lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.5471 - Accuracy: 0.4118 - F1: 0.4398
sub_1:Test (Best Model) - Loss: 1.7449 - Accuracy: 0.4118 - F1: 0.4201
sub_1:Test (Best Model) - Loss: 1.8090 - Accuracy: 0.3529 - F1: 0.3484
sub_1:Test (Best Model) - Loss: 1.3764 - Accuracy: 0.4412 - F1: 0.4737
sub_1:Test (Best Model) - Loss: 1.6403 - Accuracy: 0.4265 - F1: 0.4481
sub_1:Test (Best Model) - Loss: 1.8226 - Accuracy: 0.4348 - F1: 0.4155
sub_1:Test (Best Model) - Loss: 1.9682 - Accuracy: 0.4058 - F1: 0.3949
sub_1:Test (Best Model) - Loss: 2.0949 - Accuracy: 0.4058 - F1: 0.3849
sub_1:Test (Best Model) - Loss: 1.9724 - Accuracy: 0.4348 - F1: 0.4152
sub_1:Test (Best Model) - Loss: 2.0871 - Accuracy: 0.2899 - F1: 0.2908
sub_1:Test (Best Model) - Loss: 1.6959 - Accuracy: 0.3529 - F1: 0.3342
sub_1:Test (Best Model) - Loss: 1.3262 - Accuracy: 0.4265 - F1: 0.4256
sub_1:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.5000 - F1: 0.5146
sub_1:Test (Best Model) - Loss: 1.7911 - Accuracy: 0.4412 - F1: 0.4306
sub_1:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.4853 - F1: 0.4655
sub_2:Test (Best Model) - Loss: 2.1025 - Accuracy: 0.2319 - F1: 0.2538
sub_2:Test (Best Model) - Loss: 2.3271 - Accuracy: 0.2609 - F1: 0.2738
sub_2:Test (Best Model) - Loss: 2.0922 - Accuracy: 0.2464 - F1: 0.2734
sub_2:Test (Best Model) - Loss: 2.1480 - Accuracy: 0.1884 - F1: 0.2246
sub_2:Test (Best Model) - Loss: 2.4820 - Accuracy: 0.2464 - F1: 0.2770
sub_2:Test (Best Model) - Loss: 1.8021 - Accuracy: 0.2794 - F1: 0.2612
sub_2:Test (Best Model) - Loss: 1.9407 - Accuracy: 0.2500 - F1: 0.2315
sub_2:Test (Best Model) - Loss: 1.6723 - Accuracy: 0.3971 - F1: 0.4128
sub_2:Test (Best Model) - Loss: 1.7884 - Accuracy: 0.3971 - F1: 0.3720
sub_2:Test (Best Model) - Loss: 1.7913 - Accuracy: 0.3382 - F1: 0.3548
sub_2:Test (Best Model) - Loss: 2.2154 - Accuracy: 0.3333 - F1: 0.2975
sub_2:Test (Best Model) - Loss: 1.9567 - Accuracy: 0.3333 - F1: 0.2762
sub_2:Test (Best Model) - Loss: 1.8680 - Accuracy: 0.3333 - F1: 0.3171
sub_2:Test (Best Model) - Loss: 1.9644 - Accuracy: 0.3478 - F1: 0.2986
sub_2:Test (Best Model) - Loss: 2.0577 - Accuracy: 0.3913 - F1: 0.3602
sub_3:Test (Best Model) - Loss: 2.1728 - Accuracy: 0.3382 - F1: 0.3343
sub_3:Test (Best Model) - Loss: 2.1809 - Accuracy: 0.3088 - F1: 0.3052
sub_3:Test (Best Model) - Loss: 2.3294 - Accuracy: 0.2794 - F1: 0.2825
sub_3:Test (Best Model) - Loss: 2.1395 - Accuracy: 0.2647 - F1: 0.2579
sub_3:Test (Best Model) - Loss: 2.2163 - Accuracy: 0.2794 - F1: 0.2794
sub_3:Test (Best Model) - Loss: 1.9290 - Accuracy: 0.3623 - F1: 0.3247
sub_3:Test (Best Model) - Loss: 2.0312 - Accuracy: 0.2464 - F1: 0.2470
sub_3:Test (Best Model) - Loss: 2.0367 - Accuracy: 0.2174 - F1: 0.2027
sub_3:Test (Best Model) - Loss: 1.9969 - Accuracy: 0.2899 - F1: 0.2456
sub_3:Test (Best Model) - Loss: 1.9313 - Accuracy: 0.3043 - F1: 0.3142
sub_3:Test (Best Model) - Loss: 2.5278 - Accuracy: 0.2754 - F1: 0.2650
sub_3:Test (Best Model) - Loss: 2.2821 - Accuracy: 0.2464 - F1: 0.2220
sub_3:Test (Best Model) - Loss: 2.3552 - Accuracy: 0.3043 - F1: 0.2938
sub_3:Test (Best Model) - Loss: 2.2900 - Accuracy: 0.3043 - F1: 0.2825
sub_3:Test (Best Model) - Loss: 2.6450 - Accuracy: 0.3333 - F1: 0.3076
sub_4:Test (Best Model) - Loss: 1.6300 - Accuracy: 0.5072 - F1: 0.5237
sub_4:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.4493 - F1: 0.4480
sub_4:Test (Best Model) - Loss: 1.7577 - Accuracy: 0.4783 - F1: 0.4869
sub_4:Test (Best Model) - Loss: 1.5024 - Accuracy: 0.5507 - F1: 0.5427
sub_4:Test (Best Model) - Loss: 1.9318 - Accuracy: 0.4203 - F1: 0.4044
sub_4:Test (Best Model) - Loss: 1.5072 - Accuracy: 0.4928 - F1: 0.4854
sub_4:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.4638 - F1: 0.4705
sub_4:Test (Best Model) - Loss: 1.2350 - Accuracy: 0.4928 - F1: 0.4953
sub_4:Test (Best Model) - Loss: 1.4805 - Accuracy: 0.4783 - F1: 0.4651
sub_4:Test (Best Model) - Loss: 1.3989 - Accuracy: 0.3913 - F1: 0.3963
