lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.4853 - F1: 0.5150
sub_1:Test (Best Model) - Loss: 1.6016 - Accuracy: 0.5000 - F1: 0.5248
sub_1:Test (Best Model) - Loss: 1.9917 - Accuracy: 0.3088 - F1: 0.3148
sub_1:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.4412 - F1: 0.4770
sub_1:Test (Best Model) - Loss: 1.6677 - Accuracy: 0.4853 - F1: 0.5258
sub_1:Test (Best Model) - Loss: 1.7595 - Accuracy: 0.4638 - F1: 0.4209
sub_1:Test (Best Model) - Loss: 2.0392 - Accuracy: 0.4348 - F1: 0.4192
sub_1:Test (Best Model) - Loss: 2.0952 - Accuracy: 0.4203 - F1: 0.3917
sub_1:Test (Best Model) - Loss: 2.1600 - Accuracy: 0.4783 - F1: 0.4593
sub_1:Test (Best Model) - Loss: 2.2807 - Accuracy: 0.3913 - F1: 0.3877
sub_1:Test (Best Model) - Loss: 1.6465 - Accuracy: 0.4412 - F1: 0.4216
sub_1:Test (Best Model) - Loss: 1.4255 - Accuracy: 0.5588 - F1: 0.5645
sub_1:Test (Best Model) - Loss: 1.2315 - Accuracy: 0.5735 - F1: 0.5898
sub_1:Test (Best Model) - Loss: 1.8872 - Accuracy: 0.4412 - F1: 0.4356
sub_1:Test (Best Model) - Loss: 1.6275 - Accuracy: 0.4706 - F1: 0.4567
sub_2:Test (Best Model) - Loss: 2.2279 - Accuracy: 0.2754 - F1: 0.2917
sub_2:Test (Best Model) - Loss: 2.6141 - Accuracy: 0.3043 - F1: 0.3328
sub_2:Test (Best Model) - Loss: 2.4574 - Accuracy: 0.2174 - F1: 0.2441
sub_2:Test (Best Model) - Loss: 2.4480 - Accuracy: 0.2319 - F1: 0.2678
sub_2:Test (Best Model) - Loss: 2.7302 - Accuracy: 0.2464 - F1: 0.2802
sub_2:Test (Best Model) - Loss: 1.9397 - Accuracy: 0.3235 - F1: 0.3054
sub_2:Test (Best Model) - Loss: 1.8427 - Accuracy: 0.2647 - F1: 0.2627
sub_2:Test (Best Model) - Loss: 1.8810 - Accuracy: 0.3382 - F1: 0.3552
sub_2:Test (Best Model) - Loss: 1.8238 - Accuracy: 0.3235 - F1: 0.3192
sub_2:Test (Best Model) - Loss: 2.0299 - Accuracy: 0.3676 - F1: 0.3708
sub_2:Test (Best Model) - Loss: 2.4797 - Accuracy: 0.3913 - F1: 0.3393
sub_2:Test (Best Model) - Loss: 1.8719 - Accuracy: 0.4058 - F1: 0.3739
sub_2:Test (Best Model) - Loss: 1.7213 - Accuracy: 0.4348 - F1: 0.4310
sub_2:Test (Best Model) - Loss: 1.8548 - Accuracy: 0.4058 - F1: 0.3679
sub_2:Test (Best Model) - Loss: 2.2674 - Accuracy: 0.3913 - F1: 0.3681
sub_3:Test (Best Model) - Loss: 2.5548 - Accuracy: 0.3235 - F1: 0.3236
sub_3:Test (Best Model) - Loss: 2.1161 - Accuracy: 0.2794 - F1: 0.2690
sub_3:Test (Best Model) - Loss: 2.4436 - Accuracy: 0.3382 - F1: 0.3365
sub_3:Test (Best Model) - Loss: 2.3342 - Accuracy: 0.2500 - F1: 0.2402
sub_3:Test (Best Model) - Loss: 2.6130 - Accuracy: 0.3235 - F1: 0.3210
sub_3:Test (Best Model) - Loss: 2.1580 - Accuracy: 0.3043 - F1: 0.2807
sub_3:Test (Best Model) - Loss: 2.3081 - Accuracy: 0.3188 - F1: 0.3136
sub_3:Test (Best Model) - Loss: 2.2560 - Accuracy: 0.2609 - F1: 0.2302
sub_3:Test (Best Model) - Loss: 2.2962 - Accuracy: 0.3333 - F1: 0.3236
sub_3:Test (Best Model) - Loss: 2.1880 - Accuracy: 0.3188 - F1: 0.3140
sub_3:Test (Best Model) - Loss: 2.8412 - Accuracy: 0.3188 - F1: 0.2977
sub_3:Test (Best Model) - Loss: 2.3139 - Accuracy: 0.3043 - F1: 0.2819
sub_3:Test (Best Model) - Loss: 2.5305 - Accuracy: 0.3043 - F1: 0.3009
sub_3:Test (Best Model) - Loss: 2.4158 - Accuracy: 0.3333 - F1: 0.3188
sub_3:Test (Best Model) - Loss: 3.1190 - Accuracy: 0.3768 - F1: 0.3433
sub_4:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.5362 - F1: 0.5503
sub_4:Test (Best Model) - Loss: 1.3856 - Accuracy: 0.5507 - F1: 0.5467
sub_4:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.5072 - F1: 0.5140
sub_4:Test (Best Model) - Loss: 1.5002 - Accuracy: 0.5652 - F1: 0.5849
sub_4:Test (Best Model) - Loss: 1.9017 - Accuracy: 0.4783 - F1: 0.4779
sub_4:Test (Best Model) - Loss: 1.8897 - Accuracy: 0.4203 - F1: 0.3840
sub_4:Test (Best Model) - Loss: 1.6661 - Accuracy: 0.4348 - F1: 0.4538
sub_4:Test (Best Model) - Loss: 1.1922 - Accuracy: 0.5797 - F1: 0.5859
sub_4:Test (Best Model) - Loss: 1.5596 - Accuracy: 0.4928 - F1: 0.5074
sub_4:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.4638 - F1: 0.4727
