lr: 1e-06
sub_3:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.1618 - F1: 0.1710
sub_6:Test (Best Model) - Loss: 1.4501 - Accuracy: 0.1324 - F1: 0.0608
sub_5:Test (Best Model) - Loss: 1.4177 - Accuracy: 0.1471 - F1: 0.2035
sub_25:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2464 - F1: 0.2962
sub_18:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2319 - F1: 0.2432
sub_24:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2500 - F1: 0.2026
sub_10:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3088 - F1: 0.2641
sub_8:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.2794 - F1: 0.2569
sub_14:Test (Best Model) - Loss: 1.4271 - Accuracy: 0.1618 - F1: 0.1682
sub_17:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2319 - F1: 0.1953
sub_9:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3382 - F1: 0.3673
sub_27:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2319 - F1: 0.1953
sub_2:Test (Best Model) - Loss: 1.4105 - Accuracy: 0.3333 - F1: 0.3025
sub_26:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3188 - F1: 0.3530
sub_28:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2941 - F1: 0.2337
sub_1:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3529 - F1: 0.3665
sub_4:Test (Best Model) - Loss: 1.4090 - Accuracy: 0.2319 - F1: 0.2431
sub_11:Test (Best Model) - Loss: 1.4557 - Accuracy: 0.1304 - F1: 0.1644
sub_16:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.4559 - F1: 0.4168
sub_7:Test (Best Model) - Loss: 1.4200 - Accuracy: 0.0882 - F1: 0.1500
sub_20:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2794 - F1: 0.2960
sub_6:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.1471 - F1: 0.1227
sub_22:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.2500 - F1: 0.2793
sub_19:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.3088 - F1: 0.2841
sub_15:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3088 - F1: 0.3298
sub_12:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.2647 - F1: 0.2451
sub_5:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.4265 - F1: 0.3012
sub_13:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.1765 - F1: 0.1206
sub_18:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.0870 - F1: 0.1088
sub_14:Test (Best Model) - Loss: 1.3419 - Accuracy: 0.5147 - F1: 0.4770
sub_24:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3088 - F1: 0.2487
sub_21:Test (Best Model) - Loss: 1.4664 - Accuracy: 0.0735 - F1: 0.1003
sub_10:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.2206 - F1: 0.1463
sub_26:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.1884 - F1: 0.1414
sub_23:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.4348 - F1: 0.4217
sub_4:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.4493 - F1: 0.3753
sub_16:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.3824 - F1: 0.3586
sub_28:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.5588 - F1: 0.5381
sub_29:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.2206 - F1: 0.2286
sub_1:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3824 - F1: 0.3429
sub_2:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.0725 - F1: 0.0813
sub_11:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.4638 - F1: 0.3969
sub_17:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3623 - F1: 0.3019
sub_20:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3088 - F1: 0.2904
sub_8:Test (Best Model) - Loss: 1.4421 - Accuracy: 0.1765 - F1: 0.1064
sub_27:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3623 - F1: 0.3019
sub_25:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2464 - F1: 0.1454
sub_9:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.3382 - F1: 0.2823
sub_3:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3824 - F1: 0.2962
sub_14:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.1765 - F1: 0.1622
sub_13:Test (Best Model) - Loss: 1.3480 - Accuracy: 0.4265 - F1: 0.3990
sub_15:Test (Best Model) - Loss: 1.3703 - Accuracy: 0.2941 - F1: 0.2331
sub_12:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.1471 - F1: 0.1313
sub_26:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2754 - F1: 0.2383
sub_18:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3623 - F1: 0.3497
sub_19:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2941 - F1: 0.2273
sub_21:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2353 - F1: 0.1910
sub_10:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.2135
sub_6:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.2647 - F1: 0.2287
sub_28:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.1912 - F1: 0.1654
sub_16:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.1029 - F1: 0.0791
sub_17:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2754 - F1: 0.2918