sub_4:Test (Best Model) - Loss: 1.6941 - Accuracy: 0.4058 - F1: 0.3881
sub_4:Test (Best Model) - Loss: 1.6397 - Accuracy: 0.4638 - F1: 0.4555
sub_4:Test (Best Model) - Loss: 1.7653 - Accuracy: 0.3768 - F1: 0.3795
sub_4:Test (Best Model) - Loss: 1.6432 - Accuracy: 0.4058 - F1: 0.4098
sub_4:Test (Best Model) - Loss: 1.7725 - Accuracy: 0.4928 - F1: 0.4965
sub_5:Test (Best Model) - Loss: 2.3565 - Accuracy: 0.4118 - F1: 0.3702
sub_5:Test (Best Model) - Loss: 2.6525 - Accuracy: 0.3824 - F1: 0.3489
sub_5:Test (Best Model) - Loss: 3.0553 - Accuracy: 0.3971 - F1: 0.4055
sub_5:Test (Best Model) - Loss: 2.4291 - Accuracy: 0.4559 - F1: 0.4679
sub_5:Test (Best Model) - Loss: 2.1977 - Accuracy: 0.3824 - F1: 0.4019
sub_5:Test (Best Model) - Loss: 1.2677 - Accuracy: 0.5441 - F1: 0.5457
sub_5:Test (Best Model) - Loss: 1.1854 - Accuracy: 0.5294 - F1: 0.5199
sub_5:Test (Best Model) - Loss: 1.4414 - Accuracy: 0.4412 - F1: 0.4495
sub_5:Test (Best Model) - Loss: 1.1749 - Accuracy: 0.5882 - F1: 0.6001
sub_5:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.5147 - F1: 0.5150
sub_5:Test (Best Model) - Loss: 1.4961 - Accuracy: 0.4265 - F1: 0.4214
sub_5:Test (Best Model) - Loss: 1.6794 - Accuracy: 0.3676 - F1: 0.3686
sub_5:Test (Best Model) - Loss: 1.6274 - Accuracy: 0.4265 - F1: 0.4105
sub_5:Test (Best Model) - Loss: 1.5460 - Accuracy: 0.3676 - F1: 0.3671
sub_5:Test (Best Model) - Loss: 1.4513 - Accuracy: 0.3971 - F1: 0.4018
sub_6:Test (Best Model) - Loss: 1.3072 - Accuracy: 0.5000 - F1: 0.4900
sub_6:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.4559 - F1: 0.4530
sub_6:Test (Best Model) - Loss: 1.5668 - Accuracy: 0.5147 - F1: 0.5035
sub_6:Test (Best Model) - Loss: 1.2769 - Accuracy: 0.4412 - F1: 0.4197
sub_6:Test (Best Model) - Loss: 1.4621 - Accuracy: 0.5147 - F1: 0.4994
sub_6:Test (Best Model) - Loss: 2.0350 - Accuracy: 0.4203 - F1: 0.3392
sub_6:Test (Best Model) - Loss: 1.7556 - Accuracy: 0.4348 - F1: 0.3537
sub_6:Test (Best Model) - Loss: 1.8653 - Accuracy: 0.3768 - F1: 0.3168
sub_6:Test (Best Model) - Loss: 1.6970 - Accuracy: 0.3913 - F1: 0.3399
sub_6:Test (Best Model) - Loss: 1.9020 - Accuracy: 0.3478 - F1: 0.2701
sub_6:Test (Best Model) - Loss: 1.6248 - Accuracy: 0.3478 - F1: 0.3475
sub_6:Test (Best Model) - Loss: 2.0101 - Accuracy: 0.3913 - F1: 0.3707
sub_6:Test (Best Model) - Loss: 1.7946 - Accuracy: 0.4203 - F1: 0.4302
sub_6:Test (Best Model) - Loss: 1.5381 - Accuracy: 0.4348 - F1: 0.4251
sub_6:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.4928 - F1: 0.4896
sub_7:Test (Best Model) - Loss: 1.4465 - Accuracy: 0.5588 - F1: 0.5339
sub_7:Test (Best Model) - Loss: 1.3841 - Accuracy: 0.4559 - F1: 0.4475
sub_7:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.5147 - F1: 0.4744
sub_7:Test (Best Model) - Loss: 1.2515 - Accuracy: 0.5294 - F1: 0.5095
sub_7:Test (Best Model) - Loss: 1.6870 - Accuracy: 0.4853 - F1: 0.4671
sub_7:Test (Best Model) - Loss: 2.2566 - Accuracy: 0.3529 - F1: 0.3241
sub_7:Test (Best Model) - Loss: 2.1091 - Accuracy: 0.3971 - F1: 0.3708
sub_7:Test (Best Model) - Loss: 1.9041 - Accuracy: 0.3382 - F1: 0.3402
sub_7:Test (Best Model) - Loss: 2.1790 - Accuracy: 0.4265 - F1: 0.3987
sub_7:Test (Best Model) - Loss: 1.8654 - Accuracy: 0.3971 - F1: 0.3519
sub_7:Test (Best Model) - Loss: 1.5873 - Accuracy: 0.4706 - F1: 0.4663
sub_7:Test (Best Model) - Loss: 1.8109 - Accuracy: 0.3824 - F1: 0.3810
sub_7:Test (Best Model) - Loss: 1.8466 - Accuracy: 0.3676 - F1: 0.3741
sub_7:Test (Best Model) - Loss: 1.7523 - Accuracy: 0.4559 - F1: 0.4559
sub_7:Test (Best Model) - Loss: 1.7532 - Accuracy: 0.3824 - F1: 0.3828
sub_8:Test (Best Model) - Loss: 2.4753 - Accuracy: 0.2794 - F1: 0.2790
sub_8:Test (Best Model) - Loss: 2.6523 - Accuracy: 0.2500 - F1: 0.2427
sub_8:Test (Best Model) - Loss: 2.6470 - Accuracy: 0.2794 - F1: 0.3078
sub_8:Test (Best Model) - Loss: 2.3484 - Accuracy: 0.3235 - F1: 0.3019
sub_8:Test (Best Model) - Loss: 2.2978 - Accuracy: 0.2647 - F1: 0.2675
