lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.1919 - Accuracy: 0.4706 - F1: 0.5114
sub_1:Test (Best Model) - Loss: 1.1661 - Accuracy: 0.5000 - F1: 0.5360
sub_1:Test (Best Model) - Loss: 1.2027 - Accuracy: 0.4118 - F1: 0.4467
sub_1:Test (Best Model) - Loss: 1.1666 - Accuracy: 0.5000 - F1: 0.5345
sub_1:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.4559 - F1: 0.4822
sub_1:Test (Best Model) - Loss: 1.2667 - Accuracy: 0.3623 - F1: 0.3750
sub_1:Test (Best Model) - Loss: 1.2537 - Accuracy: 0.3768 - F1: 0.3761
sub_1:Test (Best Model) - Loss: 1.2691 - Accuracy: 0.4058 - F1: 0.4110
sub_1:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.4203 - F1: 0.4220
sub_1:Test (Best Model) - Loss: 1.2467 - Accuracy: 0.4058 - F1: 0.4068
sub_1:Test (Best Model) - Loss: 1.1797 - Accuracy: 0.4706 - F1: 0.4510
sub_1:Test (Best Model) - Loss: 1.1335 - Accuracy: 0.5588 - F1: 0.5610
sub_1:Test (Best Model) - Loss: 1.0610 - Accuracy: 0.5441 - F1: 0.5584
sub_1:Test (Best Model) - Loss: 1.1785 - Accuracy: 0.5294 - F1: 0.5149
sub_1:Test (Best Model) - Loss: 1.1626 - Accuracy: 0.4412 - F1: 0.4391
sub_2:Test (Best Model) - Loss: 1.3840 - Accuracy: 0.2319 - F1: 0.2367
sub_2:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.2754 - F1: 0.2951
sub_2:Test (Best Model) - Loss: 1.4457 - Accuracy: 0.2319 - F1: 0.2556
sub_2:Test (Best Model) - Loss: 1.4498 - Accuracy: 0.2464 - F1: 0.2598
sub_2:Test (Best Model) - Loss: 1.5334 - Accuracy: 0.2754 - F1: 0.3112
sub_2:Test (Best Model) - Loss: 1.3930 - Accuracy: 0.2647 - F1: 0.2844
sub_2:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.2353 - F1: 0.2503
sub_2:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.4118 - F1: 0.4435
sub_2:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3676 - F1: 0.3735
sub_2:Test (Best Model) - Loss: 1.3535 - Accuracy: 0.3235 - F1: 0.3580
sub_2:Test (Best Model) - Loss: 1.3677 - Accuracy: 0.3623 - F1: 0.3467
sub_2:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3333 - F1: 0.3410
sub_2:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.4058 - F1: 0.4194
sub_2:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.3478 - F1: 0.3335
sub_2:Test (Best Model) - Loss: 1.3156 - Accuracy: 0.3478 - F1: 0.3519
sub_3:Test (Best Model) - Loss: 1.4034 - Accuracy: 0.2794 - F1: 0.2792
sub_3:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3529 - F1: 0.3328
sub_3:Test (Best Model) - Loss: 1.4219 - Accuracy: 0.2794 - F1: 0.2773
sub_3:Test (Best Model) - Loss: 1.4205 - Accuracy: 0.2353 - F1: 0.2328
sub_3:Test (Best Model) - Loss: 1.3921 - Accuracy: 0.3382 - F1: 0.3307
sub_3:Test (Best Model) - Loss: 1.3806 - Accuracy: 0.3043 - F1: 0.2609
sub_3:Test (Best Model) - Loss: 1.4378 - Accuracy: 0.3043 - F1: 0.2942
sub_3:Test (Best Model) - Loss: 1.3727 - Accuracy: 0.2899 - F1: 0.2497
sub_3:Test (Best Model) - Loss: 1.3839 - Accuracy: 0.3623 - F1: 0.3415
sub_3:Test (Best Model) - Loss: 1.3504 - Accuracy: 0.3623 - F1: 0.3241
sub_3:Test (Best Model) - Loss: 1.4482 - Accuracy: 0.3333 - F1: 0.3120
sub_3:Test (Best Model) - Loss: 1.3746 - Accuracy: 0.3478 - F1: 0.3332
sub_3:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.2754 - F1: 0.2735
sub_3:Test (Best Model) - Loss: 1.4388 - Accuracy: 0.3043 - F1: 0.2825
sub_3:Test (Best Model) - Loss: 1.3851 - Accuracy: 0.3478 - F1: 0.3346
sub_4:Test (Best Model) - Loss: 1.0525 - Accuracy: 0.4928 - F1: 0.5120
sub_4:Test (Best Model) - Loss: 1.0178 - Accuracy: 0.4928 - F1: 0.5209
sub_4:Test (Best Model) - Loss: 1.0692 - Accuracy: 0.5072 - F1: 0.5319
sub_4:Test (Best Model) - Loss: 1.0007 - Accuracy: 0.5652 - F1: 0.5798
sub_4:Test (Best Model) - Loss: 1.0248 - Accuracy: 0.5797 - F1: 0.5879
sub_4:Test (Best Model) - Loss: 1.0259 - Accuracy: 0.5362 - F1: 0.5533
sub_4:Test (Best Model) - Loss: 1.0897 - Accuracy: 0.5362 - F1: 0.5558
sub_4:Test (Best Model) - Loss: 0.9934 - Accuracy: 0.6232 - F1: 0.6373
sub_4:Test (Best Model) - Loss: 1.0387 - Accuracy: 0.6087 - F1: 0.6121
sub_4:Test (Best Model) - Loss: 1.0031 - Accuracy: 0.5217 - F1: 0.5428
