solver.cpp:105] Iteration 4968, lr = 0.005
I0406 14:35:32.794133 23057 solver.cpp:218] Iteration 4980 (2.26837 iter/s, 5.29014s/12 iters), loss = 0.63468
I0406 14:35:32.794196 23057 solver.cpp:237]     Train net output #0: loss = 0.63468 (* 1 = 0.63468 loss)
I0406 14:35:32.794205 23057 sgd_solver.cpp:105] Iteration 4980, lr = 0.005
I0406 14:35:38.104530 23057 solver.cpp:218] Iteration 4992 (2.25977 iter/s, 5.31028s/12 iters), loss = 0.589885
I0406 14:35:38.104581 23057 solver.cpp:237]     Train net output #0: loss = 0.589885 (* 1 = 0.589885 loss)
I0406 14:35:38.104588 23057 sgd_solver.cpp:105] Iteration 4992, lr = 0.005
I0406 14:35:40.254020 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel
I0406 14:35:43.291416 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate
I0406 14:35:45.587474 23057 solver.cpp:330] Iteration 4998, Testing net (#0)
I0406 14:35:45.587492 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:35:47.940876 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:35:49.866057 23057 solver.cpp:397]     Test net output #0: accuracy = 0.334559
I0406 14:35:49.866093 23057 solver.cpp:397]     Test net output #1: loss = 3.33546 (* 1 = 3.33546 loss)
I0406 14:35:51.791174 23057 solver.cpp:218] Iteration 5004 (0.876778 iter/s, 13.6865s/12 iters), loss = 0.715085
I0406 14:35:51.791215 23057 solver.cpp:237]     Train net output #0: loss = 0.715085 (* 1 = 0.715085 loss)
I0406 14:35:51.791221 23057 sgd_solver.cpp:105] Iteration 5004, lr = 0.005
I0406 14:35:56.841089 23057 solver.cpp:218] Iteration 5016 (2.37632 iter/s, 5.04982s/12 iters), loss = 0.399664
I0406 14:35:56.841248 23057 solver.cpp:237]     Train net output #0: loss = 0.399664 (* 1 = 0.399664 loss)
I0406 14:35:56.841257 23057 sgd_solver.cpp:105] Iteration 5016, lr = 0.005
I0406 14:36:02.154415 23057 solver.cpp:218] Iteration 5028 (2.25856 iter/s, 5.31311s/12 iters), loss = 0.4436
I0406 14:36:02.154471 23057 solver.cpp:237]     Train net output #0: loss = 0.4436 (* 1 = 0.4436 loss)
I0406 14:36:02.154480 23057 sgd_solver.cpp:105] Iteration 5028, lr = 0.005
I0406 14:36:07.324445 23057 solver.cpp:218] Iteration 5040 (2.32112 iter/s, 5.16992s/12 iters), loss = 0.636451
I0406 14:36:07.324483 23057 solver.cpp:237]     Train net output #0: loss = 0.636451 (* 1 = 0.636451 loss)
I0406 14:36:07.324489 23057 sgd_solver.cpp:105] Iteration 5040, lr = 0.005
I0406 14:36:12.460353 23057 solver.cpp:218] Iteration 5052 (2.33653 iter/s, 5.13581s/12 iters), loss = 0.672723
I0406 14:36:12.460402 23057 solver.cpp:237]     Train net output #0: loss = 0.672723 (* 1 = 0.672723 loss)
I0406 14:36:12.460409 23057 sgd_solver.cpp:105] Iteration 5052, lr = 0.005
I0406 14:36:14.428645 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:36:17.389443 23057 solver.cpp:218] Iteration 5064 (2.43457 iter/s, 4.92899s/12 iters), loss = 0.505545
I0406 14:36:17.389482 23057 solver.cpp:237]     Train net output #0: loss = 0.505545 (* 1 = 0.505545 loss)
I0406 14:36:17.389487 23057 sgd_solver.cpp:105] Iteration 5064, lr = 0.005
I0406 14:36:22.275568 23057 solver.cpp:218] Iteration 5076 (2.45598 iter/s, 4.88603s/12 iters), loss = 0.737877
I0406 14:36:22.275612 23057 solver.cpp:237]     Train net output #0: loss = 0.737877 (* 1 = 0.737877 loss)
I0406 14:36:22.275617 23057 sgd_solver.cpp:105] Iteration 5076, lr = 0.005
I0406 14:36:27.546823 23057 solver.cpp:218] Iteration 5088 (2.27654 iter/s, 5.27116s/12 iters), loss = 0.492155
I0406 14:36:27.546931 23057 solver.cpp:237]     Train net output #0: loss = 0.492155 (* 1 = 0.492155 loss)
I0406 14:36:27.546937 23057 sgd_solver.cpp:105] Iteration 5088, lr = 0.005
I0406 14:36:32.320677 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel
I0406 14:36:35.292555 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate
I0406 14:36:37.609946 23057 solver.cpp:330] Iteration 5100, Testing net (#0)
I0406 14:36:37.609964 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:36:39.906538 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:36:41.890250 23057 solver.cpp:397]     Test net output #0: accuracy = 0.353554
I0406 14:36:41.890285 23057 solver.cpp:397]     Test net output #1: loss = 3.35417 (* 1 = 3.35417 loss)
I0406 14:36:42.030701 23057 solver.cpp:218] Iteration 5100 (0.82852 iter/s, 14.4837s/12 iters), loss = 0.765453
I0406 14:36:42.030751 23057 solver.cpp:237]     Train net output #0: loss = 0.765453 (* 1 = 0.765453 loss)
I0406 14:36:42.030761 23057 sgd_solver.cpp:105] Iteration 5100, lr = 0.005
I0406 14:36:46.256705 23057 solver.cpp:218] Iteration 5112 (2.83962 iter/s, 4.22591s/12 iters), loss = 0.618629
I0406 14:36:46.256747 23057 solver.cpp:237]     Train net output #0: loss = 0.618629 (* 1 = 0.618629 loss)
I0406 14:36:46.256752 23057 sgd_solver.cpp:105] Iteration 5112, lr = 0.005
I0406 14:36:51.485666 23057 solver.cpp:218] Iteration 5124 (2.29495 iter/s, 5.22886s/12 iters), loss = 0.583677
I0406 14:36:51.485714 23057 solver.cpp:237]     Train net output #0: loss = 0.583677 (* 1 = 0.583677 loss)
I0406 14:36:51.485723 23057 sgd_solver.cpp:105] Iteration 5124, lr = 0.005
I0406 14:36:56.731587 23057 solver.cpp:218] Iteration 5136 (2.28753 iter/s, 5.24582s/12 iters), loss = 0.737149
I0406 14:36:56.731628 23057 solver.cpp:237]     Train net output #0: loss = 0.737149 (* 1 = 0.737149 loss)
I0406 14:36:56.731635 23057 sgd_solver.cpp:105] Iteration 5136, lr = 0.005
I0406 14:37:02.038544 23057 solver.cpp:218] Iteration 5148 (2.26122 iter/s, 5.30686s/12 iters), loss = 0.57475
I0406 14:37:02.038630 23057 solver.cpp:237]     Train net output #0: loss = 0.57475 (* 1 = 0.57475 loss)
I0406 14:37:02.038636 23057 sgd_solver.cpp:105] Iteration 5148, lr = 0.005
I0406 14:37:06.211602 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:37:07.267738 23057 solver.cpp:218] Iteration 5160 (2.29487 iter/s, 5.22905s/12 iters), loss = 0.71623
I0406 14:37:07.267794 23057 solver.cpp:237]     Train net output #0: loss = 0.71623 (* 1 = 0.71623 loss)
I0406 14:37:07.267802 23057 sgd_solver.cpp:105] Iteration 5160, lr = 0.005
I0406 14:37:12.411619 23057 solver.cpp:218] Iteration 5172 (2.33292 iter/s, 5.14377s/12 iters), loss = 0.667351
I0406 14:37:12.411660 23057 solver.cpp:237]     Train net output #0: loss = 0.667351 (* 1 = 0.667351 loss)
I0406 14:37:12.411666 23057 sgd_solver.cpp:105] Iteration 5172, lr = 0.005
I0406 14:37:17.637468 23057 solver.cpp:218] Iteration 5184 (2.29632 iter/s, 5.22575s/12 iters), loss = 0.372285
I0406 14:37:17.637507 23057 solver.cpp:237]     Train net output #0: loss = 0.372285 (* 1 = 0.372285 loss)
I0406 14:37:17.637514 23057 sgd_solver.cpp:105] Iteration 5184, lr = 0.005
I0406 14:37:22.893568 23057 solver.cpp:218] Iteration 5196 (2.2831 iter/s, 5.25601s/12 iters), loss = 0.555473
I0406 14:37:22.893610 23057 solver.cpp:237]     Train net output #0: loss = 0.555473 (* 1 = 0.555473 loss)
I0406 14:37:22.893615 23057 sgd_solver.cpp:105] Iteration 5196, lr = 0.005
I0406 14:37:24.991847 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel
I0406 14:37:28.045186 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate
I0406 14:37:30.345904 23057 solver.cpp:330] Iteration 5202, Testing net (#0)
I0406 14:37:30.345928 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:37:32.657903 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:37:34.710626 23057 solver.cpp:397]     Test net output #0: accuracy = 0.358456
I0406 14:37:34.710664 23057 solver.cpp:397]     Test net output #1: loss = 3.26031 (* 1 = 3.26031 loss)
I0406 14:37:36.592367 23057 solver.cpp:218] Iteration 5208 (0.875999 iter/s, 13.6986s/12 iters), loss = 0.711409
I0406 14:37:36.592415 23057 solver.cpp:237]     Train net output #0: loss = 0.711409 (* 1 = 0.711409 loss)
I0406 14:37:36.592424 23057 sgd_solver.cpp:105] Iteration 5208, lr = 0.005
I0406 14:37:41.943508 23057 solver.cpp:218] Iteration 5220 (2.24256 iter/s, 5.35103s/12 iters), loss = 0.720997
I0406 14:37:41.943570 23057 solver.cpp:237]     Train net output #0: loss = 0.720997 (* 1 = 0.720997 loss)
I0406 14:37:41.943580 23057 sgd_solver.cpp:105] Iteration 5220, lr = 0.005
I0406 14:37:47.261168 23057 solver.cpp:218] Iteration 5232 (2.25669 iter/s, 5.31753s/12 iters), loss = 0.613464
I0406 14:37:47.261238 23057 solver.cpp:237]     Train net output #0: loss = 0.613464 (* 1 = 0.613464 loss)
I0406 14:37:47.261252 23057 sgd_solver.cpp:105] Iteration 5232, lr = 0.005
I0406 14:37:52.618042 23057 solver.cpp:218] Iteration 5244 (2.24016 iter/s, 5.35676s/12 iters), loss = 0.810611
I0406 14:37:52.618085 23057 solver.cpp:237]     Train net output #0: loss = 0.810611 (* 1 = 0.810611 loss)
I0406 14:37:52.618091 23057 sgd_solver.cpp:105] Iteration 5244, lr = 0.005
I0406 14:37:57.978762 23057 solver.cpp:218] Iteration 5256 (2.23855 iter/s, 5.36062s/12 iters), loss = 0.57764
I0406 14:37:57.985504 23057 solver.cpp:237]     Train net output #0: loss = 0.57764 (* 1 = 0.57764 loss)
I0406 14:37:57.985525 23057 sgd_solver.cpp:105] Iteration 5256, lr = 0.005
I0406 14:37:59.427461 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:38:03.450199 23057 solver.cpp:218] Iteration 5268 (2.19593 iter/s, 5.46466s/12 iters), loss = 0.465187
I0406 14:38:03.450286 23057 solver.cpp:237]     Train net output #0: loss = 0.465187 (* 1 = 0.465187 loss)
I0406 14:38:03.450292 23057 sgd_solver.cpp:105] Iteration 5268, lr = 0.005
I0406 14:38:08.762940 23057 solver.cpp:218] Iteration 5280 (2.25878 iter/s, 5.3126s/12 iters), loss = 0.453223
I0406 14:38:08.762984 23057 solver.cpp:237]     Train net output #0: loss = 0.453223 (* 1 = 0.453223 loss)
I0406 14:38:08.762989 23057 sgd_solver.cpp:105] Iteration 5280, lr = 0.005
I0406 14:38:13.938228 23057 solver.cpp:218] Iteration 5292 (2.31876 iter/s, 5.17519s/12 iters), loss = 0.855478
I0406 14:38:13.938279 23057 solver.cpp:237]     Train net output #0: loss = 0.855478 (* 1 = 0.855478 loss)
I0406 14:38:13.938287 23057 sgd_solver.cpp:105] Iteration 5292, lr = 0.005
I0406 14:38:18.592123 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel
I0406 14:38:21.629160 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate
I0406 14:38:23.967234 23057 solver.cpp:330] Iteration 5304, Testing net (#0)
I0406 14:38:23.967253 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:38:26.205986 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:38:28.292243 23057 solver.cpp:397]     Test net output #0: accuracy = 0.354167
I0406 14:38:28.292279 23057 solver.cpp:397]     Test net output #1: loss = 3.1824 (* 1 = 3.1824 loss)
I0406 14:38:28.432643 23057 solver.cpp:218] Iteration 5304 (0.827915 iter/s, 14.4942s/12 iters), loss = 0.666949
I0406 14:38:28.432693 23057 solver.cpp:237]     Train net output #0: loss = 0.666949 (* 1 = 0.666949 loss)
I0406 14:38:28.432701 23057 sgd_solver.cpp:105] Iteration 5304, lr = 0.005
I0406 14:38:32.867816 23057 solver.cpp:218] Iteration 5316 (2.7057 iter/s, 4.43507s/12 iters), loss = 0.569911
I0406 14:38:32.867877 23057 solver.cpp:237]     Train net output #0: loss = 0.569911 (* 1 = 0.569911 loss)
I0406 14:38:32.867887 23057 sgd_solver.cpp:105] Iteration 5316, lr = 0.005
I0406 14:38:38.143005 23057 solver.cpp:218] Iteration 5328 (2.27485 iter/s, 5.27508s/12 iters), loss = 0.582683
I0406 14:38:38.143146 23057 solver.cpp:237]     Train net output #0: loss = 0.582683 (* 1 = 0.582683 loss)
I0406 14:38:38.143157 23057 sgd_solver.cpp:105] Iteration 5328, lr = 0.005
I0406 14:38:43.379559 23057 solver.cpp:218] Iteration 5340 (2.29167 iter/s, 5.23637s/12 iters), loss = 0.580659
I0406 14:38:43.379599 23057 solver.cpp:237]     Train net output #0: loss = 0.580659 (* 1 = 0.580659 loss)
I0406 14:38:43.379606 23057 sgd_solver.cpp:105] Iteration 5340, lr = 0.005
I0406 14:38:48.609433 23057 solver.cpp:218] Iteration 5352 (2.29455 iter/s, 5.22978s/12 iters), loss = 0.443549
I0406 14:38:48.609481 23057 solver.cpp:237]     Train net output #0: loss = 0.443549 (* 1 = 0.443549 loss)
I0406 14:38:48.609486 23057 sgd_solver.cpp:105] Iteration 5352, lr = 0.005
I0406 14:38:52.085166 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:38:53.767519 23057 solver.cpp:218] Iteration 5364 (2.32649 iter/s, 5.15798s/12 iters), loss = 0.597286
I0406 14:38:53.767575 23057 solver.cpp:237]     Train net output #0: loss = 0.597286 (* 1 = 0.597286 loss)
I0406 14:38:53.767582 23057 sgd_solver.cpp:105] Iteration 5364, lr = 0.005
I0406 14:38:59.240121 23057 solver.cpp:218] Iteration 5376 (2.19279 iter/s, 5.47249s/12 iters), loss = 0.413631
I0406 14:38:59.240159 23057 solver.cpp:237]     Train net output #0: loss = 0.413631 (* 1 = 0.413631 loss)
I0406 14:38:59.240165 23057 sgd_solver.cpp:105] Iteration 5376, lr = 0.005
I0406 14:39:04.509932 23057 solver.cpp:218] Iteration 5388 (2.27716 iter/s, 5.26973s/12 iters), loss = 0.448093
I0406 14:39:04.509964 23057 solver.cpp:237]     Train net output #0: loss = 0.448093 (* 1 = 0.448093 loss)
I0406 14:39:04.509969 23057 sgd_solver.cpp:105] Iteration 5388, lr = 0.005
I0406 14:39:09.649920 23057 solver.cpp:218] Iteration 5400 (2.33468 iter/s, 5.1399s/12 iters), loss = 0.455788
I0406 14:39:09.650018 23057 solver.cpp:237]     Train net output #0: loss = 0.455788 (* 1 = 0.455788 loss)
I0406 14:39:09.650024 23057 sgd_solver.cpp:105] Iteration 5400, lr = 0.005
I0406 14:39:11.658967 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel
I0406 14:39:14.720919 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate
I0406 14:39:17.045725 23057 solver.cpp:330] Iteration 5406, Testing net (#0)
I0406 14:39:17.045745 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:39:19.357177 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:39:21.551538 23057 solver.cpp:397]     Test net output #0: accuracy = 0.35049
I0406 14:39:21.551573 23057 solver.cpp:397]     Test net output #1: loss = 3.27426 (* 1 = 3.27426 loss)
I0406 14:39:23.514403 23057 solver.cpp:218] Iteration 5412 (0.865534 iter/s, 13.8643s/12 iters), loss = 0.671705
I0406 14:39:23.514449 23057 solver.cpp:237]     Train net output #0: loss = 0.671705 (* 1 = 0.671705 loss)
I0406 14:39:23.514454 23057 sgd_solver.cpp:105] Iteration 5412, lr = 0.005
I0406 14:39:28.880528 23057 solver.cpp:218] Iteration 5424 (2.23629 iter/s, 5.36602s/12 iters), loss = 0.39991
I0406 14:39:28.880573 23057 solver.cpp:237]     Train net output #0: loss = 0.39991 (* 1 = 0.39991 loss)
I0406 14:39:28.880579 23057 sgd_solver.cpp:105] Iteration 5424, lr = 0.005
I0406 14:39:34.029055 23057 solver.cpp:218] Iteration 5436 (2.33081 iter/s, 5.14843s/12 iters), loss = 0.537992
I0406 14:39:34.029111 23057 solver.cpp:237]     Train net output #0: loss = 0.537992 (* 1 = 0.537992 loss)
I0406 14:39:34.029120 23057 sgd_solver.cpp:105] Iteration 5436, lr = 0.005
I0406 14:39:39.117529 23057 solver.cpp:218] Iteration 5448 (2.35832 iter/s, 5.08837s/12 iters), loss = 0.662717
I0406 14:39:39.117568 23057 solver.cpp:237]     Train net output #0: loss = 0.662717 (* 1 = 0.662717 loss)
I0406 14:39:39.117574 23057 sgd_solver.cpp:105] Iteration 5448, lr = 0.005
I0406 14:39:44.450050 23057 solver.cpp:218] Iteration 5460 (2.25038 iter/s, 5.33243s/12 iters), loss = 0.370613
I0406 14:39:44.450184 23057 solver.cpp:237]     Train net output #0: loss = 0.370613 (* 1 = 0.370613 loss)
I0406 14:39:44.450191 23057 sgd_solver.cpp:105] Iteration 5460, lr = 0.005
I0406 14:39:45.038345 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:39:49.727083 23057 solver.cpp:218] Iteration 5472 (2.27409 iter/s, 5.27684s/12 iters), loss = 0.415247
I0406 14:39:49.727149 23057 solver.cpp:237]     Train net output #0: loss = 0.415247 (* 1 = 0.415247 loss)
I0406 14:39:49.727159 23057 sgd_solver.cpp:105] Iteration 5472, lr = 0.005
I0406 14:39:55.098637 23057 solver.cpp:218] Iteration 5484 (2.23404 iter/s, 5.37143s/12 iters), loss = 0.351616
I0406 14:39:55.098690 23057 solver.cpp:237]     Train net output #0: loss = 0.351616 (* 1 = 0.351616 loss)
I0406 14:39:55.098698 23057 sgd_solver.cpp:105] Iteration 5484, lr = 0.005
I0406 14:40:00.409173 23057 solver.cpp:218] Iteration 5496 (2.25971 iter/s, 5.31043s/12 iters), loss = 0.358986
I0406 14:40:00.409226 23057 solver.cpp:237]     Train net output #0: loss = 0.358986 (* 1 = 0.358986 loss)
I0406 14:40:00.409235 23057 sgd_solver.cpp:105] Iteration 5496, lr = 0.005
I0406 14:40:05.347038 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel
I0406 14:40:08.452399 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate
I0406 14:40:10.752082 23057 solver.cpp:330] Iteration 5508, Testing net (#0)
I0406 14:40:10.752101 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:40:12.893255 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:40:15.053704 23057 solver.cpp:397]     Test net output #0: accuracy = 0.365809
I0406 14:40:15.053812 23057 solver.cpp:397]     Test net output #1: loss = 3.24416 (* 1 = 3.24416 loss)
I0406 14:40:15.194236 23057 solver.cpp:218] Iteration 5508 (0.81164 iter/s, 14.7849s/12 iters), loss = 0.648364
I0406 14:40:15.194288 23057 solver.cpp:237]     Train net output #0: loss = 0.648364 (* 1 = 0.648364 loss)
I0406 14:40:15.194298 23057 sgd_solver.cpp:105] Iteration 5508, lr = 0.005
I0406 14:40:19.694207 23057 solver.cpp:218] Iteration 5520 (2.66674 iter/s, 4.49987s/12 iters), loss = 0.440694
I0406 14:40:19.694247 23057 solver.cpp:237]     Train net output #0: loss = 0.440694 (* 1 = 0.440694 loss)
I0406 14:40:19.694253 23057 sgd_solver.cpp:105] Iteration 5520, lr = 0.005
I0406 14:40:22.253871 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:40:24.977097 23057 solver.cpp:218] Iteration 5532 (2.27153 iter/s, 5.28279s/12 iters), loss = 0.413619
I0406 14:40:24.977144 23057 solver.cpp:237]     Train net output #0: loss = 0.413619 (* 1 = 0.413619 loss)
I0406 14:40:24.977150 23057 sgd_solver.cpp:105] Iteration 5532, lr = 0.005
I0406 14:40:30.339967 23057 solver.cpp:218] Iteration 5544 (2.23765 iter/s, 5.36277s/12 iters), loss = 0.600021
I0406 14:40:30.340009 23057 solver.cpp:237]     Train net output #0: loss = 0.600021 (* 1 = 0.600021 loss)
I0406 14:40:30.340015 23057 sgd_solver.cpp:105] Iteration 5544, lr = 0.005
I0406 14:40:35.405910 23057 solver.cpp:218] Iteration 5556 (2.3688 iter/s, 5.06585s/12 iters), loss = 0.686143
I0406 14:40:35.405956 23057 solver.cpp:237]     Train net output #0: loss = 0.686143 (* 1 = 0.686143 loss)
I0406 14:40:35.405962 23057 sgd_solver.cpp:105] Iteration 5556, lr = 0.005
I0406 14:40:38.167479 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:40:40.681646 23057 solver.cpp:218] Iteration 5568 (2.27461 iter/s, 5.27564s/12 iters), loss = 0.569762
I0406 14:40:40.681686 23057 solver.cpp:237]     Train net output #0: loss = 0.569762 (* 1 = 0.569762 loss)
I0406 14:40:40.681691 23057 sgd_solver.cpp:105] Iteration 5568, lr = 0.005
I0406 14:40:45.767357 23057 solver.cpp:218] Iteration 5580 (2.3596 iter/s, 5.08562s/12 iters), loss = 0.569339
I0406 14:40:45.767491 23057 solver.cpp:237]     Train net output #0: loss = 0.569339 (* 1 = 0.569339 loss)
I0406 14:40:45.767498 23057 sgd_solver.cpp:105] Iteration 5580, lr = 0.005
I0406 14:40:51.018841 23057 solver.cpp:218] Iteration 5592 (2.28515 iter/s, 5.2513s/12 iters), loss = 0.509088
I0406 14:40:51.018896 23057 solver.cpp:237]     Train net output #0: loss = 0.509088 (* 1 = 0.509088 loss)
I0406 14:40:51.018905 23057 sgd_solver.cpp:105] Iteration 5592, lr = 0.005
I0406 14:40:56.340885 23057 solver.cpp:218] Iteration 5604 (2.25482 iter/s, 5.32193s/12 iters), loss = 0.343012
I0406 14:40:56.340929 23057 solver.cpp:237]     Train net output #0: loss = 0.343012 (* 1 = 0.343012 loss)
I0406 14:40:56.340935 23057 sgd_solver.cpp:105] Iteration 5604, lr = 0.005
I0406 14:40:58.622632 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel
I0406 14:41:01.570950 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate
I0406 14:41:03.866832 23057 solver.cpp:330] Iteration 5610, Testing net (#0)
I0406 14:41:03.866852 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:41:06.001237 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:41:08.249658 23057 solver.cpp:397]     Test net output #0: accuracy = 0.375613
I0406 14:41:08.249686 23057 solver.cpp:397]     Test net output #1: loss = 3.26696 (* 1 = 3.26696 loss)
I0406 14:41:10.033232 23057 solver.cpp:218] Iteration 5616 (0.876412 iter/s, 13.6922s/12 iters), loss = 0.439382
I0406 14:41:10.033282 23057 solver.cpp:237]     Train net output #0: loss = 0.439382 (* 1 = 0.439382 loss)
I0406 14:41:10.033290 23057 sgd_solver.cpp:105] Iteration 5616, lr = 0.005
I0406 14:41:15.337808 23057 solver.cpp:218] Iteration 5628 (2.26224 iter/s, 5.30447s/12 iters), loss = 0.452483
I0406 14:41:15.337879 23057 solver.cpp:237]     Train net output #0: loss = 0.452483 (* 1 = 0.452483 loss)
I0406 14:41:15.337888 23057 sgd_solver.cpp:105] Iteration 5628, lr = 0.005
I0406 14:41:20.534801 23057 solver.cpp:218] Iteration 5640 (2.30908 iter/s, 5.19687s/12 iters), loss = 0.331741
I0406 14:41:20.534926 23057 solver.cpp:237]     Train net output #0: loss = 0.331741 (* 1 = 0.331741 loss)
I0406 14:41:20.534936 23057 sgd_solver.cpp:105] Iteration 5640, lr = 0.005
I0406 14:41:25.520272 23057 solver.cpp:218] Iteration 5652 (2.40708 iter/s, 4.9853s/12 iters), loss = 0.549777
I0406 14:41:25.520315 23057 solver.cpp:237]     Train net output #0: loss = 0.549777 (* 1 = 0.549777 loss)
I0406 14:41:25.520323 23057 sgd_solver.cpp:105] Iteration 5652, lr = 0.005
I0406 14:41:30.463848 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:41:30.685092 23057 solver.cpp:218] Iteration 5664 (2.32346 iter/s, 5.16472s/12 iters), loss = 0.45296
I0406 14:41:30.685135 23057 solver.cpp:237]     Train net output #0: loss = 0.45296 (* 1 = 0.45296 loss)
I0406 14:41:30.685142 23057 sgd_solver.cpp:105] Iteration 5664, lr = 0.005
I0406 14:41:35.959569 23057 solver.cpp:218] Iteration 5676 (2.27515 iter/s, 5.27438s/12 iters), loss = 0.351661
I0406 14:41:35.959617 23057 solver.cpp:237]     Train net output #0: loss = 0.351661 (* 1 = 0.351661 loss)
I0406 14:41:35.959625 23057 sgd_solver.cpp:105] Iteration 5676, lr = 0.005
I0406 14:41:41.366540 23057 solver.cpp:218] Iteration 5688 (2.2194 iter/s, 5.40687s/12 iters), loss = 0.414565
I0406 14:41:41.366588 23057 solver.cpp:237]     Train net output #0: loss = 0.414565 (* 1 = 0.414565 loss)
I0406 14:41:41.366595 23057 sgd_solver.cpp:105] Iteration 5688, lr = 0.005
I0406 14:41:46.525996 23057 solver.cpp:218] Iteration 5700 (2.32587 iter/s, 5.15936s/12 iters), loss = 0.279871
I0406 14:41:46.526039 23057 solver.cpp:237]     Train net output #0: loss = 0.279871 (* 1 = 0.279871 loss)
I0406 14:41:46.526046 23057 sgd_solver.cpp:105] Iteration 5700, lr = 0.005
I0406 14:41:51.020606 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel
I0406 14:41:54.076357 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate
I0406 14:41:57.027320 23057 solver.cpp:330] Iteration 5712, Testing net (#0)
I0406 14:41:57.027343 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:41:59.238360 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:42:01.441267 23057 solver.cpp:397]     Test net output #0: accuracy = 0.384191
I0406 14:42:01.441304 23057 solver.cpp:397]     Test net output #1: loss = 3.09827 (* 1 = 3.09827 loss)
I0406 14:42:01.581792 23057 solver.cpp:218] Iteration 5712 (0.797044 iter/s, 15.0556s/12 iters), loss = 0.574749
I0406 14:42:01.581840 23057 solver.cpp:237]     Train net output #0: loss = 0.574749 (* 1 = 0.574749 loss)
I0406 14:42:01.581845 23057 sgd_solver.cpp:105] Iteration 5712, lr = 0.005
I0406 14:42:05.983882 23057 solver.cpp:218] Iteration 5724 (2.72604 iter/s, 4.40199s/12 iters), loss = 0.41638
I0406 14:42:05.983932 23057 solver.cpp:237]     Train net output #0: loss = 0.41638 (* 1 = 0.41638 loss)
I0406 14:42:05.983940 23057 sgd_solver.cpp:105] Iteration 5724, lr = 0.005
I0406 14:42:11.229910 23057 solver.cpp:218] Iteration 5736 (2.28749 iter/s, 5.24592s/12 iters), loss = 0.485074
I0406 14:42:11.229951 23057 solver.cpp:237]     Train net output #0: loss = 0.485074 (* 1 = 0.485074 loss)
I0406 14:42:11.229957 23057 sgd_solver.cpp:105] Iteration 5736, lr = 0.005
I0406 14:42:16.412505 23057 solver.cpp:218] Iteration 5748 (2.31549 iter/s, 5.1825s/12 iters), loss = 0.416637
I0406 14:42:16.412544 23057 solver.cpp:237]     Train net output #0: loss = 0.416637 (* 1 = 0.416637 loss)
I0406 14:42:16.412550 23057 sgd_solver.cpp:105] Iteration 5748, lr = 0.005
I0406 14:42:21.628813 23057 solver.cpp:218] Iteration 5760 (2.30052 iter/s, 5.21621s/12 iters), loss = 0.290341
I0406 14:42:21.628947 23057 solver.cpp:237]     Train net output #0: loss = 0.290341 (* 1 = 0.290341 loss)
I0406 14:42:21.628955 23057 sgd_solver.cpp:105] Iteration 5760, lr = 0.005
I0406 14:42:23.629426 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:42:26.858857 23057 solver.cpp:218] Iteration 5772 (2.29452 iter/s, 5.22986s/12 iters), loss = 0.535507
I0406 14:42:26.858901 23057 solver.cpp:237]     Train net output #0: loss = 0.535507 (* 1 = 0.535507 loss)
I0406 14:42:26.858906 23057 sgd_solver.cpp:105] Iteration 5772, lr = 0.005
I0406 14:42:32.073906 23057 solver.cpp:218] Iteration 5784 (2.30108 iter/s, 5.21495s/12 iters), loss = 0.289152
I0406 14:42:32.073959 23057 solver.cpp:237]     Train net output #0: loss = 0.289152 (* 1 = 0.289152 loss)
I0406 14:42:32.073967 23057 sgd_solver.cpp:105] Iteration 5784, lr = 0.005
I0406 14:42:37.478479 23057 solver.cpp:218] Iteration 5796 (2.22038 iter/s, 5.40447s/12 iters), loss = 0.246716
I0406 14:42:37.478519 23057 solver.cpp:237]     Train net output #0: loss = 0.246716 (* 1 = 0.246716 loss)
I0406 14:42:37.478525 23057 sgd_solver.cpp:105] Iteration 5796, lr = 0.005
I0406 14:42:42.568991 23057 solver.cpp:218] Iteration 5808 (2.35737 iter/s, 5.09042s/12 iters), loss = 0.472525
I0406 14:42:42.569042 23057 solver.cpp:237]     Train net output #0: loss = 0.472525 (* 1 = 0.472525 loss)
I0406 14:42:42.569049 23057 sgd_solver.cpp:105] Iteration 5808, lr = 0.005
I0406 14:42:44.709836 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel
I0406 14:42:48.596112 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate
I0406 14:42:52.390343 23057 solver.cpp:330] Iteration 5814, Testing net (#0)
I0406 14:42:52.390430 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:42:54.413210 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:42:56.709982 23057 solver.cpp:397]     Test net output #0: accuracy = 0.364583
I0406 14:42:56.710013 23057 solver.cpp:397]     Test net output #1: loss = 3.18041 (* 1 = 3.18041 loss)
I0406 14:42:58.543431 23057 solver.cpp:218] Iteration 5820 (0.751209 iter/s, 15.9743s/12 iters), loss = 0.36424
I0406 14:42:58.543485 23057 solver.cpp:237]     Train net output #0: loss = 0.36424 (* 1 = 0.36424 loss)
I0406 14:42:58.543495 23057 sgd_solver.cpp:105] Iteration 5820, lr = 0.005
I0406 14:43:03.768662 23057 solver.cpp:218] Iteration 5832 (2.2966 iter/s, 5.22512s/12 iters), loss = 0.570785
I0406 14:43:03.768715 23057 solver.cpp:237]     Train net output #0: loss = 0.570785 (* 1 = 0.570785 loss)
I0406 14:43:03.768723 23057 sgd_solver.cpp:105] Iteration 5832, lr = 0.005
I0406 14:43:08.690240 23057 solver.cpp:218] Iteration 5844 (2.43829 iter/s, 4.92147s/12 iters), loss = 0.455355
I0406 14:43:08.690294 23057 solver.cpp:237]     Train net output #0: loss = 0.455355 (* 1 = 0.455355 loss)
I0406 14:43:08.690302 23057 sgd_solver.cpp:105] Iteration 5844, lr = 0.005
I0406 14:43:14.044466 23057 solver.cpp:218] Iteration 5856 (2.24126 iter/s, 5.35412s/12 iters), loss = 0.504539
I0406 14:43:14.044525 23057 solver.cpp:237]     Train net output #0: loss = 0.504539 (* 1 = 0.504539 loss)
I0406 14:43:14.044535 23057 sgd_solver.cpp:105] Iteration 5856, lr = 0.005
I0406 14:43:18.366302 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:43:19.242542 23057 solver.cpp:218] Iteration 5868 (2.3086 iter/s, 5.19796s/12 iters), loss = 0.342477
I0406 14:43:19.242583 23057 solver.cpp:237]     Train net output #0: loss = 0.342477 (* 1 = 0.342477 loss)
I0406 14:43:19.242589 23057 sgd_solver.cpp:105] Iteration 5868, lr = 0.005
I0406 14:43:24.295076 23057 solver.cpp:218] Iteration 5880 (2.37509 iter/s, 5.05244s/12 iters), loss = 0.432861
I0406 14:43:24.295195 23057 solver.cpp:237]     Train net output #0: loss = 0.432861 (* 1 = 0.432861 loss)
I0406 14:43:24.295202 23057 sgd_solver.cpp:105] Iteration 5880, lr = 0.005
I0406 14:43:29.712373 23057 solver.cpp:218] Iteration 5892 (2.2152 iter/s, 5.41712s/12 iters), loss = 0.257194
I0406 14:43:29.712432 23057 solver.cpp:237]     Train net output #0: loss = 0.257194 (* 1 = 0.257194 loss)
I0406 14:43:29.712441 23057 sgd_solver.cpp:105] Iteration 5892, lr = 0.005
I0406 14:43:35.224987 23057 solver.cpp:218] Iteration 5904 (2.17691 iter/s, 5.5124s/12 iters), loss = 0.336581
I0406 14:43:35.225039 23057 solver.cpp:237]     Train net output #0: loss = 0.336581 (* 1 = 0.336581 loss)
I0406 14:43:35.225049 23057 sgd_solver.cpp:105] Iteration 5904, lr = 0.005
I0406 14:43:41.110044 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel
I0406 14:43:44.574057 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate
I0406 14:43:47.401072 23057 solver.cpp:330] Iteration 5916, Testing net (#0)
I0406 14:43:47.401094 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:43:49.962544 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:43:53.047354 23057 solver.cpp:397]     Test net output #0: accuracy = 0.368873
I0406 14:43:53.047387 23057 solver.cpp:397]     Test net output #1: loss = 3.25085 (* 1 = 3.25085 loss)
I0406 14:43:53.189337 23057 solver.cpp:218] Iteration 5916 (0.667997 iter/s, 17.9642s/12 iters), loss = 0.380029
I0406 14:43:53.189378 23057 solver.cpp:237]     Train net output #0: loss = 0.380029 (* 1 = 0.380029 loss)
I0406 14:43:53.189383 23057 sgd_solver.cpp:105] Iteration 5916, lr = 0.005
I0406 14:43:58.294239 23057 solver.cpp:218] Iteration 5928 (2.35073 iter/s, 5.1048s/12 iters), loss = 0.414762
I0406 14:43:58.294363 23057 solver.cpp:237]     Train net output #0: loss = 0.414762 (* 1 = 0.414762 loss)
I0406 14:43:58.294370 23057 sgd_solver.cpp:105] Iteration 5928, lr = 0.005
I0406 14:44:04.626384 23057 solver.cpp:218] Iteration 5940 (1.89515 iter/s, 6.33196s/12 iters), loss = 0.456733
I0406 14:44:04.626431 23057 solver.cpp:237]     Train net output #0: loss = 0.456733 (* 1 = 0.456733 loss)
I0406 14:44:04.626441 23057 sgd_solver.cpp:105] Iteration 5940, lr = 0.005
I0406 14:44:10.499275 23057 solver.cpp:218] Iteration 5952 (2.04333 iter/s, 5.87278s/12 iters), loss = 0.518516
I0406 14:44:10.499337 23057 solver.cpp:237]     Train net output #0: loss = 0.518516 (* 1 = 0.518516 loss)
I0406 14:44:10.499348 23057 sgd_solver.cpp:105] Iteration 5952, lr = 0.005
I0406 14:44:16.654502 23057 solver.cpp:218] Iteration 5964 (1.9496 iter/s, 6.15511s/12 iters), loss = 0.592578
I0406 14:44:16.654552 23057 solver.cpp:237]     Train net output #0: loss = 0.592578 (* 1 = 0.592578 loss)
I0406 14:44:16.654561 23057 sgd_solver.cpp:105] Iteration 5964, lr = 0.005
I0406 14:44:17.992846 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:44:22.323802 23057 solver.cpp:218] Iteration 5976 (2.1167 iter/s, 5.66919s/12 iters), loss = 0.372712
I0406 14:44:22.323856 23057 solver.cpp:237]     Train net output #0: loss = 0.372712 (* 1 = 0.372712 loss)
I0406 14:44:22.323864 23057 sgd_solver.cpp:105] Iteration 5976, lr = 0.005
I0406 14:44:28.248234 23057 solver.cpp:218] Iteration 5988 (2.02555 iter/s, 5.92432s/12 iters), loss = 0.403783
I0406 14:44:28.248279 23057 solver.cpp:237]     Train net output #0: loss = 0.403783 (* 1 = 0.403783 loss)
I0406 14:44:28.248286 23057 sgd_solver.cpp:105] Iteration 5988, lr = 0.005
I0406 14:44:34.404347 23057 solver.cpp:218] Iteration 6000 (1.94932 iter/s, 6.156s/12 iters), loss = 0.318681
I0406 14:44:34.404489 23057 solver.cpp:237]     Train net output #0: loss = 0.318681 (* 1 = 0.318681 loss)
I0406 14:44:34.404498 23057 sgd_solver.cpp:105] Iteration 6000, lr = 0.005
I0406 14:44:40.595150 23057 solver.cpp:218] Iteration 6012 (1.93842 iter/s, 6.1906s/12 iters), loss = 0.222454
I0406 14:44:40.601356 23057 solver.cpp:237]     Train net output #0: loss = 0.222454 (* 1 = 0.222454 loss)
I0406 14:44:40.601377 23057 sgd_solver.cpp:105] Iteration 6012, lr = 0.005
I0406 14:44:43.010669 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel
I0406 14:44:46.508025 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate
I0406 14:44:49.412735 23057 solver.cpp:330] Iteration 6018, Testing net (#0)
I0406 14:44:49.412758 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:44:52.214120 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:44:55.043834 23057 solver.cpp:397]     Test net output #0: accuracy = 0.367034
I0406 14:44:55.043872 23057 solver.cpp:397]     Test net output #1: loss = 3.22092 (* 1 = 3.22092 loss)
I0406 14:44:57.087656 23057 solver.cpp:218] Iteration 6024 (0.727883 iter/s, 16.4862s/12 iters), loss = 0.242281
I0406 14:44:57.087713 23057 solver.cpp:237]     Train net output #0: loss = 0.242281 (* 1 = 0.242281 loss)
I0406 14:44:57.087721 23057 sgd_solver.cpp:105] Iteration 6024, lr = 0.005
I0406 14:45:02.707787 23057 solver.cpp:218] Iteration 6036 (2.13523 iter/s, 5.62001s/12 iters), loss = 0.403363
I0406 14:45:02.707839 23057 solver.cpp:237]     Train net output #0: loss = 0.403363 (* 1 = 0.403363 loss)
I0406 14:45:02.707849 23057 sgd_solver.cpp:105] Iteration 6036, lr = 0.005
I0406 14:45:08.751497 23057 solver.cpp:218] Iteration 6048 (1.98557 iter/s, 6.04359s/12 iters), loss = 0.512374
I0406 14:45:08.751643 23057 solver.cpp:237]     Train net output #0: loss = 0.512374 (* 1 = 0.512374 loss)
I0406 14:45:08.751652 23057 sgd_solver.cpp:105] Iteration 6048, lr = 0.005
I0406 14:45:14.398655 23057 solver.cpp:218] Iteration 6060 (2.12504 iter/s, 5.64695s/12 iters), loss = 0.438643
I0406 14:45:14.398712 23057 solver.cpp:237]     Train net output #0: loss = 0.438643 (* 1 = 0.438643 loss)
I0406 14:45:14.398721 23057 sgd_solver.cpp:105] Iteration 6060, lr = 0.005
I0406 14:45:18.485502 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:45:20.229493 23057 solver.cpp:218] Iteration 6072 (2.05807 iter/s, 5.83072s/12 iters), loss = 0.574662
I0406 14:45:20.229545 23057 solver.cpp:237]     Train net output #0: loss = 0.574662 (* 1 = 0.574662 loss)
I0406 14:45:20.229553 23057 sgd_solver.cpp:105] Iteration 6072, lr = 0.005
I0406 14:45:25.580384 23057 solver.cpp:218] Iteration 6084 (2.24266 iter/s, 5.35078s/12 iters), loss = 0.5315
I0406 14:45:25.580430 23057 solver.cpp:237]     Train net output #0: loss = 0.5315 (* 1 = 0.5315 loss)
I0406 14:45:25.580435 23057 sgd_solver.cpp:105] Iteration 6084, lr = 0.005
I0406 14:45:31.675789 23057 solver.cpp:218] Iteration 6096 (1.96873 iter/s, 6.09529s/12 iters), loss = 0.356427
I0406 14:45:31.682001 23057 solver.cpp:237]     Train net output #0: loss = 0.356427 (* 1 = 0.356427 loss)
I0406 14:45:31.682021 23057 sgd_solver.cpp:105] Iteration 6096, lr = 0.005
I0406 14:45:37.593452 23057 solver.cpp:218] Iteration 6108 (2.02997 iter/s, 5.9114s/12 iters), loss = 0.349531
I0406 14:45:37.593506 23057 solver.cpp:237]     Train net output #0: loss = 0.349531 (* 1 = 0.349531 loss)
I0406 14:45:37.593515 23057 sgd_solver.cpp:105] Iteration 6108, lr = 0.005
I0406 14:45:43.169236 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel
I0406 14:45:46.419751 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate
I0406 14:45:48.885360 23057 solver.cpp:330] Iteration 6120, Testing net (#0)
I0406 14:45:48.885380 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:45:51.133589 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:45:54.001214 23057 solver.cpp:397]     Test net output #0: accuracy = 0.371324
I0406 14:45:54.001250 23057 solver.cpp:397]     Test net output #1: loss = 3.16797 (* 1 = 3.16797 loss)
I0406 14:45:54.141413 23057 solver.cpp:218] Iteration 6120 (0.725174 iter/s, 16.5478s/12 iters), loss = 0.400149
I0406 14:45:54.141467 23057 solver.cpp:237]     Train net output #0: loss = 0.400149 (* 1 = 0.400149 loss)
I0406 14:45:54.141476 23057 sgd_solver.cpp:105] Iteration 6120, lr = 0.005
I0406 14:45:59.025059 23057 solver.cpp:218] Iteration 6132 (2.45723 iter/s, 4.88354s/12 iters), loss = 0.241484
I0406 14:45:59.025111 23057 solver.cpp:237]     Train net output #0: loss = 0.241484 (* 1 = 0.241484 loss)
I0406 14:45:59.025123 23057 sgd_solver.cpp:105] Iteration 6132, lr = 0.005
I0406 14:46:04.314033 23057 solver.cpp:218] Iteration 6144 (2.26892 iter/s, 5.28887s/12 iters), loss = 0.239963
I0406 14:46:04.314069 23057 solver.cpp:237]     Train net output #0: loss = 0.239963 (* 1 = 0.239963 loss)
I0406 14:46:04.314075 23057 sgd_solver.cpp:105] Iteration 6144, lr = 0.005
I0406 14:46:09.502779 23057 solver.cpp:218] Iteration 6156 (2.31274 iter/s, 5.18865s/12 iters), loss = 0.524511
I0406 14:46:09.502822 23057 solver.cpp:237]     Train net output #0: loss = 0.524511 (* 1 = 0.524511 loss)
I0406 14:46:09.502828 23057 sgd_solver.cpp:105] Iteration 6156, lr = 0.005
I0406 14:46:14.731004 23057 solver.cpp:218] Iteration 6168 (2.29528 iter/s, 5.22813s/12 iters), loss = 0.564998
I0406 14:46:14.731094 23057 solver.cpp:237]     Train net output #0: loss = 0.564998 (* 1 = 0.564998 loss)
I0406 14:46:14.731101 23057 sgd_solver.cpp:105] Iteration 6168, lr = 0.005
I0406 14:46:15.384161 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:46:19.721002 23057 solver.cpp:218] Iteration 6180 (2.40488 iter/s, 4.98985s/12 iters), loss = 0.294735
I0406 14:46:19.721053 23057 solver.cpp:237]     Train net output #0: loss = 0.294735 (* 1 = 0.294735 loss)
I0406 14:46:19.721061 23057 sgd_solver.cpp:105] Iteration 6180, lr = 0.005
I0406 14:46:24.985641 23057 solver.cpp:218] Iteration 6192 (2.27941 iter/s, 5.26453s/12 iters), loss = 0.474545
I0406 14:46:24.985685 23057 solver.cpp:237]     Train net output #0: loss = 0.474545 (* 1 = 0.474545 loss)
I0406 14:46:24.985692 23057 sgd_solver.cpp:105] Iteration 6192, lr = 0.005
I0406 14:46:30.053496 23057 solver.cpp:218] Iteration 6204 (2.36791 iter/s, 5.06776s/12 iters), loss = 0.264619
I0406 14:46:30.053542 23057 solver.cpp:237]     Train net output #0: loss = 0.264619 (* 1 = 0.264619 loss)
I0406 14:46:30.053548 23057 sgd_solver.cpp:105] Iteration 6204, lr = 0.005
I0406 14:46:35.363512 23057 solver.cpp:218] Iteration 6216 (2.25992 iter/s, 5.30992s/12 iters), loss = 0.28183
I0406 14:46:35.363546 23057 solver.cpp:237]     Train net output #0: loss = 0.28183 (* 1 = 0.28183 loss)
I0406 14:46:35.363551 23057 sgd_solver.cpp:105] Iteration 6216, lr = 0.005
I0406 14:46:37.339275 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel
I0406 14:46:40.325824 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate
I0406 14:46:42.623991 23057 solver.cpp:330] Iteration 6222, Testing net (#0)
I0406 14:46:42.624012 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:46:44.536698 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:46:45.895583 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:46:47.073258 23057 solver.cpp:397]     Test net output #0: accuracy = 0.377451
I0406 14:46:47.073294 23057 solver.cpp:397]     Test net output #1: loss = 3.17084 (* 1 = 3.17084 loss)
I0406 14:46:48.890494 23057 solver.cpp:218] Iteration 6228 (0.887126 iter/s, 13.5268s/12 iters), loss = 0.408842
I0406 14:46:48.890540 23057 solver.cpp:237]     Train net output #0: loss = 0.408842 (* 1 = 0.408842 loss)
I0406 14:46:48.890548 23057 sgd_solver.cpp:105] Iteration 6228, lr = 0.005
I0406 14:46:53.911197 23057 solver.cpp:218] Iteration 6240 (2.39015 iter/s, 5.0206s/12 iters), loss = 0.484709
I0406 14:46:53.911252 23057 solver.cpp:237]     Train net output #0: loss = 0.484709 (* 1 = 0.484709 loss)
I0406 14:46:53.911260 23057 sgd_solver.cpp:105] Iteration 6240, lr = 0.005
I0406 14:46:59.090418 23057 solver.cpp:218] Iteration 6252 (2.317 iter/s, 5.17911s/12 iters), loss = 0.366862
I0406 14:46:59.090461 23057 solver.cpp:237]     Train net output #0: loss = 0.366863 (* 1 = 0.366863 loss)
I0406 14:46:59.090467 23057 sgd_solver.cpp:105] Iteration 6252, lr = 0.005
I0406 14:47:04.307824 23057 solver.cpp:218] Iteration 6264 (2.30004 iter/s, 5.21731s/12 iters), loss = 0.538451
I0406 14:47:04.307862 23057 solver.cpp:237]     Train net output #0: loss = 0.538451 (* 1 = 0.538451 loss)
I0406 14:47:04.307868 23057 sgd_solver.cpp:105] Iteration 6264, lr = 0.005
I0406 14:47:07.361174 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:47:09.841192 23057 solver.cpp:218] Iteration 6276 (2.1687 iter/s, 5.53327s/12 iters), loss = 0.481389
I0406 14:47:09.841244 23057 solver.cpp:237]     Train net output #0: loss = 0.481389 (* 1 = 0.481389 loss)
I0406 14:47:09.841253 23057 sgd_solver.cpp:105] Iteration 6276, lr = 0.005
I0406 14:47:15.066812 23057 solver.cpp:218] Iteration 6288 (2.29643 iter/s, 5.22551s/12 iters), loss = 0.453504
I0406 14:47:15.066872 23057 solver.cpp:237]     Train net output #0: loss = 0.453504 (* 1 = 0.453504 loss)
I0406 14:47:15.066881 23057 sgd_solver.cpp:105] Iteration 6288, lr = 0.005
I0406 14:47:20.458240 23057 solver.cpp:218] Iteration 6300 (2.2258 iter/s, 5.39131s/12 iters), loss = 0.328337
I0406 14:47:20.458361 23057 solver.cpp:237]     Train net output #0: loss = 0.328337 (* 1 = 0.328337 loss)
I0406 14:47:20.458370 23057 sgd_solver.cpp:105] Iteration 6300, lr = 0.005
I0406 14:47:25.880776 23057 solver.cpp:218] Iteration 6312 (2.21306 iter/s, 5.42236s/12 iters), loss = 0.432927
I0406 14:47:25.880831 23057 solver.cpp:237]     Train net output #0: loss = 0.432927 (* 1 = 0.432927 loss)
I0406 14:47:25.880839 23057 sgd_solver.cpp:105] Iteration 6312, lr = 0.005
I0406 14:47:30.812440 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel
I0406 14:47:33.864279 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate
I0406 14:47:36.194674 23057 solver.cpp:330] Iteration 6324, Testing net (#0)
I0406 14:47:36.194694 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:47:38.129046 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:47:40.622236 23057 solver.cpp:397]     Test net output #0: accuracy = 0.375
I0406 14:47:40.622263 23057 solver.cpp:397]     Test net output #1: loss = 3.24013 (* 1 = 3.24013 loss)
I0406 14:47:40.762701 23057 solver.cpp:218] Iteration 6324 (0.806357 iter/s, 14.8817s/12 iters), loss = 0.505498
I0406 14:47:40.762766 23057 solver.cpp:237]     Train net output #0: loss = 0.505498 (* 1 = 0.505498 loss)
I0406 14:47:40.762773 23057 sgd_solver.cpp:105] Iteration 6324, lr = 0.005
I0406 14:47:45.335269 23057 solver.cpp:218] Iteration 6336 (2.62441 iter/s, 4.57245s/12 iters), loss = 0.475771
I0406 14:47:45.335306 23057 solver.cpp:237]     Train net output #0: loss = 0.475771 (* 1 = 0.475771 loss)
I0406 14:47:45.335312 23057 sgd_solver.cpp:105] Iteration 6336, lr = 0.005
I0406 14:47:50.635286 23057 solver.cpp:218] Iteration 6348 (2.26418 iter/s, 5.29992s/12 iters), loss = 0.203062
I0406 14:47:50.635422 23057 solver.cpp:237]     Train net output #0: loss = 0.203062 (* 1 = 0.203062 loss)
I0406 14:47:50.635430 23057 sgd_solver.cpp:105] Iteration 6348, lr = 0.005
I0406 14:47:55.851689 23057 solver.cpp:218] Iteration 6360 (2.30052 iter/s, 5.21622s/12 iters), loss = 0.331559
I0406 14:47:55.851729 23057 solver.cpp:237]     Train net output #0: loss = 0.331559 (* 1 = 0.331559 loss)
I0406 14:47:55.851737 23057 sgd_solver.cpp:105] Iteration 6360, lr = 0.005
I0406 14:48:00.878895 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:48:01.070927 23057 solver.cpp:218] Iteration 6372 (2.29923 iter/s, 5.21914s/12 iters), loss = 0.342482
I0406 14:48:01.070986 23057 solver.cpp:237]     Train net output #0: loss = 0.342482 (* 1 = 0.342482 loss)
I0406 14:48:01.070994 23057 sgd_solver.cpp:105] Iteration 6372, lr = 0.005
I0406 14:48:06.479825 23057 solver.cpp:218] Iteration 6384 (2.21861 iter/s, 5.40879s/12 iters), loss = 0.318754
I0406 14:48:06.479872 23057 solver.cpp:237]     Train net output #0: loss = 0.318754 (* 1 = 0.318754 loss)
I0406 14:48:06.479880 23057 sgd_solver.cpp:105] Iteration 6384, lr = 0.005
I0406 14:48:11.719132 23057 solver.cpp:218] Iteration 6396 (2.29043 iter/s, 5.2392s/12 iters), loss = 0.54999
I0406 14:48:11.719187 23057 solver.cpp:237]     Train net output #0: loss = 0.549991 (* 1 = 0.549991 loss)
I0406 14:48:11.719194 23057 sgd_solver.cpp:105] Iteration 6396, lr = 0.005
I0406 14:48:16.995540 23057 solver.cpp:218] Iteration 6408 (2.27432 iter/s, 5.2763s/12 iters), loss = 0.499666
I0406 14:48:16.995581 23057 solver.cpp:237]     Train net output #0: loss = 0.499667 (* 1 = 0.499667 loss)
I0406 14:48:16.995587 23057 sgd_solver.cpp:105] Iteration 6408, lr = 0.005
I0406 14:48:22.350028 23057 solver.cpp:218] Iteration 6420 (2.24115 iter/s, 5.35439s/12 iters), loss = 0.271376
I0406 14:48:22.350118 23057 solver.cpp:237]     Train net output #0: loss = 0.271376 (* 1 = 0.271376 loss)
I0406 14:48:22.350126 23057 sgd_solver.cpp:105] Iteration 6420, lr = 0.005
I0406 14:48:24.522660 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel
I0406 14:48:27.520020 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate
I0406 14:48:29.859547 23057 solver.cpp:330] Iteration 6426, Testing net (#0)
I0406 14:48:29.859566 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:48:31.721310 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:48:34.254521 23057 solver.cpp:397]     Test net output #0: accuracy = 0.365196
I0406 14:48:34.254550 23057 solver.cpp:397]     Test net output #1: loss = 3.2612 (* 1 = 3.2612 loss)
I0406 14:48:36.175487 23057 solver.cpp:218] Iteration 6432 (0.867977 iter/s, 13.8253s/12 iters), loss = 0.272405
I0406 14:48:36.175529 23057 solver.cpp:237]     Train net output #0: loss = 0.272405 (* 1 = 0.272405 loss)
I0406 14:48:36.175535 23057 sgd_solver.cpp:105] Iteration 6432, lr = 0.005
I0406 14:48:41.530077 23057 solver.cpp:218] Iteration 6444 (2.24111 iter/s, 5.35449s/12 iters), loss = 0.337629
I0406 14:48:41.530120 23057 solver.cpp:237]     Train net output #0: loss = 0.337629 (* 1 = 0.337629 loss)
I0406 14:48:41.530126 23057 sgd_solver.cpp:105] Iteration 6444, lr = 0.005
I0406 14:48:46.728147 23057 solver.cpp:218] Iteration 6456 (2.3086 iter/s, 5.19797s/12 iters), loss = 0.327592
I0406 14:48:46.728204 23057 solver.cpp:237]     Train net output #0: loss = 0.327592 (* 1 = 0.327592 loss)
I0406 14:48:46.728211 23057 sgd_solver.cpp:105] Iteration 6456, lr = 0.005
I0406 14:48:51.996848 23057 solver.cpp:218] Iteration 6468 (2.27765 iter/s, 5.2686s/12 iters), loss = 0.354903
I0406 14:48:51.996894 23057 solver.cpp:237]     Train net output #0: loss = 0.354903 (* 1 = 0.354903 loss)
I0406 14:48:51.996901 23057 sgd_solver.cpp:105] Iteration 6468, lr = 0.005
I0406 14:48:54.097399 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:48:57.346524 23057 solver.cpp:218] Iteration 6480 (2.24317 iter/s, 5.34958s/12 iters), loss = 0.416205
I0406 14:48:57.346570 23057 solver.cpp:237]     Train net output #0: loss = 0.416205 (* 1 = 0.416205 loss)
I0406 14:48:57.346577 23057 sgd_solver.cpp:105] Iteration 6480, lr = 0.005
I0406 14:49:02.676357 23057 solver.cpp:218] Iteration 6492 (2.25152 iter/s, 5.32973s/12 iters), loss = 0.500413
I0406 14:49:02.676396 23057 solver.cpp:237]     Train net output #0: loss = 0.500413 (* 1 = 0.500413 loss)
I0406 14:49:02.676401 23057 sgd_solver.cpp:105] Iteration 6492, lr = 0.005
I0406 14:49:07.935328 23057 solver.cpp:218] Iteration 6504 (2.28186 iter/s, 5.25887s/12 iters), loss = 0.23488
I0406 14:49:07.935372 23057 solver.cpp:237]     Train net output #0: loss = 0.23488 (* 1 = 0.23488 loss)
I0406 14:49:07.935379 23057 sgd_solver.cpp:105] Iteration 6504, lr = 0.005
I0406 14:49:12.963510 23057 solver.cpp:218] Iteration 6516 (2.38659 iter/s, 5.02809s/12 iters), loss = 0.415278
I0406 14:49:12.963551 23057 solver.cpp:237]     Train net output #0: loss = 0.415278 (* 1 = 0.415278 loss)
I0406 14:49:12.963557 23057 sgd_solver.cpp:105] Iteration 6516, lr = 0.005
I0406 14:49:17.684715 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel
I0406 14:49:20.777817 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate
I0406 14:49:23.078671 23057 solver.cpp:330] Iteration 6528, Testing net (#0)
I0406 14:49:23.078691 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:49:24.932495 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:49:27.574916 23057 solver.cpp:397]     Test net output #0: accuracy = 0.384804
I0406 14:49:27.574945 23057 solver.cpp:397]     Test net output #1: loss = 3.11893 (* 1 = 3.11893 loss)
I0406 14:49:27.715461 23057 solver.cpp:218] Iteration 6528 (0.813461 iter/s, 14.7518s/12 iters), loss = 0.291243
I0406 14:49:27.715535 23057 solver.cpp:237]     Train net output #0: loss = 0.291243 (* 1 = 0.291243 loss)
I0406 14:49:27.715545 23057 sgd_solver.cpp:105] Iteration 6528, lr = 0.005
I0406 14:49:32.071105 23057 solver.cpp:218] Iteration 6540 (2.75512 iter/s, 4.35552s/12 iters), loss = 0.332655
I0406 14:49:32.071149 23057 solver.cpp:237]     Train net output #0: loss = 0.332656 (* 1 = 0.332656 loss)
I0406 14:49:32.071154 23057 sgd_solver.cpp:105] Iteration 6540, lr = 0.005
I0406 14:49:37.338452 23057 solver.cpp:218] Iteration 6552 (2.27823 iter/s, 5.26725s/12 iters), loss = 0.341928
I0406 14:49:37.338492 23057 solver.cpp:237]     Train net output #0: loss = 0.341928 (* 1 = 0.341928 loss)
I0406 14:49:37.338498 23057 sgd_solver.cpp:105] Iteration 6552, lr = 0.005
I0406 14:49:42.807922 23057 solver.cpp:218] Iteration 6564 (2.19403 iter/s, 5.46938s/12 iters), loss = 0.504018
I0406 14:49:42.807962 23057 solver.cpp:237]     Train net output #0: loss = 0.504018 (* 1 = 0.504018 loss)
I0406 14:49:42.807967 23057 sgd_solver.cpp:105] Iteration 6564, lr = 0.005
I0406 14:49:47.130776 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:49:47.971963 23057 solver.cpp:218] Iteration 6576 (2.32381 iter/s, 5.16394s/12 iters), loss = 0.451707
I0406 14:49:47.972007 23057 solver.cpp:237]     Train net output #0: loss = 0.451707 (* 1 = 0.451707 loss)
I0406 14:49:47.972014 23057 sgd_solver.cpp:105] Iteration 6576, lr = 0.005
I0406 14:49:53.375716 23057 solver.cpp:218] Iteration 6588 (2.22072 iter/s, 5.40365s/12 iters), loss = 0.2648
I0406 14:49:53.375761 23057 solver.cpp:237]     Train net output #0: loss = 0.2648 (* 1 = 0.2648 loss)
I0406 14:49:53.375767 23057 sgd_solver.cpp:105] Iteration 6588, lr = 0.005
I0406 14:49:58.681486 23057 solver.cpp:218] Iteration 6600 (2.26173 iter/s, 5.30567s/12 iters), loss = 0.202989
I0406 14:49:58.681608 23057 solver.cpp:237]     Train net output #0: loss = 0.202989 (* 1 = 0.202989 loss)
I0406 14:49:58.681615 23057 sgd_solver.cpp:105] Iteration 6600, lr = 0.005
I0406 14:50:03.993319 23057 solver.cpp:218] Iteration 6612 (2.25918 iter/s, 5.31166s/12 iters), loss = 0.436795
I0406 14:50:03.993364 23057 solver.cpp:237]     Train net output #0: loss = 0.436796 (* 1 = 0.436796 loss)
I0406 14:50:03.993373 23057 sgd_solver.cpp:105] Iteration 6612, lr = 0.005
I0406 14:50:09.115489 23057 solver.cpp:218] Iteration 6624 (2.3428 iter/s, 5.12207s/12 iters), loss = 0.355219
I0406 14:50:09.115525 23057 solver.cpp:237]     Train net output #0: loss = 0.35522 (* 1 = 0.35522 loss)
I0406 14:50:09.115531 23057 sgd_solver.cpp:105] Iteration 6624, lr = 0.005
I0406 14:50:11.085356 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel
I0406 14:50:14.108640 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate
I0406 14:50:16.410027 23057 solver.cpp:330] Iteration 6630, Testing net (#0)
I0406 14:50:16.410046 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:50:18.204525 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:50:20.801147 23057 solver.cpp:397]     Test net output #0: accuracy = 0.381127
I0406 14:50:20.801179 23057 solver.cpp:397]     Test net output #1: loss = 3.30558 (* 1 = 3.30558 loss)
I0406 14:50:22.778715 23057 solver.cpp:218] Iteration 6636 (0.87828 iter/s, 13.6631s/12 iters), loss = 0.460436
I0406 14:50:22.778766 23057 solver.cpp:237]     Train net output #0: loss = 0.460436 (* 1 = 0.460436 loss)
I0406 14:50:22.778772 23057 sgd_solver.cpp:105] Iteration 6636, lr = 0.005
I0406 14:50:27.832161 23057 solver.cpp:218] Iteration 6648 (2.37467 iter/s, 5.05334s/12 iters), loss = 0.300271
I0406 14:50:27.832212 23057 solver.cpp:237]     Train net output #0: loss = 0.300271 (* 1 = 0.300271 loss)
I0406 14:50:27.832219 23057 sgd_solver.cpp:105] Iteration 6648, lr = 0.005
I0406 14:50:33.028967 23057 solver.cpp:218] Iteration 6660 (2.30916 iter/s, 5.1967s/12 iters), loss = 0.32929
I0406 14:50:33.029084 23057 solver.cpp:237]     Train net output #0: loss = 0.32929 (* 1 = 0.32929 loss)
I0406 14:50:33.029094 23057 sgd_solver.cpp:105] Iteration 6660, lr = 0.005
I0406 14:50:38.211683 23057 solver.cpp:218] Iteration 6672 (2.31546 iter/s, 5.18255s/12 iters), loss = 0.411483
I0406 14:50:38.211733 23057 solver.cpp:237]     Train net output #0: loss = 0.411483 (* 1 = 0.411483 loss)
I0406 14:50:38.211741 23057 sgd_solver.cpp:105] Iteration 6672, lr = 0.005
I0406 14:50:39.610617 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:50:43.476125 23057 solver.cpp:218] Iteration 6684 (2.27949 iter/s, 5.26434s/12 iters), loss = 0.333981
I0406 14:50:43.476161 23057 solver.cpp:237]     Train net output #0: loss = 0.333981 (* 1 = 0.333981 loss)
I0406 14:50:43.476167 23057 sgd_solver.cpp:105] Iteration 6684, lr = 0.005
I0406 14:50:48.802888 23057 solver.cpp:218] Iteration 6696 (2.25281 iter/s, 5.32667s/12 iters), loss = 0.378522
I0406 14:50:48.802933 23057 solver.cpp:237]     Train net output #0: loss = 0.378522 (* 1 = 0.378522 loss)
I0406 14:50:48.802940 23057 sgd_solver.cpp:105] Iteration 6696, lr = 0.005
I0406 14:50:53.837879 23057 solver.cpp:218] Iteration 6708 (2.38337 iter/s, 5.03489s/12 iters), loss = 0.35788
I0406 14:50:53.837929 23057 solver.cpp:237]     Train net output #0: loss = 0.35788 (* 1 = 0.35788 loss)
I0406 14:50:53.837936 23057 sgd_solver.cpp:105] Iteration 6708, lr = 0.005
I0406 14:50:59.124398 23057 solver.cpp:218] Iteration 6720 (2.26997 iter/s, 5.28641s/12 iters), loss = 0.46964
I0406 14:50:59.124451 23057 solver.cpp:237]     Train net output #0: loss = 0.46964 (* 1 = 0.46964 loss)
I0406 14:50:59.124459 23057 sgd_solver.cpp:105] Iteration 6720, lr = 0.005
I0406 14:51:03.818374 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel
I0406 14:51:06.904402 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate
I0406 14:51:09.228235 23057 solver.cpp:330] Iteration 6732, Testing net (#0)
I0406 14:51:09.228264 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:51:10.983404 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:51:13.673800 23057 solver.cpp:397]     Test net output #0: accuracy = 0.385417
I0406 14:51:13.673830 23057 solver.cpp:397]     Test net output #1: loss = 3.15687 (* 1 = 3.15687 loss)
I0406 14:51:13.814262 23057 solver.cpp:218] Iteration 6732 (0.8169 iter/s, 14.6897s/12 iters), loss = 0.265143
I0406 14:51:13.814327 23057 solver.cpp:237]     Train net output #0: loss = 0.265144 (* 1 = 0.265144 loss)
I0406 14:51:13.814334 23057 sgd_solver.cpp:105] Iteration 6732, lr = 0.005
I0406 14:51:18.178247 23057 solver.cpp:218] Iteration 6744 (2.74985 iter/s, 4.36388s/12 iters), loss = 0.265473
I0406 14:51:18.178294 23057 solver.cpp:237]     Train net output #0: loss = 0.265473 (* 1 = 0.265473 loss)
I0406 14:51:18.178299 23057 sgd_solver.cpp:105] Iteration 6744, lr = 0.005
I0406 14:51:23.404680 23057 solver.cpp:218] Iteration 6756 (2.29607 iter/s, 5.22633s/12 iters), loss = 0.200165
I0406 14:51:23.404721 23057 solver.cpp:237]     Train net output #0: loss = 0.200165 (* 1 = 0.200165 loss)
I0406 14:51:23.404727 23057 sgd_solver.cpp:105] Iteration 6756, lr = 0.005
I0406 14:51:28.579469 23057 solver.cpp:218] Iteration 6768 (2.31898 iter/s, 5.17469s/12 iters), loss = 0.513978
I0406 14:51:28.579514 23057 solver.cpp:237]     Train net output #0: loss = 0.513979 (* 1 = 0.513979 loss)
I0406 14:51:28.579520 23057 sgd_solver.cpp:105] Iteration 6768, lr = 0.005
I0406 14:51:32.338618 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:51:33.982339 23057 solver.cpp:218] Iteration 6780 (2.22109 iter/s, 5.40276s/12 iters), loss = 0.359799
I0406 14:51:33.982481 23057 solver.cpp:237]     Train net output #0: loss = 0.359799 (* 1 = 0.359799 loss)
I0406 14:51:33.982492 23057 sgd_solver.cpp:105] Iteration 6780, lr = 0.005
I0406 14:51:39.222553 23057 solver.cpp:218] Iteration 6792 (2.29007 iter/s, 5.24002s/12 iters), loss = 0.234442
I0406 14:51:39.222612 23057 solver.cpp:237]     Train net output #0: loss = 0.234442 (* 1 = 0.234442 loss)
I0406 14:51:39.222621 23057 sgd_solver.cpp:105] Iteration 6792, lr = 0.005
I0406 14:51:44.489275 23057 solver.cpp:218] Iteration 6804 (2.27851 iter/s, 5.26661s/12 iters), loss = 0.42431
I0406 14:51:44.489318 23057 solver.cpp:237]     Train net output #0: loss = 0.42431 (* 1 = 0.42431 loss)
I0406 14:51:44.489329 23057 sgd_solver.cpp:105] Iteration 6804, lr = 0.005
I0406 14:51:49.484163 23057 solver.cpp:218] Iteration 6816 (2.4025 iter/s, 4.99479s/12 iters), loss = 0.314131
I0406 14:51:49.484211 23057 solver.cpp:237]     Train net output #0: loss = 0.314131 (* 1 = 0.314131 loss)
I0406 14:51:49.484216 23057 sgd_solver.cpp:105] Iteration 6816, lr = 0.005
I0406 14:51:54.672448 23057 solver.cpp:218] Iteration 6828 (2.31295 iter/s, 5.18818s/12 iters), loss = 0.461366
I0406 14:51:54.672489 23057 solver.cpp:237]     Train net output #0: loss = 0.461366 (* 1 = 0.461366 loss)
I0406 14:51:54.672497 23057 sgd_solver.cpp:105] Iteration 6828, lr = 0.005
I0406 14:51:56.768185 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel
I0406 14:51:59.761065 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate
I0406 14:52:02.448410 23057 solver.cpp:330] Iteration 6834, Testing net (#0)
I0406 14:52:02.448431 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:52:04.228695 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:52:07.009433 23057 solver.cpp:397]     Test net output #0: accuracy = 0.392157
I0406 14:52:07.009466 23057 solver.cpp:397]     Test net output #1: loss = 3.23739 (* 1 = 3.23739 loss)
I0406 14:52:08.911855 23057 solver.cpp:218] Iteration 6840 (0.842741 iter/s, 14.2392s/12 iters), loss = 0.374619
I0406 14:52:08.911896 23057 solver.cpp:237]     Train net output #0: loss = 0.374619 (* 1 = 0.374619 loss)
I0406 14:52:08.911902 23057 sgd_solver.cpp:105] Iteration 6840, lr = 0.005
I0406 14:52:14.184660 23057 solver.cpp:218] Iteration 6852 (2.27587 iter/s, 5.27271s/12 iters), loss = 0.328992
I0406 14:52:14.184700 23057 solver.cpp:237]     Train net output #0: loss = 0.328992 (* 1 = 0.328992 loss)
I0406 14:52:14.184705 23057 sgd_solver.cpp:105] Iteration 6852, lr = 0.005
I0406 14:52:19.440699 23057 solver.cpp:218] Iteration 6864 (2.28313 iter/s, 5.25594s/12 iters), loss = 0.283039
I0406 14:52:19.440739 23057 solver.cpp:237]     Train net output #0: loss = 0.283039 (* 1 = 0.283039 loss)
I0406 14:52:19.440747 23057 sgd_solver.cpp:105] Iteration 6864, lr = 0.005
I0406 14:52:24.665294 23057 solver.cpp:218] Iteration 6876 (2.29687 iter/s, 5.2245s/12 iters), loss = 0.405519
I0406 14:52:24.665340 23057 solver.cpp:237]     Train net output #0: loss = 0.405519 (* 1 = 0.405519 loss)
I0406 14:52:24.665346 23057 sgd_solver.cpp:105] Iteration 6876, lr = 0.005
I0406 14:52:25.299882 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:52:29.777024 23057 solver.cpp:218] Iteration 6888 (2.34759 iter/s, 5.11163s/12 iters), loss = 0.257374
I0406 14:52:29.777077 23057 solver.cpp:237]     Train net output #0: loss = 0.257374 (* 1 = 0.257374 loss)
I0406 14:52:29.777086 23057 sgd_solver.cpp:105] Iteration 6888, lr = 0.005
I0406 14:52:35.053223 23057 solver.cpp:218] Iteration 6900 (2.27441 iter/s, 5.27609s/12 iters), loss = 0.329627
I0406 14:52:35.053320 23057 solver.cpp:237]     Train net output #0: loss = 0.329627 (* 1 = 0.329627 loss)
I0406 14:52:35.053328 23057 sgd_solver.cpp:105] Iteration 6900, lr = 0.005
I0406 14:52:40.105479 23057 solver.cpp:218] Iteration 6912 (2.37525 iter/s, 5.0521s/12 iters), loss = 0.446826
I0406 14:52:40.105523 23057 solver.cpp:237]     Train net output #0: loss = 0.446826 (* 1 = 0.446826 loss)
I0406 14:52:40.105530 23057 sgd_solver.cpp:105] Iteration 6912, lr = 0.005
I0406 14:52:45.361369 23057 solver.cpp:218] Iteration 6924 (2.28319 iter/s, 5.25579s/12 iters), loss = 0.373922
I0406 14:52:45.361411 23057 solver.cpp:237]     Train net output #0: loss = 0.373922 (* 1 = 0.373922 loss)
I0406 14:52:45.361419 23057 sgd_solver.cpp:105] Iteration 6924, lr = 0.005
I0406 14:52:50.122011 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel
