lr: 0.001
sub_6:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2353 - F1: 0.1739
sub_9:Test (Best Model) - Loss: 1.1688 - Accuracy: 0.3824 - F1: 0.3447
sub_4:Test (Best Model) - Loss: 1.2032 - Accuracy: 0.4348 - F1: 0.2889
sub_5:Test (Best Model) - Loss: 1.3324 - Accuracy: 0.3088 - F1: 0.2022
sub_7:Test (Best Model) - Loss: 1.2405 - Accuracy: 0.4265 - F1: 0.3819
sub_10:Test (Best Model) - Loss: 1.0740 - Accuracy: 0.4559 - F1: 0.3628
sub_2:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.5797 - F1: 0.5761
sub_8:Test (Best Model) - Loss: 2.8126 - Accuracy: 0.3088 - F1: 0.2723
sub_3:Test (Best Model) - Loss: 1.1057 - Accuracy: 0.6029 - F1: 0.5990
sub_6:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.3971 - F1: 0.3743
sub_5:Test (Best Model) - Loss: 1.0174 - Accuracy: 0.5735 - F1: 0.5057
sub_1:Test (Best Model) - Loss: 0.9644 - Accuracy: 0.5441 - F1: 0.4542
sub_4:Test (Best Model) - Loss: 1.1397 - Accuracy: 0.4203 - F1: 0.3568
sub_9:Test (Best Model) - Loss: 1.0909 - Accuracy: 0.3824 - F1: 0.2796
sub_2:Test (Best Model) - Loss: 1.1050 - Accuracy: 0.4203 - F1: 0.3645
sub_3:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.5294 - F1: 0.4761
sub_7:Test (Best Model) - Loss: 1.9714 - Accuracy: 0.4118 - F1: 0.4069
sub_10:Test (Best Model) - Loss: 1.1147 - Accuracy: 0.4853 - F1: 0.4820
sub_6:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.3824 - F1: 0.3804
sub_5:Test (Best Model) - Loss: 1.7158 - Accuracy: 0.3382 - F1: 0.2949
sub_8:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.3676 - F1: 0.3455
sub_3:Test (Best Model) - Loss: 1.9844 - Accuracy: 0.3382 - F1: 0.2423
sub_2:Test (Best Model) - Loss: 1.1139 - Accuracy: 0.4058 - F1: 0.3219
sub_7:Test (Best Model) - Loss: 1.3170 - Accuracy: 0.3676 - F1: 0.2806
sub_5:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3529 - F1: 0.3145
sub_6:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2647 - F1: 0.1084
sub_1:Test (Best Model) - Loss: 1.1447 - Accuracy: 0.5441 - F1: 0.5600
sub_4:Test (Best Model) - Loss: 1.6656 - Accuracy: 0.4638 - F1: 0.4819
sub_5:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.2647 - F1: 0.2204
sub_9:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.6471 - F1: 0.6132
sub_2:Test (Best Model) - Loss: 1.2180 - Accuracy: 0.3623 - F1: 0.2785
sub_8:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.3088 - F1: 0.2611
sub_10:Test (Best Model) - Loss: 1.0793 - Accuracy: 0.4118 - F1: 0.4354
sub_7:Test (Best Model) - Loss: 1.0997 - Accuracy: 0.4706 - F1: 0.3786
sub_6:Test (Best Model) - Loss: 1.5096 - Accuracy: 0.2941 - F1: 0.2065
sub_2:Test (Best Model) - Loss: 1.2090 - Accuracy: 0.3623 - F1: 0.2661
sub_3:Test (Best Model) - Loss: 1.6244 - Accuracy: 0.4706 - F1: 0.4189
sub_4:Test (Best Model) - Loss: 0.9681 - Accuracy: 0.5797 - F1: 0.5955
sub_1:Test (Best Model) - Loss: 1.0938 - Accuracy: 0.4853 - F1: 0.5045
sub_9:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.4559 - F1: 0.4187
sub_7:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.2647 - F1: 0.2518
sub_4:Test (Best Model) - Loss: 1.2266 - Accuracy: 0.3768 - F1: 0.2878
sub_6:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.2609 - F1: 0.2102
sub_5:Test (Best Model) - Loss: 1.6741 - Accuracy: 0.5294 - F1: 0.5338
sub_2:Test (Best Model) - Loss: 1.0419 - Accuracy: 0.4706 - F1: 0.4000
sub_10:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.3971 - F1: 0.3458
sub_7:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.4118 - F1: 0.3020
sub_8:Test (Best Model) - Loss: 4.0708 - Accuracy: 0.3529 - F1: 0.3305
sub_3:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.3529 - F1: 0.2732
sub_6:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.2609 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 1.1068 - Accuracy: 0.4853 - F1: 0.4614
sub_9:Test (Best Model) - Loss: 1.1174 - Accuracy: 0.5147 - F1: 0.5045
sub_4:Test (Best Model) - Loss: 1.2670 - Accuracy: 0.5507 - F1: 0.5041
sub_6:Test (Best Model) - Loss: 1.2745 - Accuracy: 0.3623 - F1: 0.2800
