lr: 1e-05
sub_2:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.5476 - F1: 0.4458
sub_1:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.7381 - F1: 0.7306
sub_3:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.5952 - F1: 0.5361
sub_1:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.6905 - F1: 0.6898
sub_3:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6140 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5238 - F1: 0.4013
sub_3:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.5869 - Accuracy: 0.7381 - F1: 0.7306
sub_2:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5476 - F1: 0.4312
sub_1:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.7143 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.5238 - F1: 0.3842
sub_3:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6667 - F1: 0.6541
sub_1:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.8929 - F1: 0.8928
sub_2:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.6781 - Accuracy: 0.6071 - F1: 0.5452
sub_1:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5595 - F1: 0.4535
sub_2:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.5476 - F1: 0.4312
sub_1:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.9048 - F1: 0.9045
sub_3:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.4881 - F1: 0.3806
sub_2:Test (Best Model) - Loss: 0.6576 - Accuracy: 0.7500 - F1: 0.7333
sub_3:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.6046 - Accuracy: 0.8929 - F1: 0.8925
sub_3:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5238 - F1: 0.4887
sub_1:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.6667 - F1: 0.6370
sub_3:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.5119 - F1: 0.4459
sub_1:Test (Best Model) - Loss: 0.5887 - Accuracy: 0.7738 - F1: 0.7738
sub_3:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.8204 - Accuracy: 0.5238 - F1: 0.5195
sub_3:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5476 - F1: 0.4312
sub_1:Test (Best Model) - Loss: 0.5342 - Accuracy: 0.6786 - F1: 0.6730
sub_2:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.6310 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.5833 - F1: 0.5828
sub_1:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.6667 - F1: 0.6571
sub_1:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.7024 - F1: 0.6863
sub_2:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6548 - F1: 0.6080
sub_1:Test (Best Model) - Loss: 0.5369 - Accuracy: 0.6786 - F1: 0.6648
sub_5:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.7143 - F1: 0.7035
sub_5:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.5714 - F1: 0.5260
sub_6:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.6667 - F1: 0.6250
sub_5:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.7746 - Accuracy: 0.6786 - F1: 0.6774
sub_6:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.5595 - F1: 0.4535
sub_5:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.6548 - F1: 0.6361
sub_5:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.5595 - F1: 0.4535
sub_6:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.6429 - F1: 0.5906
sub_4:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.5357 - F1: 0.4081
sub_5:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.5119 - F1: 0.3593
sub_6:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.6667 - F1: 0.6313
sub_4:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.6905 - F1: 0.6876
sub_5:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.5595 - F1: 0.4535
sub_6:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.6190 - F1: 0.5544
sub_5:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.5714 - F1: 0.4750
sub_4:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.6190 - F1: 0.5544
sub_6:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5119 - F1: 0.3593
sub_5:Test (Best Model) - Loss: 0.6449 - Accuracy: 0.6548 - F1: 0.6080
sub_4:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.5476 - F1: 0.4312
sub_4:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5714 - F1: 0.4750
sub_6:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7500 - F1: 0.7365
sub_5:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6310 - F1: 0.6245
sub_6:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.8929 - F1: 0.8928
sub_4:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6905 - F1: 0.6577
sub_5:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.5238 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7024 - F1: 0.6783
sub_5:Test (Best Model) - Loss: 0.6771 - Accuracy: 0.5238 - F1: 0.3842
sub_6:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.6711 - Accuracy: 0.4762 - F1: 0.3736
sub_4:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.7738 - F1: 0.7699
sub_5:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.4762 - F1: 0.4376
sub_4:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.7309 - Accuracy: 0.4524 - F1: 0.4037
sub_4:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6190 - F1: 0.5910
sub_6:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.4524 - F1: 0.3944
sub_6:Test (Best Model) - Loss: 0.7359 - Accuracy: 0.5119 - F1: 0.4794
sub_4:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.7857 - F1: 0.7856
sub_6:Test (Best Model) - Loss: 0.7706 - Accuracy: 0.4762 - F1: 0.3736
sub_4:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.7619 - F1: 0.7618
sub_8:Test (Best Model) - Loss: 0.6261 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.6270 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.7976 - F1: 0.7910
sub_9:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6768 - Accuracy: 0.7738 - F1: 0.7699
sub_9:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.6667 - F1: 0.6650
sub_8:Test (Best Model) - Loss: 0.5019 - Accuracy: 0.8929 - F1: 0.8921
sub_7:Test (Best Model) - Loss: 0.6689 - Accuracy: 0.6071 - F1: 0.5354
sub_8:Test (Best Model) - Loss: 0.5796 - Accuracy: 0.8333 - F1: 0.8299
sub_9:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6222 - Accuracy: 0.8810 - F1: 0.8809
sub_9:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.7381 - F1: 0.7282
sub_7:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.6310 - F1: 0.5728
sub_9:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.5238 - F1: 0.4013
sub_8:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.5595 - F1: 0.4535
sub_8:Test (Best Model) - Loss: 0.6114 - Accuracy: 0.6905 - F1: 0.6577
sub_7:Test (Best Model) - Loss: 0.6775 - Accuracy: 0.6786 - F1: 0.6612
