lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.3510 - Accuracy: 0.3824 - F1: 0.3838
sub_1:Test (Best Model) - Loss: 1.3258 - Accuracy: 0.3676 - F1: 0.4026
sub_1:Test (Best Model) - Loss: 1.3343 - Accuracy: 0.3971 - F1: 0.4028
sub_1:Test (Best Model) - Loss: 1.3059 - Accuracy: 0.3971 - F1: 0.4260
sub_1:Test (Best Model) - Loss: 1.3084 - Accuracy: 0.3529 - F1: 0.3861
sub_1:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.3478 - F1: 0.3594
sub_1:Test (Best Model) - Loss: 1.3046 - Accuracy: 0.2754 - F1: 0.2936
sub_1:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.2899 - F1: 0.3101
sub_1:Test (Best Model) - Loss: 1.2717 - Accuracy: 0.4783 - F1: 0.4676
sub_1:Test (Best Model) - Loss: 1.3326 - Accuracy: 0.3478 - F1: 0.3548
sub_1:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.3824 - F1: 0.3709
sub_1:Test (Best Model) - Loss: 1.2855 - Accuracy: 0.4412 - F1: 0.4514
sub_1:Test (Best Model) - Loss: 1.2827 - Accuracy: 0.4412 - F1: 0.4442
sub_1:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.4265 - F1: 0.4275
sub_1:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.3235 - F1: 0.2950
sub_2:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2609 - F1: 0.2583
sub_2:Test (Best Model) - Loss: 1.4076 - Accuracy: 0.1884 - F1: 0.2009
sub_2:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.2029 - F1: 0.2013
sub_2:Test (Best Model) - Loss: 1.4022 - Accuracy: 0.2319 - F1: 0.2394
sub_2:Test (Best Model) - Loss: 1.3951 - Accuracy: 0.2464 - F1: 0.2522
sub_2:Test (Best Model) - Loss: 1.4027 - Accuracy: 0.2059 - F1: 0.1837
sub_2:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.3088 - F1: 0.3301
sub_2:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2794 - F1: 0.2523
sub_2:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.3088 - F1: 0.3227
sub_2:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.2941 - F1: 0.3005
sub_2:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.2319 - F1: 0.2307
sub_2:Test (Best Model) - Loss: 1.4323 - Accuracy: 0.2464 - F1: 0.2514
sub_2:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3913 - F1: 0.3969
sub_2:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.3043 - F1: 0.2914
sub_2:Test (Best Model) - Loss: 1.4104 - Accuracy: 0.2319 - F1: 0.2236
sub_3:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2500 - F1: 0.2123
sub_3:Test (Best Model) - Loss: 1.3790 - Accuracy: 0.2500 - F1: 0.2225
sub_3:Test (Best Model) - Loss: 1.3976 - Accuracy: 0.2059 - F1: 0.2020
sub_3:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.2794 - F1: 0.2772
sub_3:Test (Best Model) - Loss: 1.4189 - Accuracy: 0.2500 - F1: 0.2495
sub_3:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.3043 - F1: 0.2885
sub_3:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.2609 - F1: 0.2560
sub_3:Test (Best Model) - Loss: 1.3799 - Accuracy: 0.2464 - F1: 0.2387
sub_3:Test (Best Model) - Loss: 1.3610 - Accuracy: 0.3913 - F1: 0.3855
sub_3:Test (Best Model) - Loss: 1.3701 - Accuracy: 0.2899 - F1: 0.2672
sub_3:Test (Best Model) - Loss: 1.3823 - Accuracy: 0.2319 - F1: 0.2056
sub_3:Test (Best Model) - Loss: 1.4026 - Accuracy: 0.2174 - F1: 0.1941
sub_3:Test (Best Model) - Loss: 1.3372 - Accuracy: 0.3478 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.3333 - F1: 0.2969
sub_3:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2754 - F1: 0.2458
sub_4:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.3913 - F1: 0.4098
sub_4:Test (Best Model) - Loss: 1.2631 - Accuracy: 0.3913 - F1: 0.4144
sub_4:Test (Best Model) - Loss: 1.2161 - Accuracy: 0.4348 - F1: 0.4672
sub_4:Test (Best Model) - Loss: 1.1952 - Accuracy: 0.4783 - F1: 0.5124
sub_4:Test (Best Model) - Loss: 1.2873 - Accuracy: 0.4058 - F1: 0.4287
sub_4:Test (Best Model) - Loss: 1.2100 - Accuracy: 0.4638 - F1: 0.4790
sub_4:Test (Best Model) - Loss: 1.2487 - Accuracy: 0.3768 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 1.1552 - Accuracy: 0.5507 - F1: 0.5577
sub_4:Test (Best Model) - Loss: 1.2082 - Accuracy: 0.5362 - F1: 0.5445
sub_4:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.3478 - F1: 0.3658
