lr: 1e-05
sub_19:Test (Best Model) - Loss: 1.3220 - Accuracy: 0.4118 - F1: 0.3881
sub_12:Test (Best Model) - Loss: 1.3625 - Accuracy: 0.3382 - F1: 0.3129
sub_28:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.2941 - F1: 0.2241
sub_7:Test (Best Model) - Loss: 1.3654 - Accuracy: 0.1765 - F1: 0.2231
sub_18:Test (Best Model) - Loss: 1.3329 - Accuracy: 0.3768 - F1: 0.3800
sub_10:Test (Best Model) - Loss: 1.3409 - Accuracy: 0.4706 - F1: 0.4360
sub_22:Test (Best Model) - Loss: 1.3171 - Accuracy: 0.5000 - F1: 0.5047
sub_29:Test (Best Model) - Loss: 1.3471 - Accuracy: 0.3235 - F1: 0.3140
sub_21:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.3382 - F1: 0.2874
sub_6:Test (Best Model) - Loss: 1.3667 - Accuracy: 0.2941 - F1: 0.2357
sub_26:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.4203 - F1: 0.4394
sub_20:Test (Best Model) - Loss: 1.2558 - Accuracy: 0.6176 - F1: 0.6067
sub_1:Test (Best Model) - Loss: 1.2855 - Accuracy: 0.6618 - F1: 0.6774
sub_3:Test (Best Model) - Loss: 1.2860 - Accuracy: 0.5588 - F1: 0.5418
sub_16:Test (Best Model) - Loss: 1.2342 - Accuracy: 0.7059 - F1: 0.7045
sub_17:Test (Best Model) - Loss: 1.2781 - Accuracy: 0.5797 - F1: 0.5298
sub_14:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.4265 - F1: 0.3400
sub_24:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.5588 - F1: 0.5110
sub_5:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.6618 - F1: 0.6049
sub_27:Test (Best Model) - Loss: 1.2781 - Accuracy: 0.5797 - F1: 0.5298
sub_28:Test (Best Model) - Loss: 1.2934 - Accuracy: 0.6618 - F1: 0.6397
sub_8:Test (Best Model) - Loss: 1.3114 - Accuracy: 0.4265 - F1: 0.4170
sub_22:Test (Best Model) - Loss: 1.3948 - Accuracy: 0.3382 - F1: 0.2344
sub_23:Test (Best Model) - Loss: 1.2166 - Accuracy: 0.6812 - F1: 0.6272
sub_9:Test (Best Model) - Loss: 1.2216 - Accuracy: 0.6176 - F1: 0.6395
sub_19:Test (Best Model) - Loss: 1.3379 - Accuracy: 0.3235 - F1: 0.2506
sub_13:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.4265 - F1: 0.4029
sub_2:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.7246 - F1: 0.7117
sub_26:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2464 - F1: 0.1996
sub_18:Test (Best Model) - Loss: 1.3030 - Accuracy: 0.6087 - F1: 0.6000
sub_4:Test (Best Model) - Loss: 1.2276 - Accuracy: 0.5942 - F1: 0.5939
sub_21:Test (Best Model) - Loss: 1.3324 - Accuracy: 0.3971 - F1: 0.3120
sub_11:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.4203 - F1: 0.3807
sub_25:Test (Best Model) - Loss: 1.1757 - Accuracy: 0.8116 - F1: 0.8058
sub_10:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.3382 - F1: 0.3333
sub_15:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.5735 - F1: 0.5958
sub_12:Test (Best Model) - Loss: 1.2380 - Accuracy: 0.6029 - F1: 0.6007
sub_7:Test (Best Model) - Loss: 1.2193 - Accuracy: 0.6471 - F1: 0.5721
sub_14:Test (Best Model) - Loss: 1.3127 - Accuracy: 0.3971 - F1: 0.3382
sub_29:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.5588 - F1: 0.5088
sub_6:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.4706 - F1: 0.4224
sub_20:Test (Best Model) - Loss: 1.2511 - Accuracy: 0.5588 - F1: 0.5539
sub_16:Test (Best Model) - Loss: 1.2779 - Accuracy: 0.6618 - F1: 0.6033
sub_24:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.5882 - F1: 0.5525
sub_11:Test (Best Model) - Loss: 1.2621 - Accuracy: 0.6667 - F1: 0.5913
sub_26:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.5652 - F1: 0.5636
sub_2:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.3333 - F1: 0.3326
sub_3:Test (Best Model) - Loss: 1.2878 - Accuracy: 0.6029 - F1: 0.5431
sub_9:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.5000 - F1: 0.4934
sub_5:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.6765 - F1: 0.6082
sub_28:Test (Best Model) - Loss: 1.3261 - Accuracy: 0.5000 - F1: 0.4744
sub_25:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.5797 - F1: 0.5616
sub_23:Test (Best Model) - Loss: 1.2785 - Accuracy: 0.6087 - F1: 0.5625
sub_17:Test (Best Model) - Loss: 1.2602 - Accuracy: 0.6522 - F1: 0.5658
