lr: 0.0001
sub_8:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2647 - F1: 0.1216
sub_3:Test (Best Model) - Loss: 1.2430 - Accuracy: 0.5294 - F1: 0.4760
sub_15:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.3529 - F1: 0.2800
sub_5:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4559 - F1: 0.3517
sub_10:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.1426 - Accuracy: 0.4493 - F1: 0.3538
sub_12:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.3971 - F1: 0.3286
sub_6:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.3235 - F1: 0.1910
sub_11:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.4783 - F1: 0.3231
sub_9:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.4853 - F1: 0.4338
sub_13:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2500 - F1: 0.1000
sub_3:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.5882 - F1: 0.5165
sub_2:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.4348 - F1: 0.2847
sub_8:Test (Best Model) - Loss: 1.2524 - Accuracy: 0.4412 - F1: 0.3524
sub_1:Test (Best Model) - Loss: 1.0436 - Accuracy: 0.4118 - F1: 0.3316
sub_4:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2899 - F1: 0.1548
sub_7:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.3382 - F1: 0.2455
sub_14:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.3121 - Accuracy: 0.4118 - F1: 0.3053
sub_15:Test (Best Model) - Loss: 1.1839 - Accuracy: 0.4412 - F1: 0.3162
sub_2:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.3971 - F1: 0.3125
sub_6:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.3676 - F1: 0.2831
sub_3:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.3235 - F1: 0.2695
sub_4:Test (Best Model) - Loss: 1.2165 - Accuracy: 0.4348 - F1: 0.3056
sub_8:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.3382 - F1: 0.2746
sub_10:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.1029 - F1: 0.0507
sub_13:Test (Best Model) - Loss: 1.3503 - Accuracy: 0.4265 - F1: 0.2876
sub_5:Test (Best Model) - Loss: 1.2736 - Accuracy: 0.4559 - F1: 0.3181
sub_15:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2647 - F1: 0.2163
sub_2:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.4928 - F1: 0.3357
sub_1:Test (Best Model) - Loss: 1.0734 - Accuracy: 0.4118 - F1: 0.3351
sub_9:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.3088 - F1: 0.2002
sub_6:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.2647 - F1: 0.1059
sub_11:Test (Best Model) - Loss: 1.0910 - Accuracy: 0.4638 - F1: 0.3272
sub_7:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.5588 - F1: 0.4462
sub_4:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.2609 - F1: 0.1034
sub_8:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3529 - F1: 0.2694
sub_10:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.2941 - F1: 0.1696
sub_14:Test (Best Model) - Loss: 1.5229 - Accuracy: 0.0588 - F1: 0.0362
sub_2:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.2754 - F1: 0.1359
sub_12:Test (Best Model) - Loss: 1.0955 - Accuracy: 0.5882 - F1: 0.5506
sub_11:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.4559 - F1: 0.3657
sub_5:Test (Best Model) - Loss: 1.2544 - Accuracy: 0.4559 - F1: 0.3119
sub_15:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3971 - F1: 0.2793
sub_14:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3235 - F1: 0.2236
sub_8:Test (Best Model) - Loss: 1.2638 - Accuracy: 0.3824 - F1: 0.2972
sub_12:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.1654 - Accuracy: 0.3824 - F1: 0.3452
sub_10:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2941 - F1: 0.1571
sub_4:Test (Best Model) - Loss: 1.2258 - Accuracy: 0.4203 - F1: 0.3332
sub_6:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3529 - F1: 0.2212
sub_9:Test (Best Model) - Loss: 1.2312 - Accuracy: 0.4265 - F1: 0.3400
sub_11:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.4783 - F1: 0.3365
sub_5:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.1471 - F1: 0.1326
sub_13:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.2794 - F1: 0.1630
sub_7:Test (Best Model) - Loss: 0.9790 - Accuracy: 0.5000 - F1: 0.4286
sub_14:Test (Best Model) - Loss: 1.3637 - Accuracy: 0.2941 - F1: 0.1539
sub_10:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.2647 - F1: 0.1047
sub_1:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.1545 - Accuracy: 0.4928 - F1: 0.4036
sub_13:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3165 - Accuracy: 0.3824 - F1: 0.2972
sub_4:Test (Best Model) - Loss: 1.2581 - Accuracy: 0.4783 - F1: 0.3750
