lr: 0.001
sub_1:Test (Best Model) - Loss: 22.7435 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 17.8371 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 22.4499 - Accuracy: 0.7024 - F1: 0.6735
sub_1:Test (Best Model) - Loss: 21.9916 - Accuracy: 0.6786 - F1: 0.6707
sub_1:Test (Best Model) - Loss: 14.8455 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 7.9674 - Accuracy: 0.7619 - F1: 0.7529
sub_1:Test (Best Model) - Loss: 5.9989 - Accuracy: 0.8214 - F1: 0.8202
sub_1:Test (Best Model) - Loss: 8.8784 - Accuracy: 0.7143 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 6.8200 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 5.4108 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 7.5150 - Accuracy: 0.8571 - F1: 0.8558
sub_1:Test (Best Model) - Loss: 24.8292 - Accuracy: 0.6310 - F1: 0.5728
sub_1:Test (Best Model) - Loss: 3.4699 - Accuracy: 0.9167 - F1: 0.9166
sub_1:Test (Best Model) - Loss: 9.8072 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 13.9267 - Accuracy: 0.7738 - F1: 0.7641
sub_2:Test (Best Model) - Loss: 7.2406 - Accuracy: 0.7024 - F1: 0.6783
sub_2:Test (Best Model) - Loss: 14.8183 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 7.1560 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 3.9672 - Accuracy: 0.8929 - F1: 0.8916
sub_2:Test (Best Model) - Loss: 37.8419 - Accuracy: 0.5714 - F1: 0.4750
sub_2:Test (Best Model) - Loss: 1.8645 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 3.7357 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.5077 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 2.1776 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.8786 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.7643 - Accuracy: 0.9405 - F1: 0.9404
sub_2:Test (Best Model) - Loss: 1.5559 - Accuracy: 0.9286 - F1: 0.9286
sub_2:Test (Best Model) - Loss: 2.4279 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 1.5473 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 6.1760 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 14.6586 - Accuracy: 0.5476 - F1: 0.4458
sub_3:Test (Best Model) - Loss: 13.2722 - Accuracy: 0.5476 - F1: 0.4312
sub_3:Test (Best Model) - Loss: 12.3972 - Accuracy: 0.5714 - F1: 0.4875
sub_3:Test (Best Model) - Loss: 5.6211 - Accuracy: 0.7024 - F1: 0.6863
sub_3:Test (Best Model) - Loss: 22.0217 - Accuracy: 0.5119 - F1: 0.3593
sub_3:Test (Best Model) - Loss: 5.6439 - Accuracy: 0.7738 - F1: 0.7738
sub_3:Test (Best Model) - Loss: 4.0072 - Accuracy: 0.7262 - F1: 0.7262
sub_3:Test (Best Model) - Loss: 7.2014 - Accuracy: 0.6786 - F1: 0.6782
sub_3:Test (Best Model) - Loss: 7.6457 - Accuracy: 0.6786 - F1: 0.6707
sub_3:Test (Best Model) - Loss: 8.0372 - Accuracy: 0.6905 - F1: 0.6677
sub_3:Test (Best Model) - Loss: 11.8796 - Accuracy: 0.6548 - F1: 0.6150
sub_3:Test (Best Model) - Loss: 24.2156 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 18.5986 - Accuracy: 0.5714 - F1: 0.4750