sub_19:Test (Best Model) - Loss: 1.3564 - Accuracy: 0.2206 - F1: 0.2537
sub_8:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.3971 - F1: 0.3269
sub_13:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.6471 - F1: 0.6615
sub_21:Test (Best Model) - Loss: 1.2737 - Accuracy: 0.6618 - F1: 0.6774
sub_18:Test (Best Model) - Loss: 1.2699 - Accuracy: 0.6812 - F1: 0.6878
sub_4:Test (Best Model) - Loss: 1.2189 - Accuracy: 0.7391 - F1: 0.7379
sub_22:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.4265 - F1: 0.3675
sub_27:Test (Best Model) - Loss: 1.2602 - Accuracy: 0.6522 - F1: 0.5658
sub_6:Test (Best Model) - Loss: 1.3495 - Accuracy: 0.3676 - F1: 0.3065
sub_1:Test (Best Model) - Loss: 1.2426 - Accuracy: 0.6618 - F1: 0.6188
sub_28:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.3824 - F1: 0.2878
sub_7:Test (Best Model) - Loss: 1.2771 - Accuracy: 0.6324 - F1: 0.5904
sub_9:Test (Best Model) - Loss: 1.3607 - Accuracy: 0.3529 - F1: 0.3384
sub_12:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.6176 - F1: 0.6356
sub_20:Test (Best Model) - Loss: 1.2846 - Accuracy: 0.6618 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 1.3341 - Accuracy: 0.3768 - F1: 0.2957
sub_14:Test (Best Model) - Loss: 1.3252 - Accuracy: 0.4412 - F1: 0.3906
sub_21:Test (Best Model) - Loss: 1.2788 - Accuracy: 0.6324 - F1: 0.6512
sub_24:Test (Best Model) - Loss: 1.3068 - Accuracy: 0.5000 - F1: 0.4651
sub_19:Test (Best Model) - Loss: 1.3253 - Accuracy: 0.4706 - F1: 0.3818
sub_10:Test (Best Model) - Loss: 1.3144 - Accuracy: 0.5147 - F1: 0.5040
sub_16:Test (Best Model) - Loss: 1.3108 - Accuracy: 0.4412 - F1: 0.4500
sub_11:Test (Best Model) - Loss: 1.3097 - Accuracy: 0.4928 - F1: 0.4670
sub_29:Test (Best Model) - Loss: 1.2851 - Accuracy: 0.4706 - F1: 0.4689
sub_26:Test (Best Model) - Loss: 1.2318 - Accuracy: 0.6667 - F1: 0.6515
sub_15:Test (Best Model) - Loss: 1.2650 - Accuracy: 0.5735 - F1: 0.5643
sub_18:Test (Best Model) - Loss: 1.2768 - Accuracy: 0.6377 - F1: 0.6471
sub_8:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.3676 - F1: 0.3553
sub_5:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.6618 - F1: 0.6026
sub_22:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.5000 - F1: 0.5230
sub_23:Test (Best Model) - Loss: 1.2837 - Accuracy: 0.6522 - F1: 0.6597
sub_12:Test (Best Model) - Loss: 1.3438 - Accuracy: 0.3824 - F1: 0.3979
sub_3:Test (Best Model) - Loss: 1.2432 - Accuracy: 0.8382 - F1: 0.8387
sub_17:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.6667 - F1: 0.6528
sub_20:Test (Best Model) - Loss: 1.3516 - Accuracy: 0.2647 - F1: 0.2527
sub_2:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.4348 - F1: 0.3774
sub_24:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3824 - F1: 0.3214
sub_25:Test (Best Model) - Loss: 1.2384 - Accuracy: 0.6377 - F1: 0.6122
sub_27:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.6667 - F1: 0.6528
sub_13:Test (Best Model) - Loss: 1.3429 - Accuracy: 0.4265 - F1: 0.4072
sub_1:Test (Best Model) - Loss: 1.2878 - Accuracy: 0.5882 - F1: 0.5898
sub_4:Test (Best Model) - Loss: 1.2769 - Accuracy: 0.5507 - F1: 0.5171
sub_16:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.3676 - F1: 0.3535
sub_6:Test (Best Model) - Loss: 1.2837 - Accuracy: 0.5588 - F1: 0.5180
sub_21:Test (Best Model) - Loss: 1.3427 - Accuracy: 0.3088 - F1: 0.2214
sub_8:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.3382 - F1: 0.2799
sub_5:Test (Best Model) - Loss: 1.3011 - Accuracy: 0.5441 - F1: 0.5467
sub_28:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.5000 - F1: 0.4374
sub_14:Test (Best Model) - Loss: 1.3297 - Accuracy: 0.4706 - F1: 0.4052
sub_10:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.4265 - F1: 0.4118
sub_7:Test (Best Model) - Loss: 1.2317 - Accuracy: 0.8382 - F1: 0.8336
sub_26:Test (Best Model) - Loss: 1.2851 - Accuracy: 0.6377 - F1: 0.6287
sub_20:Test (Best Model) - Loss: 1.2794 - Accuracy: 0.5735 - F1: 0.5138
sub_22:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.4559 - F1: 0.4301
sub_2:Test (Best Model) - Loss: 1.3203 - Accuracy: 0.5362 - F1: 0.4831
