lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.2468 - Accuracy: 0.3824 - F1: 0.4216
sub_1:Test (Best Model) - Loss: 1.2563 - Accuracy: 0.4412 - F1: 0.4790
sub_1:Test (Best Model) - Loss: 1.2439 - Accuracy: 0.4118 - F1: 0.4453
sub_1:Test (Best Model) - Loss: 1.1856 - Accuracy: 0.4118 - F1: 0.4447
sub_1:Test (Best Model) - Loss: 1.2397 - Accuracy: 0.4412 - F1: 0.4715
sub_1:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.3623 - F1: 0.3583
sub_1:Test (Best Model) - Loss: 1.2790 - Accuracy: 0.3188 - F1: 0.3217
sub_1:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.4348 - F1: 0.4297
sub_1:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.4058 - F1: 0.4073
sub_1:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.3478 - F1: 0.3583
sub_1:Test (Best Model) - Loss: 1.1463 - Accuracy: 0.4559 - F1: 0.4370
sub_1:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.5588 - F1: 0.5731
sub_1:Test (Best Model) - Loss: 1.1734 - Accuracy: 0.5441 - F1: 0.5601
sub_1:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.4853 - F1: 0.4787
sub_1:Test (Best Model) - Loss: 1.1101 - Accuracy: 0.5000 - F1: 0.4852
sub_2:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.2754 - F1: 0.2959
sub_2:Test (Best Model) - Loss: 1.4159 - Accuracy: 0.2754 - F1: 0.3021
sub_2:Test (Best Model) - Loss: 1.4108 - Accuracy: 0.2899 - F1: 0.3074
sub_2:Test (Best Model) - Loss: 1.4673 - Accuracy: 0.2174 - F1: 0.2401
sub_2:Test (Best Model) - Loss: 1.4904 - Accuracy: 0.2754 - F1: 0.2971
sub_2:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.2794 - F1: 0.2985
sub_2:Test (Best Model) - Loss: 1.4038 - Accuracy: 0.2647 - F1: 0.2740
sub_2:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3529 - F1: 0.3764
sub_2:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.3529 - F1: 0.3792
sub_2:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.2941 - F1: 0.3331
sub_2:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.3768 - F1: 0.3639
sub_2:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3623 - F1: 0.3554
sub_2:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3913 - F1: 0.3765
sub_2:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.3623 - F1: 0.3361
sub_2:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3623 - F1: 0.3803
sub_3:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.3235 - F1: 0.3319
sub_3:Test (Best Model) - Loss: 1.3486 - Accuracy: 0.2794 - F1: 0.2766
sub_3:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2500 - F1: 0.2592
sub_3:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2941 - F1: 0.2931
sub_3:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3235 - F1: 0.3275
sub_3:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.3913 - F1: 0.3672
sub_3:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.2754 - F1: 0.2593
sub_3:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2899 - F1: 0.2864
sub_3:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.3913 - F1: 0.3789
sub_3:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.3188 - F1: 0.3104
sub_3:Test (Best Model) - Loss: 1.4823 - Accuracy: 0.2754 - F1: 0.2584
sub_3:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.3043 - F1: 0.2912
sub_3:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.3043 - F1: 0.2807
sub_3:Test (Best Model) - Loss: 1.4077 - Accuracy: 0.3043 - F1: 0.2798
sub_3:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.3043 - F1: 0.2818
sub_4:Test (Best Model) - Loss: 1.1159 - Accuracy: 0.4638 - F1: 0.4888
sub_4:Test (Best Model) - Loss: 1.0569 - Accuracy: 0.5072 - F1: 0.5362
sub_4:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.4928 - F1: 0.5143
sub_4:Test (Best Model) - Loss: 1.0803 - Accuracy: 0.5942 - F1: 0.6058
sub_4:Test (Best Model) - Loss: 1.1203 - Accuracy: 0.5072 - F1: 0.5198
sub_4:Test (Best Model) - Loss: 1.0706 - Accuracy: 0.5072 - F1: 0.5250
sub_4:Test (Best Model) - Loss: 1.1319 - Accuracy: 0.5652 - F1: 0.5893
sub_4:Test (Best Model) - Loss: 1.0790 - Accuracy: 0.5797 - F1: 0.6000
sub_4:Test (Best Model) - Loss: 1.0919 - Accuracy: 0.5217 - F1: 0.5233