sub_14:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.2500 - F1: 0.1012
sub_1:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.1043 - Accuracy: 0.4559 - F1: 0.3640
sub_8:Test (Best Model) - Loss: 1.1714 - Accuracy: 0.4265 - F1: 0.3725
sub_5:Test (Best Model) - Loss: 1.1285 - Accuracy: 0.4706 - F1: 0.3750
sub_3:Test (Best Model) - Loss: 1.1008 - Accuracy: 0.4058 - F1: 0.3233
sub_7:Test (Best Model) - Loss: 1.1145 - Accuracy: 0.2941 - F1: 0.3056
sub_14:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.1068 - Accuracy: 0.4118 - F1: 0.3352
sub_11:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.3913 - F1: 0.2918
sub_6:Test (Best Model) - Loss: 1.2298 - Accuracy: 0.3478 - F1: 0.2986
sub_5:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 0.9216 - Accuracy: 0.6471 - F1: 0.5894
sub_3:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.4348 - F1: 0.3748
sub_1:Test (Best Model) - Loss: 1.2228 - Accuracy: 0.3188 - F1: 0.2326
sub_12:Test (Best Model) - Loss: 1.1911 - Accuracy: 0.3913 - F1: 0.3059
sub_15:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2647 - F1: 0.1435
sub_9:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.3529 - F1: 0.2625
sub_13:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2609 - F1: 0.1410
sub_8:Test (Best Model) - Loss: 1.1403 - Accuracy: 0.6324 - F1: 0.5948
sub_10:Test (Best Model) - Loss: 1.0821 - Accuracy: 0.5147 - F1: 0.4835
sub_7:Test (Best Model) - Loss: 1.3368 - Accuracy: 0.2794 - F1: 0.1363
sub_3:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.3043 - F1: 0.1700
sub_13:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.2899 - F1: 0.2289
sub_4:Test (Best Model) - Loss: 0.5684 - Accuracy: 0.8406 - F1: 0.8423
sub_14:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2794 - F1: 0.1322
sub_1:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.2464 - F1: 0.1104
sub_12:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.4493 - F1: 0.3538
sub_9:Test (Best Model) - Loss: 1.2520 - Accuracy: 0.2647 - F1: 0.2172
sub_6:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.3623 - F1: 0.2579
sub_5:Test (Best Model) - Loss: 0.7631 - Accuracy: 0.6912 - F1: 0.6307
sub_15:Test (Best Model) - Loss: 1.0458 - Accuracy: 0.4559 - F1: 0.3657
sub_2:Test (Best Model) - Loss: 1.0383 - Accuracy: 0.5294 - F1: 0.5017
sub_10:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.3235 - F1: 0.1874
sub_11:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.2899 - F1: 0.1667
sub_8:Test (Best Model) - Loss: 0.9040 - Accuracy: 0.4559 - F1: 0.4054
sub_14:Test (Best Model) - Loss: 1.2414 - Accuracy: 0.4559 - F1: 0.3976
sub_13:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2754 - F1: 0.1310
sub_4:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.4638 - F1: 0.3326
sub_15:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.5000 - F1: 0.4502
sub_3:Test (Best Model) - Loss: 1.2063 - Accuracy: 0.3768 - F1: 0.2908
sub_10:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3529 - F1: 0.2244
sub_1:Test (Best Model) - Loss: 1.2616 - Accuracy: 0.2464 - F1: 0.1565
sub_12:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.4638 - F1: 0.4222
sub_11:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.0665 - Accuracy: 0.4706 - F1: 0.3786
sub_6:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.3478 - F1: 0.2554
sub_13:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.3235 - F1: 0.2209
sub_7:Test (Best Model) - Loss: 1.4382 - Accuracy: 0.3235 - F1: 0.2284
sub_10:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.2174 - F1: 0.1000
sub_14:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.2754 - F1: 0.1589
sub_4:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.3768 - F1: 0.2878
sub_2:Test (Best Model) - Loss: 1.1045 - Accuracy: 0.4412 - F1: 0.3786
sub_9:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.2941 - F1: 0.2299
sub_8:Test (Best Model) - Loss: 1.0460 - Accuracy: 0.4412 - F1: 0.3558
sub_11:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.4638 - F1: 0.3047
sub_6:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.4118 - F1: 0.2755
sub_13:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.4118 - F1: 0.2673
sub_7:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.3971 - F1: 0.3173
sub_10:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3623 - F1: 0.2407
sub_14:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.2206 - F1: 0.1266
sub_1:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2609 - F1: 0.1154
sub_3:Test (Best Model) - Loss: 1.3690 - Accuracy: 0.4203 - F1: 0.3081
sub_8:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.5147 - F1: 0.3475
