lr: 0.0001
sub_22:Test (Best Model) - Loss: 1.2261 - Accuracy: 0.5000 - F1: 0.4428
sub_7:Test (Best Model) - Loss: 1.0912 - Accuracy: 0.9265 - F1: 0.9230
sub_3:Test (Best Model) - Loss: 1.1745 - Accuracy: 0.6176 - F1: 0.5892
sub_27:Test (Best Model) - Loss: 1.1566 - Accuracy: 0.6957 - F1: 0.6827
sub_2:Test (Best Model) - Loss: 1.1067 - Accuracy: 0.6812 - F1: 0.6723
sub_20:Test (Best Model) - Loss: 1.1746 - Accuracy: 0.5882 - F1: 0.5647
sub_17:Test (Best Model) - Loss: 1.1566 - Accuracy: 0.6957 - F1: 0.6827
sub_8:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.6029 - F1: 0.5707
sub_18:Test (Best Model) - Loss: 1.1133 - Accuracy: 0.6667 - F1: 0.6579
sub_5:Test (Best Model) - Loss: 1.2118 - Accuracy: 0.6324 - F1: 0.5872
sub_10:Test (Best Model) - Loss: 1.2533 - Accuracy: 0.4853 - F1: 0.5199
sub_6:Test (Best Model) - Loss: 1.2370 - Accuracy: 0.4853 - F1: 0.4375
sub_1:Test (Best Model) - Loss: 1.1562 - Accuracy: 0.6618 - F1: 0.6818
sub_13:Test (Best Model) - Loss: 1.2475 - Accuracy: 0.4412 - F1: 0.4566
sub_26:Test (Best Model) - Loss: 1.1254 - Accuracy: 0.6667 - F1: 0.6773
sub_11:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.6377 - F1: 0.6291
sub_4:Test (Best Model) - Loss: 1.0942 - Accuracy: 0.6377 - F1: 0.6468
sub_21:Test (Best Model) - Loss: 1.1528 - Accuracy: 0.7059 - F1: 0.7202
sub_12:Test (Best Model) - Loss: 1.1571 - Accuracy: 0.6912 - F1: 0.7000
sub_28:Test (Best Model) - Loss: 1.2362 - Accuracy: 0.6471 - F1: 0.5860
sub_25:Test (Best Model) - Loss: 1.0814 - Accuracy: 0.8696 - F1: 0.8636
sub_24:Test (Best Model) - Loss: 1.1560 - Accuracy: 0.6324 - F1: 0.6113
sub_19:Test (Best Model) - Loss: 1.2477 - Accuracy: 0.4265 - F1: 0.4011
sub_9:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.5735 - F1: 0.5974
sub_16:Test (Best Model) - Loss: 1.1132 - Accuracy: 0.6765 - F1: 0.6835
sub_14:Test (Best Model) - Loss: 1.3114 - Accuracy: 0.3676 - F1: 0.2835
sub_23:Test (Best Model) - Loss: 1.0881 - Accuracy: 0.7391 - F1: 0.7204
sub_29:Test (Best Model) - Loss: 1.1668 - Accuracy: 0.5294 - F1: 0.5757
sub_27:Test (Best Model) - Loss: 1.1676 - Accuracy: 0.6232 - F1: 0.6042
sub_15:Test (Best Model) - Loss: 1.0738 - Accuracy: 0.7059 - F1: 0.7224
sub_5:Test (Best Model) - Loss: 1.2484 - Accuracy: 0.7059 - F1: 0.6357
sub_10:Test (Best Model) - Loss: 1.2952 - Accuracy: 0.4412 - F1: 0.4554
sub_8:Test (Best Model) - Loss: 1.2532 - Accuracy: 0.5147 - F1: 0.4807
sub_17:Test (Best Model) - Loss: 1.1676 - Accuracy: 0.6232 - F1: 0.6042
sub_9:Test (Best Model) - Loss: 1.2542 - Accuracy: 0.4853 - F1: 0.5257
sub_3:Test (Best Model) - Loss: 1.1652 - Accuracy: 0.6618 - F1: 0.6127
sub_4:Test (Best Model) - Loss: 1.1373 - Accuracy: 0.6232 - F1: 0.6041
sub_28:Test (Best Model) - Loss: 1.2915 - Accuracy: 0.4559 - F1: 0.4345
sub_24:Test (Best Model) - Loss: 1.2263 - Accuracy: 0.6029 - F1: 0.5861
sub_6:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.5441 - F1: 0.5098
sub_7:Test (Best Model) - Loss: 0.9747 - Accuracy: 0.9559 - F1: 0.9520
sub_20:Test (Best Model) - Loss: 1.1033 - Accuracy: 0.5294 - F1: 0.4908
sub_25:Test (Best Model) - Loss: 1.0800 - Accuracy: 0.7681 - F1: 0.7713
sub_11:Test (Best Model) - Loss: 1.1077 - Accuracy: 0.7391 - F1: 0.7412
sub_21:Test (Best Model) - Loss: 1.1160 - Accuracy: 0.7500 - F1: 0.7505
sub_22:Test (Best Model) - Loss: 1.2774 - Accuracy: 0.5735 - F1: 0.5121
sub_16:Test (Best Model) - Loss: 1.1689 - Accuracy: 0.6471 - F1: 0.6553
sub_12:Test (Best Model) - Loss: 1.1734 - Accuracy: 0.4853 - F1: 0.5081
sub_19:Test (Best Model) - Loss: 1.3058 - Accuracy: 0.2941 - F1: 0.2569
sub_2:Test (Best Model) - Loss: 1.1128 - Accuracy: 0.6667 - F1: 0.6514
sub_1:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.6029 - F1: 0.6083
sub_13:Test (Best Model) - Loss: 1.1812 - Accuracy: 0.5441 - F1: 0.5222
sub_18:Test (Best Model) - Loss: 1.1431 - Accuracy: 0.5942 - F1: 0.5776
sub_14:Test (Best Model) - Loss: 1.3206 - Accuracy: 0.3382 - F1: 0.2470