sub_4:Test (Best Model) - Loss: 1.1193 - Accuracy: 0.4928 - F1: 0.5213
sub_4:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.4058 - F1: 0.3908
sub_4:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.4348 - F1: 0.4500
sub_4:Test (Best Model) - Loss: 1.1192 - Accuracy: 0.4203 - F1: 0.4379
sub_4:Test (Best Model) - Loss: 1.1060 - Accuracy: 0.4203 - F1: 0.4249
sub_4:Test (Best Model) - Loss: 1.1303 - Accuracy: 0.5072 - F1: 0.5039
sub_5:Test (Best Model) - Loss: 1.4663 - Accuracy: 0.4412 - F1: 0.4099
sub_5:Test (Best Model) - Loss: 1.4096 - Accuracy: 0.4559 - F1: 0.4099
sub_5:Test (Best Model) - Loss: 1.4717 - Accuracy: 0.4559 - F1: 0.4503
sub_5:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.4559 - F1: 0.4387
sub_5:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.3971 - F1: 0.3821
sub_5:Test (Best Model) - Loss: 1.1727 - Accuracy: 0.4412 - F1: 0.4140
sub_5:Test (Best Model) - Loss: 1.0897 - Accuracy: 0.4853 - F1: 0.4877
sub_5:Test (Best Model) - Loss: 1.1198 - Accuracy: 0.4265 - F1: 0.4424
sub_5:Test (Best Model) - Loss: 1.0952 - Accuracy: 0.5000 - F1: 0.4699
sub_5:Test (Best Model) - Loss: 1.1485 - Accuracy: 0.4559 - F1: 0.4377
sub_5:Test (Best Model) - Loss: 1.1573 - Accuracy: 0.4265 - F1: 0.4280
sub_5:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.3824 - F1: 0.3718
sub_5:Test (Best Model) - Loss: 1.2156 - Accuracy: 0.3676 - F1: 0.3759
sub_5:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.3824 - F1: 0.3966
sub_5:Test (Best Model) - Loss: 1.1362 - Accuracy: 0.3971 - F1: 0.3789
sub_6:Test (Best Model) - Loss: 1.1944 - Accuracy: 0.5000 - F1: 0.5143
sub_6:Test (Best Model) - Loss: 1.1492 - Accuracy: 0.5000 - F1: 0.5080
sub_6:Test (Best Model) - Loss: 1.1866 - Accuracy: 0.4265 - F1: 0.4160
sub_6:Test (Best Model) - Loss: 1.1756 - Accuracy: 0.3971 - F1: 0.3967
sub_6:Test (Best Model) - Loss: 1.2136 - Accuracy: 0.4706 - F1: 0.4935
sub_6:Test (Best Model) - Loss: 1.2754 - Accuracy: 0.4203 - F1: 0.3578
sub_6:Test (Best Model) - Loss: 1.2611 - Accuracy: 0.4203 - F1: 0.3414
sub_6:Test (Best Model) - Loss: 1.2512 - Accuracy: 0.4348 - F1: 0.3661
sub_6:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.4203 - F1: 0.3677
sub_6:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.3623 - F1: 0.3013
sub_6:Test (Best Model) - Loss: 1.2826 - Accuracy: 0.3188 - F1: 0.3455
sub_6:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.3623 - F1: 0.3692
sub_6:Test (Best Model) - Loss: 1.3327 - Accuracy: 0.3913 - F1: 0.4207
sub_6:Test (Best Model) - Loss: 1.2341 - Accuracy: 0.4493 - F1: 0.4865
sub_6:Test (Best Model) - Loss: 1.2326 - Accuracy: 0.5072 - F1: 0.5241
sub_7:Test (Best Model) - Loss: 1.1432 - Accuracy: 0.5882 - F1: 0.5841
sub_7:Test (Best Model) - Loss: 0.9706 - Accuracy: 0.5735 - F1: 0.5488
sub_7:Test (Best Model) - Loss: 1.1905 - Accuracy: 0.4118 - F1: 0.3907
sub_7:Test (Best Model) - Loss: 1.1160 - Accuracy: 0.5882 - F1: 0.5831
sub_7:Test (Best Model) - Loss: 1.1504 - Accuracy: 0.5147 - F1: 0.4918
sub_7:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.3971 - F1: 0.3719
sub_7:Test (Best Model) - Loss: 1.2604 - Accuracy: 0.3971 - F1: 0.3923
sub_7:Test (Best Model) - Loss: 1.2553 - Accuracy: 0.4412 - F1: 0.4477
sub_7:Test (Best Model) - Loss: 1.2285 - Accuracy: 0.4559 - F1: 0.4331
sub_7:Test (Best Model) - Loss: 1.1424 - Accuracy: 0.5000 - F1: 0.4826
sub_7:Test (Best Model) - Loss: 1.2089 - Accuracy: 0.5147 - F1: 0.5238
sub_7:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.5000 - F1: 0.5029
sub_7:Test (Best Model) - Loss: 1.2483 - Accuracy: 0.5441 - F1: 0.5400
sub_7:Test (Best Model) - Loss: 1.1839 - Accuracy: 0.4706 - F1: 0.4761
sub_7:Test (Best Model) - Loss: 1.2697 - Accuracy: 0.4265 - F1: 0.4347
sub_8:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.2647 - F1: 0.2704
sub_8:Test (Best Model) - Loss: 1.4703 - Accuracy: 0.2794 - F1: 0.2843
sub_8:Test (Best Model) - Loss: 1.4407 - Accuracy: 0.2206 - F1: 0.2443
sub_8:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.2941 - F1: 0.2880
sub_8:Test (Best Model) - Loss: 1.4254 - Accuracy: 0.3235 - F1: 0.3227
