lr: 1e-05
sub_20:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3088 - F1: 0.3073
sub_26:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3188 - F1: 0.3163
sub_22:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.4706 - F1: 0.4904
sub_1:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.4559 - F1: 0.4909
sub_12:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2794 - F1: 0.2611
sub_3:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.2500 - F1: 0.2859
sub_9:Test (Best Model) - Loss: 1.3181 - Accuracy: 0.4412 - F1: 0.4396
sub_2:Test (Best Model) - Loss: 1.3911 - Accuracy: 0.2609 - F1: 0.2451
sub_8:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2647 - F1: 0.2299
sub_14:Test (Best Model) - Loss: 1.3980 - Accuracy: 0.2941 - F1: 0.2614
sub_10:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.3529 - F1: 0.2903
sub_15:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.5000 - F1: 0.5203
sub_19:Test (Best Model) - Loss: 1.3129 - Accuracy: 0.4706 - F1: 0.4681
sub_23:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.5942 - F1: 0.5452
sub_24:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.5294 - F1: 0.4950
sub_25:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.4783 - F1: 0.4897
sub_27:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3333 - F1: 0.2907
sub_17:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3333 - F1: 0.2907
sub_7:Test (Best Model) - Loss: 1.2938 - Accuracy: 0.5147 - F1: 0.4486
sub_4:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.3623 - F1: 0.3736
sub_28:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.4118 - F1: 0.3206
sub_13:Test (Best Model) - Loss: 1.3676 - Accuracy: 0.3676 - F1: 0.3596
sub_16:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4706 - F1: 0.4364
sub_29:Test (Best Model) - Loss: 1.3038 - Accuracy: 0.5000 - F1: 0.5190
sub_23:Test (Best Model) - Loss: 1.3641 - Accuracy: 0.3043 - F1: 0.2266
sub_5:Test (Best Model) - Loss: 1.3080 - Accuracy: 0.5147 - F1: 0.4972
sub_18:Test (Best Model) - Loss: 1.3051 - Accuracy: 0.4348 - F1: 0.4320
sub_20:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.5147 - F1: 0.4815
sub_1:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.6471 - F1: 0.6334
sub_21:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.4118 - F1: 0.4010
sub_9:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.4853 - F1: 0.5163
sub_3:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.6471 - F1: 0.6045
sub_11:Test (Best Model) - Loss: 1.2955 - Accuracy: 0.5217 - F1: 0.5070
sub_26:Test (Best Model) - Loss: 1.2641 - Accuracy: 0.6232 - F1: 0.6169
sub_16:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.3824 - F1: 0.3655
sub_7:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.5147 - F1: 0.4226
sub_14:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.2353 - F1: 0.1212
sub_19:Test (Best Model) - Loss: 1.3370 - Accuracy: 0.3382 - F1: 0.2992
sub_27:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.5217 - F1: 0.4469
sub_10:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3824 - F1: 0.3769
sub_15:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.4706 - F1: 0.4597
sub_22:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3382 - F1: 0.2503
sub_17:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.5217 - F1: 0.4469
sub_2:Test (Best Model) - Loss: 1.3027 - Accuracy: 0.5652 - F1: 0.5505
sub_4:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.5942 - F1: 0.5844
sub_29:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.4412 - F1: 0.3884
sub_25:Test (Best Model) - Loss: 1.2512 - Accuracy: 0.6232 - F1: 0.6215
sub_20:Test (Best Model) - Loss: 1.3041 - Accuracy: 0.5882 - F1: 0.5806
sub_13:Test (Best Model) - Loss: 1.3123 - Accuracy: 0.5147 - F1: 0.4898
sub_28:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.6029 - F1: 0.5721
sub_3:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.7353 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 1.3141 - Accuracy: 0.5000 - F1: 0.4409
sub_9:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.5000 - F1: 0.5167
sub_8:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.4118 - F1: 0.3630
