DIGITS-CNN/cars/lr-investigations/fixed/1e-3/caffe_output.log

I0405 13:16:14.318145  1863 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210405-115540-ad40/solver.prototxt
I0405 13:16:14.318292  1863 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string).
W0405 13:16:14.318296  1863 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type.
I0405 13:16:14.318351  1863 caffe.cpp:218] Using GPUs 2
I0405 13:16:14.333146  1863 caffe.cpp:223] GPU 2: GeForce GTX TITAN X
I0405 13:16:14.538969  1863 solver.cpp:44] Initializing solver from parameters:
test_iter: 51
test_interval: 102
base_lr: 0.001
display: 12
max_iter: 20400
lr_policy: "fixed"
momentum: 0.9
weight_decay: 1.0000001e-05
snapshot: 102
snapshot_prefix: "snapshot"
solver_mode: GPU
device_id: 2
net: "train_val.prototxt"
train_state {
level: 0
stage: ""
}
type: "SGD"
I0405 13:16:14.539878  1863 solver.cpp:87] Creating training net from net file: train_val.prototxt
I0405 13:16:14.540518  1863 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data
I0405 13:16:14.540530  1863 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy
I0405 13:16:14.540652  1863 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"
}
I0405 13:16:14.540730  1863 layer_factory.hpp:77] Creating layer train-data
I0405 13:16:14.542685  1863 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/train_db
I0405 13:16:14.542927  1863 net.cpp:84] Creating Layer train-data
I0405 13:16:14.542937  1863 net.cpp:380] train-data -> data
I0405 13:16:14.542954  1863 net.cpp:380] train-data -> label
I0405 13:16:14.542963  1863 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0405 13:16:14.547616  1863 data_layer.cpp:45] output data size: 128,3,227,227
I0405 13:16:14.685828  1863 net.cpp:122] Setting up train-data
I0405 13:16:14.685850  1863 net.cpp:129] Top shape: 128 3 227 227 (19787136)
I0405 13:16:14.685854  1863 net.cpp:129] Top shape: 128 (128)
I0405 13:16:14.685856  1863 net.cpp:137] Memory required for data: 79149056
I0405 13:16:14.685864  1863 layer_factory.hpp:77] Creating layer conv1
I0405 13:16:14.685883  1863 net.cpp:84] Creating Layer conv1
I0405 13:16:14.685889  1863 net.cpp:406] conv1 <- data
I0405 13:16:14.685899  1863 net.cpp:380] conv1 -> conv1
I0405 13:16:15.109823  1863 net.cpp:122] Setting up conv1
I0405 13:16:15.109846  1863 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 13:16:15.109849  1863 net.cpp:137] Memory required for data: 227833856
I0405 13:16:15.109867  1863 layer_factory.hpp:77] Creating layer relu1
I0405 13:16:15.109877  1863 net.cpp:84] Creating Layer relu1
I0405 13:16:15.109880  1863 net.cpp:406] relu1 <- conv1
I0405 13:16:15.109885  1863 net.cpp:367] relu1 -> conv1 (in-place)
I0405 13:16:15.110142  1863 net.cpp:122] Setting up relu1
I0405 13:16:15.110149  1863 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 13:16:15.110152  1863 net.cpp:137] Memory required for data: 376518656
I0405 13:16:15.110154  1863 layer_factory.hpp:77] Creating layer norm1
I0405 13:16:15.110162  1863 net.cpp:84] Creating Layer norm1
I0405 13:16:15.110164  1863 net.cpp:406] norm1 <- conv1
I0405 13:16:15.110190  1863 net.cpp:380] norm1 -> norm1
I0405 13:16:15.110599  1863 net.cpp:122] Setting up norm1
I0405 13:16:15.110607  1863 net.cpp:129] Top shape: 128 96 55 55 (37171200)
I0405 13:16:15.110610  1863 net.cpp:137] Memory required for data: 525203456
I0405 13:16:15.110612  1863 layer_factory.hpp:77] Creating layer pool1
I0405 13:16:15.110618  1863 net.cpp:84] Creating Layer pool1
I0405 13:16:15.110621  1863 net.cpp:406] pool1 <- norm1
I0405 13:16:15.110625  1863 net.cpp:380] pool1 -> pool1
I0405 13:16:15.110656  1863 net.cpp:122] Setting up pool1
I0405 13:16:15.110661  1863 net.cpp:129] Top shape: 128 96 27 27 (8957952)
I0405 13:16:15.110663  1863 net.cpp:137] Memory required for data: 561035264
I0405 13:16:15.110666  1863 layer_factory.hpp:77] Creating layer conv2
I0405 13:16:15.110674  1863 net.cpp:84] Creating Layer conv2
I0405 13:16:15.110677  1863 net.cpp:406] conv2 <- pool1
I0405 13:16:15.110680  1863 net.cpp:380] conv2 -> conv2
I0405 13:16:15.116248  1863 net.cpp:122] Setting up conv2
I0405 13:16:15.116268  1863 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 13:16:15.116271  1863 net.cpp:137] Memory required for data: 656586752
I0405 13:16:15.116279  1863 layer_factory.hpp:77] Creating layer relu2
I0405 13:16:15.116286  1863 net.cpp:84] Creating Layer relu2
I0405 13:16:15.116289  1863 net.cpp:406] relu2 <- conv2
I0405 13:16:15.116294  1863 net.cpp:367] relu2 -> conv2 (in-place)
I0405 13:16:15.116734  1863 net.cpp:122] Setting up relu2
I0405 13:16:15.116742  1863 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 13:16:15.116745  1863 net.cpp:137] Memory required for data: 752138240
I0405 13:16:15.116747  1863 layer_factory.hpp:77] Creating layer norm2
I0405 13:16:15.116755  1863 net.cpp:84] Creating Layer norm2
I0405 13:16:15.116756  1863 net.cpp:406] norm2 <- conv2
I0405 13:16:15.116761  1863 net.cpp:380] norm2 -> norm2
I0405 13:16:15.117102  1863 net.cpp:122] Setting up norm2
I0405 13:16:15.117110  1863 net.cpp:129] Top shape: 128 256 27 27 (23887872)
I0405 13:16:15.117113  1863 net.cpp:137] Memory required for data: 847689728
I0405 13:16:15.117115  1863 layer_factory.hpp:77] Creating layer pool2
I0405 13:16:15.117123  1863 net.cpp:84] Creating Layer pool2
I0405 13:16:15.117125  1863 net.cpp:406] pool2 <- norm2
I0405 13:16:15.117130  1863 net.cpp:380] pool2 -> pool2
I0405 13:16:15.117157  1863 net.cpp:122] Setting up pool2
I0405 13:16:15.117161  1863 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 13:16:15.117163  1863 net.cpp:137] Memory required for data: 869840896
I0405 13:16:15.117166  1863 layer_factory.hpp:77] Creating layer conv3
I0405 13:16:15.117174  1863 net.cpp:84] Creating Layer conv3
I0405 13:16:15.117177  1863 net.cpp:406] conv3 <- pool2
I0405 13:16:15.117182  1863 net.cpp:380] conv3 -> conv3
I0405 13:16:15.130030  1863 net.cpp:122] Setting up conv3
I0405 13:16:15.130049  1863 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 13:16:15.130051  1863 net.cpp:137] Memory required for data: 903067648
I0405 13:16:15.130061  1863 layer_factory.hpp:77] Creating layer relu3
I0405 13:16:15.130071  1863 net.cpp:84] Creating Layer relu3
I0405 13:16:15.130074  1863 net.cpp:406] relu3 <- conv3
I0405 13:16:15.130079  1863 net.cpp:367] relu3 -> conv3 (in-place)
I0405 13:16:15.130535  1863 net.cpp:122] Setting up relu3
I0405 13:16:15.130543  1863 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 13:16:15.130546  1863 net.cpp:137] Memory required for data: 936294400
I0405 13:16:15.130549  1863 layer_factory.hpp:77] Creating layer conv4
I0405 13:16:15.130559  1863 net.cpp:84] Creating Layer conv4
I0405 13:16:15.130561  1863 net.cpp:406] conv4 <- conv3
I0405 13:16:15.130568  1863 net.cpp:380] conv4 -> conv4
I0405 13:16:15.139864  1863 net.cpp:122] Setting up conv4
I0405 13:16:15.139886  1863 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 13:16:15.139889  1863 net.cpp:137] Memory required for data: 969521152
I0405 13:16:15.139897  1863 layer_factory.hpp:77] Creating layer relu4
I0405 13:16:15.139907  1863 net.cpp:84] Creating Layer relu4
I0405 13:16:15.139931  1863 net.cpp:406] relu4 <- conv4
I0405 13:16:15.139936  1863 net.cpp:367] relu4 -> conv4 (in-place)
I0405 13:16:15.140249  1863 net.cpp:122] Setting up relu4
I0405 13:16:15.140259  1863 net.cpp:129] Top shape: 128 384 13 13 (8306688)
I0405 13:16:15.140260  1863 net.cpp:137] Memory required for data: 1002747904
I0405 13:16:15.140262  1863 layer_factory.hpp:77] Creating layer conv5
I0405 13:16:15.140272  1863 net.cpp:84] Creating Layer conv5
I0405 13:16:15.140275  1863 net.cpp:406] conv5 <- conv4
I0405 13:16:15.140278  1863 net.cpp:380] conv5 -> conv5
I0405 13:16:15.147621  1863 net.cpp:122] Setting up conv5
I0405 13:16:15.147641  1863 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 13:16:15.147644  1863 net.cpp:137] Memory required for data: 1024899072
I0405 13:16:15.147655  1863 layer_factory.hpp:77] Creating layer relu5
I0405 13:16:15.147663  1863 net.cpp:84] Creating Layer relu5
I0405 13:16:15.147666  1863 net.cpp:406] relu5 <- conv5
I0405 13:16:15.147671  1863 net.cpp:367] relu5 -> conv5 (in-place)
I0405 13:16:15.148123  1863 net.cpp:122] Setting up relu5
I0405 13:16:15.148131  1863 net.cpp:129] Top shape: 128 256 13 13 (5537792)
I0405 13:16:15.148133  1863 net.cpp:137] Memory required for data: 1047050240
I0405 13:16:15.148135  1863 layer_factory.hpp:77] Creating layer pool5
I0405 13:16:15.148141  1863 net.cpp:84] Creating Layer pool5
I0405 13:16:15.148144  1863 net.cpp:406] pool5 <- conv5
I0405 13:16:15.148149  1863 net.cpp:380] pool5 -> pool5
I0405 13:16:15.148182  1863 net.cpp:122] Setting up pool5
I0405 13:16:15.148186  1863 net.cpp:129] Top shape: 128 256 6 6 (1179648)
I0405 13:16:15.148188  1863 net.cpp:137] Memory required for data: 1051768832
I0405 13:16:15.148190  1863 layer_factory.hpp:77] Creating layer fc6
I0405 13:16:15.148200  1863 net.cpp:84] Creating Layer fc6
I0405 13:16:15.148202  1863 net.cpp:406] fc6 <- pool5
I0405 13:16:15.148206  1863 net.cpp:380] fc6 -> fc6
I0405 13:16:15.492358  1863 net.cpp:122] Setting up fc6
I0405 13:16:15.492380  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.492383  1863 net.cpp:137] Memory required for data: 1053865984
I0405 13:16:15.492391  1863 layer_factory.hpp:77] Creating layer relu6
I0405 13:16:15.492404  1863 net.cpp:84] Creating Layer relu6
I0405 13:16:15.492408  1863 net.cpp:406] relu6 <- fc6
I0405 13:16:15.492413  1863 net.cpp:367] relu6 -> fc6 (in-place)
I0405 13:16:15.493022  1863 net.cpp:122] Setting up relu6
I0405 13:16:15.493031  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.493034  1863 net.cpp:137] Memory required for data: 1055963136
I0405 13:16:15.493036  1863 layer_factory.hpp:77] Creating layer drop6
I0405 13:16:15.493042  1863 net.cpp:84] Creating Layer drop6
I0405 13:16:15.493044  1863 net.cpp:406] drop6 <- fc6
I0405 13:16:15.493049  1863 net.cpp:367] drop6 -> fc6 (in-place)
I0405 13:16:15.493073  1863 net.cpp:122] Setting up drop6
I0405 13:16:15.493077  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.493079  1863 net.cpp:137] Memory required for data: 1058060288
I0405 13:16:15.493081  1863 layer_factory.hpp:77] Creating layer fc7
I0405 13:16:15.493090  1863 net.cpp:84] Creating Layer fc7
I0405 13:16:15.493093  1863 net.cpp:406] fc7 <- fc6
I0405 13:16:15.493098  1863 net.cpp:380] fc7 -> fc7
I0405 13:16:15.641261  1863 net.cpp:122] Setting up fc7
I0405 13:16:15.641281  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.641283  1863 net.cpp:137] Memory required for data: 1060157440
I0405 13:16:15.641292  1863 layer_factory.hpp:77] Creating layer relu7
I0405 13:16:15.641300  1863 net.cpp:84] Creating Layer relu7
I0405 13:16:15.641304  1863 net.cpp:406] relu7 <- fc7
I0405 13:16:15.641309  1863 net.cpp:367] relu7 -> fc7 (in-place)
I0405 13:16:15.641677  1863 net.cpp:122] Setting up relu7
I0405 13:16:15.641686  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.641688  1863 net.cpp:137] Memory required for data: 1062254592
I0405 13:16:15.641690  1863 layer_factory.hpp:77] Creating layer drop7
I0405 13:16:15.641695  1863 net.cpp:84] Creating Layer drop7
I0405 13:16:15.641717  1863 net.cpp:406] drop7 <- fc7
I0405 13:16:15.641721  1863 net.cpp:367] drop7 -> fc7 (in-place)
I0405 13:16:15.641742  1863 net.cpp:122] Setting up drop7
I0405 13:16:15.641746  1863 net.cpp:129] Top shape: 128 4096 (524288)
I0405 13:16:15.641748  1863 net.cpp:137] Memory required for data: 1064351744
I0405 13:16:15.641750  1863 layer_factory.hpp:77] Creating layer fc8
I0405 13:16:15.641757  1863 net.cpp:84] Creating Layer fc8
I0405 13:16:15.641759  1863 net.cpp:406] fc8 <- fc7
I0405 13:16:15.641763  1863 net.cpp:380] fc8 -> fc8
I0405 13:16:15.648928  1863 net.cpp:122] Setting up fc8
I0405 13:16:15.648945  1863 net.cpp:129] Top shape: 128 196 (25088)
I0405 13:16:15.648948  1863 net.cpp:137] Memory required for data: 1064452096
I0405 13:16:15.648957  1863 layer_factory.hpp:77] Creating layer loss
I0405 13:16:15.648963  1863 net.cpp:84] Creating Layer loss
I0405 13:16:15.648967  1863 net.cpp:406] loss <- fc8
I0405 13:16:15.648970  1863 net.cpp:406] loss <- label
I0405 13:16:15.648977  1863 net.cpp:380] loss -> loss
I0405 13:16:15.648986  1863 layer_factory.hpp:77] Creating layer loss
I0405 13:16:15.649670  1863 net.cpp:122] Setting up loss
I0405 13:16:15.649678  1863 net.cpp:129] Top shape: (1)
I0405 13:16:15.649680  1863 net.cpp:132]     with loss weight 1
I0405 13:16:15.649698  1863 net.cpp:137] Memory required for data: 1064452100
I0405 13:16:15.649700  1863 net.cpp:198] loss needs backward computation.
I0405 13:16:15.649705  1863 net.cpp:198] fc8 needs backward computation.
I0405 13:16:15.649708  1863 net.cpp:198] drop7 needs backward computation.
I0405 13:16:15.649709  1863 net.cpp:198] relu7 needs backward computation.
I0405 13:16:15.649711  1863 net.cpp:198] fc7 needs backward computation.
I0405 13:16:15.649714  1863 net.cpp:198] drop6 needs backward computation.
I0405 13:16:15.649716  1863 net.cpp:198] relu6 needs backward computation.
I0405 13:16:15.649718  1863 net.cpp:198] fc6 needs backward computation.
I0405 13:16:15.649720  1863 net.cpp:198] pool5 needs backward computation.
I0405 13:16:15.649724  1863 net.cpp:198] relu5 needs backward computation.
I0405 13:16:15.649725  1863 net.cpp:198] conv5 needs backward computation.
I0405 13:16:15.649727  1863 net.cpp:198] relu4 needs backward computation.
I0405 13:16:15.649729  1863 net.cpp:198] conv4 needs backward computation.
I0405 13:16:15.649731  1863 net.cpp:198] relu3 needs backward computation.
I0405 13:16:15.649734  1863 net.cpp:198] conv3 needs backward computation.
I0405 13:16:15.649736  1863 net.cpp:198] pool2 needs backward computation.
I0405 13:16:15.649739  1863 net.cpp:198] norm2 needs backward computation.
I0405 13:16:15.649741  1863 net.cpp:198] relu2 needs backward computation.
I0405 13:16:15.649744  1863 net.cpp:198] conv2 needs backward computation.
I0405 13:16:15.649745  1863 net.cpp:198] pool1 needs backward computation.
I0405 13:16:15.649749  1863 net.cpp:198] norm1 needs backward computation.
I0405 13:16:15.649750  1863 net.cpp:198] relu1 needs backward computation.
I0405 13:16:15.649752  1863 net.cpp:198] conv1 needs backward computation.
I0405 13:16:15.649755  1863 net.cpp:200] train-data does not need backward computation.
I0405 13:16:15.649758  1863 net.cpp:242] This network produces output loss
I0405 13:16:15.649770  1863 net.cpp:255] Network initialization done.
I0405 13:16:15.650286  1863 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt
I0405 13:16:15.650313  1863 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data
I0405 13:16:15.650441  1863 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"
}
I0405 13:16:15.650539  1863 layer_factory.hpp:77] Creating layer val-data
I0405 13:16:15.652529  1863 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/val_db
I0405 13:16:15.652766  1863 net.cpp:84] Creating Layer val-data
I0405 13:16:15.652777  1863 net.cpp:380] val-data -> data
I0405 13:16:15.652784  1863 net.cpp:380] val-data -> label
I0405 13:16:15.652789  1863 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-AIN-3/digits/jobs/20210401-115716-aaf7/mean.binaryproto
I0405 13:16:15.656452  1863 data_layer.cpp:45] output data size: 32,3,227,227
I0405 13:16:15.689146  1863 net.cpp:122] Setting up val-data
I0405 13:16:15.689168  1863 net.cpp:129] Top shape: 32 3 227 227 (4946784)
I0405 13:16:15.689172  1863 net.cpp:129] Top shape: 32 (32)
I0405 13:16:15.689173  1863 net.cpp:137] Memory required for data: 19787264
I0405 13:16:15.689178  1863 layer_factory.hpp:77] Creating layer label_val-data_1_split
I0405 13:16:15.689188  1863 net.cpp:84] Creating Layer label_val-data_1_split
I0405 13:16:15.689193  1863 net.cpp:406] label_val-data_1_split <- label
I0405 13:16:15.689198  1863 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0
I0405 13:16:15.689205  1863 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1
I0405 13:16:15.689285  1863 net.cpp:122] Setting up label_val-data_1_split
I0405 13:16:15.689292  1863 net.cpp:129] Top shape: 32 (32)
I0405 13:16:15.689294  1863 net.cpp:129] Top shape: 32 (32)
I0405 13:16:15.689296  1863 net.cpp:137] Memory required for data: 19787520
I0405 13:16:15.689298  1863 layer_factory.hpp:77] Creating layer conv1
I0405 13:16:15.689309  1863 net.cpp:84] Creating Layer conv1
I0405 13:16:15.689312  1863 net.cpp:406] conv1 <- data
I0405 13:16:15.689316  1863 net.cpp:380] conv1 -> conv1
I0405 13:16:15.691622  1863 net.cpp:122] Setting up conv1
I0405 13:16:15.691634  1863 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 13:16:15.691637  1863 net.cpp:137] Memory required for data: 56958720
I0405 13:16:15.691645  1863 layer_factory.hpp:77] Creating layer relu1
I0405 13:16:15.691651  1863 net.cpp:84] Creating Layer relu1
I0405 13:16:15.691653  1863 net.cpp:406] relu1 <- conv1
I0405 13:16:15.691658  1863 net.cpp:367] relu1 -> conv1 (in-place)
I0405 13:16:15.691916  1863 net.cpp:122] Setting up relu1
I0405 13:16:15.691923  1863 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 13:16:15.691926  1863 net.cpp:137] Memory required for data: 94129920
I0405 13:16:15.691928  1863 layer_factory.hpp:77] Creating layer norm1
I0405 13:16:15.691934  1863 net.cpp:84] Creating Layer norm1
I0405 13:16:15.691937  1863 net.cpp:406] norm1 <- conv1
I0405 13:16:15.691941  1863 net.cpp:380] norm1 -> norm1
I0405 13:16:15.692358  1863 net.cpp:122] Setting up norm1
I0405 13:16:15.692366  1863 net.cpp:129] Top shape: 32 96 55 55 (9292800)
I0405 13:16:15.692368  1863 net.cpp:137] Memory required for data: 131301120
I0405 13:16:15.692370  1863 layer_factory.hpp:77] Creating layer pool1
I0405 13:16:15.692375  1863 net.cpp:84] Creating Layer pool1
I0405 13:16:15.692378  1863 net.cpp:406] pool1 <- norm1
I0405 13:16:15.692382  1863 net.cpp:380] pool1 -> pool1
I0405 13:16:15.692407  1863 net.cpp:122] Setting up pool1
I0405 13:16:15.692411  1863 net.cpp:129] Top shape: 32 96 27 27 (2239488)
I0405 13:16:15.692414  1863 net.cpp:137] Memory required for data: 140259072
I0405 13:16:15.692415  1863 layer_factory.hpp:77] Creating layer conv2
I0405 13:16:15.692421  1863 net.cpp:84] Creating Layer conv2
I0405 13:16:15.692425  1863 net.cpp:406] conv2 <- pool1
I0405 13:16:15.692448  1863 net.cpp:380] conv2 -> conv2
I0405 13:16:15.698367  1863 net.cpp:122] Setting up conv2
I0405 13:16:15.698385  1863 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 13:16:15.698387  1863 net.cpp:137] Memory required for data: 164146944
I0405 13:16:15.698397  1863 layer_factory.hpp:77] Creating layer relu2
I0405 13:16:15.698405  1863 net.cpp:84] Creating Layer relu2
I0405 13:16:15.698408  1863 net.cpp:406] relu2 <- conv2
I0405 13:16:15.698413  1863 net.cpp:367] relu2 -> conv2 (in-place)
I0405 13:16:15.701848  1863 net.cpp:122] Setting up relu2
I0405 13:16:15.701860  1863 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 13:16:15.701862  1863 net.cpp:137] Memory required for data: 188034816
I0405 13:16:15.701865  1863 layer_factory.hpp:77] Creating layer norm2
I0405 13:16:15.701875  1863 net.cpp:84] Creating Layer norm2
I0405 13:16:15.701879  1863 net.cpp:406] norm2 <- conv2
I0405 13:16:15.701884  1863 net.cpp:380] norm2 -> norm2
I0405 13:16:15.705041  1863 net.cpp:122] Setting up norm2
I0405 13:16:15.705054  1863 net.cpp:129] Top shape: 32 256 27 27 (5971968)
I0405 13:16:15.705056  1863 net.cpp:137] Memory required for data: 211922688
I0405 13:16:15.705060  1863 layer_factory.hpp:77] Creating layer pool2
I0405 13:16:15.705065  1863 net.cpp:84] Creating Layer pool2
I0405 13:16:15.705067  1863 net.cpp:406] pool2 <- norm2
I0405 13:16:15.705073  1863 net.cpp:380] pool2 -> pool2
I0405 13:16:15.705103  1863 net.cpp:122] Setting up pool2
I0405 13:16:15.705107  1863 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 13:16:15.705109  1863 net.cpp:137] Memory required for data: 217460480
I0405 13:16:15.705111  1863 layer_factory.hpp:77] Creating layer conv3
I0405 13:16:15.705123  1863 net.cpp:84] Creating Layer conv3
I0405 13:16:15.705125  1863 net.cpp:406] conv3 <- pool2
I0405 13:16:15.705129  1863 net.cpp:380] conv3 -> conv3
I0405 13:16:15.717329  1863 net.cpp:122] Setting up conv3
I0405 13:16:15.717348  1863 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 13:16:15.717350  1863 net.cpp:137] Memory required for data: 225767168
I0405 13:16:15.717362  1863 layer_factory.hpp:77] Creating layer relu3
I0405 13:16:15.717370  1863 net.cpp:84] Creating Layer relu3
I0405 13:16:15.717372  1863 net.cpp:406] relu3 <- conv3
I0405 13:16:15.717379  1863 net.cpp:367] relu3 -> conv3 (in-place)
I0405 13:16:15.717839  1863 net.cpp:122] Setting up relu3
I0405 13:16:15.717849  1863 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 13:16:15.717851  1863 net.cpp:137] Memory required for data: 234073856
I0405 13:16:15.717854  1863 layer_factory.hpp:77] Creating layer conv4
I0405 13:16:15.717864  1863 net.cpp:84] Creating Layer conv4
I0405 13:16:15.717866  1863 net.cpp:406] conv4 <- conv3
I0405 13:16:15.717870  1863 net.cpp:380] conv4 -> conv4
I0405 13:16:15.728333  1863 net.cpp:122] Setting up conv4
I0405 13:16:15.728360  1863 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 13:16:15.728365  1863 net.cpp:137] Memory required for data: 242380544
I0405 13:16:15.728376  1863 layer_factory.hpp:77] Creating layer relu4
I0405 13:16:15.728387  1863 net.cpp:84] Creating Layer relu4
I0405 13:16:15.728392  1863 net.cpp:406] relu4 <- conv4
I0405 13:16:15.728402  1863 net.cpp:367] relu4 -> conv4 (in-place)
I0405 13:16:15.728890  1863 net.cpp:122] Setting up relu4
I0405 13:16:15.728901  1863 net.cpp:129] Top shape: 32 384 13 13 (2076672)
I0405 13:16:15.728904  1863 net.cpp:137] Memory required for data: 250687232
I0405 13:16:15.728909  1863 layer_factory.hpp:77] Creating layer conv5
I0405 13:16:15.728924  1863 net.cpp:84] Creating Layer conv5
I0405 13:16:15.728929  1863 net.cpp:406] conv5 <- conv4
I0405 13:16:15.728940  1863 net.cpp:380] conv5 -> conv5
I0405 13:16:15.740880  1863 net.cpp:122] Setting up conv5
I0405 13:16:15.740913  1863 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 13:16:15.740917  1863 net.cpp:137] Memory required for data: 256225024
I0405 13:16:15.740936  1863 layer_factory.hpp:77] Creating layer relu5
I0405 13:16:15.740945  1863 net.cpp:84] Creating Layer relu5
I0405 13:16:15.740958  1863 net.cpp:406] relu5 <- conv5
I0405 13:16:15.740990  1863 net.cpp:367] relu5 -> conv5 (in-place)
I0405 13:16:15.741658  1863 net.cpp:122] Setting up relu5
I0405 13:16:15.741670  1863 net.cpp:129] Top shape: 32 256 13 13 (1384448)
I0405 13:16:15.741674  1863 net.cpp:137] Memory required for data: 261762816
I0405 13:16:15.741678  1863 layer_factory.hpp:77] Creating layer pool5
I0405 13:16:15.741690  1863 net.cpp:84] Creating Layer pool5
I0405 13:16:15.741694  1863 net.cpp:406] pool5 <- conv5
I0405 13:16:15.741700  1863 net.cpp:380] pool5 -> pool5
I0405 13:16:15.741748  1863 net.cpp:122] Setting up pool5
I0405 13:16:15.741755  1863 net.cpp:129] Top shape: 32 256 6 6 (294912)
I0405 13:16:15.741760  1863 net.cpp:137] Memory required for data: 262942464
I0405 13:16:15.741762  1863 layer_factory.hpp:77] Creating layer fc6
I0405 13:16:15.741772  1863 net.cpp:84] Creating Layer fc6
I0405 13:16:15.741775  1863 net.cpp:406] fc6 <- pool5
I0405 13:16:15.741781  1863 net.cpp:380] fc6 -> fc6
I0405 13:16:16.104166  1863 net.cpp:122] Setting up fc6
I0405 13:16:16.104187  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.104189  1863 net.cpp:137] Memory required for data: 263466752
I0405 13:16:16.104198  1863 layer_factory.hpp:77] Creating layer relu6
I0405 13:16:16.104207  1863 net.cpp:84] Creating Layer relu6
I0405 13:16:16.104210  1863 net.cpp:406] relu6 <- fc6
I0405 13:16:16.104215  1863 net.cpp:367] relu6 -> fc6 (in-place)
I0405 13:16:16.104897  1863 net.cpp:122] Setting up relu6
I0405 13:16:16.104907  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.104908  1863 net.cpp:137] Memory required for data: 263991040
I0405 13:16:16.104910  1863 layer_factory.hpp:77] Creating layer drop6
I0405 13:16:16.104918  1863 net.cpp:84] Creating Layer drop6
I0405 13:16:16.104919  1863 net.cpp:406] drop6 <- fc6
I0405 13:16:16.104923  1863 net.cpp:367] drop6 -> fc6 (in-place)
I0405 13:16:16.104946  1863 net.cpp:122] Setting up drop6
I0405 13:16:16.104950  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.104952  1863 net.cpp:137] Memory required for data: 264515328
I0405 13:16:16.104954  1863 layer_factory.hpp:77] Creating layer fc7
I0405 13:16:16.104959  1863 net.cpp:84] Creating Layer fc7
I0405 13:16:16.104961  1863 net.cpp:406] fc7 <- fc6
I0405 13:16:16.104966  1863 net.cpp:380] fc7 -> fc7
I0405 13:16:16.254206  1863 net.cpp:122] Setting up fc7
I0405 13:16:16.254228  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.254231  1863 net.cpp:137] Memory required for data: 265039616
I0405 13:16:16.254240  1863 layer_factory.hpp:77] Creating layer relu7
I0405 13:16:16.254246  1863 net.cpp:84] Creating Layer relu7
I0405 13:16:16.254251  1863 net.cpp:406] relu7 <- fc7
I0405 13:16:16.254256  1863 net.cpp:367] relu7 -> fc7 (in-place)
I0405 13:16:16.254663  1863 net.cpp:122] Setting up relu7
I0405 13:16:16.254673  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.254674  1863 net.cpp:137] Memory required for data: 265563904
I0405 13:16:16.254676  1863 layer_factory.hpp:77] Creating layer drop7
I0405 13:16:16.254681  1863 net.cpp:84] Creating Layer drop7
I0405 13:16:16.254683  1863 net.cpp:406] drop7 <- fc7
I0405 13:16:16.254688  1863 net.cpp:367] drop7 -> fc7 (in-place)
I0405 13:16:16.254709  1863 net.cpp:122] Setting up drop7
I0405 13:16:16.254714  1863 net.cpp:129] Top shape: 32 4096 (131072)
I0405 13:16:16.254714  1863 net.cpp:137] Memory required for data: 266088192
I0405 13:16:16.254717  1863 layer_factory.hpp:77] Creating layer fc8
I0405 13:16:16.254724  1863 net.cpp:84] Creating Layer fc8
I0405 13:16:16.254726  1863 net.cpp:406] fc8 <- fc7
I0405 13:16:16.254729  1863 net.cpp:380] fc8 -> fc8
I0405 13:16:16.261979  1863 net.cpp:122] Setting up fc8
I0405 13:16:16.261998  1863 net.cpp:129] Top shape: 32 196 (6272)
I0405 13:16:16.262001  1863 net.cpp:137] Memory required for data: 266113280
I0405 13:16:16.262007  1863 layer_factory.hpp:77] Creating layer fc8_fc8_0_split
I0405 13:16:16.262015  1863 net.cpp:84] Creating Layer fc8_fc8_0_split
I0405 13:16:16.262018  1863 net.cpp:406] fc8_fc8_0_split <- fc8
I0405 13:16:16.262045  1863 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0
I0405 13:16:16.262053  1863 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1
I0405 13:16:16.262086  1863 net.cpp:122] Setting up fc8_fc8_0_split
I0405 13:16:16.262090  1863 net.cpp:129] Top shape: 32 196 (6272)
I0405 13:16:16.262092  1863 net.cpp:129] Top shape: 32 196 (6272)
I0405 13:16:16.262094  1863 net.cpp:137] Memory required for data: 266163456
I0405 13:16:16.262096  1863 layer_factory.hpp:77] Creating layer accuracy
I0405 13:16:16.262102  1863 net.cpp:84] Creating Layer accuracy
I0405 13:16:16.262105  1863 net.cpp:406] accuracy <- fc8_fc8_0_split_0
I0405 13:16:16.262109  1863 net.cpp:406] accuracy <- label_val-data_1_split_0
I0405 13:16:16.262112  1863 net.cpp:380] accuracy -> accuracy
I0405 13:16:16.262117  1863 net.cpp:122] Setting up accuracy
I0405 13:16:16.262120  1863 net.cpp:129] Top shape: (1)
I0405 13:16:16.262122  1863 net.cpp:137] Memory required for data: 266163460
I0405 13:16:16.262125  1863 layer_factory.hpp:77] Creating layer loss
I0405 13:16:16.262128  1863 net.cpp:84] Creating Layer loss
I0405 13:16:16.262130  1863 net.cpp:406] loss <- fc8_fc8_0_split_1
I0405 13:16:16.262133  1863 net.cpp:406] loss <- label_val-data_1_split_1
I0405 13:16:16.262136  1863 net.cpp:380] loss -> loss
I0405 13:16:16.262143  1863 layer_factory.hpp:77] Creating layer loss
I0405 13:16:16.262837  1863 net.cpp:122] Setting up loss
I0405 13:16:16.262846  1863 net.cpp:129] Top shape: (1)
I0405 13:16:16.262848  1863 net.cpp:132]     with loss weight 1
I0405 13:16:16.262856  1863 net.cpp:137] Memory required for data: 266163464
I0405 13:16:16.262858  1863 net.cpp:198] loss needs backward computation.
I0405 13:16:16.262862  1863 net.cpp:200] accuracy does not need backward computation.
I0405 13:16:16.262866  1863 net.cpp:198] fc8_fc8_0_split needs backward computation.
I0405 13:16:16.262867  1863 net.cpp:198] fc8 needs backward computation.
I0405 13:16:16.262869  1863 net.cpp:198] drop7 needs backward computation.
I0405 13:16:16.262872  1863 net.cpp:198] relu7 needs backward computation.
I0405 13:16:16.262874  1863 net.cpp:198] fc7 needs backward computation.
I0405 13:16:16.262876  1863 net.cpp:198] drop6 needs backward computation.
I0405 13:16:16.262878  1863 net.cpp:198] relu6 needs backward computation.
I0405 13:16:16.262881  1863 net.cpp:198] fc6 needs backward computation.
I0405 13:16:16.262884  1863 net.cpp:198] pool5 needs backward computation.
I0405 13:16:16.262887  1863 net.cpp:198] relu5 needs backward computation.
I0405 13:16:16.262888  1863 net.cpp:198] conv5 needs backward computation.
I0405 13:16:16.262892  1863 net.cpp:198] relu4 needs backward computation.
I0405 13:16:16.262893  1863 net.cpp:198] conv4 needs backward computation.
I0405 13:16:16.262895  1863 net.cpp:198] relu3 needs backward computation.
I0405 13:16:16.262897  1863 net.cpp:198] conv3 needs backward computation.
I0405 13:16:16.262899  1863 net.cpp:198] pool2 needs backward computation.
I0405 13:16:16.262902  1863 net.cpp:198] norm2 needs backward computation.
I0405 13:16:16.262904  1863 net.cpp:198] relu2 needs backward computation.
I0405 13:16:16.262907  1863 net.cpp:198] conv2 needs backward computation.
I0405 13:16:16.262908  1863 net.cpp:198] pool1 needs backward computation.
I0405 13:16:16.262910  1863 net.cpp:198] norm1 needs backward computation.
I0405 13:16:16.262912  1863 net.cpp:198] relu1 needs backward computation.
I0405 13:16:16.262914  1863 net.cpp:198] conv1 needs backward computation.
I0405 13:16:16.262917  1863 net.cpp:200] label_val-data_1_split does not need backward computation.
I0405 13:16:16.262920  1863 net.cpp:200] val-data does not need backward computation.
I0405 13:16:16.262923  1863 net.cpp:242] This network produces output accuracy
I0405 13:16:16.262924  1863 net.cpp:242] This network produces output loss
I0405 13:16:16.262938  1863 net.cpp:255] Network initialization done.
I0405 13:16:16.263005  1863 solver.cpp:56] Solver scaffolding done.
I0405 13:16:16.263399  1863 caffe.cpp:248] Starting Optimization
I0405 13:16:16.263406  1863 solver.cpp:272] Solving
I0405 13:16:16.263419  1863 solver.cpp:273] Learning Rate Policy: fixed
I0405 13:16:16.264986  1863 solver.cpp:330] Iteration 0, Testing net (#0)
I0405 13:16:16.264995  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:16:16.365502  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:16:20.516546  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:16:20.565470  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00428922
I0405 13:16:20.565500  1863 solver.cpp:397]     Test net output #1: loss = 5.27977 (* 1 = 5.27977 loss)
I0405 13:16:20.710703  1863 solver.cpp:218] Iteration 0 (-4.50245e-08 iter/s, 4.44723s/12 iters), loss = 5.28111
I0405 13:16:20.712319  1863 solver.cpp:237]     Train net output #0: loss = 5.28111 (* 1 = 5.28111 loss)
I0405 13:16:20.712332  1863 sgd_solver.cpp:105] Iteration 0, lr = 0.001
I0405 13:16:24.852725  1863 solver.cpp:218] Iteration 12 (2.89828 iter/s, 4.14039s/12 iters), loss = 5.28454
I0405 13:16:24.852766  1863 solver.cpp:237]     Train net output #0: loss = 5.28454 (* 1 = 5.28454 loss)
I0405 13:16:24.852771  1863 sgd_solver.cpp:105] Iteration 12, lr = 0.001
I0405 13:16:29.887854  1863 solver.cpp:218] Iteration 24 (2.38328 iter/s, 5.03508s/12 iters), loss = 5.29321
I0405 13:16:29.887897  1863 solver.cpp:237]     Train net output #0: loss = 5.29321 (* 1 = 5.29321 loss)
I0405 13:16:29.887903  1863 sgd_solver.cpp:105] Iteration 24, lr = 0.001
I0405 13:16:35.022188  1863 solver.cpp:218] Iteration 36 (2.33723 iter/s, 5.13428s/12 iters), loss = 5.29654
I0405 13:16:35.022228  1863 solver.cpp:237]     Train net output #0: loss = 5.29654 (* 1 = 5.29654 loss)
I0405 13:16:35.022234  1863 sgd_solver.cpp:105] Iteration 36, lr = 0.001
I0405 13:16:40.141526  1863 solver.cpp:218] Iteration 48 (2.34408 iter/s, 5.11929s/12 iters), loss = 5.30003
I0405 13:16:40.141571  1863 solver.cpp:237]     Train net output #0: loss = 5.30003 (* 1 = 5.30003 loss)
I0405 13:16:40.141577  1863 sgd_solver.cpp:105] Iteration 48, lr = 0.001
I0405 13:16:45.411485  1863 solver.cpp:218] Iteration 60 (2.27708 iter/s, 5.2699s/12 iters), loss = 5.28926
I0405 13:16:45.411629  1863 solver.cpp:237]     Train net output #0: loss = 5.28926 (* 1 = 5.28926 loss)
I0405 13:16:45.411638  1863 sgd_solver.cpp:105] Iteration 60, lr = 0.001
I0405 13:16:50.595137  1863 solver.cpp:218] Iteration 72 (2.31504 iter/s, 5.1835s/12 iters), loss = 5.29525
I0405 13:16:50.595177  1863 solver.cpp:237]     Train net output #0: loss = 5.29525 (* 1 = 5.29525 loss)
I0405 13:16:50.595183  1863 sgd_solver.cpp:105] Iteration 72, lr = 0.001
I0405 13:16:55.766696  1863 solver.cpp:218] Iteration 84 (2.32041 iter/s, 5.1715s/12 iters), loss = 5.28636
I0405 13:16:55.766741  1863 solver.cpp:237]     Train net output #0: loss = 5.28636 (* 1 = 5.28636 loss)
I0405 13:16:55.766747  1863 sgd_solver.cpp:105] Iteration 84, lr = 0.001
I0405 13:17:01.023928  1863 solver.cpp:218] Iteration 96 (2.2826 iter/s, 5.25717s/12 iters), loss = 5.27594
I0405 13:17:01.023975  1863 solver.cpp:237]     Train net output #0: loss = 5.27594 (* 1 = 5.27594 loss)
I0405 13:17:01.023983  1863 sgd_solver.cpp:105] Iteration 96, lr = 0.001
I0405 13:17:02.819327  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:03.122097  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel
I0405 13:17:06.256019  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate
I0405 13:17:08.562599  1863 solver.cpp:330] Iteration 102, Testing net (#0)
I0405 13:17:08.562626  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:17:12.942632  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:13.021157  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:17:13.021193  1863 solver.cpp:397]     Test net output #1: loss = 5.28018 (* 1 = 5.28018 loss)
I0405 13:17:14.828670  1863 solver.cpp:218] Iteration 108 (0.86927 iter/s, 13.8047s/12 iters), loss = 5.30729
I0405 13:17:14.828709  1863 solver.cpp:237]     Train net output #0: loss = 5.30729 (* 1 = 5.30729 loss)
I0405 13:17:14.828716  1863 sgd_solver.cpp:105] Iteration 108, lr = 0.001
I0405 13:17:19.678898  1863 solver.cpp:218] Iteration 120 (2.47414 iter/s, 4.85017s/12 iters), loss = 5.27993
I0405 13:17:19.679031  1863 solver.cpp:237]     Train net output #0: loss = 5.27993 (* 1 = 5.27993 loss)
I0405 13:17:19.679039  1863 sgd_solver.cpp:105] Iteration 120, lr = 0.001
I0405 13:17:25.048267  1863 solver.cpp:218] Iteration 132 (2.23496 iter/s, 5.36923s/12 iters), loss = 5.28223
I0405 13:17:25.048307  1863 solver.cpp:237]     Train net output #0: loss = 5.28223 (* 1 = 5.28223 loss)
I0405 13:17:25.048311  1863 sgd_solver.cpp:105] Iteration 132, lr = 0.001
I0405 13:17:30.080709  1863 solver.cpp:218] Iteration 144 (2.38455 iter/s, 5.03239s/12 iters), loss = 5.26468
I0405 13:17:30.080749  1863 solver.cpp:237]     Train net output #0: loss = 5.26468 (* 1 = 5.26468 loss)
I0405 13:17:30.080754  1863 sgd_solver.cpp:105] Iteration 144, lr = 0.001
I0405 13:17:35.128609  1863 solver.cpp:218] Iteration 156 (2.37725 iter/s, 5.04785s/12 iters), loss = 5.28327
I0405 13:17:35.128664  1863 solver.cpp:237]     Train net output #0: loss = 5.28327 (* 1 = 5.28327 loss)
I0405 13:17:35.128672  1863 sgd_solver.cpp:105] Iteration 156, lr = 0.001
I0405 13:17:40.198236  1863 solver.cpp:218] Iteration 168 (2.36707 iter/s, 5.06956s/12 iters), loss = 5.26408
I0405 13:17:40.198285  1863 solver.cpp:237]     Train net output #0: loss = 5.26408 (* 1 = 5.26408 loss)
I0405 13:17:40.198293  1863 sgd_solver.cpp:105] Iteration 168, lr = 0.001
I0405 13:17:45.308259  1863 solver.cpp:218] Iteration 180 (2.34835 iter/s, 5.10996s/12 iters), loss = 5.28411
I0405 13:17:45.308315  1863 solver.cpp:237]     Train net output #0: loss = 5.28411 (* 1 = 5.28411 loss)
I0405 13:17:45.308322  1863 sgd_solver.cpp:105] Iteration 180, lr = 0.001
I0405 13:17:50.537760  1863 solver.cpp:218] Iteration 192 (2.2947 iter/s, 5.22943s/12 iters), loss = 5.2662
I0405 13:17:50.537909  1863 solver.cpp:237]     Train net output #0: loss = 5.2662 (* 1 = 5.2662 loss)
I0405 13:17:50.537917  1863 sgd_solver.cpp:105] Iteration 192, lr = 0.001
I0405 13:17:54.571765  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:17:55.269657  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel
I0405 13:17:58.380859  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate
I0405 13:18:00.683876  1863 solver.cpp:330] Iteration 204, Testing net (#0)
I0405 13:18:00.683895  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:18:04.910212  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:18:05.036077  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:18:05.036118  1863 solver.cpp:397]     Test net output #1: loss = 5.28188 (* 1 = 5.28188 loss)
I0405 13:18:05.178109  1863 solver.cpp:218] Iteration 204 (0.819661 iter/s, 14.6402s/12 iters), loss = 5.276
I0405 13:18:05.178161  1863 solver.cpp:237]     Train net output #0: loss = 5.276 (* 1 = 5.276 loss)
I0405 13:18:05.178169  1863 sgd_solver.cpp:105] Iteration 204, lr = 0.001
I0405 13:18:09.552067  1863 solver.cpp:218] Iteration 216 (2.74355 iter/s, 4.37389s/12 iters), loss = 5.27228
I0405 13:18:09.552119  1863 solver.cpp:237]     Train net output #0: loss = 5.27228 (* 1 = 5.27228 loss)
I0405 13:18:09.552127  1863 sgd_solver.cpp:105] Iteration 216, lr = 0.001
I0405 13:18:14.737645  1863 solver.cpp:218] Iteration 228 (2.31414 iter/s, 5.18552s/12 iters), loss = 5.27928
I0405 13:18:14.737687  1863 solver.cpp:237]     Train net output #0: loss = 5.27928 (* 1 = 5.27928 loss)
I0405 13:18:14.737694  1863 sgd_solver.cpp:105] Iteration 228, lr = 0.001
I0405 13:18:19.989235  1863 solver.cpp:218] Iteration 240 (2.28505 iter/s, 5.25153s/12 iters), loss = 5.26905
I0405 13:18:19.989282  1863 solver.cpp:237]     Train net output #0: loss = 5.26905 (* 1 = 5.26905 loss)
I0405 13:18:19.989289  1863 sgd_solver.cpp:105] Iteration 240, lr = 0.001
I0405 13:18:25.157946  1863 solver.cpp:218] Iteration 252 (2.32169 iter/s, 5.16866s/12 iters), loss = 5.26832
I0405 13:18:25.158095  1863 solver.cpp:237]     Train net output #0: loss = 5.26832 (* 1 = 5.26832 loss)
I0405 13:18:25.158102  1863 sgd_solver.cpp:105] Iteration 252, lr = 0.001
I0405 13:18:30.215250  1863 solver.cpp:218] Iteration 264 (2.37288 iter/s, 5.05715s/12 iters), loss = 5.27643
I0405 13:18:30.215291  1863 solver.cpp:237]     Train net output #0: loss = 5.27643 (* 1 = 5.27643 loss)
I0405 13:18:30.215296  1863 sgd_solver.cpp:105] Iteration 264, lr = 0.001
I0405 13:18:35.600200  1863 solver.cpp:218] Iteration 276 (2.22846 iter/s, 5.38489s/12 iters), loss = 5.28131
I0405 13:18:35.600260  1863 solver.cpp:237]     Train net output #0: loss = 5.28131 (* 1 = 5.28131 loss)
I0405 13:18:35.600268  1863 sgd_solver.cpp:105] Iteration 276, lr = 0.001
I0405 13:18:40.832836  1863 solver.cpp:218] Iteration 288 (2.29333 iter/s, 5.23257s/12 iters), loss = 5.26526
I0405 13:18:40.832875  1863 solver.cpp:237]     Train net output #0: loss = 5.26526 (* 1 = 5.26526 loss)
I0405 13:18:40.832880  1863 sgd_solver.cpp:105] Iteration 288, lr = 0.001
I0405 13:18:46.071071  1863 solver.cpp:218] Iteration 300 (2.29087 iter/s, 5.23818s/12 iters), loss = 5.2749
I0405 13:18:46.071115  1863 solver.cpp:237]     Train net output #0: loss = 5.2749 (* 1 = 5.2749 loss)
I0405 13:18:46.071120  1863 sgd_solver.cpp:105] Iteration 300, lr = 0.001
I0405 13:18:47.147914  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:18:48.244846  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel
I0405 13:18:51.232956  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate
I0405 13:18:53.556994  1863 solver.cpp:330] Iteration 306, Testing net (#0)
I0405 13:18:53.557027  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:18:57.738812  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:18:57.895625  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:18:57.895660  1863 solver.cpp:397]     Test net output #1: loss = 5.2826 (* 1 = 5.2826 loss)
I0405 13:18:59.790370  1863 solver.cpp:218] Iteration 312 (0.874683 iter/s, 13.7193s/12 iters), loss = 5.28882
I0405 13:18:59.790422  1863 solver.cpp:237]     Train net output #0: loss = 5.28882 (* 1 = 5.28882 loss)
I0405 13:18:59.790431  1863 sgd_solver.cpp:105] Iteration 312, lr = 0.001
I0405 13:19:04.883625  1863 solver.cpp:218] Iteration 324 (2.35608 iter/s, 5.0932s/12 iters), loss = 5.28173
I0405 13:19:04.883669  1863 solver.cpp:237]     Train net output #0: loss = 5.28173 (* 1 = 5.28173 loss)
I0405 13:19:04.883675  1863 sgd_solver.cpp:105] Iteration 324, lr = 0.001
I0405 13:19:09.844297  1863 solver.cpp:218] Iteration 336 (2.41906 iter/s, 4.96061s/12 iters), loss = 5.27286
I0405 13:19:09.844347  1863 solver.cpp:237]     Train net output #0: loss = 5.27286 (* 1 = 5.27286 loss)
I0405 13:19:09.844354  1863 sgd_solver.cpp:105] Iteration 336, lr = 0.001
I0405 13:19:15.170481  1863 solver.cpp:218] Iteration 348 (2.25304 iter/s, 5.32613s/12 iters), loss = 5.26868
I0405 13:19:15.170527  1863 solver.cpp:237]     Train net output #0: loss = 5.26868 (* 1 = 5.26868 loss)
I0405 13:19:15.170533  1863 sgd_solver.cpp:105] Iteration 348, lr = 0.001
I0405 13:19:20.489764  1863 solver.cpp:218] Iteration 360 (2.25597 iter/s, 5.31922s/12 iters), loss = 5.29531
I0405 13:19:20.489820  1863 solver.cpp:237]     Train net output #0: loss = 5.29531 (* 1 = 5.29531 loss)
I0405 13:19:20.489827  1863 sgd_solver.cpp:105] Iteration 360, lr = 0.001
I0405 13:19:25.687646  1863 solver.cpp:218] Iteration 372 (2.30866 iter/s, 5.19782s/12 iters), loss = 5.26358
I0405 13:19:25.687685  1863 solver.cpp:237]     Train net output #0: loss = 5.26358 (* 1 = 5.26358 loss)
I0405 13:19:25.687691  1863 sgd_solver.cpp:105] Iteration 372, lr = 0.001
I0405 13:19:30.832310  1863 solver.cpp:218] Iteration 384 (2.33254 iter/s, 5.14462s/12 iters), loss = 5.27761
I0405 13:19:30.832437  1863 solver.cpp:237]     Train net output #0: loss = 5.27761 (* 1 = 5.27761 loss)
I0405 13:19:30.832444  1863 sgd_solver.cpp:105] Iteration 384, lr = 0.001
I0405 13:19:35.940268  1863 solver.cpp:218] Iteration 396 (2.34934 iter/s, 5.10782s/12 iters), loss = 5.29355
I0405 13:19:35.940310  1863 solver.cpp:237]     Train net output #0: loss = 5.29355 (* 1 = 5.29355 loss)
I0405 13:19:35.940316  1863 sgd_solver.cpp:105] Iteration 396, lr = 0.001
I0405 13:19:39.225967  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:19:40.675179  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel
I0405 13:19:43.735164  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate
I0405 13:19:46.043532  1863 solver.cpp:330] Iteration 408, Testing net (#0)
I0405 13:19:46.043553  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:19:50.332043  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:19:50.539343  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:19:50.539384  1863 solver.cpp:397]     Test net output #1: loss = 5.28242 (* 1 = 5.28242 loss)
I0405 13:19:50.674896  1863 solver.cpp:218] Iteration 408 (0.814411 iter/s, 14.7346s/12 iters), loss = 5.25339
I0405 13:19:50.676450  1863 solver.cpp:237]     Train net output #0: loss = 5.25339 (* 1 = 5.25339 loss)
I0405 13:19:50.676461  1863 sgd_solver.cpp:105] Iteration 408, lr = 0.001
I0405 13:19:54.897794  1863 solver.cpp:218] Iteration 420 (2.8427 iter/s, 4.22134s/12 iters), loss = 5.26429
I0405 13:19:54.897832  1863 solver.cpp:237]     Train net output #0: loss = 5.26429 (* 1 = 5.26429 loss)
I0405 13:19:54.897838  1863 sgd_solver.cpp:105] Iteration 420, lr = 0.001
I0405 13:19:59.967988  1863 solver.cpp:218] Iteration 432 (2.3668 iter/s, 5.07013s/12 iters), loss = 5.28635
I0405 13:19:59.974315  1863 solver.cpp:237]     Train net output #0: loss = 5.28635 (* 1 = 5.28635 loss)
I0405 13:19:59.974336  1863 sgd_solver.cpp:105] Iteration 432, lr = 0.001
I0405 13:20:05.151921  1863 solver.cpp:218] Iteration 444 (2.31767 iter/s, 5.17762s/12 iters), loss = 5.27888
I0405 13:20:05.152036  1863 solver.cpp:237]     Train net output #0: loss = 5.27888 (* 1 = 5.27888 loss)
I0405 13:20:05.152045  1863 sgd_solver.cpp:105] Iteration 444, lr = 0.001
I0405 13:20:10.169224  1863 solver.cpp:218] Iteration 456 (2.39178 iter/s, 5.01718s/12 iters), loss = 5.29067
I0405 13:20:10.169270  1863 solver.cpp:237]     Train net output #0: loss = 5.29067 (* 1 = 5.29067 loss)
I0405 13:20:10.169278  1863 sgd_solver.cpp:105] Iteration 456, lr = 0.001
I0405 13:20:15.434420  1863 solver.cpp:218] Iteration 468 (2.27914 iter/s, 5.26514s/12 iters), loss = 5.26559
I0405 13:20:15.434459  1863 solver.cpp:237]     Train net output #0: loss = 5.26559 (* 1 = 5.26559 loss)
I0405 13:20:15.434464  1863 sgd_solver.cpp:105] Iteration 468, lr = 0.001
I0405 13:20:20.616400  1863 solver.cpp:218] Iteration 480 (2.31574 iter/s, 5.18192s/12 iters), loss = 5.26018
I0405 13:20:20.616444  1863 solver.cpp:237]     Train net output #0: loss = 5.26018 (* 1 = 5.26018 loss)
I0405 13:20:20.616451  1863 sgd_solver.cpp:105] Iteration 480, lr = 0.001
I0405 13:20:26.013554  1863 solver.cpp:218] Iteration 492 (2.22342 iter/s, 5.3971s/12 iters), loss = 5.27021
I0405 13:20:26.013607  1863 solver.cpp:237]     Train net output #0: loss = 5.27021 (* 1 = 5.27021 loss)
I0405 13:20:26.013615  1863 sgd_solver.cpp:105] Iteration 492, lr = 0.001
I0405 13:20:31.374089  1863 solver.cpp:218] Iteration 504 (2.23861 iter/s, 5.36047s/12 iters), loss = 5.28774
I0405 13:20:31.374145  1863 solver.cpp:237]     Train net output #0: loss = 5.28774 (* 1 = 5.28774 loss)
I0405 13:20:31.374153  1863 sgd_solver.cpp:105] Iteration 504, lr = 0.001
I0405 13:20:31.605522  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:20:33.428428  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel
I0405 13:20:36.791141  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate
I0405 13:20:39.100378  1863 solver.cpp:330] Iteration 510, Testing net (#0)
I0405 13:20:39.100404  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:20:43.255709  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:20:43.494074  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:20:43.494108  1863 solver.cpp:397]     Test net output #1: loss = 5.2809 (* 1 = 5.2809 loss)
I0405 13:20:45.399307  1863 solver.cpp:218] Iteration 516 (0.855605 iter/s, 14.0252s/12 iters), loss = 5.27414
I0405 13:20:45.399348  1863 solver.cpp:237]     Train net output #0: loss = 5.27414 (* 1 = 5.27414 loss)
I0405 13:20:45.399353  1863 sgd_solver.cpp:105] Iteration 516, lr = 0.001
I0405 13:20:50.492122  1863 solver.cpp:218] Iteration 528 (2.35628 iter/s, 5.09276s/12 iters), loss = 5.30851
I0405 13:20:50.492172  1863 solver.cpp:237]     Train net output #0: loss = 5.30851 (* 1 = 5.30851 loss)
I0405 13:20:50.492180  1863 sgd_solver.cpp:105] Iteration 528, lr = 0.001
I0405 13:20:55.781299  1863 solver.cpp:218] Iteration 540 (2.26881 iter/s, 5.28912s/12 iters), loss = 5.26
I0405 13:20:55.781342  1863 solver.cpp:237]     Train net output #0: loss = 5.26 (* 1 = 5.26 loss)
I0405 13:20:55.781350  1863 sgd_solver.cpp:105] Iteration 540, lr = 0.001
I0405 13:21:01.046241  1863 solver.cpp:218] Iteration 552 (2.27926 iter/s, 5.26487s/12 iters), loss = 5.26576
I0405 13:21:01.046295  1863 solver.cpp:237]     Train net output #0: loss = 5.26576 (* 1 = 5.26576 loss)
I0405 13:21:01.046303  1863 sgd_solver.cpp:105] Iteration 552, lr = 0.001
I0405 13:21:06.367627  1863 solver.cpp:218] Iteration 564 (2.25508 iter/s, 5.32132s/12 iters), loss = 5.26306
I0405 13:21:06.367666  1863 solver.cpp:237]     Train net output #0: loss = 5.26306 (* 1 = 5.26306 loss)
I0405 13:21:06.367672  1863 sgd_solver.cpp:105] Iteration 564, lr = 0.001
I0405 13:21:11.589661  1863 solver.cpp:218] Iteration 576 (2.29798 iter/s, 5.22198s/12 iters), loss = 5.25087
I0405 13:21:11.589792  1863 solver.cpp:237]     Train net output #0: loss = 5.25087 (* 1 = 5.25087 loss)
I0405 13:21:11.589800  1863 sgd_solver.cpp:105] Iteration 576, lr = 0.001
I0405 13:21:16.700577  1863 solver.cpp:218] Iteration 588 (2.34798 iter/s, 5.11078s/12 iters), loss = 5.2703
I0405 13:21:16.700618  1863 solver.cpp:237]     Train net output #0: loss = 5.2703 (* 1 = 5.2703 loss)
I0405 13:21:16.700623  1863 sgd_solver.cpp:105] Iteration 588, lr = 0.001
I0405 13:21:22.137805  1863 solver.cpp:218] Iteration 600 (2.20703 iter/s, 5.43718s/12 iters), loss = 5.25965
I0405 13:21:22.137850  1863 solver.cpp:237]     Train net output #0: loss = 5.25965 (* 1 = 5.25965 loss)
I0405 13:21:22.137856  1863 sgd_solver.cpp:105] Iteration 600, lr = 0.001
I0405 13:21:24.622674  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:21:26.934635  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel
I0405 13:21:30.059358  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate
I0405 13:21:32.363155  1863 solver.cpp:330] Iteration 612, Testing net (#0)
I0405 13:21:32.363180  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:21:36.538987  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:21:36.843668  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00551471
I0405 13:21:36.843699  1863 solver.cpp:397]     Test net output #1: loss = 5.27616 (* 1 = 5.27616 loss)
I0405 13:21:36.985646  1863 solver.cpp:218] Iteration 612 (0.808201 iter/s, 14.8478s/12 iters), loss = 5.26381
I0405 13:21:36.985684  1863 solver.cpp:237]     Train net output #0: loss = 5.26381 (* 1 = 5.26381 loss)
I0405 13:21:36.985689  1863 sgd_solver.cpp:105] Iteration 612, lr = 0.001
I0405 13:21:41.216382  1863 solver.cpp:218] Iteration 624 (2.83642 iter/s, 4.23068s/12 iters), loss = 5.25831
I0405 13:21:41.216425  1863 solver.cpp:237]     Train net output #0: loss = 5.25831 (* 1 = 5.25831 loss)
I0405 13:21:41.216431  1863 sgd_solver.cpp:105] Iteration 624, lr = 0.001
I0405 13:21:46.339104  1863 solver.cpp:218] Iteration 636 (2.34253 iter/s, 5.12267s/12 iters), loss = 5.25917
I0405 13:21:46.339247  1863 solver.cpp:237]     Train net output #0: loss = 5.25917 (* 1 = 5.25917 loss)
I0405 13:21:46.339254  1863 sgd_solver.cpp:105] Iteration 636, lr = 0.001
I0405 13:21:51.500679  1863 solver.cpp:218] Iteration 648 (2.32494 iter/s, 5.16142s/12 iters), loss = 5.24945
I0405 13:21:51.500725  1863 solver.cpp:237]     Train net output #0: loss = 5.24945 (* 1 = 5.24945 loss)
I0405 13:21:51.500730  1863 sgd_solver.cpp:105] Iteration 648, lr = 0.001
I0405 13:21:56.720000  1863 solver.cpp:218] Iteration 660 (2.29917 iter/s, 5.21927s/12 iters), loss = 5.25905
I0405 13:21:56.720039  1863 solver.cpp:237]     Train net output #0: loss = 5.25905 (* 1 = 5.25905 loss)
I0405 13:21:56.720046  1863 sgd_solver.cpp:105] Iteration 660, lr = 0.001
I0405 13:22:01.690656  1863 solver.cpp:218] Iteration 672 (2.41419 iter/s, 4.97061s/12 iters), loss = 5.28526
I0405 13:22:01.690696  1863 solver.cpp:237]     Train net output #0: loss = 5.28526 (* 1 = 5.28526 loss)
I0405 13:22:01.690702  1863 sgd_solver.cpp:105] Iteration 672, lr = 0.001
I0405 13:22:06.752115  1863 solver.cpp:218] Iteration 684 (2.37088 iter/s, 5.06141s/12 iters), loss = 5.2509
I0405 13:22:06.752158  1863 solver.cpp:237]     Train net output #0: loss = 5.2509 (* 1 = 5.2509 loss)
I0405 13:22:06.752164  1863 sgd_solver.cpp:105] Iteration 684, lr = 0.001
I0405 13:22:07.561920  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:22:11.853397  1863 solver.cpp:218] Iteration 696 (2.35238 iter/s, 5.10122s/12 iters), loss = 5.26623
I0405 13:22:11.853451  1863 solver.cpp:237]     Train net output #0: loss = 5.26623 (* 1 = 5.26623 loss)
I0405 13:22:11.853461  1863 sgd_solver.cpp:105] Iteration 696, lr = 0.001
I0405 13:22:16.509043  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:22:16.932516  1863 solver.cpp:218] Iteration 708 (2.36264 iter/s, 5.07906s/12 iters), loss = 5.28327
I0405 13:22:16.932552  1863 solver.cpp:237]     Train net output #0: loss = 5.28327 (* 1 = 5.28327 loss)
I0405 13:22:16.932559  1863 sgd_solver.cpp:105] Iteration 708, lr = 0.001
I0405 13:22:19.125032  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel
I0405 13:22:23.429653  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate
I0405 13:22:25.744951  1863 solver.cpp:330] Iteration 714, Testing net (#0)
I0405 13:22:25.744973  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:22:29.912303  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:22:30.240372  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00612745
I0405 13:22:30.240398  1863 solver.cpp:397]     Test net output #1: loss = 5.26463 (* 1 = 5.26463 loss)
I0405 13:22:32.079460  1863 solver.cpp:218] Iteration 720 (0.792241 iter/s, 15.1469s/12 iters), loss = 5.22618
I0405 13:22:32.079504  1863 solver.cpp:237]     Train net output #0: loss = 5.22618 (* 1 = 5.22618 loss)
I0405 13:22:32.079510  1863 sgd_solver.cpp:105] Iteration 720, lr = 0.001
I0405 13:22:37.163822  1863 solver.cpp:218] Iteration 732 (2.36021 iter/s, 5.0843s/12 iters), loss = 5.25149
I0405 13:22:37.163873  1863 solver.cpp:237]     Train net output #0: loss = 5.25149 (* 1 = 5.25149 loss)
I0405 13:22:37.163882  1863 sgd_solver.cpp:105] Iteration 732, lr = 0.001
I0405 13:22:42.521910  1863 solver.cpp:218] Iteration 744 (2.23963 iter/s, 5.35803s/12 iters), loss = 5.25921
I0405 13:22:42.521960  1863 solver.cpp:237]     Train net output #0: loss = 5.25921 (* 1 = 5.25921 loss)
I0405 13:22:42.521967  1863 sgd_solver.cpp:105] Iteration 744, lr = 0.001
I0405 13:22:47.867897  1863 solver.cpp:218] Iteration 756 (2.2447 iter/s, 5.34592s/12 iters), loss = 5.24315
I0405 13:22:47.868177  1863 solver.cpp:237]     Train net output #0: loss = 5.24315 (* 1 = 5.24315 loss)
I0405 13:22:47.868186  1863 sgd_solver.cpp:105] Iteration 756, lr = 0.001
I0405 13:22:53.232038  1863 solver.cpp:218] Iteration 768 (2.2372 iter/s, 5.36385s/12 iters), loss = 5.24769
I0405 13:22:53.232087  1863 solver.cpp:237]     Train net output #0: loss = 5.24769 (* 1 = 5.24769 loss)
I0405 13:22:53.232093  1863 sgd_solver.cpp:105] Iteration 768, lr = 0.001
I0405 13:22:58.445200  1863 solver.cpp:218] Iteration 780 (2.30189 iter/s, 5.2131s/12 iters), loss = 5.23806
I0405 13:22:58.445240  1863 solver.cpp:237]     Train net output #0: loss = 5.23806 (* 1 = 5.23806 loss)
I0405 13:22:58.445245  1863 sgd_solver.cpp:105] Iteration 780, lr = 0.001
I0405 13:23:03.790828  1863 solver.cpp:218] Iteration 792 (2.24485 iter/s, 5.34558s/12 iters), loss = 5.24582
I0405 13:23:03.790869  1863 solver.cpp:237]     Train net output #0: loss = 5.24582 (* 1 = 5.24582 loss)
I0405 13:23:03.790875  1863 sgd_solver.cpp:105] Iteration 792, lr = 0.001
I0405 13:23:09.234642  1863 solver.cpp:218] Iteration 804 (2.20436 iter/s, 5.44376s/12 iters), loss = 5.22173
I0405 13:23:09.234681  1863 solver.cpp:237]     Train net output #0: loss = 5.22173 (* 1 = 5.22173 loss)
I0405 13:23:09.234686  1863 sgd_solver.cpp:105] Iteration 804, lr = 0.001
I0405 13:23:11.030210  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:23:14.026393  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel
I0405 13:23:17.709316  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate
I0405 13:23:20.274380  1863 solver.cpp:330] Iteration 816, Testing net (#0)
I0405 13:23:20.274502  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:23:24.552826  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:23:24.899471  1863 solver.cpp:397]     Test net output #0: accuracy = 0.00796569
I0405 13:23:24.899503  1863 solver.cpp:397]     Test net output #1: loss = 5.22583 (* 1 = 5.22583 loss)
I0405 13:23:25.041237  1863 solver.cpp:218] Iteration 816 (0.759179 iter/s, 15.8066s/12 iters), loss = 5.25483
I0405 13:23:25.041290  1863 solver.cpp:237]     Train net output #0: loss = 5.25483 (* 1 = 5.25483 loss)
I0405 13:23:25.041298  1863 sgd_solver.cpp:105] Iteration 816, lr = 0.001
I0405 13:23:29.445173  1863 solver.cpp:218] Iteration 828 (2.72488 iter/s, 4.40387s/12 iters), loss = 5.16958
I0405 13:23:29.445235  1863 solver.cpp:237]     Train net output #0: loss = 5.16958 (* 1 = 5.16958 loss)
I0405 13:23:29.445245  1863 sgd_solver.cpp:105] Iteration 828, lr = 0.001
I0405 13:23:34.531978  1863 solver.cpp:218] Iteration 840 (2.35908 iter/s, 5.08673s/12 iters), loss = 5.17633
I0405 13:23:34.532021  1863 solver.cpp:237]     Train net output #0: loss = 5.17633 (* 1 = 5.17633 loss)
I0405 13:23:34.532025  1863 sgd_solver.cpp:105] Iteration 840, lr = 0.001
I0405 13:23:39.936857  1863 solver.cpp:218] Iteration 852 (2.22024 iter/s, 5.40482s/12 iters), loss = 5.19723
I0405 13:23:39.936911  1863 solver.cpp:237]     Train net output #0: loss = 5.19723 (* 1 = 5.19723 loss)
I0405 13:23:39.936919  1863 sgd_solver.cpp:105] Iteration 852, lr = 0.001
I0405 13:23:45.381634  1863 solver.cpp:218] Iteration 864 (2.20397 iter/s, 5.44472s/12 iters), loss = 5.15805
I0405 13:23:45.381672  1863 solver.cpp:237]     Train net output #0: loss = 5.15805 (* 1 = 5.15805 loss)
I0405 13:23:45.381678  1863 sgd_solver.cpp:105] Iteration 864, lr = 0.001
I0405 13:23:50.649458  1863 solver.cpp:218] Iteration 876 (2.278 iter/s, 5.26777s/12 iters), loss = 5.20261
I0405 13:23:50.649567  1863 solver.cpp:237]     Train net output #0: loss = 5.20261 (* 1 = 5.20261 loss)
I0405 13:23:50.649574  1863 sgd_solver.cpp:105] Iteration 876, lr = 0.001
I0405 13:23:55.983937  1863 solver.cpp:218] Iteration 888 (2.24957 iter/s, 5.33436s/12 iters), loss = 5.2379
I0405 13:23:55.983987  1863 solver.cpp:237]     Train net output #0: loss = 5.2379 (* 1 = 5.2379 loss)
I0405 13:23:55.983994  1863 sgd_solver.cpp:105] Iteration 888, lr = 0.001
I0405 13:24:01.120191  1863 solver.cpp:218] Iteration 900 (2.33636 iter/s, 5.13619s/12 iters), loss = 5.11192
I0405 13:24:01.120236  1863 solver.cpp:237]     Train net output #0: loss = 5.11192 (* 1 = 5.11192 loss)
I0405 13:24:01.120244  1863 sgd_solver.cpp:105] Iteration 900, lr = 0.001
I0405 13:24:05.288663  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:24:06.511914  1863 solver.cpp:218] Iteration 912 (2.22566 iter/s, 5.39166s/12 iters), loss = 5.16029
I0405 13:24:06.511960  1863 solver.cpp:237]     Train net output #0: loss = 5.16029 (* 1 = 5.16029 loss)
I0405 13:24:06.511965  1863 sgd_solver.cpp:105] Iteration 912, lr = 0.001
I0405 13:24:08.701151  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel
I0405 13:24:11.734514  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate
I0405 13:24:14.772187  1863 solver.cpp:330] Iteration 918, Testing net (#0)
I0405 13:24:14.772212  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:24:18.735204  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:24:19.128283  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0128676
I0405 13:24:19.128320  1863 solver.cpp:397]     Test net output #1: loss = 5.15498 (* 1 = 5.15498 loss)
I0405 13:24:21.112990  1863 solver.cpp:218] Iteration 924 (0.82186 iter/s, 14.601s/12 iters), loss = 5.17872
I0405 13:24:21.113121  1863 solver.cpp:237]     Train net output #0: loss = 5.17872 (* 1 = 5.17872 loss)
I0405 13:24:21.113127  1863 sgd_solver.cpp:105] Iteration 924, lr = 0.001
I0405 13:24:26.261831  1863 solver.cpp:218] Iteration 936 (2.33069 iter/s, 5.1487s/12 iters), loss = 5.17896
I0405 13:24:26.261873  1863 solver.cpp:237]     Train net output #0: loss = 5.17896 (* 1 = 5.17896 loss)
I0405 13:24:26.261878  1863 sgd_solver.cpp:105] Iteration 936, lr = 0.001
I0405 13:24:31.332969  1863 solver.cpp:218] Iteration 948 (2.36636 iter/s, 5.07107s/12 iters), loss = 5.11213
I0405 13:24:31.333024  1863 solver.cpp:237]     Train net output #0: loss = 5.11213 (* 1 = 5.11213 loss)
I0405 13:24:31.333032  1863 sgd_solver.cpp:105] Iteration 948, lr = 0.001
I0405 13:24:36.484071  1863 solver.cpp:218] Iteration 960 (2.32963 iter/s, 5.15103s/12 iters), loss = 5.24019
I0405 13:24:36.484124  1863 solver.cpp:237]     Train net output #0: loss = 5.24019 (* 1 = 5.24019 loss)
I0405 13:24:36.484133  1863 sgd_solver.cpp:105] Iteration 960, lr = 0.001
I0405 13:24:41.678931  1863 solver.cpp:218] Iteration 972 (2.31 iter/s, 5.1948s/12 iters), loss = 5.04745
I0405 13:24:41.678975  1863 solver.cpp:237]     Train net output #0: loss = 5.04745 (* 1 = 5.04745 loss)
I0405 13:24:41.678982  1863 sgd_solver.cpp:105] Iteration 972, lr = 0.001
I0405 13:24:46.997797  1863 solver.cpp:218] Iteration 984 (2.25614 iter/s, 5.31881s/12 iters), loss = 5.13612
I0405 13:24:46.997836  1863 solver.cpp:237]     Train net output #0: loss = 5.13612 (* 1 = 5.13612 loss)
I0405 13:24:46.997843  1863 sgd_solver.cpp:105] Iteration 984, lr = 0.001
I0405 13:24:52.389190  1863 solver.cpp:218] Iteration 996 (2.22579 iter/s, 5.39134s/12 iters), loss = 5.10398
I0405 13:24:52.389318  1863 solver.cpp:237]     Train net output #0: loss = 5.10398 (* 1 = 5.10398 loss)
I0405 13:24:52.389328  1863 sgd_solver.cpp:105] Iteration 996, lr = 0.001
I0405 13:24:57.685223  1863 solver.cpp:218] Iteration 1008 (2.2659 iter/s, 5.2959s/12 iters), loss = 5.18791
I0405 13:24:57.685259  1863 solver.cpp:237]     Train net output #0: loss = 5.18791 (* 1 = 5.18791 loss)
I0405 13:24:57.685264  1863 sgd_solver.cpp:105] Iteration 1008, lr = 0.001
I0405 13:24:58.802043  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:25:02.522800  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel
I0405 13:25:07.138593  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate
I0405 13:25:09.434089  1863 solver.cpp:330] Iteration 1020, Testing net (#0)
I0405 13:25:09.434110  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:25:13.444876  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:25:13.868412  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0104167
I0405 13:25:13.868449  1863 solver.cpp:397]     Test net output #1: loss = 5.12398 (* 1 = 5.12398 loss)
I0405 13:25:14.003728  1863 solver.cpp:218] Iteration 1020 (0.735363 iter/s, 16.3185s/12 iters), loss = 5.11485
I0405 13:25:14.005502  1863 solver.cpp:237]     Train net output #0: loss = 5.11485 (* 1 = 5.11485 loss)
I0405 13:25:14.005514  1863 sgd_solver.cpp:105] Iteration 1020, lr = 0.001
I0405 13:25:18.273517  1863 solver.cpp:218] Iteration 1032 (2.81161 iter/s, 4.26801s/12 iters), loss = 5.23189
I0405 13:25:18.273557  1863 solver.cpp:237]     Train net output #0: loss = 5.23189 (* 1 = 5.23189 loss)
I0405 13:25:18.273563  1863 sgd_solver.cpp:105] Iteration 1032, lr = 0.001
I0405 13:25:23.764366  1863 solver.cpp:218] Iteration 1044 (2.18548 iter/s, 5.49079s/12 iters), loss = 5.18565
I0405 13:25:23.764508  1863 solver.cpp:237]     Train net output #0: loss = 5.18565 (* 1 = 5.18565 loss)
I0405 13:25:23.764516  1863 sgd_solver.cpp:105] Iteration 1044, lr = 0.001
I0405 13:25:28.989504  1863 solver.cpp:218] Iteration 1056 (2.29666 iter/s, 5.22499s/12 iters), loss = 5.07116
I0405 13:25:28.989544  1863 solver.cpp:237]     Train net output #0: loss = 5.07116 (* 1 = 5.07116 loss)
I0405 13:25:28.989550  1863 sgd_solver.cpp:105] Iteration 1056, lr = 0.001
I0405 13:25:33.982376  1863 solver.cpp:218] Iteration 1068 (2.40345 iter/s, 4.99282s/12 iters), loss = 5.16479
I0405 13:25:33.982419  1863 solver.cpp:237]     Train net output #0: loss = 5.16479 (* 1 = 5.16479 loss)
I0405 13:25:33.982426  1863 sgd_solver.cpp:105] Iteration 1068, lr = 0.001
I0405 13:25:39.108752  1863 solver.cpp:218] Iteration 1080 (2.34086 iter/s, 5.12631s/12 iters), loss = 5.04961
I0405 13:25:39.108810  1863 solver.cpp:237]     Train net output #0: loss = 5.04961 (* 1 = 5.04961 loss)
I0405 13:25:39.108821  1863 sgd_solver.cpp:105] Iteration 1080, lr = 0.001
I0405 13:25:44.303812  1863 solver.cpp:218] Iteration 1092 (2.30992 iter/s, 5.19499s/12 iters), loss = 5.18445
I0405 13:25:44.303872  1863 solver.cpp:237]     Train net output #0: loss = 5.18445 (* 1 = 5.18445 loss)
I0405 13:25:44.303882  1863 sgd_solver.cpp:105] Iteration 1092, lr = 0.001
I0405 13:25:49.671370  1863 solver.cpp:218] Iteration 1104 (2.23568 iter/s, 5.36749s/12 iters), loss = 5.09934
I0405 13:25:49.671413  1863 solver.cpp:237]     Train net output #0: loss = 5.09934 (* 1 = 5.09934 loss)
I0405 13:25:49.671419  1863 sgd_solver.cpp:105] Iteration 1104, lr = 0.001
I0405 13:25:52.940515  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:25:54.736490  1863 solver.cpp:218] Iteration 1116 (2.36917 iter/s, 5.06506s/12 iters), loss = 5.04197
I0405 13:25:54.736614  1863 solver.cpp:237]     Train net output #0: loss = 5.04197 (* 1 = 5.04197 loss)
I0405 13:25:54.736625  1863 sgd_solver.cpp:105] Iteration 1116, lr = 0.001
I0405 13:25:56.858074  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel
I0405 13:26:00.769737  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate
I0405 13:26:03.099774  1863 solver.cpp:330] Iteration 1122, Testing net (#0)
I0405 13:26:03.099794  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:26:06.994309  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:26:07.464771  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0183824
I0405 13:26:07.464813  1863 solver.cpp:397]     Test net output #1: loss = 5.09748 (* 1 = 5.09748 loss)
I0405 13:26:09.355872  1863 solver.cpp:218] Iteration 1128 (0.820835 iter/s, 14.6193s/12 iters), loss = 5.09792
I0405 13:26:09.355917  1863 solver.cpp:237]     Train net output #0: loss = 5.09792 (* 1 = 5.09792 loss)
I0405 13:26:09.355924  1863 sgd_solver.cpp:105] Iteration 1128, lr = 0.001
I0405 13:26:14.442461  1863 solver.cpp:218] Iteration 1140 (2.35917 iter/s, 5.08653s/12 iters), loss = 5.08792
I0405 13:26:14.442502  1863 solver.cpp:237]     Train net output #0: loss = 5.08792 (* 1 = 5.08792 loss)
I0405 13:26:14.442508  1863 sgd_solver.cpp:105] Iteration 1140, lr = 0.001
I0405 13:26:19.618952  1863 solver.cpp:218] Iteration 1152 (2.3182 iter/s, 5.17643s/12 iters), loss = 5.1226
I0405 13:26:19.619005  1863 solver.cpp:237]     Train net output #0: loss = 5.1226 (* 1 = 5.1226 loss)
I0405 13:26:19.619014  1863 sgd_solver.cpp:105] Iteration 1152, lr = 0.001
I0405 13:26:24.833739  1863 solver.cpp:218] Iteration 1164 (2.30118 iter/s, 5.21472s/12 iters), loss = 5.13174
I0405 13:26:24.833856  1863 solver.cpp:237]     Train net output #0: loss = 5.13174 (* 1 = 5.13174 loss)
I0405 13:26:24.833863  1863 sgd_solver.cpp:105] Iteration 1164, lr = 0.001
I0405 13:26:30.016530  1863 solver.cpp:218] Iteration 1176 (2.31541 iter/s, 5.18267s/12 iters), loss = 5.07971
I0405 13:26:30.016571  1863 solver.cpp:237]     Train net output #0: loss = 5.07971 (* 1 = 5.07971 loss)
I0405 13:26:30.016578  1863 sgd_solver.cpp:105] Iteration 1176, lr = 0.001
I0405 13:26:35.361748  1863 solver.cpp:218] Iteration 1188 (2.24502 iter/s, 5.34516s/12 iters), loss = 5.0221
I0405 13:26:35.361806  1863 solver.cpp:237]     Train net output #0: loss = 5.0221 (* 1 = 5.0221 loss)
I0405 13:26:35.361814  1863 sgd_solver.cpp:105] Iteration 1188, lr = 0.001
I0405 13:26:40.694027  1863 solver.cpp:218] Iteration 1200 (2.25047 iter/s, 5.33221s/12 iters), loss = 5.10289
I0405 13:26:40.694067  1863 solver.cpp:237]     Train net output #0: loss = 5.10289 (* 1 = 5.10289 loss)
I0405 13:26:40.694072  1863 sgd_solver.cpp:105] Iteration 1200, lr = 0.001
I0405 13:26:45.951365  1863 solver.cpp:218] Iteration 1212 (2.28255 iter/s, 5.25728s/12 iters), loss = 5.09922
I0405 13:26:45.951433  1863 solver.cpp:237]     Train net output #0: loss = 5.09922 (* 1 = 5.09922 loss)
I0405 13:26:45.951442  1863 sgd_solver.cpp:105] Iteration 1212, lr = 0.001
I0405 13:26:46.210605  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:26:50.808246  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel
I0405 13:26:54.285569  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate
I0405 13:26:56.581863  1863 solver.cpp:330] Iteration 1224, Testing net (#0)
I0405 13:26:56.581938  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:27:00.400744  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:27:00.904995  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0202206
I0405 13:27:00.905030  1863 solver.cpp:397]     Test net output #1: loss = 5.07093 (* 1 = 5.07093 loss)
I0405 13:27:01.042480  1863 solver.cpp:218] Iteration 1224 (0.795173 iter/s, 15.091s/12 iters), loss = 5.11313
I0405 13:27:01.044044  1863 solver.cpp:237]     Train net output #0: loss = 5.11313 (* 1 = 5.11313 loss)
I0405 13:27:01.044055  1863 sgd_solver.cpp:105] Iteration 1224, lr = 0.001
I0405 13:27:05.250766  1863 solver.cpp:218] Iteration 1236 (2.85259 iter/s, 4.20671s/12 iters), loss = 5.16574
I0405 13:27:05.250823  1863 solver.cpp:237]     Train net output #0: loss = 5.16574 (* 1 = 5.16574 loss)
I0405 13:27:05.250830  1863 sgd_solver.cpp:105] Iteration 1236, lr = 0.001
I0405 13:27:10.370914  1863 solver.cpp:218] Iteration 1248 (2.34371 iter/s, 5.12008s/12 iters), loss = 5.04096
I0405 13:27:10.370956  1863 solver.cpp:237]     Train net output #0: loss = 5.04096 (* 1 = 5.04096 loss)
I0405 13:27:10.370961  1863 sgd_solver.cpp:105] Iteration 1248, lr = 0.001
I0405 13:27:15.747706  1863 solver.cpp:218] Iteration 1260 (2.23184 iter/s, 5.37673s/12 iters), loss = 5.08556
I0405 13:27:15.747750  1863 solver.cpp:237]     Train net output #0: loss = 5.08556 (* 1 = 5.08556 loss)
I0405 13:27:15.747756  1863 sgd_solver.cpp:105] Iteration 1260, lr = 0.001
I0405 13:27:21.067162  1863 solver.cpp:218] Iteration 1272 (2.25589 iter/s, 5.3194s/12 iters), loss = 5.08598
I0405 13:27:21.067200  1863 solver.cpp:237]     Train net output #0: loss = 5.08598 (* 1 = 5.08598 loss)
I0405 13:27:21.067206  1863 sgd_solver.cpp:105] Iteration 1272, lr = 0.001
I0405 13:27:26.437849  1863 solver.cpp:218] Iteration 1284 (2.23437 iter/s, 5.37063s/12 iters), loss = 5.0159
I0405 13:27:26.437896  1863 solver.cpp:237]     Train net output #0: loss = 5.0159 (* 1 = 5.0159 loss)
I0405 13:27:26.437902  1863 sgd_solver.cpp:105] Iteration 1284, lr = 0.001
I0405 13:27:31.726092  1863 solver.cpp:218] Iteration 1296 (2.26921 iter/s, 5.28818s/12 iters), loss = 5.11757
I0405 13:27:31.726259  1863 solver.cpp:237]     Train net output #0: loss = 5.11757 (* 1 = 5.11757 loss)
I0405 13:27:31.726266  1863 sgd_solver.cpp:105] Iteration 1296, lr = 0.001
I0405 13:27:37.159793  1863 solver.cpp:218] Iteration 1308 (2.20851 iter/s, 5.43353s/12 iters), loss = 5.03457
I0405 13:27:37.159832  1863 solver.cpp:237]     Train net output #0: loss = 5.03457 (* 1 = 5.03457 loss)
I0405 13:27:37.159837  1863 sgd_solver.cpp:105] Iteration 1308, lr = 0.001
I0405 13:27:39.648968  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:27:42.281572  1863 solver.cpp:218] Iteration 1320 (2.34296 iter/s, 5.12172s/12 iters), loss = 5.07883
I0405 13:27:42.281621  1863 solver.cpp:237]     Train net output #0: loss = 5.07883 (* 1 = 5.07883 loss)
I0405 13:27:42.281627  1863 sgd_solver.cpp:105] Iteration 1320, lr = 0.001
I0405 13:27:44.477495  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel
I0405 13:27:48.002069  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate
I0405 13:27:50.343619  1863 solver.cpp:330] Iteration 1326, Testing net (#0)
I0405 13:27:50.343638  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:27:54.262787  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:27:54.855644  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0196078
I0405 13:27:54.855679  1863 solver.cpp:397]     Test net output #1: loss = 5.05287 (* 1 = 5.05287 loss)
I0405 13:27:56.758210  1863 solver.cpp:218] Iteration 1332 (0.828925 iter/s, 14.4766s/12 iters), loss = 5.03884
I0405 13:27:56.758260  1863 solver.cpp:237]     Train net output #0: loss = 5.03884 (* 1 = 5.03884 loss)
I0405 13:27:56.758265  1863 sgd_solver.cpp:105] Iteration 1332, lr = 0.001
I0405 13:28:01.863672  1863 solver.cpp:218] Iteration 1344 (2.35045 iter/s, 5.1054s/12 iters), loss = 5.11667
I0405 13:28:01.863785  1863 solver.cpp:237]     Train net output #0: loss = 5.11667 (* 1 = 5.11667 loss)
I0405 13:28:01.863796  1863 sgd_solver.cpp:105] Iteration 1344, lr = 0.001
I0405 13:28:07.159250  1863 solver.cpp:218] Iteration 1356 (2.26609 iter/s, 5.29546s/12 iters), loss = 5.02294
I0405 13:28:07.159307  1863 solver.cpp:237]     Train net output #0: loss = 5.02294 (* 1 = 5.02294 loss)
I0405 13:28:07.159315  1863 sgd_solver.cpp:105] Iteration 1356, lr = 0.001
I0405 13:28:12.682595  1863 solver.cpp:218] Iteration 1368 (2.17262 iter/s, 5.52328s/12 iters), loss = 5.11169
I0405 13:28:12.682642  1863 solver.cpp:237]     Train net output #0: loss = 5.11169 (* 1 = 5.11169 loss)
I0405 13:28:12.682647  1863 sgd_solver.cpp:105] Iteration 1368, lr = 0.001
I0405 13:28:13.908413  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:28:17.916419  1863 solver.cpp:218] Iteration 1380 (2.2928 iter/s, 5.23377s/12 iters), loss = 5.03272
I0405 13:28:17.916460  1863 solver.cpp:237]     Train net output #0: loss = 5.03272 (* 1 = 5.03272 loss)
I0405 13:28:17.916465  1863 sgd_solver.cpp:105] Iteration 1380, lr = 0.001
I0405 13:28:23.141476  1863 solver.cpp:218] Iteration 1392 (2.29665 iter/s, 5.225s/12 iters), loss = 5.02668
I0405 13:28:23.141531  1863 solver.cpp:237]     Train net output #0: loss = 5.02668 (* 1 = 5.02668 loss)
I0405 13:28:23.141539  1863 sgd_solver.cpp:105] Iteration 1392, lr = 0.001
I0405 13:28:28.268108  1863 solver.cpp:218] Iteration 1404 (2.34075 iter/s, 5.12656s/12 iters), loss = 4.99882
I0405 13:28:28.268164  1863 solver.cpp:237]     Train net output #0: loss = 4.99882 (* 1 = 4.99882 loss)
I0405 13:28:28.268172  1863 sgd_solver.cpp:105] Iteration 1404, lr = 0.001
I0405 13:28:33.123380  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:28:33.509905  1863 solver.cpp:218] Iteration 1416 (2.28932 iter/s, 5.24173s/12 iters), loss = 5.00448
I0405 13:28:33.509948  1863 solver.cpp:237]     Train net output #0: loss = 5.00448 (* 1 = 5.00448 loss)
I0405 13:28:33.509953  1863 sgd_solver.cpp:105] Iteration 1416, lr = 0.001
I0405 13:28:38.233368  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel
I0405 13:28:42.262754  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate
I0405 13:28:44.571681  1863 solver.cpp:330] Iteration 1428, Testing net (#0)
I0405 13:28:44.571702  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:28:48.380586  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:28:48.964123  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0214461
I0405 13:28:48.964155  1863 solver.cpp:397]     Test net output #1: loss = 5.03452 (* 1 = 5.03452 loss)
I0405 13:28:49.101198  1863 solver.cpp:218] Iteration 1428 (0.769663 iter/s, 15.5912s/12 iters), loss = 4.99486
I0405 13:28:49.101248  1863 solver.cpp:237]     Train net output #0: loss = 4.99486 (* 1 = 4.99486 loss)
I0405 13:28:49.101256  1863 sgd_solver.cpp:105] Iteration 1428, lr = 0.001
I0405 13:28:53.476274  1863 solver.cpp:218] Iteration 1440 (2.74285 iter/s, 4.37501s/12 iters), loss = 4.96036
I0405 13:28:53.476315  1863 solver.cpp:237]     Train net output #0: loss = 4.96036 (* 1 = 4.96036 loss)
I0405 13:28:53.476320  1863 sgd_solver.cpp:105] Iteration 1440, lr = 0.001
I0405 13:28:58.761310  1863 solver.cpp:218] Iteration 1452 (2.27059 iter/s, 5.28498s/12 iters), loss = 4.96013
I0405 13:28:58.761368  1863 solver.cpp:237]     Train net output #0: loss = 4.96013 (* 1 = 4.96013 loss)
I0405 13:28:58.761377  1863 sgd_solver.cpp:105] Iteration 1452, lr = 0.001
I0405 13:29:04.082098  1863 solver.cpp:218] Iteration 1464 (2.25534 iter/s, 5.32071s/12 iters), loss = 4.99455
I0405 13:29:04.082248  1863 solver.cpp:237]     Train net output #0: loss = 4.99455 (* 1 = 4.99455 loss)
I0405 13:29:04.082258  1863 sgd_solver.cpp:105] Iteration 1464, lr = 0.001
I0405 13:29:09.248138  1863 solver.cpp:218] Iteration 1476 (2.32294 iter/s, 5.16588s/12 iters), loss = 5.15966
I0405 13:29:09.248178  1863 solver.cpp:237]     Train net output #0: loss = 5.15966 (* 1 = 5.15966 loss)
I0405 13:29:09.248184  1863 sgd_solver.cpp:105] Iteration 1476, lr = 0.001
I0405 13:29:14.497040  1863 solver.cpp:218] Iteration 1488 (2.28622 iter/s, 5.24884s/12 iters), loss = 4.98285
I0405 13:29:14.497088  1863 solver.cpp:237]     Train net output #0: loss = 4.98285 (* 1 = 4.98285 loss)
I0405 13:29:14.497098  1863 sgd_solver.cpp:105] Iteration 1488, lr = 0.001
I0405 13:29:19.818465  1863 solver.cpp:218] Iteration 1500 (2.25506 iter/s, 5.32137s/12 iters), loss = 5.08674
I0405 13:29:19.818512  1863 solver.cpp:237]     Train net output #0: loss = 5.08674 (* 1 = 5.08674 loss)
I0405 13:29:19.818521  1863 sgd_solver.cpp:105] Iteration 1500, lr = 0.001
I0405 13:29:25.114317  1863 solver.cpp:218] Iteration 1512 (2.26595 iter/s, 5.29579s/12 iters), loss = 5.03557
I0405 13:29:25.114362  1863 solver.cpp:237]     Train net output #0: loss = 5.03557 (* 1 = 5.03557 loss)
I0405 13:29:25.114369  1863 sgd_solver.cpp:105] Iteration 1512, lr = 0.001
I0405 13:29:27.048461  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:29:30.417644  1863 solver.cpp:218] Iteration 1524 (2.26275 iter/s, 5.30327s/12 iters), loss = 5.0736
I0405 13:29:30.417680  1863 solver.cpp:237]     Train net output #0: loss = 5.0736 (* 1 = 5.0736 loss)
I0405 13:29:30.417685  1863 sgd_solver.cpp:105] Iteration 1524, lr = 0.001
I0405 13:29:32.542536  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel
I0405 13:29:37.377143  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate
I0405 13:29:39.709822  1863 solver.cpp:330] Iteration 1530, Testing net (#0)
I0405 13:29:39.709848  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:29:43.759838  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:29:44.393688  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 13:29:44.393725  1863 solver.cpp:397]     Test net output #1: loss = 5.01883 (* 1 = 5.01883 loss)
I0405 13:29:46.264744  1863 solver.cpp:218] Iteration 1536 (0.757239 iter/s, 15.8471s/12 iters), loss = 4.96732
I0405 13:29:46.264803  1863 solver.cpp:237]     Train net output #0: loss = 4.96732 (* 1 = 4.96732 loss)
I0405 13:29:46.264812  1863 sgd_solver.cpp:105] Iteration 1536, lr = 0.001
I0405 13:29:51.320413  1863 solver.cpp:218] Iteration 1548 (2.37361 iter/s, 5.0556s/12 iters), loss = 5.02201
I0405 13:29:51.320458  1863 solver.cpp:237]     Train net output #0: loss = 5.02201 (* 1 = 5.02201 loss)
I0405 13:29:51.320463  1863 sgd_solver.cpp:105] Iteration 1548, lr = 0.001
I0405 13:29:56.612432  1863 solver.cpp:218] Iteration 1560 (2.26759 iter/s, 5.29196s/12 iters), loss = 5.01922
I0405 13:29:56.612475  1863 solver.cpp:237]     Train net output #0: loss = 5.01922 (* 1 = 5.01922 loss)
I0405 13:29:56.612480  1863 sgd_solver.cpp:105] Iteration 1560, lr = 0.001
I0405 13:30:01.712539  1863 solver.cpp:218] Iteration 1572 (2.35292 iter/s, 5.10005s/12 iters), loss = 4.94869
I0405 13:30:01.712582  1863 solver.cpp:237]     Train net output #0: loss = 4.94869 (* 1 = 4.94869 loss)
I0405 13:30:01.712587  1863 sgd_solver.cpp:105] Iteration 1572, lr = 0.001
I0405 13:30:06.753245  1863 solver.cpp:218] Iteration 1584 (2.38065 iter/s, 5.04065s/12 iters), loss = 5.01284
I0405 13:30:06.753289  1863 solver.cpp:237]     Train net output #0: loss = 5.01284 (* 1 = 5.01284 loss)
I0405 13:30:06.753295  1863 sgd_solver.cpp:105] Iteration 1584, lr = 0.001
I0405 13:30:12.084743  1863 solver.cpp:218] Iteration 1596 (2.2508 iter/s, 5.33144s/12 iters), loss = 5.07797
I0405 13:30:12.084864  1863 solver.cpp:237]     Train net output #0: loss = 5.07797 (* 1 = 5.07797 loss)
I0405 13:30:12.084870  1863 sgd_solver.cpp:105] Iteration 1596, lr = 0.001
I0405 13:30:17.515425  1863 solver.cpp:218] Iteration 1608 (2.20972 iter/s, 5.43055s/12 iters), loss = 4.94805
I0405 13:30:17.515484  1863 solver.cpp:237]     Train net output #0: loss = 4.94805 (* 1 = 4.94805 loss)
I0405 13:30:17.515493  1863 sgd_solver.cpp:105] Iteration 1608, lr = 0.001
I0405 13:30:21.706212  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:30:22.900058  1863 solver.cpp:218] Iteration 1620 (2.22859 iter/s, 5.38456s/12 iters), loss = 4.97395
I0405 13:30:22.900100  1863 solver.cpp:237]     Train net output #0: loss = 4.97395 (* 1 = 4.97395 loss)
I0405 13:30:22.900105  1863 sgd_solver.cpp:105] Iteration 1620, lr = 0.001
I0405 13:30:27.724025  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel
I0405 13:30:32.766322  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate
I0405 13:30:35.073418  1863 solver.cpp:330] Iteration 1632, Testing net (#0)
I0405 13:30:35.073441  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:30:38.757534  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:30:39.465253  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0226716
I0405 13:30:39.465292  1863 solver.cpp:397]     Test net output #1: loss = 5.00467 (* 1 = 5.00467 loss)
I0405 13:30:39.606992  1863 solver.cpp:218] Iteration 1632 (0.718267 iter/s, 16.7069s/12 iters), loss = 5.04073
I0405 13:30:39.607053  1863 solver.cpp:237]     Train net output #0: loss = 5.04073 (* 1 = 5.04073 loss)
I0405 13:30:39.607061  1863 sgd_solver.cpp:105] Iteration 1632, lr = 0.001
I0405 13:30:43.923125  1863 solver.cpp:218] Iteration 1644 (2.78032 iter/s, 4.31605s/12 iters), loss = 4.99717
I0405 13:30:43.923246  1863 solver.cpp:237]     Train net output #0: loss = 4.99717 (* 1 = 4.99717 loss)
I0405 13:30:43.923255  1863 sgd_solver.cpp:105] Iteration 1644, lr = 0.001
I0405 13:30:49.245064  1863 solver.cpp:218] Iteration 1656 (2.25487 iter/s, 5.32181s/12 iters), loss = 4.94868
I0405 13:30:49.245111  1863 solver.cpp:237]     Train net output #0: loss = 4.94868 (* 1 = 4.94868 loss)
I0405 13:30:49.245117  1863 sgd_solver.cpp:105] Iteration 1656, lr = 0.001
I0405 13:30:54.575873  1863 solver.cpp:218] Iteration 1668 (2.25109 iter/s, 5.33075s/12 iters), loss = 5.13384
I0405 13:30:54.575915  1863 solver.cpp:237]     Train net output #0: loss = 5.13384 (* 1 = 5.13384 loss)
I0405 13:30:54.575922  1863 sgd_solver.cpp:105] Iteration 1668, lr = 0.001
I0405 13:30:59.759254  1863 solver.cpp:218] Iteration 1680 (2.31512 iter/s, 5.18332s/12 iters), loss = 4.88375
I0405 13:30:59.759307  1863 solver.cpp:237]     Train net output #0: loss = 4.88375 (* 1 = 4.88375 loss)
I0405 13:30:59.759315  1863 sgd_solver.cpp:105] Iteration 1680, lr = 0.001
I0405 13:31:04.976168  1863 solver.cpp:218] Iteration 1692 (2.30024 iter/s, 5.21685s/12 iters), loss = 5.04995
I0405 13:31:04.976208  1863 solver.cpp:237]     Train net output #0: loss = 5.04995 (* 1 = 5.04995 loss)
I0405 13:31:04.976213  1863 sgd_solver.cpp:105] Iteration 1692, lr = 0.001
I0405 13:31:10.160418  1863 solver.cpp:218] Iteration 1704 (2.31473 iter/s, 5.1842s/12 iters), loss = 4.94559
I0405 13:31:10.160457  1863 solver.cpp:237]     Train net output #0: loss = 4.94559 (* 1 = 4.94559 loss)
I0405 13:31:10.160463  1863 sgd_solver.cpp:105] Iteration 1704, lr = 0.001
I0405 13:31:15.495569  1863 solver.cpp:218] Iteration 1716 (2.24926 iter/s, 5.3351s/12 iters), loss = 5.0023
