lr: 0.001
sub_4:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.5072 - F1: 0.5326
sub_6:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.3971 - F1: 0.3899
sub_7:Test (Best Model) - Loss: 1.0227 - Accuracy: 0.5735 - F1: 0.5398
sub_3:Test (Best Model) - Loss: 1.0785 - Accuracy: 0.5294 - F1: 0.5231
sub_5:Test (Best Model) - Loss: 1.1236 - Accuracy: 0.6324 - F1: 0.5801
sub_13:Test (Best Model) - Loss: 1.1494 - Accuracy: 0.5588 - F1: 0.5633
sub_12:Test (Best Model) - Loss: 0.9206 - Accuracy: 0.6029 - F1: 0.5988
sub_1:Test (Best Model) - Loss: 1.0834 - Accuracy: 0.5588 - F1: 0.5845
sub_26:Test (Best Model) - Loss: 0.9518 - Accuracy: 0.6377 - F1: 0.6470
sub_24:Test (Best Model) - Loss: 0.8763 - Accuracy: 0.6912 - F1: 0.6843
sub_15:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.6471 - F1: 0.6642
sub_16:Test (Best Model) - Loss: 1.0360 - Accuracy: 0.6765 - F1: 0.6491
sub_20:Test (Best Model) - Loss: 1.0725 - Accuracy: 0.4559 - F1: 0.4560
sub_28:Test (Best Model) - Loss: 1.3335 - Accuracy: 0.5294 - F1: 0.4845
sub_2:Test (Best Model) - Loss: 1.0877 - Accuracy: 0.5797 - F1: 0.5856
sub_14:Test (Best Model) - Loss: 1.8198 - Accuracy: 0.3676 - F1: 0.2804
sub_8:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.5000 - F1: 0.4832
sub_11:Test (Best Model) - Loss: 1.1745 - Accuracy: 0.5362 - F1: 0.5095
sub_29:Test (Best Model) - Loss: 0.9637 - Accuracy: 0.5882 - F1: 0.5921
sub_10:Test (Best Model) - Loss: 1.0557 - Accuracy: 0.5882 - F1: 0.5542
sub_19:Test (Best Model) - Loss: 2.3295 - Accuracy: 0.2206 - F1: 0.1500
sub_25:Test (Best Model) - Loss: 0.9478 - Accuracy: 0.6667 - F1: 0.6621
sub_9:Test (Best Model) - Loss: 0.9359 - Accuracy: 0.6471 - F1: 0.6113
sub_23:Test (Best Model) - Loss: 0.8631 - Accuracy: 0.6667 - F1: 0.6703
sub_18:Test (Best Model) - Loss: 0.8838 - Accuracy: 0.6522 - F1: 0.6594
sub_6:Test (Best Model) - Loss: 1.2974 - Accuracy: 0.3971 - F1: 0.3985
sub_22:Test (Best Model) - Loss: 1.3715 - Accuracy: 0.4118 - F1: 0.3832
sub_15:Test (Best Model) - Loss: 1.0430 - Accuracy: 0.5588 - F1: 0.5748
sub_21:Test (Best Model) - Loss: 1.4119 - Accuracy: 0.5294 - F1: 0.5056
sub_4:Test (Best Model) - Loss: 1.2876 - Accuracy: 0.4783 - F1: 0.4789
sub_12:Test (Best Model) - Loss: 1.0101 - Accuracy: 0.5735 - F1: 0.5519
sub_16:Test (Best Model) - Loss: 1.0080 - Accuracy: 0.5882 - F1: 0.5732
sub_1:Test (Best Model) - Loss: 1.0228 - Accuracy: 0.5588 - F1: 0.5741
sub_7:Test (Best Model) - Loss: 0.9078 - Accuracy: 0.6176 - F1: 0.6268
sub_24:Test (Best Model) - Loss: 0.9370 - Accuracy: 0.6471 - F1: 0.6299
sub_3:Test (Best Model) - Loss: 1.1701 - Accuracy: 0.5000 - F1: 0.4777
sub_5:Test (Best Model) - Loss: 1.1773 - Accuracy: 0.6471 - F1: 0.6004
sub_11:Test (Best Model) - Loss: 1.1113 - Accuracy: 0.5797 - F1: 0.5597
sub_27:Test (Best Model) - Loss: 1.1419 - Accuracy: 0.5362 - F1: 0.5303
sub_2:Test (Best Model) - Loss: 1.0204 - Accuracy: 0.5217 - F1: 0.5181
sub_17:Test (Best Model) - Loss: 1.1419 - Accuracy: 0.5362 - F1: 0.5303
sub_10:Test (Best Model) - Loss: 1.0538 - Accuracy: 0.5588 - F1: 0.5476
sub_14:Test (Best Model) - Loss: 1.9467 - Accuracy: 0.2500 - F1: 0.1772
sub_26:Test (Best Model) - Loss: 1.0310 - Accuracy: 0.6667 - F1: 0.6782
sub_13:Test (Best Model) - Loss: 1.1158 - Accuracy: 0.5000 - F1: 0.5075
sub_29:Test (Best Model) - Loss: 0.9042 - Accuracy: 0.6471 - F1: 0.6273
sub_25:Test (Best Model) - Loss: 0.9121 - Accuracy: 0.6667 - F1: 0.6534
sub_12:Test (Best Model) - Loss: 1.0447 - Accuracy: 0.6324 - F1: 0.6147
sub_28:Test (Best Model) - Loss: 1.3472 - Accuracy: 0.4706 - F1: 0.4262
sub_19:Test (Best Model) - Loss: 1.6907 - Accuracy: 0.2206 - F1: 0.1618
sub_23:Test (Best Model) - Loss: 0.8393 - Accuracy: 0.7101 - F1: 0.7069
sub_8:Test (Best Model) - Loss: 1.6860 - Accuracy: 0.4118 - F1: 0.4322
sub_21:Test (Best Model) - Loss: 1.1382 - Accuracy: 0.5000 - F1: 0.4849
sub_11:Test (Best Model) - Loss: 1.1340 - Accuracy: 0.5652 - F1: 0.5212