sub_23:Test (Best Model) - Loss: 1.3180 - Accuracy: 0.4783 - F1: 0.4559
sub_19:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.3529 - F1: 0.2833
sub_15:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.4706 - F1: 0.4511
sub_29:Test (Best Model) - Loss: 1.2849 - Accuracy: 0.5882 - F1: 0.5965
sub_4:Test (Best Model) - Loss: 1.2659 - Accuracy: 0.6377 - F1: 0.6199
sub_18:Test (Best Model) - Loss: 1.2321 - Accuracy: 0.6377 - F1: 0.6206
sub_25:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.7101 - F1: 0.7027
sub_8:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.4265 - F1: 0.3854
sub_1:Test (Best Model) - Loss: 1.3164 - Accuracy: 0.4853 - F1: 0.4772
sub_6:Test (Best Model) - Loss: 1.3248 - Accuracy: 0.5294 - F1: 0.4638
sub_13:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.3235 - F1: 0.2709
sub_9:Test (Best Model) - Loss: 1.3133 - Accuracy: 0.4118 - F1: 0.4242
sub_17:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.5797 - F1: 0.5647
sub_12:Test (Best Model) - Loss: 1.2562 - Accuracy: 0.6912 - F1: 0.6373
sub_20:Test (Best Model) - Loss: 1.2331 - Accuracy: 0.6471 - F1: 0.6378
sub_16:Test (Best Model) - Loss: 1.2964 - Accuracy: 0.5735 - F1: 0.5330
sub_28:Test (Best Model) - Loss: 1.3819 - Accuracy: 0.3088 - F1: 0.2099
sub_24:Test (Best Model) - Loss: 1.2666 - Accuracy: 0.5588 - F1: 0.5552
sub_2:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.6471 - F1: 0.6205
sub_27:Test (Best Model) - Loss: 1.2733 - Accuracy: 0.5797 - F1: 0.5647
sub_14:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.4118 - F1: 0.3231
sub_11:Test (Best Model) - Loss: 1.2480 - Accuracy: 0.5652 - F1: 0.5639
sub_5:Test (Best Model) - Loss: 1.3040 - Accuracy: 0.6471 - F1: 0.5996
sub_18:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.4118 - F1: 0.4001
sub_7:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.6176 - F1: 0.6058
sub_23:Test (Best Model) - Loss: 1.3086 - Accuracy: 0.4058 - F1: 0.3395
sub_10:Test (Best Model) - Loss: 1.3140 - Accuracy: 0.4412 - F1: 0.4454
sub_22:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.4203 - F1: 0.3798
sub_15:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.4706 - F1: 0.4830
sub_26:Test (Best Model) - Loss: 1.2243 - Accuracy: 0.6029 - F1: 0.5868
sub_4:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.5942 - F1: 0.5347
sub_3:Test (Best Model) - Loss: 1.2217 - Accuracy: 0.6912 - F1: 0.6615
sub_8:Test (Best Model) - Loss: 1.2442 - Accuracy: 0.6912 - F1: 0.6709
sub_6:Test (Best Model) - Loss: 1.2833 - Accuracy: 0.5942 - F1: 0.5477
sub_9:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.3824 - F1: 0.3714
sub_29:Test (Best Model) - Loss: 1.3119 - Accuracy: 0.4706 - F1: 0.4459
sub_1:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.3824 - F1: 0.2904
sub_13:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.4559 - F1: 0.4591
sub_28:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.3235 - F1: 0.3172
sub_17:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.4638 - F1: 0.4206
sub_20:Test (Best Model) - Loss: 1.2601 - Accuracy: 0.6029 - F1: 0.5904
sub_21:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.5882 - F1: 0.5478
sub_24:Test (Best Model) - Loss: 1.2970 - Accuracy: 0.5000 - F1: 0.4729
sub_19:Test (Best Model) - Loss: 1.3336 - Accuracy: 0.3382 - F1: 0.2918
sub_14:Test (Best Model) - Loss: 1.2735 - Accuracy: 0.6618 - F1: 0.6638
sub_16:Test (Best Model) - Loss: 1.2731 - Accuracy: 0.5882 - F1: 0.5986
sub_2:Test (Best Model) - Loss: 1.2642 - Accuracy: 0.5735 - F1: 0.5530
sub_25:Test (Best Model) - Loss: 1.1907 - Accuracy: 0.8116 - F1: 0.7975
sub_23:Test (Best Model) - Loss: 1.2919 - Accuracy: 0.6176 - F1: 0.5869
sub_10:Test (Best Model) - Loss: 1.2605 - Accuracy: 0.6176 - F1: 0.6082
sub_12:Test (Best Model) - Loss: 1.2803 - Accuracy: 0.5507 - F1: 0.5414
sub_9:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.5147 - F1: 0.5215
sub_5:Test (Best Model) - Loss: 1.2507 - Accuracy: 0.7059 - F1: 0.6309
sub_27:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.4638 - F1: 0.4206