I0406 14:52:53.202791 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate
I0406 14:52:55.520340 23057 solver.cpp:330] Iteration 6936, Testing net (#0)
I0406 14:52:55.520361 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:52:56.077888 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:52:57.168313 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:52:59.851521 23057 solver.cpp:397]     Test net output #0: accuracy = 0.384804
I0406 14:52:59.851554 23057 solver.cpp:397]     Test net output #1: loss = 3.13046 (* 1 = 3.13046 loss)
I0406 14:52:59.991827 23057 solver.cpp:218] Iteration 6936 (0.820216 iter/s, 14.6303s/12 iters), loss = 0.40303
I0406 14:52:59.991887 23057 solver.cpp:237]     Train net output #0: loss = 0.40303 (* 1 = 0.40303 loss)
I0406 14:52:59.991896 23057 sgd_solver.cpp:105] Iteration 6936, lr = 0.005
I0406 14:53:04.421452 23057 solver.cpp:218] Iteration 6948 (2.7091 iter/s, 4.42952s/12 iters), loss = 0.432428
I0406 14:53:04.421492 23057 solver.cpp:237]     Train net output #0: loss = 0.432428 (* 1 = 0.432428 loss)
I0406 14:53:04.421499 23057 sgd_solver.cpp:105] Iteration 6948, lr = 0.005
I0406 14:53:09.581037 23057 solver.cpp:218] Iteration 6960 (2.32581 iter/s, 5.15949s/12 iters), loss = 0.360963
I0406 14:53:09.581166 23057 solver.cpp:237]     Train net output #0: loss = 0.360963 (* 1 = 0.360963 loss)
I0406 14:53:09.581173 23057 sgd_solver.cpp:105] Iteration 6960, lr = 0.005
I0406 14:53:14.674562 23057 solver.cpp:218] Iteration 6972 (2.35602 iter/s, 5.09334s/12 iters), loss = 0.249746
I0406 14:53:14.674607 23057 solver.cpp:237]     Train net output #0: loss = 0.249746 (* 1 = 0.249746 loss)
I0406 14:53:14.674614 23057 sgd_solver.cpp:105] Iteration 6972, lr = 0.005
I0406 14:53:17.527874 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:53:19.978567 23057 solver.cpp:218] Iteration 6984 (2.26249 iter/s, 5.3039s/12 iters), loss = 0.27781
I0406 14:53:19.978623 23057 solver.cpp:237]     Train net output #0: loss = 0.27781 (* 1 = 0.27781 loss)
I0406 14:53:19.978632 23057 sgd_solver.cpp:105] Iteration 6984, lr = 0.005
I0406 14:53:25.235903 23057 solver.cpp:218] Iteration 6996 (2.28257 iter/s, 5.25723s/12 iters), loss = 0.304005
I0406 14:53:25.235944 23057 solver.cpp:237]     Train net output #0: loss = 0.304005 (* 1 = 0.304005 loss)
I0406 14:53:25.235950 23057 sgd_solver.cpp:105] Iteration 6996, lr = 0.005
I0406 14:53:30.618566 23057 solver.cpp:218] Iteration 7008 (2.22942 iter/s, 5.38256s/12 iters), loss = 0.316144
I0406 14:53:30.618611 23057 solver.cpp:237]     Train net output #0: loss = 0.316144 (* 1 = 0.316144 loss)
I0406 14:53:30.618618 23057 sgd_solver.cpp:105] Iteration 7008, lr = 0.005
I0406 14:53:35.815732 23057 solver.cpp:218] Iteration 7020 (2.309 iter/s, 5.19707s/12 iters), loss = 0.471184
I0406 14:53:35.815773 23057 solver.cpp:237]     Train net output #0: loss = 0.471184 (* 1 = 0.471184 loss)
I0406 14:53:35.815779 23057 sgd_solver.cpp:105] Iteration 7020, lr = 0.005
I0406 14:53:40.788309 23057 solver.cpp:218] Iteration 7032 (2.41328 iter/s, 4.97248s/12 iters), loss = 0.249983
I0406 14:53:40.788416 23057 solver.cpp:237]     Train net output #0: loss = 0.249983 (* 1 = 0.249983 loss)
I0406 14:53:40.788424 23057 sgd_solver.cpp:105] Iteration 7032, lr = 0.005
I0406 14:53:42.917240 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel
I0406 14:53:45.926831 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate
I0406 14:53:48.219359 23057 solver.cpp:330] Iteration 7038, Testing net (#0)
I0406 14:53:48.219377 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:53:49.797189 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:53:52.503736 23057 solver.cpp:397]     Test net output #0: accuracy = 0.395221
I0406 14:53:52.503767 23057 solver.cpp:397]     Test net output #1: loss = 3.23172 (* 1 = 3.23172 loss)
I0406 14:53:54.352769 23057 solver.cpp:218] Iteration 7044 (0.884679 iter/s, 13.5642s/12 iters), loss = 0.241099
I0406 14:53:54.352810 23057 solver.cpp:237]     Train net output #0: loss = 0.241099 (* 1 = 0.241099 loss)
I0406 14:53:54.352816 23057 sgd_solver.cpp:105] Iteration 7044, lr = 0.005
I0406 14:53:59.449837 23057 solver.cpp:218] Iteration 7056 (2.35434 iter/s, 5.09697s/12 iters), loss = 0.265467
I0406 14:53:59.449875 23057 solver.cpp:237]     Train net output #0: loss = 0.265467 (* 1 = 0.265467 loss)
I0406 14:53:59.449880 23057 sgd_solver.cpp:105] Iteration 7056, lr = 0.005
I0406 14:54:04.582418 23057 solver.cpp:218] Iteration 7068 (2.33805 iter/s, 5.13249s/12 iters), loss = 0.353289
I0406 14:54:04.582474 23057 solver.cpp:237]     Train net output #0: loss = 0.353289 (* 1 = 0.353289 loss)
I0406 14:54:04.582484 23057 sgd_solver.cpp:105] Iteration 7068, lr = 0.005
I0406 14:54:09.737763 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:54:09.902010 23057 solver.cpp:218] Iteration 7080 (2.25586 iter/s, 5.31948s/12 iters), loss = 0.318164
I0406 14:54:09.902077 23057 solver.cpp:237]     Train net output #0: loss = 0.318165 (* 1 = 0.318165 loss)
I0406 14:54:09.902086 23057 sgd_solver.cpp:105] Iteration 7080, lr = 0.005
I0406 14:54:15.263909 23057 solver.cpp:218] Iteration 7092 (2.23806 iter/s, 5.36178s/12 iters), loss = 0.40508
I0406 14:54:15.264046 23057 solver.cpp:237]     Train net output #0: loss = 0.40508 (* 1 = 0.40508 loss)
I0406 14:54:15.264053 23057 sgd_solver.cpp:105] Iteration 7092, lr = 0.005
I0406 14:54:20.545954 23057 solver.cpp:218] Iteration 7104 (2.27193 iter/s, 5.28186s/12 iters), loss = 0.358548
I0406 14:54:20.545997 23057 solver.cpp:237]     Train net output #0: loss = 0.358548 (* 1 = 0.358548 loss)
I0406 14:54:20.546003 23057 sgd_solver.cpp:105] Iteration 7104, lr = 0.005
I0406 14:54:25.713924 23057 solver.cpp:218] Iteration 7116 (2.32204 iter/s, 5.16786s/12 iters), loss = 0.423422
I0406 14:54:25.713990 23057 solver.cpp:237]     Train net output #0: loss = 0.423422 (* 1 = 0.423422 loss)
I0406 14:54:25.713999 23057 sgd_solver.cpp:105] Iteration 7116, lr = 0.005
I0406 14:54:30.845412 23057 solver.cpp:218] Iteration 7128 (2.33856 iter/s, 5.13137s/12 iters), loss = 0.331106
I0406 14:54:30.845461 23057 solver.cpp:237]     Train net output #0: loss = 0.331107 (* 1 = 0.331107 loss)
I0406 14:54:30.845468 23057 sgd_solver.cpp:105] Iteration 7128, lr = 0.005
I0406 14:54:35.638164 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel
I0406 14:54:38.638630 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate
I0406 14:54:40.982117 23057 solver.cpp:330] Iteration 7140, Testing net (#0)
I0406 14:54:40.982138 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:54:42.526995 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:54:45.349805 23057 solver.cpp:397]     Test net output #0: accuracy = 0.390319
I0406 14:54:45.349910 23057 solver.cpp:397]     Test net output #1: loss = 3.2444 (* 1 = 3.2444 loss)
I0406 14:54:45.490474 23057 solver.cpp:218] Iteration 7140 (0.819398 iter/s, 14.6449s/12 iters), loss = 0.290973
I0406 14:54:45.492043 23057 solver.cpp:237]     Train net output #0: loss = 0.290973 (* 1 = 0.290973 loss)
I0406 14:54:45.492055 23057 sgd_solver.cpp:105] Iteration 7140, lr = 0.005
I0406 14:54:49.924139 23057 solver.cpp:218] Iteration 7152 (2.70755 iter/s, 4.43205s/12 iters), loss = 0.333728
I0406 14:54:49.924182 23057 solver.cpp:237]     Train net output #0: loss = 0.333729 (* 1 = 0.333729 loss)
I0406 14:54:49.924188 23057 sgd_solver.cpp:105] Iteration 7152, lr = 0.005
I0406 14:54:55.265462 23057 solver.cpp:218] Iteration 7164 (2.24668 iter/s, 5.34122s/12 iters), loss = 0.229892
I0406 14:54:55.265522 23057 solver.cpp:237]     Train net output #0: loss = 0.229892 (* 1 = 0.229892 loss)
I0406 14:54:55.265529 23057 sgd_solver.cpp:105] Iteration 7164, lr = 0.005
I0406 14:55:00.449159 23057 solver.cpp:218] Iteration 7176 (2.315 iter/s, 5.18359s/12 iters), loss = 0.397826
I0406 14:55:00.449201 23057 solver.cpp:237]     Train net output #0: loss = 0.397826 (* 1 = 0.397826 loss)
I0406 14:55:00.449208 23057 sgd_solver.cpp:105] Iteration 7176, lr = 0.005
I0406 14:55:02.641106 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:55:05.714493 23057 solver.cpp:218] Iteration 7188 (2.2791 iter/s, 5.26523s/12 iters), loss = 0.33628
I0406 14:55:05.714536 23057 solver.cpp:237]     Train net output #0: loss = 0.336281 (* 1 = 0.336281 loss)
I0406 14:55:05.714541 23057 sgd_solver.cpp:105] Iteration 7188, lr = 0.005
I0406 14:55:11.108088 23057 solver.cpp:218] Iteration 7200 (2.2249 iter/s, 5.39349s/12 iters), loss = 0.341255
I0406 14:55:11.108145 23057 solver.cpp:237]     Train net output #0: loss = 0.341255 (* 1 = 0.341255 loss)
I0406 14:55:11.108155 23057 sgd_solver.cpp:105] Iteration 7200, lr = 0.005
I0406 14:55:16.391955 23057 solver.cpp:218] Iteration 7212 (2.27111 iter/s, 5.28376s/12 iters), loss = 0.29256
I0406 14:55:16.392081 23057 solver.cpp:237]     Train net output #0: loss = 0.29256 (* 1 = 0.29256 loss)
I0406 14:55:16.392087 23057 sgd_solver.cpp:105] Iteration 7212, lr = 0.005
I0406 14:55:21.716620 23057 solver.cpp:218] Iteration 7224 (2.25374 iter/s, 5.32448s/12 iters), loss = 0.210611
I0406 14:55:21.716666 23057 solver.cpp:237]     Train net output #0: loss = 0.210611 (* 1 = 0.210611 loss)
I0406 14:55:21.716673 23057 sgd_solver.cpp:105] Iteration 7224, lr = 0.005
I0406 14:55:26.892916 23057 solver.cpp:218] Iteration 7236 (2.31831 iter/s, 5.17619s/12 iters), loss = 0.161851
I0406 14:55:26.892957 23057 solver.cpp:237]     Train net output #0: loss = 0.161851 (* 1 = 0.161851 loss)
I0406 14:55:26.892963 23057 sgd_solver.cpp:105] Iteration 7236, lr = 0.005
I0406 14:55:28.996238 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel
I0406 14:55:33.034309 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate
I0406 14:55:36.105137 23057 solver.cpp:330] Iteration 7242, Testing net (#0)
I0406 14:55:36.105165 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:55:37.590600 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:55:40.488612 23057 solver.cpp:397]     Test net output #0: accuracy = 0.381127
I0406 14:55:40.488647 23057 solver.cpp:397]     Test net output #1: loss = 3.23086 (* 1 = 3.23086 loss)
I0406 14:55:42.615886 23057 solver.cpp:218] Iteration 7248 (0.763223 iter/s, 15.7228s/12 iters), loss = 0.280859
I0406 14:55:42.615931 23057 solver.cpp:237]     Train net output #0: loss = 0.280859 (* 1 = 0.280859 loss)
I0406 14:55:42.615936 23057 sgd_solver.cpp:105] Iteration 7248, lr = 0.005
I0406 14:55:47.977886 23057 solver.cpp:218] Iteration 7260 (2.23801 iter/s, 5.3619s/12 iters), loss = 0.186988
I0406 14:55:47.977978 23057 solver.cpp:237]     Train net output #0: loss = 0.186989 (* 1 = 0.186989 loss)
I0406 14:55:47.977985 23057 sgd_solver.cpp:105] Iteration 7260, lr = 0.005
I0406 14:55:53.354360 23057 solver.cpp:218] Iteration 7272 (2.23201 iter/s, 5.37632s/12 iters), loss = 0.230334
I0406 14:55:53.354413 23057 solver.cpp:237]     Train net output #0: loss = 0.230334 (* 1 = 0.230334 loss)
I0406 14:55:53.354420 23057 sgd_solver.cpp:105] Iteration 7272, lr = 0.005
I0406 14:55:57.837467 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:55:58.698837 23057 solver.cpp:218] Iteration 7284 (2.24535 iter/s, 5.34437s/12 iters), loss = 0.407457
I0406 14:55:58.698879 23057 solver.cpp:237]     Train net output #0: loss = 0.407457 (* 1 = 0.407457 loss)
I0406 14:55:58.698885 23057 sgd_solver.cpp:105] Iteration 7284, lr = 0.005
I0406 14:56:03.908427 23057 solver.cpp:218] Iteration 7296 (2.30349 iter/s, 5.20949s/12 iters), loss = 0.263087
I0406 14:56:03.908463 23057 solver.cpp:237]     Train net output #0: loss = 0.263087 (* 1 = 0.263087 loss)
I0406 14:56:03.908469 23057 sgd_solver.cpp:105] Iteration 7296, lr = 0.005
I0406 14:56:09.176105 23057 solver.cpp:218] Iteration 7308 (2.27808 iter/s, 5.26759s/12 iters), loss = 0.388716
I0406 14:56:09.176147 23057 solver.cpp:237]     Train net output #0: loss = 0.388716 (* 1 = 0.388716 loss)
I0406 14:56:09.176154 23057 sgd_solver.cpp:105] Iteration 7308, lr = 0.005
I0406 14:56:14.562070 23057 solver.cpp:218] Iteration 7320 (2.22805 iter/s, 5.38587s/12 iters), loss = 0.489009
I0406 14:56:14.562124 23057 solver.cpp:237]     Train net output #0: loss = 0.489009 (* 1 = 0.489009 loss)
I0406 14:56:14.562131 23057 sgd_solver.cpp:105] Iteration 7320, lr = 0.005
I0406 14:56:19.898524 23057 solver.cpp:218] Iteration 7332 (2.24873 iter/s, 5.33635s/12 iters), loss = 0.438032
I0406 14:56:19.898627 23057 solver.cpp:237]     Train net output #0: loss = 0.438032 (* 1 = 0.438032 loss)
I0406 14:56:19.898633 23057 sgd_solver.cpp:105] Iteration 7332, lr = 0.005
I0406 14:56:24.669883 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel
I0406 14:56:27.659812 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate
I0406 14:56:29.961527 23057 solver.cpp:330] Iteration 7344, Testing net (#0)
I0406 14:56:29.961549 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:56:31.476548 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:56:34.359113 23057 solver.cpp:397]     Test net output #0: accuracy = 0.387255
I0406 14:56:34.359148 23057 solver.cpp:397]     Test net output #1: loss = 3.24108 (* 1 = 3.24108 loss)
I0406 14:56:34.499766 23057 solver.cpp:218] Iteration 7344 (0.82186 iter/s, 14.601s/12 iters), loss = 0.316562
I0406 14:56:34.501353 23057 solver.cpp:237]     Train net output #0: loss = 0.316563 (* 1 = 0.316563 loss)
I0406 14:56:34.501368 23057 sgd_solver.cpp:105] Iteration 7344, lr = 0.005
I0406 14:56:38.973630 23057 solver.cpp:218] Iteration 7356 (2.68322 iter/s, 4.47223s/12 iters), loss = 0.42202
I0406 14:56:38.973692 23057 solver.cpp:237]     Train net output #0: loss = 0.42202 (* 1 = 0.42202 loss)
I0406 14:56:38.973701 23057 sgd_solver.cpp:105] Iteration 7356, lr = 0.005
I0406 14:56:44.313661 23057 solver.cpp:218] Iteration 7368 (2.24723 iter/s, 5.33992s/12 iters), loss = 0.230012
I0406 14:56:44.313704 23057 solver.cpp:237]     Train net output #0: loss = 0.230012 (* 1 = 0.230012 loss)
I0406 14:56:44.313709 23057 sgd_solver.cpp:105] Iteration 7368, lr = 0.005
I0406 14:56:49.408355 23057 solver.cpp:218] Iteration 7380 (2.35543 iter/s, 5.0946s/12 iters), loss = 0.291478
I0406 14:56:49.408393 23057 solver.cpp:237]     Train net output #0: loss = 0.291478 (* 1 = 0.291478 loss)
I0406 14:56:49.408401 23057 sgd_solver.cpp:105] Iteration 7380, lr = 0.005
I0406 14:56:50.727787 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:56:54.486260 23057 solver.cpp:218] Iteration 7392 (2.36322 iter/s, 5.07781s/12 iters), loss = 0.222388
I0406 14:56:54.486302 23057 solver.cpp:237]     Train net output #0: loss = 0.222388 (* 1 = 0.222388 loss)
I0406 14:56:54.486308 23057 sgd_solver.cpp:105] Iteration 7392, lr = 0.005
I0406 14:56:59.599892 23057 solver.cpp:218] Iteration 7404 (2.34672 iter/s, 5.11353s/12 iters), loss = 0.314907
I0406 14:56:59.599936 23057 solver.cpp:237]     Train net output #0: loss = 0.314907 (* 1 = 0.314907 loss)
I0406 14:56:59.599941 23057 sgd_solver.cpp:105] Iteration 7404, lr = 0.005
I0406 14:57:04.971738 23057 solver.cpp:218] Iteration 7416 (2.23391 iter/s, 5.37175s/12 iters), loss = 0.286847
I0406 14:57:04.971781 23057 solver.cpp:237]     Train net output #0: loss = 0.286847 (* 1 = 0.286847 loss)
I0406 14:57:04.971787 23057 sgd_solver.cpp:105] Iteration 7416, lr = 0.005
I0406 14:57:10.046406 23057 solver.cpp:218] Iteration 7428 (2.36473 iter/s, 5.07457s/12 iters), loss = 0.273223
I0406 14:57:10.046464 23057 solver.cpp:237]     Train net output #0: loss = 0.273223 (* 1 = 0.273223 loss)
I0406 14:57:10.046473 23057 sgd_solver.cpp:105] Iteration 7428, lr = 0.005
I0406 14:57:15.372561 23057 solver.cpp:218] Iteration 7440 (2.25308 iter/s, 5.32604s/12 iters), loss = 0.222493
I0406 14:57:15.372617 23057 solver.cpp:237]     Train net output #0: loss = 0.222493 (* 1 = 0.222493 loss)
I0406 14:57:15.372625 23057 sgd_solver.cpp:105] Iteration 7440, lr = 0.005
I0406 14:57:17.457650 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel
I0406 14:57:20.525008 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate
I0406 14:57:22.832041 23057 solver.cpp:330] Iteration 7446, Testing net (#0)
I0406 14:57:22.832126 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:57:24.253248 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:57:27.112948 23057 solver.cpp:397]     Test net output #0: accuracy = 0.384804
I0406 14:57:27.112987 23057 solver.cpp:397]     Test net output #1: loss = 3.31195 (* 1 = 3.31195 loss)
I0406 14:57:29.065726 23057 solver.cpp:218] Iteration 7452 (0.87636 iter/s, 13.693s/12 iters), loss = 0.389965
I0406 14:57:29.065766 23057 solver.cpp:237]     Train net output #0: loss = 0.389966 (* 1 = 0.389966 loss)
I0406 14:57:29.065773 23057 sgd_solver.cpp:105] Iteration 7452, lr = 0.005
I0406 14:57:34.258756 23057 solver.cpp:218] Iteration 7464 (2.31083 iter/s, 5.19294s/12 iters), loss = 0.27055
I0406 14:57:34.258795 23057 solver.cpp:237]     Train net output #0: loss = 0.27055 (* 1 = 0.27055 loss)
I0406 14:57:34.258801 23057 sgd_solver.cpp:105] Iteration 7464, lr = 0.005
I0406 14:57:39.580366 23057 solver.cpp:218] Iteration 7476 (2.255 iter/s, 5.32152s/12 iters), loss = 0.274564
I0406 14:57:39.580413 23057 solver.cpp:237]     Train net output #0: loss = 0.274564 (* 1 = 0.274564 loss)
I0406 14:57:39.580421 23057 sgd_solver.cpp:105] Iteration 7476, lr = 0.005
I0406 14:57:43.230470 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:57:44.791209 23057 solver.cpp:218] Iteration 7488 (2.30293 iter/s, 5.21074s/12 iters), loss = 0.450679
I0406 14:57:44.791249 23057 solver.cpp:237]     Train net output #0: loss = 0.450679 (* 1 = 0.450679 loss)
I0406 14:57:44.791254 23057 sgd_solver.cpp:105] Iteration 7488, lr = 0.005
I0406 14:57:50.004703 23057 solver.cpp:218] Iteration 7500 (2.30176 iter/s, 5.2134s/12 iters), loss = 0.369231
I0406 14:57:50.004740 23057 solver.cpp:237]     Train net output #0: loss = 0.369231 (* 1 = 0.369231 loss)
I0406 14:57:50.004745 23057 sgd_solver.cpp:105] Iteration 7500, lr = 0.005
I0406 14:57:55.260826 23057 solver.cpp:218] Iteration 7512 (2.28309 iter/s, 5.25603s/12 iters), loss = 0.266616
I0406 14:57:55.260962 23057 solver.cpp:237]     Train net output #0: loss = 0.266617 (* 1 = 0.266617 loss)
I0406 14:57:55.260969 23057 sgd_solver.cpp:105] Iteration 7512, lr = 0.005
I0406 14:58:00.599146 23057 solver.cpp:218] Iteration 7524 (2.24798 iter/s, 5.33814s/12 iters), loss = 0.417303
I0406 14:58:00.599186 23057 solver.cpp:237]     Train net output #0: loss = 0.417303 (* 1 = 0.417303 loss)
I0406 14:58:00.599192 23057 sgd_solver.cpp:105] Iteration 7524, lr = 0.005
I0406 14:58:05.779803 23057 solver.cpp:218] Iteration 7536 (2.31635 iter/s, 5.18056s/12 iters), loss = 0.40074
I0406 14:58:05.779853 23057 solver.cpp:237]     Train net output #0: loss = 0.40074 (* 1 = 0.40074 loss)
I0406 14:58:05.779861 23057 sgd_solver.cpp:105] Iteration 7536, lr = 0.005
I0406 14:58:10.550215 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel
I0406 14:58:13.668009 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate
I0406 14:58:15.991134 23057 solver.cpp:330] Iteration 7548, Testing net (#0)
I0406 14:58:15.991158 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:58:17.370954 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:58:20.379038 23057 solver.cpp:397]     Test net output #0: accuracy = 0.404412
I0406 14:58:20.379073 23057 solver.cpp:397]     Test net output #1: loss = 3.23827 (* 1 = 3.23827 loss)
I0406 14:58:20.519683 23057 solver.cpp:218] Iteration 7548 (0.814127 iter/s, 14.7397s/12 iters), loss = 0.160959
I0406 14:58:20.519742 23057 solver.cpp:237]     Train net output #0: loss = 0.160959 (* 1 = 0.160959 loss)
I0406 14:58:20.519749 23057 sgd_solver.cpp:105] Iteration 7548, lr = 0.005
I0406 14:58:24.914402 23057 solver.cpp:218] Iteration 7560 (2.73062 iter/s, 4.39461s/12 iters), loss = 0.233606
I0406 14:58:24.914454 23057 solver.cpp:237]     Train net output #0: loss = 0.233606 (* 1 = 0.233606 loss)
I0406 14:58:24.914463 23057 sgd_solver.cpp:105] Iteration 7560, lr = 0.005
I0406 14:58:30.032765 23057 solver.cpp:218] Iteration 7572 (2.34455 iter/s, 5.11826s/12 iters), loss = 0.334408
I0406 14:58:30.032955 23057 solver.cpp:237]     Train net output #0: loss = 0.334409 (* 1 = 0.334409 loss)
I0406 14:58:30.032968 23057 sgd_solver.cpp:105] Iteration 7572, lr = 0.005
I0406 14:58:35.279116 23057 solver.cpp:218] Iteration 7584 (2.28741 iter/s, 5.24611s/12 iters), loss = 0.389284
I0406 14:58:35.279168 23057 solver.cpp:237]     Train net output #0: loss = 0.389284 (* 1 = 0.389284 loss)
I0406 14:58:35.279176 23057 sgd_solver.cpp:105] Iteration 7584, lr = 0.005
I0406 14:58:35.800752 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:58:40.372743 23057 solver.cpp:218] Iteration 7596 (2.35593 iter/s, 5.09352s/12 iters), loss = 0.302864
I0406 14:58:40.372784 23057 solver.cpp:237]     Train net output #0: loss = 0.302865 (* 1 = 0.302865 loss)
I0406 14:58:40.372789 23057 sgd_solver.cpp:105] Iteration 7596, lr = 0.005
I0406 14:58:45.513259 23057 solver.cpp:218] Iteration 7608 (2.33444 iter/s, 5.14042s/12 iters), loss = 0.270276
I0406 14:58:45.513295 23057 solver.cpp:237]     Train net output #0: loss = 0.270276 (* 1 = 0.270276 loss)
I0406 14:58:45.513301 23057 sgd_solver.cpp:105] Iteration 7608, lr = 0.005
I0406 14:58:50.823016 23057 solver.cpp:218] Iteration 7620 (2.26003 iter/s, 5.30967s/12 iters), loss = 0.146724
I0406 14:58:50.823057 23057 solver.cpp:237]     Train net output #0: loss = 0.146724 (* 1 = 0.146724 loss)
I0406 14:58:50.823065 23057 sgd_solver.cpp:105] Iteration 7620, lr = 0.005
I0406 14:58:53.305174 23057 blocking_queue.cpp:49] Waiting for data
I0406 14:58:55.935319 23057 solver.cpp:218] Iteration 7632 (2.34732 iter/s, 5.11221s/12 iters), loss = 0.25352
I0406 14:58:55.935370 23057 solver.cpp:237]     Train net output #0: loss = 0.25352 (* 1 = 0.25352 loss)
I0406 14:58:55.935379 23057 sgd_solver.cpp:105] Iteration 7632, lr = 0.005
I0406 14:59:01.202134 23057 solver.cpp:218] Iteration 7644 (2.27846 iter/s, 5.26671s/12 iters), loss = 0.233882
I0406 14:59:01.202260 23057 solver.cpp:237]     Train net output #0: loss = 0.233882 (* 1 = 0.233882 loss)
I0406 14:59:01.202267 23057 sgd_solver.cpp:105] Iteration 7644, lr = 0.005
I0406 14:59:03.253511 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel
I0406 14:59:06.320035 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate
I0406 14:59:08.627908 23057 solver.cpp:330] Iteration 7650, Testing net (#0)
I0406 14:59:08.627928 23057 net.cpp:676] Ignoring source layer train-data
I0406 14:59:10.077425 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:59:13.221963 23057 solver.cpp:397]     Test net output #0: accuracy = 0.397059
I0406 14:59:13.221992 23057 solver.cpp:397]     Test net output #1: loss = 3.29048 (* 1 = 3.29048 loss)
I0406 14:59:15.135989 23057 solver.cpp:218] Iteration 7656 (0.861226 iter/s, 13.9336s/12 iters), loss = 0.17715
I0406 14:59:15.136034 23057 solver.cpp:237]     Train net output #0: loss = 0.17715 (* 1 = 0.17715 loss)
I0406 14:59:15.136040 23057 sgd_solver.cpp:105] Iteration 7656, lr = 0.005
I0406 14:59:20.504165 23057 solver.cpp:218] Iteration 7668 (2.23543 iter/s, 5.36808s/12 iters), loss = 0.282347
I0406 14:59:20.504199 23057 solver.cpp:237]     Train net output #0: loss = 0.282347 (* 1 = 0.282347 loss)
I0406 14:59:20.504204 23057 sgd_solver.cpp:105] Iteration 7668, lr = 0.005
I0406 14:59:25.779053 23057 solver.cpp:218] Iteration 7680 (2.27497 iter/s, 5.27479s/12 iters), loss = 0.240603
I0406 14:59:25.779116 23057 solver.cpp:237]     Train net output #0: loss = 0.240603 (* 1 = 0.240603 loss)
I0406 14:59:25.779126 23057 sgd_solver.cpp:105] Iteration 7680, lr = 0.005
I0406 14:59:28.719331 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 14:59:31.167246 23057 solver.cpp:218] Iteration 7692 (2.22714 iter/s, 5.38808s/12 iters), loss = 0.236288
I0406 14:59:31.167286 23057 solver.cpp:237]     Train net output #0: loss = 0.236288 (* 1 = 0.236288 loss)
I0406 14:59:31.167292 23057 sgd_solver.cpp:105] Iteration 7692, lr = 0.005
I0406 14:59:36.304704 23057 solver.cpp:218] Iteration 7704 (2.33583 iter/s, 5.13737s/12 iters), loss = 0.409427
I0406 14:59:36.304802 23057 solver.cpp:237]     Train net output #0: loss = 0.409427 (* 1 = 0.409427 loss)
I0406 14:59:36.304809 23057 sgd_solver.cpp:105] Iteration 7704, lr = 0.005
I0406 14:59:41.320281 23057 solver.cpp:218] Iteration 7716 (2.39262 iter/s, 5.01542s/12 iters), loss = 0.315833
I0406 14:59:41.320322 23057 solver.cpp:237]     Train net output #0: loss = 0.315833 (* 1 = 0.315833 loss)
I0406 14:59:41.320327 23057 sgd_solver.cpp:105] Iteration 7716, lr = 0.005
I0406 14:59:46.636862 23057 solver.cpp:218] Iteration 7728 (2.25713 iter/s, 5.31649s/12 iters), loss = 0.251826
I0406 14:59:46.636914 23057 solver.cpp:237]     Train net output #0: loss = 0.251827 (* 1 = 0.251827 loss)
I0406 14:59:46.636920 23057 sgd_solver.cpp:105] Iteration 7728, lr = 0.005
I0406 14:59:51.923194 23057 solver.cpp:218] Iteration 7740 (2.27005 iter/s, 5.28623s/12 iters), loss = 0.264056
I0406 14:59:51.923234 23057 solver.cpp:237]     Train net output #0: loss = 0.264056 (* 1 = 0.264056 loss)
I0406 14:59:51.923240 23057 sgd_solver.cpp:105] Iteration 7740, lr = 0.005
I0406 14:59:56.757156 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel
I0406 14:59:59.778573 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate
I0406 15:00:02.853298 23057 solver.cpp:330] Iteration 7752, Testing net (#0)
I0406 15:00:02.853322 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:00:04.179837 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:00:07.149011 23057 solver.cpp:397]     Test net output #0: accuracy = 0.391544
I0406 15:00:07.149137 23057 solver.cpp:397]     Test net output #1: loss = 3.3398 (* 1 = 3.3398 loss)
I0406 15:00:07.289469 23057 solver.cpp:218] Iteration 7752 (0.780939 iter/s, 15.3661s/12 iters), loss = 0.166083
I0406 15:00:07.289530 23057 solver.cpp:237]     Train net output #0: loss = 0.166083 (* 1 = 0.166083 loss)
I0406 15:00:07.289536 23057 sgd_solver.cpp:105] Iteration 7752, lr = 0.005
I0406 15:00:11.836591 23057 solver.cpp:218] Iteration 7764 (2.6391 iter/s, 4.54701s/12 iters), loss = 0.324086
I0406 15:00:11.836638 23057 solver.cpp:237]     Train net output #0: loss = 0.324086 (* 1 = 0.324086 loss)
I0406 15:00:11.836647 23057 sgd_solver.cpp:105] Iteration 7764, lr = 0.005
I0406 15:00:16.899013 23057 solver.cpp:218] Iteration 7776 (2.37045 iter/s, 5.06232s/12 iters), loss = 0.223624
I0406 15:00:16.899053 23057 solver.cpp:237]     Train net output #0: loss = 0.223624 (* 1 = 0.223624 loss)
I0406 15:00:16.899058 23057 sgd_solver.cpp:105] Iteration 7776, lr = 0.005
I0406 15:00:21.939828 23057 solver.cpp:218] Iteration 7788 (2.38061 iter/s, 5.04072s/12 iters), loss = 0.272177
I0406 15:00:21.939872 23057 solver.cpp:237]     Train net output #0: loss = 0.272177 (* 1 = 0.272177 loss)
I0406 15:00:21.939878 23057 sgd_solver.cpp:105] Iteration 7788, lr = 0.005
I0406 15:00:21.946328 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:00:27.311249 23057 solver.cpp:218] Iteration 7800 (2.23409 iter/s, 5.37132s/12 iters), loss = 0.359617
I0406 15:00:27.311311 23057 solver.cpp:237]     Train net output #0: loss = 0.359617 (* 1 = 0.359617 loss)
I0406 15:00:27.311321 23057 sgd_solver.cpp:105] Iteration 7800, lr = 0.005
I0406 15:00:32.468791 23057 solver.cpp:218] Iteration 7812 (2.32674 iter/s, 5.15743s/12 iters), loss = 0.348856
I0406 15:00:32.468839 23057 solver.cpp:237]     Train net output #0: loss = 0.348856 (* 1 = 0.348856 loss)
I0406 15:00:32.468847 23057 sgd_solver.cpp:105] Iteration 7812, lr = 0.005
I0406 15:00:37.717363 23057 solver.cpp:218] Iteration 7824 (2.28638 iter/s, 5.24847s/12 iters), loss = 0.287459
I0406 15:00:37.717499 23057 solver.cpp:237]     Train net output #0: loss = 0.287459 (* 1 = 0.287459 loss)
I0406 15:00:37.717509 23057 sgd_solver.cpp:105] Iteration 7824, lr = 0.005
I0406 15:00:42.793174 23057 solver.cpp:218] Iteration 7836 (2.36424 iter/s, 5.07562s/12 iters), loss = 0.238329
I0406 15:00:42.793216 23057 solver.cpp:237]     Train net output #0: loss = 0.238329 (* 1 = 0.238329 loss)
I0406 15:00:42.793222 23057 sgd_solver.cpp:105] Iteration 7836, lr = 0.005
I0406 15:00:47.994688 23057 solver.cpp:218] Iteration 7848 (2.30706 iter/s, 5.20142s/12 iters), loss = 0.184223
I0406 15:00:47.994738 23057 solver.cpp:237]     Train net output #0: loss = 0.184223 (* 1 = 0.184223 loss)
I0406 15:00:47.994745 23057 sgd_solver.cpp:105] Iteration 7848, lr = 0.005
I0406 15:00:50.173004 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel
I0406 15:00:53.148245 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate
I0406 15:00:55.450392 23057 solver.cpp:330] Iteration 7854, Testing net (#0)
I0406 15:00:55.450414 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:00:56.693565 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:00:59.810222 23057 solver.cpp:397]     Test net output #0: accuracy = 0.387868
I0406 15:00:59.810250 23057 solver.cpp:397]     Test net output #1: loss = 3.29694 (* 1 = 3.29694 loss)
I0406 15:01:01.678731 23057 solver.cpp:218] Iteration 7860 (0.876944 iter/s, 13.6839s/12 iters), loss = 0.326101
I0406 15:01:01.678774 23057 solver.cpp:237]     Train net output #0: loss = 0.326101 (* 1 = 0.326101 loss)
I0406 15:01:01.678781 23057 sgd_solver.cpp:105] Iteration 7860, lr = 0.005
I0406 15:01:06.903132 23057 solver.cpp:218] Iteration 7872 (2.29696 iter/s, 5.2243s/12 iters), loss = 0.258995
I0406 15:01:06.903175 23057 solver.cpp:237]     Train net output #0: loss = 0.258995 (* 1 = 0.258995 loss)
I0406 15:01:06.903182 23057 sgd_solver.cpp:105] Iteration 7872, lr = 0.005
I0406 15:01:12.027110 23057 solver.cpp:218] Iteration 7884 (2.34197 iter/s, 5.12388s/12 iters), loss = 0.24123
I0406 15:01:12.027240 23057 solver.cpp:237]     Train net output #0: loss = 0.24123 (* 1 = 0.24123 loss)
I0406 15:01:12.027248 23057 sgd_solver.cpp:105] Iteration 7884, lr = 0.005
I0406 15:01:14.330999 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:01:17.366950 23057 solver.cpp:218] Iteration 7896 (2.24734 iter/s, 5.33966s/12 iters), loss = 0.310772
I0406 15:01:17.367003 23057 solver.cpp:237]     Train net output #0: loss = 0.310772 (* 1 = 0.310772 loss)
I0406 15:01:17.367012 23057 sgd_solver.cpp:105] Iteration 7896, lr = 0.005
I0406 15:01:22.583914 23057 solver.cpp:218] Iteration 7908 (2.30024 iter/s, 5.21686s/12 iters), loss = 0.261844
I0406 15:01:22.583959 23057 solver.cpp:237]     Train net output #0: loss = 0.261844 (* 1 = 0.261844 loss)
I0406 15:01:22.583966 23057 sgd_solver.cpp:105] Iteration 7908, lr = 0.005
I0406 15:01:27.643771 23057 solver.cpp:218] Iteration 7920 (2.37165 iter/s, 5.05976s/12 iters), loss = 0.386339
I0406 15:01:27.643812 23057 solver.cpp:237]     Train net output #0: loss = 0.386339 (* 1 = 0.386339 loss)
I0406 15:01:27.643818 23057 sgd_solver.cpp:105] Iteration 7920, lr = 0.005
I0406 15:01:32.719908 23057 solver.cpp:218] Iteration 7932 (2.36405 iter/s, 5.07604s/12 iters), loss = 0.113527
I0406 15:01:32.719954 23057 solver.cpp:237]     Train net output #0: loss = 0.113527 (* 1 = 0.113527 loss)
I0406 15:01:32.719960 23057 sgd_solver.cpp:105] Iteration 7932, lr = 0.005
I0406 15:01:37.800346 23057 solver.cpp:218] Iteration 7944 (2.36205 iter/s, 5.08034s/12 iters), loss = 0.215101
I0406 15:01:37.800387 23057 solver.cpp:237]     Train net output #0: loss = 0.215102 (* 1 = 0.215102 loss)
I0406 15:01:37.800393 23057 sgd_solver.cpp:105] Iteration 7944, lr = 0.005
I0406 15:01:42.550367 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel
I0406 15:01:45.461094 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate
I0406 15:01:47.771802 23057 solver.cpp:330] Iteration 7956, Testing net (#0)
I0406 15:01:47.771823 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:01:49.065337 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:01:52.258432 23057 solver.cpp:397]     Test net output #0: accuracy = 0.400735
I0406 15:01:52.258460 23057 solver.cpp:397]     Test net output #1: loss = 3.22589 (* 1 = 3.22589 loss)
I0406 15:01:52.399001 23057 solver.cpp:218] Iteration 7956 (0.822002 iter/s, 14.5985s/12 iters), loss = 0.263765
I0406 15:01:52.400593 23057 solver.cpp:237]     Train net output #0: loss = 0.263765 (* 1 = 0.263765 loss)
I0406 15:01:52.400604 23057 sgd_solver.cpp:105] Iteration 7956, lr = 0.005
I0406 15:01:56.886451 23057 solver.cpp:218] Iteration 7968 (2.6751 iter/s, 4.48582s/12 iters), loss = 0.172445
I0406 15:01:56.886494 23057 solver.cpp:237]     Train net output #0: loss = 0.172445 (* 1 = 0.172445 loss)
I0406 15:01:56.886500 23057 sgd_solver.cpp:105] Iteration 7968, lr = 0.005
I0406 15:02:02.115424 23057 solver.cpp:218] Iteration 7980 (2.29495 iter/s, 5.22888s/12 iters), loss = 0.435616
I0406 15:02:02.115463 23057 solver.cpp:237]     Train net output #0: loss = 0.435616 (* 1 = 0.435616 loss)
I0406 15:02:02.115469 23057 sgd_solver.cpp:105] Iteration 7980, lr = 0.005
I0406 15:02:06.609751 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:02:07.415123 23057 solver.cpp:218] Iteration 7992 (2.26432 iter/s, 5.2996s/12 iters), loss = 0.294446
I0406 15:02:07.415164 23057 solver.cpp:237]     Train net output #0: loss = 0.294446 (* 1 = 0.294446 loss)
I0406 15:02:07.415170 23057 sgd_solver.cpp:105] Iteration 7992, lr = 0.005
I0406 15:02:12.797428 23057 solver.cpp:218] Iteration 8004 (2.22957 iter/s, 5.38221s/12 iters), loss = 0.3981
I0406 15:02:12.797576 23057 solver.cpp:237]     Train net output #0: loss = 0.398101 (* 1 = 0.398101 loss)
I0406 15:02:12.797586 23057 sgd_solver.cpp:105] Iteration 8004, lr = 0.005
I0406 15:02:17.851958 23057 solver.cpp:218] Iteration 8016 (2.3742 iter/s, 5.05433s/12 iters), loss = 0.289367
I0406 15:02:17.852015 23057 solver.cpp:237]     Train net output #0: loss = 0.289367 (* 1 = 0.289367 loss)
I0406 15:02:17.852025 23057 sgd_solver.cpp:105] Iteration 8016, lr = 0.005
I0406 15:02:23.230741 23057 solver.cpp:218] Iteration 8028 (2.23103 iter/s, 5.37867s/12 iters), loss = 0.159304
I0406 15:02:23.230790 23057 solver.cpp:237]     Train net output #0: loss = 0.159304 (* 1 = 0.159304 loss)
I0406 15:02:23.230798 23057 sgd_solver.cpp:105] Iteration 8028, lr = 0.005
I0406 15:02:28.228929 23057 solver.cpp:218] Iteration 8040 (2.40092 iter/s, 4.99809s/12 iters), loss = 0.166079
I0406 15:02:28.228972 23057 solver.cpp:237]     Train net output #0: loss = 0.166079 (* 1 = 0.166079 loss)
I0406 15:02:28.228978 23057 sgd_solver.cpp:105] Iteration 8040, lr = 0.005
I0406 15:02:33.514334 23057 solver.cpp:218] Iteration 8052 (2.27045 iter/s, 5.2853s/12 iters), loss = 0.332853
I0406 15:02:33.514377 23057 solver.cpp:237]     Train net output #0: loss = 0.332853 (* 1 = 0.332853 loss)
I0406 15:02:33.514382 23057 sgd_solver.cpp:105] Iteration 8052, lr = 0.005
I0406 15:02:35.704493 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel
I0406 15:02:38.718678 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate
I0406 15:02:41.069056 23057 solver.cpp:330] Iteration 8058, Testing net (#0)
I0406 15:02:41.069074 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:02:42.349488 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:02:45.514163 23057 solver.cpp:397]     Test net output #0: accuracy = 0.381127
I0406 15:02:45.514254 23057 solver.cpp:397]     Test net output #1: loss = 3.44307 (* 1 = 3.44307 loss)
I0406 15:02:47.452200 23057 solver.cpp:218] Iteration 8064 (0.860973 iter/s, 13.9377s/12 iters), loss = 0.389145
I0406 15:02:47.452241 23057 solver.cpp:237]     Train net output #0: loss = 0.389145 (* 1 = 0.389145 loss)
I0406 15:02:47.452247 23057 sgd_solver.cpp:105] Iteration 8064, lr = 0.005
I0406 15:02:52.558519 23057 solver.cpp:218] Iteration 8076 (2.35007 iter/s, 5.10622s/12 iters), loss = 0.291491
I0406 15:02:52.558558 23057 solver.cpp:237]     Train net output #0: loss = 0.291491 (* 1 = 0.291491 loss)
I0406 15:02:52.558564 23057 sgd_solver.cpp:105] Iteration 8076, lr = 0.005
I0406 15:02:57.999254 23057 solver.cpp:218] Iteration 8088 (2.20562 iter/s, 5.44064s/12 iters), loss = 0.334739
I0406 15:02:57.999295 23057 solver.cpp:237]     Train net output #0: loss = 0.334739 (* 1 = 0.334739 loss)
I0406 15:02:57.999301 23057 sgd_solver.cpp:105] Iteration 8088, lr = 0.005
I0406 15:02:59.383424 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:03:03.113241 23057 solver.cpp:218] Iteration 8100 (2.34655 iter/s, 5.11389s/12 iters), loss = 0.337855
I0406 15:03:03.113289 23057 solver.cpp:237]     Train net output #0: loss = 0.337855 (* 1 = 0.337855 loss)
I0406 15:03:03.113297 23057 sgd_solver.cpp:105] Iteration 8100, lr = 0.005
I0406 15:03:08.534862 23057 solver.cpp:218] Iteration 8112 (2.2134 iter/s, 5.42152s/12 iters), loss = 0.256338
I0406 15:03:08.534904 23057 solver.cpp:237]     Train net output #0: loss = 0.256338 (* 1 = 0.256338 loss)
I0406 15:03:08.534909 23057 sgd_solver.cpp:105] Iteration 8112, lr = 0.005
I0406 15:03:13.801784 23057 solver.cpp:218] Iteration 8124 (2.27841 iter/s, 5.26683s/12 iters), loss = 0.163506
I0406 15:03:13.808001 23057 solver.cpp:237]     Train net output #0: loss = 0.163507 (* 1 = 0.163507 loss)
I0406 15:03:13.808020 23057 sgd_solver.cpp:105] Iteration 8124, lr = 0.005
I0406 15:03:19.135603 23057 solver.cpp:218] Iteration 8136 (2.25244 iter/s, 5.32756s/12 iters), loss = 0.163702
I0406 15:03:19.135792 23057 solver.cpp:237]     Train net output #0: loss = 0.163702 (* 1 = 0.163702 loss)
I0406 15:03:19.135802 23057 sgd_solver.cpp:105] Iteration 8136, lr = 0.005
I0406 15:03:24.307785 23057 solver.cpp:218] Iteration 8148 (2.32021 iter/s, 5.17194s/12 iters), loss = 0.215292
I0406 15:03:24.307835 23057 solver.cpp:237]     Train net output #0: loss = 0.215293 (* 1 = 0.215293 loss)
I0406 15:03:24.307844 23057 sgd_solver.cpp:105] Iteration 8148, lr = 0.005
I0406 15:03:29.037371 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel
I0406 15:03:31.982129 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate
I0406 15:03:34.315940 23057 solver.cpp:330] Iteration 8160, Testing net (#0)
I0406 15:03:34.315960 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:03:35.507751 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:03:38.669144 23057 solver.cpp:397]     Test net output #0: accuracy = 0.40625
I0406 15:03:38.669179 23057 solver.cpp:397]     Test net output #1: loss = 3.3355 (* 1 = 3.3355 loss)
I0406 15:03:38.809749 23057 solver.cpp:218] Iteration 8160 (0.827484 iter/s, 14.5018s/12 iters), loss = 0.224273
I0406 15:03:38.809789 23057 solver.cpp:237]     Train net output #0: loss = 0.224273 (* 1 = 0.224273 loss)
I0406 15:03:38.809795 23057 sgd_solver.cpp:105] Iteration 8160, lr = 0.005
I0406 15:03:43.030887 23057 solver.cpp:218] Iteration 8172 (2.8429 iter/s, 4.22105s/12 iters), loss = 0.234144
I0406 15:03:43.030930 23057 solver.cpp:237]     Train net output #0: loss = 0.234144 (* 1 = 0.234144 loss)
I0406 15:03:43.030936 23057 sgd_solver.cpp:105] Iteration 8172, lr = 0.005
I0406 15:03:48.311816 23057 solver.cpp:218] Iteration 8184 (2.27237 iter/s, 5.28083s/12 iters), loss = 0.175646
I0406 15:03:48.311856 23057 solver.cpp:237]     Train net output #0: loss = 0.175646 (* 1 = 0.175646 loss)
I0406 15:03:48.311862 23057 sgd_solver.cpp:105] Iteration 8184, lr = 0.005
I0406 15:03:52.161967 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:03:53.654960 23057 solver.cpp:218] Iteration 8196 (2.24591 iter/s, 5.34305s/12 iters), loss = 0.528677
I0406 15:03:53.655001 23057 solver.cpp:237]     Train net output #0: loss = 0.528677 (* 1 = 0.528677 loss)
I0406 15:03:53.655007 23057 sgd_solver.cpp:105] Iteration 8196, lr = 0.005
I0406 15:03:58.830615 23057 solver.cpp:218] Iteration 8208 (2.31859 iter/s, 5.17556s/12 iters), loss = 0.287839
I0406 15:03:58.830664 23057 solver.cpp:237]     Train net output #0: loss = 0.287839 (* 1 = 0.287839 loss)
I0406 15:03:58.830672 23057 sgd_solver.cpp:105] Iteration 8208, lr = 0.005
I0406 15:04:03.891530 23057 solver.cpp:218] Iteration 8220 (2.37116 iter/s, 5.06082s/12 iters), loss = 0.22197
I0406 15:04:03.891567 23057 solver.cpp:237]     Train net output #0: loss = 0.22197 (* 1 = 0.22197 loss)
I0406 15:04:03.891573 23057 sgd_solver.cpp:105] Iteration 8220, lr = 0.005
I0406 15:04:09.284550 23057 solver.cpp:218] Iteration 8232 (2.22514 iter/s, 5.39293s/12 iters), loss = 0.335025
I0406 15:04:09.284593 23057 solver.cpp:237]     Train net output #0: loss = 0.335025 (* 1 = 0.335025 loss)
I0406 15:04:09.284600 23057 sgd_solver.cpp:105] Iteration 8232, lr = 0.005
I0406 15:04:14.692308 23057 solver.cpp:218] Iteration 8244 (2.21908 iter/s, 5.40766s/12 iters), loss = 0.294148
I0406 15:04:14.692353 23057 solver.cpp:237]     Train net output #0: loss = 0.294148 (* 1 = 0.294148 loss)
I0406 15:04:14.692359 23057 sgd_solver.cpp:105] Iteration 8244, lr = 0.005
I0406 15:04:19.684315 23057 solver.cpp:218] Iteration 8256 (2.40389 iter/s, 4.99191s/12 iters), loss = 0.182818
I0406 15:04:19.684355 23057 solver.cpp:237]     Train net output #0: loss = 0.182818 (* 1 = 0.182818 loss)
I0406 15:04:19.684360 23057 sgd_solver.cpp:105] Iteration 8256, lr = 0.005
I0406 15:04:21.752182 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel
I0406 15:04:24.778749 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate
I0406 15:04:27.068959 23057 solver.cpp:330] Iteration 8262, Testing net (#0)
I0406 15:04:27.068979 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:04:28.227552 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:04:31.408427 23057 solver.cpp:397]     Test net output #0: accuracy = 0.405637
I0406 15:04:31.408463 23057 solver.cpp:397]     Test net output #1: loss = 3.3896 (* 1 = 3.3896 loss)
I0406 15:04:33.266124 23057 solver.cpp:218] Iteration 8268 (0.883545 iter/s, 13.5817s/12 iters), loss = 0.146421
I0406 15:04:33.266175 23057 solver.cpp:237]     Train net output #0: loss = 0.146421 (* 1 = 0.146421 loss)
I0406 15:04:33.266182 23057 sgd_solver.cpp:105] Iteration 8268, lr = 0.005
I0406 15:04:38.626621 23057 solver.cpp:218] Iteration 8280 (2.23864 iter/s, 5.36039s/12 iters), loss = 0.234723
I0406 15:04:38.626664 23057 solver.cpp:237]     Train net output #0: loss = 0.234723 (* 1 = 0.234723 loss)
I0406 15:04:38.626670 23057 sgd_solver.cpp:105] Iteration 8280, lr = 0.005
I0406 15:04:43.854486 23057 solver.cpp:218] Iteration 8292 (2.29543 iter/s, 5.22777s/12 iters), loss = 0.230224
I0406 15:04:43.854524 23057 solver.cpp:237]     Train net output #0: loss = 0.230224 (* 1 = 0.230224 loss)
I0406 15:04:43.854530 23057 sgd_solver.cpp:105] Iteration 8292, lr = 0.005
I0406 15:04:44.520730 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:04:48.868961 23057 solver.cpp:218] Iteration 8304 (2.39312 iter/s, 5.01438s/12 iters), loss = 0.213738
I0406 15:04:48.869007 23057 solver.cpp:237]     Train net output #0: loss = 0.213738 (* 1 = 0.213738 loss)
I0406 15:04:48.869014 23057 sgd_solver.cpp:105] Iteration 8304, lr = 0.005
I0406 15:04:51.729687 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:04:54.052224 23057 solver.cpp:218] Iteration 8316 (2.31519 iter/s, 5.18315s/12 iters), loss = 0.137278
I0406 15:04:54.052280 23057 solver.cpp:237]     Train net output #0: loss = 0.137278 (* 1 = 0.137278 loss)
I0406 15:04:54.052289 23057 sgd_solver.cpp:105] Iteration 8316, lr = 0.005
I0406 15:04:59.479672 23057 solver.cpp:218] Iteration 8328 (2.21103 iter/s, 5.42734s/12 iters), loss = 0.273518
I0406 15:04:59.479800 23057 solver.cpp:237]     Train net output #0: loss = 0.273518 (* 1 = 0.273518 loss)
I0406 15:04:59.479809 23057 sgd_solver.cpp:105] Iteration 8328, lr = 0.005
I0406 15:05:04.672761 23057 solver.cpp:218] Iteration 8340 (2.31084 iter/s, 5.19291s/12 iters), loss = 0.398913
I0406 15:05:04.672811 23057 solver.cpp:237]     Train net output #0: loss = 0.398913 (* 1 = 0.398913 loss)
I0406 15:05:04.672817 23057 sgd_solver.cpp:105] Iteration 8340, lr = 0.005
I0406 15:05:09.794363 23057 solver.cpp:218] Iteration 8352 (2.34306 iter/s, 5.1215s/12 iters), loss = 0.236097
I0406 15:05:09.794409 23057 solver.cpp:237]     Train net output #0: loss = 0.236098 (* 1 = 0.236098 loss)
I0406 15:05:09.794415 23057 sgd_solver.cpp:105] Iteration 8352, lr = 0.005
I0406 15:05:14.544559 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel
I0406 15:05:17.622648 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate
I0406 15:05:19.945123 23057 solver.cpp:330] Iteration 8364, Testing net (#0)
I0406 15:05:19.945142 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:05:21.013885 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:05:24.381055 23057 solver.cpp:397]     Test net output #0: accuracy = 0.391544
I0406 15:05:24.381090 23057 solver.cpp:397]     Test net output #1: loss = 3.34558 (* 1 = 3.34558 loss)
I0406 15:05:24.521298 23057 solver.cpp:218] Iteration 8364 (0.814843 iter/s, 14.7268s/12 iters), loss = 0.150115
I0406 15:05:24.521354 23057 solver.cpp:237]     Train net output #0: loss = 0.150115 (* 1 = 0.150115 loss)
I0406 15:05:24.521363 23057 sgd_solver.cpp:105] Iteration 8364, lr = 0.005
I0406 15:05:28.874243 23057 solver.cpp:218] Iteration 8376 (2.75682 iter/s, 4.35284s/12 iters), loss = 0.20173
I0406 15:05:28.874282 23057 solver.cpp:237]     Train net output #0: loss = 0.20173 (* 1 = 0.20173 loss)
I0406 15:05:28.874289 23057 sgd_solver.cpp:105] Iteration 8376, lr = 0.005
I0406 15:05:34.037225 23057 solver.cpp:218] Iteration 8388 (2.32428 iter/s, 5.16289s/12 iters), loss = 0.299009
I0406 15:05:34.037382 23057 solver.cpp:237]     Train net output #0: loss = 0.299009 (* 1 = 0.299009 loss)
I0406 15:05:34.037391 23057 sgd_solver.cpp:105] Iteration 8388, lr = 0.005
I0406 15:05:37.034117 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:05:39.395584 23057 solver.cpp:218] Iteration 8400 (2.23958 iter/s, 5.35815s/12 iters), loss = 0.155384
I0406 15:05:39.395623 23057 solver.cpp:237]     Train net output #0: loss = 0.155384 (* 1 = 0.155384 loss)
I0406 15:05:39.395629 23057 sgd_solver.cpp:105] Iteration 8400, lr = 0.005
I0406 15:05:44.414721 23057 solver.cpp:218] Iteration 8412 (2.3909 iter/s, 5.01904s/12 iters), loss = 0.273865
I0406 15:05:44.414772 23057 solver.cpp:237]     Train net output #0: loss = 0.273865 (* 1 = 0.273865 loss)
I0406 15:05:44.414781 23057 sgd_solver.cpp:105] Iteration 8412, lr = 0.005
I0406 15:05:49.671167 23057 solver.cpp:218] Iteration 8424 (2.28296 iter/s, 5.25634s/12 iters), loss = 0.238406
I0406 15:05:49.671222 23057 solver.cpp:237]     Train net output #0: loss = 0.238406 (* 1 = 0.238406 loss)
I0406 15:05:49.671231 23057 sgd_solver.cpp:105] Iteration 8424, lr = 0.005
I0406 15:05:54.900493 23057 solver.cpp:218] Iteration 8436 (2.2948 iter/s, 5.22922s/12 iters), loss = 0.198466
I0406 15:05:54.900537 23057 solver.cpp:237]     Train net output #0: loss = 0.198466 (* 1 = 0.198466 loss)
I0406 15:05:54.900542 23057 sgd_solver.cpp:105] Iteration 8436, lr = 0.005
I0406 15:06:00.110982 23057 solver.cpp:218] Iteration 8448 (2.30309 iter/s, 5.21039s/12 iters), loss = 0.150189
I0406 15:06:00.111022 23057 solver.cpp:237]     Train net output #0: loss = 0.150189 (* 1 = 0.150189 loss)
I0406 15:06:00.111028 23057 sgd_solver.cpp:105] Iteration 8448, lr = 0.005
I0406 15:06:05.421319 23057 solver.cpp:218] Iteration 8460 (2.25979 iter/s, 5.31024s/12 iters), loss = 0.296538
I0406 15:06:05.421458 23057 solver.cpp:237]     Train net output #0: loss = 0.296538 (* 1 = 0.296538 loss)
I0406 15:06:05.421468 23057 sgd_solver.cpp:105] Iteration 8460, lr = 0.005
I0406 15:06:07.559128 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel
I0406 15:06:10.581914 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate
I0406 15:06:13.902155 23057 solver.cpp:330] Iteration 8466, Testing net (#0)
I0406 15:06:13.902177 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:06:14.931378 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:06:18.184319 23057 solver.cpp:397]     Test net output #0: accuracy = 0.394608
I0406 15:06:18.184355 23057 solver.cpp:397]     Test net output #1: loss = 3.32689 (* 1 = 3.32689 loss)
I0406 15:06:20.180702 23057 solver.cpp:218] Iteration 8472 (0.813056 iter/s, 14.7591s/12 iters), loss = 0.173103
I0406 15:06:20.180758 23057 solver.cpp:237]     Train net output #0: loss = 0.173103 (* 1 = 0.173103 loss)
I0406 15:06:20.180768 23057 sgd_solver.cpp:105] Iteration 8472, lr = 0.005
I0406 15:06:25.748136 23057 solver.cpp:218] Iteration 8484 (2.15544 iter/s, 5.56732s/12 iters), loss = 0.272272
I0406 15:06:25.748189 23057 solver.cpp:237]     Train net output #0: loss = 0.272272 (* 1 = 0.272272 loss)
I0406 15:06:25.748200 23057 sgd_solver.cpp:105] Iteration 8484, lr = 0.005
I0406 15:06:30.985741 23057 solver.cpp:218] Iteration 8496 (2.29117 iter/s, 5.2375s/12 iters), loss = 0.237019
I0406 15:06:30.985786 23057 solver.cpp:237]     Train net output #0: loss = 0.237019 (* 1 = 0.237019 loss)
I0406 15:06:30.985792 23057 sgd_solver.cpp:105] Iteration 8496, lr = 0.005
I0406 15:06:31.020687 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:06:36.275910 23057 solver.cpp:218] Iteration 8508 (2.2684 iter/s, 5.29007s/12 iters), loss = 0.153757
I0406 15:06:36.276059 23057 solver.cpp:237]     Train net output #0: loss = 0.153757 (* 1 = 0.153757 loss)
I0406 15:06:36.276069 23057 sgd_solver.cpp:105] Iteration 8508, lr = 0.005
I0406 15:06:41.659807 23057 solver.cpp:218] Iteration 8520 (2.22895 iter/s, 5.38369s/12 iters), loss = 0.231502
I0406 15:06:41.659853 23057 solver.cpp:237]     Train net output #0: loss = 0.231502 (* 1 = 0.231502 loss)
I0406 15:06:41.659859 23057 sgd_solver.cpp:105] Iteration 8520, lr = 0.005
I0406 15:06:46.873987 23057 solver.cpp:218] Iteration 8532 (2.30146 iter/s, 5.21408s/12 iters), loss = 0.370272
I0406 15:06:46.874028 23057 solver.cpp:237]     Train net output #0: loss = 0.370272 (* 1 = 0.370272 loss)
I0406 15:06:46.874035 23057 sgd_solver.cpp:105] Iteration 8532, lr = 0.005
I0406 15:06:52.166153 23057 solver.cpp:218] Iteration 8544 (2.26754 iter/s, 5.29207s/12 iters), loss = 0.263428
I0406 15:06:52.166208 23057 solver.cpp:237]     Train net output #0: loss = 0.263428 (* 1 = 0.263428 loss)
I0406 15:06:52.166218 23057 sgd_solver.cpp:105] Iteration 8544, lr = 0.005
I0406 15:06:57.514504 23057 solver.cpp:218] Iteration 8556 (2.24373 iter/s, 5.34824s/12 iters), loss = 0.212217
I0406 15:06:57.514542 23057 solver.cpp:237]     Train net output #0: loss = 0.212217 (* 1 = 0.212217 loss)
I0406 15:06:57.514549 23057 sgd_solver.cpp:105] Iteration 8556, lr = 0.005
I0406 15:07:02.360826 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel
I0406 15:07:07.894321 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate
I0406 15:07:10.203316 23057 solver.cpp:330] Iteration 8568, Testing net (#0)
I0406 15:07:10.203341 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:07:11.227442 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:07:14.682093 23057 solver.cpp:397]     Test net output #0: accuracy = 0.384804
I0406 15:07:14.682126 23057 solver.cpp:397]     Test net output #1: loss = 3.41419 (* 1 = 3.41419 loss)
I0406 15:07:14.815385 23057 solver.cpp:218] Iteration 8568 (0.693614 iter/s, 17.3007s/12 iters), loss = 0.254342
I0406 15:07:14.815436 23057 solver.cpp:237]     Train net output #0: loss = 0.254343 (* 1 = 0.254343 loss)
I0406 15:07:14.815444 23057 sgd_solver.cpp:105] Iteration 8568, lr = 0.005
I0406 15:07:19.088044 23057 solver.cpp:218] Iteration 8580 (2.80862 iter/s, 4.27256s/12 iters), loss = 0.190081
I0406 15:07:19.088084 23057 solver.cpp:237]     Train net output #0: loss = 0.190081 (* 1 = 0.190081 loss)
I0406 15:07:19.088090 23057 sgd_solver.cpp:105] Iteration 8580, lr = 0.005
I0406 15:07:24.506688 23057 solver.cpp:218] Iteration 8592 (2.21462 iter/s, 5.41854s/12 iters), loss = 0.130922
I0406 15:07:24.506734 23057 solver.cpp:237]     Train net output #0: loss = 0.130922 (* 1 = 0.130922 loss)
I0406 15:07:24.506742 23057 sgd_solver.cpp:105] Iteration 8592, lr = 0.005
I0406 15:07:26.722453 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:07:29.673707 23057 solver.cpp:218] Iteration 8604 (2.32247 iter/s, 5.16691s/12 iters), loss = 0.21709
I0406 15:07:29.673758 23057 solver.cpp:237]     Train net output #0: loss = 0.21709 (* 1 = 0.21709 loss)
I0406 15:07:29.673768 23057 sgd_solver.cpp:105] Iteration 8604, lr = 0.005
I0406 15:07:34.969491 23057 solver.cpp:218] Iteration 8616 (2.266 iter/s, 5.29567s/12 iters), loss = 0.125799
I0406 15:07:34.969544 23057 solver.cpp:237]     Train net output #0: loss = 0.125799 (* 1 = 0.125799 loss)
I0406 15:07:34.969552 23057 sgd_solver.cpp:105] Iteration 8616, lr = 0.005
I0406 15:07:40.057282 23057 solver.cpp:218] Iteration 8628 (2.35864 iter/s, 5.08768s/12 iters), loss = 0.343368
I0406 15:07:40.057438 23057 solver.cpp:237]     Train net output #0: loss = 0.343368 (* 1 = 0.343368 loss)
I0406 15:07:40.057448 23057 sgd_solver.cpp:105] Iteration 8628, lr = 0.005
I0406 15:07:45.229322 23057 solver.cpp:218] Iteration 8640 (2.32026 iter/s, 5.17183s/12 iters), loss = 0.233519
I0406 15:07:45.229373 23057 solver.cpp:237]     Train net output #0: loss = 0.233519 (* 1 = 0.233519 loss)
I0406 15:07:45.229382 23057 sgd_solver.cpp:105] Iteration 8640, lr = 0.005
I0406 15:07:50.249902 23057 solver.cpp:218] Iteration 8652 (2.39021 iter/s, 5.02048s/12 iters), loss = 0.181159
I0406 15:07:50.249945 23057 solver.cpp:237]     Train net output #0: loss = 0.181159 (* 1 = 0.181159 loss)
I0406 15:07:50.249951 23057 sgd_solver.cpp:105] Iteration 8652, lr = 0.005
I0406 15:07:55.575595 23057 solver.cpp:218] Iteration 8664 (2.25327 iter/s, 5.32559s/12 iters), loss = 0.236685
I0406 15:07:55.575637 23057 solver.cpp:237]     Train net output #0: loss = 0.236685 (* 1 = 0.236685 loss)
I0406 15:07:55.575644 23057 sgd_solver.cpp:105] Iteration 8664, lr = 0.005
I0406 15:07:57.641352 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel
I0406 15:08:01.225524 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate
I0406 15:08:03.534020 23057 solver.cpp:330] Iteration 8670, Testing net (#0)
I0406 15:08:03.534042 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:08:04.474865 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:08:08.052119 23057 solver.cpp:397]     Test net output #0: accuracy = 0.387255
I0406 15:08:08.052147 23057 solver.cpp:397]     Test net output #1: loss = 3.4155 (* 1 = 3.4155 loss)
I0406 15:08:09.998268 23057 solver.cpp:218] Iteration 8676 (0.832033 iter/s, 14.4225s/12 iters), loss = 0.256855
I0406 15:08:09.998329 23057 solver.cpp:237]     Train net output #0: loss = 0.256855 (* 1 = 0.256855 loss)
I0406 15:08:09.998337 23057 sgd_solver.cpp:105] Iteration 8676, lr = 0.005
I0406 15:08:15.297472 23057 solver.cpp:218] Iteration 8688 (2.26454 iter/s, 5.29909s/12 iters), loss = 0.175021
I0406 15:08:15.297578 23057 solver.cpp:237]     Train net output #0: loss = 0.175021 (* 1 = 0.175021 loss)
I0406 15:08:15.297587 23057 sgd_solver.cpp:105] Iteration 8688, lr = 0.005
I0406 15:08:19.680680 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:08:20.439880 23057 solver.cpp:218] Iteration 8700 (2.33361 iter/s, 5.14225s/12 iters), loss = 0.222084
I0406 15:08:20.439922 23057 solver.cpp:237]     Train net output #0: loss = 0.222085 (* 1 = 0.222085 loss)
I0406 15:08:20.439929 23057 sgd_solver.cpp:105] Iteration 8700, lr = 0.005
I0406 15:08:25.338905 23057 solver.cpp:218] Iteration 8712 (2.44952 iter/s, 4.89893s/12 iters), loss = 0.219258
I0406 15:08:25.338950 23057 solver.cpp:237]     Train net output #0: loss = 0.219258 (* 1 = 0.219258 loss)
I0406 15:08:25.338956 23057 sgd_solver.cpp:105] Iteration 8712, lr = 0.005
I0406 15:08:30.558878 23057 solver.cpp:218] Iteration 8724 (2.29891 iter/s, 5.21987s/12 iters), loss = 0.158667
I0406 15:08:30.558925 23057 solver.cpp:237]     Train net output #0: loss = 0.158667 (* 1 = 0.158667 loss)
I0406 15:08:30.558931 23057 sgd_solver.cpp:105] Iteration 8724, lr = 0.005
I0406 15:08:35.636236 23057 solver.cpp:218] Iteration 8736 (2.36348 iter/s, 5.07726s/12 iters), loss = 0.141008
I0406 15:08:35.636279 23057 solver.cpp:237]     Train net output #0: loss = 0.141008 (* 1 = 0.141008 loss)
I0406 15:08:35.636286 23057 sgd_solver.cpp:105] Iteration 8736, lr = 0.005
I0406 15:08:40.914182 23057 solver.cpp:218] Iteration 8748 (2.27365 iter/s, 5.27785s/12 iters), loss = 0.172521
I0406 15:08:40.914223 23057 solver.cpp:237]     Train net output #0: loss = 0.172521 (* 1 = 0.172521 loss)
I0406 15:08:40.914230 23057 sgd_solver.cpp:105] Iteration 8748, lr = 0.005
I0406 15:08:46.285547 23057 solver.cpp:218] Iteration 8760 (2.23411 iter/s, 5.37127s/12 iters), loss = 0.163559
I0406 15:08:46.285709 23057 solver.cpp:237]     Train net output #0: loss = 0.163559 (* 1 = 0.163559 loss)
I0406 15:08:46.285719 23057 sgd_solver.cpp:105] Iteration 8760, lr = 0.005
I0406 15:08:51.087296 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel
I0406 15:08:54.076535 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate
I0406 15:08:56.369555 23057 solver.cpp:330] Iteration 8772, Testing net (#0)
I0406 15:08:56.369575 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:08:57.357048 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:09:00.837788 23057 solver.cpp:397]     Test net output #0: accuracy = 0.395221
I0406 15:09:00.837815 23057 solver.cpp:397]     Test net output #1: loss = 3.29567 (* 1 = 3.29567 loss)
I0406 15:09:00.978117 23057 solver.cpp:218] Iteration 8772 (0.816755 iter/s, 14.6923s/12 iters), loss = 0.38054
I0406 15:09:00.978178 23057 solver.cpp:237]     Train net output #0: loss = 0.38054 (* 1 = 0.38054 loss)
I0406 15:09:00.978185 23057 sgd_solver.cpp:105] Iteration 8772, lr = 0.005
I0406 15:09:05.278102 23057 solver.cpp:218] Iteration 8784 (2.79078 iter/s, 4.29988s/12 iters), loss = 0.106494
I0406 15:09:05.278146 23057 solver.cpp:237]     Train net output #0: loss = 0.106494 (* 1 = 0.106494 loss)
I0406 15:09:05.278151 23057 sgd_solver.cpp:105] Iteration 8784, lr = 0.005
I0406 15:09:10.467605 23057 solver.cpp:218] Iteration 8796 (2.3124 iter/s, 5.1894s/12 iters), loss = 0.297662
I0406 15:09:10.467650 23057 solver.cpp:237]     Train net output #0: loss = 0.297662 (* 1 = 0.297662 loss)
I0406 15:09:10.467656 23057 sgd_solver.cpp:105] Iteration 8796, lr = 0.005
I0406 15:09:12.107129 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:09:15.961866 23057 solver.cpp:218] Iteration 8808 (2.18414 iter/s, 5.49416s/12 iters), loss = 0.114189
I0406 15:09:15.961928 23057 solver.cpp:237]     Train net output #0: loss = 0.114189 (* 1 = 0.114189 loss)
I0406 15:09:15.961937 23057 sgd_solver.cpp:105] Iteration 8808, lr = 0.005
I0406 15:09:20.959758 23057 solver.cpp:218] Iteration 8820 (2.40107 iter/s, 4.99778s/12 iters), loss = 0.13646
I0406 15:09:20.959858 23057 solver.cpp:237]     Train net output #0: loss = 0.13646 (* 1 = 0.13646 loss)
I0406 15:09:20.959865 23057 sgd_solver.cpp:105] Iteration 8820, lr = 0.005
I0406 15:09:26.202502 23057 solver.cpp:218] Iteration 8832 (2.28895 iter/s, 5.24259s/12 iters), loss = 0.211017
I0406 15:09:26.202551 23057 solver.cpp:237]     Train net output #0: loss = 0.211017 (* 1 = 0.211017 loss)
I0406 15:09:26.202558 23057 sgd_solver.cpp:105] Iteration 8832, lr = 0.005
I0406 15:09:31.521891 23057 solver.cpp:218] Iteration 8844 (2.25594 iter/s, 5.31929s/12 iters), loss = 0.310245
I0406 15:09:31.521935 23057 solver.cpp:237]     Train net output #0: loss = 0.310246 (* 1 = 0.310246 loss)
I0406 15:09:31.521941 23057 sgd_solver.cpp:105] Iteration 8844, lr = 0.005
I0406 15:09:36.567047 23057 solver.cpp:218] Iteration 8856 (2.37857 iter/s, 5.04505s/12 iters), loss = 0.121916
I0406 15:09:36.567095 23057 solver.cpp:237]     Train net output #0: loss = 0.121916 (* 1 = 0.121916 loss)
I0406 15:09:36.567102 23057 sgd_solver.cpp:105] Iteration 8856, lr = 0.005
I0406 15:09:41.932147 23057 solver.cpp:218] Iteration 8868 (2.23672 iter/s, 5.36499s/12 iters), loss = 0.461085
I0406 15:09:41.932191 23057 solver.cpp:237]     Train net output #0: loss = 0.461085 (* 1 = 0.461085 loss)
I0406 15:09:41.932197 23057 sgd_solver.cpp:105] Iteration 8868, lr = 0.005
I0406 15:09:43.899013 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel
I0406 15:09:46.916278 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate
I0406 15:09:49.239580 23057 solver.cpp:330] Iteration 8874, Testing net (#0)
I0406 15:09:49.239607 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:09:50.127904 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:09:53.583469 23057 solver.cpp:397]     Test net output #0: accuracy = 0.398897
