lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2941 - F1: 0.3062
sub_1:Test (Best Model) - Loss: 1.3440 - Accuracy: 0.4265 - F1: 0.4435
sub_1:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3529 - F1: 0.3591
sub_1:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3824 - F1: 0.3946
sub_1:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.3676 - F1: 0.3802
sub_1:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3333 - F1: 0.3268
sub_1:Test (Best Model) - Loss: 1.3235 - Accuracy: 0.3623 - F1: 0.3683
sub_1:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.4203 - F1: 0.4232
sub_1:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.3478 - F1: 0.3650
sub_1:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3333 - F1: 0.3285
sub_1:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.3676 - F1: 0.3395
sub_1:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3235 - F1: 0.2894
sub_1:Test (Best Model) - Loss: 1.3268 - Accuracy: 0.4265 - F1: 0.4386
sub_1:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.3676 - F1: 0.3547
sub_1:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3088 - F1: 0.2825
sub_2:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2319 - F1: 0.2240
sub_2:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2319 - F1: 0.2566
sub_2:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.2464 - F1: 0.2454
sub_2:Test (Best Model) - Loss: 1.4061 - Accuracy: 0.1884 - F1: 0.1931
sub_2:Test (Best Model) - Loss: 1.4086 - Accuracy: 0.2174 - F1: 0.1929
sub_2:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2500 - F1: 0.2567
sub_2:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2500 - F1: 0.2116
sub_2:Test (Best Model) - Loss: 1.4075 - Accuracy: 0.1912 - F1: 0.1621
sub_2:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2794 - F1: 0.2835
sub_2:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.2353 - F1: 0.2252
sub_2:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.3043 - F1: 0.2912
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2754 - F1: 0.2723
sub_2:Test (Best Model) - Loss: 1.4132 - Accuracy: 0.2174 - F1: 0.2089
sub_2:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2319 - F1: 0.2256
sub_2:Test (Best Model) - Loss: 1.3965 - Accuracy: 0.2754 - F1: 0.2696
sub_3:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2500 - F1: 0.2523
sub_3:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.3382 - F1: 0.3436
sub_3:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2941 - F1: 0.2918
sub_3:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2500 - F1: 0.2506
sub_3:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2941 - F1: 0.2682
sub_3:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2464 - F1: 0.2315
sub_3:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3188 - F1: 0.2889
sub_3:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2319 - F1: 0.2101
sub_3:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2319 - F1: 0.2147
sub_3:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2754 - F1: 0.2627
sub_3:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2609 - F1: 0.2523
sub_3:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2029 - F1: 0.1817
sub_3:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.2609 - F1: 0.2541
sub_3:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2464 - F1: 0.2352
sub_3:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.2609 - F1: 0.2497
sub_4:Test (Best Model) - Loss: 1.3356 - Accuracy: 0.3768 - F1: 0.3917
sub_4:Test (Best Model) - Loss: 1.3267 - Accuracy: 0.3478 - F1: 0.3682
sub_4:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3768 - F1: 0.3697
sub_4:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.3623 - F1: 0.3854
sub_4:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.4348 - F1: 0.4497
sub_4:Test (Best Model) - Loss: 1.3061 - Accuracy: 0.5072 - F1: 0.4861
sub_4:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3623 - F1: 0.3295
sub_4:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.3768 - F1: 0.3810
sub_4:Test (Best Model) - Loss: 1.2936 - Accuracy: 0.4348 - F1: 0.4449
sub_4:Test (Best Model) - Loss: 1.3418 - Accuracy: 0.3623 - F1: 0.3631
sub_4:Test (Best Model) - Loss: 1.3418 - Accuracy: 0.2609 - F1: 0.1989
sub_4:Test (Best Model) - Loss: 1.2965 - Accuracy: 0.3188 - F1: 0.2673
sub_4:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.4348 - F1: 0.4411
sub_4:Test (Best Model) - Loss: 1.3280 - Accuracy: 0.3623 - F1: 0.3229
sub_4:Test (Best Model) - Loss: 1.3091 - Accuracy: 0.3913 - F1: 0.3719
sub_5:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3971 - F1: 0.3936
sub_5:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.4118 - F1: 0.3710
sub_5:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.3824 - F1: 0.3810
