lr: 0.0001
sub_1:Test (Best Model) - Loss: 3.0999 - Accuracy: 0.7143 - F1: 0.6971
sub_1:Test (Best Model) - Loss: 4.0895 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 2.9015 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 2.7588 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 2.6963 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 2.0707 - Accuracy: 0.7500 - F1: 0.7418
sub_1:Test (Best Model) - Loss: 1.1843 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.7619 - F1: 0.7597
sub_1:Test (Best Model) - Loss: 1.1439 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 1.0687 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 1.5116 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 1.0527 - Accuracy: 0.8095 - F1: 0.8024
sub_1:Test (Best Model) - Loss: 1.2773 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.9313 - Accuracy: 0.7500 - F1: 0.7333
sub_1:Test (Best Model) - Loss: 1.8261 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 1.2891 - Accuracy: 0.6905 - F1: 0.6905
sub_2:Test (Best Model) - Loss: 0.8527 - Accuracy: 0.6905 - F1: 0.6903
sub_2:Test (Best Model) - Loss: 1.0543 - Accuracy: 0.6786 - F1: 0.6774
sub_2:Test (Best Model) - Loss: 0.8545 - Accuracy: 0.7976 - F1: 0.7962
sub_2:Test (Best Model) - Loss: 1.0302 - Accuracy: 0.6905 - F1: 0.6719
sub_2:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.7976 - F1: 0.7927
sub_2:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.7381 - F1: 0.7326
sub_2:Test (Best Model) - Loss: 0.4727 - Accuracy: 0.8333 - F1: 0.8325
sub_2:Test (Best Model) - Loss: 0.5968 - Accuracy: 0.7976 - F1: 0.7941
sub_2:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.8818 - Accuracy: 0.8214 - F1: 0.8212
sub_2:Test (Best Model) - Loss: 0.8750 - Accuracy: 0.8214 - F1: 0.8214
sub_2:Test (Best Model) - Loss: 0.5042 - Accuracy: 0.8333 - F1: 0.8318
sub_2:Test (Best Model) - Loss: 0.6190 - Accuracy: 0.8571 - F1: 0.8571
sub_2:Test (Best Model) - Loss: 0.8546 - Accuracy: 0.7738 - F1: 0.7730
sub_3:Test (Best Model) - Loss: 2.6115 - Accuracy: 0.5238 - F1: 0.4542
sub_3:Test (Best Model) - Loss: 2.6943 - Accuracy: 0.5476 - F1: 0.4458
sub_3:Test (Best Model) - Loss: 2.8375 - Accuracy: 0.5833 - F1: 0.5073
sub_3:Test (Best Model) - Loss: 2.3584 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 3.9090 - Accuracy: 0.5357 - F1: 0.4081
sub_3:Test (Best Model) - Loss: 1.2227 - Accuracy: 0.7143 - F1: 0.7102
sub_3:Test (Best Model) - Loss: 1.3905 - Accuracy: 0.7024 - F1: 0.7003
sub_3:Test (Best Model) - Loss: 1.4818 - Accuracy: 0.6667 - F1: 0.6667
sub_3:Test (Best Model) - Loss: 1.7049 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 1.0880 - Accuracy: 0.7262 - F1: 0.7230
sub_3:Test (Best Model) - Loss: 2.1361 - Accuracy: 0.7143 - F1: 0.6932
sub_3:Test (Best Model) - Loss: 2.8333 - Accuracy: 0.7024 - F1: 0.6783
sub_3:Test (Best Model) - Loss: 2.1073 - Accuracy: 0.6786 - F1: 0.6415
sub_3:Test (Best Model) - Loss: 1.6608 - Accuracy: 0.6548 - F1: 0.6268
sub_3:Test (Best Model) - Loss: 2.1995 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 1.1751 - Accuracy: 0.7619 - F1: 0.7614
sub_4:Test (Best Model) - Loss: 1.6507 - Accuracy: 0.6310 - F1: 0.6309
sub_4:Test (Best Model) - Loss: 1.6975 - Accuracy: 0.6905 - F1: 0.6876
sub_4:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.6310 - F1: 0.6267
sub_4:Test (Best Model) - Loss: 1.4063 - Accuracy: 0.6786 - F1: 0.6730
sub_4:Test (Best Model) - Loss: 1.6879 - Accuracy: 0.7143 - F1: 0.7141
sub_4:Test (Best Model) - Loss: 0.9663 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 0.8827 - Accuracy: 0.7738 - F1: 0.7699
sub_4:Test (Best Model) - Loss: 0.9658 - Accuracy: 0.7381 - F1: 0.7326
