lr: 1e-06
sub_8:Test (Best Model) - Loss: 1.4190 - Accuracy: 0.1618 - F1: 0.1609
sub_14:Test (Best Model) - Loss: 1.4070 - Accuracy: 0.1765 - F1: 0.1639
sub_12:Test (Best Model) - Loss: 1.4096 - Accuracy: 0.1176 - F1: 0.1026
sub_20:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.3824 - F1: 0.3211
sub_23:Test (Best Model) - Loss: 1.4252 - Accuracy: 0.1304 - F1: 0.1263
sub_21:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2647 - F1: 0.2656
sub_1:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.1324 - F1: 0.1292
sub_18:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2609 - F1: 0.2619
sub_24:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.3088 - F1: 0.3038
sub_17:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.1884 - F1: 0.1836
sub_22:Test (Best Model) - Loss: 1.4253 - Accuracy: 0.0735 - F1: 0.0718
sub_11:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.2319 - F1: 0.2378
sub_15:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2059 - F1: 0.1954
sub_3:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.2059 - F1: 0.1969
sub_27:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.1884 - F1: 0.1836
sub_2:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.3043 - F1: 0.2831
sub_6:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3382 - F1: 0.3372
sub_10:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.3235 - F1: 0.3052
sub_29:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.3088 - F1: 0.3094
sub_25:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3188 - F1: 0.3061
sub_8:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.4412 - F1: 0.4300
sub_4:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.2754 - F1: 0.2637
sub_16:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.1765 - F1: 0.1699
sub_26:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2464 - F1: 0.2475
sub_14:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.2059 - F1: 0.1944
sub_28:Test (Best Model) - Loss: 1.4043 - Accuracy: 0.2353 - F1: 0.2381
sub_9:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3235 - F1: 0.2906
sub_12:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2353 - F1: 0.2060
sub_5:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.1618 - F1: 0.1444
sub_20:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.1765 - F1: 0.1803
sub_24:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2941 - F1: 0.2943
sub_7:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.2206 - F1: 0.1901
sub_19:Test (Best Model) - Loss: 1.4372 - Accuracy: 0.1912 - F1: 0.1496
sub_22:Test (Best Model) - Loss: 1.4169 - Accuracy: 0.1471 - F1: 0.1273
sub_11:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2174 - F1: 0.1649
sub_1:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3382 - F1: 0.3332
sub_23:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3478 - F1: 0.3523
sub_15:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.2206 - F1: 0.2155
sub_3:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.4118 - F1: 0.4068
sub_13:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2353 - F1: 0.2164
sub_6:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2941 - F1: 0.2992
sub_14:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.2059 - F1: 0.1981
sub_8:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.2500 - F1: 0.2415
sub_29:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2353 - F1: 0.2254
sub_18:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3478 - F1: 0.3366
sub_12:Test (Best Model) - Loss: 1.4101 - Accuracy: 0.1618 - F1: 0.1479
sub_25:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2464 - F1: 0.2454
sub_20:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.2500 - F1: 0.2296
sub_26:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.2754 - F1: 0.2599
sub_10:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.2647 - F1: 0.2511
sub_4:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.1304 - F1: 0.1320
sub_24:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2794 - F1: 0.2639
sub_17:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3188 - F1: 0.3025
sub_21:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.1618 - F1: 0.1410
sub_9:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.1471 - F1: 0.1502
sub_16:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2647 - F1: 0.2631
sub_22:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.1912 - F1: 0.1877
sub_27:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3188 - F1: 0.3025
sub_28:Test (Best Model) - Loss: 1.4229 - Accuracy: 0.1029 - F1: 0.1021
sub_14:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3824 - F1: 0.3608
sub_2:Test (Best Model) - Loss: 1.3986 - Accuracy: 0.2029 - F1: 0.2123
sub_6:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.2647 - F1: 0.2558
