lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.2333 - Accuracy: 0.4853 - F1: 0.5251
sub_1:Test (Best Model) - Loss: 1.1755 - Accuracy: 0.5441 - F1: 0.5792
sub_1:Test (Best Model) - Loss: 1.2048 - Accuracy: 0.5147 - F1: 0.5443
sub_1:Test (Best Model) - Loss: 1.1248 - Accuracy: 0.4853 - F1: 0.5252
sub_1:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.4559 - F1: 0.4971
sub_1:Test (Best Model) - Loss: 1.2543 - Accuracy: 0.4203 - F1: 0.4188
sub_1:Test (Best Model) - Loss: 1.2740 - Accuracy: 0.3478 - F1: 0.3404
sub_1:Test (Best Model) - Loss: 1.2611 - Accuracy: 0.3913 - F1: 0.3977
sub_1:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.4203 - F1: 0.4209
sub_1:Test (Best Model) - Loss: 1.2544 - Accuracy: 0.3623 - F1: 0.3761
sub_1:Test (Best Model) - Loss: 1.1706 - Accuracy: 0.4853 - F1: 0.4750
sub_1:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.5588 - F1: 0.5622
sub_1:Test (Best Model) - Loss: 1.1489 - Accuracy: 0.5294 - F1: 0.5348
sub_1:Test (Best Model) - Loss: 1.2021 - Accuracy: 0.5147 - F1: 0.4840
sub_1:Test (Best Model) - Loss: 1.1241 - Accuracy: 0.4265 - F1: 0.4198
sub_2:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.2609 - F1: 0.2751
sub_2:Test (Best Model) - Loss: 1.4542 - Accuracy: 0.3333 - F1: 0.3552
sub_2:Test (Best Model) - Loss: 1.3747 - Accuracy: 0.2174 - F1: 0.2330
sub_2:Test (Best Model) - Loss: 1.3967 - Accuracy: 0.2319 - F1: 0.2314
sub_2:Test (Best Model) - Loss: 1.5057 - Accuracy: 0.2754 - F1: 0.2990
sub_2:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3235 - F1: 0.3198
sub_2:Test (Best Model) - Loss: 1.3922 - Accuracy: 0.2500 - F1: 0.2588
sub_2:Test (Best Model) - Loss: 1.3217 - Accuracy: 0.4853 - F1: 0.5037
sub_2:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.3382 - F1: 0.3546
sub_2:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3382 - F1: 0.3602
sub_2:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.3623 - F1: 0.3476
sub_2:Test (Best Model) - Loss: 1.3354 - Accuracy: 0.3768 - F1: 0.3676
sub_2:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.4058 - F1: 0.3876
sub_2:Test (Best Model) - Loss: 1.3305 - Accuracy: 0.3768 - F1: 0.3429
sub_2:Test (Best Model) - Loss: 1.3928 - Accuracy: 0.3768 - F1: 0.3894
sub_3:Test (Best Model) - Loss: 1.3836 - Accuracy: 0.3088 - F1: 0.3170
sub_3:Test (Best Model) - Loss: 1.3453 - Accuracy: 0.3235 - F1: 0.3079
sub_3:Test (Best Model) - Loss: 1.4673 - Accuracy: 0.2794 - F1: 0.2905
sub_3:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2647 - F1: 0.2642
sub_3:Test (Best Model) - Loss: 1.3961 - Accuracy: 0.3088 - F1: 0.3206
sub_3:Test (Best Model) - Loss: 1.3714 - Accuracy: 0.3478 - F1: 0.3107
sub_3:Test (Best Model) - Loss: 1.4179 - Accuracy: 0.2899 - F1: 0.2703
sub_3:Test (Best Model) - Loss: 1.3745 - Accuracy: 0.2754 - F1: 0.2748
sub_3:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.3623 - F1: 0.3411
sub_3:Test (Best Model) - Loss: 1.3545 - Accuracy: 0.3043 - F1: 0.2529
sub_3:Test (Best Model) - Loss: 1.4980 - Accuracy: 0.2754 - F1: 0.2369
sub_3:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2754 - F1: 0.2289
sub_3:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2609 - F1: 0.2545
sub_3:Test (Best Model) - Loss: 1.4045 - Accuracy: 0.2609 - F1: 0.2418
sub_3:Test (Best Model) - Loss: 1.4631 - Accuracy: 0.2899 - F1: 0.2544
sub_4:Test (Best Model) - Loss: 1.0517 - Accuracy: 0.5362 - F1: 0.5554
sub_4:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.4783 - F1: 0.5039
sub_4:Test (Best Model) - Loss: 1.1088 - Accuracy: 0.5072 - F1: 0.5268
sub_4:Test (Best Model) - Loss: 1.0241 - Accuracy: 0.5217 - F1: 0.5351
sub_4:Test (Best Model) - Loss: 1.0728 - Accuracy: 0.5507 - F1: 0.5689
sub_4:Test (Best Model) - Loss: 1.0731 - Accuracy: 0.4928 - F1: 0.5021
sub_4:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.5797 - F1: 0.6025
sub_4:Test (Best Model) - Loss: 0.9864 - Accuracy: 0.5797 - F1: 0.6051
sub_4:Test (Best Model) - Loss: 1.0603 - Accuracy: 0.5797 - F1: 0.5859
sub_4:Test (Best Model) - Loss: 1.0095 - Accuracy: 0.5362 - F1: 0.5597