sub_29:Test (Best Model) - Loss: 1.2191 - Accuracy: 0.5441 - F1: 0.5565
sub_5:Test (Best Model) - Loss: 1.2325 - Accuracy: 0.7059 - F1: 0.6376
sub_10:Test (Best Model) - Loss: 1.2372 - Accuracy: 0.5000 - F1: 0.5244
sub_26:Test (Best Model) - Loss: 1.0958 - Accuracy: 0.7391 - F1: 0.7511
sub_8:Test (Best Model) - Loss: 1.2378 - Accuracy: 0.4706 - F1: 0.4428
sub_23:Test (Best Model) - Loss: 1.0310 - Accuracy: 0.8841 - F1: 0.8876
sub_3:Test (Best Model) - Loss: 1.1040 - Accuracy: 0.6765 - F1: 0.6523
sub_25:Test (Best Model) - Loss: 1.0881 - Accuracy: 0.8406 - F1: 0.8373
sub_22:Test (Best Model) - Loss: 1.3014 - Accuracy: 0.4412 - F1: 0.3770
sub_9:Test (Best Model) - Loss: 1.2106 - Accuracy: 0.4706 - F1: 0.4971
sub_15:Test (Best Model) - Loss: 1.1694 - Accuracy: 0.6765 - F1: 0.6892
sub_27:Test (Best Model) - Loss: 1.1264 - Accuracy: 0.6667 - F1: 0.6758
sub_6:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.5882 - F1: 0.5727
sub_20:Test (Best Model) - Loss: 1.1487 - Accuracy: 0.5294 - F1: 0.4986
sub_4:Test (Best Model) - Loss: 1.1356 - Accuracy: 0.5797 - F1: 0.5361
sub_24:Test (Best Model) - Loss: 1.2126 - Accuracy: 0.5882 - F1: 0.5855
sub_17:Test (Best Model) - Loss: 1.1264 - Accuracy: 0.6667 - F1: 0.6758
sub_11:Test (Best Model) - Loss: 1.1627 - Accuracy: 0.7101 - F1: 0.7159
sub_28:Test (Best Model) - Loss: 1.2788 - Accuracy: 0.5588 - F1: 0.5155
sub_19:Test (Best Model) - Loss: 1.2911 - Accuracy: 0.3235 - F1: 0.3240
sub_16:Test (Best Model) - Loss: 1.2030 - Accuracy: 0.5441 - F1: 0.5739
sub_7:Test (Best Model) - Loss: 1.0326 - Accuracy: 0.9265 - F1: 0.9179
sub_13:Test (Best Model) - Loss: 1.2511 - Accuracy: 0.4559 - F1: 0.5010
sub_1:Test (Best Model) - Loss: 1.1615 - Accuracy: 0.6029 - F1: 0.6066
sub_8:Test (Best Model) - Loss: 1.2240 - Accuracy: 0.5735 - F1: 0.5448
sub_22:Test (Best Model) - Loss: 1.3223 - Accuracy: 0.3824 - F1: 0.3782
sub_10:Test (Best Model) - Loss: 1.3138 - Accuracy: 0.4118 - F1: 0.4381
sub_12:Test (Best Model) - Loss: 1.1482 - Accuracy: 0.6765 - F1: 0.6826
sub_18:Test (Best Model) - Loss: 1.1163 - Accuracy: 0.6812 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 1.1858 - Accuracy: 0.5217 - F1: 0.4422
sub_14:Test (Best Model) - Loss: 1.3193 - Accuracy: 0.3824 - F1: 0.3182
sub_5:Test (Best Model) - Loss: 1.2334 - Accuracy: 0.5882 - F1: 0.5548
sub_21:Test (Best Model) - Loss: 1.1147 - Accuracy: 0.7206 - F1: 0.7244
sub_26:Test (Best Model) - Loss: 1.1547 - Accuracy: 0.7101 - F1: 0.7239
sub_29:Test (Best Model) - Loss: 1.1733 - Accuracy: 0.4265 - F1: 0.4698
sub_6:Test (Best Model) - Loss: 1.2155 - Accuracy: 0.5735 - F1: 0.5321
sub_3:Test (Best Model) - Loss: 1.1240 - Accuracy: 0.7059 - F1: 0.6812
sub_25:Test (Best Model) - Loss: 1.0399 - Accuracy: 0.7826 - F1: 0.7758
sub_28:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.4265 - F1: 0.3925
sub_20:Test (Best Model) - Loss: 1.1258 - Accuracy: 0.5588 - F1: 0.5206
sub_15:Test (Best Model) - Loss: 1.1957 - Accuracy: 0.6176 - F1: 0.6220
sub_9:Test (Best Model) - Loss: 1.2088 - Accuracy: 0.4412 - F1: 0.4818
sub_1:Test (Best Model) - Loss: 1.2131 - Accuracy: 0.5147 - F1: 0.5149
sub_2:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.5652 - F1: 0.4987
sub_24:Test (Best Model) - Loss: 1.2093 - Accuracy: 0.5294 - F1: 0.4842
sub_4:Test (Best Model) - Loss: 1.1072 - Accuracy: 0.5507 - F1: 0.5489
sub_13:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.5000 - F1: 0.4512
sub_27:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.7536 - F1: 0.7544
sub_10:Test (Best Model) - Loss: 1.2280 - Accuracy: 0.5000 - F1: 0.5416
sub_21:Test (Best Model) - Loss: 1.1580 - Accuracy: 0.8088 - F1: 0.8060
sub_16:Test (Best Model) - Loss: 1.1540 - Accuracy: 0.6029 - F1: 0.6216
sub_17:Test (Best Model) - Loss: 1.0758 - Accuracy: 0.7536 - F1: 0.7544
sub_11:Test (Best Model) - Loss: 1.1524 - Accuracy: 0.7391 - F1: 0.7407
sub_19:Test (Best Model) - Loss: 1.2311 - Accuracy: 0.3824 - F1: 0.3556
sub_5:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.5147 - F1: 0.5014
