lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3088 - F1: 0.3154
sub_1:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3088 - F1: 0.3142
sub_1:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.2941 - F1: 0.3095
sub_1:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2794 - F1: 0.2886
sub_1:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3235 - F1: 0.3038
sub_1:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2899 - F1: 0.2936
sub_1:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2319 - F1: 0.2324
sub_1:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2609 - F1: 0.2609
sub_1:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.2464 - F1: 0.2383
sub_1:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2464 - F1: 0.2240
sub_1:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3088 - F1: 0.2523
sub_1:Test (Best Model) - Loss: 1.3344 - Accuracy: 0.3971 - F1: 0.4171
sub_1:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3971 - F1: 0.3901
sub_1:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.3971 - F1: 0.3980
sub_1:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.4265 - F1: 0.4101
sub_2:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.2899 - F1: 0.2939
sub_2:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.3478 - F1: 0.3542
sub_2:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2029 - F1: 0.1818
sub_2:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.2609 - F1: 0.2654
sub_2:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.2464 - F1: 0.2234
sub_2:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2794 - F1: 0.2659
sub_2:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2941 - F1: 0.2832
sub_2:Test (Best Model) - Loss: 1.3986 - Accuracy: 0.1912 - F1: 0.1793
sub_2:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2059 - F1: 0.1970
sub_2:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2647 - F1: 0.2407
sub_2:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.2754 - F1: 0.2704
sub_2:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3768 - F1: 0.3278
sub_2:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.3188 - F1: 0.3038
sub_2:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2029 - F1: 0.1797
sub_2:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2609 - F1: 0.2420
sub_3:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.1765 - F1: 0.1774
sub_3:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2500 - F1: 0.2459
sub_3:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2647 - F1: 0.2628
sub_3:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.2500 - F1: 0.2331
sub_3:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.1765 - F1: 0.1601
sub_3:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.3043 - F1: 0.2909
sub_3:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2174 - F1: 0.1911
sub_3:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.1884 - F1: 0.1702
sub_3:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2029 - F1: 0.2060
sub_3:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2899 - F1: 0.2497
sub_3:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.1884 - F1: 0.1923
sub_3:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2319 - F1: 0.2178
sub_3:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2609 - F1: 0.2425
sub_3:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.2029 - F1: 0.1794
sub_3:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.3043 - F1: 0.2839
sub_4:Test (Best Model) - Loss: 1.3271 - Accuracy: 0.4058 - F1: 0.3801
sub_4:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3913 - F1: 0.4030
sub_4:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.4058 - F1: 0.4218
sub_4:Test (Best Model) - Loss: 1.3356 - Accuracy: 0.4348 - F1: 0.4144
sub_4:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.4058 - F1: 0.3901
sub_4:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3913 - F1: 0.3870
sub_4:Test (Best Model) - Loss: 1.3229 - Accuracy: 0.4203 - F1: 0.4144
sub_4:Test (Best Model) - Loss: 1.3391 - Accuracy: 0.4058 - F1: 0.4233
sub_4:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3913 - F1: 0.3885
sub_4:Test (Best Model) - Loss: 1.2767 - Accuracy: 0.4928 - F1: 0.5115
sub_4:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.3623 - F1: 0.3468
sub_4:Test (Best Model) - Loss: 1.3396 - Accuracy: 0.3478 - F1: 0.3109
sub_4:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.3768 - F1: 0.3814
sub_4:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.3333 - F1: 0.3346
sub_4:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.3188 - F1: 0.3099
sub_5:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.4412 - F1: 0.4126
sub_5:Test (Best Model) - Loss: 1.3364 - Accuracy: 0.3971 - F1: 0.3811
sub_5:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.3971 - F1: 0.3791
sub_5:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.4118 - F1: 0.4162
sub_5:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.2941 - F1: 0.2817
sub_5:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.3971 - F1: 0.3933
sub_5:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.4559 - F1: 0.4582
sub_5:Test (Best Model) - Loss: 1.3096 - Accuracy: 0.4853 - F1: 0.5090
sub_5:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.4412 - F1: 0.3997
sub_5:Test (Best Model) - Loss: 1.2995 - Accuracy: 0.5000 - F1: 0.5188
sub_5:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.4265 - F1: 0.3969
sub_5:Test (Best Model) - Loss: 1.3146 - Accuracy: 0.5147 - F1: 0.5142
sub_5:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3382 - F1: 0.3293
