lr: 1e-05
sub_15:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2794 - F1: 0.2563
sub_6:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.3382 - F1: 0.3321
sub_23:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.1304 - F1: 0.1268
sub_18:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.3333 - F1: 0.3271
sub_24:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.3971 - F1: 0.3767
sub_3:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2206 - F1: 0.2212
sub_1:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.1912 - F1: 0.1899
sub_26:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.2754 - F1: 0.2717
sub_25:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.4203 - F1: 0.3963
sub_12:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.1765 - F1: 0.1751
sub_28:Test (Best Model) - Loss: 1.4000 - Accuracy: 0.2353 - F1: 0.2276
sub_16:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2500 - F1: 0.2137
sub_21:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2647 - F1: 0.2657
sub_27:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2319 - F1: 0.2288
sub_14:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.2647 - F1: 0.2288
sub_8:Test (Best Model) - Loss: 1.4117 - Accuracy: 0.2059 - F1: 0.2030
sub_5:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3382 - F1: 0.2808
sub_2:Test (Best Model) - Loss: 1.3787 - Accuracy: 0.3188 - F1: 0.2976
sub_9:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.4118 - F1: 0.4077
sub_20:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.3971 - F1: 0.3461
sub_29:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3824 - F1: 0.3782
sub_13:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2500 - F1: 0.2519
sub_17:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.2319 - F1: 0.2288
sub_7:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2941 - F1: 0.2573
sub_27:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3043 - F1: 0.2891
sub_10:Test (Best Model) - Loss: 1.3496 - Accuracy: 0.3235 - F1: 0.3115
sub_22:Test (Best Model) - Loss: 1.4075 - Accuracy: 0.1176 - F1: 0.1055
sub_6:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3088 - F1: 0.2920
sub_19:Test (Best Model) - Loss: 1.4169 - Accuracy: 0.1765 - F1: 0.1954
sub_4:Test (Best Model) - Loss: 1.3326 - Accuracy: 0.3913 - F1: 0.3775
sub_24:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.3235 - F1: 0.3232
sub_15:Test (Best Model) - Loss: 1.3805 - Accuracy: 0.2794 - F1: 0.2785
sub_18:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.4203 - F1: 0.4167
sub_23:Test (Best Model) - Loss: 1.3336 - Accuracy: 0.4638 - F1: 0.4651
sub_28:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.1471 - F1: 0.1318
sub_16:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3088 - F1: 0.3073
sub_25:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3333 - F1: 0.3354
sub_17:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3043 - F1: 0.2891
sub_11:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3043 - F1: 0.3058
sub_14:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2794 - F1: 0.2595
sub_5:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3088 - F1: 0.2552
sub_21:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2206 - F1: 0.1859
sub_3:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.4559 - F1: 0.4483
sub_26:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.4348 - F1: 0.4201
sub_24:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3529 - F1: 0.3475
sub_20:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2941 - F1: 0.2848
sub_29:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3971 - F1: 0.3981
sub_7:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.4706 - F1: 0.4374
sub_22:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.1912 - F1: 0.1860
sub_28:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.3235 - F1: 0.3017
sub_2:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2464 - F1: 0.2523
sub_1:Test (Best Model) - Loss: 1.3336 - Accuracy: 0.4412 - F1: 0.4321
sub_10:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.3088 - F1: 0.3024
sub_4:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2609 - F1: 0.2490
sub_9:Test (Best Model) - Loss: 1.3364 - Accuracy: 0.3971 - F1: 0.3809
sub_27:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.3043 - F1: 0.2974
sub_25:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2464 - F1: 0.2430
sub_12:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2794 - F1: 0.2410
sub_21:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.3088 - F1: 0.3008
sub_8:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.4118 - F1: 0.4271
sub_16:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2500 - F1: 0.2146
sub_13:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.1618 - F1: 0.1391
sub_19:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2206 - F1: 0.1817
sub_7:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.3382 - F1: 0.3373
sub_15:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3971 - F1: 0.3843
sub_5:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.4853 - F1: 0.4822
sub_20:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.2647 - F1: 0.2583
sub_17:Test (Best Model) - Loss: 1.3789 - Accuracy: 0.3043 - F1: 0.2974
sub_22:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2353 - F1: 0.2430
sub_4:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2754 - F1: 0.2689
sub_11:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3333 - F1: 0.2876
sub_28:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3235 - F1: 0.2664
sub_27:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.2658
