Epoch: [0][0/45]	Time 28.807 (28.807)	Data 21.450 (21.450)	Loss 1.1422 (1.1422)	MAE 0.999 (0.999)
Epoch: [0][1/45]	Time 26.848 (27.827)	Data 20.083 (20.767)	Loss 1.0313 (1.0868)	MAE 0.987 (0.993)
Epoch: [0][2/45]	Time 27.646 (27.767)	Data 20.691 (20.742)	Loss 1.1087 (1.0941)	MAE 1.014 (1.000)
Epoch: [0][3/45]	Time 29.390 (28.173)	Data 22.002 (21.057)	Loss 1.3756 (1.1645)	MAE 1.085 (1.021)
Epoch: [0][4/45]	Time 26.924 (27.923)	Data 20.051 (20.856)	Loss 2.1051 (1.3526)	MAE 1.381 (1.093)
Epoch: [0][5/45]	Time 27.716 (27.888)	Data 20.783 (20.844)	Loss 2.1518 (1.4858)	MAE 1.397 (1.144)
Epoch: [0][6/45]	Time 28.262 (27.942)	Data 21.522 (20.940)	Loss 0.9792 (1.4134)	MAE 0.948 (1.116)
Epoch: [0][7/45]	Time 28.068 (27.958)	Data 21.137 (20.965)	Loss 0.8590 (1.3441)	MAE 0.902 (1.089)
Epoch: [0][8/45]	Time 29.235 (28.100)	Data 22.270 (21.110)	Loss 1.0692 (1.3136)	MAE 0.911 (1.069)
Epoch: [0][9/45]	Time 28.205 (28.110)	Data 21.270 (21.126)	Loss 0.6756 (1.2498)	MAE 0.732 (1.036)
Epoch: [0][10/45]	Time 29.010 (28.192)	Data 21.960 (21.202)	Loss 1.1030 (1.2364)	MAE 1.016 (1.034)
Epoch: [0][11/45]	Time 27.504 (28.135)	Data 20.835 (21.171)	Loss 0.7654 (1.1972)	MAE 0.802 (1.015)
Epoch: [0][12/45]	Time 29.047 (28.205)	Data 21.977 (21.233)	Loss 0.8732 (1.1723)	MAE 0.822 (1.000)
Epoch: [0][13/45]	Time 30.272 (28.353)	Data 23.173 (21.372)	Loss 0.5653 (1.1289)	MAE 0.677 (0.977)
Epoch: [0][14/45]	Time 29.510 (28.430)	Data 22.414 (21.441)	Loss 0.6675 (1.0982)	MAE 0.757 (0.962)
Epoch: [0][15/45]	Time 28.929 (28.461)	Data 22.322 (21.496)	Loss 0.7052 (1.0736)	MAE 0.780 (0.951)
Epoch: [0][16/45]	Time 26.796 (28.363)	Data 19.834 (21.399)	Loss 0.6238 (1.0471)	MAE 0.715 (0.937)
Epoch: [0][17/45]	Time 28.416 (28.366)	Data 21.340 (21.395)	Loss 0.4276 (1.0127)	MAE 0.590 (0.918)
Epoch: [0][18/45]	Time 28.966 (28.398)	Data 22.160 (21.436)	Loss 0.5343 (0.9875)	MAE 0.667 (0.904)
Epoch: [0][19/45]	Time 30.154 (28.485)	Data 23.285 (21.528)	Loss 0.5359 (0.9650)	MAE 0.651 (0.892)
Epoch: [0][20/45]	Time 27.476 (28.437)	Data 20.515 (21.480)	Loss 0.6020 (0.9477)	MAE 0.707 (0.883)
Epoch: [0][21/45]	Time 26.555 (28.352)	Data 19.966 (21.411)	Loss 0.4617 (0.9256)	MAE 0.617 (0.871)
Epoch: [0][22/45]	Time 27.779 (28.327)	Data 20.728 (21.381)	Loss 0.5162 (0.9078)	MAE 0.646 (0.861)
Epoch: [0][23/45]	Time 27.967 (28.312)	Data 21.024 (21.366)	Loss 0.4457 (0.8885)	MAE 0.595 (0.850)
Epoch: [0][24/45]	Time 26.955 (28.258)	Data 20.064 (21.314)	Loss 0.4235 (0.8699)	MAE 0.585 (0.839)
Epoch: [0][25/45]	Time 29.360 (28.300)	Data 22.146 (21.346)	Loss 0.4335 (0.8531)	MAE 0.580 (0.829)