sub_4:Test (Best Model) - Loss: 1.1038 - Accuracy: 0.4638 - F1: 0.4344
sub_4:Test (Best Model) - Loss: 1.0854 - Accuracy: 0.4493 - F1: 0.4313
sub_4:Test (Best Model) - Loss: 1.0794 - Accuracy: 0.4348 - F1: 0.4549
sub_4:Test (Best Model) - Loss: 1.0871 - Accuracy: 0.4928 - F1: 0.4736
sub_4:Test (Best Model) - Loss: 1.0765 - Accuracy: 0.5072 - F1: 0.4871
sub_5:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.5000 - F1: 0.4766
sub_5:Test (Best Model) - Loss: 1.4533 - Accuracy: 0.4853 - F1: 0.4474
sub_5:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.4118 - F1: 0.3852
sub_5:Test (Best Model) - Loss: 1.4072 - Accuracy: 0.4118 - F1: 0.4006
sub_5:Test (Best Model) - Loss: 1.5234 - Accuracy: 0.3971 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 1.1143 - Accuracy: 0.4853 - F1: 0.4675
sub_5:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.5000 - F1: 0.4751
sub_5:Test (Best Model) - Loss: 1.0819 - Accuracy: 0.4853 - F1: 0.4979
sub_5:Test (Best Model) - Loss: 1.0839 - Accuracy: 0.4559 - F1: 0.4310
sub_5:Test (Best Model) - Loss: 1.1113 - Accuracy: 0.4412 - F1: 0.4271
sub_5:Test (Best Model) - Loss: 1.1086 - Accuracy: 0.4853 - F1: 0.4950
sub_5:Test (Best Model) - Loss: 1.1634 - Accuracy: 0.4706 - F1: 0.4580
sub_5:Test (Best Model) - Loss: 1.1665 - Accuracy: 0.3971 - F1: 0.3837
sub_5:Test (Best Model) - Loss: 1.1629 - Accuracy: 0.3382 - F1: 0.3275
sub_5:Test (Best Model) - Loss: 1.0709 - Accuracy: 0.4559 - F1: 0.4326
sub_6:Test (Best Model) - Loss: 1.1492 - Accuracy: 0.4706 - F1: 0.4950
sub_6:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.4412 - F1: 0.4632
sub_6:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.4265 - F1: 0.4371
sub_6:Test (Best Model) - Loss: 1.1457 - Accuracy: 0.5000 - F1: 0.5056
sub_6:Test (Best Model) - Loss: 1.1301 - Accuracy: 0.4412 - F1: 0.4592
sub_6:Test (Best Model) - Loss: 1.2331 - Accuracy: 0.4348 - F1: 0.3474
sub_6:Test (Best Model) - Loss: 1.2380 - Accuracy: 0.4638 - F1: 0.3928
sub_6:Test (Best Model) - Loss: 1.2257 - Accuracy: 0.4348 - F1: 0.3786
sub_6:Test (Best Model) - Loss: 1.2404 - Accuracy: 0.4493 - F1: 0.3925
sub_6:Test (Best Model) - Loss: 1.2215 - Accuracy: 0.4783 - F1: 0.4470
sub_6:Test (Best Model) - Loss: 1.2540 - Accuracy: 0.3478 - F1: 0.3720
sub_6:Test (Best Model) - Loss: 1.3385 - Accuracy: 0.4058 - F1: 0.4220
sub_6:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3913 - F1: 0.4102
sub_6:Test (Best Model) - Loss: 1.1965 - Accuracy: 0.4348 - F1: 0.4564
sub_6:Test (Best Model) - Loss: 1.1917 - Accuracy: 0.5072 - F1: 0.5363
sub_7:Test (Best Model) - Loss: 1.0332 - Accuracy: 0.5882 - F1: 0.5621
sub_7:Test (Best Model) - Loss: 1.0118 - Accuracy: 0.5882 - F1: 0.5772
sub_7:Test (Best Model) - Loss: 1.0599 - Accuracy: 0.4853 - F1: 0.4536
sub_7:Test (Best Model) - Loss: 0.9682 - Accuracy: 0.6765 - F1: 0.6658
sub_7:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.5441 - F1: 0.5136
sub_7:Test (Best Model) - Loss: 1.2485 - Accuracy: 0.3971 - F1: 0.3662
sub_7:Test (Best Model) - Loss: 1.2726 - Accuracy: 0.4265 - F1: 0.4178
sub_7:Test (Best Model) - Loss: 1.2009 - Accuracy: 0.4559 - F1: 0.4617
sub_7:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.4265 - F1: 0.4057
sub_7:Test (Best Model) - Loss: 1.1186 - Accuracy: 0.5000 - F1: 0.4655
sub_7:Test (Best Model) - Loss: 1.1384 - Accuracy: 0.5441 - F1: 0.5479
sub_7:Test (Best Model) - Loss: 1.1658 - Accuracy: 0.5147 - F1: 0.5081
sub_7:Test (Best Model) - Loss: 1.2112 - Accuracy: 0.5000 - F1: 0.4874
sub_7:Test (Best Model) - Loss: 1.1694 - Accuracy: 0.5147 - F1: 0.5265
sub_7:Test (Best Model) - Loss: 1.2031 - Accuracy: 0.4706 - F1: 0.4868
sub_8:Test (Best Model) - Loss: 1.5068 - Accuracy: 0.2353 - F1: 0.2380
sub_8:Test (Best Model) - Loss: 1.4598 - Accuracy: 0.2206 - F1: 0.2251
sub_8:Test (Best Model) - Loss: 1.4528 - Accuracy: 0.2794 - F1: 0.3126
sub_8:Test (Best Model) - Loss: 1.4187 - Accuracy: 0.3088 - F1: 0.3179
sub_8:Test (Best Model) - Loss: 1.4525 - Accuracy: 0.3088 - F1: 0.3173
