lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.8263 - Accuracy: 0.3088 - F1: 0.3089
sub_1:Test (Best Model) - Loss: 1.9773 - Accuracy: 0.3529 - F1: 0.3480
sub_1:Test (Best Model) - Loss: 1.9821 - Accuracy: 0.2500 - F1: 0.2577
sub_1:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.3676 - F1: 0.3824
sub_1:Test (Best Model) - Loss: 1.7454 - Accuracy: 0.4118 - F1: 0.4233
sub_1:Test (Best Model) - Loss: 1.7239 - Accuracy: 0.3913 - F1: 0.3337
sub_1:Test (Best Model) - Loss: 2.0344 - Accuracy: 0.3333 - F1: 0.3101
sub_1:Test (Best Model) - Loss: 1.8286 - Accuracy: 0.3913 - F1: 0.3794
sub_1:Test (Best Model) - Loss: 1.9410 - Accuracy: 0.4058 - F1: 0.3859
sub_1:Test (Best Model) - Loss: 2.0537 - Accuracy: 0.3043 - F1: 0.2733
sub_1:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3824 - F1: 0.3634
sub_1:Test (Best Model) - Loss: 1.4992 - Accuracy: 0.4412 - F1: 0.4500
sub_1:Test (Best Model) - Loss: 1.3065 - Accuracy: 0.5000 - F1: 0.5015
sub_1:Test (Best Model) - Loss: 1.8222 - Accuracy: 0.3824 - F1: 0.3681
sub_1:Test (Best Model) - Loss: 1.5641 - Accuracy: 0.4706 - F1: 0.4665
sub_2:Test (Best Model) - Loss: 2.0192 - Accuracy: 0.2609 - F1: 0.2595
sub_2:Test (Best Model) - Loss: 2.0927 - Accuracy: 0.2609 - F1: 0.2630
sub_2:Test (Best Model) - Loss: 1.8984 - Accuracy: 0.2609 - F1: 0.2670
sub_2:Test (Best Model) - Loss: 2.1350 - Accuracy: 0.1884 - F1: 0.2148
sub_2:Test (Best Model) - Loss: 2.1955 - Accuracy: 0.2609 - F1: 0.2788
sub_2:Test (Best Model) - Loss: 1.8800 - Accuracy: 0.3088 - F1: 0.3147
sub_2:Test (Best Model) - Loss: 1.8576 - Accuracy: 0.2647 - F1: 0.2350
sub_2:Test (Best Model) - Loss: 1.6523 - Accuracy: 0.3382 - F1: 0.3278
sub_2:Test (Best Model) - Loss: 1.9165 - Accuracy: 0.3088 - F1: 0.2877
sub_2:Test (Best Model) - Loss: 1.9308 - Accuracy: 0.3235 - F1: 0.3146
sub_2:Test (Best Model) - Loss: 1.9466 - Accuracy: 0.3043 - F1: 0.2649
sub_2:Test (Best Model) - Loss: 1.8688 - Accuracy: 0.3188 - F1: 0.2509
sub_2:Test (Best Model) - Loss: 1.6496 - Accuracy: 0.3333 - F1: 0.3128
sub_2:Test (Best Model) - Loss: 1.9112 - Accuracy: 0.3188 - F1: 0.2735
sub_2:Test (Best Model) - Loss: 1.8350 - Accuracy: 0.3913 - F1: 0.3714
sub_3:Test (Best Model) - Loss: 2.2919 - Accuracy: 0.2941 - F1: 0.2819
sub_3:Test (Best Model) - Loss: 1.8982 - Accuracy: 0.2353 - F1: 0.2298
sub_3:Test (Best Model) - Loss: 2.1898 - Accuracy: 0.2647 - F1: 0.2616
sub_3:Test (Best Model) - Loss: 2.0533 - Accuracy: 0.2353 - F1: 0.2273
sub_3:Test (Best Model) - Loss: 2.1960 - Accuracy: 0.3088 - F1: 0.3060
sub_3:Test (Best Model) - Loss: 1.9226 - Accuracy: 0.3188 - F1: 0.2997
sub_3:Test (Best Model) - Loss: 2.0495 - Accuracy: 0.1884 - F1: 0.1911
sub_3:Test (Best Model) - Loss: 1.8745 - Accuracy: 0.2174 - F1: 0.2113
sub_3:Test (Best Model) - Loss: 2.0271 - Accuracy: 0.2899 - F1: 0.2622
sub_3:Test (Best Model) - Loss: 1.9011 - Accuracy: 0.3043 - F1: 0.3071
sub_3:Test (Best Model) - Loss: 2.2898 - Accuracy: 0.3043 - F1: 0.2985
sub_3:Test (Best Model) - Loss: 1.9289 - Accuracy: 0.3188 - F1: 0.2995
sub_3:Test (Best Model) - Loss: 2.3090 - Accuracy: 0.2464 - F1: 0.2354
sub_3:Test (Best Model) - Loss: 2.1066 - Accuracy: 0.2899 - F1: 0.2779
sub_3:Test (Best Model) - Loss: 2.3403 - Accuracy: 0.3188 - F1: 0.3046
sub_4:Test (Best Model) - Loss: 1.9079 - Accuracy: 0.3623 - F1: 0.3597
sub_4:Test (Best Model) - Loss: 1.6665 - Accuracy: 0.4058 - F1: 0.4146
sub_4:Test (Best Model) - Loss: 1.9158 - Accuracy: 0.4058 - F1: 0.4250
sub_4:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.4203 - F1: 0.4039
sub_4:Test (Best Model) - Loss: 2.0337 - Accuracy: 0.4058 - F1: 0.3751
sub_4:Test (Best Model) - Loss: 1.6675 - Accuracy: 0.4203 - F1: 0.4254
sub_4:Test (Best Model) - Loss: 1.4789 - Accuracy: 0.3768 - F1: 0.3817
sub_4:Test (Best Model) - Loss: 1.2194 - Accuracy: 0.4493 - F1: 0.4508
sub_4:Test (Best Model) - Loss: 1.6282 - Accuracy: 0.4058 - F1: 0.3943
sub_4:Test (Best Model) - Loss: 1.5218 - Accuracy: 0.3623 - F1: 0.3468