sub_12:Test (Best Model) - Loss: 1.2799 - Accuracy: 0.4853 - F1: 0.4915
sub_22:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3529 - F1: 0.3004
sub_23:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.5507 - F1: 0.5603
sub_21:Test (Best Model) - Loss: 1.3282 - Accuracy: 0.4265 - F1: 0.3779
sub_24:Test (Best Model) - Loss: 1.3042 - Accuracy: 0.5588 - F1: 0.5351
sub_5:Test (Best Model) - Loss: 1.3159 - Accuracy: 0.6765 - F1: 0.6197
sub_18:Test (Best Model) - Loss: 1.3229 - Accuracy: 0.4928 - F1: 0.4824
sub_19:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3676 - F1: 0.3835
sub_15:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.4706 - F1: 0.4436
sub_27:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.5652 - F1: 0.5678
sub_16:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2500 - F1: 0.2758
sub_7:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.6176 - F1: 0.6096
sub_11:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.6812 - F1: 0.6132
sub_1:Test (Best Model) - Loss: 1.2964 - Accuracy: 0.5294 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.3529 - F1: 0.2872
sub_17:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.5652 - F1: 0.5678
sub_2:Test (Best Model) - Loss: 1.3507 - Accuracy: 0.4928 - F1: 0.4098
sub_4:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.4638 - F1: 0.4384
sub_10:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3676 - F1: 0.3577
sub_21:Test (Best Model) - Loss: 1.3533 - Accuracy: 0.4412 - F1: 0.4188
sub_20:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.4559 - F1: 0.4105
sub_9:Test (Best Model) - Loss: 1.3461 - Accuracy: 0.3971 - F1: 0.3933
sub_12:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.4559 - F1: 0.4788
sub_15:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.4706 - F1: 0.4972
sub_8:Test (Best Model) - Loss: 1.3353 - Accuracy: 0.3971 - F1: 0.3676
sub_25:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.5362 - F1: 0.5260
sub_29:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.3971 - F1: 0.3636
sub_26:Test (Best Model) - Loss: 1.2963 - Accuracy: 0.5507 - F1: 0.5452
sub_22:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.2647 - F1: 0.2993
sub_13:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.2941 - F1: 0.2898
sub_23:Test (Best Model) - Loss: 1.3323 - Accuracy: 0.3768 - F1: 0.3834
sub_6:Test (Best Model) - Loss: 1.2965 - Accuracy: 0.4412 - F1: 0.3943
sub_24:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.3235 - F1: 0.3196
sub_16:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3676 - F1: 0.3601
sub_18:Test (Best Model) - Loss: 1.3237 - Accuracy: 0.5217 - F1: 0.5086
sub_27:Test (Best Model) - Loss: 1.3008 - Accuracy: 0.5797 - F1: 0.5792
sub_1:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4853 - F1: 0.4818
sub_19:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.4265 - F1: 0.3512
sub_11:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.3188 - F1: 0.3023
sub_9:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.3382 - F1: 0.3291
sub_14:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.4412 - F1: 0.3743
sub_17:Test (Best Model) - Loss: 1.3008 - Accuracy: 0.5797 - F1: 0.5792
sub_5:Test (Best Model) - Loss: 1.3115 - Accuracy: 0.6029 - F1: 0.5556
sub_2:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.5507 - F1: 0.4901
sub_29:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.2647 - F1: 0.2579
sub_12:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.3676 - F1: 0.3932
sub_7:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.5588 - F1: 0.5632
sub_3:Test (Best Model) - Loss: 1.2660 - Accuracy: 0.7353 - F1: 0.7241
sub_23:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.4058 - F1: 0.3744
sub_15:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.2647 - F1: 0.2433
sub_25:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.6377 - F1: 0.6215
sub_21:Test (Best Model) - Loss: 1.2594 - Accuracy: 0.7059 - F1: 0.7246
sub_24:Test (Best Model) - Loss: 1.3557 - Accuracy: 0.3971 - F1: 0.3788
sub_8:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.3382 - F1: 0.3040
sub_10:Test (Best Model) - Loss: 1.3498 - Accuracy: 0.4265 - F1: 0.4360