sub_26:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.6232 - F1: 0.6115
sub_23:Test (Best Model) - Loss: 1.0023 - Accuracy: 0.6957 - F1: 0.6875
sub_7:Test (Best Model) - Loss: 1.0143 - Accuracy: 0.8824 - F1: 0.8760
sub_18:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.5797 - F1: 0.5857
sub_8:Test (Best Model) - Loss: 1.1716 - Accuracy: 0.5735 - F1: 0.5442
sub_14:Test (Best Model) - Loss: 1.3136 - Accuracy: 0.3971 - F1: 0.3280
sub_20:Test (Best Model) - Loss: 1.1873 - Accuracy: 0.5441 - F1: 0.5074
sub_22:Test (Best Model) - Loss: 1.2474 - Accuracy: 0.5147 - F1: 0.4666
sub_2:Test (Best Model) - Loss: 1.1907 - Accuracy: 0.5942 - F1: 0.5249
sub_12:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.6618 - F1: 0.6732
sub_29:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.5000 - F1: 0.5253
sub_28:Test (Best Model) - Loss: 1.2998 - Accuracy: 0.5735 - F1: 0.5008
sub_3:Test (Best Model) - Loss: 1.1187 - Accuracy: 0.6471 - F1: 0.6379
sub_24:Test (Best Model) - Loss: 1.2024 - Accuracy: 0.5147 - F1: 0.4911
sub_6:Test (Best Model) - Loss: 1.1489 - Accuracy: 0.6324 - F1: 0.5757
sub_13:Test (Best Model) - Loss: 1.2056 - Accuracy: 0.5441 - F1: 0.5461
sub_19:Test (Best Model) - Loss: 1.2841 - Accuracy: 0.2941 - F1: 0.2634
sub_25:Test (Best Model) - Loss: 1.0592 - Accuracy: 0.8261 - F1: 0.8182
sub_4:Test (Best Model) - Loss: 1.0967 - Accuracy: 0.5652 - F1: 0.5406
sub_10:Test (Best Model) - Loss: 1.2992 - Accuracy: 0.5441 - F1: 0.5142
sub_11:Test (Best Model) - Loss: 1.1176 - Accuracy: 0.7826 - F1: 0.7849
sub_1:Test (Best Model) - Loss: 1.1328 - Accuracy: 0.5588 - F1: 0.5522
sub_15:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.6029 - F1: 0.5976
sub_7:Test (Best Model) - Loss: 1.1239 - Accuracy: 0.8382 - F1: 0.8263
sub_18:Test (Best Model) - Loss: 1.1360 - Accuracy: 0.6812 - F1: 0.6963
sub_27:Test (Best Model) - Loss: 1.0718 - Accuracy: 0.6522 - F1: 0.6534
sub_9:Test (Best Model) - Loss: 1.1934 - Accuracy: 0.4853 - F1: 0.4728
sub_2:Test (Best Model) - Loss: 1.0517 - Accuracy: 0.7941 - F1: 0.7986
sub_16:Test (Best Model) - Loss: 1.1352 - Accuracy: 0.6324 - F1: 0.5936
sub_21:Test (Best Model) - Loss: 1.0646 - Accuracy: 0.7794 - F1: 0.7692
sub_26:Test (Best Model) - Loss: 1.0716 - Accuracy: 0.7101 - F1: 0.7264
sub_8:Test (Best Model) - Loss: 1.1090 - Accuracy: 0.7647 - F1: 0.7756
sub_17:Test (Best Model) - Loss: 1.0718 - Accuracy: 0.6522 - F1: 0.6534
sub_29:Test (Best Model) - Loss: 1.2141 - Accuracy: 0.4412 - F1: 0.4730
sub_20:Test (Best Model) - Loss: 1.0754 - Accuracy: 0.7206 - F1: 0.6528
sub_14:Test (Best Model) - Loss: 1.3101 - Accuracy: 0.3824 - F1: 0.3086
sub_4:Test (Best Model) - Loss: 1.1503 - Accuracy: 0.6957 - F1: 0.6936
sub_5:Test (Best Model) - Loss: 1.0696 - Accuracy: 0.7647 - F1: 0.7144
sub_6:Test (Best Model) - Loss: 1.1335 - Accuracy: 0.6667 - F1: 0.6784
sub_28:Test (Best Model) - Loss: 1.3554 - Accuracy: 0.3676 - F1: 0.2900
sub_23:Test (Best Model) - Loss: 1.1534 - Accuracy: 0.6812 - F1: 0.6692
sub_22:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.4783 - F1: 0.4240
sub_3:Test (Best Model) - Loss: 1.1421 - Accuracy: 0.6232 - F1: 0.5842
sub_12:Test (Best Model) - Loss: 1.1375 - Accuracy: 0.6324 - F1: 0.6080
sub_24:Test (Best Model) - Loss: 1.0985 - Accuracy: 0.6765 - F1: 0.6030
sub_13:Test (Best Model) - Loss: 1.2258 - Accuracy: 0.5362 - F1: 0.4970
sub_11:Test (Best Model) - Loss: 1.1376 - Accuracy: 0.7246 - F1: 0.7280
sub_10:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.4412 - F1: 0.3941
sub_19:Test (Best Model) - Loss: 1.1903 - Accuracy: 0.5882 - F1: 0.5675
sub_1:Test (Best Model) - Loss: 1.1977 - Accuracy: 0.4928 - F1: 0.4801
sub_25:Test (Best Model) - Loss: 1.0596 - Accuracy: 0.7353 - F1: 0.7249
sub_18:Test (Best Model) - Loss: 1.1812 - Accuracy: 0.5441 - F1: 0.5511
sub_8:Test (Best Model) - Loss: 1.1288 - Accuracy: 0.6618 - F1: 0.6136
sub_7:Test (Best Model) - Loss: 1.1330 - Accuracy: 0.6765 - F1: 0.6004
