lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.5568 - Accuracy: 0.4559 - F1: 0.4903
sub_1:Test (Best Model) - Loss: 1.7209 - Accuracy: 0.4559 - F1: 0.4737
sub_1:Test (Best Model) - Loss: 1.6595 - Accuracy: 0.3235 - F1: 0.3274
sub_1:Test (Best Model) - Loss: 1.4490 - Accuracy: 0.3971 - F1: 0.4333
sub_1:Test (Best Model) - Loss: 1.6901 - Accuracy: 0.4559 - F1: 0.4884
sub_1:Test (Best Model) - Loss: 1.8551 - Accuracy: 0.4058 - F1: 0.3732
sub_1:Test (Best Model) - Loss: 2.0268 - Accuracy: 0.4348 - F1: 0.4176
sub_1:Test (Best Model) - Loss: 2.0584 - Accuracy: 0.4203 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 2.0044 - Accuracy: 0.4348 - F1: 0.4043
sub_1:Test (Best Model) - Loss: 2.0366 - Accuracy: 0.3768 - F1: 0.3719
sub_1:Test (Best Model) - Loss: 1.5506 - Accuracy: 0.4412 - F1: 0.4347
sub_1:Test (Best Model) - Loss: 1.2962 - Accuracy: 0.5294 - F1: 0.5467
sub_1:Test (Best Model) - Loss: 1.2491 - Accuracy: 0.6029 - F1: 0.6151
sub_1:Test (Best Model) - Loss: 1.7610 - Accuracy: 0.3971 - F1: 0.3773
sub_1:Test (Best Model) - Loss: 1.3627 - Accuracy: 0.4265 - F1: 0.4092
sub_2:Test (Best Model) - Loss: 2.1393 - Accuracy: 0.2319 - F1: 0.2581
sub_2:Test (Best Model) - Loss: 2.2860 - Accuracy: 0.2754 - F1: 0.2906
sub_2:Test (Best Model) - Loss: 2.3566 - Accuracy: 0.2319 - F1: 0.2613
sub_2:Test (Best Model) - Loss: 2.5150 - Accuracy: 0.1739 - F1: 0.2133
sub_2:Test (Best Model) - Loss: 2.4018 - Accuracy: 0.2899 - F1: 0.3081
sub_2:Test (Best Model) - Loss: 1.9806 - Accuracy: 0.2941 - F1: 0.2959
sub_2:Test (Best Model) - Loss: 1.9748 - Accuracy: 0.2941 - F1: 0.2604
sub_2:Test (Best Model) - Loss: 1.6770 - Accuracy: 0.3824 - F1: 0.3895
sub_2:Test (Best Model) - Loss: 1.8695 - Accuracy: 0.3382 - F1: 0.3310
sub_2:Test (Best Model) - Loss: 1.9755 - Accuracy: 0.3529 - F1: 0.3573
sub_2:Test (Best Model) - Loss: 2.2470 - Accuracy: 0.3333 - F1: 0.2858
sub_2:Test (Best Model) - Loss: 2.0408 - Accuracy: 0.3478 - F1: 0.3130
sub_2:Test (Best Model) - Loss: 1.7777 - Accuracy: 0.4203 - F1: 0.4234
sub_2:Test (Best Model) - Loss: 1.9007 - Accuracy: 0.4058 - F1: 0.3740
sub_2:Test (Best Model) - Loss: 1.9186 - Accuracy: 0.3623 - F1: 0.3350
sub_3:Test (Best Model) - Loss: 2.4087 - Accuracy: 0.3235 - F1: 0.3187
sub_3:Test (Best Model) - Loss: 1.9899 - Accuracy: 0.2794 - F1: 0.2710
sub_3:Test (Best Model) - Loss: 2.4614 - Accuracy: 0.2794 - F1: 0.2830
sub_3:Test (Best Model) - Loss: 2.1787 - Accuracy: 0.2794 - F1: 0.2725
sub_3:Test (Best Model) - Loss: 2.3225 - Accuracy: 0.2941 - F1: 0.2924
sub_3:Test (Best Model) - Loss: 1.9118 - Accuracy: 0.2899 - F1: 0.2800
sub_3:Test (Best Model) - Loss: 2.3512 - Accuracy: 0.2609 - F1: 0.2644
sub_3:Test (Best Model) - Loss: 2.1583 - Accuracy: 0.2029 - F1: 0.1906
sub_3:Test (Best Model) - Loss: 1.9162 - Accuracy: 0.3913 - F1: 0.3816
sub_3:Test (Best Model) - Loss: 2.1622 - Accuracy: 0.3478 - F1: 0.3520
sub_3:Test (Best Model) - Loss: 2.3673 - Accuracy: 0.3043 - F1: 0.2867
sub_3:Test (Best Model) - Loss: 2.1603 - Accuracy: 0.3623 - F1: 0.3202
sub_3:Test (Best Model) - Loss: 2.5387 - Accuracy: 0.2754 - F1: 0.2555
sub_3:Test (Best Model) - Loss: 2.5899 - Accuracy: 0.2754 - F1: 0.2590
sub_3:Test (Best Model) - Loss: 2.4780 - Accuracy: 0.3333 - F1: 0.3084
sub_4:Test (Best Model) - Loss: 1.6577 - Accuracy: 0.4783 - F1: 0.4842
sub_4:Test (Best Model) - Loss: 1.4456 - Accuracy: 0.5797 - F1: 0.5892
sub_4:Test (Best Model) - Loss: 1.7725 - Accuracy: 0.4783 - F1: 0.5002
sub_4:Test (Best Model) - Loss: 1.6268 - Accuracy: 0.5217 - F1: 0.5245
sub_4:Test (Best Model) - Loss: 2.0327 - Accuracy: 0.4928 - F1: 0.4971
sub_4:Test (Best Model) - Loss: 1.7391 - Accuracy: 0.4493 - F1: 0.4226
sub_4:Test (Best Model) - Loss: 1.4754 - Accuracy: 0.4493 - F1: 0.4603
sub_4:Test (Best Model) - Loss: 1.1993 - Accuracy: 0.5507 - F1: 0.5576
sub_4:Test (Best Model) - Loss: 1.5109 - Accuracy: 0.4638 - F1: 0.4432
sub_4:Test (Best Model) - Loss: 1.3280 - Accuracy: 0.4928 - F1: 0.5046