sub_20:Test (Best Model) - Loss: 1.3146 - Accuracy: 0.4559 - F1: 0.3889
sub_28:Test (Best Model) - Loss: 1.3432 - Accuracy: 0.4265 - F1: 0.4066
sub_4:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.5362 - F1: 0.5346
sub_1:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.2500 - F1: 0.2089
sub_16:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2059 - F1: 0.2091
sub_26:Test (Best Model) - Loss: 1.2969 - Accuracy: 0.5652 - F1: 0.5432
sub_27:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.3913 - F1: 0.3304
sub_6:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.4118 - F1: 0.4048
sub_12:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.2941 - F1: 0.2535
sub_22:Test (Best Model) - Loss: 1.3289 - Accuracy: 0.4559 - F1: 0.4356
sub_2:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.3188 - F1: 0.2352
sub_14:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.2500 - F1: 0.1764
sub_11:Test (Best Model) - Loss: 1.3243 - Accuracy: 0.4348 - F1: 0.4043
sub_18:Test (Best Model) - Loss: 1.3101 - Accuracy: 0.5652 - F1: 0.5485
sub_5:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4265 - F1: 0.4296
sub_23:Test (Best Model) - Loss: 1.3160 - Accuracy: 0.5000 - F1: 0.4747
sub_17:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.3913 - F1: 0.3304
sub_28:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2794 - F1: 0.2511
sub_29:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.3676 - F1: 0.3510
sub_20:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.5588 - F1: 0.5527
sub_19:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3529 - F1: 0.3350
sub_26:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.4203 - F1: 0.3973
sub_7:Test (Best Model) - Loss: 1.2838 - Accuracy: 0.6176 - F1: 0.6167
sub_21:Test (Best Model) - Loss: 1.3285 - Accuracy: 0.4118 - F1: 0.3593
sub_13:Test (Best Model) - Loss: 1.3184 - Accuracy: 0.3676 - F1: 0.3448
sub_3:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.4853 - F1: 0.4635
sub_24:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.3529 - F1: 0.3409
sub_25:Test (Best Model) - Loss: 1.2276 - Accuracy: 0.7101 - F1: 0.6882
sub_10:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.4118 - F1: 0.3912
sub_16:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.4706 - F1: 0.4318
sub_15:Test (Best Model) - Loss: 1.3007 - Accuracy: 0.4559 - F1: 0.4350
sub_8:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.4265 - F1: 0.3605
sub_27:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.4058 - F1: 0.4053
sub_1:Test (Best Model) - Loss: 1.2986 - Accuracy: 0.4783 - F1: 0.4470
sub_9:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.7647 - F1: 0.7574
sub_5:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3824 - F1: 0.3820
sub_19:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.2500 - F1: 0.2190
sub_28:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.3529 - F1: 0.3197
sub_13:Test (Best Model) - Loss: 1.3699 - Accuracy: 0.3088 - F1: 0.2844
sub_17:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.4058 - F1: 0.4053
sub_11:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.5507 - F1: 0.5518
sub_23:Test (Best Model) - Loss: 1.3602 - Accuracy: 0.4265 - F1: 0.3698
sub_2:Test (Best Model) - Loss: 1.2975 - Accuracy: 0.3971 - F1: 0.3549
sub_4:Test (Best Model) - Loss: 1.2432 - Accuracy: 0.5652 - F1: 0.5081
sub_22:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.4058 - F1: 0.3340
sub_20:Test (Best Model) - Loss: 1.3321 - Accuracy: 0.4265 - F1: 0.3597
sub_6:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.5588 - F1: 0.5426
sub_14:Test (Best Model) - Loss: 1.2999 - Accuracy: 0.4412 - F1: 0.4165
sub_3:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.2899 - F1: 0.2960
sub_12:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.3333 - F1: 0.3227
sub_21:Test (Best Model) - Loss: 1.2633 - Accuracy: 0.6029 - F1: 0.5562
sub_26:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.5000 - F1: 0.4554
sub_29:Test (Best Model) - Loss: 1.2615 - Accuracy: 0.6471 - F1: 0.6195
sub_23:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3088 - F1: 0.2295
