lr: 0.001
sub_2:Test (Best Model) - Loss: 9.2987 - Accuracy: 0.8571 - F1: 0.8551
sub_1:Test (Best Model) - Loss: 1.6827 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 11.3459 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 4.7986 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 5.6557 - Accuracy: 0.5833 - F1: 0.4958
sub_1:Test (Best Model) - Loss: 6.5327 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 3.8983 - Accuracy: 0.8810 - F1: 0.8799
sub_3:Test (Best Model) - Loss: 8.0939 - Accuracy: 0.8095 - F1: 0.8024
sub_1:Test (Best Model) - Loss: 3.3997 - Accuracy: 0.7381 - F1: 0.7188
sub_2:Test (Best Model) - Loss: 5.1028 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 20.1264 - Accuracy: 0.6548 - F1: 0.6080
sub_1:Test (Best Model) - Loss: 2.9159 - Accuracy: 0.7619 - F1: 0.7476
sub_2:Test (Best Model) - Loss: 6.8021 - Accuracy: 0.7738 - F1: 0.7616
sub_3:Test (Best Model) - Loss: 13.3568 - Accuracy: 0.5357 - F1: 0.4081
sub_2:Test (Best Model) - Loss: 0.9321 - Accuracy: 0.9048 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 4.9966 - Accuracy: 0.7262 - F1: 0.7040
sub_3:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.8810 - F1: 0.8803
sub_1:Test (Best Model) - Loss: 0.9560 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.8582 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.3791 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 1.2804 - Accuracy: 0.9167 - F1: 0.9164
sub_2:Test (Best Model) - Loss: 0.3320 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.3734 - Accuracy: 0.9167 - F1: 0.9166
sub_2:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 2.4728 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.4758 - Accuracy: 0.8929 - F1: 0.8928
sub_2:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.8810 - F1: 0.8792
sub_2:Test (Best Model) - Loss: 7.2595 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 0.7246 - Accuracy: 0.8571 - F1: 0.8551
sub_1:Test (Best Model) - Loss: 0.7567 - Accuracy: 0.9048 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 6.2885 - Accuracy: 0.8690 - F1: 0.8675
sub_1:Test (Best Model) - Loss: 1.0823 - Accuracy: 0.8571 - F1: 0.8542
sub_3:Test (Best Model) - Loss: 9.8074 - Accuracy: 0.8214 - F1: 0.8155
sub_1:Test (Best Model) - Loss: 0.7403 - Accuracy: 0.8452 - F1: 0.8434
sub_2:Test (Best Model) - Loss: 7.9183 - Accuracy: 0.7976 - F1: 0.7890
sub_3:Test (Best Model) - Loss: 6.9665 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 7.7778 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 11.7404 - Accuracy: 0.7857 - F1: 0.7754
sub_1:Test (Best Model) - Loss: 0.1459 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 2.0943 - Accuracy: 0.8690 - F1: 0.8675
sub_3:Test (Best Model) - Loss: 2.1117 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 2.4325 - Accuracy: 0.8095 - F1: 0.8091
sub_1:Test (Best Model) - Loss: 1.4062 - Accuracy: 0.8214 - F1: 0.8183
sub_1:Test (Best Model) - Loss: 0.5566 - Accuracy: 0.9167 - F1: 0.9166
sub_1:Test (Best Model) - Loss: 1.1485 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 2.9892 - Accuracy: 0.7857 - F1: 0.7796
sub_6:Test (Best Model) - Loss: 1.0316 - Accuracy: 0.8452 - F1: 0.8425
sub_5:Test (Best Model) - Loss: 9.8531 - Accuracy: 0.6310 - F1: 0.6309
sub_4:Test (Best Model) - Loss: 3.0412 - Accuracy: 0.8095 - F1: 0.8068
sub_5:Test (Best Model) - Loss: 2.4101 - Accuracy: 0.6905 - F1: 0.6840
sub_6:Test (Best Model) - Loss: 0.3714 - Accuracy: 0.9167 - F1: 0.9164
