lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.2002 - Accuracy: 0.5147 - F1: 0.5506
sub_1:Test (Best Model) - Loss: 1.1815 - Accuracy: 0.5000 - F1: 0.5369
sub_1:Test (Best Model) - Loss: 1.1833 - Accuracy: 0.4706 - F1: 0.5011
sub_1:Test (Best Model) - Loss: 1.1033 - Accuracy: 0.5147 - F1: 0.5419
sub_1:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.4559 - F1: 0.4853
sub_1:Test (Best Model) - Loss: 1.2235 - Accuracy: 0.3768 - F1: 0.3857
sub_1:Test (Best Model) - Loss: 1.2346 - Accuracy: 0.3478 - F1: 0.3484
sub_1:Test (Best Model) - Loss: 1.2620 - Accuracy: 0.4058 - F1: 0.4153
sub_1:Test (Best Model) - Loss: 1.1883 - Accuracy: 0.4638 - F1: 0.4605
sub_1:Test (Best Model) - Loss: 1.2137 - Accuracy: 0.3768 - F1: 0.3900
sub_1:Test (Best Model) - Loss: 1.1165 - Accuracy: 0.5000 - F1: 0.4755
sub_1:Test (Best Model) - Loss: 1.0729 - Accuracy: 0.5735 - F1: 0.5737
sub_1:Test (Best Model) - Loss: 1.0580 - Accuracy: 0.6176 - F1: 0.6268
sub_1:Test (Best Model) - Loss: 1.1616 - Accuracy: 0.5000 - F1: 0.4770
sub_1:Test (Best Model) - Loss: 1.1134 - Accuracy: 0.4706 - F1: 0.4545
sub_2:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.3188 - F1: 0.3184
sub_2:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.2464 - F1: 0.2690
sub_2:Test (Best Model) - Loss: 1.4238 - Accuracy: 0.2319 - F1: 0.2371
sub_2:Test (Best Model) - Loss: 1.4337 - Accuracy: 0.2464 - F1: 0.2689
sub_2:Test (Best Model) - Loss: 1.4792 - Accuracy: 0.3043 - F1: 0.3252
sub_2:Test (Best Model) - Loss: 1.3900 - Accuracy: 0.2059 - F1: 0.2249
sub_2:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.2941 - F1: 0.3255
sub_2:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.5000 - F1: 0.5048
sub_2:Test (Best Model) - Loss: 1.3771 - Accuracy: 0.3676 - F1: 0.3736
sub_2:Test (Best Model) - Loss: 1.3422 - Accuracy: 0.3676 - F1: 0.3742
sub_2:Test (Best Model) - Loss: 1.3530 - Accuracy: 0.3333 - F1: 0.3439
sub_2:Test (Best Model) - Loss: 1.4169 - Accuracy: 0.2319 - F1: 0.2319
sub_2:Test (Best Model) - Loss: 1.2191 - Accuracy: 0.4783 - F1: 0.4800
sub_2:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.3623 - F1: 0.3510
sub_2:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3913 - F1: 0.3914
sub_3:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.2500 - F1: 0.2466
sub_3:Test (Best Model) - Loss: 1.3342 - Accuracy: 0.3382 - F1: 0.3427
sub_3:Test (Best Model) - Loss: 1.4098 - Accuracy: 0.2794 - F1: 0.2789
sub_3:Test (Best Model) - Loss: 1.3847 - Accuracy: 0.3088 - F1: 0.3071
sub_3:Test (Best Model) - Loss: 1.4331 - Accuracy: 0.3676 - F1: 0.3644
sub_3:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.3188 - F1: 0.2909
sub_3:Test (Best Model) - Loss: 1.4091 - Accuracy: 0.3043 - F1: 0.2737
sub_3:Test (Best Model) - Loss: 1.3733 - Accuracy: 0.2609 - F1: 0.2410
sub_3:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3768 - F1: 0.3629
sub_3:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3478 - F1: 0.2950
sub_3:Test (Best Model) - Loss: 1.5119 - Accuracy: 0.3478 - F1: 0.3214
sub_3:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.3333 - F1: 0.2942
sub_3:Test (Best Model) - Loss: 1.3923 - Accuracy: 0.3043 - F1: 0.2672
sub_3:Test (Best Model) - Loss: 1.3915 - Accuracy: 0.3043 - F1: 0.2800
sub_3:Test (Best Model) - Loss: 1.4348 - Accuracy: 0.4058 - F1: 0.3821
sub_4:Test (Best Model) - Loss: 1.0107 - Accuracy: 0.5072 - F1: 0.5279
sub_4:Test (Best Model) - Loss: 1.0235 - Accuracy: 0.4928 - F1: 0.5211
sub_4:Test (Best Model) - Loss: 1.1003 - Accuracy: 0.5217 - F1: 0.5380
sub_4:Test (Best Model) - Loss: 0.9112 - Accuracy: 0.6087 - F1: 0.6198
sub_4:Test (Best Model) - Loss: 0.9786 - Accuracy: 0.5797 - F1: 0.5867
sub_4:Test (Best Model) - Loss: 1.0268 - Accuracy: 0.5362 - F1: 0.5466
sub_4:Test (Best Model) - Loss: 1.0348 - Accuracy: 0.5217 - F1: 0.5457
sub_4:Test (Best Model) - Loss: 0.9563 - Accuracy: 0.5942 - F1: 0.6190
sub_4:Test (Best Model) - Loss: 0.9574 - Accuracy: 0.6087 - F1: 0.6161
sub_4:Test (Best Model) - Loss: 1.0082 - Accuracy: 0.5072 - F1: 0.5337