sub_15:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3382 - F1: 0.3159
sub_19:Test (Best Model) - Loss: 1.3405 - Accuracy: 0.3529 - F1: 0.3462
sub_10:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.2647 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 1.2919 - Accuracy: 0.6176 - F1: 0.6056
sub_7:Test (Best Model) - Loss: 1.2741 - Accuracy: 0.5147 - F1: 0.4086
sub_6:Test (Best Model) - Loss: 1.3489 - Accuracy: 0.4265 - F1: 0.3770
sub_18:Test (Best Model) - Loss: 1.2580 - Accuracy: 0.5507 - F1: 0.5077
sub_11:Test (Best Model) - Loss: 1.2994 - Accuracy: 0.4928 - F1: 0.4947
sub_4:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.3188 - F1: 0.3054
sub_9:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.5882 - F1: 0.5718
sub_24:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.5735 - F1: 0.5528
sub_28:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3088 - F1: 0.2241
sub_21:Test (Best Model) - Loss: 1.3125 - Accuracy: 0.5588 - F1: 0.4942
sub_25:Test (Best Model) - Loss: 1.2241 - Accuracy: 0.6029 - F1: 0.5926
sub_12:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.3478 - F1: 0.3552
sub_8:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.6176 - F1: 0.5585
sub_13:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.4783 - F1: 0.4382
sub_1:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.4348 - F1: 0.4400
sub_16:Test (Best Model) - Loss: 1.2585 - Accuracy: 0.6324 - F1: 0.5869
sub_2:Test (Best Model) - Loss: 1.2539 - Accuracy: 0.6765 - F1: 0.6467
sub_27:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.4203 - F1: 0.4014
sub_14:Test (Best Model) - Loss: 1.2743 - Accuracy: 0.6471 - F1: 0.6473
sub_23:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.4118 - F1: 0.3631
sub_19:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.3676 - F1: 0.3502
sub_10:Test (Best Model) - Loss: 1.3672 - Accuracy: 0.4265 - F1: 0.2851
sub_15:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.5735 - F1: 0.5993
sub_6:Test (Best Model) - Loss: 1.2703 - Accuracy: 0.6232 - F1: 0.6079
sub_17:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.4203 - F1: 0.4014
sub_26:Test (Best Model) - Loss: 1.2713 - Accuracy: 0.5294 - F1: 0.5085
sub_29:Test (Best Model) - Loss: 1.2617 - Accuracy: 0.5882 - F1: 0.5739
sub_22:Test (Best Model) - Loss: 1.3053 - Accuracy: 0.3913 - F1: 0.3317
sub_3:Test (Best Model) - Loss: 1.2724 - Accuracy: 0.4493 - F1: 0.4352
sub_20:Test (Best Model) - Loss: 1.2756 - Accuracy: 0.6324 - F1: 0.6016
sub_5:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.7647 - F1: 0.7455
sub_28:Test (Best Model) - Loss: 1.3707 - Accuracy: 0.2794 - F1: 0.2708
sub_4:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.6377 - F1: 0.6218
sub_25:Test (Best Model) - Loss: 1.3071 - Accuracy: 0.5441 - F1: 0.5294
sub_16:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.4118 - F1: 0.4038
sub_18:Test (Best Model) - Loss: 1.3236 - Accuracy: 0.5000 - F1: 0.4986
sub_12:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.2464 - F1: 0.2322
sub_27:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.4058 - F1: 0.4236
sub_23:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.3824 - F1: 0.3195
sub_21:Test (Best Model) - Loss: 1.2634 - Accuracy: 0.6912 - F1: 0.6749
sub_9:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.6471 - F1: 0.6019
sub_7:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.5147 - F1: 0.4197
sub_3:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.4928 - F1: 0.4921
sub_2:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.6029 - F1: 0.5506
sub_13:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.4058 - F1: 0.3652
sub_10:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.2647 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.5000 - F1: 0.4412
sub_17:Test (Best Model) - Loss: 1.3315 - Accuracy: 0.4058 - F1: 0.4236
sub_5:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.2794 - F1: 0.3229
sub_11:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.3768 - F1: 0.3716
sub_24:Test (Best Model) - Loss: 1.3065 - Accuracy: 0.5147 - F1: 0.5114
sub_1:Test (Best Model) - Loss: 1.3168 - Accuracy: 0.5072 - F1: 0.5075