sub_2:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.5441 - F1: 0.5341
sub_5:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.4118 - F1: 0.4030
sub_10:Test (Best Model) - Loss: 0.8631 - Accuracy: 0.6029 - F1: 0.5910
sub_6:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2464 - F1: 0.1214
sub_7:Test (Best Model) - Loss: 1.2575 - Accuracy: 0.4118 - F1: 0.4280
sub_3:Test (Best Model) - Loss: 1.1369 - Accuracy: 0.4203 - F1: 0.3697
sub_9:Test (Best Model) - Loss: 1.1517 - Accuracy: 0.4706 - F1: 0.3540
sub_8:Test (Best Model) - Loss: 1.9627 - Accuracy: 0.2941 - F1: 0.1764
sub_1:Test (Best Model) - Loss: 0.8839 - Accuracy: 0.6765 - F1: 0.6892
sub_4:Test (Best Model) - Loss: 0.9925 - Accuracy: 0.5072 - F1: 0.4818
sub_6:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.3478 - F1: 0.3299
sub_10:Test (Best Model) - Loss: 0.8519 - Accuracy: 0.7059 - F1: 0.7093
sub_8:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2794 - F1: 0.1832
sub_2:Test (Best Model) - Loss: 1.0013 - Accuracy: 0.5441 - F1: 0.5090
sub_6:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2899 - F1: 0.1580
sub_5:Test (Best Model) - Loss: 0.9646 - Accuracy: 0.5441 - F1: 0.5285
sub_7:Test (Best Model) - Loss: 1.6845 - Accuracy: 0.2647 - F1: 0.2755
sub_4:Test (Best Model) - Loss: 1.2063 - Accuracy: 0.4928 - F1: 0.4677
sub_6:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2754 - F1: 0.1410
sub_3:Test (Best Model) - Loss: 0.9276 - Accuracy: 0.6522 - F1: 0.6332
sub_9:Test (Best Model) - Loss: 0.8725 - Accuracy: 0.7059 - F1: 0.7071
sub_10:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.6029 - F1: 0.5968
sub_6:Test (Best Model) - Loss: 1.3249 - Accuracy: 0.2899 - F1: 0.1653
sub_5:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3824 - F1: 0.3253
sub_8:Test (Best Model) - Loss: 1.8806 - Accuracy: 0.2206 - F1: 0.2490
sub_7:Test (Best Model) - Loss: 1.0170 - Accuracy: 0.5441 - F1: 0.5566
sub_6:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2899 - F1: 0.1647
sub_3:Test (Best Model) - Loss: 1.1900 - Accuracy: 0.4928 - F1: 0.3530
sub_2:Test (Best Model) - Loss: 0.9074 - Accuracy: 0.5294 - F1: 0.5114
sub_1:Test (Best Model) - Loss: 2.2736 - Accuracy: 0.4928 - F1: 0.4687
sub_8:Test (Best Model) - Loss: 1.4565 - Accuracy: 0.3529 - F1: 0.2785
sub_4:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.4203 - F1: 0.3712
sub_10:Test (Best Model) - Loss: 1.0718 - Accuracy: 0.4559 - F1: 0.4388
sub_5:Test (Best Model) - Loss: 1.1633 - Accuracy: 0.4412 - F1: 0.4328
sub_9:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.6029 - F1: 0.5663
sub_6:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.3043 - F1: 0.2214
sub_1:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.5652 - F1: 0.5565
sub_4:Test (Best Model) - Loss: 1.1341 - Accuracy: 0.4638 - F1: 0.4254
sub_8:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.3088 - F1: 0.2293
sub_2:Test (Best Model) - Loss: 0.9082 - Accuracy: 0.6029 - F1: 0.5824
sub_10:Test (Best Model) - Loss: 1.0290 - Accuracy: 0.6029 - F1: 0.6009
sub_9:Test (Best Model) - Loss: 1.1415 - Accuracy: 0.4265 - F1: 0.3755
sub_3:Test (Best Model) - Loss: 0.9809 - Accuracy: 0.4493 - F1: 0.3752
sub_7:Test (Best Model) - Loss: 1.9530 - Accuracy: 0.4118 - F1: 0.3878
sub_8:Test (Best Model) - Loss: 1.3037 - Accuracy: 0.3529 - F1: 0.3022
sub_5:Test (Best Model) - Loss: 1.6570 - Accuracy: 0.3382 - F1: 0.2911
sub_4:Test (Best Model) - Loss: 1.1395 - Accuracy: 0.5072 - F1: 0.5162
sub_2:Test (Best Model) - Loss: 0.9484 - Accuracy: 0.5217 - F1: 0.4785
sub_1:Test (Best Model) - Loss: 1.1368 - Accuracy: 0.4928 - F1: 0.5020
sub_7:Test (Best Model) - Loss: 1.3005 - Accuracy: 0.3382 - F1: 0.2683
sub_9:Test (Best Model) - Loss: 1.0176 - Accuracy: 0.5441 - F1: 0.4771
sub_10:Test (Best Model) - Loss: 0.9207 - Accuracy: 0.5735 - F1: 0.5793
sub_8:Test (Best Model) - Loss: 0.9667 - Accuracy: 0.5294 - F1: 0.4943
sub_2:Test (Best Model) - Loss: 0.9514 - Accuracy: 0.5507 - F1: 0.4957
sub_4:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4638 - F1: 0.3782