sub_23:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.4493 - F1: 0.3186
sub_22:Test (Best Model) - Loss: 1.4233 - Accuracy: 0.2059 - F1: 0.1395
sub_5:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.1618 - F1: 0.1082
sub_29:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.2941 - F1: 0.1721
sub_7:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.3529 - F1: 0.2663
sub_4:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.2319 - F1: 0.2303
sub_2:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.1739 - F1: 0.1496
sub_9:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2941 - F1: 0.2682
sub_8:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2647 - F1: 0.1806
sub_14:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.2941 - F1: 0.2642
sub_20:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3529 - F1: 0.3209
sub_27:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2754 - F1: 0.2918
sub_12:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2941 - F1: 0.2655
sub_24:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.1471 - F1: 0.1403
sub_13:Test (Best Model) - Loss: 1.4109 - Accuracy: 0.0147 - F1: 0.0076
sub_18:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.4203 - F1: 0.3912
sub_6:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3235 - F1: 0.2854
sub_26:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3623 - F1: 0.3445
sub_11:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.2029 - F1: 0.1808
sub_10:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3676 - F1: 0.3244
sub_19:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.2353 - F1: 0.2106
sub_16:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.2794 - F1: 0.2428
sub_22:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.1765 - F1: 0.1238
sub_28:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3971 - F1: 0.3166
sub_17:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4203 - F1: 0.4036
sub_14:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.2941 - F1: 0.2120
sub_23:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.3623 - F1: 0.3385
sub_3:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.4118 - F1: 0.3881
sub_7:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.4118 - F1: 0.3349
sub_2:Test (Best Model) - Loss: 1.3536 - Accuracy: 0.3623 - F1: 0.3185
sub_15:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2794 - F1: 0.2751
sub_4:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.4058 - F1: 0.3384
sub_25:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.2609 - F1: 0.2191
sub_20:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.1765 - F1: 0.1859
sub_9:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.2206 - F1: 0.1974
sub_5:Test (Best Model) - Loss: 1.3248 - Accuracy: 0.3676 - F1: 0.3163
sub_24:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.3088 - F1: 0.2720
sub_12:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.2500 - F1: 0.2618
sub_27:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4203 - F1: 0.4036
sub_29:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.3676 - F1: 0.3290
sub_8:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.2233
sub_6:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.1176 - F1: 0.1160
sub_1:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.3529 - F1: 0.3613
sub_11:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.2899 - F1: 0.2639
sub_26:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2174 - F1: 0.2040
sub_10:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2794 - F1: 0.1578
sub_18:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.2754 - F1: 0.2267
sub_19:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.2500 - F1: 0.1672
sub_22:Test (Best Model) - Loss: 1.3428 - Accuracy: 0.3971 - F1: 0.4040
sub_28:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.0882 - F1: 0.0999
sub_14:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.1912 - F1: 0.1756
sub_16:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.1912 - F1: 0.1585
sub_7:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.4853 - F1: 0.5032
sub_20:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.4706 - F1: 0.3293
sub_2:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.2464 - F1: 0.1774
sub_13:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2353 - F1: 0.1399
sub_23:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.2319 - F1: 0.2059
sub_21:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.3676 - F1: 0.3630
sub_24:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.1618 - F1: 0.1195
sub_15:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3235 - F1: 0.2852
sub_12:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2353 - F1: 0.1802
sub_8:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3676 - F1: 0.3406