sub_5:Test (Best Model) - Loss: 1.3183 - Accuracy: 0.4559 - F1: 0.4301
sub_5:Test (Best Model) - Loss: 1.3076 - Accuracy: 0.4706 - F1: 0.4616
sub_6:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.3824 - F1: 0.3861
sub_6:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2206 - F1: 0.2183
sub_6:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3676 - F1: 0.3722
sub_6:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.3971 - F1: 0.4055
sub_6:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3235 - F1: 0.3348
sub_6:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.2899 - F1: 0.2816
sub_6:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.2754 - F1: 0.2355
sub_6:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3333 - F1: 0.2887
sub_6:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.2609 - F1: 0.2277
sub_6:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.4348 - F1: 0.3634
sub_6:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.3043 - F1: 0.2974
sub_6:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2464 - F1: 0.1972
sub_6:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.2609 - F1: 0.2436
sub_6:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2754 - F1: 0.2717
sub_6:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.3913 - F1: 0.3973
sub_7:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.4265 - F1: 0.4115
sub_7:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.3676 - F1: 0.3416
sub_7:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.3971 - F1: 0.3415
sub_7:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.4412 - F1: 0.4387
sub_7:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.3824 - F1: 0.3653
sub_7:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.3529 - F1: 0.3223
sub_7:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.3824 - F1: 0.3644
sub_7:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.4118 - F1: 0.4186
sub_7:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2941 - F1: 0.2760
sub_7:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.3676 - F1: 0.3354
sub_7:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.4265 - F1: 0.4407
sub_7:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.3088 - F1: 0.2802
sub_7:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.3382 - F1: 0.3252
sub_7:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3382 - F1: 0.3147
sub_7:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.3088 - F1: 0.3136
sub_8:Test (Best Model) - Loss: 1.4026 - Accuracy: 0.1765 - F1: 0.1743
sub_8:Test (Best Model) - Loss: 1.4097 - Accuracy: 0.2647 - F1: 0.2612
sub_8:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.2500 - F1: 0.2564
sub_8:Test (Best Model) - Loss: 1.4115 - Accuracy: 0.2647 - F1: 0.2367
sub_8:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.2647 - F1: 0.2535
sub_8:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2794 - F1: 0.2873
sub_8:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2941 - F1: 0.2812
sub_8:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3088 - F1: 0.3095
sub_8:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2059 - F1: 0.1906
sub_8:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2647 - F1: 0.2183
sub_8:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.2647 - F1: 0.2574
sub_8:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2794 - F1: 0.2625
sub_8:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2794 - F1: 0.2866
sub_8:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2794 - F1: 0.2812
sub_8:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3235 - F1: 0.3271
sub_9:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.4265 - F1: 0.4468
sub_9:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3088 - F1: 0.3084
sub_9:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.3676 - F1: 0.4055
sub_9:Test (Best Model) - Loss: 1.3196 - Accuracy: 0.3971 - F1: 0.4150
sub_9:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3824 - F1: 0.4036
sub_9:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.2647 - F1: 0.2851
sub_9:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3382 - F1: 0.3750
sub_9:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.2794 - F1: 0.2932
sub_9:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3088 - F1: 0.3001
sub_9:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.2353 - F1: 0.2385
sub_9:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3676 - F1: 0.3552
sub_9:Test (Best Model) - Loss: 1.3549 - Accuracy: 0.2941 - F1: 0.2897
sub_9:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.4412 - F1: 0.4485
sub_9:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2647 - F1: 0.2540
sub_9:Test (Best Model) - Loss: 1.3536 - Accuracy: 0.3676 - F1: 0.3871
sub_10:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2353 - F1: 0.1980
sub_10:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2500 - F1: 0.2437
sub_10:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.4118 - F1: 0.4140
sub_10:Test (Best Model) - Loss: 1.3986 - Accuracy: 0.1912 - F1: 0.1842
sub_10:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.2647 - F1: 0.2466
sub_10:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3382 - F1: 0.3140
sub_10:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2059 - F1: 0.1816
sub_10:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2647 - F1: 0.2491
sub_10:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2353 - F1: 0.2158
sub_10:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2794 - F1: 0.2618
sub_10:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2464 - F1: 0.2446
