lr: 0.001
sub_1:Test (Best Model) - Loss: 4.5474 - Accuracy: 0.6905 - F1: 0.6756
sub_1:Test (Best Model) - Loss: 4.0304 - Accuracy: 0.7143 - F1: 0.6932
sub_1:Test (Best Model) - Loss: 5.7627 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 7.9690 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 8.3168 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 6.2998 - Accuracy: 0.7143 - F1: 0.7061
sub_1:Test (Best Model) - Loss: 1.7471 - Accuracy: 0.7738 - F1: 0.7730
sub_1:Test (Best Model) - Loss: 6.3052 - Accuracy: 0.7024 - F1: 0.6951
sub_1:Test (Best Model) - Loss: 3.0492 - Accuracy: 0.6786 - F1: 0.6763
sub_1:Test (Best Model) - Loss: 3.4444 - Accuracy: 0.7500 - F1: 0.7491
sub_1:Test (Best Model) - Loss: 3.9138 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 2.4766 - Accuracy: 0.7738 - F1: 0.7683
sub_1:Test (Best Model) - Loss: 3.6002 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 4.1610 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 3.1444 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 1.0806 - Accuracy: 0.7143 - F1: 0.7102
sub_2:Test (Best Model) - Loss: 1.4008 - Accuracy: 0.8095 - F1: 0.8094
sub_2:Test (Best Model) - Loss: 1.1536 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 2.0483 - Accuracy: 0.7262 - F1: 0.7079
sub_2:Test (Best Model) - Loss: 2.0619 - Accuracy: 0.7381 - F1: 0.7343
sub_2:Test (Best Model) - Loss: 2.1951 - Accuracy: 0.7976 - F1: 0.7953
sub_2:Test (Best Model) - Loss: 1.9778 - Accuracy: 0.7619 - F1: 0.7597
sub_2:Test (Best Model) - Loss: 1.9361 - Accuracy: 0.7857 - F1: 0.7826
sub_2:Test (Best Model) - Loss: 1.9775 - Accuracy: 0.7262 - F1: 0.7172
sub_2:Test (Best Model) - Loss: 1.3066 - Accuracy: 0.8452 - F1: 0.8414
sub_2:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.7857 - F1: 0.7856
sub_2:Test (Best Model) - Loss: 2.0690 - Accuracy: 0.8571 - F1: 0.8558
sub_2:Test (Best Model) - Loss: 2.6776 - Accuracy: 0.7619 - F1: 0.7551
sub_2:Test (Best Model) - Loss: 1.1019 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 2.6429 - Accuracy: 0.7738 - F1: 0.7699
sub_3:Test (Best Model) - Loss: 5.7757 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 7.9894 - Accuracy: 0.5238 - F1: 0.3842
sub_3:Test (Best Model) - Loss: 4.1782 - Accuracy: 0.5595 - F1: 0.4999
sub_3:Test (Best Model) - Loss: 4.2180 - Accuracy: 0.5357 - F1: 0.4625
sub_3:Test (Best Model) - Loss: 5.2330 - Accuracy: 0.6310 - F1: 0.5728
sub_3:Test (Best Model) - Loss: 2.2421 - Accuracy: 0.7262 - F1: 0.7230
sub_3:Test (Best Model) - Loss: 1.5471 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 4.3517 - Accuracy: 0.5833 - F1: 0.5819
sub_3:Test (Best Model) - Loss: 2.3431 - Accuracy: 0.7381 - F1: 0.7326
sub_3:Test (Best Model) - Loss: 1.3528 - Accuracy: 0.7500 - F1: 0.7491
sub_3:Test (Best Model) - Loss: 5.4286 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 4.9462 - Accuracy: 0.5595 - F1: 0.4535
sub_3:Test (Best Model) - Loss: 2.8617 - Accuracy: 0.6786 - F1: 0.6525