sub_5:Test (Best Model) - Loss: 1.3128 - Accuracy: 0.5000 - F1: 0.4788
sub_5:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.3971 - F1: 0.3678
sub_5:Test (Best Model) - Loss: 1.3156 - Accuracy: 0.4559 - F1: 0.4766
sub_5:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3382 - F1: 0.3358
sub_5:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.5147 - F1: 0.5271
sub_5:Test (Best Model) - Loss: 1.2643 - Accuracy: 0.4412 - F1: 0.4121
sub_5:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.4118 - F1: 0.4204
sub_5:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.4412 - F1: 0.4493
sub_5:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.4265 - F1: 0.4276
sub_5:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3971 - F1: 0.4147
sub_5:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.3235 - F1: 0.2995
sub_5:Test (Best Model) - Loss: 1.2941 - Accuracy: 0.4559 - F1: 0.4270
sub_6:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.3382 - F1: 0.3296
sub_6:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3235 - F1: 0.3061
sub_6:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3971 - F1: 0.4161
sub_6:Test (Best Model) - Loss: 1.3038 - Accuracy: 0.3529 - F1: 0.3482
sub_6:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.3382 - F1: 0.3121
sub_6:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.2754 - F1: 0.2488
sub_6:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.2899 - F1: 0.2473
sub_6:Test (Best Model) - Loss: 1.3498 - Accuracy: 0.3478 - F1: 0.3326
sub_6:Test (Best Model) - Loss: 1.3665 - Accuracy: 0.3333 - F1: 0.3057
sub_6:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3043 - F1: 0.2797
sub_6:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.2899 - F1: 0.3077
sub_6:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3043 - F1: 0.2808
sub_6:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3188 - F1: 0.3383
sub_6:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.2899 - F1: 0.2959
sub_6:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.3333 - F1: 0.3271
sub_7:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.5441 - F1: 0.5385
sub_7:Test (Best Model) - Loss: 1.2778 - Accuracy: 0.4706 - F1: 0.4125
sub_7:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.3529 - F1: 0.3365
sub_7:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.4559 - F1: 0.4510
sub_7:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.3971 - F1: 0.3726
sub_7:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.3824 - F1: 0.3340
sub_7:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.3676 - F1: 0.3520
sub_7:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.3676 - F1: 0.3585
sub_7:Test (Best Model) - Loss: 1.3007 - Accuracy: 0.4853 - F1: 0.4877
sub_7:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.4706 - F1: 0.4630
sub_7:Test (Best Model) - Loss: 1.3324 - Accuracy: 0.3971 - F1: 0.3657
sub_7:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.2794 - F1: 0.2506
sub_7:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.4265 - F1: 0.4067
sub_7:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.3971 - F1: 0.3678
sub_7:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.2794 - F1: 0.2618
sub_8:Test (Best Model) - Loss: 1.3974 - Accuracy: 0.2059 - F1: 0.2215
sub_8:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.1765 - F1: 0.1685
sub_8:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2353 - F1: 0.2363
sub_8:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.2206 - F1: 0.2198
sub_8:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.3235 - F1: 0.2958
sub_8:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2206 - F1: 0.2024
sub_8:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.3088 - F1: 0.3137
sub_8:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3088 - F1: 0.3052
sub_8:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.1618 - F1: 0.1592
sub_8:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.3382 - F1: 0.3263
sub_8:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.3235 - F1: 0.3107
sub_8:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.2941 - F1: 0.3107
sub_8:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3235 - F1: 0.3268
sub_8:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3824 - F1: 0.3906
sub_8:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2794 - F1: 0.2652
sub_9:Test (Best Model) - Loss: 1.3078 - Accuracy: 0.3529 - F1: 0.3735
sub_9:Test (Best Model) - Loss: 1.3385 - Accuracy: 0.2941 - F1: 0.2851
sub_9:Test (Best Model) - Loss: 1.3154 - Accuracy: 0.4118 - F1: 0.4343
sub_9:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.3971 - F1: 0.4212
sub_9:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.2500 - F1: 0.2689
sub_9:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.4559 - F1: 0.4736
