lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.1057 - Accuracy: 0.7024 - F1: 0.6972
sub_3:Test (Best Model) - Loss: 1.9455 - Accuracy: 0.5714 - F1: 0.5179
sub_2:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.8214 - F1: 0.8194
sub_3:Test (Best Model) - Loss: 1.7794 - Accuracy: 0.5833 - F1: 0.5353
sub_1:Test (Best Model) - Loss: 1.0135 - Accuracy: 0.7619 - F1: 0.7614
sub_3:Test (Best Model) - Loss: 1.7435 - Accuracy: 0.5238 - F1: 0.4430
sub_2:Test (Best Model) - Loss: 0.5248 - Accuracy: 0.7143 - F1: 0.6971
sub_1:Test (Best Model) - Loss: 0.9921 - Accuracy: 0.7024 - F1: 0.6989
sub_2:Test (Best Model) - Loss: 0.2911 - Accuracy: 0.9286 - F1: 0.9285
sub_1:Test (Best Model) - Loss: 1.2182 - Accuracy: 0.7143 - F1: 0.7141
sub_3:Test (Best Model) - Loss: 2.7439 - Accuracy: 0.6310 - F1: 0.6063
sub_2:Test (Best Model) - Loss: 0.3940 - Accuracy: 0.7976 - F1: 0.7941
sub_1:Test (Best Model) - Loss: 1.0522 - Accuracy: 0.7262 - F1: 0.7230
sub_1:Test (Best Model) - Loss: 0.5405 - Accuracy: 0.7976 - F1: 0.7962
sub_3:Test (Best Model) - Loss: 3.4250 - Accuracy: 0.6071 - F1: 0.5452
sub_2:Test (Best Model) - Loss: 0.5748 - Accuracy: 0.6786 - F1: 0.6525
sub_2:Test (Best Model) - Loss: 0.6012 - Accuracy: 0.7619 - F1: 0.7569
sub_1:Test (Best Model) - Loss: 1.4427 - Accuracy: 0.8095 - F1: 0.8094
sub_3:Test (Best Model) - Loss: 1.0921 - Accuracy: 0.6190 - F1: 0.6047
sub_1:Test (Best Model) - Loss: 0.5350 - Accuracy: 0.8214 - F1: 0.8212
sub_2:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.6905 - F1: 0.6905
sub_3:Test (Best Model) - Loss: 1.2103 - Accuracy: 0.6310 - F1: 0.6111
sub_1:Test (Best Model) - Loss: 0.4786 - Accuracy: 0.8214 - F1: 0.8183
sub_2:Test (Best Model) - Loss: 0.2673 - Accuracy: 0.8214 - F1: 0.8208
sub_3:Test (Best Model) - Loss: 1.4094 - Accuracy: 0.6429 - F1: 0.6327
sub_2:Test (Best Model) - Loss: 0.3405 - Accuracy: 0.8214 - F1: 0.8212
sub_1:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.8214 - F1: 0.8208
sub_1:Test (Best Model) - Loss: 0.6327 - Accuracy: 0.7976 - F1: 0.7976
sub_2:Test (Best Model) - Loss: 0.3545 - Accuracy: 0.8333 - F1: 0.8330
sub_3:Test (Best Model) - Loss: 1.2443 - Accuracy: 0.6310 - F1: 0.6219
sub_2:Test (Best Model) - Loss: 3.2877 - Accuracy: 0.7500 - F1: 0.7439
sub_3:Test (Best Model) - Loss: 0.6404 - Accuracy: 0.6786 - F1: 0.6774
sub_1:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.7857 - F1: 0.7856
sub_2:Test (Best Model) - Loss: 7.6216 - Accuracy: 0.7619 - F1: 0.7614
sub_3:Test (Best Model) - Loss: 0.8182 - Accuracy: 0.6786 - F1: 0.6748
sub_1:Test (Best Model) - Loss: 0.3679 - Accuracy: 0.8333 - F1: 0.8332
sub_3:Test (Best Model) - Loss: 0.7579 - Accuracy: 0.6667 - F1: 0.6636
sub_1:Test (Best Model) - Loss: 1.0773 - Accuracy: 0.7738 - F1: 0.7730
sub_2:Test (Best Model) - Loss: 2.7215 - Accuracy: 0.7619 - F1: 0.7569
sub_1:Test (Best Model) - Loss: 0.7773 - Accuracy: 0.8214 - F1: 0.8202
sub_3:Test (Best Model) - Loss: 1.8333 - Accuracy: 0.7262 - F1: 0.7230
sub_2:Test (Best Model) - Loss: 7.2488 - Accuracy: 0.7381 - F1: 0.7368
