lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3327 - Accuracy: 0.2941 - F1: 0.3167
sub_1:Test (Best Model) - Loss: 1.3137 - Accuracy: 0.3971 - F1: 0.4214
sub_1:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.3088 - F1: 0.3009
sub_1:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.3676 - F1: 0.3951
sub_1:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.3235 - F1: 0.3220
sub_1:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.2754 - F1: 0.3004
sub_1:Test (Best Model) - Loss: 1.3216 - Accuracy: 0.3768 - F1: 0.3676
sub_1:Test (Best Model) - Loss: 1.3491 - Accuracy: 0.4203 - F1: 0.4194
sub_1:Test (Best Model) - Loss: 1.2738 - Accuracy: 0.4203 - F1: 0.4401
sub_1:Test (Best Model) - Loss: 1.3497 - Accuracy: 0.3188 - F1: 0.3395
sub_1:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.3824 - F1: 0.3872
sub_1:Test (Best Model) - Loss: 1.3461 - Accuracy: 0.3676 - F1: 0.3812
sub_1:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.2794 - F1: 0.2646
sub_1:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.4265 - F1: 0.4154
sub_1:Test (Best Model) - Loss: 1.3550 - Accuracy: 0.3676 - F1: 0.3536
sub_2:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.2754 - F1: 0.2655
sub_2:Test (Best Model) - Loss: 1.3830 - Accuracy: 0.3043 - F1: 0.3056
sub_2:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2609 - F1: 0.2621
sub_2:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.1449 - F1: 0.1432
sub_2:Test (Best Model) - Loss: 1.4232 - Accuracy: 0.2899 - F1: 0.2943
sub_2:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2500 - F1: 0.2529
sub_2:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2206 - F1: 0.2195
sub_2:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.2059 - F1: 0.1923
sub_2:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.3088 - F1: 0.3250
sub_2:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3529 - F1: 0.3655
sub_2:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.2754 - F1: 0.2646
sub_2:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2319 - F1: 0.2427
sub_2:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.3478 - F1: 0.3481
sub_2:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.2899 - F1: 0.2858
sub_2:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.3623 - F1: 0.3742
sub_3:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.2794 - F1: 0.2196
sub_3:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3529 - F1: 0.3422
sub_3:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.1765 - F1: 0.1564
sub_3:Test (Best Model) - Loss: 1.4076 - Accuracy: 0.2206 - F1: 0.2104
sub_3:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2206 - F1: 0.2205
sub_3:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.3043 - F1: 0.2670
sub_3:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.2609 - F1: 0.2077
sub_3:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2174 - F1: 0.2131
sub_3:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2754 - F1: 0.2644
sub_3:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.2754 - F1: 0.2367
sub_3:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3333 - F1: 0.3032
sub_3:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.2754 - F1: 0.2656
sub_3:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2174 - F1: 0.2093
sub_3:Test (Best Model) - Loss: 1.3945 - Accuracy: 0.2319 - F1: 0.1941
sub_3:Test (Best Model) - Loss: 1.3639 - Accuracy: 0.3188 - F1: 0.3026
sub_4:Test (Best Model) - Loss: 1.2045 - Accuracy: 0.4783 - F1: 0.4936
sub_4:Test (Best Model) - Loss: 1.3013 - Accuracy: 0.4203 - F1: 0.4189
sub_4:Test (Best Model) - Loss: 1.2582 - Accuracy: 0.4638 - F1: 0.4751
sub_4:Test (Best Model) - Loss: 1.2657 - Accuracy: 0.4203 - F1: 0.4380
sub_4:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.3913 - F1: 0.4054
sub_4:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4783 - F1: 0.4873
sub_4:Test (Best Model) - Loss: 1.2835 - Accuracy: 0.4493 - F1: 0.4518
sub_4:Test (Best Model) - Loss: 1.2720 - Accuracy: 0.4058 - F1: 0.4107
sub_4:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.3768 - F1: 0.3864
sub_4:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.4783 - F1: 0.4782
