lr: 0.0001
sub_1:Test (Best Model) - Loss: 2.7012 - Accuracy: 0.7024 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 2.7760 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 1.9760 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 2.2990 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 2.0397 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.9327 - Accuracy: 0.7381 - F1: 0.7375
sub_1:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.8333 - F1: 0.8333
sub_1:Test (Best Model) - Loss: 1.5838 - Accuracy: 0.7619 - F1: 0.7607
sub_1:Test (Best Model) - Loss: 1.3005 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 0.9315 - Accuracy: 0.7738 - F1: 0.7712
sub_1:Test (Best Model) - Loss: 1.4973 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 1.4843 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 1.3023 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 1.1832 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 1.4784 - Accuracy: 0.7024 - F1: 0.6783
sub_2:Test (Best Model) - Loss: 1.1156 - Accuracy: 0.6786 - F1: 0.6730
sub_2:Test (Best Model) - Loss: 0.4334 - Accuracy: 0.8095 - F1: 0.8085
sub_2:Test (Best Model) - Loss: 0.4250 - Accuracy: 0.8333 - F1: 0.8330
sub_2:Test (Best Model) - Loss: 1.2007 - Accuracy: 0.7500 - F1: 0.7439
sub_2:Test (Best Model) - Loss: 0.8334 - Accuracy: 0.6190 - F1: 0.6047
sub_2:Test (Best Model) - Loss: 0.9541 - Accuracy: 0.6905 - F1: 0.6677
sub_2:Test (Best Model) - Loss: 0.7407 - Accuracy: 0.7262 - F1: 0.7145
sub_2:Test (Best Model) - Loss: 0.4955 - Accuracy: 0.7857 - F1: 0.7796
sub_2:Test (Best Model) - Loss: 0.8464 - Accuracy: 0.6905 - F1: 0.6719
sub_2:Test (Best Model) - Loss: 0.5089 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.7500 - F1: 0.7497
sub_2:Test (Best Model) - Loss: 0.8224 - Accuracy: 0.7738 - F1: 0.7735
sub_2:Test (Best Model) - Loss: 0.8528 - Accuracy: 0.7024 - F1: 0.7013
sub_2:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.8214 - F1: 0.8202
sub_2:Test (Best Model) - Loss: 0.7708 - Accuracy: 0.7500 - F1: 0.7497
sub_3:Test (Best Model) - Loss: 4.0634 - Accuracy: 0.5238 - F1: 0.3842
sub_3:Test (Best Model) - Loss: 2.0374 - Accuracy: 0.5833 - F1: 0.5176
sub_3:Test (Best Model) - Loss: 2.1087 - Accuracy: 0.5714 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 2.1637 - Accuracy: 0.5238 - F1: 0.4542
sub_3:Test (Best Model) - Loss: 3.1539 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 0.9900 - Accuracy: 0.7738 - F1: 0.7738
sub_3:Test (Best Model) - Loss: 1.2450 - Accuracy: 0.6429 - F1: 0.6327
sub_3:Test (Best Model) - Loss: 1.4999 - Accuracy: 0.6548 - F1: 0.6547
sub_3:Test (Best Model) - Loss: 1.2092 - Accuracy: 0.6667 - F1: 0.6619
sub_3:Test (Best Model) - Loss: 0.8528 - Accuracy: 0.7500 - F1: 0.7483
sub_3:Test (Best Model) - Loss: 2.7112 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 1.8670 - Accuracy: 0.6548 - F1: 0.6150
sub_3:Test (Best Model) - Loss: 1.6892 - Accuracy: 0.6429 - F1: 0.6111
sub_3:Test (Best Model) - Loss: 1.4828 - Accuracy: 0.6429 - F1: 0.6050
sub_3:Test (Best Model) - Loss: 1.9554 - Accuracy: 0.6548 - F1: 0.6080
sub_4:Test (Best Model) - Loss: 1.1570 - Accuracy: 0.7381 - F1: 0.7379
sub_4:Test (Best Model) - Loss: 1.3276 - Accuracy: 0.6190 - F1: 0.6136
sub_4:Test (Best Model) - Loss: 1.2154 - Accuracy: 0.6429 - F1: 0.6377
sub_4:Test (Best Model) - Loss: 1.0669 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 1.1006 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 1.1594 - Accuracy: 0.6667 - F1: 0.6597
sub_4:Test (Best Model) - Loss: 1.0732 - Accuracy: 0.7619 - F1: 0.7529