sub_2:Test (Best Model) - Loss: 2.1427 - Accuracy: 0.7381 - F1: 0.7357
sub_3:Test (Best Model) - Loss: 1.7241 - Accuracy: 0.6667 - F1: 0.6636
sub_3:Test (Best Model) - Loss: 1.1581 - Accuracy: 0.7500 - F1: 0.7497
sub_6:Test (Best Model) - Loss: 0.5529 - Accuracy: 0.7976 - F1: 0.7969
sub_4:Test (Best Model) - Loss: 3.5326 - Accuracy: 0.6905 - F1: 0.6903
sub_5:Test (Best Model) - Loss: 1.8219 - Accuracy: 0.5238 - F1: 0.5102
sub_6:Test (Best Model) - Loss: 0.4577 - Accuracy: 0.8333 - F1: 0.8330
sub_4:Test (Best Model) - Loss: 4.6114 - Accuracy: 0.7024 - F1: 0.7020
sub_5:Test (Best Model) - Loss: 0.9172 - Accuracy: 0.5476 - F1: 0.5074
sub_4:Test (Best Model) - Loss: 3.2103 - Accuracy: 0.6190 - F1: 0.6171
sub_6:Test (Best Model) - Loss: 0.4944 - Accuracy: 0.7976 - F1: 0.7953
sub_5:Test (Best Model) - Loss: 5.1026 - Accuracy: 0.6190 - F1: 0.6136
sub_4:Test (Best Model) - Loss: 6.6567 - Accuracy: 0.6310 - F1: 0.6309
sub_5:Test (Best Model) - Loss: 3.0326 - Accuracy: 0.6548 - F1: 0.6463
sub_6:Test (Best Model) - Loss: 0.5007 - Accuracy: 0.8690 - F1: 0.8681
sub_4:Test (Best Model) - Loss: 3.5573 - Accuracy: 0.7143 - F1: 0.7141
sub_6:Test (Best Model) - Loss: 0.4430 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 2.4485 - Accuracy: 0.6548 - F1: 0.6361
sub_6:Test (Best Model) - Loss: 3.1643 - Accuracy: 0.6429 - F1: 0.6214
sub_4:Test (Best Model) - Loss: 0.8916 - Accuracy: 0.7381 - F1: 0.7282
sub_5:Test (Best Model) - Loss: 0.7208 - Accuracy: 0.6905 - F1: 0.6876
sub_4:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.7262 - F1: 0.7079
sub_6:Test (Best Model) - Loss: 1.9476 - Accuracy: 0.6786 - F1: 0.6648
sub_4:Test (Best Model) - Loss: 0.9837 - Accuracy: 0.7143 - F1: 0.7083
sub_5:Test (Best Model) - Loss: 1.2398 - Accuracy: 0.7024 - F1: 0.6926
sub_6:Test (Best Model) - Loss: 3.5420 - Accuracy: 0.7500 - F1: 0.7439
sub_4:Test (Best Model) - Loss: 0.7952 - Accuracy: 0.7619 - F1: 0.7614
sub_5:Test (Best Model) - Loss: 0.8872 - Accuracy: 0.6786 - F1: 0.6571
sub_6:Test (Best Model) - Loss: 4.5644 - Accuracy: 0.6667 - F1: 0.6421
sub_4:Test (Best Model) - Loss: 0.9651 - Accuracy: 0.7738 - F1: 0.7664
sub_5:Test (Best Model) - Loss: 0.9008 - Accuracy: 0.7381 - F1: 0.7379
sub_6:Test (Best Model) - Loss: 3.3002 - Accuracy: 0.6786 - F1: 0.6648
sub_5:Test (Best Model) - Loss: 0.5389 - Accuracy: 0.8095 - F1: 0.8078
sub_4:Test (Best Model) - Loss: 0.7601 - Accuracy: 0.7976 - F1: 0.7976
sub_6:Test (Best Model) - Loss: 1.9488 - Accuracy: 0.6786 - F1: 0.6782
sub_4:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.7024 - F1: 0.7003
sub_5:Test (Best Model) - Loss: 1.1267 - Accuracy: 0.5595 - F1: 0.5580
sub_6:Test (Best Model) - Loss: 2.2066 - Accuracy: 0.5238 - F1: 0.5139
sub_6:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.5119 - F1: 0.4911
sub_5:Test (Best Model) - Loss: 0.8506 - Accuracy: 0.6071 - F1: 0.5904
sub_6:Test (Best Model) - Loss: 1.2557 - Accuracy: 0.5357 - F1: 0.5325
sub_4:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.7143 - F1: 0.7143