sub_4:Test (Best Model) - Loss: 2.0853 - Accuracy: 0.3623 - F1: 0.3381
sub_4:Test (Best Model) - Loss: 1.7947 - Accuracy: 0.4493 - F1: 0.4464
sub_4:Test (Best Model) - Loss: 1.6518 - Accuracy: 0.3478 - F1: 0.3692
sub_4:Test (Best Model) - Loss: 1.8463 - Accuracy: 0.3913 - F1: 0.3773
sub_4:Test (Best Model) - Loss: 1.6731 - Accuracy: 0.4638 - F1: 0.4640
sub_5:Test (Best Model) - Loss: 2.7509 - Accuracy: 0.3824 - F1: 0.3569
sub_5:Test (Best Model) - Loss: 2.7339 - Accuracy: 0.3676 - F1: 0.3414
sub_5:Test (Best Model) - Loss: 3.2244 - Accuracy: 0.3971 - F1: 0.3765
sub_5:Test (Best Model) - Loss: 2.7415 - Accuracy: 0.4412 - F1: 0.4495
sub_5:Test (Best Model) - Loss: 3.1498 - Accuracy: 0.3088 - F1: 0.3084
sub_5:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.4853 - F1: 0.4559
sub_5:Test (Best Model) - Loss: 1.4311 - Accuracy: 0.5441 - F1: 0.5317
sub_5:Test (Best Model) - Loss: 1.4993 - Accuracy: 0.4706 - F1: 0.4806
sub_5:Test (Best Model) - Loss: 1.4816 - Accuracy: 0.5294 - F1: 0.5072
sub_5:Test (Best Model) - Loss: 1.5645 - Accuracy: 0.4853 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 1.6350 - Accuracy: 0.4265 - F1: 0.4222
sub_5:Test (Best Model) - Loss: 1.7201 - Accuracy: 0.3824 - F1: 0.3690
sub_5:Test (Best Model) - Loss: 1.7782 - Accuracy: 0.4118 - F1: 0.4106
sub_5:Test (Best Model) - Loss: 1.7009 - Accuracy: 0.3824 - F1: 0.3913
sub_5:Test (Best Model) - Loss: 1.2981 - Accuracy: 0.4412 - F1: 0.4480
sub_6:Test (Best Model) - Loss: 1.3238 - Accuracy: 0.4853 - F1: 0.4823
sub_6:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.4853 - F1: 0.4885
sub_6:Test (Best Model) - Loss: 1.5029 - Accuracy: 0.4853 - F1: 0.4849
sub_6:Test (Best Model) - Loss: 1.2593 - Accuracy: 0.4412 - F1: 0.4371
sub_6:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.5294 - F1: 0.5239
sub_6:Test (Best Model) - Loss: 1.8577 - Accuracy: 0.4058 - F1: 0.3602
sub_6:Test (Best Model) - Loss: 1.7761 - Accuracy: 0.4058 - F1: 0.3589
sub_6:Test (Best Model) - Loss: 1.8973 - Accuracy: 0.3478 - F1: 0.2762
sub_6:Test (Best Model) - Loss: 1.7992 - Accuracy: 0.4348 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 2.1920 - Accuracy: 0.3623 - F1: 0.2755
sub_6:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.3913 - F1: 0.3912
sub_6:Test (Best Model) - Loss: 1.9671 - Accuracy: 0.3768 - F1: 0.3664
sub_6:Test (Best Model) - Loss: 1.6871 - Accuracy: 0.4928 - F1: 0.4950
sub_6:Test (Best Model) - Loss: 1.5321 - Accuracy: 0.5217 - F1: 0.5288
sub_6:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.4058 - F1: 0.4138
sub_7:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.5294 - F1: 0.4832
sub_7:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.6176 - F1: 0.5881
sub_7:Test (Best Model) - Loss: 1.4131 - Accuracy: 0.4853 - F1: 0.4633
sub_7:Test (Best Model) - Loss: 1.1287 - Accuracy: 0.5882 - F1: 0.5779
sub_7:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.5441 - F1: 0.5198
sub_7:Test (Best Model) - Loss: 2.2969 - Accuracy: 0.3382 - F1: 0.3150
sub_7:Test (Best Model) - Loss: 2.3769 - Accuracy: 0.3971 - F1: 0.3698
sub_7:Test (Best Model) - Loss: 1.8801 - Accuracy: 0.4412 - F1: 0.4214
sub_7:Test (Best Model) - Loss: 2.3954 - Accuracy: 0.3676 - F1: 0.3510
sub_7:Test (Best Model) - Loss: 2.0138 - Accuracy: 0.4265 - F1: 0.3963
sub_7:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.4412 - F1: 0.4372
sub_7:Test (Best Model) - Loss: 1.7193 - Accuracy: 0.4559 - F1: 0.4518
sub_7:Test (Best Model) - Loss: 1.8129 - Accuracy: 0.3824 - F1: 0.3872
sub_7:Test (Best Model) - Loss: 1.5272 - Accuracy: 0.5000 - F1: 0.4988
sub_7:Test (Best Model) - Loss: 1.8079 - Accuracy: 0.3088 - F1: 0.3079
sub_8:Test (Best Model) - Loss: 2.5779 - Accuracy: 0.2647 - F1: 0.2729
sub_8:Test (Best Model) - Loss: 2.8020 - Accuracy: 0.2353 - F1: 0.2281
sub_8:Test (Best Model) - Loss: 2.6952 - Accuracy: 0.2647 - F1: 0.3012
sub_8:Test (Best Model) - Loss: 2.4146 - Accuracy: 0.3382 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 2.2977 - Accuracy: 0.3382 - F1: 0.3298
