lr: 0.0001
sub_1:Test (Best Model) - Loss: 4.4800 - Accuracy: 0.3529 - F1: 0.2680
sub_2:Test (Best Model) - Loss: 1.3521 - Accuracy: 0.4058 - F1: 0.2846
sub_3:Test (Best Model) - Loss: 13.3967 - Accuracy: 0.6176 - F1: 0.5471
sub_1:Test (Best Model) - Loss: 8.9309 - Accuracy: 0.4706 - F1: 0.4351
sub_2:Test (Best Model) - Loss: 2.3669 - Accuracy: 0.5797 - F1: 0.5704
sub_1:Test (Best Model) - Loss: 8.7506 - Accuracy: 0.4853 - F1: 0.4494
sub_3:Test (Best Model) - Loss: 8.2457 - Accuracy: 0.5441 - F1: 0.5054
sub_1:Test (Best Model) - Loss: 10.1752 - Accuracy: 0.5441 - F1: 0.5295
sub_2:Test (Best Model) - Loss: 3.4740 - Accuracy: 0.5942 - F1: 0.5758
sub_1:Test (Best Model) - Loss: 11.8614 - Accuracy: 0.5000 - F1: 0.4700
sub_3:Test (Best Model) - Loss: 6.7903 - Accuracy: 0.6471 - F1: 0.5890
sub_2:Test (Best Model) - Loss: 2.7210 - Accuracy: 0.5507 - F1: 0.5327
sub_3:Test (Best Model) - Loss: 4.9486 - Accuracy: 0.6471 - F1: 0.5839
sub_2:Test (Best Model) - Loss: 3.4287 - Accuracy: 0.5362 - F1: 0.5281
sub_1:Test (Best Model) - Loss: 1.9023 - Accuracy: 0.4348 - F1: 0.4063
sub_3:Test (Best Model) - Loss: 7.5875 - Accuracy: 0.5882 - F1: 0.5310
sub_1:Test (Best Model) - Loss: 2.1705 - Accuracy: 0.3768 - F1: 0.3111
sub_3:Test (Best Model) - Loss: 1.3492 - Accuracy: 0.6377 - F1: 0.6367
sub_2:Test (Best Model) - Loss: 0.7921 - Accuracy: 0.6912 - F1: 0.7042
sub_2:Test (Best Model) - Loss: 1.0237 - Accuracy: 0.3824 - F1: 0.2565
sub_1:Test (Best Model) - Loss: 2.5705 - Accuracy: 0.5217 - F1: 0.5404
sub_3:Test (Best Model) - Loss: 1.1124 - Accuracy: 0.6667 - F1: 0.6738
sub_2:Test (Best Model) - Loss: 1.1377 - Accuracy: 0.3971 - F1: 0.2692
sub_1:Test (Best Model) - Loss: 7.4969 - Accuracy: 0.4058 - F1: 0.3722
sub_2:Test (Best Model) - Loss: 0.8018 - Accuracy: 0.7059 - F1: 0.7080
sub_3:Test (Best Model) - Loss: 0.9207 - Accuracy: 0.7101 - F1: 0.7190
sub_1:Test (Best Model) - Loss: 3.4573 - Accuracy: 0.3913 - F1: 0.3252
sub_2:Test (Best Model) - Loss: 0.7631 - Accuracy: 0.6471 - F1: 0.6314
sub_3:Test (Best Model) - Loss: 2.5751 - Accuracy: 0.6522 - F1: 0.6542
sub_1:Test (Best Model) - Loss: 0.8943 - Accuracy: 0.6912 - F1: 0.6561
sub_3:Test (Best Model) - Loss: 1.1308 - Accuracy: 0.6087 - F1: 0.6114
sub_2:Test (Best Model) - Loss: 2.8688 - Accuracy: 0.5217 - F1: 0.5041
sub_1:Test (Best Model) - Loss: 0.8283 - Accuracy: 0.7206 - F1: 0.6467
sub_2:Test (Best Model) - Loss: 1.8788 - Accuracy: 0.4348 - F1: 0.3006
sub_3:Test (Best Model) - Loss: 4.0976 - Accuracy: 0.5942 - F1: 0.5801
