lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.1799 - Accuracy: 0.4412 - F1: 0.4799
sub_1:Test (Best Model) - Loss: 1.1771 - Accuracy: 0.4559 - F1: 0.4873
sub_1:Test (Best Model) - Loss: 1.2017 - Accuracy: 0.3971 - F1: 0.4344
sub_1:Test (Best Model) - Loss: 1.0964 - Accuracy: 0.5000 - F1: 0.5293
sub_1:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.4559 - F1: 0.4911
sub_1:Test (Best Model) - Loss: 1.2208 - Accuracy: 0.3913 - F1: 0.3908
sub_1:Test (Best Model) - Loss: 1.2842 - Accuracy: 0.3623 - F1: 0.3619
sub_1:Test (Best Model) - Loss: 1.2609 - Accuracy: 0.4493 - F1: 0.4503
sub_1:Test (Best Model) - Loss: 1.2422 - Accuracy: 0.4058 - F1: 0.4023
sub_1:Test (Best Model) - Loss: 1.2242 - Accuracy: 0.4058 - F1: 0.4022
sub_1:Test (Best Model) - Loss: 1.1478 - Accuracy: 0.4706 - F1: 0.4470
sub_1:Test (Best Model) - Loss: 1.0814 - Accuracy: 0.6029 - F1: 0.5803
sub_1:Test (Best Model) - Loss: 1.0367 - Accuracy: 0.5441 - F1: 0.5406
sub_1:Test (Best Model) - Loss: 1.1553 - Accuracy: 0.5000 - F1: 0.4837
sub_1:Test (Best Model) - Loss: 1.1042 - Accuracy: 0.5147 - F1: 0.5037
sub_2:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.2464 - F1: 0.2748
sub_2:Test (Best Model) - Loss: 1.4200 - Accuracy: 0.2754 - F1: 0.3070
sub_2:Test (Best Model) - Loss: 1.4296 - Accuracy: 0.2319 - F1: 0.2552
sub_2:Test (Best Model) - Loss: 1.4099 - Accuracy: 0.2464 - F1: 0.2714
sub_2:Test (Best Model) - Loss: 1.5216 - Accuracy: 0.2754 - F1: 0.2948
sub_2:Test (Best Model) - Loss: 1.3612 - Accuracy: 0.3676 - F1: 0.3647
sub_2:Test (Best Model) - Loss: 1.3666 - Accuracy: 0.3235 - F1: 0.3615
sub_2:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.3971 - F1: 0.4260
sub_2:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3088 - F1: 0.3324
sub_2:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.3529 - F1: 0.3750
sub_2:Test (Best Model) - Loss: 1.4250 - Accuracy: 0.3623 - F1: 0.3464
sub_2:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.2754 - F1: 0.2670
sub_2:Test (Best Model) - Loss: 1.3044 - Accuracy: 0.4638 - F1: 0.4601
sub_2:Test (Best Model) - Loss: 1.2751 - Accuracy: 0.4493 - F1: 0.4375
sub_2:Test (Best Model) - Loss: 1.3433 - Accuracy: 0.3478 - F1: 0.3480
sub_3:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.3529 - F1: 0.3460
sub_3:Test (Best Model) - Loss: 1.3415 - Accuracy: 0.3235 - F1: 0.3157
sub_3:Test (Best Model) - Loss: 1.4204 - Accuracy: 0.2647 - F1: 0.2826
sub_3:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.2794 - F1: 0.2809
sub_3:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.2941 - F1: 0.2606
sub_3:Test (Best Model) - Loss: 1.3706 - Accuracy: 0.3333 - F1: 0.3136
sub_3:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.2754 - F1: 0.2538
sub_3:Test (Best Model) - Loss: 1.3831 - Accuracy: 0.2319 - F1: 0.2234
sub_3:Test (Best Model) - Loss: 1.3506 - Accuracy: 0.4058 - F1: 0.3952
sub_3:Test (Best Model) - Loss: 1.3754 - Accuracy: 0.3333 - F1: 0.3332
sub_3:Test (Best Model) - Loss: 1.4435 - Accuracy: 0.2754 - F1: 0.2600
sub_3:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.3478 - F1: 0.3052
sub_3:Test (Best Model) - Loss: 1.3983 - Accuracy: 0.3333 - F1: 0.3231
sub_3:Test (Best Model) - Loss: 1.3987 - Accuracy: 0.3623 - F1: 0.3447
sub_3:Test (Best Model) - Loss: 1.4190 - Accuracy: 0.3333 - F1: 0.3094
sub_4:Test (Best Model) - Loss: 1.0393 - Accuracy: 0.5217 - F1: 0.5492
sub_4:Test (Best Model) - Loss: 0.9538 - Accuracy: 0.5942 - F1: 0.6191
sub_4:Test (Best Model) - Loss: 1.1038 - Accuracy: 0.4928 - F1: 0.5182
sub_4:Test (Best Model) - Loss: 0.9463 - Accuracy: 0.5797 - F1: 0.5964
sub_4:Test (Best Model) - Loss: 0.9965 - Accuracy: 0.5362 - F1: 0.5387
sub_4:Test (Best Model) - Loss: 1.0535 - Accuracy: 0.4928 - F1: 0.5031
sub_4:Test (Best Model) - Loss: 1.0100 - Accuracy: 0.6087 - F1: 0.6232
sub_4:Test (Best Model) - Loss: 0.9641 - Accuracy: 0.6232 - F1: 0.6416
sub_4:Test (Best Model) - Loss: 0.9896 - Accuracy: 0.5507 - F1: 0.5651
sub_4:Test (Best Model) - Loss: 0.9978 - Accuracy: 0.5362 - F1: 0.5628