sub_16:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.7353 - F1: 0.7409
sub_29:Test (Best Model) - Loss: 1.0741 - Accuracy: 0.7353 - F1: 0.7376
sub_9:Test (Best Model) - Loss: 1.1097 - Accuracy: 0.7206 - F1: 0.7131
sub_21:Test (Best Model) - Loss: 1.0429 - Accuracy: 0.8382 - F1: 0.8381
sub_15:Test (Best Model) - Loss: 1.1077 - Accuracy: 0.5441 - F1: 0.5262
sub_14:Test (Best Model) - Loss: 1.1714 - Accuracy: 0.5147 - F1: 0.5140
sub_3:Test (Best Model) - Loss: 1.2031 - Accuracy: 0.5217 - F1: 0.5109
sub_5:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.7500 - F1: 0.6675
sub_20:Test (Best Model) - Loss: 1.1058 - Accuracy: 0.7206 - F1: 0.6965
sub_26:Test (Best Model) - Loss: 1.1092 - Accuracy: 0.6324 - F1: 0.6211
sub_6:Test (Best Model) - Loss: 1.1307 - Accuracy: 0.5652 - F1: 0.5618
sub_4:Test (Best Model) - Loss: 1.0542 - Accuracy: 0.7536 - F1: 0.7584
sub_2:Test (Best Model) - Loss: 0.9837 - Accuracy: 0.7794 - F1: 0.7889
sub_22:Test (Best Model) - Loss: 1.1940 - Accuracy: 0.4928 - F1: 0.4420
sub_18:Test (Best Model) - Loss: 1.2026 - Accuracy: 0.5294 - F1: 0.5354
sub_10:Test (Best Model) - Loss: 1.3691 - Accuracy: 0.2647 - F1: 0.1071
sub_27:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.5362 - F1: 0.5297
sub_1:Test (Best Model) - Loss: 1.2305 - Accuracy: 0.4783 - F1: 0.4501
sub_24:Test (Best Model) - Loss: 1.1721 - Accuracy: 0.6912 - F1: 0.6998
sub_12:Test (Best Model) - Loss: 1.1979 - Accuracy: 0.6667 - F1: 0.6474
sub_28:Test (Best Model) - Loss: 1.3589 - Accuracy: 0.3824 - F1: 0.3154
sub_19:Test (Best Model) - Loss: 1.2091 - Accuracy: 0.5588 - F1: 0.5643
sub_16:Test (Best Model) - Loss: 1.1508 - Accuracy: 0.7206 - F1: 0.7142
sub_17:Test (Best Model) - Loss: 1.1875 - Accuracy: 0.5362 - F1: 0.5297
sub_8:Test (Best Model) - Loss: 1.1789 - Accuracy: 0.6618 - F1: 0.6087
sub_25:Test (Best Model) - Loss: 1.1313 - Accuracy: 0.7500 - F1: 0.7071
sub_11:Test (Best Model) - Loss: 1.1231 - Accuracy: 0.6377 - F1: 0.6398
sub_13:Test (Best Model) - Loss: 1.2268 - Accuracy: 0.5217 - F1: 0.4483
sub_14:Test (Best Model) - Loss: 1.1891 - Accuracy: 0.4706 - F1: 0.4666
sub_7:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.5588 - F1: 0.4536
sub_26:Test (Best Model) - Loss: 1.1651 - Accuracy: 0.6324 - F1: 0.6128
sub_20:Test (Best Model) - Loss: 1.1137 - Accuracy: 0.6618 - F1: 0.6244
sub_29:Test (Best Model) - Loss: 1.0903 - Accuracy: 0.7941 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 1.1381 - Accuracy: 0.7971 - F1: 0.7902
sub_6:Test (Best Model) - Loss: 1.1931 - Accuracy: 0.5217 - F1: 0.5250
sub_18:Test (Best Model) - Loss: 1.2872 - Accuracy: 0.5588 - F1: 0.5352
sub_12:Test (Best Model) - Loss: 1.1225 - Accuracy: 0.6957 - F1: 0.7121
sub_9:Test (Best Model) - Loss: 1.0926 - Accuracy: 0.6324 - F1: 0.6420
sub_1:Test (Best Model) - Loss: 1.2528 - Accuracy: 0.5507 - F1: 0.5176
sub_15:Test (Best Model) - Loss: 1.0890 - Accuracy: 0.8088 - F1: 0.8130
sub_10:Test (Best Model) - Loss: 1.3522 - Accuracy: 0.3529 - F1: 0.2625
sub_22:Test (Best Model) - Loss: 1.2637 - Accuracy: 0.4638 - F1: 0.4163
sub_21:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.7794 - F1: 0.7652
sub_23:Test (Best Model) - Loss: 1.0478 - Accuracy: 0.5942 - F1: 0.5479
sub_28:Test (Best Model) - Loss: 1.3837 - Accuracy: 0.2794 - F1: 0.1990
sub_3:Test (Best Model) - Loss: 1.1933 - Accuracy: 0.5652 - F1: 0.5302
sub_2:Test (Best Model) - Loss: 1.0279 - Accuracy: 0.7353 - F1: 0.7284
sub_5:Test (Best Model) - Loss: 1.1727 - Accuracy: 0.6765 - F1: 0.6180
sub_16:Test (Best Model) - Loss: 1.2012 - Accuracy: 0.5735 - F1: 0.5742
sub_24:Test (Best Model) - Loss: 1.1278 - Accuracy: 0.6471 - F1: 0.5910
sub_26:Test (Best Model) - Loss: 1.1609 - Accuracy: 0.6618 - F1: 0.6132
sub_14:Test (Best Model) - Loss: 1.1529 - Accuracy: 0.6324 - F1: 0.6415
sub_6:Test (Best Model) - Loss: 1.1755 - Accuracy: 0.5652 - F1: 0.5651
sub_8:Test (Best Model) - Loss: 1.1363 - Accuracy: 0.6765 - F1: 0.7049
sub_12:Test (Best Model) - Loss: 1.2008 - Accuracy: 0.5942 - F1: 0.6113