sub_4:Test (Best Model) - Loss: 1.2438 - Accuracy: 0.3623 - F1: 0.3254
sub_4:Test (Best Model) - Loss: 1.2283 - Accuracy: 0.3913 - F1: 0.3803
sub_4:Test (Best Model) - Loss: 1.1803 - Accuracy: 0.4348 - F1: 0.4493
sub_4:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.3913 - F1: 0.3727
sub_4:Test (Best Model) - Loss: 1.2064 - Accuracy: 0.4638 - F1: 0.4530
sub_5:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.5147 - F1: 0.4858
sub_5:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.4559 - F1: 0.4244
sub_5:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.3971 - F1: 0.3654
sub_5:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.4559 - F1: 0.4330
sub_5:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.4412 - F1: 0.4100
sub_5:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.3676 - F1: 0.3537
sub_5:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.3824 - F1: 0.3985
sub_5:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.4559 - F1: 0.4352
sub_5:Test (Best Model) - Loss: 1.2075 - Accuracy: 0.4853 - F1: 0.4605
sub_5:Test (Best Model) - Loss: 1.2396 - Accuracy: 0.4118 - F1: 0.3798
sub_5:Test (Best Model) - Loss: 1.2410 - Accuracy: 0.3971 - F1: 0.3894
sub_5:Test (Best Model) - Loss: 1.2524 - Accuracy: 0.3235 - F1: 0.3030
sub_5:Test (Best Model) - Loss: 1.2664 - Accuracy: 0.4118 - F1: 0.4041
sub_5:Test (Best Model) - Loss: 1.2481 - Accuracy: 0.4265 - F1: 0.4179
sub_5:Test (Best Model) - Loss: 1.2150 - Accuracy: 0.4118 - F1: 0.3962
sub_6:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.3676 - F1: 0.3761
sub_6:Test (Best Model) - Loss: 1.3281 - Accuracy: 0.3971 - F1: 0.3856
sub_6:Test (Best Model) - Loss: 1.2956 - Accuracy: 0.4706 - F1: 0.4530
sub_6:Test (Best Model) - Loss: 1.3285 - Accuracy: 0.3676 - F1: 0.3625
sub_6:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.4118 - F1: 0.3678
sub_6:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3478 - F1: 0.3078
sub_6:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.2899 - F1: 0.2684
sub_6:Test (Best Model) - Loss: 1.2787 - Accuracy: 0.4058 - F1: 0.3751
sub_6:Test (Best Model) - Loss: 1.3470 - Accuracy: 0.3333 - F1: 0.3357
sub_6:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.4203 - F1: 0.3979
sub_6:Test (Best Model) - Loss: 1.3504 - Accuracy: 0.2899 - F1: 0.2902
sub_6:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2754 - F1: 0.2605
sub_6:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3478 - F1: 0.3488
sub_6:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.3913 - F1: 0.4102
sub_6:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3913 - F1: 0.4069
sub_7:Test (Best Model) - Loss: 1.1910 - Accuracy: 0.4706 - F1: 0.4384
sub_7:Test (Best Model) - Loss: 1.3043 - Accuracy: 0.4118 - F1: 0.3817
sub_7:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.3676 - F1: 0.3486
sub_7:Test (Best Model) - Loss: 1.2314 - Accuracy: 0.5735 - F1: 0.5543
sub_7:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.4706 - F1: 0.4369
sub_7:Test (Best Model) - Loss: 1.3139 - Accuracy: 0.3824 - F1: 0.3685
sub_7:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3529 - F1: 0.3422
sub_7:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.3824 - F1: 0.3649
sub_7:Test (Best Model) - Loss: 1.2956 - Accuracy: 0.3824 - F1: 0.3905
sub_7:Test (Best Model) - Loss: 1.1946 - Accuracy: 0.5147 - F1: 0.5175
sub_7:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.3676 - F1: 0.3477
sub_7:Test (Best Model) - Loss: 1.2842 - Accuracy: 0.4265 - F1: 0.4001
sub_7:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.5588 - F1: 0.5599
sub_7:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.4559 - F1: 0.4484
sub_7:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.4559 - F1: 0.4563
sub_8:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3235 - F1: 0.3108
sub_8:Test (Best Model) - Loss: 1.3898 - Accuracy: 0.3088 - F1: 0.3072
sub_8:Test (Best Model) - Loss: 1.3927 - Accuracy: 0.2794 - F1: 0.2928
sub_8:Test (Best Model) - Loss: 1.3969 - Accuracy: 0.3235 - F1: 0.3212
sub_8:Test (Best Model) - Loss: 1.4034 - Accuracy: 0.2353 - F1: 0.2405
