lr: 1e-06
sub_6:Test (Best Model) - Loss: 1.0822 - Accuracy: 0.5119 - F1: 0.3778
sub_13:Test (Best Model) - Loss: 1.1973 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6173 - Accuracy: 0.7024 - F1: 0.6825
sub_7:Test (Best Model) - Loss: 0.9304 - Accuracy: 0.5476 - F1: 0.5306
sub_10:Test (Best Model) - Loss: 0.8910 - Accuracy: 0.5357 - F1: 0.4081
sub_11:Test (Best Model) - Loss: 1.3561 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.5955 - Accuracy: 0.7143 - F1: 0.7117
sub_2:Test (Best Model) - Loss: 0.5644 - Accuracy: 0.7262 - F1: 0.7172
sub_13:Test (Best Model) - Loss: 0.5482 - Accuracy: 0.7619 - F1: 0.7614
sub_5:Test (Best Model) - Loss: 0.7297 - Accuracy: 0.5833 - F1: 0.5609
sub_3:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.5476 - F1: 0.4590
sub_12:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.6310 - F1: 0.6219
sub_9:Test (Best Model) - Loss: 1.0557 - Accuracy: 0.4881 - F1: 0.3649
sub_8:Test (Best Model) - Loss: 0.3708 - Accuracy: 0.8333 - F1: 0.8325
sub_14:Test (Best Model) - Loss: 0.5483 - Accuracy: 0.6667 - F1: 0.6466
sub_5:Test (Best Model) - Loss: 0.8485 - Accuracy: 0.5119 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.7489 - Accuracy: 0.5595 - F1: 0.5407
sub_1:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.6071 - F1: 0.5540
sub_13:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.6548 - F1: 0.6212
sub_7:Test (Best Model) - Loss: 0.6500 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.9510 - Accuracy: 0.5238 - F1: 0.4167
sub_10:Test (Best Model) - Loss: 0.4257 - Accuracy: 0.7976 - F1: 0.7962
sub_3:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.7738 - F1: 0.7641
sub_11:Test (Best Model) - Loss: 0.5195 - Accuracy: 0.7500 - F1: 0.7471
sub_8:Test (Best Model) - Loss: 0.8804 - Accuracy: 0.4048 - F1: 0.3519
sub_14:Test (Best Model) - Loss: 0.7723 - Accuracy: 0.5714 - F1: 0.5692
sub_2:Test (Best Model) - Loss: 0.4737 - Accuracy: 0.8333 - F1: 0.8333
sub_13:Test (Best Model) - Loss: 0.9081 - Accuracy: 0.3571 - F1: 0.3329
sub_1:Test (Best Model) - Loss: 0.6120 - Accuracy: 0.6786 - F1: 0.6612
sub_4:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.6667 - F1: 0.6619
sub_5:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.6429 - F1: 0.6294
sub_9:Test (Best Model) - Loss: 0.4116 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.5912 - Accuracy: 0.6429 - F1: 0.6214
sub_7:Test (Best Model) - Loss: 0.7808 - Accuracy: 0.5714 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 1.1729 - Accuracy: 0.3452 - F1: 0.3237
sub_14:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6429 - F1: 0.6377
sub_3:Test (Best Model) - Loss: 0.6127 - Accuracy: 0.6667 - F1: 0.6665
sub_13:Test (Best Model) - Loss: 1.1734 - Accuracy: 0.3571 - F1: 0.2632
sub_1:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.5595 - F1: 0.4791
sub_5:Test (Best Model) - Loss: 0.8107 - Accuracy: 0.5119 - F1: 0.4999
sub_3:Test (Best Model) - Loss: 0.6159 - Accuracy: 0.6429 - F1: 0.6377