sub_5:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3235 - F1: 0.2491
sub_3:Test (Best Model) - Loss: 1.0309 - Accuracy: 0.5797 - F1: 0.5523
sub_1:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.4493 - F1: 0.4204
sub_4:Test (Best Model) - Loss: 1.5207 - Accuracy: 0.3333 - F1: 0.2375
sub_2:Test (Best Model) - Loss: 1.2580 - Accuracy: 0.5072 - F1: 0.4948
sub_8:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.4265 - F1: 0.4031
sub_10:Test (Best Model) - Loss: 1.0844 - Accuracy: 0.5652 - F1: 0.5473
sub_9:Test (Best Model) - Loss: 1.8294 - Accuracy: 0.2941 - F1: 0.2282
sub_7:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.3235 - F1: 0.3356
sub_1:Test (Best Model) - Loss: 1.2005 - Accuracy: 0.4783 - F1: 0.4689
sub_5:Test (Best Model) - Loss: 1.3332 - Accuracy: 0.3529 - F1: 0.2527
sub_8:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.4412 - F1: 0.3712
sub_4:Test (Best Model) - Loss: 1.3165 - Accuracy: 0.4783 - F1: 0.4555
sub_8:Test (Best Model) - Loss: 1.2938 - Accuracy: 0.3529 - F1: 0.2818
sub_4:Test (Best Model) - Loss: 1.4696 - Accuracy: 0.2464 - F1: 0.1024
sub_3:Test (Best Model) - Loss: 1.6178 - Accuracy: 0.5217 - F1: 0.4637
sub_9:Test (Best Model) - Loss: 1.3005 - Accuracy: 0.3088 - F1: 0.1905
sub_7:Test (Best Model) - Loss: 1.0611 - Accuracy: 0.4559 - F1: 0.3212
sub_2:Test (Best Model) - Loss: 0.9402 - Accuracy: 0.5797 - F1: 0.5873
sub_10:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.5652 - F1: 0.5337
sub_1:Test (Best Model) - Loss: 1.8264 - Accuracy: 0.4265 - F1: 0.4025
sub_8:Test (Best Model) - Loss: 1.4558 - Accuracy: 0.2941 - F1: 0.2178
sub_5:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.4559 - F1: 0.4354
sub_10:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4058 - F1: 0.3184
sub_7:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.4412 - F1: 0.3738
sub_9:Test (Best Model) - Loss: 2.1234 - Accuracy: 0.4118 - F1: 0.2731
sub_3:Test (Best Model) - Loss: 1.9922 - Accuracy: 0.2754 - F1: 0.1310
sub_2:Test (Best Model) - Loss: 0.8691 - Accuracy: 0.5507 - F1: 0.4828
sub_5:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.1375 - Accuracy: 0.5735 - F1: 0.5081
sub_10:Test (Best Model) - Loss: 0.8531 - Accuracy: 0.5652 - F1: 0.5614
sub_7:Test (Best Model) - Loss: 1.0993 - Accuracy: 0.2647 - F1: 0.2674
sub_1:Test (Best Model) - Loss: 1.1436 - Accuracy: 0.4118 - F1: 0.3216
sub_10:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.4203 - F1: 0.3348
sub_3:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.4928 - F1: 0.4036
sub_9:Test (Best Model) - Loss: 1.0781 - Accuracy: 0.3235 - F1: 0.2500
sub_9:Test (Best Model) - Loss: 1.2113 - Accuracy: 0.3676 - F1: 0.2942
sub_1:Test (Best Model) - Loss: 1.3309 - Accuracy: 0.6471 - F1: 0.6389
sub_3:Test (Best Model) - Loss: 2.2788 - Accuracy: 0.5797 - F1: 0.5106
sub_1:Test (Best Model) - Loss: 1.2241 - Accuracy: 0.6471 - F1: 0.5775
sub_3:Test (Best Model) - Loss: 1.1643 - Accuracy: 0.4058 - F1: 0.3368
sub_20:Test (Best Model) - Loss: 1.8557 - Accuracy: 0.2500 - F1: 0.1321
sub_12:Test (Best Model) - Loss: 1.1880 - Accuracy: 0.3824 - F1: 0.3758
sub_18:Test (Best Model) - Loss: 0.9613 - Accuracy: 0.4638 - F1: 0.3076
sub_17:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.4638 - F1: 0.3122
sub_19:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.3824 - F1: 0.3203
sub_16:Test (Best Model) - Loss: 1.1723 - Accuracy: 0.5735 - F1: 0.5804
sub_14:Test (Best Model) - Loss: 2.9468 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.4638 - F1: 0.4611
sub_15:Test (Best Model) - Loss: 1.2935 - Accuracy: 0.4412 - F1: 0.4067
sub_12:Test (Best Model) - Loss: 1.2782 - Accuracy: 0.3676 - F1: 0.3195
sub_20:Test (Best Model) - Loss: 1.6534 - Accuracy: 0.3088 - F1: 0.2732
sub_17:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.3768 - F1: 0.2548
sub_18:Test (Best Model) - Loss: 0.7308 - Accuracy: 0.5942 - F1: 0.5890
sub_13:Test (Best Model) - Loss: 1.2909 - Accuracy: 0.3529 - F1: 0.3713