sub_3:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2500 - F1: 0.2443
sub_18:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3333 - F1: 0.3195
sub_11:Test (Best Model) - Loss: 1.4038 - Accuracy: 0.2174 - F1: 0.1992
sub_23:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3913 - F1: 0.4062
sub_15:Test (Best Model) - Loss: 1.3626 - Accuracy: 0.3529 - F1: 0.3278
sub_20:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2059 - F1: 0.2101
sub_12:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.2206 - F1: 0.2192
sub_13:Test (Best Model) - Loss: 1.4312 - Accuracy: 0.1471 - F1: 0.1292
sub_4:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2029 - F1: 0.1985
sub_7:Test (Best Model) - Loss: 1.3724 - Accuracy: 0.3382 - F1: 0.3122
sub_8:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2206 - F1: 0.2025
sub_29:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2647 - F1: 0.2577
sub_10:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.1324 - F1: 0.1336
sub_25:Test (Best Model) - Loss: 1.4103 - Accuracy: 0.1739 - F1: 0.1809
sub_5:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.2647 - F1: 0.2129
sub_28:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.3088 - F1: 0.2848
sub_1:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.3088 - F1: 0.3010
sub_14:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.1912 - F1: 0.1704
sub_21:Test (Best Model) - Loss: 1.3945 - Accuracy: 0.2794 - F1: 0.2770
sub_22:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.1765 - F1: 0.1995
sub_16:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2353 - F1: 0.2019
sub_26:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2754 - F1: 0.2800
sub_24:Test (Best Model) - Loss: 1.4156 - Accuracy: 0.1765 - F1: 0.1714
sub_2:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2464 - F1: 0.2135
sub_6:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.3088 - F1: 0.3189
sub_3:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.1912 - F1: 0.1778
sub_18:Test (Best Model) - Loss: 1.4259 - Accuracy: 0.1159 - F1: 0.1088
sub_19:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2059 - F1: 0.1866
sub_4:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.1739 - F1: 0.1721
sub_8:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.3235 - F1: 0.3039
sub_20:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3088 - F1: 0.2930
sub_11:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.1884 - F1: 0.1877
sub_10:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.1912 - F1: 0.1866
sub_12:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3529 - F1: 0.3674
sub_29:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.2500 - F1: 0.2396
sub_15:Test (Best Model) - Loss: 1.4038 - Accuracy: 0.1765 - F1: 0.1705
sub_7:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3088 - F1: 0.2999
sub_9:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.3382 - F1: 0.3419
sub_5:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.3971 - F1: 0.3906
sub_17:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2464 - F1: 0.2459
sub_27:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2464 - F1: 0.2459
sub_13:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2794 - F1: 0.2710
sub_14:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3971 - F1: 0.3829
sub_1:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2059 - F1: 0.2053
sub_6:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.2206 - F1: 0.1855
sub_26:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.1739 - F1: 0.1608
sub_24:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3235 - F1: 0.3457
sub_2:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.1594 - F1: 0.1751
sub_21:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.2059 - F1: 0.2018
sub_18:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2899 - F1: 0.2917
sub_28:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3676 - F1: 0.3053
sub_23:Test (Best Model) - Loss: 1.4069 - Accuracy: 0.2174 - F1: 0.2020
sub_3:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.3971 - F1: 0.3749
sub_22:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2647 - F1: 0.2414
sub_25:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.2174 - F1: 0.1910
sub_4:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3333 - F1: 0.3318
sub_8:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2941 - F1: 0.2929
sub_11:Test (Best Model) - Loss: 1.4009 - Accuracy: 0.2174 - F1: 0.2122
sub_16:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.1324 - F1: 0.1310
sub_14:Test (Best Model) - Loss: 1.4195 - Accuracy: 0.1765 - F1: 0.1697
sub_20:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2794 - F1: 0.2890
sub_6:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2464 - F1: 0.2274