sub_4:Test (Best Model) - Loss: 1.6731 - Accuracy: 0.3623 - F1: 0.3151
sub_4:Test (Best Model) - Loss: 1.6324 - Accuracy: 0.3623 - F1: 0.3399
sub_4:Test (Best Model) - Loss: 1.5431 - Accuracy: 0.3768 - F1: 0.3878
sub_4:Test (Best Model) - Loss: 1.4773 - Accuracy: 0.4783 - F1: 0.4953
sub_4:Test (Best Model) - Loss: 1.5724 - Accuracy: 0.4783 - F1: 0.4801
sub_5:Test (Best Model) - Loss: 2.4360 - Accuracy: 0.3235 - F1: 0.2996
sub_5:Test (Best Model) - Loss: 2.3962 - Accuracy: 0.2941 - F1: 0.2639
sub_5:Test (Best Model) - Loss: 2.7156 - Accuracy: 0.2794 - F1: 0.2696
sub_5:Test (Best Model) - Loss: 2.4721 - Accuracy: 0.4559 - F1: 0.4537
sub_5:Test (Best Model) - Loss: 2.0178 - Accuracy: 0.3088 - F1: 0.3092
sub_5:Test (Best Model) - Loss: 1.4330 - Accuracy: 0.4559 - F1: 0.4536
sub_5:Test (Best Model) - Loss: 1.3143 - Accuracy: 0.4559 - F1: 0.4495
sub_5:Test (Best Model) - Loss: 1.4237 - Accuracy: 0.4118 - F1: 0.4220
sub_5:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.5147 - F1: 0.5203
sub_5:Test (Best Model) - Loss: 1.4164 - Accuracy: 0.4265 - F1: 0.4259
sub_5:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.3382 - F1: 0.3359
sub_5:Test (Best Model) - Loss: 1.6336 - Accuracy: 0.3382 - F1: 0.2979
sub_5:Test (Best Model) - Loss: 1.5654 - Accuracy: 0.3824 - F1: 0.3628
sub_5:Test (Best Model) - Loss: 1.5251 - Accuracy: 0.4118 - F1: 0.3977
sub_5:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.4265 - F1: 0.4149
sub_6:Test (Best Model) - Loss: 1.3585 - Accuracy: 0.4706 - F1: 0.4619
sub_6:Test (Best Model) - Loss: 1.4058 - Accuracy: 0.4412 - F1: 0.4380
sub_6:Test (Best Model) - Loss: 1.4589 - Accuracy: 0.4265 - F1: 0.4170
sub_6:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.4559 - F1: 0.4473
sub_6:Test (Best Model) - Loss: 1.4459 - Accuracy: 0.4412 - F1: 0.4357
sub_6:Test (Best Model) - Loss: 1.9868 - Accuracy: 0.3623 - F1: 0.2845
sub_6:Test (Best Model) - Loss: 1.9435 - Accuracy: 0.3478 - F1: 0.2707
sub_6:Test (Best Model) - Loss: 1.9168 - Accuracy: 0.3478 - F1: 0.2684
sub_6:Test (Best Model) - Loss: 1.8623 - Accuracy: 0.3913 - F1: 0.3175
sub_6:Test (Best Model) - Loss: 1.8741 - Accuracy: 0.3188 - F1: 0.2340
sub_6:Test (Best Model) - Loss: 1.6814 - Accuracy: 0.3478 - F1: 0.3388
sub_6:Test (Best Model) - Loss: 1.9293 - Accuracy: 0.3333 - F1: 0.3108
sub_6:Test (Best Model) - Loss: 1.8134 - Accuracy: 0.4348 - F1: 0.4349
sub_6:Test (Best Model) - Loss: 1.5282 - Accuracy: 0.4493 - F1: 0.4327
sub_6:Test (Best Model) - Loss: 1.6265 - Accuracy: 0.4493 - F1: 0.4428
sub_7:Test (Best Model) - Loss: 1.6727 - Accuracy: 0.4853 - F1: 0.4447
sub_7:Test (Best Model) - Loss: 1.5404 - Accuracy: 0.4559 - F1: 0.4481
sub_7:Test (Best Model) - Loss: 1.6770 - Accuracy: 0.3382 - F1: 0.3332
sub_7:Test (Best Model) - Loss: 1.4666 - Accuracy: 0.4559 - F1: 0.4460
sub_7:Test (Best Model) - Loss: 1.6292 - Accuracy: 0.4265 - F1: 0.4034
sub_7:Test (Best Model) - Loss: 2.1391 - Accuracy: 0.2941 - F1: 0.2873
sub_7:Test (Best Model) - Loss: 1.8845 - Accuracy: 0.3676 - F1: 0.3601
sub_7:Test (Best Model) - Loss: 1.7334 - Accuracy: 0.3824 - F1: 0.3951
sub_7:Test (Best Model) - Loss: 1.9686 - Accuracy: 0.3676 - F1: 0.3570
sub_7:Test (Best Model) - Loss: 1.6488 - Accuracy: 0.4265 - F1: 0.4089
sub_7:Test (Best Model) - Loss: 1.6239 - Accuracy: 0.4118 - F1: 0.4091
sub_7:Test (Best Model) - Loss: 1.8422 - Accuracy: 0.3824 - F1: 0.3851
sub_7:Test (Best Model) - Loss: 1.7546 - Accuracy: 0.3824 - F1: 0.3858
sub_7:Test (Best Model) - Loss: 1.8545 - Accuracy: 0.3676 - F1: 0.3666
sub_7:Test (Best Model) - Loss: 1.7538 - Accuracy: 0.3382 - F1: 0.3391
sub_8:Test (Best Model) - Loss: 2.3749 - Accuracy: 0.2647 - F1: 0.2585
sub_8:Test (Best Model) - Loss: 2.3661 - Accuracy: 0.2353 - F1: 0.2237
sub_8:Test (Best Model) - Loss: 2.4680 - Accuracy: 0.2500 - F1: 0.2671
sub_8:Test (Best Model) - Loss: 2.0553 - Accuracy: 0.3235 - F1: 0.2949
sub_8:Test (Best Model) - Loss: 2.1232 - Accuracy: 0.2353 - F1: 0.2385