sub_8:Test (Best Model) - Loss: 1.8394 - Accuracy: 0.3235 - F1: 0.3415
sub_8:Test (Best Model) - Loss: 2.1017 - Accuracy: 0.3088 - F1: 0.2822
sub_8:Test (Best Model) - Loss: 1.8323 - Accuracy: 0.2941 - F1: 0.2915
sub_8:Test (Best Model) - Loss: 2.3185 - Accuracy: 0.2794 - F1: 0.2761
sub_8:Test (Best Model) - Loss: 2.1594 - Accuracy: 0.2941 - F1: 0.2957
sub_8:Test (Best Model) - Loss: 2.5215 - Accuracy: 0.2059 - F1: 0.1853
sub_8:Test (Best Model) - Loss: 2.6508 - Accuracy: 0.2500 - F1: 0.2399
sub_8:Test (Best Model) - Loss: 2.4811 - Accuracy: 0.3088 - F1: 0.3139
sub_8:Test (Best Model) - Loss: 2.3794 - Accuracy: 0.3382 - F1: 0.3319
sub_8:Test (Best Model) - Loss: 2.0950 - Accuracy: 0.3235 - F1: 0.3040
sub_9:Test (Best Model) - Loss: 1.5729 - Accuracy: 0.4118 - F1: 0.4224
sub_9:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.5000 - F1: 0.5299
sub_9:Test (Best Model) - Loss: 1.6151 - Accuracy: 0.4118 - F1: 0.4480
sub_9:Test (Best Model) - Loss: 1.3721 - Accuracy: 0.5588 - F1: 0.5750
sub_9:Test (Best Model) - Loss: 1.3272 - Accuracy: 0.4706 - F1: 0.4787
sub_9:Test (Best Model) - Loss: 2.8918 - Accuracy: 0.2500 - F1: 0.2427
sub_9:Test (Best Model) - Loss: 2.6034 - Accuracy: 0.3676 - F1: 0.3692
sub_9:Test (Best Model) - Loss: 2.1925 - Accuracy: 0.3824 - F1: 0.3713
sub_9:Test (Best Model) - Loss: 1.9751 - Accuracy: 0.3235 - F1: 0.3317
sub_9:Test (Best Model) - Loss: 2.1660 - Accuracy: 0.2647 - F1: 0.2812
sub_9:Test (Best Model) - Loss: 2.4811 - Accuracy: 0.3824 - F1: 0.3999
sub_9:Test (Best Model) - Loss: 2.2827 - Accuracy: 0.4853 - F1: 0.4991
sub_9:Test (Best Model) - Loss: 2.2699 - Accuracy: 0.3676 - F1: 0.3978
sub_9:Test (Best Model) - Loss: 2.5028 - Accuracy: 0.3676 - F1: 0.3819
sub_9:Test (Best Model) - Loss: 2.3328 - Accuracy: 0.4265 - F1: 0.4445
sub_10:Test (Best Model) - Loss: 2.3131 - Accuracy: 0.2059 - F1: 0.1779
sub_10:Test (Best Model) - Loss: 2.0610 - Accuracy: 0.3382 - F1: 0.3368
sub_10:Test (Best Model) - Loss: 2.1101 - Accuracy: 0.2794 - F1: 0.2505
sub_10:Test (Best Model) - Loss: 2.0947 - Accuracy: 0.3382 - F1: 0.3301
sub_10:Test (Best Model) - Loss: 2.2447 - Accuracy: 0.3676 - F1: 0.3633
sub_10:Test (Best Model) - Loss: 2.1084 - Accuracy: 0.2647 - F1: 0.2551
sub_10:Test (Best Model) - Loss: 2.0555 - Accuracy: 0.2500 - F1: 0.2566
sub_10:Test (Best Model) - Loss: 2.0406 - Accuracy: 0.3235 - F1: 0.3251
sub_10:Test (Best Model) - Loss: 1.9400 - Accuracy: 0.2794 - F1: 0.2758
sub_10:Test (Best Model) - Loss: 2.1676 - Accuracy: 0.2500 - F1: 0.2464
sub_10:Test (Best Model) - Loss: 2.8052 - Accuracy: 0.2174 - F1: 0.2064
sub_10:Test (Best Model) - Loss: 2.5261 - Accuracy: 0.2609 - F1: 0.2573
sub_10:Test (Best Model) - Loss: 2.2595 - Accuracy: 0.2899 - F1: 0.2841
sub_10:Test (Best Model) - Loss: 2.0436 - Accuracy: 0.2899 - F1: 0.2789
sub_10:Test (Best Model) - Loss: 2.0424 - Accuracy: 0.2899 - F1: 0.2820
sub_11:Test (Best Model) - Loss: 2.3932 - Accuracy: 0.3623 - F1: 0.3468
sub_11:Test (Best Model) - Loss: 2.1116 - Accuracy: 0.3333 - F1: 0.3313
sub_11:Test (Best Model) - Loss: 2.1682 - Accuracy: 0.3043 - F1: 0.3083
sub_11:Test (Best Model) - Loss: 2.1226 - Accuracy: 0.2899 - F1: 0.2941
sub_11:Test (Best Model) - Loss: 2.3393 - Accuracy: 0.2609 - F1: 0.2666
sub_11:Test (Best Model) - Loss: 1.9612 - Accuracy: 0.4348 - F1: 0.3804
sub_11:Test (Best Model) - Loss: 1.9525 - Accuracy: 0.4493 - F1: 0.4084
sub_11:Test (Best Model) - Loss: 1.6436 - Accuracy: 0.4493 - F1: 0.4039
sub_11:Test (Best Model) - Loss: 2.0983 - Accuracy: 0.4348 - F1: 0.3970
sub_11:Test (Best Model) - Loss: 1.9482 - Accuracy: 0.4348 - F1: 0.3599
sub_11:Test (Best Model) - Loss: 1.7361 - Accuracy: 0.3623 - F1: 0.2967
sub_11:Test (Best Model) - Loss: 2.0234 - Accuracy: 0.3768 - F1: 0.3469
sub_11:Test (Best Model) - Loss: 1.8358 - Accuracy: 0.4348 - F1: 0.3801
sub_11:Test (Best Model) - Loss: 1.8362 - Accuracy: 0.3623 - F1: 0.3398
sub_11:Test (Best Model) - Loss: 1.9773 - Accuracy: 0.3913 - F1: 0.3472