sub_9:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2941 - F1: 0.2845
sub_9:Test (Best Model) - Loss: 1.3316 - Accuracy: 0.3382 - F1: 0.3436
sub_9:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.4559 - F1: 0.4703
sub_9:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3235 - F1: 0.3418
sub_9:Test (Best Model) - Loss: 1.3480 - Accuracy: 0.3676 - F1: 0.3754
sub_9:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.3529 - F1: 0.3345
sub_9:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.2941 - F1: 0.3085
sub_9:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3676 - F1: 0.3739
sub_9:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.3382 - F1: 0.3459
sub_10:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2059 - F1: 0.2041
sub_10:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.3971 - F1: 0.3625
sub_10:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3529 - F1: 0.3386
sub_10:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.1912 - F1: 0.1919
sub_10:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.1912 - F1: 0.1885
sub_10:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3235 - F1: 0.3047
sub_10:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2500 - F1: 0.2393
sub_10:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.1912 - F1: 0.1839
sub_10:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2794 - F1: 0.2695
sub_10:Test (Best Model) - Loss: 1.4167 - Accuracy: 0.1912 - F1: 0.1759
sub_10:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.2899 - F1: 0.2897
sub_10:Test (Best Model) - Loss: 1.4000 - Accuracy: 0.2754 - F1: 0.2960
sub_10:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2899 - F1: 0.2839
sub_10:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2754 - F1: 0.2678
sub_10:Test (Best Model) - Loss: 1.4170 - Accuracy: 0.2174 - F1: 0.2069
sub_11:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.3478 - F1: 0.3201
sub_11:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.3333 - F1: 0.3289
sub_11:Test (Best Model) - Loss: 1.3428 - Accuracy: 0.2754 - F1: 0.2679
sub_11:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.2899 - F1: 0.2637
sub_11:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2029 - F1: 0.1748
sub_11:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.3333 - F1: 0.2859
sub_11:Test (Best Model) - Loss: 1.3342 - Accuracy: 0.3623 - F1: 0.3388
sub_11:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4058 - F1: 0.3900
sub_11:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.3768 - F1: 0.3709
sub_11:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.3188 - F1: 0.2860
sub_11:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2899 - F1: 0.2527
sub_11:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3188 - F1: 0.3090
sub_11:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3333 - F1: 0.3367
sub_11:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3333 - F1: 0.3199
sub_11:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2609 - F1: 0.2368
sub_12:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.4118 - F1: 0.3767
sub_12:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.4118 - F1: 0.4144
sub_12:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.3529 - F1: 0.3691
sub_12:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.3824 - F1: 0.4046
sub_12:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.4412 - F1: 0.4396
sub_12:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2609 - F1: 0.2407
sub_12:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4058 - F1: 0.4089
sub_12:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.3188 - F1: 0.2942
sub_12:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.3188 - F1: 0.2976
sub_12:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3623 - F1: 0.3422
sub_12:Test (Best Model) - Loss: 1.3364 - Accuracy: 0.3676 - F1: 0.3341
sub_12:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.3235 - F1: 0.2649
sub_12:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.3382 - F1: 0.3447
sub_12:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2353 - F1: 0.2060
sub_12:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3971 - F1: 0.4067
sub_13:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2206 - F1: 0.2379
sub_13:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.2647 - F1: 0.2598
sub_13:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.3382 - F1: 0.3479
sub_13:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.2941 - F1: 0.3127
sub_13:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.1765 - F1: 0.1941
sub_13:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.2606
sub_13:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2029 - F1: 0.1832
sub_13:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2754 - F1: 0.2362
