lr: 1e-06
sub_3:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.3971 - F1: 0.3785
sub_7:Test (Best Model) - Loss: 1.4467 - Accuracy: 0.2500 - F1: 0.1887
sub_6:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.3676 - F1: 0.3185
sub_23:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.3623 - F1: 0.3741
sub_1:Test (Best Model) - Loss: 1.3380 - Accuracy: 0.4118 - F1: 0.3898
sub_5:Test (Best Model) - Loss: 1.3194 - Accuracy: 0.4706 - F1: 0.4431
sub_4:Test (Best Model) - Loss: 1.3816 - Accuracy: 0.2754 - F1: 0.2729
sub_21:Test (Best Model) - Loss: 1.2614 - Accuracy: 0.3676 - F1: 0.3709
sub_29:Test (Best Model) - Loss: 1.3753 - Accuracy: 0.3088 - F1: 0.2821
sub_27:Test (Best Model) - Loss: 1.4969 - Accuracy: 0.2319 - F1: 0.1848
sub_28:Test (Best Model) - Loss: 1.3490 - Accuracy: 0.3382 - F1: 0.3272
sub_10:Test (Best Model) - Loss: 1.3895 - Accuracy: 0.2647 - F1: 0.2057
sub_13:Test (Best Model) - Loss: 1.4703 - Accuracy: 0.3088 - F1: 0.2694
sub_17:Test (Best Model) - Loss: 1.4969 - Accuracy: 0.2319 - F1: 0.1848
sub_12:Test (Best Model) - Loss: 1.6684 - Accuracy: 0.1029 - F1: 0.0944
sub_15:Test (Best Model) - Loss: 1.3807 - Accuracy: 0.3235 - F1: 0.2885
sub_9:Test (Best Model) - Loss: 1.4829 - Accuracy: 0.2794 - F1: 0.2622
sub_2:Test (Best Model) - Loss: 1.5746 - Accuracy: 0.2174 - F1: 0.1964
sub_25:Test (Best Model) - Loss: 1.1767 - Accuracy: 0.4058 - F1: 0.3939
sub_3:Test (Best Model) - Loss: 1.3100 - Accuracy: 0.3235 - F1: 0.2969
sub_8:Test (Best Model) - Loss: 1.5126 - Accuracy: 0.2647 - F1: 0.2347
sub_18:Test (Best Model) - Loss: 1.3643 - Accuracy: 0.2899 - F1: 0.3173
sub_26:Test (Best Model) - Loss: 1.3150 - Accuracy: 0.4203 - F1: 0.3839
sub_20:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.3088 - F1: 0.2735
sub_16:Test (Best Model) - Loss: 1.5188 - Accuracy: 0.3529 - F1: 0.3171
sub_19:Test (Best Model) - Loss: 1.3899 - Accuracy: 0.3382 - F1: 0.2835
sub_14:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.2500 - F1: 0.2071
sub_10:Test (Best Model) - Loss: 1.4602 - Accuracy: 0.2500 - F1: 0.2320
sub_28:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.2941 - F1: 0.3230
sub_21:Test (Best Model) - Loss: 1.3685 - Accuracy: 0.3676 - F1: 0.3547
sub_4:Test (Best Model) - Loss: 1.5721 - Accuracy: 0.2609 - F1: 0.2412
sub_2:Test (Best Model) - Loss: 1.4213 - Accuracy: 0.2754 - F1: 0.2548
sub_24:Test (Best Model) - Loss: 1.3842 - Accuracy: 0.4706 - F1: 0.4247
sub_22:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.3529 - F1: 0.3639
sub_23:Test (Best Model) - Loss: 1.3049 - Accuracy: 0.5072 - F1: 0.4475
sub_1:Test (Best Model) - Loss: 1.2545 - Accuracy: 0.4706 - F1: 0.4727
sub_29:Test (Best Model) - Loss: 1.4443 - Accuracy: 0.3088 - F1: 0.2476
sub_16:Test (Best Model) - Loss: 1.4950 - Accuracy: 0.2500 - F1: 0.2240
sub_13:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.3382 - F1: 0.2427
sub_7:Test (Best Model) - Loss: 1.3033 - Accuracy: 0.3529 - F1: 0.3039
sub_19:Test (Best Model) - Loss: 1.5255 - Accuracy: 0.2500 - F1: 0.2204
sub_21:Test (Best Model) - Loss: 1.4111 - Accuracy: 0.3971 - F1: 0.3287
sub_11:Test (Best Model) - Loss: 1.4603 - Accuracy: 0.2609 - F1: 0.2356
sub_15:Test (Best Model) - Loss: 1.3170 - Accuracy: 0.4265 - F1: 0.3901
sub_17:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.2899 - F1: 0.2905
sub_27:Test (Best Model) - Loss: 1.3443 - Accuracy: 0.2899 - F1: 0.2905
sub_23:Test (Best Model) - Loss: 1.4484 - Accuracy: 0.4348 - F1: 0.3331
sub_20:Test (Best Model) - Loss: 1.5165 - Accuracy: 0.2794 - F1: 0.2430
sub_3:Test (Best Model) - Loss: 1.6619 - Accuracy: 0.2500 - F1: 0.1477
sub_10:Test (Best Model) - Loss: 1.6560 - Accuracy: 0.1912 - F1: 0.1669
sub_12:Test (Best Model) - Loss: 1.3777 - Accuracy: 0.3382 - F1: 0.3124
sub_6:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.4706 - F1: 0.4445
sub_19:Test (Best Model) - Loss: 1.4120 - Accuracy: 0.3529 - F1: 0.2216
sub_16:Test (Best Model) - Loss: 1.7460 - Accuracy: 0.1912 - F1: 0.1229