sub_4:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.7619 - F1: 0.7614
sub_4:Test (Best Model) - Loss: 0.8723 - Accuracy: 0.7262 - F1: 0.7214
sub_4:Test (Best Model) - Loss: 1.0547 - Accuracy: 0.7262 - F1: 0.7258
sub_4:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.7262 - F1: 0.7214
sub_4:Test (Best Model) - Loss: 0.8444 - Accuracy: 0.7381 - F1: 0.7368
sub_4:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.8214 - F1: 0.8214
sub_5:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.8690 - F1: 0.8686
sub_5:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.7857 - F1: 0.7838
sub_5:Test (Best Model) - Loss: 0.3490 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 1.1521 - Accuracy: 0.7024 - F1: 0.6825
sub_5:Test (Best Model) - Loss: 0.5055 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.8510 - Accuracy: 0.7976 - F1: 0.7969
sub_5:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.8690 - F1: 0.8690
sub_5:Test (Best Model) - Loss: 0.4609 - Accuracy: 0.8333 - F1: 0.8330
sub_5:Test (Best Model) - Loss: 1.1321 - Accuracy: 0.7143 - F1: 0.7005
sub_5:Test (Best Model) - Loss: 0.4025 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 0.7869 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 1.1476 - Accuracy: 0.7619 - F1: 0.7619
sub_5:Test (Best Model) - Loss: 0.5241 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 0.8299 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 0.5709 - Accuracy: 0.8214 - F1: 0.8208
sub_6:Test (Best Model) - Loss: 1.6355 - Accuracy: 0.6071 - F1: 0.6071
sub_6:Test (Best Model) - Loss: 1.5192 - Accuracy: 0.6190 - F1: 0.6136
sub_6:Test (Best Model) - Loss: 1.7559 - Accuracy: 0.5595 - F1: 0.5590
sub_6:Test (Best Model) - Loss: 2.1494 - Accuracy: 0.6071 - F1: 0.6003
sub_6:Test (Best Model) - Loss: 1.3563 - Accuracy: 0.6310 - F1: 0.6284
sub_6:Test (Best Model) - Loss: 1.4966 - Accuracy: 0.6905 - F1: 0.6860
sub_6:Test (Best Model) - Loss: 2.5174 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 1.4754 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 1.3039 - Accuracy: 0.6310 - F1: 0.6296
sub_6:Test (Best Model) - Loss: 1.3719 - Accuracy: 0.6786 - F1: 0.6763
sub_6:Test (Best Model) - Loss: 1.5101 - Accuracy: 0.6786 - F1: 0.6785
sub_6:Test (Best Model) - Loss: 1.2715 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 0.8200 - Accuracy: 0.6905 - F1: 0.6905
sub_6:Test (Best Model) - Loss: 1.4304 - Accuracy: 0.6190 - F1: 0.6082
sub_6:Test (Best Model) - Loss: 1.0182 - Accuracy: 0.6667 - F1: 0.6659
sub_7:Test (Best Model) - Loss: 1.7970 - Accuracy: 0.6548 - F1: 0.6361
sub_7:Test (Best Model) - Loss: 1.8701 - Accuracy: 0.6310 - F1: 0.6296
sub_7:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.6786 - F1: 0.6648
sub_7:Test (Best Model) - Loss: 1.5655 - Accuracy: 0.6548 - F1: 0.6543
sub_7:Test (Best Model) - Loss: 1.8214 - Accuracy: 0.6190 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 1.0037 - Accuracy: 0.6905 - F1: 0.6876
sub_7:Test (Best Model) - Loss: 1.3846 - Accuracy: 0.5952 - F1: 0.5915
sub_7:Test (Best Model) - Loss: 1.0586 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 1.5695 - Accuracy: 0.6310 - F1: 0.6284
sub_7:Test (Best Model) - Loss: 0.8890 - Accuracy: 0.6310 - F1: 0.6152
sub_7:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.6190 - F1: 0.6182
sub_7:Test (Best Model) - Loss: 1.7902 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 1.2218 - Accuracy: 0.6190 - F1: 0.6156
sub_7:Test (Best Model) - Loss: 1.3845 - Accuracy: 0.6548 - F1: 0.6463
sub_7:Test (Best Model) - Loss: 1.3009 - Accuracy: 0.6190 - F1: 0.6182
sub_8:Test (Best Model) - Loss: 1.0820 - Accuracy: 0.7857 - F1: 0.7846
