lr: 1e-06
sub_1:Test (Best Model) - Loss: 0.5778 - Accuracy: 0.6548 - F1: 0.6487
sub_1:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.6667 - F1: 0.6506
sub_1:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.6429 - F1: 0.6377
sub_1:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.6190 - F1: 0.6182
sub_1:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6071 - F1: 0.6026
sub_1:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.7381 - F1: 0.7343
sub_1:Test (Best Model) - Loss: 0.5435 - Accuracy: 0.7738 - F1: 0.7683
sub_1:Test (Best Model) - Loss: 0.5178 - Accuracy: 0.7976 - F1: 0.7969
sub_1:Test (Best Model) - Loss: 0.5269 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 0.5423 - Accuracy: 0.7500 - F1: 0.7471
sub_1:Test (Best Model) - Loss: 0.5338 - Accuracy: 0.7024 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.5624 - Accuracy: 0.7024 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.5063 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.5871 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.5319 - Accuracy: 0.7143 - F1: 0.6889
sub_2:Test (Best Model) - Loss: 0.5953 - Accuracy: 0.6548 - F1: 0.6150
sub_2:Test (Best Model) - Loss: 0.5518 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.5335 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.5698 - Accuracy: 0.7500 - F1: 0.7456
sub_2:Test (Best Model) - Loss: 0.5094 - Accuracy: 0.7857 - F1: 0.7826
sub_2:Test (Best Model) - Loss: 0.4954 - Accuracy: 0.6667 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.5370 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.5350 - Accuracy: 0.6548 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 0.5043 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 0.5285 - Accuracy: 0.6548 - F1: 0.6080
sub_2:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.7381 - F1: 0.7224
sub_2:Test (Best Model) - Loss: 0.5189 - Accuracy: 0.7143 - F1: 0.6932
sub_2:Test (Best Model) - Loss: 0.5048 - Accuracy: 0.7738 - F1: 0.7641
sub_2:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8690 - F1: 0.8675
sub_2:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.6190 - F1: 0.5634
sub_3:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.6071 - F1: 0.5452
sub_3:Test (Best Model) - Loss: 0.6028 - Accuracy: 0.6190 - F1: 0.5714
sub_3:Test (Best Model) - Loss: 0.6644 - Accuracy: 0.5833 - F1: 0.5270
sub_3:Test (Best Model) - Loss: 0.6505 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.6137 - Accuracy: 0.7024 - F1: 0.7020
sub_3:Test (Best Model) - Loss: 0.5666 - Accuracy: 0.7143 - F1: 0.7136
sub_3:Test (Best Model) - Loss: 0.6227 - Accuracy: 0.6310 - F1: 0.6267
sub_3:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.6429 - F1: 0.6354
sub_3:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.7024 - F1: 0.7013
sub_3:Test (Best Model) - Loss: 0.5972 - Accuracy: 0.7143 - F1: 0.6932
sub_3:Test (Best Model) - Loss: 0.5718 - Accuracy: 0.7619 - F1: 0.7529
sub_3:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.7024 - F1: 0.6825
sub_3:Test (Best Model) - Loss: 0.5936 - Accuracy: 0.7024 - F1: 0.6897
sub_3:Test (Best Model) - Loss: 0.5798 - Accuracy: 0.7262 - F1: 0.7114
sub_4:Test (Best Model) - Loss: 0.6288 - Accuracy: 0.6429 - F1: 0.6354
sub_4:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.6667 - F1: 0.6665
sub_4:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.6667 - F1: 0.6665
sub_4:Test (Best Model) - Loss: 0.6144 - Accuracy: 0.6548 - F1: 0.6547
sub_4:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.6667 - F1: 0.6659
sub_4:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.6548 - F1: 0.6361
sub_4:Test (Best Model) - Loss: 0.5732 - Accuracy: 0.7262 - F1: 0.7172
sub_4:Test (Best Model) - Loss: 0.6207 - Accuracy: 0.6548 - F1: 0.6463
