lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.3529 - F1: 0.3306
sub_1:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.2941 - F1: 0.3017
sub_1:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2353 - F1: 0.2429
sub_1:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2647 - F1: 0.2744
sub_1:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2941 - F1: 0.2745
sub_1:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2754 - F1: 0.2884
sub_1:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3188 - F1: 0.2965
sub_1:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3188 - F1: 0.3103
sub_1:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.3043 - F1: 0.3020
sub_1:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2174 - F1: 0.2279
sub_1:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2941 - F1: 0.2933
sub_1:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2794 - F1: 0.2656
sub_1:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.2153
sub_1:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2353 - F1: 0.2458
sub_1:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2647 - F1: 0.2462
sub_2:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2899 - F1: 0.2880
sub_2:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.2029 - F1: 0.2068
sub_2:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2464 - F1: 0.2557
sub_2:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2899 - F1: 0.2922
sub_2:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.2684
sub_2:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2353 - F1: 0.2169
sub_2:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.1618 - F1: 0.1617
sub_2:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.1765 - F1: 0.1773
sub_2:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3529 - F1: 0.3401
sub_2:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.1912 - F1: 0.1865
sub_2:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2899 - F1: 0.2722
sub_2:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2174 - F1: 0.2060
sub_2:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3043 - F1: 0.3011
sub_2:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.1884 - F1: 0.1722
sub_2:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2174 - F1: 0.2025
sub_3:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2353 - F1: 0.2018
sub_3:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2206 - F1: 0.2122
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2059 - F1: 0.2069
sub_3:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.2353 - F1: 0.2332
sub_3:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2206 - F1: 0.1925
sub_3:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2319 - F1: 0.2263
sub_3:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.1739 - F1: 0.1636
sub_3:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2319 - F1: 0.2218
sub_3:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2319 - F1: 0.2300
sub_3:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2464 - F1: 0.2446
sub_3:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2754 - F1: 0.2707
sub_3:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2609 - F1: 0.2518
sub_3:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.1739 - F1: 0.1669
sub_3:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.1739 - F1: 0.1781
sub_3:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2464 - F1: 0.2366
sub_4:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3043 - F1: 0.2906
sub_4:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2609 - F1: 0.2555
sub_4:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2464 - F1: 0.2307
sub_4:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.3478 - F1: 0.3273
sub_4:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3333 - F1: 0.3297
sub_4:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3623 - F1: 0.3579
sub_4:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3043 - F1: 0.2966
sub_4:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.4638 - F1: 0.4606
sub_4:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.4058 - F1: 0.3939
sub_4:Test (Best Model) - Loss: 1.3754 - Accuracy: 0.3478 - F1: 0.3494
sub_4:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2464 - F1: 0.2010
sub_4:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3768 - F1: 0.3555
sub_4:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.2609 - F1: 0.2419
sub_4:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2754 - F1: 0.2747
sub_4:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.3768 - F1: 0.3427
sub_5:Test (Best Model) - Loss: 1.3921 - Accuracy: 0.3382 - F1: 0.3096
sub_5:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.3676 - F1: 0.3616
sub_5:Test (Best Model) - Loss: 1.4076 - Accuracy: 0.3529 - F1: 0.3735
sub_5:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.3824 - F1: 0.3677
sub_5:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.2500 - F1: 0.2348
sub_5:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3382 - F1: 0.3254
sub_5:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.3235 - F1: 0.3289
sub_5:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3971 - F1: 0.3952
sub_5:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3971 - F1: 0.3858
sub_5:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.4265 - F1: 0.4148
sub_5:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2647 - F1: 0.2643
sub_5:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3529 - F1: 0.3401
sub_5:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3235 - F1: 0.3197
sub_5:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.3235 - F1: 0.3213
sub_5:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3529 - F1: 0.3341
sub_6:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2206 - F1: 0.2057
sub_6:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3088 - F1: 0.3114
sub_6:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3382 - F1: 0.3057
sub_6:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2500 - F1: 0.1917
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2794 - F1: 0.2611
sub_6:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2174 - F1: 0.2119
sub_6:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2319 - F1: 0.2301
sub_6:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.2464 - F1: 0.2404
sub_6:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.1884 - F1: 0.1838
sub_6:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.3043 - F1: 0.2894
sub_6:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2464 - F1: 0.2473
sub_6:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2029 - F1: 0.1913
sub_6:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2899 - F1: 0.2879