sub_8:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.3382 - F1: 0.3512
sub_8:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2647 - F1: 0.2628
sub_8:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.3824 - F1: 0.3928
sub_8:Test (Best Model) - Loss: 1.4134 - Accuracy: 0.2353 - F1: 0.2288
sub_8:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3088 - F1: 0.3150
sub_8:Test (Best Model) - Loss: 1.4485 - Accuracy: 0.3088 - F1: 0.2946
sub_8:Test (Best Model) - Loss: 1.4423 - Accuracy: 0.3235 - F1: 0.3490
sub_8:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.4412 - F1: 0.4475
sub_8:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.4412 - F1: 0.4638
sub_8:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.3088 - F1: 0.3060
sub_9:Test (Best Model) - Loss: 1.1020 - Accuracy: 0.5882 - F1: 0.6037
sub_9:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.4412 - F1: 0.4646
sub_9:Test (Best Model) - Loss: 1.1016 - Accuracy: 0.4706 - F1: 0.5019
sub_9:Test (Best Model) - Loss: 1.0624 - Accuracy: 0.5294 - F1: 0.5557
sub_9:Test (Best Model) - Loss: 1.0777 - Accuracy: 0.5735 - F1: 0.5886
sub_9:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3529 - F1: 0.3828
sub_9:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.3529 - F1: 0.3839
sub_9:Test (Best Model) - Loss: 1.2708 - Accuracy: 0.3529 - F1: 0.3711
sub_9:Test (Best Model) - Loss: 1.2492 - Accuracy: 0.4265 - F1: 0.4419
sub_9:Test (Best Model) - Loss: 1.2938 - Accuracy: 0.3235 - F1: 0.3641
sub_9:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.3824 - F1: 0.4112
sub_9:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3824 - F1: 0.3884
sub_9:Test (Best Model) - Loss: 1.2581 - Accuracy: 0.3676 - F1: 0.4009
sub_9:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.3971 - F1: 0.4273
sub_9:Test (Best Model) - Loss: 1.2951 - Accuracy: 0.3971 - F1: 0.4164
sub_10:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.3235 - F1: 0.3068
sub_10:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.4118 - F1: 0.3668
sub_10:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2941 - F1: 0.3058
sub_10:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3824 - F1: 0.3908
sub_10:Test (Best Model) - Loss: 1.4190 - Accuracy: 0.3235 - F1: 0.3233
sub_10:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.2941 - F1: 0.2607
sub_10:Test (Best Model) - Loss: 1.4203 - Accuracy: 0.2206 - F1: 0.2023
sub_10:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.2941 - F1: 0.2952
sub_10:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2941 - F1: 0.2947
sub_10:Test (Best Model) - Loss: 1.4367 - Accuracy: 0.2500 - F1: 0.2455
sub_10:Test (Best Model) - Loss: 1.4888 - Accuracy: 0.2609 - F1: 0.2631
sub_10:Test (Best Model) - Loss: 1.4425 - Accuracy: 0.2464 - F1: 0.2581
sub_10:Test (Best Model) - Loss: 1.4115 - Accuracy: 0.2609 - F1: 0.2520
sub_10:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.3333 - F1: 0.3279
sub_10:Test (Best Model) - Loss: 1.4514 - Accuracy: 0.2754 - F1: 0.2703
sub_11:Test (Best Model) - Loss: 1.4005 - Accuracy: 0.3333 - F1: 0.3123
sub_11:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3623 - F1: 0.3463
sub_11:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3333 - F1: 0.3404
sub_11:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2899 - F1: 0.2870
sub_11:Test (Best Model) - Loss: 1.4170 - Accuracy: 0.3043 - F1: 0.3009
sub_11:Test (Best Model) - Loss: 1.3336 - Accuracy: 0.4638 - F1: 0.4135
sub_11:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.4348 - F1: 0.4243
sub_11:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.4493 - F1: 0.4382
sub_11:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.4348 - F1: 0.3986
sub_11:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.3478 - F1: 0.3089
sub_11:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.3478 - F1: 0.3152
sub_11:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3188 - F1: 0.2874
sub_11:Test (Best Model) - Loss: 1.2515 - Accuracy: 0.4638 - F1: 0.4276
sub_11:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3478 - F1: 0.3378
