lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.2794 - F1: 0.2801
sub_1:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2794 - F1: 0.2693
sub_1:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2500 - F1: 0.2206
sub_1:Test (Best Model) - Loss: 1.3422 - Accuracy: 0.3824 - F1: 0.3998
sub_1:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.3088 - F1: 0.3158
sub_1:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3333 - F1: 0.3213
sub_1:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3623 - F1: 0.3439
sub_1:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3623 - F1: 0.3546
sub_1:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3333 - F1: 0.3318
sub_1:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3478 - F1: 0.3614
sub_1:Test (Best Model) - Loss: 1.3461 - Accuracy: 0.3235 - F1: 0.2966
sub_1:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3824 - F1: 0.3790
sub_1:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2059 - F1: 0.1961
sub_1:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2941 - F1: 0.2657
sub_1:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.3235 - F1: 0.3169
sub_2:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.2174 - F1: 0.2165
sub_2:Test (Best Model) - Loss: 1.4043 - Accuracy: 0.2029 - F1: 0.1919
sub_2:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.2899 - F1: 0.2892
sub_2:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3043 - F1: 0.3082
sub_2:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2609 - F1: 0.2611
sub_2:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.2059 - F1: 0.1932
sub_2:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2206 - F1: 0.1809
sub_2:Test (Best Model) - Loss: 1.4009 - Accuracy: 0.2500 - F1: 0.2503
sub_2:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2353 - F1: 0.2285
sub_2:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.3088 - F1: 0.2976
sub_2:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2609 - F1: 0.2497
sub_2:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2319 - F1: 0.2272
sub_2:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2899 - F1: 0.2765
sub_2:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2319 - F1: 0.2263
sub_2:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2319 - F1: 0.2228
sub_3:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.2059 - F1: 0.1995
sub_3:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.2353 - F1: 0.2379
sub_3:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2353 - F1: 0.2312
sub_3:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2059 - F1: 0.2070
sub_3:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2059 - F1: 0.1887
sub_3:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.3043 - F1: 0.2765
sub_3:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2464 - F1: 0.2396
sub_3:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2899 - F1: 0.2939
sub_3:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3043 - F1: 0.3058
sub_3:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.3478 - F1: 0.3286
sub_3:Test (Best Model) - Loss: 1.4009 - Accuracy: 0.2609 - F1: 0.2389
sub_3:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3478 - F1: 0.3291
sub_3:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2029 - F1: 0.1882
sub_3:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.2029 - F1: 0.1996
sub_3:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.2319 - F1: 0.2137
sub_4:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.3478 - F1: 0.3557
sub_4:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3188 - F1: 0.3016
sub_4:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.2754 - F1: 0.2710
sub_4:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3913 - F1: 0.3799
sub_4:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3768 - F1: 0.3680
sub_4:Test (Best Model) - Loss: 1.3386 - Accuracy: 0.3333 - F1: 0.3219
sub_4:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.4058 - F1: 0.4187
sub_4:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.4058 - F1: 0.4082
sub_4:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3768 - F1: 0.3809
sub_4:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.3768 - F1: 0.3702
sub_4:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3043 - F1: 0.2327
sub_4:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.3478 - F1: 0.2851
sub_4:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.3333 - F1: 0.3501
sub_4:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3188 - F1: 0.2929
sub_4:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3333 - F1: 0.3197
sub_5:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.3676 - F1: 0.3356
sub_5:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3824 - F1: 0.3533
sub_5:Test (Best Model) - Loss: 1.4183 - Accuracy: 0.3676 - F1: 0.3771
sub_5:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3971 - F1: 0.4001
sub_5:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2647 - F1: 0.2500
sub_5:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.4118 - F1: 0.4054
sub_5:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3382 - F1: 0.3513
sub_5:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.4265 - F1: 0.4003
sub_5:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3382 - F1: 0.3276
sub_5:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.4559 - F1: 0.4569
sub_5:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3235 - F1: 0.3036
sub_5:Test (Best Model) - Loss: 1.3569 - Accuracy: 0.3088 - F1: 0.3206
sub_5:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3971 - F1: 0.3821
sub_5:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.3676 - F1: 0.3629