sub_2:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.3043 - F1: 0.2805
sub_1:Test (Best Model) - Loss: 1.3754 - Accuracy: 0.3529 - F1: 0.3521
sub_18:Test (Best Model) - Loss: 1.3173 - Accuracy: 0.5652 - F1: 0.5475
sub_12:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.1765 - F1: 0.1593
sub_13:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2941 - F1: 0.2940
sub_6:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3088 - F1: 0.3002
sub_8:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3088 - F1: 0.2858
sub_16:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.1618 - F1: 0.1692
sub_25:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3333 - F1: 0.3112
sub_15:Test (Best Model) - Loss: 1.3977 - Accuracy: 0.2059 - F1: 0.1989
sub_9:Test (Best Model) - Loss: 1.3234 - Accuracy: 0.5441 - F1: 0.5115
sub_14:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2206 - F1: 0.1633
sub_10:Test (Best Model) - Loss: 1.3958 - Accuracy: 0.2206 - F1: 0.2294
sub_5:Test (Best Model) - Loss: 1.4287 - Accuracy: 0.0588 - F1: 0.0566
sub_29:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.4412 - F1: 0.4441
sub_24:Test (Best Model) - Loss: 1.3900 - Accuracy: 0.2059 - F1: 0.1951
sub_20:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2059 - F1: 0.2092
sub_4:Test (Best Model) - Loss: 1.3998 - Accuracy: 0.2029 - F1: 0.1979
sub_18:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.1739 - F1: 0.1567
sub_7:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.1765 - F1: 0.1563
sub_11:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2609 - F1: 0.2460
sub_23:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.5072 - F1: 0.5190
sub_2:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.1739 - F1: 0.1879
sub_3:Test (Best Model) - Loss: 1.3543 - Accuracy: 0.3088 - F1: 0.3177
sub_22:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.2500 - F1: 0.2659
sub_12:Test (Best Model) - Loss: 1.3974 - Accuracy: 0.2500 - F1: 0.2490
sub_13:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.3235 - F1: 0.2829
sub_6:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.3529 - F1: 0.3564
sub_17:Test (Best Model) - Loss: 1.3861 - Accuracy: 0.2609 - F1: 0.2658
sub_15:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2500 - F1: 0.2412
sub_21:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2647 - F1: 0.2500
sub_26:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.4348 - F1: 0.4282
sub_24:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3676 - F1: 0.3805
sub_10:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.2500 - F1: 0.2334
sub_28:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.3676 - F1: 0.3604
sub_7:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.2500 - F1: 0.2385
sub_29:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3088 - F1: 0.2958
sub_11:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.1739 - F1: 0.1750
sub_27:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.2754 - F1: 0.2595
sub_23:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2464 - F1: 0.2199
sub_16:Test (Best Model) - Loss: 1.3965 - Accuracy: 0.2647 - F1: 0.2627
sub_25:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3188 - F1: 0.3208
sub_2:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.2319 - F1: 0.2388
sub_9:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.3088 - F1: 0.2999
sub_3:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2500 - F1: 0.2369
sub_13:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2500 - F1: 0.2362
sub_8:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2353 - F1: 0.2196
sub_15:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3088 - F1: 0.2939
sub_5:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.3824 - F1: 0.3261
sub_19:Test (Best Model) - Loss: 1.3445 - Accuracy: 0.4265 - F1: 0.4146
sub_1:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3235 - F1: 0.3289
sub_14:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.3971 - F1: 0.3907
sub_22:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3529 - F1: 0.3537
sub_6:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2353 - F1: 0.1941
sub_27:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3188 - F1: 0.2736
sub_29:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.2794 - F1: 0.2645
sub_4:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.3768 - F1: 0.3794
sub_18:Test (Best Model) - Loss: 1.3266 - Accuracy: 0.5217 - F1: 0.5260
sub_23:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3768 - F1: 0.3714
sub_13:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.4058 - F1: 0.3639
sub_25:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.3235 - F1: 0.3341
sub_24:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3235 - F1: 0.3293
sub_3:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.4118 - F1: 0.3965
sub_10:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3529 - F1: 0.3654
sub_17:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.2754 - F1: 0.2595
sub_16:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.3971 - F1: 0.3928
sub_28:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.2794 - F1: 0.1798
sub_9:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.3382 - F1: 0.3497
sub_20:Test (Best Model) - Loss: 1.3359 - Accuracy: 0.3971 - F1: 0.3679
sub_7:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.3235 - F1: 0.3185
sub_11:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.2899 - F1: 0.2758
sub_14:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.1765 - F1: 0.1611