I0406 15:09:53.583580 23057 solver.cpp:397]     Test net output #1: loss = 3.28593 (* 1 = 3.28593 loss)
I0406 15:09:55.561578 23057 solver.cpp:218] Iteration 8880 (0.880458 iter/s, 13.6293s/12 iters), loss = 0.190291
I0406 15:09:55.561621 23057 solver.cpp:237]     Train net output #0: loss = 0.190291 (* 1 = 0.190291 loss)
I0406 15:09:55.561628 23057 sgd_solver.cpp:105] Iteration 8880, lr = 0.005
I0406 15:10:00.886513 23057 solver.cpp:218] Iteration 8892 (2.25359 iter/s, 5.32484s/12 iters), loss = 0.196027
I0406 15:10:00.886555 23057 solver.cpp:237]     Train net output #0: loss = 0.196027 (* 1 = 0.196027 loss)
I0406 15:10:00.886561 23057 sgd_solver.cpp:105] Iteration 8892, lr = 0.005
I0406 15:10:04.525202 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:10:06.103296 23057 solver.cpp:218] Iteration 8904 (2.30031 iter/s, 5.21668s/12 iters), loss = 0.186786
I0406 15:10:06.103338 23057 solver.cpp:237]     Train net output #0: loss = 0.186786 (* 1 = 0.186786 loss)
I0406 15:10:06.103343 23057 sgd_solver.cpp:105] Iteration 8904, lr = 0.005
I0406 15:10:11.443549 23057 solver.cpp:218] Iteration 8916 (2.24713 iter/s, 5.34015s/12 iters), loss = 0.292498
I0406 15:10:11.443590 23057 solver.cpp:237]     Train net output #0: loss = 0.292498 (* 1 = 0.292498 loss)
I0406 15:10:11.443596 23057 sgd_solver.cpp:105] Iteration 8916, lr = 0.005
I0406 15:10:16.839864 23057 solver.cpp:218] Iteration 8928 (2.22378 iter/s, 5.39621s/12 iters), loss = 0.335793
I0406 15:10:16.839901 23057 solver.cpp:237]     Train net output #0: loss = 0.335793 (* 1 = 0.335793 loss)
I0406 15:10:16.839910 23057 sgd_solver.cpp:105] Iteration 8928, lr = 0.005
I0406 15:10:21.858114 23057 solver.cpp:218] Iteration 8940 (2.39132 iter/s, 5.01815s/12 iters), loss = 0.256662
I0406 15:10:21.858165 23057 solver.cpp:237]     Train net output #0: loss = 0.256662 (* 1 = 0.256662 loss)
I0406 15:10:21.858172 23057 sgd_solver.cpp:105] Iteration 8940, lr = 0.005
I0406 15:10:27.124781 23057 solver.cpp:218] Iteration 8952 (2.27853 iter/s, 5.26656s/12 iters), loss = 0.125232
I0406 15:10:27.124876 23057 solver.cpp:237]     Train net output #0: loss = 0.125233 (* 1 = 0.125233 loss)
I0406 15:10:27.124886 23057 sgd_solver.cpp:105] Iteration 8952, lr = 0.005
I0406 15:10:32.194443 23057 solver.cpp:218] Iteration 8964 (2.36709 iter/s, 5.06951s/12 iters), loss = 0.339559
I0406 15:10:32.194485 23057 solver.cpp:237]     Train net output #0: loss = 0.339559 (* 1 = 0.339559 loss)
I0406 15:10:32.194491 23057 sgd_solver.cpp:105] Iteration 8964, lr = 0.005
I0406 15:10:37.076084 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel
I0406 15:10:40.064317 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate
I0406 15:10:42.358573 23057 solver.cpp:330] Iteration 8976, Testing net (#0)
I0406 15:10:42.358594 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:10:43.210256 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:10:46.706202 23057 solver.cpp:397]     Test net output #0: accuracy = 0.415441
I0406 15:10:46.706238 23057 solver.cpp:397]     Test net output #1: loss = 3.32172 (* 1 = 3.32172 loss)
I0406 15:10:46.847719 23057 solver.cpp:218] Iteration 8976 (0.818939 iter/s, 14.6531s/12 iters), loss = 0.0903514
I0406 15:10:46.847769 23057 solver.cpp:237]     Train net output #0: loss = 0.0903516 (* 1 = 0.0903516 loss)
I0406 15:10:46.847776 23057 sgd_solver.cpp:105] Iteration 8976, lr = 0.005
I0406 15:10:51.319523 23057 solver.cpp:218] Iteration 8988 (2.68354 iter/s, 4.4717s/12 iters), loss = 0.15205
I0406 15:10:51.319579 23057 solver.cpp:237]     Train net output #0: loss = 0.15205 (* 1 = 0.15205 loss)
I0406 15:10:51.319588 23057 sgd_solver.cpp:105] Iteration 8988, lr = 0.005
I0406 15:10:54.673506 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:10:56.496333 23057 solver.cpp:218] Iteration 9000 (2.31808 iter/s, 5.1767s/12 iters), loss = 0.336719
I0406 15:10:56.496381 23057 solver.cpp:237]     Train net output #0: loss = 0.33672 (* 1 = 0.33672 loss)
I0406 15:10:56.496389 23057 sgd_solver.cpp:105] Iteration 9000, lr = 0.005
I0406 15:10:57.215018 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:11:01.712962 23057 solver.cpp:218] Iteration 9012 (2.30038 iter/s, 5.21652s/12 iters), loss = 0.234777
I0406 15:11:01.713021 23057 solver.cpp:237]     Train net output #0: loss = 0.234777 (* 1 = 0.234777 loss)
I0406 15:11:01.713029 23057 sgd_solver.cpp:105] Iteration 9012, lr = 0.005
I0406 15:11:07.086645 23057 solver.cpp:218] Iteration 9024 (2.23315 iter/s, 5.37357s/12 iters), loss = 0.379537
I0406 15:11:07.086694 23057 solver.cpp:237]     Train net output #0: loss = 0.379537 (* 1 = 0.379537 loss)
I0406 15:11:07.086701 23057 sgd_solver.cpp:105] Iteration 9024, lr = 0.005
I0406 15:11:12.417198 23057 solver.cpp:218] Iteration 9036 (2.25122 iter/s, 5.33045s/12 iters), loss = 0.200606
I0406 15:11:12.417243 23057 solver.cpp:237]     Train net output #0: loss = 0.200606 (* 1 = 0.200606 loss)
I0406 15:11:12.417248 23057 sgd_solver.cpp:105] Iteration 9036, lr = 0.005
I0406 15:11:17.700029 23057 solver.cpp:218] Iteration 9048 (2.27155 iter/s, 5.28273s/12 iters), loss = 0.234699
I0406 15:11:17.700088 23057 solver.cpp:237]     Train net output #0: loss = 0.2347 (* 1 = 0.2347 loss)
I0406 15:11:17.700095 23057 sgd_solver.cpp:105] Iteration 9048, lr = 0.005
I0406 15:11:22.837960 23057 solver.cpp:218] Iteration 9060 (2.33562 iter/s, 5.13782s/12 iters), loss = 0.386809
I0406 15:11:22.838001 23057 solver.cpp:237]     Train net output #0: loss = 0.386809 (* 1 = 0.386809 loss)
I0406 15:11:22.838006 23057 sgd_solver.cpp:105] Iteration 9060, lr = 0.005
I0406 15:11:28.129076 23057 solver.cpp:218] Iteration 9072 (2.26799 iter/s, 5.29102s/12 iters), loss = 0.217445
I0406 15:11:28.129166 23057 solver.cpp:237]     Train net output #0: loss = 0.217445 (* 1 = 0.217445 loss)
I0406 15:11:28.129173 23057 sgd_solver.cpp:105] Iteration 9072, lr = 0.005
I0406 15:11:30.123994 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel
I0406 15:11:33.128754 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate
I0406 15:11:35.425493 23057 solver.cpp:330] Iteration 9078, Testing net (#0)
I0406 15:11:35.425513 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:11:36.313459 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:11:39.846113 23057 solver.cpp:397]     Test net output #0: accuracy = 0.409314
I0406 15:11:39.846153 23057 solver.cpp:397]     Test net output #1: loss = 3.25032 (* 1 = 3.25032 loss)
I0406 15:11:41.682516 23057 solver.cpp:218] Iteration 9084 (0.885398 iter/s, 13.5532s/12 iters), loss = 0.314999
I0406 15:11:41.682562 23057 solver.cpp:237]     Train net output #0: loss = 0.314999 (* 1 = 0.314999 loss)
I0406 15:11:41.682569 23057 sgd_solver.cpp:105] Iteration 9084, lr = 0.005
I0406 15:11:46.768863 23057 solver.cpp:218] Iteration 9096 (2.35931 iter/s, 5.08624s/12 iters), loss = 0.160611
I0406 15:11:46.768929 23057 solver.cpp:237]     Train net output #0: loss = 0.160611 (* 1 = 0.160611 loss)
I0406 15:11:46.768937 23057 sgd_solver.cpp:105] Iteration 9096, lr = 0.005
I0406 15:11:49.586174 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:11:51.859845 23057 solver.cpp:218] Iteration 9108 (2.35716 iter/s, 5.09086s/12 iters), loss = 0.253662
I0406 15:11:51.859882 23057 solver.cpp:237]     Train net output #0: loss = 0.253662 (* 1 = 0.253662 loss)
I0406 15:11:51.859889 23057 sgd_solver.cpp:105] Iteration 9108, lr = 0.005
I0406 15:11:57.155961 23057 solver.cpp:218] Iteration 9120 (2.26585 iter/s, 5.29602s/12 iters), loss = 0.206058
I0406 15:11:57.156002 23057 solver.cpp:237]     Train net output #0: loss = 0.206058 (* 1 = 0.206058 loss)
I0406 15:11:57.156008 23057 sgd_solver.cpp:105] Iteration 9120, lr = 0.005
I0406 15:12:02.451421 23057 solver.cpp:218] Iteration 9132 (2.26613 iter/s, 5.29536s/12 iters), loss = 0.132827
I0406 15:12:02.451543 23057 solver.cpp:237]     Train net output #0: loss = 0.132827 (* 1 = 0.132827 loss)
I0406 15:12:02.451550 23057 sgd_solver.cpp:105] Iteration 9132, lr = 0.005
I0406 15:12:07.893319 23057 solver.cpp:218] Iteration 9144 (2.20519 iter/s, 5.44172s/12 iters), loss = 0.136176
I0406 15:12:07.893359 23057 solver.cpp:237]     Train net output #0: loss = 0.136176 (* 1 = 0.136176 loss)
I0406 15:12:07.893365 23057 sgd_solver.cpp:105] Iteration 9144, lr = 0.005
I0406 15:12:13.462911 23057 solver.cpp:218] Iteration 9156 (2.15459 iter/s, 5.56949s/12 iters), loss = 0.163603
I0406 15:12:13.462949 23057 solver.cpp:237]     Train net output #0: loss = 0.163603 (* 1 = 0.163603 loss)
I0406 15:12:13.462954 23057 sgd_solver.cpp:105] Iteration 9156, lr = 0.005
I0406 15:12:18.690024 23057 solver.cpp:218] Iteration 9168 (2.29577 iter/s, 5.22701s/12 iters), loss = 0.163186
I0406 15:12:18.690068 23057 solver.cpp:237]     Train net output #0: loss = 0.163186 (* 1 = 0.163186 loss)
I0406 15:12:18.690075 23057 sgd_solver.cpp:105] Iteration 9168, lr = 0.005
I0406 15:12:23.384073 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel
I0406 15:12:26.401468 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate
I0406 15:12:28.693539 23057 solver.cpp:330] Iteration 9180, Testing net (#0)
I0406 15:12:28.693559 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:12:29.440492 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:12:32.966580 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 15:12:32.966658 23057 solver.cpp:397]     Test net output #1: loss = 3.4928 (* 1 = 3.4928 loss)
I0406 15:12:33.104200 23057 solver.cpp:218] Iteration 9180 (0.832524 iter/s, 14.414s/12 iters), loss = 0.212077
I0406 15:12:33.104257 23057 solver.cpp:237]     Train net output #0: loss = 0.212077 (* 1 = 0.212077 loss)
I0406 15:12:33.104264 23057 sgd_solver.cpp:105] Iteration 9180, lr = 0.005
I0406 15:12:37.455984 23057 solver.cpp:218] Iteration 9192 (2.75756 iter/s, 4.35167s/12 iters), loss = 0.204567
I0406 15:12:37.456032 23057 solver.cpp:237]     Train net output #0: loss = 0.204567 (* 1 = 0.204567 loss)
I0406 15:12:37.456040 23057 sgd_solver.cpp:105] Iteration 9192, lr = 0.005
I0406 15:12:42.861965 23057 solver.cpp:218] Iteration 9204 (2.21981 iter/s, 5.40587s/12 iters), loss = 0.327391
I0406 15:12:42.862020 23057 solver.cpp:237]     Train net output #0: loss = 0.327391 (* 1 = 0.327391 loss)
I0406 15:12:42.862027 23057 sgd_solver.cpp:105] Iteration 9204, lr = 0.005
I0406 15:12:42.936440 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:12:48.238219 23057 solver.cpp:218] Iteration 9216 (2.23208 iter/s, 5.37614s/12 iters), loss = 0.180481
I0406 15:12:48.238273 23057 solver.cpp:237]     Train net output #0: loss = 0.180481 (* 1 = 0.180481 loss)
I0406 15:12:48.238282 23057 sgd_solver.cpp:105] Iteration 9216, lr = 0.005
I0406 15:12:53.556653 23057 solver.cpp:218] Iteration 9228 (2.25635 iter/s, 5.31832s/12 iters), loss = 0.246326
I0406 15:12:53.556705 23057 solver.cpp:237]     Train net output #0: loss = 0.246326 (* 1 = 0.246326 loss)
I0406 15:12:53.556715 23057 sgd_solver.cpp:105] Iteration 9228, lr = 0.005
I0406 15:12:58.824960 23057 solver.cpp:218] Iteration 9240 (2.27782 iter/s, 5.26819s/12 iters), loss = 0.238906
I0406 15:12:58.825017 23057 solver.cpp:237]     Train net output #0: loss = 0.238906 (* 1 = 0.238906 loss)
I0406 15:12:58.825026 23057 sgd_solver.cpp:105] Iteration 9240, lr = 0.005
I0406 15:13:04.198472 23057 solver.cpp:218] Iteration 9252 (2.23322 iter/s, 5.3734s/12 iters), loss = 0.269912
I0406 15:13:04.198587 23057 solver.cpp:237]     Train net output #0: loss = 0.269912 (* 1 = 0.269912 loss)
I0406 15:13:04.198596 23057 sgd_solver.cpp:105] Iteration 9252, lr = 0.005
I0406 15:13:09.461290 23057 solver.cpp:218] Iteration 9264 (2.28022 iter/s, 5.26265s/12 iters), loss = 0.124248
I0406 15:13:09.461346 23057 solver.cpp:237]     Train net output #0: loss = 0.124248 (* 1 = 0.124248 loss)
I0406 15:13:09.461355 23057 sgd_solver.cpp:105] Iteration 9264, lr = 0.005
I0406 15:13:14.727355 23057 solver.cpp:218] Iteration 9276 (2.27879 iter/s, 5.26595s/12 iters), loss = 0.253485
I0406 15:13:14.727396 23057 solver.cpp:237]     Train net output #0: loss = 0.253485 (* 1 = 0.253485 loss)
I0406 15:13:14.727401 23057 sgd_solver.cpp:105] Iteration 9276, lr = 0.005
I0406 15:13:16.918711 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel
I0406 15:13:19.872718 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate
I0406 15:13:22.181237 23057 solver.cpp:330] Iteration 9282, Testing net (#0)
I0406 15:13:22.181257 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:13:22.904225 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:13:26.564472 23057 solver.cpp:397]     Test net output #0: accuracy = 0.387868
I0406 15:13:26.564509 23057 solver.cpp:397]     Test net output #1: loss = 3.3569 (* 1 = 3.3569 loss)
I0406 15:13:28.559890 23057 solver.cpp:218] Iteration 9288 (0.86753 iter/s, 13.8324s/12 iters), loss = 0.188103
I0406 15:13:28.559929 23057 solver.cpp:237]     Train net output #0: loss = 0.188103 (* 1 = 0.188103 loss)
I0406 15:13:28.559935 23057 sgd_solver.cpp:105] Iteration 9288, lr = 0.005
I0406 15:13:33.534668 23057 solver.cpp:218] Iteration 9300 (2.41221 iter/s, 4.97468s/12 iters), loss = 0.157516
I0406 15:13:33.534708 23057 solver.cpp:237]     Train net output #0: loss = 0.157516 (* 1 = 0.157516 loss)
I0406 15:13:33.534713 23057 sgd_solver.cpp:105] Iteration 9300, lr = 0.005
I0406 15:13:35.843515 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:13:38.676939 23057 solver.cpp:218] Iteration 9312 (2.33364 iter/s, 5.14217s/12 iters), loss = 0.229654
I0406 15:13:38.677006 23057 solver.cpp:237]     Train net output #0: loss = 0.229654 (* 1 = 0.229654 loss)
I0406 15:13:38.677016 23057 sgd_solver.cpp:105] Iteration 9312, lr = 0.005
I0406 15:13:44.093894 23057 solver.cpp:218] Iteration 9324 (2.21532 iter/s, 5.41683s/12 iters), loss = 0.0902429
I0406 15:13:44.093952 23057 solver.cpp:237]     Train net output #0: loss = 0.090243 (* 1 = 0.090243 loss)
I0406 15:13:44.093961 23057 sgd_solver.cpp:105] Iteration 9324, lr = 0.005
I0406 15:13:49.345651 23057 solver.cpp:218] Iteration 9336 (2.285 iter/s, 5.25164s/12 iters), loss = 0.237379
I0406 15:13:49.345693 23057 solver.cpp:237]     Train net output #0: loss = 0.237379 (* 1 = 0.237379 loss)
I0406 15:13:49.345700 23057 sgd_solver.cpp:105] Iteration 9336, lr = 0.005
I0406 15:13:54.377792 23057 solver.cpp:218] Iteration 9348 (2.38472 iter/s, 5.03204s/12 iters), loss = 0.233888
I0406 15:13:54.377833 23057 solver.cpp:237]     Train net output #0: loss = 0.233888 (* 1 = 0.233888 loss)
I0406 15:13:54.377840 23057 sgd_solver.cpp:105] Iteration 9348, lr = 0.005
I0406 15:13:59.571244 23057 solver.cpp:218] Iteration 9360 (2.31065 iter/s, 5.19335s/12 iters), loss = 0.272172
I0406 15:13:59.571285 23057 solver.cpp:237]     Train net output #0: loss = 0.272172 (* 1 = 0.272172 loss)
I0406 15:13:59.571292 23057 sgd_solver.cpp:105] Iteration 9360, lr = 0.005
I0406 15:14:04.805554 23057 solver.cpp:218] Iteration 9372 (2.29261 iter/s, 5.23421s/12 iters), loss = 0.289365
I0406 15:14:04.805606 23057 solver.cpp:237]     Train net output #0: loss = 0.289365 (* 1 = 0.289365 loss)
I0406 15:14:04.805613 23057 sgd_solver.cpp:105] Iteration 9372, lr = 0.005
I0406 15:14:09.612288 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel
I0406 15:14:12.611701 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate
I0406 15:14:14.913908 23057 solver.cpp:330] Iteration 9384, Testing net (#0)
I0406 15:14:14.913928 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:14:15.591131 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:14:19.221601 23057 solver.cpp:397]     Test net output #0: accuracy = 0.413603
I0406 15:14:19.221629 23057 solver.cpp:397]     Test net output #1: loss = 3.2141 (* 1 = 3.2141 loss)
I0406 15:14:19.357270 23057 solver.cpp:218] Iteration 9384 (0.824655 iter/s, 14.5515s/12 iters), loss = 0.0676558
I0406 15:14:19.357314 23057 solver.cpp:237]     Train net output #0: loss = 0.0676558 (* 1 = 0.0676558 loss)
I0406 15:14:19.357321 23057 sgd_solver.cpp:105] Iteration 9384, lr = 0.005
I0406 15:14:23.769227 23057 solver.cpp:218] Iteration 9396 (2.71994 iter/s, 4.41186s/12 iters), loss = 0.147349
I0406 15:14:23.769270 23057 solver.cpp:237]     Train net output #0: loss = 0.147349 (* 1 = 0.147349 loss)
I0406 15:14:23.769276 23057 sgd_solver.cpp:105] Iteration 9396, lr = 0.005
I0406 15:14:28.420615 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:14:29.148977 23057 solver.cpp:218] Iteration 9408 (2.23063 iter/s, 5.37965s/12 iters), loss = 0.200482
I0406 15:14:29.149022 23057 solver.cpp:237]     Train net output #0: loss = 0.200482 (* 1 = 0.200482 loss)
I0406 15:14:29.149029 23057 sgd_solver.cpp:105] Iteration 9408, lr = 0.005
I0406 15:14:34.223975 23057 solver.cpp:218] Iteration 9420 (2.36458 iter/s, 5.0749s/12 iters), loss = 0.260339
I0406 15:14:34.224025 23057 solver.cpp:237]     Train net output #0: loss = 0.260339 (* 1 = 0.260339 loss)
I0406 15:14:34.224033 23057 sgd_solver.cpp:105] Iteration 9420, lr = 0.005
I0406 15:14:39.499667 23057 solver.cpp:218] Iteration 9432 (2.27463 iter/s, 5.27558s/12 iters), loss = 0.372566
I0406 15:14:39.499711 23057 solver.cpp:237]     Train net output #0: loss = 0.372566 (* 1 = 0.372566 loss)
I0406 15:14:39.499716 23057 sgd_solver.cpp:105] Iteration 9432, lr = 0.005
I0406 15:14:44.828255 23057 solver.cpp:218] Iteration 9444 (2.25205 iter/s, 5.32849s/12 iters), loss = 0.215182
I0406 15:14:44.828413 23057 solver.cpp:237]     Train net output #0: loss = 0.215182 (* 1 = 0.215182 loss)
I0406 15:14:44.828421 23057 sgd_solver.cpp:105] Iteration 9444, lr = 0.005
I0406 15:14:50.159204 23057 solver.cpp:218] Iteration 9456 (2.25112 iter/s, 5.33068s/12 iters), loss = 0.189493
I0406 15:14:50.159276 23057 solver.cpp:237]     Train net output #0: loss = 0.189493 (* 1 = 0.189493 loss)
I0406 15:14:50.159286 23057 sgd_solver.cpp:105] Iteration 9456, lr = 0.005
I0406 15:14:55.289484 23057 solver.cpp:218] Iteration 9468 (2.33911 iter/s, 5.13016s/12 iters), loss = 0.139952
I0406 15:14:55.289530 23057 solver.cpp:237]     Train net output #0: loss = 0.139952 (* 1 = 0.139952 loss)
I0406 15:14:55.289535 23057 sgd_solver.cpp:105] Iteration 9468, lr = 0.005
I0406 15:15:00.417948 23057 solver.cpp:218] Iteration 9480 (2.33993 iter/s, 5.12836s/12 iters), loss = 0.120825
I0406 15:15:00.417989 23057 solver.cpp:237]     Train net output #0: loss = 0.120825 (* 1 = 0.120825 loss)
I0406 15:15:00.417994 23057 sgd_solver.cpp:105] Iteration 9480, lr = 0.005
I0406 15:15:02.677816 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel
I0406 15:15:05.653045 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate
I0406 15:15:07.960186 23057 solver.cpp:330] Iteration 9486, Testing net (#0)
I0406 15:15:07.960204 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:15:08.604301 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:15:12.325724 23057 solver.cpp:397]     Test net output #0: accuracy = 0.410539
I0406 15:15:12.325755 23057 solver.cpp:397]     Test net output #1: loss = 3.27779 (* 1 = 3.27779 loss)
I0406 15:15:14.064321 23057 solver.cpp:218] Iteration 9492 (0.879365 iter/s, 13.6462s/12 iters), loss = 0.149357
I0406 15:15:14.064381 23057 solver.cpp:237]     Train net output #0: loss = 0.149357 (* 1 = 0.149357 loss)
I0406 15:15:14.064389 23057 sgd_solver.cpp:105] Iteration 9492, lr = 0.005
I0406 15:15:19.133883 23057 solver.cpp:218] Iteration 9504 (2.36712 iter/s, 5.06945s/12 iters), loss = 0.197808
I0406 15:15:19.133970 23057 solver.cpp:237]     Train net output #0: loss = 0.197808 (* 1 = 0.197808 loss)
I0406 15:15:19.133976 23057 sgd_solver.cpp:105] Iteration 9504, lr = 0.005
I0406 15:15:20.668099 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:15:24.349457 23057 solver.cpp:218] Iteration 9516 (2.30087 iter/s, 5.21543s/12 iters), loss = 0.317148
I0406 15:15:24.349504 23057 solver.cpp:237]     Train net output #0: loss = 0.317148 (* 1 = 0.317148 loss)
I0406 15:15:24.349511 23057 sgd_solver.cpp:105] Iteration 9516, lr = 0.005
I0406 15:15:29.539454 23057 solver.cpp:218] Iteration 9528 (2.31219 iter/s, 5.18989s/12 iters), loss = 0.244729
I0406 15:15:29.539505 23057 solver.cpp:237]     Train net output #0: loss = 0.244729 (* 1 = 0.244729 loss)
I0406 15:15:29.539512 23057 sgd_solver.cpp:105] Iteration 9528, lr = 0.005
I0406 15:15:34.495260 23057 solver.cpp:218] Iteration 9540 (2.42145 iter/s, 4.9557s/12 iters), loss = 0.357014
I0406 15:15:34.495307 23057 solver.cpp:237]     Train net output #0: loss = 0.357014 (* 1 = 0.357014 loss)
I0406 15:15:34.495314 23057 sgd_solver.cpp:105] Iteration 9540, lr = 0.005
I0406 15:15:39.775494 23057 solver.cpp:218] Iteration 9552 (2.27267 iter/s, 5.28013s/12 iters), loss = 0.178867
I0406 15:15:39.775534 23057 solver.cpp:237]     Train net output #0: loss = 0.178867 (* 1 = 0.178867 loss)
I0406 15:15:39.775540 23057 sgd_solver.cpp:105] Iteration 9552, lr = 0.005
I0406 15:15:45.163594 23057 solver.cpp:218] Iteration 9564 (2.22717 iter/s, 5.388s/12 iters), loss = 0.161416
I0406 15:15:45.163640 23057 solver.cpp:237]     Train net output #0: loss = 0.161416 (* 1 = 0.161416 loss)
I0406 15:15:45.163647 23057 sgd_solver.cpp:105] Iteration 9564, lr = 0.005
I0406 15:15:50.361968 23057 solver.cpp:218] Iteration 9576 (2.30846 iter/s, 5.19827s/12 iters), loss = 0.282103
I0406 15:15:50.362138 23057 solver.cpp:237]     Train net output #0: loss = 0.282103 (* 1 = 0.282103 loss)
I0406 15:15:50.362147 23057 sgd_solver.cpp:105] Iteration 9576, lr = 0.005
I0406 15:15:55.259315 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel
I0406 15:15:58.276691 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate
I0406 15:16:00.601161 23057 solver.cpp:330] Iteration 9588, Testing net (#0)
I0406 15:16:00.601181 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:16:01.224697 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:16:05.025979 23057 solver.cpp:397]     Test net output #0: accuracy = 0.413603
I0406 15:16:05.026016 23057 solver.cpp:397]     Test net output #1: loss = 3.33405 (* 1 = 3.33405 loss)
I0406 15:16:05.173013 23057 solver.cpp:218] Iteration 9588 (0.810223 iter/s, 14.8107s/12 iters), loss = 0.109763
I0406 15:16:05.174582 23057 solver.cpp:237]     Train net output #0: loss = 0.109764 (* 1 = 0.109764 loss)
I0406 15:16:05.174595 23057 sgd_solver.cpp:105] Iteration 9588, lr = 0.005
I0406 15:16:09.759918 23057 solver.cpp:218] Iteration 9600 (2.61706 iter/s, 4.58529s/12 iters), loss = 0.199789
I0406 15:16:09.759960 23057 solver.cpp:237]     Train net output #0: loss = 0.199789 (* 1 = 0.199789 loss)
I0406 15:16:09.759968 23057 sgd_solver.cpp:105] Iteration 9600, lr = 0.005
I0406 15:16:13.523053 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:16:15.058712 23057 solver.cpp:218] Iteration 9612 (2.26471 iter/s, 5.29869s/12 iters), loss = 0.130154
I0406 15:16:15.058758 23057 solver.cpp:237]     Train net output #0: loss = 0.130154 (* 1 = 0.130154 loss)
I0406 15:16:15.058763 23057 sgd_solver.cpp:105] Iteration 9612, lr = 0.005
I0406 15:16:20.396991 23057 solver.cpp:218] Iteration 9624 (2.24796 iter/s, 5.33818s/12 iters), loss = 0.2463
I0406 15:16:20.397111 23057 solver.cpp:237]     Train net output #0: loss = 0.2463 (* 1 = 0.2463 loss)
I0406 15:16:20.397119 23057 sgd_solver.cpp:105] Iteration 9624, lr = 0.005
I0406 15:16:25.694955 23057 solver.cpp:218] Iteration 9636 (2.2651 iter/s, 5.29779s/12 iters), loss = 0.0715614
I0406 15:16:25.695003 23057 solver.cpp:237]     Train net output #0: loss = 0.0715615 (* 1 = 0.0715615 loss)
I0406 15:16:25.695009 23057 sgd_solver.cpp:105] Iteration 9636, lr = 0.005
I0406 15:16:30.770658 23057 solver.cpp:218] Iteration 9648 (2.36425 iter/s, 5.0756s/12 iters), loss = 0.0593488
I0406 15:16:30.770704 23057 solver.cpp:237]     Train net output #0: loss = 0.0593488 (* 1 = 0.0593488 loss)
I0406 15:16:30.770710 23057 sgd_solver.cpp:105] Iteration 9648, lr = 0.005
I0406 15:16:35.962347 23057 solver.cpp:218] Iteration 9660 (2.31143 iter/s, 5.19159s/12 iters), loss = 0.0937029
I0406 15:16:35.962388 23057 solver.cpp:237]     Train net output #0: loss = 0.0937029 (* 1 = 0.0937029 loss)
I0406 15:16:35.962393 23057 sgd_solver.cpp:105] Iteration 9660, lr = 0.005
I0406 15:16:40.979189 23057 solver.cpp:218] Iteration 9672 (2.39199 iter/s, 5.01675s/12 iters), loss = 0.128687
I0406 15:16:40.979230 23057 solver.cpp:237]     Train net output #0: loss = 0.128687 (* 1 = 0.128687 loss)
I0406 15:16:40.979236 23057 sgd_solver.cpp:105] Iteration 9672, lr = 0.005
I0406 15:16:46.401073 23057 solver.cpp:218] Iteration 9684 (2.2133 iter/s, 5.42178s/12 iters), loss = 0.146098
I0406 15:16:46.401120 23057 solver.cpp:237]     Train net output #0: loss = 0.146098 (* 1 = 0.146098 loss)
I0406 15:16:46.401126 23057 sgd_solver.cpp:105] Iteration 9684, lr = 0.005
I0406 15:16:48.599738 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel
I0406 15:16:51.595115 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate
I0406 15:16:54.635171 23057 solver.cpp:330] Iteration 9690, Testing net (#0)
I0406 15:16:54.635192 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:16:55.240598 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:16:58.021328 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:16:59.086352 23057 solver.cpp:397]     Test net output #0: accuracy = 0.41973
I0406 15:16:59.086390 23057 solver.cpp:397]     Test net output #1: loss = 3.26821 (* 1 = 3.26821 loss)
I0406 15:17:01.036309 23057 solver.cpp:218] Iteration 9696 (0.819949 iter/s, 14.6351s/12 iters), loss = 0.14563
I0406 15:17:01.036346 23057 solver.cpp:237]     Train net output #0: loss = 0.14563 (* 1 = 0.14563 loss)
I0406 15:17:01.036352 23057 sgd_solver.cpp:105] Iteration 9696, lr = 0.005
I0406 15:17:06.377856 23057 solver.cpp:218] Iteration 9708 (2.24658 iter/s, 5.34145s/12 iters), loss = 0.28163
I0406 15:17:06.377915 23057 solver.cpp:237]     Train net output #0: loss = 0.28163 (* 1 = 0.28163 loss)
I0406 15:17:06.377924 23057 sgd_solver.cpp:105] Iteration 9708, lr = 0.005
I0406 15:17:07.125334 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:17:11.719656 23057 solver.cpp:218] Iteration 9720 (2.24648 iter/s, 5.34169s/12 iters), loss = 0.233093
I0406 15:17:11.719717 23057 solver.cpp:237]     Train net output #0: loss = 0.233093 (* 1 = 0.233093 loss)
I0406 15:17:11.719725 23057 sgd_solver.cpp:105] Iteration 9720, lr = 0.005
I0406 15:17:16.956504 23057 solver.cpp:218] Iteration 9732 (2.2915 iter/s, 5.23673s/12 iters), loss = 0.253671
I0406 15:17:16.956545 23057 solver.cpp:237]     Train net output #0: loss = 0.253672 (* 1 = 0.253672 loss)
I0406 15:17:16.956552 23057 sgd_solver.cpp:105] Iteration 9732, lr = 0.005
I0406 15:17:22.051178 23057 solver.cpp:218] Iteration 9744 (2.35545 iter/s, 5.09458s/12 iters), loss = 0.26012
I0406 15:17:22.051276 23057 solver.cpp:237]     Train net output #0: loss = 0.26012 (* 1 = 0.26012 loss)
I0406 15:17:22.051283 23057 sgd_solver.cpp:105] Iteration 9744, lr = 0.005
I0406 15:17:27.387398 23057 solver.cpp:218] Iteration 9756 (2.24885 iter/s, 5.33606s/12 iters), loss = 0.108381
I0406 15:17:27.387445 23057 solver.cpp:237]     Train net output #0: loss = 0.108381 (* 1 = 0.108381 loss)
I0406 15:17:27.387450 23057 sgd_solver.cpp:105] Iteration 9756, lr = 0.005
I0406 15:17:32.668284 23057 solver.cpp:218] Iteration 9768 (2.27239 iter/s, 5.28078s/12 iters), loss = 0.127057
I0406 15:17:32.668326 23057 solver.cpp:237]     Train net output #0: loss = 0.127057 (* 1 = 0.127057 loss)
I0406 15:17:32.668334 23057 sgd_solver.cpp:105] Iteration 9768, lr = 0.005
I0406 15:17:37.863406 23057 solver.cpp:218] Iteration 9780 (2.3099 iter/s, 5.19502s/12 iters), loss = 0.187622
I0406 15:17:37.863448 23057 solver.cpp:237]     Train net output #0: loss = 0.187622 (* 1 = 0.187622 loss)
I0406 15:17:37.863454 23057 sgd_solver.cpp:105] Iteration 9780, lr = 0.005
I0406 15:17:42.615794 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel
I0406 15:17:45.625416 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate
I0406 15:17:48.007616 23057 solver.cpp:330] Iteration 9792, Testing net (#0)
I0406 15:17:48.007635 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:17:48.521680 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:17:52.441020 23057 solver.cpp:397]     Test net output #0: accuracy = 0.409314
I0406 15:17:52.441129 23057 solver.cpp:397]     Test net output #1: loss = 3.26314 (* 1 = 3.26314 loss)
I0406 15:17:52.578023 23057 solver.cpp:218] Iteration 9792 (0.815525 iter/s, 14.7144s/12 iters), loss = 0.265669
I0406 15:17:52.578090 23057 solver.cpp:237]     Train net output #0: loss = 0.265669 (* 1 = 0.265669 loss)
I0406 15:17:52.578099 23057 sgd_solver.cpp:105] Iteration 9792, lr = 0.005
I0406 15:17:56.831487 23057 solver.cpp:218] Iteration 9804 (2.8213 iter/s, 4.25335s/12 iters), loss = 0.22403
I0406 15:17:56.831526 23057 solver.cpp:237]     Train net output #0: loss = 0.22403 (* 1 = 0.22403 loss)
I0406 15:17:56.831532 23057 sgd_solver.cpp:105] Iteration 9804, lr = 0.005
I0406 15:17:59.993103 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:18:02.195005 23057 solver.cpp:218] Iteration 9816 (2.23738 iter/s, 5.36342s/12 iters), loss = 0.0759374
I0406 15:18:02.195051 23057 solver.cpp:237]     Train net output #0: loss = 0.0759375 (* 1 = 0.0759375 loss)
I0406 15:18:02.195058 23057 sgd_solver.cpp:105] Iteration 9816, lr = 0.005
I0406 15:18:07.295514 23057 solver.cpp:218] Iteration 9828 (2.35275 iter/s, 5.10041s/12 iters), loss = 0.126391
I0406 15:18:07.295559 23057 solver.cpp:237]     Train net output #0: loss = 0.126391 (* 1 = 0.126391 loss)
I0406 15:18:07.295565 23057 sgd_solver.cpp:105] Iteration 9828, lr = 0.005
I0406 15:18:12.610654 23057 solver.cpp:218] Iteration 9840 (2.25775 iter/s, 5.31503s/12 iters), loss = 0.209315
I0406 15:18:12.610708 23057 solver.cpp:237]     Train net output #0: loss = 0.209315 (* 1 = 0.209315 loss)
I0406 15:18:12.610716 23057 sgd_solver.cpp:105] Iteration 9840, lr = 0.005
I0406 15:18:17.664094 23057 solver.cpp:218] Iteration 9852 (2.37467 iter/s, 5.05333s/12 iters), loss = 0.0463286
I0406 15:18:17.664149 23057 solver.cpp:237]     Train net output #0: loss = 0.0463287 (* 1 = 0.0463287 loss)
I0406 15:18:17.664156 23057 sgd_solver.cpp:105] Iteration 9852, lr = 0.005
I0406 15:18:22.962010 23057 solver.cpp:218] Iteration 9864 (2.26509 iter/s, 5.2978s/12 iters), loss = 0.329878
I0406 15:18:22.962111 23057 solver.cpp:237]     Train net output #0: loss = 0.329879 (* 1 = 0.329879 loss)
I0406 15:18:22.962118 23057 sgd_solver.cpp:105] Iteration 9864, lr = 0.005
I0406 15:18:28.006345 23057 solver.cpp:218] Iteration 9876 (2.37898 iter/s, 5.04418s/12 iters), loss = 0.209358
I0406 15:18:28.006392 23057 solver.cpp:237]     Train net output #0: loss = 0.209358 (* 1 = 0.209358 loss)
I0406 15:18:28.006400 23057 sgd_solver.cpp:105] Iteration 9876, lr = 0.005
I0406 15:18:32.986038 23057 solver.cpp:218] Iteration 9888 (2.40984 iter/s, 4.97959s/12 iters), loss = 0.38481
I0406 15:18:32.986078 23057 solver.cpp:237]     Train net output #0: loss = 0.38481 (* 1 = 0.38481 loss)
I0406 15:18:32.986084 23057 sgd_solver.cpp:105] Iteration 9888, lr = 0.005
I0406 15:18:35.072474 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel
I0406 15:18:38.876863 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate
I0406 15:18:42.154032 23057 solver.cpp:330] Iteration 9894, Testing net (#0)
I0406 15:18:42.154055 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:18:42.645503 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:18:46.606642 23057 solver.cpp:397]     Test net output #0: accuracy = 0.403799
I0406 15:18:46.606683 23057 solver.cpp:397]     Test net output #1: loss = 3.39446 (* 1 = 3.39446 loss)
I0406 15:18:48.466172 23057 solver.cpp:218] Iteration 9900 (0.775196 iter/s, 15.48s/12 iters), loss = 0.126818
I0406 15:18:48.466217 23057 solver.cpp:237]     Train net output #0: loss = 0.126818 (* 1 = 0.126818 loss)
I0406 15:18:48.466224 23057 sgd_solver.cpp:105] Iteration 9900, lr = 0.005
I0406 15:18:53.899869 23057 solver.cpp:218] Iteration 9912 (2.20848 iter/s, 5.43359s/12 iters), loss = 0.343983
I0406 15:18:53.899986 23057 solver.cpp:237]     Train net output #0: loss = 0.343983 (* 1 = 0.343983 loss)
I0406 15:18:53.899992 23057 sgd_solver.cpp:105] Iteration 9912, lr = 0.005
I0406 15:18:54.001507 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:18:59.376255 23057 solver.cpp:218] Iteration 9924 (2.19129 iter/s, 5.47622s/12 iters), loss = 0.409674
I0406 15:18:59.376293 23057 solver.cpp:237]     Train net output #0: loss = 0.409674 (* 1 = 0.409674 loss)
I0406 15:18:59.376298 23057 sgd_solver.cpp:105] Iteration 9924, lr = 0.005
I0406 15:19:04.391908 23057 solver.cpp:218] Iteration 9936 (2.39255 iter/s, 5.01556s/12 iters), loss = 0.235162
I0406 15:19:04.391947 23057 solver.cpp:237]     Train net output #0: loss = 0.235162 (* 1 = 0.235162 loss)
I0406 15:19:04.391952 23057 sgd_solver.cpp:105] Iteration 9936, lr = 0.005
I0406 15:19:09.598260 23057 solver.cpp:218] Iteration 9948 (2.30492 iter/s, 5.20626s/12 iters), loss = 0.171061
I0406 15:19:09.598299 23057 solver.cpp:237]     Train net output #0: loss = 0.171061 (* 1 = 0.171061 loss)
I0406 15:19:09.598305 23057 sgd_solver.cpp:105] Iteration 9948, lr = 0.005
I0406 15:19:14.606808 23057 solver.cpp:218] Iteration 9960 (2.39595 iter/s, 5.00845s/12 iters), loss = 0.142023
I0406 15:19:14.606851 23057 solver.cpp:237]     Train net output #0: loss = 0.142023 (* 1 = 0.142023 loss)
I0406 15:19:14.606858 23057 sgd_solver.cpp:105] Iteration 9960, lr = 0.005
I0406 15:19:19.922178 23057 solver.cpp:218] Iteration 9972 (2.25765 iter/s, 5.31527s/12 iters), loss = 0.123838
I0406 15:19:19.922215 23057 solver.cpp:237]     Train net output #0: loss = 0.123838 (* 1 = 0.123838 loss)
I0406 15:19:19.922220 23057 sgd_solver.cpp:105] Iteration 9972, lr = 0.005
I0406 15:19:25.016943 23057 solver.cpp:218] Iteration 9984 (2.3554 iter/s, 5.09467s/12 iters), loss = 0.248443
I0406 15:19:25.017037 23057 solver.cpp:237]     Train net output #0: loss = 0.248443 (* 1 = 0.248443 loss)
I0406 15:19:25.017045 23057 sgd_solver.cpp:105] Iteration 9984, lr = 0.005
I0406 15:19:29.792582 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel
I0406 15:19:32.787070 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate
I0406 15:19:35.117136 23057 solver.cpp:330] Iteration 9996, Testing net (#0)
I0406 15:19:35.117163 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:19:35.604285 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:19:39.430445 23057 solver.cpp:397]     Test net output #0: accuracy = 0.411152
I0406 15:19:39.430483 23057 solver.cpp:397]     Test net output #1: loss = 3.30241 (* 1 = 3.30241 loss)
I0406 15:19:39.578284 23057 solver.cpp:218] Iteration 9996 (0.824113 iter/s, 14.5611s/12 iters), loss = 0.180616
I0406 15:19:39.578330 23057 solver.cpp:237]     Train net output #0: loss = 0.180616 (* 1 = 0.180616 loss)
I0406 15:19:39.578336 23057 sgd_solver.cpp:105] Iteration 9996, lr = 0.005
I0406 15:19:43.757205 23057 solver.cpp:218] Iteration 10008 (2.87162 iter/s, 4.17883s/12 iters), loss = 0.221001
I0406 15:19:43.757248 23057 solver.cpp:237]     Train net output #0: loss = 0.221001 (* 1 = 0.221001 loss)
I0406 15:19:43.757254 23057 sgd_solver.cpp:105] Iteration 10008, lr = 0.005
I0406 15:19:46.107985 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:19:49.100617 23057 solver.cpp:218] Iteration 10020 (2.2458 iter/s, 5.3433s/12 iters), loss = 0.211404
I0406 15:19:49.100666 23057 solver.cpp:237]     Train net output #0: loss = 0.211404 (* 1 = 0.211404 loss)
I0406 15:19:49.100672 23057 sgd_solver.cpp:105] Iteration 10020, lr = 0.005
I0406 15:19:54.438737 23057 solver.cpp:218] Iteration 10032 (2.24803 iter/s, 5.33801s/12 iters), loss = 0.15101
I0406 15:19:54.438779 23057 solver.cpp:237]     Train net output #0: loss = 0.15101 (* 1 = 0.15101 loss)
I0406 15:19:54.438786 23057 sgd_solver.cpp:105] Iteration 10032, lr = 0.005
I0406 15:19:59.800597 23057 solver.cpp:218] Iteration 10044 (2.23807 iter/s, 5.36176s/12 iters), loss = 0.184151
I0406 15:19:59.800736 23057 solver.cpp:237]     Train net output #0: loss = 0.184151 (* 1 = 0.184151 loss)
I0406 15:19:59.800743 23057 sgd_solver.cpp:105] Iteration 10044, lr = 0.005
I0406 15:20:04.774768 23057 solver.cpp:218] Iteration 10056 (2.41256 iter/s, 4.97398s/12 iters), loss = 0.179522
I0406 15:20:04.774816 23057 solver.cpp:237]     Train net output #0: loss = 0.179522 (* 1 = 0.179522 loss)
I0406 15:20:04.774822 23057 sgd_solver.cpp:105] Iteration 10056, lr = 0.005
I0406 15:20:10.071751 23057 solver.cpp:218] Iteration 10068 (2.26549 iter/s, 5.29688s/12 iters), loss = 0.285609
I0406 15:20:10.071796 23057 solver.cpp:237]     Train net output #0: loss = 0.285609 (* 1 = 0.285609 loss)
I0406 15:20:10.071801 23057 sgd_solver.cpp:105] Iteration 10068, lr = 0.005
I0406 15:20:15.508069 23057 solver.cpp:218] Iteration 10080 (2.20742 iter/s, 5.43621s/12 iters), loss = 0.109626
I0406 15:20:15.508113 23057 solver.cpp:237]     Train net output #0: loss = 0.109626 (* 1 = 0.109626 loss)
I0406 15:20:15.508118 23057 sgd_solver.cpp:105] Iteration 10080, lr = 0.005
I0406 15:20:20.697490 23057 solver.cpp:218] Iteration 10092 (2.31244 iter/s, 5.18932s/12 iters), loss = 0.185196
I0406 15:20:20.697530 23057 solver.cpp:237]     Train net output #0: loss = 0.185196 (* 1 = 0.185196 loss)
I0406 15:20:20.697536 23057 sgd_solver.cpp:105] Iteration 10092, lr = 0.005
I0406 15:20:22.851832 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel
I0406 15:20:25.919786 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate
I0406 15:20:28.219224 23057 solver.cpp:330] Iteration 10098, Testing net (#0)
I0406 15:20:28.219242 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:20:28.641528 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:20:32.618475 23057 solver.cpp:397]     Test net output #0: accuracy = 0.398897
I0406 15:20:32.618562 23057 solver.cpp:397]     Test net output #1: loss = 3.23044 (* 1 = 3.23044 loss)
I0406 15:20:34.534124 23057 solver.cpp:218] Iteration 10104 (0.867273 iter/s, 13.8365s/12 iters), loss = 0.0861
I0406 15:20:34.534169 23057 solver.cpp:237]     Train net output #0: loss = 0.0861001 (* 1 = 0.0861001 loss)
I0406 15:20:34.534175 23057 sgd_solver.cpp:105] Iteration 10104, lr = 0.005
I0406 15:20:39.270066 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:20:39.973670 23057 solver.cpp:218] Iteration 10116 (2.20611 iter/s, 5.43944s/12 iters), loss = 0.154007
I0406 15:20:39.973712 23057 solver.cpp:237]     Train net output #0: loss = 0.154007 (* 1 = 0.154007 loss)
I0406 15:20:39.973718 23057 sgd_solver.cpp:105] Iteration 10116, lr = 0.005
I0406 15:20:45.103258 23057 solver.cpp:218] Iteration 10128 (2.33942 iter/s, 5.12949s/12 iters), loss = 0.203604
I0406 15:20:45.103304 23057 solver.cpp:237]     Train net output #0: loss = 0.203604 (* 1 = 0.203604 loss)
I0406 15:20:45.103310 23057 sgd_solver.cpp:105] Iteration 10128, lr = 0.005
I0406 15:20:50.344928 23057 solver.cpp:218] Iteration 10140 (2.28939 iter/s, 5.24156s/12 iters), loss = 0.262073
I0406 15:20:50.344972 23057 solver.cpp:237]     Train net output #0: loss = 0.262073 (* 1 = 0.262073 loss)
I0406 15:20:50.344978 23057 sgd_solver.cpp:105] Iteration 10140, lr = 0.005
I0406 15:20:55.665460 23057 solver.cpp:218] Iteration 10152 (2.25546 iter/s, 5.32043s/12 iters), loss = 0.0934716
I0406 15:20:55.665519 23057 solver.cpp:237]     Train net output #0: loss = 0.0934716 (* 1 = 0.0934716 loss)
I0406 15:20:55.665530 23057 sgd_solver.cpp:105] Iteration 10152, lr = 0.005
I0406 15:21:01.000142 23057 solver.cpp:218] Iteration 10164 (2.24949 iter/s, 5.33455s/12 iters), loss = 0.112594
I0406 15:21:01.000198 23057 solver.cpp:237]     Train net output #0: loss = 0.112594 (* 1 = 0.112594 loss)
I0406 15:21:01.000206 23057 sgd_solver.cpp:105] Iteration 10164, lr = 0.005
I0406 15:21:06.247941 23057 solver.cpp:218] Iteration 10176 (2.28672 iter/s, 5.24768s/12 iters), loss = 0.214168
I0406 15:21:06.248085 23057 solver.cpp:237]     Train net output #0: loss = 0.214168 (* 1 = 0.214168 loss)
I0406 15:21:06.248095 23057 sgd_solver.cpp:105] Iteration 10176, lr = 0.005
I0406 15:21:11.514688 23057 solver.cpp:218] Iteration 10188 (2.27853 iter/s, 5.26655s/12 iters), loss = 0.263278
I0406 15:21:11.514729 23057 solver.cpp:237]     Train net output #0: loss = 0.263278 (* 1 = 0.263278 loss)
I0406 15:21:11.514735 23057 sgd_solver.cpp:105] Iteration 10188, lr = 0.005
I0406 15:21:15.991477 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel
I0406 15:21:18.988323 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate
I0406 15:21:21.287484 23057 solver.cpp:330] Iteration 10200, Testing net (#0)
I0406 15:21:21.287505 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:21:21.645676 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:21:25.574301 23057 solver.cpp:397]     Test net output #0: accuracy = 0.409314
I0406 15:21:25.574337 23057 solver.cpp:397]     Test net output #1: loss = 3.32619 (* 1 = 3.32619 loss)
I0406 15:21:25.709762 23057 solver.cpp:218] Iteration 10200 (0.845374 iter/s, 14.1949s/12 iters), loss = 0.160423
I0406 15:21:25.709831 23057 solver.cpp:237]     Train net output #0: loss = 0.160423 (* 1 = 0.160423 loss)
I0406 15:21:25.709841 23057 sgd_solver.cpp:105] Iteration 10200, lr = 0.005
I0406 15:21:30.166744 23057 solver.cpp:218] Iteration 10212 (2.69248 iter/s, 4.45687s/12 iters), loss = 0.101864
I0406 15:21:30.166795 23057 solver.cpp:237]     Train net output #0: loss = 0.101864 (* 1 = 0.101864 loss)
I0406 15:21:30.166802 23057 sgd_solver.cpp:105] Iteration 10212, lr = 0.005
I0406 15:21:31.661839 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:21:35.373142 23057 solver.cpp:218] Iteration 10224 (2.30491 iter/s, 5.20629s/12 iters), loss = 0.251469
I0406 15:21:35.373195 23057 solver.cpp:237]     Train net output #0: loss = 0.251469 (* 1 = 0.251469 loss)
I0406 15:21:35.373203 23057 sgd_solver.cpp:105] Iteration 10224, lr = 0.005
I0406 15:21:40.670912 23057 solver.cpp:218] Iteration 10236 (2.26515 iter/s, 5.29766s/12 iters), loss = 0.156812
I0406 15:21:40.671053 23057 solver.cpp:237]     Train net output #0: loss = 0.156812 (* 1 = 0.156812 loss)
I0406 15:21:40.671063 23057 sgd_solver.cpp:105] Iteration 10236, lr = 0.005
I0406 15:21:45.895875 23057 solver.cpp:218] Iteration 10248 (2.29675 iter/s, 5.22477s/12 iters), loss = 0.310593
I0406 15:21:45.895917 23057 solver.cpp:237]     Train net output #0: loss = 0.310593 (* 1 = 0.310593 loss)
I0406 15:21:45.895925 23057 sgd_solver.cpp:105] Iteration 10248, lr = 0.005
I0406 15:21:50.945482 23057 solver.cpp:218] Iteration 10260 (2.37647 iter/s, 5.0495s/12 iters), loss = 0.144819
I0406 15:21:50.945540 23057 solver.cpp:237]     Train net output #0: loss = 0.144819 (* 1 = 0.144819 loss)
I0406 15:21:50.945549 23057 sgd_solver.cpp:105] Iteration 10260, lr = 0.005
I0406 15:21:56.296088 23057 solver.cpp:218] Iteration 10272 (2.24278 iter/s, 5.35049s/12 iters), loss = 0.331825
I0406 15:21:56.296128 23057 solver.cpp:237]     Train net output #0: loss = 0.331825 (* 1 = 0.331825 loss)
I0406 15:21:56.296134 23057 sgd_solver.cpp:105] Iteration 10272, lr = 0.005
I0406 15:22:01.708566 23057 solver.cpp:218] Iteration 10284 (2.21714 iter/s, 5.41238s/12 iters), loss = 0.390704
I0406 15:22:01.708626 23057 solver.cpp:237]     Train net output #0: loss = 0.390704 (* 1 = 0.390704 loss)
I0406 15:22:01.708636 23057 sgd_solver.cpp:105] Iteration 10284, lr = 0.005
I0406 15:22:06.879482 23057 solver.cpp:218] Iteration 10296 (2.32073 iter/s, 5.17079s/12 iters), loss = 0.206438
I0406 15:22:06.879549 23057 solver.cpp:237]     Train net output #0: loss = 0.206438 (* 1 = 0.206438 loss)
I0406 15:22:06.879559 23057 sgd_solver.cpp:105] Iteration 10296, lr = 0.005
I0406 15:22:08.969615 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10302.caffemodel
I0406 15:22:12.027287 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10302.solverstate
I0406 15:22:14.336999 23057 solver.cpp:330] Iteration 10302, Testing net (#0)
I0406 15:22:14.337026 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:22:14.690603 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:22:18.785286 23057 solver.cpp:397]     Test net output #0: accuracy = 0.414216
I0406 15:22:18.785322 23057 solver.cpp:397]     Test net output #1: loss = 3.38843 (* 1 = 3.38843 loss)
I0406 15:22:20.697569 23057 solver.cpp:218] Iteration 10308 (0.868439 iter/s, 13.8179s/12 iters), loss = 0.161417
I0406 15:22:20.697614 23057 solver.cpp:237]     Train net output #0: loss = 0.161417 (* 1 = 0.161417 loss)
I0406 15:22:20.697621 23057 sgd_solver.cpp:105] Iteration 10308, lr = 0.005
I0406 15:22:24.604351 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:22:26.143663 23057 solver.cpp:218] Iteration 10320 (2.20346 iter/s, 5.44599s/12 iters), loss = 0.213693
I0406 15:22:26.143703 23057 solver.cpp:237]     Train net output #0: loss = 0.213693 (* 1 = 0.213693 loss)
I0406 15:22:26.143710 23057 sgd_solver.cpp:105] Iteration 10320, lr = 0.005
I0406 15:22:31.546973 23057 solver.cpp:218] Iteration 10332 (2.2209 iter/s, 5.4032s/12 iters), loss = 0.13332
I0406 15:22:31.547036 23057 solver.cpp:237]     Train net output #0: loss = 0.13332 (* 1 = 0.13332 loss)
I0406 15:22:31.547046 23057 sgd_solver.cpp:105] Iteration 10332, lr = 0.005
I0406 15:22:36.787125 23057 solver.cpp:218] Iteration 10344 (2.29006 iter/s, 5.24003s/12 iters), loss = 0.311093
I0406 15:22:36.787171 23057 solver.cpp:237]     Train net output #0: loss = 0.311093 (* 1 = 0.311093 loss)
I0406 15:22:36.787176 23057 sgd_solver.cpp:105] Iteration 10344, lr = 0.005
I0406 15:22:41.888015 23057 solver.cpp:218] Iteration 10356 (2.35258 iter/s, 5.10078s/12 iters), loss = 0.206556
I0406 15:22:41.888060 23057 solver.cpp:237]     Train net output #0: loss = 0.206556 (* 1 = 0.206556 loss)
I0406 15:22:41.888067 23057 sgd_solver.cpp:105] Iteration 10356, lr = 0.005
I0406 15:22:47.172544 23057 solver.cpp:218] Iteration 10368 (2.27083 iter/s, 5.28442s/12 iters), loss = 0.183002
I0406 15:22:47.172639 23057 solver.cpp:237]     Train net output #0: loss = 0.183002 (* 1 = 0.183002 loss)
I0406 15:22:47.172646 23057 sgd_solver.cpp:105] Iteration 10368, lr = 0.005
I0406 15:22:52.472612 23057 solver.cpp:218] Iteration 10380 (2.26419 iter/s, 5.29991s/12 iters), loss = 0.216448
I0406 15:22:52.472657 23057 solver.cpp:237]     Train net output #0: loss = 0.216448 (* 1 = 0.216448 loss)
I0406 15:22:52.472663 23057 sgd_solver.cpp:105] Iteration 10380, lr = 0.005
I0406 15:22:57.769124 23057 solver.cpp:218] Iteration 10392 (2.26569 iter/s, 5.2964s/12 iters), loss = 0.201586
I0406 15:22:57.769178 23057 solver.cpp:237]     Train net output #0: loss = 0.201586 (* 1 = 0.201586 loss)
I0406 15:22:57.769186 23057 sgd_solver.cpp:105] Iteration 10392, lr = 0.005
I0406 15:23:02.494606 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10404.caffemodel
I0406 15:23:05.559139 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10404.solverstate
I0406 15:23:07.858317 23057 solver.cpp:330] Iteration 10404, Testing net (#0)
I0406 15:23:07.858335 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:23:08.132087 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:23:08.654237 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:23:12.258134 23057 solver.cpp:397]     Test net output #0: accuracy = 0.412377
I0406 15:23:12.258168 23057 solver.cpp:397]     Test net output #1: loss = 3.24483 (* 1 = 3.24483 loss)
I0406 15:23:12.395741 23057 solver.cpp:218] Iteration 10404 (0.820432 iter/s, 14.6264s/12 iters), loss = 0.354647
I0406 15:23:12.395785 23057 solver.cpp:237]     Train net output #0: loss = 0.354647 (* 1 = 0.354647 loss)
I0406 15:23:12.395792 23057 sgd_solver.cpp:105] Iteration 10404, lr = 0.005
I0406 15:23:16.703207 23057 solver.cpp:218] Iteration 10416 (2.78593 iter/s, 4.30736s/12 iters), loss = 0.198037
I0406 15:23:16.703264 23057 solver.cpp:237]     Train net output #0: loss = 0.198037 (* 1 = 0.198037 loss)
I0406 15:23:16.703274 23057 sgd_solver.cpp:105] Iteration 10416, lr = 0.005
I0406 15:23:17.626161 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:23:21.890401 23057 solver.cpp:218] Iteration 10428 (2.31344 iter/s, 5.18707s/12 iters), loss = 0.436195
I0406 15:23:21.890466 23057 solver.cpp:237]     Train net output #0: loss = 0.436195 (* 1 = 0.436195 loss)
I0406 15:23:21.890475 23057 sgd_solver.cpp:105] Iteration 10428, lr = 0.005
I0406 15:23:27.131824 23057 solver.cpp:218] Iteration 10440 (2.28951 iter/s, 5.2413s/12 iters), loss = 0.248309
I0406 15:23:27.131876 23057 solver.cpp:237]     Train net output #0: loss = 0.248309 (* 1 = 0.248309 loss)
I0406 15:23:27.131886 23057 sgd_solver.cpp:105] Iteration 10440, lr = 0.005
I0406 15:23:32.287287 23057 solver.cpp:218] Iteration 10452 (2.32768 iter/s, 5.15535s/12 iters), loss = 0.079527
I0406 15:23:32.287333 23057 solver.cpp:237]     Train net output #0: loss = 0.079527 (* 1 = 0.079527 loss)
I0406 15:23:32.287338 23057 sgd_solver.cpp:105] Iteration 10452, lr = 0.005
I0406 15:23:37.712075 23057 solver.cpp:218] Iteration 10464 (2.21211 iter/s, 5.42468s/12 iters), loss = 0.114318
I0406 15:23:37.712131 23057 solver.cpp:237]     Train net output #0: loss = 0.114318 (* 1 = 0.114318 loss)
I0406 15:23:37.712139 23057 sgd_solver.cpp:105] Iteration 10464, lr = 0.005
I0406 15:23:43.039358 23057 solver.cpp:218] Iteration 10476 (2.2526 iter/s, 5.32717s/12 iters), loss = 0.252621
I0406 15:23:43.039402 23057 solver.cpp:237]     Train net output #0: loss = 0.252621 (* 1 = 0.252621 loss)
I0406 15:23:43.039409 23057 sgd_solver.cpp:105] Iteration 10476, lr = 0.005
I0406 15:23:48.378273 23057 solver.cpp:218] Iteration 10488 (2.24769 iter/s, 5.33881s/12 iters), loss = 0.106045
I0406 15:23:48.378376 23057 solver.cpp:237]     Train net output #0: loss = 0.106045 (* 1 = 0.106045 loss)
I0406 15:23:48.378382 23057 sgd_solver.cpp:105] Iteration 10488, lr = 0.005
I0406 15:23:53.829828 23057 solver.cpp:218] Iteration 10500 (2.20127 iter/s, 5.4514s/12 iters), loss = 0.113749
I0406 15:23:53.829866 23057 solver.cpp:237]     Train net output #0: loss = 0.113749 (* 1 = 0.113749 loss)
I0406 15:23:53.829874 23057 sgd_solver.cpp:105] Iteration 10500, lr = 0.005
I0406 15:23:56.092144 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10506.caffemodel
I0406 15:23:59.041115 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10506.solverstate
I0406 15:24:01.370592 23057 solver.cpp:330] Iteration 10506, Testing net (#0)
I0406 15:24:01.370615 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:24:01.679536 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:24:05.750439 23057 solver.cpp:397]     Test net output #0: accuracy = 0.42402
I0406 15:24:05.750469 23057 solver.cpp:397]     Test net output #1: loss = 3.27044 (* 1 = 3.27044 loss)
I0406 15:24:07.787914 23057 solver.cpp:218] Iteration 10512 (0.859727 iter/s, 13.9579s/12 iters), loss = 0.212948
I0406 15:24:07.787955 23057 solver.cpp:237]     Train net output #0: loss = 0.212948 (* 1 = 0.212948 loss)
I0406 15:24:07.787961 23057 sgd_solver.cpp:105] Iteration 10512, lr = 0.005
I0406 15:24:11.001166 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:24:13.015393 23057 solver.cpp:218] Iteration 10524 (2.29561 iter/s, 5.22738s/12 iters), loss = 0.0991518
I0406 15:24:13.015439 23057 solver.cpp:237]     Train net output #0: loss = 0.0991518 (* 1 = 0.0991518 loss)
I0406 15:24:13.015444 23057 sgd_solver.cpp:105] Iteration 10524, lr = 0.005
I0406 15:24:18.307497 23057 solver.cpp:218] Iteration 10536 (2.26758 iter/s, 5.29199s/12 iters), loss = 0.130892
I0406 15:24:18.307560 23057 solver.cpp:237]     Train net output #0: loss = 0.130892 (* 1 = 0.130892 loss)
I0406 15:24:18.307570 23057 sgd_solver.cpp:105] Iteration 10536, lr = 0.005
I0406 15:24:23.622145 23057 solver.cpp:218] Iteration 10548 (2.25796 iter/s, 5.31453s/12 iters), loss = 0.148812
I0406 15:24:23.622270 23057 solver.cpp:237]     Train net output #0: loss = 0.148812 (* 1 = 0.148812 loss)
I0406 15:24:23.622277 23057 sgd_solver.cpp:105] Iteration 10548, lr = 0.005
I0406 15:24:28.941103 23057 solver.cpp:218] Iteration 10560 (2.25616 iter/s, 5.31878s/12 iters), loss = 0.151639
I0406 15:24:28.941144 23057 solver.cpp:237]     Train net output #0: loss = 0.151639 (* 1 = 0.151639 loss)
I0406 15:24:28.941150 23057 sgd_solver.cpp:105] Iteration 10560, lr = 0.005
I0406 15:24:34.275467 23057 solver.cpp:218] Iteration 10572 (2.24961 iter/s, 5.33427s/12 iters), loss = 0.170918
I0406 15:24:34.275512 23057 solver.cpp:237]     Train net output #0: loss = 0.170918 (* 1 = 0.170918 loss)
I0406 15:24:34.275519 23057 sgd_solver.cpp:105] Iteration 10572, lr = 0.005
I0406 15:24:39.540984 23057 solver.cpp:218] Iteration 10584 (2.27903 iter/s, 5.2654s/12 iters), loss = 0.227198
I0406 15:24:39.541049 23057 solver.cpp:237]     Train net output #0: loss = 0.227198 (* 1 = 0.227198 loss)
I0406 15:24:39.541059 23057 sgd_solver.cpp:105] Iteration 10584, lr = 0.005
I0406 15:24:44.829025 23057 solver.cpp:218] Iteration 10596 (2.26932 iter/s, 5.28793s/12 iters), loss = 0.114064
I0406 15:24:44.829064 23057 solver.cpp:237]     Train net output #0: loss = 0.114064 (* 1 = 0.114064 loss)
I0406 15:24:44.829071 23057 sgd_solver.cpp:105] Iteration 10596, lr = 0.005
I0406 15:24:49.490140 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10608.caffemodel
I0406 15:24:52.497048 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10608.solverstate
I0406 15:24:54.795708 23057 solver.cpp:330] Iteration 10608, Testing net (#0)
I0406 15:24:54.795801 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:24:55.000699 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:24:59.194972 23057 solver.cpp:397]     Test net output #0: accuracy = 0.423407
I0406 15:24:59.195000 23057 solver.cpp:397]     Test net output #1: loss = 3.2687 (* 1 = 3.2687 loss)
I0406 15:24:59.326324 23057 solver.cpp:218] Iteration 10608 (0.82775 iter/s, 14.4971s/12 iters), loss = 0.0757048
I0406 15:24:59.326388 23057 solver.cpp:237]     Train net output #0: loss = 0.0757048 (* 1 = 0.0757048 loss)
I0406 15:24:59.326395 23057 sgd_solver.cpp:105] Iteration 10608, lr = 0.005
I0406 15:25:03.615762 23057 solver.cpp:218] Iteration 10620 (2.79765 iter/s, 4.28932s/12 iters), loss = 0.0941414
I0406 15:25:03.615803 23057 solver.cpp:237]     Train net output #0: loss = 0.0941414 (* 1 = 0.0941414 loss)
I0406 15:25:03.615808 23057 sgd_solver.cpp:105] Iteration 10620, lr = 0.005
I0406 15:25:03.737764 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:25:08.711418 23057 solver.cpp:218] Iteration 10632 (2.35499 iter/s, 5.09556s/12 iters), loss = 0.201148
I0406 15:25:08.711465 23057 solver.cpp:237]     Train net output #0: loss = 0.201148 (* 1 = 0.201148 loss)
I0406 15:25:08.711474 23057 sgd_solver.cpp:105] Iteration 10632, lr = 0.005
I0406 15:25:13.822540 23057 solver.cpp:218] Iteration 10644 (2.34787 iter/s, 5.11102s/12 iters), loss = 0.232634
I0406 15:25:13.822584 23057 solver.cpp:237]     Train net output #0: loss = 0.232634 (* 1 = 0.232634 loss)
I0406 15:25:13.822592 23057 sgd_solver.cpp:105] Iteration 10644, lr = 0.005
I0406 15:25:19.116681 23057 solver.cpp:218] Iteration 10656 (2.2667 iter/s, 5.29404s/12 iters), loss = 0.161908
I0406 15:25:19.116721 23057 solver.cpp:237]     Train net output #0: loss = 0.161908 (* 1 = 0.161908 loss)
I0406 15:25:19.116727 23057 sgd_solver.cpp:105] Iteration 10656, lr = 0.005
I0406 15:25:24.294483 23057 solver.cpp:218] Iteration 10668 (2.31763 iter/s, 5.17771s/12 iters), loss = 0.210634
I0406 15:25:24.294521 23057 solver.cpp:237]     Train net output #0: loss = 0.210634 (* 1 = 0.210634 loss)
I0406 15:25:24.294526 23057 sgd_solver.cpp:105] Iteration 10668, lr = 0.005
I0406 15:25:29.703374 23057 solver.cpp:218] Iteration 10680 (2.21861 iter/s, 5.40879s/12 iters), loss = 0.0435928
I0406 15:25:29.703536 23057 solver.cpp:237]     Train net output #0: loss = 0.0435928 (* 1 = 0.0435928 loss)
I0406 15:25:29.703547 23057 sgd_solver.cpp:105] Iteration 10680, lr = 0.005
I0406 15:25:34.846563 23057 solver.cpp:218] Iteration 10692 (2.33328 iter/s, 5.14297s/12 iters), loss = 0.0876691
I0406 15:25:34.846613 23057 solver.cpp:237]     Train net output #0: loss = 0.0876691 (* 1 = 0.0876691 loss)
I0406 15:25:34.846619 23057 sgd_solver.cpp:105] Iteration 10692, lr = 0.005
I0406 15:25:39.976413 23057 solver.cpp:218] Iteration 10704 (2.3393 iter/s, 5.12974s/12 iters), loss = 0.19101
I0406 15:25:39.976461 23057 solver.cpp:237]     Train net output #0: loss = 0.19101 (* 1 = 0.19101 loss)
I0406 15:25:39.976467 23057 sgd_solver.cpp:105] Iteration 10704, lr = 0.005
I0406 15:25:42.146333 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10710.caffemodel
I0406 15:25:45.158769 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10710.solverstate
I0406 15:25:47.831339 23057 solver.cpp:330] Iteration 10710, Testing net (#0)
I0406 15:25:47.831362 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:25:48.013756 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:25:52.241461 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 15:25:52.241500 23057 solver.cpp:397]     Test net output #1: loss = 3.18187 (* 1 = 3.18187 loss)
I0406 15:25:54.317195 23057 solver.cpp:218] Iteration 10716 (0.836785 iter/s, 14.3406s/12 iters), loss = 0.199818
I0406 15:25:54.317242 23057 solver.cpp:237]     Train net output #0: loss = 0.199818 (* 1 = 0.199818 loss)
I0406 15:25:54.317250 23057 sgd_solver.cpp:105] Iteration 10716, lr = 0.005
I0406 15:25:56.779343 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:25:59.669028 23057 solver.cpp:218] Iteration 10728 (2.24227 iter/s, 5.35173s/12 iters), loss = 0.160832
I0406 15:25:59.669078 23057 solver.cpp:237]     Train net output #0: loss = 0.160832 (* 1 = 0.160832 loss)
I0406 15:25:59.669087 23057 sgd_solver.cpp:105] Iteration 10728, lr = 0.005
I0406 15:26:05.104849 23057 solver.cpp:218] Iteration 10740 (2.20762 iter/s, 5.43571s/12 iters), loss = 0.15282
I0406 15:26:05.104933 23057 solver.cpp:237]     Train net output #0: loss = 0.15282 (* 1 = 0.15282 loss)
I0406 15:26:05.104939 23057 sgd_solver.cpp:105] Iteration 10740, lr = 0.005
I0406 15:26:10.338841 23057 solver.cpp:218] Iteration 10752 (2.29277 iter/s, 5.23385s/12 iters), loss = 0.125619
I0406 15:26:10.338887 23057 solver.cpp:237]     Train net output #0: loss = 0.125619 (* 1 = 0.125619 loss)
I0406 15:26:10.338893 23057 sgd_solver.cpp:105] Iteration 10752, lr = 0.005
I0406 15:26:15.609903 23057 solver.cpp:218] Iteration 10764 (2.27663 iter/s, 5.27095s/12 iters), loss = 0.129475
I0406 15:26:15.609951 23057 solver.cpp:237]     Train net output #0: loss = 0.129475 (* 1 = 0.129475 loss)
I0406 15:26:15.609956 23057 sgd_solver.cpp:105] Iteration 10764, lr = 0.005
I0406 15:26:20.809406 23057 solver.cpp:218] Iteration 10776 (2.30796 iter/s, 5.19939s/12 iters), loss = 0.198976
I0406 15:26:20.809451 23057 solver.cpp:237]     Train net output #0: loss = 0.198977 (* 1 = 0.198977 loss)
I0406 15:26:20.809458 23057 sgd_solver.cpp:105] Iteration 10776, lr = 0.005
I0406 15:26:26.069777 23057 solver.cpp:218] Iteration 10788 (2.28125 iter/s, 5.26027s/12 iters), loss = 0.167215
I0406 15:26:26.069821 23057 solver.cpp:237]     Train net output #0: loss = 0.167215 (* 1 = 0.167215 loss)
I0406 15:26:26.069828 23057 sgd_solver.cpp:105] Iteration 10788, lr = 0.005
I0406 15:26:31.247591 23057 solver.cpp:218] Iteration 10800 (2.31763 iter/s, 5.17771s/12 iters), loss = 0.241546
I0406 15:26:31.247634 23057 solver.cpp:237]     Train net output #0: loss = 0.241546 (* 1 = 0.241546 loss)
I0406 15:26:31.247640 23057 sgd_solver.cpp:105] Iteration 10800, lr = 0.005
I0406 15:26:35.740753 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10812.caffemodel
I0406 15:26:38.538295 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10812.solverstate
I0406 15:26:40.831581 23057 solver.cpp:330] Iteration 10812, Testing net (#0)
I0406 15:26:40.831599 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:26:40.966529 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:26:45.394356 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 15:26:45.394384 23057 solver.cpp:397]     Test net output #1: loss = 3.23956 (* 1 = 3.23956 loss)
I0406 15:26:45.529161 23057 solver.cpp:218] Iteration 10812 (0.840254 iter/s, 14.2814s/12 iters), loss = 0.105617