sub_3:Test (Best Model) - Loss: 16.5465 - Accuracy: 0.6667 - F1: 0.6313
sub_3:Test (Best Model) - Loss: 12.5101 - Accuracy: 0.6310 - F1: 0.5728
sub_4:Test (Best Model) - Loss: 6.2482 - Accuracy: 0.8214 - F1: 0.8212
sub_4:Test (Best Model) - Loss: 4.1840 - Accuracy: 0.8452 - F1: 0.8442
sub_4:Test (Best Model) - Loss: 13.7593 - Accuracy: 0.7262 - F1: 0.7079
sub_4:Test (Best Model) - Loss: 6.9963 - Accuracy: 0.7381 - F1: 0.7368
sub_4:Test (Best Model) - Loss: 14.6254 - Accuracy: 0.7024 - F1: 0.6825
sub_4:Test (Best Model) - Loss: 9.8243 - Accuracy: 0.7381 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 2.3355 - Accuracy: 0.8452 - F1: 0.8447
sub_4:Test (Best Model) - Loss: 4.8519 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 4.4783 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 2.4336 - Accuracy: 0.8095 - F1: 0.8091
sub_4:Test (Best Model) - Loss: 1.8651 - Accuracy: 0.9167 - F1: 0.9167
sub_4:Test (Best Model) - Loss: 2.5550 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 3.5770 - Accuracy: 0.8810 - F1: 0.8807
sub_4:Test (Best Model) - Loss: 1.8289 - Accuracy: 0.7381 - F1: 0.7326
sub_4:Test (Best Model) - Loss: 2.2024 - Accuracy: 0.9048 - F1: 0.9048
sub_5:Test (Best Model) - Loss: 7.9424 - Accuracy: 0.7262 - F1: 0.7079
sub_5:Test (Best Model) - Loss: 3.1573 - Accuracy: 0.8333 - F1: 0.8299
sub_5:Test (Best Model) - Loss: 3.7051 - Accuracy: 0.8810 - F1: 0.8809
sub_5:Test (Best Model) - Loss: 5.9651 - Accuracy: 0.8452 - F1: 0.8442
sub_5:Test (Best Model) - Loss: 9.4922 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 5.4175 - Accuracy: 0.8452 - F1: 0.8450
sub_5:Test (Best Model) - Loss: 4.9527 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 3.4180 - Accuracy: 0.8214 - F1: 0.8212
sub_5:Test (Best Model) - Loss: 4.6113 - Accuracy: 0.8214 - F1: 0.8170
sub_5:Test (Best Model) - Loss: 3.7266 - Accuracy: 0.8571 - F1: 0.8568
sub_5:Test (Best Model) - Loss: 2.8944 - Accuracy: 0.8690 - F1: 0.8689
sub_5:Test (Best Model) - Loss: 3.7420 - Accuracy: 0.8810 - F1: 0.8803
sub_5:Test (Best Model) - Loss: 5.9180 - Accuracy: 0.8690 - F1: 0.8686
sub_5:Test (Best Model) - Loss: 3.8773 - Accuracy: 0.9048 - F1: 0.9045
sub_5:Test (Best Model) - Loss: 5.7611 - Accuracy: 0.8095 - F1: 0.8094
sub_6:Test (Best Model) - Loss: 7.0109 - Accuracy: 0.6786 - F1: 0.6763
sub_6:Test (Best Model) - Loss: 7.0818 - Accuracy: 0.7024 - F1: 0.6989
sub_6:Test (Best Model) - Loss: 10.8131 - Accuracy: 0.6429 - F1: 0.6377
sub_6:Test (Best Model) - Loss: 9.6374 - Accuracy: 0.6429 - F1: 0.6377
sub_6:Test (Best Model) - Loss: 8.8421 - Accuracy: 0.6429 - F1: 0.6429
sub_6:Test (Best Model) - Loss: 14.3217 - Accuracy: 0.6786 - F1: 0.6612
sub_6:Test (Best Model) - Loss: 8.4037 - Accuracy: 0.7262 - F1: 0.7230
sub_6:Test (Best Model) - Loss: 7.3940 - Accuracy: 0.7500 - F1: 0.7491
sub_6:Test (Best Model) - Loss: 4.8522 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 4.8365 - Accuracy: 0.7024 - F1: 0.7003