sub_11:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.3623 - F1: 0.3321
sub_12:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.4118 - F1: 0.3843
sub_12:Test (Best Model) - Loss: 1.0974 - Accuracy: 0.5735 - F1: 0.5737
sub_12:Test (Best Model) - Loss: 1.0702 - Accuracy: 0.5588 - F1: 0.5298
sub_12:Test (Best Model) - Loss: 1.1374 - Accuracy: 0.5441 - F1: 0.5654
sub_12:Test (Best Model) - Loss: 1.0968 - Accuracy: 0.4559 - F1: 0.4594
sub_12:Test (Best Model) - Loss: 1.2378 - Accuracy: 0.4203 - F1: 0.4426
sub_12:Test (Best Model) - Loss: 1.1635 - Accuracy: 0.4493 - F1: 0.4577
sub_12:Test (Best Model) - Loss: 1.1213 - Accuracy: 0.4348 - F1: 0.4407
sub_12:Test (Best Model) - Loss: 1.1800 - Accuracy: 0.4348 - F1: 0.4353
sub_12:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.4493 - F1: 0.4431
sub_12:Test (Best Model) - Loss: 1.2115 - Accuracy: 0.4706 - F1: 0.4663
sub_12:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.4118 - F1: 0.4084
sub_12:Test (Best Model) - Loss: 1.2122 - Accuracy: 0.4118 - F1: 0.4205
sub_12:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.4412 - F1: 0.4494
sub_12:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.4853 - F1: 0.5079
sub_13:Test (Best Model) - Loss: 1.3190 - Accuracy: 0.3676 - F1: 0.3890
sub_13:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.3382 - F1: 0.3357
sub_13:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.3971 - F1: 0.4152
sub_13:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.3382 - F1: 0.3645
sub_13:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3529 - F1: 0.3711
sub_13:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3043 - F1: 0.2991
sub_13:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.3188 - F1: 0.3117
sub_13:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3333 - F1: 0.3269
sub_13:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.3478 - F1: 0.3577
sub_13:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.3768 - F1: 0.3738
sub_13:Test (Best Model) - Loss: 1.3507 - Accuracy: 0.4118 - F1: 0.4160
sub_13:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3235 - F1: 0.3319
sub_13:Test (Best Model) - Loss: 1.4081 - Accuracy: 0.3088 - F1: 0.3289
sub_13:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.3382 - F1: 0.3436
sub_13:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.3382 - F1: 0.3559
sub_14:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.2941 - F1: 0.3281
sub_14:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3382 - F1: 0.3699
sub_14:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2941 - F1: 0.3170
sub_14:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2059 - F1: 0.2364
sub_14:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3676 - F1: 0.3934
sub_14:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3971 - F1: 0.3819
sub_14:Test (Best Model) - Loss: 1.4121 - Accuracy: 0.3676 - F1: 0.3623
sub_14:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3382 - F1: 0.3287
sub_14:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.3971 - F1: 0.3978
sub_14:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.3088 - F1: 0.3005
sub_14:Test (Best Model) - Loss: 1.3185 - Accuracy: 0.3235 - F1: 0.3209
sub_14:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.3529 - F1: 0.3076
sub_14:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3824 - F1: 0.3819
sub_14:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.3676 - F1: 0.3638
sub_14:Test (Best Model) - Loss: 1.2871 - Accuracy: 0.3088 - F1: 0.3081
sub_15:Test (Best Model) - Loss: 1.2501 - Accuracy: 0.4118 - F1: 0.4253
sub_15:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3676 - F1: 0.3834
sub_15:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.3676 - F1: 0.3909
sub_15:Test (Best Model) - Loss: 1.1851 - Accuracy: 0.3824 - F1: 0.4202
sub_15:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.4412 - F1: 0.4675
sub_15:Test (Best Model) - Loss: 1.0523 - Accuracy: 0.5588 - F1: 0.5582
sub_15:Test (Best Model) - Loss: 1.2138 - Accuracy: 0.5147 - F1: 0.5285
