lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.2835 - Accuracy: 0.3676 - F1: 0.3868
sub_1:Test (Best Model) - Loss: 1.2352 - Accuracy: 0.5147 - F1: 0.5377
sub_1:Test (Best Model) - Loss: 1.2614 - Accuracy: 0.4412 - F1: 0.4655
sub_1:Test (Best Model) - Loss: 1.2361 - Accuracy: 0.4412 - F1: 0.4718
sub_1:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.4412 - F1: 0.4607
sub_1:Test (Best Model) - Loss: 1.3336 - Accuracy: 0.3768 - F1: 0.3710
sub_1:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.3333 - F1: 0.3342
sub_1:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.3913 - F1: 0.3893
sub_1:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.4058 - F1: 0.4032
sub_1:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.3333 - F1: 0.3400
sub_1:Test (Best Model) - Loss: 1.2453 - Accuracy: 0.4118 - F1: 0.3814
sub_1:Test (Best Model) - Loss: 1.1787 - Accuracy: 0.5000 - F1: 0.4963
sub_1:Test (Best Model) - Loss: 1.1503 - Accuracy: 0.5147 - F1: 0.5223
sub_1:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.4118 - F1: 0.3961
sub_1:Test (Best Model) - Loss: 1.1701 - Accuracy: 0.4706 - F1: 0.4504
sub_2:Test (Best Model) - Loss: 1.4077 - Accuracy: 0.2319 - F1: 0.2527
sub_2:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.2899 - F1: 0.3173
sub_2:Test (Best Model) - Loss: 1.4116 - Accuracy: 0.2319 - F1: 0.2415
sub_2:Test (Best Model) - Loss: 1.4154 - Accuracy: 0.2029 - F1: 0.2215
sub_2:Test (Best Model) - Loss: 1.4852 - Accuracy: 0.2899 - F1: 0.3096
sub_2:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.2794 - F1: 0.2808
sub_2:Test (Best Model) - Loss: 1.4196 - Accuracy: 0.2353 - F1: 0.2456
sub_2:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.3235 - F1: 0.3304
sub_2:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.2941 - F1: 0.3070
sub_2:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2941 - F1: 0.3386
sub_2:Test (Best Model) - Loss: 1.4549 - Accuracy: 0.3333 - F1: 0.3107
sub_2:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3768 - F1: 0.3788
sub_2:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.3768 - F1: 0.3321
sub_2:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2609 - F1: 0.2310
sub_2:Test (Best Model) - Loss: 1.3657 - Accuracy: 0.3478 - F1: 0.3587
sub_3:Test (Best Model) - Loss: 1.4018 - Accuracy: 0.3235 - F1: 0.3287
sub_3:Test (Best Model) - Loss: 1.3675 - Accuracy: 0.3088 - F1: 0.3099
sub_3:Test (Best Model) - Loss: 1.4330 - Accuracy: 0.2206 - F1: 0.2250
sub_3:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.2353 - F1: 0.2343
sub_3:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.2206 - F1: 0.2169
sub_3:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3478 - F1: 0.3167
sub_3:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.2609 - F1: 0.2446
sub_3:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.2464 - F1: 0.2282
sub_3:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2899 - F1: 0.2661
sub_3:Test (Best Model) - Loss: 1.3822 - Accuracy: 0.3478 - F1: 0.3422
sub_3:Test (Best Model) - Loss: 1.4694 - Accuracy: 0.2609 - F1: 0.2312
sub_3:Test (Best Model) - Loss: 1.4098 - Accuracy: 0.2464 - F1: 0.2301
sub_3:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2609 - F1: 0.2367
sub_3:Test (Best Model) - Loss: 1.4346 - Accuracy: 0.2609 - F1: 0.2389
sub_3:Test (Best Model) - Loss: 1.4268 - Accuracy: 0.3478 - F1: 0.3201
sub_4:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.4348 - F1: 0.4517
sub_4:Test (Best Model) - Loss: 1.1622 - Accuracy: 0.4493 - F1: 0.4790
sub_4:Test (Best Model) - Loss: 1.1851 - Accuracy: 0.4203 - F1: 0.4415
sub_4:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.5362 - F1: 0.5494
sub_4:Test (Best Model) - Loss: 1.1168 - Accuracy: 0.5217 - F1: 0.5267
sub_4:Test (Best Model) - Loss: 1.1401 - Accuracy: 0.4638 - F1: 0.4718
sub_4:Test (Best Model) - Loss: 1.1227 - Accuracy: 0.5507 - F1: 0.5698
sub_4:Test (Best Model) - Loss: 1.0761 - Accuracy: 0.5652 - F1: 0.5881
sub_4:Test (Best Model) - Loss: 1.1561 - Accuracy: 0.5217 - F1: 0.5109
sub_4:Test (Best Model) - Loss: 1.1574 - Accuracy: 0.5362 - F1: 0.5588
