lr: 0.001
sub_7:Test (Best Model) - Loss: 0.8754 - Accuracy: 0.5476 - F1: 0.4312
sub_2:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.8214 - F1: 0.8155
sub_1:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.7976 - F1: 0.7910
sub_4:Test (Best Model) - Loss: 0.0920 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.4516 - Accuracy: 0.8571 - F1: 0.8551
sub_6:Test (Best Model) - Loss: 0.6316 - Accuracy: 0.7500 - F1: 0.7365
sub_3:Test (Best Model) - Loss: 0.1699 - Accuracy: 0.9286 - F1: 0.9285
sub_7:Test (Best Model) - Loss: 1.1354 - Accuracy: 0.5357 - F1: 0.4382
sub_1:Test (Best Model) - Loss: 0.4037 - Accuracy: 0.8571 - F1: 0.8568
sub_2:Test (Best Model) - Loss: 0.5496 - Accuracy: 0.7976 - F1: 0.7890
sub_5:Test (Best Model) - Loss: 0.8309 - Accuracy: 0.7143 - F1: 0.6889
sub_4:Test (Best Model) - Loss: 0.2872 - Accuracy: 0.9048 - F1: 0.9045
sub_3:Test (Best Model) - Loss: 0.4716 - Accuracy: 0.7857 - F1: 0.7776
sub_6:Test (Best Model) - Loss: 0.7508 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 0.3493 - Accuracy: 0.8690 - F1: 0.8689
sub_7:Test (Best Model) - Loss: 0.5711 - Accuracy: 0.7143 - F1: 0.7128
sub_3:Test (Best Model) - Loss: 0.3760 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 0.9944 - Accuracy: 0.7619 - F1: 0.7504
sub_2:Test (Best Model) - Loss: 0.1452 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.8214 - F1: 0.8155
sub_3:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.5595 - F1: 0.4791
sub_6:Test (Best Model) - Loss: 0.5171 - Accuracy: 0.7619 - F1: 0.7597
sub_5:Test (Best Model) - Loss: 0.7720 - Accuracy: 0.5476 - F1: 0.4590
sub_1:Test (Best Model) - Loss: 0.2295 - Accuracy: 0.9286 - F1: 0.9285
sub_4:Test (Best Model) - Loss: 0.5930 - Accuracy: 0.7262 - F1: 0.7040
sub_6:Test (Best Model) - Loss: 1.3404 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 1.5385 - Accuracy: 0.5000 - F1: 0.3534
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.4762 - F1: 0.4714
sub_4:Test (Best Model) - Loss: 1.6243 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 1.0773 - Accuracy: 0.6429 - F1: 0.5982
sub_3:Test (Best Model) - Loss: 0.3362 - Accuracy: 0.8452 - F1: 0.8414
sub_5:Test (Best Model) - Loss: 0.5992 - Accuracy: 0.7738 - F1: 0.7664
sub_1:Test (Best Model) - Loss: 0.2772 - Accuracy: 0.9167 - F1: 0.9167
sub_6:Test (Best Model) - Loss: 0.8312 - Accuracy: 0.7024 - F1: 0.6735
sub_7:Test (Best Model) - Loss: 1.4198 - Accuracy: 0.5238 - F1: 0.3842
sub_4:Test (Best Model) - Loss: 0.3987 - Accuracy: 0.8452 - F1: 0.8434
sub_7:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.6310 - F1: 0.6296
sub_1:Test (Best Model) - Loss: 1.0840 - Accuracy: 0.6786 - F1: 0.6473
sub_6:Test (Best Model) - Loss: 0.8774 - Accuracy: 0.4881 - F1: 0.3280
sub_2:Test (Best Model) - Loss: 1.0465 - Accuracy: 0.7262 - F1: 0.7079
sub_7:Test (Best Model) - Loss: 0.6876 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.7857 - F1: 0.7846
sub_6:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.8199 - Accuracy: 0.6310 - F1: 0.5810
sub_3:Test (Best Model) - Loss: 1.0557 - Accuracy: 0.7024 - F1: 0.6783
sub_1:Test (Best Model) - Loss: 0.1970 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 0.0862 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.5731 - Accuracy: 0.7024 - F1: 0.7023
sub_6:Test (Best Model) - Loss: 0.7353 - Accuracy: 0.7262 - F1: 0.7079
sub_4:Test (Best Model) - Loss: 0.2172 - Accuracy: 0.9048 - F1: 0.9047
sub_5:Test (Best Model) - Loss: 0.5664 - Accuracy: 0.7500 - F1: 0.7471