sub_18:Test (Best Model) - Loss: 1.2229 - Accuracy: 0.5441 - F1: 0.5814
sub_25:Test (Best Model) - Loss: 1.0832 - Accuracy: 0.7353 - F1: 0.7291
sub_10:Test (Best Model) - Loss: 1.3617 - Accuracy: 0.2647 - F1: 0.1059
sub_7:Test (Best Model) - Loss: 1.1900 - Accuracy: 0.6324 - F1: 0.5847
sub_4:Test (Best Model) - Loss: 1.1162 - Accuracy: 0.6957 - F1: 0.6623
sub_20:Test (Best Model) - Loss: 1.1148 - Accuracy: 0.6471 - F1: 0.6051
sub_11:Test (Best Model) - Loss: 1.1109 - Accuracy: 0.6957 - F1: 0.6906
sub_28:Test (Best Model) - Loss: 1.3904 - Accuracy: 0.3235 - F1: 0.2275
sub_2:Test (Best Model) - Loss: 1.1412 - Accuracy: 0.6618 - F1: 0.6397
sub_14:Test (Best Model) - Loss: 1.2208 - Accuracy: 0.5735 - F1: 0.6004
sub_27:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.4058 - F1: 0.3906
sub_26:Test (Best Model) - Loss: 1.1667 - Accuracy: 0.5735 - F1: 0.5655
sub_13:Test (Best Model) - Loss: 1.2188 - Accuracy: 0.5217 - F1: 0.4884
sub_17:Test (Best Model) - Loss: 1.2294 - Accuracy: 0.4058 - F1: 0.3906
sub_23:Test (Best Model) - Loss: 1.2191 - Accuracy: 0.6176 - F1: 0.5828
sub_29:Test (Best Model) - Loss: 1.0922 - Accuracy: 0.7941 - F1: 0.8000
sub_3:Test (Best Model) - Loss: 1.1793 - Accuracy: 0.6377 - F1: 0.6207
sub_19:Test (Best Model) - Loss: 1.1226 - Accuracy: 0.6912 - F1: 0.6998
sub_12:Test (Best Model) - Loss: 1.1990 - Accuracy: 0.5652 - F1: 0.5786
sub_1:Test (Best Model) - Loss: 1.2232 - Accuracy: 0.5072 - F1: 0.4712
sub_15:Test (Best Model) - Loss: 1.1505 - Accuracy: 0.6176 - F1: 0.6457
sub_20:Test (Best Model) - Loss: 1.1715 - Accuracy: 0.7794 - F1: 0.7875
sub_21:Test (Best Model) - Loss: 1.0360 - Accuracy: 0.8676 - F1: 0.8666
sub_24:Test (Best Model) - Loss: 1.1771 - Accuracy: 0.6912 - F1: 0.6780
sub_22:Test (Best Model) - Loss: 1.2024 - Accuracy: 0.4783 - F1: 0.4302
sub_6:Test (Best Model) - Loss: 1.1356 - Accuracy: 0.5797 - F1: 0.5695
sub_16:Test (Best Model) - Loss: 1.1412 - Accuracy: 0.6765 - F1: 0.6204
sub_10:Test (Best Model) - Loss: 1.1219 - Accuracy: 0.7101 - F1: 0.6604
sub_9:Test (Best Model) - Loss: 1.0781 - Accuracy: 0.6471 - F1: 0.6346
sub_26:Test (Best Model) - Loss: 1.2112 - Accuracy: 0.5000 - F1: 0.4723
sub_14:Test (Best Model) - Loss: 1.2844 - Accuracy: 0.4412 - F1: 0.4131
sub_5:Test (Best Model) - Loss: 1.1279 - Accuracy: 0.7059 - F1: 0.6334
sub_18:Test (Best Model) - Loss: 1.1961 - Accuracy: 0.5147 - F1: 0.5125
sub_8:Test (Best Model) - Loss: 1.0841 - Accuracy: 0.6765 - F1: 0.6444
sub_7:Test (Best Model) - Loss: 1.1793 - Accuracy: 0.6618 - F1: 0.6218
sub_28:Test (Best Model) - Loss: 1.3649 - Accuracy: 0.2941 - F1: 0.2254
sub_4:Test (Best Model) - Loss: 1.0533 - Accuracy: 0.7391 - F1: 0.7283
sub_2:Test (Best Model) - Loss: 1.0687 - Accuracy: 0.7794 - F1: 0.7805
sub_25:Test (Best Model) - Loss: 1.0851 - Accuracy: 0.7500 - F1: 0.7285
sub_12:Test (Best Model) - Loss: 1.1298 - Accuracy: 0.6957 - F1: 0.7056
sub_15:Test (Best Model) - Loss: 1.1663 - Accuracy: 0.6618 - F1: 0.6840
sub_16:Test (Best Model) - Loss: 1.2388 - Accuracy: 0.5294 - F1: 0.5046
sub_17:Test (Best Model) - Loss: 1.2153 - Accuracy: 0.4928 - F1: 0.5012
sub_3:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.6522 - F1: 0.6186
sub_20:Test (Best Model) - Loss: 1.1590 - Accuracy: 0.6667 - F1: 0.6452
sub_6:Test (Best Model) - Loss: 1.1458 - Accuracy: 0.6812 - F1: 0.6320
sub_27:Test (Best Model) - Loss: 1.2153 - Accuracy: 0.4928 - F1: 0.5012
sub_24:Test (Best Model) - Loss: 1.1607 - Accuracy: 0.7059 - F1: 0.6850
sub_9:Test (Best Model) - Loss: 1.1373 - Accuracy: 0.7353 - F1: 0.7226
sub_11:Test (Best Model) - Loss: 1.1085 - Accuracy: 0.6232 - F1: 0.5710
sub_29:Test (Best Model) - Loss: 1.0909 - Accuracy: 0.7500 - F1: 0.7214
sub_23:Test (Best Model) - Loss: 1.2423 - Accuracy: 0.4853 - F1: 0.4194
sub_19:Test (Best Model) - Loss: 1.1435 - Accuracy: 0.6912 - F1: 0.7086
sub_13:Test (Best Model) - Loss: 1.2207 - Accuracy: 0.4783 - F1: 0.4616