sub_6:Test (Best Model) - Loss: 7.0311 - Accuracy: 0.6310 - F1: 0.5884
sub_6:Test (Best Model) - Loss: 5.4534 - Accuracy: 0.7619 - F1: 0.7569
sub_6:Test (Best Model) - Loss: 4.0841 - Accuracy: 0.7262 - F1: 0.7243
sub_6:Test (Best Model) - Loss: 9.2488 - Accuracy: 0.5000 - F1: 0.4974
sub_6:Test (Best Model) - Loss: 6.5791 - Accuracy: 0.7143 - F1: 0.7102
sub_7:Test (Best Model) - Loss: 16.9037 - Accuracy: 0.6548 - F1: 0.6080
sub_7:Test (Best Model) - Loss: 9.1967 - Accuracy: 0.6310 - F1: 0.6111
sub_7:Test (Best Model) - Loss: 14.7320 - Accuracy: 0.6548 - F1: 0.6463
sub_7:Test (Best Model) - Loss: 13.1304 - Accuracy: 0.6905 - F1: 0.6788
sub_7:Test (Best Model) - Loss: 7.4128 - Accuracy: 0.5833 - F1: 0.5609
sub_7:Test (Best Model) - Loss: 4.0233 - Accuracy: 0.6548 - F1: 0.6317
sub_7:Test (Best Model) - Loss: 6.0564 - Accuracy: 0.6905 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 8.1575 - Accuracy: 0.5952 - F1: 0.5950
sub_7:Test (Best Model) - Loss: 11.2346 - Accuracy: 0.6667 - F1: 0.6650
sub_7:Test (Best Model) - Loss: 7.5839 - Accuracy: 0.5833 - F1: 0.5609
sub_7:Test (Best Model) - Loss: 6.8547 - Accuracy: 0.5952 - F1: 0.5837
sub_7:Test (Best Model) - Loss: 10.3229 - Accuracy: 0.6667 - F1: 0.6506
sub_7:Test (Best Model) - Loss: 12.0678 - Accuracy: 0.6310 - F1: 0.5884
sub_7:Test (Best Model) - Loss: 8.7188 - Accuracy: 0.6667 - F1: 0.6650
sub_7:Test (Best Model) - Loss: 8.5819 - Accuracy: 0.5714 - F1: 0.5553
sub_8:Test (Best Model) - Loss: 7.5636 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 26.2157 - Accuracy: 0.7976 - F1: 0.7927
sub_8:Test (Best Model) - Loss: 14.6215 - Accuracy: 0.8333 - F1: 0.8309
sub_8:Test (Best Model) - Loss: 8.1346 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 8.9222 - Accuracy: 0.8929 - F1: 0.8921
sub_8:Test (Best Model) - Loss: 7.5715 - Accuracy: 0.8214 - F1: 0.8155
sub_8:Test (Best Model) - Loss: 1.0426 - Accuracy: 0.9048 - F1: 0.9045
sub_8:Test (Best Model) - Loss: 4.1278 - Accuracy: 0.8452 - F1: 0.8414
sub_8:Test (Best Model) - Loss: 5.0575 - Accuracy: 0.8452 - F1: 0.8447
sub_8:Test (Best Model) - Loss: 2.7566 - Accuracy: 0.9048 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.0613 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 6.7078 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.5325 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 1.7433 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 2.6200 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 4.7575 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 5.3991 - Accuracy: 0.8214 - F1: 0.8170
sub_9:Test (Best Model) - Loss: 13.3059 - Accuracy: 0.6786 - F1: 0.6525
sub_9:Test (Best Model) - Loss: 36.4365 - Accuracy: 0.6190 - F1: 0.5544
sub_9:Test (Best Model) - Loss: 9.4431 - Accuracy: 0.6667 - F1: 0.6313
sub_9:Test (Best Model) - Loss: 6.3544 - Accuracy: 0.7500 - F1: 0.7456
sub_9:Test (Best Model) - Loss: 5.4509 - Accuracy: 0.8333 - F1: 0.8332
sub_9:Test (Best Model) - Loss: 7.0458 - Accuracy: 0.7857 - F1: 0.7838