sub_3:Test (Best Model) - Loss: 1.3320 - Accuracy: 0.4853 - F1: 0.4334
sub_4:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.3768 - F1: 0.2692
sub_10:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.3824 - F1: 0.2561
sub_22:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.3824 - F1: 0.3005
sub_5:Test (Best Model) - Loss: 1.3718 - Accuracy: 0.3235 - F1: 0.3039
sub_7:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.2941 - F1: 0.2022
sub_1:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2059 - F1: 0.2095
sub_28:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.1471 - F1: 0.1318
sub_17:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2319 - F1: 0.1712
sub_26:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.4412 - F1: 0.3684
sub_23:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.3043 - F1: 0.2216
sub_13:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2941 - F1: 0.2311
sub_29:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.4118 - F1: 0.3850
sub_9:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.1618 - F1: 0.1698
sub_25:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3043 - F1: 0.2971
sub_2:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.3824 - F1: 0.2861
sub_11:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.4638 - F1: 0.4204
sub_16:Test (Best Model) - Loss: 1.3578 - Accuracy: 0.3824 - F1: 0.2601
sub_20:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.2353 - F1: 0.2545
sub_21:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.5000 - F1: 0.4963
sub_6:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.2464 - F1: 0.2653
sub_12:Test (Best Model) - Loss: 1.4346 - Accuracy: 0.0435 - F1: 0.0406
sub_8:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3971 - F1: 0.3652
sub_14:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.2206 - F1: 0.2353
sub_27:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2319 - F1: 0.1712
sub_15:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.2941 - F1: 0.2431
sub_1:Test (Best Model) - Loss: 1.4013 - Accuracy: 0.2353 - F1: 0.1849
sub_10:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2941 - F1: 0.1880
sub_18:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2500 - F1: 0.2447
sub_24:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.1324 - F1: 0.1472
sub_19:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3971 - F1: 0.3092
sub_26:Test (Best Model) - Loss: 1.3402 - Accuracy: 0.4706 - F1: 0.4095
sub_3:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2206 - F1: 0.1833
sub_2:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3676 - F1: 0.2994
sub_22:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.3043 - F1: 0.2632
sub_9:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.1765 - F1: 0.1968
sub_13:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2754 - F1: 0.2365
sub_4:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2464 - F1: 0.2094
sub_20:Test (Best Model) - Loss: 1.4123 - Accuracy: 0.2353 - F1: 0.1881
sub_6:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3478 - F1: 0.3349
sub_14:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.2941 - F1: 0.2493
sub_28:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.3676 - F1: 0.2749
sub_8:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3529 - F1: 0.2748
sub_29:Test (Best Model) - Loss: 1.4034 - Accuracy: 0.0735 - F1: 0.0686
sub_15:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2794 - F1: 0.2700
sub_17:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3623 - F1: 0.3021
sub_21:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.1912 - F1: 0.1243
sub_11:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.3768 - F1: 0.3139
sub_10:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2500 - F1: 0.1941
sub_23:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.3676 - F1: 0.2597
sub_12:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.2754 - F1: 0.2500
sub_19:Test (Best Model) - Loss: 1.4295 - Accuracy: 0.1471 - F1: 0.1208
sub_24:Test (Best Model) - Loss: 1.4125 - Accuracy: 0.2059 - F1: 0.1616
sub_16:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.4559 - F1: 0.4475
sub_2:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3235 - F1: 0.2341
sub_22:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3913 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.4203 - F1: 0.3750
sub_7:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3529 - F1: 0.3294
sub_18:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.3529 - F1: 0.2337
sub_3:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.1159 - F1: 0.1263
sub_5:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2794 - F1: 0.3021
sub_14:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.4706 - F1: 0.4333