sub_4:Test (Best Model) - Loss: 2.2784 - Accuracy: 0.3913 - F1: 0.3279
sub_4:Test (Best Model) - Loss: 1.9321 - Accuracy: 0.4638 - F1: 0.4849
sub_4:Test (Best Model) - Loss: 1.8854 - Accuracy: 0.4203 - F1: 0.3970
sub_4:Test (Best Model) - Loss: 2.2050 - Accuracy: 0.4348 - F1: 0.4354
sub_4:Test (Best Model) - Loss: 1.8033 - Accuracy: 0.5217 - F1: 0.5178
sub_5:Test (Best Model) - Loss: 3.0367 - Accuracy: 0.4265 - F1: 0.3874
sub_5:Test (Best Model) - Loss: 4.0608 - Accuracy: 0.3382 - F1: 0.3089
sub_5:Test (Best Model) - Loss: 3.4587 - Accuracy: 0.4412 - F1: 0.4470
sub_5:Test (Best Model) - Loss: 2.9946 - Accuracy: 0.4412 - F1: 0.4015
sub_5:Test (Best Model) - Loss: 2.7767 - Accuracy: 0.3971 - F1: 0.3893
sub_5:Test (Best Model) - Loss: 1.4497 - Accuracy: 0.5000 - F1: 0.4701
sub_5:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.5588 - F1: 0.5153
sub_5:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.5294 - F1: 0.5307
sub_5:Test (Best Model) - Loss: 1.0049 - Accuracy: 0.6029 - F1: 0.5966
sub_5:Test (Best Model) - Loss: 1.8097 - Accuracy: 0.4706 - F1: 0.4489
sub_5:Test (Best Model) - Loss: 1.7117 - Accuracy: 0.4412 - F1: 0.4243
sub_5:Test (Best Model) - Loss: 1.7228 - Accuracy: 0.3971 - F1: 0.3809
sub_5:Test (Best Model) - Loss: 2.5946 - Accuracy: 0.3971 - F1: 0.3962
sub_5:Test (Best Model) - Loss: 1.8145 - Accuracy: 0.3235 - F1: 0.3351
sub_5:Test (Best Model) - Loss: 1.4514 - Accuracy: 0.4559 - F1: 0.4829
sub_6:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.5441 - F1: 0.5401
sub_6:Test (Best Model) - Loss: 1.5298 - Accuracy: 0.5000 - F1: 0.4641
sub_6:Test (Best Model) - Loss: 1.5469 - Accuracy: 0.5000 - F1: 0.4920
sub_6:Test (Best Model) - Loss: 1.3834 - Accuracy: 0.5588 - F1: 0.5679
sub_6:Test (Best Model) - Loss: 1.3284 - Accuracy: 0.5735 - F1: 0.5627
sub_6:Test (Best Model) - Loss: 1.9023 - Accuracy: 0.4493 - F1: 0.3724
sub_6:Test (Best Model) - Loss: 1.7708 - Accuracy: 0.4638 - F1: 0.4336
sub_6:Test (Best Model) - Loss: 1.8659 - Accuracy: 0.4058 - F1: 0.3533
sub_6:Test (Best Model) - Loss: 1.9832 - Accuracy: 0.4493 - F1: 0.3702
sub_6:Test (Best Model) - Loss: 2.2492 - Accuracy: 0.4058 - F1: 0.3027
sub_6:Test (Best Model) - Loss: 1.7124 - Accuracy: 0.3188 - F1: 0.3254
sub_6:Test (Best Model) - Loss: 2.0529 - Accuracy: 0.4493 - F1: 0.4078
sub_6:Test (Best Model) - Loss: 2.0316 - Accuracy: 0.4493 - F1: 0.4558
sub_6:Test (Best Model) - Loss: 1.5304 - Accuracy: 0.4783 - F1: 0.4905
sub_6:Test (Best Model) - Loss: 1.7290 - Accuracy: 0.4493 - F1: 0.4461
sub_7:Test (Best Model) - Loss: 1.1578 - Accuracy: 0.6029 - F1: 0.5701
sub_7:Test (Best Model) - Loss: 1.5216 - Accuracy: 0.5147 - F1: 0.5020
sub_7:Test (Best Model) - Loss: 1.6417 - Accuracy: 0.5147 - F1: 0.4914
sub_7:Test (Best Model) - Loss: 1.0643 - Accuracy: 0.5735 - F1: 0.5616
sub_7:Test (Best Model) - Loss: 1.7852 - Accuracy: 0.5147 - F1: 0.4952
sub_7:Test (Best Model) - Loss: 2.3875 - Accuracy: 0.3824 - F1: 0.3425
sub_7:Test (Best Model) - Loss: 2.3252 - Accuracy: 0.3824 - F1: 0.3781
sub_7:Test (Best Model) - Loss: 2.1849 - Accuracy: 0.4265 - F1: 0.4160
sub_7:Test (Best Model) - Loss: 2.2793 - Accuracy: 0.4118 - F1: 0.3852
sub_7:Test (Best Model) - Loss: 1.8587 - Accuracy: 0.5294 - F1: 0.4604
sub_7:Test (Best Model) - Loss: 1.5708 - Accuracy: 0.5000 - F1: 0.4991
sub_7:Test (Best Model) - Loss: 1.7699 - Accuracy: 0.5147 - F1: 0.4993
sub_7:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.4853 - F1: 0.4742
sub_7:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.4559 - F1: 0.4589
sub_7:Test (Best Model) - Loss: 1.4596 - Accuracy: 0.4559 - F1: 0.4518
sub_8:Test (Best Model) - Loss: 2.7993 - Accuracy: 0.3088 - F1: 0.3174
sub_8:Test (Best Model) - Loss: 2.8365 - Accuracy: 0.2794 - F1: 0.2695
sub_8:Test (Best Model) - Loss: 2.5362 - Accuracy: 0.2500 - F1: 0.2906
sub_8:Test (Best Model) - Loss: 2.3299 - Accuracy: 0.3824 - F1: 0.3931
sub_8:Test (Best Model) - Loss: 2.5132 - Accuracy: 0.2647 - F1: 0.2696
