lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.5303 - Accuracy: 0.5000 - F1: 0.5293
sub_1:Test (Best Model) - Loss: 1.5575 - Accuracy: 0.5000 - F1: 0.5316
sub_1:Test (Best Model) - Loss: 1.8809 - Accuracy: 0.3676 - F1: 0.3995
sub_1:Test (Best Model) - Loss: 1.5356 - Accuracy: 0.3971 - F1: 0.4290
sub_1:Test (Best Model) - Loss: 1.8749 - Accuracy: 0.4706 - F1: 0.5048
sub_1:Test (Best Model) - Loss: 2.1380 - Accuracy: 0.4203 - F1: 0.4244
sub_1:Test (Best Model) - Loss: 2.4184 - Accuracy: 0.4058 - F1: 0.4052
sub_1:Test (Best Model) - Loss: 2.0855 - Accuracy: 0.4203 - F1: 0.4057
sub_1:Test (Best Model) - Loss: 1.9201 - Accuracy: 0.4928 - F1: 0.4742
sub_1:Test (Best Model) - Loss: 2.2271 - Accuracy: 0.4348 - F1: 0.4194
sub_1:Test (Best Model) - Loss: 1.9573 - Accuracy: 0.4853 - F1: 0.4593
sub_1:Test (Best Model) - Loss: 1.2135 - Accuracy: 0.6029 - F1: 0.6000
sub_1:Test (Best Model) - Loss: 1.6633 - Accuracy: 0.5147 - F1: 0.5018
sub_1:Test (Best Model) - Loss: 2.0381 - Accuracy: 0.3971 - F1: 0.3825
sub_1:Test (Best Model) - Loss: 1.6679 - Accuracy: 0.5000 - F1: 0.4557
sub_2:Test (Best Model) - Loss: 2.1903 - Accuracy: 0.2609 - F1: 0.2829
sub_2:Test (Best Model) - Loss: 2.4331 - Accuracy: 0.3333 - F1: 0.3573
sub_2:Test (Best Model) - Loss: 2.8076 - Accuracy: 0.2609 - F1: 0.2760
sub_2:Test (Best Model) - Loss: 2.5712 - Accuracy: 0.1884 - F1: 0.2255
sub_2:Test (Best Model) - Loss: 3.2660 - Accuracy: 0.2319 - F1: 0.2673
sub_2:Test (Best Model) - Loss: 2.3704 - Accuracy: 0.3088 - F1: 0.3020
sub_2:Test (Best Model) - Loss: 2.1870 - Accuracy: 0.2353 - F1: 0.2485
sub_2:Test (Best Model) - Loss: 1.6593 - Accuracy: 0.4118 - F1: 0.4130
sub_2:Test (Best Model) - Loss: 1.8520 - Accuracy: 0.3529 - F1: 0.3604
sub_2:Test (Best Model) - Loss: 2.0125 - Accuracy: 0.3676 - F1: 0.3817
sub_2:Test (Best Model) - Loss: 2.5864 - Accuracy: 0.3333 - F1: 0.3062
sub_2:Test (Best Model) - Loss: 1.9938 - Accuracy: 0.3623 - F1: 0.3281
sub_2:Test (Best Model) - Loss: 1.8992 - Accuracy: 0.4493 - F1: 0.4108
sub_2:Test (Best Model) - Loss: 1.8786 - Accuracy: 0.4058 - F1: 0.3921
sub_2:Test (Best Model) - Loss: 2.1353 - Accuracy: 0.3478 - F1: 0.3241
sub_3:Test (Best Model) - Loss: 2.7640 - Accuracy: 0.3529 - F1: 0.3528
sub_3:Test (Best Model) - Loss: 2.0969 - Accuracy: 0.3235 - F1: 0.3230
sub_3:Test (Best Model) - Loss: 2.4483 - Accuracy: 0.3088 - F1: 0.3007
sub_3:Test (Best Model) - Loss: 2.5883 - Accuracy: 0.2500 - F1: 0.2484
sub_3:Test (Best Model) - Loss: 2.4547 - Accuracy: 0.2794 - F1: 0.2801
sub_3:Test (Best Model) - Loss: 2.2508 - Accuracy: 0.2899 - F1: 0.2586
sub_3:Test (Best Model) - Loss: 2.8195 - Accuracy: 0.2754 - F1: 0.2786
sub_3:Test (Best Model) - Loss: 2.6025 - Accuracy: 0.2464 - F1: 0.2253
sub_3:Test (Best Model) - Loss: 2.4355 - Accuracy: 0.3913 - F1: 0.3649
sub_3:Test (Best Model) - Loss: 2.3766 - Accuracy: 0.2174 - F1: 0.2023
sub_3:Test (Best Model) - Loss: 3.1123 - Accuracy: 0.3333 - F1: 0.3205
sub_3:Test (Best Model) - Loss: 2.7500 - Accuracy: 0.3478 - F1: 0.3209
sub_3:Test (Best Model) - Loss: 2.7606 - Accuracy: 0.3768 - F1: 0.3371
sub_3:Test (Best Model) - Loss: 2.7645 - Accuracy: 0.3188 - F1: 0.3072
sub_3:Test (Best Model) - Loss: 3.2798 - Accuracy: 0.3333 - F1: 0.3237
sub_4:Test (Best Model) - Loss: 1.7868 - Accuracy: 0.5217 - F1: 0.5349
sub_4:Test (Best Model) - Loss: 1.5827 - Accuracy: 0.5217 - F1: 0.5253
sub_4:Test (Best Model) - Loss: 1.5847 - Accuracy: 0.5507 - F1: 0.5562
sub_4:Test (Best Model) - Loss: 1.7210 - Accuracy: 0.5217 - F1: 0.5208
sub_4:Test (Best Model) - Loss: 1.6703 - Accuracy: 0.5652 - F1: 0.5617
sub_4:Test (Best Model) - Loss: 1.7887 - Accuracy: 0.4928 - F1: 0.4881
sub_4:Test (Best Model) - Loss: 1.7592 - Accuracy: 0.4638 - F1: 0.4874
sub_4:Test (Best Model) - Loss: 1.3525 - Accuracy: 0.4928 - F1: 0.5149
sub_4:Test (Best Model) - Loss: 2.0598 - Accuracy: 0.4493 - F1: 0.4554
sub_4:Test (Best Model) - Loss: 1.7095 - Accuracy: 0.5072 - F1: 0.5158