sub_10:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2319 - F1: 0.2173
sub_10:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.2899 - F1: 0.2825
sub_10:Test (Best Model) - Loss: 1.3942 - Accuracy: 0.2174 - F1: 0.2153
sub_10:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2174 - F1: 0.2050
sub_11:Test (Best Model) - Loss: 1.3566 - Accuracy: 0.3333 - F1: 0.3288
sub_11:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.2754 - F1: 0.2658
sub_11:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.2464 - F1: 0.2365
sub_11:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.2609 - F1: 0.2408
sub_11:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3188 - F1: 0.3149
sub_11:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3333 - F1: 0.3242
sub_11:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.4348 - F1: 0.4173
sub_11:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2609 - F1: 0.2440
sub_11:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.3913 - F1: 0.3788
sub_11:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3478 - F1: 0.3295
sub_11:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.2269
sub_11:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2464 - F1: 0.2034
sub_11:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3043 - F1: 0.2754
sub_11:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3043 - F1: 0.3041
sub_11:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.3188 - F1: 0.3093
sub_12:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3088 - F1: 0.2888
sub_12:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.3676 - F1: 0.3764
sub_12:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.2500 - F1: 0.2496
sub_12:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.3382 - F1: 0.3484
sub_12:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.2647 - F1: 0.2645
sub_12:Test (Best Model) - Loss: 1.3471 - Accuracy: 0.3768 - F1: 0.3858
sub_12:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3333 - F1: 0.2997
sub_12:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3043 - F1: 0.2591
sub_12:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.3623 - F1: 0.3760
sub_12:Test (Best Model) - Loss: 1.3537 - Accuracy: 0.3188 - F1: 0.3170
sub_12:Test (Best Model) - Loss: 1.3430 - Accuracy: 0.3824 - F1: 0.3517
sub_12:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2500 - F1: 0.2592
sub_12:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.3382 - F1: 0.3507
sub_12:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2794 - F1: 0.2759
sub_12:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3529 - F1: 0.3418
sub_13:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.2353 - F1: 0.2390
sub_13:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.2500 - F1: 0.2458
sub_13:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.3235 - F1: 0.2903
sub_13:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3824 - F1: 0.3690
sub_13:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2353 - F1: 0.2247
sub_13:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3043 - F1: 0.2639
sub_13:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2464 - F1: 0.2253
sub_13:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2464 - F1: 0.2386
sub_13:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3188 - F1: 0.3330
sub_13:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2899 - F1: 0.2773
sub_13:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2059 - F1: 0.1852
sub_13:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2647 - F1: 0.2559
sub_13:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2647 - F1: 0.2564
sub_13:Test (Best Model) - Loss: 1.4013 - Accuracy: 0.2059 - F1: 0.2038
sub_13:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.3088 - F1: 0.3159
sub_14:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3382 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3235 - F1: 0.3229
sub_14:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2500 - F1: 0.2195
sub_14:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2794 - F1: 0.3100
sub_14:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.1912 - F1: 0.1680
sub_14:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.2647 - F1: 0.2638
sub_14:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.3824 - F1: 0.3920
sub_14:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3676 - F1: 0.3209
sub_14:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2941 - F1: 0.2724
sub_14:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3088 - F1: 0.2636
sub_14:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.2500 - F1: 0.2233
sub_14:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.3088 - F1: 0.2869
sub_14:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3382 - F1: 0.3019
sub_14:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2941 - F1: 0.2804
sub_14:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3382 - F1: 0.2894
sub_15:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.3824 - F1: 0.4157
sub_15:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.3382 - F1: 0.3496
sub_15:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3382 - F1: 0.3720
sub_15:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.3971 - F1: 0.4348
sub_15:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.3676 - F1: 0.3885
sub_15:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.3971 - F1: 0.4141
sub_15:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.4706 - F1: 0.4619
sub_15:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.3824 - F1: 0.3674
sub_15:Test (Best Model) - Loss: 1.2898 - Accuracy: 0.4265 - F1: 0.4262
