lr: 0.001
sub_12:Test (Best Model) - Loss: 1.0073 - Accuracy: 0.5294 - F1: 0.4818
sub_8:Test (Best Model) - Loss: 2.3559 - Accuracy: 0.3529 - F1: 0.2749
sub_2:Test (Best Model) - Loss: 0.5505 - Accuracy: 0.6232 - F1: 0.5644
sub_4:Test (Best Model) - Loss: 0.6546 - Accuracy: 0.7826 - F1: 0.7853
sub_5:Test (Best Model) - Loss: 2.1712 - Accuracy: 0.5000 - F1: 0.4267
sub_14:Test (Best Model) - Loss: 0.7785 - Accuracy: 0.7059 - F1: 0.7084
sub_15:Test (Best Model) - Loss: 0.6203 - Accuracy: 0.7353 - F1: 0.7360
sub_11:Test (Best Model) - Loss: 0.9067 - Accuracy: 0.7246 - F1: 0.7233
sub_13:Test (Best Model) - Loss: 6.8650 - Accuracy: 0.4265 - F1: 0.3318
sub_1:Test (Best Model) - Loss: 0.7679 - Accuracy: 0.7059 - F1: 0.7217
sub_10:Test (Best Model) - Loss: 2.1594 - Accuracy: 0.4118 - F1: 0.4297
sub_3:Test (Best Model) - Loss: 2.7172 - Accuracy: 0.5882 - F1: 0.5735
sub_9:Test (Best Model) - Loss: 1.7254 - Accuracy: 0.3235 - F1: 0.3940
sub_7:Test (Best Model) - Loss: 0.7454 - Accuracy: 0.7794 - F1: 0.7699
sub_6:Test (Best Model) - Loss: 5.4223 - Accuracy: 0.3824 - F1: 0.2623
sub_4:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.5072 - F1: 0.4499
sub_14:Test (Best Model) - Loss: 2.2806 - Accuracy: 0.4412 - F1: 0.4148
sub_8:Test (Best Model) - Loss: 1.5226 - Accuracy: 0.5882 - F1: 0.5580
sub_5:Test (Best Model) - Loss: 0.4979 - Accuracy: 0.7353 - F1: 0.6956
sub_2:Test (Best Model) - Loss: 1.0845 - Accuracy: 0.6667 - F1: 0.6567
sub_6:Test (Best Model) - Loss: 3.3554 - Accuracy: 0.4118 - F1: 0.3268
sub_12:Test (Best Model) - Loss: 1.3290 - Accuracy: 0.5441 - F1: 0.5000
sub_8:Test (Best Model) - Loss: 1.6274 - Accuracy: 0.3971 - F1: 0.3398
sub_14:Test (Best Model) - Loss: 1.8582 - Accuracy: 0.2059 - F1: 0.1358
sub_1:Test (Best Model) - Loss: 1.1832 - Accuracy: 0.5294 - F1: 0.5200
sub_7:Test (Best Model) - Loss: 1.3623 - Accuracy: 0.5147 - F1: 0.5107
sub_15:Test (Best Model) - Loss: 0.7658 - Accuracy: 0.6176 - F1: 0.6023
sub_11:Test (Best Model) - Loss: 1.8137 - Accuracy: 0.4928 - F1: 0.4673
sub_9:Test (Best Model) - Loss: 2.1955 - Accuracy: 0.3529 - F1: 0.3424
sub_2:Test (Best Model) - Loss: 1.8429 - Accuracy: 0.5507 - F1: 0.5014
sub_5:Test (Best Model) - Loss: 2.1174 - Accuracy: 0.4412 - F1: 0.3615
sub_10:Test (Best Model) - Loss: 1.6591 - Accuracy: 0.3529 - F1: 0.3409
sub_4:Test (Best Model) - Loss: 1.4668 - Accuracy: 0.5797 - F1: 0.5190
sub_13:Test (Best Model) - Loss: 4.6710 - Accuracy: 0.4412 - F1: 0.3524
sub_3:Test (Best Model) - Loss: 2.7860 - Accuracy: 0.4412 - F1: 0.4308
sub_8:Test (Best Model) - Loss: 1.6704 - Accuracy: 0.5294 - F1: 0.5117
sub_6:Test (Best Model) - Loss: 3.4984 - Accuracy: 0.4118 - F1: 0.3268
sub_11:Test (Best Model) - Loss: 0.9390 - Accuracy: 0.5217 - F1: 0.4460
sub_12:Test (Best Model) - Loss: 2.6986 - Accuracy: 0.5000 - F1: 0.4506
sub_7:Test (Best Model) - Loss: 2.7672 - Accuracy: 0.4853 - F1: 0.3957
sub_10:Test (Best Model) - Loss: 2.3199 - Accuracy: 0.0882 - F1: 0.0566
sub_14:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.7353 - F1: 0.7433
sub_15:Test (Best Model) - Loss: 1.1441 - Accuracy: 0.5441 - F1: 0.5778
sub_5:Test (Best Model) - Loss: 0.9420 - Accuracy: 0.6029 - F1: 0.5535
sub_1:Test (Best Model) - Loss: 0.9828 - Accuracy: 0.6324 - F1: 0.6506
sub_2:Test (Best Model) - Loss: 1.3947 - Accuracy: 0.3043 - F1: 0.2494
sub_9:Test (Best Model) - Loss: 2.0892 - Accuracy: 0.5000 - F1: 0.3953
sub_3:Test (Best Model) - Loss: 2.0394 - Accuracy: 0.5441 - F1: 0.4625
sub_8:Test (Best Model) - Loss: 1.0257 - Accuracy: 0.7500 - F1: 0.7600
sub_4:Test (Best Model) - Loss: 0.8783 - Accuracy: 0.6232 - F1: 0.5776
sub_14:Test (Best Model) - Loss: 0.3824 - Accuracy: 0.8088 - F1: 0.8147
sub_13:Test (Best Model) - Loss: 8.4895 - Accuracy: 0.2059 - F1: 0.0854
sub_11:Test (Best Model) - Loss: 0.9489 - Accuracy: 0.5797 - F1: 0.5685
sub_6:Test (Best Model) - Loss: 3.9681 - Accuracy: 0.4118 - F1: 0.3490
sub_8:Test (Best Model) - Loss: 0.9777 - Accuracy: 0.4706 - F1: 0.4529