sub_15:Test (Best Model) - Loss: 1.1085 - Accuracy: 0.6029 - F1: 0.6066
sub_15:Test (Best Model) - Loss: 1.0754 - Accuracy: 0.5588 - F1: 0.5687
sub_15:Test (Best Model) - Loss: 1.0917 - Accuracy: 0.5147 - F1: 0.5208
sub_15:Test (Best Model) - Loss: 1.1708 - Accuracy: 0.4559 - F1: 0.4495
sub_15:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.5147 - F1: 0.5226
sub_15:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.4559 - F1: 0.4647
sub_15:Test (Best Model) - Loss: 1.1735 - Accuracy: 0.4412 - F1: 0.4438
sub_15:Test (Best Model) - Loss: 1.2308 - Accuracy: 0.4265 - F1: 0.4328
sub_16:Test (Best Model) - Loss: 1.1922 - Accuracy: 0.4706 - F1: 0.3752
sub_16:Test (Best Model) - Loss: 1.2079 - Accuracy: 0.4853 - F1: 0.4654
sub_16:Test (Best Model) - Loss: 1.2001 - Accuracy: 0.5441 - F1: 0.5107
sub_16:Test (Best Model) - Loss: 1.1937 - Accuracy: 0.5000 - F1: 0.4700
sub_16:Test (Best Model) - Loss: 1.1743 - Accuracy: 0.5294 - F1: 0.4859
sub_16:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.3529 - F1: 0.3228
sub_16:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.3235 - F1: 0.2979
sub_16:Test (Best Model) - Loss: 1.2886 - Accuracy: 0.4412 - F1: 0.4320
sub_16:Test (Best Model) - Loss: 1.2289 - Accuracy: 0.4265 - F1: 0.3918
sub_16:Test (Best Model) - Loss: 1.4677 - Accuracy: 0.3824 - F1: 0.3786
sub_16:Test (Best Model) - Loss: 1.1941 - Accuracy: 0.4559 - F1: 0.4007
sub_16:Test (Best Model) - Loss: 1.1372 - Accuracy: 0.5294 - F1: 0.4824
sub_16:Test (Best Model) - Loss: 1.2337 - Accuracy: 0.4706 - F1: 0.4354
sub_16:Test (Best Model) - Loss: 1.1925 - Accuracy: 0.4853 - F1: 0.4581
sub_16:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.4853 - F1: 0.4142
sub_17:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.5072 - F1: 0.4811
sub_17:Test (Best Model) - Loss: 1.2342 - Accuracy: 0.3768 - F1: 0.3388
sub_17:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4203 - F1: 0.4079
sub_17:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.4493 - F1: 0.4531
sub_17:Test (Best Model) - Loss: 1.2359 - Accuracy: 0.4493 - F1: 0.4463
sub_17:Test (Best Model) - Loss: 1.4289 - Accuracy: 0.3333 - F1: 0.2829
sub_17:Test (Best Model) - Loss: 1.4464 - Accuracy: 0.3188 - F1: 0.2704
sub_17:Test (Best Model) - Loss: 1.4486 - Accuracy: 0.4203 - F1: 0.3665
sub_17:Test (Best Model) - Loss: 1.4216 - Accuracy: 0.4203 - F1: 0.3790
sub_17:Test (Best Model) - Loss: 1.4247 - Accuracy: 0.3913 - F1: 0.3418
sub_17:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4265 - F1: 0.4094
sub_17:Test (Best Model) - Loss: 1.2181 - Accuracy: 0.4265 - F1: 0.4227
sub_17:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.3971 - F1: 0.3967
sub_17:Test (Best Model) - Loss: 1.2790 - Accuracy: 0.4265 - F1: 0.4359
sub_17:Test (Best Model) - Loss: 1.2658 - Accuracy: 0.3824 - F1: 0.3781
sub_18:Test (Best Model) - Loss: 1.2519 - Accuracy: 0.4058 - F1: 0.4181
sub_18:Test (Best Model) - Loss: 1.2718 - Accuracy: 0.3478 - F1: 0.3701
sub_18:Test (Best Model) - Loss: 1.2446 - Accuracy: 0.3623 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 1.2631 - Accuracy: 0.4348 - F1: 0.4368
sub_18:Test (Best Model) - Loss: 1.2260 - Accuracy: 0.4638 - F1: 0.4748
sub_18:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.3235 - F1: 0.3555
sub_18:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3529 - F1: 0.3761
sub_18:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3529 - F1: 0.3782
sub_18:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.3382 - F1: 0.3635
sub_18:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3235 - F1: 0.3638
sub_18:Test (Best Model) - Loss: 1.2648 - Accuracy: 0.3971 - F1: 0.4116
sub_18:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3088 - F1: 0.3220
sub_18:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.3529 - F1: 0.3547
sub_18:Test (Best Model) - Loss: 1.2501 - Accuracy: 0.3824 - F1: 0.4031
sub_18:Test (Best Model) - Loss: 1.2709 - Accuracy: 0.4118 - F1: 0.4329
sub_19:Test (Best Model) - Loss: 1.4807 - Accuracy: 0.3529 - F1: 0.3311
sub_19:Test (Best Model) - Loss: 1.4720 - Accuracy: 0.2500 - F1: 0.2713