sub_4:Test (Best Model) - Loss: 1.1309 - Accuracy: 0.4348 - F1: 0.3959
sub_4:Test (Best Model) - Loss: 1.0964 - Accuracy: 0.4638 - F1: 0.4464
sub_4:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.4348 - F1: 0.4472
sub_4:Test (Best Model) - Loss: 1.0848 - Accuracy: 0.5072 - F1: 0.5211
sub_4:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.4928 - F1: 0.4851
sub_5:Test (Best Model) - Loss: 1.4740 - Accuracy: 0.5000 - F1: 0.4777
sub_5:Test (Best Model) - Loss: 1.5341 - Accuracy: 0.4706 - F1: 0.4260
sub_5:Test (Best Model) - Loss: 1.5470 - Accuracy: 0.4265 - F1: 0.4100
sub_5:Test (Best Model) - Loss: 1.4636 - Accuracy: 0.4265 - F1: 0.3979
sub_5:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.4265 - F1: 0.4090
sub_5:Test (Best Model) - Loss: 1.1259 - Accuracy: 0.4265 - F1: 0.3934
sub_5:Test (Best Model) - Loss: 1.0782 - Accuracy: 0.5588 - F1: 0.5183
sub_5:Test (Best Model) - Loss: 1.0902 - Accuracy: 0.4559 - F1: 0.4643
sub_5:Test (Best Model) - Loss: 1.1004 - Accuracy: 0.4559 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 1.1159 - Accuracy: 0.4412 - F1: 0.4406
sub_5:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.4559 - F1: 0.4446
sub_5:Test (Best Model) - Loss: 1.2075 - Accuracy: 0.3676 - F1: 0.3512
sub_5:Test (Best Model) - Loss: 1.1658 - Accuracy: 0.3824 - F1: 0.3821
sub_5:Test (Best Model) - Loss: 1.1338 - Accuracy: 0.3676 - F1: 0.3652
sub_5:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.4412 - F1: 0.4390
sub_6:Test (Best Model) - Loss: 1.1680 - Accuracy: 0.4559 - F1: 0.4640
sub_6:Test (Best Model) - Loss: 1.1910 - Accuracy: 0.4853 - F1: 0.4971
sub_6:Test (Best Model) - Loss: 1.1811 - Accuracy: 0.4265 - F1: 0.4194
sub_6:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.4412 - F1: 0.4418
sub_6:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.5000 - F1: 0.5175
sub_6:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.4058 - F1: 0.3221
sub_6:Test (Best Model) - Loss: 1.2377 - Accuracy: 0.4783 - F1: 0.3746
sub_6:Test (Best Model) - Loss: 1.2114 - Accuracy: 0.3913 - F1: 0.3155
sub_6:Test (Best Model) - Loss: 1.2591 - Accuracy: 0.4638 - F1: 0.4299
sub_6:Test (Best Model) - Loss: 1.2172 - Accuracy: 0.4348 - F1: 0.4031
sub_6:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.3188 - F1: 0.3516
sub_6:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3913 - F1: 0.4032
sub_6:Test (Best Model) - Loss: 1.2870 - Accuracy: 0.4493 - F1: 0.4787
sub_6:Test (Best Model) - Loss: 1.2145 - Accuracy: 0.4638 - F1: 0.4827
sub_6:Test (Best Model) - Loss: 1.2770 - Accuracy: 0.3623 - F1: 0.3970
sub_7:Test (Best Model) - Loss: 1.0080 - Accuracy: 0.6029 - F1: 0.5947
sub_7:Test (Best Model) - Loss: 0.9840 - Accuracy: 0.5588 - F1: 0.5278
sub_7:Test (Best Model) - Loss: 1.1156 - Accuracy: 0.4265 - F1: 0.3979
sub_7:Test (Best Model) - Loss: 0.9880 - Accuracy: 0.6471 - F1: 0.6285
sub_7:Test (Best Model) - Loss: 1.0736 - Accuracy: 0.5588 - F1: 0.5654
sub_7:Test (Best Model) - Loss: 1.2753 - Accuracy: 0.3824 - F1: 0.3630
sub_7:Test (Best Model) - Loss: 1.2759 - Accuracy: 0.3676 - F1: 0.3684
sub_7:Test (Best Model) - Loss: 1.2077 - Accuracy: 0.4853 - F1: 0.4917
sub_7:Test (Best Model) - Loss: 1.2448 - Accuracy: 0.4265 - F1: 0.4155
sub_7:Test (Best Model) - Loss: 1.1693 - Accuracy: 0.5000 - F1: 0.4727
sub_7:Test (Best Model) - Loss: 1.1518 - Accuracy: 0.5882 - F1: 0.6031
sub_7:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.4853 - F1: 0.4818
sub_7:Test (Best Model) - Loss: 1.1955 - Accuracy: 0.5294 - F1: 0.5193
sub_7:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.5294 - F1: 0.5339
sub_7:Test (Best Model) - Loss: 1.2317 - Accuracy: 0.4706 - F1: 0.4934
sub_8:Test (Best Model) - Loss: 1.4776 - Accuracy: 0.2794 - F1: 0.3155
sub_8:Test (Best Model) - Loss: 1.5050 - Accuracy: 0.2353 - F1: 0.2423
sub_8:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.2500 - F1: 0.2728
sub_8:Test (Best Model) - Loss: 1.4293 - Accuracy: 0.3529 - F1: 0.3573
sub_8:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.2794 - F1: 0.2912