sub_1:Test (Best Model) - Loss: 1.0204 - Accuracy: 0.6618 - F1: 0.5726
sub_2:Test (Best Model) - Loss: 3.7002 - Accuracy: 0.4928 - F1: 0.4672
sub_3:Test (Best Model) - Loss: 4.0637 - Accuracy: 0.5797 - F1: 0.5401
sub_1:Test (Best Model) - Loss: 0.9013 - Accuracy: 0.6765 - F1: 0.6196
sub_2:Test (Best Model) - Loss: 4.4594 - Accuracy: 0.4638 - F1: 0.4236
sub_3:Test (Best Model) - Loss: 2.1894 - Accuracy: 0.5362 - F1: 0.4966
sub_1:Test (Best Model) - Loss: 0.9407 - Accuracy: 0.6618 - F1: 0.5761
sub_2:Test (Best Model) - Loss: 2.1930 - Accuracy: 0.5362 - F1: 0.4679
sub_3:Test (Best Model) - Loss: 3.9566 - Accuracy: 0.6087 - F1: 0.5842
sub_3:Test (Best Model) - Loss: 3.8569 - Accuracy: 0.6232 - F1: 0.5968
sub_5:Test (Best Model) - Loss: 7.4710 - Accuracy: 0.4118 - F1: 0.2742
sub_4:Test (Best Model) - Loss: 2.2285 - Accuracy: 0.5507 - F1: 0.5563
sub_6:Test (Best Model) - Loss: 1.3296 - Accuracy: 0.5000 - F1: 0.4905
sub_5:Test (Best Model) - Loss: 36.0662 - Accuracy: 0.4559 - F1: 0.3466
sub_4:Test (Best Model) - Loss: 2.2570 - Accuracy: 0.4493 - F1: 0.4679
sub_6:Test (Best Model) - Loss: 1.3027 - Accuracy: 0.5294 - F1: 0.5052
sub_5:Test (Best Model) - Loss: 23.5044 - Accuracy: 0.4412 - F1: 0.3924
sub_4:Test (Best Model) - Loss: 1.7684 - Accuracy: 0.5362 - F1: 0.5589
sub_6:Test (Best Model) - Loss: 1.4239 - Accuracy: 0.5147 - F1: 0.4982
sub_6:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.5000 - F1: 0.4773
sub_4:Test (Best Model) - Loss: 1.9940 - Accuracy: 0.4928 - F1: 0.5093
sub_5:Test (Best Model) - Loss: 64.5333 - Accuracy: 0.4265 - F1: 0.3269
sub_4:Test (Best Model) - Loss: 2.1415 - Accuracy: 0.4783 - F1: 0.4817
sub_5:Test (Best Model) - Loss: 30.4884 - Accuracy: 0.3971 - F1: 0.3183
sub_6:Test (Best Model) - Loss: 1.5065 - Accuracy: 0.4706 - F1: 0.4496
sub_4:Test (Best Model) - Loss: 4.9749 - Accuracy: 0.3768 - F1: 0.2976
sub_5:Test (Best Model) - Loss: 4.2482 - Accuracy: 0.5882 - F1: 0.5837
sub_6:Test (Best Model) - Loss: 3.8301 - Accuracy: 0.4348 - F1: 0.4026
sub_4:Test (Best Model) - Loss: 4.0713 - Accuracy: 0.3623 - F1: 0.2817
sub_5:Test (Best Model) - Loss: 1.3389 - Accuracy: 0.4118 - F1: 0.3693
sub_4:Test (Best Model) - Loss: 4.0202 - Accuracy: 0.4928 - F1: 0.4292
sub_5:Test (Best Model) - Loss: 2.9722 - Accuracy: 0.5000 - F1: 0.4848
sub_6:Test (Best Model) - Loss: 3.1241 - Accuracy: 0.5072 - F1: 0.4966
sub_6:Test (Best Model) - Loss: 2.9716 - Accuracy: 0.4493 - F1: 0.4372
sub_5:Test (Best Model) - Loss: 3.5879 - Accuracy: 0.5147 - F1: 0.5091
sub_4:Test (Best Model) - Loss: 3.7230 - Accuracy: 0.4348 - F1: 0.3545