sub_24:Test (Best Model) - Loss: 0.9305 - Accuracy: 0.6029 - F1: 0.5774
sub_20:Test (Best Model) - Loss: 1.2197 - Accuracy: 0.5441 - F1: 0.5622
sub_3:Test (Best Model) - Loss: 1.0261 - Accuracy: 0.5882 - F1: 0.5929
sub_22:Test (Best Model) - Loss: 1.7276 - Accuracy: 0.4412 - F1: 0.4151
sub_16:Test (Best Model) - Loss: 0.9894 - Accuracy: 0.5882 - F1: 0.5987
sub_4:Test (Best Model) - Loss: 1.2578 - Accuracy: 0.4928 - F1: 0.5152
sub_9:Test (Best Model) - Loss: 0.9694 - Accuracy: 0.6324 - F1: 0.5775
sub_29:Test (Best Model) - Loss: 0.9592 - Accuracy: 0.6618 - F1: 0.6488
sub_18:Test (Best Model) - Loss: 0.8258 - Accuracy: 0.6812 - F1: 0.6784
sub_7:Test (Best Model) - Loss: 1.0265 - Accuracy: 0.5441 - F1: 0.5553
sub_6:Test (Best Model) - Loss: 1.6214 - Accuracy: 0.3382 - F1: 0.3289
sub_15:Test (Best Model) - Loss: 1.1151 - Accuracy: 0.5735 - F1: 0.5951
sub_26:Test (Best Model) - Loss: 0.9918 - Accuracy: 0.6232 - F1: 0.6343
sub_5:Test (Best Model) - Loss: 1.1264 - Accuracy: 0.6471 - F1: 0.5913
sub_25:Test (Best Model) - Loss: 1.0146 - Accuracy: 0.6812 - F1: 0.6719
sub_2:Test (Best Model) - Loss: 1.0777 - Accuracy: 0.5797 - F1: 0.5491
sub_19:Test (Best Model) - Loss: 1.4910 - Accuracy: 0.2647 - F1: 0.2114
sub_14:Test (Best Model) - Loss: 1.7789 - Accuracy: 0.3235 - F1: 0.2417
sub_1:Test (Best Model) - Loss: 1.2591 - Accuracy: 0.5294 - F1: 0.5597
sub_13:Test (Best Model) - Loss: 1.1934 - Accuracy: 0.5147 - F1: 0.5257
sub_28:Test (Best Model) - Loss: 1.3795 - Accuracy: 0.4559 - F1: 0.4107
sub_8:Test (Best Model) - Loss: 1.3838 - Accuracy: 0.4559 - F1: 0.4589
sub_12:Test (Best Model) - Loss: 0.9996 - Accuracy: 0.6029 - F1: 0.5917
sub_4:Test (Best Model) - Loss: 1.1047 - Accuracy: 0.4638 - F1: 0.4738
sub_3:Test (Best Model) - Loss: 1.1339 - Accuracy: 0.5441 - F1: 0.5190
sub_24:Test (Best Model) - Loss: 0.9551 - Accuracy: 0.5882 - F1: 0.5790
sub_18:Test (Best Model) - Loss: 0.9097 - Accuracy: 0.7101 - F1: 0.7152
sub_27:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.5942 - F1: 0.6021
sub_17:Test (Best Model) - Loss: 1.1228 - Accuracy: 0.5942 - F1: 0.6021
sub_10:Test (Best Model) - Loss: 1.0746 - Accuracy: 0.5882 - F1: 0.5876
sub_20:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.5000 - F1: 0.5092
sub_16:Test (Best Model) - Loss: 1.0087 - Accuracy: 0.6029 - F1: 0.5660
sub_23:Test (Best Model) - Loss: 0.8611 - Accuracy: 0.6522 - F1: 0.6556
sub_29:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.6912 - F1: 0.6695
sub_21:Test (Best Model) - Loss: 1.2133 - Accuracy: 0.5294 - F1: 0.5180
sub_6:Test (Best Model) - Loss: 1.3674 - Accuracy: 0.4706 - F1: 0.4753
sub_11:Test (Best Model) - Loss: 1.0919 - Accuracy: 0.5507 - F1: 0.5443
sub_7:Test (Best Model) - Loss: 1.0737 - Accuracy: 0.6176 - F1: 0.6027
sub_15:Test (Best Model) - Loss: 1.1133 - Accuracy: 0.5882 - F1: 0.6042
sub_22:Test (Best Model) - Loss: 1.4143 - Accuracy: 0.4412 - F1: 0.4153
sub_14:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.3529 - F1: 0.2615
sub_9:Test (Best Model) - Loss: 0.9095 - Accuracy: 0.6912 - F1: 0.6540
sub_25:Test (Best Model) - Loss: 0.9736 - Accuracy: 0.6377 - F1: 0.6115
sub_13:Test (Best Model) - Loss: 1.0882 - Accuracy: 0.5588 - F1: 0.5382
sub_19:Test (Best Model) - Loss: 1.5594 - Accuracy: 0.2941 - F1: 0.2351
sub_5:Test (Best Model) - Loss: 1.2187 - Accuracy: 0.5294 - F1: 0.4928
sub_2:Test (Best Model) - Loss: 1.1062 - Accuracy: 0.5652 - F1: 0.5520
sub_26:Test (Best Model) - Loss: 1.0053 - Accuracy: 0.6087 - F1: 0.6096
sub_8:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.4853 - F1: 0.4704
sub_4:Test (Best Model) - Loss: 1.1457 - Accuracy: 0.4348 - F1: 0.4768
sub_3:Test (Best Model) - Loss: 0.9029 - Accuracy: 0.6324 - F1: 0.6361
sub_1:Test (Best Model) - Loss: 1.0757 - Accuracy: 0.5294 - F1: 0.5517
sub_23:Test (Best Model) - Loss: 0.9146 - Accuracy: 0.7101 - F1: 0.7107
sub_20:Test (Best Model) - Loss: 1.0868 - Accuracy: 0.5000 - F1: 0.5013
sub_11:Test (Best Model) - Loss: 1.0417 - Accuracy: 0.5942 - F1: 0.5943