sub_10:Test (Best Model) - Loss: 1.5807 - Accuracy: 0.4118 - F1: 0.3886
sub_12:Test (Best Model) - Loss: 2.0928 - Accuracy: 0.5000 - F1: 0.4862
sub_9:Test (Best Model) - Loss: 2.7244 - Accuracy: 0.4265 - F1: 0.4104
sub_1:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.6912 - F1: 0.6862
sub_2:Test (Best Model) - Loss: 2.1316 - Accuracy: 0.4638 - F1: 0.4274
sub_5:Test (Best Model) - Loss: 6.1441 - Accuracy: 0.2059 - F1: 0.1045
sub_7:Test (Best Model) - Loss: 0.5516 - Accuracy: 0.7794 - F1: 0.7796
sub_11:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7391 - F1: 0.7265
sub_8:Test (Best Model) - Loss: 0.5514 - Accuracy: 0.7941 - F1: 0.8006
sub_15:Test (Best Model) - Loss: 0.7760 - Accuracy: 0.6912 - F1: 0.7017
sub_13:Test (Best Model) - Loss: 8.3203 - Accuracy: 0.2941 - F1: 0.1917
sub_4:Test (Best Model) - Loss: 0.6256 - Accuracy: 0.7681 - F1: 0.7736
sub_14:Test (Best Model) - Loss: 1.5137 - Accuracy: 0.6912 - F1: 0.6629
sub_3:Test (Best Model) - Loss: 0.7916 - Accuracy: 0.7647 - F1: 0.7655
sub_4:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.6812 - F1: 0.6097
sub_10:Test (Best Model) - Loss: 1.4889 - Accuracy: 0.5147 - F1: 0.5062
sub_12:Test (Best Model) - Loss: 0.8986 - Accuracy: 0.4559 - F1: 0.4564
sub_6:Test (Best Model) - Loss: 2.4408 - Accuracy: 0.4412 - F1: 0.3507
sub_8:Test (Best Model) - Loss: 1.0488 - Accuracy: 0.5882 - F1: 0.5819
sub_1:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.7647 - F1: 0.7774
sub_9:Test (Best Model) - Loss: 1.5094 - Accuracy: 0.5882 - F1: 0.6136
sub_13:Test (Best Model) - Loss: 4.8766 - Accuracy: 0.4559 - F1: 0.3611
sub_12:Test (Best Model) - Loss: 1.3502 - Accuracy: 0.4058 - F1: 0.3184
sub_5:Test (Best Model) - Loss: 1.7547 - Accuracy: 0.6765 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 1.5535 - Accuracy: 0.6471 - F1: 0.6257
sub_2:Test (Best Model) - Loss: 0.8477 - Accuracy: 0.5882 - F1: 0.6207
sub_15:Test (Best Model) - Loss: 2.0085 - Accuracy: 0.6029 - F1: 0.6253
sub_4:Test (Best Model) - Loss: 0.4686 - Accuracy: 0.8841 - F1: 0.8855
sub_6:Test (Best Model) - Loss: 0.9740 - Accuracy: 0.6087 - F1: 0.5737
sub_9:Test (Best Model) - Loss: 2.1392 - Accuracy: 0.4559 - F1: 0.3492
sub_12:Test (Best Model) - Loss: 0.9892 - Accuracy: 0.4348 - F1: 0.3490
sub_11:Test (Best Model) - Loss: 1.4577 - Accuracy: 0.6087 - F1: 0.5894
sub_10:Test (Best Model) - Loss: 2.2264 - Accuracy: 0.4559 - F1: 0.4123
sub_3:Test (Best Model) - Loss: 0.7763 - Accuracy: 0.7059 - F1: 0.7172
sub_14:Test (Best Model) - Loss: 1.4282 - Accuracy: 0.6618 - F1: 0.5868
sub_7:Test (Best Model) - Loss: 3.1640 - Accuracy: 0.6176 - F1: 0.5646
sub_15:Test (Best Model) - Loss: 0.8677 - Accuracy: 0.5441 - F1: 0.4971
sub_9:Test (Best Model) - Loss: 1.0561 - Accuracy: 0.5588 - F1: 0.5769
sub_1:Test (Best Model) - Loss: 3.2105 - Accuracy: 0.3623 - F1: 0.2836
sub_8:Test (Best Model) - Loss: 0.6274 - Accuracy: 0.6618 - F1: 0.6359
sub_5:Test (Best Model) - Loss: 1.3054 - Accuracy: 0.5588 - F1: 0.5599
sub_6:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6812 - F1: 0.6520
sub_12:Test (Best Model) - Loss: 1.0282 - Accuracy: 0.4493 - F1: 0.3931
sub_3:Test (Best Model) - Loss: 1.1691 - Accuracy: 0.4928 - F1: 0.4723
sub_2:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.6324 - F1: 0.6214
sub_13:Test (Best Model) - Loss: 3.4050 - Accuracy: 0.3333 - F1: 0.2535
sub_14:Test (Best Model) - Loss: 1.3735 - Accuracy: 0.6765 - F1: 0.6487
sub_7:Test (Best Model) - Loss: 6.9443 - Accuracy: 0.3529 - F1: 0.2750
sub_6:Test (Best Model) - Loss: 1.1531 - Accuracy: 0.5942 - F1: 0.5343
sub_1:Test (Best Model) - Loss: 3.1493 - Accuracy: 0.4493 - F1: 0.3874
sub_4:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.7681 - F1: 0.7681
sub_10:Test (Best Model) - Loss: 1.5574 - Accuracy: 0.5588 - F1: 0.5143
sub_11:Test (Best Model) - Loss: 0.9216 - Accuracy: 0.6667 - F1: 0.6128
sub_15:Test (Best Model) - Loss: 0.5237 - Accuracy: 0.7794 - F1: 0.7848