sub_8:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3529 - F1: 0.3648
sub_8:Test (Best Model) - Loss: 1.3678 - Accuracy: 0.3088 - F1: 0.3099
sub_8:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.3676 - F1: 0.3695
sub_8:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.3088 - F1: 0.3144
sub_8:Test (Best Model) - Loss: 1.3482 - Accuracy: 0.3676 - F1: 0.3778
sub_8:Test (Best Model) - Loss: 1.4558 - Accuracy: 0.2647 - F1: 0.2582
sub_8:Test (Best Model) - Loss: 1.4148 - Accuracy: 0.3824 - F1: 0.4090
sub_8:Test (Best Model) - Loss: 1.3917 - Accuracy: 0.4118 - F1: 0.4428
sub_8:Test (Best Model) - Loss: 1.3887 - Accuracy: 0.4118 - F1: 0.4250
sub_8:Test (Best Model) - Loss: 1.3966 - Accuracy: 0.4559 - F1: 0.4782
sub_9:Test (Best Model) - Loss: 1.0850 - Accuracy: 0.5441 - F1: 0.5685
sub_9:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.5588 - F1: 0.5752
sub_9:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.4265 - F1: 0.4559
sub_9:Test (Best Model) - Loss: 1.0606 - Accuracy: 0.5147 - F1: 0.5431
sub_9:Test (Best Model) - Loss: 1.0296 - Accuracy: 0.5882 - F1: 0.6075
sub_9:Test (Best Model) - Loss: 1.3531 - Accuracy: 0.3235 - F1: 0.3280
sub_9:Test (Best Model) - Loss: 1.3919 - Accuracy: 0.3382 - F1: 0.3593
sub_9:Test (Best Model) - Loss: 1.2707 - Accuracy: 0.3676 - F1: 0.3864
sub_9:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.3676 - F1: 0.3894
sub_9:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.3382 - F1: 0.3756
sub_9:Test (Best Model) - Loss: 1.3662 - Accuracy: 0.3971 - F1: 0.4202
sub_9:Test (Best Model) - Loss: 1.2817 - Accuracy: 0.4118 - F1: 0.4329
sub_9:Test (Best Model) - Loss: 1.2483 - Accuracy: 0.4559 - F1: 0.4826
sub_9:Test (Best Model) - Loss: 1.2946 - Accuracy: 0.3676 - F1: 0.3962
sub_9:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.3676 - F1: 0.3994
sub_10:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.2647 - F1: 0.2579
sub_10:Test (Best Model) - Loss: 1.3586 - Accuracy: 0.3824 - F1: 0.3915
sub_10:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3529 - F1: 0.3514
sub_10:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.2941 - F1: 0.3097
sub_10:Test (Best Model) - Loss: 1.4262 - Accuracy: 0.3676 - F1: 0.3857
sub_10:Test (Best Model) - Loss: 1.3748 - Accuracy: 0.4118 - F1: 0.3999
sub_10:Test (Best Model) - Loss: 1.4307 - Accuracy: 0.1912 - F1: 0.1807
sub_10:Test (Best Model) - Loss: 1.4123 - Accuracy: 0.2500 - F1: 0.2472
sub_10:Test (Best Model) - Loss: 1.3512 - Accuracy: 0.2206 - F1: 0.2195
sub_10:Test (Best Model) - Loss: 1.4224 - Accuracy: 0.2794 - F1: 0.2827
sub_10:Test (Best Model) - Loss: 1.5443 - Accuracy: 0.2754 - F1: 0.2936
sub_10:Test (Best Model) - Loss: 1.4477 - Accuracy: 0.2899 - F1: 0.2974
sub_10:Test (Best Model) - Loss: 1.4233 - Accuracy: 0.3188 - F1: 0.3167
sub_10:Test (Best Model) - Loss: 1.3934 - Accuracy: 0.3333 - F1: 0.3228
sub_10:Test (Best Model) - Loss: 1.4251 - Accuracy: 0.3043 - F1: 0.3069
sub_11:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3623 - F1: 0.3497
sub_11:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.3333 - F1: 0.3215
sub_11:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.3478 - F1: 0.3558
sub_11:Test (Best Model) - Loss: 1.3546 - Accuracy: 0.3188 - F1: 0.3132
sub_11:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.3188 - F1: 0.3131
sub_11:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.4058 - F1: 0.3648
sub_11:Test (Best Model) - Loss: 1.2931 - Accuracy: 0.4783 - F1: 0.4461
sub_11:Test (Best Model) - Loss: 1.2623 - Accuracy: 0.4348 - F1: 0.4209
sub_11:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.4058 - F1: 0.3798
sub_11:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.4493 - F1: 0.4169
sub_11:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.3623 - F1: 0.3166
sub_11:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.3623 - F1: 0.3347
sub_11:Test (Best Model) - Loss: 1.2633 - Accuracy: 0.4638 - F1: 0.4312
sub_11:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.3913 - F1: 0.3659