sub_8:Test (Best Model) - Loss: 1.7659 - Accuracy: 0.3529 - F1: 0.3518
sub_8:Test (Best Model) - Loss: 2.1032 - Accuracy: 0.2941 - F1: 0.2906
sub_8:Test (Best Model) - Loss: 1.6754 - Accuracy: 0.3235 - F1: 0.3160
sub_8:Test (Best Model) - Loss: 2.0961 - Accuracy: 0.2206 - F1: 0.2060
sub_8:Test (Best Model) - Loss: 2.1452 - Accuracy: 0.2353 - F1: 0.2352
sub_8:Test (Best Model) - Loss: 2.3464 - Accuracy: 0.1176 - F1: 0.1017
sub_8:Test (Best Model) - Loss: 2.2640 - Accuracy: 0.2941 - F1: 0.2891
sub_8:Test (Best Model) - Loss: 2.4056 - Accuracy: 0.3235 - F1: 0.3258
sub_8:Test (Best Model) - Loss: 2.1864 - Accuracy: 0.3382 - F1: 0.3329
sub_8:Test (Best Model) - Loss: 2.0014 - Accuracy: 0.2500 - F1: 0.2323
sub_9:Test (Best Model) - Loss: 1.6775 - Accuracy: 0.4118 - F1: 0.4188
sub_9:Test (Best Model) - Loss: 1.4911 - Accuracy: 0.4412 - F1: 0.4542
sub_9:Test (Best Model) - Loss: 1.5400 - Accuracy: 0.3971 - F1: 0.4324
sub_9:Test (Best Model) - Loss: 1.3636 - Accuracy: 0.4412 - F1: 0.4597
sub_9:Test (Best Model) - Loss: 1.3892 - Accuracy: 0.5147 - F1: 0.5297
sub_9:Test (Best Model) - Loss: 2.9587 - Accuracy: 0.2500 - F1: 0.2362
sub_9:Test (Best Model) - Loss: 2.3742 - Accuracy: 0.3382 - F1: 0.3588
sub_9:Test (Best Model) - Loss: 2.3428 - Accuracy: 0.3676 - F1: 0.3789
sub_9:Test (Best Model) - Loss: 1.8903 - Accuracy: 0.3382 - F1: 0.3505
sub_9:Test (Best Model) - Loss: 2.1853 - Accuracy: 0.2647 - F1: 0.2739
sub_9:Test (Best Model) - Loss: 2.2493 - Accuracy: 0.3382 - F1: 0.3608
sub_9:Test (Best Model) - Loss: 2.0346 - Accuracy: 0.3971 - F1: 0.4163
sub_9:Test (Best Model) - Loss: 1.9750 - Accuracy: 0.3088 - F1: 0.3463
sub_9:Test (Best Model) - Loss: 2.4689 - Accuracy: 0.3676 - F1: 0.3920
sub_9:Test (Best Model) - Loss: 2.4881 - Accuracy: 0.4118 - F1: 0.4359
sub_10:Test (Best Model) - Loss: 2.2244 - Accuracy: 0.2206 - F1: 0.2074
sub_10:Test (Best Model) - Loss: 1.9194 - Accuracy: 0.3088 - F1: 0.3072
sub_10:Test (Best Model) - Loss: 2.0804 - Accuracy: 0.2794 - F1: 0.2578
sub_10:Test (Best Model) - Loss: 1.9943 - Accuracy: 0.2941 - F1: 0.2778
sub_10:Test (Best Model) - Loss: 2.1070 - Accuracy: 0.3088 - F1: 0.2970
sub_10:Test (Best Model) - Loss: 2.0954 - Accuracy: 0.2941 - F1: 0.2842
sub_10:Test (Best Model) - Loss: 2.1279 - Accuracy: 0.2353 - F1: 0.2402
sub_10:Test (Best Model) - Loss: 2.0234 - Accuracy: 0.2206 - F1: 0.2073
sub_10:Test (Best Model) - Loss: 1.9989 - Accuracy: 0.2794 - F1: 0.2731
sub_10:Test (Best Model) - Loss: 2.0104 - Accuracy: 0.2206 - F1: 0.2220
sub_10:Test (Best Model) - Loss: 2.6007 - Accuracy: 0.2174 - F1: 0.2052
sub_10:Test (Best Model) - Loss: 2.1971 - Accuracy: 0.2319 - F1: 0.2320
sub_10:Test (Best Model) - Loss: 2.0443 - Accuracy: 0.2464 - F1: 0.2282
sub_10:Test (Best Model) - Loss: 2.0174 - Accuracy: 0.2754 - F1: 0.2706
sub_10:Test (Best Model) - Loss: 2.1244 - Accuracy: 0.2174 - F1: 0.2164
sub_11:Test (Best Model) - Loss: 2.2422 - Accuracy: 0.3333 - F1: 0.3281
sub_11:Test (Best Model) - Loss: 2.1972 - Accuracy: 0.2899 - F1: 0.2873
sub_11:Test (Best Model) - Loss: 2.2113 - Accuracy: 0.2899 - F1: 0.2852
sub_11:Test (Best Model) - Loss: 2.0813 - Accuracy: 0.3043 - F1: 0.3115
sub_11:Test (Best Model) - Loss: 2.0379 - Accuracy: 0.3043 - F1: 0.3060
sub_11:Test (Best Model) - Loss: 1.9833 - Accuracy: 0.4348 - F1: 0.3976
sub_11:Test (Best Model) - Loss: 1.8705 - Accuracy: 0.4203 - F1: 0.3669
sub_11:Test (Best Model) - Loss: 1.7312 - Accuracy: 0.4493 - F1: 0.4196
sub_11:Test (Best Model) - Loss: 2.1944 - Accuracy: 0.4058 - F1: 0.3701
sub_11:Test (Best Model) - Loss: 1.9250 - Accuracy: 0.4348 - F1: 0.3988
sub_11:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.2899 - F1: 0.2351
sub_11:Test (Best Model) - Loss: 1.9135 - Accuracy: 0.3478 - F1: 0.3177
sub_11:Test (Best Model) - Loss: 1.8480 - Accuracy: 0.4058 - F1: 0.3479
sub_11:Test (Best Model) - Loss: 1.7907 - Accuracy: 0.3043 - F1: 0.2623
sub_11:Test (Best Model) - Loss: 1.9170 - Accuracy: 0.3188 - F1: 0.2871