sub_5:Test (Best Model) - Loss: 1.4341 - Accuracy: 0.0294 - F1: 0.0351
sub_29:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2206 - F1: 0.2044
sub_2:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.2029 - F1: 0.2115
sub_9:Test (Best Model) - Loss: 1.4225 - Accuracy: 0.2206 - F1: 0.1804
sub_15:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2500 - F1: 0.2412
sub_26:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2899 - F1: 0.2648
sub_10:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3235 - F1: 0.3389
sub_27:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2174 - F1: 0.2158
sub_12:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3043 - F1: 0.3045
sub_24:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.3382 - F1: 0.3408
sub_18:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.1912 - F1: 0.1851
sub_28:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.3529 - F1: 0.3254
sub_22:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.4348 - F1: 0.4273
sub_3:Test (Best Model) - Loss: 1.3703 - Accuracy: 0.2899 - F1: 0.2987
sub_19:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.3676 - F1: 0.3707
sub_1:Test (Best Model) - Loss: 1.3863 - Accuracy: 0.2941 - F1: 0.2785
sub_17:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2174 - F1: 0.2158
sub_7:Test (Best Model) - Loss: 1.4377 - Accuracy: 0.1176 - F1: 0.1025
sub_25:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2609 - F1: 0.2667
sub_16:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.2206 - F1: 0.2092
sub_14:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2500 - F1: 0.2406
sub_8:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2941 - F1: 0.2943
sub_6:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2609 - F1: 0.2300
sub_20:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.2794 - F1: 0.2650
sub_12:Test (Best Model) - Loss: 1.4222 - Accuracy: 0.1014 - F1: 0.1063
sub_4:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2754 - F1: 0.2845
sub_10:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.3382 - F1: 0.2790
sub_13:Test (Best Model) - Loss: 1.3573 - Accuracy: 0.2794 - F1: 0.2390
sub_29:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3824 - F1: 0.3742
sub_18:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.2500 - F1: 0.2528
sub_21:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2353 - F1: 0.2378
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.2794 - F1: 0.2658
sub_26:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.3824 - F1: 0.3713
sub_23:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2899 - F1: 0.2736
sub_24:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3088 - F1: 0.2889
sub_11:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.1739 - F1: 0.1513
sub_27:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2899 - F1: 0.2482
sub_2:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2500 - F1: 0.2360
sub_22:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.2174 - F1: 0.1773
sub_3:Test (Best Model) - Loss: 1.4431 - Accuracy: 0.0580 - F1: 0.0533
sub_17:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2899 - F1: 0.2482
sub_19:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.3382 - F1: 0.3097
sub_9:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.1176 - F1: 0.1236
sub_25:Test (Best Model) - Loss: 1.3909 - Accuracy: 0.2353 - F1: 0.2458
sub_7:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.1471 - F1: 0.1394
sub_1:Test (Best Model) - Loss: 1.3445 - Accuracy: 0.3768 - F1: 0.3663
sub_16:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.3529 - F1: 0.3445
sub_12:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.4058 - F1: 0.3479
sub_8:Test (Best Model) - Loss: 1.4047 - Accuracy: 0.2353 - F1: 0.2154
sub_4:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3623 - F1: 0.3333
sub_20:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2500 - F1: 0.2285
sub_26:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.2353 - F1: 0.2406
sub_24:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.2206 - F1: 0.1957
sub_21:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.2059 - F1: 0.2035
sub_28:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3235 - F1: 0.2610
sub_29:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.2571
sub_23:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2206 - F1: 0.1835
sub_18:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3235 - F1: 0.3130
sub_6:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2899 - F1: 0.2733
sub_11:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.3333 - F1: 0.3003
sub_10:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2794 - F1: 0.2520
sub_13:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.2539
sub_27:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2754 - F1: 0.2523