sub_13:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2319 - F1: 0.2239
sub_13:Test (Best Model) - Loss: 1.3755 - Accuracy: 0.2319 - F1: 0.2043
sub_13:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3382 - F1: 0.3520
sub_13:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2500 - F1: 0.2493
sub_13:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.2647 - F1: 0.2442
sub_13:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.2941 - F1: 0.2997
sub_13:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.3382 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.1912 - F1: 0.1758
sub_14:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.2500 - F1: 0.2446
sub_14:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.2353 - F1: 0.2244
sub_14:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.2794 - F1: 0.2900
sub_14:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2500 - F1: 0.2112
sub_14:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3529 - F1: 0.3014
sub_14:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3235 - F1: 0.2780
sub_14:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2647 - F1: 0.2311
sub_14:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3529 - F1: 0.3433
sub_14:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2941 - F1: 0.2886
sub_14:Test (Best Model) - Loss: 1.3637 - Accuracy: 0.2794 - F1: 0.2843
sub_14:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.3382 - F1: 0.2752
sub_14:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.3088 - F1: 0.2811
sub_14:Test (Best Model) - Loss: 1.3442 - Accuracy: 0.3824 - F1: 0.3485
sub_14:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3235 - F1: 0.3148
sub_15:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3529 - F1: 0.3848
sub_15:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3088 - F1: 0.3115
sub_15:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3088 - F1: 0.3120
sub_15:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3676 - F1: 0.3881
sub_15:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.4118 - F1: 0.4376
sub_15:Test (Best Model) - Loss: 1.3025 - Accuracy: 0.3824 - F1: 0.3944
sub_15:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.3824 - F1: 0.3741
sub_15:Test (Best Model) - Loss: 1.2662 - Accuracy: 0.4706 - F1: 0.4658
sub_15:Test (Best Model) - Loss: 1.3202 - Accuracy: 0.4853 - F1: 0.4817
sub_15:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.4265 - F1: 0.4213
sub_15:Test (Best Model) - Loss: 1.2730 - Accuracy: 0.4559 - F1: 0.4655
sub_15:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.3382 - F1: 0.3608
sub_15:Test (Best Model) - Loss: 1.3082 - Accuracy: 0.4559 - F1: 0.4609
sub_15:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.3824 - F1: 0.4077
sub_15:Test (Best Model) - Loss: 1.3026 - Accuracy: 0.4265 - F1: 0.4450
sub_16:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3382 - F1: 0.3306
sub_16:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.3971 - F1: 0.3838
sub_16:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.3971 - F1: 0.3617
sub_16:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3529 - F1: 0.3325
sub_16:Test (Best Model) - Loss: 1.3238 - Accuracy: 0.3235 - F1: 0.3028
sub_16:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3088 - F1: 0.2521
sub_16:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2500 - F1: 0.2362
sub_16:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2206 - F1: 0.2181
sub_16:Test (Best Model) - Loss: 1.3369 - Accuracy: 0.2794 - F1: 0.2245
sub_16:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2647 - F1: 0.2470
sub_16:Test (Best Model) - Loss: 1.3466 - Accuracy: 0.4265 - F1: 0.3907
sub_16:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.3824 - F1: 0.3304
sub_16:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.2647 - F1: 0.2520
sub_16:Test (Best Model) - Loss: 1.3383 - Accuracy: 0.3088 - F1: 0.2789
sub_16:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3971 - F1: 0.3601
sub_17:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.4928 - F1: 0.4362
sub_17:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3188 - F1: 0.3201
sub_17:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.4203 - F1: 0.4140
sub_17:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.3623 - F1: 0.3449
sub_17:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2899 - F1: 0.2704
sub_17:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.3043 - F1: 0.2645
sub_17:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3333 - F1: 0.2660
sub_17:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3478 - F1: 0.2992
sub_17:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.3623 - F1: 0.2965
sub_17:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3623 - F1: 0.3479
