lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.2828 - Accuracy: 0.7381 - F1: 0.7224
sub_1:Test (Best Model) - Loss: 1.3524 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 1.2746 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 1.1032 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 1.2008 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 1.1137 - Accuracy: 0.7262 - F1: 0.7258
sub_1:Test (Best Model) - Loss: 0.5810 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.7976 - F1: 0.7974
sub_1:Test (Best Model) - Loss: 0.8360 - Accuracy: 0.7738 - F1: 0.7735
sub_1:Test (Best Model) - Loss: 0.7226 - Accuracy: 0.7381 - F1: 0.7381
sub_1:Test (Best Model) - Loss: 0.8945 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.9659 - Accuracy: 0.6667 - F1: 0.6250
sub_1:Test (Best Model) - Loss: 0.8326 - Accuracy: 0.6905 - F1: 0.6577
sub_1:Test (Best Model) - Loss: 0.9447 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 1.0574 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.7457 - Accuracy: 0.7262 - F1: 0.7195
sub_2:Test (Best Model) - Loss: 0.5752 - Accuracy: 0.7738 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 0.8219 - Accuracy: 0.6905 - F1: 0.6903
sub_2:Test (Best Model) - Loss: 0.6156 - Accuracy: 0.7500 - F1: 0.7439
sub_2:Test (Best Model) - Loss: 0.7013 - Accuracy: 0.6786 - F1: 0.6525
sub_2:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.7500 - F1: 0.7483
sub_2:Test (Best Model) - Loss: 0.4371 - Accuracy: 0.7738 - F1: 0.7699
sub_2:Test (Best Model) - Loss: 0.4654 - Accuracy: 0.7738 - F1: 0.7730
sub_2:Test (Best Model) - Loss: 0.4099 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.7799 - Accuracy: 0.7262 - F1: 0.7258
sub_2:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.7500 - F1: 0.7491
sub_2:Test (Best Model) - Loss: 0.7180 - Accuracy: 0.7381 - F1: 0.7379
sub_2:Test (Best Model) - Loss: 0.5273 - Accuracy: 0.7381 - F1: 0.7375
sub_2:Test (Best Model) - Loss: 0.9025 - Accuracy: 0.7262 - F1: 0.7252
sub_3:Test (Best Model) - Loss: 1.4747 - Accuracy: 0.5714 - F1: 0.5179
sub_3:Test (Best Model) - Loss: 1.3042 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 1.0507 - Accuracy: 0.5952 - F1: 0.5446
sub_3:Test (Best Model) - Loss: 1.1949 - Accuracy: 0.5714 - F1: 0.5260
sub_3:Test (Best Model) - Loss: 1.4449 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.7262 - F1: 0.7252
sub_3:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.7143 - F1: 0.7136
sub_3:Test (Best Model) - Loss: 0.8171 - Accuracy: 0.6548 - F1: 0.6547
sub_3:Test (Best Model) - Loss: 0.7270 - Accuracy: 0.7024 - F1: 0.7023
sub_3:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.7262 - F1: 0.7252
sub_3:Test (Best Model) - Loss: 1.1352 - Accuracy: 0.6548 - F1: 0.6080
sub_3:Test (Best Model) - Loss: 1.1921 - Accuracy: 0.6310 - F1: 0.5728
sub_3:Test (Best Model) - Loss: 1.1672 - Accuracy: 0.6548 - F1: 0.6150
sub_3:Test (Best Model) - Loss: 0.7956 - Accuracy: 0.6667 - F1: 0.6421
sub_3:Test (Best Model) - Loss: 0.9563 - Accuracy: 0.6905 - F1: 0.6577
sub_4:Test (Best Model) - Loss: 1.0266 - Accuracy: 0.6310 - F1: 0.6309
sub_4:Test (Best Model) - Loss: 1.2827 - Accuracy: 0.4881 - F1: 0.4863
sub_4:Test (Best Model) - Loss: 1.0823 - Accuracy: 0.6071 - F1: 0.6044
sub_4:Test (Best Model) - Loss: 1.1253 - Accuracy: 0.6310 - F1: 0.6284
sub_4:Test (Best Model) - Loss: 0.9340 - Accuracy: 0.6429 - F1: 0.6396
sub_4:Test (Best Model) - Loss: 1.0071 - Accuracy: 0.6190 - F1: 0.6156
sub_4:Test (Best Model) - Loss: 0.5834 - Accuracy: 0.7143 - F1: 0.7102
sub_4:Test (Best Model) - Loss: 0.8556 - Accuracy: 0.6905 - F1: 0.6898