I0406 15:26:45.529215 23057 solver.cpp:237]     Train net output #0: loss = 0.105617 (* 1 = 0.105617 loss)
I0406 15:26:45.529222 23057 sgd_solver.cpp:105] Iteration 10812, lr = 0.005
I0406 15:26:49.313030 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:26:49.991684 23057 solver.cpp:218] Iteration 10824 (2.68913 iter/s, 4.46241s/12 iters), loss = 0.146181
I0406 15:26:49.991734 23057 solver.cpp:237]     Train net output #0: loss = 0.146181 (* 1 = 0.146181 loss)
I0406 15:26:49.991744 23057 sgd_solver.cpp:105] Iteration 10824, lr = 0.005
I0406 15:26:55.339123 23057 solver.cpp:218] Iteration 10836 (2.24411 iter/s, 5.34733s/12 iters), loss = 0.319271
I0406 15:26:55.339179 23057 solver.cpp:237]     Train net output #0: loss = 0.319271 (* 1 = 0.319271 loss)
I0406 15:26:55.339187 23057 sgd_solver.cpp:105] Iteration 10836, lr = 0.005
I0406 15:27:00.681502 23057 solver.cpp:218] Iteration 10848 (2.24624 iter/s, 5.34226s/12 iters), loss = 0.0890722
I0406 15:27:00.681563 23057 solver.cpp:237]     Train net output #0: loss = 0.0890722 (* 1 = 0.0890722 loss)
I0406 15:27:00.681572 23057 sgd_solver.cpp:105] Iteration 10848, lr = 0.005
I0406 15:27:06.032685 23057 solver.cpp:218] Iteration 10860 (2.24254 iter/s, 5.35107s/12 iters), loss = 0.0370144
I0406 15:27:06.032773 23057 solver.cpp:237]     Train net output #0: loss = 0.0370144 (* 1 = 0.0370144 loss)
I0406 15:27:06.032779 23057 sgd_solver.cpp:105] Iteration 10860, lr = 0.005
I0406 15:27:10.943768 23057 solver.cpp:218] Iteration 10872 (2.44352 iter/s, 4.91094s/12 iters), loss = 0.0911308
I0406 15:27:10.943807 23057 solver.cpp:237]     Train net output #0: loss = 0.0911309 (* 1 = 0.0911309 loss)
I0406 15:27:10.943814 23057 sgd_solver.cpp:105] Iteration 10872, lr = 0.005
I0406 15:27:16.228273 23057 solver.cpp:218] Iteration 10884 (2.27083 iter/s, 5.2844s/12 iters), loss = 0.271049
I0406 15:27:16.228318 23057 solver.cpp:237]     Train net output #0: loss = 0.271049 (* 1 = 0.271049 loss)
I0406 15:27:16.228324 23057 sgd_solver.cpp:105] Iteration 10884, lr = 0.005
I0406 15:27:21.447448 23057 solver.cpp:218] Iteration 10896 (2.29926 iter/s, 5.21907s/12 iters), loss = 0.092435
I0406 15:27:21.447487 23057 solver.cpp:237]     Train net output #0: loss = 0.092435 (* 1 = 0.092435 loss)
I0406 15:27:21.447492 23057 sgd_solver.cpp:105] Iteration 10896, lr = 0.005
I0406 15:27:26.569514 23057 solver.cpp:218] Iteration 10908 (2.34285 iter/s, 5.12197s/12 iters), loss = 0.133395
I0406 15:27:26.569561 23057 solver.cpp:237]     Train net output #0: loss = 0.133395 (* 1 = 0.133395 loss)
I0406 15:27:26.569567 23057 sgd_solver.cpp:105] Iteration 10908, lr = 0.005
I0406 15:27:28.576711 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10914.caffemodel
I0406 15:27:31.611079 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10914.solverstate
I0406 15:27:33.926371 23057 solver.cpp:330] Iteration 10914, Testing net (#0)
I0406 15:27:33.926390 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:27:34.033875 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:27:38.339140 23057 solver.cpp:397]     Test net output #0: accuracy = 0.411152
I0406 15:27:38.339267 23057 solver.cpp:397]     Test net output #1: loss = 3.39357 (* 1 = 3.39357 loss)
I0406 15:27:40.244048 23057 solver.cpp:218] Iteration 10920 (0.877554 iter/s, 13.6744s/12 iters), loss = 0.0847791
I0406 15:27:40.244091 23057 solver.cpp:237]     Train net output #0: loss = 0.0847792 (* 1 = 0.0847792 loss)
I0406 15:27:40.244097 23057 sgd_solver.cpp:105] Iteration 10920, lr = 0.005
I0406 15:27:41.757952 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:27:45.603520 23057 solver.cpp:218] Iteration 10932 (2.23907 iter/s, 5.35936s/12 iters), loss = 0.153851
I0406 15:27:45.603571 23057 solver.cpp:237]     Train net output #0: loss = 0.153851 (* 1 = 0.153851 loss)
I0406 15:27:45.603579 23057 sgd_solver.cpp:105] Iteration 10932, lr = 0.005
I0406 15:27:50.896965 23057 solver.cpp:218] Iteration 10944 (2.267 iter/s, 5.29334s/12 iters), loss = 0.109553
I0406 15:27:50.897025 23057 solver.cpp:237]     Train net output #0: loss = 0.109553 (* 1 = 0.109553 loss)
I0406 15:27:50.897035 23057 sgd_solver.cpp:105] Iteration 10944, lr = 0.005
I0406 15:27:56.103188 23057 solver.cpp:218] Iteration 10956 (2.30504 iter/s, 5.20598s/12 iters), loss = 0.19183
I0406 15:27:56.103235 23057 solver.cpp:237]     Train net output #0: loss = 0.19183 (* 1 = 0.19183 loss)
I0406 15:27:56.103241 23057 sgd_solver.cpp:105] Iteration 10956, lr = 0.005
I0406 15:28:01.455222 23057 solver.cpp:218] Iteration 10968 (2.24218 iter/s, 5.35193s/12 iters), loss = 0.125698
I0406 15:28:01.455260 23057 solver.cpp:237]     Train net output #0: loss = 0.125698 (* 1 = 0.125698 loss)
I0406 15:28:01.455266 23057 sgd_solver.cpp:105] Iteration 10968, lr = 0.005
I0406 15:28:06.844048 23057 solver.cpp:218] Iteration 10980 (2.22687 iter/s, 5.38872s/12 iters), loss = 0.208437
I0406 15:28:06.844092 23057 solver.cpp:237]     Train net output #0: loss = 0.208437 (* 1 = 0.208437 loss)
I0406 15:28:06.844099 23057 sgd_solver.cpp:105] Iteration 10980, lr = 0.005
I0406 15:28:12.006582 23057 solver.cpp:218] Iteration 10992 (2.32448 iter/s, 5.16243s/12 iters), loss = 0.274672
I0406 15:28:12.006693 23057 solver.cpp:237]     Train net output #0: loss = 0.274672 (* 1 = 0.274672 loss)
I0406 15:28:12.006700 23057 sgd_solver.cpp:105] Iteration 10992, lr = 0.005
I0406 15:28:17.375377 23057 solver.cpp:218] Iteration 11004 (2.23521 iter/s, 5.36863s/12 iters), loss = 0.184548
I0406 15:28:17.375425 23057 solver.cpp:237]     Train net output #0: loss = 0.184548 (* 1 = 0.184548 loss)
I0406 15:28:17.375433 23057 sgd_solver.cpp:105] Iteration 11004, lr = 0.005
I0406 15:28:22.085933 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11016.caffemodel
I0406 15:28:25.153323 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11016.solverstate
I0406 15:28:27.449681 23057 solver.cpp:330] Iteration 11016, Testing net (#0)
I0406 15:28:27.449699 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:28:27.501194 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:28:31.896051 23057 solver.cpp:397]     Test net output #0: accuracy = 0.426471
I0406 15:28:31.896086 23057 solver.cpp:397]     Test net output #1: loss = 3.32509 (* 1 = 3.32509 loss)
I0406 15:28:32.034631 23057 solver.cpp:218] Iteration 11016 (0.818606 iter/s, 14.6591s/12 iters), loss = 0.201961
I0406 15:28:32.034673 23057 solver.cpp:237]     Train net output #0: loss = 0.201961 (* 1 = 0.201961 loss)
I0406 15:28:32.034679 23057 sgd_solver.cpp:105] Iteration 11016, lr = 0.005
I0406 15:28:32.530576 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:28:34.907634 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:28:36.255206 23057 solver.cpp:218] Iteration 11028 (2.84328 iter/s, 4.22049s/12 iters), loss = 0.0850033
I0406 15:28:36.255247 23057 solver.cpp:237]     Train net output #0: loss = 0.0850034 (* 1 = 0.0850034 loss)
I0406 15:28:36.255254 23057 sgd_solver.cpp:105] Iteration 11028, lr = 0.005
I0406 15:28:41.693289 23057 solver.cpp:218] Iteration 11040 (2.2067 iter/s, 5.43798s/12 iters), loss = 0.223514
I0406 15:28:41.693344 23057 solver.cpp:237]     Train net output #0: loss = 0.223514 (* 1 = 0.223514 loss)
I0406 15:28:41.693354 23057 sgd_solver.cpp:105] Iteration 11040, lr = 0.005
I0406 15:28:46.827031 23057 solver.cpp:218] Iteration 11052 (2.33752 iter/s, 5.13364s/12 iters), loss = 0.101643
I0406 15:28:46.827157 23057 solver.cpp:237]     Train net output #0: loss = 0.101643 (* 1 = 0.101643 loss)
I0406 15:28:46.827167 23057 sgd_solver.cpp:105] Iteration 11052, lr = 0.005
I0406 15:28:51.925429 23057 solver.cpp:218] Iteration 11064 (2.35376 iter/s, 5.09822s/12 iters), loss = 0.236592
I0406 15:28:51.925472 23057 solver.cpp:237]     Train net output #0: loss = 0.236592 (* 1 = 0.236592 loss)
I0406 15:28:51.925478 23057 sgd_solver.cpp:105] Iteration 11064, lr = 0.005
I0406 15:28:57.127689 23057 solver.cpp:218] Iteration 11076 (2.30673 iter/s, 5.20216s/12 iters), loss = 0.0838088
I0406 15:28:57.127729 23057 solver.cpp:237]     Train net output #0: loss = 0.083809 (* 1 = 0.083809 loss)
I0406 15:28:57.127735 23057 sgd_solver.cpp:105] Iteration 11076, lr = 0.005
I0406 15:29:02.449199 23057 solver.cpp:218] Iteration 11088 (2.25504 iter/s, 5.32141s/12 iters), loss = 0.182741
I0406 15:29:02.449244 23057 solver.cpp:237]     Train net output #0: loss = 0.182741 (* 1 = 0.182741 loss)
I0406 15:29:02.449249 23057 sgd_solver.cpp:105] Iteration 11088, lr = 0.005
I0406 15:29:05.941975 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:29:07.623524 23057 solver.cpp:218] Iteration 11100 (2.31919 iter/s, 5.17422s/12 iters), loss = 0.142656
I0406 15:29:07.623571 23057 solver.cpp:237]     Train net output #0: loss = 0.142656 (* 1 = 0.142656 loss)
I0406 15:29:07.623579 23057 sgd_solver.cpp:105] Iteration 11100, lr = 0.005
I0406 15:29:12.501472 23057 solver.cpp:218] Iteration 11112 (2.4601 iter/s, 4.87785s/12 iters), loss = 0.106205
I0406 15:29:12.501510 23057 solver.cpp:237]     Train net output #0: loss = 0.106205 (* 1 = 0.106205 loss)
I0406 15:29:12.501516 23057 sgd_solver.cpp:105] Iteration 11112, lr = 0.005
I0406 15:29:14.640221 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11118.caffemodel
I0406 15:29:17.662642 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11118.solverstate
I0406 15:29:19.979979 23057 solver.cpp:330] Iteration 11118, Testing net (#0)
I0406 15:29:19.980003 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:29:24.512570 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425245
I0406 15:29:24.512601 23057 solver.cpp:397]     Test net output #1: loss = 3.44236 (* 1 = 3.44236 loss)
I0406 15:29:24.969933 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:29:26.346305 23057 solver.cpp:218] Iteration 11124 (0.86676 iter/s, 13.8447s/12 iters), loss = 0.105589
I0406 15:29:26.346364 23057 solver.cpp:237]     Train net output #0: loss = 0.105589 (* 1 = 0.105589 loss)
I0406 15:29:26.346372 23057 sgd_solver.cpp:105] Iteration 11124, lr = 0.005
I0406 15:29:27.303284 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:29:31.701894 23057 solver.cpp:218] Iteration 11136 (2.2407 iter/s, 5.35548s/12 iters), loss = 0.0361734
I0406 15:29:31.701933 23057 solver.cpp:237]     Train net output #0: loss = 0.0361735 (* 1 = 0.0361735 loss)
I0406 15:29:31.701939 23057 sgd_solver.cpp:105] Iteration 11136, lr = 0.005
I0406 15:29:36.717550 23057 solver.cpp:218] Iteration 11148 (2.39255 iter/s, 5.01556s/12 iters), loss = 0.168902
I0406 15:29:36.717588 23057 solver.cpp:237]     Train net output #0: loss = 0.168903 (* 1 = 0.168903 loss)
I0406 15:29:36.717594 23057 sgd_solver.cpp:105] Iteration 11148, lr = 0.005
I0406 15:29:41.708233 23057 solver.cpp:218] Iteration 11160 (2.40453 iter/s, 4.99058s/12 iters), loss = 0.129883
I0406 15:29:41.708282 23057 solver.cpp:237]     Train net output #0: loss = 0.129883 (* 1 = 0.129883 loss)
I0406 15:29:41.708290 23057 sgd_solver.cpp:105] Iteration 11160, lr = 0.005
I0406 15:29:47.140429 23057 solver.cpp:218] Iteration 11172 (2.2091 iter/s, 5.43209s/12 iters), loss = 0.207546
I0406 15:29:47.140470 23057 solver.cpp:237]     Train net output #0: loss = 0.207546 (* 1 = 0.207546 loss)
I0406 15:29:47.140475 23057 sgd_solver.cpp:105] Iteration 11172, lr = 0.005
I0406 15:29:52.416296 23057 solver.cpp:218] Iteration 11184 (2.27455 iter/s, 5.27577s/12 iters), loss = 0.180934
I0406 15:29:52.416440 23057 solver.cpp:237]     Train net output #0: loss = 0.180934 (* 1 = 0.180934 loss)
I0406 15:29:52.416450 23057 sgd_solver.cpp:105] Iteration 11184, lr = 0.005
I0406 15:29:57.504546 23057 solver.cpp:218] Iteration 11196 (2.35846 iter/s, 5.08806s/12 iters), loss = 0.175907
I0406 15:29:57.504585 23057 solver.cpp:237]     Train net output #0: loss = 0.175907 (* 1 = 0.175907 loss)
I0406 15:29:57.504591 23057 sgd_solver.cpp:105] Iteration 11196, lr = 0.005
I0406 15:30:02.770206 23057 solver.cpp:218] Iteration 11208 (2.27896 iter/s, 5.26556s/12 iters), loss = 0.15348
I0406 15:30:02.770248 23057 solver.cpp:237]     Train net output #0: loss = 0.15348 (* 1 = 0.15348 loss)
I0406 15:30:02.770253 23057 sgd_solver.cpp:105] Iteration 11208, lr = 0.005
I0406 15:30:07.347797 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11220.caffemodel
I0406 15:30:10.409546 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11220.solverstate
I0406 15:30:14.443615 23057 solver.cpp:330] Iteration 11220, Testing net (#0)
I0406 15:30:14.443636 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:30:18.752130 23057 solver.cpp:397]     Test net output #0: accuracy = 0.403799
I0406 15:30:18.752164 23057 solver.cpp:397]     Test net output #1: loss = 3.43525 (* 1 = 3.43525 loss)
I0406 15:30:18.893079 23057 solver.cpp:218] Iteration 11220 (0.744293 iter/s, 16.1227s/12 iters), loss = 0.0950768
I0406 15:30:18.894755 23057 solver.cpp:237]     Train net output #0: loss = 0.0950769 (* 1 = 0.0950769 loss)
I0406 15:30:18.894767 23057 sgd_solver.cpp:105] Iteration 11220, lr = 0.005
I0406 15:30:19.056445 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:30:21.123103 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:30:23.168177 23057 solver.cpp:218] Iteration 11232 (2.80808 iter/s, 4.27338s/12 iters), loss = 0.147359
I0406 15:30:23.168298 23057 solver.cpp:237]     Train net output #0: loss = 0.147359 (* 1 = 0.147359 loss)
I0406 15:30:23.168308 23057 sgd_solver.cpp:105] Iteration 11232, lr = 0.005
I0406 15:30:28.480093 23057 solver.cpp:218] Iteration 11244 (2.25914 iter/s, 5.31175s/12 iters), loss = 0.174295
I0406 15:30:28.480130 23057 solver.cpp:237]     Train net output #0: loss = 0.174295 (* 1 = 0.174295 loss)
I0406 15:30:28.480136 23057 sgd_solver.cpp:105] Iteration 11244, lr = 0.005
I0406 15:30:33.840512 23057 solver.cpp:218] Iteration 11256 (2.23867 iter/s, 5.36032s/12 iters), loss = 0.23398
I0406 15:30:33.840556 23057 solver.cpp:237]     Train net output #0: loss = 0.23398 (* 1 = 0.23398 loss)
I0406 15:30:33.840564 23057 sgd_solver.cpp:105] Iteration 11256, lr = 0.005
I0406 15:30:39.138842 23057 solver.cpp:218] Iteration 11268 (2.26491 iter/s, 5.29822s/12 iters), loss = 0.109241
I0406 15:30:39.138892 23057 solver.cpp:237]     Train net output #0: loss = 0.109241 (* 1 = 0.109241 loss)
I0406 15:30:39.138897 23057 sgd_solver.cpp:105] Iteration 11268, lr = 0.005
I0406 15:30:44.148342 23057 solver.cpp:218] Iteration 11280 (2.3955 iter/s, 5.00939s/12 iters), loss = 0.198181
I0406 15:30:44.148398 23057 solver.cpp:237]     Train net output #0: loss = 0.198181 (* 1 = 0.198181 loss)
I0406 15:30:44.148407 23057 sgd_solver.cpp:105] Iteration 11280, lr = 0.005
I0406 15:30:49.451161 23057 solver.cpp:218] Iteration 11292 (2.263 iter/s, 5.3027s/12 iters), loss = 0.0762653
I0406 15:30:49.451212 23057 solver.cpp:237]     Train net output #0: loss = 0.0762654 (* 1 = 0.0762654 loss)
I0406 15:30:49.451221 23057 sgd_solver.cpp:105] Iteration 11292, lr = 0.005
I0406 15:30:54.846405 23057 solver.cpp:218] Iteration 11304 (2.22423 iter/s, 5.39514s/12 iters), loss = 0.213099
I0406 15:30:54.846545 23057 solver.cpp:237]     Train net output #0: loss = 0.213099 (* 1 = 0.213099 loss)
I0406 15:30:54.846552 23057 sgd_solver.cpp:105] Iteration 11304, lr = 0.005
I0406 15:31:00.043092 23057 solver.cpp:218] Iteration 11316 (2.30925 iter/s, 5.19649s/12 iters), loss = 0.151121
I0406 15:31:00.043134 23057 solver.cpp:237]     Train net output #0: loss = 0.151121 (* 1 = 0.151121 loss)
I0406 15:31:00.043141 23057 sgd_solver.cpp:105] Iteration 11316, lr = 0.005
I0406 15:31:02.316221 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11322.caffemodel
I0406 15:31:05.915268 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11322.solverstate
I0406 15:31:08.279036 23057 solver.cpp:330] Iteration 11322, Testing net (#0)
I0406 15:31:08.279057 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:31:12.668910 23057 solver.cpp:397]     Test net output #0: accuracy = 0.438726
I0406 15:31:12.668942 23057 solver.cpp:397]     Test net output #1: loss = 3.23751 (* 1 = 3.23751 loss)
I0406 15:31:13.039597 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:31:14.514741 23057 solver.cpp:218] Iteration 11328 (0.829218 iter/s, 14.4715s/12 iters), loss = 0.162566
I0406 15:31:14.514797 23057 solver.cpp:237]     Train net output #0: loss = 0.162566 (* 1 = 0.162566 loss)
I0406 15:31:14.514806 23057 sgd_solver.cpp:105] Iteration 11328, lr = 0.005
I0406 15:31:14.660830 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:31:19.740659 23057 solver.cpp:218] Iteration 11340 (2.2963 iter/s, 5.2258s/12 iters), loss = 0.217845
I0406 15:31:19.740707 23057 solver.cpp:237]     Train net output #0: loss = 0.217845 (* 1 = 0.217845 loss)
I0406 15:31:19.740715 23057 sgd_solver.cpp:105] Iteration 11340, lr = 0.005
I0406 15:31:24.973254 23057 solver.cpp:218] Iteration 11352 (2.29336 iter/s, 5.23249s/12 iters), loss = 0.097087
I0406 15:31:24.973354 23057 solver.cpp:237]     Train net output #0: loss = 0.0970871 (* 1 = 0.0970871 loss)
I0406 15:31:24.973361 23057 sgd_solver.cpp:105] Iteration 11352, lr = 0.005
I0406 15:31:30.411218 23057 solver.cpp:218] Iteration 11364 (2.20677 iter/s, 5.4378s/12 iters), loss = 0.281659
I0406 15:31:30.411260 23057 solver.cpp:237]     Train net output #0: loss = 0.281659 (* 1 = 0.281659 loss)
I0406 15:31:30.411267 23057 sgd_solver.cpp:105] Iteration 11364, lr = 0.005
I0406 15:31:35.409621 23057 solver.cpp:218] Iteration 11376 (2.40081 iter/s, 4.99831s/12 iters), loss = 0.302719
I0406 15:31:35.409658 23057 solver.cpp:237]     Train net output #0: loss = 0.302719 (* 1 = 0.302719 loss)
I0406 15:31:35.409664 23057 sgd_solver.cpp:105] Iteration 11376, lr = 0.005
I0406 15:31:40.566488 23057 solver.cpp:218] Iteration 11388 (2.32704 iter/s, 5.15677s/12 iters), loss = 0.155905
I0406 15:31:40.566530 23057 solver.cpp:237]     Train net output #0: loss = 0.155905 (* 1 = 0.155905 loss)
I0406 15:31:40.566537 23057 sgd_solver.cpp:105] Iteration 11388, lr = 0.005
I0406 15:31:45.864439 23057 solver.cpp:218] Iteration 11400 (2.26507 iter/s, 5.29785s/12 iters), loss = 0.125683
I0406 15:31:45.864485 23057 solver.cpp:237]     Train net output #0: loss = 0.125683 (* 1 = 0.125683 loss)
I0406 15:31:45.864490 23057 sgd_solver.cpp:105] Iteration 11400, lr = 0.005
I0406 15:31:51.008054 23057 solver.cpp:218] Iteration 11412 (2.33304 iter/s, 5.14351s/12 iters), loss = 0.240508
I0406 15:31:51.008101 23057 solver.cpp:237]     Train net output #0: loss = 0.240508 (* 1 = 0.240508 loss)
I0406 15:31:51.008106 23057 sgd_solver.cpp:105] Iteration 11412, lr = 0.005
I0406 15:31:55.845325 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11424.caffemodel
I0406 15:31:58.824118 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11424.solverstate
I0406 15:32:01.127125 23057 solver.cpp:330] Iteration 11424, Testing net (#0)
I0406 15:32:01.127144 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:32:05.455716 23057 solver.cpp:397]     Test net output #0: accuracy = 0.427083
I0406 15:32:05.455746 23057 solver.cpp:397]     Test net output #1: loss = 3.21637 (* 1 = 3.21637 loss)
I0406 15:32:05.595589 23057 solver.cpp:218] Iteration 11424 (0.82263 iter/s, 14.5874s/12 iters), loss = 0.233844
I0406 15:32:05.595641 23057 solver.cpp:237]     Train net output #0: loss = 0.233845 (* 1 = 0.233845 loss)
I0406 15:32:05.595649 23057 sgd_solver.cpp:105] Iteration 11424, lr = 0.005
I0406 15:32:05.792371 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:32:07.206089 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:32:10.157992 23057 solver.cpp:218] Iteration 11436 (2.63026 iter/s, 4.56229s/12 iters), loss = 0.348602
I0406 15:32:10.158033 23057 solver.cpp:237]     Train net output #0: loss = 0.348602 (* 1 = 0.348602 loss)
I0406 15:32:10.158039 23057 sgd_solver.cpp:105] Iteration 11436, lr = 0.005
I0406 15:32:15.177783 23057 solver.cpp:218] Iteration 11448 (2.39059 iter/s, 5.01969s/12 iters), loss = 0.10975
I0406 15:32:15.177825 23057 solver.cpp:237]     Train net output #0: loss = 0.10975 (* 1 = 0.10975 loss)
I0406 15:32:15.177831 23057 sgd_solver.cpp:105] Iteration 11448, lr = 0.005
I0406 15:32:20.460736 23057 solver.cpp:218] Iteration 11460 (2.2715 iter/s, 5.28285s/12 iters), loss = 0.113293
I0406 15:32:20.460777 23057 solver.cpp:237]     Train net output #0: loss = 0.113293 (* 1 = 0.113293 loss)
I0406 15:32:20.460781 23057 sgd_solver.cpp:105] Iteration 11460, lr = 0.005
I0406 15:32:25.812762 23057 solver.cpp:218] Iteration 11472 (2.24219 iter/s, 5.35192s/12 iters), loss = 0.167493
I0406 15:32:25.812809 23057 solver.cpp:237]     Train net output #0: loss = 0.167493 (* 1 = 0.167493 loss)
I0406 15:32:25.812816 23057 sgd_solver.cpp:105] Iteration 11472, lr = 0.005
I0406 15:32:30.991031 23057 solver.cpp:218] Iteration 11484 (2.31742 iter/s, 5.17816s/12 iters), loss = 0.161593
I0406 15:32:30.991158 23057 solver.cpp:237]     Train net output #0: loss = 0.161593 (* 1 = 0.161593 loss)
I0406 15:32:30.991165 23057 sgd_solver.cpp:105] Iteration 11484, lr = 0.005
I0406 15:32:36.235879 23057 solver.cpp:218] Iteration 11496 (2.28804 iter/s, 5.24466s/12 iters), loss = 0.160023
I0406 15:32:36.235925 23057 solver.cpp:237]     Train net output #0: loss = 0.160023 (* 1 = 0.160023 loss)
I0406 15:32:36.235931 23057 sgd_solver.cpp:105] Iteration 11496, lr = 0.005
I0406 15:32:41.631588 23057 solver.cpp:218] Iteration 11508 (2.22403 iter/s, 5.3956s/12 iters), loss = 0.138537
I0406 15:32:41.631634 23057 solver.cpp:237]     Train net output #0: loss = 0.138537 (* 1 = 0.138537 loss)
I0406 15:32:41.631640 23057 sgd_solver.cpp:105] Iteration 11508, lr = 0.005
I0406 15:32:46.884575 23057 solver.cpp:218] Iteration 11520 (2.28446 iter/s, 5.25288s/12 iters), loss = 0.141958
I0406 15:32:46.884624 23057 solver.cpp:237]     Train net output #0: loss = 0.141958 (* 1 = 0.141958 loss)
I0406 15:32:46.884632 23057 sgd_solver.cpp:105] Iteration 11520, lr = 0.005
I0406 15:32:49.047597 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11526.caffemodel
I0406 15:32:51.984484 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11526.solverstate
I0406 15:32:54.274386 23057 solver.cpp:330] Iteration 11526, Testing net (#0)
I0406 15:32:54.274407 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:32:58.653581 23057 solver.cpp:397]     Test net output #0: accuracy = 0.427083
I0406 15:32:58.653615 23057 solver.cpp:397]     Test net output #1: loss = 3.40903 (* 1 = 3.40903 loss)
I0406 15:32:58.747156 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:33:00.095868 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:33:00.648591 23057 solver.cpp:218] Iteration 11532 (0.87185 iter/s, 13.7638s/12 iters), loss = 0.157862
I0406 15:33:00.648636 23057 solver.cpp:237]     Train net output #0: loss = 0.157862 (* 1 = 0.157862 loss)
I0406 15:33:00.648643 23057 sgd_solver.cpp:105] Iteration 11532, lr = 0.005
I0406 15:33:06.002071 23057 solver.cpp:218] Iteration 11544 (2.24158 iter/s, 5.35338s/12 iters), loss = 0.0930536
I0406 15:33:06.002187 23057 solver.cpp:237]     Train net output #0: loss = 0.0930538 (* 1 = 0.0930538 loss)
I0406 15:33:06.002193 23057 sgd_solver.cpp:105] Iteration 11544, lr = 0.005
I0406 15:33:11.245491 23057 solver.cpp:218] Iteration 11556 (2.28866 iter/s, 5.24324s/12 iters), loss = 0.162219
I0406 15:33:11.245558 23057 solver.cpp:237]     Train net output #0: loss = 0.162219 (* 1 = 0.162219 loss)
I0406 15:33:11.245568 23057 sgd_solver.cpp:105] Iteration 11556, lr = 0.005
I0406 15:33:16.496138 23057 solver.cpp:218] Iteration 11568 (2.28549 iter/s, 5.25053s/12 iters), loss = 0.144164
I0406 15:33:16.496179 23057 solver.cpp:237]     Train net output #0: loss = 0.144164 (* 1 = 0.144164 loss)
I0406 15:33:16.496186 23057 sgd_solver.cpp:105] Iteration 11568, lr = 0.005
I0406 15:33:21.756640 23057 solver.cpp:218] Iteration 11580 (2.28119 iter/s, 5.2604s/12 iters), loss = 0.270298
I0406 15:33:21.756687 23057 solver.cpp:237]     Train net output #0: loss = 0.270298 (* 1 = 0.270298 loss)
I0406 15:33:21.756693 23057 sgd_solver.cpp:105] Iteration 11580, lr = 0.005
I0406 15:33:27.032510 23057 solver.cpp:218] Iteration 11592 (2.27455 iter/s, 5.27576s/12 iters), loss = 0.152317
I0406 15:33:27.032568 23057 solver.cpp:237]     Train net output #0: loss = 0.152317 (* 1 = 0.152317 loss)
I0406 15:33:27.032577 23057 sgd_solver.cpp:105] Iteration 11592, lr = 0.005
I0406 15:33:32.411620 23057 solver.cpp:218] Iteration 11604 (2.2309 iter/s, 5.379s/12 iters), loss = 0.213277
I0406 15:33:32.411660 23057 solver.cpp:237]     Train net output #0: loss = 0.213277 (* 1 = 0.213277 loss)
I0406 15:33:32.411665 23057 sgd_solver.cpp:105] Iteration 11604, lr = 0.005
I0406 15:33:37.762648 23057 solver.cpp:218] Iteration 11616 (2.2426 iter/s, 5.35092s/12 iters), loss = 0.094509
I0406 15:33:37.762786 23057 solver.cpp:237]     Train net output #0: loss = 0.0945091 (* 1 = 0.0945091 loss)
I0406 15:33:37.762795 23057 sgd_solver.cpp:105] Iteration 11616, lr = 0.005
I0406 15:33:42.482633 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11628.caffemodel
I0406 15:33:45.518257 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11628.solverstate
I0406 15:33:47.873194 23057 solver.cpp:330] Iteration 11628, Testing net (#0)
I0406 15:33:47.873214 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:33:52.321158 23057 solver.cpp:397]     Test net output #0: accuracy = 0.42402
I0406 15:33:52.321202 23057 solver.cpp:397]     Test net output #1: loss = 3.40109 (* 1 = 3.40109 loss)
I0406 15:33:52.383178 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:33:52.461293 23057 solver.cpp:218] Iteration 11628 (0.816417 iter/s, 14.6984s/12 iters), loss = 0.119553
I0406 15:33:52.462864 23057 solver.cpp:237]     Train net output #0: loss = 0.119553 (* 1 = 0.119553 loss)
I0406 15:33:52.462877 23057 sgd_solver.cpp:105] Iteration 11628, lr = 0.005
I0406 15:33:53.176540 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:33:56.942628 23057 solver.cpp:218] Iteration 11640 (2.67874 iter/s, 4.47972s/12 iters), loss = 0.0805469
I0406 15:33:56.942682 23057 solver.cpp:237]     Train net output #0: loss = 0.080547 (* 1 = 0.080547 loss)
I0406 15:33:56.942690 23057 sgd_solver.cpp:105] Iteration 11640, lr = 0.005
I0406 15:34:02.209296 23057 solver.cpp:218] Iteration 11652 (2.27853 iter/s, 5.26656s/12 iters), loss = 0.0755477
I0406 15:34:02.209338 23057 solver.cpp:237]     Train net output #0: loss = 0.0755478 (* 1 = 0.0755478 loss)
I0406 15:34:02.209344 23057 sgd_solver.cpp:105] Iteration 11652, lr = 0.005
I0406 15:34:07.429590 23057 solver.cpp:218] Iteration 11664 (2.29877 iter/s, 5.22019s/12 iters), loss = 0.156279
I0406 15:34:07.429630 23057 solver.cpp:237]     Train net output #0: loss = 0.156279 (* 1 = 0.156279 loss)
I0406 15:34:07.429636 23057 sgd_solver.cpp:105] Iteration 11664, lr = 0.005
I0406 15:34:12.833109 23057 solver.cpp:218] Iteration 11676 (2.22082 iter/s, 5.40342s/12 iters), loss = 0.208657
I0406 15:34:12.833564 23057 solver.cpp:237]     Train net output #0: loss = 0.208657 (* 1 = 0.208657 loss)
I0406 15:34:12.833572 23057 sgd_solver.cpp:105] Iteration 11676, lr = 0.005
I0406 15:34:18.124167 23057 solver.cpp:218] Iteration 11688 (2.2682 iter/s, 5.29054s/12 iters), loss = 0.270773
I0406 15:34:18.124228 23057 solver.cpp:237]     Train net output #0: loss = 0.270773 (* 1 = 0.270773 loss)
I0406 15:34:18.124236 23057 sgd_solver.cpp:105] Iteration 11688, lr = 0.005
I0406 15:34:23.426481 23057 solver.cpp:218] Iteration 11700 (2.26321 iter/s, 5.30219s/12 iters), loss = 0.348096
I0406 15:34:23.432698 23057 solver.cpp:237]     Train net output #0: loss = 0.348097 (* 1 = 0.348097 loss)
I0406 15:34:23.432713 23057 sgd_solver.cpp:105] Iteration 11700, lr = 0.005
I0406 15:34:28.826089 23057 solver.cpp:218] Iteration 11712 (2.22497 iter/s, 5.39334s/12 iters), loss = 0.346405
I0406 15:34:28.826145 23057 solver.cpp:237]     Train net output #0: loss = 0.346405 (* 1 = 0.346405 loss)
I0406 15:34:28.826153 23057 sgd_solver.cpp:105] Iteration 11712, lr = 0.005
I0406 15:34:34.181538 23057 solver.cpp:218] Iteration 11724 (2.24076 iter/s, 5.35533s/12 iters), loss = 0.156585
I0406 15:34:34.181604 23057 solver.cpp:237]     Train net output #0: loss = 0.156585 (* 1 = 0.156585 loss)
I0406 15:34:34.181613 23057 sgd_solver.cpp:105] Iteration 11724, lr = 0.005
I0406 15:34:36.390513 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11730.caffemodel
I0406 15:34:39.310151 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11730.solverstate
I0406 15:34:42.007380 23057 solver.cpp:330] Iteration 11730, Testing net (#0)
I0406 15:34:42.007405 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:34:46.398216 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:34:46.428433 23057 solver.cpp:397]     Test net output #0: accuracy = 0.405024
I0406 15:34:46.428464 23057 solver.cpp:397]     Test net output #1: loss = 3.50733 (* 1 = 3.50733 loss)
I0406 15:34:47.036077 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:34:48.290674 23057 solver.cpp:218] Iteration 11736 (0.850524 iter/s, 14.1089s/12 iters), loss = 0.0567502
I0406 15:34:48.290712 23057 solver.cpp:237]     Train net output #0: loss = 0.0567503 (* 1 = 0.0567503 loss)
I0406 15:34:48.290719 23057 sgd_solver.cpp:105] Iteration 11736, lr = 0.005
I0406 15:34:53.485688 23057 solver.cpp:218] Iteration 11748 (2.30995 iter/s, 5.19492s/12 iters), loss = 0.220765
I0406 15:34:53.485731 23057 solver.cpp:237]     Train net output #0: loss = 0.220765 (* 1 = 0.220765 loss)
I0406 15:34:53.485738 23057 sgd_solver.cpp:105] Iteration 11748, lr = 0.005
I0406 15:34:58.767014 23057 solver.cpp:218] Iteration 11760 (2.2722 iter/s, 5.28122s/12 iters), loss = 0.114633
I0406 15:34:58.767063 23057 solver.cpp:237]     Train net output #0: loss = 0.114633 (* 1 = 0.114633 loss)
I0406 15:34:58.767071 23057 sgd_solver.cpp:105] Iteration 11760, lr = 0.005
I0406 15:35:03.999537 23057 solver.cpp:218] Iteration 11772 (2.2934 iter/s, 5.23242s/12 iters), loss = 0.190789
I0406 15:35:03.999577 23057 solver.cpp:237]     Train net output #0: loss = 0.190789 (* 1 = 0.190789 loss)
I0406 15:35:03.999581 23057 sgd_solver.cpp:105] Iteration 11772, lr = 0.005
I0406 15:35:07.826905 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:35:09.250792 23057 solver.cpp:218] Iteration 11784 (2.28521 iter/s, 5.25116s/12 iters), loss = 0.101164
I0406 15:35:09.250851 23057 solver.cpp:237]     Train net output #0: loss = 0.101164 (* 1 = 0.101164 loss)
I0406 15:35:09.250861 23057 sgd_solver.cpp:105] Iteration 11784, lr = 0.005
I0406 15:35:14.606014 23057 solver.cpp:218] Iteration 11796 (2.24085 iter/s, 5.35511s/12 iters), loss = 0.212085
I0406 15:35:14.606056 23057 solver.cpp:237]     Train net output #0: loss = 0.212085 (* 1 = 0.212085 loss)
I0406 15:35:14.606062 23057 sgd_solver.cpp:105] Iteration 11796, lr = 0.005
I0406 15:35:19.771375 23057 solver.cpp:218] Iteration 11808 (2.32321 iter/s, 5.16526s/12 iters), loss = 0.0610568
I0406 15:35:19.771510 23057 solver.cpp:237]     Train net output #0: loss = 0.0610569 (* 1 = 0.0610569 loss)
I0406 15:35:19.771519 23057 sgd_solver.cpp:105] Iteration 11808, lr = 0.005
I0406 15:35:24.991585 23057 solver.cpp:218] Iteration 11820 (2.29884 iter/s, 5.22002s/12 iters), loss = 0.295302
I0406 15:35:24.991645 23057 solver.cpp:237]     Train net output #0: loss = 0.295302 (* 1 = 0.295302 loss)
I0406 15:35:24.991654 23057 sgd_solver.cpp:105] Iteration 11820, lr = 0.005
I0406 15:35:29.609387 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11832.caffemodel
I0406 15:35:32.661057 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11832.solverstate
I0406 15:35:34.965922 23057 solver.cpp:330] Iteration 11832, Testing net (#0)
I0406 15:35:34.965945 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:35:39.286593 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:35:39.348671 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422181
I0406 15:35:39.348699 23057 solver.cpp:397]     Test net output #1: loss = 3.23813 (* 1 = 3.23813 loss)
I0406 15:35:39.489166 23057 solver.cpp:218] Iteration 11832 (0.827735 iter/s, 14.4974s/12 iters), loss = 0.0547613
I0406 15:35:39.489225 23057 solver.cpp:237]     Train net output #0: loss = 0.0547614 (* 1 = 0.0547614 loss)
I0406 15:35:39.489233 23057 sgd_solver.cpp:105] Iteration 11832, lr = 0.005
I0406 15:35:39.571513 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:35:43.682569 23057 solver.cpp:218] Iteration 11844 (2.86171 iter/s, 4.1933s/12 iters), loss = 0.190734
I0406 15:35:43.682610 23057 solver.cpp:237]     Train net output #0: loss = 0.190734 (* 1 = 0.190734 loss)
I0406 15:35:43.682615 23057 sgd_solver.cpp:105] Iteration 11844, lr = 0.005
I0406 15:35:48.739548 23057 solver.cpp:218] Iteration 11856 (2.37301 iter/s, 5.05688s/12 iters), loss = 0.0824414
I0406 15:35:48.739601 23057 solver.cpp:237]     Train net output #0: loss = 0.0824414 (* 1 = 0.0824414 loss)
I0406 15:35:48.739612 23057 sgd_solver.cpp:105] Iteration 11856, lr = 0.005
I0406 15:35:54.116966 23057 solver.cpp:218] Iteration 11868 (2.2316 iter/s, 5.37731s/12 iters), loss = 0.10135
I0406 15:35:54.117123 23057 solver.cpp:237]     Train net output #0: loss = 0.10135 (* 1 = 0.10135 loss)
I0406 15:35:54.117132 23057 sgd_solver.cpp:105] Iteration 11868, lr = 0.005
I0406 15:35:59.163394 23057 solver.cpp:218] Iteration 11880 (2.37802 iter/s, 5.04622s/12 iters), loss = 0.0879414
I0406 15:35:59.163440 23057 solver.cpp:237]     Train net output #0: loss = 0.0879415 (* 1 = 0.0879415 loss)
I0406 15:35:59.163446 23057 sgd_solver.cpp:105] Iteration 11880, lr = 0.005
I0406 15:36:04.300421 23057 solver.cpp:218] Iteration 11892 (2.33603 iter/s, 5.13692s/12 iters), loss = 0.197146
I0406 15:36:04.300469 23057 solver.cpp:237]     Train net output #0: loss = 0.197146 (* 1 = 0.197146 loss)
I0406 15:36:04.300477 23057 sgd_solver.cpp:105] Iteration 11892, lr = 0.005
I0406 15:36:09.510118 23057 solver.cpp:218] Iteration 11904 (2.30344 iter/s, 5.20959s/12 iters), loss = 0.113294
I0406 15:36:09.510169 23057 solver.cpp:237]     Train net output #0: loss = 0.113294 (* 1 = 0.113294 loss)
I0406 15:36:09.510179 23057 sgd_solver.cpp:105] Iteration 11904, lr = 0.005
I0406 15:36:14.934923 23057 solver.cpp:218] Iteration 11916 (2.21211 iter/s, 5.42469s/12 iters), loss = 0.16648
I0406 15:36:14.934968 23057 solver.cpp:237]     Train net output #0: loss = 0.16648 (* 1 = 0.16648 loss)
I0406 15:36:14.934975 23057 sgd_solver.cpp:105] Iteration 11916, lr = 0.005
I0406 15:36:20.233530 23057 solver.cpp:218] Iteration 11928 (2.26479 iter/s, 5.2985s/12 iters), loss = 0.235566
I0406 15:36:20.233572 23057 solver.cpp:237]     Train net output #0: loss = 0.235566 (* 1 = 0.235566 loss)
I0406 15:36:20.233578 23057 sgd_solver.cpp:105] Iteration 11928, lr = 0.005
I0406 15:36:22.381664 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11934.caffemodel
I0406 15:36:23.352337 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:36:25.428877 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11934.solverstate
I0406 15:36:27.789917 23057 solver.cpp:330] Iteration 11934, Testing net (#0)
I0406 15:36:27.789943 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:36:32.018949 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:36:32.125407 23057 solver.cpp:397]     Test net output #0: accuracy = 0.415441
I0406 15:36:32.125437 23057 solver.cpp:397]     Test net output #1: loss = 3.33513 (* 1 = 3.33513 loss)
I0406 15:36:34.130617 23057 solver.cpp:218] Iteration 11940 (0.863501 iter/s, 13.8969s/12 iters), loss = 0.170408
I0406 15:36:34.130671 23057 solver.cpp:237]     Train net output #0: loss = 0.170409 (* 1 = 0.170409 loss)
I0406 15:36:34.130677 23057 sgd_solver.cpp:105] Iteration 11940, lr = 0.005
I0406 15:36:39.434401 23057 solver.cpp:218] Iteration 11952 (2.26258 iter/s, 5.30367s/12 iters), loss = 0.137758
I0406 15:36:39.434442 23057 solver.cpp:237]     Train net output #0: loss = 0.137758 (* 1 = 0.137758 loss)
I0406 15:36:39.434448 23057 sgd_solver.cpp:105] Iteration 11952, lr = 0.005
I0406 15:36:44.803138 23057 solver.cpp:218] Iteration 11964 (2.2352 iter/s, 5.36864s/12 iters), loss = 0.188286
I0406 15:36:44.803201 23057 solver.cpp:237]     Train net output #0: loss = 0.188286 (* 1 = 0.188286 loss)
I0406 15:36:44.803210 23057 sgd_solver.cpp:105] Iteration 11964, lr = 0.005
I0406 15:36:50.170120 23057 solver.cpp:218] Iteration 11976 (2.23594 iter/s, 5.36686s/12 iters), loss = 0.224208
I0406 15:36:50.170157 23057 solver.cpp:237]     Train net output #0: loss = 0.224208 (* 1 = 0.224208 loss)
I0406 15:36:50.170164 23057 sgd_solver.cpp:105] Iteration 11976, lr = 0.005
I0406 15:36:55.466617 23057 solver.cpp:218] Iteration 11988 (2.26569 iter/s, 5.29639s/12 iters), loss = 0.0740939
I0406 15:36:55.466727 23057 solver.cpp:237]     Train net output #0: loss = 0.074094 (* 1 = 0.074094 loss)
I0406 15:36:55.466734 23057 sgd_solver.cpp:105] Iteration 11988, lr = 0.005
I0406 15:37:00.905768 23057 solver.cpp:218] Iteration 12000 (2.20629 iter/s, 5.43898s/12 iters), loss = 0.0856382
I0406 15:37:00.905809 23057 solver.cpp:237]     Train net output #0: loss = 0.0856383 (* 1 = 0.0856383 loss)
I0406 15:37:00.905815 23057 sgd_solver.cpp:105] Iteration 12000, lr = 0.005
I0406 15:37:06.240351 23057 solver.cpp:218] Iteration 12012 (2.24952 iter/s, 5.33448s/12 iters), loss = 0.0801925
I0406 15:37:06.240394 23057 solver.cpp:237]     Train net output #0: loss = 0.0801926 (* 1 = 0.0801926 loss)
I0406 15:37:06.240401 23057 sgd_solver.cpp:105] Iteration 12012, lr = 0.005
I0406 15:37:11.551612 23057 solver.cpp:218] Iteration 12024 (2.25939 iter/s, 5.31116s/12 iters), loss = 0.128593
I0406 15:37:11.551656 23057 solver.cpp:237]     Train net output #0: loss = 0.128593 (* 1 = 0.128593 loss)
I0406 15:37:11.551662 23057 sgd_solver.cpp:105] Iteration 12024, lr = 0.005
I0406 15:37:16.216444 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12036.caffemodel
I0406 15:37:16.871261 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:37:19.241708 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12036.solverstate
I0406 15:37:21.544281 23057 solver.cpp:330] Iteration 12036, Testing net (#0)
I0406 15:37:21.544299 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:37:25.779306 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:37:25.917707 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422181
I0406 15:37:25.917737 23057 solver.cpp:397]     Test net output #1: loss = 3.31419 (* 1 = 3.31419 loss)
I0406 15:37:26.057744 23057 solver.cpp:218] Iteration 12036 (0.827247 iter/s, 14.506s/12 iters), loss = 0.147327
I0406 15:37:26.057794 23057 solver.cpp:237]     Train net output #0: loss = 0.147327 (* 1 = 0.147327 loss)
I0406 15:37:26.057801 23057 sgd_solver.cpp:105] Iteration 12036, lr = 0.005
I0406 15:37:30.345095 23057 solver.cpp:218] Iteration 12048 (2.799 iter/s, 4.28725s/12 iters), loss = 0.241445
I0406 15:37:30.345136 23057 solver.cpp:237]     Train net output #0: loss = 0.241445 (* 1 = 0.241445 loss)
I0406 15:37:30.345142 23057 sgd_solver.cpp:105] Iteration 12048, lr = 0.005
I0406 15:37:35.656998 23057 solver.cpp:218] Iteration 12060 (2.25912 iter/s, 5.3118s/12 iters), loss = 0.154282
I0406 15:37:35.657045 23057 solver.cpp:237]     Train net output #0: loss = 0.154282 (* 1 = 0.154282 loss)
I0406 15:37:35.657052 23057 sgd_solver.cpp:105] Iteration 12060, lr = 0.005
I0406 15:37:40.923457 23057 solver.cpp:218] Iteration 12072 (2.27862 iter/s, 5.26635s/12 iters), loss = 0.205087
I0406 15:37:40.923497 23057 solver.cpp:237]     Train net output #0: loss = 0.205087 (* 1 = 0.205087 loss)
I0406 15:37:40.923503 23057 sgd_solver.cpp:105] Iteration 12072, lr = 0.005
I0406 15:37:46.311209 23057 solver.cpp:218] Iteration 12084 (2.22732 iter/s, 5.38765s/12 iters), loss = 0.197368
I0406 15:37:46.311254 23057 solver.cpp:237]     Train net output #0: loss = 0.197368 (* 1 = 0.197368 loss)
I0406 15:37:46.311259 23057 sgd_solver.cpp:105] Iteration 12084, lr = 0.005
I0406 15:37:51.452033 23057 solver.cpp:218] Iteration 12096 (2.3343 iter/s, 5.14072s/12 iters), loss = 0.149593
I0406 15:37:51.452071 23057 solver.cpp:237]     Train net output #0: loss = 0.149593 (* 1 = 0.149593 loss)
I0406 15:37:51.452077 23057 sgd_solver.cpp:105] Iteration 12096, lr = 0.005
I0406 15:37:56.766427 23057 solver.cpp:218] Iteration 12108 (2.25806 iter/s, 5.31429s/12 iters), loss = 0.143662
I0406 15:37:56.766577 23057 solver.cpp:237]     Train net output #0: loss = 0.143663 (* 1 = 0.143663 loss)
I0406 15:37:56.766587 23057 sgd_solver.cpp:105] Iteration 12108, lr = 0.005
I0406 15:38:02.010298 23057 solver.cpp:218] Iteration 12120 (2.28847 iter/s, 5.24367s/12 iters), loss = 0.100648
I0406 15:38:02.010340 23057 solver.cpp:237]     Train net output #0: loss = 0.100648 (* 1 = 0.100648 loss)
I0406 15:38:02.010346 23057 sgd_solver.cpp:105] Iteration 12120, lr = 0.005
I0406 15:38:07.313127 23057 solver.cpp:218] Iteration 12132 (2.26299 iter/s, 5.30273s/12 iters), loss = 0.155359
I0406 15:38:07.313169 23057 solver.cpp:237]     Train net output #0: loss = 0.155359 (* 1 = 0.155359 loss)
I0406 15:38:07.313175 23057 sgd_solver.cpp:105] Iteration 12132, lr = 0.005
I0406 15:38:09.421602 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12138.caffemodel
I0406 15:38:09.748582 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:38:12.457165 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12138.solverstate
I0406 15:38:14.752070 23057 solver.cpp:330] Iteration 12138, Testing net (#0)
I0406 15:38:14.752096 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:38:19.216373 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:38:19.399737 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425858
I0406 15:38:19.399772 23057 solver.cpp:397]     Test net output #1: loss = 3.30667 (* 1 = 3.30667 loss)
I0406 15:38:21.353433 23057 solver.cpp:218] Iteration 12144 (0.854693 iter/s, 14.0401s/12 iters), loss = 0.187686
I0406 15:38:21.353507 23057 solver.cpp:237]     Train net output #0: loss = 0.187686 (* 1 = 0.187686 loss)
I0406 15:38:21.353514 23057 sgd_solver.cpp:105] Iteration 12144, lr = 0.005
I0406 15:38:26.550174 23057 solver.cpp:218] Iteration 12156 (2.3092 iter/s, 5.19661s/12 iters), loss = 0.107772
I0406 15:38:26.550215 23057 solver.cpp:237]     Train net output #0: loss = 0.107772 (* 1 = 0.107772 loss)
I0406 15:38:26.550220 23057 sgd_solver.cpp:105] Iteration 12156, lr = 0.005
I0406 15:38:31.859154 23057 solver.cpp:218] Iteration 12168 (2.26036 iter/s, 5.30888s/12 iters), loss = 0.199686
I0406 15:38:31.859261 23057 solver.cpp:237]     Train net output #0: loss = 0.199686 (* 1 = 0.199686 loss)
I0406 15:38:31.859269 23057 sgd_solver.cpp:105] Iteration 12168, lr = 0.005
I0406 15:38:37.297453 23057 solver.cpp:218] Iteration 12180 (2.20664 iter/s, 5.43814s/12 iters), loss = 0.122704
I0406 15:38:37.297494 23057 solver.cpp:237]     Train net output #0: loss = 0.122704 (* 1 = 0.122704 loss)
I0406 15:38:37.297502 23057 sgd_solver.cpp:105] Iteration 12180, lr = 0.005
I0406 15:38:42.559273 23057 solver.cpp:218] Iteration 12192 (2.28062 iter/s, 5.26172s/12 iters), loss = 0.161044
I0406 15:38:42.559316 23057 solver.cpp:237]     Train net output #0: loss = 0.161044 (* 1 = 0.161044 loss)
I0406 15:38:42.559322 23057 sgd_solver.cpp:105] Iteration 12192, lr = 0.005
I0406 15:38:47.638012 23057 solver.cpp:218] Iteration 12204 (2.36284 iter/s, 5.07864s/12 iters), loss = 0.146073
I0406 15:38:47.638051 23057 solver.cpp:237]     Train net output #0: loss = 0.146074 (* 1 = 0.146074 loss)
I0406 15:38:47.638056 23057 sgd_solver.cpp:105] Iteration 12204, lr = 0.005
I0406 15:38:52.825232 23057 solver.cpp:218] Iteration 12216 (2.31342 iter/s, 5.18712s/12 iters), loss = 0.181042
I0406 15:38:52.825285 23057 solver.cpp:237]     Train net output #0: loss = 0.181042 (* 1 = 0.181042 loss)
I0406 15:38:52.825294 23057 sgd_solver.cpp:105] Iteration 12216, lr = 0.005
I0406 15:38:58.214586 23057 solver.cpp:218] Iteration 12228 (2.22666 iter/s, 5.38924s/12 iters), loss = 0.218987
I0406 15:38:58.214637 23057 solver.cpp:237]     Train net output #0: loss = 0.218987 (* 1 = 0.218987 loss)
I0406 15:38:58.214645 23057 sgd_solver.cpp:105] Iteration 12228, lr = 0.005
I0406 15:39:02.762702 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:39:02.912778 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12240.caffemodel
I0406 15:39:05.925949 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12240.solverstate
I0406 15:39:08.429406 23057 solver.cpp:330] Iteration 12240, Testing net (#0)
I0406 15:39:08.429425 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:39:12.599542 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:39:12.823268 23057 solver.cpp:397]     Test net output #0: accuracy = 0.403799
I0406 15:39:12.823303 23057 solver.cpp:397]     Test net output #1: loss = 3.49972 (* 1 = 3.49972 loss)
I0406 15:39:12.964105 23057 solver.cpp:218] Iteration 12240 (0.813596 iter/s, 14.7493s/12 iters), loss = 0.20503
I0406 15:39:12.964172 23057 solver.cpp:237]     Train net output #0: loss = 0.20503 (* 1 = 0.20503 loss)
I0406 15:39:12.964181 23057 sgd_solver.cpp:105] Iteration 12240, lr = 0.005
I0406 15:39:17.332139 23057 solver.cpp:218] Iteration 12252 (2.74731 iter/s, 4.36792s/12 iters), loss = 0.204338
I0406 15:39:17.332183 23057 solver.cpp:237]     Train net output #0: loss = 0.204338 (* 1 = 0.204338 loss)
I0406 15:39:17.332190 23057 sgd_solver.cpp:105] Iteration 12252, lr = 0.005
I0406 15:39:22.689715 23057 solver.cpp:218] Iteration 12264 (2.23987 iter/s, 5.35746s/12 iters), loss = 0.290122
I0406 15:39:22.689770 23057 solver.cpp:237]     Train net output #0: loss = 0.290123 (* 1 = 0.290123 loss)
I0406 15:39:22.689779 23057 sgd_solver.cpp:105] Iteration 12264, lr = 0.005
I0406 15:39:27.759678 23057 solver.cpp:218] Iteration 12276 (2.36693 iter/s, 5.06986s/12 iters), loss = 0.175627
I0406 15:39:27.759717 23057 solver.cpp:237]     Train net output #0: loss = 0.175627 (* 1 = 0.175627 loss)
I0406 15:39:27.759723 23057 sgd_solver.cpp:105] Iteration 12276, lr = 0.005
I0406 15:39:32.931347 23057 solver.cpp:218] Iteration 12288 (2.32038 iter/s, 5.17157s/12 iters), loss = 0.229053
I0406 15:39:32.931455 23057 solver.cpp:237]     Train net output #0: loss = 0.229053 (* 1 = 0.229053 loss)
I0406 15:39:32.931463 23057 sgd_solver.cpp:105] Iteration 12288, lr = 0.005
I0406 15:39:38.162101 23057 solver.cpp:218] Iteration 12300 (2.2942 iter/s, 5.23059s/12 iters), loss = 0.151595
I0406 15:39:38.162137 23057 solver.cpp:237]     Train net output #0: loss = 0.151595 (* 1 = 0.151595 loss)
I0406 15:39:38.162142 23057 sgd_solver.cpp:105] Iteration 12300, lr = 0.005
I0406 15:39:43.400979 23057 solver.cpp:218] Iteration 12312 (2.29061 iter/s, 5.23878s/12 iters), loss = 0.176015
I0406 15:39:43.401015 23057 solver.cpp:237]     Train net output #0: loss = 0.176015 (* 1 = 0.176015 loss)
I0406 15:39:43.401021 23057 sgd_solver.cpp:105] Iteration 12312, lr = 0.005
I0406 15:39:48.676471 23057 solver.cpp:218] Iteration 12324 (2.27471 iter/s, 5.2754s/12 iters), loss = 0.0834714
I0406 15:39:48.676512 23057 solver.cpp:237]     Train net output #0: loss = 0.0834714 (* 1 = 0.0834714 loss)
I0406 15:39:48.676517 23057 sgd_solver.cpp:105] Iteration 12324, lr = 0.005
I0406 15:39:53.989253 23057 solver.cpp:218] Iteration 12336 (2.25875 iter/s, 5.31268s/12 iters), loss = 0.111574
I0406 15:39:53.989295 23057 solver.cpp:237]     Train net output #0: loss = 0.111574 (* 1 = 0.111574 loss)
I0406 15:39:53.989300 23057 sgd_solver.cpp:105] Iteration 12336, lr = 0.005
I0406 15:39:55.757800 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:39:56.091022 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12342.caffemodel
I0406 15:39:59.164062 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12342.solverstate
I0406 15:40:01.994732 23057 solver.cpp:330] Iteration 12342, Testing net (#0)
I0406 15:40:01.994755 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:40:06.225006 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:40:06.477308 23057 solver.cpp:397]     Test net output #0: accuracy = 0.411765
I0406 15:40:06.477334 23057 solver.cpp:397]     Test net output #1: loss = 3.43749 (* 1 = 3.43749 loss)
I0406 15:40:08.435178 23057 solver.cpp:218] Iteration 12348 (0.830694 iter/s, 14.4458s/12 iters), loss = 0.083948
I0406 15:40:08.435215 23057 solver.cpp:237]     Train net output #0: loss = 0.0839481 (* 1 = 0.0839481 loss)
I0406 15:40:08.435221 23057 sgd_solver.cpp:105] Iteration 12348, lr = 0.005
I0406 15:40:13.782233 23057 solver.cpp:218] Iteration 12360 (2.24427 iter/s, 5.34696s/12 iters), loss = 0.307767
I0406 15:40:13.782276 23057 solver.cpp:237]     Train net output #0: loss = 0.307767 (* 1 = 0.307767 loss)
I0406 15:40:13.782281 23057 sgd_solver.cpp:105] Iteration 12360, lr = 0.005
I0406 15:40:19.155246 23057 solver.cpp:218] Iteration 12372 (2.23343 iter/s, 5.37291s/12 iters), loss = 0.202458
I0406 15:40:19.155292 23057 solver.cpp:237]     Train net output #0: loss = 0.202458 (* 1 = 0.202458 loss)
I0406 15:40:19.155297 23057 sgd_solver.cpp:105] Iteration 12372, lr = 0.005
I0406 15:40:24.411731 23057 solver.cpp:218] Iteration 12384 (2.28294 iter/s, 5.25638s/12 iters), loss = 0.197412
I0406 15:40:24.411768 23057 solver.cpp:237]     Train net output #0: loss = 0.197412 (* 1 = 0.197412 loss)
I0406 15:40:24.411775 23057 sgd_solver.cpp:105] Iteration 12384, lr = 0.005
I0406 15:40:29.606446 23057 solver.cpp:218] Iteration 12396 (2.31008 iter/s, 5.19461s/12 iters), loss = 0.127543
I0406 15:40:29.606501 23057 solver.cpp:237]     Train net output #0: loss = 0.127543 (* 1 = 0.127543 loss)
I0406 15:40:29.606510 23057 sgd_solver.cpp:105] Iteration 12396, lr = 0.005
I0406 15:40:34.612666 23057 solver.cpp:218] Iteration 12408 (2.39707 iter/s, 5.00611s/12 iters), loss = 0.125188
I0406 15:40:34.612720 23057 solver.cpp:237]     Train net output #0: loss = 0.125189 (* 1 = 0.125189 loss)
I0406 15:40:34.612728 23057 sgd_solver.cpp:105] Iteration 12408, lr = 0.005
I0406 15:40:39.785645 23057 solver.cpp:218] Iteration 12420 (2.3198 iter/s, 5.17287s/12 iters), loss = 0.145887
I0406 15:40:39.785753 23057 solver.cpp:237]     Train net output #0: loss = 0.145887 (* 1 = 0.145887 loss)
I0406 15:40:39.785759 23057 sgd_solver.cpp:105] Iteration 12420, lr = 0.005
I0406 15:40:45.039650 23057 solver.cpp:218] Iteration 12432 (2.28404 iter/s, 5.25384s/12 iters), loss = 0.26534
I0406 15:40:45.039690 23057 solver.cpp:237]     Train net output #0: loss = 0.26534 (* 1 = 0.26534 loss)
I0406 15:40:45.039696 23057 sgd_solver.cpp:105] Iteration 12432, lr = 0.005
I0406 15:40:49.191803 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:40:49.930231 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12444.caffemodel
I0406 15:40:53.911096 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12444.solverstate
I0406 15:40:57.577909 23057 solver.cpp:330] Iteration 12444, Testing net (#0)
I0406 15:40:57.577929 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:41:01.678942 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:41:01.975884 23057 solver.cpp:397]     Test net output #0: accuracy = 0.423407
I0406 15:41:01.975920 23057 solver.cpp:397]     Test net output #1: loss = 3.43211 (* 1 = 3.43211 loss)
I0406 15:41:02.110656 23057 solver.cpp:218] Iteration 12444 (0.702954 iter/s, 17.0708s/12 iters), loss = 0.099195
I0406 15:41:02.110707 23057 solver.cpp:237]     Train net output #0: loss = 0.099195 (* 1 = 0.099195 loss)
I0406 15:41:02.110713 23057 sgd_solver.cpp:105] Iteration 12444, lr = 0.005
I0406 15:41:06.490077 23057 solver.cpp:218] Iteration 12456 (2.74015 iter/s, 4.37932s/12 iters), loss = 0.259074
I0406 15:41:06.490119 23057 solver.cpp:237]     Train net output #0: loss = 0.259074 (* 1 = 0.259074 loss)
I0406 15:41:06.490125 23057 sgd_solver.cpp:105] Iteration 12456, lr = 0.005
I0406 15:41:10.718454 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:41:11.695291 23057 solver.cpp:218] Iteration 12468 (2.30543 iter/s, 5.20511s/12 iters), loss = 0.161548
I0406 15:41:11.695335 23057 solver.cpp:237]     Train net output #0: loss = 0.161548 (* 1 = 0.161548 loss)
I0406 15:41:11.695341 23057 sgd_solver.cpp:105] Iteration 12468, lr = 0.005
I0406 15:41:16.613709 23057 solver.cpp:218] Iteration 12480 (2.43986 iter/s, 4.91832s/12 iters), loss = 0.270067
I0406 15:41:16.613747 23057 solver.cpp:237]     Train net output #0: loss = 0.270067 (* 1 = 0.270067 loss)
I0406 15:41:16.613754 23057 sgd_solver.cpp:105] Iteration 12480, lr = 0.005
I0406 15:41:21.965306 23057 solver.cpp:218] Iteration 12492 (2.24236 iter/s, 5.3515s/12 iters), loss = 0.0911338
I0406 15:41:21.965363 23057 solver.cpp:237]     Train net output #0: loss = 0.0911338 (* 1 = 0.0911338 loss)
I0406 15:41:21.965373 23057 sgd_solver.cpp:105] Iteration 12492, lr = 0.005
I0406 15:41:27.299381 23057 solver.cpp:218] Iteration 12504 (2.24974 iter/s, 5.33396s/12 iters), loss = 0.164984
I0406 15:41:27.299423 23057 solver.cpp:237]     Train net output #0: loss = 0.164984 (* 1 = 0.164984 loss)
I0406 15:41:27.299429 23057 sgd_solver.cpp:105] Iteration 12504, lr = 0.005
I0406 15:41:32.617092 23057 solver.cpp:218] Iteration 12516 (2.25665 iter/s, 5.31761s/12 iters), loss = 0.153038
I0406 15:41:32.617134 23057 solver.cpp:237]     Train net output #0: loss = 0.153038 (* 1 = 0.153038 loss)
I0406 15:41:32.617141 23057 sgd_solver.cpp:105] Iteration 12516, lr = 0.005
I0406 15:41:37.836333 23057 solver.cpp:218] Iteration 12528 (2.29923 iter/s, 5.21914s/12 iters), loss = 0.114573
I0406 15:41:37.836375 23057 solver.cpp:237]     Train net output #0: loss = 0.114573 (* 1 = 0.114573 loss)
I0406 15:41:37.836381 23057 sgd_solver.cpp:105] Iteration 12528, lr = 0.005
I0406 15:41:43.089439 23057 solver.cpp:218] Iteration 12540 (2.28441 iter/s, 5.25301s/12 iters), loss = 0.0700302
I0406 15:41:43.089551 23057 solver.cpp:237]     Train net output #0: loss = 0.0700302 (* 1 = 0.0700302 loss)
I0406 15:41:43.089558 23057 sgd_solver.cpp:105] Iteration 12540, lr = 0.005
I0406 15:41:44.020197 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:41:45.072329 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12546.caffemodel
I0406 15:41:48.105528 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12546.solverstate
I0406 15:41:50.522194 23057 solver.cpp:330] Iteration 12546, Testing net (#0)
I0406 15:41:50.522214 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:41:54.645289 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:41:54.975509 23057 solver.cpp:397]     Test net output #0: accuracy = 0.41973
I0406 15:41:54.975546 23057 solver.cpp:397]     Test net output #1: loss = 3.3709 (* 1 = 3.3709 loss)
I0406 15:41:56.808388 23057 solver.cpp:218] Iteration 12552 (0.874718 iter/s, 13.7187s/12 iters), loss = 0.18336
I0406 15:41:56.808436 23057 solver.cpp:237]     Train net output #0: loss = 0.18336 (* 1 = 0.18336 loss)
I0406 15:41:56.808444 23057 sgd_solver.cpp:105] Iteration 12552, lr = 0.005
I0406 15:42:01.877765 23057 solver.cpp:218] Iteration 12564 (2.3672 iter/s, 5.06928s/12 iters), loss = 0.109954
I0406 15:42:01.877806 23057 solver.cpp:237]     Train net output #0: loss = 0.109954 (* 1 = 0.109954 loss)
I0406 15:42:01.877812 23057 sgd_solver.cpp:105] Iteration 12564, lr = 0.005
I0406 15:42:06.983423 23057 solver.cpp:218] Iteration 12576 (2.35038 iter/s, 5.10556s/12 iters), loss = 0.311274
I0406 15:42:06.983475 23057 solver.cpp:237]     Train net output #0: loss = 0.311274 (* 1 = 0.311274 loss)
I0406 15:42:06.983484 23057 sgd_solver.cpp:105] Iteration 12576, lr = 0.005
I0406 15:42:12.227309 23057 solver.cpp:218] Iteration 12588 (2.28843 iter/s, 5.24378s/12 iters), loss = 0.219338
I0406 15:42:12.227349 23057 solver.cpp:237]     Train net output #0: loss = 0.219338 (* 1 = 0.219338 loss)
I0406 15:42:12.227355 23057 sgd_solver.cpp:105] Iteration 12588, lr = 0.005
I0406 15:42:17.477332 23057 solver.cpp:218] Iteration 12600 (2.28575 iter/s, 5.24992s/12 iters), loss = 0.0753784
I0406 15:42:17.477502 23057 solver.cpp:237]     Train net output #0: loss = 0.0753784 (* 1 = 0.0753784 loss)
I0406 15:42:17.477512 23057 sgd_solver.cpp:105] Iteration 12600, lr = 0.005
I0406 15:42:22.782001 23057 solver.cpp:218] Iteration 12612 (2.26225 iter/s, 5.30444s/12 iters), loss = 0.14938
I0406 15:42:22.782042 23057 solver.cpp:237]     Train net output #0: loss = 0.14938 (* 1 = 0.14938 loss)
I0406 15:42:22.782048 23057 sgd_solver.cpp:105] Iteration 12612, lr = 0.005
I0406 15:42:27.798158 23057 solver.cpp:218] Iteration 12624 (2.39232 iter/s, 5.01606s/12 iters), loss = 0.0971322
I0406 15:42:27.798203 23057 solver.cpp:237]     Train net output #0: loss = 0.0971321 (* 1 = 0.0971321 loss)
I0406 15:42:27.798208 23057 sgd_solver.cpp:105] Iteration 12624, lr = 0.005
I0406 15:42:32.959604 23057 solver.cpp:218] Iteration 12636 (2.32498 iter/s, 5.16135s/12 iters), loss = 0.166793
I0406 15:42:32.959643 23057 solver.cpp:237]     Train net output #0: loss = 0.166793 (* 1 = 0.166793 loss)
I0406 15:42:32.959648 23057 sgd_solver.cpp:105] Iteration 12636, lr = 0.005
I0406 15:42:36.349561 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:42:37.889755 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12648.caffemodel
I0406 15:42:40.963938 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12648.solverstate
I0406 15:42:43.260910 23057 solver.cpp:330] Iteration 12648, Testing net (#0)
I0406 15:42:43.260929 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:42:47.414513 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:42:47.789595 23057 solver.cpp:397]     Test net output #0: accuracy = 0.439951
I0406 15:42:47.789671 23057 solver.cpp:397]     Test net output #1: loss = 3.4142 (* 1 = 3.4142 loss)
I0406 15:42:47.929513 23057 solver.cpp:218] Iteration 12648 (0.801617 iter/s, 14.9697s/12 iters), loss = 0.221814
I0406 15:42:47.929565 23057 solver.cpp:237]     Train net output #0: loss = 0.221814 (* 1 = 0.221814 loss)
I0406 15:42:47.929572 23057 sgd_solver.cpp:105] Iteration 12648, lr = 0.005
I0406 15:42:52.202598 23057 solver.cpp:218] Iteration 12660 (2.80834 iter/s, 4.27299s/12 iters), loss = 0.108334
I0406 15:42:52.202641 23057 solver.cpp:237]     Train net output #0: loss = 0.108334 (* 1 = 0.108334 loss)
I0406 15:42:52.202647 23057 sgd_solver.cpp:105] Iteration 12660, lr = 0.005
I0406 15:42:57.380738 23057 solver.cpp:218] Iteration 12672 (2.31748 iter/s, 5.17804s/12 iters), loss = 0.205389
I0406 15:42:57.380784 23057 solver.cpp:237]     Train net output #0: loss = 0.205389 (* 1 = 0.205389 loss)
I0406 15:42:57.380789 23057 sgd_solver.cpp:105] Iteration 12672, lr = 0.005
I0406 15:43:02.718215 23057 solver.cpp:218] Iteration 12684 (2.2483 iter/s, 5.33737s/12 iters), loss = 0.0957166
I0406 15:43:02.718253 23057 solver.cpp:237]     Train net output #0: loss = 0.0957166 (* 1 = 0.0957166 loss)
I0406 15:43:02.718259 23057 sgd_solver.cpp:105] Iteration 12684, lr = 0.005
I0406 15:43:08.066627 23057 solver.cpp:218] Iteration 12696 (2.2437 iter/s, 5.34831s/12 iters), loss = 0.139683
I0406 15:43:08.066666 23057 solver.cpp:237]     Train net output #0: loss = 0.139683 (* 1 = 0.139683 loss)
I0406 15:43:08.066673 23057 sgd_solver.cpp:105] Iteration 12696, lr = 0.005
I0406 15:43:13.341444 23057 solver.cpp:218] Iteration 12708 (2.275 iter/s, 5.27472s/12 iters), loss = 0.0946504
I0406 15:43:13.341485 23057 solver.cpp:237]     Train net output #0: loss = 0.0946504 (* 1 = 0.0946504 loss)
I0406 15:43:13.341490 23057 sgd_solver.cpp:105] Iteration 12708, lr = 0.005
I0406 15:43:18.255187 23057 solver.cpp:218] Iteration 12720 (2.44218 iter/s, 4.91364s/12 iters), loss = 0.140861
I0406 15:43:18.255323 23057 solver.cpp:237]     Train net output #0: loss = 0.140861 (* 1 = 0.140861 loss)
I0406 15:43:18.255331 23057 sgd_solver.cpp:105] Iteration 12720, lr = 0.005
I0406 15:43:23.469800 23057 solver.cpp:218] Iteration 12732 (2.30131 iter/s, 5.21442s/12 iters), loss = 0.155735
I0406 15:43:23.469842 23057 solver.cpp:237]     Train net output #0: loss = 0.155735 (* 1 = 0.155735 loss)
I0406 15:43:23.469848 23057 sgd_solver.cpp:105] Iteration 12732, lr = 0.005
I0406 15:43:28.892575 23057 solver.cpp:218] Iteration 12744 (2.21293 iter/s, 5.42267s/12 iters), loss = 0.224391
I0406 15:43:28.892619 23057 solver.cpp:237]     Train net output #0: loss = 0.224391 (* 1 = 0.224391 loss)
I0406 15:43:28.892625 23057 sgd_solver.cpp:105] Iteration 12744, lr = 0.005