sub_4:Test (Best Model) - Loss: 2.6046 - Accuracy: 0.4638 - F1: 0.4266
sub_4:Test (Best Model) - Loss: 2.2686 - Accuracy: 0.4058 - F1: 0.4052
sub_4:Test (Best Model) - Loss: 2.3758 - Accuracy: 0.3478 - F1: 0.3463
sub_4:Test (Best Model) - Loss: 2.6410 - Accuracy: 0.4638 - F1: 0.4441
sub_4:Test (Best Model) - Loss: 2.1074 - Accuracy: 0.4493 - F1: 0.4529
sub_5:Test (Best Model) - Loss: 3.2203 - Accuracy: 0.4706 - F1: 0.4481
sub_5:Test (Best Model) - Loss: 3.7303 - Accuracy: 0.4265 - F1: 0.3781
sub_5:Test (Best Model) - Loss: 3.6766 - Accuracy: 0.4265 - F1: 0.4236
sub_5:Test (Best Model) - Loss: 3.7077 - Accuracy: 0.4412 - F1: 0.4098
sub_5:Test (Best Model) - Loss: 3.4005 - Accuracy: 0.4265 - F1: 0.3789
sub_5:Test (Best Model) - Loss: 1.7703 - Accuracy: 0.5000 - F1: 0.4668
sub_5:Test (Best Model) - Loss: 1.8679 - Accuracy: 0.5441 - F1: 0.4920
sub_5:Test (Best Model) - Loss: 1.5207 - Accuracy: 0.5000 - F1: 0.4477
sub_5:Test (Best Model) - Loss: 1.5608 - Accuracy: 0.5294 - F1: 0.4942
sub_5:Test (Best Model) - Loss: 2.7040 - Accuracy: 0.4853 - F1: 0.4605
sub_5:Test (Best Model) - Loss: 2.3456 - Accuracy: 0.3676 - F1: 0.3616
sub_5:Test (Best Model) - Loss: 1.9515 - Accuracy: 0.3971 - F1: 0.3682
sub_5:Test (Best Model) - Loss: 2.3333 - Accuracy: 0.3676 - F1: 0.3761
sub_5:Test (Best Model) - Loss: 2.4544 - Accuracy: 0.3235 - F1: 0.3366
sub_5:Test (Best Model) - Loss: 1.7769 - Accuracy: 0.3971 - F1: 0.3880
sub_6:Test (Best Model) - Loss: 1.4997 - Accuracy: 0.5000 - F1: 0.5060
sub_6:Test (Best Model) - Loss: 1.2572 - Accuracy: 0.5735 - F1: 0.5764
sub_6:Test (Best Model) - Loss: 1.7780 - Accuracy: 0.5147 - F1: 0.5070
sub_6:Test (Best Model) - Loss: 1.5718 - Accuracy: 0.5000 - F1: 0.5008
sub_6:Test (Best Model) - Loss: 1.8961 - Accuracy: 0.5000 - F1: 0.5015
sub_6:Test (Best Model) - Loss: 2.2081 - Accuracy: 0.3043 - F1: 0.2619
sub_6:Test (Best Model) - Loss: 2.1104 - Accuracy: 0.4783 - F1: 0.4119
sub_6:Test (Best Model) - Loss: 1.8544 - Accuracy: 0.4203 - F1: 0.3931
sub_6:Test (Best Model) - Loss: 1.7044 - Accuracy: 0.4493 - F1: 0.4305
sub_6:Test (Best Model) - Loss: 1.8660 - Accuracy: 0.3623 - F1: 0.3151
sub_6:Test (Best Model) - Loss: 1.7874 - Accuracy: 0.4493 - F1: 0.4347
sub_6:Test (Best Model) - Loss: 2.1294 - Accuracy: 0.5072 - F1: 0.4967
sub_6:Test (Best Model) - Loss: 2.0649 - Accuracy: 0.4058 - F1: 0.4156
sub_6:Test (Best Model) - Loss: 1.5119 - Accuracy: 0.5507 - F1: 0.5579
sub_6:Test (Best Model) - Loss: 1.6769 - Accuracy: 0.5507 - F1: 0.5628
sub_7:Test (Best Model) - Loss: 1.1831 - Accuracy: 0.6176 - F1: 0.5759
sub_7:Test (Best Model) - Loss: 1.3444 - Accuracy: 0.6176 - F1: 0.5835
sub_7:Test (Best Model) - Loss: 1.5132 - Accuracy: 0.5735 - F1: 0.5647
sub_7:Test (Best Model) - Loss: 0.8096 - Accuracy: 0.7059 - F1: 0.6830
sub_7:Test (Best Model) - Loss: 1.4441 - Accuracy: 0.5441 - F1: 0.5445
sub_7:Test (Best Model) - Loss: 2.8282 - Accuracy: 0.3529 - F1: 0.3406
sub_7:Test (Best Model) - Loss: 2.9509 - Accuracy: 0.4118 - F1: 0.3972
sub_7:Test (Best Model) - Loss: 2.0089 - Accuracy: 0.4853 - F1: 0.4486
sub_7:Test (Best Model) - Loss: 2.4153 - Accuracy: 0.4559 - F1: 0.4210
sub_7:Test (Best Model) - Loss: 2.2087 - Accuracy: 0.4853 - F1: 0.4338
sub_7:Test (Best Model) - Loss: 1.5724 - Accuracy: 0.4706 - F1: 0.4665
sub_7:Test (Best Model) - Loss: 1.7943 - Accuracy: 0.5000 - F1: 0.4880
sub_7:Test (Best Model) - Loss: 1.8345 - Accuracy: 0.5147 - F1: 0.5103
sub_7:Test (Best Model) - Loss: 2.1053 - Accuracy: 0.4706 - F1: 0.4793
sub_7:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.4706 - F1: 0.4675
sub_8:Test (Best Model) - Loss: 2.6253 - Accuracy: 0.2794 - F1: 0.2787
sub_8:Test (Best Model) - Loss: 2.8822 - Accuracy: 0.2941 - F1: 0.2987
sub_8:Test (Best Model) - Loss: 3.3855 - Accuracy: 0.2206 - F1: 0.2572
sub_8:Test (Best Model) - Loss: 2.8432 - Accuracy: 0.3088 - F1: 0.3131
sub_8:Test (Best Model) - Loss: 2.7588 - Accuracy: 0.2353 - F1: 0.2697