sub_1:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.4348 - F1: 0.4176
sub_14:Test (Best Model) - Loss: 1.0973 - Accuracy: 0.7353 - F1: 0.7323
sub_10:Test (Best Model) - Loss: 1.0984 - Accuracy: 0.6957 - F1: 0.6802
sub_18:Test (Best Model) - Loss: 1.1859 - Accuracy: 0.5000 - F1: 0.5055
sub_8:Test (Best Model) - Loss: 1.1715 - Accuracy: 0.5294 - F1: 0.5795
sub_22:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.4348 - F1: 0.3946
sub_4:Test (Best Model) - Loss: 1.1307 - Accuracy: 0.6667 - F1: 0.6776
sub_21:Test (Best Model) - Loss: 1.0769 - Accuracy: 0.8088 - F1: 0.8052
sub_16:Test (Best Model) - Loss: 1.2159 - Accuracy: 0.5000 - F1: 0.4941
sub_28:Test (Best Model) - Loss: 1.3671 - Accuracy: 0.2941 - F1: 0.2107
sub_5:Test (Best Model) - Loss: 1.0609 - Accuracy: 0.7941 - F1: 0.8000
sub_7:Test (Best Model) - Loss: 1.1760 - Accuracy: 0.6618 - F1: 0.6319
sub_12:Test (Best Model) - Loss: 1.1932 - Accuracy: 0.5882 - F1: 0.6108
sub_2:Test (Best Model) - Loss: 1.2544 - Accuracy: 0.4783 - F1: 0.4385
sub_17:Test (Best Model) - Loss: 1.2254 - Accuracy: 0.5797 - F1: 0.5910
sub_27:Test (Best Model) - Loss: 1.2254 - Accuracy: 0.5797 - F1: 0.5910
sub_26:Test (Best Model) - Loss: 1.2565 - Accuracy: 0.4265 - F1: 0.4466
sub_6:Test (Best Model) - Loss: 1.1139 - Accuracy: 0.6957 - F1: 0.6752
sub_1:Test (Best Model) - Loss: 1.1966 - Accuracy: 0.6471 - F1: 0.6065
sub_24:Test (Best Model) - Loss: 1.1838 - Accuracy: 0.6029 - F1: 0.5931
sub_15:Test (Best Model) - Loss: 1.0606 - Accuracy: 0.7941 - F1: 0.8047
sub_25:Test (Best Model) - Loss: 1.0520 - Accuracy: 0.7353 - F1: 0.7062
sub_3:Test (Best Model) - Loss: 1.0879 - Accuracy: 0.8116 - F1: 0.8150
sub_8:Test (Best Model) - Loss: 1.1877 - Accuracy: 0.5588 - F1: 0.5859
sub_20:Test (Best Model) - Loss: 1.0500 - Accuracy: 0.6667 - F1: 0.6647
sub_11:Test (Best Model) - Loss: 1.1698 - Accuracy: 0.7681 - F1: 0.7677
sub_9:Test (Best Model) - Loss: 1.0889 - Accuracy: 0.7206 - F1: 0.7251
sub_18:Test (Best Model) - Loss: 1.1734 - Accuracy: 0.6471 - F1: 0.6428
sub_29:Test (Best Model) - Loss: 1.1897 - Accuracy: 0.7353 - F1: 0.7406
sub_14:Test (Best Model) - Loss: 1.1237 - Accuracy: 0.6765 - F1: 0.6922
sub_16:Test (Best Model) - Loss: 1.1723 - Accuracy: 0.5735 - F1: 0.5639
sub_10:Test (Best Model) - Loss: 1.0878 - Accuracy: 0.6522 - F1: 0.6218
sub_21:Test (Best Model) - Loss: 1.0497 - Accuracy: 0.8382 - F1: 0.8395
sub_12:Test (Best Model) - Loss: 1.1186 - Accuracy: 0.6471 - F1: 0.6381
sub_4:Test (Best Model) - Loss: 1.0369 - Accuracy: 0.6667 - F1: 0.6641
sub_6:Test (Best Model) - Loss: 1.1353 - Accuracy: 0.6957 - F1: 0.6698
sub_5:Test (Best Model) - Loss: 1.1613 - Accuracy: 0.5882 - F1: 0.5302
sub_23:Test (Best Model) - Loss: 1.2231 - Accuracy: 0.5588 - F1: 0.5234
sub_22:Test (Best Model) - Loss: 1.1880 - Accuracy: 0.7206 - F1: 0.7177
sub_2:Test (Best Model) - Loss: 1.1850 - Accuracy: 0.4638 - F1: 0.4219
sub_26:Test (Best Model) - Loss: 1.2228 - Accuracy: 0.5882 - F1: 0.6031
sub_28:Test (Best Model) - Loss: 1.3788 - Accuracy: 0.3676 - F1: 0.2923
sub_17:Test (Best Model) - Loss: 1.2040 - Accuracy: 0.4638 - F1: 0.4720
sub_24:Test (Best Model) - Loss: 1.1413 - Accuracy: 0.7500 - F1: 0.7593
sub_20:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.6957 - F1: 0.6962
sub_25:Test (Best Model) - Loss: 1.1177 - Accuracy: 0.8235 - F1: 0.8296
sub_27:Test (Best Model) - Loss: 1.2040 - Accuracy: 0.4638 - F1: 0.4720
sub_13:Test (Best Model) - Loss: 1.1707 - Accuracy: 0.5797 - F1: 0.6106
sub_7:Test (Best Model) - Loss: 1.0959 - Accuracy: 0.6912 - F1: 0.6955
sub_11:Test (Best Model) - Loss: 1.1574 - Accuracy: 0.6667 - F1: 0.6625
sub_9:Test (Best Model) - Loss: 1.1672 - Accuracy: 0.6618 - F1: 0.6635
sub_3:Test (Best Model) - Loss: 1.1556 - Accuracy: 0.7101 - F1: 0.7222
sub_29:Test (Best Model) - Loss: 1.1671 - Accuracy: 0.6812 - F1: 0.6085
sub_1:Test (Best Model) - Loss: 1.0853 - Accuracy: 0.6618 - F1: 0.6398
sub_8:Test (Best Model) - Loss: 1.1913 - Accuracy: 0.5882 - F1: 0.6143