sub_25:Test (Best Model) - Loss: 1.4122 - Accuracy: 0.3768 - F1: 0.3735
sub_26:Test (Best Model) - Loss: 1.4538 - Accuracy: 0.2754 - F1: 0.2354
sub_21:Test (Best Model) - Loss: 1.3637 - Accuracy: 0.2794 - F1: 0.2072
sub_15:Test (Best Model) - Loss: 1.3065 - Accuracy: 0.3676 - F1: 0.2408
sub_5:Test (Best Model) - Loss: 1.2422 - Accuracy: 0.3676 - F1: 0.3134
sub_14:Test (Best Model) - Loss: 1.6428 - Accuracy: 0.2353 - F1: 0.2172
sub_18:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.3623 - F1: 0.3549
sub_24:Test (Best Model) - Loss: 1.3484 - Accuracy: 0.3235 - F1: 0.2926
sub_10:Test (Best Model) - Loss: 1.2998 - Accuracy: 0.4412 - F1: 0.3696
sub_28:Test (Best Model) - Loss: 1.7912 - Accuracy: 0.1471 - F1: 0.1155
sub_29:Test (Best Model) - Loss: 1.6639 - Accuracy: 0.2647 - F1: 0.1111
sub_22:Test (Best Model) - Loss: 1.3208 - Accuracy: 0.3529 - F1: 0.3497
sub_13:Test (Best Model) - Loss: 1.5845 - Accuracy: 0.3088 - F1: 0.2158
sub_9:Test (Best Model) - Loss: 1.2613 - Accuracy: 0.4706 - F1: 0.4540
sub_19:Test (Best Model) - Loss: 1.3208 - Accuracy: 0.3235 - F1: 0.2260
sub_17:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.2899 - F1: 0.2463
sub_2:Test (Best Model) - Loss: 1.3403 - Accuracy: 0.4203 - F1: 0.3637
sub_7:Test (Best Model) - Loss: 1.4102 - Accuracy: 0.3824 - F1: 0.3009
sub_11:Test (Best Model) - Loss: 1.3250 - Accuracy: 0.3768 - F1: 0.3598
sub_27:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.2899 - F1: 0.2463
sub_4:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.4348 - F1: 0.3802
sub_15:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.4265 - F1: 0.3604
sub_1:Test (Best Model) - Loss: 1.3626 - Accuracy: 0.3824 - F1: 0.3197
sub_23:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.2609 - F1: 0.1813
sub_3:Test (Best Model) - Loss: 1.4755 - Accuracy: 0.2647 - F1: 0.2053
sub_14:Test (Best Model) - Loss: 1.9505 - Accuracy: 0.2647 - F1: 0.1047
sub_24:Test (Best Model) - Loss: 1.6565 - Accuracy: 0.3088 - F1: 0.2181
sub_10:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.2941 - F1: 0.1757
sub_28:Test (Best Model) - Loss: 1.3959 - Accuracy: 0.3529 - F1: 0.2636
sub_13:Test (Best Model) - Loss: 1.5040 - Accuracy: 0.2941 - F1: 0.2264
sub_21:Test (Best Model) - Loss: 1.4381 - Accuracy: 0.3235 - F1: 0.1890
sub_17:Test (Best Model) - Loss: 1.3051 - Accuracy: 0.4203 - F1: 0.3788
sub_27:Test (Best Model) - Loss: 1.3051 - Accuracy: 0.4203 - F1: 0.3788
sub_15:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2353 - F1: 0.1538
sub_20:Test (Best Model) - Loss: 1.4268 - Accuracy: 0.4118 - F1: 0.3129
sub_23:Test (Best Model) - Loss: 1.9258 - Accuracy: 0.1159 - F1: 0.0875
sub_26:Test (Best Model) - Loss: 1.4261 - Accuracy: 0.3333 - F1: 0.2591
sub_1:Test (Best Model) - Loss: 1.5012 - Accuracy: 0.2941 - F1: 0.1976
sub_16:Test (Best Model) - Loss: 1.2950 - Accuracy: 0.3824 - F1: 0.3011
sub_25:Test (Best Model) - Loss: 1.6774 - Accuracy: 0.2609 - F1: 0.1846
sub_3:Test (Best Model) - Loss: 1.7268 - Accuracy: 0.2353 - F1: 0.1013
sub_29:Test (Best Model) - Loss: 1.4142 - Accuracy: 0.3382 - F1: 0.2843
sub_8:Test (Best Model) - Loss: 1.2245 - Accuracy: 0.5294 - F1: 0.5254
sub_5:Test (Best Model) - Loss: 1.1155 - Accuracy: 0.3088 - F1: 0.1886
sub_9:Test (Best Model) - Loss: 1.4667 - Accuracy: 0.2941 - F1: 0.1941
sub_24:Test (Best Model) - Loss: 1.5076 - Accuracy: 0.2059 - F1: 0.1160
sub_2:Test (Best Model) - Loss: 1.5153 - Accuracy: 0.2899 - F1: 0.2024
sub_19:Test (Best Model) - Loss: 1.6998 - Accuracy: 0.2353 - F1: 0.1488
sub_7:Test (Best Model) - Loss: 1.4743 - Accuracy: 0.3235 - F1: 0.2417
sub_28:Test (Best Model) - Loss: 1.6150 - Accuracy: 0.2500 - F1: 0.1245
sub_13:Test (Best Model) - Loss: 1.6846 - Accuracy: 0.2647 - F1: 0.1098
sub_27:Test (Best Model) - Loss: 1.5348 - Accuracy: 0.3043 - F1: 0.1824
sub_14:Test (Best Model) - Loss: 1.4962 - Accuracy: 0.2647 - F1: 0.1845
sub_17:Test (Best Model) - Loss: 1.5348 - Accuracy: 0.3043 - F1: 0.1824
sub_21:Test (Best Model) - Loss: 1.3421 - Accuracy: 0.3382 - F1: 0.2893