sub_8:Test (Best Model) - Loss: 1.8433 - Accuracy: 0.3529 - F1: 0.3580
sub_8:Test (Best Model) - Loss: 2.0450 - Accuracy: 0.2941 - F1: 0.2901
sub_8:Test (Best Model) - Loss: 1.7124 - Accuracy: 0.3235 - F1: 0.3401
sub_8:Test (Best Model) - Loss: 2.1609 - Accuracy: 0.3529 - F1: 0.3442
sub_8:Test (Best Model) - Loss: 2.1902 - Accuracy: 0.2500 - F1: 0.2524
sub_8:Test (Best Model) - Loss: 2.7531 - Accuracy: 0.1765 - F1: 0.1412
sub_8:Test (Best Model) - Loss: 2.5282 - Accuracy: 0.2647 - F1: 0.2743
sub_8:Test (Best Model) - Loss: 2.7430 - Accuracy: 0.3235 - F1: 0.3337
sub_8:Test (Best Model) - Loss: 2.5034 - Accuracy: 0.3971 - F1: 0.4042
sub_8:Test (Best Model) - Loss: 2.1279 - Accuracy: 0.2794 - F1: 0.2769
sub_9:Test (Best Model) - Loss: 1.7019 - Accuracy: 0.4706 - F1: 0.4682
sub_9:Test (Best Model) - Loss: 1.7149 - Accuracy: 0.4853 - F1: 0.5127
sub_9:Test (Best Model) - Loss: 1.6512 - Accuracy: 0.4706 - F1: 0.4959
sub_9:Test (Best Model) - Loss: 1.5708 - Accuracy: 0.5588 - F1: 0.5774
sub_9:Test (Best Model) - Loss: 1.3784 - Accuracy: 0.5735 - F1: 0.5824
sub_9:Test (Best Model) - Loss: 3.2571 - Accuracy: 0.2647 - F1: 0.2656
sub_9:Test (Best Model) - Loss: 3.0059 - Accuracy: 0.3529 - F1: 0.3497
sub_9:Test (Best Model) - Loss: 2.5980 - Accuracy: 0.2794 - F1: 0.2781
sub_9:Test (Best Model) - Loss: 2.3959 - Accuracy: 0.3824 - F1: 0.3770
sub_9:Test (Best Model) - Loss: 2.6075 - Accuracy: 0.2941 - F1: 0.3025
sub_9:Test (Best Model) - Loss: 2.3122 - Accuracy: 0.4706 - F1: 0.4858
sub_9:Test (Best Model) - Loss: 2.3332 - Accuracy: 0.4559 - F1: 0.4821
sub_9:Test (Best Model) - Loss: 2.2797 - Accuracy: 0.4412 - F1: 0.4724
sub_9:Test (Best Model) - Loss: 2.5079 - Accuracy: 0.3529 - F1: 0.3732
sub_9:Test (Best Model) - Loss: 2.2309 - Accuracy: 0.4265 - F1: 0.4573
sub_10:Test (Best Model) - Loss: 2.4058 - Accuracy: 0.2353 - F1: 0.2192
sub_10:Test (Best Model) - Loss: 2.1024 - Accuracy: 0.3529 - F1: 0.3296
sub_10:Test (Best Model) - Loss: 2.2045 - Accuracy: 0.2647 - F1: 0.2330
sub_10:Test (Best Model) - Loss: 2.3888 - Accuracy: 0.3088 - F1: 0.2993
sub_10:Test (Best Model) - Loss: 2.1541 - Accuracy: 0.3382 - F1: 0.3494
sub_10:Test (Best Model) - Loss: 2.0705 - Accuracy: 0.2647 - F1: 0.2634
sub_10:Test (Best Model) - Loss: 2.1173 - Accuracy: 0.2647 - F1: 0.2653
sub_10:Test (Best Model) - Loss: 2.0788 - Accuracy: 0.3088 - F1: 0.3179
sub_10:Test (Best Model) - Loss: 1.9039 - Accuracy: 0.2941 - F1: 0.2873
sub_10:Test (Best Model) - Loss: 2.2382 - Accuracy: 0.3088 - F1: 0.2997
sub_10:Test (Best Model) - Loss: 2.8429 - Accuracy: 0.2754 - F1: 0.2713
sub_10:Test (Best Model) - Loss: 2.5357 - Accuracy: 0.2899 - F1: 0.2984
sub_10:Test (Best Model) - Loss: 2.1451 - Accuracy: 0.2609 - F1: 0.2488
sub_10:Test (Best Model) - Loss: 2.1716 - Accuracy: 0.2754 - F1: 0.2689
sub_10:Test (Best Model) - Loss: 2.1451 - Accuracy: 0.3478 - F1: 0.3480
sub_11:Test (Best Model) - Loss: 2.5834 - Accuracy: 0.3478 - F1: 0.3287
sub_11:Test (Best Model) - Loss: 2.3750 - Accuracy: 0.3043 - F1: 0.2932
sub_11:Test (Best Model) - Loss: 2.3191 - Accuracy: 0.3043 - F1: 0.3015
sub_11:Test (Best Model) - Loss: 2.4041 - Accuracy: 0.2899 - F1: 0.2844
sub_11:Test (Best Model) - Loss: 2.2555 - Accuracy: 0.3768 - F1: 0.3798
sub_11:Test (Best Model) - Loss: 2.3769 - Accuracy: 0.4783 - F1: 0.4286
sub_11:Test (Best Model) - Loss: 2.0144 - Accuracy: 0.5072 - F1: 0.4376
sub_11:Test (Best Model) - Loss: 2.0803 - Accuracy: 0.4203 - F1: 0.3472
sub_11:Test (Best Model) - Loss: 2.2186 - Accuracy: 0.3913 - F1: 0.3234
sub_11:Test (Best Model) - Loss: 2.0551 - Accuracy: 0.4783 - F1: 0.4294
sub_11:Test (Best Model) - Loss: 1.5148 - Accuracy: 0.4348 - F1: 0.4050
sub_11:Test (Best Model) - Loss: 1.9739 - Accuracy: 0.3913 - F1: 0.3362
sub_11:Test (Best Model) - Loss: 1.8274 - Accuracy: 0.4638 - F1: 0.4330
sub_11:Test (Best Model) - Loss: 1.5759 - Accuracy: 0.3913 - F1: 0.3475
sub_11:Test (Best Model) - Loss: 1.7156 - Accuracy: 0.4203 - F1: 0.3984
