lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.3235 - F1: 0.3169
sub_1:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3088 - F1: 0.3359
sub_1:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.3676 - F1: 0.3708
sub_1:Test (Best Model) - Loss: 1.2896 - Accuracy: 0.4265 - F1: 0.4666
sub_1:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.2500 - F1: 0.2582
sub_1:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.3333 - F1: 0.3275
sub_1:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.2464 - F1: 0.2440
sub_1:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3188 - F1: 0.3218
sub_1:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.2464 - F1: 0.2626
sub_1:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.4058 - F1: 0.4267
sub_1:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3824 - F1: 0.3817
sub_1:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.4412 - F1: 0.4544
sub_1:Test (Best Model) - Loss: 1.3271 - Accuracy: 0.3676 - F1: 0.3838
sub_1:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.4559 - F1: 0.4540
sub_1:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.4853 - F1: 0.4921
sub_2:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2899 - F1: 0.2904
sub_2:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.3043 - F1: 0.3001
sub_2:Test (Best Model) - Loss: 1.3820 - Accuracy: 0.2899 - F1: 0.2917
sub_2:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.2697
sub_2:Test (Best Model) - Loss: 1.4148 - Accuracy: 0.2609 - F1: 0.2433
sub_2:Test (Best Model) - Loss: 1.3817 - Accuracy: 0.3529 - F1: 0.3462
sub_2:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3235 - F1: 0.3183
sub_2:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2794 - F1: 0.2793
sub_2:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2500 - F1: 0.2546
sub_2:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.3382 - F1: 0.3498
sub_2:Test (Best Model) - Loss: 1.4368 - Accuracy: 0.2609 - F1: 0.2694
sub_2:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.2319 - F1: 0.2276
sub_2:Test (Best Model) - Loss: 1.3921 - Accuracy: 0.2609 - F1: 0.2633
sub_2:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3913 - F1: 0.3900
sub_2:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.2899 - F1: 0.3019
sub_3:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.2941 - F1: 0.2766
sub_3:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.2353 - F1: 0.2267
sub_3:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.2500 - F1: 0.2616
sub_3:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.2941 - F1: 0.2758
sub_3:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.2353 - F1: 0.2065
sub_3:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.3043 - F1: 0.2812
sub_3:Test (Best Model) - Loss: 1.4031 - Accuracy: 0.2029 - F1: 0.1960
sub_3:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.2754 - F1: 0.2733
sub_3:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.2464 - F1: 0.2452
sub_3:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.3188 - F1: 0.2890
sub_3:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.3913 - F1: 0.3829
sub_3:Test (Best Model) - Loss: 1.3608 - Accuracy: 0.3333 - F1: 0.3208
sub_3:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.2754 - F1: 0.2538
sub_3:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2899 - F1: 0.2505
sub_3:Test (Best Model) - Loss: 1.3631 - Accuracy: 0.2609 - F1: 0.2589
sub_4:Test (Best Model) - Loss: 1.2377 - Accuracy: 0.3913 - F1: 0.4179
sub_4:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.4058 - F1: 0.4095
sub_4:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.2754 - F1: 0.2642
sub_4:Test (Best Model) - Loss: 1.1923 - Accuracy: 0.5652 - F1: 0.5981
sub_4:Test (Best Model) - Loss: 1.1571 - Accuracy: 0.5072 - F1: 0.5198
sub_4:Test (Best Model) - Loss: 1.2582 - Accuracy: 0.4058 - F1: 0.4171
sub_4:Test (Best Model) - Loss: 1.2298 - Accuracy: 0.5217 - F1: 0.5247
sub_4:Test (Best Model) - Loss: 1.2488 - Accuracy: 0.4928 - F1: 0.5132
sub_4:Test (Best Model) - Loss: 1.2646 - Accuracy: 0.5362 - F1: 0.5333
