lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.5947 - Accuracy: 0.5588 - F1: 0.5771
sub_1:Test (Best Model) - Loss: 2.4320 - Accuracy: 0.4853 - F1: 0.4873
sub_1:Test (Best Model) - Loss: 1.9587 - Accuracy: 0.4265 - F1: 0.4656
sub_1:Test (Best Model) - Loss: 1.8246 - Accuracy: 0.5147 - F1: 0.5538
sub_1:Test (Best Model) - Loss: 1.7158 - Accuracy: 0.5147 - F1: 0.5574
sub_1:Test (Best Model) - Loss: 2.8324 - Accuracy: 0.4928 - F1: 0.4389
sub_1:Test (Best Model) - Loss: 2.0274 - Accuracy: 0.4348 - F1: 0.4186
sub_1:Test (Best Model) - Loss: 2.5570 - Accuracy: 0.4203 - F1: 0.4201
sub_1:Test (Best Model) - Loss: 2.4674 - Accuracy: 0.4348 - F1: 0.4128
sub_1:Test (Best Model) - Loss: 2.2016 - Accuracy: 0.4928 - F1: 0.4678
sub_1:Test (Best Model) - Loss: 2.1134 - Accuracy: 0.5147 - F1: 0.4890
sub_1:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.5735 - F1: 0.5640
sub_1:Test (Best Model) - Loss: 1.7506 - Accuracy: 0.5735 - F1: 0.5608
sub_1:Test (Best Model) - Loss: 2.0826 - Accuracy: 0.4412 - F1: 0.4436
sub_1:Test (Best Model) - Loss: 2.1213 - Accuracy: 0.5294 - F1: 0.4946
sub_2:Test (Best Model) - Loss: 2.2890 - Accuracy: 0.3043 - F1: 0.3160
sub_2:Test (Best Model) - Loss: 2.7761 - Accuracy: 0.3768 - F1: 0.3815
sub_2:Test (Best Model) - Loss: 3.3795 - Accuracy: 0.3188 - F1: 0.3378
sub_2:Test (Best Model) - Loss: 3.0552 - Accuracy: 0.3188 - F1: 0.3587
sub_2:Test (Best Model) - Loss: 3.5190 - Accuracy: 0.2609 - F1: 0.2915
sub_2:Test (Best Model) - Loss: 1.8734 - Accuracy: 0.3088 - F1: 0.2994
sub_2:Test (Best Model) - Loss: 1.7229 - Accuracy: 0.3088 - F1: 0.3195
sub_2:Test (Best Model) - Loss: 1.7286 - Accuracy: 0.3529 - F1: 0.3541
sub_2:Test (Best Model) - Loss: 2.1027 - Accuracy: 0.4118 - F1: 0.3968
sub_2:Test (Best Model) - Loss: 1.9455 - Accuracy: 0.3971 - F1: 0.3687
sub_2:Test (Best Model) - Loss: 2.3987 - Accuracy: 0.4493 - F1: 0.4242
sub_2:Test (Best Model) - Loss: 2.4792 - Accuracy: 0.3333 - F1: 0.3183
sub_2:Test (Best Model) - Loss: 1.7258 - Accuracy: 0.4928 - F1: 0.4790
sub_2:Test (Best Model) - Loss: 2.2113 - Accuracy: 0.3768 - F1: 0.3720
sub_2:Test (Best Model) - Loss: 2.5648 - Accuracy: 0.3913 - F1: 0.3856
sub_3:Test (Best Model) - Loss: 3.3784 - Accuracy: 0.3382 - F1: 0.3370
sub_3:Test (Best Model) - Loss: 2.5242 - Accuracy: 0.2941 - F1: 0.2842
sub_3:Test (Best Model) - Loss: 2.7198 - Accuracy: 0.3971 - F1: 0.3799
sub_3:Test (Best Model) - Loss: 3.5285 - Accuracy: 0.3235 - F1: 0.3073
sub_3:Test (Best Model) - Loss: 2.9349 - Accuracy: 0.2647 - F1: 0.2574
sub_3:Test (Best Model) - Loss: 1.9769 - Accuracy: 0.4348 - F1: 0.4047
sub_3:Test (Best Model) - Loss: 3.1022 - Accuracy: 0.2029 - F1: 0.1933
sub_3:Test (Best Model) - Loss: 3.1599 - Accuracy: 0.3043 - F1: 0.2578
sub_3:Test (Best Model) - Loss: 2.6754 - Accuracy: 0.2899 - F1: 0.2316
sub_3:Test (Best Model) - Loss: 2.7214 - Accuracy: 0.3043 - F1: 0.2852
sub_3:Test (Best Model) - Loss: 3.6141 - Accuracy: 0.3188 - F1: 0.3077
sub_3:Test (Best Model) - Loss: 3.0958 - Accuracy: 0.4203 - F1: 0.3605
sub_3:Test (Best Model) - Loss: 4.1912 - Accuracy: 0.2029 - F1: 0.1792
sub_3:Test (Best Model) - Loss: 3.4223 - Accuracy: 0.3623 - F1: 0.3459
sub_3:Test (Best Model) - Loss: 3.6460 - Accuracy: 0.4058 - F1: 0.3972
sub_4:Test (Best Model) - Loss: 2.4482 - Accuracy: 0.5362 - F1: 0.5453
sub_4:Test (Best Model) - Loss: 1.9993 - Accuracy: 0.4928 - F1: 0.4964
sub_4:Test (Best Model) - Loss: 2.9019 - Accuracy: 0.5797 - F1: 0.5897
sub_4:Test (Best Model) - Loss: 2.1248 - Accuracy: 0.5217 - F1: 0.5400
sub_4:Test (Best Model) - Loss: 3.1121 - Accuracy: 0.5362 - F1: 0.5483
sub_4:Test (Best Model) - Loss: 2.1100 - Accuracy: 0.3478 - F1: 0.3543
sub_4:Test (Best Model) - Loss: 2.5590 - Accuracy: 0.5217 - F1: 0.5482
sub_4:Test (Best Model) - Loss: 2.0357 - Accuracy: 0.5362 - F1: 0.5614
sub_4:Test (Best Model) - Loss: 2.1816 - Accuracy: 0.4928 - F1: 0.5136
sub_4:Test (Best Model) - Loss: 2.7286 - Accuracy: 0.4493 - F1: 0.4720
