lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.3382 - F1: 0.3444
sub_1:Test (Best Model) - Loss: 1.3254 - Accuracy: 0.3676 - F1: 0.3733
sub_1:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3235 - F1: 0.3125
sub_1:Test (Best Model) - Loss: 1.2737 - Accuracy: 0.3971 - F1: 0.4145
sub_1:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.4118 - F1: 0.4404
sub_1:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3623 - F1: 0.3631
sub_1:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3043 - F1: 0.3056
sub_1:Test (Best Model) - Loss: 1.3549 - Accuracy: 0.3913 - F1: 0.3725
sub_1:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.3913 - F1: 0.3882
sub_1:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.3043 - F1: 0.3247
sub_1:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.4118 - F1: 0.3971
sub_1:Test (Best Model) - Loss: 1.2784 - Accuracy: 0.4559 - F1: 0.4636
sub_1:Test (Best Model) - Loss: 1.2330 - Accuracy: 0.4706 - F1: 0.4879
sub_1:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.4118 - F1: 0.3863
sub_1:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.4265 - F1: 0.4135
sub_2:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.2464 - F1: 0.2641
sub_2:Test (Best Model) - Loss: 1.4328 - Accuracy: 0.2174 - F1: 0.2328
sub_2:Test (Best Model) - Loss: 1.4367 - Accuracy: 0.2754 - F1: 0.2862
sub_2:Test (Best Model) - Loss: 1.4305 - Accuracy: 0.2319 - F1: 0.2524
sub_2:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.3043 - F1: 0.3275
sub_2:Test (Best Model) - Loss: 1.4241 - Accuracy: 0.2500 - F1: 0.2688
sub_2:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.2059 - F1: 0.2060
sub_2:Test (Best Model) - Loss: 1.4049 - Accuracy: 0.3235 - F1: 0.3474
sub_2:Test (Best Model) - Loss: 1.4199 - Accuracy: 0.2500 - F1: 0.2619
sub_2:Test (Best Model) - Loss: 1.4303 - Accuracy: 0.2794 - F1: 0.3091
sub_2:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.3333 - F1: 0.3258
sub_2:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.3188 - F1: 0.3051
sub_2:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3188 - F1: 0.3036
sub_2:Test (Best Model) - Loss: 1.3738 - Accuracy: 0.3478 - F1: 0.3175
sub_2:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.3043 - F1: 0.3073
sub_3:Test (Best Model) - Loss: 1.4180 - Accuracy: 0.2353 - F1: 0.2373
sub_3:Test (Best Model) - Loss: 1.3885 - Accuracy: 0.2941 - F1: 0.2921
sub_3:Test (Best Model) - Loss: 1.4260 - Accuracy: 0.2353 - F1: 0.2379
sub_3:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.2206 - F1: 0.2205
sub_3:Test (Best Model) - Loss: 1.4158 - Accuracy: 0.2794 - F1: 0.2784
sub_3:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3913 - F1: 0.3523
sub_3:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.2319 - F1: 0.2246
sub_3:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2174 - F1: 0.2075
sub_3:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.3333 - F1: 0.3339
sub_3:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.3188 - F1: 0.3036
sub_3:Test (Best Model) - Loss: 1.4996 - Accuracy: 0.2899 - F1: 0.2844
sub_3:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2899 - F1: 0.2553
sub_3:Test (Best Model) - Loss: 1.4177 - Accuracy: 0.2319 - F1: 0.2006
sub_3:Test (Best Model) - Loss: 1.4611 - Accuracy: 0.2464 - F1: 0.2400
sub_3:Test (Best Model) - Loss: 1.4616 - Accuracy: 0.2899 - F1: 0.2703
sub_4:Test (Best Model) - Loss: 1.2859 - Accuracy: 0.3768 - F1: 0.3876
sub_4:Test (Best Model) - Loss: 1.2795 - Accuracy: 0.3333 - F1: 0.3542
sub_4:Test (Best Model) - Loss: 1.3073 - Accuracy: 0.3768 - F1: 0.3889
sub_4:Test (Best Model) - Loss: 1.2590 - Accuracy: 0.4058 - F1: 0.4241
sub_4:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.3478 - F1: 0.3525
sub_4:Test (Best Model) - Loss: 1.2645 - Accuracy: 0.4348 - F1: 0.4445
sub_4:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.4638 - F1: 0.4778
sub_4:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.4638 - F1: 0.4784
sub_4:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.4203 - F1: 0.4156
sub_4:Test (Best Model) - Loss: 1.2397 - Accuracy: 0.4348 - F1: 0.4470
