TACC:  Starting up job 3497142 
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
warning: variables which starts with __, is a module or class declaration are omitted
process rank 2 is bound to device 2
Files already downloaded and verified
Files already downloaded and verified
warning: variables which starts with __, is a module or class declaration are omitted
process rank 3 is bound to device 3
Files already downloaded and verified
Files already downloaded and verified
Files already downloaded and verified
Files already downloaded and verified
training and testing dataloaders are created
loss is created
optimizer is created
start training
warning: variables which starts with __, is a module or class declaration are omitted
process rank 1 is bound to device 1
Files already downloaded and verified
Files already downloaded and verified
epoch: 0, train loss: 1.9320369898056498
epoch: 1, train loss: 1.6352128605453335
epoch: 1, eval loss: 1.5123237550258637, correct: 4542, total: 10000, acc = 0.45419999957084656
epoch: 2, train loss: 1.4457968728882926
epoch: 3, train loss: 1.3382204977833494
epoch: 3, eval loss: 1.2539702713489533, correct: 5451, total: 10000, acc = 0.5450999736785889
epoch: 4, train loss: 1.2739947474732691
epoch: 5, train loss: 1.2285400483073021
epoch: 5, eval loss: 1.1386113047599793, correct: 5908, total: 10000, acc = 0.5907999873161316
epoch: 6, train loss: 1.1903334296479517
epoch: 7, train loss: 1.1711674235305007
epoch: 7, eval loss: 1.1258068561553956, correct: 5967, total: 10000, acc = 0.5967000126838684
epoch: 8, train loss: 1.1419668745021432
epoch: 9, train loss: 1.1143895728247506
epoch: 9, eval loss: 1.040754759311676, correct: 6224, total: 10000, acc = 0.6223999857902527
epoch: 10, train loss: 1.1041023871120141
epoch: 11, train loss: 1.089750115968743
epoch: 11, eval loss: 1.0472844064235687, correct: 6265, total: 10000, acc = 0.6265000104904175
epoch: 12, train loss: 1.064698440687997
epoch: 13, train loss: 1.038266262229608
epoch: 13, eval loss: 1.0117274671792984, correct: 6415, total: 10000, acc = 0.6414999961853027
epoch: 14, train loss: 1.029945282303557
epoch: 15, train loss: 1.0171620620756734
epoch: 15, eval loss: 0.9712629705667496, correct: 6519, total: 10000, acc = 0.6518999934196472
epoch: 16, train loss: 0.9928132119227429
epoch: 17, train loss: 0.9921575498824217
epoch: 17, eval loss: 0.9429782271385193, correct: 6641, total: 10000, acc = 0.6640999913215637
epoch: 18, train loss: 0.9607366293060536
epoch: 19, train loss: 0.9427766927650997
epoch: 19, eval loss: 0.9346068739891052, correct: 6623, total: 10000, acc = 0.6622999906539917
epoch: 20, train loss: 0.9219280481338501
epoch: 21, train loss: 0.8945026689646195
epoch: 21, eval loss: 0.8710516095161438, correct: 6909, total: 10000, acc = 0.6908999681472778
epoch: 22, train loss: 0.8807675826306246
epoch: 23, train loss: 0.851514169756247
epoch: 23, eval loss: 0.8239740908145905, correct: 7052, total: 10000, acc = 0.7051999568939209
epoch: 24, train loss: 0.8388774534877466
epoch: 25, train loss: 0.8265813291072845
epoch: 25, eval loss: 0.8102335959672928, correct: 7137, total: 10000, acc = 0.713699996471405
epoch: 26, train loss: 0.8057564490911912
epoch: 27, train loss: 0.7816558753957554
epoch: 27, eval loss: 0.7648743063211441, correct: 7292, total: 10000, acc = 0.729200005531311
epoch: 28, train loss: 0.766656969883004
epoch: 29, train loss: 0.7515677390049915
epoch: 29, eval loss: 0.7517296761274338, correct: 7360, total: 10000, acc = 0.7360000014305115
epoch: 30, train loss: 0.7300611174836451
epoch: 31, train loss: 0.7038229193006244
epoch: 31, eval loss: 0.7385401755571366, correct: 7375, total: 10000, acc = 0.7374999523162842
epoch: 32, train loss: 0.6928578931458143
epoch: 33, train loss: 0.672958068093475
epoch: 33, eval loss: 0.6915913820266724, correct: 7596, total: 10000, acc = 0.7595999836921692
epoch: 34, train loss: 0.6505378533382805
epoch: 35, train loss: 0.6292881539889744
epoch: 35, eval loss: 0.7068031072616577, correct: 7567, total: 10000, acc = 0.7566999793052673
epoch: 36, train loss: 0.6092992303322773
epoch: 37, train loss: 0.5922880838720166
epoch: 37, eval loss: 0.6735526144504547, correct: 7662, total: 10000, acc = 0.7662000060081482
epoch: 38, train loss: 0.5777627850065425
epoch: 39, train loss: 0.562178050376931
epoch: 39, eval loss: 0.6323211371898652, correct: 7799, total: 10000, acc = 0.7798999547958374
epoch: 40, train loss: 0.5385949274106901
epoch: 41, train loss: 0.5233490755971597
epoch: 41, eval loss: 0.6360922038555146, correct: 7806, total: 10000, acc = 0.7805999517440796
epoch: 42, train loss: 0.50960702373057
epoch: 43, train loss: 0.48859657985823496
epoch: 43, eval loss: 0.607847985625267, correct: 7914, total: 10000, acc = 0.7913999557495117
epoch: 44, train loss: 0.47382923291654006
epoch: 45, train loss: 0.45052725380780745
epoch: 45, eval loss: 0.5986941397190094, correct: 8012, total: 10000, acc = 0.8011999726295471
epoch: 46, train loss: 0.43711013392526277
epoch: 47, train loss: 0.42507915229213483
epoch: 47, eval loss: 0.5871582478284836, correct: 8002, total: 10000, acc = 0.8001999855041504
epoch: 48, train loss: 0.40591827947266246
epoch: 49, train loss: 0.3911267008100237
epoch: 49, eval loss: 0.5832945287227631, correct: 8047, total: 10000, acc = 0.8046999573707581
epoch: 50, train loss: 0.3770884950550235
epoch: 51, train loss: 0.3587312725733738
epoch: 51, eval loss: 0.5942261666059494, correct: 8073, total: 10000, acc = 0.8072999715805054
epoch: 52, train loss: 0.34132662324272856
epoch: 53, train loss: 0.3267737687850485
epoch: 53, eval loss: 0.5920912757515907, correct: 8118, total: 10000, acc = 0.8118000030517578
epoch: 54, train loss: 0.3116904997399875
epoch: 55, train loss: 0.30321489380938665
epoch: 55, eval loss: 0.5957943320274353, correct: 8082, total: 10000, acc = 0.8082000017166138
epoch: 56, train loss: 0.2874147834218278
epoch: 57, train loss: 0.27991348140093747
epoch: 57, eval loss: 0.5895262002944947, correct: 8165, total: 10000, acc = 0.8165000081062317
epoch: 58, train loss: 0.274563160173747
epoch: 59, train loss: 0.2600744918596988
epoch: 59, eval loss: 0.5934095367789268, correct: 8150, total: 10000, acc = 0.8149999976158142
finish training