sub_6:Test (Best Model) - Loss: 0.8975 - Accuracy: 0.5217 - F1: 0.5240
sub_12:Test (Best Model) - Loss: 1.0943 - Accuracy: 0.3768 - F1: 0.2989
sub_3:Test (Best Model) - Loss: 1.7883 - Accuracy: 0.6522 - F1: 0.6243
sub_13:Test (Best Model) - Loss: 0.6053 - Accuracy: 0.6957 - F1: 0.6691
sub_9:Test (Best Model) - Loss: 3.2794 - Accuracy: 0.5000 - F1: 0.3890
sub_10:Test (Best Model) - Loss: 1.0293 - Accuracy: 0.5588 - F1: 0.5279
sub_7:Test (Best Model) - Loss: 5.8151 - Accuracy: 0.3971 - F1: 0.3173
sub_5:Test (Best Model) - Loss: 0.9574 - Accuracy: 0.6176 - F1: 0.6399
sub_2:Test (Best Model) - Loss: 0.6386 - Accuracy: 0.6176 - F1: 0.6120
sub_8:Test (Best Model) - Loss: 0.2856 - Accuracy: 0.8676 - F1: 0.8740
sub_14:Test (Best Model) - Loss: 0.4252 - Accuracy: 0.8971 - F1: 0.8914
sub_1:Test (Best Model) - Loss: 2.3540 - Accuracy: 0.4783 - F1: 0.4000
sub_4:Test (Best Model) - Loss: 0.4288 - Accuracy: 0.7246 - F1: 0.7287
sub_11:Test (Best Model) - Loss: 1.2295 - Accuracy: 0.5942 - F1: 0.5917
sub_7:Test (Best Model) - Loss: 2.7389 - Accuracy: 0.2794 - F1: 0.2982
sub_15:Test (Best Model) - Loss: 0.7509 - Accuracy: 0.6912 - F1: 0.6926
sub_9:Test (Best Model) - Loss: 2.6804 - Accuracy: 0.2794 - F1: 0.2588
sub_10:Test (Best Model) - Loss: 0.9109 - Accuracy: 0.4853 - F1: 0.4653
sub_6:Test (Best Model) - Loss: 0.9491 - Accuracy: 0.6232 - F1: 0.5580
sub_2:Test (Best Model) - Loss: 0.4960 - Accuracy: 0.7647 - F1: 0.7580
sub_13:Test (Best Model) - Loss: 1.0267 - Accuracy: 0.6087 - F1: 0.5817
sub_3:Test (Best Model) - Loss: 0.9130 - Accuracy: 0.6957 - F1: 0.6984
sub_14:Test (Best Model) - Loss: 1.4869 - Accuracy: 0.5441 - F1: 0.4735
sub_12:Test (Best Model) - Loss: 3.4454 - Accuracy: 0.4783 - F1: 0.4461
sub_5:Test (Best Model) - Loss: 2.2812 - Accuracy: 0.4559 - F1: 0.4300
sub_8:Test (Best Model) - Loss: 0.7457 - Accuracy: 0.5882 - F1: 0.5500
sub_10:Test (Best Model) - Loss: 0.9524 - Accuracy: 0.6765 - F1: 0.6281
sub_1:Test (Best Model) - Loss: 0.8727 - Accuracy: 0.5652 - F1: 0.5619
sub_12:Test (Best Model) - Loss: 0.8780 - Accuracy: 0.4559 - F1: 0.4054
sub_7:Test (Best Model) - Loss: 6.7288 - Accuracy: 0.3824 - F1: 0.3002
sub_4:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.8986 - F1: 0.8988
sub_13:Test (Best Model) - Loss: 0.8016 - Accuracy: 0.5217 - F1: 0.5109
sub_3:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.3913 - F1: 0.3290
sub_10:Test (Best Model) - Loss: 1.0679 - Accuracy: 0.4783 - F1: 0.4572
sub_11:Test (Best Model) - Loss: 1.1339 - Accuracy: 0.5652 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.8538 - Accuracy: 0.6176 - F1: 0.6109
sub_6:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.6232 - F1: 0.5868
sub_2:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.7500 - F1: 0.7220
sub_15:Test (Best Model) - Loss: 0.5032 - Accuracy: 0.8382 - F1: 0.8402
sub_8:Test (Best Model) - Loss: 1.0872 - Accuracy: 0.6765 - F1: 0.6778
sub_9:Test (Best Model) - Loss: 5.2409 - Accuracy: 0.4706 - F1: 0.3377
sub_7:Test (Best Model) - Loss: 1.0266 - Accuracy: 0.6471 - F1: 0.6693
sub_14:Test (Best Model) - Loss: 1.0101 - Accuracy: 0.7794 - F1: 0.7867
sub_5:Test (Best Model) - Loss: 1.1092 - Accuracy: 0.6176 - F1: 0.6220
sub_9:Test (Best Model) - Loss: 1.4818 - Accuracy: 0.5000 - F1: 0.4457
sub_10:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.5362 - F1: 0.4986
sub_1:Test (Best Model) - Loss: 2.0049 - Accuracy: 0.4348 - F1: 0.3661
sub_13:Test (Best Model) - Loss: 1.0435 - Accuracy: 0.7101 - F1: 0.6800
sub_3:Test (Best Model) - Loss: 2.6331 - Accuracy: 0.4928 - F1: 0.5345
sub_11:Test (Best Model) - Loss: 0.8622 - Accuracy: 0.6377 - F1: 0.6155
sub_12:Test (Best Model) - Loss: 0.8001 - Accuracy: 0.5000 - F1: 0.4867
sub_4:Test (Best Model) - Loss: 0.4407 - Accuracy: 0.7246 - F1: 0.6513
sub_15:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.6471 - F1: 0.6277
sub_1:Test (Best Model) - Loss: 0.8757 - Accuracy: 0.7206 - F1: 0.6789
sub_6:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.6957 - F1: 0.6858
