lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.4522 - Accuracy: 0.5441 - F1: 0.5631
sub_1:Test (Best Model) - Loss: 1.9013 - Accuracy: 0.4559 - F1: 0.4821
sub_1:Test (Best Model) - Loss: 1.9060 - Accuracy: 0.4412 - F1: 0.4926
sub_1:Test (Best Model) - Loss: 1.4493 - Accuracy: 0.5294 - F1: 0.5671
sub_1:Test (Best Model) - Loss: 1.6770 - Accuracy: 0.4559 - F1: 0.4913
sub_1:Test (Best Model) - Loss: 2.3086 - Accuracy: 0.4348 - F1: 0.4075
sub_1:Test (Best Model) - Loss: 1.9781 - Accuracy: 0.4928 - F1: 0.4707
sub_1:Test (Best Model) - Loss: 2.3949 - Accuracy: 0.4348 - F1: 0.4038
sub_1:Test (Best Model) - Loss: 2.3426 - Accuracy: 0.3913 - F1: 0.3874
sub_1:Test (Best Model) - Loss: 2.3302 - Accuracy: 0.4348 - F1: 0.4146
sub_1:Test (Best Model) - Loss: 1.9638 - Accuracy: 0.3971 - F1: 0.3960
sub_1:Test (Best Model) - Loss: 1.8955 - Accuracy: 0.5147 - F1: 0.4942
sub_1:Test (Best Model) - Loss: 1.8243 - Accuracy: 0.5882 - F1: 0.5714
sub_1:Test (Best Model) - Loss: 2.1058 - Accuracy: 0.4265 - F1: 0.3964
sub_1:Test (Best Model) - Loss: 1.8751 - Accuracy: 0.4559 - F1: 0.4336
sub_2:Test (Best Model) - Loss: 2.3653 - Accuracy: 0.2754 - F1: 0.2922
sub_2:Test (Best Model) - Loss: 2.9344 - Accuracy: 0.2319 - F1: 0.2661
sub_2:Test (Best Model) - Loss: 3.1280 - Accuracy: 0.2754 - F1: 0.3121
sub_2:Test (Best Model) - Loss: 2.6994 - Accuracy: 0.2174 - F1: 0.2452
sub_2:Test (Best Model) - Loss: 3.2239 - Accuracy: 0.2754 - F1: 0.3067
sub_2:Test (Best Model) - Loss: 2.2488 - Accuracy: 0.2647 - F1: 0.2588
sub_2:Test (Best Model) - Loss: 2.1023 - Accuracy: 0.2647 - F1: 0.2620
sub_2:Test (Best Model) - Loss: 2.0017 - Accuracy: 0.3676 - F1: 0.3794
sub_2:Test (Best Model) - Loss: 2.3321 - Accuracy: 0.3529 - F1: 0.3319
sub_2:Test (Best Model) - Loss: 1.9673 - Accuracy: 0.4118 - F1: 0.4139
sub_2:Test (Best Model) - Loss: 2.7191 - Accuracy: 0.3913 - F1: 0.3652
sub_2:Test (Best Model) - Loss: 2.2188 - Accuracy: 0.4203 - F1: 0.3803
sub_2:Test (Best Model) - Loss: 2.4874 - Accuracy: 0.4348 - F1: 0.4363
sub_2:Test (Best Model) - Loss: 2.1759 - Accuracy: 0.3913 - F1: 0.3627
sub_2:Test (Best Model) - Loss: 2.5051 - Accuracy: 0.3768 - F1: 0.3549
sub_3:Test (Best Model) - Loss: 3.0145 - Accuracy: 0.3382 - F1: 0.3362
sub_3:Test (Best Model) - Loss: 2.4137 - Accuracy: 0.3382 - F1: 0.3239
sub_3:Test (Best Model) - Loss: 2.8511 - Accuracy: 0.3088 - F1: 0.3125
sub_3:Test (Best Model) - Loss: 2.8020 - Accuracy: 0.2647 - F1: 0.2436
sub_3:Test (Best Model) - Loss: 2.5892 - Accuracy: 0.3529 - F1: 0.3309
sub_3:Test (Best Model) - Loss: 2.0764 - Accuracy: 0.3913 - F1: 0.3814
sub_3:Test (Best Model) - Loss: 2.6612 - Accuracy: 0.2609 - F1: 0.2692
sub_3:Test (Best Model) - Loss: 2.4531 - Accuracy: 0.2319 - F1: 0.1930
sub_3:Test (Best Model) - Loss: 2.0467 - Accuracy: 0.4058 - F1: 0.3824
sub_3:Test (Best Model) - Loss: 2.3321 - Accuracy: 0.3043 - F1: 0.2784
sub_3:Test (Best Model) - Loss: 2.7154 - Accuracy: 0.3188 - F1: 0.3103
sub_3:Test (Best Model) - Loss: 3.2063 - Accuracy: 0.3188 - F1: 0.3056
sub_3:Test (Best Model) - Loss: 3.9749 - Accuracy: 0.3043 - F1: 0.2489
sub_3:Test (Best Model) - Loss: 3.4571 - Accuracy: 0.2899 - F1: 0.2673
sub_3:Test (Best Model) - Loss: 3.1812 - Accuracy: 0.3188 - F1: 0.2885
sub_4:Test (Best Model) - Loss: 1.8935 - Accuracy: 0.5217 - F1: 0.5281
sub_4:Test (Best Model) - Loss: 1.3972 - Accuracy: 0.6087 - F1: 0.6057
sub_4:Test (Best Model) - Loss: 1.7036 - Accuracy: 0.5652 - F1: 0.5798
sub_4:Test (Best Model) - Loss: 1.4513 - Accuracy: 0.5942 - F1: 0.6075
sub_4:Test (Best Model) - Loss: 2.1676 - Accuracy: 0.5652 - F1: 0.5564
sub_4:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.4928 - F1: 0.4938
sub_4:Test (Best Model) - Loss: 1.7417 - Accuracy: 0.5507 - F1: 0.5419
sub_4:Test (Best Model) - Loss: 1.8708 - Accuracy: 0.5217 - F1: 0.5225
sub_4:Test (Best Model) - Loss: 1.7217 - Accuracy: 0.5217 - F1: 0.4816
sub_4:Test (Best Model) - Loss: 1.9445 - Accuracy: 0.5072 - F1: 0.5282