sub_8:Test (Best Model) - Loss: 1.3191 - Accuracy: 0.3676 - F1: 0.3798
sub_8:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.3088 - F1: 0.3166
sub_8:Test (Best Model) - Loss: 1.3003 - Accuracy: 0.4265 - F1: 0.4443
sub_8:Test (Best Model) - Loss: 1.3454 - Accuracy: 0.3824 - F1: 0.3924
sub_8:Test (Best Model) - Loss: 1.3539 - Accuracy: 0.3088 - F1: 0.3253
sub_8:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.3529 - F1: 0.3527
sub_8:Test (Best Model) - Loss: 1.4135 - Accuracy: 0.3088 - F1: 0.3402
sub_8:Test (Best Model) - Loss: 1.4506 - Accuracy: 0.4559 - F1: 0.4920
sub_8:Test (Best Model) - Loss: 1.4028 - Accuracy: 0.4265 - F1: 0.4401
sub_8:Test (Best Model) - Loss: 1.3780 - Accuracy: 0.3382 - F1: 0.3428
sub_9:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.5441 - F1: 0.5677
sub_9:Test (Best Model) - Loss: 1.0716 - Accuracy: 0.5588 - F1: 0.5815
sub_9:Test (Best Model) - Loss: 1.0652 - Accuracy: 0.4412 - F1: 0.4690
sub_9:Test (Best Model) - Loss: 1.0752 - Accuracy: 0.5147 - F1: 0.5422
sub_9:Test (Best Model) - Loss: 1.0406 - Accuracy: 0.5588 - F1: 0.5804
sub_9:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.3235 - F1: 0.3359
sub_9:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.3529 - F1: 0.3710
sub_9:Test (Best Model) - Loss: 1.2324 - Accuracy: 0.3382 - F1: 0.3385
sub_9:Test (Best Model) - Loss: 1.2330 - Accuracy: 0.3676 - F1: 0.3890
sub_9:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.3529 - F1: 0.3853
sub_9:Test (Best Model) - Loss: 1.3500 - Accuracy: 0.3529 - F1: 0.3732
sub_9:Test (Best Model) - Loss: 1.2922 - Accuracy: 0.4265 - F1: 0.4426
sub_9:Test (Best Model) - Loss: 1.2532 - Accuracy: 0.4265 - F1: 0.4606
sub_9:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.3824 - F1: 0.4156
sub_9:Test (Best Model) - Loss: 1.2239 - Accuracy: 0.4118 - F1: 0.4378
sub_10:Test (Best Model) - Loss: 1.4011 - Accuracy: 0.2647 - F1: 0.2439
sub_10:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.3676 - F1: 0.3689
sub_10:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.2941 - F1: 0.3001
sub_10:Test (Best Model) - Loss: 1.3660 - Accuracy: 0.3088 - F1: 0.3233
sub_10:Test (Best Model) - Loss: 1.4197 - Accuracy: 0.3382 - F1: 0.3445
sub_10:Test (Best Model) - Loss: 1.3783 - Accuracy: 0.3088 - F1: 0.3067
sub_10:Test (Best Model) - Loss: 1.4293 - Accuracy: 0.2647 - F1: 0.2416
sub_10:Test (Best Model) - Loss: 1.4144 - Accuracy: 0.2647 - F1: 0.2547
sub_10:Test (Best Model) - Loss: 1.3634 - Accuracy: 0.3676 - F1: 0.3574
sub_10:Test (Best Model) - Loss: 1.4099 - Accuracy: 0.2941 - F1: 0.2975
sub_10:Test (Best Model) - Loss: 1.5183 - Accuracy: 0.3188 - F1: 0.3289
sub_10:Test (Best Model) - Loss: 1.4179 - Accuracy: 0.2754 - F1: 0.2861
sub_10:Test (Best Model) - Loss: 1.4166 - Accuracy: 0.3623 - F1: 0.3730
sub_10:Test (Best Model) - Loss: 1.3924 - Accuracy: 0.3043 - F1: 0.3013
sub_10:Test (Best Model) - Loss: 1.4279 - Accuracy: 0.2754 - F1: 0.2816
sub_11:Test (Best Model) - Loss: 1.3417 - Accuracy: 0.3478 - F1: 0.3373
sub_11:Test (Best Model) - Loss: 1.3401 - Accuracy: 0.3333 - F1: 0.3147
sub_11:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.3478 - F1: 0.3433
sub_11:Test (Best Model) - Loss: 1.3499 - Accuracy: 0.3333 - F1: 0.3263
sub_11:Test (Best Model) - Loss: 1.3826 - Accuracy: 0.3188 - F1: 0.3046
sub_11:Test (Best Model) - Loss: 1.2480 - Accuracy: 0.4638 - F1: 0.4279
sub_11:Test (Best Model) - Loss: 1.2732 - Accuracy: 0.4783 - F1: 0.4440
sub_11:Test (Best Model) - Loss: 1.2386 - Accuracy: 0.4493 - F1: 0.4347
sub_11:Test (Best Model) - Loss: 1.2963 - Accuracy: 0.4058 - F1: 0.3657
sub_11:Test (Best Model) - Loss: 1.2767 - Accuracy: 0.3768 - F1: 0.3358
sub_11:Test (Best Model) - Loss: 1.3179 - Accuracy: 0.3478 - F1: 0.2800
sub_11:Test (Best Model) - Loss: 1.3314 - Accuracy: 0.3478 - F1: 0.3091
sub_11:Test (Best Model) - Loss: 1.2095 - Accuracy: 0.4783 - F1: 0.4542
sub_11:Test (Best Model) - Loss: 1.2776 - Accuracy: 0.4203 - F1: 0.4200
