city2eigen.log

W0105 11:10:39.824003  9104 device_context.cc:447] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 10.1, Runtime API Version: 10.1
W0105 11:10:39.830708  9104 device_context.cc:465] device: 0, cuDNN Version: 7.6.
total number of training samples: 22600
total number of training steps: 141250
total number of validation samples: 888
number of trainable parameters: 58452008
batch    100 | examples/s: 27.50 | loss: 0.82033 | time elapsed: 0.01h | time left: 16.71h
batch    200 | examples/s: 27.39 | loss: 0.77667 | time elapsed: 0.02h | time left: 16.37h
batch    300 | examples/s: 27.87 | loss: 0.73725 | time elapsed: 0.03h | time left: 16.22h
batch    400 | examples/s: 26.41 | loss: 0.72170 | time elapsed: 0.05h | time left: 16.15h
batch    500 | examples/s: 28.21 | loss: 0.72490 | time elapsed: 0.06h | time left: 16.07h
batch    600 | examples/s: 28.41 | loss: 0.72501 | time elapsed: 0.07h | time left: 16.03h
batch    700 | examples/s: 27.80 | loss: 0.72987 | time elapsed: 0.08h | time left: 16.02h
batch    800 | examples/s: 28.22 | loss: 0.71136 | time elapsed: 0.09h | time left: 15.99h
batch    900 | examples/s: 27.35 | loss: 0.71467 | time elapsed: 0.10h | time left: 15.96h
batch   1000 | examples/s: 27.97 | loss: 0.68444 | time elapsed: 0.11h | time left: 15.93h
batch   1100 | examples/s: 27.42 | loss: 0.69316 | time elapsed: 0.12h | time left: 15.91h
batch   1200 | examples/s: 27.93 | loss: 0.69581 | time elapsed: 0.14h | time left: 15.89h
batch   1300 | examples/s: 27.94 | loss: 0.70063 | time elapsed: 0.15h | time left: 15.87h
batch   1400 | examples/s: 28.42 | loss: 0.69808 | time elapsed: 0.16h | time left: 15.85h
batch   1500 | examples/s: 27.84 | loss: 0.69758 | time elapsed: 0.17h | time left: 15.83h
batch   1600 | examples/s: 28.28 | loss: 0.67438 | time elapsed: 0.18h | time left: 15.82h
batch   1700 | examples/s: 27.76 | loss: 0.66091 | time elapsed: 0.19h | time left: 15.80h
batch   1800 | examples/s: 28.23 | loss: 0.68425 | time elapsed: 0.20h | time left: 15.78h
batch   1900 | examples/s: 28.17 | loss: 0.69291 | time elapsed: 0.21h | time left: 15.76h
batch   2000 | examples/s: 28.03 | loss: 0.67278 | time elapsed: 0.23h | time left: 15.75h
batch   2100 | examples/s: 27.81 | loss: 0.67941 | time elapsed: 0.24h | time left: 15.74h
batch   2200 | examples/s: 28.14 | loss: 0.66612 | time elapsed: 0.25h | time left: 15.73h
batch   2300 | examples/s: 27.44 | loss: 0.66738 | time elapsed: 0.26h | time left: 15.72h
batch   2400 | examples/s: 27.91 | loss: 0.64577 | time elapsed: 0.27h | time left: 15.70h
batch   2500 | examples/s: 28.05 | loss: 0.65399 | time elapsed: 0.28h | time left: 15.69h
batch   2600 | examples/s: 27.16 | loss: 0.67445 | time elapsed: 0.29h | time left: 15.69h
batch   2700 | examples/s: 25.79 | loss: 0.72103 | time elapsed: 0.31h | time left: 15.70h
batch   2800 | examples/s: 27.44 | loss: 0.67885 | time elapsed: 0.32h | time left: 15.70h
epoch   0 | val loss: 0.66390 | time cost: 21.83 s |
batch   2900 | examples/s: 25.55 | loss: 0.67821 | time elapsed: 0.34h | time left: 16.03h
batch   3000 | examples/s: 27.81 | loss: 0.66793 | time elapsed: 0.35h | time left: 16.03h
batch   3100 | examples/s: 27.66 | loss: 0.66143 | time elapsed: 0.36h | time left: 16.00h
batch   3200 | examples/s: 25.84 | loss: 0.64713 | time elapsed: 0.37h | time left: 15.99h
batch   3300 | examples/s: 27.91 | loss: 0.64495 | time elapsed: 0.38h | time left: 15.98h
batch   3400 | examples/s: 25.19 | loss: 0.64607 | time elapsed: 0.39h | time left: 15.95h
batch   3500 | examples/s: 28.10 | loss: 0.66006 | time elapsed: 0.41h | time left: 15.94h
batch   3600 | examples/s: 28.06 | loss: 0.64116 | time elapsed: 0.42h | time left: 15.92h
batch   3700 | examples/s: 27.63 | loss: 0.64367 | time elapsed: 0.43h | time left: 15.90h
batch   3800 | examples/s: 27.92 | loss: 0.65218 | time elapsed: 0.44h | time left: 15.88h
batch   3900 | examples/s: 28.05 | loss: 0.63624 | time elapsed: 0.45h | time left: 15.85h
batch   4000 | examples/s: 27.72 | loss: 0.66020 | time elapsed: 0.46h | time left: 15.84h
batch   4100 | examples/s: 27.85 | loss: 0.63495 | time elapsed: 0.47h | time left: 15.82h
batch   4200 | examples/s: 28.09 | loss: 0.64657 | time elapsed: 0.48h | time left: 15.80h
batch   4300 | examples/s: 27.67 | loss: 0.64525 | time elapsed: 0.50h | time left: 15.78h
batch   4400 | examples/s: 27.79 | loss: 0.63566 | time elapsed: 0.51h | time left: 15.76h
batch   4500 | examples/s: 28.03 | loss: 0.62973 | time elapsed: 0.52h | time left: 15.74h
batch   4600 | examples/s: 28.22 | loss: 0.65814 | time elapsed: 0.53h | time left: 15.73h
batch   4700 | examples/s: 28.00 | loss: 0.62481 | time elapsed: 0.54h | time left: 15.71h
batch   4800 | examples/s: 27.88 | loss: 0.63505 | time elapsed: 0.55h | time left: 15.69h
batch   4900 | examples/s: 28.44 | loss: 0.62800 | time elapsed: 0.56h | time left: 15.67h
batch   5000 | examples/s: 28.02 | loss: 0.64399 | time elapsed: 0.57h | time left: 15.66h
batch   5100 | examples/s: 27.14 | loss: 0.62483 | time elapsed: 0.59h | time left: 15.65h
batch   5200 | examples/s: 27.82 | loss: 0.60744 | time elapsed: 0.60h | time left: 15.63h
batch   5300 | examples/s: 28.25 | loss: 0.63892 | time elapsed: 0.61h | time left: 15.62h
batch   5400 | examples/s: 28.06 | loss: 0.63310 | time elapsed: 0.62h | time left: 15.60h
batch   5500 | examples/s: 28.27 | loss: 0.63110 | time elapsed: 0.63h | time left: 15.58h
batch   5600 | examples/s: 28.00 | loss: 0.62893 | time elapsed: 0.64h | time left: 15.57h
epoch   1 | val loss: 0.61853 | time cost: 20.13 s |
batch   5700 | examples/s: 28.01 | loss: 0.61408 | time elapsed: 0.66h | time left: 15.71h
batch   5800 | examples/s: 28.00 | loss: 0.62566 | time elapsed: 0.67h | time left: 15.69h
batch   5900 | examples/s: 27.40 | loss: 0.61154 | time elapsed: 0.68h | time left: 15.68h
batch   6000 | examples/s: 27.94 | loss: 0.61885 | time elapsed: 0.69h | time left: 15.66h
batch   6100 | examples/s: 27.11 | loss: 0.61171 | time elapsed: 0.71h | time left: 15.64h
batch   6200 | examples/s: 26.98 | loss: 0.62152 | time elapsed: 0.72h | time left: 15.63h
batch   6300 | examples/s: 26.79 | loss: 0.63764 | time elapsed: 0.73h | time left: 15.61h
batch   6400 | examples/s: 28.10 | loss: 0.61538 | time elapsed: 0.74h | time left: 15.60h
batch   6500 | examples/s: 28.41 | loss: 0.63848 | time elapsed: 0.75h | time left: 15.58h
batch   6600 | examples/s: 28.18 | loss: 0.60483 | time elapsed: 0.76h | time left: 15.57h
batch   6700 | examples/s: 25.65 | loss: 0.60912 | time elapsed: 0.77h | time left: 15.56h
batch   6800 | examples/s: 28.15 | loss: 0.61427 | time elapsed: 0.79h | time left: 15.54h
batch   6900 | examples/s: 27.98 | loss: 0.61963 | time elapsed: 0.80h | time left: 15.53h
batch   7000 | examples/s: 28.06 | loss: 0.60552 | time elapsed: 0.81h | time left: 15.51h
batch   7100 | examples/s: 27.96 | loss: 0.61382 | time elapsed: 0.82h | time left: 15.50h
batch   7200 | examples/s: 27.66 | loss: 0.61785 | time elapsed: 0.83h | time left: 15.49h
batch   7300 | examples/s: 27.44 | loss: 0.60365 | time elapsed: 0.84h | time left: 15.47h
batch   7400 | examples/s: 27.62 | loss: 0.63037 | time elapsed: 0.85h | time left: 15.46h
batch   7500 | examples/s: 27.70 | loss: 0.62598 | time elapsed: 0.87h | time left: 15.44h
batch   7600 | examples/s: 27.32 | loss: 0.61322 | time elapsed: 0.88h | time left: 15.43h
batch   7700 | examples/s: 27.66 | loss: 0.62030 | time elapsed: 0.89h | time left: 15.42h
batch   7800 | examples/s: 27.90 | loss: 0.59910 | time elapsed: 0.90h | time left: 15.40h
batch   7900 | examples/s: 28.00 | loss: 0.63004 | time elapsed: 0.91h | time left: 15.39h
batch   8000 | examples/s: 28.07 | loss: 0.62705 | time elapsed: 0.92h | time left: 15.37h
batch   8100 | examples/s: 27.66 | loss: 0.59545 | time elapsed: 0.93h | time left: 15.36h
batch   8200 | examples/s: 27.52 | loss: 0.59642 | time elapsed: 0.95h | time left: 15.34h
batch   8300 | examples/s: 27.43 | loss: 0.61234 | time elapsed: 0.96h | time left: 15.33h
batch   8400 | examples/s: 26.45 | loss: 0.60877 | time elapsed: 0.97h | time left: 15.32h
epoch   2 | val loss: 0.60458 | time cost: 19.78 s |
batch   8500 | examples/s: 28.41 | loss: 0.59881 | time elapsed: 0.99h | time left: 15.41h
batch   8600 | examples/s: 27.09 | loss: 0.58898 | time elapsed: 1.00h | time left: 15.39h
batch   8700 | examples/s: 27.95 | loss: 0.60074 | time elapsed: 1.01h | time left: 15.38h
batch   8800 | examples/s: 27.74 | loss: 0.60189 | time elapsed: 1.02h | time left: 15.36h
batch   8900 | examples/s: 27.76 | loss: 0.59129 | time elapsed: 1.03h | time left: 15.35h
batch   9000 | examples/s: 25.05 | loss: 0.60457 | time elapsed: 1.04h | time left: 15.33h
batch   9100 | examples/s: 28.10 | loss: 0.59251 | time elapsed: 1.05h | time left: 15.32h
batch   9200 | examples/s: 28.11 | loss: 0.60211 | time elapsed: 1.07h | time left: 15.30h
batch   9300 | examples/s: 28.03 | loss: 0.61766 | time elapsed: 1.08h | time left: 15.28h
batch   9400 | examples/s: 27.34 | loss: 0.60896 | time elapsed: 1.09h | time left: 15.27h
batch   9500 | examples/s: 28.00 | loss: 0.60107 | time elapsed: 1.10h | time left: 15.25h
batch   9600 | examples/s: 25.46 | loss: 0.62332 | time elapsed: 1.11h | time left: 15.24h
batch   9700 | examples/s: 28.42 | loss: 0.61228 | time elapsed: 1.12h | time left: 15.23h
batch   9800 | examples/s: 28.02 | loss: 0.59998 | time elapsed: 1.13h | time left: 15.21h
batch   9900 | examples/s: 27.57 | loss: 0.59430 | time elapsed: 1.15h | time left: 15.20h
batch  10000 | examples/s: 27.21 | loss: 0.60932 | time elapsed: 1.16h | time left: 15.18h
batch  10100 | examples/s: 27.61 | loss: 0.58495 | time elapsed: 1.17h | time left: 15.17h
batch  10200 | examples/s: 28.20 | loss: 0.58354 | time elapsed: 1.18h | time left: 15.15h
batch  10300 | examples/s: 27.56 | loss: 0.60158 | time elapsed: 1.19h | time left: 15.14h
batch  10400 | examples/s: 27.61 | loss: 0.59956 | time elapsed: 1.20h | time left: 15.12h
batch  10500 | examples/s: 27.97 | loss: 0.59452 | time elapsed: 1.21h | time left: 15.11h
batch  10600 | examples/s: 27.98 | loss: 0.60024 | time elapsed: 1.22h | time left: 15.10h
batch  10700 | examples/s: 28.04 | loss: 0.59445 | time elapsed: 1.24h | time left: 15.08h
batch  10800 | examples/s: 27.70 | loss: 0.60514 | time elapsed: 1.25h | time left: 15.07h
batch  10900 | examples/s: 26.77 | loss: 0.59880 | time elapsed: 1.26h | time left: 15.05h
batch  11000 | examples/s: 28.04 | loss: 0.59172 | time elapsed: 1.27h | time left: 15.04h
batch  11100 | examples/s: 27.52 | loss: 0.58568 | time elapsed: 1.28h | time left: 15.03h
batch  11200 | examples/s: 27.67 | loss: 0.59979 | time elapsed: 1.29h | time left: 15.01h
batch  11300 | examples/s: 27.83 | loss: 0.59181 | time elapsed: 1.30h | time left: 15.00h
epoch   3 | val loss: 0.59112 | time cost: 19.43 s |
batch  11400 | examples/s: 28.20 | loss: 0.59499 | time elapsed: 1.32h | time left: 15.06h
batch  11500 | examples/s: 26.93 | loss: 0.57742 | time elapsed: 1.33h | time left: 15.04h
batch  11600 | examples/s: 28.02 | loss: 0.59260 | time elapsed: 1.34h | time left: 15.03h
batch  11700 | examples/s: 28.04 | loss: 0.59889 | time elapsed: 1.36h | time left: 15.01h
batch  11800 | examples/s: 27.50 | loss: 0.58863 | time elapsed: 1.37h | time left: 15.00h
batch  11900 | examples/s: 27.94 | loss: 0.58095 | time elapsed: 1.38h | time left: 14.99h
batch  12000 | examples/s: 27.93 | loss: 0.57710 | time elapsed: 1.39h | time left: 14.97h
batch  12100 | examples/s: 27.49 | loss: 0.57062 | time elapsed: 1.40h | time left: 14.96h
batch  12200 | examples/s: 27.93 | loss: 0.58864 | time elapsed: 1.41h | time left: 14.94h
batch  12300 | examples/s: 26.62 | loss: 0.59060 | time elapsed: 1.42h | time left: 14.93h
batch  12400 | examples/s: 28.17 | loss: 0.58837 | time elapsed: 1.44h | time left: 14.92h
batch  12500 | examples/s: 28.07 | loss: 0.60679 | time elapsed: 1.45h | time left: 14.90h
batch  12600 | examples/s: 28.11 | loss: 0.58561 | time elapsed: 1.46h | time left: 14.89h
batch  12700 | examples/s: 27.61 | loss: 0.57967 | time elapsed: 1.47h | time left: 14.87h
batch  12800 | examples/s: 28.08 | loss: 0.57734 | time elapsed: 1.48h | time left: 14.86h
batch  12900 | examples/s: 27.35 | loss: 0.58531 | time elapsed: 1.49h | time left: 14.84h
batch  13000 | examples/s: 28.00 | loss: 0.58286 | time elapsed: 1.50h | time left: 14.83h
batch  13100 | examples/s: 28.15 | loss: 0.59370 | time elapsed: 1.51h | time left: 14.82h
batch  13200 | examples/s: 27.10 | loss: 0.58994 | time elapsed: 1.53h | time left: 14.80h
batch  13300 | examples/s: 27.84 | loss: 0.59681 | time elapsed: 1.54h | time left: 14.79h
batch  13400 | examples/s: 28.26 | loss: 0.58336 | time elapsed: 1.55h | time left: 14.77h
batch  13500 | examples/s: 28.00 | loss: 0.58642 | time elapsed: 1.56h | time left: 14.76h