sub_4:Test (Best Model) - Loss: 4.0840 - Accuracy: 0.3913 - F1: 0.3381
sub_4:Test (Best Model) - Loss: 3.5665 - Accuracy: 0.4493 - F1: 0.4002
sub_4:Test (Best Model) - Loss: 2.7165 - Accuracy: 0.3623 - F1: 0.3352
sub_4:Test (Best Model) - Loss: 3.1324 - Accuracy: 0.4203 - F1: 0.3975
sub_4:Test (Best Model) - Loss: 2.2576 - Accuracy: 0.5072 - F1: 0.4828
sub_5:Test (Best Model) - Loss: 4.2227 - Accuracy: 0.5735 - F1: 0.5413
sub_5:Test (Best Model) - Loss: 5.7496 - Accuracy: 0.4559 - F1: 0.4226
sub_5:Test (Best Model) - Loss: 5.6281 - Accuracy: 0.3676 - F1: 0.3572
sub_5:Test (Best Model) - Loss: 4.6644 - Accuracy: 0.4559 - F1: 0.4417
sub_5:Test (Best Model) - Loss: 4.5067 - Accuracy: 0.4265 - F1: 0.3804
sub_5:Test (Best Model) - Loss: 1.7884 - Accuracy: 0.4118 - F1: 0.3344
sub_5:Test (Best Model) - Loss: 3.4478 - Accuracy: 0.5588 - F1: 0.5177
sub_5:Test (Best Model) - Loss: 1.8330 - Accuracy: 0.5294 - F1: 0.4992
sub_5:Test (Best Model) - Loss: 1.9490 - Accuracy: 0.5441 - F1: 0.5113
sub_5:Test (Best Model) - Loss: 2.5011 - Accuracy: 0.4559 - F1: 0.4283
sub_5:Test (Best Model) - Loss: 3.1915 - Accuracy: 0.4265 - F1: 0.4077
sub_5:Test (Best Model) - Loss: 3.0802 - Accuracy: 0.3088 - F1: 0.2596
sub_5:Test (Best Model) - Loss: 3.3730 - Accuracy: 0.3235 - F1: 0.3338
sub_5:Test (Best Model) - Loss: 2.1987 - Accuracy: 0.3676 - F1: 0.3794
sub_5:Test (Best Model) - Loss: 2.2832 - Accuracy: 0.3971 - F1: 0.3972
sub_6:Test (Best Model) - Loss: 1.8411 - Accuracy: 0.4559 - F1: 0.4675
sub_6:Test (Best Model) - Loss: 1.6732 - Accuracy: 0.5294 - F1: 0.5275
sub_6:Test (Best Model) - Loss: 1.8002 - Accuracy: 0.4706 - F1: 0.4655
sub_6:Test (Best Model) - Loss: 1.6758 - Accuracy: 0.4706 - F1: 0.4873
sub_6:Test (Best Model) - Loss: 1.8173 - Accuracy: 0.5882 - F1: 0.6026
sub_6:Test (Best Model) - Loss: 1.9822 - Accuracy: 0.4783 - F1: 0.4610
sub_6:Test (Best Model) - Loss: 1.8561 - Accuracy: 0.4348 - F1: 0.4034
sub_6:Test (Best Model) - Loss: 2.5585 - Accuracy: 0.4493 - F1: 0.3912
sub_6:Test (Best Model) - Loss: 2.1036 - Accuracy: 0.4203 - F1: 0.3687
sub_6:Test (Best Model) - Loss: 1.7447 - Accuracy: 0.4928 - F1: 0.4558
sub_6:Test (Best Model) - Loss: 2.0898 - Accuracy: 0.3623 - F1: 0.3817
sub_6:Test (Best Model) - Loss: 2.4794 - Accuracy: 0.4493 - F1: 0.4462
sub_6:Test (Best Model) - Loss: 1.8214 - Accuracy: 0.4783 - F1: 0.4844
sub_6:Test (Best Model) - Loss: 2.0998 - Accuracy: 0.4783 - F1: 0.4733
sub_6:Test (Best Model) - Loss: 2.1727 - Accuracy: 0.5217 - F1: 0.5386
sub_7:Test (Best Model) - Loss: 1.1952 - Accuracy: 0.6471 - F1: 0.6367
sub_7:Test (Best Model) - Loss: 1.2908 - Accuracy: 0.5441 - F1: 0.5233
sub_7:Test (Best Model) - Loss: 1.7538 - Accuracy: 0.5441 - F1: 0.5248
sub_7:Test (Best Model) - Loss: 1.1579 - Accuracy: 0.6324 - F1: 0.6130
sub_7:Test (Best Model) - Loss: 1.8528 - Accuracy: 0.6176 - F1: 0.5848
sub_7:Test (Best Model) - Loss: 2.4453 - Accuracy: 0.4265 - F1: 0.3778
sub_7:Test (Best Model) - Loss: 3.0945 - Accuracy: 0.3088 - F1: 0.2906
sub_7:Test (Best Model) - Loss: 2.5989 - Accuracy: 0.5000 - F1: 0.4806
sub_7:Test (Best Model) - Loss: 2.8463 - Accuracy: 0.4559 - F1: 0.4431
sub_7:Test (Best Model) - Loss: 2.5988 - Accuracy: 0.4853 - F1: 0.4340
sub_7:Test (Best Model) - Loss: 2.3346 - Accuracy: 0.3824 - F1: 0.3638
sub_7:Test (Best Model) - Loss: 1.7901 - Accuracy: 0.6029 - F1: 0.5956
sub_7:Test (Best Model) - Loss: 1.8285 - Accuracy: 0.4559 - F1: 0.4395
sub_7:Test (Best Model) - Loss: 2.2440 - Accuracy: 0.4706 - F1: 0.4626
sub_7:Test (Best Model) - Loss: 2.0479 - Accuracy: 0.3676 - F1: 0.3673
sub_8:Test (Best Model) - Loss: 3.1472 - Accuracy: 0.3088 - F1: 0.3114
sub_8:Test (Best Model) - Loss: 3.3132 - Accuracy: 0.2206 - F1: 0.2202
sub_8:Test (Best Model) - Loss: 3.2139 - Accuracy: 0.2500 - F1: 0.2679
sub_8:Test (Best Model) - Loss: 2.8183 - Accuracy: 0.3235 - F1: 0.3312
sub_8:Test (Best Model) - Loss: 3.1458 - Accuracy: 0.2794 - F1: 0.2855