sub_8:Test (Best Model) - Loss: 1.9133 - Accuracy: 0.3382 - F1: 0.3618
sub_8:Test (Best Model) - Loss: 2.3176 - Accuracy: 0.3235 - F1: 0.3232
sub_8:Test (Best Model) - Loss: 1.8381 - Accuracy: 0.3971 - F1: 0.4181
sub_8:Test (Best Model) - Loss: 2.5300 - Accuracy: 0.3529 - F1: 0.3456
sub_8:Test (Best Model) - Loss: 2.4278 - Accuracy: 0.3529 - F1: 0.3629
sub_8:Test (Best Model) - Loss: 3.0146 - Accuracy: 0.2353 - F1: 0.2096
sub_8:Test (Best Model) - Loss: 2.7947 - Accuracy: 0.2353 - F1: 0.2465
sub_8:Test (Best Model) - Loss: 2.7874 - Accuracy: 0.3676 - F1: 0.3940
sub_8:Test (Best Model) - Loss: 2.7813 - Accuracy: 0.3971 - F1: 0.4205
sub_8:Test (Best Model) - Loss: 2.7262 - Accuracy: 0.3235 - F1: 0.3151
sub_9:Test (Best Model) - Loss: 1.9006 - Accuracy: 0.5000 - F1: 0.5067
sub_9:Test (Best Model) - Loss: 1.5961 - Accuracy: 0.5882 - F1: 0.5943
sub_9:Test (Best Model) - Loss: 1.8070 - Accuracy: 0.4559 - F1: 0.4747
sub_9:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.5882 - F1: 0.6030
sub_9:Test (Best Model) - Loss: 1.4902 - Accuracy: 0.6324 - F1: 0.6468
sub_9:Test (Best Model) - Loss: 4.0536 - Accuracy: 0.3235 - F1: 0.3073
sub_9:Test (Best Model) - Loss: 3.5891 - Accuracy: 0.3971 - F1: 0.3832
sub_9:Test (Best Model) - Loss: 4.0825 - Accuracy: 0.2941 - F1: 0.2924
sub_9:Test (Best Model) - Loss: 3.1643 - Accuracy: 0.3971 - F1: 0.3808
sub_9:Test (Best Model) - Loss: 2.5689 - Accuracy: 0.3235 - F1: 0.3508
sub_9:Test (Best Model) - Loss: 3.1094 - Accuracy: 0.4706 - F1: 0.4867
sub_9:Test (Best Model) - Loss: 2.5244 - Accuracy: 0.4853 - F1: 0.5040
sub_9:Test (Best Model) - Loss: 2.3221 - Accuracy: 0.4265 - F1: 0.4664
sub_9:Test (Best Model) - Loss: 3.1327 - Accuracy: 0.3971 - F1: 0.4222
sub_9:Test (Best Model) - Loss: 2.5357 - Accuracy: 0.4412 - F1: 0.4695
sub_10:Test (Best Model) - Loss: 2.5389 - Accuracy: 0.2500 - F1: 0.2500
sub_10:Test (Best Model) - Loss: 2.3665 - Accuracy: 0.3824 - F1: 0.3437
sub_10:Test (Best Model) - Loss: 2.1793 - Accuracy: 0.3088 - F1: 0.3014
sub_10:Test (Best Model) - Loss: 2.4760 - Accuracy: 0.3529 - F1: 0.3642
sub_10:Test (Best Model) - Loss: 2.5845 - Accuracy: 0.3235 - F1: 0.3088
sub_10:Test (Best Model) - Loss: 1.9890 - Accuracy: 0.3676 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 2.3418 - Accuracy: 0.2794 - F1: 0.2775
sub_10:Test (Best Model) - Loss: 2.3615 - Accuracy: 0.3676 - F1: 0.3710
sub_10:Test (Best Model) - Loss: 2.2016 - Accuracy: 0.3088 - F1: 0.3172
sub_10:Test (Best Model) - Loss: 2.3271 - Accuracy: 0.2794 - F1: 0.2725
sub_10:Test (Best Model) - Loss: 2.7975 - Accuracy: 0.2464 - F1: 0.2453
sub_10:Test (Best Model) - Loss: 2.5779 - Accuracy: 0.3188 - F1: 0.3328
sub_10:Test (Best Model) - Loss: 2.3491 - Accuracy: 0.3188 - F1: 0.3099
sub_10:Test (Best Model) - Loss: 2.3244 - Accuracy: 0.3623 - F1: 0.3435
sub_10:Test (Best Model) - Loss: 2.4299 - Accuracy: 0.3043 - F1: 0.3180
sub_11:Test (Best Model) - Loss: 2.8059 - Accuracy: 0.3043 - F1: 0.2982
sub_11:Test (Best Model) - Loss: 2.6978 - Accuracy: 0.3188 - F1: 0.3027
sub_11:Test (Best Model) - Loss: 2.7430 - Accuracy: 0.3188 - F1: 0.3039
sub_11:Test (Best Model) - Loss: 2.8112 - Accuracy: 0.3188 - F1: 0.3180
sub_11:Test (Best Model) - Loss: 3.6500 - Accuracy: 0.2174 - F1: 0.2190
sub_11:Test (Best Model) - Loss: 2.1655 - Accuracy: 0.3913 - F1: 0.3763
sub_11:Test (Best Model) - Loss: 1.7960 - Accuracy: 0.5362 - F1: 0.5073
sub_11:Test (Best Model) - Loss: 2.0853 - Accuracy: 0.4203 - F1: 0.3775
sub_11:Test (Best Model) - Loss: 2.2937 - Accuracy: 0.4203 - F1: 0.3476
sub_11:Test (Best Model) - Loss: 1.9964 - Accuracy: 0.4638 - F1: 0.4306
sub_11:Test (Best Model) - Loss: 1.8099 - Accuracy: 0.4348 - F1: 0.3793
sub_11:Test (Best Model) - Loss: 2.0891 - Accuracy: 0.4203 - F1: 0.3549
sub_11:Test (Best Model) - Loss: 1.7374 - Accuracy: 0.4783 - F1: 0.4341
sub_11:Test (Best Model) - Loss: 1.7371 - Accuracy: 0.4493 - F1: 0.4298
sub_11:Test (Best Model) - Loss: 1.8923 - Accuracy: 0.4348 - F1: 0.3785