Epoch: [0][26/45]	Time 27.466 (28.269)	Data 20.710 (21.323)	Loss 0.5166 (0.8407)	MAE 0.650 (0.823)
Epoch: [0][27/45]	Time 27.659 (28.247)	Data 20.919 (21.308)	Loss 0.4279 (0.8259)	MAE 0.605 (0.815)
Epoch: [0][28/45]	Time 26.863 (28.200)	Data 20.118 (21.267)	Loss 0.4284 (0.8122)	MAE 0.603 (0.808)
Epoch: [0][29/45]	Time 26.760 (28.152)	Data 20.171 (21.231)	Loss 0.3970 (0.7984)	MAE 0.564 (0.800)
Epoch: [0][30/45]	Time 26.988 (28.114)	Data 20.282 (21.200)	Loss 0.4777 (0.7880)	MAE 0.610 (0.793)
Epoch: [0][31/45]	Time 27.537 (28.096)	Data 20.809 (21.188)	Loss 0.4413 (0.7772)	MAE 0.600 (0.787)
Epoch: [0][32/45]	Time 27.713 (28.084)	Data 20.754 (21.175)	Loss 0.4224 (0.7664)	MAE 0.591 (0.781)
Epoch: [0][33/45]	Time 28.144 (28.086)	Data 21.075 (21.172)	Loss 0.3373 (0.7538)	MAE 0.510 (0.773)
Epoch: [0][34/45]	Time 27.433 (28.067)	Data 20.827 (21.162)	Loss 0.4358 (0.7447)	MAE 0.580 (0.768)
Epoch: [0][35/45]	Time 28.767 (28.087)	Data 21.460 (21.170)	Loss 0.4014 (0.7352)	MAE 0.542 (0.762)
Epoch: [0][36/45]	Time 28.622 (28.101)	Data 21.594 (21.182)	Loss 0.3988 (0.7261)	MAE 0.540 (0.756)
Epoch: [0][37/45]	Time 26.750 (28.066)	Data 20.193 (21.156)	Loss 0.4446 (0.7187)	MAE 0.584 (0.751)
Epoch: [0][38/45]	Time 27.168 (28.043)	Data 20.343 (21.135)	Loss 0.4282 (0.7113)	MAE 0.560 (0.746)
Epoch: [0][39/45]	Time 26.667 (28.008)	Data 20.074 (21.108)	Loss 0.4163 (0.7039)	MAE 0.588 (0.742)
Epoch: [0][40/45]	Time 26.819 (27.979)	Data 20.242 (21.087)	Loss 0.4148 (0.6968)	MAE 0.553 (0.738)
Epoch: [0][41/45]	Time 28.329 (27.988)	Data 21.439 (21.096)	Loss 0.4015 (0.6898)	MAE 0.598 (0.734)
Epoch: [0][42/45]	Time 29.131 (28.014)	Data 22.346 (21.125)	Loss 0.4827 (0.6850)	MAE 0.609 (0.731)
Epoch: [0][43/45]	Time 26.441 (27.979)	Data 19.741 (21.093)	Loss 0.3543 (0.6775)	MAE 0.526 (0.727)
Epoch: [0][44/45]	Time 13.212 (27.650)	Data 9.797 (20.842)	Loss 0.3276 (0.6736)	MAE 0.528 (0.725)
Validation: [0/6]	Time 23.425 (23.425)	Loss 0.5935 (0.5935)	MAE 0.736 (0.736)
Validation: [1/6]	Time 24.361 (23.893)	Loss 0.5134 (0.5535)	MAE 0.660 (0.698)
Validation: [2/6]	Time 22.521 (23.436)	Loss 0.6047 (0.5705)	MAE 0.731 (0.709)
Validation: [3/6]	Time 25.423 (23.932)	Loss 0.5812 (0.5732)	MAE 0.712 (0.710)
Validation: [4/6]	Time 25.616 (24.269)	Loss 0.5098 (0.5605)	MAE 0.665 (0.701)
Validation: [5/6]	Time 13.435 (22.463)	Loss 0.5318 (0.5577)	MAE 0.676 (0.698)
 * MAE 0.698
Epoch: [1][0/45]	Time 7.170 (7.170)	Data 0.030 (0.030)	Loss 0.3952 (0.3952)	MAE 0.579 (0.579)
Epoch: [1][1/45]	Time 7.104 (7.137)	Data 0.029 (0.029)	Loss 0.5019 (0.4486)	MAE 0.596 (0.587)