sub_4:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.3478 - F1: 0.3297
sub_4:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.3478 - F1: 0.3401
sub_4:Test (Best Model) - Loss: 1.2316 - Accuracy: 0.4493 - F1: 0.4493
sub_4:Test (Best Model) - Loss: 1.2720 - Accuracy: 0.3333 - F1: 0.3416
sub_4:Test (Best Model) - Loss: 1.2955 - Accuracy: 0.4638 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.4706 - F1: 0.4354
sub_5:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.4559 - F1: 0.4063
sub_5:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.3971 - F1: 0.3873
sub_5:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.4412 - F1: 0.4338
sub_5:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.3824 - F1: 0.3631
sub_5:Test (Best Model) - Loss: 1.2483 - Accuracy: 0.4853 - F1: 0.4682
sub_5:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.4559 - F1: 0.4501
sub_5:Test (Best Model) - Loss: 1.2560 - Accuracy: 0.4853 - F1: 0.4637
sub_5:Test (Best Model) - Loss: 1.2103 - Accuracy: 0.4559 - F1: 0.4318
sub_5:Test (Best Model) - Loss: 1.2902 - Accuracy: 0.4412 - F1: 0.4533
sub_5:Test (Best Model) - Loss: 1.2565 - Accuracy: 0.4265 - F1: 0.4253
sub_5:Test (Best Model) - Loss: 1.2896 - Accuracy: 0.4412 - F1: 0.4465
sub_5:Test (Best Model) - Loss: 1.2882 - Accuracy: 0.3971 - F1: 0.3613
sub_5:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.3824 - F1: 0.3716
sub_5:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.4265 - F1: 0.4218
sub_6:Test (Best Model) - Loss: 1.3436 - Accuracy: 0.4412 - F1: 0.4469
sub_6:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3676 - F1: 0.3715
sub_6:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.3382 - F1: 0.3299
sub_6:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.3971 - F1: 0.4060
sub_6:Test (Best Model) - Loss: 1.3283 - Accuracy: 0.3235 - F1: 0.3051
sub_6:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.4493 - F1: 0.4049
sub_6:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.3478 - F1: 0.3051
sub_6:Test (Best Model) - Loss: 1.3433 - Accuracy: 0.3333 - F1: 0.2896
sub_6:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3768 - F1: 0.3518
sub_6:Test (Best Model) - Loss: 1.3259 - Accuracy: 0.3768 - F1: 0.3517
sub_6:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.3188 - F1: 0.3318
sub_6:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.3043 - F1: 0.2910
sub_6:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2464 - F1: 0.2482
sub_6:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3333 - F1: 0.3453
sub_6:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3623 - F1: 0.3676
sub_7:Test (Best Model) - Loss: 1.3108 - Accuracy: 0.4412 - F1: 0.4093
sub_7:Test (Best Model) - Loss: 1.2819 - Accuracy: 0.4853 - F1: 0.4738
sub_7:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.3971 - F1: 0.3896
sub_7:Test (Best Model) - Loss: 1.2567 - Accuracy: 0.4706 - F1: 0.4572
sub_7:Test (Best Model) - Loss: 1.2361 - Accuracy: 0.4265 - F1: 0.4127
sub_7:Test (Best Model) - Loss: 1.3124 - Accuracy: 0.3529 - F1: 0.3301
sub_7:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.2941 - F1: 0.2900
sub_7:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.3971 - F1: 0.4083
sub_7:Test (Best Model) - Loss: 1.3520 - Accuracy: 0.3676 - F1: 0.3401
sub_7:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.3824 - F1: 0.3692
sub_7:Test (Best Model) - Loss: 1.2983 - Accuracy: 0.4412 - F1: 0.4208
sub_7:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3529 - F1: 0.3187
sub_7:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.3088 - F1: 0.2818
sub_7:Test (Best Model) - Loss: 1.3233 - Accuracy: 0.3382 - F1: 0.3182
sub_7:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.3529 - F1: 0.3809
sub_8:Test (Best Model) - Loss: 1.4054 - Accuracy: 0.2206 - F1: 0.2095
sub_8:Test (Best Model) - Loss: 1.4005 - Accuracy: 0.2353 - F1: 0.2504
sub_8:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.2647 - F1: 0.2888
sub_8:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.3382 - F1: 0.3362
sub_8:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2794 - F1: 0.2875