sub_26:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.6029 - F1: 0.5366
sub_22:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3478 - F1: 0.2903
sub_16:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.4706 - F1: 0.4399
sub_8:Test (Best Model) - Loss: 1.2814 - Accuracy: 0.6029 - F1: 0.5586
sub_15:Test (Best Model) - Loss: 1.2731 - Accuracy: 0.7059 - F1: 0.7096
sub_19:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.4853 - F1: 0.4706
sub_27:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.4348 - F1: 0.4350
sub_12:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.5507 - F1: 0.5503
sub_9:Test (Best Model) - Loss: 1.2783 - Accuracy: 0.6912 - F1: 0.6635
sub_2:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3529 - F1: 0.2919
sub_1:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.4783 - F1: 0.4801
sub_14:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.5882 - F1: 0.5617
sub_29:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.6176 - F1: 0.5717
sub_20:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.4118 - F1: 0.3720
sub_6:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.3913 - F1: 0.3525
sub_17:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.4348 - F1: 0.4350
sub_3:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.6522 - F1: 0.6493
sub_10:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2500 - F1: 0.1104
sub_28:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.2206 - F1: 0.1253
sub_7:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.4559 - F1: 0.4265
sub_21:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.5882 - F1: 0.5599
sub_26:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.5000 - F1: 0.4382
sub_4:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.4493 - F1: 0.3801
sub_19:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2941 - F1: 0.2602
sub_12:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2899 - F1: 0.2565
sub_11:Test (Best Model) - Loss: 1.3310 - Accuracy: 0.3913 - F1: 0.3730
sub_25:Test (Best Model) - Loss: 1.2669 - Accuracy: 0.6471 - F1: 0.6403
sub_22:Test (Best Model) - Loss: 1.3268 - Accuracy: 0.3913 - F1: 0.3396
sub_5:Test (Best Model) - Loss: 1.2985 - Accuracy: 0.5294 - F1: 0.4916
sub_9:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.5441 - F1: 0.5693
sub_27:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3043 - F1: 0.2602
sub_13:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.5072 - F1: 0.5058
sub_2:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.5147 - F1: 0.4750
sub_15:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.5735 - F1: 0.5866
sub_17:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3043 - F1: 0.2602
sub_19:Test (Best Model) - Loss: 1.4020 - Accuracy: 0.2500 - F1: 0.2184
sub_23:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.5362 - F1: 0.5585
sub_1:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.3913 - F1: 0.3429
sub_29:Test (Best Model) - Loss: 1.2657 - Accuracy: 0.6912 - F1: 0.6888
sub_11:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3043 - F1: 0.2615
sub_12:Test (Best Model) - Loss: 1.3687 - Accuracy: 0.2941 - F1: 0.2585
sub_16:Test (Best Model) - Loss: 1.3598 - Accuracy: 0.3235 - F1: 0.3254
sub_7:Test (Best Model) - Loss: 1.3104 - Accuracy: 0.5441 - F1: 0.5454
sub_8:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.6029 - F1: 0.5590
sub_10:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.2647 - F1: 0.1098
sub_5:Test (Best Model) - Loss: 1.2777 - Accuracy: 0.5147 - F1: 0.5468
sub_25:Test (Best Model) - Loss: 1.2660 - Accuracy: 0.6618 - F1: 0.6139
sub_24:Test (Best Model) - Loss: 1.3356 - Accuracy: 0.4265 - F1: 0.4081
sub_21:Test (Best Model) - Loss: 1.3019 - Accuracy: 0.6029 - F1: 0.5898
sub_14:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.4265 - F1: 0.4378
sub_20:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.4783 - F1: 0.4660
sub_18:Test (Best Model) - Loss: 1.2512 - Accuracy: 0.5735 - F1: 0.5690
sub_4:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.5652 - F1: 0.5199
sub_26:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.5000 - F1: 0.4645
