lr: 0.0001
sub_3:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2353 - F1: 0.1841
sub_7:Test (Best Model) - Loss: 1.2900 - Accuracy: 0.5294 - F1: 0.3508
sub_5:Test (Best Model) - Loss: 1.2393 - Accuracy: 0.4853 - F1: 0.3215
sub_10:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2647 - F1: 0.1059
sub_12:Test (Best Model) - Loss: 1.1944 - Accuracy: 0.2500 - F1: 0.2707
sub_6:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.3382 - F1: 0.2078
sub_4:Test (Best Model) - Loss: 1.1647 - Accuracy: 0.5072 - F1: 0.4670
sub_2:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2609 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2794 - F1: 0.1322
sub_11:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.4638 - F1: 0.3041
sub_15:Test (Best Model) - Loss: 1.0003 - Accuracy: 0.5000 - F1: 0.4425
sub_14:Test (Best Model) - Loss: 1.4050 - Accuracy: 0.1765 - F1: 0.0952
sub_5:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.5294 - F1: 0.4475
sub_8:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.4853 - F1: 0.4591
sub_9:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.3088 - F1: 0.2251
sub_1:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.3824 - F1: 0.3138
sub_10:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2647 - F1: 0.1047
sub_2:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.3676 - F1: 0.2407
sub_11:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.2805 - Accuracy: 0.3971 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2794 - F1: 0.1588
sub_3:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3235 - F1: 0.2215
sub_13:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2500 - F1: 0.1205
sub_4:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.5362 - F1: 0.5194
sub_6:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3824 - F1: 0.2972
sub_2:Test (Best Model) - Loss: 1.4450 - Accuracy: 0.2609 - F1: 0.1084
sub_10:Test (Best Model) - Loss: 1.7726 - Accuracy: 0.1471 - F1: 0.1746
sub_15:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3235 - F1: 0.2209
sub_12:Test (Best Model) - Loss: 1.2292 - Accuracy: 0.3824 - F1: 0.2972
sub_7:Test (Best Model) - Loss: 1.3023 - Accuracy: 0.4265 - F1: 0.3361
sub_14:Test (Best Model) - Loss: 1.4761 - Accuracy: 0.1029 - F1: 0.0473
sub_8:Test (Best Model) - Loss: 1.2325 - Accuracy: 0.4559 - F1: 0.3640
sub_1:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.3824 - F1: 0.2972
sub_5:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.3529 - F1: 0.3577
sub_13:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2794 - F1: 0.1321
sub_6:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.1059
sub_4:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3623 - F1: 0.2716
sub_10:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1059
sub_2:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.2754 - F1: 0.1466
sub_12:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3824 - F1: 0.2972
sub_15:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2500 - F1: 0.1704
sub_7:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3088 - F1: 0.1825
sub_11:Test (Best Model) - Loss: 1.1966 - Accuracy: 0.4783 - F1: 0.3933
sub_14:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.0882 - F1: 0.0484
sub_3:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.2500 - F1: 0.2224
sub_9:Test (Best Model) - Loss: 1.0862 - Accuracy: 0.4853 - F1: 0.4808
sub_5:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2941 - F1: 0.2543
sub_13:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.2754 - F1: 0.1664
sub_10:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2500 - F1: 0.1012
sub_7:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2794 - F1: 0.1333
sub_15:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.4118 - F1: 0.3503
sub_11:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.4058 - F1: 0.2671
sub_2:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2609 - F1: 0.1059
sub_12:Test (Best Model) - Loss: 1.2131 - Accuracy: 0.3824 - F1: 0.3002
sub_3:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.4265 - F1: 0.3365
sub_6:Test (Best Model) - Loss: 1.1625 - Accuracy: 0.4783 - F1: 0.4322
sub_1:Test (Best Model) - Loss: 1.2292 - Accuracy: 0.3824 - F1: 0.3398
sub_8:Test (Best Model) - Loss: 1.2883 - Accuracy: 0.4118 - F1: 0.3300
sub_5:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3529 - F1: 0.2306
sub_7:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.2647 - F1: 0.1047
sub_14:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2353 - F1: 0.1312
sub_2:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.4493 - F1: 0.3418
sub_6:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.3913 - F1: 0.2625
sub_1:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.2941 - F1: 0.1696
sub_9:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.3676 - F1: 0.2952
