lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.6429 - F1: 0.6427
sub_1:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.6667 - F1: 0.6659
sub_1:Test (Best Model) - Loss: 0.6042 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 0.6026 - Accuracy: 0.6667 - F1: 0.6650
sub_1:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6667 - F1: 0.6650
sub_1:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.6548 - F1: 0.6487
sub_1:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.7024 - F1: 0.7003
sub_1:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.7262 - F1: 0.7258
sub_1:Test (Best Model) - Loss: 0.6176 - Accuracy: 0.6667 - F1: 0.6665
sub_1:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.6190 - F1: 0.5852
sub_1:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.6071 - F1: 0.5753
sub_1:Test (Best Model) - Loss: 0.5716 - Accuracy: 0.6786 - F1: 0.6473
sub_1:Test (Best Model) - Loss: 0.5555 - Accuracy: 0.6786 - F1: 0.6473
sub_1:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.6310 - F1: 0.5728
sub_2:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6310 - F1: 0.6245
sub_2:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.6071 - F1: 0.5942
sub_2:Test (Best Model) - Loss: 0.6219 - Accuracy: 0.6548 - F1: 0.6535
sub_2:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.6786 - F1: 0.6782
sub_2:Test (Best Model) - Loss: 0.6128 - Accuracy: 0.6310 - F1: 0.6305
sub_2:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.6429 - F1: 0.6294
sub_2:Test (Best Model) - Loss: 0.6220 - Accuracy: 0.6071 - F1: 0.5942
sub_2:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.6548 - F1: 0.6434
sub_2:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.7143 - F1: 0.6932
sub_2:Test (Best Model) - Loss: 0.5819 - Accuracy: 0.6190 - F1: 0.5852
sub_2:Test (Best Model) - Loss: 0.6468 - Accuracy: 0.5952 - F1: 0.5932
sub_2:Test (Best Model) - Loss: 0.6569 - Accuracy: 0.6190 - F1: 0.6136
sub_2:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.5833 - F1: 0.5804
sub_2:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.6667 - F1: 0.6597
sub_2:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6548 - F1: 0.6543
sub_3:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.6310 - F1: 0.6267
sub_3:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6071 - F1: 0.5942
sub_3:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.6429 - F1: 0.6294
sub_3:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.6190 - F1: 0.5962
sub_3:Test (Best Model) - Loss: 0.6606 - Accuracy: 0.6667 - F1: 0.6506
sub_3:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.5952 - F1: 0.5943
sub_3:Test (Best Model) - Loss: 0.6345 - Accuracy: 0.6429 - F1: 0.6427
sub_3:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.6190 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.6190 - F1: 0.6188
sub_3:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.6548 - F1: 0.6212
sub_3:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.6429 - F1: 0.6111
sub_3:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.5952 - F1: 0.5654
sub_3:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.6310 - F1: 0.6219
sub_3:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.6786 - F1: 0.6525
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5357 - F1: 0.5303
sub_4:Test (Best Model) - Loss: 0.7328 - Accuracy: 0.4048 - F1: 0.4048
sub_4:Test (Best Model) - Loss: 0.7288 - Accuracy: 0.4762 - F1: 0.4762
sub_4:Test (Best Model) - Loss: 0.7439 - Accuracy: 0.4643 - F1: 0.4581
sub_4:Test (Best Model) - Loss: 0.7076 - Accuracy: 0.5476 - F1: 0.5453
sub_4:Test (Best Model) - Loss: 0.6916 - Accuracy: 0.5119 - F1: 0.4999
sub_4:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.5357 - F1: 0.5159
sub_4:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5476 - F1: 0.5435
sub_4:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.6667 - F1: 0.6665
sub_4:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5238 - F1: 0.5170
sub_4:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5357 - F1: 0.5243
sub_4:Test (Best Model) - Loss: 0.6744 - Accuracy: 0.5714 - F1: 0.5675
sub_4:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.5833 - F1: 0.5819
sub_4:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5595 - F1: 0.5518
sub_4:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.5595 - F1: 0.5564
sub_5:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.6190 - F1: 0.6182
sub_5:Test (Best Model) - Loss: 0.6401 - Accuracy: 0.6786 - F1: 0.6680
sub_5:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6786 - F1: 0.6763
sub_5:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6190 - F1: 0.6136
sub_5:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6190 - F1: 0.5852
sub_5:Test (Best Model) - Loss: 0.6674 - Accuracy: 0.5595 - F1: 0.5358
sub_5:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.5238 - F1: 0.5059
sub_5:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.5714 - F1: 0.5692
sub_5:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.6071 - F1: 0.6003
sub_5:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.6071 - F1: 0.5975