sub_8:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.2647 - F1: 0.2609
sub_8:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.3529 - F1: 0.3581
sub_8:Test (Best Model) - Loss: 1.3517 - Accuracy: 0.3382 - F1: 0.3414
sub_8:Test (Best Model) - Loss: 1.3772 - Accuracy: 0.3235 - F1: 0.3324
sub_8:Test (Best Model) - Loss: 1.3794 - Accuracy: 0.3235 - F1: 0.3350
sub_8:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.2500 - F1: 0.2309
sub_8:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.3382 - F1: 0.3347
sub_8:Test (Best Model) - Loss: 1.4450 - Accuracy: 0.2794 - F1: 0.2822
sub_8:Test (Best Model) - Loss: 1.3902 - Accuracy: 0.3235 - F1: 0.3229
sub_8:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.2941 - F1: 0.2856
sub_9:Test (Best Model) - Loss: 1.2547 - Accuracy: 0.4706 - F1: 0.4721
sub_9:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.4118 - F1: 0.4373
sub_9:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.3971 - F1: 0.4210
sub_9:Test (Best Model) - Loss: 1.2227 - Accuracy: 0.4412 - F1: 0.4670
sub_9:Test (Best Model) - Loss: 1.2970 - Accuracy: 0.3824 - F1: 0.4133
sub_9:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.3676 - F1: 0.3971
sub_9:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.3529 - F1: 0.3721
sub_9:Test (Best Model) - Loss: 1.3288 - Accuracy: 0.3824 - F1: 0.4008
sub_9:Test (Best Model) - Loss: 1.2445 - Accuracy: 0.4412 - F1: 0.4477
sub_9:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.2941 - F1: 0.3202
sub_9:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.3088 - F1: 0.2938
sub_9:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.4265 - F1: 0.4227
sub_9:Test (Best Model) - Loss: 1.2830 - Accuracy: 0.3676 - F1: 0.3721
sub_9:Test (Best Model) - Loss: 1.3122 - Accuracy: 0.3971 - F1: 0.3892
sub_9:Test (Best Model) - Loss: 1.3298 - Accuracy: 0.3382 - F1: 0.3340
sub_10:Test (Best Model) - Loss: 1.4034 - Accuracy: 0.2206 - F1: 0.2005
sub_10:Test (Best Model) - Loss: 1.4056 - Accuracy: 0.2794 - F1: 0.2878
sub_10:Test (Best Model) - Loss: 1.3997 - Accuracy: 0.2500 - F1: 0.2514
sub_10:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.1765 - F1: 0.1710
sub_10:Test (Best Model) - Loss: 1.3720 - Accuracy: 0.2500 - F1: 0.2405
sub_10:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2941 - F1: 0.2998
sub_10:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.1618 - F1: 0.1546
sub_10:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.3088 - F1: 0.3010
sub_10:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2353 - F1: 0.2235
sub_10:Test (Best Model) - Loss: 1.3766 - Accuracy: 0.3088 - F1: 0.2872
sub_10:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.2029 - F1: 0.2114
sub_10:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2899 - F1: 0.2931
sub_10:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.2899 - F1: 0.2712
sub_10:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.3043 - F1: 0.3152
sub_10:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.2464 - F1: 0.2420
sub_11:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.3913 - F1: 0.3362
sub_11:Test (Best Model) - Loss: 1.3378 - Accuracy: 0.3478 - F1: 0.3215
sub_11:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2464 - F1: 0.2196
sub_11:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.3043 - F1: 0.2780
sub_11:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.3623 - F1: 0.3422
sub_11:Test (Best Model) - Loss: 1.3118 - Accuracy: 0.3913 - F1: 0.4017
sub_11:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.3478 - F1: 0.3404
sub_11:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.4348 - F1: 0.4182
sub_11:Test (Best Model) - Loss: 1.3523 - Accuracy: 0.3623 - F1: 0.3110
sub_11:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.4058 - F1: 0.3768
sub_11:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.3478 - F1: 0.3049
sub_11:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.3913 - F1: 0.3661
sub_11:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.3768 - F1: 0.3537
sub_11:Test (Best Model) - Loss: 1.3080 - Accuracy: 0.4058 - F1: 0.3943