sub_11:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.3768 - F1: 0.3517
sub_12:Test (Best Model) - Loss: 1.0065 - Accuracy: 0.5000 - F1: 0.4861
sub_12:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.5735 - F1: 0.5571
sub_12:Test (Best Model) - Loss: 1.0576 - Accuracy: 0.5294 - F1: 0.5089
sub_12:Test (Best Model) - Loss: 1.0714 - Accuracy: 0.5882 - F1: 0.6052
sub_12:Test (Best Model) - Loss: 1.0561 - Accuracy: 0.4853 - F1: 0.4985
sub_12:Test (Best Model) - Loss: 1.1617 - Accuracy: 0.4348 - F1: 0.4530
sub_12:Test (Best Model) - Loss: 1.0818 - Accuracy: 0.4783 - F1: 0.4916
sub_12:Test (Best Model) - Loss: 1.0588 - Accuracy: 0.5362 - F1: 0.5346
sub_12:Test (Best Model) - Loss: 1.0908 - Accuracy: 0.5507 - F1: 0.5623
sub_12:Test (Best Model) - Loss: 1.1534 - Accuracy: 0.5072 - F1: 0.5195
sub_12:Test (Best Model) - Loss: 1.1749 - Accuracy: 0.4706 - F1: 0.4701
sub_12:Test (Best Model) - Loss: 1.1994 - Accuracy: 0.4706 - F1: 0.4862
sub_12:Test (Best Model) - Loss: 1.1631 - Accuracy: 0.4559 - F1: 0.4712
sub_12:Test (Best Model) - Loss: 1.2014 - Accuracy: 0.4853 - F1: 0.4827
sub_12:Test (Best Model) - Loss: 1.1417 - Accuracy: 0.5147 - F1: 0.5288
sub_13:Test (Best Model) - Loss: 1.2880 - Accuracy: 0.4118 - F1: 0.4382
sub_13:Test (Best Model) - Loss: 1.2620 - Accuracy: 0.3529 - F1: 0.3611
sub_13:Test (Best Model) - Loss: 1.2425 - Accuracy: 0.3824 - F1: 0.4105
sub_13:Test (Best Model) - Loss: 1.2871 - Accuracy: 0.2941 - F1: 0.3323
sub_13:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.4265 - F1: 0.4279
sub_13:Test (Best Model) - Loss: 1.3308 - Accuracy: 0.4203 - F1: 0.4352
sub_13:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.3913 - F1: 0.3974
sub_13:Test (Best Model) - Loss: 1.3673 - Accuracy: 0.3333 - F1: 0.3237
sub_13:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.4348 - F1: 0.4439
sub_13:Test (Best Model) - Loss: 1.3125 - Accuracy: 0.4348 - F1: 0.4435
sub_13:Test (Best Model) - Loss: 1.3177 - Accuracy: 0.3529 - F1: 0.3716
sub_13:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3529 - F1: 0.3690
sub_13:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3529 - F1: 0.3779
sub_13:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.3676 - F1: 0.3845
sub_13:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.2794 - F1: 0.2988
sub_14:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.3529 - F1: 0.3764
sub_14:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.3824 - F1: 0.4159
sub_14:Test (Best Model) - Loss: 1.3222 - Accuracy: 0.3382 - F1: 0.3635
sub_14:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.2794 - F1: 0.2924
sub_14:Test (Best Model) - Loss: 1.3093 - Accuracy: 0.3676 - F1: 0.3798
sub_14:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.4118 - F1: 0.4258
sub_14:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.4412 - F1: 0.4581
sub_14:Test (Best Model) - Loss: 1.2970 - Accuracy: 0.4265 - F1: 0.4327
sub_14:Test (Best Model) - Loss: 1.3410 - Accuracy: 0.3235 - F1: 0.3313
sub_14:Test (Best Model) - Loss: 1.3052 - Accuracy: 0.3382 - F1: 0.3251
sub_14:Test (Best Model) - Loss: 1.2968 - Accuracy: 0.3971 - F1: 0.4157
sub_14:Test (Best Model) - Loss: 1.3029 - Accuracy: 0.3676 - F1: 0.3247
sub_14:Test (Best Model) - Loss: 1.2975 - Accuracy: 0.3676 - F1: 0.3781
sub_14:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.4412 - F1: 0.4340
sub_14:Test (Best Model) - Loss: 1.2514 - Accuracy: 0.3676 - F1: 0.3761
sub_15:Test (Best Model) - Loss: 1.2024 - Accuracy: 0.3824 - F1: 0.4115
sub_15:Test (Best Model) - Loss: 1.3377 - Accuracy: 0.3971 - F1: 0.4147
sub_15:Test (Best Model) - Loss: 1.2367 - Accuracy: 0.3971 - F1: 0.4154
sub_15:Test (Best Model) - Loss: 1.1934 - Accuracy: 0.3971 - F1: 0.4352
sub_15:Test (Best Model) - Loss: 1.2023 - Accuracy: 0.4706 - F1: 0.4991
sub_15:Test (Best Model) - Loss: 1.0113 - Accuracy: 0.5588 - F1: 0.5597
sub_15:Test (Best Model) - Loss: 1.1580 - Accuracy: 0.4706 - F1: 0.4845
sub_15:Test (Best Model) - Loss: 1.0383 - Accuracy: 0.5735 - F1: 0.5779