sub_6:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3043 - F1: 0.2951
sub_6:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2609 - F1: 0.2375
sub_7:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3088 - F1: 0.2963
sub_7:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2941 - F1: 0.2758
sub_7:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3824 - F1: 0.3694
sub_7:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.3824 - F1: 0.3787
sub_7:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3529 - F1: 0.3131
sub_7:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2500 - F1: 0.2212
sub_7:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.4118 - F1: 0.4003
sub_7:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2353 - F1: 0.2108
sub_7:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3235 - F1: 0.3203
sub_7:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.4265 - F1: 0.4018
sub_7:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3529 - F1: 0.3334
sub_7:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2941 - F1: 0.2882
sub_7:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.3088 - F1: 0.2870
sub_7:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2941 - F1: 0.2757
sub_7:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3235 - F1: 0.2858
sub_8:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.2580
sub_8:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.3088 - F1: 0.3215
sub_8:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2353 - F1: 0.2308
sub_8:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2206 - F1: 0.2201
sub_8:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2500 - F1: 0.2583
sub_8:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.3382 - F1: 0.3213
sub_8:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2059 - F1: 0.2071
sub_8:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2500 - F1: 0.2367
sub_8:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2206 - F1: 0.2124
sub_8:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2206 - F1: 0.2097
sub_8:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2059 - F1: 0.1999
sub_8:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2500 - F1: 0.2453
sub_8:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.2500 - F1: 0.2454
sub_8:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2206 - F1: 0.2048
sub_8:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2353 - F1: 0.2254
sub_9:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3088 - F1: 0.3144
sub_9:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2794 - F1: 0.2804
sub_9:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.3088 - F1: 0.3193
sub_9:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2941 - F1: 0.3113
sub_9:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2794 - F1: 0.2906
sub_9:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2794 - F1: 0.2854
sub_9:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2794 - F1: 0.2988
sub_9:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2500 - F1: 0.2486
sub_9:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.2794 - F1: 0.2770
sub_9:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2647 - F1: 0.2690
sub_9:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2206 - F1: 0.2037
sub_9:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.3382 - F1: 0.3325
sub_9:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2647 - F1: 0.2428
sub_9:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2059 - F1: 0.2141
sub_9:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2647 - F1: 0.2558
sub_10:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2500 - F1: 0.2434
sub_10:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2500 - F1: 0.2448
sub_10:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.2665
sub_10:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2500 - F1: 0.2510
sub_10:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2206 - F1: 0.2118
sub_10:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2206 - F1: 0.2221
sub_10:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.2206 - F1: 0.1981
sub_10:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.3382 - F1: 0.3360
sub_10:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2794 - F1: 0.2671
sub_10:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.1618 - F1: 0.1590
sub_10:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2319 - F1: 0.2311
sub_10:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2174 - F1: 0.1898
sub_10:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2319 - F1: 0.2279
sub_10:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2754 - F1: 0.2585
sub_10:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.1594 - F1: 0.1409
sub_11:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2609 - F1: 0.2417
sub_11:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.3188 - F1: 0.3153
sub_11:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2609 - F1: 0.2493
sub_11:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.2610
sub_11:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2319 - F1: 0.2287
sub_11:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3043 - F1: 0.2898
sub_11:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3333 - F1: 0.3276
sub_11:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3623 - F1: 0.3544
sub_11:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2754 - F1: 0.2728
sub_11:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3623 - F1: 0.3445
sub_11:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.1884 - F1: 0.1665
sub_11:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2464 - F1: 0.2070
sub_11:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.3478 - F1: 0.3373
sub_11:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2754 - F1: 0.2738
sub_11:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3188 - F1: 0.3098
sub_12:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3235 - F1: 0.3079
sub_12:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.1912 - F1: 0.1840
sub_12:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.2296
sub_12:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2500 - F1: 0.2395
sub_12:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.2041
sub_12:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2464 - F1: 0.2449
sub_12:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3188 - F1: 0.3307
sub_12:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2899 - F1: 0.2788
sub_12:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.2319 - F1: 0.2051
sub_12:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2899 - F1: 0.2897
sub_12:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3382 - F1: 0.3244
