lr: 1e-06
sub_2:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5238 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5238 - F1: 0.3842
sub_2:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6071 - F1: 0.6003
sub_3:Test (Best Model) - Loss: 0.6570 - Accuracy: 0.8333 - F1: 0.8309
sub_1:Test (Best Model) - Loss: 0.7362 - Accuracy: 0.4881 - F1: 0.3280
sub_3:Test (Best Model) - Loss: 0.7632 - Accuracy: 0.3571 - F1: 0.2632
sub_2:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5833 - F1: 0.5073
sub_1:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.7670 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.4524 - F1: 0.3292
sub_3:Test (Best Model) - Loss: 0.7956 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.7619 - F1: 0.7597
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3713
sub_1:Test (Best Model) - Loss: 0.7242 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.5960 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5000 - F1: 0.4700
sub_1:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.7738 - F1: 0.7738
sub_2:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5119 - F1: 0.3944
sub_3:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.5000 - F1: 0.4759
sub_2:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.8333 - F1: 0.8318
sub_3:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5714 - F1: 0.4875
sub_2:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.5238 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.6786 - F1: 0.6730
sub_3:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4762 - F1: 0.3873
sub_2:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.6905 - F1: 0.6840
sub_1:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.6667 - F1: 0.6667
sub_2:Test (Best Model) - Loss: 0.7419 - Accuracy: 0.6667 - F1: 0.6466
sub_1:Test (Best Model) - Loss: 0.7564 - Accuracy: 0.6310 - F1: 0.6063
sub_3:Test (Best Model) - Loss: 0.8355 - Accuracy: 0.7381 - F1: 0.7357
sub_2:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.8214 - F1: 0.8212
sub_1:Test (Best Model) - Loss: 0.8029 - Accuracy: 0.6667 - F1: 0.6370
sub_3:Test (Best Model) - Loss: 0.7700 - Accuracy: 0.5000 - F1: 0.4470
sub_2:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6667 - F1: 0.6313
sub_1:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.8603 - Accuracy: 0.5119 - F1: 0.4349
sub_2:Test (Best Model) - Loss: 0.9737 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.6310 - F1: 0.5728
sub_5:Test (Best Model) - Loss: 0.8122 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6786 - F1: 0.6748
sub_6:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.4405 - F1: 0.3861
sub_5:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.3929 - F1: 0.2971
sub_4:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6667 - F1: 0.6506
sub_6:Test (Best Model) - Loss: 0.7170 - Accuracy: 0.4286 - F1: 0.3680
sub_4:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.6310 - F1: 0.6219
sub_5:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.5833 - F1: 0.5176
sub_5:Test (Best Model) - Loss: 0.7887 - Accuracy: 0.4762 - F1: 0.3226
sub_6:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5952 - F1: 0.5943
sub_4:Test (Best Model) - Loss: 0.7514 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.7738 - Accuracy: 0.6190 - F1: 0.5787
sub_5:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.6190 - F1: 0.6136
sub_6:Test (Best Model) - Loss: 0.6531 - Accuracy: 0.6667 - F1: 0.6313
sub_4:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4881 - F1: 0.3474
sub_5:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5595 - F1: 0.4535
sub_6:Test (Best Model) - Loss: 0.7520 - Accuracy: 0.4524 - F1: 0.3115
sub_4:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5595 - F1: 0.5544
sub_5:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.7024 - F1: 0.6897
sub_6:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.7024 - F1: 0.7013
sub_4:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4881 - F1: 0.3474
sub_6:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.4881 - F1: 0.3280
sub_4:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5238 - F1: 0.5102
sub_4:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4762 - F1: 0.3226
sub_5:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5476 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.4881 - F1: 0.4540
sub_5:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.5000 - F1: 0.4470
sub_4:Test (Best Model) - Loss: 0.6887 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6735 - Accuracy: 0.5833 - F1: 0.5428
sub_5:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.6786 - F1: 0.6648
sub_4:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.6071 - F1: 0.5860
sub_5:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.7619 - F1: 0.7618
sub_4:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6667 - F1: 0.6659
sub_6:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.5000 - F1: 0.4954
sub_5:Test (Best Model) - Loss: 0.7339 - Accuracy: 0.3929 - F1: 0.3780
sub_4:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5476 - F1: 0.4815
sub_5:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.5476 - F1: 0.4815
sub_4:Test (Best Model) - Loss: 0.7393 - Accuracy: 0.5476 - F1: 0.4815
sub_6:Test (Best Model) - Loss: 8.9584 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.5119 - F1: 0.3778
sub_7:Test (Best Model) - Loss: 0.7258 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5238 - F1: 0.3842
sub_9:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.7024 - F1: 0.6972
sub_8:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.5833 - F1: 0.5073
sub_7:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4405 - F1: 0.3523
sub_7:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.5357 - F1: 0.4382
sub_7:Test (Best Model) - Loss: 0.7424 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.6190 - F1: 0.6188
sub_8:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.9048 - F1: 0.9047
sub_9:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.6905 - F1: 0.6630
sub_7:Test (Best Model) - Loss: 0.7008 - Accuracy: 0.5357 - F1: 0.4081
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5000 - F1: 0.4812
sub_9:Test (Best Model) - Loss: 0.7263 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.8929 - F1: 0.8927