I0405 13:31:15.495743  1863 solver.cpp:237]     Train net output #0: loss = 5.0023 (* 1 = 5.0023 loss)
I0405 13:31:15.495751  1863 sgd_solver.cpp:105] Iteration 1716, lr = 0.001
I0405 13:31:16.576189  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:31:20.837200  1863 solver.cpp:218] Iteration 1728 (2.24658 iter/s, 5.34145s/12 iters), loss = 4.98466
I0405 13:31:20.837240  1863 solver.cpp:237]     Train net output #0: loss = 4.98466 (* 1 = 4.98466 loss)
I0405 13:31:20.837246  1863 sgd_solver.cpp:105] Iteration 1728, lr = 0.001
I0405 13:31:22.915419  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel
I0405 13:31:27.586692  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate
I0405 13:31:29.997879  1863 solver.cpp:330] Iteration 1734, Testing net (#0)
I0405 13:31:29.997900  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:31:33.846191  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:31:34.542418  1863 solver.cpp:397]     Test net output #0: accuracy = 0.028799
I0405 13:31:34.542452  1863 solver.cpp:397]     Test net output #1: loss = 4.98343 (* 1 = 4.98343 loss)
I0405 13:31:36.438283  1863 solver.cpp:218] Iteration 1740 (0.76918 iter/s, 15.601s/12 iters), loss = 5.02176
I0405 13:31:36.438331  1863 solver.cpp:237]     Train net output #0: loss = 5.02176 (* 1 = 5.02176 loss)
I0405 13:31:36.438338  1863 sgd_solver.cpp:105] Iteration 1740, lr = 0.001
I0405 13:31:41.751595  1863 solver.cpp:218] Iteration 1752 (2.25851 iter/s, 5.31325s/12 iters), loss = 4.99259
I0405 13:31:41.751646  1863 solver.cpp:237]     Train net output #0: loss = 4.99259 (* 1 = 4.99259 loss)
I0405 13:31:41.751653  1863 sgd_solver.cpp:105] Iteration 1752, lr = 0.001
I0405 13:31:47.175618  1863 solver.cpp:218] Iteration 1764 (2.2124 iter/s, 5.42396s/12 iters), loss = 4.96413
I0405 13:31:47.175714  1863 solver.cpp:237]     Train net output #0: loss = 4.96413 (* 1 = 4.96413 loss)
I0405 13:31:47.175721  1863 sgd_solver.cpp:105] Iteration 1764, lr = 0.001
I0405 13:31:52.470592  1863 solver.cpp:218] Iteration 1776 (2.26635 iter/s, 5.29486s/12 iters), loss = 4.98746
I0405 13:31:52.470641  1863 solver.cpp:237]     Train net output #0: loss = 4.98746 (* 1 = 4.98746 loss)
I0405 13:31:52.470649  1863 sgd_solver.cpp:105] Iteration 1776, lr = 0.001
I0405 13:31:57.858654  1863 solver.cpp:218] Iteration 1788 (2.22717 iter/s, 5.388s/12 iters), loss = 4.85707
I0405 13:31:57.858693  1863 solver.cpp:237]     Train net output #0: loss = 4.85707 (* 1 = 4.85707 loss)
I0405 13:31:57.858698  1863 sgd_solver.cpp:105] Iteration 1788, lr = 0.001
I0405 13:32:03.215728  1863 solver.cpp:218] Iteration 1800 (2.24005 iter/s, 5.35702s/12 iters), loss = 4.98532
I0405 13:32:03.215786  1863 solver.cpp:237]     Train net output #0: loss = 4.98532 (* 1 = 4.98532 loss)
I0405 13:32:03.215796  1863 sgd_solver.cpp:105] Iteration 1800, lr = 0.001
I0405 13:32:08.588393  1863 solver.cpp:218] Iteration 1812 (2.23356 iter/s, 5.37259s/12 iters), loss = 4.95461
I0405 13:32:08.588452  1863 solver.cpp:237]     Train net output #0: loss = 4.95461 (* 1 = 4.95461 loss)
I0405 13:32:08.588461  1863 sgd_solver.cpp:105] Iteration 1812, lr = 0.001
I0405 13:32:11.989785  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:32:13.888711  1863 solver.cpp:218] Iteration 1824 (2.26405 iter/s, 5.30025s/12 iters), loss = 4.90306
I0405 13:32:13.888751  1863 solver.cpp:237]     Train net output #0: loss = 4.90306 (* 1 = 4.90306 loss)
I0405 13:32:13.888757  1863 sgd_solver.cpp:105] Iteration 1824, lr = 0.001
I0405 13:32:18.568969  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel
I0405 13:32:23.236646  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate
I0405 13:32:25.563434  1863 solver.cpp:330] Iteration 1836, Testing net (#0)
I0405 13:32:25.563457  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:32:29.268075  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:32:30.031213  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0306373
I0405 13:32:30.031262  1863 solver.cpp:397]     Test net output #1: loss = 4.95911 (* 1 = 4.95911 loss)
I0405 13:32:30.172456  1863 solver.cpp:218] Iteration 1836 (0.736933 iter/s, 16.2837s/12 iters), loss = 4.86763
I0405 13:32:30.172503  1863 solver.cpp:237]     Train net output #0: loss = 4.86763 (* 1 = 4.86763 loss)
I0405 13:32:30.172510  1863 sgd_solver.cpp:105] Iteration 1836, lr = 0.001
I0405 13:32:34.467483  1863 solver.cpp:218] Iteration 1848 (2.79397 iter/s, 4.29497s/12 iters), loss = 4.93787
I0405 13:32:34.467530  1863 solver.cpp:237]     Train net output #0: loss = 4.93787 (* 1 = 4.93787 loss)
I0405 13:32:34.467536  1863 sgd_solver.cpp:105] Iteration 1848, lr = 0.001
I0405 13:32:39.643678  1863 solver.cpp:218] Iteration 1860 (2.31833 iter/s, 5.17614s/12 iters), loss = 4.98702
I0405 13:32:39.643720  1863 solver.cpp:237]     Train net output #0: loss = 4.98702 (* 1 = 4.98702 loss)
I0405 13:32:39.643726  1863 sgd_solver.cpp:105] Iteration 1860, lr = 0.001
I0405 13:32:44.966639  1863 solver.cpp:218] Iteration 1872 (2.25441 iter/s, 5.3229s/12 iters), loss = 5.01784
I0405 13:32:44.966693  1863 solver.cpp:237]     Train net output #0: loss = 5.01784 (* 1 = 5.01784 loss)
I0405 13:32:44.966702  1863 sgd_solver.cpp:105] Iteration 1872, lr = 0.001
I0405 13:32:50.143064  1863 solver.cpp:218] Iteration 1884 (2.31823 iter/s, 5.17636s/12 iters), loss = 4.9056
I0405 13:32:50.143162  1863 solver.cpp:237]     Train net output #0: loss = 4.9056 (* 1 = 4.9056 loss)
I0405 13:32:50.143168  1863 sgd_solver.cpp:105] Iteration 1884, lr = 0.001
I0405 13:32:55.409456  1863 solver.cpp:218] Iteration 1896 (2.27865 iter/s, 5.26628s/12 iters), loss = 4.92867
I0405 13:32:55.409493  1863 solver.cpp:237]     Train net output #0: loss = 4.92867 (* 1 = 4.92867 loss)
I0405 13:32:55.409498  1863 sgd_solver.cpp:105] Iteration 1896, lr = 0.001
I0405 13:33:00.840729  1863 solver.cpp:218] Iteration 1908 (2.20945 iter/s, 5.43122s/12 iters), loss = 4.98246
I0405 13:33:00.840767  1863 solver.cpp:237]     Train net output #0: loss = 4.98246 (* 1 = 4.98246 loss)
I0405 13:33:00.840773  1863 sgd_solver.cpp:105] Iteration 1908, lr = 0.001
I0405 13:33:06.112035  1863 solver.cpp:218] Iteration 1920 (2.2765 iter/s, 5.27126s/12 iters), loss = 4.8427
I0405 13:33:06.112071  1863 solver.cpp:237]     Train net output #0: loss = 4.8427 (* 1 = 4.8427 loss)
I0405 13:33:06.112076  1863 sgd_solver.cpp:105] Iteration 1920, lr = 0.001
I0405 13:33:06.343462  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:33:11.139056  1863 solver.cpp:218] Iteration 1932 (2.38712 iter/s, 5.02697s/12 iters), loss = 4.92997
I0405 13:33:11.139102  1863 solver.cpp:237]     Train net output #0: loss = 4.92997 (* 1 = 4.92997 loss)
I0405 13:33:11.139108  1863 sgd_solver.cpp:105] Iteration 1932, lr = 0.001
I0405 13:33:13.290777  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel
I0405 13:33:17.668146  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate
I0405 13:33:19.975096  1863 solver.cpp:330] Iteration 1938, Testing net (#0)
I0405 13:33:19.975121  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:33:23.591872  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:33:24.420312  1863 solver.cpp:397]     Test net output #0: accuracy = 0.033701
I0405 13:33:24.420358  1863 solver.cpp:397]     Test net output #1: loss = 4.93459 (* 1 = 4.93459 loss)
I0405 13:33:26.313439  1863 solver.cpp:218] Iteration 1944 (0.790809 iter/s, 15.1743s/12 iters), loss = 5.10564
I0405 13:33:26.313479  1863 solver.cpp:237]     Train net output #0: loss = 5.10564 (* 1 = 5.10564 loss)
I0405 13:33:26.313484  1863 sgd_solver.cpp:105] Iteration 1944, lr = 0.001
I0405 13:33:31.633522  1863 solver.cpp:218] Iteration 1956 (2.25563 iter/s, 5.32003s/12 iters), loss = 4.85495
I0405 13:33:31.633566  1863 solver.cpp:237]     Train net output #0: loss = 4.85495 (* 1 = 4.85495 loss)
I0405 13:33:31.633571  1863 sgd_solver.cpp:105] Iteration 1956, lr = 0.001
I0405 13:33:36.702203  1863 solver.cpp:218] Iteration 1968 (2.36751 iter/s, 5.06862s/12 iters), loss = 4.95798
I0405 13:33:36.702248  1863 solver.cpp:237]     Train net output #0: loss = 4.95798 (* 1 = 4.95798 loss)
I0405 13:33:36.702255  1863 sgd_solver.cpp:105] Iteration 1968, lr = 0.001
I0405 13:33:41.680902  1863 solver.cpp:218] Iteration 1980 (2.4103 iter/s, 4.97863s/12 iters), loss = 4.82191
I0405 13:33:41.680955  1863 solver.cpp:237]     Train net output #0: loss = 4.82191 (* 1 = 4.82191 loss)
I0405 13:33:41.680963  1863 sgd_solver.cpp:105] Iteration 1980, lr = 0.001
I0405 13:33:46.985450  1863 solver.cpp:218] Iteration 1992 (2.26224 iter/s, 5.30448s/12 iters), loss = 4.80464
I0405 13:33:46.985503  1863 solver.cpp:237]     Train net output #0: loss = 4.80464 (* 1 = 4.80464 loss)
I0405 13:33:46.985513  1863 sgd_solver.cpp:105] Iteration 1992, lr = 0.001
I0405 13:33:52.486757  1863 solver.cpp:218] Iteration 2004 (2.18135 iter/s, 5.50119s/12 iters), loss = 4.96025
I0405 13:33:52.486807  1863 solver.cpp:237]     Train net output #0: loss = 4.96025 (* 1 = 4.96025 loss)
I0405 13:33:52.486816  1863 sgd_solver.cpp:105] Iteration 2004, lr = 0.001
I0405 13:33:58.066757  1863 solver.cpp:218] Iteration 2016 (2.15056 iter/s, 5.57994s/12 iters), loss = 4.94338
I0405 13:33:58.066864  1863 solver.cpp:237]     Train net output #0: loss = 4.94338 (* 1 = 4.94338 loss)
I0405 13:33:58.066872  1863 sgd_solver.cpp:105] Iteration 2016, lr = 0.001
I0405 13:34:00.895025  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:34:03.544051  1863 solver.cpp:218] Iteration 2028 (2.19091 iter/s, 5.47717s/12 iters), loss = 4.93754
I0405 13:34:03.544107  1863 solver.cpp:237]     Train net output #0: loss = 4.93754 (* 1 = 4.93754 loss)
I0405 13:34:03.544116  1863 sgd_solver.cpp:105] Iteration 2028, lr = 0.001
I0405 13:34:08.425161  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel
I0405 13:34:12.929525  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate
I0405 13:34:15.265126  1863 solver.cpp:330] Iteration 2040, Testing net (#0)
I0405 13:34:15.265152  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:34:18.829880  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:34:19.693117  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0447304
I0405 13:34:19.693156  1863 solver.cpp:397]     Test net output #1: loss = 4.90162 (* 1 = 4.90162 loss)
I0405 13:34:19.835129  1863 solver.cpp:218] Iteration 2040 (0.736602 iter/s, 16.291s/12 iters), loss = 4.97657
I0405 13:34:19.836766  1863 solver.cpp:237]     Train net output #0: loss = 4.97657 (* 1 = 4.97657 loss)
I0405 13:34:19.836779  1863 sgd_solver.cpp:105] Iteration 2040, lr = 0.001
I0405 13:34:24.201967  1863 solver.cpp:218] Iteration 2052 (2.74902 iter/s, 4.36519s/12 iters), loss = 4.86813
I0405 13:34:24.202023  1863 solver.cpp:237]     Train net output #0: loss = 4.86813 (* 1 = 4.86813 loss)
I0405 13:34:24.202031  1863 sgd_solver.cpp:105] Iteration 2052, lr = 0.001
I0405 13:34:25.959779  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:34:29.454926  1863 solver.cpp:218] Iteration 2064 (2.28445 iter/s, 5.2529s/12 iters), loss = 4.91309
I0405 13:34:29.455056  1863 solver.cpp:237]     Train net output #0: loss = 4.91309 (* 1 = 4.91309 loss)
I0405 13:34:29.455062  1863 sgd_solver.cpp:105] Iteration 2064, lr = 0.001
I0405 13:34:34.663228  1863 solver.cpp:218] Iteration 2076 (2.30408 iter/s, 5.20816s/12 iters), loss = 4.86409
I0405 13:34:34.663267  1863 solver.cpp:237]     Train net output #0: loss = 4.86409 (* 1 = 4.86409 loss)
I0405 13:34:34.663272  1863 sgd_solver.cpp:105] Iteration 2076, lr = 0.001
I0405 13:34:39.962424  1863 solver.cpp:218] Iteration 2088 (2.26452 iter/s, 5.29914s/12 iters), loss = 4.85525
I0405 13:34:39.962466  1863 solver.cpp:237]     Train net output #0: loss = 4.85525 (* 1 = 4.85525 loss)
I0405 13:34:39.962473  1863 sgd_solver.cpp:105] Iteration 2088, lr = 0.001
I0405 13:34:45.295200  1863 solver.cpp:218] Iteration 2100 (2.25026 iter/s, 5.33272s/12 iters), loss = 4.84209
I0405 13:34:45.295245  1863 solver.cpp:237]     Train net output #0: loss = 4.84209 (* 1 = 4.84209 loss)
I0405 13:34:45.295253  1863 sgd_solver.cpp:105] Iteration 2100, lr = 0.001
I0405 13:34:50.682014  1863 solver.cpp:218] Iteration 2112 (2.22768 iter/s, 5.38676s/12 iters), loss = 4.73837
I0405 13:34:50.682054  1863 solver.cpp:237]     Train net output #0: loss = 4.73837 (* 1 = 4.73837 loss)
I0405 13:34:50.682058  1863 sgd_solver.cpp:105] Iteration 2112, lr = 0.001
I0405 13:34:55.951231  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:34:56.313601  1863 solver.cpp:218] Iteration 2124 (2.13086 iter/s, 5.63152s/12 iters), loss = 4.84801
I0405 13:34:56.313642  1863 solver.cpp:237]     Train net output #0: loss = 4.84801 (* 1 = 4.84801 loss)
I0405 13:34:56.313648  1863 sgd_solver.cpp:105] Iteration 2124, lr = 0.001
I0405 13:35:01.634811  1863 solver.cpp:218] Iteration 2136 (2.25515 iter/s, 5.32116s/12 iters), loss = 4.81284
I0405 13:35:01.634969  1863 solver.cpp:237]     Train net output #0: loss = 4.81284 (* 1 = 4.81284 loss)
I0405 13:35:01.634979  1863 sgd_solver.cpp:105] Iteration 2136, lr = 0.001
I0405 13:35:03.799365  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel
I0405 13:35:07.958356  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate
I0405 13:35:10.255831  1863 solver.cpp:330] Iteration 2142, Testing net (#0)
I0405 13:35:10.255848  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:35:13.694209  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:35:14.551668  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0398284
I0405 13:35:14.551700  1863 solver.cpp:397]     Test net output #1: loss = 4.89653 (* 1 = 4.89653 loss)
I0405 13:35:16.436144  1863 solver.cpp:218] Iteration 2148 (0.810747 iter/s, 14.8012s/12 iters), loss = 4.70651
I0405 13:35:16.436192  1863 solver.cpp:237]     Train net output #0: loss = 4.70651 (* 1 = 4.70651 loss)
I0405 13:35:16.436198  1863 sgd_solver.cpp:105] Iteration 2148, lr = 0.001
I0405 13:35:21.728207  1863 solver.cpp:218] Iteration 2160 (2.26757 iter/s, 5.29201s/12 iters), loss = 4.82715
I0405 13:35:21.728250  1863 solver.cpp:237]     Train net output #0: loss = 4.82715 (* 1 = 4.82715 loss)
I0405 13:35:21.728255  1863 sgd_solver.cpp:105] Iteration 2160, lr = 0.001
I0405 13:35:26.776091  1863 solver.cpp:218] Iteration 2172 (2.37726 iter/s, 5.04782s/12 iters), loss = 4.77178
I0405 13:35:26.776140  1863 solver.cpp:237]     Train net output #0: loss = 4.77178 (* 1 = 4.77178 loss)
I0405 13:35:26.776147  1863 sgd_solver.cpp:105] Iteration 2172, lr = 0.001
I0405 13:35:32.123864  1863 solver.cpp:218] Iteration 2184 (2.24395 iter/s, 5.34771s/12 iters), loss = 5.03811
I0405 13:35:32.123991  1863 solver.cpp:237]     Train net output #0: loss = 5.03811 (* 1 = 5.03811 loss)
I0405 13:35:32.123997  1863 sgd_solver.cpp:105] Iteration 2184, lr = 0.001
I0405 13:35:37.501657  1863 solver.cpp:218] Iteration 2196 (2.23146 iter/s, 5.37765s/12 iters), loss = 4.73474
I0405 13:35:37.501715  1863 solver.cpp:237]     Train net output #0: loss = 4.73474 (* 1 = 4.73474 loss)
I0405 13:35:37.501724  1863 sgd_solver.cpp:105] Iteration 2196, lr = 0.001
I0405 13:35:42.850119  1863 solver.cpp:218] Iteration 2208 (2.24367 iter/s, 5.34839s/12 iters), loss = 4.78
I0405 13:35:42.850170  1863 solver.cpp:237]     Train net output #0: loss = 4.78 (* 1 = 4.78 loss)
I0405 13:35:42.850178  1863 sgd_solver.cpp:105] Iteration 2208, lr = 0.001
I0405 13:35:48.155448  1863 solver.cpp:218] Iteration 2220 (2.2619 iter/s, 5.30526s/12 iters), loss = 4.78225
I0405 13:35:48.155488  1863 solver.cpp:237]     Train net output #0: loss = 4.78225 (* 1 = 4.78225 loss)
I0405 13:35:48.155493  1863 sgd_solver.cpp:105] Iteration 2220, lr = 0.001
I0405 13:35:50.080509  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:35:53.278195  1863 solver.cpp:218] Iteration 2232 (2.34252 iter/s, 5.12269s/12 iters), loss = 4.81873
I0405 13:35:53.278239  1863 solver.cpp:237]     Train net output #0: loss = 4.81873 (* 1 = 4.81873 loss)
I0405 13:35:53.278244  1863 sgd_solver.cpp:105] Iteration 2232, lr = 0.001
I0405 13:35:58.074151  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel
I0405 13:36:02.240373  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate
I0405 13:36:04.544700  1863 solver.cpp:330] Iteration 2244, Testing net (#0)
I0405 13:36:04.544721  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:36:08.023336  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:36:08.962093  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0410539
I0405 13:36:08.962123  1863 solver.cpp:397]     Test net output #1: loss = 4.88294 (* 1 = 4.88294 loss)
I0405 13:36:09.103744  1863 solver.cpp:218] Iteration 2244 (0.75827 iter/s, 15.8255s/12 iters), loss = 4.84759
I0405 13:36:09.103802  1863 solver.cpp:237]     Train net output #0: loss = 4.84759 (* 1 = 4.84759 loss)
I0405 13:36:09.103811  1863 sgd_solver.cpp:105] Iteration 2244, lr = 0.001
I0405 13:36:13.436857  1863 solver.cpp:218] Iteration 2256 (2.76941 iter/s, 4.33305s/12 iters), loss = 4.8085
I0405 13:36:13.436913  1863 solver.cpp:237]     Train net output #0: loss = 4.8085 (* 1 = 4.8085 loss)
I0405 13:36:13.436921  1863 sgd_solver.cpp:105] Iteration 2256, lr = 0.001
I0405 13:36:18.527422  1863 solver.cpp:218] Iteration 2268 (2.35733 iter/s, 5.0905s/12 iters), loss = 4.75976
I0405 13:36:18.527460  1863 solver.cpp:237]     Train net output #0: loss = 4.75976 (* 1 = 4.75976 loss)
I0405 13:36:18.527467  1863 sgd_solver.cpp:105] Iteration 2268, lr = 0.001
I0405 13:36:23.804560  1863 solver.cpp:218] Iteration 2280 (2.27398 iter/s, 5.27708s/12 iters), loss = 4.82168
I0405 13:36:23.804606  1863 solver.cpp:237]     Train net output #0: loss = 4.82168 (* 1 = 4.82168 loss)
I0405 13:36:23.804612  1863 sgd_solver.cpp:105] Iteration 2280, lr = 0.001
I0405 13:36:29.090160  1863 solver.cpp:218] Iteration 2292 (2.27034 iter/s, 5.28555s/12 iters), loss = 4.85928
I0405 13:36:29.090198  1863 solver.cpp:237]     Train net output #0: loss = 4.85928 (* 1 = 4.85928 loss)
I0405 13:36:29.090204  1863 sgd_solver.cpp:105] Iteration 2292, lr = 0.001
I0405 13:36:34.308151  1863 solver.cpp:218] Iteration 2304 (2.29976 iter/s, 5.21794s/12 iters), loss = 4.86659
I0405 13:36:34.308285  1863 solver.cpp:237]     Train net output #0: loss = 4.86659 (* 1 = 4.86659 loss)
I0405 13:36:34.308295  1863 sgd_solver.cpp:105] Iteration 2304, lr = 0.001
I0405 13:36:39.421455  1863 solver.cpp:218] Iteration 2316 (2.34689 iter/s, 5.11316s/12 iters), loss = 4.79796
I0405 13:36:39.421509  1863 solver.cpp:237]     Train net output #0: loss = 4.79796 (* 1 = 4.79796 loss)
I0405 13:36:39.421517  1863 sgd_solver.cpp:105] Iteration 2316, lr = 0.001
I0405 13:36:43.636662  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:36:44.776146  1863 solver.cpp:218] Iteration 2328 (2.24105 iter/s, 5.35463s/12 iters), loss = 4.74486
I0405 13:36:44.776185  1863 solver.cpp:237]     Train net output #0: loss = 4.74486 (* 1 = 4.74486 loss)
I0405 13:36:44.776191  1863 sgd_solver.cpp:105] Iteration 2328, lr = 0.001
I0405 13:36:49.850775  1863 solver.cpp:218] Iteration 2340 (2.36473 iter/s, 5.07458s/12 iters), loss = 4.88373
I0405 13:36:49.850831  1863 solver.cpp:237]     Train net output #0: loss = 4.88373 (* 1 = 4.88373 loss)
I0405 13:36:49.850838  1863 sgd_solver.cpp:105] Iteration 2340, lr = 0.001
I0405 13:36:52.083683  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel
I0405 13:36:56.321087  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate
I0405 13:36:58.649183  1863 solver.cpp:330] Iteration 2346, Testing net (#0)
I0405 13:36:58.649204  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:37:02.027416  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:37:02.956796  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0551471
I0405 13:37:02.956830  1863 solver.cpp:397]     Test net output #1: loss = 4.81119 (* 1 = 4.81119 loss)
I0405 13:37:04.857270  1863 solver.cpp:218] Iteration 2352 (0.799657 iter/s, 15.0064s/12 iters), loss = 4.73248
I0405 13:37:04.857394  1863 solver.cpp:237]     Train net output #0: loss = 4.73248 (* 1 = 4.73248 loss)
I0405 13:37:04.857401  1863 sgd_solver.cpp:105] Iteration 2352, lr = 0.001
I0405 13:37:10.175557  1863 solver.cpp:218] Iteration 2364 (2.25642 iter/s, 5.31815s/12 iters), loss = 4.83745
I0405 13:37:10.175603  1863 solver.cpp:237]     Train net output #0: loss = 4.83745 (* 1 = 4.83745 loss)
I0405 13:37:10.175608  1863 sgd_solver.cpp:105] Iteration 2364, lr = 0.001
I0405 13:37:15.584206  1863 solver.cpp:218] Iteration 2376 (2.2187 iter/s, 5.40858s/12 iters), loss = 4.95073
I0405 13:37:15.584259  1863 solver.cpp:237]     Train net output #0: loss = 4.95073 (* 1 = 4.95073 loss)
I0405 13:37:15.584267  1863 sgd_solver.cpp:105] Iteration 2376, lr = 0.001
I0405 13:37:20.683533  1863 solver.cpp:218] Iteration 2388 (2.35328 iter/s, 5.09927s/12 iters), loss = 4.65969
I0405 13:37:20.683574  1863 solver.cpp:237]     Train net output #0: loss = 4.65969 (* 1 = 4.65969 loss)
I0405 13:37:20.683581  1863 sgd_solver.cpp:105] Iteration 2388, lr = 0.001
I0405 13:37:25.905890  1863 solver.cpp:218] Iteration 2400 (2.29784 iter/s, 5.2223s/12 iters), loss = 4.68673
I0405 13:37:25.905933  1863 solver.cpp:237]     Train net output #0: loss = 4.68673 (* 1 = 4.68673 loss)
I0405 13:37:25.905939  1863 sgd_solver.cpp:105] Iteration 2400, lr = 0.001
I0405 13:37:31.187278  1863 solver.cpp:218] Iteration 2412 (2.27216 iter/s, 5.28133s/12 iters), loss = 4.72029
I0405 13:37:31.187320  1863 solver.cpp:237]     Train net output #0: loss = 4.72029 (* 1 = 4.72029 loss)
I0405 13:37:31.187325  1863 sgd_solver.cpp:105] Iteration 2412, lr = 0.001
I0405 13:37:36.500007  1863 solver.cpp:218] Iteration 2424 (2.25875 iter/s, 5.31267s/12 iters), loss = 4.75333
I0405 13:37:36.500149  1863 solver.cpp:237]     Train net output #0: loss = 4.75333 (* 1 = 4.75333 loss)
I0405 13:37:36.500159  1863 sgd_solver.cpp:105] Iteration 2424, lr = 0.001
I0405 13:37:37.621657  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:37:41.883520  1863 solver.cpp:218] Iteration 2436 (2.22909 iter/s, 5.38336s/12 iters), loss = 4.78507
I0405 13:37:41.883574  1863 solver.cpp:237]     Train net output #0: loss = 4.78507 (* 1 = 4.78507 loss)
I0405 13:37:41.883582  1863 sgd_solver.cpp:105] Iteration 2436, lr = 0.001
I0405 13:37:46.697067  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel
I0405 13:37:51.693145  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate
I0405 13:37:54.014827  1863 solver.cpp:330] Iteration 2448, Testing net (#0)
I0405 13:37:54.014853  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:37:57.611774  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:37:58.584141  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0545343
I0405 13:37:58.584185  1863 solver.cpp:397]     Test net output #1: loss = 4.79044 (* 1 = 4.79044 loss)
I0405 13:37:58.722215  1863 solver.cpp:218] Iteration 2448 (0.712647 iter/s, 16.8386s/12 iters), loss = 4.87054
I0405 13:37:58.722261  1863 solver.cpp:237]     Train net output #0: loss = 4.87054 (* 1 = 4.87054 loss)
I0405 13:37:58.722267  1863 sgd_solver.cpp:105] Iteration 2448, lr = 0.001
I0405 13:38:02.958529  1863 solver.cpp:218] Iteration 2460 (2.83269 iter/s, 4.23625s/12 iters), loss = 4.8037
I0405 13:38:02.958585  1863 solver.cpp:237]     Train net output #0: loss = 4.8037 (* 1 = 4.8037 loss)
I0405 13:38:02.958593  1863 sgd_solver.cpp:105] Iteration 2460, lr = 0.001
I0405 13:38:08.053120  1863 solver.cpp:218] Iteration 2472 (2.35547 iter/s, 5.09452s/12 iters), loss = 4.80384
I0405 13:38:08.053277  1863 solver.cpp:237]     Train net output #0: loss = 4.80384 (* 1 = 4.80384 loss)
I0405 13:38:08.053287  1863 sgd_solver.cpp:105] Iteration 2472, lr = 0.001
I0405 13:38:13.201596  1863 solver.cpp:218] Iteration 2484 (2.33086 iter/s, 5.14831s/12 iters), loss = 4.75889
I0405 13:38:13.201647  1863 solver.cpp:237]     Train net output #0: loss = 4.75889 (* 1 = 4.75889 loss)
I0405 13:38:13.201654  1863 sgd_solver.cpp:105] Iteration 2484, lr = 0.001
I0405 13:38:18.496803  1863 solver.cpp:218] Iteration 2496 (2.26623 iter/s, 5.29514s/12 iters), loss = 4.72536
I0405 13:38:18.496850  1863 solver.cpp:237]     Train net output #0: loss = 4.72536 (* 1 = 4.72536 loss)
I0405 13:38:18.496856  1863 sgd_solver.cpp:105] Iteration 2496, lr = 0.001
I0405 13:38:23.888808  1863 solver.cpp:218] Iteration 2508 (2.22554 iter/s, 5.39194s/12 iters), loss = 4.59744
I0405 13:38:23.888864  1863 solver.cpp:237]     Train net output #0: loss = 4.59744 (* 1 = 4.59744 loss)
I0405 13:38:23.888872  1863 sgd_solver.cpp:105] Iteration 2508, lr = 0.001
I0405 13:38:29.162422  1863 solver.cpp:218] Iteration 2520 (2.27551 iter/s, 5.27355s/12 iters), loss = 4.64735
I0405 13:38:29.162461  1863 solver.cpp:237]     Train net output #0: loss = 4.64735 (* 1 = 4.64735 loss)
I0405 13:38:29.162467  1863 sgd_solver.cpp:105] Iteration 2520, lr = 0.001
I0405 13:38:32.282084  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:38:34.370388  1863 solver.cpp:218] Iteration 2532 (2.30418 iter/s, 5.20792s/12 iters), loss = 4.5553
I0405 13:38:34.370424  1863 solver.cpp:237]     Train net output #0: loss = 4.5553 (* 1 = 4.5553 loss)
I0405 13:38:34.370429  1863 sgd_solver.cpp:105] Iteration 2532, lr = 0.001
I0405 13:38:39.845276  1863 solver.cpp:218] Iteration 2544 (2.19184 iter/s, 5.47484s/12 iters), loss = 4.57118
I0405 13:38:39.845399  1863 solver.cpp:237]     Train net output #0: loss = 4.57118 (* 1 = 4.57118 loss)
I0405 13:38:39.845408  1863 sgd_solver.cpp:105] Iteration 2544, lr = 0.001
I0405 13:38:42.113406  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel
I0405 13:38:46.959110  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate
I0405 13:38:49.280514  1863 solver.cpp:330] Iteration 2550, Testing net (#0)
I0405 13:38:49.280536  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:38:52.740450  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:38:53.751958  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0484069
I0405 13:38:53.751996  1863 solver.cpp:397]     Test net output #1: loss = 4.78246 (* 1 = 4.78246 loss)
I0405 13:38:55.645541  1863 solver.cpp:218] Iteration 2556 (0.759487 iter/s, 15.8001s/12 iters), loss = 4.8119
I0405 13:38:55.645584  1863 solver.cpp:237]     Train net output #0: loss = 4.8119 (* 1 = 4.8119 loss)
I0405 13:38:55.645591  1863 sgd_solver.cpp:105] Iteration 2556, lr = 0.001
I0405 13:39:00.731664  1863 solver.cpp:218] Iteration 2568 (2.35939 iter/s, 5.08606s/12 iters), loss = 4.76319
I0405 13:39:00.731710  1863 solver.cpp:237]     Train net output #0: loss = 4.76319 (* 1 = 4.76319 loss)
I0405 13:39:00.731716  1863 sgd_solver.cpp:105] Iteration 2568, lr = 0.001
I0405 13:39:06.006712  1863 solver.cpp:218] Iteration 2580 (2.27489 iter/s, 5.27498s/12 iters), loss = 4.88524
I0405 13:39:06.006769  1863 solver.cpp:237]     Train net output #0: loss = 4.88524 (* 1 = 4.88524 loss)
I0405 13:39:06.006778  1863 sgd_solver.cpp:105] Iteration 2580, lr = 0.001
I0405 13:39:11.042834  1863 solver.cpp:218] Iteration 2592 (2.38282 iter/s, 5.03605s/12 iters), loss = 4.67022
I0405 13:39:11.042984  1863 solver.cpp:237]     Train net output #0: loss = 4.67022 (* 1 = 4.67022 loss)
I0405 13:39:11.042992  1863 sgd_solver.cpp:105] Iteration 2592, lr = 0.001
I0405 13:39:16.202216  1863 solver.cpp:218] Iteration 2604 (2.32593 iter/s, 5.15922s/12 iters), loss = 4.67666
I0405 13:39:16.202271  1863 solver.cpp:237]     Train net output #0: loss = 4.67666 (* 1 = 4.67666 loss)
I0405 13:39:16.202280  1863 sgd_solver.cpp:105] Iteration 2604, lr = 0.001
I0405 13:39:21.610044  1863 solver.cpp:218] Iteration 2616 (2.21903 iter/s, 5.40776s/12 iters), loss = 4.7134
I0405 13:39:21.610105  1863 solver.cpp:237]     Train net output #0: loss = 4.7134 (* 1 = 4.7134 loss)
I0405 13:39:21.610116  1863 sgd_solver.cpp:105] Iteration 2616, lr = 0.001
I0405 13:39:26.691619  1863 solver.cpp:218] Iteration 2628 (2.3615 iter/s, 5.08151s/12 iters), loss = 4.53929
I0405 13:39:26.691656  1863 solver.cpp:237]     Train net output #0: loss = 4.53929 (* 1 = 4.53929 loss)
I0405 13:39:26.691663  1863 sgd_solver.cpp:105] Iteration 2628, lr = 0.001
I0405 13:39:27.164417  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:39:32.012324  1863 solver.cpp:218] Iteration 2640 (2.25536 iter/s, 5.32065s/12 iters), loss = 4.65917
I0405 13:39:32.012372  1863 solver.cpp:237]     Train net output #0: loss = 4.65917 (* 1 = 4.65917 loss)
I0405 13:39:32.012379  1863 sgd_solver.cpp:105] Iteration 2640, lr = 0.001
I0405 13:39:36.836827  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel
I0405 13:39:41.439034  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate
I0405 13:39:43.823316  1863 solver.cpp:330] Iteration 2652, Testing net (#0)
I0405 13:39:43.823341  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:39:47.131237  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:39:48.217651  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0569853
I0405 13:39:48.217689  1863 solver.cpp:397]     Test net output #1: loss = 4.72602 (* 1 = 4.72602 loss)
I0405 13:39:48.359037  1863 solver.cpp:218] Iteration 2652 (0.734095 iter/s, 16.3467s/12 iters), loss = 4.8426
I0405 13:39:48.359098  1863 solver.cpp:237]     Train net output #0: loss = 4.8426 (* 1 = 4.8426 loss)
I0405 13:39:48.359107  1863 sgd_solver.cpp:105] Iteration 2652, lr = 0.001
I0405 13:39:52.490602  1863 solver.cpp:218] Iteration 2664 (2.90452 iter/s, 4.13149s/12 iters), loss = 4.61465
I0405 13:39:52.490648  1863 solver.cpp:237]     Train net output #0: loss = 4.61465 (* 1 = 4.61465 loss)
I0405 13:39:52.490653  1863 sgd_solver.cpp:105] Iteration 2664, lr = 0.001
I0405 13:39:57.914304  1863 solver.cpp:218] Iteration 2676 (2.21253 iter/s, 5.42364s/12 iters), loss = 4.57103
I0405 13:39:57.914342  1863 solver.cpp:237]     Train net output #0: loss = 4.57103 (* 1 = 4.57103 loss)
I0405 13:39:57.914347  1863 sgd_solver.cpp:105] Iteration 2676, lr = 0.001
I0405 13:40:03.342674  1863 solver.cpp:218] Iteration 2688 (2.21063 iter/s, 5.42832s/12 iters), loss = 4.56822
I0405 13:40:03.342728  1863 solver.cpp:237]     Train net output #0: loss = 4.56822 (* 1 = 4.56822 loss)
I0405 13:40:03.342736  1863 sgd_solver.cpp:105] Iteration 2688, lr = 0.001
I0405 13:40:08.748839  1863 solver.cpp:218] Iteration 2700 (2.21972 iter/s, 5.4061s/12 iters), loss = 4.4753
I0405 13:40:08.748903  1863 solver.cpp:237]     Train net output #0: loss = 4.4753 (* 1 = 4.4753 loss)
I0405 13:40:08.748911  1863 sgd_solver.cpp:105] Iteration 2700, lr = 0.001
I0405 13:40:14.017642  1863 solver.cpp:218] Iteration 2712 (2.27759 iter/s, 5.26873s/12 iters), loss = 4.62786
I0405 13:40:14.017813  1863 solver.cpp:237]     Train net output #0: loss = 4.62786 (* 1 = 4.62786 loss)
I0405 13:40:14.017822  1863 sgd_solver.cpp:105] Iteration 2712, lr = 0.001
I0405 13:40:19.400065  1863 solver.cpp:218] Iteration 2724 (2.22955 iter/s, 5.38224s/12 iters), loss = 4.71894
I0405 13:40:19.400110  1863 solver.cpp:237]     Train net output #0: loss = 4.71894 (* 1 = 4.71894 loss)
I0405 13:40:19.400115  1863 sgd_solver.cpp:105] Iteration 2724, lr = 0.001
I0405 13:40:22.180344  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:40:24.871431  1863 solver.cpp:218] Iteration 2736 (2.19326 iter/s, 5.47131s/12 iters), loss = 4.78988
I0405 13:40:24.871470  1863 solver.cpp:237]     Train net output #0: loss = 4.78988 (* 1 = 4.78988 loss)
I0405 13:40:24.871476  1863 sgd_solver.cpp:105] Iteration 2736, lr = 0.001
I0405 13:40:30.256767  1863 solver.cpp:218] Iteration 2748 (2.2283 iter/s, 5.38528s/12 iters), loss = 4.66341
I0405 13:40:30.256816  1863 solver.cpp:237]     Train net output #0: loss = 4.66341 (* 1 = 4.66341 loss)
I0405 13:40:30.256824  1863 sgd_solver.cpp:105] Iteration 2748, lr = 0.001
I0405 13:40:32.354490  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel
I0405 13:40:37.162390  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate
I0405 13:40:39.466331  1863 solver.cpp:330] Iteration 2754, Testing net (#0)
I0405 13:40:39.466352  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:40:42.795569  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:40:43.071382  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:40:44.283265  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0551471
I0405 13:40:44.283397  1863 solver.cpp:397]     Test net output #1: loss = 4.68584 (* 1 = 4.68584 loss)
I0405 13:40:46.105576  1863 solver.cpp:218] Iteration 2760 (0.757157 iter/s, 15.8488s/12 iters), loss = 4.63894
I0405 13:40:46.105615  1863 solver.cpp:237]     Train net output #0: loss = 4.63894 (* 1 = 4.63894 loss)
I0405 13:40:46.105621  1863 sgd_solver.cpp:105] Iteration 2760, lr = 0.001
I0405 13:40:51.291003  1863 solver.cpp:218] Iteration 2772 (2.3142 iter/s, 5.18537s/12 iters), loss = 4.47178
I0405 13:40:51.291056  1863 solver.cpp:237]     Train net output #0: loss = 4.47178 (* 1 = 4.47178 loss)
I0405 13:40:51.291064  1863 sgd_solver.cpp:105] Iteration 2772, lr = 0.001
I0405 13:40:56.565534  1863 solver.cpp:218] Iteration 2784 (2.27511 iter/s, 5.27446s/12 iters), loss = 4.56683
I0405 13:40:56.565582  1863 solver.cpp:237]     Train net output #0: loss = 4.56683 (* 1 = 4.56683 loss)
I0405 13:40:56.565587  1863 sgd_solver.cpp:105] Iteration 2784, lr = 0.001
I0405 13:41:01.865711  1863 solver.cpp:218] Iteration 2796 (2.2641 iter/s, 5.30011s/12 iters), loss = 4.61441
I0405 13:41:01.865761  1863 solver.cpp:237]     Train net output #0: loss = 4.61441 (* 1 = 4.61441 loss)
I0405 13:41:01.865768  1863 sgd_solver.cpp:105] Iteration 2796, lr = 0.001
I0405 13:41:07.090481  1863 solver.cpp:218] Iteration 2808 (2.29678 iter/s, 5.22471s/12 iters), loss = 4.42961
I0405 13:41:07.090525  1863 solver.cpp:237]     Train net output #0: loss = 4.42961 (* 1 = 4.42961 loss)
I0405 13:41:07.090530  1863 sgd_solver.cpp:105] Iteration 2808, lr = 0.001
I0405 13:41:12.180135  1863 solver.cpp:218] Iteration 2820 (2.35775 iter/s, 5.08959s/12 iters), loss = 4.47885
I0405 13:41:12.180181  1863 solver.cpp:237]     Train net output #0: loss = 4.47885 (* 1 = 4.47885 loss)
I0405 13:41:12.180189  1863 sgd_solver.cpp:105] Iteration 2820, lr = 0.001
I0405 13:41:17.109591  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:41:17.439388  1863 solver.cpp:218] Iteration 2832 (2.28172 iter/s, 5.25919s/12 iters), loss = 4.57767
I0405 13:41:17.439435  1863 solver.cpp:237]     Train net output #0: loss = 4.57767 (* 1 = 4.57767 loss)
I0405 13:41:17.439440  1863 sgd_solver.cpp:105] Iteration 2832, lr = 0.001
I0405 13:41:22.685638  1863 solver.cpp:218] Iteration 2844 (2.28737 iter/s, 5.24619s/12 iters), loss = 4.47928
I0405 13:41:22.685693  1863 solver.cpp:237]     Train net output #0: loss = 4.47928 (* 1 = 4.47928 loss)
I0405 13:41:22.685700  1863 sgd_solver.cpp:105] Iteration 2844, lr = 0.001
I0405 13:41:27.364703  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel
I0405 13:41:32.182775  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate
I0405 13:41:34.522908  1863 solver.cpp:330] Iteration 2856, Testing net (#0)
I0405 13:41:34.522930  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:41:37.832262  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:41:38.995558  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0667892
I0405 13:41:38.995589  1863 solver.cpp:397]     Test net output #1: loss = 4.62598 (* 1 = 4.62598 loss)
I0405 13:41:39.136776  1863 solver.cpp:218] Iteration 2856 (0.729435 iter/s, 16.4511s/12 iters), loss = 4.4833
I0405 13:41:39.136829  1863 solver.cpp:237]     Train net output #0: loss = 4.4833 (* 1 = 4.4833 loss)
I0405 13:41:39.136835  1863 sgd_solver.cpp:105] Iteration 2856, lr = 0.001
I0405 13:41:43.200225  1863 solver.cpp:218] Iteration 2868 (2.9532 iter/s, 4.06338s/12 iters), loss = 4.43106
I0405 13:41:43.200264  1863 solver.cpp:237]     Train net output #0: loss = 4.43106 (* 1 = 4.43106 loss)
I0405 13:41:43.200270  1863 sgd_solver.cpp:105] Iteration 2868, lr = 0.001
I0405 13:41:48.558559  1863 solver.cpp:218] Iteration 2880 (2.23952 iter/s, 5.35828s/12 iters), loss = 4.39555
I0405 13:41:48.558689  1863 solver.cpp:237]     Train net output #0: loss = 4.39555 (* 1 = 4.39555 loss)
I0405 13:41:48.558696  1863 sgd_solver.cpp:105] Iteration 2880, lr = 0.001
I0405 13:41:53.759003  1863 solver.cpp:218] Iteration 2892 (2.30756 iter/s, 5.2003s/12 iters), loss = 4.65172
I0405 13:41:53.759043  1863 solver.cpp:237]     Train net output #0: loss = 4.65172 (* 1 = 4.65172 loss)
I0405 13:41:53.759049  1863 sgd_solver.cpp:105] Iteration 2892, lr = 0.001
I0405 13:41:58.995878  1863 solver.cpp:218] Iteration 2904 (2.29147 iter/s, 5.23682s/12 iters), loss = 4.45791
I0405 13:41:58.995919  1863 solver.cpp:237]     Train net output #0: loss = 4.45791 (* 1 = 4.45791 loss)
I0405 13:41:58.995925  1863 sgd_solver.cpp:105] Iteration 2904, lr = 0.001
I0405 13:42:04.274196  1863 solver.cpp:218] Iteration 2916 (2.27348 iter/s, 5.27826s/12 iters), loss = 4.39048
I0405 13:42:04.274240  1863 solver.cpp:237]     Train net output #0: loss = 4.39048 (* 1 = 4.39048 loss)
I0405 13:42:04.274246  1863 sgd_solver.cpp:105] Iteration 2916, lr = 0.001
I0405 13:42:09.340705  1863 solver.cpp:218] Iteration 2928 (2.36852 iter/s, 5.06645s/12 iters), loss = 4.38756
I0405 13:42:09.340756  1863 solver.cpp:237]     Train net output #0: loss = 4.38756 (* 1 = 4.38756 loss)
I0405 13:42:09.340764  1863 sgd_solver.cpp:105] Iteration 2928, lr = 0.001
I0405 13:42:11.237248  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:42:14.435688  1863 solver.cpp:218] Iteration 2940 (2.35529 iter/s, 5.09492s/12 iters), loss = 4.4376
I0405 13:42:14.435729  1863 solver.cpp:237]     Train net output #0: loss = 4.4376 (* 1 = 4.4376 loss)
I0405 13:42:14.435734  1863 sgd_solver.cpp:105] Iteration 2940, lr = 0.001
I0405 13:42:19.728102  1863 solver.cpp:218] Iteration 2952 (2.26742 iter/s, 5.29236s/12 iters), loss = 4.52864
I0405 13:42:19.728225  1863 solver.cpp:237]     Train net output #0: loss = 4.52864 (* 1 = 4.52864 loss)
I0405 13:42:19.728235  1863 sgd_solver.cpp:105] Iteration 2952, lr = 0.001
I0405 13:42:21.945098  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel
I0405 13:42:26.652281  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate
I0405 13:42:29.085446  1863 solver.cpp:330] Iteration 2958, Testing net (#0)
I0405 13:42:29.085467  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:42:32.327105  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:42:33.494715  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0661765
I0405 13:42:33.494747  1863 solver.cpp:397]     Test net output #1: loss = 4.61604 (* 1 = 4.61604 loss)
I0405 13:42:35.325415  1863 solver.cpp:218] Iteration 2964 (0.76937 iter/s, 15.5972s/12 iters), loss = 4.40909
I0405 13:42:35.325467  1863 solver.cpp:237]     Train net output #0: loss = 4.40909 (* 1 = 4.40909 loss)
I0405 13:42:35.325474  1863 sgd_solver.cpp:105] Iteration 2964, lr = 0.001
I0405 13:42:40.579427  1863 solver.cpp:218] Iteration 2976 (2.284 iter/s, 5.25395s/12 iters), loss = 4.45495
I0405 13:42:40.579471  1863 solver.cpp:237]     Train net output #0: loss = 4.45495 (* 1 = 4.45495 loss)
I0405 13:42:40.579478  1863 sgd_solver.cpp:105] Iteration 2976, lr = 0.001
I0405 13:42:45.715445  1863 solver.cpp:218] Iteration 2988 (2.33647 iter/s, 5.13596s/12 iters), loss = 4.64349
I0405 13:42:45.715487  1863 solver.cpp:237]     Train net output #0: loss = 4.64349 (* 1 = 4.64349 loss)
I0405 13:42:45.715492  1863 sgd_solver.cpp:105] Iteration 2988, lr = 0.001
I0405 13:42:51.130779  1863 solver.cpp:218] Iteration 3000 (2.21595 iter/s, 5.41528s/12 iters), loss = 4.58816
I0405 13:42:51.130905  1863 solver.cpp:237]     Train net output #0: loss = 4.58816 (* 1 = 4.58816 loss)
I0405 13:42:51.130913  1863 sgd_solver.cpp:105] Iteration 3000, lr = 0.001
I0405 13:42:56.348832  1863 solver.cpp:218] Iteration 3012 (2.29977 iter/s, 5.21792s/12 iters), loss = 4.47344
I0405 13:42:56.348875  1863 solver.cpp:237]     Train net output #0: loss = 4.47344 (* 1 = 4.47344 loss)
I0405 13:42:56.348881  1863 sgd_solver.cpp:105] Iteration 3012, lr = 0.001
I0405 13:43:01.598547  1863 solver.cpp:218] Iteration 3024 (2.28586 iter/s, 5.24966s/12 iters), loss = 4.41518
I0405 13:43:01.598588  1863 solver.cpp:237]     Train net output #0: loss = 4.41518 (* 1 = 4.41518 loss)
I0405 13:43:01.598593  1863 sgd_solver.cpp:105] Iteration 3024, lr = 0.001
I0405 13:43:05.861940  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:43:06.975443  1863 solver.cpp:218] Iteration 3036 (2.23179 iter/s, 5.37684s/12 iters), loss = 4.41526
I0405 13:43:06.975483  1863 solver.cpp:237]     Train net output #0: loss = 4.41526 (* 1 = 4.41526 loss)
I0405 13:43:06.975488  1863 sgd_solver.cpp:105] Iteration 3036, lr = 0.001
I0405 13:43:12.253966  1863 solver.cpp:218] Iteration 3048 (2.27339 iter/s, 5.27847s/12 iters), loss = 4.44696
I0405 13:43:12.254015  1863 solver.cpp:237]     Train net output #0: loss = 4.44696 (* 1 = 4.44696 loss)
I0405 13:43:12.254024  1863 sgd_solver.cpp:105] Iteration 3048, lr = 0.001
I0405 13:43:17.061794  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel
I0405 13:43:21.685626  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate
I0405 13:43:24.150202  1863 solver.cpp:330] Iteration 3060, Testing net (#0)
I0405 13:43:24.150224  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:43:27.422516  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:43:28.632863  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0710784
I0405 13:43:28.632915  1863 solver.cpp:397]     Test net output #1: loss = 4.55741 (* 1 = 4.55741 loss)
I0405 13:43:28.768508  1863 solver.cpp:218] Iteration 3060 (0.726634 iter/s, 16.5145s/12 iters), loss = 4.5497
I0405 13:43:28.770140  1863 solver.cpp:237]     Train net output #0: loss = 4.5497 (* 1 = 4.5497 loss)
I0405 13:43:28.770153  1863 sgd_solver.cpp:105] Iteration 3060, lr = 0.001
I0405 13:43:33.121943  1863 solver.cpp:218] Iteration 3072 (2.75748 iter/s, 4.3518s/12 iters), loss = 4.50928
I0405 13:43:33.121984  1863 solver.cpp:237]     Train net output #0: loss = 4.50928 (* 1 = 4.50928 loss)
I0405 13:43:33.121989  1863 sgd_solver.cpp:105] Iteration 3072, lr = 0.001
I0405 13:43:38.371610  1863 solver.cpp:218] Iteration 3084 (2.28588 iter/s, 5.24962s/12 iters), loss = 4.46928
I0405 13:43:38.371657  1863 solver.cpp:237]     Train net output #0: loss = 4.46928 (* 1 = 4.46928 loss)
I0405 13:43:38.371665  1863 sgd_solver.cpp:105] Iteration 3084, lr = 0.001
I0405 13:43:43.729786  1863 solver.cpp:218] Iteration 3096 (2.23959 iter/s, 5.35812s/12 iters), loss = 4.1949
I0405 13:43:43.729831  1863 solver.cpp:237]     Train net output #0: loss = 4.1949 (* 1 = 4.1949 loss)
I0405 13:43:43.729836  1863 sgd_solver.cpp:105] Iteration 3096, lr = 0.001
I0405 13:43:49.263053  1863 solver.cpp:218] Iteration 3108 (2.16872 iter/s, 5.53321s/12 iters), loss = 4.29686
I0405 13:43:49.263094  1863 solver.cpp:237]     Train net output #0: loss = 4.29686 (* 1 = 4.29686 loss)
I0405 13:43:49.263100  1863 sgd_solver.cpp:105] Iteration 3108, lr = 0.001
I0405 13:43:54.499891  1863 solver.cpp:218] Iteration 3120 (2.29148 iter/s, 5.23679s/12 iters), loss = 4.53301
I0405 13:43:54.500017  1863 solver.cpp:237]     Train net output #0: loss = 4.53301 (* 1 = 4.53301 loss)
I0405 13:43:54.500025  1863 sgd_solver.cpp:105] Iteration 3120, lr = 0.001
I0405 13:43:59.568166  1863 solver.cpp:218] Iteration 3132 (2.36774 iter/s, 5.06813s/12 iters), loss = 4.49104
I0405 13:43:59.568212  1863 solver.cpp:237]     Train net output #0: loss = 4.49104 (* 1 = 4.49104 loss)
I0405 13:43:59.568217  1863 sgd_solver.cpp:105] Iteration 3132, lr = 0.001
I0405 13:44:00.613890  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:44:04.805022  1863 solver.cpp:218] Iteration 3144 (2.29148 iter/s, 5.2368s/12 iters), loss = 4.38923
I0405 13:44:04.805074  1863 solver.cpp:237]     Train net output #0: loss = 4.38923 (* 1 = 4.38923 loss)
I0405 13:44:04.805081  1863 sgd_solver.cpp:105] Iteration 3144, lr = 0.001
I0405 13:44:10.104565  1863 solver.cpp:218] Iteration 3156 (2.26437 iter/s, 5.29948s/12 iters), loss = 4.4754
I0405 13:44:10.104604  1863 solver.cpp:237]     Train net output #0: loss = 4.4754 (* 1 = 4.4754 loss)
I0405 13:44:10.104609  1863 sgd_solver.cpp:105] Iteration 3156, lr = 0.001
I0405 13:44:12.224720  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel
I0405 13:44:16.629671  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate
I0405 13:44:19.395588  1863 solver.cpp:330] Iteration 3162, Testing net (#0)
I0405 13:44:19.395612  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:44:22.520941  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:44:23.874366  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0765931
I0405 13:44:23.874408  1863 solver.cpp:397]     Test net output #1: loss = 4.50676 (* 1 = 4.50676 loss)
I0405 13:44:25.756321  1863 solver.cpp:218] Iteration 3168 (0.766689 iter/s, 15.6517s/12 iters), loss = 4.46962
I0405 13:44:25.756467  1863 solver.cpp:237]     Train net output #0: loss = 4.46962 (* 1 = 4.46962 loss)
I0405 13:44:25.756479  1863 sgd_solver.cpp:105] Iteration 3168, lr = 0.001
I0405 13:44:30.896858  1863 solver.cpp:218] Iteration 3180 (2.33446 iter/s, 5.14039s/12 iters), loss = 4.30954
I0405 13:44:30.896903  1863 solver.cpp:237]     Train net output #0: loss = 4.30954 (* 1 = 4.30954 loss)
I0405 13:44:30.896908  1863 sgd_solver.cpp:105] Iteration 3180, lr = 0.001
I0405 13:44:36.081418  1863 solver.cpp:218] Iteration 3192 (2.31459 iter/s, 5.1845s/12 iters), loss = 4.3141
I0405 13:44:36.081459  1863 solver.cpp:237]     Train net output #0: loss = 4.3141 (* 1 = 4.3141 loss)
I0405 13:44:36.081465  1863 sgd_solver.cpp:105] Iteration 3192, lr = 0.001
I0405 13:44:41.301159  1863 solver.cpp:218] Iteration 3204 (2.29899 iter/s, 5.21969s/12 iters), loss = 4.3259
I0405 13:44:41.301203  1863 solver.cpp:237]     Train net output #0: loss = 4.3259 (* 1 = 4.3259 loss)
I0405 13:44:41.301208  1863 sgd_solver.cpp:105] Iteration 3204, lr = 0.001
I0405 13:44:46.708711  1863 solver.cpp:218] Iteration 3216 (2.21914 iter/s, 5.4075s/12 iters), loss = 4.27825
I0405 13:44:46.708748  1863 solver.cpp:237]     Train net output #0: loss = 4.27825 (* 1 = 4.27825 loss)
I0405 13:44:46.708755  1863 sgd_solver.cpp:105] Iteration 3216, lr = 0.001
I0405 13:44:51.928556  1863 solver.cpp:218] Iteration 3228 (2.29894 iter/s, 5.2198s/12 iters), loss = 4.21414
I0405 13:44:51.928599  1863 solver.cpp:237]     Train net output #0: loss = 4.21414 (* 1 = 4.21414 loss)
I0405 13:44:51.928604  1863 sgd_solver.cpp:105] Iteration 3228, lr = 0.001
I0405 13:44:55.321730  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:44:57.319288  1863 solver.cpp:218] Iteration 3240 (2.22607 iter/s, 5.39068s/12 iters), loss = 4.36014
I0405 13:44:57.319422  1863 solver.cpp:237]     Train net output #0: loss = 4.36014 (* 1 = 4.36014 loss)
I0405 13:44:57.319428  1863 sgd_solver.cpp:105] Iteration 3240, lr = 0.001
I0405 13:45:02.605448  1863 solver.cpp:218] Iteration 3252 (2.27014 iter/s, 5.28602s/12 iters), loss = 4.2683
I0405 13:45:02.605492  1863 solver.cpp:237]     Train net output #0: loss = 4.2683 (* 1 = 4.2683 loss)
I0405 13:45:02.605497  1863 sgd_solver.cpp:105] Iteration 3252, lr = 0.001
I0405 13:45:07.123754  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel
I0405 13:45:11.646783  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate
I0405 13:45:14.884425  1863 solver.cpp:330] Iteration 3264, Testing net (#0)
I0405 13:45:14.884451  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:45:18.014329  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:45:19.290019  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0704657
I0405 13:45:19.290055  1863 solver.cpp:397]     Test net output #1: loss = 4.50785 (* 1 = 4.50785 loss)
I0405 13:45:19.431218  1863 solver.cpp:218] Iteration 3264 (0.713194 iter/s, 16.8257s/12 iters), loss = 4.36701
I0405 13:45:19.431277  1863 solver.cpp:237]     Train net output #0: loss = 4.36701 (* 1 = 4.36701 loss)
I0405 13:45:19.431284  1863 sgd_solver.cpp:105] Iteration 3264, lr = 0.001
I0405 13:45:23.778715  1863 solver.cpp:218] Iteration 3276 (2.76026 iter/s, 4.34742s/12 iters), loss = 4.24971
I0405 13:45:23.778774  1863 solver.cpp:237]     Train net output #0: loss = 4.24971 (* 1 = 4.24971 loss)
I0405 13:45:23.778784  1863 sgd_solver.cpp:105] Iteration 3276, lr = 0.001
I0405 13:45:29.040448  1863 solver.cpp:218] Iteration 3288 (2.28065 iter/s, 5.26166s/12 iters), loss = 4.43401
I0405 13:45:29.040565  1863 solver.cpp:237]     Train net output #0: loss = 4.43401 (* 1 = 4.43401 loss)
I0405 13:45:29.040573  1863 sgd_solver.cpp:105] Iteration 3288, lr = 0.001
I0405 13:45:34.257745  1863 solver.cpp:218] Iteration 3300 (2.3001 iter/s, 5.21717s/12 iters), loss = 4.28207
I0405 13:45:34.257797  1863 solver.cpp:237]     Train net output #0: loss = 4.28207 (* 1 = 4.28207 loss)
I0405 13:45:34.257804  1863 sgd_solver.cpp:105] Iteration 3300, lr = 0.001
I0405 13:45:39.472398  1863 solver.cpp:218] Iteration 3312 (2.30124 iter/s, 5.21459s/12 iters), loss = 4.12412
I0405 13:45:39.472442  1863 solver.cpp:237]     Train net output #0: loss = 4.12412 (* 1 = 4.12412 loss)
I0405 13:45:39.472448  1863 sgd_solver.cpp:105] Iteration 3312, lr = 0.001
I0405 13:45:44.701594  1863 solver.cpp:218] Iteration 3324 (2.29484 iter/s, 5.22913s/12 iters), loss = 4.35515
I0405 13:45:44.701642  1863 solver.cpp:237]     Train net output #0: loss = 4.35515 (* 1 = 4.35515 loss)
I0405 13:45:44.701647  1863 sgd_solver.cpp:105] Iteration 3324, lr = 0.001
I0405 13:45:50.019524  1863 solver.cpp:218] Iteration 3336 (2.25654 iter/s, 5.31787s/12 iters), loss = 4.26053
I0405 13:45:50.019572  1863 solver.cpp:237]     Train net output #0: loss = 4.26053 (* 1 = 4.26053 loss)
I0405 13:45:50.019579  1863 sgd_solver.cpp:105] Iteration 3336, lr = 0.001
I0405 13:45:50.502121  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:45:55.402153  1863 solver.cpp:218] Iteration 3348 (2.22942 iter/s, 5.38257s/12 iters), loss = 4.24564
I0405 13:45:55.402195  1863 solver.cpp:237]     Train net output #0: loss = 4.24564 (* 1 = 4.24564 loss)
I0405 13:45:55.402200  1863 sgd_solver.cpp:105] Iteration 3348, lr = 0.001
I0405 13:46:00.242874  1863 solver.cpp:218] Iteration 3360 (2.479 iter/s, 4.84066s/12 iters), loss = 4.36346
I0405 13:46:00.243041  1863 solver.cpp:237]     Train net output #0: loss = 4.36346 (* 1 = 4.36346 loss)
I0405 13:46:00.243049  1863 sgd_solver.cpp:105] Iteration 3360, lr = 0.001
I0405 13:46:02.424289  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel
I0405 13:46:07.355748  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate
I0405 13:46:09.997700  1863 solver.cpp:330] Iteration 3366, Testing net (#0)
I0405 13:46:09.997722  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:46:13.027801  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:46:14.336383  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0790441
I0405 13:46:14.336419  1863 solver.cpp:397]     Test net output #1: loss = 4.47505 (* 1 = 4.47505 loss)
I0405 13:46:16.262045  1863 solver.cpp:218] Iteration 3372 (0.74911 iter/s, 16.019s/12 iters), loss = 4.26114
I0405 13:46:16.262089  1863 solver.cpp:237]     Train net output #0: loss = 4.26114 (* 1 = 4.26114 loss)
I0405 13:46:16.262094  1863 sgd_solver.cpp:105] Iteration 3372, lr = 0.001
I0405 13:46:21.141499  1863 solver.cpp:218] Iteration 3384 (2.45932 iter/s, 4.87939s/12 iters), loss = 4.23
I0405 13:46:21.141546  1863 solver.cpp:237]     Train net output #0: loss = 4.23 (* 1 = 4.23 loss)
I0405 13:46:21.141551  1863 sgd_solver.cpp:105] Iteration 3384, lr = 0.001
I0405 13:46:26.423905  1863 solver.cpp:218] Iteration 3396 (2.27172 iter/s, 5.28235s/12 iters), loss = 4.156
I0405 13:46:26.423949  1863 solver.cpp:237]     Train net output #0: loss = 4.156 (* 1 = 4.156 loss)
I0405 13:46:26.423956  1863 sgd_solver.cpp:105] Iteration 3396, lr = 0.001
I0405 13:46:31.564527  1863 solver.cpp:218] Iteration 3408 (2.33438 iter/s, 5.14056s/12 iters), loss = 4.0638
I0405 13:46:31.564656  1863 solver.cpp:237]     Train net output #0: loss = 4.0638 (* 1 = 4.0638 loss)
I0405 13:46:31.564664  1863 sgd_solver.cpp:105] Iteration 3408, lr = 0.001
I0405 13:46:36.741561  1863 solver.cpp:218] Iteration 3420 (2.31799 iter/s, 5.1769s/12 iters), loss = 4.21122
I0405 13:46:36.741600  1863 solver.cpp:237]     Train net output #0: loss = 4.21122 (* 1 = 4.21122 loss)
I0405 13:46:36.741605  1863 sgd_solver.cpp:105] Iteration 3420, lr = 0.001
I0405 13:46:41.992862  1863 solver.cpp:218] Iteration 3432 (2.28517 iter/s, 5.25125s/12 iters), loss = 4.33146
I0405 13:46:41.992905  1863 solver.cpp:237]     Train net output #0: loss = 4.33146 (* 1 = 4.33146 loss)
I0405 13:46:41.992910  1863 sgd_solver.cpp:105] Iteration 3432, lr = 0.001
I0405 13:46:44.727027  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:46:47.322263  1863 solver.cpp:218] Iteration 3444 (2.25168 iter/s, 5.32934s/12 iters), loss = 4.42426
I0405 13:46:47.322319  1863 solver.cpp:237]     Train net output #0: loss = 4.42426 (* 1 = 4.42426 loss)
I0405 13:46:47.322327  1863 sgd_solver.cpp:105] Iteration 3444, lr = 0.001
I0405 13:46:52.721174  1863 solver.cpp:218] Iteration 3456 (2.2227 iter/s, 5.39884s/12 iters), loss = 4.10613
I0405 13:46:52.721213  1863 solver.cpp:237]     Train net output #0: loss = 4.10613 (* 1 = 4.10613 loss)
I0405 13:46:52.721218  1863 sgd_solver.cpp:105] Iteration 3456, lr = 0.001
I0405 13:46:57.389914  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel
I0405 13:47:02.886656  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate
I0405 13:47:05.746229  1863 solver.cpp:330] Iteration 3468, Testing net (#0)
I0405 13:47:05.746255  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:47:06.167265  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:47:08.755335  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:47:10.205718  1863 solver.cpp:397]     Test net output #0: accuracy = 0.088848
I0405 13:47:10.205756  1863 solver.cpp:397]     Test net output #1: loss = 4.41889 (* 1 = 4.41889 loss)
I0405 13:47:10.344821  1863 solver.cpp:218] Iteration 3468 (0.680905 iter/s, 17.6236s/12 iters), loss = 4.1866
I0405 13:47:10.346433  1863 solver.cpp:237]     Train net output #0: loss = 4.1866 (* 1 = 4.1866 loss)
I0405 13:47:10.346446  1863 sgd_solver.cpp:105] Iteration 3468, lr = 0.001
I0405 13:47:14.531587  1863 solver.cpp:218] Iteration 3480 (2.86728 iter/s, 4.18515s/12 iters), loss = 4.16836
I0405 13:47:14.531626  1863 solver.cpp:237]     Train net output #0: loss = 4.16836 (* 1 = 4.16836 loss)
I0405 13:47:14.531631  1863 sgd_solver.cpp:105] Iteration 3480, lr = 0.001
I0405 13:47:19.789039  1863 solver.cpp:218] Iteration 3492 (2.2825 iter/s, 5.2574s/12 iters), loss = 4.14481
I0405 13:47:19.789079  1863 solver.cpp:237]     Train net output #0: loss = 4.14481 (* 1 = 4.14481 loss)
I0405 13:47:19.789085  1863 sgd_solver.cpp:105] Iteration 3492, lr = 0.001
I0405 13:47:24.818336  1863 solver.cpp:218] Iteration 3504 (2.38605 iter/s, 5.02924s/12 iters), loss = 4.27957
I0405 13:47:24.818380  1863 solver.cpp:237]     Train net output #0: loss = 4.27957 (* 1 = 4.27957 loss)
I0405 13:47:24.818388  1863 sgd_solver.cpp:105] Iteration 3504, lr = 0.001
I0405 13:47:30.190292  1863 solver.cpp:218] Iteration 3516 (2.23385 iter/s, 5.3719s/12 iters), loss = 3.94564
I0405 13:47:30.190336  1863 solver.cpp:237]     Train net output #0: loss = 3.94564 (* 1 = 3.94564 loss)
I0405 13:47:30.190342  1863 sgd_solver.cpp:105] Iteration 3516, lr = 0.001
I0405 13:47:35.247326  1863 solver.cpp:218] Iteration 3528 (2.37296 iter/s, 5.05698s/12 iters), loss = 4.06718
I0405 13:47:35.247452  1863 solver.cpp:237]     Train net output #0: loss = 4.06718 (* 1 = 4.06718 loss)
I0405 13:47:35.247459  1863 sgd_solver.cpp:105] Iteration 3528, lr = 0.001
I0405 13:47:40.256115  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:47:40.560075  1863 solver.cpp:218] Iteration 3540 (2.25878 iter/s, 5.31261s/12 iters), loss = 4.15983
I0405 13:47:40.560119  1863 solver.cpp:237]     Train net output #0: loss = 4.15983 (* 1 = 4.15983 loss)
I0405 13:47:40.560125  1863 sgd_solver.cpp:105] Iteration 3540, lr = 0.001
I0405 13:47:45.878432  1863 solver.cpp:218] Iteration 3552 (2.25636 iter/s, 5.3183s/12 iters), loss = 4.31639
I0405 13:47:45.878469  1863 solver.cpp:237]     Train net output #0: loss = 4.31639 (* 1 = 4.31639 loss)
I0405 13:47:45.878474  1863 sgd_solver.cpp:105] Iteration 3552, lr = 0.001
I0405 13:47:51.273037  1863 solver.cpp:218] Iteration 3564 (2.22446 iter/s, 5.39456s/12 iters), loss = 3.87414
I0405 13:47:51.273079  1863 solver.cpp:237]     Train net output #0: loss = 3.87414 (* 1 = 3.87414 loss)
I0405 13:47:51.273087  1863 sgd_solver.cpp:105] Iteration 3564, lr = 0.001
I0405 13:47:53.359275  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel
I0405 13:47:57.783512  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate
I0405 13:48:01.211855  1863 solver.cpp:330] Iteration 3570, Testing net (#0)
I0405 13:48:01.211879  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:48:04.280681  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:48:05.762329  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0980392
I0405 13:48:05.762411  1863 solver.cpp:397]     Test net output #1: loss = 4.33451 (* 1 = 4.33451 loss)
I0405 13:48:07.733115  1863 solver.cpp:218] Iteration 3576 (0.729039 iter/s, 16.46s/12 iters), loss = 4.12797
I0405 13:48:07.733160  1863 solver.cpp:237]     Train net output #0: loss = 4.12797 (* 1 = 4.12797 loss)
I0405 13:48:07.733166  1863 sgd_solver.cpp:105] Iteration 3576, lr = 0.001
I0405 13:48:12.784849  1863 solver.cpp:218] Iteration 3588 (2.37545 iter/s, 5.05167s/12 iters), loss = 3.88531
I0405 13:48:12.784904  1863 solver.cpp:237]     Train net output #0: loss = 3.88531 (* 1 = 3.88531 loss)
I0405 13:48:12.784912  1863 sgd_solver.cpp:105] Iteration 3588, lr = 0.001
I0405 13:48:18.093978  1863 solver.cpp:218] Iteration 3600 (2.26029 iter/s, 5.30906s/12 iters), loss = 4.15101
I0405 13:48:18.094029  1863 solver.cpp:237]     Train net output #0: loss = 4.15101 (* 1 = 4.15101 loss)
I0405 13:48:18.094036  1863 sgd_solver.cpp:105] Iteration 3600, lr = 0.001
I0405 13:48:23.319517  1863 solver.cpp:218] Iteration 3612 (2.29644 iter/s, 5.22548s/12 iters), loss = 4.02096
I0405 13:48:23.319573  1863 solver.cpp:237]     Train net output #0: loss = 4.02096 (* 1 = 4.02096 loss)
I0405 13:48:23.319582  1863 sgd_solver.cpp:105] Iteration 3612, lr = 0.001
I0405 13:48:28.662464  1863 solver.cpp:218] Iteration 3624 (2.24598 iter/s, 5.34289s/12 iters), loss = 4.09458
I0405 13:48:28.662503  1863 solver.cpp:237]     Train net output #0: loss = 4.09458 (* 1 = 4.09458 loss)
I0405 13:48:28.662508  1863 sgd_solver.cpp:105] Iteration 3624, lr = 0.001
I0405 13:48:33.882217  1863 solver.cpp:218] Iteration 3636 (2.29898 iter/s, 5.2197s/12 iters), loss = 3.97506
I0405 13:48:33.882266  1863 solver.cpp:237]     Train net output #0: loss = 3.97506 (* 1 = 3.97506 loss)
I0405 13:48:33.882273  1863 sgd_solver.cpp:105] Iteration 3636, lr = 0.001
I0405 13:48:35.972611  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:48:39.433523  1863 solver.cpp:218] Iteration 3648 (2.16168 iter/s, 5.55125s/12 iters), loss = 3.92565
I0405 13:48:39.433566  1863 solver.cpp:237]     Train net output #0: loss = 3.92565 (* 1 = 3.92565 loss)
I0405 13:48:39.433571  1863 sgd_solver.cpp:105] Iteration 3648, lr = 0.001
I0405 13:48:44.744668  1863 solver.cpp:218] Iteration 3660 (2.25942 iter/s, 5.31109s/12 iters), loss = 4.27384
I0405 13:48:44.744709  1863 solver.cpp:237]     Train net output #0: loss = 4.27384 (* 1 = 4.27384 loss)
I0405 13:48:44.744715  1863 sgd_solver.cpp:105] Iteration 3660, lr = 0.001
I0405 13:48:49.349589  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel
I0405 13:48:53.718588  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate
I0405 13:48:56.663197  1863 solver.cpp:330] Iteration 3672, Testing net (#0)
I0405 13:48:56.663218  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:48:59.555663  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:49:01.024740  1863 solver.cpp:397]     Test net output #0: accuracy = 0.0870098
I0405 13:49:01.024780  1863 solver.cpp:397]     Test net output #1: loss = 4.34208 (* 1 = 4.34208 loss)
I0405 13:49:01.166203  1863 solver.cpp:218] Iteration 3672 (0.73075 iter/s, 16.4215s/12 iters), loss = 3.74511
I0405 13:49:01.166265  1863 solver.cpp:237]     Train net output #0: loss = 3.74511 (* 1 = 3.74511 loss)
I0405 13:49:01.166272  1863 sgd_solver.cpp:105] Iteration 3672, lr = 0.001
I0405 13:49:05.417853  1863 solver.cpp:218] Iteration 3684 (2.82248 iter/s, 4.25158s/12 iters), loss = 4.03594
I0405 13:49:05.417906  1863 solver.cpp:237]     Train net output #0: loss = 4.03594 (* 1 = 4.03594 loss)
I0405 13:49:05.417914  1863 sgd_solver.cpp:105] Iteration 3684, lr = 0.001
I0405 13:49:10.236119  1863 solver.cpp:218] Iteration 3696 (2.49056 iter/s, 4.8182s/12 iters), loss = 4.21558
I0405 13:49:10.236215  1863 solver.cpp:237]     Train net output #0: loss = 4.21558 (* 1 = 4.21558 loss)
I0405 13:49:10.236222  1863 sgd_solver.cpp:105] Iteration 3696, lr = 0.001
I0405 13:49:15.478559  1863 solver.cpp:218] Iteration 3708 (2.28906 iter/s, 5.24233s/12 iters), loss = 4.15281
I0405 13:49:15.478616  1863 solver.cpp:237]     Train net output #0: loss = 4.15281 (* 1 = 4.15281 loss)
I0405 13:49:15.478626  1863 sgd_solver.cpp:105] Iteration 3708, lr = 0.001
I0405 13:49:20.758869  1863 solver.cpp:218] Iteration 3720 (2.27263 iter/s, 5.28024s/12 iters), loss = 4.03825
I0405 13:49:20.758921  1863 solver.cpp:237]     Train net output #0: loss = 4.03825 (* 1 = 4.03825 loss)
I0405 13:49:20.758929  1863 sgd_solver.cpp:105] Iteration 3720, lr = 0.001
I0405 13:49:26.175139  1863 solver.cpp:218] Iteration 3732 (2.21557 iter/s, 5.41621s/12 iters), loss = 3.90901
I0405 13:49:26.175189  1863 solver.cpp:237]     Train net output #0: loss = 3.90901 (* 1 = 3.90901 loss)
I0405 13:49:26.175196  1863 sgd_solver.cpp:105] Iteration 3732, lr = 0.001
I0405 13:49:30.159147  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:49:31.277119  1863 solver.cpp:218] Iteration 3744 (2.35206 iter/s, 5.10192s/12 iters), loss = 4.11425
I0405 13:49:31.277171  1863 solver.cpp:237]     Train net output #0: loss = 4.11425 (* 1 = 4.11425 loss)
I0405 13:49:31.277179  1863 sgd_solver.cpp:105] Iteration 3744, lr = 0.001
I0405 13:49:36.478883  1863 solver.cpp:218] Iteration 3756 (2.30694 iter/s, 5.2017s/12 iters), loss = 4.06517
I0405 13:49:36.478924  1863 solver.cpp:237]     Train net output #0: loss = 4.06517 (* 1 = 4.06517 loss)
I0405 13:49:36.478930  1863 sgd_solver.cpp:105] Iteration 3756, lr = 0.001
I0405 13:49:41.978536  1863 solver.cpp:218] Iteration 3768 (2.18198 iter/s, 5.4996s/12 iters), loss = 4.0104
I0405 13:49:41.978655  1863 solver.cpp:237]     Train net output #0: loss = 4.0104 (* 1 = 4.0104 loss)
I0405 13:49:41.978662  1863 sgd_solver.cpp:105] Iteration 3768, lr = 0.001
I0405 13:49:44.014245  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel
I0405 13:49:48.465888  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate
I0405 13:49:51.644763  1863 solver.cpp:330] Iteration 3774, Testing net (#0)
I0405 13:49:51.644785  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:49:54.450091  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:49:55.923650  1863 solver.cpp:397]     Test net output #0: accuracy = 0.102328
I0405 13:49:55.923688  1863 solver.cpp:397]     Test net output #1: loss = 4.25138 (* 1 = 4.25138 loss)
I0405 13:49:57.811834  1863 solver.cpp:218] Iteration 3780 (0.757902 iter/s, 15.8332s/12 iters), loss = 4.00938
I0405 13:49:57.811885  1863 solver.cpp:237]     Train net output #0: loss = 4.00938 (* 1 = 4.00938 loss)
I0405 13:49:57.811892  1863 sgd_solver.cpp:105] Iteration 3780, lr = 0.001
I0405 13:50:03.036921  1863 solver.cpp:218] Iteration 3792 (2.29664 iter/s, 5.22503s/12 iters), loss = 3.9134
I0405 13:50:03.036957  1863 solver.cpp:237]     Train net output #0: loss = 3.9134 (* 1 = 3.9134 loss)
I0405 13:50:03.036962  1863 sgd_solver.cpp:105] Iteration 3792, lr = 0.001
I0405 13:50:08.383424  1863 solver.cpp:218] Iteration 3804 (2.24448 iter/s, 5.34645s/12 iters), loss = 3.91713
I0405 13:50:08.383479  1863 solver.cpp:237]     Train net output #0: loss = 3.91713 (* 1 = 3.91713 loss)
I0405 13:50:08.383488  1863 sgd_solver.cpp:105] Iteration 3804, lr = 0.001
I0405 13:50:13.616278  1863 solver.cpp:218] Iteration 3816 (2.29323 iter/s, 5.23279s/12 iters), loss = 3.9614
I0405 13:50:13.616389  1863 solver.cpp:237]     Train net output #0: loss = 3.9614 (* 1 = 3.9614 loss)
I0405 13:50:13.616394  1863 sgd_solver.cpp:105] Iteration 3816, lr = 0.001
I0405 13:50:18.895398  1863 solver.cpp:218] Iteration 3828 (2.27316 iter/s, 5.279s/12 iters), loss = 3.82911
I0405 13:50:18.895444  1863 solver.cpp:237]     Train net output #0: loss = 3.82911 (* 1 = 3.82911 loss)
I0405 13:50:18.895449  1863 sgd_solver.cpp:105] Iteration 3828, lr = 0.001
I0405 13:50:24.177304  1863 solver.cpp:218] Iteration 3840 (2.27193 iter/s, 5.28185s/12 iters), loss = 3.89705
I0405 13:50:24.177347  1863 solver.cpp:237]     Train net output #0: loss = 3.89705 (* 1 = 3.89705 loss)
I0405 13:50:24.177356  1863 sgd_solver.cpp:105] Iteration 3840, lr = 0.001
I0405 13:50:25.258111  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:50:29.256422  1863 solver.cpp:218] Iteration 3852 (2.36264 iter/s, 5.07906s/12 iters), loss = 3.98772
I0405 13:50:29.256459  1863 solver.cpp:237]     Train net output #0: loss = 3.98772 (* 1 = 3.98772 loss)
I0405 13:50:29.256464  1863 sgd_solver.cpp:105] Iteration 3852, lr = 0.001
I0405 13:50:34.484371  1863 solver.cpp:218] Iteration 3864 (2.29538 iter/s, 5.2279s/12 iters), loss = 4.10929
I0405 13:50:34.484413  1863 solver.cpp:237]     Train net output #0: loss = 4.10929 (* 1 = 4.10929 loss)
I0405 13:50:34.484418  1863 sgd_solver.cpp:105] Iteration 3864, lr = 0.001
I0405 13:50:39.186122  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel
I0405 13:50:43.680025  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate
I0405 13:50:47.166244  1863 solver.cpp:330] Iteration 3876, Testing net (#0)
I0405 13:50:47.166266  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:50:50.037541  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:50:51.560179  1863 solver.cpp:397]     Test net output #0: accuracy = 0.098652
I0405 13:50:51.560223  1863 solver.cpp:397]     Test net output #1: loss = 4.25724 (* 1 = 4.25724 loss)
I0405 13:50:51.694561  1863 solver.cpp:218] Iteration 3876 (0.697263 iter/s, 17.2101s/12 iters), loss = 3.8791
I0405 13:50:51.694613  1863 solver.cpp:237]     Train net output #0: loss = 3.8791 (* 1 = 3.8791 loss)
I0405 13:50:51.694622  1863 sgd_solver.cpp:105] Iteration 3876, lr = 0.001
I0405 13:50:56.093607  1863 solver.cpp:218] Iteration 3888 (2.72791 iter/s, 4.39898s/12 iters), loss = 3.76428
I0405 13:50:56.093649  1863 solver.cpp:237]     Train net output #0: loss = 3.76428 (* 1 = 3.76428 loss)
I0405 13:50:56.093654  1863 sgd_solver.cpp:105] Iteration 3888, lr = 0.001
I0405 13:51:01.415428  1863 solver.cpp:218] Iteration 3900 (2.25489 iter/s, 5.32176s/12 iters), loss = 3.70815
I0405 13:51:01.415473  1863 solver.cpp:237]     Train net output #0: loss = 3.70815 (* 1 = 3.70815 loss)
I0405 13:51:01.415479  1863 sgd_solver.cpp:105] Iteration 3900, lr = 0.001
I0405 13:51:06.734752  1863 solver.cpp:218] Iteration 3912 (2.25595 iter/s, 5.31927s/12 iters), loss = 3.99968
I0405 13:51:06.734791  1863 solver.cpp:237]     Train net output #0: loss = 3.99968 (* 1 = 3.99968 loss)
I0405 13:51:06.734797  1863 sgd_solver.cpp:105] Iteration 3912, lr = 0.001
I0405 13:51:12.154572  1863 solver.cpp:218] Iteration 3924 (2.21412 iter/s, 5.41976s/12 iters), loss = 3.71245
I0405 13:51:12.154630  1863 solver.cpp:237]     Train net output #0: loss = 3.71245 (* 1 = 3.71245 loss)
I0405 13:51:12.154639  1863 sgd_solver.cpp:105] Iteration 3924, lr = 0.001
I0405 13:51:17.504842  1863 solver.cpp:218] Iteration 3936 (2.24291 iter/s, 5.3502s/12 iters), loss = 3.71677
I0405 13:51:17.504947  1863 solver.cpp:237]     Train net output #0: loss = 3.71677 (* 1 = 3.71677 loss)
I0405 13:51:17.504954  1863 sgd_solver.cpp:105] Iteration 3936, lr = 0.001
I0405 13:51:21.202941  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:51:22.931422  1863 solver.cpp:218] Iteration 3948 (2.21139 iter/s, 5.42646s/12 iters), loss = 3.67197
I0405 13:51:22.931466  1863 solver.cpp:237]     Train net output #0: loss = 3.67197 (* 1 = 3.67197 loss)
I0405 13:51:22.931474  1863 sgd_solver.cpp:105] Iteration 3948, lr = 0.001
I0405 13:51:28.235945  1863 solver.cpp:218] Iteration 3960 (2.26224 iter/s, 5.30447s/12 iters), loss = 3.75034
I0405 13:51:28.235988  1863 solver.cpp:237]     Train net output #0: loss = 3.75034 (* 1 = 3.75034 loss)
I0405 13:51:28.235994  1863 sgd_solver.cpp:105] Iteration 3960, lr = 0.001
I0405 13:51:33.816154  1863 solver.cpp:218] Iteration 3972 (2.15048 iter/s, 5.58014s/12 iters), loss = 3.85041
I0405 13:51:33.816211  1863 solver.cpp:237]     Train net output #0: loss = 3.85041 (* 1 = 3.85041 loss)
I0405 13:51:33.816220  1863 sgd_solver.cpp:105] Iteration 3972, lr = 0.001
I0405 13:51:35.927371  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel
I0405 13:51:40.360447  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate
I0405 13:51:43.232913  1863 solver.cpp:330] Iteration 3978, Testing net (#0)
I0405 13:51:43.232936  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:51:46.003700  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:51:47.562942  1863 solver.cpp:397]     Test net output #0: accuracy = 0.116422
I0405 13:51:47.563035  1863 solver.cpp:397]     Test net output #1: loss = 4.18717 (* 1 = 4.18717 loss)
I0405 13:51:49.485091  1863 solver.cpp:218] Iteration 3984 (0.76585 iter/s, 15.6689s/12 iters), loss = 3.78199
I0405 13:51:49.485141  1863 solver.cpp:237]     Train net output #0: loss = 3.78199 (* 1 = 3.78199 loss)
I0405 13:51:49.485149  1863 sgd_solver.cpp:105] Iteration 3984, lr = 0.001
I0405 13:51:54.813155  1863 solver.cpp:218] Iteration 3996 (2.25225 iter/s, 5.328s/12 iters), loss = 4.03189
I0405 13:51:54.813202  1863 solver.cpp:237]     Train net output #0: loss = 4.03189 (* 1 = 4.03189 loss)
I0405 13:51:54.813210  1863 sgd_solver.cpp:105] Iteration 3996, lr = 0.001
I0405 13:51:59.940028  1863 solver.cpp:218] Iteration 4008 (2.34063 iter/s, 5.12682s/12 iters), loss = 3.5966
I0405 13:51:59.940068  1863 solver.cpp:237]     Train net output #0: loss = 3.5966 (* 1 = 3.5966 loss)
I0405 13:51:59.940074  1863 sgd_solver.cpp:105] Iteration 4008, lr = 0.001
I0405 13:52:05.279757  1863 solver.cpp:218] Iteration 4020 (2.24733 iter/s, 5.33967s/12 iters), loss = 3.80966
I0405 13:52:05.279803  1863 solver.cpp:237]     Train net output #0: loss = 3.80966 (* 1 = 3.80966 loss)
I0405 13:52:05.279811  1863 sgd_solver.cpp:105] Iteration 4020, lr = 0.001
I0405 13:52:10.622164  1863 solver.cpp:218] Iteration 4032 (2.2462 iter/s, 5.34235s/12 iters), loss = 3.67895
I0405 13:52:10.622202  1863 solver.cpp:237]     Train net output #0: loss = 3.67895 (* 1 = 3.67895 loss)
I0405 13:52:10.622208  1863 sgd_solver.cpp:105] Iteration 4032, lr = 0.001
I0405 13:52:16.006940  1863 solver.cpp:218] Iteration 4044 (2.22853 iter/s, 5.38473s/12 iters), loss = 3.73648
I0405 13:52:16.006989  1863 solver.cpp:237]     Train net output #0: loss = 3.73648 (* 1 = 3.73648 loss)
I0405 13:52:16.006994  1863 sgd_solver.cpp:105] Iteration 4044, lr = 0.001
I0405 13:52:16.493417  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:52:21.318123  1863 solver.cpp:218] Iteration 4056 (2.25941 iter/s, 5.31112s/12 iters), loss = 3.84397
I0405 13:52:21.318264  1863 solver.cpp:237]     Train net output #0: loss = 3.84397 (* 1 = 3.84397 loss)
I0405 13:52:21.318271  1863 sgd_solver.cpp:105] Iteration 4056, lr = 0.001
I0405 13:52:26.580005  1863 solver.cpp:218] Iteration 4068 (2.28062 iter/s, 5.26174s/12 iters), loss = 3.8418
I0405 13:52:26.580042  1863 solver.cpp:237]     Train net output #0: loss = 3.8418 (* 1 = 3.8418 loss)
I0405 13:52:26.580049  1863 sgd_solver.cpp:105] Iteration 4068, lr = 0.001
I0405 13:52:31.298216  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel
I0405 13:52:35.708223  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate
I0405 13:52:38.727813  1863 solver.cpp:330] Iteration 4080, Testing net (#0)
I0405 13:52:38.727838  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:52:41.596674  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:52:43.174466  1863 solver.cpp:397]     Test net output #0: accuracy = 0.122549
I0405 13:52:43.174502  1863 solver.cpp:397]     Test net output #1: loss = 4.17174 (* 1 = 4.17174 loss)
I0405 13:52:43.316381  1863 solver.cpp:218] Iteration 4080 (0.717003 iter/s, 16.7363s/12 iters), loss = 3.70291
I0405 13:52:43.316437  1863 solver.cpp:237]     Train net output #0: loss = 3.70291 (* 1 = 3.70291 loss)
I0405 13:52:43.316445  1863 sgd_solver.cpp:105] Iteration 4080, lr = 0.001
I0405 13:52:47.728592  1863 solver.cpp:218] Iteration 4092 (2.71977 iter/s, 4.41214s/12 iters), loss = 3.80721
I0405 13:52:47.728636  1863 solver.cpp:237]     Train net output #0: loss = 3.80721 (* 1 = 3.80721 loss)
I0405 13:52:47.728642  1863 sgd_solver.cpp:105] Iteration 4092, lr = 0.001
I0405 13:52:52.830247  1863 solver.cpp:218] Iteration 4104 (2.3522 iter/s, 5.1016s/12 iters), loss = 3.72282
I0405 13:52:52.830336  1863 solver.cpp:237]     Train net output #0: loss = 3.72282 (* 1 = 3.72282 loss)
I0405 13:52:52.830343  1863 sgd_solver.cpp:105] Iteration 4104, lr = 0.001
I0405 13:52:58.049078  1863 solver.cpp:218] Iteration 4116 (2.29941 iter/s, 5.21874s/12 iters), loss = 3.79289
I0405 13:52:58.049118  1863 solver.cpp:237]     Train net output #0: loss = 3.79289 (* 1 = 3.79289 loss)
I0405 13:52:58.049124  1863 sgd_solver.cpp:105] Iteration 4116, lr = 0.001
I0405 13:53:03.205729  1863 solver.cpp:218] Iteration 4128 (2.32712 iter/s, 5.15659s/12 iters), loss = 3.70976
I0405 13:53:03.205771  1863 solver.cpp:237]     Train net output #0: loss = 3.70976 (* 1 = 3.70976 loss)
I0405 13:53:03.205776  1863 sgd_solver.cpp:105] Iteration 4128, lr = 0.001
I0405 13:53:08.266763  1863 solver.cpp:218] Iteration 4140 (2.37108 iter/s, 5.06099s/12 iters), loss = 3.72833
I0405 13:53:08.266799  1863 solver.cpp:237]     Train net output #0: loss = 3.72833 (* 1 = 3.72833 loss)
I0405 13:53:08.266804  1863 sgd_solver.cpp:105] Iteration 4140, lr = 0.001
I0405 13:53:10.981508  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:53:13.406576  1863 solver.cpp:218] Iteration 4152 (2.33474 iter/s, 5.13976s/12 iters), loss = 3.66105
I0405 13:53:13.406627  1863 solver.cpp:237]     Train net output #0: loss = 3.66105 (* 1 = 3.66105 loss)
I0405 13:53:13.406635  1863 sgd_solver.cpp:105] Iteration 4152, lr = 0.001
I0405 13:53:15.072551  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:53:18.680033  1863 solver.cpp:218] Iteration 4164 (2.27557 iter/s, 5.2734s/12 iters), loss = 3.57206
I0405 13:53:18.680081  1863 solver.cpp:237]     Train net output #0: loss = 3.57206 (* 1 = 3.57206 loss)
I0405 13:53:18.680089  1863 sgd_solver.cpp:105] Iteration 4164, lr = 0.001
I0405 13:53:23.680305  1863 solver.cpp:218] Iteration 4176 (2.3999 iter/s, 5.00021s/12 iters), loss = 3.50177
I0405 13:53:23.680433  1863 solver.cpp:237]     Train net output #0: loss = 3.50177 (* 1 = 3.50177 loss)
I0405 13:53:23.680438  1863 sgd_solver.cpp:105] Iteration 4176, lr = 0.001
I0405 13:53:25.782126  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel
I0405 13:53:30.638248  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate
I0405 13:53:34.808461  1863 solver.cpp:330] Iteration 4182, Testing net (#0)
I0405 13:53:34.808481  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:53:37.477080  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:53:39.101419  1863 solver.cpp:397]     Test net output #0: accuracy = 0.137255
I0405 13:53:39.101456  1863 solver.cpp:397]     Test net output #1: loss = 4.12438 (* 1 = 4.12438 loss)
I0405 13:53:40.956918  1863 solver.cpp:218] Iteration 4188 (0.694586 iter/s, 17.2765s/12 iters), loss = 3.58032
I0405 13:53:40.956959  1863 solver.cpp:237]     Train net output #0: loss = 3.58032 (* 1 = 3.58032 loss)
I0405 13:53:40.956964  1863 sgd_solver.cpp:105] Iteration 4188, lr = 0.001
I0405 13:53:46.185237  1863 solver.cpp:218] Iteration 4200 (2.29522 iter/s, 5.22827s/12 iters), loss = 3.68481
I0405 13:53:46.185287  1863 solver.cpp:237]     Train net output #0: loss = 3.68481 (* 1 = 3.68481 loss)
I0405 13:53:46.185297  1863 sgd_solver.cpp:105] Iteration 4200, lr = 0.001
I0405 13:53:51.407338  1863 solver.cpp:218] Iteration 4212 (2.29795 iter/s, 5.22204s/12 iters), loss = 3.69573
I0405 13:53:51.407382  1863 solver.cpp:237]     Train net output #0: loss = 3.69573 (* 1 = 3.69573 loss)
I0405 13:53:51.407388  1863 sgd_solver.cpp:105] Iteration 4212, lr = 0.001
I0405 13:53:56.837136  1863 solver.cpp:218] Iteration 4224 (2.21005 iter/s, 5.42974s/12 iters), loss = 3.59432
I0405 13:53:56.837218  1863 solver.cpp:237]     Train net output #0: loss = 3.59432 (* 1 = 3.59432 loss)
I0405 13:53:56.837224  1863 sgd_solver.cpp:105] Iteration 4224, lr = 0.001
I0405 13:54:02.185714  1863 solver.cpp:218] Iteration 4236 (2.24363 iter/s, 5.34848s/12 iters), loss = 3.73748
I0405 13:54:02.185763  1863 solver.cpp:237]     Train net output #0: loss = 3.73748 (* 1 = 3.73748 loss)
I0405 13:54:02.185771  1863 sgd_solver.cpp:105] Iteration 4236, lr = 0.001
I0405 13:54:07.078181  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:54:07.355887  1863 solver.cpp:218] Iteration 4248 (2.32103 iter/s, 5.17011s/12 iters), loss = 3.65121
I0405 13:54:07.355943  1863 solver.cpp:237]     Train net output #0: loss = 3.65121 (* 1 = 3.65121 loss)
I0405 13:54:07.355952  1863 sgd_solver.cpp:105] Iteration 4248, lr = 0.001
I0405 13:54:12.745206  1863 solver.cpp:218] Iteration 4260 (2.22666 iter/s, 5.38925s/12 iters), loss = 3.86829
I0405 13:54:12.745265  1863 solver.cpp:237]     Train net output #0: loss = 3.86829 (* 1 = 3.86829 loss)
I0405 13:54:12.745275  1863 sgd_solver.cpp:105] Iteration 4260, lr = 0.001
I0405 13:54:18.067929  1863 solver.cpp:218] Iteration 4272 (2.25451 iter/s, 5.32265s/12 iters), loss = 3.59174
I0405 13:54:18.067970  1863 solver.cpp:237]     Train net output #0: loss = 3.59174 (* 1 = 3.59174 loss)
I0405 13:54:18.067975  1863 sgd_solver.cpp:105] Iteration 4272, lr = 0.001
I0405 13:54:23.016199  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel
I0405 13:54:28.150857  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate
I0405 13:54:33.546031  1863 solver.cpp:330] Iteration 4284, Testing net (#0)
I0405 13:54:33.546057  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:54:36.631204  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:54:38.369062  1863 solver.cpp:397]     Test net output #0: accuracy = 0.135417
I0405 13:54:38.369097  1863 solver.cpp:397]     Test net output #1: loss = 4.15264 (* 1 = 4.15264 loss)
I0405 13:54:38.520119  1863 solver.cpp:218] Iteration 4284 (0.586735 iter/s, 20.4522s/12 iters), loss = 3.63726
I0405 13:54:38.521724  1863 solver.cpp:237]     Train net output #0: loss = 3.63726 (* 1 = 3.63726 loss)
I0405 13:54:38.521739  1863 sgd_solver.cpp:105] Iteration 4284, lr = 0.001
I0405 13:54:42.864284  1863 solver.cpp:218] Iteration 4296 (2.76335 iter/s, 4.34256s/12 iters), loss = 3.45966
I0405 13:54:42.864322  1863 solver.cpp:237]     Train net output #0: loss = 3.45966 (* 1 = 3.45966 loss)
I0405 13:54:42.864327  1863 sgd_solver.cpp:105] Iteration 4296, lr = 0.001
I0405 13:54:48.194057  1863 solver.cpp:218] Iteration 4308 (2.25152 iter/s, 5.32972s/12 iters), loss = 3.66703
I0405 13:54:48.194104  1863 solver.cpp:237]     Train net output #0: loss = 3.66703 (* 1 = 3.66703 loss)
I0405 13:54:48.194113  1863 sgd_solver.cpp:105] Iteration 4308, lr = 0.001
I0405 13:54:53.472843  1863 solver.cpp:218] Iteration 4320 (2.27328 iter/s, 5.27873s/12 iters), loss = 3.45301
I0405 13:54:53.472892  1863 solver.cpp:237]     Train net output #0: loss = 3.45301 (* 1 = 3.45301 loss)
I0405 13:54:53.472898  1863 sgd_solver.cpp:105] Iteration 4320, lr = 0.001
I0405 13:54:58.846385  1863 solver.cpp:218] Iteration 4332 (2.23319 iter/s, 5.37349s/12 iters), loss = 3.47095
I0405 13:54:58.846498  1863 solver.cpp:237]     Train net output #0: loss = 3.47095 (* 1 = 3.47095 loss)
I0405 13:54:58.846506  1863 sgd_solver.cpp:105] Iteration 4332, lr = 0.001
I0405 13:55:04.315459  1863 solver.cpp:218] Iteration 4344 (2.19421 iter/s, 5.46895s/12 iters), loss = 3.58232
I0405 13:55:04.315524  1863 solver.cpp:237]     Train net output #0: loss = 3.58232 (* 1 = 3.58232 loss)
I0405 13:55:04.315533  1863 sgd_solver.cpp:105] Iteration 4344, lr = 0.001
I0405 13:55:06.320456  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:55:09.689357  1863 solver.cpp:218] Iteration 4356 (2.23305 iter/s, 5.37382s/12 iters), loss = 3.39919
I0405 13:55:09.689407  1863 solver.cpp:237]     Train net output #0: loss = 3.39919 (* 1 = 3.39919 loss)
I0405 13:55:09.689414  1863 sgd_solver.cpp:105] Iteration 4356, lr = 0.001
I0405 13:55:14.945993  1863 solver.cpp:218] Iteration 4368 (2.28286 iter/s, 5.25658s/12 iters), loss = 3.74433
I0405 13:55:14.946049  1863 solver.cpp:237]     Train net output #0: loss = 3.74433 (* 1 = 3.74433 loss)
I0405 13:55:14.946058  1863 sgd_solver.cpp:105] Iteration 4368, lr = 0.001
I0405 13:55:20.313216  1863 solver.cpp:218] Iteration 4380 (2.23582 iter/s, 5.36715s/12 iters), loss = 3.39488
I0405 13:55:20.313266  1863 solver.cpp:237]     Train net output #0: loss = 3.39488 (* 1 = 3.39488 loss)
I0405 13:55:20.313273  1863 sgd_solver.cpp:105] Iteration 4380, lr = 0.001
I0405 13:55:22.368000  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel
I0405 13:55:26.979926  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate
I0405 13:55:30.887648  1863 solver.cpp:330] Iteration 4386, Testing net (#0)
I0405 13:55:30.887785  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:55:33.468029  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:55:35.218950  1863 solver.cpp:397]     Test net output #0: accuracy = 0.126838
I0405 13:55:35.218987  1863 solver.cpp:397]     Test net output #1: loss = 4.10294 (* 1 = 4.10294 loss)
I0405 13:55:37.277585  1863 solver.cpp:218] Iteration 4392 (0.707367 iter/s, 16.9643s/12 iters), loss = 3.55174
I0405 13:55:37.277644  1863 solver.cpp:237]     Train net output #0: loss = 3.55174 (* 1 = 3.55174 loss)
I0405 13:55:37.277652  1863 sgd_solver.cpp:105] Iteration 4392, lr = 0.001
I0405 13:55:42.640316  1863 solver.cpp:218] Iteration 4404 (2.2377 iter/s, 5.36266s/12 iters), loss = 3.59786
I0405 13:55:42.640365  1863 solver.cpp:237]     Train net output #0: loss = 3.59786 (* 1 = 3.59786 loss)
I0405 13:55:42.640373  1863 sgd_solver.cpp:105] Iteration 4404, lr = 0.001
I0405 13:55:47.887279  1863 solver.cpp:218] Iteration 4416 (2.28707 iter/s, 5.2469s/12 iters), loss = 3.53144
I0405 13:55:47.887328  1863 solver.cpp:237]     Train net output #0: loss = 3.53144 (* 1 = 3.53144 loss)