sub_4:Test (Best Model) - Loss: 1.2374 - Accuracy: 0.5072 - F1: 0.5230
sub_4:Test (Best Model) - Loss: 1.2244 - Accuracy: 0.4203 - F1: 0.3789
sub_4:Test (Best Model) - Loss: 1.3169 - Accuracy: 0.3623 - F1: 0.3498
sub_4:Test (Best Model) - Loss: 1.2314 - Accuracy: 0.4638 - F1: 0.4580
sub_4:Test (Best Model) - Loss: 1.2178 - Accuracy: 0.4058 - F1: 0.4213
sub_4:Test (Best Model) - Loss: 1.2838 - Accuracy: 0.5072 - F1: 0.4950
sub_5:Test (Best Model) - Loss: 1.3352 - Accuracy: 0.4706 - F1: 0.4322
sub_5:Test (Best Model) - Loss: 1.3378 - Accuracy: 0.4559 - F1: 0.4314
sub_5:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.4265 - F1: 0.4086
sub_5:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.4559 - F1: 0.4540
sub_5:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.3676 - F1: 0.3567
sub_5:Test (Best Model) - Loss: 1.2398 - Accuracy: 0.4853 - F1: 0.4839
sub_5:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.4853 - F1: 0.4855
sub_5:Test (Best Model) - Loss: 1.2310 - Accuracy: 0.4559 - F1: 0.4611
sub_5:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.4853 - F1: 0.4622
sub_5:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.4265 - F1: 0.4365
sub_5:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.4853 - F1: 0.4869
sub_5:Test (Best Model) - Loss: 1.3065 - Accuracy: 0.4265 - F1: 0.4126
sub_5:Test (Best Model) - Loss: 1.2635 - Accuracy: 0.4706 - F1: 0.4877
sub_5:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.4118 - F1: 0.4045
sub_5:Test (Best Model) - Loss: 1.2055 - Accuracy: 0.4559 - F1: 0.4327
sub_6:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.3971 - F1: 0.4117
sub_6:Test (Best Model) - Loss: 1.3344 - Accuracy: 0.3529 - F1: 0.3575
sub_6:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.3529 - F1: 0.3277
sub_6:Test (Best Model) - Loss: 1.3126 - Accuracy: 0.3824 - F1: 0.4034
sub_6:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.4265 - F1: 0.4285
sub_6:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.4493 - F1: 0.4275
sub_6:Test (Best Model) - Loss: 1.3009 - Accuracy: 0.4348 - F1: 0.4203
sub_6:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.3043 - F1: 0.2682
sub_6:Test (Best Model) - Loss: 1.3017 - Accuracy: 0.4638 - F1: 0.4375
sub_6:Test (Best Model) - Loss: 1.3593 - Accuracy: 0.3478 - F1: 0.3183
sub_6:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.3188 - F1: 0.3260
sub_6:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.3333 - F1: 0.3421
sub_6:Test (Best Model) - Loss: 1.3258 - Accuracy: 0.3333 - F1: 0.3412
sub_6:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.3913 - F1: 0.3960
sub_6:Test (Best Model) - Loss: 1.3337 - Accuracy: 0.4058 - F1: 0.4171
sub_7:Test (Best Model) - Loss: 1.2128 - Accuracy: 0.5588 - F1: 0.5276
sub_7:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.4118 - F1: 0.3886
sub_7:Test (Best Model) - Loss: 1.2378 - Accuracy: 0.4853 - F1: 0.4718
sub_7:Test (Best Model) - Loss: 1.2606 - Accuracy: 0.5147 - F1: 0.4923
sub_7:Test (Best Model) - Loss: 1.2811 - Accuracy: 0.4559 - F1: 0.4382
sub_7:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.3235 - F1: 0.3187
sub_7:Test (Best Model) - Loss: 1.2735 - Accuracy: 0.4412 - F1: 0.4437
sub_7:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.4118 - F1: 0.4151
sub_7:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.4853 - F1: 0.4835
sub_7:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.3971 - F1: 0.4005
sub_7:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.3676 - F1: 0.3620
sub_7:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.4265 - F1: 0.3742
sub_7:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.4118 - F1: 0.3839
sub_7:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3971 - F1: 0.3993
sub_7:Test (Best Model) - Loss: 1.3071 - Accuracy: 0.3971 - F1: 0.3861
sub_8:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.2794 - F1: 0.2642
sub_8:Test (Best Model) - Loss: 1.3994 - Accuracy: 0.2794 - F1: 0.2680
sub_8:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.1912 - F1: 0.2101
sub_8:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.2794 - F1: 0.2858