sub_18:Test (Best Model) - Loss: 0.7491 - Accuracy: 0.6957 - F1: 0.7179
sub_12:Test (Best Model) - Loss: 1.0249 - Accuracy: 0.5441 - F1: 0.5257
sub_16:Test (Best Model) - Loss: 0.9580 - Accuracy: 0.6618 - F1: 0.6347
sub_6:Test (Best Model) - Loss: 1.3285 - Accuracy: 0.3971 - F1: 0.3930
sub_17:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.4783 - F1: 0.4725
sub_15:Test (Best Model) - Loss: 0.9689 - Accuracy: 0.6029 - F1: 0.6133
sub_29:Test (Best Model) - Loss: 0.9049 - Accuracy: 0.6324 - F1: 0.6144
sub_2:Test (Best Model) - Loss: 0.9553 - Accuracy: 0.6232 - F1: 0.6333
sub_13:Test (Best Model) - Loss: 1.0780 - Accuracy: 0.5441 - F1: 0.5269
sub_27:Test (Best Model) - Loss: 1.3925 - Accuracy: 0.4783 - F1: 0.4725
sub_24:Test (Best Model) - Loss: 0.8669 - Accuracy: 0.6912 - F1: 0.6957
sub_14:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.3529 - F1: 0.2649
sub_8:Test (Best Model) - Loss: 1.2233 - Accuracy: 0.5294 - F1: 0.4998
sub_28:Test (Best Model) - Loss: 1.4039 - Accuracy: 0.4265 - F1: 0.3845
sub_5:Test (Best Model) - Loss: 1.1461 - Accuracy: 0.6471 - F1: 0.5812
sub_7:Test (Best Model) - Loss: 1.0000 - Accuracy: 0.6471 - F1: 0.6379
sub_22:Test (Best Model) - Loss: 1.3334 - Accuracy: 0.4706 - F1: 0.4338
sub_10:Test (Best Model) - Loss: 1.1216 - Accuracy: 0.6176 - F1: 0.6148
sub_26:Test (Best Model) - Loss: 0.9493 - Accuracy: 0.5797 - F1: 0.5761
sub_9:Test (Best Model) - Loss: 1.0130 - Accuracy: 0.6471 - F1: 0.5983
sub_21:Test (Best Model) - Loss: 1.2255 - Accuracy: 0.5441 - F1: 0.5275
sub_18:Test (Best Model) - Loss: 0.8777 - Accuracy: 0.7681 - F1: 0.7779
sub_19:Test (Best Model) - Loss: 1.5759 - Accuracy: 0.3382 - F1: 0.2670
sub_4:Test (Best Model) - Loss: 0.8117 - Accuracy: 0.6232 - F1: 0.6302
sub_23:Test (Best Model) - Loss: 0.8392 - Accuracy: 0.6667 - F1: 0.6682
sub_1:Test (Best Model) - Loss: 1.0108 - Accuracy: 0.5588 - F1: 0.5622
sub_16:Test (Best Model) - Loss: 0.9651 - Accuracy: 0.6471 - F1: 0.6178
sub_6:Test (Best Model) - Loss: 1.0061 - Accuracy: 0.5942 - F1: 0.5892
sub_20:Test (Best Model) - Loss: 1.0176 - Accuracy: 0.5147 - F1: 0.5115
sub_25:Test (Best Model) - Loss: 0.9813 - Accuracy: 0.6377 - F1: 0.5973
sub_3:Test (Best Model) - Loss: 0.7512 - Accuracy: 0.7536 - F1: 0.7344
sub_17:Test (Best Model) - Loss: 1.1369 - Accuracy: 0.5217 - F1: 0.5113
sub_15:Test (Best Model) - Loss: 0.9600 - Accuracy: 0.5588 - F1: 0.5840
sub_22:Test (Best Model) - Loss: 1.2389 - Accuracy: 0.4706 - F1: 0.4451
sub_21:Test (Best Model) - Loss: 1.1203 - Accuracy: 0.5147 - F1: 0.5001
sub_26:Test (Best Model) - Loss: 1.0685 - Accuracy: 0.5294 - F1: 0.4846
sub_11:Test (Best Model) - Loss: 0.9802 - Accuracy: 0.5942 - F1: 0.5423
sub_24:Test (Best Model) - Loss: 1.0641 - Accuracy: 0.5588 - F1: 0.5539
sub_29:Test (Best Model) - Loss: 0.7773 - Accuracy: 0.7059 - F1: 0.7116
sub_27:Test (Best Model) - Loss: 1.1369 - Accuracy: 0.5217 - F1: 0.5113
sub_13:Test (Best Model) - Loss: 1.2521 - Accuracy: 0.4203 - F1: 0.3191
sub_14:Test (Best Model) - Loss: 0.9701 - Accuracy: 0.5147 - F1: 0.5560
sub_2:Test (Best Model) - Loss: 0.9905 - Accuracy: 0.5882 - F1: 0.5792
sub_12:Test (Best Model) - Loss: 0.9314 - Accuracy: 0.6377 - F1: 0.6474
sub_8:Test (Best Model) - Loss: 1.2403 - Accuracy: 0.5441 - F1: 0.5078
sub_10:Test (Best Model) - Loss: 1.0463 - Accuracy: 0.5441 - F1: 0.5565
sub_5:Test (Best Model) - Loss: 0.8444 - Accuracy: 0.6765 - F1: 0.6484
sub_28:Test (Best Model) - Loss: 1.3613 - Accuracy: 0.2941 - F1: 0.2747
sub_9:Test (Best Model) - Loss: 0.8546 - Accuracy: 0.7206 - F1: 0.6833
sub_4:Test (Best Model) - Loss: 0.8252 - Accuracy: 0.6377 - F1: 0.6348
sub_1:Test (Best Model) - Loss: 0.9573 - Accuracy: 0.5797 - F1: 0.5936
sub_18:Test (Best Model) - Loss: 1.1856 - Accuracy: 0.5735 - F1: 0.5654
sub_7:Test (Best Model) - Loss: 1.4574 - Accuracy: 0.4853 - F1: 0.4640
sub_16:Test (Best Model) - Loss: 0.8453 - Accuracy: 0.6765 - F1: 0.6724