sub_4:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.3333 - F1: 0.2990
sub_4:Test (Best Model) - Loss: 1.2635 - Accuracy: 0.3913 - F1: 0.3616
sub_4:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.3768 - F1: 0.3899
sub_4:Test (Best Model) - Loss: 1.2422 - Accuracy: 0.3623 - F1: 0.3705
sub_4:Test (Best Model) - Loss: 1.2092 - Accuracy: 0.4638 - F1: 0.4535
sub_5:Test (Best Model) - Loss: 1.4581 - Accuracy: 0.3676 - F1: 0.3385
sub_5:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.4118 - F1: 0.3692
sub_5:Test (Best Model) - Loss: 1.5416 - Accuracy: 0.4559 - F1: 0.4669
sub_5:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.4559 - F1: 0.4480
sub_5:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.3529 - F1: 0.3410
sub_5:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.4412 - F1: 0.4197
sub_5:Test (Best Model) - Loss: 1.2995 - Accuracy: 0.4412 - F1: 0.4438
sub_5:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.4412 - F1: 0.4218
sub_5:Test (Best Model) - Loss: 1.2539 - Accuracy: 0.4706 - F1: 0.4196
sub_5:Test (Best Model) - Loss: 1.2836 - Accuracy: 0.4265 - F1: 0.4084
sub_5:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.4412 - F1: 0.4416
sub_5:Test (Best Model) - Loss: 1.2762 - Accuracy: 0.3676 - F1: 0.3448
sub_5:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.3971 - F1: 0.3504
sub_5:Test (Best Model) - Loss: 1.2409 - Accuracy: 0.3971 - F1: 0.3792
sub_5:Test (Best Model) - Loss: 1.2083 - Accuracy: 0.4412 - F1: 0.4271
sub_6:Test (Best Model) - Loss: 1.2767 - Accuracy: 0.5000 - F1: 0.5140
sub_6:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.3824 - F1: 0.3972
sub_6:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.3676 - F1: 0.3582
sub_6:Test (Best Model) - Loss: 1.2523 - Accuracy: 0.4265 - F1: 0.4198
sub_6:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.3971 - F1: 0.4142
sub_6:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.3768 - F1: 0.3042
sub_6:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.3913 - F1: 0.3231
sub_6:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.3478 - F1: 0.2917
sub_6:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3043 - F1: 0.2782
sub_6:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.3188 - F1: 0.2457
sub_6:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3043 - F1: 0.3198
sub_6:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3333 - F1: 0.3380
sub_6:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.3043 - F1: 0.3195
sub_6:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3043 - F1: 0.3199
sub_6:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.3043 - F1: 0.2991
sub_7:Test (Best Model) - Loss: 1.2690 - Accuracy: 0.4265 - F1: 0.3951
sub_7:Test (Best Model) - Loss: 1.2482 - Accuracy: 0.4412 - F1: 0.4099
sub_7:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.3088 - F1: 0.2821
sub_7:Test (Best Model) - Loss: 1.2195 - Accuracy: 0.5588 - F1: 0.5474
sub_7:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.4853 - F1: 0.4576
sub_7:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3382 - F1: 0.3128
sub_7:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.4412 - F1: 0.4412
sub_7:Test (Best Model) - Loss: 1.3115 - Accuracy: 0.4265 - F1: 0.4386
sub_7:Test (Best Model) - Loss: 1.2894 - Accuracy: 0.4265 - F1: 0.4300
sub_7:Test (Best Model) - Loss: 1.2613 - Accuracy: 0.3529 - F1: 0.3495
sub_7:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.4412 - F1: 0.4130
sub_7:Test (Best Model) - Loss: 1.3196 - Accuracy: 0.3971 - F1: 0.3720
sub_7:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3824 - F1: 0.3701
sub_7:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.2794 - F1: 0.2548
sub_7:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.3529 - F1: 0.3585
sub_8:Test (Best Model) - Loss: 1.4267 - Accuracy: 0.2647 - F1: 0.2549
sub_8:Test (Best Model) - Loss: 1.4601 - Accuracy: 0.2794 - F1: 0.2731
sub_8:Test (Best Model) - Loss: 1.4483 - Accuracy: 0.2647 - F1: 0.2741
sub_8:Test (Best Model) - Loss: 1.4052 - Accuracy: 0.3088 - F1: 0.3075
sub_8:Test (Best Model) - Loss: 1.4220 - Accuracy: 0.2941 - F1: 0.3163