sub_3:Test (Best Model) - Loss: 0.3866 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.1606 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.3143 - Accuracy: 0.8810 - F1: 0.8807
sub_7:Test (Best Model) - Loss: 0.4892 - Accuracy: 0.7619 - F1: 0.7476
sub_6:Test (Best Model) - Loss: 1.0887 - Accuracy: 0.5000 - F1: 0.3534
sub_7:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.2521 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.3919 - Accuracy: 0.7738 - F1: 0.7738
sub_4:Test (Best Model) - Loss: 0.1737 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.3214 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.7976 - F1: 0.7941
sub_7:Test (Best Model) - Loss: 0.7183 - Accuracy: 0.4881 - F1: 0.4755
sub_6:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.7381 - F1: 0.7343
sub_4:Test (Best Model) - Loss: 0.3940 - Accuracy: 0.8214 - F1: 0.8194
sub_1:Test (Best Model) - Loss: 0.2948 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.7410 - Accuracy: 0.6190 - F1: 0.5910
sub_5:Test (Best Model) - Loss: 0.3196 - Accuracy: 0.8333 - F1: 0.8325
sub_3:Test (Best Model) - Loss: 0.3646 - Accuracy: 0.8810 - F1: 0.8799
sub_6:Test (Best Model) - Loss: 0.7512 - Accuracy: 0.6429 - F1: 0.6294
sub_1:Test (Best Model) - Loss: 2.1953 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.0554 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.7262 - F1: 0.7230
sub_6:Test (Best Model) - Loss: 0.8445 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.2109 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 1.0318 - Accuracy: 0.6190 - F1: 0.5634
sub_1:Test (Best Model) - Loss: 1.6638 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.8582 - Accuracy: 0.7262 - F1: 0.7040
sub_6:Test (Best Model) - Loss: 1.0292 - Accuracy: 0.6190 - F1: 0.5634
sub_7:Test (Best Model) - Loss: 0.5692 - Accuracy: 0.6548 - F1: 0.6535
sub_3:Test (Best Model) - Loss: 1.0019 - Accuracy: 0.6548 - F1: 0.6463
sub_2:Test (Best Model) - Loss: 0.5011 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 0.7620 - Accuracy: 0.5238 - F1: 0.3842
sub_1:Test (Best Model) - Loss: 0.1656 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.9669 - Accuracy: 0.5952 - F1: 0.5800
sub_4:Test (Best Model) - Loss: 1.8661 - Accuracy: 0.5833 - F1: 0.4958
sub_2:Test (Best Model) - Loss: 0.4964 - Accuracy: 0.8095 - F1: 0.8024
sub_6:Test (Best Model) - Loss: 1.3069 - Accuracy: 0.5000 - F1: 0.4632
sub_5:Test (Best Model) - Loss: 2.4602 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.9641 - Accuracy: 0.5714 - F1: 0.5088
sub_1:Test (Best Model) - Loss: 1.2702 - Accuracy: 0.5357 - F1: 0.4081
sub_5:Test (Best Model) - Loss: 1.0788 - Accuracy: 0.6190 - F1: 0.5962
sub_6:Test (Best Model) - Loss: 2.5523 - Accuracy: 0.4643 - F1: 0.4122
sub_3:Test (Best Model) - Loss: 1.0608 - Accuracy: 0.6071 - F1: 0.5540
sub_2:Test (Best Model) - Loss: 0.4416 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.9209 - Accuracy: 0.7143 - F1: 0.7117
sub_1:Test (Best Model) - Loss: 0.4103 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 0.4490 - Accuracy: 0.8214 - F1: 0.8212
sub_2:Test (Best Model) - Loss: 0.3670 - Accuracy: 0.8690 - F1: 0.8689
sub_3:Test (Best Model) - Loss: 0.4003 - Accuracy: 0.7976 - F1: 0.7962
sub_4:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.7738 - F1: 0.7735
sub_2:Test (Best Model) - Loss: 0.3998 - Accuracy: 0.8810 - F1: 0.8799
sub_3:Test (Best Model) - Loss: 0.9067 - Accuracy: 0.6548 - F1: 0.6212
sub_3:Test (Best Model) - Loss: 0.7857 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 1.1384 - Accuracy: 0.6548 - F1: 0.6080
sub_13:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.7976 - F1: 0.7890