sub_4:Test (Best Model) - Loss: 1.1391 - Accuracy: 0.4638 - F1: 0.4359
sub_4:Test (Best Model) - Loss: 1.0905 - Accuracy: 0.4783 - F1: 0.4796
sub_4:Test (Best Model) - Loss: 1.0618 - Accuracy: 0.4638 - F1: 0.4670
sub_4:Test (Best Model) - Loss: 1.0797 - Accuracy: 0.4493 - F1: 0.4566
sub_4:Test (Best Model) - Loss: 1.0557 - Accuracy: 0.5507 - F1: 0.5587
sub_5:Test (Best Model) - Loss: 1.5299 - Accuracy: 0.5000 - F1: 0.4653
sub_5:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.4853 - F1: 0.4553
sub_5:Test (Best Model) - Loss: 1.6736 - Accuracy: 0.4412 - F1: 0.4265
sub_5:Test (Best Model) - Loss: 1.5010 - Accuracy: 0.4412 - F1: 0.4278
sub_5:Test (Best Model) - Loss: 1.5418 - Accuracy: 0.4706 - F1: 0.4424
sub_5:Test (Best Model) - Loss: 1.0807 - Accuracy: 0.5000 - F1: 0.4715
sub_5:Test (Best Model) - Loss: 1.0137 - Accuracy: 0.5735 - F1: 0.5610
sub_5:Test (Best Model) - Loss: 1.0592 - Accuracy: 0.5000 - F1: 0.5020
sub_5:Test (Best Model) - Loss: 1.0374 - Accuracy: 0.5294 - F1: 0.5116
sub_5:Test (Best Model) - Loss: 1.0756 - Accuracy: 0.4853 - F1: 0.4582
sub_5:Test (Best Model) - Loss: 1.0966 - Accuracy: 0.4559 - F1: 0.4599
sub_5:Test (Best Model) - Loss: 1.1469 - Accuracy: 0.4265 - F1: 0.4155
sub_5:Test (Best Model) - Loss: 1.1576 - Accuracy: 0.3971 - F1: 0.4019
sub_5:Test (Best Model) - Loss: 1.1262 - Accuracy: 0.3676 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 1.0793 - Accuracy: 0.4118 - F1: 0.3952
sub_6:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4265 - F1: 0.4506
sub_6:Test (Best Model) - Loss: 1.1597 - Accuracy: 0.4118 - F1: 0.4295
sub_6:Test (Best Model) - Loss: 1.1391 - Accuracy: 0.4265 - F1: 0.4293
sub_6:Test (Best Model) - Loss: 1.1476 - Accuracy: 0.4706 - F1: 0.4944
sub_6:Test (Best Model) - Loss: 1.1398 - Accuracy: 0.4559 - F1: 0.4738
sub_6:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.4783 - F1: 0.4104
sub_6:Test (Best Model) - Loss: 1.2098 - Accuracy: 0.5217 - F1: 0.4601
sub_6:Test (Best Model) - Loss: 1.2264 - Accuracy: 0.4058 - F1: 0.3298
sub_6:Test (Best Model) - Loss: 1.2254 - Accuracy: 0.4203 - F1: 0.3321
sub_6:Test (Best Model) - Loss: 1.2192 - Accuracy: 0.4493 - F1: 0.3803
sub_6:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.3623 - F1: 0.3830
sub_6:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.4783 - F1: 0.5055
sub_6:Test (Best Model) - Loss: 1.2588 - Accuracy: 0.4493 - F1: 0.4676
sub_6:Test (Best Model) - Loss: 1.2124 - Accuracy: 0.4348 - F1: 0.4491
sub_6:Test (Best Model) - Loss: 1.1698 - Accuracy: 0.5072 - F1: 0.5284
sub_7:Test (Best Model) - Loss: 1.0546 - Accuracy: 0.5588 - F1: 0.5529
sub_7:Test (Best Model) - Loss: 1.0200 - Accuracy: 0.5441 - F1: 0.5193
sub_7:Test (Best Model) - Loss: 1.0258 - Accuracy: 0.4706 - F1: 0.4550
sub_7:Test (Best Model) - Loss: 0.9435 - Accuracy: 0.6324 - F1: 0.6257
sub_7:Test (Best Model) - Loss: 1.0069 - Accuracy: 0.5735 - F1: 0.5601
sub_7:Test (Best Model) - Loss: 1.2487 - Accuracy: 0.3824 - F1: 0.3677
sub_7:Test (Best Model) - Loss: 1.2192 - Accuracy: 0.4265 - F1: 0.4122
sub_7:Test (Best Model) - Loss: 1.2256 - Accuracy: 0.4118 - F1: 0.4205
sub_7:Test (Best Model) - Loss: 1.2121 - Accuracy: 0.5147 - F1: 0.4937
sub_7:Test (Best Model) - Loss: 1.1430 - Accuracy: 0.4706 - F1: 0.4225
sub_7:Test (Best Model) - Loss: 1.1397 - Accuracy: 0.5441 - F1: 0.5446
sub_7:Test (Best Model) - Loss: 1.1269 - Accuracy: 0.5294 - F1: 0.5171
sub_7:Test (Best Model) - Loss: 1.1515 - Accuracy: 0.5147 - F1: 0.5131
sub_7:Test (Best Model) - Loss: 1.1753 - Accuracy: 0.5294 - F1: 0.5288
sub_7:Test (Best Model) - Loss: 1.1996 - Accuracy: 0.4853 - F1: 0.4944
sub_8:Test (Best Model) - Loss: 1.4641 - Accuracy: 0.3088 - F1: 0.3281
sub_8:Test (Best Model) - Loss: 1.5013 - Accuracy: 0.2647 - F1: 0.2492
sub_8:Test (Best Model) - Loss: 1.4650 - Accuracy: 0.2353 - F1: 0.2637
sub_8:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.3235 - F1: 0.3255
sub_8:Test (Best Model) - Loss: 1.4784 - Accuracy: 0.3235 - F1: 0.3385
