lr: 1e-05
sub_3:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6429 - F1: 0.6420
sub_13:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6310 - F1: 0.6296
sub_6:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7381 - F1: 0.7379
sub_5:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.6429 - F1: 0.6420
sub_3:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7381 - F1: 0.7357
sub_7:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.5357 - F1: 0.5048
sub_2:Test (Best Model) - Loss: 0.6079 - Accuracy: 0.8810 - F1: 0.8799
sub_9:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.6190 - F1: 0.6171
sub_1:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.6548 - F1: 0.6543
sub_5:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6667 - F1: 0.6659
sub_4:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6310 - F1: 0.6305
sub_11:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6310 - F1: 0.6296
sub_14:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.7262 - F1: 0.7252
sub_12:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5357 - F1: 0.5341
sub_10:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6548 - F1: 0.6508
sub_6:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7381 - F1: 0.7326
sub_13:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.7262 - F1: 0.7243
sub_8:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7619 - F1: 0.7614
sub_7:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.7381 - F1: 0.7375
sub_3:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.5119 - F1: 0.5113
sub_5:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.6190 - F1: 0.5787
sub_1:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6190 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.6310 - F1: 0.6245
sub_11:Test (Best Model) - Loss: 0.6670 - Accuracy: 0.6667 - F1: 0.6619
sub_7:Test (Best Model) - Loss: 0.7042 - Accuracy: 0.4762 - F1: 0.4612
sub_14:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.7262 - F1: 0.7214
sub_3:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4048 - F1: 0.3690
sub_2:Test (Best Model) - Loss: 0.5953 - Accuracy: 0.8452 - F1: 0.8452
sub_4:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6190 - F1: 0.6156
sub_1:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.4881 - F1: 0.4845
sub_13:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.6548 - F1: 0.6361
sub_11:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5714 - F1: 0.5712
sub_9:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.8452 - F1: 0.8447
sub_10:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.7262 - F1: 0.7230
sub_12:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5357 - F1: 0.5351
sub_8:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7500 - F1: 0.7497
sub_5:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.6071 - F1: 0.5904
sub_1:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6190 - F1: 0.6136
sub_3:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.6905 - F1: 0.6860
sub_7:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.4643 - F1: 0.4511
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.4974
sub_13:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5714 - F1: 0.5712
sub_4:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5238 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.5769 - Accuracy: 0.8690 - F1: 0.8675
sub_14:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6905 - F1: 0.6898
sub_11:Test (Best Model) - Loss: 0.6626 - Accuracy: 0.6310 - F1: 0.6245
sub_10:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.5357 - F1: 0.5351
sub_3:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5714 - F1: 0.5653
sub_1:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5238 - F1: 0.5059
sub_13:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4524 - F1: 0.4474
sub_5:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.7262 - F1: 0.7195
sub_9:Test (Best Model) - Loss: 0.6609 - Accuracy: 0.6310 - F1: 0.6111
sub_6:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.7024 - F1: 0.7020
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5238 - F1: 0.5214
sub_3:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5119 - F1: 0.5034
sub_1:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5476 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5595 - F1: 0.5595
sub_12:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.6071 - F1: 0.6057
sub_8:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.7976 - F1: 0.7969
sub_5:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.6429 - F1: 0.6294
sub_14:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.7024 - F1: 0.7023
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5476 - F1: 0.5474
sub_10:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6310 - F1: 0.6010
sub_4:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4762 - F1: 0.4714
sub_2:Test (Best Model) - Loss: 0.5848 - Accuracy: 0.8690 - F1: 0.8686
sub_13:Test (Best Model) - Loss: 0.6776 - Accuracy: 0.6190 - F1: 0.6111