sub_15:Test (Best Model) - Loss: 1.3001 - Accuracy: 0.2941 - F1: 0.2316
sub_3:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.2794 - F1: 0.1882
sub_4:Test (Best Model) - Loss: 1.0762 - Accuracy: 0.4638 - F1: 0.3664
sub_7:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.3235 - F1: 0.1910
sub_14:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 1.1689 - Accuracy: 0.3529 - F1: 0.3482
sub_13:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.3043 - F1: 0.1725
sub_12:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.3768 - F1: 0.2878
sub_1:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2500 - F1: 0.1076
sub_8:Test (Best Model) - Loss: 1.2686 - Accuracy: 0.4118 - F1: 0.3283
sub_9:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2794 - F1: 0.1392
sub_2:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.3235 - F1: 0.1895
sub_11:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2754 - F1: 0.1361
sub_13:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.3043 - F1: 0.2129
sub_10:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2353 - F1: 0.1259
sub_5:Test (Best Model) - Loss: 1.3055 - Accuracy: 0.3382 - F1: 0.2099
sub_9:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.2647 - F1: 0.1125
sub_3:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.2899 - F1: 0.1637
sub_2:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.3478 - F1: 0.2540
sub_11:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2899 - F1: 0.1524
sub_7:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.4412 - F1: 0.2894
sub_8:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.3382 - F1: 0.2497
sub_1:Test (Best Model) - Loss: 1.2925 - Accuracy: 0.3333 - F1: 0.2404
sub_14:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.3333 - F1: 0.2341
sub_13:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2754 - F1: 0.1310
sub_3:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.3971 - F1: 0.3327
sub_15:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.0165 - Accuracy: 0.4638 - F1: 0.4567
sub_11:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2609 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.4853 - F1: 0.3281
sub_5:Test (Best Model) - Loss: 1.2190 - Accuracy: 0.4853 - F1: 0.3407
sub_6:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2609 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.4559 - F1: 0.4195
sub_12:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.3913 - F1: 0.3161
sub_2:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3824 - F1: 0.2649
sub_14:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1084
sub_9:Test (Best Model) - Loss: 1.2235 - Accuracy: 0.3824 - F1: 0.2972
sub_1:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3913 - F1: 0.2554
sub_8:Test (Best Model) - Loss: 1.0193 - Accuracy: 0.5000 - F1: 0.4281
sub_6:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.3245 - Accuracy: 0.2941 - F1: 0.1539
sub_10:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3088 - F1: 0.1980
sub_12:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.3768 - F1: 0.2878
sub_2:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2609 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.2919 - Accuracy: 0.3913 - F1: 0.3316
sub_15:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2609 - F1: 0.1169
sub_11:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2899 - F1: 0.2179
sub_1:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3188 - F1: 0.2192
sub_6:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3768 - F1: 0.2417
sub_4:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.3913 - F1: 0.3059
sub_15:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3971 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.5882 - F1: 0.5549
sub_3:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3188 - F1: 0.2150
sub_5:Test (Best Model) - Loss: 1.2951 - Accuracy: 0.4559 - F1: 0.3014
sub_14:Test (Best Model) - Loss: 1.3100 - Accuracy: 0.4559 - F1: 0.3031
sub_13:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3036 - Accuracy: 0.3478 - F1: 0.2568
sub_7:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.2941 - F1: 0.1744
sub_6:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2609 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.4118 - F1: 0.3446
sub_8:Test (Best Model) - Loss: 1.0179 - Accuracy: 0.6765 - F1: 0.6547
sub_1:Test (Best Model) - Loss: 1.2778 - Accuracy: 0.4203 - F1: 0.3300
sub_2:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.2609 - F1: 0.1034
sub_15:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.2647 - F1: 0.1098
sub_4:Test (Best Model) - Loss: 1.3141 - Accuracy: 0.4783 - F1: 0.3907
sub_3:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.2754 - F1: 0.1339
sub_13:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3419 - Accuracy: 0.3382 - F1: 0.2441
sub_10:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.3333 - F1: 0.2220