sub_4:Test (Best Model) - Loss: 0.8233 - Accuracy: 0.7738 - F1: 0.7730
sub_4:Test (Best Model) - Loss: 0.9859 - Accuracy: 0.7024 - F1: 0.6926
sub_4:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 1.0845 - Accuracy: 0.6786 - F1: 0.6782
sub_4:Test (Best Model) - Loss: 0.7476 - Accuracy: 0.7857 - F1: 0.7846
sub_4:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 0.9214 - Accuracy: 0.7500 - F1: 0.7497
sub_4:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 0.5200 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 0.7462 - Accuracy: 0.7619 - F1: 0.7614
sub_5:Test (Best Model) - Loss: 0.6721 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.7857 - F1: 0.7846
sub_5:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.7857 - F1: 0.7856
sub_5:Test (Best Model) - Loss: 1.3584 - Accuracy: 0.6667 - F1: 0.6541
sub_5:Test (Best Model) - Loss: 0.6427 - Accuracy: 0.7857 - F1: 0.7838
sub_5:Test (Best Model) - Loss: 0.6620 - Accuracy: 0.7976 - F1: 0.7976
sub_5:Test (Best Model) - Loss: 0.5696 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.7976 - F1: 0.7941
sub_5:Test (Best Model) - Loss: 0.5657 - Accuracy: 0.8095 - F1: 0.8078
sub_5:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7976 - F1: 0.7974
sub_5:Test (Best Model) - Loss: 0.5741 - Accuracy: 0.8333 - F1: 0.8325
sub_5:Test (Best Model) - Loss: 0.5332 - Accuracy: 0.8571 - F1: 0.8564
sub_5:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.8214 - F1: 0.8214
sub_6:Test (Best Model) - Loss: 1.5266 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 1.3644 - Accuracy: 0.5714 - F1: 0.5705
sub_6:Test (Best Model) - Loss: 1.8031 - Accuracy: 0.5833 - F1: 0.5804
sub_6:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.5595 - F1: 0.5595
sub_6:Test (Best Model) - Loss: 1.3151 - Accuracy: 0.5595 - F1: 0.5595
sub_6:Test (Best Model) - Loss: 1.2572 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 1.2993 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 1.5866 - Accuracy: 0.6786 - F1: 0.6774
sub_6:Test (Best Model) - Loss: 1.5235 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 1.1690 - Accuracy: 0.6429 - F1: 0.6327
sub_6:Test (Best Model) - Loss: 1.4390 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.9799 - Accuracy: 0.7381 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 0.9228 - Accuracy: 0.6905 - F1: 0.6903
sub_6:Test (Best Model) - Loss: 1.1797 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 1.0280 - Accuracy: 0.6548 - F1: 0.6523
sub_7:Test (Best Model) - Loss: 1.5591 - Accuracy: 0.6667 - F1: 0.6597
sub_7:Test (Best Model) - Loss: 1.6384 - Accuracy: 0.6190 - F1: 0.6047
sub_7:Test (Best Model) - Loss: 1.2377 - Accuracy: 0.7262 - F1: 0.7145
sub_7:Test (Best Model) - Loss: 1.6355 - Accuracy: 0.6429 - F1: 0.6294
sub_7:Test (Best Model) - Loss: 1.5702 - Accuracy: 0.5952 - F1: 0.5758
sub_7:Test (Best Model) - Loss: 1.0433 - Accuracy: 0.6071 - F1: 0.5942
sub_7:Test (Best Model) - Loss: 1.1194 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 0.9194 - Accuracy: 0.7262 - F1: 0.7214
sub_7:Test (Best Model) - Loss: 1.3250 - Accuracy: 0.5952 - F1: 0.5915
sub_7:Test (Best Model) - Loss: 1.4199 - Accuracy: 0.5714 - F1: 0.5399
sub_7:Test (Best Model) - Loss: 1.4128 - Accuracy: 0.5595 - F1: 0.5595
sub_7:Test (Best Model) - Loss: 1.5459 - Accuracy: 0.6190 - F1: 0.6007
sub_7:Test (Best Model) - Loss: 1.1014 - Accuracy: 0.6310 - F1: 0.6245
sub_7:Test (Best Model) - Loss: 1.3688 - Accuracy: 0.6190 - F1: 0.6171
sub_7:Test (Best Model) - Loss: 0.8938 - Accuracy: 0.6190 - F1: 0.6188