sub_2:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2353 - F1: 0.2095
sub_5:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.2794 - F1: 0.2294
sub_15:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2794 - F1: 0.2733
sub_14:Test (Best Model) - Loss: 1.4088 - Accuracy: 0.2647 - F1: 0.2501
sub_22:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3188 - F1: 0.3050
sub_16:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.2059 - F1: 0.1993
sub_8:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.1618 - F1: 0.1468
sub_7:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.2500 - F1: 0.2445
sub_17:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.2754 - F1: 0.2523
sub_12:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2899 - F1: 0.2690
sub_25:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2353 - F1: 0.2506
sub_1:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.3188 - F1: 0.3145
sub_26:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.1471 - F1: 0.1533
sub_3:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.3043 - F1: 0.2868
sub_24:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2647 - F1: 0.2591
sub_28:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.3088 - F1: 0.2116
sub_18:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2059 - F1: 0.2008
sub_21:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2794 - F1: 0.2521
sub_20:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.1912 - F1: 0.1903
sub_6:Test (Best Model) - Loss: 1.4077 - Accuracy: 0.1884 - F1: 0.1958
sub_11:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.2754 - F1: 0.2495
sub_4:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2899 - F1: 0.2972
sub_10:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.3824 - F1: 0.3427
sub_23:Test (Best Model) - Loss: 1.4113 - Accuracy: 0.1912 - F1: 0.1876
sub_27:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.1739 - F1: 0.1716
sub_13:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3768 - F1: 0.3362
sub_19:Test (Best Model) - Loss: 1.4035 - Accuracy: 0.2059 - F1: 0.1949
sub_16:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.2500 - F1: 0.2533
sub_14:Test (Best Model) - Loss: 1.3503 - Accuracy: 0.4118 - F1: 0.4367
sub_22:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2609 - F1: 0.2595
sub_9:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2941 - F1: 0.2842
sub_8:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2941 - F1: 0.2675
sub_17:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.1739 - F1: 0.1716
sub_26:Test (Best Model) - Loss: 1.4015 - Accuracy: 0.1324 - F1: 0.1203
sub_2:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2500 - F1: 0.2468
sub_25:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2500 - F1: 0.2419
sub_15:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.1029 - F1: 0.1053
sub_18:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.1912 - F1: 0.1843
sub_1:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.1884 - F1: 0.1788
sub_29:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3235 - F1: 0.3158
sub_6:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.3333 - F1: 0.3072
sub_7:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3529 - F1: 0.3385
sub_4:Test (Best Model) - Loss: 1.4225 - Accuracy: 0.1739 - F1: 0.1565
sub_20:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2794 - F1: 0.2860
sub_21:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.3382 - F1: 0.3227
sub_5:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.2626
sub_27:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2464 - F1: 0.2445
sub_12:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.2319 - F1: 0.2341
sub_10:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.2941 - F1: 0.2253
sub_24:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2353 - F1: 0.2349
sub_28:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.4118 - F1: 0.3633
sub_22:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2464 - F1: 0.2491
sub_13:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.1884 - F1: 0.1629
sub_11:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.1304 - F1: 0.1271
sub_3:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3333 - F1: 0.3046
sub_16:Test (Best Model) - Loss: 1.4159 - Accuracy: 0.2059 - F1: 0.1995
sub_2:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2206 - F1: 0.2187
sub_9:Test (Best Model) - Loss: 1.4224 - Accuracy: 0.1029 - F1: 0.1010
sub_1:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.3478 - F1: 0.3464
sub_25:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.2353 - F1: 0.2256
sub_17:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2464 - F1: 0.2445
sub_18:Test (Best Model) - Loss: 1.4203 - Accuracy: 0.1765 - F1: 0.1854