sub_8:Test (Best Model) - Loss: 1.3362 - Accuracy: 0.3824 - F1: 0.4022
sub_8:Test (Best Model) - Loss: 1.3769 - Accuracy: 0.3382 - F1: 0.3489
sub_8:Test (Best Model) - Loss: 1.2920 - Accuracy: 0.4118 - F1: 0.4255
sub_8:Test (Best Model) - Loss: 1.3683 - Accuracy: 0.3382 - F1: 0.3294
sub_8:Test (Best Model) - Loss: 1.3151 - Accuracy: 0.3676 - F1: 0.3905
sub_8:Test (Best Model) - Loss: 1.4620 - Accuracy: 0.3088 - F1: 0.3054
sub_8:Test (Best Model) - Loss: 1.4323 - Accuracy: 0.3824 - F1: 0.4113
sub_8:Test (Best Model) - Loss: 1.4274 - Accuracy: 0.3676 - F1: 0.3833
sub_8:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.4559 - F1: 0.4839
sub_8:Test (Best Model) - Loss: 1.3979 - Accuracy: 0.3676 - F1: 0.3833
sub_9:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.5735 - F1: 0.5930
sub_9:Test (Best Model) - Loss: 1.0817 - Accuracy: 0.5000 - F1: 0.5256
sub_9:Test (Best Model) - Loss: 1.0876 - Accuracy: 0.4853 - F1: 0.5143
sub_9:Test (Best Model) - Loss: 1.0455 - Accuracy: 0.5000 - F1: 0.5281
sub_9:Test (Best Model) - Loss: 1.0120 - Accuracy: 0.6176 - F1: 0.6251
sub_9:Test (Best Model) - Loss: 1.3559 - Accuracy: 0.3235 - F1: 0.3388
sub_9:Test (Best Model) - Loss: 1.3628 - Accuracy: 0.3382 - F1: 0.3595
sub_9:Test (Best Model) - Loss: 1.2424 - Accuracy: 0.3824 - F1: 0.3952
sub_9:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.4412 - F1: 0.4532
sub_9:Test (Best Model) - Loss: 1.2577 - Accuracy: 0.3235 - F1: 0.3481
sub_9:Test (Best Model) - Loss: 1.3212 - Accuracy: 0.3676 - F1: 0.3967
sub_9:Test (Best Model) - Loss: 1.3176 - Accuracy: 0.3971 - F1: 0.4093
sub_9:Test (Best Model) - Loss: 1.2681 - Accuracy: 0.4412 - F1: 0.4620
sub_9:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.3824 - F1: 0.4136
sub_9:Test (Best Model) - Loss: 1.2299 - Accuracy: 0.3971 - F1: 0.4246
sub_10:Test (Best Model) - Loss: 1.4093 - Accuracy: 0.2941 - F1: 0.2699
sub_10:Test (Best Model) - Loss: 1.3730 - Accuracy: 0.3676 - F1: 0.3590
sub_10:Test (Best Model) - Loss: 1.3913 - Accuracy: 0.3382 - F1: 0.3304
sub_10:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.3676 - F1: 0.3750
sub_10:Test (Best Model) - Loss: 1.3936 - Accuracy: 0.3676 - F1: 0.3841
sub_10:Test (Best Model) - Loss: 1.3734 - Accuracy: 0.3235 - F1: 0.3057
sub_10:Test (Best Model) - Loss: 1.4269 - Accuracy: 0.2353 - F1: 0.2225
sub_10:Test (Best Model) - Loss: 1.4064 - Accuracy: 0.2794 - F1: 0.2658
sub_10:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.2794 - F1: 0.2789
sub_10:Test (Best Model) - Loss: 1.3996 - Accuracy: 0.3088 - F1: 0.3020
sub_10:Test (Best Model) - Loss: 1.5214 - Accuracy: 0.3043 - F1: 0.3138
sub_10:Test (Best Model) - Loss: 1.4333 - Accuracy: 0.2899 - F1: 0.3114
sub_10:Test (Best Model) - Loss: 1.4259 - Accuracy: 0.3478 - F1: 0.3654
sub_10:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.3768 - F1: 0.3808
sub_10:Test (Best Model) - Loss: 1.4329 - Accuracy: 0.3333 - F1: 0.3374
sub_11:Test (Best Model) - Loss: 1.3293 - Accuracy: 0.3913 - F1: 0.3628
sub_11:Test (Best Model) - Loss: 1.3184 - Accuracy: 0.3913 - F1: 0.3637
sub_11:Test (Best Model) - Loss: 1.3291 - Accuracy: 0.3188 - F1: 0.3144
sub_11:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.3478 - F1: 0.3503
sub_11:Test (Best Model) - Loss: 1.3411 - Accuracy: 0.3768 - F1: 0.3736
sub_11:Test (Best Model) - Loss: 1.2913 - Accuracy: 0.5072 - F1: 0.4805
sub_11:Test (Best Model) - Loss: 1.2533 - Accuracy: 0.4783 - F1: 0.4432
sub_11:Test (Best Model) - Loss: 1.2205 - Accuracy: 0.4638 - F1: 0.4169
sub_11:Test (Best Model) - Loss: 1.2979 - Accuracy: 0.4493 - F1: 0.4181
sub_11:Test (Best Model) - Loss: 1.2710 - Accuracy: 0.3913 - F1: 0.3505
sub_11:Test (Best Model) - Loss: 1.2835 - Accuracy: 0.4493 - F1: 0.4274
sub_11:Test (Best Model) - Loss: 1.3232 - Accuracy: 0.3623 - F1: 0.3239
sub_11:Test (Best Model) - Loss: 1.2174 - Accuracy: 0.4783 - F1: 0.4226
sub_11:Test (Best Model) - Loss: 1.2813 - Accuracy: 0.4203 - F1: 0.3983