sub_4:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.7143 - F1: 0.7128
sub_4:Test (Best Model) - Loss: 0.6355 - Accuracy: 0.6429 - F1: 0.6257
sub_4:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.5476 - F1: 0.4312
sub_4:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.5595 - F1: 0.4535
sub_4:Test (Best Model) - Loss: 0.6466 - Accuracy: 0.5595 - F1: 0.4791
sub_4:Test (Best Model) - Loss: 0.6038 - Accuracy: 0.5714 - F1: 0.4875
sub_4:Test (Best Model) - Loss: 0.6117 - Accuracy: 0.6429 - F1: 0.5906
sub_5:Test (Best Model) - Loss: 0.5054 - Accuracy: 0.8214 - F1: 0.8208
sub_5:Test (Best Model) - Loss: 0.5301 - Accuracy: 0.7381 - F1: 0.7282
sub_5:Test (Best Model) - Loss: 0.5937 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.5924 - Accuracy: 0.7262 - F1: 0.7195
sub_5:Test (Best Model) - Loss: 0.6026 - Accuracy: 0.6310 - F1: 0.5810
sub_5:Test (Best Model) - Loss: 0.5457 - Accuracy: 0.6905 - F1: 0.6630
sub_5:Test (Best Model) - Loss: 0.6273 - Accuracy: 0.6190 - F1: 0.5634
sub_5:Test (Best Model) - Loss: 0.5468 - Accuracy: 0.7262 - F1: 0.7195
sub_5:Test (Best Model) - Loss: 0.5534 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 0.5909 - Accuracy: 0.6310 - F1: 0.5951
sub_5:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.6905 - F1: 0.6677
sub_5:Test (Best Model) - Loss: 0.5099 - Accuracy: 0.7619 - F1: 0.7529
sub_5:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.6429 - F1: 0.6111
sub_5:Test (Best Model) - Loss: 0.5182 - Accuracy: 0.7024 - F1: 0.6825
sub_5:Test (Best Model) - Loss: 0.5948 - Accuracy: 0.6905 - F1: 0.6840
sub_6:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5357 - F1: 0.5204
sub_6:Test (Best Model) - Loss: 0.6304 - Accuracy: 0.6310 - F1: 0.6267
sub_6:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.5952 - F1: 0.5915
sub_6:Test (Best Model) - Loss: 0.6731 - Accuracy: 0.5714 - F1: 0.5675
sub_6:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.6429 - F1: 0.6427
sub_6:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.5952 - F1: 0.5894
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6071 - F1: 0.5942
sub_6:Test (Best Model) - Loss: 0.6361 - Accuracy: 0.6190 - F1: 0.6182
sub_6:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.6667 - F1: 0.6597
sub_6:Test (Best Model) - Loss: 0.6085 - Accuracy: 0.7143 - F1: 0.7136
sub_6:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.5476 - F1: 0.5382
sub_6:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6190 - F1: 0.6156
sub_6:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.6905 - F1: 0.6898
sub_6:Test (Best Model) - Loss: 0.6717 - Accuracy: 0.6429 - F1: 0.6410
sub_6:Test (Best Model) - Loss: 0.6263 - Accuracy: 0.6786 - F1: 0.6785
sub_7:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.6429 - F1: 0.6420
sub_7:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5238 - F1: 0.5059
sub_7:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.6429 - F1: 0.6354
sub_7:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5119 - F1: 0.5085
sub_7:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.5357 - F1: 0.5243
sub_7:Test (Best Model) - Loss: 0.6654 - Accuracy: 0.6071 - F1: 0.5860
sub_7:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.6190 - F1: 0.6007
sub_7:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5357 - F1: 0.5204
sub_7:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.6667 - F1: 0.6619
sub_7:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.5952 - F1: 0.5524
sub_7:Test (Best Model) - Loss: 0.6417 - Accuracy: 0.5714 - F1: 0.5457
sub_7:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5238 - F1: 0.5214
sub_7:Test (Best Model) - Loss: 0.6591 - Accuracy: 0.5952 - F1: 0.5932
sub_7:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4881 - F1: 0.4880