sub_4:Test (Best Model) - Loss: 1.1182 - Accuracy: 0.4493 - F1: 0.4191
sub_4:Test (Best Model) - Loss: 1.0913 - Accuracy: 0.5217 - F1: 0.5319
sub_4:Test (Best Model) - Loss: 1.0629 - Accuracy: 0.4928 - F1: 0.4971
sub_4:Test (Best Model) - Loss: 1.0512 - Accuracy: 0.4638 - F1: 0.4227
sub_4:Test (Best Model) - Loss: 1.0402 - Accuracy: 0.5072 - F1: 0.4957
sub_5:Test (Best Model) - Loss: 1.5449 - Accuracy: 0.5294 - F1: 0.5075
sub_5:Test (Best Model) - Loss: 1.6967 - Accuracy: 0.4706 - F1: 0.4407
sub_5:Test (Best Model) - Loss: 1.7293 - Accuracy: 0.4265 - F1: 0.4002
sub_5:Test (Best Model) - Loss: 1.5514 - Accuracy: 0.4706 - F1: 0.4470
sub_5:Test (Best Model) - Loss: 1.5899 - Accuracy: 0.4706 - F1: 0.4359
sub_5:Test (Best Model) - Loss: 1.1462 - Accuracy: 0.4412 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 1.0578 - Accuracy: 0.4853 - F1: 0.4349
sub_5:Test (Best Model) - Loss: 1.0519 - Accuracy: 0.4706 - F1: 0.4609
sub_5:Test (Best Model) - Loss: 1.0325 - Accuracy: 0.5147 - F1: 0.4931
sub_5:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.4412 - F1: 0.4229
sub_5:Test (Best Model) - Loss: 1.1442 - Accuracy: 0.3971 - F1: 0.3980
sub_5:Test (Best Model) - Loss: 1.1569 - Accuracy: 0.3824 - F1: 0.3519
sub_5:Test (Best Model) - Loss: 1.1578 - Accuracy: 0.4118 - F1: 0.3841
sub_5:Test (Best Model) - Loss: 1.1203 - Accuracy: 0.4265 - F1: 0.4183
sub_5:Test (Best Model) - Loss: 1.0859 - Accuracy: 0.3971 - F1: 0.3564
sub_6:Test (Best Model) - Loss: 1.1725 - Accuracy: 0.4265 - F1: 0.4498
sub_6:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.4706 - F1: 0.4781
sub_6:Test (Best Model) - Loss: 1.1380 - Accuracy: 0.5000 - F1: 0.4916
sub_6:Test (Best Model) - Loss: 1.1343 - Accuracy: 0.4853 - F1: 0.4987
sub_6:Test (Best Model) - Loss: 1.1801 - Accuracy: 0.4706 - F1: 0.4892
sub_6:Test (Best Model) - Loss: 1.2584 - Accuracy: 0.4348 - F1: 0.3761
sub_6:Test (Best Model) - Loss: 1.2219 - Accuracy: 0.4928 - F1: 0.4315
sub_6:Test (Best Model) - Loss: 1.2158 - Accuracy: 0.4638 - F1: 0.4187
sub_6:Test (Best Model) - Loss: 1.2439 - Accuracy: 0.4493 - F1: 0.3915
sub_6:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.5217 - F1: 0.4671
sub_6:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.3768 - F1: 0.4021
sub_6:Test (Best Model) - Loss: 1.3363 - Accuracy: 0.4348 - F1: 0.4515
sub_6:Test (Best Model) - Loss: 1.3076 - Accuracy: 0.4348 - F1: 0.4601
sub_6:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.4638 - F1: 0.4915
sub_6:Test (Best Model) - Loss: 1.2099 - Accuracy: 0.4638 - F1: 0.4943
sub_7:Test (Best Model) - Loss: 1.0138 - Accuracy: 0.6176 - F1: 0.6159
sub_7:Test (Best Model) - Loss: 0.9392 - Accuracy: 0.6471 - F1: 0.6157
sub_7:Test (Best Model) - Loss: 1.0198 - Accuracy: 0.4706 - F1: 0.4297
sub_7:Test (Best Model) - Loss: 0.9406 - Accuracy: 0.6029 - F1: 0.5917
sub_7:Test (Best Model) - Loss: 0.9829 - Accuracy: 0.5588 - F1: 0.5628
sub_7:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.4412 - F1: 0.4136
sub_7:Test (Best Model) - Loss: 1.2665 - Accuracy: 0.4118 - F1: 0.3883
sub_7:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.4853 - F1: 0.4962
sub_7:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.4706 - F1: 0.4517
sub_7:Test (Best Model) - Loss: 1.1215 - Accuracy: 0.5000 - F1: 0.4619
sub_7:Test (Best Model) - Loss: 1.1423 - Accuracy: 0.5441 - F1: 0.5525
sub_7:Test (Best Model) - Loss: 1.1301 - Accuracy: 0.5147 - F1: 0.5026
sub_7:Test (Best Model) - Loss: 1.1253 - Accuracy: 0.5588 - F1: 0.5530
sub_7:Test (Best Model) - Loss: 1.1500 - Accuracy: 0.6029 - F1: 0.6100
sub_7:Test (Best Model) - Loss: 1.1878 - Accuracy: 0.5147 - F1: 0.5284
sub_8:Test (Best Model) - Loss: 1.4638 - Accuracy: 0.3529 - F1: 0.3644
sub_8:Test (Best Model) - Loss: 1.5176 - Accuracy: 0.2794 - F1: 0.2698
sub_8:Test (Best Model) - Loss: 1.4198 - Accuracy: 0.2647 - F1: 0.3068
sub_8:Test (Best Model) - Loss: 1.4551 - Accuracy: 0.3824 - F1: 0.3821
sub_8:Test (Best Model) - Loss: 1.4246 - Accuracy: 0.3235 - F1: 0.3494