sub_11:Test (Best Model) - Loss: 1.3462 - Accuracy: 0.3623 - F1: 0.3327
sub_12:Test (Best Model) - Loss: 1.1317 - Accuracy: 0.4706 - F1: 0.4715
sub_12:Test (Best Model) - Loss: 1.0648 - Accuracy: 0.5588 - F1: 0.5460
sub_12:Test (Best Model) - Loss: 1.0385 - Accuracy: 0.5588 - F1: 0.5284
sub_12:Test (Best Model) - Loss: 1.0367 - Accuracy: 0.5588 - F1: 0.5597
sub_12:Test (Best Model) - Loss: 1.0759 - Accuracy: 0.5588 - F1: 0.5484
sub_12:Test (Best Model) - Loss: 1.2069 - Accuracy: 0.4348 - F1: 0.4462
sub_12:Test (Best Model) - Loss: 1.0943 - Accuracy: 0.4783 - F1: 0.4870
sub_12:Test (Best Model) - Loss: 1.0841 - Accuracy: 0.5072 - F1: 0.5123
sub_12:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.4783 - F1: 0.4943
sub_12:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.5072 - F1: 0.5155
sub_12:Test (Best Model) - Loss: 1.1755 - Accuracy: 0.4853 - F1: 0.4914
sub_12:Test (Best Model) - Loss: 1.2171 - Accuracy: 0.4265 - F1: 0.4320
sub_12:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.4706 - F1: 0.4837
sub_12:Test (Best Model) - Loss: 1.2159 - Accuracy: 0.4706 - F1: 0.4807
sub_12:Test (Best Model) - Loss: 1.1561 - Accuracy: 0.5147 - F1: 0.5226
sub_13:Test (Best Model) - Loss: 1.3077 - Accuracy: 0.4412 - F1: 0.4650
sub_13:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.3529 - F1: 0.3717
sub_13:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.4265 - F1: 0.4441
sub_13:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.3088 - F1: 0.3506
sub_13:Test (Best Model) - Loss: 1.2879 - Accuracy: 0.4265 - F1: 0.4417
sub_13:Test (Best Model) - Loss: 1.3400 - Accuracy: 0.4058 - F1: 0.4032
sub_13:Test (Best Model) - Loss: 1.3171 - Accuracy: 0.2754 - F1: 0.2587
sub_13:Test (Best Model) - Loss: 1.3868 - Accuracy: 0.2899 - F1: 0.2883
sub_13:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.4058 - F1: 0.4209
sub_13:Test (Best Model) - Loss: 1.3259 - Accuracy: 0.4348 - F1: 0.4401
sub_13:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.3235 - F1: 0.3239
sub_13:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3235 - F1: 0.3383
sub_13:Test (Best Model) - Loss: 1.4192 - Accuracy: 0.3088 - F1: 0.3313
sub_13:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.2941 - F1: 0.3061
sub_13:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.3824 - F1: 0.3977
sub_14:Test (Best Model) - Loss: 1.3360 - Accuracy: 0.2794 - F1: 0.3102
sub_14:Test (Best Model) - Loss: 1.2902 - Accuracy: 0.3529 - F1: 0.3834
sub_14:Test (Best Model) - Loss: 1.3064 - Accuracy: 0.3529 - F1: 0.3621
sub_14:Test (Best Model) - Loss: 1.3382 - Accuracy: 0.2794 - F1: 0.3193
sub_14:Test (Best Model) - Loss: 1.3009 - Accuracy: 0.3824 - F1: 0.3988
sub_14:Test (Best Model) - Loss: 1.3345 - Accuracy: 0.4265 - F1: 0.4526
sub_14:Test (Best Model) - Loss: 1.3464 - Accuracy: 0.4412 - F1: 0.4562
sub_14:Test (Best Model) - Loss: 1.3271 - Accuracy: 0.3235 - F1: 0.3187
sub_14:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3676 - F1: 0.3784
sub_14:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3235 - F1: 0.3428
sub_14:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3382 - F1: 0.3635
sub_14:Test (Best Model) - Loss: 1.3218 - Accuracy: 0.3235 - F1: 0.2993
sub_14:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.3676 - F1: 0.3757
sub_14:Test (Best Model) - Loss: 1.2147 - Accuracy: 0.4118 - F1: 0.3981
sub_14:Test (Best Model) - Loss: 1.2786 - Accuracy: 0.3088 - F1: 0.3153
sub_15:Test (Best Model) - Loss: 1.2255 - Accuracy: 0.3824 - F1: 0.4154
sub_15:Test (Best Model) - Loss: 1.3297 - Accuracy: 0.3824 - F1: 0.4048
sub_15:Test (Best Model) - Loss: 1.2379 - Accuracy: 0.3971 - F1: 0.4220
sub_15:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.4118 - F1: 0.4453
sub_15:Test (Best Model) - Loss: 1.1993 - Accuracy: 0.4559 - F1: 0.4872
sub_15:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.5147 - F1: 0.5039
sub_15:Test (Best Model) - Loss: 1.2119 - Accuracy: 0.5147 - F1: 0.5191
sub_15:Test (Best Model) - Loss: 1.0959 - Accuracy: 0.5735 - F1: 0.5906