sub_4:Test (Best Model) - Loss: 2.2881 - Accuracy: 0.4638 - F1: 0.4037
sub_4:Test (Best Model) - Loss: 2.3977 - Accuracy: 0.4348 - F1: 0.4268
sub_4:Test (Best Model) - Loss: 2.3783 - Accuracy: 0.3623 - F1: 0.3406
sub_4:Test (Best Model) - Loss: 3.0223 - Accuracy: 0.4203 - F1: 0.4002
sub_4:Test (Best Model) - Loss: 3.2539 - Accuracy: 0.4638 - F1: 0.4421
sub_5:Test (Best Model) - Loss: 4.3109 - Accuracy: 0.5147 - F1: 0.4944
sub_5:Test (Best Model) - Loss: 4.6619 - Accuracy: 0.4706 - F1: 0.4323
sub_5:Test (Best Model) - Loss: 4.4812 - Accuracy: 0.4559 - F1: 0.4330
sub_5:Test (Best Model) - Loss: 4.2576 - Accuracy: 0.4853 - F1: 0.4587
sub_5:Test (Best Model) - Loss: 3.0390 - Accuracy: 0.4853 - F1: 0.4600
sub_5:Test (Best Model) - Loss: 2.2685 - Accuracy: 0.4706 - F1: 0.4034
sub_5:Test (Best Model) - Loss: 1.4879 - Accuracy: 0.5294 - F1: 0.4826
sub_5:Test (Best Model) - Loss: 2.5929 - Accuracy: 0.4559 - F1: 0.4208
sub_5:Test (Best Model) - Loss: 1.8980 - Accuracy: 0.5441 - F1: 0.5225
sub_5:Test (Best Model) - Loss: 2.7137 - Accuracy: 0.5882 - F1: 0.5382
sub_5:Test (Best Model) - Loss: 2.0318 - Accuracy: 0.4265 - F1: 0.4141
sub_5:Test (Best Model) - Loss: 3.1152 - Accuracy: 0.3971 - F1: 0.3780
sub_5:Test (Best Model) - Loss: 2.4191 - Accuracy: 0.3824 - F1: 0.3873
sub_5:Test (Best Model) - Loss: 2.5015 - Accuracy: 0.3235 - F1: 0.3111
sub_5:Test (Best Model) - Loss: 2.3428 - Accuracy: 0.3529 - F1: 0.3546
sub_6:Test (Best Model) - Loss: 1.7148 - Accuracy: 0.4559 - F1: 0.4736
sub_6:Test (Best Model) - Loss: 1.6184 - Accuracy: 0.5441 - F1: 0.5273
sub_6:Test (Best Model) - Loss: 1.6622 - Accuracy: 0.4706 - F1: 0.4789
sub_6:Test (Best Model) - Loss: 1.9034 - Accuracy: 0.4412 - F1: 0.4467
sub_6:Test (Best Model) - Loss: 1.7382 - Accuracy: 0.4265 - F1: 0.4390
sub_6:Test (Best Model) - Loss: 1.9432 - Accuracy: 0.4928 - F1: 0.4530
sub_6:Test (Best Model) - Loss: 2.1703 - Accuracy: 0.4783 - F1: 0.4034
sub_6:Test (Best Model) - Loss: 2.7110 - Accuracy: 0.3913 - F1: 0.2993
sub_6:Test (Best Model) - Loss: 2.2578 - Accuracy: 0.4203 - F1: 0.3740
sub_6:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.5072 - F1: 0.5141
sub_6:Test (Best Model) - Loss: 1.9723 - Accuracy: 0.3913 - F1: 0.4093
sub_6:Test (Best Model) - Loss: 2.7573 - Accuracy: 0.4493 - F1: 0.4336
sub_6:Test (Best Model) - Loss: 1.9919 - Accuracy: 0.4928 - F1: 0.4929
sub_6:Test (Best Model) - Loss: 1.7447 - Accuracy: 0.5362 - F1: 0.5263
sub_6:Test (Best Model) - Loss: 1.7540 - Accuracy: 0.5072 - F1: 0.4993
sub_7:Test (Best Model) - Loss: 1.2534 - Accuracy: 0.6471 - F1: 0.6258
sub_7:Test (Best Model) - Loss: 1.5244 - Accuracy: 0.5588 - F1: 0.5236
sub_7:Test (Best Model) - Loss: 1.7139 - Accuracy: 0.4559 - F1: 0.4255
sub_7:Test (Best Model) - Loss: 0.9645 - Accuracy: 0.6471 - F1: 0.6415
sub_7:Test (Best Model) - Loss: 1.0764 - Accuracy: 0.6029 - F1: 0.5967
sub_7:Test (Best Model) - Loss: 2.5325 - Accuracy: 0.4118 - F1: 0.3711
sub_7:Test (Best Model) - Loss: 2.4974 - Accuracy: 0.4265 - F1: 0.3990
sub_7:Test (Best Model) - Loss: 2.5585 - Accuracy: 0.4706 - F1: 0.4557
sub_7:Test (Best Model) - Loss: 2.7553 - Accuracy: 0.4265 - F1: 0.4115
sub_7:Test (Best Model) - Loss: 2.3441 - Accuracy: 0.4559 - F1: 0.4111
sub_7:Test (Best Model) - Loss: 2.9547 - Accuracy: 0.3824 - F1: 0.3665
sub_7:Test (Best Model) - Loss: 1.9400 - Accuracy: 0.5000 - F1: 0.4721
sub_7:Test (Best Model) - Loss: 1.6280 - Accuracy: 0.4706 - F1: 0.4450
sub_7:Test (Best Model) - Loss: 2.2333 - Accuracy: 0.4265 - F1: 0.4241
sub_7:Test (Best Model) - Loss: 2.3062 - Accuracy: 0.4853 - F1: 0.4977
sub_8:Test (Best Model) - Loss: 2.9268 - Accuracy: 0.2794 - F1: 0.3025
sub_8:Test (Best Model) - Loss: 2.7903 - Accuracy: 0.2794 - F1: 0.2772
sub_8:Test (Best Model) - Loss: 3.5409 - Accuracy: 0.2647 - F1: 0.2921
sub_8:Test (Best Model) - Loss: 2.7313 - Accuracy: 0.3382 - F1: 0.3619
sub_8:Test (Best Model) - Loss: 2.4319 - Accuracy: 0.3235 - F1: 0.3416