sub_8:Test (Best Model) - Loss: 1.2868 - Accuracy: 0.3676 - F1: 0.3904
sub_8:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.3235 - F1: 0.3409
sub_8:Test (Best Model) - Loss: 1.2707 - Accuracy: 0.4265 - F1: 0.4312
sub_8:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.3088 - F1: 0.3085
sub_8:Test (Best Model) - Loss: 1.3338 - Accuracy: 0.3382 - F1: 0.3487
sub_8:Test (Best Model) - Loss: 1.4616 - Accuracy: 0.3676 - F1: 0.3613
sub_8:Test (Best Model) - Loss: 1.4046 - Accuracy: 0.3824 - F1: 0.3939
sub_8:Test (Best Model) - Loss: 1.4704 - Accuracy: 0.4412 - F1: 0.4710
sub_8:Test (Best Model) - Loss: 1.4308 - Accuracy: 0.4559 - F1: 0.4656
sub_8:Test (Best Model) - Loss: 1.3933 - Accuracy: 0.3382 - F1: 0.3448
sub_9:Test (Best Model) - Loss: 1.0209 - Accuracy: 0.5735 - F1: 0.5876
sub_9:Test (Best Model) - Loss: 1.0430 - Accuracy: 0.5588 - F1: 0.5804
sub_9:Test (Best Model) - Loss: 1.0516 - Accuracy: 0.5147 - F1: 0.5448
sub_9:Test (Best Model) - Loss: 1.0501 - Accuracy: 0.5441 - F1: 0.5704
sub_9:Test (Best Model) - Loss: 0.9898 - Accuracy: 0.5588 - F1: 0.5794
sub_9:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.3088 - F1: 0.3069
sub_9:Test (Best Model) - Loss: 1.3091 - Accuracy: 0.3824 - F1: 0.4113
sub_9:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.3529 - F1: 0.3718
sub_9:Test (Best Model) - Loss: 1.1840 - Accuracy: 0.3971 - F1: 0.4152
sub_9:Test (Best Model) - Loss: 1.2916 - Accuracy: 0.3529 - F1: 0.3831
sub_9:Test (Best Model) - Loss: 1.3285 - Accuracy: 0.3824 - F1: 0.4121
sub_9:Test (Best Model) - Loss: 1.2892 - Accuracy: 0.3971 - F1: 0.4148
sub_9:Test (Best Model) - Loss: 1.2603 - Accuracy: 0.4265 - F1: 0.4571
sub_9:Test (Best Model) - Loss: 1.2368 - Accuracy: 0.4118 - F1: 0.4419
sub_9:Test (Best Model) - Loss: 1.2442 - Accuracy: 0.3824 - F1: 0.4086
sub_10:Test (Best Model) - Loss: 1.3960 - Accuracy: 0.3088 - F1: 0.2979
sub_10:Test (Best Model) - Loss: 1.3949 - Accuracy: 0.3529 - F1: 0.3589
sub_10:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.2941 - F1: 0.2991
sub_10:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.3235 - F1: 0.3365
sub_10:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.3382 - F1: 0.3582
sub_10:Test (Best Model) - Loss: 1.3632 - Accuracy: 0.3235 - F1: 0.3058
sub_10:Test (Best Model) - Loss: 1.4466 - Accuracy: 0.2206 - F1: 0.2049
sub_10:Test (Best Model) - Loss: 1.3867 - Accuracy: 0.3529 - F1: 0.3478
sub_10:Test (Best Model) - Loss: 1.3552 - Accuracy: 0.2500 - F1: 0.2591
sub_10:Test (Best Model) - Loss: 1.3854 - Accuracy: 0.3088 - F1: 0.3069
sub_10:Test (Best Model) - Loss: 1.5156 - Accuracy: 0.2609 - F1: 0.2682
sub_10:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.2899 - F1: 0.3060
sub_10:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.2899 - F1: 0.2909
sub_10:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.3623 - F1: 0.3771
sub_10:Test (Best Model) - Loss: 1.4267 - Accuracy: 0.2464 - F1: 0.2615
sub_11:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.4058 - F1: 0.3739
sub_11:Test (Best Model) - Loss: 1.3374 - Accuracy: 0.4058 - F1: 0.3743
sub_11:Test (Best Model) - Loss: 1.3778 - Accuracy: 0.3333 - F1: 0.3292
sub_11:Test (Best Model) - Loss: 1.3115 - Accuracy: 0.3043 - F1: 0.2930
sub_11:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.3333 - F1: 0.3433
sub_11:Test (Best Model) - Loss: 1.2580 - Accuracy: 0.4638 - F1: 0.4251
sub_11:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.4638 - F1: 0.4463
sub_11:Test (Best Model) - Loss: 1.2034 - Accuracy: 0.4493 - F1: 0.4238
sub_11:Test (Best Model) - Loss: 1.3090 - Accuracy: 0.3768 - F1: 0.3256
sub_11:Test (Best Model) - Loss: 1.2541 - Accuracy: 0.4203 - F1: 0.3563
sub_11:Test (Best Model) - Loss: 1.3116 - Accuracy: 0.3478 - F1: 0.2837
sub_11:Test (Best Model) - Loss: 1.3279 - Accuracy: 0.3623 - F1: 0.3161
sub_11:Test (Best Model) - Loss: 1.2338 - Accuracy: 0.4783 - F1: 0.4418
sub_11:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.4203 - F1: 0.4092