sub_8:Test (Best Model) - Loss: 0.8656 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 0.9622 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 0.9136 - Accuracy: 0.8214 - F1: 0.8212
sub_8:Test (Best Model) - Loss: 0.8333 - Accuracy: 0.8333 - F1: 0.8332
sub_8:Test (Best Model) - Loss: 0.9973 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.4286 - Accuracy: 0.8929 - F1: 0.8927
sub_8:Test (Best Model) - Loss: 0.6118 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.4643 - Accuracy: 0.8929 - F1: 0.8927
sub_8:Test (Best Model) - Loss: 0.5564 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.3197 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.3357 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.5093 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 0.3781 - Accuracy: 0.8690 - F1: 0.8681
sub_8:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.9167 - F1: 0.9167
sub_8:Test (Best Model) - Loss: 0.6080 - Accuracy: 0.7976 - F1: 0.7953
sub_9:Test (Best Model) - Loss: 1.0363 - Accuracy: 0.7024 - F1: 0.6863
sub_9:Test (Best Model) - Loss: 0.9300 - Accuracy: 0.7143 - F1: 0.7141
sub_9:Test (Best Model) - Loss: 1.6687 - Accuracy: 0.6429 - F1: 0.6166
sub_9:Test (Best Model) - Loss: 1.0602 - Accuracy: 0.7262 - F1: 0.7145
sub_9:Test (Best Model) - Loss: 1.3270 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.8204 - Accuracy: 0.7619 - F1: 0.7597
sub_9:Test (Best Model) - Loss: 0.9954 - Accuracy: 0.7500 - F1: 0.7500
sub_9:Test (Best Model) - Loss: 1.2431 - Accuracy: 0.5952 - F1: 0.5932
sub_9:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.8095 - F1: 0.8094
sub_9:Test (Best Model) - Loss: 0.5119 - Accuracy: 0.7976 - F1: 0.7976
sub_9:Test (Best Model) - Loss: 1.8176 - Accuracy: 0.6786 - F1: 0.6473
sub_9:Test (Best Model) - Loss: 0.8195 - Accuracy: 0.7976 - F1: 0.7927
sub_9:Test (Best Model) - Loss: 0.9759 - Accuracy: 0.7262 - F1: 0.7145
sub_9:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.7857 - F1: 0.7754
sub_9:Test (Best Model) - Loss: 1.1110 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.9545 - Accuracy: 0.7024 - F1: 0.7020
sub_10:Test (Best Model) - Loss: 0.8614 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 1.1909 - Accuracy: 0.7143 - F1: 0.7143
sub_10:Test (Best Model) - Loss: 1.1696 - Accuracy: 0.6786 - F1: 0.6763
sub_10:Test (Best Model) - Loss: 0.8725 - Accuracy: 0.7500 - F1: 0.7483
sub_10:Test (Best Model) - Loss: 1.0092 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 1.1674 - Accuracy: 0.6429 - F1: 0.6354
sub_10:Test (Best Model) - Loss: 1.2709 - Accuracy: 0.5833 - F1: 0.5819
sub_10:Test (Best Model) - Loss: 1.2831 - Accuracy: 0.5952 - F1: 0.5932
sub_10:Test (Best Model) - Loss: 1.2969 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 1.0407 - Accuracy: 0.7262 - F1: 0.7243
sub_10:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.7619 - F1: 0.7618
sub_10:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.7857 - F1: 0.7856
sub_10:Test (Best Model) - Loss: 0.7551 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 0.7905 - Accuracy: 0.6905 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 1.2673 - Accuracy: 0.5714 - F1: 0.5692
sub_11:Test (Best Model) - Loss: 1.0998 - Accuracy: 0.6548 - F1: 0.6508
sub_11:Test (Best Model) - Loss: 0.9844 - Accuracy: 0.7024 - F1: 0.7020
sub_11:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.5952 - F1: 0.5800
sub_11:Test (Best Model) - Loss: 1.1275 - Accuracy: 0.6548 - F1: 0.6508
sub_11:Test (Best Model) - Loss: 0.5493 - Accuracy: 0.7976 - F1: 0.7974
sub_11:Test (Best Model) - Loss: 0.7934 - Accuracy: 0.7381 - F1: 0.7306
sub_11:Test (Best Model) - Loss: 0.5753 - Accuracy: 0.7857 - F1: 0.7846