sub_8:Test (Best Model) - Loss: 0.2342 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.1815 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.7143 - F1: 0.6889
sub_11:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.8095 - F1: 0.8024
sub_10:Test (Best Model) - Loss: 0.4075 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.8122 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.2920 - Accuracy: 0.8690 - F1: 0.8681
sub_12:Test (Best Model) - Loss: 0.1400 - Accuracy: 0.9643 - F1: 0.9643
sub_9:Test (Best Model) - Loss: 2.1194 - Accuracy: 0.6548 - F1: 0.6080
sub_14:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.7857 - F1: 0.7838
sub_11:Test (Best Model) - Loss: 0.9511 - Accuracy: 0.6667 - F1: 0.6506
sub_12:Test (Best Model) - Loss: 0.2258 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.2269 - Accuracy: 0.9167 - F1: 0.9164
sub_10:Test (Best Model) - Loss: 0.4465 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 0.7283 - Accuracy: 0.7619 - F1: 0.7476
sub_13:Test (Best Model) - Loss: 0.5953 - Accuracy: 0.7976 - F1: 0.7941
sub_11:Test (Best Model) - Loss: 0.2974 - Accuracy: 0.8929 - F1: 0.8927
sub_9:Test (Best Model) - Loss: 2.3694 - Accuracy: 0.5714 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 0.5791 - Accuracy: 0.7619 - F1: 0.7529
sub_14:Test (Best Model) - Loss: 0.2831 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 0.2125 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2441 - Accuracy: 0.8929 - F1: 0.8921
sub_11:Test (Best Model) - Loss: 1.4396 - Accuracy: 0.6786 - F1: 0.6525
sub_13:Test (Best Model) - Loss: 0.1531 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 1.3474 - Accuracy: 0.5357 - F1: 0.4081
sub_12:Test (Best Model) - Loss: 0.0697 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.7287 - Accuracy: 0.7619 - F1: 0.7529
sub_8:Test (Best Model) - Loss: 0.2636 - Accuracy: 0.8690 - F1: 0.8681
sub_9:Test (Best Model) - Loss: 1.0324 - Accuracy: 0.6905 - F1: 0.6577
sub_14:Test (Best Model) - Loss: 0.4244 - Accuracy: 0.8452 - F1: 0.8442
sub_13:Test (Best Model) - Loss: 1.6575 - Accuracy: 0.6071 - F1: 0.5354
sub_8:Test (Best Model) - Loss: 0.0700 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.2488 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.2074 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.8547 - Accuracy: 0.8214 - F1: 0.8155
sub_14:Test (Best Model) - Loss: 0.9347 - Accuracy: 0.7262 - F1: 0.7040
sub_13:Test (Best Model) - Loss: 2.9917 - Accuracy: 0.5119 - F1: 0.3778
sub_10:Test (Best Model) - Loss: 0.7758 - Accuracy: 0.7857 - F1: 0.7812
sub_12:Test (Best Model) - Loss: 0.2140 - Accuracy: 0.9167 - F1: 0.9167
sub_8:Test (Best Model) - Loss: 0.0393 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.2800 - Accuracy: 0.8571 - F1: 0.8564
sub_9:Test (Best Model) - Loss: 1.9677 - Accuracy: 0.6548 - F1: 0.6080
sub_13:Test (Best Model) - Loss: 0.2920 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.1857 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.2851 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 1.5435 - Accuracy: 0.6429 - F1: 0.5906
sub_12:Test (Best Model) - Loss: 0.1403 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.0505 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.0508 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.4370 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.6158 - Accuracy: 0.6667 - F1: 0.6506
sub_11:Test (Best Model) - Loss: 0.3476 - Accuracy: 0.8690 - F1: 0.8675