sub_8:Test (Best Model) - Loss: 2.3420 - Accuracy: 0.3529 - F1: 0.3107
sub_8:Test (Best Model) - Loss: 2.3002 - Accuracy: 0.3382 - F1: 0.3453
sub_8:Test (Best Model) - Loss: 1.9446 - Accuracy: 0.4559 - F1: 0.4680
sub_8:Test (Best Model) - Loss: 2.9310 - Accuracy: 0.2647 - F1: 0.2749
sub_8:Test (Best Model) - Loss: 2.4489 - Accuracy: 0.2941 - F1: 0.2893
sub_8:Test (Best Model) - Loss: 3.3109 - Accuracy: 0.2206 - F1: 0.2334
sub_8:Test (Best Model) - Loss: 3.3440 - Accuracy: 0.2794 - F1: 0.3052
sub_8:Test (Best Model) - Loss: 3.7408 - Accuracy: 0.3824 - F1: 0.4019
sub_8:Test (Best Model) - Loss: 3.7166 - Accuracy: 0.3088 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 2.9410 - Accuracy: 0.3382 - F1: 0.3264
sub_9:Test (Best Model) - Loss: 2.6796 - Accuracy: 0.5000 - F1: 0.5034
sub_9:Test (Best Model) - Loss: 2.3675 - Accuracy: 0.6176 - F1: 0.6354
sub_9:Test (Best Model) - Loss: 1.9315 - Accuracy: 0.6471 - F1: 0.6583
sub_9:Test (Best Model) - Loss: 2.5579 - Accuracy: 0.5147 - F1: 0.5182
sub_9:Test (Best Model) - Loss: 2.0075 - Accuracy: 0.6176 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 4.7362 - Accuracy: 0.2794 - F1: 0.2583
sub_9:Test (Best Model) - Loss: 5.6288 - Accuracy: 0.4412 - F1: 0.3912
sub_9:Test (Best Model) - Loss: 4.4509 - Accuracy: 0.3235 - F1: 0.3273
sub_9:Test (Best Model) - Loss: 4.1398 - Accuracy: 0.3529 - F1: 0.3789
sub_9:Test (Best Model) - Loss: 3.9912 - Accuracy: 0.3088 - F1: 0.3256
sub_9:Test (Best Model) - Loss: 2.6651 - Accuracy: 0.4706 - F1: 0.4864
sub_9:Test (Best Model) - Loss: 3.1588 - Accuracy: 0.5000 - F1: 0.5232
sub_9:Test (Best Model) - Loss: 2.8728 - Accuracy: 0.4853 - F1: 0.4417
sub_9:Test (Best Model) - Loss: 3.3263 - Accuracy: 0.3971 - F1: 0.4129
sub_9:Test (Best Model) - Loss: 3.1352 - Accuracy: 0.4706 - F1: 0.4958
sub_10:Test (Best Model) - Loss: 2.7930 - Accuracy: 0.3235 - F1: 0.3263
sub_10:Test (Best Model) - Loss: 2.5258 - Accuracy: 0.3971 - F1: 0.3572
sub_10:Test (Best Model) - Loss: 2.1056 - Accuracy: 0.3529 - F1: 0.3480
sub_10:Test (Best Model) - Loss: 2.5468 - Accuracy: 0.3676 - F1: 0.3759
sub_10:Test (Best Model) - Loss: 2.4604 - Accuracy: 0.3235 - F1: 0.3296
sub_10:Test (Best Model) - Loss: 2.1682 - Accuracy: 0.3971 - F1: 0.3919
sub_10:Test (Best Model) - Loss: 2.4167 - Accuracy: 0.2647 - F1: 0.2726
sub_10:Test (Best Model) - Loss: 2.3516 - Accuracy: 0.3676 - F1: 0.3701
sub_10:Test (Best Model) - Loss: 2.2372 - Accuracy: 0.3529 - F1: 0.3359
sub_10:Test (Best Model) - Loss: 2.3940 - Accuracy: 0.2647 - F1: 0.2641
sub_10:Test (Best Model) - Loss: 3.2722 - Accuracy: 0.2754 - F1: 0.2726
sub_10:Test (Best Model) - Loss: 2.6400 - Accuracy: 0.3043 - F1: 0.3037
sub_10:Test (Best Model) - Loss: 2.7511 - Accuracy: 0.3478 - F1: 0.3426
sub_10:Test (Best Model) - Loss: 2.9107 - Accuracy: 0.2899 - F1: 0.2881
sub_10:Test (Best Model) - Loss: 2.5457 - Accuracy: 0.3043 - F1: 0.3010
sub_11:Test (Best Model) - Loss: 2.9029 - Accuracy: 0.3478 - F1: 0.3287
sub_11:Test (Best Model) - Loss: 2.8007 - Accuracy: 0.2609 - F1: 0.2457
sub_11:Test (Best Model) - Loss: 3.5088 - Accuracy: 0.3333 - F1: 0.3151
sub_11:Test (Best Model) - Loss: 3.2554 - Accuracy: 0.3333 - F1: 0.3378
sub_11:Test (Best Model) - Loss: 3.5671 - Accuracy: 0.3478 - F1: 0.2802
sub_11:Test (Best Model) - Loss: 2.5276 - Accuracy: 0.4058 - F1: 0.3771
sub_11:Test (Best Model) - Loss: 2.3906 - Accuracy: 0.5507 - F1: 0.5220
sub_11:Test (Best Model) - Loss: 2.4970 - Accuracy: 0.5362 - F1: 0.4950
sub_11:Test (Best Model) - Loss: 3.4351 - Accuracy: 0.4493 - F1: 0.3955
sub_11:Test (Best Model) - Loss: 3.2312 - Accuracy: 0.4783 - F1: 0.3918
sub_11:Test (Best Model) - Loss: 2.2537 - Accuracy: 0.4928 - F1: 0.4126
sub_11:Test (Best Model) - Loss: 2.1779 - Accuracy: 0.4203 - F1: 0.4254
sub_11:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.6087 - F1: 0.5730
sub_11:Test (Best Model) - Loss: 2.2818 - Accuracy: 0.4348 - F1: 0.3863