sub_5:Test (Best Model) - Loss: 3.1505 - Accuracy: 0.5000 - F1: 0.4474
sub_8:Test (Best Model) - Loss: 1.4882 - Accuracy: 0.6029 - F1: 0.5843
sub_7:Test (Best Model) - Loss: 2.1426 - Accuracy: 0.7059 - F1: 0.6337
sub_3:Test (Best Model) - Loss: 3.2827 - Accuracy: 0.5652 - F1: 0.4846
sub_9:Test (Best Model) - Loss: 0.8593 - Accuracy: 0.5000 - F1: 0.4205
sub_13:Test (Best Model) - Loss: 1.2250 - Accuracy: 0.4118 - F1: 0.3135
sub_10:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.6812 - F1: 0.6680
sub_2:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.7246 - F1: 0.7348
sub_14:Test (Best Model) - Loss: 3.9290 - Accuracy: 0.4559 - F1: 0.3601
sub_4:Test (Best Model) - Loss: 0.4874 - Accuracy: 0.7391 - F1: 0.7232
sub_9:Test (Best Model) - Loss: 0.7513 - Accuracy: 0.5147 - F1: 0.4246
sub_5:Test (Best Model) - Loss: 0.9599 - Accuracy: 0.4559 - F1: 0.3400
sub_12:Test (Best Model) - Loss: 0.8391 - Accuracy: 0.5882 - F1: 0.6057
sub_11:Test (Best Model) - Loss: 3.6351 - Accuracy: 0.3478 - F1: 0.2621
sub_1:Test (Best Model) - Loss: 0.2459 - Accuracy: 0.9412 - F1: 0.9440
sub_6:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.6087 - F1: 0.6330
sub_8:Test (Best Model) - Loss: 0.5413 - Accuracy: 0.8529 - F1: 0.8545
sub_3:Test (Best Model) - Loss: 2.9817 - Accuracy: 0.4928 - F1: 0.4233
sub_7:Test (Best Model) - Loss: 2.6939 - Accuracy: 0.4706 - F1: 0.4375
sub_14:Test (Best Model) - Loss: 1.0500 - Accuracy: 0.5735 - F1: 0.5503
sub_10:Test (Best Model) - Loss: 0.8912 - Accuracy: 0.7391 - F1: 0.7208
sub_15:Test (Best Model) - Loss: 1.1940 - Accuracy: 0.7500 - F1: 0.7266
sub_13:Test (Best Model) - Loss: 1.8604 - Accuracy: 0.2647 - F1: 0.2473
sub_12:Test (Best Model) - Loss: 0.5753 - Accuracy: 0.7059 - F1: 0.6395
sub_2:Test (Best Model) - Loss: 5.2340 - Accuracy: 0.1884 - F1: 0.1140
sub_5:Test (Best Model) - Loss: 1.5597 - Accuracy: 0.6912 - F1: 0.6240
sub_3:Test (Best Model) - Loss: 1.8791 - Accuracy: 0.4493 - F1: 0.3676
sub_9:Test (Best Model) - Loss: 1.3102 - Accuracy: 0.5441 - F1: 0.5469
sub_11:Test (Best Model) - Loss: 2.0003 - Accuracy: 0.6087 - F1: 0.5975
sub_1:Test (Best Model) - Loss: 1.0266 - Accuracy: 0.6471 - F1: 0.6374
sub_6:Test (Best Model) - Loss: 0.5874 - Accuracy: 0.6812 - F1: 0.7049
sub_7:Test (Best Model) - Loss: 1.6603 - Accuracy: 0.6765 - F1: 0.6843
sub_4:Test (Best Model) - Loss: 0.4510 - Accuracy: 0.7101 - F1: 0.6468
sub_8:Test (Best Model) - Loss: 0.4285 - Accuracy: 0.8382 - F1: 0.8382
sub_14:Test (Best Model) - Loss: 1.0582 - Accuracy: 0.8088 - F1: 0.8120
sub_13:Test (Best Model) - Loss: 1.0710 - Accuracy: 0.5147 - F1: 0.4959
sub_5:Test (Best Model) - Loss: 1.0055 - Accuracy: 0.7353 - F1: 0.6748
sub_15:Test (Best Model) - Loss: 0.8443 - Accuracy: 0.6618 - F1: 0.6408
sub_10:Test (Best Model) - Loss: 1.2059 - Accuracy: 0.6522 - F1: 0.6534
sub_11:Test (Best Model) - Loss: 1.2283 - Accuracy: 0.5797 - F1: 0.5360
sub_3:Test (Best Model) - Loss: 2.2538 - Accuracy: 0.5362 - F1: 0.4939
sub_2:Test (Best Model) - Loss: 4.6182 - Accuracy: 0.3188 - F1: 0.2255
sub_6:Test (Best Model) - Loss: 0.4606 - Accuracy: 0.7971 - F1: 0.7981
sub_1:Test (Best Model) - Loss: 0.5905 - Accuracy: 0.7647 - F1: 0.7654
sub_14:Test (Best Model) - Loss: 2.1043 - Accuracy: 0.7059 - F1: 0.5973
sub_4:Test (Best Model) - Loss: 0.2834 - Accuracy: 0.8841 - F1: 0.8857
sub_13:Test (Best Model) - Loss: 1.1625 - Accuracy: 0.5588 - F1: 0.5333
sub_9:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.5588 - F1: 0.5493
sub_15:Test (Best Model) - Loss: 0.7721 - Accuracy: 0.6912 - F1: 0.6838
sub_7:Test (Best Model) - Loss: 0.7030 - Accuracy: 0.7794 - F1: 0.7723
sub_2:Test (Best Model) - Loss: 0.7597 - Accuracy: 0.6087 - F1: 0.5774
sub_5:Test (Best Model) - Loss: 3.7078 - Accuracy: 0.2941 - F1: 0.1949
sub_13:Test (Best Model) - Loss: 0.9399 - Accuracy: 0.5588 - F1: 0.5567
sub_1:Test (Best Model) - Loss: 0.8822 - Accuracy: 0.6912 - F1: 0.6075
sub_11:Test (Best Model) - Loss: 1.1939 - Accuracy: 0.6812 - F1: 0.6503