sub_8:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2206 - F1: 0.2314
sub_8:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.2941 - F1: 0.3071
sub_8:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.2353 - F1: 0.2374
sub_8:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.2794 - F1: 0.2957
sub_8:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2794 - F1: 0.2650
sub_8:Test (Best Model) - Loss: 1.3653 - Accuracy: 0.3235 - F1: 0.3091
sub_8:Test (Best Model) - Loss: 1.3829 - Accuracy: 0.4118 - F1: 0.4087
sub_8:Test (Best Model) - Loss: 1.3756 - Accuracy: 0.2941 - F1: 0.2999
sub_8:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.3088 - F1: 0.3217
sub_8:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.4265 - F1: 0.4313
sub_8:Test (Best Model) - Loss: 1.3982 - Accuracy: 0.2206 - F1: 0.2412
sub_9:Test (Best Model) - Loss: 1.2535 - Accuracy: 0.4412 - F1: 0.4637
sub_9:Test (Best Model) - Loss: 1.2955 - Accuracy: 0.4412 - F1: 0.4540
sub_9:Test (Best Model) - Loss: 1.2957 - Accuracy: 0.3676 - F1: 0.3673
sub_9:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.3971 - F1: 0.4077
sub_9:Test (Best Model) - Loss: 1.3087 - Accuracy: 0.3824 - F1: 0.4133
sub_9:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.3529 - F1: 0.3828
sub_9:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.2500 - F1: 0.2539
sub_9:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.3382 - F1: 0.3642
sub_9:Test (Best Model) - Loss: 1.2458 - Accuracy: 0.3529 - F1: 0.3753
sub_9:Test (Best Model) - Loss: 1.3414 - Accuracy: 0.3088 - F1: 0.3192
sub_9:Test (Best Model) - Loss: 1.3540 - Accuracy: 0.2500 - F1: 0.2518
sub_9:Test (Best Model) - Loss: 1.3053 - Accuracy: 0.3676 - F1: 0.3554
sub_9:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.2941 - F1: 0.3121
sub_9:Test (Best Model) - Loss: 1.3109 - Accuracy: 0.3824 - F1: 0.3849
sub_9:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.3382 - F1: 0.3441
sub_10:Test (Best Model) - Loss: 1.3883 - Accuracy: 0.2500 - F1: 0.2460
sub_10:Test (Best Model) - Loss: 1.3812 - Accuracy: 0.2647 - F1: 0.2701
sub_10:Test (Best Model) - Loss: 1.4182 - Accuracy: 0.2059 - F1: 0.1903
sub_10:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3382 - F1: 0.3495
sub_10:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.3676 - F1: 0.3498
sub_10:Test (Best Model) - Loss: 1.3853 - Accuracy: 0.2353 - F1: 0.2094
sub_10:Test (Best Model) - Loss: 1.4108 - Accuracy: 0.1912 - F1: 0.1951
sub_10:Test (Best Model) - Loss: 1.4139 - Accuracy: 0.1912 - F1: 0.1734
sub_10:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.2353 - F1: 0.2355
sub_10:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2500 - F1: 0.2509
sub_10:Test (Best Model) - Loss: 1.4003 - Accuracy: 0.2754 - F1: 0.2805
sub_10:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2899 - F1: 0.2833
sub_10:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2464 - F1: 0.2394
sub_10:Test (Best Model) - Loss: 1.3825 - Accuracy: 0.3043 - F1: 0.3092
sub_10:Test (Best Model) - Loss: 1.4101 - Accuracy: 0.2319 - F1: 0.1979
sub_11:Test (Best Model) - Loss: 1.3231 - Accuracy: 0.3188 - F1: 0.2952
sub_11:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.4058 - F1: 0.3961
sub_11:Test (Best Model) - Loss: 1.3394 - Accuracy: 0.2609 - F1: 0.2576
sub_11:Test (Best Model) - Loss: 1.3423 - Accuracy: 0.4348 - F1: 0.4177
sub_11:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.2609 - F1: 0.2213
sub_11:Test (Best Model) - Loss: 1.3375 - Accuracy: 0.3623 - F1: 0.3476
sub_11:Test (Best Model) - Loss: 1.3311 - Accuracy: 0.3478 - F1: 0.3159
sub_11:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.4348 - F1: 0.3934
sub_11:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.3768 - F1: 0.3541
sub_11:Test (Best Model) - Loss: 1.3711 - Accuracy: 0.2754 - F1: 0.2315
sub_11:Test (Best Model) - Loss: 1.3594 - Accuracy: 0.3333 - F1: 0.2978
sub_11:Test (Best Model) - Loss: 1.3569 - Accuracy: 0.2754 - F1: 0.2310
sub_11:Test (Best Model) - Loss: 1.3286 - Accuracy: 0.3478 - F1: 0.3335
sub_11:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.4493 - F1: 0.4297