sub_9:Test (Best Model) - Loss: 5.2993 - Accuracy: 0.8095 - F1: 0.8041
sub_9:Test (Best Model) - Loss: 3.5251 - Accuracy: 0.8333 - F1: 0.8309
sub_9:Test (Best Model) - Loss: 20.0293 - Accuracy: 0.6429 - F1: 0.5906
sub_9:Test (Best Model) - Loss: 22.5959 - Accuracy: 0.7262 - F1: 0.7040
sub_9:Test (Best Model) - Loss: 24.8584 - Accuracy: 0.6667 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 27.2419 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 24.9987 - Accuracy: 0.6190 - F1: 0.5544
sub_10:Test (Best Model) - Loss: 4.6632 - Accuracy: 0.6786 - F1: 0.6782
sub_10:Test (Best Model) - Loss: 6.4874 - Accuracy: 0.7143 - F1: 0.7141
sub_10:Test (Best Model) - Loss: 6.1815 - Accuracy: 0.7262 - F1: 0.7172
sub_10:Test (Best Model) - Loss: 9.1252 - Accuracy: 0.5714 - F1: 0.5399
sub_10:Test (Best Model) - Loss: 6.6717 - Accuracy: 0.7024 - F1: 0.6897
sub_10:Test (Best Model) - Loss: 9.1034 - Accuracy: 0.6905 - F1: 0.6898
sub_10:Test (Best Model) - Loss: 9.6796 - Accuracy: 0.6667 - F1: 0.6665
sub_10:Test (Best Model) - Loss: 8.0826 - Accuracy: 0.6548 - F1: 0.6150
sub_10:Test (Best Model) - Loss: 3.9834 - Accuracy: 0.6667 - F1: 0.6597
sub_10:Test (Best Model) - Loss: 8.4584 - Accuracy: 0.6548 - F1: 0.6434
sub_10:Test (Best Model) - Loss: 5.3105 - Accuracy: 0.5357 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 2.4506 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 6.5514 - Accuracy: 0.7857 - F1: 0.7838
sub_10:Test (Best Model) - Loss: 11.7352 - Accuracy: 0.6667 - F1: 0.6421
sub_10:Test (Best Model) - Loss: 8.0804 - Accuracy: 0.7500 - F1: 0.7393
sub_11:Test (Best Model) - Loss: 14.5258 - Accuracy: 0.6429 - F1: 0.6427
sub_11:Test (Best Model) - Loss: 10.6415 - Accuracy: 0.6667 - F1: 0.6619
sub_11:Test (Best Model) - Loss: 6.0822 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 29.8478 - Accuracy: 0.5357 - F1: 0.4081
sub_11:Test (Best Model) - Loss: 8.3772 - Accuracy: 0.7381 - F1: 0.7326
sub_11:Test (Best Model) - Loss: 2.3708 - Accuracy: 0.8095 - F1: 0.8095
sub_11:Test (Best Model) - Loss: 7.2505 - Accuracy: 0.7619 - F1: 0.7597
sub_11:Test (Best Model) - Loss: 3.6762 - Accuracy: 0.8214 - F1: 0.8202
sub_11:Test (Best Model) - Loss: 3.5059 - Accuracy: 0.8095 - F1: 0.8085
sub_11:Test (Best Model) - Loss: 4.1491 - Accuracy: 0.8690 - F1: 0.8690
sub_11:Test (Best Model) - Loss: 3.1965 - Accuracy: 0.7857 - F1: 0.7857
sub_11:Test (Best Model) - Loss: 7.4993 - Accuracy: 0.7738 - F1: 0.7722
sub_11:Test (Best Model) - Loss: 2.9506 - Accuracy: 0.7857 - F1: 0.7776
sub_11:Test (Best Model) - Loss: 5.9869 - Accuracy: 0.8333 - F1: 0.8318
sub_11:Test (Best Model) - Loss: 5.9015 - Accuracy: 0.7381 - F1: 0.7306
sub_12:Test (Best Model) - Loss: 7.1825 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 2.9619 - Accuracy: 0.8810 - F1: 0.8799
sub_12:Test (Best Model) - Loss: 2.6349 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 3.9084 - Accuracy: 0.8810 - F1: 0.8799