sub_27:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3623 - F1: 0.3021
sub_1:Test (Best Model) - Loss: 1.3986 - Accuracy: 0.2464 - F1: 0.2149
sub_20:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.2500 - F1: 0.2248
sub_15:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.2206 - F1: 0.2000
sub_26:Test (Best Model) - Loss: 1.3615 - Accuracy: 0.3824 - F1: 0.3250
sub_28:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.3088 - F1: 0.2840
sub_10:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.5882 - F1: 0.6054
sub_23:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.3676 - F1: 0.3016
sub_24:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3382 - F1: 0.2912
sub_6:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3768 - F1: 0.2913
sub_12:Test (Best Model) - Loss: 1.4282 - Accuracy: 0.1304 - F1: 0.0852
sub_13:Test (Best Model) - Loss: 1.4041 - Accuracy: 0.1594 - F1: 0.1353
sub_11:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.1739 - F1: 0.1564
sub_8:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.3529 - F1: 0.2869
sub_29:Test (Best Model) - Loss: 1.4159 - Accuracy: 0.2941 - F1: 0.2426
sub_9:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.5294 - F1: 0.4533
sub_3:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.3188 - F1: 0.2814
sub_21:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.3235 - F1: 0.2849
sub_19:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2647 - F1: 0.2073
sub_2:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.2353 - F1: 0.1432
sub_18:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.1912 - F1: 0.1421
sub_20:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.4412 - F1: 0.3799
sub_4:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.3333 - F1: 0.2524
sub_1:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.1884 - F1: 0.1849
sub_25:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3235 - F1: 0.2788
sub_22:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.4058 - F1: 0.3950
sub_10:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3088 - F1: 0.2017
sub_17:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.2609 - F1: 0.2214
sub_24:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.1765 - F1: 0.1505
sub_14:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.0882 - F1: 0.1005
sub_5:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.5441 - F1: 0.4460
sub_12:Test (Best Model) - Loss: 1.3402 - Accuracy: 0.4638 - F1: 0.4607
sub_8:Test (Best Model) - Loss: 1.3422 - Accuracy: 0.3824 - F1: 0.3934
sub_28:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.1912 - F1: 0.1295
sub_13:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.1884 - F1: 0.1476
sub_16:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3529 - F1: 0.3597
sub_29:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.4118 - F1: 0.3596
sub_26:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.3235 - F1: 0.3030
sub_2:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.4265 - F1: 0.4119
sub_11:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2899 - F1: 0.2745
sub_15:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.2500 - F1: 0.2236
sub_19:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.1618 - F1: 0.1578
sub_27:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.2609 - F1: 0.2214
sub_6:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.4638 - F1: 0.4453
sub_9:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3529 - F1: 0.3211
sub_22:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.3333 - F1: 0.2660
sub_7:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3235 - F1: 0.2570
sub_20:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3235 - F1: 0.2615
sub_23:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.1912 - F1: 0.1507
sub_3:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.2899 - F1: 0.2719
sub_4:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.1014 - F1: 0.0951
sub_24:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.2941 - F1: 0.2867
sub_25:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3529 - F1: 0.3313
sub_18:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.3088 - F1: 0.2824
sub_14:Test (Best Model) - Loss: 1.4089 - Accuracy: 0.3235 - F1: 0.2738
sub_17:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.3768 - F1: 0.3754
sub_28:Test (Best Model) - Loss: 1.4285 - Accuracy: 0.0294 - F1: 0.0156
sub_2:Test (Best Model) - Loss: 1.4213 - Accuracy: 0.2174 - F1: 0.1544
sub_8:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.2941 - F1: 0.2364
sub_21:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4118 - F1: 0.3737
sub_16:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3824 - F1: 0.3764
sub_29:Test (Best Model) - Loss: 1.4243 - Accuracy: 0.0882 - F1: 0.0682