sub_15:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3382 - F1: 0.3567
sub_15:Test (Best Model) - Loss: 1.3309 - Accuracy: 0.3971 - F1: 0.3943
sub_15:Test (Best Model) - Loss: 1.3361 - Accuracy: 0.3676 - F1: 0.3623
sub_15:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.4265 - F1: 0.4250
sub_15:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.3971 - F1: 0.4015
sub_15:Test (Best Model) - Loss: 1.3250 - Accuracy: 0.4559 - F1: 0.4654
sub_16:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.3235 - F1: 0.3108
sub_16:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.2353 - F1: 0.1968
sub_16:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.3088 - F1: 0.2738
sub_16:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.3382 - F1: 0.3286
sub_16:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.3676 - F1: 0.3251
sub_16:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2353 - F1: 0.2216
sub_16:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.3088 - F1: 0.3061
sub_16:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.2647 - F1: 0.2647
sub_16:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2647 - F1: 0.2449
sub_16:Test (Best Model) - Loss: 1.4054 - Accuracy: 0.2059 - F1: 0.1982
sub_16:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.4118 - F1: 0.3382
sub_16:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.4559 - F1: 0.3958
sub_16:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2794 - F1: 0.2771
sub_16:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.3382 - F1: 0.3362
sub_16:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.3088 - F1: 0.2864
sub_17:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2609 - F1: 0.2231
sub_17:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2899 - F1: 0.2649
sub_17:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3913 - F1: 0.3657
sub_17:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.4348 - F1: 0.4274
sub_17:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.3768 - F1: 0.3691
sub_17:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3478 - F1: 0.3023
sub_17:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2754 - F1: 0.2209
sub_17:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3188 - F1: 0.2814
sub_17:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3623 - F1: 0.3176
sub_17:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3333 - F1: 0.2783
sub_17:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3382 - F1: 0.2995
sub_17:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.3676 - F1: 0.3543
sub_17:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3235 - F1: 0.3211
sub_17:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3529 - F1: 0.3509
sub_17:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2353 - F1: 0.2055
sub_18:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3188 - F1: 0.3267
sub_18:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.4783 - F1: 0.4876
sub_18:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4493 - F1: 0.4428
sub_18:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.3623 - F1: 0.3274
sub_18:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3623 - F1: 0.3495
sub_18:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2500 - F1: 0.2586
sub_18:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2500 - F1: 0.2570
sub_18:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2500 - F1: 0.2562
sub_18:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2353 - F1: 0.2266
sub_18:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2353 - F1: 0.2248
sub_18:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3088 - F1: 0.3068
sub_18:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2941 - F1: 0.2933
sub_18:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3235 - F1: 0.3276
sub_18:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.3088 - F1: 0.3144
sub_18:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2353 - F1: 0.2443
sub_19:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3382 - F1: 0.2771
sub_19:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2206 - F1: 0.2343
sub_19:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2647 - F1: 0.2509
sub_19:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2206 - F1: 0.2201
sub_19:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2206 - F1: 0.1954
sub_19:Test (Best Model) - Loss: 1.3576 - Accuracy: 0.2941 - F1: 0.2406
sub_19:Test (Best Model) - Loss: 1.3592 - Accuracy: 0.3382 - F1: 0.3230
sub_19:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3529 - F1: 0.3270
sub_19:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3676 - F1: 0.3221
sub_19:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.3676 - F1: 0.3436
sub_19:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2500 - F1: 0.2379
sub_19:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2794 - F1: 0.2813
sub_19:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.3088 - F1: 0.2857
sub_19:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3824 - F1: 0.3853
sub_19:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3088 - F1: 0.3182
sub_20:Test (Best Model) - Loss: 1.2996 - Accuracy: 0.4706 - F1: 0.4714
sub_20:Test (Best Model) - Loss: 1.3091 - Accuracy: 0.3676 - F1: 0.3990
sub_20:Test (Best Model) - Loss: 1.3129 - Accuracy: 0.3971 - F1: 0.3622
sub_20:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3382 - F1: 0.3083
sub_20:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.4412 - F1: 0.4394
sub_20:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.2794 - F1: 0.2377