sub_8:Test (Best Model) - Loss: 1.8461 - Accuracy: 0.3088 - F1: 0.3078
sub_8:Test (Best Model) - Loss: 2.1832 - Accuracy: 0.3824 - F1: 0.3755
sub_8:Test (Best Model) - Loss: 1.8260 - Accuracy: 0.3382 - F1: 0.3228
sub_8:Test (Best Model) - Loss: 2.3118 - Accuracy: 0.2647 - F1: 0.2659
sub_8:Test (Best Model) - Loss: 2.1634 - Accuracy: 0.3088 - F1: 0.3192
sub_8:Test (Best Model) - Loss: 2.9428 - Accuracy: 0.3676 - F1: 0.3672
sub_8:Test (Best Model) - Loss: 2.8606 - Accuracy: 0.2500 - F1: 0.2611
sub_8:Test (Best Model) - Loss: 2.8963 - Accuracy: 0.3971 - F1: 0.4264
sub_8:Test (Best Model) - Loss: 2.6118 - Accuracy: 0.3088 - F1: 0.3133
sub_8:Test (Best Model) - Loss: 2.2887 - Accuracy: 0.3529 - F1: 0.3621
sub_9:Test (Best Model) - Loss: 1.6844 - Accuracy: 0.5147 - F1: 0.5186
sub_9:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.6324 - F1: 0.6382
sub_9:Test (Best Model) - Loss: 1.7703 - Accuracy: 0.5147 - F1: 0.5444
sub_9:Test (Best Model) - Loss: 1.9694 - Accuracy: 0.5000 - F1: 0.5189
sub_9:Test (Best Model) - Loss: 1.4771 - Accuracy: 0.5441 - F1: 0.5720
sub_9:Test (Best Model) - Loss: 3.5751 - Accuracy: 0.3088 - F1: 0.2913
sub_9:Test (Best Model) - Loss: 3.4033 - Accuracy: 0.4265 - F1: 0.4190
sub_9:Test (Best Model) - Loss: 3.3559 - Accuracy: 0.2794 - F1: 0.2842
sub_9:Test (Best Model) - Loss: 2.3300 - Accuracy: 0.4118 - F1: 0.4086
sub_9:Test (Best Model) - Loss: 2.5638 - Accuracy: 0.2941 - F1: 0.3158
sub_9:Test (Best Model) - Loss: 3.2214 - Accuracy: 0.3382 - F1: 0.3602
sub_9:Test (Best Model) - Loss: 2.6677 - Accuracy: 0.4706 - F1: 0.4941
sub_9:Test (Best Model) - Loss: 1.7293 - Accuracy: 0.4853 - F1: 0.5096
sub_9:Test (Best Model) - Loss: 2.7889 - Accuracy: 0.3824 - F1: 0.4193
sub_9:Test (Best Model) - Loss: 2.4739 - Accuracy: 0.3824 - F1: 0.4200
sub_10:Test (Best Model) - Loss: 2.5811 - Accuracy: 0.2353 - F1: 0.2197
sub_10:Test (Best Model) - Loss: 2.0677 - Accuracy: 0.4118 - F1: 0.4193
sub_10:Test (Best Model) - Loss: 2.0810 - Accuracy: 0.3676 - F1: 0.3678
sub_10:Test (Best Model) - Loss: 2.3298 - Accuracy: 0.3676 - F1: 0.3610
sub_10:Test (Best Model) - Loss: 2.2475 - Accuracy: 0.3529 - F1: 0.3743
sub_10:Test (Best Model) - Loss: 2.0971 - Accuracy: 0.3382 - F1: 0.3270
sub_10:Test (Best Model) - Loss: 2.0987 - Accuracy: 0.2353 - F1: 0.2516
sub_10:Test (Best Model) - Loss: 2.0865 - Accuracy: 0.3971 - F1: 0.4186
sub_10:Test (Best Model) - Loss: 1.9466 - Accuracy: 0.3235 - F1: 0.3218
sub_10:Test (Best Model) - Loss: 2.4062 - Accuracy: 0.2647 - F1: 0.2678
sub_10:Test (Best Model) - Loss: 2.8476 - Accuracy: 0.2464 - F1: 0.2417
sub_10:Test (Best Model) - Loss: 2.5174 - Accuracy: 0.3043 - F1: 0.3076
sub_10:Test (Best Model) - Loss: 2.3705 - Accuracy: 0.3043 - F1: 0.3032
sub_10:Test (Best Model) - Loss: 2.1957 - Accuracy: 0.2899 - F1: 0.2835
sub_10:Test (Best Model) - Loss: 2.1488 - Accuracy: 0.2899 - F1: 0.2861
sub_11:Test (Best Model) - Loss: 2.7487 - Accuracy: 0.3043 - F1: 0.2948
sub_11:Test (Best Model) - Loss: 2.5377 - Accuracy: 0.2609 - F1: 0.2271
sub_11:Test (Best Model) - Loss: 2.5423 - Accuracy: 0.2609 - F1: 0.2518
sub_11:Test (Best Model) - Loss: 2.3076 - Accuracy: 0.3043 - F1: 0.2995
sub_11:Test (Best Model) - Loss: 3.1661 - Accuracy: 0.2464 - F1: 0.2607
sub_11:Test (Best Model) - Loss: 1.9426 - Accuracy: 0.4493 - F1: 0.4153
sub_11:Test (Best Model) - Loss: 1.6993 - Accuracy: 0.5362 - F1: 0.5014
sub_11:Test (Best Model) - Loss: 1.8904 - Accuracy: 0.4928 - F1: 0.4521
sub_11:Test (Best Model) - Loss: 2.9419 - Accuracy: 0.5072 - F1: 0.4566
sub_11:Test (Best Model) - Loss: 2.1217 - Accuracy: 0.4928 - F1: 0.4336
sub_11:Test (Best Model) - Loss: 1.8974 - Accuracy: 0.4783 - F1: 0.3921
sub_11:Test (Best Model) - Loss: 1.6624 - Accuracy: 0.5217 - F1: 0.4812
sub_11:Test (Best Model) - Loss: 1.6377 - Accuracy: 0.5217 - F1: 0.4610
sub_11:Test (Best Model) - Loss: 1.7116 - Accuracy: 0.4058 - F1: 0.3800
sub_11:Test (Best Model) - Loss: 1.8263 - Accuracy: 0.5072 - F1: 0.4469