sub_5:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.4118 - F1: 0.3747
sub_6:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2500 - F1: 0.2336
sub_6:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2941 - F1: 0.2936
sub_6:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3088 - F1: 0.2923
sub_6:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.2794 - F1: 0.2843
sub_6:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3676 - F1: 0.3651
sub_6:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.4058 - F1: 0.3754
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3333 - F1: 0.3212
sub_6:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3333 - F1: 0.3065
sub_6:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.1884 - F1: 0.1416
sub_6:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.3188 - F1: 0.2876
sub_6:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3188 - F1: 0.3158
sub_6:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2609 - F1: 0.2742
sub_6:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2174 - F1: 0.2101
sub_6:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2609 - F1: 0.2546
sub_6:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.1884 - F1: 0.1604
sub_7:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.4118 - F1: 0.3966
sub_7:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.4118 - F1: 0.3787
sub_7:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.3382 - F1: 0.3264
sub_7:Test (Best Model) - Loss: 1.3383 - Accuracy: 0.4118 - F1: 0.4112
sub_7:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.4559 - F1: 0.4615
sub_7:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2794 - F1: 0.2580
sub_7:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.4118 - F1: 0.3950
sub_7:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3235 - F1: 0.3277
sub_7:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3971 - F1: 0.3813
sub_7:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3676 - F1: 0.3748
sub_7:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3235 - F1: 0.3117
sub_7:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.3382 - F1: 0.2972
sub_7:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3382 - F1: 0.3221
sub_7:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2941 - F1: 0.2676
sub_7:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2941 - F1: 0.2759
sub_8:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.2353 - F1: 0.2330
sub_8:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2794 - F1: 0.2467
sub_8:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.2059 - F1: 0.2054
sub_8:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.3676 - F1: 0.3613
sub_8:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.3088 - F1: 0.3187
sub_8:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3235 - F1: 0.2736
sub_8:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2206 - F1: 0.2140
sub_8:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2794 - F1: 0.2804
sub_8:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.2059 - F1: 0.2034
sub_8:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2206 - F1: 0.1978
sub_8:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.2353 - F1: 0.2220
sub_8:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2206 - F1: 0.2178
sub_8:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2059 - F1: 0.1795
sub_8:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.2794 - F1: 0.2742
sub_8:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2500 - F1: 0.2190
sub_9:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.4265 - F1: 0.4465
sub_9:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.2500 - F1: 0.2119
sub_9:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3676 - F1: 0.3871
sub_9:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.3971 - F1: 0.4223
sub_9:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3971 - F1: 0.4219
sub_9:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3235 - F1: 0.3347
sub_9:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3088 - F1: 0.3129
sub_9:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2353 - F1: 0.2370
sub_9:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3088 - F1: 0.3085
sub_9:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3088 - F1: 0.3016
sub_9:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.1912 - F1: 0.1573
sub_9:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.3088 - F1: 0.3012
sub_9:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2941 - F1: 0.3006
sub_9:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2794 - F1: 0.2710
sub_9:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3088 - F1: 0.3342
sub_10:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.2500 - F1: 0.2370
sub_10:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3382 - F1: 0.3414
sub_10:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.2059 - F1: 0.2001
sub_10:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3824 - F1: 0.3824
sub_10:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2500 - F1: 0.2421
sub_10:Test (Best Model) - Loss: 1.4055 - Accuracy: 0.1765 - F1: 0.1797
sub_10:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2353 - F1: 0.2153
sub_10:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.3235 - F1: 0.3025
sub_10:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.1471 - F1: 0.1393
sub_10:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2941 - F1: 0.2910
sub_10:Test (Best Model) - Loss: 1.4049 - Accuracy: 0.1739 - F1: 0.1702
sub_10:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2464 - F1: 0.2464