batch  13600 | examples/s: 28.19 | loss: 0.58522 | time elapsed: 1.57h | time left: 14.75h
batch  13700 | examples/s: 28.18 | loss: 0.56576 | time elapsed: 1.58h | time left: 14.73h
batch  13800 | examples/s: 28.04 | loss: 0.58969 | time elapsed: 1.59h | time left: 14.72h
batch  13900 | examples/s: 27.73 | loss: 0.57734 | time elapsed: 1.61h | time left: 14.71h
batch  14000 | examples/s: 28.26 | loss: 0.56749 | time elapsed: 1.62h | time left: 14.69h
batch  14100 | examples/s: 28.04 | loss: 0.58815 | time elapsed: 1.63h | time left: 14.68h
epoch   4 | val loss: 0.58245 | time cost: 20.29 s |
batch  14200 | examples/s: 28.02 | loss: 0.58831 | time elapsed: 1.65h | time left: 14.73h
batch  14300 | examples/s: 28.00 | loss: 0.56782 | time elapsed: 1.66h | time left: 14.71h
batch  14400 | examples/s: 27.89 | loss: 0.57117 | time elapsed: 1.67h | time left: 14.70h
batch  14500 | examples/s: 27.96 | loss: 0.56950 | time elapsed: 1.68h | time left: 14.68h
batch  14600 | examples/s: 27.98 | loss: 0.58888 | time elapsed: 1.69h | time left: 14.67h
batch  14700 | examples/s: 26.76 | loss: 0.58136 | time elapsed: 1.70h | time left: 14.66h
batch  14800 | examples/s: 28.12 | loss: 0.58728 | time elapsed: 1.71h | time left: 14.64h
batch  14900 | examples/s: 27.82 | loss: 0.57958 | time elapsed: 1.73h | time left: 14.63h
batch  15000 | examples/s: 28.14 | loss: 0.57694 | time elapsed: 1.74h | time left: 14.62h
batch  15100 | examples/s: 27.88 | loss: 0.57732 | time elapsed: 1.75h | time left: 14.60h
batch  15200 | examples/s: 27.37 | loss: 0.58374 | time elapsed: 1.76h | time left: 14.59h
batch  15300 | examples/s: 28.06 | loss: 0.56564 | time elapsed: 1.77h | time left: 14.58h
batch  15400 | examples/s: 27.45 | loss: 0.59108 | time elapsed: 1.78h | time left: 14.56h
batch  15500 | examples/s: 25.83 | loss: 0.59230 | time elapsed: 1.79h | time left: 14.55h
batch  15600 | examples/s: 28.31 | loss: 0.56872 | time elapsed: 1.81h | time left: 14.54h
batch  15700 | examples/s: 26.80 | loss: 0.55894 | time elapsed: 1.82h | time left: 14.53h
batch  15800 | examples/s: 27.79 | loss: 0.57236 | time elapsed: 1.83h | time left: 14.51h
batch  15900 | examples/s: 27.93 | loss: 0.56903 | time elapsed: 1.84h | time left: 14.50h
batch  16000 | examples/s: 27.88 | loss: 0.56240 | time elapsed: 1.85h | time left: 14.49h
batch  16100 | examples/s: 27.68 | loss: 0.58101 | time elapsed: 1.86h | time left: 14.47h
batch  16200 | examples/s: 28.12 | loss: 0.57149 | time elapsed: 1.87h | time left: 14.46h
batch  16300 | examples/s: 28.45 | loss: 0.56174 | time elapsed: 1.88h | time left: 14.45h
batch  16400 | examples/s: 27.90 | loss: 0.57999 | time elapsed: 1.90h | time left: 14.43h
batch  16500 | examples/s: 28.02 | loss: 0.56800 | time elapsed: 1.91h | time left: 14.42h
batch  16600 | examples/s: 27.32 | loss: 0.57423 | time elapsed: 1.92h | time left: 14.41h
batch  16700 | examples/s: 28.31 | loss: 0.55654 | time elapsed: 1.93h | time left: 14.39h
batch  16800 | examples/s: 28.19 | loss: 0.58644 | time elapsed: 1.94h | time left: 14.38h
batch  16900 | examples/s: 28.26 | loss: 0.56861 | time elapsed: 1.95h | time left: 14.37h
epoch   5 | val loss: 0.57524 | time cost: 19.93 s |
batch  17000 | examples/s: 28.06 | loss: 0.56152 | time elapsed: 1.97h | time left: 14.40h
batch  17100 | examples/s: 27.80 | loss: 0.57906 | time elapsed: 1.98h | time left: 14.39h
batch  17200 | examples/s: 27.31 | loss: 0.57905 | time elapsed: 1.99h | time left: 14.38h
batch  17300 | examples/s: 28.10 | loss: 0.57869 | time elapsed: 2.00h | time left: 14.36h
batch  17400 | examples/s: 27.79 | loss: 0.56567 | time elapsed: 2.02h | time left: 14.35h
batch  17500 | examples/s: 27.10 | loss: 0.55893 | time elapsed: 2.03h | time left: 14.34h
batch  17600 | examples/s: 27.41 | loss: 0.56293 | time elapsed: 2.04h | time left: 14.32h
batch  17700 | examples/s: 27.67 | loss: 0.56714 | time elapsed: 2.05h | time left: 14.31h
batch  17800 | examples/s: 26.64 | loss: 0.57224 | time elapsed: 2.06h | time left: 14.30h
batch  17900 | examples/s: 27.76 | loss: 0.56296 | time elapsed: 2.07h | time left: 14.28h
batch  18000 | examples/s: 28.09 | loss: 0.57317 | time elapsed: 2.08h | time left: 14.27h
batch  18100 | examples/s: 27.59 | loss: 0.56729 | time elapsed: 2.10h | time left: 14.26h
batch  18200 | examples/s: 27.98 | loss: 0.56039 | time elapsed: 2.11h | time left: 14.24h
batch  18300 | examples/s: 27.50 | loss: 0.56186 | time elapsed: 2.12h | time left: 14.23h
batch  18400 | examples/s: 28.06 | loss: 0.55748 | time elapsed: 2.13h | time left: 14.22h
batch  18500 | examples/s: 27.99 | loss: 0.56816 | time elapsed: 2.14h | time left: 14.21h
batch  18600 | examples/s: 27.98 | loss: 0.55835 | time elapsed: 2.15h | time left: 14.19h
batch  18700 | examples/s: 27.87 | loss: 0.56518 | time elapsed: 2.16h | time left: 14.18h
batch  18800 | examples/s: 27.55 | loss: 0.55519 | time elapsed: 2.18h | time left: 14.17h
batch  18900 | examples/s: 27.43 | loss: 0.57370 | time elapsed: 2.19h | time left: 14.15h
batch  19000 | examples/s: 27.90 | loss: 0.57331 | time elapsed: 2.20h | time left: 14.14h
batch  19100 | examples/s: 27.63 | loss: 0.58008 | time elapsed: 2.21h | time left: 14.13h
batch  19200 | examples/s: 27.27 | loss: 0.56507 | time elapsed: 2.22h | time left: 14.12h
batch  19300 | examples/s: 27.61 | loss: 0.57320 | time elapsed: 2.23h | time left: 14.10h
batch  19400 | examples/s: 27.84 | loss: 0.56481 | time elapsed: 2.24h | time left: 14.09h
batch  19500 | examples/s: 28.44 | loss: 0.53896 | time elapsed: 2.25h | time left: 14.08h
batch  19600 | examples/s: 27.79 | loss: 0.55673 | time elapsed: 2.27h | time left: 14.06h
batch  19700 | examples/s: 26.84 | loss: 0.55677 | time elapsed: 2.28h | time left: 14.05h
epoch   6 | val loss: 0.56634 | time cost: 19.47 s |
batch  19800 | examples/s: 26.34 | loss: 0.58285 | time elapsed: 2.30h | time left: 14.08h
batch  19900 | examples/s: 27.61 | loss: 0.55737 | time elapsed: 2.31h | time left: 14.07h
batch  20000 | examples/s: 27.83 | loss: 0.55288 | time elapsed: 2.32h | time left: 14.05h
batch  20100 | examples/s: 28.43 | loss: 0.57382 | time elapsed: 2.33h | time left: 14.04h
batch  20200 | examples/s: 26.61 | loss: 0.55117 | time elapsed: 2.34h | time left: 14.03h
batch  20300 | examples/s: 25.43 | loss: 0.55244 | time elapsed: 2.35h | time left: 14.01h
batch  20400 | examples/s: 27.62 | loss: 0.56656 | time elapsed: 2.36h | time left: 14.00h
batch  20500 | examples/s: 27.76 | loss: 0.55803 | time elapsed: 2.38h | time left: 13.99h
batch  20600 | examples/s: 27.45 | loss: 0.56880 | time elapsed: 2.39h | time left: 13.98h
batch  20700 | examples/s: 28.36 | loss: 0.57564 | time elapsed: 2.40h | time left: 13.96h
batch  20800 | examples/s: 27.53 | loss: 0.56959 | time elapsed: 2.41h | time left: 13.95h
batch  20900 | examples/s: 28.22 | loss: 0.55820 | time elapsed: 2.42h | time left: 13.94h
batch  21000 | examples/s: 27.06 | loss: 0.56081 | time elapsed: 2.43h | time left: 13.93h
batch  21100 | examples/s: 28.14 | loss: 0.55782 | time elapsed: 2.44h | time left: 13.91h
batch  21200 | examples/s: 27.25 | loss: 0.55757 | time elapsed: 2.45h | time left: 13.90h
batch  21300 | examples/s: 26.43 | loss: 0.56202 | time elapsed: 2.47h | time left: 13.89h
batch  21400 | examples/s: 27.40 | loss: 0.56269 | time elapsed: 2.48h | time left: 13.88h
batch  21500 | examples/s: 27.25 | loss: 0.54771 | time elapsed: 2.49h | time left: 13.86h
batch  21600 | examples/s: 27.73 | loss: 0.55927 | time elapsed: 2.50h | time left: 13.85h
batch  21700 | examples/s: 27.68 | loss: 0.55276 | time elapsed: 2.51h | time left: 13.84h
batch  21800 | examples/s: 27.52 | loss: 0.55022 | time elapsed: 2.52h | time left: 13.82h
batch  21900 | examples/s: 27.81 | loss: 0.55529 | time elapsed: 2.53h | time left: 13.81h
batch  22000 | examples/s: 28.44 | loss: 0.55172 | time elapsed: 2.55h | time left: 13.80h
batch  22100 | examples/s: 27.63 | loss: 0.54654 | time elapsed: 2.56h | time left: 13.79h
batch  22200 | examples/s: 27.16 | loss: 0.54917 | time elapsed: 2.57h | time left: 13.77h
batch  22300 | examples/s: 27.61 | loss: 0.55082 | time elapsed: 2.58h | time left: 13.76h
batch  22400 | examples/s: 27.07 | loss: 0.55593 | time elapsed: 2.59h | time left: 13.75h
batch  22500 | examples/s: 27.27 | loss: 0.57120 | time elapsed: 2.60h | time left: 13.74h
batch  22600 | examples/s: 28.15 | loss: 0.56622 | time elapsed: 2.61h | time left: 13.73h
epoch   7 | val loss: 0.55740 | time cost: 19.64 s |
batch  22700 | examples/s: 27.34 | loss: 0.55705 | time elapsed: 2.63h | time left: 13.75h
batch  22800 | examples/s: 28.07 | loss: 0.53786 | time elapsed: 2.64h | time left: 13.73h
batch  22900 | examples/s: 27.68 | loss: 0.54565 | time elapsed: 2.66h | time left: 13.72h
batch  23000 | examples/s: 27.91 | loss: 0.54827 | time elapsed: 2.67h | time left: 13.71h
batch  23100 | examples/s: 26.96 | loss: 0.56558 | time elapsed: 2.68h | time left: 13.70h
batch  23200 | examples/s: 28.32 | loss: 0.57106 | time elapsed: 2.69h | time left: 13.69h
batch  23300 | examples/s: 26.23 | loss: 0.56129 | time elapsed: 2.70h | time left: 13.68h
batch  23400 | examples/s: 26.82 | loss: 0.55523 | time elapsed: 2.71h | time left: 13.66h
batch  23500 | examples/s: 27.83 | loss: 0.54732 | time elapsed: 2.72h | time left: 13.65h
batch  23600 | examples/s: 26.94 | loss: 0.55432 | time elapsed: 2.74h | time left: 13.64h
batch  23700 | examples/s: 27.85 | loss: 0.55461 | time elapsed: 2.75h | time left: 13.63h
batch  23800 | examples/s: 27.59 | loss: 0.55278 | time elapsed: 2.76h | time left: 13.61h
batch  23900 | examples/s: 26.41 | loss: 0.53356 | time elapsed: 2.77h | time left: 13.60h
batch  24000 | examples/s: 27.46 | loss: 0.56431 | time elapsed: 2.78h | time left: 13.59h
batch  24100 | examples/s: 27.81 | loss: 0.55644 | time elapsed: 2.79h | time left: 13.58h
batch  24200 | examples/s: 28.33 | loss: 0.54360 | time elapsed: 2.80h | time left: 13.56h
batch  24300 | examples/s: 27.67 | loss: 0.54442 | time elapsed: 2.82h | time left: 13.55h
batch  24400 | examples/s: 27.56 | loss: 0.53933 | time elapsed: 2.83h | time left: 13.54h
batch  24500 | examples/s: 26.72 | loss: 0.56240 | time elapsed: 2.84h | time left: 13.53h
batch  24600 | examples/s: 27.83 | loss: 0.55632 | time elapsed: 2.85h | time left: 13.51h
batch  24700 | examples/s: 28.00 | loss: 0.55519 | time elapsed: 2.86h | time left: 13.50h
batch  24800 | examples/s: 26.98 | loss: 0.54791 | time elapsed: 2.87h | time left: 13.49h
batch  24900 | examples/s: 26.99 | loss: 0.54836 | time elapsed: 2.88h | time left: 13.48h
batch  25000 | examples/s: 25.94 | loss: 0.55263 | time elapsed: 2.90h | time left: 13.46h
batch  25100 | examples/s: 28.15 | loss: 0.55512 | time elapsed: 2.91h | time left: 13.45h
batch  25200 | examples/s: 27.89 | loss: 0.54543 | time elapsed: 2.92h | time left: 13.44h
batch  25300 | examples/s: 27.87 | loss: 0.55148 | time elapsed: 2.93h | time left: 13.43h
batch  25400 | examples/s: 27.10 | loss: 0.55627 | time elapsed: 2.94h | time left: 13.41h
epoch   8 | val loss: 0.55619 | time cost: 19.61 s |
batch  25500 | examples/s: 27.52 | loss: 0.55487 | time elapsed: 2.96h | time left: 13.43h
batch  25600 | examples/s: 27.71 | loss: 0.55327 | time elapsed: 2.97h | time left: 13.42h
batch  25700 | examples/s: 28.44 | loss: 0.54799 | time elapsed: 2.98h | time left: 13.41h
batch  25800 | examples/s: 28.01 | loss: 0.54375 | time elapsed: 2.99h | time left: 13.39h
batch  25900 | examples/s: 27.23 | loss: 0.56455 | time elapsed: 3.00h | time left: 13.38h
batch  26000 | examples/s: 28.04 | loss: 0.53730 | time elapsed: 3.02h | time left: 13.37h
batch  26100 | examples/s: 27.92 | loss: 0.54794 | time elapsed: 3.03h | time left: 13.36h
batch  26200 | examples/s: 27.11 | loss: 0.54697 | time elapsed: 3.04h | time left: 13.34h
batch  26300 | examples/s: 27.91 | loss: 0.54647 | time elapsed: 3.05h | time left: 13.33h
batch  26400 | examples/s: 27.61 | loss: 0.54723 | time elapsed: 3.06h | time left: 13.32h
batch  26500 | examples/s: 28.01 | loss: 0.55877 | time elapsed: 3.07h | time left: 13.31h
batch  26600 | examples/s: 28.01 | loss: 0.54652 | time elapsed: 3.08h | time left: 13.29h
batch  26700 | examples/s: 26.86 | loss: 0.54411 | time elapsed: 3.10h | time left: 13.28h
batch  26800 | examples/s: 27.71 | loss: 0.57523 | time elapsed: 3.11h | time left: 13.27h
batch  26900 | examples/s: 28.15 | loss: 0.53494 | time elapsed: 3.12h | time left: 13.26h
batch  27000 | examples/s: 27.80 | loss: 0.54616 | time elapsed: 3.13h | time left: 13.24h
batch  27100 | examples/s: 27.53 | loss: 0.54009 | time elapsed: 3.14h | time left: 13.23h
batch  27200 | examples/s: 26.88 | loss: 0.55100 | time elapsed: 3.15h | time left: 13.22h
batch  27300 | examples/s: 27.12 | loss: 0.54020 | time elapsed: 3.16h | time left: 13.21h
batch  27400 | examples/s: 28.05 | loss: 0.53739 | time elapsed: 3.18h | time left: 13.20h