sub_8:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.3382 - F1: 0.3362
sub_8:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.3088 - F1: 0.3122
sub_8:Test (Best Model) - Loss: 1.3698 - Accuracy: 0.3529 - F1: 0.3532
sub_8:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.2206 - F1: 0.2248
sub_8:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2500 - F1: 0.2447
sub_8:Test (Best Model) - Loss: 1.4695 - Accuracy: 0.2941 - F1: 0.2728
sub_8:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.3235 - F1: 0.3279
sub_8:Test (Best Model) - Loss: 1.4274 - Accuracy: 0.3235 - F1: 0.3232
sub_8:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.2794 - F1: 0.2590
sub_8:Test (Best Model) - Loss: 1.4507 - Accuracy: 0.3382 - F1: 0.3177
sub_9:Test (Best Model) - Loss: 1.2619 - Accuracy: 0.4412 - F1: 0.4569
sub_9:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.4118 - F1: 0.4286
sub_9:Test (Best Model) - Loss: 1.2870 - Accuracy: 0.3235 - F1: 0.3574
sub_9:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.4559 - F1: 0.4839
sub_9:Test (Best Model) - Loss: 1.2183 - Accuracy: 0.4265 - F1: 0.4549
sub_9:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.3235 - F1: 0.3387
sub_9:Test (Best Model) - Loss: 1.4286 - Accuracy: 0.3382 - F1: 0.3584
sub_9:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.3235 - F1: 0.3336
sub_9:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3529 - F1: 0.3765
sub_9:Test (Best Model) - Loss: 1.3762 - Accuracy: 0.2500 - F1: 0.2764
sub_9:Test (Best Model) - Loss: 1.4578 - Accuracy: 0.3088 - F1: 0.3193
sub_9:Test (Best Model) - Loss: 1.3713 - Accuracy: 0.3676 - F1: 0.3797
sub_9:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3971 - F1: 0.4173
sub_9:Test (Best Model) - Loss: 1.4254 - Accuracy: 0.2941 - F1: 0.2987
sub_9:Test (Best Model) - Loss: 1.3970 - Accuracy: 0.3676 - F1: 0.3881
sub_10:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.2647 - F1: 0.2539
sub_10:Test (Best Model) - Loss: 1.3978 - Accuracy: 0.3235 - F1: 0.3078
sub_10:Test (Best Model) - Loss: 1.3981 - Accuracy: 0.2647 - F1: 0.2592
sub_10:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3235 - F1: 0.3184
sub_10:Test (Best Model) - Loss: 1.4193 - Accuracy: 0.2941 - F1: 0.2946
sub_10:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.2941 - F1: 0.2821
sub_10:Test (Best Model) - Loss: 1.4233 - Accuracy: 0.2353 - F1: 0.2076
sub_10:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.2500 - F1: 0.2432
sub_10:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.1765 - F1: 0.1672
sub_10:Test (Best Model) - Loss: 1.4485 - Accuracy: 0.2353 - F1: 0.2262
sub_10:Test (Best Model) - Loss: 1.4748 - Accuracy: 0.2609 - F1: 0.2545
sub_10:Test (Best Model) - Loss: 1.4404 - Accuracy: 0.2609 - F1: 0.2633
sub_10:Test (Best Model) - Loss: 1.4171 - Accuracy: 0.2899 - F1: 0.2990
sub_10:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.2174 - F1: 0.1986
sub_10:Test (Best Model) - Loss: 1.4481 - Accuracy: 0.2174 - F1: 0.1973
sub_11:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3623 - F1: 0.3488
sub_11:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3333 - F1: 0.3165
sub_11:Test (Best Model) - Loss: 1.4438 - Accuracy: 0.3333 - F1: 0.3272
sub_11:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.2899 - F1: 0.2939
sub_11:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.3188 - F1: 0.3133
sub_11:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3768 - F1: 0.3548
sub_11:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.3913 - F1: 0.3731
sub_11:Test (Best Model) - Loss: 1.3286 - Accuracy: 0.3478 - F1: 0.3441
sub_11:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.3478 - F1: 0.3338
sub_11:Test (Best Model) - Loss: 1.3576 - Accuracy: 0.3623 - F1: 0.3224
sub_11:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.2899 - F1: 0.2353
sub_11:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.3188 - F1: 0.3031
sub_11:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.4058 - F1: 0.3847
sub_11:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.3478 - F1: 0.3355
sub_11:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.3188 - F1: 0.2997