sub_15:Test (Best Model) - Loss: 1.0202 - Accuracy: 0.5735 - F1: 0.5874
sub_15:Test (Best Model) - Loss: 1.0816 - Accuracy: 0.5735 - F1: 0.5695
sub_15:Test (Best Model) - Loss: 1.1479 - Accuracy: 0.4853 - F1: 0.4778
sub_15:Test (Best Model) - Loss: 1.1216 - Accuracy: 0.4853 - F1: 0.4867
sub_15:Test (Best Model) - Loss: 1.1632 - Accuracy: 0.4412 - F1: 0.4389
sub_15:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.4412 - F1: 0.4232
sub_15:Test (Best Model) - Loss: 1.2121 - Accuracy: 0.4559 - F1: 0.4650
sub_16:Test (Best Model) - Loss: 1.1748 - Accuracy: 0.4706 - F1: 0.3901
sub_16:Test (Best Model) - Loss: 1.1242 - Accuracy: 0.5441 - F1: 0.5110
sub_16:Test (Best Model) - Loss: 1.1457 - Accuracy: 0.5000 - F1: 0.4600
sub_16:Test (Best Model) - Loss: 1.1841 - Accuracy: 0.5441 - F1: 0.5283
sub_16:Test (Best Model) - Loss: 1.0855 - Accuracy: 0.5735 - F1: 0.5227
sub_16:Test (Best Model) - Loss: 1.2498 - Accuracy: 0.3824 - F1: 0.3480
sub_16:Test (Best Model) - Loss: 1.2618 - Accuracy: 0.3382 - F1: 0.3175
sub_16:Test (Best Model) - Loss: 1.2718 - Accuracy: 0.4412 - F1: 0.4058
sub_16:Test (Best Model) - Loss: 1.2098 - Accuracy: 0.4853 - F1: 0.4690
sub_16:Test (Best Model) - Loss: 1.4792 - Accuracy: 0.4118 - F1: 0.3934
sub_16:Test (Best Model) - Loss: 1.1830 - Accuracy: 0.5294 - F1: 0.4576
sub_16:Test (Best Model) - Loss: 1.1100 - Accuracy: 0.5882 - F1: 0.4987
sub_16:Test (Best Model) - Loss: 1.0956 - Accuracy: 0.5147 - F1: 0.4690
sub_16:Test (Best Model) - Loss: 1.1760 - Accuracy: 0.5000 - F1: 0.4604
sub_16:Test (Best Model) - Loss: 1.1666 - Accuracy: 0.4853 - F1: 0.4179
sub_17:Test (Best Model) - Loss: 1.2268 - Accuracy: 0.4348 - F1: 0.3886
sub_17:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4058 - F1: 0.3599
sub_17:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.3913 - F1: 0.3573
sub_17:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.4348 - F1: 0.4350
sub_17:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.3913 - F1: 0.3666
sub_17:Test (Best Model) - Loss: 1.4489 - Accuracy: 0.4058 - F1: 0.3601
sub_17:Test (Best Model) - Loss: 1.4975 - Accuracy: 0.3768 - F1: 0.3359
sub_17:Test (Best Model) - Loss: 1.4437 - Accuracy: 0.4203 - F1: 0.3607
sub_17:Test (Best Model) - Loss: 1.4718 - Accuracy: 0.4638 - F1: 0.4042
sub_17:Test (Best Model) - Loss: 1.5154 - Accuracy: 0.3913 - F1: 0.3312
sub_17:Test (Best Model) - Loss: 1.2220 - Accuracy: 0.4559 - F1: 0.4397
sub_17:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.4706 - F1: 0.4666
sub_17:Test (Best Model) - Loss: 1.2282 - Accuracy: 0.4412 - F1: 0.4329
sub_17:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.4706 - F1: 0.4777
sub_17:Test (Best Model) - Loss: 1.2526 - Accuracy: 0.4118 - F1: 0.4127
sub_18:Test (Best Model) - Loss: 1.2136 - Accuracy: 0.3478 - F1: 0.3745
sub_18:Test (Best Model) - Loss: 1.2239 - Accuracy: 0.3478 - F1: 0.3653
sub_18:Test (Best Model) - Loss: 1.1972 - Accuracy: 0.4203 - F1: 0.4109
sub_18:Test (Best Model) - Loss: 1.2520 - Accuracy: 0.4203 - F1: 0.4400
sub_18:Test (Best Model) - Loss: 1.2205 - Accuracy: 0.3913 - F1: 0.4258
sub_18:Test (Best Model) - Loss: 1.3569 - Accuracy: 0.3235 - F1: 0.3463
sub_18:Test (Best Model) - Loss: 1.3129 - Accuracy: 0.3529 - F1: 0.3684
sub_18:Test (Best Model) - Loss: 1.3725 - Accuracy: 0.2941 - F1: 0.3259
sub_18:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3088 - F1: 0.3453
sub_18:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.3529 - F1: 0.3812
sub_18:Test (Best Model) - Loss: 1.2436 - Accuracy: 0.3971 - F1: 0.4279
sub_18:Test (Best Model) - Loss: 1.2997 - Accuracy: 0.3382 - F1: 0.3479
sub_18:Test (Best Model) - Loss: 1.3099 - Accuracy: 0.3382 - F1: 0.3518
sub_18:Test (Best Model) - Loss: 1.2373 - Accuracy: 0.3676 - F1: 0.3845
sub_18:Test (Best Model) - Loss: 1.2273 - Accuracy: 0.3529 - F1: 0.3966
sub_19:Test (Best Model) - Loss: 1.5436 - Accuracy: 0.1912 - F1: 0.1909
sub_19:Test (Best Model) - Loss: 1.4429 - Accuracy: 0.2500 - F1: 0.2404
sub_19:Test (Best Model) - Loss: 1.4847 - Accuracy: 0.2353 - F1: 0.2587