sub_8:Test (Best Model) - Loss: 0.5708 - Accuracy: 0.9048 - F1: 0.9039
sub_7:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.5833 - F1: 0.5176
sub_7:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.6071 - F1: 0.5354
sub_8:Test (Best Model) - Loss: 0.5895 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.6048 - Accuracy: 0.7857 - F1: 0.7838
sub_7:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.5833 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.8690 - F1: 0.8668
sub_7:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5833 - F1: 0.4958
sub_8:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.8095 - F1: 0.8056
sub_9:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.4167 - F1: 0.3918
sub_7:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.5357 - F1: 0.4906
sub_8:Test (Best Model) - Loss: 0.5244 - Accuracy: 0.8095 - F1: 0.8078
sub_9:Test (Best Model) - Loss: 0.8106 - Accuracy: 0.2619 - F1: 0.2615
sub_7:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6378 - Accuracy: 0.8810 - F1: 0.8809
sub_9:Test (Best Model) - Loss: 0.7358 - Accuracy: 0.3929 - F1: 0.2821
sub_7:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.5714 - F1: 0.4875
sub_7:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.3333 - F1: 0.3299
sub_7:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.5585 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.7221 - Accuracy: 0.3571 - F1: 0.3568
sub_11:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.6190 - F1: 0.5852
sub_12:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6667 - F1: 0.6571
sub_10:Test (Best Model) - Loss: 0.5588 - Accuracy: 0.6429 - F1: 0.5982
sub_11:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.7500 - F1: 0.7500
sub_12:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.7500 - F1: 0.7497
sub_10:Test (Best Model) - Loss: 0.5951 - Accuracy: 0.6548 - F1: 0.6212
sub_11:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6071 - F1: 0.5690
sub_12:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5476 - F1: 0.4590
sub_10:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.5952 - F1: 0.5361
sub_12:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.5833 - F1: 0.5270
sub_11:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.5952 - F1: 0.5265
sub_10:Test (Best Model) - Loss: 0.5749 - Accuracy: 0.6548 - F1: 0.6268
sub_12:Test (Best Model) - Loss: 0.6480 - Accuracy: 0.6429 - F1: 0.6294
sub_11:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6429 - F1: 0.6166
sub_11:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.5833 - F1: 0.4958
sub_10:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.7500 - F1: 0.7418
sub_12:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.7143 - F1: 0.7035
sub_11:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.7262 - F1: 0.7040
sub_12:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.5238 - F1: 0.4013
sub_10:Test (Best Model) - Loss: 0.6057 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6905 - F1: 0.6677
sub_10:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7262 - F1: 0.7040
sub_10:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7857 - F1: 0.7796
sub_12:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.7262 - F1: 0.7114
sub_11:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.6125 - Accuracy: 0.7619 - F1: 0.7569
sub_12:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.5952 - F1: 0.5446
sub_11:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.5238 - F1: 0.3842
sub_10:Test (Best Model) - Loss: 0.6341 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.5017 - Accuracy: 0.8095 - F1: 0.8078
sub_11:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.4881 - F1: 0.4880
sub_10:Test (Best Model) - Loss: 0.6563 - Accuracy: 0.7262 - F1: 0.7040
sub_10:Test (Best Model) - Loss: 0.6554 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.4716 - Accuracy: 0.8810 - F1: 0.8807
sub_11:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.4405 - F1: 0.4032
sub_10:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.6190 - F1: 0.5544
sub_12:Test (Best Model) - Loss: 0.5713 - Accuracy: 0.8452 - F1: 0.8452
sub_11:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.4643 - F1: 0.4549
sub_12:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.5476 - F1: 0.4312
sub_11:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.4524 - F1: 0.4496
sub_10:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6667 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 0.6313 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.4762 - F1: 0.4376
sub_14:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.6548 - F1: 0.6150
sub_13:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6268 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.6266 - Accuracy: 0.7619 - F1: 0.7569
sub_13:Test (Best Model) - Loss: 0.5525 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.7857 - F1: 0.7796
sub_14:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.7857 - F1: 0.7776
sub_13:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.6310 - F1: 0.5728
sub_13:Test (Best Model) - Loss: 0.6069 - Accuracy: 0.8690 - F1: 0.8689
sub_14:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.4807 - Accuracy: 0.8214 - F1: 0.8183
sub_14:Test (Best Model) - Loss: 0.6462 - Accuracy: 0.7976 - F1: 0.7910
sub_13:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.8571 - F1: 0.8558
sub_14:Test (Best Model) - Loss: 0.6506 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.6208 - Accuracy: 0.8690 - F1: 0.8675
sub_13:Test (Best Model) - Loss: 0.6050 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.5595 - F1: 0.4791
sub_13:Test (Best Model) - Loss: 0.5481 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.5000 - F1: 0.3534
sub_13:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.7738 - F1: 0.7641
sub_14:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.5595 - F1: 0.4791
sub_13:Test (Best Model) - Loss: 0.5613 - Accuracy: 0.8333 - F1: 0.8299
sub_14:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.5238 - F1: 0.4167
sub_14:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.5119 - F1: 0.3778
sub_13:Test (Best Model) - Loss: 0.5282 - Accuracy: 0.8690 - F1: 0.8675
sub_13:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.7857 - F1: 0.7776

=== Summary Results ===

acc: 65.09 ± 10.05
F1: 59.80 ± 13.02
acc-in: 76.04 ± 6.90
F1-in: 74.24 ± 8.04
runing time: 1114.19 seconds
