lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3321 - Accuracy: 0.3676 - F1: 0.3860
sub_1:Test (Best Model) - Loss: 1.3158 - Accuracy: 0.4853 - F1: 0.4989
sub_1:Test (Best Model) - Loss: 1.3305 - Accuracy: 0.4412 - F1: 0.4401
sub_1:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.3676 - F1: 0.3770
sub_1:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3971 - F1: 0.4082
sub_1:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.3768 - F1: 0.3809
sub_1:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.3623 - F1: 0.3565
sub_1:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.4348 - F1: 0.4280
sub_1:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2754 - F1: 0.2829
sub_1:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3188 - F1: 0.3104
sub_1:Test (Best Model) - Loss: 1.3368 - Accuracy: 0.3235 - F1: 0.3080
sub_1:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.4559 - F1: 0.4690
sub_1:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.3382 - F1: 0.3442
sub_1:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.3529 - F1: 0.3408
sub_1:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.2941 - F1: 0.2927
sub_2:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2899 - F1: 0.2842
sub_2:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.2174 - F1: 0.2214
sub_2:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.2754 - F1: 0.2724
sub_2:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2899 - F1: 0.2695
sub_2:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2609 - F1: 0.2667
sub_2:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.2941 - F1: 0.2758
sub_2:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.2647 - F1: 0.2581
sub_2:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.2794 - F1: 0.2292
sub_2:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2353 - F1: 0.2374
sub_2:Test (Best Model) - Loss: 1.3943 - Accuracy: 0.2353 - F1: 0.2397
sub_2:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2754 - F1: 0.2758
sub_2:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.4203 - F1: 0.4219
sub_2:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3043 - F1: 0.2928
sub_2:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2174 - F1: 0.2086
sub_2:Test (Best Model) - Loss: 1.4125 - Accuracy: 0.2174 - F1: 0.2198
sub_3:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.2500 - F1: 0.2391
sub_3:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.2059 - F1: 0.2038
sub_3:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.2500 - F1: 0.2548
sub_3:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2206 - F1: 0.2224
sub_3:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.1912 - F1: 0.1893
sub_3:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3043 - F1: 0.2825
sub_3:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2609 - F1: 0.2473
sub_3:Test (Best Model) - Loss: 1.3881 - Accuracy: 0.2754 - F1: 0.2597
sub_3:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2319 - F1: 0.2293
sub_3:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2464 - F1: 0.2233
sub_3:Test (Best Model) - Loss: 1.4071 - Accuracy: 0.2029 - F1: 0.2027
sub_3:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.2754 - F1: 0.2581
sub_3:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.3623 - F1: 0.3523
sub_3:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.2754 - F1: 0.2620
sub_3:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2754 - F1: 0.2499
sub_4:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.3913 - F1: 0.3843
sub_4:Test (Best Model) - Loss: 1.3001 - Accuracy: 0.3333 - F1: 0.3449
sub_4:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.4058 - F1: 0.3976
sub_4:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3623 - F1: 0.3866
sub_4:Test (Best Model) - Loss: 1.3249 - Accuracy: 0.3478 - F1: 0.3583
sub_4:Test (Best Model) - Loss: 1.3008 - Accuracy: 0.4493 - F1: 0.4481
sub_4:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.4348 - F1: 0.4230
sub_4:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.4638 - F1: 0.4734
sub_4:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.4058 - F1: 0.4245