I0405 13:55:47.887336  1863 sgd_solver.cpp:105] Iteration 4416, lr = 0.001
I0405 13:55:53.249866  1863 solver.cpp:218] Iteration 4428 (2.23775 iter/s, 5.36252s/12 iters), loss = 3.56733
I0405 13:55:53.249914  1863 solver.cpp:237]     Train net output #0: loss = 3.56733 (* 1 = 3.56733 loss)
I0405 13:55:53.249922  1863 sgd_solver.cpp:105] Iteration 4428, lr = 0.001
I0405 13:55:58.639930  1863 solver.cpp:218] Iteration 4440 (2.22634 iter/s, 5.39s/12 iters), loss = 3.34603
I0405 13:55:58.639976  1863 solver.cpp:237]     Train net output #0: loss = 3.34603 (* 1 = 3.34603 loss)
I0405 13:55:58.639981  1863 sgd_solver.cpp:105] Iteration 4440, lr = 0.001
I0405 13:56:02.692255  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:56:03.831507  1863 solver.cpp:218] Iteration 4452 (2.31146 iter/s, 5.19151s/12 iters), loss = 3.43337
I0405 13:56:03.831558  1863 solver.cpp:237]     Train net output #0: loss = 3.43337 (* 1 = 3.43337 loss)
I0405 13:56:03.831566  1863 sgd_solver.cpp:105] Iteration 4452, lr = 0.001
I0405 13:56:09.188800  1863 solver.cpp:218] Iteration 4464 (2.23996 iter/s, 5.35723s/12 iters), loss = 3.4428
I0405 13:56:09.188846  1863 solver.cpp:237]     Train net output #0: loss = 3.4428 (* 1 = 3.4428 loss)
I0405 13:56:09.188854  1863 sgd_solver.cpp:105] Iteration 4464, lr = 0.001
I0405 13:56:14.365681  1863 solver.cpp:218] Iteration 4476 (2.31802 iter/s, 5.17682s/12 iters), loss = 3.67948
I0405 13:56:14.365726  1863 solver.cpp:237]     Train net output #0: loss = 3.67948 (* 1 = 3.67948 loss)
I0405 13:56:14.365732  1863 sgd_solver.cpp:105] Iteration 4476, lr = 0.001
I0405 13:56:19.042054  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel
I0405 13:56:23.636669  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate
I0405 13:56:27.491526  1863 solver.cpp:330] Iteration 4488, Testing net (#0)
I0405 13:56:27.491549  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:56:30.114301  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:56:31.878721  1863 solver.cpp:397]     Test net output #0: accuracy = 0.137868
I0405 13:56:31.878758  1863 solver.cpp:397]     Test net output #1: loss = 4.12583 (* 1 = 4.12583 loss)
I0405 13:56:32.016916  1863 solver.cpp:218] Iteration 4488 (0.679841 iter/s, 17.6512s/12 iters), loss = 3.53442
I0405 13:56:32.016975  1863 solver.cpp:237]     Train net output #0: loss = 3.53442 (* 1 = 3.53442 loss)
I0405 13:56:32.016983  1863 sgd_solver.cpp:105] Iteration 4488, lr = 0.001
I0405 13:56:36.289465  1863 solver.cpp:218] Iteration 4500 (2.80868 iter/s, 4.27247s/12 iters), loss = 3.69418
I0405 13:56:36.289569  1863 solver.cpp:237]     Train net output #0: loss = 3.69418 (* 1 = 3.69418 loss)
I0405 13:56:36.289579  1863 sgd_solver.cpp:105] Iteration 4500, lr = 0.001
I0405 13:56:41.699322  1863 solver.cpp:218] Iteration 4512 (2.21822 iter/s, 5.40974s/12 iters), loss = 3.50654
I0405 13:56:41.699364  1863 solver.cpp:237]     Train net output #0: loss = 3.50654 (* 1 = 3.50654 loss)
I0405 13:56:41.699370  1863 sgd_solver.cpp:105] Iteration 4512, lr = 0.001
I0405 13:56:47.146656  1863 solver.cpp:218] Iteration 4524 (2.20294 iter/s, 5.44727s/12 iters), loss = 3.2697
I0405 13:56:47.146714  1863 solver.cpp:237]     Train net output #0: loss = 3.2697 (* 1 = 3.2697 loss)
I0405 13:56:47.146723  1863 sgd_solver.cpp:105] Iteration 4524, lr = 0.001
I0405 13:56:52.457029  1863 solver.cpp:218] Iteration 4536 (2.25976 iter/s, 5.3103s/12 iters), loss = 3.47975
I0405 13:56:52.457072  1863 solver.cpp:237]     Train net output #0: loss = 3.47975 (* 1 = 3.47975 loss)
I0405 13:56:52.457078  1863 sgd_solver.cpp:105] Iteration 4536, lr = 0.001
I0405 13:56:57.823668  1863 solver.cpp:218] Iteration 4548 (2.23606 iter/s, 5.36658s/12 iters), loss = 3.48542
I0405 13:56:57.823716  1863 solver.cpp:237]     Train net output #0: loss = 3.48542 (* 1 = 3.48542 loss)
I0405 13:56:57.823722  1863 sgd_solver.cpp:105] Iteration 4548, lr = 0.001
I0405 13:56:59.006808  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:57:03.101186  1863 solver.cpp:218] Iteration 4560 (2.27382 iter/s, 5.27745s/12 iters), loss = 3.37557
I0405 13:57:03.101248  1863 solver.cpp:237]     Train net output #0: loss = 3.37557 (* 1 = 3.37557 loss)
I0405 13:57:03.101258  1863 sgd_solver.cpp:105] Iteration 4560, lr = 0.001
I0405 13:57:08.471060  1863 solver.cpp:218] Iteration 4572 (2.23472 iter/s, 5.3698s/12 iters), loss = 3.70078
I0405 13:57:08.471182  1863 solver.cpp:237]     Train net output #0: loss = 3.70078 (* 1 = 3.70078 loss)
I0405 13:57:08.471189  1863 sgd_solver.cpp:105] Iteration 4572, lr = 0.001
I0405 13:57:13.889273  1863 solver.cpp:218] Iteration 4584 (2.21481 iter/s, 5.41808s/12 iters), loss = 3.37647
I0405 13:57:13.889315  1863 solver.cpp:237]     Train net output #0: loss = 3.37647 (* 1 = 3.37647 loss)
I0405 13:57:13.889320  1863 sgd_solver.cpp:105] Iteration 4584, lr = 0.001
I0405 13:57:16.020396  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel
I0405 13:57:20.624490  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate
I0405 13:57:24.135787  1863 solver.cpp:330] Iteration 4590, Testing net (#0)
I0405 13:57:24.135807  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:57:26.735977  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:57:28.739437  1863 solver.cpp:397]     Test net output #0: accuracy = 0.120711
I0405 13:57:28.739475  1863 solver.cpp:397]     Test net output #1: loss = 4.21656 (* 1 = 4.21656 loss)
I0405 13:57:30.667227  1863 solver.cpp:218] Iteration 4596 (0.715226 iter/s, 16.7779s/12 iters), loss = 3.62827
I0405 13:57:30.667266  1863 solver.cpp:237]     Train net output #0: loss = 3.62827 (* 1 = 3.62827 loss)
I0405 13:57:30.667273  1863 sgd_solver.cpp:105] Iteration 4596, lr = 0.001
I0405 13:57:36.008850  1863 solver.cpp:218] Iteration 4608 (2.24653 iter/s, 5.34157s/12 iters), loss = 3.21174
I0405 13:57:36.008898  1863 solver.cpp:237]     Train net output #0: loss = 3.21174 (* 1 = 3.21174 loss)
I0405 13:57:36.008903  1863 sgd_solver.cpp:105] Iteration 4608, lr = 0.001
I0405 13:57:41.538738  1863 solver.cpp:218] Iteration 4620 (2.17005 iter/s, 5.52983s/12 iters), loss = 3.34676
I0405 13:57:41.538830  1863 solver.cpp:237]     Train net output #0: loss = 3.34676 (* 1 = 3.34676 loss)
I0405 13:57:41.538837  1863 sgd_solver.cpp:105] Iteration 4620, lr = 0.001
I0405 13:57:46.626976  1863 solver.cpp:218] Iteration 4632 (2.35843 iter/s, 5.08813s/12 iters), loss = 3.01417
I0405 13:57:46.627018  1863 solver.cpp:237]     Train net output #0: loss = 3.01417 (* 1 = 3.01417 loss)
I0405 13:57:46.627025  1863 sgd_solver.cpp:105] Iteration 4632, lr = 0.001
I0405 13:57:51.918303  1863 solver.cpp:218] Iteration 4644 (2.26789 iter/s, 5.29127s/12 iters), loss = 3.53171
I0405 13:57:51.918347  1863 solver.cpp:237]     Train net output #0: loss = 3.53171 (* 1 = 3.53171 loss)
I0405 13:57:51.918354  1863 sgd_solver.cpp:105] Iteration 4644, lr = 0.001
I0405 13:57:55.275197  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:57:57.000685  1863 solver.cpp:218] Iteration 4656 (2.36112 iter/s, 5.08233s/12 iters), loss = 3.2745
I0405 13:57:57.000735  1863 solver.cpp:237]     Train net output #0: loss = 3.2745 (* 1 = 3.2745 loss)
I0405 13:57:57.000742  1863 sgd_solver.cpp:105] Iteration 4656, lr = 0.001
I0405 13:58:02.428941  1863 solver.cpp:218] Iteration 4668 (2.21068 iter/s, 5.4282s/12 iters), loss = 3.42032
I0405 13:58:02.428978  1863 solver.cpp:237]     Train net output #0: loss = 3.42032 (* 1 = 3.42032 loss)
I0405 13:58:02.428983  1863 sgd_solver.cpp:105] Iteration 4668, lr = 0.001
I0405 13:58:07.473124  1863 solver.cpp:218] Iteration 4680 (2.379 iter/s, 5.04413s/12 iters), loss = 3.57583
I0405 13:58:07.473176  1863 solver.cpp:237]     Train net output #0: loss = 3.57583 (* 1 = 3.57583 loss)
I0405 13:58:07.473183  1863 sgd_solver.cpp:105] Iteration 4680, lr = 0.001
I0405 13:58:12.273214  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel
I0405 13:58:17.692816  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate
I0405 13:58:22.252835  1863 solver.cpp:330] Iteration 4692, Testing net (#0)
I0405 13:58:22.252854  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:58:24.777547  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:58:26.657670  1863 solver.cpp:397]     Test net output #0: accuracy = 0.117647
I0405 13:58:26.657718  1863 solver.cpp:397]     Test net output #1: loss = 4.26915 (* 1 = 4.26915 loss)
I0405 13:58:26.788347  1863 solver.cpp:218] Iteration 4692 (0.621273 iter/s, 19.3152s/12 iters), loss = 3.31612
I0405 13:58:26.788415  1863 solver.cpp:237]     Train net output #0: loss = 3.31612 (* 1 = 3.31612 loss)
I0405 13:58:26.788424  1863 sgd_solver.cpp:105] Iteration 4692, lr = 0.001
I0405 13:58:31.005484  1863 solver.cpp:218] Iteration 4704 (2.84559 iter/s, 4.21706s/12 iters), loss = 3.24357
I0405 13:58:31.005529  1863 solver.cpp:237]     Train net output #0: loss = 3.24357 (* 1 = 3.24357 loss)
I0405 13:58:31.005537  1863 sgd_solver.cpp:105] Iteration 4704, lr = 0.001
I0405 13:58:36.264086  1863 solver.cpp:218] Iteration 4716 (2.282 iter/s, 5.25854s/12 iters), loss = 3.00887
I0405 13:58:36.264128  1863 solver.cpp:237]     Train net output #0: loss = 3.00887 (* 1 = 3.00887 loss)
I0405 13:58:36.264133  1863 sgd_solver.cpp:105] Iteration 4716, lr = 0.001
I0405 13:58:41.607098  1863 solver.cpp:218] Iteration 4728 (2.24595 iter/s, 5.34295s/12 iters), loss = 3.10048
I0405 13:58:41.607143  1863 solver.cpp:237]     Train net output #0: loss = 3.10048 (* 1 = 3.10048 loss)
I0405 13:58:41.607151  1863 sgd_solver.cpp:105] Iteration 4728, lr = 0.001
I0405 13:58:46.874301  1863 solver.cpp:218] Iteration 4740 (2.27827 iter/s, 5.26714s/12 iters), loss = 3.20764
I0405 13:58:46.874439  1863 solver.cpp:237]     Train net output #0: loss = 3.20764 (* 1 = 3.20764 loss)
I0405 13:58:46.874447  1863 sgd_solver.cpp:105] Iteration 4740, lr = 0.001
I0405 13:58:52.243337  1863 solver.cpp:218] Iteration 4752 (2.2351 iter/s, 5.36889s/12 iters), loss = 3.19415
I0405 13:58:52.243386  1863 solver.cpp:237]     Train net output #0: loss = 3.19415 (* 1 = 3.19415 loss)
I0405 13:58:52.243394  1863 sgd_solver.cpp:105] Iteration 4752, lr = 0.001
I0405 13:58:52.804374  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:58:57.550688  1863 solver.cpp:218] Iteration 4764 (2.26104 iter/s, 5.30729s/12 iters), loss = 3.3831
I0405 13:58:57.550725  1863 solver.cpp:237]     Train net output #0: loss = 3.3831 (* 1 = 3.3831 loss)
I0405 13:58:57.550730  1863 sgd_solver.cpp:105] Iteration 4764, lr = 0.001
I0405 13:59:02.895133  1863 solver.cpp:218] Iteration 4776 (2.24534 iter/s, 5.3444s/12 iters), loss = 3.46546
I0405 13:59:02.895175  1863 solver.cpp:237]     Train net output #0: loss = 3.46546 (* 1 = 3.46546 loss)
I0405 13:59:02.895181  1863 sgd_solver.cpp:105] Iteration 4776, lr = 0.001
I0405 13:59:08.232575  1863 solver.cpp:218] Iteration 4788 (2.24829 iter/s, 5.33739s/12 iters), loss = 3.22529
I0405 13:59:08.232615  1863 solver.cpp:237]     Train net output #0: loss = 3.22529 (* 1 = 3.22529 loss)
I0405 13:59:08.232621  1863 sgd_solver.cpp:105] Iteration 4788, lr = 0.001
I0405 13:59:10.406307  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel
I0405 13:59:15.314366  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate
I0405 13:59:18.853474  1863 solver.cpp:330] Iteration 4794, Testing net (#0)
I0405 13:59:18.853569  1863 net.cpp:676] Ignoring source layer train-data
I0405 13:59:21.254371  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:59:23.130475  1863 solver.cpp:397]     Test net output #0: accuracy = 0.122549
I0405 13:59:23.130507  1863 solver.cpp:397]     Test net output #1: loss = 4.22995 (* 1 = 4.22995 loss)
I0405 13:59:25.065953  1863 solver.cpp:218] Iteration 4800 (0.712871 iter/s, 16.8333s/12 iters), loss = 3.23359
I0405 13:59:25.065994  1863 solver.cpp:237]     Train net output #0: loss = 3.23359 (* 1 = 3.23359 loss)
I0405 13:59:25.065999  1863 sgd_solver.cpp:105] Iteration 4800, lr = 0.001
I0405 13:59:30.135171  1863 solver.cpp:218] Iteration 4812 (2.36725 iter/s, 5.06916s/12 iters), loss = 3.30466
I0405 13:59:30.135227  1863 solver.cpp:237]     Train net output #0: loss = 3.30466 (* 1 = 3.30466 loss)
I0405 13:59:30.135237  1863 sgd_solver.cpp:105] Iteration 4812, lr = 0.001
I0405 13:59:35.370813  1863 solver.cpp:218] Iteration 4824 (2.29201 iter/s, 5.23557s/12 iters), loss = 2.90051
I0405 13:59:35.370857  1863 solver.cpp:237]     Train net output #0: loss = 2.90051 (* 1 = 2.90051 loss)
I0405 13:59:35.370862  1863 sgd_solver.cpp:105] Iteration 4824, lr = 0.001
I0405 13:59:40.735738  1863 solver.cpp:218] Iteration 4836 (2.23677 iter/s, 5.36487s/12 iters), loss = 3.31248
I0405 13:59:40.735787  1863 solver.cpp:237]     Train net output #0: loss = 3.31248 (* 1 = 3.31248 loss)
I0405 13:59:40.735795  1863 sgd_solver.cpp:105] Iteration 4836, lr = 0.001
I0405 13:59:42.813704  1863 blocking_queue.cpp:49] Waiting for data
I0405 13:59:46.052548  1863 solver.cpp:218] Iteration 4848 (2.25702 iter/s, 5.31675s/12 iters), loss = 3.1597
I0405 13:59:46.052600  1863 solver.cpp:237]     Train net output #0: loss = 3.1597 (* 1 = 3.1597 loss)
I0405 13:59:46.052608  1863 sgd_solver.cpp:105] Iteration 4848, lr = 0.001
I0405 13:59:48.912684  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 13:59:51.331115  1863 solver.cpp:218] Iteration 4860 (2.27337 iter/s, 5.27851s/12 iters), loss = 3.22411
I0405 13:59:51.331152  1863 solver.cpp:237]     Train net output #0: loss = 3.22411 (* 1 = 3.22411 loss)
I0405 13:59:51.331157  1863 sgd_solver.cpp:105] Iteration 4860, lr = 0.001
I0405 13:59:56.654256  1863 solver.cpp:218] Iteration 4872 (2.25433 iter/s, 5.32309s/12 iters), loss = 3.0253
I0405 13:59:56.654307  1863 solver.cpp:237]     Train net output #0: loss = 3.0253 (* 1 = 3.0253 loss)
I0405 13:59:56.654315  1863 sgd_solver.cpp:105] Iteration 4872, lr = 0.001
I0405 14:00:01.939527  1863 solver.cpp:218] Iteration 4884 (2.27049 iter/s, 5.28521s/12 iters), loss = 3.18491
I0405 14:00:01.939568  1863 solver.cpp:237]     Train net output #0: loss = 3.18491 (* 1 = 3.18491 loss)
I0405 14:00:01.939574  1863 sgd_solver.cpp:105] Iteration 4884, lr = 0.001
I0405 14:00:06.746706  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel
I0405 14:00:11.913358  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate
I0405 14:00:15.428985  1863 solver.cpp:330] Iteration 4896, Testing net (#0)
I0405 14:00:15.429008  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:00:17.866174  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:00:19.908269  1863 solver.cpp:397]     Test net output #0: accuracy = 0.132966
I0405 14:00:19.908398  1863 solver.cpp:397]     Test net output #1: loss = 4.22818 (* 1 = 4.22818 loss)
I0405 14:00:20.050083  1863 solver.cpp:218] Iteration 4896 (0.662599 iter/s, 18.1105s/12 iters), loss = 3.21523
I0405 14:00:20.050135  1863 solver.cpp:237]     Train net output #0: loss = 3.21523 (* 1 = 3.21523 loss)
I0405 14:00:20.050143  1863 sgd_solver.cpp:105] Iteration 4896, lr = 0.001
I0405 14:00:24.389545  1863 solver.cpp:218] Iteration 4908 (2.76536 iter/s, 4.3394s/12 iters), loss = 3.29155
I0405 14:00:24.389596  1863 solver.cpp:237]     Train net output #0: loss = 3.29155 (* 1 = 3.29155 loss)
I0405 14:00:24.389605  1863 sgd_solver.cpp:105] Iteration 4908, lr = 0.001
I0405 14:00:29.632802  1863 solver.cpp:218] Iteration 4920 (2.28868 iter/s, 5.2432s/12 iters), loss = 3.13985
I0405 14:00:29.632848  1863 solver.cpp:237]     Train net output #0: loss = 3.13985 (* 1 = 3.13985 loss)
I0405 14:00:29.632854  1863 sgd_solver.cpp:105] Iteration 4920, lr = 0.001
I0405 14:00:34.793445  1863 solver.cpp:218] Iteration 4932 (2.32532 iter/s, 5.16059s/12 iters), loss = 2.99179
I0405 14:00:34.793485  1863 solver.cpp:237]     Train net output #0: loss = 2.99179 (* 1 = 2.99179 loss)
I0405 14:00:34.793491  1863 sgd_solver.cpp:105] Iteration 4932, lr = 0.001
I0405 14:00:40.260794  1863 solver.cpp:218] Iteration 4944 (2.19487 iter/s, 5.46729s/12 iters), loss = 3.00572
I0405 14:00:40.260838  1863 solver.cpp:237]     Train net output #0: loss = 3.00572 (* 1 = 3.00572 loss)
I0405 14:00:40.260843  1863 sgd_solver.cpp:105] Iteration 4944, lr = 0.001
I0405 14:00:45.254285  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:00:45.503830  1863 solver.cpp:218] Iteration 4956 (2.28878 iter/s, 5.24298s/12 iters), loss = 3.29523
I0405 14:00:45.503881  1863 solver.cpp:237]     Train net output #0: loss = 3.29523 (* 1 = 3.29523 loss)
I0405 14:00:45.503888  1863 sgd_solver.cpp:105] Iteration 4956, lr = 0.001
I0405 14:00:50.853075  1863 solver.cpp:218] Iteration 4968 (2.24333 iter/s, 5.34919s/12 iters), loss = 3.37145
I0405 14:00:50.853166  1863 solver.cpp:237]     Train net output #0: loss = 3.37145 (* 1 = 3.37145 loss)
I0405 14:00:50.853173  1863 sgd_solver.cpp:105] Iteration 4968, lr = 0.001
I0405 14:00:56.319326  1863 solver.cpp:218] Iteration 4980 (2.19533 iter/s, 5.46615s/12 iters), loss = 3.28584
I0405 14:00:56.319382  1863 solver.cpp:237]     Train net output #0: loss = 3.28584 (* 1 = 3.28584 loss)
I0405 14:00:56.319391  1863 sgd_solver.cpp:105] Iteration 4980, lr = 0.001
I0405 14:01:01.638573  1863 solver.cpp:218] Iteration 4992 (2.25599 iter/s, 5.31918s/12 iters), loss = 3.30852
I0405 14:01:01.638615  1863 solver.cpp:237]     Train net output #0: loss = 3.30852 (* 1 = 3.30852 loss)
I0405 14:01:01.638622  1863 sgd_solver.cpp:105] Iteration 4992, lr = 0.001
I0405 14:01:03.698361  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel
I0405 14:01:08.150911  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate
I0405 14:01:11.334705  1863 solver.cpp:330] Iteration 4998, Testing net (#0)
I0405 14:01:11.334731  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:01:13.722782  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:01:15.725435  1863 solver.cpp:397]     Test net output #0: accuracy = 0.129902
I0405 14:01:15.725471  1863 solver.cpp:397]     Test net output #1: loss = 4.09089 (* 1 = 4.09089 loss)
I0405 14:01:17.710621  1863 solver.cpp:218] Iteration 5004 (0.74664 iter/s, 16.072s/12 iters), loss = 3.01897
I0405 14:01:17.710661  1863 solver.cpp:237]     Train net output #0: loss = 3.01897 (* 1 = 3.01897 loss)
I0405 14:01:17.710666  1863 sgd_solver.cpp:105] Iteration 5004, lr = 0.001
I0405 14:01:22.826094  1863 solver.cpp:218] Iteration 5016 (2.34585 iter/s, 5.11542s/12 iters), loss = 3.09514
I0405 14:01:22.826195  1863 solver.cpp:237]     Train net output #0: loss = 3.09514 (* 1 = 3.09514 loss)
I0405 14:01:22.826201  1863 sgd_solver.cpp:105] Iteration 5016, lr = 0.001
I0405 14:01:28.025920  1863 solver.cpp:218] Iteration 5028 (2.30782 iter/s, 5.19971s/12 iters), loss = 2.80057
I0405 14:01:28.025976  1863 solver.cpp:237]     Train net output #0: loss = 2.80057 (* 1 = 2.80057 loss)
I0405 14:01:28.025986  1863 sgd_solver.cpp:105] Iteration 5028, lr = 0.001
I0405 14:01:33.396859  1863 solver.cpp:218] Iteration 5040 (2.23427 iter/s, 5.37087s/12 iters), loss = 2.75118
I0405 14:01:33.396917  1863 solver.cpp:237]     Train net output #0: loss = 2.75118 (* 1 = 2.75118 loss)
I0405 14:01:33.396926  1863 sgd_solver.cpp:105] Iteration 5040, lr = 0.001
I0405 14:01:38.650019  1863 solver.cpp:218] Iteration 5052 (2.28437 iter/s, 5.25309s/12 iters), loss = 3.07916
I0405 14:01:38.650068  1863 solver.cpp:237]     Train net output #0: loss = 3.07916 (* 1 = 3.07916 loss)
I0405 14:01:38.650079  1863 sgd_solver.cpp:105] Iteration 5052, lr = 0.001
I0405 14:01:40.529136  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:01:43.642925  1863 solver.cpp:218] Iteration 5064 (2.40344 iter/s, 4.99284s/12 iters), loss = 2.79678
I0405 14:01:43.642968  1863 solver.cpp:237]     Train net output #0: loss = 2.79678 (* 1 = 2.79678 loss)
I0405 14:01:43.642974  1863 sgd_solver.cpp:105] Iteration 5064, lr = 0.001
I0405 14:01:48.698935  1863 solver.cpp:218] Iteration 5076 (2.37344 iter/s, 5.05595s/12 iters), loss = 3.0349
I0405 14:01:48.698984  1863 solver.cpp:237]     Train net output #0: loss = 3.0349 (* 1 = 3.0349 loss)
I0405 14:01:48.698992  1863 sgd_solver.cpp:105] Iteration 5076, lr = 0.001
I0405 14:01:53.900460  1863 solver.cpp:218] Iteration 5088 (2.30704 iter/s, 5.20147s/12 iters), loss = 3.10519
I0405 14:01:53.900591  1863 solver.cpp:237]     Train net output #0: loss = 3.10519 (* 1 = 3.10519 loss)
I0405 14:01:53.900599  1863 sgd_solver.cpp:105] Iteration 5088, lr = 0.001
I0405 14:01:58.487118  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel
I0405 14:02:02.989878  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate
I0405 14:02:06.815867  1863 solver.cpp:330] Iteration 5100, Testing net (#0)
I0405 14:02:06.815888  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:02:09.224264  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:02:11.287684  1863 solver.cpp:397]     Test net output #0: accuracy = 0.137868
I0405 14:02:11.287722  1863 solver.cpp:397]     Test net output #1: loss = 4.10494 (* 1 = 4.10494 loss)
I0405 14:02:11.427857  1863 solver.cpp:218] Iteration 5100 (0.684648 iter/s, 17.5273s/12 iters), loss = 2.92715
I0405 14:02:11.427917  1863 solver.cpp:237]     Train net output #0: loss = 2.92715 (* 1 = 2.92715 loss)
I0405 14:02:11.427924  1863 sgd_solver.cpp:105] Iteration 5100, lr = 0.001
I0405 14:02:15.709568  1863 solver.cpp:218] Iteration 5112 (2.80267 iter/s, 4.28163s/12 iters), loss = 2.96095
I0405 14:02:15.709620  1863 solver.cpp:237]     Train net output #0: loss = 2.96095 (* 1 = 2.96095 loss)
I0405 14:02:15.709628  1863 sgd_solver.cpp:105] Iteration 5112, lr = 0.001
I0405 14:02:21.087319  1863 solver.cpp:218] Iteration 5124 (2.23144 iter/s, 5.37769s/12 iters), loss = 3.05647
I0405 14:02:21.087359  1863 solver.cpp:237]     Train net output #0: loss = 3.05647 (* 1 = 3.05647 loss)
I0405 14:02:21.087365  1863 sgd_solver.cpp:105] Iteration 5124, lr = 0.001
I0405 14:02:26.368074  1863 solver.cpp:218] Iteration 5136 (2.27243 iter/s, 5.2807s/12 iters), loss = 3.072
I0405 14:02:26.368208  1863 solver.cpp:237]     Train net output #0: loss = 3.072 (* 1 = 3.072 loss)
I0405 14:02:26.368216  1863 sgd_solver.cpp:105] Iteration 5136, lr = 0.001
I0405 14:02:31.666436  1863 solver.cpp:218] Iteration 5148 (2.26491 iter/s, 5.29822s/12 iters), loss = 2.81222
I0405 14:02:31.666477  1863 solver.cpp:237]     Train net output #0: loss = 2.81222 (* 1 = 2.81222 loss)
I0405 14:02:31.666483  1863 sgd_solver.cpp:105] Iteration 5148, lr = 0.001
I0405 14:02:35.920526  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:02:36.981704  1863 solver.cpp:218] Iteration 5160 (2.25767 iter/s, 5.31521s/12 iters), loss = 2.73326
I0405 14:02:36.981745  1863 solver.cpp:237]     Train net output #0: loss = 2.73326 (* 1 = 2.73326 loss)
I0405 14:02:36.981751  1863 sgd_solver.cpp:105] Iteration 5160, lr = 0.001
I0405 14:02:42.206358  1863 solver.cpp:218] Iteration 5172 (2.29683 iter/s, 5.2246s/12 iters), loss = 3.1716
I0405 14:02:42.206395  1863 solver.cpp:237]     Train net output #0: loss = 3.1716 (* 1 = 3.1716 loss)
I0405 14:02:42.206401  1863 sgd_solver.cpp:105] Iteration 5172, lr = 0.001
I0405 14:02:47.403687  1863 solver.cpp:218] Iteration 5184 (2.3089 iter/s, 5.19728s/12 iters), loss = 3.38644
I0405 14:02:47.403728  1863 solver.cpp:237]     Train net output #0: loss = 3.38644 (* 1 = 3.38644 loss)
I0405 14:02:47.403733  1863 sgd_solver.cpp:105] Iteration 5184, lr = 0.001
I0405 14:02:52.683940  1863 solver.cpp:218] Iteration 5196 (2.27264 iter/s, 5.2802s/12 iters), loss = 2.90183
I0405 14:02:52.683992  1863 solver.cpp:237]     Train net output #0: loss = 2.90183 (* 1 = 2.90183 loss)
I0405 14:02:52.684000  1863 sgd_solver.cpp:105] Iteration 5196, lr = 0.001
I0405 14:02:54.838049  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel
I0405 14:02:59.616570  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate
I0405 14:03:03.602474  1863 solver.cpp:330] Iteration 5202, Testing net (#0)
I0405 14:03:03.602494  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:03:05.910642  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:03:07.985285  1863 solver.cpp:397]     Test net output #0: accuracy = 0.135417
I0405 14:03:07.985318  1863 solver.cpp:397]     Test net output #1: loss = 4.1288 (* 1 = 4.1288 loss)
I0405 14:03:09.736471  1863 solver.cpp:218] Iteration 5208 (0.70371 iter/s, 17.0525s/12 iters), loss = 3.15551
I0405 14:03:09.736513  1863 solver.cpp:237]     Train net output #0: loss = 3.15551 (* 1 = 3.15551 loss)
I0405 14:03:09.736519  1863 sgd_solver.cpp:105] Iteration 5208, lr = 0.001
I0405 14:03:14.967978  1863 solver.cpp:218] Iteration 5220 (2.29382 iter/s, 5.23145s/12 iters), loss = 2.87347
I0405 14:03:14.968021  1863 solver.cpp:237]     Train net output #0: loss = 2.87347 (* 1 = 2.87347 loss)
I0405 14:03:14.968027  1863 sgd_solver.cpp:105] Iteration 5220, lr = 0.001
I0405 14:03:20.419328  1863 solver.cpp:218] Iteration 5232 (2.20131 iter/s, 5.45129s/12 iters), loss = 2.66619
I0405 14:03:20.419384  1863 solver.cpp:237]     Train net output #0: loss = 2.66619 (* 1 = 2.66619 loss)
I0405 14:03:20.419392  1863 sgd_solver.cpp:105] Iteration 5232, lr = 0.001
I0405 14:03:25.759647  1863 solver.cpp:218] Iteration 5244 (2.24708 iter/s, 5.34026s/12 iters), loss = 2.78442
I0405 14:03:25.759685  1863 solver.cpp:237]     Train net output #0: loss = 2.78442 (* 1 = 2.78442 loss)
I0405 14:03:25.759691  1863 sgd_solver.cpp:105] Iteration 5244, lr = 0.001
I0405 14:03:30.975587  1863 solver.cpp:218] Iteration 5256 (2.30066 iter/s, 5.21589s/12 iters), loss = 2.83635
I0405 14:03:30.975720  1863 solver.cpp:237]     Train net output #0: loss = 2.83635 (* 1 = 2.83635 loss)
I0405 14:03:30.975730  1863 sgd_solver.cpp:105] Iteration 5256, lr = 0.001
I0405 14:03:32.255059  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:03:36.192036  1863 solver.cpp:218] Iteration 5268 (2.30048 iter/s, 5.21631s/12 iters), loss = 2.83092
I0405 14:03:36.192087  1863 solver.cpp:237]     Train net output #0: loss = 2.83092 (* 1 = 2.83092 loss)
I0405 14:03:36.192095  1863 sgd_solver.cpp:105] Iteration 5268, lr = 0.001
I0405 14:03:41.464190  1863 solver.cpp:218] Iteration 5280 (2.27614 iter/s, 5.27209s/12 iters), loss = 2.99868
I0405 14:03:41.464234  1863 solver.cpp:237]     Train net output #0: loss = 2.99868 (* 1 = 2.99868 loss)
I0405 14:03:41.464239  1863 sgd_solver.cpp:105] Iteration 5280, lr = 0.001
I0405 14:03:46.759981  1863 solver.cpp:218] Iteration 5292 (2.26597 iter/s, 5.29574s/12 iters), loss = 3.11001
I0405 14:03:46.760021  1863 solver.cpp:237]     Train net output #0: loss = 3.11001 (* 1 = 3.11001 loss)
I0405 14:03:46.760026  1863 sgd_solver.cpp:105] Iteration 5292, lr = 0.001
I0405 14:03:51.605204  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel
I0405 14:03:56.086774  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate
I0405 14:03:59.814692  1863 solver.cpp:330] Iteration 5304, Testing net (#0)
I0405 14:03:59.814718  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:04:02.076081  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:04:04.322582  1863 solver.cpp:397]     Test net output #0: accuracy = 0.128064
I0405 14:04:04.322620  1863 solver.cpp:397]     Test net output #1: loss = 4.18233 (* 1 = 4.18233 loss)
I0405 14:04:04.459900  1863 solver.cpp:218] Iteration 5304 (0.677971 iter/s, 17.6999s/12 iters), loss = 3.16113
I0405 14:04:04.459949  1863 solver.cpp:237]     Train net output #0: loss = 3.16113 (* 1 = 3.16113 loss)
I0405 14:04:04.459954  1863 sgd_solver.cpp:105] Iteration 5304, lr = 0.001
I0405 14:04:08.638118  1863 solver.cpp:218] Iteration 5316 (2.87209 iter/s, 4.17815s/12 iters), loss = 2.80161
I0405 14:04:08.638170  1863 solver.cpp:237]     Train net output #0: loss = 2.80161 (* 1 = 2.80161 loss)
I0405 14:04:08.638178  1863 sgd_solver.cpp:105] Iteration 5316, lr = 0.001
I0405 14:04:13.957738  1863 solver.cpp:218] Iteration 5328 (2.25583 iter/s, 5.31956s/12 iters), loss = 2.64451
I0405 14:04:13.957780  1863 solver.cpp:237]     Train net output #0: loss = 2.64451 (* 1 = 2.64451 loss)
I0405 14:04:13.957785  1863 sgd_solver.cpp:105] Iteration 5328, lr = 0.001
I0405 14:04:19.224893  1863 solver.cpp:218] Iteration 5340 (2.2783 iter/s, 5.26709s/12 iters), loss = 2.64586
I0405 14:04:19.224941  1863 solver.cpp:237]     Train net output #0: loss = 2.64586 (* 1 = 2.64586 loss)
I0405 14:04:19.224947  1863 sgd_solver.cpp:105] Iteration 5340, lr = 0.001
I0405 14:04:24.467311  1863 solver.cpp:218] Iteration 5352 (2.28905 iter/s, 5.24236s/12 iters), loss = 2.53277
I0405 14:04:24.467360  1863 solver.cpp:237]     Train net output #0: loss = 2.53277 (* 1 = 2.53277 loss)
I0405 14:04:24.467368  1863 sgd_solver.cpp:105] Iteration 5352, lr = 0.001
I0405 14:04:27.887244  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:04:29.526273  1863 solver.cpp:218] Iteration 5364 (2.37206 iter/s, 5.0589s/12 iters), loss = 2.95104
I0405 14:04:29.526315  1863 solver.cpp:237]     Train net output #0: loss = 2.95104 (* 1 = 2.95104 loss)
I0405 14:04:29.526321  1863 sgd_solver.cpp:105] Iteration 5364, lr = 0.001
I0405 14:04:35.049646  1863 solver.cpp:218] Iteration 5376 (2.17261 iter/s, 5.52332s/12 iters), loss = 2.78644
I0405 14:04:35.049744  1863 solver.cpp:237]     Train net output #0: loss = 2.78644 (* 1 = 2.78644 loss)
I0405 14:04:35.049751  1863 sgd_solver.cpp:105] Iteration 5376, lr = 0.001
I0405 14:04:40.477752  1863 solver.cpp:218] Iteration 5388 (2.21076 iter/s, 5.42799s/12 iters), loss = 2.94762
I0405 14:04:40.477816  1863 solver.cpp:237]     Train net output #0: loss = 2.94762 (* 1 = 2.94762 loss)
I0405 14:04:40.477828  1863 sgd_solver.cpp:105] Iteration 5388, lr = 0.001
I0405 14:04:45.654011  1863 solver.cpp:218] Iteration 5400 (2.31831 iter/s, 5.17618s/12 iters), loss = 2.8496
I0405 14:04:45.654062  1863 solver.cpp:237]     Train net output #0: loss = 2.8496 (* 1 = 2.8496 loss)
I0405 14:04:45.654069  1863 sgd_solver.cpp:105] Iteration 5400, lr = 0.001
I0405 14:04:47.616009  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel
I0405 14:04:52.173327  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate
I0405 14:04:55.935432  1863 solver.cpp:330] Iteration 5406, Testing net (#0)
I0405 14:04:55.935453  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:04:58.149278  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:05:00.265538  1863 solver.cpp:397]     Test net output #0: accuracy = 0.125613
I0405 14:05:00.265578  1863 solver.cpp:397]     Test net output #1: loss = 4.15383 (* 1 = 4.15383 loss)
I0405 14:05:02.175678  1863 solver.cpp:218] Iteration 5412 (0.726322 iter/s, 16.5216s/12 iters), loss = 3.06335
I0405 14:05:02.175725  1863 solver.cpp:237]     Train net output #0: loss = 3.06335 (* 1 = 3.06335 loss)
I0405 14:05:02.175731  1863 sgd_solver.cpp:105] Iteration 5412, lr = 0.001
I0405 14:05:07.484396  1863 solver.cpp:218] Iteration 5424 (2.26046 iter/s, 5.30866s/12 iters), loss = 2.90298
I0405 14:05:07.484510  1863 solver.cpp:237]     Train net output #0: loss = 2.90298 (* 1 = 2.90298 loss)
I0405 14:05:07.484517  1863 sgd_solver.cpp:105] Iteration 5424, lr = 0.001
I0405 14:05:12.561450  1863 solver.cpp:218] Iteration 5436 (2.36363 iter/s, 5.07693s/12 iters), loss = 2.28696
I0405 14:05:12.561501  1863 solver.cpp:237]     Train net output #0: loss = 2.28696 (* 1 = 2.28696 loss)
I0405 14:05:12.561509  1863 sgd_solver.cpp:105] Iteration 5436, lr = 0.001
I0405 14:05:17.811545  1863 solver.cpp:218] Iteration 5448 (2.2857 iter/s, 5.25003s/12 iters), loss = 2.61031
I0405 14:05:17.811594  1863 solver.cpp:237]     Train net output #0: loss = 2.61031 (* 1 = 2.61031 loss)
I0405 14:05:17.811602  1863 sgd_solver.cpp:105] Iteration 5448, lr = 0.001
I0405 14:05:22.924185  1863 solver.cpp:218] Iteration 5460 (2.34715 iter/s, 5.11257s/12 iters), loss = 2.88191
I0405 14:05:22.924240  1863 solver.cpp:237]     Train net output #0: loss = 2.88191 (* 1 = 2.88191 loss)
I0405 14:05:22.924248  1863 sgd_solver.cpp:105] Iteration 5460, lr = 0.001
I0405 14:05:23.517971  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:05:28.248375  1863 solver.cpp:218] Iteration 5472 (2.25389 iter/s, 5.32412s/12 iters), loss = 2.78344
I0405 14:05:28.248417  1863 solver.cpp:237]     Train net output #0: loss = 2.78344 (* 1 = 2.78344 loss)
I0405 14:05:28.248425  1863 sgd_solver.cpp:105] Iteration 5472, lr = 0.001
I0405 14:05:33.542692  1863 solver.cpp:218] Iteration 5484 (2.2666 iter/s, 5.29426s/12 iters), loss = 2.89303
I0405 14:05:33.542734  1863 solver.cpp:237]     Train net output #0: loss = 2.89303 (* 1 = 2.89303 loss)
I0405 14:05:33.542739  1863 sgd_solver.cpp:105] Iteration 5484, lr = 0.001
I0405 14:05:38.871508  1863 solver.cpp:218] Iteration 5496 (2.25193 iter/s, 5.32876s/12 iters), loss = 3.19012
I0405 14:05:38.871598  1863 solver.cpp:237]     Train net output #0: loss = 3.19012 (* 1 = 3.19012 loss)
I0405 14:05:38.871605  1863 sgd_solver.cpp:105] Iteration 5496, lr = 0.001
I0405 14:05:43.792975  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel
I0405 14:05:48.226594  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate
I0405 14:05:51.488811  1863 solver.cpp:330] Iteration 5508, Testing net (#0)
I0405 14:05:51.488837  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:05:53.679407  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:05:55.900316  1863 solver.cpp:397]     Test net output #0: accuracy = 0.135417
I0405 14:05:55.900354  1863 solver.cpp:397]     Test net output #1: loss = 4.06653 (* 1 = 4.06653 loss)
I0405 14:05:56.036933  1863 solver.cpp:218] Iteration 5508 (0.699083 iter/s, 17.1653s/12 iters), loss = 3.17917
I0405 14:05:56.036985  1863 solver.cpp:237]     Train net output #0: loss = 3.17917 (* 1 = 3.17917 loss)
I0405 14:05:56.036993  1863 sgd_solver.cpp:105] Iteration 5508, lr = 0.001
I0405 14:06:00.405238  1863 solver.cpp:218] Iteration 5520 (2.7471 iter/s, 4.36824s/12 iters), loss = 2.84958
I0405 14:06:00.405282  1863 solver.cpp:237]     Train net output #0: loss = 2.84958 (* 1 = 2.84958 loss)
I0405 14:06:00.405287  1863 sgd_solver.cpp:105] Iteration 5520, lr = 0.001
I0405 14:06:03.117960  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:06:05.779893  1863 solver.cpp:218] Iteration 5532 (2.23272 iter/s, 5.3746s/12 iters), loss = 2.42618
I0405 14:06:05.779938  1863 solver.cpp:237]     Train net output #0: loss = 2.42618 (* 1 = 2.42618 loss)
I0405 14:06:05.779945  1863 sgd_solver.cpp:105] Iteration 5532, lr = 0.001
I0405 14:06:10.832178  1863 solver.cpp:218] Iteration 5544 (2.37519 iter/s, 5.05222s/12 iters), loss = 2.6502
I0405 14:06:10.832307  1863 solver.cpp:237]     Train net output #0: loss = 2.6502 (* 1 = 2.6502 loss)
I0405 14:06:10.832314  1863 sgd_solver.cpp:105] Iteration 5544, lr = 0.001
I0405 14:06:15.934556  1863 solver.cpp:218] Iteration 5556 (2.35191 iter/s, 5.10224s/12 iters), loss = 2.84319
I0405 14:06:15.934612  1863 solver.cpp:237]     Train net output #0: loss = 2.84319 (* 1 = 2.84319 loss)
I0405 14:06:15.934621  1863 sgd_solver.cpp:105] Iteration 5556, lr = 0.001
I0405 14:06:18.793963  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:06:21.299625  1863 solver.cpp:218] Iteration 5568 (2.23672 iter/s, 5.365s/12 iters), loss = 2.96687
I0405 14:06:21.299672  1863 solver.cpp:237]     Train net output #0: loss = 2.96687 (* 1 = 2.96687 loss)
I0405 14:06:21.299680  1863 sgd_solver.cpp:105] Iteration 5568, lr = 0.001
I0405 14:06:26.524554  1863 solver.cpp:218] Iteration 5580 (2.29671 iter/s, 5.22487s/12 iters), loss = 2.65687
I0405 14:06:26.524593  1863 solver.cpp:237]     Train net output #0: loss = 2.65687 (* 1 = 2.65687 loss)
I0405 14:06:26.524598  1863 sgd_solver.cpp:105] Iteration 5580, lr = 0.001
I0405 14:06:31.696846  1863 solver.cpp:218] Iteration 5592 (2.32008 iter/s, 5.17224s/12 iters), loss = 2.79064
I0405 14:06:31.696909  1863 solver.cpp:237]     Train net output #0: loss = 2.79064 (* 1 = 2.79064 loss)
I0405 14:06:31.696919  1863 sgd_solver.cpp:105] Iteration 5592, lr = 0.001
I0405 14:06:37.068917  1863 solver.cpp:218] Iteration 5604 (2.23381 iter/s, 5.372s/12 iters), loss = 2.71741
I0405 14:06:37.068965  1863 solver.cpp:237]     Train net output #0: loss = 2.71741 (* 1 = 2.71741 loss)
I0405 14:06:37.068974  1863 sgd_solver.cpp:105] Iteration 5604, lr = 0.001
I0405 14:06:39.213752  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel
I0405 14:06:43.724261  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate
I0405 14:06:46.861801  1863 solver.cpp:330] Iteration 5610, Testing net (#0)
I0405 14:06:46.861826  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:06:49.092952  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:06:51.330233  1863 solver.cpp:397]     Test net output #0: accuracy = 0.133578
I0405 14:06:51.330276  1863 solver.cpp:397]     Test net output #1: loss = 4.10127 (* 1 = 4.10127 loss)
I0405 14:06:53.337289  1863 solver.cpp:218] Iteration 5616 (0.73763 iter/s, 16.2683s/12 iters), loss = 2.8621
I0405 14:06:53.337334  1863 solver.cpp:237]     Train net output #0: loss = 2.8621 (* 1 = 2.8621 loss)
I0405 14:06:53.337342  1863 sgd_solver.cpp:105] Iteration 5616, lr = 0.001
I0405 14:06:58.451557  1863 solver.cpp:218] Iteration 5628 (2.3464 iter/s, 5.11421s/12 iters), loss = 2.48159
I0405 14:06:58.451604  1863 solver.cpp:237]     Train net output #0: loss = 2.48159 (* 1 = 2.48159 loss)
I0405 14:06:58.451612  1863 sgd_solver.cpp:105] Iteration 5628, lr = 0.001
I0405 14:07:03.875972  1863 solver.cpp:218] Iteration 5640 (2.21225 iter/s, 5.42435s/12 iters), loss = 2.23974
I0405 14:07:03.876019  1863 solver.cpp:237]     Train net output #0: loss = 2.23974 (* 1 = 2.23974 loss)
I0405 14:07:03.876026  1863 sgd_solver.cpp:105] Iteration 5640, lr = 0.001
I0405 14:07:09.058176  1863 solver.cpp:218] Iteration 5652 (2.31564 iter/s, 5.18215s/12 iters), loss = 2.45293
I0405 14:07:09.058216  1863 solver.cpp:237]     Train net output #0: loss = 2.45293 (* 1 = 2.45293 loss)
I0405 14:07:09.058223  1863 sgd_solver.cpp:105] Iteration 5652, lr = 0.001
I0405 14:07:14.208236  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:07:14.428190  1863 solver.cpp:218] Iteration 5664 (2.23465 iter/s, 5.36996s/12 iters), loss = 2.87022
I0405 14:07:14.428226  1863 solver.cpp:237]     Train net output #0: loss = 2.87022 (* 1 = 2.87022 loss)
I0405 14:07:14.428232  1863 sgd_solver.cpp:105] Iteration 5664, lr = 0.001
I0405 14:07:19.714854  1863 solver.cpp:218] Iteration 5676 (2.26988 iter/s, 5.28661s/12 iters), loss = 3.06967
I0405 14:07:19.714908  1863 solver.cpp:237]     Train net output #0: loss = 3.06967 (* 1 = 3.06967 loss)
I0405 14:07:19.714916  1863 sgd_solver.cpp:105] Iteration 5676, lr = 0.001
I0405 14:07:25.127112  1863 solver.cpp:218] Iteration 5688 (2.21722 iter/s, 5.41219s/12 iters), loss = 2.85032
I0405 14:07:25.127164  1863 solver.cpp:237]     Train net output #0: loss = 2.85032 (* 1 = 2.85032 loss)
I0405 14:07:25.127173  1863 sgd_solver.cpp:105] Iteration 5688, lr = 0.001
I0405 14:07:30.457787  1863 solver.cpp:218] Iteration 5700 (2.25115 iter/s, 5.33062s/12 iters), loss = 2.99106
I0405 14:07:30.457828  1863 solver.cpp:237]     Train net output #0: loss = 2.99106 (* 1 = 2.99106 loss)
I0405 14:07:30.457834  1863 sgd_solver.cpp:105] Iteration 5700, lr = 0.001
I0405 14:07:35.298949  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel
I0405 14:07:39.800978  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate
I0405 14:07:42.317464  1863 solver.cpp:330] Iteration 5712, Testing net (#0)
I0405 14:07:42.317483  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:07:44.489537  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:07:46.703534  1863 solver.cpp:397]     Test net output #0: accuracy = 0.153799
I0405 14:07:46.703568  1863 solver.cpp:397]     Test net output #1: loss = 4.06751 (* 1 = 4.06751 loss)
I0405 14:07:46.845149  1863 solver.cpp:218] Iteration 5712 (0.732274 iter/s, 16.3873s/12 iters), loss = 2.68806
I0405 14:07:46.845191  1863 solver.cpp:237]     Train net output #0: loss = 2.68806 (* 1 = 2.68806 loss)
I0405 14:07:46.845196  1863 sgd_solver.cpp:105] Iteration 5712, lr = 0.001
I0405 14:07:51.155544  1863 solver.cpp:218] Iteration 5724 (2.78401 iter/s, 4.31033s/12 iters), loss = 2.90438
I0405 14:07:51.155604  1863 solver.cpp:237]     Train net output #0: loss = 2.90438 (* 1 = 2.90438 loss)
I0405 14:07:51.155612  1863 sgd_solver.cpp:105] Iteration 5724, lr = 0.001
I0405 14:07:56.205018  1863 solver.cpp:218] Iteration 5736 (2.37652 iter/s, 5.04941s/12 iters), loss = 2.2755
I0405 14:07:56.205054  1863 solver.cpp:237]     Train net output #0: loss = 2.2755 (* 1 = 2.2755 loss)
I0405 14:07:56.205060  1863 sgd_solver.cpp:105] Iteration 5736, lr = 0.001
I0405 14:08:01.628669  1863 solver.cpp:218] Iteration 5748 (2.21255 iter/s, 5.4236s/12 iters), loss = 2.43793
I0405 14:08:01.628708  1863 solver.cpp:237]     Train net output #0: loss = 2.43793 (* 1 = 2.43793 loss)
I0405 14:08:01.628715  1863 sgd_solver.cpp:105] Iteration 5748, lr = 0.001
I0405 14:08:06.907184  1863 solver.cpp:218] Iteration 5760 (2.27339 iter/s, 5.27846s/12 iters), loss = 2.50697
I0405 14:08:06.907224  1863 solver.cpp:237]     Train net output #0: loss = 2.50697 (* 1 = 2.50697 loss)
I0405 14:08:06.907230  1863 sgd_solver.cpp:105] Iteration 5760, lr = 0.001
I0405 14:08:08.835976  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:08:12.138504  1863 solver.cpp:218] Iteration 5772 (2.2939 iter/s, 5.23127s/12 iters), loss = 2.36959
I0405 14:08:12.138545  1863 solver.cpp:237]     Train net output #0: loss = 2.36959 (* 1 = 2.36959 loss)
I0405 14:08:12.138550  1863 sgd_solver.cpp:105] Iteration 5772, lr = 0.001
I0405 14:08:17.465106  1863 solver.cpp:218] Iteration 5784 (2.25287 iter/s, 5.32655s/12 iters), loss = 2.63095
I0405 14:08:17.465220  1863 solver.cpp:237]     Train net output #0: loss = 2.63095 (* 1 = 2.63095 loss)
I0405 14:08:17.465226  1863 sgd_solver.cpp:105] Iteration 5784, lr = 0.001
I0405 14:08:22.909034  1863 solver.cpp:218] Iteration 5796 (2.20434 iter/s, 5.4438s/12 iters), loss = 2.3403
I0405 14:08:22.909091  1863 solver.cpp:237]     Train net output #0: loss = 2.3403 (* 1 = 2.3403 loss)
I0405 14:08:22.909101  1863 sgd_solver.cpp:105] Iteration 5796, lr = 0.001
I0405 14:08:28.281695  1863 solver.cpp:218] Iteration 5808 (2.23356 iter/s, 5.37259s/12 iters), loss = 2.5039
I0405 14:08:28.281741  1863 solver.cpp:237]     Train net output #0: loss = 2.5039 (* 1 = 2.5039 loss)
I0405 14:08:28.281749  1863 sgd_solver.cpp:105] Iteration 5808, lr = 0.001
I0405 14:08:30.333066  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel
I0405 14:08:34.626477  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate
I0405 14:08:37.323173  1863 solver.cpp:330] Iteration 5814, Testing net (#0)
I0405 14:08:37.323195  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:08:39.459295  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:08:41.727756  1863 solver.cpp:397]     Test net output #0: accuracy = 0.158088
I0405 14:08:41.727790  1863 solver.cpp:397]     Test net output #1: loss = 4.03705 (* 1 = 4.03705 loss)
I0405 14:08:43.598994  1863 solver.cpp:218] Iteration 5820 (0.783431 iter/s, 15.3172s/12 iters), loss = 2.68114
I0405 14:08:43.599045  1863 solver.cpp:237]     Train net output #0: loss = 2.68114 (* 1 = 2.68114 loss)
I0405 14:08:43.599053  1863 sgd_solver.cpp:105] Iteration 5820, lr = 0.001
I0405 14:08:48.777704  1863 solver.cpp:218] Iteration 5832 (2.31721 iter/s, 5.17865s/12 iters), loss = 2.60981
I0405 14:08:48.777827  1863 solver.cpp:237]     Train net output #0: loss = 2.60981 (* 1 = 2.60981 loss)
I0405 14:08:48.777833  1863 sgd_solver.cpp:105] Iteration 5832, lr = 0.001
I0405 14:08:54.139940  1863 solver.cpp:218] Iteration 5844 (2.23793 iter/s, 5.3621s/12 iters), loss = 2.22772
I0405 14:08:54.139999  1863 solver.cpp:237]     Train net output #0: loss = 2.22772 (* 1 = 2.22772 loss)
I0405 14:08:54.140008  1863 sgd_solver.cpp:105] Iteration 5844, lr = 0.001
I0405 14:08:59.503443  1863 solver.cpp:218] Iteration 5856 (2.23737 iter/s, 5.36343s/12 iters), loss = 2.02028
I0405 14:08:59.503496  1863 solver.cpp:237]     Train net output #0: loss = 2.02028 (* 1 = 2.02028 loss)
I0405 14:08:59.503505  1863 sgd_solver.cpp:105] Iteration 5856, lr = 0.001
I0405 14:09:03.904392  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:09:04.802222  1863 solver.cpp:218] Iteration 5868 (2.2647 iter/s, 5.29871s/12 iters), loss = 2.71389
I0405 14:09:04.802265  1863 solver.cpp:237]     Train net output #0: loss = 2.71389 (* 1 = 2.71389 loss)
I0405 14:09:04.802270  1863 sgd_solver.cpp:105] Iteration 5868, lr = 0.001
I0405 14:09:10.029556  1863 solver.cpp:218] Iteration 5880 (2.29565 iter/s, 5.22728s/12 iters), loss = 2.54086
I0405 14:09:10.029595  1863 solver.cpp:237]     Train net output #0: loss = 2.54086 (* 1 = 2.54086 loss)
I0405 14:09:10.029600  1863 sgd_solver.cpp:105] Iteration 5880, lr = 0.001
I0405 14:09:15.254001  1863 solver.cpp:218] Iteration 5892 (2.29692 iter/s, 5.2244s/12 iters), loss = 2.33711
I0405 14:09:15.254042  1863 solver.cpp:237]     Train net output #0: loss = 2.33711 (* 1 = 2.33711 loss)
I0405 14:09:15.254050  1863 sgd_solver.cpp:105] Iteration 5892, lr = 0.001
I0405 14:09:20.809286  1863 solver.cpp:218] Iteration 5904 (2.16012 iter/s, 5.55523s/12 iters), loss = 2.28211
I0405 14:09:20.809393  1863 solver.cpp:237]     Train net output #0: loss = 2.28211 (* 1 = 2.28211 loss)
I0405 14:09:20.809401  1863 sgd_solver.cpp:105] Iteration 5904, lr = 0.001
I0405 14:09:25.537699  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel
I0405 14:09:29.922399  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate
I0405 14:09:32.415645  1863 solver.cpp:330] Iteration 5916, Testing net (#0)
I0405 14:09:32.415665  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:09:34.516817  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:09:36.941696  1863 solver.cpp:397]     Test net output #0: accuracy = 0.164216
I0405 14:09:36.941735  1863 solver.cpp:397]     Test net output #1: loss = 4.07241 (* 1 = 4.07241 loss)
I0405 14:09:37.083513  1863 solver.cpp:218] Iteration 5916 (0.737367 iter/s, 16.2741s/12 iters), loss = 2.39762
I0405 14:09:37.085089  1863 solver.cpp:237]     Train net output #0: loss = 2.39762 (* 1 = 2.39762 loss)
I0405 14:09:37.085101  1863 sgd_solver.cpp:105] Iteration 5916, lr = 0.001
I0405 14:09:41.429643  1863 solver.cpp:218] Iteration 5928 (2.76208 iter/s, 4.34455s/12 iters), loss = 2.43677
I0405 14:09:41.429697  1863 solver.cpp:237]     Train net output #0: loss = 2.43677 (* 1 = 2.43677 loss)
I0405 14:09:41.429706  1863 sgd_solver.cpp:105] Iteration 5928, lr = 0.001
I0405 14:09:46.672966  1863 solver.cpp:218] Iteration 5940 (2.28865 iter/s, 5.24326s/12 iters), loss = 2.02164
I0405 14:09:46.673003  1863 solver.cpp:237]     Train net output #0: loss = 2.02164 (* 1 = 2.02164 loss)
I0405 14:09:46.673009  1863 sgd_solver.cpp:105] Iteration 5940, lr = 0.001
I0405 14:09:51.687943  1863 solver.cpp:218] Iteration 5952 (2.39286 iter/s, 5.01493s/12 iters), loss = 2.61348
I0405 14:09:51.688099  1863 solver.cpp:237]     Train net output #0: loss = 2.61348 (* 1 = 2.61348 loss)
I0405 14:09:51.688109  1863 sgd_solver.cpp:105] Iteration 5952, lr = 0.001
I0405 14:09:57.196422  1863 solver.cpp:218] Iteration 5964 (2.17853 iter/s, 5.50831s/12 iters), loss = 2.32701
I0405 14:09:57.196466  1863 solver.cpp:237]     Train net output #0: loss = 2.32701 (* 1 = 2.32701 loss)
I0405 14:09:57.196473  1863 sgd_solver.cpp:105] Iteration 5964, lr = 0.001
I0405 14:09:58.617558  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:10:02.431316  1863 solver.cpp:218] Iteration 5976 (2.29233 iter/s, 5.23484s/12 iters), loss = 2.38901
I0405 14:10:02.431360  1863 solver.cpp:237]     Train net output #0: loss = 2.38901 (* 1 = 2.38901 loss)
I0405 14:10:02.431366  1863 sgd_solver.cpp:105] Iteration 5976, lr = 0.001
I0405 14:10:07.882412  1863 solver.cpp:218] Iteration 5988 (2.20142 iter/s, 5.45103s/12 iters), loss = 2.23348
I0405 14:10:07.882472  1863 solver.cpp:237]     Train net output #0: loss = 2.23348 (* 1 = 2.23348 loss)
I0405 14:10:07.882479  1863 sgd_solver.cpp:105] Iteration 5988, lr = 0.001
I0405 14:10:13.197244  1863 solver.cpp:218] Iteration 6000 (2.25786 iter/s, 5.31476s/12 iters), loss = 2.52407
I0405 14:10:13.197295  1863 solver.cpp:237]     Train net output #0: loss = 2.52407 (* 1 = 2.52407 loss)
I0405 14:10:13.197304  1863 sgd_solver.cpp:105] Iteration 6000, lr = 0.001
I0405 14:10:18.518934  1863 solver.cpp:218] Iteration 6012 (2.25495 iter/s, 5.32163s/12 iters), loss = 2.23845
I0405 14:10:18.518981  1863 solver.cpp:237]     Train net output #0: loss = 2.23845 (* 1 = 2.23845 loss)
I0405 14:10:18.518988  1863 sgd_solver.cpp:105] Iteration 6012, lr = 0.001
I0405 14:10:20.588392  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel
I0405 14:10:24.986346  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate
I0405 14:10:27.370276  1863 solver.cpp:330] Iteration 6018, Testing net (#0)
I0405 14:10:27.370296  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:10:29.313211  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:10:31.646396  1863 solver.cpp:397]     Test net output #0: accuracy = 0.167892
I0405 14:10:31.646428  1863 solver.cpp:397]     Test net output #1: loss = 4.06586 (* 1 = 4.06586 loss)
I0405 14:10:33.543723  1863 solver.cpp:218] Iteration 6024 (0.798683 iter/s, 15.0247s/12 iters), loss = 2.28912
I0405 14:10:33.543782  1863 solver.cpp:237]     Train net output #0: loss = 2.28912 (* 1 = 2.28912 loss)
I0405 14:10:33.543792  1863 sgd_solver.cpp:105] Iteration 6024, lr = 0.001
I0405 14:10:38.701941  1863 solver.cpp:218] Iteration 6036 (2.32642 iter/s, 5.15815s/12 iters), loss = 1.98871
I0405 14:10:38.701982  1863 solver.cpp:237]     Train net output #0: loss = 1.98871 (* 1 = 1.98871 loss)
I0405 14:10:38.701987  1863 sgd_solver.cpp:105] Iteration 6036, lr = 0.001
I0405 14:10:44.031239  1863 solver.cpp:218] Iteration 6048 (2.25173 iter/s, 5.32924s/12 iters), loss = 1.88219
I0405 14:10:44.031291  1863 solver.cpp:237]     Train net output #0: loss = 1.88219 (* 1 = 1.88219 loss)
I0405 14:10:44.031298  1863 sgd_solver.cpp:105] Iteration 6048, lr = 0.001
I0405 14:10:48.924347  1863 solver.cpp:218] Iteration 6060 (2.45246 iter/s, 4.89305s/12 iters), loss = 1.96644
I0405 14:10:48.924386  1863 solver.cpp:237]     Train net output #0: loss = 1.96644 (* 1 = 1.96644 loss)
I0405 14:10:48.924392  1863 sgd_solver.cpp:105] Iteration 6060, lr = 0.001
I0405 14:10:52.554498  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:10:54.247857  1863 solver.cpp:218] Iteration 6072 (2.25417 iter/s, 5.32346s/12 iters), loss = 2.50774
I0405 14:10:54.247910  1863 solver.cpp:237]     Train net output #0: loss = 2.50774 (* 1 = 2.50774 loss)
I0405 14:10:54.247920  1863 sgd_solver.cpp:105] Iteration 6072, lr = 0.001
I0405 14:10:59.549147  1863 solver.cpp:218] Iteration 6084 (2.26363 iter/s, 5.30122s/12 iters), loss = 2.20785
I0405 14:10:59.549273  1863 solver.cpp:237]     Train net output #0: loss = 2.20785 (* 1 = 2.20785 loss)
I0405 14:10:59.549279  1863 sgd_solver.cpp:105] Iteration 6084, lr = 0.001
I0405 14:11:04.859292  1863 solver.cpp:218] Iteration 6096 (2.25988 iter/s, 5.31001s/12 iters), loss = 2.13748
I0405 14:11:04.859330  1863 solver.cpp:237]     Train net output #0: loss = 2.13748 (* 1 = 2.13748 loss)
I0405 14:11:04.859336  1863 sgd_solver.cpp:105] Iteration 6096, lr = 0.001
I0405 14:11:10.139766  1863 solver.cpp:218] Iteration 6108 (2.27255 iter/s, 5.28042s/12 iters), loss = 1.93112
I0405 14:11:10.139824  1863 solver.cpp:237]     Train net output #0: loss = 1.93112 (* 1 = 1.93112 loss)
I0405 14:11:10.139833  1863 sgd_solver.cpp:105] Iteration 6108, lr = 0.001
I0405 14:11:14.831296  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel
I0405 14:11:19.208696  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate
I0405 14:11:22.407217  1863 solver.cpp:330] Iteration 6120, Testing net (#0)
I0405 14:11:22.407239  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:11:24.377782  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:11:26.768158  1863 solver.cpp:397]     Test net output #0: accuracy = 0.163603
I0405 14:11:26.768205  1863 solver.cpp:397]     Test net output #1: loss = 4.04378 (* 1 = 4.04378 loss)
I0405 14:11:26.899533  1863 solver.cpp:218] Iteration 6120 (0.716003 iter/s, 16.7597s/12 iters), loss = 2.04247
I0405 14:11:26.899585  1863 solver.cpp:237]     Train net output #0: loss = 2.04247 (* 1 = 2.04247 loss)
I0405 14:11:26.899592  1863 sgd_solver.cpp:105] Iteration 6120, lr = 0.001
I0405 14:11:31.368146  1863 solver.cpp:218] Iteration 6132 (2.68544 iter/s, 4.46855s/12 iters), loss = 1.85219
I0405 14:11:31.368247  1863 solver.cpp:237]     Train net output #0: loss = 1.85219 (* 1 = 1.85219 loss)
I0405 14:11:31.368257  1863 sgd_solver.cpp:105] Iteration 6132, lr = 0.001
I0405 14:11:36.836724  1863 solver.cpp:218] Iteration 6144 (2.1944 iter/s, 5.46847s/12 iters), loss = 2.04189
I0405 14:11:36.836768  1863 solver.cpp:237]     Train net output #0: loss = 2.04189 (* 1 = 2.04189 loss)
I0405 14:11:36.836776  1863 sgd_solver.cpp:105] Iteration 6144, lr = 0.001
I0405 14:11:42.327812  1863 solver.cpp:218] Iteration 6156 (2.18538 iter/s, 5.49103s/12 iters), loss = 1.77336
I0405 14:11:42.327865  1863 solver.cpp:237]     Train net output #0: loss = 1.77336 (* 1 = 1.77336 loss)
I0405 14:11:42.327873  1863 sgd_solver.cpp:105] Iteration 6156, lr = 0.001
I0405 14:11:47.524025  1863 solver.cpp:218] Iteration 6168 (2.3094 iter/s, 5.19615s/12 iters), loss = 2.02458
I0405 14:11:47.524080  1863 solver.cpp:237]     Train net output #0: loss = 2.02458 (* 1 = 2.02458 loss)
I0405 14:11:47.524089  1863 sgd_solver.cpp:105] Iteration 6168, lr = 0.001
I0405 14:11:48.136015  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:11:52.834383  1863 solver.cpp:218] Iteration 6180 (2.25976 iter/s, 5.31029s/12 iters), loss = 2.44414
I0405 14:11:52.834434  1863 solver.cpp:237]     Train net output #0: loss = 2.44414 (* 1 = 2.44414 loss)
I0405 14:11:52.834444  1863 sgd_solver.cpp:105] Iteration 6180, lr = 0.001
I0405 14:11:58.150885  1863 solver.cpp:218] Iteration 6192 (2.25715 iter/s, 5.31645s/12 iters), loss = 2.06359
I0405 14:11:58.150926  1863 solver.cpp:237]     Train net output #0: loss = 2.06359 (* 1 = 2.06359 loss)
I0405 14:11:58.150931  1863 sgd_solver.cpp:105] Iteration 6192, lr = 0.001
I0405 14:12:03.315354  1863 solver.cpp:218] Iteration 6204 (2.32359 iter/s, 5.16441s/12 iters), loss = 1.91219
I0405 14:12:03.315521  1863 solver.cpp:237]     Train net output #0: loss = 1.91219 (* 1 = 1.91219 loss)
I0405 14:12:03.315531  1863 sgd_solver.cpp:105] Iteration 6204, lr = 0.001
I0405 14:12:08.632972  1863 solver.cpp:218] Iteration 6216 (2.25672 iter/s, 5.31744s/12 iters), loss = 2.49468
I0405 14:12:08.633016  1863 solver.cpp:237]     Train net output #0: loss = 2.49468 (* 1 = 2.49468 loss)
I0405 14:12:08.633023  1863 sgd_solver.cpp:105] Iteration 6216, lr = 0.001
I0405 14:12:10.680675  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel
I0405 14:12:15.125478  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate
I0405 14:12:17.750151  1863 solver.cpp:330] Iteration 6222, Testing net (#0)
I0405 14:12:17.750176  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:12:19.622260  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:12:20.946285  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:12:22.188169  1863 solver.cpp:397]     Test net output #0: accuracy = 0.167279
I0405 14:12:22.188207  1863 solver.cpp:397]     Test net output #1: loss = 4.08457 (* 1 = 4.08457 loss)
I0405 14:12:23.942020  1863 solver.cpp:218] Iteration 6228 (0.783853 iter/s, 15.309s/12 iters), loss = 2.38838
I0405 14:12:23.942075  1863 solver.cpp:237]     Train net output #0: loss = 2.38838 (* 1 = 2.38838 loss)
I0405 14:12:23.942082  1863 sgd_solver.cpp:105] Iteration 6228, lr = 0.001
I0405 14:12:28.939106  1863 solver.cpp:218] Iteration 6240 (2.40143 iter/s, 4.99702s/12 iters), loss = 1.91901
I0405 14:12:28.939149  1863 solver.cpp:237]     Train net output #0: loss = 1.91901 (* 1 = 1.91901 loss)
I0405 14:12:28.939155  1863 sgd_solver.cpp:105] Iteration 6240, lr = 0.001
I0405 14:12:34.245265  1863 solver.cpp:218] Iteration 6252 (2.26155 iter/s, 5.30611s/12 iters), loss = 2.21943
I0405 14:12:34.245363  1863 solver.cpp:237]     Train net output #0: loss = 2.21943 (* 1 = 2.21943 loss)
I0405 14:12:34.245370  1863 sgd_solver.cpp:105] Iteration 6252, lr = 0.001
I0405 14:12:39.520653  1863 solver.cpp:218] Iteration 6264 (2.27476 iter/s, 5.27527s/12 iters), loss = 2.27392
I0405 14:12:39.520702  1863 solver.cpp:237]     Train net output #0: loss = 2.27392 (* 1 = 2.27392 loss)
I0405 14:12:39.520709  1863 sgd_solver.cpp:105] Iteration 6264, lr = 0.001
I0405 14:12:42.308470  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:12:44.736800  1863 solver.cpp:218] Iteration 6276 (2.30057 iter/s, 5.21609s/12 iters), loss = 2.40334
I0405 14:12:44.736843  1863 solver.cpp:237]     Train net output #0: loss = 2.40334 (* 1 = 2.40334 loss)
I0405 14:12:44.736848  1863 sgd_solver.cpp:105] Iteration 6276, lr = 0.001
I0405 14:12:49.630653  1863 solver.cpp:218] Iteration 6288 (2.45208 iter/s, 4.8938s/12 iters), loss = 2.28874
I0405 14:12:49.630697  1863 solver.cpp:237]     Train net output #0: loss = 2.28874 (* 1 = 2.28874 loss)
I0405 14:12:49.630702  1863 sgd_solver.cpp:105] Iteration 6288, lr = 0.001
I0405 14:12:55.036144  1863 solver.cpp:218] Iteration 6300 (2.21999 iter/s, 5.40544s/12 iters), loss = 1.87352
I0405 14:12:55.036185  1863 solver.cpp:237]     Train net output #0: loss = 1.87352 (* 1 = 1.87352 loss)
I0405 14:12:55.036191  1863 sgd_solver.cpp:105] Iteration 6300, lr = 0.001
I0405 14:13:00.424521  1863 solver.cpp:218] Iteration 6312 (2.22704 iter/s, 5.38832s/12 iters), loss = 2.09715
I0405 14:13:00.424578  1863 solver.cpp:237]     Train net output #0: loss = 2.09715 (* 1 = 2.09715 loss)
I0405 14:13:00.424587  1863 sgd_solver.cpp:105] Iteration 6312, lr = 0.001
I0405 14:13:05.098783  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel
I0405 14:13:09.979225  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate
I0405 14:13:14.861325  1863 solver.cpp:330] Iteration 6324, Testing net (#0)
I0405 14:13:14.861346  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:13:16.724057  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:13:19.153170  1863 solver.cpp:397]     Test net output #0: accuracy = 0.170343
I0405 14:13:19.153206  1863 solver.cpp:397]     Test net output #1: loss = 4.12963 (* 1 = 4.12963 loss)
I0405 14:13:19.288007  1863 solver.cpp:218] Iteration 6324 (0.636152 iter/s, 18.8634s/12 iters), loss = 1.8569
I0405 14:13:19.289634  1863 solver.cpp:237]     Train net output #0: loss = 1.8569 (* 1 = 1.8569 loss)
I0405 14:13:19.289651  1863 sgd_solver.cpp:105] Iteration 6324, lr = 0.001
I0405 14:13:23.596735  1863 solver.cpp:218] Iteration 6336 (2.7861 iter/s, 4.3071s/12 iters), loss = 2.00038
I0405 14:13:23.596784  1863 solver.cpp:237]     Train net output #0: loss = 2.00038 (* 1 = 2.00038 loss)
I0405 14:13:23.596792  1863 sgd_solver.cpp:105] Iteration 6336, lr = 0.001
I0405 14:13:28.870223  1863 solver.cpp:218] Iteration 6348 (2.27556 iter/s, 5.27343s/12 iters), loss = 1.70362
I0405 14:13:28.870263  1863 solver.cpp:237]     Train net output #0: loss = 1.70362 (* 1 = 1.70362 loss)
I0405 14:13:28.870270  1863 sgd_solver.cpp:105] Iteration 6348, lr = 0.001
I0405 14:13:34.327702  1863 solver.cpp:218] Iteration 6360 (2.19884 iter/s, 5.45742s/12 iters), loss = 2.0569
I0405 14:13:34.327749  1863 solver.cpp:237]     Train net output #0: loss = 2.0569 (* 1 = 2.0569 loss)
I0405 14:13:34.327756  1863 sgd_solver.cpp:105] Iteration 6360, lr = 0.001
I0405 14:13:39.258471  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:13:39.453495  1863 solver.cpp:218] Iteration 6372 (2.34113 iter/s, 5.12573s/12 iters), loss = 2.01264
I0405 14:13:39.453541  1863 solver.cpp:237]     Train net output #0: loss = 2.01264 (* 1 = 2.01264 loss)
I0405 14:13:39.453548  1863 sgd_solver.cpp:105] Iteration 6372, lr = 0.001
I0405 14:13:44.804605  1863 solver.cpp:218] Iteration 6384 (2.24255 iter/s, 5.35105s/12 iters), loss = 2.33247
I0405 14:13:44.804644  1863 solver.cpp:237]     Train net output #0: loss = 2.33247 (* 1 = 2.33247 loss)
I0405 14:13:44.804651  1863 sgd_solver.cpp:105] Iteration 6384, lr = 0.001
I0405 14:13:50.128664  1863 solver.cpp:218] Iteration 6396 (2.25394 iter/s, 5.32401s/12 iters), loss = 2.36936
I0405 14:13:50.128707  1863 solver.cpp:237]     Train net output #0: loss = 2.36936 (* 1 = 2.36936 loss)
I0405 14:13:50.128712  1863 sgd_solver.cpp:105] Iteration 6396, lr = 0.001
I0405 14:13:55.151463  1863 solver.cpp:218] Iteration 6408 (2.38913 iter/s, 5.02274s/12 iters), loss = 1.86006
I0405 14:13:55.151512  1863 solver.cpp:237]     Train net output #0: loss = 1.86006 (* 1 = 1.86006 loss)
I0405 14:13:55.151520  1863 sgd_solver.cpp:105] Iteration 6408, lr = 0.001
I0405 14:14:00.483168  1863 solver.cpp:218] Iteration 6420 (2.25071 iter/s, 5.33164s/12 iters), loss = 1.68728
I0405 14:14:00.483219  1863 solver.cpp:237]     Train net output #0: loss = 1.68728 (* 1 = 1.68728 loss)
I0405 14:14:00.483227  1863 sgd_solver.cpp:105] Iteration 6420, lr = 0.001
I0405 14:14:02.569340  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel
I0405 14:14:08.397157  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate
I0405 14:14:13.844018  1863 solver.cpp:330] Iteration 6426, Testing net (#0)
I0405 14:14:13.844101  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:14:15.822733  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:14:18.346369  1863 solver.cpp:397]     Test net output #0: accuracy = 0.175858
I0405 14:14:18.346396  1863 solver.cpp:397]     Test net output #1: loss = 4.05987 (* 1 = 4.05987 loss)
I0405 14:14:20.254233  1863 solver.cpp:218] Iteration 6432 (0.606949 iter/s, 19.771s/12 iters), loss = 2.17451
I0405 14:14:20.254271  1863 solver.cpp:237]     Train net output #0: loss = 2.17451 (* 1 = 2.17451 loss)
I0405 14:14:20.254277  1863 sgd_solver.cpp:105] Iteration 6432, lr = 0.001
I0405 14:14:25.494103  1863 solver.cpp:218] Iteration 6444 (2.29015 iter/s, 5.23983s/12 iters), loss = 1.90048
I0405 14:14:25.494143  1863 solver.cpp:237]     Train net output #0: loss = 1.90048 (* 1 = 1.90048 loss)
I0405 14:14:25.494148  1863 sgd_solver.cpp:105] Iteration 6444, lr = 0.001
I0405 14:14:30.596949  1863 solver.cpp:218] Iteration 6456 (2.35165 iter/s, 5.10279s/12 iters), loss = 1.84848
I0405 14:14:30.596992  1863 solver.cpp:237]     Train net output #0: loss = 1.84848 (* 1 = 1.84848 loss)
I0405 14:14:30.596997  1863 sgd_solver.cpp:105] Iteration 6456, lr = 0.001
I0405 14:14:35.771045  1863 solver.cpp:218] Iteration 6468 (2.31927 iter/s, 5.17405s/12 iters), loss = 1.72583
I0405 14:14:35.771085  1863 solver.cpp:237]     Train net output #0: loss = 1.72583 (* 1 = 1.72583 loss)
I0405 14:14:35.771091  1863 sgd_solver.cpp:105] Iteration 6468, lr = 0.001
I0405 14:14:37.768949  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:14:41.110770  1863 solver.cpp:218] Iteration 6480 (2.24733 iter/s, 5.33967s/12 iters), loss = 2.13382
I0405 14:14:41.110813  1863 solver.cpp:237]     Train net output #0: loss = 2.13382 (* 1 = 2.13382 loss)
I0405 14:14:41.110819  1863 sgd_solver.cpp:105] Iteration 6480, lr = 0.001
I0405 14:14:46.226689  1863 solver.cpp:218] Iteration 6492 (2.34565 iter/s, 5.11586s/12 iters), loss = 2.37849
I0405 14:14:46.226821  1863 solver.cpp:237]     Train net output #0: loss = 2.37849 (* 1 = 2.37849 loss)
I0405 14:14:46.226828  1863 sgd_solver.cpp:105] Iteration 6492, lr = 0.001
I0405 14:14:51.348825  1863 solver.cpp:218] Iteration 6504 (2.34284 iter/s, 5.12199s/12 iters), loss = 1.75587
I0405 14:14:51.348866  1863 solver.cpp:237]     Train net output #0: loss = 1.75587 (* 1 = 1.75587 loss)
I0405 14:14:51.348872  1863 sgd_solver.cpp:105] Iteration 6504, lr = 0.001
I0405 14:14:56.561410  1863 solver.cpp:218] Iteration 6516 (2.30214 iter/s, 5.21253s/12 iters), loss = 1.88694
I0405 14:14:56.561460  1863 solver.cpp:237]     Train net output #0: loss = 1.88694 (* 1 = 1.88694 loss)
I0405 14:14:56.561467  1863 sgd_solver.cpp:105] Iteration 6516, lr = 0.001
I0405 14:15:01.181380  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel
I0405 14:15:04.891288  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate
I0405 14:15:08.531622  1863 solver.cpp:330] Iteration 6528, Testing net (#0)
I0405 14:15:08.531644  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:15:10.314954  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:15:12.853703  1863 solver.cpp:397]     Test net output #0: accuracy = 0.167892
I0405 14:15:12.853737  1863 solver.cpp:397]     Test net output #1: loss = 4.08339 (* 1 = 4.08339 loss)
I0405 14:15:12.993656  1863 solver.cpp:218] Iteration 6528 (0.730274 iter/s, 16.4322s/12 iters), loss = 1.85099
I0405 14:15:12.993721  1863 solver.cpp:237]     Train net output #0: loss = 1.85099 (* 1 = 1.85099 loss)
I0405 14:15:12.993729  1863 sgd_solver.cpp:105] Iteration 6528, lr = 0.001
I0405 14:15:17.270887  1863 solver.cpp:218] Iteration 6540 (2.8056 iter/s, 4.27716s/12 iters), loss = 2.09875
I0405 14:15:17.270989  1863 solver.cpp:237]     Train net output #0: loss = 2.09875 (* 1 = 2.09875 loss)
I0405 14:15:17.270996  1863 sgd_solver.cpp:105] Iteration 6540, lr = 0.001
I0405 14:15:22.344585  1863 solver.cpp:218] Iteration 6552 (2.36519 iter/s, 5.07358s/12 iters), loss = 1.93333
I0405 14:15:22.344628  1863 solver.cpp:237]     Train net output #0: loss = 1.93333 (* 1 = 1.93333 loss)
I0405 14:15:22.344635  1863 sgd_solver.cpp:105] Iteration 6552, lr = 0.001
I0405 14:15:27.743669  1863 solver.cpp:218] Iteration 6564 (2.22262 iter/s, 5.39903s/12 iters), loss = 2.15879
I0405 14:15:27.743722  1863 solver.cpp:237]     Train net output #0: loss = 2.15879 (* 1 = 2.15879 loss)
I0405 14:15:27.743731  1863 sgd_solver.cpp:105] Iteration 6564, lr = 0.001
I0405 14:15:32.146297  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:15:32.992805  1863 solver.cpp:218] Iteration 6576 (2.28612 iter/s, 5.24907s/12 iters), loss = 1.79186
I0405 14:15:32.992844  1863 solver.cpp:237]     Train net output #0: loss = 1.79186 (* 1 = 1.79186 loss)
I0405 14:15:32.992851  1863 sgd_solver.cpp:105] Iteration 6576, lr = 0.001
I0405 14:15:38.530565  1863 solver.cpp:218] Iteration 6588 (2.16696 iter/s, 5.53771s/12 iters), loss = 1.83085
I0405 14:15:38.530604  1863 solver.cpp:237]     Train net output #0: loss = 1.83085 (* 1 = 1.83085 loss)
I0405 14:15:38.530609  1863 sgd_solver.cpp:105] Iteration 6588, lr = 0.001
I0405 14:15:43.910285  1863 solver.cpp:218] Iteration 6600 (2.23062 iter/s, 5.37966s/12 iters), loss = 2.22732
I0405 14:15:43.910344  1863 solver.cpp:237]     Train net output #0: loss = 2.22732 (* 1 = 2.22732 loss)
I0405 14:15:43.910353  1863 sgd_solver.cpp:105] Iteration 6600, lr = 0.001
I0405 14:15:49.272608  1863 solver.cpp:218] Iteration 6612 (2.23786 iter/s, 5.36226s/12 iters), loss = 1.73656
I0405 14:15:49.272737  1863 solver.cpp:237]     Train net output #0: loss = 1.73656 (* 1 = 1.73656 loss)
I0405 14:15:49.272742  1863 sgd_solver.cpp:105] Iteration 6612, lr = 0.001
I0405 14:15:54.475039  1863 solver.cpp:218] Iteration 6624 (2.30667 iter/s, 5.2023s/12 iters), loss = 1.69535
I0405 14:15:54.475078  1863 solver.cpp:237]     Train net output #0: loss = 1.69535 (* 1 = 1.69535 loss)
I0405 14:15:54.475085  1863 sgd_solver.cpp:105] Iteration 6624, lr = 0.001
I0405 14:15:56.537261  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel
I0405 14:16:00.320289  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate
I0405 14:16:04.012070  1863 solver.cpp:330] Iteration 6630, Testing net (#0)
I0405 14:16:04.012091  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:16:05.742411  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:16:08.571664  1863 solver.cpp:397]     Test net output #0: accuracy = 0.165441
I0405 14:16:08.571703  1863 solver.cpp:397]     Test net output #1: loss = 4.05796 (* 1 = 4.05796 loss)
I0405 14:16:10.570820  1863 solver.cpp:218] Iteration 6636 (0.745539 iter/s, 16.0957s/12 iters), loss = 1.80531
I0405 14:16:10.570875  1863 solver.cpp:237]     Train net output #0: loss = 1.80531 (* 1 = 1.80531 loss)
I0405 14:16:10.570884  1863 sgd_solver.cpp:105] Iteration 6636, lr = 0.001
I0405 14:16:15.727418  1863 solver.cpp:218] Iteration 6648 (2.32715 iter/s, 5.15653s/12 iters), loss = 1.69636
I0405 14:16:15.727463  1863 solver.cpp:237]     Train net output #0: loss = 1.69636 (* 1 = 1.69636 loss)
I0405 14:16:15.727468  1863 sgd_solver.cpp:105] Iteration 6648, lr = 0.001
I0405 14:16:20.986320  1863 solver.cpp:218] Iteration 6660 (2.28187 iter/s, 5.25885s/12 iters), loss = 1.98386
I0405 14:16:20.986433  1863 solver.cpp:237]     Train net output #0: loss = 1.98386 (* 1 = 1.98386 loss)
I0405 14:16:20.986439  1863 sgd_solver.cpp:105] Iteration 6660, lr = 0.001
I0405 14:16:26.311775  1863 solver.cpp:218] Iteration 6672 (2.25338 iter/s, 5.32533s/12 iters), loss = 2.10549
I0405 14:16:26.311823  1863 solver.cpp:237]     Train net output #0: loss = 2.10549 (* 1 = 2.10549 loss)
I0405 14:16:26.311830  1863 sgd_solver.cpp:105] Iteration 6672, lr = 0.001
I0405 14:16:27.781698  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:16:31.735989  1863 solver.cpp:218] Iteration 6684 (2.21233 iter/s, 5.42415s/12 iters), loss = 1.95228
I0405 14:16:31.736033  1863 solver.cpp:237]     Train net output #0: loss = 1.95228 (* 1 = 1.95228 loss)
I0405 14:16:31.736039  1863 sgd_solver.cpp:105] Iteration 6684, lr = 0.001
I0405 14:16:37.072023  1863 solver.cpp:218] Iteration 6696 (2.24889 iter/s, 5.33598s/12 iters), loss = 2.34034
I0405 14:16:37.072063  1863 solver.cpp:237]     Train net output #0: loss = 2.34034 (* 1 = 2.34034 loss)
I0405 14:16:37.072068  1863 sgd_solver.cpp:105] Iteration 6696, lr = 0.001
I0405 14:16:42.351835  1863 solver.cpp:218] Iteration 6708 (2.27283 iter/s, 5.27976s/12 iters), loss = 2.0612
I0405 14:16:42.351872  1863 solver.cpp:237]     Train net output #0: loss = 2.0612 (* 1 = 2.0612 loss)
I0405 14:16:42.351878  1863 sgd_solver.cpp:105] Iteration 6708, lr = 0.001
I0405 14:16:47.591554  1863 solver.cpp:218] Iteration 6720 (2.29022 iter/s, 5.23966s/12 iters), loss = 2.19585
I0405 14:16:47.591610  1863 solver.cpp:237]     Train net output #0: loss = 2.19585 (* 1 = 2.19585 loss)
I0405 14:16:47.591619  1863 sgd_solver.cpp:105] Iteration 6720, lr = 0.001
I0405 14:16:52.343230  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel
I0405 14:16:56.598578  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate
I0405 14:17:00.343578  1863 solver.cpp:330] Iteration 6732, Testing net (#0)
I0405 14:17:00.343600  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:17:02.081058  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:17:04.754197  1863 solver.cpp:397]     Test net output #0: accuracy = 0.160539
I0405 14:17:04.754233  1863 solver.cpp:397]     Test net output #1: loss = 4.1376 (* 1 = 4.1376 loss)
I0405 14:17:04.892266  1863 solver.cpp:218] Iteration 6732 (0.693615 iter/s, 17.3007s/12 iters), loss = 1.58037
I0405 14:17:04.892308  1863 solver.cpp:237]     Train net output #0: loss = 1.58037 (* 1 = 1.58037 loss)
I0405 14:17:04.892315  1863 sgd_solver.cpp:105] Iteration 6732, lr = 0.001
I0405 14:17:09.049350  1863 solver.cpp:218] Iteration 6744 (2.88668 iter/s, 4.15702s/12 iters), loss = 1.72283
I0405 14:17:09.049396  1863 solver.cpp:237]     Train net output #0: loss = 1.72283 (* 1 = 1.72283 loss)
I0405 14:17:09.049403  1863 sgd_solver.cpp:105] Iteration 6744, lr = 0.001
I0405 14:17:14.201720  1863 solver.cpp:218] Iteration 6756 (2.32905 iter/s, 5.15231s/12 iters), loss = 1.54992
I0405 14:17:14.201761  1863 solver.cpp:237]     Train net output #0: loss = 1.54992 (* 1 = 1.54992 loss)
I0405 14:17:14.201766  1863 sgd_solver.cpp:105] Iteration 6756, lr = 0.001
I0405 14:17:19.372925  1863 solver.cpp:218] Iteration 6768 (2.32057 iter/s, 5.17115s/12 iters), loss = 1.89508
I0405 14:17:19.372964  1863 solver.cpp:237]     Train net output #0: loss = 1.89508 (* 1 = 1.89508 loss)
I0405 14:17:19.372970  1863 sgd_solver.cpp:105] Iteration 6768, lr = 0.001
I0405 14:17:23.131006  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:17:24.735509  1863 solver.cpp:218] Iteration 6780 (2.23775 iter/s, 5.36253s/12 iters), loss = 1.85027
I0405 14:17:24.735566  1863 solver.cpp:237]     Train net output #0: loss = 1.85027 (* 1 = 1.85027 loss)
I0405 14:17:24.735575  1863 sgd_solver.cpp:105] Iteration 6780, lr = 0.001
I0405 14:17:29.987866  1863 solver.cpp:218] Iteration 6792 (2.28472 iter/s, 5.25229s/12 iters), loss = 1.89149
I0405 14:17:29.987908  1863 solver.cpp:237]     Train net output #0: loss = 1.89149 (* 1 = 1.89149 loss)
I0405 14:17:29.987915  1863 sgd_solver.cpp:105] Iteration 6792, lr = 0.001
I0405 14:17:35.140271  1863 solver.cpp:218] Iteration 6804 (2.32903 iter/s, 5.15235s/12 iters), loss = 1.56978
I0405 14:17:35.140311  1863 solver.cpp:237]     Train net output #0: loss = 1.56978 (* 1 = 1.56978 loss)
I0405 14:17:35.140316  1863 sgd_solver.cpp:105] Iteration 6804, lr = 0.001
I0405 14:17:40.198729  1863 solver.cpp:218] Iteration 6816 (2.37229 iter/s, 5.05841s/12 iters), loss = 1.5288
I0405 14:17:40.198766  1863 solver.cpp:237]     Train net output #0: loss = 1.5288 (* 1 = 1.5288 loss)
I0405 14:17:40.198772  1863 sgd_solver.cpp:105] Iteration 6816, lr = 0.001
I0405 14:17:45.473436  1863 solver.cpp:218] Iteration 6828 (2.27503 iter/s, 5.27465s/12 iters), loss = 1.81041
I0405 14:17:45.473479  1863 solver.cpp:237]     Train net output #0: loss = 1.81041 (* 1 = 1.81041 loss)
I0405 14:17:45.473486  1863 sgd_solver.cpp:105] Iteration 6828, lr = 0.001
I0405 14:17:47.553117  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel
I0405 14:17:50.869652  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate
I0405 14:17:56.164713  1863 solver.cpp:330] Iteration 6834, Testing net (#0)
I0405 14:17:56.164772  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:17:57.883817  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:00.689003  1863 solver.cpp:397]     Test net output #0: accuracy = 0.164216
I0405 14:18:00.689050  1863 solver.cpp:397]     Test net output #1: loss = 4.149 (* 1 = 4.149 loss)
I0405 14:18:02.613993  1863 solver.cpp:218] Iteration 6840 (0.700095 iter/s, 17.1405s/12 iters), loss = 2.03979
I0405 14:18:02.614032  1863 solver.cpp:237]     Train net output #0: loss = 2.03979 (* 1 = 2.03979 loss)
I0405 14:18:02.614038  1863 sgd_solver.cpp:105] Iteration 6840, lr = 0.001
I0405 14:18:07.725246  1863 solver.cpp:218] Iteration 6852 (2.34779 iter/s, 5.1112s/12 iters), loss = 1.32523
I0405 14:18:07.725304  1863 solver.cpp:237]     Train net output #0: loss = 1.32523 (* 1 = 1.32523 loss)
I0405 14:18:07.725313  1863 sgd_solver.cpp:105] Iteration 6852, lr = 0.001
I0405 14:18:13.119614  1863 solver.cpp:218] Iteration 6864 (2.22457 iter/s, 5.39429s/12 iters), loss = 1.58074
I0405 14:18:13.119673  1863 solver.cpp:237]     Train net output #0: loss = 1.58074 (* 1 = 1.58074 loss)
I0405 14:18:13.119681  1863 sgd_solver.cpp:105] Iteration 6864, lr = 0.001
I0405 14:18:18.344496  1863 solver.cpp:218] Iteration 6876 (2.29673 iter/s, 5.22481s/12 iters), loss = 1.60671
I0405 14:18:18.344543  1863 solver.cpp:237]     Train net output #0: loss = 1.60671 (* 1 = 1.60671 loss)
I0405 14:18:18.344548  1863 sgd_solver.cpp:105] Iteration 6876, lr = 0.001
I0405 14:18:18.867343  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:23.420578  1863 solver.cpp:218] Iteration 6888 (2.36406 iter/s, 5.07602s/12 iters), loss = 1.63049
I0405 14:18:23.420634  1863 solver.cpp:237]     Train net output #0: loss = 1.63049 (* 1 = 1.63049 loss)
I0405 14:18:23.420644  1863 sgd_solver.cpp:105] Iteration 6888, lr = 0.001
I0405 14:18:28.715891  1863 solver.cpp:218] Iteration 6900 (2.26618 iter/s, 5.29524s/12 iters), loss = 2.11272
I0405 14:18:28.716027  1863 solver.cpp:237]     Train net output #0: loss = 2.11272 (* 1 = 2.11272 loss)
I0405 14:18:28.716035  1863 sgd_solver.cpp:105] Iteration 6900, lr = 0.001
I0405 14:18:34.060786  1863 solver.cpp:218] Iteration 6912 (2.24519 iter/s, 5.34475s/12 iters), loss = 1.69759
I0405 14:18:34.060833  1863 solver.cpp:237]     Train net output #0: loss = 1.69759 (* 1 = 1.69759 loss)
I0405 14:18:34.060840  1863 sgd_solver.cpp:105] Iteration 6912, lr = 0.001
I0405 14:18:39.266760  1863 solver.cpp:218] Iteration 6924 (2.30507 iter/s, 5.20592s/12 iters), loss = 1.72555
I0405 14:18:39.266803  1863 solver.cpp:237]     Train net output #0: loss = 1.72555 (* 1 = 1.72555 loss)
I0405 14:18:39.266809  1863 sgd_solver.cpp:105] Iteration 6924, lr = 0.001
I0405 14:18:43.843327  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel
I0405 14:18:46.916548  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate
I0405 14:18:50.918038  1863 solver.cpp:330] Iteration 6936, Testing net (#0)
I0405 14:18:50.918064  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:18:51.582053  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:18:52.703634  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:18:55.492532  1863 solver.cpp:397]     Test net output #0: accuracy = 0.176471
I0405 14:18:55.492569  1863 solver.cpp:397]     Test net output #1: loss = 4.14788 (* 1 = 4.14788 loss)
I0405 14:18:55.629529  1863 solver.cpp:218] Iteration 6936 (0.733374 iter/s, 16.3627s/12 iters), loss = 1.47122
I0405 14:18:55.629588  1863 solver.cpp:237]     Train net output #0: loss = 1.47122 (* 1 = 1.47122 loss)
I0405 14:18:55.629596  1863 sgd_solver.cpp:105] Iteration 6936, lr = 0.001
I0405 14:18:59.870927  1863 solver.cpp:218] Iteration 6948 (2.8293 iter/s, 4.24133s/12 iters), loss = 1.73252
I0405 14:18:59.871033  1863 solver.cpp:237]     Train net output #0: loss = 1.73252 (* 1 = 1.73252 loss)
I0405 14:18:59.871042  1863 sgd_solver.cpp:105] Iteration 6948, lr = 0.001
I0405 14:19:05.016459  1863 solver.cpp:218] Iteration 6960 (2.33217 iter/s, 5.14542s/12 iters), loss = 1.41287
I0405 14:19:05.016505  1863 solver.cpp:237]     Train net output #0: loss = 1.41287 (* 1 = 1.41287 loss)
I0405 14:19:05.016511  1863 sgd_solver.cpp:105] Iteration 6960, lr = 0.001
I0405 14:19:10.163117  1863 solver.cpp:218] Iteration 6972 (2.33164 iter/s, 5.1466s/12 iters), loss = 1.68819
I0405 14:19:10.163159  1863 solver.cpp:237]     Train net output #0: loss = 1.68819 (* 1 = 1.68819 loss)
I0405 14:19:10.163165  1863 sgd_solver.cpp:105] Iteration 6972, lr = 0.001
I0405 14:19:13.040742  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:19:15.544502  1863 solver.cpp:218] Iteration 6984 (2.22993 iter/s, 5.38133s/12 iters), loss = 1.62064
I0405 14:19:15.544557  1863 solver.cpp:237]     Train net output #0: loss = 1.62064 (* 1 = 1.62064 loss)
I0405 14:19:15.544567  1863 sgd_solver.cpp:105] Iteration 6984, lr = 0.001
I0405 14:19:20.824244  1863 solver.cpp:218] Iteration 6996 (2.27287 iter/s, 5.27968s/12 iters), loss = 1.62794
I0405 14:19:20.824287  1863 solver.cpp:237]     Train net output #0: loss = 1.62794 (* 1 = 1.62794 loss)
I0405 14:19:20.824292  1863 sgd_solver.cpp:105] Iteration 6996, lr = 0.001
I0405 14:19:26.150992  1863 solver.cpp:218] Iteration 7008 (2.2528 iter/s, 5.32669s/12 iters), loss = 1.74262
I0405 14:19:26.151036  1863 solver.cpp:237]     Train net output #0: loss = 1.74262 (* 1 = 1.74262 loss)
I0405 14:19:26.151042  1863 sgd_solver.cpp:105] Iteration 7008, lr = 0.001
I0405 14:19:31.428681  1863 solver.cpp:218] Iteration 7020 (2.27375 iter/s, 5.27763s/12 iters), loss = 1.83975
I0405 14:19:31.428853  1863 solver.cpp:237]     Train net output #0: loss = 1.83975 (* 1 = 1.83975 loss)
I0405 14:19:31.428861  1863 sgd_solver.cpp:105] Iteration 7020, lr = 0.001
I0405 14:19:36.695083  1863 solver.cpp:218] Iteration 7032 (2.27867 iter/s, 5.26622s/12 iters), loss = 1.62585
I0405 14:19:36.695124  1863 solver.cpp:237]     Train net output #0: loss = 1.62585 (* 1 = 1.62585 loss)
I0405 14:19:36.695130  1863 sgd_solver.cpp:105] Iteration 7032, lr = 0.001
I0405 14:19:38.983541  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel
I0405 14:19:41.973886  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate
I0405 14:19:45.930632  1863 solver.cpp:330] Iteration 7038, Testing net (#0)
I0405 14:19:45.930657  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:19:47.498553  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:19:50.249429  1863 solver.cpp:397]     Test net output #0: accuracy = 0.174632
I0405 14:19:50.249457  1863 solver.cpp:397]     Test net output #1: loss = 4.22 (* 1 = 4.22 loss)
I0405 14:19:52.130730  1863 solver.cpp:218] Iteration 7044 (0.777424 iter/s, 15.4356s/12 iters), loss = 1.49086
I0405 14:19:52.130784  1863 solver.cpp:237]     Train net output #0: loss = 1.49086 (* 1 = 1.49086 loss)
I0405 14:19:52.130791  1863 sgd_solver.cpp:105] Iteration 7044, lr = 0.001
I0405 14:19:57.301240  1863 solver.cpp:218] Iteration 7056 (2.32088 iter/s, 5.17044s/12 iters), loss = 1.43267
I0405 14:19:57.301290  1863 solver.cpp:237]     Train net output #0: loss = 1.43267 (* 1 = 1.43267 loss)
I0405 14:19:57.301297  1863 sgd_solver.cpp:105] Iteration 7056, lr = 0.001
I0405 14:20:02.488795  1863 solver.cpp:218] Iteration 7068 (2.31326 iter/s, 5.18749s/12 iters), loss = 1.27471
I0405 14:20:02.488893  1863 solver.cpp:237]     Train net output #0: loss = 1.27471 (* 1 = 1.27471 loss)
I0405 14:20:02.488901  1863 sgd_solver.cpp:105] Iteration 7068, lr = 0.001
I0405 14:20:07.638464  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:20:07.805121  1863 solver.cpp:218] Iteration 7080 (2.25724 iter/s, 5.31623s/12 iters), loss = 1.60255
I0405 14:20:07.805167  1863 solver.cpp:237]     Train net output #0: loss = 1.60255 (* 1 = 1.60255 loss)
I0405 14:20:07.805174  1863 sgd_solver.cpp:105] Iteration 7080, lr = 0.001
I0405 14:20:13.151602  1863 solver.cpp:218] Iteration 7092 (2.24449 iter/s, 5.34642s/12 iters), loss = 1.55922
I0405 14:20:13.151664  1863 solver.cpp:237]     Train net output #0: loss = 1.55922 (* 1 = 1.55922 loss)
I0405 14:20:13.151672  1863 sgd_solver.cpp:105] Iteration 7092, lr = 0.001
I0405 14:20:18.401350  1863 solver.cpp:218] Iteration 7104 (2.28585 iter/s, 5.24968s/12 iters), loss = 1.71936
I0405 14:20:18.401389  1863 solver.cpp:237]     Train net output #0: loss = 1.71936 (* 1 = 1.71936 loss)
I0405 14:20:18.401396  1863 sgd_solver.cpp:105] Iteration 7104, lr = 0.001
I0405 14:20:23.648237  1863 solver.cpp:218] Iteration 7116 (2.2871 iter/s, 5.24683s/12 iters), loss = 1.44981
I0405 14:20:23.648293  1863 solver.cpp:237]     Train net output #0: loss = 1.44981 (* 1 = 1.44981 loss)
I0405 14:20:23.648303  1863 sgd_solver.cpp:105] Iteration 7116, lr = 0.001
I0405 14:20:28.917801  1863 solver.cpp:218] Iteration 7128 (2.27726 iter/s, 5.2695s/12 iters), loss = 1.31222
I0405 14:20:28.917836  1863 solver.cpp:237]     Train net output #0: loss = 1.31222 (* 1 = 1.31222 loss)
I0405 14:20:28.917842  1863 sgd_solver.cpp:105] Iteration 7128, lr = 0.001
I0405 14:20:33.583549  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel
I0405 14:20:36.584609  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate
I0405 14:20:40.114248  1863 solver.cpp:330] Iteration 7140, Testing net (#0)
