lr: 0.001
sub_1:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5119 - F1: 0.3944
sub_1:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.6786 - F1: 0.6785
sub_1:Test (Best Model) - Loss: 0.7062 - Accuracy: 0.5000 - F1: 0.4857
sub_1:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5476 - F1: 0.4708
sub_1:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5357 - F1: 0.4510
sub_1:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.6310 - F1: 0.5810
sub_1:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.6667 - F1: 0.6466
sub_1:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5595 - F1: 0.4670
sub_1:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8095 - F1: 0.8041
sub_1:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.6490 - Accuracy: 0.6429 - F1: 0.6214
sub_1:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5238 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5952 - F1: 0.5159
sub_2:Test (Best Model) - Loss: 0.4906 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 0.4997 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.5131 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.5053 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.5043 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.4972 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.4731 - Accuracy: 0.8333 - F1: 0.8330
sub_2:Test (Best Model) - Loss: 0.5012 - Accuracy: 0.8571 - F1: 0.8558
sub_2:Test (Best Model) - Loss: 0.4552 - Accuracy: 0.9048 - F1: 0.9047
sub_2:Test (Best Model) - Loss: 0.5091 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 0.5130 - Accuracy: 0.7500 - F1: 0.7491
sub_2:Test (Best Model) - Loss: 0.4996 - Accuracy: 0.7738 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 0.5372 - Accuracy: 0.7143 - F1: 0.7035
sub_2:Test (Best Model) - Loss: 0.4855 - Accuracy: 0.7857 - F1: 0.7826
sub_2:Test (Best Model) - Loss: 0.5378 - Accuracy: 0.6548 - F1: 0.6434
sub_3:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5238 - F1: 0.4734
sub_3:Test (Best Model) - Loss: 0.6968 - Accuracy: 0.4405 - F1: 0.4220
sub_3:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.6190 - F1: 0.6111
sub_3:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.6548 - F1: 0.6400
sub_3:Test (Best Model) - Loss: 0.6660 - Accuracy: 0.6190 - F1: 0.6171
sub_3:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.4762 - F1: 0.3226
sub_3:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5119 - F1: 0.4459
sub_3:Test (Best Model) - Loss: 0.7029 - Accuracy: 0.5000 - F1: 0.4954
sub_3:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5357 - F1: 0.5276
sub_3:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.5357 - F1: 0.5351
sub_3:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5357 - F1: 0.4382
sub_3:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.5952 - F1: 0.5868
sub_3:Test (Best Model) - Loss: 0.6903 - Accuracy: 0.5238 - F1: 0.4643
sub_3:Test (Best Model) - Loss: 0.6846 - Accuracy: 0.5595 - F1: 0.5544
sub_4:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6310 - F1: 0.6267
sub_4:Test (Best Model) - Loss: 0.5107 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.5004 - Accuracy: 0.7619 - F1: 0.7619
sub_4:Test (Best Model) - Loss: 0.5152 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 0.6686 - Accuracy: 0.6071 - F1: 0.5753
sub_4:Test (Best Model) - Loss: 0.6543 - Accuracy: 0.6429 - F1: 0.6050
sub_4:Test (Best Model) - Loss: 0.3744 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.4588 - Accuracy: 0.8571 - F1: 0.8564
sub_4:Test (Best Model) - Loss: 0.4378 - Accuracy: 0.8452 - F1: 0.8442
sub_4:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.7143 - F1: 0.7141
sub_4:Test (Best Model) - Loss: 0.7639 - Accuracy: 0.5119 - F1: 0.5085
sub_4:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.5833 - F1: 0.5819
sub_4:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5476 - F1: 0.5411
sub_4:Test (Best Model) - Loss: 0.7459 - Accuracy: 0.5595 - F1: 0.5580
sub_4:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5476 - F1: 0.5453
sub_5:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.5119 - F1: 0.5034
sub_5:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.4643 - F1: 0.4642
sub_5:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.4167 - F1: 0.3918
sub_5:Test (Best Model) - Loss: 0.7145 - Accuracy: 0.4405 - F1: 0.3760
sub_5:Test (Best Model) - Loss: 0.7876 - Accuracy: 0.3571 - F1: 0.3438
sub_5:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6071 - F1: 0.6057
sub_5:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5714 - F1: 0.5553
sub_5:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.6190 - F1: 0.6188
sub_5:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.6310 - F1: 0.6188
sub_5:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6310 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5238 - F1: 0.4643
sub_5:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5119 - F1: 0.4911
sub_5:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.4762 - F1: 0.4447
