lr: 1e-06
sub_9:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6190 - F1: 0.5910
sub_10:Test (Best Model) - Loss: 0.7406 - Accuracy: 0.3929 - F1: 0.3107
sub_7:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4286 - F1: 0.4282
sub_5:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.4048 - F1: 0.3761
sub_6:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5476 - F1: 0.4815
sub_4:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5238 - F1: 0.4887
sub_8:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5238 - F1: 0.5102
sub_12:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5833 - F1: 0.5785
sub_1:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5833 - F1: 0.5556
sub_11:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.4524 - F1: 0.4260
sub_2:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5476 - F1: 0.5466
sub_3:Test (Best Model) - Loss: 0.7066 - Accuracy: 0.4167 - F1: 0.4126
sub_14:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5833 - F1: 0.5496
sub_6:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.6429 - F1: 0.6427
sub_5:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.4405 - F1: 0.4166
sub_4:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4524 - F1: 0.4121
sub_7:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4405 - F1: 0.4220
sub_13:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4405 - F1: 0.3760
sub_8:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.7381 - F1: 0.7375
sub_12:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.4286 - F1: 0.4011
sub_10:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5357 - F1: 0.4239
sub_9:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5833 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.6310 - F1: 0.6284
sub_6:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5714 - F1: 0.5179
sub_4:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.7024 - F1: 0.6951
sub_14:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5833 - F1: 0.5833
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5714 - F1: 0.5457
sub_10:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6429 - F1: 0.6294
sub_13:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4524 - F1: 0.3451
sub_12:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.7976 - F1: 0.7953
sub_8:Test (Best Model) - Loss: 0.6493 - Accuracy: 0.7500 - F1: 0.7483
sub_11:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.4405 - F1: 0.3648
sub_14:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.7738 - F1: 0.7712
sub_4:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4762 - F1: 0.4612
sub_9:Test (Best Model) - Loss: 0.7261 - Accuracy: 0.2976 - F1: 0.2951
sub_7:Test (Best Model) - Loss: 0.6688 - Accuracy: 0.5952 - F1: 0.5524
sub_3:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7619 - F1: 0.7597
sub_1:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.7619 - F1: 0.7619
sub_2:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5833 - F1: 0.5428
sub_11:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5357 - F1: 0.5204
sub_10:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5476 - F1: 0.5411
sub_8:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5476 - F1: 0.5466
sub_12:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.4405 - F1: 0.4404
sub_3:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5357 - F1: 0.4510
sub_14:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.3571 - F1: 0.3329
sub_13:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.7262 - F1: 0.7252
sub_7:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.3810 - F1: 0.3576
sub_10:Test (Best Model) - Loss: 0.7161 - Accuracy: 0.3929 - F1: 0.3524
sub_4:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5476 - F1: 0.4911
sub_2:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6786 - F1: 0.6473
sub_12:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5476 - F1: 0.5258
sub_1:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5476 - F1: 0.4997
sub_3:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.7738 - F1: 0.7712
sub_7:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4286 - F1: 0.4233
sub_8:Test (Best Model) - Loss: 0.7336 - Accuracy: 0.3095 - F1: 0.2763
sub_5:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.4643 - F1: 0.4642
sub_13:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4524 - F1: 0.4511
sub_9:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.6310 - F1: 0.6010
sub_11:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5357 - F1: 0.5276
sub_14:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5357 - F1: 0.4510
sub_6:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6071 - F1: 0.6003
sub_12:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.4857
sub_5:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5952 - F1: 0.5800
sub_9:Test (Best Model) - Loss: 0.7238 - Accuracy: 0.3690 - F1: 0.3350
sub_7:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.3810 - F1: 0.3154
sub_1:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.5952 - F1: 0.5943
sub_14:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.2143 - F1: 0.1847
sub_3:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5238 - F1: 0.4305