sub_15:Test (Best Model) - Loss: 1.3210 - Accuracy: 0.5441 - F1: 0.5387
sub_12:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.3043 - F1: 0.2852
sub_6:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3333 - F1: 0.2605
sub_19:Test (Best Model) - Loss: 1.3357 - Accuracy: 0.5000 - F1: 0.4871
sub_1:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.2754 - F1: 0.2576
sub_27:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.3768 - F1: 0.3754
sub_4:Test (Best Model) - Loss: 1.3260 - Accuracy: 0.5072 - F1: 0.4476
sub_7:Test (Best Model) - Loss: 1.3761 - Accuracy: 0.2206 - F1: 0.2125
sub_10:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.3623 - F1: 0.3294
sub_24:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.1471 - F1: 0.1292
sub_26:Test (Best Model) - Loss: 1.3486 - Accuracy: 0.3676 - F1: 0.3194
sub_17:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3768 - F1: 0.3495
sub_23:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.2647 - F1: 0.2402
sub_13:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.2754 - F1: 0.1832
sub_25:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.4265 - F1: 0.3809
sub_2:Test (Best Model) - Loss: 1.4242 - Accuracy: 0.2609 - F1: 0.1736
sub_14:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2059 - F1: 0.1704
sub_28:Test (Best Model) - Loss: 1.4141 - Accuracy: 0.2206 - F1: 0.1138
sub_11:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.3333 - F1: 0.2900
sub_8:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.1176 - F1: 0.1059
sub_18:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3529 - F1: 0.2780
sub_16:Test (Best Model) - Loss: 1.4297 - Accuracy: 0.1324 - F1: 0.1332
sub_29:Test (Best Model) - Loss: 1.3216 - Accuracy: 0.5735 - F1: 0.5648
sub_3:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.5797 - F1: 0.5824
sub_21:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2647 - F1: 0.2580
sub_22:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.1739 - F1: 0.1435
sub_6:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.1449 - F1: 0.0977
sub_15:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.2647 - F1: 0.2492
sub_12:Test (Best Model) - Loss: 1.4180 - Accuracy: 0.1324 - F1: 0.1217
sub_10:Test (Best Model) - Loss: 1.4158 - Accuracy: 0.2319 - F1: 0.1786
sub_1:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.4493 - F1: 0.4148
sub_4:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3043 - F1: 0.2266
sub_26:Test (Best Model) - Loss: 1.4480 - Accuracy: 0.0441 - F1: 0.0341
sub_27:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3768 - F1: 0.3495
sub_5:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.1912 - F1: 0.2024
sub_17:Test (Best Model) - Loss: 1.4121 - Accuracy: 0.1884 - F1: 0.1476
sub_9:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.6912 - F1: 0.6934
sub_23:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.3676 - F1: 0.2627
sub_20:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.1739 - F1: 0.1402
sub_13:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2174 - F1: 0.1736
sub_8:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.1324 - F1: 0.1175
sub_19:Test (Best Model) - Loss: 1.4355 - Accuracy: 0.0588 - F1: 0.0656
sub_3:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3623 - F1: 0.3771
sub_28:Test (Best Model) - Loss: 1.4133 - Accuracy: 0.2647 - F1: 0.1643
sub_2:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3333 - F1: 0.3081
sub_29:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.2381
sub_12:Test (Best Model) - Loss: 1.4345 - Accuracy: 0.1618 - F1: 0.1431
sub_15:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2353 - F1: 0.1396
sub_25:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.5735 - F1: 0.5484
sub_1:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2319 - F1: 0.1544
sub_27:Test (Best Model) - Loss: 1.4121 - Accuracy: 0.1884 - F1: 0.1476
sub_21:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.4265 - F1: 0.3822
sub_26:Test (Best Model) - Loss: 1.4520 - Accuracy: 0.0588 - F1: 0.0615
sub_4:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2029 - F1: 0.1368
sub_16:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.1912 - F1: 0.1636
sub_24:Test (Best Model) - Loss: 1.4007 - Accuracy: 0.2500 - F1: 0.2061
sub_17:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.2353 - F1: 0.1687
sub_9:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.2647 - F1: 0.2148
sub_22:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3382 - F1: 0.2988
sub_10:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.3768 - F1: 0.3367
sub_7:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3676 - F1: 0.3201
sub_23:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3768 - F1: 0.3230
sub_14:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3676 - F1: 0.2961