sub_12:Test (Best Model) - Loss: 1.2497 - Accuracy: 0.4265 - F1: 0.3356
sub_20:Test (Best Model) - Loss: 1.1981 - Accuracy: 0.4853 - F1: 0.4135
sub_10:Test (Best Model) - Loss: 1.3696 - Accuracy: 0.3529 - F1: 0.2700
sub_15:Test (Best Model) - Loss: 1.5191 - Accuracy: 0.2941 - F1: 0.2478
sub_16:Test (Best Model) - Loss: 1.7395 - Accuracy: 0.1618 - F1: 0.1250
sub_26:Test (Best Model) - Loss: 1.4883 - Accuracy: 0.2174 - F1: 0.1632
sub_24:Test (Best Model) - Loss: 1.7302 - Accuracy: 0.2353 - F1: 0.0964
sub_1:Test (Best Model) - Loss: 1.7878 - Accuracy: 0.2206 - F1: 0.1336
sub_25:Test (Best Model) - Loss: 1.3709 - Accuracy: 0.4638 - F1: 0.3652
sub_18:Test (Best Model) - Loss: 1.4705 - Accuracy: 0.4348 - F1: 0.3587
sub_29:Test (Best Model) - Loss: 1.8345 - Accuracy: 0.1618 - F1: 0.0797
sub_22:Test (Best Model) - Loss: 1.3460 - Accuracy: 0.3382 - F1: 0.2459
sub_2:Test (Best Model) - Loss: 1.5199 - Accuracy: 0.3188 - F1: 0.1890
sub_7:Test (Best Model) - Loss: 1.3941 - Accuracy: 0.3235 - F1: 0.2201
sub_9:Test (Best Model) - Loss: 1.3357 - Accuracy: 0.4412 - F1: 0.3323
sub_8:Test (Best Model) - Loss: 1.6782 - Accuracy: 0.2500 - F1: 0.1690
sub_6:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.3382 - F1: 0.2541
sub_14:Test (Best Model) - Loss: 1.2848 - Accuracy: 0.4265 - F1: 0.3251
sub_4:Test (Best Model) - Loss: 1.3629 - Accuracy: 0.5217 - F1: 0.4569
sub_10:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.2647 - F1: 0.1047
sub_12:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.2647 - F1: 0.2240
sub_19:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.3382 - F1: 0.2870
sub_28:Test (Best Model) - Loss: 1.4512 - Accuracy: 0.2353 - F1: 0.2265
sub_16:Test (Best Model) - Loss: 1.5327 - Accuracy: 0.2941 - F1: 0.2904
sub_26:Test (Best Model) - Loss: 1.7865 - Accuracy: 0.2319 - F1: 0.1608
sub_1:Test (Best Model) - Loss: 1.2870 - Accuracy: 0.3478 - F1: 0.3135
sub_25:Test (Best Model) - Loss: 1.6529 - Accuracy: 0.3188 - F1: 0.2125
sub_22:Test (Best Model) - Loss: 1.4682 - Accuracy: 0.2500 - F1: 0.1280
sub_23:Test (Best Model) - Loss: 1.7059 - Accuracy: 0.1029 - F1: 0.0574
sub_2:Test (Best Model) - Loss: 1.4598 - Accuracy: 0.3529 - F1: 0.2671
sub_9:Test (Best Model) - Loss: 1.7459 - Accuracy: 0.2353 - F1: 0.1415
sub_17:Test (Best Model) - Loss: 1.4402 - Accuracy: 0.3188 - F1: 0.2657
sub_15:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2500 - F1: 0.1516
sub_20:Test (Best Model) - Loss: 1.6867 - Accuracy: 0.2941 - F1: 0.1752
sub_27:Test (Best Model) - Loss: 1.4402 - Accuracy: 0.3188 - F1: 0.2657
sub_6:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.3088 - F1: 0.1944
sub_5:Test (Best Model) - Loss: 1.5886 - Accuracy: 0.1912 - F1: 0.1498
sub_11:Test (Best Model) - Loss: 1.5453 - Accuracy: 0.2609 - F1: 0.1627
sub_7:Test (Best Model) - Loss: 1.4351 - Accuracy: 0.2647 - F1: 0.2751
sub_21:Test (Best Model) - Loss: 1.5407 - Accuracy: 0.3235 - F1: 0.2139
sub_12:Test (Best Model) - Loss: 1.7322 - Accuracy: 0.2059 - F1: 0.1059
sub_29:Test (Best Model) - Loss: 1.2723 - Accuracy: 0.4559 - F1: 0.3825
sub_16:Test (Best Model) - Loss: 1.4963 - Accuracy: 0.2794 - F1: 0.1600
sub_18:Test (Best Model) - Loss: 1.4755 - Accuracy: 0.2464 - F1: 0.1794
sub_28:Test (Best Model) - Loss: 1.6367 - Accuracy: 0.2647 - F1: 0.1084
sub_8:Test (Best Model) - Loss: 1.4905 - Accuracy: 0.3088 - F1: 0.2081
sub_3:Test (Best Model) - Loss: 1.2957 - Accuracy: 0.4348 - F1: 0.4303
sub_19:Test (Best Model) - Loss: 1.5731 - Accuracy: 0.2941 - F1: 0.2005
sub_15:Test (Best Model) - Loss: 1.7479 - Accuracy: 0.2647 - F1: 0.1304
sub_13:Test (Best Model) - Loss: 1.5376 - Accuracy: 0.1014 - F1: 0.0946
sub_9:Test (Best Model) - Loss: 1.5545 - Accuracy: 0.2353 - F1: 0.1719
sub_22:Test (Best Model) - Loss: 1.4029 - Accuracy: 0.3824 - F1: 0.2833
sub_17:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.3333 - F1: 0.2182
sub_6:Test (Best Model) - Loss: 1.5353 - Accuracy: 0.3088 - F1: 0.1932