sub_4:Test (Best Model) - Loss: 1.2558 - Accuracy: 0.4638 - F1: 0.4852
sub_4:Test (Best Model) - Loss: 1.2552 - Accuracy: 0.3333 - F1: 0.3068
sub_4:Test (Best Model) - Loss: 1.2850 - Accuracy: 0.4203 - F1: 0.3867
sub_4:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.3913 - F1: 0.3907
sub_4:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.3333 - F1: 0.3148
sub_4:Test (Best Model) - Loss: 1.3117 - Accuracy: 0.4058 - F1: 0.3781
sub_5:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.4118 - F1: 0.3946
sub_5:Test (Best Model) - Loss: 1.3304 - Accuracy: 0.4706 - F1: 0.4371
sub_5:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.4118 - F1: 0.3902
sub_5:Test (Best Model) - Loss: 1.3246 - Accuracy: 0.4118 - F1: 0.3893
sub_5:Test (Best Model) - Loss: 1.3391 - Accuracy: 0.3676 - F1: 0.3466
sub_5:Test (Best Model) - Loss: 1.2547 - Accuracy: 0.4559 - F1: 0.4258
sub_5:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4265 - F1: 0.4307
sub_5:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.5000 - F1: 0.5019
sub_5:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.4265 - F1: 0.3884
sub_5:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.4118 - F1: 0.4042
sub_5:Test (Best Model) - Loss: 1.2708 - Accuracy: 0.4265 - F1: 0.4467
sub_5:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.3235 - F1: 0.3314
sub_5:Test (Best Model) - Loss: 1.3110 - Accuracy: 0.4118 - F1: 0.4082
sub_5:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.4118 - F1: 0.3999
sub_5:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.4118 - F1: 0.3579
sub_6:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.2794 - F1: 0.2899
sub_6:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.3676 - F1: 0.3634
sub_6:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3824 - F1: 0.3645
sub_6:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3088 - F1: 0.2795
sub_6:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3382 - F1: 0.3575
sub_6:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.2754 - F1: 0.2617
sub_6:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.4493 - F1: 0.3933
sub_6:Test (Best Model) - Loss: 1.3076 - Accuracy: 0.3768 - F1: 0.3273
sub_6:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.3188 - F1: 0.3136
sub_6:Test (Best Model) - Loss: 1.3405 - Accuracy: 0.3623 - F1: 0.3462
sub_6:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3043 - F1: 0.3261
sub_6:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.2899 - F1: 0.2935
sub_6:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.4058 - F1: 0.4288
sub_6:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3768 - F1: 0.3876
sub_6:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.2174 - F1: 0.1995
sub_7:Test (Best Model) - Loss: 1.2162 - Accuracy: 0.5735 - F1: 0.5730
sub_7:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.4265 - F1: 0.3894
sub_7:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.4118 - F1: 0.3786
sub_7:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.5000 - F1: 0.4721
sub_7:Test (Best Model) - Loss: 1.2792 - Accuracy: 0.4559 - F1: 0.4558
sub_7:Test (Best Model) - Loss: 1.3160 - Accuracy: 0.3235 - F1: 0.2906
sub_7:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.3824 - F1: 0.3732
sub_7:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.4412 - F1: 0.4442
sub_7:Test (Best Model) - Loss: 1.3414 - Accuracy: 0.3382 - F1: 0.3386
sub_7:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3824 - F1: 0.3643
sub_7:Test (Best Model) - Loss: 1.3242 - Accuracy: 0.4265 - F1: 0.4385
sub_7:Test (Best Model) - Loss: 1.3391 - Accuracy: 0.3676 - F1: 0.3381
sub_7:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.4412 - F1: 0.4117
sub_7:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.4559 - F1: 0.4593
sub_7:Test (Best Model) - Loss: 1.3250 - Accuracy: 0.3235 - F1: 0.3000
sub_8:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.2059 - F1: 0.2143
sub_8:Test (Best Model) - Loss: 1.4180 - Accuracy: 0.2206 - F1: 0.2086
sub_8:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.1912 - F1: 0.1939
sub_8:Test (Best Model) - Loss: 1.3813 - Accuracy: 0.2647 - F1: 0.2746