sub_11:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3333 - F1: 0.3091
sub_12:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.2794 - F1: 0.2559
sub_12:Test (Best Model) - Loss: 1.2869 - Accuracy: 0.4118 - F1: 0.4349
sub_12:Test (Best Model) - Loss: 1.2262 - Accuracy: 0.4853 - F1: 0.4861
sub_12:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.5588 - F1: 0.5538
sub_12:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.5000 - F1: 0.5095
sub_12:Test (Best Model) - Loss: 1.2764 - Accuracy: 0.4638 - F1: 0.4762
sub_12:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3478 - F1: 0.3489
sub_12:Test (Best Model) - Loss: 1.2551 - Accuracy: 0.4493 - F1: 0.4480
sub_12:Test (Best Model) - Loss: 1.2982 - Accuracy: 0.3478 - F1: 0.3445
sub_12:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.4928 - F1: 0.5156
sub_12:Test (Best Model) - Loss: 1.2694 - Accuracy: 0.4412 - F1: 0.4029
sub_12:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.3382 - F1: 0.2831
sub_12:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.3529 - F1: 0.3685
sub_12:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.4265 - F1: 0.4418
sub_12:Test (Best Model) - Loss: 1.2502 - Accuracy: 0.5147 - F1: 0.5250
sub_13:Test (Best Model) - Loss: 1.3640 - Accuracy: 0.2794 - F1: 0.2998
sub_13:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.2206 - F1: 0.1997
sub_13:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.2353 - F1: 0.2304
sub_13:Test (Best Model) - Loss: 1.3162 - Accuracy: 0.3235 - F1: 0.3337
sub_13:Test (Best Model) - Loss: 1.3786 - Accuracy: 0.2794 - F1: 0.2827
sub_13:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.2609 - F1: 0.2463
sub_13:Test (Best Model) - Loss: 1.3459 - Accuracy: 0.3188 - F1: 0.3105
sub_13:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.2754 - F1: 0.2644
sub_13:Test (Best Model) - Loss: 1.3596 - Accuracy: 0.2899 - F1: 0.2990
sub_13:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.3043 - F1: 0.3010
sub_13:Test (Best Model) - Loss: 1.3791 - Accuracy: 0.2794 - F1: 0.2686
sub_13:Test (Best Model) - Loss: 1.3921 - Accuracy: 0.2941 - F1: 0.2943
sub_13:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.2794 - F1: 0.2866
sub_13:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.2647 - F1: 0.2429
sub_13:Test (Best Model) - Loss: 1.4114 - Accuracy: 0.2059 - F1: 0.2117
sub_14:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.3382 - F1: 0.2917
sub_14:Test (Best Model) - Loss: 1.3319 - Accuracy: 0.2941 - F1: 0.2816
sub_14:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3235 - F1: 0.2725
sub_14:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.2941 - F1: 0.3336
sub_14:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.2941 - F1: 0.2913
sub_14:Test (Best Model) - Loss: 1.3111 - Accuracy: 0.3235 - F1: 0.2555
sub_14:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.3971 - F1: 0.3613
sub_14:Test (Best Model) - Loss: 1.3127 - Accuracy: 0.3088 - F1: 0.2714
sub_14:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.4118 - F1: 0.3966
sub_14:Test (Best Model) - Loss: 1.2994 - Accuracy: 0.3088 - F1: 0.2811
sub_14:Test (Best Model) - Loss: 1.3621 - Accuracy: 0.2500 - F1: 0.2613
sub_14:Test (Best Model) - Loss: 1.3041 - Accuracy: 0.3676 - F1: 0.3179
sub_14:Test (Best Model) - Loss: 1.3437 - Accuracy: 0.2794 - F1: 0.2695
sub_14:Test (Best Model) - Loss: 1.3431 - Accuracy: 0.3529 - F1: 0.3020
sub_14:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.2941 - F1: 0.2732
sub_15:Test (Best Model) - Loss: 1.2670 - Accuracy: 0.3676 - F1: 0.4008
sub_15:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3529 - F1: 0.3411
sub_15:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.3529 - F1: 0.3902
sub_15:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.3235 - F1: 0.3326
sub_15:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.3824 - F1: 0.4094
sub_15:Test (Best Model) - Loss: 1.2479 - Accuracy: 0.4265 - F1: 0.4101
sub_15:Test (Best Model) - Loss: 1.3160 - Accuracy: 0.3529 - F1: 0.3281
sub_15:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.4265 - F1: 0.4211
sub_15:Test (Best Model) - Loss: 1.2531 - Accuracy: 0.5000 - F1: 0.4918