sub_19:Test (Best Model) - Loss: 1.1713 - Accuracy: 0.5294 - F1: 0.4733
sub_11:Test (Best Model) - Loss: 0.9746 - Accuracy: 0.5797 - F1: 0.5379
sub_20:Test (Best Model) - Loss: 0.9457 - Accuracy: 0.5735 - F1: 0.5557
sub_17:Test (Best Model) - Loss: 1.1073 - Accuracy: 0.5507 - F1: 0.5508
sub_26:Test (Best Model) - Loss: 1.1157 - Accuracy: 0.4412 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 0.9463 - Accuracy: 0.6324 - F1: 0.6275
sub_23:Test (Best Model) - Loss: 1.4979 - Accuracy: 0.3971 - F1: 0.3256
sub_21:Test (Best Model) - Loss: 0.8538 - Accuracy: 0.6471 - F1: 0.6477
sub_6:Test (Best Model) - Loss: 0.9564 - Accuracy: 0.5652 - F1: 0.5288
sub_25:Test (Best Model) - Loss: 1.1394 - Accuracy: 0.5588 - F1: 0.5371
sub_28:Test (Best Model) - Loss: 1.4336 - Accuracy: 0.3971 - F1: 0.3189
sub_27:Test (Best Model) - Loss: 1.1073 - Accuracy: 0.5507 - F1: 0.5508
sub_3:Test (Best Model) - Loss: 1.0867 - Accuracy: 0.6232 - F1: 0.5821
sub_14:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.3971 - F1: 0.4267
sub_15:Test (Best Model) - Loss: 1.0952 - Accuracy: 0.5147 - F1: 0.5429
sub_12:Test (Best Model) - Loss: 0.9218 - Accuracy: 0.6667 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 1.1941 - Accuracy: 0.5000 - F1: 0.4504
sub_2:Test (Best Model) - Loss: 1.2157 - Accuracy: 0.4706 - F1: 0.4649
sub_9:Test (Best Model) - Loss: 0.7509 - Accuracy: 0.7353 - F1: 0.7176
sub_22:Test (Best Model) - Loss: 1.3650 - Accuracy: 0.4783 - F1: 0.4503
sub_13:Test (Best Model) - Loss: 1.2321 - Accuracy: 0.5072 - F1: 0.4497
sub_7:Test (Best Model) - Loss: 1.2358 - Accuracy: 0.4706 - F1: 0.4438
sub_10:Test (Best Model) - Loss: 0.9275 - Accuracy: 0.6176 - F1: 0.6209
sub_5:Test (Best Model) - Loss: 0.8969 - Accuracy: 0.6765 - F1: 0.6807
sub_16:Test (Best Model) - Loss: 0.8324 - Accuracy: 0.7647 - F1: 0.7586
sub_4:Test (Best Model) - Loss: 0.8293 - Accuracy: 0.7246 - F1: 0.7298
sub_18:Test (Best Model) - Loss: 1.1260 - Accuracy: 0.5294 - F1: 0.5476
sub_20:Test (Best Model) - Loss: 1.0575 - Accuracy: 0.5735 - F1: 0.5604
sub_29:Test (Best Model) - Loss: 0.8365 - Accuracy: 0.6618 - F1: 0.6614
sub_24:Test (Best Model) - Loss: 1.0064 - Accuracy: 0.5441 - F1: 0.5445
sub_23:Test (Best Model) - Loss: 1.4257 - Accuracy: 0.3824 - F1: 0.2829
sub_26:Test (Best Model) - Loss: 1.1188 - Accuracy: 0.5147 - F1: 0.4977
sub_17:Test (Best Model) - Loss: 1.1417 - Accuracy: 0.4348 - F1: 0.4702
sub_11:Test (Best Model) - Loss: 1.0032 - Accuracy: 0.6087 - F1: 0.5640
sub_19:Test (Best Model) - Loss: 0.9144 - Accuracy: 0.6176 - F1: 0.5737
sub_12:Test (Best Model) - Loss: 0.8099 - Accuracy: 0.7391 - F1: 0.7397
sub_1:Test (Best Model) - Loss: 0.9987 - Accuracy: 0.6377 - F1: 0.6650
sub_21:Test (Best Model) - Loss: 0.8139 - Accuracy: 0.6618 - F1: 0.6623
sub_27:Test (Best Model) - Loss: 1.1417 - Accuracy: 0.4348 - F1: 0.4702
sub_14:Test (Best Model) - Loss: 1.1029 - Accuracy: 0.5147 - F1: 0.5108
sub_15:Test (Best Model) - Loss: 1.1506 - Accuracy: 0.4706 - F1: 0.4996
sub_2:Test (Best Model) - Loss: 1.1610 - Accuracy: 0.5588 - F1: 0.5526
sub_9:Test (Best Model) - Loss: 0.9112 - Accuracy: 0.5882 - F1: 0.5656
sub_8:Test (Best Model) - Loss: 1.2748 - Accuracy: 0.5441 - F1: 0.5350
sub_28:Test (Best Model) - Loss: 1.5684 - Accuracy: 0.3676 - F1: 0.2859
sub_25:Test (Best Model) - Loss: 1.4322 - Accuracy: 0.3971 - F1: 0.3802
sub_4:Test (Best Model) - Loss: 0.9084 - Accuracy: 0.6667 - F1: 0.6685
sub_22:Test (Best Model) - Loss: 1.3526 - Accuracy: 0.4348 - F1: 0.3767
sub_3:Test (Best Model) - Loss: 0.9828 - Accuracy: 0.6377 - F1: 0.6331
sub_6:Test (Best Model) - Loss: 1.0386 - Accuracy: 0.5942 - F1: 0.5859
sub_10:Test (Best Model) - Loss: 0.9027 - Accuracy: 0.6765 - F1: 0.6505
sub_16:Test (Best Model) - Loss: 0.8882 - Accuracy: 0.6765 - F1: 0.6804
sub_18:Test (Best Model) - Loss: 1.0807 - Accuracy: 0.5735 - F1: 0.5739
sub_17:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3623 - F1: 0.3737
sub_7:Test (Best Model) - Loss: 1.5486 - Accuracy: 0.4118 - F1: 0.3731