sub_8:Test (Best Model) - Loss: 1.9763 - Accuracy: 0.3676 - F1: 0.3866
sub_8:Test (Best Model) - Loss: 2.3861 - Accuracy: 0.3676 - F1: 0.3625
sub_8:Test (Best Model) - Loss: 2.1996 - Accuracy: 0.3824 - F1: 0.3902
sub_8:Test (Best Model) - Loss: 2.6274 - Accuracy: 0.2647 - F1: 0.2783
sub_8:Test (Best Model) - Loss: 2.4868 - Accuracy: 0.3088 - F1: 0.2982
sub_8:Test (Best Model) - Loss: 3.2768 - Accuracy: 0.3824 - F1: 0.3575
sub_8:Test (Best Model) - Loss: 3.1933 - Accuracy: 0.2500 - F1: 0.2284
sub_8:Test (Best Model) - Loss: 2.8861 - Accuracy: 0.3382 - F1: 0.3466
sub_8:Test (Best Model) - Loss: 3.2341 - Accuracy: 0.3529 - F1: 0.3533
sub_8:Test (Best Model) - Loss: 2.5249 - Accuracy: 0.3088 - F1: 0.2990
sub_9:Test (Best Model) - Loss: 2.1774 - Accuracy: 0.5147 - F1: 0.5284
sub_9:Test (Best Model) - Loss: 1.9194 - Accuracy: 0.5735 - F1: 0.5836
sub_9:Test (Best Model) - Loss: 2.6579 - Accuracy: 0.5000 - F1: 0.5252
sub_9:Test (Best Model) - Loss: 2.3990 - Accuracy: 0.5000 - F1: 0.5288
sub_9:Test (Best Model) - Loss: 2.0511 - Accuracy: 0.5735 - F1: 0.5972
sub_9:Test (Best Model) - Loss: 4.0249 - Accuracy: 0.3235 - F1: 0.3037
sub_9:Test (Best Model) - Loss: 4.2364 - Accuracy: 0.3824 - F1: 0.3726
sub_9:Test (Best Model) - Loss: 3.0734 - Accuracy: 0.3676 - F1: 0.3694
sub_9:Test (Best Model) - Loss: 2.9955 - Accuracy: 0.3971 - F1: 0.4223
sub_9:Test (Best Model) - Loss: 3.4069 - Accuracy: 0.3235 - F1: 0.3225
sub_9:Test (Best Model) - Loss: 2.8371 - Accuracy: 0.4853 - F1: 0.4930
sub_9:Test (Best Model) - Loss: 3.0741 - Accuracy: 0.5147 - F1: 0.5366
sub_9:Test (Best Model) - Loss: 2.4802 - Accuracy: 0.4118 - F1: 0.4279
sub_9:Test (Best Model) - Loss: 3.0643 - Accuracy: 0.3971 - F1: 0.4130
sub_9:Test (Best Model) - Loss: 3.1853 - Accuracy: 0.4412 - F1: 0.4754
sub_10:Test (Best Model) - Loss: 2.7995 - Accuracy: 0.2941 - F1: 0.3002
sub_10:Test (Best Model) - Loss: 2.0982 - Accuracy: 0.3382 - F1: 0.3295
sub_10:Test (Best Model) - Loss: 2.8894 - Accuracy: 0.2794 - F1: 0.2727
sub_10:Test (Best Model) - Loss: 2.3056 - Accuracy: 0.3971 - F1: 0.3915
sub_10:Test (Best Model) - Loss: 2.4701 - Accuracy: 0.3529 - F1: 0.3567
sub_10:Test (Best Model) - Loss: 2.2056 - Accuracy: 0.3088 - F1: 0.3092
sub_10:Test (Best Model) - Loss: 2.2957 - Accuracy: 0.2353 - F1: 0.2383
sub_10:Test (Best Model) - Loss: 2.5447 - Accuracy: 0.2500 - F1: 0.2536
sub_10:Test (Best Model) - Loss: 2.1500 - Accuracy: 0.2941 - F1: 0.2826
sub_10:Test (Best Model) - Loss: 2.4145 - Accuracy: 0.2941 - F1: 0.2725
sub_10:Test (Best Model) - Loss: 3.0341 - Accuracy: 0.3043 - F1: 0.3000
sub_10:Test (Best Model) - Loss: 2.7914 - Accuracy: 0.3188 - F1: 0.3339
sub_10:Test (Best Model) - Loss: 2.7404 - Accuracy: 0.3188 - F1: 0.3246
sub_10:Test (Best Model) - Loss: 2.3801 - Accuracy: 0.3478 - F1: 0.3302
sub_10:Test (Best Model) - Loss: 2.3523 - Accuracy: 0.3043 - F1: 0.3039
sub_11:Test (Best Model) - Loss: 3.0526 - Accuracy: 0.3333 - F1: 0.3184
sub_11:Test (Best Model) - Loss: 2.6261 - Accuracy: 0.2899 - F1: 0.2697
sub_11:Test (Best Model) - Loss: 3.4577 - Accuracy: 0.2754 - F1: 0.2679
sub_11:Test (Best Model) - Loss: 3.8319 - Accuracy: 0.3333 - F1: 0.3106
sub_11:Test (Best Model) - Loss: 3.4734 - Accuracy: 0.2319 - F1: 0.2417
sub_11:Test (Best Model) - Loss: 2.6085 - Accuracy: 0.4058 - F1: 0.3146
sub_11:Test (Best Model) - Loss: 2.0509 - Accuracy: 0.4638 - F1: 0.4090
sub_11:Test (Best Model) - Loss: 2.2867 - Accuracy: 0.4783 - F1: 0.4530
sub_11:Test (Best Model) - Loss: 3.2749 - Accuracy: 0.4348 - F1: 0.3957
sub_11:Test (Best Model) - Loss: 2.6719 - Accuracy: 0.4058 - F1: 0.3393
sub_11:Test (Best Model) - Loss: 1.9611 - Accuracy: 0.4493 - F1: 0.4145
sub_11:Test (Best Model) - Loss: 2.1141 - Accuracy: 0.4203 - F1: 0.3975
sub_11:Test (Best Model) - Loss: 2.2636 - Accuracy: 0.4638 - F1: 0.4112
sub_11:Test (Best Model) - Loss: 1.7108 - Accuracy: 0.4203 - F1: 0.3574
sub_11:Test (Best Model) - Loss: 2.3465 - Accuracy: 0.4493 - F1: 0.3962