sub_12:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.5294 - F1: 0.5156
sub_12:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.5000 - F1: 0.4852
sub_12:Test (Best Model) - Loss: 1.5522 - Accuracy: 0.5147 - F1: 0.4612
sub_12:Test (Best Model) - Loss: 1.2102 - Accuracy: 0.6176 - F1: 0.6229
sub_12:Test (Best Model) - Loss: 1.4458 - Accuracy: 0.4706 - F1: 0.4749
sub_12:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.4783 - F1: 0.4912
sub_12:Test (Best Model) - Loss: 1.4639 - Accuracy: 0.4203 - F1: 0.4376
sub_12:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.5217 - F1: 0.5226
sub_12:Test (Best Model) - Loss: 1.5694 - Accuracy: 0.4638 - F1: 0.4509
sub_12:Test (Best Model) - Loss: 1.4861 - Accuracy: 0.5217 - F1: 0.5184
sub_12:Test (Best Model) - Loss: 1.9482 - Accuracy: 0.4412 - F1: 0.4406
sub_12:Test (Best Model) - Loss: 1.6942 - Accuracy: 0.4706 - F1: 0.4630
sub_12:Test (Best Model) - Loss: 2.2635 - Accuracy: 0.3824 - F1: 0.3854
sub_12:Test (Best Model) - Loss: 2.3351 - Accuracy: 0.4706 - F1: 0.4682
sub_12:Test (Best Model) - Loss: 1.7095 - Accuracy: 0.5000 - F1: 0.4926
sub_13:Test (Best Model) - Loss: 2.1687 - Accuracy: 0.5147 - F1: 0.5160
sub_13:Test (Best Model) - Loss: 2.5369 - Accuracy: 0.4559 - F1: 0.4717
sub_13:Test (Best Model) - Loss: 2.0321 - Accuracy: 0.4706 - F1: 0.4965
sub_13:Test (Best Model) - Loss: 2.3809 - Accuracy: 0.4559 - F1: 0.4612
sub_13:Test (Best Model) - Loss: 2.0136 - Accuracy: 0.5147 - F1: 0.5141
sub_13:Test (Best Model) - Loss: 2.1683 - Accuracy: 0.4493 - F1: 0.4538
sub_13:Test (Best Model) - Loss: 2.1603 - Accuracy: 0.4348 - F1: 0.4363
sub_13:Test (Best Model) - Loss: 2.4963 - Accuracy: 0.4348 - F1: 0.4282
sub_13:Test (Best Model) - Loss: 2.1876 - Accuracy: 0.4493 - F1: 0.4550
sub_13:Test (Best Model) - Loss: 2.3019 - Accuracy: 0.4928 - F1: 0.5003
sub_13:Test (Best Model) - Loss: 2.0112 - Accuracy: 0.4118 - F1: 0.4137
sub_13:Test (Best Model) - Loss: 1.8618 - Accuracy: 0.3971 - F1: 0.4095
sub_13:Test (Best Model) - Loss: 2.2145 - Accuracy: 0.3971 - F1: 0.4219
sub_13:Test (Best Model) - Loss: 2.1160 - Accuracy: 0.4118 - F1: 0.4232
sub_13:Test (Best Model) - Loss: 1.9914 - Accuracy: 0.4706 - F1: 0.4714
sub_14:Test (Best Model) - Loss: 2.2471 - Accuracy: 0.3529 - F1: 0.3772
sub_14:Test (Best Model) - Loss: 2.3921 - Accuracy: 0.2941 - F1: 0.3225
sub_14:Test (Best Model) - Loss: 2.1644 - Accuracy: 0.3088 - F1: 0.3336
sub_14:Test (Best Model) - Loss: 2.1619 - Accuracy: 0.2794 - F1: 0.2982
sub_14:Test (Best Model) - Loss: 2.3323 - Accuracy: 0.3529 - F1: 0.3546
sub_14:Test (Best Model) - Loss: 2.3067 - Accuracy: 0.3824 - F1: 0.4051
sub_14:Test (Best Model) - Loss: 2.4837 - Accuracy: 0.5000 - F1: 0.5197
sub_14:Test (Best Model) - Loss: 2.2900 - Accuracy: 0.5000 - F1: 0.5127
sub_14:Test (Best Model) - Loss: 2.5068 - Accuracy: 0.4118 - F1: 0.4263
sub_14:Test (Best Model) - Loss: 2.7525 - Accuracy: 0.2353 - F1: 0.1969
sub_14:Test (Best Model) - Loss: 2.2296 - Accuracy: 0.4706 - F1: 0.4715
sub_14:Test (Best Model) - Loss: 2.1636 - Accuracy: 0.4118 - F1: 0.3737
sub_14:Test (Best Model) - Loss: 2.3474 - Accuracy: 0.4265 - F1: 0.4288
sub_14:Test (Best Model) - Loss: 2.2489 - Accuracy: 0.3676 - F1: 0.3747
sub_14:Test (Best Model) - Loss: 1.8579 - Accuracy: 0.3824 - F1: 0.4003
sub_15:Test (Best Model) - Loss: 2.1027 - Accuracy: 0.5147 - F1: 0.5339
sub_15:Test (Best Model) - Loss: 2.7657 - Accuracy: 0.3971 - F1: 0.3985
sub_15:Test (Best Model) - Loss: 2.1892 - Accuracy: 0.4412 - F1: 0.4634
sub_15:Test (Best Model) - Loss: 1.7546 - Accuracy: 0.4706 - F1: 0.4914
sub_15:Test (Best Model) - Loss: 2.0709 - Accuracy: 0.4412 - F1: 0.4557
sub_15:Test (Best Model) - Loss: 1.6655 - Accuracy: 0.5735 - F1: 0.5813
sub_15:Test (Best Model) - Loss: 2.0748 - Accuracy: 0.5588 - F1: 0.5523
sub_15:Test (Best Model) - Loss: 1.9053 - Accuracy: 0.5588 - F1: 0.5706
sub_15:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.5588 - F1: 0.5774