sub_12:Test (Best Model) - Loss: 1.2889 - Accuracy: 0.3676 - F1: 0.3484
sub_12:Test (Best Model) - Loss: 1.2470 - Accuracy: 0.4265 - F1: 0.4288
sub_12:Test (Best Model) - Loss: 1.2478 - Accuracy: 0.3971 - F1: 0.3836
sub_12:Test (Best Model) - Loss: 1.2526 - Accuracy: 0.4706 - F1: 0.4644
sub_12:Test (Best Model) - Loss: 1.2445 - Accuracy: 0.4118 - F1: 0.4182
sub_12:Test (Best Model) - Loss: 1.3471 - Accuracy: 0.3478 - F1: 0.3488
sub_12:Test (Best Model) - Loss: 1.2905 - Accuracy: 0.3188 - F1: 0.3060
sub_12:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.4058 - F1: 0.3528
sub_12:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.3768 - F1: 0.3524
sub_12:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.3188 - F1: 0.3191
sub_12:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.3824 - F1: 0.3760
sub_12:Test (Best Model) - Loss: 1.3321 - Accuracy: 0.3971 - F1: 0.3842
sub_12:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.3971 - F1: 0.4105
sub_12:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.3676 - F1: 0.3673
sub_12:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3529 - F1: 0.3500
sub_13:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.2941 - F1: 0.3062
sub_13:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.2794 - F1: 0.3001
sub_13:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.2941 - F1: 0.2960
sub_13:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.3088 - F1: 0.3271
sub_13:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3235 - F1: 0.3412
sub_13:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2899 - F1: 0.2644
sub_13:Test (Best Model) - Loss: 1.3952 - Accuracy: 0.2319 - F1: 0.2062
sub_13:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.2319 - F1: 0.2260
sub_13:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.3188 - F1: 0.3267
sub_13:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3188 - F1: 0.3031
sub_13:Test (Best Model) - Loss: 1.4007 - Accuracy: 0.2794 - F1: 0.2366
sub_13:Test (Best Model) - Loss: 1.3865 - Accuracy: 0.3088 - F1: 0.3183
sub_13:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.3235 - F1: 0.3349
sub_13:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2794 - F1: 0.2955
sub_13:Test (Best Model) - Loss: 1.3976 - Accuracy: 0.2794 - F1: 0.2806
sub_14:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.2353 - F1: 0.2436
sub_14:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.2794 - F1: 0.2907
sub_14:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.2794 - F1: 0.2797
sub_14:Test (Best Model) - Loss: 1.4151 - Accuracy: 0.2059 - F1: 0.2239
sub_14:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.2647 - F1: 0.2784
sub_14:Test (Best Model) - Loss: 1.4252 - Accuracy: 0.3235 - F1: 0.2981
sub_14:Test (Best Model) - Loss: 1.4283 - Accuracy: 0.2941 - F1: 0.2580
sub_14:Test (Best Model) - Loss: 1.4052 - Accuracy: 0.3088 - F1: 0.2945
sub_14:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.3235 - F1: 0.3142
sub_14:Test (Best Model) - Loss: 1.4163 - Accuracy: 0.3235 - F1: 0.2903
sub_14:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3382 - F1: 0.3305
sub_14:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3088 - F1: 0.2967
sub_14:Test (Best Model) - Loss: 1.3781 - Accuracy: 0.3088 - F1: 0.2862
sub_14:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.3235 - F1: 0.3185
sub_14:Test (Best Model) - Loss: 1.3426 - Accuracy: 0.2794 - F1: 0.2806
sub_15:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.3529 - F1: 0.3784
sub_15:Test (Best Model) - Loss: 1.4224 - Accuracy: 0.3382 - F1: 0.3612
sub_15:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.3382 - F1: 0.3475
sub_15:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3971 - F1: 0.4264
sub_15:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.3235 - F1: 0.3554
sub_15:Test (Best Model) - Loss: 1.2183 - Accuracy: 0.4853 - F1: 0.4917
sub_15:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.4118 - F1: 0.4448
sub_15:Test (Best Model) - Loss: 1.2188 - Accuracy: 0.5588 - F1: 0.5616
sub_15:Test (Best Model) - Loss: 1.2450 - Accuracy: 0.4559 - F1: 0.4624