sub_4:Test (Best Model) - Loss: 0.7830 - Accuracy: 0.7024 - F1: 0.7013
sub_4:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.7262 - F1: 0.7243
sub_4:Test (Best Model) - Loss: 0.8125 - Accuracy: 0.6548 - F1: 0.6535
sub_4:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.7143 - F1: 0.7141
sub_4:Test (Best Model) - Loss: 0.5855 - Accuracy: 0.7619 - F1: 0.7619
sub_4:Test (Best Model) - Loss: 0.9810 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 0.8308 - Accuracy: 0.6429 - F1: 0.6429
sub_5:Test (Best Model) - Loss: 0.4804 - Accuracy: 0.7857 - F1: 0.7856
sub_5:Test (Best Model) - Loss: 0.5410 - Accuracy: 0.7262 - F1: 0.7258
sub_5:Test (Best Model) - Loss: 0.4764 - Accuracy: 0.7738 - F1: 0.7738
sub_5:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.6905 - F1: 0.6860
sub_5:Test (Best Model) - Loss: 0.4879 - Accuracy: 0.7381 - F1: 0.7375
sub_5:Test (Best Model) - Loss: 0.5310 - Accuracy: 0.7857 - F1: 0.7826
sub_5:Test (Best Model) - Loss: 0.4646 - Accuracy: 0.7619 - F1: 0.7607
sub_5:Test (Best Model) - Loss: 0.5703 - Accuracy: 0.7262 - F1: 0.7252
sub_5:Test (Best Model) - Loss: 0.5631 - Accuracy: 0.7500 - F1: 0.7491
sub_5:Test (Best Model) - Loss: 0.4578 - Accuracy: 0.7976 - F1: 0.7962
sub_5:Test (Best Model) - Loss: 0.4117 - Accuracy: 0.7976 - F1: 0.7962
sub_5:Test (Best Model) - Loss: 0.4271 - Accuracy: 0.8095 - F1: 0.8094
sub_5:Test (Best Model) - Loss: 0.4146 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 0.5314 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.6786 - F1: 0.6774
sub_6:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.5595 - F1: 0.5564
sub_6:Test (Best Model) - Loss: 1.0066 - Accuracy: 0.5952 - F1: 0.5952
sub_6:Test (Best Model) - Loss: 1.3633 - Accuracy: 0.6429 - F1: 0.6410
sub_6:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.5833 - F1: 0.5828
sub_6:Test (Best Model) - Loss: 1.3226 - Accuracy: 0.5833 - F1: 0.5819
sub_6:Test (Best Model) - Loss: 0.8828 - Accuracy: 0.7024 - F1: 0.7020
sub_6:Test (Best Model) - Loss: 1.0735 - Accuracy: 0.6190 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.6548 - F1: 0.6547
sub_6:Test (Best Model) - Loss: 1.2803 - Accuracy: 0.6071 - F1: 0.6044
sub_6:Test (Best Model) - Loss: 0.9047 - Accuracy: 0.6310 - F1: 0.6267
sub_6:Test (Best Model) - Loss: 0.8815 - Accuracy: 0.6310 - F1: 0.6305
sub_6:Test (Best Model) - Loss: 1.0643 - Accuracy: 0.6429 - F1: 0.6429
sub_6:Test (Best Model) - Loss: 0.8368 - Accuracy: 0.6667 - F1: 0.6650
sub_6:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.5119 - F1: 0.5085
sub_6:Test (Best Model) - Loss: 1.0216 - Accuracy: 0.5833 - F1: 0.5833
sub_7:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.6786 - F1: 0.6774
sub_7:Test (Best Model) - Loss: 1.0145 - Accuracy: 0.5595 - F1: 0.5590
sub_7:Test (Best Model) - Loss: 0.9273 - Accuracy: 0.7143 - F1: 0.7102
sub_7:Test (Best Model) - Loss: 1.0742 - Accuracy: 0.6071 - F1: 0.6026
sub_7:Test (Best Model) - Loss: 1.0307 - Accuracy: 0.6310 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 0.9269 - Accuracy: 0.5595 - F1: 0.5487
sub_7:Test (Best Model) - Loss: 0.8753 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 0.8814 - Accuracy: 0.6190 - F1: 0.6136
sub_7:Test (Best Model) - Loss: 1.1230 - Accuracy: 0.5000 - F1: 0.4812
sub_7:Test (Best Model) - Loss: 0.8338 - Accuracy: 0.5714 - F1: 0.5592
sub_7:Test (Best Model) - Loss: 0.8553 - Accuracy: 0.5714 - F1: 0.5712
sub_7:Test (Best Model) - Loss: 0.9742 - Accuracy: 0.5952 - F1: 0.5932
sub_7:Test (Best Model) - Loss: 0.8431 - Accuracy: 0.6429 - F1: 0.6410
sub_7:Test (Best Model) - Loss: 0.8959 - Accuracy: 0.6310 - F1: 0.6296
sub_7:Test (Best Model) - Loss: 1.0111 - Accuracy: 0.5476 - F1: 0.5411