sub_10:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2464 - F1: 0.2517
sub_10:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.2319 - F1: 0.2176
sub_10:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.1014 - F1: 0.0833
sub_11:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.4058 - F1: 0.4131
sub_11:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2754 - F1: 0.2496
sub_11:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2464 - F1: 0.2322
sub_11:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.2899 - F1: 0.2728
sub_11:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2174 - F1: 0.1823
sub_11:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2754 - F1: 0.2556
sub_11:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3043 - F1: 0.2917
sub_11:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3188 - F1: 0.2891
sub_11:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.3333 - F1: 0.3060
sub_11:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3043 - F1: 0.2807
sub_11:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2899 - F1: 0.2458
sub_11:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.1884 - F1: 0.1633
sub_11:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.3478 - F1: 0.3371
sub_11:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2899 - F1: 0.2828
sub_11:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.2592
sub_12:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.2500 - F1: 0.2302
sub_12:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.3676 - F1: 0.3522
sub_12:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.4265 - F1: 0.4207
sub_12:Test (Best Model) - Loss: 1.3636 - Accuracy: 0.2941 - F1: 0.3025
sub_12:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3824 - F1: 0.3505
sub_12:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.3333 - F1: 0.3130
sub_12:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.3478 - F1: 0.3302
sub_12:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2464 - F1: 0.2424
sub_12:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2464 - F1: 0.1927
sub_12:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.3188 - F1: 0.3179
sub_12:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3529 - F1: 0.3264
sub_12:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3088 - F1: 0.2981
sub_12:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.3235 - F1: 0.3243
sub_12:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3382 - F1: 0.3141
sub_12:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3824 - F1: 0.3708
sub_13:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2941 - F1: 0.2908
sub_13:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.2941 - F1: 0.2931
sub_13:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2206 - F1: 0.2219
sub_13:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3382 - F1: 0.3452
sub_13:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.2647 - F1: 0.2845
sub_13:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.3043 - F1: 0.2494
sub_13:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2754 - F1: 0.2550
sub_13:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.1739 - F1: 0.1717
sub_13:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2899 - F1: 0.2529
sub_13:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.3623 - F1: 0.3543
sub_13:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2353 - F1: 0.2018
sub_13:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.3824 - F1: 0.3935
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2941 - F1: 0.2930
sub_13:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.2251
sub_13:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2794 - F1: 0.2736
sub_14:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2500 - F1: 0.2401
sub_14:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3088 - F1: 0.2979
sub_14:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2500 - F1: 0.2422
sub_14:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2647 - F1: 0.2906
sub_14:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.2647 - F1: 0.2173
sub_14:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.2941 - F1: 0.2804
sub_14:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2794 - F1: 0.2707
sub_14:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3235 - F1: 0.3233
sub_14:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.2294
sub_14:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.3235 - F1: 0.3199
sub_14:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2059 - F1: 0.2050
sub_14:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3529 - F1: 0.3099
sub_14:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2647 - F1: 0.2355
sub_14:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3235 - F1: 0.3103
sub_14:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2206 - F1: 0.1856
sub_15:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.3235 - F1: 0.3571
sub_15:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3088 - F1: 0.3027
sub_15:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.3382 - F1: 0.3413
sub_15:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3529 - F1: 0.3794
sub_15:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3235 - F1: 0.3553
sub_15:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.4118 - F1: 0.4222
sub_15:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3235 - F1: 0.3077
sub_15:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3676 - F1: 0.3743
sub_15:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.4412 - F1: 0.4293