sub_12:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.5588 - F1: 0.5514
sub_12:Test (Best Model) - Loss: 1.4608 - Accuracy: 0.5441 - F1: 0.5194
sub_12:Test (Best Model) - Loss: 1.6873 - Accuracy: 0.5735 - F1: 0.5591
sub_12:Test (Best Model) - Loss: 1.4145 - Accuracy: 0.5588 - F1: 0.5551
sub_12:Test (Best Model) - Loss: 1.4820 - Accuracy: 0.5441 - F1: 0.5267
sub_12:Test (Best Model) - Loss: 1.9592 - Accuracy: 0.5217 - F1: 0.5131
sub_12:Test (Best Model) - Loss: 1.2242 - Accuracy: 0.5217 - F1: 0.5122
sub_12:Test (Best Model) - Loss: 1.5054 - Accuracy: 0.4783 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 1.6358 - Accuracy: 0.5797 - F1: 0.5774
sub_12:Test (Best Model) - Loss: 1.6887 - Accuracy: 0.5217 - F1: 0.5309
sub_12:Test (Best Model) - Loss: 1.8342 - Accuracy: 0.5147 - F1: 0.5097
sub_12:Test (Best Model) - Loss: 1.9327 - Accuracy: 0.4118 - F1: 0.4147
sub_12:Test (Best Model) - Loss: 2.0055 - Accuracy: 0.4412 - F1: 0.4532
sub_12:Test (Best Model) - Loss: 2.0103 - Accuracy: 0.4412 - F1: 0.4444
sub_12:Test (Best Model) - Loss: 2.0390 - Accuracy: 0.4853 - F1: 0.5025
sub_13:Test (Best Model) - Loss: 2.2916 - Accuracy: 0.5441 - F1: 0.5356
sub_13:Test (Best Model) - Loss: 2.9191 - Accuracy: 0.4559 - F1: 0.4632
sub_13:Test (Best Model) - Loss: 2.1421 - Accuracy: 0.4853 - F1: 0.5134
sub_13:Test (Best Model) - Loss: 2.5210 - Accuracy: 0.3971 - F1: 0.4112
sub_13:Test (Best Model) - Loss: 2.1318 - Accuracy: 0.5294 - F1: 0.5206
sub_13:Test (Best Model) - Loss: 2.6397 - Accuracy: 0.4928 - F1: 0.4846
sub_13:Test (Best Model) - Loss: 2.0830 - Accuracy: 0.4493 - F1: 0.4584
sub_13:Test (Best Model) - Loss: 2.4832 - Accuracy: 0.4493 - F1: 0.4631
sub_13:Test (Best Model) - Loss: 3.1168 - Accuracy: 0.4203 - F1: 0.4352
sub_13:Test (Best Model) - Loss: 2.2395 - Accuracy: 0.5217 - F1: 0.5336
sub_13:Test (Best Model) - Loss: 2.2352 - Accuracy: 0.3824 - F1: 0.3896
sub_13:Test (Best Model) - Loss: 2.3187 - Accuracy: 0.4265 - F1: 0.4308
sub_13:Test (Best Model) - Loss: 2.6521 - Accuracy: 0.4118 - F1: 0.4349
sub_13:Test (Best Model) - Loss: 2.3155 - Accuracy: 0.3824 - F1: 0.3933
sub_13:Test (Best Model) - Loss: 1.9816 - Accuracy: 0.5147 - F1: 0.5084
sub_14:Test (Best Model) - Loss: 2.1874 - Accuracy: 0.3676 - F1: 0.4009
sub_14:Test (Best Model) - Loss: 2.3655 - Accuracy: 0.3235 - F1: 0.3168
sub_14:Test (Best Model) - Loss: 2.8731 - Accuracy: 0.2647 - F1: 0.2893
sub_14:Test (Best Model) - Loss: 2.1793 - Accuracy: 0.3235 - F1: 0.3556
sub_14:Test (Best Model) - Loss: 2.4834 - Accuracy: 0.4412 - F1: 0.4434
sub_14:Test (Best Model) - Loss: 2.5727 - Accuracy: 0.3676 - F1: 0.3927
sub_14:Test (Best Model) - Loss: 2.8958 - Accuracy: 0.4412 - F1: 0.4636
sub_14:Test (Best Model) - Loss: 2.3768 - Accuracy: 0.4706 - F1: 0.4909
sub_14:Test (Best Model) - Loss: 2.9565 - Accuracy: 0.3676 - F1: 0.3939
sub_14:Test (Best Model) - Loss: 3.0058 - Accuracy: 0.4118 - F1: 0.4285
sub_14:Test (Best Model) - Loss: 2.5858 - Accuracy: 0.4559 - F1: 0.4611
sub_14:Test (Best Model) - Loss: 1.9828 - Accuracy: 0.4265 - F1: 0.4345
sub_14:Test (Best Model) - Loss: 2.8376 - Accuracy: 0.4412 - F1: 0.4526
sub_14:Test (Best Model) - Loss: 2.6118 - Accuracy: 0.3824 - F1: 0.3895
sub_14:Test (Best Model) - Loss: 2.3628 - Accuracy: 0.3971 - F1: 0.4069
sub_15:Test (Best Model) - Loss: 2.1931 - Accuracy: 0.4706 - F1: 0.4991
sub_15:Test (Best Model) - Loss: 2.3325 - Accuracy: 0.4412 - F1: 0.4422
sub_15:Test (Best Model) - Loss: 3.0080 - Accuracy: 0.4118 - F1: 0.4085
sub_15:Test (Best Model) - Loss: 1.8077 - Accuracy: 0.5294 - F1: 0.5604
sub_15:Test (Best Model) - Loss: 2.8323 - Accuracy: 0.4118 - F1: 0.4419
sub_15:Test (Best Model) - Loss: 1.5781 - Accuracy: 0.5882 - F1: 0.5852
sub_15:Test (Best Model) - Loss: 2.5233 - Accuracy: 0.4853 - F1: 0.4962
sub_15:Test (Best Model) - Loss: 1.7433 - Accuracy: 0.5882 - F1: 0.5927
sub_15:Test (Best Model) - Loss: 2.2545 - Accuracy: 0.5000 - F1: 0.5132