sub_12:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.5000 - F1: 0.4916
sub_12:Test (Best Model) - Loss: 1.2817 - Accuracy: 0.5294 - F1: 0.5225
sub_12:Test (Best Model) - Loss: 1.5047 - Accuracy: 0.5000 - F1: 0.4515
sub_12:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.6029 - F1: 0.6041
sub_12:Test (Best Model) - Loss: 1.3811 - Accuracy: 0.4853 - F1: 0.4999
sub_12:Test (Best Model) - Loss: 1.9457 - Accuracy: 0.4928 - F1: 0.4954
sub_12:Test (Best Model) - Loss: 1.4025 - Accuracy: 0.4783 - F1: 0.4489
sub_12:Test (Best Model) - Loss: 1.5037 - Accuracy: 0.4783 - F1: 0.4817
sub_12:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.5217 - F1: 0.5222
sub_12:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.4348 - F1: 0.4275
sub_12:Test (Best Model) - Loss: 1.6616 - Accuracy: 0.4853 - F1: 0.4602
sub_12:Test (Best Model) - Loss: 1.8076 - Accuracy: 0.3676 - F1: 0.3685
sub_12:Test (Best Model) - Loss: 1.8585 - Accuracy: 0.3676 - F1: 0.3475
sub_12:Test (Best Model) - Loss: 1.9331 - Accuracy: 0.4118 - F1: 0.4043
sub_12:Test (Best Model) - Loss: 1.8065 - Accuracy: 0.3676 - F1: 0.3632
sub_13:Test (Best Model) - Loss: 2.0769 - Accuracy: 0.4706 - F1: 0.4728
sub_13:Test (Best Model) - Loss: 2.1009 - Accuracy: 0.4265 - F1: 0.4455
sub_13:Test (Best Model) - Loss: 2.1123 - Accuracy: 0.4265 - F1: 0.4523
sub_13:Test (Best Model) - Loss: 2.2142 - Accuracy: 0.4118 - F1: 0.4435
sub_13:Test (Best Model) - Loss: 1.9895 - Accuracy: 0.4412 - F1: 0.4442
sub_13:Test (Best Model) - Loss: 2.3651 - Accuracy: 0.3768 - F1: 0.3825
sub_13:Test (Best Model) - Loss: 1.8595 - Accuracy: 0.4203 - F1: 0.4324
sub_13:Test (Best Model) - Loss: 2.1943 - Accuracy: 0.3478 - F1: 0.3679
sub_13:Test (Best Model) - Loss: 2.3369 - Accuracy: 0.3913 - F1: 0.3914
sub_13:Test (Best Model) - Loss: 2.3169 - Accuracy: 0.4058 - F1: 0.4193
sub_13:Test (Best Model) - Loss: 1.8548 - Accuracy: 0.3824 - F1: 0.3808
sub_13:Test (Best Model) - Loss: 1.8824 - Accuracy: 0.4265 - F1: 0.4263
sub_13:Test (Best Model) - Loss: 2.2178 - Accuracy: 0.3676 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 2.0160 - Accuracy: 0.3529 - F1: 0.3859
sub_13:Test (Best Model) - Loss: 1.8115 - Accuracy: 0.4559 - F1: 0.4686
sub_14:Test (Best Model) - Loss: 2.1090 - Accuracy: 0.3382 - F1: 0.3717
sub_14:Test (Best Model) - Loss: 2.0620 - Accuracy: 0.2941 - F1: 0.3125
sub_14:Test (Best Model) - Loss: 2.0628 - Accuracy: 0.3529 - F1: 0.3770
sub_14:Test (Best Model) - Loss: 2.1455 - Accuracy: 0.3529 - F1: 0.3653
sub_14:Test (Best Model) - Loss: 2.0703 - Accuracy: 0.3676 - F1: 0.3778
sub_14:Test (Best Model) - Loss: 2.1836 - Accuracy: 0.4118 - F1: 0.4379
sub_14:Test (Best Model) - Loss: 2.4171 - Accuracy: 0.4706 - F1: 0.4936
sub_14:Test (Best Model) - Loss: 2.2369 - Accuracy: 0.4265 - F1: 0.4565
sub_14:Test (Best Model) - Loss: 2.2499 - Accuracy: 0.4265 - F1: 0.4477
sub_14:Test (Best Model) - Loss: 2.3854 - Accuracy: 0.3235 - F1: 0.3492
sub_14:Test (Best Model) - Loss: 1.9615 - Accuracy: 0.4118 - F1: 0.4178
sub_14:Test (Best Model) - Loss: 2.2746 - Accuracy: 0.3971 - F1: 0.3818
sub_14:Test (Best Model) - Loss: 2.0510 - Accuracy: 0.3382 - F1: 0.3407
sub_14:Test (Best Model) - Loss: 1.8504 - Accuracy: 0.3529 - F1: 0.3567
sub_14:Test (Best Model) - Loss: 1.9739 - Accuracy: 0.3529 - F1: 0.3613
sub_15:Test (Best Model) - Loss: 2.0313 - Accuracy: 0.4706 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 2.9575 - Accuracy: 0.3676 - F1: 0.3800
sub_15:Test (Best Model) - Loss: 2.4623 - Accuracy: 0.4412 - F1: 0.4445
sub_15:Test (Best Model) - Loss: 1.5873 - Accuracy: 0.5000 - F1: 0.5346
sub_15:Test (Best Model) - Loss: 2.1765 - Accuracy: 0.4412 - F1: 0.4711
sub_15:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.5882 - F1: 0.5879
sub_15:Test (Best Model) - Loss: 1.9821 - Accuracy: 0.5000 - F1: 0.5052
sub_15:Test (Best Model) - Loss: 1.6371 - Accuracy: 0.5735 - F1: 0.5741
sub_15:Test (Best Model) - Loss: 1.4601 - Accuracy: 0.4706 - F1: 0.4883