sub_15:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.4412 - F1: 0.4493
sub_15:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.4118 - F1: 0.4344
sub_15:Test (Best Model) - Loss: 1.3480 - Accuracy: 0.3676 - F1: 0.3702
sub_15:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3971 - F1: 0.4026
sub_15:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.3382 - F1: 0.3418
sub_15:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.3088 - F1: 0.2977
sub_16:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3088 - F1: 0.2588
sub_16:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3676 - F1: 0.3672
sub_16:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.2941 - F1: 0.2737
sub_16:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.2941 - F1: 0.2764
sub_16:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3235 - F1: 0.2919
sub_16:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2794 - F1: 0.2716
sub_16:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.2794 - F1: 0.2808
sub_16:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2500 - F1: 0.2381
sub_16:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2794 - F1: 0.2545
sub_16:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.2353 - F1: 0.2411
sub_16:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.3235 - F1: 0.2973
sub_16:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.4265 - F1: 0.3819
sub_16:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3676 - F1: 0.3636
sub_16:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2059 - F1: 0.1946
sub_16:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.2941 - F1: 0.2561
sub_17:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3043 - F1: 0.2660
sub_17:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.3478 - F1: 0.2981
sub_17:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3333 - F1: 0.2821
sub_17:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3333 - F1: 0.3089
sub_17:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.4203 - F1: 0.3977
sub_17:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3478 - F1: 0.3269
sub_17:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3043 - F1: 0.2974
sub_17:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.3623 - F1: 0.3483
sub_17:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.3478 - F1: 0.3161
sub_17:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.2899 - F1: 0.2344
sub_17:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.3676 - F1: 0.3067
sub_17:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3382 - F1: 0.3293
sub_17:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.3676 - F1: 0.3083
sub_17:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3676 - F1: 0.3648
sub_17:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3824 - F1: 0.3533
sub_18:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.3623 - F1: 0.3584
sub_18:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3188 - F1: 0.3117
sub_18:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.2464 - F1: 0.2251
sub_18:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3043 - F1: 0.3250
sub_18:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.4058 - F1: 0.4050
sub_18:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2353 - F1: 0.2542
sub_18:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2206 - F1: 0.2211
sub_18:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2206 - F1: 0.2159
sub_18:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2353 - F1: 0.2408
sub_18:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2206 - F1: 0.2129
sub_18:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2500 - F1: 0.2154
sub_18:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.3235 - F1: 0.3017
sub_18:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.3088 - F1: 0.3204
sub_18:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2794 - F1: 0.2776
sub_18:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2353 - F1: 0.2245
sub_19:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.3676 - F1: 0.3176
sub_19:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2941 - F1: 0.2439
sub_19:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2500 - F1: 0.2185
sub_19:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.2206 - F1: 0.2015
sub_19:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2794 - F1: 0.2391
sub_19:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3824 - F1: 0.3452
sub_19:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3235 - F1: 0.3135
sub_19:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.3676 - F1: 0.3608
sub_19:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3382 - F1: 0.3040
sub_19:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3676 - F1: 0.3720
sub_19:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.2794 - F1: 0.2467
sub_19:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.3088 - F1: 0.2907
sub_19:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3235 - F1: 0.3220
sub_19:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.1912 - F1: 0.2013
sub_19:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.3382 - F1: 0.3144
sub_20:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.3824 - F1: 0.3323
sub_20:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3971 - F1: 0.4039
sub_20:Test (Best Model) - Loss: 1.3569 - Accuracy: 0.3235 - F1: 0.2899
sub_20:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2941 - F1: 0.2870
sub_20:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3676 - F1: 0.3622
sub_20:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.3235 - F1: 0.3149