sub_28:Test (Best Model) - Loss: 1.4081 - Accuracy: 0.2794 - F1: 0.1487
sub_23:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.1594 - F1: 0.1846
sub_27:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.5882 - F1: 0.5857
sub_24:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.2059 - F1: 0.1895
sub_3:Test (Best Model) - Loss: 1.2883 - Accuracy: 0.5507 - F1: 0.5359
sub_6:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.5652 - F1: 0.5541
sub_13:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.3623 - F1: 0.3452
sub_7:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.4559 - F1: 0.4479
sub_1:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.3676 - F1: 0.3401
sub_15:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.3824 - F1: 0.3659
sub_17:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.5882 - F1: 0.5857
sub_8:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.5441 - F1: 0.5457
sub_29:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.4853 - F1: 0.4710
sub_2:Test (Best Model) - Loss: 1.3440 - Accuracy: 0.4493 - F1: 0.3966
sub_22:Test (Best Model) - Loss: 1.3267 - Accuracy: 0.3768 - F1: 0.3655
sub_5:Test (Best Model) - Loss: 1.3475 - Accuracy: 0.4118 - F1: 0.4034
sub_9:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.5294 - F1: 0.5373
sub_19:Test (Best Model) - Loss: 1.4184 - Accuracy: 0.2647 - F1: 0.2402
sub_11:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.5362 - F1: 0.4871
sub_6:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.4493 - F1: 0.3903
sub_27:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.1765 - F1: 0.1309
sub_21:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3529 - F1: 0.2748
sub_14:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.3824 - F1: 0.3575
sub_12:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.4706 - F1: 0.4027
sub_17:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.1765 - F1: 0.1309
sub_4:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.6087 - F1: 0.5550
sub_18:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.3824 - F1: 0.2984
sub_28:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.2500 - F1: 0.2164
sub_20:Test (Best Model) - Loss: 1.3051 - Accuracy: 0.5217 - F1: 0.5205
sub_8:Test (Best Model) - Loss: 1.3241 - Accuracy: 0.4559 - F1: 0.5008
sub_25:Test (Best Model) - Loss: 1.2545 - Accuracy: 0.6471 - F1: 0.6214
sub_16:Test (Best Model) - Loss: 1.3166 - Accuracy: 0.3971 - F1: 0.3847
sub_26:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.2941 - F1: 0.3246
sub_15:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3382 - F1: 0.2672
sub_3:Test (Best Model) - Loss: 1.2942 - Accuracy: 0.5942 - F1: 0.5676
sub_10:Test (Best Model) - Loss: 1.2666 - Accuracy: 0.6667 - F1: 0.6226
sub_6:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.5072 - F1: 0.4583
sub_23:Test (Best Model) - Loss: 1.3161 - Accuracy: 0.4348 - F1: 0.4133
sub_13:Test (Best Model) - Loss: 1.3298 - Accuracy: 0.4783 - F1: 0.4776
sub_7:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.4853 - F1: 0.4228
sub_18:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.4412 - F1: 0.4584
sub_22:Test (Best Model) - Loss: 1.2977 - Accuracy: 0.5441 - F1: 0.5363
sub_14:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.6324 - F1: 0.6298
sub_27:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.3824 - F1: 0.3867
sub_28:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.1471 - F1: 0.1017
sub_12:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.3971 - F1: 0.3676
sub_16:Test (Best Model) - Loss: 1.3742 - Accuracy: 0.2794 - F1: 0.2501
sub_15:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.3676 - F1: 0.3267
sub_2:Test (Best Model) - Loss: 1.2877 - Accuracy: 0.4928 - F1: 0.4274
sub_29:Test (Best Model) - Loss: 1.3234 - Accuracy: 0.5797 - F1: 0.5174
sub_1:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.7353 - F1: 0.7441
sub_24:Test (Best Model) - Loss: 1.2894 - Accuracy: 0.5588 - F1: 0.5552
sub_9:Test (Best Model) - Loss: 1.3256 - Accuracy: 0.4559 - F1: 0.4680
sub_19:Test (Best Model) - Loss: 1.2947 - Accuracy: 0.5441 - F1: 0.5433
sub_8:Test (Best Model) - Loss: 1.3376 - Accuracy: 0.4265 - F1: 0.4346