sub_9:Test (Best Model) - Loss: 1.2388 - Accuracy: 0.4853 - F1: 0.4625
sub_5:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.2941 - F1: 0.1764
sub_11:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.3333 - F1: 0.2466
sub_6:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.3623 - F1: 0.2627
sub_4:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2609 - F1: 0.1034
sub_7:Test (Best Model) - Loss: 1.4190 - Accuracy: 0.2941 - F1: 0.1731
sub_9:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.3824 - F1: 0.2972
sub_5:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3088 - F1: 0.1720
sub_3:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3768 - F1: 0.2597
sub_8:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.4853 - F1: 0.3492
sub_15:Test (Best Model) - Loss: 1.3011 - Accuracy: 0.3382 - F1: 0.2455
sub_1:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2647 - F1: 0.1169
sub_14:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1047
sub_10:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.2609 - F1: 0.1098
sub_12:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.2794 - F1: 0.1392
sub_2:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3478 - F1: 0.2568
sub_7:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2647 - F1: 0.1047
sub_9:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.6029 - F1: 0.5210
sub_5:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.1047
sub_11:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2899 - F1: 0.1571
sub_13:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.4265 - F1: 0.2800
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2647 - F1: 0.1047
sub_6:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.5942 - F1: 0.5277
sub_1:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2941 - F1: 0.1552
sub_4:Test (Best Model) - Loss: 1.1775 - Accuracy: 0.5217 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2609 - F1: 0.1034
sub_5:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.3971 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2794 - F1: 0.1902
sub_13:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.2647 - F1: 0.1047
sub_3:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.4203 - F1: 0.3036
sub_8:Test (Best Model) - Loss: 1.0261 - Accuracy: 0.4706 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3824 - F1: 0.2500
sub_15:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2794 - F1: 0.1322
sub_14:Test (Best Model) - Loss: 1.3173 - Accuracy: 0.4412 - F1: 0.3268
sub_11:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.4928 - F1: 0.3253
sub_10:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2899 - F1: 0.1640
sub_13:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3235 - F1: 0.2101
sub_3:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3971 - F1: 0.3125
sub_9:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2500 - F1: 0.1012
sub_1:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.3382 - F1: 0.2875
sub_14:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.2794 - F1: 0.1640
sub_8:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.4265 - F1: 0.2748
sub_7:Test (Best Model) - Loss: 1.2792 - Accuracy: 0.4412 - F1: 0.4027
sub_5:Test (Best Model) - Loss: 1.0876 - Accuracy: 0.4559 - F1: 0.3326
sub_12:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.3824 - F1: 0.2972
sub_9:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.4058 - F1: 0.2795
sub_8:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3088 - F1: 0.1877
sub_15:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.2647 - F1: 0.1059
sub_13:Test (Best Model) - Loss: 1.3297 - Accuracy: 0.3529 - F1: 0.2201
sub_10:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.4348 - F1: 0.3959
sub_1:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.3676 - F1: 0.2806
sub_3:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.2899 - F1: 0.2167
sub_4:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3768 - F1: 0.2995
sub_9:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2794 - F1: 0.1401
sub_8:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.2647 - F1: 0.1047
sub_15:Test (Best Model) - Loss: 1.2267 - Accuracy: 0.3676 - F1: 0.2942
sub_9:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.3824 - F1: 0.2972
sub_8:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.2647 - F1: 0.1047
sub_4:Test (Best Model) - Loss: 1.2501 - Accuracy: 0.3913 - F1: 0.3059
sub_5:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.6324 - F1: 0.5611
sub_14:Test (Best Model) - Loss: 0.7873 - Accuracy: 0.6176 - F1: 0.4903
sub_1:Test (Best Model) - Loss: 1.1930 - Accuracy: 0.4265 - F1: 0.3686
sub_8:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3824 - F1: 0.2585
sub_3:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3043 - F1: 0.1905
