lr: 0.001
sub_1:Test (Best Model) - Loss: 6.5290 - Accuracy: 0.6905 - F1: 0.6677
sub_1:Test (Best Model) - Loss: 10.6042 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 14.4270 - Accuracy: 0.6667 - F1: 0.6370
sub_1:Test (Best Model) - Loss: 9.1392 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 12.3326 - Accuracy: 0.6905 - F1: 0.6630
sub_1:Test (Best Model) - Loss: 2.5888 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 5.2385 - Accuracy: 0.7262 - F1: 0.7114
sub_1:Test (Best Model) - Loss: 6.8291 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 2.0060 - Accuracy: 0.7857 - F1: 0.7846
sub_1:Test (Best Model) - Loss: 2.9644 - Accuracy: 0.7976 - F1: 0.7974
sub_1:Test (Best Model) - Loss: 3.7583 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 7.1939 - Accuracy: 0.7500 - F1: 0.7365
sub_1:Test (Best Model) - Loss: 3.8070 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 2.5716 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 2.1155 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 1.7573 - Accuracy: 0.7976 - F1: 0.7953
sub_2:Test (Best Model) - Loss: 1.9072 - Accuracy: 0.7500 - F1: 0.7497
sub_2:Test (Best Model) - Loss: 5.0963 - Accuracy: 0.6667 - F1: 0.6313
sub_2:Test (Best Model) - Loss: 9.4744 - Accuracy: 0.5714 - F1: 0.4750
sub_2:Test (Best Model) - Loss: 4.0952 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 2.3640 - Accuracy: 0.7857 - F1: 0.7812
sub_2:Test (Best Model) - Loss: 0.7550 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 1.0001 - Accuracy: 0.8929 - F1: 0.8927
sub_2:Test (Best Model) - Loss: 1.6776 - Accuracy: 0.8452 - F1: 0.8442
sub_2:Test (Best Model) - Loss: 0.8126 - Accuracy: 0.9405 - F1: 0.9404
sub_2:Test (Best Model) - Loss: 2.8534 - Accuracy: 0.8095 - F1: 0.8094
sub_2:Test (Best Model) - Loss: 1.8189 - Accuracy: 0.8214 - F1: 0.8214
sub_2:Test (Best Model) - Loss: 2.4345 - Accuracy: 0.8333 - F1: 0.8332
sub_2:Test (Best Model) - Loss: 2.2823 - Accuracy: 0.8095 - F1: 0.8095
sub_2:Test (Best Model) - Loss: 2.6627 - Accuracy: 0.7500 - F1: 0.7418
sub_3:Test (Best Model) - Loss: 4.7941 - Accuracy: 0.5595 - F1: 0.4670
sub_3:Test (Best Model) - Loss: 6.9719 - Accuracy: 0.5833 - F1: 0.5270
sub_3:Test (Best Model) - Loss: 8.5695 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 3.9505 - Accuracy: 0.6071 - F1: 0.5540
sub_3:Test (Best Model) - Loss: 5.1891 - Accuracy: 0.5595 - F1: 0.4670
sub_3:Test (Best Model) - Loss: 1.9418 - Accuracy: 0.7619 - F1: 0.7618
sub_3:Test (Best Model) - Loss: 1.9909 - Accuracy: 0.7143 - F1: 0.7143
sub_3:Test (Best Model) - Loss: 5.5510 - Accuracy: 0.6071 - F1: 0.6026
sub_3:Test (Best Model) - Loss: 3.7556 - Accuracy: 0.7024 - F1: 0.6951
sub_3:Test (Best Model) - Loss: 1.6611 - Accuracy: 0.7976 - F1: 0.7962
sub_3:Test (Best Model) - Loss: 9.4059 - Accuracy: 0.5833 - F1: 0.5073
sub_3:Test (Best Model) - Loss: 5.5303 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 3.5505 - Accuracy: 0.6429 - F1: 0.5982