sub_12:Test (Best Model) - Loss: 0.9840 - Accuracy: 0.6667 - F1: 0.6546
sub_13:Test (Best Model) - Loss: 1.2863 - Accuracy: 0.4928 - F1: 0.4546
sub_19:Test (Best Model) - Loss: 1.0693 - Accuracy: 0.5441 - F1: 0.4928
sub_20:Test (Best Model) - Loss: 1.1732 - Accuracy: 0.5000 - F1: 0.4544
sub_29:Test (Best Model) - Loss: 0.9872 - Accuracy: 0.5735 - F1: 0.5853
sub_26:Test (Best Model) - Loss: 1.1074 - Accuracy: 0.5294 - F1: 0.5196
sub_24:Test (Best Model) - Loss: 1.0791 - Accuracy: 0.5588 - F1: 0.5702
sub_5:Test (Best Model) - Loss: 0.8288 - Accuracy: 0.7059 - F1: 0.7206
sub_27:Test (Best Model) - Loss: 1.3021 - Accuracy: 0.3623 - F1: 0.3737
sub_23:Test (Best Model) - Loss: 1.5797 - Accuracy: 0.4265 - F1: 0.3250
sub_8:Test (Best Model) - Loss: 1.1694 - Accuracy: 0.5588 - F1: 0.5379
sub_11:Test (Best Model) - Loss: 0.9179 - Accuracy: 0.6377 - F1: 0.6283
sub_1:Test (Best Model) - Loss: 1.0134 - Accuracy: 0.5942 - F1: 0.6002
sub_4:Test (Best Model) - Loss: 0.8147 - Accuracy: 0.7101 - F1: 0.7092
sub_2:Test (Best Model) - Loss: 1.0910 - Accuracy: 0.5294 - F1: 0.5198
sub_21:Test (Best Model) - Loss: 0.8127 - Accuracy: 0.6618 - F1: 0.6376
sub_25:Test (Best Model) - Loss: 1.3062 - Accuracy: 0.4706 - F1: 0.4389
sub_18:Test (Best Model) - Loss: 1.0275 - Accuracy: 0.5882 - F1: 0.5981
sub_9:Test (Best Model) - Loss: 0.7331 - Accuracy: 0.7647 - F1: 0.7584
sub_15:Test (Best Model) - Loss: 1.0136 - Accuracy: 0.6324 - F1: 0.6478
sub_28:Test (Best Model) - Loss: 1.5413 - Accuracy: 0.4706 - F1: 0.4125
sub_6:Test (Best Model) - Loss: 1.0464 - Accuracy: 0.5652 - F1: 0.5103
sub_14:Test (Best Model) - Loss: 1.0173 - Accuracy: 0.5882 - F1: 0.5757
sub_7:Test (Best Model) - Loss: 1.3057 - Accuracy: 0.4706 - F1: 0.4275
sub_13:Test (Best Model) - Loss: 1.3083 - Accuracy: 0.4493 - F1: 0.4071
sub_16:Test (Best Model) - Loss: 0.8623 - Accuracy: 0.7647 - F1: 0.7672
sub_10:Test (Best Model) - Loss: 1.0416 - Accuracy: 0.6324 - F1: 0.5761
sub_17:Test (Best Model) - Loss: 1.3093 - Accuracy: 0.3623 - F1: 0.3707
sub_20:Test (Best Model) - Loss: 1.1012 - Accuracy: 0.5441 - F1: 0.5230
sub_29:Test (Best Model) - Loss: 0.9657 - Accuracy: 0.5588 - F1: 0.5891
sub_3:Test (Best Model) - Loss: 0.8373 - Accuracy: 0.7101 - F1: 0.6721
sub_4:Test (Best Model) - Loss: 0.9717 - Accuracy: 0.5507 - F1: 0.5520
sub_12:Test (Best Model) - Loss: 0.9288 - Accuracy: 0.6377 - F1: 0.6507
sub_5:Test (Best Model) - Loss: 0.8891 - Accuracy: 0.6176 - F1: 0.6205
sub_18:Test (Best Model) - Loss: 1.0761 - Accuracy: 0.5882 - F1: 0.5981
sub_27:Test (Best Model) - Loss: 1.3093 - Accuracy: 0.3623 - F1: 0.3707
sub_19:Test (Best Model) - Loss: 1.0014 - Accuracy: 0.6324 - F1: 0.5872
sub_26:Test (Best Model) - Loss: 1.1302 - Accuracy: 0.5735 - F1: 0.5824
sub_8:Test (Best Model) - Loss: 1.1640 - Accuracy: 0.5000 - F1: 0.4745
sub_23:Test (Best Model) - Loss: 1.4131 - Accuracy: 0.4853 - F1: 0.4057
sub_11:Test (Best Model) - Loss: 1.0502 - Accuracy: 0.5797 - F1: 0.5305
sub_15:Test (Best Model) - Loss: 1.0770 - Accuracy: 0.5000 - F1: 0.5170
sub_22:Test (Best Model) - Loss: 1.1936 - Accuracy: 0.4493 - F1: 0.4294
sub_28:Test (Best Model) - Loss: 1.5089 - Accuracy: 0.3676 - F1: 0.2917
sub_25:Test (Best Model) - Loss: 1.2524 - Accuracy: 0.4853 - F1: 0.4524
sub_16:Test (Best Model) - Loss: 1.0375 - Accuracy: 0.5882 - F1: 0.5530
sub_24:Test (Best Model) - Loss: 1.0726 - Accuracy: 0.5882 - F1: 0.5811
sub_2:Test (Best Model) - Loss: 1.1586 - Accuracy: 0.5735 - F1: 0.5778
sub_21:Test (Best Model) - Loss: 0.7796 - Accuracy: 0.6324 - F1: 0.6371
sub_1:Test (Best Model) - Loss: 0.9860 - Accuracy: 0.6232 - F1: 0.6363
sub_10:Test (Best Model) - Loss: 1.0151 - Accuracy: 0.6176 - F1: 0.5877
sub_7:Test (Best Model) - Loss: 1.3645 - Accuracy: 0.4412 - F1: 0.4115
sub_17:Test (Best Model) - Loss: 1.2701 - Accuracy: 0.3913 - F1: 0.4066
sub_6:Test (Best Model) - Loss: 0.9090 - Accuracy: 0.6087 - F1: 0.5741
sub_9:Test (Best Model) - Loss: 0.9973 - Accuracy: 0.6471 - F1: 0.6306
