
c196-011[rtx](1013)$ bash ./test.sh 1 1 1 0.001
TACC:  Starting up job 3503164
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: 1.9408839624755236
epoch: 0, eval loss: 1.7896566271781922, correct: 3488, total: 10000, acc = 0.34880000352859497
epoch time: 40.82966494560242
epoch: 1, train loss: 1.6500030257263962
epoch: 1, eval loss: 1.5464953780174255, correct: 4545, total: 10000, acc = 0.4544999897480011
epoch time: 40.01254224777222
epoch: 2, train loss: 1.422887429899099
epoch: 2, eval loss: 1.37536381483078, correct: 5074, total: 10000, acc = 0.5073999762535095
epoch time: 40.107905864715576
epoch: 3, train loss: 1.3217590207956276
epoch: 3, eval loss: 1.3036327004432677, correct: 5377, total: 10000, acc = 0.5376999974250793
epoch time: 40.12306189537048
epoch: 4, train loss: 1.262234352072891
epoch: 4, eval loss: 1.2568134129047395, correct: 5475, total: 10000, acc = 0.5475000143051147
epoch time: 40.10755228996277
epoch: 5, train loss: 1.2381379117771072
epoch: 5, eval loss: 1.1941023647785187, correct: 5676, total: 10000, acc = 0.5676000118255615
epoch time: 40.119303464889526
epoch: 6, train loss: 1.2061052650821453
epoch: 6, eval loss: 1.1313925206661224, correct: 5938, total: 10000, acc = 0.5938000082969666
epoch time: 40.07719683647156
epoch: 7, train loss: 1.1659562563409611
epoch: 7, eval loss: 1.125486546754837, correct: 5958, total: 10000, acc = 0.59579998254776
epoch time: 40.1702299118042
epoch: 8, train loss: 1.1378972846634534
epoch: 8, eval loss: 1.082760637998581, correct: 6102, total: 10000, acc = 0.6101999878883362
epoch time: 40.22099733352661
epoch: 9, train loss: 1.1073276430976635
epoch: 9, eval loss: 1.1077564001083373, correct: 6038, total: 10000, acc = 0.6037999987602234
epoch time: 40.1106858253479
epoch: 10, train loss: 1.087894769347444
epoch: 10, eval loss: 1.0400531351566316, correct: 6311, total: 10000, acc = 0.6310999989509583
epoch time: 40.20973324775696
epoch: 11, train loss: 1.0556547295074075
epoch: 11, eval loss: 1.0295817345380782, correct: 6359, total: 10000, acc = 0.6358999609947205
epoch time: 40.23791980743408
epoch: 12, train loss: 1.0299884901971232
epoch: 12, eval loss: 1.003737959265709, correct: 6380, total: 10000, acc = 0.6380000114440918
epoch time: 40.08779859542847
epoch: 13, train loss: 0.9972386627781148
epoch: 13, eval loss: 0.9707699298858643, correct: 6499, total: 10000, acc = 0.649899959564209
epoch time: 40.10878801345825
epoch: 14, train loss: 0.9784559072280417
epoch: 14, eval loss: 0.9253897607326508, correct: 6641, total: 10000, acc = 0.6640999913215637
epoch time: 40.13168978691101
epoch: 15, train loss: 0.9409253481699495
epoch: 15, eval loss: 0.9120320588350296, correct: 6759, total: 10000, acc = 0.6758999824523926
epoch time: 40.162830114364624
epoch: 16, train loss: 0.925923115136672
epoch: 16, eval loss: 0.8850776582956315, correct: 6870, total: 10000, acc = 0.6869999766349792
epoch time: 40.145774602890015
epoch: 17, train loss: 0.8923340841215484
epoch: 17, eval loss: 0.8570599347352982, correct: 6950, total: 10000, acc = 0.6949999928474426
epoch time: 40.18058943748474
epoch: 18, train loss: 0.8638542884466599
epoch: 18, eval loss: 0.838410159945488, correct: 6971, total: 10000, acc = 0.6970999836921692
epoch time: 40.110822439193726
epoch: 19, train loss: 0.8400422529298432
epoch: 19, eval loss: 0.8189669162034988, correct: 7097, total: 10000, acc = 0.7096999883651733