sub_19:Test (Best Model) - Loss: 1.4301 - Accuracy: 0.2794 - F1: 0.2534
sub_19:Test (Best Model) - Loss: 1.3945 - Accuracy: 0.3088 - F1: 0.2982
sub_19:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.3235 - F1: 0.2979
sub_19:Test (Best Model) - Loss: 1.2925 - Accuracy: 0.3824 - F1: 0.3700
sub_19:Test (Best Model) - Loss: 1.3011 - Accuracy: 0.4265 - F1: 0.3815
sub_19:Test (Best Model) - Loss: 1.2728 - Accuracy: 0.5000 - F1: 0.5183
sub_19:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.4706 - F1: 0.4743
sub_19:Test (Best Model) - Loss: 1.2949 - Accuracy: 0.3971 - F1: 0.3863
sub_19:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.3676 - F1: 0.3560
sub_19:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.2941 - F1: 0.2872
sub_19:Test (Best Model) - Loss: 1.2740 - Accuracy: 0.3529 - F1: 0.3305
sub_19:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.3676 - F1: 0.3855
sub_19:Test (Best Model) - Loss: 1.2969 - Accuracy: 0.3676 - F1: 0.3788
sub_20:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.4706 - F1: 0.4902
sub_20:Test (Best Model) - Loss: 1.1696 - Accuracy: 0.5294 - F1: 0.5492
sub_20:Test (Best Model) - Loss: 1.2022 - Accuracy: 0.5000 - F1: 0.5193
sub_20:Test (Best Model) - Loss: 1.1998 - Accuracy: 0.4559 - F1: 0.4659
sub_20:Test (Best Model) - Loss: 1.2068 - Accuracy: 0.5294 - F1: 0.5453
sub_20:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.3971 - F1: 0.3880
sub_20:Test (Best Model) - Loss: 1.2131 - Accuracy: 0.4706 - F1: 0.4892
sub_20:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.4853 - F1: 0.4955
sub_20:Test (Best Model) - Loss: 1.2668 - Accuracy: 0.3824 - F1: 0.3826
sub_20:Test (Best Model) - Loss: 1.2400 - Accuracy: 0.4559 - F1: 0.4717
sub_20:Test (Best Model) - Loss: 1.2018 - Accuracy: 0.3913 - F1: 0.4070
sub_20:Test (Best Model) - Loss: 1.2503 - Accuracy: 0.4348 - F1: 0.4323
sub_20:Test (Best Model) - Loss: 1.2873 - Accuracy: 0.3478 - F1: 0.3656
sub_20:Test (Best Model) - Loss: 1.2244 - Accuracy: 0.4493 - F1: 0.4626
sub_20:Test (Best Model) - Loss: 1.1679 - Accuracy: 0.4348 - F1: 0.4596
sub_21:Test (Best Model) - Loss: 1.1670 - Accuracy: 0.4706 - F1: 0.4500
sub_21:Test (Best Model) - Loss: 1.2002 - Accuracy: 0.3529 - F1: 0.3221
sub_21:Test (Best Model) - Loss: 1.2478 - Accuracy: 0.4118 - F1: 0.3879
sub_21:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.4118 - F1: 0.3817
sub_21:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3676 - F1: 0.3507
sub_21:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.3235 - F1: 0.3017
sub_21:Test (Best Model) - Loss: 1.1984 - Accuracy: 0.3824 - F1: 0.3703
sub_21:Test (Best Model) - Loss: 1.1793 - Accuracy: 0.4265 - F1: 0.3942
sub_21:Test (Best Model) - Loss: 1.1968 - Accuracy: 0.4412 - F1: 0.4252
sub_21:Test (Best Model) - Loss: 1.1623 - Accuracy: 0.4265 - F1: 0.4139
sub_21:Test (Best Model) - Loss: 1.2159 - Accuracy: 0.3529 - F1: 0.3406
sub_21:Test (Best Model) - Loss: 1.2531 - Accuracy: 0.3529 - F1: 0.3154
sub_21:Test (Best Model) - Loss: 1.2218 - Accuracy: 0.3529 - F1: 0.2985
sub_21:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.4412 - F1: 0.4184
sub_21:Test (Best Model) - Loss: 1.1966 - Accuracy: 0.4412 - F1: 0.4113
sub_22:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3529 - F1: 0.3913
sub_22:Test (Best Model) - Loss: 1.3391 - Accuracy: 0.4265 - F1: 0.4298
sub_22:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.3382 - F1: 0.3480
sub_22:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.3676 - F1: 0.4004
sub_22:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.3529 - F1: 0.3943
sub_22:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.3768 - F1: 0.3684
sub_22:Test (Best Model) - Loss: 1.2645 - Accuracy: 0.3768 - F1: 0.3314
sub_22:Test (Best Model) - Loss: 1.2722 - Accuracy: 0.4203 - F1: 0.3926
sub_22:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.4348 - F1: 0.4537
sub_22:Test (Best Model) - Loss: 1.3075 - Accuracy: 0.3043 - F1: 0.2910
sub_22:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.3676 - F1: 0.3872
sub_22:Test (Best Model) - Loss: 1.2819 - Accuracy: 0.3676 - F1: 0.3881