sub_8:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.2500 - F1: 0.2519
sub_8:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3529 - F1: 0.3553
sub_8:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3529 - F1: 0.3639
sub_8:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2794 - F1: 0.2675
sub_8:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.2941 - F1: 0.3119
sub_8:Test (Best Model) - Loss: 1.3946 - Accuracy: 0.2647 - F1: 0.2504
sub_8:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3529 - F1: 0.3515
sub_8:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.3235 - F1: 0.3263
sub_8:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3529 - F1: 0.3641
sub_8:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2206 - F1: 0.2310
sub_9:Test (Best Model) - Loss: 1.2395 - Accuracy: 0.5000 - F1: 0.5313
sub_9:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.4118 - F1: 0.4184
sub_9:Test (Best Model) - Loss: 1.2286 - Accuracy: 0.3235 - F1: 0.3630
sub_9:Test (Best Model) - Loss: 1.3129 - Accuracy: 0.3971 - F1: 0.4267
sub_9:Test (Best Model) - Loss: 1.2819 - Accuracy: 0.3676 - F1: 0.3891
sub_9:Test (Best Model) - Loss: 1.2912 - Accuracy: 0.3824 - F1: 0.4009
sub_9:Test (Best Model) - Loss: 1.3396 - Accuracy: 0.2794 - F1: 0.2735
sub_9:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.3088 - F1: 0.3185
sub_9:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.3971 - F1: 0.4020
sub_9:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.3088 - F1: 0.3337
sub_9:Test (Best Model) - Loss: 1.3551 - Accuracy: 0.3235 - F1: 0.3093
sub_9:Test (Best Model) - Loss: 1.3104 - Accuracy: 0.3676 - F1: 0.3516
sub_9:Test (Best Model) - Loss: 1.3027 - Accuracy: 0.3824 - F1: 0.4090
sub_9:Test (Best Model) - Loss: 1.3327 - Accuracy: 0.3824 - F1: 0.3728
sub_9:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.3824 - F1: 0.3819
sub_10:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2647 - F1: 0.2628
sub_10:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2941 - F1: 0.2801
sub_10:Test (Best Model) - Loss: 1.3538 - Accuracy: 0.2647 - F1: 0.2528
sub_10:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.3088 - F1: 0.3100
sub_10:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.2206 - F1: 0.2060
sub_10:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2500 - F1: 0.2463
sub_10:Test (Best Model) - Loss: 1.4073 - Accuracy: 0.3235 - F1: 0.3030
sub_10:Test (Best Model) - Loss: 1.4149 - Accuracy: 0.1471 - F1: 0.1485
sub_10:Test (Best Model) - Loss: 1.3935 - Accuracy: 0.2794 - F1: 0.2543
sub_10:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.2647 - F1: 0.2671
sub_10:Test (Best Model) - Loss: 1.4047 - Accuracy: 0.2754 - F1: 0.2740
sub_10:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.2754 - F1: 0.2825
sub_10:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.3913 - F1: 0.3889
sub_10:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3623 - F1: 0.3532
sub_10:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.2174 - F1: 0.2011
sub_11:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.4203 - F1: 0.4220
sub_11:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2609 - F1: 0.2320
sub_11:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.3043 - F1: 0.2905
sub_11:Test (Best Model) - Loss: 1.3422 - Accuracy: 0.3043 - F1: 0.2970
sub_11:Test (Best Model) - Loss: 1.3647 - Accuracy: 0.3188 - F1: 0.3169
sub_11:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.4348 - F1: 0.4202
sub_11:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.3913 - F1: 0.3724
sub_11:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.4493 - F1: 0.4452
sub_11:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.3623 - F1: 0.3398
sub_11:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.3043 - F1: 0.2940
sub_11:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.2754 - F1: 0.2428
sub_11:Test (Best Model) - Loss: 1.3350 - Accuracy: 0.4493 - F1: 0.4391
sub_11:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.3913 - F1: 0.3899
sub_11:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.3623 - F1: 0.3492
sub_11:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.3333 - F1: 0.3259