sub_8:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.3529 - F1: 0.3303
sub_1:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.3088 - F1: 0.2962
sub_12:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4559 - F1: 0.4480
sub_15:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3529 - F1: 0.3563
sub_6:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.2319 - F1: 0.2156
sub_21:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2941 - F1: 0.2912
sub_13:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2174 - F1: 0.1994
sub_3:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.3188 - F1: 0.3272
sub_28:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.3235 - F1: 0.2342
sub_17:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.3188 - F1: 0.2736
sub_22:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.4638 - F1: 0.4583
sub_10:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3529 - F1: 0.2694
sub_29:Test (Best Model) - Loss: 1.3128 - Accuracy: 0.5294 - F1: 0.5259
sub_26:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.4348 - F1: 0.4219
sub_14:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.4412 - F1: 0.4200
sub_1:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.4638 - F1: 0.4559
sub_24:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.2941 - F1: 0.2766
sub_25:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.3824 - F1: 0.3737
sub_2:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3824 - F1: 0.3826
sub_16:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3088 - F1: 0.2928
sub_4:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3188 - F1: 0.3256
sub_21:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.2941 - F1: 0.2866
sub_11:Test (Best Model) - Loss: 1.3926 - Accuracy: 0.2029 - F1: 0.1682
sub_27:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.1884 - F1: 0.1808
sub_19:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.3235 - F1: 0.3338
sub_10:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2794 - F1: 0.2515
sub_18:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3235 - F1: 0.3092
sub_5:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.3971 - F1: 0.3904
sub_22:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.2899 - F1: 0.2180
sub_23:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2059 - F1: 0.1479
sub_3:Test (Best Model) - Loss: 1.4322 - Accuracy: 0.0725 - F1: 0.0661
sub_28:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3529 - F1: 0.3292
sub_13:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3623 - F1: 0.3330
sub_20:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.3971 - F1: 0.4007
sub_26:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.4203 - F1: 0.4088
sub_29:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3088 - F1: 0.3137
sub_16:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.2647 - F1: 0.2594
sub_4:Test (Best Model) - Loss: 1.3536 - Accuracy: 0.3913 - F1: 0.3736
sub_7:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.4706 - F1: 0.4676
sub_10:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.4265 - F1: 0.3887
sub_12:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.4058 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2899 - F1: 0.2192
sub_8:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.3529 - F1: 0.3364
sub_9:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.4412 - F1: 0.3954
sub_1:Test (Best Model) - Loss: 1.3453 - Accuracy: 0.3768 - F1: 0.3751
sub_27:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2319 - F1: 0.2318
sub_21:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3088 - F1: 0.2805
sub_25:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3088 - F1: 0.2842
sub_17:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.1884 - F1: 0.1808
sub_22:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3188 - F1: 0.3169
sub_15:Test (Best Model) - Loss: 1.4089 - Accuracy: 0.1324 - F1: 0.1337
sub_18:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.3529 - F1: 0.3569
sub_24:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2647 - F1: 0.2288
sub_20:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.3088 - F1: 0.2916
sub_28:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3824 - F1: 0.3527
sub_13:Test (Best Model) - Loss: 1.3879 - Accuracy: 0.2609 - F1: 0.2205
sub_10:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2941 - F1: 0.2274
sub_3:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.4058 - F1: 0.3824
sub_16:Test (Best Model) - Loss: 1.4084 - Accuracy: 0.2206 - F1: 0.2214
sub_23:Test (Best Model) - Loss: 1.4066 - Accuracy: 0.2353 - F1: 0.2229
sub_1:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2319 - F1: 0.2247
sub_2:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.2794 - F1: 0.2064
sub_29:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3824 - F1: 0.3814
sub_8:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.3382 - F1: 0.3388
sub_27:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3043 - F1: 0.2842
sub_11:Test (Best Model) - Loss: 1.3466 - Accuracy: 0.4348 - F1: 0.4006
sub_19:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2500 - F1: 0.2061
sub_17:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2319 - F1: 0.2318
sub_14:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3971 - F1: 0.3641
sub_6:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.3043 - F1: 0.2711
sub_18:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.3529 - F1: 0.3535
sub_21:Test (Best Model) - Loss: 1.3635 - Accuracy: 0.3235 - F1: 0.3123
sub_24:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2941 - F1: 0.2860