batch  27500 | examples/s: 27.02 | loss: 0.54698 | time elapsed: 3.19h | time left: 13.18h
batch  27600 | examples/s: 27.77 | loss: 0.55193 | time elapsed: 3.20h | time left: 13.17h
batch  27700 | examples/s: 26.60 | loss: 0.54568 | time elapsed: 3.21h | time left: 13.16h
batch  27800 | examples/s: 28.09 | loss: 0.52324 | time elapsed: 3.22h | time left: 13.15h
batch  27900 | examples/s: 26.37 | loss: 0.54287 | time elapsed: 3.23h | time left: 13.13h
batch  28000 | examples/s: 27.46 | loss: 0.55190 | time elapsed: 3.24h | time left: 13.12h
batch  28100 | examples/s: 27.88 | loss: 0.52904 | time elapsed: 3.26h | time left: 13.11h
batch  28200 | examples/s: 27.43 | loss: 0.55778 | time elapsed: 3.27h | time left: 13.10h
epoch   9 | val loss: 0.55467 | time cost: 19.70 s |
batch  28300 | examples/s: 26.89 | loss: 0.53381 | time elapsed: 3.29h | time left: 13.12h
batch  28400 | examples/s: 28.15 | loss: 0.54251 | time elapsed: 3.30h | time left: 13.10h
batch  28500 | examples/s: 27.66 | loss: 0.54879 | time elapsed: 3.31h | time left: 13.09h
batch  28600 | examples/s: 28.16 | loss: 0.54543 | time elapsed: 3.32h | time left: 13.08h
batch  28700 | examples/s: 26.92 | loss: 0.54069 | time elapsed: 3.33h | time left: 13.07h
batch  28800 | examples/s: 27.20 | loss: 0.53774 | time elapsed: 3.34h | time left: 13.05h
batch  28900 | examples/s: 27.72 | loss: 0.52464 | time elapsed: 3.35h | time left: 13.04h
batch  29000 | examples/s: 27.86 | loss: 0.52343 | time elapsed: 3.37h | time left: 13.03h
batch  29100 | examples/s: 27.57 | loss: 0.54460 | time elapsed: 3.38h | time left: 13.02h
batch  29200 | examples/s: 28.30 | loss: 0.53247 | time elapsed: 3.39h | time left: 13.00h
batch  29300 | examples/s: 28.11 | loss: 0.54299 | time elapsed: 3.40h | time left: 12.99h
batch  29400 | examples/s: 27.88 | loss: 0.55855 | time elapsed: 3.41h | time left: 12.98h
batch  29500 | examples/s: 27.89 | loss: 0.53500 | time elapsed: 3.42h | time left: 12.97h
batch  29600 | examples/s: 27.83 | loss: 0.53527 | time elapsed: 3.43h | time left: 12.95h
batch  29700 | examples/s: 28.27 | loss: 0.54673 | time elapsed: 3.45h | time left: 12.94h
batch  29800 | examples/s: 28.29 | loss: 0.52468 | time elapsed: 3.46h | time left: 12.93h
batch  29900 | examples/s: 27.94 | loss: 0.54091 | time elapsed: 3.47h | time left: 12.92h
batch  30000 | examples/s: 27.46 | loss: 0.53595 | time elapsed: 3.48h | time left: 12.90h
batch  30100 | examples/s: 28.12 | loss: 0.53742 | time elapsed: 3.49h | time left: 12.89h
batch  30200 | examples/s: 27.91 | loss: 0.54317 | time elapsed: 3.50h | time left: 12.88h
batch  30300 | examples/s: 28.24 | loss: 0.54872 | time elapsed: 3.51h | time left: 12.86h
batch  30400 | examples/s: 28.07 | loss: 0.54492 | time elapsed: 3.52h | time left: 12.85h
batch  30500 | examples/s: 28.14 | loss: 0.56244 | time elapsed: 3.54h | time left: 12.84h
batch  30600 | examples/s: 27.58 | loss: 0.54110 | time elapsed: 3.55h | time left: 12.83h
batch  30700 | examples/s: 26.83 | loss: 0.53740 | time elapsed: 3.56h | time left: 12.81h
batch  30800 | examples/s: 27.69 | loss: 0.54616 | time elapsed: 3.57h | time left: 12.80h
batch  30900 | examples/s: 27.76 | loss: 0.53993 | time elapsed: 3.58h | time left: 12.79h
batch  31000 | examples/s: 26.69 | loss: 0.55069 | time elapsed: 3.59h | time left: 12.78h
epoch  10 | val loss: 0.54693 | time cost: 19.51 s |
batch  31100 | examples/s: 27.42 | loss: 0.53400 | time elapsed: 3.61h | time left: 12.79h
batch  31200 | examples/s: 27.98 | loss: 0.53659 | time elapsed: 3.62h | time left: 12.77h
batch  31300 | examples/s: 27.79 | loss: 0.54275 | time elapsed: 3.63h | time left: 12.76h
batch  31400 | examples/s: 27.44 | loss: 0.53635 | time elapsed: 3.64h | time left: 12.75h
batch  31500 | examples/s: 27.83 | loss: 0.54994 | time elapsed: 3.66h | time left: 12.74h
batch  31600 | examples/s: 27.89 | loss: 0.53549 | time elapsed: 3.67h | time left: 12.72h
batch  31700 | examples/s: 26.99 | loss: 0.53266 | time elapsed: 3.68h | time left: 12.71h
batch  31800 | examples/s: 28.12 | loss: 0.53227 | time elapsed: 3.69h | time left: 12.70h
batch  31900 | examples/s: 28.06 | loss: 0.54250 | time elapsed: 3.70h | time left: 12.69h
batch  32000 | examples/s: 28.52 | loss: 0.53283 | time elapsed: 3.71h | time left: 12.67h
batch  32100 | examples/s: 27.76 | loss: 0.53259 | time elapsed: 3.72h | time left: 12.66h
batch  32200 | examples/s: 28.01 | loss: 0.54186 | time elapsed: 3.73h | time left: 12.65h
batch  32300 | examples/s: 27.83 | loss: 0.53105 | time elapsed: 3.75h | time left: 12.64h
batch  32400 | examples/s: 28.20 | loss: 0.53571 | time elapsed: 3.76h | time left: 12.62h
batch  32500 | examples/s: 26.71 | loss: 0.53986 | time elapsed: 3.77h | time left: 12.61h
batch  32600 | examples/s: 27.03 | loss: 0.54030 | time elapsed: 3.78h | time left: 12.60h
batch  32700 | examples/s: 28.05 | loss: 0.53717 | time elapsed: 3.79h | time left: 12.59h
batch  32800 | examples/s: 28.07 | loss: 0.53026 | time elapsed: 3.80h | time left: 12.57h
batch  32900 | examples/s: 28.12 | loss: 0.52282 | time elapsed: 3.81h | time left: 12.56h
batch  33000 | examples/s: 27.79 | loss: 0.53676 | time elapsed: 3.83h | time left: 12.55h
batch  33100 | examples/s: 27.49 | loss: 0.53392 | time elapsed: 3.84h | time left: 12.54h
batch  33200 | examples/s: 28.04 | loss: 0.52921 | time elapsed: 3.85h | time left: 12.53h
batch  33300 | examples/s: 27.89 | loss: 0.53921 | time elapsed: 3.86h | time left: 12.51h
batch  33400 | examples/s: 27.94 | loss: 0.52671 | time elapsed: 3.87h | time left: 12.50h
batch  33500 | examples/s: 26.65 | loss: 0.52910 | time elapsed: 3.88h | time left: 12.49h
batch  33600 | examples/s: 27.05 | loss: 0.52691 | time elapsed: 3.89h | time left: 12.48h
batch  33700 | examples/s: 28.03 | loss: 0.53484 | time elapsed: 3.91h | time left: 12.46h
batch  33800 | examples/s: 26.98 | loss: 0.53947 | time elapsed: 3.92h | time left: 12.45h
batch  33900 | examples/s: 26.39 | loss: 0.53383 | time elapsed: 3.93h | time left: 12.44h
epoch  11 | val loss: 0.54389 | time cost: 19.85 s |
batch  34000 | examples/s: 28.41 | loss: 0.53804 | time elapsed: 3.95h | time left: 12.45h
batch  34100 | examples/s: 27.99 | loss: 0.52940 | time elapsed: 3.96h | time left: 12.44h
batch  34200 | examples/s: 28.14 | loss: 0.54314 | time elapsed: 3.97h | time left: 12.42h
batch  34300 | examples/s: 27.06 | loss: 0.53740 | time elapsed: 3.98h | time left: 12.41h
batch  34400 | examples/s: 27.79 | loss: 0.53837 | time elapsed: 3.99h | time left: 12.40h
batch  34500 | examples/s: 27.30 | loss: 0.52681 | time elapsed: 4.00h | time left: 12.39h
batch  34600 | examples/s: 27.74 | loss: 0.54232 | time elapsed: 4.01h | time left: 12.37h
batch  34700 | examples/s: 27.65 | loss: 0.55458 | time elapsed: 4.03h | time left: 12.36h
batch  34800 | examples/s: 27.61 | loss: 0.54335 | time elapsed: 4.04h | time left: 12.35h
batch  34900 | examples/s: 28.08 | loss: 0.53055 | time elapsed: 4.05h | time left: 12.34h
batch  35000 | examples/s: 26.83 | loss: 0.52805 | time elapsed: 4.06h | time left: 12.33h
batch  35100 | examples/s: 27.62 | loss: 0.52866 | time elapsed: 4.07h | time left: 12.31h
batch  35200 | examples/s: 27.87 | loss: 0.54548 | time elapsed: 4.08h | time left: 12.30h
batch  35300 | examples/s: 27.22 | loss: 0.52658 | time elapsed: 4.09h | time left: 12.29h
batch  35400 | examples/s: 27.86 | loss: 0.52625 | time elapsed: 4.11h | time left: 12.28h
batch  35500 | examples/s: 28.70 | loss: 0.52249 | time elapsed: 4.12h | time left: 12.26h
batch  35600 | examples/s: 28.11 | loss: 0.51880 | time elapsed: 4.13h | time left: 12.25h
batch  35700 | examples/s: 28.13 | loss: 0.53723 | time elapsed: 4.14h | time left: 12.24h
batch  35800 | examples/s: 27.63 | loss: 0.53024 | time elapsed: 4.15h | time left: 12.23h
batch  35900 | examples/s: 27.64 | loss: 0.52222 | time elapsed: 4.16h | time left: 12.21h
batch  36000 | examples/s: 27.80 | loss: 0.53110 | time elapsed: 4.17h | time left: 12.20h
batch  36100 | examples/s: 27.93 | loss: 0.53316 | time elapsed: 4.18h | time left: 12.19h
batch  36200 | examples/s: 27.50 | loss: 0.52928 | time elapsed: 4.20h | time left: 12.18h
batch  36300 | examples/s: 28.05 | loss: 0.52257 | time elapsed: 4.21h | time left: 12.16h
batch  36400 | examples/s: 27.85 | loss: 0.53008 | time elapsed: 4.22h | time left: 12.15h
batch  36500 | examples/s: 26.96 | loss: 0.52333 | time elapsed: 4.23h | time left: 12.14h
batch  36600 | examples/s: 26.33 | loss: 0.51696 | time elapsed: 4.24h | time left: 12.13h
batch  36700 | examples/s: 26.88 | loss: 0.54559 | time elapsed: 4.25h | time left: 12.12h
epoch  12 | val loss: 0.53987 | time cost: 19.69 s |
batch  36800 | examples/s: 27.75 | loss: 0.52225 | time elapsed: 4.27h | time left: 12.12h
batch  36900 | examples/s: 28.14 | loss: 0.54262 | time elapsed: 4.28h | time left: 12.11h
batch  37000 | examples/s: 27.79 | loss: 0.51715 | time elapsed: 4.29h | time left: 12.10h
batch  37100 | examples/s: 27.63 | loss: 0.51906 | time elapsed: 4.31h | time left: 12.09h
batch  37200 | examples/s: 28.26 | loss: 0.52697 | time elapsed: 4.32h | time left: 12.07h
batch  37300 | examples/s: 27.79 | loss: 0.51640 | time elapsed: 4.33h | time left: 12.06h
batch  37400 | examples/s: 27.93 | loss: 0.53349 | time elapsed: 4.34h | time left: 12.05h
batch  37500 | examples/s: 28.20 | loss: 0.53589 | time elapsed: 4.35h | time left: 12.04h
batch  37600 | examples/s: 28.31 | loss: 0.53394 | time elapsed: 4.36h | time left: 12.03h
batch  37700 | examples/s: 28.07 | loss: 0.53590 | time elapsed: 4.37h | time left: 12.01h
batch  37800 | examples/s: 27.94 | loss: 0.53261 | time elapsed: 4.38h | time left: 12.00h
batch  37900 | examples/s: 27.45 | loss: 0.51571 | time elapsed: 4.40h | time left: 11.99h
batch  38000 | examples/s: 27.56 | loss: 0.53990 | time elapsed: 4.41h | time left: 11.98h
batch  38100 | examples/s: 27.98 | loss: 0.51508 | time elapsed: 4.42h | time left: 11.96h
batch  38200 | examples/s: 27.27 | loss: 0.53659 | time elapsed: 4.43h | time left: 11.95h
batch  38300 | examples/s: 28.07 | loss: 0.52050 | time elapsed: 4.44h | time left: 11.94h
batch  38400 | examples/s: 27.95 | loss: 0.53286 | time elapsed: 4.45h | time left: 11.93h
batch  38500 | examples/s: 27.27 | loss: 0.52913 | time elapsed: 4.46h | time left: 11.91h
batch  38600 | examples/s: 27.74 | loss: 0.52677 | time elapsed: 4.48h | time left: 11.90h
batch  38700 | examples/s: 28.14 | loss: 0.51739 | time elapsed: 4.49h | time left: 11.89h
batch  38800 | examples/s: 27.86 | loss: 0.53755 | time elapsed: 4.50h | time left: 11.88h
batch  38900 | examples/s: 28.25 | loss: 0.53478 | time elapsed: 4.51h | time left: 11.87h
batch  39000 | examples/s: 27.93 | loss: 0.52800 | time elapsed: 4.52h | time left: 11.85h
batch  39100 | examples/s: 27.43 | loss: 0.51833 | time elapsed: 4.53h | time left: 11.84h
batch  39200 | examples/s: 28.19 | loss: 0.54036 | time elapsed: 4.54h | time left: 11.83h
batch  39300 | examples/s: 27.63 | loss: 0.53033 | time elapsed: 4.56h | time left: 11.82h
batch  39400 | examples/s: 27.61 | loss: 0.52274 | time elapsed: 4.57h | time left: 11.80h
batch  39500 | examples/s: 28.07 | loss: 0.53059 | time elapsed: 4.58h | time left: 11.79h
epoch  13 | val loss: 0.54009 | time cost: 19.56 s |
batch  39600 | examples/s: 27.51 | loss: 0.51761 | time elapsed: 4.60h | time left: 11.80h
batch  39700 | examples/s: 28.15 | loss: 0.51548 | time elapsed: 4.61h | time left: 11.78h
batch  39800 | examples/s: 27.67 | loss: 0.52771 | time elapsed: 4.62h | time left: 11.77h
batch  39900 | examples/s: 27.93 | loss: 0.52854 | time elapsed: 4.63h | time left: 11.76h
batch  40000 | examples/s: 27.79 | loss: 0.51917 | time elapsed: 4.64h | time left: 11.75h
batch  40100 | examples/s: 27.57 | loss: 0.51784 | time elapsed: 4.65h | time left: 11.73h
batch  40200 | examples/s: 27.58 | loss: 0.51525 | time elapsed: 4.66h | time left: 11.72h
batch  40300 | examples/s: 27.84 | loss: 0.53196 | time elapsed: 4.68h | time left: 11.71h
batch  40400 | examples/s: 28.08 | loss: 0.52704 | time elapsed: 4.69h | time left: 11.70h
batch  40500 | examples/s: 27.00 | loss: 0.52040 | time elapsed: 4.70h | time left: 11.69h
batch  40600 | examples/s: 27.57 | loss: 0.53029 | time elapsed: 4.71h | time left: 11.67h
batch  40700 | examples/s: 26.99 | loss: 0.53528 | time elapsed: 4.72h | time left: 11.66h
batch  40800 | examples/s: 27.93 | loss: 0.52507 | time elapsed: 4.73h | time left: 11.65h
batch  40900 | examples/s: 27.84 | loss: 0.53774 | time elapsed: 4.74h | time left: 11.64h
batch  41000 | examples/s: 27.97 | loss: 0.55220 | time elapsed: 4.75h | time left: 11.63h
batch  41100 | examples/s: 25.34 | loss: 0.51517 | time elapsed: 4.77h | time left: 11.61h
batch  41200 | examples/s: 27.36 | loss: 0.52306 | time elapsed: 4.78h | time left: 11.60h
batch  41300 | examples/s: 27.39 | loss: 0.52237 | time elapsed: 4.79h | time left: 11.59h