sub_5:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.6190 - F1: 0.6082
sub_5:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.6548 - F1: 0.6361
sub_5:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6786 - F1: 0.6785
sub_5:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.5952 - F1: 0.5894
sub_5:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.5833 - F1: 0.5833
sub_6:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5357 - F1: 0.5325
sub_6:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.5595 - F1: 0.5564
sub_6:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.5476 - F1: 0.5453
sub_6:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.5714 - F1: 0.5705
sub_6:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5238 - F1: 0.5238
sub_6:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5595 - F1: 0.5564
sub_6:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5476 - F1: 0.5411
sub_6:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5595 - F1: 0.5564
sub_6:Test (Best Model) - Loss: 0.6902 - Accuracy: 0.5714 - F1: 0.5692
sub_6:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.5952 - F1: 0.5943
sub_6:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.6071 - F1: 0.6057
sub_6:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5833 - F1: 0.5761
sub_6:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5119 - F1: 0.5118
sub_6:Test (Best Model) - Loss: 0.6993 - Accuracy: 0.5119 - F1: 0.5062
sub_7:Test (Best Model) - Loss: 0.6567 - Accuracy: 0.5833 - F1: 0.5785
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5595 - F1: 0.5238
sub_7:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.6071 - F1: 0.6057
sub_7:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.5952 - F1: 0.5758
sub_7:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.5238 - F1: 0.5227
sub_7:Test (Best Model) - Loss: 0.6763 - Accuracy: 0.5357 - F1: 0.5048
sub_7:Test (Best Model) - Loss: 0.7148 - Accuracy: 0.4405 - F1: 0.4307
sub_7:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.5238 - F1: 0.5227
sub_7:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5714 - F1: 0.5333
sub_7:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5476 - F1: 0.5306
sub_7:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4881 - F1: 0.4755
sub_7:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.5833 - F1: 0.5655
sub_7:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.4989
sub_7:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4762 - F1: 0.4376
sub_8:Test (Best Model) - Loss: 0.5513 - Accuracy: 0.6905 - F1: 0.6905
sub_8:Test (Best Model) - Loss: 0.5090 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.5910 - Accuracy: 0.7262 - F1: 0.7258
sub_8:Test (Best Model) - Loss: 0.5750 - Accuracy: 0.7738 - F1: 0.7738
sub_8:Test (Best Model) - Loss: 0.5443 - Accuracy: 0.6786 - F1: 0.6774
sub_8:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.6786 - F1: 0.6774
sub_8:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.6548 - F1: 0.6487
sub_8:Test (Best Model) - Loss: 0.6006 - Accuracy: 0.6667 - F1: 0.6650
sub_8:Test (Best Model) - Loss: 0.5733 - Accuracy: 0.6667 - F1: 0.6665
sub_8:Test (Best Model) - Loss: 0.6016 - Accuracy: 0.7024 - F1: 0.7013
sub_8:Test (Best Model) - Loss: 0.5534 - Accuracy: 0.7262 - F1: 0.7243
sub_8:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.6905 - F1: 0.6788
sub_8:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.6905 - F1: 0.6876
sub_8:Test (Best Model) - Loss: 0.6112 - Accuracy: 0.6905 - F1: 0.6788
sub_8:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.6905 - F1: 0.6876
sub_9:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.6310 - F1: 0.6284
sub_9:Test (Best Model) - Loss: 0.6218 - Accuracy: 0.6429 - F1: 0.6354
sub_9:Test (Best Model) - Loss: 0.6283 - Accuracy: 0.6786 - F1: 0.6774
sub_9:Test (Best Model) - Loss: 0.6093 - Accuracy: 0.7024 - F1: 0.7023
sub_9:Test (Best Model) - Loss: 0.6281 - Accuracy: 0.7143 - F1: 0.7128
sub_9:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6429 - F1: 0.6354
sub_9:Test (Best Model) - Loss: 0.7183 - Accuracy: 0.6190 - F1: 0.6171
sub_9:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.5714 - F1: 0.5653
sub_9:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.6786 - F1: 0.6785
sub_9:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5357 - F1: 0.5325
sub_9:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.6548 - F1: 0.6317
sub_9:Test (Best Model) - Loss: 0.6524 - Accuracy: 0.6071 - F1: 0.5975
sub_9:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5476 - F1: 0.5411
sub_9:Test (Best Model) - Loss: 0.6748 - Accuracy: 0.5833 - F1: 0.5828
sub_9:Test (Best Model) - Loss: 0.6039 - Accuracy: 0.6786 - F1: 0.6473
sub_10:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5595 - F1: 0.5590
sub_10:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.5595 - F1: 0.5595
sub_10:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5357 - F1: 0.5351
sub_10:Test (Best Model) - Loss: 0.6804 - Accuracy: 0.5714 - F1: 0.5692
sub_10:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.5833 - F1: 0.5833