sub_24:Test (Best Model) - Loss: 1.3307 - Accuracy: 0.3676 - F1: 0.3591
sub_20:Test (Best Model) - Loss: 1.4048 - Accuracy: 0.3382 - F1: 0.3245
sub_27:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.3333 - F1: 0.2182
sub_5:Test (Best Model) - Loss: 1.3752 - Accuracy: 0.5000 - F1: 0.3482
sub_7:Test (Best Model) - Loss: 1.5194 - Accuracy: 0.2059 - F1: 0.1386
sub_12:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.1739 - F1: 0.1637
sub_10:Test (Best Model) - Loss: 1.5534 - Accuracy: 0.2206 - F1: 0.1361
sub_21:Test (Best Model) - Loss: 1.5515 - Accuracy: 0.2794 - F1: 0.2188
sub_1:Test (Best Model) - Loss: 1.7042 - Accuracy: 0.1884 - F1: 0.1067
sub_29:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.2059 - F1: 0.1067
sub_14:Test (Best Model) - Loss: 1.3371 - Accuracy: 0.3971 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2319 - F1: 0.1670
sub_18:Test (Best Model) - Loss: 1.6852 - Accuracy: 0.2609 - F1: 0.1047
sub_16:Test (Best Model) - Loss: 1.6388 - Accuracy: 0.2059 - F1: 0.1695
sub_2:Test (Best Model) - Loss: 1.4914 - Accuracy: 0.2941 - F1: 0.1598
sub_11:Test (Best Model) - Loss: 1.5521 - Accuracy: 0.1739 - F1: 0.1443
sub_13:Test (Best Model) - Loss: 1.5099 - Accuracy: 0.2609 - F1: 0.1084
sub_24:Test (Best Model) - Loss: 1.6453 - Accuracy: 0.2500 - F1: 0.1717
sub_23:Test (Best Model) - Loss: 1.4552 - Accuracy: 0.2647 - F1: 0.1760
sub_9:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2059 - F1: 0.1258
sub_6:Test (Best Model) - Loss: 1.4154 - Accuracy: 0.3333 - F1: 0.3378
sub_28:Test (Best Model) - Loss: 1.5416 - Accuracy: 0.2353 - F1: 0.1641
sub_5:Test (Best Model) - Loss: 1.4637 - Accuracy: 0.3824 - F1: 0.2984
sub_12:Test (Best Model) - Loss: 1.5129 - Accuracy: 0.3188 - F1: 0.1955
sub_20:Test (Best Model) - Loss: 1.5356 - Accuracy: 0.2941 - F1: 0.1742
sub_22:Test (Best Model) - Loss: 1.4174 - Accuracy: 0.3188 - F1: 0.3006
sub_14:Test (Best Model) - Loss: 1.6377 - Accuracy: 0.2353 - F1: 0.1271
sub_19:Test (Best Model) - Loss: 1.6250 - Accuracy: 0.2206 - F1: 0.1636
sub_2:Test (Best Model) - Loss: 1.5691 - Accuracy: 0.3529 - F1: 0.2251
sub_26:Test (Best Model) - Loss: 1.3425 - Accuracy: 0.3382 - F1: 0.3044
sub_8:Test (Best Model) - Loss: 1.5757 - Accuracy: 0.2500 - F1: 0.1164
sub_17:Test (Best Model) - Loss: 1.4706 - Accuracy: 0.3623 - F1: 0.3106
sub_27:Test (Best Model) - Loss: 1.4706 - Accuracy: 0.3623 - F1: 0.3106
sub_3:Test (Best Model) - Loss: 1.5320 - Accuracy: 0.2899 - F1: 0.1767
sub_1:Test (Best Model) - Loss: 1.5794 - Accuracy: 0.2899 - F1: 0.2140
sub_24:Test (Best Model) - Loss: 1.4878 - Accuracy: 0.1618 - F1: 0.1698
sub_11:Test (Best Model) - Loss: 1.7010 - Accuracy: 0.2609 - F1: 0.1059
sub_9:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.2059 - F1: 0.1838
sub_6:Test (Best Model) - Loss: 1.6504 - Accuracy: 0.3623 - F1: 0.2384
sub_23:Test (Best Model) - Loss: 1.8480 - Accuracy: 0.2353 - F1: 0.1143
sub_15:Test (Best Model) - Loss: 1.2928 - Accuracy: 0.4118 - F1: 0.3950
sub_13:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.3333 - F1: 0.2761
sub_12:Test (Best Model) - Loss: 1.4267 - Accuracy: 0.2609 - F1: 0.2200
sub_20:Test (Best Model) - Loss: 1.4773 - Accuracy: 0.2794 - F1: 0.1477
sub_22:Test (Best Model) - Loss: 1.4850 - Accuracy: 0.2174 - F1: 0.1415
sub_21:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.4559 - F1: 0.4278
sub_29:Test (Best Model) - Loss: 1.4358 - Accuracy: 0.2206 - F1: 0.1966
sub_10:Test (Best Model) - Loss: 1.6546 - Accuracy: 0.2647 - F1: 0.1047
sub_7:Test (Best Model) - Loss: 1.5038 - Accuracy: 0.3382 - F1: 0.2497
sub_5:Test (Best Model) - Loss: 1.6550 - Accuracy: 0.2353 - F1: 0.1397
sub_26:Test (Best Model) - Loss: 1.5146 - Accuracy: 0.2647 - F1: 0.1771
sub_2:Test (Best Model) - Loss: 1.4601 - Accuracy: 0.2647 - F1: 0.2218
sub_16:Test (Best Model) - Loss: 1.4194 - Accuracy: 0.3235 - F1: 0.2886
sub_3:Test (Best Model) - Loss: 1.7520 - Accuracy: 0.1449 - F1: 0.0938
sub_18:Test (Best Model) - Loss: 1.2535 - Accuracy: 0.4706 - F1: 0.4198