sub_17:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.3529 - F1: 0.3104
sub_17:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.3382 - F1: 0.3125
sub_17:Test (Best Model) - Loss: 1.3031 - Accuracy: 0.3676 - F1: 0.3570
sub_17:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3676 - F1: 0.3691
sub_17:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.3971 - F1: 0.3677
sub_18:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3768 - F1: 0.3730
sub_18:Test (Best Model) - Loss: 1.3461 - Accuracy: 0.4058 - F1: 0.4206
sub_18:Test (Best Model) - Loss: 1.3386 - Accuracy: 0.4058 - F1: 0.4019
sub_18:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.3913 - F1: 0.3728
sub_18:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2899 - F1: 0.3046
sub_18:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2353 - F1: 0.2380
sub_18:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3382 - F1: 0.3620
sub_18:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3235 - F1: 0.3273
sub_18:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2941 - F1: 0.3135
sub_18:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2353 - F1: 0.2453
sub_18:Test (Best Model) - Loss: 1.3478 - Accuracy: 0.3088 - F1: 0.3296
sub_18:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3088 - F1: 0.2998
sub_18:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2206 - F1: 0.2175
sub_18:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3676 - F1: 0.3606
sub_18:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2941 - F1: 0.2953
sub_19:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.2941 - F1: 0.3001
sub_19:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2794 - F1: 0.2687
sub_19:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.2206 - F1: 0.1697
sub_19:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.2941 - F1: 0.2773
sub_19:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.2647 - F1: 0.1742
sub_19:Test (Best Model) - Loss: 1.3244 - Accuracy: 0.3676 - F1: 0.3523
sub_19:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.3529 - F1: 0.2765
sub_19:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.3824 - F1: 0.3687
sub_19:Test (Best Model) - Loss: 1.3082 - Accuracy: 0.3676 - F1: 0.3579
sub_19:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.2794 - F1: 0.2736
sub_19:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3824 - F1: 0.3842
sub_19:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3235 - F1: 0.3160
sub_19:Test (Best Model) - Loss: 1.3299 - Accuracy: 0.3235 - F1: 0.2938
sub_19:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.2941 - F1: 0.3100
sub_19:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3088 - F1: 0.2984
sub_20:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.4118 - F1: 0.3990
sub_20:Test (Best Model) - Loss: 1.2563 - Accuracy: 0.4706 - F1: 0.5056
sub_20:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.3382 - F1: 0.3238
sub_20:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.3824 - F1: 0.3959
sub_20:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.3824 - F1: 0.3682
sub_20:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.3088 - F1: 0.2799
sub_20:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.3235 - F1: 0.3150
sub_20:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.3971 - F1: 0.3997
sub_20:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.2647 - F1: 0.2876
sub_20:Test (Best Model) - Loss: 1.3498 - Accuracy: 0.3824 - F1: 0.3596
sub_20:Test (Best Model) - Loss: 1.3332 - Accuracy: 0.3188 - F1: 0.3034
sub_20:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.3623 - F1: 0.3631
sub_20:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.2754 - F1: 0.2795
sub_20:Test (Best Model) - Loss: 1.3067 - Accuracy: 0.4348 - F1: 0.4290
sub_20:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3043 - F1: 0.3215
sub_21:Test (Best Model) - Loss: 1.3063 - Accuracy: 0.2941 - F1: 0.2468
sub_21:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.2647 - F1: 0.2488
sub_21:Test (Best Model) - Loss: 1.3365 - Accuracy: 0.3088 - F1: 0.2684
sub_21:Test (Best Model) - Loss: 1.3067 - Accuracy: 0.4412 - F1: 0.4329
sub_21:Test (Best Model) - Loss: 1.3637 - Accuracy: 0.2941 - F1: 0.2368
sub_21:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.3382 - F1: 0.3093
sub_21:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.2647 - F1: 0.2437
sub_21:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.3235 - F1: 0.3094
sub_21:Test (Best Model) - Loss: 1.3117 - Accuracy: 0.4265 - F1: 0.4175
sub_21:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.2353 - F1: 0.1986
sub_21:Test (Best Model) - Loss: 1.3361 - Accuracy: 0.3382 - F1: 0.3201
sub_21:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.2647 - F1: 0.2300