sub_8:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.3235 - F1: 0.3157
sub_8:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.2470
sub_8:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.2794 - F1: 0.2867
sub_8:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2500 - F1: 0.2314
sub_8:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2647 - F1: 0.2572
sub_8:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3235 - F1: 0.3219
sub_8:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.3235 - F1: 0.3277
sub_8:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.3088 - F1: 0.3057
sub_8:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3235 - F1: 0.3253
sub_8:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.3235 - F1: 0.3386
sub_8:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2941 - F1: 0.2903
sub_9:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.3382 - F1: 0.3475
sub_9:Test (Best Model) - Loss: 1.3025 - Accuracy: 0.4118 - F1: 0.4181
sub_9:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3529 - F1: 0.3824
sub_9:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.3824 - F1: 0.3979
sub_9:Test (Best Model) - Loss: 1.3025 - Accuracy: 0.4412 - F1: 0.4741
sub_9:Test (Best Model) - Loss: 1.3470 - Accuracy: 0.2794 - F1: 0.2826
sub_9:Test (Best Model) - Loss: 1.3599 - Accuracy: 0.2500 - F1: 0.2879
sub_9:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.3235 - F1: 0.3262
sub_9:Test (Best Model) - Loss: 1.2826 - Accuracy: 0.3382 - F1: 0.3327
sub_9:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.3824 - F1: 0.3973
sub_9:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.2500 - F1: 0.2496
sub_9:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.3676 - F1: 0.3513
sub_9:Test (Best Model) - Loss: 1.3137 - Accuracy: 0.3529 - F1: 0.3678
sub_9:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2500 - F1: 0.2567
sub_9:Test (Best Model) - Loss: 1.2903 - Accuracy: 0.3676 - F1: 0.3924
sub_10:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2941 - F1: 0.2815
sub_10:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2941 - F1: 0.2899
sub_10:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3382 - F1: 0.3328
sub_10:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2059 - F1: 0.1753
sub_10:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2353 - F1: 0.2297
sub_10:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2353 - F1: 0.2192
sub_10:Test (Best Model) - Loss: 1.4057 - Accuracy: 0.2500 - F1: 0.2346
sub_10:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.2794 - F1: 0.2710
sub_10:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2059 - F1: 0.2021
sub_10:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.2500 - F1: 0.2446
sub_10:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.2319 - F1: 0.2378
sub_10:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.3188 - F1: 0.3179
sub_10:Test (Best Model) - Loss: 1.3940 - Accuracy: 0.2754 - F1: 0.2461
sub_10:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.3188 - F1: 0.3128
sub_10:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.1594 - F1: 0.1590
sub_11:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.3188 - F1: 0.3009
sub_11:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3188 - F1: 0.2845
sub_11:Test (Best Model) - Loss: 1.3615 - Accuracy: 0.3043 - F1: 0.3181
sub_11:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.3478 - F1: 0.3511
sub_11:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3188 - F1: 0.3013
sub_11:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3333 - F1: 0.3107
sub_11:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.3333 - F1: 0.3218
sub_11:Test (Best Model) - Loss: 1.3396 - Accuracy: 0.3623 - F1: 0.3276
sub_11:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3768 - F1: 0.3714
sub_11:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.3188 - F1: 0.2865
sub_11:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.3188 - F1: 0.3089
sub_11:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.2609 - F1: 0.2526
sub_11:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.3768 - F1: 0.3512
sub_11:Test (Best Model) - Loss: 1.3344 - Accuracy: 0.3623 - F1: 0.3305