I0406 15:43:29.100186 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:43:31.058838 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12750.caffemodel
I0406 15:43:34.066884 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12750.solverstate
I0406 15:43:36.766440 23057 solver.cpp:330] Iteration 12750, Testing net (#0)
I0406 15:43:36.766464 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:43:40.753618 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:43:41.174253 23057 solver.cpp:397]     Test net output #0: accuracy = 0.415441
I0406 15:43:41.174280 23057 solver.cpp:397]     Test net output #1: loss = 3.55236 (* 1 = 3.55236 loss)
I0406 15:43:43.067178 23057 solver.cpp:218] Iteration 12756 (0.846595 iter/s, 14.1744s/12 iters), loss = 0.197265
I0406 15:43:43.067221 23057 solver.cpp:237]     Train net output #0: loss = 0.197265 (* 1 = 0.197265 loss)
I0406 15:43:43.067227 23057 sgd_solver.cpp:105] Iteration 12756, lr = 0.005
I0406 15:43:48.235700 23057 solver.cpp:218] Iteration 12768 (2.32179 iter/s, 5.16842s/12 iters), loss = 0.298906
I0406 15:43:48.235741 23057 solver.cpp:237]     Train net output #0: loss = 0.298906 (* 1 = 0.298906 loss)
I0406 15:43:48.235746 23057 sgd_solver.cpp:105] Iteration 12768, lr = 0.005
I0406 15:43:53.536243 23057 solver.cpp:218] Iteration 12780 (2.26396 iter/s, 5.30045s/12 iters), loss = 0.129318
I0406 15:43:53.536366 23057 solver.cpp:237]     Train net output #0: loss = 0.129318 (* 1 = 0.129318 loss)
I0406 15:43:53.536375 23057 sgd_solver.cpp:105] Iteration 12780, lr = 0.005
I0406 15:43:58.720331 23057 solver.cpp:218] Iteration 12792 (2.31486 iter/s, 5.18391s/12 iters), loss = 0.0762383
I0406 15:43:58.720391 23057 solver.cpp:237]     Train net output #0: loss = 0.0762383 (* 1 = 0.0762383 loss)
I0406 15:43:58.720399 23057 sgd_solver.cpp:105] Iteration 12792, lr = 0.005
I0406 15:44:04.039269 23057 solver.cpp:218] Iteration 12804 (2.25614 iter/s, 5.31883s/12 iters), loss = 0.102222
I0406 15:44:04.039309 23057 solver.cpp:237]     Train net output #0: loss = 0.102222 (* 1 = 0.102222 loss)
I0406 15:44:04.039315 23057 sgd_solver.cpp:105] Iteration 12804, lr = 0.005
I0406 15:44:09.146317 23057 solver.cpp:218] Iteration 12816 (2.34974 iter/s, 5.10695s/12 iters), loss = 0.135395
I0406 15:44:09.146358 23057 solver.cpp:237]     Train net output #0: loss = 0.135395 (* 1 = 0.135395 loss)
I0406 15:44:09.146364 23057 sgd_solver.cpp:105] Iteration 12816, lr = 0.005
I0406 15:44:14.397481 23057 solver.cpp:218] Iteration 12828 (2.28525 iter/s, 5.25106s/12 iters), loss = 0.337532
I0406 15:44:14.397531 23057 solver.cpp:237]     Train net output #0: loss = 0.337532 (* 1 = 0.337532 loss)
I0406 15:44:14.397537 23057 sgd_solver.cpp:105] Iteration 12828, lr = 0.005
I0406 15:44:19.592926 23057 solver.cpp:218] Iteration 12840 (2.30977 iter/s, 5.19533s/12 iters), loss = 0.229262
I0406 15:44:19.592967 23057 solver.cpp:237]     Train net output #0: loss = 0.229262 (* 1 = 0.229262 loss)
I0406 15:44:19.592973 23057 sgd_solver.cpp:105] Iteration 12840, lr = 0.005
I0406 15:44:21.988824 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:44:24.339437 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12852.caffemodel
I0406 15:44:27.350998 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12852.solverstate
I0406 15:44:30.005326 23057 solver.cpp:330] Iteration 12852, Testing net (#0)
I0406 15:44:30.005345 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:44:33.832849 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:44:34.286787 23057 solver.cpp:397]     Test net output #0: accuracy = 0.417892
I0406 15:44:34.286816 23057 solver.cpp:397]     Test net output #1: loss = 3.58532 (* 1 = 3.58532 loss)
I0406 15:44:34.426970 23057 solver.cpp:218] Iteration 12852 (0.808959 iter/s, 14.8339s/12 iters), loss = 0.235924
I0406 15:44:34.427014 23057 solver.cpp:237]     Train net output #0: loss = 0.235924 (* 1 = 0.235924 loss)
I0406 15:44:34.427019 23057 sgd_solver.cpp:105] Iteration 12852, lr = 0.005
I0406 15:44:38.831070 23057 solver.cpp:218] Iteration 12864 (2.72479 iter/s, 4.404s/12 iters), loss = 0.142026
I0406 15:44:38.831110 23057 solver.cpp:237]     Train net output #0: loss = 0.142026 (* 1 = 0.142026 loss)
I0406 15:44:38.831116 23057 sgd_solver.cpp:105] Iteration 12864, lr = 0.005
I0406 15:44:44.212781 23057 solver.cpp:218] Iteration 12876 (2.22982 iter/s, 5.38161s/12 iters), loss = 0.234855
I0406 15:44:44.212826 23057 solver.cpp:237]     Train net output #0: loss = 0.234855 (* 1 = 0.234855 loss)
I0406 15:44:44.212833 23057 sgd_solver.cpp:105] Iteration 12876, lr = 0.005
I0406 15:44:49.434235 23057 solver.cpp:218] Iteration 12888 (2.29826 iter/s, 5.22135s/12 iters), loss = 0.206631
I0406 15:44:49.434275 23057 solver.cpp:237]     Train net output #0: loss = 0.206631 (* 1 = 0.206631 loss)
I0406 15:44:49.434281 23057 sgd_solver.cpp:105] Iteration 12888, lr = 0.005
I0406 15:44:54.626128 23057 solver.cpp:218] Iteration 12900 (2.31134 iter/s, 5.19179s/12 iters), loss = 0.270616
I0406 15:44:54.626222 23057 solver.cpp:237]     Train net output #0: loss = 0.270616 (* 1 = 0.270616 loss)
I0406 15:44:54.626228 23057 sgd_solver.cpp:105] Iteration 12900, lr = 0.005
I0406 15:45:00.016556 23057 solver.cpp:218] Iteration 12912 (2.22623 iter/s, 5.39027s/12 iters), loss = 0.13481
I0406 15:45:00.016595 23057 solver.cpp:237]     Train net output #0: loss = 0.13481 (* 1 = 0.13481 loss)
I0406 15:45:00.016600 23057 sgd_solver.cpp:105] Iteration 12912, lr = 0.005
I0406 15:45:05.348122 23057 solver.cpp:218] Iteration 12924 (2.25079 iter/s, 5.33147s/12 iters), loss = 0.0593466
I0406 15:45:05.348166 23057 solver.cpp:237]     Train net output #0: loss = 0.0593466 (* 1 = 0.0593466 loss)
I0406 15:45:05.348172 23057 sgd_solver.cpp:105] Iteration 12924, lr = 0.005
I0406 15:45:10.468999 23057 solver.cpp:218] Iteration 12936 (2.3434 iter/s, 5.12077s/12 iters), loss = 0.0979834
I0406 15:45:10.469055 23057 solver.cpp:237]     Train net output #0: loss = 0.0979834 (* 1 = 0.0979834 loss)
I0406 15:45:10.469064 23057 sgd_solver.cpp:105] Iteration 12936, lr = 0.005
I0406 15:45:15.102372 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:45:15.694445 23057 solver.cpp:218] Iteration 12948 (2.29651 iter/s, 5.22533s/12 iters), loss = 0.166424
I0406 15:45:15.694505 23057 solver.cpp:237]     Train net output #0: loss = 0.166424 (* 1 = 0.166424 loss)
I0406 15:45:15.694515 23057 sgd_solver.cpp:105] Iteration 12948, lr = 0.005
I0406 15:45:17.834940 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12954.caffemodel
I0406 15:45:20.875538 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12954.solverstate
I0406 15:45:23.173028 23057 solver.cpp:330] Iteration 12954, Testing net (#0)
I0406 15:45:23.173048 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:45:27.094498 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:45:27.578650 23057 solver.cpp:397]     Test net output #0: accuracy = 0.41973
I0406 15:45:27.578681 23057 solver.cpp:397]     Test net output #1: loss = 3.53572 (* 1 = 3.53572 loss)
I0406 15:45:29.413012 23057 solver.cpp:218] Iteration 12960 (0.874739 iter/s, 13.7184s/12 iters), loss = 0.141183
I0406 15:45:29.413058 23057 solver.cpp:237]     Train net output #0: loss = 0.141183 (* 1 = 0.141183 loss)
I0406 15:45:29.413062 23057 sgd_solver.cpp:105] Iteration 12960, lr = 0.005
I0406 15:45:34.654552 23057 solver.cpp:218] Iteration 12972 (2.28945 iter/s, 5.24144s/12 iters), loss = 0.187543
I0406 15:45:34.654597 23057 solver.cpp:237]     Train net output #0: loss = 0.187543 (* 1 = 0.187543 loss)
I0406 15:45:34.654603 23057 sgd_solver.cpp:105] Iteration 12972, lr = 0.005
I0406 15:45:39.995205 23057 solver.cpp:218] Iteration 12984 (2.24696 iter/s, 5.34055s/12 iters), loss = 0.115002
I0406 15:45:39.995247 23057 solver.cpp:237]     Train net output #0: loss = 0.115002 (* 1 = 0.115002 loss)
I0406 15:45:39.995252 23057 sgd_solver.cpp:105] Iteration 12984, lr = 0.005
I0406 15:45:45.325212 23057 solver.cpp:218] Iteration 12996 (2.25145 iter/s, 5.3299s/12 iters), loss = 0.194627
I0406 15:45:45.325264 23057 solver.cpp:237]     Train net output #0: loss = 0.194627 (* 1 = 0.194627 loss)
I0406 15:45:45.325270 23057 sgd_solver.cpp:105] Iteration 12996, lr = 0.005
I0406 15:45:50.752243 23057 solver.cpp:218] Iteration 13008 (2.2112 iter/s, 5.42692s/12 iters), loss = 0.102172
I0406 15:45:50.752295 23057 solver.cpp:237]     Train net output #0: loss = 0.102172 (* 1 = 0.102172 loss)
I0406 15:45:50.752302 23057 sgd_solver.cpp:105] Iteration 13008, lr = 0.005
I0406 15:45:56.113004 23057 solver.cpp:218] Iteration 13020 (2.23854 iter/s, 5.36065s/12 iters), loss = 0.308569
I0406 15:45:56.113049 23057 solver.cpp:237]     Train net output #0: loss = 0.308569 (* 1 = 0.308569 loss)
I0406 15:45:56.113054 23057 sgd_solver.cpp:105] Iteration 13020, lr = 0.005
I0406 15:46:00.971946 23057 solver.cpp:218] Iteration 13032 (2.46972 iter/s, 4.85884s/12 iters), loss = 0.056127
I0406 15:46:00.972026 23057 solver.cpp:237]     Train net output #0: loss = 0.056127 (* 1 = 0.056127 loss)
I0406 15:46:00.972033 23057 sgd_solver.cpp:105] Iteration 13032, lr = 0.005
I0406 15:46:06.250159 23057 solver.cpp:218] Iteration 13044 (2.27356 iter/s, 5.27807s/12 iters), loss = 0.0911479
I0406 15:46:06.250223 23057 solver.cpp:237]     Train net output #0: loss = 0.0911479 (* 1 = 0.0911479 loss)
I0406 15:46:06.250234 23057 sgd_solver.cpp:105] Iteration 13044, lr = 0.005
I0406 15:46:08.091559 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:46:11.059689 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13056.caffemodel
I0406 15:46:14.100450 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13056.solverstate
I0406 15:46:16.432008 23057 solver.cpp:330] Iteration 13056, Testing net (#0)
I0406 15:46:16.432026 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:46:20.286895 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:46:20.809072 23057 solver.cpp:397]     Test net output #0: accuracy = 0.426471
I0406 15:46:20.809111 23057 solver.cpp:397]     Test net output #1: loss = 3.62246 (* 1 = 3.62246 loss)
I0406 15:46:20.943892 23057 solver.cpp:218] Iteration 13056 (0.816685 iter/s, 14.6935s/12 iters), loss = 0.202515
I0406 15:46:20.943940 23057 solver.cpp:237]     Train net output #0: loss = 0.202515 (* 1 = 0.202515 loss)
I0406 15:46:20.943946 23057 sgd_solver.cpp:105] Iteration 13056, lr = 0.005
I0406 15:46:25.235620 23057 solver.cpp:218] Iteration 13068 (2.79614 iter/s, 4.29163s/12 iters), loss = 0.0668765
I0406 15:46:25.235677 23057 solver.cpp:237]     Train net output #0: loss = 0.0668765 (* 1 = 0.0668765 loss)
I0406 15:46:25.235687 23057 sgd_solver.cpp:105] Iteration 13068, lr = 0.005
I0406 15:46:30.587091 23057 solver.cpp:218] Iteration 13080 (2.24242 iter/s, 5.35135s/12 iters), loss = 0.11457
I0406 15:46:30.587157 23057 solver.cpp:237]     Train net output #0: loss = 0.11457 (* 1 = 0.11457 loss)
I0406 15:46:30.587167 23057 sgd_solver.cpp:105] Iteration 13080, lr = 0.005
I0406 15:46:35.839447 23057 solver.cpp:218] Iteration 13092 (2.28474 iter/s, 5.25223s/12 iters), loss = 0.0725107
I0406 15:46:35.839566 23057 solver.cpp:237]     Train net output #0: loss = 0.0725107 (* 1 = 0.0725107 loss)
I0406 15:46:35.839574 23057 sgd_solver.cpp:105] Iteration 13092, lr = 0.005
I0406 15:46:41.148059 23057 solver.cpp:218] Iteration 13104 (2.26055 iter/s, 5.30843s/12 iters), loss = 0.232704
I0406 15:46:41.148108 23057 solver.cpp:237]     Train net output #0: loss = 0.232704 (* 1 = 0.232704 loss)
I0406 15:46:41.148114 23057 sgd_solver.cpp:105] Iteration 13104, lr = 0.005
I0406 15:46:46.537504 23057 solver.cpp:218] Iteration 13116 (2.22662 iter/s, 5.38933s/12 iters), loss = 0.514265
I0406 15:46:46.537564 23057 solver.cpp:237]     Train net output #0: loss = 0.514264 (* 1 = 0.514264 loss)
I0406 15:46:46.537572 23057 sgd_solver.cpp:105] Iteration 13116, lr = 0.005
I0406 15:46:51.818506 23057 solver.cpp:218] Iteration 13128 (2.27234 iter/s, 5.28089s/12 iters), loss = 0.103575
I0406 15:46:51.818540 23057 solver.cpp:237]     Train net output #0: loss = 0.103575 (* 1 = 0.103575 loss)
I0406 15:46:51.818547 23057 sgd_solver.cpp:105] Iteration 13128, lr = 0.005
I0406 15:46:57.127315 23057 solver.cpp:218] Iteration 13140 (2.26044 iter/s, 5.30871s/12 iters), loss = 0.0906165
I0406 15:46:57.127360 23057 solver.cpp:237]     Train net output #0: loss = 0.0906164 (* 1 = 0.0906164 loss)
I0406 15:46:57.127367 23057 sgd_solver.cpp:105] Iteration 13140, lr = 0.005
I0406 15:47:01.279889 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:47:02.525826 23057 solver.cpp:218] Iteration 13152 (2.22288 iter/s, 5.3984s/12 iters), loss = 0.116857
I0406 15:47:02.525871 23057 solver.cpp:237]     Train net output #0: loss = 0.116857 (* 1 = 0.116857 loss)
I0406 15:47:02.525876 23057 sgd_solver.cpp:105] Iteration 13152, lr = 0.005
I0406 15:47:04.685200 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13158.caffemodel
I0406 15:47:07.739629 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13158.solverstate
I0406 15:47:10.883891 23057 solver.cpp:330] Iteration 13158, Testing net (#0)
I0406 15:47:10.883919 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:47:14.580209 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:47:14.811646 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:47:15.375520 23057 solver.cpp:397]     Test net output #0: accuracy = 0.409926
I0406 15:47:15.375551 23057 solver.cpp:397]     Test net output #1: loss = 3.48429 (* 1 = 3.48429 loss)
I0406 15:47:17.364004 23057 solver.cpp:218] Iteration 13164 (0.808734 iter/s, 14.838s/12 iters), loss = 0.26211
I0406 15:47:17.364058 23057 solver.cpp:237]     Train net output #0: loss = 0.26211 (* 1 = 0.26211 loss)
I0406 15:47:17.364065 23057 sgd_solver.cpp:105] Iteration 13164, lr = 0.005
I0406 15:47:22.750577 23057 solver.cpp:218] Iteration 13176 (2.22781 iter/s, 5.38646s/12 iters), loss = 0.210855
I0406 15:47:22.750633 23057 solver.cpp:237]     Train net output #0: loss = 0.210855 (* 1 = 0.210855 loss)
I0406 15:47:22.750641 23057 sgd_solver.cpp:105] Iteration 13176, lr = 0.005
I0406 15:47:27.714746 23057 solver.cpp:218] Iteration 13188 (2.41738 iter/s, 4.96406s/12 iters), loss = 0.0845259
I0406 15:47:27.714785 23057 solver.cpp:237]     Train net output #0: loss = 0.0845258 (* 1 = 0.0845258 loss)
I0406 15:47:27.714790 23057 sgd_solver.cpp:105] Iteration 13188, lr = 0.005
I0406 15:47:33.031432 23057 solver.cpp:218] Iteration 13200 (2.25709 iter/s, 5.31658s/12 iters), loss = 0.0839237
I0406 15:47:33.031488 23057 solver.cpp:237]     Train net output #0: loss = 0.0839236 (* 1 = 0.0839236 loss)
I0406 15:47:33.031497 23057 sgd_solver.cpp:105] Iteration 13200, lr = 0.005
I0406 15:47:38.177737 23057 solver.cpp:218] Iteration 13212 (2.33182 iter/s, 5.14619s/12 iters), loss = 0.114634
I0406 15:47:38.177899 23057 solver.cpp:237]     Train net output #0: loss = 0.114633 (* 1 = 0.114633 loss)
I0406 15:47:38.177909 23057 sgd_solver.cpp:105] Iteration 13212, lr = 0.005
I0406 15:47:43.398484 23057 solver.cpp:218] Iteration 13224 (2.29862 iter/s, 5.22053s/12 iters), loss = 0.158926
I0406 15:47:43.398538 23057 solver.cpp:237]     Train net output #0: loss = 0.158926 (* 1 = 0.158926 loss)
I0406 15:47:43.398547 23057 sgd_solver.cpp:105] Iteration 13224, lr = 0.005
I0406 15:47:48.479422 23057 solver.cpp:218] Iteration 13236 (2.36182 iter/s, 5.08083s/12 iters), loss = 0.0947081
I0406 15:47:48.479463 23057 solver.cpp:237]     Train net output #0: loss = 0.0947081 (* 1 = 0.0947081 loss)
I0406 15:47:48.479470 23057 sgd_solver.cpp:105] Iteration 13236, lr = 0.005
I0406 15:47:53.789840 23057 solver.cpp:218] Iteration 13248 (2.25975 iter/s, 5.31031s/12 iters), loss = 0.164715
I0406 15:47:53.789894 23057 solver.cpp:237]     Train net output #0: loss = 0.164715 (* 1 = 0.164715 loss)
I0406 15:47:53.789902 23057 sgd_solver.cpp:105] Iteration 13248, lr = 0.005
I0406 15:47:54.758127 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:47:58.544535 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13260.caffemodel
I0406 15:48:01.552028 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13260.solverstate
I0406 15:48:04.658406 23057 solver.cpp:330] Iteration 13260, Testing net (#0)
I0406 15:48:04.658423 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:48:08.479728 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:48:09.074615 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 15:48:09.074643 23057 solver.cpp:397]     Test net output #1: loss = 3.45577 (* 1 = 3.45577 loss)
I0406 15:48:09.215006 23057 solver.cpp:218] Iteration 13260 (0.777959 iter/s, 15.425s/12 iters), loss = 0.144558
I0406 15:48:09.215056 23057 solver.cpp:237]     Train net output #0: loss = 0.144558 (* 1 = 0.144558 loss)
I0406 15:48:09.215065 23057 sgd_solver.cpp:105] Iteration 13260, lr = 0.005
I0406 15:48:13.516151 23057 solver.cpp:218] Iteration 13272 (2.79002 iter/s, 4.30105s/12 iters), loss = 0.143585
I0406 15:48:13.516189 23057 solver.cpp:237]     Train net output #0: loss = 0.143585 (* 1 = 0.143585 loss)
I0406 15:48:13.516196 23057 sgd_solver.cpp:105] Iteration 13272, lr = 0.005
I0406 15:48:18.790239 23057 solver.cpp:218] Iteration 13284 (2.27532 iter/s, 5.27399s/12 iters), loss = 0.0270713
I0406 15:48:18.790284 23057 solver.cpp:237]     Train net output #0: loss = 0.0270713 (* 1 = 0.0270713 loss)
I0406 15:48:18.790290 23057 sgd_solver.cpp:105] Iteration 13284, lr = 0.005
I0406 15:48:23.828850 23057 solver.cpp:218] Iteration 13296 (2.38166 iter/s, 5.03851s/12 iters), loss = 0.121658
I0406 15:48:23.828905 23057 solver.cpp:237]     Train net output #0: loss = 0.121658 (* 1 = 0.121658 loss)
I0406 15:48:23.828914 23057 sgd_solver.cpp:105] Iteration 13296, lr = 0.005
I0406 15:48:29.077086 23057 solver.cpp:218] Iteration 13308 (2.28653 iter/s, 5.24812s/12 iters), loss = 0.0895472
I0406 15:48:29.077128 23057 solver.cpp:237]     Train net output #0: loss = 0.0895471 (* 1 = 0.0895471 loss)
I0406 15:48:29.077133 23057 sgd_solver.cpp:105] Iteration 13308, lr = 0.005
I0406 15:48:34.498576 23057 solver.cpp:218] Iteration 13320 (2.21346 iter/s, 5.42139s/12 iters), loss = 0.209668
I0406 15:48:34.498620 23057 solver.cpp:237]     Train net output #0: loss = 0.209668 (* 1 = 0.209668 loss)
I0406 15:48:34.498625 23057 sgd_solver.cpp:105] Iteration 13320, lr = 0.005
I0406 15:48:39.620465 23057 solver.cpp:218] Iteration 13332 (2.34293 iter/s, 5.12179s/12 iters), loss = 0.0689776
I0406 15:48:39.620553 23057 solver.cpp:237]     Train net output #0: loss = 0.0689775 (* 1 = 0.0689775 loss)
I0406 15:48:39.620560 23057 sgd_solver.cpp:105] Iteration 13332, lr = 0.005
I0406 15:48:44.751633 23057 solver.cpp:218] Iteration 13344 (2.33872 iter/s, 5.13102s/12 iters), loss = 0.0963676
I0406 15:48:44.751682 23057 solver.cpp:237]     Train net output #0: loss = 0.0963675 (* 1 = 0.0963675 loss)
I0406 15:48:44.751688 23057 sgd_solver.cpp:105] Iteration 13344, lr = 0.005
I0406 15:48:47.934547 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:48:49.985078 23057 solver.cpp:218] Iteration 13356 (2.29299 iter/s, 5.23333s/12 iters), loss = 0.175771
I0406 15:48:49.985134 23057 solver.cpp:237]     Train net output #0: loss = 0.175771 (* 1 = 0.175771 loss)
I0406 15:48:49.985143 23057 sgd_solver.cpp:105] Iteration 13356, lr = 0.005
I0406 15:48:52.097275 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13362.caffemodel
I0406 15:48:55.117193 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13362.solverstate
I0406 15:48:58.330057 23057 solver.cpp:330] Iteration 13362, Testing net (#0)
I0406 15:48:58.330080 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:49:02.155098 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:49:02.813583 23057 solver.cpp:397]     Test net output #0: accuracy = 0.410539
I0406 15:49:02.813623 23057 solver.cpp:397]     Test net output #1: loss = 3.54167 (* 1 = 3.54167 loss)
I0406 15:49:04.743551 23057 solver.cpp:218] Iteration 13368 (0.813103 iter/s, 14.7583s/12 iters), loss = 0.165796
I0406 15:49:04.743597 23057 solver.cpp:237]     Train net output #0: loss = 0.165796 (* 1 = 0.165796 loss)
I0406 15:49:04.743604 23057 sgd_solver.cpp:105] Iteration 13368, lr = 0.005
I0406 15:49:09.814031 23057 solver.cpp:218] Iteration 13380 (2.36669 iter/s, 5.07037s/12 iters), loss = 0.127618
I0406 15:49:09.814170 23057 solver.cpp:237]     Train net output #0: loss = 0.127618 (* 1 = 0.127618 loss)
I0406 15:49:09.814177 23057 sgd_solver.cpp:105] Iteration 13380, lr = 0.005
I0406 15:49:15.215219 23057 solver.cpp:218] Iteration 13392 (2.22182 iter/s, 5.40098s/12 iters), loss = 0.0285514
I0406 15:49:15.215281 23057 solver.cpp:237]     Train net output #0: loss = 0.0285513 (* 1 = 0.0285513 loss)
I0406 15:49:15.215291 23057 sgd_solver.cpp:105] Iteration 13392, lr = 0.005
I0406 15:49:20.501838 23057 solver.cpp:218] Iteration 13404 (2.26993 iter/s, 5.2865s/12 iters), loss = 0.162651
I0406 15:49:20.501893 23057 solver.cpp:237]     Train net output #0: loss = 0.162651 (* 1 = 0.162651 loss)
I0406 15:49:20.501900 23057 sgd_solver.cpp:105] Iteration 13404, lr = 0.005
I0406 15:49:25.698891 23057 solver.cpp:218] Iteration 13416 (2.30905 iter/s, 5.19694s/12 iters), loss = 0.060086
I0406 15:49:25.698936 23057 solver.cpp:237]     Train net output #0: loss = 0.0600859 (* 1 = 0.0600859 loss)
I0406 15:49:25.698943 23057 sgd_solver.cpp:105] Iteration 13416, lr = 0.005
I0406 15:49:30.960783 23057 solver.cpp:218] Iteration 13428 (2.2806 iter/s, 5.26178s/12 iters), loss = 0.144095
I0406 15:49:30.960839 23057 solver.cpp:237]     Train net output #0: loss = 0.144095 (* 1 = 0.144095 loss)
I0406 15:49:30.960850 23057 sgd_solver.cpp:105] Iteration 13428, lr = 0.005
I0406 15:49:36.125938 23057 solver.cpp:218] Iteration 13440 (2.32331 iter/s, 5.16505s/12 iters), loss = 0.0387475
I0406 15:49:36.125978 23057 solver.cpp:237]     Train net output #0: loss = 0.0387474 (* 1 = 0.0387474 loss)
I0406 15:49:36.125984 23057 sgd_solver.cpp:105] Iteration 13440, lr = 0.005
I0406 15:49:41.173491 23057 solver.cpp:218] Iteration 13452 (2.37743 iter/s, 5.04746s/12 iters), loss = 0.107493
I0406 15:49:41.173599 23057 solver.cpp:237]     Train net output #0: loss = 0.107493 (* 1 = 0.107493 loss)
I0406 15:49:41.173606 23057 sgd_solver.cpp:105] Iteration 13452, lr = 0.005
I0406 15:49:41.409061 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:49:45.981407 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13464.caffemodel
I0406 15:49:48.978772 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13464.solverstate
I0406 15:49:51.961230 23057 solver.cpp:330] Iteration 13464, Testing net (#0)
I0406 15:49:51.961247 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:49:55.665208 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:49:56.347781 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 15:49:56.347831 23057 solver.cpp:397]     Test net output #1: loss = 3.50854 (* 1 = 3.50854 loss)
I0406 15:49:56.486632 23057 solver.cpp:218] Iteration 13464 (0.783653 iter/s, 15.3129s/12 iters), loss = 0.113137
I0406 15:49:56.488209 23057 solver.cpp:237]     Train net output #0: loss = 0.113137 (* 1 = 0.113137 loss)
I0406 15:49:56.488219 23057 sgd_solver.cpp:105] Iteration 13464, lr = 0.005
I0406 15:50:00.828797 23057 solver.cpp:218] Iteration 13476 (2.76463 iter/s, 4.34055s/12 iters), loss = 0.0913353
I0406 15:50:00.828840 23057 solver.cpp:237]     Train net output #0: loss = 0.0913352 (* 1 = 0.0913352 loss)
I0406 15:50:00.828846 23057 sgd_solver.cpp:105] Iteration 13476, lr = 0.005
I0406 15:50:06.199662 23057 solver.cpp:218] Iteration 13488 (2.23432 iter/s, 5.37076s/12 iters), loss = 0.02244
I0406 15:50:06.199715 23057 solver.cpp:237]     Train net output #0: loss = 0.02244 (* 1 = 0.02244 loss)
I0406 15:50:06.199723 23057 sgd_solver.cpp:105] Iteration 13488, lr = 0.005
I0406 15:50:11.376302 23057 solver.cpp:218] Iteration 13500 (2.31815 iter/s, 5.17654s/12 iters), loss = 0.156855
I0406 15:50:11.376443 23057 solver.cpp:237]     Train net output #0: loss = 0.156855 (* 1 = 0.156855 loss)
I0406 15:50:11.376452 23057 sgd_solver.cpp:105] Iteration 13500, lr = 0.005
I0406 15:50:16.575942 23057 solver.cpp:218] Iteration 13512 (2.30794 iter/s, 5.19944s/12 iters), loss = 0.232643
I0406 15:50:16.575996 23057 solver.cpp:237]     Train net output #0: loss = 0.232643 (* 1 = 0.232643 loss)
I0406 15:50:16.576005 23057 sgd_solver.cpp:105] Iteration 13512, lr = 0.005
I0406 15:50:21.921643 23057 solver.cpp:218] Iteration 13524 (2.24484 iter/s, 5.34559s/12 iters), loss = 0.0279922
I0406 15:50:21.921690 23057 solver.cpp:237]     Train net output #0: loss = 0.0279921 (* 1 = 0.0279921 loss)
I0406 15:50:21.921696 23057 sgd_solver.cpp:105] Iteration 13524, lr = 0.005
I0406 15:50:26.990237 23057 solver.cpp:218] Iteration 13536 (2.36757 iter/s, 5.06849s/12 iters), loss = 0.0942347
I0406 15:50:26.990278 23057 solver.cpp:237]     Train net output #0: loss = 0.0942347 (* 1 = 0.0942347 loss)
I0406 15:50:26.990284 23057 sgd_solver.cpp:105] Iteration 13536, lr = 0.005
I0406 15:50:32.186731 23057 solver.cpp:218] Iteration 13548 (2.30929 iter/s, 5.19639s/12 iters), loss = 0.120824
I0406 15:50:32.186774 23057 solver.cpp:237]     Train net output #0: loss = 0.120824 (* 1 = 0.120824 loss)
I0406 15:50:32.186779 23057 sgd_solver.cpp:105] Iteration 13548, lr = 0.005
I0406 15:50:34.694859 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:50:37.518837 23057 solver.cpp:218] Iteration 13560 (2.25056 iter/s, 5.332s/12 iters), loss = 0.119028
I0406 15:50:37.518879 23057 solver.cpp:237]     Train net output #0: loss = 0.119027 (* 1 = 0.119027 loss)
I0406 15:50:37.518885 23057 sgd_solver.cpp:105] Iteration 13560, lr = 0.005
I0406 15:50:39.501763 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13566.caffemodel
I0406 15:50:42.534896 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13566.solverstate
I0406 15:50:46.409487 23057 solver.cpp:330] Iteration 13566, Testing net (#0)
I0406 15:50:46.409508 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:50:49.988152 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:50:50.733510 23057 solver.cpp:397]     Test net output #0: accuracy = 0.417279
I0406 15:50:50.733549 23057 solver.cpp:397]     Test net output #1: loss = 3.42335 (* 1 = 3.42335 loss)
I0406 15:50:52.594254 23057 solver.cpp:218] Iteration 13572 (0.796007 iter/s, 15.0752s/12 iters), loss = 0.0801081
I0406 15:50:52.594298 23057 solver.cpp:237]     Train net output #0: loss = 0.080108 (* 1 = 0.080108 loss)
I0406 15:50:52.594305 23057 sgd_solver.cpp:105] Iteration 13572, lr = 0.005
I0406 15:50:57.734586 23057 solver.cpp:218] Iteration 13584 (2.33453 iter/s, 5.14022s/12 iters), loss = 0.0742585
I0406 15:50:57.734642 23057 solver.cpp:237]     Train net output #0: loss = 0.0742584 (* 1 = 0.0742584 loss)
I0406 15:50:57.734649 23057 sgd_solver.cpp:105] Iteration 13584, lr = 0.005
I0406 15:51:02.850385 23057 solver.cpp:218] Iteration 13596 (2.34573 iter/s, 5.11568s/12 iters), loss = 0.0657522
I0406 15:51:02.850446 23057 solver.cpp:237]     Train net output #0: loss = 0.0657522 (* 1 = 0.0657522 loss)
I0406 15:51:02.850455 23057 sgd_solver.cpp:105] Iteration 13596, lr = 0.005
I0406 15:51:08.132335 23057 solver.cpp:218] Iteration 13608 (2.27194 iter/s, 5.28183s/12 iters), loss = 0.109727
I0406 15:51:08.132395 23057 solver.cpp:237]     Train net output #0: loss = 0.109727 (* 1 = 0.109727 loss)
I0406 15:51:08.132405 23057 sgd_solver.cpp:105] Iteration 13608, lr = 0.005
I0406 15:51:13.248953 23057 solver.cpp:218] Iteration 13620 (2.34535 iter/s, 5.1165s/12 iters), loss = 0.108622
I0406 15:51:13.249078 23057 solver.cpp:237]     Train net output #0: loss = 0.108622 (* 1 = 0.108622 loss)
I0406 15:51:13.249086 23057 sgd_solver.cpp:105] Iteration 13620, lr = 0.005
I0406 15:51:18.635035 23057 solver.cpp:218] Iteration 13632 (2.22804 iter/s, 5.3859s/12 iters), loss = 0.145438
I0406 15:51:18.635082 23057 solver.cpp:237]     Train net output #0: loss = 0.145438 (* 1 = 0.145438 loss)
I0406 15:51:18.635088 23057 sgd_solver.cpp:105] Iteration 13632, lr = 0.005
I0406 15:51:23.779942 23057 solver.cpp:218] Iteration 13644 (2.33245 iter/s, 5.1448s/12 iters), loss = 0.130993
I0406 15:51:23.779994 23057 solver.cpp:237]     Train net output #0: loss = 0.130993 (* 1 = 0.130993 loss)
I0406 15:51:23.780004 23057 sgd_solver.cpp:105] Iteration 13644, lr = 0.005
I0406 15:51:28.742678 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:51:29.153977 23057 solver.cpp:218] Iteration 13656 (2.233 iter/s, 5.37393s/12 iters), loss = 0.097068
I0406 15:51:29.154031 23057 solver.cpp:237]     Train net output #0: loss = 0.097068 (* 1 = 0.097068 loss)
I0406 15:51:29.154038 23057 sgd_solver.cpp:105] Iteration 13656, lr = 0.005
I0406 15:51:33.810731 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13668.caffemodel
I0406 15:51:38.360371 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13668.solverstate
I0406 15:51:41.869136 23057 solver.cpp:330] Iteration 13668, Testing net (#0)
I0406 15:51:41.869156 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:51:45.631539 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:51:46.388339 23057 solver.cpp:397]     Test net output #0: accuracy = 0.424632
I0406 15:51:46.388382 23057 solver.cpp:397]     Test net output #1: loss = 3.42501 (* 1 = 3.42501 loss)
I0406 15:51:46.528923 23057 solver.cpp:218] Iteration 13668 (0.690658 iter/s, 17.3747s/12 iters), loss = 0.0452356
I0406 15:51:46.530500 23057 solver.cpp:237]     Train net output #0: loss = 0.0452356 (* 1 = 0.0452356 loss)
I0406 15:51:46.530517 23057 sgd_solver.cpp:105] Iteration 13668, lr = 0.005
I0406 15:51:50.861335 23057 solver.cpp:218] Iteration 13680 (2.77085 iter/s, 4.3308s/12 iters), loss = 0.211665
I0406 15:51:50.861377 23057 solver.cpp:237]     Train net output #0: loss = 0.211665 (* 1 = 0.211665 loss)
I0406 15:51:50.861382 23057 sgd_solver.cpp:105] Iteration 13680, lr = 0.005
I0406 15:51:56.185819 23057 solver.cpp:218] Iteration 13692 (2.25378 iter/s, 5.32439s/12 iters), loss = 0.104871
I0406 15:51:56.185861 23057 solver.cpp:237]     Train net output #0: loss = 0.104871 (* 1 = 0.104871 loss)
I0406 15:51:56.185869 23057 sgd_solver.cpp:105] Iteration 13692, lr = 0.005
I0406 15:52:01.131700 23057 solver.cpp:218] Iteration 13704 (2.42631 iter/s, 4.94578s/12 iters), loss = 0.168451
I0406 15:52:01.131752 23057 solver.cpp:237]     Train net output #0: loss = 0.168451 (* 1 = 0.168451 loss)
I0406 15:52:01.131762 23057 sgd_solver.cpp:105] Iteration 13704, lr = 0.005
I0406 15:52:06.359756 23057 solver.cpp:218] Iteration 13716 (2.29536 iter/s, 5.22795s/12 iters), loss = 0.0842674
I0406 15:52:06.359802 23057 solver.cpp:237]     Train net output #0: loss = 0.0842673 (* 1 = 0.0842673 loss)
I0406 15:52:06.359809 23057 sgd_solver.cpp:105] Iteration 13716, lr = 0.005
I0406 15:52:11.561733 23057 solver.cpp:218] Iteration 13728 (2.30686 iter/s, 5.20188s/12 iters), loss = 0.0890655
I0406 15:52:11.561771 23057 solver.cpp:237]     Train net output #0: loss = 0.0890654 (* 1 = 0.0890654 loss)
I0406 15:52:11.561777 23057 sgd_solver.cpp:105] Iteration 13728, lr = 0.005
I0406 15:52:16.787380 23057 solver.cpp:218] Iteration 13740 (2.29641 iter/s, 5.22556s/12 iters), loss = 0.132386
I0406 15:52:16.787505 23057 solver.cpp:237]     Train net output #0: loss = 0.132385 (* 1 = 0.132385 loss)
I0406 15:52:16.787513 23057 sgd_solver.cpp:105] Iteration 13740, lr = 0.005
I0406 15:52:22.065923 23057 solver.cpp:218] Iteration 13752 (2.27343 iter/s, 5.27836s/12 iters), loss = 0.0716394
I0406 15:52:22.065963 23057 solver.cpp:237]     Train net output #0: loss = 0.0716393 (* 1 = 0.0716393 loss)
I0406 15:52:22.065969 23057 sgd_solver.cpp:105] Iteration 13752, lr = 0.005
I0406 15:52:23.871656 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:52:27.264591 23057 solver.cpp:218] Iteration 13764 (2.30833 iter/s, 5.19857s/12 iters), loss = 0.119319
I0406 15:52:27.264637 23057 solver.cpp:237]     Train net output #0: loss = 0.119318 (* 1 = 0.119318 loss)
I0406 15:52:27.264643 23057 sgd_solver.cpp:105] Iteration 13764, lr = 0.005
I0406 15:52:29.400475 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13770.caffemodel
I0406 15:52:32.468245 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13770.solverstate
I0406 15:52:35.904729 23057 solver.cpp:330] Iteration 13770, Testing net (#0)
I0406 15:52:35.904750 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:52:39.435575 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:52:40.280313 23057 solver.cpp:397]     Test net output #0: accuracy = 0.423407
I0406 15:52:40.280342 23057 solver.cpp:397]     Test net output #1: loss = 3.5405 (* 1 = 3.5405 loss)
I0406 15:52:42.108050 23057 solver.cpp:218] Iteration 13776 (0.808447 iter/s, 14.8433s/12 iters), loss = 0.120727
I0406 15:52:42.108099 23057 solver.cpp:237]     Train net output #0: loss = 0.120727 (* 1 = 0.120727 loss)
I0406 15:52:42.108108 23057 sgd_solver.cpp:105] Iteration 13776, lr = 0.005
I0406 15:52:47.396636 23057 solver.cpp:218] Iteration 13788 (2.26908 iter/s, 5.28848s/12 iters), loss = 0.14736
I0406 15:52:47.396754 23057 solver.cpp:237]     Train net output #0: loss = 0.14736 (* 1 = 0.14736 loss)
I0406 15:52:47.396762 23057 sgd_solver.cpp:105] Iteration 13788, lr = 0.005
I0406 15:52:52.756564 23057 solver.cpp:218] Iteration 13800 (2.23891 iter/s, 5.35975s/12 iters), loss = 0.0996642
I0406 15:52:52.756619 23057 solver.cpp:237]     Train net output #0: loss = 0.0996642 (* 1 = 0.0996642 loss)
I0406 15:52:52.756628 23057 sgd_solver.cpp:105] Iteration 13800, lr = 0.005
I0406 15:52:57.855141 23057 solver.cpp:218] Iteration 13812 (2.35365 iter/s, 5.09846s/12 iters), loss = 0.11365
I0406 15:52:57.855201 23057 solver.cpp:237]     Train net output #0: loss = 0.11365 (* 1 = 0.11365 loss)
I0406 15:52:57.855208 23057 sgd_solver.cpp:105] Iteration 13812, lr = 0.005
I0406 15:53:03.124477 23057 solver.cpp:218] Iteration 13824 (2.27738 iter/s, 5.26922s/12 iters), loss = 0.263853
I0406 15:53:03.124536 23057 solver.cpp:237]     Train net output #0: loss = 0.263853 (* 1 = 0.263853 loss)
I0406 15:53:03.124544 23057 sgd_solver.cpp:105] Iteration 13824, lr = 0.005
I0406 15:53:08.418860 23057 solver.cpp:218] Iteration 13836 (2.2666 iter/s, 5.29427s/12 iters), loss = 0.111046
I0406 15:53:08.418897 23057 solver.cpp:237]     Train net output #0: loss = 0.111046 (* 1 = 0.111046 loss)
I0406 15:53:08.418902 23057 sgd_solver.cpp:105] Iteration 13836, lr = 0.005
I0406 15:53:13.488318 23057 solver.cpp:218] Iteration 13848 (2.36716 iter/s, 5.06936s/12 iters), loss = 0.137239
I0406 15:53:13.488361 23057 solver.cpp:237]     Train net output #0: loss = 0.137239 (* 1 = 0.137239 loss)
I0406 15:53:13.488368 23057 sgd_solver.cpp:105] Iteration 13848, lr = 0.005
I0406 15:53:17.573496 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:53:18.900702 23057 solver.cpp:218] Iteration 13860 (2.21718 iter/s, 5.41228s/12 iters), loss = 0.223162
I0406 15:53:18.900748 23057 solver.cpp:237]     Train net output #0: loss = 0.223162 (* 1 = 0.223162 loss)
I0406 15:53:18.900753 23057 sgd_solver.cpp:105] Iteration 13860, lr = 0.005
I0406 15:53:23.727175 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13872.caffemodel
I0406 15:53:26.696517 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13872.solverstate
I0406 15:53:31.476891 23057 solver.cpp:330] Iteration 13872, Testing net (#0)
I0406 15:53:31.476912 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:53:32.424034 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:53:34.988314 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:53:35.837925 23057 solver.cpp:397]     Test net output #0: accuracy = 0.417892
I0406 15:53:35.837961 23057 solver.cpp:397]     Test net output #1: loss = 3.39245 (* 1 = 3.39245 loss)
I0406 15:53:35.972810 23057 solver.cpp:218] Iteration 13872 (0.702909 iter/s, 17.0719s/12 iters), loss = 0.129947
I0406 15:53:35.972858 23057 solver.cpp:237]     Train net output #0: loss = 0.129947 (* 1 = 0.129947 loss)
I0406 15:53:35.972867 23057 sgd_solver.cpp:105] Iteration 13872, lr = 0.005
I0406 15:53:40.274142 23057 solver.cpp:218] Iteration 13884 (2.7899 iter/s, 4.30123s/12 iters), loss = 0.324488
I0406 15:53:40.274179 23057 solver.cpp:237]     Train net output #0: loss = 0.324488 (* 1 = 0.324488 loss)
I0406 15:53:40.274184 23057 sgd_solver.cpp:105] Iteration 13884, lr = 0.005
I0406 15:53:45.410163 23057 solver.cpp:218] Iteration 13896 (2.33648 iter/s, 5.13593s/12 iters), loss = 0.187928
I0406 15:53:45.410193 23057 solver.cpp:237]     Train net output #0: loss = 0.187928 (* 1 = 0.187928 loss)
I0406 15:53:45.410198 23057 sgd_solver.cpp:105] Iteration 13896, lr = 0.005
I0406 15:53:50.542582 23057 solver.cpp:218] Iteration 13908 (2.33812 iter/s, 5.13233s/12 iters), loss = 0.15856
I0406 15:53:50.542701 23057 solver.cpp:237]     Train net output #0: loss = 0.15856 (* 1 = 0.15856 loss)
I0406 15:53:50.542707 23057 sgd_solver.cpp:105] Iteration 13908, lr = 0.005
I0406 15:53:55.959975 23057 solver.cpp:218] Iteration 13920 (2.21516 iter/s, 5.41721s/12 iters), loss = 0.145152
I0406 15:53:55.960032 23057 solver.cpp:237]     Train net output #0: loss = 0.145152 (* 1 = 0.145152 loss)
I0406 15:53:55.960041 23057 sgd_solver.cpp:105] Iteration 13920, lr = 0.005
I0406 15:54:01.299922 23057 solver.cpp:218] Iteration 13932 (2.24726 iter/s, 5.33983s/12 iters), loss = 0.153259
I0406 15:54:01.299963 23057 solver.cpp:237]     Train net output #0: loss = 0.153259 (* 1 = 0.153259 loss)
I0406 15:54:01.299969 23057 sgd_solver.cpp:105] Iteration 13932, lr = 0.005
I0406 15:54:06.803536 23057 solver.cpp:218] Iteration 13944 (2.18043 iter/s, 5.50351s/12 iters), loss = 0.116076
I0406 15:54:06.803580 23057 solver.cpp:237]     Train net output #0: loss = 0.116076 (* 1 = 0.116076 loss)
I0406 15:54:06.803584 23057 sgd_solver.cpp:105] Iteration 13944, lr = 0.005
I0406 15:54:12.147668 23057 solver.cpp:218] Iteration 13956 (2.2455 iter/s, 5.34403s/12 iters), loss = 0.0375142
I0406 15:54:12.147711 23057 solver.cpp:237]     Train net output #0: loss = 0.0375141 (* 1 = 0.0375141 loss)
I0406 15:54:12.147717 23057 sgd_solver.cpp:105] Iteration 13956, lr = 0.005
I0406 15:54:13.224140 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:54:17.464246 23057 solver.cpp:218] Iteration 13968 (2.25713 iter/s, 5.31647s/12 iters), loss = 0.197723
I0406 15:54:17.464285 23057 solver.cpp:237]     Train net output #0: loss = 0.197723 (* 1 = 0.197723 loss)
I0406 15:54:17.464290 23057 sgd_solver.cpp:105] Iteration 13968, lr = 0.005
I0406 15:54:19.802642 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13974.caffemodel
I0406 15:54:22.790755 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13974.solverstate
I0406 15:54:26.589560 23057 solver.cpp:330] Iteration 13974, Testing net (#0)
I0406 15:54:26.589582 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:54:29.993304 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:54:30.858681 23057 solver.cpp:397]     Test net output #0: accuracy = 0.414216
I0406 15:54:30.858717 23057 solver.cpp:397]     Test net output #1: loss = 3.4105 (* 1 = 3.4105 loss)
I0406 15:54:32.863854 23057 solver.cpp:218] Iteration 13980 (0.779249 iter/s, 15.3994s/12 iters), loss = 0.0438326
I0406 15:54:32.863895 23057 solver.cpp:237]     Train net output #0: loss = 0.0438325 (* 1 = 0.0438325 loss)
I0406 15:54:32.863900 23057 sgd_solver.cpp:105] Iteration 13980, lr = 0.005
I0406 15:54:38.068974 23057 solver.cpp:218] Iteration 13992 (2.30547 iter/s, 5.20501s/12 iters), loss = 0.0693641
I0406 15:54:38.069020 23057 solver.cpp:237]     Train net output #0: loss = 0.069364 (* 1 = 0.069364 loss)
I0406 15:54:38.069026 23057 sgd_solver.cpp:105] Iteration 13992, lr = 0.005
I0406 15:54:43.440349 23057 solver.cpp:218] Iteration 14004 (2.23411 iter/s, 5.37127s/12 iters), loss = 0.12041
I0406 15:54:43.440403 23057 solver.cpp:237]     Train net output #0: loss = 0.12041 (* 1 = 0.12041 loss)
I0406 15:54:43.440413 23057 sgd_solver.cpp:105] Iteration 14004, lr = 0.005
I0406 15:54:48.678860 23057 solver.cpp:218] Iteration 14016 (2.29077 iter/s, 5.2384s/12 iters), loss = 0.206256
I0406 15:54:48.678900 23057 solver.cpp:237]     Train net output #0: loss = 0.206256 (* 1 = 0.206256 loss)
I0406 15:54:48.678905 23057 sgd_solver.cpp:105] Iteration 14016, lr = 0.005
I0406 15:54:53.775018 23057 solver.cpp:218] Iteration 14028 (2.35476 iter/s, 5.09606s/12 iters), loss = 0.117621
I0406 15:54:53.775107 23057 solver.cpp:237]     Train net output #0: loss = 0.117621 (* 1 = 0.117621 loss)
I0406 15:54:53.775113 23057 sgd_solver.cpp:105] Iteration 14028, lr = 0.005
I0406 15:54:59.068593 23057 solver.cpp:218] Iteration 14040 (2.26696 iter/s, 5.29342s/12 iters), loss = 0.121138
I0406 15:54:59.068639 23057 solver.cpp:237]     Train net output #0: loss = 0.121138 (* 1 = 0.121138 loss)
I0406 15:54:59.068645 23057 sgd_solver.cpp:105] Iteration 14040, lr = 0.005
I0406 15:55:04.428354 23057 solver.cpp:218] Iteration 14052 (2.23895 iter/s, 5.35966s/12 iters), loss = 0.133419
I0406 15:55:04.428395 23057 solver.cpp:237]     Train net output #0: loss = 0.133419 (* 1 = 0.133419 loss)
I0406 15:55:04.428401 23057 sgd_solver.cpp:105] Iteration 14052, lr = 0.005
I0406 15:55:07.725143 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:55:09.659332 23057 solver.cpp:218] Iteration 14064 (2.29407 iter/s, 5.23088s/12 iters), loss = 0.0863752
I0406 15:55:09.659370 23057 solver.cpp:237]     Train net output #0: loss = 0.0863751 (* 1 = 0.0863751 loss)
I0406 15:55:09.659376 23057 sgd_solver.cpp:105] Iteration 14064, lr = 0.005
I0406 15:55:14.435724 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14076.caffemodel
I0406 15:55:17.475508 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14076.solverstate
I0406 15:55:21.300297 23057 solver.cpp:330] Iteration 14076, Testing net (#0)
I0406 15:55:21.300319 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:55:24.820020 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:55:25.732632 23057 solver.cpp:397]     Test net output #0: accuracy = 0.431373
I0406 15:55:25.732663 23057 solver.cpp:397]     Test net output #1: loss = 3.42861 (* 1 = 3.42861 loss)
I0406 15:55:25.867458 23057 solver.cpp:218] Iteration 14076 (0.740378 iter/s, 16.2079s/12 iters), loss = 0.067533
I0406 15:55:25.867501 23057 solver.cpp:237]     Train net output #0: loss = 0.0675329 (* 1 = 0.0675329 loss)
I0406 15:55:25.867507 23057 sgd_solver.cpp:105] Iteration 14076, lr = 0.005
I0406 15:55:30.237876 23057 solver.cpp:218] Iteration 14088 (2.74579 iter/s, 4.37032s/12 iters), loss = 0.0953048
I0406 15:55:30.237937 23057 solver.cpp:237]     Train net output #0: loss = 0.0953047 (* 1 = 0.0953047 loss)
I0406 15:55:30.237947 23057 sgd_solver.cpp:105] Iteration 14088, lr = 0.005
I0406 15:55:35.801205 23057 solver.cpp:218] Iteration 14100 (2.15703 iter/s, 5.56321s/12 iters), loss = 0.0625489
I0406 15:55:35.801244 23057 solver.cpp:237]     Train net output #0: loss = 0.0625488 (* 1 = 0.0625488 loss)
I0406 15:55:35.801250 23057 sgd_solver.cpp:105] Iteration 14100, lr = 0.005
I0406 15:55:40.801808 23057 solver.cpp:218] Iteration 14112 (2.39976 iter/s, 5.0005s/12 iters), loss = 0.0237763
I0406 15:55:40.801853 23057 solver.cpp:237]     Train net output #0: loss = 0.0237762 (* 1 = 0.0237762 loss)
I0406 15:55:40.801859 23057 sgd_solver.cpp:105] Iteration 14112, lr = 0.005
I0406 15:55:45.985707 23057 solver.cpp:218] Iteration 14124 (2.31491 iter/s, 5.18379s/12 iters), loss = 0.0383146
I0406 15:55:45.985761 23057 solver.cpp:237]     Train net output #0: loss = 0.0383146 (* 1 = 0.0383146 loss)
I0406 15:55:45.985770 23057 sgd_solver.cpp:105] Iteration 14124, lr = 0.005
I0406 15:55:51.250864 23057 solver.cpp:218] Iteration 14136 (2.27918 iter/s, 5.26504s/12 iters), loss = 0.160123
I0406 15:55:51.250913 23057 solver.cpp:237]     Train net output #0: loss = 0.160122 (* 1 = 0.160122 loss)
I0406 15:55:51.250921 23057 sgd_solver.cpp:105] Iteration 14136, lr = 0.005
I0406 15:55:56.621438 23057 solver.cpp:218] Iteration 14148 (2.23444 iter/s, 5.37047s/12 iters), loss = 0.0952911
I0406 15:55:56.621570 23057 solver.cpp:237]     Train net output #0: loss = 0.0952911 (* 1 = 0.0952911 loss)
I0406 15:55:56.621578 23057 sgd_solver.cpp:105] Iteration 14148, lr = 0.005
I0406 15:56:01.897979 23057 solver.cpp:218] Iteration 14160 (2.2743 iter/s, 5.27635s/12 iters), loss = 0.129165
I0406 15:56:01.898025 23057 solver.cpp:237]     Train net output #0: loss = 0.129165 (* 1 = 0.129165 loss)
I0406 15:56:01.898030 23057 sgd_solver.cpp:105] Iteration 14160, lr = 0.005
I0406 15:56:02.161605 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:56:06.917652 23057 solver.cpp:218] Iteration 14172 (2.39065 iter/s, 5.01956s/12 iters), loss = 0.246879
I0406 15:56:06.917697 23057 solver.cpp:237]     Train net output #0: loss = 0.246879 (* 1 = 0.246879 loss)
I0406 15:56:06.917704 23057 sgd_solver.cpp:105] Iteration 14172, lr = 0.005
I0406 15:56:08.980906 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14178.caffemodel
I0406 15:56:12.041291 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14178.solverstate
I0406 15:56:16.165328 23057 solver.cpp:330] Iteration 14178, Testing net (#0)
I0406 15:56:16.165347 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:56:19.502017 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:56:20.515583 23057 solver.cpp:397]     Test net output #0: accuracy = 0.42402
I0406 15:56:20.515611 23057 solver.cpp:397]     Test net output #1: loss = 3.32904 (* 1 = 3.32904 loss)
I0406 15:56:22.292343 23057 solver.cpp:218] Iteration 14184 (0.780513 iter/s, 15.3745s/12 iters), loss = 0.0583298
I0406 15:56:22.292402 23057 solver.cpp:237]     Train net output #0: loss = 0.0583297 (* 1 = 0.0583297 loss)
I0406 15:56:22.292409 23057 sgd_solver.cpp:105] Iteration 14184, lr = 0.005
I0406 15:56:27.245510 23057 solver.cpp:218] Iteration 14196 (2.42275 iter/s, 4.95305s/12 iters), loss = 0.0565274
I0406 15:56:27.245604 23057 solver.cpp:237]     Train net output #0: loss = 0.0565273 (* 1 = 0.0565273 loss)
I0406 15:56:27.245610 23057 sgd_solver.cpp:105] Iteration 14196, lr = 0.005
I0406 15:56:32.511673 23057 solver.cpp:218] Iteration 14208 (2.27876 iter/s, 5.26601s/12 iters), loss = 0.0901867
I0406 15:56:32.511716 23057 solver.cpp:237]     Train net output #0: loss = 0.0901867 (* 1 = 0.0901867 loss)
I0406 15:56:32.511723 23057 sgd_solver.cpp:105] Iteration 14208, lr = 0.005
I0406 15:56:37.889783 23057 solver.cpp:218] Iteration 14220 (2.23131 iter/s, 5.37801s/12 iters), loss = 0.0154449
I0406 15:56:37.889835 23057 solver.cpp:237]     Train net output #0: loss = 0.0154448 (* 1 = 0.0154448 loss)
I0406 15:56:37.889843 23057 sgd_solver.cpp:105] Iteration 14220, lr = 0.005
I0406 15:56:43.266585 23057 solver.cpp:218] Iteration 14232 (2.23186 iter/s, 5.37669s/12 iters), loss = 0.13408
I0406 15:56:43.266636 23057 solver.cpp:237]     Train net output #0: loss = 0.13408 (* 1 = 0.13408 loss)
I0406 15:56:43.266644 23057 sgd_solver.cpp:105] Iteration 14232, lr = 0.005
I0406 15:56:48.591001 23057 solver.cpp:218] Iteration 14244 (2.25381 iter/s, 5.32431s/12 iters), loss = 0.12732
I0406 15:56:48.591044 23057 solver.cpp:237]     Train net output #0: loss = 0.12732 (* 1 = 0.12732 loss)
I0406 15:56:48.591050 23057 sgd_solver.cpp:105] Iteration 14244, lr = 0.005
I0406 15:56:53.945497 23057 solver.cpp:218] Iteration 14256 (2.24115 iter/s, 5.35439s/12 iters), loss = 0.177126
I0406 15:56:53.945540 23057 solver.cpp:237]     Train net output #0: loss = 0.177126 (* 1 = 0.177126 loss)
I0406 15:56:53.945546 23057 sgd_solver.cpp:105] Iteration 14256, lr = 0.005
I0406 15:56:56.442375 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:56:59.115170 23057 solver.cpp:218] Iteration 14268 (2.32128 iter/s, 5.16957s/12 iters), loss = 0.165831
I0406 15:56:59.115360 23057 solver.cpp:237]     Train net output #0: loss = 0.165831 (* 1 = 0.165831 loss)
I0406 15:56:59.115370 23057 sgd_solver.cpp:105] Iteration 14268, lr = 0.005
I0406 15:57:03.915674 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14280.caffemodel
I0406 15:57:07.386121 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14280.solverstate
I0406 15:57:11.134253 23057 solver.cpp:330] Iteration 14280, Testing net (#0)
I0406 15:57:11.134279 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:57:14.422564 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:57:15.439584 23057 solver.cpp:397]     Test net output #0: accuracy = 0.450368
I0406 15:57:15.439620 23057 solver.cpp:397]     Test net output #1: loss = 3.41177 (* 1 = 3.41177 loss)
I0406 15:57:15.575851 23057 solver.cpp:218] Iteration 14280 (0.729025 iter/s, 16.4604s/12 iters), loss = 0.066145
I0406 15:57:15.575906 23057 solver.cpp:237]     Train net output #0: loss = 0.0661449 (* 1 = 0.0661449 loss)
I0406 15:57:15.575917 23057 sgd_solver.cpp:105] Iteration 14280, lr = 0.005
I0406 15:57:19.839676 23057 solver.cpp:218] Iteration 14292 (2.81445 iter/s, 4.26372s/12 iters), loss = 0.0582169
I0406 15:57:19.839723 23057 solver.cpp:237]     Train net output #0: loss = 0.0582169 (* 1 = 0.0582169 loss)
I0406 15:57:19.839728 23057 sgd_solver.cpp:105] Iteration 14292, lr = 0.005
I0406 15:57:24.991492 23057 solver.cpp:218] Iteration 14304 (2.32932 iter/s, 5.15171s/12 iters), loss = 0.0232724
I0406 15:57:24.991534 23057 solver.cpp:237]     Train net output #0: loss = 0.0232723 (* 1 = 0.0232723 loss)
I0406 15:57:24.991540 23057 sgd_solver.cpp:105] Iteration 14304, lr = 0.005
I0406 15:57:30.400739 23057 solver.cpp:218] Iteration 14316 (2.21847 iter/s, 5.40914s/12 iters), loss = 0.0745064
I0406 15:57:30.400853 23057 solver.cpp:237]     Train net output #0: loss = 0.0745064 (* 1 = 0.0745064 loss)
I0406 15:57:30.400862 23057 sgd_solver.cpp:105] Iteration 14316, lr = 0.005
I0406 15:57:35.676316 23057 solver.cpp:218] Iteration 14328 (2.27471 iter/s, 5.2754s/12 iters), loss = 0.235471
I0406 15:57:35.676378 23057 solver.cpp:237]     Train net output #0: loss = 0.235471 (* 1 = 0.235471 loss)
I0406 15:57:35.676388 23057 sgd_solver.cpp:105] Iteration 14328, lr = 0.005
I0406 15:57:40.979171 23057 solver.cpp:218] Iteration 14340 (2.26298 iter/s, 5.30273s/12 iters), loss = 0.0940594
I0406 15:57:40.979238 23057 solver.cpp:237]     Train net output #0: loss = 0.0940594 (* 1 = 0.0940594 loss)
I0406 15:57:40.979246 23057 sgd_solver.cpp:105] Iteration 14340, lr = 0.005
I0406 15:57:46.268396 23057 solver.cpp:218] Iteration 14352 (2.26881 iter/s, 5.2891s/12 iters), loss = 0.0778992
I0406 15:57:46.268438 23057 solver.cpp:237]     Train net output #0: loss = 0.0778992 (* 1 = 0.0778992 loss)
I0406 15:57:46.268443 23057 sgd_solver.cpp:105] Iteration 14352, lr = 0.005
I0406 15:57:51.081909 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:57:51.465507 23057 solver.cpp:218] Iteration 14364 (2.30902 iter/s, 5.19701s/12 iters), loss = 0.0694394
I0406 15:57:51.465555 23057 solver.cpp:237]     Train net output #0: loss = 0.0694394 (* 1 = 0.0694394 loss)
I0406 15:57:51.465564 23057 sgd_solver.cpp:105] Iteration 14364, lr = 0.005
I0406 15:57:56.777501 23057 solver.cpp:218] Iteration 14376 (2.25909 iter/s, 5.31188s/12 iters), loss = 0.243069
I0406 15:57:56.777561 23057 solver.cpp:237]     Train net output #0: loss = 0.243069 (* 1 = 0.243069 loss)
I0406 15:57:56.777570 23057 sgd_solver.cpp:105] Iteration 14376, lr = 0.005
I0406 15:57:58.851539 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14382.caffemodel
I0406 15:58:02.152261 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14382.solverstate
I0406 15:58:05.893466 23057 solver.cpp:330] Iteration 14382, Testing net (#0)
I0406 15:58:05.893491 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:58:09.221971 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:58:10.242291 23057 solver.cpp:397]     Test net output #0: accuracy = 0.426471
I0406 15:58:10.242324 23057 solver.cpp:397]     Test net output #1: loss = 3.58851 (* 1 = 3.58851 loss)
I0406 15:58:12.015576 23057 solver.cpp:218] Iteration 14388 (0.787511 iter/s, 15.2379s/12 iters), loss = 0.0330146
I0406 15:58:12.015635 23057 solver.cpp:237]     Train net output #0: loss = 0.0330146 (* 1 = 0.0330146 loss)
I0406 15:58:12.015643 23057 sgd_solver.cpp:105] Iteration 14388, lr = 0.005
I0406 15:58:17.181468 23057 solver.cpp:218] Iteration 14400 (2.32298 iter/s, 5.16578s/12 iters), loss = 0.252283
I0406 15:58:17.181506 23057 solver.cpp:237]     Train net output #0: loss = 0.252283 (* 1 = 0.252283 loss)
I0406 15:58:17.181511 23057 sgd_solver.cpp:105] Iteration 14400, lr = 0.005
I0406 15:58:22.483389 23057 solver.cpp:218] Iteration 14412 (2.26337 iter/s, 5.30182s/12 iters), loss = 0.19014
I0406 15:58:22.483433 23057 solver.cpp:237]     Train net output #0: loss = 0.19014 (* 1 = 0.19014 loss)
I0406 15:58:22.483438 23057 sgd_solver.cpp:105] Iteration 14412, lr = 0.005
I0406 15:58:27.558985 23057 solver.cpp:218] Iteration 14424 (2.3643 iter/s, 5.0755s/12 iters), loss = 0.0683593
I0406 15:58:27.559026 23057 solver.cpp:237]     Train net output #0: loss = 0.0683592 (* 1 = 0.0683592 loss)
I0406 15:58:27.559031 23057 sgd_solver.cpp:105] Iteration 14424, lr = 0.005
I0406 15:58:32.511530 23057 solver.cpp:218] Iteration 14436 (2.42305 iter/s, 4.95244s/12 iters), loss = 0.123053
I0406 15:58:32.511656 23057 solver.cpp:237]     Train net output #0: loss = 0.123053 (* 1 = 0.123053 loss)
I0406 15:58:32.511664 23057 sgd_solver.cpp:105] Iteration 14436, lr = 0.005
I0406 15:58:37.739322 23057 solver.cpp:218] Iteration 14448 (2.2955 iter/s, 5.22762s/12 iters), loss = 0.151913
I0406 15:58:37.739359 23057 solver.cpp:237]     Train net output #0: loss = 0.151913 (* 1 = 0.151913 loss)
I0406 15:58:37.739365 23057 sgd_solver.cpp:105] Iteration 14448, lr = 0.005
I0406 15:58:42.851810 23057 solver.cpp:218] Iteration 14460 (2.34724 iter/s, 5.11239s/12 iters), loss = 0.148143
I0406 15:58:42.851855 23057 solver.cpp:237]     Train net output #0: loss = 0.148143 (* 1 = 0.148143 loss)
I0406 15:58:42.851861 23057 sgd_solver.cpp:105] Iteration 14460, lr = 0.005
I0406 15:58:44.716131 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:58:48.186132 23057 solver.cpp:218] Iteration 14472 (2.24963 iter/s, 5.33422s/12 iters), loss = 0.151242
I0406 15:58:48.186177 23057 solver.cpp:237]     Train net output #0: loss = 0.151242 (* 1 = 0.151242 loss)
I0406 15:58:48.186182 23057 sgd_solver.cpp:105] Iteration 14472, lr = 0.005
I0406 15:58:52.842489 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14484.caffemodel
I0406 15:58:55.887790 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14484.solverstate
I0406 15:58:59.781039 23057 solver.cpp:330] Iteration 14484, Testing net (#0)
I0406 15:58:59.781064 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:59:02.972671 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:59:04.155436 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422794
I0406 15:59:04.155472 23057 solver.cpp:397]     Test net output #1: loss = 3.56838 (* 1 = 3.56838 loss)
I0406 15:59:04.292191 23057 solver.cpp:218] Iteration 14484 (0.74507 iter/s, 16.1059s/12 iters), loss = 0.129001
I0406 15:59:04.292237 23057 solver.cpp:237]     Train net output #0: loss = 0.129001 (* 1 = 0.129001 loss)
I0406 15:59:04.292245 23057 sgd_solver.cpp:105] Iteration 14484, lr = 0.005
I0406 15:59:08.711520 23057 solver.cpp:218] Iteration 14496 (2.7154 iter/s, 4.41923s/12 iters), loss = 0.216896
I0406 15:59:08.711561 23057 solver.cpp:237]     Train net output #0: loss = 0.216896 (* 1 = 0.216896 loss)
I0406 15:59:08.711567 23057 sgd_solver.cpp:105] Iteration 14496, lr = 0.005
I0406 15:59:13.961370 23057 solver.cpp:218] Iteration 14508 (2.28582 iter/s, 5.24975s/12 iters), loss = 0.0730471
I0406 15:59:13.961414 23057 solver.cpp:237]     Train net output #0: loss = 0.0730471 (* 1 = 0.0730471 loss)
I0406 15:59:13.961421 23057 sgd_solver.cpp:105] Iteration 14508, lr = 0.005
I0406 15:59:19.003443 23057 solver.cpp:218] Iteration 14520 (2.38002 iter/s, 5.04197s/12 iters), loss = 0.160432
I0406 15:59:19.003501 23057 solver.cpp:237]     Train net output #0: loss = 0.160432 (* 1 = 0.160432 loss)
I0406 15:59:19.003511 23057 sgd_solver.cpp:105] Iteration 14520, lr = 0.005
I0406 15:59:24.223249 23057 solver.cpp:218] Iteration 14532 (2.29898 iter/s, 5.2197s/12 iters), loss = 0.129794
I0406 15:59:24.223285 23057 solver.cpp:237]     Train net output #0: loss = 0.129794 (* 1 = 0.129794 loss)
I0406 15:59:24.223290 23057 sgd_solver.cpp:105] Iteration 14532, lr = 0.005
I0406 15:59:29.512305 23057 solver.cpp:218] Iteration 14544 (2.26888 iter/s, 5.28896s/12 iters), loss = 0.172653
I0406 15:59:29.512339 23057 solver.cpp:237]     Train net output #0: loss = 0.172653 (* 1 = 0.172653 loss)
I0406 15:59:29.512346 23057 sgd_solver.cpp:105] Iteration 14544, lr = 0.005
I0406 15:59:34.803799 23057 solver.cpp:218] Iteration 14556 (2.26783 iter/s, 5.2914s/12 iters), loss = 0.190286
I0406 15:59:34.803890 23057 solver.cpp:237]     Train net output #0: loss = 0.190286 (* 1 = 0.190286 loss)
I0406 15:59:34.803897 23057 sgd_solver.cpp:105] Iteration 14556, lr = 0.005
I0406 15:59:38.878504 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 15:59:39.089376 23057 blocking_queue.cpp:49] Waiting for data
I0406 15:59:40.115048 23057 solver.cpp:218] Iteration 14568 (2.25942 iter/s, 5.3111s/12 iters), loss = 0.121614
I0406 15:59:40.115087 23057 solver.cpp:237]     Train net output #0: loss = 0.121614 (* 1 = 0.121614 loss)
I0406 15:59:40.115092 23057 sgd_solver.cpp:105] Iteration 14568, lr = 0.005
I0406 15:59:45.270478 23057 solver.cpp:218] Iteration 14580 (2.32769 iter/s, 5.15533s/12 iters), loss = 0.210673
I0406 15:59:45.270519 23057 solver.cpp:237]     Train net output #0: loss = 0.210673 (* 1 = 0.210673 loss)
I0406 15:59:45.270524 23057 sgd_solver.cpp:105] Iteration 14580, lr = 0.005
I0406 15:59:47.276684 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14586.caffemodel
I0406 15:59:50.370196 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14586.solverstate
I0406 15:59:56.123966 23057 solver.cpp:330] Iteration 14586, Testing net (#0)
I0406 15:59:56.123984 23057 net.cpp:676] Ignoring source layer train-data
I0406 15:59:59.460451 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:00:00.571038 23057 solver.cpp:397]     Test net output #0: accuracy = 0.429534
I0406 16:00:00.571069 23057 solver.cpp:397]     Test net output #1: loss = 3.42605 (* 1 = 3.42605 loss)
I0406 16:00:02.454527 23057 solver.cpp:218] Iteration 14592 (0.69833 iter/s, 17.1839s/12 iters), loss = 0.0590007
I0406 16:00:02.454571 23057 solver.cpp:237]     Train net output #0: loss = 0.0590007 (* 1 = 0.0590007 loss)
I0406 16:00:02.454576 23057 sgd_solver.cpp:105] Iteration 14592, lr = 0.005
I0406 16:00:07.757465 23057 solver.cpp:218] Iteration 14604 (2.26294 iter/s, 5.30284s/12 iters), loss = 0.211801
I0406 16:00:07.757582 23057 solver.cpp:237]     Train net output #0: loss = 0.211801 (* 1 = 0.211801 loss)
I0406 16:00:07.757591 23057 sgd_solver.cpp:105] Iteration 14604, lr = 0.005
I0406 16:00:12.905122 23057 solver.cpp:218] Iteration 14616 (2.33124 iter/s, 5.14748s/12 iters), loss = 0.0526505
I0406 16:00:12.905164 23057 solver.cpp:237]     Train net output #0: loss = 0.0526505 (* 1 = 0.0526505 loss)
I0406 16:00:12.905170 23057 sgd_solver.cpp:105] Iteration 14616, lr = 0.005
I0406 16:00:17.933221 23057 solver.cpp:218] Iteration 14628 (2.38664 iter/s, 5.028s/12 iters), loss = 0.11696
I0406 16:00:17.933266 23057 solver.cpp:237]     Train net output #0: loss = 0.11696 (* 1 = 0.11696 loss)
I0406 16:00:17.933274 23057 sgd_solver.cpp:105] Iteration 14628, lr = 0.005
I0406 16:00:23.225188 23057 solver.cpp:218] Iteration 14640 (2.26763 iter/s, 5.29186s/12 iters), loss = 0.037931
I0406 16:00:23.225241 23057 solver.cpp:237]     Train net output #0: loss = 0.037931 (* 1 = 0.037931 loss)
I0406 16:00:23.225250 23057 sgd_solver.cpp:105] Iteration 14640, lr = 0.005
I0406 16:00:28.436646 23057 solver.cpp:218] Iteration 14652 (2.30267 iter/s, 5.21135s/12 iters), loss = 0.0849994
I0406 16:00:28.436687 23057 solver.cpp:237]     Train net output #0: loss = 0.0849994 (* 1 = 0.0849994 loss)
I0406 16:00:28.436693 23057 sgd_solver.cpp:105] Iteration 14652, lr = 0.005
I0406 16:00:33.731341 23057 solver.cpp:218] Iteration 14664 (2.26646 iter/s, 5.29459s/12 iters), loss = 0.10893
I0406 16:00:33.731396 23057 solver.cpp:237]     Train net output #0: loss = 0.10893 (* 1 = 0.10893 loss)