sub_15:Test (Best Model) - Loss: 1.8745 - Accuracy: 0.5000 - F1: 0.4953
sub_15:Test (Best Model) - Loss: 2.4141 - Accuracy: 0.4412 - F1: 0.4169
sub_15:Test (Best Model) - Loss: 2.1614 - Accuracy: 0.3824 - F1: 0.3649
sub_15:Test (Best Model) - Loss: 2.5829 - Accuracy: 0.3971 - F1: 0.3682
sub_15:Test (Best Model) - Loss: 2.4503 - Accuracy: 0.3529 - F1: 0.3529
sub_15:Test (Best Model) - Loss: 2.5430 - Accuracy: 0.4412 - F1: 0.4253
sub_16:Test (Best Model) - Loss: 1.2591 - Accuracy: 0.5735 - F1: 0.5204
sub_16:Test (Best Model) - Loss: 1.1709 - Accuracy: 0.5147 - F1: 0.5010
sub_16:Test (Best Model) - Loss: 1.3501 - Accuracy: 0.5735 - F1: 0.5600
sub_16:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.5147 - F1: 0.5047
sub_16:Test (Best Model) - Loss: 0.9287 - Accuracy: 0.6471 - F1: 0.6276
sub_16:Test (Best Model) - Loss: 1.7392 - Accuracy: 0.4706 - F1: 0.4461
sub_16:Test (Best Model) - Loss: 2.2825 - Accuracy: 0.4853 - F1: 0.4891
sub_16:Test (Best Model) - Loss: 1.9514 - Accuracy: 0.4265 - F1: 0.3880
sub_16:Test (Best Model) - Loss: 1.4673 - Accuracy: 0.5735 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 3.1985 - Accuracy: 0.3971 - F1: 0.4036
sub_16:Test (Best Model) - Loss: 1.5781 - Accuracy: 0.5441 - F1: 0.5142
sub_16:Test (Best Model) - Loss: 1.7166 - Accuracy: 0.5147 - F1: 0.4307
sub_16:Test (Best Model) - Loss: 1.3581 - Accuracy: 0.6176 - F1: 0.5518
sub_16:Test (Best Model) - Loss: 1.4732 - Accuracy: 0.5147 - F1: 0.4803
sub_16:Test (Best Model) - Loss: 1.2516 - Accuracy: 0.5882 - F1: 0.5555
sub_17:Test (Best Model) - Loss: 2.0320 - Accuracy: 0.4928 - F1: 0.4721
sub_17:Test (Best Model) - Loss: 1.3962 - Accuracy: 0.4638 - F1: 0.4524
sub_17:Test (Best Model) - Loss: 1.6455 - Accuracy: 0.3768 - F1: 0.3528
sub_17:Test (Best Model) - Loss: 1.8504 - Accuracy: 0.4638 - F1: 0.4590
sub_17:Test (Best Model) - Loss: 1.6540 - Accuracy: 0.3913 - F1: 0.3913
sub_17:Test (Best Model) - Loss: 3.4535 - Accuracy: 0.4348 - F1: 0.3846
sub_17:Test (Best Model) - Loss: 4.1646 - Accuracy: 0.3333 - F1: 0.2985
sub_17:Test (Best Model) - Loss: 3.5247 - Accuracy: 0.4203 - F1: 0.3912
sub_17:Test (Best Model) - Loss: 3.2767 - Accuracy: 0.4783 - F1: 0.4283
sub_17:Test (Best Model) - Loss: 3.3749 - Accuracy: 0.3478 - F1: 0.3053
sub_17:Test (Best Model) - Loss: 1.8805 - Accuracy: 0.4265 - F1: 0.4275
sub_17:Test (Best Model) - Loss: 1.7891 - Accuracy: 0.4265 - F1: 0.4212
sub_17:Test (Best Model) - Loss: 2.2931 - Accuracy: 0.4118 - F1: 0.4066
sub_17:Test (Best Model) - Loss: 1.9411 - Accuracy: 0.4412 - F1: 0.4409
sub_17:Test (Best Model) - Loss: 2.1170 - Accuracy: 0.3824 - F1: 0.3838
sub_18:Test (Best Model) - Loss: 1.6319 - Accuracy: 0.3768 - F1: 0.3860
sub_18:Test (Best Model) - Loss: 1.7846 - Accuracy: 0.3913 - F1: 0.4038
sub_18:Test (Best Model) - Loss: 1.8800 - Accuracy: 0.4058 - F1: 0.3815
sub_18:Test (Best Model) - Loss: 2.0442 - Accuracy: 0.3913 - F1: 0.3929
sub_18:Test (Best Model) - Loss: 1.5667 - Accuracy: 0.4493 - F1: 0.4759
sub_18:Test (Best Model) - Loss: 2.0543 - Accuracy: 0.3382 - F1: 0.3727
sub_18:Test (Best Model) - Loss: 2.0659 - Accuracy: 0.3529 - F1: 0.3780
sub_18:Test (Best Model) - Loss: 2.2526 - Accuracy: 0.2941 - F1: 0.3234
sub_18:Test (Best Model) - Loss: 2.1782 - Accuracy: 0.3529 - F1: 0.3680
sub_18:Test (Best Model) - Loss: 2.2833 - Accuracy: 0.3529 - F1: 0.3725
sub_18:Test (Best Model) - Loss: 2.0647 - Accuracy: 0.3382 - F1: 0.3664
sub_18:Test (Best Model) - Loss: 2.8674 - Accuracy: 0.2647 - F1: 0.2973
sub_18:Test (Best Model) - Loss: 2.4577 - Accuracy: 0.2353 - F1: 0.2669
sub_18:Test (Best Model) - Loss: 2.4215 - Accuracy: 0.3382 - F1: 0.3690
sub_18:Test (Best Model) - Loss: 1.9991 - Accuracy: 0.3235 - F1: 0.3675
sub_19:Test (Best Model) - Loss: 3.2918 - Accuracy: 0.1912 - F1: 0.1426
sub_19:Test (Best Model) - Loss: 3.1032 - Accuracy: 0.2059 - F1: 0.1847
sub_19:Test (Best Model) - Loss: 3.0832 - Accuracy: 0.3088 - F1: 0.2986