sub_19:Test (Best Model) - Loss: 1.4176 - Accuracy: 0.2647 - F1: 0.2658
sub_19:Test (Best Model) - Loss: 1.4530 - Accuracy: 0.2941 - F1: 0.3160
sub_19:Test (Best Model) - Loss: 1.2358 - Accuracy: 0.3971 - F1: 0.3675
sub_19:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.4412 - F1: 0.3960
sub_19:Test (Best Model) - Loss: 1.2454 - Accuracy: 0.4853 - F1: 0.5017
sub_19:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.5147 - F1: 0.4998
sub_19:Test (Best Model) - Loss: 1.2098 - Accuracy: 0.5000 - F1: 0.4987
sub_19:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.3824 - F1: 0.3633
sub_19:Test (Best Model) - Loss: 1.4066 - Accuracy: 0.3382 - F1: 0.3396
sub_19:Test (Best Model) - Loss: 1.2475 - Accuracy: 0.3971 - F1: 0.3840
sub_19:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3088 - F1: 0.3221
sub_19:Test (Best Model) - Loss: 1.2485 - Accuracy: 0.3676 - F1: 0.3523
sub_20:Test (Best Model) - Loss: 1.1107 - Accuracy: 0.5882 - F1: 0.6093
sub_20:Test (Best Model) - Loss: 1.0905 - Accuracy: 0.5441 - F1: 0.5625
sub_20:Test (Best Model) - Loss: 1.0940 - Accuracy: 0.5588 - F1: 0.5789
sub_20:Test (Best Model) - Loss: 1.1014 - Accuracy: 0.5294 - F1: 0.5369
sub_20:Test (Best Model) - Loss: 1.1364 - Accuracy: 0.5735 - F1: 0.5944
sub_20:Test (Best Model) - Loss: 1.2160 - Accuracy: 0.4265 - F1: 0.4139
sub_20:Test (Best Model) - Loss: 1.1604 - Accuracy: 0.4853 - F1: 0.4963
sub_20:Test (Best Model) - Loss: 1.2157 - Accuracy: 0.4412 - F1: 0.4643
sub_20:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.3971 - F1: 0.3808
sub_20:Test (Best Model) - Loss: 1.2284 - Accuracy: 0.4265 - F1: 0.4392
sub_20:Test (Best Model) - Loss: 1.1947 - Accuracy: 0.4203 - F1: 0.4349
sub_20:Test (Best Model) - Loss: 1.2071 - Accuracy: 0.4348 - F1: 0.4497
sub_20:Test (Best Model) - Loss: 1.2569 - Accuracy: 0.3478 - F1: 0.3738
sub_20:Test (Best Model) - Loss: 1.1599 - Accuracy: 0.4783 - F1: 0.4870
sub_20:Test (Best Model) - Loss: 1.1276 - Accuracy: 0.5072 - F1: 0.5209
sub_21:Test (Best Model) - Loss: 1.1666 - Accuracy: 0.4265 - F1: 0.3854
sub_21:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.4118 - F1: 0.3693
sub_21:Test (Best Model) - Loss: 1.2685 - Accuracy: 0.4118 - F1: 0.3822
sub_21:Test (Best Model) - Loss: 1.2659 - Accuracy: 0.4118 - F1: 0.3838
sub_21:Test (Best Model) - Loss: 1.2879 - Accuracy: 0.3971 - F1: 0.3804
sub_21:Test (Best Model) - Loss: 1.2257 - Accuracy: 0.3235 - F1: 0.3078
sub_21:Test (Best Model) - Loss: 1.1297 - Accuracy: 0.4559 - F1: 0.4345
sub_21:Test (Best Model) - Loss: 1.1286 - Accuracy: 0.3235 - F1: 0.2992
sub_21:Test (Best Model) - Loss: 1.1818 - Accuracy: 0.4118 - F1: 0.3841
sub_21:Test (Best Model) - Loss: 1.0948 - Accuracy: 0.4559 - F1: 0.4140
sub_21:Test (Best Model) - Loss: 1.1573 - Accuracy: 0.4118 - F1: 0.3956
sub_21:Test (Best Model) - Loss: 1.1670 - Accuracy: 0.3824 - F1: 0.3776
sub_21:Test (Best Model) - Loss: 1.1658 - Accuracy: 0.4265 - F1: 0.3726
sub_21:Test (Best Model) - Loss: 1.1621 - Accuracy: 0.4265 - F1: 0.4052
sub_21:Test (Best Model) - Loss: 1.1752 - Accuracy: 0.4265 - F1: 0.3983
sub_22:Test (Best Model) - Loss: 1.3247 - Accuracy: 0.3529 - F1: 0.3848
sub_22:Test (Best Model) - Loss: 1.3200 - Accuracy: 0.3971 - F1: 0.3946
sub_22:Test (Best Model) - Loss: 1.3487 - Accuracy: 0.3382 - F1: 0.3622
sub_22:Test (Best Model) - Loss: 1.2984 - Accuracy: 0.4853 - F1: 0.4988
sub_22:Test (Best Model) - Loss: 1.3507 - Accuracy: 0.3676 - F1: 0.4087
sub_22:Test (Best Model) - Loss: 1.3131 - Accuracy: 0.3478 - F1: 0.3030
sub_22:Test (Best Model) - Loss: 1.2554 - Accuracy: 0.4493 - F1: 0.4299
sub_22:Test (Best Model) - Loss: 1.2631 - Accuracy: 0.3913 - F1: 0.3793
sub_22:Test (Best Model) - Loss: 1.2847 - Accuracy: 0.3623 - F1: 0.3592
sub_22:Test (Best Model) - Loss: 1.2673 - Accuracy: 0.3623 - F1: 0.3615
sub_22:Test (Best Model) - Loss: 1.3060 - Accuracy: 0.3676 - F1: 0.4020
sub_22:Test (Best Model) - Loss: 1.2211 - Accuracy: 0.3676 - F1: 0.3965
sub_22:Test (Best Model) - Loss: 1.2900 - Accuracy: 0.3824 - F1: 0.3935