Epoch: [1][2/45]	Time 7.163 (7.146)	Data 0.042 (0.033)	Loss 0.4190 (0.4387)	MAE 0.572 (0.582)
Epoch: [1][3/45]	Time 7.119 (7.139)	Data 0.034 (0.034)	Loss 0.3264 (0.4107)	MAE 0.513 (0.565)
Epoch: [1][4/45]	Time 6.793 (7.070)	Data 0.034 (0.034)	Loss 0.3935 (0.4072)	MAE 0.527 (0.557)
Epoch: [1][5/45]	Time 7.113 (7.077)	Data 0.028 (0.033)	Loss 0.3717 (0.4013)	MAE 0.555 (0.557)
Epoch: [1][6/45]	Time 7.064 (7.075)	Data 0.034 (0.033)	Loss 0.4180 (0.4037)	MAE 0.580 (0.560)
Epoch: [1][7/45]	Time 6.703 (7.029)	Data 0.033 (0.033)	Loss 0.4279 (0.4067)	MAE 0.577 (0.562)
Epoch: [1][8/45]	Time 6.838 (7.007)	Data 0.029 (0.032)	Loss 0.3737 (0.4031)	MAE 0.536 (0.560)
Epoch: [1][9/45]	Time 6.932 (7.000)	Data 0.026 (0.032)	Loss 0.4235 (0.4051)	MAE 0.573 (0.561)
Epoch: [1][10/45]	Time 6.832 (6.985)	Data 0.026 (0.031)	Loss 0.3665 (0.4016)	MAE 0.535 (0.558)
Epoch: [1][11/45]	Time 6.729 (6.963)	Data 0.025 (0.031)	Loss 0.3709 (0.3990)	MAE 0.552 (0.558)
Epoch: [1][12/45]	Time 6.972 (6.964)	Data 0.025 (0.030)	Loss 0.4126 (0.4001)	MAE 0.571 (0.559)
Epoch: [1][13/45]	Time 6.939 (6.962)	Data 0.033 (0.030)	Loss 0.4212 (0.4016)	MAE 0.552 (0.558)
Epoch: [1][14/45]	Time 6.872 (6.956)	Data 0.035 (0.031)	Loss 0.4076 (0.4020)	MAE 0.544 (0.557)
Epoch: [1][15/45]	Time 7.229 (6.973)	Data 0.026 (0.030)	Loss 0.3912 (0.4013)	MAE 0.558 (0.557)
Epoch: [1][16/45]	Time 6.721 (6.958)	Data 0.030 (0.030)	Loss 0.4010 (0.4013)	MAE 0.561 (0.558)
Epoch: [1][17/45]	Time 6.763 (6.948)	Data 0.025 (0.030)	Loss 0.3673 (0.3994)	MAE 0.546 (0.557)
Epoch: [1][18/45]	Time 6.815 (6.941)	Data 0.028 (0.030)	Loss 0.3550 (0.3971)	MAE 0.519 (0.555)
Epoch: [1][19/45]	Time 6.789 (6.933)	Data 0.026 (0.030)	Loss 0.3852 (0.3965)	MAE 0.546 (0.555)
Epoch: [1][20/45]	Time 7.045 (6.938)	Data 0.028 (0.030)	Loss 0.3508 (0.3943)	MAE 0.523 (0.553)
Epoch: [1][21/45]	Time 6.685 (6.927)	Data 0.026 (0.030)	Loss 0.3622 (0.3928)	MAE 0.529 (0.552)
Epoch: [1][22/45]	Time 6.930 (6.927)	Data 0.026 (0.029)	Loss 0.3819 (0.3924)	MAE 0.547 (0.552)
Epoch: [1][23/45]	Time 6.969 (6.929)	Data 0.031 (0.029)	Loss 0.4475 (0.3947)	MAE 0.548 (0.552)
Epoch: [1][24/45]	Time 7.075 (6.935)	Data 0.030 (0.030)	Loss 0.3654 (0.3935)	MAE 0.511 (0.550)
Epoch: [1][25/45]	Time 7.061 (6.939)	Data 0.030 (0.030)	Loss 0.3537 (0.3920)	MAE 0.514 (0.549)
Epoch: [1][26/45]	Time 6.690 (6.930)	Data 0.025 (0.029)	Loss 0.3701 (0.3911)	MAE 0.528 (0.548)
Epoch: [1][27/45]	Time 6.970 (6.932)	Data 0.029 (0.029)	Loss 0.3711 (0.3904)	MAE 0.527 (0.547)
Epoch: [1][28/45]	Time 7.017 (6.935)	Data 0.025 (0.029)	Loss 0.2952 (0.3871)	MAE 0.474 (0.545)