sub_11:Test (Best Model) - Loss: 1.2966 - Accuracy: 0.3913 - F1: 0.3611
sub_12:Test (Best Model) - Loss: 1.0940 - Accuracy: 0.5147 - F1: 0.4955
sub_12:Test (Best Model) - Loss: 1.0492 - Accuracy: 0.5735 - F1: 0.5707
sub_12:Test (Best Model) - Loss: 1.0487 - Accuracy: 0.5735 - F1: 0.5424
sub_12:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.5441 - F1: 0.5598
sub_12:Test (Best Model) - Loss: 1.0027 - Accuracy: 0.5588 - F1: 0.5657
sub_12:Test (Best Model) - Loss: 1.1650 - Accuracy: 0.4203 - F1: 0.4337
sub_12:Test (Best Model) - Loss: 1.0848 - Accuracy: 0.5507 - F1: 0.5489
sub_12:Test (Best Model) - Loss: 1.1117 - Accuracy: 0.4928 - F1: 0.5032
sub_12:Test (Best Model) - Loss: 1.1187 - Accuracy: 0.4493 - F1: 0.4643
sub_12:Test (Best Model) - Loss: 1.0398 - Accuracy: 0.5507 - F1: 0.5661
sub_12:Test (Best Model) - Loss: 1.1527 - Accuracy: 0.4706 - F1: 0.4732
sub_12:Test (Best Model) - Loss: 1.2250 - Accuracy: 0.4559 - F1: 0.4595
sub_12:Test (Best Model) - Loss: 1.1436 - Accuracy: 0.4853 - F1: 0.5035
sub_12:Test (Best Model) - Loss: 1.1599 - Accuracy: 0.5000 - F1: 0.5139
sub_12:Test (Best Model) - Loss: 1.1664 - Accuracy: 0.4265 - F1: 0.4366
sub_13:Test (Best Model) - Loss: 1.3000 - Accuracy: 0.3824 - F1: 0.4122
sub_13:Test (Best Model) - Loss: 1.2583 - Accuracy: 0.3382 - F1: 0.3496
sub_13:Test (Best Model) - Loss: 1.1959 - Accuracy: 0.4853 - F1: 0.5107
sub_13:Test (Best Model) - Loss: 1.2688 - Accuracy: 0.3529 - F1: 0.3917
sub_13:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.4412 - F1: 0.4597
sub_13:Test (Best Model) - Loss: 1.3181 - Accuracy: 0.4348 - F1: 0.4200
sub_13:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.3913 - F1: 0.3926
sub_13:Test (Best Model) - Loss: 1.3848 - Accuracy: 0.3043 - F1: 0.3122
sub_13:Test (Best Model) - Loss: 1.3670 - Accuracy: 0.4058 - F1: 0.4094
sub_13:Test (Best Model) - Loss: 1.2500 - Accuracy: 0.4928 - F1: 0.5070
sub_13:Test (Best Model) - Loss: 1.3604 - Accuracy: 0.3382 - F1: 0.3533
sub_13:Test (Best Model) - Loss: 1.3228 - Accuracy: 0.3088 - F1: 0.3286
sub_13:Test (Best Model) - Loss: 1.3760 - Accuracy: 0.3382 - F1: 0.3557
sub_13:Test (Best Model) - Loss: 1.3081 - Accuracy: 0.3676 - F1: 0.3644
sub_13:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.3235 - F1: 0.3258
sub_14:Test (Best Model) - Loss: 1.2885 - Accuracy: 0.3971 - F1: 0.4293
sub_14:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.3824 - F1: 0.4026
sub_14:Test (Best Model) - Loss: 1.3287 - Accuracy: 0.3676 - F1: 0.4040
sub_14:Test (Best Model) - Loss: 1.3684 - Accuracy: 0.2941 - F1: 0.3316
sub_14:Test (Best Model) - Loss: 1.3195 - Accuracy: 0.3382 - F1: 0.3615
sub_14:Test (Best Model) - Loss: 1.3452 - Accuracy: 0.4118 - F1: 0.4055
sub_14:Test (Best Model) - Loss: 1.3221 - Accuracy: 0.4559 - F1: 0.4772
sub_14:Test (Best Model) - Loss: 1.3229 - Accuracy: 0.3529 - F1: 0.3323
sub_14:Test (Best Model) - Loss: 1.3404 - Accuracy: 0.3824 - F1: 0.3959
sub_14:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.2941 - F1: 0.2859
sub_14:Test (Best Model) - Loss: 1.3259 - Accuracy: 0.3529 - F1: 0.3736
sub_14:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.4412 - F1: 0.4289
sub_14:Test (Best Model) - Loss: 1.2781 - Accuracy: 0.3382 - F1: 0.3340
sub_14:Test (Best Model) - Loss: 1.2201 - Accuracy: 0.4265 - F1: 0.4255
sub_14:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.3235 - F1: 0.3093
sub_15:Test (Best Model) - Loss: 1.2011 - Accuracy: 0.4265 - F1: 0.4605
sub_15:Test (Best Model) - Loss: 1.3154 - Accuracy: 0.3824 - F1: 0.4047
sub_15:Test (Best Model) - Loss: 1.1619 - Accuracy: 0.4412 - F1: 0.4718
sub_15:Test (Best Model) - Loss: 1.1583 - Accuracy: 0.4559 - F1: 0.4866
sub_15:Test (Best Model) - Loss: 1.2119 - Accuracy: 0.4559 - F1: 0.4877
sub_15:Test (Best Model) - Loss: 1.0093 - Accuracy: 0.5294 - F1: 0.5309
sub_15:Test (Best Model) - Loss: 1.1638 - Accuracy: 0.5294 - F1: 0.5407
sub_15:Test (Best Model) - Loss: 1.0605 - Accuracy: 0.5882 - F1: 0.6022
sub_15:Test (Best Model) - Loss: 0.9845 - Accuracy: 0.5882 - F1: 0.6000