sub_22:Test (Best Model) - Loss: 1.2523 - Accuracy: 0.3824 - F1: 0.4056
sub_22:Test (Best Model) - Loss: 1.2561 - Accuracy: 0.4412 - F1: 0.4791
sub_23:Test (Best Model) - Loss: 1.1669 - Accuracy: 0.4058 - F1: 0.4187
sub_23:Test (Best Model) - Loss: 1.1068 - Accuracy: 0.4203 - F1: 0.4433
sub_23:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.3768 - F1: 0.3948
sub_23:Test (Best Model) - Loss: 1.0611 - Accuracy: 0.5652 - F1: 0.5869
sub_23:Test (Best Model) - Loss: 1.0753 - Accuracy: 0.4493 - F1: 0.4649
sub_23:Test (Best Model) - Loss: 1.1615 - Accuracy: 0.4853 - F1: 0.4614
sub_23:Test (Best Model) - Loss: 1.0970 - Accuracy: 0.5147 - F1: 0.5196
sub_23:Test (Best Model) - Loss: 1.1130 - Accuracy: 0.5147 - F1: 0.5058
sub_23:Test (Best Model) - Loss: 1.0870 - Accuracy: 0.5147 - F1: 0.5117
sub_23:Test (Best Model) - Loss: 1.1388 - Accuracy: 0.5294 - F1: 0.5177
sub_23:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.3913 - F1: 0.4028
sub_23:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.4203 - F1: 0.4110
sub_23:Test (Best Model) - Loss: 1.1932 - Accuracy: 0.4348 - F1: 0.4307
sub_23:Test (Best Model) - Loss: 1.1701 - Accuracy: 0.4783 - F1: 0.4903
sub_23:Test (Best Model) - Loss: 1.1930 - Accuracy: 0.3768 - F1: 0.3820
sub_24:Test (Best Model) - Loss: 1.3990 - Accuracy: 0.3382 - F1: 0.3279
sub_24:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3971 - F1: 0.3823
sub_24:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.2794 - F1: 0.2836
sub_24:Test (Best Model) - Loss: 1.4469 - Accuracy: 0.2647 - F1: 0.2603
sub_24:Test (Best Model) - Loss: 1.4069 - Accuracy: 0.1765 - F1: 0.1755
sub_24:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.2794 - F1: 0.2752
sub_24:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3235 - F1: 0.3303
sub_24:Test (Best Model) - Loss: 1.3397 - Accuracy: 0.3235 - F1: 0.3173
sub_24:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.4118 - F1: 0.4151
sub_24:Test (Best Model) - Loss: 1.3320 - Accuracy: 0.3676 - F1: 0.3667
sub_24:Test (Best Model) - Loss: 1.4428 - Accuracy: 0.2500 - F1: 0.2497
sub_24:Test (Best Model) - Loss: 1.4769 - Accuracy: 0.2500 - F1: 0.2434
sub_24:Test (Best Model) - Loss: 1.4359 - Accuracy: 0.2353 - F1: 0.2267
sub_24:Test (Best Model) - Loss: 1.4222 - Accuracy: 0.3235 - F1: 0.3267
sub_24:Test (Best Model) - Loss: 1.4078 - Accuracy: 0.2794 - F1: 0.2789
sub_25:Test (Best Model) - Loss: 1.1687 - Accuracy: 0.4783 - F1: 0.4376
sub_25:Test (Best Model) - Loss: 1.2250 - Accuracy: 0.4203 - F1: 0.3701
sub_25:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.4058 - F1: 0.3777
sub_25:Test (Best Model) - Loss: 1.2062 - Accuracy: 0.4058 - F1: 0.3264
sub_25:Test (Best Model) - Loss: 1.2349 - Accuracy: 0.4493 - F1: 0.4200
sub_25:Test (Best Model) - Loss: 1.2691 - Accuracy: 0.4265 - F1: 0.3640
sub_25:Test (Best Model) - Loss: 1.2529 - Accuracy: 0.4853 - F1: 0.4112
sub_25:Test (Best Model) - Loss: 1.2495 - Accuracy: 0.4559 - F1: 0.4071
sub_25:Test (Best Model) - Loss: 1.2289 - Accuracy: 0.5000 - F1: 0.4419
sub_25:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.5147 - F1: 0.4601
sub_25:Test (Best Model) - Loss: 1.2171 - Accuracy: 0.4853 - F1: 0.4629
sub_25:Test (Best Model) - Loss: 1.2404 - Accuracy: 0.4118 - F1: 0.3836
sub_25:Test (Best Model) - Loss: 1.2012 - Accuracy: 0.4265 - F1: 0.3980
sub_25:Test (Best Model) - Loss: 1.2459 - Accuracy: 0.3676 - F1: 0.3447
sub_25:Test (Best Model) - Loss: 1.2271 - Accuracy: 0.4412 - F1: 0.4027
sub_26:Test (Best Model) - Loss: 1.1068 - Accuracy: 0.4638 - F1: 0.4816
sub_26:Test (Best Model) - Loss: 1.1704 - Accuracy: 0.4783 - F1: 0.4780
sub_26:Test (Best Model) - Loss: 1.1280 - Accuracy: 0.4928 - F1: 0.5115
sub_26:Test (Best Model) - Loss: 1.0757 - Accuracy: 0.5652 - F1: 0.5719
sub_26:Test (Best Model) - Loss: 1.0933 - Accuracy: 0.5072 - F1: 0.5245
sub_26:Test (Best Model) - Loss: 1.2509 - Accuracy: 0.3971 - F1: 0.4277
sub_26:Test (Best Model) - Loss: 1.2201 - Accuracy: 0.3824 - F1: 0.3783