sub_15:Test (Best Model) - Loss: 1.7697 - Accuracy: 0.5882 - F1: 0.5798
sub_15:Test (Best Model) - Loss: 2.1074 - Accuracy: 0.4706 - F1: 0.4429
sub_15:Test (Best Model) - Loss: 1.9191 - Accuracy: 0.3382 - F1: 0.3402
sub_15:Test (Best Model) - Loss: 2.0990 - Accuracy: 0.3676 - F1: 0.3699
sub_15:Test (Best Model) - Loss: 2.2500 - Accuracy: 0.3824 - F1: 0.3782
sub_15:Test (Best Model) - Loss: 2.2252 - Accuracy: 0.4118 - F1: 0.4191
sub_16:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.5588 - F1: 0.5193
sub_16:Test (Best Model) - Loss: 1.3361 - Accuracy: 0.5441 - F1: 0.4861
sub_16:Test (Best Model) - Loss: 1.2318 - Accuracy: 0.5441 - F1: 0.5230
sub_16:Test (Best Model) - Loss: 1.2160 - Accuracy: 0.5735 - F1: 0.5564
sub_16:Test (Best Model) - Loss: 1.0069 - Accuracy: 0.6176 - F1: 0.6033
sub_16:Test (Best Model) - Loss: 1.8769 - Accuracy: 0.4559 - F1: 0.4509
sub_16:Test (Best Model) - Loss: 1.6373 - Accuracy: 0.4853 - F1: 0.4918
sub_16:Test (Best Model) - Loss: 1.7100 - Accuracy: 0.4853 - F1: 0.4753
sub_16:Test (Best Model) - Loss: 1.5706 - Accuracy: 0.5000 - F1: 0.4920
sub_16:Test (Best Model) - Loss: 2.3002 - Accuracy: 0.4412 - F1: 0.4444
sub_16:Test (Best Model) - Loss: 1.6559 - Accuracy: 0.5588 - F1: 0.4894
sub_16:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.5147 - F1: 0.4886
sub_16:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.5441 - F1: 0.5030
sub_16:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.4853 - F1: 0.4587
sub_16:Test (Best Model) - Loss: 1.5239 - Accuracy: 0.5588 - F1: 0.5267
sub_17:Test (Best Model) - Loss: 1.7682 - Accuracy: 0.4638 - F1: 0.4616
sub_17:Test (Best Model) - Loss: 1.5560 - Accuracy: 0.4493 - F1: 0.4552
sub_17:Test (Best Model) - Loss: 1.8001 - Accuracy: 0.3913 - F1: 0.3705
sub_17:Test (Best Model) - Loss: 1.8175 - Accuracy: 0.4493 - F1: 0.4473
sub_17:Test (Best Model) - Loss: 1.5531 - Accuracy: 0.4058 - F1: 0.4057
sub_17:Test (Best Model) - Loss: 2.5052 - Accuracy: 0.3913 - F1: 0.3419
sub_17:Test (Best Model) - Loss: 3.1413 - Accuracy: 0.3478 - F1: 0.3254
sub_17:Test (Best Model) - Loss: 2.7434 - Accuracy: 0.4638 - F1: 0.4144
sub_17:Test (Best Model) - Loss: 3.1123 - Accuracy: 0.4493 - F1: 0.4049
sub_17:Test (Best Model) - Loss: 2.8377 - Accuracy: 0.4058 - F1: 0.3443
sub_17:Test (Best Model) - Loss: 1.6399 - Accuracy: 0.5000 - F1: 0.5023
sub_17:Test (Best Model) - Loss: 1.7090 - Accuracy: 0.4412 - F1: 0.4380
sub_17:Test (Best Model) - Loss: 1.8744 - Accuracy: 0.5000 - F1: 0.4984
sub_17:Test (Best Model) - Loss: 1.7498 - Accuracy: 0.4412 - F1: 0.4489
sub_17:Test (Best Model) - Loss: 2.0087 - Accuracy: 0.4265 - F1: 0.4273
sub_18:Test (Best Model) - Loss: 1.6351 - Accuracy: 0.4493 - F1: 0.4466
sub_18:Test (Best Model) - Loss: 1.7466 - Accuracy: 0.3913 - F1: 0.4016
sub_18:Test (Best Model) - Loss: 1.6821 - Accuracy: 0.4203 - F1: 0.4141
sub_18:Test (Best Model) - Loss: 1.7983 - Accuracy: 0.4348 - F1: 0.4654
sub_18:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.4058 - F1: 0.4231
sub_18:Test (Best Model) - Loss: 1.9428 - Accuracy: 0.3382 - F1: 0.3688
sub_18:Test (Best Model) - Loss: 2.0424 - Accuracy: 0.4118 - F1: 0.4238
sub_18:Test (Best Model) - Loss: 2.1457 - Accuracy: 0.2794 - F1: 0.2963
sub_18:Test (Best Model) - Loss: 2.1087 - Accuracy: 0.3088 - F1: 0.3394
sub_18:Test (Best Model) - Loss: 2.2615 - Accuracy: 0.3088 - F1: 0.3480
sub_18:Test (Best Model) - Loss: 1.9759 - Accuracy: 0.3088 - F1: 0.3327
sub_18:Test (Best Model) - Loss: 2.3391 - Accuracy: 0.2353 - F1: 0.2672
sub_18:Test (Best Model) - Loss: 2.3937 - Accuracy: 0.2353 - F1: 0.2472
sub_18:Test (Best Model) - Loss: 2.2891 - Accuracy: 0.3088 - F1: 0.3290
sub_18:Test (Best Model) - Loss: 1.9436 - Accuracy: 0.3088 - F1: 0.3272
sub_19:Test (Best Model) - Loss: 2.7546 - Accuracy: 0.2059 - F1: 0.1527
sub_19:Test (Best Model) - Loss: 2.5986 - Accuracy: 0.2206 - F1: 0.1939
sub_19:Test (Best Model) - Loss: 2.7446 - Accuracy: 0.2353 - F1: 0.2287