sub_20:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.3235 - F1: 0.3266
sub_20:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3529 - F1: 0.3764
sub_20:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2647 - F1: 0.2731
sub_20:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2941 - F1: 0.2953
sub_20:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.3623 - F1: 0.3440
sub_20:Test (Best Model) - Loss: 1.3376 - Accuracy: 0.4058 - F1: 0.4111
sub_20:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.3333 - F1: 0.3494
sub_20:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.3623 - F1: 0.3637
sub_20:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.2754 - F1: 0.2672
sub_21:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.3382 - F1: 0.3177
sub_21:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3235 - F1: 0.2790
sub_21:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.3088 - F1: 0.2843
sub_21:Test (Best Model) - Loss: 1.3396 - Accuracy: 0.4412 - F1: 0.4017
sub_21:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.2647 - F1: 0.2280
sub_21:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.2794 - F1: 0.2931
sub_21:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.3235 - F1: 0.3094
sub_21:Test (Best Model) - Loss: 1.3503 - Accuracy: 0.3676 - F1: 0.3494
sub_21:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.3824 - F1: 0.3849
sub_21:Test (Best Model) - Loss: 1.3566 - Accuracy: 0.3382 - F1: 0.3103
sub_21:Test (Best Model) - Loss: 1.3304 - Accuracy: 0.3824 - F1: 0.3138
sub_21:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.2647 - F1: 0.2890
sub_21:Test (Best Model) - Loss: 1.3665 - Accuracy: 0.3088 - F1: 0.2918
sub_21:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.2500 - F1: 0.2266
sub_21:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.3382 - F1: 0.3103
sub_22:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2647 - F1: 0.2747
sub_22:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2353 - F1: 0.2419
sub_22:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3235 - F1: 0.3191
sub_22:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.3382 - F1: 0.3200
sub_22:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2353 - F1: 0.2420
sub_22:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3768 - F1: 0.3756
sub_22:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.2899 - F1: 0.2643
sub_22:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.2754 - F1: 0.2846
sub_22:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2754 - F1: 0.2773
sub_22:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3188 - F1: 0.2768
sub_22:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.3676 - F1: 0.3705
sub_22:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2941 - F1: 0.3000
sub_22:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3235 - F1: 0.2970
sub_22:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2353 - F1: 0.2457
sub_22:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3382 - F1: 0.3457
sub_23:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.2609 - F1: 0.2290
sub_23:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3043 - F1: 0.3046
sub_23:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3188 - F1: 0.3284
sub_23:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.3768 - F1: 0.3790
sub_23:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3043 - F1: 0.2900
sub_23:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.4265 - F1: 0.4161
sub_23:Test (Best Model) - Loss: 1.3325 - Accuracy: 0.4412 - F1: 0.4521
sub_23:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.2941 - F1: 0.3038
sub_23:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.4265 - F1: 0.4111
sub_23:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.3382 - F1: 0.3592
sub_23:Test (Best Model) - Loss: 1.3165 - Accuracy: 0.2754 - F1: 0.2733
sub_23:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.2609 - F1: 0.2483
sub_23:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.4493 - F1: 0.4267
sub_23:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3188 - F1: 0.3190
sub_23:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.2754 - F1: 0.2726
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2059 - F1: 0.1945
sub_24:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3088 - F1: 0.2699
sub_24:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2941 - F1: 0.2700
sub_24:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.2500 - F1: 0.2340
sub_24:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2941 - F1: 0.2980
sub_24:Test (Best Model) - Loss: 1.3859 - Accuracy: 0.2353 - F1: 0.2316
sub_24:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3235 - F1: 0.3236
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.3235 - F1: 0.3299
sub_24:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3235 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2206 - F1: 0.1936
sub_24:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.1912 - F1: 0.1927
sub_24:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2206 - F1: 0.2292
sub_24:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.2059 - F1: 0.2072
sub_24:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2941 - F1: 0.2929
sub_24:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2941 - F1: 0.2963
sub_25:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3188 - F1: 0.2920
sub_25:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.3333 - F1: 0.3355
sub_25:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3188 - F1: 0.2863
sub_25:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3478 - F1: 0.3263