sub_3:Test (Best Model) - Loss: 3.3765 - Accuracy: 0.6429 - F1: 0.6111
sub_3:Test (Best Model) - Loss: 2.9916 - Accuracy: 0.6905 - F1: 0.6577
sub_4:Test (Best Model) - Loss: 2.5287 - Accuracy: 0.6667 - F1: 0.6665
sub_4:Test (Best Model) - Loss: 2.6485 - Accuracy: 0.6548 - F1: 0.6535
sub_4:Test (Best Model) - Loss: 4.6057 - Accuracy: 0.7262 - F1: 0.7252
sub_4:Test (Best Model) - Loss: 6.0437 - Accuracy: 0.6667 - F1: 0.6541
sub_4:Test (Best Model) - Loss: 2.1398 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 1.7609 - Accuracy: 0.7500 - F1: 0.7483
sub_4:Test (Best Model) - Loss: 2.0894 - Accuracy: 0.7024 - F1: 0.6951
sub_4:Test (Best Model) - Loss: 1.8295 - Accuracy: 0.6905 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 2.8514 - Accuracy: 0.6667 - F1: 0.6650
sub_4:Test (Best Model) - Loss: 1.7485 - Accuracy: 0.7857 - F1: 0.7857
sub_4:Test (Best Model) - Loss: 2.2881 - Accuracy: 0.5952 - F1: 0.5932
sub_4:Test (Best Model) - Loss: 1.2419 - Accuracy: 0.8095 - F1: 0.8085
sub_4:Test (Best Model) - Loss: 1.9571 - Accuracy: 0.7143 - F1: 0.7141
sub_4:Test (Best Model) - Loss: 2.3023 - Accuracy: 0.7500 - F1: 0.7497
sub_4:Test (Best Model) - Loss: 1.8529 - Accuracy: 0.7857 - F1: 0.7852
sub_5:Test (Best Model) - Loss: 0.9561 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 0.9361 - Accuracy: 0.8333 - F1: 0.8309
sub_5:Test (Best Model) - Loss: 1.6707 - Accuracy: 0.8214 - F1: 0.8183
sub_5:Test (Best Model) - Loss: 2.4061 - Accuracy: 0.8214 - F1: 0.8170
sub_5:Test (Best Model) - Loss: 1.4906 - Accuracy: 0.7976 - F1: 0.7976
sub_5:Test (Best Model) - Loss: 0.5790 - Accuracy: 0.9048 - F1: 0.9045
sub_5:Test (Best Model) - Loss: 0.9164 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 1.3729 - Accuracy: 0.7857 - F1: 0.7846
sub_5:Test (Best Model) - Loss: 2.1632 - Accuracy: 0.7262 - F1: 0.7040
sub_5:Test (Best Model) - Loss: 0.9911 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 1.3732 - Accuracy: 0.8333 - F1: 0.8318
sub_5:Test (Best Model) - Loss: 2.1093 - Accuracy: 0.7738 - F1: 0.7699
sub_5:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.7143 - F1: 0.7005
sub_5:Test (Best Model) - Loss: 1.6394 - Accuracy: 0.7381 - F1: 0.7379
sub_6:Test (Best Model) - Loss: 2.9219 - Accuracy: 0.5833 - F1: 0.5761
sub_6:Test (Best Model) - Loss: 2.5679 - Accuracy: 0.5952 - F1: 0.5950
sub_6:Test (Best Model) - Loss: 3.4075 - Accuracy: 0.6310 - F1: 0.6284
sub_6:Test (Best Model) - Loss: 4.7004 - Accuracy: 0.5952 - F1: 0.5894
sub_6:Test (Best Model) - Loss: 4.0845 - Accuracy: 0.7024 - F1: 0.7013
sub_6:Test (Best Model) - Loss: 3.6031 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 2.3054 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 4.1165 - Accuracy: 0.6071 - F1: 0.6026
sub_6:Test (Best Model) - Loss: 3.6800 - Accuracy: 0.5833 - F1: 0.5761
sub_6:Test (Best Model) - Loss: 3.8753 - Accuracy: 0.5952 - F1: 0.5932