sub_11:Test (Best Model) - Loss: 1.3056 - Accuracy: 0.3043 - F1: 0.2759
sub_12:Test (Best Model) - Loss: 1.0827 - Accuracy: 0.4559 - F1: 0.4488
sub_12:Test (Best Model) - Loss: 1.0480 - Accuracy: 0.5441 - F1: 0.5473
sub_12:Test (Best Model) - Loss: 1.0236 - Accuracy: 0.5735 - F1: 0.5557
sub_12:Test (Best Model) - Loss: 0.9840 - Accuracy: 0.5882 - F1: 0.5992
sub_12:Test (Best Model) - Loss: 0.9977 - Accuracy: 0.5735 - F1: 0.5786
sub_12:Test (Best Model) - Loss: 1.1044 - Accuracy: 0.5362 - F1: 0.5538
sub_12:Test (Best Model) - Loss: 1.0490 - Accuracy: 0.5072 - F1: 0.5375
sub_12:Test (Best Model) - Loss: 1.0642 - Accuracy: 0.5507 - F1: 0.5542
sub_12:Test (Best Model) - Loss: 1.0652 - Accuracy: 0.5652 - F1: 0.5653
sub_12:Test (Best Model) - Loss: 1.0230 - Accuracy: 0.5217 - F1: 0.5370
sub_12:Test (Best Model) - Loss: 1.1411 - Accuracy: 0.5000 - F1: 0.4939
sub_12:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.3676 - F1: 0.3632
sub_12:Test (Best Model) - Loss: 1.1549 - Accuracy: 0.4265 - F1: 0.4498
sub_12:Test (Best Model) - Loss: 1.2104 - Accuracy: 0.4412 - F1: 0.4620
sub_12:Test (Best Model) - Loss: 1.1063 - Accuracy: 0.5000 - F1: 0.5173
sub_13:Test (Best Model) - Loss: 1.2627 - Accuracy: 0.4118 - F1: 0.4361
sub_13:Test (Best Model) - Loss: 1.2492 - Accuracy: 0.4265 - F1: 0.4425
sub_13:Test (Best Model) - Loss: 1.1927 - Accuracy: 0.4118 - F1: 0.4478
sub_13:Test (Best Model) - Loss: 1.2764 - Accuracy: 0.3529 - F1: 0.3711
sub_13:Test (Best Model) - Loss: 1.2313 - Accuracy: 0.4559 - F1: 0.4789
sub_13:Test (Best Model) - Loss: 1.3067 - Accuracy: 0.4348 - F1: 0.4519
sub_13:Test (Best Model) - Loss: 1.3028 - Accuracy: 0.3623 - F1: 0.3607
sub_13:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.4348 - F1: 0.4307
sub_13:Test (Best Model) - Loss: 1.3359 - Accuracy: 0.4203 - F1: 0.4254
sub_13:Test (Best Model) - Loss: 1.2644 - Accuracy: 0.4348 - F1: 0.4528
sub_13:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.3676 - F1: 0.3856
sub_13:Test (Best Model) - Loss: 1.3498 - Accuracy: 0.3529 - F1: 0.3533
sub_13:Test (Best Model) - Loss: 1.3749 - Accuracy: 0.3971 - F1: 0.4281
sub_13:Test (Best Model) - Loss: 1.3257 - Accuracy: 0.4265 - F1: 0.4467
sub_13:Test (Best Model) - Loss: 1.3579 - Accuracy: 0.3382 - F1: 0.3526
sub_14:Test (Best Model) - Loss: 1.2793 - Accuracy: 0.3235 - F1: 0.3457
sub_14:Test (Best Model) - Loss: 1.2668 - Accuracy: 0.3824 - F1: 0.4229
sub_14:Test (Best Model) - Loss: 1.3124 - Accuracy: 0.3676 - F1: 0.3835
sub_14:Test (Best Model) - Loss: 1.3886 - Accuracy: 0.3088 - F1: 0.3338
sub_14:Test (Best Model) - Loss: 1.2972 - Accuracy: 0.3676 - F1: 0.3902
sub_14:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.3971 - F1: 0.4056
sub_14:Test (Best Model) - Loss: 1.3395 - Accuracy: 0.4118 - F1: 0.4183
sub_14:Test (Best Model) - Loss: 1.2595 - Accuracy: 0.4118 - F1: 0.4215
sub_14:Test (Best Model) - Loss: 1.3032 - Accuracy: 0.4265 - F1: 0.4501
sub_14:Test (Best Model) - Loss: 1.3016 - Accuracy: 0.3676 - F1: 0.3746
sub_14:Test (Best Model) - Loss: 1.3197 - Accuracy: 0.3382 - F1: 0.3569
sub_14:Test (Best Model) - Loss: 1.2700 - Accuracy: 0.3676 - F1: 0.3495
sub_14:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.3382 - F1: 0.3505
sub_14:Test (Best Model) - Loss: 1.2473 - Accuracy: 0.4559 - F1: 0.4405
sub_14:Test (Best Model) - Loss: 1.2676 - Accuracy: 0.3676 - F1: 0.3757
sub_15:Test (Best Model) - Loss: 1.1763 - Accuracy: 0.4118 - F1: 0.4460
sub_15:Test (Best Model) - Loss: 1.3630 - Accuracy: 0.3824 - F1: 0.4049
sub_15:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.4265 - F1: 0.4534
sub_15:Test (Best Model) - Loss: 1.1565 - Accuracy: 0.4559 - F1: 0.4886
sub_15:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.4412 - F1: 0.4676
sub_15:Test (Best Model) - Loss: 0.9462 - Accuracy: 0.6176 - F1: 0.6243
sub_15:Test (Best Model) - Loss: 1.1941 - Accuracy: 0.4706 - F1: 0.4707
sub_15:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.5735 - F1: 0.5891