sub_3:Test (Best Model) - Loss: 1.7015 - Accuracy: 0.5797 - F1: 0.5749
sub_15:Test (Best Model) - Loss: 0.5683 - Accuracy: 0.7647 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 1.2062 - Accuracy: 0.5072 - F1: 0.5183
sub_4:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.6812 - F1: 0.6562
sub_11:Test (Best Model) - Loss: 1.6910 - Accuracy: 0.5797 - F1: 0.5257
sub_15:Test (Best Model) - Loss: 0.6522 - Accuracy: 0.6618 - F1: 0.6646
sub_18:Test (Best Model) - Loss: 1.0300 - Accuracy: 0.4348 - F1: 0.3360
sub_19:Test (Best Model) - Loss: 1.2089 - Accuracy: 0.5882 - F1: 0.6066
sub_26:Test (Best Model) - Loss: 0.4937 - Accuracy: 0.7246 - F1: 0.6758
sub_16:Test (Best Model) - Loss: 1.8304 - Accuracy: 0.4853 - F1: 0.4582
sub_29:Test (Best Model) - Loss: 0.8744 - Accuracy: 0.4853 - F1: 0.4031
sub_23:Test (Best Model) - Loss: 0.8908 - Accuracy: 0.4638 - F1: 0.3949
sub_20:Test (Best Model) - Loss: 1.1088 - Accuracy: 0.5294 - F1: 0.4811
sub_22:Test (Best Model) - Loss: 1.2756 - Accuracy: 0.3824 - F1: 0.4249
sub_21:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.6912 - F1: 0.6944
sub_25:Test (Best Model) - Loss: 0.9965 - Accuracy: 0.7826 - F1: 0.7751
sub_24:Test (Best Model) - Loss: 1.0485 - Accuracy: 0.7059 - F1: 0.6996
sub_26:Test (Best Model) - Loss: 0.8657 - Accuracy: 0.4928 - F1: 0.4151
sub_27:Test (Best Model) - Loss: 2.3080 - Accuracy: 0.4928 - F1: 0.4336
sub_28:Test (Best Model) - Loss: 1.4033 - Accuracy: 0.7500 - F1: 0.7305
sub_17:Test (Best Model) - Loss: 2.3080 - Accuracy: 0.4928 - F1: 0.4336
sub_23:Test (Best Model) - Loss: 1.0200 - Accuracy: 0.3913 - F1: 0.3583
sub_18:Test (Best Model) - Loss: 1.2646 - Accuracy: 0.7101 - F1: 0.6655
sub_25:Test (Best Model) - Loss: 1.1557 - Accuracy: 0.5072 - F1: 0.4850
sub_29:Test (Best Model) - Loss: 0.9291 - Accuracy: 0.6324 - F1: 0.6539
sub_22:Test (Best Model) - Loss: 2.5223 - Accuracy: 0.4853 - F1: 0.4736
sub_21:Test (Best Model) - Loss: 1.9974 - Accuracy: 0.6324 - F1: 0.6086
sub_20:Test (Best Model) - Loss: 1.0597 - Accuracy: 0.6471 - F1: 0.6001
sub_28:Test (Best Model) - Loss: 3.1152 - Accuracy: 0.3088 - F1: 0.2779
sub_24:Test (Best Model) - Loss: 1.1976 - Accuracy: 0.5735 - F1: 0.5472
sub_18:Test (Best Model) - Loss: 0.7533 - Accuracy: 0.7101 - F1: 0.7147
sub_16:Test (Best Model) - Loss: 4.5487 - Accuracy: 0.4265 - F1: 0.3481
sub_27:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.7826 - F1: 0.7778
sub_17:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.7826 - F1: 0.7778
sub_19:Test (Best Model) - Loss: 0.8757 - Accuracy: 0.7794 - F1: 0.7843
sub_21:Test (Best Model) - Loss: 1.0693 - Accuracy: 0.5882 - F1: 0.5344
sub_23:Test (Best Model) - Loss: 0.8956 - Accuracy: 0.5072 - F1: 0.4691
sub_25:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.5362 - F1: 0.5006
sub_29:Test (Best Model) - Loss: 1.7094 - Accuracy: 0.4853 - F1: 0.5020
sub_26:Test (Best Model) - Loss: 1.7630 - Accuracy: 0.5362 - F1: 0.5187
sub_18:Test (Best Model) - Loss: 0.8673 - Accuracy: 0.4638 - F1: 0.3697
sub_22:Test (Best Model) - Loss: 2.6128 - Accuracy: 0.5735 - F1: 0.5582
sub_24:Test (Best Model) - Loss: 1.4646 - Accuracy: 0.5882 - F1: 0.5385
sub_20:Test (Best Model) - Loss: 1.6510 - Accuracy: 0.5000 - F1: 0.4512
sub_28:Test (Best Model) - Loss: 0.9030 - Accuracy: 0.7059 - F1: 0.7143
sub_19:Test (Best Model) - Loss: 2.8600 - Accuracy: 0.4265 - F1: 0.3400
sub_23:Test (Best Model) - Loss: 2.8733 - Accuracy: 0.4058 - F1: 0.3516
sub_18:Test (Best Model) - Loss: 1.3059 - Accuracy: 0.3188 - F1: 0.3042
sub_16:Test (Best Model) - Loss: 2.6353 - Accuracy: 0.3971 - F1: 0.4109
sub_27:Test (Best Model) - Loss: 0.8572 - Accuracy: 0.6232 - F1: 0.5766
sub_17:Test (Best Model) - Loss: 0.8572 - Accuracy: 0.6232 - F1: 0.5766
sub_29:Test (Best Model) - Loss: 0.9141 - Accuracy: 0.5000 - F1: 0.4769
sub_21:Test (Best Model) - Loss: 2.5310 - Accuracy: 0.5147 - F1: 0.4887
sub_22:Test (Best Model) - Loss: 0.9124 - Accuracy: 0.5294 - F1: 0.5011