sub_19:Test (Best Model) - Loss: 2.3011 - Accuracy: 0.3088 - F1: 0.2741
sub_19:Test (Best Model) - Loss: 2.6743 - Accuracy: 0.2059 - F1: 0.2043
sub_19:Test (Best Model) - Loss: 2.3473 - Accuracy: 0.3235 - F1: 0.2934
sub_19:Test (Best Model) - Loss: 2.0061 - Accuracy: 0.3235 - F1: 0.3005
sub_19:Test (Best Model) - Loss: 2.0116 - Accuracy: 0.3676 - F1: 0.3275
sub_19:Test (Best Model) - Loss: 1.8914 - Accuracy: 0.4265 - F1: 0.3633
sub_19:Test (Best Model) - Loss: 1.8288 - Accuracy: 0.5000 - F1: 0.4824
sub_19:Test (Best Model) - Loss: 2.7359 - Accuracy: 0.3088 - F1: 0.2969
sub_19:Test (Best Model) - Loss: 3.3212 - Accuracy: 0.2647 - F1: 0.2426
sub_19:Test (Best Model) - Loss: 2.2872 - Accuracy: 0.3529 - F1: 0.3016
sub_19:Test (Best Model) - Loss: 2.7573 - Accuracy: 0.3382 - F1: 0.3283
sub_19:Test (Best Model) - Loss: 2.3862 - Accuracy: 0.3676 - F1: 0.3577
sub_20:Test (Best Model) - Loss: 1.6789 - Accuracy: 0.5441 - F1: 0.5483
sub_20:Test (Best Model) - Loss: 1.7939 - Accuracy: 0.5000 - F1: 0.5061
sub_20:Test (Best Model) - Loss: 1.8234 - Accuracy: 0.5588 - F1: 0.5671
sub_20:Test (Best Model) - Loss: 1.8124 - Accuracy: 0.4853 - F1: 0.4966
sub_20:Test (Best Model) - Loss: 2.0960 - Accuracy: 0.5294 - F1: 0.5414
sub_20:Test (Best Model) - Loss: 1.7118 - Accuracy: 0.3971 - F1: 0.4129
sub_20:Test (Best Model) - Loss: 1.9884 - Accuracy: 0.4853 - F1: 0.4963
sub_20:Test (Best Model) - Loss: 2.5053 - Accuracy: 0.4118 - F1: 0.4290
sub_20:Test (Best Model) - Loss: 2.1721 - Accuracy: 0.4265 - F1: 0.4344
sub_20:Test (Best Model) - Loss: 2.0333 - Accuracy: 0.4265 - F1: 0.4441
sub_20:Test (Best Model) - Loss: 1.9825 - Accuracy: 0.4348 - F1: 0.4385
sub_20:Test (Best Model) - Loss: 2.4690 - Accuracy: 0.3913 - F1: 0.3998
sub_20:Test (Best Model) - Loss: 2.2470 - Accuracy: 0.4058 - F1: 0.3931
sub_20:Test (Best Model) - Loss: 2.3526 - Accuracy: 0.3478 - F1: 0.3184
sub_20:Test (Best Model) - Loss: 2.3794 - Accuracy: 0.4058 - F1: 0.4268
sub_21:Test (Best Model) - Loss: 2.2673 - Accuracy: 0.4118 - F1: 0.4047
sub_21:Test (Best Model) - Loss: 1.7986 - Accuracy: 0.4559 - F1: 0.4458
sub_21:Test (Best Model) - Loss: 2.3502 - Accuracy: 0.4706 - F1: 0.4474
sub_21:Test (Best Model) - Loss: 2.2189 - Accuracy: 0.4265 - F1: 0.4159
sub_21:Test (Best Model) - Loss: 2.3376 - Accuracy: 0.4118 - F1: 0.3936
sub_21:Test (Best Model) - Loss: 1.7841 - Accuracy: 0.4412 - F1: 0.4251
sub_21:Test (Best Model) - Loss: 1.6287 - Accuracy: 0.3824 - F1: 0.3752
sub_21:Test (Best Model) - Loss: 1.4869 - Accuracy: 0.3971 - F1: 0.3796
sub_21:Test (Best Model) - Loss: 1.9813 - Accuracy: 0.4412 - F1: 0.4256
sub_21:Test (Best Model) - Loss: 1.7263 - Accuracy: 0.4559 - F1: 0.4335
sub_21:Test (Best Model) - Loss: 1.7614 - Accuracy: 0.3971 - F1: 0.3837
sub_21:Test (Best Model) - Loss: 1.8576 - Accuracy: 0.3676 - F1: 0.3494
sub_21:Test (Best Model) - Loss: 1.8796 - Accuracy: 0.3971 - F1: 0.3493
sub_21:Test (Best Model) - Loss: 1.7862 - Accuracy: 0.4118 - F1: 0.3924
sub_21:Test (Best Model) - Loss: 1.8825 - Accuracy: 0.3382 - F1: 0.3015
sub_22:Test (Best Model) - Loss: 2.1513 - Accuracy: 0.3382 - F1: 0.3520
sub_22:Test (Best Model) - Loss: 2.5105 - Accuracy: 0.4412 - F1: 0.4572
sub_22:Test (Best Model) - Loss: 2.2979 - Accuracy: 0.3971 - F1: 0.4057
sub_22:Test (Best Model) - Loss: 2.1610 - Accuracy: 0.3529 - F1: 0.3703
sub_22:Test (Best Model) - Loss: 2.3812 - Accuracy: 0.4118 - F1: 0.4198
sub_22:Test (Best Model) - Loss: 1.7343 - Accuracy: 0.3478 - F1: 0.3358
sub_22:Test (Best Model) - Loss: 1.6478 - Accuracy: 0.3913 - F1: 0.3429
sub_22:Test (Best Model) - Loss: 1.8777 - Accuracy: 0.3913 - F1: 0.3780
sub_22:Test (Best Model) - Loss: 1.8133 - Accuracy: 0.4203 - F1: 0.4248
sub_22:Test (Best Model) - Loss: 1.9322 - Accuracy: 0.2899 - F1: 0.2780
sub_22:Test (Best Model) - Loss: 1.7874 - Accuracy: 0.3529 - F1: 0.3757
sub_22:Test (Best Model) - Loss: 1.9044 - Accuracy: 0.3971 - F1: 0.3847
sub_22:Test (Best Model) - Loss: 1.6452 - Accuracy: 0.4118 - F1: 0.4315