sub_5:Test (Best Model) - Loss: 3.4515 - Accuracy: 0.4853 - F1: 0.4805
sub_6:Test (Best Model) - Loss: 3.8877 - Accuracy: 0.4783 - F1: 0.4593
sub_4:Test (Best Model) - Loss: 2.8588 - Accuracy: 0.4058 - F1: 0.3220
sub_5:Test (Best Model) - Loss: 1.6269 - Accuracy: 0.3235 - F1: 0.2010
sub_4:Test (Best Model) - Loss: 1.7800 - Accuracy: 0.5217 - F1: 0.4709
sub_6:Test (Best Model) - Loss: 1.9544 - Accuracy: 0.3188 - F1: 0.2589
sub_5:Test (Best Model) - Loss: 1.3416 - Accuracy: 0.5588 - F1: 0.4743
sub_4:Test (Best Model) - Loss: 2.1403 - Accuracy: 0.4928 - F1: 0.4596
sub_6:Test (Best Model) - Loss: 1.3619 - Accuracy: 0.5652 - F1: 0.4987
sub_5:Test (Best Model) - Loss: 1.3712 - Accuracy: 0.5000 - F1: 0.4819
sub_6:Test (Best Model) - Loss: 2.9364 - Accuracy: 0.5797 - F1: 0.5440
sub_4:Test (Best Model) - Loss: 1.4165 - Accuracy: 0.5652 - F1: 0.5275
sub_5:Test (Best Model) - Loss: 1.5524 - Accuracy: 0.4706 - F1: 0.4013
sub_6:Test (Best Model) - Loss: 1.6820 - Accuracy: 0.3913 - F1: 0.2960
sub_4:Test (Best Model) - Loss: 2.2592 - Accuracy: 0.5072 - F1: 0.4523
sub_5:Test (Best Model) - Loss: 1.5645 - Accuracy: 0.4853 - F1: 0.4125
sub_4:Test (Best Model) - Loss: 1.2505 - Accuracy: 0.6232 - F1: 0.5396
sub_6:Test (Best Model) - Loss: 2.2893 - Accuracy: 0.5362 - F1: 0.4855
sub_6:Test (Best Model) - Loss: 1.3302 - Accuracy: 0.4638 - F1: 0.4019
sub_7:Test (Best Model) - Loss: 2.4417 - Accuracy: 0.5000 - F1: 0.4764
sub_9:Test (Best Model) - Loss: 1.4781 - Accuracy: 0.3529 - F1: 0.3205
sub_8:Test (Best Model) - Loss: 3.7827 - Accuracy: 0.6029 - F1: 0.5226
sub_9:Test (Best Model) - Loss: 4.0633 - Accuracy: 0.2500 - F1: 0.2896
sub_7:Test (Best Model) - Loss: 1.7352 - Accuracy: 0.5588 - F1: 0.5401
sub_8:Test (Best Model) - Loss: 1.3095 - Accuracy: 0.4559 - F1: 0.3883
sub_8:Test (Best Model) - Loss: 1.4687 - Accuracy: 0.4265 - F1: 0.3360
sub_9:Test (Best Model) - Loss: 2.5248 - Accuracy: 0.2500 - F1: 0.3034
sub_7:Test (Best Model) - Loss: 1.9454 - Accuracy: 0.5441 - F1: 0.5315
sub_7:Test (Best Model) - Loss: 3.4426 - Accuracy: 0.4118 - F1: 0.3824
sub_8:Test (Best Model) - Loss: 2.2271 - Accuracy: 0.4706 - F1: 0.4082
sub_9:Test (Best Model) - Loss: 2.5329 - Accuracy: 0.3088 - F1: 0.3366
sub_8:Test (Best Model) - Loss: 2.3945 - Accuracy: 0.4412 - F1: 0.3499
sub_7:Test (Best Model) - Loss: 4.5566 - Accuracy: 0.5294 - F1: 0.5104
sub_8:Test (Best Model) - Loss: 1.8275 - Accuracy: 0.5147 - F1: 0.5054
sub_9:Test (Best Model) - Loss: 3.8815 - Accuracy: 0.2500 - F1: 0.2891