sub_12:Test (Best Model) - Loss: 1.3494 - Accuracy: 0.5147 - F1: 0.4994
sub_12:Test (Best Model) - Loss: 1.3317 - Accuracy: 0.5294 - F1: 0.5351
sub_12:Test (Best Model) - Loss: 1.5056 - Accuracy: 0.4706 - F1: 0.4311
sub_12:Test (Best Model) - Loss: 1.2732 - Accuracy: 0.5294 - F1: 0.5254
sub_12:Test (Best Model) - Loss: 1.5068 - Accuracy: 0.4706 - F1: 0.4550
sub_12:Test (Best Model) - Loss: 1.8200 - Accuracy: 0.3913 - F1: 0.3980
sub_12:Test (Best Model) - Loss: 1.5400 - Accuracy: 0.4638 - F1: 0.4303
sub_12:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.4203 - F1: 0.4239
sub_12:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.4493 - F1: 0.4446
sub_12:Test (Best Model) - Loss: 1.7871 - Accuracy: 0.3913 - F1: 0.3981
sub_12:Test (Best Model) - Loss: 1.7466 - Accuracy: 0.4265 - F1: 0.4075
sub_12:Test (Best Model) - Loss: 1.8265 - Accuracy: 0.4118 - F1: 0.4019
sub_12:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.3529 - F1: 0.3502
sub_12:Test (Best Model) - Loss: 1.9749 - Accuracy: 0.4118 - F1: 0.4135
sub_12:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.4265 - F1: 0.4335
sub_13:Test (Best Model) - Loss: 2.0248 - Accuracy: 0.3824 - F1: 0.3853
sub_13:Test (Best Model) - Loss: 2.2193 - Accuracy: 0.3971 - F1: 0.3948
sub_13:Test (Best Model) - Loss: 2.0998 - Accuracy: 0.4559 - F1: 0.4678
sub_13:Test (Best Model) - Loss: 1.9956 - Accuracy: 0.3529 - F1: 0.3697
sub_13:Test (Best Model) - Loss: 1.7278 - Accuracy: 0.4706 - F1: 0.4739
sub_13:Test (Best Model) - Loss: 1.8826 - Accuracy: 0.3768 - F1: 0.3759
sub_13:Test (Best Model) - Loss: 1.8301 - Accuracy: 0.3913 - F1: 0.4029
sub_13:Test (Best Model) - Loss: 2.2601 - Accuracy: 0.3043 - F1: 0.3085
sub_13:Test (Best Model) - Loss: 2.3722 - Accuracy: 0.3913 - F1: 0.4097
sub_13:Test (Best Model) - Loss: 2.0215 - Accuracy: 0.4493 - F1: 0.4618
sub_13:Test (Best Model) - Loss: 1.9730 - Accuracy: 0.3971 - F1: 0.4067
sub_13:Test (Best Model) - Loss: 1.8626 - Accuracy: 0.3382 - F1: 0.3605
sub_13:Test (Best Model) - Loss: 2.2260 - Accuracy: 0.3382 - F1: 0.3595
sub_13:Test (Best Model) - Loss: 2.0179 - Accuracy: 0.3382 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 1.6851 - Accuracy: 0.3676 - F1: 0.3709
sub_14:Test (Best Model) - Loss: 1.9041 - Accuracy: 0.3088 - F1: 0.3442
sub_14:Test (Best Model) - Loss: 1.9889 - Accuracy: 0.2500 - F1: 0.2605
sub_14:Test (Best Model) - Loss: 1.8945 - Accuracy: 0.3235 - F1: 0.3443
sub_14:Test (Best Model) - Loss: 2.2150 - Accuracy: 0.3529 - F1: 0.3546
sub_14:Test (Best Model) - Loss: 1.8941 - Accuracy: 0.3529 - F1: 0.3668
sub_14:Test (Best Model) - Loss: 1.8644 - Accuracy: 0.3235 - F1: 0.3366
sub_14:Test (Best Model) - Loss: 2.2560 - Accuracy: 0.4265 - F1: 0.4368
sub_14:Test (Best Model) - Loss: 2.0563 - Accuracy: 0.3676 - F1: 0.3806
sub_14:Test (Best Model) - Loss: 1.9268 - Accuracy: 0.3676 - F1: 0.3833
sub_14:Test (Best Model) - Loss: 2.1356 - Accuracy: 0.3235 - F1: 0.3120
sub_14:Test (Best Model) - Loss: 1.8403 - Accuracy: 0.4559 - F1: 0.4568
sub_14:Test (Best Model) - Loss: 2.1806 - Accuracy: 0.3529 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 1.8747 - Accuracy: 0.3824 - F1: 0.3832
sub_14:Test (Best Model) - Loss: 1.8133 - Accuracy: 0.2941 - F1: 0.2967
sub_14:Test (Best Model) - Loss: 1.8270 - Accuracy: 0.3088 - F1: 0.3265
sub_15:Test (Best Model) - Loss: 2.1053 - Accuracy: 0.3971 - F1: 0.4210
sub_15:Test (Best Model) - Loss: 2.6053 - Accuracy: 0.3382 - F1: 0.3450
sub_15:Test (Best Model) - Loss: 2.2103 - Accuracy: 0.3824 - F1: 0.4081
sub_15:Test (Best Model) - Loss: 1.6881 - Accuracy: 0.4265 - F1: 0.4532
sub_15:Test (Best Model) - Loss: 1.9914 - Accuracy: 0.3971 - F1: 0.4177
sub_15:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.5294 - F1: 0.5384
sub_15:Test (Best Model) - Loss: 2.0579 - Accuracy: 0.5000 - F1: 0.5046
sub_15:Test (Best Model) - Loss: 1.5125 - Accuracy: 0.5000 - F1: 0.5141
sub_15:Test (Best Model) - Loss: 1.5648 - Accuracy: 0.4706 - F1: 0.4887