sub_15:Test (Best Model) - Loss: 1.0400 - Accuracy: 0.5735 - F1: 0.5891
sub_15:Test (Best Model) - Loss: 1.0358 - Accuracy: 0.5588 - F1: 0.5573
sub_15:Test (Best Model) - Loss: 1.1908 - Accuracy: 0.4412 - F1: 0.4390
sub_15:Test (Best Model) - Loss: 1.1822 - Accuracy: 0.4412 - F1: 0.4458
sub_15:Test (Best Model) - Loss: 1.1894 - Accuracy: 0.4559 - F1: 0.4598
sub_15:Test (Best Model) - Loss: 1.1580 - Accuracy: 0.3971 - F1: 0.3918
sub_15:Test (Best Model) - Loss: 1.2475 - Accuracy: 0.4559 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.4706 - F1: 0.3909
sub_16:Test (Best Model) - Loss: 1.1183 - Accuracy: 0.4706 - F1: 0.4357
sub_16:Test (Best Model) - Loss: 1.2063 - Accuracy: 0.5441 - F1: 0.5056
sub_16:Test (Best Model) - Loss: 1.1410 - Accuracy: 0.5294 - F1: 0.5028
sub_16:Test (Best Model) - Loss: 1.0927 - Accuracy: 0.5735 - F1: 0.5139
sub_16:Test (Best Model) - Loss: 1.2527 - Accuracy: 0.3971 - F1: 0.3793
sub_16:Test (Best Model) - Loss: 1.2094 - Accuracy: 0.3676 - F1: 0.3353
sub_16:Test (Best Model) - Loss: 1.3289 - Accuracy: 0.3676 - F1: 0.3210
sub_16:Test (Best Model) - Loss: 1.2412 - Accuracy: 0.3971 - F1: 0.3530
sub_16:Test (Best Model) - Loss: 1.4739 - Accuracy: 0.4265 - F1: 0.4090
sub_16:Test (Best Model) - Loss: 1.2018 - Accuracy: 0.4559 - F1: 0.3568
sub_16:Test (Best Model) - Loss: 1.1364 - Accuracy: 0.5000 - F1: 0.4334
sub_16:Test (Best Model) - Loss: 1.1553 - Accuracy: 0.5294 - F1: 0.4961
sub_16:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4706 - F1: 0.4455
sub_16:Test (Best Model) - Loss: 1.1454 - Accuracy: 0.5588 - F1: 0.5015
sub_17:Test (Best Model) - Loss: 1.2396 - Accuracy: 0.4348 - F1: 0.3815
sub_17:Test (Best Model) - Loss: 1.1334 - Accuracy: 0.4638 - F1: 0.4595
sub_17:Test (Best Model) - Loss: 1.1705 - Accuracy: 0.4783 - F1: 0.4855
sub_17:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.4348 - F1: 0.4325
sub_17:Test (Best Model) - Loss: 1.1976 - Accuracy: 0.3913 - F1: 0.3730
sub_17:Test (Best Model) - Loss: 1.4689 - Accuracy: 0.3623 - F1: 0.3175
sub_17:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.3913 - F1: 0.3436
sub_17:Test (Best Model) - Loss: 1.4850 - Accuracy: 0.4493 - F1: 0.3935
sub_17:Test (Best Model) - Loss: 1.4483 - Accuracy: 0.4348 - F1: 0.3945
sub_17:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.4348 - F1: 0.3902
sub_17:Test (Best Model) - Loss: 1.1849 - Accuracy: 0.4265 - F1: 0.4098
sub_17:Test (Best Model) - Loss: 1.2021 - Accuracy: 0.4706 - F1: 0.4573
sub_17:Test (Best Model) - Loss: 1.2352 - Accuracy: 0.4265 - F1: 0.4378
sub_17:Test (Best Model) - Loss: 1.2518 - Accuracy: 0.4412 - F1: 0.4442
sub_17:Test (Best Model) - Loss: 1.2420 - Accuracy: 0.4265 - F1: 0.4329
sub_18:Test (Best Model) - Loss: 1.2420 - Accuracy: 0.3768 - F1: 0.3863
sub_18:Test (Best Model) - Loss: 1.2312 - Accuracy: 0.4058 - F1: 0.4321
sub_18:Test (Best Model) - Loss: 1.2039 - Accuracy: 0.4348 - F1: 0.4186
sub_18:Test (Best Model) - Loss: 1.2364 - Accuracy: 0.4058 - F1: 0.4328
sub_18:Test (Best Model) - Loss: 1.2605 - Accuracy: 0.4058 - F1: 0.4252
sub_18:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.3235 - F1: 0.3283
sub_18:Test (Best Model) - Loss: 1.3147 - Accuracy: 0.3824 - F1: 0.4151
sub_18:Test (Best Model) - Loss: 1.3514 - Accuracy: 0.3971 - F1: 0.4244
sub_18:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3382 - F1: 0.3673
sub_18:Test (Best Model) - Loss: 1.3457 - Accuracy: 0.3824 - F1: 0.4123
sub_18:Test (Best Model) - Loss: 1.2415 - Accuracy: 0.4118 - F1: 0.4278
sub_18:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.3529 - F1: 0.3725
sub_18:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.2647 - F1: 0.2828
sub_18:Test (Best Model) - Loss: 1.2535 - Accuracy: 0.3971 - F1: 0.4169
sub_18:Test (Best Model) - Loss: 1.2601 - Accuracy: 0.2941 - F1: 0.3196
sub_19:Test (Best Model) - Loss: 1.5508 - Accuracy: 0.2647 - F1: 0.2388
sub_19:Test (Best Model) - Loss: 1.4536 - Accuracy: 0.2647 - F1: 0.2589
sub_19:Test (Best Model) - Loss: 1.4319 - Accuracy: 0.2647 - F1: 0.2991