sub_26:Test (Best Model) - Loss: 1.2011 - Accuracy: 0.3971 - F1: 0.3946
sub_26:Test (Best Model) - Loss: 1.2099 - Accuracy: 0.4118 - F1: 0.4248
sub_26:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.3971 - F1: 0.4305
sub_26:Test (Best Model) - Loss: 1.1350 - Accuracy: 0.5735 - F1: 0.6062
sub_26:Test (Best Model) - Loss: 1.2134 - Accuracy: 0.5294 - F1: 0.5484
sub_26:Test (Best Model) - Loss: 1.1683 - Accuracy: 0.5588 - F1: 0.5825
sub_26:Test (Best Model) - Loss: 1.1428 - Accuracy: 0.5735 - F1: 0.5930
sub_26:Test (Best Model) - Loss: 1.1895 - Accuracy: 0.5294 - F1: 0.5590
sub_27:Test (Best Model) - Loss: 1.2268 - Accuracy: 0.4348 - F1: 0.3886
sub_27:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4058 - F1: 0.3599
sub_27:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.3913 - F1: 0.3573
sub_27:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.4348 - F1: 0.4350
sub_27:Test (Best Model) - Loss: 1.1978 - Accuracy: 0.3913 - F1: 0.3666
sub_27:Test (Best Model) - Loss: 1.4489 - Accuracy: 0.4058 - F1: 0.3601
sub_27:Test (Best Model) - Loss: 1.4975 - Accuracy: 0.3768 - F1: 0.3359
sub_27:Test (Best Model) - Loss: 1.4437 - Accuracy: 0.4203 - F1: 0.3607
sub_27:Test (Best Model) - Loss: 1.4718 - Accuracy: 0.4638 - F1: 0.4042
sub_27:Test (Best Model) - Loss: 1.5154 - Accuracy: 0.3913 - F1: 0.3312
sub_27:Test (Best Model) - Loss: 1.2220 - Accuracy: 0.4559 - F1: 0.4397
sub_27:Test (Best Model) - Loss: 1.2186 - Accuracy: 0.4706 - F1: 0.4666
sub_27:Test (Best Model) - Loss: 1.2282 - Accuracy: 0.4412 - F1: 0.4329
sub_27:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.4706 - F1: 0.4777
sub_27:Test (Best Model) - Loss: 1.2526 - Accuracy: 0.4118 - F1: 0.4127
sub_28:Test (Best Model) - Loss: 1.3575 - Accuracy: 0.3529 - F1: 0.3450
sub_28:Test (Best Model) - Loss: 1.3920 - Accuracy: 0.2941 - F1: 0.2496
sub_28:Test (Best Model) - Loss: 1.5062 - Accuracy: 0.3235 - F1: 0.3214
sub_28:Test (Best Model) - Loss: 1.4732 - Accuracy: 0.2941 - F1: 0.3087
sub_28:Test (Best Model) - Loss: 1.5459 - Accuracy: 0.2941 - F1: 0.3034
sub_28:Test (Best Model) - Loss: 1.6797 - Accuracy: 0.2500 - F1: 0.2210
sub_28:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2941 - F1: 0.2606
sub_28:Test (Best Model) - Loss: 1.6812 - Accuracy: 0.2794 - F1: 0.2423
sub_28:Test (Best Model) - Loss: 1.8191 - Accuracy: 0.2500 - F1: 0.2201
sub_28:Test (Best Model) - Loss: 1.6873 - Accuracy: 0.2647 - F1: 0.2303
sub_28:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.3971 - F1: 0.3290
sub_28:Test (Best Model) - Loss: 1.2594 - Accuracy: 0.4265 - F1: 0.3671
sub_28:Test (Best Model) - Loss: 1.2514 - Accuracy: 0.5147 - F1: 0.4629
sub_28:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.4706 - F1: 0.4386
sub_28:Test (Best Model) - Loss: 1.2541 - Accuracy: 0.5294 - F1: 0.4918
sub_29:Test (Best Model) - Loss: 1.1413 - Accuracy: 0.5000 - F1: 0.5133
sub_29:Test (Best Model) - Loss: 1.0504 - Accuracy: 0.5588 - F1: 0.5648
sub_29:Test (Best Model) - Loss: 0.9889 - Accuracy: 0.5735 - F1: 0.5806
sub_29:Test (Best Model) - Loss: 1.0806 - Accuracy: 0.5147 - F1: 0.5173
sub_29:Test (Best Model) - Loss: 1.0741 - Accuracy: 0.6029 - F1: 0.5920
sub_29:Test (Best Model) - Loss: 0.9589 - Accuracy: 0.5882 - F1: 0.6090
sub_29:Test (Best Model) - Loss: 0.9402 - Accuracy: 0.5882 - F1: 0.6086
sub_29:Test (Best Model) - Loss: 0.9392 - Accuracy: 0.5735 - F1: 0.5867
sub_29:Test (Best Model) - Loss: 0.9213 - Accuracy: 0.6471 - F1: 0.6675
sub_29:Test (Best Model) - Loss: 0.9238 - Accuracy: 0.5882 - F1: 0.6136
sub_29:Test (Best Model) - Loss: 0.9562 - Accuracy: 0.5362 - F1: 0.5608
sub_29:Test (Best Model) - Loss: 0.9675 - Accuracy: 0.5217 - F1: 0.5445
sub_29:Test (Best Model) - Loss: 0.9889 - Accuracy: 0.5362 - F1: 0.5590
sub_29:Test (Best Model) - Loss: 0.9037 - Accuracy: 0.6377 - F1: 0.6506
sub_29:Test (Best Model) - Loss: 0.9459 - Accuracy: 0.5652 - F1: 0.5802

=== Summary Results ===

acc: 41.75 ± 7.04
F1: 41.40 ± 7.31
acc-in: 50.65 ± 6.32
F1-in: 49.20 ± 6.42