sub_22:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.3235 - F1: 0.3343
sub_22:Test (Best Model) - Loss: 1.3115 - Accuracy: 0.2794 - F1: 0.3242
sub_22:Test (Best Model) - Loss: 1.2516 - Accuracy: 0.3824 - F1: 0.4170
sub_23:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.3913 - F1: 0.4113
sub_23:Test (Best Model) - Loss: 1.1783 - Accuracy: 0.4203 - F1: 0.4420
sub_23:Test (Best Model) - Loss: 1.1784 - Accuracy: 0.3768 - F1: 0.3801
sub_23:Test (Best Model) - Loss: 1.1333 - Accuracy: 0.5072 - F1: 0.5220
sub_23:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.4203 - F1: 0.4395
sub_23:Test (Best Model) - Loss: 1.1985 - Accuracy: 0.4559 - F1: 0.4279
sub_23:Test (Best Model) - Loss: 1.1635 - Accuracy: 0.5294 - F1: 0.5317
sub_23:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.4853 - F1: 0.4665
sub_23:Test (Best Model) - Loss: 1.1364 - Accuracy: 0.5147 - F1: 0.5070
sub_23:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.5000 - F1: 0.4708
sub_23:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.3043 - F1: 0.3136
sub_23:Test (Best Model) - Loss: 1.2682 - Accuracy: 0.4348 - F1: 0.4346
sub_23:Test (Best Model) - Loss: 1.2112 - Accuracy: 0.4348 - F1: 0.4308
sub_23:Test (Best Model) - Loss: 1.2665 - Accuracy: 0.4928 - F1: 0.5031
sub_23:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.3333 - F1: 0.3468
sub_24:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.3235 - F1: 0.3078
sub_24:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.3235 - F1: 0.3107
sub_24:Test (Best Model) - Loss: 1.4200 - Accuracy: 0.2794 - F1: 0.2786
sub_24:Test (Best Model) - Loss: 1.4205 - Accuracy: 0.3824 - F1: 0.3719
sub_24:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.2500 - F1: 0.2470
sub_24:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.2794 - F1: 0.2745
sub_24:Test (Best Model) - Loss: 1.3442 - Accuracy: 0.3382 - F1: 0.3464
sub_24:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.2647 - F1: 0.2481
sub_24:Test (Best Model) - Loss: 1.3246 - Accuracy: 0.3529 - F1: 0.3425
sub_24:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.3088 - F1: 0.3080
sub_24:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2059 - F1: 0.2099
sub_24:Test (Best Model) - Loss: 1.4733 - Accuracy: 0.1912 - F1: 0.1934
sub_24:Test (Best Model) - Loss: 1.4397 - Accuracy: 0.2353 - F1: 0.2355
sub_24:Test (Best Model) - Loss: 1.4457 - Accuracy: 0.3235 - F1: 0.3225
sub_24:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.2647 - F1: 0.2615
sub_25:Test (Best Model) - Loss: 1.2222 - Accuracy: 0.4638 - F1: 0.4241
sub_25:Test (Best Model) - Loss: 1.2635 - Accuracy: 0.4058 - F1: 0.3814
sub_25:Test (Best Model) - Loss: 1.2445 - Accuracy: 0.4493 - F1: 0.4135
sub_25:Test (Best Model) - Loss: 1.2406 - Accuracy: 0.4638 - F1: 0.4372
sub_25:Test (Best Model) - Loss: 1.2889 - Accuracy: 0.3623 - F1: 0.3485
sub_25:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.4118 - F1: 0.3566
sub_25:Test (Best Model) - Loss: 1.2914 - Accuracy: 0.4412 - F1: 0.3950
sub_25:Test (Best Model) - Loss: 1.2612 - Accuracy: 0.4853 - F1: 0.4574
sub_25:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.5000 - F1: 0.4348
sub_25:Test (Best Model) - Loss: 1.2530 - Accuracy: 0.4853 - F1: 0.3957
sub_25:Test (Best Model) - Loss: 1.2771 - Accuracy: 0.3971 - F1: 0.3988
sub_25:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.3971 - F1: 0.3512
sub_25:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.4265 - F1: 0.4147
sub_25:Test (Best Model) - Loss: 1.2409 - Accuracy: 0.3235 - F1: 0.2547
sub_25:Test (Best Model) - Loss: 1.2430 - Accuracy: 0.4265 - F1: 0.3716
sub_26:Test (Best Model) - Loss: 1.1368 - Accuracy: 0.4058 - F1: 0.4305
sub_26:Test (Best Model) - Loss: 1.2425 - Accuracy: 0.4348 - F1: 0.4340
sub_26:Test (Best Model) - Loss: 1.1707 - Accuracy: 0.4928 - F1: 0.5070
sub_26:Test (Best Model) - Loss: 1.1725 - Accuracy: 0.5362 - F1: 0.5385
sub_26:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.5362 - F1: 0.5622
sub_26:Test (Best Model) - Loss: 1.2484 - Accuracy: 0.4265 - F1: 0.4554