sub_14:Test (Best Model) - Loss: 3.8242 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 0.8637 - Accuracy: 0.6029 - F1: 0.5936
sub_12:Test (Best Model) - Loss: 1.4578 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.2794 - F1: 0.1815
sub_16:Test (Best Model) - Loss: 1.2556 - Accuracy: 0.5294 - F1: 0.5234
sub_11:Test (Best Model) - Loss: 1.0420 - Accuracy: 0.5217 - F1: 0.5104
sub_12:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.2941 - F1: 0.1764
sub_14:Test (Best Model) - Loss: 3.6928 - Accuracy: 0.2794 - F1: 0.1322
sub_20:Test (Best Model) - Loss: 2.2804 - Accuracy: 0.3382 - F1: 0.2978
sub_15:Test (Best Model) - Loss: 1.5854 - Accuracy: 0.3088 - F1: 0.2105
sub_18:Test (Best Model) - Loss: 0.8423 - Accuracy: 0.4493 - F1: 0.3908
sub_17:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.6232 - F1: 0.6121
sub_12:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.2353 - F1: 0.2501
sub_20:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.3088 - F1: 0.2613
sub_16:Test (Best Model) - Loss: 1.4294 - Accuracy: 0.4706 - F1: 0.4457
sub_15:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2941 - F1: 0.2149
sub_14:Test (Best Model) - Loss: 4.5418 - Accuracy: 0.2353 - F1: 0.0976
sub_17:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3188 - F1: 0.2016
sub_18:Test (Best Model) - Loss: 0.8942 - Accuracy: 0.4783 - F1: 0.3995
sub_12:Test (Best Model) - Loss: 1.4218 - Accuracy: 0.4203 - F1: 0.4101
sub_16:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3088 - F1: 0.2159
sub_13:Test (Best Model) - Loss: 2.0612 - Accuracy: 0.3529 - F1: 0.3484
sub_11:Test (Best Model) - Loss: 1.3246 - Accuracy: 0.4493 - F1: 0.3777
sub_19:Test (Best Model) - Loss: 1.1370 - Accuracy: 0.5147 - F1: 0.4916
sub_14:Test (Best Model) - Loss: 4.1683 - Accuracy: 0.2647 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.2791 - Accuracy: 0.3768 - F1: 0.2989
sub_20:Test (Best Model) - Loss: 0.9564 - Accuracy: 0.4853 - F1: 0.3986
sub_12:Test (Best Model) - Loss: 1.5680 - Accuracy: 0.2609 - F1: 0.1920
sub_11:Test (Best Model) - Loss: 1.3170 - Accuracy: 0.4058 - F1: 0.3315
sub_18:Test (Best Model) - Loss: 1.0856 - Accuracy: 0.6087 - F1: 0.5865
sub_20:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.3971 - F1: 0.3059
sub_15:Test (Best Model) - Loss: 1.4745 - Accuracy: 0.3382 - F1: 0.2905
sub_12:Test (Best Model) - Loss: 1.4207 - Accuracy: 0.2899 - F1: 0.1548
sub_16:Test (Best Model) - Loss: 1.3084 - Accuracy: 0.3235 - F1: 0.2418
sub_14:Test (Best Model) - Loss: 1.0405 - Accuracy: 0.3676 - F1: 0.2744
sub_19:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2941 - F1: 0.2519
sub_13:Test (Best Model) - Loss: 1.4788 - Accuracy: 0.4853 - F1: 0.4794
sub_12:Test (Best Model) - Loss: 1.4974 - Accuracy: 0.2899 - F1: 0.2124
sub_14:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3088 - F1: 0.1778
sub_16:Test (Best Model) - Loss: 1.5635 - Accuracy: 0.4118 - F1: 0.3218
sub_18:Test (Best Model) - Loss: 1.6005 - Accuracy: 0.4412 - F1: 0.3379
sub_17:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2754 - F1: 0.1675
sub_12:Test (Best Model) - Loss: 1.7857 - Accuracy: 0.2609 - F1: 0.1125
sub_20:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.5000 - F1: 0.5014
sub_11:Test (Best Model) - Loss: 1.0248 - Accuracy: 0.4638 - F1: 0.4446
sub_14:Test (Best Model) - Loss: 1.0271 - Accuracy: 0.5000 - F1: 0.3852
sub_16:Test (Best Model) - Loss: 1.5707 - Accuracy: 0.3088 - F1: 0.2598
sub_20:Test (Best Model) - Loss: 1.2603 - Accuracy: 0.3971 - F1: 0.3391
sub_18:Test (Best Model) - Loss: 1.1511 - Accuracy: 0.4412 - F1: 0.4382
sub_19:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.5294 - F1: 0.5499
sub_14:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.4265 - F1: 0.2777
sub_13:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.3971 - F1: 0.3563
sub_12:Test (Best Model) - Loss: 1.2426 - Accuracy: 0.3235 - F1: 0.3182
sub_17:Test (Best Model) - Loss: 1.0095 - Accuracy: 0.5652 - F1: 0.5797
sub_15:Test (Best Model) - Loss: 2.3373 - Accuracy: 0.3235 - F1: 0.3475
sub_18:Test (Best Model) - Loss: 0.8253 - Accuracy: 0.5882 - F1: 0.5841