sub_19:Test (Best Model) - Loss: 1.3963 - Accuracy: 0.2941 - F1: 0.2939
sub_19:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.3235 - F1: 0.3480
sub_19:Test (Best Model) - Loss: 1.2496 - Accuracy: 0.3971 - F1: 0.3846
sub_19:Test (Best Model) - Loss: 1.2446 - Accuracy: 0.4559 - F1: 0.4251
sub_19:Test (Best Model) - Loss: 1.2264 - Accuracy: 0.4706 - F1: 0.4572
sub_19:Test (Best Model) - Loss: 1.2030 - Accuracy: 0.5000 - F1: 0.4964
sub_19:Test (Best Model) - Loss: 1.2080 - Accuracy: 0.4706 - F1: 0.4714
sub_19:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.3529 - F1: 0.3346
sub_19:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.2794 - F1: 0.2815
sub_19:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.3676 - F1: 0.3471
sub_19:Test (Best Model) - Loss: 1.3702 - Accuracy: 0.3235 - F1: 0.3441
sub_19:Test (Best Model) - Loss: 1.2706 - Accuracy: 0.3676 - F1: 0.3722
sub_20:Test (Best Model) - Loss: 1.0890 - Accuracy: 0.5882 - F1: 0.6046
sub_20:Test (Best Model) - Loss: 1.1244 - Accuracy: 0.5441 - F1: 0.5597
sub_20:Test (Best Model) - Loss: 1.1675 - Accuracy: 0.5000 - F1: 0.5162
sub_20:Test (Best Model) - Loss: 1.1064 - Accuracy: 0.5147 - F1: 0.5247
sub_20:Test (Best Model) - Loss: 1.1405 - Accuracy: 0.5147 - F1: 0.5314
sub_20:Test (Best Model) - Loss: 1.2169 - Accuracy: 0.4265 - F1: 0.4300
sub_20:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.4853 - F1: 0.5137
sub_20:Test (Best Model) - Loss: 1.2375 - Accuracy: 0.4118 - F1: 0.4363
sub_20:Test (Best Model) - Loss: 1.2550 - Accuracy: 0.3235 - F1: 0.3227
sub_20:Test (Best Model) - Loss: 1.2063 - Accuracy: 0.4559 - F1: 0.4593
sub_20:Test (Best Model) - Loss: 1.1728 - Accuracy: 0.4493 - F1: 0.4543
sub_20:Test (Best Model) - Loss: 1.2443 - Accuracy: 0.4058 - F1: 0.4119
sub_20:Test (Best Model) - Loss: 1.2433 - Accuracy: 0.3623 - F1: 0.3813
sub_20:Test (Best Model) - Loss: 1.1599 - Accuracy: 0.4638 - F1: 0.4758
sub_20:Test (Best Model) - Loss: 1.1529 - Accuracy: 0.4928 - F1: 0.5095
sub_21:Test (Best Model) - Loss: 1.1772 - Accuracy: 0.3676 - F1: 0.3401
sub_21:Test (Best Model) - Loss: 1.1700 - Accuracy: 0.3824 - F1: 0.3569
sub_21:Test (Best Model) - Loss: 1.2753 - Accuracy: 0.4118 - F1: 0.3968
sub_21:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.4265 - F1: 0.3793
sub_21:Test (Best Model) - Loss: 1.2772 - Accuracy: 0.4265 - F1: 0.4249
sub_21:Test (Best Model) - Loss: 1.1714 - Accuracy: 0.3382 - F1: 0.3117
sub_21:Test (Best Model) - Loss: 1.1544 - Accuracy: 0.4559 - F1: 0.4330
sub_21:Test (Best Model) - Loss: 1.1727 - Accuracy: 0.3529 - F1: 0.3090
sub_21:Test (Best Model) - Loss: 1.2095 - Accuracy: 0.3529 - F1: 0.3435
sub_21:Test (Best Model) - Loss: 1.1041 - Accuracy: 0.4412 - F1: 0.4076
sub_21:Test (Best Model) - Loss: 1.1741 - Accuracy: 0.4412 - F1: 0.4358
sub_21:Test (Best Model) - Loss: 1.2236 - Accuracy: 0.3676 - F1: 0.3360
sub_21:Test (Best Model) - Loss: 1.1756 - Accuracy: 0.4265 - F1: 0.3775
sub_21:Test (Best Model) - Loss: 1.1508 - Accuracy: 0.4412 - F1: 0.4102
sub_21:Test (Best Model) - Loss: 1.2008 - Accuracy: 0.3971 - F1: 0.3778
sub_22:Test (Best Model) - Loss: 1.3333 - Accuracy: 0.4118 - F1: 0.4332
sub_22:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.4706 - F1: 0.4706
sub_22:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3088 - F1: 0.3311
sub_22:Test (Best Model) - Loss: 1.3109 - Accuracy: 0.3824 - F1: 0.4100
sub_22:Test (Best Model) - Loss: 1.3518 - Accuracy: 0.3235 - F1: 0.3506
sub_22:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.3478 - F1: 0.3367
sub_22:Test (Best Model) - Loss: 1.2454 - Accuracy: 0.4058 - F1: 0.3738
sub_22:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.3478 - F1: 0.3215
sub_22:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.3478 - F1: 0.3592
sub_22:Test (Best Model) - Loss: 1.2835 - Accuracy: 0.3478 - F1: 0.3359
sub_22:Test (Best Model) - Loss: 1.2650 - Accuracy: 0.3529 - F1: 0.3788
sub_22:Test (Best Model) - Loss: 1.2983 - Accuracy: 0.3529 - F1: 0.3687