batch  41400 | examples/s: 27.41 | loss: 0.53614 | time elapsed: 4.80h | time left: 11.58h
batch  41500 | examples/s: 26.33 | loss: 0.51571 | time elapsed: 4.81h | time left: 11.57h
batch  41600 | examples/s: 27.70 | loss: 0.52521 | time elapsed: 4.82h | time left: 11.55h
batch  41700 | examples/s: 25.93 | loss: 0.53407 | time elapsed: 4.83h | time left: 11.54h
batch  41800 | examples/s: 28.06 | loss: 0.51962 | time elapsed: 4.85h | time left: 11.53h
batch  41900 | examples/s: 27.64 | loss: 0.52884 | time elapsed: 4.86h | time left: 11.52h
batch  42000 | examples/s: 28.27 | loss: 0.51925 | time elapsed: 4.87h | time left: 11.51h
batch  42100 | examples/s: 28.31 | loss: 0.52827 | time elapsed: 4.88h | time left: 11.49h
batch  42200 | examples/s: 28.01 | loss: 0.51438 | time elapsed: 4.89h | time left: 11.48h
batch  42300 | examples/s: 28.15 | loss: 0.51487 | time elapsed: 4.90h | time left: 11.47h
epoch  14 | val loss: 0.53422 | time cost: 19.63 s |
batch  42400 | examples/s: 28.20 | loss: 0.50855 | time elapsed: 4.92h | time left: 11.47h
batch  42500 | examples/s: 28.08 | loss: 0.52283 | time elapsed: 4.93h | time left: 11.46h
batch  42600 | examples/s: 27.48 | loss: 0.52835 | time elapsed: 4.94h | time left: 11.45h
batch  42700 | examples/s: 28.09 | loss: 0.51780 | time elapsed: 4.95h | time left: 11.43h
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batch  43000 | examples/s: 27.13 | loss: 0.51555 | time elapsed: 4.99h | time left: 11.40h
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batch  43700 | examples/s: 25.69 | loss: 0.51718 | time elapsed: 5.07h | time left: 11.31h
batch  43800 | examples/s: 28.05 | loss: 0.52151 | time elapsed: 5.08h | time left: 11.30h
batch  43900 | examples/s: 28.11 | loss: 0.52034 | time elapsed: 5.09h | time left: 11.29h
batch  44000 | examples/s: 28.43 | loss: 0.51299 | time elapsed: 5.10h | time left: 11.28h
batch  44100 | examples/s: 27.37 | loss: 0.51152 | time elapsed: 5.11h | time left: 11.26h
batch  44200 | examples/s: 28.11 | loss: 0.52392 | time elapsed: 5.12h | time left: 11.25h
batch  44300 | examples/s: 27.25 | loss: 0.51885 | time elapsed: 5.14h | time left: 11.24h
batch  44400 | examples/s: 27.74 | loss: 0.52187 | time elapsed: 5.15h | time left: 11.23h
batch  44500 | examples/s: 28.10 | loss: 0.51310 | time elapsed: 5.16h | time left: 11.22h
batch  44600 | examples/s: 27.36 | loss: 0.52877 | time elapsed: 5.17h | time left: 11.21h
batch  44700 | examples/s: 28.03 | loss: 0.52047 | time elapsed: 5.18h | time left: 11.19h
batch  44800 | examples/s: 28.30 | loss: 0.51893 | time elapsed: 5.19h | time left: 11.18h
batch  44900 | examples/s: 27.37 | loss: 0.51653 | time elapsed: 5.21h | time left: 11.17h
batch  45000 | examples/s: 26.93 | loss: 0.52179 | time elapsed: 5.22h | time left: 11.16h
batch  45100 | examples/s: 27.73 | loss: 0.51898 | time elapsed: 5.23h | time left: 11.15h
batch  45200 | examples/s: 28.09 | loss: 0.53222 | time elapsed: 5.24h | time left: 11.13h
epoch  15 | val loss: 0.53333 | time cost: 19.50 s |
batch  45300 | examples/s: 27.46 | loss: 0.52792 | time elapsed: 5.26h | time left: 11.14h
batch  45400 | examples/s: 28.19 | loss: 0.51391 | time elapsed: 5.27h | time left: 11.12h
batch  45500 | examples/s: 28.23 | loss: 0.52738 | time elapsed: 5.28h | time left: 11.11h
batch  45600 | examples/s: 27.32 | loss: 0.51131 | time elapsed: 5.29h | time left: 11.10h
batch  45700 | examples/s: 27.51 | loss: 0.52980 | time elapsed: 5.30h | time left: 11.09h
batch  45800 | examples/s: 28.01 | loss: 0.52938 | time elapsed: 5.31h | time left: 11.08h
batch  45900 | examples/s: 27.43 | loss: 0.53064 | time elapsed: 5.33h | time left: 11.06h
batch  46000 | examples/s: 28.01 | loss: 0.50920 | time elapsed: 5.34h | time left: 11.05h
batch  46100 | examples/s: 27.77 | loss: 0.51735 | time elapsed: 5.35h | time left: 11.04h
batch  46200 | examples/s: 26.90 | loss: 0.53017 | time elapsed: 5.36h | time left: 11.03h
batch  46300 | examples/s: 28.19 | loss: 0.51587 | time elapsed: 5.37h | time left: 11.02h
batch  46400 | examples/s: 27.83 | loss: 0.50926 | time elapsed: 5.38h | time left: 11.00h
batch  46500 | examples/s: 27.83 | loss: 0.52442 | time elapsed: 5.39h | time left: 10.99h
batch  46600 | examples/s: 27.78 | loss: 0.52352 | time elapsed: 5.41h | time left: 10.98h
batch  46700 | examples/s: 28.27 | loss: 0.51250 | time elapsed: 5.42h | time left: 10.97h
batch  46800 | examples/s: 27.32 | loss: 0.52371 | time elapsed: 5.43h | time left: 10.95h
batch  46900 | examples/s: 28.33 | loss: 0.52143 | time elapsed: 5.44h | time left: 10.94h
batch  47000 | examples/s: 27.90 | loss: 0.52227 | time elapsed: 5.45h | time left: 10.93h
batch  47100 | examples/s: 28.03 | loss: 0.51485 | time elapsed: 5.46h | time left: 10.92h
batch  47200 | examples/s: 27.96 | loss: 0.50525 | time elapsed: 5.47h | time left: 10.91h
batch  47300 | examples/s: 27.96 | loss: 0.51151 | time elapsed: 5.48h | time left: 10.89h
batch  47400 | examples/s: 28.02 | loss: 0.51372 | time elapsed: 5.50h | time left: 10.88h
batch  47500 | examples/s: 28.23 | loss: 0.52551 | time elapsed: 5.51h | time left: 10.87h
batch  47600 | examples/s: 27.84 | loss: 0.51207 | time elapsed: 5.52h | time left: 10.86h
batch  47700 | examples/s: 27.49 | loss: 0.51506 | time elapsed: 5.53h | time left: 10.85h
batch  47800 | examples/s: 28.15 | loss: 0.51462 | time elapsed: 5.54h | time left: 10.83h
batch  47900 | examples/s: 28.25 | loss: 0.52378 | time elapsed: 5.55h | time left: 10.82h
batch  48000 | examples/s: 28.33 | loss: 0.51523 | time elapsed: 5.56h | time left: 10.81h
epoch  16 | val loss: 0.53711 | time cost: 20.19 s |
batch  48100 | examples/s: 26.62 | loss: 0.50584 | time elapsed: 5.58h | time left: 10.81h
batch  48200 | examples/s: 27.34 | loss: 0.53242 | time elapsed: 5.59h | time left: 10.80h
batch  48300 | examples/s: 27.77 | loss: 0.52075 | time elapsed: 5.60h | time left: 10.79h
batch  48400 | examples/s: 27.98 | loss: 0.51521 | time elapsed: 5.62h | time left: 10.77h
batch  48500 | examples/s: 27.42 | loss: 0.50507 | time elapsed: 5.63h | time left: 10.76h
batch  48600 | examples/s: 27.98 | loss: 0.51472 | time elapsed: 5.64h | time left: 10.75h
batch  48700 | examples/s: 26.86 | loss: 0.52235 | time elapsed: 5.65h | time left: 10.74h
batch  48800 | examples/s: 28.01 | loss: 0.51939 | time elapsed: 5.66h | time left: 10.73h
batch  48900 | examples/s: 27.69 | loss: 0.52069 | time elapsed: 5.67h | time left: 10.71h
batch  49000 | examples/s: 27.97 | loss: 0.51234 | time elapsed: 5.68h | time left: 10.70h
batch  49100 | examples/s: 27.42 | loss: 0.50962 | time elapsed: 5.70h | time left: 10.69h
batch  49200 | examples/s: 27.51 | loss: 0.52320 | time elapsed: 5.71h | time left: 10.68h
batch  49300 | examples/s: 25.94 | loss: 0.51152 | time elapsed: 5.72h | time left: 10.67h
batch  49400 | examples/s: 27.52 | loss: 0.50333 | time elapsed: 5.73h | time left: 10.65h
batch  49500 | examples/s: 27.25 | loss: 0.51375 | time elapsed: 5.74h | time left: 10.64h
batch  49600 | examples/s: 28.26 | loss: 0.52081 | time elapsed: 5.75h | time left: 10.63h
batch  49700 | examples/s: 28.39 | loss: 0.51452 | time elapsed: 5.77h | time left: 10.62h
batch  49800 | examples/s: 27.97 | loss: 0.53214 | time elapsed: 5.78h | time left: 10.61h
batch  49900 | examples/s: 28.19 | loss: 0.51571 | time elapsed: 5.79h | time left: 10.60h
batch  50000 | examples/s: 28.42 | loss: 0.52816 | time elapsed: 5.80h | time left: 10.58h
batch  50100 | examples/s: 27.20 | loss: 0.50946 | time elapsed: 5.81h | time left: 10.57h
batch  50200 | examples/s: 28.21 | loss: 0.50901 | time elapsed: 5.82h | time left: 10.56h
batch  50300 | examples/s: 28.24 | loss: 0.50987 | time elapsed: 5.83h | time left: 10.55h
batch  50400 | examples/s: 27.98 | loss: 0.52336 | time elapsed: 5.84h | time left: 10.54h
batch  50500 | examples/s: 27.58 | loss: 0.51836 | time elapsed: 5.86h | time left: 10.52h
batch  50600 | examples/s: 27.73 | loss: 0.52765 | time elapsed: 5.87h | time left: 10.51h
batch  50700 | examples/s: 27.63 | loss: 0.52055 | time elapsed: 5.88h | time left: 10.50h
batch  50800 | examples/s: 28.26 | loss: 0.51764 | time elapsed: 5.89h | time left: 10.49h
epoch  17 | val loss: 0.52733 | time cost: 19.66 s |
batch  50900 | examples/s: 26.57 | loss: 0.52160 | time elapsed: 5.91h | time left: 10.49h
batch  51000 | examples/s: 27.97 | loss: 0.49834 | time elapsed: 5.92h | time left: 10.47h
batch  51100 | examples/s: 27.88 | loss: 0.50669 | time elapsed: 5.93h | time left: 10.46h
batch  51200 | examples/s: 28.01 | loss: 0.51220 | time elapsed: 5.94h | time left: 10.45h
batch  51300 | examples/s: 27.75 | loss: 0.52103 | time elapsed: 5.95h | time left: 10.44h
batch  51400 | examples/s: 27.72 | loss: 0.50662 | time elapsed: 5.96h | time left: 10.43h
batch  51500 | examples/s: 28.24 | loss: 0.51784 | time elapsed: 5.98h | time left: 10.41h
batch  51600 | examples/s: 27.89 | loss: 0.52456 | time elapsed: 5.99h | time left: 10.40h
batch  51700 | examples/s: 28.30 | loss: 0.51074 | time elapsed: 6.00h | time left: 10.39h
batch  51800 | examples/s: 27.27 | loss: 0.50222 | time elapsed: 6.01h | time left: 10.38h
batch  51900 | examples/s: 27.64 | loss: 0.51160 | time elapsed: 6.02h | time left: 10.37h
batch  52000 | examples/s: 27.14 | loss: 0.52286 | time elapsed: 6.03h | time left: 10.35h
batch  52100 | examples/s: 28.38 | loss: 0.52951 | time elapsed: 6.04h | time left: 10.34h
batch  52200 | examples/s: 28.04 | loss: 0.51418 | time elapsed: 6.06h | time left: 10.33h
batch  52300 | examples/s: 26.89 | loss: 0.52524 | time elapsed: 6.07h | time left: 10.32h
batch  52400 | examples/s: 28.24 | loss: 0.50235 | time elapsed: 6.08h | time left: 10.31h
batch  52500 | examples/s: 28.30 | loss: 0.51285 | time elapsed: 6.09h | time left: 10.29h
batch  52600 | examples/s: 27.83 | loss: 0.51598 | time elapsed: 6.10h | time left: 10.28h
batch  52700 | examples/s: 28.22 | loss: 0.50684 | time elapsed: 6.11h | time left: 10.27h
batch  52800 | examples/s: 27.82 | loss: 0.52414 | time elapsed: 6.12h | time left: 10.26h
batch  52900 | examples/s: 27.96 | loss: 0.50575 | time elapsed: 6.14h | time left: 10.25h
batch  53000 | examples/s: 27.13 | loss: 0.50867 | time elapsed: 6.15h | time left: 10.24h
batch  53100 | examples/s: 28.20 | loss: 0.51243 | time elapsed: 6.16h | time left: 10.22h
batch  53200 | examples/s: 27.44 | loss: 0.50167 | time elapsed: 6.17h | time left: 10.21h
batch  53300 | examples/s: 28.14 | loss: 0.50336 | time elapsed: 6.18h | time left: 10.20h
batch  53400 | examples/s: 27.31 | loss: 0.52239 | time elapsed: 6.19h | time left: 10.19h
batch  53500 | examples/s: 27.96 | loss: 0.52274 | time elapsed: 6.20h | time left: 10.18h
batch  53600 | examples/s: 28.05 | loss: 0.52030 | time elapsed: 6.22h | time left: 10.16h
epoch  18 | val loss: 0.53123 | time cost: 19.95 s |
batch  53700 | examples/s: 27.54 | loss: 0.50561 | time elapsed: 6.23h | time left: 10.16h
batch  53800 | examples/s: 26.16 | loss: 0.50138 | time elapsed: 6.24h | time left: 10.15h
batch  53900 | examples/s: 26.36 | loss: 0.50923 | time elapsed: 6.26h | time left: 10.14h
batch  54000 | examples/s: 28.04 | loss: 0.51058 | time elapsed: 6.27h | time left: 10.13h
batch  54100 | examples/s: 26.97 | loss: 0.50579 | time elapsed: 6.28h | time left: 10.11h
batch  54200 | examples/s: 27.70 | loss: 0.50768 | time elapsed: 6.29h | time left: 10.10h
batch  54300 | examples/s: 27.92 | loss: 0.50967 | time elapsed: 6.30h | time left: 10.09h
batch  54400 | examples/s: 27.69 | loss: 0.51356 | time elapsed: 6.31h | time left: 10.08h
batch  54500 | examples/s: 28.02 | loss: 0.51951 | time elapsed: 6.32h | time left: 10.07h
batch  54600 | examples/s: 26.26 | loss: 0.51696 | time elapsed: 6.34h | time left: 10.06h
batch  54700 | examples/s: 27.16 | loss: 0.52234 | time elapsed: 6.35h | time left: 10.04h
batch  54800 | examples/s: 27.67 | loss: 0.51817 | time elapsed: 6.36h | time left: 10.03h
batch  54900 | examples/s: 27.59 | loss: 0.50741 | time elapsed: 6.37h | time left: 10.02h
batch  55000 | examples/s: 27.17 | loss: 0.50430 | time elapsed: 6.38h | time left: 10.01h
batch  55100 | examples/s: 26.14 | loss: 0.52161 | time elapsed: 6.39h | time left: 10.00h
batch  55200 | examples/s: 27.28 | loss: 0.51475 | time elapsed: 6.40h | time left: 9.98h
batch  55300 | examples/s: 27.71 | loss: 0.49438 | time elapsed: 6.42h | time left: 9.97h
batch  55400 | examples/s: 27.99 | loss: 0.51073 | time elapsed: 6.43h | time left: 9.96h
batch  55500 | examples/s: 28.09 | loss: 0.51545 | time elapsed: 6.44h | time left: 9.95h
batch  55600 | examples/s: 28.00 | loss: 0.53386 | time elapsed: 6.45h | time left: 9.94h
batch  55700 | examples/s: 28.10 | loss: 0.50055 | time elapsed: 6.46h | time left: 9.92h
batch  55800 | examples/s: 27.11 | loss: 0.50084 | time elapsed: 6.47h | time left: 9.91h