sub_14:Test (Best Model) - Loss: 1.0128 - Accuracy: 0.6324 - F1: 0.6277
sub_18:Test (Best Model) - Loss: 1.0083 - Accuracy: 0.5735 - F1: 0.5739
sub_20:Test (Best Model) - Loss: 1.1628 - Accuracy: 0.5441 - F1: 0.5227
sub_26:Test (Best Model) - Loss: 0.9934 - Accuracy: 0.6471 - F1: 0.6647
sub_29:Test (Best Model) - Loss: 0.9308 - Accuracy: 0.5882 - F1: 0.6045
sub_13:Test (Best Model) - Loss: 1.3988 - Accuracy: 0.4783 - F1: 0.4191
sub_5:Test (Best Model) - Loss: 0.8566 - Accuracy: 0.6176 - F1: 0.6416
sub_27:Test (Best Model) - Loss: 1.2701 - Accuracy: 0.3913 - F1: 0.4066
sub_11:Test (Best Model) - Loss: 1.0152 - Accuracy: 0.6377 - F1: 0.6368
sub_3:Test (Best Model) - Loss: 0.9582 - Accuracy: 0.6812 - F1: 0.6493
sub_12:Test (Best Model) - Loss: 1.0361 - Accuracy: 0.6471 - F1: 0.6410
sub_23:Test (Best Model) - Loss: 1.5440 - Accuracy: 0.3529 - F1: 0.2680
sub_19:Test (Best Model) - Loss: 1.0543 - Accuracy: 0.6176 - F1: 0.5737
sub_8:Test (Best Model) - Loss: 1.2742 - Accuracy: 0.4265 - F1: 0.4610
sub_16:Test (Best Model) - Loss: 1.0603 - Accuracy: 0.5294 - F1: 0.5451
sub_7:Test (Best Model) - Loss: 1.0079 - Accuracy: 0.6471 - F1: 0.6511
sub_15:Test (Best Model) - Loss: 1.4775 - Accuracy: 0.3971 - F1: 0.3460
sub_17:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.4638 - F1: 0.4832
sub_28:Test (Best Model) - Loss: 1.7199 - Accuracy: 0.3088 - F1: 0.2042
sub_10:Test (Best Model) - Loss: 1.1241 - Accuracy: 0.5294 - F1: 0.4939
sub_22:Test (Best Model) - Loss: 1.2622 - Accuracy: 0.4493 - F1: 0.4351
sub_29:Test (Best Model) - Loss: 0.8850 - Accuracy: 0.7246 - F1: 0.7139
sub_2:Test (Best Model) - Loss: 0.9756 - Accuracy: 0.6667 - F1: 0.6650
sub_1:Test (Best Model) - Loss: 0.9899 - Accuracy: 0.6522 - F1: 0.6595
sub_24:Test (Best Model) - Loss: 0.8607 - Accuracy: 0.6765 - F1: 0.6867
sub_4:Test (Best Model) - Loss: 0.9819 - Accuracy: 0.6087 - F1: 0.6220
sub_18:Test (Best Model) - Loss: 0.9569 - Accuracy: 0.5588 - F1: 0.5563
sub_26:Test (Best Model) - Loss: 1.1546 - Accuracy: 0.4265 - F1: 0.4506
sub_21:Test (Best Model) - Loss: 0.8130 - Accuracy: 0.6324 - F1: 0.6265
sub_9:Test (Best Model) - Loss: 0.9069 - Accuracy: 0.6176 - F1: 0.6027
sub_20:Test (Best Model) - Loss: 0.9930 - Accuracy: 0.6377 - F1: 0.6360
sub_11:Test (Best Model) - Loss: 0.9407 - Accuracy: 0.6812 - F1: 0.6906
sub_25:Test (Best Model) - Loss: 1.2700 - Accuracy: 0.5147 - F1: 0.4792
sub_27:Test (Best Model) - Loss: 1.2149 - Accuracy: 0.4638 - F1: 0.4832
sub_14:Test (Best Model) - Loss: 1.0845 - Accuracy: 0.4853 - F1: 0.5218
sub_6:Test (Best Model) - Loss: 1.1190 - Accuracy: 0.5652 - F1: 0.5689
sub_3:Test (Best Model) - Loss: 0.9319 - Accuracy: 0.6087 - F1: 0.6083
sub_16:Test (Best Model) - Loss: 1.0398 - Accuracy: 0.6029 - F1: 0.5789
sub_15:Test (Best Model) - Loss: 1.3448 - Accuracy: 0.4265 - F1: 0.3902
sub_5:Test (Best Model) - Loss: 0.9956 - Accuracy: 0.6324 - F1: 0.6025
sub_7:Test (Best Model) - Loss: 1.0732 - Accuracy: 0.5588 - F1: 0.5815
sub_23:Test (Best Model) - Loss: 1.0976 - Accuracy: 0.4928 - F1: 0.4527
sub_1:Test (Best Model) - Loss: 0.8897 - Accuracy: 0.6618 - F1: 0.6300
sub_8:Test (Best Model) - Loss: 1.3750 - Accuracy: 0.4412 - F1: 0.4443
sub_19:Test (Best Model) - Loss: 1.1430 - Accuracy: 0.6029 - F1: 0.5373
sub_12:Test (Best Model) - Loss: 1.0901 - Accuracy: 0.5441 - F1: 0.5351
sub_18:Test (Best Model) - Loss: 1.0721 - Accuracy: 0.5735 - F1: 0.5684
sub_25:Test (Best Model) - Loss: 1.1349 - Accuracy: 0.5147 - F1: 0.5355
sub_4:Test (Best Model) - Loss: 1.0097 - Accuracy: 0.5797 - F1: 0.5660
sub_28:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.2647 - F1: 0.2477
sub_10:Test (Best Model) - Loss: 0.8939 - Accuracy: 0.6812 - F1: 0.6555
sub_22:Test (Best Model) - Loss: 1.3458 - Accuracy: 0.4493 - F1: 0.4372
sub_20:Test (Best Model) - Loss: 1.0641 - Accuracy: 0.5797 - F1: 0.5788
sub_26:Test (Best Model) - Loss: 0.9805 - Accuracy: 0.5735 - F1: 0.6024