sub_22:Test (Best Model) - Loss: 1.2852 - Accuracy: 0.3971 - F1: 0.3999
sub_22:Test (Best Model) - Loss: 1.2679 - Accuracy: 0.4118 - F1: 0.4396
sub_22:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.3676 - F1: 0.4017
sub_23:Test (Best Model) - Loss: 1.1831 - Accuracy: 0.4203 - F1: 0.4385
sub_23:Test (Best Model) - Loss: 1.1311 - Accuracy: 0.4058 - F1: 0.4377
sub_23:Test (Best Model) - Loss: 1.1605 - Accuracy: 0.4058 - F1: 0.4137
sub_23:Test (Best Model) - Loss: 1.0649 - Accuracy: 0.5072 - F1: 0.5280
sub_23:Test (Best Model) - Loss: 1.1021 - Accuracy: 0.4493 - F1: 0.4561
sub_23:Test (Best Model) - Loss: 1.1706 - Accuracy: 0.4559 - F1: 0.4359
sub_23:Test (Best Model) - Loss: 1.1120 - Accuracy: 0.4853 - F1: 0.4877
sub_23:Test (Best Model) - Loss: 1.1784 - Accuracy: 0.5294 - F1: 0.5226
sub_23:Test (Best Model) - Loss: 1.1632 - Accuracy: 0.5147 - F1: 0.5112
sub_23:Test (Best Model) - Loss: 1.1725 - Accuracy: 0.5000 - F1: 0.4843
sub_23:Test (Best Model) - Loss: 1.2802 - Accuracy: 0.4058 - F1: 0.4067
sub_23:Test (Best Model) - Loss: 1.2674 - Accuracy: 0.4058 - F1: 0.3978
sub_23:Test (Best Model) - Loss: 1.1994 - Accuracy: 0.4203 - F1: 0.4033
sub_23:Test (Best Model) - Loss: 1.2388 - Accuracy: 0.4783 - F1: 0.4926
sub_23:Test (Best Model) - Loss: 1.2171 - Accuracy: 0.3913 - F1: 0.3881
sub_24:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3382 - F1: 0.3255
sub_24:Test (Best Model) - Loss: 1.3944 - Accuracy: 0.3676 - F1: 0.3633
sub_24:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.2500 - F1: 0.2489
sub_24:Test (Best Model) - Loss: 1.4169 - Accuracy: 0.2500 - F1: 0.2523
sub_24:Test (Best Model) - Loss: 1.3912 - Accuracy: 0.2500 - F1: 0.2545
sub_24:Test (Best Model) - Loss: 1.3451 - Accuracy: 0.3088 - F1: 0.2943
sub_24:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3676 - F1: 0.3641
sub_24:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.3529 - F1: 0.3419
sub_24:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.4706 - F1: 0.4676
sub_24:Test (Best Model) - Loss: 1.3229 - Accuracy: 0.3529 - F1: 0.3412
sub_24:Test (Best Model) - Loss: 1.4105 - Accuracy: 0.2500 - F1: 0.2517
sub_24:Test (Best Model) - Loss: 1.4631 - Accuracy: 0.2206 - F1: 0.2271
sub_24:Test (Best Model) - Loss: 1.4381 - Accuracy: 0.2500 - F1: 0.2545
sub_24:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.3824 - F1: 0.3742
sub_24:Test (Best Model) - Loss: 1.4411 - Accuracy: 0.3088 - F1: 0.2981
sub_25:Test (Best Model) - Loss: 1.1979 - Accuracy: 0.4783 - F1: 0.4495
sub_25:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.4783 - F1: 0.4399
sub_25:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.4638 - F1: 0.4304
sub_25:Test (Best Model) - Loss: 1.2295 - Accuracy: 0.4638 - F1: 0.4113
sub_25:Test (Best Model) - Loss: 1.2575 - Accuracy: 0.3623 - F1: 0.3571
sub_25:Test (Best Model) - Loss: 1.2949 - Accuracy: 0.4265 - F1: 0.3650
sub_25:Test (Best Model) - Loss: 1.2903 - Accuracy: 0.4853 - F1: 0.4208
sub_25:Test (Best Model) - Loss: 1.2399 - Accuracy: 0.4706 - F1: 0.4560
sub_25:Test (Best Model) - Loss: 1.2300 - Accuracy: 0.5147 - F1: 0.4295
sub_25:Test (Best Model) - Loss: 1.2242 - Accuracy: 0.5294 - F1: 0.4689
sub_25:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.4559 - F1: 0.4406
sub_25:Test (Best Model) - Loss: 1.2291 - Accuracy: 0.4412 - F1: 0.3958
sub_25:Test (Best Model) - Loss: 1.1586 - Accuracy: 0.5000 - F1: 0.4991
sub_25:Test (Best Model) - Loss: 1.2425 - Accuracy: 0.4265 - F1: 0.4138
sub_25:Test (Best Model) - Loss: 1.2046 - Accuracy: 0.4265 - F1: 0.3918
sub_26:Test (Best Model) - Loss: 1.1092 - Accuracy: 0.4783 - F1: 0.4949
sub_26:Test (Best Model) - Loss: 1.1833 - Accuracy: 0.4348 - F1: 0.4254
sub_26:Test (Best Model) - Loss: 1.1782 - Accuracy: 0.4203 - F1: 0.4401
sub_26:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.4783 - F1: 0.4742
sub_26:Test (Best Model) - Loss: 1.0052 - Accuracy: 0.5942 - F1: 0.6079
sub_26:Test (Best Model) - Loss: 1.2281 - Accuracy: 0.3824 - F1: 0.4175
sub_26:Test (Best Model) - Loss: 1.2155 - Accuracy: 0.4118 - F1: 0.4324
