c196-012[rtx](1006)$ bash ./test.sh 1 1 1 0.0001
TACC:  Starting up job 3503177
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
USE_VANILLA model
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: 2.07912605757616
epoch: 0, eval loss: 1.9337591707706452, correct: 2845, total: 10000, acc = 0.28450000286102295
epoch time: 48.79993748664856
epoch: 1, train loss: 1.8506990890113675
epoch: 1, eval loss: 1.7832269430160523, correct: 3506, total: 10000, acc = 0.350600004196167
epoch time: 39.10968255996704
epoch: 2, train loss: 1.707400695401795
epoch: 2, eval loss: 1.6983122050762176, correct: 3935, total: 10000, acc = 0.3935000002384186
epoch time: 39.205119609832764
epoch: 3, train loss: 1.5925798574272467
epoch: 3, eval loss: 1.6361137092113496, correct: 4276, total: 10000, acc = 0.4275999963283539
epoch time: 39.220152378082275
epoch: 4, train loss: 1.4817699790000916
epoch: 4, eval loss: 1.4869949519634247, correct: 4706, total: 10000, acc = 0.4705999791622162
epoch time: 39.297648191452026
epoch: 5, train loss: 1.3685331247290786
epoch: 5, eval loss: 1.4110832333564758, correct: 5043, total: 10000, acc = 0.5042999982833862
epoch time: 39.31484127044678
epoch: 6, train loss: 1.283743022655954
epoch: 6, eval loss: 1.317776972055435, correct: 5320, total: 10000, acc = 0.5320000052452087
epoch time: 39.31891870498657
epoch: 7, train loss: 1.2292176107971036
epoch: 7, eval loss: 1.2397323846817017, correct: 5619, total: 10000, acc = 0.5618999600410461
epoch time: 39.31014013290405
epoch: 8, train loss: 1.1705418606193698
epoch: 8, eval loss: 1.2041720151901245, correct: 5696, total: 10000, acc = 0.569599986076355
epoch time: 39.29190945625305
epoch: 9, train loss: 1.1253369718181843
epoch: 9, eval loss: 1.1219275832176208, correct: 6039, total: 10000, acc = 0.6038999557495117
epoch time: 39.314892053604126
epoch: 10, train loss: 1.0875617825255102
epoch: 10, eval loss: 1.1398449420928956, correct: 5921, total: 10000, acc = 0.5920999646186829
epoch time: 39.29768466949463
epoch: 11, train loss: 1.055325626110544
epoch: 11, eval loss: 1.0739773243665696, correct: 6212, total: 10000, acc = 0.6211999654769897
epoch time: 39.26834416389465
epoch: 12, train loss: 1.0238730627663282
epoch: 12, eval loss: 1.0526267528533935, correct: 6244, total: 10000, acc = 0.6243999600410461
epoch time: 39.30522894859314
epoch: 13, train loss: 0.9906492087305808
epoch: 13, eval loss: 1.0342225402593612, correct: 6295, total: 10000, acc = 0.6294999718666077
epoch time: 39.28985071182251
epoch: 14, train loss: 0.968360669758855
epoch: 14, eval loss: 0.9747557610273361, correct: 6498, total: 10000, acc = 0.6498000025749207
epoch time: 39.33563685417175
epoch: 15, train loss: 0.9413909072778663
epoch: 15, eval loss: 0.9359912216663361, correct: 6659, total: 10000, acc = 0.6658999919891357
epoch time: 39.332377672195435
epoch: 16, train loss: 0.9215109226654987
epoch: 16, eval loss: 0.9215879321098328, correct: 6693, total: 10000, acc = 0.6692999601364136
epoch time: 39.35148882865906
epoch: 17, train loss: 0.9036085179873875
epoch: 17, eval loss: 0.8947311192750931, correct: 6787, total: 10000, acc = 0.6786999702453613
epoch time: 39.31995511054993
epoch: 18, train loss: 0.8774841433885147
epoch: 18, eval loss: 0.8880111247301101, correct: 6844, total: 10000, acc = 0.6843999624252319
epoch time: 39.32100558280945
epoch: 19, train loss: 0.8607137598553483