sub_19:Test (Best Model) - Loss: 1.2394 - Accuracy: 0.6176 - F1: 0.5832
sub_25:Test (Best Model) - Loss: 0.6159 - Accuracy: 0.7971 - F1: 0.7966
sub_26:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.7826 - F1: 0.7897
sub_18:Test (Best Model) - Loss: 1.5113 - Accuracy: 0.2941 - F1: 0.2055
sub_28:Test (Best Model) - Loss: 0.7731 - Accuracy: 0.6176 - F1: 0.6185
sub_23:Test (Best Model) - Loss: 0.9201 - Accuracy: 0.4638 - F1: 0.3878
sub_24:Test (Best Model) - Loss: 0.4392 - Accuracy: 0.8382 - F1: 0.8404
sub_20:Test (Best Model) - Loss: 0.5883 - Accuracy: 0.6912 - F1: 0.6595
sub_23:Test (Best Model) - Loss: 0.9887 - Accuracy: 0.4853 - F1: 0.3892
sub_19:Test (Best Model) - Loss: 1.9270 - Accuracy: 0.4265 - F1: 0.4088
sub_29:Test (Best Model) - Loss: 0.7453 - Accuracy: 0.6618 - F1: 0.5921
sub_22:Test (Best Model) - Loss: 3.2948 - Accuracy: 0.4853 - F1: 0.4544
sub_25:Test (Best Model) - Loss: 0.9004 - Accuracy: 0.7681 - F1: 0.7626
sub_23:Test (Best Model) - Loss: 1.0723 - Accuracy: 0.5294 - F1: 0.4630
sub_28:Test (Best Model) - Loss: 3.2756 - Accuracy: 0.5294 - F1: 0.4399
sub_20:Test (Best Model) - Loss: 2.0117 - Accuracy: 0.4265 - F1: 0.3652
sub_18:Test (Best Model) - Loss: 1.3303 - Accuracy: 0.5000 - F1: 0.4855
sub_27:Test (Best Model) - Loss: 1.6497 - Accuracy: 0.6232 - F1: 0.5561
sub_26:Test (Best Model) - Loss: 0.7114 - Accuracy: 0.7101 - F1: 0.7037
sub_16:Test (Best Model) - Loss: 2.5252 - Accuracy: 0.4412 - F1: 0.4069
sub_21:Test (Best Model) - Loss: 1.8262 - Accuracy: 0.5441 - F1: 0.4914
sub_24:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.7500 - F1: 0.7592
sub_17:Test (Best Model) - Loss: 1.6497 - Accuracy: 0.6232 - F1: 0.5561
sub_25:Test (Best Model) - Loss: 0.8422 - Accuracy: 0.5147 - F1: 0.4788
sub_28:Test (Best Model) - Loss: 1.7131 - Accuracy: 0.4118 - F1: 0.3635
sub_20:Test (Best Model) - Loss: 0.5049 - Accuracy: 0.7206 - F1: 0.6803
sub_22:Test (Best Model) - Loss: 0.9722 - Accuracy: 0.5362 - F1: 0.5146
sub_29:Test (Best Model) - Loss: 0.3764 - Accuracy: 0.7500 - F1: 0.7563
sub_19:Test (Best Model) - Loss: 2.5822 - Accuracy: 0.6471 - F1: 0.6274
sub_18:Test (Best Model) - Loss: 0.7497 - Accuracy: 0.6176 - F1: 0.6162
sub_28:Test (Best Model) - Loss: 2.4561 - Accuracy: 0.3676 - F1: 0.2469
sub_27:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.5942 - F1: 0.5731
sub_26:Test (Best Model) - Loss: 2.9583 - Accuracy: 0.6176 - F1: 0.5754
sub_25:Test (Best Model) - Loss: 1.0314 - Accuracy: 0.7353 - F1: 0.7338
sub_16:Test (Best Model) - Loss: 4.0310 - Accuracy: 0.4412 - F1: 0.3850
sub_23:Test (Best Model) - Loss: 2.1074 - Accuracy: 0.3235 - F1: 0.2598
sub_17:Test (Best Model) - Loss: 0.8856 - Accuracy: 0.5942 - F1: 0.5731
sub_19:Test (Best Model) - Loss: 0.8785 - Accuracy: 0.4118 - F1: 0.4399
sub_24:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.7353 - F1: 0.7174
sub_18:Test (Best Model) - Loss: 0.8707 - Accuracy: 0.4706 - F1: 0.3750
sub_21:Test (Best Model) - Loss: 0.3921 - Accuracy: 0.8382 - F1: 0.8341
sub_22:Test (Best Model) - Loss: 2.3167 - Accuracy: 0.4203 - F1: 0.3844
sub_27:Test (Best Model) - Loss: 1.1768 - Accuracy: 0.4348 - F1: 0.3557
sub_17:Test (Best Model) - Loss: 1.1768 - Accuracy: 0.4348 - F1: 0.3557
sub_20:Test (Best Model) - Loss: 0.5767 - Accuracy: 0.7941 - F1: 0.7986
sub_23:Test (Best Model) - Loss: 0.8932 - Accuracy: 0.5000 - F1: 0.4846
sub_29:Test (Best Model) - Loss: 0.7756 - Accuracy: 0.5147 - F1: 0.4519
sub_26:Test (Best Model) - Loss: 2.1841 - Accuracy: 0.4118 - F1: 0.3369
sub_24:Test (Best Model) - Loss: 1.0457 - Accuracy: 0.7206 - F1: 0.7373
sub_28:Test (Best Model) - Loss: 1.9756 - Accuracy: 0.4706 - F1: 0.4278
sub_25:Test (Best Model) - Loss: 0.9000 - Accuracy: 0.6618 - F1: 0.6633
sub_22:Test (Best Model) - Loss: 1.6847 - Accuracy: 0.4928 - F1: 0.4329
sub_16:Test (Best Model) - Loss: 2.2343 - Accuracy: 0.4706 - F1: 0.4042
sub_18:Test (Best Model) - Loss: 1.4173 - Accuracy: 0.5588 - F1: 0.5344
sub_21:Test (Best Model) - Loss: 1.9187 - Accuracy: 0.6912 - F1: 0.6292