sub_15:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.5147 - F1: 0.5188
sub_15:Test (Best Model) - Loss: 1.7834 - Accuracy: 0.4559 - F1: 0.4545
sub_15:Test (Best Model) - Loss: 1.7692 - Accuracy: 0.3088 - F1: 0.3328
sub_15:Test (Best Model) - Loss: 1.9633 - Accuracy: 0.4118 - F1: 0.4138
sub_15:Test (Best Model) - Loss: 1.8098 - Accuracy: 0.3824 - F1: 0.3995
sub_15:Test (Best Model) - Loss: 2.0052 - Accuracy: 0.3676 - F1: 0.3768
sub_16:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.4412 - F1: 0.3890
sub_16:Test (Best Model) - Loss: 1.3340 - Accuracy: 0.4706 - F1: 0.4060
sub_16:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.4412 - F1: 0.4207
sub_16:Test (Best Model) - Loss: 1.4103 - Accuracy: 0.4412 - F1: 0.4396
sub_16:Test (Best Model) - Loss: 1.2959 - Accuracy: 0.4706 - F1: 0.4311
sub_16:Test (Best Model) - Loss: 1.9411 - Accuracy: 0.4118 - F1: 0.4038
sub_16:Test (Best Model) - Loss: 1.7332 - Accuracy: 0.4265 - F1: 0.4310
sub_16:Test (Best Model) - Loss: 1.9024 - Accuracy: 0.3971 - F1: 0.3845
sub_16:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.3824 - F1: 0.3686
sub_16:Test (Best Model) - Loss: 2.4049 - Accuracy: 0.3529 - F1: 0.3612
sub_16:Test (Best Model) - Loss: 1.5467 - Accuracy: 0.4559 - F1: 0.4069
sub_16:Test (Best Model) - Loss: 1.5669 - Accuracy: 0.5147 - F1: 0.4637
sub_16:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.4706 - F1: 0.4380
sub_16:Test (Best Model) - Loss: 1.5260 - Accuracy: 0.4118 - F1: 0.3956
sub_16:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.4853 - F1: 0.4470
sub_17:Test (Best Model) - Loss: 1.5346 - Accuracy: 0.5217 - F1: 0.5104
sub_17:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.4348 - F1: 0.4398
sub_17:Test (Best Model) - Loss: 1.5305 - Accuracy: 0.4203 - F1: 0.4063
sub_17:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.3623 - F1: 0.3636
sub_17:Test (Best Model) - Loss: 1.4440 - Accuracy: 0.4058 - F1: 0.4080
sub_17:Test (Best Model) - Loss: 2.2814 - Accuracy: 0.3623 - F1: 0.3254
sub_17:Test (Best Model) - Loss: 2.3549 - Accuracy: 0.3478 - F1: 0.3078
sub_17:Test (Best Model) - Loss: 2.3146 - Accuracy: 0.4493 - F1: 0.4028
sub_17:Test (Best Model) - Loss: 2.3120 - Accuracy: 0.4203 - F1: 0.3805
sub_17:Test (Best Model) - Loss: 2.3369 - Accuracy: 0.3768 - F1: 0.3388
sub_17:Test (Best Model) - Loss: 1.6834 - Accuracy: 0.4412 - F1: 0.4418
sub_17:Test (Best Model) - Loss: 1.8160 - Accuracy: 0.3971 - F1: 0.3924
sub_17:Test (Best Model) - Loss: 1.7733 - Accuracy: 0.4118 - F1: 0.4068
sub_17:Test (Best Model) - Loss: 1.8703 - Accuracy: 0.4706 - F1: 0.4821
sub_17:Test (Best Model) - Loss: 1.7059 - Accuracy: 0.4118 - F1: 0.4033
sub_18:Test (Best Model) - Loss: 1.6725 - Accuracy: 0.3043 - F1: 0.3014
sub_18:Test (Best Model) - Loss: 1.6454 - Accuracy: 0.4203 - F1: 0.4278
sub_18:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.4348 - F1: 0.4339
sub_18:Test (Best Model) - Loss: 1.7616 - Accuracy: 0.4203 - F1: 0.4387
sub_18:Test (Best Model) - Loss: 1.5754 - Accuracy: 0.4348 - F1: 0.4589
sub_18:Test (Best Model) - Loss: 1.7824 - Accuracy: 0.3971 - F1: 0.4329
sub_18:Test (Best Model) - Loss: 1.8659 - Accuracy: 0.3676 - F1: 0.3840
sub_18:Test (Best Model) - Loss: 1.9619 - Accuracy: 0.3382 - F1: 0.3495
sub_18:Test (Best Model) - Loss: 1.9841 - Accuracy: 0.3235 - F1: 0.3552
sub_18:Test (Best Model) - Loss: 2.0038 - Accuracy: 0.3529 - F1: 0.3839
sub_18:Test (Best Model) - Loss: 1.7953 - Accuracy: 0.3235 - F1: 0.3421
sub_18:Test (Best Model) - Loss: 2.1024 - Accuracy: 0.2941 - F1: 0.3182
sub_18:Test (Best Model) - Loss: 2.0634 - Accuracy: 0.2500 - F1: 0.2774
sub_18:Test (Best Model) - Loss: 1.9249 - Accuracy: 0.3676 - F1: 0.3810
sub_18:Test (Best Model) - Loss: 1.8213 - Accuracy: 0.3676 - F1: 0.3885
sub_19:Test (Best Model) - Loss: 2.1820 - Accuracy: 0.2500 - F1: 0.2177
sub_19:Test (Best Model) - Loss: 2.1445 - Accuracy: 0.2206 - F1: 0.2342
sub_19:Test (Best Model) - Loss: 2.2020 - Accuracy: 0.2206 - F1: 0.2280