sub_15:Test (Best Model) - Loss: 1.2747 - Accuracy: 0.4265 - F1: 0.4408
sub_15:Test (Best Model) - Loss: 1.2553 - Accuracy: 0.4559 - F1: 0.4460
sub_15:Test (Best Model) - Loss: 1.2555 - Accuracy: 0.4412 - F1: 0.4448
sub_15:Test (Best Model) - Loss: 1.2961 - Accuracy: 0.3676 - F1: 0.3718
sub_15:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.3971 - F1: 0.3978
sub_15:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.4265 - F1: 0.4418
sub_16:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.3235 - F1: 0.2564
sub_16:Test (Best Model) - Loss: 1.2531 - Accuracy: 0.3971 - F1: 0.3848
sub_16:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.4706 - F1: 0.4252
sub_16:Test (Best Model) - Loss: 1.3304 - Accuracy: 0.3824 - F1: 0.3681
sub_16:Test (Best Model) - Loss: 1.2877 - Accuracy: 0.4265 - F1: 0.3801
sub_16:Test (Best Model) - Loss: 1.3404 - Accuracy: 0.2941 - F1: 0.2861
sub_16:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.2941 - F1: 0.2921
sub_16:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.3382 - F1: 0.3212
sub_16:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.3676 - F1: 0.3510
sub_16:Test (Best Model) - Loss: 1.5325 - Accuracy: 0.2794 - F1: 0.2805
sub_16:Test (Best Model) - Loss: 1.3322 - Accuracy: 0.3824 - F1: 0.3335
sub_16:Test (Best Model) - Loss: 1.2895 - Accuracy: 0.4412 - F1: 0.3729
sub_16:Test (Best Model) - Loss: 1.2248 - Accuracy: 0.3971 - F1: 0.3740
sub_16:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.2647 - F1: 0.2452
sub_16:Test (Best Model) - Loss: 1.3210 - Accuracy: 0.4118 - F1: 0.3637
sub_17:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.4203 - F1: 0.3685
sub_17:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.3913 - F1: 0.3503
sub_17:Test (Best Model) - Loss: 1.2700 - Accuracy: 0.4203 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3913 - F1: 0.3788
sub_17:Test (Best Model) - Loss: 1.2698 - Accuracy: 0.4203 - F1: 0.4083
sub_17:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3333 - F1: 0.2821
sub_17:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.3333 - F1: 0.2889
sub_17:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.4058 - F1: 0.3473
sub_17:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.3333 - F1: 0.3010
sub_17:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3478 - F1: 0.3003
sub_17:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.4118 - F1: 0.3798
sub_17:Test (Best Model) - Loss: 1.3178 - Accuracy: 0.3676 - F1: 0.3423
sub_17:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3676 - F1: 0.3621
sub_17:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.4265 - F1: 0.4212
sub_17:Test (Best Model) - Loss: 1.3246 - Accuracy: 0.3824 - F1: 0.3800
sub_18:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.3188 - F1: 0.3190
sub_18:Test (Best Model) - Loss: 1.3231 - Accuracy: 0.3768 - F1: 0.3971
sub_18:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.3768 - F1: 0.3570
sub_18:Test (Best Model) - Loss: 1.3327 - Accuracy: 0.3478 - F1: 0.3596
sub_18:Test (Best Model) - Loss: 1.3034 - Accuracy: 0.4058 - F1: 0.4206
sub_18:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.2985
sub_18:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.2794 - F1: 0.3078
sub_18:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.2647 - F1: 0.2745
sub_18:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.2794 - F1: 0.2984
sub_18:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.3088 - F1: 0.3282
sub_18:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3235 - F1: 0.3261
sub_18:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3235 - F1: 0.3080
sub_18:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.2647 - F1: 0.2645
sub_18:Test (Best Model) - Loss: 1.3297 - Accuracy: 0.3529 - F1: 0.3538
sub_18:Test (Best Model) - Loss: 1.3461 - Accuracy: 0.3235 - F1: 0.3479
sub_19:Test (Best Model) - Loss: 1.4064 - Accuracy: 0.3382 - F1: 0.3155
sub_19:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3382 - F1: 0.3034
sub_19:Test (Best Model) - Loss: 1.4306 - Accuracy: 0.2794 - F1: 0.2647