sub_12:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.2174 - F1: 0.2134
sub_10:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.2500 - F1: 0.1881
sub_5:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3235 - F1: 0.3126
sub_8:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.2353 - F1: 0.2154
sub_7:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3382 - F1: 0.3325
sub_1:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.3768 - F1: 0.3779
sub_9:Test (Best Model) - Loss: 1.3309 - Accuracy: 0.3235 - F1: 0.2349
sub_18:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.2941 - F1: 0.2899
sub_4:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.3623 - F1: 0.3631
sub_29:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.1471 - F1: 0.1540
sub_14:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2647 - F1: 0.2440
sub_28:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.2647 - F1: 0.2172
sub_2:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.3382 - F1: 0.3133
sub_13:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2319 - F1: 0.2011
sub_17:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3043 - F1: 0.2842
sub_15:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2206 - F1: 0.2125
sub_26:Test (Best Model) - Loss: 1.3150 - Accuracy: 0.4412 - F1: 0.4151
sub_21:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.1765 - F1: 0.1752
sub_12:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.4348 - F1: 0.3657
sub_16:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3529 - F1: 0.3536
sub_7:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3235 - F1: 0.3255
sub_6:Test (Best Model) - Loss: 1.3954 - Accuracy: 0.2029 - F1: 0.2051
sub_23:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.2059 - F1: 0.1986
sub_20:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2500 - F1: 0.2345
sub_19:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3676 - F1: 0.3171
sub_14:Test (Best Model) - Loss: 1.3964 - Accuracy: 0.2794 - F1: 0.2508
sub_4:Test (Best Model) - Loss: 1.4110 - Accuracy: 0.2174 - F1: 0.2055
sub_28:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2794 - F1: 0.2792
sub_11:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.3188 - F1: 0.2932
sub_22:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.3043 - F1: 0.2965
sub_24:Test (Best Model) - Loss: 1.3692 - Accuracy: 0.2500 - F1: 0.2434
sub_16:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.1912 - F1: 0.1766
sub_21:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.3382 - F1: 0.3413
sub_29:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.2941 - F1: 0.2912
sub_25:Test (Best Model) - Loss: 1.3797 - Accuracy: 0.3088 - F1: 0.3084
sub_8:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.1912 - F1: 0.1891
sub_10:Test (Best Model) - Loss: 1.3890 - Accuracy: 0.2029 - F1: 0.2034
sub_2:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.2500 - F1: 0.2455
sub_6:Test (Best Model) - Loss: 1.3679 - Accuracy: 0.3768 - F1: 0.3529
sub_20:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.2059 - F1: 0.2067
sub_13:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.3676 - F1: 0.3538
sub_18:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2353 - F1: 0.2278
sub_1:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.4203 - F1: 0.4093
sub_12:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.3478 - F1: 0.3132
sub_3:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.4058 - F1: 0.3893
sub_16:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3382 - F1: 0.3125
sub_4:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.3043 - F1: 0.2951
sub_11:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.1449 - F1: 0.1351
sub_23:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.2206 - F1: 0.2097
sub_7:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3676 - F1: 0.3627
sub_22:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.2899 - F1: 0.2785
sub_27:Test (Best Model) - Loss: 1.3381 - Accuracy: 0.3913 - F1: 0.3470
sub_2:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.3088 - F1: 0.2876
sub_18:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.2059 - F1: 0.2034
sub_8:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.3235 - F1: 0.3004
sub_15:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.3235 - F1: 0.3265
sub_20:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.2794 - F1: 0.2757
sub_19:Test (Best Model) - Loss: 1.3571 - Accuracy: 0.3971 - F1: 0.3905
sub_14:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.4118 - F1: 0.4597
sub_29:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.4203 - F1: 0.4126
sub_6:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3043 - F1: 0.2742
sub_11:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2464 - F1: 0.2360
sub_21:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3529 - F1: 0.3484
sub_9:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.5882 - F1: 0.5727
sub_5:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.4265 - F1: 0.4283
sub_23:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2941 - F1: 0.2373
sub_24:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3088 - F1: 0.2988
sub_4:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3478 - F1: 0.3214
sub_12:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.3333 - F1: 0.3463
sub_25:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.3676 - F1: 0.3423
sub_1:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3235 - F1: 0.3007
sub_28:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.4118 - F1: 0.3908