epoch time: 40.066970109939575
epoch: 20, train loss: 0.8072922752828015
epoch: 20, eval loss: 0.7772788077592849, correct: 7240, total: 10000, acc = 0.7239999771118164
epoch time: 40.045086145401
epoch: 21, train loss: 0.788195074821005
epoch: 21, eval loss: 0.7793144911527634, correct: 7261, total: 10000, acc = 0.726099967956543
epoch time: 40.05983781814575
epoch: 22, train loss: 0.7574447350842612
epoch: 22, eval loss: 0.7660320281982422, correct: 7272, total: 10000, acc = 0.7271999716758728
epoch time: 40.11693739891052
epoch: 23, train loss: 0.7402738150285215
epoch: 23, eval loss: 0.7264292597770691, correct: 7418, total: 10000, acc = 0.7418000102043152
epoch time: 40.18724513053894
epoch: 24, train loss: 0.7125097580102026
epoch: 24, eval loss: 0.7105035990476608, correct: 7506, total: 10000, acc = 0.7505999803543091
epoch time: 40.1254940032959
epoch: 25, train loss: 0.6900304744438249
epoch: 25, eval loss: 0.6911167114973068, correct: 7562, total: 10000, acc = 0.7561999559402466
epoch time: 40.103896617889404
epoch: 26, train loss: 0.6648721482072558
epoch: 26, eval loss: 0.6780407190322876, correct: 7624, total: 10000, acc = 0.7623999714851379
epoch time: 40.18161463737488
epoch: 27, train loss: 0.6446310062797702
epoch: 27, eval loss: 0.6820667266845704, correct: 7612, total: 10000, acc = 0.761199951171875
epoch time: 40.19018864631653
epoch: 28, train loss: 0.6262476389505425
epoch: 28, eval loss: 0.6506347745656967, correct: 7704, total: 10000, acc = 0.7703999876976013
epoch time: 40.23526978492737
epoch: 29, train loss: 0.5968854001590184
epoch: 29, eval loss: 0.6507940381765366, correct: 7727, total: 10000, acc = 0.7726999521255493
epoch time: 40.26889181137085
epoch: 30, train loss: 0.587430303194085
epoch: 30, eval loss: 0.6333519726991653, correct: 7788, total: 10000, acc = 0.7787999510765076
epoch time: 40.28285789489746
epoch: 31, train loss: 0.5701514035463333
epoch: 31, eval loss: 0.6348810195922852, correct: 7799, total: 10000, acc = 0.7798999547958374
epoch time: 40.199995040893555
epoch: 32, train loss: 0.5482188679125845
epoch: 32, eval loss: 0.6192457497119903, correct: 7833, total: 10000, acc = 0.78329998254776
epoch time: 40.270729780197144
epoch: 33, train loss: 0.534268391375639
epoch: 33, eval loss: 0.6381673783063888, correct: 7790, total: 10000, acc = 0.7789999842643738
epoch time: 40.36342120170593
epoch: 34, train loss: 0.5104483384258893
epoch: 34, eval loss: 0.6173199415206909, correct: 7867, total: 10000, acc = 0.7866999506950378
epoch time: 40.34266257286072
epoch: 35, train loss: 0.4968841674984718
epoch: 35, eval loss: 0.604002220928669, correct: 7916, total: 10000, acc = 0.7915999889373779
epoch time: 40.39444589614868
epoch: 36, train loss: 0.4773432207959039
epoch: 36, eval loss: 0.5884111285209656, correct: 7965, total: 10000, acc = 0.7964999675750732
epoch time: 40.40647268295288
epoch: 37, train loss: 0.4621481445370888
epoch: 37, eval loss: 0.5748852327466011, correct: 8047, total: 10000, acc = 0.8046999573707581
epoch time: 40.29281520843506
epoch: 38, train loss: 0.4431859048045411
epoch: 38, eval loss: 0.5874941781163215, correct: 7995, total: 10000, acc = 0.7994999885559082
epoch time: 40.40029954910278
epoch: 39, train loss: 0.4305852785402415
epoch: 39, eval loss: 0.5991648495197296, correct: 7972, total: 10000, acc = 0.7971999645233154
epoch time: 40.399904012680054