sub_12:Test (Best Model) - Loss: 1.4602 - Accuracy: 0.5882 - F1: 0.5765
sub_12:Test (Best Model) - Loss: 1.9043 - Accuracy: 0.5147 - F1: 0.4820
sub_12:Test (Best Model) - Loss: 2.1011 - Accuracy: 0.5294 - F1: 0.4900
sub_12:Test (Best Model) - Loss: 1.2608 - Accuracy: 0.6029 - F1: 0.5968
sub_12:Test (Best Model) - Loss: 1.6862 - Accuracy: 0.5882 - F1: 0.5671
sub_12:Test (Best Model) - Loss: 1.8268 - Accuracy: 0.5217 - F1: 0.5269
sub_12:Test (Best Model) - Loss: 1.9562 - Accuracy: 0.5362 - F1: 0.5524
sub_12:Test (Best Model) - Loss: 1.9226 - Accuracy: 0.4928 - F1: 0.4691
sub_12:Test (Best Model) - Loss: 2.1141 - Accuracy: 0.5217 - F1: 0.5136
sub_12:Test (Best Model) - Loss: 2.3018 - Accuracy: 0.5217 - F1: 0.5489
sub_12:Test (Best Model) - Loss: 1.8240 - Accuracy: 0.5147 - F1: 0.5142
sub_12:Test (Best Model) - Loss: 2.2300 - Accuracy: 0.4706 - F1: 0.4848
sub_12:Test (Best Model) - Loss: 2.2799 - Accuracy: 0.4265 - F1: 0.4453
sub_12:Test (Best Model) - Loss: 2.4870 - Accuracy: 0.3824 - F1: 0.3758
sub_12:Test (Best Model) - Loss: 2.1499 - Accuracy: 0.3824 - F1: 0.3995
sub_13:Test (Best Model) - Loss: 2.5326 - Accuracy: 0.5441 - F1: 0.5350
sub_13:Test (Best Model) - Loss: 2.3155 - Accuracy: 0.5588 - F1: 0.5618
sub_13:Test (Best Model) - Loss: 2.6847 - Accuracy: 0.4853 - F1: 0.5140
sub_13:Test (Best Model) - Loss: 2.3800 - Accuracy: 0.5000 - F1: 0.4818
sub_13:Test (Best Model) - Loss: 2.4572 - Accuracy: 0.4853 - F1: 0.5078
sub_13:Test (Best Model) - Loss: 2.4263 - Accuracy: 0.5217 - F1: 0.5237
sub_13:Test (Best Model) - Loss: 1.9054 - Accuracy: 0.5217 - F1: 0.5018
sub_13:Test (Best Model) - Loss: 2.4998 - Accuracy: 0.4493 - F1: 0.4459
sub_13:Test (Best Model) - Loss: 2.9262 - Accuracy: 0.4638 - F1: 0.4701
sub_13:Test (Best Model) - Loss: 2.5842 - Accuracy: 0.4493 - F1: 0.4472
sub_13:Test (Best Model) - Loss: 2.2929 - Accuracy: 0.4412 - F1: 0.4183
sub_13:Test (Best Model) - Loss: 2.4311 - Accuracy: 0.4706 - F1: 0.4861
sub_13:Test (Best Model) - Loss: 2.7596 - Accuracy: 0.3824 - F1: 0.3822
sub_13:Test (Best Model) - Loss: 2.2452 - Accuracy: 0.4412 - F1: 0.4658
sub_13:Test (Best Model) - Loss: 2.2986 - Accuracy: 0.4706 - F1: 0.4662
sub_14:Test (Best Model) - Loss: 2.3143 - Accuracy: 0.3382 - F1: 0.3691
sub_14:Test (Best Model) - Loss: 2.5409 - Accuracy: 0.3824 - F1: 0.3936
sub_14:Test (Best Model) - Loss: 2.6695 - Accuracy: 0.3824 - F1: 0.3861
sub_14:Test (Best Model) - Loss: 3.2005 - Accuracy: 0.2794 - F1: 0.3282
sub_14:Test (Best Model) - Loss: 2.8698 - Accuracy: 0.2794 - F1: 0.2968
sub_14:Test (Best Model) - Loss: 2.5827 - Accuracy: 0.4412 - F1: 0.4638
sub_14:Test (Best Model) - Loss: 3.1437 - Accuracy: 0.4412 - F1: 0.4654
sub_14:Test (Best Model) - Loss: 3.0204 - Accuracy: 0.4559 - F1: 0.4923
sub_14:Test (Best Model) - Loss: 2.7135 - Accuracy: 0.4265 - F1: 0.4532
sub_14:Test (Best Model) - Loss: 3.1490 - Accuracy: 0.3676 - F1: 0.3793
sub_14:Test (Best Model) - Loss: 2.8536 - Accuracy: 0.3676 - F1: 0.3706
sub_14:Test (Best Model) - Loss: 2.3160 - Accuracy: 0.4853 - F1: 0.4859
sub_14:Test (Best Model) - Loss: 2.3785 - Accuracy: 0.4706 - F1: 0.4705
sub_14:Test (Best Model) - Loss: 2.2417 - Accuracy: 0.3971 - F1: 0.4156
sub_14:Test (Best Model) - Loss: 2.3758 - Accuracy: 0.3971 - F1: 0.4069
sub_15:Test (Best Model) - Loss: 2.4496 - Accuracy: 0.5000 - F1: 0.5235
sub_15:Test (Best Model) - Loss: 3.5097 - Accuracy: 0.3971 - F1: 0.4217
sub_15:Test (Best Model) - Loss: 2.1389 - Accuracy: 0.4853 - F1: 0.5026
sub_15:Test (Best Model) - Loss: 2.1591 - Accuracy: 0.5147 - F1: 0.5145
sub_15:Test (Best Model) - Loss: 3.1285 - Accuracy: 0.4265 - F1: 0.4592
sub_15:Test (Best Model) - Loss: 1.9434 - Accuracy: 0.5735 - F1: 0.5851
sub_15:Test (Best Model) - Loss: 2.4717 - Accuracy: 0.5588 - F1: 0.5701
sub_15:Test (Best Model) - Loss: 2.0222 - Accuracy: 0.5735 - F1: 0.5909
sub_15:Test (Best Model) - Loss: 2.0731 - Accuracy: 0.5588 - F1: 0.5606
sub_15:Test (Best Model) - Loss: 1.8880 - Accuracy: 0.5441 - F1: 0.5301