sub_12:Test (Best Model) - Loss: 1.2152 - Accuracy: 0.4559 - F1: 0.4447
sub_12:Test (Best Model) - Loss: 1.3063 - Accuracy: 0.4118 - F1: 0.4000
sub_12:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.3971 - F1: 0.3711
sub_12:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.4853 - F1: 0.5054
sub_12:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3971 - F1: 0.3890
sub_12:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.3333 - F1: 0.3421
sub_12:Test (Best Model) - Loss: 1.3272 - Accuracy: 0.3913 - F1: 0.3766
sub_12:Test (Best Model) - Loss: 1.2504 - Accuracy: 0.4493 - F1: 0.4194
sub_12:Test (Best Model) - Loss: 1.3104 - Accuracy: 0.3478 - F1: 0.3613
sub_12:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.2464 - F1: 0.2260
sub_12:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.3676 - F1: 0.3673
sub_12:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.4118 - F1: 0.4222
sub_12:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.3235 - F1: 0.3325
sub_12:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.4853 - F1: 0.4927
sub_12:Test (Best Model) - Loss: 1.3326 - Accuracy: 0.3971 - F1: 0.4064
sub_13:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.2206 - F1: 0.1980
sub_13:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3824 - F1: 0.3822
sub_13:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.3382 - F1: 0.3497
sub_13:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.2941 - F1: 0.3096
sub_13:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.2794 - F1: 0.2940
sub_13:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.3623 - F1: 0.3569
sub_13:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.2609 - F1: 0.2560
sub_13:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.3043 - F1: 0.2892
sub_13:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.2899 - F1: 0.3006
sub_13:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.2899 - F1: 0.2651
sub_13:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.2500 - F1: 0.2471
sub_13:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.3235 - F1: 0.3204
sub_13:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.1912 - F1: 0.1888
sub_13:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2794 - F1: 0.2563
sub_13:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.2647 - F1: 0.2795
sub_14:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.3382 - F1: 0.3403
sub_14:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.2941 - F1: 0.2896
sub_14:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.3382 - F1: 0.3411
sub_14:Test (Best Model) - Loss: 1.3272 - Accuracy: 0.2941 - F1: 0.3098
sub_14:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.2206 - F1: 0.1974
sub_14:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.2941 - F1: 0.2907
sub_14:Test (Best Model) - Loss: 1.3350 - Accuracy: 0.3824 - F1: 0.3581
sub_14:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.4118 - F1: 0.3842
sub_14:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.2941 - F1: 0.2532
sub_14:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.2794 - F1: 0.2421
sub_14:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.2941 - F1: 0.3005
sub_14:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3088 - F1: 0.2983
sub_14:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.2794 - F1: 0.2515
sub_14:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.3529 - F1: 0.3294
sub_14:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.3529 - F1: 0.3103
sub_15:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.3676 - F1: 0.3893
sub_15:Test (Best Model) - Loss: 1.3189 - Accuracy: 0.3529 - F1: 0.3541
sub_15:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.3382 - F1: 0.3472
sub_15:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.3088 - F1: 0.3458
sub_15:Test (Best Model) - Loss: 1.2663 - Accuracy: 0.4265 - F1: 0.4402
sub_15:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.4559 - F1: 0.4289
sub_15:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.3824 - F1: 0.3981
sub_15:Test (Best Model) - Loss: 1.2415 - Accuracy: 0.5441 - F1: 0.5390