sub_3:Test (Best Model) - Loss: 6.3316 - Accuracy: 0.6071 - F1: 0.5540
sub_3:Test (Best Model) - Loss: 3.4267 - Accuracy: 0.7976 - F1: 0.7890
sub_4:Test (Best Model) - Loss: 4.9381 - Accuracy: 0.6190 - F1: 0.6171
sub_4:Test (Best Model) - Loss: 2.9636 - Accuracy: 0.6786 - F1: 0.6785
sub_4:Test (Best Model) - Loss: 4.4585 - Accuracy: 0.6310 - F1: 0.6010
sub_4:Test (Best Model) - Loss: 2.4082 - Accuracy: 0.7738 - F1: 0.7722
sub_4:Test (Best Model) - Loss: 2.7131 - Accuracy: 0.7500 - F1: 0.7497
sub_4:Test (Best Model) - Loss: 2.2209 - Accuracy: 0.6786 - F1: 0.6648
sub_4:Test (Best Model) - Loss: 2.4005 - Accuracy: 0.7738 - F1: 0.7712
sub_4:Test (Best Model) - Loss: 3.7360 - Accuracy: 0.7500 - F1: 0.7471
sub_4:Test (Best Model) - Loss: 1.7020 - Accuracy: 0.7857 - F1: 0.7857
sub_4:Test (Best Model) - Loss: 2.2303 - Accuracy: 0.7381 - F1: 0.7282
sub_4:Test (Best Model) - Loss: 2.2547 - Accuracy: 0.7619 - F1: 0.7607
sub_4:Test (Best Model) - Loss: 1.7709 - Accuracy: 0.7857 - F1: 0.7852
sub_4:Test (Best Model) - Loss: 2.2220 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 2.3943 - Accuracy: 0.6786 - F1: 0.6763
sub_4:Test (Best Model) - Loss: 2.7739 - Accuracy: 0.7381 - F1: 0.7343
sub_5:Test (Best Model) - Loss: 0.9913 - Accuracy: 0.8452 - F1: 0.8452
sub_5:Test (Best Model) - Loss: 1.5164 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 0.9410 - Accuracy: 0.9048 - F1: 0.9047
sub_5:Test (Best Model) - Loss: 3.2472 - Accuracy: 0.7738 - F1: 0.7641
sub_5:Test (Best Model) - Loss: 2.1998 - Accuracy: 0.7976 - F1: 0.7969
sub_5:Test (Best Model) - Loss: 1.7205 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 3.7516 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 3.7370 - Accuracy: 0.7262 - F1: 0.7230
sub_5:Test (Best Model) - Loss: 1.4622 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 1.2865 - Accuracy: 0.8929 - F1: 0.8921
sub_5:Test (Best Model) - Loss: 2.1077 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 2.6375 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 1.1771 - Accuracy: 0.8690 - F1: 0.8681
sub_5:Test (Best Model) - Loss: 2.3857 - Accuracy: 0.7500 - F1: 0.7393
sub_5:Test (Best Model) - Loss: 1.8350 - Accuracy: 0.7857 - F1: 0.7846
sub_6:Test (Best Model) - Loss: 4.3113 - Accuracy: 0.5833 - F1: 0.5833
sub_6:Test (Best Model) - Loss: 3.9225 - Accuracy: 0.6548 - F1: 0.6543
sub_6:Test (Best Model) - Loss: 6.9984 - Accuracy: 0.5714 - F1: 0.5625
sub_6:Test (Best Model) - Loss: 3.6686 - Accuracy: 0.5714 - F1: 0.5712
sub_6:Test (Best Model) - Loss: 4.6554 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 3.1356 - Accuracy: 0.6548 - F1: 0.6463
sub_6:Test (Best Model) - Loss: 5.1410 - Accuracy: 0.6071 - F1: 0.6066
sub_6:Test (Best Model) - Loss: 4.3110 - Accuracy: 0.6429 - F1: 0.6396
sub_6:Test (Best Model) - Loss: 3.4987 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 4.2277 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 2.5554 - Accuracy: 0.6667 - F1: 0.6665