sub_15:Test (Best Model) - Loss: 2.7984 - Accuracy: 0.4265 - F1: 0.4063
sub_15:Test (Best Model) - Loss: 1.9497 - Accuracy: 0.4412 - F1: 0.4103
sub_15:Test (Best Model) - Loss: 3.3708 - Accuracy: 0.3971 - F1: 0.3167
sub_15:Test (Best Model) - Loss: 2.5794 - Accuracy: 0.4412 - F1: 0.4184
sub_15:Test (Best Model) - Loss: 3.5182 - Accuracy: 0.4412 - F1: 0.4285
sub_16:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.6324 - F1: 0.5918
sub_16:Test (Best Model) - Loss: 1.4979 - Accuracy: 0.5588 - F1: 0.5074
sub_16:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.5294 - F1: 0.4558
sub_16:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.5147 - F1: 0.4746
sub_16:Test (Best Model) - Loss: 1.0211 - Accuracy: 0.6029 - F1: 0.5247
sub_16:Test (Best Model) - Loss: 1.8959 - Accuracy: 0.5294 - F1: 0.5281
sub_16:Test (Best Model) - Loss: 1.9323 - Accuracy: 0.3971 - F1: 0.3568
sub_16:Test (Best Model) - Loss: 2.2680 - Accuracy: 0.4706 - F1: 0.4477
sub_16:Test (Best Model) - Loss: 1.7309 - Accuracy: 0.5735 - F1: 0.5579
sub_16:Test (Best Model) - Loss: 2.6151 - Accuracy: 0.4853 - F1: 0.4755
sub_16:Test (Best Model) - Loss: 1.8885 - Accuracy: 0.5147 - F1: 0.4305
sub_16:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.5147 - F1: 0.4814
sub_16:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.6176 - F1: 0.5417
sub_16:Test (Best Model) - Loss: 1.2522 - Accuracy: 0.6029 - F1: 0.5807
sub_16:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.5882 - F1: 0.5226
sub_17:Test (Best Model) - Loss: 2.1629 - Accuracy: 0.4493 - F1: 0.4141
sub_17:Test (Best Model) - Loss: 1.4976 - Accuracy: 0.4638 - F1: 0.4820
sub_17:Test (Best Model) - Loss: 2.1026 - Accuracy: 0.3768 - F1: 0.3905
sub_17:Test (Best Model) - Loss: 2.3228 - Accuracy: 0.3188 - F1: 0.2926
sub_17:Test (Best Model) - Loss: 2.0697 - Accuracy: 0.3333 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 4.4205 - Accuracy: 0.3333 - F1: 0.2950
sub_17:Test (Best Model) - Loss: 4.9471 - Accuracy: 0.3768 - F1: 0.3317
sub_17:Test (Best Model) - Loss: 3.6279 - Accuracy: 0.5072 - F1: 0.4476
sub_17:Test (Best Model) - Loss: 3.6896 - Accuracy: 0.4348 - F1: 0.4092
sub_17:Test (Best Model) - Loss: 3.3533 - Accuracy: 0.4058 - F1: 0.3586
sub_17:Test (Best Model) - Loss: 1.8650 - Accuracy: 0.5000 - F1: 0.4941
sub_17:Test (Best Model) - Loss: 2.1524 - Accuracy: 0.4118 - F1: 0.4104
sub_17:Test (Best Model) - Loss: 2.8219 - Accuracy: 0.3824 - F1: 0.3814
sub_17:Test (Best Model) - Loss: 2.1274 - Accuracy: 0.4412 - F1: 0.4415
sub_17:Test (Best Model) - Loss: 2.0843 - Accuracy: 0.4265 - F1: 0.4385
sub_18:Test (Best Model) - Loss: 1.7041 - Accuracy: 0.3913 - F1: 0.3885
sub_18:Test (Best Model) - Loss: 1.8854 - Accuracy: 0.3913 - F1: 0.4117
sub_18:Test (Best Model) - Loss: 1.7576 - Accuracy: 0.4058 - F1: 0.3917
sub_18:Test (Best Model) - Loss: 2.3852 - Accuracy: 0.3913 - F1: 0.3830
sub_18:Test (Best Model) - Loss: 1.5538 - Accuracy: 0.4638 - F1: 0.4879
sub_18:Test (Best Model) - Loss: 2.3862 - Accuracy: 0.3235 - F1: 0.3524
sub_18:Test (Best Model) - Loss: 2.4321 - Accuracy: 0.3382 - F1: 0.3597
sub_18:Test (Best Model) - Loss: 2.7448 - Accuracy: 0.4265 - F1: 0.4067
sub_18:Test (Best Model) - Loss: 2.4052 - Accuracy: 0.3971 - F1: 0.4038
sub_18:Test (Best Model) - Loss: 2.2720 - Accuracy: 0.3676 - F1: 0.3837
sub_18:Test (Best Model) - Loss: 2.7276 - Accuracy: 0.2794 - F1: 0.3149
sub_18:Test (Best Model) - Loss: 2.4699 - Accuracy: 0.3235 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 2.4783 - Accuracy: 0.3382 - F1: 0.3635
sub_18:Test (Best Model) - Loss: 2.6204 - Accuracy: 0.3235 - F1: 0.3428
sub_18:Test (Best Model) - Loss: 2.2933 - Accuracy: 0.3824 - F1: 0.4086
sub_19:Test (Best Model) - Loss: 3.5304 - Accuracy: 0.1324 - F1: 0.1086
sub_19:Test (Best Model) - Loss: 3.7133 - Accuracy: 0.1324 - F1: 0.1129
sub_19:Test (Best Model) - Loss: 3.8000 - Accuracy: 0.1912 - F1: 0.2177
sub_19:Test (Best Model) - Loss: 2.7787 - Accuracy: 0.3088 - F1: 0.2865