sub_12:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3235 - F1: 0.2798
sub_12:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.2631
sub_12:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2794 - F1: 0.2736
sub_12:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3235 - F1: 0.2840
sub_13:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.1912 - F1: 0.1828
sub_13:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2353 - F1: 0.2285
sub_13:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2794 - F1: 0.2824
sub_13:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3529 - F1: 0.3535
sub_13:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2206 - F1: 0.2204
sub_13:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2029 - F1: 0.1749
sub_13:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2754 - F1: 0.2621
sub_13:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2609 - F1: 0.2317
sub_13:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2754 - F1: 0.2806
sub_13:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2464 - F1: 0.2323
sub_13:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2794 - F1: 0.2500
sub_13:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2794 - F1: 0.2433
sub_13:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.2686
sub_13:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.3235 - F1: 0.3314
sub_13:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2941 - F1: 0.2846
sub_14:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2353 - F1: 0.2255
sub_14:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2941 - F1: 0.3104
sub_14:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2500 - F1: 0.2612
sub_14:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2059 - F1: 0.2161
sub_14:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.1765 - F1: 0.1544
sub_14:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.1912 - F1: 0.1805
sub_14:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2059 - F1: 0.2034
sub_14:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.3382 - F1: 0.3376
sub_14:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2794 - F1: 0.2798
sub_14:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.3088 - F1: 0.2962
sub_14:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.1765 - F1: 0.1628
sub_14:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2941 - F1: 0.2722
sub_14:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2206 - F1: 0.2102
sub_14:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3088 - F1: 0.3011
sub_14:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.3529 - F1: 0.3100
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2206 - F1: 0.2108
sub_15:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2941 - F1: 0.2923
sub_15:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2794 - F1: 0.2983
sub_15:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.3529 - F1: 0.3754
sub_15:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2941 - F1: 0.3131
sub_15:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3529 - F1: 0.3623
sub_15:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.3382 - F1: 0.3431
sub_15:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.4118 - F1: 0.4018
sub_15:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3235 - F1: 0.3202
sub_15:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.3382 - F1: 0.3362
sub_15:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3971 - F1: 0.4036
sub_15:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3824 - F1: 0.3668
sub_15:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.4265 - F1: 0.4314
sub_15:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2941 - F1: 0.2941
sub_15:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3971 - F1: 0.3741
sub_16:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2500 - F1: 0.1959
sub_16:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2353 - F1: 0.2306
sub_16:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2794 - F1: 0.2798
sub_16:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2059 - F1: 0.1984
sub_16:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.3382 - F1: 0.3107
sub_16:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.2558
sub_16:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2353 - F1: 0.2333
sub_16:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.1912 - F1: 0.2039
sub_16:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2794 - F1: 0.2582
sub_16:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2206 - F1: 0.2209
sub_16:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3088 - F1: 0.3074
sub_16:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3382 - F1: 0.3277
sub_16:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2500 - F1: 0.2454
sub_16:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2500 - F1: 0.2490
sub_16:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2500 - F1: 0.2320
sub_17:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.2221
sub_17:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2899 - F1: 0.2715
sub_17:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2899 - F1: 0.2676
sub_17:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2464 - F1: 0.2395
sub_17:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3043 - F1: 0.2638
sub_17:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3333 - F1: 0.3310
sub_17:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.3188 - F1: 0.2789
sub_17:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2464 - F1: 0.2384
sub_17:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3188 - F1: 0.2828
sub_17:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2464 - F1: 0.2348
sub_17:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3529 - F1: 0.3517
sub_17:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3529 - F1: 0.3480
sub_17:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.3235 - F1: 0.2984
sub_17:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3088 - F1: 0.2965
sub_17:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2941 - F1: 0.2866
sub_18:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3188 - F1: 0.3024
sub_18:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2609 - F1: 0.2658
sub_18:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2899 - F1: 0.2831
sub_18:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2464 - F1: 0.2313
sub_18:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3043 - F1: 0.3170
sub_18:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.3235 - F1: 0.3322
sub_18:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2794 - F1: 0.2774
sub_18:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.2500 - F1: 0.2519