sub_4:Test (Best Model) - Loss: 1.2093 - Accuracy: 0.3768 - F1: 0.3507
sub_4:Test (Best Model) - Loss: 1.2309 - Accuracy: 0.4203 - F1: 0.3879
sub_4:Test (Best Model) - Loss: 1.1656 - Accuracy: 0.4203 - F1: 0.4373
sub_4:Test (Best Model) - Loss: 1.1827 - Accuracy: 0.4493 - F1: 0.4726
sub_4:Test (Best Model) - Loss: 1.1460 - Accuracy: 0.4783 - F1: 0.4806
sub_5:Test (Best Model) - Loss: 1.4180 - Accuracy: 0.4265 - F1: 0.3910
sub_5:Test (Best Model) - Loss: 1.4019 - Accuracy: 0.4559 - F1: 0.4071
sub_5:Test (Best Model) - Loss: 1.4810 - Accuracy: 0.4118 - F1: 0.4087
sub_5:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.3971 - F1: 0.3918
sub_5:Test (Best Model) - Loss: 1.3903 - Accuracy: 0.4412 - F1: 0.4274
sub_5:Test (Best Model) - Loss: 1.1582 - Accuracy: 0.4853 - F1: 0.4600
sub_5:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.4412 - F1: 0.4397
sub_5:Test (Best Model) - Loss: 1.1836 - Accuracy: 0.4706 - F1: 0.5021
sub_5:Test (Best Model) - Loss: 1.1070 - Accuracy: 0.4706 - F1: 0.4537
sub_5:Test (Best Model) - Loss: 1.2003 - Accuracy: 0.4706 - F1: 0.4738
sub_5:Test (Best Model) - Loss: 1.1880 - Accuracy: 0.4559 - F1: 0.4520
sub_5:Test (Best Model) - Loss: 1.2146 - Accuracy: 0.4265 - F1: 0.4047
sub_5:Test (Best Model) - Loss: 1.2611 - Accuracy: 0.4118 - F1: 0.3962
sub_5:Test (Best Model) - Loss: 1.1916 - Accuracy: 0.3676 - F1: 0.3614
sub_5:Test (Best Model) - Loss: 1.1020 - Accuracy: 0.4559 - F1: 0.4470
sub_6:Test (Best Model) - Loss: 1.2075 - Accuracy: 0.5294 - F1: 0.5340
sub_6:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.3676 - F1: 0.3617
sub_6:Test (Best Model) - Loss: 1.2127 - Accuracy: 0.4559 - F1: 0.4561
sub_6:Test (Best Model) - Loss: 1.1910 - Accuracy: 0.4706 - F1: 0.4690
sub_6:Test (Best Model) - Loss: 1.2333 - Accuracy: 0.4412 - F1: 0.4610
sub_6:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.3333 - F1: 0.2831
sub_6:Test (Best Model) - Loss: 1.2666 - Accuracy: 0.4203 - F1: 0.3514
sub_6:Test (Best Model) - Loss: 1.2260 - Accuracy: 0.4348 - F1: 0.3762
sub_6:Test (Best Model) - Loss: 1.2504 - Accuracy: 0.3913 - F1: 0.3641
sub_6:Test (Best Model) - Loss: 1.2826 - Accuracy: 0.3913 - F1: 0.3267
sub_6:Test (Best Model) - Loss: 1.2949 - Accuracy: 0.3188 - F1: 0.3329
sub_6:Test (Best Model) - Loss: 1.3803 - Accuracy: 0.2899 - F1: 0.2864
sub_6:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.3913 - F1: 0.4064
sub_6:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.3623 - F1: 0.3840
sub_6:Test (Best Model) - Loss: 1.2207 - Accuracy: 0.4638 - F1: 0.4964
sub_7:Test (Best Model) - Loss: 1.2022 - Accuracy: 0.4559 - F1: 0.4341
sub_7:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.4706 - F1: 0.4234
sub_7:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.3824 - F1: 0.3571
sub_7:Test (Best Model) - Loss: 1.1063 - Accuracy: 0.5882 - F1: 0.5805
sub_7:Test (Best Model) - Loss: 1.1690 - Accuracy: 0.5000 - F1: 0.4842
sub_7:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.3529 - F1: 0.3523
sub_7:Test (Best Model) - Loss: 1.2918 - Accuracy: 0.3382 - F1: 0.3340
sub_7:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.4265 - F1: 0.4374
sub_7:Test (Best Model) - Loss: 1.2819 - Accuracy: 0.4265 - F1: 0.4119
sub_7:Test (Best Model) - Loss: 1.2134 - Accuracy: 0.4118 - F1: 0.3965
sub_7:Test (Best Model) - Loss: 1.2310 - Accuracy: 0.5147 - F1: 0.5147
sub_7:Test (Best Model) - Loss: 1.2533 - Accuracy: 0.4412 - F1: 0.4282
sub_7:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.3971 - F1: 0.3894
sub_7:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3676 - F1: 0.3633
sub_7:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.4559 - F1: 0.4714
sub_8:Test (Best Model) - Loss: 1.4477 - Accuracy: 0.2500 - F1: 0.2648
sub_8:Test (Best Model) - Loss: 1.4765 - Accuracy: 0.2941 - F1: 0.2944
sub_8:Test (Best Model) - Loss: 1.4512 - Accuracy: 0.2353 - F1: 0.2553
sub_8:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.3235 - F1: 0.3099
sub_8:Test (Best Model) - Loss: 1.4308 - Accuracy: 0.2794 - F1: 0.2902