sub_15:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.4412 - F1: 0.4644
sub_15:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.4265 - F1: 0.4252
sub_15:Test (Best Model) - Loss: 1.2794 - Accuracy: 0.3382 - F1: 0.3479
sub_15:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.4412 - F1: 0.4591
sub_15:Test (Best Model) - Loss: 1.2904 - Accuracy: 0.4118 - F1: 0.4085
sub_15:Test (Best Model) - Loss: 1.2386 - Accuracy: 0.4265 - F1: 0.4353
sub_15:Test (Best Model) - Loss: 1.2762 - Accuracy: 0.4412 - F1: 0.4580
sub_16:Test (Best Model) - Loss: 1.2789 - Accuracy: 0.3971 - F1: 0.3352
sub_16:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3529 - F1: 0.3214
sub_16:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.4265 - F1: 0.4196
sub_16:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.3676 - F1: 0.3669
sub_16:Test (Best Model) - Loss: 1.2270 - Accuracy: 0.5000 - F1: 0.4712
sub_16:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.3824 - F1: 0.3261
sub_16:Test (Best Model) - Loss: 1.3931 - Accuracy: 0.2353 - F1: 0.2288
sub_16:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3529 - F1: 0.3420
sub_16:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.2794 - F1: 0.2531
sub_16:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3529 - F1: 0.3380
sub_16:Test (Best Model) - Loss: 1.2870 - Accuracy: 0.4706 - F1: 0.3786
sub_16:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.5000 - F1: 0.4214
sub_16:Test (Best Model) - Loss: 1.2929 - Accuracy: 0.5441 - F1: 0.5232
sub_16:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.3088 - F1: 0.2840
sub_16:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.4118 - F1: 0.3650
sub_17:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.3768 - F1: 0.3383
sub_17:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3333 - F1: 0.3148
sub_17:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3043 - F1: 0.2457
sub_17:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3188 - F1: 0.3105
sub_17:Test (Best Model) - Loss: 1.3037 - Accuracy: 0.4058 - F1: 0.3577
sub_17:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.3913 - F1: 0.3404
sub_17:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3623 - F1: 0.2971
sub_17:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.4058 - F1: 0.3688
sub_17:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.4203 - F1: 0.3585
sub_17:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.3333 - F1: 0.2905
sub_17:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3235 - F1: 0.2914
sub_17:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.3676 - F1: 0.3381
sub_17:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.3529 - F1: 0.3502
sub_17:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.4118 - F1: 0.4058
sub_17:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.3382 - F1: 0.3051
sub_18:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.3333 - F1: 0.3373
sub_18:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.2609 - F1: 0.2688
sub_18:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.4058 - F1: 0.4134
sub_18:Test (Best Model) - Loss: 1.3183 - Accuracy: 0.4203 - F1: 0.4250
sub_18:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.3333 - F1: 0.3470
sub_18:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.2794 - F1: 0.3047
sub_18:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3088 - F1: 0.3118
sub_18:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2206 - F1: 0.2275
sub_18:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.2059 - F1: 0.2116
sub_18:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3235 - F1: 0.3305
sub_18:Test (Best Model) - Loss: 1.3359 - Accuracy: 0.3676 - F1: 0.3825
sub_18:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3235 - F1: 0.3220
sub_18:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.2941 - F1: 0.2981
sub_18:Test (Best Model) - Loss: 1.3324 - Accuracy: 0.3088 - F1: 0.3259
sub_18:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.2500 - F1: 0.2579
sub_19:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.2353 - F1: 0.2084