sub_19:Test (Best Model) - Loss: 4.1215 - Accuracy: 0.1471 - F1: 0.1194
sub_19:Test (Best Model) - Loss: 2.2574 - Accuracy: 0.3824 - F1: 0.3102
sub_19:Test (Best Model) - Loss: 2.2861 - Accuracy: 0.3824 - F1: 0.3276
sub_19:Test (Best Model) - Loss: 2.2542 - Accuracy: 0.3676 - F1: 0.3303
sub_19:Test (Best Model) - Loss: 2.2133 - Accuracy: 0.4706 - F1: 0.4156
sub_19:Test (Best Model) - Loss: 2.0762 - Accuracy: 0.5000 - F1: 0.4978
sub_19:Test (Best Model) - Loss: 3.3247 - Accuracy: 0.3824 - F1: 0.3661
sub_19:Test (Best Model) - Loss: 3.8236 - Accuracy: 0.2647 - F1: 0.2468
sub_19:Test (Best Model) - Loss: 2.7623 - Accuracy: 0.2794 - F1: 0.2594
sub_19:Test (Best Model) - Loss: 3.3486 - Accuracy: 0.2794 - F1: 0.2757
sub_19:Test (Best Model) - Loss: 2.8497 - Accuracy: 0.3382 - F1: 0.3299
sub_20:Test (Best Model) - Loss: 1.6991 - Accuracy: 0.6324 - F1: 0.6311
sub_20:Test (Best Model) - Loss: 2.4835 - Accuracy: 0.5147 - F1: 0.5242
sub_20:Test (Best Model) - Loss: 2.3335 - Accuracy: 0.5882 - F1: 0.5955
sub_20:Test (Best Model) - Loss: 2.1790 - Accuracy: 0.5000 - F1: 0.5161
sub_20:Test (Best Model) - Loss: 2.6437 - Accuracy: 0.5441 - F1: 0.5456
sub_20:Test (Best Model) - Loss: 2.0582 - Accuracy: 0.4559 - F1: 0.4829
sub_20:Test (Best Model) - Loss: 2.6070 - Accuracy: 0.4265 - F1: 0.4352
sub_20:Test (Best Model) - Loss: 2.6550 - Accuracy: 0.4118 - F1: 0.4286
sub_20:Test (Best Model) - Loss: 2.3133 - Accuracy: 0.4265 - F1: 0.4198
sub_20:Test (Best Model) - Loss: 1.9867 - Accuracy: 0.4853 - F1: 0.5080
sub_20:Test (Best Model) - Loss: 2.5703 - Accuracy: 0.3768 - F1: 0.3801
sub_20:Test (Best Model) - Loss: 2.5129 - Accuracy: 0.4493 - F1: 0.4617
sub_20:Test (Best Model) - Loss: 2.3997 - Accuracy: 0.4348 - F1: 0.4397
sub_20:Test (Best Model) - Loss: 2.2382 - Accuracy: 0.4348 - F1: 0.4433
sub_20:Test (Best Model) - Loss: 2.9051 - Accuracy: 0.4493 - F1: 0.4593
sub_21:Test (Best Model) - Loss: 2.5692 - Accuracy: 0.4559 - F1: 0.4446
sub_21:Test (Best Model) - Loss: 2.2189 - Accuracy: 0.3971 - F1: 0.3739
sub_21:Test (Best Model) - Loss: 3.6008 - Accuracy: 0.5000 - F1: 0.4740
sub_21:Test (Best Model) - Loss: 2.8285 - Accuracy: 0.3971 - F1: 0.3872
sub_21:Test (Best Model) - Loss: 2.7329 - Accuracy: 0.4265 - F1: 0.4006
sub_21:Test (Best Model) - Loss: 2.5588 - Accuracy: 0.4412 - F1: 0.4217
sub_21:Test (Best Model) - Loss: 1.8113 - Accuracy: 0.3971 - F1: 0.3935
sub_21:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.4412 - F1: 0.4229
sub_21:Test (Best Model) - Loss: 2.1998 - Accuracy: 0.4706 - F1: 0.4423
sub_21:Test (Best Model) - Loss: 1.9610 - Accuracy: 0.5294 - F1: 0.4962
sub_21:Test (Best Model) - Loss: 1.9228 - Accuracy: 0.3824 - F1: 0.3513
sub_21:Test (Best Model) - Loss: 2.1839 - Accuracy: 0.4118 - F1: 0.3964
sub_21:Test (Best Model) - Loss: 2.9464 - Accuracy: 0.3529 - F1: 0.2843
sub_21:Test (Best Model) - Loss: 3.0384 - Accuracy: 0.3382 - F1: 0.2823
sub_21:Test (Best Model) - Loss: 2.0252 - Accuracy: 0.3824 - F1: 0.3503
sub_22:Test (Best Model) - Loss: 2.3783 - Accuracy: 0.3824 - F1: 0.4025
sub_22:Test (Best Model) - Loss: 2.3696 - Accuracy: 0.4706 - F1: 0.4872
sub_22:Test (Best Model) - Loss: 3.0684 - Accuracy: 0.3529 - F1: 0.3767
sub_22:Test (Best Model) - Loss: 2.3257 - Accuracy: 0.4265 - F1: 0.4404
sub_22:Test (Best Model) - Loss: 2.6556 - Accuracy: 0.4118 - F1: 0.4387
sub_22:Test (Best Model) - Loss: 1.8131 - Accuracy: 0.3188 - F1: 0.3337
sub_22:Test (Best Model) - Loss: 1.6447 - Accuracy: 0.3768 - F1: 0.3705
sub_22:Test (Best Model) - Loss: 2.3817 - Accuracy: 0.3333 - F1: 0.2949
sub_22:Test (Best Model) - Loss: 2.2274 - Accuracy: 0.3768 - F1: 0.3865
sub_22:Test (Best Model) - Loss: 1.7988 - Accuracy: 0.3768 - F1: 0.3727
sub_22:Test (Best Model) - Loss: 2.0392 - Accuracy: 0.3824 - F1: 0.3957
sub_22:Test (Best Model) - Loss: 1.8639 - Accuracy: 0.3676 - F1: 0.3910
sub_22:Test (Best Model) - Loss: 2.5016 - Accuracy: 0.3235 - F1: 0.3368