sub_15:Test (Best Model) - Loss: 1.2460 - Accuracy: 0.4559 - F1: 0.4502
sub_15:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.4412 - F1: 0.4510
sub_15:Test (Best Model) - Loss: 1.2847 - Accuracy: 0.3971 - F1: 0.4034
sub_15:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.4412 - F1: 0.4288
sub_15:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4412 - F1: 0.4160
sub_15:Test (Best Model) - Loss: 1.2858 - Accuracy: 0.4118 - F1: 0.3837
sub_16:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.3529 - F1: 0.3130
sub_16:Test (Best Model) - Loss: 1.3199 - Accuracy: 0.4118 - F1: 0.4016
sub_16:Test (Best Model) - Loss: 1.2619 - Accuracy: 0.4412 - F1: 0.4155
sub_16:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.4118 - F1: 0.4101
sub_16:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.3529 - F1: 0.2898
sub_16:Test (Best Model) - Loss: 1.2988 - Accuracy: 0.3824 - F1: 0.3547
sub_16:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3824 - F1: 0.3785
sub_16:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3676 - F1: 0.3632
sub_16:Test (Best Model) - Loss: 1.3328 - Accuracy: 0.3088 - F1: 0.2690
sub_16:Test (Best Model) - Loss: 1.4281 - Accuracy: 0.2794 - F1: 0.2508
sub_16:Test (Best Model) - Loss: 1.2933 - Accuracy: 0.4412 - F1: 0.3840
sub_16:Test (Best Model) - Loss: 1.3020 - Accuracy: 0.4559 - F1: 0.4045
sub_16:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.4706 - F1: 0.4548
sub_16:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.4118 - F1: 0.3886
sub_16:Test (Best Model) - Loss: 1.3051 - Accuracy: 0.4559 - F1: 0.4055
sub_17:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.2899 - F1: 0.2368
sub_17:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3333 - F1: 0.2650
sub_17:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3333 - F1: 0.3209
sub_17:Test (Best Model) - Loss: 1.3267 - Accuracy: 0.3333 - F1: 0.2908
sub_17:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.3623 - F1: 0.3029
sub_17:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3623 - F1: 0.3434
sub_17:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3188 - F1: 0.2437
sub_17:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3043 - F1: 0.2641
sub_17:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3478 - F1: 0.3031
sub_17:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3478 - F1: 0.3058
sub_17:Test (Best Model) - Loss: 1.3077 - Accuracy: 0.3382 - F1: 0.2992
sub_17:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.4118 - F1: 0.3812
sub_17:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.3529 - F1: 0.3446
sub_17:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.3676 - F1: 0.3653
sub_17:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.3529 - F1: 0.3323
sub_18:Test (Best Model) - Loss: 1.2860 - Accuracy: 0.4783 - F1: 0.4808
sub_18:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.3913 - F1: 0.4241
sub_18:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.4783 - F1: 0.4549
sub_18:Test (Best Model) - Loss: 1.3093 - Accuracy: 0.3768 - F1: 0.3773
sub_18:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.3913 - F1: 0.3813
sub_18:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.3824 - F1: 0.3975
sub_18:Test (Best Model) - Loss: 1.3577 - Accuracy: 0.3088 - F1: 0.3340
sub_18:Test (Best Model) - Loss: 1.3590 - Accuracy: 0.2647 - F1: 0.2739
sub_18:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.2206 - F1: 0.2312
sub_18:Test (Best Model) - Loss: 1.3050 - Accuracy: 0.3824 - F1: 0.4206
sub_18:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3235 - F1: 0.3430
sub_18:Test (Best Model) - Loss: 1.3378 - Accuracy: 0.3676 - F1: 0.3739
sub_18:Test (Best Model) - Loss: 1.3157 - Accuracy: 0.4265 - F1: 0.4306
sub_18:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.3676 - F1: 0.3353
sub_18:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.3088 - F1: 0.3124
sub_19:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.2794 - F1: 0.2434
sub_19:Test (Best Model) - Loss: 1.3992 - Accuracy: 0.2941 - F1: 0.2596
sub_19:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.2794 - F1: 0.2512