sub_18:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.3088 - F1: 0.2970
sub_18:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2794 - F1: 0.2728
sub_18:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2500 - F1: 0.2436
sub_18:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2206 - F1: 0.2181
sub_18:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3382 - F1: 0.3436
sub_18:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2941 - F1: 0.2857
sub_18:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2647 - F1: 0.2484
sub_19:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2794 - F1: 0.2605
sub_19:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.2341
sub_19:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2941 - F1: 0.2810
sub_19:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.3529 - F1: 0.3416
sub_19:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2794 - F1: 0.2786
sub_19:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2647 - F1: 0.2301
sub_19:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3088 - F1: 0.3163
sub_19:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.3382 - F1: 0.3369
sub_19:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.3382 - F1: 0.3298
sub_19:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2794 - F1: 0.2640
sub_19:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3088 - F1: 0.3023
sub_19:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.2570
sub_19:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3382 - F1: 0.3377
sub_19:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2206 - F1: 0.2236
sub_19:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3824 - F1: 0.3618
sub_20:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3382 - F1: 0.3237
sub_20:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.2430
sub_20:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3382 - F1: 0.3301
sub_20:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2353 - F1: 0.2393
sub_20:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2353 - F1: 0.2235
sub_20:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.1912 - F1: 0.1869
sub_20:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3382 - F1: 0.3399
sub_20:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.2718
sub_20:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.1912 - F1: 0.1854
sub_20:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.2463
sub_20:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.2609 - F1: 0.2659
sub_20:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3768 - F1: 0.3644
sub_20:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2754 - F1: 0.2806
sub_20:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2609 - F1: 0.2702
sub_20:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3188 - F1: 0.3144
sub_21:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3088 - F1: 0.2731
sub_21:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2647 - F1: 0.2308
sub_21:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3382 - F1: 0.3374
sub_21:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.1912 - F1: 0.1949
sub_21:Test (Best Model) - Loss: 1.3954 - Accuracy: 0.2206 - F1: 0.2081
sub_21:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.1471 - F1: 0.1354
sub_21:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.3235 - F1: 0.3076
sub_21:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2500 - F1: 0.2270
sub_21:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2794 - F1: 0.2755
sub_21:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.3235 - F1: 0.3223
sub_21:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3235 - F1: 0.3007
sub_21:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.3529 - F1: 0.3329
sub_21:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2206 - F1: 0.2330
sub_21:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2794 - F1: 0.2731
sub_21:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3235 - F1: 0.3148
sub_22:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.1912 - F1: 0.1806
sub_22:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.2602
sub_22:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2647 - F1: 0.2609
sub_22:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2647 - F1: 0.2642
sub_22:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2794 - F1: 0.2944
sub_22:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2464 - F1: 0.2354
sub_22:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2609 - F1: 0.2557
sub_22:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2174 - F1: 0.1800
sub_22:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2754 - F1: 0.2701
sub_22:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.3043 - F1: 0.2923
sub_22:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2794 - F1: 0.2691
sub_22:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.2644
sub_22:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2647 - F1: 0.2599
sub_22:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.3235 - F1: 0.3082
sub_22:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2794 - F1: 0.2442
sub_23:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2754 - F1: 0.2547
sub_23:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3333 - F1: 0.3262
sub_23:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2319 - F1: 0.2325
sub_23:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.3188 - F1: 0.3182
sub_23:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.1594 - F1: 0.1663
sub_23:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2941 - F1: 0.2788
sub_23:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2500 - F1: 0.2249
sub_23:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2647 - F1: 0.2632
sub_23:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2500 - F1: 0.2554
sub_23:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2059 - F1: 0.1857
sub_23:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2319 - F1: 0.2234
sub_23:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2464 - F1: 0.2340
sub_23:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3333 - F1: 0.3163
sub_23:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.2899 - F1: 0.2838
sub_23:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2754 - F1: 0.2441
sub_24:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3529 - F1: 0.3541
sub_24:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.2206 - F1: 0.2232
sub_24:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2794 - F1: 0.2787
sub_24:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.1912 - F1: 0.1798
sub_24:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3235 - F1: 0.3157