sub_11:Test (Best Model) - Loss: 2.0255 - Accuracy: 0.4783 - F1: 0.4721
sub_12:Test (Best Model) - Loss: 1.5282 - Accuracy: 0.5735 - F1: 0.5715
sub_12:Test (Best Model) - Loss: 1.4278 - Accuracy: 0.6324 - F1: 0.6295
sub_12:Test (Best Model) - Loss: 2.3524 - Accuracy: 0.4853 - F1: 0.4392
sub_12:Test (Best Model) - Loss: 1.5194 - Accuracy: 0.6176 - F1: 0.6048
sub_12:Test (Best Model) - Loss: 1.7888 - Accuracy: 0.5294 - F1: 0.5369
sub_12:Test (Best Model) - Loss: 1.8616 - Accuracy: 0.5652 - F1: 0.5626
sub_12:Test (Best Model) - Loss: 1.6746 - Accuracy: 0.5072 - F1: 0.5020
sub_12:Test (Best Model) - Loss: 1.4644 - Accuracy: 0.5507 - F1: 0.5437
sub_12:Test (Best Model) - Loss: 1.4774 - Accuracy: 0.5797 - F1: 0.5486
sub_12:Test (Best Model) - Loss: 1.3689 - Accuracy: 0.6087 - F1: 0.6196
sub_12:Test (Best Model) - Loss: 2.5250 - Accuracy: 0.4559 - F1: 0.4563
sub_12:Test (Best Model) - Loss: 2.0747 - Accuracy: 0.5000 - F1: 0.5236
sub_12:Test (Best Model) - Loss: 2.3297 - Accuracy: 0.4559 - F1: 0.4688
sub_12:Test (Best Model) - Loss: 2.6498 - Accuracy: 0.4706 - F1: 0.4712
sub_12:Test (Best Model) - Loss: 2.4527 - Accuracy: 0.4706 - F1: 0.4898
sub_13:Test (Best Model) - Loss: 2.6464 - Accuracy: 0.5147 - F1: 0.5093
sub_13:Test (Best Model) - Loss: 2.5515 - Accuracy: 0.5735 - F1: 0.5679
sub_13:Test (Best Model) - Loss: 2.2535 - Accuracy: 0.4559 - F1: 0.4890
sub_13:Test (Best Model) - Loss: 3.1409 - Accuracy: 0.4853 - F1: 0.5115
sub_13:Test (Best Model) - Loss: 2.9925 - Accuracy: 0.5441 - F1: 0.5551
sub_13:Test (Best Model) - Loss: 3.2533 - Accuracy: 0.5072 - F1: 0.5111
sub_13:Test (Best Model) - Loss: 3.2286 - Accuracy: 0.4638 - F1: 0.4860
sub_13:Test (Best Model) - Loss: 3.9255 - Accuracy: 0.3913 - F1: 0.3549
sub_13:Test (Best Model) - Loss: 3.2489 - Accuracy: 0.4348 - F1: 0.4385
sub_13:Test (Best Model) - Loss: 2.7658 - Accuracy: 0.5507 - F1: 0.5630
sub_13:Test (Best Model) - Loss: 3.0626 - Accuracy: 0.4118 - F1: 0.3967
sub_13:Test (Best Model) - Loss: 2.5248 - Accuracy: 0.4265 - F1: 0.4249
sub_13:Test (Best Model) - Loss: 3.5179 - Accuracy: 0.4412 - F1: 0.4452
sub_13:Test (Best Model) - Loss: 3.1733 - Accuracy: 0.4265 - F1: 0.4363
sub_13:Test (Best Model) - Loss: 2.4530 - Accuracy: 0.4559 - F1: 0.4441
sub_14:Test (Best Model) - Loss: 3.5605 - Accuracy: 0.3235 - F1: 0.3353
sub_14:Test (Best Model) - Loss: 2.9181 - Accuracy: 0.3088 - F1: 0.3256
sub_14:Test (Best Model) - Loss: 2.6347 - Accuracy: 0.3971 - F1: 0.4222
sub_14:Test (Best Model) - Loss: 3.2380 - Accuracy: 0.3529 - F1: 0.3784
sub_14:Test (Best Model) - Loss: 3.3091 - Accuracy: 0.4118 - F1: 0.4280
sub_14:Test (Best Model) - Loss: 3.5212 - Accuracy: 0.4265 - F1: 0.4414
sub_14:Test (Best Model) - Loss: 2.7449 - Accuracy: 0.5588 - F1: 0.5693
sub_14:Test (Best Model) - Loss: 3.0089 - Accuracy: 0.4265 - F1: 0.4426
sub_14:Test (Best Model) - Loss: 2.5408 - Accuracy: 0.4559 - F1: 0.4670
sub_14:Test (Best Model) - Loss: 2.8935 - Accuracy: 0.4265 - F1: 0.4483
sub_14:Test (Best Model) - Loss: 2.7357 - Accuracy: 0.5147 - F1: 0.5101
sub_14:Test (Best Model) - Loss: 2.6794 - Accuracy: 0.4265 - F1: 0.4265
sub_14:Test (Best Model) - Loss: 2.9338 - Accuracy: 0.4559 - F1: 0.4587
sub_14:Test (Best Model) - Loss: 3.2444 - Accuracy: 0.3971 - F1: 0.3887
sub_14:Test (Best Model) - Loss: 3.0368 - Accuracy: 0.4706 - F1: 0.4904
sub_15:Test (Best Model) - Loss: 2.4969 - Accuracy: 0.6029 - F1: 0.6175
sub_15:Test (Best Model) - Loss: 4.6688 - Accuracy: 0.2794 - F1: 0.3136
sub_15:Test (Best Model) - Loss: 4.1015 - Accuracy: 0.4118 - F1: 0.4482
sub_15:Test (Best Model) - Loss: 2.7007 - Accuracy: 0.4118 - F1: 0.4463
sub_15:Test (Best Model) - Loss: 3.1680 - Accuracy: 0.4853 - F1: 0.5085
sub_15:Test (Best Model) - Loss: 1.4627 - Accuracy: 0.6471 - F1: 0.6421
sub_15:Test (Best Model) - Loss: 2.5066 - Accuracy: 0.5735 - F1: 0.5737
sub_15:Test (Best Model) - Loss: 1.7229 - Accuracy: 0.5441 - F1: 0.5691
sub_15:Test (Best Model) - Loss: 2.6152 - Accuracy: 0.5735 - F1: 0.5645