sub_12:Test (Best Model) - Loss: 1.3901 - Accuracy: 0.4559 - F1: 0.4331
sub_12:Test (Best Model) - Loss: 1.4925 - Accuracy: 0.3971 - F1: 0.3985
sub_12:Test (Best Model) - Loss: 1.4832 - Accuracy: 0.4559 - F1: 0.4216
sub_12:Test (Best Model) - Loss: 1.3957 - Accuracy: 0.4559 - F1: 0.4510
sub_12:Test (Best Model) - Loss: 1.5119 - Accuracy: 0.3676 - F1: 0.3652
sub_12:Test (Best Model) - Loss: 1.7746 - Accuracy: 0.3623 - F1: 0.3560
sub_12:Test (Best Model) - Loss: 1.4991 - Accuracy: 0.3913 - F1: 0.3664
sub_12:Test (Best Model) - Loss: 1.6702 - Accuracy: 0.4058 - F1: 0.3919
sub_12:Test (Best Model) - Loss: 1.7175 - Accuracy: 0.4348 - F1: 0.4308
sub_12:Test (Best Model) - Loss: 1.7347 - Accuracy: 0.4348 - F1: 0.4355
sub_12:Test (Best Model) - Loss: 1.6846 - Accuracy: 0.4265 - F1: 0.4084
sub_12:Test (Best Model) - Loss: 1.7403 - Accuracy: 0.3088 - F1: 0.2831
sub_12:Test (Best Model) - Loss: 1.5388 - Accuracy: 0.3382 - F1: 0.3393
sub_12:Test (Best Model) - Loss: 1.8450 - Accuracy: 0.3676 - F1: 0.3497
sub_12:Test (Best Model) - Loss: 1.6922 - Accuracy: 0.3824 - F1: 0.3656
sub_13:Test (Best Model) - Loss: 2.0576 - Accuracy: 0.3529 - F1: 0.3542
sub_13:Test (Best Model) - Loss: 2.1241 - Accuracy: 0.3088 - F1: 0.3217
sub_13:Test (Best Model) - Loss: 1.9709 - Accuracy: 0.3676 - F1: 0.3791
sub_13:Test (Best Model) - Loss: 2.1442 - Accuracy: 0.2794 - F1: 0.2878
sub_13:Test (Best Model) - Loss: 1.9849 - Accuracy: 0.4559 - F1: 0.4592
sub_13:Test (Best Model) - Loss: 1.9787 - Accuracy: 0.3043 - F1: 0.3034
sub_13:Test (Best Model) - Loss: 1.9452 - Accuracy: 0.3768 - F1: 0.3778
sub_13:Test (Best Model) - Loss: 1.9864 - Accuracy: 0.2754 - F1: 0.2774
sub_13:Test (Best Model) - Loss: 2.2630 - Accuracy: 0.3623 - F1: 0.3715
sub_13:Test (Best Model) - Loss: 2.0067 - Accuracy: 0.3043 - F1: 0.2932
sub_13:Test (Best Model) - Loss: 1.8535 - Accuracy: 0.3529 - F1: 0.3397
sub_13:Test (Best Model) - Loss: 1.6698 - Accuracy: 0.3088 - F1: 0.3065
sub_13:Test (Best Model) - Loss: 2.0432 - Accuracy: 0.3382 - F1: 0.3527
sub_13:Test (Best Model) - Loss: 1.8649 - Accuracy: 0.3529 - F1: 0.3648
sub_13:Test (Best Model) - Loss: 1.7014 - Accuracy: 0.3235 - F1: 0.3203
sub_14:Test (Best Model) - Loss: 1.8622 - Accuracy: 0.2941 - F1: 0.3033
sub_14:Test (Best Model) - Loss: 1.8055 - Accuracy: 0.2941 - F1: 0.2753
sub_14:Test (Best Model) - Loss: 1.7706 - Accuracy: 0.2941 - F1: 0.2978
sub_14:Test (Best Model) - Loss: 1.9481 - Accuracy: 0.2794 - F1: 0.2856
sub_14:Test (Best Model) - Loss: 1.8628 - Accuracy: 0.3235 - F1: 0.3275
sub_14:Test (Best Model) - Loss: 2.0881 - Accuracy: 0.3235 - F1: 0.3275
sub_14:Test (Best Model) - Loss: 2.0095 - Accuracy: 0.4118 - F1: 0.4193
sub_14:Test (Best Model) - Loss: 1.9137 - Accuracy: 0.3235 - F1: 0.3418
sub_14:Test (Best Model) - Loss: 2.0434 - Accuracy: 0.3824 - F1: 0.3980
sub_14:Test (Best Model) - Loss: 2.2010 - Accuracy: 0.3088 - F1: 0.3075
sub_14:Test (Best Model) - Loss: 1.9226 - Accuracy: 0.3676 - F1: 0.3695
sub_14:Test (Best Model) - Loss: 1.7762 - Accuracy: 0.4265 - F1: 0.4161
sub_14:Test (Best Model) - Loss: 1.8969 - Accuracy: 0.2794 - F1: 0.2745
sub_14:Test (Best Model) - Loss: 1.7904 - Accuracy: 0.3088 - F1: 0.3135
sub_14:Test (Best Model) - Loss: 1.8242 - Accuracy: 0.2647 - F1: 0.2654
sub_15:Test (Best Model) - Loss: 2.0797 - Accuracy: 0.3529 - F1: 0.3720
sub_15:Test (Best Model) - Loss: 2.4004 - Accuracy: 0.3088 - F1: 0.3076
sub_15:Test (Best Model) - Loss: 1.8968 - Accuracy: 0.3382 - F1: 0.3497
sub_15:Test (Best Model) - Loss: 1.6294 - Accuracy: 0.3971 - F1: 0.4160
sub_15:Test (Best Model) - Loss: 2.1619 - Accuracy: 0.3235 - F1: 0.3398
sub_15:Test (Best Model) - Loss: 1.4186 - Accuracy: 0.4559 - F1: 0.4654
sub_15:Test (Best Model) - Loss: 2.1556 - Accuracy: 0.4265 - F1: 0.4396
sub_15:Test (Best Model) - Loss: 1.5626 - Accuracy: 0.5147 - F1: 0.5200
sub_15:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.4118 - F1: 0.4245
sub_15:Test (Best Model) - Loss: 1.6892 - Accuracy: 0.4706 - F1: 0.4680