sub_16:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.3529 - F1: 0.3116
sub_15:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.1765 - F1: 0.1760
sub_17:Test (Best Model) - Loss: 1.3381 - Accuracy: 0.3913 - F1: 0.3470
sub_18:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.4853 - F1: 0.4609
sub_5:Test (Best Model) - Loss: 1.3798 - Accuracy: 0.2794 - F1: 0.2718
sub_3:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.3043 - F1: 0.3058
sub_10:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.4348 - F1: 0.4136
sub_26:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4412 - F1: 0.4193
sub_2:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2899 - F1: 0.2768
sub_13:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.3971 - F1: 0.3847
sub_23:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.2029 - F1: 0.1677
sub_11:Test (Best Model) - Loss: 1.3992 - Accuracy: 0.2609 - F1: 0.2525
sub_25:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.2561
sub_8:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2353 - F1: 0.2471
sub_24:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.4118 - F1: 0.4056
sub_22:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2941 - F1: 0.2794
sub_4:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3623 - F1: 0.3736
sub_21:Test (Best Model) - Loss: 1.3751 - Accuracy: 0.2647 - F1: 0.2617
sub_19:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.4265 - F1: 0.3908
sub_20:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.2319 - F1: 0.1969
sub_27:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2647 - F1: 0.2620
sub_16:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3235 - F1: 0.3235
sub_5:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.3971 - F1: 0.4141
sub_12:Test (Best Model) - Loss: 1.3743 - Accuracy: 0.3088 - F1: 0.3114
sub_3:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.2754 - F1: 0.2681
sub_25:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2794 - F1: 0.2790
sub_28:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3088 - F1: 0.2787
sub_1:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3088 - F1: 0.3081
sub_22:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2794 - F1: 0.2767
sub_9:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.4412 - F1: 0.3725
sub_26:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.1618 - F1: 0.1601
sub_14:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.3971 - F1: 0.3812
sub_16:Test (Best Model) - Loss: 1.4080 - Accuracy: 0.2059 - F1: 0.1970
sub_2:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3913 - F1: 0.3761
sub_10:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.2319 - F1: 0.2100
sub_7:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.4559 - F1: 0.4525
sub_6:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.3333 - F1: 0.3338
sub_29:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.5362 - F1: 0.5012
sub_24:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2206 - F1: 0.2213
sub_20:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.3188 - F1: 0.3137
sub_28:Test (Best Model) - Loss: 1.3938 - Accuracy: 0.2500 - F1: 0.2609
sub_21:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3088 - F1: 0.3089
sub_8:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3382 - F1: 0.3204
sub_11:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.4348 - F1: 0.4361
sub_17:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.2647 - F1: 0.2620
sub_1:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2500 - F1: 0.2359
sub_26:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.1471 - F1: 0.1335
sub_22:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.1765 - F1: 0.1716
sub_27:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3382 - F1: 0.3156
sub_4:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.2174 - F1: 0.1910
sub_14:Test (Best Model) - Loss: 1.3553 - Accuracy: 0.3382 - F1: 0.3248
sub_19:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2353 - F1: 0.2046
sub_18:Test (Best Model) - Loss: 1.3609 - Accuracy: 0.3824 - F1: 0.3805
sub_7:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.4118 - F1: 0.3757
sub_2:Test (Best Model) - Loss: 1.4002 - Accuracy: 0.2609 - F1: 0.2617
sub_9:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.4118 - F1: 0.3722
sub_23:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.3768 - F1: 0.3308
sub_13:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.3235 - F1: 0.3013
sub_11:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.2319 - F1: 0.2312
sub_15:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.3088 - F1: 0.3110
sub_8:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2500 - F1: 0.2403
sub_28:Test (Best Model) - Loss: 1.4100 - Accuracy: 0.2353 - F1: 0.1813
sub_26:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.4265 - F1: 0.4146
sub_12:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3529 - F1: 0.3303
sub_14:Test (Best Model) - Loss: 1.3942 - Accuracy: 0.2353 - F1: 0.1932
sub_1:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.3971 - F1: 0.3569
sub_4:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2899 - F1: 0.2881
sub_10:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3478 - F1: 0.3377
sub_2:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3188 - F1: 0.2819
sub_6:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.3768 - F1: 0.3484
sub_22:Test (Best Model) - Loss: 1.3731 - Accuracy: 0.2941 - F1: 0.2758
sub_25:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.2941 - F1: 0.2785
sub_7:Test (Best Model) - Loss: 1.4021 - Accuracy: 0.2353 - F1: 0.2184