sub_11:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.8333 - F1: 0.8299
sub_6:Test (Best Model) - Loss: 0.3137 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.3609 - Accuracy: 0.8095 - F1: 0.8024
sub_2:Test (Best Model) - Loss: 0.8303 - Accuracy: 0.6548 - F1: 0.6080
sub_7:Test (Best Model) - Loss: 0.8018 - Accuracy: 0.5833 - F1: 0.5353
sub_14:Test (Best Model) - Loss: 0.7696 - Accuracy: 0.6429 - F1: 0.5982
sub_4:Test (Best Model) - Loss: 0.8037 - Accuracy: 0.5714 - F1: 0.5675
sub_3:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.7024 - F1: 0.7003
sub_9:Test (Best Model) - Loss: 0.2370 - Accuracy: 0.9405 - F1: 0.9404
sub_13:Test (Best Model) - Loss: 0.3802 - Accuracy: 0.8571 - F1: 0.8558
sub_12:Test (Best Model) - Loss: 0.4508 - Accuracy: 0.7738 - F1: 0.7738
sub_5:Test (Best Model) - Loss: 0.9391 - Accuracy: 0.5000 - F1: 0.4375
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.6429 - F1: 0.6166
sub_6:Test (Best Model) - Loss: 0.4027 - Accuracy: 0.8571 - F1: 0.8571
sub_1:Test (Best Model) - Loss: 0.4533 - Accuracy: 0.7738 - F1: 0.7722
sub_2:Test (Best Model) - Loss: 0.4768 - Accuracy: 0.7738 - F1: 0.7735
sub_14:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6310 - F1: 0.6305
sub_8:Test (Best Model) - Loss: 0.2530 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.6667 - F1: 0.6597
sub_7:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.5952 - F1: 0.5265
sub_1:Test (Best Model) - Loss: 0.7434 - Accuracy: 0.5714 - F1: 0.5692
sub_4:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5952 - F1: 0.5524
sub_5:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.7024 - F1: 0.7013
sub_7:Test (Best Model) - Loss: 0.5849 - Accuracy: 0.7024 - F1: 0.7020
sub_9:Test (Best Model) - Loss: 0.5006 - Accuracy: 0.7857 - F1: 0.7812
sub_3:Test (Best Model) - Loss: 0.5149 - Accuracy: 0.7619 - F1: 0.7569
sub_5:Test (Best Model) - Loss: 0.8984 - Accuracy: 0.4405 - F1: 0.3861
sub_13:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.5952 - F1: 0.5758
sub_14:Test (Best Model) - Loss: 0.4601 - Accuracy: 0.7619 - F1: 0.7597
sub_12:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.7976 - F1: 0.7953
sub_6:Test (Best Model) - Loss: 0.7580 - Accuracy: 0.5833 - F1: 0.5428
sub_8:Test (Best Model) - Loss: 0.3014 - Accuracy: 0.8690 - F1: 0.8681
sub_4:Test (Best Model) - Loss: 0.5649 - Accuracy: 0.7500 - F1: 0.7471
sub_5:Test (Best Model) - Loss: 0.5664 - Accuracy: 0.7024 - F1: 0.6897
sub_11:Test (Best Model) - Loss: 0.3133 - Accuracy: 0.8929 - F1: 0.8927
sub_14:Test (Best Model) - Loss: 0.5932 - Accuracy: 0.6548 - F1: 0.6543
sub_7:Test (Best Model) - Loss: 0.7301 - Accuracy: 0.6190 - F1: 0.6111
sub_10:Test (Best Model) - Loss: 0.4328 - Accuracy: 0.7738 - F1: 0.7616
sub_13:Test (Best Model) - Loss: 0.6399 - Accuracy: 0.6548 - F1: 0.6535
sub_9:Test (Best Model) - Loss: 0.1771 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.7980 - Accuracy: 0.5119 - F1: 0.4958
sub_1:Test (Best Model) - Loss: 0.5155 - Accuracy: 0.7381 - F1: 0.7306