sub_22:Test (Best Model) - Loss: 2.0261 - Accuracy: 0.3824 - F1: 0.4143
sub_22:Test (Best Model) - Loss: 1.8076 - Accuracy: 0.4412 - F1: 0.4606
sub_23:Test (Best Model) - Loss: 2.0932 - Accuracy: 0.3333 - F1: 0.3535
sub_23:Test (Best Model) - Loss: 1.8821 - Accuracy: 0.4493 - F1: 0.4628
sub_23:Test (Best Model) - Loss: 1.8355 - Accuracy: 0.4493 - F1: 0.4702
sub_23:Test (Best Model) - Loss: 1.5279 - Accuracy: 0.4928 - F1: 0.4987
sub_23:Test (Best Model) - Loss: 1.8261 - Accuracy: 0.5507 - F1: 0.5618
sub_23:Test (Best Model) - Loss: 1.9240 - Accuracy: 0.4559 - F1: 0.4107
sub_23:Test (Best Model) - Loss: 1.7006 - Accuracy: 0.4559 - F1: 0.4495
sub_23:Test (Best Model) - Loss: 1.3858 - Accuracy: 0.5588 - F1: 0.5419
sub_23:Test (Best Model) - Loss: 1.4504 - Accuracy: 0.5441 - F1: 0.5439
sub_23:Test (Best Model) - Loss: 1.5869 - Accuracy: 0.5294 - F1: 0.5168
sub_23:Test (Best Model) - Loss: 2.9010 - Accuracy: 0.4058 - F1: 0.3962
sub_23:Test (Best Model) - Loss: 3.3590 - Accuracy: 0.3623 - F1: 0.3528
sub_23:Test (Best Model) - Loss: 2.1155 - Accuracy: 0.4348 - F1: 0.4440
sub_23:Test (Best Model) - Loss: 2.9557 - Accuracy: 0.4058 - F1: 0.3937
sub_23:Test (Best Model) - Loss: 2.7792 - Accuracy: 0.3623 - F1: 0.3372
sub_24:Test (Best Model) - Loss: 2.1882 - Accuracy: 0.3529 - F1: 0.3495
sub_24:Test (Best Model) - Loss: 2.1806 - Accuracy: 0.3529 - F1: 0.3511
sub_24:Test (Best Model) - Loss: 1.9081 - Accuracy: 0.3235 - F1: 0.3240
sub_24:Test (Best Model) - Loss: 2.3070 - Accuracy: 0.2941 - F1: 0.2851
sub_24:Test (Best Model) - Loss: 2.1345 - Accuracy: 0.3529 - F1: 0.3433
sub_24:Test (Best Model) - Loss: 1.7455 - Accuracy: 0.4265 - F1: 0.4250
sub_24:Test (Best Model) - Loss: 1.7668 - Accuracy: 0.3971 - F1: 0.4026
sub_24:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.3971 - F1: 0.3863
sub_24:Test (Best Model) - Loss: 1.4483 - Accuracy: 0.4265 - F1: 0.4239
sub_24:Test (Best Model) - Loss: 1.7846 - Accuracy: 0.2941 - F1: 0.3037
sub_24:Test (Best Model) - Loss: 2.0916 - Accuracy: 0.3088 - F1: 0.2925
sub_24:Test (Best Model) - Loss: 2.0977 - Accuracy: 0.3529 - F1: 0.3386
sub_24:Test (Best Model) - Loss: 2.3336 - Accuracy: 0.3088 - F1: 0.3120
sub_24:Test (Best Model) - Loss: 1.9409 - Accuracy: 0.3824 - F1: 0.3803
sub_24:Test (Best Model) - Loss: 2.2882 - Accuracy: 0.3235 - F1: 0.3195
sub_25:Test (Best Model) - Loss: 1.5414 - Accuracy: 0.5362 - F1: 0.4959
sub_25:Test (Best Model) - Loss: 1.6593 - Accuracy: 0.4348 - F1: 0.4148
sub_25:Test (Best Model) - Loss: 1.6540 - Accuracy: 0.4928 - F1: 0.4462
sub_25:Test (Best Model) - Loss: 1.7195 - Accuracy: 0.4348 - F1: 0.3789
sub_25:Test (Best Model) - Loss: 1.9207 - Accuracy: 0.4348 - F1: 0.4174
sub_25:Test (Best Model) - Loss: 2.2961 - Accuracy: 0.4265 - F1: 0.3712
sub_25:Test (Best Model) - Loss: 2.4006 - Accuracy: 0.3676 - F1: 0.3068
sub_25:Test (Best Model) - Loss: 1.8867 - Accuracy: 0.4559 - F1: 0.3861
sub_25:Test (Best Model) - Loss: 2.3856 - Accuracy: 0.4706 - F1: 0.3922
sub_25:Test (Best Model) - Loss: 1.8623 - Accuracy: 0.5588 - F1: 0.4970
sub_25:Test (Best Model) - Loss: 1.6898 - Accuracy: 0.4559 - F1: 0.4434
sub_25:Test (Best Model) - Loss: 2.0894 - Accuracy: 0.3971 - F1: 0.3942
sub_25:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.4412 - F1: 0.4121
sub_25:Test (Best Model) - Loss: 1.7649 - Accuracy: 0.3676 - F1: 0.3454
sub_25:Test (Best Model) - Loss: 1.7391 - Accuracy: 0.4265 - F1: 0.3535
sub_26:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.4783 - F1: 0.5048
sub_26:Test (Best Model) - Loss: 1.7123 - Accuracy: 0.3913 - F1: 0.4008
sub_26:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.4638 - F1: 0.4706
sub_26:Test (Best Model) - Loss: 1.3239 - Accuracy: 0.4928 - F1: 0.5064
sub_26:Test (Best Model) - Loss: 1.3253 - Accuracy: 0.5797 - F1: 0.5815
sub_26:Test (Best Model) - Loss: 2.1056 - Accuracy: 0.3676 - F1: 0.3787
sub_26:Test (Best Model) - Loss: 2.0802 - Accuracy: 0.3235 - F1: 0.3222