sub_19:Test (Best Model) - Loss: 2.7906 - Accuracy: 0.5000 - F1: 0.4607
sub_27:Test (Best Model) - Loss: 1.4551 - Accuracy: 0.4058 - F1: 0.3443
sub_23:Test (Best Model) - Loss: 1.9090 - Accuracy: 0.4559 - F1: 0.4294
sub_28:Test (Best Model) - Loss: 0.6411 - Accuracy: 0.6324 - F1: 0.5770
sub_17:Test (Best Model) - Loss: 1.4551 - Accuracy: 0.4058 - F1: 0.3443
sub_20:Test (Best Model) - Loss: 0.6188 - Accuracy: 0.7647 - F1: 0.7653
sub_18:Test (Best Model) - Loss: 0.9468 - Accuracy: 0.4559 - F1: 0.3640
sub_29:Test (Best Model) - Loss: 0.9103 - Accuracy: 0.6618 - F1: 0.5934
sub_24:Test (Best Model) - Loss: 0.8612 - Accuracy: 0.6765 - F1: 0.6949
sub_20:Test (Best Model) - Loss: 0.9549 - Accuracy: 0.5294 - F1: 0.4823
sub_26:Test (Best Model) - Loss: 2.9686 - Accuracy: 0.5441 - F1: 0.4930
sub_27:Test (Best Model) - Loss: 0.8736 - Accuracy: 0.4783 - F1: 0.3768
sub_16:Test (Best Model) - Loss: 5.9597 - Accuracy: 0.2500 - F1: 0.2833
sub_23:Test (Best Model) - Loss: 1.1166 - Accuracy: 0.4638 - F1: 0.4855
sub_17:Test (Best Model) - Loss: 0.8736 - Accuracy: 0.4783 - F1: 0.3768
sub_25:Test (Best Model) - Loss: 0.3633 - Accuracy: 0.9118 - F1: 0.9115
sub_28:Test (Best Model) - Loss: 5.2826 - Accuracy: 0.3088 - F1: 0.1739
sub_21:Test (Best Model) - Loss: 0.4974 - Accuracy: 0.7500 - F1: 0.7238
sub_24:Test (Best Model) - Loss: 0.8019 - Accuracy: 0.6176 - F1: 0.6153
sub_22:Test (Best Model) - Loss: 2.5469 - Accuracy: 0.4783 - F1: 0.4143
sub_25:Test (Best Model) - Loss: 2.0720 - Accuracy: 0.3235 - F1: 0.2663
sub_18:Test (Best Model) - Loss: 1.7165 - Accuracy: 0.4853 - F1: 0.4694
sub_19:Test (Best Model) - Loss: 3.6837 - Accuracy: 0.5441 - F1: 0.5312
sub_16:Test (Best Model) - Loss: 0.9975 - Accuracy: 0.5588 - F1: 0.5575
sub_28:Test (Best Model) - Loss: 1.6323 - Accuracy: 0.4559 - F1: 0.3501
sub_21:Test (Best Model) - Loss: 0.9511 - Accuracy: 0.4412 - F1: 0.3887
sub_20:Test (Best Model) - Loss: 0.7739 - Accuracy: 0.7500 - F1: 0.7453
sub_26:Test (Best Model) - Loss: 0.9532 - Accuracy: 0.5441 - F1: 0.5320
sub_29:Test (Best Model) - Loss: 0.3618 - Accuracy: 0.8676 - F1: 0.8741
sub_24:Test (Best Model) - Loss: 0.6730 - Accuracy: 0.7353 - F1: 0.7290
sub_25:Test (Best Model) - Loss: 1.1357 - Accuracy: 0.6618 - F1: 0.6726
sub_23:Test (Best Model) - Loss: 5.0082 - Accuracy: 0.5507 - F1: 0.4964
sub_16:Test (Best Model) - Loss: 1.2283 - Accuracy: 0.3824 - F1: 0.3516
sub_22:Test (Best Model) - Loss: 3.9934 - Accuracy: 0.4783 - F1: 0.4213
sub_27:Test (Best Model) - Loss: 2.0159 - Accuracy: 0.5507 - F1: 0.5137
sub_17:Test (Best Model) - Loss: 2.0159 - Accuracy: 0.5507 - F1: 0.5137
sub_21:Test (Best Model) - Loss: 1.2265 - Accuracy: 0.6324 - F1: 0.5716
sub_27:Test (Best Model) - Loss: 1.6557 - Accuracy: 0.3768 - F1: 0.2939
sub_22:Test (Best Model) - Loss: 1.0609 - Accuracy: 0.4412 - F1: 0.3895
sub_20:Test (Best Model) - Loss: 2.0200 - Accuracy: 0.6812 - F1: 0.6735
sub_18:Test (Best Model) - Loss: 1.5036 - Accuracy: 0.6029 - F1: 0.6201
sub_19:Test (Best Model) - Loss: 2.0514 - Accuracy: 0.4853 - F1: 0.4680
sub_17:Test (Best Model) - Loss: 1.6557 - Accuracy: 0.3768 - F1: 0.2939
sub_29:Test (Best Model) - Loss: 0.7570 - Accuracy: 0.6765 - F1: 0.6437
sub_28:Test (Best Model) - Loss: 2.1564 - Accuracy: 0.4706 - F1: 0.4373
sub_26:Test (Best Model) - Loss: 1.4707 - Accuracy: 0.4265 - F1: 0.4122
sub_24:Test (Best Model) - Loss: 3.2768 - Accuracy: 0.3529 - F1: 0.2966
sub_27:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.4853 - F1: 0.5056
sub_20:Test (Best Model) - Loss: 0.6813 - Accuracy: 0.6957 - F1: 0.6969
sub_17:Test (Best Model) - Loss: 1.1491 - Accuracy: 0.4853 - F1: 0.5056
sub_26:Test (Best Model) - Loss: 1.1616 - Accuracy: 0.4118 - F1: 0.3316
sub_25:Test (Best Model) - Loss: 1.1975 - Accuracy: 0.6324 - F1: 0.6255
sub_23:Test (Best Model) - Loss: 3.0658 - Accuracy: 0.6087 - F1: 0.5433
sub_21:Test (Best Model) - Loss: 2.8844 - Accuracy: 0.5147 - F1: 0.4622