sub_4:Test (Best Model) - Loss: 0.8554 - Accuracy: 0.7500 - F1: 0.7333
sub_5:Test (Best Model) - Loss: 8.9574 - Accuracy: 0.6190 - F1: 0.6136
sub_6:Test (Best Model) - Loss: 0.0650 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 3.9130 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 3.8674 - Accuracy: 0.6429 - F1: 0.6214
sub_6:Test (Best Model) - Loss: 0.3940 - Accuracy: 0.9048 - F1: 0.9048
sub_5:Test (Best Model) - Loss: 8.9375 - Accuracy: 0.6190 - F1: 0.5910
sub_4:Test (Best Model) - Loss: 2.6929 - Accuracy: 0.7976 - F1: 0.7890
sub_4:Test (Best Model) - Loss: 1.1354 - Accuracy: 0.7976 - F1: 0.7974
sub_6:Test (Best Model) - Loss: 0.2796 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 1.1261 - Accuracy: 0.8571 - F1: 0.8551
sub_4:Test (Best Model) - Loss: 1.2261 - Accuracy: 0.7976 - F1: 0.7969
sub_5:Test (Best Model) - Loss: 10.4548 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 2.2854 - Accuracy: 0.8810 - F1: 0.8799
sub_4:Test (Best Model) - Loss: 1.1311 - Accuracy: 0.8095 - F1: 0.8085
sub_5:Test (Best Model) - Loss: 0.4647 - Accuracy: 0.9048 - F1: 0.9048
sub_4:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.8214 - F1: 0.8214
sub_6:Test (Best Model) - Loss: 3.6417 - Accuracy: 0.8095 - F1: 0.8024
sub_4:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.8571 - F1: 0.8571
sub_5:Test (Best Model) - Loss: 1.7337 - Accuracy: 0.8810 - F1: 0.8810
sub_6:Test (Best Model) - Loss: 3.2100 - Accuracy: 0.8452 - F1: 0.8434
sub_5:Test (Best Model) - Loss: 0.1462 - Accuracy: 0.9286 - F1: 0.9285
sub_4:Test (Best Model) - Loss: 2.2088 - Accuracy: 0.7976 - F1: 0.7941
sub_6:Test (Best Model) - Loss: 1.3541 - Accuracy: 0.8929 - F1: 0.8921
sub_4:Test (Best Model) - Loss: 1.1979 - Accuracy: 0.8214 - F1: 0.8183
sub_5:Test (Best Model) - Loss: 1.0026 - Accuracy: 0.7500 - F1: 0.7418
sub_6:Test (Best Model) - Loss: 1.2103 - Accuracy: 0.9286 - F1: 0.9285
sub_4:Test (Best Model) - Loss: 2.0072 - Accuracy: 0.7976 - F1: 0.7910
sub_6:Test (Best Model) - Loss: 2.2537 - Accuracy: 0.7500 - F1: 0.7418
sub_4:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.6548 - F1: 0.6080
sub_5:Test (Best Model) - Loss: 0.8645 - Accuracy: 0.7143 - F1: 0.7061
sub_4:Test (Best Model) - Loss: 1.4899 - Accuracy: 0.7500 - F1: 0.7365
sub_6:Test (Best Model) - Loss: 5.5811 - Accuracy: 0.7976 - F1: 0.7962
sub_5:Test (Best Model) - Loss: 1.5226 - Accuracy: 0.7619 - F1: 0.7551
sub_6:Test (Best Model) - Loss: 1.6154 - Accuracy: 0.7857 - F1: 0.7796
sub_5:Test (Best Model) - Loss: 1.3802 - Accuracy: 0.7381 - F1: 0.7255
sub_6:Test (Best Model) - Loss: 2.3712 - Accuracy: 0.8214 - F1: 0.8202
sub_5:Test (Best Model) - Loss: 1.3513 - Accuracy: 0.7500 - F1: 0.7418
sub_6:Test (Best Model) - Loss: 51.7835 - Accuracy: 0.7381 - F1: 0.7326
sub_8:Test (Best Model) - Loss: 0.7980 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 12.4488 - Accuracy: 0.5714 - F1: 0.4875
sub_7:Test (Best Model) - Loss: 0.4711 - Accuracy: 0.8571 - F1: 0.8558
sub_8:Test (Best Model) - Loss: 0.6852 - Accuracy: 0.9167 - F1: 0.9166
sub_9:Test (Best Model) - Loss: 5.4132 - Accuracy: 0.7381 - F1: 0.7224
sub_8:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.8556 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 3.4668 - Accuracy: 0.8452 - F1: 0.8425
sub_7:Test (Best Model) - Loss: 1.2610 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.3137 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.1045 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 2.6563 - Accuracy: 0.7619 - F1: 0.7476