batch  55900 | examples/s: 27.86 | loss: 0.50441 | time elapsed: 6.48h | time left: 9.90h
batch  56000 | examples/s: 27.90 | loss: 0.52923 | time elapsed: 6.50h | time left: 9.89h
batch  56100 | examples/s: 27.36 | loss: 0.51276 | time elapsed: 6.51h | time left: 9.88h
batch  56200 | examples/s: 27.33 | loss: 0.49582 | time elapsed: 6.52h | time left: 9.86h
batch  56300 | examples/s: 27.54 | loss: 0.51445 | time elapsed: 6.53h | time left: 9.85h
batch  56400 | examples/s: 28.33 | loss: 0.51593 | time elapsed: 6.54h | time left: 9.84h
batch  56500 | examples/s: 27.51 | loss: 0.51276 | time elapsed: 6.55h | time left: 9.83h
epoch  19 | val loss: 0.52539 | time cost: 19.62 s |
batch  56600 | examples/s: 28.32 | loss: 0.49359 | time elapsed: 6.57h | time left: 9.83h
batch  56700 | examples/s: 27.47 | loss: 0.50928 | time elapsed: 6.58h | time left: 9.81h
batch  56800 | examples/s: 27.11 | loss: 0.50154 | time elapsed: 6.59h | time left: 9.80h
batch  56900 | examples/s: 27.52 | loss: 0.51654 | time elapsed: 6.60h | time left: 9.79h
batch  57000 | examples/s: 27.81 | loss: 0.52039 | time elapsed: 6.62h | time left: 9.78h
batch  57100 | examples/s: 28.20 | loss: 0.51543 | time elapsed: 6.63h | time left: 9.77h
batch  57200 | examples/s: 27.59 | loss: 0.51326 | time elapsed: 6.64h | time left: 9.76h
batch  57300 | examples/s: 27.54 | loss: 0.49812 | time elapsed: 6.65h | time left: 9.74h
batch  57400 | examples/s: 28.32 | loss: 0.49728 | time elapsed: 6.66h | time left: 9.73h
batch  57500 | examples/s: 27.73 | loss: 0.50027 | time elapsed: 6.67h | time left: 9.72h
batch  57600 | examples/s: 27.27 | loss: 0.51695 | time elapsed: 6.68h | time left: 9.71h
batch  57700 | examples/s: 28.24 | loss: 0.51944 | time elapsed: 6.70h | time left: 9.70h
batch  57800 | examples/s: 27.44 | loss: 0.50647 | time elapsed: 6.71h | time left: 9.68h
batch  57900 | examples/s: 27.32 | loss: 0.51059 | time elapsed: 6.72h | time left: 9.67h
batch  58000 | examples/s: 27.72 | loss: 0.51622 | time elapsed: 6.73h | time left: 9.66h
batch  58100 | examples/s: 27.07 | loss: 0.50663 | time elapsed: 6.74h | time left: 9.65h
batch  58200 | examples/s: 27.66 | loss: 0.50549 | time elapsed: 6.75h | time left: 9.64h
batch  58300 | examples/s: 27.86 | loss: 0.51893 | time elapsed: 6.76h | time left: 9.62h
batch  58400 | examples/s: 27.96 | loss: 0.50338 | time elapsed: 6.78h | time left: 9.61h
batch  58500 | examples/s: 26.28 | loss: 0.51162 | time elapsed: 6.79h | time left: 9.60h
batch  58600 | examples/s: 28.38 | loss: 0.50711 | time elapsed: 6.80h | time left: 9.59h
batch  58700 | examples/s: 27.45 | loss: 0.50309 | time elapsed: 6.81h | time left: 9.58h
batch  58800 | examples/s: 26.53 | loss: 0.50274 | time elapsed: 6.82h | time left: 9.56h
batch  58900 | examples/s: 27.83 | loss: 0.51630 | time elapsed: 6.83h | time left: 9.55h
batch  59000 | examples/s: 28.22 | loss: 0.51678 | time elapsed: 6.84h | time left: 9.54h
batch  59100 | examples/s: 27.50 | loss: 0.51291 | time elapsed: 6.85h | time left: 9.53h
batch  59200 | examples/s: 28.07 | loss: 0.49720 | time elapsed: 6.87h | time left: 9.52h
batch  59300 | examples/s: 24.11 | loss: 0.50797 | time elapsed: 6.88h | time left: 9.50h
epoch  20 | val loss: 0.52398 | time cost: 19.64 s |
batch  59400 | examples/s: 26.14 | loss: 0.49923 | time elapsed: 6.90h | time left: 9.50h
batch  59500 | examples/s: 27.16 | loss: 0.49294 | time elapsed: 6.91h | time left: 9.49h
batch  59600 | examples/s: 26.96 | loss: 0.51224 | time elapsed: 6.92h | time left: 9.48h
batch  59700 | examples/s: 27.35 | loss: 0.52141 | time elapsed: 6.93h | time left: 9.47h
batch  59800 | examples/s: 27.94 | loss: 0.51340 | time elapsed: 6.94h | time left: 9.45h
batch  59900 | examples/s: 28.23 | loss: 0.51387 | time elapsed: 6.95h | time left: 9.44h
batch  60000 | examples/s: 27.32 | loss: 0.50148 | time elapsed: 6.96h | time left: 9.43h
batch  60100 | examples/s: 28.07 | loss: 0.51034 | time elapsed: 6.97h | time left: 9.42h
batch  60200 | examples/s: 28.28 | loss: 0.50257 | time elapsed: 6.99h | time left: 9.41h
batch  60300 | examples/s: 28.05 | loss: 0.50653 | time elapsed: 7.00h | time left: 9.39h
batch  60400 | examples/s: 27.91 | loss: 0.51109 | time elapsed: 7.01h | time left: 9.38h
batch  60500 | examples/s: 27.76 | loss: 0.50115 | time elapsed: 7.02h | time left: 9.37h
batch  60600 | examples/s: 27.45 | loss: 0.51429 | time elapsed: 7.03h | time left: 9.36h
batch  60700 | examples/s: 27.99 | loss: 0.49787 | time elapsed: 7.04h | time left: 9.35h
batch  60800 | examples/s: 27.98 | loss: 0.49999 | time elapsed: 7.05h | time left: 9.33h
batch  60900 | examples/s: 27.17 | loss: 0.50024 | time elapsed: 7.07h | time left: 9.32h
batch  61000 | examples/s: 27.65 | loss: 0.51786 | time elapsed: 7.08h | time left: 9.31h
batch  61100 | examples/s: 27.63 | loss: 0.51784 | time elapsed: 7.09h | time left: 9.30h
batch  61200 | examples/s: 27.57 | loss: 0.50071 | time elapsed: 7.10h | time left: 9.29h
batch  61300 | examples/s: 26.71 | loss: 0.51115 | time elapsed: 7.11h | time left: 9.27h
batch  61400 | examples/s: 27.76 | loss: 0.51477 | time elapsed: 7.12h | time left: 9.26h
batch  61500 | examples/s: 28.20 | loss: 0.51048 | time elapsed: 7.13h | time left: 9.25h
batch  61600 | examples/s: 28.40 | loss: 0.50383 | time elapsed: 7.15h | time left: 9.24h
batch  61700 | examples/s: 27.59 | loss: 0.51116 | time elapsed: 7.16h | time left: 9.23h
batch  61800 | examples/s: 27.46 | loss: 0.51114 | time elapsed: 7.17h | time left: 9.22h
batch  61900 | examples/s: 27.19 | loss: 0.50514 | time elapsed: 7.18h | time left: 9.20h
batch  62000 | examples/s: 28.09 | loss: 0.51303 | time elapsed: 7.19h | time left: 9.19h
batch  62100 | examples/s: 27.81 | loss: 0.50957 | time elapsed: 7.20h | time left: 9.18h
epoch  21 | val loss: 0.52180 | time cost: 19.44 s |
batch  62200 | examples/s: 27.49 | loss: 0.49266 | time elapsed: 7.22h | time left: 9.18h
batch  62300 | examples/s: 27.35 | loss: 0.51714 | time elapsed: 7.23h | time left: 9.16h
batch  62400 | examples/s: 27.53 | loss: 0.48798 | time elapsed: 7.24h | time left: 9.15h
batch  62500 | examples/s: 27.79 | loss: 0.50477 | time elapsed: 7.25h | time left: 9.14h
batch  62600 | examples/s: 27.76 | loss: 0.51199 | time elapsed: 7.27h | time left: 9.13h
batch  62700 | examples/s: 28.00 | loss: 0.51042 | time elapsed: 7.28h | time left: 9.12h
batch  62800 | examples/s: 26.87 | loss: 0.49781 | time elapsed: 7.29h | time left: 9.10h
batch  62900 | examples/s: 28.12 | loss: 0.51490 | time elapsed: 7.30h | time left: 9.09h
batch  63000 | examples/s: 27.20 | loss: 0.50243 | time elapsed: 7.31h | time left: 9.08h
batch  63100 | examples/s: 27.69 | loss: 0.49957 | time elapsed: 7.32h | time left: 9.07h
batch  63200 | examples/s: 27.90 | loss: 0.49635 | time elapsed: 7.33h | time left: 9.06h
batch  63300 | examples/s: 27.89 | loss: 0.51621 | time elapsed: 7.34h | time left: 9.04h
batch  63400 | examples/s: 28.08 | loss: 0.51199 | time elapsed: 7.36h | time left: 9.03h
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batch  63600 | examples/s: 27.83 | loss: 0.50498 | time elapsed: 7.38h | time left: 9.01h
batch  63700 | examples/s: 27.99 | loss: 0.50157 | time elapsed: 7.39h | time left: 9.00h
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batch  63900 | examples/s: 24.58 | loss: 0.49884 | time elapsed: 7.41h | time left: 8.97h
batch  64000 | examples/s: 28.18 | loss: 0.51567 | time elapsed: 7.42h | time left: 8.96h
batch  64100 | examples/s: 27.21 | loss: 0.51046 | time elapsed: 7.44h | time left: 8.95h
batch  64200 | examples/s: 28.26 | loss: 0.51040 | time elapsed: 7.45h | time left: 8.94h
batch  64300 | examples/s: 27.78 | loss: 0.49530 | time elapsed: 7.46h | time left: 8.93h
batch  64400 | examples/s: 28.17 | loss: 0.50307 | time elapsed: 7.47h | time left: 8.91h
batch  64500 | examples/s: 27.97 | loss: 0.49128 | time elapsed: 7.48h | time left: 8.90h
batch  64600 | examples/s: 28.06 | loss: 0.51416 | time elapsed: 7.49h | time left: 8.89h
batch  64700 | examples/s: 27.82 | loss: 0.51015 | time elapsed: 7.50h | time left: 8.88h
batch  64800 | examples/s: 27.67 | loss: 0.49862 | time elapsed: 7.52h | time left: 8.87h
batch  64900 | examples/s: 27.43 | loss: 0.50832 | time elapsed: 7.53h | time left: 8.86h
epoch  22 | val loss: 0.52312 | time cost: 19.85 s |
batch  65000 | examples/s: 27.49 | loss: 0.50434 | time elapsed: 7.54h | time left: 8.85h
batch  65100 | examples/s: 28.25 | loss: 0.50238 | time elapsed: 7.56h | time left: 8.84h
batch  65200 | examples/s: 27.99 | loss: 0.50152 | time elapsed: 7.57h | time left: 8.83h
batch  65300 | examples/s: 28.08 | loss: 0.50205 | time elapsed: 7.58h | time left: 8.81h
batch  65400 | examples/s: 27.09 | loss: 0.50376 | time elapsed: 7.59h | time left: 8.80h
batch  65500 | examples/s: 27.28 | loss: 0.50993 | time elapsed: 7.60h | time left: 8.79h
batch  65600 | examples/s: 27.62 | loss: 0.49870 | time elapsed: 7.61h | time left: 8.78h
batch  65700 | examples/s: 27.40 | loss: 0.50898 | time elapsed: 7.62h | time left: 8.77h
batch  65800 | examples/s: 28.05 | loss: 0.51125 | time elapsed: 7.64h | time left: 8.76h
batch  65900 | examples/s: 27.51 | loss: 0.51074 | time elapsed: 7.65h | time left: 8.74h
batch  66000 | examples/s: 28.18 | loss: 0.49348 | time elapsed: 7.66h | time left: 8.73h
batch  66100 | examples/s: 27.40 | loss: 0.50238 | time elapsed: 7.67h | time left: 8.72h
batch  66200 | examples/s: 27.58 | loss: 0.50563 | time elapsed: 7.68h | time left: 8.71h
batch  66300 | examples/s: 27.09 | loss: 0.50596 | time elapsed: 7.69h | time left: 8.70h
batch  66400 | examples/s: 27.61 | loss: 0.49506 | time elapsed: 7.70h | time left: 8.68h
batch  66500 | examples/s: 27.64 | loss: 0.50372 | time elapsed: 7.72h | time left: 8.67h
batch  66600 | examples/s: 24.07 | loss: 0.50514 | time elapsed: 7.73h | time left: 8.66h
batch  66700 | examples/s: 27.95 | loss: 0.49062 | time elapsed: 7.74h | time left: 8.65h
batch  66800 | examples/s: 26.04 | loss: 0.50051 | time elapsed: 7.75h | time left: 8.64h
batch  66900 | examples/s: 27.79 | loss: 0.50977 | time elapsed: 7.76h | time left: 8.63h
batch  67000 | examples/s: 27.69 | loss: 0.51205 | time elapsed: 7.77h | time left: 8.61h
batch  67100 | examples/s: 27.49 | loss: 0.51097 | time elapsed: 7.78h | time left: 8.60h
batch  67200 | examples/s: 27.95 | loss: 0.50514 | time elapsed: 7.80h | time left: 8.59h
batch  67300 | examples/s: 27.50 | loss: 0.50602 | time elapsed: 7.81h | time left: 8.58h
batch  67400 | examples/s: 26.72 | loss: 0.48805 | time elapsed: 7.82h | time left: 8.57h
batch  67500 | examples/s: 25.35 | loss: 0.49288 | time elapsed: 7.83h | time left: 8.56h
batch  67600 | examples/s: 20.67 | loss: 0.51425 | time elapsed: 7.84h | time left: 8.54h
batch  67700 | examples/s: 28.07 | loss: 0.51187 | time elapsed: 7.85h | time left: 8.53h
batch  67800 | examples/s: 27.61 | loss: 0.50645 | time elapsed: 7.87h | time left: 8.52h
epoch  23 | val loss: 0.52154 | time cost: 19.95 s |
batch  67900 | examples/s: 28.10 | loss: 0.51783 | time elapsed: 7.88h | time left: 8.52h
batch  68000 | examples/s: 26.84 | loss: 0.49946 | time elapsed: 7.89h | time left: 8.50h
batch  68100 | examples/s: 27.83 | loss: 0.49931 | time elapsed: 7.91h | time left: 8.49h
batch  68200 | examples/s: 27.59 | loss: 0.50681 | time elapsed: 7.92h | time left: 8.48h
batch  68300 | examples/s: 27.81 | loss: 0.50314 | time elapsed: 7.93h | time left: 8.47h
batch  68400 | examples/s: 27.96 | loss: 0.49870 | time elapsed: 7.94h | time left: 8.46h
batch  68500 | examples/s: 26.46 | loss: 0.50576 | time elapsed: 7.95h | time left: 8.44h
batch  68600 | examples/s: 28.17 | loss: 0.50813 | time elapsed: 7.96h | time left: 8.43h
batch  68700 | examples/s: 27.00 | loss: 0.49065 | time elapsed: 7.97h | time left: 8.42h
batch  68800 | examples/s: 27.25 | loss: 0.48862 | time elapsed: 7.99h | time left: 8.41h
batch  68900 | examples/s: 25.22 | loss: 0.51112 | time elapsed: 8.00h | time left: 8.40h
batch  69000 | examples/s: 27.81 | loss: 0.50804 | time elapsed: 8.01h | time left: 8.39h
batch  69100 | examples/s: 27.92 | loss: 0.49762 | time elapsed: 8.02h | time left: 8.37h
batch  69200 | examples/s: 27.46 | loss: 0.48620 | time elapsed: 8.03h | time left: 8.36h
batch  69300 | examples/s: 26.30 | loss: 0.49338 | time elapsed: 8.04h | time left: 8.35h
batch  69400 | examples/s: 24.70 | loss: 0.50436 | time elapsed: 8.05h | time left: 8.34h
batch  69500 | examples/s: 28.18 | loss: 0.49941 | time elapsed: 8.07h | time left: 8.33h
batch  69600 | examples/s: 27.39 | loss: 0.50359 | time elapsed: 8.08h | time left: 8.32h
batch  69700 | examples/s: 28.00 | loss: 0.50422 | time elapsed: 8.09h | time left: 8.30h
batch  69800 | examples/s: 28.13 | loss: 0.49184 | time elapsed: 8.10h | time left: 8.29h
batch  69900 | examples/s: 25.92 | loss: 0.50200 | time elapsed: 8.11h | time left: 8.28h
batch  70000 | examples/s: 27.87 | loss: 0.50426 | time elapsed: 8.12h | time left: 8.27h