sub_19:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.2500 - F1: 0.2721
sub_19:Test (Best Model) - Loss: 1.4066 - Accuracy: 0.2794 - F1: 0.2378
sub_19:Test (Best Model) - Loss: 1.3059 - Accuracy: 0.4706 - F1: 0.4798
sub_19:Test (Best Model) - Loss: 1.3198 - Accuracy: 0.3382 - F1: 0.2980
sub_19:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.4559 - F1: 0.4429
sub_19:Test (Best Model) - Loss: 1.2758 - Accuracy: 0.4559 - F1: 0.4378
sub_19:Test (Best Model) - Loss: 1.2901 - Accuracy: 0.4118 - F1: 0.3795
sub_19:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.2941 - F1: 0.2914
sub_19:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.2941 - F1: 0.2725
sub_19:Test (Best Model) - Loss: 1.2696 - Accuracy: 0.3676 - F1: 0.3460
sub_19:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.3382 - F1: 0.3307
sub_19:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.3088 - F1: 0.3005
sub_20:Test (Best Model) - Loss: 1.3138 - Accuracy: 0.3382 - F1: 0.2928
sub_20:Test (Best Model) - Loss: 1.2094 - Accuracy: 0.4853 - F1: 0.5054
sub_20:Test (Best Model) - Loss: 1.1793 - Accuracy: 0.4853 - F1: 0.5084
sub_20:Test (Best Model) - Loss: 1.2506 - Accuracy: 0.4412 - F1: 0.4417
sub_20:Test (Best Model) - Loss: 1.2866 - Accuracy: 0.3971 - F1: 0.4015
sub_20:Test (Best Model) - Loss: 1.2667 - Accuracy: 0.4118 - F1: 0.4179
sub_20:Test (Best Model) - Loss: 1.2875 - Accuracy: 0.3824 - F1: 0.3782
sub_20:Test (Best Model) - Loss: 1.2552 - Accuracy: 0.4412 - F1: 0.4490
sub_20:Test (Best Model) - Loss: 1.2868 - Accuracy: 0.3529 - F1: 0.3632
sub_20:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.3529 - F1: 0.3582
sub_20:Test (Best Model) - Loss: 1.2595 - Accuracy: 0.4493 - F1: 0.4588
sub_20:Test (Best Model) - Loss: 1.2436 - Accuracy: 0.4058 - F1: 0.4081
sub_20:Test (Best Model) - Loss: 1.3187 - Accuracy: 0.3768 - F1: 0.3691
sub_20:Test (Best Model) - Loss: 1.2513 - Accuracy: 0.4638 - F1: 0.4467
sub_20:Test (Best Model) - Loss: 1.2699 - Accuracy: 0.4203 - F1: 0.3971
sub_21:Test (Best Model) - Loss: 1.2890 - Accuracy: 0.2647 - F1: 0.2172
sub_21:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.3088 - F1: 0.2453
sub_21:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.2794 - F1: 0.2383
sub_21:Test (Best Model) - Loss: 1.3399 - Accuracy: 0.3676 - F1: 0.3401
sub_21:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.2794 - F1: 0.2396
sub_21:Test (Best Model) - Loss: 1.2867 - Accuracy: 0.3382 - F1: 0.2844
sub_21:Test (Best Model) - Loss: 1.2595 - Accuracy: 0.3235 - F1: 0.3044
sub_21:Test (Best Model) - Loss: 1.2474 - Accuracy: 0.3676 - F1: 0.3376
sub_21:Test (Best Model) - Loss: 1.1994 - Accuracy: 0.4118 - F1: 0.3999
sub_21:Test (Best Model) - Loss: 1.1817 - Accuracy: 0.4853 - F1: 0.4644
sub_21:Test (Best Model) - Loss: 1.2811 - Accuracy: 0.4118 - F1: 0.3799
sub_21:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.3235 - F1: 0.3089
sub_21:Test (Best Model) - Loss: 1.2794 - Accuracy: 0.3382 - F1: 0.3143
sub_21:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.3676 - F1: 0.3767
sub_21:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.3971 - F1: 0.4121
sub_22:Test (Best Model) - Loss: 1.3534 - Accuracy: 0.2794 - F1: 0.2802
sub_22:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.2794 - F1: 0.2863
sub_22:Test (Best Model) - Loss: 1.3133 - Accuracy: 0.4118 - F1: 0.3932
sub_22:Test (Best Model) - Loss: 1.2955 - Accuracy: 0.3676 - F1: 0.3861
sub_22:Test (Best Model) - Loss: 1.4231 - Accuracy: 0.1618 - F1: 0.1330
sub_22:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.2464 - F1: 0.2380
sub_22:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3043 - F1: 0.3317
sub_22:Test (Best Model) - Loss: 1.3349 - Accuracy: 0.3333 - F1: 0.3557
sub_22:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.3188 - F1: 0.3193
sub_22:Test (Best Model) - Loss: 1.3556 - Accuracy: 0.3623 - F1: 0.3558
sub_22:Test (Best Model) - Loss: 1.3548 - Accuracy: 0.2353 - F1: 0.2626
sub_22:Test (Best Model) - Loss: 1.3357 - Accuracy: 0.3676 - F1: 0.3743
sub_22:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.2941 - F1: 0.3100