sub_4:Test (Best Model) - Loss: 1.3002 - Accuracy: 0.4783 - F1: 0.4602
sub_11:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.7391 - F1: 0.7379
sub_18:Test (Best Model) - Loss: 1.2671 - Accuracy: 0.5882 - F1: 0.5898
sub_26:Test (Best Model) - Loss: 1.2544 - Accuracy: 0.5882 - F1: 0.5806
sub_6:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.5942 - F1: 0.5392
sub_22:Test (Best Model) - Loss: 1.2802 - Accuracy: 0.4348 - F1: 0.3839
sub_8:Test (Best Model) - Loss: 1.2631 - Accuracy: 0.6176 - F1: 0.5722
sub_7:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.6912 - F1: 0.6224
sub_15:Test (Best Model) - Loss: 1.2512 - Accuracy: 0.4853 - F1: 0.4629
sub_12:Test (Best Model) - Loss: 1.3595 - Accuracy: 0.3768 - F1: 0.3476
sub_21:Test (Best Model) - Loss: 1.2564 - Accuracy: 0.6029 - F1: 0.5670
sub_17:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.5072 - F1: 0.4523
sub_28:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.2647 - F1: 0.1554
sub_13:Test (Best Model) - Loss: 1.3096 - Accuracy: 0.5217 - F1: 0.5199
sub_9:Test (Best Model) - Loss: 1.2465 - Accuracy: 0.6618 - F1: 0.6455
sub_16:Test (Best Model) - Loss: 1.2935 - Accuracy: 0.5735 - F1: 0.5492
sub_19:Test (Best Model) - Loss: 1.2852 - Accuracy: 0.4706 - F1: 0.4822
sub_29:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.6618 - F1: 0.6209
sub_6:Test (Best Model) - Loss: 1.2899 - Accuracy: 0.5072 - F1: 0.4951
sub_3:Test (Best Model) - Loss: 1.2853 - Accuracy: 0.5588 - F1: 0.5242
sub_5:Test (Best Model) - Loss: 1.2292 - Accuracy: 0.8824 - F1: 0.8898
sub_2:Test (Best Model) - Loss: 1.2387 - Accuracy: 0.6029 - F1: 0.5244
sub_22:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.4783 - F1: 0.4652
sub_20:Test (Best Model) - Loss: 1.2177 - Accuracy: 0.6176 - F1: 0.5595
sub_14:Test (Best Model) - Loss: 1.2493 - Accuracy: 0.5441 - F1: 0.5248
sub_27:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.5072 - F1: 0.4523
sub_4:Test (Best Model) - Loss: 1.2390 - Accuracy: 0.7536 - F1: 0.7522
sub_8:Test (Best Model) - Loss: 1.3106 - Accuracy: 0.6324 - F1: 0.5747
sub_26:Test (Best Model) - Loss: 1.2780 - Accuracy: 0.6765 - F1: 0.5875
sub_21:Test (Best Model) - Loss: 1.2938 - Accuracy: 0.6176 - F1: 0.6104
sub_15:Test (Best Model) - Loss: 1.2899 - Accuracy: 0.5294 - F1: 0.4878
sub_10:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.5147 - F1: 0.4643
sub_13:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.3043 - F1: 0.2538
sub_24:Test (Best Model) - Loss: 1.2678 - Accuracy: 0.5294 - F1: 0.5347
sub_20:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.5441 - F1: 0.4845
sub_18:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.4559 - F1: 0.3324
sub_7:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.5882 - F1: 0.5359
sub_11:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.5652 - F1: 0.5600
sub_1:Test (Best Model) - Loss: 1.2788 - Accuracy: 0.5217 - F1: 0.4740
sub_28:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.2794 - F1: 0.1518
sub_6:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.6377 - F1: 0.6289
sub_23:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.4412 - F1: 0.3627
sub_12:Test (Best Model) - Loss: 1.3390 - Accuracy: 0.4928 - F1: 0.4461
sub_29:Test (Best Model) - Loss: 1.2619 - Accuracy: 0.6324 - F1: 0.6309
sub_17:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3768 - F1: 0.3536
sub_5:Test (Best Model) - Loss: 1.3351 - Accuracy: 0.4412 - F1: 0.4869
sub_2:Test (Best Model) - Loss: 1.2812 - Accuracy: 0.5441 - F1: 0.4872
sub_9:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.6618 - F1: 0.6179
sub_25:Test (Best Model) - Loss: 1.1680 - Accuracy: 0.7500 - F1: 0.7451
sub_14:Test (Best Model) - Loss: 1.3085 - Accuracy: 0.4706 - F1: 0.4686
sub_19:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.6176 - F1: 0.6156
sub_3:Test (Best Model) - Loss: 1.3012 - Accuracy: 0.4638 - F1: 0.3930
sub_27:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3768 - F1: 0.3536
sub_13:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.3043 - F1: 0.2633
sub_22:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.3913 - F1: 0.3359