batch  70100 | examples/s: 27.86 | loss: 0.49915 | time elapsed: 8.14h | time left: 8.26h
batch  70200 | examples/s: 27.22 | loss: 0.50910 | time elapsed: 8.15h | time left: 8.25h
batch  70300 | examples/s: 27.58 | loss: 0.50537 | time elapsed: 8.16h | time left: 8.23h
batch  70400 | examples/s: 26.42 | loss: 0.50706 | time elapsed: 8.17h | time left: 8.22h
batch  70500 | examples/s: 27.80 | loss: 0.50250 | time elapsed: 8.18h | time left: 8.21h
batch  70600 | examples/s: 28.15 | loss: 0.50782 | time elapsed: 8.19h | time left: 8.20h
epoch  24 | val loss: 0.51780 | time cost: 20.05 s |
batch  70700 | examples/s: 26.62 | loss: 0.49838 | time elapsed: 8.21h | time left: 8.19h
batch  70800 | examples/s: 26.96 | loss: 0.49024 | time elapsed: 8.22h | time left: 8.18h
batch  70900 | examples/s: 27.19 | loss: 0.49982 | time elapsed: 8.23h | time left: 8.17h
batch  71000 | examples/s: 28.07 | loss: 0.50338 | time elapsed: 8.24h | time left: 8.16h
batch  71100 | examples/s: 27.71 | loss: 0.49110 | time elapsed: 8.26h | time left: 8.15h
batch  71200 | examples/s: 28.00 | loss: 0.50518 | time elapsed: 8.27h | time left: 8.13h
batch  71300 | examples/s: 28.16 | loss: 0.49932 | time elapsed: 8.28h | time left: 8.12h
batch  71400 | examples/s: 27.13 | loss: 0.50218 | time elapsed: 8.29h | time left: 8.11h
batch  71500 | examples/s: 27.37 | loss: 0.49734 | time elapsed: 8.30h | time left: 8.10h
batch  71600 | examples/s: 27.22 | loss: 0.48703 | time elapsed: 8.31h | time left: 8.09h
batch  71700 | examples/s: 26.84 | loss: 0.50931 | time elapsed: 8.32h | time left: 8.08h
batch  71800 | examples/s: 27.85 | loss: 0.50684 | time elapsed: 8.34h | time left: 8.06h
batch  71900 | examples/s: 27.88 | loss: 0.50179 | time elapsed: 8.35h | time left: 8.05h
batch  72000 | examples/s: 28.22 | loss: 0.50144 | time elapsed: 8.36h | time left: 8.04h
batch  72100 | examples/s: 28.01 | loss: 0.51168 | time elapsed: 8.37h | time left: 8.03h
batch  72200 | examples/s: 28.14 | loss: 0.49574 | time elapsed: 8.38h | time left: 8.02h
batch  72300 | examples/s: 28.25 | loss: 0.50817 | time elapsed: 8.39h | time left: 8.00h
batch  72400 | examples/s: 27.73 | loss: 0.51768 | time elapsed: 8.40h | time left: 7.99h
batch  72500 | examples/s: 27.50 | loss: 0.50451 | time elapsed: 8.42h | time left: 7.98h
batch  72600 | examples/s: 27.48 | loss: 0.50070 | time elapsed: 8.43h | time left: 7.97h
batch  72700 | examples/s: 28.18 | loss: 0.49276 | time elapsed: 8.44h | time left: 7.96h
batch  72800 | examples/s: 27.52 | loss: 0.48632 | time elapsed: 8.45h | time left: 7.95h
batch  72900 | examples/s: 25.40 | loss: 0.50674 | time elapsed: 8.46h | time left: 7.93h
batch  73000 | examples/s: 25.55 | loss: 0.49763 | time elapsed: 8.47h | time left: 7.92h
batch  73100 | examples/s: 26.52 | loss: 0.49224 | time elapsed: 8.49h | time left: 7.91h
batch  73200 | examples/s: 27.91 | loss: 0.48977 | time elapsed: 8.50h | time left: 7.90h
batch  73300 | examples/s: 28.00 | loss: 0.50110 | time elapsed: 8.51h | time left: 7.89h
batch  73400 | examples/s: 28.08 | loss: 0.49811 | time elapsed: 8.52h | time left: 7.88h
epoch  25 | val loss: 0.51629 | time cost: 19.69 s |
batch  73500 | examples/s: 26.59 | loss: 0.51107 | time elapsed: 8.54h | time left: 7.87h
batch  73600 | examples/s: 27.16 | loss: 0.51599 | time elapsed: 8.55h | time left: 7.86h
batch  73700 | examples/s: 25.63 | loss: 0.49899 | time elapsed: 8.56h | time left: 7.85h
batch  73800 | examples/s: 27.20 | loss: 0.48828 | time elapsed: 8.57h | time left: 7.83h
batch  73900 | examples/s: 27.76 | loss: 0.49012 | time elapsed: 8.58h | time left: 7.82h
batch  74000 | examples/s: 27.33 | loss: 0.48776 | time elapsed: 8.60h | time left: 7.81h
batch  74100 | examples/s: 28.19 | loss: 0.50526 | time elapsed: 8.61h | time left: 7.80h
batch  74200 | examples/s: 27.62 | loss: 0.50735 | time elapsed: 8.62h | time left: 7.79h
batch  74300 | examples/s: 27.57 | loss: 0.49392 | time elapsed: 8.63h | time left: 7.78h
batch  74400 | examples/s: 27.47 | loss: 0.48743 | time elapsed: 8.64h | time left: 7.76h
batch  74500 | examples/s: 27.96 | loss: 0.50177 | time elapsed: 8.65h | time left: 7.75h
batch  74600 | examples/s: 27.53 | loss: 0.48705 | time elapsed: 8.66h | time left: 7.74h
batch  74700 | examples/s: 25.99 | loss: 0.51796 | time elapsed: 8.68h | time left: 7.73h
batch  74800 | examples/s: 27.77 | loss: 0.49450 | time elapsed: 8.69h | time left: 7.72h
batch  74900 | examples/s: 27.91 | loss: 0.48876 | time elapsed: 8.70h | time left: 7.71h
batch  75000 | examples/s: 27.46 | loss: 0.49827 | time elapsed: 8.71h | time left: 7.69h
batch  75100 | examples/s: 27.63 | loss: 0.49051 | time elapsed: 8.72h | time left: 7.68h
batch  75200 | examples/s: 27.87 | loss: 0.49405 | time elapsed: 8.73h | time left: 7.67h
batch  75300 | examples/s: 25.35 | loss: 0.49358 | time elapsed: 8.74h | time left: 7.66h
batch  75400 | examples/s: 26.90 | loss: 0.50987 | time elapsed: 8.76h | time left: 7.65h
batch  75500 | examples/s: 27.13 | loss: 0.51689 | time elapsed: 8.77h | time left: 7.63h
batch  75600 | examples/s: 28.16 | loss: 0.48528 | time elapsed: 8.78h | time left: 7.62h
batch  75700 | examples/s: 28.18 | loss: 0.50539 | time elapsed: 8.79h | time left: 7.61h
batch  75800 | examples/s: 28.24 | loss: 0.49421 | time elapsed: 8.80h | time left: 7.60h
batch  75900 | examples/s: 28.01 | loss: 0.50131 | time elapsed: 8.81h | time left: 7.59h
batch  76000 | examples/s: 27.90 | loss: 0.48212 | time elapsed: 8.82h | time left: 7.58h
batch  76100 | examples/s: 27.33 | loss: 0.50670 | time elapsed: 8.84h | time left: 7.56h
batch  76200 | examples/s: 26.61 | loss: 0.49538 | time elapsed: 8.85h | time left: 7.55h
epoch  26 | val loss: 0.51531 | time cost: 20.11 s |
batch  76300 | examples/s: 26.83 | loss: 0.48180 | time elapsed: 8.86h | time left: 7.55h
batch  76400 | examples/s: 27.65 | loss: 0.49831 | time elapsed: 8.88h | time left: 7.53h
batch  76500 | examples/s: 26.90 | loss: 0.49925 | time elapsed: 8.89h | time left: 7.52h
batch  76600 | examples/s: 27.05 | loss: 0.48619 | time elapsed: 8.90h | time left: 7.51h
batch  76700 | examples/s: 27.87 | loss: 0.50051 | time elapsed: 8.91h | time left: 7.50h
batch  76800 | examples/s: 25.71 | loss: 0.48696 | time elapsed: 8.92h | time left: 7.49h
batch  76900 | examples/s: 27.87 | loss: 0.49634 | time elapsed: 8.93h | time left: 7.48h
batch  77000 | examples/s: 27.48 | loss: 0.49326 | time elapsed: 8.94h | time left: 7.46h
batch  77100 | examples/s: 27.12 | loss: 0.48171 | time elapsed: 8.96h | time left: 7.45h
batch  77200 | examples/s: 27.65 | loss: 0.50611 | time elapsed: 8.97h | time left: 7.44h
batch  77300 | examples/s: 26.64 | loss: 0.48233 | time elapsed: 8.98h | time left: 7.43h
batch  77400 | examples/s: 27.61 | loss: 0.51027 | time elapsed: 8.99h | time left: 7.42h
batch  77500 | examples/s: 27.42 | loss: 0.49099 | time elapsed: 9.00h | time left: 7.40h
batch  77600 | examples/s: 27.07 | loss: 0.49472 | time elapsed: 9.01h | time left: 7.39h
batch  77700 | examples/s: 27.98 | loss: 0.50521 | time elapsed: 9.02h | time left: 7.38h
batch  77800 | examples/s: 27.92 | loss: 0.49521 | time elapsed: 9.04h | time left: 7.37h
batch  77900 | examples/s: 27.83 | loss: 0.49578 | time elapsed: 9.05h | time left: 7.36h
batch  78000 | examples/s: 28.31 | loss: 0.51046 | time elapsed: 9.06h | time left: 7.35h
batch  78100 | examples/s: 27.25 | loss: 0.48257 | time elapsed: 9.07h | time left: 7.33h
batch  78200 | examples/s: 26.58 | loss: 0.49633 | time elapsed: 9.08h | time left: 7.32h
batch  78300 | examples/s: 28.30 | loss: 0.50435 | time elapsed: 9.09h | time left: 7.31h
batch  78400 | examples/s: 26.88 | loss: 0.50238 | time elapsed: 9.10h | time left: 7.30h
batch  78500 | examples/s: 27.35 | loss: 0.49400 | time elapsed: 9.12h | time left: 7.29h
batch  78600 | examples/s: 27.57 | loss: 0.48905 | time elapsed: 9.13h | time left: 7.28h
batch  78700 | examples/s: 28.05 | loss: 0.49804 | time elapsed: 9.14h | time left: 7.26h
batch  78800 | examples/s: 27.43 | loss: 0.49681 | time elapsed: 9.15h | time left: 7.25h
batch  78900 | examples/s: 27.73 | loss: 0.49716 | time elapsed: 9.16h | time left: 7.24h
batch  79000 | examples/s: 27.40 | loss: 0.51022 | time elapsed: 9.17h | time left: 7.23h
batch  79100 | examples/s: 27.80 | loss: 0.51077 | time elapsed: 9.18h | time left: 7.22h
epoch  27 | val loss: 0.51300 | time cost: 21.83 s |
batch  79200 | examples/s: 27.10 | loss: 0.48352 | time elapsed: 9.20h | time left: 7.21h
batch  79300 | examples/s: 27.65 | loss: 0.51038 | time elapsed: 9.21h | time left: 7.20h
batch  79400 | examples/s: 27.27 | loss: 0.51452 | time elapsed: 9.23h | time left: 7.19h
batch  79500 | examples/s: 27.78 | loss: 0.49126 | time elapsed: 9.24h | time left: 7.17h
batch  79600 | examples/s: 26.23 | loss: 0.51502 | time elapsed: 9.25h | time left: 7.16h
batch  79700 | examples/s: 27.66 | loss: 0.49509 | time elapsed: 9.26h | time left: 7.15h
batch  79800 | examples/s: 27.50 | loss: 0.49898 | time elapsed: 9.27h | time left: 7.14h
batch  79900 | examples/s: 27.79 | loss: 0.49130 | time elapsed: 9.28h | time left: 7.13h
batch  80000 | examples/s: 27.49 | loss: 0.48468 | time elapsed: 9.30h | time left: 7.12h
batch  80100 | examples/s: 26.91 | loss: 0.48672 | time elapsed: 9.31h | time left: 7.10h
batch  80200 | examples/s: 26.93 | loss: 0.50024 | time elapsed: 9.32h | time left: 7.09h
batch  80300 | examples/s: 27.51 | loss: 0.48361 | time elapsed: 9.33h | time left: 7.08h
batch  80400 | examples/s: 26.56 | loss: 0.49906 | time elapsed: 9.34h | time left: 7.07h
batch  80500 | examples/s: 27.94 | loss: 0.48059 | time elapsed: 9.35h | time left: 7.06h
batch  80600 | examples/s: 27.22 | loss: 0.49201 | time elapsed: 9.36h | time left: 7.05h
batch  80700 | examples/s: 26.08 | loss: 0.50390 | time elapsed: 9.38h | time left: 7.03h
batch  80800 | examples/s: 27.28 | loss: 0.49365 | time elapsed: 9.39h | time left: 7.02h
batch  80900 | examples/s: 27.34 | loss: 0.49471 | time elapsed: 9.40h | time left: 7.01h
batch  81000 | examples/s: 27.49 | loss: 0.48348 | time elapsed: 9.41h | time left: 7.00h
batch  81100 | examples/s: 28.14 | loss: 0.48417 | time elapsed: 9.42h | time left: 6.99h
batch  81200 | examples/s: 26.43 | loss: 0.49803 | time elapsed: 9.43h | time left: 6.98h
batch  81300 | examples/s: 27.25 | loss: 0.49014 | time elapsed: 9.44h | time left: 6.96h
batch  81400 | examples/s: 26.75 | loss: 0.49510 | time elapsed: 9.46h | time left: 6.95h
batch  81500 | examples/s: 26.91 | loss: 0.50019 | time elapsed: 9.47h | time left: 6.94h
batch  81600 | examples/s: 27.81 | loss: 0.49609 | time elapsed: 9.48h | time left: 6.93h
batch  81700 | examples/s: 28.13 | loss: 0.50139 | time elapsed: 9.49h | time left: 6.92h
batch  81800 | examples/s: 27.61 | loss: 0.49472 | time elapsed: 9.50h | time left: 6.91h
batch  81900 | examples/s: 27.86 | loss: 0.49450 | time elapsed: 9.51h | time left: 6.89h
epoch  28 | val loss: 0.51645 | time cost: 19.77 s |
batch  82000 | examples/s: 27.89 | loss: 0.47690 | time elapsed: 9.53h | time left: 6.89h
batch  82100 | examples/s: 27.91 | loss: 0.49721 | time elapsed: 9.54h | time left: 6.87h
batch  82200 | examples/s: 28.12 | loss: 0.49315 | time elapsed: 9.55h | time left: 6.86h
batch  82300 | examples/s: 23.44 | loss: 0.47554 | time elapsed: 9.57h | time left: 6.85h
batch  82400 | examples/s: 26.74 | loss: 0.50656 | time elapsed: 9.58h | time left: 6.84h
batch  82500 | examples/s: 25.83 | loss: 0.48629 | time elapsed: 9.59h | time left: 6.83h
batch  82600 | examples/s: 27.87 | loss: 0.50116 | time elapsed: 9.60h | time left: 6.82h
batch  82700 | examples/s: 28.21 | loss: 0.49743 | time elapsed: 9.61h | time left: 6.80h
batch  82800 | examples/s: 28.41 | loss: 0.48225 | time elapsed: 9.62h | time left: 6.79h
batch  82900 | examples/s: 28.37 | loss: 0.48196 | time elapsed: 9.63h | time left: 6.78h
batch  83000 | examples/s: 27.39 | loss: 0.49730 | time elapsed: 9.65h | time left: 6.77h
batch  83100 | examples/s: 27.88 | loss: 0.48743 | time elapsed: 9.66h | time left: 6.76h
batch  83200 | examples/s: 27.41 | loss: 0.49716 | time elapsed: 9.67h | time left: 6.75h
batch  83300 | examples/s: 27.61 | loss: 0.48792 | time elapsed: 9.68h | time left: 6.73h
batch  83400 | examples/s: 27.05 | loss: 0.50462 | time elapsed: 9.69h | time left: 6.72h
batch  83500 | examples/s: 28.00 | loss: 0.50395 | time elapsed: 9.70h | time left: 6.71h
batch  83600 | examples/s: 26.98 | loss: 0.48040 | time elapsed: 9.71h | time left: 6.70h
batch  83700 | examples/s: 28.03 | loss: 0.49116 | time elapsed: 9.73h | time left: 6.69h
batch  83800 | examples/s: 28.07 | loss: 0.49331 | time elapsed: 9.74h | time left: 6.68h
batch  83900 | examples/s: 23.85 | loss: 0.49528 | time elapsed: 9.75h | time left: 6.66h
batch  84000 | examples/s: 27.83 | loss: 0.49210 | time elapsed: 9.76h | time left: 6.65h
