cifar10_LeNet_SGD_50.txt

[1, 2000] loss: 2.27476
[1, 4000] loss: 2.02874
[1, 6000] loss: 1.8359
[1, 8000] loss: 1.70182
[1, 10000] loss: 1.58244
[1, 12000] loss: 1.5653
[2, 2000] loss: 1.5013
[2, 4000] loss: 1.46316
[2, 6000] loss: 1.43072
[2, 8000] loss: 1.43355
[2, 10000] loss: 1.40814
[2, 12000] loss: 1.39249
[3, 2000] loss: 1.32972
[3, 4000] loss: 1.32369
[3, 6000] loss: 1.32204
[3, 8000] loss: 1.2926
[3, 10000] loss: 1.28321
[3, 12000] loss: 1.28078
[4, 2000] loss: 1.21503
[4, 4000] loss: 1.21594
[4, 6000] loss: 1.20238
[4, 8000] loss: 1.23337
[4, 10000] loss: 1.21639
[4, 12000] loss: 1.19798
[5, 2000] loss: 1.12231
[5, 4000] loss: 1.12658
[5, 6000] loss: 1.15117
[5, 8000] loss: 1.16419
[5, 10000] loss: 1.16901
[5, 12000] loss: 1.1374
[6, 2000] loss: 1.06296
[6, 4000] loss: 1.08275
[6, 6000] loss: 1.08028
[6, 8000] loss: 1.08816
[6, 10000] loss: 1.0966
[6, 12000] loss: 1.07088
[7, 2000] loss: 0.992769
[7, 4000] loss: 1.02668
[7, 6000] loss: 1.04004
[7, 8000] loss: 1.03704
[7, 10000] loss: 1.03646
[7, 12000] loss: 1.05778
[8, 2000] loss: 0.978718
[8, 4000] loss: 0.970925
[8, 6000] loss: 0.982906
[8, 8000] loss: 0.992852
[8, 10000] loss: 1.00803
[8, 12000] loss: 1.03003
[9, 2000] loss: 0.934979
[9, 4000] loss: 0.941591
[9, 6000] loss: 0.947035
[9, 8000] loss: 0.964331
[9, 10000] loss: 0.974936
[9, 12000] loss: 0.986031
[10, 2000] loss: 0.870811
[10, 4000] loss: 0.901036
[10, 6000] loss: 0.920247
[10, 8000] loss: 0.925312
[10, 10000] loss: 0.962889
[10, 12000] loss: 0.954043
[11, 2000] loss: 0.835802
[11, 4000] loss: 0.877299
[11, 6000] loss: 0.893253
[11, 8000] loss: 0.90645
[11, 10000] loss: 0.920989
[11, 12000] loss: 0.933847
[12, 2000] loss: 0.837616
[12, 4000] loss: 0.837846
[12, 6000] loss: 0.869885
[12, 8000] loss: 0.893365
[12, 10000] loss: 0.896523
[12, 12000] loss: 0.9042
[13, 2000] loss: 0.79386
[13, 4000] loss: 0.828146
[13, 6000] loss: 0.841644
[13, 8000] loss: 0.89127
[13, 10000] loss: 0.880898
[13, 12000] loss: 0.87856
[14, 2000] loss: 0.762243
[14, 4000] loss: 0.791685
[14, 6000] loss: 0.830719
[14, 8000] loss: 0.853102
[14, 10000] loss: 0.846633
[14, 12000] loss: 0.860243
[15, 2000] loss: 0.754761
[15, 4000] loss: 0.789346
[15, 6000] loss: 0.79424
[15, 8000] loss: 0.804138
[15, 10000] loss: 0.848495
[15, 12000] loss: 0.861076
[16, 2000] loss: 0.719504
[16, 4000] loss: 0.789299
[16, 6000] loss: 0.786059
[16, 8000] loss: 0.791669
[16, 10000] loss: 0.820129
[16, 12000] loss: 0.839707
[17, 2000] loss: 0.709841
[17, 4000] loss: 0.75434
[17, 6000] loss: 0.769749
[17, 8000] loss: 0.79745
[17, 10000] loss: 0.806593
[17, 12000] loss: 0.795161