sub_17:Test (Best Model) - Loss: 1.0932 - Accuracy: 0.5000 - F1: 0.5027
sub_13:Test (Best Model) - Loss: 1.3384 - Accuracy: 0.4265 - F1: 0.4302
sub_24:Test (Best Model) - Loss: 1.0054 - Accuracy: 0.5735 - F1: 0.5623
sub_21:Test (Best Model) - Loss: 0.9658 - Accuracy: 0.5882 - F1: 0.5948
sub_1:Test (Best Model) - Loss: 0.9187 - Accuracy: 0.7059 - F1: 0.6625
sub_23:Test (Best Model) - Loss: 1.1592 - Accuracy: 0.4783 - F1: 0.4301
sub_14:Test (Best Model) - Loss: 1.0856 - Accuracy: 0.4706 - F1: 0.4785
sub_18:Test (Best Model) - Loss: 0.9385 - Accuracy: 0.6324 - F1: 0.6297
sub_9:Test (Best Model) - Loss: 1.0996 - Accuracy: 0.5588 - F1: 0.5390
sub_6:Test (Best Model) - Loss: 1.0675 - Accuracy: 0.5797 - F1: 0.5693
sub_15:Test (Best Model) - Loss: 1.3680 - Accuracy: 0.4265 - F1: 0.3854
sub_19:Test (Best Model) - Loss: 1.1742 - Accuracy: 0.5294 - F1: 0.4771
sub_20:Test (Best Model) - Loss: 1.1486 - Accuracy: 0.5507 - F1: 0.5578
sub_27:Test (Best Model) - Loss: 1.0932 - Accuracy: 0.5000 - F1: 0.5027
sub_2:Test (Best Model) - Loss: 0.8511 - Accuracy: 0.6812 - F1: 0.6836
sub_7:Test (Best Model) - Loss: 0.9152 - Accuracy: 0.6765 - F1: 0.6908
sub_3:Test (Best Model) - Loss: 1.0156 - Accuracy: 0.5652 - F1: 0.5771
sub_29:Test (Best Model) - Loss: 0.8360 - Accuracy: 0.6667 - F1: 0.6520
sub_11:Test (Best Model) - Loss: 0.9642 - Accuracy: 0.6087 - F1: 0.6036
sub_12:Test (Best Model) - Loss: 0.9921 - Accuracy: 0.6324 - F1: 0.6237
sub_16:Test (Best Model) - Loss: 0.9685 - Accuracy: 0.6324 - F1: 0.6291
sub_22:Test (Best Model) - Loss: 1.1306 - Accuracy: 0.5000 - F1: 0.4929
sub_10:Test (Best Model) - Loss: 0.8912 - Accuracy: 0.6957 - F1: 0.6917
sub_5:Test (Best Model) - Loss: 0.8782 - Accuracy: 0.7206 - F1: 0.6741
sub_28:Test (Best Model) - Loss: 1.3162 - Accuracy: 0.4118 - F1: 0.3906
sub_8:Test (Best Model) - Loss: 1.8181 - Accuracy: 0.3971 - F1: 0.4270
sub_13:Test (Best Model) - Loss: 1.4457 - Accuracy: 0.3971 - F1: 0.3859
sub_24:Test (Best Model) - Loss: 0.9569 - Accuracy: 0.6324 - F1: 0.6457
sub_4:Test (Best Model) - Loss: 1.1665 - Accuracy: 0.5652 - F1: 0.5421
sub_18:Test (Best Model) - Loss: 0.9984 - Accuracy: 0.6324 - F1: 0.6358
sub_25:Test (Best Model) - Loss: 1.4626 - Accuracy: 0.4118 - F1: 0.4440
sub_21:Test (Best Model) - Loss: 0.9481 - Accuracy: 0.6324 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 1.1602 - Accuracy: 0.4853 - F1: 0.4796
sub_6:Test (Best Model) - Loss: 1.0808 - Accuracy: 0.4928 - F1: 0.4871
sub_17:Test (Best Model) - Loss: 1.0728 - Accuracy: 0.5882 - F1: 0.6035
sub_26:Test (Best Model) - Loss: 1.0776 - Accuracy: 0.5882 - F1: 0.6193
sub_15:Test (Best Model) - Loss: 1.3117 - Accuracy: 0.3971 - F1: 0.3296
sub_7:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.6324 - F1: 0.6409
sub_2:Test (Best Model) - Loss: 1.0108 - Accuracy: 0.6232 - F1: 0.6113
sub_19:Test (Best Model) - Loss: 1.1683 - Accuracy: 0.5735 - F1: 0.5323
sub_23:Test (Best Model) - Loss: 1.2370 - Accuracy: 0.4493 - F1: 0.4198
sub_9:Test (Best Model) - Loss: 1.2276 - Accuracy: 0.5147 - F1: 0.4785
sub_20:Test (Best Model) - Loss: 1.1460 - Accuracy: 0.5362 - F1: 0.5296
sub_27:Test (Best Model) - Loss: 1.0728 - Accuracy: 0.5882 - F1: 0.6035
sub_3:Test (Best Model) - Loss: 1.0366 - Accuracy: 0.5217 - F1: 0.5039
sub_11:Test (Best Model) - Loss: 0.9555 - Accuracy: 0.6232 - F1: 0.6360
sub_16:Test (Best Model) - Loss: 1.0384 - Accuracy: 0.5294 - F1: 0.5400
sub_22:Test (Best Model) - Loss: 1.1824 - Accuracy: 0.4853 - F1: 0.4930
sub_10:Test (Best Model) - Loss: 0.9476 - Accuracy: 0.6087 - F1: 0.5724
sub_12:Test (Best Model) - Loss: 0.9800 - Accuracy: 0.6029 - F1: 0.6146
sub_8:Test (Best Model) - Loss: 1.4370 - Accuracy: 0.4118 - F1: 0.4459
sub_28:Test (Best Model) - Loss: 1.5552 - Accuracy: 0.2794 - F1: 0.2628
sub_13:Test (Best Model) - Loss: 1.3273 - Accuracy: 0.3529 - F1: 0.3308
sub_26:Test (Best Model) - Loss: 1.0901 - Accuracy: 0.5147 - F1: 0.5475
sub_4:Test (Best Model) - Loss: 1.1511 - Accuracy: 0.5652 - F1: 0.5614