sub_22:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.4265 - F1: 0.4536
sub_22:Test (Best Model) - Loss: 1.9612 - Accuracy: 0.4706 - F1: 0.4762
sub_23:Test (Best Model) - Loss: 2.2641 - Accuracy: 0.4058 - F1: 0.4152
sub_23:Test (Best Model) - Loss: 1.7989 - Accuracy: 0.4638 - F1: 0.4733
sub_23:Test (Best Model) - Loss: 2.1271 - Accuracy: 0.4348 - F1: 0.4705
sub_23:Test (Best Model) - Loss: 1.8250 - Accuracy: 0.5217 - F1: 0.5167
sub_23:Test (Best Model) - Loss: 1.9860 - Accuracy: 0.4928 - F1: 0.5096
sub_23:Test (Best Model) - Loss: 2.1418 - Accuracy: 0.4118 - F1: 0.3861
sub_23:Test (Best Model) - Loss: 2.1378 - Accuracy: 0.4118 - F1: 0.3477
sub_23:Test (Best Model) - Loss: 1.4461 - Accuracy: 0.5735 - F1: 0.5736
sub_23:Test (Best Model) - Loss: 1.7441 - Accuracy: 0.4559 - F1: 0.4576
sub_23:Test (Best Model) - Loss: 1.8024 - Accuracy: 0.4853 - F1: 0.4810
sub_23:Test (Best Model) - Loss: 3.8306 - Accuracy: 0.4203 - F1: 0.4298
sub_23:Test (Best Model) - Loss: 3.7591 - Accuracy: 0.4348 - F1: 0.4363
sub_23:Test (Best Model) - Loss: 3.9188 - Accuracy: 0.3913 - F1: 0.3959
sub_23:Test (Best Model) - Loss: 3.3543 - Accuracy: 0.4058 - F1: 0.3949
sub_23:Test (Best Model) - Loss: 3.7242 - Accuracy: 0.4058 - F1: 0.4065
sub_24:Test (Best Model) - Loss: 2.4160 - Accuracy: 0.3676 - F1: 0.3601
sub_24:Test (Best Model) - Loss: 2.3793 - Accuracy: 0.3824 - F1: 0.3730
sub_24:Test (Best Model) - Loss: 2.0042 - Accuracy: 0.2941 - F1: 0.2946
sub_24:Test (Best Model) - Loss: 2.7524 - Accuracy: 0.3088 - F1: 0.3012
sub_24:Test (Best Model) - Loss: 2.1919 - Accuracy: 0.3529 - F1: 0.3366
sub_24:Test (Best Model) - Loss: 2.0159 - Accuracy: 0.3088 - F1: 0.2915
sub_24:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.4412 - F1: 0.4352
sub_24:Test (Best Model) - Loss: 2.2579 - Accuracy: 0.3382 - F1: 0.3133
sub_24:Test (Best Model) - Loss: 1.4167 - Accuracy: 0.4118 - F1: 0.4036
sub_24:Test (Best Model) - Loss: 1.8490 - Accuracy: 0.4559 - F1: 0.3931
sub_24:Test (Best Model) - Loss: 2.1497 - Accuracy: 0.3235 - F1: 0.3189
sub_24:Test (Best Model) - Loss: 2.1378 - Accuracy: 0.3088 - F1: 0.3091
sub_24:Test (Best Model) - Loss: 2.4716 - Accuracy: 0.2794 - F1: 0.2795
sub_24:Test (Best Model) - Loss: 2.0999 - Accuracy: 0.3529 - F1: 0.3527
sub_24:Test (Best Model) - Loss: 2.2733 - Accuracy: 0.3529 - F1: 0.3406
sub_25:Test (Best Model) - Loss: 1.6478 - Accuracy: 0.5797 - F1: 0.5340
sub_25:Test (Best Model) - Loss: 1.7509 - Accuracy: 0.4783 - F1: 0.4348
sub_25:Test (Best Model) - Loss: 1.8099 - Accuracy: 0.4638 - F1: 0.4103
sub_25:Test (Best Model) - Loss: 1.6852 - Accuracy: 0.4493 - F1: 0.3933
sub_25:Test (Best Model) - Loss: 2.1887 - Accuracy: 0.4203 - F1: 0.3761
sub_25:Test (Best Model) - Loss: 3.1644 - Accuracy: 0.4118 - F1: 0.3274
sub_25:Test (Best Model) - Loss: 3.2876 - Accuracy: 0.4118 - F1: 0.3017
sub_25:Test (Best Model) - Loss: 2.3135 - Accuracy: 0.4706 - F1: 0.4376
sub_25:Test (Best Model) - Loss: 4.0591 - Accuracy: 0.4265 - F1: 0.3614
sub_25:Test (Best Model) - Loss: 2.3265 - Accuracy: 0.5147 - F1: 0.4488
sub_25:Test (Best Model) - Loss: 1.9798 - Accuracy: 0.5441 - F1: 0.5480
sub_25:Test (Best Model) - Loss: 1.9046 - Accuracy: 0.5147 - F1: 0.5033
sub_25:Test (Best Model) - Loss: 2.0779 - Accuracy: 0.5294 - F1: 0.5009
sub_25:Test (Best Model) - Loss: 1.8066 - Accuracy: 0.5000 - F1: 0.4761
sub_25:Test (Best Model) - Loss: 1.8967 - Accuracy: 0.4853 - F1: 0.4294
sub_26:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.4783 - F1: 0.5015
sub_26:Test (Best Model) - Loss: 1.7053 - Accuracy: 0.3623 - F1: 0.3763
sub_26:Test (Best Model) - Loss: 1.8491 - Accuracy: 0.5072 - F1: 0.5066
sub_26:Test (Best Model) - Loss: 1.4462 - Accuracy: 0.4783 - F1: 0.4961
sub_26:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.5942 - F1: 0.6111
sub_26:Test (Best Model) - Loss: 2.3895 - Accuracy: 0.4265 - F1: 0.4183
sub_26:Test (Best Model) - Loss: 2.6439 - Accuracy: 0.4118 - F1: 0.4039