sub_11:Test (Best Model) - Loss: 1.0521 - Accuracy: 0.6667 - F1: 0.6650
sub_11:Test (Best Model) - Loss: 0.8580 - Accuracy: 0.7381 - F1: 0.7343
sub_11:Test (Best Model) - Loss: 1.1902 - Accuracy: 0.6310 - F1: 0.6245
sub_11:Test (Best Model) - Loss: 1.1503 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 0.7412 - Accuracy: 0.7619 - F1: 0.7607
sub_11:Test (Best Model) - Loss: 0.7297 - Accuracy: 0.7857 - F1: 0.7856
sub_11:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.7143 - F1: 0.7136
sub_12:Test (Best Model) - Loss: 0.7471 - Accuracy: 0.8095 - F1: 0.8094
sub_12:Test (Best Model) - Loss: 0.2552 - Accuracy: 0.8929 - F1: 0.8927
sub_12:Test (Best Model) - Loss: 0.3590 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.3554 - Accuracy: 0.8810 - F1: 0.8803
sub_12:Test (Best Model) - Loss: 0.4758 - Accuracy: 0.8095 - F1: 0.8095
sub_12:Test (Best Model) - Loss: 2.1122 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 1.4717 - Accuracy: 0.6667 - F1: 0.6421
sub_12:Test (Best Model) - Loss: 1.4406 - Accuracy: 0.7500 - F1: 0.7393
sub_12:Test (Best Model) - Loss: 1.9001 - Accuracy: 0.7381 - F1: 0.7224
sub_12:Test (Best Model) - Loss: 1.3112 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 0.8637 - Accuracy: 0.7500 - F1: 0.7491
sub_12:Test (Best Model) - Loss: 0.8326 - Accuracy: 0.8214 - F1: 0.8194
sub_12:Test (Best Model) - Loss: 0.5533 - Accuracy: 0.7857 - F1: 0.7812
sub_12:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.7857 - F1: 0.7856
sub_12:Test (Best Model) - Loss: 0.8280 - Accuracy: 0.7857 - F1: 0.7812
sub_13:Test (Best Model) - Loss: 0.7676 - Accuracy: 0.6905 - F1: 0.6860
sub_13:Test (Best Model) - Loss: 0.8127 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 1.2301 - Accuracy: 0.6548 - F1: 0.6434
sub_13:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.7640 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 1.0696 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.7738 - F1: 0.7738
sub_13:Test (Best Model) - Loss: 0.9440 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.8664 - Accuracy: 0.7500 - F1: 0.7500
sub_13:Test (Best Model) - Loss: 0.7858 - Accuracy: 0.8095 - F1: 0.8094
sub_13:Test (Best Model) - Loss: 0.8086 - Accuracy: 0.7738 - F1: 0.7699
sub_13:Test (Best Model) - Loss: 0.8617 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.8678 - Accuracy: 0.7024 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.4334 - Accuracy: 0.8333 - F1: 0.8325
sub_13:Test (Best Model) - Loss: 0.6597 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.7741 - Accuracy: 0.7381 - F1: 0.7357
sub_14:Test (Best Model) - Loss: 0.9238 - Accuracy: 0.7262 - F1: 0.7195
sub_14:Test (Best Model) - Loss: 0.4403 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.7720 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 1.0764 - Accuracy: 0.7500 - F1: 0.7483
sub_14:Test (Best Model) - Loss: 0.3006 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 1.0906 - Accuracy: 0.6905 - F1: 0.6788
sub_14:Test (Best Model) - Loss: 0.8103 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.7857 - F1: 0.7838
sub_14:Test (Best Model) - Loss: 0.5275 - Accuracy: 0.8333 - F1: 0.8318
sub_14:Test (Best Model) - Loss: 0.7820 - Accuracy: 0.7381 - F1: 0.7375
sub_14:Test (Best Model) - Loss: 0.5277 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.7857 - F1: 0.7857
sub_14:Test (Best Model) - Loss: 0.5024 - Accuracy: 0.8452 - F1: 0.8447
sub_14:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.7500 - F1: 0.7500

=== Summary Results ===

acc: 72.72 ± 6.53
F1: 71.92 ± 7.09
acc-in: 79.77 ± 6.78
F1-in: 79.45 ± 6.95