sub_19:Test (Best Model) - Loss: 2.7019 - Accuracy: 0.2206 - F1: 0.2101
sub_19:Test (Best Model) - Loss: 3.1489 - Accuracy: 0.1912 - F1: 0.1782
sub_19:Test (Best Model) - Loss: 2.5326 - Accuracy: 0.3676 - F1: 0.3368
sub_19:Test (Best Model) - Loss: 2.5015 - Accuracy: 0.3382 - F1: 0.2849
sub_19:Test (Best Model) - Loss: 1.8838 - Accuracy: 0.4412 - F1: 0.3933
sub_19:Test (Best Model) - Loss: 1.8757 - Accuracy: 0.5000 - F1: 0.4489
sub_19:Test (Best Model) - Loss: 2.4446 - Accuracy: 0.4559 - F1: 0.4677
sub_19:Test (Best Model) - Loss: 3.0158 - Accuracy: 0.3824 - F1: 0.3462
sub_19:Test (Best Model) - Loss: 4.0743 - Accuracy: 0.2500 - F1: 0.2405
sub_19:Test (Best Model) - Loss: 2.8282 - Accuracy: 0.3382 - F1: 0.2923
sub_19:Test (Best Model) - Loss: 3.0670 - Accuracy: 0.2941 - F1: 0.2980
sub_19:Test (Best Model) - Loss: 2.5340 - Accuracy: 0.3971 - F1: 0.3805
sub_20:Test (Best Model) - Loss: 1.6713 - Accuracy: 0.5588 - F1: 0.5635
sub_20:Test (Best Model) - Loss: 2.2476 - Accuracy: 0.5147 - F1: 0.5215
sub_20:Test (Best Model) - Loss: 1.8793 - Accuracy: 0.6029 - F1: 0.5981
sub_20:Test (Best Model) - Loss: 2.1644 - Accuracy: 0.5000 - F1: 0.5035
sub_20:Test (Best Model) - Loss: 2.2565 - Accuracy: 0.4559 - F1: 0.4607
sub_20:Test (Best Model) - Loss: 1.7770 - Accuracy: 0.4706 - F1: 0.4857
sub_20:Test (Best Model) - Loss: 2.1041 - Accuracy: 0.4265 - F1: 0.4444
sub_20:Test (Best Model) - Loss: 2.1347 - Accuracy: 0.3824 - F1: 0.4051
sub_20:Test (Best Model) - Loss: 2.2065 - Accuracy: 0.4118 - F1: 0.4171
sub_20:Test (Best Model) - Loss: 2.4495 - Accuracy: 0.4706 - F1: 0.4926
sub_20:Test (Best Model) - Loss: 2.4167 - Accuracy: 0.3913 - F1: 0.4037
sub_20:Test (Best Model) - Loss: 2.5974 - Accuracy: 0.4203 - F1: 0.4241
sub_20:Test (Best Model) - Loss: 1.9592 - Accuracy: 0.4928 - F1: 0.4955
sub_20:Test (Best Model) - Loss: 2.7650 - Accuracy: 0.4203 - F1: 0.4290
sub_20:Test (Best Model) - Loss: 2.1576 - Accuracy: 0.4348 - F1: 0.4512
sub_21:Test (Best Model) - Loss: 2.6066 - Accuracy: 0.4559 - F1: 0.4432
sub_21:Test (Best Model) - Loss: 2.4950 - Accuracy: 0.3676 - F1: 0.3340
sub_21:Test (Best Model) - Loss: 2.8976 - Accuracy: 0.4559 - F1: 0.4196
sub_21:Test (Best Model) - Loss: 2.3838 - Accuracy: 0.4412 - F1: 0.4275
sub_21:Test (Best Model) - Loss: 3.4647 - Accuracy: 0.4412 - F1: 0.3904
sub_21:Test (Best Model) - Loss: 1.6667 - Accuracy: 0.4559 - F1: 0.4202
sub_21:Test (Best Model) - Loss: 1.5260 - Accuracy: 0.5441 - F1: 0.5406
sub_21:Test (Best Model) - Loss: 1.8765 - Accuracy: 0.4265 - F1: 0.3644
sub_21:Test (Best Model) - Loss: 1.9497 - Accuracy: 0.5147 - F1: 0.4902
sub_21:Test (Best Model) - Loss: 1.9646 - Accuracy: 0.4559 - F1: 0.4210
sub_21:Test (Best Model) - Loss: 1.9621 - Accuracy: 0.2941 - F1: 0.2836
sub_21:Test (Best Model) - Loss: 1.9507 - Accuracy: 0.3824 - F1: 0.3733
sub_21:Test (Best Model) - Loss: 1.7348 - Accuracy: 0.4118 - F1: 0.3832
sub_21:Test (Best Model) - Loss: 2.2806 - Accuracy: 0.4118 - F1: 0.3924
sub_21:Test (Best Model) - Loss: 1.8644 - Accuracy: 0.5294 - F1: 0.4909
sub_22:Test (Best Model) - Loss: 2.2564 - Accuracy: 0.3382 - F1: 0.3625
sub_22:Test (Best Model) - Loss: 2.2159 - Accuracy: 0.4559 - F1: 0.4744
sub_22:Test (Best Model) - Loss: 2.9125 - Accuracy: 0.3235 - F1: 0.3408
sub_22:Test (Best Model) - Loss: 2.3355 - Accuracy: 0.4118 - F1: 0.4288
sub_22:Test (Best Model) - Loss: 3.0182 - Accuracy: 0.3529 - F1: 0.3809
sub_22:Test (Best Model) - Loss: 1.8192 - Accuracy: 0.3333 - F1: 0.3094
sub_22:Test (Best Model) - Loss: 1.9421 - Accuracy: 0.3623 - F1: 0.3173
sub_22:Test (Best Model) - Loss: 2.0619 - Accuracy: 0.4058 - F1: 0.3750
sub_22:Test (Best Model) - Loss: 1.9338 - Accuracy: 0.4058 - F1: 0.4255
sub_22:Test (Best Model) - Loss: 2.4025 - Accuracy: 0.3043 - F1: 0.2701
sub_22:Test (Best Model) - Loss: 1.9423 - Accuracy: 0.3676 - F1: 0.3911
sub_22:Test (Best Model) - Loss: 1.7119 - Accuracy: 0.3971 - F1: 0.4035
sub_22:Test (Best Model) - Loss: 1.9059 - Accuracy: 0.3529 - F1: 0.3737