epoch: 40, train loss: 0.4092241589512144
epoch: 40, eval loss: 0.5725525215268135, correct: 8069, total: 10000, acc = 0.8068999648094177
epoch time: 40.32663059234619
epoch: 41, train loss: 0.39218547179990887
epoch: 41, eval loss: 0.5886161357164383, correct: 8068, total: 10000, acc = 0.8068000078201294
epoch time: 40.32424521446228
epoch: 42, train loss: 0.3773612398274091
epoch: 42, eval loss: 0.5762413635849952, correct: 8126, total: 10000, acc = 0.8125999569892883
epoch time: 40.44430422782898
epoch: 43, train loss: 0.3593267098981507
epoch: 43, eval loss: 0.5729024946689606, correct: 8107, total: 10000, acc = 0.810699999332428
epoch time: 40.488121032714844
epoch: 44, train loss: 0.3396431426612698
epoch: 44, eval loss: 0.5944831907749176, correct: 8072, total: 10000, acc = 0.8071999549865723
epoch time: 40.41803979873657
epoch: 45, train loss: 0.32412939716358574
epoch: 45, eval loss: 0.5849291861057282, correct: 8171, total: 10000, acc = 0.8170999884605408
epoch time: 40.428131341934204
epoch: 46, train loss: 0.3099915471916296
epoch: 46, eval loss: 0.5797522723674774, correct: 8121, total: 10000, acc = 0.8120999932289124
epoch time: 40.623990058898926
epoch: 47, train loss: 0.29422828676749246
epoch: 47, eval loss: 0.5898703813552857, correct: 8175, total: 10000, acc = 0.8174999952316284
epoch time: 40.71224045753479
epoch: 48, train loss: 0.27581544600579205
epoch: 48, eval loss: 0.5950756087899208, correct: 8170, total: 10000, acc = 0.8169999718666077
epoch time: 40.53409385681152
epoch: 49, train loss: 0.26118586242807157
epoch: 49, eval loss: 0.5998703584074974, correct: 8213, total: 10000, acc = 0.8212999701499939
epoch time: 40.564385175704956
epoch: 50, train loss: 0.2513351797753451
epoch: 50, eval loss: 0.6011391341686249, correct: 8226, total: 10000, acc = 0.8226000070571899
epoch time: 40.55033254623413
epoch: 51, train loss: 0.22965944299892505
epoch: 51, eval loss: 0.5979882061481476, correct: 8233, total: 10000, acc = 0.8233000040054321
epoch time: 40.54532980918884
epoch: 52, train loss: 0.21661002188920975
epoch: 52, eval loss: 0.6121026620268821, correct: 8220, total: 10000, acc = 0.8219999670982361
epoch time: 40.649473667144775
epoch: 53, train loss: 0.20266114950788264
epoch: 53, eval loss: 0.6016955643892288, correct: 8260, total: 10000, acc = 0.8259999752044678
epoch time: 40.752054929733276
epoch: 54, train loss: 0.19287180794136866
epoch: 54, eval loss: 0.6043265879154205, correct: 8284, total: 10000, acc = 0.8283999562263489
epoch time: 40.68043255805969
epoch: 55, train loss: 0.175087109208107
epoch: 55, eval loss: 0.6146622076630592, correct: 8316, total: 10000, acc = 0.8315999507904053
epoch time: 40.58446717262268
epoch: 56, train loss: 0.16749868762432313
epoch: 56, eval loss: 0.6235148012638092, correct: 8313, total: 10000, acc = 0.8312999606132507
epoch time: 40.62826180458069
epoch: 57, train loss: 0.15567801619062618
epoch: 57, eval loss: 0.6325852945446968, correct: 8308, total: 10000, acc = 0.8307999968528748
epoch time: 40.72224497795105
epoch: 58, train loss: 0.1484297229623308
epoch: 58, eval loss: 0.6329193383455276, correct: 8325, total: 10000, acc = 0.8324999809265137
epoch time: 40.750558614730835
epoch: 59, train loss: 0.14238623818572688
epoch: 59, eval loss: 0.6318104699254036, correct: 8329, total: 10000, acc = 0.8328999876976013
epoch time: 40.77172636985779
finish training