sub_12:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5714 - F1: 0.5625
sub_6:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.7024 - F1: 0.7013
sub_9:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.8690 - F1: 0.8675
sub_7:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5119 - F1: 0.5118
sub_14:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.6429 - F1: 0.6420
sub_5:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.6310 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6667 - F1: 0.6665
sub_1:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.6786 - F1: 0.6680
sub_3:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.4881 - F1: 0.4880
sub_10:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.6548 - F1: 0.6268
sub_2:Test (Best Model) - Loss: 0.6208 - Accuracy: 0.8333 - F1: 0.8330
sub_8:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6548 - F1: 0.6487
sub_14:Test (Best Model) - Loss: 0.6803 - Accuracy: 0.5833 - F1: 0.5833
sub_3:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5595 - F1: 0.5580
sub_10:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.7262 - F1: 0.7252
sub_9:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7976 - F1: 0.7969
sub_12:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.7262 - F1: 0.7252
sub_5:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5595 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.6754 - Accuracy: 0.5952 - F1: 0.5950
sub_3:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4643 - F1: 0.4605
sub_2:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.8095 - F1: 0.8085
sub_7:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6667 - F1: 0.6466
sub_8:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.7262 - F1: 0.7252
sub_14:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.8095 - F1: 0.8085
sub_13:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.6548 - F1: 0.6543
sub_1:Test (Best Model) - Loss: 0.6063 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.7262 - F1: 0.7258
sub_10:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.6310 - F1: 0.6219
sub_7:Test (Best Model) - Loss: 0.6614 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5119 - F1: 0.4911
sub_2:Test (Best Model) - Loss: 0.6347 - Accuracy: 0.7976 - F1: 0.7969
sub_6:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6071 - F1: 0.6057
sub_1:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6905 - F1: 0.6860
sub_14:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.7976 - F1: 0.7976
sub_10:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.7619 - F1: 0.7618
sub_4:Test (Best Model) - Loss: 0.6384 - Accuracy: 0.8333 - F1: 0.8332
sub_11:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6429 - F1: 0.6396
sub_7:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.3929 - F1: 0.3921
sub_9:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.8571 - F1: 0.8568
sub_12:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.7738 - F1: 0.7722
sub_6:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.5952 - F1: 0.5709
sub_10:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5833 - F1: 0.5761
sub_5:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5833 - F1: 0.5804
sub_1:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6548 - F1: 0.6543
sub_2:Test (Best Model) - Loss: 0.6483 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.7381 - F1: 0.7306
sub_13:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.6071 - F1: 0.6066
sub_3:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.6905 - F1: 0.6898
sub_5:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5595 - F1: 0.5595
sub_4:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5238 - F1: 0.5227
sub_6:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4286 - F1: 0.4233
sub_11:Test (Best Model) - Loss: 0.6410 - Accuracy: 0.8333 - F1: 0.8333
sub_4:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5119 - F1: 0.5118
sub_9:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.8929 - F1: 0.8916
sub_2:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.8333 - F1: 0.8330
sub_13:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.4405 - F1: 0.4366
sub_8:Test (Best Model) - Loss: 0.6365 - Accuracy: 0.6548 - F1: 0.6080
sub_10:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7500 - F1: 0.7500
sub_5:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.6071 - F1: 0.6071
sub_14:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.8214 - F1: 0.8194
sub_7:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.4762 - F1: 0.4735
sub_12:Test (Best Model) - Loss: 0.6035 - Accuracy: 0.8929 - F1: 0.8927
sub_13:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.6786 - F1: 0.6707
sub_9:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.7024 - F1: 0.7023
sub_4:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.7500 - F1: 0.7497
sub_14:Test (Best Model) - Loss: 0.6659 - Accuracy: 0.6429 - F1: 0.6429
sub_6:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5952 - F1: 0.5915