sub_8:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.3529 - F1: 0.3625
sub_8:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.3676 - F1: 0.3653
sub_8:Test (Best Model) - Loss: 1.3511 - Accuracy: 0.3529 - F1: 0.3553
sub_8:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2941 - F1: 0.2816
sub_8:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2500 - F1: 0.2557
sub_8:Test (Best Model) - Loss: 1.4665 - Accuracy: 0.2941 - F1: 0.2776
sub_8:Test (Best Model) - Loss: 1.4573 - Accuracy: 0.2353 - F1: 0.2165
sub_8:Test (Best Model) - Loss: 1.4528 - Accuracy: 0.3824 - F1: 0.4009
sub_8:Test (Best Model) - Loss: 1.4257 - Accuracy: 0.3235 - F1: 0.3281
sub_8:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.3676 - F1: 0.3565
sub_9:Test (Best Model) - Loss: 1.1945 - Accuracy: 0.4559 - F1: 0.4747
sub_9:Test (Best Model) - Loss: 1.1832 - Accuracy: 0.4559 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 1.1728 - Accuracy: 0.4265 - F1: 0.4589
sub_9:Test (Best Model) - Loss: 1.1803 - Accuracy: 0.4559 - F1: 0.4765
sub_9:Test (Best Model) - Loss: 1.1637 - Accuracy: 0.5000 - F1: 0.5278
sub_9:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.3088 - F1: 0.3174
sub_9:Test (Best Model) - Loss: 1.4642 - Accuracy: 0.3529 - F1: 0.3818
sub_9:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.3824 - F1: 0.4026
sub_9:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.3235 - F1: 0.3423
sub_9:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.2206 - F1: 0.2515
sub_9:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3382 - F1: 0.3493
sub_9:Test (Best Model) - Loss: 1.3407 - Accuracy: 0.3824 - F1: 0.4007
sub_9:Test (Best Model) - Loss: 1.3074 - Accuracy: 0.3824 - F1: 0.4127
sub_9:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.3382 - F1: 0.3501
sub_9:Test (Best Model) - Loss: 1.3101 - Accuracy: 0.3529 - F1: 0.3916
sub_10:Test (Best Model) - Loss: 1.4292 - Accuracy: 0.2794 - F1: 0.2553
sub_10:Test (Best Model) - Loss: 1.3814 - Accuracy: 0.3088 - F1: 0.3028
sub_10:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.2647 - F1: 0.2619
sub_10:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.2647 - F1: 0.2639
sub_10:Test (Best Model) - Loss: 1.4235 - Accuracy: 0.3088 - F1: 0.3000
sub_10:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.3529 - F1: 0.3428
sub_10:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.1912 - F1: 0.1844
sub_10:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.2206 - F1: 0.2053
sub_10:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2794 - F1: 0.2706
sub_10:Test (Best Model) - Loss: 1.4203 - Accuracy: 0.2206 - F1: 0.2185
sub_10:Test (Best Model) - Loss: 1.4875 - Accuracy: 0.2464 - F1: 0.2414
sub_10:Test (Best Model) - Loss: 1.4375 - Accuracy: 0.2464 - F1: 0.2527
sub_10:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.3043 - F1: 0.3131
sub_10:Test (Best Model) - Loss: 1.4271 - Accuracy: 0.2609 - F1: 0.2534
sub_10:Test (Best Model) - Loss: 1.4442 - Accuracy: 0.2609 - F1: 0.2486
sub_11:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3768 - F1: 0.3491
sub_11:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3333 - F1: 0.3227
sub_11:Test (Best Model) - Loss: 1.4054 - Accuracy: 0.3043 - F1: 0.3015
sub_11:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.3043 - F1: 0.3152
sub_11:Test (Best Model) - Loss: 1.4242 - Accuracy: 0.3478 - F1: 0.3486
sub_11:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.4638 - F1: 0.4275
sub_11:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.4203 - F1: 0.3984
sub_11:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3478 - F1: 0.3348
sub_11:Test (Best Model) - Loss: 1.3401 - Accuracy: 0.3913 - F1: 0.3697
sub_11:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.3768 - F1: 0.3635
sub_11:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3188 - F1: 0.2776
sub_11:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.3333 - F1: 0.3033
sub_11:Test (Best Model) - Loss: 1.2977 - Accuracy: 0.4203 - F1: 0.3883
sub_11:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.3623 - F1: 0.3573