sub_11:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.2899 - F1: 0.2818
sub_12:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.3088 - F1: 0.3076
sub_12:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.4265 - F1: 0.4345
sub_12:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.3382 - F1: 0.3297
sub_12:Test (Best Model) - Loss: 1.3245 - Accuracy: 0.3824 - F1: 0.3577
sub_12:Test (Best Model) - Loss: 1.3123 - Accuracy: 0.3971 - F1: 0.3729
sub_12:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3333 - F1: 0.3393
sub_12:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.2899 - F1: 0.3077
sub_12:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.4203 - F1: 0.4086
sub_12:Test (Best Model) - Loss: 1.3236 - Accuracy: 0.3623 - F1: 0.3689
sub_12:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.3623 - F1: 0.3546
sub_12:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.3382 - F1: 0.3020
sub_12:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3235 - F1: 0.3264
sub_12:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.4706 - F1: 0.4593
sub_12:Test (Best Model) - Loss: 1.3254 - Accuracy: 0.3824 - F1: 0.3949
sub_12:Test (Best Model) - Loss: 1.3473 - Accuracy: 0.4412 - F1: 0.4333
sub_13:Test (Best Model) - Loss: 1.3682 - Accuracy: 0.2941 - F1: 0.2940
sub_13:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.2794 - F1: 0.2622
sub_13:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.2647 - F1: 0.2463
sub_13:Test (Best Model) - Loss: 1.3047 - Accuracy: 0.3382 - F1: 0.3666
sub_13:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2500 - F1: 0.2584
sub_13:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.3043 - F1: 0.2687
sub_13:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2174 - F1: 0.1772
sub_13:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.2464 - F1: 0.2495
sub_13:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3333 - F1: 0.3187
sub_13:Test (Best Model) - Loss: 1.3442 - Accuracy: 0.3043 - F1: 0.2894
sub_13:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2353 - F1: 0.1972
sub_13:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.2647 - F1: 0.2440
sub_13:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.3088 - F1: 0.2753
sub_13:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.2794 - F1: 0.2933
sub_13:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.2941 - F1: 0.2936
sub_14:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3235 - F1: 0.3618
sub_14:Test (Best Model) - Loss: 1.3269 - Accuracy: 0.4118 - F1: 0.4188
sub_14:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.2794 - F1: 0.2764
sub_14:Test (Best Model) - Loss: 1.3470 - Accuracy: 0.2941 - F1: 0.2958
sub_14:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.2941 - F1: 0.2647
sub_14:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3235 - F1: 0.3054
sub_14:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.3382 - F1: 0.3408
sub_14:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.2941 - F1: 0.2894
sub_14:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3088 - F1: 0.3078
sub_14:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2500 - F1: 0.2444
sub_14:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2941 - F1: 0.3039
sub_14:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.2794 - F1: 0.2635
sub_14:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.3382 - F1: 0.3325
sub_14:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.4118 - F1: 0.4063
sub_14:Test (Best Model) - Loss: 1.3569 - Accuracy: 0.3088 - F1: 0.2310
sub_15:Test (Best Model) - Loss: 1.2964 - Accuracy: 0.2794 - F1: 0.3110
sub_15:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.3088 - F1: 0.2769
sub_15:Test (Best Model) - Loss: 1.2955 - Accuracy: 0.4412 - F1: 0.4654
sub_15:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.3676 - F1: 0.3947
sub_15:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.4412 - F1: 0.4642
sub_15:Test (Best Model) - Loss: 1.2795 - Accuracy: 0.4265 - F1: 0.4241
sub_15:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.4853 - F1: 0.4767
sub_15:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.4265 - F1: 0.4467