sub_11:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.3333 - F1: 0.3117
sub_12:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.4559 - F1: 0.4167
sub_12:Test (Best Model) - Loss: 1.2287 - Accuracy: 0.4706 - F1: 0.4917
sub_12:Test (Best Model) - Loss: 1.3173 - Accuracy: 0.2794 - F1: 0.2527
sub_12:Test (Best Model) - Loss: 1.2572 - Accuracy: 0.4118 - F1: 0.4188
sub_12:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.4118 - F1: 0.4061
sub_12:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.4203 - F1: 0.4143
sub_12:Test (Best Model) - Loss: 1.3086 - Accuracy: 0.3623 - F1: 0.3485
sub_12:Test (Best Model) - Loss: 1.3071 - Accuracy: 0.4058 - F1: 0.4059
sub_12:Test (Best Model) - Loss: 1.3154 - Accuracy: 0.3768 - F1: 0.3834
sub_12:Test (Best Model) - Loss: 1.3123 - Accuracy: 0.3623 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 1.3062 - Accuracy: 0.4265 - F1: 0.3996
sub_12:Test (Best Model) - Loss: 1.3148 - Accuracy: 0.4265 - F1: 0.4270
sub_12:Test (Best Model) - Loss: 1.2805 - Accuracy: 0.4706 - F1: 0.4687
sub_12:Test (Best Model) - Loss: 1.2708 - Accuracy: 0.4706 - F1: 0.4817
sub_12:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.4412 - F1: 0.4566
sub_13:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3382 - F1: 0.3447
sub_13:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.2500 - F1: 0.2531
sub_13:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.3088 - F1: 0.2879
sub_13:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.3235 - F1: 0.3389
sub_13:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.2794 - F1: 0.3025
sub_13:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3333 - F1: 0.3135
sub_13:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3623 - F1: 0.3490
sub_13:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.2754 - F1: 0.2681
sub_13:Test (Best Model) - Loss: 1.3906 - Accuracy: 0.3333 - F1: 0.3242
sub_13:Test (Best Model) - Loss: 1.3292 - Accuracy: 0.3623 - F1: 0.3773
sub_13:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2353 - F1: 0.2185
sub_13:Test (Best Model) - Loss: 1.3668 - Accuracy: 0.3676 - F1: 0.3472
sub_13:Test (Best Model) - Loss: 1.3728 - Accuracy: 0.3676 - F1: 0.3492
sub_13:Test (Best Model) - Loss: 1.3782 - Accuracy: 0.2647 - F1: 0.2193
sub_13:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.2794 - F1: 0.2787
sub_14:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.3088 - F1: 0.3158
sub_14:Test (Best Model) - Loss: 1.3436 - Accuracy: 0.3529 - F1: 0.3673
sub_14:Test (Best Model) - Loss: 1.3267 - Accuracy: 0.3088 - F1: 0.3141
sub_14:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.2500 - F1: 0.2096
sub_14:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.3235 - F1: 0.3043
sub_14:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.3235 - F1: 0.2717
sub_14:Test (Best Model) - Loss: 1.2951 - Accuracy: 0.3676 - F1: 0.3832
sub_14:Test (Best Model) - Loss: 1.3251 - Accuracy: 0.3235 - F1: 0.3060
sub_14:Test (Best Model) - Loss: 1.3558 - Accuracy: 0.2941 - F1: 0.2798
sub_14:Test (Best Model) - Loss: 1.3412 - Accuracy: 0.2941 - F1: 0.2508
sub_14:Test (Best Model) - Loss: 1.3652 - Accuracy: 0.2794 - F1: 0.2611
sub_14:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.3088 - F1: 0.2897
sub_14:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.3235 - F1: 0.3278
sub_14:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.2941 - F1: 0.2854
sub_14:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.3529 - F1: 0.3425
sub_15:Test (Best Model) - Loss: 1.2514 - Accuracy: 0.4265 - F1: 0.4542
sub_15:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.4265 - F1: 0.4310
sub_15:Test (Best Model) - Loss: 1.2971 - Accuracy: 0.4412 - F1: 0.4622
sub_15:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.3824 - F1: 0.4123
sub_15:Test (Best Model) - Loss: 1.2948 - Accuracy: 0.3824 - F1: 0.4119
sub_15:Test (Best Model) - Loss: 1.2479 - Accuracy: 0.5000 - F1: 0.4940
sub_15:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.4265 - F1: 0.4390
sub_15:Test (Best Model) - Loss: 1.2448 - Accuracy: 0.3971 - F1: 0.3965
sub_15:Test (Best Model) - Loss: 1.1433 - Accuracy: 0.5882 - F1: 0.5866