sub_9:Test (Best Model) - Loss: 0.7084 - Accuracy: 0.5119 - F1: 0.3778
sub_7:Test (Best Model) - Loss: 0.7215 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5119 - F1: 0.3593
sub_7:Test (Best Model) - Loss: 0.7124 - Accuracy: 0.5000 - F1: 0.3713
sub_8:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.8452 - F1: 0.8442
sub_7:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5000 - F1: 0.4470
sub_9:Test (Best Model) - Loss: 0.5985 - Accuracy: 0.9286 - F1: 0.9284
sub_7:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5357 - F1: 0.5107
sub_7:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5238 - F1: 0.5009
sub_7:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.4762 - F1: 0.3414
sub_9:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.5000 - F1: 0.3534
sub_8:Test (Best Model) - Loss: 0.6165 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.6291 - Accuracy: 0.7024 - F1: 0.6972
sub_9:Test (Best Model) - Loss: 0.7540 - Accuracy: 0.5238 - F1: 0.3842
sub_9:Test (Best Model) - Loss: 0.7645 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.7857 - F1: 0.7754
sub_9:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6786 - F1: 0.6473
sub_8:Test (Best Model) - Loss: 0.6406 - Accuracy: 0.8214 - F1: 0.8183
sub_9:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.6136 - Accuracy: 0.7500 - F1: 0.7393
sub_8:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.8333 - F1: 0.8325
sub_9:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4762 - F1: 0.4207
sub_8:Test (Best Model) - Loss: 0.5622 - Accuracy: 0.7143 - F1: 0.6889
sub_8:Test (Best Model) - Loss: 0.6421 - Accuracy: 0.6548 - F1: 0.6150
sub_9:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7143 - F1: 0.7035
sub_8:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5238 - F1: 0.3842
sub_9:Test (Best Model) - Loss: 1.1993 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.5238 - F1: 0.3842
sub_11:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7186 - Accuracy: 0.5119 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.6190 - F1: 0.6047
sub_10:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6786 - F1: 0.6782
sub_12:Test (Best Model) - Loss: 0.7014 - Accuracy: 0.4167 - F1: 0.3694
sub_12:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.6310 - F1: 0.6188
sub_11:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.8333 - F1: 0.8332
sub_12:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6429 - F1: 0.6410
sub_12:Test (Best Model) - Loss: 0.7324 - Accuracy: 0.3333 - F1: 0.3272
sub_10:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.5357 - F1: 0.4729
sub_12:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.5238 - F1: 0.4430
sub_10:Test (Best Model) - Loss: 0.7558 - Accuracy: 0.4881 - F1: 0.3280
sub_11:Test (Best Model) - Loss: 0.6703 - Accuracy: 0.6905 - F1: 0.6677
sub_10:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6548 - F1: 0.6212
sub_12:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5714 - F1: 0.5625
sub_11:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6548 - F1: 0.6080
sub_12:Test (Best Model) - Loss: 0.7150 - Accuracy: 0.6190 - F1: 0.5544
sub_11:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.6190 - F1: 0.5634
sub_12:Test (Best Model) - Loss: 0.7505 - Accuracy: 0.3810 - F1: 0.2904
sub_11:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.7143 - F1: 0.7083
sub_11:Test (Best Model) - Loss: 0.7255 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6667 - F1: 0.6636
sub_12:Test (Best Model) - Loss: 0.9462 - Accuracy: 0.4881 - F1: 0.3280
sub_11:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.8214 - F1: 0.8170
sub_10:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5833 - F1: 0.4958
sub_12:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.5714 - F1: 0.4750
sub_12:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.3095 - F1: 0.2951
sub_11:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.6429 - F1: 0.6166
sub_12:Test (Best Model) - Loss: 0.9887 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.5357 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.6544 - Accuracy: 0.8929 - F1: 0.8928
sub_10:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.8095 - F1: 0.8056
sub_11:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.7619 - F1: 0.7619
sub_10:Test (Best Model) - Loss: 0.6585 - Accuracy: 0.7024 - F1: 0.6783
sub_10:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.7775 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6786 - F1: 0.6680
sub_11:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5714 - F1: 0.4987
sub_11:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.5119 - F1: 0.3593
sub_13:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.7619 - F1: 0.7476
sub_13:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5595 - F1: 0.5518
sub_13:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4881 - F1: 0.3280
sub_14:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.5595 - F1: 0.4791
sub_13:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.7976 - F1: 0.7974
sub_13:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6878 - Accuracy: 0.6548 - F1: 0.6361
sub_14:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4762 - F1: 0.3414
sub_13:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.7738 - F1: 0.7722
sub_13:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.7619 - F1: 0.7607
sub_13:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6786 - F1: 0.6707
sub_14:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.5714 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5952 - F1: 0.5159
sub_13:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.6429 - F1: 0.6166
sub_13:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.7500 - F1: 0.7439
sub_14:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.5476 - F1: 0.4312
sub_14:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5357 - F1: 0.4906
sub_13:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.6429 - F1: 0.6420
sub_13:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.7024 - F1: 0.6951
sub_14:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.8214 - F1: 0.8183
sub_13:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.5000 - F1: 0.3333

=== Summary Results ===

acc: 59.19 ± 5.76
F1: 51.74 ± 6.57
acc-in: 63.37 ± 7.12
F1-in: 56.95 ± 8.14
runing time: 1095.42 seconds