sub_15:Test (Best Model) - Loss: 1.2680 - Accuracy: 0.4706 - F1: 0.4662
sub_15:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4412 - F1: 0.4622
sub_15:Test (Best Model) - Loss: 1.3309 - Accuracy: 0.4412 - F1: 0.4308
sub_15:Test (Best Model) - Loss: 1.2779 - Accuracy: 0.3676 - F1: 0.3707
sub_15:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.4265 - F1: 0.4219
sub_15:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.3676 - F1: 0.3885
sub_15:Test (Best Model) - Loss: 1.3067 - Accuracy: 0.3824 - F1: 0.3921
sub_16:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.4118 - F1: 0.3696
sub_16:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.4412 - F1: 0.4272
sub_16:Test (Best Model) - Loss: 1.2984 - Accuracy: 0.4412 - F1: 0.4047
sub_16:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.2941 - F1: 0.2837
sub_16:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.4706 - F1: 0.4483
sub_16:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.2794 - F1: 0.2372
sub_16:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3382 - F1: 0.3153
sub_16:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2353 - F1: 0.2206
sub_16:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2794 - F1: 0.2515
sub_16:Test (Best Model) - Loss: 1.4032 - Accuracy: 0.2941 - F1: 0.2763
sub_16:Test (Best Model) - Loss: 1.3248 - Accuracy: 0.3676 - F1: 0.2655
sub_16:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.4118 - F1: 0.3812
sub_16:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.3382 - F1: 0.3244
sub_16:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2941 - F1: 0.2893
sub_16:Test (Best Model) - Loss: 1.3087 - Accuracy: 0.4853 - F1: 0.4333
sub_17:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3333 - F1: 0.3013
sub_17:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.3913 - F1: 0.3702
sub_17:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.4058 - F1: 0.3991
sub_17:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3043 - F1: 0.2490
sub_17:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.4493 - F1: 0.4375
sub_17:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3188 - F1: 0.2430
sub_17:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.3478 - F1: 0.2615
sub_17:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3043 - F1: 0.2542
sub_17:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.3478 - F1: 0.2844
sub_17:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.3478 - F1: 0.2926
sub_17:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.4118 - F1: 0.3852
sub_17:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.4559 - F1: 0.4378
sub_17:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3676 - F1: 0.3716
sub_17:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3088 - F1: 0.2810
sub_17:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.4265 - F1: 0.4005
sub_18:Test (Best Model) - Loss: 1.3297 - Accuracy: 0.4058 - F1: 0.3954
sub_18:Test (Best Model) - Loss: 1.3253 - Accuracy: 0.3478 - F1: 0.3531
sub_18:Test (Best Model) - Loss: 1.2945 - Accuracy: 0.4928 - F1: 0.4847
sub_18:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3043 - F1: 0.2982
sub_18:Test (Best Model) - Loss: 1.3843 - Accuracy: 0.2174 - F1: 0.2165
sub_18:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.3824 - F1: 0.3875
sub_18:Test (Best Model) - Loss: 1.3602 - Accuracy: 0.3824 - F1: 0.3578
sub_18:Test (Best Model) - Loss: 1.3655 - Accuracy: 0.2941 - F1: 0.3005
sub_18:Test (Best Model) - Loss: 1.3405 - Accuracy: 0.3088 - F1: 0.3225
sub_18:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.2941 - F1: 0.3146
sub_18:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.4265 - F1: 0.4169
sub_18:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.3382 - F1: 0.3516
sub_18:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3088 - F1: 0.3206
sub_18:Test (Best Model) - Loss: 1.3601 - Accuracy: 0.3382 - F1: 0.3126
sub_18:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3235 - F1: 0.3271
sub_19:Test (Best Model) - Loss: 1.4265 - Accuracy: 0.2206 - F1: 0.1896
sub_19:Test (Best Model) - Loss: 1.4080 - Accuracy: 0.3235 - F1: 0.2753