sub_21:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.2941 - F1: 0.2648
sub_21:Test (Best Model) - Loss: 1.3188 - Accuracy: 0.3529 - F1: 0.3346
sub_21:Test (Best Model) - Loss: 1.3231 - Accuracy: 0.3824 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2353 - F1: 0.2329
sub_22:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2647 - F1: 0.2592
sub_22:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2941 - F1: 0.2997
sub_22:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.3235 - F1: 0.3357
sub_22:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2353 - F1: 0.2180
sub_22:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2609 - F1: 0.2484
sub_22:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.3623 - F1: 0.3250
sub_22:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3188 - F1: 0.3104
sub_22:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.3043 - F1: 0.2926
sub_22:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3333 - F1: 0.2925
sub_22:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.2941 - F1: 0.3175
sub_22:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.3529 - F1: 0.3160
sub_22:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.3235 - F1: 0.3085
sub_22:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2500 - F1: 0.2579
sub_22:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2941 - F1: 0.3046
sub_23:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.3913 - F1: 0.3978
sub_23:Test (Best Model) - Loss: 1.3158 - Accuracy: 0.3478 - F1: 0.3309
sub_23:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.3478 - F1: 0.3332
sub_23:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.2754 - F1: 0.2450
sub_23:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.3913 - F1: 0.3911
sub_23:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.3676 - F1: 0.3766
sub_23:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.4853 - F1: 0.5004
sub_23:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3971 - F1: 0.3955
sub_23:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.4412 - F1: 0.4519
sub_23:Test (Best Model) - Loss: 1.3386 - Accuracy: 0.4706 - F1: 0.4527
sub_23:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.2609 - F1: 0.2628
sub_23:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.3188 - F1: 0.3167
sub_23:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.3478 - F1: 0.3066
sub_23:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.3768 - F1: 0.3789
sub_23:Test (Best Model) - Loss: 1.3162 - Accuracy: 0.3333 - F1: 0.3546
sub_24:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.3088 - F1: 0.3026
sub_24:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3088 - F1: 0.2481
sub_24:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2353 - F1: 0.2318
sub_24:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2941 - F1: 0.2883
sub_24:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2794 - F1: 0.2850
sub_24:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.2206 - F1: 0.2054
sub_24:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2647 - F1: 0.2536
sub_24:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2500 - F1: 0.2416
sub_24:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2353 - F1: 0.2354
sub_24:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2353 - F1: 0.2365
sub_24:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2353 - F1: 0.2378
sub_24:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.2353 - F1: 0.2164
sub_24:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.1176 - F1: 0.1192
sub_24:Test (Best Model) - Loss: 1.4185 - Accuracy: 0.2353 - F1: 0.2410
sub_24:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2353 - F1: 0.2343
sub_25:Test (Best Model) - Loss: 1.3143 - Accuracy: 0.3768 - F1: 0.3576
sub_25:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.3478 - F1: 0.3370
sub_25:Test (Best Model) - Loss: 1.3418 - Accuracy: 0.3188 - F1: 0.2973
sub_25:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.3623 - F1: 0.3306
sub_25:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.3333 - F1: 0.3046
sub_25:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2353 - F1: 0.1925
sub_25:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.3529 - F1: 0.3364
sub_25:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3971 - F1: 0.3246
sub_25:Test (Best Model) - Loss: 1.3326 - Accuracy: 0.3824 - F1: 0.3626
sub_25:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.4118 - F1: 0.3876
sub_25:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.3088 - F1: 0.2888
sub_25:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.3235 - F1: 0.2713
sub_25:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.3382 - F1: 0.3055
sub_25:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.2794 - F1: 0.2342