epoch: 19, eval loss: 0.8770220369100571, correct: 6883, total: 10000, acc = 0.6882999539375305
epoch time: 39.3321533203125
epoch: 20, train loss: 0.8482279163234088
epoch: 20, eval loss: 0.8661656975746155, correct: 6926, total: 10000, acc = 0.6926000118255615
epoch time: 39.319167613983154
epoch: 21, train loss: 0.8280732814146547
epoch: 21, eval loss: 0.8369802534580231, correct: 7041, total: 10000, acc = 0.7040999531745911
epoch time: 39.32543706893921
epoch: 22, train loss: 0.8162973212952517
epoch: 22, eval loss: 0.8281545102596283, correct: 7096, total: 10000, acc = 0.7095999717712402
epoch time: 39.344929695129395
epoch: 23, train loss: 0.8043988426120914
epoch: 23, eval loss: 0.8369941651821137, correct: 7070, total: 10000, acc = 0.7069999575614929
epoch time: 39.342397928237915
epoch: 24, train loss: 0.788704516328111
epoch: 24, eval loss: 0.8305304765701294, correct: 7040, total: 10000, acc = 0.7039999961853027
epoch time: 39.349589347839355
epoch: 25, train loss: 0.7747861517935383
epoch: 25, eval loss: 0.8025588423013688, correct: 7164, total: 10000, acc = 0.7163999676704407
epoch time: 39.35692596435547
epoch: 26, train loss: 0.7557641073149077
epoch: 26, eval loss: 0.7929455429315567, correct: 7204, total: 10000, acc = 0.7203999757766724
epoch time: 39.36091661453247
epoch: 27, train loss: 0.7422851062550837
epoch: 27, eval loss: 0.7790816932916641, correct: 7249, total: 10000, acc = 0.7249000072479248
epoch time: 39.355828046798706
epoch: 28, train loss: 0.7305653861590794
epoch: 28, eval loss: 0.7937072366476059, correct: 7204, total: 10000, acc = 0.7203999757766724
epoch time: 39.3598473072052
epoch: 29, train loss: 0.719313730998915
epoch: 29, eval loss: 0.7657937437295914, correct: 7320, total: 10000, acc = 0.7319999933242798
epoch time: 39.353551626205444
epoch: 30, train loss: 0.7127084263733455
epoch: 30, eval loss: 0.7556168884038925, correct: 7341, total: 10000, acc = 0.7340999841690063
epoch time: 39.37097501754761
epoch: 31, train loss: 0.7044506967067719
epoch: 31, eval loss: 0.7438590109348298, correct: 7359, total: 10000, acc = 0.7358999848365784
epoch time: 39.37364745140076
epoch: 32, train loss: 0.6920064693810989
epoch: 32, eval loss: 0.7408553540706635, correct: 7419, total: 10000, acc = 0.7418999671936035
epoch time: 39.372353076934814
epoch: 33, train loss: 0.6790882920732304
epoch: 33, eval loss: 0.7541307628154754, correct: 7332, total: 10000, acc = 0.733199954032898
epoch time: 39.310251235961914
epoch: 34, train loss: 0.6666433202977083
epoch: 34, eval loss: 0.7413494348526001, correct: 7401, total: 10000, acc = 0.7400999665260315
epoch time: 39.394805908203125
epoch: 35, train loss: 0.6561720742254841
epoch: 35, eval loss: 0.7245241671800613, correct: 7483, total: 10000, acc = 0.7482999563217163
epoch time: 39.34455704689026
epoch: 36, train loss: 0.6433814526820669
epoch: 36, eval loss: 0.7294039458036423, correct: 7483, total: 10000, acc = 0.7482999563217163
epoch time: 39.337549924850464
epoch: 37, train loss: 0.6366085136423305
epoch: 37, eval loss: 0.7336494833230972, correct: 7462, total: 10000, acc = 0.7461999654769897
epoch time: 39.338196754455566
epoch: 38, train loss: 0.6294400272320728
epoch: 38, eval loss: 0.719609409570694, correct: 7532, total: 10000, acc = 0.7531999945640564
epoch time: 39.33430027961731
epoch: 39, train loss: 0.6179663903859197
epoch: 39, eval loss: 0.7210630685091018, correct: 7507, total: 10000, acc = 0.7506999969482422