sub_2:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.7976 - F1: 0.7969
sub_11:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6786 - F1: 0.6730
sub_5:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6190 - F1: 0.5962
sub_3:Test (Best Model) - Loss: 0.6709 - Accuracy: 0.6429 - F1: 0.6327
sub_8:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6548 - F1: 0.6463
sub_7:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5119 - F1: 0.4999
sub_10:Test (Best Model) - Loss: 0.7202 - Accuracy: 0.3571 - F1: 0.3262
sub_6:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.5714 - F1: 0.5712
sub_1:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6310 - F1: 0.6309
sub_3:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.4928
sub_7:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4881 - F1: 0.4792
sub_9:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5952 - F1: 0.5952
sub_2:Test (Best Model) - Loss: 0.6022 - Accuracy: 0.8333 - F1: 0.8330
sub_4:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.5952 - F1: 0.5837
sub_13:Test (Best Model) - Loss: 0.6645 - Accuracy: 0.6905 - F1: 0.6816
sub_14:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.6786 - F1: 0.6782
sub_9:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.7500 - F1: 0.7456
sub_12:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6548 - F1: 0.6508
sub_5:Test (Best Model) - Loss: 0.6584 - Accuracy: 0.7143 - F1: 0.7035
sub_10:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.4556
sub_11:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7143 - F1: 0.7128
sub_1:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4881 - F1: 0.4792
sub_8:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6905 - F1: 0.6840
sub_2:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.7262 - F1: 0.7243
sub_12:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.5357 - F1: 0.5243
sub_4:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.6905 - F1: 0.6905
sub_7:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.6905 - F1: 0.6860
sub_10:Test (Best Model) - Loss: 0.6622 - Accuracy: 0.7857 - F1: 0.7838
sub_6:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.8690 - F1: 0.8690
sub_13:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5952 - F1: 0.5915
sub_14:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.6905 - F1: 0.6876
sub_7:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.4167 - F1: 0.4159
sub_6:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.6071 - F1: 0.5904
sub_13:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5119 - F1: 0.5113
sub_9:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.7500 - F1: 0.7418
sub_2:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.8333 - F1: 0.8333
sub_11:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.8095 - F1: 0.8094
sub_1:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.7262 - F1: 0.7243
sub_8:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7381 - F1: 0.7224
sub_14:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 0.6788 - Accuracy: 0.5595 - F1: 0.5238
sub_2:Test (Best Model) - Loss: 0.6121 - Accuracy: 0.7976 - F1: 0.7976
sub_6:Test (Best Model) - Loss: 0.6290 - Accuracy: 0.7857 - F1: 0.7838
sub_4:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7262 - F1: 0.7145
sub_1:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5714 - F1: 0.5692
sub_9:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6429 - F1: 0.6166
sub_8:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.5833 - F1: 0.5556
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4762 - F1: 0.4735
sub_11:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.7738 - F1: 0.7735
sub_6:Test (Best Model) - Loss: 0.7242 - Accuracy: 0.3333 - F1: 0.3330
sub_2:Test (Best Model) - Loss: 0.6236 - Accuracy: 0.7738 - F1: 0.7722
sub_12:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5714 - F1: 0.5692
sub_4:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.7262 - F1: 0.7243
sub_14:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.6071 - F1: 0.6066
sub_9:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6667 - F1: 0.6619
sub_8:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.8095 - F1: 0.8068
sub_12:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.6071 - F1: 0.5942
sub_11:Test (Best Model) - Loss: 0.6280 - Accuracy: 0.7500 - F1: 0.7418
sub_4:Test (Best Model) - Loss: 0.6599 - Accuracy: 0.7262 - F1: 0.7258
sub_9:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6190 - F1: 0.5910
sub_8:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.8810 - F1: 0.8807
sub_11:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.7738 - F1: 0.7735
sub_8:Test (Best Model) - Loss: 0.6390 - Accuracy: 0.7857 - F1: 0.7846
sub_9:Test (Best Model) - Loss: 0.6465 - Accuracy: 0.6905 - F1: 0.6756
sub_8:Test (Best Model) - Loss: 0.7202 - Accuracy: 0.3810 - F1: 0.3778

=== Summary Results ===

acc: 65.50 ± 6.66
F1: 64.96 ± 6.82
acc-in: 70.29 ± 6.75
F1-in: 69.88 ± 6.91