sub_21:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.6765 - F1: 0.6478
sub_12:Test (Best Model) - Loss: 1.3192 - Accuracy: 0.5072 - F1: 0.4967
sub_20:Test (Best Model) - Loss: 1.2854 - Accuracy: 0.6029 - F1: 0.5990
sub_7:Test (Best Model) - Loss: 1.2966 - Accuracy: 0.4559 - F1: 0.4265
sub_16:Test (Best Model) - Loss: 1.2970 - Accuracy: 0.5441 - F1: 0.5117
sub_8:Test (Best Model) - Loss: 1.2333 - Accuracy: 0.6176 - F1: 0.6176
sub_15:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.5735 - F1: 0.5607
sub_26:Test (Best Model) - Loss: 1.2478 - Accuracy: 0.6176 - F1: 0.6101
sub_17:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.5362 - F1: 0.5466
sub_28:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.2647 - F1: 0.1886
sub_4:Test (Best Model) - Loss: 1.2369 - Accuracy: 0.7536 - F1: 0.7106
sub_10:Test (Best Model) - Loss: 1.3047 - Accuracy: 0.5147 - F1: 0.5489
sub_1:Test (Best Model) - Loss: 1.3105 - Accuracy: 0.3478 - F1: 0.3223
sub_6:Test (Best Model) - Loss: 1.2706 - Accuracy: 0.5652 - F1: 0.5423
sub_29:Test (Best Model) - Loss: 1.3330 - Accuracy: 0.5147 - F1: 0.4801
sub_18:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.4559 - F1: 0.4890
sub_23:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.3676 - F1: 0.2967
sub_2:Test (Best Model) - Loss: 1.2738 - Accuracy: 0.6765 - F1: 0.6491
sub_11:Test (Best Model) - Loss: 1.2747 - Accuracy: 0.3768 - F1: 0.3816
sub_24:Test (Best Model) - Loss: 1.2772 - Accuracy: 0.5735 - F1: 0.5237
sub_16:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.4412 - F1: 0.4383
sub_26:Test (Best Model) - Loss: 1.3035 - Accuracy: 0.5000 - F1: 0.4815
sub_25:Test (Best Model) - Loss: 1.2463 - Accuracy: 0.6912 - F1: 0.6521
sub_27:Test (Best Model) - Loss: 1.3113 - Accuracy: 0.5362 - F1: 0.5466
sub_19:Test (Best Model) - Loss: 1.2775 - Accuracy: 0.6618 - F1: 0.6627
sub_6:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3768 - F1: 0.3210
sub_13:Test (Best Model) - Loss: 1.3298 - Accuracy: 0.4348 - F1: 0.3991
sub_14:Test (Best Model) - Loss: 1.2457 - Accuracy: 0.6176 - F1: 0.6345
sub_20:Test (Best Model) - Loss: 1.3045 - Accuracy: 0.5362 - F1: 0.5015
sub_29:Test (Best Model) - Loss: 1.2878 - Accuracy: 0.7500 - F1: 0.7564
sub_12:Test (Best Model) - Loss: 1.3121 - Accuracy: 0.5217 - F1: 0.4936
sub_4:Test (Best Model) - Loss: 1.2610 - Accuracy: 0.6522 - F1: 0.6459
sub_8:Test (Best Model) - Loss: 1.2945 - Accuracy: 0.4706 - F1: 0.4872
sub_22:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.4058 - F1: 0.3936
sub_9:Test (Best Model) - Loss: 1.2041 - Accuracy: 0.7941 - F1: 0.7875
sub_5:Test (Best Model) - Loss: 1.2453 - Accuracy: 0.6912 - F1: 0.6331
sub_3:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.4783 - F1: 0.4635
sub_28:Test (Best Model) - Loss: 1.3889 - Accuracy: 0.2794 - F1: 0.1393
sub_15:Test (Best Model) - Loss: 1.2791 - Accuracy: 0.5882 - F1: 0.6075
sub_7:Test (Best Model) - Loss: 1.2861 - Accuracy: 0.5735 - F1: 0.5715
sub_18:Test (Best Model) - Loss: 1.3273 - Accuracy: 0.4706 - F1: 0.4318
sub_23:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3971 - F1: 0.3274
sub_1:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.4783 - F1: 0.4775
sub_2:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.3768 - F1: 0.2571
sub_10:Test (Best Model) - Loss: 1.2708 - Accuracy: 0.7353 - F1: 0.7539
sub_13:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3478 - F1: 0.3381
sub_11:Test (Best Model) - Loss: 1.2965 - Accuracy: 0.4783 - F1: 0.4438
sub_24:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.4412 - F1: 0.4251
sub_20:Test (Best Model) - Loss: 1.2408 - Accuracy: 0.6667 - F1: 0.6636
sub_17:Test (Best Model) - Loss: 1.2761 - Accuracy: 0.4928 - F1: 0.4651
sub_12:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.4265 - F1: 0.4099
sub_4:Test (Best Model) - Loss: 1.2567 - Accuracy: 0.5797 - F1: 0.5182
sub_21:Test (Best Model) - Loss: 1.1968 - Accuracy: 0.7941 - F1: 0.7703
sub_19:Test (Best Model) - Loss: 1.3418 - Accuracy: 0.4559 - F1: 0.4051