I0406 16:00:33.731405 23057 sgd_solver.cpp:105] Iteration 14664, lr = 0.005
I0406 16:00:34.925549 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:00:38.989478 23057 solver.cpp:218] Iteration 14676 (2.28223 iter/s, 5.25803s/12 iters), loss = 0.167829
I0406 16:00:38.989576 23057 solver.cpp:237]     Train net output #0: loss = 0.167829 (* 1 = 0.167829 loss)
I0406 16:00:38.989583 23057 sgd_solver.cpp:105] Iteration 14676, lr = 0.005
I0406 16:00:43.746968 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14688.caffemodel
I0406 16:00:48.572031 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14688.solverstate
I0406 16:00:52.203261 23057 solver.cpp:330] Iteration 14688, Testing net (#0)
I0406 16:00:52.203284 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:00:55.491055 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:00:56.618552 23057 solver.cpp:397]     Test net output #0: accuracy = 0.426471
I0406 16:00:56.618587 23057 solver.cpp:397]     Test net output #1: loss = 3.42485 (* 1 = 3.42485 loss)
I0406 16:00:56.759819 23057 solver.cpp:218] Iteration 14688 (0.675292 iter/s, 17.7701s/12 iters), loss = 0.101581
I0406 16:00:56.759871 23057 solver.cpp:237]     Train net output #0: loss = 0.101581 (* 1 = 0.101581 loss)
I0406 16:00:56.759879 23057 sgd_solver.cpp:105] Iteration 14688, lr = 0.005
I0406 16:01:01.252032 23057 solver.cpp:218] Iteration 14700 (2.67135 iter/s, 4.49211s/12 iters), loss = 0.183219
I0406 16:01:01.252074 23057 solver.cpp:237]     Train net output #0: loss = 0.183219 (* 1 = 0.183219 loss)
I0406 16:01:01.252080 23057 sgd_solver.cpp:105] Iteration 14700, lr = 0.005
I0406 16:01:06.532184 23057 solver.cpp:218] Iteration 14712 (2.27271 iter/s, 5.28005s/12 iters), loss = 0.158836
I0406 16:01:06.532235 23057 solver.cpp:237]     Train net output #0: loss = 0.158836 (* 1 = 0.158836 loss)
I0406 16:01:06.532243 23057 sgd_solver.cpp:105] Iteration 14712, lr = 0.005
I0406 16:01:11.623615 23057 solver.cpp:218] Iteration 14724 (2.35695 iter/s, 5.09133s/12 iters), loss = 0.036114
I0406 16:01:11.623713 23057 solver.cpp:237]     Train net output #0: loss = 0.036114 (* 1 = 0.036114 loss)
I0406 16:01:11.623723 23057 sgd_solver.cpp:105] Iteration 14724, lr = 0.005
I0406 16:01:16.985291 23057 solver.cpp:218] Iteration 14736 (2.23817 iter/s, 5.36152s/12 iters), loss = 0.0271873
I0406 16:01:16.985337 23057 solver.cpp:237]     Train net output #0: loss = 0.0271872 (* 1 = 0.0271872 loss)
I0406 16:01:16.985344 23057 sgd_solver.cpp:105] Iteration 14736, lr = 0.005
I0406 16:01:22.317672 23057 solver.cpp:218] Iteration 14748 (2.25045 iter/s, 5.33228s/12 iters), loss = 0.181193
I0406 16:01:22.317715 23057 solver.cpp:237]     Train net output #0: loss = 0.181193 (* 1 = 0.181193 loss)
I0406 16:01:22.317721 23057 sgd_solver.cpp:105] Iteration 14748, lr = 0.005
I0406 16:01:27.691079 23057 solver.cpp:218] Iteration 14760 (2.23326 iter/s, 5.37331s/12 iters), loss = 0.124473
I0406 16:01:27.691129 23057 solver.cpp:237]     Train net output #0: loss = 0.124473 (* 1 = 0.124473 loss)
I0406 16:01:27.691138 23057 sgd_solver.cpp:105] Iteration 14760, lr = 0.005
I0406 16:01:30.937145 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:01:32.834128 23057 solver.cpp:218] Iteration 14772 (2.33329 iter/s, 5.14295s/12 iters), loss = 0.12497
I0406 16:01:32.834168 23057 solver.cpp:237]     Train net output #0: loss = 0.12497 (* 1 = 0.12497 loss)
I0406 16:01:32.834174 23057 sgd_solver.cpp:105] Iteration 14772, lr = 0.005
I0406 16:01:38.003818 23057 solver.cpp:218] Iteration 14784 (2.32127 iter/s, 5.16959s/12 iters), loss = 0.0946136
I0406 16:01:38.003866 23057 solver.cpp:237]     Train net output #0: loss = 0.0946136 (* 1 = 0.0946136 loss)
I0406 16:01:38.003872 23057 sgd_solver.cpp:105] Iteration 14784, lr = 0.005
I0406 16:01:40.130898 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14790.caffemodel
I0406 16:01:43.977524 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14790.solverstate
I0406 16:01:47.732980 23057 solver.cpp:330] Iteration 14790, Testing net (#0)
I0406 16:01:47.732998 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:01:50.901945 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:01:52.113533 23057 solver.cpp:397]     Test net output #0: accuracy = 0.419118
I0406 16:01:52.113564 23057 solver.cpp:397]     Test net output #1: loss = 3.34258 (* 1 = 3.34258 loss)
I0406 16:01:54.094692 23057 solver.cpp:218] Iteration 14796 (0.745773 iter/s, 16.0907s/12 iters), loss = 0.0848683
I0406 16:01:54.094743 23057 solver.cpp:237]     Train net output #0: loss = 0.0848682 (* 1 = 0.0848682 loss)
I0406 16:01:54.094750 23057 sgd_solver.cpp:105] Iteration 14796, lr = 0.005
I0406 16:01:59.232707 23057 solver.cpp:218] Iteration 14808 (2.33558 iter/s, 5.1379s/12 iters), loss = 0.114267
I0406 16:01:59.232758 23057 solver.cpp:237]     Train net output #0: loss = 0.114267 (* 1 = 0.114267 loss)
I0406 16:01:59.232766 23057 sgd_solver.cpp:105] Iteration 14808, lr = 0.005
I0406 16:02:04.234732 23057 solver.cpp:218] Iteration 14820 (2.39908 iter/s, 5.00192s/12 iters), loss = 0.073689
I0406 16:02:04.234784 23057 solver.cpp:237]     Train net output #0: loss = 0.0736889 (* 1 = 0.0736889 loss)
I0406 16:02:04.234792 23057 sgd_solver.cpp:105] Iteration 14820, lr = 0.005
I0406 16:02:09.482064 23057 solver.cpp:218] Iteration 14832 (2.28692 iter/s, 5.24723s/12 iters), loss = 0.0469061
I0406 16:02:09.482101 23057 solver.cpp:237]     Train net output #0: loss = 0.046906 (* 1 = 0.046906 loss)
I0406 16:02:09.482107 23057 sgd_solver.cpp:105] Iteration 14832, lr = 0.005
I0406 16:02:14.657555 23057 solver.cpp:218] Iteration 14844 (2.31866 iter/s, 5.1754s/12 iters), loss = 0.118995
I0406 16:02:14.657657 23057 solver.cpp:237]     Train net output #0: loss = 0.118995 (* 1 = 0.118995 loss)
I0406 16:02:14.657665 23057 sgd_solver.cpp:105] Iteration 14844, lr = 0.005
I0406 16:02:20.092675 23057 solver.cpp:218] Iteration 14856 (2.20793 iter/s, 5.43496s/12 iters), loss = 0.0270357
I0406 16:02:20.092725 23057 solver.cpp:237]     Train net output #0: loss = 0.0270357 (* 1 = 0.0270357 loss)
I0406 16:02:20.092731 23057 sgd_solver.cpp:105] Iteration 14856, lr = 0.005
I0406 16:02:25.322356 23057 solver.cpp:218] Iteration 14868 (2.29464 iter/s, 5.22957s/12 iters), loss = 0.204193
I0406 16:02:25.322400 23057 solver.cpp:237]     Train net output #0: loss = 0.204193 (* 1 = 0.204193 loss)
I0406 16:02:25.322407 23057 sgd_solver.cpp:105] Iteration 14868, lr = 0.005
I0406 16:02:25.609299 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:02:30.623183 23057 solver.cpp:218] Iteration 14880 (2.26384 iter/s, 5.30072s/12 iters), loss = 0.0397613
I0406 16:02:30.623226 23057 solver.cpp:237]     Train net output #0: loss = 0.0397612 (* 1 = 0.0397612 loss)
I0406 16:02:30.623232 23057 sgd_solver.cpp:105] Iteration 14880, lr = 0.005
I0406 16:02:35.270045 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14892.caffemodel
I0406 16:02:38.929379 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14892.solverstate
I0406 16:02:42.659791 23057 solver.cpp:330] Iteration 14892, Testing net (#0)
I0406 16:02:42.659813 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:02:45.727249 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:02:46.937732 23057 solver.cpp:397]     Test net output #0: accuracy = 0.428309
I0406 16:02:46.937772 23057 solver.cpp:397]     Test net output #1: loss = 3.46435 (* 1 = 3.46435 loss)
I0406 16:02:47.074831 23057 solver.cpp:218] Iteration 14892 (0.729418 iter/s, 16.4515s/12 iters), loss = 0.0241547
I0406 16:02:47.076411 23057 solver.cpp:237]     Train net output #0: loss = 0.0241547 (* 1 = 0.0241547 loss)
I0406 16:02:47.076424 23057 sgd_solver.cpp:105] Iteration 14892, lr = 0.005
I0406 16:02:51.483592 23057 solver.cpp:218] Iteration 14904 (2.72285 iter/s, 4.40714s/12 iters), loss = 0.0547392
I0406 16:02:51.483637 23057 solver.cpp:237]     Train net output #0: loss = 0.0547392 (* 1 = 0.0547392 loss)
I0406 16:02:51.483644 23057 sgd_solver.cpp:105] Iteration 14904, lr = 0.005
I0406 16:02:56.656121 23057 solver.cpp:218] Iteration 14916 (2.31999 iter/s, 5.17243s/12 iters), loss = 0.0823264
I0406 16:02:56.656163 23057 solver.cpp:237]     Train net output #0: loss = 0.0823263 (* 1 = 0.0823263 loss)
I0406 16:02:56.656169 23057 sgd_solver.cpp:105] Iteration 14916, lr = 0.005
I0406 16:03:02.049405 23057 solver.cpp:218] Iteration 14928 (2.22503 iter/s, 5.39318s/12 iters), loss = 0.0920043
I0406 16:03:02.049444 23057 solver.cpp:237]     Train net output #0: loss = 0.0920042 (* 1 = 0.0920042 loss)
I0406 16:03:02.049450 23057 sgd_solver.cpp:105] Iteration 14928, lr = 0.005
I0406 16:03:07.451308 23057 solver.cpp:218] Iteration 14940 (2.22148 iter/s, 5.4018s/12 iters), loss = 0.0967511
I0406 16:03:07.451350 23057 solver.cpp:237]     Train net output #0: loss = 0.096751 (* 1 = 0.096751 loss)
I0406 16:03:07.451356 23057 sgd_solver.cpp:105] Iteration 14940, lr = 0.005
I0406 16:03:12.908803 23057 solver.cpp:218] Iteration 14952 (2.19885 iter/s, 5.45739s/12 iters), loss = 0.180079
I0406 16:03:12.908852 23057 solver.cpp:237]     Train net output #0: loss = 0.180079 (* 1 = 0.180079 loss)
I0406 16:03:12.908860 23057 sgd_solver.cpp:105] Iteration 14952, lr = 0.005
I0406 16:03:18.142832 23057 solver.cpp:218] Iteration 14964 (2.29273 iter/s, 5.23393s/12 iters), loss = 0.274348
I0406 16:03:18.142932 23057 solver.cpp:237]     Train net output #0: loss = 0.274348 (* 1 = 0.274348 loss)
I0406 16:03:18.142940 23057 sgd_solver.cpp:105] Iteration 14964, lr = 0.005
I0406 16:03:20.740279 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:03:23.552116 23057 solver.cpp:218] Iteration 14976 (2.21847 iter/s, 5.40913s/12 iters), loss = 0.194711
I0406 16:03:23.552168 23057 solver.cpp:237]     Train net output #0: loss = 0.194711 (* 1 = 0.194711 loss)
I0406 16:03:23.552177 23057 sgd_solver.cpp:105] Iteration 14976, lr = 0.005
I0406 16:03:28.904496 23057 solver.cpp:218] Iteration 14988 (2.24204 iter/s, 5.35227s/12 iters), loss = 0.111824
I0406 16:03:28.904557 23057 solver.cpp:237]     Train net output #0: loss = 0.111824 (* 1 = 0.111824 loss)
I0406 16:03:28.904567 23057 sgd_solver.cpp:105] Iteration 14988, lr = 0.005
I0406 16:03:31.049580 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14994.caffemodel
I0406 16:03:35.687130 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14994.solverstate
I0406 16:03:39.603479 23057 solver.cpp:330] Iteration 14994, Testing net (#0)
I0406 16:03:39.603502 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:03:42.678895 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:03:43.936126 23057 solver.cpp:397]     Test net output #0: accuracy = 0.44424
I0406 16:03:43.936161 23057 solver.cpp:397]     Test net output #1: loss = 3.33423 (* 1 = 3.33423 loss)
I0406 16:03:45.885433 23057 solver.cpp:218] Iteration 15000 (0.706683 iter/s, 16.9807s/12 iters), loss = 0.168231
I0406 16:03:45.885481 23057 solver.cpp:237]     Train net output #0: loss = 0.168231 (* 1 = 0.168231 loss)
I0406 16:03:45.885488 23057 sgd_solver.cpp:105] Iteration 15000, lr = 0.005
I0406 16:03:51.165220 23057 solver.cpp:218] Iteration 15012 (2.27287 iter/s, 5.27968s/12 iters), loss = 0.0317371
I0406 16:03:51.165377 23057 solver.cpp:237]     Train net output #0: loss = 0.031737 (* 1 = 0.031737 loss)
I0406 16:03:51.165386 23057 sgd_solver.cpp:105] Iteration 15012, lr = 0.005
I0406 16:03:56.513363 23057 solver.cpp:218] Iteration 15024 (2.24386 iter/s, 5.34793s/12 iters), loss = 0.086513
I0406 16:03:56.513420 23057 solver.cpp:237]     Train net output #0: loss = 0.0865129 (* 1 = 0.0865129 loss)
I0406 16:03:56.513429 23057 sgd_solver.cpp:105] Iteration 15024, lr = 0.005
I0406 16:04:01.759634 23057 solver.cpp:218] Iteration 15036 (2.28739 iter/s, 5.24616s/12 iters), loss = 0.235961
I0406 16:04:01.759678 23057 solver.cpp:237]     Train net output #0: loss = 0.235961 (* 1 = 0.235961 loss)
I0406 16:04:01.759685 23057 sgd_solver.cpp:105] Iteration 15036, lr = 0.005
I0406 16:04:07.057857 23057 solver.cpp:218] Iteration 15048 (2.26496 iter/s, 5.29812s/12 iters), loss = 0.146893
I0406 16:04:07.057909 23057 solver.cpp:237]     Train net output #0: loss = 0.146893 (* 1 = 0.146893 loss)
I0406 16:04:07.057915 23057 sgd_solver.cpp:105] Iteration 15048, lr = 0.005
I0406 16:04:12.377104 23057 solver.cpp:218] Iteration 15060 (2.25601 iter/s, 5.31913s/12 iters), loss = 0.0530298
I0406 16:04:12.377167 23057 solver.cpp:237]     Train net output #0: loss = 0.0530297 (* 1 = 0.0530297 loss)
I0406 16:04:12.377177 23057 sgd_solver.cpp:105] Iteration 15060, lr = 0.005
I0406 16:04:17.370263 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:04:17.739365 23057 solver.cpp:218] Iteration 15072 (2.23791 iter/s, 5.36214s/12 iters), loss = 0.164985
I0406 16:04:17.739413 23057 solver.cpp:237]     Train net output #0: loss = 0.164985 (* 1 = 0.164985 loss)
I0406 16:04:17.739418 23057 sgd_solver.cpp:105] Iteration 15072, lr = 0.005
I0406 16:04:23.104488 23057 solver.cpp:218] Iteration 15084 (2.23671 iter/s, 5.36502s/12 iters), loss = 0.208093
I0406 16:04:23.104687 23057 solver.cpp:237]     Train net output #0: loss = 0.208093 (* 1 = 0.208093 loss)
I0406 16:04:23.104694 23057 sgd_solver.cpp:105] Iteration 15084, lr = 0.005
I0406 16:04:27.841848 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15096.caffemodel
I0406 16:04:32.318673 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15096.solverstate
I0406 16:04:36.135234 23057 solver.cpp:330] Iteration 15096, Testing net (#0)
I0406 16:04:36.135253 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:04:39.178663 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:04:40.466408 23057 solver.cpp:397]     Test net output #0: accuracy = 0.441789
I0406 16:04:40.466444 23057 solver.cpp:397]     Test net output #1: loss = 3.42801 (* 1 = 3.42801 loss)
I0406 16:04:40.610293 23057 solver.cpp:218] Iteration 15096 (0.6855 iter/s, 17.5055s/12 iters), loss = 0.153054
I0406 16:04:40.610332 23057 solver.cpp:237]     Train net output #0: loss = 0.153054 (* 1 = 0.153054 loss)
I0406 16:04:40.610338 23057 sgd_solver.cpp:105] Iteration 15096, lr = 0.005
I0406 16:04:44.992887 23057 solver.cpp:218] Iteration 15108 (2.73817 iter/s, 4.38249s/12 iters), loss = 0.166363
I0406 16:04:44.992942 23057 solver.cpp:237]     Train net output #0: loss = 0.166363 (* 1 = 0.166363 loss)
I0406 16:04:44.992951 23057 sgd_solver.cpp:105] Iteration 15108, lr = 0.005
I0406 16:04:50.105562 23057 solver.cpp:218] Iteration 15120 (2.34716 iter/s, 5.11256s/12 iters), loss = 0.162768
I0406 16:04:50.105610 23057 solver.cpp:237]     Train net output #0: loss = 0.162768 (* 1 = 0.162768 loss)
I0406 16:04:50.105616 23057 sgd_solver.cpp:105] Iteration 15120, lr = 0.005
I0406 16:04:55.285435 23057 solver.cpp:218] Iteration 15132 (2.3167 iter/s, 5.17977s/12 iters), loss = 0.0996586
I0406 16:04:55.285562 23057 solver.cpp:237]     Train net output #0: loss = 0.0996585 (* 1 = 0.0996585 loss)
I0406 16:04:55.285569 23057 sgd_solver.cpp:105] Iteration 15132, lr = 0.005
I0406 16:05:00.686632 23057 solver.cpp:218] Iteration 15144 (2.22181 iter/s, 5.40101s/12 iters), loss = 0.21219
I0406 16:05:00.686683 23057 solver.cpp:237]     Train net output #0: loss = 0.21219 (* 1 = 0.21219 loss)
I0406 16:05:00.686691 23057 sgd_solver.cpp:105] Iteration 15144, lr = 0.005
I0406 16:05:06.001708 23057 solver.cpp:218] Iteration 15156 (2.25778 iter/s, 5.31497s/12 iters), loss = 0.0232917
I0406 16:05:06.001758 23057 solver.cpp:237]     Train net output #0: loss = 0.0232916 (* 1 = 0.0232916 loss)
I0406 16:05:06.001765 23057 sgd_solver.cpp:105] Iteration 15156, lr = 0.005
I0406 16:05:11.283232 23057 solver.cpp:218] Iteration 15168 (2.27212 iter/s, 5.28141s/12 iters), loss = 0.111244
I0406 16:05:11.283293 23057 solver.cpp:237]     Train net output #0: loss = 0.111244 (* 1 = 0.111244 loss)
I0406 16:05:11.283301 23057 sgd_solver.cpp:105] Iteration 15168, lr = 0.005
I0406 16:05:13.201867 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:05:16.655059 23057 solver.cpp:218] Iteration 15180 (2.23393 iter/s, 5.37171s/12 iters), loss = 0.199225
I0406 16:05:16.655107 23057 solver.cpp:237]     Train net output #0: loss = 0.199225 (* 1 = 0.199225 loss)
I0406 16:05:16.655113 23057 sgd_solver.cpp:105] Iteration 15180, lr = 0.005
I0406 16:05:21.886162 23057 solver.cpp:218] Iteration 15192 (2.29402 iter/s, 5.231s/12 iters), loss = 0.0681788
I0406 16:05:21.886199 23057 solver.cpp:237]     Train net output #0: loss = 0.0681787 (* 1 = 0.0681787 loss)
I0406 16:05:21.886205 23057 sgd_solver.cpp:105] Iteration 15192, lr = 0.005
I0406 16:05:23.983078 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15198.caffemodel
I0406 16:05:28.344092 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15198.solverstate
I0406 16:05:31.944615 23057 solver.cpp:330] Iteration 15198, Testing net (#0)
I0406 16:05:31.944638 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:05:34.923756 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:05:36.267988 23057 solver.cpp:397]     Test net output #0: accuracy = 0.429534
I0406 16:05:36.268023 23057 solver.cpp:397]     Test net output #1: loss = 3.48161 (* 1 = 3.48161 loss)
I0406 16:05:38.121690 23057 solver.cpp:218] Iteration 15204 (0.739128 iter/s, 16.2353s/12 iters), loss = 0.0685662
I0406 16:05:38.121750 23057 solver.cpp:237]     Train net output #0: loss = 0.0685661 (* 1 = 0.0685661 loss)
I0406 16:05:38.121760 23057 sgd_solver.cpp:105] Iteration 15204, lr = 0.005
I0406 16:05:43.470044 23057 solver.cpp:218] Iteration 15216 (2.24373 iter/s, 5.34824s/12 iters), loss = 0.122423
I0406 16:05:43.470086 23057 solver.cpp:237]     Train net output #0: loss = 0.122423 (* 1 = 0.122423 loss)
I0406 16:05:43.470093 23057 sgd_solver.cpp:105] Iteration 15216, lr = 0.005
I0406 16:05:48.723536 23057 solver.cpp:218] Iteration 15228 (2.28424 iter/s, 5.25338s/12 iters), loss = 0.143447
I0406 16:05:48.723583 23057 solver.cpp:237]     Train net output #0: loss = 0.143447 (* 1 = 0.143447 loss)
I0406 16:05:48.723589 23057 sgd_solver.cpp:105] Iteration 15228, lr = 0.005
I0406 16:05:54.119593 23057 solver.cpp:218] Iteration 15240 (2.22389 iter/s, 5.39595s/12 iters), loss = 0.139017
I0406 16:05:54.119645 23057 solver.cpp:237]     Train net output #0: loss = 0.139016 (* 1 = 0.139016 loss)
I0406 16:05:54.119654 23057 sgd_solver.cpp:105] Iteration 15240, lr = 0.005
I0406 16:05:58.796567 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:05:59.349540 23057 solver.cpp:218] Iteration 15252 (2.29452 iter/s, 5.22984s/12 iters), loss = 0.145865
I0406 16:05:59.349581 23057 solver.cpp:237]     Train net output #0: loss = 0.145865 (* 1 = 0.145865 loss)
I0406 16:05:59.349586 23057 sgd_solver.cpp:105] Iteration 15252, lr = 0.005
I0406 16:06:04.302326 23057 solver.cpp:218] Iteration 15264 (2.42293 iter/s, 4.95269s/12 iters), loss = 0.0972483
I0406 16:06:04.302366 23057 solver.cpp:237]     Train net output #0: loss = 0.0972482 (* 1 = 0.0972482 loss)
I0406 16:06:04.302372 23057 sgd_solver.cpp:105] Iteration 15264, lr = 0.005
I0406 16:06:08.563541 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:06:09.725507 23057 solver.cpp:218] Iteration 15276 (2.21277 iter/s, 5.42308s/12 iters), loss = 0.11795
I0406 16:06:09.725551 23057 solver.cpp:237]     Train net output #0: loss = 0.117949 (* 1 = 0.117949 loss)
I0406 16:06:09.725558 23057 sgd_solver.cpp:105] Iteration 15276, lr = 0.005
I0406 16:06:14.924644 23057 solver.cpp:218] Iteration 15288 (2.30812 iter/s, 5.19903s/12 iters), loss = 0.103091
I0406 16:06:14.924695 23057 solver.cpp:237]     Train net output #0: loss = 0.103091 (* 1 = 0.103091 loss)
I0406 16:06:14.924701 23057 sgd_solver.cpp:105] Iteration 15288, lr = 0.005
I0406 16:06:19.624660 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15300.caffemodel
I0406 16:06:23.980777 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15300.solverstate
I0406 16:06:27.690559 23057 solver.cpp:330] Iteration 15300, Testing net (#0)
I0406 16:06:27.690575 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:06:30.828969 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:06:32.271944 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425245
I0406 16:06:32.271977 23057 solver.cpp:397]     Test net output #1: loss = 3.67551 (* 1 = 3.67551 loss)
I0406 16:06:32.406031 23057 solver.cpp:218] Iteration 15300 (0.686452 iter/s, 17.4812s/12 iters), loss = 0.119689
I0406 16:06:32.407594 23057 solver.cpp:237]     Train net output #0: loss = 0.119689 (* 1 = 0.119689 loss)
I0406 16:06:32.407604 23057 sgd_solver.cpp:105] Iteration 15300, lr = 0.005
I0406 16:06:36.573505 23057 solver.cpp:218] Iteration 15312 (2.88055 iter/s, 4.16587s/12 iters), loss = 0.0978656
I0406 16:06:36.573544 23057 solver.cpp:237]     Train net output #0: loss = 0.0978655 (* 1 = 0.0978655 loss)
I0406 16:06:36.573549 23057 sgd_solver.cpp:105] Iteration 15312, lr = 0.005
I0406 16:06:41.813480 23057 solver.cpp:218] Iteration 15324 (2.29013 iter/s, 5.23988s/12 iters), loss = 0.124061
I0406 16:06:41.813525 23057 solver.cpp:237]     Train net output #0: loss = 0.124061 (* 1 = 0.124061 loss)
I0406 16:06:41.813531 23057 sgd_solver.cpp:105] Iteration 15324, lr = 0.005
I0406 16:06:47.184440 23057 solver.cpp:218] Iteration 15336 (2.23428 iter/s, 5.37085s/12 iters), loss = 0.111886
I0406 16:06:47.184486 23057 solver.cpp:237]     Train net output #0: loss = 0.111886 (* 1 = 0.111886 loss)
I0406 16:06:47.184494 23057 sgd_solver.cpp:105] Iteration 15336, lr = 0.005
I0406 16:06:52.362949 23057 solver.cpp:218] Iteration 15348 (2.31732 iter/s, 5.1784s/12 iters), loss = 0.0776339
I0406 16:06:52.363008 23057 solver.cpp:237]     Train net output #0: loss = 0.0776338 (* 1 = 0.0776338 loss)
I0406 16:06:52.363016 23057 sgd_solver.cpp:105] Iteration 15348, lr = 0.005
I0406 16:06:57.710691 23057 solver.cpp:218] Iteration 15360 (2.24399 iter/s, 5.34762s/12 iters), loss = 0.141085
I0406 16:06:57.710752 23057 solver.cpp:237]     Train net output #0: loss = 0.141085 (* 1 = 0.141085 loss)
I0406 16:06:57.710760 23057 sgd_solver.cpp:105] Iteration 15360, lr = 0.005
I0406 16:07:03.081120 23057 solver.cpp:218] Iteration 15372 (2.23451 iter/s, 5.37031s/12 iters), loss = 0.104734
I0406 16:07:03.081245 23057 solver.cpp:237]     Train net output #0: loss = 0.104734 (* 1 = 0.104734 loss)
I0406 16:07:03.081252 23057 sgd_solver.cpp:105] Iteration 15372, lr = 0.005
I0406 16:07:04.218158 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:07:08.484038 23057 solver.cpp:218] Iteration 15384 (2.2211 iter/s, 5.40274s/12 iters), loss = 0.0910628
I0406 16:07:08.484079 23057 solver.cpp:237]     Train net output #0: loss = 0.0910627 (* 1 = 0.0910627 loss)
I0406 16:07:08.484086 23057 sgd_solver.cpp:105] Iteration 15384, lr = 0.005
I0406 16:07:13.755002 23057 solver.cpp:218] Iteration 15396 (2.27667 iter/s, 5.27086s/12 iters), loss = 0.0768058
I0406 16:07:13.755048 23057 solver.cpp:237]     Train net output #0: loss = 0.0768057 (* 1 = 0.0768057 loss)
I0406 16:07:13.755054 23057 sgd_solver.cpp:105] Iteration 15396, lr = 0.005
I0406 16:07:15.860538 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15402.caffemodel
I0406 16:07:21.415443 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15402.solverstate
I0406 16:07:26.389983 23057 solver.cpp:330] Iteration 15402, Testing net (#0)
I0406 16:07:26.390002 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:07:29.257892 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:07:30.674990 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425245
I0406 16:07:30.675021 23057 solver.cpp:397]     Test net output #1: loss = 3.30351 (* 1 = 3.30351 loss)
I0406 16:07:32.616310 23057 solver.cpp:218] Iteration 15408 (0.63623 iter/s, 18.8611s/12 iters), loss = 0.069251
I0406 16:07:32.616353 23057 solver.cpp:237]     Train net output #0: loss = 0.0692508 (* 1 = 0.0692508 loss)
I0406 16:07:32.616360 23057 sgd_solver.cpp:105] Iteration 15408, lr = 0.005
I0406 16:07:37.892853 23057 solver.cpp:218] Iteration 15420 (2.27426 iter/s, 5.27644s/12 iters), loss = 0.0933529
I0406 16:07:37.893074 23057 solver.cpp:237]     Train net output #0: loss = 0.0933528 (* 1 = 0.0933528 loss)
I0406 16:07:37.893085 23057 sgd_solver.cpp:105] Iteration 15420, lr = 0.005
I0406 16:07:43.081893 23057 solver.cpp:218] Iteration 15432 (2.31269 iter/s, 5.18877s/12 iters), loss = 0.0912759
I0406 16:07:43.081934 23057 solver.cpp:237]     Train net output #0: loss = 0.0912758 (* 1 = 0.0912758 loss)
I0406 16:07:43.081940 23057 sgd_solver.cpp:105] Iteration 15432, lr = 0.005
I0406 16:07:48.215301 23057 solver.cpp:218] Iteration 15444 (2.33767 iter/s, 5.13331s/12 iters), loss = 0.0532974
I0406 16:07:48.215340 23057 solver.cpp:237]     Train net output #0: loss = 0.0532973 (* 1 = 0.0532973 loss)
I0406 16:07:48.215345 23057 sgd_solver.cpp:105] Iteration 15444, lr = 0.005
I0406 16:07:53.512384 23057 solver.cpp:218] Iteration 15456 (2.26544 iter/s, 5.29698s/12 iters), loss = 0.0994684
I0406 16:07:53.512424 23057 solver.cpp:237]     Train net output #0: loss = 0.0994683 (* 1 = 0.0994683 loss)
I0406 16:07:53.512429 23057 sgd_solver.cpp:105] Iteration 15456, lr = 0.005
I0406 16:07:58.611907 23057 solver.cpp:218] Iteration 15468 (2.35321 iter/s, 5.09942s/12 iters), loss = 0.0317755
I0406 16:07:58.611954 23057 solver.cpp:237]     Train net output #0: loss = 0.0317754 (* 1 = 0.0317754 loss)
I0406 16:07:58.611963 23057 sgd_solver.cpp:105] Iteration 15468, lr = 0.005
I0406 16:08:01.662748 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:08:03.595757 23057 solver.cpp:218] Iteration 15480 (2.40783 iter/s, 4.98375s/12 iters), loss = 0.124632
I0406 16:08:03.595793 23057 solver.cpp:237]     Train net output #0: loss = 0.124632 (* 1 = 0.124632 loss)
I0406 16:08:03.595798 23057 sgd_solver.cpp:105] Iteration 15480, lr = 0.005
I0406 16:08:08.948839 23057 solver.cpp:218] Iteration 15492 (2.24174 iter/s, 5.35299s/12 iters), loss = 0.0777187
I0406 16:08:08.948935 23057 solver.cpp:237]     Train net output #0: loss = 0.0777186 (* 1 = 0.0777186 loss)
I0406 16:08:08.948941 23057 sgd_solver.cpp:105] Iteration 15492, lr = 0.005
I0406 16:08:13.747000 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15504.caffemodel
I0406 16:08:19.334439 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15504.solverstate
I0406 16:08:23.950924 23057 solver.cpp:330] Iteration 15504, Testing net (#0)
I0406 16:08:23.950942 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:08:26.781230 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:08:28.273247 23057 solver.cpp:397]     Test net output #0: accuracy = 0.44424
I0406 16:08:28.273283 23057 solver.cpp:397]     Test net output #1: loss = 3.43453 (* 1 = 3.43453 loss)
I0406 16:08:28.412791 23057 solver.cpp:218] Iteration 15504 (0.616533 iter/s, 19.4637s/12 iters), loss = 0.125145
I0406 16:08:28.412840 23057 solver.cpp:237]     Train net output #0: loss = 0.125145 (* 1 = 0.125145 loss)
I0406 16:08:28.412847 23057 sgd_solver.cpp:105] Iteration 15504, lr = 0.005
I0406 16:08:32.606582 23057 solver.cpp:218] Iteration 15516 (2.86144 iter/s, 4.1937s/12 iters), loss = 0.152024
I0406 16:08:32.606621 23057 solver.cpp:237]     Train net output #0: loss = 0.152023 (* 1 = 0.152023 loss)
I0406 16:08:32.606626 23057 sgd_solver.cpp:105] Iteration 15516, lr = 0.005
I0406 16:08:37.645956 23057 solver.cpp:218] Iteration 15528 (2.38129 iter/s, 5.03928s/12 iters), loss = 0.122142
I0406 16:08:37.645994 23057 solver.cpp:237]     Train net output #0: loss = 0.122141 (* 1 = 0.122141 loss)
I0406 16:08:37.646000 23057 sgd_solver.cpp:105] Iteration 15528, lr = 0.005
I0406 16:08:42.869350 23057 solver.cpp:218] Iteration 15540 (2.2974 iter/s, 5.2233s/12 iters), loss = 0.131159
I0406 16:08:42.869483 23057 solver.cpp:237]     Train net output #0: loss = 0.131159 (* 1 = 0.131159 loss)
I0406 16:08:42.869491 23057 sgd_solver.cpp:105] Iteration 15540, lr = 0.005
I0406 16:08:48.085974 23057 solver.cpp:218] Iteration 15552 (2.30042 iter/s, 5.21643s/12 iters), loss = 0.0942874
I0406 16:08:48.086021 23057 solver.cpp:237]     Train net output #0: loss = 0.0942872 (* 1 = 0.0942872 loss)
I0406 16:08:48.086028 23057 sgd_solver.cpp:105] Iteration 15552, lr = 0.005
I0406 16:08:53.379283 23057 solver.cpp:218] Iteration 15564 (2.26706 iter/s, 5.2932s/12 iters), loss = 0.0871706
I0406 16:08:53.379326 23057 solver.cpp:237]     Train net output #0: loss = 0.0871705 (* 1 = 0.0871705 loss)
I0406 16:08:53.379333 23057 sgd_solver.cpp:105] Iteration 15564, lr = 0.005
I0406 16:08:58.449749 23057 solver.cpp:218] Iteration 15576 (2.36669 iter/s, 5.07037s/12 iters), loss = 0.0944468
I0406 16:08:58.449808 23057 solver.cpp:237]     Train net output #0: loss = 0.0944467 (* 1 = 0.0944467 loss)
I0406 16:08:58.449817 23057 sgd_solver.cpp:105] Iteration 15576, lr = 0.005
I0406 16:08:58.919518 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:09:03.806289 23057 solver.cpp:218] Iteration 15588 (2.2403 iter/s, 5.35643s/12 iters), loss = 0.0655271
I0406 16:09:03.806329 23057 solver.cpp:237]     Train net output #0: loss = 0.0655269 (* 1 = 0.0655269 loss)
I0406 16:09:03.806334 23057 sgd_solver.cpp:105] Iteration 15588, lr = 0.005
I0406 16:09:08.965023 23057 solver.cpp:218] Iteration 15600 (2.3262 iter/s, 5.15864s/12 iters), loss = 0.120956
I0406 16:09:08.965068 23057 solver.cpp:237]     Train net output #0: loss = 0.120956 (* 1 = 0.120956 loss)
I0406 16:09:08.965076 23057 sgd_solver.cpp:105] Iteration 15600, lr = 0.005
I0406 16:09:11.009632 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15606.caffemodel
I0406 16:09:15.804540 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15606.solverstate
I0406 16:09:19.858453 23057 solver.cpp:330] Iteration 15606, Testing net (#0)
I0406 16:09:19.858471 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:09:22.752604 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:09:24.308971 23057 solver.cpp:397]     Test net output #0: accuracy = 0.435662
I0406 16:09:24.309000 23057 solver.cpp:397]     Test net output #1: loss = 3.36377 (* 1 = 3.36377 loss)
I0406 16:09:26.255786 23057 solver.cpp:218] Iteration 15612 (0.69402 iter/s, 17.2906s/12 iters), loss = 0.0644636
I0406 16:09:26.255831 23057 solver.cpp:237]     Train net output #0: loss = 0.0644635 (* 1 = 0.0644635 loss)
I0406 16:09:26.255837 23057 sgd_solver.cpp:105] Iteration 15612, lr = 0.005
I0406 16:09:31.531729 23057 solver.cpp:218] Iteration 15624 (2.27452 iter/s, 5.27584s/12 iters), loss = 0.0876402
I0406 16:09:31.531766 23057 solver.cpp:237]     Train net output #0: loss = 0.08764 (* 1 = 0.08764 loss)
I0406 16:09:31.531772 23057 sgd_solver.cpp:105] Iteration 15624, lr = 0.005
I0406 16:09:36.828238 23057 solver.cpp:218] Iteration 15636 (2.26569 iter/s, 5.29641s/12 iters), loss = 0.177928
I0406 16:09:36.828279 23057 solver.cpp:237]     Train net output #0: loss = 0.177928 (* 1 = 0.177928 loss)
I0406 16:09:36.828285 23057 sgd_solver.cpp:105] Iteration 15636, lr = 0.005
I0406 16:09:42.173122 23057 solver.cpp:218] Iteration 15648 (2.24518 iter/s, 5.34478s/12 iters), loss = 0.163836
I0406 16:09:42.173179 23057 solver.cpp:237]     Train net output #0: loss = 0.163836 (* 1 = 0.163836 loss)
I0406 16:09:42.173189 23057 sgd_solver.cpp:105] Iteration 15648, lr = 0.005
I0406 16:09:47.357206 23057 solver.cpp:218] Iteration 15660 (2.31483 iter/s, 5.18397s/12 iters), loss = 0.177656
I0406 16:09:47.357370 23057 solver.cpp:237]     Train net output #0: loss = 0.177656 (* 1 = 0.177656 loss)
I0406 16:09:47.357378 23057 sgd_solver.cpp:105] Iteration 15660, lr = 0.005
I0406 16:09:52.610575 23057 solver.cpp:218] Iteration 15672 (2.28434 iter/s, 5.25315s/12 iters), loss = 0.157116
I0406 16:09:52.610612 23057 solver.cpp:237]     Train net output #0: loss = 0.157116 (* 1 = 0.157116 loss)
I0406 16:09:52.610618 23057 sgd_solver.cpp:105] Iteration 15672, lr = 0.005
I0406 16:09:55.498071 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:09:58.013581 23057 solver.cpp:218] Iteration 15684 (2.22103 iter/s, 5.40291s/12 iters), loss = 0.174695
I0406 16:09:58.013623 23057 solver.cpp:237]     Train net output #0: loss = 0.174695 (* 1 = 0.174695 loss)
I0406 16:09:58.013630 23057 sgd_solver.cpp:105] Iteration 15684, lr = 0.005
I0406 16:10:03.351063 23057 solver.cpp:218] Iteration 15696 (2.24829 iter/s, 5.33738s/12 iters), loss = 0.100496
I0406 16:10:03.351102 23057 solver.cpp:237]     Train net output #0: loss = 0.100496 (* 1 = 0.100496 loss)
I0406 16:10:03.351109 23057 sgd_solver.cpp:105] Iteration 15696, lr = 0.005
I0406 16:10:08.107798 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15708.caffemodel
I0406 16:10:12.466718 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15708.solverstate
I0406 16:10:16.336282 23057 solver.cpp:330] Iteration 15708, Testing net (#0)
I0406 16:10:16.336302 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:10:19.120028 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:10:20.671916 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425858
I0406 16:10:20.671945 23057 solver.cpp:397]     Test net output #1: loss = 3.53796 (* 1 = 3.53796 loss)
I0406 16:10:20.811101 23057 solver.cpp:218] Iteration 15708 (0.687291 iter/s, 17.4598s/12 iters), loss = 0.16076
I0406 16:10:20.811141 23057 solver.cpp:237]     Train net output #0: loss = 0.16076 (* 1 = 0.16076 loss)
I0406 16:10:20.811147 23057 sgd_solver.cpp:105] Iteration 15708, lr = 0.005
I0406 16:10:24.938282 23057 solver.cpp:218] Iteration 15720 (2.90762 iter/s, 4.12709s/12 iters), loss = 0.070845
I0406 16:10:24.938321 23057 solver.cpp:237]     Train net output #0: loss = 0.0708448 (* 1 = 0.0708448 loss)
I0406 16:10:24.938326 23057 sgd_solver.cpp:105] Iteration 15720, lr = 0.005
I0406 16:10:30.268537 23057 solver.cpp:218] Iteration 15732 (2.25134 iter/s, 5.33015s/12 iters), loss = 0.189944
I0406 16:10:30.268581 23057 solver.cpp:237]     Train net output #0: loss = 0.189944 (* 1 = 0.189944 loss)
I0406 16:10:30.268589 23057 sgd_solver.cpp:105] Iteration 15732, lr = 0.005
I0406 16:10:35.587841 23057 solver.cpp:218] Iteration 15744 (2.25598 iter/s, 5.3192s/12 iters), loss = 0.158001
I0406 16:10:35.587894 23057 solver.cpp:237]     Train net output #0: loss = 0.158001 (* 1 = 0.158001 loss)
I0406 16:10:35.587903 23057 sgd_solver.cpp:105] Iteration 15744, lr = 0.005
I0406 16:10:41.035712 23057 solver.cpp:218] Iteration 15756 (2.20274 iter/s, 5.44776s/12 iters), loss = 0.0936967
I0406 16:10:41.035755 23057 solver.cpp:237]     Train net output #0: loss = 0.0936965 (* 1 = 0.0936965 loss)
I0406 16:10:41.035761 23057 sgd_solver.cpp:105] Iteration 15756, lr = 0.005
I0406 16:10:46.205138 23057 solver.cpp:218] Iteration 15768 (2.32139 iter/s, 5.16933s/12 iters), loss = 0.0981743
I0406 16:10:46.205179 23057 solver.cpp:237]     Train net output #0: loss = 0.0981741 (* 1 = 0.0981741 loss)
I0406 16:10:46.205186 23057 sgd_solver.cpp:105] Iteration 15768, lr = 0.005
I0406 16:10:51.204749 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:10:51.538486 23057 solver.cpp:218] Iteration 15780 (2.25004 iter/s, 5.33325s/12 iters), loss = 0.0245029
I0406 16:10:51.538527 23057 solver.cpp:237]     Train net output #0: loss = 0.0245026 (* 1 = 0.0245026 loss)
I0406 16:10:51.538534 23057 sgd_solver.cpp:105] Iteration 15780, lr = 0.005
I0406 16:10:56.735947 23057 solver.cpp:218] Iteration 15792 (2.30886 iter/s, 5.19736s/12 iters), loss = 0.122162
I0406 16:10:56.735991 23057 solver.cpp:237]     Train net output #0: loss = 0.122162 (* 1 = 0.122162 loss)
I0406 16:10:56.735997 23057 sgd_solver.cpp:105] Iteration 15792, lr = 0.005
I0406 16:11:01.730474 23057 solver.cpp:218] Iteration 15804 (2.40268 iter/s, 4.99442s/12 iters), loss = 0.0839824
I0406 16:11:01.730518 23057 solver.cpp:237]     Train net output #0: loss = 0.0839822 (* 1 = 0.0839822 loss)
I0406 16:11:01.730525 23057 sgd_solver.cpp:105] Iteration 15804, lr = 0.005
I0406 16:11:03.918802 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15810.caffemodel
I0406 16:11:08.283190 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15810.solverstate
I0406 16:11:12.024610 23057 solver.cpp:330] Iteration 15810, Testing net (#0)
I0406 16:11:12.024629 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:11:14.780704 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:11:16.354391 23057 solver.cpp:397]     Test net output #0: accuracy = 0.401961
I0406 16:11:16.354426 23057 solver.cpp:397]     Test net output #1: loss = 3.50275 (* 1 = 3.50275 loss)
I0406 16:11:18.202069 23057 solver.cpp:218] Iteration 15816 (0.728535 iter/s, 16.4714s/12 iters), loss = 0.127413
I0406 16:11:18.202124 23057 solver.cpp:237]     Train net output #0: loss = 0.127413 (* 1 = 0.127413 loss)
I0406 16:11:18.202132 23057 sgd_solver.cpp:105] Iteration 15816, lr = 0.005
I0406 16:11:23.515947 23057 solver.cpp:218] Iteration 15828 (2.25829 iter/s, 5.31377s/12 iters), loss = 0.0652149
I0406 16:11:23.516032 23057 solver.cpp:237]     Train net output #0: loss = 0.0652147 (* 1 = 0.0652147 loss)
I0406 16:11:23.516039 23057 sgd_solver.cpp:105] Iteration 15828, lr = 0.005
I0406 16:11:28.333971 23057 solver.cpp:218] Iteration 15840 (2.49072 iter/s, 4.81789s/12 iters), loss = 0.156085
I0406 16:11:28.334004 23057 solver.cpp:237]     Train net output #0: loss = 0.156085 (* 1 = 0.156085 loss)
I0406 16:11:28.334009 23057 sgd_solver.cpp:105] Iteration 15840, lr = 0.005
I0406 16:11:33.560429 23057 solver.cpp:218] Iteration 15852 (2.29605 iter/s, 5.22636s/12 iters), loss = 0.179103
I0406 16:11:33.560473 23057 solver.cpp:237]     Train net output #0: loss = 0.179103 (* 1 = 0.179103 loss)
I0406 16:11:33.560482 23057 sgd_solver.cpp:105] Iteration 15852, lr = 0.005
I0406 16:11:38.794190 23057 solver.cpp:218] Iteration 15864 (2.29285 iter/s, 5.23365s/12 iters), loss = 0.14053
I0406 16:11:38.794245 23057 solver.cpp:237]     Train net output #0: loss = 0.14053 (* 1 = 0.14053 loss)
I0406 16:11:38.794252 23057 sgd_solver.cpp:105] Iteration 15864, lr = 0.005
I0406 16:11:43.857573 23057 solver.cpp:218] Iteration 15876 (2.37001 iter/s, 5.06327s/12 iters), loss = 0.115557
I0406 16:11:43.857617 23057 solver.cpp:237]     Train net output #0: loss = 0.115557 (* 1 = 0.115557 loss)
I0406 16:11:43.857625 23057 sgd_solver.cpp:105] Iteration 15876, lr = 0.005
I0406 16:11:45.760742 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:11:49.037214 23057 solver.cpp:218] Iteration 15888 (2.31681 iter/s, 5.17954s/12 iters), loss = 0.11519
I0406 16:11:49.037266 23057 solver.cpp:237]     Train net output #0: loss = 0.11519 (* 1 = 0.11519 loss)
I0406 16:11:49.037274 23057 sgd_solver.cpp:105] Iteration 15888, lr = 0.005
I0406 16:11:54.286060 23057 solver.cpp:218] Iteration 15900 (2.28626 iter/s, 5.24874s/12 iters), loss = 0.128919
I0406 16:11:54.286196 23057 solver.cpp:237]     Train net output #0: loss = 0.128919 (* 1 = 0.128919 loss)
I0406 16:11:54.286203 23057 sgd_solver.cpp:105] Iteration 15900, lr = 0.005
I0406 16:11:58.867578 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15912.caffemodel
I0406 16:12:03.547298 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15912.solverstate
I0406 16:12:07.601191 23057 solver.cpp:330] Iteration 15912, Testing net (#0)
I0406 16:12:07.601212 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:12:10.345665 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:12:11.995894 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425245
I0406 16:12:11.995923 23057 solver.cpp:397]     Test net output #1: loss = 3.51497 (* 1 = 3.51497 loss)
I0406 16:12:12.136296 23057 solver.cpp:218] Iteration 15912 (0.672271 iter/s, 17.8499s/12 iters), loss = 0.0767464
I0406 16:12:12.136349 23057 solver.cpp:237]     Train net output #0: loss = 0.0767462 (* 1 = 0.0767462 loss)
I0406 16:12:12.136358 23057 sgd_solver.cpp:105] Iteration 15912, lr = 0.005
I0406 16:12:16.506207 23057 solver.cpp:218] Iteration 15924 (2.74612 iter/s, 4.3698s/12 iters), loss = 0.13172
I0406 16:12:16.506268 23057 solver.cpp:237]     Train net output #0: loss = 0.13172 (* 1 = 0.13172 loss)
I0406 16:12:16.506275 23057 sgd_solver.cpp:105] Iteration 15924, lr = 0.005
I0406 16:12:21.482539 23057 solver.cpp:218] Iteration 15936 (2.41147 iter/s, 4.97622s/12 iters), loss = 0.102611
I0406 16:12:21.482594 23057 solver.cpp:237]     Train net output #0: loss = 0.10261 (* 1 = 0.10261 loss)
I0406 16:12:21.482602 23057 sgd_solver.cpp:105] Iteration 15936, lr = 0.005
I0406 16:12:21.482858 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:12:26.737053 23057 solver.cpp:218] Iteration 15948 (2.2838 iter/s, 5.2544s/12 iters), loss = 0.18863
I0406 16:12:26.737181 23057 solver.cpp:237]     Train net output #0: loss = 0.18863 (* 1 = 0.18863 loss)
I0406 16:12:26.737190 23057 sgd_solver.cpp:105] Iteration 15948, lr = 0.005
I0406 16:12:31.802909 23057 solver.cpp:218] Iteration 15960 (2.36889 iter/s, 5.06567s/12 iters), loss = 0.0201319
I0406 16:12:31.802973 23057 solver.cpp:237]     Train net output #0: loss = 0.0201316 (* 1 = 0.0201316 loss)
I0406 16:12:31.802983 23057 sgd_solver.cpp:105] Iteration 15960, lr = 0.005
I0406 16:12:37.068935 23057 solver.cpp:218] Iteration 15972 (2.27881 iter/s, 5.2659s/12 iters), loss = 0.0378406
I0406 16:12:37.068982 23057 solver.cpp:237]     Train net output #0: loss = 0.0378403 (* 1 = 0.0378403 loss)
I0406 16:12:37.068989 23057 sgd_solver.cpp:105] Iteration 15972, lr = 0.005
I0406 16:12:41.309162 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:12:42.447072 23057 solver.cpp:218] Iteration 15984 (2.2313 iter/s, 5.37803s/12 iters), loss = 0.110112
I0406 16:12:42.447119 23057 solver.cpp:237]     Train net output #0: loss = 0.110112 (* 1 = 0.110112 loss)
I0406 16:12:42.447125 23057 sgd_solver.cpp:105] Iteration 15984, lr = 0.005
I0406 16:12:47.719022 23057 solver.cpp:218] Iteration 15996 (2.27625 iter/s, 5.27184s/12 iters), loss = 0.177227
I0406 16:12:47.719079 23057 solver.cpp:237]     Train net output #0: loss = 0.177227 (* 1 = 0.177227 loss)
I0406 16:12:47.719087 23057 sgd_solver.cpp:105] Iteration 15996, lr = 0.005
I0406 16:12:52.879650 23057 solver.cpp:218] Iteration 16008 (2.32535 iter/s, 5.16052s/12 iters), loss = 0.0260225
I0406 16:12:52.879686 23057 solver.cpp:237]     Train net output #0: loss = 0.0260223 (* 1 = 0.0260223 loss)
I0406 16:12:52.879691 23057 sgd_solver.cpp:105] Iteration 16008, lr = 0.005
I0406 16:12:55.104053 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16014.caffemodel
I0406 16:13:00.148985 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16014.solverstate
I0406 16:13:04.463485 23057 solver.cpp:330] Iteration 16014, Testing net (#0)
I0406 16:13:04.463505 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:13:07.187451 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:13:08.820518 23057 solver.cpp:397]     Test net output #0: accuracy = 0.424632
I0406 16:13:08.820551 23057 solver.cpp:397]     Test net output #1: loss = 3.5666 (* 1 = 3.5666 loss)
I0406 16:13:10.905357 23057 solver.cpp:218] Iteration 16020 (0.665723 iter/s, 18.0255s/12 iters), loss = 0.0736877
I0406 16:13:10.905400 23057 solver.cpp:237]     Train net output #0: loss = 0.0736875 (* 1 = 0.0736875 loss)
I0406 16:13:10.905406 23057 sgd_solver.cpp:105] Iteration 16020, lr = 0.005
I0406 16:13:16.034556 23057 solver.cpp:218] Iteration 16032 (2.33959 iter/s, 5.1291s/12 iters), loss = 0.217214
I0406 16:13:16.034605 23057 solver.cpp:237]     Train net output #0: loss = 0.217214 (* 1 = 0.217214 loss)
I0406 16:13:16.034613 23057 sgd_solver.cpp:105] Iteration 16032, lr = 0.005
I0406 16:13:21.423830 23057 solver.cpp:218] Iteration 16044 (2.22669 iter/s, 5.38916s/12 iters), loss = 0.197743
I0406 16:13:21.423875 23057 solver.cpp:237]     Train net output #0: loss = 0.197743 (* 1 = 0.197743 loss)
I0406 16:13:21.423883 23057 sgd_solver.cpp:105] Iteration 16044, lr = 0.005
I0406 16:13:26.611532 23057 solver.cpp:218] Iteration 16056 (2.31321 iter/s, 5.1876s/12 iters), loss = 0.0649257
I0406 16:13:26.611583 23057 solver.cpp:237]     Train net output #0: loss = 0.0649254 (* 1 = 0.0649254 loss)
I0406 16:13:26.611591 23057 sgd_solver.cpp:105] Iteration 16056, lr = 0.005
I0406 16:13:31.851749 23057 solver.cpp:218] Iteration 16068 (2.29003 iter/s, 5.24011s/12 iters), loss = 0.0719328
I0406 16:13:31.851838 23057 solver.cpp:237]     Train net output #0: loss = 0.0719326 (* 1 = 0.0719326 loss)
I0406 16:13:31.851845 23057 sgd_solver.cpp:105] Iteration 16068, lr = 0.005
I0406 16:13:36.734601 23057 solver.cpp:218] Iteration 16080 (2.45765 iter/s, 4.88271s/12 iters), loss = 0.0863305
I0406 16:13:36.734643 23057 solver.cpp:237]     Train net output #0: loss = 0.0863303 (* 1 = 0.0863303 loss)
I0406 16:13:36.734650 23057 sgd_solver.cpp:105] Iteration 16080, lr = 0.005
I0406 16:13:37.785830 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:13:41.934716 23057 solver.cpp:218] Iteration 16092 (2.30769 iter/s, 5.20001s/12 iters), loss = 0.0339916
I0406 16:13:41.934762 23057 solver.cpp:237]     Train net output #0: loss = 0.0339914 (* 1 = 0.0339914 loss)
I0406 16:13:41.934767 23057 sgd_solver.cpp:105] Iteration 16092, lr = 0.005
I0406 16:13:47.097797 23057 solver.cpp:218] Iteration 16104 (2.32424 iter/s, 5.16298s/12 iters), loss = 0.0575677
I0406 16:13:47.097841 23057 solver.cpp:237]     Train net output #0: loss = 0.0575675 (* 1 = 0.0575675 loss)
I0406 16:13:47.097846 23057 sgd_solver.cpp:105] Iteration 16104, lr = 0.005
I0406 16:13:51.604100 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16116.caffemodel
I0406 16:13:56.129966 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16116.solverstate
I0406 16:14:00.041589 23057 solver.cpp:330] Iteration 16116, Testing net (#0)
I0406 16:14:00.041616 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:14:02.620682 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:14:04.328163 23057 solver.cpp:397]     Test net output #0: accuracy = 0.412377
I0406 16:14:04.328200 23057 solver.cpp:397]     Test net output #1: loss = 3.52517 (* 1 = 3.52517 loss)
I0406 16:14:04.464668 23057 solver.cpp:218] Iteration 16116 (0.690979 iter/s, 17.3667s/12 iters), loss = 0.152581
I0406 16:14:04.464721 23057 solver.cpp:237]     Train net output #0: loss = 0.152581 (* 1 = 0.152581 loss)
I0406 16:14:04.464730 23057 sgd_solver.cpp:105] Iteration 16116, lr = 0.005
I0406 16:14:08.763556 23057 solver.cpp:218] Iteration 16128 (2.79149 iter/s, 4.29879s/12 iters), loss = 0.103063
I0406 16:14:08.763598 23057 solver.cpp:237]     Train net output #0: loss = 0.103063 (* 1 = 0.103063 loss)
I0406 16:14:08.763603 23057 sgd_solver.cpp:105] Iteration 16128, lr = 0.005
I0406 16:14:14.068292 23057 solver.cpp:218] Iteration 16140 (2.26217 iter/s, 5.30463s/12 iters), loss = 0.193396
I0406 16:14:14.068334 23057 solver.cpp:237]     Train net output #0: loss = 0.193396 (* 1 = 0.193396 loss)
I0406 16:14:14.068341 23057 sgd_solver.cpp:105] Iteration 16140, lr = 0.005
I0406 16:14:19.333662 23057 solver.cpp:218] Iteration 16152 (2.27909 iter/s, 5.26527s/12 iters), loss = 0.18745
I0406 16:14:19.333701 23057 solver.cpp:237]     Train net output #0: loss = 0.18745 (* 1 = 0.18745 loss)
I0406 16:14:19.333709 23057 sgd_solver.cpp:105] Iteration 16152, lr = 0.005
I0406 16:14:24.495959 23057 solver.cpp:218] Iteration 16164 (2.32459 iter/s, 5.1622s/12 iters), loss = 0.118767
I0406 16:14:24.496001 23057 solver.cpp:237]     Train net output #0: loss = 0.118766 (* 1 = 0.118766 loss)
I0406 16:14:24.496006 23057 sgd_solver.cpp:105] Iteration 16164, lr = 0.005
I0406 16:14:29.788174 23057 solver.cpp:218] Iteration 16176 (2.26753 iter/s, 5.29211s/12 iters), loss = 0.146068
I0406 16:14:29.788223 23057 solver.cpp:237]     Train net output #0: loss = 0.146068 (* 1 = 0.146068 loss)
I0406 16:14:29.788230 23057 sgd_solver.cpp:105] Iteration 16176, lr = 0.005
I0406 16:14:33.153025 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:14:35.074472 23057 solver.cpp:218] Iteration 16188 (2.27007 iter/s, 5.28619s/12 iters), loss = 0.133431
I0406 16:14:35.074533 23057 solver.cpp:237]     Train net output #0: loss = 0.13343 (* 1 = 0.13343 loss)
I0406 16:14:35.074542 23057 sgd_solver.cpp:105] Iteration 16188, lr = 0.005
I0406 16:14:40.375360 23057 solver.cpp:218] Iteration 16200 (2.26382 iter/s, 5.30077s/12 iters), loss = 0.0921725
I0406 16:14:40.375406 23057 solver.cpp:237]     Train net output #0: loss = 0.0921722 (* 1 = 0.0921722 loss)
I0406 16:14:40.375412 23057 sgd_solver.cpp:105] Iteration 16200, lr = 0.005
I0406 16:14:45.647471 23057 solver.cpp:218] Iteration 16212 (2.27617 iter/s, 5.27201s/12 iters), loss = 0.0278178
I0406 16:14:45.647509 23057 solver.cpp:237]     Train net output #0: loss = 0.0278176 (* 1 = 0.0278176 loss)
I0406 16:14:45.647516 23057 sgd_solver.cpp:105] Iteration 16212, lr = 0.005
I0406 16:14:47.797891 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16218.caffemodel
I0406 16:14:53.510617 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16218.solverstate
I0406 16:14:58.780555 23057 solver.cpp:330] Iteration 16218, Testing net (#0)
I0406 16:14:58.780575 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:15:01.450877 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:15:03.187613 23057 solver.cpp:397]     Test net output #0: accuracy = 0.408701
I0406 16:15:03.187718 23057 solver.cpp:397]     Test net output #1: loss = 3.60518 (* 1 = 3.60518 loss)
I0406 16:15:05.077167 23057 solver.cpp:218] Iteration 16224 (0.617618 iter/s, 19.4295s/12 iters), loss = 0.0399888
I0406 16:15:05.077215 23057 solver.cpp:237]     Train net output #0: loss = 0.0399886 (* 1 = 0.0399886 loss)
I0406 16:15:05.077220 23057 sgd_solver.cpp:105] Iteration 16224, lr = 0.005
I0406 16:15:10.418527 23057 solver.cpp:218] Iteration 16236 (2.24667 iter/s, 5.34125s/12 iters), loss = 0.150805
I0406 16:15:10.418576 23057 solver.cpp:237]     Train net output #0: loss = 0.150805 (* 1 = 0.150805 loss)
I0406 16:15:10.418582 23057 sgd_solver.cpp:105] Iteration 16236, lr = 0.005
I0406 16:15:15.614941 23057 solver.cpp:218] Iteration 16248 (2.30933 iter/s, 5.19631s/12 iters), loss = 0.0708137
I0406 16:15:15.614979 23057 solver.cpp:237]     Train net output #0: loss = 0.0708135 (* 1 = 0.0708135 loss)
I0406 16:15:15.614984 23057 sgd_solver.cpp:105] Iteration 16248, lr = 0.005
I0406 16:15:20.851986 23057 solver.cpp:218] Iteration 16260 (2.29141 iter/s, 5.23695s/12 iters), loss = 0.0448178
I0406 16:15:20.852038 23057 solver.cpp:237]     Train net output #0: loss = 0.0448175 (* 1 = 0.0448175 loss)
I0406 16:15:20.852046 23057 sgd_solver.cpp:105] Iteration 16260, lr = 0.005
I0406 16:15:26.059310 23057 solver.cpp:218] Iteration 16272 (2.3045 iter/s, 5.20721s/12 iters), loss = 0.0530682
I0406 16:15:26.059368 23057 solver.cpp:237]     Train net output #0: loss = 0.053068 (* 1 = 0.053068 loss)
I0406 16:15:26.059376 23057 sgd_solver.cpp:105] Iteration 16272, lr = 0.005
I0406 16:15:31.430447 23057 solver.cpp:218] Iteration 16284 (2.23421 iter/s, 5.37102s/12 iters), loss = 0.142186
I0406 16:15:31.430491 23057 solver.cpp:237]     Train net output #0: loss = 0.142186 (* 1 = 0.142186 loss)
I0406 16:15:31.430497 23057 sgd_solver.cpp:105] Iteration 16284, lr = 0.005
I0406 16:15:31.928735 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:15:36.678591 23057 solver.cpp:218] Iteration 16296 (2.28657 iter/s, 5.24803s/12 iters), loss = 0.142508
I0406 16:15:36.678751 23057 solver.cpp:237]     Train net output #0: loss = 0.142508 (* 1 = 0.142508 loss)
I0406 16:15:36.678761 23057 sgd_solver.cpp:105] Iteration 16296, lr = 0.005
I0406 16:15:41.897009 23057 solver.cpp:218] Iteration 16308 (2.29964 iter/s, 5.2182s/12 iters), loss = 0.0999412
I0406 16:15:41.897053 23057 solver.cpp:237]     Train net output #0: loss = 0.0999409 (* 1 = 0.0999409 loss)
I0406 16:15:41.897058 23057 sgd_solver.cpp:105] Iteration 16308, lr = 0.005
I0406 16:15:46.753825 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16320.caffemodel
I0406 16:15:51.183595 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16320.solverstate
I0406 16:15:54.644796 23057 solver.cpp:330] Iteration 16320, Testing net (#0)
I0406 16:15:54.644821 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:15:57.234344 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:15:59.057024 23057 solver.cpp:397]     Test net output #0: accuracy = 0.42402
I0406 16:15:59.057054 23057 solver.cpp:397]     Test net output #1: loss = 3.52626 (* 1 = 3.52626 loss)
I0406 16:15:59.193953 23057 solver.cpp:218] Iteration 16320 (0.693772 iter/s, 17.2967s/12 iters), loss = 0.0704831
I0406 16:15:59.195523 23057 solver.cpp:237]     Train net output #0: loss = 0.0704828 (* 1 = 0.0704828 loss)
I0406 16:15:59.195541 23057 sgd_solver.cpp:105] Iteration 16320, lr = 0.005
I0406 16:16:03.475320 23057 solver.cpp:218] Iteration 16332 (2.8039 iter/s, 4.27976s/12 iters), loss = 0.171612
I0406 16:16:03.475370 23057 solver.cpp:237]     Train net output #0: loss = 0.171612 (* 1 = 0.171612 loss)
I0406 16:16:03.475378 23057 sgd_solver.cpp:105] Iteration 16332, lr = 0.005
I0406 16:16:08.487448 23057 solver.cpp:218] Iteration 16344 (2.39424 iter/s, 5.01202s/12 iters), loss = 0.0587876
I0406 16:16:08.487581 23057 solver.cpp:237]     Train net output #0: loss = 0.0587874 (* 1 = 0.0587874 loss)
I0406 16:16:08.487591 23057 sgd_solver.cpp:105] Iteration 16344, lr = 0.005
I0406 16:16:13.527098 23057 solver.cpp:218] Iteration 16356 (2.38121 iter/s, 5.03946s/12 iters), loss = 0.0313455
I0406 16:16:13.527143 23057 solver.cpp:237]     Train net output #0: loss = 0.0313453 (* 1 = 0.0313453 loss)
I0406 16:16:13.527148 23057 sgd_solver.cpp:105] Iteration 16356, lr = 0.005
I0406 16:16:18.821398 23057 solver.cpp:218] Iteration 16368 (2.26663 iter/s, 5.29419s/12 iters), loss = 0.164289
I0406 16:16:18.821453 23057 solver.cpp:237]     Train net output #0: loss = 0.164289 (* 1 = 0.164289 loss)
I0406 16:16:18.821462 23057 sgd_solver.cpp:105] Iteration 16368, lr = 0.005
I0406 16:16:24.061362 23057 solver.cpp:218] Iteration 16380 (2.29014 iter/s, 5.23985s/12 iters), loss = 0.108744
I0406 16:16:24.061406 23057 solver.cpp:237]     Train net output #0: loss = 0.108744 (* 1 = 0.108744 loss)
I0406 16:16:24.061412 23057 sgd_solver.cpp:105] Iteration 16380, lr = 0.005
I0406 16:16:26.734761 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:16:29.348997 23057 solver.cpp:218] Iteration 16392 (2.26949 iter/s, 5.28753s/12 iters), loss = 0.0672445
I0406 16:16:29.349046 23057 solver.cpp:237]     Train net output #0: loss = 0.0672443 (* 1 = 0.0672443 loss)
I0406 16:16:29.349054 23057 sgd_solver.cpp:105] Iteration 16392, lr = 0.005
I0406 16:16:34.763686 23057 solver.cpp:218] Iteration 16404 (2.21624 iter/s, 5.41458s/12 iters), loss = 0.0892471
I0406 16:16:34.763752 23057 solver.cpp:237]     Train net output #0: loss = 0.0892469 (* 1 = 0.0892469 loss)
I0406 16:16:34.763761 23057 sgd_solver.cpp:105] Iteration 16404, lr = 0.005
I0406 16:16:40.099912 23057 solver.cpp:218] Iteration 16416 (2.24883 iter/s, 5.3361s/12 iters), loss = 0.0800852
I0406 16:16:40.100069 23057 solver.cpp:237]     Train net output #0: loss = 0.0800849 (* 1 = 0.0800849 loss)
I0406 16:16:40.100080 23057 sgd_solver.cpp:105] Iteration 16416, lr = 0.005
I0406 16:16:42.226305 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16422.caffemodel
I0406 16:16:46.711493 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16422.solverstate
I0406 16:16:50.419201 23057 solver.cpp:330] Iteration 16422, Testing net (#0)
I0406 16:16:50.419222 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:16:52.916167 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:16:54.722168 23057 solver.cpp:397]     Test net output #0: accuracy = 0.417279
I0406 16:16:54.722198 23057 solver.cpp:397]     Test net output #1: loss = 3.42513 (* 1 = 3.42513 loss)
I0406 16:16:56.641461 23057 solver.cpp:218] Iteration 16428 (0.725459 iter/s, 16.5412s/12 iters), loss = 0.0519426
I0406 16:16:56.641522 23057 solver.cpp:237]     Train net output #0: loss = 0.0519423 (* 1 = 0.0519423 loss)
I0406 16:16:56.641531 23057 sgd_solver.cpp:105] Iteration 16428, lr = 0.005
I0406 16:17:01.692410 23057 solver.cpp:218] Iteration 16440 (2.37585 iter/s, 5.05083s/12 iters), loss = 0.136843
I0406 16:17:01.692458 23057 solver.cpp:237]     Train net output #0: loss = 0.136843 (* 1 = 0.136843 loss)
I0406 16:17:01.692466 23057 sgd_solver.cpp:105] Iteration 16440, lr = 0.005
I0406 16:17:06.945070 23057 solver.cpp:218] Iteration 16452 (2.28461 iter/s, 5.25255s/12 iters), loss = 0.142881
I0406 16:17:06.945114 23057 solver.cpp:237]     Train net output #0: loss = 0.142881 (* 1 = 0.142881 loss)
I0406 16:17:06.945120 23057 sgd_solver.cpp:105] Iteration 16452, lr = 0.005
I0406 16:17:12.235491 23057 solver.cpp:218] Iteration 16464 (2.2683 iter/s, 5.29031s/12 iters), loss = 0.131103
I0406 16:17:12.235607 23057 solver.cpp:237]     Train net output #0: loss = 0.131103 (* 1 = 0.131103 loss)
I0406 16:17:12.235615 23057 sgd_solver.cpp:105] Iteration 16464, lr = 0.005
I0406 16:17:17.447001 23057 solver.cpp:218] Iteration 16476 (2.30267 iter/s, 5.21134s/12 iters), loss = 0.121001
I0406 16:17:17.447039 23057 solver.cpp:237]     Train net output #0: loss = 0.121001 (* 1 = 0.121001 loss)
I0406 16:17:17.447046 23057 sgd_solver.cpp:105] Iteration 16476, lr = 0.005
I0406 16:17:22.586086 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:17:22.898787 23057 solver.cpp:218] Iteration 16488 (2.20115 iter/s, 5.45169s/12 iters), loss = 0.137531
I0406 16:17:22.898834 23057 solver.cpp:237]     Train net output #0: loss = 0.13753 (* 1 = 0.13753 loss)
I0406 16:17:22.898842 23057 sgd_solver.cpp:105] Iteration 16488, lr = 0.005
I0406 16:17:28.289834 23057 solver.cpp:218] Iteration 16500 (2.22596 iter/s, 5.39094s/12 iters), loss = 0.209974
I0406 16:17:28.289894 23057 solver.cpp:237]     Train net output #0: loss = 0.209974 (* 1 = 0.209974 loss)
I0406 16:17:28.289906 23057 sgd_solver.cpp:105] Iteration 16500, lr = 0.005
I0406 16:17:33.604532 23057 solver.cpp:218] Iteration 16512 (2.25794 iter/s, 5.31459s/12 iters), loss = 0.105932
I0406 16:17:33.604570 23057 solver.cpp:237]     Train net output #0: loss = 0.105932 (* 1 = 0.105932 loss)
I0406 16:17:33.604578 23057 sgd_solver.cpp:105] Iteration 16512, lr = 0.005
I0406 16:17:38.448084 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16524.caffemodel
I0406 16:17:42.965034 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16524.solverstate
I0406 16:17:46.479408 23057 solver.cpp:330] Iteration 16524, Testing net (#0)
I0406 16:17:46.479429 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:17:48.925590 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:17:50.781332 23057 solver.cpp:397]     Test net output #0: accuracy = 0.433211
I0406 16:17:50.781360 23057 solver.cpp:397]     Test net output #1: loss = 3.363 (* 1 = 3.363 loss)
I0406 16:17:50.918650 23057 solver.cpp:218] Iteration 16524 (0.693084 iter/s, 17.3139s/12 iters), loss = 0.112124
I0406 16:17:50.918723 23057 solver.cpp:237]     Train net output #0: loss = 0.112124 (* 1 = 0.112124 loss)
I0406 16:17:50.918733 23057 sgd_solver.cpp:105] Iteration 16524, lr = 0.005
I0406 16:17:55.234867 23057 solver.cpp:218] Iteration 16536 (2.78029 iter/s, 4.31609s/12 iters), loss = 0.0554466
I0406 16:17:55.234911 23057 solver.cpp:237]     Train net output #0: loss = 0.0554464 (* 1 = 0.0554464 loss)
I0406 16:17:55.234917 23057 sgd_solver.cpp:105] Iteration 16536, lr = 0.005
I0406 16:18:00.508698 23057 solver.cpp:218] Iteration 16548 (2.27543 iter/s, 5.27373s/12 iters), loss = 0.0504426
I0406 16:18:00.508739 23057 solver.cpp:237]     Train net output #0: loss = 0.0504424 (* 1 = 0.0504424 loss)
I0406 16:18:00.508745 23057 sgd_solver.cpp:105] Iteration 16548, lr = 0.005
I0406 16:18:05.808991 23057 solver.cpp:218] Iteration 16560 (2.26407 iter/s, 5.30019s/12 iters), loss = 0.140723
I0406 16:18:05.809039 23057 solver.cpp:237]     Train net output #0: loss = 0.140723 (* 1 = 0.140723 loss)
I0406 16:18:05.809046 23057 sgd_solver.cpp:105] Iteration 16560, lr = 0.005
I0406 16:18:11.261065 23057 solver.cpp:218] Iteration 16572 (2.20104 iter/s, 5.45197s/12 iters), loss = 0.0889052
I0406 16:18:11.261107 23057 solver.cpp:237]     Train net output #0: loss = 0.088905 (* 1 = 0.088905 loss)
I0406 16:18:11.261113 23057 sgd_solver.cpp:105] Iteration 16572, lr = 0.005
I0406 16:18:16.539919 23057 solver.cpp:218] Iteration 16584 (2.27326 iter/s, 5.27876s/12 iters), loss = 0.0452103
I0406 16:18:16.540014 23057 solver.cpp:237]     Train net output #0: loss = 0.04521 (* 1 = 0.04521 loss)