sub_19:Test (Best Model) - Loss: 2.0865 - Accuracy: 0.2353 - F1: 0.2138
sub_19:Test (Best Model) - Loss: 1.9676 - Accuracy: 0.3235 - F1: 0.3392
sub_19:Test (Best Model) - Loss: 1.9920 - Accuracy: 0.3088 - F1: 0.2790
sub_19:Test (Best Model) - Loss: 1.8692 - Accuracy: 0.3824 - F1: 0.3445
sub_19:Test (Best Model) - Loss: 1.9603 - Accuracy: 0.3529 - F1: 0.3098
sub_19:Test (Best Model) - Loss: 1.7648 - Accuracy: 0.3235 - F1: 0.3114
sub_19:Test (Best Model) - Loss: 2.0969 - Accuracy: 0.4265 - F1: 0.4344
sub_19:Test (Best Model) - Loss: 2.2840 - Accuracy: 0.3676 - F1: 0.3505
sub_19:Test (Best Model) - Loss: 2.6343 - Accuracy: 0.2941 - F1: 0.3060
sub_19:Test (Best Model) - Loss: 2.0363 - Accuracy: 0.3529 - F1: 0.3134
sub_19:Test (Best Model) - Loss: 2.4908 - Accuracy: 0.3529 - F1: 0.3658
sub_19:Test (Best Model) - Loss: 1.7547 - Accuracy: 0.4265 - F1: 0.4332
sub_20:Test (Best Model) - Loss: 1.7577 - Accuracy: 0.4706 - F1: 0.4683
sub_20:Test (Best Model) - Loss: 1.8750 - Accuracy: 0.4706 - F1: 0.4789
sub_20:Test (Best Model) - Loss: 1.7033 - Accuracy: 0.5147 - F1: 0.5093
sub_20:Test (Best Model) - Loss: 1.8364 - Accuracy: 0.4118 - F1: 0.4205
sub_20:Test (Best Model) - Loss: 2.0060 - Accuracy: 0.4853 - F1: 0.4969
sub_20:Test (Best Model) - Loss: 1.6844 - Accuracy: 0.3971 - F1: 0.4130
sub_20:Test (Best Model) - Loss: 1.9470 - Accuracy: 0.4412 - F1: 0.4595
sub_20:Test (Best Model) - Loss: 2.2133 - Accuracy: 0.4118 - F1: 0.4291
sub_20:Test (Best Model) - Loss: 1.9001 - Accuracy: 0.4412 - F1: 0.4267
sub_20:Test (Best Model) - Loss: 2.0047 - Accuracy: 0.3824 - F1: 0.4029
sub_20:Test (Best Model) - Loss: 1.7828 - Accuracy: 0.4058 - F1: 0.4177
sub_20:Test (Best Model) - Loss: 2.0921 - Accuracy: 0.4203 - F1: 0.4227
sub_20:Test (Best Model) - Loss: 1.9041 - Accuracy: 0.4058 - F1: 0.4007
sub_20:Test (Best Model) - Loss: 1.9414 - Accuracy: 0.4203 - F1: 0.4142
sub_20:Test (Best Model) - Loss: 1.9656 - Accuracy: 0.4203 - F1: 0.4309
sub_21:Test (Best Model) - Loss: 1.6251 - Accuracy: 0.4118 - F1: 0.3890
sub_21:Test (Best Model) - Loss: 1.7459 - Accuracy: 0.4118 - F1: 0.3873
sub_21:Test (Best Model) - Loss: 2.0946 - Accuracy: 0.5000 - F1: 0.4668
sub_21:Test (Best Model) - Loss: 1.8520 - Accuracy: 0.3529 - F1: 0.3297
sub_21:Test (Best Model) - Loss: 2.2066 - Accuracy: 0.3824 - F1: 0.3491
sub_21:Test (Best Model) - Loss: 1.6415 - Accuracy: 0.3824 - F1: 0.3488
sub_21:Test (Best Model) - Loss: 1.5708 - Accuracy: 0.4118 - F1: 0.4089
sub_21:Test (Best Model) - Loss: 1.4052 - Accuracy: 0.4412 - F1: 0.4302
sub_21:Test (Best Model) - Loss: 1.6335 - Accuracy: 0.4412 - F1: 0.4220
sub_21:Test (Best Model) - Loss: 1.4559 - Accuracy: 0.4559 - F1: 0.4373
sub_21:Test (Best Model) - Loss: 1.4331 - Accuracy: 0.3382 - F1: 0.3214
sub_21:Test (Best Model) - Loss: 1.7391 - Accuracy: 0.4265 - F1: 0.4110
sub_21:Test (Best Model) - Loss: 1.7285 - Accuracy: 0.3971 - F1: 0.3538
sub_21:Test (Best Model) - Loss: 1.9560 - Accuracy: 0.3382 - F1: 0.3140
sub_21:Test (Best Model) - Loss: 1.6720 - Accuracy: 0.3676 - F1: 0.3259
sub_22:Test (Best Model) - Loss: 2.1898 - Accuracy: 0.3676 - F1: 0.3871
sub_22:Test (Best Model) - Loss: 2.1210 - Accuracy: 0.4265 - F1: 0.4375
sub_22:Test (Best Model) - Loss: 2.3444 - Accuracy: 0.2794 - F1: 0.2916
sub_22:Test (Best Model) - Loss: 1.9899 - Accuracy: 0.3529 - F1: 0.3746
sub_22:Test (Best Model) - Loss: 2.2642 - Accuracy: 0.3088 - F1: 0.3198
sub_22:Test (Best Model) - Loss: 1.6581 - Accuracy: 0.2899 - F1: 0.2672
sub_22:Test (Best Model) - Loss: 1.4493 - Accuracy: 0.3188 - F1: 0.3035
sub_22:Test (Best Model) - Loss: 1.6659 - Accuracy: 0.3623 - F1: 0.3528
sub_22:Test (Best Model) - Loss: 1.6291 - Accuracy: 0.3913 - F1: 0.4021
sub_22:Test (Best Model) - Loss: 1.7067 - Accuracy: 0.2609 - F1: 0.2566
sub_22:Test (Best Model) - Loss: 1.6243 - Accuracy: 0.3676 - F1: 0.3915
sub_22:Test (Best Model) - Loss: 1.5520 - Accuracy: 0.3529 - F1: 0.3793
sub_22:Test (Best Model) - Loss: 1.6787 - Accuracy: 0.3676 - F1: 0.3860