sub_15:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3088 - F1: 0.1896
sub_11:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.5217 - F1: 0.3635
sub_6:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2609 - F1: 0.1034
sub_9:Test (Best Model) - Loss: 1.2687 - Accuracy: 0.5735 - F1: 0.5151
sub_13:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.1331 - Accuracy: 0.3768 - F1: 0.2939
sub_10:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.1034
sub_14:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.0918 - Accuracy: 0.6029 - F1: 0.5583
sub_8:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3084 - Accuracy: 0.2794 - F1: 0.1372
sub_15:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.1071
sub_4:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.3913 - F1: 0.3029
sub_9:Test (Best Model) - Loss: 1.3445 - Accuracy: 0.3676 - F1: 0.2806
sub_12:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.2609 - F1: 0.1139
sub_13:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3382 - F1: 0.2168
sub_5:Test (Best Model) - Loss: 1.1376 - Accuracy: 0.4265 - F1: 0.3433
sub_14:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.4203 - F1: 0.2751
sub_10:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.2426 - Accuracy: 0.3623 - F1: 0.2845
sub_2:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3824 - F1: 0.2414
sub_8:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.5294 - F1: 0.4644
sub_7:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.4706 - F1: 0.3392
sub_4:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.5217 - F1: 0.3545
sub_12:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3676 - F1: 0.2806
sub_6:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.5217 - F1: 0.4358
sub_11:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2609 - F1: 0.1059
sub_15:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3676 - F1: 0.2315
sub_1:Test (Best Model) - Loss: 1.2927 - Accuracy: 0.4559 - F1: 0.4079
sub_8:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1084
sub_7:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.2609 - F1: 0.1200
sub_6:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.1592 - Accuracy: 0.5362 - F1: 0.4761
sub_14:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.5147 - F1: 0.3641
sub_9:Test (Best Model) - Loss: 1.1297 - Accuracy: 0.4265 - F1: 0.2888
sub_10:Test (Best Model) - Loss: 1.0509 - Accuracy: 0.4493 - F1: 0.3996
sub_7:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.1356 - Accuracy: 0.3824 - F1: 0.3051
sub_12:Test (Best Model) - Loss: 1.0646 - Accuracy: 0.4706 - F1: 0.3762
sub_11:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2899 - F1: 0.1559
sub_6:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.0983 - Accuracy: 0.4265 - F1: 0.3416
sub_9:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.2647 - F1: 0.1047
sub_5:Test (Best Model) - Loss: 1.0500 - Accuracy: 0.5000 - F1: 0.3581
sub_12:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.1884 - F1: 0.1226
sub_7:Test (Best Model) - Loss: 1.3615 - Accuracy: 0.3971 - F1: 0.3141
sub_4:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.3623 - F1: 0.2716
sub_11:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.2754 - F1: 0.1310
sub_6:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.2899 - F1: 0.1647
sub_1:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2059 - F1: 0.1094
sub_2:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.4638 - F1: 0.3114
sub_5:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.5294 - F1: 0.4575
sub_12:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2647 - F1: 0.1047
sub_8:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.4559 - F1: 0.3640
sub_2:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3143 - Accuracy: 0.3676 - F1: 0.2806
sub_9:Test (Best Model) - Loss: 1.1309 - Accuracy: 0.6176 - F1: 0.5020
sub_3:Test (Best Model) - Loss: 1.0508 - Accuracy: 0.6087 - F1: 0.5463
sub_1:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.2794 - F1: 0.1322
sub_2:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.3768 - F1: 0.2681
sub_5:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.3382 - F1: 0.2427
sub_9:Test (Best Model) - Loss: 1.2249 - Accuracy: 0.3971 - F1: 0.3173
sub_8:Test (Best Model) - Loss: 0.9564 - Accuracy: 0.4559 - F1: 0.3640
sub_1:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.6176 - F1: 0.5488
sub_2:Test (Best Model) - Loss: 1.3257 - Accuracy: 0.3913 - F1: 0.3029
sub_28:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.2500 - F1: 0.1149