sub_20:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2174 - F1: 0.1832
sub_24:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.1765 - F1: 0.1589
sub_8:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2353 - F1: 0.2459
sub_7:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3235 - F1: 0.3107
sub_13:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3188 - F1: 0.2723
sub_5:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.1912 - F1: 0.1836
sub_6:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.2754 - F1: 0.2567
sub_22:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.1765 - F1: 0.1739
sub_10:Test (Best Model) - Loss: 1.3986 - Accuracy: 0.2059 - F1: 0.1375
sub_19:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2206 - F1: 0.2096
sub_21:Test (Best Model) - Loss: 1.4070 - Accuracy: 0.1765 - F1: 0.1773
sub_11:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.2029 - F1: 0.1994
sub_26:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3382 - F1: 0.3301
sub_29:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.1176 - F1: 0.1238
sub_23:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.1765 - F1: 0.1717
sub_14:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.1912 - F1: 0.1814
sub_27:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3043 - F1: 0.2826
sub_15:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.1765 - F1: 0.1673
sub_3:Test (Best Model) - Loss: 1.3992 - Accuracy: 0.2174 - F1: 0.2188
sub_4:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2899 - F1: 0.2750
sub_16:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2647 - F1: 0.2584
sub_28:Test (Best Model) - Loss: 1.3763 - Accuracy: 0.3235 - F1: 0.3261
sub_2:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.2647 - F1: 0.2419
sub_20:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.2899 - F1: 0.2717
sub_1:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2609 - F1: 0.2538
sub_12:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.1912 - F1: 0.1941
sub_24:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.4118 - F1: 0.3969
sub_6:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2899 - F1: 0.2919
sub_17:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3043 - F1: 0.2826
sub_13:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2464 - F1: 0.2117
sub_8:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.3235 - F1: 0.3102
sub_22:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.2500 - F1: 0.2513
sub_26:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3235 - F1: 0.2376
sub_11:Test (Best Model) - Loss: 1.4058 - Accuracy: 0.2319 - F1: 0.2193
sub_14:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.2941 - F1: 0.2847
sub_9:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.3088 - F1: 0.3166
sub_21:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2941 - F1: 0.2921
sub_3:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.2609 - F1: 0.2394
sub_27:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3333 - F1: 0.2836
sub_16:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.1912 - F1: 0.1766
sub_25:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.2794 - F1: 0.2642
sub_7:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3088 - F1: 0.3069
sub_23:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.2353 - F1: 0.2279
sub_18:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.4559 - F1: 0.4349
sub_5:Test (Best Model) - Loss: 1.3857 - Accuracy: 0.2353 - F1: 0.2116
sub_10:Test (Best Model) - Loss: 1.4066 - Accuracy: 0.2029 - F1: 0.2075
sub_17:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.3333 - F1: 0.2836
sub_19:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.3088 - F1: 0.2949
sub_28:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2353 - F1: 0.1636
sub_6:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3043 - F1: 0.2972
sub_24:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.1912 - F1: 0.1838
sub_29:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2353 - F1: 0.2338
sub_22:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.1765 - F1: 0.1704
sub_13:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2464 - F1: 0.2006
sub_4:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2899 - F1: 0.2699
sub_15:Test (Best Model) - Loss: 1.3739 - Accuracy: 0.2794 - F1: 0.2772
sub_26:Test (Best Model) - Loss: 1.3592 - Accuracy: 0.3529 - F1: 0.3300
sub_14:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.2353 - F1: 0.1944
sub_8:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.2206 - F1: 0.2269
sub_9:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2647 - F1: 0.2564
sub_2:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2319 - F1: 0.2117
sub_11:Test (Best Model) - Loss: 1.3465 - Accuracy: 0.3623 - F1: 0.3710