sub_19:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2794 - F1: 0.2731
sub_19:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.3088 - F1: 0.2729
sub_19:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.2521
sub_19:Test (Best Model) - Loss: 1.3228 - Accuracy: 0.3824 - F1: 0.3794
sub_19:Test (Best Model) - Loss: 1.3007 - Accuracy: 0.4118 - F1: 0.4127
sub_19:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.4412 - F1: 0.4050
sub_19:Test (Best Model) - Loss: 1.3020 - Accuracy: 0.4412 - F1: 0.4189
sub_19:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.3529 - F1: 0.3174
sub_19:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.2941 - F1: 0.2761
sub_19:Test (Best Model) - Loss: 1.3507 - Accuracy: 0.3235 - F1: 0.3224
sub_19:Test (Best Model) - Loss: 1.2565 - Accuracy: 0.4559 - F1: 0.4515
sub_19:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3088 - F1: 0.3298
sub_19:Test (Best Model) - Loss: 1.3321 - Accuracy: 0.2941 - F1: 0.3097
sub_20:Test (Best Model) - Loss: 1.2850 - Accuracy: 0.4265 - F1: 0.4090
sub_20:Test (Best Model) - Loss: 1.2867 - Accuracy: 0.3971 - F1: 0.4084
sub_20:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.3088 - F1: 0.3131
sub_20:Test (Best Model) - Loss: 1.3228 - Accuracy: 0.3824 - F1: 0.3886
sub_20:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.3971 - F1: 0.4165
sub_20:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.3235 - F1: 0.3050
sub_20:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.3382 - F1: 0.3430
sub_20:Test (Best Model) - Loss: 1.2837 - Accuracy: 0.3676 - F1: 0.4122
sub_20:Test (Best Model) - Loss: 1.3250 - Accuracy: 0.3235 - F1: 0.3169
sub_20:Test (Best Model) - Loss: 1.3505 - Accuracy: 0.3382 - F1: 0.3406
sub_20:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.4348 - F1: 0.4302
sub_20:Test (Best Model) - Loss: 1.3019 - Accuracy: 0.3478 - F1: 0.3468
sub_20:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.3623 - F1: 0.3720
sub_20:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.5507 - F1: 0.5403
sub_20:Test (Best Model) - Loss: 1.3079 - Accuracy: 0.3478 - F1: 0.3388
sub_21:Test (Best Model) - Loss: 1.3254 - Accuracy: 0.3088 - F1: 0.3061
sub_21:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.3824 - F1: 0.3363
sub_21:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.2647 - F1: 0.2620
sub_21:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.3235 - F1: 0.2771
sub_21:Test (Best Model) - Loss: 1.3119 - Accuracy: 0.3529 - F1: 0.3391
sub_21:Test (Best Model) - Loss: 1.3033 - Accuracy: 0.2647 - F1: 0.2437
sub_21:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.2794 - F1: 0.2468
sub_21:Test (Best Model) - Loss: 1.3066 - Accuracy: 0.3529 - F1: 0.3281
sub_21:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.3088 - F1: 0.3070
sub_21:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.3088 - F1: 0.2468
sub_21:Test (Best Model) - Loss: 1.3012 - Accuracy: 0.3824 - F1: 0.3640
sub_21:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.2647 - F1: 0.2332
sub_21:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3235 - F1: 0.2984
sub_21:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.3529 - F1: 0.3595
sub_21:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.3382 - F1: 0.3057
sub_22:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3235 - F1: 0.3362
sub_22:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.4706 - F1: 0.4513
sub_22:Test (Best Model) - Loss: 1.3654 - Accuracy: 0.3235 - F1: 0.3448
sub_22:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2647 - F1: 0.2786
sub_22:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2500 - F1: 0.2521
sub_22:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.3333 - F1: 0.3232
sub_22:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3913 - F1: 0.3607
sub_22:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.2899 - F1: 0.2842
sub_22:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2464 - F1: 0.2417
sub_22:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3043 - F1: 0.2861
sub_22:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.2794 - F1: 0.2777
sub_22:Test (Best Model) - Loss: 1.3774 - Accuracy: 0.2206 - F1: 0.2374