sub_11:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3623 - F1: 0.3314
sub_12:Test (Best Model) - Loss: 1.2489 - Accuracy: 0.4412 - F1: 0.4276
sub_12:Test (Best Model) - Loss: 1.2239 - Accuracy: 0.4706 - F1: 0.4730
sub_12:Test (Best Model) - Loss: 1.1844 - Accuracy: 0.4853 - F1: 0.4688
sub_12:Test (Best Model) - Loss: 1.1060 - Accuracy: 0.5588 - F1: 0.5720
sub_12:Test (Best Model) - Loss: 1.1409 - Accuracy: 0.4853 - F1: 0.4929
sub_12:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.4058 - F1: 0.4132
sub_12:Test (Best Model) - Loss: 1.2408 - Accuracy: 0.3913 - F1: 0.3903
sub_12:Test (Best Model) - Loss: 1.1712 - Accuracy: 0.4638 - F1: 0.4587
sub_12:Test (Best Model) - Loss: 1.2519 - Accuracy: 0.4058 - F1: 0.4051
sub_12:Test (Best Model) - Loss: 1.2486 - Accuracy: 0.3623 - F1: 0.3782
sub_12:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.4265 - F1: 0.4220
sub_12:Test (Best Model) - Loss: 1.2855 - Accuracy: 0.4118 - F1: 0.4117
sub_12:Test (Best Model) - Loss: 1.2622 - Accuracy: 0.4118 - F1: 0.4223
sub_12:Test (Best Model) - Loss: 1.2662 - Accuracy: 0.4559 - F1: 0.4704
sub_12:Test (Best Model) - Loss: 1.1936 - Accuracy: 0.4412 - F1: 0.4679
sub_13:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.3676 - F1: 0.3877
sub_13:Test (Best Model) - Loss: 1.3234 - Accuracy: 0.3235 - F1: 0.3214
sub_13:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.3529 - F1: 0.3671
sub_13:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.2794 - F1: 0.3100
sub_13:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.3529 - F1: 0.3641
sub_13:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.3623 - F1: 0.3507
sub_13:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.3188 - F1: 0.3190
sub_13:Test (Best Model) - Loss: 1.4037 - Accuracy: 0.3478 - F1: 0.3322
sub_13:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.3043 - F1: 0.3186
sub_13:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.4058 - F1: 0.3961
sub_13:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3676 - F1: 0.3664
sub_13:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3088 - F1: 0.3328
sub_13:Test (Best Model) - Loss: 1.4247 - Accuracy: 0.2941 - F1: 0.3025
sub_13:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.2941 - F1: 0.2947
sub_13:Test (Best Model) - Loss: 1.3694 - Accuracy: 0.3088 - F1: 0.3133
sub_14:Test (Best Model) - Loss: 1.3503 - Accuracy: 0.2794 - F1: 0.2895
sub_14:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3088 - F1: 0.3335
sub_14:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.2794 - F1: 0.3013
sub_14:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2206 - F1: 0.2470
sub_14:Test (Best Model) - Loss: 1.3417 - Accuracy: 0.2941 - F1: 0.3034
sub_14:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3235 - F1: 0.3024
sub_14:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3529 - F1: 0.3525
sub_14:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.2941 - F1: 0.2756
sub_14:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.3235 - F1: 0.3321
sub_14:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.2353 - F1: 0.2089
sub_14:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.3971 - F1: 0.4038
sub_14:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.3235 - F1: 0.2833
sub_14:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3088 - F1: 0.3053
sub_14:Test (Best Model) - Loss: 1.3154 - Accuracy: 0.3529 - F1: 0.3414
sub_14:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.3382 - F1: 0.3346
sub_15:Test (Best Model) - Loss: 1.2683 - Accuracy: 0.4265 - F1: 0.4457
sub_15:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.3529 - F1: 0.3700
sub_15:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.3676 - F1: 0.4009
sub_15:Test (Best Model) - Loss: 1.2337 - Accuracy: 0.3971 - F1: 0.4332
sub_15:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.3971 - F1: 0.4250
sub_15:Test (Best Model) - Loss: 1.1035 - Accuracy: 0.5000 - F1: 0.5069
sub_15:Test (Best Model) - Loss: 1.2413 - Accuracy: 0.5000 - F1: 0.5088
sub_15:Test (Best Model) - Loss: 1.1341 - Accuracy: 0.5294 - F1: 0.5345