sub_7:Test (Best Model) - Loss: 1.4519 - Accuracy: 0.6324 - F1: 0.6318
sub_9:Test (Best Model) - Loss: 1.5460 - Accuracy: 0.4706 - F1: 0.4111
sub_8:Test (Best Model) - Loss: 2.1834 - Accuracy: 0.6471 - F1: 0.6568
sub_7:Test (Best Model) - Loss: 1.5219 - Accuracy: 0.5882 - F1: 0.5982
sub_9:Test (Best Model) - Loss: 1.7665 - Accuracy: 0.5441 - F1: 0.5167
sub_8:Test (Best Model) - Loss: 3.4229 - Accuracy: 0.5441 - F1: 0.5417
sub_7:Test (Best Model) - Loss: 2.1255 - Accuracy: 0.6324 - F1: 0.6386
sub_9:Test (Best Model) - Loss: 1.5628 - Accuracy: 0.5147 - F1: 0.4840
sub_7:Test (Best Model) - Loss: 1.5362 - Accuracy: 0.5588 - F1: 0.5345
sub_8:Test (Best Model) - Loss: 3.4064 - Accuracy: 0.6029 - F1: 0.6154
sub_8:Test (Best Model) - Loss: 1.9338 - Accuracy: 0.5441 - F1: 0.5434
sub_9:Test (Best Model) - Loss: 1.1862 - Accuracy: 0.4853 - F1: 0.4712
sub_7:Test (Best Model) - Loss: 2.1257 - Accuracy: 0.6029 - F1: 0.6174
sub_9:Test (Best Model) - Loss: 1.3669 - Accuracy: 0.5000 - F1: 0.4419
sub_8:Test (Best Model) - Loss: 4.5492 - Accuracy: 0.5441 - F1: 0.4766
sub_7:Test (Best Model) - Loss: 3.6391 - Accuracy: 0.5882 - F1: 0.5852
sub_9:Test (Best Model) - Loss: 4.5596 - Accuracy: 0.2941 - F1: 0.2859
sub_7:Test (Best Model) - Loss: 2.6416 - Accuracy: 0.5294 - F1: 0.5307
sub_8:Test (Best Model) - Loss: 4.2402 - Accuracy: 0.5441 - F1: 0.4836
sub_9:Test (Best Model) - Loss: 4.8237 - Accuracy: 0.4265 - F1: 0.3992
sub_8:Test (Best Model) - Loss: 7.2466 - Accuracy: 0.5147 - F1: 0.4568
sub_7:Test (Best Model) - Loss: 6.5102 - Accuracy: 0.5588 - F1: 0.5483
sub_9:Test (Best Model) - Loss: 4.1433 - Accuracy: 0.3088 - F1: 0.3006
sub_9:Test (Best Model) - Loss: 3.5871 - Accuracy: 0.3529 - F1: 0.3510
sub_8:Test (Best Model) - Loss: 9.1811 - Accuracy: 0.5588 - F1: 0.5162
sub_7:Test (Best Model) - Loss: 4.3363 - Accuracy: 0.5441 - F1: 0.5517
sub_8:Test (Best Model) - Loss: 4.4925 - Accuracy: 0.5000 - F1: 0.4280
sub_9:Test (Best Model) - Loss: 4.1635 - Accuracy: 0.2206 - F1: 0.2278
sub_7:Test (Best Model) - Loss: 2.4798 - Accuracy: 0.5441 - F1: 0.5316
sub_12:Test (Best Model) - Loss: 2.8009 - Accuracy: 0.5000 - F1: 0.4838
sub_11:Test (Best Model) - Loss: 2.5172 - Accuracy: 0.3768 - F1: 0.3481
sub_10:Test (Best Model) - Loss: 13.1200 - Accuracy: 0.5588 - F1: 0.4942
sub_12:Test (Best Model) - Loss: 1.4843 - Accuracy: 0.6176 - F1: 0.6093
sub_11:Test (Best Model) - Loss: 2.5224 - Accuracy: 0.4203 - F1: 0.4024
sub_11:Test (Best Model) - Loss: 2.1360 - Accuracy: 0.3188 - F1: 0.2887
sub_10:Test (Best Model) - Loss: 5.7921 - Accuracy: 0.5147 - F1: 0.4582