sub_6:Test (Best Model) - Loss: 1.6945 - Accuracy: 0.7024 - F1: 0.7003
sub_4:Test (Best Model) - Loss: 0.5739 - Accuracy: 0.7262 - F1: 0.7145
sub_5:Test (Best Model) - Loss: 2.6011 - Accuracy: 0.5357 - F1: 0.5325
sub_4:Test (Best Model) - Loss: 0.7584 - Accuracy: 0.7619 - F1: 0.7619
sub_5:Test (Best Model) - Loss: 1.0868 - Accuracy: 0.6905 - F1: 0.6719
sub_5:Test (Best Model) - Loss: 1.0210 - Accuracy: 0.5833 - F1: 0.5655
sub_7:Test (Best Model) - Loss: 0.8581 - Accuracy: 0.6667 - F1: 0.6466
sub_9:Test (Best Model) - Loss: 4.2423 - Accuracy: 0.5476 - F1: 0.4312
sub_8:Test (Best Model) - Loss: 0.3038 - Accuracy: 0.8690 - F1: 0.8675
sub_7:Test (Best Model) - Loss: 1.1980 - Accuracy: 0.6667 - F1: 0.6506
sub_9:Test (Best Model) - Loss: 2.9867 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.2141 - Accuracy: 0.9167 - F1: 0.9167
sub_7:Test (Best Model) - Loss: 0.5966 - Accuracy: 0.6786 - F1: 0.6680
sub_9:Test (Best Model) - Loss: 2.2857 - Accuracy: 0.5952 - F1: 0.5159
sub_8:Test (Best Model) - Loss: 0.5495 - Accuracy: 0.8095 - F1: 0.8056
sub_8:Test (Best Model) - Loss: 0.2688 - Accuracy: 0.8929 - F1: 0.8925
sub_7:Test (Best Model) - Loss: 0.8229 - Accuracy: 0.6667 - F1: 0.6506
sub_9:Test (Best Model) - Loss: 3.4739 - Accuracy: 0.5714 - F1: 0.4750
sub_7:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.6429 - F1: 0.6166
sub_8:Test (Best Model) - Loss: 0.2919 - Accuracy: 0.8810 - F1: 0.8799
sub_7:Test (Best Model) - Loss: 0.6336 - Accuracy: 0.7857 - F1: 0.7852
sub_9:Test (Best Model) - Loss: 3.8358 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.1518 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.3400 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.4134 - Accuracy: 0.8214 - F1: 0.8208
sub_7:Test (Best Model) - Loss: 0.4583 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 1.3205 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.8690 - F1: 0.8686
sub_7:Test (Best Model) - Loss: 0.4192 - Accuracy: 0.8452 - F1: 0.8452
sub_8:Test (Best Model) - Loss: 0.2181 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 1.1603 - Accuracy: 0.7857 - F1: 0.7846
sub_7:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.7857 - F1: 0.7856
sub_8:Test (Best Model) - Loss: 0.1798 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 1.0137 - Accuracy: 0.7976 - F1: 0.7974
sub_7:Test (Best Model) - Loss: 1.4352 - Accuracy: 0.5833 - F1: 0.5176
sub_7:Test (Best Model) - Loss: 0.8666 - Accuracy: 0.6667 - F1: 0.6466
sub_8:Test (Best Model) - Loss: 0.9101 - Accuracy: 0.7024 - F1: 0.6926
sub_9:Test (Best Model) - Loss: 0.4229 - Accuracy: 0.8214 - F1: 0.8194
sub_9:Test (Best Model) - Loss: 0.8306 - Accuracy: 0.7619 - F1: 0.7585
sub_7:Test (Best Model) - Loss: 0.9139 - Accuracy: 0.6905 - F1: 0.6756
sub_8:Test (Best Model) - Loss: 1.2070 - Accuracy: 0.7381 - F1: 0.7326
sub_9:Test (Best Model) - Loss: 6.9091 - Accuracy: 0.3690 - F1: 0.3077
sub_7:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.7024 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 1.3155 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 15.5893 - Accuracy: 0.3452 - F1: 0.3407