sub_22:Test (Best Model) - Loss: 1.5810 - Accuracy: 0.3529 - F1: 0.3794
sub_22:Test (Best Model) - Loss: 1.5205 - Accuracy: 0.4559 - F1: 0.4843
sub_23:Test (Best Model) - Loss: 1.8714 - Accuracy: 0.3188 - F1: 0.3254
sub_23:Test (Best Model) - Loss: 1.6393 - Accuracy: 0.4058 - F1: 0.4046
sub_23:Test (Best Model) - Loss: 1.6347 - Accuracy: 0.3768 - F1: 0.3735
sub_23:Test (Best Model) - Loss: 1.3574 - Accuracy: 0.5072 - F1: 0.5022
sub_23:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.4348 - F1: 0.4523
sub_23:Test (Best Model) - Loss: 1.8082 - Accuracy: 0.4118 - F1: 0.3760
sub_23:Test (Best Model) - Loss: 1.4124 - Accuracy: 0.4265 - F1: 0.4211
sub_23:Test (Best Model) - Loss: 1.4572 - Accuracy: 0.4559 - F1: 0.4471
sub_23:Test (Best Model) - Loss: 1.4424 - Accuracy: 0.5147 - F1: 0.5162
sub_23:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.4853 - F1: 0.4475
sub_23:Test (Best Model) - Loss: 2.9002 - Accuracy: 0.3333 - F1: 0.2867
sub_23:Test (Best Model) - Loss: 2.3502 - Accuracy: 0.3623 - F1: 0.3443
sub_23:Test (Best Model) - Loss: 2.2737 - Accuracy: 0.3623 - F1: 0.3546
sub_23:Test (Best Model) - Loss: 2.6415 - Accuracy: 0.3333 - F1: 0.2978
sub_23:Test (Best Model) - Loss: 2.4308 - Accuracy: 0.3478 - F1: 0.3081
sub_24:Test (Best Model) - Loss: 1.9121 - Accuracy: 0.3529 - F1: 0.3551
sub_24:Test (Best Model) - Loss: 2.0134 - Accuracy: 0.3529 - F1: 0.3537
sub_24:Test (Best Model) - Loss: 1.9552 - Accuracy: 0.3088 - F1: 0.3117
sub_24:Test (Best Model) - Loss: 2.3022 - Accuracy: 0.3382 - F1: 0.3229
sub_24:Test (Best Model) - Loss: 1.7691 - Accuracy: 0.3382 - F1: 0.3342
sub_24:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.3088 - F1: 0.3089
sub_24:Test (Best Model) - Loss: 1.7215 - Accuracy: 0.3382 - F1: 0.3356
sub_24:Test (Best Model) - Loss: 1.5887 - Accuracy: 0.3824 - F1: 0.3807
sub_24:Test (Best Model) - Loss: 1.4560 - Accuracy: 0.3824 - F1: 0.3799
sub_24:Test (Best Model) - Loss: 1.6533 - Accuracy: 0.3235 - F1: 0.3190
sub_24:Test (Best Model) - Loss: 1.9375 - Accuracy: 0.2941 - F1: 0.3077
sub_24:Test (Best Model) - Loss: 2.0610 - Accuracy: 0.2794 - F1: 0.2803
sub_24:Test (Best Model) - Loss: 2.0583 - Accuracy: 0.2500 - F1: 0.2521
sub_24:Test (Best Model) - Loss: 1.8452 - Accuracy: 0.3529 - F1: 0.3557
sub_24:Test (Best Model) - Loss: 1.9429 - Accuracy: 0.3088 - F1: 0.3050
sub_25:Test (Best Model) - Loss: 1.5473 - Accuracy: 0.4058 - F1: 0.3552
sub_25:Test (Best Model) - Loss: 1.6732 - Accuracy: 0.3478 - F1: 0.3158
sub_25:Test (Best Model) - Loss: 1.6916 - Accuracy: 0.4058 - F1: 0.3755
sub_25:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.4493 - F1: 0.4088
sub_25:Test (Best Model) - Loss: 1.9686 - Accuracy: 0.3623 - F1: 0.3334
sub_25:Test (Best Model) - Loss: 1.7058 - Accuracy: 0.4559 - F1: 0.3867
sub_25:Test (Best Model) - Loss: 1.9430 - Accuracy: 0.3971 - F1: 0.3492
sub_25:Test (Best Model) - Loss: 1.6587 - Accuracy: 0.3971 - F1: 0.3608
sub_25:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.4559 - F1: 0.3856
sub_25:Test (Best Model) - Loss: 1.7368 - Accuracy: 0.4706 - F1: 0.3877
sub_25:Test (Best Model) - Loss: 1.5469 - Accuracy: 0.3971 - F1: 0.3903
sub_25:Test (Best Model) - Loss: 1.7423 - Accuracy: 0.3971 - F1: 0.3657
sub_25:Test (Best Model) - Loss: 1.4357 - Accuracy: 0.4853 - F1: 0.4578
sub_25:Test (Best Model) - Loss: 1.7071 - Accuracy: 0.3824 - F1: 0.3236
sub_25:Test (Best Model) - Loss: 1.5864 - Accuracy: 0.3824 - F1: 0.2939
sub_26:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.3623 - F1: 0.3811
sub_26:Test (Best Model) - Loss: 1.7416 - Accuracy: 0.3913 - F1: 0.4004
sub_26:Test (Best Model) - Loss: 1.6362 - Accuracy: 0.4348 - F1: 0.4484
sub_26:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.3623 - F1: 0.3856
sub_26:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.5507 - F1: 0.5559
sub_26:Test (Best Model) - Loss: 1.6720 - Accuracy: 0.3529 - F1: 0.3816
sub_26:Test (Best Model) - Loss: 1.7200 - Accuracy: 0.3235 - F1: 0.3472