sub_15:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.5294 - F1: 0.5385
sub_15:Test (Best Model) - Loss: 2.0232 - Accuracy: 0.4118 - F1: 0.4084
sub_15:Test (Best Model) - Loss: 1.8654 - Accuracy: 0.4118 - F1: 0.4214
sub_15:Test (Best Model) - Loss: 1.9261 - Accuracy: 0.4559 - F1: 0.4541
sub_15:Test (Best Model) - Loss: 1.9570 - Accuracy: 0.3529 - F1: 0.3588
sub_15:Test (Best Model) - Loss: 2.0583 - Accuracy: 0.3824 - F1: 0.3814
sub_16:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.5441 - F1: 0.4973
sub_16:Test (Best Model) - Loss: 1.4053 - Accuracy: 0.5147 - F1: 0.4720
sub_16:Test (Best Model) - Loss: 1.2943 - Accuracy: 0.4706 - F1: 0.4586
sub_16:Test (Best Model) - Loss: 1.2791 - Accuracy: 0.4559 - F1: 0.4414
sub_16:Test (Best Model) - Loss: 1.1529 - Accuracy: 0.5441 - F1: 0.5117
sub_16:Test (Best Model) - Loss: 1.9097 - Accuracy: 0.4559 - F1: 0.4605
sub_16:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.4412 - F1: 0.4356
sub_16:Test (Best Model) - Loss: 1.7562 - Accuracy: 0.4412 - F1: 0.4184
sub_16:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.4559 - F1: 0.4493
sub_16:Test (Best Model) - Loss: 2.7329 - Accuracy: 0.3824 - F1: 0.3864
sub_16:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.5441 - F1: 0.4766
sub_16:Test (Best Model) - Loss: 1.4363 - Accuracy: 0.4853 - F1: 0.4340
sub_16:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.5000 - F1: 0.4700
sub_16:Test (Best Model) - Loss: 1.4223 - Accuracy: 0.4559 - F1: 0.4348
sub_16:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.5588 - F1: 0.5302
sub_17:Test (Best Model) - Loss: 1.6715 - Accuracy: 0.5072 - F1: 0.5044
sub_17:Test (Best Model) - Loss: 1.4479 - Accuracy: 0.4203 - F1: 0.4248
sub_17:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.3768 - F1: 0.3640
sub_17:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.4493 - F1: 0.4489
sub_17:Test (Best Model) - Loss: 1.4836 - Accuracy: 0.4638 - F1: 0.4540
sub_17:Test (Best Model) - Loss: 2.4630 - Accuracy: 0.3623 - F1: 0.3291
sub_17:Test (Best Model) - Loss: 2.9192 - Accuracy: 0.3478 - F1: 0.3178
sub_17:Test (Best Model) - Loss: 2.3601 - Accuracy: 0.4928 - F1: 0.4406
sub_17:Test (Best Model) - Loss: 2.8055 - Accuracy: 0.3913 - F1: 0.3447
sub_17:Test (Best Model) - Loss: 2.3612 - Accuracy: 0.3768 - F1: 0.3240
sub_17:Test (Best Model) - Loss: 1.5251 - Accuracy: 0.5000 - F1: 0.4886
sub_17:Test (Best Model) - Loss: 1.7431 - Accuracy: 0.4412 - F1: 0.4420
sub_17:Test (Best Model) - Loss: 2.0111 - Accuracy: 0.3971 - F1: 0.3959
sub_17:Test (Best Model) - Loss: 1.9011 - Accuracy: 0.4412 - F1: 0.4479
sub_17:Test (Best Model) - Loss: 2.0237 - Accuracy: 0.3971 - F1: 0.3845
sub_18:Test (Best Model) - Loss: 1.7185 - Accuracy: 0.3913 - F1: 0.3936
sub_18:Test (Best Model) - Loss: 1.6938 - Accuracy: 0.3913 - F1: 0.4007
sub_18:Test (Best Model) - Loss: 1.6971 - Accuracy: 0.3913 - F1: 0.3752
sub_18:Test (Best Model) - Loss: 1.8283 - Accuracy: 0.3768 - F1: 0.3805
sub_18:Test (Best Model) - Loss: 1.4923 - Accuracy: 0.4493 - F1: 0.4749
sub_18:Test (Best Model) - Loss: 2.1886 - Accuracy: 0.3529 - F1: 0.3717
sub_18:Test (Best Model) - Loss: 1.8777 - Accuracy: 0.3676 - F1: 0.3853
sub_18:Test (Best Model) - Loss: 1.9898 - Accuracy: 0.2647 - F1: 0.2917
sub_18:Test (Best Model) - Loss: 2.1428 - Accuracy: 0.3382 - F1: 0.3666
sub_18:Test (Best Model) - Loss: 2.1649 - Accuracy: 0.2941 - F1: 0.3221
sub_18:Test (Best Model) - Loss: 1.7710 - Accuracy: 0.3235 - F1: 0.3456
sub_18:Test (Best Model) - Loss: 2.1898 - Accuracy: 0.2794 - F1: 0.3073
sub_18:Test (Best Model) - Loss: 1.9979 - Accuracy: 0.2647 - F1: 0.2876
sub_18:Test (Best Model) - Loss: 1.7910 - Accuracy: 0.3529 - F1: 0.3802
sub_18:Test (Best Model) - Loss: 1.7923 - Accuracy: 0.3235 - F1: 0.3507
sub_19:Test (Best Model) - Loss: 2.4426 - Accuracy: 0.1765 - F1: 0.1320
sub_19:Test (Best Model) - Loss: 2.2632 - Accuracy: 0.2353 - F1: 0.2191
sub_19:Test (Best Model) - Loss: 2.3860 - Accuracy: 0.2059 - F1: 0.2110