sub_12:Test (Best Model) - Loss: 1.5333 - Accuracy: 0.5441 - F1: 0.5405
sub_11:Test (Best Model) - Loss: 1.9531 - Accuracy: 0.3913 - F1: 0.3638
sub_10:Test (Best Model) - Loss: 5.6452 - Accuracy: 0.5441 - F1: 0.4931
sub_12:Test (Best Model) - Loss: 1.4603 - Accuracy: 0.6029 - F1: 0.5857
sub_11:Test (Best Model) - Loss: 2.4101 - Accuracy: 0.3478 - F1: 0.3205
sub_12:Test (Best Model) - Loss: 1.5361 - Accuracy: 0.4559 - F1: 0.3647
sub_10:Test (Best Model) - Loss: 7.1662 - Accuracy: 0.4853 - F1: 0.4354
sub_11:Test (Best Model) - Loss: 3.2403 - Accuracy: 0.4928 - F1: 0.4648
sub_12:Test (Best Model) - Loss: 3.2866 - Accuracy: 0.5217 - F1: 0.5048
sub_11:Test (Best Model) - Loss: 2.2933 - Accuracy: 0.4928 - F1: 0.4279
sub_10:Test (Best Model) - Loss: 9.9721 - Accuracy: 0.5441 - F1: 0.4836
sub_12:Test (Best Model) - Loss: 1.4701 - Accuracy: 0.4928 - F1: 0.4963
sub_10:Test (Best Model) - Loss: 31.7793 - Accuracy: 0.4412 - F1: 0.4089
sub_11:Test (Best Model) - Loss: 4.9535 - Accuracy: 0.4928 - F1: 0.4677
sub_12:Test (Best Model) - Loss: 1.8337 - Accuracy: 0.5217 - F1: 0.5191
sub_11:Test (Best Model) - Loss: 3.0653 - Accuracy: 0.5507 - F1: 0.5475
sub_10:Test (Best Model) - Loss: 19.6340 - Accuracy: 0.4706 - F1: 0.4121
sub_12:Test (Best Model) - Loss: 1.4856 - Accuracy: 0.4928 - F1: 0.5010
sub_11:Test (Best Model) - Loss: 2.1100 - Accuracy: 0.4928 - F1: 0.4237
sub_10:Test (Best Model) - Loss: 12.2287 - Accuracy: 0.3971 - F1: 0.3108
sub_12:Test (Best Model) - Loss: 1.8054 - Accuracy: 0.4348 - F1: 0.4307
sub_11:Test (Best Model) - Loss: 1.4980 - Accuracy: 0.5362 - F1: 0.5096
sub_10:Test (Best Model) - Loss: 28.6946 - Accuracy: 0.5000 - F1: 0.4367
sub_12:Test (Best Model) - Loss: 2.0726 - Accuracy: 0.5147 - F1: 0.5049
sub_11:Test (Best Model) - Loss: 1.1755 - Accuracy: 0.5942 - F1: 0.5981
sub_12:Test (Best Model) - Loss: 1.2031 - Accuracy: 0.5294 - F1: 0.4972
sub_10:Test (Best Model) - Loss: 21.6910 - Accuracy: 0.4559 - F1: 0.4273
sub_11:Test (Best Model) - Loss: 1.3897 - Accuracy: 0.5362 - F1: 0.5345
sub_12:Test (Best Model) - Loss: 1.2109 - Accuracy: 0.6324 - F1: 0.6325
sub_10:Test (Best Model) - Loss: 1.5067 - Accuracy: 0.6377 - F1: 0.5791
sub_11:Test (Best Model) - Loss: 1.2548 - Accuracy: 0.5217 - F1: 0.5214
sub_11:Test (Best Model) - Loss: 1.1895 - Accuracy: 0.5797 - F1: 0.5637
sub_12:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.5882 - F1: 0.5609
sub_12:Test (Best Model) - Loss: 1.0930 - Accuracy: 0.5441 - F1: 0.4583
sub_10:Test (Best Model) - Loss: 2.6997 - Accuracy: 0.5797 - F1: 0.5398