sub_15:Test (Best Model) - Loss: 0.9888 - Accuracy: 0.5588 - F1: 0.5771
sub_15:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.5882 - F1: 0.5901
sub_15:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.5294 - F1: 0.5262
sub_15:Test (Best Model) - Loss: 1.1040 - Accuracy: 0.5000 - F1: 0.5205
sub_15:Test (Best Model) - Loss: 1.2012 - Accuracy: 0.4118 - F1: 0.4198
sub_15:Test (Best Model) - Loss: 1.1441 - Accuracy: 0.4412 - F1: 0.4282
sub_15:Test (Best Model) - Loss: 1.1949 - Accuracy: 0.4559 - F1: 0.4712
sub_16:Test (Best Model) - Loss: 1.1424 - Accuracy: 0.5000 - F1: 0.4267
sub_16:Test (Best Model) - Loss: 1.0972 - Accuracy: 0.5000 - F1: 0.4645
sub_16:Test (Best Model) - Loss: 1.0968 - Accuracy: 0.5147 - F1: 0.4862
sub_16:Test (Best Model) - Loss: 1.1338 - Accuracy: 0.5588 - F1: 0.5517
sub_16:Test (Best Model) - Loss: 1.1182 - Accuracy: 0.5294 - F1: 0.4671
sub_16:Test (Best Model) - Loss: 1.2503 - Accuracy: 0.4118 - F1: 0.3956
sub_16:Test (Best Model) - Loss: 1.2422 - Accuracy: 0.3529 - F1: 0.3216
sub_16:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.4412 - F1: 0.4103
sub_16:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.3824 - F1: 0.3578
sub_16:Test (Best Model) - Loss: 1.5317 - Accuracy: 0.3971 - F1: 0.3607
sub_16:Test (Best Model) - Loss: 1.1320 - Accuracy: 0.5147 - F1: 0.4246
sub_16:Test (Best Model) - Loss: 1.0966 - Accuracy: 0.5294 - F1: 0.4548
sub_16:Test (Best Model) - Loss: 1.1566 - Accuracy: 0.5294 - F1: 0.4738
sub_16:Test (Best Model) - Loss: 1.1490 - Accuracy: 0.5147 - F1: 0.4956
sub_16:Test (Best Model) - Loss: 1.1743 - Accuracy: 0.5147 - F1: 0.4569
sub_17:Test (Best Model) - Loss: 1.2036 - Accuracy: 0.4203 - F1: 0.3908
sub_17:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.3768 - F1: 0.3189
sub_17:Test (Best Model) - Loss: 1.1741 - Accuracy: 0.4058 - F1: 0.3820
sub_17:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.4058 - F1: 0.4103
sub_17:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.4493 - F1: 0.4442
sub_17:Test (Best Model) - Loss: 1.4923 - Accuracy: 0.4058 - F1: 0.3819
sub_17:Test (Best Model) - Loss: 1.5393 - Accuracy: 0.3623 - F1: 0.3126
sub_17:Test (Best Model) - Loss: 1.4795 - Accuracy: 0.4348 - F1: 0.3778
sub_17:Test (Best Model) - Loss: 1.4988 - Accuracy: 0.3913 - F1: 0.3507
sub_17:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.4058 - F1: 0.3598
sub_17:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.4706 - F1: 0.4710
sub_17:Test (Best Model) - Loss: 1.1884 - Accuracy: 0.4853 - F1: 0.4747
sub_17:Test (Best Model) - Loss: 1.2744 - Accuracy: 0.4412 - F1: 0.4521
sub_17:Test (Best Model) - Loss: 1.2102 - Accuracy: 0.4559 - F1: 0.4679
sub_17:Test (Best Model) - Loss: 1.2398 - Accuracy: 0.4118 - F1: 0.4063
sub_18:Test (Best Model) - Loss: 1.1956 - Accuracy: 0.4203 - F1: 0.4481
sub_18:Test (Best Model) - Loss: 1.2041 - Accuracy: 0.4058 - F1: 0.4305
sub_18:Test (Best Model) - Loss: 1.1768 - Accuracy: 0.4928 - F1: 0.4720
sub_18:Test (Best Model) - Loss: 1.1976 - Accuracy: 0.4928 - F1: 0.5113
sub_18:Test (Best Model) - Loss: 1.1908 - Accuracy: 0.4928 - F1: 0.5211
sub_18:Test (Best Model) - Loss: 1.3034 - Accuracy: 0.3382 - F1: 0.3613
sub_18:Test (Best Model) - Loss: 1.3387 - Accuracy: 0.3382 - F1: 0.3644
sub_18:Test (Best Model) - Loss: 1.3529 - Accuracy: 0.3235 - F1: 0.3643
sub_18:Test (Best Model) - Loss: 1.3341 - Accuracy: 0.3529 - F1: 0.3812
sub_18:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.3676 - F1: 0.4003
sub_18:Test (Best Model) - Loss: 1.2243 - Accuracy: 0.3971 - F1: 0.4311
sub_18:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.2941 - F1: 0.3128
sub_18:Test (Best Model) - Loss: 1.2647 - Accuracy: 0.3382 - F1: 0.3677
sub_18:Test (Best Model) - Loss: 1.2475 - Accuracy: 0.3824 - F1: 0.4145
sub_18:Test (Best Model) - Loss: 1.2284 - Accuracy: 0.3824 - F1: 0.4128
sub_19:Test (Best Model) - Loss: 1.5849 - Accuracy: 0.2206 - F1: 0.2125
sub_19:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.2059 - F1: 0.2294