batch  84100 | examples/s: 27.44 | loss: 0.49372 | time elapsed: 9.77h | time left: 6.64h
batch  84200 | examples/s: 25.17 | loss: 0.49983 | time elapsed: 9.78h | time left: 6.63h
batch  84300 | examples/s: 27.85 | loss: 0.50289 | time elapsed: 9.79h | time left: 6.62h
batch  84400 | examples/s: 27.28 | loss: 0.49888 | time elapsed: 9.81h | time left: 6.60h
batch  84500 | examples/s: 27.40 | loss: 0.50275 | time elapsed: 9.82h | time left: 6.59h
batch  84600 | examples/s: 27.79 | loss: 0.50783 | time elapsed: 9.83h | time left: 6.58h
batch  84700 | examples/s: 28.14 | loss: 0.49801 | time elapsed: 9.84h | time left: 6.57h
epoch  29 | val loss: 0.51276 | time cost: 19.72 s |
batch  84800 | examples/s: 28.17 | loss: 0.47646 | time elapsed: 9.86h | time left: 6.56h
batch  84900 | examples/s: 27.36 | loss: 0.49034 | time elapsed: 9.87h | time left: 6.55h
batch  85000 | examples/s: 27.36 | loss: 0.49094 | time elapsed: 9.88h | time left: 6.54h
batch  85100 | examples/s: 26.29 | loss: 0.47625 | time elapsed: 9.89h | time left: 6.53h
batch  85200 | examples/s: 27.50 | loss: 0.48870 | time elapsed: 9.90h | time left: 6.52h
batch  85300 | examples/s: 28.06 | loss: 0.48215 | time elapsed: 9.92h | time left: 6.50h
batch  85400 | examples/s: 27.82 | loss: 0.48353 | time elapsed: 9.93h | time left: 6.49h
batch  85500 | examples/s: 27.77 | loss: 0.48742 | time elapsed: 9.94h | time left: 6.48h
batch  85600 | examples/s: 26.95 | loss: 0.47780 | time elapsed: 9.95h | time left: 6.47h
batch  85700 | examples/s: 27.17 | loss: 0.48324 | time elapsed: 9.96h | time left: 6.46h
batch  85800 | examples/s: 28.03 | loss: 0.47876 | time elapsed: 9.97h | time left: 6.44h
batch  85900 | examples/s: 27.48 | loss: 0.48687 | time elapsed: 9.98h | time left: 6.43h
batch  86000 | examples/s: 27.08 | loss: 0.47891 | time elapsed: 10.00h | time left: 6.42h
batch  86100 | examples/s: 28.01 | loss: 0.48201 | time elapsed: 10.01h | time left: 6.41h
batch  86200 | examples/s: 27.04 | loss: 0.48998 | time elapsed: 10.02h | time left: 6.40h
batch  86300 | examples/s: 27.93 | loss: 0.49069 | time elapsed: 10.03h | time left: 6.39h
batch  86400 | examples/s: 28.10 | loss: 0.48775 | time elapsed: 10.04h | time left: 6.37h
batch  86500 | examples/s: 26.26 | loss: 0.47425 | time elapsed: 10.05h | time left: 6.36h
batch  86600 | examples/s: 27.82 | loss: 0.48543 | time elapsed: 10.06h | time left: 6.35h
batch  86700 | examples/s: 25.31 | loss: 0.48459 | time elapsed: 10.08h | time left: 6.34h
batch  86800 | examples/s: 27.82 | loss: 0.49360 | time elapsed: 10.09h | time left: 6.33h
batch  86900 | examples/s: 27.42 | loss: 0.48103 | time elapsed: 10.10h | time left: 6.32h
batch  87000 | examples/s: 25.41 | loss: 0.47582 | time elapsed: 10.11h | time left: 6.30h
batch  87100 | examples/s: 25.26 | loss: 0.48982 | time elapsed: 10.12h | time left: 6.29h
batch  87200 | examples/s: 27.29 | loss: 0.47619 | time elapsed: 10.13h | time left: 6.28h
batch  87300 | examples/s: 27.15 | loss: 0.48499 | time elapsed: 10.15h | time left: 6.27h
batch  87400 | examples/s: 28.00 | loss: 0.47627 | time elapsed: 10.16h | time left: 6.26h
batch  87500 | examples/s: 27.97 | loss: 0.47668 | time elapsed: 10.17h | time left: 6.25h
epoch  30 | val loss: 0.49985 | time cost: 20.02 s |
batch  87600 | examples/s: 27.43 | loss: 0.46559 | time elapsed: 10.19h | time left: 6.24h
batch  87700 | examples/s: 27.97 | loss: 0.48142 | time elapsed: 10.20h | time left: 6.23h
batch  87800 | examples/s: 26.58 | loss: 0.48139 | time elapsed: 10.21h | time left: 6.21h
batch  87900 | examples/s: 27.69 | loss: 0.48124 | time elapsed: 10.22h | time left: 6.20h
batch  88000 | examples/s: 26.69 | loss: 0.47324 | time elapsed: 10.23h | time left: 6.19h
batch  88100 | examples/s: 23.69 | loss: 0.48106 | time elapsed: 10.24h | time left: 6.18h
batch  88200 | examples/s: 27.19 | loss: 0.47344 | time elapsed: 10.26h | time left: 6.17h
batch  88300 | examples/s: 27.35 | loss: 0.47115 | time elapsed: 10.27h | time left: 6.16h
batch  88400 | examples/s: 27.28 | loss: 0.46607 | time elapsed: 10.28h | time left: 6.14h
batch  88500 | examples/s: 27.98 | loss: 0.48472 | time elapsed: 10.29h | time left: 6.13h
batch  88600 | examples/s: 26.96 | loss: 0.47592 | time elapsed: 10.30h | time left: 6.12h
batch  88700 | examples/s: 26.92 | loss: 0.47737 | time elapsed: 10.31h | time left: 6.11h
batch  88800 | examples/s: 27.61 | loss: 0.48403 | time elapsed: 10.32h | time left: 6.10h
batch  88900 | examples/s: 27.44 | loss: 0.48307 | time elapsed: 10.34h | time left: 6.09h
batch  89000 | examples/s: 27.88 | loss: 0.48284 | time elapsed: 10.35h | time left: 6.07h
batch  89100 | examples/s: 27.94 | loss: 0.47742 | time elapsed: 10.36h | time left: 6.06h
batch  89200 | examples/s: 27.82 | loss: 0.49110 | time elapsed: 10.37h | time left: 6.05h
batch  89300 | examples/s: 28.20 | loss: 0.47274 | time elapsed: 10.38h | time left: 6.04h
batch  89400 | examples/s: 27.50 | loss: 0.47785 | time elapsed: 10.39h | time left: 6.03h
batch  89500 | examples/s: 27.71 | loss: 0.47780 | time elapsed: 10.40h | time left: 6.02h
batch  89600 | examples/s: 27.77 | loss: 0.46933 | time elapsed: 10.42h | time left: 6.00h
batch  89700 | examples/s: 27.72 | loss: 0.47631 | time elapsed: 10.43h | time left: 5.99h
batch  89800 | examples/s: 26.48 | loss: 0.48724 | time elapsed: 10.44h | time left: 5.98h
batch  89900 | examples/s: 27.28 | loss: 0.47251 | time elapsed: 10.45h | time left: 5.97h
batch  90000 | examples/s: 27.45 | loss: 0.46492 | time elapsed: 10.46h | time left: 5.96h
batch  90100 | examples/s: 28.45 | loss: 0.47660 | time elapsed: 10.47h | time left: 5.95h
batch  90200 | examples/s: 27.99 | loss: 0.48176 | time elapsed: 10.48h | time left: 5.93h
batch  90300 | examples/s: 27.40 | loss: 0.47020 | time elapsed: 10.50h | time left: 5.92h
batch  90400 | examples/s: 27.06 | loss: 0.46340 | time elapsed: 10.51h | time left: 5.91h
epoch  31 | val loss: 0.49810 | time cost: 20.08 s |
batch  90500 | examples/s: 27.78 | loss: 0.47370 | time elapsed: 10.53h | time left: 5.90h
batch  90600 | examples/s: 27.48 | loss: 0.47429 | time elapsed: 10.54h | time left: 5.89h
batch  90700 | examples/s: 27.94 | loss: 0.47107 | time elapsed: 10.55h | time left: 5.88h
batch  90800 | examples/s: 27.54 | loss: 0.47115 | time elapsed: 10.56h | time left: 5.87h
batch  90900 | examples/s: 27.53 | loss: 0.48065 | time elapsed: 10.57h | time left: 5.86h
batch  91000 | examples/s: 27.16 | loss: 0.47017 | time elapsed: 10.58h | time left: 5.84h
batch  91100 | examples/s: 27.76 | loss: 0.47514 | time elapsed: 10.59h | time left: 5.83h
batch  91200 | examples/s: 27.63 | loss: 0.46688 | time elapsed: 10.61h | time left: 5.82h
batch  91300 | examples/s: 28.10 | loss: 0.48519 | time elapsed: 10.62h | time left: 5.81h
batch  91400 | examples/s: 27.02 | loss: 0.46663 | time elapsed: 10.63h | time left: 5.80h
batch  91500 | examples/s: 27.42 | loss: 0.47554 | time elapsed: 10.64h | time left: 5.79h
batch  91600 | examples/s: 26.97 | loss: 0.47301 | time elapsed: 10.65h | time left: 5.77h
batch  91700 | examples/s: 27.84 | loss: 0.48087 | time elapsed: 10.66h | time left: 5.76h
batch  91800 | examples/s: 25.42 | loss: 0.47853 | time elapsed: 10.67h | time left: 5.75h
batch  91900 | examples/s: 27.32 | loss: 0.47325 | time elapsed: 10.69h | time left: 5.74h
batch  92000 | examples/s: 28.29 | loss: 0.47273 | time elapsed: 10.70h | time left: 5.73h
batch  92100 | examples/s: 28.01 | loss: 0.47478 | time elapsed: 10.71h | time left: 5.72h
batch  92200 | examples/s: 28.10 | loss: 0.48897 | time elapsed: 10.72h | time left: 5.70h
batch  92300 | examples/s: 27.09 | loss: 0.46879 | time elapsed: 10.73h | time left: 5.69h
batch  92400 | examples/s: 27.74 | loss: 0.48576 | time elapsed: 10.74h | time left: 5.68h
batch  92500 | examples/s: 27.80 | loss: 0.47108 | time elapsed: 10.75h | time left: 5.67h
batch  92600 | examples/s: 26.48 | loss: 0.46761 | time elapsed: 10.77h | time left: 5.66h
batch  92700 | examples/s: 26.31 | loss: 0.47037 | time elapsed: 10.78h | time left: 5.64h
batch  92800 | examples/s: 27.94 | loss: 0.47134 | time elapsed: 10.79h | time left: 5.63h
batch  92900 | examples/s: 27.78 | loss: 0.47073 | time elapsed: 10.80h | time left: 5.62h
batch  93000 | examples/s: 27.94 | loss: 0.47079 | time elapsed: 10.81h | time left: 5.61h
batch  93100 | examples/s: 27.50 | loss: 0.47411 | time elapsed: 10.82h | time left: 5.60h
batch  93200 | examples/s: 26.98 | loss: 0.47825 | time elapsed: 10.83h | time left: 5.59h
epoch  32 | val loss: 0.49854 | time cost: 20.26 s |
batch  93300 | examples/s: 26.59 | loss: 0.47125 | time elapsed: 10.85h | time left: 5.58h
batch  93400 | examples/s: 26.54 | loss: 0.47828 | time elapsed: 10.86h | time left: 5.57h
batch  93500 | examples/s: 27.86 | loss: 0.47765 | time elapsed: 10.88h | time left: 5.55h
batch  93600 | examples/s: 27.04 | loss: 0.46883 | time elapsed: 10.89h | time left: 5.54h
batch  93700 | examples/s: 28.28 | loss: 0.46121 | time elapsed: 10.90h | time left: 5.53h
batch  93800 | examples/s: 27.19 | loss: 0.46623 | time elapsed: 10.91h | time left: 5.52h
batch  93900 | examples/s: 27.07 | loss: 0.47388 | time elapsed: 10.92h | time left: 5.51h
batch  94000 | examples/s: 27.80 | loss: 0.48066 | time elapsed: 10.93h | time left: 5.50h
batch  94100 | examples/s: 28.08 | loss: 0.46797 | time elapsed: 10.94h | time left: 5.48h
batch  94200 | examples/s: 26.90 | loss: 0.47066 | time elapsed: 10.96h | time left: 5.47h
batch  94300 | examples/s: 27.49 | loss: 0.46261 | time elapsed: 10.97h | time left: 5.46h
batch  94400 | examples/s: 27.64 | loss: 0.47614 | time elapsed: 10.98h | time left: 5.45h
batch  94500 | examples/s: 27.80 | loss: 0.47255 | time elapsed: 10.99h | time left: 5.44h
batch  94600 | examples/s: 28.03 | loss: 0.46590 | time elapsed: 11.00h | time left: 5.43h
batch  94700 | examples/s: 27.22 | loss: 0.47758 | time elapsed: 11.01h | time left: 5.41h
batch  94800 | examples/s: 26.43 | loss: 0.48573 | time elapsed: 11.02h | time left: 5.40h
batch  94900 | examples/s: 27.89 | loss: 0.46973 | time elapsed: 11.04h | time left: 5.39h
batch  95000 | examples/s: 26.07 | loss: 0.47318 | time elapsed: 11.05h | time left: 5.38h
batch  95100 | examples/s: 26.59 | loss: 0.48095 | time elapsed: 11.06h | time left: 5.37h
batch  95200 | examples/s: 27.63 | loss: 0.46001 | time elapsed: 11.07h | time left: 5.36h
batch  95300 | examples/s: 26.84 | loss: 0.46978 | time elapsed: 11.08h | time left: 5.34h
batch  95400 | examples/s: 26.83 | loss: 0.47943 | time elapsed: 11.09h | time left: 5.33h
batch  95500 | examples/s: 27.69 | loss: 0.46526 | time elapsed: 11.11h | time left: 5.32h
batch  95600 | examples/s: 27.83 | loss: 0.46488 | time elapsed: 11.12h | time left: 5.31h
batch  95700 | examples/s: 28.02 | loss: 0.47610 | time elapsed: 11.13h | time left: 5.30h
batch  95800 | examples/s: 28.04 | loss: 0.48370 | time elapsed: 11.14h | time left: 5.29h
batch  95900 | examples/s: 27.66 | loss: 0.47842 | time elapsed: 11.15h | time left: 5.27h
batch  96000 | examples/s: 27.10 | loss: 0.46848 | time elapsed: 11.16h | time left: 5.26h
epoch  33 | val loss: 0.49806 | time cost: 19.59 s |
batch  96100 | examples/s: 27.81 | loss: 0.45936 | time elapsed: 11.18h | time left: 5.25h
batch  96200 | examples/s: 28.07 | loss: 0.48431 | time elapsed: 11.19h | time left: 5.24h
batch  96300 | examples/s: 27.22 | loss: 0.48111 | time elapsed: 11.20h | time left: 5.23h
batch  96400 | examples/s: 27.22 | loss: 0.45799 | time elapsed: 11.22h | time left: 5.22h
batch  96500 | examples/s: 27.89 | loss: 0.46208 | time elapsed: 11.23h | time left: 5.21h
batch  96600 | examples/s: 27.99 | loss: 0.47800 | time elapsed: 11.24h | time left: 5.19h
batch  96700 | examples/s: 26.55 | loss: 0.47150 | time elapsed: 11.25h | time left: 5.18h
batch  96800 | examples/s: 26.67 | loss: 0.46227 | time elapsed: 11.26h | time left: 5.17h
batch  96900 | examples/s: 27.52 | loss: 0.46411 | time elapsed: 11.27h | time left: 5.16h
batch  97000 | examples/s: 28.02 | loss: 0.47427 | time elapsed: 11.28h | time left: 5.15h
batch  97100 | examples/s: 25.48 | loss: 0.47724 | time elapsed: 11.30h | time left: 5.14h
batch  97200 | examples/s: 26.45 | loss: 0.47246 | time elapsed: 11.31h | time left: 5.12h
batch  97300 | examples/s: 27.61 | loss: 0.46513 | time elapsed: 11.32h | time left: 5.11h
batch  97400 | examples/s: 27.26 | loss: 0.47130 | time elapsed: 11.33h | time left: 5.10h
batch  97500 | examples/s: 27.30 | loss: 0.47924 | time elapsed: 11.34h | time left: 5.09h
batch  97600 | examples/s: 27.93 | loss: 0.47501 | time elapsed: 11.35h | time left: 5.08h
batch  97700 | examples/s: 27.91 | loss: 0.47424 | time elapsed: 11.36h | time left: 5.07h
batch  97800 | examples/s: 27.70 | loss: 0.46809 | time elapsed: 11.38h | time left: 5.05h
batch  97900 | examples/s: 27.08 | loss: 0.46632 | time elapsed: 11.39h | time left: 5.04h