sub_19:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.2353 - F1: 0.1962
sub_19:Test (Best Model) - Loss: 1.3907 - Accuracy: 0.2647 - F1: 0.2258
sub_19:Test (Best Model) - Loss: 1.3862 - Accuracy: 0.2941 - F1: 0.3071
sub_19:Test (Best Model) - Loss: 1.4047 - Accuracy: 0.2941 - F1: 0.2376
sub_19:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.3529 - F1: 0.3515
sub_19:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.2941 - F1: 0.2735
sub_19:Test (Best Model) - Loss: 1.3219 - Accuracy: 0.3676 - F1: 0.3674
sub_19:Test (Best Model) - Loss: 1.3079 - Accuracy: 0.3382 - F1: 0.3118
sub_19:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.4118 - F1: 0.3860
sub_19:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3235 - F1: 0.2913
sub_19:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.3382 - F1: 0.3137
sub_19:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.3382 - F1: 0.3100
sub_19:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.2794 - F1: 0.2926
sub_19:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.2794 - F1: 0.2966
sub_20:Test (Best Model) - Loss: 1.2239 - Accuracy: 0.5588 - F1: 0.5742
sub_20:Test (Best Model) - Loss: 1.2830 - Accuracy: 0.4265 - F1: 0.4189
sub_20:Test (Best Model) - Loss: 1.3001 - Accuracy: 0.3382 - F1: 0.3251
sub_20:Test (Best Model) - Loss: 1.2812 - Accuracy: 0.4412 - F1: 0.4359
sub_20:Test (Best Model) - Loss: 1.2502 - Accuracy: 0.4265 - F1: 0.4437
sub_20:Test (Best Model) - Loss: 1.3265 - Accuracy: 0.3529 - F1: 0.3233
sub_20:Test (Best Model) - Loss: 1.2581 - Accuracy: 0.3824 - F1: 0.3806
sub_20:Test (Best Model) - Loss: 1.3181 - Accuracy: 0.3971 - F1: 0.4046
sub_20:Test (Best Model) - Loss: 1.3107 - Accuracy: 0.3529 - F1: 0.3256
sub_20:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.3235 - F1: 0.3237
sub_20:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.3913 - F1: 0.3720
sub_20:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.3188 - F1: 0.3433
sub_20:Test (Best Model) - Loss: 1.3183 - Accuracy: 0.3623 - F1: 0.3703
sub_20:Test (Best Model) - Loss: 1.2494 - Accuracy: 0.4638 - F1: 0.4466
sub_20:Test (Best Model) - Loss: 1.3082 - Accuracy: 0.3623 - F1: 0.3342
sub_21:Test (Best Model) - Loss: 1.3042 - Accuracy: 0.3676 - F1: 0.3262
sub_21:Test (Best Model) - Loss: 1.2637 - Accuracy: 0.3824 - F1: 0.3347
sub_21:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.2941 - F1: 0.2641
sub_21:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.3235 - F1: 0.3119
sub_21:Test (Best Model) - Loss: 1.3236 - Accuracy: 0.2941 - F1: 0.2749
sub_21:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.3676 - F1: 0.3827
sub_21:Test (Best Model) - Loss: 1.3033 - Accuracy: 0.3235 - F1: 0.3048
sub_21:Test (Best Model) - Loss: 1.2886 - Accuracy: 0.3235 - F1: 0.2995
sub_21:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.3382 - F1: 0.3303
sub_21:Test (Best Model) - Loss: 1.2452 - Accuracy: 0.4118 - F1: 0.3661
sub_21:Test (Best Model) - Loss: 1.2812 - Accuracy: 0.3088 - F1: 0.2779
sub_21:Test (Best Model) - Loss: 1.2907 - Accuracy: 0.3529 - F1: 0.3562
sub_21:Test (Best Model) - Loss: 1.3053 - Accuracy: 0.2647 - F1: 0.2378
sub_21:Test (Best Model) - Loss: 1.3327 - Accuracy: 0.3971 - F1: 0.3651
sub_21:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.4118 - F1: 0.3894
sub_22:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.3235 - F1: 0.3235
sub_22:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.2353 - F1: 0.2139
sub_22:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.2353 - F1: 0.2479
sub_22:Test (Best Model) - Loss: 1.3572 - Accuracy: 0.4118 - F1: 0.4276
sub_22:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.2059 - F1: 0.2212
sub_22:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.2464 - F1: 0.2352
sub_22:Test (Best Model) - Loss: 1.3253 - Accuracy: 0.3913 - F1: 0.3217
sub_22:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.3333 - F1: 0.3376
sub_22:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3333 - F1: 0.3189
sub_22:Test (Best Model) - Loss: 1.3321 - Accuracy: 0.3333 - F1: 0.3219
sub_22:Test (Best Model) - Loss: 1.3833 - Accuracy: 0.2059 - F1: 0.2096
sub_22:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.3529 - F1: 0.3666