I0405 14:20:40.114271  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:20:41.644745  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:20:44.562355  1863 solver.cpp:397]     Test net output #0: accuracy = 0.177083
I0405 14:20:44.562394  1863 solver.cpp:397]     Test net output #1: loss = 4.24895 (* 1 = 4.24895 loss)
I0405 14:20:44.698472  1863 solver.cpp:218] Iteration 7140 (0.760426 iter/s, 15.7806s/12 iters), loss = 1.66885
I0405 14:20:44.698525  1863 solver.cpp:237]     Train net output #0: loss = 1.66885 (* 1 = 1.66885 loss)
I0405 14:20:44.698534  1863 sgd_solver.cpp:105] Iteration 7140, lr = 0.001
I0405 14:20:49.204361  1863 solver.cpp:218] Iteration 7152 (2.66322 iter/s, 4.50582s/12 iters), loss = 1.71183
I0405 14:20:49.204411  1863 solver.cpp:237]     Train net output #0: loss = 1.71183 (* 1 = 1.71183 loss)
I0405 14:20:49.204416  1863 sgd_solver.cpp:105] Iteration 7152, lr = 0.001
I0405 14:20:54.433547  1863 solver.cpp:218] Iteration 7164 (2.29484 iter/s, 5.22912s/12 iters), loss = 1.47545
I0405 14:20:54.433586  1863 solver.cpp:237]     Train net output #0: loss = 1.47545 (* 1 = 1.47545 loss)
I0405 14:20:54.433591  1863 sgd_solver.cpp:105] Iteration 7164, lr = 0.001
I0405 14:20:59.404202  1863 solver.cpp:218] Iteration 7176 (2.4142 iter/s, 4.9706s/12 iters), loss = 1.53203
I0405 14:20:59.404260  1863 solver.cpp:237]     Train net output #0: loss = 1.53203 (* 1 = 1.53203 loss)
I0405 14:20:59.404269  1863 sgd_solver.cpp:105] Iteration 7176, lr = 0.001
I0405 14:21:01.689658  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:21:04.768545  1863 solver.cpp:218] Iteration 7188 (2.23702 iter/s, 5.36427s/12 iters), loss = 1.56525
I0405 14:21:04.768657  1863 solver.cpp:237]     Train net output #0: loss = 1.56525 (* 1 = 1.56525 loss)
I0405 14:21:04.768664  1863 sgd_solver.cpp:105] Iteration 7188, lr = 0.001
I0405 14:21:09.941323  1863 solver.cpp:218] Iteration 7200 (2.31989 iter/s, 5.17265s/12 iters), loss = 1.61866
I0405 14:21:09.941370  1863 solver.cpp:237]     Train net output #0: loss = 1.61866 (* 1 = 1.61866 loss)
I0405 14:21:09.941376  1863 sgd_solver.cpp:105] Iteration 7200, lr = 0.001
I0405 14:21:15.495767  1863 solver.cpp:218] Iteration 7212 (2.16046 iter/s, 5.55438s/12 iters), loss = 1.5805
I0405 14:21:15.495815  1863 solver.cpp:237]     Train net output #0: loss = 1.5805 (* 1 = 1.5805 loss)
I0405 14:21:15.495820  1863 sgd_solver.cpp:105] Iteration 7212, lr = 0.001
I0405 14:21:20.713035  1863 solver.cpp:218] Iteration 7224 (2.30008 iter/s, 5.21721s/12 iters), loss = 2.27328
I0405 14:21:20.713086  1863 solver.cpp:237]     Train net output #0: loss = 2.27328 (* 1 = 2.27328 loss)
I0405 14:21:20.713094  1863 sgd_solver.cpp:105] Iteration 7224, lr = 0.001
I0405 14:21:26.080461  1863 solver.cpp:218] Iteration 7236 (2.23574 iter/s, 5.36736s/12 iters), loss = 1.49256
I0405 14:21:26.080513  1863 solver.cpp:237]     Train net output #0: loss = 1.49256 (* 1 = 1.49256 loss)
I0405 14:21:26.080523  1863 sgd_solver.cpp:105] Iteration 7236, lr = 0.001
I0405 14:21:28.231436  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel
I0405 14:21:31.264688  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate
I0405 14:21:34.606122  1863 solver.cpp:330] Iteration 7242, Testing net (#0)
I0405 14:21:34.606148  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:21:36.110724  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:21:39.204504  1863 solver.cpp:397]     Test net output #0: accuracy = 0.163603
I0405 14:21:39.204542  1863 solver.cpp:397]     Test net output #1: loss = 4.27834 (* 1 = 4.27834 loss)
I0405 14:21:41.172232  1863 solver.cpp:218] Iteration 7248 (0.795138 iter/s, 15.0917s/12 iters), loss = 1.96292
I0405 14:21:41.172283  1863 solver.cpp:237]     Train net output #0: loss = 1.96292 (* 1 = 1.96292 loss)
I0405 14:21:41.172291  1863 sgd_solver.cpp:105] Iteration 7248, lr = 0.001
I0405 14:21:46.400733  1863 solver.cpp:218] Iteration 7260 (2.29514 iter/s, 5.22844s/12 iters), loss = 1.62679
I0405 14:21:46.400777  1863 solver.cpp:237]     Train net output #0: loss = 1.62679 (* 1 = 1.62679 loss)
I0405 14:21:46.400782  1863 sgd_solver.cpp:105] Iteration 7260, lr = 0.001
I0405 14:21:51.779493  1863 solver.cpp:218] Iteration 7272 (2.23102 iter/s, 5.3787s/12 iters), loss = 1.08621
I0405 14:21:51.779552  1863 solver.cpp:237]     Train net output #0: loss = 1.08621 (* 1 = 1.08621 loss)
I0405 14:21:51.779561  1863 sgd_solver.cpp:105] Iteration 7272, lr = 0.001
I0405 14:21:56.350565  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:21:57.172492  1863 solver.cpp:218] Iteration 7284 (2.22513 iter/s, 5.39293s/12 iters), loss = 1.67724
I0405 14:21:57.172539  1863 solver.cpp:237]     Train net output #0: loss = 1.67724 (* 1 = 1.67724 loss)
I0405 14:21:57.172546  1863 sgd_solver.cpp:105] Iteration 7284, lr = 0.001
I0405 14:22:02.485491  1863 solver.cpp:218] Iteration 7296 (2.25864 iter/s, 5.31294s/12 iters), loss = 1.39463
I0405 14:22:02.485529  1863 solver.cpp:237]     Train net output #0: loss = 1.39463 (* 1 = 1.39463 loss)
I0405 14:22:02.485535  1863 sgd_solver.cpp:105] Iteration 7296, lr = 0.001
I0405 14:22:07.800837  1863 solver.cpp:218] Iteration 7308 (2.25764 iter/s, 5.31529s/12 iters), loss = 1.69034
I0405 14:22:07.801213  1863 solver.cpp:237]     Train net output #0: loss = 1.69034 (* 1 = 1.69034 loss)
I0405 14:22:07.801223  1863 sgd_solver.cpp:105] Iteration 7308, lr = 0.001
I0405 14:22:13.111721  1863 solver.cpp:218] Iteration 7320 (2.25967 iter/s, 5.3105s/12 iters), loss = 1.91061
I0405 14:22:13.111766  1863 solver.cpp:237]     Train net output #0: loss = 1.91061 (* 1 = 1.91061 loss)
I0405 14:22:13.111773  1863 sgd_solver.cpp:105] Iteration 7320, lr = 0.001
I0405 14:22:18.389407  1863 solver.cpp:218] Iteration 7332 (2.27375 iter/s, 5.27762s/12 iters), loss = 1.80008
I0405 14:22:18.389461  1863 solver.cpp:237]     Train net output #0: loss = 1.80008 (* 1 = 1.80008 loss)
I0405 14:22:18.389469  1863 sgd_solver.cpp:105] Iteration 7332, lr = 0.001
I0405 14:22:23.233799  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel
I0405 14:22:26.311278  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate
I0405 14:22:28.882395  1863 solver.cpp:330] Iteration 7344, Testing net (#0)
I0405 14:22:28.882417  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:22:30.357432  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:22:33.198220  1863 solver.cpp:397]     Test net output #0: accuracy = 0.159314
I0405 14:22:33.198267  1863 solver.cpp:397]     Test net output #1: loss = 4.31482 (* 1 = 4.31482 loss)
I0405 14:22:33.339951  1863 solver.cpp:218] Iteration 7344 (0.80265 iter/s, 14.9505s/12 iters), loss = 1.49208
I0405 14:22:33.340062  1863 solver.cpp:237]     Train net output #0: loss = 1.49208 (* 1 = 1.49208 loss)
I0405 14:22:33.340070  1863 sgd_solver.cpp:105] Iteration 7344, lr = 0.001
I0405 14:22:37.639250  1863 solver.cpp:218] Iteration 7356 (2.79123 iter/s, 4.29917s/12 iters), loss = 1.64742
I0405 14:22:37.639300  1863 solver.cpp:237]     Train net output #0: loss = 1.64742 (* 1 = 1.64742 loss)
I0405 14:22:37.639309  1863 sgd_solver.cpp:105] Iteration 7356, lr = 0.001
I0405 14:22:42.900243  1863 solver.cpp:218] Iteration 7368 (2.28096 iter/s, 5.26094s/12 iters), loss = 1.78388
I0405 14:22:42.900363  1863 solver.cpp:237]     Train net output #0: loss = 1.78388 (* 1 = 1.78388 loss)
I0405 14:22:42.900370  1863 sgd_solver.cpp:105] Iteration 7368, lr = 0.001
I0405 14:22:48.072170  1863 solver.cpp:218] Iteration 7380 (2.32028 iter/s, 5.17179s/12 iters), loss = 1.37073
I0405 14:22:48.072212  1863 solver.cpp:237]     Train net output #0: loss = 1.37073 (* 1 = 1.37073 loss)
I0405 14:22:48.072218  1863 sgd_solver.cpp:105] Iteration 7380, lr = 0.001
I0405 14:22:49.624644  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:22:53.416680  1863 solver.cpp:218] Iteration 7392 (2.24532 iter/s, 5.34445s/12 iters), loss = 1.31473
I0405 14:22:53.416736  1863 solver.cpp:237]     Train net output #0: loss = 1.31473 (* 1 = 1.31473 loss)
I0405 14:22:53.416744  1863 sgd_solver.cpp:105] Iteration 7392, lr = 0.001
I0405 14:22:58.655275  1863 solver.cpp:218] Iteration 7404 (2.29072 iter/s, 5.23853s/12 iters), loss = 1.55771
I0405 14:22:58.655318  1863 solver.cpp:237]     Train net output #0: loss = 1.55771 (* 1 = 1.55771 loss)
I0405 14:22:58.655324  1863 sgd_solver.cpp:105] Iteration 7404, lr = 0.001
I0405 14:23:04.006206  1863 solver.cpp:218] Iteration 7416 (2.24263 iter/s, 5.35087s/12 iters), loss = 1.77653
I0405 14:23:04.006263  1863 solver.cpp:237]     Train net output #0: loss = 1.77653 (* 1 = 1.77653 loss)
I0405 14:23:04.006271  1863 sgd_solver.cpp:105] Iteration 7416, lr = 0.001
I0405 14:23:09.189534  1863 solver.cpp:218] Iteration 7428 (2.31515 iter/s, 5.18326s/12 iters), loss = 1.64588
I0405 14:23:09.189594  1863 solver.cpp:237]     Train net output #0: loss = 1.64588 (* 1 = 1.64588 loss)
I0405 14:23:09.189601  1863 sgd_solver.cpp:105] Iteration 7428, lr = 0.001
I0405 14:23:14.579510  1863 solver.cpp:218] Iteration 7440 (2.22638 iter/s, 5.38991s/12 iters), loss = 1.46324
I0405 14:23:14.579617  1863 solver.cpp:237]     Train net output #0: loss = 1.46324 (* 1 = 1.46324 loss)
I0405 14:23:14.579623  1863 sgd_solver.cpp:105] Iteration 7440, lr = 0.001
I0405 14:23:16.713003  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel
I0405 14:23:19.732004  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate
I0405 14:23:22.046479  1863 solver.cpp:330] Iteration 7446, Testing net (#0)
I0405 14:23:22.046504  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:23:23.588866  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:23:26.573877  1863 solver.cpp:397]     Test net output #0: accuracy = 0.172794
I0405 14:23:26.573926  1863 solver.cpp:397]     Test net output #1: loss = 4.31853 (* 1 = 4.31853 loss)
I0405 14:23:28.510310  1863 solver.cpp:218] Iteration 7452 (0.861408 iter/s, 13.9307s/12 iters), loss = 1.36268
I0405 14:23:28.510360  1863 solver.cpp:237]     Train net output #0: loss = 1.36268 (* 1 = 1.36268 loss)
I0405 14:23:28.510366  1863 sgd_solver.cpp:105] Iteration 7452, lr = 0.001
I0405 14:23:33.571732  1863 solver.cpp:218] Iteration 7464 (2.37091 iter/s, 5.06136s/12 iters), loss = 1.53543
I0405 14:23:33.571779  1863 solver.cpp:237]     Train net output #0: loss = 1.53543 (* 1 = 1.53543 loss)
I0405 14:23:33.571789  1863 sgd_solver.cpp:105] Iteration 7464, lr = 0.001
I0405 14:23:38.897858  1863 solver.cpp:218] Iteration 7476 (2.25307 iter/s, 5.32606s/12 iters), loss = 1.33478
I0405 14:23:38.897917  1863 solver.cpp:237]     Train net output #0: loss = 1.33478 (* 1 = 1.33478 loss)
I0405 14:23:38.897925  1863 sgd_solver.cpp:105] Iteration 7476, lr = 0.001
I0405 14:23:42.502280  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:23:44.123359  1863 solver.cpp:218] Iteration 7488 (2.29646 iter/s, 5.22543s/12 iters), loss = 1.43538
I0405 14:23:44.123417  1863 solver.cpp:237]     Train net output #0: loss = 1.43538 (* 1 = 1.43538 loss)
I0405 14:23:44.123426  1863 sgd_solver.cpp:105] Iteration 7488, lr = 0.001
I0405 14:23:49.460400  1863 solver.cpp:218] Iteration 7500 (2.24847 iter/s, 5.33697s/12 iters), loss = 1.3615
I0405 14:23:49.460557  1863 solver.cpp:237]     Train net output #0: loss = 1.3615 (* 1 = 1.3615 loss)
I0405 14:23:49.460568  1863 sgd_solver.cpp:105] Iteration 7500, lr = 0.001
I0405 14:23:54.608650  1863 solver.cpp:218] Iteration 7512 (2.33096 iter/s, 5.14809s/12 iters), loss = 1.31261
I0405 14:23:54.608695  1863 solver.cpp:237]     Train net output #0: loss = 1.31261 (* 1 = 1.31261 loss)
I0405 14:23:54.608700  1863 sgd_solver.cpp:105] Iteration 7512, lr = 0.001
I0405 14:23:59.995878  1863 solver.cpp:218] Iteration 7524 (2.22751 iter/s, 5.38717s/12 iters), loss = 1.32191
I0405 14:23:59.995927  1863 solver.cpp:237]     Train net output #0: loss = 1.32191 (* 1 = 1.32191 loss)
I0405 14:23:59.995935  1863 sgd_solver.cpp:105] Iteration 7524, lr = 0.001
I0405 14:24:05.220744  1863 solver.cpp:218] Iteration 7536 (2.29674 iter/s, 5.22481s/12 iters), loss = 1.42916
I0405 14:24:05.220785  1863 solver.cpp:237]     Train net output #0: loss = 1.42916 (* 1 = 1.42916 loss)
I0405 14:24:05.220791  1863 sgd_solver.cpp:105] Iteration 7536, lr = 0.001
I0405 14:24:09.819438  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel
I0405 14:24:12.885419  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate
I0405 14:24:15.179911  1863 solver.cpp:330] Iteration 7548, Testing net (#0)
I0405 14:24:15.179930  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:24:16.731377  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:24:19.807245  1863 solver.cpp:397]     Test net output #0: accuracy = 0.181373
I0405 14:24:19.807322  1863 solver.cpp:397]     Test net output #1: loss = 4.31812 (* 1 = 4.31812 loss)
I0405 14:24:19.945693  1863 solver.cpp:218] Iteration 7548 (0.814946 iter/s, 14.7249s/12 iters), loss = 1.21337
I0405 14:24:19.945732  1863 solver.cpp:237]     Train net output #0: loss = 1.21337 (* 1 = 1.21337 loss)
I0405 14:24:19.945739  1863 sgd_solver.cpp:105] Iteration 7548, lr = 0.001
I0405 14:24:24.325784  1863 solver.cpp:218] Iteration 7560 (2.73971 iter/s, 4.38003s/12 iters), loss = 1.24496
I0405 14:24:24.325836  1863 solver.cpp:237]     Train net output #0: loss = 1.24496 (* 1 = 1.24496 loss)
I0405 14:24:24.325845  1863 sgd_solver.cpp:105] Iteration 7560, lr = 0.001
I0405 14:24:29.532987  1863 solver.cpp:218] Iteration 7572 (2.30453 iter/s, 5.20714s/12 iters), loss = 1.15579
I0405 14:24:29.533031  1863 solver.cpp:237]     Train net output #0: loss = 1.15579 (* 1 = 1.15579 loss)
I0405 14:24:29.533037  1863 sgd_solver.cpp:105] Iteration 7572, lr = 0.001
I0405 14:24:34.712007  1863 solver.cpp:218] Iteration 7584 (2.31707 iter/s, 5.17896s/12 iters), loss = 1.0965
I0405 14:24:34.712052  1863 solver.cpp:237]     Train net output #0: loss = 1.0965 (* 1 = 1.0965 loss)
I0405 14:24:34.712059  1863 sgd_solver.cpp:105] Iteration 7584, lr = 0.001
I0405 14:24:35.417553  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:24:40.149523  1863 solver.cpp:218] Iteration 7596 (2.20692 iter/s, 5.43745s/12 iters), loss = 1.26668
I0405 14:24:40.149576  1863 solver.cpp:237]     Train net output #0: loss = 1.26668 (* 1 = 1.26668 loss)
I0405 14:24:40.149583  1863 sgd_solver.cpp:105] Iteration 7596, lr = 0.001
I0405 14:24:45.309453  1863 solver.cpp:218] Iteration 7608 (2.32564 iter/s, 5.15987s/12 iters), loss = 1.09141
I0405 14:24:45.309491  1863 solver.cpp:237]     Train net output #0: loss = 1.09141 (* 1 = 1.09141 loss)
I0405 14:24:45.309496  1863 sgd_solver.cpp:105] Iteration 7608, lr = 0.001
I0405 14:24:50.697655  1863 solver.cpp:218] Iteration 7620 (2.22711 iter/s, 5.38815s/12 iters), loss = 1.20155
I0405 14:24:50.697794  1863 solver.cpp:237]     Train net output #0: loss = 1.20155 (* 1 = 1.20155 loss)
I0405 14:24:50.697803  1863 sgd_solver.cpp:105] Iteration 7620, lr = 0.001
I0405 14:24:53.193938  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:24:55.716022  1863 solver.cpp:218] Iteration 7632 (2.39129 iter/s, 5.01822s/12 iters), loss = 1.36988
I0405 14:24:55.716063  1863 solver.cpp:237]     Train net output #0: loss = 1.36988 (* 1 = 1.36988 loss)
I0405 14:24:55.716068  1863 sgd_solver.cpp:105] Iteration 7632, lr = 0.001
I0405 14:25:00.989655  1863 solver.cpp:218] Iteration 7644 (2.27549 iter/s, 5.27358s/12 iters), loss = 1.16063
I0405 14:25:00.989699  1863 solver.cpp:237]     Train net output #0: loss = 1.16063 (* 1 = 1.16063 loss)
I0405 14:25:00.989704  1863 sgd_solver.cpp:105] Iteration 7644, lr = 0.001
I0405 14:25:03.044035  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel
I0405 14:25:06.029448  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate
I0405 14:25:08.334141  1863 solver.cpp:330] Iteration 7650, Testing net (#0)
I0405 14:25:08.334161  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:25:09.724503  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:25:12.741137  1863 solver.cpp:397]     Test net output #0: accuracy = 0.174632
I0405 14:25:12.741168  1863 solver.cpp:397]     Test net output #1: loss = 4.26106 (* 1 = 4.26106 loss)
I0405 14:25:14.539655  1863 solver.cpp:218] Iteration 7656 (0.885613 iter/s, 13.5499s/12 iters), loss = 1.11169
I0405 14:25:14.539710  1863 solver.cpp:237]     Train net output #0: loss = 1.11169 (* 1 = 1.11169 loss)
I0405 14:25:14.539717  1863 sgd_solver.cpp:105] Iteration 7656, lr = 0.001
I0405 14:25:19.701858  1863 solver.cpp:218] Iteration 7668 (2.32462 iter/s, 5.16213s/12 iters), loss = 1.32397
I0405 14:25:19.701915  1863 solver.cpp:237]     Train net output #0: loss = 1.32397 (* 1 = 1.32397 loss)
I0405 14:25:19.701923  1863 sgd_solver.cpp:105] Iteration 7668, lr = 0.001
I0405 14:25:24.766561  1863 solver.cpp:218] Iteration 7680 (2.36937 iter/s, 5.06463s/12 iters), loss = 1.29848
I0405 14:25:24.766674  1863 solver.cpp:237]     Train net output #0: loss = 1.29848 (* 1 = 1.29848 loss)
I0405 14:25:24.766682  1863 sgd_solver.cpp:105] Iteration 7680, lr = 0.001
I0405 14:25:27.841307  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:25:30.152411  1863 solver.cpp:218] Iteration 7692 (2.22811 iter/s, 5.38573s/12 iters), loss = 1.28467
I0405 14:25:30.152449  1863 solver.cpp:237]     Train net output #0: loss = 1.28467 (* 1 = 1.28467 loss)
I0405 14:25:30.152456  1863 sgd_solver.cpp:105] Iteration 7692, lr = 0.001
I0405 14:25:35.454900  1863 solver.cpp:218] Iteration 7704 (2.26311 iter/s, 5.30243s/12 iters), loss = 1.45355
I0405 14:25:35.454942  1863 solver.cpp:237]     Train net output #0: loss = 1.45355 (* 1 = 1.45355 loss)
I0405 14:25:35.454948  1863 sgd_solver.cpp:105] Iteration 7704, lr = 0.001
I0405 14:25:40.643076  1863 solver.cpp:218] Iteration 7716 (2.31298 iter/s, 5.18812s/12 iters), loss = 1.25735
I0405 14:25:40.643121  1863 solver.cpp:237]     Train net output #0: loss = 1.25735 (* 1 = 1.25735 loss)
I0405 14:25:40.643126  1863 sgd_solver.cpp:105] Iteration 7716, lr = 0.001
I0405 14:25:46.001521  1863 solver.cpp:218] Iteration 7728 (2.23948 iter/s, 5.35839s/12 iters), loss = 1.14256
I0405 14:25:46.001561  1863 solver.cpp:237]     Train net output #0: loss = 1.14256 (* 1 = 1.14256 loss)
I0405 14:25:46.001569  1863 sgd_solver.cpp:105] Iteration 7728, lr = 0.001
I0405 14:25:51.161140  1863 solver.cpp:218] Iteration 7740 (2.32578 iter/s, 5.15956s/12 iters), loss = 1.43461
I0405 14:25:51.161191  1863 solver.cpp:237]     Train net output #0: loss = 1.43461 (* 1 = 1.43461 loss)
I0405 14:25:51.161198  1863 sgd_solver.cpp:105] Iteration 7740, lr = 0.001
I0405 14:25:56.019294  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel
I0405 14:25:59.085193  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate
I0405 14:26:01.411576  1863 solver.cpp:330] Iteration 7752, Testing net (#0)
I0405 14:26:01.411602  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:26:02.736836  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:05.974853  1863 solver.cpp:397]     Test net output #0: accuracy = 0.184436
I0405 14:26:05.974880  1863 solver.cpp:397]     Test net output #1: loss = 4.29937 (* 1 = 4.29937 loss)
I0405 14:26:06.116158  1863 solver.cpp:218] Iteration 7752 (0.802409 iter/s, 14.955s/12 iters), loss = 0.983792
I0405 14:26:06.116219  1863 solver.cpp:237]     Train net output #0: loss = 0.983792 (* 1 = 0.983792 loss)
I0405 14:26:06.116226  1863 sgd_solver.cpp:105] Iteration 7752, lr = 0.001
I0405 14:26:10.403935  1863 solver.cpp:218] Iteration 7764 (2.7987 iter/s, 4.2877s/12 iters), loss = 1.15164
I0405 14:26:10.403987  1863 solver.cpp:237]     Train net output #0: loss = 1.15164 (* 1 = 1.15164 loss)
I0405 14:26:10.403998  1863 sgd_solver.cpp:105] Iteration 7764, lr = 0.001
I0405 14:26:15.487610  1863 solver.cpp:218] Iteration 7776 (2.36053 iter/s, 5.08361s/12 iters), loss = 1.1536
I0405 14:26:15.487655  1863 solver.cpp:237]     Train net output #0: loss = 1.1536 (* 1 = 1.1536 loss)
I0405 14:26:15.487660  1863 sgd_solver.cpp:105] Iteration 7776, lr = 0.001
I0405 14:26:20.607332  1863 solver.cpp:218] Iteration 7788 (2.3439 iter/s, 5.11966s/12 iters), loss = 1.33541
I0405 14:26:20.607381  1863 solver.cpp:237]     Train net output #0: loss = 1.33541 (* 1 = 1.33541 loss)
I0405 14:26:20.607388  1863 sgd_solver.cpp:105] Iteration 7788, lr = 0.001
I0405 14:26:20.613888  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:26.088280  1863 solver.cpp:218] Iteration 7800 (2.18943 iter/s, 5.48089s/12 iters), loss = 1.16405
I0405 14:26:26.088440  1863 solver.cpp:237]     Train net output #0: loss = 1.16405 (* 1 = 1.16405 loss)
I0405 14:26:26.088449  1863 sgd_solver.cpp:105] Iteration 7800, lr = 0.001
I0405 14:26:31.466778  1863 solver.cpp:218] Iteration 7812 (2.23118 iter/s, 5.37833s/12 iters), loss = 1.32773
I0405 14:26:31.466827  1863 solver.cpp:237]     Train net output #0: loss = 1.32773 (* 1 = 1.32773 loss)
I0405 14:26:31.466835  1863 sgd_solver.cpp:105] Iteration 7812, lr = 0.001
I0405 14:26:36.557965  1863 solver.cpp:218] Iteration 7824 (2.35704 iter/s, 5.09112s/12 iters), loss = 1.1683
I0405 14:26:36.558009  1863 solver.cpp:237]     Train net output #0: loss = 1.1683 (* 1 = 1.1683 loss)
I0405 14:26:36.558014  1863 sgd_solver.cpp:105] Iteration 7824, lr = 0.001
I0405 14:26:41.728236  1863 solver.cpp:218] Iteration 7836 (2.32099 iter/s, 5.17021s/12 iters), loss = 1.06116
I0405 14:26:41.728276  1863 solver.cpp:237]     Train net output #0: loss = 1.06116 (* 1 = 1.06116 loss)
I0405 14:26:41.728282  1863 sgd_solver.cpp:105] Iteration 7836, lr = 0.001
I0405 14:26:47.169891  1863 solver.cpp:218] Iteration 7848 (2.20524 iter/s, 5.4416s/12 iters), loss = 1.0558
I0405 14:26:47.169958  1863 solver.cpp:237]     Train net output #0: loss = 1.0558 (* 1 = 1.0558 loss)
I0405 14:26:47.169967  1863 sgd_solver.cpp:105] Iteration 7848, lr = 0.001
I0405 14:26:49.251762  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel
I0405 14:26:52.289556  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate
I0405 14:26:54.591482  1863 solver.cpp:330] Iteration 7854, Testing net (#0)
I0405 14:26:54.591501  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:26:55.921151  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:26:59.042400  1863 solver.cpp:397]     Test net output #0: accuracy = 0.191789
I0405 14:26:59.042490  1863 solver.cpp:397]     Test net output #1: loss = 4.2764 (* 1 = 4.2764 loss)
I0405 14:27:00.979454  1863 solver.cpp:218] Iteration 7860 (0.868968 iter/s, 13.8095s/12 iters), loss = 1.50966
I0405 14:27:00.979496  1863 solver.cpp:237]     Train net output #0: loss = 1.50966 (* 1 = 1.50966 loss)
I0405 14:27:00.979501  1863 sgd_solver.cpp:105] Iteration 7860, lr = 0.001
I0405 14:27:06.198071  1863 solver.cpp:218] Iteration 7872 (2.29948 iter/s, 5.21857s/12 iters), loss = 1.41585
I0405 14:27:06.198112  1863 solver.cpp:237]     Train net output #0: loss = 1.41585 (* 1 = 1.41585 loss)
I0405 14:27:06.198117  1863 sgd_solver.cpp:105] Iteration 7872, lr = 0.001
I0405 14:27:11.468875  1863 solver.cpp:218] Iteration 7884 (2.27672 iter/s, 5.27075s/12 iters), loss = 1.01782
I0405 14:27:11.468925  1863 solver.cpp:237]     Train net output #0: loss = 1.01782 (* 1 = 1.01782 loss)
I0405 14:27:11.468932  1863 sgd_solver.cpp:105] Iteration 7884, lr = 0.001
I0405 14:27:13.805078  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:27:16.910271  1863 solver.cpp:218] Iteration 7896 (2.20534 iter/s, 5.44133s/12 iters), loss = 1.06014
I0405 14:27:16.910315  1863 solver.cpp:237]     Train net output #0: loss = 1.06014 (* 1 = 1.06014 loss)
I0405 14:27:16.910321  1863 sgd_solver.cpp:105] Iteration 7896, lr = 0.001
I0405 14:27:22.158555  1863 solver.cpp:218] Iteration 7908 (2.28649 iter/s, 5.24822s/12 iters), loss = 1.50239
I0405 14:27:22.158609  1863 solver.cpp:237]     Train net output #0: loss = 1.50239 (* 1 = 1.50239 loss)
I0405 14:27:22.158618  1863 sgd_solver.cpp:105] Iteration 7908, lr = 0.001
I0405 14:27:27.413190  1863 solver.cpp:218] Iteration 7920 (2.28373 iter/s, 5.25457s/12 iters), loss = 1.22846
I0405 14:27:27.413240  1863 solver.cpp:237]     Train net output #0: loss = 1.22846 (* 1 = 1.22846 loss)
I0405 14:27:27.413249  1863 sgd_solver.cpp:105] Iteration 7920, lr = 0.001
I0405 14:27:32.771646  1863 solver.cpp:218] Iteration 7932 (2.23948 iter/s, 5.35839s/12 iters), loss = 1.12791
I0405 14:27:32.771796  1863 solver.cpp:237]     Train net output #0: loss = 1.12791 (* 1 = 1.12791 loss)
I0405 14:27:32.771803  1863 sgd_solver.cpp:105] Iteration 7932, lr = 0.001
I0405 14:27:37.825727  1863 solver.cpp:218] Iteration 7944 (2.3744 iter/s, 5.05391s/12 iters), loss = 1.42017
I0405 14:27:37.825779  1863 solver.cpp:237]     Train net output #0: loss = 1.42017 (* 1 = 1.42017 loss)
I0405 14:27:37.825788  1863 sgd_solver.cpp:105] Iteration 7944, lr = 0.001
I0405 14:27:42.492230  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel
I0405 14:27:46.075217  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate
I0405 14:27:48.376600  1863 solver.cpp:330] Iteration 7956, Testing net (#0)
I0405 14:27:48.376621  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:27:49.656419  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:27:52.849400  1863 solver.cpp:397]     Test net output #0: accuracy = 0.185662
I0405 14:27:52.849429  1863 solver.cpp:397]     Test net output #1: loss = 4.30779 (* 1 = 4.30779 loss)
I0405 14:27:52.990484  1863 solver.cpp:218] Iteration 7956 (0.791312 iter/s, 15.1647s/12 iters), loss = 1.09664
I0405 14:27:52.992080  1863 solver.cpp:237]     Train net output #0: loss = 1.09664 (* 1 = 1.09664 loss)
I0405 14:27:52.992094  1863 sgd_solver.cpp:105] Iteration 7956, lr = 0.001
I0405 14:27:57.766208  1863 solver.cpp:218] Iteration 7968 (2.51355 iter/s, 4.77412s/12 iters), loss = 1.24313
I0405 14:27:57.766253  1863 solver.cpp:237]     Train net output #0: loss = 1.24313 (* 1 = 1.24313 loss)
I0405 14:27:57.766259  1863 sgd_solver.cpp:105] Iteration 7968, lr = 0.001
I0405 14:28:03.404563  1863 solver.cpp:218] Iteration 7980 (2.1283 iter/s, 5.63829s/12 iters), loss = 0.955546
I0405 14:28:03.404678  1863 solver.cpp:237]     Train net output #0: loss = 0.955546 (* 1 = 0.955546 loss)
I0405 14:28:03.404687  1863 sgd_solver.cpp:105] Iteration 7980, lr = 0.001
I0405 14:28:08.323213  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:09.242835  1863 solver.cpp:218] Iteration 7992 (2.05545 iter/s, 5.83815s/12 iters), loss = 0.975454
I0405 14:28:09.242877  1863 solver.cpp:237]     Train net output #0: loss = 0.975454 (* 1 = 0.975454 loss)
I0405 14:28:09.242883  1863 sgd_solver.cpp:105] Iteration 7992, lr = 0.001
I0405 14:28:14.423647  1863 solver.cpp:218] Iteration 8004 (2.31626 iter/s, 5.18075s/12 iters), loss = 1.24468
I0405 14:28:14.423693  1863 solver.cpp:237]     Train net output #0: loss = 1.24468 (* 1 = 1.24468 loss)
I0405 14:28:14.423702  1863 sgd_solver.cpp:105] Iteration 8004, lr = 0.001
I0405 14:28:19.516418  1863 solver.cpp:218] Iteration 8016 (2.35631 iter/s, 5.09271s/12 iters), loss = 1.36326
I0405 14:28:19.516470  1863 solver.cpp:237]     Train net output #0: loss = 1.36326 (* 1 = 1.36326 loss)
I0405 14:28:19.516479  1863 sgd_solver.cpp:105] Iteration 8016, lr = 0.001
I0405 14:28:24.949831  1863 solver.cpp:218] Iteration 8028 (2.20858 iter/s, 5.43335s/12 iters), loss = 1.01846
I0405 14:28:24.949873  1863 solver.cpp:237]     Train net output #0: loss = 1.01846 (* 1 = 1.01846 loss)
I0405 14:28:24.949880  1863 sgd_solver.cpp:105] Iteration 8028, lr = 0.001
I0405 14:28:30.468891  1863 solver.cpp:218] Iteration 8040 (2.17431 iter/s, 5.519s/12 iters), loss = 1.0353
I0405 14:28:30.468946  1863 solver.cpp:237]     Train net output #0: loss = 1.0353 (* 1 = 1.0353 loss)
I0405 14:28:30.468955  1863 sgd_solver.cpp:105] Iteration 8040, lr = 0.001
I0405 14:28:35.551862  1863 solver.cpp:218] Iteration 8052 (2.36086 iter/s, 5.0829s/12 iters), loss = 1.08934
I0405 14:28:35.551992  1863 solver.cpp:237]     Train net output #0: loss = 1.08934 (* 1 = 1.08934 loss)
I0405 14:28:35.552000  1863 sgd_solver.cpp:105] Iteration 8052, lr = 0.001
I0405 14:28:37.772166  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel
I0405 14:28:40.783699  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate
I0405 14:28:43.090472  1863 solver.cpp:330] Iteration 8058, Testing net (#0)
I0405 14:28:43.090493  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:28:44.350677  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:28:47.552681  1863 solver.cpp:397]     Test net output #0: accuracy = 0.190564
I0405 14:28:47.552716  1863 solver.cpp:397]     Test net output #1: loss = 4.33276 (* 1 = 4.33276 loss)
I0405 14:28:49.580010  1863 solver.cpp:218] Iteration 8064 (0.855432 iter/s, 14.028s/12 iters), loss = 1.14171
I0405 14:28:49.580065  1863 solver.cpp:237]     Train net output #0: loss = 1.14171 (* 1 = 1.14171 loss)
I0405 14:28:49.580073  1863 sgd_solver.cpp:105] Iteration 8064, lr = 0.001
I0405 14:28:54.631433  1863 solver.cpp:218] Iteration 8076 (2.3756 iter/s, 5.05136s/12 iters), loss = 1.43486
I0405 14:28:54.631472  1863 solver.cpp:237]     Train net output #0: loss = 1.43486 (* 1 = 1.43486 loss)
I0405 14:28:54.631479  1863 sgd_solver.cpp:105] Iteration 8076, lr = 0.001
I0405 14:29:00.014432  1863 solver.cpp:218] Iteration 8088 (2.22926 iter/s, 5.38295s/12 iters), loss = 0.831676
I0405 14:29:00.014475  1863 solver.cpp:237]     Train net output #0: loss = 0.831676 (* 1 = 0.831676 loss)
I0405 14:29:00.014482  1863 sgd_solver.cpp:105] Iteration 8088, lr = 0.001
I0405 14:29:01.473233  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:29:05.201571  1863 solver.cpp:218] Iteration 8100 (2.31344 iter/s, 5.18708s/12 iters), loss = 1.11759
I0405 14:29:05.201613  1863 solver.cpp:237]     Train net output #0: loss = 1.11759 (* 1 = 1.11759 loss)
I0405 14:29:05.201619  1863 sgd_solver.cpp:105] Iteration 8100, lr = 0.001
I0405 14:29:10.593499  1863 solver.cpp:218] Iteration 8112 (2.22557 iter/s, 5.39188s/12 iters), loss = 1.26201
I0405 14:29:10.593603  1863 solver.cpp:237]     Train net output #0: loss = 1.26201 (* 1 = 1.26201 loss)
I0405 14:29:10.593611  1863 sgd_solver.cpp:105] Iteration 8112, lr = 0.001
I0405 14:29:16.011482  1863 solver.cpp:218] Iteration 8124 (2.2149 iter/s, 5.41786s/12 iters), loss = 1.13176
I0405 14:29:16.011533  1863 solver.cpp:237]     Train net output #0: loss = 1.13176 (* 1 = 1.13176 loss)
I0405 14:29:16.011539  1863 sgd_solver.cpp:105] Iteration 8124, lr = 0.001
I0405 14:29:21.031925  1863 solver.cpp:218] Iteration 8136 (2.39026 iter/s, 5.02038s/12 iters), loss = 1.13273
I0405 14:29:21.031966  1863 solver.cpp:237]     Train net output #0: loss = 1.13273 (* 1 = 1.13273 loss)
I0405 14:29:21.031973  1863 sgd_solver.cpp:105] Iteration 8136, lr = 0.001
I0405 14:29:26.551376  1863 solver.cpp:218] Iteration 8148 (2.17415 iter/s, 5.51939s/12 iters), loss = 0.983404
I0405 14:29:26.551420  1863 solver.cpp:237]     Train net output #0: loss = 0.983404 (* 1 = 0.983404 loss)
I0405 14:29:26.551426  1863 sgd_solver.cpp:105] Iteration 8148, lr = 0.001
I0405 14:29:31.156129  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel
I0405 14:29:34.215080  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate
I0405 14:29:36.551600  1863 solver.cpp:330] Iteration 8160, Testing net (#0)
I0405 14:29:36.551623  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:29:37.680569  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:29:40.948545  1863 solver.cpp:397]     Test net output #0: accuracy = 0.19424
I0405 14:29:40.948683  1863 solver.cpp:397]     Test net output #1: loss = 4.35196 (* 1 = 4.35196 loss)
I0405 14:29:41.089278  1863 solver.cpp:218] Iteration 8160 (0.825432 iter/s, 14.5378s/12 iters), loss = 0.995382
I0405 14:29:41.089344  1863 solver.cpp:237]     Train net output #0: loss = 0.995382 (* 1 = 0.995382 loss)
I0405 14:29:41.089352  1863 sgd_solver.cpp:105] Iteration 8160, lr = 0.001
I0405 14:29:45.326501  1863 solver.cpp:218] Iteration 8172 (2.8321 iter/s, 4.23714s/12 iters), loss = 0.965777
I0405 14:29:45.326545  1863 solver.cpp:237]     Train net output #0: loss = 0.965777 (* 1 = 0.965777 loss)
I0405 14:29:45.326550  1863 sgd_solver.cpp:105] Iteration 8172, lr = 0.001
I0405 14:29:50.607347  1863 solver.cpp:218] Iteration 8184 (2.27239 iter/s, 5.28079s/12 iters), loss = 1.171
I0405 14:29:50.607389  1863 solver.cpp:237]     Train net output #0: loss = 1.171 (* 1 = 1.171 loss)
I0405 14:29:50.607394  1863 sgd_solver.cpp:105] Iteration 8184, lr = 0.001
I0405 14:29:54.278317  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:29:55.787873  1863 solver.cpp:218] Iteration 8196 (2.31639 iter/s, 5.18046s/12 iters), loss = 1.1451
I0405 14:29:55.787931  1863 solver.cpp:237]     Train net output #0: loss = 1.1451 (* 1 = 1.1451 loss)
I0405 14:29:55.787940  1863 sgd_solver.cpp:105] Iteration 8196, lr = 0.001
I0405 14:30:00.912242  1863 solver.cpp:218] Iteration 8208 (2.34178 iter/s, 5.1243s/12 iters), loss = 1.04244
I0405 14:30:00.912283  1863 solver.cpp:237]     Train net output #0: loss = 1.04244 (* 1 = 1.04244 loss)
I0405 14:30:00.912288  1863 sgd_solver.cpp:105] Iteration 8208, lr = 0.001
I0405 14:30:06.285754  1863 solver.cpp:218] Iteration 8220 (2.2332 iter/s, 5.37346s/12 iters), loss = 1.28195
I0405 14:30:06.285809  1863 solver.cpp:237]     Train net output #0: loss = 1.28195 (* 1 = 1.28195 loss)
I0405 14:30:06.285816  1863 sgd_solver.cpp:105] Iteration 8220, lr = 0.001
I0405 14:30:11.602691  1863 solver.cpp:218] Iteration 8232 (2.25697 iter/s, 5.31687s/12 iters), loss = 1.00795
I0405 14:30:11.602762  1863 solver.cpp:237]     Train net output #0: loss = 1.00795 (* 1 = 1.00795 loss)
I0405 14:30:11.602768  1863 sgd_solver.cpp:105] Iteration 8232, lr = 0.001
I0405 14:30:16.856668  1863 solver.cpp:218] Iteration 8244 (2.28402 iter/s, 5.25389s/12 iters), loss = 0.870433
I0405 14:30:16.856709  1863 solver.cpp:237]     Train net output #0: loss = 0.870433 (* 1 = 0.870433 loss)
I0405 14:30:16.856715  1863 sgd_solver.cpp:105] Iteration 8244, lr = 0.001
I0405 14:30:21.834077  1863 solver.cpp:218] Iteration 8256 (2.41092 iter/s, 4.97735s/12 iters), loss = 1.07615
I0405 14:30:21.834122  1863 solver.cpp:237]     Train net output #0: loss = 1.07615 (* 1 = 1.07615 loss)
I0405 14:30:21.834128  1863 sgd_solver.cpp:105] Iteration 8256, lr = 0.001
I0405 14:30:23.921550  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel
I0405 14:30:27.036332  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate
I0405 14:30:29.331336  1863 solver.cpp:330] Iteration 8262, Testing net (#0)
I0405 14:30:29.331357  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:30:30.557415  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:30:34.037216  1863 solver.cpp:397]     Test net output #0: accuracy = 0.20527
I0405 14:30:34.037246  1863 solver.cpp:397]     Test net output #1: loss = 4.27579 (* 1 = 4.27579 loss)
I0405 14:30:36.025275  1863 solver.cpp:218] Iteration 8268 (0.845598 iter/s, 14.1911s/12 iters), loss = 0.885026
I0405 14:30:36.025311  1863 solver.cpp:237]     Train net output #0: loss = 0.885026 (* 1 = 0.885026 loss)
I0405 14:30:36.025317  1863 sgd_solver.cpp:105] Iteration 8268, lr = 0.001
I0405 14:30:41.358625  1863 solver.cpp:218] Iteration 8280 (2.25002 iter/s, 5.3333s/12 iters), loss = 0.80347
I0405 14:30:41.358666  1863 solver.cpp:237]     Train net output #0: loss = 0.80347 (* 1 = 0.80347 loss)
I0405 14:30:41.358672  1863 sgd_solver.cpp:105] Iteration 8280, lr = 0.001
I0405 14:30:46.626128  1863 solver.cpp:218] Iteration 8292 (2.27814 iter/s, 5.26745s/12 iters), loss = 0.961396
I0405 14:30:46.626302  1863 solver.cpp:237]     Train net output #0: loss = 0.961396 (* 1 = 0.961396 loss)
I0405 14:30:46.626312  1863 sgd_solver.cpp:105] Iteration 8292, lr = 0.001
I0405 14:30:47.242751  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:30:51.474833  1863 solver.cpp:218] Iteration 8304 (2.47498 iter/s, 4.84852s/12 iters), loss = 1.1396
I0405 14:30:51.474879  1863 solver.cpp:237]     Train net output #0: loss = 1.1396 (* 1 = 1.1396 loss)
I0405 14:30:51.474884  1863 sgd_solver.cpp:105] Iteration 8304, lr = 0.001
I0405 14:30:54.425832  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:30:56.764070  1863 solver.cpp:218] Iteration 8316 (2.26878 iter/s, 5.28918s/12 iters), loss = 1.11987
I0405 14:30:56.764118  1863 solver.cpp:237]     Train net output #0: loss = 1.11987 (* 1 = 1.11987 loss)
I0405 14:30:56.764124  1863 sgd_solver.cpp:105] Iteration 8316, lr = 0.001
I0405 14:31:02.035948  1863 solver.cpp:218] Iteration 8328 (2.27626 iter/s, 5.27181s/12 iters), loss = 1.15854
I0405 14:31:02.036005  1863 solver.cpp:237]     Train net output #0: loss = 1.15854 (* 1 = 1.15854 loss)
I0405 14:31:02.036013  1863 sgd_solver.cpp:105] Iteration 8328, lr = 0.001
I0405 14:31:07.127041  1863 solver.cpp:218] Iteration 8340 (2.35709 iter/s, 5.09102s/12 iters), loss = 0.935446
I0405 14:31:07.127102  1863 solver.cpp:237]     Train net output #0: loss = 0.935446 (* 1 = 0.935446 loss)
I0405 14:31:07.127110  1863 sgd_solver.cpp:105] Iteration 8340, lr = 0.001
I0405 14:31:12.202872  1863 solver.cpp:218] Iteration 8352 (2.36418 iter/s, 5.07576s/12 iters), loss = 1.06675
I0405 14:31:12.202915  1863 solver.cpp:237]     Train net output #0: loss = 1.06675 (* 1 = 1.06675 loss)
I0405 14:31:12.202921  1863 sgd_solver.cpp:105] Iteration 8352, lr = 0.001
I0405 14:31:16.868752  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel
I0405 14:31:19.906771  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate
I0405 14:31:22.206225  1863 solver.cpp:330] Iteration 8364, Testing net (#0)
I0405 14:31:22.206246  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:31:23.329522  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:31:26.660125  1863 solver.cpp:397]     Test net output #0: accuracy = 0.191176
I0405 14:31:26.660152  1863 solver.cpp:397]     Test net output #1: loss = 4.28652 (* 1 = 4.28652 loss)
I0405 14:31:26.801080  1863 solver.cpp:218] Iteration 8364 (0.822022 iter/s, 14.5982s/12 iters), loss = 0.706301
I0405 14:31:26.801132  1863 solver.cpp:237]     Train net output #0: loss = 0.706301 (* 1 = 0.706301 loss)
I0405 14:31:26.801141  1863 sgd_solver.cpp:105] Iteration 8364, lr = 0.001
I0405 14:31:31.141592  1863 solver.cpp:218] Iteration 8376 (2.76469 iter/s, 4.34045s/12 iters), loss = 1.12948
I0405 14:31:31.141639  1863 solver.cpp:237]     Train net output #0: loss = 1.12948 (* 1 = 1.12948 loss)
I0405 14:31:31.141647  1863 sgd_solver.cpp:105] Iteration 8376, lr = 0.001
I0405 14:31:36.406894  1863 solver.cpp:218] Iteration 8388 (2.2791 iter/s, 5.26524s/12 iters), loss = 1.07956
I0405 14:31:36.406955  1863 solver.cpp:237]     Train net output #0: loss = 1.07956 (* 1 = 1.07956 loss)
I0405 14:31:36.406962  1863 sgd_solver.cpp:105] Iteration 8388, lr = 0.001
I0405 14:31:39.203070  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:31:41.605845  1863 solver.cpp:218] Iteration 8400 (2.30819 iter/s, 5.19887s/12 iters), loss = 0.888907
I0405 14:31:41.605896  1863 solver.cpp:237]     Train net output #0: loss = 0.888907 (* 1 = 0.888907 loss)
I0405 14:31:41.605906  1863 sgd_solver.cpp:105] Iteration 8400, lr = 0.001
I0405 14:31:46.662812  1863 solver.cpp:218] Iteration 8412 (2.37299 iter/s, 5.05691s/12 iters), loss = 0.737681
I0405 14:31:46.662858  1863 solver.cpp:237]     Train net output #0: loss = 0.737681 (* 1 = 0.737681 loss)
I0405 14:31:46.662865  1863 sgd_solver.cpp:105] Iteration 8412, lr = 0.001
I0405 14:31:51.949374  1863 solver.cpp:218] Iteration 8424 (2.26993 iter/s, 5.2865s/12 iters), loss = 1.26201
I0405 14:31:51.949530  1863 solver.cpp:237]     Train net output #0: loss = 1.26201 (* 1 = 1.26201 loss)
I0405 14:31:51.949539  1863 sgd_solver.cpp:105] Iteration 8424, lr = 0.001
I0405 14:31:57.223847  1863 solver.cpp:218] Iteration 8436 (2.27518 iter/s, 5.27431s/12 iters), loss = 0.650832
I0405 14:31:57.223892  1863 solver.cpp:237]     Train net output #0: loss = 0.650832 (* 1 = 0.650832 loss)
I0405 14:31:57.223897  1863 sgd_solver.cpp:105] Iteration 8436, lr = 0.001
I0405 14:32:02.423182  1863 solver.cpp:218] Iteration 8448 (2.30801 iter/s, 5.19928s/12 iters), loss = 1.08178
I0405 14:32:02.423225  1863 solver.cpp:237]     Train net output #0: loss = 1.08178 (* 1 = 1.08178 loss)
I0405 14:32:02.423230  1863 sgd_solver.cpp:105] Iteration 8448, lr = 0.001
I0405 14:32:07.505195  1863 solver.cpp:218] Iteration 8460 (2.3613 iter/s, 5.08195s/12 iters), loss = 1.03324
I0405 14:32:07.505247  1863 solver.cpp:237]     Train net output #0: loss = 1.03324 (* 1 = 1.03324 loss)
I0405 14:32:07.505255  1863 sgd_solver.cpp:105] Iteration 8460, lr = 0.001
I0405 14:32:09.665771  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel
I0405 14:32:12.685549  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate
I0405 14:32:14.999719  1863 solver.cpp:330] Iteration 8466, Testing net (#0)
I0405 14:32:14.999745  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:32:16.030702  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:32:19.304673  1863 solver.cpp:397]     Test net output #0: accuracy = 0.192402
I0405 14:32:19.304702  1863 solver.cpp:397]     Test net output #1: loss = 4.28915 (* 1 = 4.28915 loss)
I0405 14:32:21.166062  1863 solver.cpp:218] Iteration 8472 (0.878425 iter/s, 13.6608s/12 iters), loss = 1.03619
I0405 14:32:21.166102  1863 solver.cpp:237]     Train net output #0: loss = 1.03619 (* 1 = 1.03619 loss)
I0405 14:32:21.166108  1863 sgd_solver.cpp:105] Iteration 8472, lr = 0.001
I0405 14:32:26.312484  1863 solver.cpp:218] Iteration 8484 (2.33174 iter/s, 5.14636s/12 iters), loss = 0.615466
I0405 14:32:26.312583  1863 solver.cpp:237]     Train net output #0: loss = 0.615466 (* 1 = 0.615466 loss)
I0405 14:32:26.312590  1863 sgd_solver.cpp:105] Iteration 8484, lr = 0.001
I0405 14:32:31.642818  1863 solver.cpp:218] Iteration 8496 (2.25131 iter/s, 5.33022s/12 iters), loss = 1.05746
I0405 14:32:31.642872  1863 solver.cpp:237]     Train net output #0: loss = 1.05746 (* 1 = 1.05746 loss)
I0405 14:32:31.642881  1863 sgd_solver.cpp:105] Iteration 8496, lr = 0.001
I0405 14:32:31.677807  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:32:36.765799  1863 solver.cpp:218] Iteration 8508 (2.34242 iter/s, 5.12291s/12 iters), loss = 0.79465
I0405 14:32:36.765851  1863 solver.cpp:237]     Train net output #0: loss = 0.79465 (* 1 = 0.79465 loss)
I0405 14:32:36.765859  1863 sgd_solver.cpp:105] Iteration 8508, lr = 0.001
I0405 14:32:42.129707  1863 solver.cpp:218] Iteration 8520 (2.2372 iter/s, 5.36384s/12 iters), loss = 0.938856
I0405 14:32:42.129750  1863 solver.cpp:237]     Train net output #0: loss = 0.938856 (* 1 = 0.938856 loss)
I0405 14:32:42.129755  1863 sgd_solver.cpp:105] Iteration 8520, lr = 0.001
I0405 14:32:47.418262  1863 solver.cpp:218] Iteration 8532 (2.26908 iter/s, 5.28849s/12 iters), loss = 0.685209
I0405 14:32:47.418323  1863 solver.cpp:237]     Train net output #0: loss = 0.685209 (* 1 = 0.685209 loss)
I0405 14:32:47.418332  1863 sgd_solver.cpp:105] Iteration 8532, lr = 0.001
I0405 14:32:52.719043  1863 solver.cpp:218] Iteration 8544 (2.26385 iter/s, 5.30071s/12 iters), loss = 1.10119
I0405 14:32:52.719089  1863 solver.cpp:237]     Train net output #0: loss = 1.10119 (* 1 = 1.10119 loss)
I0405 14:32:52.719096  1863 sgd_solver.cpp:105] Iteration 8544, lr = 0.001
I0405 14:32:57.973484  1863 solver.cpp:218] Iteration 8556 (2.28381 iter/s, 5.25438s/12 iters), loss = 0.92272
I0405 14:32:57.975522  1863 solver.cpp:237]     Train net output #0: loss = 0.92272 (* 1 = 0.92272 loss)
I0405 14:32:57.975531  1863 sgd_solver.cpp:105] Iteration 8556, lr = 0.001
I0405 14:33:02.716017  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel
I0405 14:33:05.739220  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate
I0405 14:33:08.048426  1863 solver.cpp:330] Iteration 8568, Testing net (#0)
I0405 14:33:08.048449  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:33:09.046380  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:33:12.371182  1863 solver.cpp:397]     Test net output #0: accuracy = 0.210172
I0405 14:33:12.371217  1863 solver.cpp:397]     Test net output #1: loss = 4.25924 (* 1 = 4.25924 loss)
I0405 14:33:12.512825  1863 solver.cpp:218] Iteration 8568 (0.825463 iter/s, 14.5373s/12 iters), loss = 0.792363
I0405 14:33:12.512871  1863 solver.cpp:237]     Train net output #0: loss = 0.792363 (* 1 = 0.792363 loss)
I0405 14:33:12.512877  1863 sgd_solver.cpp:105] Iteration 8568, lr = 0.001
I0405 14:33:16.784478  1863 solver.cpp:218] Iteration 8580 (2.80926 iter/s, 4.27159s/12 iters), loss = 0.701148
I0405 14:33:16.784528  1863 solver.cpp:237]     Train net output #0: loss = 0.701148 (* 1 = 0.701148 loss)
I0405 14:33:16.784534  1863 sgd_solver.cpp:105] Iteration 8580, lr = 0.001
I0405 14:33:21.851557  1863 solver.cpp:218] Iteration 8592 (2.36826 iter/s, 5.06702s/12 iters), loss = 1.04
I0405 14:33:21.851601  1863 solver.cpp:237]     Train net output #0: loss = 1.04 (* 1 = 1.04 loss)
I0405 14:33:21.851608  1863 sgd_solver.cpp:105] Iteration 8592, lr = 0.001
I0405 14:33:24.105229  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:33:27.124660  1863 solver.cpp:218] Iteration 8604 (2.27572 iter/s, 5.27305s/12 iters), loss = 0.799197
I0405 14:33:27.124701  1863 solver.cpp:237]     Train net output #0: loss = 0.799197 (* 1 = 0.799197 loss)
I0405 14:33:27.124707  1863 sgd_solver.cpp:105] Iteration 8604, lr = 0.001
I0405 14:33:32.623785  1863 solver.cpp:218] Iteration 8616 (2.18219 iter/s, 5.49907s/12 iters), loss = 0.924571
I0405 14:33:32.623898  1863 solver.cpp:237]     Train net output #0: loss = 0.924571 (* 1 = 0.924571 loss)
I0405 14:33:32.623905  1863 sgd_solver.cpp:105] Iteration 8616, lr = 0.001
I0405 14:33:37.994328  1863 solver.cpp:218] Iteration 8628 (2.23446 iter/s, 5.37041s/12 iters), loss = 0.898515
I0405 14:33:37.994379  1863 solver.cpp:237]     Train net output #0: loss = 0.898515 (* 1 = 0.898515 loss)
I0405 14:33:37.994386  1863 sgd_solver.cpp:105] Iteration 8628, lr = 0.001
I0405 14:33:43.280371  1863 solver.cpp:218] Iteration 8640 (2.27016 iter/s, 5.28598s/12 iters), loss = 0.815304
I0405 14:33:43.280427  1863 solver.cpp:237]     Train net output #0: loss = 0.815304 (* 1 = 0.815304 loss)
I0405 14:33:43.280437  1863 sgd_solver.cpp:105] Iteration 8640, lr = 0.001
I0405 14:33:48.417656  1863 solver.cpp:218] Iteration 8652 (2.3359 iter/s, 5.13722s/12 iters), loss = 0.676774
I0405 14:33:48.417701  1863 solver.cpp:237]     Train net output #0: loss = 0.676774 (* 1 = 0.676774 loss)
I0405 14:33:48.417706  1863 sgd_solver.cpp:105] Iteration 8652, lr = 0.001
I0405 14:33:53.807924  1863 solver.cpp:218] Iteration 8664 (2.22626 iter/s, 5.39021s/12 iters), loss = 0.903359
I0405 14:33:53.807981  1863 solver.cpp:237]     Train net output #0: loss = 0.903359 (* 1 = 0.903359 loss)
I0405 14:33:53.807989  1863 sgd_solver.cpp:105] Iteration 8664, lr = 0.001
I0405 14:33:55.958151  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel
I0405 14:33:58.995338  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate
I0405 14:34:01.297746  1863 solver.cpp:330] Iteration 8670, Testing net (#0)
I0405 14:34:01.297767  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:34:02.263314  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:34:05.689996  1863 solver.cpp:397]     Test net output #0: accuracy = 0.213235
I0405 14:34:05.690212  1863 solver.cpp:397]     Test net output #1: loss = 4.25895 (* 1 = 4.25895 loss)
I0405 14:34:07.617462  1863 solver.cpp:218] Iteration 8676 (0.868969 iter/s, 13.8095s/12 iters), loss = 0.837927
I0405 14:34:07.617527  1863 solver.cpp:237]     Train net output #0: loss = 0.837927 (* 1 = 0.837927 loss)
I0405 14:34:07.617537  1863 sgd_solver.cpp:105] Iteration 8676, lr = 0.001
I0405 14:34:12.800781  1863 solver.cpp:218] Iteration 8688 (2.31515 iter/s, 5.18324s/12 iters), loss = 0.717315
I0405 14:34:12.800832  1863 solver.cpp:237]     Train net output #0: loss = 0.717315 (* 1 = 0.717315 loss)
I0405 14:34:12.800839  1863 sgd_solver.cpp:105] Iteration 8688, lr = 0.001
I0405 14:34:17.245559  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:34:18.010205  1863 solver.cpp:218] Iteration 8700 (2.30355 iter/s, 5.20936s/12 iters), loss = 0.792502
I0405 14:34:18.010262  1863 solver.cpp:237]     Train net output #0: loss = 0.792502 (* 1 = 0.792502 loss)
I0405 14:34:18.010270  1863 sgd_solver.cpp:105] Iteration 8700, lr = 0.001
I0405 14:34:23.371944  1863 solver.cpp:218] Iteration 8712 (2.23811 iter/s, 5.36167s/12 iters), loss = 0.959052
I0405 14:34:23.372002  1863 solver.cpp:237]     Train net output #0: loss = 0.959052 (* 1 = 0.959052 loss)
I0405 14:34:23.372011  1863 sgd_solver.cpp:105] Iteration 8712, lr = 0.001
I0405 14:34:28.691429  1863 solver.cpp:218] Iteration 8724 (2.25589 iter/s, 5.31942s/12 iters), loss = 0.966584
I0405 14:34:28.691471  1863 solver.cpp:237]     Train net output #0: loss = 0.966584 (* 1 = 0.966584 loss)
I0405 14:34:28.691478  1863 sgd_solver.cpp:105] Iteration 8724, lr = 0.001
I0405 14:34:33.893421  1863 solver.cpp:218] Iteration 8736 (2.30683 iter/s, 5.20193s/12 iters), loss = 0.816408
I0405 14:34:33.893465  1863 solver.cpp:237]     Train net output #0: loss = 0.816408 (* 1 = 0.816408 loss)
I0405 14:34:33.893471  1863 sgd_solver.cpp:105] Iteration 8736, lr = 0.001
I0405 14:34:39.221652  1863 solver.cpp:218] Iteration 8748 (2.25218 iter/s, 5.32817s/12 iters), loss = 0.652984
I0405 14:34:39.221774  1863 solver.cpp:237]     Train net output #0: loss = 0.652984 (* 1 = 0.652984 loss)
I0405 14:34:39.221783  1863 sgd_solver.cpp:105] Iteration 8748, lr = 0.001
I0405 14:34:44.531538  1863 solver.cpp:218] Iteration 8760 (2.25999 iter/s, 5.30975s/12 iters), loss = 0.801571
I0405 14:34:44.531591  1863 solver.cpp:237]     Train net output #0: loss = 0.801571 (* 1 = 0.801571 loss)
I0405 14:34:44.531599  1863 sgd_solver.cpp:105] Iteration 8760, lr = 0.001
I0405 14:34:49.072319  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel
I0405 14:34:52.096519  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate
I0405 14:34:54.408161  1863 solver.cpp:330] Iteration 8772, Testing net (#0)
I0405 14:34:54.408180  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:34:55.336714  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:34:58.782716  1863 solver.cpp:397]     Test net output #0: accuracy = 0.208946
I0405 14:34:58.782754  1863 solver.cpp:397]     Test net output #1: loss = 4.36944 (* 1 = 4.36944 loss)
I0405 14:34:58.922019  1863 solver.cpp:218] Iteration 8772 (0.833888 iter/s, 14.3904s/12 iters), loss = 0.771685
I0405 14:34:58.922070  1863 solver.cpp:237]     Train net output #0: loss = 0.771685 (* 1 = 0.771685 loss)
I0405 14:34:58.922078  1863 sgd_solver.cpp:105] Iteration 8772, lr = 0.001
I0405 14:35:03.152221  1863 solver.cpp:218] Iteration 8784 (2.83679 iter/s, 4.23014s/12 iters), loss = 0.797509
I0405 14:35:03.152266  1863 solver.cpp:237]     Train net output #0: loss = 0.797509 (* 1 = 0.797509 loss)
I0405 14:35:03.152272  1863 sgd_solver.cpp:105] Iteration 8784, lr = 0.001
I0405 14:35:08.158031  1863 solver.cpp:218] Iteration 8796 (2.39724 iter/s, 5.00575s/12 iters), loss = 0.607087
I0405 14:35:08.158083  1863 solver.cpp:237]     Train net output #0: loss = 0.607087 (* 1 = 0.607087 loss)
I0405 14:35:08.158092  1863 sgd_solver.cpp:105] Iteration 8796, lr = 0.001
I0405 14:35:09.649168  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:35:13.401297  1863 solver.cpp:218] Iteration 8808 (2.28868 iter/s, 5.2432s/12 iters), loss = 0.77196
I0405 14:35:13.401336  1863 solver.cpp:237]     Train net output #0: loss = 0.77196 (* 1 = 0.77196 loss)
I0405 14:35:13.401341  1863 sgd_solver.cpp:105] Iteration 8808, lr = 0.001
I0405 14:35:18.719929  1863 solver.cpp:218] Iteration 8820 (2.25624 iter/s, 5.31858s/12 iters), loss = 0.698523
I0405 14:35:18.719970  1863 solver.cpp:237]     Train net output #0: loss = 0.698523 (* 1 = 0.698523 loss)
I0405 14:35:18.719976  1863 sgd_solver.cpp:105] Iteration 8820, lr = 0.001
I0405 14:35:23.825966  1863 solver.cpp:218] Iteration 8832 (2.35019 iter/s, 5.10598s/12 iters), loss = 0.789174
I0405 14:35:23.826030  1863 solver.cpp:237]     Train net output #0: loss = 0.789174 (* 1 = 0.789174 loss)
I0405 14:35:23.826037  1863 sgd_solver.cpp:105] Iteration 8832, lr = 0.001
I0405 14:35:29.128072  1863 solver.cpp:218] Iteration 8844 (2.26329 iter/s, 5.30203s/12 iters), loss = 0.878986
I0405 14:35:29.128121  1863 solver.cpp:237]     Train net output #0: loss = 0.878986 (* 1 = 0.878986 loss)
I0405 14:35:29.128129  1863 sgd_solver.cpp:105] Iteration 8844, lr = 0.001
I0405 14:35:34.428938  1863 solver.cpp:218] Iteration 8856 (2.26381 iter/s, 5.3008s/12 iters), loss = 0.900076
I0405 14:35:34.428992  1863 solver.cpp:237]     Train net output #0: loss = 0.900076 (* 1 = 0.900076 loss)
I0405 14:35:34.429003  1863 sgd_solver.cpp:105] Iteration 8856, lr = 0.001
I0405 14:35:39.816511  1863 solver.cpp:218] Iteration 8868 (2.22738 iter/s, 5.38751s/12 iters), loss = 0.938563
I0405 14:35:39.816642  1863 solver.cpp:237]     Train net output #0: loss = 0.938563 (* 1 = 0.938563 loss)
I0405 14:35:39.816651  1863 sgd_solver.cpp:105] Iteration 8868, lr = 0.001
I0405 14:35:41.892717  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel
I0405 14:35:44.933144  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate
I0405 14:35:47.239806  1863 solver.cpp:330] Iteration 8874, Testing net (#0)
I0405 14:35:47.239825  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:35:48.099666  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:35:51.511271  1863 solver.cpp:397]     Test net output #0: accuracy = 0.210172
I0405 14:35:51.511307  1863 solver.cpp:397]     Test net output #1: loss = 4.30046 (* 1 = 4.30046 loss)
I0405 14:35:53.525867  1863 solver.cpp:218] Iteration 8880 (0.875324 iter/s, 13.7092s/12 iters), loss = 0.837007
I0405 14:35:53.525920  1863 solver.cpp:237]     Train net output #0: loss = 0.837007 (* 1 = 0.837007 loss)
I0405 14:35:53.525930  1863 sgd_solver.cpp:105] Iteration 8880, lr = 0.001
I0405 14:35:58.629689  1863 solver.cpp:218] Iteration 8892 (2.35121 iter/s, 5.10375s/12 iters), loss = 0.675042
I0405 14:35:58.629736  1863 solver.cpp:237]     Train net output #0: loss = 0.675042 (* 1 = 0.675042 loss)
I0405 14:35:58.629743  1863 sgd_solver.cpp:105] Iteration 8892, lr = 0.001
I0405 14:36:02.360533  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:36:03.914374  1863 solver.cpp:218] Iteration 8904 (2.27074 iter/s, 5.28462s/12 iters), loss = 0.69387
I0405 14:36:03.914422  1863 solver.cpp:237]     Train net output #0: loss = 0.69387 (* 1 = 0.69387 loss)
I0405 14:36:03.914430  1863 sgd_solver.cpp:105] Iteration 8904, lr = 0.001
I0405 14:36:09.149497  1863 solver.cpp:218] Iteration 8916 (2.29223 iter/s, 5.23507s/12 iters), loss = 0.625301
I0405 14:36:09.149538  1863 solver.cpp:237]     Train net output #0: loss = 0.625301 (* 1 = 0.625301 loss)
I0405 14:36:09.149542  1863 sgd_solver.cpp:105] Iteration 8916, lr = 0.001
I0405 14:36:14.525787  1863 solver.cpp:218] Iteration 8928 (2.23204 iter/s, 5.37624s/12 iters), loss = 0.524302
I0405 14:36:14.525899  1863 solver.cpp:237]     Train net output #0: loss = 0.524302 (* 1 = 0.524302 loss)
I0405 14:36:14.525905  1863 sgd_solver.cpp:105] Iteration 8928, lr = 0.001
I0405 14:36:19.823130  1863 solver.cpp:218] Iteration 8940 (2.26534 iter/s, 5.29722s/12 iters), loss = 0.60159
I0405 14:36:19.823174  1863 solver.cpp:237]     Train net output #0: loss = 0.60159 (* 1 = 0.60159 loss)
I0405 14:36:19.823182  1863 sgd_solver.cpp:105] Iteration 8940, lr = 0.001
I0405 14:36:24.973593  1863 solver.cpp:218] Iteration 8952 (2.32991 iter/s, 5.15041s/12 iters), loss = 0.78671
I0405 14:36:24.973631  1863 solver.cpp:237]     Train net output #0: loss = 0.78671 (* 1 = 0.78671 loss)
I0405 14:36:24.973636  1863 sgd_solver.cpp:105] Iteration 8952, lr = 0.001
I0405 14:36:30.317961  1863 solver.cpp:218] Iteration 8964 (2.24538 iter/s, 5.34431s/12 iters), loss = 0.768469
I0405 14:36:30.318011  1863 solver.cpp:237]     Train net output #0: loss = 0.768469 (* 1 = 0.768469 loss)
I0405 14:36:30.318018  1863 sgd_solver.cpp:105] Iteration 8964, lr = 0.001
I0405 14:36:35.208546  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel
I0405 14:36:38.210917  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate
I0405 14:36:40.524976  1863 solver.cpp:330] Iteration 8976, Testing net (#0)
I0405 14:36:40.524998  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:36:41.375217  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:36:44.896087  1863 solver.cpp:397]     Test net output #0: accuracy = 0.223039
I0405 14:36:44.896185  1863 solver.cpp:397]     Test net output #1: loss = 4.34148 (* 1 = 4.34148 loss)
I0405 14:36:45.027391  1863 solver.cpp:218] Iteration 8976 (0.815806 iter/s, 14.7094s/12 iters), loss = 0.605519
I0405 14:36:45.027452  1863 solver.cpp:237]     Train net output #0: loss = 0.605519 (* 1 = 0.605519 loss)
I0405 14:36:45.027460  1863 sgd_solver.cpp:105] Iteration 8976, lr = 0.001
I0405 14:36:49.287937  1863 solver.cpp:218] Iteration 8988 (2.81659 iter/s, 4.26047s/12 iters), loss = 0.662237
I0405 14:36:49.287977  1863 solver.cpp:237]     Train net output #0: loss = 0.662237 (* 1 = 0.662237 loss)
I0405 14:36:49.287982  1863 sgd_solver.cpp:105] Iteration 8988, lr = 0.001
I0405 14:36:52.665562  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:36:54.469856  1863 solver.cpp:218] Iteration 9000 (2.31577 iter/s, 5.18186s/12 iters), loss = 0.973305
I0405 14:36:54.469910  1863 solver.cpp:237]     Train net output #0: loss = 0.973305 (* 1 = 0.973305 loss)
I0405 14:36:54.469918  1863 sgd_solver.cpp:105] Iteration 9000, lr = 0.001
I0405 14:36:55.133972  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:36:59.908212  1863 solver.cpp:218] Iteration 9012 (2.20658 iter/s, 5.43829s/12 iters), loss = 0.810762
I0405 14:36:59.908270  1863 solver.cpp:237]     Train net output #0: loss = 0.810762 (* 1 = 0.810762 loss)
I0405 14:36:59.908278  1863 sgd_solver.cpp:105] Iteration 9012, lr = 0.001
I0405 14:37:05.107556  1863 solver.cpp:218] Iteration 9024 (2.30802 iter/s, 5.19927s/12 iters), loss = 0.745238
I0405 14:37:05.107599  1863 solver.cpp:237]     Train net output #0: loss = 0.745238 (* 1 = 0.745238 loss)
I0405 14:37:05.107604  1863 sgd_solver.cpp:105] Iteration 9024, lr = 0.001
I0405 14:37:10.462460  1863 solver.cpp:218] Iteration 9036 (2.24096 iter/s, 5.35485s/12 iters), loss = 0.543304
I0405 14:37:10.462505  1863 solver.cpp:237]     Train net output #0: loss = 0.543304 (* 1 = 0.543304 loss)
I0405 14:37:10.462512  1863 sgd_solver.cpp:105] Iteration 9036, lr = 0.001
I0405 14:37:15.635071  1863 solver.cpp:218] Iteration 9048 (2.31994 iter/s, 5.17255s/12 iters), loss = 0.748061
I0405 14:37:15.648969  1863 solver.cpp:237]     Train net output #0: loss = 0.748061 (* 1 = 0.748061 loss)
I0405 14:37:15.648986  1863 sgd_solver.cpp:105] Iteration 9048, lr = 0.001
I0405 14:37:20.918107  1863 solver.cpp:218] Iteration 9060 (2.27741 iter/s, 5.26914s/12 iters), loss = 0.468138
I0405 14:37:20.918149  1863 solver.cpp:237]     Train net output #0: loss = 0.468138 (* 1 = 0.468138 loss)
I0405 14:37:20.918155  1863 sgd_solver.cpp:105] Iteration 9060, lr = 0.001
I0405 14:37:26.229545  1863 solver.cpp:218] Iteration 9072 (2.2593 iter/s, 5.31138s/12 iters), loss = 0.486985
I0405 14:37:26.229590  1863 solver.cpp:237]     Train net output #0: loss = 0.486985 (* 1 = 0.486985 loss)
I0405 14:37:26.229596  1863 sgd_solver.cpp:105] Iteration 9072, lr = 0.001
I0405 14:37:28.467898  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel
I0405 14:37:31.448709  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate
I0405 14:37:34.195789  1863 solver.cpp:330] Iteration 9078, Testing net (#0)
I0405 14:37:34.195812  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:37:35.087774  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:37:38.682895  1863 solver.cpp:397]     Test net output #0: accuracy = 0.215686
I0405 14:37:38.682929  1863 solver.cpp:397]     Test net output #1: loss = 4.30672 (* 1 = 4.30672 loss)
I0405 14:37:40.525863  1863 solver.cpp:218] Iteration 9084 (0.83938 iter/s, 14.2963s/12 iters), loss = 0.710508
I0405 14:37:40.525910  1863 solver.cpp:237]     Train net output #0: loss = 0.710508 (* 1 = 0.710508 loss)
I0405 14:37:40.525916  1863 sgd_solver.cpp:105] Iteration 9084, lr = 0.001
I0405 14:37:45.696848  1863 solver.cpp:218] Iteration 9096 (2.32067 iter/s, 5.17092s/12 iters), loss = 0.582865
I0405 14:37:45.696967  1863 solver.cpp:237]     Train net output #0: loss = 0.582865 (* 1 = 0.582865 loss)
I0405 14:37:45.696977  1863 sgd_solver.cpp:105] Iteration 9096, lr = 0.001
I0405 14:37:48.594434  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:37:50.818418  1863 solver.cpp:218] Iteration 9108 (2.3431 iter/s, 5.12143s/12 iters), loss = 0.697037
I0405 14:37:50.818468  1863 solver.cpp:237]     Train net output #0: loss = 0.697037 (* 1 = 0.697037 loss)
I0405 14:37:50.818477  1863 sgd_solver.cpp:105] Iteration 9108, lr = 0.001
I0405 14:37:56.076933  1863 solver.cpp:218] Iteration 9120 (2.28204 iter/s, 5.25845s/12 iters), loss = 0.683738
I0405 14:37:56.076987  1863 solver.cpp:237]     Train net output #0: loss = 0.683738 (* 1 = 0.683738 loss)
I0405 14:37:56.076997  1863 sgd_solver.cpp:105] Iteration 9120, lr = 0.001
I0405 14:38:01.487845  1863 solver.cpp:218] Iteration 9132 (2.21777 iter/s, 5.41084s/12 iters), loss = 0.812555
I0405 14:38:01.487887  1863 solver.cpp:237]     Train net output #0: loss = 0.812555 (* 1 = 0.812555 loss)
I0405 14:38:01.487893  1863 sgd_solver.cpp:105] Iteration 9132, lr = 0.001
I0405 14:38:06.694008  1863 solver.cpp:218] Iteration 9144 (2.30499 iter/s, 5.2061s/12 iters), loss = 0.650377
I0405 14:38:06.694062  1863 solver.cpp:237]     Train net output #0: loss = 0.650377 (* 1 = 0.650377 loss)
I0405 14:38:06.694072  1863 sgd_solver.cpp:105] Iteration 9144, lr = 0.001
I0405 14:38:12.079854  1863 solver.cpp:218] Iteration 9156 (2.22809 iter/s, 5.38578s/12 iters), loss = 0.893754
I0405 14:38:12.079900  1863 solver.cpp:237]     Train net output #0: loss = 0.893754 (* 1 = 0.893754 loss)
I0405 14:38:12.079906  1863 sgd_solver.cpp:105] Iteration 9156, lr = 0.001
I0405 14:38:17.243592  1863 solver.cpp:218] Iteration 9168 (2.32393 iter/s, 5.16368s/12 iters), loss = 0.825082
I0405 14:38:17.243714  1863 solver.cpp:237]     Train net output #0: loss = 0.825082 (* 1 = 0.825082 loss)
I0405 14:38:17.243734  1863 sgd_solver.cpp:105] Iteration 9168, lr = 0.001
I0405 14:38:21.977797  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel
I0405 14:38:25.015650  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate
I0405 14:38:27.503885  1863 solver.cpp:330] Iteration 9180, Testing net (#0)
I0405 14:38:27.503904  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:38:28.272102  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:38:31.809046  1863 solver.cpp:397]     Test net output #0: accuracy = 0.216912
I0405 14:38:31.809089  1863 solver.cpp:397]     Test net output #1: loss = 4.45031 (* 1 = 4.45031 loss)
I0405 14:38:31.950150  1863 solver.cpp:218] Iteration 9180 (0.81597 iter/s, 14.7064s/12 iters), loss = 0.582985
I0405 14:38:31.950208  1863 solver.cpp:237]     Train net output #0: loss = 0.582985 (* 1 = 0.582985 loss)
I0405 14:38:31.950218  1863 sgd_solver.cpp:105] Iteration 9180, lr = 0.001
I0405 14:38:36.148048  1863 solver.cpp:218] Iteration 9192 (2.85863 iter/s, 4.19782s/12 iters), loss = 0.565389
I0405 14:38:36.148102  1863 solver.cpp:237]     Train net output #0: loss = 0.565389 (* 1 = 0.565389 loss)
I0405 14:38:36.148109  1863 sgd_solver.cpp:105] Iteration 9192, lr = 0.001
I0405 14:38:41.572240  1863 solver.cpp:218] Iteration 9204 (2.21234 iter/s, 5.42413s/12 iters), loss = 0.657689
I0405 14:38:41.572278  1863 solver.cpp:237]     Train net output #0: loss = 0.657689 (* 1 = 0.657689 loss)
I0405 14:38:41.572284  1863 sgd_solver.cpp:105] Iteration 9204, lr = 0.001
I0405 14:38:41.634037  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:38:47.123968  1863 solver.cpp:218] Iteration 9216 (2.16151 iter/s, 5.55167s/12 iters), loss = 0.948261
I0405 14:38:47.124012  1863 solver.cpp:237]     Train net output #0: loss = 0.948261 (* 1 = 0.948261 loss)
I0405 14:38:47.124018  1863 sgd_solver.cpp:105] Iteration 9216, lr = 0.001
I0405 14:38:52.517033  1863 solver.cpp:218] Iteration 9228 (2.2251 iter/s, 5.39301s/12 iters), loss = 0.720008
I0405 14:38:52.517127  1863 solver.cpp:237]     Train net output #0: loss = 0.720008 (* 1 = 0.720008 loss)
I0405 14:38:52.517132  1863 sgd_solver.cpp:105] Iteration 9228, lr = 0.001
I0405 14:38:57.781251  1863 solver.cpp:218] Iteration 9240 (2.27959 iter/s, 5.26411s/12 iters), loss = 0.677995
I0405 14:38:57.781292  1863 solver.cpp:237]     Train net output #0: loss = 0.677995 (* 1 = 0.677995 loss)
I0405 14:38:57.781298  1863 sgd_solver.cpp:105] Iteration 9240, lr = 0.001
I0405 14:39:03.194247  1863 solver.cpp:218] Iteration 9252 (2.21691 iter/s, 5.41293s/12 iters), loss = 0.878166
I0405 14:39:03.194304  1863 solver.cpp:237]     Train net output #0: loss = 0.878166 (* 1 = 0.878166 loss)
I0405 14:39:03.194314  1863 sgd_solver.cpp:105] Iteration 9252, lr = 0.001
I0405 14:39:08.446707  1863 solver.cpp:218] Iteration 9264 (2.28467 iter/s, 5.25239s/12 iters), loss = 0.640333
I0405 14:39:08.446748  1863 solver.cpp:237]     Train net output #0: loss = 0.640333 (* 1 = 0.640333 loss)
I0405 14:39:08.446754  1863 sgd_solver.cpp:105] Iteration 9264, lr = 0.001
I0405 14:39:13.772222  1863 solver.cpp:218] Iteration 9276 (2.25333 iter/s, 5.32546s/12 iters), loss = 0.574499
I0405 14:39:13.772264  1863 solver.cpp:237]     Train net output #0: loss = 0.574499 (* 1 = 0.574499 loss)
I0405 14:39:13.772269  1863 sgd_solver.cpp:105] Iteration 9276, lr = 0.001
I0405 14:39:15.978358  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel
I0405 14:39:19.056288  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate
I0405 14:39:22.140738  1863 solver.cpp:330] Iteration 9282, Testing net (#0)
I0405 14:39:22.140760  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:39:22.898864  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:39:26.544821  1863 solver.cpp:397]     Test net output #0: accuracy = 0.223652
I0405 14:39:26.544870  1863 solver.cpp:397]     Test net output #1: loss = 4.34085 (* 1 = 4.34085 loss)
I0405 14:39:28.395645  1863 solver.cpp:218] Iteration 9288 (0.820605 iter/s, 14.6234s/12 iters), loss = 0.705223
I0405 14:39:28.395711  1863 solver.cpp:237]     Train net output #0: loss = 0.705223 (* 1 = 0.705223 loss)
I0405 14:39:28.395720  1863 sgd_solver.cpp:105] Iteration 9288, lr = 0.001
I0405 14:39:33.513126  1863 solver.cpp:218] Iteration 9300 (2.34494 iter/s, 5.1174s/12 iters), loss = 0.548925
I0405 14:39:33.513175  1863 solver.cpp:237]     Train net output #0: loss = 0.548925 (* 1 = 0.548925 loss)
I0405 14:39:33.513181  1863 sgd_solver.cpp:105] Iteration 9300, lr = 0.001
I0405 14:39:35.761005  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:39:38.656358  1863 solver.cpp:218] Iteration 9312 (2.33319 iter/s, 5.14317s/12 iters), loss = 0.603621
I0405 14:39:38.656419  1863 solver.cpp:237]     Train net output #0: loss = 0.603621 (* 1 = 0.603621 loss)
I0405 14:39:38.656428  1863 sgd_solver.cpp:105] Iteration 9312, lr = 0.001
I0405 14:39:43.978580  1863 solver.cpp:218] Iteration 9324 (2.25473 iter/s, 5.32215s/12 iters), loss = 0.611842
I0405 14:39:43.978626  1863 solver.cpp:237]     Train net output #0: loss = 0.611842 (* 1 = 0.611842 loss)
I0405 14:39:43.978631  1863 sgd_solver.cpp:105] Iteration 9324, lr = 0.001
I0405 14:39:49.221029  1863 solver.cpp:218] Iteration 9336 (2.28903 iter/s, 5.24239s/12 iters), loss = 0.590982
I0405 14:39:49.221076  1863 solver.cpp:237]     Train net output #0: loss = 0.590982 (* 1 = 0.590982 loss)
I0405 14:39:49.221082  1863 sgd_solver.cpp:105] Iteration 9336, lr = 0.001
I0405 14:39:54.366029  1863 solver.cpp:218] Iteration 9348 (2.33239 iter/s, 5.14494s/12 iters), loss = 0.647094
I0405 14:39:54.366153  1863 solver.cpp:237]     Train net output #0: loss = 0.647094 (* 1 = 0.647094 loss)
I0405 14:39:54.366159  1863 sgd_solver.cpp:105] Iteration 9348, lr = 0.001
I0405 14:39:59.712899  1863 solver.cpp:218] Iteration 9360 (2.24436 iter/s, 5.34672s/12 iters), loss = 0.55806
I0405 14:39:59.712956  1863 solver.cpp:237]     Train net output #0: loss = 0.55806 (* 1 = 0.55806 loss)
I0405 14:39:59.712965  1863 sgd_solver.cpp:105] Iteration 9360, lr = 0.001
I0405 14:40:04.988620  1863 solver.cpp:218] Iteration 9372 (2.2746 iter/s, 5.27565s/12 iters), loss = 0.595931
I0405 14:40:04.988677  1863 solver.cpp:237]     Train net output #0: loss = 0.595931 (* 1 = 0.595931 loss)
I0405 14:40:04.988685  1863 sgd_solver.cpp:105] Iteration 9372, lr = 0.001
I0405 14:40:09.684644  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel
I0405 14:40:12.735023  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate
I0405 14:40:15.791512  1863 solver.cpp:330] Iteration 9384, Testing net (#0)
I0405 14:40:15.791530  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:40:16.510720  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:40:20.166502  1863 solver.cpp:397]     Test net output #0: accuracy = 0.228554
I0405 14:40:20.166543  1863 solver.cpp:397]     Test net output #1: loss = 4.37432 (* 1 = 4.37432 loss)
I0405 14:40:20.301419  1863 solver.cpp:218] Iteration 9384 (0.783662 iter/s, 15.3127s/12 iters), loss = 0.533907
I0405 14:40:20.301479  1863 solver.cpp:237]     Train net output #0: loss = 0.533907 (* 1 = 0.533907 loss)
I0405 14:40:20.301487  1863 sgd_solver.cpp:105] Iteration 9384, lr = 0.001
I0405 14:40:24.682020  1863 solver.cpp:218] Iteration 9396 (2.7394 iter/s, 4.38052s/12 iters), loss = 0.588942
I0405 14:40:24.682123  1863 solver.cpp:237]     Train net output #0: loss = 0.588942 (* 1 = 0.588942 loss)
I0405 14:40:24.682132  1863 sgd_solver.cpp:105] Iteration 9396, lr = 0.001
I0405 14:40:29.261271  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:40:29.995857  1863 solver.cpp:218] Iteration 9408 (2.2583 iter/s, 5.31372s/12 iters), loss = 0.508008
I0405 14:40:29.995894  1863 solver.cpp:237]     Train net output #0: loss = 0.508008 (* 1 = 0.508008 loss)
I0405 14:40:29.995899  1863 sgd_solver.cpp:105] Iteration 9408, lr = 0.001
I0405 14:40:35.263250  1863 solver.cpp:218] Iteration 9420 (2.27819 iter/s, 5.26734s/12 iters), loss = 0.645514
I0405 14:40:35.263293  1863 solver.cpp:237]     Train net output #0: loss = 0.645514 (* 1 = 0.645514 loss)
I0405 14:40:35.263298  1863 sgd_solver.cpp:105] Iteration 9420, lr = 0.001
I0405 14:40:40.443482  1863 solver.cpp:218] Iteration 9432 (2.31653 iter/s, 5.18017s/12 iters), loss = 0.402178
I0405 14:40:40.443536  1863 solver.cpp:237]     Train net output #0: loss = 0.402178 (* 1 = 0.402178 loss)
I0405 14:40:40.443543  1863 sgd_solver.cpp:105] Iteration 9432, lr = 0.001
I0405 14:40:45.753196  1863 solver.cpp:218] Iteration 9444 (2.26004 iter/s, 5.30964s/12 iters), loss = 0.754394
I0405 14:40:45.753242  1863 solver.cpp:237]     Train net output #0: loss = 0.754394 (* 1 = 0.754394 loss)
I0405 14:40:45.753248  1863 sgd_solver.cpp:105] Iteration 9444, lr = 0.001
I0405 14:40:50.973395  1863 solver.cpp:218] Iteration 9456 (2.29879 iter/s, 5.22014s/12 iters), loss = 0.609527
I0405 14:40:50.973438  1863 solver.cpp:237]     Train net output #0: loss = 0.609527 (* 1 = 0.609527 loss)
I0405 14:40:50.973443  1863 sgd_solver.cpp:105] Iteration 9456, lr = 0.001
I0405 14:40:56.352730  1863 solver.cpp:218] Iteration 9468 (2.23078 iter/s, 5.37927s/12 iters), loss = 0.665707
I0405 14:40:56.352847  1863 solver.cpp:237]     Train net output #0: loss = 0.665707 (* 1 = 0.665707 loss)
I0405 14:40:56.352854  1863 sgd_solver.cpp:105] Iteration 9468, lr = 0.001
I0405 14:41:01.664991  1863 solver.cpp:218] Iteration 9480 (2.25898 iter/s, 5.31213s/12 iters), loss = 0.66145
I0405 14:41:01.665050  1863 solver.cpp:237]     Train net output #0: loss = 0.66145 (* 1 = 0.66145 loss)
I0405 14:41:01.665058  1863 sgd_solver.cpp:105] Iteration 9480, lr = 0.001
I0405 14:41:03.717594  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel
I0405 14:41:07.221614  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate
I0405 14:41:09.600555  1863 solver.cpp:330] Iteration 9486, Testing net (#0)
I0405 14:41:09.600575  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:41:10.304855  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:41:14.074883  1863 solver.cpp:397]     Test net output #0: accuracy = 0.229167
I0405 14:41:14.074931  1863 solver.cpp:397]     Test net output #1: loss = 4.41048 (* 1 = 4.41048 loss)
I0405 14:41:16.037182  1863 solver.cpp:218] Iteration 9492 (0.83495 iter/s, 14.3721s/12 iters), loss = 0.74024
I0405 14:41:16.037235  1863 solver.cpp:237]     Train net output #0: loss = 0.74024 (* 1 = 0.74024 loss)
I0405 14:41:16.037242  1863 sgd_solver.cpp:105] Iteration 9492, lr = 0.001
I0405 14:41:21.224483  1863 solver.cpp:218] Iteration 9504 (2.31337 iter/s, 5.18724s/12 iters), loss = 0.479841
I0405 14:41:21.224536  1863 solver.cpp:237]     Train net output #0: loss = 0.479841 (* 1 = 0.479841 loss)
I0405 14:41:21.224545  1863 sgd_solver.cpp:105] Iteration 9504, lr = 0.001
I0405 14:41:22.815897  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:41:26.563364  1863 solver.cpp:218] Iteration 9516 (2.24769 iter/s, 5.33881s/12 iters), loss = 0.461515
I0405 14:41:26.563482  1863 solver.cpp:237]     Train net output #0: loss = 0.461515 (* 1 = 0.461515 loss)
I0405 14:41:26.563491  1863 sgd_solver.cpp:105] Iteration 9516, lr = 0.001
I0405 14:41:31.759982  1863 solver.cpp:218] Iteration 9528 (2.30925 iter/s, 5.19648s/12 iters), loss = 0.443389
I0405 14:41:31.760028  1863 solver.cpp:237]     Train net output #0: loss = 0.443389 (* 1 = 0.443389 loss)
I0405 14:41:31.760035  1863 sgd_solver.cpp:105] Iteration 9528, lr = 0.001
I0405 14:41:37.030357  1863 solver.cpp:218] Iteration 9540 (2.2769 iter/s, 5.27032s/12 iters), loss = 0.518856
I0405 14:41:37.030405  1863 solver.cpp:237]     Train net output #0: loss = 0.518856 (* 1 = 0.518856 loss)
I0405 14:41:37.030411  1863 sgd_solver.cpp:105] Iteration 9540, lr = 0.001
I0405 14:41:42.363468  1863 solver.cpp:218] Iteration 9552 (2.25012 iter/s, 5.33305s/12 iters), loss = 0.566103
I0405 14:41:42.363508  1863 solver.cpp:237]     Train net output #0: loss = 0.566103 (* 1 = 0.566103 loss)
I0405 14:41:42.363514  1863 sgd_solver.cpp:105] Iteration 9552, lr = 0.001
I0405 14:41:47.639390  1863 solver.cpp:218] Iteration 9564 (2.27451 iter/s, 5.27587s/12 iters), loss = 0.472259
I0405 14:41:47.639444  1863 solver.cpp:237]     Train net output #0: loss = 0.472259 (* 1 = 0.472259 loss)
I0405 14:41:47.639453  1863 sgd_solver.cpp:105] Iteration 9564, lr = 0.001
I0405 14:41:52.549823  1863 solver.cpp:218] Iteration 9576 (2.44381 iter/s, 4.91037s/12 iters), loss = 0.652366
I0405 14:41:52.549872  1863 solver.cpp:237]     Train net output #0: loss = 0.652366 (* 1 = 0.652366 loss)
I0405 14:41:52.549880  1863 sgd_solver.cpp:105] Iteration 9576, lr = 0.001
I0405 14:41:57.370443  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel
I0405 14:42:01.128718  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate
I0405 14:42:03.432524  1863 solver.cpp:330] Iteration 9588, Testing net (#0)
I0405 14:42:03.432545  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:42:04.081542  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:42:07.751091  1863 solver.cpp:397]     Test net output #0: accuracy = 0.228554
I0405 14:42:07.751125  1863 solver.cpp:397]     Test net output #1: loss = 4.37878 (* 1 = 4.37878 loss)
I0405 14:42:07.894380  1863 solver.cpp:218] Iteration 9588 (0.782039 iter/s, 15.3445s/12 iters), loss = 0.294607
I0405 14:42:07.894435  1863 solver.cpp:237]     Train net output #0: loss = 0.294607 (* 1 = 0.294607 loss)
I0405 14:42:07.894443  1863 sgd_solver.cpp:105] Iteration 9588, lr = 0.001
I0405 14:42:12.239113  1863 solver.cpp:218] Iteration 9600 (2.76201 iter/s, 4.34466s/12 iters), loss = 0.357172
I0405 14:42:12.239156  1863 solver.cpp:237]     Train net output #0: loss = 0.357172 (* 1 = 0.357172 loss)
I0405 14:42:12.239162  1863 sgd_solver.cpp:105] Iteration 9600, lr = 0.001
I0405 14:42:15.928915  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:42:17.462931  1863 solver.cpp:218] Iteration 9612 (2.2972 iter/s, 5.22376s/12 iters), loss = 0.456625
I0405 14:42:17.462972  1863 solver.cpp:237]     Train net output #0: loss = 0.456625 (* 1 = 0.456625 loss)
I0405 14:42:17.462978  1863 sgd_solver.cpp:105] Iteration 9612, lr = 0.001
I0405 14:42:22.800858  1863 solver.cpp:218] Iteration 9624 (2.24809 iter/s, 5.33787s/12 iters), loss = 0.634906
I0405 14:42:22.800904  1863 solver.cpp:237]     Train net output #0: loss = 0.634906 (* 1 = 0.634906 loss)
I0405 14:42:22.800912  1863 sgd_solver.cpp:105] Iteration 9624, lr = 0.001
I0405 14:42:28.195086  1863 solver.cpp:218] Iteration 9636 (2.22463 iter/s, 5.39416s/12 iters), loss = 0.507932
I0405 14:42:28.195173  1863 solver.cpp:237]     Train net output #0: loss = 0.507932 (* 1 = 0.507932 loss)
I0405 14:42:28.195179  1863 sgd_solver.cpp:105] Iteration 9636, lr = 0.001
I0405 14:42:33.455155  1863 solver.cpp:218] Iteration 9648 (2.28138 iter/s, 5.25997s/12 iters), loss = 0.636248
I0405 14:42:33.455201  1863 solver.cpp:237]     Train net output #0: loss = 0.636248 (* 1 = 0.636248 loss)
I0405 14:42:33.455207  1863 sgd_solver.cpp:105] Iteration 9648, lr = 0.001
I0405 14:42:38.821125  1863 solver.cpp:218] Iteration 9660 (2.23634 iter/s, 5.36591s/12 iters), loss = 0.637123
I0405 14:42:38.821163  1863 solver.cpp:237]     Train net output #0: loss = 0.637123 (* 1 = 0.637123 loss)
I0405 14:42:38.821169  1863 sgd_solver.cpp:105] Iteration 9660, lr = 0.001
I0405 14:42:44.125209  1863 solver.cpp:218] Iteration 9672 (2.26243 iter/s, 5.30403s/12 iters), loss = 0.566864
I0405 14:42:44.125258  1863 solver.cpp:237]     Train net output #0: loss = 0.566864 (* 1 = 0.566864 loss)
I0405 14:42:44.125264  1863 sgd_solver.cpp:105] Iteration 9672, lr = 0.001
I0405 14:42:49.328683  1863 solver.cpp:218] Iteration 9684 (2.30618 iter/s, 5.20341s/12 iters), loss = 0.540577
I0405 14:42:49.328724  1863 solver.cpp:237]     Train net output #0: loss = 0.540577 (* 1 = 0.540577 loss)
I0405 14:42:49.328729  1863 sgd_solver.cpp:105] Iteration 9684, lr = 0.001
I0405 14:42:51.456212  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel
I0405 14:42:54.928403  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate
I0405 14:42:57.265887  1863 solver.cpp:330] Iteration 9690, Testing net (#0)
I0405 14:42:57.265913  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:42:57.817402  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:00.576645  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:43:01.655172  1863 solver.cpp:397]     Test net output #0: accuracy = 0.234069
I0405 14:43:01.655201  1863 solver.cpp:397]     Test net output #1: loss = 4.41892 (* 1 = 4.41892 loss)
I0405 14:43:03.520547  1863 solver.cpp:218] Iteration 9696 (0.845558 iter/s, 14.1918s/12 iters), loss = 0.55769
I0405 14:43:03.520592  1863 solver.cpp:237]     Train net output #0: loss = 0.55769 (* 1 = 0.55769 loss)
I0405 14:43:03.520599  1863 sgd_solver.cpp:105] Iteration 9696, lr = 0.001
I0405 14:43:08.777819  1863 solver.cpp:218] Iteration 9708 (2.28258 iter/s, 5.2572s/12 iters), loss = 0.709726
I0405 14:43:08.777880  1863 solver.cpp:237]     Train net output #0: loss = 0.709726 (* 1 = 0.709726 loss)
I0405 14:43:08.777889  1863 sgd_solver.cpp:105] Iteration 9708, lr = 0.001
I0405 14:43:09.525998  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:14.141944  1863 solver.cpp:218] Iteration 9720 (2.23711 iter/s, 5.36406s/12 iters), loss = 0.604854
I0405 14:43:14.141984  1863 solver.cpp:237]     Train net output #0: loss = 0.604854 (* 1 = 0.604854 loss)
I0405 14:43:14.141989  1863 sgd_solver.cpp:105] Iteration 9720, lr = 0.001
I0405 14:43:19.441558  1863 solver.cpp:218] Iteration 9732 (2.26434 iter/s, 5.29956s/12 iters), loss = 0.536766
I0405 14:43:19.441612  1863 solver.cpp:237]     Train net output #0: loss = 0.536766 (* 1 = 0.536766 loss)
I0405 14:43:19.441622  1863 sgd_solver.cpp:105] Iteration 9732, lr = 0.001
I0405 14:43:24.752390  1863 solver.cpp:218] Iteration 9744 (2.25956 iter/s, 5.31077s/12 iters), loss = 0.464403
I0405 14:43:24.752429  1863 solver.cpp:237]     Train net output #0: loss = 0.464403 (* 1 = 0.464403 loss)
I0405 14:43:24.752434  1863 sgd_solver.cpp:105] Iteration 9744, lr = 0.001
I0405 14:43:30.196570  1863 solver.cpp:218] Iteration 9756 (2.20421 iter/s, 5.44413s/12 iters), loss = 0.554037
I0405 14:43:30.196611  1863 solver.cpp:237]     Train net output #0: loss = 0.554037 (* 1 = 0.554037 loss)
I0405 14:43:30.196617  1863 sgd_solver.cpp:105] Iteration 9756, lr = 0.001
I0405 14:43:35.714536  1863 solver.cpp:218] Iteration 9768 (2.17474 iter/s, 5.51791s/12 iters), loss = 0.498099
I0405 14:43:35.714663  1863 solver.cpp:237]     Train net output #0: loss = 0.498099 (* 1 = 0.498099 loss)
I0405 14:43:35.714671  1863 sgd_solver.cpp:105] Iteration 9768, lr = 0.001
I0405 14:43:40.823843  1863 solver.cpp:218] Iteration 9780 (2.34872 iter/s, 5.10916s/12 iters), loss = 0.569
I0405 14:43:40.823909  1863 solver.cpp:237]     Train net output #0: loss = 0.569 (* 1 = 0.569 loss)
I0405 14:43:40.823917  1863 sgd_solver.cpp:105] Iteration 9780, lr = 0.001
I0405 14:43:45.706015  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel
I0405 14:43:48.742733  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate
I0405 14:43:51.064604  1863 solver.cpp:330] Iteration 9792, Testing net (#0)
I0405 14:43:51.064622  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:43:51.617489  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:43:55.446553  1863 solver.cpp:397]     Test net output #0: accuracy = 0.234681
I0405 14:43:55.446590  1863 solver.cpp:397]     Test net output #1: loss = 4.4162 (* 1 = 4.4162 loss)
I0405 14:43:55.581156  1863 solver.cpp:218] Iteration 9792 (0.81316 iter/s, 14.7572s/12 iters), loss = 0.386832
I0405 14:43:55.581212  1863 solver.cpp:237]     Train net output #0: loss = 0.386832 (* 1 = 0.386832 loss)
I0405 14:43:55.581219  1863 sgd_solver.cpp:105] Iteration 9792, lr = 0.001
I0405 14:43:59.916998  1863 solver.cpp:218] Iteration 9804 (2.76767 iter/s, 4.33577s/12 iters), loss = 0.437904
I0405 14:43:59.917050  1863 solver.cpp:237]     Train net output #0: loss = 0.437904 (* 1 = 0.437904 loss)
I0405 14:43:59.917062  1863 sgd_solver.cpp:105] Iteration 9804, lr = 0.001
I0405 14:44:03.001374  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:44:05.257441  1863 solver.cpp:218] Iteration 9816 (2.24703 iter/s, 5.34038s/12 iters), loss = 0.449122
I0405 14:44:05.257483  1863 solver.cpp:237]     Train net output #0: loss = 0.449122 (* 1 = 0.449122 loss)
I0405 14:44:05.257488  1863 sgd_solver.cpp:105] Iteration 9816, lr = 0.001
I0405 14:44:10.549544  1863 solver.cpp:218] Iteration 9828 (2.26755 iter/s, 5.29205s/12 iters), loss = 0.938792