sub_22:Test (Best Model) - Loss: 2.0280 - Accuracy: 0.3676 - F1: 0.3928
sub_22:Test (Best Model) - Loss: 1.4938 - Accuracy: 0.4412 - F1: 0.4835
sub_23:Test (Best Model) - Loss: 2.1032 - Accuracy: 0.3913 - F1: 0.4067
sub_23:Test (Best Model) - Loss: 1.4478 - Accuracy: 0.4783 - F1: 0.5046
sub_23:Test (Best Model) - Loss: 1.9469 - Accuracy: 0.4928 - F1: 0.5033
sub_23:Test (Best Model) - Loss: 1.7533 - Accuracy: 0.5072 - F1: 0.5060
sub_23:Test (Best Model) - Loss: 1.8344 - Accuracy: 0.5217 - F1: 0.5461
sub_23:Test (Best Model) - Loss: 1.6476 - Accuracy: 0.4853 - F1: 0.4581
sub_23:Test (Best Model) - Loss: 1.9123 - Accuracy: 0.4412 - F1: 0.4441
sub_23:Test (Best Model) - Loss: 1.5293 - Accuracy: 0.5147 - F1: 0.5057
sub_23:Test (Best Model) - Loss: 1.6922 - Accuracy: 0.5294 - F1: 0.5187
sub_23:Test (Best Model) - Loss: 1.7700 - Accuracy: 0.5147 - F1: 0.4835
sub_23:Test (Best Model) - Loss: 3.0808 - Accuracy: 0.3913 - F1: 0.3607
sub_23:Test (Best Model) - Loss: 3.0786 - Accuracy: 0.4203 - F1: 0.4137
sub_23:Test (Best Model) - Loss: 3.1245 - Accuracy: 0.4058 - F1: 0.4117
sub_23:Test (Best Model) - Loss: 3.3153 - Accuracy: 0.4783 - F1: 0.4619
sub_23:Test (Best Model) - Loss: 3.3390 - Accuracy: 0.3768 - F1: 0.3679
sub_24:Test (Best Model) - Loss: 2.3571 - Accuracy: 0.3676 - F1: 0.3627
sub_24:Test (Best Model) - Loss: 2.0961 - Accuracy: 0.4265 - F1: 0.4256
sub_24:Test (Best Model) - Loss: 2.3568 - Accuracy: 0.2794 - F1: 0.2777
sub_24:Test (Best Model) - Loss: 2.4918 - Accuracy: 0.3235 - F1: 0.3178
sub_24:Test (Best Model) - Loss: 2.0053 - Accuracy: 0.3676 - F1: 0.3605
sub_24:Test (Best Model) - Loss: 2.0210 - Accuracy: 0.3971 - F1: 0.3978
sub_24:Test (Best Model) - Loss: 1.8246 - Accuracy: 0.3676 - F1: 0.3654
sub_24:Test (Best Model) - Loss: 1.5576 - Accuracy: 0.3971 - F1: 0.3733
sub_24:Test (Best Model) - Loss: 1.5156 - Accuracy: 0.3529 - F1: 0.3327
sub_24:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.4706 - F1: 0.4554
sub_24:Test (Best Model) - Loss: 1.9011 - Accuracy: 0.3382 - F1: 0.3324
sub_24:Test (Best Model) - Loss: 2.1581 - Accuracy: 0.3529 - F1: 0.3287
sub_24:Test (Best Model) - Loss: 2.4878 - Accuracy: 0.2647 - F1: 0.2733
sub_24:Test (Best Model) - Loss: 1.9617 - Accuracy: 0.3824 - F1: 0.3942
sub_24:Test (Best Model) - Loss: 2.1861 - Accuracy: 0.3529 - F1: 0.3436
sub_25:Test (Best Model) - Loss: 1.5522 - Accuracy: 0.5797 - F1: 0.5328
sub_25:Test (Best Model) - Loss: 1.8164 - Accuracy: 0.4348 - F1: 0.3809
sub_25:Test (Best Model) - Loss: 1.6951 - Accuracy: 0.4493 - F1: 0.4265
sub_25:Test (Best Model) - Loss: 1.7495 - Accuracy: 0.4638 - F1: 0.4390
sub_25:Test (Best Model) - Loss: 1.8380 - Accuracy: 0.4203 - F1: 0.4004
sub_25:Test (Best Model) - Loss: 2.7541 - Accuracy: 0.4412 - F1: 0.3851
sub_25:Test (Best Model) - Loss: 3.1469 - Accuracy: 0.3529 - F1: 0.3138
sub_25:Test (Best Model) - Loss: 2.1919 - Accuracy: 0.5147 - F1: 0.4328
sub_25:Test (Best Model) - Loss: 2.4131 - Accuracy: 0.4412 - F1: 0.3746
sub_25:Test (Best Model) - Loss: 2.1842 - Accuracy: 0.4118 - F1: 0.3894
sub_25:Test (Best Model) - Loss: 2.1238 - Accuracy: 0.4118 - F1: 0.4050
sub_25:Test (Best Model) - Loss: 2.0990 - Accuracy: 0.4559 - F1: 0.4296
sub_25:Test (Best Model) - Loss: 1.7590 - Accuracy: 0.4412 - F1: 0.4196
sub_25:Test (Best Model) - Loss: 1.7008 - Accuracy: 0.4559 - F1: 0.3746
sub_25:Test (Best Model) - Loss: 1.8793 - Accuracy: 0.3971 - F1: 0.3126
sub_26:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.5072 - F1: 0.5272
sub_26:Test (Best Model) - Loss: 1.6692 - Accuracy: 0.5072 - F1: 0.5193
sub_26:Test (Best Model) - Loss: 1.5864 - Accuracy: 0.4928 - F1: 0.4972
sub_26:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.5072 - F1: 0.5069
sub_26:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.4928 - F1: 0.4952
sub_26:Test (Best Model) - Loss: 2.3313 - Accuracy: 0.3235 - F1: 0.3429
sub_26:Test (Best Model) - Loss: 2.3222 - Accuracy: 0.2941 - F1: 0.3140