sub_20:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.1739 - F1: 0.1835
sub_16:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3235 - F1: 0.2939
sub_3:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.2754 - F1: 0.2238
sub_25:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2059 - F1: 0.2002
sub_12:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2794 - F1: 0.2572
sub_28:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2794 - F1: 0.2711
sub_5:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2500 - F1: 0.2289
sub_7:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.3529 - F1: 0.3445
sub_23:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2647 - F1: 0.2144
sub_13:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3382 - F1: 0.3277
sub_10:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2899 - F1: 0.2730
sub_6:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.1739 - F1: 0.1739
sub_22:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.2059 - F1: 0.1889
sub_27:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2647 - F1: 0.2639
sub_1:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.2647 - F1: 0.2412
sub_29:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3333 - F1: 0.3286
sub_11:Test (Best Model) - Loss: 1.4042 - Accuracy: 0.2029 - F1: 0.1995
sub_26:Test (Best Model) - Loss: 1.4099 - Accuracy: 0.2059 - F1: 0.2188
sub_14:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.1912 - F1: 0.1937
sub_15:Test (Best Model) - Loss: 1.4099 - Accuracy: 0.1912 - F1: 0.1865
sub_18:Test (Best Model) - Loss: 1.4158 - Accuracy: 0.2059 - F1: 0.1777
sub_24:Test (Best Model) - Loss: 1.4060 - Accuracy: 0.1912 - F1: 0.1828
sub_20:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.2174 - F1: 0.2095
sub_9:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2794 - F1: 0.2422
sub_17:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.2647 - F1: 0.2639
sub_16:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.2353 - F1: 0.2128
sub_4:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3188 - F1: 0.3287
sub_25:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2353 - F1: 0.2406
sub_13:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.3824 - F1: 0.3725
sub_8:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.1765 - F1: 0.1536
sub_23:Test (Best Model) - Loss: 1.4154 - Accuracy: 0.0870 - F1: 0.0755
sub_21:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2794 - F1: 0.2761
sub_5:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.3676 - F1: 0.3800
sub_28:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3824 - F1: 0.3571
sub_12:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.2647 - F1: 0.2498
sub_27:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3529 - F1: 0.3333
sub_22:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.2059 - F1: 0.1924
sub_15:Test (Best Model) - Loss: 1.3974 - Accuracy: 0.2500 - F1: 0.2397
sub_19:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.3824 - F1: 0.3436
sub_11:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.1449 - F1: 0.1467
sub_3:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.1739 - F1: 0.1523
sub_26:Test (Best Model) - Loss: 1.4085 - Accuracy: 0.2353 - F1: 0.2227
sub_2:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3913 - F1: 0.3652
sub_7:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2794 - F1: 0.2679
sub_10:Test (Best Model) - Loss: 1.4244 - Accuracy: 0.0870 - F1: 0.0868
sub_14:Test (Best Model) - Loss: 1.4179 - Accuracy: 0.1176 - F1: 0.1365
sub_29:Test (Best Model) - Loss: 1.3346 - Accuracy: 0.4493 - F1: 0.4203
sub_18:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.2059 - F1: 0.1985
sub_20:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.3188 - F1: 0.3002
sub_16:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2647 - F1: 0.2632
sub_25:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2059 - F1: 0.2174
sub_23:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.3478 - F1: 0.2825
sub_17:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3529 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2353 - F1: 0.2167
sub_28:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.3235 - F1: 0.3036
sub_6:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.1304 - F1: 0.1180
sub_9:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.2794 - F1: 0.2364
sub_13:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2353 - F1: 0.2287
sub_24:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2941 - F1: 0.2889
sub_4:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.1594 - F1: 0.1248
sub_1:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.1912 - F1: 0.1966
sub_3:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.1739 - F1: 0.1605
sub_12:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2500 - F1: 0.2094