sub_23:Test (Best Model) - Loss: 1.3320 - Accuracy: 0.4265 - F1: 0.3771
sub_29:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.7059 - F1: 0.6667
sub_22:Test (Best Model) - Loss: 1.2985 - Accuracy: 0.6029 - F1: 0.5971
sub_26:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.4706 - F1: 0.4577
sub_6:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.6377 - F1: 0.5841
sub_15:Test (Best Model) - Loss: 1.2659 - Accuracy: 0.6618 - F1: 0.6623
sub_9:Test (Best Model) - Loss: 1.2601 - Accuracy: 0.6618 - F1: 0.6737
sub_16:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.3676 - F1: 0.3685
sub_14:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.4853 - F1: 0.4211
sub_12:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.2206 - F1: 0.1909
sub_7:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.6618 - F1: 0.6647
sub_25:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.7941 - F1: 0.7894
sub_5:Test (Best Model) - Loss: 1.2306 - Accuracy: 0.7500 - F1: 0.7589
sub_27:Test (Best Model) - Loss: 1.2761 - Accuracy: 0.4928 - F1: 0.4651
sub_24:Test (Best Model) - Loss: 1.3348 - Accuracy: 0.3676 - F1: 0.3735
sub_1:Test (Best Model) - Loss: 1.2577 - Accuracy: 0.5797 - F1: 0.5822
sub_28:Test (Best Model) - Loss: 1.3773 - Accuracy: 0.3529 - F1: 0.2317
sub_5:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.5147 - F1: 0.4559
sub_18:Test (Best Model) - Loss: 1.2989 - Accuracy: 0.5588 - F1: 0.5321
sub_10:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.4412 - F1: 0.4145
sub_3:Test (Best Model) - Loss: 1.3130 - Accuracy: 0.4348 - F1: 0.3854
sub_20:Test (Best Model) - Loss: 1.2327 - Accuracy: 0.7391 - F1: 0.7496
sub_6:Test (Best Model) - Loss: 1.2856 - Accuracy: 0.5942 - F1: 0.5801
sub_13:Test (Best Model) - Loss: 1.3408 - Accuracy: 0.4853 - F1: 0.4061
sub_29:Test (Best Model) - Loss: 1.3119 - Accuracy: 0.6087 - F1: 0.5341
sub_8:Test (Best Model) - Loss: 1.2796 - Accuracy: 0.5588 - F1: 0.5245
sub_25:Test (Best Model) - Loss: 1.2461 - Accuracy: 0.7500 - F1: 0.7447
sub_4:Test (Best Model) - Loss: 1.2152 - Accuracy: 0.6957 - F1: 0.6894
sub_2:Test (Best Model) - Loss: 1.2812 - Accuracy: 0.5942 - F1: 0.5276
sub_21:Test (Best Model) - Loss: 1.2757 - Accuracy: 0.4853 - F1: 0.4396
sub_14:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.5000 - F1: 0.4288
sub_5:Test (Best Model) - Loss: 1.3808 - Accuracy: 0.3529 - F1: 0.2887
sub_26:Test (Best Model) - Loss: 1.2709 - Accuracy: 0.5294 - F1: 0.5429
sub_11:Test (Best Model) - Loss: 1.2652 - Accuracy: 0.6232 - F1: 0.5652
sub_22:Test (Best Model) - Loss: 1.3005 - Accuracy: 0.5000 - F1: 0.4770
sub_17:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.4203 - F1: 0.3889
sub_7:Test (Best Model) - Loss: 1.3034 - Accuracy: 0.5294 - F1: 0.4710
sub_19:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.4265 - F1: 0.3848
sub_23:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.5797 - F1: 0.6072
sub_1:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3768 - F1: 0.3168
sub_15:Test (Best Model) - Loss: 1.2698 - Accuracy: 0.5147 - F1: 0.5103
sub_24:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3529 - F1: 0.2943
sub_6:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.3768 - F1: 0.3664
sub_12:Test (Best Model) - Loss: 1.3254 - Accuracy: 0.5441 - F1: 0.5060
sub_27:Test (Best Model) - Loss: 1.3213 - Accuracy: 0.4203 - F1: 0.3889
sub_20:Test (Best Model) - Loss: 1.1868 - Accuracy: 0.6957 - F1: 0.6855
sub_9:Test (Best Model) - Loss: 1.2442 - Accuracy: 0.5882 - F1: 0.6019
sub_19:Test (Best Model) - Loss: 1.4214 - Accuracy: 0.1618 - F1: 0.1629
sub_28:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.2353 - F1: 0.1781
sub_16:Test (Best Model) - Loss: 1.2840 - Accuracy: 0.4706 - F1: 0.4374
sub_3:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.6087 - F1: 0.5925
sub_23:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.1739 - F1: 0.1986
sub_25:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.6324 - F1: 0.6224
sub_26:Test (Best Model) - Loss: 1.2578 - Accuracy: 0.6176 - F1: 0.6194
sub_8:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.5294 - F1: 0.5084