sub_22:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.4265 - F1: 0.4220
sub_22:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.2500 - F1: 0.2544
sub_23:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.4493 - F1: 0.4547
sub_23:Test (Best Model) - Loss: 1.2071 - Accuracy: 0.3768 - F1: 0.3873
sub_23:Test (Best Model) - Loss: 1.2644 - Accuracy: 0.3913 - F1: 0.3729
sub_23:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.4493 - F1: 0.4704
sub_23:Test (Best Model) - Loss: 1.2679 - Accuracy: 0.3768 - F1: 0.3855
sub_23:Test (Best Model) - Loss: 1.2996 - Accuracy: 0.3824 - F1: 0.3604
sub_23:Test (Best Model) - Loss: 1.2812 - Accuracy: 0.4412 - F1: 0.4518
sub_23:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.4706 - F1: 0.4739
sub_23:Test (Best Model) - Loss: 1.2125 - Accuracy: 0.5000 - F1: 0.5065
sub_23:Test (Best Model) - Loss: 1.2862 - Accuracy: 0.4412 - F1: 0.4487
sub_23:Test (Best Model) - Loss: 1.2500 - Accuracy: 0.3478 - F1: 0.3195
sub_23:Test (Best Model) - Loss: 1.2401 - Accuracy: 0.3768 - F1: 0.3777
sub_23:Test (Best Model) - Loss: 1.2211 - Accuracy: 0.4203 - F1: 0.4094
sub_23:Test (Best Model) - Loss: 1.2377 - Accuracy: 0.4783 - F1: 0.4881
sub_23:Test (Best Model) - Loss: 1.3178 - Accuracy: 0.3333 - F1: 0.3203
sub_24:Test (Best Model) - Loss: 1.3779 - Accuracy: 0.3676 - F1: 0.3442
sub_24:Test (Best Model) - Loss: 1.3801 - Accuracy: 0.2794 - F1: 0.2686
sub_24:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.3235 - F1: 0.3154
sub_24:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2500 - F1: 0.2505
sub_24:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3382 - F1: 0.3427
sub_24:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.2794 - F1: 0.2700
sub_24:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.3382 - F1: 0.3418
sub_24:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.3382 - F1: 0.3233
sub_24:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.3529 - F1: 0.3581
sub_24:Test (Best Model) - Loss: 1.3392 - Accuracy: 0.3382 - F1: 0.3331
sub_24:Test (Best Model) - Loss: 1.4120 - Accuracy: 0.2206 - F1: 0.2063
sub_24:Test (Best Model) - Loss: 1.4289 - Accuracy: 0.2206 - F1: 0.2157
sub_24:Test (Best Model) - Loss: 1.3705 - Accuracy: 0.3088 - F1: 0.3096
sub_24:Test (Best Model) - Loss: 1.4328 - Accuracy: 0.2500 - F1: 0.2487
sub_24:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.3088 - F1: 0.2952
sub_25:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.4348 - F1: 0.3506
sub_25:Test (Best Model) - Loss: 1.3414 - Accuracy: 0.3768 - F1: 0.3503
sub_25:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.4493 - F1: 0.4023
sub_25:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.3333 - F1: 0.2885
sub_25:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.3188 - F1: 0.2318
sub_25:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.3088 - F1: 0.3072
sub_25:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.3676 - F1: 0.3231
sub_25:Test (Best Model) - Loss: 1.2988 - Accuracy: 0.4412 - F1: 0.4260
sub_25:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.4559 - F1: 0.4278
sub_25:Test (Best Model) - Loss: 1.3041 - Accuracy: 0.3382 - F1: 0.3168
sub_25:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.3235 - F1: 0.3123
sub_25:Test (Best Model) - Loss: 1.3086 - Accuracy: 0.4265 - F1: 0.4123
sub_25:Test (Best Model) - Loss: 1.2921 - Accuracy: 0.3676 - F1: 0.3274
sub_25:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.3676 - F1: 0.3474
sub_25:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.3676 - F1: 0.3304
sub_26:Test (Best Model) - Loss: 1.2677 - Accuracy: 0.4058 - F1: 0.4140
sub_26:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.3333 - F1: 0.3340
sub_26:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3478 - F1: 0.3460
sub_26:Test (Best Model) - Loss: 1.2166 - Accuracy: 0.5362 - F1: 0.5443
sub_26:Test (Best Model) - Loss: 1.2622 - Accuracy: 0.4493 - F1: 0.4642
sub_26:Test (Best Model) - Loss: 1.3041 - Accuracy: 0.3529 - F1: 0.3782
sub_26:Test (Best Model) - Loss: 1.2649 - Accuracy: 0.4265 - F1: 0.4470