sub_5:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5238 - F1: 0.5170
sub_5:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.5119 - F1: 0.4557
sub_6:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.6548 - F1: 0.6361
sub_6:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.6429 - F1: 0.6111
sub_6:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.7381 - F1: 0.7357
sub_6:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.6905 - F1: 0.6905
sub_6:Test (Best Model) - Loss: 0.6574 - Accuracy: 0.6667 - F1: 0.6421
sub_6:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.6310 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.6429 - F1: 0.6050
sub_6:Test (Best Model) - Loss: 0.7405 - Accuracy: 0.6071 - F1: 0.5690
sub_6:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5952 - F1: 0.5524
sub_6:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.6071 - F1: 0.5690
sub_6:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.6667 - F1: 0.6313
sub_6:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.7024 - F1: 0.6783
sub_6:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.7143 - F1: 0.6971
sub_6:Test (Best Model) - Loss: 0.6328 - Accuracy: 0.7143 - F1: 0.7061
sub_6:Test (Best Model) - Loss: 0.6408 - Accuracy: 0.7262 - F1: 0.7079
sub_7:Test (Best Model) - Loss: 0.7207 - Accuracy: 0.5238 - F1: 0.3842
sub_7:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7173 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.4881 - F1: 0.3474
sub_7:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4762 - F1: 0.4510
sub_7:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.4762 - F1: 0.4612
sub_7:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4167 - F1: 0.4166
sub_7:Test (Best Model) - Loss: 0.6561 - Accuracy: 0.6190 - F1: 0.5852
sub_7:Test (Best Model) - Loss: 0.6463 - Accuracy: 0.6310 - F1: 0.5951
sub_7:Test (Best Model) - Loss: 0.7213 - Accuracy: 0.4048 - F1: 0.3690
sub_7:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.6310 - F1: 0.5810
sub_7:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.4524 - F1: 0.4367
sub_7:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4524 - F1: 0.4521
sub_7:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.6071 - F1: 0.5942
sub_7:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4762 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.7143 - F1: 0.6932
sub_8:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.7619 - F1: 0.7585
sub_8:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6071 - F1: 0.5354
sub_8:Test (Best Model) - Loss: 0.6604 - Accuracy: 0.5476 - F1: 0.4312
sub_8:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.6429 - F1: 0.6396
sub_8:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5357 - F1: 0.4239
sub_8:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.6429 - F1: 0.6420
sub_8:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.6786 - F1: 0.6763
sub_8:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6429 - F1: 0.6420
sub_8:Test (Best Model) - Loss: 0.5375 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 0.5774 - Accuracy: 0.7619 - F1: 0.7607
sub_8:Test (Best Model) - Loss: 0.5295 - Accuracy: 0.7500 - F1: 0.7456
sub_8:Test (Best Model) - Loss: 0.5082 - Accuracy: 0.7976 - F1: 0.7927
sub_8:Test (Best Model) - Loss: 0.5263 - Accuracy: 0.7976 - F1: 0.7927
sub_9:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5357 - F1: 0.4625
sub_9:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.6548 - F1: 0.6543
sub_9:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5476 - F1: 0.5074
sub_9:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.6071 - F1: 0.5540
sub_9:Test (Best Model) - Loss: 0.6518 - Accuracy: 0.6667 - F1: 0.6466
sub_9:Test (Best Model) - Loss: 0.7430 - Accuracy: 0.4405 - F1: 0.4103
sub_9:Test (Best Model) - Loss: 0.8198 - Accuracy: 0.4167 - F1: 0.4024
sub_9:Test (Best Model) - Loss: 0.7415 - Accuracy: 0.4286 - F1: 0.4204
sub_9:Test (Best Model) - Loss: 0.7506 - Accuracy: 0.4286 - F1: 0.3865
sub_9:Test (Best Model) - Loss: 0.7827 - Accuracy: 0.4643 - F1: 0.4549
sub_9:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5238 - F1: 0.4643
sub_9:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.4762 - F1: 0.4296
sub_9:Test (Best Model) - Loss: 0.7437 - Accuracy: 0.5595 - F1: 0.4791
sub_9:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5238 - F1: 0.4305
sub_9:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5952 - F1: 0.5709
sub_10:Test (Best Model) - Loss: 0.6467 - Accuracy: 0.6071 - F1: 0.5975
sub_10:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.7024 - F1: 0.6926
sub_10:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.6429 - F1: 0.6396
sub_10:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.5833 - F1: 0.5496
sub_10:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.6786 - F1: 0.6612
sub_10:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.5238 - F1: 0.4952
sub_10:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4762 - F1: 0.3414