sub_6:Test (Best Model) - Loss: 1.0620 - Accuracy: 0.5652 - F1: 0.5585
sub_24:Test (Best Model) - Loss: 0.8497 - Accuracy: 0.6765 - F1: 0.6908
sub_1:Test (Best Model) - Loss: 1.0782 - Accuracy: 0.6324 - F1: 0.6005
sub_5:Test (Best Model) - Loss: 0.9788 - Accuracy: 0.6618 - F1: 0.6295
sub_2:Test (Best Model) - Loss: 0.9468 - Accuracy: 0.6232 - F1: 0.6161
sub_20:Test (Best Model) - Loss: 1.1871 - Accuracy: 0.5362 - F1: 0.5459
sub_14:Test (Best Model) - Loss: 1.2023 - Accuracy: 0.4706 - F1: 0.4923
sub_25:Test (Best Model) - Loss: 1.1435 - Accuracy: 0.5588 - F1: 0.5797
sub_19:Test (Best Model) - Loss: 1.1862 - Accuracy: 0.5588 - F1: 0.5074
sub_21:Test (Best Model) - Loss: 0.9364 - Accuracy: 0.6324 - F1: 0.6195
sub_9:Test (Best Model) - Loss: 1.1618 - Accuracy: 0.4853 - F1: 0.4835
sub_22:Test (Best Model) - Loss: 1.1226 - Accuracy: 0.5000 - F1: 0.5087
sub_3:Test (Best Model) - Loss: 0.9788 - Accuracy: 0.5942 - F1: 0.5657
sub_23:Test (Best Model) - Loss: 1.4040 - Accuracy: 0.4203 - F1: 0.3915
sub_15:Test (Best Model) - Loss: 1.6588 - Accuracy: 0.4412 - F1: 0.3970
sub_12:Test (Best Model) - Loss: 1.0440 - Accuracy: 0.6176 - F1: 0.6194
sub_7:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.6029 - F1: 0.6256
sub_29:Test (Best Model) - Loss: 0.9460 - Accuracy: 0.6667 - F1: 0.6497
sub_11:Test (Best Model) - Loss: 0.9481 - Accuracy: 0.6087 - F1: 0.6107
sub_17:Test (Best Model) - Loss: 1.0081 - Accuracy: 0.6618 - F1: 0.6682
sub_28:Test (Best Model) - Loss: 1.5484 - Accuracy: 0.2941 - F1: 0.2770
sub_8:Test (Best Model) - Loss: 1.5301 - Accuracy: 0.3971 - F1: 0.4334
sub_13:Test (Best Model) - Loss: 1.2564 - Accuracy: 0.3235 - F1: 0.3111
sub_27:Test (Best Model) - Loss: 1.0081 - Accuracy: 0.6618 - F1: 0.6682
sub_2:Test (Best Model) - Loss: 1.1352 - Accuracy: 0.5652 - F1: 0.5361
sub_1:Test (Best Model) - Loss: 0.9444 - Accuracy: 0.6324 - F1: 0.6155
sub_6:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.5362 - F1: 0.5382
sub_3:Test (Best Model) - Loss: 1.0688 - Accuracy: 0.5072 - F1: 0.5131
sub_22:Test (Best Model) - Loss: 1.1823 - Accuracy: 0.4853 - F1: 0.4630
sub_10:Test (Best Model) - Loss: 0.8879 - Accuracy: 0.6957 - F1: 0.6898
sub_14:Test (Best Model) - Loss: 1.2256 - Accuracy: 0.4706 - F1: 0.4747
sub_29:Test (Best Model) - Loss: 0.9682 - Accuracy: 0.6232 - F1: 0.6111
sub_24:Test (Best Model) - Loss: 0.8714 - Accuracy: 0.6471 - F1: 0.6546
sub_28:Test (Best Model) - Loss: 1.8302 - Accuracy: 0.2794 - F1: 0.2820
sub_23:Test (Best Model) - Loss: 1.3094 - Accuracy: 0.4203 - F1: 0.3844
sub_19:Test (Best Model) - Loss: 1.2719 - Accuracy: 0.5588 - F1: 0.5102
sub_21:Test (Best Model) - Loss: 0.8337 - Accuracy: 0.6029 - F1: 0.6046
sub_25:Test (Best Model) - Loss: 1.1324 - Accuracy: 0.5882 - F1: 0.6025
sub_5:Test (Best Model) - Loss: 1.0235 - Accuracy: 0.6765 - F1: 0.6148
sub_17:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.5735 - F1: 0.5767
sub_9:Test (Best Model) - Loss: 1.1548 - Accuracy: 0.6176 - F1: 0.5667
sub_13:Test (Best Model) - Loss: 1.3002 - Accuracy: 0.4706 - F1: 0.4715
sub_10:Test (Best Model) - Loss: 1.0288 - Accuracy: 0.6087 - F1: 0.5938
sub_27:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.5735 - F1: 0.5767
sub_22:Test (Best Model) - Loss: 1.1589 - Accuracy: 0.5294 - F1: 0.5311
sub_1:Test (Best Model) - Loss: 0.9556 - Accuracy: 0.6471 - F1: 0.6013
sub_17:Test (Best Model) - Loss: 1.1297 - Accuracy: 0.5441 - F1: 0.5551
sub_29:Test (Best Model) - Loss: 0.9885 - Accuracy: 0.6377 - F1: 0.6374
sub_9:Test (Best Model) - Loss: 1.2148 - Accuracy: 0.5147 - F1: 0.4959
sub_25:Test (Best Model) - Loss: 1.3089 - Accuracy: 0.4412 - F1: 0.4770
sub_5:Test (Best Model) - Loss: 0.8267 - Accuracy: 0.7500 - F1: 0.7387
sub_27:Test (Best Model) - Loss: 1.1297 - Accuracy: 0.5441 - F1: 0.5551
sub_21:Test (Best Model) - Loss: 0.9323 - Accuracy: 0.6618 - F1: 0.6362

=== Summary Results ===

acc: 55.39 ± 6.96
F1: 54.17 ± 7.63
acc-in: 81.73 ± 5.99
F1-in: 81.34 ± 6.11