sub_15:Test (Best Model) - Loss: 1.0568 - Accuracy: 0.5735 - F1: 0.5778
sub_15:Test (Best Model) - Loss: 1.1634 - Accuracy: 0.4559 - F1: 0.4441
sub_15:Test (Best Model) - Loss: 1.1443 - Accuracy: 0.4412 - F1: 0.4495
sub_15:Test (Best Model) - Loss: 1.1413 - Accuracy: 0.4559 - F1: 0.4600
sub_15:Test (Best Model) - Loss: 1.1548 - Accuracy: 0.4706 - F1: 0.4686
sub_15:Test (Best Model) - Loss: 1.1961 - Accuracy: 0.4559 - F1: 0.4698
sub_16:Test (Best Model) - Loss: 1.1111 - Accuracy: 0.5147 - F1: 0.4553
sub_16:Test (Best Model) - Loss: 1.0819 - Accuracy: 0.5147 - F1: 0.4963
sub_16:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.5294 - F1: 0.4813
sub_16:Test (Best Model) - Loss: 1.1458 - Accuracy: 0.5294 - F1: 0.5167
sub_16:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.5882 - F1: 0.5354
sub_16:Test (Best Model) - Loss: 1.2158 - Accuracy: 0.4265 - F1: 0.4030
sub_16:Test (Best Model) - Loss: 1.2164 - Accuracy: 0.4265 - F1: 0.4042
sub_16:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.3824 - F1: 0.3493
sub_16:Test (Best Model) - Loss: 1.1759 - Accuracy: 0.5147 - F1: 0.5047
sub_16:Test (Best Model) - Loss: 1.3888 - Accuracy: 0.4853 - F1: 0.4648
sub_16:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.5441 - F1: 0.4828
sub_16:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.5735 - F1: 0.4976
sub_16:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.5294 - F1: 0.4844
sub_16:Test (Best Model) - Loss: 1.1404 - Accuracy: 0.5147 - F1: 0.4909
sub_16:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.5882 - F1: 0.5364
sub_17:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.4348 - F1: 0.4185
sub_17:Test (Best Model) - Loss: 1.0907 - Accuracy: 0.4928 - F1: 0.5017
sub_17:Test (Best Model) - Loss: 1.1210 - Accuracy: 0.4928 - F1: 0.4634
sub_17:Test (Best Model) - Loss: 1.1593 - Accuracy: 0.4203 - F1: 0.4112
sub_17:Test (Best Model) - Loss: 1.1633 - Accuracy: 0.4493 - F1: 0.4547
sub_17:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.3333 - F1: 0.2652
sub_17:Test (Best Model) - Loss: 1.4841 - Accuracy: 0.3623 - F1: 0.3136
sub_17:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.4203 - F1: 0.3616
sub_17:Test (Best Model) - Loss: 1.4559 - Accuracy: 0.3913 - F1: 0.3525
sub_17:Test (Best Model) - Loss: 1.4780 - Accuracy: 0.4203 - F1: 0.3773
sub_17:Test (Best Model) - Loss: 1.1623 - Accuracy: 0.4559 - F1: 0.4491
sub_17:Test (Best Model) - Loss: 1.2278 - Accuracy: 0.4706 - F1: 0.4595
sub_17:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.4559 - F1: 0.4578
sub_17:Test (Best Model) - Loss: 1.2304 - Accuracy: 0.4265 - F1: 0.4277
sub_17:Test (Best Model) - Loss: 1.2264 - Accuracy: 0.4265 - F1: 0.4331
sub_18:Test (Best Model) - Loss: 1.2300 - Accuracy: 0.4058 - F1: 0.4259
sub_18:Test (Best Model) - Loss: 1.2215 - Accuracy: 0.3768 - F1: 0.3921
sub_18:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.4493 - F1: 0.4392
sub_18:Test (Best Model) - Loss: 1.1816 - Accuracy: 0.4493 - F1: 0.4746
sub_18:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.3913 - F1: 0.4115
sub_18:Test (Best Model) - Loss: 1.3580 - Accuracy: 0.3235 - F1: 0.3508
sub_18:Test (Best Model) - Loss: 1.3045 - Accuracy: 0.3971 - F1: 0.4314
sub_18:Test (Best Model) - Loss: 1.3447 - Accuracy: 0.3529 - F1: 0.3638
sub_18:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.3971 - F1: 0.4278
sub_18:Test (Best Model) - Loss: 1.3439 - Accuracy: 0.3971 - F1: 0.4233
sub_18:Test (Best Model) - Loss: 1.2123 - Accuracy: 0.4412 - F1: 0.4689
sub_18:Test (Best Model) - Loss: 1.2857 - Accuracy: 0.3676 - F1: 0.3648
sub_18:Test (Best Model) - Loss: 1.2873 - Accuracy: 0.3529 - F1: 0.3711
sub_18:Test (Best Model) - Loss: 1.2089 - Accuracy: 0.3382 - F1: 0.3625
sub_18:Test (Best Model) - Loss: 1.2451 - Accuracy: 0.3971 - F1: 0.4374
sub_19:Test (Best Model) - Loss: 1.5419 - Accuracy: 0.2500 - F1: 0.2298
sub_19:Test (Best Model) - Loss: 1.5383 - Accuracy: 0.2353 - F1: 0.2619
sub_19:Test (Best Model) - Loss: 1.4974 - Accuracy: 0.2353 - F1: 0.2500