sub_24:Test (Best Model) - Loss: 1.5062 - Accuracy: 0.2794 - F1: 0.2095
sub_15:Test (Best Model) - Loss: 1.6256 - Accuracy: 0.1324 - F1: 0.1104
sub_23:Test (Best Model) - Loss: 1.7249 - Accuracy: 0.1912 - F1: 0.1278
sub_28:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.2647 - F1: 0.2421
sub_6:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2174 - F1: 0.1728
sub_20:Test (Best Model) - Loss: 1.4979 - Accuracy: 0.2353 - F1: 0.2380
sub_21:Test (Best Model) - Loss: 1.4935 - Accuracy: 0.1618 - F1: 0.1565
sub_14:Test (Best Model) - Loss: 1.5826 - Accuracy: 0.1618 - F1: 0.1235
sub_4:Test (Best Model) - Loss: 1.1543 - Accuracy: 0.4783 - F1: 0.4523
sub_1:Test (Best Model) - Loss: 1.5333 - Accuracy: 0.2899 - F1: 0.2000
sub_25:Test (Best Model) - Loss: 1.2670 - Accuracy: 0.4412 - F1: 0.4174
sub_7:Test (Best Model) - Loss: 1.3793 - Accuracy: 0.3088 - F1: 0.3202
sub_26:Test (Best Model) - Loss: 1.6432 - Accuracy: 0.2500 - F1: 0.1809
sub_2:Test (Best Model) - Loss: 1.5489 - Accuracy: 0.1765 - F1: 0.1578
sub_8:Test (Best Model) - Loss: 1.3874 - Accuracy: 0.2647 - F1: 0.2460
sub_5:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.1765 - F1: 0.1219
sub_22:Test (Best Model) - Loss: 1.5031 - Accuracy: 0.3188 - F1: 0.2315
sub_16:Test (Best Model) - Loss: 1.3849 - Accuracy: 0.2647 - F1: 0.2901
sub_13:Test (Best Model) - Loss: 1.4978 - Accuracy: 0.3913 - F1: 0.3341
sub_18:Test (Best Model) - Loss: 1.5822 - Accuracy: 0.2206 - F1: 0.1475
sub_24:Test (Best Model) - Loss: 1.4007 - Accuracy: 0.3824 - F1: 0.3242
sub_10:Test (Best Model) - Loss: 1.4369 - Accuracy: 0.1618 - F1: 0.1100
sub_15:Test (Best Model) - Loss: 1.6541 - Accuracy: 0.2206 - F1: 0.1333
sub_28:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.1765 - F1: 0.1280
sub_29:Test (Best Model) - Loss: 1.1518 - Accuracy: 0.4559 - F1: 0.4459
sub_23:Test (Best Model) - Loss: 1.6194 - Accuracy: 0.1618 - F1: 0.1165
sub_17:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3043 - F1: 0.3058
sub_9:Test (Best Model) - Loss: 1.3587 - Accuracy: 0.3235 - F1: 0.3094
sub_27:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.3043 - F1: 0.3058
sub_7:Test (Best Model) - Loss: 1.4385 - Accuracy: 0.4265 - F1: 0.3718
sub_25:Test (Best Model) - Loss: 1.5259 - Accuracy: 0.2647 - F1: 0.1472
sub_19:Test (Best Model) - Loss: 1.4937 - Accuracy: 0.2206 - F1: 0.1454
sub_8:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.3088 - F1: 0.2040
sub_4:Test (Best Model) - Loss: 1.5038 - Accuracy: 0.2899 - F1: 0.1782
sub_13:Test (Best Model) - Loss: 1.3872 - Accuracy: 0.3768 - F1: 0.3189
sub_1:Test (Best Model) - Loss: 1.5139 - Accuracy: 0.2609 - F1: 0.2349
sub_3:Test (Best Model) - Loss: 1.4744 - Accuracy: 0.2029 - F1: 0.1525
sub_18:Test (Best Model) - Loss: 1.4510 - Accuracy: 0.2353 - F1: 0.1755
sub_15:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2353 - F1: 0.1645
sub_21:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.4412 - F1: 0.3448
sub_12:Test (Best Model) - Loss: 1.1679 - Accuracy: 0.4493 - F1: 0.4131
sub_28:Test (Best Model) - Loss: 1.7827 - Accuracy: 0.2647 - F1: 0.1303
sub_9:Test (Best Model) - Loss: 1.4854 - Accuracy: 0.2647 - F1: 0.2178
sub_11:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.3913 - F1: 0.3684
sub_27:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.1739 - F1: 0.1524
sub_17:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.1739 - F1: 0.1524
sub_22:Test (Best Model) - Loss: 1.3717 - Accuracy: 0.3913 - F1: 0.3823
sub_14:Test (Best Model) - Loss: 1.4140 - Accuracy: 0.3088 - F1: 0.3086
sub_16:Test (Best Model) - Loss: 1.3768 - Accuracy: 0.3824 - F1: 0.3106
sub_2:Test (Best Model) - Loss: 1.4107 - Accuracy: 0.2899 - F1: 0.2289
sub_20:Test (Best Model) - Loss: 1.3844 - Accuracy: 0.3529 - F1: 0.2916
sub_7:Test (Best Model) - Loss: 1.3565 - Accuracy: 0.3529 - F1: 0.3015
sub_1:Test (Best Model) - Loss: 1.5129 - Accuracy: 0.2500 - F1: 0.1803
sub_6:Test (Best Model) - Loss: 1.3456 - Accuracy: 0.3623 - F1: 0.3402