I0406 16:18:16.540021 23057 sgd_solver.cpp:105] Iteration 16584, lr = 0.005
I0406 16:18:18.419840 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:18:21.578873 23057 solver.cpp:218] Iteration 16596 (2.38152 iter/s, 5.0388s/12 iters), loss = 0.0211161
I0406 16:18:21.578925 23057 solver.cpp:237]     Train net output #0: loss = 0.0211159 (* 1 = 0.0211159 loss)
I0406 16:18:21.578933 23057 sgd_solver.cpp:105] Iteration 16596, lr = 0.005
I0406 16:18:26.853523 23057 solver.cpp:218] Iteration 16608 (2.27508 iter/s, 5.27455s/12 iters), loss = 0.0287849
I0406 16:18:26.853569 23057 solver.cpp:237]     Train net output #0: loss = 0.0287846 (* 1 = 0.0287846 loss)
I0406 16:18:26.853576 23057 sgd_solver.cpp:105] Iteration 16608, lr = 0.005
I0406 16:18:32.336098 23057 solver.cpp:218] Iteration 16620 (2.18879 iter/s, 5.48247s/12 iters), loss = 0.0523952
I0406 16:18:32.336140 23057 solver.cpp:237]     Train net output #0: loss = 0.052395 (* 1 = 0.052395 loss)
I0406 16:18:32.336146 23057 sgd_solver.cpp:105] Iteration 16620, lr = 0.005
I0406 16:18:34.510962 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16626.caffemodel
I0406 16:18:39.066289 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16626.solverstate
I0406 16:18:41.456321 23057 solver.cpp:330] Iteration 16626, Testing net (#0)
I0406 16:18:41.456342 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:18:43.960510 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:18:45.223966 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:18:45.839650 23057 solver.cpp:397]     Test net output #0: accuracy = 0.41299
I0406 16:18:45.839684 23057 solver.cpp:397]     Test net output #1: loss = 3.60677 (* 1 = 3.60677 loss)
I0406 16:18:47.878357 23057 solver.cpp:218] Iteration 16632 (0.772098 iter/s, 15.5421s/12 iters), loss = 0.08673
I0406 16:18:47.878525 23057 solver.cpp:237]     Train net output #0: loss = 0.0867298 (* 1 = 0.0867298 loss)
I0406 16:18:47.878535 23057 sgd_solver.cpp:105] Iteration 16632, lr = 0.005
I0406 16:18:52.902117 23057 solver.cpp:218] Iteration 16644 (2.38876 iter/s, 5.02354s/12 iters), loss = 0.185097
I0406 16:18:52.902158 23057 solver.cpp:237]     Train net output #0: loss = 0.185097 (* 1 = 0.185097 loss)
I0406 16:18:52.902164 23057 sgd_solver.cpp:105] Iteration 16644, lr = 0.005
I0406 16:18:58.102777 23057 solver.cpp:218] Iteration 16656 (2.30744 iter/s, 5.20056s/12 iters), loss = 0.0228334
I0406 16:18:58.102828 23057 solver.cpp:237]     Train net output #0: loss = 0.0228332 (* 1 = 0.0228332 loss)
I0406 16:18:58.102836 23057 sgd_solver.cpp:105] Iteration 16656, lr = 0.005
I0406 16:19:03.503278 23057 solver.cpp:218] Iteration 16668 (2.22206 iter/s, 5.40039s/12 iters), loss = 0.0920691
I0406 16:19:03.503316 23057 solver.cpp:237]     Train net output #0: loss = 0.0920689 (* 1 = 0.0920689 loss)
I0406 16:19:03.503322 23057 sgd_solver.cpp:105] Iteration 16668, lr = 0.005
I0406 16:19:08.686832 23057 solver.cpp:218] Iteration 16680 (2.31506 iter/s, 5.18346s/12 iters), loss = 0.0833047
I0406 16:19:08.686888 23057 solver.cpp:237]     Train net output #0: loss = 0.0833045 (* 1 = 0.0833045 loss)
I0406 16:19:08.686897 23057 sgd_solver.cpp:105] Iteration 16680, lr = 0.005
I0406 16:19:12.811731 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:19:13.875144 23057 solver.cpp:218] Iteration 16692 (2.31294 iter/s, 5.1882s/12 iters), loss = 0.0247606
I0406 16:19:13.875187 23057 solver.cpp:237]     Train net output #0: loss = 0.0247603 (* 1 = 0.0247603 loss)
I0406 16:19:13.875193 23057 sgd_solver.cpp:105] Iteration 16692, lr = 0.005
I0406 16:19:19.005620 23057 solver.cpp:218] Iteration 16704 (2.33901 iter/s, 5.13037s/12 iters), loss = 0.218651
I0406 16:19:19.005775 23057 solver.cpp:237]     Train net output #0: loss = 0.21865 (* 1 = 0.21865 loss)
I0406 16:19:19.005786 23057 sgd_solver.cpp:105] Iteration 16704, lr = 0.005
I0406 16:19:24.293226 23057 solver.cpp:218] Iteration 16716 (2.26955 iter/s, 5.2874s/12 iters), loss = 0.0313032
I0406 16:19:24.293267 23057 solver.cpp:237]     Train net output #0: loss = 0.031303 (* 1 = 0.031303 loss)
I0406 16:19:24.293272 23057 sgd_solver.cpp:105] Iteration 16716, lr = 0.005
I0406 16:19:29.222687 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16728.caffemodel
I0406 16:19:34.206939 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16728.solverstate
I0406 16:19:36.527027 23057 solver.cpp:330] Iteration 16728, Testing net (#0)
I0406 16:19:36.527052 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:19:39.031025 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:19:40.944218 23057 solver.cpp:397]     Test net output #0: accuracy = 0.432598
I0406 16:19:40.944252 23057 solver.cpp:397]     Test net output #1: loss = 3.50737 (* 1 = 3.50737 loss)
I0406 16:19:41.085676 23057 solver.cpp:218] Iteration 16728 (0.714615 iter/s, 16.7923s/12 iters), loss = 0.107492
I0406 16:19:41.085724 23057 solver.cpp:237]     Train net output #0: loss = 0.107492 (* 1 = 0.107492 loss)
I0406 16:19:41.085732 23057 sgd_solver.cpp:105] Iteration 16728, lr = 0.005
I0406 16:19:45.191464 23057 solver.cpp:218] Iteration 16740 (2.92277 iter/s, 4.10569s/12 iters), loss = 0.099368
I0406 16:19:45.191509 23057 solver.cpp:237]     Train net output #0: loss = 0.0993677 (* 1 = 0.0993677 loss)
I0406 16:19:45.191515 23057 sgd_solver.cpp:105] Iteration 16740, lr = 0.005
I0406 16:19:50.468813 23057 solver.cpp:218] Iteration 16752 (2.27392 iter/s, 5.27724s/12 iters), loss = 0.116055
I0406 16:19:50.468914 23057 solver.cpp:237]     Train net output #0: loss = 0.116054 (* 1 = 0.116054 loss)
I0406 16:19:50.468921 23057 sgd_solver.cpp:105] Iteration 16752, lr = 0.005
I0406 16:19:55.640985 23057 solver.cpp:218] Iteration 16764 (2.32018 iter/s, 5.17202s/12 iters), loss = 0.127156
I0406 16:19:55.641024 23057 solver.cpp:237]     Train net output #0: loss = 0.127155 (* 1 = 0.127155 loss)
I0406 16:19:55.641031 23057 sgd_solver.cpp:105] Iteration 16764, lr = 0.005
I0406 16:20:00.843787 23057 solver.cpp:218] Iteration 16776 (2.30649 iter/s, 5.2027s/12 iters), loss = 0.0912137
I0406 16:20:00.843828 23057 solver.cpp:237]     Train net output #0: loss = 0.0912134 (* 1 = 0.0912134 loss)
I0406 16:20:00.843834 23057 sgd_solver.cpp:105] Iteration 16776, lr = 0.005
I0406 16:20:06.105427 23057 solver.cpp:218] Iteration 16788 (2.2807 iter/s, 5.26154s/12 iters), loss = 0.0712565
I0406 16:20:06.105477 23057 solver.cpp:237]     Train net output #0: loss = 0.0712563 (* 1 = 0.0712563 loss)
I0406 16:20:06.105485 23057 sgd_solver.cpp:105] Iteration 16788, lr = 0.005
I0406 16:20:07.267488 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:20:11.424029 23057 solver.cpp:218] Iteration 16800 (2.25628 iter/s, 5.31849s/12 iters), loss = 0.00776324
I0406 16:20:11.424072 23057 solver.cpp:237]     Train net output #0: loss = 0.00776299 (* 1 = 0.00776299 loss)
I0406 16:20:11.424078 23057 sgd_solver.cpp:105] Iteration 16800, lr = 0.005
I0406 16:20:16.811975 23057 solver.cpp:218] Iteration 16812 (2.22724 iter/s, 5.38784s/12 iters), loss = 0.0386067
I0406 16:20:16.812021 23057 solver.cpp:237]     Train net output #0: loss = 0.0386064 (* 1 = 0.0386064 loss)
I0406 16:20:16.812026 23057 sgd_solver.cpp:105] Iteration 16812, lr = 0.005
I0406 16:20:22.032917 23057 solver.cpp:218] Iteration 16824 (2.29848 iter/s, 5.22084s/12 iters), loss = 0.0302351
I0406 16:20:22.033221 23057 solver.cpp:237]     Train net output #0: loss = 0.0302349 (* 1 = 0.0302349 loss)
I0406 16:20:22.033243 23057 sgd_solver.cpp:105] Iteration 16824, lr = 0.005
I0406 16:20:24.182353 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16830.caffemodel
I0406 16:20:28.835848 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16830.solverstate
I0406 16:20:31.128479 23057 solver.cpp:330] Iteration 16830, Testing net (#0)
I0406 16:20:31.128499 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:20:33.473995 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:20:35.430675 23057 solver.cpp:397]     Test net output #0: accuracy = 0.429534
I0406 16:20:35.430714 23057 solver.cpp:397]     Test net output #1: loss = 3.53101 (* 1 = 3.53101 loss)
I0406 16:20:37.342733 23057 solver.cpp:218] Iteration 16836 (0.783827 iter/s, 15.3095s/12 iters), loss = 0.0546216
I0406 16:20:37.342783 23057 solver.cpp:237]     Train net output #0: loss = 0.0546213 (* 1 = 0.0546213 loss)
I0406 16:20:37.342792 23057 sgd_solver.cpp:105] Iteration 16836, lr = 0.005
I0406 16:20:42.800911 23057 solver.cpp:218] Iteration 16848 (2.19858 iter/s, 5.45807s/12 iters), loss = 0.117524
I0406 16:20:42.800972 23057 solver.cpp:237]     Train net output #0: loss = 0.117524 (* 1 = 0.117524 loss)
I0406 16:20:42.800981 23057 sgd_solver.cpp:105] Iteration 16848, lr = 0.005
I0406 16:20:47.973318 23057 solver.cpp:218] Iteration 16860 (2.32005 iter/s, 5.17229s/12 iters), loss = 0.0867284
I0406 16:20:47.973353 23057 solver.cpp:237]     Train net output #0: loss = 0.0867281 (* 1 = 0.0867281 loss)
I0406 16:20:47.973359 23057 sgd_solver.cpp:105] Iteration 16860, lr = 0.005
I0406 16:20:53.183719 23057 solver.cpp:218] Iteration 16872 (2.30313 iter/s, 5.21031s/12 iters), loss = 0.0168565
I0406 16:20:53.183835 23057 solver.cpp:237]     Train net output #0: loss = 0.0168562 (* 1 = 0.0168562 loss)
I0406 16:20:53.183841 23057 sgd_solver.cpp:105] Iteration 16872, lr = 0.005
I0406 16:20:58.195608 23057 solver.cpp:218] Iteration 16884 (2.39439 iter/s, 5.01171s/12 iters), loss = 0.0263589
I0406 16:20:58.195664 23057 solver.cpp:237]     Train net output #0: loss = 0.0263586 (* 1 = 0.0263586 loss)
I0406 16:20:58.195672 23057 sgd_solver.cpp:105] Iteration 16884, lr = 0.005
I0406 16:21:01.785853 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:21:03.572034 23057 solver.cpp:218] Iteration 16896 (2.23201 iter/s, 5.37631s/12 iters), loss = 0.152613
I0406 16:21:03.572082 23057 solver.cpp:237]     Train net output #0: loss = 0.152613 (* 1 = 0.152613 loss)
I0406 16:21:03.572088 23057 sgd_solver.cpp:105] Iteration 16896, lr = 0.005
I0406 16:21:08.869326 23057 solver.cpp:218] Iteration 16908 (2.26535 iter/s, 5.29719s/12 iters), loss = 0.0986987
I0406 16:21:08.869367 23057 solver.cpp:237]     Train net output #0: loss = 0.0986984 (* 1 = 0.0986984 loss)
I0406 16:21:08.869374 23057 sgd_solver.cpp:105] Iteration 16908, lr = 0.005
I0406 16:21:14.155100 23057 solver.cpp:218] Iteration 16920 (2.27029 iter/s, 5.28567s/12 iters), loss = 0.127337
I0406 16:21:14.155146 23057 solver.cpp:237]     Train net output #0: loss = 0.127337 (* 1 = 0.127337 loss)
I0406 16:21:14.155151 23057 sgd_solver.cpp:105] Iteration 16920, lr = 0.005
I0406 16:21:18.962476 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16932.caffemodel
I0406 16:21:23.213989 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16932.solverstate
I0406 16:21:25.529950 23057 solver.cpp:330] Iteration 16932, Testing net (#0)
I0406 16:21:25.529968 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:21:27.811230 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:21:29.801318 23057 solver.cpp:397]     Test net output #0: accuracy = 0.428922
I0406 16:21:29.801354 23057 solver.cpp:397]     Test net output #1: loss = 3.655 (* 1 = 3.655 loss)
I0406 16:21:29.941677 23057 solver.cpp:218] Iteration 16932 (0.760149 iter/s, 15.7864s/12 iters), loss = 0.0360656
I0406 16:21:29.941737 23057 solver.cpp:237]     Train net output #0: loss = 0.0360654 (* 1 = 0.0360654 loss)
I0406 16:21:29.941746 23057 sgd_solver.cpp:105] Iteration 16932, lr = 0.005
I0406 16:21:34.150827 23057 solver.cpp:218] Iteration 16944 (2.85101 iter/s, 4.20904s/12 iters), loss = 0.0333234
I0406 16:21:34.150882 23057 solver.cpp:237]     Train net output #0: loss = 0.0333232 (* 1 = 0.0333232 loss)
I0406 16:21:34.150890 23057 sgd_solver.cpp:105] Iteration 16944, lr = 0.005
I0406 16:21:39.593524 23057 solver.cpp:218] Iteration 16956 (2.20483 iter/s, 5.44259s/12 iters), loss = 0.0752201
I0406 16:21:39.593559 23057 solver.cpp:237]     Train net output #0: loss = 0.0752198 (* 1 = 0.0752198 loss)
I0406 16:21:39.593564 23057 sgd_solver.cpp:105] Iteration 16956, lr = 0.005
I0406 16:21:44.947136 23057 solver.cpp:218] Iteration 16968 (2.24152 iter/s, 5.35352s/12 iters), loss = 0.120952
I0406 16:21:44.947186 23057 solver.cpp:237]     Train net output #0: loss = 0.120951 (* 1 = 0.120951 loss)
I0406 16:21:44.947196 23057 sgd_solver.cpp:105] Iteration 16968, lr = 0.005
I0406 16:21:50.288831 23057 solver.cpp:218] Iteration 16980 (2.24652 iter/s, 5.34159s/12 iters), loss = 0.0477841
I0406 16:21:50.288892 23057 solver.cpp:237]     Train net output #0: loss = 0.0477838 (* 1 = 0.0477838 loss)
I0406 16:21:50.288900 23057 sgd_solver.cpp:105] Iteration 16980, lr = 0.005
I0406 16:21:55.673816 23057 solver.cpp:218] Iteration 16992 (2.22846 iter/s, 5.38487s/12 iters), loss = 0.0769924
I0406 16:21:55.673914 23057 solver.cpp:237]     Train net output #0: loss = 0.0769921 (* 1 = 0.0769921 loss)
I0406 16:21:55.673923 23057 sgd_solver.cpp:105] Iteration 16992, lr = 0.005
I0406 16:21:56.192827 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:22:00.906309 23057 solver.cpp:218] Iteration 17004 (2.29343 iter/s, 5.23234s/12 iters), loss = 0.0716069
I0406 16:22:00.906348 23057 solver.cpp:237]     Train net output #0: loss = 0.0716066 (* 1 = 0.0716066 loss)
I0406 16:22:00.906354 23057 sgd_solver.cpp:105] Iteration 17004, lr = 0.005
I0406 16:22:06.220782 23057 solver.cpp:218] Iteration 17016 (2.25803 iter/s, 5.31437s/12 iters), loss = 0.147216
I0406 16:22:06.220829 23057 solver.cpp:237]     Train net output #0: loss = 0.147215 (* 1 = 0.147215 loss)
I0406 16:22:06.220835 23057 sgd_solver.cpp:105] Iteration 17016, lr = 0.005
I0406 16:22:11.553661 23057 solver.cpp:218] Iteration 17028 (2.25023 iter/s, 5.33278s/12 iters), loss = 0.092463
I0406 16:22:11.553695 23057 solver.cpp:237]     Train net output #0: loss = 0.0924627 (* 1 = 0.0924627 loss)
I0406 16:22:11.553701 23057 sgd_solver.cpp:105] Iteration 17028, lr = 0.005
I0406 16:22:13.602932 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17034.caffemodel
I0406 16:22:17.730057 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17034.solverstate
I0406 16:22:20.114929 23057 solver.cpp:330] Iteration 17034, Testing net (#0)
I0406 16:22:20.114950 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:22:22.408756 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:22:24.528681 23057 solver.cpp:397]     Test net output #0: accuracy = 0.424632
I0406 16:22:24.528712 23057 solver.cpp:397]     Test net output #1: loss = 3.45268 (* 1 = 3.45268 loss)
I0406 16:22:26.356681 23057 solver.cpp:218] Iteration 17040 (0.810655 iter/s, 14.8029s/12 iters), loss = 0.131672
I0406 16:22:26.356827 23057 solver.cpp:237]     Train net output #0: loss = 0.131671 (* 1 = 0.131671 loss)
I0406 16:22:26.356835 23057 sgd_solver.cpp:105] Iteration 17040, lr = 0.005
I0406 16:22:31.770759 23057 solver.cpp:218] Iteration 17052 (2.21652 iter/s, 5.41388s/12 iters), loss = 0.113698
I0406 16:22:31.770790 23057 solver.cpp:237]     Train net output #0: loss = 0.113698 (* 1 = 0.113698 loss)
I0406 16:22:31.770797 23057 sgd_solver.cpp:105] Iteration 17052, lr = 0.005
I0406 16:22:36.947072 23057 solver.cpp:218] Iteration 17064 (2.31829 iter/s, 5.17622s/12 iters), loss = 0.064426
I0406 16:22:36.947108 23057 solver.cpp:237]     Train net output #0: loss = 0.0644257 (* 1 = 0.0644257 loss)
I0406 16:22:36.947114 23057 sgd_solver.cpp:105] Iteration 17064, lr = 0.005
I0406 16:22:42.275907 23057 solver.cpp:218] Iteration 17076 (2.25194 iter/s, 5.32874s/12 iters), loss = 0.109596
I0406 16:22:42.275959 23057 solver.cpp:237]     Train net output #0: loss = 0.109596 (* 1 = 0.109596 loss)
I0406 16:22:42.275967 23057 sgd_solver.cpp:105] Iteration 17076, lr = 0.005
I0406 16:22:47.491641 23057 solver.cpp:218] Iteration 17088 (2.30078 iter/s, 5.21563s/12 iters), loss = 0.14704
I0406 16:22:47.491677 23057 solver.cpp:237]     Train net output #0: loss = 0.147039 (* 1 = 0.147039 loss)
I0406 16:22:47.491683 23057 sgd_solver.cpp:105] Iteration 17088, lr = 0.005
I0406 16:22:50.207196 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:22:52.754375 23057 solver.cpp:218] Iteration 17100 (2.28022 iter/s, 5.26264s/12 iters), loss = 0.0339568
I0406 16:22:52.754426 23057 solver.cpp:237]     Train net output #0: loss = 0.0339565 (* 1 = 0.0339565 loss)
I0406 16:22:52.754434 23057 sgd_solver.cpp:105] Iteration 17100, lr = 0.005
I0406 16:22:58.062719 23057 solver.cpp:218] Iteration 17112 (2.26064 iter/s, 5.30824s/12 iters), loss = 0.0961288
I0406 16:22:58.062810 23057 solver.cpp:237]     Train net output #0: loss = 0.0961285 (* 1 = 0.0961285 loss)
I0406 16:22:58.062816 23057 sgd_solver.cpp:105] Iteration 17112, lr = 0.005
I0406 16:23:03.205180 23057 solver.cpp:218] Iteration 17124 (2.33358 iter/s, 5.14231s/12 iters), loss = 0.135374
I0406 16:23:03.205227 23057 solver.cpp:237]     Train net output #0: loss = 0.135374 (* 1 = 0.135374 loss)
I0406 16:23:03.205235 23057 sgd_solver.cpp:105] Iteration 17124, lr = 0.005
I0406 16:23:07.775192 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17136.caffemodel
I0406 16:23:12.191823 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17136.solverstate
I0406 16:23:14.607831 23057 solver.cpp:330] Iteration 17136, Testing net (#0)
I0406 16:23:14.607851 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:23:16.923123 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:23:19.057190 23057 solver.cpp:397]     Test net output #0: accuracy = 0.431373
I0406 16:23:19.057225 23057 solver.cpp:397]     Test net output #1: loss = 3.49481 (* 1 = 3.49481 loss)
I0406 16:23:19.197638 23057 solver.cpp:218] Iteration 17136 (0.750362 iter/s, 15.9923s/12 iters), loss = 0.0692034
I0406 16:23:19.197679 23057 solver.cpp:237]     Train net output #0: loss = 0.0692031 (* 1 = 0.0692031 loss)
I0406 16:23:19.197685 23057 sgd_solver.cpp:105] Iteration 17136, lr = 0.005
I0406 16:23:23.503394 23057 solver.cpp:218] Iteration 17148 (2.78703 iter/s, 4.30567s/12 iters), loss = 0.0341894
I0406 16:23:23.503425 23057 solver.cpp:237]     Train net output #0: loss = 0.0341891 (* 1 = 0.0341891 loss)
I0406 16:23:23.503430 23057 sgd_solver.cpp:105] Iteration 17148, lr = 0.005
I0406 16:23:28.704274 23057 solver.cpp:218] Iteration 17160 (2.30734 iter/s, 5.20079s/12 iters), loss = 0.0382312
I0406 16:23:28.704422 23057 solver.cpp:237]     Train net output #0: loss = 0.0382309 (* 1 = 0.0382309 loss)
I0406 16:23:28.704432 23057 sgd_solver.cpp:105] Iteration 17160, lr = 0.005
I0406 16:23:33.938314 23057 solver.cpp:218] Iteration 17172 (2.29277 iter/s, 5.23383s/12 iters), loss = 0.0891326
I0406 16:23:33.938378 23057 solver.cpp:237]     Train net output #0: loss = 0.0891323 (* 1 = 0.0891323 loss)
I0406 16:23:33.938387 23057 sgd_solver.cpp:105] Iteration 17172, lr = 0.005
I0406 16:23:39.276036 23057 solver.cpp:218] Iteration 17184 (2.2482 iter/s, 5.3376s/12 iters), loss = 0.149393
I0406 16:23:39.276089 23057 solver.cpp:237]     Train net output #0: loss = 0.149393 (* 1 = 0.149393 loss)
I0406 16:23:39.276098 23057 sgd_solver.cpp:105] Iteration 17184, lr = 0.005
I0406 16:23:44.260316 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:23:44.537647 23057 solver.cpp:218] Iteration 17196 (2.28072 iter/s, 5.2615s/12 iters), loss = 0.215988
I0406 16:23:44.537688 23057 solver.cpp:237]     Train net output #0: loss = 0.215988 (* 1 = 0.215988 loss)
I0406 16:23:44.537693 23057 sgd_solver.cpp:105] Iteration 17196, lr = 0.005
I0406 16:23:49.751799 23057 solver.cpp:218] Iteration 17208 (2.30147 iter/s, 5.21405s/12 iters), loss = 0.0177895
I0406 16:23:49.751842 23057 solver.cpp:237]     Train net output #0: loss = 0.0177892 (* 1 = 0.0177892 loss)
I0406 16:23:49.751848 23057 sgd_solver.cpp:105] Iteration 17208, lr = 0.005
I0406 16:23:54.998769 23057 solver.cpp:218] Iteration 17220 (2.28708 iter/s, 5.24686s/12 iters), loss = 0.0904302
I0406 16:23:54.998809 23057 solver.cpp:237]     Train net output #0: loss = 0.0904299 (* 1 = 0.0904299 loss)
I0406 16:23:54.998814 23057 sgd_solver.cpp:105] Iteration 17220, lr = 0.005
I0406 16:24:00.327302 23057 solver.cpp:218] Iteration 17232 (2.25207 iter/s, 5.32843s/12 iters), loss = 0.116309
I0406 16:24:00.327417 23057 solver.cpp:237]     Train net output #0: loss = 0.116309 (* 1 = 0.116309 loss)
I0406 16:24:00.327423 23057 sgd_solver.cpp:105] Iteration 17232, lr = 0.005
I0406 16:24:02.532589 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17238.caffemodel
I0406 16:24:06.309324 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17238.solverstate
I0406 16:24:08.617394 23057 solver.cpp:330] Iteration 17238, Testing net (#0)
I0406 16:24:08.617415 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:24:10.866150 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:24:12.970268 23057 solver.cpp:397]     Test net output #0: accuracy = 0.43076
I0406 16:24:12.970299 23057 solver.cpp:397]     Test net output #1: loss = 3.61754 (* 1 = 3.61754 loss)
I0406 16:24:14.924974 23057 solver.cpp:218] Iteration 17244 (0.822063 iter/s, 14.5974s/12 iters), loss = 0.0678084
I0406 16:24:14.925024 23057 solver.cpp:237]     Train net output #0: loss = 0.067808 (* 1 = 0.067808 loss)
I0406 16:24:14.925032 23057 sgd_solver.cpp:105] Iteration 17244, lr = 0.005
I0406 16:24:20.176564 23057 solver.cpp:218] Iteration 17256 (2.28507 iter/s, 5.25149s/12 iters), loss = 0.0527428
I0406 16:24:20.176605 23057 solver.cpp:237]     Train net output #0: loss = 0.0527425 (* 1 = 0.0527425 loss)
I0406 16:24:20.176611 23057 sgd_solver.cpp:105] Iteration 17256, lr = 0.005
I0406 16:24:25.285449 23057 solver.cpp:218] Iteration 17268 (2.3489 iter/s, 5.10879s/12 iters), loss = 0.0706944
I0406 16:24:25.285490 23057 solver.cpp:237]     Train net output #0: loss = 0.070694 (* 1 = 0.070694 loss)
I0406 16:24:25.285496 23057 sgd_solver.cpp:105] Iteration 17268, lr = 0.005
I0406 16:24:30.539232 23057 solver.cpp:218] Iteration 17280 (2.28411 iter/s, 5.25368s/12 iters), loss = 0.0698969
I0406 16:24:30.539393 23057 solver.cpp:237]     Train net output #0: loss = 0.0698965 (* 1 = 0.0698965 loss)
I0406 16:24:30.539404 23057 sgd_solver.cpp:105] Iteration 17280, lr = 0.005
I0406 16:24:35.923117 23057 solver.cpp:218] Iteration 17292 (2.22896 iter/s, 5.38367s/12 iters), loss = 0.054164
I0406 16:24:35.923161 23057 solver.cpp:237]     Train net output #0: loss = 0.0541637 (* 1 = 0.0541637 loss)
I0406 16:24:35.923166 23057 sgd_solver.cpp:105] Iteration 17292, lr = 0.005
I0406 16:24:37.916966 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:24:41.147476 23057 solver.cpp:218] Iteration 17304 (2.29698 iter/s, 5.22426s/12 iters), loss = 0.0537768
I0406 16:24:41.147514 23057 solver.cpp:237]     Train net output #0: loss = 0.0537764 (* 1 = 0.0537764 loss)
I0406 16:24:41.147521 23057 sgd_solver.cpp:105] Iteration 17304, lr = 0.005
I0406 16:24:46.110420 23057 solver.cpp:218] Iteration 17316 (2.41797 iter/s, 4.96285s/12 iters), loss = 0.0626443
I0406 16:24:46.110469 23057 solver.cpp:237]     Train net output #0: loss = 0.062644 (* 1 = 0.062644 loss)
I0406 16:24:46.110477 23057 sgd_solver.cpp:105] Iteration 17316, lr = 0.005
I0406 16:24:51.385888 23057 solver.cpp:218] Iteration 17328 (2.27473 iter/s, 5.27535s/12 iters), loss = 0.137028
I0406 16:24:51.385946 23057 solver.cpp:237]     Train net output #0: loss = 0.137028 (* 1 = 0.137028 loss)
I0406 16:24:51.385955 23057 sgd_solver.cpp:105] Iteration 17328, lr = 0.005
I0406 16:24:56.006719 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17340.caffemodel
I0406 16:25:00.159598 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17340.solverstate
I0406 16:25:02.468806 23057 solver.cpp:330] Iteration 17340, Testing net (#0)
I0406 16:25:02.468878 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:25:03.620110 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:25:04.643889 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:25:06.864769 23057 solver.cpp:397]     Test net output #0: accuracy = 0.429534
I0406 16:25:06.864806 23057 solver.cpp:397]     Test net output #1: loss = 3.594 (* 1 = 3.594 loss)
I0406 16:25:06.999934 23057 solver.cpp:218] Iteration 17340 (0.768549 iter/s, 15.6138s/12 iters), loss = 0.144804
I0406 16:25:06.999985 23057 solver.cpp:237]     Train net output #0: loss = 0.144804 (* 1 = 0.144804 loss)
I0406 16:25:06.999994 23057 sgd_solver.cpp:105] Iteration 17340, lr = 0.005
I0406 16:25:11.378767 23057 solver.cpp:218] Iteration 17352 (2.74052 iter/s, 4.37873s/12 iters), loss = 0.204758
I0406 16:25:11.378832 23057 solver.cpp:237]     Train net output #0: loss = 0.204758 (* 1 = 0.204758 loss)
I0406 16:25:11.378841 23057 sgd_solver.cpp:105] Iteration 17352, lr = 0.005
I0406 16:25:16.639211 23057 solver.cpp:218] Iteration 17364 (2.28123 iter/s, 5.26032s/12 iters), loss = 0.126193
I0406 16:25:16.639256 23057 solver.cpp:237]     Train net output #0: loss = 0.126193 (* 1 = 0.126193 loss)
I0406 16:25:16.639261 23057 sgd_solver.cpp:105] Iteration 17364, lr = 0.005
I0406 16:25:21.711797 23057 solver.cpp:218] Iteration 17376 (2.36571 iter/s, 5.07248s/12 iters), loss = 0.127208
I0406 16:25:21.711846 23057 solver.cpp:237]     Train net output #0: loss = 0.127208 (* 1 = 0.127208 loss)
I0406 16:25:21.711853 23057 sgd_solver.cpp:105] Iteration 17376, lr = 0.005
I0406 16:25:26.949316 23057 solver.cpp:218] Iteration 17388 (2.29121 iter/s, 5.23741s/12 iters), loss = 0.155899
I0406 16:25:26.949359 23057 solver.cpp:237]     Train net output #0: loss = 0.155899 (* 1 = 0.155899 loss)
I0406 16:25:26.949365 23057 sgd_solver.cpp:105] Iteration 17388, lr = 0.005
I0406 16:25:31.355784 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:25:32.350590 23057 solver.cpp:218] Iteration 17400 (2.22174 iter/s, 5.40117s/12 iters), loss = 0.0514163
I0406 16:25:32.350638 23057 solver.cpp:237]     Train net output #0: loss = 0.0514159 (* 1 = 0.0514159 loss)
I0406 16:25:32.350646 23057 sgd_solver.cpp:105] Iteration 17400, lr = 0.005
I0406 16:25:37.555274 23057 solver.cpp:218] Iteration 17412 (2.30566 iter/s, 5.20458s/12 iters), loss = 0.102394
I0406 16:25:37.555415 23057 solver.cpp:237]     Train net output #0: loss = 0.102394 (* 1 = 0.102394 loss)
I0406 16:25:37.555423 23057 sgd_solver.cpp:105] Iteration 17412, lr = 0.005
I0406 16:25:42.757371 23057 solver.cpp:218] Iteration 17424 (2.30685 iter/s, 5.2019s/12 iters), loss = 0.0884851
I0406 16:25:42.757412 23057 solver.cpp:237]     Train net output #0: loss = 0.0884848 (* 1 = 0.0884848 loss)
I0406 16:25:42.757418 23057 sgd_solver.cpp:105] Iteration 17424, lr = 0.005
I0406 16:25:48.140583 23057 solver.cpp:218] Iteration 17436 (2.22919 iter/s, 5.38311s/12 iters), loss = 0.131987
I0406 16:25:48.140626 23057 solver.cpp:237]     Train net output #0: loss = 0.131986 (* 1 = 0.131986 loss)
I0406 16:25:48.140632 23057 sgd_solver.cpp:105] Iteration 17436, lr = 0.005
I0406 16:25:50.292207 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17442.caffemodel
I0406 16:25:53.736912 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17442.solverstate
I0406 16:25:56.048395 23057 solver.cpp:330] Iteration 17442, Testing net (#0)
I0406 16:25:56.048419 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:25:58.205180 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:26:00.386159 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420956
I0406 16:26:00.386193 23057 solver.cpp:397]     Test net output #1: loss = 3.50652 (* 1 = 3.50652 loss)
I0406 16:26:02.388695 23057 solver.cpp:218] Iteration 17448 (0.842227 iter/s, 14.2479s/12 iters), loss = 0.0493857
I0406 16:26:02.388753 23057 solver.cpp:237]     Train net output #0: loss = 0.0493854 (* 1 = 0.0493854 loss)
I0406 16:26:02.388763 23057 sgd_solver.cpp:105] Iteration 17448, lr = 0.005
I0406 16:26:07.792232 23057 solver.cpp:218] Iteration 17460 (2.22082 iter/s, 5.40342s/12 iters), loss = 0.0834141
I0406 16:26:07.792357 23057 solver.cpp:237]     Train net output #0: loss = 0.0834138 (* 1 = 0.0834138 loss)
I0406 16:26:07.792366 23057 sgd_solver.cpp:105] Iteration 17460, lr = 0.005
I0406 16:26:12.859602 23057 solver.cpp:218] Iteration 17472 (2.36818 iter/s, 5.06719s/12 iters), loss = 0.143366
I0406 16:26:12.859640 23057 solver.cpp:237]     Train net output #0: loss = 0.143366 (* 1 = 0.143366 loss)
I0406 16:26:12.859647 23057 sgd_solver.cpp:105] Iteration 17472, lr = 0.005
I0406 16:26:18.234426 23057 solver.cpp:218] Iteration 17484 (2.23267 iter/s, 5.37472s/12 iters), loss = 0.0433828
I0406 16:26:18.234469 23057 solver.cpp:237]     Train net output #0: loss = 0.0433825 (* 1 = 0.0433825 loss)
I0406 16:26:18.234477 23057 sgd_solver.cpp:105] Iteration 17484, lr = 0.005
I0406 16:26:23.406256 23057 solver.cpp:218] Iteration 17496 (2.32031 iter/s, 5.17172s/12 iters), loss = 0.0573753
I0406 16:26:23.406312 23057 solver.cpp:237]     Train net output #0: loss = 0.057375 (* 1 = 0.057375 loss)
I0406 16:26:23.406320 23057 sgd_solver.cpp:105] Iteration 17496, lr = 0.005
I0406 16:26:24.734040 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:26:28.726133 23057 solver.cpp:218] Iteration 17508 (2.25574 iter/s, 5.31976s/12 iters), loss = 0.0682647
I0406 16:26:28.726187 23057 solver.cpp:237]     Train net output #0: loss = 0.0682644 (* 1 = 0.0682644 loss)
I0406 16:26:28.726197 23057 sgd_solver.cpp:105] Iteration 17508, lr = 0.005
I0406 16:26:34.079742 23057 solver.cpp:218] Iteration 17520 (2.24153 iter/s, 5.35349s/12 iters), loss = 0.0813331
I0406 16:26:34.079790 23057 solver.cpp:237]     Train net output #0: loss = 0.0813328 (* 1 = 0.0813328 loss)
I0406 16:26:34.079797 23057 sgd_solver.cpp:105] Iteration 17520, lr = 0.005
I0406 16:26:38.999657 23057 solver.cpp:218] Iteration 17532 (2.43912 iter/s, 4.91981s/12 iters), loss = 0.120944
I0406 16:26:38.999819 23057 solver.cpp:237]     Train net output #0: loss = 0.120944 (* 1 = 0.120944 loss)
I0406 16:26:38.999828 23057 sgd_solver.cpp:105] Iteration 17532, lr = 0.005
I0406 16:26:43.839139 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17544.caffemodel
I0406 16:26:46.954658 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17544.solverstate
I0406 16:26:49.261988 23057 solver.cpp:330] Iteration 17544, Testing net (#0)
I0406 16:26:49.262009 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:26:51.431968 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:26:53.662036 23057 solver.cpp:397]     Test net output #0: accuracy = 0.448529
I0406 16:26:53.662067 23057 solver.cpp:397]     Test net output #1: loss = 3.45782 (* 1 = 3.45782 loss)
I0406 16:26:53.803442 23057 solver.cpp:218] Iteration 17544 (0.81062 iter/s, 14.8035s/12 iters), loss = 0.111979
I0406 16:26:53.803496 23057 solver.cpp:237]     Train net output #0: loss = 0.111979 (* 1 = 0.111979 loss)
I0406 16:26:53.803506 23057 sgd_solver.cpp:105] Iteration 17544, lr = 0.005
I0406 16:26:58.183318 23057 solver.cpp:218] Iteration 17556 (2.73987 iter/s, 4.37977s/12 iters), loss = 0.0257702
I0406 16:26:58.183363 23057 solver.cpp:237]     Train net output #0: loss = 0.0257699 (* 1 = 0.0257699 loss)
I0406 16:26:58.183368 23057 sgd_solver.cpp:105] Iteration 17556, lr = 0.005
I0406 16:27:03.386644 23057 solver.cpp:218] Iteration 17568 (2.30626 iter/s, 5.20322s/12 iters), loss = 0.101315
I0406 16:27:03.386682 23057 solver.cpp:237]     Train net output #0: loss = 0.101315 (* 1 = 0.101315 loss)
I0406 16:27:03.386688 23057 sgd_solver.cpp:105] Iteration 17568, lr = 0.005
I0406 16:27:08.499600 23057 solver.cpp:218] Iteration 17580 (2.34703 iter/s, 5.11285s/12 iters), loss = 0.0537469
I0406 16:27:08.499645 23057 solver.cpp:237]     Train net output #0: loss = 0.0537466 (* 1 = 0.0537466 loss)
I0406 16:27:08.499651 23057 sgd_solver.cpp:105] Iteration 17580, lr = 0.005
I0406 16:27:13.728590 23057 solver.cpp:218] Iteration 17592 (2.29495 iter/s, 5.22888s/12 iters), loss = 0.168746
I0406 16:27:13.728729 23057 solver.cpp:237]     Train net output #0: loss = 0.168745 (* 1 = 0.168745 loss)
I0406 16:27:13.728741 23057 sgd_solver.cpp:105] Iteration 17592, lr = 0.005
I0406 16:27:17.314831 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:27:19.066035 23057 solver.cpp:218] Iteration 17604 (2.24835 iter/s, 5.33725s/12 iters), loss = 0.223168
I0406 16:27:19.066078 23057 solver.cpp:237]     Train net output #0: loss = 0.223168 (* 1 = 0.223168 loss)
I0406 16:27:19.066085 23057 sgd_solver.cpp:105] Iteration 17604, lr = 0.005
I0406 16:27:24.388181 23057 solver.cpp:218] Iteration 17616 (2.25477 iter/s, 5.32204s/12 iters), loss = 0.0789322
I0406 16:27:24.388234 23057 solver.cpp:237]     Train net output #0: loss = 0.0789319 (* 1 = 0.0789319 loss)
I0406 16:27:24.388243 23057 sgd_solver.cpp:105] Iteration 17616, lr = 0.005
I0406 16:27:29.632458 23057 solver.cpp:218] Iteration 17628 (2.28826 iter/s, 5.24417s/12 iters), loss = 0.0864661
I0406 16:27:29.632498 23057 solver.cpp:237]     Train net output #0: loss = 0.0864658 (* 1 = 0.0864658 loss)
I0406 16:27:29.632503 23057 sgd_solver.cpp:105] Iteration 17628, lr = 0.005
I0406 16:27:34.771178 23057 solver.cpp:218] Iteration 17640 (2.33526 iter/s, 5.13862s/12 iters), loss = 0.0543644
I0406 16:27:34.771220 23057 solver.cpp:237]     Train net output #0: loss = 0.0543641 (* 1 = 0.0543641 loss)
I0406 16:27:34.771226 23057 sgd_solver.cpp:105] Iteration 17640, lr = 0.005
I0406 16:27:36.992535 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17646.caffemodel
I0406 16:27:40.409077 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17646.solverstate
I0406 16:27:42.720346 23057 solver.cpp:330] Iteration 17646, Testing net (#0)
I0406 16:27:42.720366 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:27:44.788900 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:27:47.118474 23057 solver.cpp:397]     Test net output #0: accuracy = 0.431373
I0406 16:27:47.118505 23057 solver.cpp:397]     Test net output #1: loss = 3.52931 (* 1 = 3.52931 loss)
I0406 16:27:49.014103 23057 solver.cpp:218] Iteration 17652 (0.842534 iter/s, 14.2428s/12 iters), loss = 0.0963405
I0406 16:27:49.014147 23057 solver.cpp:237]     Train net output #0: loss = 0.0963402 (* 1 = 0.0963402 loss)
I0406 16:27:49.014153 23057 sgd_solver.cpp:105] Iteration 17652, lr = 0.005
I0406 16:27:54.246729 23057 solver.cpp:218] Iteration 17664 (2.29335 iter/s, 5.23252s/12 iters), loss = 0.074731
I0406 16:27:54.246775 23057 solver.cpp:237]     Train net output #0: loss = 0.0747307 (* 1 = 0.0747307 loss)
I0406 16:27:54.246780 23057 sgd_solver.cpp:105] Iteration 17664, lr = 0.005
I0406 16:27:59.496707 23057 solver.cpp:218] Iteration 17676 (2.28577 iter/s, 5.24987s/12 iters), loss = 0.215239
I0406 16:27:59.496750 23057 solver.cpp:237]     Train net output #0: loss = 0.215239 (* 1 = 0.215239 loss)
I0406 16:27:59.496757 23057 sgd_solver.cpp:105] Iteration 17676, lr = 0.005
I0406 16:28:04.593014 23057 solver.cpp:218] Iteration 17688 (2.35469 iter/s, 5.0962s/12 iters), loss = 0.0939912
I0406 16:28:04.593058 23057 solver.cpp:237]     Train net output #0: loss = 0.0939909 (* 1 = 0.0939909 loss)
I0406 16:28:04.593065 23057 sgd_solver.cpp:105] Iteration 17688, lr = 0.005
I0406 16:28:09.898291 23057 solver.cpp:218] Iteration 17700 (2.26195 iter/s, 5.30516s/12 iters), loss = 0.108881
I0406 16:28:09.898330 23057 solver.cpp:237]     Train net output #0: loss = 0.108881 (* 1 = 0.108881 loss)
I0406 16:28:09.898336 23057 sgd_solver.cpp:105] Iteration 17700, lr = 0.005
I0406 16:28:10.476672 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:28:15.497762 23057 solver.cpp:218] Iteration 17712 (2.1431 iter/s, 5.59937s/12 iters), loss = 0.128005
I0406 16:28:15.497922 23057 solver.cpp:237]     Train net output #0: loss = 0.128004 (* 1 = 0.128004 loss)
I0406 16:28:15.497931 23057 sgd_solver.cpp:105] Iteration 17712, lr = 0.005
I0406 16:28:20.553421 23057 solver.cpp:218] Iteration 17724 (2.37368 iter/s, 5.05544s/12 iters), loss = 0.129407
I0406 16:28:20.553465 23057 solver.cpp:237]     Train net output #0: loss = 0.129407 (* 1 = 0.129407 loss)
I0406 16:28:20.553472 23057 sgd_solver.cpp:105] Iteration 17724, lr = 0.005
I0406 16:28:25.650233 23057 solver.cpp:218] Iteration 17736 (2.35446 iter/s, 5.09671s/12 iters), loss = 0.0675781
I0406 16:28:25.650277 23057 solver.cpp:237]     Train net output #0: loss = 0.0675777 (* 1 = 0.0675777 loss)
I0406 16:28:25.650283 23057 sgd_solver.cpp:105] Iteration 17736, lr = 0.005
I0406 16:28:30.567332 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17748.caffemodel
I0406 16:28:33.714884 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17748.solverstate
I0406 16:28:36.020112 23057 solver.cpp:330] Iteration 17748, Testing net (#0)
I0406 16:28:36.020133 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:28:37.974339 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:28:40.297492 23057 solver.cpp:397]     Test net output #0: accuracy = 0.449755
I0406 16:28:40.297523 23057 solver.cpp:397]     Test net output #1: loss = 3.52377 (* 1 = 3.52377 loss)
I0406 16:28:40.428900 23057 solver.cpp:218] Iteration 17748 (0.811991 iter/s, 14.7785s/12 iters), loss = 0.102629
I0406 16:28:40.428944 23057 solver.cpp:237]     Train net output #0: loss = 0.102629 (* 1 = 0.102629 loss)
I0406 16:28:40.428951 23057 sgd_solver.cpp:105] Iteration 17748, lr = 0.005
I0406 16:28:44.829133 23057 solver.cpp:218] Iteration 17760 (2.72719 iter/s, 4.40013s/12 iters), loss = 0.0690623
I0406 16:28:44.829183 23057 solver.cpp:237]     Train net output #0: loss = 0.0690619 (* 1 = 0.0690619 loss)
I0406 16:28:44.829190 23057 sgd_solver.cpp:105] Iteration 17760, lr = 0.005
I0406 16:28:50.021175 23057 solver.cpp:218] Iteration 17772 (2.31128 iter/s, 5.19194s/12 iters), loss = 0.0880207
I0406 16:28:50.021270 23057 solver.cpp:237]     Train net output #0: loss = 0.0880203 (* 1 = 0.0880203 loss)
I0406 16:28:50.021276 23057 sgd_solver.cpp:105] Iteration 17772, lr = 0.005
I0406 16:28:55.319420 23057 solver.cpp:218] Iteration 17784 (2.26497 iter/s, 5.29808s/12 iters), loss = 0.126198
I0406 16:28:55.319481 23057 solver.cpp:237]     Train net output #0: loss = 0.126198 (* 1 = 0.126198 loss)
I0406 16:28:55.319491 23057 sgd_solver.cpp:105] Iteration 17784, lr = 0.005
I0406 16:29:00.671533 23057 solver.cpp:218] Iteration 17796 (2.24216 iter/s, 5.35199s/12 iters), loss = 0.0606754
I0406 16:29:00.671600 23057 solver.cpp:237]     Train net output #0: loss = 0.0606751 (* 1 = 0.0606751 loss)
I0406 16:29:00.671608 23057 sgd_solver.cpp:105] Iteration 17796, lr = 0.005
I0406 16:29:03.498495 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:29:05.936288 23057 solver.cpp:218] Iteration 17808 (2.27936 iter/s, 5.26463s/12 iters), loss = 0.0844266
I0406 16:29:05.936340 23057 solver.cpp:237]     Train net output #0: loss = 0.0844263 (* 1 = 0.0844263 loss)
I0406 16:29:05.936348 23057 sgd_solver.cpp:105] Iteration 17808, lr = 0.005
I0406 16:29:11.239269 23057 solver.cpp:218] Iteration 17820 (2.26293 iter/s, 5.30287s/12 iters), loss = 0.20848
I0406 16:29:11.239328 23057 solver.cpp:237]     Train net output #0: loss = 0.208479 (* 1 = 0.208479 loss)
I0406 16:29:11.239337 23057 sgd_solver.cpp:105] Iteration 17820, lr = 0.005
I0406 16:29:16.555364 23057 solver.cpp:218] Iteration 17832 (2.25735 iter/s, 5.31598s/12 iters), loss = 0.0631119
I0406 16:29:16.555423 23057 solver.cpp:237]     Train net output #0: loss = 0.0631116 (* 1 = 0.0631116 loss)
I0406 16:29:16.555433 23057 sgd_solver.cpp:105] Iteration 17832, lr = 0.005
I0406 16:29:21.778123 23057 solver.cpp:218] Iteration 17844 (2.29769 iter/s, 5.22264s/12 iters), loss = 0.0983457
I0406 16:29:21.778270 23057 solver.cpp:237]     Train net output #0: loss = 0.0983454 (* 1 = 0.0983454 loss)
I0406 16:29:21.778277 23057 sgd_solver.cpp:105] Iteration 17844, lr = 0.005
I0406 16:29:23.716346 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17850.caffemodel
I0406 16:29:26.697749 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17850.solverstate
I0406 16:29:29.022047 23057 solver.cpp:330] Iteration 17850, Testing net (#0)
I0406 16:29:29.022068 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:29:31.000427 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:29:33.341070 23057 solver.cpp:397]     Test net output #0: accuracy = 0.45527
I0406 16:29:33.341102 23057 solver.cpp:397]     Test net output #1: loss = 3.59122 (* 1 = 3.59122 loss)
I0406 16:29:35.306741 23057 solver.cpp:218] Iteration 17856 (0.887026 iter/s, 13.5283s/12 iters), loss = 0.103967
I0406 16:29:35.306792 23057 solver.cpp:237]     Train net output #0: loss = 0.103967 (* 1 = 0.103967 loss)
I0406 16:29:35.306799 23057 sgd_solver.cpp:105] Iteration 17856, lr = 0.005
I0406 16:29:40.667582 23057 solver.cpp:218] Iteration 17868 (2.2385 iter/s, 5.36073s/12 iters), loss = 0.0721101
I0406 16:29:40.667642 23057 solver.cpp:237]     Train net output #0: loss = 0.0721098 (* 1 = 0.0721098 loss)
I0406 16:29:40.667651 23057 sgd_solver.cpp:105] Iteration 17868, lr = 0.005
I0406 16:29:45.947309 23057 solver.cpp:218] Iteration 17880 (2.2729 iter/s, 5.2796s/12 iters), loss = 0.0243671
I0406 16:29:45.947368 23057 solver.cpp:237]     Train net output #0: loss = 0.0243668 (* 1 = 0.0243668 loss)
I0406 16:29:45.947376 23057 sgd_solver.cpp:105] Iteration 17880, lr = 0.005
I0406 16:29:51.259649 23057 solver.cpp:218] Iteration 17892 (2.25894 iter/s, 5.31222s/12 iters), loss = 0.10826
I0406 16:29:51.259702 23057 solver.cpp:237]     Train net output #0: loss = 0.108259 (* 1 = 0.108259 loss)
I0406 16:29:51.259711 23057 sgd_solver.cpp:105] Iteration 17892, lr = 0.005
I0406 16:29:56.221560 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:29:56.471158 23057 solver.cpp:218] Iteration 17904 (2.30264 iter/s, 5.2114s/12 iters), loss = 0.0926427
I0406 16:29:56.471196 23057 solver.cpp:237]     Train net output #0: loss = 0.0926424 (* 1 = 0.0926424 loss)
I0406 16:29:56.471202 23057 sgd_solver.cpp:105] Iteration 17904, lr = 0.005
I0406 16:30:01.565791 23057 solver.cpp:218] Iteration 17916 (2.35547 iter/s, 5.09453s/12 iters), loss = 0.0565668
I0406 16:30:01.565835 23057 solver.cpp:237]     Train net output #0: loss = 0.0565664 (* 1 = 0.0565664 loss)
I0406 16:30:01.565841 23057 sgd_solver.cpp:105] Iteration 17916, lr = 0.005
I0406 16:30:06.586978 23057 solver.cpp:218] Iteration 17928 (2.38993 iter/s, 5.02108s/12 iters), loss = 0.120283
I0406 16:30:06.587029 23057 solver.cpp:237]     Train net output #0: loss = 0.120283 (* 1 = 0.120283 loss)
I0406 16:30:06.587035 23057 sgd_solver.cpp:105] Iteration 17928, lr = 0.005
I0406 16:30:11.773912 23057 solver.cpp:218] Iteration 17940 (2.31355 iter/s, 5.18682s/12 iters), loss = 0.201249
I0406 16:30:11.773952 23057 solver.cpp:237]     Train net output #0: loss = 0.201249 (* 1 = 0.201249 loss)
I0406 16:30:11.773958 23057 sgd_solver.cpp:105] Iteration 17940, lr = 0.005
I0406 16:30:16.677315 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17952.caffemodel
I0406 16:30:19.743479 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17952.solverstate
I0406 16:30:22.046600 23057 solver.cpp:330] Iteration 17952, Testing net (#0)
I0406 16:30:22.046624 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:30:24.041103 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:30:26.451524 23057 solver.cpp:397]     Test net output #0: accuracy = 0.434436
I0406 16:30:26.451685 23057 solver.cpp:397]     Test net output #1: loss = 3.61951 (* 1 = 3.61951 loss)
I0406 16:30:26.592208 23057 solver.cpp:218] Iteration 17952 (0.80982 iter/s, 14.8181s/12 iters), loss = 0.147293
I0406 16:30:26.592273 23057 solver.cpp:237]     Train net output #0: loss = 0.147293 (* 1 = 0.147293 loss)
I0406 16:30:26.592283 23057 sgd_solver.cpp:105] Iteration 17952, lr = 0.005
I0406 16:30:30.778796 23057 solver.cpp:218] Iteration 17964 (2.86637 iter/s, 4.18647s/12 iters), loss = 0.0374083
I0406 16:30:30.778841 23057 solver.cpp:237]     Train net output #0: loss = 0.0374079 (* 1 = 0.0374079 loss)
I0406 16:30:30.778847 23057 sgd_solver.cpp:105] Iteration 17964, lr = 0.005
I0406 16:30:36.124018 23057 solver.cpp:218] Iteration 17976 (2.24504 iter/s, 5.34512s/12 iters), loss = 0.144355
I0406 16:30:36.124060 23057 solver.cpp:237]     Train net output #0: loss = 0.144355 (* 1 = 0.144355 loss)
I0406 16:30:36.124066 23057 sgd_solver.cpp:105] Iteration 17976, lr = 0.005
I0406 16:30:41.309563 23057 solver.cpp:218] Iteration 17988 (2.31417 iter/s, 5.18544s/12 iters), loss = 0.0680317
I0406 16:30:41.309602 23057 solver.cpp:237]     Train net output #0: loss = 0.0680314 (* 1 = 0.0680314 loss)
I0406 16:30:41.309608 23057 sgd_solver.cpp:105] Iteration 17988, lr = 0.005
I0406 16:30:46.716030 23057 solver.cpp:218] Iteration 18000 (2.21961 iter/s, 5.40636s/12 iters), loss = 0.0535121
I0406 16:30:46.716090 23057 solver.cpp:237]     Train net output #0: loss = 0.0535118 (* 1 = 0.0535118 loss)
I0406 16:30:46.716099 23057 sgd_solver.cpp:105] Iteration 18000, lr = 0.005
I0406 16:30:48.656617 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:30:51.806380 23057 solver.cpp:218] Iteration 18012 (2.35746 iter/s, 5.09023s/12 iters), loss = 0.106333
I0406 16:30:51.806423 23057 solver.cpp:237]     Train net output #0: loss = 0.106332 (* 1 = 0.106332 loss)
I0406 16:30:51.806430 23057 sgd_solver.cpp:105] Iteration 18012, lr = 0.005
I0406 16:30:56.883808 23057 solver.cpp:218] Iteration 18024 (2.36345 iter/s, 5.07733s/12 iters), loss = 0.0617682
I0406 16:30:56.883939 23057 solver.cpp:237]     Train net output #0: loss = 0.061768 (* 1 = 0.061768 loss)
I0406 16:30:56.883949 23057 sgd_solver.cpp:105] Iteration 18024, lr = 0.005
I0406 16:31:02.142565 23057 solver.cpp:218] Iteration 18036 (2.28199 iter/s, 5.25857s/12 iters), loss = 0.150869
I0406 16:31:02.142611 23057 solver.cpp:237]     Train net output #0: loss = 0.150869 (* 1 = 0.150869 loss)
I0406 16:31:02.142617 23057 sgd_solver.cpp:105] Iteration 18036, lr = 0.005
I0406 16:31:02.142799 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:31:07.503965 23057 solver.cpp:218] Iteration 18048 (2.23826 iter/s, 5.3613s/12 iters), loss = 0.0191413
I0406 16:31:07.504004 23057 solver.cpp:237]     Train net output #0: loss = 0.019141 (* 1 = 0.019141 loss)
I0406 16:31:07.504010 23057 sgd_solver.cpp:105] Iteration 18048, lr = 0.005
I0406 16:31:09.471060 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18054.caffemodel
I0406 16:31:12.905385 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18054.solverstate
I0406 16:31:15.214860 23057 solver.cpp:330] Iteration 18054, Testing net (#0)
I0406 16:31:15.214884 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:31:17.053618 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:31:19.487493 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422181
I0406 16:31:19.487520 23057 solver.cpp:397]     Test net output #1: loss = 3.47803 (* 1 = 3.47803 loss)
I0406 16:31:21.354384 23057 solver.cpp:218] Iteration 18060 (0.866411 iter/s, 13.8502s/12 iters), loss = 0.106546
I0406 16:31:21.354439 23057 solver.cpp:237]     Train net output #0: loss = 0.106546 (* 1 = 0.106546 loss)
I0406 16:31:21.354449 23057 sgd_solver.cpp:105] Iteration 18060, lr = 0.005
I0406 16:31:26.586800 23057 solver.cpp:218] Iteration 18072 (2.29345 iter/s, 5.2323s/12 iters), loss = 0.0997001
I0406 16:31:26.586848 23057 solver.cpp:237]     Train net output #0: loss = 0.0996999 (* 1 = 0.0996999 loss)
I0406 16:31:26.586853 23057 sgd_solver.cpp:105] Iteration 18072, lr = 0.005
I0406 16:31:31.684722 23057 solver.cpp:218] Iteration 18084 (2.35395 iter/s, 5.09782s/12 iters), loss = 0.0152083
I0406 16:31:31.684849 23057 solver.cpp:237]     Train net output #0: loss = 0.0152081 (* 1 = 0.0152081 loss)
I0406 16:31:31.684855 23057 sgd_solver.cpp:105] Iteration 18084, lr = 0.005
I0406 16:31:36.936141 23057 solver.cpp:218] Iteration 18096 (2.28518 iter/s, 5.25123s/12 iters), loss = 0.154479
I0406 16:31:36.936184 23057 solver.cpp:237]     Train net output #0: loss = 0.154479 (* 1 = 0.154479 loss)
I0406 16:31:36.936190 23057 sgd_solver.cpp:105] Iteration 18096, lr = 0.005
I0406 16:31:41.110889 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:31:42.165791 23057 solver.cpp:218] Iteration 18108 (2.29466 iter/s, 5.22954s/12 iters), loss = 0.0299869
I0406 16:31:42.165849 23057 solver.cpp:237]     Train net output #0: loss = 0.0299866 (* 1 = 0.0299866 loss)
I0406 16:31:42.165858 23057 sgd_solver.cpp:105] Iteration 18108, lr = 0.005
I0406 16:31:47.631728 23057 solver.cpp:218] Iteration 18120 (2.19546 iter/s, 5.46583s/12 iters), loss = 0.147974
I0406 16:31:47.631767 23057 solver.cpp:237]     Train net output #0: loss = 0.147974 (* 1 = 0.147974 loss)
I0406 16:31:47.631772 23057 sgd_solver.cpp:105] Iteration 18120, lr = 0.005
I0406 16:31:52.955896 23057 solver.cpp:218] Iteration 18132 (2.25392 iter/s, 5.32407s/12 iters), loss = 0.0625603
I0406 16:31:52.955940 23057 solver.cpp:237]     Train net output #0: loss = 0.06256 (* 1 = 0.06256 loss)
I0406 16:31:52.955946 23057 sgd_solver.cpp:105] Iteration 18132, lr = 0.005
I0406 16:31:58.246783 23057 solver.cpp:218] Iteration 18144 (2.2681 iter/s, 5.29078s/12 iters), loss = 0.0719966
I0406 16:31:58.246825 23057 solver.cpp:237]     Train net output #0: loss = 0.0719963 (* 1 = 0.0719963 loss)
I0406 16:31:58.246831 23057 sgd_solver.cpp:105] Iteration 18144, lr = 0.005
I0406 16:32:02.930598 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18156.caffemodel
I0406 16:32:06.804137 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18156.solverstate
I0406 16:32:09.108613 23057 solver.cpp:330] Iteration 18156, Testing net (#0)
I0406 16:32:09.108634 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:32:10.970765 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:32:13.436615 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425858
I0406 16:32:13.436650 23057 solver.cpp:397]     Test net output #1: loss = 3.54356 (* 1 = 3.54356 loss)
I0406 16:32:13.576898 23057 solver.cpp:218] Iteration 18156 (0.782783 iter/s, 15.3299s/12 iters), loss = 0.0316716
I0406 16:32:13.576953 23057 solver.cpp:237]     Train net output #0: loss = 0.0316713 (* 1 = 0.0316713 loss)
I0406 16:32:13.576962 23057 sgd_solver.cpp:105] Iteration 18156, lr = 0.005
I0406 16:32:17.844836 23057 solver.cpp:218] Iteration 18168 (2.81174 iter/s, 4.26782s/12 iters), loss = 0.0828187
I0406 16:32:17.844898 23057 solver.cpp:237]     Train net output #0: loss = 0.0828184 (* 1 = 0.0828184 loss)
I0406 16:32:17.844907 23057 sgd_solver.cpp:105] Iteration 18168, lr = 0.005
I0406 16:32:23.125988 23057 solver.cpp:218] Iteration 18180 (2.27228 iter/s, 5.28104s/12 iters), loss = 0.120411
I0406 16:32:23.126040 23057 solver.cpp:237]     Train net output #0: loss = 0.12041 (* 1 = 0.12041 loss)
I0406 16:32:23.126049 23057 sgd_solver.cpp:105] Iteration 18180, lr = 0.005
I0406 16:32:28.612215 23057 solver.cpp:218] Iteration 18192 (2.18734 iter/s, 5.48611s/12 iters), loss = 0.103692
I0406 16:32:28.612262 23057 solver.cpp:237]     Train net output #0: loss = 0.103691 (* 1 = 0.103691 loss)
I0406 16:32:28.612268 23057 sgd_solver.cpp:105] Iteration 18192, lr = 0.005
I0406 16:32:33.982172 23057 solver.cpp:218] Iteration 18204 (2.2347 iter/s, 5.36985s/12 iters), loss = 0.071684
I0406 16:32:33.982316 23057 solver.cpp:237]     Train net output #0: loss = 0.0716837 (* 1 = 0.0716837 loss)
I0406 16:32:33.982322 23057 sgd_solver.cpp:105] Iteration 18204, lr = 0.005
I0406 16:32:35.274401 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:32:39.256837 23057 solver.cpp:218] Iteration 18216 (2.27511 iter/s, 5.27446s/12 iters), loss = 0.031867
I0406 16:32:39.256886 23057 solver.cpp:237]     Train net output #0: loss = 0.0318667 (* 1 = 0.0318667 loss)
I0406 16:32:39.256893 23057 sgd_solver.cpp:105] Iteration 18216, lr = 0.005
I0406 16:32:44.504815 23057 solver.cpp:218] Iteration 18228 (2.28664 iter/s, 5.24788s/12 iters), loss = 0.0758826
I0406 16:32:44.504855 23057 solver.cpp:237]     Train net output #0: loss = 0.0758824 (* 1 = 0.0758824 loss)
I0406 16:32:44.504861 23057 sgd_solver.cpp:105] Iteration 18228, lr = 0.005
I0406 16:32:49.844631 23057 solver.cpp:218] Iteration 18240 (2.24731 iter/s, 5.33971s/12 iters), loss = 0.156599
I0406 16:32:49.844673 23057 solver.cpp:237]     Train net output #0: loss = 0.156598 (* 1 = 0.156598 loss)
I0406 16:32:49.844678 23057 sgd_solver.cpp:105] Iteration 18240, lr = 0.005
I0406 16:32:55.196200 23057 solver.cpp:218] Iteration 18252 (2.24238 iter/s, 5.35147s/12 iters), loss = 0.134388
I0406 16:32:55.196250 23057 solver.cpp:237]     Train net output #0: loss = 0.134387 (* 1 = 0.134387 loss)
I0406 16:32:55.196259 23057 sgd_solver.cpp:105] Iteration 18252, lr = 0.005
I0406 16:32:57.338097 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18258.caffemodel
I0406 16:33:00.357369 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18258.solverstate
I0406 16:33:02.654312 23057 solver.cpp:330] Iteration 18258, Testing net (#0)
I0406 16:33:02.654330 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:33:04.516606 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:33:07.055483 23057 solver.cpp:397]     Test net output #0: accuracy = 0.432598
I0406 16:33:07.055519 23057 solver.cpp:397]     Test net output #1: loss = 3.63704 (* 1 = 3.63704 loss)
I0406 16:33:09.024964 23057 solver.cpp:218] Iteration 18264 (0.867767 iter/s, 13.8286s/12 iters), loss = 0.01628
I0406 16:33:09.025010 23057 solver.cpp:237]     Train net output #0: loss = 0.0162798 (* 1 = 0.0162798 loss)
I0406 16:33:09.025018 23057 sgd_solver.cpp:105] Iteration 18264, lr = 0.005
I0406 16:33:14.408921 23057 solver.cpp:218] Iteration 18276 (2.22889 iter/s, 5.38385s/12 iters), loss = 0.0370573
I0406 16:33:14.408958 23057 solver.cpp:237]     Train net output #0: loss = 0.037057 (* 1 = 0.037057 loss)
I0406 16:33:14.408964 23057 sgd_solver.cpp:105] Iteration 18276, lr = 0.005
I0406 16:33:19.583204 23057 solver.cpp:218] Iteration 18288 (2.31921 iter/s, 5.17419s/12 iters), loss = 0.0729153
I0406 16:33:19.583254 23057 solver.cpp:237]     Train net output #0: loss = 0.072915 (* 1 = 0.072915 loss)
I0406 16:33:19.583261 23057 sgd_solver.cpp:105] Iteration 18288, lr = 0.005
I0406 16:33:24.638711 23057 solver.cpp:218] Iteration 18300 (2.3737 iter/s, 5.0554s/12 iters), loss = 0.0660958
I0406 16:33:24.638756 23057 solver.cpp:237]     Train net output #0: loss = 0.0660955 (* 1 = 0.0660955 loss)
I0406 16:33:24.638762 23057 sgd_solver.cpp:105] Iteration 18300, lr = 0.005
I0406 16:33:28.113130 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:33:29.813480 23057 solver.cpp:218] Iteration 18312 (2.31899 iter/s, 5.17466s/12 iters), loss = 0.0770659
I0406 16:33:29.813520 23057 solver.cpp:237]     Train net output #0: loss = 0.0770656 (* 1 = 0.0770656 loss)
I0406 16:33:29.813526 23057 sgd_solver.cpp:105] Iteration 18312, lr = 0.005
I0406 16:33:35.208211 23057 solver.cpp:218] Iteration 18324 (2.22443 iter/s, 5.39463s/12 iters), loss = 0.0583577
I0406 16:33:35.208348 23057 solver.cpp:237]     Train net output #0: loss = 0.0583574 (* 1 = 0.0583574 loss)
I0406 16:33:35.208356 23057 sgd_solver.cpp:105] Iteration 18324, lr = 0.005
I0406 16:33:40.108601 23057 solver.cpp:218] Iteration 18336 (2.44888 iter/s, 4.9002s/12 iters), loss = 0.0578664
I0406 16:33:40.108649 23057 solver.cpp:237]     Train net output #0: loss = 0.0578661 (* 1 = 0.0578661 loss)
I0406 16:33:40.108657 23057 sgd_solver.cpp:105] Iteration 18336, lr = 0.005
I0406 16:33:45.409796 23057 solver.cpp:218] Iteration 18348 (2.26369 iter/s, 5.30109s/12 iters), loss = 0.0865694
I0406 16:33:45.409837 23057 solver.cpp:237]     Train net output #0: loss = 0.0865691 (* 1 = 0.0865691 loss)
I0406 16:33:45.409843 23057 sgd_solver.cpp:105] Iteration 18348, lr = 0.005
I0406 16:33:50.030222 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18360.caffemodel
I0406 16:33:53.059031 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18360.solverstate
I0406 16:33:55.356003 23057 solver.cpp:330] Iteration 18360, Testing net (#0)
I0406 16:33:55.356021 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:33:57.110992 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:33:59.712841 23057 solver.cpp:397]     Test net output #0: accuracy = 0.439338
I0406 16:33:59.712878 23057 solver.cpp:397]     Test net output #1: loss = 3.47182 (* 1 = 3.47182 loss)
I0406 16:33:59.853106 23057 solver.cpp:218] Iteration 18360 (0.830845 iter/s, 14.4431s/12 iters), loss = 0.170337
I0406 16:33:59.853149 23057 solver.cpp:237]     Train net output #0: loss = 0.170337 (* 1 = 0.170337 loss)
I0406 16:33:59.853155 23057 sgd_solver.cpp:105] Iteration 18360, lr = 0.005
I0406 16:34:04.257418 23057 solver.cpp:218] Iteration 18372 (2.72466 iter/s, 4.40421s/12 iters), loss = 0.117858
I0406 16:34:04.257467 23057 solver.cpp:237]     Train net output #0: loss = 0.117857 (* 1 = 0.117857 loss)
I0406 16:34:04.257477 23057 sgd_solver.cpp:105] Iteration 18372, lr = 0.005
I0406 16:34:09.652796 23057 solver.cpp:218] Iteration 18384 (2.22417 iter/s, 5.39527s/12 iters), loss = 0.128989
I0406 16:34:09.652910 23057 solver.cpp:237]     Train net output #0: loss = 0.128989 (* 1 = 0.128989 loss)
I0406 16:34:09.652917 23057 sgd_solver.cpp:105] Iteration 18384, lr = 0.005
I0406 16:34:14.718783 23057 solver.cpp:218] Iteration 18396 (2.36882 iter/s, 5.06582s/12 iters), loss = 0.102181
I0406 16:34:14.718827 23057 solver.cpp:237]     Train net output #0: loss = 0.102181 (* 1 = 0.102181 loss)
I0406 16:34:14.718832 23057 sgd_solver.cpp:105] Iteration 18396, lr = 0.005
I0406 16:34:20.069026 23057 solver.cpp:218] Iteration 18408 (2.24293 iter/s, 5.35014s/12 iters), loss = 0.179582
I0406 16:34:20.069065 23057 solver.cpp:237]     Train net output #0: loss = 0.179582 (* 1 = 0.179582 loss)
I0406 16:34:20.069072 23057 sgd_solver.cpp:105] Iteration 18408, lr = 0.005
I0406 16:34:20.653802 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:34:25.451656 23057 solver.cpp:218] Iteration 18420 (2.22944 iter/s, 5.38253s/12 iters), loss = 0.0895095
I0406 16:34:25.451699 23057 solver.cpp:237]     Train net output #0: loss = 0.0895092 (* 1 = 0.0895092 loss)
I0406 16:34:25.451704 23057 sgd_solver.cpp:105] Iteration 18420, lr = 0.005
I0406 16:34:30.666764 23057 solver.cpp:218] Iteration 18432 (2.30105 iter/s, 5.215s/12 iters), loss = 0.0907952
I0406 16:34:30.666819 23057 solver.cpp:237]     Train net output #0: loss = 0.0907949 (* 1 = 0.0907949 loss)
I0406 16:34:30.666827 23057 sgd_solver.cpp:105] Iteration 18432, lr = 0.005
I0406 16:34:35.811851 23057 solver.cpp:218] Iteration 18444 (2.33237 iter/s, 5.14497s/12 iters), loss = 0.0609804
I0406 16:34:35.811894 23057 solver.cpp:237]     Train net output #0: loss = 0.0609801 (* 1 = 0.0609801 loss)
I0406 16:34:35.811899 23057 sgd_solver.cpp:105] Iteration 18444, lr = 0.005
I0406 16:34:41.011256 23057 solver.cpp:218] Iteration 18456 (2.308 iter/s, 5.1993s/12 iters), loss = 0.0387664
I0406 16:34:41.011371 23057 solver.cpp:237]     Train net output #0: loss = 0.0387661 (* 1 = 0.0387661 loss)
I0406 16:34:41.011379 23057 sgd_solver.cpp:105] Iteration 18456, lr = 0.005
I0406 16:34:43.144385 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18462.caffemodel
I0406 16:34:46.276775 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18462.solverstate
I0406 16:34:48.575474 23057 solver.cpp:330] Iteration 18462, Testing net (#0)
I0406 16:34:48.575495 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:34:50.351843 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:34:52.967435 23057 solver.cpp:397]     Test net output #0: accuracy = 0.431985
I0406 16:34:52.967471 23057 solver.cpp:397]     Test net output #1: loss = 3.48149 (* 1 = 3.48149 loss)
I0406 16:34:54.919793 23057 solver.cpp:218] Iteration 18468 (0.862795 iter/s, 13.9083s/12 iters), loss = 0.0430049
I0406 16:34:54.919852 23057 solver.cpp:237]     Train net output #0: loss = 0.0430046 (* 1 = 0.0430046 loss)
I0406 16:34:54.919859 23057 sgd_solver.cpp:105] Iteration 18468, lr = 0.005
I0406 16:35:00.182209 23057 solver.cpp:218] Iteration 18480 (2.28037 iter/s, 5.2623s/12 iters), loss = 0.204957
I0406 16:35:00.182261 23057 solver.cpp:237]     Train net output #0: loss = 0.204957 (* 1 = 0.204957 loss)
I0406 16:35:00.182269 23057 sgd_solver.cpp:105] Iteration 18480, lr = 0.005
I0406 16:35:05.507081 23057 solver.cpp:218] Iteration 18492 (2.25362 iter/s, 5.32477s/12 iters), loss = 0.170274
I0406 16:35:05.507117 23057 solver.cpp:237]     Train net output #0: loss = 0.170274 (* 1 = 0.170274 loss)
