lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.6319 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 0.5880 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 0.4490 - Accuracy: 0.8452 - F1: 0.8442
sub_1:Test (Best Model) - Loss: 0.4194 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.4379 - Accuracy: 0.8333 - F1: 0.8330
sub_1:Test (Best Model) - Loss: 0.3892 - Accuracy: 0.8452 - F1: 0.8447
sub_1:Test (Best Model) - Loss: 0.4100 - Accuracy: 0.8214 - F1: 0.8212
sub_1:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 0.5167 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.5267 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5418 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.5064 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.4637 - Accuracy: 0.8095 - F1: 0.8091
sub_2:Test (Best Model) - Loss: 0.4460 - Accuracy: 0.7857 - F1: 0.7857
sub_2:Test (Best Model) - Loss: 0.4065 - Accuracy: 0.9048 - F1: 0.9047
sub_2:Test (Best Model) - Loss: 0.4377 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.4697 - Accuracy: 0.7976 - F1: 0.7974
sub_2:Test (Best Model) - Loss: 0.4394 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.4206 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.3885 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.3904 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.4065 - Accuracy: 0.7738 - F1: 0.7616
sub_2:Test (Best Model) - Loss: 0.3997 - Accuracy: 0.7976 - F1: 0.7953
sub_2:Test (Best Model) - Loss: 0.3667 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.4267 - Accuracy: 0.8333 - F1: 0.8318
sub_2:Test (Best Model) - Loss: 0.3232 - Accuracy: 0.9048 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.8571 - F1: 0.8564
sub_3:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.5952 - F1: 0.5265
sub_3:Test (Best Model) - Loss: 0.7694 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 0.7804 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.4541 - Accuracy: 0.7500 - F1: 0.7500
sub_3:Test (Best Model) - Loss: 0.4780 - Accuracy: 0.7619 - F1: 0.7618
sub_3:Test (Best Model) - Loss: 0.5215 - Accuracy: 0.7143 - F1: 0.7143
sub_3:Test (Best Model) - Loss: 0.4908 - Accuracy: 0.7738 - F1: 0.7722
sub_3:Test (Best Model) - Loss: 0.4737 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.6667 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.7143 - F1: 0.6889
sub_3:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6905 - F1: 0.6577
sub_3:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.6667 - F1: 0.6250
sub_4:Test (Best Model) - Loss: 0.5096 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.5424 - Accuracy: 0.7381 - F1: 0.7375
sub_4:Test (Best Model) - Loss: 0.5204 - Accuracy: 0.7738 - F1: 0.7735
sub_4:Test (Best Model) - Loss: 0.5642 - Accuracy: 0.7143 - F1: 0.7141
sub_4:Test (Best Model) - Loss: 0.5246 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 0.5337 - Accuracy: 0.6905 - F1: 0.6816
sub_4:Test (Best Model) - Loss: 0.4994 - Accuracy: 0.6905 - F1: 0.6788
sub_4:Test (Best Model) - Loss: 0.4346 - Accuracy: 0.8095 - F1: 0.8091
sub_4:Test (Best Model) - Loss: 0.4140 - Accuracy: 0.8095 - F1: 0.8068
sub_4:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 0.4689 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.7024 - F1: 0.6825
sub_4:Test (Best Model) - Loss: 0.4817 - Accuracy: 0.7619 - F1: 0.7569
sub_4:Test (Best Model) - Loss: 0.5329 - Accuracy: 0.7143 - F1: 0.7005
sub_4:Test (Best Model) - Loss: 0.4526 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 0.4041 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.3788 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.3605 - Accuracy: 0.8810 - F1: 0.8807
sub_5:Test (Best Model) - Loss: 0.3859 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.4067 - Accuracy: 0.8452 - F1: 0.8442
sub_5:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4009 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.4390 - Accuracy: 0.7500 - F1: 0.7483
sub_5:Test (Best Model) - Loss: 0.4069 - Accuracy: 0.8571 - F1: 0.8542
sub_5:Test (Best Model) - Loss: 0.4207 - Accuracy: 0.8095 - F1: 0.8085
sub_5:Test (Best Model) - Loss: 0.3859 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.3957 - Accuracy: 0.8214 - F1: 0.8194
sub_5:Test (Best Model) - Loss: 0.3529 - Accuracy: 0.8452 - F1: 0.8447