sub_6:Test (Best Model) - Loss: 1.8647 - Accuracy: 0.7143 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 1.7596 - Accuracy: 0.7143 - F1: 0.7136
sub_6:Test (Best Model) - Loss: 2.0597 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 3.8816 - Accuracy: 0.5714 - F1: 0.5625
sub_6:Test (Best Model) - Loss: 2.2477 - Accuracy: 0.6071 - F1: 0.6044
sub_7:Test (Best Model) - Loss: 2.5781 - Accuracy: 0.6667 - F1: 0.6506
sub_7:Test (Best Model) - Loss: 3.1555 - Accuracy: 0.5714 - F1: 0.5705
sub_7:Test (Best Model) - Loss: 6.7820 - Accuracy: 0.6667 - F1: 0.6541
sub_7:Test (Best Model) - Loss: 3.2819 - Accuracy: 0.5714 - F1: 0.5553
sub_7:Test (Best Model) - Loss: 3.7924 - Accuracy: 0.6786 - F1: 0.6648
sub_7:Test (Best Model) - Loss: 2.6486 - Accuracy: 0.6071 - F1: 0.6057
sub_7:Test (Best Model) - Loss: 2.8088 - Accuracy: 0.6429 - F1: 0.6214
sub_7:Test (Best Model) - Loss: 3.4572 - Accuracy: 0.5833 - F1: 0.5804
sub_7:Test (Best Model) - Loss: 3.8490 - Accuracy: 0.5476 - F1: 0.5347
sub_7:Test (Best Model) - Loss: 1.8642 - Accuracy: 0.6548 - F1: 0.6547
sub_7:Test (Best Model) - Loss: 6.4430 - Accuracy: 0.5595 - F1: 0.5450
sub_7:Test (Best Model) - Loss: 4.8394 - Accuracy: 0.5595 - F1: 0.5407
sub_7:Test (Best Model) - Loss: 3.2948 - Accuracy: 0.5714 - F1: 0.5625
sub_7:Test (Best Model) - Loss: 4.9053 - Accuracy: 0.5833 - F1: 0.5696
sub_7:Test (Best Model) - Loss: 2.4940 - Accuracy: 0.5952 - F1: 0.5943
sub_8:Test (Best Model) - Loss: 2.2629 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 2.6856 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 1.9484 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 2.4425 - Accuracy: 0.8214 - F1: 0.8208
sub_8:Test (Best Model) - Loss: 3.0465 - Accuracy: 0.7976 - F1: 0.7969
sub_8:Test (Best Model) - Loss: 1.0421 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 2.0863 - Accuracy: 0.7976 - F1: 0.7962
sub_8:Test (Best Model) - Loss: 1.2246 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 2.0909 - Accuracy: 0.7500 - F1: 0.7497
sub_8:Test (Best Model) - Loss: 1.6284 - Accuracy: 0.7857 - F1: 0.7826
sub_8:Test (Best Model) - Loss: 0.8953 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.8659 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 1.1482 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.9226 - Accuracy: 0.8690 - F1: 0.8690
sub_8:Test (Best Model) - Loss: 1.5909 - Accuracy: 0.7262 - F1: 0.7214
sub_9:Test (Best Model) - Loss: 2.4096 - Accuracy: 0.6786 - F1: 0.6707
sub_9:Test (Best Model) - Loss: 3.7624 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 2.9762 - Accuracy: 0.6905 - F1: 0.6630
sub_9:Test (Best Model) - Loss: 3.6866 - Accuracy: 0.6548 - F1: 0.6268
sub_9:Test (Best Model) - Loss: 3.8480 - Accuracy: 0.6786 - F1: 0.6525
sub_9:Test (Best Model) - Loss: 1.9029 - Accuracy: 0.8333 - F1: 0.8330
sub_9:Test (Best Model) - Loss: 0.9121 - Accuracy: 0.7976 - F1: 0.7974
sub_9:Test (Best Model) - Loss: 2.8761 - Accuracy: 0.6310 - F1: 0.6305