sub_16:Test (Best Model) - Loss: 1.1530 - Accuracy: 0.4706 - F1: 0.4697
sub_20:Test (Best Model) - Loss: 1.0338 - Accuracy: 0.5735 - F1: 0.5805
sub_11:Test (Best Model) - Loss: 1.2562 - Accuracy: 0.3623 - F1: 0.3140
sub_14:Test (Best Model) - Loss: 1.1878 - Accuracy: 0.3971 - F1: 0.3371
sub_12:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.3824 - F1: 0.3970
sub_16:Test (Best Model) - Loss: 1.5776 - Accuracy: 0.2794 - F1: 0.1500
sub_18:Test (Best Model) - Loss: 1.0416 - Accuracy: 0.3971 - F1: 0.2731
sub_19:Test (Best Model) - Loss: 1.2256 - Accuracy: 0.4559 - F1: 0.4819
sub_15:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.3529 - F1: 0.2425
sub_20:Test (Best Model) - Loss: 1.0680 - Accuracy: 0.5735 - F1: 0.5619
sub_11:Test (Best Model) - Loss: 1.1692 - Accuracy: 0.4203 - F1: 0.3605
sub_16:Test (Best Model) - Loss: 1.0475 - Accuracy: 0.4559 - F1: 0.4510
sub_14:Test (Best Model) - Loss: 0.9696 - Accuracy: 0.4706 - F1: 0.3610
sub_17:Test (Best Model) - Loss: 1.1245 - Accuracy: 0.5797 - F1: 0.5796
sub_13:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.4493 - F1: 0.4237
sub_19:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.3088 - F1: 0.2007
sub_12:Test (Best Model) - Loss: 1.0990 - Accuracy: 0.4559 - F1: 0.4646
sub_16:Test (Best Model) - Loss: 1.2807 - Accuracy: 0.5000 - F1: 0.5152
sub_15:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.3382 - F1: 0.2342
sub_11:Test (Best Model) - Loss: 2.1454 - Accuracy: 0.3043 - F1: 0.2111
sub_14:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.2941 - F1: 0.2381
sub_18:Test (Best Model) - Loss: 1.1172 - Accuracy: 0.5147 - F1: 0.4981
sub_12:Test (Best Model) - Loss: 1.1673 - Accuracy: 0.3676 - F1: 0.2878
sub_20:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.4348 - F1: 0.4159
sub_16:Test (Best Model) - Loss: 1.2975 - Accuracy: 0.4118 - F1: 0.3859
sub_13:Test (Best Model) - Loss: 1.7076 - Accuracy: 0.2899 - F1: 0.2429
sub_19:Test (Best Model) - Loss: 1.2278 - Accuracy: 0.4412 - F1: 0.4599
sub_18:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.3824 - F1: 0.2631
sub_16:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.3529 - F1: 0.2789
sub_12:Test (Best Model) - Loss: 1.4990 - Accuracy: 0.4559 - F1: 0.4539
sub_20:Test (Best Model) - Loss: 1.7124 - Accuracy: 0.3768 - F1: 0.3903
sub_14:Test (Best Model) - Loss: 2.2900 - Accuracy: 0.5294 - F1: 0.5254
sub_17:Test (Best Model) - Loss: 1.1804 - Accuracy: 0.5507 - F1: 0.5556
sub_11:Test (Best Model) - Loss: 1.5213 - Accuracy: 0.4638 - F1: 0.4177
sub_16:Test (Best Model) - Loss: 1.2005 - Accuracy: 0.4118 - F1: 0.4020
sub_18:Test (Best Model) - Loss: 1.7201 - Accuracy: 0.3824 - F1: 0.2861
sub_13:Test (Best Model) - Loss: 1.2884 - Accuracy: 0.3768 - F1: 0.3306
sub_15:Test (Best Model) - Loss: 1.5649 - Accuracy: 0.3824 - F1: 0.3427
sub_20:Test (Best Model) - Loss: 1.4867 - Accuracy: 0.3768 - F1: 0.3517
sub_14:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.3529 - F1: 0.2480
sub_13:Test (Best Model) - Loss: 1.6446 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.1710 - Accuracy: 0.3824 - F1: 0.3240
sub_18:Test (Best Model) - Loss: 1.2571 - Accuracy: 0.5147 - F1: 0.4842
sub_19:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.4559 - F1: 0.4345
sub_20:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.3333 - F1: 0.2354
sub_15:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.3235 - F1: 0.2030
sub_17:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.5072 - F1: 0.4602
sub_11:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.3623 - F1: 0.2905
sub_14:Test (Best Model) - Loss: 1.1576 - Accuracy: 0.5294 - F1: 0.5199
sub_20:Test (Best Model) - Loss: 1.5387 - Accuracy: 0.3478 - F1: 0.3177
sub_19:Test (Best Model) - Loss: 1.0992 - Accuracy: 0.5000 - F1: 0.4793
sub_18:Test (Best Model) - Loss: 1.5696 - Accuracy: 0.3382 - F1: 0.2186
sub_13:Test (Best Model) - Loss: 1.2207 - Accuracy: 0.4348 - F1: 0.4114
sub_11:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2899 - F1: 0.2271