sub_5:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 0.3636 - Accuracy: 0.8810 - F1: 0.8807
sub_6:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.6124 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6667 - F1: 0.6636
sub_6:Test (Best Model) - Loss: 0.6182 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.6014 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 0.6104 - Accuracy: 0.6429 - F1: 0.6420
sub_6:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.6786 - F1: 0.6763
sub_6:Test (Best Model) - Loss: 0.5656 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 0.5766 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 0.5601 - Accuracy: 0.7262 - F1: 0.7262
sub_6:Test (Best Model) - Loss: 0.5465 - Accuracy: 0.7738 - F1: 0.7735
sub_6:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6548 - F1: 0.6543
sub_6:Test (Best Model) - Loss: 0.5975 - Accuracy: 0.6667 - F1: 0.6659
sub_7:Test (Best Model) - Loss: 0.6632 - Accuracy: 0.6667 - F1: 0.6650
sub_7:Test (Best Model) - Loss: 0.7206 - Accuracy: 0.5476 - F1: 0.5476
sub_7:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.5952 - F1: 0.5932
sub_7:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.6548 - F1: 0.6523
sub_7:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.5714 - F1: 0.5705
sub_7:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.5476 - F1: 0.5074
sub_7:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.5714 - F1: 0.5088
sub_7:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.5833 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.5952 - F1: 0.5894
sub_7:Test (Best Model) - Loss: 0.6173 - Accuracy: 0.6667 - F1: 0.6370
sub_7:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.5595 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.6905 - F1: 0.6898
sub_7:Test (Best Model) - Loss: 0.6521 - Accuracy: 0.5952 - F1: 0.5932
sub_7:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5952 - F1: 0.5868
sub_8:Test (Best Model) - Loss: 0.3567 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3673 - Accuracy: 0.8333 - F1: 0.8330
sub_8:Test (Best Model) - Loss: 0.3677 - Accuracy: 0.8690 - F1: 0.8689
sub_8:Test (Best Model) - Loss: 0.3560 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.3574 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.2995 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.3390 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.8810 - F1: 0.8807
sub_8:Test (Best Model) - Loss: 0.3156 - Accuracy: 0.8571 - F1: 0.8564
sub_8:Test (Best Model) - Loss: 0.3382 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.3120 - Accuracy: 0.8690 - F1: 0.8681
sub_8:Test (Best Model) - Loss: 0.3033 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2479 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.2725 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.3050 - Accuracy: 0.8690 - F1: 0.8681
sub_9:Test (Best Model) - Loss: 0.4169 - Accuracy: 0.8214 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 0.4527 - Accuracy: 0.7619 - F1: 0.7607
sub_9:Test (Best Model) - Loss: 0.3971 - Accuracy: 0.8452 - F1: 0.8442
sub_9:Test (Best Model) - Loss: 0.4659 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.4822 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 0.4323 - Accuracy: 0.8095 - F1: 0.8085
sub_9:Test (Best Model) - Loss: 0.4326 - Accuracy: 0.8214 - F1: 0.8208
sub_9:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.8095 - F1: 0.8091
sub_9:Test (Best Model) - Loss: 0.5002 - Accuracy: 0.7976 - F1: 0.7974
sub_9:Test (Best Model) - Loss: 0.4128 - Accuracy: 0.8333 - F1: 0.8330
sub_9:Test (Best Model) - Loss: 0.5667 - Accuracy: 0.7024 - F1: 0.6735
sub_9:Test (Best Model) - Loss: 0.5107 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 0.4944 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 0.4748 - Accuracy: 0.7143 - F1: 0.6932
sub_9:Test (Best Model) - Loss: 0.5009 - Accuracy: 0.7143 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.5987 - Accuracy: 0.6548 - F1: 0.6523
sub_10:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6310 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 0.5994 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.6190 - F1: 0.6188
sub_10:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6429 - F1: 0.6429
sub_10:Test (Best Model) - Loss: 0.5868 - Accuracy: 0.6667 - F1: 0.6636