sub_11:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3043 - F1: 0.2818
sub_18:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.3529 - F1: 0.2617
sub_2:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.3478 - F1: 0.2861
sub_19:Test (Best Model) - Loss: 1.4355 - Accuracy: 0.1176 - F1: 0.1157
sub_12:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2500 - F1: 0.2266
sub_25:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.1912 - F1: 0.1898
sub_4:Test (Best Model) - Loss: 1.4527 - Accuracy: 0.0435 - F1: 0.0476
sub_16:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.2794 - F1: 0.2156
sub_20:Test (Best Model) - Loss: 1.4048 - Accuracy: 0.2319 - F1: 0.2272
sub_8:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2647 - F1: 0.2841
sub_22:Test (Best Model) - Loss: 1.4067 - Accuracy: 0.1618 - F1: 0.1708
sub_6:Test (Best Model) - Loss: 1.4320 - Accuracy: 0.1884 - F1: 0.1424
sub_24:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.5147 - F1: 0.4839
sub_15:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.1324 - F1: 0.1125
sub_27:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.2353 - F1: 0.1687
sub_29:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.2464 - F1: 0.1885
sub_13:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3088 - F1: 0.1913
sub_17:Test (Best Model) - Loss: 1.4692 - Accuracy: 0.1029 - F1: 0.0593
sub_14:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.3971 - F1: 0.3882
sub_3:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3913 - F1: 0.3604
sub_9:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.2500 - F1: 0.2015
sub_7:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.3088 - F1: 0.2190
sub_28:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.1618 - F1: 0.1137
sub_23:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.0580 - F1: 0.0650
sub_11:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.2464 - F1: 0.1810
sub_5:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2794 - F1: 0.2326
sub_26:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.4706 - F1: 0.4411
sub_2:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.2609 - F1: 0.2273
sub_1:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.1324 - F1: 0.1545
sub_19:Test (Best Model) - Loss: 1.4547 - Accuracy: 0.1324 - F1: 0.1270
sub_16:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.4559 - F1: 0.4211
sub_21:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2941 - F1: 0.3050
sub_15:Test (Best Model) - Loss: 1.3710 - Accuracy: 0.3971 - F1: 0.2758
sub_20:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.3188 - F1: 0.3356
sub_8:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3235 - F1: 0.3126
sub_22:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3529 - F1: 0.3241
sub_25:Test (Best Model) - Loss: 1.4096 - Accuracy: 0.1618 - F1: 0.1646
sub_27:Test (Best Model) - Loss: 1.4692 - Accuracy: 0.1029 - F1: 0.0593
sub_10:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.1884 - F1: 0.1263
sub_29:Test (Best Model) - Loss: 1.4208 - Accuracy: 0.1304 - F1: 0.1050
sub_14:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.1765 - F1: 0.1760
sub_12:Test (Best Model) - Loss: 1.3430 - Accuracy: 0.4412 - F1: 0.4105
sub_4:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.2899 - F1: 0.2379
sub_18:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.5000 - F1: 0.4553
sub_6:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2754 - F1: 0.2678
sub_13:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2794 - F1: 0.1568
sub_7:Test (Best Model) - Loss: 1.4114 - Accuracy: 0.1765 - F1: 0.1275
sub_23:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3188 - F1: 0.3010
sub_24:Test (Best Model) - Loss: 1.4121 - Accuracy: 0.2794 - F1: 0.1954
sub_17:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3235 - F1: 0.2712
sub_11:Test (Best Model) - Loss: nan - Accuracy: 0.00 - F1: 0.00
sub_19:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.4853 - F1: 0.4717
sub_8:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3382 - F1: 0.3120
sub_9:Test (Best Model) - Loss: 1.4240 - Accuracy: 0.2500 - F1: 0.1442
sub_3:Test (Best Model) - Loss: 1.4590 - Accuracy: 0.1449 - F1: 0.0950
sub_15:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.3971 - F1: 0.3395
sub_4:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.2029 - F1: 0.2010
sub_6:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2464 - F1: 0.2263
sub_28:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.1912 - F1: 0.1379
sub_10:Test (Best Model) - Loss: 1.3471 - Accuracy: 0.5072 - F1: 0.4690
sub_5:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3088 - F1: 0.2985
sub_16:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.2794 - F1: 0.2085
sub_12:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2941 - F1: 0.2671
