TACC:  Starting up job 3498663 
TACC:  Starting parallel tasks... 
warning: variables which starts with __, is a module or class declaration are omitted
process rank 0 is bound to device 0
distributed environment is initialzied
model is created
Files already downloaded and verified
Files already downloaded and verified
training and testing dataloaders are created
loss is created
optimizer is created
start training
epoch: 0, train loss: 2.095031557034473
epoch: 1, train loss: 1.8454539605549403
epoch: 1, eval loss: 1.7768513083457946, correct: 3564, total: 10000, acc = 0.3563999831676483
epoch: 2, train loss: 1.7044833728245325
epoch: 3, train loss: 1.5999061124665397
epoch: 3, eval loss: 1.5574450254440309, correct: 4389, total: 10000, acc = 0.4388999938964844
epoch: 4, train loss: 1.4929670217085858
epoch: 5, train loss: 1.401450170546162
epoch: 5, eval loss: 1.4644017696380616, correct: 4857, total: 10000, acc = 0.48569998145103455
epoch: 6, train loss: 1.319102376091237
epoch: 7, train loss: 1.2555806539496597
epoch: 7, eval loss: 1.2475590467453004, correct: 5486, total: 10000, acc = 0.5485999584197998
epoch: 8, train loss: 1.1992503173497258
epoch: 9, train loss: 1.1600336493278036
epoch: 9, eval loss: 1.1786625683307648, correct: 5834, total: 10000, acc = 0.5834000110626221
epoch: 10, train loss: 1.1214540807568296
epoch: 11, train loss: 1.0808329728184913
epoch: 11, eval loss: 1.096825110912323, correct: 6072, total: 10000, acc = 0.6071999669075012
epoch: 12, train loss: 1.0521019423494533
epoch: 13, train loss: 1.0262362957000732
epoch: 13, eval loss: 1.056444275379181, correct: 6268, total: 10000, acc = 0.626800000667572
epoch: 14, train loss: 0.9932536555796253
epoch: 15, train loss: 0.9653559442685575
epoch: 15, eval loss: 0.9576991081237793, correct: 6582, total: 10000, acc = 0.6581999659538269
epoch: 16, train loss: 0.9465620943478176
epoch: 17, train loss: 0.9181081974992946
epoch: 17, eval loss: 0.9245584070682525, correct: 6747, total: 10000, acc = 0.6746999621391296
epoch: 18, train loss: 0.8987109752333894
epoch: 19, train loss: 0.8840238646585115
epoch: 19, eval loss: 0.8989996433258056, correct: 6787, total: 10000, acc = 0.6786999702453613
epoch: 20, train loss: 0.8591911811001447
epoch: 21, train loss: 0.843510093129411
epoch: 21, eval loss: 0.8595858901739121, correct: 6969, total: 10000, acc = 0.6969000101089478
epoch: 22, train loss: 0.8306782276046519
epoch: 23, train loss: 0.8181647640101763
epoch: 23, eval loss: 0.8600298583507537, correct: 7005, total: 10000, acc = 0.7005000114440918
epoch: 24, train loss: 0.7964763343334198
epoch: 25, train loss: 0.7840689718723297
epoch: 25, eval loss: 0.824479615688324, correct: 7073, total: 10000, acc = 0.7073000073432922
epoch: 26, train loss: 0.7709570752114666
epoch: 27, train loss: 0.7591698108887186
epoch: 27, eval loss: 0.7967212647199631, correct: 7196, total: 10000, acc = 0.7195999622344971
epoch: 28, train loss: 0.7438001352913526
epoch: 29, train loss: 0.7341659853653032
epoch: 29, eval loss: 0.8041222035884857, correct: 7168, total: 10000, acc = 0.7167999744415283
epoch: 30, train loss: 0.7254330929444761
epoch: 31, train loss: 0.710246913895315
epoch: 31, eval loss: 0.7848481118679047, correct: 7287, total: 10000, acc = 0.7286999821662903
epoch: 32, train loss: 0.6976562008565786
epoch: 33, train loss: 0.6906438475968887
epoch: 33, eval loss: 0.7644171923398971, correct: 7370, total: 10000, acc = 0.7369999885559082
epoch: 34, train loss: 0.6795850834067987
epoch: 35, train loss: 0.6724951656497254
epoch: 35, eval loss: 0.7515032321214676, correct: 7368, total: 10000, acc = 0.736799955368042
epoch: 36, train loss: 0.6527298372619006
epoch: 37, train loss: 0.651018523440069
epoch: 37, eval loss: 0.7381327033042908, correct: 7449, total: 10000, acc = 0.7448999881744385
epoch: 38, train loss: 0.6365304406808348
epoch: 39, train loss: 0.6372388047831399
epoch: 39, eval loss: 0.7342826008796692, correct: 7453, total: 10000, acc = 0.7452999949455261
epoch: 40, train loss: 0.6199644664112403
epoch: 41, train loss: 0.6101092303894005
epoch: 41, eval loss: 0.7353240340948105, correct: 7466, total: 10000, acc = 0.7465999722480774
epoch: 42, train loss: 0.6093496211937496
epoch: 43, train loss: 0.6019633388032719
epoch: 43, eval loss: 0.7350291252136231, correct: 7479, total: 10000, acc = 0.7479000091552734
epoch: 44, train loss: 0.5928211437196148
epoch: 45, train loss: 0.5840530048827736
epoch: 45, eval loss: 0.7301350146532058, correct: 7525, total: 10000, acc = 0.7524999976158142
epoch: 46, train loss: 0.578370426078232
epoch: 47, train loss: 0.5703256440405943
epoch: 47, eval loss: 0.7226948082447052, correct: 7526, total: 10000, acc = 0.7525999546051025
epoch: 48, train loss: 0.5622531275968162
epoch: 49, train loss: 0.5543749076979501
epoch: 49, eval loss: 0.7278151929378509, correct: 7536, total: 10000, acc = 0.753600001335144
epoch: 50, train loss: 0.5494355583677486
epoch: 51, train loss: 0.5427058047177841
epoch: 51, eval loss: 0.7180711388587951, correct: 7608, total: 10000, acc = 0.7608000040054321
epoch: 52, train loss: 0.5323820530760045
epoch: 53, train loss: 0.5341374232452742
epoch: 53, eval loss: 0.7136827558279037, correct: 7618, total: 10000, acc = 0.7617999911308289
epoch: 54, train loss: 0.5295403867351766
epoch: 55, train loss: 0.5226148692320804
epoch: 55, eval loss: 0.7158426463603973, correct: 7624, total: 10000, acc = 0.7623999714851379
epoch: 56, train loss: 0.5206544593888887
epoch: 57, train loss: 0.5186455438331682
epoch: 57, eval loss: 0.7141193479299546, correct: 7611, total: 10000, acc = 0.7610999941825867
epoch: 58, train loss: 0.5130856335163116
epoch: 59, train loss: 0.5103850683995655
epoch: 59, eval loss: 0.7077989399433136, correct: 7628, total: 10000, acc = 0.7627999782562256
finish training