sub_26:Test (Best Model) - Loss: 1.4923 - Accuracy: 0.2647 - F1: 0.2377
sub_23:Test (Best Model) - Loss: 1.7280 - Accuracy: 0.1739 - F1: 0.1325
sub_13:Test (Best Model) - Loss: 1.5536 - Accuracy: 0.3824 - F1: 0.2858
sub_3:Test (Best Model) - Loss: 1.4634 - Accuracy: 0.3478 - F1: 0.3034
sub_10:Test (Best Model) - Loss: 1.3775 - Accuracy: 0.2609 - F1: 0.1756
sub_18:Test (Best Model) - Loss: 1.4327 - Accuracy: 0.3971 - F1: 0.3189
sub_12:Test (Best Model) - Loss: 1.3757 - Accuracy: 0.4203 - F1: 0.3923
sub_15:Test (Best Model) - Loss: 1.8201 - Accuracy: 0.1176 - F1: 0.1000
sub_29:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2059 - F1: 0.1478
sub_21:Test (Best Model) - Loss: 1.5874 - Accuracy: 0.1765 - F1: 0.1478
sub_25:Test (Best Model) - Loss: 1.5089 - Accuracy: 0.3971 - F1: 0.3452
sub_11:Test (Best Model) - Loss: 1.5579 - Accuracy: 0.2899 - F1: 0.1726
sub_4:Test (Best Model) - Loss: 1.4706 - Accuracy: 0.3188 - F1: 0.1985
sub_27:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.3676 - F1: 0.2744
sub_17:Test (Best Model) - Loss: 1.3264 - Accuracy: 0.3676 - F1: 0.2744
sub_14:Test (Best Model) - Loss: 1.5284 - Accuracy: 0.2647 - F1: 0.2367
sub_16:Test (Best Model) - Loss: 1.6469 - Accuracy: 0.2353 - F1: 0.1617
sub_20:Test (Best Model) - Loss: 1.6566 - Accuracy: 0.2029 - F1: 0.1774
sub_5:Test (Best Model) - Loss: 1.5404 - Accuracy: 0.3676 - F1: 0.3011
sub_7:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.3235 - F1: 0.2292
sub_24:Test (Best Model) - Loss: 1.5551 - Accuracy: 0.2353 - F1: 0.1786
sub_1:Test (Best Model) - Loss: 1.5175 - Accuracy: 0.3382 - F1: 0.2126
sub_19:Test (Best Model) - Loss: 1.5217 - Accuracy: 0.2353 - F1: 0.1730
sub_23:Test (Best Model) - Loss: 1.3929 - Accuracy: 0.3188 - F1: 0.2348
sub_3:Test (Best Model) - Loss: 1.3708 - Accuracy: 0.2899 - F1: 0.2358
sub_28:Test (Best Model) - Loss: 1.8732 - Accuracy: 0.1618 - F1: 0.1120
sub_21:Test (Best Model) - Loss: 1.6820 - Accuracy: 0.1765 - F1: 0.1651
sub_8:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2500 - F1: 0.1796
sub_12:Test (Best Model) - Loss: 1.4274 - Accuracy: 0.2059 - F1: 0.1717
sub_11:Test (Best Model) - Loss: 1.5171 - Accuracy: 0.3623 - F1: 0.2802
sub_22:Test (Best Model) - Loss: 1.5074 - Accuracy: 0.2174 - F1: 0.1825
sub_4:Test (Best Model) - Loss: 1.2945 - Accuracy: 0.4348 - F1: 0.3802
sub_6:Test (Best Model) - Loss: 1.6222 - Accuracy: 0.2319 - F1: 0.1947
sub_27:Test (Best Model) - Loss: 1.4760 - Accuracy: 0.1765 - F1: 0.1384
sub_14:Test (Best Model) - Loss: 1.4315 - Accuracy: 0.3676 - F1: 0.2732
sub_17:Test (Best Model) - Loss: 1.4760 - Accuracy: 0.1765 - F1: 0.1384
sub_15:Test (Best Model) - Loss: 1.2576 - Accuracy: 0.3382 - F1: 0.3695
sub_9:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.2353 - F1: 0.1598
sub_13:Test (Best Model) - Loss: 1.4651 - Accuracy: 0.2941 - F1: 0.2834
sub_19:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.2500 - F1: 0.2269
sub_23:Test (Best Model) - Loss: 1.9576 - Accuracy: 0.2029 - F1: 0.1095
sub_10:Test (Best Model) - Loss: 1.7115 - Accuracy: 0.1884 - F1: 0.1206
sub_3:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.4058 - F1: 0.3186
sub_8:Test (Best Model) - Loss: 1.4827 - Accuracy: 0.2647 - F1: 0.2264
sub_11:Test (Best Model) - Loss: 1.5838 - Accuracy: 0.2609 - F1: 0.2128
sub_29:Test (Best Model) - Loss: 1.2818 - Accuracy: 0.3623 - F1: 0.3180
sub_28:Test (Best Model) - Loss: 1.6309 - Accuracy: 0.1765 - F1: 0.1199
sub_4:Test (Best Model) - Loss: 1.5030 - Accuracy: 0.1739 - F1: 0.1360
sub_17:Test (Best Model) - Loss: 1.7762 - Accuracy: 0.2059 - F1: 0.1061
sub_24:Test (Best Model) - Loss: 1.6270 - Accuracy: 0.2500 - F1: 0.1615
sub_27:Test (Best Model) - Loss: 1.7762 - Accuracy: 0.2059 - F1: 0.1061
sub_26:Test (Best Model) - Loss: 1.6574 - Accuracy: 0.1912 - F1: 0.1472
sub_14:Test (Best Model) - Loss: 1.6677 - Accuracy: 0.2353 - F1: 0.1815
sub_7:Test (Best Model) - Loss: 1.7019 - Accuracy: 0.1765 - F1: 0.1288
sub_5:Test (Best Model) - Loss: 1.4079 - Accuracy: 0.2206 - F1: 0.1802