sub_15:Test (Best Model) - Loss: 2.3239 - Accuracy: 0.4853 - F1: 0.4867
sub_15:Test (Best Model) - Loss: 3.1168 - Accuracy: 0.4265 - F1: 0.3720
sub_15:Test (Best Model) - Loss: 2.3192 - Accuracy: 0.4559 - F1: 0.4239
sub_15:Test (Best Model) - Loss: 3.7301 - Accuracy: 0.4265 - F1: 0.3775
sub_15:Test (Best Model) - Loss: 3.2296 - Accuracy: 0.3824 - F1: 0.3748
sub_15:Test (Best Model) - Loss: 3.6666 - Accuracy: 0.3382 - F1: 0.3544
sub_16:Test (Best Model) - Loss: 1.3434 - Accuracy: 0.6324 - F1: 0.5852
sub_16:Test (Best Model) - Loss: 1.3877 - Accuracy: 0.5441 - F1: 0.4901
sub_16:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.5147 - F1: 0.4742
sub_16:Test (Best Model) - Loss: 1.2035 - Accuracy: 0.6176 - F1: 0.6095
sub_16:Test (Best Model) - Loss: 0.9982 - Accuracy: 0.5882 - F1: 0.5678
sub_16:Test (Best Model) - Loss: 4.0322 - Accuracy: 0.3971 - F1: 0.3411
sub_16:Test (Best Model) - Loss: 2.2547 - Accuracy: 0.4853 - F1: 0.4589
sub_16:Test (Best Model) - Loss: 2.7714 - Accuracy: 0.3824 - F1: 0.3448
sub_16:Test (Best Model) - Loss: 1.7503 - Accuracy: 0.5735 - F1: 0.5668
sub_16:Test (Best Model) - Loss: 3.2211 - Accuracy: 0.4412 - F1: 0.4370
sub_16:Test (Best Model) - Loss: 1.5760 - Accuracy: 0.5441 - F1: 0.5025
sub_16:Test (Best Model) - Loss: 1.3009 - Accuracy: 0.5882 - F1: 0.5480
sub_16:Test (Best Model) - Loss: 1.7425 - Accuracy: 0.5735 - F1: 0.4720
sub_16:Test (Best Model) - Loss: 1.4425 - Accuracy: 0.5441 - F1: 0.5109
sub_16:Test (Best Model) - Loss: 1.2705 - Accuracy: 0.6029 - F1: 0.5613
sub_17:Test (Best Model) - Loss: 2.9005 - Accuracy: 0.3913 - F1: 0.3892
sub_17:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.4203 - F1: 0.4269
sub_17:Test (Best Model) - Loss: 2.3900 - Accuracy: 0.3913 - F1: 0.3641
sub_17:Test (Best Model) - Loss: 1.9813 - Accuracy: 0.4058 - F1: 0.4088
sub_17:Test (Best Model) - Loss: 2.3017 - Accuracy: 0.4348 - F1: 0.4012
sub_17:Test (Best Model) - Loss: 3.6998 - Accuracy: 0.4203 - F1: 0.3887
sub_17:Test (Best Model) - Loss: 5.7304 - Accuracy: 0.2899 - F1: 0.2526
sub_17:Test (Best Model) - Loss: 4.9945 - Accuracy: 0.4058 - F1: 0.3378
sub_17:Test (Best Model) - Loss: 4.4099 - Accuracy: 0.4928 - F1: 0.4471
sub_17:Test (Best Model) - Loss: 3.5436 - Accuracy: 0.4928 - F1: 0.4434
sub_17:Test (Best Model) - Loss: 2.0286 - Accuracy: 0.4853 - F1: 0.4777
sub_17:Test (Best Model) - Loss: 2.0510 - Accuracy: 0.4412 - F1: 0.4437
sub_17:Test (Best Model) - Loss: 3.3018 - Accuracy: 0.3676 - F1: 0.3461
sub_17:Test (Best Model) - Loss: 3.3100 - Accuracy: 0.4706 - F1: 0.4671
sub_17:Test (Best Model) - Loss: 2.1787 - Accuracy: 0.4559 - F1: 0.4438
sub_18:Test (Best Model) - Loss: 1.9914 - Accuracy: 0.4203 - F1: 0.3697
sub_18:Test (Best Model) - Loss: 1.7600 - Accuracy: 0.4348 - F1: 0.4361
sub_18:Test (Best Model) - Loss: 1.8817 - Accuracy: 0.4348 - F1: 0.3906
sub_18:Test (Best Model) - Loss: 2.1020 - Accuracy: 0.4203 - F1: 0.4198
sub_18:Test (Best Model) - Loss: 1.7945 - Accuracy: 0.4783 - F1: 0.4843
sub_18:Test (Best Model) - Loss: 2.8301 - Accuracy: 0.3382 - F1: 0.3646
sub_18:Test (Best Model) - Loss: 2.4760 - Accuracy: 0.4118 - F1: 0.3970
sub_18:Test (Best Model) - Loss: 2.6278 - Accuracy: 0.3971 - F1: 0.3885
sub_18:Test (Best Model) - Loss: 2.8532 - Accuracy: 0.3529 - F1: 0.3814
sub_18:Test (Best Model) - Loss: 2.7141 - Accuracy: 0.3235 - F1: 0.3378
sub_18:Test (Best Model) - Loss: 2.3821 - Accuracy: 0.3088 - F1: 0.3019
sub_18:Test (Best Model) - Loss: 3.1482 - Accuracy: 0.2794 - F1: 0.3214
sub_18:Test (Best Model) - Loss: 2.7905 - Accuracy: 0.2794 - F1: 0.3288
sub_18:Test (Best Model) - Loss: 2.4399 - Accuracy: 0.4412 - F1: 0.4266
sub_18:Test (Best Model) - Loss: 2.6788 - Accuracy: 0.3529 - F1: 0.3883
sub_19:Test (Best Model) - Loss: 3.4721 - Accuracy: 0.2647 - F1: 0.2587
sub_19:Test (Best Model) - Loss: 3.0097 - Accuracy: 0.2206 - F1: 0.2459
sub_19:Test (Best Model) - Loss: 4.1881 - Accuracy: 0.1618 - F1: 0.1576