sub_6:Test (Best Model) - Loss: 0.9404 - Accuracy: 0.5000 - F1: 0.4700
sub_12:Test (Best Model) - Loss: 0.6032 - Accuracy: 0.6905 - F1: 0.6816
sub_3:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6310 - F1: 0.6284
sub_5:Test (Best Model) - Loss: 0.9080 - Accuracy: 0.5357 - F1: 0.4510
sub_4:Test (Best Model) - Loss: 0.6349 - Accuracy: 0.7024 - F1: 0.7013
sub_10:Test (Best Model) - Loss: 0.4570 - Accuracy: 0.8214 - F1: 0.8194
sub_11:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.7619 - F1: 0.7585
sub_7:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6786 - F1: 0.6571
sub_8:Test (Best Model) - Loss: 0.1440 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.4839 - Accuracy: 0.7619 - F1: 0.7476
sub_6:Test (Best Model) - Loss: 0.6863 - Accuracy: 0.5595 - F1: 0.5088
sub_13:Test (Best Model) - Loss: 0.4382 - Accuracy: 0.7738 - F1: 0.7664
sub_14:Test (Best Model) - Loss: 0.5605 - Accuracy: 0.6667 - F1: 0.6466
sub_10:Test (Best Model) - Loss: 0.8217 - Accuracy: 0.4762 - F1: 0.4750
sub_9:Test (Best Model) - Loss: 0.6229 - Accuracy: 0.6667 - F1: 0.6650
sub_3:Test (Best Model) - Loss: 0.7371 - Accuracy: 0.6429 - F1: 0.6327
sub_12:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.6667 - F1: 0.6541
sub_5:Test (Best Model) - Loss: 0.5701 - Accuracy: 0.7024 - F1: 0.7003
sub_7:Test (Best Model) - Loss: 0.4905 - Accuracy: 0.7381 - F1: 0.7306
sub_1:Test (Best Model) - Loss: 0.5434 - Accuracy: 0.6786 - F1: 0.6612
sub_8:Test (Best Model) - Loss: 0.4516 - Accuracy: 0.7857 - F1: 0.7796
sub_6:Test (Best Model) - Loss: 0.6203 - Accuracy: 0.7262 - F1: 0.7040
sub_5:Test (Best Model) - Loss: 1.0611 - Accuracy: 0.4762 - F1: 0.3873
sub_11:Test (Best Model) - Loss: 0.2002 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5833 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.9217 - Accuracy: 0.4643 - F1: 0.4209
sub_3:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.6310 - F1: 0.6245
sub_4:Test (Best Model) - Loss: 0.4402 - Accuracy: 0.7738 - F1: 0.7712
sub_14:Test (Best Model) - Loss: 0.4061 - Accuracy: 0.8095 - F1: 0.8041
sub_2:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.8095 - F1: 0.8056
sub_1:Test (Best Model) - Loss: 0.4667 - Accuracy: 0.8214 - F1: 0.8194
sub_7:Test (Best Model) - Loss: 0.7199 - Accuracy: 0.5952 - F1: 0.5709
sub_10:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.7976 - F1: 0.7976
sub_4:Test (Best Model) - Loss: 0.5330 - Accuracy: 0.7024 - F1: 0.7013
sub_9:Test (Best Model) - Loss: 0.4328 - Accuracy: 0.7857 - F1: 0.7754
sub_14:Test (Best Model) - Loss: 0.7648 - Accuracy: 0.5595 - F1: 0.5450
sub_13:Test (Best Model) - Loss: 0.7691 - Accuracy: 0.5595 - F1: 0.5487
sub_5:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.7381 - F1: 0.7306
sub_11:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.7976 - F1: 0.7910
sub_12:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.9048 - F1: 0.9045
sub_8:Test (Best Model) - Loss: 0.4063 - Accuracy: 0.8571 - F1: 0.8564