sub_19:Test (Best Model) - Loss: 1.3953 - Accuracy: 0.2941 - F1: 0.2918
sub_19:Test (Best Model) - Loss: 1.3697 - Accuracy: 0.3382 - F1: 0.2659
sub_19:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3824 - F1: 0.3831
sub_19:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3971 - F1: 0.3523
sub_19:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3824 - F1: 0.3717
sub_19:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3824 - F1: 0.3698
sub_19:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.3676 - F1: 0.3306
sub_19:Test (Best Model) - Loss: 1.3736 - Accuracy: 0.3529 - F1: 0.3301
sub_19:Test (Best Model) - Loss: 1.3654 - Accuracy: 0.3235 - F1: 0.3425
sub_19:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.3529 - F1: 0.3643
sub_19:Test (Best Model) - Loss: 1.4115 - Accuracy: 0.2941 - F1: 0.3148
sub_19:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.3529 - F1: 0.3654
sub_20:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.3971 - F1: 0.4076
sub_20:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.4853 - F1: 0.4981
sub_20:Test (Best Model) - Loss: 1.2946 - Accuracy: 0.4853 - F1: 0.4997
sub_20:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.3235 - F1: 0.3296
sub_20:Test (Best Model) - Loss: 1.2991 - Accuracy: 0.4706 - F1: 0.4816
sub_20:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.3824 - F1: 0.3927
sub_20:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.3676 - F1: 0.3794
sub_20:Test (Best Model) - Loss: 1.3505 - Accuracy: 0.4559 - F1: 0.4783
sub_20:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.3382 - F1: 0.3369
sub_20:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.4412 - F1: 0.4521
sub_20:Test (Best Model) - Loss: 1.2917 - Accuracy: 0.3478 - F1: 0.3462
sub_20:Test (Best Model) - Loss: 1.3210 - Accuracy: 0.3478 - F1: 0.3436
sub_20:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2754 - F1: 0.2490
sub_20:Test (Best Model) - Loss: 1.2978 - Accuracy: 0.4058 - F1: 0.4010
sub_20:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3478 - F1: 0.3655
sub_21:Test (Best Model) - Loss: 1.3197 - Accuracy: 0.2941 - F1: 0.2722
sub_21:Test (Best Model) - Loss: 1.3001 - Accuracy: 0.3529 - F1: 0.3284
sub_21:Test (Best Model) - Loss: 1.3316 - Accuracy: 0.3529 - F1: 0.3453
sub_21:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.3382 - F1: 0.3200
sub_21:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.3088 - F1: 0.2899
sub_21:Test (Best Model) - Loss: 1.3368 - Accuracy: 0.2794 - F1: 0.2634
sub_21:Test (Best Model) - Loss: 1.3274 - Accuracy: 0.2941 - F1: 0.2695
sub_21:Test (Best Model) - Loss: 1.3373 - Accuracy: 0.3529 - F1: 0.3032
sub_21:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.3235 - F1: 0.2985
sub_21:Test (Best Model) - Loss: 1.2911 - Accuracy: 0.3676 - F1: 0.3640
sub_21:Test (Best Model) - Loss: 1.3125 - Accuracy: 0.3529 - F1: 0.3471
sub_21:Test (Best Model) - Loss: 1.3488 - Accuracy: 0.2794 - F1: 0.2531
sub_21:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.2941 - F1: 0.2585
sub_21:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.3529 - F1: 0.3195
sub_21:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.3382 - F1: 0.3354
sub_22:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.2941 - F1: 0.2978
sub_22:Test (Best Model) - Loss: 1.3549 - Accuracy: 0.3382 - F1: 0.3387
sub_22:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.3382 - F1: 0.3592
sub_22:Test (Best Model) - Loss: 1.3716 - Accuracy: 0.2941 - F1: 0.3362
sub_22:Test (Best Model) - Loss: 1.4043 - Accuracy: 0.3088 - F1: 0.3324
sub_22:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3188 - F1: 0.2907
sub_22:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.3768 - F1: 0.3437
sub_22:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3043 - F1: 0.2563
sub_22:Test (Best Model) - Loss: 1.3391 - Accuracy: 0.4058 - F1: 0.4103
sub_22:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.2754 - F1: 0.2713
sub_22:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.2941 - F1: 0.3060
sub_22:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3088 - F1: 0.3165