sub_19:Test (Best Model) - Loss: 1.4136 - Accuracy: 0.2500 - F1: 0.2666
sub_19:Test (Best Model) - Loss: 1.4636 - Accuracy: 0.2353 - F1: 0.2286
sub_19:Test (Best Model) - Loss: 1.2672 - Accuracy: 0.4118 - F1: 0.3696
sub_19:Test (Best Model) - Loss: 1.2212 - Accuracy: 0.4559 - F1: 0.4412
sub_19:Test (Best Model) - Loss: 1.1950 - Accuracy: 0.4853 - F1: 0.4810
sub_19:Test (Best Model) - Loss: 1.1584 - Accuracy: 0.5735 - F1: 0.5675
sub_19:Test (Best Model) - Loss: 1.1703 - Accuracy: 0.5294 - F1: 0.5417
sub_19:Test (Best Model) - Loss: 1.3582 - Accuracy: 0.3529 - F1: 0.3532
sub_19:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.2647 - F1: 0.2611
sub_19:Test (Best Model) - Loss: 1.2378 - Accuracy: 0.3676 - F1: 0.3477
sub_19:Test (Best Model) - Loss: 1.3509 - Accuracy: 0.3529 - F1: 0.3689
sub_19:Test (Best Model) - Loss: 1.2641 - Accuracy: 0.3382 - F1: 0.3205
sub_20:Test (Best Model) - Loss: 1.0838 - Accuracy: 0.5735 - F1: 0.5902
sub_20:Test (Best Model) - Loss: 1.0857 - Accuracy: 0.5735 - F1: 0.5879
sub_20:Test (Best Model) - Loss: 1.0958 - Accuracy: 0.5735 - F1: 0.5891
sub_20:Test (Best Model) - Loss: 1.1035 - Accuracy: 0.5294 - F1: 0.5332
sub_20:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.6029 - F1: 0.6121
sub_20:Test (Best Model) - Loss: 1.2204 - Accuracy: 0.4118 - F1: 0.4149
sub_20:Test (Best Model) - Loss: 1.1843 - Accuracy: 0.5000 - F1: 0.5178
sub_20:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.4412 - F1: 0.4526
sub_20:Test (Best Model) - Loss: 1.2250 - Accuracy: 0.3824 - F1: 0.3855
sub_20:Test (Best Model) - Loss: 1.1809 - Accuracy: 0.4559 - F1: 0.4596
sub_20:Test (Best Model) - Loss: 1.1862 - Accuracy: 0.4348 - F1: 0.4458
sub_20:Test (Best Model) - Loss: 1.2208 - Accuracy: 0.4203 - F1: 0.4308
sub_20:Test (Best Model) - Loss: 1.2375 - Accuracy: 0.3768 - F1: 0.4113
sub_20:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.4638 - F1: 0.4762
sub_20:Test (Best Model) - Loss: 1.1577 - Accuracy: 0.4928 - F1: 0.5078
sub_21:Test (Best Model) - Loss: 1.1244 - Accuracy: 0.4706 - F1: 0.4353
sub_21:Test (Best Model) - Loss: 1.1594 - Accuracy: 0.3971 - F1: 0.3687
sub_21:Test (Best Model) - Loss: 1.2267 - Accuracy: 0.4412 - F1: 0.4153
sub_21:Test (Best Model) - Loss: 1.2532 - Accuracy: 0.4265 - F1: 0.4002
sub_21:Test (Best Model) - Loss: 1.2515 - Accuracy: 0.3971 - F1: 0.3794
sub_21:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.4118 - F1: 0.4006
sub_21:Test (Best Model) - Loss: 1.1575 - Accuracy: 0.3529 - F1: 0.3181
sub_21:Test (Best Model) - Loss: 1.1674 - Accuracy: 0.3971 - F1: 0.3624
sub_21:Test (Best Model) - Loss: 1.1605 - Accuracy: 0.4118 - F1: 0.3802
sub_21:Test (Best Model) - Loss: 1.0907 - Accuracy: 0.4559 - F1: 0.4092
sub_21:Test (Best Model) - Loss: 1.1138 - Accuracy: 0.4118 - F1: 0.3740
sub_21:Test (Best Model) - Loss: 1.2138 - Accuracy: 0.4118 - F1: 0.3946
sub_21:Test (Best Model) - Loss: 1.1533 - Accuracy: 0.4412 - F1: 0.3854
sub_21:Test (Best Model) - Loss: 1.1247 - Accuracy: 0.4853 - F1: 0.4520
sub_21:Test (Best Model) - Loss: 1.1365 - Accuracy: 0.4412 - F1: 0.4123
sub_22:Test (Best Model) - Loss: 1.2800 - Accuracy: 0.4559 - F1: 0.4737
sub_22:Test (Best Model) - Loss: 1.2967 - Accuracy: 0.3824 - F1: 0.3778
sub_22:Test (Best Model) - Loss: 1.3312 - Accuracy: 0.3529 - F1: 0.3678
sub_22:Test (Best Model) - Loss: 1.3004 - Accuracy: 0.3971 - F1: 0.4167
sub_22:Test (Best Model) - Loss: 1.3435 - Accuracy: 0.3529 - F1: 0.3879
sub_22:Test (Best Model) - Loss: 1.3172 - Accuracy: 0.3623 - F1: 0.2988
sub_22:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.3623 - F1: 0.3352
sub_22:Test (Best Model) - Loss: 1.2599 - Accuracy: 0.3478 - F1: 0.3093
sub_22:Test (Best Model) - Loss: 1.2690 - Accuracy: 0.3623 - F1: 0.3685
sub_22:Test (Best Model) - Loss: 1.2665 - Accuracy: 0.4058 - F1: 0.3928
sub_22:Test (Best Model) - Loss: 1.2740 - Accuracy: 0.4412 - F1: 0.4629
sub_22:Test (Best Model) - Loss: 1.2461 - Accuracy: 0.3676 - F1: 0.3979