sub_6:Test (Best Model) - Loss: 4.1823 - Accuracy: 0.7024 - F1: 0.7023
sub_6:Test (Best Model) - Loss: 1.3468 - Accuracy: 0.7738 - F1: 0.7735
sub_6:Test (Best Model) - Loss: 2.8074 - Accuracy: 0.5357 - F1: 0.5303
sub_6:Test (Best Model) - Loss: 2.3275 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 4.5960 - Accuracy: 0.6786 - F1: 0.6612
sub_7:Test (Best Model) - Loss: 5.1412 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 2.8574 - Accuracy: 0.6310 - F1: 0.6010
sub_7:Test (Best Model) - Loss: 4.2196 - Accuracy: 0.6667 - F1: 0.6421
sub_7:Test (Best Model) - Loss: 2.6501 - Accuracy: 0.7143 - F1: 0.7005
sub_7:Test (Best Model) - Loss: 4.8367 - Accuracy: 0.6071 - F1: 0.6057
sub_7:Test (Best Model) - Loss: 2.2946 - Accuracy: 0.6786 - F1: 0.6763
sub_7:Test (Best Model) - Loss: 4.1316 - Accuracy: 0.5357 - F1: 0.5303
sub_7:Test (Best Model) - Loss: 6.5862 - Accuracy: 0.5476 - F1: 0.5435
sub_7:Test (Best Model) - Loss: 3.4407 - Accuracy: 0.5595 - F1: 0.5302
sub_7:Test (Best Model) - Loss: 3.1520 - Accuracy: 0.5952 - F1: 0.5943
sub_7:Test (Best Model) - Loss: 3.2467 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 3.1081 - Accuracy: 0.6786 - F1: 0.6730
sub_7:Test (Best Model) - Loss: 4.2803 - Accuracy: 0.6071 - F1: 0.6071
sub_7:Test (Best Model) - Loss: 4.2597 - Accuracy: 0.5714 - F1: 0.5179
sub_8:Test (Best Model) - Loss: 3.3471 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 4.1252 - Accuracy: 0.7738 - F1: 0.7699
sub_8:Test (Best Model) - Loss: 6.0082 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 4.6208 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 2.9684 - Accuracy: 0.7738 - F1: 0.7730
sub_8:Test (Best Model) - Loss: 1.3306 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 2.9550 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 2.4845 - Accuracy: 0.7857 - F1: 0.7812
sub_8:Test (Best Model) - Loss: 1.2546 - Accuracy: 0.8690 - F1: 0.8686
sub_8:Test (Best Model) - Loss: 1.2411 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 1.9416 - Accuracy: 0.8571 - F1: 0.8564
sub_8:Test (Best Model) - Loss: 2.6062 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.9892 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 1.8147 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.2927 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 6.1324 - Accuracy: 0.6667 - F1: 0.6421
sub_9:Test (Best Model) - Loss: 4.2125 - Accuracy: 0.6190 - F1: 0.6082
sub_9:Test (Best Model) - Loss: 5.3801 - Accuracy: 0.7143 - F1: 0.7136
sub_9:Test (Best Model) - Loss: 3.5708 - Accuracy: 0.6429 - F1: 0.6327
sub_9:Test (Best Model) - Loss: 4.4010 - Accuracy: 0.6548 - F1: 0.6317
sub_9:Test (Best Model) - Loss: 3.0409 - Accuracy: 0.7738 - F1: 0.7738
sub_9:Test (Best Model) - Loss: 2.4936 - Accuracy: 0.6786 - F1: 0.6763
sub_9:Test (Best Model) - Loss: 2.8184 - Accuracy: 0.7500 - F1: 0.7439