sub_29:Test (Best Model) - Loss: 1.2483 - Accuracy: 0.5072 - F1: 0.3955
sub_27:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.7353 - F1: 0.7463
sub_19:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.5441 - F1: 0.5111
sub_16:Test (Best Model) - Loss: 5.0484 - Accuracy: 0.3529 - F1: 0.3274
sub_17:Test (Best Model) - Loss: 0.6999 - Accuracy: 0.7353 - F1: 0.7463
sub_24:Test (Best Model) - Loss: 3.1631 - Accuracy: 0.3529 - F1: 0.3407
sub_18:Test (Best Model) - Loss: 1.4665 - Accuracy: 0.5588 - F1: 0.5865
sub_22:Test (Best Model) - Loss: 3.1994 - Accuracy: 0.4412 - F1: 0.3852
sub_21:Test (Best Model) - Loss: 2.5071 - Accuracy: 0.4265 - F1: 0.3490
sub_28:Test (Best Model) - Loss: 2.8761 - Accuracy: 0.3235 - F1: 0.2958
sub_26:Test (Best Model) - Loss: 2.0291 - Accuracy: 0.6618 - F1: 0.6131
sub_20:Test (Best Model) - Loss: 1.9971 - Accuracy: 0.5942 - F1: 0.5679
sub_23:Test (Best Model) - Loss: 3.4699 - Accuracy: 0.5072 - F1: 0.4509
sub_19:Test (Best Model) - Loss: 2.0030 - Accuracy: 0.2500 - F1: 0.2143
sub_25:Test (Best Model) - Loss: 2.2982 - Accuracy: 0.3529 - F1: 0.2672
sub_16:Test (Best Model) - Loss: 2.2774 - Accuracy: 0.3235 - F1: 0.2763
sub_27:Test (Best Model) - Loss: 0.9803 - Accuracy: 0.7059 - F1: 0.6647
sub_24:Test (Best Model) - Loss: 2.1034 - Accuracy: 0.4118 - F1: 0.4199
sub_29:Test (Best Model) - Loss: 1.4235 - Accuracy: 0.4638 - F1: 0.4422
sub_17:Test (Best Model) - Loss: 0.9803 - Accuracy: 0.7059 - F1: 0.6647
sub_18:Test (Best Model) - Loss: 1.5046 - Accuracy: 0.4706 - F1: 0.4078
sub_28:Test (Best Model) - Loss: 2.0929 - Accuracy: 0.5147 - F1: 0.4572
sub_20:Test (Best Model) - Loss: 0.5166 - Accuracy: 0.7681 - F1: 0.7798
sub_23:Test (Best Model) - Loss: 1.0889 - Accuracy: 0.4203 - F1: 0.3661
sub_21:Test (Best Model) - Loss: 0.9343 - Accuracy: 0.6471 - F1: 0.5832
sub_19:Test (Best Model) - Loss: 3.1761 - Accuracy: 0.3382 - F1: 0.2653
sub_22:Test (Best Model) - Loss: 4.5773 - Accuracy: 0.3382 - F1: 0.2489
sub_25:Test (Best Model) - Loss: 1.2289 - Accuracy: 0.5588 - F1: 0.5496
sub_16:Test (Best Model) - Loss: 2.6857 - Accuracy: 0.4412 - F1: 0.4113
sub_26:Test (Best Model) - Loss: 3.2868 - Accuracy: 0.6765 - F1: 0.6168
sub_20:Test (Best Model) - Loss: 1.0442 - Accuracy: 0.4928 - F1: 0.4472
sub_28:Test (Best Model) - Loss: 1.2760 - Accuracy: 0.5735 - F1: 0.4917
sub_27:Test (Best Model) - Loss: 2.1111 - Accuracy: 0.6029 - F1: 0.5272
sub_29:Test (Best Model) - Loss: 0.8096 - Accuracy: 0.5797 - F1: 0.5264
sub_19:Test (Best Model) - Loss: 2.6479 - Accuracy: 0.3088 - F1: 0.3305
sub_24:Test (Best Model) - Loss: 3.4111 - Accuracy: 0.4706 - F1: 0.4328
sub_17:Test (Best Model) - Loss: 2.1111 - Accuracy: 0.6029 - F1: 0.5272
sub_25:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.5294 - F1: 0.4991
sub_22:Test (Best Model) - Loss: 3.5849 - Accuracy: 0.5000 - F1: 0.4664
sub_26:Test (Best Model) - Loss: 1.3467 - Accuracy: 0.6176 - F1: 0.6118
sub_21:Test (Best Model) - Loss: 3.0990 - Accuracy: 0.5000 - F1: 0.4278
sub_16:Test (Best Model) - Loss: 3.0558 - Accuracy: 0.3824 - F1: 0.3407
sub_27:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.7059 - F1: 0.6949
sub_19:Test (Best Model) - Loss: 1.3695 - Accuracy: 0.4559 - F1: 0.4640
sub_22:Test (Best Model) - Loss: 0.9455 - Accuracy: 0.6176 - F1: 0.5577
sub_24:Test (Best Model) - Loss: 4.7474 - Accuracy: 0.3382 - F1: 0.2688
sub_29:Test (Best Model) - Loss: 1.2486 - Accuracy: 0.5942 - F1: 0.5715
sub_17:Test (Best Model) - Loss: 0.6383 - Accuracy: 0.7059 - F1: 0.6949
sub_21:Test (Best Model) - Loss: 0.7144 - Accuracy: 0.6618 - F1: 0.6557
sub_26:Test (Best Model) - Loss: 1.8266 - Accuracy: 0.6176 - F1: 0.6048
sub_16:Test (Best Model) - Loss: 3.2818 - Accuracy: 0.3382 - F1: 0.2731
sub_29:Test (Best Model) - Loss: 1.1855 - Accuracy: 0.5217 - F1: 0.4538
sub_16:Test (Best Model) - Loss: 1.1311 - Accuracy: 0.4706 - F1: 0.4693

=== Summary Results ===

acc: 56.16 ± 7.16
F1: 52.77 ± 7.85
acc-in: 81.57 ± 5.86
F1-in: 79.89 ± 6.85
runing time: 2326.53 seconds