sub_22:Test (Best Model) - Loss: 1.2632 - Accuracy: 0.3824 - F1: 0.4016
sub_22:Test (Best Model) - Loss: 1.2314 - Accuracy: 0.3824 - F1: 0.4278
sub_22:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.4118 - F1: 0.4487
sub_23:Test (Best Model) - Loss: 1.1892 - Accuracy: 0.4203 - F1: 0.4332
sub_23:Test (Best Model) - Loss: 1.0816 - Accuracy: 0.4493 - F1: 0.4642
sub_23:Test (Best Model) - Loss: 1.1238 - Accuracy: 0.4348 - F1: 0.4403
sub_23:Test (Best Model) - Loss: 1.0073 - Accuracy: 0.5507 - F1: 0.5666
sub_23:Test (Best Model) - Loss: 1.0682 - Accuracy: 0.4493 - F1: 0.4649
sub_23:Test (Best Model) - Loss: 1.1775 - Accuracy: 0.4559 - F1: 0.4355
sub_23:Test (Best Model) - Loss: 1.1074 - Accuracy: 0.5588 - F1: 0.5680
sub_23:Test (Best Model) - Loss: 1.0817 - Accuracy: 0.5441 - F1: 0.5221
sub_23:Test (Best Model) - Loss: 1.0872 - Accuracy: 0.5441 - F1: 0.5523
sub_23:Test (Best Model) - Loss: 1.1007 - Accuracy: 0.5441 - F1: 0.5314
sub_23:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.4348 - F1: 0.4321
sub_23:Test (Best Model) - Loss: 1.2385 - Accuracy: 0.4348 - F1: 0.4343
sub_23:Test (Best Model) - Loss: 1.1557 - Accuracy: 0.4058 - F1: 0.3954
sub_23:Test (Best Model) - Loss: 1.2181 - Accuracy: 0.5362 - F1: 0.5394
sub_23:Test (Best Model) - Loss: 1.2140 - Accuracy: 0.4638 - F1: 0.4584
sub_24:Test (Best Model) - Loss: 1.3744 - Accuracy: 0.3382 - F1: 0.3320
sub_24:Test (Best Model) - Loss: 1.3871 - Accuracy: 0.3235 - F1: 0.3122
sub_24:Test (Best Model) - Loss: 1.3499 - Accuracy: 0.3088 - F1: 0.3112
sub_24:Test (Best Model) - Loss: 1.4475 - Accuracy: 0.2794 - F1: 0.2841
sub_24:Test (Best Model) - Loss: 1.4017 - Accuracy: 0.2941 - F1: 0.2886
sub_24:Test (Best Model) - Loss: 1.3449 - Accuracy: 0.2941 - F1: 0.2829
sub_24:Test (Best Model) - Loss: 1.3169 - Accuracy: 0.3382 - F1: 0.3265
sub_24:Test (Best Model) - Loss: 1.3142 - Accuracy: 0.4412 - F1: 0.4316
sub_24:Test (Best Model) - Loss: 1.2977 - Accuracy: 0.4118 - F1: 0.4084
sub_24:Test (Best Model) - Loss: 1.3591 - Accuracy: 0.3235 - F1: 0.3151
sub_24:Test (Best Model) - Loss: 1.4167 - Accuracy: 0.2353 - F1: 0.2445
sub_24:Test (Best Model) - Loss: 1.4554 - Accuracy: 0.2500 - F1: 0.2539
sub_24:Test (Best Model) - Loss: 1.4162 - Accuracy: 0.2353 - F1: 0.2363
sub_24:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.2941 - F1: 0.3056
sub_24:Test (Best Model) - Loss: 1.4087 - Accuracy: 0.3382 - F1: 0.3348
sub_25:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.4928 - F1: 0.4487
sub_25:Test (Best Model) - Loss: 1.2227 - Accuracy: 0.4493 - F1: 0.4003
sub_25:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.4638 - F1: 0.4108
sub_25:Test (Best Model) - Loss: 1.1507 - Accuracy: 0.4638 - F1: 0.4169
sub_25:Test (Best Model) - Loss: 1.2418 - Accuracy: 0.4058 - F1: 0.3853
sub_25:Test (Best Model) - Loss: 1.2611 - Accuracy: 0.4265 - F1: 0.3632
sub_25:Test (Best Model) - Loss: 1.2936 - Accuracy: 0.4706 - F1: 0.4073
sub_25:Test (Best Model) - Loss: 1.2358 - Accuracy: 0.5147 - F1: 0.4760
sub_25:Test (Best Model) - Loss: 1.2741 - Accuracy: 0.5000 - F1: 0.4257
sub_25:Test (Best Model) - Loss: 1.2335 - Accuracy: 0.5441 - F1: 0.5144
sub_25:Test (Best Model) - Loss: 1.2567 - Accuracy: 0.4559 - F1: 0.4556
sub_25:Test (Best Model) - Loss: 1.2327 - Accuracy: 0.4559 - F1: 0.4304
sub_25:Test (Best Model) - Loss: 1.1942 - Accuracy: 0.4559 - F1: 0.4304
sub_25:Test (Best Model) - Loss: 1.2173 - Accuracy: 0.3235 - F1: 0.2276
sub_25:Test (Best Model) - Loss: 1.2053 - Accuracy: 0.4412 - F1: 0.3834
sub_26:Test (Best Model) - Loss: 1.0960 - Accuracy: 0.4783 - F1: 0.4958
sub_26:Test (Best Model) - Loss: 1.1416 - Accuracy: 0.4638 - F1: 0.4707
sub_26:Test (Best Model) - Loss: 1.1255 - Accuracy: 0.4928 - F1: 0.5019
sub_26:Test (Best Model) - Loss: 1.0843 - Accuracy: 0.5362 - F1: 0.5478
sub_26:Test (Best Model) - Loss: 1.0664 - Accuracy: 0.5797 - F1: 0.5944
sub_26:Test (Best Model) - Loss: 1.2427 - Accuracy: 0.4265 - F1: 0.4450
sub_26:Test (Best Model) - Loss: 1.2091 - Accuracy: 0.4412 - F1: 0.4526