sub_20:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.3676 - F1: 0.3713
sub_20:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3382 - F1: 0.3554
sub_20:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2794 - F1: 0.2547
sub_20:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3235 - F1: 0.3209
sub_20:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.3333 - F1: 0.3114
sub_20:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.4203 - F1: 0.4207
sub_20:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2174 - F1: 0.2064
sub_20:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3333 - F1: 0.3433
sub_20:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3623 - F1: 0.3821
sub_21:Test (Best Model) - Loss: 1.3550 - Accuracy: 0.3235 - F1: 0.3314
sub_21:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2500 - F1: 0.2373
sub_21:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.2941 - F1: 0.2626
sub_21:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3088 - F1: 0.2843
sub_21:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2794 - F1: 0.2709
sub_21:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3235 - F1: 0.3093
sub_21:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2353 - F1: 0.2075
sub_21:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2647 - F1: 0.2632
sub_21:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.3235 - F1: 0.3146
sub_21:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.4559 - F1: 0.4363
sub_21:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.3382 - F1: 0.3179
sub_21:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.3676 - F1: 0.3322
sub_21:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.2941 - F1: 0.2489
sub_21:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.4265 - F1: 0.4043
sub_21:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3088 - F1: 0.3076
sub_22:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3382 - F1: 0.3291
sub_22:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.3529 - F1: 0.3615
sub_22:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.2941 - F1: 0.3044
sub_22:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2941 - F1: 0.2955
sub_22:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2941 - F1: 0.2590
sub_22:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2754 - F1: 0.2626
sub_22:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.3043 - F1: 0.3055
sub_22:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.2174 - F1: 0.2197
sub_22:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.1884 - F1: 0.1453
sub_22:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2754 - F1: 0.2061
sub_22:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2794 - F1: 0.2932
sub_22:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2794 - F1: 0.2777
sub_22:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3676 - F1: 0.3631
sub_22:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2794 - F1: 0.2751
sub_22:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2794 - F1: 0.2922
sub_23:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3333 - F1: 0.3152
sub_23:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3768 - F1: 0.3803
sub_23:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.2609 - F1: 0.2260
sub_23:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3333 - F1: 0.3430
sub_23:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.3623 - F1: 0.3782
sub_23:Test (Best Model) - Loss: 1.3692 - Accuracy: 0.3529 - F1: 0.3559
sub_23:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3824 - F1: 0.3823
sub_23:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.3235 - F1: 0.3356
sub_23:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3529 - F1: 0.3183
sub_23:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.2941 - F1: 0.2936
sub_23:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2464 - F1: 0.1903
sub_23:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3188 - F1: 0.3129
sub_23:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3478 - F1: 0.3087
sub_23:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3188 - F1: 0.3053
sub_23:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2899 - F1: 0.2832
sub_24:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.2941 - F1: 0.2874
sub_24:Test (Best Model) - Loss: 1.3900 - Accuracy: 0.1765 - F1: 0.1664
sub_24:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.1912 - F1: 0.1551
sub_24:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3088 - F1: 0.3115
sub_24:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.2059 - F1: 0.1930
sub_24:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.1618 - F1: 0.1558
sub_24:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2500 - F1: 0.2527
sub_24:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2941 - F1: 0.2917
sub_24:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2500 - F1: 0.2436
sub_24:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.2647 - F1: 0.2549
sub_24:Test (Best Model) - Loss: 1.4059 - Accuracy: 0.1471 - F1: 0.1430
sub_24:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.1912 - F1: 0.1936
sub_24:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2941 - F1: 0.2914
sub_24:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.2353 - F1: 0.2174
sub_24:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2500 - F1: 0.2612
sub_25:Test (Best Model) - Loss: 1.3690 - Accuracy: 0.3333 - F1: 0.3301
sub_25:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.3913 - F1: 0.3726
sub_25:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3188 - F1: 0.3047
sub_25:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3623 - F1: 0.3394