sub_19:Test (Best Model) - Loss: 3.6923 - Accuracy: 0.2353 - F1: 0.2287
sub_19:Test (Best Model) - Loss: 3.7378 - Accuracy: 0.3088 - F1: 0.3099
sub_19:Test (Best Model) - Loss: 3.1360 - Accuracy: 0.3382 - F1: 0.3119
sub_19:Test (Best Model) - Loss: 2.3369 - Accuracy: 0.3824 - F1: 0.3506
sub_19:Test (Best Model) - Loss: 1.9718 - Accuracy: 0.5000 - F1: 0.4686
sub_19:Test (Best Model) - Loss: 2.0629 - Accuracy: 0.5000 - F1: 0.4912
sub_19:Test (Best Model) - Loss: 1.9695 - Accuracy: 0.5441 - F1: 0.5373
sub_19:Test (Best Model) - Loss: 3.4140 - Accuracy: 0.3676 - F1: 0.3460
sub_19:Test (Best Model) - Loss: 5.4705 - Accuracy: 0.2500 - F1: 0.2204
sub_19:Test (Best Model) - Loss: 2.9889 - Accuracy: 0.3382 - F1: 0.3243
sub_19:Test (Best Model) - Loss: 3.8877 - Accuracy: 0.3088 - F1: 0.3040
sub_19:Test (Best Model) - Loss: 3.3405 - Accuracy: 0.2941 - F1: 0.2994
sub_20:Test (Best Model) - Loss: 1.8555 - Accuracy: 0.6324 - F1: 0.6229
sub_20:Test (Best Model) - Loss: 2.1304 - Accuracy: 0.5588 - F1: 0.5695
sub_20:Test (Best Model) - Loss: 2.2679 - Accuracy: 0.5294 - F1: 0.5315
sub_20:Test (Best Model) - Loss: 2.3168 - Accuracy: 0.4706 - F1: 0.4780
sub_20:Test (Best Model) - Loss: 2.4897 - Accuracy: 0.5000 - F1: 0.4889
sub_20:Test (Best Model) - Loss: 3.9455 - Accuracy: 0.3529 - F1: 0.3618
sub_20:Test (Best Model) - Loss: 2.2023 - Accuracy: 0.4706 - F1: 0.4892
sub_20:Test (Best Model) - Loss: 2.6345 - Accuracy: 0.4412 - F1: 0.4645
sub_20:Test (Best Model) - Loss: 2.8972 - Accuracy: 0.3382 - F1: 0.3618
sub_20:Test (Best Model) - Loss: 2.2374 - Accuracy: 0.5147 - F1: 0.5167
sub_20:Test (Best Model) - Loss: 2.5678 - Accuracy: 0.4348 - F1: 0.4395
sub_20:Test (Best Model) - Loss: 4.2893 - Accuracy: 0.4058 - F1: 0.3983
sub_20:Test (Best Model) - Loss: 2.6459 - Accuracy: 0.4348 - F1: 0.4443
sub_20:Test (Best Model) - Loss: 3.1200 - Accuracy: 0.4348 - F1: 0.4241
sub_20:Test (Best Model) - Loss: 3.2185 - Accuracy: 0.3768 - F1: 0.4014
sub_21:Test (Best Model) - Loss: 2.8756 - Accuracy: 0.4265 - F1: 0.4135
sub_21:Test (Best Model) - Loss: 2.5912 - Accuracy: 0.3971 - F1: 0.3824
sub_21:Test (Best Model) - Loss: 3.7173 - Accuracy: 0.4265 - F1: 0.3833
sub_21:Test (Best Model) - Loss: 2.9495 - Accuracy: 0.4853 - F1: 0.4477
sub_21:Test (Best Model) - Loss: 2.8255 - Accuracy: 0.4118 - F1: 0.4041
sub_21:Test (Best Model) - Loss: 2.3270 - Accuracy: 0.4853 - F1: 0.4738
sub_21:Test (Best Model) - Loss: 1.7022 - Accuracy: 0.5588 - F1: 0.5048
sub_21:Test (Best Model) - Loss: 1.8709 - Accuracy: 0.4412 - F1: 0.4273
sub_21:Test (Best Model) - Loss: 2.5213 - Accuracy: 0.4265 - F1: 0.4147
sub_21:Test (Best Model) - Loss: 1.7547 - Accuracy: 0.5147 - F1: 0.5003
sub_21:Test (Best Model) - Loss: 2.2004 - Accuracy: 0.4118 - F1: 0.4105
sub_21:Test (Best Model) - Loss: 2.6288 - Accuracy: 0.4559 - F1: 0.4211
sub_21:Test (Best Model) - Loss: 2.9840 - Accuracy: 0.4265 - F1: 0.3944
sub_21:Test (Best Model) - Loss: 2.5767 - Accuracy: 0.3235 - F1: 0.2927
sub_21:Test (Best Model) - Loss: 2.6001 - Accuracy: 0.4412 - F1: 0.3599
sub_22:Test (Best Model) - Loss: 2.5667 - Accuracy: 0.3971 - F1: 0.4040
sub_22:Test (Best Model) - Loss: 2.2887 - Accuracy: 0.4706 - F1: 0.4793
sub_22:Test (Best Model) - Loss: 2.9258 - Accuracy: 0.3971 - F1: 0.4127
sub_22:Test (Best Model) - Loss: 2.1593 - Accuracy: 0.3824 - F1: 0.4017
sub_22:Test (Best Model) - Loss: 2.4484 - Accuracy: 0.4559 - F1: 0.4602
sub_22:Test (Best Model) - Loss: 2.2369 - Accuracy: 0.3623 - F1: 0.3436
sub_22:Test (Best Model) - Loss: 2.1120 - Accuracy: 0.3768 - F1: 0.3282
sub_22:Test (Best Model) - Loss: 2.0404 - Accuracy: 0.3913 - F1: 0.4046
sub_22:Test (Best Model) - Loss: 2.5330 - Accuracy: 0.2899 - F1: 0.3021
sub_22:Test (Best Model) - Loss: 2.4323 - Accuracy: 0.3478 - F1: 0.3320
sub_22:Test (Best Model) - Loss: 2.1559 - Accuracy: 0.4118 - F1: 0.4396
sub_22:Test (Best Model) - Loss: 2.4636 - Accuracy: 0.4412 - F1: 0.4664
sub_22:Test (Best Model) - Loss: 2.1239 - Accuracy: 0.3529 - F1: 0.3692