batch  98000 | examples/s: 27.41 | loss: 0.47686 | time elapsed: 11.40h | time left: 5.03h
batch  98100 | examples/s: 27.06 | loss: 0.47345 | time elapsed: 11.41h | time left: 5.02h
batch  98200 | examples/s: 26.75 | loss: 0.46940 | time elapsed: 11.42h | time left: 5.01h
batch  98300 | examples/s: 28.13 | loss: 0.46826 | time elapsed: 11.43h | time left: 5.00h
batch  98400 | examples/s: 27.52 | loss: 0.46446 | time elapsed: 11.45h | time left: 4.98h
batch  98500 | examples/s: 27.96 | loss: 0.47812 | time elapsed: 11.46h | time left: 4.97h
batch  98600 | examples/s: 27.76 | loss: 0.47430 | time elapsed: 11.47h | time left: 4.96h
batch  98700 | examples/s: 27.03 | loss: 0.46846 | time elapsed: 11.48h | time left: 4.95h
batch  98800 | examples/s: 28.14 | loss: 0.47314 | time elapsed: 11.49h | time left: 4.94h
epoch  34 | val loss: 0.49460 | time cost: 22.13 s |
batch  98900 | examples/s: 28.55 | loss: 0.48562 | time elapsed: 11.51h | time left: 4.93h
batch  99000 | examples/s: 27.86 | loss: 0.46759 | time elapsed: 11.52h | time left: 4.92h
batch  99100 | examples/s: 27.22 | loss: 0.46192 | time elapsed: 11.53h | time left: 4.91h
batch  99200 | examples/s: 28.07 | loss: 0.47587 | time elapsed: 11.54h | time left: 4.89h
batch  99300 | examples/s: 26.72 | loss: 0.49173 | time elapsed: 11.56h | time left: 4.88h
batch  99400 | examples/s: 27.81 | loss: 0.46330 | time elapsed: 11.57h | time left: 4.87h
batch  99500 | examples/s: 27.35 | loss: 0.47267 | time elapsed: 11.58h | time left: 4.86h
batch  99600 | examples/s: 28.00 | loss: 0.46809 | time elapsed: 11.59h | time left: 4.85h
batch  99700 | examples/s: 27.83 | loss: 0.47142 | time elapsed: 11.60h | time left: 4.83h
batch  99800 | examples/s: 28.13 | loss: 0.46779 | time elapsed: 11.61h | time left: 4.82h
batch  99900 | examples/s: 28.31 | loss: 0.47119 | time elapsed: 11.62h | time left: 4.81h
batch 100000 | examples/s: 27.54 | loss: 0.46760 | time elapsed: 11.64h | time left: 4.80h
batch 100100 | examples/s: 25.45 | loss: 0.46729 | time elapsed: 11.65h | time left: 4.79h
batch 100200 | examples/s: 26.86 | loss: 0.46789 | time elapsed: 11.66h | time left: 4.78h
batch 100300 | examples/s: 27.68 | loss: 0.46289 | time elapsed: 11.67h | time left: 4.76h
batch 100400 | examples/s: 26.94 | loss: 0.47195 | time elapsed: 11.68h | time left: 4.75h
batch 100500 | examples/s: 28.15 | loss: 0.47106 | time elapsed: 11.69h | time left: 4.74h
batch 100600 | examples/s: 26.90 | loss: 0.47855 | time elapsed: 11.70h | time left: 4.73h
batch 100700 | examples/s: 26.99 | loss: 0.48261 | time elapsed: 11.72h | time left: 4.72h
batch 100800 | examples/s: 26.50 | loss: 0.45891 | time elapsed: 11.73h | time left: 4.71h
batch 100900 | examples/s: 28.05 | loss: 0.46365 | time elapsed: 11.74h | time left: 4.69h
batch 101000 | examples/s: 27.17 | loss: 0.46192 | time elapsed: 11.75h | time left: 4.68h
batch 101100 | examples/s: 27.60 | loss: 0.46383 | time elapsed: 11.76h | time left: 4.67h
batch 101200 | examples/s: 27.03 | loss: 0.47425 | time elapsed: 11.77h | time left: 4.66h
batch 101300 | examples/s: 26.59 | loss: 0.46291 | time elapsed: 11.79h | time left: 4.65h
batch 101400 | examples/s: 27.97 | loss: 0.46187 | time elapsed: 11.80h | time left: 4.64h
batch 101500 | examples/s: 28.03 | loss: 0.46692 | time elapsed: 11.81h | time left: 4.62h
batch 101600 | examples/s: 27.20 | loss: 0.46681 | time elapsed: 11.82h | time left: 4.61h
batch 101700 | examples/s: 27.69 | loss: 0.48029 | time elapsed: 11.83h | time left: 4.60h
epoch  35 | val loss: 0.49568 | time cost: 19.95 s |
batch 101800 | examples/s: 26.66 | loss: 0.46627 | time elapsed: 11.85h | time left: 4.59h
batch 101900 | examples/s: 27.55 | loss: 0.47151 | time elapsed: 11.86h | time left: 4.58h
batch 102000 | examples/s: 28.12 | loss: 0.47155 | time elapsed: 11.87h | time left: 4.57h
batch 102100 | examples/s: 27.78 | loss: 0.47049 | time elapsed: 11.88h | time left: 4.56h
batch 102200 | examples/s: 26.29 | loss: 0.46631 | time elapsed: 11.89h | time left: 4.54h
batch 102300 | examples/s: 27.69 | loss: 0.46264 | time elapsed: 11.91h | time left: 4.53h
batch 102400 | examples/s: 27.85 | loss: 0.45147 | time elapsed: 11.92h | time left: 4.52h
batch 102500 | examples/s: 28.16 | loss: 0.47529 | time elapsed: 11.93h | time left: 4.51h
batch 102600 | examples/s: 28.39 | loss: 0.47255 | time elapsed: 11.94h | time left: 4.50h
batch 102700 | examples/s: 27.73 | loss: 0.46967 | time elapsed: 11.95h | time left: 4.49h
batch 102800 | examples/s: 27.52 | loss: 0.46859 | time elapsed: 11.96h | time left: 4.47h
batch 102900 | examples/s: 27.93 | loss: 0.46688 | time elapsed: 11.97h | time left: 4.46h
batch 103000 | examples/s: 27.60 | loss: 0.46551 | time elapsed: 11.99h | time left: 4.45h
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batch 103200 | examples/s: 27.35 | loss: 0.46199 | time elapsed: 12.01h | time left: 4.43h
batch 103300 | examples/s: 27.07 | loss: 0.47038 | time elapsed: 12.02h | time left: 4.42h
batch 103400 | examples/s: 27.37 | loss: 0.45719 | time elapsed: 12.03h | time left: 4.40h
batch 103500 | examples/s: 27.29 | loss: 0.46239 | time elapsed: 12.04h | time left: 4.39h
batch 103600 | examples/s: 27.92 | loss: 0.46928 | time elapsed: 12.05h | time left: 4.38h
batch 103700 | examples/s: 26.85 | loss: 0.46902 | time elapsed: 12.07h | time left: 4.37h
batch 103800 | examples/s: 25.03 | loss: 0.46302 | time elapsed: 12.08h | time left: 4.36h
batch 103900 | examples/s: 26.36 | loss: 0.46699 | time elapsed: 12.09h | time left: 4.35h
batch 104000 | examples/s: 27.99 | loss: 0.46012 | time elapsed: 12.10h | time left: 4.33h
batch 104100 | examples/s: 27.60 | loss: 0.46956 | time elapsed: 12.11h | time left: 4.32h
batch 104200 | examples/s: 27.38 | loss: 0.48358 | time elapsed: 12.12h | time left: 4.31h
batch 104300 | examples/s: 26.68 | loss: 0.47241 | time elapsed: 12.13h | time left: 4.30h
batch 104400 | examples/s: 27.99 | loss: 0.46801 | time elapsed: 12.15h | time left: 4.29h
batch 104500 | examples/s: 27.14 | loss: 0.47253 | time elapsed: 12.16h | time left: 4.28h
epoch  36 | val loss: 0.49416 | time cost: 19.65 s |
batch 104600 | examples/s: 27.91 | loss: 0.46631 | time elapsed: 12.18h | time left: 4.27h
batch 104700 | examples/s: 27.03 | loss: 0.45843 | time elapsed: 12.19h | time left: 4.25h
batch 104800 | examples/s: 27.70 | loss: 0.47027 | time elapsed: 12.20h | time left: 4.24h
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batch 107000 | examples/s: 26.88 | loss: 0.45598 | time elapsed: 12.45h | time left: 3.99h
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batch 107300 | examples/s: 27.95 | loss: 0.45890 | time elapsed: 12.49h | time left: 3.95h
epoch  37 | val loss: 0.49458 | time cost: 19.84 s |
batch 107400 | examples/s: 26.82 | loss: 0.45835 | time elapsed: 12.50h | time left: 3.94h
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batch 109800 | examples/s: 28.02 | loss: 0.45804 | time elapsed: 12.78h | time left: 3.66h
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batch 110000 | examples/s: 27.46 | loss: 0.46220 | time elapsed: 12.80h | time left: 3.64h
batch 110100 | examples/s: 27.67 | loss: 0.46054 | time elapsed: 12.81h | time left: 3.62h
epoch  38 | val loss: 0.49442 | time cost: 19.82 s |
batch 110200 | examples/s: 27.45 | loss: 0.46797 | time elapsed: 12.83h | time left: 3.61h
batch 110300 | examples/s: 26.43 | loss: 0.46911 | time elapsed: 12.84h | time left: 3.60h
batch 110400 | examples/s: 27.16 | loss: 0.46123 | time elapsed: 12.85h | time left: 3.59h
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batch 112600 | examples/s: 27.77 | loss: 0.45885 | time elapsed: 13.11h | time left: 3.33h
batch 112700 | examples/s: 28.04 | loss: 0.47377 | time elapsed: 13.12h | time left: 3.32h
batch 112800 | examples/s: 27.86 | loss: 0.46100 | time elapsed: 13.13h | time left: 3.31h
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batch 113000 | examples/s: 26.96 | loss: 0.47428 | time elapsed: 13.15h | time left: 3.29h
epoch  39 | val loss: 0.49316 | time cost: 20.15 s |
batch 113100 | examples/s: 27.68 | loss: 0.46359 | time elapsed: 13.17h | time left: 3.28h
batch 113200 | examples/s: 27.81 | loss: 0.47511 | time elapsed: 13.18h | time left: 3.27h
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batch 115400 | examples/s: 27.63 | loss: 0.46652 | time elapsed: 13.43h | time left: 3.01h
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batch 115800 | examples/s: 27.37 | loss: 0.45999 | time elapsed: 13.48h | time left: 2.96h
epoch  40 | val loss: 0.48991 | time cost: 19.96 s |
batch 115900 | examples/s: 27.46 | loss: 0.46834 | time elapsed: 13.50h | time left: 2.95h
batch 116000 | examples/s: 27.98 | loss: 0.45915 | time elapsed: 13.51h | time left: 2.94h
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batch 118600 | examples/s: 26.49 | loss: 0.45608 | time elapsed: 13.81h | time left: 2.64h
epoch  41 | val loss: 0.48889 | time cost: 19.76 s |
batch 118700 | examples/s: 27.84 | loss: 0.44321 | time elapsed: 13.83h | time left: 2.63h
batch 118800 | examples/s: 27.96 | loss: 0.44974 | time elapsed: 13.84h | time left: 2.61h
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batch 121400 | examples/s: 27.83 | loss: 0.45819 | time elapsed: 14.14h | time left: 2.31h
epoch  42 | val loss: 0.48779 | time cost: 19.96 s |
batch 121500 | examples/s: 26.91 | loss: 0.45526 | time elapsed: 14.15h | time left: 2.30h
batch 121600 | examples/s: 27.78 | loss: 0.45388 | time elapsed: 14.17h | time left: 2.29h
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batch 124300 | examples/s: 27.93 | loss: 0.44561 | time elapsed: 14.48h | time left: 1.97h
epoch  43 | val loss: 0.48808 | time cost: 19.64 s |
batch 124400 | examples/s: 27.65 | loss: 0.45619 | time elapsed: 14.49h | time left: 1.96h
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batch 127100 | examples/s: 27.61 | loss: 0.45256 | time elapsed: 14.80h | time left: 1.65h
epoch  44 | val loss: 0.48718 | time cost: 21.12 s |
batch 127200 | examples/s: 27.93 | loss: 0.46185 | time elapsed: 14.82h | time left: 1.64h
batch 127300 | examples/s: 27.32 | loss: 0.46053 | time elapsed: 14.83h | time left: 1.63h
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epoch  45 | val loss: 0.48790 | time cost: 20.29 s |
batch 130000 | examples/s: 27.24 | loss: 0.46230 | time elapsed: 15.15h | time left: 1.31h
batch 130100 | examples/s: 27.82 | loss: 0.44978 | time elapsed: 15.16h | time left: 1.30h
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epoch  46 | val loss: 0.48779 | time cost: 19.78 s |
batch 132800 | examples/s: 27.81 | loss: 0.45278 | time elapsed: 15.48h | time left: 0.98h
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batch 135600 | examples/s: 25.38 | loss: 0.46033 | time elapsed: 15.80h | time left: 0.66h
epoch  47 | val loss: 0.48705 | time cost: 20.80 s |
batch 135700 | examples/s: 27.01 | loss: 0.44616 | time elapsed: 15.82h | time left: 0.65h
batch 135800 | examples/s: 27.73 | loss: 0.43835 | time elapsed: 15.83h | time left: 0.64h
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batch 138100 | examples/s: 27.69 | loss: 0.44894 | time elapsed: 16.09h | time left: 0.37h
batch 138200 | examples/s: 27.08 | loss: 0.45236 | time elapsed: 16.10h | time left: 0.36h
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batch 138400 | examples/s: 27.85 | loss: 0.46300 | time elapsed: 16.13h | time left: 0.33h
epoch  48 | val loss: 0.48673 | time cost: 20.12 s |
batch 138500 | examples/s: 27.64 | loss: 0.44032 | time elapsed: 16.14h | time left: 0.32h
batch 138600 | examples/s: 27.35 | loss: 0.43676 | time elapsed: 16.15h | time left: 0.31h
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batch 140300 | examples/s: 27.82 | loss: 0.44026 | time elapsed: 16.35h | time left: 0.11h
batch 140400 | examples/s: 27.63 | loss: 0.44777 | time elapsed: 16.36h | time left: 0.10h
batch 140500 | examples/s: 27.34 | loss: 0.46149 | time elapsed: 16.37h | time left: 0.09h
batch 140600 | examples/s: 26.40 | loss: 0.44626 | time elapsed: 16.39h | time left: 0.08h
batch 140700 | examples/s: 27.29 | loss: 0.45322 | time elapsed: 16.40h | time left: 0.06h
batch 140800 | examples/s: 28.15 | loss: 0.44896 | time elapsed: 16.41h | time left: 0.05h
batch 140900 | examples/s: 27.60 | loss: 0.45597 | time elapsed: 16.42h | time left: 0.04h
batch 141000 | examples/s: 28.28 | loss: 0.44631 | time elapsed: 16.43h | time left: 0.03h
batch 141100 | examples/s: 27.83 | loss: 0.45304 | time elapsed: 16.44h | time left: 0.02h
batch 141200 | examples/s: 28.11 | loss: 0.46040 | time elapsed: 16.45h | time left: 0.01h
epoch  49 | val loss: 0.48708 | time cost: 19.95 s |

0 files missing
   abs_rel,     sq_rel,        rms,    log_rms,     d1_all,         a1,         a2,         a3
    0.1290,     1.2393,      5.265,      0.226,      0.000,      0.843,      0.941,      0.972