epoch time: 39.33643341064453
epoch: 40, train loss: 0.6102935781284254
epoch: 40, eval loss: 0.6994094282388688, correct: 7569, total: 10000, acc = 0.7568999528884888
epoch time: 39.38672637939453
epoch: 41, train loss: 0.5990810029360712
epoch: 41, eval loss: 0.7133035778999328, correct: 7550, total: 10000, acc = 0.7549999952316284
epoch time: 39.374757528305054
epoch: 42, train loss: 0.5964441865074391
epoch: 42, eval loss: 0.7060712993144989, correct: 7577, total: 10000, acc = 0.7576999664306641
epoch time: 39.4019033908844
epoch: 43, train loss: 0.5878602710305428
epoch: 43, eval loss: 0.7106044471263886, correct: 7580, total: 10000, acc = 0.7579999566078186
epoch time: 39.408252477645874
epoch: 44, train loss: 0.5797601254010687
epoch: 44, eval loss: 0.7093768745660782, correct: 7568, total: 10000, acc = 0.7567999958992004
epoch time: 39.40289378166199
epoch: 45, train loss: 0.5684604742089097
epoch: 45, eval loss: 0.7075642883777619, correct: 7612, total: 10000, acc = 0.761199951171875
epoch time: 39.35792422294617
epoch: 46, train loss: 0.5617077308041709
epoch: 46, eval loss: 0.707081851363182, correct: 7576, total: 10000, acc = 0.7576000094413757
epoch time: 39.37784481048584
epoch: 47, train loss: 0.5572127462649832
epoch: 47, eval loss: 0.7069586098194123, correct: 7606, total: 10000, acc = 0.7605999708175659
epoch time: 39.33794188499451
epoch: 48, train loss: 0.5519619742218329
epoch: 48, eval loss: 0.6923990368843078, correct: 7679, total: 10000, acc = 0.7678999900817871
epoch time: 39.39500594139099
epoch: 49, train loss: 0.5454421751961416
epoch: 49, eval loss: 0.7032370567321777, correct: 7626, total: 10000, acc = 0.7626000046730042
epoch time: 39.38570594787598
epoch: 50, train loss: 0.5419908360559114
epoch: 50, eval loss: 0.6949253618717194, correct: 7669, total: 10000, acc = 0.7669000029563904
epoch time: 39.334325551986694
epoch: 51, train loss: 0.5299993215166793
epoch: 51, eval loss: 0.6966427147388459, correct: 7654, total: 10000, acc = 0.7653999924659729
epoch time: 39.337984561920166
epoch: 52, train loss: 0.5282451452649369
epoch: 52, eval loss: 0.6932955116033555, correct: 7664, total: 10000, acc = 0.7663999795913696
epoch time: 39.34237813949585
epoch: 53, train loss: 0.5234840703862054
epoch: 53, eval loss: 0.6988086104393005, correct: 7654, total: 10000, acc = 0.7653999924659729
epoch time: 39.364726066589355
epoch: 54, train loss: 0.5139317989957576
epoch: 54, eval loss: 0.6950253814458847, correct: 7643, total: 10000, acc = 0.7642999887466431
epoch time: 39.40451097488403
epoch: 55, train loss: 0.5158528734226616
epoch: 55, eval loss: 0.6978882610797882, correct: 7672, total: 10000, acc = 0.7671999931335449
epoch time: 39.38926696777344
epoch: 56, train loss: 0.5082419429506574
epoch: 56, eval loss: 0.6909049898386002, correct: 7692, total: 10000, acc = 0.7691999673843384
epoch time: 39.42493271827698
epoch: 57, train loss: 0.5027476120360044
epoch: 57, eval loss: 0.6897687911987305, correct: 7695, total: 10000, acc = 0.7694999575614929
epoch time: 39.35954570770264
epoch: 58, train loss: 0.5053188776483342
epoch: 58, eval loss: 0.6899506479501725, correct: 7667, total: 10000, acc = 0.7666999697685242
epoch time: 39.44884634017944
epoch: 59, train loss: 0.4997740634241883
epoch: 59, eval loss: 0.687486720085144, correct: 7678, total: 10000, acc = 0.767799973487854
epoch time: 39.391881465911865
finish training