sub_10:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7381 - F1: 0.7255
sub_10:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.7976 - F1: 0.7927
sub_10:Test (Best Model) - Loss: 0.7321 - Accuracy: 0.5119 - F1: 0.5113
sub_10:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5238 - F1: 0.5235
sub_10:Test (Best Model) - Loss: 0.7223 - Accuracy: 0.5119 - F1: 0.5118
sub_10:Test (Best Model) - Loss: 0.7182 - Accuracy: 0.5000 - F1: 0.4928
sub_10:Test (Best Model) - Loss: 0.7428 - Accuracy: 0.5119 - F1: 0.5113
sub_11:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6667 - F1: 0.6313
sub_11:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5238 - F1: 0.4952
sub_11:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.7738 - F1: 0.7712
sub_11:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.7976 - F1: 0.7910
sub_11:Test (Best Model) - Loss: 0.5995 - Accuracy: 0.7619 - F1: 0.7551
sub_11:Test (Best Model) - Loss: 0.7431 - Accuracy: 0.5000 - F1: 0.4700
sub_11:Test (Best Model) - Loss: 0.7810 - Accuracy: 0.4286 - F1: 0.4122
sub_11:Test (Best Model) - Loss: 0.8397 - Accuracy: 0.4286 - F1: 0.4167
sub_11:Test (Best Model) - Loss: 0.8037 - Accuracy: 0.4524 - F1: 0.4445
sub_11:Test (Best Model) - Loss: 0.8091 - Accuracy: 0.4643 - F1: 0.4466
sub_11:Test (Best Model) - Loss: 0.6766 - Accuracy: 0.6429 - F1: 0.6214
sub_11:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.6667 - F1: 0.6571
sub_11:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.6667 - F1: 0.6619
sub_11:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6905 - F1: 0.6860
sub_11:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.6905 - F1: 0.6816
sub_12:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5357 - F1: 0.5351
sub_12:Test (Best Model) - Loss: 0.7198 - Accuracy: 0.4762 - F1: 0.3583
sub_12:Test (Best Model) - Loss: 0.7141 - Accuracy: 0.4524 - F1: 0.3944
sub_12:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.3810 - F1: 0.3806
sub_12:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.5119 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.4762 - F1: 0.4735
sub_12:Test (Best Model) - Loss: 0.7372 - Accuracy: 0.5595 - F1: 0.5595
sub_12:Test (Best Model) - Loss: 0.7267 - Accuracy: 0.5714 - F1: 0.5714
sub_12:Test (Best Model) - Loss: 0.7490 - Accuracy: 0.5000 - F1: 0.4928
sub_12:Test (Best Model) - Loss: 0.7943 - Accuracy: 0.5119 - F1: 0.5113
sub_12:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5952 - F1: 0.5932
sub_12:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.6190 - F1: 0.5852
sub_12:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.5238 - F1: 0.4887
sub_12:Test (Best Model) - Loss: 0.7131 - Accuracy: 0.4286 - F1: 0.3942
sub_12:Test (Best Model) - Loss: 0.7121 - Accuracy: 0.3929 - F1: 0.2821
sub_13:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5357 - F1: 0.4822
sub_13:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.6786 - F1: 0.6571
sub_13:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6071 - F1: 0.6044
sub_13:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.6310 - F1: 0.6111
sub_13:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.6429 - F1: 0.6214
sub_13:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.7619 - F1: 0.7619
sub_13:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.7619 - F1: 0.7585
sub_13:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.6786 - F1: 0.6763
sub_13:Test (Best Model) - Loss: 0.6091 - Accuracy: 0.7262 - F1: 0.7214
sub_13:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.7024 - F1: 0.6926
sub_13:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.6786 - F1: 0.6782
sub_13:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.7143 - F1: 0.7143
sub_13:Test (Best Model) - Loss: 0.6209 - Accuracy: 0.6786 - F1: 0.6782
sub_14:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.6429 - F1: 0.5982
sub_14:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.6190 - F1: 0.6188
sub_14:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5714 - F1: 0.5508
sub_14:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.6310 - F1: 0.6284
sub_14:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.6429 - F1: 0.6354
sub_14:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.4881 - F1: 0.3947
sub_14:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.6786 - F1: 0.6680
sub_14:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.7262 - F1: 0.7258
sub_14:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6667 - F1: 0.6650
sub_14:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.7500 - F1: 0.7497
sub_14:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.6310 - F1: 0.6245
sub_14:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.5476 - F1: 0.4815
sub_14:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5476 - F1: 0.5204
sub_14:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5000 - F1: 0.3534
sub_14:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6667 - F1: 0.6619

=== Summary Results ===

acc: 61.17 ± 8.79
F1: 58.26 ± 10.11
acc-in: 68.97 ± 7.80
F1-in: 65.75 ± 9.90