I0405 14:44:10.549685  1863 solver.cpp:237]     Train net output #0: loss = 0.938792 (* 1 = 0.938792 loss)
I0405 14:44:10.549693  1863 sgd_solver.cpp:105] Iteration 9828, lr = 0.001
I0405 14:44:15.823047  1863 solver.cpp:218] Iteration 9840 (2.27559 iter/s, 5.27335s/12 iters), loss = 0.377781
I0405 14:44:15.823087  1863 solver.cpp:237]     Train net output #0: loss = 0.377781 (* 1 = 0.377781 loss)
I0405 14:44:15.823093  1863 sgd_solver.cpp:105] Iteration 9840, lr = 0.001
I0405 14:44:21.142014  1863 solver.cpp:218] Iteration 9852 (2.2561 iter/s, 5.31892s/12 iters), loss = 0.616508
I0405 14:44:21.142050  1863 solver.cpp:237]     Train net output #0: loss = 0.616508 (* 1 = 0.616508 loss)
I0405 14:44:21.142055  1863 sgd_solver.cpp:105] Iteration 9852, lr = 0.001
I0405 14:44:26.004612  1863 solver.cpp:218] Iteration 9864 (2.46785 iter/s, 4.86254s/12 iters), loss = 0.709006
I0405 14:44:26.004670  1863 solver.cpp:237]     Train net output #0: loss = 0.709006 (* 1 = 0.709006 loss)
I0405 14:44:26.004679  1863 sgd_solver.cpp:105] Iteration 9864, lr = 0.001
I0405 14:44:31.373026  1863 solver.cpp:218] Iteration 9876 (2.23533 iter/s, 5.36834s/12 iters), loss = 0.596666
I0405 14:44:31.373076  1863 solver.cpp:237]     Train net output #0: loss = 0.596666 (* 1 = 0.596666 loss)
I0405 14:44:31.373085  1863 sgd_solver.cpp:105] Iteration 9876, lr = 0.001
I0405 14:44:36.779279  1863 solver.cpp:218] Iteration 9888 (2.21968 iter/s, 5.40619s/12 iters), loss = 0.41467
I0405 14:44:36.779325  1863 solver.cpp:237]     Train net output #0: loss = 0.41467 (* 1 = 0.41467 loss)
I0405 14:44:36.779331  1863 sgd_solver.cpp:105] Iteration 9888, lr = 0.001
I0405 14:44:38.840909  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel
I0405 14:44:41.895972  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate
I0405 14:44:44.205739  1863 solver.cpp:330] Iteration 9894, Testing net (#0)
I0405 14:44:44.205762  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:44:44.685742  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:44:48.584436  1863 solver.cpp:397]     Test net output #0: accuracy = 0.224265
I0405 14:44:48.584465  1863 solver.cpp:397]     Test net output #1: loss = 4.43347 (* 1 = 4.43347 loss)
I0405 14:44:50.422576  1863 solver.cpp:218] Iteration 9900 (0.879556 iter/s, 13.6432s/12 iters), loss = 0.519742
I0405 14:44:50.422616  1863 solver.cpp:237]     Train net output #0: loss = 0.519742 (* 1 = 0.519742 loss)
I0405 14:44:50.422621  1863 sgd_solver.cpp:105] Iteration 9900, lr = 0.001
I0405 14:44:55.647826  1863 solver.cpp:218] Iteration 9912 (2.29657 iter/s, 5.22519s/12 iters), loss = 0.405258
I0405 14:44:55.647871  1863 solver.cpp:237]     Train net output #0: loss = 0.405258 (* 1 = 0.405258 loss)
I0405 14:44:55.647876  1863 sgd_solver.cpp:105] Iteration 9912, lr = 0.001
I0405 14:44:55.736043  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:01.003047  1863 solver.cpp:218] Iteration 9924 (2.24083 iter/s, 5.35516s/12 iters), loss = 0.481521
I0405 14:45:01.003098  1863 solver.cpp:237]     Train net output #0: loss = 0.481521 (* 1 = 0.481521 loss)
I0405 14:45:01.003106  1863 sgd_solver.cpp:105] Iteration 9924, lr = 0.001
I0405 14:45:06.292541  1863 solver.cpp:218] Iteration 9936 (2.26868 iter/s, 5.28943s/12 iters), loss = 0.283456
I0405 14:45:06.292598  1863 solver.cpp:237]     Train net output #0: loss = 0.283456 (* 1 = 0.283456 loss)
I0405 14:45:06.292606  1863 sgd_solver.cpp:105] Iteration 9936, lr = 0.001
I0405 14:45:11.553879  1863 solver.cpp:218] Iteration 9948 (2.28082 iter/s, 5.26127s/12 iters), loss = 0.545833
I0405 14:45:11.553932  1863 solver.cpp:237]     Train net output #0: loss = 0.545833 (* 1 = 0.545833 loss)
I0405 14:45:11.553941  1863 sgd_solver.cpp:105] Iteration 9948, lr = 0.001
I0405 14:45:16.763257  1863 solver.cpp:218] Iteration 9960 (2.30357 iter/s, 5.20931s/12 iters), loss = 0.498331
I0405 14:45:16.763415  1863 solver.cpp:237]     Train net output #0: loss = 0.498331 (* 1 = 0.498331 loss)
I0405 14:45:16.763425  1863 sgd_solver.cpp:105] Iteration 9960, lr = 0.001
I0405 14:45:21.966250  1863 solver.cpp:218] Iteration 9972 (2.30644 iter/s, 5.20283s/12 iters), loss = 0.346304
I0405 14:45:21.966295  1863 solver.cpp:237]     Train net output #0: loss = 0.346304 (* 1 = 0.346304 loss)
I0405 14:45:21.966300  1863 sgd_solver.cpp:105] Iteration 9972, lr = 0.001
I0405 14:45:27.187855  1863 solver.cpp:218] Iteration 9984 (2.29817 iter/s, 5.22154s/12 iters), loss = 0.585344
I0405 14:45:27.187911  1863 solver.cpp:237]     Train net output #0: loss = 0.585344 (* 1 = 0.585344 loss)
I0405 14:45:27.187920  1863 sgd_solver.cpp:105] Iteration 9984, lr = 0.001
I0405 14:45:31.974073  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel
I0405 14:45:35.020699  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate
I0405 14:45:37.319847  1863 solver.cpp:330] Iteration 9996, Testing net (#0)
I0405 14:45:37.319871  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:45:37.840191  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:41.813519  1863 solver.cpp:397]     Test net output #0: accuracy = 0.231005
I0405 14:45:41.813549  1863 solver.cpp:397]     Test net output #1: loss = 4.45775 (* 1 = 4.45775 loss)
I0405 14:45:41.949802  1863 solver.cpp:218] Iteration 9996 (0.812904 iter/s, 14.7619s/12 iters), loss = 0.472249
I0405 14:45:41.949846  1863 solver.cpp:237]     Train net output #0: loss = 0.472249 (* 1 = 0.472249 loss)
I0405 14:45:41.949852  1863 sgd_solver.cpp:105] Iteration 9996, lr = 0.001
I0405 14:45:46.348215  1863 solver.cpp:218] Iteration 10008 (2.72829 iter/s, 4.39835s/12 iters), loss = 0.336447
I0405 14:45:46.348269  1863 solver.cpp:237]     Train net output #0: loss = 0.336447 (* 1 = 0.336447 loss)
I0405 14:45:46.348278  1863 sgd_solver.cpp:105] Iteration 10008, lr = 0.001
I0405 14:45:48.708446  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:45:51.697232  1863 solver.cpp:218] Iteration 10020 (2.24343 iter/s, 5.34895s/12 iters), loss = 0.357105
I0405 14:45:51.697276  1863 solver.cpp:237]     Train net output #0: loss = 0.357105 (* 1 = 0.357105 loss)
I0405 14:45:51.697281  1863 sgd_solver.cpp:105] Iteration 10020, lr = 0.001
I0405 14:45:56.929425  1863 solver.cpp:218] Iteration 10032 (2.29352 iter/s, 5.23214s/12 iters), loss = 0.307396
I0405 14:45:56.929471  1863 solver.cpp:237]     Train net output #0: loss = 0.307396 (* 1 = 0.307396 loss)
I0405 14:45:56.929476  1863 sgd_solver.cpp:105] Iteration 10032, lr = 0.001
I0405 14:46:02.312053  1863 solver.cpp:218] Iteration 10044 (2.22942 iter/s, 5.38257s/12 iters), loss = 0.62023
I0405 14:46:02.312095  1863 solver.cpp:237]     Train net output #0: loss = 0.62023 (* 1 = 0.62023 loss)
I0405 14:46:02.312100  1863 sgd_solver.cpp:105] Iteration 10044, lr = 0.001
I0405 14:46:07.163539  1863 solver.cpp:218] Iteration 10056 (2.4735 iter/s, 4.85143s/12 iters), loss = 0.530533
I0405 14:46:07.163600  1863 solver.cpp:237]     Train net output #0: loss = 0.530533 (* 1 = 0.530533 loss)
I0405 14:46:07.163609  1863 sgd_solver.cpp:105] Iteration 10056, lr = 0.001
I0405 14:46:12.537817  1863 solver.cpp:218] Iteration 10068 (2.23289 iter/s, 5.37421s/12 iters), loss = 0.488418
I0405 14:46:12.537858  1863 solver.cpp:237]     Train net output #0: loss = 0.488418 (* 1 = 0.488418 loss)
I0405 14:46:12.537863  1863 sgd_solver.cpp:105] Iteration 10068, lr = 0.001
I0405 14:46:18.010923  1863 solver.cpp:218] Iteration 10080 (2.19256 iter/s, 5.47306s/12 iters), loss = 0.422254
I0405 14:46:18.010962  1863 solver.cpp:237]     Train net output #0: loss = 0.422254 (* 1 = 0.422254 loss)
I0405 14:46:18.010967  1863 sgd_solver.cpp:105] Iteration 10080, lr = 0.001
I0405 14:46:23.524199  1863 solver.cpp:218] Iteration 10092 (2.17658 iter/s, 5.51322s/12 iters), loss = 0.46908
I0405 14:46:23.524346  1863 solver.cpp:237]     Train net output #0: loss = 0.46908 (* 1 = 0.46908 loss)
I0405 14:46:23.524353  1863 sgd_solver.cpp:105] Iteration 10092, lr = 0.001
I0405 14:46:25.699157  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel
I0405 14:46:28.652001  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate
I0405 14:46:30.944769  1863 solver.cpp:330] Iteration 10098, Testing net (#0)
I0405 14:46:30.944787  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:46:31.396514  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:46:35.283171  1863 solver.cpp:397]     Test net output #0: accuracy = 0.22549
I0405 14:46:35.283206  1863 solver.cpp:397]     Test net output #1: loss = 4.60816 (* 1 = 4.60816 loss)
I0405 14:46:37.122395  1863 solver.cpp:218] Iteration 10104 (0.882479 iter/s, 13.5981s/12 iters), loss = 0.428985
I0405 14:46:37.122445  1863 solver.cpp:237]     Train net output #0: loss = 0.428985 (* 1 = 0.428985 loss)
I0405 14:46:37.122453  1863 sgd_solver.cpp:105] Iteration 10104, lr = 0.001
I0405 14:46:41.521374  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:46:42.171028  1863 solver.cpp:218] Iteration 10116 (2.37693 iter/s, 5.04853s/12 iters), loss = 0.651451
I0405 14:46:42.171100  1863 solver.cpp:237]     Train net output #0: loss = 0.651451 (* 1 = 0.651451 loss)
I0405 14:46:42.171113  1863 sgd_solver.cpp:105] Iteration 10116, lr = 0.001
I0405 14:46:47.416275  1863 solver.cpp:218] Iteration 10128 (2.28782 iter/s, 5.24517s/12 iters), loss = 0.297294
I0405 14:46:47.416338  1863 solver.cpp:237]     Train net output #0: loss = 0.297294 (* 1 = 0.297294 loss)
I0405 14:46:47.416347  1863 sgd_solver.cpp:105] Iteration 10128, lr = 0.001
I0405 14:46:52.494035  1863 solver.cpp:218] Iteration 10140 (2.36328 iter/s, 5.07769s/12 iters), loss = 0.593577
I0405 14:46:52.494076  1863 solver.cpp:237]     Train net output #0: loss = 0.593577 (* 1 = 0.593577 loss)
I0405 14:46:52.494082  1863 sgd_solver.cpp:105] Iteration 10140, lr = 0.001
I0405 14:46:57.579933  1863 solver.cpp:218] Iteration 10152 (2.35949 iter/s, 5.08584s/12 iters), loss = 0.384843
I0405 14:46:57.580037  1863 solver.cpp:237]     Train net output #0: loss = 0.384843 (* 1 = 0.384843 loss)
I0405 14:46:57.580044  1863 sgd_solver.cpp:105] Iteration 10152, lr = 0.001
I0405 14:47:03.042311  1863 solver.cpp:218] Iteration 10164 (2.19689 iter/s, 5.46227s/12 iters), loss = 0.385795
I0405 14:47:03.042356  1863 solver.cpp:237]     Train net output #0: loss = 0.385795 (* 1 = 0.385795 loss)
I0405 14:47:03.042361  1863 sgd_solver.cpp:105] Iteration 10164, lr = 0.001
I0405 14:47:08.285689  1863 solver.cpp:218] Iteration 10176 (2.28863 iter/s, 5.24332s/12 iters), loss = 0.430387
I0405 14:47:08.285743  1863 solver.cpp:237]     Train net output #0: loss = 0.430387 (* 1 = 0.430387 loss)
I0405 14:47:08.285751  1863 sgd_solver.cpp:105] Iteration 10176, lr = 0.001
I0405 14:47:13.522367  1863 solver.cpp:218] Iteration 10188 (2.29156 iter/s, 5.23661s/12 iters), loss = 0.428733
I0405 14:47:13.522415  1863 solver.cpp:237]     Train net output #0: loss = 0.428733 (* 1 = 0.428733 loss)
I0405 14:47:13.522423  1863 sgd_solver.cpp:105] Iteration 10188, lr = 0.001
I0405 14:47:18.147830  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel
I0405 14:47:21.192756  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate
I0405 14:47:24.647965  1863 solver.cpp:330] Iteration 10200, Testing net (#0)
I0405 14:47:24.647989  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:47:25.004026  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:47:29.030126  1863 solver.cpp:397]     Test net output #0: accuracy = 0.234069
I0405 14:47:29.030272  1863 solver.cpp:397]     Test net output #1: loss = 4.55185 (* 1 = 4.55185 loss)
I0405 14:47:29.167104  1863 solver.cpp:218] Iteration 10200 (0.767033 iter/s, 15.6447s/12 iters), loss = 0.320782
I0405 14:47:29.167153  1863 solver.cpp:237]     Train net output #0: loss = 0.320782 (* 1 = 0.320782 loss)
I0405 14:47:29.167160  1863 sgd_solver.cpp:105] Iteration 10200, lr = 0.001
I0405 14:47:33.607658  1863 solver.cpp:218] Iteration 10212 (2.7024 iter/s, 4.44049s/12 iters), loss = 0.342128
I0405 14:47:33.607699  1863 solver.cpp:237]     Train net output #0: loss = 0.342128 (* 1 = 0.342128 loss)
I0405 14:47:33.607705  1863 sgd_solver.cpp:105] Iteration 10212, lr = 0.001
I0405 14:47:35.040854  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:47:38.637015  1863 solver.cpp:218] Iteration 10224 (2.38602 iter/s, 5.0293s/12 iters), loss = 0.269988
I0405 14:47:38.637073  1863 solver.cpp:237]     Train net output #0: loss = 0.269988 (* 1 = 0.269988 loss)
I0405 14:47:38.637079  1863 sgd_solver.cpp:105] Iteration 10224, lr = 0.001
I0405 14:47:44.098356  1863 solver.cpp:218] Iteration 10236 (2.19729 iter/s, 5.46127s/12 iters), loss = 0.268816
I0405 14:47:44.098402  1863 solver.cpp:237]     Train net output #0: loss = 0.268816 (* 1 = 0.268816 loss)
I0405 14:47:44.098408  1863 sgd_solver.cpp:105] Iteration 10236, lr = 0.001
I0405 14:47:49.234073  1863 solver.cpp:218] Iteration 10248 (2.3366 iter/s, 5.13566s/12 iters), loss = 0.341158
I0405 14:47:49.234112  1863 solver.cpp:237]     Train net output #0: loss = 0.341158 (* 1 = 0.341158 loss)
I0405 14:47:49.234117  1863 sgd_solver.cpp:105] Iteration 10248, lr = 0.001
I0405 14:47:54.535418  1863 solver.cpp:218] Iteration 10260 (2.2636 iter/s, 5.3013s/12 iters), loss = 0.281574
I0405 14:47:54.535459  1863 solver.cpp:237]     Train net output #0: loss = 0.281574 (* 1 = 0.281574 loss)
I0405 14:47:54.535463  1863 sgd_solver.cpp:105] Iteration 10260, lr = 0.001
I0405 14:47:59.719061  1863 solver.cpp:218] Iteration 10272 (2.315 iter/s, 5.18359s/12 iters), loss = 0.318595
I0405 14:47:59.719173  1863 solver.cpp:237]     Train net output #0: loss = 0.318595 (* 1 = 0.318595 loss)
I0405 14:47:59.719180  1863 sgd_solver.cpp:105] Iteration 10272, lr = 0.001
I0405 14:48:05.167320  1863 solver.cpp:218] Iteration 10284 (2.20259 iter/s, 5.44814s/12 iters), loss = 0.544466
I0405 14:48:05.167371  1863 solver.cpp:237]     Train net output #0: loss = 0.544466 (* 1 = 0.544466 loss)
I0405 14:48:05.167379  1863 sgd_solver.cpp:105] Iteration 10284, lr = 0.001
I0405 14:48:10.312206  1863 solver.cpp:218] Iteration 10296 (2.33244 iter/s, 5.14483s/12 iters), loss = 0.486857
I0405 14:48:10.312249  1863 solver.cpp:237]     Train net output #0: loss = 0.486857 (* 1 = 0.486857 loss)
I0405 14:48:10.312254  1863 sgd_solver.cpp:105] Iteration 10296, lr = 0.001
I0405 14:48:12.453177  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10302.caffemodel
I0405 14:48:15.492530  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10302.solverstate
I0405 14:48:17.850670  1863 solver.cpp:330] Iteration 10302, Testing net (#0)
I0405 14:48:17.850693  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:48:18.171481  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:48:22.407618  1863 solver.cpp:397]     Test net output #0: accuracy = 0.228554
I0405 14:48:22.407650  1863 solver.cpp:397]     Test net output #1: loss = 4.53172 (* 1 = 4.53172 loss)
I0405 14:48:24.383572  1863 solver.cpp:218] Iteration 10308 (0.852798 iter/s, 14.0713s/12 iters), loss = 0.2384
I0405 14:48:24.383615  1863 solver.cpp:237]     Train net output #0: loss = 0.2384 (* 1 = 0.2384 loss)
I0405 14:48:24.383621  1863 sgd_solver.cpp:105] Iteration 10308, lr = 0.001
I0405 14:48:27.979941  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:48:29.454668  1863 solver.cpp:218] Iteration 10320 (2.36638 iter/s, 5.07103s/12 iters), loss = 0.331243
I0405 14:48:29.454730  1863 solver.cpp:237]     Train net output #0: loss = 0.331243 (* 1 = 0.331243 loss)
I0405 14:48:29.454738  1863 sgd_solver.cpp:105] Iteration 10320, lr = 0.001
I0405 14:48:34.806305  1863 solver.cpp:218] Iteration 10332 (2.24234 iter/s, 5.35156s/12 iters), loss = 0.42747
I0405 14:48:34.806512  1863 solver.cpp:237]     Train net output #0: loss = 0.42747 (* 1 = 0.42747 loss)
I0405 14:48:34.806524  1863 sgd_solver.cpp:105] Iteration 10332, lr = 0.001
I0405 14:48:40.141002  1863 solver.cpp:218] Iteration 10344 (2.24951 iter/s, 5.33449s/12 iters), loss = 0.283489
I0405 14:48:40.141057  1863 solver.cpp:237]     Train net output #0: loss = 0.283489 (* 1 = 0.283489 loss)
I0405 14:48:40.141072  1863 sgd_solver.cpp:105] Iteration 10344, lr = 0.001
I0405 14:48:45.405591  1863 solver.cpp:218] Iteration 10356 (2.27941 iter/s, 5.26452s/12 iters), loss = 0.375717
I0405 14:48:45.405637  1863 solver.cpp:237]     Train net output #0: loss = 0.375717 (* 1 = 0.375717 loss)
I0405 14:48:45.405644  1863 sgd_solver.cpp:105] Iteration 10356, lr = 0.001
I0405 14:48:50.733780  1863 solver.cpp:218] Iteration 10368 (2.25219 iter/s, 5.32814s/12 iters), loss = 0.404474
I0405 14:48:50.733817  1863 solver.cpp:237]     Train net output #0: loss = 0.404474 (* 1 = 0.404474 loss)
I0405 14:48:50.733824  1863 sgd_solver.cpp:105] Iteration 10368, lr = 0.001
I0405 14:48:56.059701  1863 solver.cpp:218] Iteration 10380 (2.25316 iter/s, 5.32586s/12 iters), loss = 0.38009
I0405 14:48:56.059756  1863 solver.cpp:237]     Train net output #0: loss = 0.38009 (* 1 = 0.38009 loss)
I0405 14:48:56.059765  1863 sgd_solver.cpp:105] Iteration 10380, lr = 0.001
I0405 14:49:01.407758  1863 solver.cpp:218] Iteration 10392 (2.24383 iter/s, 5.34799s/12 iters), loss = 0.453677
I0405 14:49:01.407800  1863 solver.cpp:237]     Train net output #0: loss = 0.453677 (* 1 = 0.453677 loss)
I0405 14:49:01.407807  1863 sgd_solver.cpp:105] Iteration 10392, lr = 0.001
I0405 14:49:06.427196  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10404.caffemodel
I0405 14:49:09.452778  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10404.solverstate
I0405 14:49:11.745894  1863 solver.cpp:330] Iteration 10404, Testing net (#0)
I0405 14:49:11.745915  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:49:12.025344  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:49:12.507454  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:49:16.091719  1863 solver.cpp:397]     Test net output #0: accuracy = 0.230392
I0405 14:49:16.091758  1863 solver.cpp:397]     Test net output #1: loss = 4.55458 (* 1 = 4.55458 loss)
I0405 14:49:16.227552  1863 solver.cpp:218] Iteration 10404 (0.80973 iter/s, 14.8198s/12 iters), loss = 0.422352
I0405 14:49:16.227596  1863 solver.cpp:237]     Train net output #0: loss = 0.422352 (* 1 = 0.422352 loss)
I0405 14:49:16.227602  1863 sgd_solver.cpp:105] Iteration 10404, lr = 0.001
I0405 14:49:20.572365  1863 solver.cpp:218] Iteration 10416 (2.76195 iter/s, 4.34475s/12 iters), loss = 0.409523
I0405 14:49:20.572409  1863 solver.cpp:237]     Train net output #0: loss = 0.409523 (* 1 = 0.409523 loss)
I0405 14:49:20.572417  1863 sgd_solver.cpp:105] Iteration 10416, lr = 0.001
I0405 14:49:21.528157  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:49:25.762634  1863 solver.cpp:218] Iteration 10428 (2.31204 iter/s, 5.19021s/12 iters), loss = 0.424467
I0405 14:49:25.762677  1863 solver.cpp:237]     Train net output #0: loss = 0.424467 (* 1 = 0.424467 loss)
I0405 14:49:25.762683  1863 sgd_solver.cpp:105] Iteration 10428, lr = 0.001
I0405 14:49:31.060801  1863 solver.cpp:218] Iteration 10440 (2.26496 iter/s, 5.29811s/12 iters), loss = 0.415287
I0405 14:49:31.060858  1863 solver.cpp:237]     Train net output #0: loss = 0.415287 (* 1 = 0.415287 loss)
I0405 14:49:31.060869  1863 sgd_solver.cpp:105] Iteration 10440, lr = 0.001
I0405 14:49:36.412930  1863 solver.cpp:218] Iteration 10452 (2.24213 iter/s, 5.35206s/12 iters), loss = 0.445425
I0405 14:49:36.412984  1863 solver.cpp:237]     Train net output #0: loss = 0.445425 (* 1 = 0.445425 loss)
I0405 14:49:36.412994  1863 sgd_solver.cpp:105] Iteration 10452, lr = 0.001
I0405 14:49:41.694586  1863 solver.cpp:218] Iteration 10464 (2.27204 iter/s, 5.28159s/12 iters), loss = 0.197844
I0405 14:49:41.694741  1863 solver.cpp:237]     Train net output #0: loss = 0.197844 (* 1 = 0.197844 loss)
I0405 14:49:41.694749  1863 sgd_solver.cpp:105] Iteration 10464, lr = 0.001
I0405 14:49:47.056035  1863 solver.cpp:218] Iteration 10476 (2.23827 iter/s, 5.36129s/12 iters), loss = 0.304899
I0405 14:49:47.056094  1863 solver.cpp:237]     Train net output #0: loss = 0.304899 (* 1 = 0.304899 loss)
I0405 14:49:47.056104  1863 sgd_solver.cpp:105] Iteration 10476, lr = 0.001
I0405 14:49:52.466883  1863 solver.cpp:218] Iteration 10488 (2.2178 iter/s, 5.41078s/12 iters), loss = 0.326626
I0405 14:49:52.466931  1863 solver.cpp:237]     Train net output #0: loss = 0.326626 (* 1 = 0.326626 loss)
I0405 14:49:52.466938  1863 sgd_solver.cpp:105] Iteration 10488, lr = 0.001
I0405 14:49:57.672721  1863 solver.cpp:218] Iteration 10500 (2.30513 iter/s, 5.20578s/12 iters), loss = 0.529994
I0405 14:49:57.672777  1863 solver.cpp:237]     Train net output #0: loss = 0.529994 (* 1 = 0.529994 loss)
I0405 14:49:57.672786  1863 sgd_solver.cpp:105] Iteration 10500, lr = 0.001
I0405 14:49:59.816598  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10506.caffemodel
I0405 14:50:02.896369  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10506.solverstate
I0405 14:50:05.199057  1863 solver.cpp:330] Iteration 10506, Testing net (#0)
I0405 14:50:05.199079  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:50:05.443027  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:50:09.595316  1863 solver.cpp:397]     Test net output #0: accuracy = 0.242034
I0405 14:50:09.595347  1863 solver.cpp:397]     Test net output #1: loss = 4.50513 (* 1 = 4.50513 loss)
I0405 14:50:11.488823  1863 solver.cpp:218] Iteration 10512 (0.868555 iter/s, 13.816s/12 iters), loss = 0.265798
I0405 14:50:11.488867  1863 solver.cpp:237]     Train net output #0: loss = 0.265798 (* 1 = 0.265798 loss)
I0405 14:50:11.488873  1863 sgd_solver.cpp:105] Iteration 10512, lr = 0.001
I0405 14:50:14.488029  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:50:16.551705  1863 solver.cpp:218] Iteration 10524 (2.37022 iter/s, 5.06282s/12 iters), loss = 0.235955
I0405 14:50:16.551759  1863 solver.cpp:237]     Train net output #0: loss = 0.235955 (* 1 = 0.235955 loss)
I0405 14:50:16.551769  1863 sgd_solver.cpp:105] Iteration 10524, lr = 0.001
I0405 14:50:21.955047  1863 solver.cpp:218] Iteration 10536 (2.22087 iter/s, 5.40328s/12 iters), loss = 0.390103
I0405 14:50:21.955094  1863 solver.cpp:237]     Train net output #0: loss = 0.390103 (* 1 = 0.390103 loss)
I0405 14:50:21.955103  1863 sgd_solver.cpp:105] Iteration 10536, lr = 0.001
I0405 14:50:27.148553  1863 solver.cpp:218] Iteration 10548 (2.3106 iter/s, 5.19345s/12 iters), loss = 0.342553
I0405 14:50:27.148593  1863 solver.cpp:237]     Train net output #0: loss = 0.342553 (* 1 = 0.342553 loss)
I0405 14:50:27.148598  1863 sgd_solver.cpp:105] Iteration 10548, lr = 0.001
I0405 14:50:32.324052  1863 solver.cpp:218] Iteration 10560 (2.31864 iter/s, 5.17545s/12 iters), loss = 0.199318
I0405 14:50:32.324090  1863 solver.cpp:237]     Train net output #0: loss = 0.199318 (* 1 = 0.199318 loss)
I0405 14:50:32.324095  1863 sgd_solver.cpp:105] Iteration 10560, lr = 0.001
I0405 14:50:37.780959  1863 solver.cpp:218] Iteration 10572 (2.19907 iter/s, 5.45686s/12 iters), loss = 0.417835
I0405 14:50:37.781008  1863 solver.cpp:237]     Train net output #0: loss = 0.417835 (* 1 = 0.417835 loss)
I0405 14:50:37.781014  1863 sgd_solver.cpp:105] Iteration 10572, lr = 0.001
I0405 14:50:43.090571  1863 solver.cpp:218] Iteration 10584 (2.26008 iter/s, 5.30955s/12 iters), loss = 0.320571
I0405 14:50:43.090612  1863 solver.cpp:237]     Train net output #0: loss = 0.320571 (* 1 = 0.320571 loss)
I0405 14:50:43.090618  1863 sgd_solver.cpp:105] Iteration 10584, lr = 0.001
I0405 14:50:48.394800  1863 solver.cpp:218] Iteration 10596 (2.26237 iter/s, 5.30417s/12 iters), loss = 0.343923
I0405 14:50:48.394956  1863 solver.cpp:237]     Train net output #0: loss = 0.343923 (* 1 = 0.343923 loss)
I0405 14:50:48.394966  1863 sgd_solver.cpp:105] Iteration 10596, lr = 0.001
I0405 14:50:53.038043  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10608.caffemodel
I0405 14:50:56.058812  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10608.solverstate
I0405 14:50:58.381021  1863 solver.cpp:330] Iteration 10608, Testing net (#0)
I0405 14:50:58.381042  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:50:58.608157  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:02.756592  1863 solver.cpp:397]     Test net output #0: accuracy = 0.240809
I0405 14:51:02.756629  1863 solver.cpp:397]     Test net output #1: loss = 4.56397 (* 1 = 4.56397 loss)
I0405 14:51:02.897217  1863 solver.cpp:218] Iteration 10608 (0.827457 iter/s, 14.5023s/12 iters), loss = 0.316181
I0405 14:51:02.897264  1863 solver.cpp:237]     Train net output #0: loss = 0.316181 (* 1 = 0.316181 loss)
I0405 14:51:02.897270  1863 sgd_solver.cpp:105] Iteration 10608, lr = 0.001
I0405 14:51:07.100562  1863 solver.cpp:218] Iteration 10620 (2.85491 iter/s, 4.20328s/12 iters), loss = 0.444582
I0405 14:51:07.100611  1863 solver.cpp:237]     Train net output #0: loss = 0.444582 (* 1 = 0.444582 loss)
I0405 14:51:07.100620  1863 sgd_solver.cpp:105] Iteration 10620, lr = 0.001
I0405 14:51:07.218740  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:12.510346  1863 solver.cpp:218] Iteration 10632 (2.21823 iter/s, 5.40972s/12 iters), loss = 0.386777
I0405 14:51:12.510396  1863 solver.cpp:237]     Train net output #0: loss = 0.386777 (* 1 = 0.386777 loss)
I0405 14:51:12.510403  1863 sgd_solver.cpp:105] Iteration 10632, lr = 0.001
I0405 14:51:17.899624  1863 solver.cpp:218] Iteration 10644 (2.22667 iter/s, 5.38922s/12 iters), loss = 0.527828
I0405 14:51:17.899675  1863 solver.cpp:237]     Train net output #0: loss = 0.527828 (* 1 = 0.527828 loss)
I0405 14:51:17.899682  1863 sgd_solver.cpp:105] Iteration 10644, lr = 0.001
I0405 14:51:23.132118  1863 solver.cpp:218] Iteration 10656 (2.29339 iter/s, 5.23243s/12 iters), loss = 0.313351
I0405 14:51:23.132246  1863 solver.cpp:237]     Train net output #0: loss = 0.313351 (* 1 = 0.313351 loss)
I0405 14:51:23.132254  1863 sgd_solver.cpp:105] Iteration 10656, lr = 0.001
I0405 14:51:28.386706  1863 solver.cpp:218] Iteration 10668 (2.28378 iter/s, 5.25445s/12 iters), loss = 0.284799
I0405 14:51:28.386767  1863 solver.cpp:237]     Train net output #0: loss = 0.284799 (* 1 = 0.284799 loss)
I0405 14:51:28.386776  1863 sgd_solver.cpp:105] Iteration 10668, lr = 0.001
I0405 14:51:33.720984  1863 solver.cpp:218] Iteration 10680 (2.24963 iter/s, 5.3342s/12 iters), loss = 0.355811
I0405 14:51:33.721041  1863 solver.cpp:237]     Train net output #0: loss = 0.355811 (* 1 = 0.355811 loss)
I0405 14:51:33.721050  1863 sgd_solver.cpp:105] Iteration 10680, lr = 0.001
I0405 14:51:39.000133  1863 solver.cpp:218] Iteration 10692 (2.27312 iter/s, 5.27908s/12 iters), loss = 0.251122
I0405 14:51:39.000174  1863 solver.cpp:237]     Train net output #0: loss = 0.251122 (* 1 = 0.251122 loss)
I0405 14:51:39.000180  1863 sgd_solver.cpp:105] Iteration 10692, lr = 0.001
I0405 14:51:44.462726  1863 solver.cpp:218] Iteration 10704 (2.19678 iter/s, 5.46254s/12 iters), loss = 0.31102
I0405 14:51:44.462774  1863 solver.cpp:237]     Train net output #0: loss = 0.31102 (* 1 = 0.31102 loss)
I0405 14:51:44.462779  1863 sgd_solver.cpp:105] Iteration 10704, lr = 0.001
I0405 14:51:46.573138  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10710.caffemodel
I0405 14:51:49.582180  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10710.solverstate
I0405 14:51:51.891036  1863 solver.cpp:330] Iteration 10710, Testing net (#0)
I0405 14:51:51.891058  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:51:52.083880  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:51:56.271674  1863 solver.cpp:397]     Test net output #0: accuracy = 0.235907
I0405 14:51:56.271818  1863 solver.cpp:397]     Test net output #1: loss = 4.5585 (* 1 = 4.5585 loss)
I0405 14:51:58.138324  1863 solver.cpp:218] Iteration 10716 (0.877479 iter/s, 13.6755s/12 iters), loss = 0.385073
I0405 14:51:58.138365  1863 solver.cpp:237]     Train net output #0: loss = 0.385073 (* 1 = 0.385073 loss)
I0405 14:51:58.138372  1863 sgd_solver.cpp:105] Iteration 10716, lr = 0.001
I0405 14:52:00.469187  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:52:03.300289  1863 solver.cpp:218] Iteration 10728 (2.32472 iter/s, 5.16191s/12 iters), loss = 0.495669
I0405 14:52:03.300330  1863 solver.cpp:237]     Train net output #0: loss = 0.495669 (* 1 = 0.495669 loss)
I0405 14:52:03.300336  1863 sgd_solver.cpp:105] Iteration 10728, lr = 0.001
I0405 14:52:08.602069  1863 solver.cpp:218] Iteration 10740 (2.26341 iter/s, 5.30173s/12 iters), loss = 0.292138
I0405 14:52:08.602111  1863 solver.cpp:237]     Train net output #0: loss = 0.292138 (* 1 = 0.292138 loss)
I0405 14:52:08.602116  1863 sgd_solver.cpp:105] Iteration 10740, lr = 0.001
I0405 14:52:13.946420  1863 solver.cpp:218] Iteration 10752 (2.24538 iter/s, 5.3443s/12 iters), loss = 0.400446
I0405 14:52:13.946478  1863 solver.cpp:237]     Train net output #0: loss = 0.400446 (* 1 = 0.400446 loss)
I0405 14:52:13.946488  1863 sgd_solver.cpp:105] Iteration 10752, lr = 0.001
I0405 14:52:19.410799  1863 solver.cpp:218] Iteration 10764 (2.19607 iter/s, 5.46431s/12 iters), loss = 0.531665
I0405 14:52:19.410851  1863 solver.cpp:237]     Train net output #0: loss = 0.531665 (* 1 = 0.531665 loss)
I0405 14:52:19.410858  1863 sgd_solver.cpp:105] Iteration 10764, lr = 0.001
I0405 14:52:24.686810  1863 solver.cpp:218] Iteration 10776 (2.27447 iter/s, 5.27595s/12 iters), loss = 0.548414
I0405 14:52:24.686848  1863 solver.cpp:237]     Train net output #0: loss = 0.548414 (* 1 = 0.548414 loss)
I0405 14:52:24.686854  1863 sgd_solver.cpp:105] Iteration 10776, lr = 0.001
I0405 14:52:29.910126  1863 solver.cpp:218] Iteration 10788 (2.29741 iter/s, 5.22326s/12 iters), loss = 0.369992
I0405 14:52:29.910244  1863 solver.cpp:237]     Train net output #0: loss = 0.369992 (* 1 = 0.369992 loss)
I0405 14:52:29.910251  1863 sgd_solver.cpp:105] Iteration 10788, lr = 0.001
I0405 14:52:35.372901  1863 solver.cpp:218] Iteration 10800 (2.19674 iter/s, 5.46264s/12 iters), loss = 0.363302
I0405 14:52:35.372962  1863 solver.cpp:237]     Train net output #0: loss = 0.363302 (* 1 = 0.363302 loss)
I0405 14:52:35.372972  1863 sgd_solver.cpp:105] Iteration 10800, lr = 0.001
I0405 14:52:40.185497  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10812.caffemodel
I0405 14:52:43.278313  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10812.solverstate
I0405 14:52:45.623029  1863 solver.cpp:330] Iteration 10812, Testing net (#0)
I0405 14:52:45.623054  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:52:45.792593  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:52:49.998980  1863 solver.cpp:397]     Test net output #0: accuracy = 0.234069
I0405 14:52:49.999014  1863 solver.cpp:397]     Test net output #1: loss = 4.61651 (* 1 = 4.61651 loss)
I0405 14:52:50.137609  1863 solver.cpp:218] Iteration 10812 (0.812752 iter/s, 14.7646s/12 iters), loss = 0.478078
I0405 14:52:50.137696  1863 solver.cpp:237]     Train net output #0: loss = 0.478078 (* 1 = 0.478078 loss)
I0405 14:52:50.137704  1863 sgd_solver.cpp:105] Iteration 10812, lr = 0.001
I0405 14:52:53.843448  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:52:54.445466  1863 solver.cpp:218] Iteration 10824 (2.78568 iter/s, 4.30775s/12 iters), loss = 0.289961
I0405 14:52:54.445523  1863 solver.cpp:237]     Train net output #0: loss = 0.289961 (* 1 = 0.289961 loss)
I0405 14:52:54.445530  1863 sgd_solver.cpp:105] Iteration 10824, lr = 0.001
I0405 14:52:59.628681  1863 solver.cpp:218] Iteration 10836 (2.3152 iter/s, 5.18315s/12 iters), loss = 0.513705
I0405 14:52:59.628727  1863 solver.cpp:237]     Train net output #0: loss = 0.513705 (* 1 = 0.513705 loss)
I0405 14:52:59.628732  1863 sgd_solver.cpp:105] Iteration 10836, lr = 0.001
I0405 14:53:04.742465  1863 solver.cpp:218] Iteration 10848 (2.34663 iter/s, 5.11373s/12 iters), loss = 0.289852
I0405 14:53:04.742597  1863 solver.cpp:237]     Train net output #0: loss = 0.289852 (* 1 = 0.289852 loss)
I0405 14:53:04.742604  1863 sgd_solver.cpp:105] Iteration 10848, lr = 0.001
I0405 14:53:10.073388  1863 solver.cpp:218] Iteration 10860 (2.25108 iter/s, 5.33078s/12 iters), loss = 0.444465
I0405 14:53:10.073431  1863 solver.cpp:237]     Train net output #0: loss = 0.444465 (* 1 = 0.444465 loss)
I0405 14:53:10.073437  1863 sgd_solver.cpp:105] Iteration 10860, lr = 0.001
I0405 14:53:15.164460  1863 solver.cpp:218] Iteration 10872 (2.35709 iter/s, 5.09102s/12 iters), loss = 0.26835
I0405 14:53:15.164501  1863 solver.cpp:237]     Train net output #0: loss = 0.26835 (* 1 = 0.26835 loss)
I0405 14:53:15.164507  1863 sgd_solver.cpp:105] Iteration 10872, lr = 0.001
I0405 14:53:20.156682  1863 solver.cpp:218] Iteration 10884 (2.40377 iter/s, 4.99216s/12 iters), loss = 0.339449
I0405 14:53:20.156740  1863 solver.cpp:237]     Train net output #0: loss = 0.339449 (* 1 = 0.339449 loss)
I0405 14:53:20.156749  1863 sgd_solver.cpp:105] Iteration 10884, lr = 0.001
I0405 14:53:25.203213  1863 solver.cpp:218] Iteration 10896 (2.3779 iter/s, 5.04646s/12 iters), loss = 0.4214
I0405 14:53:25.203253  1863 solver.cpp:237]     Train net output #0: loss = 0.4214 (* 1 = 0.4214 loss)
I0405 14:53:25.203258  1863 sgd_solver.cpp:105] Iteration 10896, lr = 0.001
I0405 14:53:30.308764  1863 solver.cpp:218] Iteration 10908 (2.3504 iter/s, 5.1055s/12 iters), loss = 0.28947
I0405 14:53:30.308805  1863 solver.cpp:237]     Train net output #0: loss = 0.28947 (* 1 = 0.28947 loss)
I0405 14:53:30.308811  1863 sgd_solver.cpp:105] Iteration 10908, lr = 0.001
I0405 14:53:32.217264  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10914.caffemodel
I0405 14:53:35.255677  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10914.solverstate
I0405 14:53:37.556732  1863 solver.cpp:330] Iteration 10914, Testing net (#0)
I0405 14:53:37.556756  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:53:37.637208  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:53:41.895071  1863 solver.cpp:397]     Test net output #0: accuracy = 0.239583
I0405 14:53:41.895105  1863 solver.cpp:397]     Test net output #1: loss = 4.57512 (* 1 = 4.57512 loss)
I0405 14:53:43.805341  1863 solver.cpp:218] Iteration 10920 (0.889118 iter/s, 13.4965s/12 iters), loss = 0.513863
I0405 14:53:43.805398  1863 solver.cpp:237]     Train net output #0: loss = 0.513863 (* 1 = 0.513863 loss)
I0405 14:53:43.805408  1863 sgd_solver.cpp:105] Iteration 10920, lr = 0.001
I0405 14:53:45.402411  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:53:49.101759  1863 solver.cpp:218] Iteration 10932 (2.26571 iter/s, 5.29635s/12 iters), loss = 0.570353
I0405 14:53:49.101804  1863 solver.cpp:237]     Train net output #0: loss = 0.570353 (* 1 = 0.570353 loss)
I0405 14:53:49.101809  1863 sgd_solver.cpp:105] Iteration 10932, lr = 0.001
I0405 14:53:54.287066  1863 solver.cpp:218] Iteration 10944 (2.31426 iter/s, 5.18524s/12 iters), loss = 0.344768
I0405 14:53:54.287133  1863 solver.cpp:237]     Train net output #0: loss = 0.344768 (* 1 = 0.344768 loss)
I0405 14:53:54.287142  1863 sgd_solver.cpp:105] Iteration 10944, lr = 0.001
I0405 14:53:59.605978  1863 solver.cpp:218] Iteration 10956 (2.25613 iter/s, 5.31883s/12 iters), loss = 0.444178
I0405 14:53:59.606026  1863 solver.cpp:237]     Train net output #0: loss = 0.444178 (* 1 = 0.444178 loss)
I0405 14:53:59.606035  1863 sgd_solver.cpp:105] Iteration 10956, lr = 0.001
I0405 14:54:04.653928  1863 solver.cpp:218] Iteration 10968 (2.37723 iter/s, 5.04789s/12 iters), loss = 0.390269
I0405 14:54:04.653970  1863 solver.cpp:237]     Train net output #0: loss = 0.390269 (* 1 = 0.390269 loss)
I0405 14:54:04.653975  1863 sgd_solver.cpp:105] Iteration 10968, lr = 0.001
I0405 14:54:10.093760  1863 solver.cpp:218] Iteration 10980 (2.20597 iter/s, 5.43978s/12 iters), loss = 0.372567
I0405 14:54:10.093889  1863 solver.cpp:237]     Train net output #0: loss = 0.372567 (* 1 = 0.372567 loss)
I0405 14:54:10.093896  1863 sgd_solver.cpp:105] Iteration 10980, lr = 0.001
I0405 14:54:15.229979  1863 solver.cpp:218] Iteration 10992 (2.33641 iter/s, 5.13607s/12 iters), loss = 0.21464
I0405 14:54:15.230032  1863 solver.cpp:237]     Train net output #0: loss = 0.21464 (* 1 = 0.21464 loss)
I0405 14:54:15.230041  1863 sgd_solver.cpp:105] Iteration 10992, lr = 0.001
I0405 14:54:20.540582  1863 solver.cpp:218] Iteration 11004 (2.25966 iter/s, 5.31054s/12 iters), loss = 0.279321
I0405 14:54:20.540628  1863 solver.cpp:237]     Train net output #0: loss = 0.279321 (* 1 = 0.279321 loss)
I0405 14:54:20.540637  1863 sgd_solver.cpp:105] Iteration 11004, lr = 0.001
I0405 14:54:24.993925  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11016.caffemodel
I0405 14:54:28.105720  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11016.solverstate
I0405 14:54:30.403190  1863 solver.cpp:330] Iteration 11016, Testing net (#0)
I0405 14:54:30.403211  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:54:30.453758  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:54:34.976334  1863 solver.cpp:397]     Test net output #0: accuracy = 0.243873
I0405 14:54:34.976370  1863 solver.cpp:397]     Test net output #1: loss = 4.66698 (* 1 = 4.66698 loss)
I0405 14:54:35.117583  1863 solver.cpp:218] Iteration 11016 (0.823217 iter/s, 14.577s/12 iters), loss = 0.257589
I0405 14:54:35.117624  1863 solver.cpp:237]     Train net output #0: loss = 0.257589 (* 1 = 0.257589 loss)
I0405 14:54:35.117630  1863 sgd_solver.cpp:105] Iteration 11016, lr = 0.001
I0405 14:54:35.685312  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:54:38.072295  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:54:39.370085  1863 solver.cpp:218] Iteration 11028 (2.82191 iter/s, 4.25244s/12 iters), loss = 0.247413
I0405 14:54:39.370138  1863 solver.cpp:237]     Train net output #0: loss = 0.247413 (* 1 = 0.247413 loss)
I0405 14:54:39.370146  1863 sgd_solver.cpp:105] Iteration 11028, lr = 0.001
I0405 14:54:44.643509  1863 solver.cpp:218] Iteration 11040 (2.27559 iter/s, 5.27336s/12 iters), loss = 0.266941
I0405 14:54:44.643596  1863 solver.cpp:237]     Train net output #0: loss = 0.266941 (* 1 = 0.266941 loss)
I0405 14:54:44.643604  1863 sgd_solver.cpp:105] Iteration 11040, lr = 0.001
I0405 14:54:49.962221  1863 solver.cpp:218] Iteration 11052 (2.25623 iter/s, 5.31862s/12 iters), loss = 0.295154
I0405 14:54:49.962263  1863 solver.cpp:237]     Train net output #0: loss = 0.295154 (* 1 = 0.295154 loss)
I0405 14:54:49.962270  1863 sgd_solver.cpp:105] Iteration 11052, lr = 0.001
I0405 14:54:55.302907  1863 solver.cpp:218] Iteration 11064 (2.24693 iter/s, 5.34063s/12 iters), loss = 0.261289
I0405 14:54:55.302958  1863 solver.cpp:237]     Train net output #0: loss = 0.261289 (* 1 = 0.261289 loss)
I0405 14:54:55.302966  1863 sgd_solver.cpp:105] Iteration 11064, lr = 0.001
I0405 14:55:00.543552  1863 solver.cpp:218] Iteration 11076 (2.28982 iter/s, 5.24058s/12 iters), loss = 0.315983
I0405 14:55:00.543596  1863 solver.cpp:237]     Train net output #0: loss = 0.315983 (* 1 = 0.315983 loss)
I0405 14:55:00.543602  1863 sgd_solver.cpp:105] Iteration 11076, lr = 0.001
I0405 14:55:05.893954  1863 solver.cpp:218] Iteration 11088 (2.24285 iter/s, 5.35035s/12 iters), loss = 0.35106
I0405 14:55:05.894006  1863 solver.cpp:237]     Train net output #0: loss = 0.35106 (* 1 = 0.35106 loss)
I0405 14:55:05.894014  1863 sgd_solver.cpp:105] Iteration 11088, lr = 0.001
I0405 14:55:09.244318  1863 blocking_queue.cpp:49] Waiting for data
I0405 14:55:11.037878  1863 solver.cpp:218] Iteration 11100 (2.33288 iter/s, 5.14386s/12 iters), loss = 0.22935
I0405 14:55:11.037922  1863 solver.cpp:237]     Train net output #0: loss = 0.22935 (* 1 = 0.22935 loss)
I0405 14:55:11.037928  1863 sgd_solver.cpp:105] Iteration 11100, lr = 0.001
I0405 14:55:16.290169  1863 solver.cpp:218] Iteration 11112 (2.28474 iter/s, 5.25223s/12 iters), loss = 0.204879
I0405 14:55:16.290303  1863 solver.cpp:237]     Train net output #0: loss = 0.204879 (* 1 = 0.204879 loss)
I0405 14:55:16.290311  1863 sgd_solver.cpp:105] Iteration 11112, lr = 0.001
I0405 14:55:18.312907  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11118.caffemodel
I0405 14:55:21.360752  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11118.solverstate
I0405 14:55:23.676870  1863 solver.cpp:330] Iteration 11118, Testing net (#0)
I0405 14:55:23.676905  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:55:28.072497  1863 solver.cpp:397]     Test net output #0: accuracy = 0.247549
I0405 14:55:28.072537  1863 solver.cpp:397]     Test net output #1: loss = 4.57241 (* 1 = 4.57241 loss)
I0405 14:55:28.684962  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:55:29.788659  1863 solver.cpp:218] Iteration 11124 (0.888997 iter/s, 13.4984s/12 iters), loss = 0.327614
I0405 14:55:29.788702  1863 solver.cpp:237]     Train net output #0: loss = 0.327614 (* 1 = 0.327614 loss)
I0405 14:55:29.788708  1863 sgd_solver.cpp:105] Iteration 11124, lr = 0.001
I0405 14:55:30.719051  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:55:35.042706  1863 solver.cpp:218] Iteration 11136 (2.28398 iter/s, 5.25398s/12 iters), loss = 0.2105
I0405 14:55:35.042765  1863 solver.cpp:237]     Train net output #0: loss = 0.2105 (* 1 = 0.2105 loss)
I0405 14:55:35.042775  1863 sgd_solver.cpp:105] Iteration 11136, lr = 0.001
I0405 14:55:40.170343  1863 solver.cpp:218] Iteration 11148 (2.34029 iter/s, 5.12757s/12 iters), loss = 0.359106
I0405 14:55:40.170387  1863 solver.cpp:237]     Train net output #0: loss = 0.359106 (* 1 = 0.359106 loss)
I0405 14:55:40.170393  1863 sgd_solver.cpp:105] Iteration 11148, lr = 0.001
I0405 14:55:45.279383  1863 solver.cpp:218] Iteration 11160 (2.3488 iter/s, 5.10899s/12 iters), loss = 0.250617
I0405 14:55:45.279424  1863 solver.cpp:237]     Train net output #0: loss = 0.250617 (* 1 = 0.250617 loss)
I0405 14:55:45.279430  1863 sgd_solver.cpp:105] Iteration 11160, lr = 0.001
I0405 14:55:50.670493  1863 solver.cpp:218] Iteration 11172 (2.22591 iter/s, 5.39106s/12 iters), loss = 0.249013
I0405 14:55:50.670619  1863 solver.cpp:237]     Train net output #0: loss = 0.249013 (* 1 = 0.249013 loss)
I0405 14:55:50.670627  1863 sgd_solver.cpp:105] Iteration 11172, lr = 0.001
I0405 14:55:56.009471  1863 solver.cpp:218] Iteration 11184 (2.24768 iter/s, 5.33884s/12 iters), loss = 0.217276
I0405 14:55:56.009527  1863 solver.cpp:237]     Train net output #0: loss = 0.217276 (* 1 = 0.217276 loss)
I0405 14:55:56.009536  1863 sgd_solver.cpp:105] Iteration 11184, lr = 0.001
I0405 14:56:01.071343  1863 solver.cpp:218] Iteration 11196 (2.37069 iter/s, 5.06181s/12 iters), loss = 0.386611
I0405 14:56:01.071382  1863 solver.cpp:237]     Train net output #0: loss = 0.386611 (* 1 = 0.386611 loss)
I0405 14:56:01.071388  1863 sgd_solver.cpp:105] Iteration 11196, lr = 0.001
I0405 14:56:06.522931  1863 solver.cpp:218] Iteration 11208 (2.20121 iter/s, 5.45154s/12 iters), loss = 0.297964
I0405 14:56:06.522974  1863 solver.cpp:237]     Train net output #0: loss = 0.297964 (* 1 = 0.297964 loss)
I0405 14:56:06.522980  1863 sgd_solver.cpp:105] Iteration 11208, lr = 0.001
I0405 14:56:11.229982  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11220.caffemodel
I0405 14:56:14.263525  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11220.solverstate
I0405 14:56:16.632670  1863 solver.cpp:330] Iteration 11220, Testing net (#0)
I0405 14:56:16.632690  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:56:21.059628  1863 solver.cpp:397]     Test net output #0: accuracy = 0.238358
I0405 14:56:21.059769  1863 solver.cpp:397]     Test net output #1: loss = 4.65066 (* 1 = 4.65066 loss)
I0405 14:56:21.201490  1863 solver.cpp:218] Iteration 11220 (0.817521 iter/s, 14.6785s/12 iters), loss = 0.298802
I0405 14:56:21.203141  1863 solver.cpp:237]     Train net output #0: loss = 0.298802 (* 1 = 0.298802 loss)
I0405 14:56:21.203153  1863 sgd_solver.cpp:105] Iteration 11220, lr = 0.001
I0405 14:56:21.351810  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:56:23.509351  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:56:25.577797  1863 solver.cpp:218] Iteration 11232 (2.74308 iter/s, 4.37465s/12 iters), loss = 0.227684
I0405 14:56:25.577841  1863 solver.cpp:237]     Train net output #0: loss = 0.227684 (* 1 = 0.227684 loss)
I0405 14:56:25.577845  1863 sgd_solver.cpp:105] Iteration 11232, lr = 0.001
I0405 14:56:30.994810  1863 solver.cpp:218] Iteration 11244 (2.21527 iter/s, 5.41696s/12 iters), loss = 0.240789
I0405 14:56:30.994856  1863 solver.cpp:237]     Train net output #0: loss = 0.240789 (* 1 = 0.240789 loss)
I0405 14:56:30.994861  1863 sgd_solver.cpp:105] Iteration 11244, lr = 0.001
I0405 14:56:36.226889  1863 solver.cpp:218] Iteration 11256 (2.29357 iter/s, 5.23202s/12 iters), loss = 0.310218
I0405 14:56:36.226943  1863 solver.cpp:237]     Train net output #0: loss = 0.310218 (* 1 = 0.310218 loss)
I0405 14:56:36.226951  1863 sgd_solver.cpp:105] Iteration 11256, lr = 0.001
I0405 14:56:41.498136  1863 solver.cpp:218] Iteration 11268 (2.27653 iter/s, 5.27119s/12 iters), loss = 0.314394
I0405 14:56:41.498174  1863 solver.cpp:237]     Train net output #0: loss = 0.314394 (* 1 = 0.314394 loss)
I0405 14:56:41.498179  1863 sgd_solver.cpp:105] Iteration 11268, lr = 0.001
I0405 14:56:46.712107  1863 solver.cpp:218] Iteration 11280 (2.30153 iter/s, 5.21392s/12 iters), loss = 0.275181
I0405 14:56:46.712167  1863 solver.cpp:237]     Train net output #0: loss = 0.275181 (* 1 = 0.275181 loss)
I0405 14:56:46.712177  1863 sgd_solver.cpp:105] Iteration 11280, lr = 0.001
I0405 14:56:51.974403  1863 solver.cpp:218] Iteration 11292 (2.2804 iter/s, 5.26223s/12 iters), loss = 0.196828
I0405 14:56:51.974514  1863 solver.cpp:237]     Train net output #0: loss = 0.196828 (* 1 = 0.196828 loss)
I0405 14:56:51.974521  1863 sgd_solver.cpp:105] Iteration 11292, lr = 0.001
I0405 14:56:57.253394  1863 solver.cpp:218] Iteration 11304 (2.27322 iter/s, 5.27887s/12 iters), loss = 0.231248
I0405 14:56:57.253445  1863 solver.cpp:237]     Train net output #0: loss = 0.231248 (* 1 = 0.231248 loss)
I0405 14:56:57.253454  1863 sgd_solver.cpp:105] Iteration 11304, lr = 0.001
I0405 14:57:02.531042  1863 solver.cpp:218] Iteration 11316 (2.27376 iter/s, 5.27759s/12 iters), loss = 0.248814
I0405 14:57:02.531085  1863 solver.cpp:237]     Train net output #0: loss = 0.248814 (* 1 = 0.248814 loss)
I0405 14:57:02.531090  1863 sgd_solver.cpp:105] Iteration 11316, lr = 0.001
I0405 14:57:04.722177  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11322.caffemodel
I0405 14:57:07.755838  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11322.solverstate
I0405 14:57:10.068373  1863 solver.cpp:330] Iteration 11322, Testing net (#0)
I0405 14:57:10.068397  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:57:14.537052  1863 solver.cpp:397]     Test net output #0: accuracy = 0.247549
I0405 14:57:14.537087  1863 solver.cpp:397]     Test net output #1: loss = 4.61645 (* 1 = 4.61645 loss)
I0405 14:57:14.997557  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:57:16.387917  1863 solver.cpp:218] Iteration 11328 (0.865999 iter/s, 13.8568s/12 iters), loss = 0.354915
I0405 14:57:16.387960  1863 solver.cpp:237]     Train net output #0: loss = 0.354915 (* 1 = 0.354915 loss)
I0405 14:57:16.387966  1863 sgd_solver.cpp:105] Iteration 11328, lr = 0.001
I0405 14:57:16.569926  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:57:21.499452  1863 solver.cpp:218] Iteration 11340 (2.34766 iter/s, 5.11148s/12 iters), loss = 0.249737
I0405 14:57:21.499503  1863 solver.cpp:237]     Train net output #0: loss = 0.249737 (* 1 = 0.249737 loss)
I0405 14:57:21.499511  1863 sgd_solver.cpp:105] Iteration 11340, lr = 0.001
I0405 14:57:26.653512  1863 solver.cpp:218] Iteration 11352 (2.32829 iter/s, 5.154s/12 iters), loss = 0.345593
I0405 14:57:26.653643  1863 solver.cpp:237]     Train net output #0: loss = 0.345593 (* 1 = 0.345593 loss)
I0405 14:57:26.653653  1863 sgd_solver.cpp:105] Iteration 11352, lr = 0.001
I0405 14:57:31.881801  1863 solver.cpp:218] Iteration 11364 (2.29527 iter/s, 5.22815s/12 iters), loss = 0.281902
I0405 14:57:31.881851  1863 solver.cpp:237]     Train net output #0: loss = 0.281902 (* 1 = 0.281902 loss)
I0405 14:57:31.881856  1863 sgd_solver.cpp:105] Iteration 11364, lr = 0.001
I0405 14:57:37.094038  1863 solver.cpp:218] Iteration 11376 (2.3023 iter/s, 5.21217s/12 iters), loss = 0.495838
I0405 14:57:37.094081  1863 solver.cpp:237]     Train net output #0: loss = 0.495838 (* 1 = 0.495838 loss)
I0405 14:57:37.094089  1863 sgd_solver.cpp:105] Iteration 11376, lr = 0.001
I0405 14:57:42.528492  1863 solver.cpp:218] Iteration 11388 (2.20815 iter/s, 5.4344s/12 iters), loss = 0.334167
I0405 14:57:42.528533  1863 solver.cpp:237]     Train net output #0: loss = 0.334167 (* 1 = 0.334167 loss)
I0405 14:57:42.528539  1863 sgd_solver.cpp:105] Iteration 11388, lr = 0.001
I0405 14:57:47.962594  1863 solver.cpp:218] Iteration 11400 (2.2083 iter/s, 5.43404s/12 iters), loss = 0.316119
I0405 14:57:47.969012  1863 solver.cpp:237]     Train net output #0: loss = 0.316119 (* 1 = 0.316119 loss)
I0405 14:57:47.969029  1863 sgd_solver.cpp:105] Iteration 11400, lr = 0.001
I0405 14:57:53.189381  1863 solver.cpp:218] Iteration 11412 (2.29869 iter/s, 5.22037s/12 iters), loss = 0.386524
I0405 14:57:53.189437  1863 solver.cpp:237]     Train net output #0: loss = 0.386524 (* 1 = 0.386524 loss)
I0405 14:57:53.189445  1863 sgd_solver.cpp:105] Iteration 11412, lr = 0.001
I0405 14:57:58.127563  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11424.caffemodel
I0405 14:58:01.119875  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11424.solverstate
I0405 14:58:03.420748  1863 solver.cpp:330] Iteration 11424, Testing net (#0)
I0405 14:58:03.420768  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:58:08.008620  1863 solver.cpp:397]     Test net output #0: accuracy = 0.249387
I0405 14:58:08.008661  1863 solver.cpp:397]     Test net output #1: loss = 4.60428 (* 1 = 4.60428 loss)
I0405 14:58:08.145223  1863 solver.cpp:218] Iteration 11424 (0.802365 iter/s, 14.9558s/12 iters), loss = 0.282001
I0405 14:58:08.145278  1863 solver.cpp:237]     Train net output #0: loss = 0.282001 (* 1 = 0.282001 loss)
I0405 14:58:08.145287  1863 sgd_solver.cpp:105] Iteration 11424, lr = 0.001
I0405 14:58:08.430608  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:58:09.611574  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:58:12.329398  1863 solver.cpp:218] Iteration 11436 (2.86799 iter/s, 4.18411s/12 iters), loss = 0.308672
I0405 14:58:12.329442  1863 solver.cpp:237]     Train net output #0: loss = 0.308672 (* 1 = 0.308672 loss)
I0405 14:58:12.329447  1863 sgd_solver.cpp:105] Iteration 11436, lr = 0.001
I0405 14:58:17.453332  1863 solver.cpp:218] Iteration 11448 (2.34198 iter/s, 5.12388s/12 iters), loss = 0.186718
I0405 14:58:17.453369  1863 solver.cpp:237]     Train net output #0: loss = 0.186718 (* 1 = 0.186718 loss)
I0405 14:58:17.453374  1863 sgd_solver.cpp:105] Iteration 11448, lr = 0.001
I0405 14:58:22.781173  1863 solver.cpp:218] Iteration 11460 (2.25234 iter/s, 5.3278s/12 iters), loss = 0.192331
I0405 14:58:22.781217  1863 solver.cpp:237]     Train net output #0: loss = 0.192331 (* 1 = 0.192331 loss)
I0405 14:58:22.781222  1863 sgd_solver.cpp:105] Iteration 11460, lr = 0.001
I0405 14:58:28.149716  1863 solver.cpp:218] Iteration 11472 (2.23527 iter/s, 5.36849s/12 iters), loss = 0.190159
I0405 14:58:28.149842  1863 solver.cpp:237]     Train net output #0: loss = 0.190159 (* 1 = 0.190159 loss)
I0405 14:58:28.149848  1863 sgd_solver.cpp:105] Iteration 11472, lr = 0.001
I0405 14:58:33.417542  1863 solver.cpp:218] Iteration 11484 (2.27804 iter/s, 5.26769s/12 iters), loss = 0.343958
I0405 14:58:33.417585  1863 solver.cpp:237]     Train net output #0: loss = 0.343958 (* 1 = 0.343958 loss)
I0405 14:58:33.417591  1863 sgd_solver.cpp:105] Iteration 11484, lr = 0.001
I0405 14:58:38.756940  1863 solver.cpp:218] Iteration 11496 (2.24747 iter/s, 5.33934s/12 iters), loss = 0.279057
I0405 14:58:38.756978  1863 solver.cpp:237]     Train net output #0: loss = 0.279057 (* 1 = 0.279057 loss)
I0405 14:58:38.756984  1863 sgd_solver.cpp:105] Iteration 11496, lr = 0.001
I0405 14:58:44.296768  1863 solver.cpp:218] Iteration 11508 (2.16616 iter/s, 5.53977s/12 iters), loss = 0.253628
I0405 14:58:44.296821  1863 solver.cpp:237]     Train net output #0: loss = 0.253628 (* 1 = 0.253628 loss)
I0405 14:58:44.296830  1863 sgd_solver.cpp:105] Iteration 11508, lr = 0.001
I0405 14:58:49.604302  1863 solver.cpp:218] Iteration 11520 (2.26096 iter/s, 5.30748s/12 iters), loss = 0.152255
I0405 14:58:49.604346  1863 solver.cpp:237]     Train net output #0: loss = 0.152255 (* 1 = 0.152255 loss)
I0405 14:58:49.604352  1863 sgd_solver.cpp:105] Iteration 11520, lr = 0.001
I0405 14:58:51.796167  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11526.caffemodel
I0405 14:58:54.987668  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11526.solverstate
I0405 14:58:57.368803  1863 solver.cpp:330] Iteration 11526, Testing net (#0)
I0405 14:58:57.368824  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:59:01.664523  1863 solver.cpp:397]     Test net output #0: accuracy = 0.245711
I0405 14:59:01.664631  1863 solver.cpp:397]     Test net output #1: loss = 4.68215 (* 1 = 4.68215 loss)
I0405 14:59:01.763638  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:02.868961  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:03.467531  1863 solver.cpp:218] Iteration 11532 (0.865602 iter/s, 13.8632s/12 iters), loss = 0.265682
I0405 14:59:03.467573  1863 solver.cpp:237]     Train net output #0: loss = 0.265682 (* 1 = 0.265682 loss)
I0405 14:59:03.467579  1863 sgd_solver.cpp:105] Iteration 11532, lr = 0.001
I0405 14:59:08.385301  1863 solver.cpp:218] Iteration 11544 (2.44016 iter/s, 4.91771s/12 iters), loss = 0.180138
I0405 14:59:08.385354  1863 solver.cpp:237]     Train net output #0: loss = 0.180138 (* 1 = 0.180138 loss)
I0405 14:59:08.385362  1863 sgd_solver.cpp:105] Iteration 11544, lr = 0.001
I0405 14:59:13.599318  1863 solver.cpp:218] Iteration 11556 (2.30152 iter/s, 5.21395s/12 iters), loss = 0.257708
I0405 14:59:13.599370  1863 solver.cpp:237]     Train net output #0: loss = 0.257708 (* 1 = 0.257708 loss)
I0405 14:59:13.599376  1863 sgd_solver.cpp:105] Iteration 11556, lr = 0.001
I0405 14:59:18.894479  1863 solver.cpp:218] Iteration 11568 (2.26624 iter/s, 5.29511s/12 iters), loss = 0.21619
I0405 14:59:18.894515  1863 solver.cpp:237]     Train net output #0: loss = 0.21619 (* 1 = 0.21619 loss)
I0405 14:59:18.894521  1863 sgd_solver.cpp:105] Iteration 11568, lr = 0.001
I0405 14:59:24.118114  1863 solver.cpp:218] Iteration 11580 (2.29727 iter/s, 5.22358s/12 iters), loss = 0.198067
I0405 14:59:24.118181  1863 solver.cpp:237]     Train net output #0: loss = 0.198067 (* 1 = 0.198067 loss)
I0405 14:59:24.118191  1863 sgd_solver.cpp:105] Iteration 11580, lr = 0.001
I0405 14:59:29.389039  1863 solver.cpp:218] Iteration 11592 (2.27667 iter/s, 5.27085s/12 iters), loss = 0.275025
I0405 14:59:29.389086  1863 solver.cpp:237]     Train net output #0: loss = 0.275025 (* 1 = 0.275025 loss)
I0405 14:59:29.389092  1863 sgd_solver.cpp:105] Iteration 11592, lr = 0.001
I0405 14:59:34.618088  1863 solver.cpp:218] Iteration 11604 (2.29489 iter/s, 5.229s/12 iters), loss = 0.326552
I0405 14:59:34.618245  1863 solver.cpp:237]     Train net output #0: loss = 0.326552 (* 1 = 0.326552 loss)
I0405 14:59:34.618255  1863 sgd_solver.cpp:105] Iteration 11604, lr = 0.001
I0405 14:59:39.974002  1863 solver.cpp:218] Iteration 11616 (2.24058 iter/s, 5.35574s/12 iters), loss = 0.377477
I0405 14:59:39.974066  1863 solver.cpp:237]     Train net output #0: loss = 0.377477 (* 1 = 0.377477 loss)
I0405 14:59:39.974074  1863 sgd_solver.cpp:105] Iteration 11616, lr = 0.001
I0405 14:59:44.804214  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11628.caffemodel
I0405 14:59:47.835534  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11628.solverstate
I0405 14:59:50.156180  1863 solver.cpp:330] Iteration 11628, Testing net (#0)
I0405 14:59:50.156199  1863 net.cpp:676] Ignoring source layer train-data
I0405 14:59:54.491868  1863 solver.cpp:397]     Test net output #0: accuracy = 0.253676
I0405 14:59:54.491904  1863 solver.cpp:397]     Test net output #1: loss = 4.69478 (* 1 = 4.69478 loss)
I0405 14:59:54.557128  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:54.633296  1863 solver.cpp:218] Iteration 11628 (0.818597 iter/s, 14.6592s/12 iters), loss = 0.27223
I0405 14:59:54.633348  1863 solver.cpp:237]     Train net output #0: loss = 0.27223 (* 1 = 0.27223 loss)
I0405 14:59:54.633355  1863 sgd_solver.cpp:105] Iteration 11628, lr = 0.001
I0405 14:59:55.352910  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 14:59:58.964671  1863 solver.cpp:218] Iteration 11640 (2.77053 iter/s, 4.33131s/12 iters), loss = 0.320082
I0405 14:59:58.964712  1863 solver.cpp:237]     Train net output #0: loss = 0.320082 (* 1 = 0.320082 loss)
I0405 14:59:58.964718  1863 sgd_solver.cpp:105] Iteration 11640, lr = 0.001
I0405 15:00:04.090034  1863 solver.cpp:218] Iteration 11652 (2.34132 iter/s, 5.1253s/12 iters), loss = 0.194993
I0405 15:00:04.090081  1863 solver.cpp:237]     Train net output #0: loss = 0.194993 (* 1 = 0.194993 loss)
I0405 15:00:04.090088  1863 sgd_solver.cpp:105] Iteration 11652, lr = 0.001
I0405 15:00:09.413008  1863 solver.cpp:218] Iteration 11664 (2.2544 iter/s, 5.32291s/12 iters), loss = 0.265747
I0405 15:00:09.413113  1863 solver.cpp:237]     Train net output #0: loss = 0.265747 (* 1 = 0.265747 loss)
I0405 15:00:09.413122  1863 sgd_solver.cpp:105] Iteration 11664, lr = 0.001
I0405 15:00:14.708483  1863 solver.cpp:218] Iteration 11676 (2.26613 iter/s, 5.29536s/12 iters), loss = 0.210126
I0405 15:00:14.708537  1863 solver.cpp:237]     Train net output #0: loss = 0.210126 (* 1 = 0.210126 loss)
I0405 15:00:14.708545  1863 sgd_solver.cpp:105] Iteration 11676, lr = 0.001
I0405 15:00:19.775759  1863 solver.cpp:218] Iteration 11688 (2.36817 iter/s, 5.06721s/12 iters), loss = 0.236854
I0405 15:00:19.775815  1863 solver.cpp:237]     Train net output #0: loss = 0.236854 (* 1 = 0.236854 loss)
I0405 15:00:19.775825  1863 sgd_solver.cpp:105] Iteration 11688, lr = 0.001
I0405 15:00:25.013377  1863 solver.cpp:218] Iteration 11700 (2.29115 iter/s, 5.23755s/12 iters), loss = 0.230697
I0405 15:00:25.013419  1863 solver.cpp:237]     Train net output #0: loss = 0.230697 (* 1 = 0.230697 loss)
I0405 15:00:25.013425  1863 sgd_solver.cpp:105] Iteration 11700, lr = 0.001
I0405 15:00:30.383687  1863 solver.cpp:218] Iteration 11712 (2.23453 iter/s, 5.37026s/12 iters), loss = 0.239986
I0405 15:00:30.383729  1863 solver.cpp:237]     Train net output #0: loss = 0.239986 (* 1 = 0.239986 loss)
I0405 15:00:30.383735  1863 sgd_solver.cpp:105] Iteration 11712, lr = 0.001
I0405 15:00:35.811947  1863 solver.cpp:218] Iteration 11724 (2.21068 iter/s, 5.4282s/12 iters), loss = 0.300614
I0405 15:00:35.811998  1863 solver.cpp:237]     Train net output #0: loss = 0.300614 (* 1 = 0.300614 loss)
I0405 15:00:35.812006  1863 sgd_solver.cpp:105] Iteration 11724, lr = 0.001
I0405 15:00:37.908272  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11730.caffemodel
I0405 15:00:40.915638  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11730.solverstate
I0405 15:00:43.212554  1863 solver.cpp:330] Iteration 11730, Testing net (#0)
I0405 15:00:43.212576  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:00:47.552636  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:00:47.583283  1863 solver.cpp:397]     Test net output #0: accuracy = 0.24326
I0405 15:00:47.583320  1863 solver.cpp:397]     Test net output #1: loss = 4.66147 (* 1 = 4.66147 loss)
I0405 15:00:48.304366  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:00:49.567102  1863 solver.cpp:218] Iteration 11736 (0.872404 iter/s, 13.7551s/12 iters), loss = 0.142227
I0405 15:00:49.567159  1863 solver.cpp:237]     Train net output #0: loss = 0.142227 (* 1 = 0.142227 loss)
I0405 15:00:49.567167  1863 sgd_solver.cpp:105] Iteration 11736, lr = 0.001
I0405 15:00:54.882936  1863 solver.cpp:218] Iteration 11748 (2.25744 iter/s, 5.31576s/12 iters), loss = 0.262587
I0405 15:00:54.882987  1863 solver.cpp:237]     Train net output #0: loss = 0.262587 (* 1 = 0.262587 loss)
I0405 15:00:54.882993  1863 sgd_solver.cpp:105] Iteration 11748, lr = 0.001
I0405 15:01:00.138819  1863 solver.cpp:218] Iteration 11760 (2.28318 iter/s, 5.25582s/12 iters), loss = 0.260747
I0405 15:01:00.138860  1863 solver.cpp:237]     Train net output #0: loss = 0.260747 (* 1 = 0.260747 loss)
I0405 15:01:00.138866  1863 sgd_solver.cpp:105] Iteration 11760, lr = 0.001
I0405 15:01:05.490765  1863 solver.cpp:218] Iteration 11772 (2.2422 iter/s, 5.35189s/12 iters), loss = 0.187564
I0405 15:01:05.490821  1863 solver.cpp:237]     Train net output #0: loss = 0.187564 (* 1 = 0.187564 loss)
I0405 15:01:05.490831  1863 sgd_solver.cpp:105] Iteration 11772, lr = 0.001
I0405 15:01:09.195333  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:01:10.552872  1863 solver.cpp:218] Iteration 11784 (2.37058 iter/s, 5.06204s/12 iters), loss = 0.288665
I0405 15:01:10.552918  1863 solver.cpp:237]     Train net output #0: loss = 0.288665 (* 1 = 0.288665 loss)
I0405 15:01:10.552923  1863 sgd_solver.cpp:105] Iteration 11784, lr = 0.001
I0405 15:01:15.846652  1863 solver.cpp:218] Iteration 11796 (2.26684 iter/s, 5.29372s/12 iters), loss = 0.176497
I0405 15:01:15.846781  1863 solver.cpp:237]     Train net output #0: loss = 0.176497 (* 1 = 0.176497 loss)
I0405 15:01:15.846789  1863 sgd_solver.cpp:105] Iteration 11796, lr = 0.001
I0405 15:01:20.894567  1863 solver.cpp:218] Iteration 11808 (2.37728 iter/s, 5.04778s/12 iters), loss = 0.263155
I0405 15:01:20.894615  1863 solver.cpp:237]     Train net output #0: loss = 0.263155 (* 1 = 0.263155 loss)
I0405 15:01:20.894623  1863 sgd_solver.cpp:105] Iteration 11808, lr = 0.001
I0405 15:01:26.136198  1863 solver.cpp:218] Iteration 11820 (2.28939 iter/s, 5.24157s/12 iters), loss = 0.152869
I0405 15:01:26.136250  1863 solver.cpp:237]     Train net output #0: loss = 0.152869 (* 1 = 0.152869 loss)
I0405 15:01:26.136262  1863 sgd_solver.cpp:105] Iteration 11820, lr = 0.001
I0405 15:01:31.040181  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11832.caffemodel
I0405 15:01:34.216060  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11832.solverstate
I0405 15:01:36.583930  1863 solver.cpp:330] Iteration 11832, Testing net (#0)
I0405 15:01:36.583947  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:01:41.001368  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:01:41.063305  1863 solver.cpp:397]     Test net output #0: accuracy = 0.256127
I0405 15:01:41.063339  1863 solver.cpp:397]     Test net output #1: loss = 4.69148 (* 1 = 4.69148 loss)
I0405 15:01:41.204017  1863 solver.cpp:218] Iteration 11832 (0.796402 iter/s, 15.0678s/12 iters), loss = 0.209086
I0405 15:01:41.204066  1863 solver.cpp:237]     Train net output #0: loss = 0.209086 (* 1 = 0.209086 loss)
I0405 15:01:41.204073  1863 sgd_solver.cpp:105] Iteration 11832, lr = 0.001
I0405 15:01:41.284407  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:01:45.551744  1863 solver.cpp:218] Iteration 11844 (2.7601 iter/s, 4.34766s/12 iters), loss = 0.206148
I0405 15:01:45.551802  1863 solver.cpp:237]     Train net output #0: loss = 0.206148 (* 1 = 0.206148 loss)
I0405 15:01:45.551810  1863 sgd_solver.cpp:105] Iteration 11844, lr = 0.001
I0405 15:01:50.831668  1863 solver.cpp:218] Iteration 11856 (2.27279 iter/s, 5.27986s/12 iters), loss = 0.411484
I0405 15:01:50.831784  1863 solver.cpp:237]     Train net output #0: loss = 0.411484 (* 1 = 0.411484 loss)
I0405 15:01:50.831792  1863 sgd_solver.cpp:105] Iteration 11856, lr = 0.001
I0405 15:01:56.114089  1863 solver.cpp:218] Iteration 11868 (2.27174 iter/s, 5.28229s/12 iters), loss = 0.28106
I0405 15:01:56.114151  1863 solver.cpp:237]     Train net output #0: loss = 0.28106 (* 1 = 0.28106 loss)
I0405 15:01:56.114161  1863 sgd_solver.cpp:105] Iteration 11868, lr = 0.001
I0405 15:02:01.400826  1863 solver.cpp:218] Iteration 11880 (2.26986 iter/s, 5.28667s/12 iters), loss = 0.213543
I0405 15:02:01.400867  1863 solver.cpp:237]     Train net output #0: loss = 0.213543 (* 1 = 0.213543 loss)
I0405 15:02:01.400873  1863 sgd_solver.cpp:105] Iteration 11880, lr = 0.001
I0405 15:02:06.583186  1863 solver.cpp:218] Iteration 11892 (2.31557 iter/s, 5.1823s/12 iters), loss = 0.268806
I0405 15:02:06.583230  1863 solver.cpp:237]     Train net output #0: loss = 0.268806 (* 1 = 0.268806 loss)
I0405 15:02:06.583237  1863 sgd_solver.cpp:105] Iteration 11892, lr = 0.001
I0405 15:02:12.103103  1863 solver.cpp:218] Iteration 11904 (2.17397 iter/s, 5.51986s/12 iters), loss = 0.19777
I0405 15:02:12.103153  1863 solver.cpp:237]     Train net output #0: loss = 0.19777 (* 1 = 0.19777 loss)
I0405 15:02:12.103161  1863 sgd_solver.cpp:105] Iteration 11904, lr = 0.001
I0405 15:02:17.327634  1863 solver.cpp:218] Iteration 11916 (2.29688 iter/s, 5.22448s/12 iters), loss = 0.233282
I0405 15:02:17.327667  1863 solver.cpp:237]     Train net output #0: loss = 0.233282 (* 1 = 0.233282 loss)
I0405 15:02:17.327672  1863 sgd_solver.cpp:105] Iteration 11916, lr = 0.001
I0405 15:02:22.612188  1863 solver.cpp:218] Iteration 11928 (2.27079 iter/s, 5.28451s/12 iters), loss = 0.169087
I0405 15:02:22.612314  1863 solver.cpp:237]     Train net output #0: loss = 0.169087 (* 1 = 0.169087 loss)
I0405 15:02:22.612323  1863 sgd_solver.cpp:105] Iteration 11928, lr = 0.001
I0405 15:02:24.751339  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_11934.caffemodel
I0405 15:02:25.777287  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:02:27.781955  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_11934.solverstate
I0405 15:02:30.082759  1863 solver.cpp:330] Iteration 11934, Testing net (#0)
I0405 15:02:30.082777  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:02:34.249496  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:02:34.355599  1863 solver.cpp:397]     Test net output #0: accuracy = 0.261642
I0405 15:02:34.355634  1863 solver.cpp:397]     Test net output #1: loss = 4.71835 (* 1 = 4.71835 loss)
I0405 15:02:36.227072  1863 solver.cpp:218] Iteration 11940 (0.881397 iter/s, 13.6148s/12 iters), loss = 0.305897
I0405 15:02:36.227120  1863 solver.cpp:237]     Train net output #0: loss = 0.305897 (* 1 = 0.305897 loss)
I0405 15:02:36.227128  1863 sgd_solver.cpp:105] Iteration 11940, lr = 0.001
I0405 15:02:41.516337  1863 solver.cpp:218] Iteration 11952 (2.26877 iter/s, 5.2892s/12 iters), loss = 0.273386
I0405 15:02:41.516381  1863 solver.cpp:237]     Train net output #0: loss = 0.273386 (* 1 = 0.273386 loss)
I0405 15:02:41.516386  1863 sgd_solver.cpp:105] Iteration 11952, lr = 0.001
I0405 15:02:49.992202  1863 solver.cpp:218] Iteration 11964 (1.41579 iter/s, 8.4758s/12 iters), loss = 0.340785
I0405 15:02:49.992266  1863 solver.cpp:237]     Train net output #0: loss = 0.340785 (* 1 = 0.340785 loss)
I0405 15:02:49.992274  1863 sgd_solver.cpp:105] Iteration 11964, lr = 0.001
I0405 15:02:59.281584  1863 solver.cpp:218] Iteration 11976 (1.29236 iter/s, 9.28531s/12 iters), loss = 0.286035
I0405 15:02:59.282438  1863 solver.cpp:237]     Train net output #0: loss = 0.286035 (* 1 = 0.286035 loss)
I0405 15:02:59.282449  1863 sgd_solver.cpp:105] Iteration 11976, lr = 0.001
I0405 15:03:08.915038  1863 solver.cpp:218] Iteration 11988 (1.24577 iter/s, 9.6326s/12 iters), loss = 0.229298
I0405 15:03:08.915099  1863 solver.cpp:237]     Train net output #0: loss = 0.229298 (* 1 = 0.229298 loss)
I0405 15:03:08.915107  1863 sgd_solver.cpp:105] Iteration 11988, lr = 0.001
I0405 15:03:15.782236  1863 solver.cpp:218] Iteration 12000 (1.74746 iter/s, 6.86713s/12 iters), loss = 0.196495
I0405 15:03:15.782285  1863 solver.cpp:237]     Train net output #0: loss = 0.196495 (* 1 = 0.196495 loss)
I0405 15:03:15.782294  1863 sgd_solver.cpp:105] Iteration 12000, lr = 0.001
I0405 15:03:22.106894  1863 solver.cpp:218] Iteration 12012 (1.89735 iter/s, 6.3246s/12 iters), loss = 0.450935
I0405 15:03:22.106948  1863 solver.cpp:237]     Train net output #0: loss = 0.450935 (* 1 = 0.450935 loss)
I0405 15:03:22.106956  1863 sgd_solver.cpp:105] Iteration 12012, lr = 0.001
I0405 15:03:28.819710  1863 solver.cpp:218] Iteration 12024 (1.78764 iter/s, 6.71275s/12 iters), loss = 0.252199
I0405 15:03:28.819764  1863 solver.cpp:237]     Train net output #0: loss = 0.252199 (* 1 = 0.252199 loss)
I0405 15:03:28.819773  1863 sgd_solver.cpp:105] Iteration 12024, lr = 0.001
I0405 15:03:34.671993  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12036.caffemodel
I0405 15:03:35.483970  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:03:38.802024  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12036.solverstate
I0405 15:03:41.515908  1863 solver.cpp:330] Iteration 12036, Testing net (#0)
I0405 15:03:41.515933  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:03:47.352660  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:03:47.535674  1863 solver.cpp:397]     Test net output #0: accuracy = 0.251838
I0405 15:03:47.535710  1863 solver.cpp:397]     Test net output #1: loss = 4.65338 (* 1 = 4.65338 loss)
I0405 15:03:47.680992  1863 solver.cpp:218] Iteration 12036 (0.636226 iter/s, 18.8612s/12 iters), loss = 0.187753
I0405 15:03:47.691231  1863 solver.cpp:237]     Train net output #0: loss = 0.187753 (* 1 = 0.187753 loss)
I0405 15:03:47.691252  1863 sgd_solver.cpp:105] Iteration 12036, lr = 0.001
I0405 15:03:53.140740  1863 solver.cpp:218] Iteration 12048 (2.20203 iter/s, 5.44952s/12 iters), loss = 0.155635
I0405 15:03:53.140794  1863 solver.cpp:237]     Train net output #0: loss = 0.155635 (* 1 = 0.155635 loss)
I0405 15:03:53.140803  1863 sgd_solver.cpp:105] Iteration 12048, lr = 0.001
I0405 15:03:59.285394  1863 solver.cpp:218] Iteration 12060 (1.95294 iter/s, 6.14459s/12 iters), loss = 0.168042
I0405 15:03:59.291958  1863 solver.cpp:237]     Train net output #0: loss = 0.168042 (* 1 = 0.168042 loss)
I0405 15:03:59.291990  1863 sgd_solver.cpp:105] Iteration 12060, lr = 0.001
I0405 15:04:05.758550  1863 solver.cpp:218] Iteration 12072 (1.85569 iter/s, 6.4666s/12 iters), loss = 0.220511
I0405 15:04:05.758677  1863 solver.cpp:237]     Train net output #0: loss = 0.220511 (* 1 = 0.220511 loss)
I0405 15:04:05.758687  1863 sgd_solver.cpp:105] Iteration 12072, lr = 0.001
I0405 15:04:12.255810  1863 solver.cpp:218] Iteration 12084 (1.84697 iter/s, 6.49712s/12 iters), loss = 0.284643
I0405 15:04:12.255867  1863 solver.cpp:237]     Train net output #0: loss = 0.284643 (* 1 = 0.284643 loss)
I0405 15:04:12.255875  1863 sgd_solver.cpp:105] Iteration 12084, lr = 0.001
I0405 15:04:18.462386  1863 solver.cpp:218] Iteration 12096 (1.93345 iter/s, 6.20651s/12 iters), loss = 0.234249
I0405 15:04:18.468588  1863 solver.cpp:237]     Train net output #0: loss = 0.234249 (* 1 = 0.234249 loss)
I0405 15:04:18.468607  1863 sgd_solver.cpp:105] Iteration 12096, lr = 0.001
I0405 15:04:25.236948  1863 solver.cpp:218] Iteration 12108 (1.77421 iter/s, 6.76356s/12 iters), loss = 0.328402
I0405 15:04:25.237000  1863 solver.cpp:237]     Train net output #0: loss = 0.328402 (* 1 = 0.328402 loss)
I0405 15:04:25.237008  1863 sgd_solver.cpp:105] Iteration 12108, lr = 0.001
I0405 15:04:31.636932  1863 solver.cpp:218] Iteration 12120 (1.87841 iter/s, 6.38837s/12 iters), loss = 0.216798
I0405 15:04:31.636992  1863 solver.cpp:237]     Train net output #0: loss = 0.216798 (* 1 = 0.216798 loss)
I0405 15:04:31.637001  1863 sgd_solver.cpp:105] Iteration 12120, lr = 0.001
I0405 15:04:37.588189  1863 solver.cpp:218] Iteration 12132 (2.0164 iter/s, 5.95119s/12 iters), loss = 0.201215
I0405 15:04:37.588313  1863 solver.cpp:237]     Train net output #0: loss = 0.201215 (* 1 = 0.201215 loss)
I0405 15:04:37.588320  1863 sgd_solver.cpp:105] Iteration 12132, lr = 0.001
I0405 15:04:39.685103  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12138.caffemodel
I0405 15:04:40.029228  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:04:42.773269  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12138.solverstate
I0405 15:04:45.063433  1863 solver.cpp:330] Iteration 12138, Testing net (#0)
I0405 15:04:45.063455  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:04:49.382411  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:04:49.553874  1863 solver.cpp:397]     Test net output #0: accuracy = 0.254289
I0405 15:04:49.553906  1863 solver.cpp:397]     Test net output #1: loss = 4.72707 (* 1 = 4.72707 loss)
I0405 15:04:51.424650  1863 solver.cpp:218] Iteration 12144 (0.867282 iter/s, 13.8363s/12 iters), loss = 0.217707
I0405 15:04:51.424700  1863 solver.cpp:237]     Train net output #0: loss = 0.217707 (* 1 = 0.217707 loss)
I0405 15:04:51.424707  1863 sgd_solver.cpp:105] Iteration 12144, lr = 0.001
I0405 15:04:56.591950  1863 solver.cpp:218] Iteration 12156 (2.32232 iter/s, 5.16724s/12 iters), loss = 0.192688
I0405 15:04:56.591992  1863 solver.cpp:237]     Train net output #0: loss = 0.192688 (* 1 = 0.192688 loss)
I0405 15:04:56.591997  1863 sgd_solver.cpp:105] Iteration 12156, lr = 0.001
I0405 15:05:01.765434  1863 solver.cpp:218] Iteration 12168 (2.31954 iter/s, 5.17343s/12 iters), loss = 0.221088
I0405 15:05:01.765477  1863 solver.cpp:237]     Train net output #0: loss = 0.221088 (* 1 = 0.221088 loss)
I0405 15:05:01.765484  1863 sgd_solver.cpp:105] Iteration 12168, lr = 0.001
I0405 15:05:07.049098  1863 solver.cpp:218] Iteration 12180 (2.27117 iter/s, 5.28361s/12 iters), loss = 0.273091
I0405 15:05:07.049139  1863 solver.cpp:237]     Train net output #0: loss = 0.273091 (* 1 = 0.273091 loss)
I0405 15:05:07.049145  1863 sgd_solver.cpp:105] Iteration 12180, lr = 0.001
I0405 15:05:12.324594  1863 solver.cpp:218] Iteration 12192 (2.27469 iter/s, 5.27544s/12 iters), loss = 0.275665
I0405 15:05:12.324723  1863 solver.cpp:237]     Train net output #0: loss = 0.275665 (* 1 = 0.275665 loss)
I0405 15:05:12.324731  1863 sgd_solver.cpp:105] Iteration 12192, lr = 0.001
I0405 15:05:17.529345  1863 solver.cpp:218] Iteration 12204 (2.30564 iter/s, 5.20462s/12 iters), loss = 0.189945
I0405 15:05:17.529390  1863 solver.cpp:237]     Train net output #0: loss = 0.189945 (* 1 = 0.189945 loss)
I0405 15:05:17.529397  1863 sgd_solver.cpp:105] Iteration 12204, lr = 0.001
I0405 15:05:22.899729  1863 solver.cpp:218] Iteration 12216 (2.2345 iter/s, 5.37033s/12 iters), loss = 0.327502
I0405 15:05:22.899775  1863 solver.cpp:237]     Train net output #0: loss = 0.327502 (* 1 = 0.327502 loss)
I0405 15:05:22.899780  1863 sgd_solver.cpp:105] Iteration 12216, lr = 0.001
I0405 15:05:28.099792  1863 solver.cpp:218] Iteration 12228 (2.30769 iter/s, 5.2s/12 iters), loss = 0.196091
I0405 15:05:28.099839  1863 solver.cpp:237]     Train net output #0: loss = 0.196091 (* 1 = 0.196091 loss)
I0405 15:05:28.099844  1863 sgd_solver.cpp:105] Iteration 12228, lr = 0.001
I0405 15:05:32.715610  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:05:32.804931  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12240.caffemodel
I0405 15:05:35.893193  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12240.solverstate
I0405 15:05:38.195480  1863 solver.cpp:330] Iteration 12240, Testing net (#0)
I0405 15:05:38.195500  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:05:42.341903  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:05:42.561334  1863 solver.cpp:397]     Test net output #0: accuracy = 0.253676
I0405 15:05:42.561372  1863 solver.cpp:397]     Test net output #1: loss = 4.71418 (* 1 = 4.71418 loss)
I0405 15:05:42.702941  1863 solver.cpp:218] Iteration 12240 (0.821743 iter/s, 14.6031s/12 iters), loss = 0.281802
I0405 15:05:42.702996  1863 solver.cpp:237]     Train net output #0: loss = 0.281802 (* 1 = 0.281802 loss)
I0405 15:05:42.703003  1863 sgd_solver.cpp:105] Iteration 12240, lr = 0.001
I0405 15:05:47.023512  1863 solver.cpp:218] Iteration 12252 (2.77746 iter/s, 4.3205s/12 iters), loss = 0.38314
I0405 15:05:47.023571  1863 solver.cpp:237]     Train net output #0: loss = 0.38314 (* 1 = 0.38314 loss)
I0405 15:05:47.023581  1863 sgd_solver.cpp:105] Iteration 12252, lr = 0.001
I0405 15:05:52.358928  1863 solver.cpp:218] Iteration 12264 (2.24915 iter/s, 5.33535s/12 iters), loss = 0.296695
I0405 15:05:52.358990  1863 solver.cpp:237]     Train net output #0: loss = 0.296695 (* 1 = 0.296695 loss)
I0405 15:05:52.359001  1863 sgd_solver.cpp:105] Iteration 12264, lr = 0.001
I0405 15:05:57.829396  1863 solver.cpp:218] Iteration 12276 (2.19363 iter/s, 5.4704s/12 iters), loss = 0.223208
I0405 15:05:57.829438  1863 solver.cpp:237]     Train net output #0: loss = 0.223208 (* 1 = 0.223208 loss)
I0405 15:05:57.829443  1863 sgd_solver.cpp:105] Iteration 12276, lr = 0.001
I0405 15:06:02.934317  1863 solver.cpp:218] Iteration 12288 (2.3507 iter/s, 5.10486s/12 iters), loss = 0.314574
I0405 15:06:02.934372  1863 solver.cpp:237]     Train net output #0: loss = 0.314573 (* 1 = 0.314573 loss)
I0405 15:06:02.934381  1863 sgd_solver.cpp:105] Iteration 12288, lr = 0.001
I0405 15:06:08.457849  1863 solver.cpp:218] Iteration 12300 (2.17255 iter/s, 5.52346s/12 iters), loss = 0.2482
I0405 15:06:08.457909  1863 solver.cpp:237]     Train net output #0: loss = 0.2482 (* 1 = 0.2482 loss)
I0405 15:06:08.457921  1863 sgd_solver.cpp:105] Iteration 12300, lr = 0.001
I0405 15:06:13.640329  1863 solver.cpp:218] Iteration 12312 (2.31552 iter/s, 5.18241s/12 iters), loss = 0.355695
I0405 15:06:13.640448  1863 solver.cpp:237]     Train net output #0: loss = 0.355695 (* 1 = 0.355695 loss)
I0405 15:06:13.640460  1863 sgd_solver.cpp:105] Iteration 12312, lr = 0.001
I0405 15:06:18.843899  1863 solver.cpp:218] Iteration 12324 (2.30617 iter/s, 5.20344s/12 iters), loss = 0.266657
I0405 15:06:18.843958  1863 solver.cpp:237]     Train net output #0: loss = 0.266657 (* 1 = 0.266657 loss)
I0405 15:06:18.843969  1863 sgd_solver.cpp:105] Iteration 12324, lr = 0.001
I0405 15:06:24.147351  1863 solver.cpp:218] Iteration 12336 (2.26271 iter/s, 5.30338s/12 iters), loss = 0.173538
I0405 15:06:24.147399  1863 solver.cpp:237]     Train net output #0: loss = 0.173538 (* 1 = 0.173538 loss)
I0405 15:06:24.147408  1863 sgd_solver.cpp:105] Iteration 12336, lr = 0.001
I0405 15:06:25.872072  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:06:26.300223  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12342.caffemodel
I0405 15:06:29.216053  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12342.solverstate
I0405 15:06:31.519534  1863 solver.cpp:330] Iteration 12342, Testing net (#0)
I0405 15:06:31.519557  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:06:35.543670  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:06:35.796012  1863 solver.cpp:397]     Test net output #0: accuracy = 0.25674
I0405 15:06:35.796048  1863 solver.cpp:397]     Test net output #1: loss = 4.6024 (* 1 = 4.6024 loss)
I0405 15:06:37.647356  1863 solver.cpp:218] Iteration 12348 (0.888892 iter/s, 13.5s/12 iters), loss = 0.154857
I0405 15:06:37.647394  1863 solver.cpp:237]     Train net output #0: loss = 0.154857 (* 1 = 0.154857 loss)
I0405 15:06:37.647400  1863 sgd_solver.cpp:105] Iteration 12348, lr = 0.001
I0405 15:06:42.941713  1863 solver.cpp:218] Iteration 12360 (2.26658 iter/s, 5.29431s/12 iters), loss = 0.158093
I0405 15:06:42.941757  1863 solver.cpp:237]     Train net output #0: loss = 0.158093 (* 1 = 0.158093 loss)
I0405 15:06:42.941762  1863 sgd_solver.cpp:105] Iteration 12360, lr = 0.001
I0405 15:06:48.046139  1863 solver.cpp:218] Iteration 12372 (2.35093 iter/s, 5.10437s/12 iters), loss = 0.190023
I0405 15:06:48.046270  1863 solver.cpp:237]     Train net output #0: loss = 0.190023 (* 1 = 0.190023 loss)
I0405 15:06:48.046277  1863 sgd_solver.cpp:105] Iteration 12372, lr = 0.001
I0405 15:06:53.290774  1863 solver.cpp:218] Iteration 12384 (2.28811 iter/s, 5.2445s/12 iters), loss = 0.219605
I0405 15:06:53.290817  1863 solver.cpp:237]     Train net output #0: loss = 0.219605 (* 1 = 0.219605 loss)
I0405 15:06:53.290823  1863 sgd_solver.cpp:105] Iteration 12384, lr = 0.001
I0405 15:06:58.709764  1863 solver.cpp:218] Iteration 12396 (2.21446 iter/s, 5.41894s/12 iters), loss = 0.165418
I0405 15:06:58.709801  1863 solver.cpp:237]     Train net output #0: loss = 0.165417 (* 1 = 0.165417 loss)
I0405 15:06:58.709806  1863 sgd_solver.cpp:105] Iteration 12396, lr = 0.001
I0405 15:07:04.146095  1863 solver.cpp:218] Iteration 12408 (2.20739 iter/s, 5.43628s/12 iters), loss = 0.266552
I0405 15:07:04.146145  1863 solver.cpp:237]     Train net output #0: loss = 0.266552 (* 1 = 0.266552 loss)
I0405 15:07:04.146153  1863 sgd_solver.cpp:105] Iteration 12408, lr = 0.001
I0405 15:07:09.476969  1863 solver.cpp:218] Iteration 12420 (2.25106 iter/s, 5.33081s/12 iters), loss = 0.230965
I0405 15:07:09.477027  1863 solver.cpp:237]     Train net output #0: loss = 0.230965 (* 1 = 0.230965 loss)
I0405 15:07:09.477036  1863 sgd_solver.cpp:105] Iteration 12420, lr = 0.001
I0405 15:07:14.785840  1863 solver.cpp:218] Iteration 12432 (2.2604 iter/s, 5.3088s/12 iters), loss = 0.272376
I0405 15:07:14.785883  1863 solver.cpp:237]     Train net output #0: loss = 0.272376 (* 1 = 0.272376 loss)
I0405 15:07:14.785890  1863 sgd_solver.cpp:105] Iteration 12432, lr = 0.001
I0405 15:07:18.925093  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:07:19.723490  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12444.caffemodel
I0405 15:07:22.858911  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12444.solverstate
I0405 15:07:25.163040  1863 solver.cpp:330] Iteration 12444, Testing net (#0)
I0405 15:07:25.163059  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:07:29.141129  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:07:29.438959  1863 solver.cpp:397]     Test net output #0: accuracy = 0.259804
I0405 15:07:29.438995  1863 solver.cpp:397]     Test net output #1: loss = 4.64856 (* 1 = 4.64856 loss)
I0405 15:07:29.580096  1863 solver.cpp:218] Iteration 12444 (0.811128 iter/s, 14.7942s/12 iters), loss = 0.32128
I0405 15:07:29.580143  1863 solver.cpp:237]     Train net output #0: loss = 0.32128 (* 1 = 0.32128 loss)
I0405 15:07:29.580150  1863 sgd_solver.cpp:105] Iteration 12444, lr = 0.001
I0405 15:07:33.888926  1863 solver.cpp:218] Iteration 12456 (2.78502 iter/s, 4.30877s/12 iters), loss = 0.188866
I0405 15:07:33.888967  1863 solver.cpp:237]     Train net output #0: loss = 0.188865 (* 1 = 0.188865 loss)
I0405 15:07:33.888972  1863 sgd_solver.cpp:105] Iteration 12456, lr = 0.001
I0405 15:07:38.110827  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:07:39.089982  1863 solver.cpp:218] Iteration 12468 (2.30725 iter/s, 5.201s/12 iters), loss = 0.193283
I0405 15:07:39.090037  1863 solver.cpp:237]     Train net output #0: loss = 0.193283 (* 1 = 0.193283 loss)
I0405 15:07:39.090045  1863 sgd_solver.cpp:105] Iteration 12468, lr = 0.001
I0405 15:07:44.276275  1863 solver.cpp:218] Iteration 12480 (2.31382 iter/s, 5.18623s/12 iters), loss = 0.244376
I0405 15:07:44.276326  1863 solver.cpp:237]     Train net output #0: loss = 0.244376 (* 1 = 0.244376 loss)