sub_18:Test (Best Model) - Loss: 1.2352 - Accuracy: 0.7353 - F1: 0.7409
sub_29:Test (Best Model) - Loss: 1.2882 - Accuracy: 0.6522 - F1: 0.5955
sub_6:Test (Best Model) - Loss: 1.2944 - Accuracy: 0.6087 - F1: 0.5847
sub_20:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.6232 - F1: 0.6043
sub_21:Test (Best Model) - Loss: 1.2845 - Accuracy: 0.5735 - F1: 0.5026
sub_10:Test (Best Model) - Loss: 1.2455 - Accuracy: 0.7101 - F1: 0.6400
sub_14:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.5882 - F1: 0.5840
sub_23:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.4203 - F1: 0.3637
sub_2:Test (Best Model) - Loss: 1.2303 - Accuracy: 0.7536 - F1: 0.7524
sub_5:Test (Best Model) - Loss: 1.2651 - Accuracy: 0.6324 - F1: 0.5801
sub_13:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.3235 - F1: 0.2738
sub_17:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.5588 - F1: 0.5190
sub_4:Test (Best Model) - Loss: 1.2328 - Accuracy: 0.6232 - F1: 0.6106
sub_12:Test (Best Model) - Loss: 1.2751 - Accuracy: 0.5882 - F1: 0.5699
sub_22:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.6176 - F1: 0.5634
sub_15:Test (Best Model) - Loss: 1.2991 - Accuracy: 0.5147 - F1: 0.5280
sub_11:Test (Best Model) - Loss: 1.2566 - Accuracy: 0.6667 - F1: 0.6537
sub_7:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.3971 - F1: 0.3389
sub_27:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.5588 - F1: 0.5190
sub_19:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.6471 - F1: 0.6307
sub_24:Test (Best Model) - Loss: 1.2869 - Accuracy: 0.5294 - F1: 0.4949
sub_28:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.2206 - F1: 0.1977
sub_1:Test (Best Model) - Loss: 1.2910 - Accuracy: 0.6324 - F1: 0.5959
sub_16:Test (Best Model) - Loss: 1.3187 - Accuracy: 0.4559 - F1: 0.4442
sub_21:Test (Best Model) - Loss: 1.2940 - Accuracy: 0.5147 - F1: 0.4744
sub_14:Test (Best Model) - Loss: 1.2626 - Accuracy: 0.7647 - F1: 0.7581
sub_23:Test (Best Model) - Loss: 1.3150 - Accuracy: 0.4638 - F1: 0.4736
sub_18:Test (Best Model) - Loss: 1.2706 - Accuracy: 0.5147 - F1: 0.4745
sub_8:Test (Best Model) - Loss: 1.2864 - Accuracy: 0.4559 - F1: 0.4920
sub_17:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.1324 - F1: 0.0804
sub_26:Test (Best Model) - Loss: 1.2119 - Accuracy: 0.6471 - F1: 0.6036
sub_9:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.5441 - F1: 0.5298
sub_10:Test (Best Model) - Loss: 1.2834 - Accuracy: 0.6667 - F1: 0.6562
sub_3:Test (Best Model) - Loss: 1.3019 - Accuracy: 0.5217 - F1: 0.4946
sub_22:Test (Best Model) - Loss: 1.2948 - Accuracy: 0.5441 - F1: 0.4992
sub_12:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.4265 - F1: 0.3896
sub_2:Test (Best Model) - Loss: 1.2893 - Accuracy: 0.4928 - F1: 0.4206
sub_5:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.5735 - F1: 0.4830
sub_4:Test (Best Model) - Loss: 1.2788 - Accuracy: 0.5507 - F1: 0.5570
sub_27:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.1324 - F1: 0.0804
sub_26:Test (Best Model) - Loss: 1.2740 - Accuracy: 0.6912 - F1: 0.6755
sub_29:Test (Best Model) - Loss: 1.2290 - Accuracy: 0.7101 - F1: 0.7155
sub_11:Test (Best Model) - Loss: 1.3101 - Accuracy: 0.4783 - F1: 0.4135
sub_28:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.2941 - F1: 0.1687
sub_7:Test (Best Model) - Loss: 1.3141 - Accuracy: 0.3235 - F1: 0.2476
sub_25:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.7353 - F1: 0.7177
sub_13:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.4412 - F1: 0.3149
sub_24:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.6765 - F1: 0.6519
sub_19:Test (Best Model) - Loss: 1.2851 - Accuracy: 0.5294 - F1: 0.4575
sub_16:Test (Best Model) - Loss: 1.3091 - Accuracy: 0.5441 - F1: 0.5388
sub_14:Test (Best Model) - Loss: 1.2579 - Accuracy: 0.6029 - F1: 0.5674
sub_2:Test (Best Model) - Loss: 1.3171 - Accuracy: 0.3188 - F1: 0.2895
sub_15:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.7206 - F1: 0.7179
sub_8:Test (Best Model) - Loss: 1.2690 - Accuracy: 0.5882 - F1: 0.5741