sub_19:Test (Best Model) - Loss: 2.1725 - Accuracy: 0.3235 - F1: 0.2988
sub_19:Test (Best Model) - Loss: 2.1822 - Accuracy: 0.3088 - F1: 0.2860
sub_19:Test (Best Model) - Loss: 2.0870 - Accuracy: 0.3676 - F1: 0.3346
sub_19:Test (Best Model) - Loss: 2.1019 - Accuracy: 0.3824 - F1: 0.3494
sub_19:Test (Best Model) - Loss: 1.8967 - Accuracy: 0.3971 - F1: 0.3839
sub_19:Test (Best Model) - Loss: 1.8714 - Accuracy: 0.3382 - F1: 0.2820
sub_19:Test (Best Model) - Loss: 2.1438 - Accuracy: 0.3971 - F1: 0.3655
sub_19:Test (Best Model) - Loss: 2.4250 - Accuracy: 0.3382 - F1: 0.3273
sub_19:Test (Best Model) - Loss: 2.7691 - Accuracy: 0.3235 - F1: 0.3284
sub_19:Test (Best Model) - Loss: 2.2816 - Accuracy: 0.3235 - F1: 0.2963
sub_19:Test (Best Model) - Loss: 2.5085 - Accuracy: 0.2941 - F1: 0.3297
sub_19:Test (Best Model) - Loss: 2.0696 - Accuracy: 0.4118 - F1: 0.4227
sub_20:Test (Best Model) - Loss: 1.6752 - Accuracy: 0.5294 - F1: 0.5298
sub_20:Test (Best Model) - Loss: 1.8858 - Accuracy: 0.4853 - F1: 0.4837
sub_20:Test (Best Model) - Loss: 1.9605 - Accuracy: 0.5000 - F1: 0.4886
sub_20:Test (Best Model) - Loss: 1.7367 - Accuracy: 0.4559 - F1: 0.4716
sub_20:Test (Best Model) - Loss: 2.1047 - Accuracy: 0.4853 - F1: 0.4897
sub_20:Test (Best Model) - Loss: 1.7136 - Accuracy: 0.4118 - F1: 0.4334
sub_20:Test (Best Model) - Loss: 1.9929 - Accuracy: 0.4265 - F1: 0.4492
sub_20:Test (Best Model) - Loss: 2.2364 - Accuracy: 0.3971 - F1: 0.4161
sub_20:Test (Best Model) - Loss: 2.0017 - Accuracy: 0.3676 - F1: 0.3772
sub_20:Test (Best Model) - Loss: 1.9275 - Accuracy: 0.4706 - F1: 0.4736
sub_20:Test (Best Model) - Loss: 2.1457 - Accuracy: 0.4058 - F1: 0.4108
sub_20:Test (Best Model) - Loss: 2.0967 - Accuracy: 0.4493 - F1: 0.4504
sub_20:Test (Best Model) - Loss: 2.3832 - Accuracy: 0.3623 - F1: 0.3597
sub_20:Test (Best Model) - Loss: 2.1702 - Accuracy: 0.4783 - F1: 0.4949
sub_20:Test (Best Model) - Loss: 2.1030 - Accuracy: 0.4203 - F1: 0.4295
sub_21:Test (Best Model) - Loss: 2.0450 - Accuracy: 0.3971 - F1: 0.3897
sub_21:Test (Best Model) - Loss: 1.9714 - Accuracy: 0.4118 - F1: 0.3865
sub_21:Test (Best Model) - Loss: 2.1773 - Accuracy: 0.4706 - F1: 0.4408
sub_21:Test (Best Model) - Loss: 2.1534 - Accuracy: 0.4118 - F1: 0.3906
sub_21:Test (Best Model) - Loss: 2.3209 - Accuracy: 0.3824 - F1: 0.3598
sub_21:Test (Best Model) - Loss: 1.5670 - Accuracy: 0.3971 - F1: 0.3885
sub_21:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.4559 - F1: 0.4501
sub_21:Test (Best Model) - Loss: 1.4403 - Accuracy: 0.4412 - F1: 0.4189
sub_21:Test (Best Model) - Loss: 1.5630 - Accuracy: 0.4412 - F1: 0.4262
sub_21:Test (Best Model) - Loss: 1.7026 - Accuracy: 0.5000 - F1: 0.4617
sub_21:Test (Best Model) - Loss: 1.5614 - Accuracy: 0.3676 - F1: 0.3490
sub_21:Test (Best Model) - Loss: 1.7746 - Accuracy: 0.3824 - F1: 0.3696
sub_21:Test (Best Model) - Loss: 1.8062 - Accuracy: 0.4118 - F1: 0.3784
sub_21:Test (Best Model) - Loss: 1.7349 - Accuracy: 0.3971 - F1: 0.3736
sub_21:Test (Best Model) - Loss: 1.7417 - Accuracy: 0.3676 - F1: 0.3326
sub_22:Test (Best Model) - Loss: 2.1377 - Accuracy: 0.3971 - F1: 0.4105
sub_22:Test (Best Model) - Loss: 2.2514 - Accuracy: 0.4118 - F1: 0.4277
sub_22:Test (Best Model) - Loss: 2.3721 - Accuracy: 0.3088 - F1: 0.3331
sub_22:Test (Best Model) - Loss: 2.0975 - Accuracy: 0.4412 - F1: 0.4569
sub_22:Test (Best Model) - Loss: 2.2934 - Accuracy: 0.4265 - F1: 0.4443
sub_22:Test (Best Model) - Loss: 1.6697 - Accuracy: 0.3478 - F1: 0.3437
sub_22:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.3043 - F1: 0.2869
sub_22:Test (Best Model) - Loss: 1.7541 - Accuracy: 0.3913 - F1: 0.3939
sub_22:Test (Best Model) - Loss: 1.7207 - Accuracy: 0.3478 - F1: 0.3385
sub_22:Test (Best Model) - Loss: 1.7054 - Accuracy: 0.2899 - F1: 0.2919
sub_22:Test (Best Model) - Loss: 1.7653 - Accuracy: 0.3529 - F1: 0.3752
sub_22:Test (Best Model) - Loss: 1.5682 - Accuracy: 0.4118 - F1: 0.4255
sub_22:Test (Best Model) - Loss: 1.8645 - Accuracy: 0.4118 - F1: 0.4095