sub_14:Test (Best Model) - Loss: 1.0121 - Accuracy: 0.4286 - F1: 0.3571
sub_7:Test (Best Model) - Loss: 0.9543 - Accuracy: 0.5357 - F1: 0.4081
sub_2:Test (Best Model) - Loss: 0.3193 - Accuracy: 0.8571 - F1: 0.8558
sub_3:Test (Best Model) - Loss: 0.5348 - Accuracy: 0.6548 - F1: 0.6150
sub_7:Test (Best Model) - Loss: 0.7363 - Accuracy: 0.5595 - F1: 0.4791
sub_11:Test (Best Model) - Loss: 0.4860 - Accuracy: 0.7857 - F1: 0.7776
sub_9:Test (Best Model) - Loss: 0.3172 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.9200 - Accuracy: 0.4167 - F1: 0.4099
sub_6:Test (Best Model) - Loss: 0.5574 - Accuracy: 0.6786 - F1: 0.6648
sub_13:Test (Best Model) - Loss: 0.3709 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.9315 - Accuracy: 0.4762 - F1: 0.3873
sub_1:Test (Best Model) - Loss: 0.6032 - Accuracy: 0.6905 - F1: 0.6577
sub_9:Test (Best Model) - Loss: 0.4661 - Accuracy: 0.7738 - F1: 0.7699
sub_4:Test (Best Model) - Loss: 0.3469 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.2934 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 0.4832 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 0.5751 - Accuracy: 0.7262 - F1: 0.7195
sub_3:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.3901 - Accuracy: 0.7976 - F1: 0.7927
sub_10:Test (Best Model) - Loss: 1.2437 - Accuracy: 0.5119 - F1: 0.3593
sub_14:Test (Best Model) - Loss: 0.8497 - Accuracy: 0.6071 - F1: 0.5619
sub_6:Test (Best Model) - Loss: 0.5436 - Accuracy: 0.7857 - F1: 0.7826
sub_7:Test (Best Model) - Loss: 1.0006 - Accuracy: 0.3810 - F1: 0.3633
sub_9:Test (Best Model) - Loss: 0.3937 - Accuracy: 0.7857 - F1: 0.7796
sub_11:Test (Best Model) - Loss: 0.3105 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 0.7809 - Accuracy: 0.5714 - F1: 0.5260
sub_1:Test (Best Model) - Loss: 0.5501 - Accuracy: 0.6667 - F1: 0.6659
sub_8:Test (Best Model) - Loss: 0.4821 - Accuracy: 0.7738 - F1: 0.7730
sub_4:Test (Best Model) - Loss: 0.4925 - Accuracy: 0.8095 - F1: 0.8056
sub_5:Test (Best Model) - Loss: 0.8724 - Accuracy: 0.5714 - F1: 0.5457
sub_13:Test (Best Model) - Loss: 0.3105 - Accuracy: 0.8452 - F1: 0.8414
sub_2:Test (Best Model) - Loss: 0.3831 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.5281 - Accuracy: 0.7262 - F1: 0.7214
sub_3:Test (Best Model) - Loss: 0.7049 - Accuracy: 0.5714 - F1: 0.5712
sub_9:Test (Best Model) - Loss: 0.9113 - Accuracy: 0.5119 - F1: 0.4459
sub_12:Test (Best Model) - Loss: 0.4385 - Accuracy: 0.8095 - F1: 0.8068
sub_1:Test (Best Model) - Loss: 0.9241 - Accuracy: 0.3571 - F1: 0.3388
sub_11:Test (Best Model) - Loss: 0.3157 - Accuracy: 0.8690 - F1: 0.8681
sub_6:Test (Best Model) - Loss: 0.6559 - Accuracy: 0.6310 - F1: 0.6219
sub_14:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6548 - F1: 0.6361
sub_10:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.6429 - F1: 0.6111
sub_4:Test (Best Model) - Loss: 0.7154 - Accuracy: 0.4881 - F1: 0.4712
sub_13:Test (Best Model) - Loss: 0.5844 - Accuracy: 0.7143 - F1: 0.7143