sub_26:Test (Best Model) - Loss: 2.1859 - Accuracy: 0.3824 - F1: 0.3797
sub_26:Test (Best Model) - Loss: 1.7965 - Accuracy: 0.3676 - F1: 0.3784
sub_26:Test (Best Model) - Loss: 2.3187 - Accuracy: 0.2941 - F1: 0.3384
sub_26:Test (Best Model) - Loss: 1.9067 - Accuracy: 0.4559 - F1: 0.4878
sub_26:Test (Best Model) - Loss: 2.3426 - Accuracy: 0.4412 - F1: 0.4704
sub_26:Test (Best Model) - Loss: 1.9648 - Accuracy: 0.5000 - F1: 0.5178
sub_26:Test (Best Model) - Loss: 1.7673 - Accuracy: 0.5294 - F1: 0.5534
sub_26:Test (Best Model) - Loss: 1.9094 - Accuracy: 0.4559 - F1: 0.4831
sub_27:Test (Best Model) - Loss: 1.7682 - Accuracy: 0.4638 - F1: 0.4616
sub_27:Test (Best Model) - Loss: 1.5560 - Accuracy: 0.4493 - F1: 0.4552
sub_27:Test (Best Model) - Loss: 1.8001 - Accuracy: 0.3913 - F1: 0.3705
sub_27:Test (Best Model) - Loss: 1.8175 - Accuracy: 0.4493 - F1: 0.4473
sub_27:Test (Best Model) - Loss: 1.5531 - Accuracy: 0.4058 - F1: 0.4057
sub_27:Test (Best Model) - Loss: 2.5052 - Accuracy: 0.3913 - F1: 0.3419
sub_27:Test (Best Model) - Loss: 3.1413 - Accuracy: 0.3478 - F1: 0.3254
sub_27:Test (Best Model) - Loss: 2.7434 - Accuracy: 0.4638 - F1: 0.4144
sub_27:Test (Best Model) - Loss: 3.1123 - Accuracy: 0.4493 - F1: 0.4049
sub_27:Test (Best Model) - Loss: 2.8377 - Accuracy: 0.4058 - F1: 0.3443
sub_27:Test (Best Model) - Loss: 1.6399 - Accuracy: 0.5000 - F1: 0.5023
sub_27:Test (Best Model) - Loss: 1.7090 - Accuracy: 0.4412 - F1: 0.4380
sub_27:Test (Best Model) - Loss: 1.8744 - Accuracy: 0.5000 - F1: 0.4984
sub_27:Test (Best Model) - Loss: 1.7498 - Accuracy: 0.4412 - F1: 0.4489
sub_27:Test (Best Model) - Loss: 2.0087 - Accuracy: 0.4265 - F1: 0.4273
sub_28:Test (Best Model) - Loss: 2.8098 - Accuracy: 0.2500 - F1: 0.2537
sub_28:Test (Best Model) - Loss: 2.6915 - Accuracy: 0.3382 - F1: 0.3310
sub_28:Test (Best Model) - Loss: 3.1750 - Accuracy: 0.2500 - F1: 0.2044
sub_28:Test (Best Model) - Loss: 2.6831 - Accuracy: 0.2647 - F1: 0.2490
sub_28:Test (Best Model) - Loss: 3.0231 - Accuracy: 0.2353 - F1: 0.2683
sub_28:Test (Best Model) - Loss: 3.9334 - Accuracy: 0.2647 - F1: 0.2455
sub_28:Test (Best Model) - Loss: 3.9395 - Accuracy: 0.2794 - F1: 0.2407
sub_28:Test (Best Model) - Loss: 3.9989 - Accuracy: 0.1765 - F1: 0.1700
sub_28:Test (Best Model) - Loss: 4.0541 - Accuracy: 0.3529 - F1: 0.3396
sub_28:Test (Best Model) - Loss: 4.1934 - Accuracy: 0.2647 - F1: 0.2249
sub_28:Test (Best Model) - Loss: 1.6840 - Accuracy: 0.3971 - F1: 0.3761
sub_28:Test (Best Model) - Loss: 1.7581 - Accuracy: 0.4412 - F1: 0.4205
sub_28:Test (Best Model) - Loss: 1.6320 - Accuracy: 0.3676 - F1: 0.3452
sub_28:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.4559 - F1: 0.4367
sub_28:Test (Best Model) - Loss: 1.7352 - Accuracy: 0.4412 - F1: 0.3801
sub_29:Test (Best Model) - Loss: 2.3393 - Accuracy: 0.5441 - F1: 0.5376
sub_29:Test (Best Model) - Loss: 2.1394 - Accuracy: 0.5588 - F1: 0.5607
sub_29:Test (Best Model) - Loss: 1.8023 - Accuracy: 0.5588 - F1: 0.5697
sub_29:Test (Best Model) - Loss: 2.3914 - Accuracy: 0.5735 - F1: 0.5648
sub_29:Test (Best Model) - Loss: 2.4938 - Accuracy: 0.4706 - F1: 0.4621
sub_29:Test (Best Model) - Loss: 1.0137 - Accuracy: 0.6176 - F1: 0.6322
sub_29:Test (Best Model) - Loss: 1.2130 - Accuracy: 0.6029 - F1: 0.6185
sub_29:Test (Best Model) - Loss: 1.5071 - Accuracy: 0.4706 - F1: 0.4791
sub_29:Test (Best Model) - Loss: 1.1235 - Accuracy: 0.5882 - F1: 0.6054
sub_29:Test (Best Model) - Loss: 1.2947 - Accuracy: 0.5147 - F1: 0.5446
sub_29:Test (Best Model) - Loss: 1.4097 - Accuracy: 0.5507 - F1: 0.5712
sub_29:Test (Best Model) - Loss: 1.5613 - Accuracy: 0.5072 - F1: 0.5260
sub_29:Test (Best Model) - Loss: 1.5663 - Accuracy: 0.5652 - F1: 0.5797
sub_29:Test (Best Model) - Loss: 1.6497 - Accuracy: 0.5942 - F1: 0.6063
sub_29:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.5797 - F1: 0.5891

=== Summary Results ===

acc: 41.78 ± 6.66
F1: 41.14 ± 6.77
acc-in: 51.39 ± 6.22
F1-in: 49.74 ± 6.26