sub_15:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.4559 - F1: 0.4652
sub_15:Test (Best Model) - Loss: 1.3059 - Accuracy: 0.3529 - F1: 0.3415
sub_15:Test (Best Model) - Loss: 1.2707 - Accuracy: 0.3971 - F1: 0.3883
sub_15:Test (Best Model) - Loss: 1.2861 - Accuracy: 0.4118 - F1: 0.3961
sub_15:Test (Best Model) - Loss: 1.2617 - Accuracy: 0.4265 - F1: 0.4208
sub_15:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.4706 - F1: 0.4791
sub_16:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.4118 - F1: 0.4000
sub_16:Test (Best Model) - Loss: 1.2775 - Accuracy: 0.5000 - F1: 0.4682
sub_16:Test (Best Model) - Loss: 1.2426 - Accuracy: 0.4706 - F1: 0.4413
sub_16:Test (Best Model) - Loss: 1.3024 - Accuracy: 0.4412 - F1: 0.4230
sub_16:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.4853 - F1: 0.4640
sub_16:Test (Best Model) - Loss: 1.2866 - Accuracy: 0.3971 - F1: 0.3599
sub_16:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.3971 - F1: 0.3944
sub_16:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3235 - F1: 0.2922
sub_16:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.3824 - F1: 0.3561
sub_16:Test (Best Model) - Loss: 1.3471 - Accuracy: 0.3529 - F1: 0.3360
sub_16:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.4853 - F1: 0.4173
sub_16:Test (Best Model) - Loss: 1.2966 - Accuracy: 0.4853 - F1: 0.4608
sub_16:Test (Best Model) - Loss: 1.3369 - Accuracy: 0.4118 - F1: 0.3697
sub_16:Test (Best Model) - Loss: 1.3217 - Accuracy: 0.3824 - F1: 0.3571
sub_16:Test (Best Model) - Loss: 1.3424 - Accuracy: 0.3529 - F1: 0.3194
sub_17:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2899 - F1: 0.2812
sub_17:Test (Best Model) - Loss: 1.2953 - Accuracy: 0.4638 - F1: 0.4421
sub_17:Test (Best Model) - Loss: 1.3258 - Accuracy: 0.3043 - F1: 0.2588
sub_17:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.3333 - F1: 0.2860
sub_17:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.3333 - F1: 0.3314
sub_17:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2899 - F1: 0.2647
sub_17:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2899 - F1: 0.2578
sub_17:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.4638 - F1: 0.4013
sub_17:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.3188 - F1: 0.2453
sub_17:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4203 - F1: 0.3436
sub_17:Test (Best Model) - Loss: 1.2646 - Accuracy: 0.3971 - F1: 0.3758
sub_17:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.3529 - F1: 0.3343
sub_17:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3235 - F1: 0.2949
sub_17:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.3971 - F1: 0.3888
sub_17:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.3235 - F1: 0.2956
sub_18:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.2899 - F1: 0.2845
sub_18:Test (Best Model) - Loss: 1.2929 - Accuracy: 0.3478 - F1: 0.3575
sub_18:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.4058 - F1: 0.4168
sub_18:Test (Best Model) - Loss: 1.3347 - Accuracy: 0.3188 - F1: 0.3220
sub_18:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.2899 - F1: 0.2956
sub_18:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2941 - F1: 0.2990
sub_18:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.3971 - F1: 0.3952
sub_18:Test (Best Model) - Loss: 1.3642 - Accuracy: 0.2206 - F1: 0.2260
sub_18:Test (Best Model) - Loss: 1.3358 - Accuracy: 0.3382 - F1: 0.3573
sub_18:Test (Best Model) - Loss: 1.3704 - Accuracy: 0.3088 - F1: 0.2977
sub_18:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.3676 - F1: 0.3659
sub_18:Test (Best Model) - Loss: 1.3603 - Accuracy: 0.3088 - F1: 0.3117
sub_18:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.4118 - F1: 0.4246
sub_18:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3676 - F1: 0.3616
sub_18:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.3676 - F1: 0.3960
sub_19:Test (Best Model) - Loss: 1.4185 - Accuracy: 0.1471 - F1: 0.1458
sub_19:Test (Best Model) - Loss: 1.4221 - Accuracy: 0.2794 - F1: 0.2632
sub_19:Test (Best Model) - Loss: 1.4129 - Accuracy: 0.2206 - F1: 0.2050