sub_7:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.6190 - F1: 0.5962
sub_8:Test (Best Model) - Loss: 0.4402 - Accuracy: 0.8214 - F1: 0.8214
sub_8:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.4275 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.5210 - Accuracy: 0.7857 - F1: 0.7846
sub_8:Test (Best Model) - Loss: 0.4652 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.4182 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.4729 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.5430 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.3867 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.4446 - Accuracy: 0.7976 - F1: 0.7890
sub_8:Test (Best Model) - Loss: 0.5450 - Accuracy: 0.6667 - F1: 0.6250
sub_8:Test (Best Model) - Loss: 0.4826 - Accuracy: 0.7619 - F1: 0.7504
sub_8:Test (Best Model) - Loss: 0.4514 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 0.4931 - Accuracy: 0.7738 - F1: 0.7641
sub_9:Test (Best Model) - Loss: 0.5519 - Accuracy: 0.7024 - F1: 0.7003
sub_9:Test (Best Model) - Loss: 0.5916 - Accuracy: 0.7262 - F1: 0.7214
sub_9:Test (Best Model) - Loss: 0.5728 - Accuracy: 0.7738 - F1: 0.7735
sub_9:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7143 - F1: 0.7141
sub_9:Test (Best Model) - Loss: 0.5673 - Accuracy: 0.7976 - F1: 0.7962
sub_9:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.6905 - F1: 0.6788
sub_9:Test (Best Model) - Loss: 0.6187 - Accuracy: 0.6429 - F1: 0.6327
sub_9:Test (Best Model) - Loss: 0.6168 - Accuracy: 0.6548 - F1: 0.6487
sub_9:Test (Best Model) - Loss: 0.5632 - Accuracy: 0.7381 - F1: 0.7326
sub_9:Test (Best Model) - Loss: 0.5363 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.5952 - F1: 0.5265
sub_9:Test (Best Model) - Loss: 0.6056 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.7143 - F1: 0.6971
sub_9:Test (Best Model) - Loss: 0.6166 - Accuracy: 0.7024 - F1: 0.6926
sub_9:Test (Best Model) - Loss: 0.5537 - Accuracy: 0.6548 - F1: 0.6080
sub_10:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6429 - F1: 0.6327
sub_10:Test (Best Model) - Loss: 0.6798 - Accuracy: 0.5714 - F1: 0.5712
sub_10:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.6429 - F1: 0.6429
sub_10:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 0.6341 - Accuracy: 0.5952 - F1: 0.5950
sub_10:Test (Best Model) - Loss: 0.6673 - Accuracy: 0.5357 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 0.6824 - Accuracy: 0.5595 - F1: 0.5564
sub_10:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.5952 - F1: 0.5894
sub_10:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.5714 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.6548 - F1: 0.6523
sub_10:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5833 - F1: 0.5828
sub_10:Test (Best Model) - Loss: 0.6403 - Accuracy: 0.6310 - F1: 0.6284
sub_10:Test (Best Model) - Loss: 0.6198 - Accuracy: 0.6905 - F1: 0.6903
sub_10:Test (Best Model) - Loss: 0.6816 - Accuracy: 0.5595 - F1: 0.5564
sub_10:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.6548 - F1: 0.6508
sub_11:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.6071 - F1: 0.5540
sub_11:Test (Best Model) - Loss: 0.6773 - Accuracy: 0.5476 - F1: 0.4815
sub_11:Test (Best Model) - Loss: 0.6241 - Accuracy: 0.6071 - F1: 0.6026
sub_11:Test (Best Model) - Loss: 0.6668 - Accuracy: 0.6071 - F1: 0.6071
sub_11:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.7024 - F1: 0.6951
sub_11:Test (Best Model) - Loss: 0.6415 - Accuracy: 0.6190 - F1: 0.5544
sub_11:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.5952 - F1: 0.5800
sub_11:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.6310 - F1: 0.6245
sub_11:Test (Best Model) - Loss: 0.5785 - Accuracy: 0.6905 - F1: 0.6860