sub_13:Test (Best Model) - Loss: 1.1461 - Accuracy: 0.2500 - F1: 0.2253
sub_1:Test (Best Model) - Loss: 0.4303 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.7143 - F1: 0.7083
sub_3:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5952 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8690 - F1: 0.8686
sub_2:Test (Best Model) - Loss: 0.5790 - Accuracy: 0.6905 - F1: 0.6876
sub_9:Test (Best Model) - Loss: 0.5096 - Accuracy: 0.6786 - F1: 0.6707
sub_12:Test (Best Model) - Loss: 0.3804 - Accuracy: 0.8214 - F1: 0.8214
sub_6:Test (Best Model) - Loss: 0.4995 - Accuracy: 0.7619 - F1: 0.7585
sub_14:Test (Best Model) - Loss: 0.6262 - Accuracy: 0.6548 - F1: 0.6080
sub_13:Test (Best Model) - Loss: 0.2949 - Accuracy: 0.9048 - F1: 0.9045
sub_3:Test (Best Model) - Loss: 0.6151 - Accuracy: 0.6310 - F1: 0.6063
sub_11:Test (Best Model) - Loss: 0.4363 - Accuracy: 0.8095 - F1: 0.8078
sub_1:Test (Best Model) - Loss: 0.5989 - Accuracy: 0.6667 - F1: 0.6636
sub_4:Test (Best Model) - Loss: 0.4737 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6190 - F1: 0.5852
sub_9:Test (Best Model) - Loss: 0.5139 - Accuracy: 0.7857 - F1: 0.7776
sub_14:Test (Best Model) - Loss: 0.8199 - Accuracy: 0.5357 - F1: 0.4981
sub_10:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6548 - F1: 0.6317
sub_1:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.7024 - F1: 0.7003
sub_3:Test (Best Model) - Loss: 0.8259 - Accuracy: 0.5000 - F1: 0.4759
sub_2:Test (Best Model) - Loss: 0.4200 - Accuracy: 0.8690 - F1: 0.8675
sub_10:Test (Best Model) - Loss: 0.9867 - Accuracy: 0.5357 - F1: 0.4081
sub_4:Test (Best Model) - Loss: 0.5483 - Accuracy: 0.7619 - F1: 0.7597
sub_11:Test (Best Model) - Loss: 0.4892 - Accuracy: 0.7857 - F1: 0.7838
sub_8:Test (Best Model) - Loss: 0.7605 - Accuracy: 0.5000 - F1: 0.4928
sub_12:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.8679 - Accuracy: 0.4286 - F1: 0.4282
sub_6:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.6190 - F1: 0.6111
sub_4:Test (Best Model) - Loss: 0.7260 - Accuracy: 0.5952 - F1: 0.5709
sub_2:Test (Best Model) - Loss: 0.2835 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.6905 - F1: 0.6840
sub_11:Test (Best Model) - Loss: 0.3209 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.3908 - Accuracy: 0.8571 - F1: 0.8564
sub_4:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.5833 - F1: 0.5828
sub_8:Test (Best Model) - Loss: 0.5376 - Accuracy: 0.7262 - F1: 0.7214
sub_12:Test (Best Model) - Loss: 0.5938 - Accuracy: 0.7024 - F1: 0.6926
sub_2:Test (Best Model) - Loss: 0.4608 - Accuracy: 0.8095 - F1: 0.8094
sub_8:Test (Best Model) - Loss: 0.5612 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.8389 - Accuracy: 0.5595 - F1: 0.4670
sub_12:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.6667 - F1: 0.6541
sub_12:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.8214 - F1: 0.8202

=== Summary Results ===

acc: 68.13 ± 6.92
F1: 66.03 ± 7.76
acc-in: 76.35 ± 8.86
F1-in: 74.52 ± 9.89
