lr: 0.001
sub_2:Test (Best Model) - Loss: 0.5306 - Accuracy: 0.8571 - F1: 0.8551
sub_4:Test (Best Model) - Loss: 0.2785 - Accuracy: 0.9048 - F1: 0.9043
sub_7:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5833 - F1: 0.4958
sub_6:Test (Best Model) - Loss: 0.2195 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.5079 - Accuracy: 0.7976 - F1: 0.7890
sub_5:Test (Best Model) - Loss: 0.7283 - Accuracy: 0.7738 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 0.5249 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 0.1470 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.4402 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.5365 - Accuracy: 0.8095 - F1: 0.8024
sub_6:Test (Best Model) - Loss: 0.4827 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.8929 - F1: 0.8927
sub_1:Test (Best Model) - Loss: 0.1367 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.3415 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.5119 - F1: 0.3593
sub_2:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.8690 - F1: 0.8675
sub_7:Test (Best Model) - Loss: 1.3544 - Accuracy: 0.5238 - F1: 0.3842
sub_5:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.8452 - F1: 0.8425
sub_2:Test (Best Model) - Loss: 0.7772 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 0.2136 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.2326 - Accuracy: 0.9048 - F1: 0.9047
sub_6:Test (Best Model) - Loss: 0.5374 - Accuracy: 0.8214 - F1: 0.8170
sub_2:Test (Best Model) - Loss: 0.1961 - Accuracy: 0.9167 - F1: 0.9164
sub_3:Test (Best Model) - Loss: 0.2313 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 0.2857 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.4907 - Accuracy: 0.7857 - F1: 0.7796
sub_5:Test (Best Model) - Loss: 0.3259 - Accuracy: 0.9167 - F1: 0.9164
sub_2:Test (Best Model) - Loss: 0.3010 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 0.9966 - Accuracy: 0.5833 - F1: 0.5270
sub_7:Test (Best Model) - Loss: 3.4765 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.1600 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.1565 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.3689 - Accuracy: 0.8452 - F1: 0.8414
sub_5:Test (Best Model) - Loss: 0.5792 - Accuracy: 0.6786 - F1: 0.6680
sub_1:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.5714 - F1: 0.4987
sub_3:Test (Best Model) - Loss: 0.3131 - Accuracy: 0.8690 - F1: 0.8675
sub_6:Test (Best Model) - Loss: 0.3029 - Accuracy: 0.8929 - F1: 0.8925
sub_1:Test (Best Model) - Loss: 2.1281 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.0829 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.0691 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 1.5324 - Accuracy: 0.5476 - F1: 0.4312
sub_5:Test (Best Model) - Loss: 0.3686 - Accuracy: 0.8810 - F1: 0.8799
sub_6:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 0.2918 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.1627 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.5610 - Accuracy: 0.8214 - F1: 0.8155
sub_3:Test (Best Model) - Loss: 0.5245 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.1020 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 1.6634 - Accuracy: 0.5357 - F1: 0.4239
sub_6:Test (Best Model) - Loss: 0.3559 - Accuracy: 0.9167 - F1: 0.9164
sub_4:Test (Best Model) - Loss: 0.1205 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.2571 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.2968 - Accuracy: 0.8929 - F1: 0.8927
sub_7:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.7024 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 0.1962 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.8571 - F1: 0.8571
sub_4:Test (Best Model) - Loss: 0.3247 - Accuracy: 0.9048 - F1: 0.9047
sub_6:Test (Best Model) - Loss: 0.2777 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.2801 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.1465 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.7671 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.9221 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.2352 - Accuracy: 0.9167 - F1: 0.9167
sub_7:Test (Best Model) - Loss: 0.1440 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.8969 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.3584 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 0.7890 - Accuracy: 0.8333 - F1: 0.8325
sub_6:Test (Best Model) - Loss: 1.7106 - Accuracy: 0.7024 - F1: 0.6825
sub_2:Test (Best Model) - Loss: 0.4793 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.1433 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.1369 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.3306 - Accuracy: 0.8690 - F1: 0.8681