sub_12:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5476 - F1: 0.5474
sub_2:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4167 - F1: 0.4166
sub_10:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4524 - F1: 0.4524
sub_4:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.3810 - F1: 0.3806
sub_7:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.4812
sub_5:Test (Best Model) - Loss: 0.7376 - Accuracy: 0.1905 - F1: 0.1900
sub_8:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4524 - F1: 0.4496
sub_13:Test (Best Model) - Loss: 0.6733 - Accuracy: 0.5595 - F1: 0.4791
sub_12:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.4881 - F1: 0.4863
sub_9:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5833 - F1: 0.5696
sub_2:Test (Best Model) - Loss: 0.7079 - Accuracy: 0.3810 - F1: 0.3778
sub_6:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.4881 - F1: 0.4662
sub_11:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.7381 - F1: 0.7343
sub_1:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.3571 - F1: 0.3438
sub_10:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 0.7185 - Accuracy: 0.4762 - F1: 0.3736
sub_2:Test (Best Model) - Loss: 0.7331 - Accuracy: 0.2024 - F1: 0.1828
sub_14:Test (Best Model) - Loss: 0.6893 - Accuracy: 0.5714 - F1: 0.5625
sub_5:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.6548 - F1: 0.6543
sub_6:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4881 - F1: 0.4845
sub_3:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5000 - F1: 0.3875
sub_13:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4405 - F1: 0.4307
sub_8:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.7229 - Accuracy: 0.2976 - F1: 0.2508
sub_10:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4048 - F1: 0.3519
sub_4:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.4881 - F1: 0.4540
sub_7:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.6071 - F1: 0.5540
sub_12:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.5119 - F1: 0.4459
sub_6:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.5833 - F1: 0.5833
sub_2:Test (Best Model) - Loss: 0.6802 - Accuracy: 0.6548 - F1: 0.6268
sub_8:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.7024 - F1: 0.7023
sub_4:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6310 - F1: 0.6063
sub_14:Test (Best Model) - Loss: 0.6827 - Accuracy: 0.5357 - F1: 0.4625
sub_1:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.7262 - F1: 0.7214
sub_2:Test (Best Model) - Loss: 0.6663 - Accuracy: 0.7381 - F1: 0.7343
sub_3:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.3810 - F1: 0.3753
sub_5:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5119 - F1: 0.5085
sub_8:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.7381 - F1: 0.7357
sub_12:Test (Best Model) - Loss: 0.7425 - Accuracy: 0.1310 - F1: 0.1308
sub_9:Test (Best Model) - Loss: 0.6586 - Accuracy: 0.7619 - F1: 0.7607
sub_7:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.4286 - F1: 0.4204
sub_2:Test (Best Model) - Loss: 0.6821 - Accuracy: 0.5714 - F1: 0.4750
sub_6:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.2381 - F1: 0.2222
sub_11:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5357 - F1: 0.5107
sub_13:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5357 - F1: 0.5341
sub_3:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5714 - F1: 0.5712
sub_14:Test (Best Model) - Loss: 0.6664 - Accuracy: 0.7500 - F1: 0.7497
sub_4:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5714 - F1: 0.4750
sub_12:Test (Best Model) - Loss: 0.6638 - Accuracy: 0.7500 - F1: 0.7483
sub_5:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6905 - F1: 0.6898
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5119 - F1: 0.5062
sub_1:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4881 - F1: 0.4712
sub_10:Test (Best Model) - Loss: 0.7401 - Accuracy: 0.1667 - F1: 0.1662
sub_4:Test (Best Model) - Loss: 0.7088 - Accuracy: 0.3452 - F1: 0.3451
sub_9:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.6786 - F1: 0.6473
sub_3:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.4881 - F1: 0.4755
sub_13:Test (Best Model) - Loss: 0.7268 - Accuracy: 0.3571 - F1: 0.2768
sub_2:Test (Best Model) - Loss: 0.7413 - Accuracy: 0.1786 - F1: 0.1515
sub_5:Test (Best Model) - Loss: 0.7280 - Accuracy: 0.2262 - F1: 0.2072
sub_11:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5952 - F1: 0.5915
sub_8:Test (Best Model) - Loss: 0.7585 - Accuracy: 0.0595 - F1: 0.0594
sub_12:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.5952 - F1: 0.5654
sub_14:Test (Best Model) - Loss: 0.7432 - Accuracy: 0.1548 - F1: 0.1537
sub_6:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.4881 - F1: 0.4662
sub_1:Test (Best Model) - Loss: 0.6839 - Accuracy: 0.4762 - F1: 0.4510
sub_2:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6310 - F1: 0.6309
sub_13:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6548 - F1: 0.6523
sub_4:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6071 - F1: 0.6066
sub_5:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5595 - F1: 0.5518
sub_6:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4286 - F1: 0.4282
sub_10:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.6190 - F1: 0.6188