sub_15:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.3971 - F1: 0.3969
sub_15:Test (Best Model) - Loss: 1.6660 - Accuracy: 0.3088 - F1: 0.3251
sub_15:Test (Best Model) - Loss: 1.6658 - Accuracy: 0.3382 - F1: 0.3525
sub_15:Test (Best Model) - Loss: 1.7571 - Accuracy: 0.3824 - F1: 0.3960
sub_15:Test (Best Model) - Loss: 1.8614 - Accuracy: 0.3382 - F1: 0.3475
sub_16:Test (Best Model) - Loss: 1.5543 - Accuracy: 0.3971 - F1: 0.3536
sub_16:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.3971 - F1: 0.3607
sub_16:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.4706 - F1: 0.4508
sub_16:Test (Best Model) - Loss: 1.5217 - Accuracy: 0.3971 - F1: 0.3963
sub_16:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.4706 - F1: 0.4288
sub_16:Test (Best Model) - Loss: 1.9554 - Accuracy: 0.3824 - F1: 0.3865
sub_16:Test (Best Model) - Loss: 1.9338 - Accuracy: 0.3382 - F1: 0.3414
sub_16:Test (Best Model) - Loss: 1.7942 - Accuracy: 0.3382 - F1: 0.3407
sub_16:Test (Best Model) - Loss: 1.7360 - Accuracy: 0.3971 - F1: 0.3994
sub_16:Test (Best Model) - Loss: 2.3989 - Accuracy: 0.2353 - F1: 0.2447
sub_16:Test (Best Model) - Loss: 1.6286 - Accuracy: 0.3971 - F1: 0.3375
sub_16:Test (Best Model) - Loss: 1.5280 - Accuracy: 0.4559 - F1: 0.4175
sub_16:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.4265 - F1: 0.4047
sub_16:Test (Best Model) - Loss: 1.6736 - Accuracy: 0.3382 - F1: 0.3255
sub_16:Test (Best Model) - Loss: 1.4803 - Accuracy: 0.4706 - F1: 0.4547
sub_17:Test (Best Model) - Loss: 1.5606 - Accuracy: 0.4928 - F1: 0.4712
sub_17:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4058 - F1: 0.3944
sub_17:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.3913 - F1: 0.3819
sub_17:Test (Best Model) - Loss: 1.5486 - Accuracy: 0.4203 - F1: 0.4248
sub_17:Test (Best Model) - Loss: 1.4408 - Accuracy: 0.4203 - F1: 0.4035
sub_17:Test (Best Model) - Loss: 2.1064 - Accuracy: 0.3333 - F1: 0.2861
sub_17:Test (Best Model) - Loss: 2.1434 - Accuracy: 0.3188 - F1: 0.2903
sub_17:Test (Best Model) - Loss: 2.0351 - Accuracy: 0.4058 - F1: 0.3594
sub_17:Test (Best Model) - Loss: 2.0451 - Accuracy: 0.3768 - F1: 0.3438
sub_17:Test (Best Model) - Loss: 1.9692 - Accuracy: 0.3478 - F1: 0.2971
sub_17:Test (Best Model) - Loss: 1.5929 - Accuracy: 0.4853 - F1: 0.4886
sub_17:Test (Best Model) - Loss: 1.6517 - Accuracy: 0.3676 - F1: 0.3560
sub_17:Test (Best Model) - Loss: 1.7800 - Accuracy: 0.3824 - F1: 0.3753
sub_17:Test (Best Model) - Loss: 1.8758 - Accuracy: 0.4118 - F1: 0.4086
sub_17:Test (Best Model) - Loss: 1.8335 - Accuracy: 0.3824 - F1: 0.3842
sub_18:Test (Best Model) - Loss: 1.7467 - Accuracy: 0.3043 - F1: 0.3015
sub_18:Test (Best Model) - Loss: 1.5993 - Accuracy: 0.3043 - F1: 0.3286
sub_18:Test (Best Model) - Loss: 1.6248 - Accuracy: 0.3478 - F1: 0.3581
sub_18:Test (Best Model) - Loss: 1.8195 - Accuracy: 0.3478 - F1: 0.3664
sub_18:Test (Best Model) - Loss: 1.4816 - Accuracy: 0.4058 - F1: 0.4304
sub_18:Test (Best Model) - Loss: 1.7898 - Accuracy: 0.3382 - F1: 0.3680
sub_18:Test (Best Model) - Loss: 1.7371 - Accuracy: 0.2941 - F1: 0.3021
sub_18:Test (Best Model) - Loss: 1.9450 - Accuracy: 0.2941 - F1: 0.3006
sub_18:Test (Best Model) - Loss: 2.0297 - Accuracy: 0.3382 - F1: 0.3606
sub_18:Test (Best Model) - Loss: 2.0131 - Accuracy: 0.3235 - F1: 0.3485
sub_18:Test (Best Model) - Loss: 1.7470 - Accuracy: 0.3235 - F1: 0.3280
sub_18:Test (Best Model) - Loss: 1.8880 - Accuracy: 0.2794 - F1: 0.2662
sub_18:Test (Best Model) - Loss: 1.7577 - Accuracy: 0.3088 - F1: 0.3238
sub_18:Test (Best Model) - Loss: 1.8967 - Accuracy: 0.3529 - F1: 0.3594
sub_18:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.3529 - F1: 0.3744
sub_19:Test (Best Model) - Loss: 1.9063 - Accuracy: 0.2647 - F1: 0.2080
sub_19:Test (Best Model) - Loss: 1.7697 - Accuracy: 0.2500 - F1: 0.2460
sub_19:Test (Best Model) - Loss: 1.8447 - Accuracy: 0.2353 - F1: 0.2370
sub_19:Test (Best Model) - Loss: 1.6358 - Accuracy: 0.3235 - F1: 0.2823