sub_25:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.3824 - F1: 0.3581
sub_26:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.4348 - F1: 0.4387
sub_26:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.3768 - F1: 0.3793
sub_26:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3913 - F1: 0.4033
sub_26:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.4348 - F1: 0.4368
sub_26:Test (Best Model) - Loss: 1.3470 - Accuracy: 0.2464 - F1: 0.2303
sub_26:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.4559 - F1: 0.4776
sub_26:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.3971 - F1: 0.3954
sub_26:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.4412 - F1: 0.4167
sub_26:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3971 - F1: 0.4056
sub_26:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.3529 - F1: 0.3764
sub_26:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.3971 - F1: 0.3997
sub_26:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.4118 - F1: 0.4124
sub_26:Test (Best Model) - Loss: 1.3272 - Accuracy: 0.4559 - F1: 0.4785
sub_26:Test (Best Model) - Loss: 1.2897 - Accuracy: 0.4559 - F1: 0.4828
sub_26:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.4559 - F1: 0.4579
sub_27:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.4928 - F1: 0.4362
sub_27:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3188 - F1: 0.3201
sub_27:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.4203 - F1: 0.4140
sub_27:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.3623 - F1: 0.3449
sub_27:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2899 - F1: 0.2704
sub_27:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.3043 - F1: 0.2645
sub_27:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3333 - F1: 0.2660
sub_27:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3478 - F1: 0.2992
sub_27:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.3623 - F1: 0.2965
sub_27:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3623 - F1: 0.3479
sub_27:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.3529 - F1: 0.3104
sub_27:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.3382 - F1: 0.3125
sub_27:Test (Best Model) - Loss: 1.3031 - Accuracy: 0.3676 - F1: 0.3570
sub_27:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3676 - F1: 0.3691
sub_27:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.3971 - F1: 0.3677
sub_28:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3235 - F1: 0.3183
sub_28:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2647 - F1: 0.2561
sub_28:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2941 - F1: 0.2922
sub_28:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.3235 - F1: 0.3233
sub_28:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.1618 - F1: 0.1413
sub_28:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.2059 - F1: 0.1887
sub_28:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.2794 - F1: 0.2223
sub_28:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2794 - F1: 0.2159
sub_28:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.2647 - F1: 0.2400
sub_28:Test (Best Model) - Loss: 1.4152 - Accuracy: 0.2500 - F1: 0.2043
sub_28:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2206 - F1: 0.1975
sub_28:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3676 - F1: 0.2880
sub_28:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.3088 - F1: 0.2855
sub_28:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.3529 - F1: 0.3205
sub_28:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.3382 - F1: 0.3036
sub_29:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.3971 - F1: 0.4318
sub_29:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.4853 - F1: 0.4927
sub_29:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.5147 - F1: 0.5295
sub_29:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.4706 - F1: 0.4801
sub_29:Test (Best Model) - Loss: 1.2777 - Accuracy: 0.4412 - F1: 0.4764
sub_29:Test (Best Model) - Loss: 1.2263 - Accuracy: 0.4706 - F1: 0.5048
sub_29:Test (Best Model) - Loss: 1.2674 - Accuracy: 0.4412 - F1: 0.4510
sub_29:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.4118 - F1: 0.4088
sub_29:Test (Best Model) - Loss: 1.2740 - Accuracy: 0.4412 - F1: 0.4573
sub_29:Test (Best Model) - Loss: 1.2374 - Accuracy: 0.5294 - F1: 0.5590
sub_29:Test (Best Model) - Loss: 1.2472 - Accuracy: 0.5217 - F1: 0.5380
sub_29:Test (Best Model) - Loss: 1.2721 - Accuracy: 0.4058 - F1: 0.4227
sub_29:Test (Best Model) - Loss: 1.3010 - Accuracy: 0.4203 - F1: 0.4330
sub_29:Test (Best Model) - Loss: 1.1986 - Accuracy: 0.5072 - F1: 0.5281
sub_29:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.4638 - F1: 0.4756

=== Summary Results ===

acc: 33.40 ± 5.46
F1: 32.35 ± 5.95
acc-in: 38.99 ± 5.17
F1-in: 36.97 ± 5.42