sub_26:Test (Best Model) - Loss: 1.6332 - Accuracy: 0.3382 - F1: 0.3521
sub_26:Test (Best Model) - Loss: 1.7757 - Accuracy: 0.3529 - F1: 0.3661
sub_26:Test (Best Model) - Loss: 1.9953 - Accuracy: 0.2794 - F1: 0.3242
sub_26:Test (Best Model) - Loss: 1.5753 - Accuracy: 0.5294 - F1: 0.5479
sub_26:Test (Best Model) - Loss: 1.9880 - Accuracy: 0.4412 - F1: 0.4542
sub_26:Test (Best Model) - Loss: 1.9495 - Accuracy: 0.4412 - F1: 0.4509
sub_26:Test (Best Model) - Loss: 1.7107 - Accuracy: 0.4559 - F1: 0.4680
sub_26:Test (Best Model) - Loss: 1.6879 - Accuracy: 0.4853 - F1: 0.4813
sub_27:Test (Best Model) - Loss: 1.5346 - Accuracy: 0.5217 - F1: 0.5104
sub_27:Test (Best Model) - Loss: 1.3240 - Accuracy: 0.4348 - F1: 0.4398
sub_27:Test (Best Model) - Loss: 1.5305 - Accuracy: 0.4203 - F1: 0.4063
sub_27:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.3623 - F1: 0.3636
sub_27:Test (Best Model) - Loss: 1.4440 - Accuracy: 0.4058 - F1: 0.4080
sub_27:Test (Best Model) - Loss: 2.2814 - Accuracy: 0.3623 - F1: 0.3254
sub_27:Test (Best Model) - Loss: 2.3549 - Accuracy: 0.3478 - F1: 0.3078
sub_27:Test (Best Model) - Loss: 2.3146 - Accuracy: 0.4493 - F1: 0.4028
sub_27:Test (Best Model) - Loss: 2.3120 - Accuracy: 0.4203 - F1: 0.3805
sub_27:Test (Best Model) - Loss: 2.3369 - Accuracy: 0.3768 - F1: 0.3388
sub_27:Test (Best Model) - Loss: 1.6834 - Accuracy: 0.4412 - F1: 0.4418
sub_27:Test (Best Model) - Loss: 1.8160 - Accuracy: 0.3971 - F1: 0.3924
sub_27:Test (Best Model) - Loss: 1.7733 - Accuracy: 0.4118 - F1: 0.4068
sub_27:Test (Best Model) - Loss: 1.8703 - Accuracy: 0.4706 - F1: 0.4821
sub_27:Test (Best Model) - Loss: 1.7059 - Accuracy: 0.4118 - F1: 0.4033
sub_28:Test (Best Model) - Loss: 2.0717 - Accuracy: 0.2794 - F1: 0.2701
sub_28:Test (Best Model) - Loss: 2.1450 - Accuracy: 0.3088 - F1: 0.3023
sub_28:Test (Best Model) - Loss: 2.3121 - Accuracy: 0.3088 - F1: 0.2985
sub_28:Test (Best Model) - Loss: 2.2550 - Accuracy: 0.2647 - F1: 0.2454
sub_28:Test (Best Model) - Loss: 2.3915 - Accuracy: 0.2647 - F1: 0.2841
sub_28:Test (Best Model) - Loss: 3.0851 - Accuracy: 0.2206 - F1: 0.2193
sub_28:Test (Best Model) - Loss: 3.1818 - Accuracy: 0.2941 - F1: 0.2960
sub_28:Test (Best Model) - Loss: 3.1583 - Accuracy: 0.1912 - F1: 0.1858
sub_28:Test (Best Model) - Loss: 3.4783 - Accuracy: 0.2647 - F1: 0.2428
sub_28:Test (Best Model) - Loss: 3.4813 - Accuracy: 0.3088 - F1: 0.3038
sub_28:Test (Best Model) - Loss: 1.6672 - Accuracy: 0.3676 - F1: 0.3489
sub_28:Test (Best Model) - Loss: 1.6198 - Accuracy: 0.3971 - F1: 0.3762
sub_28:Test (Best Model) - Loss: 1.4607 - Accuracy: 0.3824 - F1: 0.3861
sub_28:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.3971 - F1: 0.3957
sub_28:Test (Best Model) - Loss: 1.4863 - Accuracy: 0.3529 - F1: 0.3415
sub_29:Test (Best Model) - Loss: 2.0034 - Accuracy: 0.5294 - F1: 0.5329
sub_29:Test (Best Model) - Loss: 2.0600 - Accuracy: 0.5147 - F1: 0.5189
sub_29:Test (Best Model) - Loss: 1.7096 - Accuracy: 0.4853 - F1: 0.4948
sub_29:Test (Best Model) - Loss: 2.0254 - Accuracy: 0.5000 - F1: 0.5044
sub_29:Test (Best Model) - Loss: 1.8254 - Accuracy: 0.5294 - F1: 0.5250
sub_29:Test (Best Model) - Loss: 1.2307 - Accuracy: 0.5294 - F1: 0.5522
sub_29:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.5441 - F1: 0.5580
sub_29:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.4559 - F1: 0.4749
sub_29:Test (Best Model) - Loss: 1.1013 - Accuracy: 0.5882 - F1: 0.6116
sub_29:Test (Best Model) - Loss: 1.2283 - Accuracy: 0.5147 - F1: 0.5421
sub_29:Test (Best Model) - Loss: 1.3273 - Accuracy: 0.5362 - F1: 0.5603
sub_29:Test (Best Model) - Loss: 1.5541 - Accuracy: 0.5217 - F1: 0.5390
sub_29:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.4928 - F1: 0.5184
sub_29:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.5652 - F1: 0.5816
sub_29:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.5072 - F1: 0.5282

=== Summary Results ===

acc: 38.77 ± 5.83
F1: 38.19 ± 6.03
acc-in: 46.93 ± 5.33
F1-in: 45.59 ± 5.36