I0405 15:07:44.276335  1863 sgd_solver.cpp:105] Iteration 12480, lr = 0.001
I0405 15:07:49.526773  1863 solver.cpp:218] Iteration 12492 (2.28552 iter/s, 5.25044s/12 iters), loss = 0.30217
I0405 15:07:49.526914  1863 solver.cpp:237]     Train net output #0: loss = 0.30217 (* 1 = 0.30217 loss)
I0405 15:07:49.526921  1863 sgd_solver.cpp:105] Iteration 12492, lr = 0.001
I0405 15:07:54.989511  1863 solver.cpp:218] Iteration 12504 (2.19676 iter/s, 5.46258s/12 iters), loss = 0.14834
I0405 15:07:54.989579  1863 solver.cpp:237]     Train net output #0: loss = 0.14834 (* 1 = 0.14834 loss)
I0405 15:07:54.989588  1863 sgd_solver.cpp:105] Iteration 12504, lr = 0.001
I0405 15:08:00.198572  1863 solver.cpp:218] Iteration 12516 (2.3037 iter/s, 5.209s/12 iters), loss = 0.267862
I0405 15:08:00.198623  1863 solver.cpp:237]     Train net output #0: loss = 0.267862 (* 1 = 0.267862 loss)
I0405 15:08:00.198630  1863 sgd_solver.cpp:105] Iteration 12516, lr = 0.001
I0405 15:08:05.366400  1863 solver.cpp:218] Iteration 12528 (2.32209 iter/s, 5.16776s/12 iters), loss = 0.181883
I0405 15:08:05.366441  1863 solver.cpp:237]     Train net output #0: loss = 0.181883 (* 1 = 0.181883 loss)
I0405 15:08:05.366446  1863 sgd_solver.cpp:105] Iteration 12528, lr = 0.001
I0405 15:08:10.387586  1863 solver.cpp:218] Iteration 12540 (2.3899 iter/s, 5.02113s/12 iters), loss = 0.111898
I0405 15:08:10.387629  1863 solver.cpp:237]     Train net output #0: loss = 0.111898 (* 1 = 0.111898 loss)
I0405 15:08:10.387635  1863 sgd_solver.cpp:105] Iteration 12540, lr = 0.001
I0405 15:08:11.377570  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:08:12.420743  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12546.caffemodel
I0405 15:08:15.468163  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12546.solverstate
I0405 15:08:17.776880  1863 solver.cpp:330] Iteration 12546, Testing net (#0)
I0405 15:08:17.776911  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:08:21.730484  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:08:22.059514  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26348
I0405 15:08:22.059543  1863 solver.cpp:397]     Test net output #1: loss = 4.59482 (* 1 = 4.59482 loss)
I0405 15:08:23.927538  1863 solver.cpp:218] Iteration 12552 (0.886269 iter/s, 13.5399s/12 iters), loss = 0.312804
I0405 15:08:23.927579  1863 solver.cpp:237]     Train net output #0: loss = 0.312804 (* 1 = 0.312804 loss)
I0405 15:08:23.927585  1863 sgd_solver.cpp:105] Iteration 12552, lr = 0.001
I0405 15:08:29.188172  1863 solver.cpp:218] Iteration 12564 (2.28112 iter/s, 5.26058s/12 iters), loss = 0.134301
I0405 15:08:29.188230  1863 solver.cpp:237]     Train net output #0: loss = 0.134301 (* 1 = 0.134301 loss)
I0405 15:08:29.188241  1863 sgd_solver.cpp:105] Iteration 12564, lr = 0.001
I0405 15:08:34.385740  1863 solver.cpp:218] Iteration 12576 (2.3088 iter/s, 5.1975s/12 iters), loss = 0.181719
I0405 15:08:34.385790  1863 solver.cpp:237]     Train net output #0: loss = 0.181719 (* 1 = 0.181719 loss)
I0405 15:08:34.385802  1863 sgd_solver.cpp:105] Iteration 12576, lr = 0.001
I0405 15:08:39.582228  1863 solver.cpp:218] Iteration 12588 (2.30928 iter/s, 5.19643s/12 iters), loss = 0.266585
I0405 15:08:39.582275  1863 solver.cpp:237]     Train net output #0: loss = 0.266585 (* 1 = 0.266585 loss)
I0405 15:08:39.582281  1863 sgd_solver.cpp:105] Iteration 12588, lr = 0.001
I0405 15:08:44.802345  1863 solver.cpp:218] Iteration 12600 (2.29883 iter/s, 5.22006s/12 iters), loss = 0.240823
I0405 15:08:44.802400  1863 solver.cpp:237]     Train net output #0: loss = 0.240823 (* 1 = 0.240823 loss)
I0405 15:08:44.802408  1863 sgd_solver.cpp:105] Iteration 12600, lr = 0.001
I0405 15:08:49.889384  1863 solver.cpp:218] Iteration 12612 (2.35897 iter/s, 5.08697s/12 iters), loss = 0.109326
I0405 15:08:49.889426  1863 solver.cpp:237]     Train net output #0: loss = 0.109326 (* 1 = 0.109326 loss)
I0405 15:08:49.889432  1863 sgd_solver.cpp:105] Iteration 12612, lr = 0.001
I0405 15:08:54.952584  1863 solver.cpp:218] Iteration 12624 (2.37007 iter/s, 5.06315s/12 iters), loss = 0.123304
I0405 15:08:54.952710  1863 solver.cpp:237]     Train net output #0: loss = 0.123304 (* 1 = 0.123304 loss)
I0405 15:08:54.952716  1863 sgd_solver.cpp:105] Iteration 12624, lr = 0.001
I0405 15:09:00.346877  1863 solver.cpp:218] Iteration 12636 (2.22463 iter/s, 5.39415s/12 iters), loss = 0.151745
I0405 15:09:00.346930  1863 solver.cpp:237]     Train net output #0: loss = 0.151745 (* 1 = 0.151745 loss)
I0405 15:09:00.346936  1863 sgd_solver.cpp:105] Iteration 12636, lr = 0.001
I0405 15:09:03.573560  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:09:05.115823  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12648.caffemodel
I0405 15:09:08.142870  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12648.solverstate
I0405 15:09:10.440845  1863 solver.cpp:330] Iteration 12648, Testing net (#0)
I0405 15:09:10.440865  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:09:14.491854  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:09:14.869282  1863 solver.cpp:397]     Test net output #0: accuracy = 0.250613
I0405 15:09:14.869320  1863 solver.cpp:397]     Test net output #1: loss = 4.6306 (* 1 = 4.6306 loss)
I0405 15:09:15.007290  1863 solver.cpp:218] Iteration 12648 (0.818534 iter/s, 14.6604s/12 iters), loss = 0.20313
I0405 15:09:15.007340  1863 solver.cpp:237]     Train net output #0: loss = 0.20313 (* 1 = 0.20313 loss)
I0405 15:09:15.007349  1863 sgd_solver.cpp:105] Iteration 12648, lr = 0.001
I0405 15:09:19.252192  1863 solver.cpp:218] Iteration 12660 (2.82696 iter/s, 4.24484s/12 iters), loss = 0.246007
I0405 15:09:19.252243  1863 solver.cpp:237]     Train net output #0: loss = 0.246006 (* 1 = 0.246006 loss)
I0405 15:09:19.252249  1863 sgd_solver.cpp:105] Iteration 12660, lr = 0.001
I0405 15:09:24.480320  1863 solver.cpp:218] Iteration 12672 (2.2953 iter/s, 5.22806s/12 iters), loss = 0.302736
I0405 15:09:24.480374  1863 solver.cpp:237]     Train net output #0: loss = 0.302736 (* 1 = 0.302736 loss)
I0405 15:09:24.480383  1863 sgd_solver.cpp:105] Iteration 12672, lr = 0.001
I0405 15:09:29.800021  1863 solver.cpp:218] Iteration 12684 (2.25579 iter/s, 5.31963s/12 iters), loss = 0.254797
I0405 15:09:29.800139  1863 solver.cpp:237]     Train net output #0: loss = 0.254796 (* 1 = 0.254796 loss)
I0405 15:09:29.800149  1863 sgd_solver.cpp:105] Iteration 12684, lr = 0.001
I0405 15:09:35.348567  1863 solver.cpp:218] Iteration 12696 (2.16278 iter/s, 5.54842s/12 iters), loss = 0.212704
I0405 15:09:35.348616  1863 solver.cpp:237]     Train net output #0: loss = 0.212704 (* 1 = 0.212704 loss)
I0405 15:09:35.348624  1863 sgd_solver.cpp:105] Iteration 12696, lr = 0.001
I0405 15:09:40.739565  1863 solver.cpp:218] Iteration 12708 (2.22596 iter/s, 5.39094s/12 iters), loss = 0.221722
I0405 15:09:40.739609  1863 solver.cpp:237]     Train net output #0: loss = 0.221722 (* 1 = 0.221722 loss)
I0405 15:09:40.739615  1863 sgd_solver.cpp:105] Iteration 12708, lr = 0.001
I0405 15:09:45.558393  1863 solver.cpp:218] Iteration 12720 (2.49026 iter/s, 4.81877s/12 iters), loss = 0.252872
I0405 15:09:45.558432  1863 solver.cpp:237]     Train net output #0: loss = 0.252872 (* 1 = 0.252872 loss)
I0405 15:09:45.558439  1863 sgd_solver.cpp:105] Iteration 12720, lr = 0.001
I0405 15:09:50.780817  1863 solver.cpp:218] Iteration 12732 (2.29781 iter/s, 5.22237s/12 iters), loss = 0.225957
I0405 15:09:50.780869  1863 solver.cpp:237]     Train net output #0: loss = 0.225957 (* 1 = 0.225957 loss)
I0405 15:09:50.780876  1863 sgd_solver.cpp:105] Iteration 12732, lr = 0.001
I0405 15:09:56.238963  1863 solver.cpp:218] Iteration 12744 (2.19857 iter/s, 5.45808s/12 iters), loss = 0.0949854
I0405 15:09:56.239009  1863 solver.cpp:237]     Train net output #0: loss = 0.0949852 (* 1 = 0.0949852 loss)
I0405 15:09:56.239015  1863 sgd_solver.cpp:105] Iteration 12744, lr = 0.001
I0405 15:09:56.447954  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:09:58.337579  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12750.caffemodel
I0405 15:10:01.357856  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12750.solverstate
I0405 15:10:03.684775  1863 solver.cpp:330] Iteration 12750, Testing net (#0)
I0405 15:10:03.684795  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:10:07.651943  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:10:08.060317  1863 solver.cpp:397]     Test net output #0: accuracy = 0.247549
I0405 15:10:08.060353  1863 solver.cpp:397]     Test net output #1: loss = 4.73829 (* 1 = 4.73829 loss)
I0405 15:10:09.872711  1863 solver.cpp:218] Iteration 12756 (0.880172 iter/s, 13.6337s/12 iters), loss = 0.256774
I0405 15:10:09.872752  1863 solver.cpp:237]     Train net output #0: loss = 0.256773 (* 1 = 0.256773 loss)
I0405 15:10:09.872758  1863 sgd_solver.cpp:105] Iteration 12756, lr = 0.001
I0405 15:10:15.083093  1863 solver.cpp:218] Iteration 12768 (2.30312 iter/s, 5.21033s/12 iters), loss = 0.264153
I0405 15:10:15.083153  1863 solver.cpp:237]     Train net output #0: loss = 0.264153 (* 1 = 0.264153 loss)
I0405 15:10:15.083163  1863 sgd_solver.cpp:105] Iteration 12768, lr = 0.001
I0405 15:10:20.447176  1863 solver.cpp:218] Iteration 12780 (2.23713 iter/s, 5.36401s/12 iters), loss = 0.213565
I0405 15:10:20.447237  1863 solver.cpp:237]     Train net output #0: loss = 0.213565 (* 1 = 0.213565 loss)
I0405 15:10:20.447245  1863 sgd_solver.cpp:105] Iteration 12780, lr = 0.001
I0405 15:10:25.724737  1863 solver.cpp:218] Iteration 12792 (2.27381 iter/s, 5.27749s/12 iters), loss = 0.260171
I0405 15:10:25.724778  1863 solver.cpp:237]     Train net output #0: loss = 0.260171 (* 1 = 0.260171 loss)
I0405 15:10:25.724783  1863 sgd_solver.cpp:105] Iteration 12792, lr = 0.001
I0405 15:10:30.825204  1863 solver.cpp:218] Iteration 12804 (2.35275 iter/s, 5.10041s/12 iters), loss = 0.22858
I0405 15:10:30.825253  1863 solver.cpp:237]     Train net output #0: loss = 0.22858 (* 1 = 0.22858 loss)
I0405 15:10:30.825258  1863 sgd_solver.cpp:105] Iteration 12804, lr = 0.001
I0405 15:10:36.056650  1863 solver.cpp:218] Iteration 12816 (2.29385 iter/s, 5.23138s/12 iters), loss = 0.148853
I0405 15:10:36.056766  1863 solver.cpp:237]     Train net output #0: loss = 0.148853 (* 1 = 0.148853 loss)
I0405 15:10:36.056774  1863 sgd_solver.cpp:105] Iteration 12816, lr = 0.001
I0405 15:10:41.441458  1863 solver.cpp:218] Iteration 12828 (2.22854 iter/s, 5.38469s/12 iters), loss = 0.208102
I0405 15:10:41.441514  1863 solver.cpp:237]     Train net output #0: loss = 0.208102 (* 1 = 0.208102 loss)
I0405 15:10:41.441522  1863 sgd_solver.cpp:105] Iteration 12828, lr = 0.001
I0405 15:10:46.707320  1863 solver.cpp:218] Iteration 12840 (2.27886 iter/s, 5.26579s/12 iters), loss = 0.103759
I0405 15:10:46.707376  1863 solver.cpp:237]     Train net output #0: loss = 0.103759 (* 1 = 0.103759 loss)
I0405 15:10:46.707384  1863 sgd_solver.cpp:105] Iteration 12840, lr = 0.001
I0405 15:10:49.208607  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:10:51.560945  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12852.caffemodel
I0405 15:10:54.613754  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12852.solverstate
I0405 15:10:56.936343  1863 solver.cpp:330] Iteration 12852, Testing net (#0)
I0405 15:10:56.936365  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:11:00.833765  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:01.288507  1863 solver.cpp:397]     Test net output #0: accuracy = 0.249387
I0405 15:11:01.288543  1863 solver.cpp:397]     Test net output #1: loss = 4.70211 (* 1 = 4.70211 loss)
I0405 15:11:01.424672  1863 solver.cpp:218] Iteration 12852 (0.815367 iter/s, 14.7173s/12 iters), loss = 0.15596
I0405 15:11:01.426283  1863 solver.cpp:237]     Train net output #0: loss = 0.155959 (* 1 = 0.155959 loss)
I0405 15:11:01.426295  1863 sgd_solver.cpp:105] Iteration 12852, lr = 0.001
I0405 15:11:05.591544  1863 solver.cpp:218] Iteration 12864 (2.88098 iter/s, 4.16526s/12 iters), loss = 0.212637
I0405 15:11:05.591584  1863 solver.cpp:237]     Train net output #0: loss = 0.212637 (* 1 = 0.212637 loss)
I0405 15:11:05.591590  1863 sgd_solver.cpp:105] Iteration 12864, lr = 0.001
I0405 15:11:10.888026  1863 solver.cpp:218] Iteration 12876 (2.26568 iter/s, 5.29643s/12 iters), loss = 0.158335
I0405 15:11:10.888144  1863 solver.cpp:237]     Train net output #0: loss = 0.158334 (* 1 = 0.158334 loss)
I0405 15:11:10.888150  1863 sgd_solver.cpp:105] Iteration 12876, lr = 0.001
I0405 15:11:15.891448  1863 solver.cpp:218] Iteration 12888 (2.39842 iter/s, 5.00329s/12 iters), loss = 0.235264
I0405 15:11:15.891499  1863 solver.cpp:237]     Train net output #0: loss = 0.235264 (* 1 = 0.235264 loss)
I0405 15:11:15.891506  1863 sgd_solver.cpp:105] Iteration 12888, lr = 0.001
I0405 15:11:21.389650  1863 solver.cpp:218] Iteration 12900 (2.18256 iter/s, 5.49814s/12 iters), loss = 0.0971826
I0405 15:11:21.389693  1863 solver.cpp:237]     Train net output #0: loss = 0.0971825 (* 1 = 0.0971825 loss)
I0405 15:11:21.389699  1863 sgd_solver.cpp:105] Iteration 12900, lr = 0.001
I0405 15:11:26.666801  1863 solver.cpp:218] Iteration 12912 (2.27398 iter/s, 5.2771s/12 iters), loss = 0.165379
I0405 15:11:26.666842  1863 solver.cpp:237]     Train net output #0: loss = 0.165379 (* 1 = 0.165379 loss)
I0405 15:11:26.666847  1863 sgd_solver.cpp:105] Iteration 12912, lr = 0.001
I0405 15:11:32.161285  1863 solver.cpp:218] Iteration 12924 (2.18403 iter/s, 5.49443s/12 iters), loss = 0.13709
I0405 15:11:32.161377  1863 solver.cpp:237]     Train net output #0: loss = 0.13709 (* 1 = 0.13709 loss)
I0405 15:11:32.161386  1863 sgd_solver.cpp:105] Iteration 12924, lr = 0.001
I0405 15:11:37.489276  1863 solver.cpp:218] Iteration 12936 (2.2523 iter/s, 5.32789s/12 iters), loss = 0.303345
I0405 15:11:37.489331  1863 solver.cpp:237]     Train net output #0: loss = 0.303345 (* 1 = 0.303345 loss)
I0405 15:11:37.489339  1863 sgd_solver.cpp:105] Iteration 12936, lr = 0.001
I0405 15:11:42.036669  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:42.563861  1863 solver.cpp:218] Iteration 12948 (2.36475 iter/s, 5.07452s/12 iters), loss = 0.175768
I0405 15:11:42.563920  1863 solver.cpp:237]     Train net output #0: loss = 0.175768 (* 1 = 0.175768 loss)
I0405 15:11:42.563930  1863 sgd_solver.cpp:105] Iteration 12948, lr = 0.001
I0405 15:11:44.705674  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_12954.caffemodel
I0405 15:11:47.730003  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_12954.solverstate
I0405 15:11:50.037066  1863 solver.cpp:330] Iteration 12954, Testing net (#0)
I0405 15:11:50.037089  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:11:53.845743  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:11:54.332681  1863 solver.cpp:397]     Test net output #0: accuracy = 0.248775
I0405 15:11:54.332713  1863 solver.cpp:397]     Test net output #1: loss = 4.77172 (* 1 = 4.77172 loss)
I0405 15:11:56.138020  1863 solver.cpp:218] Iteration 12960 (0.884036 iter/s, 13.5741s/12 iters), loss = 0.225233
I0405 15:11:56.138064  1863 solver.cpp:237]     Train net output #0: loss = 0.225233 (* 1 = 0.225233 loss)
I0405 15:11:56.138070  1863 sgd_solver.cpp:105] Iteration 12960, lr = 0.001
I0405 15:12:01.405411  1863 solver.cpp:218] Iteration 12972 (2.27819 iter/s, 5.26733s/12 iters), loss = 0.125427
I0405 15:12:01.405457  1863 solver.cpp:237]     Train net output #0: loss = 0.125427 (* 1 = 0.125427 loss)
I0405 15:12:01.405462  1863 sgd_solver.cpp:105] Iteration 12972, lr = 0.001
I0405 15:12:06.808493  1863 solver.cpp:218] Iteration 12984 (2.22098 iter/s, 5.40302s/12 iters), loss = 0.233519
I0405 15:12:06.808537  1863 solver.cpp:237]     Train net output #0: loss = 0.233519 (* 1 = 0.233519 loss)
I0405 15:12:06.808544  1863 sgd_solver.cpp:105] Iteration 12984, lr = 0.001
I0405 15:12:12.004396  1863 solver.cpp:218] Iteration 12996 (2.30954 iter/s, 5.19584s/12 iters), loss = 0.120319
I0405 15:12:12.004462  1863 solver.cpp:237]     Train net output #0: loss = 0.120319 (* 1 = 0.120319 loss)
I0405 15:12:12.004470  1863 sgd_solver.cpp:105] Iteration 12996, lr = 0.001
I0405 15:12:17.339169  1863 solver.cpp:218] Iteration 13008 (2.24942 iter/s, 5.3347s/12 iters), loss = 0.192225
I0405 15:12:17.339311  1863 solver.cpp:237]     Train net output #0: loss = 0.192225 (* 1 = 0.192225 loss)
I0405 15:12:17.339319  1863 sgd_solver.cpp:105] Iteration 13008, lr = 0.001
I0405 15:12:22.597867  1863 solver.cpp:218] Iteration 13020 (2.282 iter/s, 5.25855s/12 iters), loss = 0.366269
I0405 15:12:22.597913  1863 solver.cpp:237]     Train net output #0: loss = 0.366269 (* 1 = 0.366269 loss)
I0405 15:12:22.597921  1863 sgd_solver.cpp:105] Iteration 13020, lr = 0.001
I0405 15:12:27.766222  1863 solver.cpp:218] Iteration 13032 (2.32185 iter/s, 5.1683s/12 iters), loss = 0.260136
I0405 15:12:27.766269  1863 solver.cpp:237]     Train net output #0: loss = 0.260136 (* 1 = 0.260136 loss)
I0405 15:12:27.766275  1863 sgd_solver.cpp:105] Iteration 13032, lr = 0.001
I0405 15:12:33.061764  1863 solver.cpp:218] Iteration 13044 (2.26608 iter/s, 5.29548s/12 iters), loss = 0.152038
I0405 15:12:33.061811  1863 solver.cpp:237]     Train net output #0: loss = 0.152038 (* 1 = 0.152038 loss)
I0405 15:12:33.061820  1863 sgd_solver.cpp:105] Iteration 13044, lr = 0.001
I0405 15:12:34.843356  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:12:37.903465  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13056.caffemodel
I0405 15:12:40.837164  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13056.solverstate
I0405 15:12:43.135212  1863 solver.cpp:330] Iteration 13056, Testing net (#0)
I0405 15:12:43.135232  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:12:47.161303  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:12:47.711587  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26348
I0405 15:12:47.711725  1863 solver.cpp:397]     Test net output #1: loss = 4.64692 (* 1 = 4.64692 loss)
I0405 15:12:47.852663  1863 solver.cpp:218] Iteration 13056 (0.811312 iter/s, 14.7908s/12 iters), loss = 0.104098
I0405 15:12:47.852723  1863 solver.cpp:237]     Train net output #0: loss = 0.104098 (* 1 = 0.104098 loss)
I0405 15:12:47.852732  1863 sgd_solver.cpp:105] Iteration 13056, lr = 0.001
I0405 15:12:52.239967  1863 solver.cpp:218] Iteration 13068 (2.73521 iter/s, 4.38723s/12 iters), loss = 0.160656
I0405 15:12:52.240013  1863 solver.cpp:237]     Train net output #0: loss = 0.160656 (* 1 = 0.160656 loss)
I0405 15:12:52.240020  1863 sgd_solver.cpp:105] Iteration 13068, lr = 0.001
I0405 15:12:57.616650  1863 solver.cpp:218] Iteration 13080 (2.23188 iter/s, 5.37662s/12 iters), loss = 0.186113
I0405 15:12:57.616704  1863 solver.cpp:237]     Train net output #0: loss = 0.186113 (* 1 = 0.186113 loss)
I0405 15:12:57.616714  1863 sgd_solver.cpp:105] Iteration 13080, lr = 0.001
I0405 15:13:02.901880  1863 solver.cpp:218] Iteration 13092 (2.27051 iter/s, 5.28516s/12 iters), loss = 0.210334
I0405 15:13:02.901923  1863 solver.cpp:237]     Train net output #0: loss = 0.210334 (* 1 = 0.210334 loss)
I0405 15:13:02.901930  1863 sgd_solver.cpp:105] Iteration 13092, lr = 0.001
I0405 15:13:08.241432  1863 solver.cpp:218] Iteration 13104 (2.2474 iter/s, 5.3395s/12 iters), loss = 0.11221
I0405 15:13:08.241484  1863 solver.cpp:237]     Train net output #0: loss = 0.11221 (* 1 = 0.11221 loss)
I0405 15:13:08.241492  1863 sgd_solver.cpp:105] Iteration 13104, lr = 0.001
I0405 15:13:13.302314  1863 solver.cpp:218] Iteration 13116 (2.37116 iter/s, 5.06082s/12 iters), loss = 0.296196
I0405 15:13:13.302356  1863 solver.cpp:237]     Train net output #0: loss = 0.296196 (* 1 = 0.296196 loss)
I0405 15:13:13.302361  1863 sgd_solver.cpp:105] Iteration 13116, lr = 0.001
I0405 15:13:18.639863  1863 solver.cpp:218] Iteration 13128 (2.24825 iter/s, 5.33749s/12 iters), loss = 0.213242
I0405 15:13:18.640007  1863 solver.cpp:237]     Train net output #0: loss = 0.213242 (* 1 = 0.213242 loss)
I0405 15:13:18.640015  1863 sgd_solver.cpp:105] Iteration 13128, lr = 0.001
I0405 15:13:23.944818  1863 solver.cpp:218] Iteration 13140 (2.2621 iter/s, 5.3048s/12 iters), loss = 0.172776
I0405 15:13:23.944890  1863 solver.cpp:237]     Train net output #0: loss = 0.172775 (* 1 = 0.172775 loss)
I0405 15:13:23.944900  1863 sgd_solver.cpp:105] Iteration 13140, lr = 0.001
I0405 15:13:28.220070  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:13:29.604046  1863 solver.cpp:218] Iteration 13152 (2.12046 iter/s, 5.65916s/12 iters), loss = 0.334418
I0405 15:13:29.604085  1863 solver.cpp:237]     Train net output #0: loss = 0.334418 (* 1 = 0.334418 loss)
I0405 15:13:29.604090  1863 sgd_solver.cpp:105] Iteration 13152, lr = 0.001
I0405 15:13:31.846048  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13158.caffemodel
I0405 15:13:34.886111  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13158.solverstate
I0405 15:13:38.175460  1863 solver.cpp:330] Iteration 13158, Testing net (#0)
I0405 15:13:38.175484  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:13:41.847100  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:13:42.073318  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:13:42.640941  1863 solver.cpp:397]     Test net output #0: accuracy = 0.251226
I0405 15:13:42.640977  1863 solver.cpp:397]     Test net output #1: loss = 4.67749 (* 1 = 4.67749 loss)
I0405 15:13:44.569103  1863 solver.cpp:218] Iteration 13164 (0.80187 iter/s, 14.965s/12 iters), loss = 0.171615
I0405 15:13:44.569159  1863 solver.cpp:237]     Train net output #0: loss = 0.171615 (* 1 = 0.171615 loss)
I0405 15:13:44.569167  1863 sgd_solver.cpp:105] Iteration 13164, lr = 0.001
I0405 15:13:49.912524  1863 solver.cpp:218] Iteration 13176 (2.24578 iter/s, 5.34336s/12 iters), loss = 0.263264
I0405 15:13:49.912614  1863 solver.cpp:237]     Train net output #0: loss = 0.263264 (* 1 = 0.263264 loss)
I0405 15:13:49.912621  1863 sgd_solver.cpp:105] Iteration 13176, lr = 0.001
I0405 15:13:54.934798  1863 solver.cpp:218] Iteration 13188 (2.38941 iter/s, 5.02217s/12 iters), loss = 0.224212
I0405 15:13:54.934849  1863 solver.cpp:237]     Train net output #0: loss = 0.224212 (* 1 = 0.224212 loss)
I0405 15:13:54.934857  1863 sgd_solver.cpp:105] Iteration 13188, lr = 0.001
I0405 15:14:00.119045  1863 solver.cpp:218] Iteration 13200 (2.31473 iter/s, 5.18419s/12 iters), loss = 0.114802
I0405 15:14:00.119093  1863 solver.cpp:237]     Train net output #0: loss = 0.114802 (* 1 = 0.114802 loss)
I0405 15:14:00.119100  1863 sgd_solver.cpp:105] Iteration 13200, lr = 0.001
I0405 15:14:05.095022  1863 solver.cpp:218] Iteration 13212 (2.41161 iter/s, 4.97592s/12 iters), loss = 0.206206
I0405 15:14:05.095062  1863 solver.cpp:237]     Train net output #0: loss = 0.206206 (* 1 = 0.206206 loss)
I0405 15:14:05.095067  1863 sgd_solver.cpp:105] Iteration 13212, lr = 0.001
I0405 15:14:10.370191  1863 solver.cpp:218] Iteration 13224 (2.27483 iter/s, 5.27511s/12 iters), loss = 0.25033
I0405 15:14:10.370231  1863 solver.cpp:237]     Train net output #0: loss = 0.25033 (* 1 = 0.25033 loss)
I0405 15:14:10.370237  1863 sgd_solver.cpp:105] Iteration 13224, lr = 0.001
I0405 15:14:15.509637  1863 solver.cpp:218] Iteration 13236 (2.33491 iter/s, 5.13939s/12 iters), loss = 0.172108
I0405 15:14:15.509685  1863 solver.cpp:237]     Train net output #0: loss = 0.172108 (* 1 = 0.172108 loss)
I0405 15:14:15.509693  1863 sgd_solver.cpp:105] Iteration 13236, lr = 0.001
I0405 15:14:20.804188  1863 solver.cpp:218] Iteration 13248 (2.26651 iter/s, 5.29449s/12 iters), loss = 0.19369
I0405 15:14:20.804284  1863 solver.cpp:237]     Train net output #0: loss = 0.19369 (* 1 = 0.19369 loss)
I0405 15:14:20.804291  1863 sgd_solver.cpp:105] Iteration 13248, lr = 0.001
I0405 15:14:21.817205  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:14:25.668278  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13260.caffemodel
I0405 15:14:28.591310  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13260.solverstate
I0405 15:14:30.894217  1863 solver.cpp:330] Iteration 13260, Testing net (#0)
I0405 15:14:30.894237  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:14:34.790318  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:14:35.389129  1863 solver.cpp:397]     Test net output #0: accuracy = 0.262868
I0405 15:14:35.389166  1863 solver.cpp:397]     Test net output #1: loss = 4.76427 (* 1 = 4.76427 loss)
I0405 15:14:35.525630  1863 solver.cpp:218] Iteration 13260 (0.815143 iter/s, 14.7213s/12 iters), loss = 0.174909
I0405 15:14:35.525686  1863 solver.cpp:237]     Train net output #0: loss = 0.174909 (* 1 = 0.174909 loss)
I0405 15:14:35.525693  1863 sgd_solver.cpp:105] Iteration 13260, lr = 0.001
I0405 15:14:40.001756  1863 solver.cpp:218] Iteration 13272 (2.68093 iter/s, 4.47605s/12 iters), loss = 0.269108
I0405 15:14:40.001809  1863 solver.cpp:237]     Train net output #0: loss = 0.269107 (* 1 = 0.269107 loss)
I0405 15:14:40.001817  1863 sgd_solver.cpp:105] Iteration 13272, lr = 0.001
I0405 15:14:45.055835  1863 solver.cpp:218] Iteration 13284 (2.37435 iter/s, 5.05402s/12 iters), loss = 0.218637
I0405 15:14:45.055879  1863 solver.cpp:237]     Train net output #0: loss = 0.218637 (* 1 = 0.218637 loss)
I0405 15:14:45.055884  1863 sgd_solver.cpp:105] Iteration 13284, lr = 0.001
I0405 15:14:50.241117  1863 solver.cpp:218] Iteration 13296 (2.31427 iter/s, 5.18522s/12 iters), loss = 0.17368
I0405 15:14:50.241164  1863 solver.cpp:237]     Train net output #0: loss = 0.17368 (* 1 = 0.17368 loss)
I0405 15:14:50.241170  1863 sgd_solver.cpp:105] Iteration 13296, lr = 0.001
I0405 15:14:55.507786  1863 solver.cpp:218] Iteration 13308 (2.27851 iter/s, 5.26661s/12 iters), loss = 0.141353
I0405 15:14:55.507920  1863 solver.cpp:237]     Train net output #0: loss = 0.141353 (* 1 = 0.141353 loss)
I0405 15:14:55.507926  1863 sgd_solver.cpp:105] Iteration 13308, lr = 0.001
I0405 15:15:00.755420  1863 solver.cpp:218] Iteration 13320 (2.28681 iter/s, 5.24749s/12 iters), loss = 0.140432
I0405 15:15:00.755472  1863 solver.cpp:237]     Train net output #0: loss = 0.140432 (* 1 = 0.140432 loss)
I0405 15:15:00.755482  1863 sgd_solver.cpp:105] Iteration 13320, lr = 0.001
I0405 15:15:06.067625  1863 solver.cpp:218] Iteration 13332 (2.25898 iter/s, 5.31214s/12 iters), loss = 0.325035
I0405 15:15:06.067677  1863 solver.cpp:237]     Train net output #0: loss = 0.325035 (* 1 = 0.325035 loss)
I0405 15:15:06.067684  1863 sgd_solver.cpp:105] Iteration 13332, lr = 0.001
I0405 15:15:11.300909  1863 solver.cpp:218] Iteration 13344 (2.29304 iter/s, 5.23322s/12 iters), loss = 0.111203
I0405 15:15:11.300952  1863 solver.cpp:237]     Train net output #0: loss = 0.111203 (* 1 = 0.111203 loss)
I0405 15:15:11.300958  1863 sgd_solver.cpp:105] Iteration 13344, lr = 0.001
I0405 15:15:14.558123  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:15:16.625072  1863 solver.cpp:218] Iteration 13356 (2.2539 iter/s, 5.3241s/12 iters), loss = 0.0610835
I0405 15:15:16.625128  1863 solver.cpp:237]     Train net output #0: loss = 0.0610834 (* 1 = 0.0610834 loss)
I0405 15:15:16.625136  1863 sgd_solver.cpp:105] Iteration 13356, lr = 0.001
I0405 15:15:18.615756  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13362.caffemodel
I0405 15:15:21.682186  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13362.solverstate
I0405 15:15:24.003904  1863 solver.cpp:330] Iteration 13362, Testing net (#0)
I0405 15:15:24.003926  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:15:27.811540  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:15:28.459738  1863 solver.cpp:397]     Test net output #0: accuracy = 0.245711
I0405 15:15:28.459774  1863 solver.cpp:397]     Test net output #1: loss = 4.6702 (* 1 = 4.6702 loss)
I0405 15:15:30.372982  1863 solver.cpp:218] Iteration 13368 (0.872864 iter/s, 13.7479s/12 iters), loss = 0.170227
I0405 15:15:30.373034  1863 solver.cpp:237]     Train net output #0: loss = 0.170226 (* 1 = 0.170226 loss)
I0405 15:15:30.373041  1863 sgd_solver.cpp:105] Iteration 13368, lr = 0.001
I0405 15:15:35.508407  1863 solver.cpp:218] Iteration 13380 (2.33674 iter/s, 5.13536s/12 iters), loss = 0.118117
I0405 15:15:35.508466  1863 solver.cpp:237]     Train net output #0: loss = 0.118116 (* 1 = 0.118116 loss)
I0405 15:15:35.508473  1863 sgd_solver.cpp:105] Iteration 13380, lr = 0.001
I0405 15:15:40.780390  1863 solver.cpp:218] Iteration 13392 (2.27621 iter/s, 5.27192s/12 iters), loss = 0.241443
I0405 15:15:40.780434  1863 solver.cpp:237]     Train net output #0: loss = 0.241443 (* 1 = 0.241443 loss)
I0405 15:15:40.780439  1863 sgd_solver.cpp:105] Iteration 13392, lr = 0.001
I0405 15:15:45.794754  1863 solver.cpp:218] Iteration 13404 (2.39315 iter/s, 5.01431s/12 iters), loss = 0.177214
I0405 15:15:45.794795  1863 solver.cpp:237]     Train net output #0: loss = 0.177214 (* 1 = 0.177214 loss)
I0405 15:15:45.794801  1863 sgd_solver.cpp:105] Iteration 13404, lr = 0.001
I0405 15:15:50.912940  1863 solver.cpp:218] Iteration 13416 (2.3446 iter/s, 5.11814s/12 iters), loss = 0.0751038
I0405 15:15:50.912983  1863 solver.cpp:237]     Train net output #0: loss = 0.0751037 (* 1 = 0.0751037 loss)
I0405 15:15:50.912990  1863 sgd_solver.cpp:105] Iteration 13416, lr = 0.001
I0405 15:15:56.190315  1863 solver.cpp:218] Iteration 13428 (2.27388 iter/s, 5.27733s/12 iters), loss = 0.17647
I0405 15:15:56.190353  1863 solver.cpp:237]     Train net output #0: loss = 0.17647 (* 1 = 0.17647 loss)
I0405 15:15:56.190359  1863 sgd_solver.cpp:105] Iteration 13428, lr = 0.001
I0405 15:16:01.423523  1863 solver.cpp:218] Iteration 13440 (2.29307 iter/s, 5.23316s/12 iters), loss = 0.0787239
I0405 15:16:01.423648  1863 solver.cpp:237]     Train net output #0: loss = 0.0787238 (* 1 = 0.0787238 loss)
I0405 15:16:01.423655  1863 sgd_solver.cpp:105] Iteration 13440, lr = 0.001
I0405 15:16:06.796825  1863 solver.cpp:218] Iteration 13452 (2.23332 iter/s, 5.37317s/12 iters), loss = 0.202404
I0405 15:16:06.796871  1863 solver.cpp:237]     Train net output #0: loss = 0.202404 (* 1 = 0.202404 loss)
I0405 15:16:06.796878  1863 sgd_solver.cpp:105] Iteration 13452, lr = 0.001
I0405 15:16:07.031704  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:16:11.520512  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13464.caffemodel
I0405 15:16:14.542753  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13464.solverstate
I0405 15:16:16.862848  1863 solver.cpp:330] Iteration 13464, Testing net (#0)
I0405 15:16:16.862866  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:16:20.581073  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:16:21.258899  1863 solver.cpp:397]     Test net output #0: accuracy = 0.257966
I0405 15:16:21.258935  1863 solver.cpp:397]     Test net output #1: loss = 4.65784 (* 1 = 4.65784 loss)
I0405 15:16:21.396557  1863 solver.cpp:218] Iteration 13464 (0.821934 iter/s, 14.5997s/12 iters), loss = 0.215804
I0405 15:16:21.398288  1863 solver.cpp:237]     Train net output #0: loss = 0.215804 (* 1 = 0.215804 loss)
I0405 15:16:21.398298  1863 sgd_solver.cpp:105] Iteration 13464, lr = 0.001
I0405 15:16:25.465731  1863 solver.cpp:218] Iteration 13476 (2.95026 iter/s, 4.06744s/12 iters), loss = 0.299288
I0405 15:16:25.465792  1863 solver.cpp:237]     Train net output #0: loss = 0.299288 (* 1 = 0.299288 loss)
I0405 15:16:25.465802  1863 sgd_solver.cpp:105] Iteration 13476, lr = 0.001
I0405 15:16:30.842250  1863 solver.cpp:218] Iteration 13488 (2.23196 iter/s, 5.37645s/12 iters), loss = 0.146285
I0405 15:16:30.842304  1863 solver.cpp:237]     Train net output #0: loss = 0.146284 (* 1 = 0.146284 loss)
I0405 15:16:30.842312  1863 sgd_solver.cpp:105] Iteration 13488, lr = 0.001
I0405 15:16:36.156347  1863 solver.cpp:218] Iteration 13500 (2.25817 iter/s, 5.31404s/12 iters), loss = 0.268455
I0405 15:16:36.156498  1863 solver.cpp:237]     Train net output #0: loss = 0.268455 (* 1 = 0.268455 loss)
I0405 15:16:36.156507  1863 sgd_solver.cpp:105] Iteration 13500, lr = 0.001
I0405 15:16:41.429049  1863 solver.cpp:218] Iteration 13512 (2.27594 iter/s, 5.27255s/12 iters), loss = 0.145625
I0405 15:16:41.429090  1863 solver.cpp:237]     Train net output #0: loss = 0.145625 (* 1 = 0.145625 loss)
I0405 15:16:41.429095  1863 sgd_solver.cpp:105] Iteration 13512, lr = 0.001
I0405 15:16:46.780145  1863 solver.cpp:218] Iteration 13524 (2.24255 iter/s, 5.35105s/12 iters), loss = 0.165387
I0405 15:16:46.780184  1863 solver.cpp:237]     Train net output #0: loss = 0.165386 (* 1 = 0.165386 loss)
I0405 15:16:46.780189  1863 sgd_solver.cpp:105] Iteration 13524, lr = 0.001
I0405 15:16:51.992669  1863 solver.cpp:218] Iteration 13536 (2.30217 iter/s, 5.21248s/12 iters), loss = 0.226179
I0405 15:16:51.992725  1863 solver.cpp:237]     Train net output #0: loss = 0.226179 (* 1 = 0.226179 loss)
I0405 15:16:51.992733  1863 sgd_solver.cpp:105] Iteration 13536, lr = 0.001
I0405 15:16:57.166083  1863 solver.cpp:218] Iteration 13548 (2.31958 iter/s, 5.17336s/12 iters), loss = 0.282433
I0405 15:16:57.166124  1863 solver.cpp:237]     Train net output #0: loss = 0.282433 (* 1 = 0.282433 loss)
I0405 15:16:57.166131  1863 sgd_solver.cpp:105] Iteration 13548, lr = 0.001
I0405 15:16:59.664590  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:17:02.644212  1863 solver.cpp:218] Iteration 13560 (2.19055 iter/s, 5.47808s/12 iters), loss = 0.221513
I0405 15:17:02.644253  1863 solver.cpp:237]     Train net output #0: loss = 0.221513 (* 1 = 0.221513 loss)
I0405 15:17:02.644258  1863 sgd_solver.cpp:105] Iteration 13560, lr = 0.001
I0405 15:17:04.689563  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13566.caffemodel
I0405 15:17:07.709503  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13566.solverstate
I0405 15:17:10.024345  1863 solver.cpp:330] Iteration 13566, Testing net (#0)
I0405 15:17:10.024371  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:17:13.699476  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:17:14.429613  1863 solver.cpp:397]     Test net output #0: accuracy = 0.265931
I0405 15:17:14.429648  1863 solver.cpp:397]     Test net output #1: loss = 4.57732 (* 1 = 4.57732 loss)
I0405 15:17:16.305933  1863 solver.cpp:218] Iteration 13572 (0.878368 iter/s, 13.6617s/12 iters), loss = 0.220014
I0405 15:17:16.305974  1863 solver.cpp:237]     Train net output #0: loss = 0.220014 (* 1 = 0.220014 loss)
I0405 15:17:16.305979  1863 sgd_solver.cpp:105] Iteration 13572, lr = 0.001
I0405 15:17:21.723488  1863 solver.cpp:218] Iteration 13584 (2.21504 iter/s, 5.4175s/12 iters), loss = 0.191325
I0405 15:17:21.723546  1863 solver.cpp:237]     Train net output #0: loss = 0.191325 (* 1 = 0.191325 loss)
I0405 15:17:21.723552  1863 sgd_solver.cpp:105] Iteration 13584, lr = 0.001
I0405 15:17:26.910032  1863 solver.cpp:218] Iteration 13596 (2.31371 iter/s, 5.18648s/12 iters), loss = 0.161271
I0405 15:17:26.910073  1863 solver.cpp:237]     Train net output #0: loss = 0.161271 (* 1 = 0.161271 loss)
I0405 15:17:26.910077  1863 sgd_solver.cpp:105] Iteration 13596, lr = 0.001
I0405 15:17:32.281487  1863 solver.cpp:218] Iteration 13608 (2.23405 iter/s, 5.37141s/12 iters), loss = 0.158795
I0405 15:17:32.281544  1863 solver.cpp:237]     Train net output #0: loss = 0.158795 (* 1 = 0.158795 loss)
I0405 15:17:32.281553  1863 sgd_solver.cpp:105] Iteration 13608, lr = 0.001
I0405 15:17:37.495335  1863 solver.cpp:218] Iteration 13620 (2.30159 iter/s, 5.21378s/12 iters), loss = 0.115087
I0405 15:17:37.495379  1863 solver.cpp:237]     Train net output #0: loss = 0.115087 (* 1 = 0.115087 loss)
I0405 15:17:37.495384  1863 sgd_solver.cpp:105] Iteration 13620, lr = 0.001
I0405 15:17:42.841907  1863 solver.cpp:218] Iteration 13632 (2.24445 iter/s, 5.34652s/12 iters), loss = 0.13322
I0405 15:17:42.842039  1863 solver.cpp:237]     Train net output #0: loss = 0.13322 (* 1 = 0.13322 loss)
I0405 15:17:42.842046  1863 sgd_solver.cpp:105] Iteration 13632, lr = 0.001
I0405 15:17:48.088366  1863 solver.cpp:218] Iteration 13644 (2.28732 iter/s, 5.24632s/12 iters), loss = 0.174304
I0405 15:17:48.088410  1863 solver.cpp:237]     Train net output #0: loss = 0.174304 (* 1 = 0.174304 loss)
I0405 15:17:48.088415  1863 sgd_solver.cpp:105] Iteration 13644, lr = 0.001
I0405 15:17:53.001677  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:17:53.419179  1863 solver.cpp:218] Iteration 13656 (2.25108 iter/s, 5.33076s/12 iters), loss = 0.111254
I0405 15:17:53.419219  1863 solver.cpp:237]     Train net output #0: loss = 0.111254 (* 1 = 0.111254 loss)
I0405 15:17:53.419224  1863 sgd_solver.cpp:105] Iteration 13656, lr = 0.001
I0405 15:17:58.146284  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13668.caffemodel
I0405 15:18:01.203411  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13668.solverstate
I0405 15:18:03.631989  1863 solver.cpp:330] Iteration 13668, Testing net (#0)
I0405 15:18:03.632010  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:18:07.217375  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:18:07.979863  1863 solver.cpp:397]     Test net output #0: accuracy = 0.259191
I0405 15:18:07.979910  1863 solver.cpp:397]     Test net output #1: loss = 4.75913 (* 1 = 4.75913 loss)
I0405 15:18:08.117708  1863 solver.cpp:218] Iteration 13668 (0.81641 iter/s, 14.6985s/12 iters), loss = 0.222442
I0405 15:18:08.117758  1863 solver.cpp:237]     Train net output #0: loss = 0.222442 (* 1 = 0.222442 loss)
I0405 15:18:08.117765  1863 sgd_solver.cpp:105] Iteration 13668, lr = 0.001
I0405 15:18:12.422905  1863 solver.cpp:218] Iteration 13680 (2.78737 iter/s, 4.30514s/12 iters), loss = 0.136597
I0405 15:18:12.422948  1863 solver.cpp:237]     Train net output #0: loss = 0.136597 (* 1 = 0.136597 loss)
I0405 15:18:12.422957  1863 sgd_solver.cpp:105] Iteration 13680, lr = 0.001
I0405 15:18:17.780601  1863 solver.cpp:218] Iteration 13692 (2.23979 iter/s, 5.35765s/12 iters), loss = 0.208752
I0405 15:18:17.780715  1863 solver.cpp:237]     Train net output #0: loss = 0.208752 (* 1 = 0.208752 loss)
I0405 15:18:17.780723  1863 sgd_solver.cpp:105] Iteration 13692, lr = 0.001
I0405 15:18:23.053987  1863 solver.cpp:218] Iteration 13704 (2.27563 iter/s, 5.27327s/12 iters), loss = 0.135906
I0405 15:18:23.054028  1863 solver.cpp:237]     Train net output #0: loss = 0.135906 (* 1 = 0.135906 loss)
I0405 15:18:23.054034  1863 sgd_solver.cpp:105] Iteration 13704, lr = 0.001
I0405 15:18:28.436623  1863 solver.cpp:218] Iteration 13716 (2.22941 iter/s, 5.38259s/12 iters), loss = 0.152423
I0405 15:18:28.436671  1863 solver.cpp:237]     Train net output #0: loss = 0.152423 (* 1 = 0.152423 loss)
I0405 15:18:28.436676  1863 sgd_solver.cpp:105] Iteration 13716, lr = 0.001
I0405 15:18:33.639518  1863 solver.cpp:218] Iteration 13728 (2.30643 iter/s, 5.20284s/12 iters), loss = 0.128521
I0405 15:18:33.639560  1863 solver.cpp:237]     Train net output #0: loss = 0.128521 (* 1 = 0.128521 loss)
I0405 15:18:33.639566  1863 sgd_solver.cpp:105] Iteration 13728, lr = 0.001
I0405 15:18:39.003913  1863 solver.cpp:218] Iteration 13740 (2.23699 iter/s, 5.36435s/12 iters), loss = 0.180897
I0405 15:18:39.003969  1863 solver.cpp:237]     Train net output #0: loss = 0.180897 (* 1 = 0.180897 loss)
I0405 15:18:39.003978  1863 sgd_solver.cpp:105] Iteration 13740, lr = 0.001
I0405 15:18:44.423591  1863 solver.cpp:218] Iteration 13752 (2.21418 iter/s, 5.41962s/12 iters), loss = 0.180665
I0405 15:18:44.423631  1863 solver.cpp:237]     Train net output #0: loss = 0.180665 (* 1 = 0.180665 loss)
I0405 15:18:44.423637  1863 sgd_solver.cpp:105] Iteration 13752, lr = 0.001
I0405 15:18:46.216434  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:18:49.562404  1863 solver.cpp:218] Iteration 13764 (2.33519 iter/s, 5.13877s/12 iters), loss = 0.132977
I0405 15:18:49.562530  1863 solver.cpp:237]     Train net output #0: loss = 0.132977 (* 1 = 0.132977 loss)
I0405 15:18:49.562537  1863 sgd_solver.cpp:105] Iteration 13764, lr = 0.001
I0405 15:18:51.682466  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13770.caffemodel
I0405 15:18:54.701243  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13770.solverstate
I0405 15:18:57.003563  1863 solver.cpp:330] Iteration 13770, Testing net (#0)
I0405 15:18:57.003583  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:19:00.528780  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:01.312994  1863 solver.cpp:397]     Test net output #0: accuracy = 0.264706
I0405 15:19:01.313031  1863 solver.cpp:397]     Test net output #1: loss = 4.76133 (* 1 = 4.76133 loss)
I0405 15:19:03.128235  1863 solver.cpp:218] Iteration 13776 (0.884583 iter/s, 13.5657s/12 iters), loss = 0.220058
I0405 15:19:03.128273  1863 solver.cpp:237]     Train net output #0: loss = 0.220058 (* 1 = 0.220058 loss)
I0405 15:19:03.128279  1863 sgd_solver.cpp:105] Iteration 13776, lr = 0.001
I0405 15:19:08.433970  1863 solver.cpp:218] Iteration 13788 (2.26172 iter/s, 5.30569s/12 iters), loss = 0.0945078
I0405 15:19:08.434029  1863 solver.cpp:237]     Train net output #0: loss = 0.0945077 (* 1 = 0.0945077 loss)
I0405 15:19:08.434038  1863 sgd_solver.cpp:105] Iteration 13788, lr = 0.001
I0405 15:19:13.750592  1863 solver.cpp:218] Iteration 13800 (2.2571 iter/s, 5.31656s/12 iters), loss = 0.229065
I0405 15:19:13.750630  1863 solver.cpp:237]     Train net output #0: loss = 0.229065 (* 1 = 0.229065 loss)
I0405 15:19:13.750636  1863 sgd_solver.cpp:105] Iteration 13800, lr = 0.001
I0405 15:19:19.028687  1863 solver.cpp:218] Iteration 13812 (2.27357 iter/s, 5.27805s/12 iters), loss = 0.280939
I0405 15:19:19.028733  1863 solver.cpp:237]     Train net output #0: loss = 0.280939 (* 1 = 0.280939 loss)
I0405 15:19:19.028739  1863 sgd_solver.cpp:105] Iteration 13812, lr = 0.001
I0405 15:19:24.252209  1863 solver.cpp:218] Iteration 13824 (2.29732 iter/s, 5.22347s/12 iters), loss = 0.200286
I0405 15:19:24.252336  1863 solver.cpp:237]     Train net output #0: loss = 0.200286 (* 1 = 0.200286 loss)
I0405 15:19:24.252348  1863 sgd_solver.cpp:105] Iteration 13824, lr = 0.001
I0405 15:19:29.592959  1863 solver.cpp:218] Iteration 13836 (2.24693 iter/s, 5.34062s/12 iters), loss = 0.181832
I0405 15:19:29.593003  1863 solver.cpp:237]     Train net output #0: loss = 0.181832 (* 1 = 0.181832 loss)
I0405 15:19:29.593008  1863 sgd_solver.cpp:105] Iteration 13836, lr = 0.001
I0405 15:19:34.655858  1863 solver.cpp:218] Iteration 13848 (2.37021 iter/s, 5.06285s/12 iters), loss = 0.288872
I0405 15:19:34.655896  1863 solver.cpp:237]     Train net output #0: loss = 0.288872 (* 1 = 0.288872 loss)
I0405 15:19:34.655901  1863 sgd_solver.cpp:105] Iteration 13848, lr = 0.001
I0405 15:19:38.671113  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:39.833029  1863 solver.cpp:218] Iteration 13860 (2.31789 iter/s, 5.17713s/12 iters), loss = 0.180308
I0405 15:19:39.833070  1863 solver.cpp:237]     Train net output #0: loss = 0.180308 (* 1 = 0.180308 loss)
I0405 15:19:39.833076  1863 sgd_solver.cpp:105] Iteration 13860, lr = 0.001
I0405 15:19:44.519100  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13872.caffemodel
I0405 15:19:48.564771  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13872.solverstate
I0405 15:19:51.568575  1863 solver.cpp:330] Iteration 13872, Testing net (#0)
I0405 15:19:51.568596  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:19:52.526331  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:19:55.039355  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:19:55.898147  1863 solver.cpp:397]     Test net output #0: accuracy = 0.272672
I0405 15:19:55.898177  1863 solver.cpp:397]     Test net output #1: loss = 4.62765 (* 1 = 4.62765 loss)
I0405 15:19:56.032719  1863 solver.cpp:218] Iteration 13872 (0.740756 iter/s, 16.1997s/12 iters), loss = 0.154344
I0405 15:19:56.032775  1863 solver.cpp:237]     Train net output #0: loss = 0.154344 (* 1 = 0.154344 loss)
I0405 15:19:56.032783  1863 sgd_solver.cpp:105] Iteration 13872, lr = 0.001
I0405 15:20:00.396612  1863 solver.cpp:218] Iteration 13884 (2.74988 iter/s, 4.36383s/12 iters), loss = 0.17945
I0405 15:20:00.396667  1863 solver.cpp:237]     Train net output #0: loss = 0.17945 (* 1 = 0.17945 loss)
I0405 15:20:00.396675  1863 sgd_solver.cpp:105] Iteration 13884, lr = 0.001
I0405 15:20:05.667994  1863 solver.cpp:218] Iteration 13896 (2.27647 iter/s, 5.27132s/12 iters), loss = 0.0820714
I0405 15:20:05.668040  1863 solver.cpp:237]     Train net output #0: loss = 0.0820713 (* 1 = 0.0820713 loss)
I0405 15:20:05.668045  1863 sgd_solver.cpp:105] Iteration 13896, lr = 0.001
I0405 15:20:11.170550  1863 solver.cpp:218] Iteration 13908 (2.18083 iter/s, 5.5025s/12 iters), loss = 0.226733
I0405 15:20:11.170598  1863 solver.cpp:237]     Train net output #0: loss = 0.226733 (* 1 = 0.226733 loss)
I0405 15:20:11.170603  1863 sgd_solver.cpp:105] Iteration 13908, lr = 0.001
I0405 15:20:16.598531  1863 solver.cpp:218] Iteration 13920 (2.21079 iter/s, 5.42793s/12 iters), loss = 0.104359
I0405 15:20:16.598577  1863 solver.cpp:237]     Train net output #0: loss = 0.104359 (* 1 = 0.104359 loss)
I0405 15:20:16.598582  1863 sgd_solver.cpp:105] Iteration 13920, lr = 0.001
I0405 15:20:21.874552  1863 solver.cpp:218] Iteration 13932 (2.27446 iter/s, 5.27597s/12 iters), loss = 0.129405
I0405 15:20:21.874601  1863 solver.cpp:237]     Train net output #0: loss = 0.129405 (* 1 = 0.129405 loss)
I0405 15:20:21.874608  1863 sgd_solver.cpp:105] Iteration 13932, lr = 0.001
I0405 15:20:27.075738  1863 solver.cpp:218] Iteration 13944 (2.30719 iter/s, 5.20113s/12 iters), loss = 0.151074
I0405 15:20:27.075901  1863 solver.cpp:237]     Train net output #0: loss = 0.151074 (* 1 = 0.151074 loss)
I0405 15:20:27.075911  1863 sgd_solver.cpp:105] Iteration 13944, lr = 0.001
I0405 15:20:32.336227  1863 solver.cpp:218] Iteration 13956 (2.28123 iter/s, 5.26033s/12 iters), loss = 0.0826224
I0405 15:20:32.336267  1863 solver.cpp:237]     Train net output #0: loss = 0.0826223 (* 1 = 0.0826223 loss)
I0405 15:20:32.336273  1863 sgd_solver.cpp:105] Iteration 13956, lr = 0.001
I0405 15:20:33.380178  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:20:37.669802  1863 solver.cpp:218] Iteration 13968 (2.24992 iter/s, 5.33353s/12 iters), loss = 0.205058
I0405 15:20:37.669852  1863 solver.cpp:237]     Train net output #0: loss = 0.205058 (* 1 = 0.205058 loss)
I0405 15:20:37.669860  1863 sgd_solver.cpp:105] Iteration 13968, lr = 0.001
I0405 15:20:39.809525  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_13974.caffemodel
I0405 15:20:42.808504  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_13974.solverstate
I0405 15:20:45.758183  1863 solver.cpp:330] Iteration 13974, Testing net (#0)
I0405 15:20:45.758205  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:20:49.373878  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:20:50.274891  1863 solver.cpp:397]     Test net output #0: accuracy = 0.265319
I0405 15:20:50.274925  1863 solver.cpp:397]     Test net output #1: loss = 4.67692 (* 1 = 4.67692 loss)
I0405 15:20:52.166668  1863 solver.cpp:218] Iteration 13980 (0.827767 iter/s, 14.4968s/12 iters), loss = 0.333236
I0405 15:20:52.166720  1863 solver.cpp:237]     Train net output #0: loss = 0.333236 (* 1 = 0.333236 loss)
I0405 15:20:52.166729  1863 sgd_solver.cpp:105] Iteration 13980, lr = 0.001
I0405 15:20:57.395437  1863 solver.cpp:218] Iteration 13992 (2.29502 iter/s, 5.22871s/12 iters), loss = 0.381336
I0405 15:20:57.395560  1863 solver.cpp:237]     Train net output #0: loss = 0.381336 (* 1 = 0.381336 loss)
I0405 15:20:57.395570  1863 sgd_solver.cpp:105] Iteration 13992, lr = 0.001
I0405 15:21:02.680203  1863 solver.cpp:218] Iteration 14004 (2.27073 iter/s, 5.28464s/12 iters), loss = 0.133765
I0405 15:21:02.680256  1863 solver.cpp:237]     Train net output #0: loss = 0.133765 (* 1 = 0.133765 loss)
I0405 15:21:02.680265  1863 sgd_solver.cpp:105] Iteration 14004, lr = 0.001
I0405 15:21:08.051425  1863 solver.cpp:218] Iteration 14016 (2.23415 iter/s, 5.37116s/12 iters), loss = 0.158611
I0405 15:21:08.051476  1863 solver.cpp:237]     Train net output #0: loss = 0.158611 (* 1 = 0.158611 loss)
I0405 15:21:08.051486  1863 sgd_solver.cpp:105] Iteration 14016, lr = 0.001
I0405 15:21:13.471002  1863 solver.cpp:218] Iteration 14028 (2.21422 iter/s, 5.41952s/12 iters), loss = 0.120261
I0405 15:21:13.471051  1863 solver.cpp:237]     Train net output #0: loss = 0.120261 (* 1 = 0.120261 loss)
I0405 15:21:13.471060  1863 sgd_solver.cpp:105] Iteration 14028, lr = 0.001
I0405 15:21:18.762876  1863 solver.cpp:218] Iteration 14040 (2.26765 iter/s, 5.29182s/12 iters), loss = 0.303368
I0405 15:21:18.762923  1863 solver.cpp:237]     Train net output #0: loss = 0.303368 (* 1 = 0.303368 loss)
I0405 15:21:18.762930  1863 sgd_solver.cpp:105] Iteration 14040, lr = 0.001
I0405 15:21:23.941581  1863 solver.cpp:218] Iteration 14052 (2.31721 iter/s, 5.17865s/12 iters), loss = 0.118043
I0405 15:21:23.941637  1863 solver.cpp:237]     Train net output #0: loss = 0.118043 (* 1 = 0.118043 loss)
I0405 15:21:23.941644  1863 sgd_solver.cpp:105] Iteration 14052, lr = 0.001
I0405 15:21:27.458016  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:21:29.380800  1863 solver.cpp:218] Iteration 14064 (2.20622 iter/s, 5.43916s/12 iters), loss = 0.129139
I0405 15:21:29.380841  1863 solver.cpp:237]     Train net output #0: loss = 0.129139 (* 1 = 0.129139 loss)
I0405 15:21:29.380847  1863 sgd_solver.cpp:105] Iteration 14064, lr = 0.001
I0405 15:21:34.004392  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14076.caffemodel
I0405 15:21:37.298648  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14076.solverstate
I0405 15:21:39.728186  1863 solver.cpp:330] Iteration 14076, Testing net (#0)
I0405 15:21:39.728209  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:21:43.109709  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:21:44.021972  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26777
I0405 15:21:44.022011  1863 solver.cpp:397]     Test net output #1: loss = 4.75042 (* 1 = 4.75042 loss)
I0405 15:21:44.163343  1863 solver.cpp:218] Iteration 14076 (0.81177 iter/s, 14.7825s/12 iters), loss = 0.190142
I0405 15:21:44.163386  1863 solver.cpp:237]     Train net output #0: loss = 0.190142 (* 1 = 0.190142 loss)
I0405 15:21:44.163391  1863 sgd_solver.cpp:105] Iteration 14076, lr = 0.001
I0405 15:21:48.520423  1863 solver.cpp:218] Iteration 14088 (2.75417 iter/s, 4.35702s/12 iters), loss = 0.2084
I0405 15:21:48.520470  1863 solver.cpp:237]     Train net output #0: loss = 0.2084 (* 1 = 0.2084 loss)
I0405 15:21:48.520476  1863 sgd_solver.cpp:105] Iteration 14088, lr = 0.001
I0405 15:21:53.882115  1863 solver.cpp:218] Iteration 14100 (2.23812 iter/s, 5.36164s/12 iters), loss = 0.132161
I0405 15:21:53.882166  1863 solver.cpp:237]     Train net output #0: loss = 0.132161 (* 1 = 0.132161 loss)
I0405 15:21:53.882174  1863 sgd_solver.cpp:105] Iteration 14100, lr = 0.001
I0405 15:21:59.211784  1863 solver.cpp:218] Iteration 14112 (2.25157 iter/s, 5.32961s/12 iters), loss = 0.20828
I0405 15:21:59.211882  1863 solver.cpp:237]     Train net output #0: loss = 0.20828 (* 1 = 0.20828 loss)
I0405 15:21:59.211889  1863 sgd_solver.cpp:105] Iteration 14112, lr = 0.001
I0405 15:22:04.485035  1863 solver.cpp:218] Iteration 14124 (2.27568 iter/s, 5.27315s/12 iters), loss = 0.234115
I0405 15:22:04.485082  1863 solver.cpp:237]     Train net output #0: loss = 0.234115 (* 1 = 0.234115 loss)
I0405 15:22:04.485088  1863 sgd_solver.cpp:105] Iteration 14124, lr = 0.001
I0405 15:22:09.886346  1863 solver.cpp:218] Iteration 14136 (2.2217 iter/s, 5.40126s/12 iters), loss = 0.214216
I0405 15:22:09.886389  1863 solver.cpp:237]     Train net output #0: loss = 0.214216 (* 1 = 0.214216 loss)
I0405 15:22:09.886395  1863 sgd_solver.cpp:105] Iteration 14136, lr = 0.001
I0405 15:22:15.110203  1863 solver.cpp:218] Iteration 14148 (2.29718 iter/s, 5.2238s/12 iters), loss = 0.155701
I0405 15:22:15.110256  1863 solver.cpp:237]     Train net output #0: loss = 0.155701 (* 1 = 0.155701 loss)
I0405 15:22:15.110265  1863 sgd_solver.cpp:105] Iteration 14148, lr = 0.001
I0405 15:22:20.508975  1863 solver.cpp:218] Iteration 14160 (2.22275 iter/s, 5.39871s/12 iters), loss = 0.17847
I0405 15:22:20.509023  1863 solver.cpp:237]     Train net output #0: loss = 0.17847 (* 1 = 0.17847 loss)
I0405 15:22:20.509029  1863 sgd_solver.cpp:105] Iteration 14160, lr = 0.001
I0405 15:22:20.769357  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:22:25.561532  1863 solver.cpp:218] Iteration 14172 (2.37506 iter/s, 5.05251s/12 iters), loss = 0.238147
I0405 15:22:25.561576  1863 solver.cpp:237]     Train net output #0: loss = 0.238147 (* 1 = 0.238147 loss)
I0405 15:22:25.561583  1863 sgd_solver.cpp:105] Iteration 14172, lr = 0.001
I0405 15:22:27.591558  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14178.caffemodel
I0405 15:22:31.423223  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14178.solverstate
I0405 15:22:33.872201  1863 solver.cpp:330] Iteration 14178, Testing net (#0)
I0405 15:22:33.872225  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:22:37.432651  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:22:38.397171  1863 solver.cpp:397]     Test net output #0: accuracy = 0.264706
I0405 15:22:38.397202  1863 solver.cpp:397]     Test net output #1: loss = 4.74983 (* 1 = 4.74983 loss)
I0405 15:22:40.299484  1863 solver.cpp:218] Iteration 14184 (0.814226 iter/s, 14.7379s/12 iters), loss = 0.131398
I0405 15:22:40.299540  1863 solver.cpp:237]     Train net output #0: loss = 0.131398 (* 1 = 0.131398 loss)
I0405 15:22:40.299547  1863 sgd_solver.cpp:105] Iteration 14184, lr = 0.001
I0405 15:22:45.390328  1863 solver.cpp:218] Iteration 14196 (2.3572 iter/s, 5.09078s/12 iters), loss = 0.247716
I0405 15:22:45.390369  1863 solver.cpp:237]     Train net output #0: loss = 0.247716 (* 1 = 0.247716 loss)
I0405 15:22:45.390375  1863 sgd_solver.cpp:105] Iteration 14196, lr = 0.001
I0405 15:22:50.836125  1863 solver.cpp:218] Iteration 14208 (2.20355 iter/s, 5.44575s/12 iters), loss = 0.171661
I0405 15:22:50.836170  1863 solver.cpp:237]     Train net output #0: loss = 0.171661 (* 1 = 0.171661 loss)
I0405 15:22:50.836176  1863 sgd_solver.cpp:105] Iteration 14208, lr = 0.001
I0405 15:22:56.234328  1863 solver.cpp:218] Iteration 14220 (2.22299 iter/s, 5.39815s/12 iters), loss = 0.183531
I0405 15:22:56.234371  1863 solver.cpp:237]     Train net output #0: loss = 0.183531 (* 1 = 0.183531 loss)
I0405 15:22:56.234376  1863 sgd_solver.cpp:105] Iteration 14220, lr = 0.001
I0405 15:23:01.398717  1863 solver.cpp:218] Iteration 14232 (2.32363 iter/s, 5.16434s/12 iters), loss = 0.174938
I0405 15:23:01.398766  1863 solver.cpp:237]     Train net output #0: loss = 0.174938 (* 1 = 0.174938 loss)
I0405 15:23:01.398772  1863 sgd_solver.cpp:105] Iteration 14232, lr = 0.001
I0405 15:23:06.707283  1863 solver.cpp:218] Iteration 14244 (2.26052 iter/s, 5.30851s/12 iters), loss = 0.122006
I0405 15:23:06.707407  1863 solver.cpp:237]     Train net output #0: loss = 0.122006 (* 1 = 0.122006 loss)
I0405 15:23:06.707417  1863 sgd_solver.cpp:105] Iteration 14244, lr = 0.001
I0405 15:23:12.140108  1863 solver.cpp:218] Iteration 14256 (2.20885 iter/s, 5.4327s/12 iters), loss = 0.275325
I0405 15:23:12.140166  1863 solver.cpp:237]     Train net output #0: loss = 0.275325 (* 1 = 0.275325 loss)
I0405 15:23:12.140174  1863 sgd_solver.cpp:105] Iteration 14256, lr = 0.001
I0405 15:23:14.802069  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:23:17.418671  1863 solver.cpp:218] Iteration 14268 (2.27337 iter/s, 5.2785s/12 iters), loss = 0.266344
I0405 15:23:17.418718  1863 solver.cpp:237]     Train net output #0: loss = 0.266344 (* 1 = 0.266344 loss)
I0405 15:23:17.418725  1863 sgd_solver.cpp:105] Iteration 14268, lr = 0.001
I0405 15:23:22.071333  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14280.caffemodel
I0405 15:23:25.164055  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14280.solverstate
I0405 15:23:28.224594  1863 solver.cpp:330] Iteration 14280, Testing net (#0)
I0405 15:23:28.224617  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:23:31.715481  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:23:32.708307  1863 solver.cpp:397]     Test net output #0: accuracy = 0.257966
I0405 15:23:32.708345  1863 solver.cpp:397]     Test net output #1: loss = 4.69896 (* 1 = 4.69896 loss)
I0405 15:23:32.852560  1863 solver.cpp:218] Iteration 14280 (0.777512 iter/s, 15.4339s/12 iters), loss = 0.237791
I0405 15:23:32.852613  1863 solver.cpp:237]     Train net output #0: loss = 0.237791 (* 1 = 0.237791 loss)
I0405 15:23:32.852622  1863 sgd_solver.cpp:105] Iteration 14280, lr = 0.001
I0405 15:23:36.973270  1863 solver.cpp:218] Iteration 14292 (2.91216 iter/s, 4.12065s/12 iters), loss = 0.181484
I0405 15:23:36.973438  1863 solver.cpp:237]     Train net output #0: loss = 0.181484 (* 1 = 0.181484 loss)
I0405 15:23:36.973448  1863 sgd_solver.cpp:105] Iteration 14292, lr = 0.001
I0405 15:23:42.283355  1863 solver.cpp:218] Iteration 14304 (2.25992 iter/s, 5.30991s/12 iters), loss = 0.120994
I0405 15:23:42.283411  1863 solver.cpp:237]     Train net output #0: loss = 0.120993 (* 1 = 0.120993 loss)
I0405 15:23:42.283421  1863 sgd_solver.cpp:105] Iteration 14304, lr = 0.001
I0405 15:23:47.644904  1863 solver.cpp:218] Iteration 14316 (2.23819 iter/s, 5.36148s/12 iters), loss = 0.169674
I0405 15:23:47.644954  1863 solver.cpp:237]     Train net output #0: loss = 0.169674 (* 1 = 0.169674 loss)
I0405 15:23:47.644963  1863 sgd_solver.cpp:105] Iteration 14316, lr = 0.001
I0405 15:23:53.032183  1863 solver.cpp:218] Iteration 14328 (2.22749 iter/s, 5.38722s/12 iters), loss = 0.109044
I0405 15:23:53.032232  1863 solver.cpp:237]     Train net output #0: loss = 0.109044 (* 1 = 0.109044 loss)
I0405 15:23:53.032240  1863 sgd_solver.cpp:105] Iteration 14328, lr = 0.001
I0405 15:23:58.560761  1863 solver.cpp:218] Iteration 14340 (2.17056 iter/s, 5.52852s/12 iters), loss = 0.126736
I0405 15:23:58.560818  1863 solver.cpp:237]     Train net output #0: loss = 0.126736 (* 1 = 0.126736 loss)
I0405 15:23:58.560828  1863 sgd_solver.cpp:105] Iteration 14340, lr = 0.001
I0405 15:24:03.718873  1863 solver.cpp:218] Iteration 14352 (2.32646 iter/s, 5.15805s/12 iters), loss = 0.19762
I0405 15:24:03.718922  1863 solver.cpp:237]     Train net output #0: loss = 0.19762 (* 1 = 0.19762 loss)
I0405 15:24:03.718930  1863 sgd_solver.cpp:105] Iteration 14352, lr = 0.001
I0405 15:24:08.539453  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:24:08.925885  1863 solver.cpp:218] Iteration 14364 (2.30461 iter/s, 5.20696s/12 iters), loss = 0.11868
I0405 15:24:08.925926  1863 solver.cpp:237]     Train net output #0: loss = 0.11868 (* 1 = 0.11868 loss)
I0405 15:24:08.925932  1863 sgd_solver.cpp:105] Iteration 14364, lr = 0.001
I0405 15:24:14.263296  1863 solver.cpp:218] Iteration 14376 (2.2483 iter/s, 5.33737s/12 iters), loss = 0.21786
I0405 15:24:14.263339  1863 solver.cpp:237]     Train net output #0: loss = 0.21786 (* 1 = 0.21786 loss)
I0405 15:24:14.263345  1863 sgd_solver.cpp:105] Iteration 14376, lr = 0.001
I0405 15:24:16.262192  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14382.caffemodel
I0405 15:24:19.288201  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14382.solverstate
I0405 15:24:21.635370  1863 solver.cpp:330] Iteration 14382, Testing net (#0)
I0405 15:24:21.635391  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:24:25.079604  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:24:26.101212  1863 solver.cpp:397]     Test net output #0: accuracy = 0.272059
I0405 15:24:26.101248  1863 solver.cpp:397]     Test net output #1: loss = 4.65864 (* 1 = 4.65864 loss)
I0405 15:24:27.907637  1863 solver.cpp:218] Iteration 14388 (0.879488 iter/s, 13.6443s/12 iters), loss = 0.0549104
I0405 15:24:27.907680  1863 solver.cpp:237]     Train net output #0: loss = 0.0549103 (* 1 = 0.0549103 loss)
I0405 15:24:27.907686  1863 sgd_solver.cpp:105] Iteration 14388, lr = 0.001
I0405 15:24:33.144063  1863 solver.cpp:218] Iteration 14400 (2.29166 iter/s, 5.23637s/12 iters), loss = 0.0753906
I0405 15:24:33.144124  1863 solver.cpp:237]     Train net output #0: loss = 0.0753905 (* 1 = 0.0753905 loss)
I0405 15:24:33.144134  1863 sgd_solver.cpp:105] Iteration 14400, lr = 0.001
I0405 15:24:38.514083  1863 solver.cpp:218] Iteration 14412 (2.23465 iter/s, 5.36996s/12 iters), loss = 0.227815
I0405 15:24:38.514127  1863 solver.cpp:237]     Train net output #0: loss = 0.227815 (* 1 = 0.227815 loss)
I0405 15:24:38.514132  1863 sgd_solver.cpp:105] Iteration 14412, lr = 0.001
I0405 15:24:43.909250  1863 solver.cpp:218] Iteration 14424 (2.22423 iter/s, 5.39512s/12 iters), loss = 0.142422
I0405 15:24:43.909898  1863 solver.cpp:237]     Train net output #0: loss = 0.142422 (* 1 = 0.142422 loss)
I0405 15:24:43.909905  1863 sgd_solver.cpp:105] Iteration 14424, lr = 0.001
I0405 15:24:48.832726  1863 solver.cpp:218] Iteration 14436 (2.43763 iter/s, 4.92282s/12 iters), loss = 0.28618
I0405 15:24:48.832768  1863 solver.cpp:237]     Train net output #0: loss = 0.28618 (* 1 = 0.28618 loss)
I0405 15:24:48.832774  1863 sgd_solver.cpp:105] Iteration 14436, lr = 0.001
I0405 15:24:54.118119  1863 solver.cpp:218] Iteration 14448 (2.27043 iter/s, 5.28534s/12 iters), loss = 0.111156
I0405 15:24:54.118160  1863 solver.cpp:237]     Train net output #0: loss = 0.111156 (* 1 = 0.111156 loss)
I0405 15:24:54.118166  1863 sgd_solver.cpp:105] Iteration 14448, lr = 0.001
I0405 15:24:59.240011  1863 solver.cpp:218] Iteration 14460 (2.34291 iter/s, 5.12184s/12 iters), loss = 0.123658
I0405 15:24:59.240065  1863 solver.cpp:237]     Train net output #0: loss = 0.123658 (* 1 = 0.123658 loss)
I0405 15:24:59.240073  1863 sgd_solver.cpp:105] Iteration 14460, lr = 0.001
I0405 15:25:01.105432  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:25:04.559127  1863 solver.cpp:218] Iteration 14472 (2.25604 iter/s, 5.31906s/12 iters), loss = 0.228238
I0405 15:25:04.559175  1863 solver.cpp:237]     Train net output #0: loss = 0.228238 (* 1 = 0.228238 loss)
I0405 15:25:04.559181  1863 sgd_solver.cpp:105] Iteration 14472, lr = 0.001
I0405 15:25:09.182343  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14484.caffemodel
I0405 15:25:12.234050  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14484.solverstate
I0405 15:25:14.548908  1863 solver.cpp:330] Iteration 14484, Testing net (#0)
I0405 15:25:14.548975  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:25:17.960160  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:25:19.029212  1863 solver.cpp:397]     Test net output #0: accuracy = 0.277574
I0405 15:25:19.029240  1863 solver.cpp:397]     Test net output #1: loss = 4.70115 (* 1 = 4.70115 loss)
I0405 15:25:19.167196  1863 solver.cpp:218] Iteration 14484 (0.821467 iter/s, 14.608s/12 iters), loss = 0.202309
I0405 15:25:19.167248  1863 solver.cpp:237]     Train net output #0: loss = 0.202309 (* 1 = 0.202309 loss)
I0405 15:25:19.167256  1863 sgd_solver.cpp:105] Iteration 14484, lr = 0.001
I0405 15:25:23.530489  1863 solver.cpp:218] Iteration 14496 (2.75025 iter/s, 4.36323s/12 iters), loss = 0.197247
I0405 15:25:23.530539  1863 solver.cpp:237]     Train net output #0: loss = 0.197246 (* 1 = 0.197246 loss)
I0405 15:25:23.530546  1863 sgd_solver.cpp:105] Iteration 14496, lr = 0.001
I0405 15:25:28.359007  1863 solver.cpp:218] Iteration 14508 (2.48526 iter/s, 4.82846s/12 iters), loss = 0.169699
I0405 15:25:28.359061  1863 solver.cpp:237]     Train net output #0: loss = 0.169699 (* 1 = 0.169699 loss)
I0405 15:25:28.359069  1863 sgd_solver.cpp:105] Iteration 14508, lr = 0.001
I0405 15:25:33.332497  1863 solver.cpp:218] Iteration 14520 (2.41282 iter/s, 4.97343s/12 iters), loss = 0.257599
I0405 15:25:33.332545  1863 solver.cpp:237]     Train net output #0: loss = 0.257599 (* 1 = 0.257599 loss)
I0405 15:25:33.332552  1863 sgd_solver.cpp:105] Iteration 14520, lr = 0.001
I0405 15:25:38.465214  1863 solver.cpp:218] Iteration 14532 (2.33797 iter/s, 5.13267s/12 iters), loss = 0.13549
I0405 15:25:38.465255  1863 solver.cpp:237]     Train net output #0: loss = 0.13549 (* 1 = 0.13549 loss)
I0405 15:25:38.465261  1863 sgd_solver.cpp:105] Iteration 14532, lr = 0.001
I0405 15:25:43.481330  1863 solver.cpp:218] Iteration 14544 (2.39231 iter/s, 5.01607s/12 iters), loss = 0.347948
I0405 15:25:43.481367  1863 solver.cpp:237]     Train net output #0: loss = 0.347948 (* 1 = 0.347948 loss)
I0405 15:25:43.481374  1863 sgd_solver.cpp:105] Iteration 14544, lr = 0.001
I0405 15:25:48.946555  1863 solver.cpp:218] Iteration 14556 (2.19572 iter/s, 5.46518s/12 iters), loss = 0.117695
I0405 15:25:48.946693  1863 solver.cpp:237]     Train net output #0: loss = 0.117695 (* 1 = 0.117695 loss)
I0405 15:25:48.946699  1863 sgd_solver.cpp:105] Iteration 14556, lr = 0.001
I0405 15:25:53.098124  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:25:53.305665  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:25:54.296905  1863 solver.cpp:218] Iteration 14568 (2.24291 iter/s, 5.3502s/12 iters), loss = 0.21269
I0405 15:25:54.296962  1863 solver.cpp:237]     Train net output #0: loss = 0.21269 (* 1 = 0.21269 loss)
I0405 15:25:54.296970  1863 sgd_solver.cpp:105] Iteration 14568, lr = 0.001
I0405 15:25:59.555049  1863 solver.cpp:218] Iteration 14580 (2.2822 iter/s, 5.25808s/12 iters), loss = 0.0471379
I0405 15:25:59.555109  1863 solver.cpp:237]     Train net output #0: loss = 0.0471379 (* 1 = 0.0471379 loss)
I0405 15:25:59.555119  1863 sgd_solver.cpp:105] Iteration 14580, lr = 0.001
I0405 15:26:01.666359  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14586.caffemodel
I0405 15:26:04.695749  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14586.solverstate
I0405 15:26:07.008601  1863 solver.cpp:330] Iteration 14586, Testing net (#0)
I0405 15:26:07.008625  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:26:10.335742  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:26:11.494966  1863 solver.cpp:397]     Test net output #0: accuracy = 0.276961
I0405 15:26:11.495003  1863 solver.cpp:397]     Test net output #1: loss = 4.61421 (* 1 = 4.61421 loss)
I0405 15:26:13.496091  1863 solver.cpp:218] Iteration 14592 (0.860771 iter/s, 13.941s/12 iters), loss = 0.0834045
I0405 15:26:13.496145  1863 solver.cpp:237]     Train net output #0: loss = 0.0834044 (* 1 = 0.0834044 loss)
I0405 15:26:13.496153  1863 sgd_solver.cpp:105] Iteration 14592, lr = 0.001
I0405 15:26:18.799228  1863 solver.cpp:218] Iteration 14604 (2.26284 iter/s, 5.30308s/12 iters), loss = 0.0439823
I0405 15:26:18.799274  1863 solver.cpp:237]     Train net output #0: loss = 0.0439822 (* 1 = 0.0439822 loss)
I0405 15:26:18.799280  1863 sgd_solver.cpp:105] Iteration 14604, lr = 0.001
I0405 15:26:24.183992  1863 solver.cpp:218] Iteration 14616 (2.22853 iter/s, 5.38471s/12 iters), loss = 0.0847289
I0405 15:26:24.184104  1863 solver.cpp:237]     Train net output #0: loss = 0.0847288 (* 1 = 0.0847288 loss)
I0405 15:26:24.184113  1863 sgd_solver.cpp:105] Iteration 14616, lr = 0.001
I0405 15:26:29.371076  1863 solver.cpp:218] Iteration 14628 (2.31349 iter/s, 5.18697s/12 iters), loss = 0.175854
I0405 15:26:29.371116  1863 solver.cpp:237]     Train net output #0: loss = 0.175854 (* 1 = 0.175854 loss)
I0405 15:26:29.371122  1863 sgd_solver.cpp:105] Iteration 14628, lr = 0.001
I0405 15:26:34.710633  1863 solver.cpp:218] Iteration 14640 (2.2474 iter/s, 5.33951s/12 iters), loss = 0.130683
I0405 15:26:34.710675  1863 solver.cpp:237]     Train net output #0: loss = 0.130683 (* 1 = 0.130683 loss)
I0405 15:26:34.710680  1863 sgd_solver.cpp:105] Iteration 14640, lr = 0.001
I0405 15:26:40.182117  1863 solver.cpp:218] Iteration 14652 (2.19321 iter/s, 5.47144s/12 iters), loss = 0.134585
I0405 15:26:40.182157  1863 solver.cpp:237]     Train net output #0: loss = 0.134585 (* 1 = 0.134585 loss)
I0405 15:26:40.182161  1863 sgd_solver.cpp:105] Iteration 14652, lr = 0.001
I0405 15:26:45.735167  1863 solver.cpp:218] Iteration 14664 (2.16099 iter/s, 5.553s/12 iters), loss = 0.142425
I0405 15:26:45.735219  1863 solver.cpp:237]     Train net output #0: loss = 0.142425 (* 1 = 0.142425 loss)
I0405 15:26:45.735227  1863 sgd_solver.cpp:105] Iteration 14664, lr = 0.001
I0405 15:26:46.716250  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:26:50.969128  1863 solver.cpp:218] Iteration 14676 (2.29274 iter/s, 5.23391s/12 iters), loss = 0.0919898
I0405 15:26:50.969167  1863 solver.cpp:237]     Train net output #0: loss = 0.0919897 (* 1 = 0.0919897 loss)
I0405 15:26:50.969173  1863 sgd_solver.cpp:105] Iteration 14676, lr = 0.001
I0405 15:26:55.587406  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14688.caffemodel
I0405 15:26:58.710115  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14688.solverstate
I0405 15:27:01.009325  1863 solver.cpp:330] Iteration 14688, Testing net (#0)
I0405 15:27:01.009346  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:27:04.200780  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:05.333237  1863 solver.cpp:397]     Test net output #0: accuracy = 0.273897
I0405 15:27:05.333271  1863 solver.cpp:397]     Test net output #1: loss = 4.69784 (* 1 = 4.69784 loss)
I0405 15:27:05.474579  1863 solver.cpp:218] Iteration 14688 (0.827277 iter/s, 14.5054s/12 iters), loss = 0.116308
I0405 15:27:05.474628  1863 solver.cpp:237]     Train net output #0: loss = 0.116308 (* 1 = 0.116308 loss)
I0405 15:27:05.474635  1863 sgd_solver.cpp:105] Iteration 14688, lr = 0.001
I0405 15:27:09.712530  1863 solver.cpp:218] Iteration 14700 (2.8316 iter/s, 4.23789s/12 iters), loss = 0.192216
I0405 15:27:09.712586  1863 solver.cpp:237]     Train net output #0: loss = 0.192216 (* 1 = 0.192216 loss)
I0405 15:27:09.712595  1863 sgd_solver.cpp:105] Iteration 14700, lr = 0.001
I0405 15:27:15.072641  1863 solver.cpp:218] Iteration 14712 (2.23879 iter/s, 5.36005s/12 iters), loss = 0.144086
I0405 15:27:15.072682  1863 solver.cpp:237]     Train net output #0: loss = 0.144086 (* 1 = 0.144086 loss)
I0405 15:27:15.072688  1863 sgd_solver.cpp:105] Iteration 14712, lr = 0.001
I0405 15:27:20.368203  1863 solver.cpp:218] Iteration 14724 (2.26607 iter/s, 5.29551s/12 iters), loss = 0.0597816
I0405 15:27:20.368258  1863 solver.cpp:237]     Train net output #0: loss = 0.0597815 (* 1 = 0.0597815 loss)
I0405 15:27:20.368266  1863 sgd_solver.cpp:105] Iteration 14724, lr = 0.001
I0405 15:27:25.742674  1863 solver.cpp:218] Iteration 14736 (2.2328 iter/s, 5.37441s/12 iters), loss = 0.154433
I0405 15:27:25.742777  1863 solver.cpp:237]     Train net output #0: loss = 0.154433 (* 1 = 0.154433 loss)
I0405 15:27:25.742786  1863 sgd_solver.cpp:105] Iteration 14736, lr = 0.001
I0405 15:27:30.957921  1863 solver.cpp:218] Iteration 14748 (2.30099 iter/s, 5.21514s/12 iters), loss = 0.300948
I0405 15:27:30.957979  1863 solver.cpp:237]     Train net output #0: loss = 0.300948 (* 1 = 0.300948 loss)
I0405 15:27:30.957988  1863 sgd_solver.cpp:105] Iteration 14748, lr = 0.001
I0405 15:27:36.248785  1863 solver.cpp:218] Iteration 14760 (2.26809 iter/s, 5.2908s/12 iters), loss = 0.268852
I0405 15:27:36.248847  1863 solver.cpp:237]     Train net output #0: loss = 0.268852 (* 1 = 0.268852 loss)
I0405 15:27:36.248855  1863 sgd_solver.cpp:105] Iteration 14760, lr = 0.001
I0405 15:27:39.447110  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:41.374186  1863 solver.cpp:218] Iteration 14772 (2.34131 iter/s, 5.12533s/12 iters), loss = 0.14777
I0405 15:27:41.374233  1863 solver.cpp:237]     Train net output #0: loss = 0.14777 (* 1 = 0.14777 loss)
I0405 15:27:41.374240  1863 sgd_solver.cpp:105] Iteration 14772, lr = 0.001
I0405 15:27:46.452149  1863 solver.cpp:218] Iteration 14784 (2.36318 iter/s, 5.0779s/12 iters), loss = 0.102008
I0405 15:27:46.452203  1863 solver.cpp:237]     Train net output #0: loss = 0.102008 (* 1 = 0.102008 loss)
I0405 15:27:46.452212  1863 sgd_solver.cpp:105] Iteration 14784, lr = 0.001
I0405 15:27:48.506992  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14790.caffemodel
I0405 15:27:51.580739  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14790.solverstate
I0405 15:27:53.951561  1863 solver.cpp:330] Iteration 14790, Testing net (#0)
I0405 15:27:53.951589  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:27:57.216650  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:27:58.398878  1863 solver.cpp:397]     Test net output #0: accuracy = 0.264093
I0405 15:27:58.398913  1863 solver.cpp:397]     Test net output #1: loss = 4.77503 (* 1 = 4.77503 loss)
I0405 15:28:00.425494  1863 solver.cpp:218] Iteration 14796 (0.858781 iter/s, 13.9733s/12 iters), loss = 0.191198
I0405 15:28:00.425549  1863 solver.cpp:237]     Train net output #0: loss = 0.191198 (* 1 = 0.191198 loss)
I0405 15:28:00.425557  1863 sgd_solver.cpp:105] Iteration 14796, lr = 0.001
I0405 15:28:05.623595  1863 solver.cpp:218] Iteration 14808 (2.30856 iter/s, 5.19804s/12 iters), loss = 0.195541
I0405 15:28:05.623644  1863 solver.cpp:237]     Train net output #0: loss = 0.195541 (* 1 = 0.195541 loss)
I0405 15:28:05.623651  1863 sgd_solver.cpp:105] Iteration 14808, lr = 0.001
I0405 15:28:11.034868  1863 solver.cpp:218] Iteration 14820 (2.21762 iter/s, 5.41122s/12 iters), loss = 0.191585
I0405 15:28:11.034911  1863 solver.cpp:237]     Train net output #0: loss = 0.191585 (* 1 = 0.191585 loss)
I0405 15:28:11.034917  1863 sgd_solver.cpp:105] Iteration 14820, lr = 0.001
I0405 15:28:16.275200  1863 solver.cpp:218] Iteration 14832 (2.28995 iter/s, 5.24028s/12 iters), loss = 0.111182
I0405 15:28:16.275254  1863 solver.cpp:237]     Train net output #0: loss = 0.111182 (* 1 = 0.111182 loss)
I0405 15:28:16.275261  1863 sgd_solver.cpp:105] Iteration 14832, lr = 0.001
I0405 15:28:21.432379  1863 solver.cpp:218] Iteration 14844 (2.32688 iter/s, 5.15713s/12 iters), loss = 0.298845
I0405 15:28:21.432418  1863 solver.cpp:237]     Train net output #0: loss = 0.298845 (* 1 = 0.298845 loss)
I0405 15:28:21.432423  1863 sgd_solver.cpp:105] Iteration 14844, lr = 0.001
I0405 15:28:26.487607  1863 solver.cpp:218] Iteration 14856 (2.3738 iter/s, 5.05518s/12 iters), loss = 0.133692
I0405 15:28:26.487649  1863 solver.cpp:237]     Train net output #0: loss = 0.133692 (* 1 = 0.133692 loss)
I0405 15:28:26.487654  1863 sgd_solver.cpp:105] Iteration 14856, lr = 0.001
I0405 15:28:31.704704  1863 solver.cpp:218] Iteration 14868 (2.30015 iter/s, 5.21705s/12 iters), loss = 0.115553
I0405 15:28:31.704799  1863 solver.cpp:237]     Train net output #0: loss = 0.115553 (* 1 = 0.115553 loss)
I0405 15:28:31.704807  1863 sgd_solver.cpp:105] Iteration 14868, lr = 0.001
I0405 15:28:31.975005  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:28:36.773011  1863 solver.cpp:218] Iteration 14880 (2.36771 iter/s, 5.0682s/12 iters), loss = 0.150735
I0405 15:28:36.773072  1863 solver.cpp:237]     Train net output #0: loss = 0.150735 (* 1 = 0.150735 loss)
I0405 15:28:36.773078  1863 sgd_solver.cpp:105] Iteration 14880, lr = 0.001
I0405 15:28:41.651660  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14892.caffemodel
I0405 15:28:44.736727  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14892.solverstate
I0405 15:28:47.045603  1863 solver.cpp:330] Iteration 14892, Testing net (#0)
I0405 15:28:47.045624  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:28:50.250130  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:28:51.467886  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275123
I0405 15:28:51.467918  1863 solver.cpp:397]     Test net output #1: loss = 4.66864 (* 1 = 4.66864 loss)
I0405 15:28:51.605782  1863 solver.cpp:218] Iteration 14892 (0.809022 iter/s, 14.8327s/12 iters), loss = 0.0691623
I0405 15:28:51.607381  1863 solver.cpp:237]     Train net output #0: loss = 0.0691622 (* 1 = 0.0691622 loss)
I0405 15:28:51.607393  1863 sgd_solver.cpp:105] Iteration 14892, lr = 0.001
I0405 15:28:55.920665  1863 solver.cpp:218] Iteration 14904 (2.78211 iter/s, 4.31328s/12 iters), loss = 0.1491
I0405 15:28:55.920724  1863 solver.cpp:237]     Train net output #0: loss = 0.1491 (* 1 = 0.1491 loss)
I0405 15:28:55.920733  1863 sgd_solver.cpp:105] Iteration 14904, lr = 0.001
I0405 15:29:01.128844  1863 solver.cpp:218] Iteration 14916 (2.3041 iter/s, 5.20812s/12 iters), loss = 0.175798
I0405 15:29:01.128899  1863 solver.cpp:237]     Train net output #0: loss = 0.175798 (* 1 = 0.175798 loss)
I0405 15:29:01.128906  1863 sgd_solver.cpp:105] Iteration 14916, lr = 0.001
I0405 15:29:06.472029  1863 solver.cpp:218] Iteration 14928 (2.24588 iter/s, 5.34312s/12 iters), loss = 0.192505
I0405 15:29:06.472158  1863 solver.cpp:237]     Train net output #0: loss = 0.192505 (* 1 = 0.192505 loss)
I0405 15:29:06.472167  1863 sgd_solver.cpp:105] Iteration 14928, lr = 0.001
I0405 15:29:11.775441  1863 solver.cpp:218] Iteration 14940 (2.26275 iter/s, 5.30328s/12 iters), loss = 0.126012
I0405 15:29:11.775486  1863 solver.cpp:237]     Train net output #0: loss = 0.126012 (* 1 = 0.126012 loss)
I0405 15:29:11.775492  1863 sgd_solver.cpp:105] Iteration 14940, lr = 0.001
I0405 15:29:17.178001  1863 solver.cpp:218] Iteration 14952 (2.22119 iter/s, 5.40251s/12 iters), loss = 0.0726154
I0405 15:29:17.178041  1863 solver.cpp:237]     Train net output #0: loss = 0.0726153 (* 1 = 0.0726153 loss)
I0405 15:29:17.178047  1863 sgd_solver.cpp:105] Iteration 14952, lr = 0.001
I0405 15:29:22.398671  1863 solver.cpp:218] Iteration 14964 (2.29858 iter/s, 5.22062s/12 iters), loss = 0.176899
I0405 15:29:22.398718  1863 solver.cpp:237]     Train net output #0: loss = 0.176898 (* 1 = 0.176898 loss)
I0405 15:29:22.398726  1863 sgd_solver.cpp:105] Iteration 14964, lr = 0.001
I0405 15:29:24.971376  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:29:27.465716  1863 solver.cpp:218] Iteration 14976 (2.36827 iter/s, 5.067s/12 iters), loss = 0.235757
I0405 15:29:27.465757  1863 solver.cpp:237]     Train net output #0: loss = 0.235757 (* 1 = 0.235757 loss)
I0405 15:29:27.465764  1863 sgd_solver.cpp:105] Iteration 14976, lr = 0.001
I0405 15:29:32.817770  1863 solver.cpp:218] Iteration 14988 (2.24215 iter/s, 5.35201s/12 iters), loss = 0.105547
I0405 15:29:32.817816  1863 solver.cpp:237]     Train net output #0: loss = 0.105547 (* 1 = 0.105547 loss)
I0405 15:29:32.817822  1863 sgd_solver.cpp:105] Iteration 14988, lr = 0.001
I0405 15:29:34.905892  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_14994.caffemodel
I0405 15:29:39.137728  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_14994.solverstate
I0405 15:29:41.486330  1863 solver.cpp:330] Iteration 14994, Testing net (#0)
I0405 15:29:41.486351  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:29:44.650074  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:29:45.909335  1863 solver.cpp:397]     Test net output #0: accuracy = 0.269608
I0405 15:29:45.909373  1863 solver.cpp:397]     Test net output #1: loss = 4.68519 (* 1 = 4.68519 loss)
I0405 15:29:47.858379  1863 solver.cpp:218] Iteration 15000 (0.797842 iter/s, 15.0406s/12 iters), loss = 0.128306
I0405 15:29:47.858433  1863 solver.cpp:237]     Train net output #0: loss = 0.128305 (* 1 = 0.128305 loss)
I0405 15:29:47.858440  1863 sgd_solver.cpp:105] Iteration 15000, lr = 0.001
I0405 15:29:53.139811  1863 solver.cpp:218] Iteration 15012 (2.27214 iter/s, 5.28137s/12 iters), loss = 0.110786
I0405 15:29:53.139856  1863 solver.cpp:237]     Train net output #0: loss = 0.110786 (* 1 = 0.110786 loss)
I0405 15:29:53.139863  1863 sgd_solver.cpp:105] Iteration 15012, lr = 0.001
I0405 15:29:58.408309  1863 solver.cpp:218] Iteration 15024 (2.27771 iter/s, 5.26844s/12 iters), loss = 0.140798
I0405 15:29:58.408366  1863 solver.cpp:237]     Train net output #0: loss = 0.140798 (* 1 = 0.140798 loss)
I0405 15:29:58.408375  1863 sgd_solver.cpp:105] Iteration 15024, lr = 0.001
I0405 15:30:03.639521  1863 solver.cpp:218] Iteration 15036 (2.29395 iter/s, 5.23115s/12 iters), loss = 0.149663
I0405 15:30:03.639575  1863 solver.cpp:237]     Train net output #0: loss = 0.149663 (* 1 = 0.149663 loss)
I0405 15:30:03.639582  1863 sgd_solver.cpp:105] Iteration 15036, lr = 0.001
I0405 15:30:09.001621  1863 solver.cpp:218] Iteration 15048 (2.23795 iter/s, 5.36204s/12 iters), loss = 0.15698
I0405 15:30:09.001675  1863 solver.cpp:237]     Train net output #0: loss = 0.15698 (* 1 = 0.15698 loss)
I0405 15:30:09.001685  1863 sgd_solver.cpp:105] Iteration 15048, lr = 0.001
I0405 15:30:14.294307  1863 solver.cpp:218] Iteration 15060 (2.2673 iter/s, 5.29263s/12 iters), loss = 0.228434
I0405 15:30:14.294426  1863 solver.cpp:237]     Train net output #0: loss = 0.228434 (* 1 = 0.228434 loss)
I0405 15:30:14.294433  1863 sgd_solver.cpp:105] Iteration 15060, lr = 0.001
I0405 15:30:19.201314  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:30:19.557478  1863 solver.cpp:218] Iteration 15072 (2.28005 iter/s, 5.26304s/12 iters), loss = 0.089635
I0405 15:30:19.557538  1863 solver.cpp:237]     Train net output #0: loss = 0.0896349 (* 1 = 0.0896349 loss)
I0405 15:30:19.557546  1863 sgd_solver.cpp:105] Iteration 15072, lr = 0.001
I0405 15:30:24.941624  1863 solver.cpp:218] Iteration 15084 (2.22879 iter/s, 5.38408s/12 iters), loss = 0.142519
I0405 15:30:24.941668  1863 solver.cpp:237]     Train net output #0: loss = 0.142519 (* 1 = 0.142519 loss)
I0405 15:30:24.941673  1863 sgd_solver.cpp:105] Iteration 15084, lr = 0.001
I0405 15:30:29.748134  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15096.caffemodel
I0405 15:30:32.854032  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15096.solverstate
I0405 15:30:35.164227  1863 solver.cpp:330] Iteration 15096, Testing net (#0)
I0405 15:30:35.164247  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:30:38.196395  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:30:39.496467  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270221
I0405 15:30:39.496502  1863 solver.cpp:397]     Test net output #1: loss = 4.72549 (* 1 = 4.72549 loss)
I0405 15:30:39.636432  1863 solver.cpp:218] Iteration 15096 (0.816617 iter/s, 14.6948s/12 iters), loss = 0.117198
I0405 15:30:39.636497  1863 solver.cpp:237]     Train net output #0: loss = 0.117198 (* 1 = 0.117198 loss)
I0405 15:30:39.636507  1863 sgd_solver.cpp:105] Iteration 15096, lr = 0.001
I0405 15:30:43.994235  1863 solver.cpp:218] Iteration 15108 (2.75373 iter/s, 4.35773s/12 iters), loss = 0.0507225
I0405 15:30:43.994287  1863 solver.cpp:237]     Train net output #0: loss = 0.0507223 (* 1 = 0.0507223 loss)
I0405 15:30:43.994293  1863 sgd_solver.cpp:105] Iteration 15108, lr = 0.001
I0405 15:30:49.124940  1863 solver.cpp:218] Iteration 15120 (2.33889 iter/s, 5.13065s/12 iters), loss = 0.164678
I0405 15:30:49.125064  1863 solver.cpp:237]     Train net output #0: loss = 0.164677 (* 1 = 0.164677 loss)
I0405 15:30:49.125073  1863 sgd_solver.cpp:105] Iteration 15120, lr = 0.001
I0405 15:30:54.265311  1863 solver.cpp:218] Iteration 15132 (2.33452 iter/s, 5.14024s/12 iters), loss = 0.0880838
I0405 15:30:54.265363  1863 solver.cpp:237]     Train net output #0: loss = 0.0880837 (* 1 = 0.0880837 loss)