sub_25:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2609 - F1: 0.2259
sub_25:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.2794 - F1: 0.2461
sub_25:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3235 - F1: 0.3002
sub_25:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.3529 - F1: 0.2899
sub_25:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.2941 - F1: 0.2944
sub_25:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.2500 - F1: 0.2020
sub_25:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3088 - F1: 0.2960
sub_25:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.3529 - F1: 0.3032
sub_25:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4559 - F1: 0.4374
sub_25:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3382 - F1: 0.3014
sub_25:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.3529 - F1: 0.2912
sub_26:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3478 - F1: 0.3473
sub_26:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3188 - F1: 0.3159
sub_26:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.4348 - F1: 0.4265
sub_26:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.4348 - F1: 0.4262
sub_26:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3623 - F1: 0.3718
sub_26:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.3235 - F1: 0.3342
sub_26:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3529 - F1: 0.3578
sub_26:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.4412 - F1: 0.4439
sub_26:Test (Best Model) - Loss: 1.3430 - Accuracy: 0.3676 - F1: 0.3672
sub_26:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.3382 - F1: 0.3450
sub_26:Test (Best Model) - Loss: 1.3370 - Accuracy: 0.4118 - F1: 0.4168
sub_26:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.2941 - F1: 0.2922
sub_26:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.3529 - F1: 0.3468
sub_26:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.4118 - F1: 0.4164
sub_26:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.4706 - F1: 0.4821
sub_27:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2609 - F1: 0.2231
sub_27:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2899 - F1: 0.2649
sub_27:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3913 - F1: 0.3657
sub_27:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.4348 - F1: 0.4274
sub_27:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.3768 - F1: 0.3691
sub_27:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3478 - F1: 0.3023
sub_27:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2754 - F1: 0.2209
sub_27:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.3188 - F1: 0.2814
sub_27:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3623 - F1: 0.3176
sub_27:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3333 - F1: 0.2783
sub_27:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3382 - F1: 0.2995
sub_27:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.3676 - F1: 0.3543
sub_27:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3235 - F1: 0.3211
sub_27:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3529 - F1: 0.3509
sub_27:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.2353 - F1: 0.2055
sub_28:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.1471 - F1: 0.1461
sub_28:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2500 - F1: 0.2440
sub_28:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.1471 - F1: 0.1254
sub_28:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.2353 - F1: 0.2271
sub_28:Test (Best Model) - Loss: 1.4014 - Accuracy: 0.2206 - F1: 0.2123
sub_28:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2059 - F1: 0.1538
sub_28:Test (Best Model) - Loss: 1.3875 - Accuracy: 0.2647 - F1: 0.2509
sub_28:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.2794 - F1: 0.2393
sub_28:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.2500 - F1: 0.2200
sub_28:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2941 - F1: 0.2493
sub_28:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.1912 - F1: 0.1852
sub_28:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.4118 - F1: 0.3838
sub_28:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.3088 - F1: 0.3093
sub_28:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.2461
sub_28:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3088 - F1: 0.2169
sub_29:Test (Best Model) - Loss: 1.3188 - Accuracy: 0.4412 - F1: 0.4652
sub_29:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3529 - F1: 0.3552
sub_29:Test (Best Model) - Loss: 1.2582 - Accuracy: 0.5000 - F1: 0.5251
sub_29:Test (Best Model) - Loss: 1.2509 - Accuracy: 0.3676 - F1: 0.4041
sub_29:Test (Best Model) - Loss: 1.2597 - Accuracy: 0.4706 - F1: 0.5073
sub_29:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.3971 - F1: 0.4159
sub_29:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.4412 - F1: 0.4528
sub_29:Test (Best Model) - Loss: 1.3012 - Accuracy: 0.3382 - F1: 0.3623
sub_29:Test (Best Model) - Loss: 1.2631 - Accuracy: 0.4412 - F1: 0.4556
sub_29:Test (Best Model) - Loss: 1.3254 - Accuracy: 0.3676 - F1: 0.3882
sub_29:Test (Best Model) - Loss: 1.2354 - Accuracy: 0.4493 - F1: 0.4534
sub_29:Test (Best Model) - Loss: 1.3045 - Accuracy: 0.4493 - F1: 0.4695
sub_29:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.3768 - F1: 0.3654
sub_29:Test (Best Model) - Loss: 1.2373 - Accuracy: 0.4928 - F1: 0.4915
sub_29:Test (Best Model) - Loss: 1.2879 - Accuracy: 0.5072 - F1: 0.5213

=== Summary Results ===

acc: 32.19 ± 4.89
F1: 31.13 ± 5.47
acc-in: 39.18 ± 4.79
F1-in: 37.37 ± 5.19