sub_10:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.5833 - F1: 0.5785
sub_10:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5238 - F1: 0.5139
sub_10:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6310 - F1: 0.6305
sub_10:Test (Best Model) - Loss: 0.6618 - Accuracy: 0.6310 - F1: 0.6309
sub_10:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6214 - Accuracy: 0.6310 - F1: 0.6309
sub_10:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.6548 - F1: 0.6523
sub_10:Test (Best Model) - Loss: 0.6413 - Accuracy: 0.6548 - F1: 0.6434
sub_10:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.6310 - F1: 0.6309
sub_11:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.5595 - F1: 0.5564
sub_11:Test (Best Model) - Loss: 0.7332 - Accuracy: 0.4881 - F1: 0.4712
sub_11:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.5000 - F1: 0.4997
sub_11:Test (Best Model) - Loss: 0.7326 - Accuracy: 0.5119 - F1: 0.5118
sub_11:Test (Best Model) - Loss: 0.6615 - Accuracy: 0.5714 - F1: 0.5712
sub_11:Test (Best Model) - Loss: 0.6575 - Accuracy: 0.5833 - F1: 0.5819
sub_11:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.5714 - F1: 0.5692
sub_11:Test (Best Model) - Loss: 0.6479 - Accuracy: 0.6190 - F1: 0.6171
sub_11:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.6071 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.6667 - F1: 0.6665
sub_11:Test (Best Model) - Loss: 0.7293 - Accuracy: 0.5000 - F1: 0.4954
sub_11:Test (Best Model) - Loss: 0.7250 - Accuracy: 0.5357 - F1: 0.5341
sub_11:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.4643 - F1: 0.4642
sub_11:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.5119 - F1: 0.5102
sub_11:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.5952 - F1: 0.5952
sub_12:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.5238 - F1: 0.5235
sub_12:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.5714 - F1: 0.5705
sub_12:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.5952 - F1: 0.5943
sub_12:Test (Best Model) - Loss: 0.6338 - Accuracy: 0.6905 - F1: 0.6905
sub_12:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.6667 - F1: 0.6597
sub_12:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.5952 - F1: 0.5837
sub_12:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6667 - F1: 0.6466
sub_12:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.7024 - F1: 0.6972
sub_12:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6905 - F1: 0.6840
sub_12:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.5833 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 0.6499 - Accuracy: 0.5476 - F1: 0.5258
sub_12:Test (Best Model) - Loss: 0.6364 - Accuracy: 0.6310 - F1: 0.6152
sub_12:Test (Best Model) - Loss: 0.6416 - Accuracy: 0.6429 - F1: 0.6396
sub_12:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6310 - F1: 0.6152
sub_13:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6548 - F1: 0.6523
sub_13:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.6429 - F1: 0.6257
sub_13:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.6527 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.6635 - Accuracy: 0.6310 - F1: 0.6296
sub_13:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.5476 - F1: 0.5306
sub_13:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.5833 - F1: 0.5696
sub_13:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.6786 - F1: 0.6774
sub_13:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.7024 - F1: 0.7020
sub_13:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.7024 - F1: 0.7013
sub_13:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6310 - F1: 0.6309
sub_13:Test (Best Model) - Loss: 0.6432 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6541 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.6429 - F1: 0.6354
sub_13:Test (Best Model) - Loss: 0.6142 - Accuracy: 0.7024 - F1: 0.7020
sub_14:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6786 - F1: 0.6785
sub_14:Test (Best Model) - Loss: 0.6434 - Accuracy: 0.6548 - F1: 0.6547
sub_14:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.6786 - F1: 0.6782
sub_14:Test (Best Model) - Loss: 0.6385 - Accuracy: 0.6548 - F1: 0.6543
sub_14:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6429 - F1: 0.6427
sub_14:Test (Best Model) - Loss: 0.6443 - Accuracy: 0.6190 - F1: 0.6007
sub_14:Test (Best Model) - Loss: 0.7021 - Accuracy: 0.5595 - F1: 0.5487
sub_14:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.6429 - F1: 0.6294
sub_14:Test (Best Model) - Loss: 0.6351 - Accuracy: 0.6667 - F1: 0.6636
sub_14:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6429 - F1: 0.6294
sub_14:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6071 - F1: 0.6044
sub_14:Test (Best Model) - Loss: 0.6375 - Accuracy: 0.6429 - F1: 0.6420
sub_14:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5833 - F1: 0.5819
sub_14:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.6429 - F1: 0.6377
sub_14:Test (Best Model) - Loss: 0.6713 - Accuracy: 0.5714 - F1: 0.5705

=== Summary Results ===

acc: 61.29 ± 4.76
F1: 60.55 ± 4.77
acc-in: 65.97 ± 4.53
F1-in: 65.27 ± 4.77