sub_15:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2500 - F1: 0.2568
sub_2:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.2319 - F1: 0.2363
sub_27:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.2353 - F1: 0.2231
sub_11:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.2754 - F1: 0.2452
sub_19:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.1765 - F1: 0.1527
sub_10:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2319 - F1: 0.2134
sub_26:Test (Best Model) - Loss: 1.4050 - Accuracy: 0.2647 - F1: 0.2525
sub_28:Test (Best Model) - Loss: 1.3956 - Accuracy: 0.2353 - F1: 0.2394
sub_16:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.1912 - F1: 0.1749
sub_18:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.2059 - F1: 0.2035
sub_7:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3529 - F1: 0.3301
sub_21:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.2500 - F1: 0.2524
sub_29:Test (Best Model) - Loss: 1.4205 - Accuracy: 0.1449 - F1: 0.1246
sub_9:Test (Best Model) - Loss: 1.3440 - Accuracy: 0.4265 - F1: 0.4448
sub_4:Test (Best Model) - Loss: 1.4075 - Accuracy: 0.2319 - F1: 0.2307
sub_3:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.2029 - F1: 0.1937
sub_17:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.2353 - F1: 0.2231
sub_12:Test (Best Model) - Loss: 1.4123 - Accuracy: 0.2647 - F1: 0.2549
sub_2:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.2754 - F1: 0.2439
sub_1:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.2353 - F1: 0.2192
sub_19:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.3088 - F1: 0.3074
sub_27:Test (Best Model) - Loss: 1.4014 - Accuracy: 0.1912 - F1: 0.1643
sub_15:Test (Best Model) - Loss: 1.3828 - Accuracy: 0.1912 - F1: 0.1734
sub_28:Test (Best Model) - Loss: 1.4070 - Accuracy: 0.2353 - F1: 0.1802
sub_10:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.1739 - F1: 0.1803
sub_23:Test (Best Model) - Loss: 1.4257 - Accuracy: 0.1304 - F1: 0.1237
sub_5:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.3676 - F1: 0.3434
sub_25:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2647 - F1: 0.2584
sub_7:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.2353 - F1: 0.2181
sub_13:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2647 - F1: 0.2525
sub_17:Test (Best Model) - Loss: 1.4014 - Accuracy: 0.1912 - F1: 0.1643
sub_29:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2609 - F1: 0.2521
sub_21:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2647 - F1: 0.2631
sub_27:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.1471 - F1: 0.1369
sub_2:Test (Best Model) - Loss: 1.4373 - Accuracy: 0.1594 - F1: 0.1508
sub_4:Test (Best Model) - Loss: 1.4233 - Accuracy: 0.1739 - F1: 0.1791
sub_23:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.2174 - F1: 0.2189
sub_15:Test (Best Model) - Loss: 1.4191 - Accuracy: 0.2059 - F1: 0.1981
sub_1:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3676 - F1: 0.3338
sub_5:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.2206 - F1: 0.2224
sub_19:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4559 - F1: 0.4371
sub_7:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.2647 - F1: 0.2206
sub_9:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.1912 - F1: 0.1947
sub_17:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.1471 - F1: 0.1369
sub_21:Test (Best Model) - Loss: 1.4124 - Accuracy: 0.1912 - F1: 0.1919
sub_29:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2464 - F1: 0.2496
sub_13:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2941 - F1: 0.2501
sub_23:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.3333 - F1: 0.2790
sub_25:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.3676 - F1: 0.3605
sub_1:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.2794 - F1: 0.2768
sub_9:Test (Best Model) - Loss: 1.4111 - Accuracy: 0.2353 - F1: 0.2240
sub_5:Test (Best Model) - Loss: 1.4137 - Accuracy: 0.1471 - F1: 0.1167
sub_7:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.1912 - F1: 0.1933
sub_21:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.2794 - F1: 0.2631
sub_19:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2647 - F1: 0.2587
sub_9:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.2206 - F1: 0.2036
sub_19:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.1324 - F1: 0.1281
sub_5:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.1912 - F1: 0.1920
sub_19:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.2206 - F1: 0.1951
sub_5:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2647 - F1: 0.2167
sub_19:Test (Best Model) - Loss: 1.4318 - Accuracy: 0.1324 - F1: 0.1253

=== Summary Results ===

acc: 25.21 ± 1.54
F1: 23.95 ± 1.38
acc-in: 27.09 ± 2.27
F1-in: 26.06 ± 2.26