sub_9:Test (Best Model) - Loss: 2.7908 - Accuracy: 0.6667 - F1: 0.6665
sub_9:Test (Best Model) - Loss: 1.6292 - Accuracy: 0.7619 - F1: 0.7618
sub_9:Test (Best Model) - Loss: 10.7496 - Accuracy: 0.6190 - F1: 0.5544
sub_9:Test (Best Model) - Loss: 1.8849 - Accuracy: 0.7619 - F1: 0.7569
sub_9:Test (Best Model) - Loss: 1.9446 - Accuracy: 0.7976 - F1: 0.7910
sub_9:Test (Best Model) - Loss: 1.4383 - Accuracy: 0.7976 - F1: 0.7910
sub_9:Test (Best Model) - Loss: 5.5307 - Accuracy: 0.6548 - F1: 0.6080
sub_10:Test (Best Model) - Loss: 3.0300 - Accuracy: 0.6190 - F1: 0.6190
sub_10:Test (Best Model) - Loss: 1.3975 - Accuracy: 0.6429 - F1: 0.6396
sub_10:Test (Best Model) - Loss: 3.0673 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 2.9993 - Accuracy: 0.6190 - F1: 0.6007
sub_10:Test (Best Model) - Loss: 1.9099 - Accuracy: 0.6548 - F1: 0.6487
sub_10:Test (Best Model) - Loss: 3.0005 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 3.2702 - Accuracy: 0.5476 - F1: 0.5347
sub_10:Test (Best Model) - Loss: 2.6004 - Accuracy: 0.5238 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 2.9239 - Accuracy: 0.6429 - F1: 0.6410
sub_10:Test (Best Model) - Loss: 2.7208 - Accuracy: 0.5476 - F1: 0.5382
sub_10:Test (Best Model) - Loss: 3.0869 - Accuracy: 0.6190 - F1: 0.6171
sub_10:Test (Best Model) - Loss: 3.9645 - Accuracy: 0.5238 - F1: 0.5195
sub_10:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.7262 - F1: 0.7214
sub_10:Test (Best Model) - Loss: 3.8403 - Accuracy: 0.6071 - F1: 0.6003
sub_10:Test (Best Model) - Loss: 2.2537 - Accuracy: 0.6071 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 3.7559 - Accuracy: 0.5595 - F1: 0.5580
sub_11:Test (Best Model) - Loss: 2.3963 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 3.6718 - Accuracy: 0.5952 - F1: 0.5837
sub_11:Test (Best Model) - Loss: 2.4313 - Accuracy: 0.6548 - F1: 0.6487
sub_11:Test (Best Model) - Loss: 2.1266 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 1.0133 - Accuracy: 0.7619 - F1: 0.7619
sub_11:Test (Best Model) - Loss: 3.2549 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 2.1153 - Accuracy: 0.6905 - F1: 0.6903
sub_11:Test (Best Model) - Loss: 1.7866 - Accuracy: 0.7262 - F1: 0.7252
sub_11:Test (Best Model) - Loss: 3.0650 - Accuracy: 0.7024 - F1: 0.6989
sub_11:Test (Best Model) - Loss: 2.0684 - Accuracy: 0.7500 - F1: 0.7471
sub_11:Test (Best Model) - Loss: 2.8504 - Accuracy: 0.6667 - F1: 0.6659
sub_11:Test (Best Model) - Loss: 2.3411 - Accuracy: 0.7143 - F1: 0.7117
sub_11:Test (Best Model) - Loss: 2.2852 - Accuracy: 0.7024 - F1: 0.6926
sub_11:Test (Best Model) - Loss: 2.1235 - Accuracy: 0.7619 - F1: 0.7614
sub_12:Test (Best Model) - Loss: 1.8484 - Accuracy: 0.7262 - F1: 0.7230
sub_12:Test (Best Model) - Loss: 1.1254 - Accuracy: 0.8214 - F1: 0.8214
sub_12:Test (Best Model) - Loss: 1.3281 - Accuracy: 0.7738 - F1: 0.7735
sub_12:Test (Best Model) - Loss: 1.4566 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 1.8244 - Accuracy: 0.7143 - F1: 0.7136