sub_15:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.5441 - F1: 0.5524
sub_15:Test (Best Model) - Loss: 1.1542 - Accuracy: 0.5000 - F1: 0.5141
sub_15:Test (Best Model) - Loss: 1.1895 - Accuracy: 0.4559 - F1: 0.4609
sub_15:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.3824 - F1: 0.3770
sub_15:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.3971 - F1: 0.4107
sub_15:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.4118 - F1: 0.4184
sub_15:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.4706 - F1: 0.4881
sub_16:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.3529 - F1: 0.2781
sub_16:Test (Best Model) - Loss: 1.2574 - Accuracy: 0.3824 - F1: 0.3580
sub_16:Test (Best Model) - Loss: 1.2693 - Accuracy: 0.4706 - F1: 0.4249
sub_16:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.4412 - F1: 0.4194
sub_16:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.5441 - F1: 0.4980
sub_16:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.3382 - F1: 0.3115
sub_16:Test (Best Model) - Loss: 1.2819 - Accuracy: 0.3529 - F1: 0.3415
sub_16:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.4265 - F1: 0.4153
sub_16:Test (Best Model) - Loss: 1.2446 - Accuracy: 0.4265 - F1: 0.3961
sub_16:Test (Best Model) - Loss: 1.4895 - Accuracy: 0.3235 - F1: 0.3146
sub_16:Test (Best Model) - Loss: 1.1688 - Accuracy: 0.4853 - F1: 0.3970
sub_16:Test (Best Model) - Loss: 1.2097 - Accuracy: 0.5147 - F1: 0.4649
sub_16:Test (Best Model) - Loss: 1.1831 - Accuracy: 0.4265 - F1: 0.4039
sub_16:Test (Best Model) - Loss: 1.2401 - Accuracy: 0.4118 - F1: 0.3826
sub_16:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.4853 - F1: 0.4338
sub_17:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.4348 - F1: 0.3892
sub_17:Test (Best Model) - Loss: 1.2402 - Accuracy: 0.4203 - F1: 0.3781
sub_17:Test (Best Model) - Loss: 1.2243 - Accuracy: 0.4203 - F1: 0.4106
sub_17:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.4203 - F1: 0.4091
sub_17:Test (Best Model) - Loss: 1.2673 - Accuracy: 0.4058 - F1: 0.3912
sub_17:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.3043 - F1: 0.2436
sub_17:Test (Best Model) - Loss: 1.4335 - Accuracy: 0.3623 - F1: 0.3107
sub_17:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.4348 - F1: 0.3854
sub_17:Test (Best Model) - Loss: 1.4620 - Accuracy: 0.3913 - F1: 0.3586
sub_17:Test (Best Model) - Loss: 1.4785 - Accuracy: 0.3913 - F1: 0.3413
sub_17:Test (Best Model) - Loss: 1.2790 - Accuracy: 0.3529 - F1: 0.3116
sub_17:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.3971 - F1: 0.3674
sub_17:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.4412 - F1: 0.4471
sub_17:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.4706 - F1: 0.4696
sub_17:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.3676 - F1: 0.3753
sub_18:Test (Best Model) - Loss: 1.2943 - Accuracy: 0.3768 - F1: 0.3993
sub_18:Test (Best Model) - Loss: 1.2559 - Accuracy: 0.4203 - F1: 0.4491
sub_18:Test (Best Model) - Loss: 1.2711 - Accuracy: 0.3913 - F1: 0.3975
sub_18:Test (Best Model) - Loss: 1.2912 - Accuracy: 0.4203 - F1: 0.4189
sub_18:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.3623 - F1: 0.3744
sub_18:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3235 - F1: 0.3531
sub_18:Test (Best Model) - Loss: 1.3378 - Accuracy: 0.3676 - F1: 0.3814
sub_18:Test (Best Model) - Loss: 1.4074 - Accuracy: 0.2794 - F1: 0.3018
sub_18:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.2941 - F1: 0.3119
sub_18:Test (Best Model) - Loss: 1.3767 - Accuracy: 0.2941 - F1: 0.3215
sub_18:Test (Best Model) - Loss: 1.3190 - Accuracy: 0.3235 - F1: 0.3486
sub_18:Test (Best Model) - Loss: 1.3441 - Accuracy: 0.3235 - F1: 0.3325
sub_18:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.2794 - F1: 0.2955
sub_18:Test (Best Model) - Loss: 1.2886 - Accuracy: 0.3824 - F1: 0.4015
sub_18:Test (Best Model) - Loss: 1.2988 - Accuracy: 0.3382 - F1: 0.3680
sub_19:Test (Best Model) - Loss: 1.4526 - Accuracy: 0.3088 - F1: 0.2840
sub_19:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.3529 - F1: 0.3576