sub_26:Test (Best Model) - Loss: 1.3364 - Accuracy: 0.3676 - F1: 0.3615
sub_26:Test (Best Model) - Loss: 1.2560 - Accuracy: 0.4706 - F1: 0.4848
sub_26:Test (Best Model) - Loss: 1.2824 - Accuracy: 0.4559 - F1: 0.4738
sub_26:Test (Best Model) - Loss: 1.2625 - Accuracy: 0.4412 - F1: 0.4402
sub_26:Test (Best Model) - Loss: 1.2589 - Accuracy: 0.5000 - F1: 0.5349
sub_26:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.5147 - F1: 0.5263
sub_26:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.5294 - F1: 0.5542
sub_26:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.3824 - F1: 0.4089
sub_27:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.2899 - F1: 0.2368
sub_27:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3333 - F1: 0.2650
sub_27:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3333 - F1: 0.3209
sub_27:Test (Best Model) - Loss: 1.3267 - Accuracy: 0.3333 - F1: 0.2908
sub_27:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.3623 - F1: 0.3029
sub_27:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.3623 - F1: 0.3434
sub_27:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.3188 - F1: 0.2437
sub_27:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.3043 - F1: 0.2641
sub_27:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3478 - F1: 0.3031
sub_27:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3478 - F1: 0.3058
sub_27:Test (Best Model) - Loss: 1.3077 - Accuracy: 0.3382 - F1: 0.2992
sub_27:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.4118 - F1: 0.3812
sub_27:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.3529 - F1: 0.3446
sub_27:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.3676 - F1: 0.3653
sub_27:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.3529 - F1: 0.3323
sub_28:Test (Best Model) - Loss: 1.3654 - Accuracy: 0.2941 - F1: 0.2627
sub_28:Test (Best Model) - Loss: 1.3796 - Accuracy: 0.2500 - F1: 0.2064
sub_28:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.2794 - F1: 0.2293
sub_28:Test (Best Model) - Loss: 1.4131 - Accuracy: 0.1912 - F1: 0.2025
sub_28:Test (Best Model) - Loss: 1.4270 - Accuracy: 0.1765 - F1: 0.1507
sub_28:Test (Best Model) - Loss: 1.4188 - Accuracy: 0.2794 - F1: 0.2329
sub_28:Test (Best Model) - Loss: 1.4344 - Accuracy: 0.2353 - F1: 0.1617
sub_28:Test (Best Model) - Loss: 1.4362 - Accuracy: 0.2353 - F1: 0.1988
sub_28:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3235 - F1: 0.3043
sub_28:Test (Best Model) - Loss: 1.4276 - Accuracy: 0.2647 - F1: 0.2338
sub_28:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2059 - F1: 0.1799
sub_28:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3971 - F1: 0.3334
sub_28:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.3676 - F1: 0.3500
sub_28:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3824 - F1: 0.3813
sub_28:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.3529 - F1: 0.3072
sub_29:Test (Best Model) - Loss: 1.1951 - Accuracy: 0.4118 - F1: 0.4393
sub_29:Test (Best Model) - Loss: 1.2126 - Accuracy: 0.5000 - F1: 0.5208
sub_29:Test (Best Model) - Loss: 1.2000 - Accuracy: 0.4265 - F1: 0.4531
sub_29:Test (Best Model) - Loss: 1.1731 - Accuracy: 0.5000 - F1: 0.5309
sub_29:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.5147 - F1: 0.5417
sub_29:Test (Best Model) - Loss: 1.1318 - Accuracy: 0.5294 - F1: 0.5413
sub_29:Test (Best Model) - Loss: 1.1612 - Accuracy: 0.4853 - F1: 0.4962
sub_29:Test (Best Model) - Loss: 1.1915 - Accuracy: 0.4412 - F1: 0.4589
sub_29:Test (Best Model) - Loss: 1.0621 - Accuracy: 0.5735 - F1: 0.5891
sub_29:Test (Best Model) - Loss: 1.0851 - Accuracy: 0.5000 - F1: 0.5301
sub_29:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.5507 - F1: 0.5551
sub_29:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.4493 - F1: 0.4602
sub_29:Test (Best Model) - Loss: 1.1594 - Accuracy: 0.4493 - F1: 0.4619
sub_29:Test (Best Model) - Loss: 1.2079 - Accuracy: 0.5652 - F1: 0.5776
sub_29:Test (Best Model) - Loss: 1.1932 - Accuracy: 0.4493 - F1: 0.4597

=== Summary Results ===

acc: 36.10 ± 6.01
F1: 35.16 ± 6.65
acc-in: 42.53 ± 5.55
F1-in: 40.83 ± 5.80