sub_22:Test (Best Model) - Loss: 1.3626 - Accuracy: 0.3824 - F1: 0.3800
sub_22:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.2941 - F1: 0.2851
sub_22:Test (Best Model) - Loss: 1.3497 - Accuracy: 0.2647 - F1: 0.2877
sub_23:Test (Best Model) - Loss: 1.2552 - Accuracy: 0.4348 - F1: 0.4362
sub_23:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.3478 - F1: 0.3299
sub_23:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.3623 - F1: 0.3561
sub_23:Test (Best Model) - Loss: 1.2997 - Accuracy: 0.4203 - F1: 0.4265
sub_23:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.3333 - F1: 0.3141
sub_23:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.4118 - F1: 0.4121
sub_23:Test (Best Model) - Loss: 1.2694 - Accuracy: 0.4559 - F1: 0.4683
sub_23:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.4118 - F1: 0.4270
sub_23:Test (Best Model) - Loss: 1.3121 - Accuracy: 0.4412 - F1: 0.4535
sub_23:Test (Best Model) - Loss: 1.2764 - Accuracy: 0.4412 - F1: 0.4454
sub_23:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.3333 - F1: 0.3347
sub_23:Test (Best Model) - Loss: 1.2664 - Accuracy: 0.3478 - F1: 0.3473
sub_23:Test (Best Model) - Loss: 1.2378 - Accuracy: 0.3913 - F1: 0.3737
sub_23:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.4638 - F1: 0.4733
sub_23:Test (Best Model) - Loss: 1.2796 - Accuracy: 0.3043 - F1: 0.3208
sub_24:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.2353 - F1: 0.2204
sub_24:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.3676 - F1: 0.3292
sub_24:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.2500 - F1: 0.2493
sub_24:Test (Best Model) - Loss: 1.4048 - Accuracy: 0.2206 - F1: 0.2080
sub_24:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.3088 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3088 - F1: 0.3100
sub_24:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2206 - F1: 0.2133
sub_24:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2206 - F1: 0.2095
sub_24:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2941 - F1: 0.2820
sub_24:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2647 - F1: 0.2344
sub_24:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.2500 - F1: 0.2489
sub_24:Test (Best Model) - Loss: 1.4280 - Accuracy: 0.1324 - F1: 0.1230
sub_24:Test (Best Model) - Loss: 1.4052 - Accuracy: 0.2059 - F1: 0.2177
sub_24:Test (Best Model) - Loss: 1.3758 - Accuracy: 0.3088 - F1: 0.3033
sub_24:Test (Best Model) - Loss: 1.3681 - Accuracy: 0.2941 - F1: 0.3006
sub_25:Test (Best Model) - Loss: 1.2717 - Accuracy: 0.4058 - F1: 0.3933
sub_25:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.3043 - F1: 0.2809
sub_25:Test (Best Model) - Loss: 1.3268 - Accuracy: 0.2899 - F1: 0.2196
sub_25:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.3623 - F1: 0.3378
sub_25:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.4058 - F1: 0.3855
sub_25:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.3088 - F1: 0.2759
sub_25:Test (Best Model) - Loss: 1.3127 - Accuracy: 0.3676 - F1: 0.3016
sub_25:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.4118 - F1: 0.3703
sub_25:Test (Best Model) - Loss: 1.3078 - Accuracy: 0.3235 - F1: 0.3045
sub_25:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.2941 - F1: 0.2369
sub_25:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3676 - F1: 0.3368
sub_25:Test (Best Model) - Loss: 1.3323 - Accuracy: 0.3235 - F1: 0.3006
sub_25:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3824 - F1: 0.3572
sub_25:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.3235 - F1: 0.3000
sub_25:Test (Best Model) - Loss: 1.3219 - Accuracy: 0.4853 - F1: 0.4617
sub_26:Test (Best Model) - Loss: 1.2785 - Accuracy: 0.4348 - F1: 0.4489
sub_26:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.3768 - F1: 0.3757
sub_26:Test (Best Model) - Loss: 1.3075 - Accuracy: 0.4348 - F1: 0.4577
sub_26:Test (Best Model) - Loss: 1.2464 - Accuracy: 0.5362 - F1: 0.5339
sub_26:Test (Best Model) - Loss: 1.3291 - Accuracy: 0.3768 - F1: 0.3718
sub_26:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.4265 - F1: 0.4599