sub_5:Test (Best Model) - Loss: 1.2203 - Accuracy: 0.3676 - F1: 0.3138
sub_14:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.5294 - F1: 0.3462
sub_8:Test (Best Model) - Loss: 1.1075 - Accuracy: 0.4559 - F1: 0.3693
sub_14:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.6912 - F1: 0.6599
sub_27:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.2754 - F1: 0.1347
sub_28:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2794 - F1: 0.1584
sub_25:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3623 - F1: 0.2374
sub_17:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.2754 - F1: 0.1347
sub_20:Test (Best Model) - Loss: 1.2413 - Accuracy: 0.2647 - F1: 0.1200
sub_16:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2647 - F1: 0.1059
sub_21:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.3824 - F1: 0.2500
sub_24:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2500 - F1: 0.1354
sub_19:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3235 - F1: 0.2221
sub_23:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.3623 - F1: 0.2872
sub_29:Test (Best Model) - Loss: 1.2456 - Accuracy: 0.3676 - F1: 0.2937
sub_18:Test (Best Model) - Loss: 1.0910 - Accuracy: 0.5507 - F1: 0.5508
sub_28:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2754 - F1: 0.1359
sub_29:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3088 - F1: 0.1967
sub_24:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2500 - F1: 0.1149
sub_26:Test (Best Model) - Loss: 1.2907 - Accuracy: 0.3333 - F1: 0.1999
sub_22:Test (Best Model) - Loss: 1.2094 - Accuracy: 0.2941 - F1: 0.2537
sub_16:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.5362 - F1: 0.5009
sub_17:Test (Best Model) - Loss: 1.1681 - Accuracy: 0.5362 - F1: 0.5009
sub_23:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.3768 - F1: 0.2878
sub_24:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2206 - F1: 0.1082
sub_28:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2647 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.3382 - F1: 0.2139
sub_19:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3529 - F1: 0.2787
sub_29:Test (Best Model) - Loss: 1.1912 - Accuracy: 0.3529 - F1: 0.2899
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2206 - F1: 0.1266
sub_18:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.3768 - F1: 0.3033
sub_16:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.2602 - Accuracy: 0.3824 - F1: 0.3002
sub_25:Test (Best Model) - Loss: 1.4383 - Accuracy: 0.2609 - F1: 0.1084
sub_27:Test (Best Model) - Loss: 1.2690 - Accuracy: 0.4058 - F1: 0.3333
sub_22:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.3235 - F1: 0.2803
sub_17:Test (Best Model) - Loss: 1.2690 - Accuracy: 0.4058 - F1: 0.3333
sub_29:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.3382 - F1: 0.2427
sub_24:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.2794 - F1: 0.1322
sub_26:Test (Best Model) - Loss: 1.3184 - Accuracy: 0.3913 - F1: 0.3029
sub_23:Test (Best Model) - Loss: 1.2467 - Accuracy: 0.3768 - F1: 0.3275
sub_28:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3386 - Accuracy: 0.3623 - F1: 0.2716
sub_16:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.3676 - F1: 0.2410
sub_25:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3043 - F1: 0.1973
sub_19:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.3235 - F1: 0.2250
sub_17:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3043 - F1: 0.1973
sub_24:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3768 - F1: 0.2878
sub_29:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.4412 - F1: 0.4015
sub_16:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.3623 - F1: 0.2830
sub_22:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.2353 - F1: 0.1777
sub_20:Test (Best Model) - Loss: 1.1791 - Accuracy: 0.4118 - F1: 0.3300
sub_25:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2609 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.2794 - F1: 0.1431
sub_24:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2500 - F1: 0.1000
sub_26:Test (Best Model) - Loss: 1.1705 - Accuracy: 0.4493 - F1: 0.3899
sub_23:Test (Best Model) - Loss: 1.3576 - Accuracy: 0.2464 - F1: 0.1090
sub_27:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3043 - F1: 0.1963
sub_17:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3043 - F1: 0.1963
sub_16:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2647 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3235 - F1: 0.2209
sub_20:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3676 - F1: 0.2821
sub_19:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.2647 - F1: 0.1125
sub_29:Test (Best Model) - Loss: 1.2679 - Accuracy: 0.3971 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 1.3608 - Accuracy: 0.3382 - F1: 0.2179
sub_24:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2794 - F1: 0.1905