sub_11:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.4493 - F1: 0.3710
sub_17:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.3824 - F1: 0.3867
sub_10:Test (Best Model) - Loss: 1.3894 - Accuracy: 0.2609 - F1: 0.2344
sub_18:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.4706 - F1: 0.3974
sub_20:Test (Best Model) - Loss: 1.2593 - Accuracy: 0.6957 - F1: 0.7001
sub_4:Test (Best Model) - Loss: 1.2865 - Accuracy: 0.5507 - F1: 0.5126
sub_21:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.5147 - F1: 0.3853
sub_1:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.3971 - F1: 0.3359
sub_13:Test (Best Model) - Loss: 1.3446 - Accuracy: 0.3529 - F1: 0.3382
sub_28:Test (Best Model) - Loss: 1.4200 - Accuracy: 0.2206 - F1: 0.1501
sub_5:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.5735 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.4559 - F1: 0.4458
sub_16:Test (Best Model) - Loss: 1.3295 - Accuracy: 0.4706 - F1: 0.4704
sub_27:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.4265 - F1: 0.3518
sub_10:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.4493 - F1: 0.3702
sub_26:Test (Best Model) - Loss: 1.3470 - Accuracy: 0.4265 - F1: 0.4221
sub_15:Test (Best Model) - Loss: 1.3038 - Accuracy: 0.4412 - F1: 0.3751
sub_17:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.4265 - F1: 0.3518
sub_20:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.5652 - F1: 0.5576
sub_14:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.6765 - F1: 0.6776
sub_3:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3043 - F1: 0.2073
sub_6:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.5362 - F1: 0.4889
sub_22:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.4118 - F1: 0.3945
sub_19:Test (Best Model) - Loss: 1.3367 - Accuracy: 0.4265 - F1: 0.3918
sub_12:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.5882 - F1: 0.5649
sub_23:Test (Best Model) - Loss: 1.2869 - Accuracy: 0.5507 - F1: 0.5066
sub_24:Test (Best Model) - Loss: 1.3485 - Accuracy: 0.4118 - F1: 0.3693
sub_2:Test (Best Model) - Loss: 1.2909 - Accuracy: 0.5507 - F1: 0.5236
sub_27:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3824 - F1: 0.2851
sub_18:Test (Best Model) - Loss: 1.3479 - Accuracy: 0.4559 - F1: 0.4115
sub_20:Test (Best Model) - Loss: 1.3013 - Accuracy: 0.5507 - F1: 0.5137
sub_21:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.3971 - F1: 0.3757
sub_17:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.3824 - F1: 0.2851
sub_7:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.3382 - F1: 0.2746
sub_9:Test (Best Model) - Loss: 1.2649 - Accuracy: 0.6029 - F1: 0.6013
sub_19:Test (Best Model) - Loss: 1.3238 - Accuracy: 0.4706 - F1: 0.4437
sub_28:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.1618 - F1: 0.1842
sub_16:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.4706 - F1: 0.4488
sub_1:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.6176 - F1: 0.5953
sub_11:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.2754 - F1: 0.1559
sub_5:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.5735 - F1: 0.5587
sub_23:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.2754 - F1: 0.2706
sub_8:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.4412 - F1: 0.4103
sub_25:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.4559 - F1: 0.4598
sub_3:Test (Best Model) - Loss: 1.2984 - Accuracy: 0.5797 - F1: 0.5517
sub_12:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.4412 - F1: 0.4181
sub_18:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.5000 - F1: 0.4697
sub_26:Test (Best Model) - Loss: 1.3143 - Accuracy: 0.5294 - F1: 0.5309
sub_28:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.2794 - F1: 0.2606
sub_9:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.2353 - F1: 0.2172
sub_29:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.5797 - F1: 0.5156
sub_10:Test (Best Model) - Loss: 1.2525 - Accuracy: 0.6087 - F1: 0.5411
sub_4:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.5507 - F1: 0.5416
sub_7:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.2647 - F1: 0.1792