sub_26:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.3824 - F1: 0.3922
sub_26:Test (Best Model) - Loss: 1.2113 - Accuracy: 0.3676 - F1: 0.3883
sub_26:Test (Best Model) - Loss: 1.2383 - Accuracy: 0.3529 - F1: 0.3871
sub_26:Test (Best Model) - Loss: 1.1175 - Accuracy: 0.6029 - F1: 0.6227
sub_26:Test (Best Model) - Loss: 1.2377 - Accuracy: 0.5000 - F1: 0.5233
sub_26:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.4853 - F1: 0.5117
sub_26:Test (Best Model) - Loss: 1.1123 - Accuracy: 0.5441 - F1: 0.5628
sub_26:Test (Best Model) - Loss: 1.1873 - Accuracy: 0.5147 - F1: 0.5404
sub_27:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.4348 - F1: 0.4185
sub_27:Test (Best Model) - Loss: 1.0907 - Accuracy: 0.4928 - F1: 0.5017
sub_27:Test (Best Model) - Loss: 1.1210 - Accuracy: 0.4928 - F1: 0.4634
sub_27:Test (Best Model) - Loss: 1.1593 - Accuracy: 0.4203 - F1: 0.4112
sub_27:Test (Best Model) - Loss: 1.1633 - Accuracy: 0.4493 - F1: 0.4547
sub_27:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.3333 - F1: 0.2652
sub_27:Test (Best Model) - Loss: 1.4841 - Accuracy: 0.3623 - F1: 0.3136
sub_27:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.4203 - F1: 0.3616
sub_27:Test (Best Model) - Loss: 1.4559 - Accuracy: 0.3913 - F1: 0.3525
sub_27:Test (Best Model) - Loss: 1.4780 - Accuracy: 0.4203 - F1: 0.3773
sub_27:Test (Best Model) - Loss: 1.1623 - Accuracy: 0.4559 - F1: 0.4491
sub_27:Test (Best Model) - Loss: 1.2278 - Accuracy: 0.4706 - F1: 0.4595
sub_27:Test (Best Model) - Loss: 1.2806 - Accuracy: 0.4559 - F1: 0.4578
sub_27:Test (Best Model) - Loss: 1.2304 - Accuracy: 0.4265 - F1: 0.4277
sub_27:Test (Best Model) - Loss: 1.2264 - Accuracy: 0.4265 - F1: 0.4331
sub_28:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.3824 - F1: 0.3902
sub_28:Test (Best Model) - Loss: 1.3827 - Accuracy: 0.3088 - F1: 0.2855
sub_28:Test (Best Model) - Loss: 1.5138 - Accuracy: 0.3235 - F1: 0.3249
sub_28:Test (Best Model) - Loss: 1.5167 - Accuracy: 0.2647 - F1: 0.2645
sub_28:Test (Best Model) - Loss: 1.5017 - Accuracy: 0.3088 - F1: 0.3091
sub_28:Test (Best Model) - Loss: 1.8193 - Accuracy: 0.2206 - F1: 0.1898
sub_28:Test (Best Model) - Loss: 1.6660 - Accuracy: 0.2794 - F1: 0.2415
sub_28:Test (Best Model) - Loss: 1.7503 - Accuracy: 0.2794 - F1: 0.2171
sub_28:Test (Best Model) - Loss: 1.8983 - Accuracy: 0.2794 - F1: 0.2644
sub_28:Test (Best Model) - Loss: 1.7748 - Accuracy: 0.2206 - F1: 0.1587
sub_28:Test (Best Model) - Loss: 1.3156 - Accuracy: 0.3676 - F1: 0.3242
sub_28:Test (Best Model) - Loss: 1.2773 - Accuracy: 0.3382 - F1: 0.2857
sub_28:Test (Best Model) - Loss: 1.2322 - Accuracy: 0.4412 - F1: 0.3970
sub_28:Test (Best Model) - Loss: 1.2833 - Accuracy: 0.4706 - F1: 0.4475
sub_28:Test (Best Model) - Loss: 1.2586 - Accuracy: 0.4706 - F1: 0.4414
sub_29:Test (Best Model) - Loss: 1.1440 - Accuracy: 0.5294 - F1: 0.5360
sub_29:Test (Best Model) - Loss: 1.0480 - Accuracy: 0.5294 - F1: 0.5381
sub_29:Test (Best Model) - Loss: 1.0102 - Accuracy: 0.6029 - F1: 0.5933
sub_29:Test (Best Model) - Loss: 1.0783 - Accuracy: 0.5000 - F1: 0.5111
sub_29:Test (Best Model) - Loss: 1.0981 - Accuracy: 0.5294 - F1: 0.5248
sub_29:Test (Best Model) - Loss: 0.8879 - Accuracy: 0.6324 - F1: 0.6548
sub_29:Test (Best Model) - Loss: 0.9183 - Accuracy: 0.5735 - F1: 0.5938
sub_29:Test (Best Model) - Loss: 0.9048 - Accuracy: 0.5588 - F1: 0.5782
sub_29:Test (Best Model) - Loss: 0.8946 - Accuracy: 0.6176 - F1: 0.6373
sub_29:Test (Best Model) - Loss: 0.9275 - Accuracy: 0.5588 - F1: 0.5869
sub_29:Test (Best Model) - Loss: 0.9127 - Accuracy: 0.5797 - F1: 0.6035
sub_29:Test (Best Model) - Loss: 0.8790 - Accuracy: 0.5797 - F1: 0.5998
sub_29:Test (Best Model) - Loss: 1.0128 - Accuracy: 0.5072 - F1: 0.5301
sub_29:Test (Best Model) - Loss: 0.8952 - Accuracy: 0.6377 - F1: 0.6471
sub_29:Test (Best Model) - Loss: 0.9474 - Accuracy: 0.6087 - F1: 0.6234

=== Summary Results ===

acc: 42.55 ± 6.99
F1: 42.24 ± 7.25
acc-in: 51.48 ± 6.69
F1-in: 50.15 ± 6.82