sub_7:Test (Best Model) - Loss: 1.0121 - Accuracy: 0.8095 - F1: 0.8068
sub_8:Test (Best Model) - Loss: 0.1113 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 2.9442 - Accuracy: 0.7500 - F1: 0.7393
sub_9:Test (Best Model) - Loss: 8.4549 - Accuracy: 0.7024 - F1: 0.6735
sub_8:Test (Best Model) - Loss: 0.3681 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.5885 - Accuracy: 0.8571 - F1: 0.8571
sub_9:Test (Best Model) - Loss: 3.8581 - Accuracy: 0.7976 - F1: 0.7962
sub_8:Test (Best Model) - Loss: 0.4846 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 2.2822 - Accuracy: 0.7857 - F1: 0.7796
sub_7:Test (Best Model) - Loss: 0.4233 - Accuracy: 0.9048 - F1: 0.9047
sub_8:Test (Best Model) - Loss: 0.1636 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 3.8641 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.8333 - F1: 0.8309
sub_7:Test (Best Model) - Loss: 5.6134 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 2.4454 - Accuracy: 0.8333 - F1: 0.8318
sub_8:Test (Best Model) - Loss: 2.1505 - Accuracy: 0.8333 - F1: 0.8286
sub_9:Test (Best Model) - Loss: 1.2455 - Accuracy: 0.8214 - F1: 0.8183
sub_9:Test (Best Model) - Loss: 0.6058 - Accuracy: 0.8095 - F1: 0.8024
sub_8:Test (Best Model) - Loss: 1.9010 - Accuracy: 0.8095 - F1: 0.8024
sub_7:Test (Best Model) - Loss: 3.4107 - Accuracy: 0.8810 - F1: 0.8803
sub_9:Test (Best Model) - Loss: 3.2532 - Accuracy: 0.8333 - F1: 0.8286
sub_8:Test (Best Model) - Loss: 1.4819 - Accuracy: 0.8333 - F1: 0.8286
sub_7:Test (Best Model) - Loss: 0.2090 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 2.1374 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.8530 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 2.5759 - Accuracy: 0.8095 - F1: 0.8041
sub_9:Test (Best Model) - Loss: 0.7200 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 1.4844 - Accuracy: 0.7976 - F1: 0.7974
sub_7:Test (Best Model) - Loss: 0.8849 - Accuracy: 0.8095 - F1: 0.8078
sub_7:Test (Best Model) - Loss: 0.9658 - Accuracy: 0.8810 - F1: 0.8807
sub_7:Test (Best Model) - Loss: 0.8407 - Accuracy: 0.8690 - F1: 0.8681
sub_7:Test (Best Model) - Loss: 0.6687 - Accuracy: 0.8810 - F1: 0.8807
sub_11:Test (Best Model) - Loss: 0.4732 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 1.6215 - Accuracy: 0.8214 - F1: 0.8155
sub_10:Test (Best Model) - Loss: 0.7724 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 2.0904 - Accuracy: 0.7976 - F1: 0.7890
sub_11:Test (Best Model) - Loss: 0.7619 - Accuracy: 0.9286 - F1: 0.9285
sub_10:Test (Best Model) - Loss: 0.1724 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 1.8483 - Accuracy: 0.8214 - F1: 0.8155
sub_11:Test (Best Model) - Loss: 0.3526 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 0.5701 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 1.4897 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.7810 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.3342 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.0086 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.8278 - Accuracy: 0.8810 - F1: 0.8803
sub_10:Test (Best Model) - Loss: 0.6636 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.5508 - Accuracy: 0.7976 - F1: 0.7910
sub_11:Test (Best Model) - Loss: 0.0328 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.5021 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.2723 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.7568 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.5353 - Accuracy: 0.9167 - F1: 0.9166