sub_8:Test (Best Model) - Loss: 0.0914 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.1221 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.4688 - Accuracy: 0.7976 - F1: 0.7941
sub_9:Test (Best Model) - Loss: 0.8181 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.2929 - Accuracy: 0.8810 - F1: 0.8799
sub_13:Test (Best Model) - Loss: 0.1469 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.1796 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.2061 - Accuracy: 0.9286 - F1: 0.9284
sub_11:Test (Best Model) - Loss: 0.1140 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 1.0610 - Accuracy: 0.7262 - F1: 0.7040
sub_13:Test (Best Model) - Loss: 0.1588 - Accuracy: 0.9286 - F1: 0.9286
sub_10:Test (Best Model) - Loss: 0.5129 - Accuracy: 0.7976 - F1: 0.7910
sub_11:Test (Best Model) - Loss: 0.4718 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.1343 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 1.0565 - Accuracy: 0.6905 - F1: 0.6719
sub_9:Test (Best Model) - Loss: 1.0947 - Accuracy: 0.6429 - F1: 0.5906
sub_14:Test (Best Model) - Loss: 0.2611 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.4886 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.2750 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.3980 - Accuracy: 0.8690 - F1: 0.8690
sub_13:Test (Best Model) - Loss: 0.5907 - Accuracy: 0.7857 - F1: 0.7856
sub_9:Test (Best Model) - Loss: 0.9670 - Accuracy: 0.5952 - F1: 0.5265
sub_14:Test (Best Model) - Loss: 0.2269 - Accuracy: 0.8929 - F1: 0.8921
sub_10:Test (Best Model) - Loss: 0.5635 - Accuracy: 0.7619 - F1: 0.7504
sub_11:Test (Best Model) - Loss: 0.3403 - Accuracy: 0.8690 - F1: 0.8681
sub_12:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.8333 - F1: 0.8325
sub_8:Test (Best Model) - Loss: 0.0798 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.3952 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 0.1148 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.4850 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 0.3248 - Accuracy: 0.8810 - F1: 0.8799
sub_9:Test (Best Model) - Loss: 0.2140 - Accuracy: 0.8810 - F1: 0.8807
sub_10:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.7381 - F1: 0.7255
sub_13:Test (Best Model) - Loss: 0.5331 - Accuracy: 0.8333 - F1: 0.8309
sub_11:Test (Best Model) - Loss: 0.9369 - Accuracy: 0.6548 - F1: 0.6543
sub_12:Test (Best Model) - Loss: 1.0289 - Accuracy: 0.8214 - F1: 0.8208
sub_8:Test (Best Model) - Loss: 0.1640 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.7876 - Accuracy: 0.7262 - F1: 0.7079
sub_14:Test (Best Model) - Loss: 1.9616 - Accuracy: 0.5833 - F1: 0.5073
sub_13:Test (Best Model) - Loss: 0.5604 - Accuracy: 0.7381 - F1: 0.7306
sub_10:Test (Best Model) - Loss: 0.6692 - Accuracy: 0.5952 - F1: 0.5265
sub_12:Test (Best Model) - Loss: 0.4951 - Accuracy: 0.8571 - F1: 0.8571
sub_8:Test (Best Model) - Loss: 0.1120 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.5651 - Accuracy: 0.8452 - F1: 0.8452
sub_14:Test (Best Model) - Loss: 1.0545 - Accuracy: 0.6429 - F1: 0.5906
sub_10:Test (Best Model) - Loss: 0.5081 - Accuracy: 0.7857 - F1: 0.7776
sub_10:Test (Best Model) - Loss: 0.6577 - Accuracy: 0.7738 - F1: 0.7616
sub_14:Test (Best Model) - Loss: 1.2825 - Accuracy: 0.6071 - F1: 0.5354
sub_10:Test (Best Model) - Loss: 0.5717 - Accuracy: 0.7500 - F1: 0.7393
sub_14:Test (Best Model) - Loss: 0.8934 - Accuracy: 0.6429 - F1: 0.5906
sub_14:Test (Best Model) - Loss: 1.9527 - Accuracy: 0.5952 - F1: 0.5159

=== Summary Results ===

acc: 76.97 ± 9.31
F1: 74.39 ± 11.26
acc-in: 89.54 ± 7.44
F1-in: 88.23 ± 9.35
runing time: 732.42 seconds