sub_4:Test (Best Model) - Loss: 0.4919 - Accuracy: 0.7976 - F1: 0.7976
sub_6:Test (Best Model) - Loss: 2.0788 - Accuracy: 0.6190 - F1: 0.5544
sub_7:Test (Best Model) - Loss: 0.7152 - Accuracy: 0.7143 - F1: 0.6889
sub_1:Test (Best Model) - Loss: 0.1860 - Accuracy: 0.9405 - F1: 0.9404
sub_4:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.8333 - F1: 0.8309
sub_6:Test (Best Model) - Loss: 1.6411 - Accuracy: 0.4762 - F1: 0.4207
sub_4:Test (Best Model) - Loss: 0.7136 - Accuracy: 0.8333 - F1: 0.8299
sub_1:Test (Best Model) - Loss: 0.1920 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.6786 - F1: 0.6571
sub_3:Test (Best Model) - Loss: 0.1471 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 0.5358 - Accuracy: 0.8095 - F1: 0.8056
sub_6:Test (Best Model) - Loss: 1.3463 - Accuracy: 0.7024 - F1: 0.7020
sub_1:Test (Best Model) - Loss: 0.5494 - Accuracy: 0.7857 - F1: 0.7776
sub_5:Test (Best Model) - Loss: 0.2731 - Accuracy: 0.8810 - F1: 0.8803
sub_1:Test (Best Model) - Loss: 0.2826 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.1988 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.1888 - Accuracy: 0.9286 - F1: 0.9285
sub_7:Test (Best Model) - Loss: 0.7793 - Accuracy: 0.5833 - F1: 0.4958
sub_5:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.8214 - F1: 0.8202
sub_3:Test (Best Model) - Loss: 0.7957 - Accuracy: 0.7143 - F1: 0.7143
sub_3:Test (Best Model) - Loss: 0.4694 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 1.8280 - Accuracy: 0.5357 - F1: 0.4981
sub_7:Test (Best Model) - Loss: 0.7890 - Accuracy: 0.6905 - F1: 0.6860
sub_5:Test (Best Model) - Loss: 0.2900 - Accuracy: 0.8571 - F1: 0.8551
sub_3:Test (Best Model) - Loss: 0.5207 - Accuracy: 0.7619 - F1: 0.7551
sub_7:Test (Best Model) - Loss: 0.7722 - Accuracy: 0.7262 - F1: 0.7195
sub_3:Test (Best Model) - Loss: 0.9056 - Accuracy: 0.7262 - F1: 0.7145
sub_5:Test (Best Model) - Loss: 0.9834 - Accuracy: 0.7500 - F1: 0.7365
sub_7:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.5952 - F1: 0.5159
sub_3:Test (Best Model) - Loss: 0.5970 - Accuracy: 0.7143 - F1: 0.7061
sub_5:Test (Best Model) - Loss: 1.0616 - Accuracy: 0.6786 - F1: 0.6525
sub_7:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 0.0599 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.4190 - Accuracy: 0.8452 - F1: 0.8442
sub_11:Test (Best Model) - Loss: 1.3542 - Accuracy: 0.6786 - F1: 0.6415
sub_13:Test (Best Model) - Loss: 0.1088 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.7535 - Accuracy: 0.7857 - F1: 0.7754
sub_8:Test (Best Model) - Loss: 0.0181 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 1.1466 - Accuracy: 0.7619 - F1: 0.7476
sub_10:Test (Best Model) - Loss: 0.1642 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 1.0947 - Accuracy: 0.7143 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.4450 - Accuracy: 0.8452 - F1: 0.8425
sub_8:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.4656 - Accuracy: 0.8095 - F1: 0.8041
sub_9:Test (Best Model) - Loss: 0.3037 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.7710 - Accuracy: 0.7976 - F1: 0.7890
sub_12:Test (Best Model) - Loss: 0.2767 - Accuracy: 0.8690 - F1: 0.8675
sub_13:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.7738 - F1: 0.7641
sub_8:Test (Best Model) - Loss: 0.1580 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.7738 - F1: 0.7616
sub_11:Test (Best Model) - Loss: 0.8722 - Accuracy: 0.8095 - F1: 0.8024
sub_13:Test (Best Model) - Loss: 1.0233 - Accuracy: 0.5476 - F1: 0.4312
sub_14:Test (Best Model) - Loss: 0.1329 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 1.2418 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.1990 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.3153 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.5782 - Accuracy: 0.8333 - F1: 0.8299
sub_11:Test (Best Model) - Loss: 1.3618 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.1978 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.2417 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.6840 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.3762 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.9279 - Accuracy: 0.6667 - F1: 0.6313
sub_11:Test (Best Model) - Loss: 0.5825 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.1269 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.2991 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.5761 - Accuracy: 0.6786 - F1: 0.6415