sub_26:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.3971 - F1: 0.4092
sub_26:Test (Best Model) - Loss: 1.2961 - Accuracy: 0.4412 - F1: 0.4267
sub_26:Test (Best Model) - Loss: 1.3031 - Accuracy: 0.4412 - F1: 0.4459
sub_26:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.3824 - F1: 0.3947
sub_26:Test (Best Model) - Loss: 1.2735 - Accuracy: 0.5000 - F1: 0.5284
sub_26:Test (Best Model) - Loss: 1.3004 - Accuracy: 0.4265 - F1: 0.4274
sub_26:Test (Best Model) - Loss: 1.3195 - Accuracy: 0.4265 - F1: 0.4354
sub_26:Test (Best Model) - Loss: 1.2563 - Accuracy: 0.4412 - F1: 0.4570
sub_26:Test (Best Model) - Loss: 1.2809 - Accuracy: 0.4706 - F1: 0.4974
sub_27:Test (Best Model) - Loss: 1.3313 - Accuracy: 0.3768 - F1: 0.3383
sub_27:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.3333 - F1: 0.3148
sub_27:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3043 - F1: 0.2457
sub_27:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3188 - F1: 0.3105
sub_27:Test (Best Model) - Loss: 1.3037 - Accuracy: 0.4058 - F1: 0.3577
sub_27:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.3913 - F1: 0.3404
sub_27:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3623 - F1: 0.2971
sub_27:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.4058 - F1: 0.3688
sub_27:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.4203 - F1: 0.3585
sub_27:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.3333 - F1: 0.2905
sub_27:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3235 - F1: 0.2914
sub_27:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.3676 - F1: 0.3381
sub_27:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.3529 - F1: 0.3502
sub_27:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.4118 - F1: 0.4058
sub_27:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.3382 - F1: 0.3051
sub_28:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3088 - F1: 0.2964
sub_28:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.2059 - F1: 0.1820
sub_28:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.2059 - F1: 0.1864
sub_28:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.2353 - F1: 0.2191
sub_28:Test (Best Model) - Loss: 1.4228 - Accuracy: 0.2206 - F1: 0.2181
sub_28:Test (Best Model) - Loss: 1.4130 - Accuracy: 0.2059 - F1: 0.1538
sub_28:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2794 - F1: 0.1860
sub_28:Test (Best Model) - Loss: 1.3855 - Accuracy: 0.2647 - F1: 0.2148
sub_28:Test (Best Model) - Loss: 1.4368 - Accuracy: 0.2500 - F1: 0.2090
sub_28:Test (Best Model) - Loss: 1.4317 - Accuracy: 0.2206 - F1: 0.1295
sub_28:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.2500 - F1: 0.2232
sub_28:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.3088 - F1: 0.2797
sub_28:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3088 - F1: 0.2998
sub_28:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3529 - F1: 0.3263
sub_28:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3824 - F1: 0.3477
sub_29:Test (Best Model) - Loss: 1.2458 - Accuracy: 0.4118 - F1: 0.4518
sub_29:Test (Best Model) - Loss: 1.2572 - Accuracy: 0.4706 - F1: 0.4677
sub_29:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.4412 - F1: 0.4762
sub_29:Test (Best Model) - Loss: 1.2136 - Accuracy: 0.4412 - F1: 0.4695
sub_29:Test (Best Model) - Loss: 1.2508 - Accuracy: 0.4412 - F1: 0.4631
sub_29:Test (Best Model) - Loss: 1.2118 - Accuracy: 0.5735 - F1: 0.5962
sub_29:Test (Best Model) - Loss: 1.1309 - Accuracy: 0.4706 - F1: 0.4895
sub_29:Test (Best Model) - Loss: 1.2458 - Accuracy: 0.4706 - F1: 0.4831
sub_29:Test (Best Model) - Loss: 1.1563 - Accuracy: 0.5294 - F1: 0.5584
sub_29:Test (Best Model) - Loss: 1.1667 - Accuracy: 0.5000 - F1: 0.5293
sub_29:Test (Best Model) - Loss: 1.2587 - Accuracy: 0.4783 - F1: 0.4954
sub_29:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.5362 - F1: 0.5528
sub_29:Test (Best Model) - Loss: 1.1298 - Accuracy: 0.4638 - F1: 0.4837
sub_29:Test (Best Model) - Loss: 1.1360 - Accuracy: 0.5652 - F1: 0.5789
sub_29:Test (Best Model) - Loss: 1.1460 - Accuracy: 0.5072 - F1: 0.5321

=== Summary Results ===

acc: 35.05 ± 5.83
F1: 34.16 ± 6.44
acc-in: 41.26 ± 6.30
F1-in: 39.76 ± 6.54