sub_26:Test (Best Model) - Loss: 1.2301 - Accuracy: 0.4118 - F1: 0.4278
sub_26:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.3676 - F1: 0.3801
sub_26:Test (Best Model) - Loss: 1.2245 - Accuracy: 0.3382 - F1: 0.3750
sub_26:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.5294 - F1: 0.5550
sub_26:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.4853 - F1: 0.5102
sub_26:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.4706 - F1: 0.4983
sub_26:Test (Best Model) - Loss: 1.1384 - Accuracy: 0.5147 - F1: 0.5269
sub_26:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.5000 - F1: 0.5272
sub_27:Test (Best Model) - Loss: 1.2396 - Accuracy: 0.4348 - F1: 0.3815
sub_27:Test (Best Model) - Loss: 1.1334 - Accuracy: 0.4638 - F1: 0.4595
sub_27:Test (Best Model) - Loss: 1.1705 - Accuracy: 0.4783 - F1: 0.4855
sub_27:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.4348 - F1: 0.4325
sub_27:Test (Best Model) - Loss: 1.1976 - Accuracy: 0.3913 - F1: 0.3730
sub_27:Test (Best Model) - Loss: 1.4689 - Accuracy: 0.3623 - F1: 0.3175
sub_27:Test (Best Model) - Loss: 1.4245 - Accuracy: 0.3913 - F1: 0.3436
sub_27:Test (Best Model) - Loss: 1.4850 - Accuracy: 0.4493 - F1: 0.3935
sub_27:Test (Best Model) - Loss: 1.4483 - Accuracy: 0.4348 - F1: 0.3945
sub_27:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.4348 - F1: 0.3902
sub_27:Test (Best Model) - Loss: 1.1849 - Accuracy: 0.4265 - F1: 0.4098
sub_27:Test (Best Model) - Loss: 1.2021 - Accuracy: 0.4706 - F1: 0.4573
sub_27:Test (Best Model) - Loss: 1.2352 - Accuracy: 0.4265 - F1: 0.4378
sub_27:Test (Best Model) - Loss: 1.2518 - Accuracy: 0.4412 - F1: 0.4442
sub_27:Test (Best Model) - Loss: 1.2420 - Accuracy: 0.4265 - F1: 0.4329
sub_28:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.3529 - F1: 0.3454
sub_28:Test (Best Model) - Loss: 1.4059 - Accuracy: 0.3382 - F1: 0.3324
sub_28:Test (Best Model) - Loss: 1.4992 - Accuracy: 0.2941 - F1: 0.2703
sub_28:Test (Best Model) - Loss: 1.4795 - Accuracy: 0.2941 - F1: 0.2805
sub_28:Test (Best Model) - Loss: 1.4964 - Accuracy: 0.2941 - F1: 0.3159
sub_28:Test (Best Model) - Loss: 1.7567 - Accuracy: 0.2500 - F1: 0.2303
sub_28:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.2794 - F1: 0.2463
sub_28:Test (Best Model) - Loss: 1.6583 - Accuracy: 0.2500 - F1: 0.2274
sub_28:Test (Best Model) - Loss: 1.6899 - Accuracy: 0.2353 - F1: 0.2045
sub_28:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.2794 - F1: 0.2585
sub_28:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.4265 - F1: 0.3814
sub_28:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.5000 - F1: 0.4891
sub_28:Test (Best Model) - Loss: 1.2511 - Accuracy: 0.4559 - F1: 0.4096
sub_28:Test (Best Model) - Loss: 1.2785 - Accuracy: 0.4559 - F1: 0.4326
sub_28:Test (Best Model) - Loss: 1.2918 - Accuracy: 0.4559 - F1: 0.3920
sub_29:Test (Best Model) - Loss: 1.1221 - Accuracy: 0.5147 - F1: 0.5314
sub_29:Test (Best Model) - Loss: 1.0631 - Accuracy: 0.5000 - F1: 0.5070
sub_29:Test (Best Model) - Loss: 1.0437 - Accuracy: 0.5147 - F1: 0.5048
sub_29:Test (Best Model) - Loss: 1.1162 - Accuracy: 0.5000 - F1: 0.4990
sub_29:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.5294 - F1: 0.5397
sub_29:Test (Best Model) - Loss: 0.9488 - Accuracy: 0.5882 - F1: 0.6081
sub_29:Test (Best Model) - Loss: 0.9917 - Accuracy: 0.5882 - F1: 0.6094
sub_29:Test (Best Model) - Loss: 0.9377 - Accuracy: 0.5441 - F1: 0.5656
sub_29:Test (Best Model) - Loss: 0.8900 - Accuracy: 0.6618 - F1: 0.6822
sub_29:Test (Best Model) - Loss: 0.9366 - Accuracy: 0.5882 - F1: 0.6150
sub_29:Test (Best Model) - Loss: 0.9183 - Accuracy: 0.5652 - F1: 0.5877
sub_29:Test (Best Model) - Loss: 0.9619 - Accuracy: 0.5797 - F1: 0.6005
sub_29:Test (Best Model) - Loss: 1.0093 - Accuracy: 0.5362 - F1: 0.5595
sub_29:Test (Best Model) - Loss: 0.9505 - Accuracy: 0.5797 - F1: 0.5998
sub_29:Test (Best Model) - Loss: 0.9793 - Accuracy: 0.5652 - F1: 0.5835

=== Summary Results ===

acc: 41.32 ± 6.74
F1: 41.07 ± 7.01
acc-in: 49.47 ± 6.27
F1-in: 48.24 ± 6.54