sub_14:Test (Best Model) - Loss: 0.3515 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.2304 - Accuracy: 0.8810 - F1: 0.8799
sub_11:Test (Best Model) - Loss: 0.0748 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.0541 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4709 - Accuracy: 0.7976 - F1: 0.7941
sub_8:Test (Best Model) - Loss: 0.0625 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.0234 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.0327 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.0750 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 0.0671 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.0712 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.2695 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.1826 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.6649 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.4652 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 1.3515 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 0.4740 - Accuracy: 0.8690 - F1: 0.8681
sub_11:Test (Best Model) - Loss: 0.0981 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.0051 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 1.6723 - Accuracy: 0.5476 - F1: 0.4312
sub_14:Test (Best Model) - Loss: 0.0625 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.1085 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.4223 - Accuracy: 0.8214 - F1: 0.8170
sub_13:Test (Best Model) - Loss: 0.3297 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.2493 - Accuracy: 0.8810 - F1: 0.8799
sub_8:Test (Best Model) - Loss: 0.5376 - Accuracy: 0.8690 - F1: 0.8668
sub_11:Test (Best Model) - Loss: 0.8876 - Accuracy: 0.6905 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.3632 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.2589 - Accuracy: 0.9048 - F1: 0.9048
sub_12:Test (Best Model) - Loss: 0.0864 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.1184 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.2702 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.0199 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.3290 - Accuracy: 0.8333 - F1: 0.8286
sub_10:Test (Best Model) - Loss: 0.2206 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.3282 - Accuracy: 0.8571 - F1: 0.8551
sub_13:Test (Best Model) - Loss: 0.4658 - Accuracy: 0.8690 - F1: 0.8689
sub_11:Test (Best Model) - Loss: 0.2962 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.0475 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.0862 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.3692 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.0949 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.8271 - Accuracy: 0.7738 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 0.1820 - Accuracy: 0.9286 - F1: 0.9286
sub_10:Test (Best Model) - Loss: 0.1200 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.0553 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0126 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.0682 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 1.5470 - Accuracy: 0.5595 - F1: 0.5487
sub_10:Test (Best Model) - Loss: 0.3004 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.0745 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 1.0536 - Accuracy: 0.6429 - F1: 0.5906
sub_12:Test (Best Model) - Loss: 0.9569 - Accuracy: 0.8571 - F1: 0.8564
sub_10:Test (Best Model) - Loss: 0.7671 - Accuracy: 0.7976 - F1: 0.7910
sub_8:Test (Best Model) - Loss: 0.1336 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 1.0012 - Accuracy: 0.8571 - F1: 0.8568
sub_14:Test (Best Model) - Loss: 0.9341 - Accuracy: 0.7738 - F1: 0.7641
sub_10:Test (Best Model) - Loss: 1.5818 - Accuracy: 0.6190 - F1: 0.5544
sub_8:Test (Best Model) - Loss: 0.1170 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.9687 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 2.4771 - Accuracy: 0.5952 - F1: 0.5159
sub_10:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.6667 - F1: 0.6571
sub_12:Test (Best Model) - Loss: 0.7651 - Accuracy: 0.7976 - F1: 0.7962
sub_14:Test (Best Model) - Loss: 0.9247 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 2.4751 - Accuracy: 0.5357 - F1: 0.4081
sub_10:Test (Best Model) - Loss: 0.2529 - Accuracy: 0.9167 - F1: 0.9164
sub_10:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.6667 - F1: 0.6250
sub_10:Test (Best Model) - Loss: 0.4962 - Accuracy: 0.7024 - F1: 0.6972

=== Summary Results ===

acc: 83.44 ± 6.48
F1: 82.08 ± 7.69
acc-in: 94.50 ± 3.77
F1-in: 94.18 ± 4.31
runing time: 913.93 seconds