sub_22:Test (Best Model) - Loss: 1.3396 - Accuracy: 0.3824 - F1: 0.3910
sub_22:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3382 - F1: 0.3652
sub_22:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.4118 - F1: 0.4382
sub_23:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.3478 - F1: 0.3352
sub_23:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.3478 - F1: 0.3588
sub_23:Test (Best Model) - Loss: 1.3031 - Accuracy: 0.3478 - F1: 0.3513
sub_23:Test (Best Model) - Loss: 1.2634 - Accuracy: 0.4638 - F1: 0.4653
sub_23:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.3768 - F1: 0.3853
sub_23:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.3824 - F1: 0.3506
sub_23:Test (Best Model) - Loss: 1.3151 - Accuracy: 0.4412 - F1: 0.4479
sub_23:Test (Best Model) - Loss: 1.2515 - Accuracy: 0.4853 - F1: 0.4743
sub_23:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.4412 - F1: 0.4507
sub_23:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.3971 - F1: 0.3757
sub_23:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.2464 - F1: 0.1954
sub_23:Test (Best Model) - Loss: 1.3638 - Accuracy: 0.3188 - F1: 0.3176
sub_23:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.3768 - F1: 0.3651
sub_23:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3043 - F1: 0.3039
sub_23:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.2754 - F1: 0.2650
sub_24:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.3088 - F1: 0.2746
sub_24:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.3088 - F1: 0.2960
sub_24:Test (Best Model) - Loss: 1.4101 - Accuracy: 0.2794 - F1: 0.2812
sub_24:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.2794 - F1: 0.2704
sub_24:Test (Best Model) - Loss: 1.4110 - Accuracy: 0.1618 - F1: 0.1538
sub_24:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.2794 - F1: 0.2706
sub_24:Test (Best Model) - Loss: 1.3818 - Accuracy: 0.3235 - F1: 0.3292
sub_24:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3088 - F1: 0.3097
sub_24:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3824 - F1: 0.3604
sub_24:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3676 - F1: 0.3603
sub_24:Test (Best Model) - Loss: 1.4324 - Accuracy: 0.2353 - F1: 0.2283
sub_24:Test (Best Model) - Loss: 1.4631 - Accuracy: 0.1912 - F1: 0.1914
sub_24:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.1471 - F1: 0.1452
sub_24:Test (Best Model) - Loss: 1.4288 - Accuracy: 0.3088 - F1: 0.3075
sub_24:Test (Best Model) - Loss: 1.4273 - Accuracy: 0.3088 - F1: 0.3032
sub_25:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.3333 - F1: 0.3083
sub_25:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.3913 - F1: 0.3841
sub_25:Test (Best Model) - Loss: 1.3276 - Accuracy: 0.3768 - F1: 0.3668
sub_25:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.4638 - F1: 0.4486
sub_25:Test (Best Model) - Loss: 1.3804 - Accuracy: 0.2754 - F1: 0.2641
sub_25:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.3088 - F1: 0.2971
sub_25:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3676 - F1: 0.3427
sub_25:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.3971 - F1: 0.3765
sub_25:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.4118 - F1: 0.3666
sub_25:Test (Best Model) - Loss: 1.3163 - Accuracy: 0.3971 - F1: 0.3854
sub_25:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3088 - F1: 0.2962
sub_25:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.3529 - F1: 0.3354
sub_25:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.4118 - F1: 0.3984
sub_25:Test (Best Model) - Loss: 1.3115 - Accuracy: 0.2794 - F1: 0.2338
sub_25:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.3382 - F1: 0.3126
sub_26:Test (Best Model) - Loss: 1.2702 - Accuracy: 0.3333 - F1: 0.3404
sub_26:Test (Best Model) - Loss: 1.2871 - Accuracy: 0.3768 - F1: 0.3766
sub_26:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.4058 - F1: 0.4108
sub_26:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.5362 - F1: 0.5583
sub_26:Test (Best Model) - Loss: 1.2519 - Accuracy: 0.4348 - F1: 0.4431
sub_26:Test (Best Model) - Loss: 1.3107 - Accuracy: 0.3676 - F1: 0.3918