sub_9:Test (Best Model) - Loss: 1.7008 - Accuracy: 0.7381 - F1: 0.7368
sub_9:Test (Best Model) - Loss: 1.1645 - Accuracy: 0.7262 - F1: 0.7172
sub_9:Test (Best Model) - Loss: 4.2000 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 2.5015 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 3.4055 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 2.8617 - Accuracy: 0.7024 - F1: 0.6783
sub_9:Test (Best Model) - Loss: 6.1330 - Accuracy: 0.6667 - F1: 0.6370
sub_10:Test (Best Model) - Loss: 3.1925 - Accuracy: 0.5952 - F1: 0.5943
sub_10:Test (Best Model) - Loss: 3.0458 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 3.2675 - Accuracy: 0.7024 - F1: 0.6989
sub_10:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.6905 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 2.5225 - Accuracy: 0.6429 - F1: 0.6327
sub_10:Test (Best Model) - Loss: 4.0968 - Accuracy: 0.6190 - F1: 0.6082
sub_10:Test (Best Model) - Loss: 6.5228 - Accuracy: 0.5714 - F1: 0.5260
sub_10:Test (Best Model) - Loss: 4.7572 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 3.2559 - Accuracy: 0.6905 - F1: 0.6860
sub_10:Test (Best Model) - Loss: 4.1186 - Accuracy: 0.6429 - F1: 0.6354
sub_10:Test (Best Model) - Loss: 2.1474 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 1.9253 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 1.4262 - Accuracy: 0.7262 - F1: 0.7252
sub_10:Test (Best Model) - Loss: 3.8941 - Accuracy: 0.7024 - F1: 0.6951
sub_10:Test (Best Model) - Loss: 3.1353 - Accuracy: 0.6905 - F1: 0.6860
sub_11:Test (Best Model) - Loss: 2.9122 - Accuracy: 0.6667 - F1: 0.6597
sub_11:Test (Best Model) - Loss: 3.4368 - Accuracy: 0.5833 - F1: 0.5828
sub_11:Test (Best Model) - Loss: 2.7519 - Accuracy: 0.6905 - F1: 0.6860
sub_11:Test (Best Model) - Loss: 3.4572 - Accuracy: 0.6667 - F1: 0.6571
sub_11:Test (Best Model) - Loss: 5.5103 - Accuracy: 0.5595 - F1: 0.4901
sub_11:Test (Best Model) - Loss: 1.6700 - Accuracy: 0.8214 - F1: 0.8202
sub_11:Test (Best Model) - Loss: 1.9877 - Accuracy: 0.8214 - F1: 0.8208
sub_11:Test (Best Model) - Loss: 0.8478 - Accuracy: 0.8333 - F1: 0.8325
sub_11:Test (Best Model) - Loss: 1.9006 - Accuracy: 0.7381 - F1: 0.7375
sub_11:Test (Best Model) - Loss: 2.2738 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 2.0452 - Accuracy: 0.7619 - F1: 0.7569
sub_11:Test (Best Model) - Loss: 4.1363 - Accuracy: 0.7143 - F1: 0.7117
sub_11:Test (Best Model) - Loss: 2.7273 - Accuracy: 0.7857 - F1: 0.7856
sub_11:Test (Best Model) - Loss: 2.6691 - Accuracy: 0.6786 - F1: 0.6763
sub_11:Test (Best Model) - Loss: 1.2665 - Accuracy: 0.6905 - F1: 0.6903
sub_12:Test (Best Model) - Loss: 1.0182 - Accuracy: 0.8214 - F1: 0.8208
sub_12:Test (Best Model) - Loss: 0.8868 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 1.9580 - Accuracy: 0.8571 - F1: 0.8571
sub_12:Test (Best Model) - Loss: 1.4452 - Accuracy: 0.8214 - F1: 0.8155
sub_12:Test (Best Model) - Loss: 1.1969 - Accuracy: 0.8333 - F1: 0.8333