sub_19:Test (Best Model) - Loss: 1.6998 - Accuracy: 0.3382 - F1: 0.3106
sub_19:Test (Best Model) - Loss: 2.0382 - Accuracy: 0.3529 - F1: 0.3395
sub_19:Test (Best Model) - Loss: 1.9497 - Accuracy: 0.3382 - F1: 0.3075
sub_19:Test (Best Model) - Loss: 1.9780 - Accuracy: 0.2941 - F1: 0.2684
sub_19:Test (Best Model) - Loss: 1.7599 - Accuracy: 0.3088 - F1: 0.2815
sub_19:Test (Best Model) - Loss: 1.8395 - Accuracy: 0.3235 - F1: 0.3003
sub_19:Test (Best Model) - Loss: 2.1683 - Accuracy: 0.3088 - F1: 0.3026
sub_19:Test (Best Model) - Loss: 2.5476 - Accuracy: 0.2941 - F1: 0.3114
sub_19:Test (Best Model) - Loss: 1.6183 - Accuracy: 0.3529 - F1: 0.3458
sub_19:Test (Best Model) - Loss: 2.3832 - Accuracy: 0.3382 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 1.9200 - Accuracy: 0.3676 - F1: 0.3850
sub_20:Test (Best Model) - Loss: 1.7987 - Accuracy: 0.4412 - F1: 0.4288
sub_20:Test (Best Model) - Loss: 1.8603 - Accuracy: 0.4853 - F1: 0.4919
sub_20:Test (Best Model) - Loss: 1.7990 - Accuracy: 0.4265 - F1: 0.4026
sub_20:Test (Best Model) - Loss: 1.8462 - Accuracy: 0.3529 - F1: 0.3496
sub_20:Test (Best Model) - Loss: 2.1027 - Accuracy: 0.4265 - F1: 0.4158
sub_20:Test (Best Model) - Loss: 1.7455 - Accuracy: 0.3529 - F1: 0.3509
sub_20:Test (Best Model) - Loss: 1.8364 - Accuracy: 0.3824 - F1: 0.3967
sub_20:Test (Best Model) - Loss: 2.0113 - Accuracy: 0.3824 - F1: 0.4035
sub_20:Test (Best Model) - Loss: 1.9983 - Accuracy: 0.4265 - F1: 0.4289
sub_20:Test (Best Model) - Loss: 1.8278 - Accuracy: 0.4412 - F1: 0.4514
sub_20:Test (Best Model) - Loss: 1.8918 - Accuracy: 0.4203 - F1: 0.4293
sub_20:Test (Best Model) - Loss: 2.1398 - Accuracy: 0.3478 - F1: 0.3350
sub_20:Test (Best Model) - Loss: 1.7824 - Accuracy: 0.4203 - F1: 0.4165
sub_20:Test (Best Model) - Loss: 1.7629 - Accuracy: 0.4058 - F1: 0.4051
sub_20:Test (Best Model) - Loss: 1.8189 - Accuracy: 0.3913 - F1: 0.3901
sub_21:Test (Best Model) - Loss: 1.6376 - Accuracy: 0.4706 - F1: 0.4499
sub_21:Test (Best Model) - Loss: 1.7492 - Accuracy: 0.4118 - F1: 0.3978
sub_21:Test (Best Model) - Loss: 1.8339 - Accuracy: 0.4412 - F1: 0.4253
sub_21:Test (Best Model) - Loss: 1.9097 - Accuracy: 0.3529 - F1: 0.3473
sub_21:Test (Best Model) - Loss: 2.0687 - Accuracy: 0.4118 - F1: 0.3985
sub_21:Test (Best Model) - Loss: 1.6730 - Accuracy: 0.3529 - F1: 0.3303
sub_21:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.3382 - F1: 0.3371
sub_21:Test (Best Model) - Loss: 1.5060 - Accuracy: 0.3235 - F1: 0.3144
sub_21:Test (Best Model) - Loss: 1.6668 - Accuracy: 0.4559 - F1: 0.4279
sub_21:Test (Best Model) - Loss: 1.5821 - Accuracy: 0.3382 - F1: 0.3059
sub_21:Test (Best Model) - Loss: 1.5313 - Accuracy: 0.3088 - F1: 0.3076
sub_21:Test (Best Model) - Loss: 1.7986 - Accuracy: 0.3235 - F1: 0.3191
sub_21:Test (Best Model) - Loss: 1.6899 - Accuracy: 0.3382 - F1: 0.3115
sub_21:Test (Best Model) - Loss: 1.9003 - Accuracy: 0.2941 - F1: 0.2925
sub_21:Test (Best Model) - Loss: 1.6756 - Accuracy: 0.3676 - F1: 0.3367
sub_22:Test (Best Model) - Loss: 1.8961 - Accuracy: 0.3529 - F1: 0.3653
sub_22:Test (Best Model) - Loss: 1.8188 - Accuracy: 0.3824 - F1: 0.3802
sub_22:Test (Best Model) - Loss: 2.0522 - Accuracy: 0.3235 - F1: 0.3464
sub_22:Test (Best Model) - Loss: 1.8445 - Accuracy: 0.2941 - F1: 0.3078
sub_22:Test (Best Model) - Loss: 1.9922 - Accuracy: 0.3676 - F1: 0.3591
sub_22:Test (Best Model) - Loss: 1.6756 - Accuracy: 0.3043 - F1: 0.2692
sub_22:Test (Best Model) - Loss: 1.5128 - Accuracy: 0.3043 - F1: 0.2739
sub_22:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.4203 - F1: 0.3873
sub_22:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.3333 - F1: 0.3487
sub_22:Test (Best Model) - Loss: 1.7084 - Accuracy: 0.2899 - F1: 0.2575
sub_22:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.3529 - F1: 0.3621
sub_22:Test (Best Model) - Loss: 1.4860 - Accuracy: 0.3382 - F1: 0.3418
sub_22:Test (Best Model) - Loss: 1.7271 - Accuracy: 0.3529 - F1: 0.3772