sub_26:Test (Best Model) - Loss: 1.2919 - Accuracy: 0.3676 - F1: 0.3927
sub_26:Test (Best Model) - Loss: 1.3037 - Accuracy: 0.3235 - F1: 0.3129
sub_26:Test (Best Model) - Loss: 1.2897 - Accuracy: 0.3971 - F1: 0.4069
sub_26:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.3235 - F1: 0.3397
sub_26:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.4853 - F1: 0.5093
sub_26:Test (Best Model) - Loss: 1.3227 - Accuracy: 0.5147 - F1: 0.5351
sub_26:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.4265 - F1: 0.4367
sub_26:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.5147 - F1: 0.5297
sub_26:Test (Best Model) - Loss: 1.3472 - Accuracy: 0.4412 - F1: 0.4743
sub_27:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.4203 - F1: 0.3685
sub_27:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.3913 - F1: 0.3503
sub_27:Test (Best Model) - Loss: 1.2700 - Accuracy: 0.4203 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3913 - F1: 0.3788
sub_27:Test (Best Model) - Loss: 1.2698 - Accuracy: 0.4203 - F1: 0.4083
sub_27:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3333 - F1: 0.2821
sub_27:Test (Best Model) - Loss: 1.4082 - Accuracy: 0.3333 - F1: 0.2889
sub_27:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.4058 - F1: 0.3473
sub_27:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.3333 - F1: 0.3010
sub_27:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.3478 - F1: 0.3003
sub_27:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.4118 - F1: 0.3798
sub_27:Test (Best Model) - Loss: 1.3178 - Accuracy: 0.3676 - F1: 0.3423
sub_27:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3676 - F1: 0.3621
sub_27:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.4265 - F1: 0.4212
sub_27:Test (Best Model) - Loss: 1.3246 - Accuracy: 0.3824 - F1: 0.3800
sub_28:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.3088 - F1: 0.3063
sub_28:Test (Best Model) - Loss: 1.4095 - Accuracy: 0.2206 - F1: 0.1732
sub_28:Test (Best Model) - Loss: 1.4986 - Accuracy: 0.2794 - F1: 0.2626
sub_28:Test (Best Model) - Loss: 1.4307 - Accuracy: 0.2794 - F1: 0.2865
sub_28:Test (Best Model) - Loss: 1.5030 - Accuracy: 0.2500 - F1: 0.2577
sub_28:Test (Best Model) - Loss: 1.5222 - Accuracy: 0.2500 - F1: 0.2431
sub_28:Test (Best Model) - Loss: 1.5834 - Accuracy: 0.2500 - F1: 0.2441
sub_28:Test (Best Model) - Loss: 1.5385 - Accuracy: 0.2206 - F1: 0.2045
sub_28:Test (Best Model) - Loss: 1.5429 - Accuracy: 0.2794 - F1: 0.2546
sub_28:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.2794 - F1: 0.2471
sub_28:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.3382 - F1: 0.2813
sub_28:Test (Best Model) - Loss: 1.3350 - Accuracy: 0.3529 - F1: 0.2815
sub_28:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.4118 - F1: 0.3671
sub_28:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.4265 - F1: 0.4272
sub_28:Test (Best Model) - Loss: 1.3465 - Accuracy: 0.3382 - F1: 0.3065
sub_29:Test (Best Model) - Loss: 1.2485 - Accuracy: 0.4706 - F1: 0.4981
sub_29:Test (Best Model) - Loss: 1.2165 - Accuracy: 0.3824 - F1: 0.4035
sub_29:Test (Best Model) - Loss: 1.1727 - Accuracy: 0.5147 - F1: 0.5254
sub_29:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.3824 - F1: 0.4137
sub_29:Test (Best Model) - Loss: 1.2137 - Accuracy: 0.4265 - F1: 0.4610
sub_29:Test (Best Model) - Loss: 1.1984 - Accuracy: 0.4706 - F1: 0.4969
sub_29:Test (Best Model) - Loss: 1.2241 - Accuracy: 0.3824 - F1: 0.3798
sub_29:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.4118 - F1: 0.4256
sub_29:Test (Best Model) - Loss: 1.0960 - Accuracy: 0.6029 - F1: 0.6249
sub_29:Test (Best Model) - Loss: 1.1465 - Accuracy: 0.4559 - F1: 0.4826
sub_29:Test (Best Model) - Loss: 1.1112 - Accuracy: 0.5217 - F1: 0.5418
sub_29:Test (Best Model) - Loss: 1.1587 - Accuracy: 0.4638 - F1: 0.4819
sub_29:Test (Best Model) - Loss: 1.1535 - Accuracy: 0.4348 - F1: 0.4490
sub_29:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.5217 - F1: 0.5410
sub_29:Test (Best Model) - Loss: 1.1848 - Accuracy: 0.5072 - F1: 0.5289

=== Summary Results ===

acc: 35.15 ± 5.12
F1: 34.50 ± 5.53
acc-in: 42.09 ± 5.12
F1-in: 40.45 ± 5.40