sub_20:Test (Best Model) - Loss: 1.5181 - Accuracy: 0.2754 - F1: 0.1913
sub_19:Test (Best Model) - Loss: 1.5678 - Accuracy: 0.2647 - F1: 0.1636
sub_13:Test (Best Model) - Loss: 1.8085 - Accuracy: 0.1176 - F1: 0.0731
sub_2:Test (Best Model) - Loss: 1.3866 - Accuracy: 0.3333 - F1: 0.2432
sub_25:Test (Best Model) - Loss: 1.4208 - Accuracy: 0.2794 - F1: 0.2449
sub_3:Test (Best Model) - Loss: 1.4945 - Accuracy: 0.2319 - F1: 0.1868
sub_16:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.3676 - F1: 0.3361
sub_8:Test (Best Model) - Loss: 1.4915 - Accuracy: 0.2941 - F1: 0.2177
sub_10:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.3913 - F1: 0.3820
sub_11:Test (Best Model) - Loss: 1.3466 - Accuracy: 0.3333 - F1: 0.2590
sub_15:Test (Best Model) - Loss: 1.3864 - Accuracy: 0.2941 - F1: 0.2936
sub_1:Test (Best Model) - Loss: 1.6348 - Accuracy: 0.1912 - F1: 0.1038
sub_17:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.4559 - F1: 0.4341
sub_4:Test (Best Model) - Loss: 1.4827 - Accuracy: 0.2029 - F1: 0.1923
sub_18:Test (Best Model) - Loss: 1.3723 - Accuracy: 0.3676 - F1: 0.3101
sub_21:Test (Best Model) - Loss: 1.2838 - Accuracy: 0.4412 - F1: 0.4032
sub_12:Test (Best Model) - Loss: 1.7107 - Accuracy: 0.2500 - F1: 0.1680
sub_26:Test (Best Model) - Loss: 1.4210 - Accuracy: 0.3529 - F1: 0.2777
sub_27:Test (Best Model) - Loss: 1.2881 - Accuracy: 0.4559 - F1: 0.4341
sub_19:Test (Best Model) - Loss: 1.5466 - Accuracy: 0.2647 - F1: 0.2233
sub_28:Test (Best Model) - Loss: 1.3832 - Accuracy: 0.3676 - F1: 0.3243
sub_10:Test (Best Model) - Loss: 1.1904 - Accuracy: 0.4783 - F1: 0.4867
sub_8:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.3382 - F1: 0.2376
sub_11:Test (Best Model) - Loss: 1.4617 - Accuracy: 0.3333 - F1: 0.2417
sub_23:Test (Best Model) - Loss: 1.1871 - Accuracy: 0.4928 - F1: 0.4854
sub_18:Test (Best Model) - Loss: 1.4996 - Accuracy: 0.2647 - F1: 0.2236
sub_7:Test (Best Model) - Loss: 1.2278 - Accuracy: 0.3676 - F1: 0.3940
sub_17:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2353 - F1: 0.2343
sub_6:Test (Best Model) - Loss: 1.5822 - Accuracy: 0.1739 - F1: 0.1338
sub_2:Test (Best Model) - Loss: 1.6215 - Accuracy: 0.2174 - F1: 0.1149
sub_1:Test (Best Model) - Loss: 1.4459 - Accuracy: 0.3824 - F1: 0.3730
sub_22:Test (Best Model) - Loss: 1.5465 - Accuracy: 0.1618 - F1: 0.1263
sub_20:Test (Best Model) - Loss: 1.5487 - Accuracy: 0.2174 - F1: 0.1542
sub_5:Test (Best Model) - Loss: 1.3225 - Accuracy: 0.1471 - F1: 0.1546
sub_26:Test (Best Model) - Loss: 1.4006 - Accuracy: 0.3971 - F1: 0.3127
sub_25:Test (Best Model) - Loss: 1.4459 - Accuracy: 0.2059 - F1: 0.2034
sub_9:Test (Best Model) - Loss: 1.6614 - Accuracy: 0.2647 - F1: 0.1690
sub_29:Test (Best Model) - Loss: 1.4681 - Accuracy: 0.2899 - F1: 0.2394
sub_14:Test (Best Model) - Loss: 1.9278 - Accuracy: 0.0294 - F1: 0.0274
sub_27:Test (Best Model) - Loss: 1.4012 - Accuracy: 0.2353 - F1: 0.2343
sub_24:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.1618 - F1: 0.1338
sub_21:Test (Best Model) - Loss: 1.5424 - Accuracy: 0.1912 - F1: 0.1687
sub_28:Test (Best Model) - Loss: 1.7074 - Accuracy: 0.1618 - F1: 0.1568
sub_10:Test (Best Model) - Loss: 1.4715 - Accuracy: 0.2174 - F1: 0.2029
sub_4:Test (Best Model) - Loss: 1.7319 - Accuracy: 0.2319 - F1: 0.1936
sub_13:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.3824 - F1: 0.3689
sub_7:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.3235 - F1: 0.2865
sub_16:Test (Best Model) - Loss: 1.3135 - Accuracy: 0.3382 - F1: 0.2658
sub_18:Test (Best Model) - Loss: 1.7125 - Accuracy: 0.0882 - F1: 0.0566
sub_3:Test (Best Model) - Loss: 1.2148 - Accuracy: 0.4638 - F1: 0.4544
sub_6:Test (Best Model) - Loss: 1.5201 - Accuracy: 0.3478 - F1: 0.2252
sub_20:Test (Best Model) - Loss: 1.1014 - Accuracy: 0.5217 - F1: 0.5326
sub_25:Test (Best Model) - Loss: 1.4810 - Accuracy: 0.3235 - F1: 0.2548
sub_9:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.2353 - F1: 0.1399
sub_29:Test (Best Model) - Loss: 1.8199 - Accuracy: 0.1594 - F1: 0.0724