I0405 15:30:54.265372  1863 sgd_solver.cpp:105] Iteration 15132, lr = 0.001
I0405 15:30:59.384089  1863 solver.cpp:218] Iteration 15144 (2.34434 iter/s, 5.11872s/12 iters), loss = 0.214336
I0405 15:30:59.384142  1863 solver.cpp:237]     Train net output #0: loss = 0.214335 (* 1 = 0.214335 loss)
I0405 15:30:59.384151  1863 sgd_solver.cpp:105] Iteration 15144, lr = 0.001
I0405 15:31:04.592262  1863 solver.cpp:218] Iteration 15156 (2.3041 iter/s, 5.20811s/12 iters), loss = 0.27204
I0405 15:31:04.592311  1863 solver.cpp:237]     Train net output #0: loss = 0.27204 (* 1 = 0.27204 loss)
I0405 15:31:04.592317  1863 sgd_solver.cpp:105] Iteration 15156, lr = 0.001
I0405 15:31:09.698191  1863 solver.cpp:218] Iteration 15168 (2.35024 iter/s, 5.10587s/12 iters), loss = 0.0807936
I0405 15:31:09.698240  1863 solver.cpp:237]     Train net output #0: loss = 0.0807935 (* 1 = 0.0807935 loss)
I0405 15:31:09.698248  1863 sgd_solver.cpp:105] Iteration 15168, lr = 0.001
I0405 15:31:11.507369  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:31:14.939723  1863 solver.cpp:218] Iteration 15180 (2.28943 iter/s, 5.24148s/12 iters), loss = 0.0849071
I0405 15:31:14.939765  1863 solver.cpp:237]     Train net output #0: loss = 0.084907 (* 1 = 0.084907 loss)
I0405 15:31:14.939771  1863 sgd_solver.cpp:105] Iteration 15180, lr = 0.001
I0405 15:31:20.380146  1863 solver.cpp:218] Iteration 15192 (2.20573 iter/s, 5.44037s/12 iters), loss = 0.0825617
I0405 15:31:20.380314  1863 solver.cpp:237]     Train net output #0: loss = 0.0825616 (* 1 = 0.0825616 loss)
I0405 15:31:20.380323  1863 sgd_solver.cpp:105] Iteration 15192, lr = 0.001
I0405 15:31:22.459050  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15198.caffemodel
I0405 15:31:25.461851  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15198.solverstate
I0405 15:31:27.779834  1863 solver.cpp:330] Iteration 15198, Testing net (#0)
I0405 15:31:27.779855  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:31:30.911370  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:31:32.320298  1863 solver.cpp:397]     Test net output #0: accuracy = 0.265319
I0405 15:31:32.320333  1863 solver.cpp:397]     Test net output #1: loss = 4.66603 (* 1 = 4.66603 loss)
I0405 15:31:34.210227  1863 solver.cpp:218] Iteration 15204 (0.867684 iter/s, 13.8299s/12 iters), loss = 0.239419
I0405 15:31:34.210270  1863 solver.cpp:237]     Train net output #0: loss = 0.239419 (* 1 = 0.239419 loss)
I0405 15:31:34.210275  1863 sgd_solver.cpp:105] Iteration 15204, lr = 0.001
I0405 15:31:39.680073  1863 solver.cpp:218] Iteration 15216 (2.19387 iter/s, 5.46979s/12 iters), loss = 0.123493
I0405 15:31:39.680128  1863 solver.cpp:237]     Train net output #0: loss = 0.123493 (* 1 = 0.123493 loss)
I0405 15:31:39.680137  1863 sgd_solver.cpp:105] Iteration 15216, lr = 0.001
I0405 15:31:44.901665  1863 solver.cpp:218] Iteration 15228 (2.29818 iter/s, 5.22153s/12 iters), loss = 0.248885
I0405 15:31:44.901710  1863 solver.cpp:237]     Train net output #0: loss = 0.248885 (* 1 = 0.248885 loss)
I0405 15:31:44.901715  1863 sgd_solver.cpp:105] Iteration 15228, lr = 0.001
I0405 15:31:50.137321  1863 solver.cpp:218] Iteration 15240 (2.292 iter/s, 5.23559s/12 iters), loss = 0.0928837
I0405 15:31:50.137382  1863 solver.cpp:237]     Train net output #0: loss = 0.0928836 (* 1 = 0.0928836 loss)
I0405 15:31:50.137389  1863 sgd_solver.cpp:105] Iteration 15240, lr = 0.001
I0405 15:31:55.054893  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:31:55.592676  1863 solver.cpp:218] Iteration 15252 (2.1997 iter/s, 5.45529s/12 iters), loss = 0.0600548
I0405 15:31:55.592726  1863 solver.cpp:237]     Train net output #0: loss = 0.0600547 (* 1 = 0.0600547 loss)
I0405 15:31:55.592733  1863 sgd_solver.cpp:105] Iteration 15252, lr = 0.001
I0405 15:32:00.814815  1863 solver.cpp:218] Iteration 15264 (2.29794 iter/s, 5.22208s/12 iters), loss = 0.10751
I0405 15:32:00.814862  1863 solver.cpp:237]     Train net output #0: loss = 0.10751 (* 1 = 0.10751 loss)
I0405 15:32:00.814868  1863 sgd_solver.cpp:105] Iteration 15264, lr = 0.001
I0405 15:32:05.039606  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:32:06.203193  1863 solver.cpp:218] Iteration 15276 (2.22704 iter/s, 5.38832s/12 iters), loss = 0.202081
I0405 15:32:06.203241  1863 solver.cpp:237]     Train net output #0: loss = 0.202081 (* 1 = 0.202081 loss)
I0405 15:32:06.203249  1863 sgd_solver.cpp:105] Iteration 15276, lr = 0.001
I0405 15:32:11.318289  1863 solver.cpp:218] Iteration 15288 (2.34602 iter/s, 5.11504s/12 iters), loss = 0.13744
I0405 15:32:11.318327  1863 solver.cpp:237]     Train net output #0: loss = 0.13744 (* 1 = 0.13744 loss)
I0405 15:32:11.318333  1863 sgd_solver.cpp:105] Iteration 15288, lr = 0.001
I0405 15:32:16.025110  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15300.caffemodel
I0405 15:32:19.079118  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15300.solverstate
I0405 15:32:21.507771  1863 solver.cpp:330] Iteration 15300, Testing net (#0)
I0405 15:32:21.507797  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:32:24.518148  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:32:25.943804  1863 solver.cpp:397]     Test net output #0: accuracy = 0.261642
I0405 15:32:25.943939  1863 solver.cpp:397]     Test net output #1: loss = 4.82957 (* 1 = 4.82957 loss)
I0405 15:32:26.078449  1863 solver.cpp:218] Iteration 15300 (0.813001 iter/s, 14.7601s/12 iters), loss = 0.18385
I0405 15:32:26.078493  1863 solver.cpp:237]     Train net output #0: loss = 0.18385 (* 1 = 0.18385 loss)
I0405 15:32:26.078498  1863 sgd_solver.cpp:105] Iteration 15300, lr = 0.001
I0405 15:32:30.333133  1863 solver.cpp:218] Iteration 15312 (2.82046 iter/s, 4.25463s/12 iters), loss = 0.101325
I0405 15:32:30.333174  1863 solver.cpp:237]     Train net output #0: loss = 0.101325 (* 1 = 0.101325 loss)
I0405 15:32:30.333180  1863 sgd_solver.cpp:105] Iteration 15312, lr = 0.001
I0405 15:32:35.589102  1863 solver.cpp:218] Iteration 15324 (2.28314 iter/s, 5.25592s/12 iters), loss = 0.154482
I0405 15:32:35.589146  1863 solver.cpp:237]     Train net output #0: loss = 0.154481 (* 1 = 0.154481 loss)
I0405 15:32:35.589152  1863 sgd_solver.cpp:105] Iteration 15324, lr = 0.001
I0405 15:32:40.913442  1863 solver.cpp:218] Iteration 15336 (2.25382 iter/s, 5.32428s/12 iters), loss = 0.155531
I0405 15:32:40.913498  1863 solver.cpp:237]     Train net output #0: loss = 0.155531 (* 1 = 0.155531 loss)
I0405 15:32:40.913506  1863 sgd_solver.cpp:105] Iteration 15336, lr = 0.001
I0405 15:32:46.248383  1863 solver.cpp:218] Iteration 15348 (2.24935 iter/s, 5.33488s/12 iters), loss = 0.0438081
I0405 15:32:46.248430  1863 solver.cpp:237]     Train net output #0: loss = 0.043808 (* 1 = 0.043808 loss)
I0405 15:32:46.248436  1863 sgd_solver.cpp:105] Iteration 15348, lr = 0.001
I0405 15:32:51.728085  1863 solver.cpp:218] Iteration 15360 (2.18992 iter/s, 5.47964s/12 iters), loss = 0.151372
I0405 15:32:51.728145  1863 solver.cpp:237]     Train net output #0: loss = 0.151372 (* 1 = 0.151372 loss)
I0405 15:32:51.728154  1863 sgd_solver.cpp:105] Iteration 15360, lr = 0.001
I0405 15:32:57.128607  1863 solver.cpp:218] Iteration 15372 (2.22203 iter/s, 5.40046s/12 iters), loss = 0.155281
I0405 15:32:57.128721  1863 solver.cpp:237]     Train net output #0: loss = 0.155281 (* 1 = 0.155281 loss)
I0405 15:32:57.128729  1863 sgd_solver.cpp:105] Iteration 15372, lr = 0.001
I0405 15:32:58.319845  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:33:02.643795  1863 solver.cpp:218] Iteration 15384 (2.17586 iter/s, 5.51507s/12 iters), loss = 0.142833
I0405 15:33:02.643837  1863 solver.cpp:237]     Train net output #0: loss = 0.142833 (* 1 = 0.142833 loss)
I0405 15:33:02.643842  1863 sgd_solver.cpp:105] Iteration 15384, lr = 0.001
I0405 15:33:07.932997  1863 solver.cpp:218] Iteration 15396 (2.2688 iter/s, 5.28915s/12 iters), loss = 0.12015
I0405 15:33:07.933063  1863 solver.cpp:237]     Train net output #0: loss = 0.12015 (* 1 = 0.12015 loss)
I0405 15:33:07.933073  1863 sgd_solver.cpp:105] Iteration 15396, lr = 0.001
I0405 15:33:10.084190  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15402.caffemodel
I0405 15:33:13.114210  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15402.solverstate
I0405 15:33:15.436048  1863 solver.cpp:330] Iteration 15402, Testing net (#0)
I0405 15:33:15.436072  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:33:18.365334  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:33:19.789047  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275123
I0405 15:33:19.789085  1863 solver.cpp:397]     Test net output #1: loss = 4.77486 (* 1 = 4.77486 loss)
I0405 15:33:21.556664  1863 solver.cpp:218] Iteration 15408 (0.880824 iter/s, 13.6236s/12 iters), loss = 0.312956
I0405 15:33:21.556707  1863 solver.cpp:237]     Train net output #0: loss = 0.312956 (* 1 = 0.312956 loss)
I0405 15:33:21.556713  1863 sgd_solver.cpp:105] Iteration 15408, lr = 0.001
I0405 15:33:26.652938  1863 solver.cpp:218] Iteration 15420 (2.35469 iter/s, 5.09622s/12 iters), loss = 0.171573
I0405 15:33:26.652985  1863 solver.cpp:237]     Train net output #0: loss = 0.171573 (* 1 = 0.171573 loss)
I0405 15:33:26.652992  1863 sgd_solver.cpp:105] Iteration 15420, lr = 0.001
I0405 15:33:32.136266  1863 solver.cpp:218] Iteration 15432 (2.18848 iter/s, 5.48327s/12 iters), loss = 0.0750628
I0405 15:33:32.136427  1863 solver.cpp:237]     Train net output #0: loss = 0.0750627 (* 1 = 0.0750627 loss)
I0405 15:33:32.136436  1863 sgd_solver.cpp:105] Iteration 15432, lr = 0.001
I0405 15:33:37.266512  1863 solver.cpp:218] Iteration 15444 (2.33914 iter/s, 5.13008s/12 iters), loss = 0.159839
I0405 15:33:37.266559  1863 solver.cpp:237]     Train net output #0: loss = 0.159839 (* 1 = 0.159839 loss)
I0405 15:33:37.266566  1863 sgd_solver.cpp:105] Iteration 15444, lr = 0.001
I0405 15:33:42.450038  1863 solver.cpp:218] Iteration 15456 (2.31505 iter/s, 5.18347s/12 iters), loss = 0.121309
I0405 15:33:42.450083  1863 solver.cpp:237]     Train net output #0: loss = 0.121309 (* 1 = 0.121309 loss)
I0405 15:33:42.450089  1863 sgd_solver.cpp:105] Iteration 15456, lr = 0.001
I0405 15:33:47.526156  1863 solver.cpp:218] Iteration 15468 (2.36404 iter/s, 5.07606s/12 iters), loss = 0.143546
I0405 15:33:47.526211  1863 solver.cpp:237]     Train net output #0: loss = 0.143546 (* 1 = 0.143546 loss)
I0405 15:33:47.526219  1863 sgd_solver.cpp:105] Iteration 15468, lr = 0.001
I0405 15:33:50.639825  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:33:52.702852  1863 solver.cpp:218] Iteration 15480 (2.31811 iter/s, 5.17663s/12 iters), loss = 0.104422
I0405 15:33:52.702899  1863 solver.cpp:237]     Train net output #0: loss = 0.104422 (* 1 = 0.104422 loss)
I0405 15:33:52.702905  1863 sgd_solver.cpp:105] Iteration 15480, lr = 0.001
I0405 15:33:57.845788  1863 solver.cpp:218] Iteration 15492 (2.33332 iter/s, 5.14288s/12 iters), loss = 0.116243
I0405 15:33:57.845839  1863 solver.cpp:237]     Train net output #0: loss = 0.116243 (* 1 = 0.116243 loss)
I0405 15:33:57.845847  1863 sgd_solver.cpp:105] Iteration 15492, lr = 0.001
I0405 15:34:02.454599  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15504.caffemodel
I0405 15:34:05.497166  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15504.solverstate
I0405 15:34:07.804026  1863 solver.cpp:330] Iteration 15504, Testing net (#0)
I0405 15:34:07.804049  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:34:10.647775  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:34:12.144302  1863 solver.cpp:397]     Test net output #0: accuracy = 0.276348
I0405 15:34:12.144340  1863 solver.cpp:397]     Test net output #1: loss = 4.82049 (* 1 = 4.82049 loss)
I0405 15:34:12.280516  1863 solver.cpp:218] Iteration 15504 (0.831331 iter/s, 14.4347s/12 iters), loss = 0.163194
I0405 15:34:12.280563  1863 solver.cpp:237]     Train net output #0: loss = 0.163194 (* 1 = 0.163194 loss)
I0405 15:34:12.280568  1863 sgd_solver.cpp:105] Iteration 15504, lr = 0.001
I0405 15:34:16.687799  1863 solver.cpp:218] Iteration 15516 (2.7228 iter/s, 4.40723s/12 iters), loss = 0.115982
I0405 15:34:16.687844  1863 solver.cpp:237]     Train net output #0: loss = 0.115982 (* 1 = 0.115982 loss)
I0405 15:34:16.687849  1863 sgd_solver.cpp:105] Iteration 15516, lr = 0.001
I0405 15:34:21.967667  1863 solver.cpp:218] Iteration 15528 (2.27281 iter/s, 5.27981s/12 iters), loss = 0.174389
I0405 15:34:21.967723  1863 solver.cpp:237]     Train net output #0: loss = 0.174389 (* 1 = 0.174389 loss)
I0405 15:34:21.967731  1863 sgd_solver.cpp:105] Iteration 15528, lr = 0.001
I0405 15:34:27.295219  1863 solver.cpp:218] Iteration 15540 (2.25247 iter/s, 5.32749s/12 iters), loss = 0.0848396
I0405 15:34:27.295274  1863 solver.cpp:237]     Train net output #0: loss = 0.0848394 (* 1 = 0.0848394 loss)
I0405 15:34:27.295282  1863 sgd_solver.cpp:105] Iteration 15540, lr = 0.001
I0405 15:34:32.375248  1863 solver.cpp:218] Iteration 15552 (2.36222 iter/s, 5.07996s/12 iters), loss = 0.120879
I0405 15:34:32.375319  1863 solver.cpp:237]     Train net output #0: loss = 0.120879 (* 1 = 0.120879 loss)
I0405 15:34:32.375329  1863 sgd_solver.cpp:105] Iteration 15552, lr = 0.001
I0405 15:34:37.798418  1863 solver.cpp:218] Iteration 15564 (2.21276 iter/s, 5.4231s/12 iters), loss = 0.0942423
I0405 15:34:37.798550  1863 solver.cpp:237]     Train net output #0: loss = 0.0942421 (* 1 = 0.0942421 loss)
I0405 15:34:37.798557  1863 sgd_solver.cpp:105] Iteration 15564, lr = 0.001
I0405 15:34:42.834244  1863 solver.cpp:218] Iteration 15576 (2.38299 iter/s, 5.03569s/12 iters), loss = 0.109124
I0405 15:34:42.834298  1863 solver.cpp:237]     Train net output #0: loss = 0.109124 (* 1 = 0.109124 loss)
I0405 15:34:42.834307  1863 sgd_solver.cpp:105] Iteration 15576, lr = 0.001
I0405 15:34:43.309968  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:34:48.267799  1863 solver.cpp:218] Iteration 15588 (2.20852 iter/s, 5.4335s/12 iters), loss = 0.101234
I0405 15:34:48.267836  1863 solver.cpp:237]     Train net output #0: loss = 0.101233 (* 1 = 0.101233 loss)
I0405 15:34:48.267843  1863 sgd_solver.cpp:105] Iteration 15588, lr = 0.001
I0405 15:34:53.610927  1863 solver.cpp:218] Iteration 15600 (2.24589 iter/s, 5.34308s/12 iters), loss = 0.0474364
I0405 15:34:53.610967  1863 solver.cpp:237]     Train net output #0: loss = 0.0474362 (* 1 = 0.0474362 loss)
I0405 15:34:53.610973  1863 sgd_solver.cpp:105] Iteration 15600, lr = 0.001
I0405 15:34:55.565652  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15606.caffemodel
I0405 15:34:58.671329  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15606.solverstate
I0405 15:35:00.980062  1863 solver.cpp:330] Iteration 15606, Testing net (#0)
I0405 15:35:00.980082  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:35:03.952822  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:35:05.441946  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270221
I0405 15:35:05.441979  1863 solver.cpp:397]     Test net output #1: loss = 4.80664 (* 1 = 4.80664 loss)
I0405 15:35:07.297360  1863 solver.cpp:218] Iteration 15612 (0.876783 iter/s, 13.6864s/12 iters), loss = 0.115643
I0405 15:35:07.297403  1863 solver.cpp:237]     Train net output #0: loss = 0.115643 (* 1 = 0.115643 loss)
I0405 15:35:07.297408  1863 sgd_solver.cpp:105] Iteration 15612, lr = 0.001
I0405 15:35:12.464612  1863 solver.cpp:218] Iteration 15624 (2.32234 iter/s, 5.1672s/12 iters), loss = 0.202211
I0405 15:35:12.464711  1863 solver.cpp:237]     Train net output #0: loss = 0.202211 (* 1 = 0.202211 loss)
I0405 15:35:12.464718  1863 sgd_solver.cpp:105] Iteration 15624, lr = 0.001
I0405 15:35:17.846217  1863 solver.cpp:218] Iteration 15636 (2.22986 iter/s, 5.3815s/12 iters), loss = 0.0921815
I0405 15:35:17.846267  1863 solver.cpp:237]     Train net output #0: loss = 0.0921813 (* 1 = 0.0921813 loss)
I0405 15:35:17.846276  1863 sgd_solver.cpp:105] Iteration 15636, lr = 0.001
I0405 15:35:23.223596  1863 solver.cpp:218] Iteration 15648 (2.23159 iter/s, 5.37732s/12 iters), loss = 0.135616
I0405 15:35:23.223798  1863 solver.cpp:237]     Train net output #0: loss = 0.135616 (* 1 = 0.135616 loss)
I0405 15:35:23.223807  1863 sgd_solver.cpp:105] Iteration 15648, lr = 0.001
I0405 15:35:28.400048  1863 solver.cpp:218] Iteration 15660 (2.31828 iter/s, 5.17624s/12 iters), loss = 0.110558
I0405 15:35:28.400094  1863 solver.cpp:237]     Train net output #0: loss = 0.110558 (* 1 = 0.110558 loss)
I0405 15:35:28.400099  1863 sgd_solver.cpp:105] Iteration 15660, lr = 0.001
I0405 15:35:33.757959  1863 solver.cpp:218] Iteration 15672 (2.2397 iter/s, 5.35786s/12 iters), loss = 0.12346
I0405 15:35:33.757999  1863 solver.cpp:237]     Train net output #0: loss = 0.12346 (* 1 = 0.12346 loss)
I0405 15:35:33.758004  1863 sgd_solver.cpp:105] Iteration 15672, lr = 0.001
I0405 15:35:36.649626  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:35:39.229508  1863 solver.cpp:218] Iteration 15684 (2.19319 iter/s, 5.47149s/12 iters), loss = 0.113888
I0405 15:35:39.229557  1863 solver.cpp:237]     Train net output #0: loss = 0.113887 (* 1 = 0.113887 loss)
I0405 15:35:39.229562  1863 sgd_solver.cpp:105] Iteration 15684, lr = 0.001
I0405 15:35:44.661203  1863 solver.cpp:218] Iteration 15696 (2.20928 iter/s, 5.43164s/12 iters), loss = 0.0974701
I0405 15:35:44.661342  1863 solver.cpp:237]     Train net output #0: loss = 0.0974699 (* 1 = 0.0974699 loss)
I0405 15:35:44.661350  1863 sgd_solver.cpp:105] Iteration 15696, lr = 0.001
I0405 15:35:49.410086  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15708.caffemodel
I0405 15:35:52.417423  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15708.solverstate
I0405 15:35:54.750519  1863 solver.cpp:330] Iteration 15708, Testing net (#0)
I0405 15:35:54.750540  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:35:57.622910  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:35:59.153838  1863 solver.cpp:397]     Test net output #0: accuracy = 0.266544
I0405 15:35:59.153878  1863 solver.cpp:397]     Test net output #1: loss = 4.82439 (* 1 = 4.82439 loss)
I0405 15:35:59.301319  1863 solver.cpp:218] Iteration 15708 (0.819673 iter/s, 14.64s/12 iters), loss = 0.0518393
I0405 15:35:59.301373  1863 solver.cpp:237]     Train net output #0: loss = 0.0518391 (* 1 = 0.0518391 loss)
I0405 15:35:59.301379  1863 sgd_solver.cpp:105] Iteration 15708, lr = 0.001
I0405 15:36:03.575820  1863 solver.cpp:218] Iteration 15720 (2.80739 iter/s, 4.27444s/12 iters), loss = 0.187906
I0405 15:36:03.575872  1863 solver.cpp:237]     Train net output #0: loss = 0.187906 (* 1 = 0.187906 loss)
I0405 15:36:03.575881  1863 sgd_solver.cpp:105] Iteration 15720, lr = 0.001
I0405 15:36:08.837401  1863 solver.cpp:218] Iteration 15732 (2.28071 iter/s, 5.26152s/12 iters), loss = 0.213136
I0405 15:36:08.837443  1863 solver.cpp:237]     Train net output #0: loss = 0.213136 (* 1 = 0.213136 loss)
I0405 15:36:08.837450  1863 sgd_solver.cpp:105] Iteration 15732, lr = 0.001
I0405 15:36:14.131938  1863 solver.cpp:218] Iteration 15744 (2.26651 iter/s, 5.29448s/12 iters), loss = 0.132903
I0405 15:36:14.131994  1863 solver.cpp:237]     Train net output #0: loss = 0.132903 (* 1 = 0.132903 loss)
I0405 15:36:14.132004  1863 sgd_solver.cpp:105] Iteration 15744, lr = 0.001
I0405 15:36:19.562749  1863 solver.cpp:218] Iteration 15756 (2.20964 iter/s, 5.43075s/12 iters), loss = 0.105803
I0405 15:36:19.562850  1863 solver.cpp:237]     Train net output #0: loss = 0.105802 (* 1 = 0.105802 loss)
I0405 15:36:19.562857  1863 sgd_solver.cpp:105] Iteration 15756, lr = 0.001
I0405 15:36:24.714552  1863 solver.cpp:218] Iteration 15768 (2.32933 iter/s, 5.15169s/12 iters), loss = 0.108827
I0405 15:36:24.714618  1863 solver.cpp:237]     Train net output #0: loss = 0.108827 (* 1 = 0.108827 loss)
I0405 15:36:24.714627  1863 sgd_solver.cpp:105] Iteration 15768, lr = 0.001
I0405 15:36:29.668269  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:36:29.998100  1863 solver.cpp:218] Iteration 15780 (2.27123 iter/s, 5.28347s/12 iters), loss = 0.159635
I0405 15:36:29.998154  1863 solver.cpp:237]     Train net output #0: loss = 0.159634 (* 1 = 0.159634 loss)
I0405 15:36:29.998162  1863 sgd_solver.cpp:105] Iteration 15780, lr = 0.001
I0405 15:36:35.222188  1863 solver.cpp:218] Iteration 15792 (2.29708 iter/s, 5.22403s/12 iters), loss = 0.0711868
I0405 15:36:35.222245  1863 solver.cpp:237]     Train net output #0: loss = 0.0711866 (* 1 = 0.0711866 loss)
I0405 15:36:35.222254  1863 sgd_solver.cpp:105] Iteration 15792, lr = 0.001
I0405 15:36:40.497501  1863 solver.cpp:218] Iteration 15804 (2.27477 iter/s, 5.27525s/12 iters), loss = 0.0751695
I0405 15:36:40.497546  1863 solver.cpp:237]     Train net output #0: loss = 0.0751694 (* 1 = 0.0751694 loss)
I0405 15:36:40.497551  1863 sgd_solver.cpp:105] Iteration 15804, lr = 0.001
I0405 15:36:42.761086  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15810.caffemodel
I0405 15:36:45.699833  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15810.solverstate
I0405 15:36:48.049486  1863 solver.cpp:330] Iteration 15810, Testing net (#0)
I0405 15:36:48.049513  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:36:50.814808  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:36:52.458922  1863 solver.cpp:397]     Test net output #0: accuracy = 0.265319
I0405 15:36:52.458956  1863 solver.cpp:397]     Test net output #1: loss = 4.76732 (* 1 = 4.76732 loss)
I0405 15:36:54.274416  1863 solver.cpp:218] Iteration 15816 (0.871025 iter/s, 13.7769s/12 iters), loss = 0.142479
I0405 15:36:54.274472  1863 solver.cpp:237]     Train net output #0: loss = 0.142478 (* 1 = 0.142478 loss)
I0405 15:36:54.274482  1863 sgd_solver.cpp:105] Iteration 15816, lr = 0.001
I0405 15:36:59.580930  1863 solver.cpp:218] Iteration 15828 (2.2614 iter/s, 5.30645s/12 iters), loss = 0.175698
I0405 15:36:59.580992  1863 solver.cpp:237]     Train net output #0: loss = 0.175697 (* 1 = 0.175697 loss)
I0405 15:36:59.581002  1863 sgd_solver.cpp:105] Iteration 15828, lr = 0.001
I0405 15:37:04.902825  1863 solver.cpp:218] Iteration 15840 (2.25486 iter/s, 5.32183s/12 iters), loss = 0.0771216
I0405 15:37:04.902866  1863 solver.cpp:237]     Train net output #0: loss = 0.0771215 (* 1 = 0.0771215 loss)
I0405 15:37:04.902871  1863 sgd_solver.cpp:105] Iteration 15840, lr = 0.001
I0405 15:37:10.199831  1863 solver.cpp:218] Iteration 15852 (2.26545 iter/s, 5.29696s/12 iters), loss = 0.109095
I0405 15:37:10.199874  1863 solver.cpp:237]     Train net output #0: loss = 0.109094 (* 1 = 0.109094 loss)
I0405 15:37:10.199880  1863 sgd_solver.cpp:105] Iteration 15852, lr = 0.001
I0405 15:37:15.524639  1863 solver.cpp:218] Iteration 15864 (2.25362 iter/s, 5.32476s/12 iters), loss = 0.0693677
I0405 15:37:15.524682  1863 solver.cpp:237]     Train net output #0: loss = 0.0693675 (* 1 = 0.0693675 loss)
I0405 15:37:15.524686  1863 sgd_solver.cpp:105] Iteration 15864, lr = 0.001
I0405 15:37:21.001644  1863 solver.cpp:218] Iteration 15876 (2.191 iter/s, 5.47695s/12 iters), loss = 0.0826481
I0405 15:37:21.001730  1863 solver.cpp:237]     Train net output #0: loss = 0.0826479 (* 1 = 0.0826479 loss)
I0405 15:37:21.001737  1863 sgd_solver.cpp:105] Iteration 15876, lr = 0.001
I0405 15:37:22.999002  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:37:26.473367  1863 solver.cpp:218] Iteration 15888 (2.19313 iter/s, 5.47163s/12 iters), loss = 0.126849
I0405 15:37:26.473418  1863 solver.cpp:237]     Train net output #0: loss = 0.126849 (* 1 = 0.126849 loss)
I0405 15:37:26.473426  1863 sgd_solver.cpp:105] Iteration 15888, lr = 0.001
I0405 15:37:31.731911  1863 solver.cpp:218] Iteration 15900 (2.28203 iter/s, 5.25848s/12 iters), loss = 0.0887852
I0405 15:37:31.731956  1863 solver.cpp:237]     Train net output #0: loss = 0.0887851 (* 1 = 0.0887851 loss)
I0405 15:37:31.731962  1863 sgd_solver.cpp:105] Iteration 15900, lr = 0.001
I0405 15:37:36.459654  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_15912.caffemodel
I0405 15:37:39.486200  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_15912.solverstate
I0405 15:37:41.798501  1863 solver.cpp:330] Iteration 15912, Testing net (#0)
I0405 15:37:41.798523  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:37:44.582818  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:37:46.233189  1863 solver.cpp:397]     Test net output #0: accuracy = 0.269608
I0405 15:37:46.233223  1863 solver.cpp:397]     Test net output #1: loss = 4.80476 (* 1 = 4.80476 loss)
I0405 15:37:46.371161  1863 solver.cpp:218] Iteration 15912 (0.819717 iter/s, 14.6392s/12 iters), loss = 0.101896
I0405 15:37:46.371225  1863 solver.cpp:237]     Train net output #0: loss = 0.101895 (* 1 = 0.101895 loss)
I0405 15:37:46.371234  1863 sgd_solver.cpp:105] Iteration 15912, lr = 0.001
I0405 15:37:50.790843  1863 solver.cpp:218] Iteration 15924 (2.71518 iter/s, 4.4196s/12 iters), loss = 0.178988
I0405 15:37:50.790900  1863 solver.cpp:237]     Train net output #0: loss = 0.178988 (* 1 = 0.178988 loss)
I0405 15:37:50.790910  1863 sgd_solver.cpp:105] Iteration 15924, lr = 0.001
I0405 15:37:56.035907  1863 solver.cpp:218] Iteration 15936 (2.28789 iter/s, 5.245s/12 iters), loss = 0.180003
I0405 15:37:56.036096  1863 solver.cpp:237]     Train net output #0: loss = 0.180003 (* 1 = 0.180003 loss)
I0405 15:37:56.036103  1863 sgd_solver.cpp:105] Iteration 15936, lr = 0.001
I0405 15:37:56.036288  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:38:01.069705  1863 solver.cpp:218] Iteration 15948 (2.38398 iter/s, 5.0336s/12 iters), loss = 0.0987231
I0405 15:38:01.069746  1863 solver.cpp:237]     Train net output #0: loss = 0.0987229 (* 1 = 0.0987229 loss)
I0405 15:38:01.069752  1863 sgd_solver.cpp:105] Iteration 15948, lr = 0.001
I0405 15:38:06.234969  1863 solver.cpp:218] Iteration 15960 (2.32323 iter/s, 5.16522s/12 iters), loss = 0.0984416
I0405 15:38:06.235008  1863 solver.cpp:237]     Train net output #0: loss = 0.0984415 (* 1 = 0.0984415 loss)
I0405 15:38:06.235014  1863 sgd_solver.cpp:105] Iteration 15960, lr = 0.001
I0405 15:38:11.693593  1863 solver.cpp:218] Iteration 15972 (2.19838 iter/s, 5.45857s/12 iters), loss = 0.130952
I0405 15:38:11.693640  1863 solver.cpp:237]     Train net output #0: loss = 0.130952 (* 1 = 0.130952 loss)
I0405 15:38:11.693645  1863 sgd_solver.cpp:105] Iteration 15972, lr = 0.001
I0405 15:38:15.931730  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:38:17.123263  1863 solver.cpp:218] Iteration 15984 (2.2101 iter/s, 5.42961s/12 iters), loss = 0.0557886
I0405 15:38:17.123307  1863 solver.cpp:237]     Train net output #0: loss = 0.0557884 (* 1 = 0.0557884 loss)
I0405 15:38:17.123313  1863 sgd_solver.cpp:105] Iteration 15984, lr = 0.001
I0405 15:38:22.565196  1863 solver.cpp:218] Iteration 15996 (2.20512 iter/s, 5.44187s/12 iters), loss = 0.175711
I0405 15:38:22.565255  1863 solver.cpp:237]     Train net output #0: loss = 0.175711 (* 1 = 0.175711 loss)
I0405 15:38:22.565264  1863 sgd_solver.cpp:105] Iteration 15996, lr = 0.001
I0405 15:38:27.874157  1863 solver.cpp:218] Iteration 16008 (2.26036 iter/s, 5.30889s/12 iters), loss = 0.13801
I0405 15:38:27.874271  1863 solver.cpp:237]     Train net output #0: loss = 0.13801 (* 1 = 0.13801 loss)
I0405 15:38:27.874279  1863 sgd_solver.cpp:105] Iteration 16008, lr = 0.001
I0405 15:38:30.184612  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16014.caffemodel
I0405 15:38:33.097033  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16014.solverstate
I0405 15:38:35.409307  1863 solver.cpp:330] Iteration 16014, Testing net (#0)
I0405 15:38:35.409330  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:38:38.319442  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:38:40.013847  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26348
I0405 15:38:40.013890  1863 solver.cpp:397]     Test net output #1: loss = 4.75854 (* 1 = 4.75854 loss)
I0405 15:38:41.904815  1863 solver.cpp:218] Iteration 16020 (0.855277 iter/s, 14.0305s/12 iters), loss = 0.133663
I0405 15:38:41.904881  1863 solver.cpp:237]     Train net output #0: loss = 0.133663 (* 1 = 0.133663 loss)
I0405 15:38:41.904898  1863 sgd_solver.cpp:105] Iteration 16020, lr = 0.001
I0405 15:38:47.165957  1863 solver.cpp:218] Iteration 16032 (2.28091 iter/s, 5.26107s/12 iters), loss = 0.268562
I0405 15:38:47.166013  1863 solver.cpp:237]     Train net output #0: loss = 0.268562 (* 1 = 0.268562 loss)
I0405 15:38:47.166020  1863 sgd_solver.cpp:105] Iteration 16032, lr = 0.001
I0405 15:38:52.616282  1863 solver.cpp:218] Iteration 16044 (2.20173 iter/s, 5.45026s/12 iters), loss = 0.138181
I0405 15:38:52.616339  1863 solver.cpp:237]     Train net output #0: loss = 0.138181 (* 1 = 0.138181 loss)
I0405 15:38:52.616349  1863 sgd_solver.cpp:105] Iteration 16044, lr = 0.001
I0405 15:38:58.055181  1863 solver.cpp:218] Iteration 16056 (2.20636 iter/s, 5.43883s/12 iters), loss = 0.237114
I0405 15:38:58.055330  1863 solver.cpp:237]     Train net output #0: loss = 0.237114 (* 1 = 0.237114 loss)
I0405 15:38:58.055338  1863 sgd_solver.cpp:105] Iteration 16056, lr = 0.001
I0405 15:39:03.607945  1863 solver.cpp:218] Iteration 16068 (2.16115 iter/s, 5.55261s/12 iters), loss = 0.0637286
I0405 15:39:03.608000  1863 solver.cpp:237]     Train net output #0: loss = 0.0637284 (* 1 = 0.0637284 loss)
I0405 15:39:03.608007  1863 sgd_solver.cpp:105] Iteration 16068, lr = 0.001
I0405 15:39:09.013167  1863 solver.cpp:218] Iteration 16080 (2.2201 iter/s, 5.40516s/12 iters), loss = 0.0729149
I0405 15:39:09.013224  1863 solver.cpp:237]     Train net output #0: loss = 0.0729147 (* 1 = 0.0729147 loss)
I0405 15:39:09.013233  1863 sgd_solver.cpp:105] Iteration 16080, lr = 0.001
I0405 15:39:10.148169  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:39:14.357674  1863 solver.cpp:218] Iteration 16092 (2.24532 iter/s, 5.34444s/12 iters), loss = 0.173631
I0405 15:39:14.357718  1863 solver.cpp:237]     Train net output #0: loss = 0.173631 (* 1 = 0.173631 loss)
I0405 15:39:14.357724  1863 sgd_solver.cpp:105] Iteration 16092, lr = 0.001
I0405 15:39:19.861007  1863 solver.cpp:218] Iteration 16104 (2.18052 iter/s, 5.50328s/12 iters), loss = 0.0817448
I0405 15:39:19.861054  1863 solver.cpp:237]     Train net output #0: loss = 0.0817446 (* 1 = 0.0817446 loss)
I0405 15:39:19.861059  1863 sgd_solver.cpp:105] Iteration 16104, lr = 0.001
I0405 15:39:24.668723  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16116.caffemodel
I0405 15:39:28.831698  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16116.solverstate
I0405 15:39:31.138576  1863 solver.cpp:330] Iteration 16116, Testing net (#0)
I0405 15:39:31.138595  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:39:33.914726  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:39:35.747681  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26777
I0405 15:39:35.747722  1863 solver.cpp:397]     Test net output #1: loss = 4.77941 (* 1 = 4.77941 loss)
I0405 15:39:35.889662  1863 solver.cpp:218] Iteration 16116 (0.748661 iter/s, 16.0286s/12 iters), loss = 0.0950283
I0405 15:39:35.889717  1863 solver.cpp:237]     Train net output #0: loss = 0.0950281 (* 1 = 0.0950281 loss)
I0405 15:39:35.889724  1863 sgd_solver.cpp:105] Iteration 16116, lr = 0.001
I0405 15:39:40.473659  1863 solver.cpp:218] Iteration 16128 (2.61784 iter/s, 4.58394s/12 iters), loss = 0.120041
I0405 15:39:40.473712  1863 solver.cpp:237]     Train net output #0: loss = 0.120041 (* 1 = 0.120041 loss)
I0405 15:39:40.473721  1863 sgd_solver.cpp:105] Iteration 16128, lr = 0.001
I0405 15:39:45.867141  1863 solver.cpp:218] Iteration 16140 (2.22493 iter/s, 5.39342s/12 iters), loss = 0.16716
I0405 15:39:45.867187  1863 solver.cpp:237]     Train net output #0: loss = 0.16716 (* 1 = 0.16716 loss)
I0405 15:39:45.867192  1863 sgd_solver.cpp:105] Iteration 16140, lr = 0.001
I0405 15:39:51.219101  1863 solver.cpp:218] Iteration 16152 (2.24219 iter/s, 5.35191s/12 iters), loss = 0.0997574
I0405 15:39:51.219161  1863 solver.cpp:237]     Train net output #0: loss = 0.0997572 (* 1 = 0.0997572 loss)
I0405 15:39:51.219170  1863 sgd_solver.cpp:105] Iteration 16152, lr = 0.001
I0405 15:39:56.688334  1863 solver.cpp:218] Iteration 16164 (2.19412 iter/s, 5.46917s/12 iters), loss = 0.223273
I0405 15:39:56.688382  1863 solver.cpp:237]     Train net output #0: loss = 0.223273 (* 1 = 0.223273 loss)
I0405 15:39:56.688410  1863 sgd_solver.cpp:105] Iteration 16164, lr = 0.001
I0405 15:40:02.111001  1863 solver.cpp:218] Iteration 16176 (2.21295 iter/s, 5.42262s/12 iters), loss = 0.189863
I0405 15:40:02.111126  1863 solver.cpp:237]     Train net output #0: loss = 0.189863 (* 1 = 0.189863 loss)
I0405 15:40:02.111132  1863 sgd_solver.cpp:105] Iteration 16176, lr = 0.001
I0405 15:40:05.698500  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:40:07.640480  1863 solver.cpp:218] Iteration 16188 (2.17024 iter/s, 5.52934s/12 iters), loss = 0.0831463
I0405 15:40:07.640537  1863 solver.cpp:237]     Train net output #0: loss = 0.0831461 (* 1 = 0.0831461 loss)
I0405 15:40:07.640545  1863 sgd_solver.cpp:105] Iteration 16188, lr = 0.001
I0405 15:40:13.023804  1863 solver.cpp:218] Iteration 16200 (2.22913 iter/s, 5.38326s/12 iters), loss = 0.127195
I0405 15:40:13.030213  1863 solver.cpp:237]     Train net output #0: loss = 0.127194 (* 1 = 0.127194 loss)
I0405 15:40:13.030233  1863 sgd_solver.cpp:105] Iteration 16200, lr = 0.001
I0405 15:40:18.545608  1863 solver.cpp:218] Iteration 16212 (2.17572 iter/s, 5.51541s/12 iters), loss = 0.0694827
I0405 15:40:18.545650  1863 solver.cpp:237]     Train net output #0: loss = 0.0694825 (* 1 = 0.0694825 loss)
I0405 15:40:18.545655  1863 sgd_solver.cpp:105] Iteration 16212, lr = 0.001
I0405 15:40:20.885921  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16218.caffemodel
I0405 15:40:23.989317  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16218.solverstate
I0405 15:40:26.301919  1863 solver.cpp:330] Iteration 16218, Testing net (#0)
I0405 15:40:26.301945  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:40:29.032608  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:40:30.762053  1863 solver.cpp:397]     Test net output #0: accuracy = 0.280637
I0405 15:40:30.762080  1863 solver.cpp:397]     Test net output #1: loss = 4.89246 (* 1 = 4.89246 loss)
I0405 15:40:32.631953  1863 solver.cpp:218] Iteration 16224 (0.851891 iter/s, 14.0863s/12 iters), loss = 0.119097
I0405 15:40:32.632072  1863 solver.cpp:237]     Train net output #0: loss = 0.119096 (* 1 = 0.119096 loss)
I0405 15:40:32.632081  1863 sgd_solver.cpp:105] Iteration 16224, lr = 0.001
I0405 15:40:38.011129  1863 solver.cpp:218] Iteration 16236 (2.23088 iter/s, 5.37906s/12 iters), loss = 0.130326
I0405 15:40:38.011170  1863 solver.cpp:237]     Train net output #0: loss = 0.130326 (* 1 = 0.130326 loss)
I0405 15:40:38.011175  1863 sgd_solver.cpp:105] Iteration 16236, lr = 0.001
I0405 15:40:43.295334  1863 solver.cpp:218] Iteration 16248 (2.27094 iter/s, 5.28415s/12 iters), loss = 0.0568472
I0405 15:40:43.295383  1863 solver.cpp:237]     Train net output #0: loss = 0.056847 (* 1 = 0.056847 loss)
I0405 15:40:43.295389  1863 sgd_solver.cpp:105] Iteration 16248, lr = 0.001
I0405 15:40:48.718250  1863 solver.cpp:218] Iteration 16260 (2.21286 iter/s, 5.42286s/12 iters), loss = 0.24584
I0405 15:40:48.718307  1863 solver.cpp:237]     Train net output #0: loss = 0.24584 (* 1 = 0.24584 loss)
I0405 15:40:48.718317  1863 sgd_solver.cpp:105] Iteration 16260, lr = 0.001
I0405 15:40:53.992897  1863 solver.cpp:218] Iteration 16272 (2.27506 iter/s, 5.27458s/12 iters), loss = 0.0926003
I0405 15:40:53.992951  1863 solver.cpp:237]     Train net output #0: loss = 0.0926001 (* 1 = 0.0926001 loss)
I0405 15:40:53.992959  1863 sgd_solver.cpp:105] Iteration 16272, lr = 0.001
I0405 15:40:59.453635  1863 solver.cpp:218] Iteration 16284 (2.19753 iter/s, 5.46068s/12 iters), loss = 0.126329
I0405 15:40:59.453676  1863 solver.cpp:237]     Train net output #0: loss = 0.126329 (* 1 = 0.126329 loss)
I0405 15:40:59.453683  1863 sgd_solver.cpp:105] Iteration 16284, lr = 0.001
I0405 15:41:00.035877  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:41:05.056293  1863 solver.cpp:218] Iteration 16296 (2.14186 iter/s, 5.60262s/12 iters), loss = 0.110346
I0405 15:41:05.056403  1863 solver.cpp:237]     Train net output #0: loss = 0.110346 (* 1 = 0.110346 loss)
I0405 15:41:05.056412  1863 sgd_solver.cpp:105] Iteration 16296, lr = 0.001
I0405 15:41:10.063601  1863 solver.cpp:218] Iteration 16308 (2.39655 iter/s, 5.00719s/12 iters), loss = 0.16583
I0405 15:41:10.063655  1863 solver.cpp:237]     Train net output #0: loss = 0.16583 (* 1 = 0.16583 loss)
I0405 15:41:10.063664  1863 sgd_solver.cpp:105] Iteration 16308, lr = 0.001
I0405 15:41:14.737569  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16320.caffemodel
I0405 15:41:17.790026  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16320.solverstate
I0405 15:41:20.096033  1863 solver.cpp:330] Iteration 16320, Testing net (#0)
I0405 15:41:20.096055  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:41:22.701792  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:41:24.563041  1863 solver.cpp:397]     Test net output #0: accuracy = 0.264706
I0405 15:41:24.563078  1863 solver.cpp:397]     Test net output #1: loss = 4.76461 (* 1 = 4.76461 loss)
I0405 15:41:24.700173  1863 solver.cpp:218] Iteration 16320 (0.819867 iter/s, 14.6365s/12 iters), loss = 0.146787
I0405 15:41:24.700232  1863 solver.cpp:237]     Train net output #0: loss = 0.146786 (* 1 = 0.146786 loss)
I0405 15:41:24.700242  1863 sgd_solver.cpp:105] Iteration 16320, lr = 0.001
I0405 15:41:28.990674  1863 solver.cpp:218] Iteration 16332 (2.79692 iter/s, 4.29044s/12 iters), loss = 0.126548
I0405 15:41:28.990732  1863 solver.cpp:237]     Train net output #0: loss = 0.126547 (* 1 = 0.126547 loss)
I0405 15:41:28.990742  1863 sgd_solver.cpp:105] Iteration 16332, lr = 0.001
I0405 15:41:34.035486  1863 solver.cpp:218] Iteration 16344 (2.37871 iter/s, 5.04475s/12 iters), loss = 0.0583436
I0405 15:41:34.035531  1863 solver.cpp:237]     Train net output #0: loss = 0.0583433 (* 1 = 0.0583433 loss)
I0405 15:41:34.035537  1863 sgd_solver.cpp:105] Iteration 16344, lr = 0.001
I0405 15:41:39.679256  1863 solver.cpp:218] Iteration 16356 (2.12626 iter/s, 5.64372s/12 iters), loss = 0.0973306
I0405 15:41:39.679385  1863 solver.cpp:237]     Train net output #0: loss = 0.0973303 (* 1 = 0.0973303 loss)
I0405 15:41:39.679392  1863 sgd_solver.cpp:105] Iteration 16356, lr = 0.001
I0405 15:41:45.122392  1863 solver.cpp:218] Iteration 16368 (2.20467 iter/s, 5.443s/12 iters), loss = 0.185124
I0405 15:41:45.122440  1863 solver.cpp:237]     Train net output #0: loss = 0.185124 (* 1 = 0.185124 loss)
I0405 15:41:45.122447  1863 sgd_solver.cpp:105] Iteration 16368, lr = 0.001
I0405 15:41:50.379431  1863 solver.cpp:218] Iteration 16380 (2.28268 iter/s, 5.25698s/12 iters), loss = 0.131949
I0405 15:41:50.379478  1863 solver.cpp:237]     Train net output #0: loss = 0.131949 (* 1 = 0.131949 loss)
I0405 15:41:50.379487  1863 sgd_solver.cpp:105] Iteration 16380, lr = 0.001
I0405 15:41:53.270707  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:41:55.770376  1863 solver.cpp:218] Iteration 16392 (2.22598 iter/s, 5.39089s/12 iters), loss = 0.137189
I0405 15:41:55.770422  1863 solver.cpp:237]     Train net output #0: loss = 0.137189 (* 1 = 0.137189 loss)
I0405 15:41:55.770428  1863 sgd_solver.cpp:105] Iteration 16392, lr = 0.001
I0405 15:42:01.194753  1863 solver.cpp:218] Iteration 16404 (2.21226 iter/s, 5.42432s/12 iters), loss = 0.0858055
I0405 15:42:01.194795  1863 solver.cpp:237]     Train net output #0: loss = 0.0858053 (* 1 = 0.0858053 loss)
I0405 15:42:01.194800  1863 sgd_solver.cpp:105] Iteration 16404, lr = 0.001
I0405 15:42:06.338147  1863 solver.cpp:218] Iteration 16416 (2.33311 iter/s, 5.14334s/12 iters), loss = 0.120172
I0405 15:42:06.338197  1863 solver.cpp:237]     Train net output #0: loss = 0.120172 (* 1 = 0.120172 loss)
I0405 15:42:06.338208  1863 sgd_solver.cpp:105] Iteration 16416, lr = 0.001
I0405 15:42:08.705121  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16422.caffemodel
I0405 15:42:11.713532  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16422.solverstate
I0405 15:42:14.133369  1863 solver.cpp:330] Iteration 16422, Testing net (#0)
I0405 15:42:14.133394  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:42:16.671218  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:42:18.487758  1863 solver.cpp:397]     Test net output #0: accuracy = 0.257966
I0405 15:42:18.487795  1863 solver.cpp:397]     Test net output #1: loss = 4.76053 (* 1 = 4.76053 loss)
I0405 15:42:20.479060  1863 solver.cpp:218] Iteration 16428 (0.848604 iter/s, 14.1409s/12 iters), loss = 0.135491
I0405 15:42:20.479116  1863 solver.cpp:237]     Train net output #0: loss = 0.135491 (* 1 = 0.135491 loss)
I0405 15:42:20.479125  1863 sgd_solver.cpp:105] Iteration 16428, lr = 0.001
I0405 15:42:25.855736  1863 solver.cpp:218] Iteration 16440 (2.23189 iter/s, 5.37661s/12 iters), loss = 0.103291
I0405 15:42:25.855787  1863 solver.cpp:237]     Train net output #0: loss = 0.103291 (* 1 = 0.103291 loss)
I0405 15:42:25.855794  1863 sgd_solver.cpp:105] Iteration 16440, lr = 0.001
I0405 15:42:31.117929  1863 solver.cpp:218] Iteration 16452 (2.28044 iter/s, 5.26214s/12 iters), loss = 0.178663
I0405 15:42:31.117972  1863 solver.cpp:237]     Train net output #0: loss = 0.178663 (* 1 = 0.178663 loss)
I0405 15:42:31.117978  1863 sgd_solver.cpp:105] Iteration 16452, lr = 0.001
I0405 15:42:36.536391  1863 solver.cpp:218] Iteration 16464 (2.21467 iter/s, 5.41841s/12 iters), loss = 0.117251
I0405 15:42:36.536430  1863 solver.cpp:237]     Train net output #0: loss = 0.117251 (* 1 = 0.117251 loss)
I0405 15:42:36.536437  1863 sgd_solver.cpp:105] Iteration 16464, lr = 0.001
I0405 15:42:41.835637  1863 solver.cpp:218] Iteration 16476 (2.26449 iter/s, 5.2992s/12 iters), loss = 0.0476707
I0405 15:42:41.835788  1863 solver.cpp:237]     Train net output #0: loss = 0.0476705 (* 1 = 0.0476705 loss)
I0405 15:42:41.835798  1863 sgd_solver.cpp:105] Iteration 16476, lr = 0.001
I0405 15:42:46.944487  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:42:47.247604  1863 solver.cpp:218] Iteration 16488 (2.21737 iter/s, 5.41181s/12 iters), loss = 0.088294
I0405 15:42:47.247663  1863 solver.cpp:237]     Train net output #0: loss = 0.0882938 (* 1 = 0.0882938 loss)
I0405 15:42:47.247673  1863 sgd_solver.cpp:105] Iteration 16488, lr = 0.001
I0405 15:42:52.623941  1863 solver.cpp:218] Iteration 16500 (2.23203 iter/s, 5.37627s/12 iters), loss = 0.105543
I0405 15:42:52.623993  1863 solver.cpp:237]     Train net output #0: loss = 0.105543 (* 1 = 0.105543 loss)
I0405 15:42:52.624001  1863 sgd_solver.cpp:105] Iteration 16500, lr = 0.001
I0405 15:42:57.794960  1863 solver.cpp:218] Iteration 16512 (2.32065 iter/s, 5.17096s/12 iters), loss = 0.113081
I0405 15:42:57.795011  1863 solver.cpp:237]     Train net output #0: loss = 0.113081 (* 1 = 0.113081 loss)
I0405 15:42:57.795019  1863 sgd_solver.cpp:105] Iteration 16512, lr = 0.001
I0405 15:43:02.641847  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16524.caffemodel
I0405 15:43:05.696867  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16524.solverstate
I0405 15:43:07.998592  1863 solver.cpp:330] Iteration 16524, Testing net (#0)
I0405 15:43:07.998616  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:43:10.570703  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:43:12.567365  1863 solver.cpp:397]     Test net output #0: accuracy = 0.271446
I0405 15:43:12.567463  1863 solver.cpp:397]     Test net output #1: loss = 4.75258 (* 1 = 4.75258 loss)
I0405 15:43:12.711959  1863 solver.cpp:218] Iteration 16524 (0.804454 iter/s, 14.917s/12 iters), loss = 0.0934284
I0405 15:43:12.712020  1863 solver.cpp:237]     Train net output #0: loss = 0.0934281 (* 1 = 0.0934281 loss)
I0405 15:43:12.712028  1863 sgd_solver.cpp:105] Iteration 16524, lr = 0.001
I0405 15:43:17.098965  1863 solver.cpp:218] Iteration 16536 (2.73539 iter/s, 4.38694s/12 iters), loss = 0.167033
I0405 15:43:17.099016  1863 solver.cpp:237]     Train net output #0: loss = 0.167033 (* 1 = 0.167033 loss)
I0405 15:43:17.099023  1863 sgd_solver.cpp:105] Iteration 16536, lr = 0.001
I0405 15:43:22.539578  1863 solver.cpp:218] Iteration 16548 (2.20566 iter/s, 5.44055s/12 iters), loss = 0.109884
I0405 15:43:22.539623  1863 solver.cpp:237]     Train net output #0: loss = 0.109884 (* 1 = 0.109884 loss)
I0405 15:43:22.539629  1863 sgd_solver.cpp:105] Iteration 16548, lr = 0.001
I0405 15:43:27.924258  1863 solver.cpp:218] Iteration 16560 (2.22857 iter/s, 5.38462s/12 iters), loss = 0.118716
I0405 15:43:27.924314  1863 solver.cpp:237]     Train net output #0: loss = 0.118716 (* 1 = 0.118716 loss)
I0405 15:43:27.924321  1863 sgd_solver.cpp:105] Iteration 16560, lr = 0.001
I0405 15:43:33.416160  1863 solver.cpp:218] Iteration 16572 (2.18506 iter/s, 5.49184s/12 iters), loss = 0.192138
I0405 15:43:33.416198  1863 solver.cpp:237]     Train net output #0: loss = 0.192138 (* 1 = 0.192138 loss)
I0405 15:43:33.416203  1863 sgd_solver.cpp:105] Iteration 16572, lr = 0.001
I0405 15:43:38.775800  1863 solver.cpp:218] Iteration 16584 (2.23898 iter/s, 5.35959s/12 iters), loss = 0.0632221
I0405 15:43:38.775856  1863 solver.cpp:237]     Train net output #0: loss = 0.0632218 (* 1 = 0.0632218 loss)
I0405 15:43:38.775863  1863 sgd_solver.cpp:105] Iteration 16584, lr = 0.001
I0405 15:43:40.819715  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:43:44.261524  1863 solver.cpp:218] Iteration 16596 (2.18752 iter/s, 5.48566s/12 iters), loss = 0.156921
I0405 15:43:44.263386  1863 solver.cpp:237]     Train net output #0: loss = 0.156921 (* 1 = 0.156921 loss)
I0405 15:43:44.263394  1863 sgd_solver.cpp:105] Iteration 16596, lr = 0.001
I0405 15:43:49.647073  1863 solver.cpp:218] Iteration 16608 (2.22896 iter/s, 5.38368s/12 iters), loss = 0.118783
I0405 15:43:49.647121  1863 solver.cpp:237]     Train net output #0: loss = 0.118782 (* 1 = 0.118782 loss)
I0405 15:43:49.647128  1863 sgd_solver.cpp:105] Iteration 16608, lr = 0.001
I0405 15:43:55.058300  1863 solver.cpp:218] Iteration 16620 (2.21763 iter/s, 5.41117s/12 iters), loss = 0.124541
I0405 15:43:55.058342  1863 solver.cpp:237]     Train net output #0: loss = 0.124541 (* 1 = 0.124541 loss)
I0405 15:43:55.058348  1863 sgd_solver.cpp:105] Iteration 16620, lr = 0.001
I0405 15:43:57.256783  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16626.caffemodel
I0405 15:44:00.304226  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16626.solverstate
I0405 15:44:02.674944  1863 solver.cpp:330] Iteration 16626, Testing net (#0)
I0405 15:44:02.674964  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:44:05.230659  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:44:06.576759  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:44:07.199218  1863 solver.cpp:397]     Test net output #0: accuracy = 0.260417
I0405 15:44:07.199254  1863 solver.cpp:397]     Test net output #1: loss = 4.77734 (* 1 = 4.77734 loss)
I0405 15:44:09.271461  1863 solver.cpp:218] Iteration 16632 (0.84429 iter/s, 14.2131s/12 iters), loss = 0.0873452
I0405 15:44:09.271517  1863 solver.cpp:237]     Train net output #0: loss = 0.087345 (* 1 = 0.087345 loss)
I0405 15:44:09.271525  1863 sgd_solver.cpp:105] Iteration 16632, lr = 0.001
I0405 15:44:14.514304  1863 solver.cpp:218] Iteration 16644 (2.28886 iter/s, 5.24278s/12 iters), loss = 0.0852154
I0405 15:44:14.514421  1863 solver.cpp:237]     Train net output #0: loss = 0.0852152 (* 1 = 0.0852152 loss)
I0405 15:44:14.514430  1863 sgd_solver.cpp:105] Iteration 16644, lr = 0.001
I0405 15:44:19.965219  1863 solver.cpp:218] Iteration 16656 (2.20152 iter/s, 5.45078s/12 iters), loss = 0.145204
I0405 15:44:19.965283  1863 solver.cpp:237]     Train net output #0: loss = 0.145204 (* 1 = 0.145204 loss)
I0405 15:44:19.965291  1863 sgd_solver.cpp:105] Iteration 16656, lr = 0.001
I0405 15:44:25.612749  1863 solver.cpp:218] Iteration 16668 (2.12485 iter/s, 5.64746s/12 iters), loss = 0.127353
I0405 15:44:25.612787  1863 solver.cpp:237]     Train net output #0: loss = 0.127353 (* 1 = 0.127353 loss)
I0405 15:44:25.612792  1863 sgd_solver.cpp:105] Iteration 16668, lr = 0.001
I0405 15:44:31.210301  1863 solver.cpp:218] Iteration 16680 (2.14381 iter/s, 5.5975s/12 iters), loss = 0.0907934
I0405 15:44:31.210363  1863 solver.cpp:237]     Train net output #0: loss = 0.0907931 (* 1 = 0.0907931 loss)
I0405 15:44:31.210372  1863 sgd_solver.cpp:105] Iteration 16680, lr = 0.001
I0405 15:44:35.630512  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:44:36.886193  1863 solver.cpp:218] Iteration 16692 (2.11423 iter/s, 5.67583s/12 iters), loss = 0.151217
I0405 15:44:36.886232  1863 solver.cpp:237]     Train net output #0: loss = 0.151217 (* 1 = 0.151217 loss)
I0405 15:44:36.886238  1863 sgd_solver.cpp:105] Iteration 16692, lr = 0.001
I0405 15:44:42.418032  1863 solver.cpp:218] Iteration 16704 (2.16928 iter/s, 5.53179s/12 iters), loss = 0.0853462
I0405 15:44:42.418073  1863 solver.cpp:237]     Train net output #0: loss = 0.0853459 (* 1 = 0.0853459 loss)
I0405 15:44:42.418078  1863 sgd_solver.cpp:105] Iteration 16704, lr = 0.001
I0405 15:44:47.876505  1863 solver.cpp:218] Iteration 16716 (2.19844 iter/s, 5.45842s/12 iters), loss = 0.113181
I0405 15:44:47.876695  1863 solver.cpp:237]     Train net output #0: loss = 0.113181 (* 1 = 0.113181 loss)
I0405 15:44:47.876706  1863 sgd_solver.cpp:105] Iteration 16716, lr = 0.001
I0405 15:44:52.725222  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16728.caffemodel
I0405 15:44:55.799522  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16728.solverstate
I0405 15:44:58.147581  1863 solver.cpp:330] Iteration 16728, Testing net (#0)
I0405 15:44:58.147605  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:45:00.693293  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:45:02.612496  1863 solver.cpp:397]     Test net output #0: accuracy = 0.268995
I0405 15:45:02.612530  1863 solver.cpp:397]     Test net output #1: loss = 4.73276 (* 1 = 4.73276 loss)
I0405 15:45:02.752230  1863 solver.cpp:218] Iteration 16728 (0.806693 iter/s, 14.8756s/12 iters), loss = 0.090705
I0405 15:45:02.752274  1863 solver.cpp:237]     Train net output #0: loss = 0.0907048 (* 1 = 0.0907048 loss)
I0405 15:45:02.752279  1863 sgd_solver.cpp:105] Iteration 16728, lr = 0.001
I0405 15:45:06.909463  1863 solver.cpp:218] Iteration 16740 (2.88657 iter/s, 4.15718s/12 iters), loss = 0.0851039
I0405 15:45:06.909505  1863 solver.cpp:237]     Train net output #0: loss = 0.0851037 (* 1 = 0.0851037 loss)
I0405 15:45:06.909512  1863 sgd_solver.cpp:105] Iteration 16740, lr = 0.001
I0405 15:45:12.324851  1863 solver.cpp:218] Iteration 16752 (2.21593 iter/s, 5.41533s/12 iters), loss = 0.0981693
I0405 15:45:12.324905  1863 solver.cpp:237]     Train net output #0: loss = 0.0981691 (* 1 = 0.0981691 loss)
I0405 15:45:12.324913  1863 sgd_solver.cpp:105] Iteration 16752, lr = 0.001
I0405 15:45:17.680917  1863 solver.cpp:218] Iteration 16764 (2.24048 iter/s, 5.356s/12 iters), loss = 0.115224
I0405 15:45:17.680969  1863 solver.cpp:237]     Train net output #0: loss = 0.115224 (* 1 = 0.115224 loss)
I0405 15:45:17.680979  1863 sgd_solver.cpp:105] Iteration 16764, lr = 0.001
I0405 15:45:22.971743  1863 solver.cpp:218] Iteration 16776 (2.2681 iter/s, 5.29077s/12 iters), loss = 0.224102
I0405 15:45:22.971843  1863 solver.cpp:237]     Train net output #0: loss = 0.224102 (* 1 = 0.224102 loss)
I0405 15:45:22.971849  1863 sgd_solver.cpp:105] Iteration 16776, lr = 0.001
I0405 15:45:28.411279  1863 solver.cpp:218] Iteration 16788 (2.20664 iter/s, 5.43814s/12 iters), loss = 0.0963756
I0405 15:45:28.411329  1863 solver.cpp:237]     Train net output #0: loss = 0.0963753 (* 1 = 0.0963753 loss)
I0405 15:45:28.411336  1863 sgd_solver.cpp:105] Iteration 16788, lr = 0.001
I0405 15:45:29.622135  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:45:33.863543  1863 solver.cpp:218] Iteration 16800 (2.20094 iter/s, 5.45221s/12 iters), loss = 0.0632419
I0405 15:45:33.863584  1863 solver.cpp:237]     Train net output #0: loss = 0.0632417 (* 1 = 0.0632417 loss)
I0405 15:45:33.863590  1863 sgd_solver.cpp:105] Iteration 16800, lr = 0.001
I0405 15:45:39.418324  1863 solver.cpp:218] Iteration 16812 (2.16032 iter/s, 5.55473s/12 iters), loss = 0.128951
I0405 15:45:39.418368  1863 solver.cpp:237]     Train net output #0: loss = 0.12895 (* 1 = 0.12895 loss)
I0405 15:45:39.418375  1863 sgd_solver.cpp:105] Iteration 16812, lr = 0.001
I0405 15:45:44.855872  1863 solver.cpp:218] Iteration 16824 (2.2069 iter/s, 5.4375s/12 iters), loss = 0.14778
I0405 15:45:44.855921  1863 solver.cpp:237]     Train net output #0: loss = 0.147779 (* 1 = 0.147779 loss)
I0405 15:45:44.855929  1863 sgd_solver.cpp:105] Iteration 16824, lr = 0.001
I0405 15:45:46.872979  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16830.caffemodel
I0405 15:45:50.058111  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16830.solverstate
I0405 15:45:52.371587  1863 solver.cpp:330] Iteration 16830, Testing net (#0)
I0405 15:45:52.371608  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:45:54.856431  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:45:57.043135  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270221
I0405 15:45:57.043169  1863 solver.cpp:397]     Test net output #1: loss = 4.84153 (* 1 = 4.84153 loss)
I0405 15:45:58.923964  1863 solver.cpp:218] Iteration 16836 (0.852997 iter/s, 14.0681s/12 iters), loss = 0.122974
I0405 15:45:58.924005  1863 solver.cpp:237]     Train net output #0: loss = 0.122974 (* 1 = 0.122974 loss)
I0405 15:45:58.924011  1863 sgd_solver.cpp:105] Iteration 16836, lr = 0.001
I0405 15:46:04.249743  1863 solver.cpp:218] Iteration 16848 (2.25321 iter/s, 5.32573s/12 iters), loss = 0.132132
I0405 15:46:04.249800  1863 solver.cpp:237]     Train net output #0: loss = 0.132132 (* 1 = 0.132132 loss)
I0405 15:46:04.249810  1863 sgd_solver.cpp:105] Iteration 16848, lr = 0.001
I0405 15:46:09.667471  1863 solver.cpp:218] Iteration 16860 (2.21498 iter/s, 5.41766s/12 iters), loss = 0.0580698
I0405 15:46:09.667523  1863 solver.cpp:237]     Train net output #0: loss = 0.0580695 (* 1 = 0.0580695 loss)
I0405 15:46:09.667531  1863 sgd_solver.cpp:105] Iteration 16860, lr = 0.001
I0405 15:46:15.171813  1863 solver.cpp:218] Iteration 16872 (2.18012 iter/s, 5.50428s/12 iters), loss = 0.159682
I0405 15:46:15.171872  1863 solver.cpp:237]     Train net output #0: loss = 0.159682 (* 1 = 0.159682 loss)
I0405 15:46:15.171880  1863 sgd_solver.cpp:105] Iteration 16872, lr = 0.001
I0405 15:46:20.625355  1863 solver.cpp:218] Iteration 16884 (2.20043 iter/s, 5.45348s/12 iters), loss = 0.0920607
I0405 15:46:20.625396  1863 solver.cpp:237]     Train net output #0: loss = 0.0920604 (* 1 = 0.0920604 loss)
I0405 15:46:20.625402  1863 sgd_solver.cpp:105] Iteration 16884, lr = 0.001
I0405 15:46:24.046425  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:46:25.851029  1863 solver.cpp:218] Iteration 16896 (2.29638 iter/s, 5.22562s/12 iters), loss = 0.126542
I0405 15:46:25.851114  1863 solver.cpp:237]     Train net output #0: loss = 0.126542 (* 1 = 0.126542 loss)
I0405 15:46:25.851119  1863 sgd_solver.cpp:105] Iteration 16896, lr = 0.001
I0405 15:46:31.401523  1863 solver.cpp:218] Iteration 16908 (2.16201 iter/s, 5.5504s/12 iters), loss = 0.0667204
I0405 15:46:31.401568  1863 solver.cpp:237]     Train net output #0: loss = 0.0667202 (* 1 = 0.0667202 loss)
I0405 15:46:31.401574  1863 sgd_solver.cpp:105] Iteration 16908, lr = 0.001
I0405 15:46:37.028426  1863 solver.cpp:218] Iteration 16920 (2.13263 iter/s, 5.62685s/12 iters), loss = 0.104222
I0405 15:46:37.028466  1863 solver.cpp:237]     Train net output #0: loss = 0.104221 (* 1 = 0.104221 loss)
I0405 15:46:37.028472  1863 sgd_solver.cpp:105] Iteration 16920, lr = 0.001
I0405 15:46:42.055534  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_16932.caffemodel
I0405 15:46:45.143776  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_16932.solverstate
I0405 15:46:47.464006  1863 solver.cpp:330] Iteration 16932, Testing net (#0)
I0405 15:46:47.464035  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:46:49.960124  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:46:52.008662  1863 solver.cpp:397]     Test net output #0: accuracy = 0.268995
I0405 15:46:52.008690  1863 solver.cpp:397]     Test net output #1: loss = 4.89567 (* 1 = 4.89567 loss)
I0405 15:46:52.148289  1863 solver.cpp:218] Iteration 16932 (0.79366 iter/s, 15.1198s/12 iters), loss = 0.0844405
I0405 15:46:52.148340  1863 solver.cpp:237]     Train net output #0: loss = 0.0844403 (* 1 = 0.0844403 loss)
I0405 15:46:52.148348  1863 sgd_solver.cpp:105] Iteration 16932, lr = 0.001
I0405 15:46:56.735100  1863 solver.cpp:218] Iteration 16944 (2.61623 iter/s, 4.58675s/12 iters), loss = 0.143569
I0405 15:46:56.735216  1863 solver.cpp:237]     Train net output #0: loss = 0.143569 (* 1 = 0.143569 loss)
I0405 15:46:56.735224  1863 sgd_solver.cpp:105] Iteration 16944, lr = 0.001
I0405 15:47:02.162935  1863 solver.cpp:218] Iteration 16956 (2.21088 iter/s, 5.42772s/12 iters), loss = 0.0434966
I0405 15:47:02.162974  1863 solver.cpp:237]     Train net output #0: loss = 0.0434964 (* 1 = 0.0434964 loss)
I0405 15:47:02.162979  1863 sgd_solver.cpp:105] Iteration 16956, lr = 0.001
I0405 15:47:07.708940  1863 solver.cpp:218] Iteration 16968 (2.16374 iter/s, 5.54596s/12 iters), loss = 0.0885037
I0405 15:47:07.708984  1863 solver.cpp:237]     Train net output #0: loss = 0.0885035 (* 1 = 0.0885035 loss)
I0405 15:47:07.708989  1863 sgd_solver.cpp:105] Iteration 16968, lr = 0.001
I0405 15:47:13.014647  1863 solver.cpp:218] Iteration 16980 (2.26174 iter/s, 5.30566s/12 iters), loss = 0.113104
I0405 15:47:13.014685  1863 solver.cpp:237]     Train net output #0: loss = 0.113104 (* 1 = 0.113104 loss)
I0405 15:47:13.014690  1863 sgd_solver.cpp:105] Iteration 16980, lr = 0.001
I0405 15:47:18.365145  1863 solver.cpp:218] Iteration 16992 (2.2428 iter/s, 5.35045s/12 iters), loss = 0.141368
I0405 15:47:18.365196  1863 solver.cpp:237]     Train net output #0: loss = 0.141368 (* 1 = 0.141368 loss)
I0405 15:47:18.365204  1863 sgd_solver.cpp:105] Iteration 16992, lr = 0.001
I0405 15:47:18.923518  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:47:23.956909  1863 solver.cpp:218] Iteration 17004 (2.14604 iter/s, 5.5917s/12 iters), loss = 0.0736273
I0405 15:47:23.956955  1863 solver.cpp:237]     Train net output #0: loss = 0.0736271 (* 1 = 0.0736271 loss)
I0405 15:47:23.956961  1863 sgd_solver.cpp:105] Iteration 17004, lr = 0.001
I0405 15:47:29.402411  1863 solver.cpp:218] Iteration 17016 (2.20368 iter/s, 5.44545s/12 iters), loss = 0.123148
I0405 15:47:29.402523  1863 solver.cpp:237]     Train net output #0: loss = 0.123148 (* 1 = 0.123148 loss)
I0405 15:47:29.402531  1863 sgd_solver.cpp:105] Iteration 17016, lr = 0.001
I0405 15:47:34.758970  1863 solver.cpp:218] Iteration 17028 (2.24029 iter/s, 5.35644s/12 iters), loss = 0.353859
I0405 15:47:34.759027  1863 solver.cpp:237]     Train net output #0: loss = 0.353859 (* 1 = 0.353859 loss)
I0405 15:47:34.759034  1863 sgd_solver.cpp:105] Iteration 17028, lr = 0.001
I0405 15:47:36.931972  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17034.caffemodel
I0405 15:47:39.993947  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17034.solverstate
I0405 15:47:42.297641  1863 solver.cpp:330] Iteration 17034, Testing net (#0)
I0405 15:47:42.297662  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:47:44.657833  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:47:46.709388  1863 solver.cpp:397]     Test net output #0: accuracy = 0.259191
I0405 15:47:46.709416  1863 solver.cpp:397]     Test net output #1: loss = 4.96637 (* 1 = 4.96637 loss)
I0405 15:47:48.732071  1863 solver.cpp:218] Iteration 17040 (0.858796 iter/s, 13.973s/12 iters), loss = 0.157661
I0405 15:47:48.732126  1863 solver.cpp:237]     Train net output #0: loss = 0.157661 (* 1 = 0.157661 loss)
I0405 15:47:48.732136  1863 sgd_solver.cpp:105] Iteration 17040, lr = 0.001
I0405 15:47:53.950767  1863 solver.cpp:218] Iteration 17052 (2.29945 iter/s, 5.21863s/12 iters), loss = 0.166211
I0405 15:47:53.950814  1863 solver.cpp:237]     Train net output #0: loss = 0.166211 (* 1 = 0.166211 loss)
I0405 15:47:53.950822  1863 sgd_solver.cpp:105] Iteration 17052, lr = 0.001
I0405 15:47:59.261298  1863 solver.cpp:218] Iteration 17064 (2.25969 iter/s, 5.31047s/12 iters), loss = 0.0968183
I0405 15:47:59.261355  1863 solver.cpp:237]     Train net output #0: loss = 0.0968181 (* 1 = 0.0968181 loss)
I0405 15:47:59.261363  1863 sgd_solver.cpp:105] Iteration 17064, lr = 0.001
I0405 15:48:04.504657  1863 solver.cpp:218] Iteration 17076 (2.28864 iter/s, 5.24329s/12 iters), loss = 0.102174
I0405 15:48:04.504818  1863 solver.cpp:237]     Train net output #0: loss = 0.102174 (* 1 = 0.102174 loss)
I0405 15:48:04.504827  1863 sgd_solver.cpp:105] Iteration 17076, lr = 0.001
I0405 15:48:09.577193  1863 solver.cpp:218] Iteration 17088 (2.36576 iter/s, 5.07237s/12 iters), loss = 0.0389472
I0405 15:48:09.577231  1863 solver.cpp:237]     Train net output #0: loss = 0.038947 (* 1 = 0.038947 loss)
I0405 15:48:09.577237  1863 sgd_solver.cpp:105] Iteration 17088, lr = 0.001
I0405 15:48:12.397861  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:48:15.111416  1863 solver.cpp:218] Iteration 17100 (2.16835 iter/s, 5.53417s/12 iters), loss = 0.131346
I0405 15:48:15.111464  1863 solver.cpp:237]     Train net output #0: loss = 0.131345 (* 1 = 0.131345 loss)
I0405 15:48:15.111471  1863 sgd_solver.cpp:105] Iteration 17100, lr = 0.001
I0405 15:48:20.537283  1863 solver.cpp:218] Iteration 17112 (2.21165 iter/s, 5.42581s/12 iters), loss = 0.0440234
I0405 15:48:20.537328  1863 solver.cpp:237]     Train net output #0: loss = 0.0440232 (* 1 = 0.0440232 loss)
I0405 15:48:20.537333  1863 sgd_solver.cpp:105] Iteration 17112, lr = 0.001
I0405 15:48:25.541276  1863 solver.cpp:218] Iteration 17124 (2.39811 iter/s, 5.00394s/12 iters), loss = 0.113278
I0405 15:48:25.541327  1863 solver.cpp:237]     Train net output #0: loss = 0.113277 (* 1 = 0.113277 loss)
I0405 15:48:25.541337  1863 sgd_solver.cpp:105] Iteration 17124, lr = 0.001
I0405 15:48:30.356946  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17136.caffemodel
I0405 15:48:33.253576  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17136.solverstate
I0405 15:48:35.547307  1863 solver.cpp:330] Iteration 17136, Testing net (#0)
I0405 15:48:35.547380  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:48:37.903028  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:48:40.074342  1863 solver.cpp:397]     Test net output #0: accuracy = 0.267157
I0405 15:48:40.074376  1863 solver.cpp:397]     Test net output #1: loss = 4.9331 (* 1 = 4.9331 loss)
I0405 15:48:40.213425  1863 solver.cpp:218] Iteration 17136 (0.817879 iter/s, 14.6721s/12 iters), loss = 0.143844
I0405 15:48:40.213481  1863 solver.cpp:237]     Train net output #0: loss = 0.143844 (* 1 = 0.143844 loss)
I0405 15:48:40.213487  1863 sgd_solver.cpp:105] Iteration 17136, lr = 0.001
I0405 15:48:44.738309  1863 solver.cpp:218] Iteration 17148 (2.65204 iter/s, 4.52482s/12 iters), loss = 0.122299
I0405 15:48:44.738353  1863 solver.cpp:237]     Train net output #0: loss = 0.122298 (* 1 = 0.122298 loss)
I0405 15:48:44.738358  1863 sgd_solver.cpp:105] Iteration 17148, lr = 0.001
I0405 15:48:49.932229  1863 solver.cpp:218] Iteration 17160 (2.31042 iter/s, 5.19387s/12 iters), loss = 0.0934023
I0405 15:48:49.932276  1863 solver.cpp:237]     Train net output #0: loss = 0.0934021 (* 1 = 0.0934021 loss)
I0405 15:48:49.932286  1863 sgd_solver.cpp:105] Iteration 17160, lr = 0.001
I0405 15:48:55.427227  1863 solver.cpp:218] Iteration 17172 (2.18383 iter/s, 5.49494s/12 iters), loss = 0.104371
I0405 15:48:55.427281  1863 solver.cpp:237]     Train net output #0: loss = 0.10437 (* 1 = 0.10437 loss)
I0405 15:48:55.427286  1863 sgd_solver.cpp:105] Iteration 17172, lr = 0.001
I0405 15:49:00.976824  1863 solver.cpp:218] Iteration 17184 (2.16234 iter/s, 5.54954s/12 iters), loss = 0.0321779
I0405 15:49:00.976891  1863 solver.cpp:237]     Train net output #0: loss = 0.0321777 (* 1 = 0.0321777 loss)
I0405 15:49:00.976902  1863 sgd_solver.cpp:105] Iteration 17184, lr = 0.001
I0405 15:49:05.952956  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:49:06.244110  1863 solver.cpp:218] Iteration 17196 (2.27824 iter/s, 5.26722s/12 iters), loss = 0.0539504
I0405 15:49:06.244163  1863 solver.cpp:237]     Train net output #0: loss = 0.0539502 (* 1 = 0.0539502 loss)
I0405 15:49:06.244170  1863 sgd_solver.cpp:105] Iteration 17196, lr = 0.001
I0405 15:49:11.560019  1863 solver.cpp:218] Iteration 17208 (2.2574 iter/s, 5.31585s/12 iters), loss = 0.0858256
I0405 15:49:11.560070  1863 solver.cpp:237]     Train net output #0: loss = 0.0858254 (* 1 = 0.0858254 loss)
I0405 15:49:11.560078  1863 sgd_solver.cpp:105] Iteration 17208, lr = 0.001
I0405 15:49:16.960151  1863 solver.cpp:218] Iteration 17220 (2.22219 iter/s, 5.40008s/12 iters), loss = 0.0563956
I0405 15:49:16.960187  1863 solver.cpp:237]     Train net output #0: loss = 0.0563954 (* 1 = 0.0563954 loss)
I0405 15:49:16.960192  1863 sgd_solver.cpp:105] Iteration 17220, lr = 0.001
I0405 15:49:22.351233  1863 solver.cpp:218] Iteration 17232 (2.22592 iter/s, 5.39103s/12 iters), loss = 0.0931183
I0405 15:49:22.351289  1863 solver.cpp:237]     Train net output #0: loss = 0.0931181 (* 1 = 0.0931181 loss)
I0405 15:49:22.351296  1863 sgd_solver.cpp:105] Iteration 17232, lr = 0.001
I0405 15:49:24.522855  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17238.caffemodel
I0405 15:49:27.531116  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17238.solverstate
I0405 15:49:29.867023  1863 solver.cpp:330] Iteration 17238, Testing net (#0)
I0405 15:49:29.867044  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:49:32.239563  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:49:34.607725  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275735
I0405 15:49:34.607754  1863 solver.cpp:397]     Test net output #1: loss = 4.78109 (* 1 = 4.78109 loss)
I0405 15:49:36.542806  1863 solver.cpp:218] Iteration 17244 (0.845576 iter/s, 14.1915s/12 iters), loss = 0.135309
I0405 15:49:36.542933  1863 solver.cpp:237]     Train net output #0: loss = 0.135309 (* 1 = 0.135309 loss)
I0405 15:49:36.542943  1863 sgd_solver.cpp:105] Iteration 17244, lr = 0.001
I0405 15:49:41.757576  1863 solver.cpp:218] Iteration 17256 (2.30122 iter/s, 5.21463s/12 iters), loss = 0.156428
I0405 15:49:41.757632  1863 solver.cpp:237]     Train net output #0: loss = 0.156428 (* 1 = 0.156428 loss)
I0405 15:49:41.757640  1863 sgd_solver.cpp:105] Iteration 17256, lr = 0.001
I0405 15:49:47.019788  1863 solver.cpp:218] Iteration 17268 (2.28044 iter/s, 5.26215s/12 iters), loss = 0.0873495
I0405 15:49:47.019837  1863 solver.cpp:237]     Train net output #0: loss = 0.0873493 (* 1 = 0.0873493 loss)
I0405 15:49:47.019845  1863 sgd_solver.cpp:105] Iteration 17268, lr = 0.001
I0405 15:49:52.478427  1863 solver.cpp:218] Iteration 17280 (2.19837 iter/s, 5.45858s/12 iters), loss = 0.0759648
I0405 15:49:52.478468  1863 solver.cpp:237]     Train net output #0: loss = 0.0759646 (* 1 = 0.0759646 loss)
I0405 15:49:52.478474  1863 sgd_solver.cpp:105] Iteration 17280, lr = 0.001
I0405 15:49:58.045087  1863 solver.cpp:218] Iteration 17292 (2.15571 iter/s, 5.56661s/12 iters), loss = 0.0525547
I0405 15:49:58.045127  1863 solver.cpp:237]     Train net output #0: loss = 0.0525545 (* 1 = 0.0525545 loss)
I0405 15:49:58.045132  1863 sgd_solver.cpp:105] Iteration 17292, lr = 0.001
I0405 15:50:00.134549  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:50:03.532920  1863 solver.cpp:218] Iteration 17304 (2.18668 iter/s, 5.48778s/12 iters), loss = 0.0520336
I0405 15:50:03.532963  1863 solver.cpp:237]     Train net output #0: loss = 0.0520334 (* 1 = 0.0520334 loss)
I0405 15:50:03.532968  1863 sgd_solver.cpp:105] Iteration 17304, lr = 0.001
I0405 15:50:09.050539  1863 solver.cpp:218] Iteration 17316 (2.17487 iter/s, 5.51756s/12 iters), loss = 0.0499186
I0405 15:50:09.050653  1863 solver.cpp:237]     Train net output #0: loss = 0.0499184 (* 1 = 0.0499184 loss)
I0405 15:50:09.050663  1863 sgd_solver.cpp:105] Iteration 17316, lr = 0.001
I0405 15:50:14.519870  1863 solver.cpp:218] Iteration 17328 (2.1941 iter/s, 5.46921s/12 iters), loss = 0.167846
I0405 15:50:14.519923  1863 solver.cpp:237]     Train net output #0: loss = 0.167846 (* 1 = 0.167846 loss)
I0405 15:50:14.519932  1863 sgd_solver.cpp:105] Iteration 17328, lr = 0.001
I0405 15:50:19.384145  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17340.caffemodel
I0405 15:50:22.501653  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17340.solverstate
I0405 15:50:24.799006  1863 solver.cpp:330] Iteration 17340, Testing net (#0)
I0405 15:50:24.799024  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:50:26.009929  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:50:27.045238  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:50:29.352752  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270833
I0405 15:50:29.352798  1863 solver.cpp:397]     Test net output #1: loss = 4.91863 (* 1 = 4.91863 loss)
I0405 15:50:29.484174  1863 solver.cpp:218] Iteration 17340 (0.801911 iter/s, 14.9643s/12 iters), loss = 0.135882
I0405 15:50:29.484215  1863 solver.cpp:237]     Train net output #0: loss = 0.135882 (* 1 = 0.135882 loss)
I0405 15:50:29.484220  1863 sgd_solver.cpp:105] Iteration 17340, lr = 0.001
I0405 15:50:33.924517  1863 solver.cpp:218] Iteration 17352 (2.70253 iter/s, 4.44029s/12 iters), loss = 0.212645
I0405 15:50:33.924566  1863 solver.cpp:237]     Train net output #0: loss = 0.212645 (* 1 = 0.212645 loss)
I0405 15:50:33.924573  1863 sgd_solver.cpp:105] Iteration 17352, lr = 0.001
I0405 15:50:39.314020  1863 solver.cpp:218] Iteration 17364 (2.22657 iter/s, 5.38945s/12 iters), loss = 0.0378321
I0405 15:50:39.314216  1863 solver.cpp:237]     Train net output #0: loss = 0.0378319 (* 1 = 0.0378319 loss)
I0405 15:50:39.314226  1863 sgd_solver.cpp:105] Iteration 17364, lr = 0.001
I0405 15:50:44.843081  1863 solver.cpp:218] Iteration 17376 (2.17043 iter/s, 5.52886s/12 iters), loss = 0.116004
I0405 15:50:44.843125  1863 solver.cpp:237]     Train net output #0: loss = 0.116003 (* 1 = 0.116003 loss)
I0405 15:50:44.843132  1863 sgd_solver.cpp:105] Iteration 17376, lr = 0.001
I0405 15:50:50.256848  1863 solver.cpp:218] Iteration 17388 (2.21659 iter/s, 5.41371s/12 iters), loss = 0.131195
I0405 15:50:50.256927  1863 solver.cpp:237]     Train net output #0: loss = 0.131195 (* 1 = 0.131195 loss)
I0405 15:50:50.256942  1863 sgd_solver.cpp:105] Iteration 17388, lr = 0.001
I0405 15:50:54.604144  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:50:55.733460  1863 solver.cpp:218] Iteration 17400 (2.19117 iter/s, 5.47653s/12 iters), loss = 0.157233
I0405 15:50:55.733511  1863 solver.cpp:237]     Train net output #0: loss = 0.157232 (* 1 = 0.157232 loss)
I0405 15:50:55.733520  1863 sgd_solver.cpp:105] Iteration 17400, lr = 0.001
I0405 15:51:01.089648  1863 solver.cpp:218] Iteration 17412 (2.24042 iter/s, 5.35613s/12 iters), loss = 0.141392
I0405 15:51:01.089689  1863 solver.cpp:237]     Train net output #0: loss = 0.141391 (* 1 = 0.141391 loss)
I0405 15:51:01.089694  1863 sgd_solver.cpp:105] Iteration 17412, lr = 0.001
I0405 15:51:06.364900  1863 solver.cpp:218] Iteration 17424 (2.2748 iter/s, 5.2752s/12 iters), loss = 0.16844
I0405 15:51:06.364953  1863 solver.cpp:237]     Train net output #0: loss = 0.16844 (* 1 = 0.16844 loss)
I0405 15:51:06.364961  1863 sgd_solver.cpp:105] Iteration 17424, lr = 0.001
I0405 15:51:11.726092  1863 solver.cpp:218] Iteration 17436 (2.23833 iter/s, 5.36113s/12 iters), loss = 0.128251
I0405 15:51:11.726186  1863 solver.cpp:237]     Train net output #0: loss = 0.128251 (* 1 = 0.128251 loss)
I0405 15:51:11.726193  1863 sgd_solver.cpp:105] Iteration 17436, lr = 0.001
I0405 15:51:13.963562  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17442.caffemodel
I0405 15:51:17.019492  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17442.solverstate
I0405 15:51:19.738685  1863 solver.cpp:330] Iteration 17442, Testing net (#0)
I0405 15:51:19.738708  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:51:21.988436  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:51:24.271097  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26777
I0405 15:51:24.271131  1863 solver.cpp:397]     Test net output #1: loss = 4.85991 (* 1 = 4.85991 loss)
I0405 15:51:26.337034  1863 solver.cpp:218] Iteration 17448 (0.821307 iter/s, 14.6109s/12 iters), loss = 0.102535
I0405 15:51:26.337074  1863 solver.cpp:237]     Train net output #0: loss = 0.102534 (* 1 = 0.102534 loss)
I0405 15:51:26.337081  1863 sgd_solver.cpp:105] Iteration 17448, lr = 0.001
I0405 15:51:31.722710  1863 solver.cpp:218] Iteration 17460 (2.22816 iter/s, 5.38562s/12 iters), loss = 0.0859623
I0405 15:51:31.722766  1863 solver.cpp:237]     Train net output #0: loss = 0.0859621 (* 1 = 0.0859621 loss)
I0405 15:51:31.722775  1863 sgd_solver.cpp:105] Iteration 17460, lr = 0.001
I0405 15:51:37.300971  1863 solver.cpp:218] Iteration 17472 (2.15123 iter/s, 5.5782s/12 iters), loss = 0.0685975
I0405 15:51:37.301010  1863 solver.cpp:237]     Train net output #0: loss = 0.0685973 (* 1 = 0.0685973 loss)
I0405 15:51:37.301015  1863 sgd_solver.cpp:105] Iteration 17472, lr = 0.001
I0405 15:51:42.663698  1863 solver.cpp:218] Iteration 17484 (2.23769 iter/s, 5.36268s/12 iters), loss = 0.127124
I0405 15:51:42.663852  1863 solver.cpp:237]     Train net output #0: loss = 0.127124 (* 1 = 0.127124 loss)
I0405 15:51:42.663861  1863 sgd_solver.cpp:105] Iteration 17484, lr = 0.001
I0405 15:51:48.039513  1863 solver.cpp:218] Iteration 17496 (2.23229 iter/s, 5.37566s/12 iters), loss = 0.120448
I0405 15:51:48.039551  1863 solver.cpp:237]     Train net output #0: loss = 0.120448 (* 1 = 0.120448 loss)
I0405 15:51:48.039556  1863 sgd_solver.cpp:105] Iteration 17496, lr = 0.001
I0405 15:51:49.278587  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:51:53.342020  1863 solver.cpp:218] Iteration 17508 (2.2631 iter/s, 5.30246s/12 iters), loss = 0.0680526
I0405 15:51:53.342059  1863 solver.cpp:237]     Train net output #0: loss = 0.0680524 (* 1 = 0.0680524 loss)
I0405 15:51:53.342067  1863 sgd_solver.cpp:105] Iteration 17508, lr = 0.001
I0405 15:51:59.011514  1863 solver.cpp:218] Iteration 17520 (2.11661 iter/s, 5.66945s/12 iters), loss = 0.0946227
I0405 15:51:59.011554  1863 solver.cpp:237]     Train net output #0: loss = 0.0946225 (* 1 = 0.0946225 loss)
I0405 15:51:59.011559  1863 sgd_solver.cpp:105] Iteration 17520, lr = 0.001
I0405 15:52:04.259429  1863 solver.cpp:218] Iteration 17532 (2.28665 iter/s, 5.24786s/12 iters), loss = 0.162004
I0405 15:52:04.259482  1863 solver.cpp:237]     Train net output #0: loss = 0.162004 (* 1 = 0.162004 loss)
I0405 15:52:04.259491  1863 sgd_solver.cpp:105] Iteration 17532, lr = 0.001
I0405 15:52:09.092933  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17544.caffemodel
I0405 15:52:12.324301  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17544.solverstate
I0405 15:52:14.804349  1863 solver.cpp:330] Iteration 17544, Testing net (#0)
I0405 15:52:14.804452  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:52:17.088165  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:52:19.527714  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275123
I0405 15:52:19.527751  1863 solver.cpp:397]     Test net output #1: loss = 4.85755 (* 1 = 4.85755 loss)
I0405 15:52:19.666379  1863 solver.cpp:218] Iteration 17544 (0.778872 iter/s, 15.4069s/12 iters), loss = 0.0588089
I0405 15:52:19.666435  1863 solver.cpp:237]     Train net output #0: loss = 0.0588087 (* 1 = 0.0588087 loss)
I0405 15:52:19.666442  1863 sgd_solver.cpp:105] Iteration 17544, lr = 0.001
I0405 15:52:24.218844  1863 solver.cpp:218] Iteration 17556 (2.63597 iter/s, 4.5524s/12 iters), loss = 0.0606742
I0405 15:52:24.218892  1863 solver.cpp:237]     Train net output #0: loss = 0.060674 (* 1 = 0.060674 loss)
I0405 15:52:24.218900  1863 sgd_solver.cpp:105] Iteration 17556, lr = 0.001
I0405 15:52:29.499663  1863 solver.cpp:218] Iteration 17568 (2.2724 iter/s, 5.28076s/12 iters), loss = 0.119247
I0405 15:52:29.499716  1863 solver.cpp:237]     Train net output #0: loss = 0.119247 (* 1 = 0.119247 loss)
I0405 15:52:29.499724  1863 sgd_solver.cpp:105] Iteration 17568, lr = 0.001
I0405 15:52:34.760447  1863 solver.cpp:218] Iteration 17580 (2.28106 iter/s, 5.26072s/12 iters), loss = 0.124321
I0405 15:52:34.760495  1863 solver.cpp:237]     Train net output #0: loss = 0.124321 (* 1 = 0.124321 loss)
I0405 15:52:34.760502  1863 sgd_solver.cpp:105] Iteration 17580, lr = 0.001
I0405 15:52:40.191521  1863 solver.cpp:218] Iteration 17592 (2.20953 iter/s, 5.43101s/12 iters), loss = 0.0553911
I0405 15:52:40.191568  1863 solver.cpp:237]     Train net output #0: loss = 0.0553909 (* 1 = 0.0553909 loss)
I0405 15:52:40.191576  1863 sgd_solver.cpp:105] Iteration 17592, lr = 0.001
I0405 15:52:43.787225  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:52:45.586021  1863 solver.cpp:218] Iteration 17604 (2.22451 iter/s, 5.39444s/12 iters), loss = 0.171226
I0405 15:52:45.586171  1863 solver.cpp:237]     Train net output #0: loss = 0.171226 (* 1 = 0.171226 loss)
I0405 15:52:45.586181  1863 sgd_solver.cpp:105] Iteration 17604, lr = 0.001
I0405 15:52:50.903005  1863 solver.cpp:218] Iteration 17616 (2.25699 iter/s, 5.31683s/12 iters), loss = 0.263517
I0405 15:52:50.903053  1863 solver.cpp:237]     Train net output #0: loss = 0.263517 (* 1 = 0.263517 loss)
I0405 15:52:50.903061  1863 sgd_solver.cpp:105] Iteration 17616, lr = 0.001
I0405 15:52:56.394104  1863 solver.cpp:218] Iteration 17628 (2.18538 iter/s, 5.49103s/12 iters), loss = 0.0130118
I0405 15:52:56.394166  1863 solver.cpp:237]     Train net output #0: loss = 0.0130116 (* 1 = 0.0130116 loss)
I0405 15:52:56.394176  1863 sgd_solver.cpp:105] Iteration 17628, lr = 0.001
I0405 15:53:01.719674  1863 solver.cpp:218] Iteration 17640 (2.25331 iter/s, 5.3255s/12 iters), loss = 0.0997683
I0405 15:53:01.719712  1863 solver.cpp:237]     Train net output #0: loss = 0.0997681 (* 1 = 0.0997681 loss)
I0405 15:53:01.719717  1863 sgd_solver.cpp:105] Iteration 17640, lr = 0.001
I0405 15:53:03.911772  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17646.caffemodel
I0405 15:53:07.797324  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17646.solverstate
I0405 15:53:10.177942  1863 solver.cpp:330] Iteration 17646, Testing net (#0)
I0405 15:53:10.177961  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:53:12.395555  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:53:14.981809  1863 solver.cpp:397]     Test net output #0: accuracy = 0.259804
I0405 15:53:14.981835  1863 solver.cpp:397]     Test net output #1: loss = 4.93504 (* 1 = 4.93504 loss)
I0405 15:53:16.900873  1863 solver.cpp:218] Iteration 17652 (0.790453 iter/s, 15.1812s/12 iters), loss = 0.0621372
I0405 15:53:16.900966  1863 solver.cpp:237]     Train net output #0: loss = 0.062137 (* 1 = 0.062137 loss)
I0405 15:53:16.900974  1863 sgd_solver.cpp:105] Iteration 17652, lr = 0.001
I0405 15:53:22.372859  1863 solver.cpp:218] Iteration 17664 (2.19303 iter/s, 5.47188s/12 iters), loss = 0.109359
I0405 15:53:22.372908  1863 solver.cpp:237]     Train net output #0: loss = 0.109359 (* 1 = 0.109359 loss)
I0405 15:53:22.372915  1863 sgd_solver.cpp:105] Iteration 17664, lr = 0.001
I0405 15:53:27.875382  1863 solver.cpp:218] Iteration 17676 (2.18084 iter/s, 5.50246s/12 iters), loss = 0.0889189
I0405 15:53:27.875437  1863 solver.cpp:237]     Train net output #0: loss = 0.0889187 (* 1 = 0.0889187 loss)
I0405 15:53:27.875447  1863 sgd_solver.cpp:105] Iteration 17676, lr = 0.001
I0405 15:53:33.647279  1863 solver.cpp:218] Iteration 17688 (2.07906 iter/s, 5.77183s/12 iters), loss = 0.0551005
I0405 15:53:33.647334  1863 solver.cpp:237]     Train net output #0: loss = 0.0551003 (* 1 = 0.0551003 loss)
I0405 15:53:33.647346  1863 sgd_solver.cpp:105] Iteration 17688, lr = 0.001
I0405 15:53:39.194072  1863 solver.cpp:218] Iteration 17700 (2.16344 iter/s, 5.54673s/12 iters), loss = 0.0921478
I0405 15:53:39.194131  1863 solver.cpp:237]     Train net output #0: loss = 0.0921475 (* 1 = 0.0921475 loss)
I0405 15:53:39.194140  1863 sgd_solver.cpp:105] Iteration 17700, lr = 0.001
I0405 15:53:39.801180  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:53:44.910127  1863 solver.cpp:218] Iteration 17712 (2.09937 iter/s, 5.71599s/12 iters), loss = 0.0702553
I0405 15:53:44.910176  1863 solver.cpp:237]     Train net output #0: loss = 0.070255 (* 1 = 0.070255 loss)
I0405 15:53:44.910182  1863 sgd_solver.cpp:105] Iteration 17712, lr = 0.001
I0405 15:53:50.555361  1863 solver.cpp:218] Iteration 17724 (2.12571 iter/s, 5.64517s/12 iters), loss = 0.135615
I0405 15:53:50.555531  1863 solver.cpp:237]     Train net output #0: loss = 0.135615 (* 1 = 0.135615 loss)
I0405 15:53:50.555538  1863 sgd_solver.cpp:105] Iteration 17724, lr = 0.001
I0405 15:53:56.215992  1863 solver.cpp:218] Iteration 17736 (2.11997 iter/s, 5.66045s/12 iters), loss = 0.0304651
I0405 15:53:56.216044  1863 solver.cpp:237]     Train net output #0: loss = 0.0304649 (* 1 = 0.0304649 loss)
I0405 15:53:56.216054  1863 sgd_solver.cpp:105] Iteration 17736, lr = 0.001
I0405 15:54:01.435272  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17748.caffemodel
I0405 15:54:04.547721  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17748.solverstate
I0405 15:54:06.943693  1863 solver.cpp:330] Iteration 17748, Testing net (#0)
I0405 15:54:06.943718  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:54:09.344951  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:54:11.899724  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26348
I0405 15:54:11.899765  1863 solver.cpp:397]     Test net output #1: loss = 4.91364 (* 1 = 4.91364 loss)
I0405 15:54:12.040658  1863 solver.cpp:218] Iteration 17748 (0.758312 iter/s, 15.8246s/12 iters), loss = 0.156071
I0405 15:54:12.040707  1863 solver.cpp:237]     Train net output #0: loss = 0.156071 (* 1 = 0.156071 loss)
I0405 15:54:12.040714  1863 sgd_solver.cpp:105] Iteration 17748, lr = 0.001
I0405 15:54:16.744151  1863 solver.cpp:218] Iteration 17760 (2.55133 iter/s, 4.70343s/12 iters), loss = 0.177975
I0405 15:54:16.744207  1863 solver.cpp:237]     Train net output #0: loss = 0.177974 (* 1 = 0.177974 loss)
I0405 15:54:16.744215  1863 sgd_solver.cpp:105] Iteration 17760, lr = 0.001
I0405 15:54:22.564718  1863 solver.cpp:218] Iteration 17772 (2.06168 iter/s, 5.8205s/12 iters), loss = 0.0941899
I0405 15:54:22.564831  1863 solver.cpp:237]     Train net output #0: loss = 0.0941897 (* 1 = 0.0941897 loss)