sub_22:Test (Best Model) - Loss: 2.2972 - Accuracy: 0.3971 - F1: 0.4202
sub_22:Test (Best Model) - Loss: 1.8080 - Accuracy: 0.3971 - F1: 0.4368
sub_23:Test (Best Model) - Loss: 2.3713 - Accuracy: 0.4493 - F1: 0.4667
sub_23:Test (Best Model) - Loss: 3.3171 - Accuracy: 0.3623 - F1: 0.3664
sub_23:Test (Best Model) - Loss: 2.1180 - Accuracy: 0.4783 - F1: 0.5039
sub_23:Test (Best Model) - Loss: 2.0999 - Accuracy: 0.5507 - F1: 0.5524
sub_23:Test (Best Model) - Loss: 2.6673 - Accuracy: 0.4928 - F1: 0.4874
sub_23:Test (Best Model) - Loss: 2.9344 - Accuracy: 0.4118 - F1: 0.3524
sub_23:Test (Best Model) - Loss: 2.1781 - Accuracy: 0.4706 - F1: 0.4552
sub_23:Test (Best Model) - Loss: 1.8662 - Accuracy: 0.6324 - F1: 0.6302
sub_23:Test (Best Model) - Loss: 2.0511 - Accuracy: 0.5147 - F1: 0.4777
sub_23:Test (Best Model) - Loss: 1.7897 - Accuracy: 0.5588 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 3.5997 - Accuracy: 0.4638 - F1: 0.4490
sub_23:Test (Best Model) - Loss: 3.4724 - Accuracy: 0.4638 - F1: 0.4596
sub_23:Test (Best Model) - Loss: 4.2370 - Accuracy: 0.3478 - F1: 0.3294
sub_23:Test (Best Model) - Loss: 5.2800 - Accuracy: 0.4058 - F1: 0.3908
sub_23:Test (Best Model) - Loss: 3.4699 - Accuracy: 0.4638 - F1: 0.4602
sub_24:Test (Best Model) - Loss: 2.6512 - Accuracy: 0.3382 - F1: 0.3321
sub_24:Test (Best Model) - Loss: 2.6260 - Accuracy: 0.2647 - F1: 0.2463
sub_24:Test (Best Model) - Loss: 2.5781 - Accuracy: 0.3088 - F1: 0.3105
sub_24:Test (Best Model) - Loss: 3.1520 - Accuracy: 0.2941 - F1: 0.2756
sub_24:Test (Best Model) - Loss: 2.7148 - Accuracy: 0.3382 - F1: 0.3410
sub_24:Test (Best Model) - Loss: 1.9399 - Accuracy: 0.4118 - F1: 0.4146
sub_24:Test (Best Model) - Loss: 1.8794 - Accuracy: 0.4559 - F1: 0.4509
sub_24:Test (Best Model) - Loss: 2.2272 - Accuracy: 0.3676 - F1: 0.3104
sub_24:Test (Best Model) - Loss: 1.6321 - Accuracy: 0.4265 - F1: 0.4313
sub_24:Test (Best Model) - Loss: 1.9813 - Accuracy: 0.3382 - F1: 0.3313
sub_24:Test (Best Model) - Loss: 2.5870 - Accuracy: 0.3382 - F1: 0.3319
sub_24:Test (Best Model) - Loss: 2.1878 - Accuracy: 0.3235 - F1: 0.3148
sub_24:Test (Best Model) - Loss: 2.0658 - Accuracy: 0.3971 - F1: 0.3862
sub_24:Test (Best Model) - Loss: 2.4774 - Accuracy: 0.3235 - F1: 0.3143
sub_24:Test (Best Model) - Loss: 2.6306 - Accuracy: 0.4118 - F1: 0.4075
sub_25:Test (Best Model) - Loss: 1.7687 - Accuracy: 0.5942 - F1: 0.5274
sub_25:Test (Best Model) - Loss: 2.2431 - Accuracy: 0.4638 - F1: 0.4039
sub_25:Test (Best Model) - Loss: 1.9658 - Accuracy: 0.5362 - F1: 0.4902
sub_25:Test (Best Model) - Loss: 1.7094 - Accuracy: 0.4783 - F1: 0.4325
sub_25:Test (Best Model) - Loss: 2.1967 - Accuracy: 0.4638 - F1: 0.4356
sub_25:Test (Best Model) - Loss: 4.4753 - Accuracy: 0.4265 - F1: 0.3856
sub_25:Test (Best Model) - Loss: 2.4858 - Accuracy: 0.3971 - F1: 0.3535
sub_25:Test (Best Model) - Loss: 4.3062 - Accuracy: 0.4706 - F1: 0.4096
sub_25:Test (Best Model) - Loss: 2.8910 - Accuracy: 0.4853 - F1: 0.4069
sub_25:Test (Best Model) - Loss: 2.8810 - Accuracy: 0.5147 - F1: 0.4671
sub_25:Test (Best Model) - Loss: 1.6690 - Accuracy: 0.5147 - F1: 0.4872
sub_25:Test (Best Model) - Loss: 1.9066 - Accuracy: 0.4265 - F1: 0.4087
sub_25:Test (Best Model) - Loss: 2.0684 - Accuracy: 0.4559 - F1: 0.4617
sub_25:Test (Best Model) - Loss: 1.8234 - Accuracy: 0.4265 - F1: 0.3924
sub_25:Test (Best Model) - Loss: 2.0268 - Accuracy: 0.4559 - F1: 0.3804
sub_26:Test (Best Model) - Loss: 1.8436 - Accuracy: 0.4783 - F1: 0.4759
sub_26:Test (Best Model) - Loss: 1.8108 - Accuracy: 0.4638 - F1: 0.4867
sub_26:Test (Best Model) - Loss: 1.9802 - Accuracy: 0.5072 - F1: 0.5005
sub_26:Test (Best Model) - Loss: 1.5385 - Accuracy: 0.4928 - F1: 0.5068
sub_26:Test (Best Model) - Loss: 1.3873 - Accuracy: 0.6232 - F1: 0.6395
sub_26:Test (Best Model) - Loss: 3.2234 - Accuracy: 0.4118 - F1: 0.4106
sub_26:Test (Best Model) - Loss: 4.5369 - Accuracy: 0.3088 - F1: 0.3276