sub_7:Test (Best Model) - Loss: 0.8311 - Accuracy: 0.7024 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.9940 - Accuracy: 0.7500 - F1: 0.7483
sub_8:Test (Best Model) - Loss: 1.1914 - Accuracy: 0.7738 - F1: 0.7683
sub_9:Test (Best Model) - Loss: 15.1808 - Accuracy: 0.3333 - F1: 0.3082
sub_9:Test (Best Model) - Loss: 17.2047 - Accuracy: 0.4762 - F1: 0.4762
sub_9:Test (Best Model) - Loss: 4.8376 - Accuracy: 0.3690 - F1: 0.3077
sub_12:Test (Best Model) - Loss: 0.5506 - Accuracy: 0.7500 - F1: 0.7491
sub_10:Test (Best Model) - Loss: 1.0402 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.7327 - Accuracy: 0.7857 - F1: 0.7857
sub_10:Test (Best Model) - Loss: 1.2727 - Accuracy: 0.7619 - F1: 0.7618
sub_12:Test (Best Model) - Loss: 0.4194 - Accuracy: 0.8690 - F1: 0.8690
sub_10:Test (Best Model) - Loss: 1.1507 - Accuracy: 0.7500 - F1: 0.7483
sub_12:Test (Best Model) - Loss: 0.6437 - Accuracy: 0.6905 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 1.8611 - Accuracy: 0.7381 - F1: 0.7368
sub_12:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.8929 - F1: 0.8928
sub_10:Test (Best Model) - Loss: 1.7444 - Accuracy: 0.7619 - F1: 0.7569
sub_10:Test (Best Model) - Loss: 1.1935 - Accuracy: 0.7024 - F1: 0.7020
sub_11:Test (Best Model) - Loss: 0.4319 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.3873 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.7337 - Accuracy: 0.8095 - F1: 0.8091
sub_10:Test (Best Model) - Loss: 0.4384 - Accuracy: 0.7857 - F1: 0.7846
sub_12:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.8452 - F1: 0.8452
sub_10:Test (Best Model) - Loss: 0.3292 - Accuracy: 0.8333 - F1: 0.8330
sub_11:Test (Best Model) - Loss: 0.7692 - Accuracy: 0.7976 - F1: 0.7969
sub_10:Test (Best Model) - Loss: 0.4344 - Accuracy: 0.8095 - F1: 0.8091
sub_12:Test (Best Model) - Loss: 0.7128 - Accuracy: 0.8214 - F1: 0.8214
sub_12:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.6429 - F1: 0.6377
sub_11:Test (Best Model) - Loss: 1.0535 - Accuracy: 0.5833 - F1: 0.5731
sub_12:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.6667 - F1: 0.6597
sub_10:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.7976 - F1: 0.7941
sub_10:Test (Best Model) - Loss: 0.3602 - Accuracy: 0.8452 - F1: 0.8450
sub_11:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.7500 - F1: 0.7500
sub_10:Test (Best Model) - Loss: 1.1429 - Accuracy: 0.5952 - F1: 0.5159
sub_12:Test (Best Model) - Loss: 0.4875 - Accuracy: 0.8452 - F1: 0.8442
sub_12:Test (Best Model) - Loss: 0.7808 - Accuracy: 0.7619 - F1: 0.7551
sub_10:Test (Best Model) - Loss: 1.2954 - Accuracy: 0.5952 - F1: 0.5654
sub_11:Test (Best Model) - Loss: 0.7259 - Accuracy: 0.7738 - F1: 0.7735
sub_12:Test (Best Model) - Loss: 5.2106 - Accuracy: 0.6071 - F1: 0.5810
sub_10:Test (Best Model) - Loss: 1.9794 - Accuracy: 0.5357 - F1: 0.4081
sub_12:Test (Best Model) - Loss: 1.0504 - Accuracy: 0.6905 - F1: 0.6719
sub_10:Test (Best Model) - Loss: 1.4450 - Accuracy: 0.5595 - F1: 0.4535