sub_10:Test (Best Model) - Loss: 0.6105 - Accuracy: 0.7143 - F1: 0.7141
sub_10:Test (Best Model) - Loss: 0.6264 - Accuracy: 0.6905 - F1: 0.6905
sub_10:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.7024 - F1: 0.7020
sub_10:Test (Best Model) - Loss: 0.4949 - Accuracy: 0.7738 - F1: 0.7735
sub_10:Test (Best Model) - Loss: 0.5938 - Accuracy: 0.7143 - F1: 0.7083
sub_10:Test (Best Model) - Loss: 0.5511 - Accuracy: 0.6429 - F1: 0.6420
sub_11:Test (Best Model) - Loss: 0.5772 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.7143 - F1: 0.7128
sub_11:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.6905 - F1: 0.6905
sub_11:Test (Best Model) - Loss: 0.4604 - Accuracy: 0.8452 - F1: 0.8450
sub_11:Test (Best Model) - Loss: 0.4536 - Accuracy: 0.7619 - F1: 0.7614
sub_11:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.8095 - F1: 0.8095
sub_11:Test (Best Model) - Loss: 0.4849 - Accuracy: 0.7500 - F1: 0.7483
sub_11:Test (Best Model) - Loss: 0.4535 - Accuracy: 0.8214 - F1: 0.8214
sub_11:Test (Best Model) - Loss: 0.5173 - Accuracy: 0.7857 - F1: 0.7826
sub_11:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.6905 - F1: 0.6860
sub_11:Test (Best Model) - Loss: 0.5206 - Accuracy: 0.7500 - F1: 0.7456
sub_11:Test (Best Model) - Loss: 0.4563 - Accuracy: 0.7619 - F1: 0.7597
sub_11:Test (Best Model) - Loss: 0.5251 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.3933 - Accuracy: 0.8333 - F1: 0.8332
sub_12:Test (Best Model) - Loss: 0.3384 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 0.3106 - Accuracy: 0.9048 - F1: 0.9047
sub_12:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.8929 - F1: 0.8928
sub_12:Test (Best Model) - Loss: 0.3989 - Accuracy: 0.7738 - F1: 0.7722
sub_12:Test (Best Model) - Loss: 0.5352 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 0.5565 - Accuracy: 0.7381 - F1: 0.7282
sub_12:Test (Best Model) - Loss: 0.4996 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.5156 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.4866 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.7738 - F1: 0.7641
sub_12:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.7857 - F1: 0.7776
sub_12:Test (Best Model) - Loss: 0.4225 - Accuracy: 0.7738 - F1: 0.7683
sub_12:Test (Best Model) - Loss: 0.4924 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 0.5308 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.5692 - Accuracy: 0.7262 - F1: 0.7258
sub_13:Test (Best Model) - Loss: 0.5315 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 0.5197 - Accuracy: 0.8095 - F1: 0.8094
sub_13:Test (Best Model) - Loss: 0.5274 - Accuracy: 0.7976 - F1: 0.7976
sub_13:Test (Best Model) - Loss: 0.5461 - Accuracy: 0.6548 - F1: 0.6487
sub_13:Test (Best Model) - Loss: 0.5205 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.4915 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.4606 - Accuracy: 0.7857 - F1: 0.7838
sub_13:Test (Best Model) - Loss: 0.4902 - Accuracy: 0.7619 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 0.4815 - Accuracy: 0.8095 - F1: 0.8068
sub_13:Test (Best Model) - Loss: 0.5051 - Accuracy: 0.7738 - F1: 0.7722
sub_13:Test (Best Model) - Loss: 0.4897 - Accuracy: 0.7857 - F1: 0.7856
sub_13:Test (Best Model) - Loss: 0.4924 - Accuracy: 0.7857 - F1: 0.7796
sub_13:Test (Best Model) - Loss: 0.5169 - Accuracy: 0.7976 - F1: 0.7953
sub_14:Test (Best Model) - Loss: 0.3492 - Accuracy: 0.8214 - F1: 0.8208
sub_14:Test (Best Model) - Loss: 0.3693 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.3068 - Accuracy: 0.8810 - F1: 0.8809
sub_14:Test (Best Model) - Loss: 0.4337 - Accuracy: 0.8452 - F1: 0.8447
sub_14:Test (Best Model) - Loss: 0.3730 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.4445 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 0.3992 - Accuracy: 0.7976 - F1: 0.7927
sub_14:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.8214 - F1: 0.8170
sub_14:Test (Best Model) - Loss: 0.3835 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 0.3974 - Accuracy: 0.8690 - F1: 0.8689
sub_14:Test (Best Model) - Loss: 0.4076 - Accuracy: 0.8095 - F1: 0.8095
sub_14:Test (Best Model) - Loss: 0.3951 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.4056 - Accuracy: 0.8214 - F1: 0.8212

=== Summary Results ===

acc: 75.20 ± 7.23
F1: 74.47 ± 7.67
acc-in: 80.54 ± 7.26
F1-in: 80.17 ± 7.52