sub_12:Test (Best Model) - Loss: 8.2788 - Accuracy: 0.7381 - F1: 0.7306
sub_12:Test (Best Model) - Loss: 7.9572 - Accuracy: 0.6905 - F1: 0.6756
sub_12:Test (Best Model) - Loss: 14.3883 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 7.6049 - Accuracy: 0.7381 - F1: 0.7326
sub_12:Test (Best Model) - Loss: 4.1936 - Accuracy: 0.6905 - F1: 0.6816
sub_12:Test (Best Model) - Loss: 2.8490 - Accuracy: 0.7619 - F1: 0.7529
sub_12:Test (Best Model) - Loss: 2.0410 - Accuracy: 0.7976 - F1: 0.7927
sub_12:Test (Best Model) - Loss: 2.0268 - Accuracy: 0.8095 - F1: 0.8056
sub_12:Test (Best Model) - Loss: 2.3312 - Accuracy: 0.7857 - F1: 0.7812
sub_12:Test (Best Model) - Loss: 1.4932 - Accuracy: 0.8571 - F1: 0.8564
sub_13:Test (Best Model) - Loss: 3.1826 - Accuracy: 0.6548 - F1: 0.6400
sub_13:Test (Best Model) - Loss: 3.6287 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 4.5709 - Accuracy: 0.7143 - F1: 0.7005
sub_13:Test (Best Model) - Loss: 3.1416 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 3.2592 - Accuracy: 0.6905 - F1: 0.6905
sub_13:Test (Best Model) - Loss: 4.3709 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 5.6140 - Accuracy: 0.7143 - F1: 0.7083
sub_13:Test (Best Model) - Loss: 2.5157 - Accuracy: 0.7143 - F1: 0.7128
sub_13:Test (Best Model) - Loss: 3.7787 - Accuracy: 0.7381 - F1: 0.7379
sub_13:Test (Best Model) - Loss: 4.7142 - Accuracy: 0.7500 - F1: 0.7483
sub_13:Test (Best Model) - Loss: 1.7396 - Accuracy: 0.7143 - F1: 0.7102
sub_13:Test (Best Model) - Loss: 3.1120 - Accuracy: 0.7024 - F1: 0.6989
sub_13:Test (Best Model) - Loss: 1.5223 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 2.9948 - Accuracy: 0.7500 - F1: 0.7393
sub_13:Test (Best Model) - Loss: 1.5379 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 2.0868 - Accuracy: 0.8452 - F1: 0.8447
sub_14:Test (Best Model) - Loss: 1.9488 - Accuracy: 0.7976 - F1: 0.7953
sub_14:Test (Best Model) - Loss: 3.9280 - Accuracy: 0.7619 - F1: 0.7607
sub_14:Test (Best Model) - Loss: 3.0841 - Accuracy: 0.7500 - F1: 0.7393
sub_14:Test (Best Model) - Loss: 3.3054 - Accuracy: 0.8452 - F1: 0.8447
sub_14:Test (Best Model) - Loss: 1.0594 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 2.4143 - Accuracy: 0.7976 - F1: 0.7910
sub_14:Test (Best Model) - Loss: 2.3939 - Accuracy: 0.8690 - F1: 0.8689
sub_14:Test (Best Model) - Loss: 1.8458 - Accuracy: 0.8095 - F1: 0.8068
sub_14:Test (Best Model) - Loss: 0.5627 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 7.2650 - Accuracy: 0.6429 - F1: 0.5982
sub_14:Test (Best Model) - Loss: 2.5083 - Accuracy: 0.8095 - F1: 0.8078
sub_14:Test (Best Model) - Loss: 2.8310 - Accuracy: 0.7857 - F1: 0.7856
sub_14:Test (Best Model) - Loss: 4.7432 - Accuracy: 0.7381 - F1: 0.7255
sub_14:Test (Best Model) - Loss: 1.2797 - Accuracy: 0.8333 - F1: 0.8325

=== Summary Results ===

acc: 72.99 ± 6.92
F1: 72.01 ± 7.41
acc-in: 81.48 ± 6.70
F1-in: 81.07 ± 7.07