sub_19:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.3235 - F1: 0.2876
sub_19:Test (Best Model) - Loss: 1.4147 - Accuracy: 0.2206 - F1: 0.1631
sub_19:Test (Best Model) - Loss: 1.3301 - Accuracy: 0.3235 - F1: 0.2943
sub_19:Test (Best Model) - Loss: 1.3141 - Accuracy: 0.3676 - F1: 0.3509
sub_19:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.3676 - F1: 0.3830
sub_19:Test (Best Model) - Loss: 1.3028 - Accuracy: 0.3971 - F1: 0.3848
sub_19:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.3382 - F1: 0.2810
sub_19:Test (Best Model) - Loss: 1.3237 - Accuracy: 0.3382 - F1: 0.3618
sub_19:Test (Best Model) - Loss: 1.3483 - Accuracy: 0.3088 - F1: 0.3051
sub_19:Test (Best Model) - Loss: 1.2670 - Accuracy: 0.3676 - F1: 0.3354
sub_19:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3235 - F1: 0.3281
sub_19:Test (Best Model) - Loss: 1.3084 - Accuracy: 0.3088 - F1: 0.2844
sub_20:Test (Best Model) - Loss: 1.2827 - Accuracy: 0.4118 - F1: 0.4103
sub_20:Test (Best Model) - Loss: 1.1910 - Accuracy: 0.5000 - F1: 0.5198
sub_20:Test (Best Model) - Loss: 1.2355 - Accuracy: 0.4706 - F1: 0.4861
sub_20:Test (Best Model) - Loss: 1.2329 - Accuracy: 0.5000 - F1: 0.4866
sub_20:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.4265 - F1: 0.4263
sub_20:Test (Best Model) - Loss: 1.3248 - Accuracy: 0.3382 - F1: 0.3130
sub_20:Test (Best Model) - Loss: 1.3283 - Accuracy: 0.3088 - F1: 0.3006
sub_20:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3088 - F1: 0.3201
sub_20:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.3088 - F1: 0.3366
sub_20:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.4118 - F1: 0.4031
sub_20:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.4058 - F1: 0.3728
sub_20:Test (Best Model) - Loss: 1.2900 - Accuracy: 0.4348 - F1: 0.4323
sub_20:Test (Best Model) - Loss: 1.2815 - Accuracy: 0.3478 - F1: 0.3632
sub_20:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.4638 - F1: 0.4657
sub_20:Test (Best Model) - Loss: 1.3087 - Accuracy: 0.3478 - F1: 0.3125
sub_21:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.4265 - F1: 0.4018
sub_21:Test (Best Model) - Loss: 1.3028 - Accuracy: 0.2941 - F1: 0.2658
sub_21:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.3382 - F1: 0.2905
sub_21:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.4265 - F1: 0.3848
sub_21:Test (Best Model) - Loss: 1.2757 - Accuracy: 0.3235 - F1: 0.3083
sub_21:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.3088 - F1: 0.3237
sub_21:Test (Best Model) - Loss: 1.3082 - Accuracy: 0.3088 - F1: 0.2733
sub_21:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.2059 - F1: 0.1820
sub_21:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.3676 - F1: 0.3437
sub_21:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.4559 - F1: 0.4135
sub_21:Test (Best Model) - Loss: 1.2808 - Accuracy: 0.3088 - F1: 0.2975
sub_21:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.3235 - F1: 0.3123
sub_21:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.3824 - F1: 0.3551
sub_21:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.5000 - F1: 0.4852
sub_21:Test (Best Model) - Loss: 1.2880 - Accuracy: 0.2941 - F1: 0.2434
sub_22:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3676 - F1: 0.3515
sub_22:Test (Best Model) - Loss: 1.3436 - Accuracy: 0.3235 - F1: 0.3458
sub_22:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.3382 - F1: 0.3252
sub_22:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.3824 - F1: 0.3919
sub_22:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.2941 - F1: 0.3054
sub_22:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.2609 - F1: 0.2333
sub_22:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.3188 - F1: 0.3083
sub_22:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3768 - F1: 0.3550
sub_22:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2029 - F1: 0.1834
sub_22:Test (Best Model) - Loss: 1.3700 - Accuracy: 0.2319 - F1: 0.2204
sub_22:Test (Best Model) - Loss: 1.3646 - Accuracy: 0.2941 - F1: 0.2923
sub_22:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.3235 - F1: 0.2958