sub_18:Test (Best Model) - Loss: 1.1993 - Accuracy: 0.5147 - F1: 0.4696
sub_10:Test (Best Model) - Loss: 1.1212 - Accuracy: 0.6087 - F1: 0.5564
sub_6:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.6232 - F1: 0.5788
sub_15:Test (Best Model) - Loss: 1.0849 - Accuracy: 0.7059 - F1: 0.7229
sub_4:Test (Best Model) - Loss: 1.1151 - Accuracy: 0.6522 - F1: 0.6129
sub_16:Test (Best Model) - Loss: 1.1474 - Accuracy: 0.6912 - F1: 0.6931
sub_19:Test (Best Model) - Loss: 1.0581 - Accuracy: 0.6618 - F1: 0.6714
sub_2:Test (Best Model) - Loss: 1.1920 - Accuracy: 0.6087 - F1: 0.6201
sub_22:Test (Best Model) - Loss: 1.1834 - Accuracy: 0.7500 - F1: 0.7567
sub_14:Test (Best Model) - Loss: 1.0771 - Accuracy: 0.7941 - F1: 0.7854
sub_21:Test (Best Model) - Loss: 1.0167 - Accuracy: 0.7941 - F1: 0.7756
sub_24:Test (Best Model) - Loss: 1.1182 - Accuracy: 0.7500 - F1: 0.7568
sub_26:Test (Best Model) - Loss: 1.1687 - Accuracy: 0.6471 - F1: 0.6337
sub_17:Test (Best Model) - Loss: 1.0944 - Accuracy: 0.6765 - F1: 0.6638
sub_5:Test (Best Model) - Loss: 1.1105 - Accuracy: 0.7059 - F1: 0.6756
sub_20:Test (Best Model) - Loss: 1.0482 - Accuracy: 0.6812 - F1: 0.6635
sub_9:Test (Best Model) - Loss: 1.2158 - Accuracy: 0.5588 - F1: 0.5705
sub_27:Test (Best Model) - Loss: 1.0944 - Accuracy: 0.6765 - F1: 0.6638
sub_29:Test (Best Model) - Loss: 1.1280 - Accuracy: 0.6667 - F1: 0.6179
sub_12:Test (Best Model) - Loss: 1.2180 - Accuracy: 0.6324 - F1: 0.6474
sub_28:Test (Best Model) - Loss: 1.3195 - Accuracy: 0.3824 - F1: 0.2714
sub_3:Test (Best Model) - Loss: 1.1298 - Accuracy: 0.7391 - F1: 0.7257
sub_8:Test (Best Model) - Loss: 1.1331 - Accuracy: 0.5882 - F1: 0.5470
sub_4:Test (Best Model) - Loss: 1.1310 - Accuracy: 0.6812 - F1: 0.6076
sub_7:Test (Best Model) - Loss: 1.0935 - Accuracy: 0.7500 - F1: 0.7366
sub_25:Test (Best Model) - Loss: 1.0806 - Accuracy: 0.7500 - F1: 0.7505
sub_13:Test (Best Model) - Loss: 1.2990 - Accuracy: 0.4265 - F1: 0.3535
sub_23:Test (Best Model) - Loss: 1.1585 - Accuracy: 0.6029 - F1: 0.5644
sub_1:Test (Best Model) - Loss: 1.1448 - Accuracy: 0.6029 - F1: 0.5884
sub_2:Test (Best Model) - Loss: 1.2206 - Accuracy: 0.6377 - F1: 0.6336
sub_19:Test (Best Model) - Loss: 1.2176 - Accuracy: 0.6471 - F1: 0.6416
sub_16:Test (Best Model) - Loss: 1.1691 - Accuracy: 0.5735 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 1.1324 - Accuracy: 0.6812 - F1: 0.6690
sub_18:Test (Best Model) - Loss: 1.1979 - Accuracy: 0.4559 - F1: 0.4301
sub_9:Test (Best Model) - Loss: 1.1930 - Accuracy: 0.6176 - F1: 0.6203
sub_15:Test (Best Model) - Loss: 1.0813 - Accuracy: 0.6912 - F1: 0.6758
sub_6:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.6667 - F1: 0.6289
sub_22:Test (Best Model) - Loss: 1.1566 - Accuracy: 0.6912 - F1: 0.6431
sub_11:Test (Best Model) - Loss: 1.1318 - Accuracy: 0.6522 - F1: 0.6537
sub_24:Test (Best Model) - Loss: 1.1129 - Accuracy: 0.6176 - F1: 0.5461
sub_5:Test (Best Model) - Loss: 1.1547 - Accuracy: 0.7206 - F1: 0.7134
sub_29:Test (Best Model) - Loss: 1.1159 - Accuracy: 0.6667 - F1: 0.6251
sub_17:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.6618 - F1: 0.6686
sub_21:Test (Best Model) - Loss: 1.0679 - Accuracy: 0.7059 - F1: 0.6339
sub_3:Test (Best Model) - Loss: 1.1620 - Accuracy: 0.7971 - F1: 0.8059
sub_26:Test (Best Model) - Loss: 1.1164 - Accuracy: 0.6765 - F1: 0.6864
sub_20:Test (Best Model) - Loss: 1.1529 - Accuracy: 0.6812 - F1: 0.6632
sub_12:Test (Best Model) - Loss: 1.1324 - Accuracy: 0.6912 - F1: 0.6873
sub_27:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.6618 - F1: 0.6686
sub_25:Test (Best Model) - Loss: 1.1564 - Accuracy: 0.5882 - F1: 0.5500
sub_8:Test (Best Model) - Loss: 1.2112 - Accuracy: 0.6029 - F1: 0.5605
sub_7:Test (Best Model) - Loss: 1.1421 - Accuracy: 0.7794 - F1: 0.7797
sub_2:Test (Best Model) - Loss: 1.2390 - Accuracy: 0.5217 - F1: 0.5022
sub_14:Test (Best Model) - Loss: 1.1294 - Accuracy: 0.7059 - F1: 0.6605
sub_1:Test (Best Model) - Loss: 1.0268 - Accuracy: 0.6912 - F1: 0.6493