sub_19:Test (Best Model) - Loss: 1.4202 - Accuracy: 0.2647 - F1: 0.2879
sub_19:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.2794 - F1: 0.3058
sub_19:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3235 - F1: 0.3239
sub_19:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.3529 - F1: 0.2962
sub_19:Test (Best Model) - Loss: 1.3017 - Accuracy: 0.4265 - F1: 0.3832
sub_19:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.4706 - F1: 0.4651
sub_19:Test (Best Model) - Loss: 1.2822 - Accuracy: 0.3971 - F1: 0.3794
sub_19:Test (Best Model) - Loss: 1.2978 - Accuracy: 0.4265 - F1: 0.4029
sub_19:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.3676 - F1: 0.3634
sub_19:Test (Best Model) - Loss: 1.3993 - Accuracy: 0.3088 - F1: 0.3132
sub_19:Test (Best Model) - Loss: 1.2792 - Accuracy: 0.3824 - F1: 0.3712
sub_19:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.3235 - F1: 0.3421
sub_19:Test (Best Model) - Loss: 1.3144 - Accuracy: 0.3529 - F1: 0.3787
sub_20:Test (Best Model) - Loss: 1.1895 - Accuracy: 0.5000 - F1: 0.5132
sub_20:Test (Best Model) - Loss: 1.2428 - Accuracy: 0.4412 - F1: 0.4668
sub_20:Test (Best Model) - Loss: 1.2165 - Accuracy: 0.4853 - F1: 0.5059
sub_20:Test (Best Model) - Loss: 1.2343 - Accuracy: 0.4412 - F1: 0.4543
sub_20:Test (Best Model) - Loss: 1.2441 - Accuracy: 0.5147 - F1: 0.5377
sub_20:Test (Best Model) - Loss: 1.2699 - Accuracy: 0.3824 - F1: 0.3833
sub_20:Test (Best Model) - Loss: 1.2757 - Accuracy: 0.3971 - F1: 0.3982
sub_20:Test (Best Model) - Loss: 1.2853 - Accuracy: 0.3971 - F1: 0.4261
sub_20:Test (Best Model) - Loss: 1.3026 - Accuracy: 0.3676 - F1: 0.3640
sub_20:Test (Best Model) - Loss: 1.2970 - Accuracy: 0.3971 - F1: 0.4126
sub_20:Test (Best Model) - Loss: 1.2065 - Accuracy: 0.4058 - F1: 0.4188
sub_20:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.3913 - F1: 0.3935
sub_20:Test (Best Model) - Loss: 1.2856 - Accuracy: 0.3478 - F1: 0.3592
sub_20:Test (Best Model) - Loss: 1.2683 - Accuracy: 0.4493 - F1: 0.4526
sub_20:Test (Best Model) - Loss: 1.2211 - Accuracy: 0.4638 - F1: 0.4711
sub_21:Test (Best Model) - Loss: 1.2380 - Accuracy: 0.3824 - F1: 0.3490
sub_21:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.3824 - F1: 0.3556
sub_21:Test (Best Model) - Loss: 1.3012 - Accuracy: 0.3971 - F1: 0.3823
sub_21:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.3824 - F1: 0.3469
sub_21:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.3824 - F1: 0.3855
sub_21:Test (Best Model) - Loss: 1.2900 - Accuracy: 0.3235 - F1: 0.3091
sub_21:Test (Best Model) - Loss: 1.2094 - Accuracy: 0.5000 - F1: 0.4782
sub_21:Test (Best Model) - Loss: 1.1946 - Accuracy: 0.3676 - F1: 0.3305
sub_21:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.3676 - F1: 0.3692
sub_21:Test (Best Model) - Loss: 1.2163 - Accuracy: 0.3529 - F1: 0.3454
sub_21:Test (Best Model) - Loss: 1.2291 - Accuracy: 0.3971 - F1: 0.3846
sub_21:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.3971 - F1: 0.3841
sub_21:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.3676 - F1: 0.3355
sub_21:Test (Best Model) - Loss: 1.2545 - Accuracy: 0.3971 - F1: 0.3589
sub_21:Test (Best Model) - Loss: 1.2824 - Accuracy: 0.3971 - F1: 0.3708
sub_22:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.3382 - F1: 0.3565
sub_22:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.3382 - F1: 0.3309
sub_22:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.3382 - F1: 0.3605
sub_22:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.3676 - F1: 0.3907
sub_22:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.3235 - F1: 0.3462
sub_22:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.3188 - F1: 0.2969
sub_22:Test (Best Model) - Loss: 1.2873 - Accuracy: 0.4493 - F1: 0.4158
sub_22:Test (Best Model) - Loss: 1.3178 - Accuracy: 0.3333 - F1: 0.2937
sub_22:Test (Best Model) - Loss: 1.3061 - Accuracy: 0.4203 - F1: 0.4300
sub_22:Test (Best Model) - Loss: 1.2985 - Accuracy: 0.3478 - F1: 0.3312
sub_22:Test (Best Model) - Loss: 1.3017 - Accuracy: 0.3529 - F1: 0.3790
sub_22:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.2941 - F1: 0.3085