sub_24:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.2708
sub_24:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2059 - F1: 0.2085
sub_24:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2500 - F1: 0.2498
sub_24:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.1765 - F1: 0.1746
sub_24:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2941 - F1: 0.2809
sub_24:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.2941 - F1: 0.2875
sub_24:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.2206 - F1: 0.2281
sub_24:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2941 - F1: 0.2929
sub_24:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2353 - F1: 0.2353
sub_24:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2647 - F1: 0.2299
sub_25:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3333 - F1: 0.3030
sub_25:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2464 - F1: 0.2432
sub_25:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2754 - F1: 0.2588
sub_25:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2174 - F1: 0.1913
sub_25:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2174 - F1: 0.1928
sub_25:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.3235 - F1: 0.3179
sub_25:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.3676 - F1: 0.3539
sub_25:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.1912 - F1: 0.1871
sub_25:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3529 - F1: 0.3347
sub_25:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.1912 - F1: 0.1908
sub_25:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.2353 - F1: 0.2232
sub_25:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3382 - F1: 0.3149
sub_25:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2500 - F1: 0.2448
sub_25:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2500 - F1: 0.2451
sub_25:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2941 - F1: 0.2860
sub_26:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2899 - F1: 0.2692
sub_26:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3333 - F1: 0.3285
sub_26:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3623 - F1: 0.3528
sub_26:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.4203 - F1: 0.4149
sub_26:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3623 - F1: 0.3294
sub_26:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.4118 - F1: 0.3986
sub_26:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.2941 - F1: 0.3051
sub_26:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.3529 - F1: 0.3364
sub_26:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3529 - F1: 0.3452
sub_26:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.3088 - F1: 0.2817
sub_26:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.4559 - F1: 0.4510
sub_26:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3235 - F1: 0.3208
sub_26:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3824 - F1: 0.3685
sub_26:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.4559 - F1: 0.4636
sub_26:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3529 - F1: 0.3566
sub_27:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2609 - F1: 0.2221
sub_27:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2899 - F1: 0.2715
sub_27:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2899 - F1: 0.2676
sub_27:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2464 - F1: 0.2395
sub_27:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3043 - F1: 0.2638
sub_27:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3333 - F1: 0.3310
sub_27:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.3188 - F1: 0.2789
sub_27:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2464 - F1: 0.2384
sub_27:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3188 - F1: 0.2828
sub_27:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2464 - F1: 0.2348
sub_27:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3529 - F1: 0.3517
sub_27:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3529 - F1: 0.3480
sub_27:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.3235 - F1: 0.2984
sub_27:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3088 - F1: 0.2965
sub_27:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2941 - F1: 0.2866
sub_28:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2500 - F1: 0.2509
sub_28:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2353 - F1: 0.2182
sub_28:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2353 - F1: 0.2162
sub_28:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2941 - F1: 0.2839
sub_28:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.1618 - F1: 0.1473
sub_28:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3088 - F1: 0.2945
sub_28:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2941 - F1: 0.2905
sub_28:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.2206 - F1: 0.2192
sub_28:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2941 - F1: 0.2857
sub_28:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2794 - F1: 0.2670
sub_28:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.2535
sub_28:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3529 - F1: 0.3356
sub_28:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2206 - F1: 0.2144
sub_28:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3824 - F1: 0.3809
sub_28:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3382 - F1: 0.3168
sub_29:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.3529 - F1: 0.3709
sub_29:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.2794 - F1: 0.2830
sub_29:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.3382 - F1: 0.3380
sub_29:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.3529 - F1: 0.3733
sub_29:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.3382 - F1: 0.3602
sub_29:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3824 - F1: 0.3666
sub_29:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3382 - F1: 0.3342
sub_29:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3235 - F1: 0.3333
sub_29:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.4412 - F1: 0.4395
sub_29:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3235 - F1: 0.3159
sub_29:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.4493 - F1: 0.4382
sub_29:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2609 - F1: 0.2462
sub_29:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3478 - F1: 0.3514
sub_29:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3333 - F1: 0.3213
sub_29:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.4058 - F1: 0.3612

=== Summary Results ===

acc: 28.41 ± 3.51
F1: 27.50 ± 3.53
acc-in: 33.92 ± 3.95
F1-in: 32.29 ± 4.14