sub_19:Test (Best Model) - Loss: 1.1650 - Accuracy: 0.6176 - F1: 0.6177
sub_28:Test (Best Model) - Loss: 1.3045 - Accuracy: 0.3971 - F1: 0.3126
sub_4:Test (Best Model) - Loss: 1.1019 - Accuracy: 0.6957 - F1: 0.6524
sub_18:Test (Best Model) - Loss: 1.2756 - Accuracy: 0.4412 - F1: 0.4224
sub_16:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.6912 - F1: 0.6827
sub_26:Test (Best Model) - Loss: 1.2202 - Accuracy: 0.7353 - F1: 0.7341
sub_23:Test (Best Model) - Loss: 1.2523 - Accuracy: 0.5735 - F1: 0.5451
sub_13:Test (Best Model) - Loss: 1.2729 - Accuracy: 0.4412 - F1: 0.3488
sub_24:Test (Best Model) - Loss: 1.1471 - Accuracy: 0.7206 - F1: 0.7365
sub_29:Test (Best Model) - Loss: 1.1613 - Accuracy: 0.5942 - F1: 0.5551
sub_15:Test (Best Model) - Loss: 1.1410 - Accuracy: 0.6618 - F1: 0.6432
sub_11:Test (Best Model) - Loss: 1.1889 - Accuracy: 0.6957 - F1: 0.6389
sub_17:Test (Best Model) - Loss: 1.1612 - Accuracy: 0.5882 - F1: 0.5742
sub_5:Test (Best Model) - Loss: 1.1823 - Accuracy: 0.5000 - F1: 0.4281
sub_19:Test (Best Model) - Loss: 1.1565 - Accuracy: 0.5882 - F1: 0.6049
sub_9:Test (Best Model) - Loss: 1.2086 - Accuracy: 0.5000 - F1: 0.4485
sub_21:Test (Best Model) - Loss: 1.0715 - Accuracy: 0.7500 - F1: 0.6978
sub_27:Test (Best Model) - Loss: 1.1612 - Accuracy: 0.5882 - F1: 0.5742
sub_25:Test (Best Model) - Loss: 1.0526 - Accuracy: 0.6324 - F1: 0.6104
sub_3:Test (Best Model) - Loss: 1.1255 - Accuracy: 0.6812 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 1.1401 - Accuracy: 0.7206 - F1: 0.7347
sub_22:Test (Best Model) - Loss: 1.1342 - Accuracy: 0.5294 - F1: 0.4873
sub_28:Test (Best Model) - Loss: 1.3211 - Accuracy: 0.3824 - F1: 0.3098
sub_1:Test (Best Model) - Loss: 1.1168 - Accuracy: 0.7059 - F1: 0.6375
sub_7:Test (Best Model) - Loss: 1.1050 - Accuracy: 0.7206 - F1: 0.7198
sub_23:Test (Best Model) - Loss: 1.2101 - Accuracy: 0.5072 - F1: 0.4865
sub_14:Test (Best Model) - Loss: 1.0515 - Accuracy: 0.7941 - F1: 0.7911
sub_22:Test (Best Model) - Loss: 1.2675 - Accuracy: 0.5000 - F1: 0.4858
sub_11:Test (Best Model) - Loss: 1.0745 - Accuracy: 0.7101 - F1: 0.7118
sub_17:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.6029 - F1: 0.5522
sub_25:Test (Best Model) - Loss: 1.1134 - Accuracy: 0.7941 - F1: 0.8008
sub_9:Test (Best Model) - Loss: 1.2071 - Accuracy: 0.6176 - F1: 0.5899
sub_27:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.6029 - F1: 0.5522
sub_15:Test (Best Model) - Loss: 1.1837 - Accuracy: 0.5588 - F1: 0.5098
sub_19:Test (Best Model) - Loss: 1.1606 - Accuracy: 0.5441 - F1: 0.5141
sub_5:Test (Best Model) - Loss: 1.1432 - Accuracy: 0.6029 - F1: 0.5415
sub_29:Test (Best Model) - Loss: 1.1554 - Accuracy: 0.4928 - F1: 0.4970
sub_21:Test (Best Model) - Loss: 1.0783 - Accuracy: 0.8235 - F1: 0.8201
sub_13:Test (Best Model) - Loss: 1.2937 - Accuracy: 0.4265 - F1: 0.3298
sub_7:Test (Best Model) - Loss: 1.0564 - Accuracy: 0.8088 - F1: 0.8015
sub_17:Test (Best Model) - Loss: 1.2058 - Accuracy: 0.5882 - F1: 0.5992
sub_27:Test (Best Model) - Loss: 1.2058 - Accuracy: 0.5882 - F1: 0.5992
sub_23:Test (Best Model) - Loss: 1.1992 - Accuracy: 0.5217 - F1: 0.4936
sub_19:Test (Best Model) - Loss: 1.1329 - Accuracy: 0.6912 - F1: 0.7054
sub_15:Test (Best Model) - Loss: 1.0822 - Accuracy: 0.6765 - F1: 0.6220
sub_11:Test (Best Model) - Loss: 1.0883 - Accuracy: 0.6667 - F1: 0.6553
sub_21:Test (Best Model) - Loss: 1.0051 - Accuracy: 0.8088 - F1: 0.7976
sub_13:Test (Best Model) - Loss: 1.2888 - Accuracy: 0.4265 - F1: 0.2894
sub_23:Test (Best Model) - Loss: 1.2702 - Accuracy: 0.4928 - F1: 0.4720
sub_15:Test (Best Model) - Loss: 1.1603 - Accuracy: 0.6618 - F1: 0.6013
sub_13:Test (Best Model) - Loss: 1.3219 - Accuracy: 0.4412 - F1: 0.3639
sub_23:Test (Best Model) - Loss: 1.2361 - Accuracy: 0.5362 - F1: 0.4835
sub_23:Test (Best Model) - Loss: 1.2686 - Accuracy: 0.4493 - F1: 0.3976

=== Summary Results ===

acc: 61.62 ± 8.06
F1: 59.76 ± 8.94
acc-in: 84.92 ± 5.33
F1-in: 83.97 ± 5.82