I0406 16:35:05.507124 23057 sgd_solver.cpp:105] Iteration 18492, lr = 0.005
I0406 16:35:10.751075 23057 solver.cpp:218] Iteration 18504 (2.28838 iter/s, 5.24389s/12 iters), loss = 0.0212777
I0406 16:35:10.751121 23057 solver.cpp:237]     Train net output #0: loss = 0.0212775 (* 1 = 0.0212775 loss)
I0406 16:35:10.751127 23057 sgd_solver.cpp:105] Iteration 18504, lr = 0.005
I0406 16:35:13.664862 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:35:16.223829 23057 solver.cpp:218] Iteration 18516 (2.19272 iter/s, 5.47264s/12 iters), loss = 0.10877
I0406 16:35:16.223870 23057 solver.cpp:237]     Train net output #0: loss = 0.10877 (* 1 = 0.10877 loss)
I0406 16:35:16.223876 23057 sgd_solver.cpp:105] Iteration 18516, lr = 0.005
I0406 16:35:21.258127 23057 solver.cpp:218] Iteration 18528 (2.3837 iter/s, 5.03419s/12 iters), loss = 0.0439571
I0406 16:35:21.258183 23057 solver.cpp:237]     Train net output #0: loss = 0.0439568 (* 1 = 0.0439568 loss)
I0406 16:35:21.258191 23057 sgd_solver.cpp:105] Iteration 18528, lr = 0.005
I0406 16:35:26.689955 23057 solver.cpp:218] Iteration 18540 (2.20925 iter/s, 5.43171s/12 iters), loss = 0.0627131
I0406 16:35:26.690004 23057 solver.cpp:237]     Train net output #0: loss = 0.0627128 (* 1 = 0.0627128 loss)
I0406 16:35:26.690012 23057 sgd_solver.cpp:105] Iteration 18540, lr = 0.005
I0406 16:35:31.960433 23057 solver.cpp:218] Iteration 18552 (2.27688 iter/s, 5.27036s/12 iters), loss = 0.00517424
I0406 16:35:31.960477 23057 solver.cpp:237]     Train net output #0: loss = 0.00517397 (* 1 = 0.00517397 loss)
I0406 16:35:31.960484 23057 sgd_solver.cpp:105] Iteration 18552, lr = 0.005
I0406 16:35:36.432158 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18564.caffemodel
I0406 16:35:39.473548 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18564.solverstate
I0406 16:35:41.779268 23057 solver.cpp:330] Iteration 18564, Testing net (#0)
I0406 16:35:41.779292 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:35:43.552546 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:35:46.312567 23057 solver.cpp:397]     Test net output #0: accuracy = 0.431985
I0406 16:35:46.312713 23057 solver.cpp:397]     Test net output #1: loss = 3.40038 (* 1 = 3.40038 loss)
I0406 16:35:46.449894 23057 solver.cpp:218] Iteration 18564 (0.828199 iter/s, 14.4893s/12 iters), loss = 0.12286
I0406 16:35:46.449957 23057 solver.cpp:237]     Train net output #0: loss = 0.12286 (* 1 = 0.12286 loss)
I0406 16:35:46.449967 23057 sgd_solver.cpp:105] Iteration 18564, lr = 0.005
I0406 16:35:50.835701 23057 solver.cpp:218] Iteration 18576 (2.73617 iter/s, 4.38569s/12 iters), loss = 0.117092
I0406 16:35:50.835754 23057 solver.cpp:237]     Train net output #0: loss = 0.117092 (* 1 = 0.117092 loss)
I0406 16:35:50.835762 23057 sgd_solver.cpp:105] Iteration 18576, lr = 0.005
I0406 16:35:56.087569 23057 solver.cpp:218] Iteration 18588 (2.28495 iter/s, 5.25175s/12 iters), loss = 0.0613177
I0406 16:35:56.087621 23057 solver.cpp:237]     Train net output #0: loss = 0.0613175 (* 1 = 0.0613175 loss)
I0406 16:35:56.087628 23057 sgd_solver.cpp:105] Iteration 18588, lr = 0.005
I0406 16:36:01.323019 23057 solver.cpp:218] Iteration 18600 (2.29211 iter/s, 5.23534s/12 iters), loss = 0.0534719
I0406 16:36:01.323062 23057 solver.cpp:237]     Train net output #0: loss = 0.0534717 (* 1 = 0.0534717 loss)
I0406 16:36:01.323068 23057 sgd_solver.cpp:105] Iteration 18600, lr = 0.005
I0406 16:36:06.456179 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:36:06.675218 23057 solver.cpp:218] Iteration 18612 (2.24211 iter/s, 5.35209s/12 iters), loss = 0.0716052
I0406 16:36:06.675264 23057 solver.cpp:237]     Train net output #0: loss = 0.0716049 (* 1 = 0.0716049 loss)
I0406 16:36:06.675271 23057 sgd_solver.cpp:105] Iteration 18612, lr = 0.005
I0406 16:36:11.970448 23057 solver.cpp:218] Iteration 18624 (2.26624 iter/s, 5.29512s/12 iters), loss = 0.158594
I0406 16:36:11.970508 23057 solver.cpp:237]     Train net output #0: loss = 0.158594 (* 1 = 0.158594 loss)
I0406 16:36:11.970517 23057 sgd_solver.cpp:105] Iteration 18624, lr = 0.005
I0406 16:36:17.321941 23057 solver.cpp:218] Iteration 18636 (2.24241 iter/s, 5.35137s/12 iters), loss = 0.114848
I0406 16:36:17.322026 23057 solver.cpp:237]     Train net output #0: loss = 0.114848 (* 1 = 0.114848 loss)
I0406 16:36:17.322032 23057 sgd_solver.cpp:105] Iteration 18636, lr = 0.005
I0406 16:36:22.574462 23057 solver.cpp:218] Iteration 18648 (2.28468 iter/s, 5.25238s/12 iters), loss = 0.0313962
I0406 16:36:22.574503 23057 solver.cpp:237]     Train net output #0: loss = 0.0313959 (* 1 = 0.0313959 loss)
I0406 16:36:22.574509 23057 sgd_solver.cpp:105] Iteration 18648, lr = 0.005
I0406 16:36:27.910769 23057 solver.cpp:218] Iteration 18660 (2.24879 iter/s, 5.3362s/12 iters), loss = 0.0652476
I0406 16:36:27.910816 23057 solver.cpp:237]     Train net output #0: loss = 0.0652473 (* 1 = 0.0652473 loss)
I0406 16:36:27.910822 23057 sgd_solver.cpp:105] Iteration 18660, lr = 0.005
I0406 16:36:29.989538 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18666.caffemodel
I0406 16:36:32.993623 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18666.solverstate
I0406 16:36:35.298723 23057 solver.cpp:330] Iteration 18666, Testing net (#0)
I0406 16:36:35.298746 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:36:37.034094 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:36:39.735515 23057 solver.cpp:397]     Test net output #0: accuracy = 0.430147
I0406 16:36:39.735553 23057 solver.cpp:397]     Test net output #1: loss = 3.47991 (* 1 = 3.47991 loss)
I0406 16:36:41.562402 23057 solver.cpp:218] Iteration 18672 (0.879027 iter/s, 13.6515s/12 iters), loss = 0.0555178
I0406 16:36:41.562443 23057 solver.cpp:237]     Train net output #0: loss = 0.0555175 (* 1 = 0.0555175 loss)
I0406 16:36:41.562448 23057 sgd_solver.cpp:105] Iteration 18672, lr = 0.005
I0406 16:36:46.749552 23057 solver.cpp:218] Iteration 18684 (2.31346 iter/s, 5.18705s/12 iters), loss = 0.0715787
I0406 16:36:46.749609 23057 solver.cpp:237]     Train net output #0: loss = 0.0715784 (* 1 = 0.0715784 loss)
I0406 16:36:46.749619 23057 sgd_solver.cpp:105] Iteration 18684, lr = 0.005
I0406 16:36:51.937899 23057 solver.cpp:218] Iteration 18696 (2.31293 iter/s, 5.18823s/12 iters), loss = 0.0363292
I0406 16:36:51.938020 23057 solver.cpp:237]     Train net output #0: loss = 0.0363289 (* 1 = 0.0363289 loss)
I0406 16:36:51.938028 23057 sgd_solver.cpp:105] Iteration 18696, lr = 0.005
I0406 16:36:57.293865 23057 solver.cpp:218] Iteration 18708 (2.24057 iter/s, 5.35578s/12 iters), loss = 0.184998
I0406 16:36:57.293920 23057 solver.cpp:237]     Train net output #0: loss = 0.184997 (* 1 = 0.184997 loss)
I0406 16:36:57.293928 23057 sgd_solver.cpp:105] Iteration 18708, lr = 0.005
I0406 16:36:59.112192 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:37:02.402077 23057 solver.cpp:218] Iteration 18720 (2.34921 iter/s, 5.10809s/12 iters), loss = 0.076055
I0406 16:37:02.402122 23057 solver.cpp:237]     Train net output #0: loss = 0.0760547 (* 1 = 0.0760547 loss)
I0406 16:37:02.402128 23057 sgd_solver.cpp:105] Iteration 18720, lr = 0.005
I0406 16:37:02.750113 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:37:07.788336 23057 solver.cpp:218] Iteration 18732 (2.22793 iter/s, 5.38616s/12 iters), loss = 0.0297836
I0406 16:37:07.788375 23057 solver.cpp:237]     Train net output #0: loss = 0.0297834 (* 1 = 0.0297834 loss)
I0406 16:37:07.788381 23057 sgd_solver.cpp:105] Iteration 18732, lr = 0.005
I0406 16:37:13.196498 23057 solver.cpp:218] Iteration 18744 (2.21891 iter/s, 5.40806s/12 iters), loss = 0.130945
I0406 16:37:13.196532 23057 solver.cpp:237]     Train net output #0: loss = 0.130944 (* 1 = 0.130944 loss)
I0406 16:37:13.196538 23057 sgd_solver.cpp:105] Iteration 18744, lr = 0.005
I0406 16:37:18.378299 23057 solver.cpp:218] Iteration 18756 (2.31584 iter/s, 5.1817s/12 iters), loss = 0.0770053
I0406 16:37:18.378351 23057 solver.cpp:237]     Train net output #0: loss = 0.0770051 (* 1 = 0.0770051 loss)
I0406 16:37:18.378358 23057 sgd_solver.cpp:105] Iteration 18756, lr = 0.005
I0406 16:37:23.193750 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18768.caffemodel
I0406 16:37:26.211958 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18768.solverstate
I0406 16:37:28.508352 23057 solver.cpp:330] Iteration 18768, Testing net (#0)
I0406 16:37:28.508371 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:37:30.137197 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:37:32.829255 23057 solver.cpp:397]     Test net output #0: accuracy = 0.434436
I0406 16:37:32.829286 23057 solver.cpp:397]     Test net output #1: loss = 3.57123 (* 1 = 3.57123 loss)
I0406 16:37:32.969125 23057 solver.cpp:218] Iteration 18768 (0.822445 iter/s, 14.5906s/12 iters), loss = 0.0772606
I0406 16:37:32.969178 23057 solver.cpp:237]     Train net output #0: loss = 0.0772604 (* 1 = 0.0772604 loss)
I0406 16:37:32.969184 23057 sgd_solver.cpp:105] Iteration 18768, lr = 0.005
I0406 16:37:37.325297 23057 solver.cpp:218] Iteration 18780 (2.75478 iter/s, 4.35607s/12 iters), loss = 0.190318
I0406 16:37:37.325343 23057 solver.cpp:237]     Train net output #0: loss = 0.190318 (* 1 = 0.190318 loss)
I0406 16:37:37.325348 23057 sgd_solver.cpp:105] Iteration 18780, lr = 0.005
I0406 16:37:42.346848 23057 solver.cpp:218] Iteration 18792 (2.38975 iter/s, 5.02144s/12 iters), loss = 0.0349569
I0406 16:37:42.346913 23057 solver.cpp:237]     Train net output #0: loss = 0.0349566 (* 1 = 0.0349566 loss)
I0406 16:37:42.346923 23057 sgd_solver.cpp:105] Iteration 18792, lr = 0.005
I0406 16:37:47.576033 23057 solver.cpp:218] Iteration 18804 (2.29487 iter/s, 5.22906s/12 iters), loss = 0.0593194
I0406 16:37:47.576077 23057 solver.cpp:237]     Train net output #0: loss = 0.0593192 (* 1 = 0.0593192 loss)
I0406 16:37:47.576083 23057 sgd_solver.cpp:105] Iteration 18804, lr = 0.005
I0406 16:37:51.890782 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:37:52.762481 23057 solver.cpp:218] Iteration 18816 (2.31377 iter/s, 5.18634s/12 iters), loss = 0.240495
I0406 16:37:52.762532 23057 solver.cpp:237]     Train net output #0: loss = 0.240495 (* 1 = 0.240495 loss)
I0406 16:37:52.762540 23057 sgd_solver.cpp:105] Iteration 18816, lr = 0.005
I0406 16:37:58.297554 23057 solver.cpp:218] Iteration 18828 (2.16804 iter/s, 5.53497s/12 iters), loss = 0.101695
I0406 16:37:58.297672 23057 solver.cpp:237]     Train net output #0: loss = 0.101695 (* 1 = 0.101695 loss)
I0406 16:37:58.297678 23057 sgd_solver.cpp:105] Iteration 18828, lr = 0.005
I0406 16:38:03.682054 23057 solver.cpp:218] Iteration 18840 (2.22869 iter/s, 5.38432s/12 iters), loss = 0.0875477
I0406 16:38:03.682096 23057 solver.cpp:237]     Train net output #0: loss = 0.0875475 (* 1 = 0.0875475 loss)
I0406 16:38:03.682102 23057 sgd_solver.cpp:105] Iteration 18840, lr = 0.005
I0406 16:38:08.926720 23057 solver.cpp:218] Iteration 18852 (2.28808 iter/s, 5.24456s/12 iters), loss = 0.13832
I0406 16:38:08.926761 23057 solver.cpp:237]     Train net output #0: loss = 0.138319 (* 1 = 0.138319 loss)
I0406 16:38:08.926767 23057 sgd_solver.cpp:105] Iteration 18852, lr = 0.005
I0406 16:38:14.138079 23057 solver.cpp:218] Iteration 18864 (2.30271 iter/s, 5.21126s/12 iters), loss = 0.124996
I0406 16:38:14.138118 23057 solver.cpp:237]     Train net output #0: loss = 0.124996 (* 1 = 0.124996 loss)
I0406 16:38:14.138123 23057 sgd_solver.cpp:105] Iteration 18864, lr = 0.005
I0406 16:38:16.333122 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18870.caffemodel
I0406 16:38:19.348470 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18870.solverstate
I0406 16:38:21.655294 23057 solver.cpp:330] Iteration 18870, Testing net (#0)
I0406 16:38:21.655315 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:38:23.234644 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:38:25.957916 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422181
I0406 16:38:25.957954 23057 solver.cpp:397]     Test net output #1: loss = 3.52944 (* 1 = 3.52944 loss)
I0406 16:38:27.680548 23057 solver.cpp:218] Iteration 18876 (0.886112 iter/s, 13.5423s/12 iters), loss = 0.174151
I0406 16:38:27.680588 23057 solver.cpp:237]     Train net output #0: loss = 0.174151 (* 1 = 0.174151 loss)
I0406 16:38:27.680593 23057 sgd_solver.cpp:105] Iteration 18876, lr = 0.005
I0406 16:38:32.921916 23057 solver.cpp:218] Iteration 18888 (2.28952 iter/s, 5.24127s/12 iters), loss = 0.0936526
I0406 16:38:32.922024 23057 solver.cpp:237]     Train net output #0: loss = 0.0936524 (* 1 = 0.0936524 loss)
I0406 16:38:32.922030 23057 sgd_solver.cpp:105] Iteration 18888, lr = 0.005
I0406 16:38:38.062577 23057 solver.cpp:218] Iteration 18900 (2.33441 iter/s, 5.14049s/12 iters), loss = 0.0271683
I0406 16:38:38.062626 23057 solver.cpp:237]     Train net output #0: loss = 0.0271681 (* 1 = 0.0271681 loss)
I0406 16:38:38.062633 23057 sgd_solver.cpp:105] Iteration 18900, lr = 0.005
I0406 16:38:43.469460 23057 solver.cpp:218] Iteration 18912 (2.21944 iter/s, 5.40677s/12 iters), loss = 0.212306
I0406 16:38:43.469503 23057 solver.cpp:237]     Train net output #0: loss = 0.212305 (* 1 = 0.212305 loss)
I0406 16:38:43.469509 23057 sgd_solver.cpp:105] Iteration 18912, lr = 0.005
I0406 16:38:44.828622 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:38:48.625953 23057 solver.cpp:218] Iteration 18924 (2.32721 iter/s, 5.15639s/12 iters), loss = 0.0868788
I0406 16:38:48.626000 23057 solver.cpp:237]     Train net output #0: loss = 0.0868786 (* 1 = 0.0868786 loss)
I0406 16:38:48.626006 23057 sgd_solver.cpp:105] Iteration 18924, lr = 0.005
I0406 16:38:53.720890 23057 solver.cpp:218] Iteration 18936 (2.35533 iter/s, 5.09482s/12 iters), loss = 0.0834649
I0406 16:38:53.720940 23057 solver.cpp:237]     Train net output #0: loss = 0.0834646 (* 1 = 0.0834646 loss)
I0406 16:38:53.720948 23057 sgd_solver.cpp:105] Iteration 18936, lr = 0.005
I0406 16:38:58.937270 23057 solver.cpp:218] Iteration 18948 (2.30049 iter/s, 5.21627s/12 iters), loss = 0.0484787
I0406 16:38:58.937312 23057 solver.cpp:237]     Train net output #0: loss = 0.0484785 (* 1 = 0.0484785 loss)
I0406 16:38:58.937317 23057 sgd_solver.cpp:105] Iteration 18948, lr = 0.005
I0406 16:39:04.073796 23057 solver.cpp:218] Iteration 18960 (2.33626 iter/s, 5.13642s/12 iters), loss = 0.110584
I0406 16:39:04.073916 23057 solver.cpp:237]     Train net output #0: loss = 0.110583 (* 1 = 0.110583 loss)
I0406 16:39:04.073923 23057 sgd_solver.cpp:105] Iteration 18960, lr = 0.005
I0406 16:39:08.772393 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18972.caffemodel
I0406 16:39:11.897312 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18972.solverstate
I0406 16:39:14.209504 23057 solver.cpp:330] Iteration 18972, Testing net (#0)
I0406 16:39:14.209529 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:39:15.836977 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:39:18.666999 23057 solver.cpp:397]     Test net output #0: accuracy = 0.426471
I0406 16:39:18.667034 23057 solver.cpp:397]     Test net output #1: loss = 3.42538 (* 1 = 3.42538 loss)
I0406 16:39:18.807399 23057 solver.cpp:218] Iteration 18972 (0.814479 iter/s, 14.7333s/12 iters), loss = 0.0282482
I0406 16:39:18.807444 23057 solver.cpp:237]     Train net output #0: loss = 0.028248 (* 1 = 0.028248 loss)
I0406 16:39:18.807451 23057 sgd_solver.cpp:105] Iteration 18972, lr = 0.005
I0406 16:39:23.108603 23057 solver.cpp:218] Iteration 18984 (2.78998 iter/s, 4.30111s/12 iters), loss = 0.111066
I0406 16:39:23.108644 23057 solver.cpp:237]     Train net output #0: loss = 0.111066 (* 1 = 0.111066 loss)
I0406 16:39:23.108649 23057 sgd_solver.cpp:105] Iteration 18984, lr = 0.005
I0406 16:39:28.312213 23057 solver.cpp:218] Iteration 18996 (2.30613 iter/s, 5.20351s/12 iters), loss = 0.20915
I0406 16:39:28.312248 23057 solver.cpp:237]     Train net output #0: loss = 0.20915 (* 1 = 0.20915 loss)
I0406 16:39:28.312254 23057 sgd_solver.cpp:105] Iteration 18996, lr = 0.005
I0406 16:39:33.741361 23057 solver.cpp:218] Iteration 19008 (2.21033 iter/s, 5.42904s/12 iters), loss = 0.07947
I0406 16:39:33.741420 23057 solver.cpp:237]     Train net output #0: loss = 0.0794697 (* 1 = 0.0794697 loss)
I0406 16:39:33.741430 23057 sgd_solver.cpp:105] Iteration 19008, lr = 0.005
I0406 16:39:37.447059 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:39:39.024912 23057 solver.cpp:218] Iteration 19020 (2.27125 iter/s, 5.28344s/12 iters), loss = 0.119948
I0406 16:39:39.024956 23057 solver.cpp:237]     Train net output #0: loss = 0.119947 (* 1 = 0.119947 loss)
I0406 16:39:39.024966 23057 sgd_solver.cpp:105] Iteration 19020, lr = 0.005
I0406 16:39:44.292239 23057 solver.cpp:218] Iteration 19032 (2.27824 iter/s, 5.26722s/12 iters), loss = 0.14122
I0406 16:39:44.292296 23057 solver.cpp:237]     Train net output #0: loss = 0.14122 (* 1 = 0.14122 loss)
I0406 16:39:44.292305 23057 sgd_solver.cpp:105] Iteration 19032, lr = 0.005
I0406 16:39:49.618125 23057 solver.cpp:218] Iteration 19044 (2.2532 iter/s, 5.32577s/12 iters), loss = 0.0489887
I0406 16:39:49.618171 23057 solver.cpp:237]     Train net output #0: loss = 0.0489884 (* 1 = 0.0489884 loss)
I0406 16:39:49.618178 23057 sgd_solver.cpp:105] Iteration 19044, lr = 0.005
I0406 16:39:54.989567 23057 solver.cpp:218] Iteration 19056 (2.23408 iter/s, 5.37134s/12 iters), loss = 0.101354
I0406 16:39:54.989607 23057 solver.cpp:237]     Train net output #0: loss = 0.101354 (* 1 = 0.101354 loss)
I0406 16:39:54.989614 23057 sgd_solver.cpp:105] Iteration 19056, lr = 0.005
I0406 16:40:00.291055 23057 solver.cpp:218] Iteration 19068 (2.26356 iter/s, 5.30139s/12 iters), loss = 0.0839927
I0406 16:40:00.291095 23057 solver.cpp:237]     Train net output #0: loss = 0.0839924 (* 1 = 0.0839924 loss)
I0406 16:40:00.291101 23057 sgd_solver.cpp:105] Iteration 19068, lr = 0.005
I0406 16:40:02.480437 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19074.caffemodel
I0406 16:40:05.507680 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19074.solverstate
I0406 16:40:07.820665 23057 solver.cpp:330] Iteration 19074, Testing net (#0)
I0406 16:40:07.820757 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:40:09.307910 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:40:12.166038 23057 solver.cpp:397]     Test net output #0: accuracy = 0.4375
I0406 16:40:12.166065 23057 solver.cpp:397]     Test net output #1: loss = 3.52481 (* 1 = 3.52481 loss)
I0406 16:40:13.956856 23057 solver.cpp:218] Iteration 19080 (0.878115 iter/s, 13.6656s/12 iters), loss = 0.0930064
I0406 16:40:13.956904 23057 solver.cpp:237]     Train net output #0: loss = 0.0930061 (* 1 = 0.0930061 loss)
I0406 16:40:13.956910 23057 sgd_solver.cpp:105] Iteration 19080, lr = 0.005
I0406 16:40:19.044219 23057 solver.cpp:218] Iteration 19092 (2.35884 iter/s, 5.08725s/12 iters), loss = 0.128225
I0406 16:40:19.044268 23057 solver.cpp:237]     Train net output #0: loss = 0.128225 (* 1 = 0.128225 loss)
I0406 16:40:19.044276 23057 sgd_solver.cpp:105] Iteration 19092, lr = 0.005
I0406 16:40:24.373924 23057 solver.cpp:218] Iteration 19104 (2.25158 iter/s, 5.3296s/12 iters), loss = 0.0451934
I0406 16:40:24.373983 23057 solver.cpp:237]     Train net output #0: loss = 0.0451931 (* 1 = 0.0451931 loss)
I0406 16:40:24.373993 23057 sgd_solver.cpp:105] Iteration 19104, lr = 0.005
I0406 16:40:29.730973 23057 solver.cpp:218] Iteration 19116 (2.24009 iter/s, 5.35693s/12 iters), loss = 0.105756
I0406 16:40:29.731022 23057 solver.cpp:237]     Train net output #0: loss = 0.105755 (* 1 = 0.105755 loss)
I0406 16:40:29.731029 23057 sgd_solver.cpp:105] Iteration 19116, lr = 0.005
I0406 16:40:30.361626 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:40:35.043030 23057 solver.cpp:218] Iteration 19128 (2.25906 iter/s, 5.31195s/12 iters), loss = 0.0968752
I0406 16:40:35.043071 23057 solver.cpp:237]     Train net output #0: loss = 0.0968749 (* 1 = 0.0968749 loss)
I0406 16:40:35.043077 23057 sgd_solver.cpp:105] Iteration 19128, lr = 0.005
I0406 16:40:40.220504 23057 solver.cpp:218] Iteration 19140 (2.31778 iter/s, 5.17737s/12 iters), loss = 0.0897673
I0406 16:40:40.220609 23057 solver.cpp:237]     Train net output #0: loss = 0.0897671 (* 1 = 0.0897671 loss)
I0406 16:40:40.220618 23057 sgd_solver.cpp:105] Iteration 19140, lr = 0.005
I0406 16:40:45.191046 23057 solver.cpp:218] Iteration 19152 (2.4143 iter/s, 4.97038s/12 iters), loss = 0.017118
I0406 16:40:45.191093 23057 solver.cpp:237]     Train net output #0: loss = 0.0171177 (* 1 = 0.0171177 loss)
I0406 16:40:45.191099 23057 sgd_solver.cpp:105] Iteration 19152, lr = 0.005
I0406 16:40:50.637491 23057 solver.cpp:218] Iteration 19164 (2.20332 iter/s, 5.44633s/12 iters), loss = 0.130403
I0406 16:40:50.637547 23057 solver.cpp:237]     Train net output #0: loss = 0.130403 (* 1 = 0.130403 loss)
I0406 16:40:50.637555 23057 sgd_solver.cpp:105] Iteration 19164, lr = 0.005
I0406 16:40:55.389470 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19176.caffemodel
I0406 16:40:58.415308 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19176.solverstate
I0406 16:41:01.509318 23057 solver.cpp:330] Iteration 19176, Testing net (#0)
I0406 16:41:01.509338 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:41:03.062729 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:41:05.919380 23057 solver.cpp:397]     Test net output #0: accuracy = 0.428309
I0406 16:41:05.919418 23057 solver.cpp:397]     Test net output #1: loss = 3.54087 (* 1 = 3.54087 loss)
I0406 16:41:06.060767 23057 solver.cpp:218] Iteration 19176 (0.778055 iter/s, 15.4231s/12 iters), loss = 0.143655
I0406 16:41:06.060822 23057 solver.cpp:237]     Train net output #0: loss = 0.143655 (* 1 = 0.143655 loss)
I0406 16:41:06.060829 23057 sgd_solver.cpp:105] Iteration 19176, lr = 0.005
I0406 16:41:10.274029 23057 solver.cpp:218] Iteration 19188 (2.84822 iter/s, 4.21315s/12 iters), loss = 0.155249
I0406 16:41:10.274189 23057 solver.cpp:237]     Train net output #0: loss = 0.155249 (* 1 = 0.155249 loss)
I0406 16:41:10.274199 23057 sgd_solver.cpp:105] Iteration 19188, lr = 0.005
I0406 16:41:15.541380 23057 solver.cpp:218] Iteration 19200 (2.27828 iter/s, 5.26713s/12 iters), loss = 0.0210529
I0406 16:41:15.541429 23057 solver.cpp:237]     Train net output #0: loss = 0.0210526 (* 1 = 0.0210526 loss)
I0406 16:41:15.541437 23057 sgd_solver.cpp:105] Iteration 19200, lr = 0.005
I0406 16:41:20.849967 23057 solver.cpp:218] Iteration 19212 (2.26054 iter/s, 5.30848s/12 iters), loss = 0.11492
I0406 16:41:20.850013 23057 solver.cpp:237]     Train net output #0: loss = 0.11492 (* 1 = 0.11492 loss)
I0406 16:41:20.850019 23057 sgd_solver.cpp:105] Iteration 19212, lr = 0.005
I0406 16:41:23.755434 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:41:26.234047 23057 solver.cpp:218] Iteration 19224 (2.22884 iter/s, 5.38397s/12 iters), loss = 0.127533
I0406 16:41:26.234102 23057 solver.cpp:237]     Train net output #0: loss = 0.127533 (* 1 = 0.127533 loss)
I0406 16:41:26.234110 23057 sgd_solver.cpp:105] Iteration 19224, lr = 0.005
I0406 16:41:31.479889 23057 solver.cpp:218] Iteration 19236 (2.28758 iter/s, 5.24573s/12 iters), loss = 0.183566
I0406 16:41:31.479944 23057 solver.cpp:237]     Train net output #0: loss = 0.183566 (* 1 = 0.183566 loss)
I0406 16:41:31.479954 23057 sgd_solver.cpp:105] Iteration 19236, lr = 0.005
I0406 16:41:36.610572 23057 solver.cpp:218] Iteration 19248 (2.33892 iter/s, 5.13057s/12 iters), loss = 0.0435107
I0406 16:41:36.610627 23057 solver.cpp:237]     Train net output #0: loss = 0.0435105 (* 1 = 0.0435105 loss)
I0406 16:41:36.610637 23057 sgd_solver.cpp:105] Iteration 19248, lr = 0.005
I0406 16:41:41.930866 23057 solver.cpp:218] Iteration 19260 (2.25556 iter/s, 5.32018s/12 iters), loss = 0.0988189
I0406 16:41:41.930963 23057 solver.cpp:237]     Train net output #0: loss = 0.0988187 (* 1 = 0.0988187 loss)
I0406 16:41:41.930971 23057 sgd_solver.cpp:105] Iteration 19260, lr = 0.005
I0406 16:41:47.202639 23057 solver.cpp:218] Iteration 19272 (2.27634 iter/s, 5.27162s/12 iters), loss = 0.0801694
I0406 16:41:47.202682 23057 solver.cpp:237]     Train net output #0: loss = 0.0801692 (* 1 = 0.0801692 loss)
I0406 16:41:47.202689 23057 sgd_solver.cpp:105] Iteration 19272, lr = 0.005
I0406 16:41:49.329797 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19278.caffemodel
I0406 16:41:52.348750 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19278.solverstate
I0406 16:41:54.639688 23057 solver.cpp:330] Iteration 19278, Testing net (#0)
I0406 16:41:54.639706 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:41:56.277814 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:41:59.204278 23057 solver.cpp:397]     Test net output #0: accuracy = 0.42402
I0406 16:41:59.204331 23057 solver.cpp:397]     Test net output #1: loss = 3.6599 (* 1 = 3.6599 loss)
I0406 16:42:01.226200 23057 solver.cpp:218] Iteration 19284 (0.855713 iter/s, 14.0234s/12 iters), loss = 0.0606623
I0406 16:42:01.226241 23057 solver.cpp:237]     Train net output #0: loss = 0.060662 (* 1 = 0.060662 loss)
I0406 16:42:01.226248 23057 sgd_solver.cpp:105] Iteration 19284, lr = 0.005
I0406 16:42:06.660050 23057 solver.cpp:218] Iteration 19296 (2.20842 iter/s, 5.43374s/12 iters), loss = 0.039193
I0406 16:42:06.660111 23057 solver.cpp:237]     Train net output #0: loss = 0.0391927 (* 1 = 0.0391927 loss)
I0406 16:42:06.660120 23057 sgd_solver.cpp:105] Iteration 19296, lr = 0.005
I0406 16:42:11.688304 23057 solver.cpp:218] Iteration 19308 (2.38657 iter/s, 5.02813s/12 iters), loss = 0.0172993
I0406 16:42:11.688364 23057 solver.cpp:237]     Train net output #0: loss = 0.017299 (* 1 = 0.017299 loss)
I0406 16:42:11.688374 23057 sgd_solver.cpp:105] Iteration 19308, lr = 0.005
I0406 16:42:16.725843 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:42:16.918365 23057 solver.cpp:218] Iteration 19320 (2.29448 iter/s, 5.22994s/12 iters), loss = 0.0242131
I0406 16:42:16.918409 23057 solver.cpp:237]     Train net output #0: loss = 0.0242128 (* 1 = 0.0242128 loss)
I0406 16:42:16.918416 23057 sgd_solver.cpp:105] Iteration 19320, lr = 0.005
I0406 16:42:22.289656 23057 solver.cpp:218] Iteration 19332 (2.23415 iter/s, 5.37118s/12 iters), loss = 0.0580721
I0406 16:42:22.289716 23057 solver.cpp:237]     Train net output #0: loss = 0.0580718 (* 1 = 0.0580718 loss)
I0406 16:42:22.289726 23057 sgd_solver.cpp:105] Iteration 19332, lr = 0.005
I0406 16:42:27.596160 23057 solver.cpp:218] Iteration 19344 (2.26143 iter/s, 5.30639s/12 iters), loss = 0.0654636
I0406 16:42:27.596200 23057 solver.cpp:237]     Train net output #0: loss = 0.0654633 (* 1 = 0.0654633 loss)
I0406 16:42:27.596206 23057 sgd_solver.cpp:105] Iteration 19344, lr = 0.005
I0406 16:42:32.763526 23057 solver.cpp:218] Iteration 19356 (2.32231 iter/s, 5.16727s/12 iters), loss = 0.179256
I0406 16:42:32.763573 23057 solver.cpp:237]     Train net output #0: loss = 0.179256 (* 1 = 0.179256 loss)
I0406 16:42:32.763581 23057 sgd_solver.cpp:105] Iteration 19356, lr = 0.005
I0406 16:42:37.963449 23057 solver.cpp:218] Iteration 19368 (2.30778 iter/s, 5.19981s/12 iters), loss = 0.0830354
I0406 16:42:37.963505 23057 solver.cpp:237]     Train net output #0: loss = 0.0830351 (* 1 = 0.0830351 loss)
I0406 16:42:37.963513 23057 sgd_solver.cpp:105] Iteration 19368, lr = 0.005
I0406 16:42:42.730501 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19380.caffemodel
I0406 16:42:45.763958 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19380.solverstate
I0406 16:42:48.068850 23057 solver.cpp:330] Iteration 19380, Testing net (#0)
I0406 16:42:48.068924 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:42:49.610054 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:42:52.545477 23057 solver.cpp:397]     Test net output #0: accuracy = 0.438113
I0406 16:42:52.545503 23057 solver.cpp:397]     Test net output #1: loss = 3.40422 (* 1 = 3.40422 loss)
I0406 16:42:52.680351 23057 solver.cpp:218] Iteration 19380 (0.8154 iter/s, 14.7167s/12 iters), loss = 0.0839178
I0406 16:42:52.680397 23057 solver.cpp:237]     Train net output #0: loss = 0.0839175 (* 1 = 0.0839175 loss)
I0406 16:42:52.680403 23057 sgd_solver.cpp:105] Iteration 19380, lr = 0.005
I0406 16:42:57.023978 23057 solver.cpp:218] Iteration 19392 (2.76273 iter/s, 4.34353s/12 iters), loss = 0.167172
I0406 16:42:57.024024 23057 solver.cpp:237]     Train net output #0: loss = 0.167171 (* 1 = 0.167171 loss)
I0406 16:42:57.024031 23057 sgd_solver.cpp:105] Iteration 19392, lr = 0.005
I0406 16:43:02.178822 23057 solver.cpp:218] Iteration 19404 (2.32796 iter/s, 5.15473s/12 iters), loss = 0.0408678
I0406 16:43:02.178882 23057 solver.cpp:237]     Train net output #0: loss = 0.0408676 (* 1 = 0.0408676 loss)
I0406 16:43:02.178891 23057 sgd_solver.cpp:105] Iteration 19404, lr = 0.005
I0406 16:43:02.993892 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:43:07.477743 23057 solver.cpp:218] Iteration 19416 (2.26466 iter/s, 5.2988s/12 iters), loss = 0.0419753
I0406 16:43:07.477803 23057 solver.cpp:237]     Train net output #0: loss = 0.0419751 (* 1 = 0.0419751 loss)
I0406 16:43:07.477811 23057 sgd_solver.cpp:105] Iteration 19416, lr = 0.005
I0406 16:43:09.406926 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:43:12.634655 23057 solver.cpp:218] Iteration 19428 (2.32702 iter/s, 5.1568s/12 iters), loss = 0.1223
I0406 16:43:12.634696 23057 solver.cpp:237]     Train net output #0: loss = 0.1223 (* 1 = 0.1223 loss)
I0406 16:43:12.634702 23057 sgd_solver.cpp:105] Iteration 19428, lr = 0.005
I0406 16:43:17.657464 23057 solver.cpp:218] Iteration 19440 (2.38915 iter/s, 5.02271s/12 iters), loss = 0.114776
I0406 16:43:17.657500 23057 solver.cpp:237]     Train net output #0: loss = 0.114775 (* 1 = 0.114775 loss)
I0406 16:43:17.657505 23057 sgd_solver.cpp:105] Iteration 19440, lr = 0.005
I0406 16:43:22.721009 23057 solver.cpp:218] Iteration 19452 (2.36992 iter/s, 5.06345s/12 iters), loss = 0.059475
I0406 16:43:22.721138 23057 solver.cpp:237]     Train net output #0: loss = 0.0594747 (* 1 = 0.0594747 loss)
I0406 16:43:22.721144 23057 sgd_solver.cpp:105] Iteration 19452, lr = 0.005
I0406 16:43:27.902148 23057 solver.cpp:218] Iteration 19464 (2.31618 iter/s, 5.18095s/12 iters), loss = 0.0121548
I0406 16:43:27.902204 23057 solver.cpp:237]     Train net output #0: loss = 0.0121546 (* 1 = 0.0121546 loss)
I0406 16:43:27.902212 23057 sgd_solver.cpp:105] Iteration 19464, lr = 0.005
I0406 16:43:33.286618 23057 solver.cpp:218] Iteration 19476 (2.22868 iter/s, 5.38436s/12 iters), loss = 0.11507
I0406 16:43:33.286664 23057 solver.cpp:237]     Train net output #0: loss = 0.115069 (* 1 = 0.115069 loss)
I0406 16:43:33.286669 23057 sgd_solver.cpp:105] Iteration 19476, lr = 0.005
I0406 16:43:35.488803 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19482.caffemodel
I0406 16:43:39.415571 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19482.solverstate
I0406 16:43:41.762040 23057 solver.cpp:330] Iteration 19482, Testing net (#0)
I0406 16:43:41.762063 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:43:43.159116 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:43:46.241055 23057 solver.cpp:397]     Test net output #0: accuracy = 0.438113
I0406 16:43:46.241082 23057 solver.cpp:397]     Test net output #1: loss = 3.42979 (* 1 = 3.42979 loss)
I0406 16:43:48.204314 23057 solver.cpp:218] Iteration 19488 (0.804424 iter/s, 14.9175s/12 iters), loss = 0.0775421
I0406 16:43:48.204355 23057 solver.cpp:237]     Train net output #0: loss = 0.0775418 (* 1 = 0.0775418 loss)
I0406 16:43:48.204360 23057 sgd_solver.cpp:105] Iteration 19488, lr = 0.005
I0406 16:43:53.536566 23057 solver.cpp:218] Iteration 19500 (2.2505 iter/s, 5.33215s/12 iters), loss = 0.0329188
I0406 16:43:53.536659 23057 solver.cpp:237]     Train net output #0: loss = 0.0329186 (* 1 = 0.0329186 loss)
I0406 16:43:53.536666 23057 sgd_solver.cpp:105] Iteration 19500, lr = 0.005
I0406 16:43:58.848080 23057 solver.cpp:218] Iteration 19512 (2.25931 iter/s, 5.31136s/12 iters), loss = 0.0853889
I0406 16:43:58.848119 23057 solver.cpp:237]     Train net output #0: loss = 0.0853887 (* 1 = 0.0853887 loss)
I0406 16:43:58.848126 23057 sgd_solver.cpp:105] Iteration 19512, lr = 0.005
I0406 16:44:03.273725 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:44:04.122474 23057 solver.cpp:218] Iteration 19524 (2.27519 iter/s, 5.2743s/12 iters), loss = 0.0401894
I0406 16:44:04.122517 23057 solver.cpp:237]     Train net output #0: loss = 0.0401891 (* 1 = 0.0401891 loss)
I0406 16:44:04.122524 23057 sgd_solver.cpp:105] Iteration 19524, lr = 0.005
I0406 16:44:09.347277 23057 solver.cpp:218] Iteration 19536 (2.29678 iter/s, 5.2247s/12 iters), loss = 0.100722
I0406 16:44:09.347317 23057 solver.cpp:237]     Train net output #0: loss = 0.100721 (* 1 = 0.100721 loss)
I0406 16:44:09.347323 23057 sgd_solver.cpp:105] Iteration 19536, lr = 0.005
I0406 16:44:14.459322 23057 solver.cpp:218] Iteration 19548 (2.34744 iter/s, 5.11194s/12 iters), loss = 0.0154613
I0406 16:44:14.459369 23057 solver.cpp:237]     Train net output #0: loss = 0.015461 (* 1 = 0.015461 loss)
I0406 16:44:14.459376 23057 sgd_solver.cpp:105] Iteration 19548, lr = 0.005
I0406 16:44:19.652446 23057 solver.cpp:218] Iteration 19560 (2.3108 iter/s, 5.19302s/12 iters), loss = 0.0776083
I0406 16:44:19.652506 23057 solver.cpp:237]     Train net output #0: loss = 0.0776081 (* 1 = 0.0776081 loss)
I0406 16:44:19.652516 23057 sgd_solver.cpp:105] Iteration 19560, lr = 0.005
I0406 16:44:24.944599 23057 solver.cpp:218] Iteration 19572 (2.26756 iter/s, 5.29204s/12 iters), loss = 0.118836
I0406 16:44:24.944778 23057 solver.cpp:237]     Train net output #0: loss = 0.118836 (* 1 = 0.118836 loss)
I0406 16:44:24.944788 23057 sgd_solver.cpp:105] Iteration 19572, lr = 0.005
I0406 16:44:29.554646 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19584.caffemodel
I0406 16:44:33.172060 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19584.solverstate
I0406 16:44:35.492451 23057 solver.cpp:330] Iteration 19584, Testing net (#0)
I0406 16:44:35.492475 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:44:36.809428 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:44:39.828280 23057 solver.cpp:397]     Test net output #0: accuracy = 0.420343
I0406 16:44:39.828305 23057 solver.cpp:397]     Test net output #1: loss = 3.61059 (* 1 = 3.61059 loss)
I0406 16:44:39.968775 23057 solver.cpp:218] Iteration 19584 (0.798729 iter/s, 15.0239s/12 iters), loss = 0.032039
I0406 16:44:39.970338 23057 solver.cpp:237]     Train net output #0: loss = 0.0320388 (* 1 = 0.0320388 loss)
I0406 16:44:39.970346 23057 sgd_solver.cpp:105] Iteration 19584, lr = 0.005
I0406 16:44:44.170665 23057 solver.cpp:218] Iteration 19596 (2.85695 iter/s, 4.20028s/12 iters), loss = 0.150259
I0406 16:44:44.170709 23057 solver.cpp:237]     Train net output #0: loss = 0.150258 (* 1 = 0.150258 loss)
I0406 16:44:44.170715 23057 sgd_solver.cpp:105] Iteration 19596, lr = 0.005
I0406 16:44:49.503209 23057 solver.cpp:218] Iteration 19608 (2.25038 iter/s, 5.33244s/12 iters), loss = 0.0887486
I0406 16:44:49.503249 23057 solver.cpp:237]     Train net output #0: loss = 0.0887483 (* 1 = 0.0887483 loss)
I0406 16:44:49.503255 23057 sgd_solver.cpp:105] Iteration 19608, lr = 0.005
I0406 16:44:54.778687 23057 solver.cpp:218] Iteration 19620 (2.27472 iter/s, 5.27537s/12 iters), loss = 0.0963691
I0406 16:44:54.778750 23057 solver.cpp:237]     Train net output #0: loss = 0.0963688 (* 1 = 0.0963688 loss)
I0406 16:44:54.778759 23057 sgd_solver.cpp:105] Iteration 19620, lr = 0.005
I0406 16:44:56.252578 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:45:00.269979 23057 solver.cpp:218] Iteration 19632 (2.18533 iter/s, 5.49117s/12 iters), loss = 0.0318926
I0406 16:45:00.270020 23057 solver.cpp:237]     Train net output #0: loss = 0.0318923 (* 1 = 0.0318923 loss)
I0406 16:45:00.270025 23057 sgd_solver.cpp:105] Iteration 19632, lr = 0.005
I0406 16:45:05.605768 23057 solver.cpp:218] Iteration 19644 (2.24901 iter/s, 5.33569s/12 iters), loss = 0.0983648
I0406 16:45:05.605809 23057 solver.cpp:237]     Train net output #0: loss = 0.0983645 (* 1 = 0.0983645 loss)
I0406 16:45:05.605815 23057 sgd_solver.cpp:105] Iteration 19644, lr = 0.005
I0406 16:45:10.631337 23057 solver.cpp:218] Iteration 19656 (2.38784 iter/s, 5.02547s/12 iters), loss = 0.0376923
I0406 16:45:10.631381 23057 solver.cpp:237]     Train net output #0: loss = 0.037692 (* 1 = 0.037692 loss)
I0406 16:45:10.631388 23057 sgd_solver.cpp:105] Iteration 19656, lr = 0.005
I0406 16:45:15.755746 23057 solver.cpp:218] Iteration 19668 (2.34178 iter/s, 5.12431s/12 iters), loss = 0.0817675
I0406 16:45:15.755787 23057 solver.cpp:237]     Train net output #0: loss = 0.0817672 (* 1 = 0.0817672 loss)
I0406 16:45:15.755793 23057 sgd_solver.cpp:105] Iteration 19668, lr = 0.005
I0406 16:45:20.964951 23057 solver.cpp:218] Iteration 19680 (2.30366 iter/s, 5.2091s/12 iters), loss = 0.127368
I0406 16:45:20.964995 23057 solver.cpp:237]     Train net output #0: loss = 0.127368 (* 1 = 0.127368 loss)
I0406 16:45:20.965000 23057 sgd_solver.cpp:105] Iteration 19680, lr = 0.005
I0406 16:45:23.140399 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19686.caffemodel
I0406 16:45:28.126368 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19686.solverstate
I0406 16:45:30.442270 23057 solver.cpp:330] Iteration 19686, Testing net (#0)
I0406 16:45:30.442289 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:45:31.735759 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:45:34.872822 23057 solver.cpp:397]     Test net output #0: accuracy = 0.439951
I0406 16:45:34.872853 23057 solver.cpp:397]     Test net output #1: loss = 3.43751 (* 1 = 3.43751 loss)
I0406 16:45:36.812783 23057 solver.cpp:218] Iteration 19692 (0.75721 iter/s, 15.8476s/12 iters), loss = 0.0560431
I0406 16:45:36.812822 23057 solver.cpp:237]     Train net output #0: loss = 0.0560428 (* 1 = 0.0560428 loss)
I0406 16:45:36.812827 23057 sgd_solver.cpp:105] Iteration 19692, lr = 0.005
I0406 16:45:42.291272 23057 solver.cpp:218] Iteration 19704 (2.19042 iter/s, 5.47839s/12 iters), loss = 0.0266687
I0406 16:45:42.291318 23057 solver.cpp:237]     Train net output #0: loss = 0.0266684 (* 1 = 0.0266684 loss)
I0406 16:45:42.291323 23057 sgd_solver.cpp:105] Iteration 19704, lr = 0.005
I0406 16:45:47.346786 23057 solver.cpp:218] Iteration 19716 (2.3737 iter/s, 5.05541s/12 iters), loss = 0.0410637
I0406 16:45:47.346833 23057 solver.cpp:237]     Train net output #0: loss = 0.0410634 (* 1 = 0.0410634 loss)
I0406 16:45:47.346839 23057 sgd_solver.cpp:105] Iteration 19716, lr = 0.005
I0406 16:45:51.050498 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:45:52.648576 23057 solver.cpp:218] Iteration 19728 (2.26343 iter/s, 5.30169s/12 iters), loss = 0.0734314
I0406 16:45:52.648612 23057 solver.cpp:237]     Train net output #0: loss = 0.0734311 (* 1 = 0.0734311 loss)
I0406 16:45:52.648617 23057 sgd_solver.cpp:105] Iteration 19728, lr = 0.005
I0406 16:45:57.906634 23057 solver.cpp:218] Iteration 19740 (2.28225 iter/s, 5.25796s/12 iters), loss = 0.175176
I0406 16:45:57.906692 23057 solver.cpp:237]     Train net output #0: loss = 0.175175 (* 1 = 0.175175 loss)
I0406 16:45:57.906700 23057 sgd_solver.cpp:105] Iteration 19740, lr = 0.005
I0406 16:46:03.270705 23057 solver.cpp:218] Iteration 19752 (2.23715 iter/s, 5.36396s/12 iters), loss = 0.0448073
I0406 16:46:03.270823 23057 solver.cpp:237]     Train net output #0: loss = 0.044807 (* 1 = 0.044807 loss)
I0406 16:46:03.270833 23057 sgd_solver.cpp:105] Iteration 19752, lr = 0.005
I0406 16:46:08.543632 23057 solver.cpp:218] Iteration 19764 (2.27585 iter/s, 5.27276s/12 iters), loss = 0.0563659
I0406 16:46:08.543660 23057 solver.cpp:237]     Train net output #0: loss = 0.0563656 (* 1 = 0.0563656 loss)
I0406 16:46:08.543666 23057 sgd_solver.cpp:105] Iteration 19764, lr = 0.005
I0406 16:46:13.924705 23057 solver.cpp:218] Iteration 19776 (2.23008 iter/s, 5.38098s/12 iters), loss = 0.0192349
I0406 16:46:13.924749 23057 solver.cpp:237]     Train net output #0: loss = 0.0192346 (* 1 = 0.0192346 loss)
I0406 16:46:13.924755 23057 sgd_solver.cpp:105] Iteration 19776, lr = 0.005
I0406 16:46:18.646814 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19788.caffemodel
I0406 16:46:22.923568 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19788.solverstate
I0406 16:46:25.243814 23057 solver.cpp:330] Iteration 19788, Testing net (#0)
I0406 16:46:25.243834 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:46:26.501745 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:46:29.620348 23057 solver.cpp:397]     Test net output #0: accuracy = 0.422794
I0406 16:46:29.620378 23057 solver.cpp:397]     Test net output #1: loss = 3.39909 (* 1 = 3.39909 loss)
I0406 16:46:29.757813 23057 solver.cpp:218] Iteration 19788 (0.757914 iter/s, 15.8329s/12 iters), loss = 0.132165
I0406 16:46:29.757850 23057 solver.cpp:237]     Train net output #0: loss = 0.132165 (* 1 = 0.132165 loss)
I0406 16:46:29.757855 23057 sgd_solver.cpp:105] Iteration 19788, lr = 0.005
I0406 16:46:33.904644 23057 solver.cpp:218] Iteration 19800 (2.89384 iter/s, 4.14674s/12 iters), loss = 0.0757547
I0406 16:46:33.904737 23057 solver.cpp:237]     Train net output #0: loss = 0.0757544 (* 1 = 0.0757544 loss)
I0406 16:46:33.904744 23057 sgd_solver.cpp:105] Iteration 19800, lr = 0.005
I0406 16:46:39.120055 23057 solver.cpp:218] Iteration 19812 (2.30094 iter/s, 5.21526s/12 iters), loss = 0.0384839
I0406 16:46:39.120112 23057 solver.cpp:237]     Train net output #0: loss = 0.0384836 (* 1 = 0.0384836 loss)
I0406 16:46:39.120121 23057 sgd_solver.cpp:105] Iteration 19812, lr = 0.005
I0406 16:46:44.452235 23057 solver.cpp:218] Iteration 19824 (2.25054 iter/s, 5.33206s/12 iters), loss = 0.0486056
I0406 16:46:44.452281 23057 solver.cpp:237]     Train net output #0: loss = 0.0486053 (* 1 = 0.0486053 loss)
I0406 16:46:44.452286 23057 sgd_solver.cpp:105] Iteration 19824, lr = 0.005
I0406 16:46:45.024878 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:46:49.522608 23057 solver.cpp:218] Iteration 19836 (2.36674 iter/s, 5.07027s/12 iters), loss = 0.0819985
I0406 16:46:49.522650 23057 solver.cpp:237]     Train net output #0: loss = 0.0819982 (* 1 = 0.0819982 loss)
I0406 16:46:49.522656 23057 sgd_solver.cpp:105] Iteration 19836, lr = 0.005
I0406 16:46:54.740288 23057 solver.cpp:218] Iteration 19848 (2.29992 iter/s, 5.21758s/12 iters), loss = 0.0698892
I0406 16:46:54.740342 23057 solver.cpp:237]     Train net output #0: loss = 0.0698889 (* 1 = 0.0698889 loss)
I0406 16:46:54.740351 23057 sgd_solver.cpp:105] Iteration 19848, lr = 0.005
I0406 16:47:00.106084 23057 solver.cpp:218] Iteration 19860 (2.23644 iter/s, 5.36568s/12 iters), loss = 0.0477214
I0406 16:47:00.106134 23057 solver.cpp:237]     Train net output #0: loss = 0.0477211 (* 1 = 0.0477211 loss)
I0406 16:47:00.106142 23057 sgd_solver.cpp:105] Iteration 19860, lr = 0.005
I0406 16:47:05.383986 23057 solver.cpp:218] Iteration 19872 (2.27368 iter/s, 5.27779s/12 iters), loss = 0.0193282
I0406 16:47:05.384150 23057 solver.cpp:237]     Train net output #0: loss = 0.019328 (* 1 = 0.019328 loss)
I0406 16:47:05.384160 23057 sgd_solver.cpp:105] Iteration 19872, lr = 0.005
I0406 16:47:10.654086 23057 solver.cpp:218] Iteration 19884 (2.27709 iter/s, 5.26988s/12 iters), loss = 0.086239
I0406 16:47:10.654129 23057 solver.cpp:237]     Train net output #0: loss = 0.0862387 (* 1 = 0.0862387 loss)
I0406 16:47:10.654135 23057 sgd_solver.cpp:105] Iteration 19884, lr = 0.005
I0406 16:47:12.706068 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19890.caffemodel
I0406 16:47:17.531013 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19890.solverstate
I0406 16:47:19.863545 23057 solver.cpp:330] Iteration 19890, Testing net (#0)
I0406 16:47:19.863572 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:47:21.010921 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:47:24.212020 23057 solver.cpp:397]     Test net output #0: accuracy = 0.417892
I0406 16:47:24.212054 23057 solver.cpp:397]     Test net output #1: loss = 3.45628 (* 1 = 3.45628 loss)
I0406 16:47:26.258940 23057 solver.cpp:218] Iteration 19896 (0.769001 iter/s, 15.6047s/12 iters), loss = 0.0705666
I0406 16:47:26.259004 23057 solver.cpp:237]     Train net output #0: loss = 0.0705664 (* 1 = 0.0705664 loss)
I0406 16:47:26.259014 23057 sgd_solver.cpp:105] Iteration 19896, lr = 0.005
I0406 16:47:31.535115 23057 solver.cpp:218] Iteration 19908 (2.27443 iter/s, 5.27605s/12 iters), loss = 0.196951
I0406 16:47:31.535169 23057 solver.cpp:237]     Train net output #0: loss = 0.196951 (* 1 = 0.196951 loss)
I0406 16:47:31.535178 23057 sgd_solver.cpp:105] Iteration 19908, lr = 0.005
I0406 16:47:36.826620 23057 solver.cpp:218] Iteration 19920 (2.26784 iter/s, 5.29139s/12 iters), loss = 0.197277
I0406 16:47:36.826738 23057 solver.cpp:237]     Train net output #0: loss = 0.197277 (* 1 = 0.197277 loss)
I0406 16:47:36.826746 23057 sgd_solver.cpp:105] Iteration 19920, lr = 0.005
I0406 16:47:39.701253 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:47:42.165621 23057 solver.cpp:218] Iteration 19932 (2.24769 iter/s, 5.33882s/12 iters), loss = 0.0430539
I0406 16:47:42.165669 23057 solver.cpp:237]     Train net output #0: loss = 0.0430536 (* 1 = 0.0430536 loss)
I0406 16:47:42.165676 23057 sgd_solver.cpp:105] Iteration 19932, lr = 0.005
I0406 16:47:47.389878 23057 solver.cpp:218] Iteration 19944 (2.29703 iter/s, 5.22415s/12 iters), loss = 0.226737
I0406 16:47:47.389930 23057 solver.cpp:237]     Train net output #0: loss = 0.226737 (* 1 = 0.226737 loss)
I0406 16:47:47.389937 23057 sgd_solver.cpp:105] Iteration 19944, lr = 0.005
I0406 16:47:52.681854 23057 solver.cpp:218] Iteration 19956 (2.26763 iter/s, 5.29186s/12 iters), loss = 0.206984
I0406 16:47:52.681898 23057 solver.cpp:237]     Train net output #0: loss = 0.206984 (* 1 = 0.206984 loss)
I0406 16:47:52.681905 23057 sgd_solver.cpp:105] Iteration 19956, lr = 0.005
I0406 16:47:57.772235 23057 solver.cpp:218] Iteration 19968 (2.35744 iter/s, 5.09027s/12 iters), loss = 0.134808
I0406 16:47:57.772289 23057 solver.cpp:237]     Train net output #0: loss = 0.134808 (* 1 = 0.134808 loss)
I0406 16:47:57.772298 23057 sgd_solver.cpp:105] Iteration 19968, lr = 0.005
I0406 16:48:03.033790 23057 solver.cpp:218] Iteration 19980 (2.28074 iter/s, 5.26144s/12 iters), loss = 0.062142
I0406 16:48:03.033836 23057 solver.cpp:237]     Train net output #0: loss = 0.0621417 (* 1 = 0.0621417 loss)
I0406 16:48:03.033843 23057 sgd_solver.cpp:105] Iteration 19980, lr = 0.005
I0406 16:48:07.962435 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19992.caffemodel
I0406 16:48:12.892204 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19992.solverstate
I0406 16:48:15.205668 23057 solver.cpp:330] Iteration 19992, Testing net (#0)
I0406 16:48:15.205693 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:48:16.374522 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:48:19.587893 23057 solver.cpp:397]     Test net output #0: accuracy = 0.436274
I0406 16:48:19.587924 23057 solver.cpp:397]     Test net output #1: loss = 3.50929 (* 1 = 3.50929 loss)
I0406 16:48:19.728233 23057 solver.cpp:218] Iteration 19992 (0.718811 iter/s, 16.6942s/12 iters), loss = 0.122608
I0406 16:48:19.729802 23057 solver.cpp:237]     Train net output #0: loss = 0.122608 (* 1 = 0.122608 loss)
I0406 16:48:19.729816 23057 sgd_solver.cpp:105] Iteration 19992, lr = 0.005
I0406 16:48:23.958130 23057 solver.cpp:218] Iteration 20004 (2.83803 iter/s, 4.22829s/12 iters), loss = 0.074628
I0406 16:48:23.958171 23057 solver.cpp:237]     Train net output #0: loss = 0.0746277 (* 1 = 0.0746277 loss)
I0406 16:48:23.958178 23057 sgd_solver.cpp:105] Iteration 20004, lr = 0.005
I0406 16:48:29.200736 23057 solver.cpp:218] Iteration 20016 (2.28898 iter/s, 5.2425s/12 iters), loss = 0.0608338
I0406 16:48:29.200778 23057 solver.cpp:237]     Train net output #0: loss = 0.0608334 (* 1 = 0.0608334 loss)
I0406 16:48:29.200783 23057 sgd_solver.cpp:105] Iteration 20016, lr = 0.005
I0406 16:48:34.419363 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:48:34.583786 23057 solver.cpp:218] Iteration 20028 (2.22926 iter/s, 5.38294s/12 iters), loss = 0.225823
I0406 16:48:34.583843 23057 solver.cpp:237]     Train net output #0: loss = 0.225823 (* 1 = 0.225823 loss)
I0406 16:48:34.583851 23057 sgd_solver.cpp:105] Iteration 20028, lr = 0.005
I0406 16:48:40.050143 23057 solver.cpp:218] Iteration 20040 (2.1953 iter/s, 5.46624s/12 iters), loss = 0.0241111
I0406 16:48:40.050253 23057 solver.cpp:237]     Train net output #0: loss = 0.0241108 (* 1 = 0.0241108 loss)
I0406 16:48:40.050266 23057 sgd_solver.cpp:105] Iteration 20040, lr = 0.005
I0406 16:48:45.164322 23057 solver.cpp:218] Iteration 20052 (2.34649 iter/s, 5.11402s/12 iters), loss = 0.0715499
I0406 16:48:45.164362 23057 solver.cpp:237]     Train net output #0: loss = 0.0715496 (* 1 = 0.0715496 loss)
I0406 16:48:45.164368 23057 sgd_solver.cpp:105] Iteration 20052, lr = 0.005
I0406 16:48:50.201481 23057 solver.cpp:218] Iteration 20064 (2.38234 iter/s, 5.03706s/12 iters), loss = 0.134341
I0406 16:48:50.201524 23057 solver.cpp:237]     Train net output #0: loss = 0.13434 (* 1 = 0.13434 loss)
I0406 16:48:50.201529 23057 sgd_solver.cpp:105] Iteration 20064, lr = 0.005
I0406 16:48:55.259599 23057 solver.cpp:218] Iteration 20076 (2.37247 iter/s, 5.05801s/12 iters), loss = 0.0449289
I0406 16:48:55.259646 23057 solver.cpp:237]     Train net output #0: loss = 0.0449286 (* 1 = 0.0449286 loss)
I0406 16:48:55.259651 23057 sgd_solver.cpp:105] Iteration 20076, lr = 0.005
I0406 16:49:00.451967 23057 solver.cpp:218] Iteration 20088 (2.31113 iter/s, 5.19227s/12 iters), loss = 0.0736496
I0406 16:49:00.452008 23057 solver.cpp:237]     Train net output #0: loss = 0.0736493 (* 1 = 0.0736493 loss)
I0406 16:49:00.452014 23057 sgd_solver.cpp:105] Iteration 20088, lr = 0.005
I0406 16:49:02.497359 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20094.caffemodel
I0406 16:49:06.963874 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20094.solverstate
I0406 16:49:09.415474 23057 solver.cpp:330] Iteration 20094, Testing net (#0)
I0406 16:49:09.415494 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:49:10.485088 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:49:13.281872 23057 blocking_queue.cpp:49] Waiting for data
I0406 16:49:13.724094 23057 solver.cpp:397]     Test net output #0: accuracy = 0.435662
I0406 16:49:13.724128 23057 solver.cpp:397]     Test net output #1: loss = 3.38682 (* 1 = 3.38682 loss)
I0406 16:49:15.563593 23057 solver.cpp:218] Iteration 20100 (0.7941 iter/s, 15.1114s/12 iters), loss = 0.0398907
I0406 16:49:15.563645 23057 solver.cpp:237]     Train net output #0: loss = 0.0398904 (* 1 = 0.0398904 loss)
I0406 16:49:15.563653 23057 sgd_solver.cpp:105] Iteration 20100, lr = 0.005
I0406 16:49:20.779239 23057 solver.cpp:218] Iteration 20112 (2.30082 iter/s, 5.21554s/12 iters), loss = 0.0263505
I0406 16:49:20.779284 23057 solver.cpp:237]     Train net output #0: loss = 0.0263502 (* 1 = 0.0263502 loss)
I0406 16:49:20.779290 23057 sgd_solver.cpp:105] Iteration 20112, lr = 0.005
I0406 16:49:25.858732 23057 solver.cpp:218] Iteration 20124 (2.36249 iter/s, 5.07939s/12 iters), loss = 0.105506
I0406 16:49:25.858781 23057 solver.cpp:237]     Train net output #0: loss = 0.105505 (* 1 = 0.105505 loss)
I0406 16:49:25.858788 23057 sgd_solver.cpp:105] Iteration 20124, lr = 0.005
I0406 16:49:28.022505 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:49:31.080915 23057 solver.cpp:218] Iteration 20136 (2.29794 iter/s, 5.22207s/12 iters), loss = 0.0759811
I0406 16:49:31.080968 23057 solver.cpp:237]     Train net output #0: loss = 0.0759808 (* 1 = 0.0759808 loss)
I0406 16:49:31.080976 23057 sgd_solver.cpp:105] Iteration 20136, lr = 0.005
I0406 16:49:36.320209 23057 solver.cpp:218] Iteration 20148 (2.29043 iter/s, 5.23919s/12 iters), loss = 0.0517724
I0406 16:49:36.320252 23057 solver.cpp:237]     Train net output #0: loss = 0.0517721 (* 1 = 0.0517721 loss)
I0406 16:49:36.320258 23057 sgd_solver.cpp:105] Iteration 20148, lr = 0.005
I0406 16:49:41.547020 23057 solver.cpp:218] Iteration 20160 (2.2959 iter/s, 5.22671s/12 iters), loss = 0.0464805
I0406 16:49:41.547156 23057 solver.cpp:237]     Train net output #0: loss = 0.0464801 (* 1 = 0.0464801 loss)
I0406 16:49:41.547163 23057 sgd_solver.cpp:105] Iteration 20160, lr = 0.005
I0406 16:49:46.774060 23057 solver.cpp:218] Iteration 20172 (2.29584 iter/s, 5.22684s/12 iters), loss = 0.131444
I0406 16:49:46.774109 23057 solver.cpp:237]     Train net output #0: loss = 0.131443 (* 1 = 0.131443 loss)
I0406 16:49:46.774116 23057 sgd_solver.cpp:105] Iteration 20172, lr = 0.005
I0406 16:49:51.996295 23057 solver.cpp:218] Iteration 20184 (2.29791 iter/s, 5.22213s/12 iters), loss = 0.02391
I0406 16:49:51.996337 23057 solver.cpp:237]     Train net output #0: loss = 0.0239097 (* 1 = 0.0239097 loss)
I0406 16:49:51.996343 23057 sgd_solver.cpp:105] Iteration 20184, lr = 0.005
I0406 16:49:57.004554 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20196.caffemodel
I0406 16:50:01.388551 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20196.solverstate
I0406 16:50:03.810201 23057 solver.cpp:330] Iteration 20196, Testing net (#0)
I0406 16:50:03.810225 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:50:04.873230 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:50:08.281195 23057 solver.cpp:397]     Test net output #0: accuracy = 0.428309
I0406 16:50:08.281230 23057 solver.cpp:397]     Test net output #1: loss = 3.4625 (* 1 = 3.4625 loss)
I0406 16:50:08.412262 23057 solver.cpp:218] Iteration 20196 (0.731004 iter/s, 16.4158s/12 iters), loss = 0.0522265
I0406 16:50:08.412313 23057 solver.cpp:237]     Train net output #0: loss = 0.0522262 (* 1 = 0.0522262 loss)
I0406 16:50:08.412322 23057 sgd_solver.cpp:105] Iteration 20196, lr = 0.005
I0406 16:50:12.704169 23057 solver.cpp:218] Iteration 20208 (2.79603 iter/s, 4.2918s/12 iters), loss = 0.0555659
I0406 16:50:12.704295 23057 solver.cpp:237]     Train net output #0: loss = 0.0555655 (* 1 = 0.0555655 loss)
I0406 16:50:12.704301 23057 sgd_solver.cpp:105] Iteration 20208, lr = 0.005
I0406 16:50:17.962333 23057 solver.cpp:218] Iteration 20220 (2.28225 iter/s, 5.25798s/12 iters), loss = 0.086246
I0406 16:50:17.962383 23057 solver.cpp:237]     Train net output #0: loss = 0.0862456 (* 1 = 0.0862456 loss)
I0406 16:50:17.962388 23057 sgd_solver.cpp:105] Iteration 20220, lr = 0.005
I0406 16:50:22.261454 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:50:23.031050 23057 solver.cpp:218] Iteration 20232 (2.36751 iter/s, 5.06861s/12 iters), loss = 0.148468
I0406 16:50:23.031095 23057 solver.cpp:237]     Train net output #0: loss = 0.148468 (* 1 = 0.148468 loss)
I0406 16:50:23.031101 23057 sgd_solver.cpp:105] Iteration 20232, lr = 0.005
I0406 16:50:28.273128 23057 solver.cpp:218] Iteration 20244 (2.28922 iter/s, 5.24197s/12 iters), loss = 0.127474
I0406 16:50:28.273177 23057 solver.cpp:237]     Train net output #0: loss = 0.127474 (* 1 = 0.127474 loss)
I0406 16:50:28.273186 23057 sgd_solver.cpp:105] Iteration 20244, lr = 0.005
I0406 16:50:33.642582 23057 solver.cpp:218] Iteration 20256 (2.23491 iter/s, 5.36935s/12 iters), loss = 0.0995337
I0406 16:50:33.642635 23057 solver.cpp:237]     Train net output #0: loss = 0.0995334 (* 1 = 0.0995334 loss)
I0406 16:50:33.642644 23057 sgd_solver.cpp:105] Iteration 20256, lr = 0.005
I0406 16:50:39.022776 23057 solver.cpp:218] Iteration 20268 (2.23045 iter/s, 5.38008s/12 iters), loss = 0.0665967
I0406 16:50:39.022819 23057 solver.cpp:237]     Train net output #0: loss = 0.0665963 (* 1 = 0.0665963 loss)
I0406 16:50:39.022825 23057 sgd_solver.cpp:105] Iteration 20268, lr = 0.005
I0406 16:50:44.379993 23057 solver.cpp:218] Iteration 20280 (2.24001 iter/s, 5.35711s/12 iters), loss = 0.0520548
I0406 16:50:44.380095 23057 solver.cpp:237]     Train net output #0: loss = 0.0520544 (* 1 = 0.0520544 loss)
I0406 16:50:44.380102 23057 sgd_solver.cpp:105] Iteration 20280, lr = 0.005
I0406 16:50:49.672390 23057 solver.cpp:218] Iteration 20292 (2.26747 iter/s, 5.29223s/12 iters), loss = 0.0408952
I0406 16:50:49.672433 23057 solver.cpp:237]     Train net output #0: loss = 0.0408949 (* 1 = 0.0408949 loss)
I0406 16:50:49.672439 23057 sgd_solver.cpp:105] Iteration 20292, lr = 0.005
I0406 16:50:51.789458 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20298.caffemodel
I0406 16:50:57.292503 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20298.solverstate
I0406 16:50:59.975647 23057 solver.cpp:330] Iteration 20298, Testing net (#0)
I0406 16:50:59.975666 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:51:01.021235 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:51:04.348125 23057 solver.cpp:397]     Test net output #0: accuracy = 0.425858
I0406 16:51:04.348157 23057 solver.cpp:397]     Test net output #1: loss = 3.6075 (* 1 = 3.6075 loss)
I0406 16:51:06.347266 23057 solver.cpp:218] Iteration 20304 (0.719654 iter/s, 16.6747s/12 iters), loss = 0.0232064
I0406 16:51:06.347311 23057 solver.cpp:237]     Train net output #0: loss = 0.0232061 (* 1 = 0.0232061 loss)
I0406 16:51:06.347317 23057 sgd_solver.cpp:105] Iteration 20304, lr = 0.005
I0406 16:51:11.676471 23057 solver.cpp:218] Iteration 20316 (2.25179 iter/s, 5.3291s/12 iters), loss = 0.0582524
I0406 16:51:11.676517 23057 solver.cpp:237]     Train net output #0: loss = 0.0582521 (* 1 = 0.0582521 loss)
I0406 16:51:11.676525 23057 sgd_solver.cpp:105] Iteration 20316, lr = 0.005
I0406 16:51:16.835593 23057 solver.cpp:218] Iteration 20328 (2.32603 iter/s, 5.15901s/12 iters), loss = 0.055012
I0406 16:51:16.835731 23057 solver.cpp:237]     Train net output #0: loss = 0.0550117 (* 1 = 0.0550117 loss)
I0406 16:51:16.835738 23057 sgd_solver.cpp:105] Iteration 20328, lr = 0.005
I0406 16:51:18.376811 23079 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:51:22.212739 23057 solver.cpp:218] Iteration 20340 (2.23175 iter/s, 5.37695s/12 iters), loss = 0.214548
I0406 16:51:22.212774 23057 solver.cpp:237]     Train net output #0: loss = 0.214548 (* 1 = 0.214548 loss)
I0406 16:51:22.212779 23057 sgd_solver.cpp:105] Iteration 20340, lr = 0.005
I0406 16:51:27.353070 23057 solver.cpp:218] Iteration 20352 (2.33452 iter/s, 5.14024s/12 iters), loss = 0.150399
I0406 16:51:27.353111 23057 solver.cpp:237]     Train net output #0: loss = 0.150399 (* 1 = 0.150399 loss)
I0406 16:51:27.353116 23057 sgd_solver.cpp:105] Iteration 20352, lr = 0.005
I0406 16:51:32.491392 23057 solver.cpp:218] Iteration 20364 (2.33544 iter/s, 5.13822s/12 iters), loss = 0.162611
I0406 16:51:32.491439 23057 solver.cpp:237]     Train net output #0: loss = 0.162611 (* 1 = 0.162611 loss)
I0406 16:51:32.491447 23057 sgd_solver.cpp:105] Iteration 20364, lr = 0.005
I0406 16:51:37.807595 23057 solver.cpp:218] Iteration 20376 (2.2573 iter/s, 5.31609s/12 iters), loss = 0.0493331
I0406 16:51:37.807651 23057 solver.cpp:237]     Train net output #0: loss = 0.0493328 (* 1 = 0.0493328 loss)
I0406 16:51:37.807659 23057 sgd_solver.cpp:105] Iteration 20376, lr = 0.005
I0406 16:51:43.439216 23057 solver.cpp:218] Iteration 20388 (2.13087 iter/s, 5.6315s/12 iters), loss = 0.174647
I0406 16:51:43.439254 23057 solver.cpp:237]     Train net output #0: loss = 0.174647 (* 1 = 0.174647 loss)
I0406 16:51:43.439260 23057 sgd_solver.cpp:105] Iteration 20388, lr = 0.005
I0406 16:51:48.421403 23057 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20400.caffemodel
I0406 16:51:53.022097 23057 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20400.solverstate
I0406 16:51:56.286005 23057 solver.cpp:310] Iteration 20400, loss = 0.0559074
I0406 16:51:56.286036 23057 solver.cpp:330] Iteration 20400, Testing net (#0)
I0406 16:51:56.286041 23057 net.cpp:676] Ignoring source layer train-data
I0406 16:51:57.232750 23114 data_layer.cpp:73] Restarting data prefetching from start.
I0406 16:52:00.815255 23057 solver.cpp:397]     Test net output #0: accuracy = 0.435049
I0406 16:52:00.815284 23057 solver.cpp:397]     Test net output #1: loss = 3.34178 (* 1 = 3.34178 loss)
I0406 16:52:00.815287 23057 solver.cpp:315] Optimization Done.
I0406 16:52:00.815290 23057 caffe.cpp:259] Optimization Done.