sub_22:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2794 - F1: 0.2682
sub_22:Test (Best Model) - Loss: 1.3737 - Accuracy: 0.2941 - F1: 0.3062
sub_22:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2500 - F1: 0.2526
sub_23:Test (Best Model) - Loss: 1.3505 - Accuracy: 0.2899 - F1: 0.2677
sub_23:Test (Best Model) - Loss: 1.2985 - Accuracy: 0.3333 - F1: 0.3389
sub_23:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.4058 - F1: 0.4130
sub_23:Test (Best Model) - Loss: 1.2890 - Accuracy: 0.3478 - F1: 0.3591
sub_23:Test (Best Model) - Loss: 1.2707 - Accuracy: 0.4203 - F1: 0.4339
sub_23:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.4265 - F1: 0.4145
sub_23:Test (Best Model) - Loss: 1.3269 - Accuracy: 0.4559 - F1: 0.4570
sub_23:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3824 - F1: 0.3790
sub_23:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.3529 - F1: 0.3473
sub_23:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.2647 - F1: 0.2618
sub_23:Test (Best Model) - Loss: 1.3101 - Accuracy: 0.3478 - F1: 0.3269
sub_23:Test (Best Model) - Loss: 1.3238 - Accuracy: 0.3188 - F1: 0.3187
sub_23:Test (Best Model) - Loss: 1.2454 - Accuracy: 0.4058 - F1: 0.3944
sub_23:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3913 - F1: 0.3890
sub_23:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.3043 - F1: 0.2978
sub_24:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.3088 - F1: 0.3025
sub_24:Test (Best Model) - Loss: 1.3821 - Accuracy: 0.3235 - F1: 0.3054
sub_24:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.3088 - F1: 0.3009
sub_24:Test (Best Model) - Loss: 1.3810 - Accuracy: 0.2647 - F1: 0.2642
sub_24:Test (Best Model) - Loss: 1.3726 - Accuracy: 0.3088 - F1: 0.3159
sub_24:Test (Best Model) - Loss: 1.3896 - Accuracy: 0.2941 - F1: 0.2956
sub_24:Test (Best Model) - Loss: 1.3809 - Accuracy: 0.3235 - F1: 0.3298
sub_24:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2647 - F1: 0.2488
sub_24:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.3088 - F1: 0.3038
sub_24:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3676 - F1: 0.3577
sub_24:Test (Best Model) - Loss: 1.4086 - Accuracy: 0.2353 - F1: 0.2481
sub_24:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.2647 - F1: 0.2632
sub_24:Test (Best Model) - Loss: 1.4048 - Accuracy: 0.2500 - F1: 0.2572
sub_24:Test (Best Model) - Loss: 1.4054 - Accuracy: 0.2353 - F1: 0.2366
sub_24:Test (Best Model) - Loss: 1.3984 - Accuracy: 0.2794 - F1: 0.2534
sub_25:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.3188 - F1: 0.3083
sub_25:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.3623 - F1: 0.3111
sub_25:Test (Best Model) - Loss: 1.3450 - Accuracy: 0.3623 - F1: 0.3522
sub_25:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.2899 - F1: 0.2209
sub_25:Test (Best Model) - Loss: 1.3466 - Accuracy: 0.2899 - F1: 0.2620
sub_25:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.2794 - F1: 0.2465
sub_25:Test (Best Model) - Loss: 1.3322 - Accuracy: 0.3824 - F1: 0.3546
sub_25:Test (Best Model) - Loss: 1.2884 - Accuracy: 0.4412 - F1: 0.4202
sub_25:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.3088 - F1: 0.2849
sub_25:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.3676 - F1: 0.3463
sub_25:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3529 - F1: 0.3487
sub_25:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.4118 - F1: 0.3649
sub_25:Test (Best Model) - Loss: 1.3215 - Accuracy: 0.4412 - F1: 0.4447
sub_25:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.2500 - F1: 0.2414
sub_25:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.3529 - F1: 0.3037
sub_26:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.4638 - F1: 0.4676
sub_26:Test (Best Model) - Loss: 1.2840 - Accuracy: 0.4058 - F1: 0.4110
sub_26:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.3913 - F1: 0.3937
sub_26:Test (Best Model) - Loss: 1.2929 - Accuracy: 0.3768 - F1: 0.3602
sub_26:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.4928 - F1: 0.5131
sub_26:Test (Best Model) - Loss: 1.3100 - Accuracy: 0.4118 - F1: 0.4201
sub_26:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3676 - F1: 0.3617