sub_22:Test (Best Model) - Loss: 1.6939 - Accuracy: 0.3382 - F1: 0.3721
sub_22:Test (Best Model) - Loss: 1.6699 - Accuracy: 0.4265 - F1: 0.4647
sub_23:Test (Best Model) - Loss: 1.9236 - Accuracy: 0.3623 - F1: 0.3849
sub_23:Test (Best Model) - Loss: 1.8347 - Accuracy: 0.3478 - F1: 0.3347
sub_23:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.5072 - F1: 0.5217
sub_23:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.4928 - F1: 0.4981
sub_23:Test (Best Model) - Loss: 1.6651 - Accuracy: 0.4638 - F1: 0.4908
sub_23:Test (Best Model) - Loss: 1.7648 - Accuracy: 0.4559 - F1: 0.4224
sub_23:Test (Best Model) - Loss: 1.4431 - Accuracy: 0.4265 - F1: 0.4127
sub_23:Test (Best Model) - Loss: 1.5135 - Accuracy: 0.4853 - F1: 0.4627
sub_23:Test (Best Model) - Loss: 1.3388 - Accuracy: 0.5000 - F1: 0.5072
sub_23:Test (Best Model) - Loss: 1.6670 - Accuracy: 0.5000 - F1: 0.4809
sub_23:Test (Best Model) - Loss: 2.8091 - Accuracy: 0.3043 - F1: 0.2537
sub_23:Test (Best Model) - Loss: 2.5958 - Accuracy: 0.3768 - F1: 0.3725
sub_23:Test (Best Model) - Loss: 2.6312 - Accuracy: 0.3623 - F1: 0.3435
sub_23:Test (Best Model) - Loss: 2.7770 - Accuracy: 0.4058 - F1: 0.3660
sub_23:Test (Best Model) - Loss: 2.5414 - Accuracy: 0.4203 - F1: 0.4088
sub_24:Test (Best Model) - Loss: 2.1180 - Accuracy: 0.3676 - F1: 0.3690
sub_24:Test (Best Model) - Loss: 2.0819 - Accuracy: 0.3382 - F1: 0.3376
sub_24:Test (Best Model) - Loss: 2.0784 - Accuracy: 0.2794 - F1: 0.2805
sub_24:Test (Best Model) - Loss: 2.2283 - Accuracy: 0.3382 - F1: 0.3215
sub_24:Test (Best Model) - Loss: 2.1602 - Accuracy: 0.2941 - F1: 0.2930
sub_24:Test (Best Model) - Loss: 1.7347 - Accuracy: 0.3529 - F1: 0.3532
sub_24:Test (Best Model) - Loss: 1.8382 - Accuracy: 0.3235 - F1: 0.3286
sub_24:Test (Best Model) - Loss: 1.5655 - Accuracy: 0.3824 - F1: 0.3689
sub_24:Test (Best Model) - Loss: 1.4927 - Accuracy: 0.3971 - F1: 0.3911
sub_24:Test (Best Model) - Loss: 1.6845 - Accuracy: 0.3382 - F1: 0.3162
sub_24:Test (Best Model) - Loss: 2.0192 - Accuracy: 0.2794 - F1: 0.2897
sub_24:Test (Best Model) - Loss: 2.1868 - Accuracy: 0.2941 - F1: 0.2964
sub_24:Test (Best Model) - Loss: 2.2109 - Accuracy: 0.2794 - F1: 0.2780
sub_24:Test (Best Model) - Loss: 1.9455 - Accuracy: 0.3676 - F1: 0.3697
sub_24:Test (Best Model) - Loss: 1.8879 - Accuracy: 0.3088 - F1: 0.3044
sub_25:Test (Best Model) - Loss: 1.4820 - Accuracy: 0.4783 - F1: 0.4498
sub_25:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.4348 - F1: 0.3842
sub_25:Test (Best Model) - Loss: 1.7448 - Accuracy: 0.4348 - F1: 0.4010
sub_25:Test (Best Model) - Loss: 1.6644 - Accuracy: 0.4638 - F1: 0.4353
sub_25:Test (Best Model) - Loss: 2.0646 - Accuracy: 0.3623 - F1: 0.3235
sub_25:Test (Best Model) - Loss: 1.7678 - Accuracy: 0.4559 - F1: 0.4054
sub_25:Test (Best Model) - Loss: 2.0191 - Accuracy: 0.3971 - F1: 0.3560
sub_25:Test (Best Model) - Loss: 1.9769 - Accuracy: 0.4853 - F1: 0.4334
sub_25:Test (Best Model) - Loss: 1.8332 - Accuracy: 0.4706 - F1: 0.4162
sub_25:Test (Best Model) - Loss: 1.8887 - Accuracy: 0.5000 - F1: 0.4250
sub_25:Test (Best Model) - Loss: 1.7135 - Accuracy: 0.4118 - F1: 0.4037
sub_25:Test (Best Model) - Loss: 1.7241 - Accuracy: 0.4706 - F1: 0.4527
sub_25:Test (Best Model) - Loss: 1.5274 - Accuracy: 0.5441 - F1: 0.5134
sub_25:Test (Best Model) - Loss: 1.5415 - Accuracy: 0.4118 - F1: 0.3611
sub_25:Test (Best Model) - Loss: 1.6717 - Accuracy: 0.4412 - F1: 0.3681
sub_26:Test (Best Model) - Loss: 1.4453 - Accuracy: 0.4348 - F1: 0.4406
sub_26:Test (Best Model) - Loss: 1.7520 - Accuracy: 0.3768 - F1: 0.3812
sub_26:Test (Best Model) - Loss: 1.6607 - Accuracy: 0.4493 - F1: 0.4606
sub_26:Test (Best Model) - Loss: 1.2935 - Accuracy: 0.5072 - F1: 0.5178
sub_26:Test (Best Model) - Loss: 1.4010 - Accuracy: 0.5072 - F1: 0.5187
sub_26:Test (Best Model) - Loss: 1.7493 - Accuracy: 0.3529 - F1: 0.3830
sub_26:Test (Best Model) - Loss: 1.9073 - Accuracy: 0.3088 - F1: 0.3277