[18, 2000] loss: 0.698725
[18, 4000] loss: 0.742876
[18, 6000] loss: 0.747293
[18, 8000] loss: 0.768023
[18, 10000] loss: 0.785341
[18, 12000] loss: 0.829424
[19, 2000] loss: 0.708112
[19, 4000] loss: 0.710963
[19, 6000] loss: 0.756832
[19, 8000] loss: 0.764703
[19, 10000] loss: 0.780609
[19, 12000] loss: 0.783991
[20, 2000] loss: 0.678829
[20, 4000] loss: 0.719327
[20, 6000] loss: 0.736198
[20, 8000] loss: 0.743777
[20, 10000] loss: 0.779877
[20, 12000] loss: 0.78099
[21, 2000] loss: 0.652012
[21, 4000] loss: 0.698443
[21, 6000] loss: 0.713807
[21, 8000] loss: 0.75495
[21, 10000] loss: 0.764031
[21, 12000] loss: 0.777317
[22, 2000] loss: 0.674383
[22, 4000] loss: 0.692912
[22, 6000] loss: 0.709694
[22, 8000] loss: 0.723122
[22, 10000] loss: 0.759379
[22, 12000] loss: 0.785706
[23, 2000] loss: 0.635107
[23, 4000] loss: 0.683915
[23, 6000] loss: 0.718503
[23, 8000] loss: 0.736745
[23, 10000] loss: 0.737422
[23, 12000] loss: 0.750957
[24, 2000] loss: 0.633942
[24, 4000] loss: 0.668047
[24, 6000] loss: 0.695163
[24, 8000] loss: 0.708725
[24, 10000] loss: 0.740924
[24, 12000] loss: 0.770263
[25, 2000] loss: 0.621156
[25, 4000] loss: 0.691195
[25, 6000] loss: 0.680128
[25, 8000] loss: 0.710324
[25, 10000] loss: 0.744715
[25, 12000] loss: 0.745485
[26, 2000] loss: 0.618231
[26, 4000] loss: 0.652279
[26, 6000] loss: 0.682274
[26, 8000] loss: 0.730391
[26, 10000] loss: 0.72918
[26, 12000] loss: 0.728108
[27, 2000] loss: 0.611302
[27, 4000] loss: 0.647281
[27, 6000] loss: 0.681858
[27, 8000] loss: 0.727529
[27, 10000] loss: 0.721372
[27, 12000] loss: 0.712414
[28, 2000] loss: 0.615367
[28, 4000] loss: 0.654659
[28, 6000] loss: 0.682947
[28, 8000] loss: 0.71386
[28, 10000] loss: 0.697381
[28, 12000] loss: 0.727296
[29, 2000] loss: 0.583298
[29, 4000] loss: 0.660547
[29, 6000] loss: 0.687712
[29, 8000] loss: 0.702407
[29, 10000] loss: 0.707604
[29, 12000] loss: 0.711452
[30, 2000] loss: 0.623436
[30, 4000] loss: 0.624452
[30, 6000] loss: 0.645073
[30, 8000] loss: 0.697651
[30, 10000] loss: 0.713304
[30, 12000] loss: 0.723063
[31, 2000] loss: 0.638924
[31, 4000] loss: 0.641113
[31, 6000] loss: 0.662039
[31, 8000] loss: 0.681592
[31, 10000] loss: 0.688946
[31, 12000] loss: 0.718592
[32, 2000] loss: 0.601951
[32, 4000] loss: 0.643987
[32, 6000] loss: 0.662205
[32, 8000] loss: 0.686749
[32, 10000] loss: 0.69154
[32, 12000] loss: 0.732938
[33, 2000] loss: 0.579907
[33, 4000] loss: 0.614433
[33, 6000] loss: 0.665078
[33, 8000] loss: 0.680112
[33, 10000] loss: 0.707404
[33, 12000] loss: 0.699299
[34, 2000] loss: 0.572225
[34, 4000] loss: 0.625085
[34, 6000] loss: 0.668591
[34, 8000] loss: 0.687325