sub_15:Test (Best Model) - Loss: 1.2302 - Accuracy: 0.3088 - F1: 0.2281
sub_17:Test (Best Model) - Loss: 1.1245 - Accuracy: 0.4559 - F1: 0.4552
sub_18:Test (Best Model) - Loss: 0.9441 - Accuracy: 0.4853 - F1: 0.4499
sub_13:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.1873 - Accuracy: 0.3824 - F1: 0.4066
sub_11:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.3913 - F1: 0.3497
sub_19:Test (Best Model) - Loss: 1.1706 - Accuracy: 0.4118 - F1: 0.3316
sub_15:Test (Best Model) - Loss: 1.9840 - Accuracy: 0.4265 - F1: 0.3933
sub_17:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.6912 - F1: 0.6915
sub_13:Test (Best Model) - Loss: 1.2535 - Accuracy: 0.3235 - F1: 0.3328
sub_11:Test (Best Model) - Loss: 1.1296 - Accuracy: 0.4203 - F1: 0.3866
sub_15:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2353 - F1: 0.1142
sub_17:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.3676 - F1: 0.2775
sub_19:Test (Best Model) - Loss: 1.1541 - Accuracy: 0.5294 - F1: 0.5456
sub_11:Test (Best Model) - Loss: 0.9460 - Accuracy: 0.5652 - F1: 0.5226
sub_13:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.3088 - F1: 0.3110
sub_15:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.2941 - F1: 0.2634
sub_13:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.2647 - F1: 0.1692
sub_19:Test (Best Model) - Loss: 1.3062 - Accuracy: 0.3235 - F1: 0.2611
sub_17:Test (Best Model) - Loss: 0.8423 - Accuracy: 0.6471 - F1: 0.6492
sub_13:Test (Best Model) - Loss: 1.2579 - Accuracy: 0.2059 - F1: 0.2404
sub_11:Test (Best Model) - Loss: 1.0881 - Accuracy: 0.4493 - F1: 0.3970
sub_17:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.3824 - F1: 0.3156
sub_15:Test (Best Model) - Loss: 1.5619 - Accuracy: 0.4559 - F1: 0.4728
sub_15:Test (Best Model) - Loss: 1.6287 - Accuracy: 0.1618 - F1: 0.1588
sub_25:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3623 - F1: 0.2779
sub_22:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2794 - F1: 0.1801
sub_28:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.2059 - F1: 0.1121
sub_27:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.4638 - F1: 0.3122
sub_23:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.3043 - F1: 0.2410
sub_29:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.3676 - F1: 0.2992
sub_24:Test (Best Model) - Loss: 0.9419 - Accuracy: 0.6471 - F1: 0.6432
sub_21:Test (Best Model) - Loss: 1.1261 - Accuracy: 0.3971 - F1: 0.3950
sub_27:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.3768 - F1: 0.2548
sub_22:Test (Best Model) - Loss: 1.1480 - Accuracy: 0.4412 - F1: 0.4292
sub_23:Test (Best Model) - Loss: 2.5235 - Accuracy: 0.2609 - F1: 0.1718
sub_28:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.1324 - F1: 0.1017
sub_26:Test (Best Model) - Loss: 1.0217 - Accuracy: 0.5507 - F1: 0.5496
sub_21:Test (Best Model) - Loss: 1.1415 - Accuracy: 0.5147 - F1: 0.4217
sub_29:Test (Best Model) - Loss: 1.2295 - Accuracy: 0.3529 - F1: 0.2639
sub_25:Test (Best Model) - Loss: 1.5348 - Accuracy: 0.3333 - F1: 0.2390
sub_28:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3088 - F1: 0.2024
sub_23:Test (Best Model) - Loss: 1.9401 - Accuracy: 0.2754 - F1: 0.1525
sub_22:Test (Best Model) - Loss: 1.1083 - Accuracy: 0.4118 - F1: 0.4142
sub_28:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2353 - F1: 0.1740
sub_25:Test (Best Model) - Loss: 1.2682 - Accuracy: 0.3768 - F1: 0.2784
sub_27:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.6232 - F1: 0.6121
sub_21:Test (Best Model) - Loss: 1.0048 - Accuracy: 0.4118 - F1: 0.3763
sub_29:Test (Best Model) - Loss: 1.3087 - Accuracy: 0.3529 - F1: 0.2768
sub_22:Test (Best Model) - Loss: 1.1604 - Accuracy: 0.3676 - F1: 0.2881
sub_26:Test (Best Model) - Loss: 1.7261 - Accuracy: 0.3913 - F1: 0.3162
sub_24:Test (Best Model) - Loss: 1.1673 - Accuracy: 0.5294 - F1: 0.5230
sub_25:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.2899 - F1: 0.1814
sub_23:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.4348 - F1: 0.3936