sub_11:Test (Best Model) - Loss: 0.9233 - Accuracy: 0.7024 - F1: 0.7013
sub_10:Test (Best Model) - Loss: 1.2031 - Accuracy: 0.5833 - F1: 0.4958
sub_12:Test (Best Model) - Loss: 4.6709 - Accuracy: 0.5000 - F1: 0.4700
sub_11:Test (Best Model) - Loss: 0.7872 - Accuracy: 0.7143 - F1: 0.7128
sub_12:Test (Best Model) - Loss: 7.5209 - Accuracy: 0.5595 - F1: 0.5302
sub_11:Test (Best Model) - Loss: 0.3494 - Accuracy: 0.8690 - F1: 0.8690
sub_11:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.7738 - F1: 0.7735
sub_11:Test (Best Model) - Loss: 0.3206 - Accuracy: 0.8571 - F1: 0.8571
sub_11:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.6310 - F1: 0.6152
sub_11:Test (Best Model) - Loss: 0.3102 - Accuracy: 0.8929 - F1: 0.8928
sub_13:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.6190 - F1: 0.5544
sub_14:Test (Best Model) - Loss: 1.8910 - Accuracy: 0.6786 - F1: 0.6748
sub_14:Test (Best Model) - Loss: 2.5000 - Accuracy: 0.7024 - F1: 0.6989
sub_13:Test (Best Model) - Loss: 0.3355 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.9024 - Accuracy: 0.7262 - F1: 0.7258
sub_14:Test (Best Model) - Loss: 0.4897 - Accuracy: 0.7500 - F1: 0.7439
sub_13:Test (Best Model) - Loss: 1.2648 - Accuracy: 0.5952 - F1: 0.5265
sub_13:Test (Best Model) - Loss: 0.5783 - Accuracy: 0.7738 - F1: 0.7616
sub_14:Test (Best Model) - Loss: 1.0790 - Accuracy: 0.7738 - F1: 0.7730
sub_14:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.7619 - F1: 0.7551
sub_13:Test (Best Model) - Loss: 0.5321 - Accuracy: 0.8214 - F1: 0.8155
sub_14:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.7381 - F1: 0.7379
sub_13:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.8095 - F1: 0.8085
sub_14:Test (Best Model) - Loss: 0.7158 - Accuracy: 0.7381 - F1: 0.7368
sub_13:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.8333 - F1: 0.8332
sub_14:Test (Best Model) - Loss: 0.8955 - Accuracy: 0.7857 - F1: 0.7838
sub_13:Test (Best Model) - Loss: 0.5934 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.4754 - Accuracy: 0.7857 - F1: 0.7812
sub_13:Test (Best Model) - Loss: 0.4495 - Accuracy: 0.8452 - F1: 0.8442
sub_14:Test (Best Model) - Loss: 0.8916 - Accuracy: 0.6190 - F1: 0.5910
sub_13:Test (Best Model) - Loss: 0.4324 - Accuracy: 0.8571 - F1: 0.8571
sub_14:Test (Best Model) - Loss: 0.9440 - Accuracy: 0.5714 - F1: 0.5333
sub_13:Test (Best Model) - Loss: 4.5470 - Accuracy: 0.8214 - F1: 0.8170
sub_14:Test (Best Model) - Loss: 1.0664 - Accuracy: 0.6429 - F1: 0.6050
sub_13:Test (Best Model) - Loss: 1.4206 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.7474 - Accuracy: 0.6310 - F1: 0.6010
sub_13:Test (Best Model) - Loss: 1.6546 - Accuracy: 0.8810 - F1: 0.8810
sub_13:Test (Best Model) - Loss: 1.8532 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 1.0174 - Accuracy: 0.6667 - F1: 0.6421
sub_13:Test (Best Model) - Loss: 0.9810 - Accuracy: 0.8810 - F1: 0.8809

=== Summary Results ===

acc: 72.31 ± 6.85
F1: 71.05 ± 7.74
acc-in: 84.27 ± 5.13
F1-in: 83.92 ± 5.34
runing time: 1339.00 seconds