sub_26:Test (Best Model) - Loss: 1.2171 - Accuracy: 0.3824 - F1: 0.4060
sub_26:Test (Best Model) - Loss: 1.2301 - Accuracy: 0.3529 - F1: 0.3530
sub_26:Test (Best Model) - Loss: 1.2405 - Accuracy: 0.4118 - F1: 0.4178
sub_26:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.3382 - F1: 0.3714
sub_26:Test (Best Model) - Loss: 1.1723 - Accuracy: 0.5147 - F1: 0.5418
sub_26:Test (Best Model) - Loss: 1.2710 - Accuracy: 0.5441 - F1: 0.5731
sub_26:Test (Best Model) - Loss: 1.2296 - Accuracy: 0.5000 - F1: 0.5158
sub_26:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.5735 - F1: 0.6019
sub_26:Test (Best Model) - Loss: 1.2117 - Accuracy: 0.5588 - F1: 0.5858
sub_27:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.5072 - F1: 0.4811
sub_27:Test (Best Model) - Loss: 1.2342 - Accuracy: 0.3768 - F1: 0.3388
sub_27:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4203 - F1: 0.4079
sub_27:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.4493 - F1: 0.4531
sub_27:Test (Best Model) - Loss: 1.2359 - Accuracy: 0.4493 - F1: 0.4463
sub_27:Test (Best Model) - Loss: 1.4289 - Accuracy: 0.3333 - F1: 0.2829
sub_27:Test (Best Model) - Loss: 1.4464 - Accuracy: 0.3188 - F1: 0.2704
sub_27:Test (Best Model) - Loss: 1.4486 - Accuracy: 0.4203 - F1: 0.3665
sub_27:Test (Best Model) - Loss: 1.4216 - Accuracy: 0.4203 - F1: 0.3790
sub_27:Test (Best Model) - Loss: 1.4247 - Accuracy: 0.3913 - F1: 0.3418
sub_27:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4265 - F1: 0.4094
sub_27:Test (Best Model) - Loss: 1.2181 - Accuracy: 0.4265 - F1: 0.4227
sub_27:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.3971 - F1: 0.3967
sub_27:Test (Best Model) - Loss: 1.2790 - Accuracy: 0.4265 - F1: 0.4359
sub_27:Test (Best Model) - Loss: 1.2658 - Accuracy: 0.3824 - F1: 0.3781
sub_28:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.3382 - F1: 0.3332
sub_28:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.3088 - F1: 0.2899
sub_28:Test (Best Model) - Loss: 1.5164 - Accuracy: 0.3529 - F1: 0.3399
sub_28:Test (Best Model) - Loss: 1.4713 - Accuracy: 0.2794 - F1: 0.2678
sub_28:Test (Best Model) - Loss: 1.4899 - Accuracy: 0.2353 - F1: 0.2452
sub_28:Test (Best Model) - Loss: 1.7343 - Accuracy: 0.2206 - F1: 0.1943
sub_28:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2647 - F1: 0.2296
sub_28:Test (Best Model) - Loss: 1.6479 - Accuracy: 0.2353 - F1: 0.2022
sub_28:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2794 - F1: 0.2703
sub_28:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.2500 - F1: 0.1966
sub_28:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.3824 - F1: 0.3304
sub_28:Test (Best Model) - Loss: 1.2686 - Accuracy: 0.4118 - F1: 0.3215
sub_28:Test (Best Model) - Loss: 1.2653 - Accuracy: 0.4265 - F1: 0.4045
sub_28:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.5000 - F1: 0.4955
sub_28:Test (Best Model) - Loss: 1.2906 - Accuracy: 0.5147 - F1: 0.4854
sub_29:Test (Best Model) - Loss: 1.1490 - Accuracy: 0.5000 - F1: 0.5127
sub_29:Test (Best Model) - Loss: 1.0879 - Accuracy: 0.4706 - F1: 0.4777
sub_29:Test (Best Model) - Loss: 1.0359 - Accuracy: 0.5735 - F1: 0.5867
sub_29:Test (Best Model) - Loss: 1.1199 - Accuracy: 0.5000 - F1: 0.4993
sub_29:Test (Best Model) - Loss: 1.0996 - Accuracy: 0.5000 - F1: 0.5183
sub_29:Test (Best Model) - Loss: 1.0455 - Accuracy: 0.5588 - F1: 0.5802
sub_29:Test (Best Model) - Loss: 1.0111 - Accuracy: 0.5735 - F1: 0.5908
sub_29:Test (Best Model) - Loss: 0.9890 - Accuracy: 0.5000 - F1: 0.5206
sub_29:Test (Best Model) - Loss: 0.9960 - Accuracy: 0.6618 - F1: 0.6773
sub_29:Test (Best Model) - Loss: 0.9717 - Accuracy: 0.5735 - F1: 0.6005
sub_29:Test (Best Model) - Loss: 1.0006 - Accuracy: 0.5217 - F1: 0.5447
sub_29:Test (Best Model) - Loss: 0.9945 - Accuracy: 0.5072 - F1: 0.5266
sub_29:Test (Best Model) - Loss: 1.0688 - Accuracy: 0.5217 - F1: 0.5437
sub_29:Test (Best Model) - Loss: 0.9681 - Accuracy: 0.6522 - F1: 0.6674
sub_29:Test (Best Model) - Loss: 0.9811 - Accuracy: 0.5507 - F1: 0.5719

=== Summary Results ===

acc: 40.16 ± 6.53
F1: 39.87 ± 6.96
acc-in: 47.65 ± 6.18
F1-in: 46.07 ± 6.60