sub_27:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3235 - F1: 0.2712
sub_20:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3333 - F1: 0.3283
sub_21:Test (Best Model) - Loss: 1.4196 - Accuracy: 0.2059 - F1: 0.2009
sub_13:Test (Best Model) - Loss: 1.3850 - Accuracy: 0.3382 - F1: 0.2250
sub_22:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3235 - F1: 0.2730
sub_29:Test (Best Model) - Loss: 1.3442 - Accuracy: 0.4348 - F1: 0.4218
sub_23:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.3043 - F1: 0.2800
sub_17:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3235 - F1: 0.2393
sub_24:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.1765 - F1: 0.1794
sub_26:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.5294 - F1: 0.5128
sub_6:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.5217 - F1: 0.4883
sub_1:Test (Best Model) - Loss: 1.4215 - Accuracy: 0.2500 - F1: 0.2171
sub_4:Test (Best Model) - Loss: 1.3289 - Accuracy: 0.5507 - F1: 0.5013
sub_16:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.4265 - F1: 0.3445
sub_15:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3529 - F1: 0.2250
sub_28:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.2794 - F1: 0.1363
sub_18:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.5000 - F1: 0.4613
sub_7:Test (Best Model) - Loss: 1.4548 - Accuracy: 0.1765 - F1: 0.0882
sub_22:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3971 - F1: 0.3302
sub_20:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.5507 - F1: 0.5176
sub_11:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3768 - F1: 0.2939
sub_25:Test (Best Model) - Loss: 1.4294 - Accuracy: 0.0882 - F1: 0.0917
sub_27:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3235 - F1: 0.2393
sub_13:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.2794 - F1: 0.2208
sub_19:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.4412 - F1: 0.3890
sub_29:Test (Best Model) - Loss: 1.4146 - Accuracy: 0.2029 - F1: 0.1402
sub_26:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.6029 - F1: 0.5827
sub_21:Test (Best Model) - Loss: 1.4056 - Accuracy: 0.1618 - F1: 0.1385
sub_5:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.4118 - F1: 0.3657
sub_17:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.4118 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4853 - F1: 0.4508
sub_23:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3333 - F1: 0.3281
sub_1:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2206 - F1: 0.2086
sub_27:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.4118 - F1: 0.3333
sub_18:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3382 - F1: 0.3046
sub_19:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.3382 - F1: 0.2702
sub_3:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.5072 - F1: 0.4792
sub_29:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.4058 - F1: 0.2722
sub_21:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2647 - F1: 0.2568
sub_5:Test (Best Model) - Loss: 1.4200 - Accuracy: 0.2500 - F1: 0.2044
sub_25:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2647 - F1: 0.2703
sub_7:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2059 - F1: 0.0933
sub_9:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.2941 - F1: 0.2891
sub_1:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2500 - F1: 0.2385
sub_13:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.3971 - F1: 0.3056
sub_11:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3913 - F1: 0.3823
sub_3:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.3478 - F1: 0.3242
sub_18:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3971 - F1: 0.3992
sub_25:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3971 - F1: 0.3740
sub_5:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.3824 - F1: 0.3907
sub_9:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.4559 - F1: 0.3943
sub_21:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2059 - F1: 0.2104
sub_3:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2029 - F1: 0.1339
sub_1:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.5735 - F1: 0.5645
sub_7:Test (Best Model) - Loss: 1.4227 - Accuracy: 0.2059 - F1: 0.1461
sub_25:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.5147 - F1: 0.5132
sub_5:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2794 - F1: 0.2242
sub_11:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.4058 - F1: 0.3222
sub_21:Test (Best Model) - Loss: 1.3027 - Accuracy: 0.5588 - F1: 0.5058
sub_7:Test (Best Model) - Loss: 1.3260 - Accuracy: 0.4706 - F1: 0.3561
sub_5:Test (Best Model) - Loss: 1.3237 - Accuracy: 0.4853 - F1: 0.3773

=== Summary Results ===

acc: 29.77 ± 2.59
F1: 26.01 ± 3.00
acc-in: 31.50 ± 2.26
F1-in: 29.52 ± 2.02