sub_8:Test (Best Model) - Loss: 0.5086 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.8214 - F1: 0.8208
sub_8:Test (Best Model) - Loss: 0.5024 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.8214 - F1: 0.8202
sub_8:Test (Best Model) - Loss: 0.4709 - Accuracy: 0.8095 - F1: 0.8091
sub_8:Test (Best Model) - Loss: 0.5393 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.5300 - Accuracy: 0.7619 - F1: 0.7614
sub_8:Test (Best Model) - Loss: 0.4586 - Accuracy: 0.7738 - F1: 0.7735
sub_8:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.5454 - Accuracy: 0.7500 - F1: 0.7500
sub_8:Test (Best Model) - Loss: 0.3653 - Accuracy: 0.8810 - F1: 0.8809
sub_8:Test (Best Model) - Loss: 0.3310 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.3331 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.3146 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.5531 - Accuracy: 0.7500 - F1: 0.7491
sub_9:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.7143 - F1: 0.7102
sub_9:Test (Best Model) - Loss: 0.7172 - Accuracy: 0.6667 - F1: 0.6636
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 0.9435 - Accuracy: 0.6548 - F1: 0.6523
sub_9:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.7619 - F1: 0.7585
sub_9:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.7500 - F1: 0.7483
sub_9:Test (Best Model) - Loss: 0.8132 - Accuracy: 0.7024 - F1: 0.7023
sub_9:Test (Best Model) - Loss: 0.7363 - Accuracy: 0.7024 - F1: 0.7020
sub_9:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.7381 - F1: 0.7381
sub_9:Test (Best Model) - Loss: 0.6752 - Accuracy: 0.7500 - F1: 0.7491
sub_9:Test (Best Model) - Loss: 0.7256 - Accuracy: 0.6429 - F1: 0.6166
sub_9:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.7262 - F1: 0.7114
sub_9:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.7143 - F1: 0.6971
sub_9:Test (Best Model) - Loss: 0.6146 - Accuracy: 0.7143 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.7143 - F1: 0.6889
sub_10:Test (Best Model) - Loss: 0.8653 - Accuracy: 0.6310 - F1: 0.6296
sub_10:Test (Best Model) - Loss: 0.8372 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 0.9201 - Accuracy: 0.6429 - F1: 0.6354
sub_10:Test (Best Model) - Loss: 0.9544 - Accuracy: 0.6548 - F1: 0.6535
sub_10:Test (Best Model) - Loss: 0.7760 - Accuracy: 0.6786 - F1: 0.6785
sub_10:Test (Best Model) - Loss: 0.8538 - Accuracy: 0.5952 - F1: 0.5932
sub_10:Test (Best Model) - Loss: 0.8323 - Accuracy: 0.6071 - F1: 0.6044
sub_10:Test (Best Model) - Loss: 1.0240 - Accuracy: 0.5714 - F1: 0.5692
sub_10:Test (Best Model) - Loss: 0.8229 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.9421 - Accuracy: 0.6429 - F1: 0.6427
sub_10:Test (Best Model) - Loss: 0.8337 - Accuracy: 0.7143 - F1: 0.7083
sub_10:Test (Best Model) - Loss: 0.6550 - Accuracy: 0.7024 - F1: 0.7020
sub_10:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.7262 - F1: 0.7230
sub_10:Test (Best Model) - Loss: 0.9150 - Accuracy: 0.7143 - F1: 0.7061
sub_10:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.9583 - Accuracy: 0.5238 - F1: 0.5235
sub_11:Test (Best Model) - Loss: 1.0802 - Accuracy: 0.5952 - F1: 0.5915
sub_11:Test (Best Model) - Loss: 1.0740 - Accuracy: 0.5476 - F1: 0.5466
sub_11:Test (Best Model) - Loss: 1.1014 - Accuracy: 0.5000 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.8627 - Accuracy: 0.6667 - F1: 0.6597
sub_11:Test (Best Model) - Loss: 0.4649 - Accuracy: 0.8095 - F1: 0.8094
sub_11:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.6548 - F1: 0.6547
sub_11:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.6905 - F1: 0.6876
sub_11:Test (Best Model) - Loss: 0.8000 - Accuracy: 0.6667 - F1: 0.6667