sub_19:Test (Best Model) - Loss: 1.4634 - Accuracy: 0.2059 - F1: 0.2152
sub_19:Test (Best Model) - Loss: 1.4332 - Accuracy: 0.2647 - F1: 0.2750
sub_19:Test (Best Model) - Loss: 1.4425 - Accuracy: 0.2794 - F1: 0.2917
sub_19:Test (Best Model) - Loss: 1.2112 - Accuracy: 0.4853 - F1: 0.4740
sub_19:Test (Best Model) - Loss: 1.2135 - Accuracy: 0.4559 - F1: 0.4113
sub_19:Test (Best Model) - Loss: 1.1818 - Accuracy: 0.5294 - F1: 0.5500
sub_19:Test (Best Model) - Loss: 1.1812 - Accuracy: 0.4853 - F1: 0.4786
sub_19:Test (Best Model) - Loss: 1.1476 - Accuracy: 0.5588 - F1: 0.5586
sub_19:Test (Best Model) - Loss: 1.3070 - Accuracy: 0.3676 - F1: 0.3511
sub_19:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.3382 - F1: 0.3298
sub_19:Test (Best Model) - Loss: 1.2637 - Accuracy: 0.3529 - F1: 0.3380
sub_19:Test (Best Model) - Loss: 1.3824 - Accuracy: 0.3529 - F1: 0.3707
sub_19:Test (Best Model) - Loss: 1.2581 - Accuracy: 0.3529 - F1: 0.3421
sub_20:Test (Best Model) - Loss: 1.0674 - Accuracy: 0.5588 - F1: 0.5824
sub_20:Test (Best Model) - Loss: 1.0596 - Accuracy: 0.5588 - F1: 0.5773
sub_20:Test (Best Model) - Loss: 1.0960 - Accuracy: 0.5588 - F1: 0.5745
sub_20:Test (Best Model) - Loss: 1.0910 - Accuracy: 0.5147 - F1: 0.5256
sub_20:Test (Best Model) - Loss: 1.1077 - Accuracy: 0.5882 - F1: 0.5975
sub_20:Test (Best Model) - Loss: 1.2063 - Accuracy: 0.3824 - F1: 0.3727
sub_20:Test (Best Model) - Loss: 1.1776 - Accuracy: 0.4412 - F1: 0.4386
sub_20:Test (Best Model) - Loss: 1.1890 - Accuracy: 0.5000 - F1: 0.5109
sub_20:Test (Best Model) - Loss: 1.2226 - Accuracy: 0.3971 - F1: 0.4095
sub_20:Test (Best Model) - Loss: 1.2017 - Accuracy: 0.4559 - F1: 0.4581
sub_20:Test (Best Model) - Loss: 1.1347 - Accuracy: 0.4783 - F1: 0.4928
sub_20:Test (Best Model) - Loss: 1.1985 - Accuracy: 0.4203 - F1: 0.4222
sub_20:Test (Best Model) - Loss: 1.2721 - Accuracy: 0.3768 - F1: 0.4027
sub_20:Test (Best Model) - Loss: 1.1514 - Accuracy: 0.4783 - F1: 0.4821
sub_20:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.5362 - F1: 0.5376
sub_21:Test (Best Model) - Loss: 1.1172 - Accuracy: 0.4265 - F1: 0.4143
sub_21:Test (Best Model) - Loss: 1.1468 - Accuracy: 0.4265 - F1: 0.3820
sub_21:Test (Best Model) - Loss: 1.2887 - Accuracy: 0.4118 - F1: 0.3718
sub_21:Test (Best Model) - Loss: 1.2749 - Accuracy: 0.4559 - F1: 0.4133
sub_21:Test (Best Model) - Loss: 1.3067 - Accuracy: 0.3971 - F1: 0.3500
sub_21:Test (Best Model) - Loss: 1.1989 - Accuracy: 0.4118 - F1: 0.3783
sub_21:Test (Best Model) - Loss: 1.1518 - Accuracy: 0.4559 - F1: 0.4515
sub_21:Test (Best Model) - Loss: 1.1219 - Accuracy: 0.4118 - F1: 0.3614
sub_21:Test (Best Model) - Loss: 1.1502 - Accuracy: 0.4412 - F1: 0.4151
sub_21:Test (Best Model) - Loss: 1.0463 - Accuracy: 0.5294 - F1: 0.4796
sub_21:Test (Best Model) - Loss: 1.1450 - Accuracy: 0.4706 - F1: 0.4354
sub_21:Test (Best Model) - Loss: 1.1799 - Accuracy: 0.3971 - F1: 0.3666
sub_21:Test (Best Model) - Loss: 1.1199 - Accuracy: 0.4412 - F1: 0.3868
sub_21:Test (Best Model) - Loss: 1.1436 - Accuracy: 0.4118 - F1: 0.4054
sub_21:Test (Best Model) - Loss: 1.1017 - Accuracy: 0.4706 - F1: 0.4274
sub_22:Test (Best Model) - Loss: 1.3294 - Accuracy: 0.3971 - F1: 0.4256
sub_22:Test (Best Model) - Loss: 1.2930 - Accuracy: 0.4118 - F1: 0.4042
sub_22:Test (Best Model) - Loss: 1.3146 - Accuracy: 0.3971 - F1: 0.4072
sub_22:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.4118 - F1: 0.4150
sub_22:Test (Best Model) - Loss: 1.3661 - Accuracy: 0.4265 - F1: 0.4528
sub_22:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.3478 - F1: 0.3356
sub_22:Test (Best Model) - Loss: 1.2596 - Accuracy: 0.3768 - F1: 0.3444
sub_22:Test (Best Model) - Loss: 1.2230 - Accuracy: 0.3768 - F1: 0.3670
sub_22:Test (Best Model) - Loss: 1.2598 - Accuracy: 0.4058 - F1: 0.4008
sub_22:Test (Best Model) - Loss: 1.2642 - Accuracy: 0.3188 - F1: 0.3137
sub_22:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.4265 - F1: 0.4588
sub_22:Test (Best Model) - Loss: 1.2208 - Accuracy: 0.3529 - F1: 0.3829