sub_22:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.3676 - F1: 0.3589
sub_22:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.3676 - F1: 0.3890
sub_22:Test (Best Model) - Loss: 1.2623 - Accuracy: 0.4559 - F1: 0.4881
sub_23:Test (Best Model) - Loss: 1.2716 - Accuracy: 0.3478 - F1: 0.3558
sub_23:Test (Best Model) - Loss: 1.2085 - Accuracy: 0.3623 - F1: 0.3754
sub_23:Test (Best Model) - Loss: 1.2174 - Accuracy: 0.3913 - F1: 0.3958
sub_23:Test (Best Model) - Loss: 1.1261 - Accuracy: 0.5072 - F1: 0.5293
sub_23:Test (Best Model) - Loss: 1.2079 - Accuracy: 0.4203 - F1: 0.4157
sub_23:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.4265 - F1: 0.3985
sub_23:Test (Best Model) - Loss: 1.2106 - Accuracy: 0.4853 - F1: 0.4945
sub_23:Test (Best Model) - Loss: 1.1834 - Accuracy: 0.4706 - F1: 0.4592
sub_23:Test (Best Model) - Loss: 1.1717 - Accuracy: 0.5441 - F1: 0.5274
sub_23:Test (Best Model) - Loss: 1.2182 - Accuracy: 0.4412 - F1: 0.4076
sub_23:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2899 - F1: 0.2771
sub_23:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.3768 - F1: 0.3885
sub_23:Test (Best Model) - Loss: 1.2312 - Accuracy: 0.3768 - F1: 0.3702
sub_23:Test (Best Model) - Loss: 1.3109 - Accuracy: 0.4493 - F1: 0.4638
sub_23:Test (Best Model) - Loss: 1.2867 - Accuracy: 0.2754 - F1: 0.2835
sub_24:Test (Best Model) - Loss: 1.3876 - Accuracy: 0.3088 - F1: 0.2804
sub_24:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2941 - F1: 0.2844
sub_24:Test (Best Model) - Loss: 1.4252 - Accuracy: 0.2794 - F1: 0.2809
sub_24:Test (Best Model) - Loss: 1.4292 - Accuracy: 0.3088 - F1: 0.3049
sub_24:Test (Best Model) - Loss: 1.4043 - Accuracy: 0.2941 - F1: 0.2957
sub_24:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.3676 - F1: 0.3641
sub_24:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3235 - F1: 0.3228
sub_24:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.3382 - F1: 0.3294
sub_24:Test (Best Model) - Loss: 1.3078 - Accuracy: 0.4559 - F1: 0.4471
sub_24:Test (Best Model) - Loss: 1.3505 - Accuracy: 0.3382 - F1: 0.3386
sub_24:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.3088 - F1: 0.3023
sub_24:Test (Best Model) - Loss: 1.4615 - Accuracy: 0.2059 - F1: 0.2111
sub_24:Test (Best Model) - Loss: 1.4317 - Accuracy: 0.1471 - F1: 0.1483
sub_24:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.3529 - F1: 0.3531
sub_24:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.2941 - F1: 0.2868
sub_25:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.3913 - F1: 0.3541
sub_25:Test (Best Model) - Loss: 1.3227 - Accuracy: 0.3623 - F1: 0.3684
sub_25:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.4058 - F1: 0.3946
sub_25:Test (Best Model) - Loss: 1.2803 - Accuracy: 0.4348 - F1: 0.4089
sub_25:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.3188 - F1: 0.3040
sub_25:Test (Best Model) - Loss: 1.2832 - Accuracy: 0.3824 - F1: 0.3164
sub_25:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.3235 - F1: 0.2642
sub_25:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.4412 - F1: 0.4311
sub_25:Test (Best Model) - Loss: 1.2232 - Accuracy: 0.4853 - F1: 0.4477
sub_25:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.5441 - F1: 0.5142
sub_25:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.4118 - F1: 0.4026
sub_25:Test (Best Model) - Loss: 1.2524 - Accuracy: 0.4265 - F1: 0.4141
sub_25:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.5000 - F1: 0.4817
sub_25:Test (Best Model) - Loss: 1.2739 - Accuracy: 0.3676 - F1: 0.3206
sub_25:Test (Best Model) - Loss: 1.2538 - Accuracy: 0.3971 - F1: 0.3429
sub_26:Test (Best Model) - Loss: 1.1740 - Accuracy: 0.3768 - F1: 0.3929
sub_26:Test (Best Model) - Loss: 1.2725 - Accuracy: 0.3768 - F1: 0.3762
sub_26:Test (Best Model) - Loss: 1.2249 - Accuracy: 0.4493 - F1: 0.4646
sub_26:Test (Best Model) - Loss: 1.1723 - Accuracy: 0.5072 - F1: 0.5122
sub_26:Test (Best Model) - Loss: 1.1003 - Accuracy: 0.5797 - F1: 0.5990
sub_26:Test (Best Model) - Loss: 1.2965 - Accuracy: 0.3971 - F1: 0.4318