sub_27:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3188 - F1: 0.2016
sub_21:Test (Best Model) - Loss: 1.2691 - Accuracy: 0.3529 - F1: 0.2279
sub_28:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.3971 - F1: 0.2799
sub_25:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2754 - F1: 0.1874
sub_27:Test (Best Model) - Loss: 1.2791 - Accuracy: 0.3768 - F1: 0.2989
sub_26:Test (Best Model) - Loss: 1.5021 - Accuracy: 0.3478 - F1: 0.2473
sub_29:Test (Best Model) - Loss: 1.1438 - Accuracy: 0.3971 - F1: 0.3612
sub_22:Test (Best Model) - Loss: 1.0051 - Accuracy: 0.5000 - F1: 0.4706
sub_23:Test (Best Model) - Loss: 2.0186 - Accuracy: 0.2609 - F1: 0.1098
sub_25:Test (Best Model) - Loss: 1.5544 - Accuracy: 0.2647 - F1: 0.1304
sub_28:Test (Best Model) - Loss: 2.2092 - Accuracy: 0.2647 - F1: 0.1508
sub_24:Test (Best Model) - Loss: 1.0731 - Accuracy: 0.5588 - F1: 0.5714
sub_21:Test (Best Model) - Loss: 1.0611 - Accuracy: 0.5000 - F1: 0.4328
sub_26:Test (Best Model) - Loss: 1.5158 - Accuracy: 0.2754 - F1: 0.1325
sub_22:Test (Best Model) - Loss: 1.7184 - Accuracy: 0.3043 - F1: 0.1848
sub_27:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2754 - F1: 0.1675
sub_29:Test (Best Model) - Loss: 1.0193 - Accuracy: 0.4853 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 1.4592 - Accuracy: 0.2941 - F1: 0.1954
sub_23:Test (Best Model) - Loss: 2.5302 - Accuracy: 0.2206 - F1: 0.1871
sub_25:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.3824 - F1: 0.2925
sub_22:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2609 - F1: 0.1034
sub_24:Test (Best Model) - Loss: 0.9239 - Accuracy: 0.6618 - F1: 0.6610
sub_26:Test (Best Model) - Loss: 1.1398 - Accuracy: 0.3478 - F1: 0.2364
sub_21:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.3971 - F1: 0.3206
sub_29:Test (Best Model) - Loss: 1.3020 - Accuracy: 0.3824 - F1: 0.3158
sub_24:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.3088 - F1: 0.2132
sub_22:Test (Best Model) - Loss: 1.2353 - Accuracy: 0.3623 - F1: 0.2716
sub_27:Test (Best Model) - Loss: 1.0095 - Accuracy: 0.5652 - F1: 0.5797
sub_25:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2647 - F1: 0.1446
sub_23:Test (Best Model) - Loss: 2.4080 - Accuracy: 0.3088 - F1: 0.1809
sub_21:Test (Best Model) - Loss: 0.9615 - Accuracy: 0.4706 - F1: 0.3739
sub_28:Test (Best Model) - Loss: 1.8976 - Accuracy: 0.2500 - F1: 0.2511
sub_29:Test (Best Model) - Loss: 1.1003 - Accuracy: 0.5588 - F1: 0.5380
sub_26:Test (Best Model) - Loss: 3.1166 - Accuracy: 0.5294 - F1: 0.4822
sub_22:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.5362 - F1: 0.5146
sub_27:Test (Best Model) - Loss: 1.1245 - Accuracy: 0.5797 - F1: 0.5796
sub_24:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.4706 - F1: 0.4924
sub_25:Test (Best Model) - Loss: 1.1502 - Accuracy: 0.4559 - F1: 0.4169
sub_21:Test (Best Model) - Loss: 1.1385 - Accuracy: 0.3971 - F1: 0.3317
sub_28:Test (Best Model) - Loss: 1.7501 - Accuracy: 0.1618 - F1: 0.1411
sub_23:Test (Best Model) - Loss: 3.2821 - Accuracy: 0.4265 - F1: 0.3172
sub_26:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.4265 - F1: 0.2969
sub_22:Test (Best Model) - Loss: 1.2925 - Accuracy: 0.3623 - F1: 0.2872
sub_21:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.3676 - F1: 0.2911
sub_25:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3382 - F1: 0.2389
sub_29:Test (Best Model) - Loss: 1.5293 - Accuracy: 0.4853 - F1: 0.4893
sub_24:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.4412 - F1: 0.4227
sub_23:Test (Best Model) - Loss: 2.1468 - Accuracy: 0.3824 - F1: 0.2757
sub_29:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.4265 - F1: 0.3661
sub_28:Test (Best Model) - Loss: 2.7588 - Accuracy: 0.3382 - F1: 0.2500
sub_27:Test (Best Model) - Loss: 1.1804 - Accuracy: 0.5507 - F1: 0.5556
sub_26:Test (Best Model) - Loss: 1.2066 - Accuracy: 0.4412 - F1: 0.3019
sub_22:Test (Best Model) - Loss: 1.1740 - Accuracy: 0.5294 - F1: 0.5076
sub_21:Test (Best Model) - Loss: 1.1051 - Accuracy: 0.4118 - F1: 0.3340