sub_12:Test (Best Model) - Loss: 3.7752 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 2.9339 - Accuracy: 0.7143 - F1: 0.7061
sub_12:Test (Best Model) - Loss: 7.1455 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 7.4509 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 3.6616 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 2.4412 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 6.6851 - Accuracy: 0.6429 - F1: 0.6050
sub_12:Test (Best Model) - Loss: 2.9334 - Accuracy: 0.7381 - F1: 0.7188
sub_12:Test (Best Model) - Loss: 1.8129 - Accuracy: 0.7738 - F1: 0.7730
sub_12:Test (Best Model) - Loss: 2.6970 - Accuracy: 0.7500 - F1: 0.7365
sub_13:Test (Best Model) - Loss: 2.1194 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 4.2511 - Accuracy: 0.6548 - F1: 0.6487
sub_13:Test (Best Model) - Loss: 1.9357 - Accuracy: 0.7381 - F1: 0.7306
sub_13:Test (Best Model) - Loss: 2.1445 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 4.0042 - Accuracy: 0.6548 - F1: 0.6523
sub_13:Test (Best Model) - Loss: 4.0427 - Accuracy: 0.6667 - F1: 0.6506
sub_13:Test (Best Model) - Loss: 1.8450 - Accuracy: 0.6905 - F1: 0.6905
sub_13:Test (Best Model) - Loss: 2.5883 - Accuracy: 0.6905 - F1: 0.6898
sub_13:Test (Best Model) - Loss: 3.2234 - Accuracy: 0.7262 - F1: 0.7214
sub_13:Test (Best Model) - Loss: 3.5168 - Accuracy: 0.7500 - F1: 0.7471
sub_13:Test (Best Model) - Loss: 1.8884 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 1.4258 - Accuracy: 0.6905 - F1: 0.6898
sub_13:Test (Best Model) - Loss: 2.1901 - Accuracy: 0.7738 - F1: 0.7699
sub_13:Test (Best Model) - Loss: 1.7036 - Accuracy: 0.7381 - F1: 0.7255
sub_13:Test (Best Model) - Loss: 3.3921 - Accuracy: 0.6786 - F1: 0.6748
sub_14:Test (Best Model) - Loss: 1.5070 - Accuracy: 0.7500 - F1: 0.7483
sub_14:Test (Best Model) - Loss: 2.1139 - Accuracy: 0.7024 - F1: 0.7020
sub_14:Test (Best Model) - Loss: 1.1973 - Accuracy: 0.7857 - F1: 0.7852
sub_14:Test (Best Model) - Loss: 1.6461 - Accuracy: 0.8095 - F1: 0.8091
sub_14:Test (Best Model) - Loss: 2.0350 - Accuracy: 0.7857 - F1: 0.7846
sub_14:Test (Best Model) - Loss: 1.0410 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 3.9655 - Accuracy: 0.7381 - F1: 0.7306
sub_14:Test (Best Model) - Loss: 2.2034 - Accuracy: 0.8095 - F1: 0.8094
sub_14:Test (Best Model) - Loss: 3.0678 - Accuracy: 0.7738 - F1: 0.7735
sub_14:Test (Best Model) - Loss: 1.3040 - Accuracy: 0.7262 - F1: 0.7230
sub_14:Test (Best Model) - Loss: 2.2434 - Accuracy: 0.7024 - F1: 0.6972
sub_14:Test (Best Model) - Loss: 0.8888 - Accuracy: 0.7500 - F1: 0.7418
sub_14:Test (Best Model) - Loss: 3.3229 - Accuracy: 0.6190 - F1: 0.6082
sub_14:Test (Best Model) - Loss: 1.4325 - Accuracy: 0.7262 - F1: 0.7230
sub_14:Test (Best Model) - Loss: 2.1601 - Accuracy: 0.7143 - F1: 0.7035

=== Summary Results ===

acc: 70.74 ± 6.85
F1: 69.81 ± 7.33
acc-in: 78.26 ± 6.22
F1-in: 77.80 ± 6.42