sub_25:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2029 - F1: 0.1028
sub_17:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2609 - F1: 0.1139
sub_27:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2609 - F1: 0.1139
sub_24:Test (Best Model) - Loss: 1.1518 - Accuracy: 0.5000 - F1: 0.4286
sub_16:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.2647 - F1: 0.1098
sub_28:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.0882 - F1: 0.0441
sub_18:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3623 - F1: 0.2841
sub_26:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.5652 - F1: 0.5151
sub_29:Test (Best Model) - Loss: 1.1310 - Accuracy: 0.4412 - F1: 0.3541
sub_23:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.2609 - F1: 0.1184
sub_21:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.5294 - F1: 0.3982
sub_16:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.2794 - F1: 0.1394
sub_20:Test (Best Model) - Loss: 1.7830 - Accuracy: 0.3971 - F1: 0.3157
sub_25:Test (Best Model) - Loss: 1.1834 - Accuracy: 0.4058 - F1: 0.3307
sub_17:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.4493 - F1: 0.3942
sub_27:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.4493 - F1: 0.3942
sub_24:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2794 - F1: 0.1607
sub_28:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.4706 - F1: 0.3098
sub_18:Test (Best Model) - Loss: 1.2125 - Accuracy: 0.4493 - F1: 0.3538
sub_21:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.2134 - Accuracy: 0.3971 - F1: 0.3125
sub_23:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.3768 - F1: 0.2878
sub_26:Test (Best Model) - Loss: 1.0356 - Accuracy: 0.4638 - F1: 0.3647
sub_17:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2609 - F1: 0.1084
sub_27:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2609 - F1: 0.1084
sub_28:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.2941 - F1: 0.1919
sub_22:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.4118 - F1: 0.3268
sub_18:Test (Best Model) - Loss: 1.2558 - Accuracy: 0.3913 - F1: 0.3108
sub_21:Test (Best Model) - Loss: 1.2983 - Accuracy: 0.4706 - F1: 0.3304
sub_19:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2941 - F1: 0.1611
sub_27:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2754 - F1: 0.1427
sub_23:Test (Best Model) - Loss: 1.2697 - Accuracy: 0.4348 - F1: 0.3889
sub_29:Test (Best Model) - Loss: 1.1353 - Accuracy: 0.4853 - F1: 0.4429
sub_16:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.3529 - F1: 0.2943
sub_21:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.4118 - F1: 0.3268
sub_18:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.4638 - F1: 0.3697
sub_27:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.2609 - F1: 0.1154
sub_20:Test (Best Model) - Loss: 1.2350 - Accuracy: 0.4118 - F1: 0.3268
sub_17:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.2609 - F1: 0.1154
sub_28:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.3676 - F1: 0.2304
sub_29:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.3623 - F1: 0.2841
sub_24:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.4706 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.4412 - F1: 0.3754
sub_21:Test (Best Model) - Loss: 1.2630 - Accuracy: 0.4265 - F1: 0.3400
sub_25:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.2609 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 1.2977 - Accuracy: 0.3623 - F1: 0.2730
sub_16:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.1469 - Accuracy: 0.4928 - F1: 0.4476
sub_29:Test (Best Model) - Loss: 1.3322 - Accuracy: 0.3824 - F1: 0.2972
sub_20:Test (Best Model) - Loss: 1.2379 - Accuracy: 0.3971 - F1: 0.3280
sub_24:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.2794 - F1: 0.1431
sub_22:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.1303 - Accuracy: 0.3913 - F1: 0.3258
sub_17:Test (Best Model) - Loss: 1.1303 - Accuracy: 0.3913 - F1: 0.3258
sub_19:Test (Best Model) - Loss: 1.3414 - Accuracy: 0.2941 - F1: 0.1758
sub_28:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2941 - F1: 0.1880
sub_18:Test (Best Model) - Loss: 1.2721 - Accuracy: 0.4706 - F1: 0.3750
sub_25:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.2941 - F1: 0.1779
sub_26:Test (Best Model) - Loss: 1.3592 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.4412 - F1: 0.3138
sub_23:Test (Best Model) - Loss: 1.2531 - Accuracy: 0.4118 - F1: 0.3268
sub_19:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2353 - F1: 0.0976