sub_26:Test (Best Model) - Loss: 2.7380 - Accuracy: 0.3676 - F1: 0.3608
sub_26:Test (Best Model) - Loss: 2.4286 - Accuracy: 0.3824 - F1: 0.3756
sub_26:Test (Best Model) - Loss: 2.9591 - Accuracy: 0.2794 - F1: 0.3249
sub_26:Test (Best Model) - Loss: 1.7430 - Accuracy: 0.4412 - F1: 0.4777
sub_26:Test (Best Model) - Loss: 2.3772 - Accuracy: 0.4559 - F1: 0.4729
sub_26:Test (Best Model) - Loss: 2.1992 - Accuracy: 0.5000 - F1: 0.4794
sub_26:Test (Best Model) - Loss: 2.0341 - Accuracy: 0.5147 - F1: 0.5384
sub_26:Test (Best Model) - Loss: 2.1713 - Accuracy: 0.4118 - F1: 0.4308
sub_27:Test (Best Model) - Loss: 2.1629 - Accuracy: 0.4493 - F1: 0.4141
sub_27:Test (Best Model) - Loss: 1.4976 - Accuracy: 0.4638 - F1: 0.4820
sub_27:Test (Best Model) - Loss: 2.1026 - Accuracy: 0.3768 - F1: 0.3905
sub_27:Test (Best Model) - Loss: 2.3228 - Accuracy: 0.3188 - F1: 0.2926
sub_27:Test (Best Model) - Loss: 2.0697 - Accuracy: 0.3333 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 4.4205 - Accuracy: 0.3333 - F1: 0.2950
sub_27:Test (Best Model) - Loss: 4.9471 - Accuracy: 0.3768 - F1: 0.3317
sub_27:Test (Best Model) - Loss: 3.6279 - Accuracy: 0.5072 - F1: 0.4476
sub_27:Test (Best Model) - Loss: 3.6896 - Accuracy: 0.4348 - F1: 0.4092
sub_27:Test (Best Model) - Loss: 3.3533 - Accuracy: 0.4058 - F1: 0.3586
sub_27:Test (Best Model) - Loss: 1.8650 - Accuracy: 0.5000 - F1: 0.4941
sub_27:Test (Best Model) - Loss: 2.1524 - Accuracy: 0.4118 - F1: 0.4104
sub_27:Test (Best Model) - Loss: 2.8219 - Accuracy: 0.3824 - F1: 0.3814
sub_27:Test (Best Model) - Loss: 2.1274 - Accuracy: 0.4412 - F1: 0.4415
sub_27:Test (Best Model) - Loss: 2.0843 - Accuracy: 0.4265 - F1: 0.4385
sub_28:Test (Best Model) - Loss: 3.6171 - Accuracy: 0.3088 - F1: 0.3250
sub_28:Test (Best Model) - Loss: 4.1782 - Accuracy: 0.3971 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 3.7814 - Accuracy: 0.3382 - F1: 0.3237
sub_28:Test (Best Model) - Loss: 2.9547 - Accuracy: 0.2500 - F1: 0.2518
sub_28:Test (Best Model) - Loss: 3.8552 - Accuracy: 0.2353 - F1: 0.2295
sub_28:Test (Best Model) - Loss: 5.7149 - Accuracy: 0.2206 - F1: 0.1962
sub_28:Test (Best Model) - Loss: 6.3522 - Accuracy: 0.2500 - F1: 0.2146
sub_28:Test (Best Model) - Loss: 6.1043 - Accuracy: 0.2941 - F1: 0.2638
sub_28:Test (Best Model) - Loss: 4.4930 - Accuracy: 0.2059 - F1: 0.1978
sub_28:Test (Best Model) - Loss: 5.0571 - Accuracy: 0.2059 - F1: 0.1945
sub_28:Test (Best Model) - Loss: 1.7569 - Accuracy: 0.4853 - F1: 0.4476
sub_28:Test (Best Model) - Loss: 2.0851 - Accuracy: 0.4853 - F1: 0.4491
sub_28:Test (Best Model) - Loss: 1.9018 - Accuracy: 0.3824 - F1: 0.3419
sub_28:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.5441 - F1: 0.5246
sub_28:Test (Best Model) - Loss: 2.1342 - Accuracy: 0.3824 - F1: 0.3520
sub_29:Test (Best Model) - Loss: 3.1809 - Accuracy: 0.4853 - F1: 0.4664
sub_29:Test (Best Model) - Loss: 2.0992 - Accuracy: 0.5882 - F1: 0.5979
sub_29:Test (Best Model) - Loss: 2.5414 - Accuracy: 0.5588 - F1: 0.5520
sub_29:Test (Best Model) - Loss: 2.2620 - Accuracy: 0.5147 - F1: 0.5338
sub_29:Test (Best Model) - Loss: 2.6091 - Accuracy: 0.5294 - F1: 0.5328
sub_29:Test (Best Model) - Loss: 1.5971 - Accuracy: 0.6176 - F1: 0.6356
sub_29:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.6029 - F1: 0.6195
sub_29:Test (Best Model) - Loss: 1.7812 - Accuracy: 0.5147 - F1: 0.5370
sub_29:Test (Best Model) - Loss: 1.4223 - Accuracy: 0.6471 - F1: 0.6641
sub_29:Test (Best Model) - Loss: 1.1058 - Accuracy: 0.6471 - F1: 0.6454
sub_29:Test (Best Model) - Loss: 1.5682 - Accuracy: 0.5942 - F1: 0.5948
sub_29:Test (Best Model) - Loss: 1.8354 - Accuracy: 0.5362 - F1: 0.5525
sub_29:Test (Best Model) - Loss: 1.6455 - Accuracy: 0.6377 - F1: 0.6487
sub_29:Test (Best Model) - Loss: 1.6860 - Accuracy: 0.6667 - F1: 0.6845
sub_29:Test (Best Model) - Loss: 2.2885 - Accuracy: 0.4928 - F1: 0.5055

=== Summary Results ===

acc: 42.47 ± 7.26
F1: 41.58 ± 7.37
acc-in: 54.03 ± 6.28
F1-in: 52.03 ± 6.31