sub_12:Test (Best Model) - Loss: 4.5727 - Accuracy: 0.8333 - F1: 0.8330
sub_12:Test (Best Model) - Loss: 18.3563 - Accuracy: 0.7619 - F1: 0.7529
sub_12:Test (Best Model) - Loss: 23.1040 - Accuracy: 0.7024 - F1: 0.6783
sub_12:Test (Best Model) - Loss: 14.0692 - Accuracy: 0.7262 - F1: 0.7145
sub_12:Test (Best Model) - Loss: 23.0335 - Accuracy: 0.7143 - F1: 0.6932
sub_12:Test (Best Model) - Loss: 7.2255 - Accuracy: 0.8214 - F1: 0.8183
sub_12:Test (Best Model) - Loss: 5.0322 - Accuracy: 0.7976 - F1: 0.7927
sub_12:Test (Best Model) - Loss: 14.7531 - Accuracy: 0.6667 - F1: 0.6250
sub_12:Test (Best Model) - Loss: 8.0026 - Accuracy: 0.7976 - F1: 0.7890
sub_12:Test (Best Model) - Loss: 3.7832 - Accuracy: 0.8452 - F1: 0.8452
sub_12:Test (Best Model) - Loss: 11.8772 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 6.4474 - Accuracy: 0.6548 - F1: 0.6212
sub_13:Test (Best Model) - Loss: 3.2816 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 4.8618 - Accuracy: 0.7262 - F1: 0.7252
sub_13:Test (Best Model) - Loss: 7.4335 - Accuracy: 0.6429 - F1: 0.6166
sub_13:Test (Best Model) - Loss: 9.5733 - Accuracy: 0.7024 - F1: 0.6897
sub_13:Test (Best Model) - Loss: 13.5819 - Accuracy: 0.6429 - F1: 0.6166
sub_13:Test (Best Model) - Loss: 6.0640 - Accuracy: 0.7262 - F1: 0.7258
sub_13:Test (Best Model) - Loss: 6.9867 - Accuracy: 0.7500 - F1: 0.7491
sub_13:Test (Best Model) - Loss: 9.5664 - Accuracy: 0.7024 - F1: 0.7020
sub_13:Test (Best Model) - Loss: 12.0977 - Accuracy: 0.6667 - F1: 0.6636
sub_13:Test (Best Model) - Loss: 5.8170 - Accuracy: 0.6429 - F1: 0.5982
sub_13:Test (Best Model) - Loss: 5.8956 - Accuracy: 0.7619 - F1: 0.7569
sub_13:Test (Best Model) - Loss: 6.0060 - Accuracy: 0.7381 - F1: 0.7306
sub_13:Test (Best Model) - Loss: 2.2665 - Accuracy: 0.7976 - F1: 0.7962
sub_13:Test (Best Model) - Loss: 9.7339 - Accuracy: 0.7381 - F1: 0.7255
sub_14:Test (Best Model) - Loss: 5.5691 - Accuracy: 0.8095 - F1: 0.8056
sub_14:Test (Best Model) - Loss: 1.4615 - Accuracy: 0.9048 - F1: 0.9048
sub_14:Test (Best Model) - Loss: 0.9436 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 1.2510 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 2.0522 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 1.8959 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 1.5718 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 1.8505 - Accuracy: 0.8810 - F1: 0.8799
sub_14:Test (Best Model) - Loss: 1.8749 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 1.7288 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 14.6819 - Accuracy: 0.7262 - F1: 0.7040
sub_14:Test (Best Model) - Loss: 3.4364 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 3.0790 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 14.3222 - Accuracy: 0.6667 - F1: 0.6250
sub_14:Test (Best Model) - Loss: 7.0966 - Accuracy: 0.8452 - F1: 0.8414

=== Summary Results ===

acc: 75.79 ± 7.98
F1: 74.47 ± 8.79
acc-in: 86.07 ± 6.80
F1-in: 85.74 ± 7.15