sub_26:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.3382 - F1: 0.3517
sub_26:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.3824 - F1: 0.3759
sub_26:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.4118 - F1: 0.4095
sub_26:Test (Best Model) - Loss: 1.2784 - Accuracy: 0.3088 - F1: 0.3392
sub_26:Test (Best Model) - Loss: 1.2119 - Accuracy: 0.4706 - F1: 0.4894
sub_26:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.4706 - F1: 0.4974
sub_26:Test (Best Model) - Loss: 1.2678 - Accuracy: 0.5000 - F1: 0.5071
sub_26:Test (Best Model) - Loss: 1.2193 - Accuracy: 0.5294 - F1: 0.5548
sub_26:Test (Best Model) - Loss: 1.2407 - Accuracy: 0.5000 - F1: 0.5279
sub_27:Test (Best Model) - Loss: 1.2592 - Accuracy: 0.4348 - F1: 0.3892
sub_27:Test (Best Model) - Loss: 1.2402 - Accuracy: 0.4203 - F1: 0.3781
sub_27:Test (Best Model) - Loss: 1.2243 - Accuracy: 0.4203 - F1: 0.4106
sub_27:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.4203 - F1: 0.4091
sub_27:Test (Best Model) - Loss: 1.2673 - Accuracy: 0.4058 - F1: 0.3912
sub_27:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.3043 - F1: 0.2436
sub_27:Test (Best Model) - Loss: 1.4335 - Accuracy: 0.3623 - F1: 0.3107
sub_27:Test (Best Model) - Loss: 1.3937 - Accuracy: 0.4348 - F1: 0.3854
sub_27:Test (Best Model) - Loss: 1.4620 - Accuracy: 0.3913 - F1: 0.3586
sub_27:Test (Best Model) - Loss: 1.4785 - Accuracy: 0.3913 - F1: 0.3413
sub_27:Test (Best Model) - Loss: 1.2790 - Accuracy: 0.3529 - F1: 0.3116
sub_27:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.3971 - F1: 0.3674
sub_27:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.4412 - F1: 0.4471
sub_27:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.4706 - F1: 0.4696
sub_27:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.3676 - F1: 0.3753
sub_28:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2941 - F1: 0.2853
sub_28:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.2500 - F1: 0.2260
sub_28:Test (Best Model) - Loss: 1.5079 - Accuracy: 0.2794 - F1: 0.2709
sub_28:Test (Best Model) - Loss: 1.4325 - Accuracy: 0.2353 - F1: 0.2345
sub_28:Test (Best Model) - Loss: 1.4962 - Accuracy: 0.2500 - F1: 0.2590
sub_28:Test (Best Model) - Loss: 1.5175 - Accuracy: 0.2500 - F1: 0.2242
sub_28:Test (Best Model) - Loss: 1.5109 - Accuracy: 0.2794 - F1: 0.2664
sub_28:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.2206 - F1: 0.2142
sub_28:Test (Best Model) - Loss: 1.6396 - Accuracy: 0.2794 - F1: 0.2750
sub_28:Test (Best Model) - Loss: 1.5530 - Accuracy: 0.2794 - F1: 0.2455
sub_28:Test (Best Model) - Loss: 1.3150 - Accuracy: 0.4412 - F1: 0.4157
sub_28:Test (Best Model) - Loss: 1.2890 - Accuracy: 0.4118 - F1: 0.3393
sub_28:Test (Best Model) - Loss: 1.2987 - Accuracy: 0.4559 - F1: 0.4185
sub_28:Test (Best Model) - Loss: 1.3361 - Accuracy: 0.3971 - F1: 0.3746
sub_28:Test (Best Model) - Loss: 1.3331 - Accuracy: 0.3824 - F1: 0.3563
sub_29:Test (Best Model) - Loss: 1.1939 - Accuracy: 0.4853 - F1: 0.5106
sub_29:Test (Best Model) - Loss: 1.1537 - Accuracy: 0.4706 - F1: 0.4868
sub_29:Test (Best Model) - Loss: 1.0772 - Accuracy: 0.5441 - F1: 0.5638
sub_29:Test (Best Model) - Loss: 1.1281 - Accuracy: 0.4706 - F1: 0.4831
sub_29:Test (Best Model) - Loss: 1.1021 - Accuracy: 0.5294 - F1: 0.5390
sub_29:Test (Best Model) - Loss: 1.1172 - Accuracy: 0.4706 - F1: 0.5061
sub_29:Test (Best Model) - Loss: 1.0400 - Accuracy: 0.5735 - F1: 0.5973
sub_29:Test (Best Model) - Loss: 1.0680 - Accuracy: 0.4706 - F1: 0.4858
sub_29:Test (Best Model) - Loss: 1.0197 - Accuracy: 0.6029 - F1: 0.6258
sub_29:Test (Best Model) - Loss: 1.0123 - Accuracy: 0.5147 - F1: 0.5416
sub_29:Test (Best Model) - Loss: 1.0479 - Accuracy: 0.5797 - F1: 0.5932
sub_29:Test (Best Model) - Loss: 1.1302 - Accuracy: 0.4928 - F1: 0.5089
sub_29:Test (Best Model) - Loss: 1.1124 - Accuracy: 0.4638 - F1: 0.4888
sub_29:Test (Best Model) - Loss: 1.0425 - Accuracy: 0.5797 - F1: 0.5950
sub_29:Test (Best Model) - Loss: 1.0845 - Accuracy: 0.4638 - F1: 0.4926

=== Summary Results ===

acc: 38.24 ± 6.16
F1: 37.86 ± 6.56
acc-in: 45.86 ± 5.89
F1-in: 44.31 ± 6.20