sub_26:Test (Best Model) - Loss: 2.8775 - Accuracy: 0.3382 - F1: 0.3641
sub_26:Test (Best Model) - Loss: 2.9418 - Accuracy: 0.3382 - F1: 0.3488
sub_26:Test (Best Model) - Loss: 3.0384 - Accuracy: 0.2647 - F1: 0.2802
sub_26:Test (Best Model) - Loss: 1.9693 - Accuracy: 0.5294 - F1: 0.5322
sub_26:Test (Best Model) - Loss: 2.6769 - Accuracy: 0.4853 - F1: 0.4786
sub_26:Test (Best Model) - Loss: 2.5133 - Accuracy: 0.5000 - F1: 0.5195
sub_26:Test (Best Model) - Loss: 3.1331 - Accuracy: 0.5441 - F1: 0.5637
sub_26:Test (Best Model) - Loss: 2.4821 - Accuracy: 0.5000 - F1: 0.5038
sub_27:Test (Best Model) - Loss: 2.9005 - Accuracy: 0.3913 - F1: 0.3892
sub_27:Test (Best Model) - Loss: 1.5526 - Accuracy: 0.4203 - F1: 0.4269
sub_27:Test (Best Model) - Loss: 2.3900 - Accuracy: 0.3913 - F1: 0.3641
sub_27:Test (Best Model) - Loss: 1.9813 - Accuracy: 0.4058 - F1: 0.4088
sub_27:Test (Best Model) - Loss: 2.3017 - Accuracy: 0.4348 - F1: 0.4012
sub_27:Test (Best Model) - Loss: 3.6998 - Accuracy: 0.4203 - F1: 0.3887
sub_27:Test (Best Model) - Loss: 5.7304 - Accuracy: 0.2899 - F1: 0.2526
sub_27:Test (Best Model) - Loss: 4.9945 - Accuracy: 0.4058 - F1: 0.3378
sub_27:Test (Best Model) - Loss: 4.4099 - Accuracy: 0.4928 - F1: 0.4471
sub_27:Test (Best Model) - Loss: 3.5436 - Accuracy: 0.4928 - F1: 0.4434
sub_27:Test (Best Model) - Loss: 2.0286 - Accuracy: 0.4853 - F1: 0.4777
sub_27:Test (Best Model) - Loss: 2.0510 - Accuracy: 0.4412 - F1: 0.4437
sub_27:Test (Best Model) - Loss: 3.3018 - Accuracy: 0.3676 - F1: 0.3461
sub_27:Test (Best Model) - Loss: 3.3100 - Accuracy: 0.4706 - F1: 0.4671
sub_27:Test (Best Model) - Loss: 2.1787 - Accuracy: 0.4559 - F1: 0.4438
sub_28:Test (Best Model) - Loss: 5.1523 - Accuracy: 0.2794 - F1: 0.2818
sub_28:Test (Best Model) - Loss: 3.2632 - Accuracy: 0.3088 - F1: 0.2984
sub_28:Test (Best Model) - Loss: 4.5757 - Accuracy: 0.2941 - F1: 0.2575
sub_28:Test (Best Model) - Loss: 3.9886 - Accuracy: 0.2647 - F1: 0.2585
sub_28:Test (Best Model) - Loss: 4.5526 - Accuracy: 0.3235 - F1: 0.3260
sub_28:Test (Best Model) - Loss: 5.5950 - Accuracy: 0.2500 - F1: 0.2364
sub_28:Test (Best Model) - Loss: 6.1211 - Accuracy: 0.2941 - F1: 0.2432
sub_28:Test (Best Model) - Loss: 5.7633 - Accuracy: 0.3088 - F1: 0.2727
sub_28:Test (Best Model) - Loss: 6.5997 - Accuracy: 0.2206 - F1: 0.2142
sub_28:Test (Best Model) - Loss: 6.4766 - Accuracy: 0.2353 - F1: 0.1886
sub_28:Test (Best Model) - Loss: 2.2869 - Accuracy: 0.4706 - F1: 0.4532
sub_28:Test (Best Model) - Loss: 2.6550 - Accuracy: 0.4559 - F1: 0.4087
sub_28:Test (Best Model) - Loss: 1.9229 - Accuracy: 0.4118 - F1: 0.4095
sub_28:Test (Best Model) - Loss: 1.9188 - Accuracy: 0.4412 - F1: 0.4109
sub_28:Test (Best Model) - Loss: 2.0503 - Accuracy: 0.3676 - F1: 0.3575
sub_29:Test (Best Model) - Loss: 4.0420 - Accuracy: 0.5294 - F1: 0.5191
sub_29:Test (Best Model) - Loss: 2.6446 - Accuracy: 0.5588 - F1: 0.5628
sub_29:Test (Best Model) - Loss: 3.9467 - Accuracy: 0.5882 - F1: 0.5657
sub_29:Test (Best Model) - Loss: 2.9344 - Accuracy: 0.5147 - F1: 0.5139
sub_29:Test (Best Model) - Loss: 3.3630 - Accuracy: 0.5735 - F1: 0.5718
sub_29:Test (Best Model) - Loss: 1.1635 - Accuracy: 0.6912 - F1: 0.7054
sub_29:Test (Best Model) - Loss: 2.2129 - Accuracy: 0.4412 - F1: 0.4236
sub_29:Test (Best Model) - Loss: 1.5489 - Accuracy: 0.5588 - F1: 0.5456
sub_29:Test (Best Model) - Loss: 1.3091 - Accuracy: 0.6471 - F1: 0.6571
sub_29:Test (Best Model) - Loss: 1.7228 - Accuracy: 0.5882 - F1: 0.6209
sub_29:Test (Best Model) - Loss: 1.3942 - Accuracy: 0.6377 - F1: 0.6525
sub_29:Test (Best Model) - Loss: 2.0835 - Accuracy: 0.5507 - F1: 0.5647
sub_29:Test (Best Model) - Loss: 2.3880 - Accuracy: 0.5507 - F1: 0.5702
sub_29:Test (Best Model) - Loss: 2.0992 - Accuracy: 0.5797 - F1: 0.5764
sub_29:Test (Best Model) - Loss: 2.2983 - Accuracy: 0.4928 - F1: 0.4640

=== Summary Results ===

acc: 43.21 ± 6.77
F1: 42.28 ± 6.83
acc-in: 54.68 ± 6.15
F1-in: 52.53 ± 6.45