sub_26:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.2941 - F1: 0.2609
sub_26:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.3382 - F1: 0.3522
sub_26:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.3971 - F1: 0.4034
sub_26:Test (Best Model) - Loss: 1.3045 - Accuracy: 0.3971 - F1: 0.4048
sub_26:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.4265 - F1: 0.4398
sub_26:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.4706 - F1: 0.4800
sub_26:Test (Best Model) - Loss: 1.2886 - Accuracy: 0.4706 - F1: 0.4951
sub_26:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.4853 - F1: 0.5137
sub_27:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.3333 - F1: 0.3013
sub_27:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.3913 - F1: 0.3702
sub_27:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.4058 - F1: 0.3991
sub_27:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3043 - F1: 0.2490
sub_27:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.4493 - F1: 0.4375
sub_27:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.3188 - F1: 0.2430
sub_27:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.3478 - F1: 0.2615
sub_27:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3043 - F1: 0.2542
sub_27:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.3478 - F1: 0.2844
sub_27:Test (Best Model) - Loss: 1.3476 - Accuracy: 0.3478 - F1: 0.2926
sub_27:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.4118 - F1: 0.3852
sub_27:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.4559 - F1: 0.4378
sub_27:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3676 - F1: 0.3716
sub_27:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3088 - F1: 0.2810
sub_27:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.4265 - F1: 0.4005
sub_28:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2647 - F1: 0.2593
sub_28:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.2941 - F1: 0.2932
sub_28:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2500 - F1: 0.2257
sub_28:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.2794 - F1: 0.2022
sub_28:Test (Best Model) - Loss: 1.4103 - Accuracy: 0.1324 - F1: 0.0994
sub_28:Test (Best Model) - Loss: 1.4026 - Accuracy: 0.2206 - F1: 0.1743
sub_28:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2941 - F1: 0.2653
sub_28:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.3235 - F1: 0.2969
sub_28:Test (Best Model) - Loss: 1.4085 - Accuracy: 0.2647 - F1: 0.2308
sub_28:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2353 - F1: 0.1918
sub_28:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2353 - F1: 0.1990
sub_28:Test (Best Model) - Loss: 1.3266 - Accuracy: 0.4265 - F1: 0.4096
sub_28:Test (Best Model) - Loss: 1.3465 - Accuracy: 0.3676 - F1: 0.3373
sub_28:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3529 - F1: 0.3381
sub_28:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.3088 - F1: 0.2858
sub_29:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.4706 - F1: 0.4997
sub_29:Test (Best Model) - Loss: 1.2556 - Accuracy: 0.4412 - F1: 0.4373
sub_29:Test (Best Model) - Loss: 1.2048 - Accuracy: 0.4706 - F1: 0.4983
sub_29:Test (Best Model) - Loss: 1.2347 - Accuracy: 0.4412 - F1: 0.4583
sub_29:Test (Best Model) - Loss: 1.2643 - Accuracy: 0.4853 - F1: 0.5060
sub_29:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.4118 - F1: 0.4167
sub_29:Test (Best Model) - Loss: 1.1770 - Accuracy: 0.4706 - F1: 0.4738
sub_29:Test (Best Model) - Loss: 1.2078 - Accuracy: 0.5000 - F1: 0.5131
sub_29:Test (Best Model) - Loss: 1.1432 - Accuracy: 0.5000 - F1: 0.5293
sub_29:Test (Best Model) - Loss: 1.1937 - Accuracy: 0.4412 - F1: 0.4612
sub_29:Test (Best Model) - Loss: 1.2058 - Accuracy: 0.4928 - F1: 0.4996
sub_29:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.4493 - F1: 0.4680
sub_29:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.4638 - F1: 0.4856
sub_29:Test (Best Model) - Loss: 1.1575 - Accuracy: 0.5217 - F1: 0.5397
sub_29:Test (Best Model) - Loss: 1.2773 - Accuracy: 0.4348 - F1: 0.4591

=== Summary Results ===

acc: 34.44 ± 5.26
F1: 33.51 ± 5.70
acc-in: 40.03 ± 5.75
F1-in: 38.19 ± 5.92