sub_22:Test (Best Model) - Loss: 1.3549 - Accuracy: 0.3088 - F1: 0.3199
sub_22:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.3088 - F1: 0.3265
sub_22:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.3382 - F1: 0.3607
sub_23:Test (Best Model) - Loss: 1.3124 - Accuracy: 0.2899 - F1: 0.2793
sub_23:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.4058 - F1: 0.4081
sub_23:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.3478 - F1: 0.3283
sub_23:Test (Best Model) - Loss: 1.2641 - Accuracy: 0.4783 - F1: 0.4751
sub_23:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.4203 - F1: 0.4390
sub_23:Test (Best Model) - Loss: 1.2978 - Accuracy: 0.4412 - F1: 0.4363
sub_23:Test (Best Model) - Loss: 1.2532 - Accuracy: 0.4559 - F1: 0.4717
sub_23:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.4265 - F1: 0.4388
sub_23:Test (Best Model) - Loss: 1.2985 - Accuracy: 0.4412 - F1: 0.4317
sub_23:Test (Best Model) - Loss: 1.3283 - Accuracy: 0.3382 - F1: 0.3504
sub_23:Test (Best Model) - Loss: 1.2678 - Accuracy: 0.4348 - F1: 0.4280
sub_23:Test (Best Model) - Loss: 1.2429 - Accuracy: 0.3768 - F1: 0.3692
sub_23:Test (Best Model) - Loss: 1.2766 - Accuracy: 0.3478 - F1: 0.3163
sub_23:Test (Best Model) - Loss: 1.2358 - Accuracy: 0.4493 - F1: 0.4665
sub_23:Test (Best Model) - Loss: 1.3036 - Accuracy: 0.3043 - F1: 0.3014
sub_24:Test (Best Model) - Loss: 1.3527 - Accuracy: 0.3529 - F1: 0.3439
sub_24:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.2353 - F1: 0.2340
sub_24:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.3529 - F1: 0.3419
sub_24:Test (Best Model) - Loss: 1.4088 - Accuracy: 0.2206 - F1: 0.2250
sub_24:Test (Best Model) - Loss: 1.3932 - Accuracy: 0.2647 - F1: 0.2654
sub_24:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2353 - F1: 0.2207
sub_24:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3382 - F1: 0.3389
sub_24:Test (Best Model) - Loss: 1.3597 - Accuracy: 0.3676 - F1: 0.3632
sub_24:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.4118 - F1: 0.4101
sub_24:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2353 - F1: 0.2357
sub_24:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.2500 - F1: 0.2599
sub_24:Test (Best Model) - Loss: 1.3991 - Accuracy: 0.2059 - F1: 0.2024
sub_24:Test (Best Model) - Loss: 1.3878 - Accuracy: 0.2794 - F1: 0.2777
sub_24:Test (Best Model) - Loss: 1.3974 - Accuracy: 0.2500 - F1: 0.2499
sub_24:Test (Best Model) - Loss: 1.3835 - Accuracy: 0.2353 - F1: 0.2435
sub_25:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.3623 - F1: 0.3298
sub_25:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3043 - F1: 0.2598
sub_25:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3333 - F1: 0.3035
sub_25:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.3478 - F1: 0.3106
sub_25:Test (Best Model) - Loss: 1.3477 - Accuracy: 0.2899 - F1: 0.2502
sub_25:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.4412 - F1: 0.4322
sub_25:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.4118 - F1: 0.4080
sub_25:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.3382 - F1: 0.3191
sub_25:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.3382 - F1: 0.3071
sub_25:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.2941 - F1: 0.2885
sub_25:Test (Best Model) - Loss: 1.3283 - Accuracy: 0.3971 - F1: 0.4016
sub_25:Test (Best Model) - Loss: 1.3037 - Accuracy: 0.3824 - F1: 0.3691
sub_25:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.3824 - F1: 0.3782
sub_25:Test (Best Model) - Loss: 1.2837 - Accuracy: 0.3676 - F1: 0.3172
sub_25:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.3529 - F1: 0.3165
sub_26:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.3043 - F1: 0.3036
sub_26:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.4638 - F1: 0.4628
sub_26:Test (Best Model) - Loss: 1.2658 - Accuracy: 0.4783 - F1: 0.4890
sub_26:Test (Best Model) - Loss: 1.3117 - Accuracy: 0.4493 - F1: 0.4656
sub_26:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.3768 - F1: 0.3914
sub_26:Test (Best Model) - Loss: 1.2909 - Accuracy: 0.3529 - F1: 0.3560