sub_22:Test (Best Model) - Loss: 1.2321 - Accuracy: 0.3971 - F1: 0.4259
sub_22:Test (Best Model) - Loss: 1.1994 - Accuracy: 0.3971 - F1: 0.4306
sub_22:Test (Best Model) - Loss: 1.2325 - Accuracy: 0.4559 - F1: 0.4867
sub_23:Test (Best Model) - Loss: 1.1367 - Accuracy: 0.4638 - F1: 0.4841
sub_23:Test (Best Model) - Loss: 1.1201 - Accuracy: 0.4058 - F1: 0.4168
sub_23:Test (Best Model) - Loss: 1.1396 - Accuracy: 0.3768 - F1: 0.3888
sub_23:Test (Best Model) - Loss: 1.0465 - Accuracy: 0.5217 - F1: 0.5445
sub_23:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.4203 - F1: 0.4286
sub_23:Test (Best Model) - Loss: 1.1496 - Accuracy: 0.4706 - F1: 0.4393
sub_23:Test (Best Model) - Loss: 1.1358 - Accuracy: 0.4412 - F1: 0.4507
sub_23:Test (Best Model) - Loss: 1.0595 - Accuracy: 0.5882 - F1: 0.5858
sub_23:Test (Best Model) - Loss: 1.0957 - Accuracy: 0.5441 - F1: 0.5370
sub_23:Test (Best Model) - Loss: 1.0961 - Accuracy: 0.5441 - F1: 0.5320
sub_23:Test (Best Model) - Loss: 1.2874 - Accuracy: 0.3913 - F1: 0.4064
sub_23:Test (Best Model) - Loss: 1.2039 - Accuracy: 0.4203 - F1: 0.4136
sub_23:Test (Best Model) - Loss: 1.1161 - Accuracy: 0.4928 - F1: 0.4768
sub_23:Test (Best Model) - Loss: 1.2044 - Accuracy: 0.4928 - F1: 0.5013
sub_23:Test (Best Model) - Loss: 1.2138 - Accuracy: 0.3768 - F1: 0.3761
sub_24:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.3676 - F1: 0.3558
sub_24:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3824 - F1: 0.3756
sub_24:Test (Best Model) - Loss: 1.3792 - Accuracy: 0.2794 - F1: 0.2799
sub_24:Test (Best Model) - Loss: 1.4296 - Accuracy: 0.3235 - F1: 0.3126
sub_24:Test (Best Model) - Loss: 1.3939 - Accuracy: 0.2353 - F1: 0.2406
sub_24:Test (Best Model) - Loss: 1.3197 - Accuracy: 0.3824 - F1: 0.3737
sub_24:Test (Best Model) - Loss: 1.3418 - Accuracy: 0.4118 - F1: 0.4158
sub_24:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.3088 - F1: 0.2839
sub_24:Test (Best Model) - Loss: 1.3018 - Accuracy: 0.3971 - F1: 0.3996
sub_24:Test (Best Model) - Loss: 1.2712 - Accuracy: 0.3235 - F1: 0.3237
sub_24:Test (Best Model) - Loss: 1.4414 - Accuracy: 0.2206 - F1: 0.2167
sub_24:Test (Best Model) - Loss: 1.4730 - Accuracy: 0.2500 - F1: 0.2551
sub_24:Test (Best Model) - Loss: 1.4004 - Accuracy: 0.2647 - F1: 0.2651
sub_24:Test (Best Model) - Loss: 1.4486 - Accuracy: 0.3382 - F1: 0.3396
sub_24:Test (Best Model) - Loss: 1.4270 - Accuracy: 0.3088 - F1: 0.3084
sub_25:Test (Best Model) - Loss: 1.1363 - Accuracy: 0.5652 - F1: 0.4932
sub_25:Test (Best Model) - Loss: 1.1938 - Accuracy: 0.4638 - F1: 0.3894
sub_25:Test (Best Model) - Loss: 1.2010 - Accuracy: 0.4203 - F1: 0.3671
sub_25:Test (Best Model) - Loss: 1.1914 - Accuracy: 0.4638 - F1: 0.4160
sub_25:Test (Best Model) - Loss: 1.2325 - Accuracy: 0.4203 - F1: 0.3881
sub_25:Test (Best Model) - Loss: 1.2747 - Accuracy: 0.4853 - F1: 0.4318
sub_25:Test (Best Model) - Loss: 1.2640 - Accuracy: 0.4853 - F1: 0.3955
sub_25:Test (Best Model) - Loss: 1.2253 - Accuracy: 0.5441 - F1: 0.5072
sub_25:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.5294 - F1: 0.4391
sub_25:Test (Best Model) - Loss: 1.2420 - Accuracy: 0.5000 - F1: 0.4363
sub_25:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.4706 - F1: 0.4757
sub_25:Test (Best Model) - Loss: 1.2360 - Accuracy: 0.5147 - F1: 0.4959
sub_25:Test (Best Model) - Loss: 1.1739 - Accuracy: 0.4559 - F1: 0.4335
sub_25:Test (Best Model) - Loss: 1.2372 - Accuracy: 0.3676 - F1: 0.3185
sub_25:Test (Best Model) - Loss: 1.2099 - Accuracy: 0.4412 - F1: 0.3885
sub_26:Test (Best Model) - Loss: 1.0999 - Accuracy: 0.4348 - F1: 0.4374
sub_26:Test (Best Model) - Loss: 1.1368 - Accuracy: 0.4638 - F1: 0.4689
sub_26:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.4638 - F1: 0.4509
sub_26:Test (Best Model) - Loss: 1.0260 - Accuracy: 0.6232 - F1: 0.6218
sub_26:Test (Best Model) - Loss: 1.0447 - Accuracy: 0.5797 - F1: 0.5956
sub_26:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.4118 - F1: 0.4398
sub_26:Test (Best Model) - Loss: 1.1817 - Accuracy: 0.4559 - F1: 0.4731