sub_17:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3382 - F1: 0.3156
sub_5:Test (Best Model) - Loss: 1.3703 - Accuracy: 0.3676 - F1: 0.3529
sub_19:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.3824 - F1: 0.3931
sub_21:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2206 - F1: 0.2196
sub_29:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.1884 - F1: 0.1814
sub_27:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.2486
sub_24:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2941 - F1: 0.2791
sub_23:Test (Best Model) - Loss: 1.4018 - Accuracy: 0.2029 - F1: 0.1999
sub_13:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2647 - F1: 0.2615
sub_4:Test (Best Model) - Loss: 1.4149 - Accuracy: 0.2029 - F1: 0.2111
sub_15:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2941 - F1: 0.2842
sub_22:Test (Best Model) - Loss: 1.3976 - Accuracy: 0.2206 - F1: 0.2149
sub_8:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.1618 - F1: 0.1483
sub_11:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.2174 - F1: 0.2076
sub_6:Test (Best Model) - Loss: 1.4001 - Accuracy: 0.2174 - F1: 0.2130
sub_9:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.3529 - F1: 0.2974
sub_12:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.3088 - F1: 0.2808
sub_18:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.2941 - F1: 0.2744
sub_7:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.3088 - F1: 0.2643
sub_25:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2500 - F1: 0.2422
sub_2:Test (Best Model) - Loss: 1.4296 - Accuracy: 0.1739 - F1: 0.1601
sub_26:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.4706 - F1: 0.4076
sub_20:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3768 - F1: 0.3504
sub_19:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.4853 - F1: 0.4621
sub_3:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.4203 - F1: 0.4012
sub_5:Test (Best Model) - Loss: 1.4011 - Accuracy: 0.2647 - F1: 0.2493
sub_14:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.3088 - F1: 0.3061
sub_15:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2647 - F1: 0.2479
sub_13:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2647 - F1: 0.2300
sub_10:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2609 - F1: 0.2755
sub_24:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.3676 - F1: 0.3732
sub_17:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.2647 - F1: 0.2486
sub_8:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2794 - F1: 0.2557
sub_11:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3043 - F1: 0.2955
sub_1:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.3824 - F1: 0.3927
sub_7:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2500 - F1: 0.2540
sub_21:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.2941 - F1: 0.2741
sub_27:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.2335
sub_23:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.3043 - F1: 0.3047
sub_18:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2500 - F1: 0.2413
sub_26:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3676 - F1: 0.3345
sub_6:Test (Best Model) - Loss: 1.4088 - Accuracy: 0.1304 - F1: 0.1225
sub_12:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2794 - F1: 0.2338
sub_5:Test (Best Model) - Loss: 1.4048 - Accuracy: 0.1912 - F1: 0.1889
sub_15:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2353 - F1: 0.2265
sub_25:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3676 - F1: 0.3631
sub_29:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3913 - F1: 0.3825
sub_9:Test (Best Model) - Loss: 1.3316 - Accuracy: 0.3824 - F1: 0.4007
sub_19:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3235 - F1: 0.3078
sub_27:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.1912 - F1: 0.1891
sub_20:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.2754 - F1: 0.2668
sub_26:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2206 - F1: 0.2266
sub_3:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2174 - F1: 0.1813
sub_17:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2647 - F1: 0.2335
sub_12:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.2941 - F1: 0.2895
sub_14:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.1471 - F1: 0.1536
sub_20:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.3623 - F1: 0.3418
sub_19:Test (Best Model) - Loss: 1.4111 - Accuracy: 0.2059 - F1: 0.2009
sub_26:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2941 - F1: 0.2794
sub_5:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2500 - F1: 0.2144
sub_23:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3333 - F1: 0.2676
sub_29:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3043 - F1: 0.3140
sub_17:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.1912 - F1: 0.1891
sub_9:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.3382 - F1: 0.3431
sub_26:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.2794 - F1: 0.2609
sub_3:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2464 - F1: 0.2327
sub_5:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3088 - F1: 0.2556
sub_19:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2353 - F1: 0.2145
sub_9:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3676 - F1: 0.3332
sub_3:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.2464 - F1: 0.2418
sub_19:Test (Best Model) - Loss: 1.4197 - Accuracy: 0.1618 - F1: 0.1532
sub_9:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2353 - F1: 0.2145

=== Summary Results ===

acc: 30.57 ± 2.90
F1: 29.12 ± 2.93
acc-in: 35.53 ± 4.78
F1-in: 34.28 ± 4.68
