TACC:  Starting up job 3498212 
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: 1.9590576728995965
epoch: 1, train loss: 1.6275222167676808
epoch: 1, eval loss: 1.5277319371700286, correct: 4435, total: 10000, acc = 0.44349998235702515
epoch: 2, train loss: 1.4355541419009774
epoch: 3, train loss: 1.3253967445723864
epoch: 3, eval loss: 1.309086227416992, correct: 5283, total: 10000, acc = 0.5282999873161316
epoch: 4, train loss: 1.2578775298838714
epoch: 5, train loss: 1.2231916554120121
epoch: 5, eval loss: 1.1699816286563873, correct: 5695, total: 10000, acc = 0.5694999694824219
epoch: 6, train loss: 1.1872552669778162
epoch: 7, train loss: 1.1616783823285783
epoch: 7, eval loss: 1.069484794139862, correct: 6183, total: 10000, acc = 0.6182999610900879
epoch: 8, train loss: 1.1155579333402672
epoch: 9, train loss: 1.0878059365311448
epoch: 9, eval loss: 1.0522838592529298, correct: 6202, total: 10000, acc = 0.620199978351593
epoch: 10, train loss: 1.0780728623575093
epoch: 11, train loss: 1.0522098152004942
epoch: 11, eval loss: 1.0902862310409547, correct: 6148, total: 10000, acc = 0.614799976348877
epoch: 12, train loss: 1.0366473337825464
epoch: 13, train loss: 1.0067467458394108
epoch: 13, eval loss: 0.9696728616952897, correct: 6531, total: 10000, acc = 0.6530999541282654
epoch: 14, train loss: 0.9676224273078295
epoch: 15, train loss: 0.9494374029490412
epoch: 15, eval loss: 0.9511896312236786, correct: 6646, total: 10000, acc = 0.6645999550819397
epoch: 16, train loss: 0.9231320935852674
epoch: 17, train loss: 0.9023846679804276
epoch: 17, eval loss: 0.8728409796953202, correct: 6866, total: 10000, acc = 0.6865999698638916
epoch: 18, train loss: 0.8684309854799387
epoch: 19, train loss: 0.836099565637355
epoch: 19, eval loss: 0.8208363801240921, correct: 7091, total: 10000, acc = 0.7091000080108643
epoch: 20, train loss: 0.8285067890371595
epoch: 21, train loss: 0.7930980793067387
epoch: 21, eval loss: 0.7793890535831451, correct: 7235, total: 10000, acc = 0.7234999537467957
epoch: 22, train loss: 0.762698369366782
epoch: 23, train loss: 0.7376812471418964
epoch: 23, eval loss: 0.746866625547409, correct: 7340, total: 10000, acc = 0.7339999675750732
epoch: 24, train loss: 0.7071484223920472
epoch: 25, train loss: 0.6905171658311572
epoch: 25, eval loss: 0.6909466415643692, correct: 7526, total: 10000, acc = 0.7525999546051025
epoch: 26, train loss: 0.6608500091397033
epoch: 27, train loss: 0.65504517907999
epoch: 27, eval loss: 0.6612646311521531, correct: 7697, total: 10000, acc = 0.7696999907493591
epoch: 28, train loss: 0.6234641969203949
epoch: 29, train loss: 0.6107665622720913
epoch: 29, eval loss: 0.666494044661522, correct: 7704, total: 10000, acc = 0.7703999876976013
epoch: 30, train loss: 0.5875011883219894
epoch: 31, train loss: 0.5739485697478665
epoch: 31, eval loss: 0.6217960953712464, correct: 7828, total: 10000, acc = 0.7827999591827393
epoch: 32, train loss: 0.548510205684876
epoch: 33, train loss: 0.5237194764979032
epoch: 33, eval loss: 0.6254391580820083, correct: 7842, total: 10000, acc = 0.7841999530792236
epoch: 34, train loss: 0.5154265892140719
epoch: 35, train loss: 0.494700480176478
epoch: 35, eval loss: 0.5981663644313813, correct: 7963, total: 10000, acc = 0.7962999939918518
epoch: 36, train loss: 0.4785171020395902
epoch: 37, train loss: 0.46277919259606576
epoch: 37, eval loss: 0.6061880439519882, correct: 7958, total: 10000, acc = 0.795799970626831
epoch: 38, train loss: 0.4398626606075131
epoch: 39, train loss: 0.4206806777083144
epoch: 39, eval loss: 0.6158866941928863, correct: 7959, total: 10000, acc = 0.7958999872207642
epoch: 40, train loss: 0.40768756550185536
epoch: 41, train loss: 0.39494050035671313
epoch: 41, eval loss: 0.5725498422980309, correct: 8132, total: 10000, acc = 0.8131999969482422
epoch: 42, train loss: 0.3742571521778496
epoch: 43, train loss: 0.3583034301290707
epoch: 43, eval loss: 0.5765605017542839, correct: 8155, total: 10000, acc = 0.8154999613761902
epoch: 44, train loss: 0.3342630756752832
epoch: 45, train loss: 0.31316718063792404
epoch: 45, eval loss: 0.583588008582592, correct: 8199, total: 10000, acc = 0.8198999762535095
epoch: 46, train loss: 0.30922748148441315
epoch: 47, train loss: 0.2906164434187266
epoch: 47, eval loss: 0.5934860140085221, correct: 8143, total: 10000, acc = 0.814300000667572
epoch: 48, train loss: 0.2741488078419043
epoch: 49, train loss: 0.2597196321098172
epoch: 49, eval loss: 0.5978868633508683, correct: 8195, total: 10000, acc = 0.8194999694824219
epoch: 50, train loss: 0.2440016470393356
epoch: 51, train loss: 0.2293997729311184
epoch: 51, eval loss: 0.5915440261363983, correct: 8232, total: 10000, acc = 0.823199987411499
epoch: 52, train loss: 0.2132072006257213
epoch: 53, train loss: 0.19785404767917128
epoch: 53, eval loss: 0.6171442106366157, correct: 8258, total: 10000, acc = 0.8258000016212463
epoch: 54, train loss: 0.1838149410121295
epoch: 55, train loss: 0.17691133977199086
epoch: 55, eval loss: 0.623777586221695, correct: 8275, total: 10000, acc = 0.8274999856948853
epoch: 56, train loss: 0.16595362697024735
epoch: 57, train loss: 0.1531825682946614
epoch: 57, eval loss: 0.6466041743755341, correct: 8243, total: 10000, acc = 0.8242999911308289
epoch: 58, train loss: 0.14334788979316243
epoch: 59, train loss: 0.13799503377201605
epoch: 59, eval loss: 0.6496601745486259, correct: 8249, total: 10000, acc = 0.8248999714851379
finish training