sub_8:Test (Best Model) - Loss: 1.0843 - Accuracy: 0.7857 - F1: 0.7857
sub_8:Test (Best Model) - Loss: 1.4772 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 1.0250 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 1.0498 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 0.7209 - Accuracy: 0.8690 - F1: 0.8675
sub_8:Test (Best Model) - Loss: 0.5067 - Accuracy: 0.8810 - F1: 0.8807
sub_8:Test (Best Model) - Loss: 0.6760 - Accuracy: 0.8690 - F1: 0.8681
sub_8:Test (Best Model) - Loss: 1.1359 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.8338 - Accuracy: 0.7976 - F1: 0.7974
sub_8:Test (Best Model) - Loss: 0.2594 - Accuracy: 0.8690 - F1: 0.8675
sub_8:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.8333 - F1: 0.8286
sub_8:Test (Best Model) - Loss: 0.4195 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.5547 - Accuracy: 0.8571 - F1: 0.8564
sub_8:Test (Best Model) - Loss: 0.4286 - Accuracy: 0.8810 - F1: 0.8799
sub_9:Test (Best Model) - Loss: 1.2136 - Accuracy: 0.7143 - F1: 0.6971
sub_9:Test (Best Model) - Loss: 1.4306 - Accuracy: 0.7024 - F1: 0.6897
sub_9:Test (Best Model) - Loss: 0.9148 - Accuracy: 0.8095 - F1: 0.8094
sub_9:Test (Best Model) - Loss: 1.3080 - Accuracy: 0.6667 - F1: 0.6541
sub_9:Test (Best Model) - Loss: 1.5507 - Accuracy: 0.6905 - F1: 0.6788
sub_9:Test (Best Model) - Loss: 1.0703 - Accuracy: 0.7381 - F1: 0.7368
sub_9:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.7262 - F1: 0.7214
sub_9:Test (Best Model) - Loss: 1.0575 - Accuracy: 0.6786 - F1: 0.6782
sub_9:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.7738 - F1: 0.7735
sub_9:Test (Best Model) - Loss: 0.7201 - Accuracy: 0.7381 - F1: 0.7379
sub_9:Test (Best Model) - Loss: 1.5833 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.6786 - F1: 0.6473
sub_9:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.7976 - F1: 0.7910
sub_9:Test (Best Model) - Loss: 1.3493 - Accuracy: 0.7381 - F1: 0.7188
sub_9:Test (Best Model) - Loss: 1.5093 - Accuracy: 0.7500 - F1: 0.7333
sub_10:Test (Best Model) - Loss: 1.0766 - Accuracy: 0.6548 - F1: 0.6543
sub_10:Test (Best Model) - Loss: 1.0130 - Accuracy: 0.7262 - F1: 0.7243
sub_10:Test (Best Model) - Loss: 1.2049 - Accuracy: 0.6429 - F1: 0.6166
sub_10:Test (Best Model) - Loss: 1.2330 - Accuracy: 0.6786 - F1: 0.6730
sub_10:Test (Best Model) - Loss: 1.1377 - Accuracy: 0.6786 - F1: 0.6748
sub_10:Test (Best Model) - Loss: 1.2794 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 1.4036 - Accuracy: 0.6548 - F1: 0.6434
sub_10:Test (Best Model) - Loss: 1.5670 - Accuracy: 0.6190 - F1: 0.6188
sub_10:Test (Best Model) - Loss: 1.3611 - Accuracy: 0.5714 - F1: 0.5675
sub_10:Test (Best Model) - Loss: 1.4087 - Accuracy: 0.6786 - F1: 0.6763
sub_10:Test (Best Model) - Loss: 0.8940 - Accuracy: 0.7500 - F1: 0.7497
sub_10:Test (Best Model) - Loss: 0.9904 - Accuracy: 0.7143 - F1: 0.7102
sub_10:Test (Best Model) - Loss: 1.0699 - Accuracy: 0.7024 - F1: 0.7023
sub_10:Test (Best Model) - Loss: 1.2722 - Accuracy: 0.7143 - F1: 0.7136
sub_10:Test (Best Model) - Loss: 0.8022 - Accuracy: 0.7143 - F1: 0.7136
sub_11:Test (Best Model) - Loss: 1.3860 - Accuracy: 0.6310 - F1: 0.6284
sub_11:Test (Best Model) - Loss: 1.4777 - Accuracy: 0.6548 - F1: 0.6535
sub_11:Test (Best Model) - Loss: 1.2039 - Accuracy: 0.5833 - F1: 0.5819
sub_11:Test (Best Model) - Loss: 1.6769 - Accuracy: 0.6190 - F1: 0.6111
sub_11:Test (Best Model) - Loss: 1.2173 - Accuracy: 0.7143 - F1: 0.7061
sub_11:Test (Best Model) - Loss: 0.8370 - Accuracy: 0.6786 - F1: 0.6774
sub_11:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.7500 - F1: 0.7497