sub_26:Test (Best Model) - Loss: 1.2258 - Accuracy: 0.3971 - F1: 0.4073
sub_26:Test (Best Model) - Loss: 1.2130 - Accuracy: 0.3971 - F1: 0.4170
sub_26:Test (Best Model) - Loss: 1.2234 - Accuracy: 0.3088 - F1: 0.3487
sub_26:Test (Best Model) - Loss: 1.1252 - Accuracy: 0.5000 - F1: 0.5224
sub_26:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.5588 - F1: 0.5746
sub_26:Test (Best Model) - Loss: 1.1614 - Accuracy: 0.5294 - F1: 0.5476
sub_26:Test (Best Model) - Loss: 1.1342 - Accuracy: 0.5588 - F1: 0.5840
sub_26:Test (Best Model) - Loss: 1.2163 - Accuracy: 0.4853 - F1: 0.5096
sub_27:Test (Best Model) - Loss: 1.2036 - Accuracy: 0.4203 - F1: 0.3908
sub_27:Test (Best Model) - Loss: 1.1678 - Accuracy: 0.3768 - F1: 0.3189
sub_27:Test (Best Model) - Loss: 1.1741 - Accuracy: 0.4058 - F1: 0.3820
sub_27:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.4058 - F1: 0.4103
sub_27:Test (Best Model) - Loss: 1.1383 - Accuracy: 0.4493 - F1: 0.4442
sub_27:Test (Best Model) - Loss: 1.4923 - Accuracy: 0.4058 - F1: 0.3819
sub_27:Test (Best Model) - Loss: 1.5393 - Accuracy: 0.3623 - F1: 0.3126
sub_27:Test (Best Model) - Loss: 1.4795 - Accuracy: 0.4348 - F1: 0.3778
sub_27:Test (Best Model) - Loss: 1.4988 - Accuracy: 0.3913 - F1: 0.3507
sub_27:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.4058 - F1: 0.3598
sub_27:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.4706 - F1: 0.4710
sub_27:Test (Best Model) - Loss: 1.1884 - Accuracy: 0.4853 - F1: 0.4747
sub_27:Test (Best Model) - Loss: 1.2744 - Accuracy: 0.4412 - F1: 0.4521
sub_27:Test (Best Model) - Loss: 1.2102 - Accuracy: 0.4559 - F1: 0.4679
sub_27:Test (Best Model) - Loss: 1.2398 - Accuracy: 0.4118 - F1: 0.4063
sub_28:Test (Best Model) - Loss: 1.3741 - Accuracy: 0.4118 - F1: 0.4123
sub_28:Test (Best Model) - Loss: 1.4386 - Accuracy: 0.3529 - F1: 0.3303
sub_28:Test (Best Model) - Loss: 1.5399 - Accuracy: 0.2941 - F1: 0.3017
sub_28:Test (Best Model) - Loss: 1.4520 - Accuracy: 0.2647 - F1: 0.2766
sub_28:Test (Best Model) - Loss: 1.5255 - Accuracy: 0.2353 - F1: 0.2503
sub_28:Test (Best Model) - Loss: 1.8703 - Accuracy: 0.2206 - F1: 0.1684
sub_28:Test (Best Model) - Loss: 1.8366 - Accuracy: 0.2647 - F1: 0.2156
sub_28:Test (Best Model) - Loss: 1.7734 - Accuracy: 0.2206 - F1: 0.1788
sub_28:Test (Best Model) - Loss: 1.7769 - Accuracy: 0.2500 - F1: 0.2184
sub_28:Test (Best Model) - Loss: 1.8568 - Accuracy: 0.2206 - F1: 0.1798
sub_28:Test (Best Model) - Loss: 1.2942 - Accuracy: 0.3676 - F1: 0.3129
sub_28:Test (Best Model) - Loss: 1.2323 - Accuracy: 0.4412 - F1: 0.4139
sub_28:Test (Best Model) - Loss: 1.2440 - Accuracy: 0.4559 - F1: 0.4212
sub_28:Test (Best Model) - Loss: 1.2695 - Accuracy: 0.4559 - F1: 0.4479
sub_28:Test (Best Model) - Loss: 1.2801 - Accuracy: 0.5000 - F1: 0.4730
sub_29:Test (Best Model) - Loss: 1.0925 - Accuracy: 0.5588 - F1: 0.5685
sub_29:Test (Best Model) - Loss: 1.0657 - Accuracy: 0.5294 - F1: 0.5411
sub_29:Test (Best Model) - Loss: 1.0439 - Accuracy: 0.5441 - F1: 0.5233
sub_29:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.5294 - F1: 0.5321
sub_29:Test (Best Model) - Loss: 1.0772 - Accuracy: 0.5000 - F1: 0.5071
sub_29:Test (Best Model) - Loss: 0.8989 - Accuracy: 0.6029 - F1: 0.6241
sub_29:Test (Best Model) - Loss: 0.9034 - Accuracy: 0.5441 - F1: 0.5616
sub_29:Test (Best Model) - Loss: 0.8929 - Accuracy: 0.5735 - F1: 0.5921
sub_29:Test (Best Model) - Loss: 0.8794 - Accuracy: 0.6912 - F1: 0.7083
sub_29:Test (Best Model) - Loss: 0.8892 - Accuracy: 0.5882 - F1: 0.6103
sub_29:Test (Best Model) - Loss: 0.8733 - Accuracy: 0.5797 - F1: 0.5981
sub_29:Test (Best Model) - Loss: 0.9128 - Accuracy: 0.6087 - F1: 0.6273
sub_29:Test (Best Model) - Loss: 0.9982 - Accuracy: 0.4638 - F1: 0.4859
sub_29:Test (Best Model) - Loss: 0.8826 - Accuracy: 0.6957 - F1: 0.7063
sub_29:Test (Best Model) - Loss: 0.9223 - Accuracy: 0.6232 - F1: 0.6329

=== Summary Results ===

acc: 42.67 ± 7.01
F1: 42.31 ± 7.32
acc-in: 52.20 ± 6.60
F1-in: 50.79 ± 6.82