sub_22:Test (Best Model) - Loss: 1.7029 - Accuracy: 0.2794 - F1: 0.2899
sub_22:Test (Best Model) - Loss: 1.5420 - Accuracy: 0.3529 - F1: 0.3852
sub_23:Test (Best Model) - Loss: 1.8725 - Accuracy: 0.2609 - F1: 0.2548
sub_23:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.3913 - F1: 0.3796
sub_23:Test (Best Model) - Loss: 1.8788 - Accuracy: 0.3623 - F1: 0.3546
sub_23:Test (Best Model) - Loss: 1.5026 - Accuracy: 0.3623 - F1: 0.3377
sub_23:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.3913 - F1: 0.4059
sub_23:Test (Best Model) - Loss: 1.7022 - Accuracy: 0.3382 - F1: 0.2885
sub_23:Test (Best Model) - Loss: 1.5399 - Accuracy: 0.3676 - F1: 0.3609
sub_23:Test (Best Model) - Loss: 1.4786 - Accuracy: 0.3971 - F1: 0.3869
sub_23:Test (Best Model) - Loss: 1.4673 - Accuracy: 0.3824 - F1: 0.4008
sub_23:Test (Best Model) - Loss: 1.5237 - Accuracy: 0.3676 - F1: 0.3355
sub_23:Test (Best Model) - Loss: 2.7324 - Accuracy: 0.2174 - F1: 0.1753
sub_23:Test (Best Model) - Loss: 2.5196 - Accuracy: 0.3478 - F1: 0.3382
sub_23:Test (Best Model) - Loss: 2.3203 - Accuracy: 0.3623 - F1: 0.3512
sub_23:Test (Best Model) - Loss: 2.4985 - Accuracy: 0.3333 - F1: 0.2949
sub_23:Test (Best Model) - Loss: 2.5760 - Accuracy: 0.3043 - F1: 0.2380
sub_24:Test (Best Model) - Loss: 1.9718 - Accuracy: 0.3676 - F1: 0.3649
sub_24:Test (Best Model) - Loss: 2.0152 - Accuracy: 0.3529 - F1: 0.3468
sub_24:Test (Best Model) - Loss: 2.0025 - Accuracy: 0.2500 - F1: 0.2552
sub_24:Test (Best Model) - Loss: 2.0207 - Accuracy: 0.2794 - F1: 0.2591
sub_24:Test (Best Model) - Loss: 1.9988 - Accuracy: 0.3088 - F1: 0.3099
sub_24:Test (Best Model) - Loss: 1.6667 - Accuracy: 0.3235 - F1: 0.3232
sub_24:Test (Best Model) - Loss: 1.7066 - Accuracy: 0.3676 - F1: 0.3648
sub_24:Test (Best Model) - Loss: 1.5204 - Accuracy: 0.3382 - F1: 0.3313
sub_24:Test (Best Model) - Loss: 1.4948 - Accuracy: 0.3971 - F1: 0.3888
sub_24:Test (Best Model) - Loss: 1.7098 - Accuracy: 0.2794 - F1: 0.2656
sub_24:Test (Best Model) - Loss: 1.9143 - Accuracy: 0.2794 - F1: 0.2997
sub_24:Test (Best Model) - Loss: 2.0559 - Accuracy: 0.2794 - F1: 0.2806
sub_24:Test (Best Model) - Loss: 1.8726 - Accuracy: 0.2941 - F1: 0.2944
sub_24:Test (Best Model) - Loss: 1.7864 - Accuracy: 0.3529 - F1: 0.3603
sub_24:Test (Best Model) - Loss: 1.7947 - Accuracy: 0.2794 - F1: 0.2758
sub_25:Test (Best Model) - Loss: 1.6256 - Accuracy: 0.3623 - F1: 0.3199
sub_25:Test (Best Model) - Loss: 1.6853 - Accuracy: 0.3478 - F1: 0.3257
sub_25:Test (Best Model) - Loss: 1.6710 - Accuracy: 0.4348 - F1: 0.4183
sub_25:Test (Best Model) - Loss: 1.6840 - Accuracy: 0.3478 - F1: 0.3092
sub_25:Test (Best Model) - Loss: 2.0012 - Accuracy: 0.3188 - F1: 0.2899
sub_25:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.4118 - F1: 0.3481
sub_25:Test (Best Model) - Loss: 1.8300 - Accuracy: 0.3676 - F1: 0.3137
sub_25:Test (Best Model) - Loss: 1.6745 - Accuracy: 0.3676 - F1: 0.3293
sub_25:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.4412 - F1: 0.3649
sub_25:Test (Best Model) - Loss: 1.5946 - Accuracy: 0.4118 - F1: 0.3660
sub_25:Test (Best Model) - Loss: 1.6910 - Accuracy: 0.3676 - F1: 0.3636
sub_25:Test (Best Model) - Loss: 1.7063 - Accuracy: 0.4412 - F1: 0.4361
sub_25:Test (Best Model) - Loss: 1.4475 - Accuracy: 0.3971 - F1: 0.3524
sub_25:Test (Best Model) - Loss: 1.6628 - Accuracy: 0.3824 - F1: 0.3451
sub_25:Test (Best Model) - Loss: 1.7167 - Accuracy: 0.3824 - F1: 0.2994
sub_26:Test (Best Model) - Loss: 1.4866 - Accuracy: 0.4348 - F1: 0.4436
sub_26:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.4203 - F1: 0.4253
sub_26:Test (Best Model) - Loss: 1.4487 - Accuracy: 0.4058 - F1: 0.4214
sub_26:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.4348 - F1: 0.4574
sub_26:Test (Best Model) - Loss: 1.4553 - Accuracy: 0.4493 - F1: 0.4210
sub_26:Test (Best Model) - Loss: 1.5862 - Accuracy: 0.3971 - F1: 0.4220
sub_26:Test (Best Model) - Loss: 1.6876 - Accuracy: 0.3088 - F1: 0.3224