sub_26:Test (Best Model) - Loss: 1.3237 - Accuracy: 0.3913 - F1: 0.3059
sub_29:Test (Best Model) - Loss: 0.9902 - Accuracy: 0.4706 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 1.2472 - Accuracy: 0.3088 - F1: 0.2744
sub_20:Test (Best Model) - Loss: 1.2344 - Accuracy: 0.3971 - F1: 0.3125
sub_16:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2647 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.1802 - Accuracy: 0.3623 - F1: 0.2942
sub_18:Test (Best Model) - Loss: 1.2635 - Accuracy: 0.5735 - F1: 0.5861
sub_19:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.2647 - F1: 0.1084
sub_17:Test (Best Model) - Loss: 1.1802 - Accuracy: 0.3623 - F1: 0.2942
sub_25:Test (Best Model) - Loss: 1.1996 - Accuracy: 0.4559 - F1: 0.3260
sub_23:Test (Best Model) - Loss: 1.2868 - Accuracy: 0.3824 - F1: 0.3050
sub_24:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.3529 - F1: 0.2540
sub_22:Test (Best Model) - Loss: 1.1280 - Accuracy: 0.3913 - F1: 0.3578
sub_27:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.0588 - F1: 0.0418
sub_19:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.3529 - F1: 0.2681
sub_17:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2609 - F1: 0.1034
sub_28:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3235 - F1: 0.2143
sub_26:Test (Best Model) - Loss: 1.0252 - Accuracy: 0.4559 - F1: 0.3751
sub_24:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.3824 - F1: 0.3168
sub_29:Test (Best Model) - Loss: 1.0334 - Accuracy: 0.6618 - F1: 0.5944
sub_21:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.4412 - F1: 0.2864
sub_18:Test (Best Model) - Loss: 1.0303 - Accuracy: 0.4853 - F1: 0.4187
sub_16:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2647 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.0433 - Accuracy: 0.4412 - F1: 0.3558
sub_24:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.2647 - F1: 0.1084
sub_29:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.3088 - F1: 0.1967
sub_21:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2647 - F1: 0.1059
sub_23:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.4265 - F1: 0.4146
sub_16:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.5147 - F1: 0.3382
sub_27:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.2609 - F1: 0.2836
sub_18:Test (Best Model) - Loss: 1.1021 - Accuracy: 0.4853 - F1: 0.4036
sub_22:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.3768 - F1: 0.3188
sub_17:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.2609 - F1: 0.2836
sub_21:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3676 - F1: 0.2806
sub_19:Test (Best Model) - Loss: 1.2536 - Accuracy: 0.4118 - F1: 0.2791
sub_24:Test (Best Model) - Loss: 1.2110 - Accuracy: 0.5147 - F1: 0.4133
sub_26:Test (Best Model) - Loss: 1.1660 - Accuracy: 0.3971 - F1: 0.3224
sub_20:Test (Best Model) - Loss: 0.9887 - Accuracy: 0.6029 - F1: 0.5649
sub_29:Test (Best Model) - Loss: 1.0362 - Accuracy: 0.4706 - F1: 0.3750
sub_28:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.5000 - F1: 0.4437
sub_27:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3043 - F1: 0.1973
sub_18:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.4118 - F1: 0.3717
sub_17:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3043 - F1: 0.1973
sub_19:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.2794 - F1: 0.1518
sub_20:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.2647 - F1: 0.1047
sub_22:Test (Best Model) - Loss: 1.2879 - Accuracy: 0.5072 - F1: 0.4830
sub_29:Test (Best Model) - Loss: 1.3381 - Accuracy: 0.5588 - F1: 0.4705
sub_24:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3971 - F1: 0.2777
sub_27:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3676 - F1: 0.2806
sub_21:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.5294 - F1: 0.3525
sub_28:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2794 - F1: 0.1321
sub_25:Test (Best Model) - Loss: 0.8873 - Accuracy: 0.6618 - F1: 0.6665
sub_23:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.3824 - F1: 0.3063
sub_18:Test (Best Model) - Loss: 1.2676 - Accuracy: 0.4559 - F1: 0.3640
sub_17:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3676 - F1: 0.2806
sub_19:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3529 - F1: 0.2404
sub_26:Test (Best Model) - Loss: 1.0759 - Accuracy: 0.4559 - F1: 0.3950
sub_21:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.3676 - F1: 0.2806
sub_28:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2206 - F1: 0.1230
sub_16:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2647 - F1: 0.1139