sub_8:Test (Best Model) - Loss: 1.8265 - Accuracy: 0.2647 - F1: 0.1934
sub_19:Test (Best Model) - Loss: 1.1343 - Accuracy: 0.6029 - F1: 0.5949
sub_24:Test (Best Model) - Loss: 1.6324 - Accuracy: 0.1765 - F1: 0.1874
sub_12:Test (Best Model) - Loss: 1.6400 - Accuracy: 0.2353 - F1: 0.1652
sub_2:Test (Best Model) - Loss: 1.3088 - Accuracy: 0.2899 - F1: 0.3053
sub_13:Test (Best Model) - Loss: 1.3985 - Accuracy: 0.2941 - F1: 0.2014
sub_26:Test (Best Model) - Loss: 1.6236 - Accuracy: 0.1765 - F1: 0.0870
sub_23:Test (Best Model) - Loss: 1.4685 - Accuracy: 0.3478 - F1: 0.3214
sub_18:Test (Best Model) - Loss: 1.6318 - Accuracy: 0.2206 - F1: 0.1484
sub_4:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2899 - F1: 0.2138
sub_25:Test (Best Model) - Loss: 1.5030 - Accuracy: 0.3235 - F1: 0.2313
sub_6:Test (Best Model) - Loss: 1.5722 - Accuracy: 0.1884 - F1: 0.1367
sub_1:Test (Best Model) - Loss: 1.3022 - Accuracy: 0.3676 - F1: 0.3824
sub_22:Test (Best Model) - Loss: 1.5079 - Accuracy: 0.2353 - F1: 0.1286
sub_24:Test (Best Model) - Loss: 1.4557 - Accuracy: 0.2500 - F1: 0.2365
sub_20:Test (Best Model) - Loss: 1.4987 - Accuracy: 0.2029 - F1: 0.1451
sub_11:Test (Best Model) - Loss: 1.3616 - Accuracy: 0.3478 - F1: 0.2832
sub_29:Test (Best Model) - Loss: 1.1662 - Accuracy: 0.5507 - F1: 0.4910
sub_5:Test (Best Model) - Loss: 1.8152 - Accuracy: 0.3824 - F1: 0.2540
sub_3:Test (Best Model) - Loss: 1.3508 - Accuracy: 0.2899 - F1: 0.2946
sub_4:Test (Best Model) - Loss: 0.9887 - Accuracy: 0.6812 - F1: 0.6822
sub_8:Test (Best Model) - Loss: 1.9769 - Accuracy: 0.1324 - F1: 0.0634
sub_16:Test (Best Model) - Loss: 1.3962 - Accuracy: 0.2941 - F1: 0.1891
sub_19:Test (Best Model) - Loss: 1.4313 - Accuracy: 0.2794 - F1: 0.2693
sub_11:Test (Best Model) - Loss: 1.4417 - Accuracy: 0.2899 - F1: 0.2534
sub_14:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.3382 - F1: 0.2969
sub_22:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2500 - F1: 0.1818
sub_6:Test (Best Model) - Loss: 1.0236 - Accuracy: 0.6957 - F1: 0.6948
sub_5:Test (Best Model) - Loss: 1.7870 - Accuracy: 0.1618 - F1: 0.1171
sub_9:Test (Best Model) - Loss: 1.1765 - Accuracy: 0.3382 - F1: 0.3693
sub_26:Test (Best Model) - Loss: 1.3077 - Accuracy: 0.3824 - F1: 0.3958
sub_18:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.2941 - F1: 0.2774
sub_2:Test (Best Model) - Loss: 1.4280 - Accuracy: 0.2609 - F1: 0.2359
sub_25:Test (Best Model) - Loss: 1.4237 - Accuracy: 0.3235 - F1: 0.2977
sub_12:Test (Best Model) - Loss: 1.0971 - Accuracy: 0.4853 - F1: 0.4687
sub_11:Test (Best Model) - Loss: 1.5289 - Accuracy: 0.3188 - F1: 0.2744
sub_9:Test (Best Model) - Loss: 1.4929 - Accuracy: 0.1471 - F1: 0.1716
sub_4:Test (Best Model) - Loss: 1.3300 - Accuracy: 0.4058 - F1: 0.3735
sub_25:Test (Best Model) - Loss: 1.2131 - Accuracy: 0.3824 - F1: 0.3890
sub_5:Test (Best Model) - Loss: 1.2120 - Accuracy: 0.3824 - F1: 0.3550
sub_14:Test (Best Model) - Loss: 1.5570 - Accuracy: 0.2794 - F1: 0.2238
sub_29:Test (Best Model) - Loss: 1.5188 - Accuracy: 0.1884 - F1: 0.1347
sub_22:Test (Best Model) - Loss: 1.2624 - Accuracy: 0.4706 - F1: 0.4196
sub_8:Test (Best Model) - Loss: 1.0599 - Accuracy: 0.5882 - F1: 0.5504
sub_18:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.3676 - F1: 0.2858
sub_26:Test (Best Model) - Loss: 1.4825 - Accuracy: 0.2353 - F1: 0.1749
sub_5:Test (Best Model) - Loss: 1.5845 - Accuracy: 0.1471 - F1: 0.1342
sub_6:Test (Best Model) - Loss: 1.3278 - Accuracy: 0.3333 - F1: 0.2983
sub_12:Test (Best Model) - Loss: 1.3995 - Accuracy: 0.1912 - F1: 0.2138
sub_22:Test (Best Model) - Loss: 1.4749 - Accuracy: 0.3235 - F1: 0.2980
sub_11:Test (Best Model) - Loss: 1.1822 - Accuracy: 0.4203 - F1: 0.3747
sub_8:Test (Best Model) - Loss: 1.2923 - Accuracy: 0.3235 - F1: 0.3095
sub_25:Test (Best Model) - Loss: 1.4665 - Accuracy: 0.1912 - F1: 0.2022

=== Summary Results ===

acc: 29.86 ± 2.04
F1: 24.24 ± 2.24
acc-in: 36.49 ± 2.27
F1-in: 31.03 ± 2.41