sub_25:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2899 - F1: 0.2804
sub_25:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2941 - F1: 0.2817
sub_25:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3529 - F1: 0.3185
sub_25:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3235 - F1: 0.3088
sub_25:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.2647 - F1: 0.2357
sub_25:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.3824 - F1: 0.3517
sub_25:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.3382 - F1: 0.3531
sub_25:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3235 - F1: 0.2957
sub_25:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2206 - F1: 0.2075
sub_25:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3088 - F1: 0.2793
sub_25:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2206 - F1: 0.2078
sub_26:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3188 - F1: 0.2864
sub_26:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.4058 - F1: 0.4023
sub_26:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.3333 - F1: 0.3253
sub_26:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.4638 - F1: 0.4694
sub_26:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3478 - F1: 0.3419
sub_26:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.3382 - F1: 0.3512
sub_26:Test (Best Model) - Loss: 1.3484 - Accuracy: 0.3971 - F1: 0.4096
sub_26:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3088 - F1: 0.2956
sub_26:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3676 - F1: 0.3588
sub_26:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2500 - F1: 0.2434
sub_26:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.2941 - F1: 0.2606
sub_26:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3971 - F1: 0.3939
sub_26:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.3824 - F1: 0.3809
sub_26:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.4265 - F1: 0.4335
sub_26:Test (Best Model) - Loss: 1.3592 - Accuracy: 0.4265 - F1: 0.4576
sub_27:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3043 - F1: 0.2660
sub_27:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.3478 - F1: 0.2981
sub_27:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3333 - F1: 0.2821
sub_27:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3333 - F1: 0.3089
sub_27:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.4203 - F1: 0.3977
sub_27:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3478 - F1: 0.3269
sub_27:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3043 - F1: 0.2974
sub_27:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.3623 - F1: 0.3483
sub_27:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.3478 - F1: 0.3161
sub_27:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.2899 - F1: 0.2344
sub_27:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.3676 - F1: 0.3067
sub_27:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3382 - F1: 0.3293
sub_27:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.3676 - F1: 0.3083
sub_27:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3676 - F1: 0.3648
sub_27:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3824 - F1: 0.3533
sub_28:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.1765 - F1: 0.1837
sub_28:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2500 - F1: 0.2043
sub_28:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.1912 - F1: 0.1704
sub_28:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2794 - F1: 0.2897
sub_28:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.1471 - F1: 0.1189
sub_28:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2941 - F1: 0.2926
sub_28:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2794 - F1: 0.2408
sub_28:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.2647 - F1: 0.2411
sub_28:Test (Best Model) - Loss: 1.4005 - Accuracy: 0.2647 - F1: 0.2078
sub_28:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2794 - F1: 0.2420
sub_28:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2647 - F1: 0.2400
sub_28:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.3382 - F1: 0.2937
sub_28:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.1912 - F1: 0.1818
sub_28:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.4118 - F1: 0.4138
sub_28:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.3529 - F1: 0.3340
sub_29:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.3676 - F1: 0.3742
sub_29:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3382 - F1: 0.3443
sub_29:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.4118 - F1: 0.4126
sub_29:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.4853 - F1: 0.5101
sub_29:Test (Best Model) - Loss: 1.3368 - Accuracy: 0.3971 - F1: 0.4250
sub_29:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.4412 - F1: 0.4732
sub_29:Test (Best Model) - Loss: 1.3031 - Accuracy: 0.4559 - F1: 0.4618
sub_29:Test (Best Model) - Loss: 1.3261 - Accuracy: 0.3824 - F1: 0.3906
sub_29:Test (Best Model) - Loss: 1.3286 - Accuracy: 0.4118 - F1: 0.4354
sub_29:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.4118 - F1: 0.4216
sub_29:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4928 - F1: 0.4896
sub_29:Test (Best Model) - Loss: 1.2983 - Accuracy: 0.3768 - F1: 0.4012
sub_29:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.3478 - F1: 0.3442
sub_29:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.4638 - F1: 0.4606
sub_29:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.3478 - F1: 0.3619

=== Summary Results ===

acc: 30.99 ± 4.32
F1: 29.83 ± 4.55
acc-in: 36.88 ± 3.98
F1-in: 34.88 ± 4.30