sub_11:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.8333 - F1: 0.8330
sub_11:Test (Best Model) - Loss: 0.7436 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 0.7873 - Accuracy: 0.7738 - F1: 0.7738
sub_11:Test (Best Model) - Loss: 0.8565 - Accuracy: 0.7381 - F1: 0.7368
sub_11:Test (Best Model) - Loss: 1.0959 - Accuracy: 0.7143 - F1: 0.7117
sub_11:Test (Best Model) - Loss: 0.7739 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.8797 - Accuracy: 0.7976 - F1: 0.7962
sub_11:Test (Best Model) - Loss: 1.2924 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 0.5770 - Accuracy: 0.8095 - F1: 0.8095
sub_12:Test (Best Model) - Loss: 0.3817 - Accuracy: 0.8333 - F1: 0.8330
sub_12:Test (Best Model) - Loss: 0.4364 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.6478 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 0.3403 - Accuracy: 0.8810 - F1: 0.8810
sub_12:Test (Best Model) - Loss: 2.2889 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 1.9290 - Accuracy: 0.7143 - F1: 0.7005
sub_12:Test (Best Model) - Loss: 2.1882 - Accuracy: 0.7381 - F1: 0.7224
sub_12:Test (Best Model) - Loss: 2.2419 - Accuracy: 0.7500 - F1: 0.7365
sub_12:Test (Best Model) - Loss: 1.8716 - Accuracy: 0.7143 - F1: 0.6971
sub_12:Test (Best Model) - Loss: 1.8414 - Accuracy: 0.6786 - F1: 0.6571
sub_12:Test (Best Model) - Loss: 1.0411 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 0.7339 - Accuracy: 0.7976 - F1: 0.7941
sub_12:Test (Best Model) - Loss: 1.1028 - Accuracy: 0.8095 - F1: 0.8078
sub_12:Test (Best Model) - Loss: 1.2098 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 0.7336 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.9418 - Accuracy: 0.7143 - F1: 0.7128
sub_13:Test (Best Model) - Loss: 1.1866 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.8911 - Accuracy: 0.7619 - F1: 0.7607
sub_13:Test (Best Model) - Loss: 0.9486 - Accuracy: 0.7619 - F1: 0.7597
sub_13:Test (Best Model) - Loss: 1.1497 - Accuracy: 0.7024 - F1: 0.7023
sub_13:Test (Best Model) - Loss: 0.8864 - Accuracy: 0.7619 - F1: 0.7607
sub_13:Test (Best Model) - Loss: 1.2976 - Accuracy: 0.7143 - F1: 0.7035
sub_13:Test (Best Model) - Loss: 0.8771 - Accuracy: 0.7738 - F1: 0.7738
sub_13:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.7619 - F1: 0.7607
sub_13:Test (Best Model) - Loss: 0.8727 - Accuracy: 0.7619 - F1: 0.7614
sub_13:Test (Best Model) - Loss: 0.8771 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 0.7750 - Accuracy: 0.7976 - F1: 0.7941
sub_13:Test (Best Model) - Loss: 0.5589 - Accuracy: 0.8333 - F1: 0.8318
sub_13:Test (Best Model) - Loss: 0.9382 - Accuracy: 0.7500 - F1: 0.7418
sub_14:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.9466 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.7669 - Accuracy: 0.8095 - F1: 0.8094
sub_14:Test (Best Model) - Loss: 0.7607 - Accuracy: 0.8214 - F1: 0.8214
sub_14:Test (Best Model) - Loss: 0.7689 - Accuracy: 0.7857 - F1: 0.7812
sub_14:Test (Best Model) - Loss: 0.7775 - Accuracy: 0.8333 - F1: 0.8299
sub_14:Test (Best Model) - Loss: 1.0328 - Accuracy: 0.7857 - F1: 0.7826
sub_14:Test (Best Model) - Loss: 0.9303 - Accuracy: 0.7976 - F1: 0.7927
sub_14:Test (Best Model) - Loss: 1.1667 - Accuracy: 0.7619 - F1: 0.7597
sub_14:Test (Best Model) - Loss: 0.4520 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.8452 - F1: 0.8452
sub_14:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.7262 - F1: 0.7114
sub_14:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.7976 - F1: 0.7953
sub_14:Test (Best Model) - Loss: 0.7333 - Accuracy: 0.8214 - F1: 0.8202

=== Summary Results ===

acc: 73.32 ± 6.08
F1: 72.58 ± 6.50
acc-in: 80.57 ± 6.76
F1-in: 80.11 ± 7.06