sub_18:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.3824 - F1: 0.2972
sub_26:Test (Best Model) - Loss: 1.3358 - Accuracy: 0.3913 - F1: 0.3029
sub_22:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.4559 - F1: 0.3021
sub_25:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.3676 - F1: 0.3099
sub_23:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.3824 - F1: 0.2972
sub_20:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.2647 - F1: 0.1200
sub_24:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2500 - F1: 0.1012
sub_21:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2794 - F1: 0.1513
sub_16:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3382 - F1: 0.2404
sub_28:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.3623 - F1: 0.2730
sub_27:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.3623 - F1: 0.2730
sub_26:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.2609 - F1: 0.1200
sub_29:Test (Best Model) - Loss: 1.2254 - Accuracy: 0.6324 - F1: 0.5584
sub_21:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.2664 - Accuracy: 0.3824 - F1: 0.2972
sub_16:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.0509 - Accuracy: 0.4265 - F1: 0.3301
sub_17:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2609 - F1: 0.1047
sub_27:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2609 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.3676 - F1: 0.2937
sub_22:Test (Best Model) - Loss: 1.3261 - Accuracy: 0.3333 - F1: 0.2424
sub_28:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.2206 - F1: 0.1056
sub_29:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.2794 - F1: 0.1392
sub_20:Test (Best Model) - Loss: 1.1151 - Accuracy: 0.4118 - F1: 0.3432
sub_24:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3382 - F1: 0.2274
sub_25:Test (Best Model) - Loss: 1.3133 - Accuracy: 0.2647 - F1: 0.1200
sub_19:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.2794 - F1: 0.1392
sub_16:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.4118 - F1: 0.2735
sub_27:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2609 - F1: 0.1139
sub_26:Test (Best Model) - Loss: 1.2097 - Accuracy: 0.3824 - F1: 0.3002
sub_17:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2609 - F1: 0.1139
sub_28:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2647 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 1.3175 - Accuracy: 0.3971 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.4559 - F1: 0.3205
sub_18:Test (Best Model) - Loss: 1.1693 - Accuracy: 0.4265 - F1: 0.3761
sub_27:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.3768 - F1: 0.2878
sub_17:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.3768 - F1: 0.2878
sub_28:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.4412 - F1: 0.3737
sub_21:Test (Best Model) - Loss: 1.1947 - Accuracy: 0.5294 - F1: 0.3776
sub_22:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.3768 - F1: 0.2939
sub_24:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2794 - F1: 0.1322
sub_25:Test (Best Model) - Loss: 1.3026 - Accuracy: 0.3971 - F1: 0.3321
sub_16:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2941 - F1: 0.1649
sub_23:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.3382 - F1: 0.2719
sub_20:Test (Best Model) - Loss: 0.9729 - Accuracy: 0.5588 - F1: 0.5189
sub_27:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.2754 - F1: 0.1424
sub_17:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.2754 - F1: 0.1424
sub_19:Test (Best Model) - Loss: 1.2324 - Accuracy: 0.3824 - F1: 0.3163
sub_28:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3824 - F1: 0.2650
sub_26:Test (Best Model) - Loss: 1.2980 - Accuracy: 0.4853 - F1: 0.4388
sub_16:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3971 - F1: 0.3266
sub_27:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.1364 - Accuracy: 0.3971 - F1: 0.3125
sub_25:Test (Best Model) - Loss: 1.2152 - Accuracy: 0.4706 - F1: 0.4168
sub_17:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.1047
sub_28:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2647 - F1: 0.1047
sub_19:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.4118 - F1: 0.3511
sub_29:Test (Best Model) - Loss: 0.9342 - Accuracy: 0.5072 - F1: 0.4432
sub_16:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_21:Test (Best Model) - Loss: 1.2701 - Accuracy: 0.5000 - F1: 0.4293
sub_24:Test (Best Model) - Loss: 1.1542 - Accuracy: 0.3824 - F1: 0.2421
sub_23:Test (Best Model) - Loss: 1.2642 - Accuracy: 0.3824 - F1: 0.3063
sub_25:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.2647 - F1: 0.1139
sub_26:Test (Best Model) - Loss: 1.1408 - Accuracy: 0.4559 - F1: 0.4157
sub_20:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.5294 - F1: 0.4435
sub_18:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.4265 - F1: 0.3732