sub_25:Test (Best Model) - Loss: 1.2655 - Accuracy: 0.3971 - F1: 0.3258
sub_23:Test (Best Model) - Loss: 1.4886 - Accuracy: 0.2794 - F1: 0.2272
sub_29:Test (Best Model) - Loss: 0.8397 - Accuracy: 0.6176 - F1: 0.6173
sub_24:Test (Best Model) - Loss: 1.6222 - Accuracy: 0.5588 - F1: 0.5858
sub_25:Test (Best Model) - Loss: 1.4223 - Accuracy: 0.3235 - F1: 0.2484
sub_26:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3971 - F1: 0.2752
sub_27:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.5072 - F1: 0.4602
sub_25:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.3088 - F1: 0.2845
sub_22:Test (Best Model) - Loss: 1.2702 - Accuracy: 0.4853 - F1: 0.4815
sub_21:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3676 - F1: 0.2314
sub_28:Test (Best Model) - Loss: 2.0868 - Accuracy: 0.3235 - F1: 0.3301
sub_23:Test (Best Model) - Loss: 2.1776 - Accuracy: 0.2609 - F1: 0.2137
sub_29:Test (Best Model) - Loss: 0.9533 - Accuracy: 0.5072 - F1: 0.4749
sub_28:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2647 - F1: 0.1581
sub_24:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.6324 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 1.4922 - Accuracy: 0.2941 - F1: 0.1788
sub_26:Test (Best Model) - Loss: 1.8710 - Accuracy: 0.5000 - F1: 0.3873
sub_27:Test (Best Model) - Loss: 1.1245 - Accuracy: 0.4559 - F1: 0.4552
sub_22:Test (Best Model) - Loss: 1.3041 - Accuracy: 0.3971 - F1: 0.4153
sub_29:Test (Best Model) - Loss: 1.0625 - Accuracy: 0.4493 - F1: 0.3913
sub_28:Test (Best Model) - Loss: 1.4321 - Accuracy: 0.4412 - F1: 0.4256
sub_24:Test (Best Model) - Loss: 1.1012 - Accuracy: 0.6324 - F1: 0.6303
sub_22:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3529 - F1: 0.3072
sub_23:Test (Best Model) - Loss: 1.7078 - Accuracy: 0.4638 - F1: 0.3762
sub_28:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.3088 - F1: 0.2338
sub_25:Test (Best Model) - Loss: 1.9031 - Accuracy: 0.2353 - F1: 0.1942
sub_21:Test (Best Model) - Loss: 1.0945 - Accuracy: 0.4853 - F1: 0.4864
sub_27:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.6912 - F1: 0.6915
sub_26:Test (Best Model) - Loss: 1.5118 - Accuracy: 0.5441 - F1: 0.5314
sub_27:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.3676 - F1: 0.2775
sub_21:Test (Best Model) - Loss: 1.2384 - Accuracy: 0.3824 - F1: 0.2972
sub_22:Test (Best Model) - Loss: 0.9757 - Accuracy: 0.4118 - F1: 0.3976
sub_29:Test (Best Model) - Loss: 0.9353 - Accuracy: 0.5217 - F1: 0.5089
sub_23:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.2609 - F1: 0.1808
sub_28:Test (Best Model) - Loss: 1.5897 - Accuracy: 0.3529 - F1: 0.3309
sub_24:Test (Best Model) - Loss: 1.0325 - Accuracy: 0.5294 - F1: 0.5464
sub_26:Test (Best Model) - Loss: 1.1522 - Accuracy: 0.5735 - F1: 0.5872
sub_21:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.3235 - F1: 0.2222
sub_24:Test (Best Model) - Loss: 1.1236 - Accuracy: 0.5588 - F1: 0.4680
sub_26:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.4118 - F1: 0.2944
sub_29:Test (Best Model) - Loss: 1.0001 - Accuracy: 0.4493 - F1: 0.4071
sub_26:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3824 - F1: 0.3067
sub_23:Test (Best Model) - Loss: 1.6978 - Accuracy: 0.4638 - F1: 0.4028
sub_24:Test (Best Model) - Loss: 1.0457 - Accuracy: 0.5147 - F1: 0.4860
sub_27:Test (Best Model) - Loss: 0.8423 - Accuracy: 0.6471 - F1: 0.6492
sub_21:Test (Best Model) - Loss: 2.0013 - Accuracy: 0.3529 - F1: 0.3843
sub_29:Test (Best Model) - Loss: 1.0067 - Accuracy: 0.5072 - F1: 0.4468
sub_24:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.4118 - F1: 0.3031
sub_23:Test (Best Model) - Loss: 1.7345 - Accuracy: 0.2899 - F1: 0.1598
sub_26:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.4559 - F1: 0.4688
sub_27:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.3824 - F1: 0.3156
sub_24:Test (Best Model) - Loss: 0.9878 - Accuracy: 0.6618 - F1: 0.6729

=== Summary Results ===

acc: 41.40 ± 6.99
F1: 35.88 ± 8.33
acc-in: 51.28 ± 7.39
F1-in: 43.72 ± 9.13
runing time: 1077.59 seconds