[34, 10000] loss: 0.706051
[34, 12000] loss: 0.677965
[35, 2000] loss: 0.579502
[35, 4000] loss: 0.608478
[35, 6000] loss: 0.658196
[35, 8000] loss: 0.648245
[35, 10000] loss: 0.699534
[35, 12000] loss: 0.720848
[36, 2000] loss: 0.624024
[36, 4000] loss: 0.612602
[36, 6000] loss: 0.664378
[36, 8000] loss: 0.659054
[36, 10000] loss: 0.685768
[36, 12000] loss: 0.708119
[37, 2000] loss: 0.574678
[37, 4000] loss: 0.611514
[37, 6000] loss: 0.649381
[37, 8000] loss: 0.641616
[37, 10000] loss: 0.695684
[37, 12000] loss: 0.704893
[38, 2000] loss: 0.580882
[38, 4000] loss: 0.601066
[38, 6000] loss: 0.653247
[38, 8000] loss: 0.68559
[38, 10000] loss: 0.686562
[38, 12000] loss: 0.711584
[39, 2000] loss: 0.59794
[39, 4000] loss: 0.627048
[39, 6000] loss: 0.61937
[39, 8000] loss: 0.663433
[39, 10000] loss: 0.702988
[39, 12000] loss: 0.693508
[40, 2000] loss: 0.565839
[40, 4000] loss: 0.606084
[40, 6000] loss: 0.661661
[40, 8000] loss: 0.657321
[40, 10000] loss: 0.690926
[40, 12000] loss: 0.720987
[41, 2000] loss: 0.567268
[41, 4000] loss: 0.622507
[41, 6000] loss: 0.639205
[41, 8000] loss: 0.641627
[41, 10000] loss: 0.675187
[41, 12000] loss: 0.728526
[42, 2000] loss: 0.574471
[42, 4000] loss: 0.623977
[42, 6000] loss: 0.652792
[42, 8000] loss: 0.688314
[42, 10000] loss: 0.675221
[42, 12000] loss: 0.701897
[43, 2000] loss: 0.578931
[43, 4000] loss: 0.63291
[43, 6000] loss: 0.63472
[43, 8000] loss: 0.643825
[43, 10000] loss: 0.651531
[43, 12000] loss: 0.693122
[44, 2000] loss: 0.550151
[44, 4000] loss: 0.601773
[44, 6000] loss: 0.663144
[44, 8000] loss: 0.676099
[44, 10000] loss: 0.662861
[44, 12000] loss: 0.65662
[45, 2000] loss: 0.587384
[45, 4000] loss: 0.613454
[45, 6000] loss: 0.616192
[45, 8000] loss: 0.660992
[45, 10000] loss: 0.661208
[45, 12000] loss: 0.662109
[46, 2000] loss: 0.574369
[46, 4000] loss: 0.624527
[46, 6000] loss: 0.609515
[46, 8000] loss: 0.647345
[46, 10000] loss: 0.706663
[46, 12000] loss: 0.678323
[47, 2000] loss: 0.567992
[47, 4000] loss: 0.650829
[47, 6000] loss: 0.608366
[47, 8000] loss: 0.644141
[47, 10000] loss: 0.67278
[47, 12000] loss: 0.67914
[48, 2000] loss: 0.577196
[48, 4000] loss: 0.573142
[48, 6000] loss: 0.632735
[48, 8000] loss: 0.668986
[48, 10000] loss: 0.663707
[48, 12000] loss: 0.670642
[49, 2000] loss: 0.59779
[49, 4000] loss: 0.593744
[49, 6000] loss: 0.640753
[49, 8000] loss: 0.640831
[49, 10000] loss: 0.667435
[49, 12000] loss: 0.709793
[50, 2000] loss: 0.589654
[50, 4000] loss: 0.608169
[50, 6000] loss: 0.662196
[50, 8000] loss: 0.679103
[50, 10000] loss: 0.682992
[50, 12000] loss: 0.689191
LeNet test accuracy: 56%