sub_10:Test (Best Model) - Loss: 0.6330 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.7298 - Accuracy: 0.8810 - F1: 0.8807
sub_11:Test (Best Model) - Loss: 0.0078 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 2.0192 - Accuracy: 0.8333 - F1: 0.8299
sub_11:Test (Best Model) - Loss: 0.1863 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 4.2027 - Accuracy: 0.8095 - F1: 0.8024
sub_11:Test (Best Model) - Loss: 0.1991 - Accuracy: 0.9405 - F1: 0.9404
sub_10:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.4877 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.5010 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.8282 - Accuracy: 0.9048 - F1: 0.9045
sub_11:Test (Best Model) - Loss: 0.2888 - Accuracy: 0.9405 - F1: 0.9404
sub_10:Test (Best Model) - Loss: 0.8518 - Accuracy: 0.8095 - F1: 0.8085
sub_12:Test (Best Model) - Loss: 1.5674 - Accuracy: 0.8810 - F1: 0.8803
sub_11:Test (Best Model) - Loss: 0.1575 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 1.2084 - Accuracy: 0.7976 - F1: 0.7890
sub_12:Test (Best Model) - Loss: 53.8104 - Accuracy: 0.5714 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 2.4389 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 1.7751 - Accuracy: 0.8929 - F1: 0.8925
sub_10:Test (Best Model) - Loss: 2.4610 - Accuracy: 0.6905 - F1: 0.6577
sub_10:Test (Best Model) - Loss: 2.8009 - Accuracy: 0.6429 - F1: 0.6214
sub_13:Test (Best Model) - Loss: 0.3572 - Accuracy: 0.8929 - F1: 0.8925
sub_14:Test (Best Model) - Loss: 3.9369 - Accuracy: 0.8214 - F1: 0.8170
sub_13:Test (Best Model) - Loss: 0.3796 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 3.1325 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 3.0204 - Accuracy: 0.6786 - F1: 0.6415
sub_13:Test (Best Model) - Loss: 0.5416 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 3.2872 - Accuracy: 0.7619 - F1: 0.7529
sub_13:Test (Best Model) - Loss: 0.4326 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 1.2591 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 2.9185 - Accuracy: 0.8333 - F1: 0.8286
sub_13:Test (Best Model) - Loss: 1.2216 - Accuracy: 0.9286 - F1: 0.9285
sub_13:Test (Best Model) - Loss: 0.0200 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.0676 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.2940 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.0705 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.3088 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.1014 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.5396 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.8601 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.0773 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 2.3858 - Accuracy: 0.6190 - F1: 0.5544
sub_13:Test (Best Model) - Loss: 0.7379 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 2.3897 - Accuracy: 0.6071 - F1: 0.5354
sub_13:Test (Best Model) - Loss: 1.8969 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 1.7971 - Accuracy: 0.5833 - F1: 0.4958
sub_14:Test (Best Model) - Loss: 1.4972 - Accuracy: 0.6190 - F1: 0.5544
sub_13:Test (Best Model) - Loss: 1.1121 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 2.6868 - Accuracy: 0.5714 - F1: 0.4750
sub_13:Test (Best Model) - Loss: 0.3742 - Accuracy: 0.9762 - F1: 0.9762

=== Summary Results ===

acc: 84.64 ± 5.49
F1: 83.85 ± 6.00
acc-in: 96.07 ± 2.20
F1-in: 96.05 ± 2.21
runing time: 1066.12 seconds