sub_18:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.4783 - F1: 0.3486
sub_27:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2941 - F1: 0.1627
sub_22:Test (Best Model) - Loss: 1.1776 - Accuracy: 0.4203 - F1: 0.3737
sub_20:Test (Best Model) - Loss: 1.1385 - Accuracy: 0.5735 - F1: 0.5133
sub_24:Test (Best Model) - Loss: 1.3364 - Accuracy: 0.3382 - F1: 0.2695
sub_25:Test (Best Model) - Loss: 1.2436 - Accuracy: 0.6765 - F1: 0.6667
sub_23:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.4058 - F1: 0.3307
sub_17:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2941 - F1: 0.1627
sub_28:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1059
sub_19:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2206 - F1: 0.1300
sub_27:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3382 - F1: 0.2167
sub_20:Test (Best Model) - Loss: 1.3245 - Accuracy: 0.4412 - F1: 0.2871
sub_23:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.3768 - F1: 0.2678
sub_17:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.1744 - Accuracy: 0.4118 - F1: 0.2971
sub_22:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.2899 - F1: 0.1652
sub_29:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4058 - F1: 0.3519
sub_28:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.3529 - F1: 0.2667
sub_27:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3626 - Accuracy: 0.3043 - F1: 0.1905
sub_23:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.2609 - F1: 0.1034
sub_16:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.2794 - F1: 0.1612
sub_26:Test (Best Model) - Loss: 0.9991 - Accuracy: 0.6176 - F1: 0.5737
sub_21:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.3676 - F1: 0.2806
sub_25:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3088 - F1: 0.1750
sub_17:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.3088 - F1: 0.1769
sub_19:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2059 - F1: 0.0886
sub_27:Test (Best Model) - Loss: 1.3110 - Accuracy: 0.3824 - F1: 0.2972
sub_20:Test (Best Model) - Loss: 1.3342 - Accuracy: 0.2899 - F1: 0.1559
sub_16:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3382 - F1: 0.2290
sub_28:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2647 - F1: 0.1059
sub_17:Test (Best Model) - Loss: 1.3110 - Accuracy: 0.3824 - F1: 0.2972
sub_26:Test (Best Model) - Loss: 1.3253 - Accuracy: 0.3676 - F1: 0.2935
sub_23:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4928 - F1: 0.4885
sub_18:Test (Best Model) - Loss: 1.3026 - Accuracy: 0.4706 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 1.3703 - Accuracy: 0.2206 - F1: 0.1250
sub_21:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3676 - F1: 0.2806
sub_20:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3623 - F1: 0.2419
sub_19:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.3382 - F1: 0.2185
sub_23:Test (Best Model) - Loss: 1.2453 - Accuracy: 0.3768 - F1: 0.2878
sub_18:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.4706 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.3529 - F1: 0.2800
sub_24:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.3235 - F1: 0.2030
sub_20:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.3382 - F1: 0.2500
sub_28:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.3824 - F1: 0.2619
sub_29:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.2609 - F1: 0.1898
sub_25:Test (Best Model) - Loss: 0.9366 - Accuracy: 0.5882 - F1: 0.4666
sub_19:Test (Best Model) - Loss: 1.1432 - Accuracy: 0.3971 - F1: 0.3125
sub_22:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.3529 - F1: 0.2375
sub_29:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.4638 - F1: 0.3647
sub_22:Test (Best Model) - Loss: 1.2860 - Accuracy: 0.3824 - F1: 0.2972
sub_24:Test (Best Model) - Loss: 1.1211 - Accuracy: 0.3676 - F1: 0.2971
sub_25:Test (Best Model) - Loss: 1.1259 - Accuracy: 0.5588 - F1: 0.4447
sub_20:Test (Best Model) - Loss: 1.0738 - Accuracy: 0.4638 - F1: 0.4182
sub_26:Test (Best Model) - Loss: 1.2661 - Accuracy: 0.4706 - F1: 0.3849
sub_25:Test (Best Model) - Loss: 1.2840 - Accuracy: 0.5294 - F1: 0.3545
sub_25:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3088 - F1: 0.1967
sub_26:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.4412 - F1: 0.3212
sub_26:Test (Best Model) - Loss: 1.1258 - Accuracy: 0.4706 - F1: 0.3734
sub_26:Test (Best Model) - Loss: 1.1424 - Accuracy: 0.3971 - F1: 0.3125

=== Summary Results ===

acc: 36.08 ± 4.65
F1: 25.03 ± 5.74
acc-in: 43.10 ± 4.84
F1-in: 31.92 ± 6.22
runing time: 1585.08 seconds