I0405 15:54:22.564837  1863 sgd_solver.cpp:105] Iteration 17772, lr = 0.001
I0405 15:54:28.264533  1863 solver.cpp:218] Iteration 17784 (2.10538 iter/s, 5.69969s/12 iters), loss = 0.128141
I0405 15:54:28.264598  1863 solver.cpp:237]     Train net output #0: loss = 0.128141 (* 1 = 0.128141 loss)
I0405 15:54:28.264607  1863 sgd_solver.cpp:105] Iteration 17784, lr = 0.001
I0405 15:54:34.119230  1863 solver.cpp:218] Iteration 17796 (2.04966 iter/s, 5.85463s/12 iters), loss = 0.0671671
I0405 15:54:34.119285  1863 solver.cpp:237]     Train net output #0: loss = 0.0671669 (* 1 = 0.0671669 loss)
I0405 15:54:34.119293  1863 sgd_solver.cpp:105] Iteration 17796, lr = 0.001
I0405 15:54:37.053645  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:54:39.561156  1863 solver.cpp:218] Iteration 17808 (2.20513 iter/s, 5.44186s/12 iters), loss = 0.0595117
I0405 15:54:39.561208  1863 solver.cpp:237]     Train net output #0: loss = 0.0595114 (* 1 = 0.0595114 loss)
I0405 15:54:39.561216  1863 sgd_solver.cpp:105] Iteration 17808, lr = 0.001
I0405 15:54:45.459722  1863 solver.cpp:218] Iteration 17820 (2.03441 iter/s, 5.89851s/12 iters), loss = 0.0172458
I0405 15:54:45.459766  1863 solver.cpp:237]     Train net output #0: loss = 0.0172456 (* 1 = 0.0172456 loss)
I0405 15:54:45.459774  1863 sgd_solver.cpp:105] Iteration 17820, lr = 0.001
I0405 15:54:51.135955  1863 solver.cpp:218] Iteration 17832 (2.1141 iter/s, 5.67617s/12 iters), loss = 0.0783934
I0405 15:54:51.136009  1863 solver.cpp:237]     Train net output #0: loss = 0.0783932 (* 1 = 0.0783932 loss)
I0405 15:54:51.136019  1863 sgd_solver.cpp:105] Iteration 17832, lr = 0.001
I0405 15:54:56.919922  1863 solver.cpp:218] Iteration 17844 (2.07472 iter/s, 5.7839s/12 iters), loss = 0.0815001
I0405 15:54:56.920066  1863 solver.cpp:237]     Train net output #0: loss = 0.0814999 (* 1 = 0.0814999 loss)
I0405 15:54:56.920076  1863 sgd_solver.cpp:105] Iteration 17844, lr = 0.001
I0405 15:54:59.205425  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17850.caffemodel
I0405 15:55:02.418486  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17850.solverstate
I0405 15:55:04.799101  1863 solver.cpp:330] Iteration 17850, Testing net (#0)
I0405 15:55:04.799125  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:55:06.945734  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:55:09.649621  1863 solver.cpp:397]     Test net output #0: accuracy = 0.265931
I0405 15:55:09.649653  1863 solver.cpp:397]     Test net output #1: loss = 4.92391 (* 1 = 4.92391 loss)
I0405 15:55:11.637207  1863 solver.cpp:218] Iteration 17856 (0.815376 iter/s, 14.7171s/12 iters), loss = 0.0522816
I0405 15:55:11.637259  1863 solver.cpp:237]     Train net output #0: loss = 0.0522814 (* 1 = 0.0522814 loss)
I0405 15:55:11.637265  1863 sgd_solver.cpp:105] Iteration 17856, lr = 0.001
I0405 15:55:17.399238  1863 solver.cpp:218] Iteration 17868 (2.08262 iter/s, 5.76197s/12 iters), loss = 0.163663
I0405 15:55:17.399289  1863 solver.cpp:237]     Train net output #0: loss = 0.163663 (* 1 = 0.163663 loss)
I0405 15:55:17.399297  1863 sgd_solver.cpp:105] Iteration 17868, lr = 0.001
I0405 15:55:23.165916  1863 solver.cpp:218] Iteration 17880 (2.08094 iter/s, 5.76662s/12 iters), loss = 0.0924474
I0405 15:55:23.165956  1863 solver.cpp:237]     Train net output #0: loss = 0.0924472 (* 1 = 0.0924472 loss)
I0405 15:55:23.165961  1863 sgd_solver.cpp:105] Iteration 17880, lr = 0.001
I0405 15:55:28.723250  1863 solver.cpp:218] Iteration 17892 (2.15933 iter/s, 5.55728s/12 iters), loss = 0.0618404
I0405 15:55:28.723366  1863 solver.cpp:237]     Train net output #0: loss = 0.0618401 (* 1 = 0.0618401 loss)
I0405 15:55:28.723376  1863 sgd_solver.cpp:105] Iteration 17892, lr = 0.001
I0405 15:55:34.233556  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:55:34.481662  1863 solver.cpp:218] Iteration 17904 (2.08395 iter/s, 5.75829s/12 iters), loss = 0.0727803
I0405 15:55:34.481710  1863 solver.cpp:237]     Train net output #0: loss = 0.0727801 (* 1 = 0.0727801 loss)
I0405 15:55:34.481719  1863 sgd_solver.cpp:105] Iteration 17904, lr = 0.001
I0405 15:55:40.264926  1863 solver.cpp:218] Iteration 17916 (2.07497 iter/s, 5.7832s/12 iters), loss = 0.147087
I0405 15:55:40.264976  1863 solver.cpp:237]     Train net output #0: loss = 0.147087 (* 1 = 0.147087 loss)
I0405 15:55:40.264982  1863 sgd_solver.cpp:105] Iteration 17916, lr = 0.001
I0405 15:55:45.778775  1863 solver.cpp:218] Iteration 17928 (2.17636 iter/s, 5.51379s/12 iters), loss = 0.142481
I0405 15:55:45.778825  1863 solver.cpp:237]     Train net output #0: loss = 0.14248 (* 1 = 0.14248 loss)
I0405 15:55:45.778832  1863 sgd_solver.cpp:105] Iteration 17928, lr = 0.001
I0405 15:55:51.752912  1863 solver.cpp:218] Iteration 17940 (2.00868 iter/s, 5.97407s/12 iters), loss = 0.191168
I0405 15:55:51.752966  1863 solver.cpp:237]     Train net output #0: loss = 0.191168 (* 1 = 0.191168 loss)
I0405 15:55:51.752975  1863 sgd_solver.cpp:105] Iteration 17940, lr = 0.001
I0405 15:55:57.189857  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_17952.caffemodel
I0405 15:56:02.483345  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_17952.solverstate
I0405 15:56:05.652045  1863 solver.cpp:330] Iteration 17952, Testing net (#0)
I0405 15:56:05.652066  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:56:07.824793  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:56:10.568874  1863 solver.cpp:397]     Test net output #0: accuracy = 0.276348
I0405 15:56:10.568917  1863 solver.cpp:397]     Test net output #1: loss = 4.87728 (* 1 = 4.87728 loss)
I0405 15:56:10.717731  1863 solver.cpp:218] Iteration 17952 (0.632752 iter/s, 18.9648s/12 iters), loss = 0.152485
I0405 15:56:10.720000  1863 solver.cpp:237]     Train net output #0: loss = 0.152485 (* 1 = 0.152485 loss)
I0405 15:56:10.720010  1863 sgd_solver.cpp:105] Iteration 17952, lr = 0.001
I0405 15:56:15.257926  1863 solver.cpp:218] Iteration 17964 (2.64438 iter/s, 4.53792s/12 iters), loss = 0.0274761
I0405 15:56:15.257974  1863 solver.cpp:237]     Train net output #0: loss = 0.0274758 (* 1 = 0.0274758 loss)
I0405 15:56:15.257982  1863 sgd_solver.cpp:105] Iteration 17964, lr = 0.001
I0405 15:56:20.814014  1863 solver.cpp:218] Iteration 17976 (2.15982 iter/s, 5.55603s/12 iters), loss = 0.091324
I0405 15:56:20.814061  1863 solver.cpp:237]     Train net output #0: loss = 0.0913237 (* 1 = 0.0913237 loss)
I0405 15:56:20.814067  1863 sgd_solver.cpp:105] Iteration 17976, lr = 0.001
I0405 15:56:26.508785  1863 solver.cpp:218] Iteration 17988 (2.10722 iter/s, 5.69471s/12 iters), loss = 0.0381973
I0405 15:56:26.508842  1863 solver.cpp:237]     Train net output #0: loss = 0.0381971 (* 1 = 0.0381971 loss)
I0405 15:56:26.508852  1863 sgd_solver.cpp:105] Iteration 17988, lr = 0.001
I0405 15:56:32.050655  1863 solver.cpp:218] Iteration 18000 (2.16536 iter/s, 5.5418s/12 iters), loss = 0.103763
I0405 15:56:32.050719  1863 solver.cpp:237]     Train net output #0: loss = 0.103763 (* 1 = 0.103763 loss)
I0405 15:56:32.050729  1863 sgd_solver.cpp:105] Iteration 18000, lr = 0.001
I0405 15:56:34.223620  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:56:37.621620  1863 solver.cpp:218] Iteration 18012 (2.15405 iter/s, 5.57089s/12 iters), loss = 0.0524943
I0405 15:56:37.621670  1863 solver.cpp:237]     Train net output #0: loss = 0.0524941 (* 1 = 0.0524941 loss)
I0405 15:56:37.621677  1863 sgd_solver.cpp:105] Iteration 18012, lr = 0.001
I0405 15:56:43.080250  1863 solver.cpp:218] Iteration 18024 (2.19838 iter/s, 5.45857s/12 iters), loss = 0.130815
I0405 15:56:43.080299  1863 solver.cpp:237]     Train net output #0: loss = 0.130814 (* 1 = 0.130814 loss)
I0405 15:56:43.080307  1863 sgd_solver.cpp:105] Iteration 18024, lr = 0.001
I0405 15:56:48.812067  1863 solver.cpp:218] Iteration 18036 (2.0936 iter/s, 5.73176s/12 iters), loss = 0.120262
I0405 15:56:48.812115  1863 solver.cpp:237]     Train net output #0: loss = 0.120261 (* 1 = 0.120261 loss)
I0405 15:56:48.812124  1863 sgd_solver.cpp:105] Iteration 18036, lr = 0.001
I0405 15:56:48.812381  1863 blocking_queue.cpp:49] Waiting for data
I0405 15:56:54.394798  1863 solver.cpp:218] Iteration 18048 (2.14951 iter/s, 5.58267s/12 iters), loss = 0.0912042
I0405 15:56:54.394835  1863 solver.cpp:237]     Train net output #0: loss = 0.0912039 (* 1 = 0.0912039 loss)
I0405 15:56:54.394841  1863 sgd_solver.cpp:105] Iteration 18048, lr = 0.001
I0405 15:56:56.670368  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18054.caffemodel
I0405 15:56:59.877408  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18054.solverstate
I0405 15:57:02.259459  1863 solver.cpp:330] Iteration 18054, Testing net (#0)
I0405 15:57:02.259483  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:57:04.421681  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:57:07.104924  1863 solver.cpp:397]     Test net output #0: accuracy = 0.259804
I0405 15:57:07.104951  1863 solver.cpp:397]     Test net output #1: loss = 4.94044 (* 1 = 4.94044 loss)
I0405 15:57:09.114902  1863 solver.cpp:218] Iteration 18060 (0.815214 iter/s, 14.7201s/12 iters), loss = 0.0580671
I0405 15:57:09.114945  1863 solver.cpp:237]     Train net output #0: loss = 0.0580669 (* 1 = 0.0580669 loss)
I0405 15:57:09.114951  1863 sgd_solver.cpp:105] Iteration 18060, lr = 0.001
I0405 15:57:14.840711  1863 solver.cpp:218] Iteration 18072 (2.09579 iter/s, 5.72575s/12 iters), loss = 0.0587179
I0405 15:57:14.840760  1863 solver.cpp:237]     Train net output #0: loss = 0.0587177 (* 1 = 0.0587177 loss)
I0405 15:57:14.840770  1863 sgd_solver.cpp:105] Iteration 18072, lr = 0.001
I0405 15:57:20.594445  1863 solver.cpp:218] Iteration 18084 (2.08563 iter/s, 5.75367s/12 iters), loss = 0.116966
I0405 15:57:20.600824  1863 solver.cpp:237]     Train net output #0: loss = 0.116966 (* 1 = 0.116966 loss)
I0405 15:57:20.600847  1863 sgd_solver.cpp:105] Iteration 18084, lr = 0.001
I0405 15:57:26.257581  1863 solver.cpp:218] Iteration 18096 (2.12135 iter/s, 5.65677s/12 iters), loss = 0.0484068
I0405 15:57:26.257618  1863 solver.cpp:237]     Train net output #0: loss = 0.0484066 (* 1 = 0.0484066 loss)
I0405 15:57:26.257623  1863 sgd_solver.cpp:105] Iteration 18096, lr = 0.001
I0405 15:57:30.778836  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:57:31.939189  1863 solver.cpp:218] Iteration 18108 (2.1121 iter/s, 5.68156s/12 iters), loss = 0.120073
I0405 15:57:31.939235  1863 solver.cpp:237]     Train net output #0: loss = 0.120073 (* 1 = 0.120073 loss)
I0405 15:57:31.939241  1863 sgd_solver.cpp:105] Iteration 18108, lr = 0.001
I0405 15:57:37.677301  1863 solver.cpp:218] Iteration 18120 (2.0913 iter/s, 5.73806s/12 iters), loss = 0.0877937
I0405 15:57:37.677455  1863 solver.cpp:237]     Train net output #0: loss = 0.0877935 (* 1 = 0.0877935 loss)
I0405 15:57:37.677465  1863 sgd_solver.cpp:105] Iteration 18120, lr = 0.001
I0405 15:57:43.088359  1863 solver.cpp:218] Iteration 18132 (2.21775 iter/s, 5.4109s/12 iters), loss = 0.115447
I0405 15:57:43.088408  1863 solver.cpp:237]     Train net output #0: loss = 0.115447 (* 1 = 0.115447 loss)
I0405 15:57:43.088418  1863 sgd_solver.cpp:105] Iteration 18132, lr = 0.001
I0405 15:57:48.526763  1863 solver.cpp:218] Iteration 18144 (2.20655 iter/s, 5.43834s/12 iters), loss = 0.0821013
I0405 15:57:48.526813  1863 solver.cpp:237]     Train net output #0: loss = 0.0821011 (* 1 = 0.0821011 loss)
I0405 15:57:48.526821  1863 sgd_solver.cpp:105] Iteration 18144, lr = 0.001
I0405 15:57:53.088646  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18156.caffemodel
I0405 15:57:56.161664  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18156.solverstate
I0405 15:57:58.513939  1863 solver.cpp:330] Iteration 18156, Testing net (#0)
I0405 15:57:58.513959  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:58:00.385864  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:58:02.958634  1863 solver.cpp:397]     Test net output #0: accuracy = 0.254902
I0405 15:58:02.958667  1863 solver.cpp:397]     Test net output #1: loss = 5.01661 (* 1 = 5.01661 loss)
I0405 15:58:03.090731  1863 solver.cpp:218] Iteration 18156 (0.823954 iter/s, 14.5639s/12 iters), loss = 0.0776264
I0405 15:58:03.090770  1863 solver.cpp:237]     Train net output #0: loss = 0.0776262 (* 1 = 0.0776262 loss)
I0405 15:58:03.090775  1863 sgd_solver.cpp:105] Iteration 18156, lr = 0.001
I0405 15:58:07.387310  1863 solver.cpp:218] Iteration 18168 (2.79295 iter/s, 4.29653s/12 iters), loss = 0.152347
I0405 15:58:07.387353  1863 solver.cpp:237]     Train net output #0: loss = 0.152347 (* 1 = 0.152347 loss)
I0405 15:58:07.387359  1863 sgd_solver.cpp:105] Iteration 18168, lr = 0.001
I0405 15:58:12.981356  1863 solver.cpp:218] Iteration 18180 (2.14516 iter/s, 5.594s/12 iters), loss = 0.168385
I0405 15:58:12.981467  1863 solver.cpp:237]     Train net output #0: loss = 0.168385 (* 1 = 0.168385 loss)
I0405 15:58:12.981477  1863 sgd_solver.cpp:105] Iteration 18180, lr = 0.001
I0405 15:58:18.387421  1863 solver.cpp:218] Iteration 18192 (2.21978 iter/s, 5.40594s/12 iters), loss = 0.0475029
I0405 15:58:18.387465  1863 solver.cpp:237]     Train net output #0: loss = 0.0475027 (* 1 = 0.0475027 loss)
I0405 15:58:18.387470  1863 sgd_solver.cpp:105] Iteration 18192, lr = 0.001
I0405 15:58:23.780184  1863 solver.cpp:218] Iteration 18204 (2.22523 iter/s, 5.39271s/12 iters), loss = 0.104033
I0405 15:58:23.780241  1863 solver.cpp:237]     Train net output #0: loss = 0.104032 (* 1 = 0.104032 loss)
I0405 15:58:23.780249  1863 sgd_solver.cpp:105] Iteration 18204, lr = 0.001
I0405 15:58:25.243258  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:58:29.269313  1863 solver.cpp:218] Iteration 18216 (2.18616 iter/s, 5.48907s/12 iters), loss = 0.0839577
I0405 15:58:29.269371  1863 solver.cpp:237]     Train net output #0: loss = 0.0839575 (* 1 = 0.0839575 loss)
I0405 15:58:29.269379  1863 sgd_solver.cpp:105] Iteration 18216, lr = 0.001
I0405 15:58:34.712821  1863 solver.cpp:218] Iteration 18228 (2.20449 iter/s, 5.44344s/12 iters), loss = 0.131933
I0405 15:58:34.712865  1863 solver.cpp:237]     Train net output #0: loss = 0.131933 (* 1 = 0.131933 loss)
I0405 15:58:34.712870  1863 sgd_solver.cpp:105] Iteration 18228, lr = 0.001
I0405 15:58:40.356137  1863 solver.cpp:218] Iteration 18240 (2.12643 iter/s, 5.64326s/12 iters), loss = 0.101992
I0405 15:58:40.356189  1863 solver.cpp:237]     Train net output #0: loss = 0.101991 (* 1 = 0.101991 loss)
I0405 15:58:40.356199  1863 sgd_solver.cpp:105] Iteration 18240, lr = 0.001
I0405 15:58:45.976963  1863 solver.cpp:218] Iteration 18252 (2.13494 iter/s, 5.62077s/12 iters), loss = 0.108439
I0405 15:58:45.977100  1863 solver.cpp:237]     Train net output #0: loss = 0.108439 (* 1 = 0.108439 loss)
I0405 15:58:45.977109  1863 sgd_solver.cpp:105] Iteration 18252, lr = 0.001
I0405 15:58:48.178169  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18258.caffemodel
I0405 15:58:51.346616  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18258.solverstate
I0405 15:58:53.733536  1863 solver.cpp:330] Iteration 18258, Testing net (#0)
I0405 15:58:53.733558  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:58:55.513995  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:58:58.235074  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275123
I0405 15:58:58.235100  1863 solver.cpp:397]     Test net output #1: loss = 4.91494 (* 1 = 4.91494 loss)
I0405 15:59:00.300298  1863 solver.cpp:218] Iteration 18264 (0.837801 iter/s, 14.3232s/12 iters), loss = 0.109018
I0405 15:59:00.300334  1863 solver.cpp:237]     Train net output #0: loss = 0.109018 (* 1 = 0.109018 loss)
I0405 15:59:00.300341  1863 sgd_solver.cpp:105] Iteration 18264, lr = 0.001
I0405 15:59:05.661703  1863 solver.cpp:218] Iteration 18276 (2.23824 iter/s, 5.36136s/12 iters), loss = 0.134942
I0405 15:59:05.661748  1863 solver.cpp:237]     Train net output #0: loss = 0.134942 (* 1 = 0.134942 loss)
I0405 15:59:05.661756  1863 sgd_solver.cpp:105] Iteration 18276, lr = 0.001
I0405 15:59:11.084678  1863 solver.cpp:218] Iteration 18288 (2.21283 iter/s, 5.42292s/12 iters), loss = 0.0717992
I0405 15:59:11.084726  1863 solver.cpp:237]     Train net output #0: loss = 0.071799 (* 1 = 0.071799 loss)
I0405 15:59:11.084734  1863 sgd_solver.cpp:105] Iteration 18288, lr = 0.001
I0405 15:59:16.429975  1863 solver.cpp:218] Iteration 18300 (2.24499 iter/s, 5.34524s/12 iters), loss = 0.0810068
I0405 15:59:16.430101  1863 solver.cpp:237]     Train net output #0: loss = 0.0810066 (* 1 = 0.0810066 loss)
I0405 15:59:16.430111  1863 sgd_solver.cpp:105] Iteration 18300, lr = 0.001
I0405 15:59:20.162441  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:59:21.929749  1863 solver.cpp:218] Iteration 18312 (2.18196 iter/s, 5.49964s/12 iters), loss = 0.134933
I0405 15:59:21.929788  1863 solver.cpp:237]     Train net output #0: loss = 0.134933 (* 1 = 0.134933 loss)
I0405 15:59:21.929795  1863 sgd_solver.cpp:105] Iteration 18312, lr = 0.001
I0405 15:59:27.303370  1863 solver.cpp:218] Iteration 18324 (2.23315 iter/s, 5.37357s/12 iters), loss = 0.075889
I0405 15:59:27.303417  1863 solver.cpp:237]     Train net output #0: loss = 0.0758888 (* 1 = 0.0758888 loss)
I0405 15:59:27.303426  1863 sgd_solver.cpp:105] Iteration 18324, lr = 0.001
I0405 15:59:32.692168  1863 solver.cpp:218] Iteration 18336 (2.22687 iter/s, 5.38874s/12 iters), loss = 0.156542
I0405 15:59:32.698554  1863 solver.cpp:237]     Train net output #0: loss = 0.156542 (* 1 = 0.156542 loss)
I0405 15:59:32.698565  1863 sgd_solver.cpp:105] Iteration 18336, lr = 0.001
I0405 15:59:38.062458  1863 solver.cpp:218] Iteration 18348 (2.23718 iter/s, 5.3639s/12 iters), loss = 0.106817
I0405 15:59:38.062508  1863 solver.cpp:237]     Train net output #0: loss = 0.106816 (* 1 = 0.106816 loss)
I0405 15:59:38.062516  1863 sgd_solver.cpp:105] Iteration 18348, lr = 0.001
I0405 15:59:42.842618  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18360.caffemodel
I0405 15:59:45.890581  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18360.solverstate
I0405 15:59:48.193171  1863 solver.cpp:330] Iteration 18360, Testing net (#0)
I0405 15:59:48.193271  1863 net.cpp:676] Ignoring source layer train-data
I0405 15:59:50.175827  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 15:59:52.886353  1863 solver.cpp:397]     Test net output #0: accuracy = 0.264706
I0405 15:59:52.886389  1863 solver.cpp:397]     Test net output #1: loss = 4.93629 (* 1 = 4.93629 loss)
I0405 15:59:53.027935  1863 solver.cpp:218] Iteration 18360 (0.801848 iter/s, 14.9654s/12 iters), loss = 0.0906655
I0405 15:59:53.027985  1863 solver.cpp:237]     Train net output #0: loss = 0.0906653 (* 1 = 0.0906653 loss)
I0405 15:59:53.027992  1863 sgd_solver.cpp:105] Iteration 18360, lr = 0.001
I0405 15:59:57.437088  1863 solver.cpp:218] Iteration 18372 (2.72165 iter/s, 4.40909s/12 iters), loss = 0.0968096
I0405 15:59:57.437146  1863 solver.cpp:237]     Train net output #0: loss = 0.0968094 (* 1 = 0.0968094 loss)
I0405 15:59:57.437155  1863 sgd_solver.cpp:105] Iteration 18372, lr = 0.001
I0405 16:00:02.648375  1863 solver.cpp:218] Iteration 18384 (2.30273 iter/s, 5.21122s/12 iters), loss = 0.0846527
I0405 16:00:02.648422  1863 solver.cpp:237]     Train net output #0: loss = 0.0846525 (* 1 = 0.0846525 loss)
I0405 16:00:02.648432  1863 sgd_solver.cpp:105] Iteration 18384, lr = 0.001
I0405 16:00:07.940902  1863 solver.cpp:218] Iteration 18396 (2.26738 iter/s, 5.29246s/12 iters), loss = 0.113568
I0405 16:00:07.940953  1863 solver.cpp:237]     Train net output #0: loss = 0.113568 (* 1 = 0.113568 loss)
I0405 16:00:07.940961  1863 sgd_solver.cpp:105] Iteration 18396, lr = 0.001
I0405 16:00:13.304942  1863 solver.cpp:218] Iteration 18408 (2.23714 iter/s, 5.36398s/12 iters), loss = 0.0920009
I0405 16:00:13.304991  1863 solver.cpp:237]     Train net output #0: loss = 0.0920007 (* 1 = 0.0920007 loss)
I0405 16:00:13.304999  1863 sgd_solver.cpp:105] Iteration 18408, lr = 0.001
I0405 16:00:13.900138  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:00:18.656574  1863 solver.cpp:218] Iteration 18420 (2.24233 iter/s, 5.35157s/12 iters), loss = 0.0431526
I0405 16:00:18.656690  1863 solver.cpp:237]     Train net output #0: loss = 0.0431524 (* 1 = 0.0431524 loss)
I0405 16:00:18.656699  1863 sgd_solver.cpp:105] Iteration 18420, lr = 0.001
I0405 16:00:23.984166  1863 solver.cpp:218] Iteration 18432 (2.25248 iter/s, 5.32746s/12 iters), loss = 0.04705
I0405 16:00:23.991015  1863 solver.cpp:237]     Train net output #0: loss = 0.0470498 (* 1 = 0.0470498 loss)
I0405 16:00:23.991030  1863 sgd_solver.cpp:105] Iteration 18432, lr = 0.001
I0405 16:00:29.405995  1863 solver.cpp:218] Iteration 18444 (2.21607 iter/s, 5.41498s/12 iters), loss = 0.13293
I0405 16:00:29.406038  1863 solver.cpp:237]     Train net output #0: loss = 0.132929 (* 1 = 0.132929 loss)
I0405 16:00:29.406044  1863 sgd_solver.cpp:105] Iteration 18444, lr = 0.001
I0405 16:00:34.786355  1863 solver.cpp:218] Iteration 18456 (2.23036 iter/s, 5.38031s/12 iters), loss = 0.0345672
I0405 16:00:34.786393  1863 solver.cpp:237]     Train net output #0: loss = 0.0345669 (* 1 = 0.0345669 loss)
I0405 16:00:34.786399  1863 sgd_solver.cpp:105] Iteration 18456, lr = 0.001
I0405 16:00:36.890235  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18462.caffemodel
I0405 16:00:39.983315  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18462.solverstate
I0405 16:00:42.292780  1863 solver.cpp:330] Iteration 18462, Testing net (#0)
I0405 16:00:42.292804  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:00:44.076323  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:00:46.786413  1863 solver.cpp:397]     Test net output #0: accuracy = 0.26777
I0405 16:00:46.786438  1863 solver.cpp:397]     Test net output #1: loss = 4.94218 (* 1 = 4.94218 loss)
I0405 16:00:48.863915  1863 solver.cpp:218] Iteration 18468 (0.852423 iter/s, 14.0775s/12 iters), loss = 0.0726097
I0405 16:00:48.864064  1863 solver.cpp:237]     Train net output #0: loss = 0.0726095 (* 1 = 0.0726095 loss)
I0405 16:00:48.864073  1863 sgd_solver.cpp:105] Iteration 18468, lr = 0.001
I0405 16:00:54.230835  1863 solver.cpp:218] Iteration 18480 (2.23598 iter/s, 5.36677s/12 iters), loss = 0.0498086
I0405 16:00:54.230883  1863 solver.cpp:237]     Train net output #0: loss = 0.0498084 (* 1 = 0.0498084 loss)
I0405 16:00:54.230890  1863 sgd_solver.cpp:105] Iteration 18480, lr = 0.001
I0405 16:00:59.699327  1863 solver.cpp:218] Iteration 18492 (2.19441 iter/s, 5.46843s/12 iters), loss = 0.111316
I0405 16:00:59.699376  1863 solver.cpp:237]     Train net output #0: loss = 0.111316 (* 1 = 0.111316 loss)
I0405 16:00:59.699384  1863 sgd_solver.cpp:105] Iteration 18492, lr = 0.001
I0405 16:01:05.161885  1863 solver.cpp:218] Iteration 18504 (2.1968 iter/s, 5.4625s/12 iters), loss = 0.0885672
I0405 16:01:05.161933  1863 solver.cpp:237]     Train net output #0: loss = 0.0885669 (* 1 = 0.0885669 loss)
I0405 16:01:05.161942  1863 sgd_solver.cpp:105] Iteration 18504, lr = 0.001
I0405 16:01:08.069648  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:01:10.562752  1863 solver.cpp:218] Iteration 18516 (2.22189 iter/s, 5.40081s/12 iters), loss = 0.0805926
I0405 16:01:10.562798  1863 solver.cpp:237]     Train net output #0: loss = 0.0805923 (* 1 = 0.0805923 loss)
I0405 16:01:10.562805  1863 sgd_solver.cpp:105] Iteration 18516, lr = 0.001
I0405 16:01:15.556365  1863 solver.cpp:218] Iteration 18528 (2.4031 iter/s, 4.99355s/12 iters), loss = 0.0559018
I0405 16:01:15.556433  1863 solver.cpp:237]     Train net output #0: loss = 0.0559015 (* 1 = 0.0559015 loss)
I0405 16:01:15.556443  1863 sgd_solver.cpp:105] Iteration 18528, lr = 0.001
I0405 16:01:21.100355  1863 solver.cpp:218] Iteration 18540 (2.16454 iter/s, 5.54391s/12 iters), loss = 0.0522086
I0405 16:01:21.100457  1863 solver.cpp:237]     Train net output #0: loss = 0.0522083 (* 1 = 0.0522083 loss)
I0405 16:01:21.100464  1863 sgd_solver.cpp:105] Iteration 18540, lr = 0.001
I0405 16:01:26.474040  1863 solver.cpp:218] Iteration 18552 (2.23315 iter/s, 5.37357s/12 iters), loss = 0.0154265
I0405 16:01:26.474086  1863 solver.cpp:237]     Train net output #0: loss = 0.0154263 (* 1 = 0.0154263 loss)
I0405 16:01:26.474092  1863 sgd_solver.cpp:105] Iteration 18552, lr = 0.001
I0405 16:01:31.282681  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18564.caffemodel
I0405 16:01:34.398553  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18564.solverstate
I0405 16:01:36.702215  1863 solver.cpp:330] Iteration 18564, Testing net (#0)
I0405 16:01:36.702234  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:01:38.463384  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:01:41.369926  1863 solver.cpp:397]     Test net output #0: accuracy = 0.269608
I0405 16:01:41.369964  1863 solver.cpp:397]     Test net output #1: loss = 5.05712 (* 1 = 5.05712 loss)
I0405 16:01:41.506923  1863 solver.cpp:218] Iteration 18564 (0.798253 iter/s, 15.0328s/12 iters), loss = 0.0657634
I0405 16:01:41.506968  1863 solver.cpp:237]     Train net output #0: loss = 0.0657632 (* 1 = 0.0657632 loss)
I0405 16:01:41.506975  1863 sgd_solver.cpp:105] Iteration 18564, lr = 0.001
I0405 16:01:45.804625  1863 solver.cpp:218] Iteration 18576 (2.79223 iter/s, 4.29765s/12 iters), loss = 0.107298
I0405 16:01:45.804662  1863 solver.cpp:237]     Train net output #0: loss = 0.107297 (* 1 = 0.107297 loss)
I0405 16:01:45.804667  1863 sgd_solver.cpp:105] Iteration 18576, lr = 0.001
I0405 16:01:51.126147  1863 solver.cpp:218] Iteration 18588 (2.25502 iter/s, 5.32147s/12 iters), loss = 0.0302681
I0405 16:01:51.126288  1863 solver.cpp:237]     Train net output #0: loss = 0.0302678 (* 1 = 0.0302678 loss)
I0405 16:01:51.126294  1863 sgd_solver.cpp:105] Iteration 18588, lr = 0.001
I0405 16:01:56.475045  1863 solver.cpp:218] Iteration 18600 (2.24352 iter/s, 5.34874s/12 iters), loss = 0.0300937
I0405 16:01:56.475095  1863 solver.cpp:237]     Train net output #0: loss = 0.0300934 (* 1 = 0.0300934 loss)
I0405 16:01:56.475102  1863 sgd_solver.cpp:105] Iteration 18600, lr = 0.001
I0405 16:02:01.709115  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:02:01.927681  1863 solver.cpp:218] Iteration 18612 (2.2008 iter/s, 5.45257s/12 iters), loss = 0.0917538
I0405 16:02:01.927724  1863 solver.cpp:237]     Train net output #0: loss = 0.0917535 (* 1 = 0.0917535 loss)
I0405 16:02:01.927729  1863 sgd_solver.cpp:105] Iteration 18612, lr = 0.001
I0405 16:02:07.286226  1863 solver.cpp:218] Iteration 18624 (2.23944 iter/s, 5.35848s/12 iters), loss = 0.133496
I0405 16:02:07.286279  1863 solver.cpp:237]     Train net output #0: loss = 0.133496 (* 1 = 0.133496 loss)
I0405 16:02:07.286288  1863 sgd_solver.cpp:105] Iteration 18624, lr = 0.001
I0405 16:02:12.757885  1863 solver.cpp:218] Iteration 18636 (2.19314 iter/s, 5.4716s/12 iters), loss = 0.118598
I0405 16:02:12.757925  1863 solver.cpp:237]     Train net output #0: loss = 0.118598 (* 1 = 0.118598 loss)
I0405 16:02:12.757930  1863 sgd_solver.cpp:105] Iteration 18636, lr = 0.001
I0405 16:02:18.133522  1863 solver.cpp:218] Iteration 18648 (2.23231 iter/s, 5.37559s/12 iters), loss = 0.0679833
I0405 16:02:18.133563  1863 solver.cpp:237]     Train net output #0: loss = 0.067983 (* 1 = 0.067983 loss)
I0405 16:02:18.133567  1863 sgd_solver.cpp:105] Iteration 18648, lr = 0.001
I0405 16:02:23.310984  1863 solver.cpp:218] Iteration 18660 (2.31776 iter/s, 5.17741s/12 iters), loss = 0.0968857
I0405 16:02:23.311094  1863 solver.cpp:237]     Train net output #0: loss = 0.0968854 (* 1 = 0.0968854 loss)
I0405 16:02:23.311101  1863 sgd_solver.cpp:105] Iteration 18660, lr = 0.001
I0405 16:02:25.528530  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18666.caffemodel
I0405 16:02:28.600234  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18666.solverstate
I0405 16:02:31.300133  1863 solver.cpp:330] Iteration 18666, Testing net (#0)
I0405 16:02:31.300155  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:02:33.064041  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:02:35.830170  1863 solver.cpp:397]     Test net output #0: accuracy = 0.273284
I0405 16:02:35.830197  1863 solver.cpp:397]     Test net output #1: loss = 5.0201 (* 1 = 5.0201 loss)
I0405 16:02:37.841818  1863 solver.cpp:218] Iteration 18672 (0.825836 iter/s, 14.5307s/12 iters), loss = 0.10551
I0405 16:02:37.841861  1863 solver.cpp:237]     Train net output #0: loss = 0.105509 (* 1 = 0.105509 loss)
I0405 16:02:37.841866  1863 sgd_solver.cpp:105] Iteration 18672, lr = 0.001
I0405 16:02:43.242686  1863 solver.cpp:218] Iteration 18684 (2.22189 iter/s, 5.40081s/12 iters), loss = 0.0717138
I0405 16:02:43.242734  1863 solver.cpp:237]     Train net output #0: loss = 0.0717136 (* 1 = 0.0717136 loss)
I0405 16:02:43.242743  1863 sgd_solver.cpp:105] Iteration 18684, lr = 0.001
I0405 16:02:48.750408  1863 solver.cpp:218] Iteration 18696 (2.17878 iter/s, 5.50767s/12 iters), loss = 0.0642408
I0405 16:02:48.750460  1863 solver.cpp:237]     Train net output #0: loss = 0.0642405 (* 1 = 0.0642405 loss)
I0405 16:02:48.750469  1863 sgd_solver.cpp:105] Iteration 18696, lr = 0.001
I0405 16:02:54.055546  1863 solver.cpp:218] Iteration 18708 (2.26198 iter/s, 5.30508s/12 iters), loss = 0.116615
I0405 16:02:54.055649  1863 solver.cpp:237]     Train net output #0: loss = 0.116615 (* 1 = 0.116615 loss)
I0405 16:02:54.055656  1863 sgd_solver.cpp:105] Iteration 18708, lr = 0.001
I0405 16:02:55.943656  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:02:59.221185  1863 solver.cpp:218] Iteration 18720 (2.32309 iter/s, 5.16552s/12 iters), loss = 0.0477286
I0405 16:02:59.221241  1863 solver.cpp:237]     Train net output #0: loss = 0.0477283 (* 1 = 0.0477283 loss)
I0405 16:02:59.221249  1863 sgd_solver.cpp:105] Iteration 18720, lr = 0.001
I0405 16:02:59.640522  1863 blocking_queue.cpp:49] Waiting for data
I0405 16:03:04.860404  1863 solver.cpp:218] Iteration 18732 (2.12798 iter/s, 5.63916s/12 iters), loss = 0.0390373
I0405 16:03:04.860443  1863 solver.cpp:237]     Train net output #0: loss = 0.0390371 (* 1 = 0.0390371 loss)
I0405 16:03:04.860448  1863 sgd_solver.cpp:105] Iteration 18732, lr = 0.001
I0405 16:03:10.364243  1863 solver.cpp:218] Iteration 18744 (2.18032 iter/s, 5.50379s/12 iters), loss = 0.0824953
I0405 16:03:10.364292  1863 solver.cpp:237]     Train net output #0: loss = 0.0824951 (* 1 = 0.0824951 loss)
I0405 16:03:10.364301  1863 sgd_solver.cpp:105] Iteration 18744, lr = 0.001
I0405 16:03:15.517050  1863 solver.cpp:218] Iteration 18756 (2.32886 iter/s, 5.15275s/12 iters), loss = 0.111714
I0405 16:03:15.517103  1863 solver.cpp:237]     Train net output #0: loss = 0.111713 (* 1 = 0.111713 loss)
I0405 16:03:15.517113  1863 sgd_solver.cpp:105] Iteration 18756, lr = 0.001
I0405 16:03:20.496136  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18768.caffemodel
I0405 16:03:23.611178  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18768.solverstate
I0405 16:03:25.914064  1863 solver.cpp:330] Iteration 18768, Testing net (#0)
I0405 16:03:25.914160  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:03:27.550374  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:03:30.466688  1863 solver.cpp:397]     Test net output #0: accuracy = 0.278186
I0405 16:03:30.466714  1863 solver.cpp:397]     Test net output #1: loss = 5.03361 (* 1 = 5.03361 loss)
I0405 16:03:30.601199  1863 solver.cpp:218] Iteration 18768 (0.795539 iter/s, 15.0841s/12 iters), loss = 0.0198451
I0405 16:03:30.601260  1863 solver.cpp:237]     Train net output #0: loss = 0.0198449 (* 1 = 0.0198449 loss)
I0405 16:03:30.601269  1863 sgd_solver.cpp:105] Iteration 18768, lr = 0.001
I0405 16:03:35.059125  1863 solver.cpp:218] Iteration 18780 (2.69188 iter/s, 4.45786s/12 iters), loss = 0.135609
I0405 16:03:35.059165  1863 solver.cpp:237]     Train net output #0: loss = 0.135609 (* 1 = 0.135609 loss)
I0405 16:03:35.059170  1863 sgd_solver.cpp:105] Iteration 18780, lr = 0.001
I0405 16:03:40.306129  1863 solver.cpp:218] Iteration 18792 (2.28704 iter/s, 5.24695s/12 iters), loss = 0.0376115
I0405 16:03:40.306188  1863 solver.cpp:237]     Train net output #0: loss = 0.0376112 (* 1 = 0.0376112 loss)
I0405 16:03:40.306197  1863 sgd_solver.cpp:105] Iteration 18792, lr = 0.001
I0405 16:03:45.886320  1863 solver.cpp:218] Iteration 18804 (2.15049 iter/s, 5.58012s/12 iters), loss = 0.0914439
I0405 16:03:45.886370  1863 solver.cpp:237]     Train net output #0: loss = 0.0914436 (* 1 = 0.0914436 loss)
I0405 16:03:45.886377  1863 sgd_solver.cpp:105] Iteration 18804, lr = 0.001
I0405 16:03:50.329568  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:03:51.202764  1863 solver.cpp:218] Iteration 18816 (2.25717 iter/s, 5.31638s/12 iters), loss = 0.0756971
I0405 16:03:51.202821  1863 solver.cpp:237]     Train net output #0: loss = 0.0756968 (* 1 = 0.0756968 loss)
I0405 16:03:51.202826  1863 sgd_solver.cpp:105] Iteration 18816, lr = 0.001
I0405 16:03:56.515422  1863 solver.cpp:218] Iteration 18828 (2.25878 iter/s, 5.31259s/12 iters), loss = 0.0947303
I0405 16:03:56.515522  1863 solver.cpp:237]     Train net output #0: loss = 0.0947301 (* 1 = 0.0947301 loss)
I0405 16:03:56.515528  1863 sgd_solver.cpp:105] Iteration 18828, lr = 0.001
I0405 16:04:01.536909  1863 solver.cpp:218] Iteration 18840 (2.38979 iter/s, 5.02137s/12 iters), loss = 0.0445802
I0405 16:04:01.536964  1863 solver.cpp:237]     Train net output #0: loss = 0.04458 (* 1 = 0.04458 loss)
I0405 16:04:01.536975  1863 sgd_solver.cpp:105] Iteration 18840, lr = 0.001
I0405 16:04:06.883733  1863 solver.cpp:218] Iteration 18852 (2.24435 iter/s, 5.34676s/12 iters), loss = 0.0343439
I0405 16:04:06.883771  1863 solver.cpp:237]     Train net output #0: loss = 0.0343436 (* 1 = 0.0343436 loss)
I0405 16:04:06.883777  1863 sgd_solver.cpp:105] Iteration 18852, lr = 0.001
I0405 16:04:12.367458  1863 solver.cpp:218] Iteration 18864 (2.18831 iter/s, 5.48368s/12 iters), loss = 0.0959626
I0405 16:04:12.367497  1863 solver.cpp:237]     Train net output #0: loss = 0.0959624 (* 1 = 0.0959624 loss)
I0405 16:04:12.367502  1863 sgd_solver.cpp:105] Iteration 18864, lr = 0.001
I0405 16:04:14.544800  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18870.caffemodel
I0405 16:04:17.614213  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18870.solverstate
I0405 16:04:19.931488  1863 solver.cpp:330] Iteration 18870, Testing net (#0)
I0405 16:04:19.931509  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:04:21.581364  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:04:24.431247  1863 solver.cpp:397]     Test net output #0: accuracy = 0.273284
I0405 16:04:24.431286  1863 solver.cpp:397]     Test net output #1: loss = 5.08846 (* 1 = 5.08846 loss)
I0405 16:04:26.246273  1863 solver.cpp:218] Iteration 18876 (0.864629 iter/s, 13.8788s/12 iters), loss = 0.0363258
I0405 16:04:26.246312  1863 solver.cpp:237]     Train net output #0: loss = 0.0363255 (* 1 = 0.0363255 loss)
I0405 16:04:26.246317  1863 sgd_solver.cpp:105] Iteration 18876, lr = 0.001
I0405 16:04:31.518616  1863 solver.cpp:218] Iteration 18888 (2.27605 iter/s, 5.27229s/12 iters), loss = 0.105201
I0405 16:04:31.518764  1863 solver.cpp:237]     Train net output #0: loss = 0.105201 (* 1 = 0.105201 loss)
I0405 16:04:31.518772  1863 sgd_solver.cpp:105] Iteration 18888, lr = 0.001
I0405 16:04:36.671512  1863 solver.cpp:218] Iteration 18900 (2.32886 iter/s, 5.15274s/12 iters), loss = 0.0574041
I0405 16:04:36.671563  1863 solver.cpp:237]     Train net output #0: loss = 0.0574039 (* 1 = 0.0574039 loss)
I0405 16:04:36.671571  1863 sgd_solver.cpp:105] Iteration 18900, lr = 0.001
I0405 16:04:42.083483  1863 solver.cpp:218] Iteration 18912 (2.21733 iter/s, 5.41192s/12 iters), loss = 0.0747
I0405 16:04:42.083523  1863 solver.cpp:237]     Train net output #0: loss = 0.0746998 (* 1 = 0.0746998 loss)
I0405 16:04:42.083528  1863 sgd_solver.cpp:105] Iteration 18912, lr = 0.001
I0405 16:04:43.494988  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:04:47.532348  1863 solver.cpp:218] Iteration 18924 (2.20232 iter/s, 5.44881s/12 iters), loss = 0.0816717
I0405 16:04:47.532407  1863 solver.cpp:237]     Train net output #0: loss = 0.0816715 (* 1 = 0.0816715 loss)
I0405 16:04:47.532415  1863 sgd_solver.cpp:105] Iteration 18924, lr = 0.001
I0405 16:04:52.816012  1863 solver.cpp:218] Iteration 18936 (2.27118 iter/s, 5.2836s/12 iters), loss = 0.111925
I0405 16:04:52.816054  1863 solver.cpp:237]     Train net output #0: loss = 0.111925 (* 1 = 0.111925 loss)
I0405 16:04:52.816059  1863 sgd_solver.cpp:105] Iteration 18936, lr = 0.001
I0405 16:04:58.306407  1863 solver.cpp:218] Iteration 18948 (2.18566 iter/s, 5.49034s/12 iters), loss = 0.104571
I0405 16:04:58.306454  1863 solver.cpp:237]     Train net output #0: loss = 0.10457 (* 1 = 0.10457 loss)
I0405 16:04:58.306463  1863 sgd_solver.cpp:105] Iteration 18948, lr = 0.001
I0405 16:05:03.525456  1863 solver.cpp:218] Iteration 18960 (2.29929 iter/s, 5.21899s/12 iters), loss = 0.103633
I0405 16:05:03.525570  1863 solver.cpp:237]     Train net output #0: loss = 0.103633 (* 1 = 0.103633 loss)
I0405 16:05:03.525579  1863 sgd_solver.cpp:105] Iteration 18960, lr = 0.001
I0405 16:05:08.629078  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_18972.caffemodel
I0405 16:05:13.732471  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_18972.solverstate
I0405 16:05:16.119752  1863 solver.cpp:330] Iteration 18972, Testing net (#0)
I0405 16:05:16.119771  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:05:17.705462  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:05:20.674942  1863 solver.cpp:397]     Test net output #0: accuracy = 0.281863
I0405 16:05:20.674978  1863 solver.cpp:397]     Test net output #1: loss = 4.96826 (* 1 = 4.96826 loss)
I0405 16:05:20.810508  1863 solver.cpp:218] Iteration 18972 (0.694246 iter/s, 17.285s/12 iters), loss = 0.0886875
I0405 16:05:20.810550  1863 solver.cpp:237]     Train net output #0: loss = 0.0886873 (* 1 = 0.0886873 loss)
I0405 16:05:20.810556  1863 sgd_solver.cpp:105] Iteration 18972, lr = 0.001
I0405 16:05:25.060667  1863 solver.cpp:218] Iteration 18984 (2.82346 iter/s, 4.25011s/12 iters), loss = 0.0575351
I0405 16:05:25.060705  1863 solver.cpp:237]     Train net output #0: loss = 0.0575349 (* 1 = 0.0575349 loss)
I0405 16:05:25.060710  1863 sgd_solver.cpp:105] Iteration 18984, lr = 0.001
I0405 16:05:30.375815  1863 solver.cpp:218] Iteration 18996 (2.25772 iter/s, 5.3151s/12 iters), loss = 0.0940318
I0405 16:05:30.375857  1863 solver.cpp:237]     Train net output #0: loss = 0.0940316 (* 1 = 0.0940316 loss)
I0405 16:05:30.375866  1863 sgd_solver.cpp:105] Iteration 18996, lr = 0.001
I0405 16:05:35.609578  1863 solver.cpp:218] Iteration 19008 (2.29283 iter/s, 5.23371s/12 iters), loss = 0.0643616
I0405 16:05:35.609730  1863 solver.cpp:237]     Train net output #0: loss = 0.0643613 (* 1 = 0.0643613 loss)
I0405 16:05:35.609738  1863 sgd_solver.cpp:105] Iteration 19008, lr = 0.001
I0405 16:05:39.242020  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:05:40.719084  1863 solver.cpp:218] Iteration 19020 (2.34863 iter/s, 5.10935s/12 iters), loss = 0.204462
I0405 16:05:40.719123  1863 solver.cpp:237]     Train net output #0: loss = 0.204461 (* 1 = 0.204461 loss)
I0405 16:05:40.719130  1863 sgd_solver.cpp:105] Iteration 19020, lr = 0.001
I0405 16:05:45.889765  1863 solver.cpp:218] Iteration 19032 (2.3208 iter/s, 5.17063s/12 iters), loss = 0.181539
I0405 16:05:45.889811  1863 solver.cpp:237]     Train net output #0: loss = 0.181539 (* 1 = 0.181539 loss)
I0405 16:05:45.889816  1863 sgd_solver.cpp:105] Iteration 19032, lr = 0.001
I0405 16:05:51.021988  1863 solver.cpp:218] Iteration 19044 (2.33819 iter/s, 5.13217s/12 iters), loss = 0.0377821
I0405 16:05:51.022028  1863 solver.cpp:237]     Train net output #0: loss = 0.0377818 (* 1 = 0.0377818 loss)
I0405 16:05:51.022034  1863 sgd_solver.cpp:105] Iteration 19044, lr = 0.001
I0405 16:05:56.185720  1863 solver.cpp:218] Iteration 19056 (2.32392 iter/s, 5.16368s/12 iters), loss = 0.0947779
I0405 16:05:56.185767  1863 solver.cpp:237]     Train net output #0: loss = 0.0947777 (* 1 = 0.0947777 loss)
I0405 16:05:56.185775  1863 sgd_solver.cpp:105] Iteration 19056, lr = 0.001
I0405 16:06:01.433756  1863 solver.cpp:218] Iteration 19068 (2.28659 iter/s, 5.24798s/12 iters), loss = 0.0813545
I0405 16:06:01.433797  1863 solver.cpp:237]     Train net output #0: loss = 0.0813543 (* 1 = 0.0813543 loss)
I0405 16:06:01.433802  1863 sgd_solver.cpp:105] Iteration 19068, lr = 0.001
I0405 16:06:03.502442  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19074.caffemodel
I0405 16:06:06.512296  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19074.solverstate
I0405 16:06:08.833639  1863 solver.cpp:330] Iteration 19074, Testing net (#0)
I0405 16:06:08.833663  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:06:10.337307  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:06:13.241422  1863 solver.cpp:397]     Test net output #0: accuracy = 0.278799
I0405 16:06:13.241456  1863 solver.cpp:397]     Test net output #1: loss = 4.94617 (* 1 = 4.94617 loss)
I0405 16:06:15.049726  1863 solver.cpp:218] Iteration 19080 (0.881321 iter/s, 13.6159s/12 iters), loss = 0.058972
I0405 16:06:15.049778  1863 solver.cpp:237]     Train net output #0: loss = 0.0589718 (* 1 = 0.0589718 loss)
I0405 16:06:15.049787  1863 sgd_solver.cpp:105] Iteration 19080, lr = 0.001
I0405 16:06:20.212548  1863 solver.cpp:218] Iteration 19092 (2.32434 iter/s, 5.16276s/12 iters), loss = 0.0939727
I0405 16:06:20.212589  1863 solver.cpp:237]     Train net output #0: loss = 0.0939724 (* 1 = 0.0939724 loss)
I0405 16:06:20.212594  1863 sgd_solver.cpp:105] Iteration 19092, lr = 0.001
I0405 16:06:25.427592  1863 solver.cpp:218] Iteration 19104 (2.30106 iter/s, 5.21499s/12 iters), loss = 0.0820165
I0405 16:06:25.427639  1863 solver.cpp:237]     Train net output #0: loss = 0.0820162 (* 1 = 0.0820162 loss)
I0405 16:06:25.427645  1863 sgd_solver.cpp:105] Iteration 19104, lr = 0.001
I0405 16:06:30.683851  1863 solver.cpp:218] Iteration 19116 (2.28302 iter/s, 5.2562s/12 iters), loss = 0.0211509
I0405 16:06:30.683909  1863 solver.cpp:237]     Train net output #0: loss = 0.0211507 (* 1 = 0.0211507 loss)
I0405 16:06:30.683918  1863 sgd_solver.cpp:105] Iteration 19116, lr = 0.001
I0405 16:06:31.296388  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:06:35.972560  1863 solver.cpp:218] Iteration 19128 (2.26901 iter/s, 5.28865s/12 iters), loss = 0.0384291
I0405 16:06:35.972602  1863 solver.cpp:237]     Train net output #0: loss = 0.0384289 (* 1 = 0.0384289 loss)
I0405 16:06:35.972609  1863 sgd_solver.cpp:105] Iteration 19128, lr = 0.001
I0405 16:06:41.330039  1863 solver.cpp:218] Iteration 19140 (2.23988 iter/s, 5.35742s/12 iters), loss = 0.0582012
I0405 16:06:41.330160  1863 solver.cpp:237]     Train net output #0: loss = 0.058201 (* 1 = 0.058201 loss)
I0405 16:06:41.330169  1863 sgd_solver.cpp:105] Iteration 19140, lr = 0.001
I0405 16:06:46.443127  1863 solver.cpp:218] Iteration 19152 (2.34698 iter/s, 5.11296s/12 iters), loss = 0.0621474
I0405 16:06:46.443176  1863 solver.cpp:237]     Train net output #0: loss = 0.0621472 (* 1 = 0.0621472 loss)
I0405 16:06:46.443181  1863 sgd_solver.cpp:105] Iteration 19152, lr = 0.001
I0405 16:06:51.895231  1863 solver.cpp:218] Iteration 19164 (2.20101 iter/s, 5.45205s/12 iters), loss = 0.114726
I0405 16:06:51.895284  1863 solver.cpp:237]     Train net output #0: loss = 0.114726 (* 1 = 0.114726 loss)
I0405 16:06:51.895292  1863 sgd_solver.cpp:105] Iteration 19164, lr = 0.001
I0405 16:06:56.661104  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19176.caffemodel
I0405 16:06:59.679877  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19176.solverstate
I0405 16:07:02.004302  1863 solver.cpp:330] Iteration 19176, Testing net (#0)
I0405 16:07:02.004330  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:07:03.481367  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:07:06.436982  1863 solver.cpp:397]     Test net output #0: accuracy = 0.276348
I0405 16:07:06.437031  1863 solver.cpp:397]     Test net output #1: loss = 4.92804 (* 1 = 4.92804 loss)
I0405 16:07:06.578390  1863 solver.cpp:218] Iteration 19176 (0.817266 iter/s, 14.6831s/12 iters), loss = 0.189364
I0405 16:07:06.578436  1863 solver.cpp:237]     Train net output #0: loss = 0.189364 (* 1 = 0.189364 loss)
I0405 16:07:06.578444  1863 sgd_solver.cpp:105] Iteration 19176, lr = 0.001
I0405 16:07:10.610024  1863 solver.cpp:218] Iteration 19188 (2.9765 iter/s, 4.03158s/12 iters), loss = 0.06787
I0405 16:07:10.610061  1863 solver.cpp:237]     Train net output #0: loss = 0.0678697 (* 1 = 0.0678697 loss)
I0405 16:07:10.610066  1863 sgd_solver.cpp:105] Iteration 19188, lr = 0.001
I0405 16:07:15.837347  1863 solver.cpp:218] Iteration 19200 (2.29565 iter/s, 5.22728s/12 iters), loss = 0.0577622
I0405 16:07:15.837469  1863 solver.cpp:237]     Train net output #0: loss = 0.057762 (* 1 = 0.057762 loss)
I0405 16:07:15.837481  1863 sgd_solver.cpp:105] Iteration 19200, lr = 0.001
I0405 16:07:21.027806  1863 solver.cpp:218] Iteration 19212 (2.31199 iter/s, 5.19033s/12 iters), loss = 0.045471
I0405 16:07:21.027860  1863 solver.cpp:237]     Train net output #0: loss = 0.0454707 (* 1 = 0.0454707 loss)
I0405 16:07:21.027871  1863 sgd_solver.cpp:105] Iteration 19212, lr = 0.001
I0405 16:07:23.841545  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:07:26.336241  1863 solver.cpp:218] Iteration 19224 (2.26058 iter/s, 5.30837s/12 iters), loss = 0.0803856
I0405 16:07:26.336288  1863 solver.cpp:237]     Train net output #0: loss = 0.0803854 (* 1 = 0.0803854 loss)
I0405 16:07:26.336297  1863 sgd_solver.cpp:105] Iteration 19224, lr = 0.001
I0405 16:07:31.660365  1863 solver.cpp:218] Iteration 19236 (2.25392 iter/s, 5.32407s/12 iters), loss = 0.0674624
I0405 16:07:31.660419  1863 solver.cpp:237]     Train net output #0: loss = 0.0674622 (* 1 = 0.0674622 loss)
I0405 16:07:31.660429  1863 sgd_solver.cpp:105] Iteration 19236, lr = 0.001
I0405 16:07:36.800173  1863 solver.cpp:218] Iteration 19248 (2.33475 iter/s, 5.13974s/12 iters), loss = 0.0503117
I0405 16:07:36.800215  1863 solver.cpp:237]     Train net output #0: loss = 0.0503115 (* 1 = 0.0503115 loss)
I0405 16:07:36.800220  1863 sgd_solver.cpp:105] Iteration 19248, lr = 0.001
I0405 16:07:42.146122  1863 solver.cpp:218] Iteration 19260 (2.24471 iter/s, 5.3459s/12 iters), loss = 0.0239985
I0405 16:07:42.146175  1863 solver.cpp:237]     Train net output #0: loss = 0.0239983 (* 1 = 0.0239983 loss)
I0405 16:07:42.146183  1863 sgd_solver.cpp:105] Iteration 19260, lr = 0.001
I0405 16:07:47.380095  1863 solver.cpp:218] Iteration 19272 (2.29274 iter/s, 5.23391s/12 iters), loss = 0.0976117
I0405 16:07:47.380266  1863 solver.cpp:237]     Train net output #0: loss = 0.0976115 (* 1 = 0.0976115 loss)
I0405 16:07:47.380275  1863 sgd_solver.cpp:105] Iteration 19272, lr = 0.001
I0405 16:07:49.558952  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19278.caffemodel
I0405 16:07:52.563391  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19278.solverstate
I0405 16:07:54.914180  1863 solver.cpp:330] Iteration 19278, Testing net (#0)
I0405 16:07:54.914203  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:07:56.384506  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:07:59.368976  1863 solver.cpp:397]     Test net output #0: accuracy = 0.275735
I0405 16:07:59.369004  1863 solver.cpp:397]     Test net output #1: loss = 4.94406 (* 1 = 4.94406 loss)
I0405 16:08:01.331707  1863 solver.cpp:218] Iteration 19284 (0.860126 iter/s, 13.9515s/12 iters), loss = 0.126471
I0405 16:08:01.331755  1863 solver.cpp:237]     Train net output #0: loss = 0.126471 (* 1 = 0.126471 loss)
I0405 16:08:01.331763  1863 sgd_solver.cpp:105] Iteration 19284, lr = 0.001
I0405 16:08:06.421198  1863 solver.cpp:218] Iteration 19296 (2.35783 iter/s, 5.08943s/12 iters), loss = 0.0654673
I0405 16:08:06.421257  1863 solver.cpp:237]     Train net output #0: loss = 0.0654671 (* 1 = 0.0654671 loss)
I0405 16:08:06.421267  1863 sgd_solver.cpp:105] Iteration 19296, lr = 0.001
I0405 16:08:11.737960  1863 solver.cpp:218] Iteration 19308 (2.25704 iter/s, 5.31669s/12 iters), loss = 0.0674534
I0405 16:08:11.738019  1863 solver.cpp:237]     Train net output #0: loss = 0.0674532 (* 1 = 0.0674532 loss)
I0405 16:08:11.738029  1863 sgd_solver.cpp:105] Iteration 19308, lr = 0.001
I0405 16:08:16.931113  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:08:17.124769  1863 solver.cpp:218] Iteration 19320 (2.22769 iter/s, 5.38675s/12 iters), loss = 0.023629
I0405 16:08:17.124809  1863 solver.cpp:237]     Train net output #0: loss = 0.0236287 (* 1 = 0.0236287 loss)
I0405 16:08:17.124816  1863 sgd_solver.cpp:105] Iteration 19320, lr = 0.001
I0405 16:08:22.466356  1863 solver.cpp:218] Iteration 19332 (2.24654 iter/s, 5.34154s/12 iters), loss = 0.194694
I0405 16:08:22.466452  1863 solver.cpp:237]     Train net output #0: loss = 0.194694 (* 1 = 0.194694 loss)
I0405 16:08:22.466459  1863 sgd_solver.cpp:105] Iteration 19332, lr = 0.001
I0405 16:08:27.822186  1863 solver.cpp:218] Iteration 19344 (2.24059 iter/s, 5.35573s/12 iters), loss = 0.0460713
I0405 16:08:27.822229  1863 solver.cpp:237]     Train net output #0: loss = 0.046071 (* 1 = 0.046071 loss)
I0405 16:08:27.822235  1863 sgd_solver.cpp:105] Iteration 19344, lr = 0.001
I0405 16:08:33.033059  1863 solver.cpp:218] Iteration 19356 (2.3029 iter/s, 5.21082s/12 iters), loss = 0.080843
I0405 16:08:33.033108  1863 solver.cpp:237]     Train net output #0: loss = 0.0808428 (* 1 = 0.0808428 loss)
I0405 16:08:33.033115  1863 sgd_solver.cpp:105] Iteration 19356, lr = 0.001
I0405 16:08:38.362823  1863 solver.cpp:218] Iteration 19368 (2.25153 iter/s, 5.32971s/12 iters), loss = 0.0443632
I0405 16:08:38.362864  1863 solver.cpp:237]     Train net output #0: loss = 0.0443629 (* 1 = 0.0443629 loss)
I0405 16:08:38.362869  1863 sgd_solver.cpp:105] Iteration 19368, lr = 0.001
I0405 16:08:43.049484  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19380.caffemodel
I0405 16:08:46.044734  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19380.solverstate
I0405 16:08:48.362123  1863 solver.cpp:330] Iteration 19380, Testing net (#0)
I0405 16:08:48.362147  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:08:49.850826  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:08:52.784224  1863 solver.cpp:397]     Test net output #0: accuracy = 0.279412
I0405 16:08:52.784355  1863 solver.cpp:397]     Test net output #1: loss = 5.06009 (* 1 = 5.06009 loss)
I0405 16:08:52.919445  1863 solver.cpp:218] Iteration 19380 (0.824369 iter/s, 14.5566s/12 iters), loss = 0.142575
I0405 16:08:52.921036  1863 solver.cpp:237]     Train net output #0: loss = 0.142574 (* 1 = 0.142574 loss)
I0405 16:08:52.921049  1863 sgd_solver.cpp:105] Iteration 19380, lr = 0.001
I0405 16:08:57.219846  1863 solver.cpp:218] Iteration 19392 (2.79147 iter/s, 4.29881s/12 iters), loss = 0.040014
I0405 16:08:57.219914  1863 solver.cpp:237]     Train net output #0: loss = 0.0400138 (* 1 = 0.0400138 loss)
I0405 16:08:57.219921  1863 sgd_solver.cpp:105] Iteration 19392, lr = 0.001
I0405 16:09:02.369670  1863 solver.cpp:218] Iteration 19404 (2.33021 iter/s, 5.14975s/12 iters), loss = 0.104372
I0405 16:09:02.369712  1863 solver.cpp:237]     Train net output #0: loss = 0.104371 (* 1 = 0.104371 loss)
I0405 16:09:02.369719  1863 sgd_solver.cpp:105] Iteration 19404, lr = 0.001
I0405 16:09:03.167845  1863 blocking_queue.cpp:49] Waiting for data
I0405 16:09:07.610674  1863 solver.cpp:218] Iteration 19416 (2.28966 iter/s, 5.24095s/12 iters), loss = 0.0791209
I0405 16:09:07.610726  1863 solver.cpp:237]     Train net output #0: loss = 0.0791207 (* 1 = 0.0791207 loss)
I0405 16:09:07.610734  1863 sgd_solver.cpp:105] Iteration 19416, lr = 0.001
I0405 16:09:09.646234  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:09:13.032845  1863 solver.cpp:218] Iteration 19428 (2.21316 iter/s, 5.42211s/12 iters), loss = 0.0766862
I0405 16:09:13.032894  1863 solver.cpp:237]     Train net output #0: loss = 0.076686 (* 1 = 0.076686 loss)
I0405 16:09:13.032902  1863 sgd_solver.cpp:105] Iteration 19428, lr = 0.001
I0405 16:09:18.091184  1863 solver.cpp:218] Iteration 19440 (2.37234 iter/s, 5.05829s/12 iters), loss = 0.122344
I0405 16:09:18.091225  1863 solver.cpp:237]     Train net output #0: loss = 0.122343 (* 1 = 0.122343 loss)
I0405 16:09:18.091231  1863 sgd_solver.cpp:105] Iteration 19440, lr = 0.001
I0405 16:09:23.427721  1863 solver.cpp:218] Iteration 19452 (2.24867 iter/s, 5.33648s/12 iters), loss = 0.0921492
I0405 16:09:23.427867  1863 solver.cpp:237]     Train net output #0: loss = 0.092149 (* 1 = 0.092149 loss)
I0405 16:09:23.427879  1863 sgd_solver.cpp:105] Iteration 19452, lr = 0.001
I0405 16:09:28.734499  1863 solver.cpp:218] Iteration 19464 (2.26132 iter/s, 5.30663s/12 iters), loss = 0.126029
I0405 16:09:28.734541  1863 solver.cpp:237]     Train net output #0: loss = 0.126029 (* 1 = 0.126029 loss)
I0405 16:09:28.734547  1863 sgd_solver.cpp:105] Iteration 19464, lr = 0.001
I0405 16:09:34.049486  1863 solver.cpp:218] Iteration 19476 (2.25779 iter/s, 5.31493s/12 iters), loss = 0.0994387
I0405 16:09:34.049530  1863 solver.cpp:237]     Train net output #0: loss = 0.0994385 (* 1 = 0.0994385 loss)
I0405 16:09:34.049536  1863 sgd_solver.cpp:105] Iteration 19476, lr = 0.001
I0405 16:09:36.277325  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19482.caffemodel
I0405 16:09:39.204226  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19482.solverstate
I0405 16:09:41.551654  1863 solver.cpp:330] Iteration 19482, Testing net (#0)
I0405 16:09:41.551674  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:09:43.016464  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:09:46.054335  1863 solver.cpp:397]     Test net output #0: accuracy = 0.273897
I0405 16:09:46.054368  1863 solver.cpp:397]     Test net output #1: loss = 5.03161 (* 1 = 5.03161 loss)
I0405 16:09:47.988559  1863 solver.cpp:218] Iteration 19488 (0.860892 iter/s, 13.939s/12 iters), loss = 0.112752
I0405 16:09:47.988613  1863 solver.cpp:237]     Train net output #0: loss = 0.112752 (* 1 = 0.112752 loss)
I0405 16:09:47.988623  1863 sgd_solver.cpp:105] Iteration 19488, lr = 0.001
I0405 16:09:53.120944  1863 solver.cpp:218] Iteration 19500 (2.33812 iter/s, 5.13232s/12 iters), loss = 0.0653506
I0405 16:09:53.120999  1863 solver.cpp:237]     Train net output #0: loss = 0.0653503 (* 1 = 0.0653503 loss)
I0405 16:09:53.121008  1863 sgd_solver.cpp:105] Iteration 19500, lr = 0.001
I0405 16:09:58.363763  1863 solver.cpp:218] Iteration 19512 (2.28887 iter/s, 5.24276s/12 iters), loss = 0.0882972
I0405 16:09:58.365731  1863 solver.cpp:237]     Train net output #0: loss = 0.088297 (* 1 = 0.088297 loss)
I0405 16:09:58.365741  1863 sgd_solver.cpp:105] Iteration 19512, lr = 0.001
I0405 16:10:02.798365  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:10:03.643224  1863 solver.cpp:218] Iteration 19524 (2.27381 iter/s, 5.27749s/12 iters), loss = 0.0371405
I0405 16:10:03.643265  1863 solver.cpp:237]     Train net output #0: loss = 0.0371403 (* 1 = 0.0371403 loss)
I0405 16:10:03.643270  1863 sgd_solver.cpp:105] Iteration 19524, lr = 0.001
I0405 16:10:08.864257  1863 solver.cpp:218] Iteration 19536 (2.29842 iter/s, 5.22098s/12 iters), loss = 0.136205
I0405 16:10:08.864298  1863 solver.cpp:237]     Train net output #0: loss = 0.136204 (* 1 = 0.136204 loss)
I0405 16:10:08.864305  1863 sgd_solver.cpp:105] Iteration 19536, lr = 0.001
I0405 16:10:14.058926  1863 solver.cpp:218] Iteration 19548 (2.31008 iter/s, 5.19462s/12 iters), loss = 0.0905844
I0405 16:10:14.058965  1863 solver.cpp:237]     Train net output #0: loss = 0.0905842 (* 1 = 0.0905842 loss)
I0405 16:10:14.058971  1863 sgd_solver.cpp:105] Iteration 19548, lr = 0.001
I0405 16:10:19.377739  1863 solver.cpp:218] Iteration 19560 (2.25617 iter/s, 5.31876s/12 iters), loss = 0.0291714
I0405 16:10:19.377786  1863 solver.cpp:237]     Train net output #0: loss = 0.0291711 (* 1 = 0.0291711 loss)
I0405 16:10:19.377792  1863 sgd_solver.cpp:105] Iteration 19560, lr = 0.001
I0405 16:10:24.374296  1863 solver.cpp:218] Iteration 19572 (2.40168 iter/s, 4.9965s/12 iters), loss = 0.0498159
I0405 16:10:24.374336  1863 solver.cpp:237]     Train net output #0: loss = 0.0498156 (* 1 = 0.0498156 loss)
I0405 16:10:24.374341  1863 sgd_solver.cpp:105] Iteration 19572, lr = 0.001
I0405 16:10:28.780714  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19584.caffemodel
I0405 16:10:31.821099  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19584.solverstate
I0405 16:10:34.117867  1863 solver.cpp:330] Iteration 19584, Testing net (#0)
I0405 16:10:34.117890  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:10:35.475797  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:10:38.550819  1863 solver.cpp:397]     Test net output #0: accuracy = 0.276348
I0405 16:10:38.550846  1863 solver.cpp:397]     Test net output #1: loss = 5.06124 (* 1 = 5.06124 loss)
I0405 16:10:38.692945  1863 solver.cpp:218] Iteration 19584 (0.83807 iter/s, 14.3186s/12 iters), loss = 0.120817
I0405 16:10:38.693003  1863 solver.cpp:237]     Train net output #0: loss = 0.120817 (* 1 = 0.120817 loss)
I0405 16:10:38.693012  1863 sgd_solver.cpp:105] Iteration 19584, lr = 0.001
I0405 16:10:42.849251  1863 solver.cpp:218] Iteration 19596 (2.88723 iter/s, 4.15624s/12 iters), loss = 0.0506079
I0405 16:10:42.849290  1863 solver.cpp:237]     Train net output #0: loss = 0.0506077 (* 1 = 0.0506077 loss)
I0405 16:10:42.849296  1863 sgd_solver.cpp:105] Iteration 19596, lr = 0.001
I0405 16:10:48.179126  1863 solver.cpp:218] Iteration 19608 (2.25148 iter/s, 5.32982s/12 iters), loss = 0.112186
I0405 16:10:48.179173  1863 solver.cpp:237]     Train net output #0: loss = 0.112186 (* 1 = 0.112186 loss)
I0405 16:10:48.179179  1863 sgd_solver.cpp:105] Iteration 19608, lr = 0.001
I0405 16:10:53.516410  1863 solver.cpp:218] Iteration 19620 (2.24836 iter/s, 5.33722s/12 iters), loss = 0.0392704
I0405 16:10:53.516469  1863 solver.cpp:237]     Train net output #0: loss = 0.0392702 (* 1 = 0.0392702 loss)
I0405 16:10:53.516476  1863 sgd_solver.cpp:105] Iteration 19620, lr = 0.001
I0405 16:10:54.956198  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:10:58.895017  1863 solver.cpp:218] Iteration 19632 (2.23109 iter/s, 5.37854s/12 iters), loss = 0.0338772
I0405 16:10:58.895181  1863 solver.cpp:237]     Train net output #0: loss = 0.033877 (* 1 = 0.033877 loss)
I0405 16:10:58.895191  1863 sgd_solver.cpp:105] Iteration 19632, lr = 0.001
I0405 16:11:04.220722  1863 solver.cpp:218] Iteration 19644 (2.25329 iter/s, 5.32554s/12 iters), loss = 0.163183
I0405 16:11:04.220758  1863 solver.cpp:237]     Train net output #0: loss = 0.163182 (* 1 = 0.163182 loss)
I0405 16:11:04.220763  1863 sgd_solver.cpp:105] Iteration 19644, lr = 0.001
I0405 16:11:09.500239  1863 solver.cpp:218] Iteration 19656 (2.27295 iter/s, 5.27947s/12 iters), loss = 0.140996
I0405 16:11:09.500283  1863 solver.cpp:237]     Train net output #0: loss = 0.140996 (* 1 = 0.140996 loss)
I0405 16:11:09.500291  1863 sgd_solver.cpp:105] Iteration 19656, lr = 0.001
I0405 16:11:14.701089  1863 solver.cpp:218] Iteration 19668 (2.30734 iter/s, 5.20079s/12 iters), loss = 0.0553535
I0405 16:11:14.701138  1863 solver.cpp:237]     Train net output #0: loss = 0.0553532 (* 1 = 0.0553532 loss)
I0405 16:11:14.701144  1863 sgd_solver.cpp:105] Iteration 19668, lr = 0.001
I0405 16:11:20.095177  1863 solver.cpp:218] Iteration 19680 (2.22468 iter/s, 5.39403s/12 iters), loss = 0.12206
I0405 16:11:20.095216  1863 solver.cpp:237]     Train net output #0: loss = 0.12206 (* 1 = 0.12206 loss)
I0405 16:11:20.095221  1863 sgd_solver.cpp:105] Iteration 19680, lr = 0.001
I0405 16:11:22.193028  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19686.caffemodel
I0405 16:11:25.218811  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19686.solverstate
I0405 16:11:27.529410  1863 solver.cpp:330] Iteration 19686, Testing net (#0)
I0405 16:11:27.529433  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:11:28.805966  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:11:31.979569  1863 solver.cpp:397]     Test net output #0: accuracy = 0.278186
I0405 16:11:31.979682  1863 solver.cpp:397]     Test net output #1: loss = 4.99632 (* 1 = 4.99632 loss)
I0405 16:11:33.975288  1863 solver.cpp:218] Iteration 19692 (0.864549 iter/s, 13.8801s/12 iters), loss = 0.0525529
I0405 16:11:33.975342  1863 solver.cpp:237]     Train net output #0: loss = 0.0525527 (* 1 = 0.0525527 loss)
I0405 16:11:33.975348  1863 sgd_solver.cpp:105] Iteration 19692, lr = 0.001
I0405 16:11:39.143663  1863 solver.cpp:218] Iteration 19704 (2.32184 iter/s, 5.16831s/12 iters), loss = 0.157237
I0405 16:11:39.143718  1863 solver.cpp:237]     Train net output #0: loss = 0.157236 (* 1 = 0.157236 loss)
I0405 16:11:39.143728  1863 sgd_solver.cpp:105] Iteration 19704, lr = 0.001
I0405 16:11:44.419531  1863 solver.cpp:218] Iteration 19716 (2.27454 iter/s, 5.2758s/12 iters), loss = 0.0458711
I0405 16:11:44.419571  1863 solver.cpp:237]     Train net output #0: loss = 0.0458709 (* 1 = 0.0458709 loss)
I0405 16:11:44.419577  1863 sgd_solver.cpp:105] Iteration 19716, lr = 0.001
I0405 16:11:48.269214  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:11:49.916596  1863 solver.cpp:218] Iteration 19728 (2.183 iter/s, 5.49701s/12 iters), loss = 0.0455452
I0405 16:11:49.916636  1863 solver.cpp:237]     Train net output #0: loss = 0.0455449 (* 1 = 0.0455449 loss)
I0405 16:11:49.916642  1863 sgd_solver.cpp:105] Iteration 19728, lr = 0.001
I0405 16:11:55.154793  1863 solver.cpp:218] Iteration 19740 (2.29089 iter/s, 5.23814s/12 iters), loss = 0.0680097
I0405 16:11:55.154832  1863 solver.cpp:237]     Train net output #0: loss = 0.0680095 (* 1 = 0.0680095 loss)
I0405 16:11:55.154839  1863 sgd_solver.cpp:105] Iteration 19740, lr = 0.001
I0405 16:12:00.669744  1863 solver.cpp:218] Iteration 19752 (2.17592 iter/s, 5.5149s/12 iters), loss = 0.0658906
I0405 16:12:00.669785  1863 solver.cpp:237]     Train net output #0: loss = 0.0658904 (* 1 = 0.0658904 loss)
I0405 16:12:00.669791  1863 sgd_solver.cpp:105] Iteration 19752, lr = 0.001
I0405 16:12:05.695977  1863 solver.cpp:218] Iteration 19764 (2.3875 iter/s, 5.02618s/12 iters), loss = 0.0297398
I0405 16:12:05.696116  1863 solver.cpp:237]     Train net output #0: loss = 0.0297395 (* 1 = 0.0297395 loss)
I0405 16:12:05.696125  1863 sgd_solver.cpp:105] Iteration 19764, lr = 0.001
I0405 16:12:11.063123  1863 solver.cpp:218] Iteration 19776 (2.23589 iter/s, 5.367s/12 iters), loss = 0.0304572
I0405 16:12:11.063167  1863 solver.cpp:237]     Train net output #0: loss = 0.030457 (* 1 = 0.030457 loss)
I0405 16:12:11.063174  1863 sgd_solver.cpp:105] Iteration 19776, lr = 0.001
I0405 16:12:15.910547  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19788.caffemodel
I0405 16:12:18.887029  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19788.solverstate
I0405 16:12:21.184335  1863 solver.cpp:330] Iteration 19788, Testing net (#0)
I0405 16:12:21.184356  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:12:22.385082  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:12:25.487196  1863 solver.cpp:397]     Test net output #0: accuracy = 0.286765
I0405 16:12:25.487232  1863 solver.cpp:397]     Test net output #1: loss = 5.00813 (* 1 = 5.00813 loss)
I0405 16:12:25.628031  1863 solver.cpp:218] Iteration 19788 (0.823901 iter/s, 14.5649s/12 iters), loss = 0.0968695
I0405 16:12:25.628080  1863 solver.cpp:237]     Train net output #0: loss = 0.0968693 (* 1 = 0.0968693 loss)
I0405 16:12:25.628088  1863 sgd_solver.cpp:105] Iteration 19788, lr = 0.001
I0405 16:12:29.922927  1863 solver.cpp:218] Iteration 19800 (2.79405 iter/s, 4.29484s/12 iters), loss = 0.0930535
I0405 16:12:29.922967  1863 solver.cpp:237]     Train net output #0: loss = 0.0930533 (* 1 = 0.0930533 loss)
I0405 16:12:29.922973  1863 sgd_solver.cpp:105] Iteration 19800, lr = 0.001
I0405 16:12:35.314913  1863 solver.cpp:218] Iteration 19812 (2.22555 iter/s, 5.39193s/12 iters), loss = 0.0695436
I0405 16:12:35.314963  1863 solver.cpp:237]     Train net output #0: loss = 0.0695433 (* 1 = 0.0695433 loss)
I0405 16:12:35.314972  1863 sgd_solver.cpp:105] Iteration 19812, lr = 0.001
I0405 16:12:40.822347  1863 solver.cpp:218] Iteration 19824 (2.1789 iter/s, 5.50737s/12 iters), loss = 0.014684
I0405 16:12:40.822449  1863 solver.cpp:237]     Train net output #0: loss = 0.0146838 (* 1 = 0.0146838 loss)
I0405 16:12:40.822455  1863 sgd_solver.cpp:105] Iteration 19824, lr = 0.001
I0405 16:12:41.478127  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:12:46.178383  1863 solver.cpp:218] Iteration 19836 (2.24051 iter/s, 5.35593s/12 iters), loss = 0.0338144
I0405 16:12:46.178426  1863 solver.cpp:237]     Train net output #0: loss = 0.0338142 (* 1 = 0.0338142 loss)
I0405 16:12:46.178431  1863 sgd_solver.cpp:105] Iteration 19836, lr = 0.001
I0405 16:12:51.531699  1863 solver.cpp:218] Iteration 19848 (2.24163 iter/s, 5.35326s/12 iters), loss = 0.0764274
I0405 16:12:51.531759  1863 solver.cpp:237]     Train net output #0: loss = 0.0764271 (* 1 = 0.0764271 loss)
I0405 16:12:51.531769  1863 sgd_solver.cpp:105] Iteration 19848, lr = 0.001
I0405 16:12:56.897850  1863 solver.cpp:218] Iteration 19860 (2.23627 iter/s, 5.36608s/12 iters), loss = 0.0512833
I0405 16:12:56.897902  1863 solver.cpp:237]     Train net output #0: loss = 0.0512831 (* 1 = 0.0512831 loss)
I0405 16:12:56.897912  1863 sgd_solver.cpp:105] Iteration 19860, lr = 0.001
I0405 16:13:02.280380  1863 solver.cpp:218] Iteration 19872 (2.22946 iter/s, 5.38247s/12 iters), loss = 0.0309871
I0405 16:13:02.280431  1863 solver.cpp:237]     Train net output #0: loss = 0.0309868 (* 1 = 0.0309868 loss)
I0405 16:13:02.280441  1863 sgd_solver.cpp:105] Iteration 19872, lr = 0.001
I0405 16:13:07.732714  1863 solver.cpp:218] Iteration 19884 (2.20092 iter/s, 5.45227s/12 iters), loss = 0.0824511
I0405 16:13:07.732769  1863 solver.cpp:237]     Train net output #0: loss = 0.0824509 (* 1 = 0.0824509 loss)
I0405 16:13:07.732779  1863 sgd_solver.cpp:105] Iteration 19884, lr = 0.001
I0405 16:13:09.945789  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19890.caffemodel
I0405 16:13:12.856734  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19890.solverstate
I0405 16:13:15.183835  1863 solver.cpp:330] Iteration 19890, Testing net (#0)
I0405 16:13:15.183863  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:13:16.359004  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:13:19.475773  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270221
I0405 16:13:19.475808  1863 solver.cpp:397]     Test net output #1: loss = 4.99588 (* 1 = 4.99588 loss)
I0405 16:13:21.374708  1863 solver.cpp:218] Iteration 19896 (0.87964 iter/s, 13.6419s/12 iters), loss = 0.0393127
I0405 16:13:21.374748  1863 solver.cpp:237]     Train net output #0: loss = 0.0393125 (* 1 = 0.0393125 loss)
I0405 16:13:21.374754  1863 sgd_solver.cpp:105] Iteration 19896, lr = 0.001
I0405 16:13:26.548204  1863 solver.cpp:218] Iteration 19908 (2.31954 iter/s, 5.17345s/12 iters), loss = 0.0784368
I0405 16:13:26.548243  1863 solver.cpp:237]     Train net output #0: loss = 0.0784366 (* 1 = 0.0784366 loss)
I0405 16:13:26.548249  1863 sgd_solver.cpp:105] Iteration 19908, lr = 0.001
I0405 16:13:31.917532  1863 solver.cpp:218] Iteration 19920 (2.23494 iter/s, 5.36928s/12 iters), loss = 0.131341
I0405 16:13:31.917588  1863 solver.cpp:237]     Train net output #0: loss = 0.131341 (* 1 = 0.131341 loss)
I0405 16:13:31.917596  1863 sgd_solver.cpp:105] Iteration 19920, lr = 0.001
I0405 16:13:34.840694  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:13:37.318804  1863 solver.cpp:218] Iteration 19932 (2.22173 iter/s, 5.4012s/12 iters), loss = 0.0982849
I0405 16:13:37.318851  1863 solver.cpp:237]     Train net output #0: loss = 0.0982847 (* 1 = 0.0982847 loss)
I0405 16:13:37.318859  1863 sgd_solver.cpp:105] Iteration 19932, lr = 0.001
I0405 16:13:42.435503  1863 solver.cpp:218] Iteration 19944 (2.34529 iter/s, 5.11664s/12 iters), loss = 0.0242907
I0405 16:13:42.435544  1863 solver.cpp:237]     Train net output #0: loss = 0.0242904 (* 1 = 0.0242904 loss)
I0405 16:13:42.435549  1863 sgd_solver.cpp:105] Iteration 19944, lr = 0.001
I0405 16:13:47.702409  1863 solver.cpp:218] Iteration 19956 (2.2784 iter/s, 5.26685s/12 iters), loss = 0.168865
I0405 16:13:47.702507  1863 solver.cpp:237]     Train net output #0: loss = 0.168864 (* 1 = 0.168864 loss)
I0405 16:13:47.702513  1863 sgd_solver.cpp:105] Iteration 19956, lr = 0.001
I0405 16:13:52.874660  1863 solver.cpp:218] Iteration 19968 (2.32012 iter/s, 5.17214s/12 iters), loss = 0.049389
I0405 16:13:52.874722  1863 solver.cpp:237]     Train net output #0: loss = 0.0493887 (* 1 = 0.0493887 loss)
I0405 16:13:52.874747  1863 sgd_solver.cpp:105] Iteration 19968, lr = 0.001
I0405 16:13:58.172145  1863 solver.cpp:218] Iteration 19980 (2.26526 iter/s, 5.29741s/12 iters), loss = 0.172586
I0405 16:13:58.172194  1863 solver.cpp:237]     Train net output #0: loss = 0.172586 (* 1 = 0.172586 loss)
I0405 16:13:58.172200  1863 sgd_solver.cpp:105] Iteration 19980, lr = 0.001
I0405 16:14:03.024279  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_19992.caffemodel
I0405 16:14:07.544716  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_19992.solverstate
I0405 16:14:11.675817  1863 solver.cpp:330] Iteration 19992, Testing net (#0)
I0405 16:14:11.675837  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:14:12.967970  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:14:16.113909  1863 solver.cpp:397]     Test net output #0: accuracy = 0.270833
I0405 16:14:16.113943  1863 solver.cpp:397]     Test net output #1: loss = 4.90962 (* 1 = 4.90962 loss)
I0405 16:14:16.251394  1863 solver.cpp:218] Iteration 19992 (0.663746 iter/s, 18.0792s/12 iters), loss = 0.196866
I0405 16:14:16.252969  1863 solver.cpp:237]     Train net output #0: loss = 0.196866 (* 1 = 0.196866 loss)
I0405 16:14:16.252980  1863 sgd_solver.cpp:105] Iteration 19992, lr = 0.001
I0405 16:14:20.633994  1863 solver.cpp:218] Iteration 20004 (2.73909 iter/s, 4.38102s/12 iters), loss = 0.0565998
I0405 16:14:20.634153  1863 solver.cpp:237]     Train net output #0: loss = 0.0565996 (* 1 = 0.0565996 loss)
I0405 16:14:20.634161  1863 sgd_solver.cpp:105] Iteration 20004, lr = 0.001
I0405 16:14:25.543283  1863 solver.cpp:218] Iteration 20016 (2.44443 iter/s, 4.90912s/12 iters), loss = 0.0277077
I0405 16:14:25.543330  1863 solver.cpp:237]     Train net output #0: loss = 0.0277075 (* 1 = 0.0277075 loss)
I0405 16:14:25.543336  1863 sgd_solver.cpp:105] Iteration 20016, lr = 0.001
I0405 16:14:30.871663  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:14:31.037922  1863 solver.cpp:218] Iteration 20028 (2.18397 iter/s, 5.49458s/12 iters), loss = 0.0276532
I0405 16:14:31.037971  1863 solver.cpp:237]     Train net output #0: loss = 0.0276529 (* 1 = 0.0276529 loss)
I0405 16:14:31.037977  1863 sgd_solver.cpp:105] Iteration 20028, lr = 0.001
I0405 16:14:36.429852  1863 solver.cpp:218] Iteration 20040 (2.22557 iter/s, 5.39187s/12 iters), loss = 0.126467
I0405 16:14:36.429893  1863 solver.cpp:237]     Train net output #0: loss = 0.126467 (* 1 = 0.126467 loss)
I0405 16:14:36.429898  1863 sgd_solver.cpp:105] Iteration 20040, lr = 0.001
I0405 16:14:41.668049  1863 solver.cpp:218] Iteration 20052 (2.29088 iter/s, 5.23815s/12 iters), loss = 0.120077
I0405 16:14:41.668089  1863 solver.cpp:237]     Train net output #0: loss = 0.120077 (* 1 = 0.120077 loss)
I0405 16:14:41.668095  1863 sgd_solver.cpp:105] Iteration 20052, lr = 0.001
I0405 16:14:46.895128  1863 solver.cpp:218] Iteration 20064 (2.29576 iter/s, 5.22702s/12 iters), loss = 0.145503
I0405 16:14:46.895182  1863 solver.cpp:237]     Train net output #0: loss = 0.145503 (* 1 = 0.145503 loss)
I0405 16:14:46.895190  1863 sgd_solver.cpp:105] Iteration 20064, lr = 0.001
I0405 16:14:52.290421  1863 solver.cpp:218] Iteration 20076 (2.22419 iter/s, 5.39523s/12 iters), loss = 0.0888584
I0405 16:14:52.290540  1863 solver.cpp:237]     Train net output #0: loss = 0.0888581 (* 1 = 0.0888581 loss)
I0405 16:14:52.290550  1863 sgd_solver.cpp:105] Iteration 20076, lr = 0.001
I0405 16:14:57.675737  1863 solver.cpp:218] Iteration 20088 (2.22833 iter/s, 5.38519s/12 iters), loss = 0.0618687
I0405 16:14:57.675786  1863 solver.cpp:237]     Train net output #0: loss = 0.0618684 (* 1 = 0.0618684 loss)
I0405 16:14:57.675793  1863 sgd_solver.cpp:105] Iteration 20088, lr = 0.001
I0405 16:14:59.823026  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20094.caffemodel
I0405 16:15:02.912356  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20094.solverstate
I0405 16:15:05.876320  1863 solver.cpp:330] Iteration 20094, Testing net (#0)
I0405 16:15:05.876338  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:15:07.026015  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:15:09.782420  1863 blocking_queue.cpp:49] Waiting for data
I0405 16:15:10.225039  1863 solver.cpp:397]     Test net output #0: accuracy = 0.27451
I0405 16:15:10.225072  1863 solver.cpp:397]     Test net output #1: loss = 4.81294 (* 1 = 4.81294 loss)
I0405 16:15:12.061173  1863 solver.cpp:218] Iteration 20100 (0.83418 iter/s, 14.3854s/12 iters), loss = 0.0717147
I0405 16:15:12.061224  1863 solver.cpp:237]     Train net output #0: loss = 0.0717145 (* 1 = 0.0717145 loss)
I0405 16:15:12.061231  1863 sgd_solver.cpp:105] Iteration 20100, lr = 0.001
I0405 16:15:17.315513  1863 solver.cpp:218] Iteration 20112 (2.28385 iter/s, 5.25428s/12 iters), loss = 0.0298301
I0405 16:15:17.315562  1863 solver.cpp:237]     Train net output #0: loss = 0.0298299 (* 1 = 0.0298299 loss)
I0405 16:15:17.315569  1863 sgd_solver.cpp:105] Iteration 20112, lr = 0.001
I0405 16:15:22.148430  1863 solver.cpp:218] Iteration 20124 (2.483 iter/s, 4.83286s/12 iters), loss = 0.0943574
I0405 16:15:22.148469  1863 solver.cpp:237]     Train net output #0: loss = 0.0943571 (* 1 = 0.0943571 loss)
I0405 16:15:22.148474  1863 sgd_solver.cpp:105] Iteration 20124, lr = 0.001
I0405 16:15:24.507977  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:15:27.634475  1863 solver.cpp:218] Iteration 20136 (2.18739 iter/s, 5.486s/12 iters), loss = 0.0451638
I0405 16:15:27.634517  1863 solver.cpp:237]     Train net output #0: loss = 0.0451636 (* 1 = 0.0451636 loss)
I0405 16:15:27.634523  1863 sgd_solver.cpp:105] Iteration 20136, lr = 0.001
I0405 16:15:33.031069  1863 solver.cpp:218] Iteration 20148 (2.22365 iter/s, 5.39654s/12 iters), loss = 0.0722595
I0405 16:15:33.031109  1863 solver.cpp:237]     Train net output #0: loss = 0.0722592 (* 1 = 0.0722592 loss)
I0405 16:15:33.031116  1863 sgd_solver.cpp:105] Iteration 20148, lr = 0.001
I0405 16:15:38.387042  1863 solver.cpp:218] Iteration 20160 (2.24051 iter/s, 5.35592s/12 iters), loss = 0.0982798
I0405 16:15:38.387094  1863 solver.cpp:237]     Train net output #0: loss = 0.0982796 (* 1 = 0.0982796 loss)
I0405 16:15:38.387104  1863 sgd_solver.cpp:105] Iteration 20160, lr = 0.001
I0405 16:15:43.662716  1863 solver.cpp:218] Iteration 20172 (2.27462 iter/s, 5.27561s/12 iters), loss = 0.142139
I0405 16:15:43.662766  1863 solver.cpp:237]     Train net output #0: loss = 0.142139 (* 1 = 0.142139 loss)
I0405 16:15:43.662775  1863 sgd_solver.cpp:105] Iteration 20172, lr = 0.001
I0405 16:15:48.869628  1863 solver.cpp:218] Iteration 20184 (2.30466 iter/s, 5.20685s/12 iters), loss = 0.0807388
I0405 16:15:48.869668  1863 solver.cpp:237]     Train net output #0: loss = 0.0807386 (* 1 = 0.0807386 loss)
I0405 16:15:48.869673  1863 sgd_solver.cpp:105] Iteration 20184, lr = 0.001
I0405 16:15:53.587355  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20196.caffemodel
I0405 16:15:56.875473  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20196.solverstate
I0405 16:15:59.275254  1863 solver.cpp:330] Iteration 20196, Testing net (#0)
I0405 16:15:59.275274  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:16:00.349337  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:16:03.787184  1863 solver.cpp:397]     Test net output #0: accuracy = 0.28125
I0405 16:16:03.787218  1863 solver.cpp:397]     Test net output #1: loss = 4.81821 (* 1 = 4.81821 loss)
I0405 16:16:03.926585  1863 solver.cpp:218] Iteration 20196 (0.796976 iter/s, 15.0569s/12 iters), loss = 0.102127
I0405 16:16:03.926636  1863 solver.cpp:237]     Train net output #0: loss = 0.102127 (* 1 = 0.102127 loss)
I0405 16:16:03.926645  1863 sgd_solver.cpp:105] Iteration 20196, lr = 0.001
I0405 16:16:08.369177  1863 solver.cpp:218] Iteration 20208 (2.70116 iter/s, 4.44253s/12 iters), loss = 0.0524662
I0405 16:16:08.369221  1863 solver.cpp:237]     Train net output #0: loss = 0.052466 (* 1 = 0.052466 loss)
I0405 16:16:08.369227  1863 sgd_solver.cpp:105] Iteration 20208, lr = 0.001
I0405 16:16:13.761534  1863 solver.cpp:218] Iteration 20220 (2.22539 iter/s, 5.3923s/12 iters), loss = 0.121176
I0405 16:16:13.761572  1863 solver.cpp:237]     Train net output #0: loss = 0.121175 (* 1 = 0.121175 loss)
I0405 16:16:13.761577  1863 sgd_solver.cpp:105] Iteration 20220, lr = 0.001
I0405 16:16:18.339838  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:16:19.203537  1863 solver.cpp:218] Iteration 20232 (2.20509 iter/s, 5.44196s/12 iters), loss = 0.0483578
I0405 16:16:19.203575  1863 solver.cpp:237]     Train net output #0: loss = 0.0483576 (* 1 = 0.0483576 loss)
I0405 16:16:19.203580  1863 sgd_solver.cpp:105] Iteration 20232, lr = 0.001
I0405 16:16:24.556051  1863 solver.cpp:218] Iteration 20244 (2.24196 iter/s, 5.35246s/12 iters), loss = 0.088474
I0405 16:16:24.556093  1863 solver.cpp:237]     Train net output #0: loss = 0.0884738 (* 1 = 0.0884738 loss)
I0405 16:16:24.556099  1863 sgd_solver.cpp:105] Iteration 20244, lr = 0.001
I0405 16:16:29.996249  1863 solver.cpp:218] Iteration 20256 (2.20582 iter/s, 5.44014s/12 iters), loss = 0.0936009
I0405 16:16:29.996379  1863 solver.cpp:237]     Train net output #0: loss = 0.0936007 (* 1 = 0.0936007 loss)
I0405 16:16:29.996387  1863 sgd_solver.cpp:105] Iteration 20256, lr = 0.001
I0405 16:16:35.315970  1863 solver.cpp:218] Iteration 20268 (2.25582 iter/s, 5.31958s/12 iters), loss = 0.0630231
I0405 16:16:35.316025  1863 solver.cpp:237]     Train net output #0: loss = 0.0630229 (* 1 = 0.0630229 loss)
I0405 16:16:35.316035  1863 sgd_solver.cpp:105] Iteration 20268, lr = 0.001
I0405 16:16:40.701020  1863 solver.cpp:218] Iteration 20280 (2.22842 iter/s, 5.38499s/12 iters), loss = 0.0421964
I0405 16:16:40.701066  1863 solver.cpp:237]     Train net output #0: loss = 0.0421962 (* 1 = 0.0421962 loss)
I0405 16:16:40.701072  1863 sgd_solver.cpp:105] Iteration 20280, lr = 0.001
I0405 16:16:46.094811  1863 solver.cpp:218] Iteration 20292 (2.2248 iter/s, 5.39374s/12 iters), loss = 0.102291
I0405 16:16:46.094848  1863 solver.cpp:237]     Train net output #0: loss = 0.102291 (* 1 = 0.102291 loss)
I0405 16:16:46.094853  1863 sgd_solver.cpp:105] Iteration 20292, lr = 0.001
I0405 16:16:48.244320  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20298.caffemodel
I0405 16:16:51.422214  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20298.solverstate
I0405 16:16:53.749094  1863 solver.cpp:330] Iteration 20298, Testing net (#0)
I0405 16:16:53.749119  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:16:54.784227  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:16:58.095904  1863 solver.cpp:397]     Test net output #0: accuracy = 0.282476
I0405 16:16:58.095935  1863 solver.cpp:397]     Test net output #1: loss = 4.88644 (* 1 = 4.88644 loss)
I0405 16:17:00.069674  1863 solver.cpp:218] Iteration 20304 (0.858687 iter/s, 13.9748s/12 iters), loss = 0.0745607
I0405 16:17:00.069770  1863 solver.cpp:237]     Train net output #0: loss = 0.0745604 (* 1 = 0.0745604 loss)
I0405 16:17:00.069777  1863 sgd_solver.cpp:105] Iteration 20304, lr = 0.001
I0405 16:17:05.198726  1863 solver.cpp:218] Iteration 20316 (2.33966 iter/s, 5.12895s/12 iters), loss = 0.0618844
I0405 16:17:05.198765  1863 solver.cpp:237]     Train net output #0: loss = 0.0618842 (* 1 = 0.0618842 loss)
I0405 16:17:05.198771  1863 sgd_solver.cpp:105] Iteration 20316, lr = 0.001
I0405 16:17:10.252734  1863 solver.cpp:218] Iteration 20328 (2.37438 iter/s, 5.05395s/12 iters), loss = 0.0466174
I0405 16:17:10.252785  1863 solver.cpp:237]     Train net output #0: loss = 0.0466171 (* 1 = 0.0466171 loss)
I0405 16:17:10.252794  1863 sgd_solver.cpp:105] Iteration 20328, lr = 0.001
I0405 16:17:11.724498  1882 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:17:15.650214  1863 solver.cpp:218] Iteration 20340 (2.22329 iter/s, 5.39742s/12 iters), loss = 0.0872605
I0405 16:17:15.650257  1863 solver.cpp:237]     Train net output #0: loss = 0.0872602 (* 1 = 0.0872602 loss)
I0405 16:17:15.650264  1863 sgd_solver.cpp:105] Iteration 20340, lr = 0.001
I0405 16:17:20.842031  1863 solver.cpp:218] Iteration 20352 (2.31136 iter/s, 5.19176s/12 iters), loss = 0.0286745
I0405 16:17:20.842080  1863 solver.cpp:237]     Train net output #0: loss = 0.0286742 (* 1 = 0.0286742 loss)
I0405 16:17:20.842088  1863 sgd_solver.cpp:105] Iteration 20352, lr = 0.001
I0405 16:17:26.131556  1863 solver.cpp:218] Iteration 20364 (2.26866 iter/s, 5.28947s/12 iters), loss = 0.0629941
I0405 16:17:26.131613  1863 solver.cpp:237]     Train net output #0: loss = 0.0629938 (* 1 = 0.0629938 loss)
I0405 16:17:26.131620  1863 sgd_solver.cpp:105] Iteration 20364, lr = 0.001
I0405 16:17:31.079602  1863 solver.cpp:218] Iteration 20376 (2.42523 iter/s, 4.94798s/12 iters), loss = 0.1835
I0405 16:17:31.079716  1863 solver.cpp:237]     Train net output #0: loss = 0.1835 (* 1 = 0.1835 loss)
I0405 16:17:31.079722  1863 sgd_solver.cpp:105] Iteration 20376, lr = 0.001
I0405 16:17:36.622511  1863 solver.cpp:218] Iteration 20388 (2.16498 iter/s, 5.54278s/12 iters), loss = 0.0572334
I0405 16:17:36.622555  1863 solver.cpp:237]     Train net output #0: loss = 0.0572331 (* 1 = 0.0572331 loss)
I0405 16:17:36.622560  1863 sgd_solver.cpp:105] Iteration 20388, lr = 0.001
I0405 16:17:41.424079  1863 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_20400.caffemodel
I0405 16:17:44.443543  1863 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_20400.solverstate
I0405 16:17:46.800561  1863 solver.cpp:310] Iteration 20400, loss = 0.185832
I0405 16:17:46.800587  1863 solver.cpp:330] Iteration 20400, Testing net (#0)
I0405 16:17:46.800590  1863 net.cpp:676] Ignoring source layer train-data
I0405 16:17:47.819444  1920 data_layer.cpp:73] Restarting data prefetching from start.
I0405 16:17:51.109302  1863 solver.cpp:397]     Test net output #0: accuracy = 0.268995
I0405 16:17:51.109333  1863 solver.cpp:397]     Test net output #1: loss = 4.97178 (* 1 = 4.97178 loss)
I0405 16:17:51.109339  1863 solver.cpp:315] Optimization Done.
I0405 16:17:51.109342  1863 caffe.cpp:259] Optimization Done.