sub_26:Test (Best Model) - Loss: 1.5927 - Accuracy: 0.3382 - F1: 0.3350
sub_26:Test (Best Model) - Loss: 1.5346 - Accuracy: 0.3529 - F1: 0.3607
sub_26:Test (Best Model) - Loss: 1.6854 - Accuracy: 0.3235 - F1: 0.3639
sub_26:Test (Best Model) - Loss: 1.5868 - Accuracy: 0.4706 - F1: 0.5025
sub_26:Test (Best Model) - Loss: 2.0042 - Accuracy: 0.3971 - F1: 0.4006
sub_26:Test (Best Model) - Loss: 1.7012 - Accuracy: 0.4706 - F1: 0.4834
sub_26:Test (Best Model) - Loss: 1.6454 - Accuracy: 0.5000 - F1: 0.5148
sub_26:Test (Best Model) - Loss: 1.7208 - Accuracy: 0.4265 - F1: 0.4369
sub_27:Test (Best Model) - Loss: 1.5606 - Accuracy: 0.4928 - F1: 0.4712
sub_27:Test (Best Model) - Loss: 1.3398 - Accuracy: 0.4058 - F1: 0.3944
sub_27:Test (Best Model) - Loss: 1.4256 - Accuracy: 0.3913 - F1: 0.3819
sub_27:Test (Best Model) - Loss: 1.5486 - Accuracy: 0.4203 - F1: 0.4248
sub_27:Test (Best Model) - Loss: 1.4408 - Accuracy: 0.4203 - F1: 0.4035
sub_27:Test (Best Model) - Loss: 2.1064 - Accuracy: 0.3333 - F1: 0.2861
sub_27:Test (Best Model) - Loss: 2.1434 - Accuracy: 0.3188 - F1: 0.2903
sub_27:Test (Best Model) - Loss: 2.0351 - Accuracy: 0.4058 - F1: 0.3594
sub_27:Test (Best Model) - Loss: 2.0451 - Accuracy: 0.3768 - F1: 0.3438
sub_27:Test (Best Model) - Loss: 1.9692 - Accuracy: 0.3478 - F1: 0.2971
sub_27:Test (Best Model) - Loss: 1.5929 - Accuracy: 0.4853 - F1: 0.4886
sub_27:Test (Best Model) - Loss: 1.6517 - Accuracy: 0.3676 - F1: 0.3560
sub_27:Test (Best Model) - Loss: 1.7800 - Accuracy: 0.3824 - F1: 0.3753
sub_27:Test (Best Model) - Loss: 1.8758 - Accuracy: 0.4118 - F1: 0.4086
sub_27:Test (Best Model) - Loss: 1.8335 - Accuracy: 0.3824 - F1: 0.3842
sub_28:Test (Best Model) - Loss: 1.9088 - Accuracy: 0.2500 - F1: 0.2446
sub_28:Test (Best Model) - Loss: 1.9278 - Accuracy: 0.2794 - F1: 0.2677
sub_28:Test (Best Model) - Loss: 2.1910 - Accuracy: 0.2941 - F1: 0.2931
sub_28:Test (Best Model) - Loss: 1.9892 - Accuracy: 0.2206 - F1: 0.2180
sub_28:Test (Best Model) - Loss: 2.2428 - Accuracy: 0.2353 - F1: 0.2396
sub_28:Test (Best Model) - Loss: 2.6090 - Accuracy: 0.2206 - F1: 0.2089
sub_28:Test (Best Model) - Loss: 2.7196 - Accuracy: 0.2059 - F1: 0.2026
sub_28:Test (Best Model) - Loss: 2.8368 - Accuracy: 0.2059 - F1: 0.2072
sub_28:Test (Best Model) - Loss: 3.0946 - Accuracy: 0.2794 - F1: 0.2570
sub_28:Test (Best Model) - Loss: 2.8724 - Accuracy: 0.3382 - F1: 0.3145
sub_28:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.3676 - F1: 0.3428
sub_28:Test (Best Model) - Loss: 1.5554 - Accuracy: 0.3529 - F1: 0.3366
sub_28:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.3382 - F1: 0.3409
sub_28:Test (Best Model) - Loss: 1.6336 - Accuracy: 0.3382 - F1: 0.3433
sub_28:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.3382 - F1: 0.3153
sub_29:Test (Best Model) - Loss: 1.9909 - Accuracy: 0.4853 - F1: 0.4905
sub_29:Test (Best Model) - Loss: 1.7633 - Accuracy: 0.4559 - F1: 0.4581
sub_29:Test (Best Model) - Loss: 1.5693 - Accuracy: 0.5000 - F1: 0.5198
sub_29:Test (Best Model) - Loss: 1.8752 - Accuracy: 0.3971 - F1: 0.4060
sub_29:Test (Best Model) - Loss: 1.9865 - Accuracy: 0.5000 - F1: 0.4915
sub_29:Test (Best Model) - Loss: 1.4181 - Accuracy: 0.4265 - F1: 0.4542
sub_29:Test (Best Model) - Loss: 1.4664 - Accuracy: 0.4559 - F1: 0.4721
sub_29:Test (Best Model) - Loss: 1.4016 - Accuracy: 0.4118 - F1: 0.4404
sub_29:Test (Best Model) - Loss: 1.2536 - Accuracy: 0.5000 - F1: 0.5208
sub_29:Test (Best Model) - Loss: 1.3255 - Accuracy: 0.4118 - F1: 0.4419
sub_29:Test (Best Model) - Loss: 1.4097 - Accuracy: 0.4783 - F1: 0.4948
sub_29:Test (Best Model) - Loss: 1.5754 - Accuracy: 0.4638 - F1: 0.4822
sub_29:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.4638 - F1: 0.4875
sub_29:Test (Best Model) - Loss: 1.4226 - Accuracy: 0.5362 - F1: 0.5521
sub_29:Test (Best Model) - Loss: 1.5623 - Accuracy: 0.4638 - F1: 0.4885

=== Summary Results ===

acc: 35.80 ± 4.95
F1: 35.04 ± 5.18
acc-in: 43.11 ± 4.58
F1-in: 41.49 ± 4.61