sub_26:Test (Best Model) - Loss: 1.9240 - Accuracy: 0.3235 - F1: 0.3464
sub_26:Test (Best Model) - Loss: 1.8838 - Accuracy: 0.3971 - F1: 0.4167
sub_26:Test (Best Model) - Loss: 1.9468 - Accuracy: 0.2941 - F1: 0.3277
sub_26:Test (Best Model) - Loss: 1.6329 - Accuracy: 0.4853 - F1: 0.5086
sub_26:Test (Best Model) - Loss: 2.1655 - Accuracy: 0.4412 - F1: 0.4621
sub_26:Test (Best Model) - Loss: 1.9899 - Accuracy: 0.4412 - F1: 0.4567
sub_26:Test (Best Model) - Loss: 1.6605 - Accuracy: 0.5000 - F1: 0.5288
sub_26:Test (Best Model) - Loss: 1.9429 - Accuracy: 0.4559 - F1: 0.4857
sub_27:Test (Best Model) - Loss: 1.6715 - Accuracy: 0.5072 - F1: 0.5044
sub_27:Test (Best Model) - Loss: 1.4479 - Accuracy: 0.4203 - F1: 0.4248
sub_27:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.3768 - F1: 0.3640
sub_27:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.4493 - F1: 0.4489
sub_27:Test (Best Model) - Loss: 1.4836 - Accuracy: 0.4638 - F1: 0.4540
sub_27:Test (Best Model) - Loss: 2.4630 - Accuracy: 0.3623 - F1: 0.3291
sub_27:Test (Best Model) - Loss: 2.9192 - Accuracy: 0.3478 - F1: 0.3178
sub_27:Test (Best Model) - Loss: 2.3601 - Accuracy: 0.4928 - F1: 0.4406
sub_27:Test (Best Model) - Loss: 2.8055 - Accuracy: 0.3913 - F1: 0.3447
sub_27:Test (Best Model) - Loss: 2.3612 - Accuracy: 0.3768 - F1: 0.3240
sub_27:Test (Best Model) - Loss: 1.5251 - Accuracy: 0.5000 - F1: 0.4886
sub_27:Test (Best Model) - Loss: 1.7431 - Accuracy: 0.4412 - F1: 0.4420
sub_27:Test (Best Model) - Loss: 2.0111 - Accuracy: 0.3971 - F1: 0.3959
sub_27:Test (Best Model) - Loss: 1.9011 - Accuracy: 0.4412 - F1: 0.4479
sub_27:Test (Best Model) - Loss: 2.0237 - Accuracy: 0.3971 - F1: 0.3845
sub_28:Test (Best Model) - Loss: 2.4141 - Accuracy: 0.2794 - F1: 0.2782
sub_28:Test (Best Model) - Loss: 2.7893 - Accuracy: 0.2941 - F1: 0.2636
sub_28:Test (Best Model) - Loss: 3.0173 - Accuracy: 0.2941 - F1: 0.2869
sub_28:Test (Best Model) - Loss: 2.4677 - Accuracy: 0.2206 - F1: 0.2155
sub_28:Test (Best Model) - Loss: 2.9587 - Accuracy: 0.2206 - F1: 0.2285
sub_28:Test (Best Model) - Loss: 3.7593 - Accuracy: 0.2206 - F1: 0.2026
sub_28:Test (Best Model) - Loss: 3.8464 - Accuracy: 0.2794 - F1: 0.2610
sub_28:Test (Best Model) - Loss: 3.7039 - Accuracy: 0.2059 - F1: 0.2066
sub_28:Test (Best Model) - Loss: 3.7575 - Accuracy: 0.2353 - F1: 0.2322
sub_28:Test (Best Model) - Loss: 3.5633 - Accuracy: 0.2059 - F1: 0.1796
sub_28:Test (Best Model) - Loss: 1.6340 - Accuracy: 0.4412 - F1: 0.4077
sub_28:Test (Best Model) - Loss: 1.5718 - Accuracy: 0.4265 - F1: 0.4092
sub_28:Test (Best Model) - Loss: 1.5161 - Accuracy: 0.3676 - F1: 0.3495
sub_28:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.4853 - F1: 0.4769
sub_28:Test (Best Model) - Loss: 1.6451 - Accuracy: 0.4412 - F1: 0.4146
sub_29:Test (Best Model) - Loss: 2.1387 - Accuracy: 0.5441 - F1: 0.5501
sub_29:Test (Best Model) - Loss: 2.1215 - Accuracy: 0.4853 - F1: 0.4785
sub_29:Test (Best Model) - Loss: 1.9891 - Accuracy: 0.5441 - F1: 0.5418
sub_29:Test (Best Model) - Loss: 1.9037 - Accuracy: 0.5147 - F1: 0.5290
sub_29:Test (Best Model) - Loss: 2.1795 - Accuracy: 0.5588 - F1: 0.5610
sub_29:Test (Best Model) - Loss: 1.2435 - Accuracy: 0.5441 - F1: 0.5706
sub_29:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.5735 - F1: 0.5931
sub_29:Test (Best Model) - Loss: 1.3125 - Accuracy: 0.4853 - F1: 0.4988
sub_29:Test (Best Model) - Loss: 0.9802 - Accuracy: 0.6324 - F1: 0.6496
sub_29:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.5735 - F1: 0.5971
sub_29:Test (Best Model) - Loss: 1.1709 - Accuracy: 0.5652 - F1: 0.5881
sub_29:Test (Best Model) - Loss: 1.6629 - Accuracy: 0.5362 - F1: 0.5529
sub_29:Test (Best Model) - Loss: 1.6817 - Accuracy: 0.4783 - F1: 0.5033
sub_29:Test (Best Model) - Loss: 1.3893 - Accuracy: 0.5942 - F1: 0.6102
sub_29:Test (Best Model) - Loss: 1.6343 - Accuracy: 0.5072 - F1: 0.5319

=== Summary Results ===

acc: 40.22 ± 6.35
F1: 39.70 ± 6.48
acc-in: 48.56 ± 5.81
F1-in: 46.85 ± 5.92