sub_28:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.5147 - F1: 0.3378
sub_19:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3382 - F1: 0.2682
sub_22:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.4058 - F1: 0.3322
sub_21:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.5000 - F1: 0.3304
sub_16:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2794 - F1: 0.1581
sub_25:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3188 - F1: 0.1925
sub_28:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3088 - F1: 0.1967
sub_18:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.2647 - F1: 0.1262
sub_29:Test (Best Model) - Loss: 1.2438 - Accuracy: 0.4493 - F1: 0.4130
sub_22:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.3768 - F1: 0.2878
sub_19:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.4265 - F1: 0.3441
sub_26:Test (Best Model) - Loss: 1.1907 - Accuracy: 0.3824 - F1: 0.2972
sub_21:Test (Best Model) - Loss: 1.3070 - Accuracy: 0.5147 - F1: 0.3733
sub_27:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3824 - F1: 0.2642
sub_18:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2647 - F1: 0.1111
sub_20:Test (Best Model) - Loss: 1.2084 - Accuracy: 0.4853 - F1: 0.3901
sub_24:Test (Best Model) - Loss: 1.0729 - Accuracy: 0.5735 - F1: 0.5133
sub_17:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3824 - F1: 0.2642
sub_25:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.6029 - F1: 0.5061
sub_29:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2609 - F1: 0.1034
sub_19:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.3529 - F1: 0.2703
sub_16:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.2794 - F1: 0.1431
sub_22:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.2754 - F1: 0.1312
sub_21:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.2384 - Accuracy: 0.5797 - F1: 0.5085
sub_27:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_18:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.3824 - F1: 0.3139
sub_19:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2647 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 1.2664 - Accuracy: 0.4118 - F1: 0.3511
sub_22:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.2647 - F1: 0.1047
sub_23:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2647 - F1: 0.1047
sub_26:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2647 - F1: 0.1047
sub_17:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2647 - F1: 0.1047
sub_20:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.2609 - F1: 0.1084
sub_22:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.4058 - F1: 0.3169
sub_18:Test (Best Model) - Loss: 1.2778 - Accuracy: 0.4118 - F1: 0.3534
sub_19:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.2647 - F1: 0.1169
sub_21:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.3971 - F1: 0.2684
sub_24:Test (Best Model) - Loss: 1.1440 - Accuracy: 0.4706 - F1: 0.3399
sub_23:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.3913 - F1: 0.2573
sub_27:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.3971 - F1: 0.3250
sub_22:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2647 - F1: 0.1047
sub_29:Test (Best Model) - Loss: 1.3144 - Accuracy: 0.3623 - F1: 0.2716
sub_17:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.3971 - F1: 0.3250
sub_21:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2647 - F1: 0.1047
sub_25:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.4706 - F1: 0.3475
sub_23:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.3768 - F1: 0.2878
sub_19:Test (Best Model) - Loss: 1.3325 - Accuracy: 0.3971 - F1: 0.3434
sub_26:Test (Best Model) - Loss: 1.1473 - Accuracy: 0.5294 - F1: 0.4958
sub_22:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3235 - F1: 0.1971
sub_20:Test (Best Model) - Loss: 1.2278 - Accuracy: 0.5652 - F1: 0.5636
sub_18:Test (Best Model) - Loss: 1.2459 - Accuracy: 0.4559 - F1: 0.4199
sub_26:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3676 - F1: 0.2473
sub_25:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.4706 - F1: 0.3206
sub_21:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.2941 - F1: 0.1541
sub_22:Test (Best Model) - Loss: 1.1846 - Accuracy: 0.3824 - F1: 0.3002
sub_26:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.4559 - F1: 0.2981
sub_25:Test (Best Model) - Loss: 1.2160 - Accuracy: 0.5294 - F1: 0.4908
sub_21:Test (Best Model) - Loss: 1.3323 - Accuracy: 0.2941 - F1: 0.1601
sub_20:Test (Best Model) - Loss: 1.0615 - Accuracy: 0.7246 - F1: 0.7188
sub_20:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.5217 - F1: 0.3932
sub_26:Test (Best Model) - Loss: 1.1429 - Accuracy: 0.4118 - F1: 0.3371
sub_20:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.4058 - F1: 0.3408

=== Summary Results ===

acc: 34.80 ± 4.06
F1: 23.63 ± 5.64
acc-in: 40.28 ± 4.93
F1-in: 28.62 ± 6.33
runing time: 1790.23 seconds