sub_26:Test (Best Model) - Loss: 2.2745 - Accuracy: 0.4706 - F1: 0.4421
sub_26:Test (Best Model) - Loss: 2.2167 - Accuracy: 0.3971 - F1: 0.3995
sub_26:Test (Best Model) - Loss: 2.3136 - Accuracy: 0.2941 - F1: 0.3272
sub_26:Test (Best Model) - Loss: 1.8425 - Accuracy: 0.4559 - F1: 0.4870
sub_26:Test (Best Model) - Loss: 2.4392 - Accuracy: 0.4412 - F1: 0.4629
sub_26:Test (Best Model) - Loss: 2.2020 - Accuracy: 0.5147 - F1: 0.5315
sub_26:Test (Best Model) - Loss: 2.0824 - Accuracy: 0.4853 - F1: 0.5090
sub_26:Test (Best Model) - Loss: 2.1425 - Accuracy: 0.5000 - F1: 0.5238
sub_27:Test (Best Model) - Loss: 2.0320 - Accuracy: 0.4928 - F1: 0.4721
sub_27:Test (Best Model) - Loss: 1.3962 - Accuracy: 0.4638 - F1: 0.4524
sub_27:Test (Best Model) - Loss: 1.6455 - Accuracy: 0.3768 - F1: 0.3528
sub_27:Test (Best Model) - Loss: 1.8504 - Accuracy: 0.4638 - F1: 0.4590
sub_27:Test (Best Model) - Loss: 1.6540 - Accuracy: 0.3913 - F1: 0.3913
sub_27:Test (Best Model) - Loss: 3.4535 - Accuracy: 0.4348 - F1: 0.3846
sub_27:Test (Best Model) - Loss: 4.1646 - Accuracy: 0.3333 - F1: 0.2985
sub_27:Test (Best Model) - Loss: 3.5247 - Accuracy: 0.4203 - F1: 0.3912
sub_27:Test (Best Model) - Loss: 3.2767 - Accuracy: 0.4783 - F1: 0.4283
sub_27:Test (Best Model) - Loss: 3.3749 - Accuracy: 0.3478 - F1: 0.3053
sub_27:Test (Best Model) - Loss: 1.8805 - Accuracy: 0.4265 - F1: 0.4275
sub_27:Test (Best Model) - Loss: 1.7891 - Accuracy: 0.4265 - F1: 0.4212
sub_27:Test (Best Model) - Loss: 2.2931 - Accuracy: 0.4118 - F1: 0.4066
sub_27:Test (Best Model) - Loss: 1.9411 - Accuracy: 0.4412 - F1: 0.4409
sub_27:Test (Best Model) - Loss: 2.1170 - Accuracy: 0.3824 - F1: 0.3838
sub_28:Test (Best Model) - Loss: 3.0700 - Accuracy: 0.2794 - F1: 0.2794
sub_28:Test (Best Model) - Loss: 2.7805 - Accuracy: 0.3529 - F1: 0.3334
sub_28:Test (Best Model) - Loss: 3.3019 - Accuracy: 0.2941 - F1: 0.2744
sub_28:Test (Best Model) - Loss: 2.9087 - Accuracy: 0.2647 - F1: 0.2508
sub_28:Test (Best Model) - Loss: 3.6892 - Accuracy: 0.2794 - F1: 0.2952
sub_28:Test (Best Model) - Loss: 5.9133 - Accuracy: 0.2059 - F1: 0.1956
sub_28:Test (Best Model) - Loss: 4.5435 - Accuracy: 0.2500 - F1: 0.2496
sub_28:Test (Best Model) - Loss: 6.0347 - Accuracy: 0.2059 - F1: 0.1852
sub_28:Test (Best Model) - Loss: 4.0630 - Accuracy: 0.2794 - F1: 0.2636
sub_28:Test (Best Model) - Loss: 4.7015 - Accuracy: 0.3088 - F1: 0.2470
sub_28:Test (Best Model) - Loss: 2.1408 - Accuracy: 0.4412 - F1: 0.4154
sub_28:Test (Best Model) - Loss: 1.9630 - Accuracy: 0.4706 - F1: 0.4467
sub_28:Test (Best Model) - Loss: 2.0119 - Accuracy: 0.3824 - F1: 0.3749
sub_28:Test (Best Model) - Loss: 1.7099 - Accuracy: 0.5147 - F1: 0.4973
sub_28:Test (Best Model) - Loss: 1.6526 - Accuracy: 0.4412 - F1: 0.4243
sub_29:Test (Best Model) - Loss: 2.5916 - Accuracy: 0.5441 - F1: 0.5305
sub_29:Test (Best Model) - Loss: 2.1840 - Accuracy: 0.5294 - F1: 0.5460
sub_29:Test (Best Model) - Loss: 1.9143 - Accuracy: 0.5882 - F1: 0.5938
sub_29:Test (Best Model) - Loss: 3.3288 - Accuracy: 0.5147 - F1: 0.5004
sub_29:Test (Best Model) - Loss: 2.2977 - Accuracy: 0.5588 - F1: 0.5462
sub_29:Test (Best Model) - Loss: 1.0460 - Accuracy: 0.6029 - F1: 0.6170
sub_29:Test (Best Model) - Loss: 1.3770 - Accuracy: 0.6324 - F1: 0.6296
sub_29:Test (Best Model) - Loss: 1.0745 - Accuracy: 0.6029 - F1: 0.6183
sub_29:Test (Best Model) - Loss: 1.2939 - Accuracy: 0.6324 - F1: 0.6309
sub_29:Test (Best Model) - Loss: 1.3651 - Accuracy: 0.5147 - F1: 0.5176
sub_29:Test (Best Model) - Loss: 1.4330 - Accuracy: 0.6087 - F1: 0.6160
sub_29:Test (Best Model) - Loss: 1.4309 - Accuracy: 0.5797 - F1: 0.5935
sub_29:Test (Best Model) - Loss: 1.8522 - Accuracy: 0.5217 - F1: 0.5394
sub_29:Test (Best Model) - Loss: 1.5898 - Accuracy: 0.6087 - F1: 0.6267
sub_29:Test (Best Model) - Loss: 1.6261 - Accuracy: 0.6377 - F1: 0.6510

=== Summary Results ===

acc: 42.21 ± 7.07
F1: 41.56 ± 7.15
acc-in: 52.39 ± 6.71
F1-in: 50.67 ± 6.72