sub_26:Test (Best Model) - Loss: 1.2587 - Accuracy: 0.4265 - F1: 0.4382
sub_26:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3971 - F1: 0.3919
sub_26:Test (Best Model) - Loss: 1.2650 - Accuracy: 0.4118 - F1: 0.4231
sub_26:Test (Best Model) - Loss: 1.3519 - Accuracy: 0.3824 - F1: 0.3729
sub_26:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.5294 - F1: 0.5565
sub_26:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.4412 - F1: 0.4593
sub_26:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.3824 - F1: 0.3759
sub_26:Test (Best Model) - Loss: 1.2325 - Accuracy: 0.5147 - F1: 0.5427
sub_26:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4118 - F1: 0.4361
sub_27:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.2899 - F1: 0.2812
sub_27:Test (Best Model) - Loss: 1.2953 - Accuracy: 0.4638 - F1: 0.4421
sub_27:Test (Best Model) - Loss: 1.3258 - Accuracy: 0.3043 - F1: 0.2588
sub_27:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.3333 - F1: 0.2860
sub_27:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.3333 - F1: 0.3314
sub_27:Test (Best Model) - Loss: 1.3880 - Accuracy: 0.2899 - F1: 0.2647
sub_27:Test (Best Model) - Loss: 1.3664 - Accuracy: 0.2899 - F1: 0.2578
sub_27:Test (Best Model) - Loss: 1.3532 - Accuracy: 0.4638 - F1: 0.4013
sub_27:Test (Best Model) - Loss: 1.3950 - Accuracy: 0.3188 - F1: 0.2453
sub_27:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4203 - F1: 0.3436
sub_27:Test (Best Model) - Loss: 1.2646 - Accuracy: 0.3971 - F1: 0.3758
sub_27:Test (Best Model) - Loss: 1.2816 - Accuracy: 0.3529 - F1: 0.3343
sub_27:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.3235 - F1: 0.2949
sub_27:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.3971 - F1: 0.3888
sub_27:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.3235 - F1: 0.2956
sub_28:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3382 - F1: 0.3443
sub_28:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.3088 - F1: 0.2659
sub_28:Test (Best Model) - Loss: 1.3614 - Accuracy: 0.3088 - F1: 0.2728
sub_28:Test (Best Model) - Loss: 1.4093 - Accuracy: 0.2059 - F1: 0.1843
sub_28:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.2059 - F1: 0.2170
sub_28:Test (Best Model) - Loss: 1.4296 - Accuracy: 0.1912 - F1: 0.1068
sub_28:Test (Best Model) - Loss: 1.3891 - Accuracy: 0.3529 - F1: 0.3267
sub_28:Test (Best Model) - Loss: 1.4400 - Accuracy: 0.2941 - F1: 0.2373
sub_28:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.2500 - F1: 0.2090
sub_28:Test (Best Model) - Loss: 1.4426 - Accuracy: 0.1765 - F1: 0.0926
sub_28:Test (Best Model) - Loss: 1.3602 - Accuracy: 0.2941 - F1: 0.2741
sub_28:Test (Best Model) - Loss: 1.3350 - Accuracy: 0.3088 - F1: 0.2513
sub_28:Test (Best Model) - Loss: 1.3504 - Accuracy: 0.4559 - F1: 0.4482
sub_28:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3088 - F1: 0.2904
sub_28:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.2500 - F1: 0.2312
sub_29:Test (Best Model) - Loss: 1.2429 - Accuracy: 0.4412 - F1: 0.4525
sub_29:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.4118 - F1: 0.4343
sub_29:Test (Best Model) - Loss: 1.1520 - Accuracy: 0.4853 - F1: 0.5034
sub_29:Test (Best Model) - Loss: 1.1784 - Accuracy: 0.4706 - F1: 0.5022
sub_29:Test (Best Model) - Loss: 1.2121 - Accuracy: 0.4412 - F1: 0.4699
sub_29:Test (Best Model) - Loss: 1.1866 - Accuracy: 0.4118 - F1: 0.4409
sub_29:Test (Best Model) - Loss: 1.1885 - Accuracy: 0.4412 - F1: 0.4597
sub_29:Test (Best Model) - Loss: 1.1731 - Accuracy: 0.4412 - F1: 0.4595
sub_29:Test (Best Model) - Loss: 1.1216 - Accuracy: 0.5294 - F1: 0.5474
sub_29:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.5147 - F1: 0.5469
sub_29:Test (Best Model) - Loss: 1.1313 - Accuracy: 0.4928 - F1: 0.5042
sub_29:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.4203 - F1: 0.4412
sub_29:Test (Best Model) - Loss: 1.2703 - Accuracy: 0.4348 - F1: 0.4471
sub_29:Test (Best Model) - Loss: 1.1719 - Accuracy: 0.5362 - F1: 0.5548
sub_29:Test (Best Model) - Loss: 1.1724 - Accuracy: 0.4783 - F1: 0.5040

=== Summary Results ===

acc: 35.85 ± 5.86
F1: 35.06 ± 6.39
acc-in: 41.81 ± 5.20
F1-in: 40.30 ± 5.77