Epoch: [1][29/45]	Time 6.489 (6.920)	Data 0.024 (0.029)	Loss 0.3046 (0.3844)	MAE 0.482 (0.543)
Epoch: [1][30/45]	Time 6.738 (6.914)	Data 0.025 (0.029)	Loss 0.3534 (0.3834)	MAE 0.525 (0.542)
Epoch: [1][31/45]	Time 6.898 (6.913)	Data 0.027 (0.029)	Loss 0.3286 (0.3817)	MAE 0.511 (0.541)
Epoch: [1][32/45]	Time 6.787 (6.910)	Data 0.025 (0.029)	Loss 0.3261 (0.3800)	MAE 0.525 (0.541)
Epoch: [1][33/45]	Time 7.487 (6.926)	Data 0.024 (0.029)	Loss 0.3819 (0.3801)	MAE 0.538 (0.540)
Epoch: [1][34/45]	Time 6.875 (6.925)	Data 0.030 (0.029)	Loss 0.3107 (0.3781)	MAE 0.489 (0.539)
Epoch: [1][35/45]	Time 7.031 (6.928)	Data 0.024 (0.028)	Loss 0.4032 (0.3788)	MAE 0.534 (0.539)
Epoch: [1][36/45]	Time 7.157 (6.934)	Data 0.027 (0.028)	Loss 0.2801 (0.3761)	MAE 0.497 (0.538)
Epoch: [1][37/45]	Time 6.872 (6.933)	Data 0.024 (0.028)	Loss 0.3881 (0.3764)	MAE 0.543 (0.538)
Epoch: [1][38/45]	Time 7.104 (6.937)	Data 0.028 (0.028)	Loss 0.3667 (0.3762)	MAE 0.546 (0.538)
Epoch: [1][39/45]	Time 7.078 (6.940)	Data 0.030 (0.028)	Loss 0.3839 (0.3764)	MAE 0.506 (0.537)
Epoch: [1][40/45]	Time 6.926 (6.940)	Data 0.035 (0.029)	Loss 0.3633 (0.3760)	MAE 0.524 (0.537)
Epoch: [1][41/45]	Time 6.791 (6.937)	Data 0.023 (0.028)	Loss 0.3300 (0.3749)	MAE 0.512 (0.536)
Epoch: [1][42/45]	Time 6.761 (6.932)	Data 0.024 (0.028)	Loss 0.3634 (0.3747)	MAE 0.530 (0.536)
Epoch: [1][43/45]	Time 6.807 (6.930)	Data 0.025 (0.028)	Loss 0.4238 (0.3758)	MAE 0.538 (0.536)
Epoch: [1][44/45]	Time 3.415 (6.851)	Data 0.013 (0.028)	Loss 0.3238 (0.3752)	MAE 0.522 (0.536)
Validation: [0/6]	Time 3.061 (3.061)	Loss 0.4465 (0.4465)	MAE 0.581 (0.581)
Validation: [1/6]	Time 3.109 (3.085)	Loss 0.3984 (0.4225)	MAE 0.546 (0.563)
Validation: [2/6]	Time 3.003 (3.057)	Loss 0.3881 (0.4110)	MAE 0.558 (0.562)
Validation: [3/6]	Time 3.005 (3.044)	Loss 0.3427 (0.3939)	MAE 0.509 (0.548)
Validation: [4/6]	Time 3.121 (3.060)	Loss 0.3937 (0.3939)	MAE 0.566 (0.552)
Validation: [5/6]	Time 1.572 (2.812)	Loss 0.4790 (0.4024)	MAE 0.605 (0.557)
 * MAE 0.557
---------Evaluate Model on Test Set---------------
Validation: [0/6]	Time 27.193 (27.193)	Loss 0.4585 (0.4585)	MAE 0.599 (0.599)
Validation: [1/6]	Time 27.790 (27.491)	Loss 0.3181 (0.3883)	MAE 0.500 (0.550)
Validation: [2/6]	Time 27.160 (27.381)	Loss 0.4632 (0.4133)	MAE 0.592 (0.564)
Validation: [3/6]	Time 29.348 (27.873)	Loss 0.3841 (0.4060)	MAE 0.541 (0.558)
Validation: [4/6]	Time 33.030 (28.904)	Loss 0.3865 (0.4021)	MAE 0.509 (0.548)
Validation: [5/6]	Time 19.275 (27.299)	Loss 0.3324 (0.3951)	MAE 0.516 (0.545)
 ** MAE 0.545