sub_11:Test (Best Model) - Loss: 0.6073 - Accuracy: 0.7024 - F1: 0.6972
sub_11:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5357 - F1: 0.5107
sub_11:Test (Best Model) - Loss: 0.6331 - Accuracy: 0.6548 - F1: 0.6463
sub_11:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.6905 - F1: 0.6788
sub_11:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.6786 - F1: 0.6730
sub_11:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6429 - F1: 0.6354
sub_12:Test (Best Model) - Loss: 0.6098 - Accuracy: 0.6905 - F1: 0.6898
sub_12:Test (Best Model) - Loss: 0.5310 - Accuracy: 0.8214 - F1: 0.8212
sub_12:Test (Best Model) - Loss: 0.5821 - Accuracy: 0.7857 - F1: 0.7846
sub_12:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.7738 - F1: 0.7738
sub_12:Test (Best Model) - Loss: 0.5883 - Accuracy: 0.7262 - F1: 0.7258
sub_12:Test (Best Model) - Loss: 0.5796 - Accuracy: 0.7619 - F1: 0.7551
sub_12:Test (Best Model) - Loss: 0.5720 - Accuracy: 0.7143 - F1: 0.7035
sub_12:Test (Best Model) - Loss: 0.5949 - Accuracy: 0.7381 - F1: 0.7224
sub_12:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.7024 - F1: 0.6989
sub_12:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.6905 - F1: 0.6788
sub_12:Test (Best Model) - Loss: 0.5331 - Accuracy: 0.7024 - F1: 0.6825
sub_12:Test (Best Model) - Loss: 0.5396 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 0.5493 - Accuracy: 0.6667 - F1: 0.6506
sub_12:Test (Best Model) - Loss: 0.5285 - Accuracy: 0.7976 - F1: 0.7953
sub_12:Test (Best Model) - Loss: 0.5535 - Accuracy: 0.7143 - F1: 0.7005
sub_13:Test (Best Model) - Loss: 0.6381 - Accuracy: 0.6310 - F1: 0.6305
sub_13:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.6548 - F1: 0.6543
sub_13:Test (Best Model) - Loss: 0.6199 - Accuracy: 0.6548 - F1: 0.6535
sub_13:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.6905 - F1: 0.6898
sub_13:Test (Best Model) - Loss: 0.5833 - Accuracy: 0.7738 - F1: 0.7730
sub_13:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.6071 - F1: 0.6071
sub_13:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.7619 - F1: 0.7618
sub_13:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.7262 - F1: 0.7262
sub_13:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.7500 - F1: 0.7439
sub_13:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.6667 - F1: 0.6619
sub_13:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.7262 - F1: 0.7258
sub_13:Test (Best Model) - Loss: 0.5862 - Accuracy: 0.7024 - F1: 0.6897
sub_13:Test (Best Model) - Loss: 0.6006 - Accuracy: 0.7143 - F1: 0.7117
sub_14:Test (Best Model) - Loss: 0.5800 - Accuracy: 0.6667 - F1: 0.6370
sub_14:Test (Best Model) - Loss: 0.4872 - Accuracy: 0.7500 - F1: 0.7439
sub_14:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.7976 - F1: 0.7941
sub_14:Test (Best Model) - Loss: 0.5030 - Accuracy: 0.7619 - F1: 0.7585
sub_14:Test (Best Model) - Loss: 0.5731 - Accuracy: 0.6310 - F1: 0.6063
sub_14:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.7143 - F1: 0.6971
sub_14:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.6786 - F1: 0.6525
sub_14:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.7024 - F1: 0.6783
sub_14:Test (Best Model) - Loss: 0.4710 - Accuracy: 0.8095 - F1: 0.8068
sub_14:Test (Best Model) - Loss: 0.4336 - Accuracy: 0.7976 - F1: 0.7910
sub_14:Test (Best Model) - Loss: 0.5218 - Accuracy: 0.7738 - F1: 0.7738
sub_14:Test (Best Model) - Loss: 0.5431 - Accuracy: 0.7738 - F1: 0.7699
sub_14:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.5833 - F1: 0.5428
sub_14:Test (Best Model) - Loss: 0.5497 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.6044 - Accuracy: 0.6786 - F1: 0.6648

=== Summary Results ===

acc: 68.42 ± 6.14
F1: 67.03 ± 6.34
acc-in: 73.10 ± 6.08
F1-in: 72.25 ± 6.20