sub_9:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.4643 - F1: 0.4026
sub_7:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.4405 - F1: 0.3861
sub_3:Test (Best Model) - Loss: 0.7325 - Accuracy: 0.3095 - F1: 0.2587
sub_13:Test (Best Model) - Loss: 0.7276 - Accuracy: 0.2857 - F1: 0.2513
sub_6:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.5952 - F1: 0.5915
sub_1:Test (Best Model) - Loss: 0.7370 - Accuracy: 0.2857 - F1: 0.2331
sub_10:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.4524 - F1: 0.3723
sub_4:Test (Best Model) - Loss: 0.7211 - Accuracy: 0.2619 - F1: 0.2602
sub_14:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5833 - F1: 0.5819
sub_3:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.7262 - F1: 0.7258
sub_11:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.3452 - F1: 0.3338
sub_7:Test (Best Model) - Loss: 0.6741 - Accuracy: 0.7381 - F1: 0.7379
sub_5:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.3095 - F1: 0.2898
sub_12:Test (Best Model) - Loss: 0.7163 - Accuracy: 0.3810 - F1: 0.2759
sub_10:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5119 - F1: 0.4645
sub_8:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6071 - F1: 0.5810
sub_14:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4524 - F1: 0.4524
sub_2:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.4881 - F1: 0.3649
sub_11:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6667 - F1: 0.6466
sub_5:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.6190 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.7436 - Accuracy: 0.2619 - F1: 0.2581
sub_4:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.6071 - F1: 0.5975
sub_8:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6310 - F1: 0.5728
sub_7:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5714 - F1: 0.5712
sub_13:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.7738 - F1: 0.7683
sub_6:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5238 - F1: 0.4952
sub_14:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5119 - F1: 0.5085
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4762 - F1: 0.4207
sub_9:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5238 - F1: 0.5139
sub_6:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.4524 - F1: 0.3594
sub_4:Test (Best Model) - Loss: 0.7320 - Accuracy: 0.2857 - F1: 0.2857
sub_1:Test (Best Model) - Loss: 0.6761 - Accuracy: 0.5714 - F1: 0.5675
sub_5:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6905 - F1: 0.6898
sub_2:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.4762 - F1: 0.4750
sub_7:Test (Best Model) - Loss: 0.7134 - Accuracy: 0.3690 - F1: 0.3617
sub_10:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4524 - F1: 0.3451
sub_8:Test (Best Model) - Loss: 0.7035 - Accuracy: 0.4048 - F1: 0.4048
sub_13:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.8690 - F1: 0.8689
sub_3:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5238 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 0.7233 - Accuracy: 0.3810 - F1: 0.3259
sub_12:Test (Best Model) - Loss: 0.6371 - Accuracy: 0.7619 - F1: 0.7569
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5357 - F1: 0.5325
sub_1:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4405 - F1: 0.3523
sub_14:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.4048 - F1: 0.3761
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5476 - F1: 0.4312
sub_2:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.6548 - F1: 0.6400
sub_14:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4405 - F1: 0.4166
sub_3:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.4286 - F1: 0.4256
sub_2:Test (Best Model) - Loss: 0.7114 - Accuracy: 0.4286 - F1: 0.3680
sub_5:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4881 - F1: 0.4291
sub_1:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.7024 - F1: 0.6825
sub_13:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.2738 - F1: 0.2347
sub_3:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.5238 - F1: 0.4887
sub_8:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5476 - F1: 0.4815
sub_8:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6667 - F1: 0.6466
sub_11:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5357 - F1: 0.5341
sub_9:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.7381 - F1: 0.7343
sub_13:Test (Best Model) - Loss: 0.7299 - Accuracy: 0.2500 - F1: 0.2499
sub_1:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5119 - F1: 0.4645
sub_13:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.8571 - F1: 0.8551
sub_11:Test (Best Model) - Loss: 0.6952 - Accuracy: 0.5119 - F1: 0.5062
sub_1:Test (Best Model) - Loss: 0.6549 - Accuracy: 0.7143 - F1: 0.7141
sub_11:Test (Best Model) - Loss: 0.7459 - Accuracy: 0.3095 - F1: 0.3091
sub_9:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.6071 - F1: 0.5540
sub_9:Test (Best Model) - Loss: 0.7179 - Accuracy: 0.3214 - F1: 0.2924
sub_9:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.4762 - F1: 0.4714
sub_9:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.4167 - F1: 0.3975

=== Summary Results ===

acc: 51.61 ± 2.41
F1: 49.11 ± 2.88
acc-in: 55.70 ± 3.70
F1-in: 54.93 ± 3.81