sub_11:Test (Best Model) - Loss: 0.8186 - Accuracy: 0.7143 - F1: 0.7128
sub_11:Test (Best Model) - Loss: 0.8427 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.8603 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.7908 - Accuracy: 0.6786 - F1: 0.6782
sub_11:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.7262 - F1: 0.7262
sub_11:Test (Best Model) - Loss: 0.8288 - Accuracy: 0.7024 - F1: 0.7023
sub_12:Test (Best Model) - Loss: 0.7396 - Accuracy: 0.6786 - F1: 0.6774
sub_12:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.7500 - F1: 0.7497
sub_12:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.7738 - F1: 0.7712
sub_12:Test (Best Model) - Loss: 0.4173 - Accuracy: 0.8095 - F1: 0.8078
sub_12:Test (Best Model) - Loss: 0.4503 - Accuracy: 0.8214 - F1: 0.8212
sub_12:Test (Best Model) - Loss: 1.0656 - Accuracy: 0.7024 - F1: 0.6897
sub_12:Test (Best Model) - Loss: 0.9469 - Accuracy: 0.6786 - F1: 0.6525
sub_12:Test (Best Model) - Loss: 1.2280 - Accuracy: 0.7024 - F1: 0.6783
sub_12:Test (Best Model) - Loss: 1.1146 - Accuracy: 0.7381 - F1: 0.7255
sub_12:Test (Best Model) - Loss: 1.0880 - Accuracy: 0.7262 - F1: 0.7114
sub_12:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.7262 - F1: 0.7195
sub_12:Test (Best Model) - Loss: 0.7876 - Accuracy: 0.6667 - F1: 0.6636
sub_12:Test (Best Model) - Loss: 0.5695 - Accuracy: 0.7381 - F1: 0.7357
sub_12:Test (Best Model) - Loss: 0.7637 - Accuracy: 0.6905 - F1: 0.6898
sub_12:Test (Best Model) - Loss: 0.8876 - Accuracy: 0.6548 - F1: 0.6463
sub_13:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.7143 - F1: 0.7117
sub_13:Test (Best Model) - Loss: 0.8151 - Accuracy: 0.7143 - F1: 0.7061
sub_13:Test (Best Model) - Loss: 0.6006 - Accuracy: 0.7381 - F1: 0.7357
sub_13:Test (Best Model) - Loss: 0.7271 - Accuracy: 0.7262 - F1: 0.7230
sub_13:Test (Best Model) - Loss: 0.8197 - Accuracy: 0.7024 - F1: 0.6972
sub_13:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.6905 - F1: 0.6840
sub_13:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.5704 - Accuracy: 0.7857 - F1: 0.7852
sub_13:Test (Best Model) - Loss: 0.5257 - Accuracy: 0.8095 - F1: 0.8091
sub_13:Test (Best Model) - Loss: 0.8144 - Accuracy: 0.7262 - F1: 0.7230
sub_13:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.7500 - F1: 0.7456
sub_13:Test (Best Model) - Loss: 0.5275 - Accuracy: 0.7857 - F1: 0.7812
sub_13:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.7857 - F1: 0.7812
sub_13:Test (Best Model) - Loss: 0.6142 - Accuracy: 0.8095 - F1: 0.8056
sub_14:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.7968 - Accuracy: 0.7262 - F1: 0.7243
sub_14:Test (Best Model) - Loss: 0.6562 - Accuracy: 0.7262 - F1: 0.7258
sub_14:Test (Best Model) - Loss: 0.7841 - Accuracy: 0.7024 - F1: 0.7023
sub_14:Test (Best Model) - Loss: 0.8929 - Accuracy: 0.7381 - F1: 0.7343
sub_14:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.7381 - F1: 0.7368
sub_14:Test (Best Model) - Loss: 0.8509 - Accuracy: 0.7619 - F1: 0.7569
sub_14:Test (Best Model) - Loss: 0.7598 - Accuracy: 0.6429 - F1: 0.6327
sub_14:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.7619 - F1: 0.7614
sub_14:Test (Best Model) - Loss: 0.5048 - Accuracy: 0.7738 - F1: 0.7722
sub_14:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.7381 - F1: 0.7282
sub_14:Test (Best Model) - Loss: 0.4380 - Accuracy: 0.7976 - F1: 0.7962
sub_14:Test (Best Model) - Loss: 0.7622 - Accuracy: 0.6310 - F1: 0.6267
sub_14:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.6786 - F1: 0.6680

=== Summary Results ===

acc: 69.95 ± 5.75
F1: 69.30 ± 5.95
acc-in: 75.32 ± 6.52
F1-in: 75.04 ± 6.63