sub_22:Test (Best Model) - Loss: 1.2980 - Accuracy: 0.5147 - F1: 0.4867
sub_4:Test (Best Model) - Loss: 1.3153 - Accuracy: 0.5072 - F1: 0.4745
sub_10:Test (Best Model) - Loss: 1.2745 - Accuracy: 0.5507 - F1: 0.5044
sub_17:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.5000 - F1: 0.4835
sub_9:Test (Best Model) - Loss: 1.2709 - Accuracy: 0.5147 - F1: 0.4906
sub_5:Test (Best Model) - Loss: 1.2661 - Accuracy: 0.5882 - F1: 0.5205
sub_18:Test (Best Model) - Loss: 1.2725 - Accuracy: 0.5147 - F1: 0.4485
sub_21:Test (Best Model) - Loss: 1.2447 - Accuracy: 0.5735 - F1: 0.5289
sub_23:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.5507 - F1: 0.4918
sub_8:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.4706 - F1: 0.4441
sub_27:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.5000 - F1: 0.4835
sub_3:Test (Best Model) - Loss: 1.2262 - Accuracy: 0.6522 - F1: 0.6327
sub_1:Test (Best Model) - Loss: 1.2865 - Accuracy: 0.7059 - F1: 0.7038
sub_4:Test (Best Model) - Loss: 1.2927 - Accuracy: 0.6087 - F1: 0.5652
sub_14:Test (Best Model) - Loss: 1.3132 - Accuracy: 0.4265 - F1: 0.3876
sub_29:Test (Best Model) - Loss: 1.3145 - Accuracy: 0.4783 - F1: 0.4219
sub_16:Test (Best Model) - Loss: 1.2779 - Accuracy: 0.6029 - F1: 0.5336
sub_13:Test (Best Model) - Loss: 1.3385 - Accuracy: 0.3971 - F1: 0.3318
sub_24:Test (Best Model) - Loss: 1.3053 - Accuracy: 0.5588 - F1: 0.4840
sub_19:Test (Best Model) - Loss: 1.2717 - Accuracy: 0.6912 - F1: 0.6870
sub_7:Test (Best Model) - Loss: 1.3376 - Accuracy: 0.2941 - F1: 0.2529
sub_25:Test (Best Model) - Loss: 1.2755 - Accuracy: 0.6029 - F1: 0.6044
sub_9:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.3824 - F1: 0.3685
sub_18:Test (Best Model) - Loss: 1.3216 - Accuracy: 0.4118 - F1: 0.4093
sub_10:Test (Best Model) - Loss: 1.2820 - Accuracy: 0.5362 - F1: 0.4270
sub_24:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3088 - F1: 0.3030
sub_11:Test (Best Model) - Loss: 1.3207 - Accuracy: 0.3623 - F1: 0.2959
sub_21:Test (Best Model) - Loss: 1.2469 - Accuracy: 0.6176 - F1: 0.5555
sub_15:Test (Best Model) - Loss: 1.3008 - Accuracy: 0.4706 - F1: 0.3207
sub_17:Test (Best Model) - Loss: 1.2666 - Accuracy: 0.4853 - F1: 0.4011
sub_9:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.5147 - F1: 0.4353
sub_10:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.5507 - F1: 0.5288
sub_1:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.4706 - F1: 0.3765
sub_16:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.5147 - F1: 0.4792
sub_7:Test (Best Model) - Loss: 1.2909 - Accuracy: 0.5735 - F1: 0.4958
sub_27:Test (Best Model) - Loss: 1.2666 - Accuracy: 0.4853 - F1: 0.4011
sub_29:Test (Best Model) - Loss: 1.2907 - Accuracy: 0.5652 - F1: 0.4845
sub_3:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.3768 - F1: 0.3528
sub_25:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.5882 - F1: 0.5474
sub_13:Test (Best Model) - Loss: 1.3765 - Accuracy: 0.4412 - F1: 0.3704
sub_15:Test (Best Model) - Loss: 1.2796 - Accuracy: 0.5441 - F1: 0.4694
sub_1:Test (Best Model) - Loss: 1.2763 - Accuracy: 0.6029 - F1: 0.5721
sub_17:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.6029 - F1: 0.5754
sub_11:Test (Best Model) - Loss: 1.2450 - Accuracy: 0.6812 - F1: 0.6285
sub_27:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.6029 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.6765 - F1: 0.6615
sub_1:Test (Best Model) - Loss: 1.2720 - Accuracy: 0.7059 - F1: 0.6741
sub_3:Test (Best Model) - Loss: 1.2016 - Accuracy: 0.6957 - F1: 0.6832
sub_11:Test (Best Model) - Loss: 1.2289 - Accuracy: 0.5507 - F1: 0.5407
sub_15:Test (Best Model) - Loss: 1.2661 - Accuracy: 0.5000 - F1: 0.4652
sub_25:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.6912 - F1: 0.7016
sub_3:Test (Best Model) - Loss: 1.3413 - Accuracy: 0.4348 - F1: 0.4058
sub_3:Test (Best Model) - Loss: 1.3262 - Accuracy: 0.4928 - F1: 0.4680
sub_11:Test (Best Model) - Loss: 1.2960 - Accuracy: 0.4493 - F1: 0.3962

=== Summary Results ===

acc: 52.90 ± 6.41
F1: 49.82 ± 7.24
acc-in: 68.04 ± 5.85
F1-in: 66.26 ± 5.94