sub_13:Test (Best Model) - Loss: 1.3355 - Accuracy: 0.3824 - F1: 0.3622
sub_15:Test (Best Model) - Loss: 1.2730 - Accuracy: 0.4559 - F1: 0.4146
sub_6:Test (Best Model) - Loss: 1.2948 - Accuracy: 0.5072 - F1: 0.4529
sub_14:Test (Best Model) - Loss: 1.2437 - Accuracy: 0.7941 - F1: 0.7958
sub_22:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.5735 - F1: 0.5357
sub_2:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.4203 - F1: 0.4025
sub_28:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.4265 - F1: 0.3048
sub_1:Test (Best Model) - Loss: 1.2642 - Accuracy: 0.6765 - F1: 0.6310
sub_11:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.6522 - F1: 0.5880
sub_7:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.1471 - F1: 0.1195
sub_16:Test (Best Model) - Loss: 1.2997 - Accuracy: 0.5147 - F1: 0.4604
sub_25:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.5000 - F1: 0.4660
sub_21:Test (Best Model) - Loss: 1.2867 - Accuracy: 0.4559 - F1: 0.4337
sub_5:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.5294 - F1: 0.4422
sub_10:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.5217 - F1: 0.4990
sub_24:Test (Best Model) - Loss: 1.3137 - Accuracy: 0.5441 - F1: 0.5100
sub_8:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.6471 - F1: 0.6727
sub_18:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.5147 - F1: 0.4639
sub_3:Test (Best Model) - Loss: 1.2884 - Accuracy: 0.6232 - F1: 0.6234
sub_9:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3529 - F1: 0.2339
sub_26:Test (Best Model) - Loss: 1.2978 - Accuracy: 0.4706 - F1: 0.4472
sub_22:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.4412 - F1: 0.4019
sub_4:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.5797 - F1: 0.5696
sub_2:Test (Best Model) - Loss: 1.3560 - Accuracy: 0.2319 - F1: 0.2147
sub_11:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.4783 - F1: 0.4226
sub_7:Test (Best Model) - Loss: 1.2984 - Accuracy: 0.4853 - F1: 0.4505
sub_13:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.3971 - F1: 0.2775
sub_21:Test (Best Model) - Loss: 1.2927 - Accuracy: 0.4853 - F1: 0.4181
sub_14:Test (Best Model) - Loss: 1.2569 - Accuracy: 0.5882 - F1: 0.5268
sub_6:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.6087 - F1: 0.6016
sub_22:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.4118 - F1: 0.3677
sub_24:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.4853 - F1: 0.4336
sub_3:Test (Best Model) - Loss: 1.3555 - Accuracy: 0.3913 - F1: 0.3440
sub_29:Test (Best Model) - Loss: 1.3104 - Accuracy: 0.4058 - F1: 0.4212
sub_26:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.6176 - F1: 0.6018
sub_25:Test (Best Model) - Loss: 1.2121 - Accuracy: 0.6029 - F1: 0.5736
sub_8:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.6029 - F1: 0.5863
sub_11:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.3768 - F1: 0.3050
sub_18:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.4412 - F1: 0.3746
sub_5:Test (Best Model) - Loss: 1.2645 - Accuracy: 0.6176 - F1: 0.5602
sub_14:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.2500 - F1: 0.2517
sub_4:Test (Best Model) - Loss: 1.3019 - Accuracy: 0.4783 - F1: 0.4652
sub_24:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.4265 - F1: 0.3682
sub_13:Test (Best Model) - Loss: 1.3499 - Accuracy: 0.3971 - F1: 0.2945
sub_4:Test (Best Model) - Loss: 1.3249 - Accuracy: 0.5362 - F1: 0.4941
sub_6:Test (Best Model) - Loss: 1.3043 - Accuracy: 0.5362 - F1: 0.5057
sub_8:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.4559 - F1: 0.4432
sub_25:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.6471 - F1: 0.6366
sub_18:Test (Best Model) - Loss: 1.3324 - Accuracy: 0.4853 - F1: 0.4828
sub_29:Test (Best Model) - Loss: 1.3420 - Accuracy: 0.3623 - F1: 0.3171
sub_24:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.2794 - F1: 0.2704
sub_6:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.5507 - F1: 0.5232
sub_13:Test (Best Model) - Loss: 1.3693 - Accuracy: 0.3382 - F1: 0.3212
sub_29:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.5362 - F1: 0.4911

=== Summary Results ===

acc: 46.00 ± 5.75
F1: 43.09 ± 6.37
acc-in: 56.44 ± 5.69
F1-in: 54.10 ± 5.53