sub_10:Test (Best Model) - Loss: 2.7903 - Accuracy: 0.5652 - F1: 0.5428
sub_10:Test (Best Model) - Loss: 2.1589 - Accuracy: 0.6232 - F1: 0.5818
sub_10:Test (Best Model) - Loss: 1.0461 - Accuracy: 0.6667 - F1: 0.6166
sub_13:Test (Best Model) - Loss: 2.1588 - Accuracy: 0.3971 - F1: 0.3626
sub_14:Test (Best Model) - Loss: 3.3116 - Accuracy: 0.2647 - F1: 0.1059
sub_15:Test (Best Model) - Loss: 6.3875 - Accuracy: 0.3676 - F1: 0.3614
sub_15:Test (Best Model) - Loss: 7.8656 - Accuracy: 0.4559 - F1: 0.4680
sub_13:Test (Best Model) - Loss: 2.6422 - Accuracy: 0.3529 - F1: 0.3745
sub_14:Test (Best Model) - Loss: 17.0030 - Accuracy: 0.2353 - F1: 0.1399
sub_13:Test (Best Model) - Loss: 2.4577 - Accuracy: 0.4118 - F1: 0.4003
sub_15:Test (Best Model) - Loss: 12.7009 - Accuracy: 0.3971 - F1: 0.3992
sub_14:Test (Best Model) - Loss: 9.9988 - Accuracy: 0.2353 - F1: 0.1187
sub_13:Test (Best Model) - Loss: 2.0131 - Accuracy: 0.5294 - F1: 0.5282
sub_15:Test (Best Model) - Loss: 3.8867 - Accuracy: 0.3088 - F1: 0.2859
sub_13:Test (Best Model) - Loss: 2.0442 - Accuracy: 0.3235 - F1: 0.3172
sub_15:Test (Best Model) - Loss: 8.9517 - Accuracy: 0.3676 - F1: 0.3805
sub_13:Test (Best Model) - Loss: 3.1546 - Accuracy: 0.4348 - F1: 0.3402
sub_14:Test (Best Model) - Loss: 20.0922 - Accuracy: 0.3235 - F1: 0.2092
sub_15:Test (Best Model) - Loss: 1.0383 - Accuracy: 0.6765 - F1: 0.6010
sub_14:Test (Best Model) - Loss: 3.8338 - Accuracy: 0.2647 - F1: 0.1047
sub_13:Test (Best Model) - Loss: 2.0927 - Accuracy: 0.5072 - F1: 0.4560
sub_15:Test (Best Model) - Loss: 1.0471 - Accuracy: 0.5294 - F1: 0.5242
sub_13:Test (Best Model) - Loss: 2.8861 - Accuracy: 0.4928 - F1: 0.4805
sub_14:Test (Best Model) - Loss: 5.8925 - Accuracy: 0.4265 - F1: 0.3908
sub_15:Test (Best Model) - Loss: 0.8664 - Accuracy: 0.6912 - F1: 0.6734
sub_13:Test (Best Model) - Loss: 2.2937 - Accuracy: 0.5652 - F1: 0.5369
sub_15:Test (Best Model) - Loss: 1.1270 - Accuracy: 0.6324 - F1: 0.6113
sub_14:Test (Best Model) - Loss: 2.8558 - Accuracy: 0.3676 - F1: 0.3454
sub_13:Test (Best Model) - Loss: 2.7394 - Accuracy: 0.5072 - F1: 0.4938
sub_15:Test (Best Model) - Loss: 0.8982 - Accuracy: 0.5588 - F1: 0.5645
sub_13:Test (Best Model) - Loss: 3.0274 - Accuracy: 0.3824 - F1: 0.2799
sub_14:Test (Best Model) - Loss: 2.1949 - Accuracy: 0.3529 - F1: 0.3399
sub_13:Test (Best Model) - Loss: 3.2221 - Accuracy: 0.3824 - F1: 0.3146
sub_15:Test (Best Model) - Loss: 2.6398 - Accuracy: 0.5441 - F1: 0.4709
sub_13:Test (Best Model) - Loss: 2.4130 - Accuracy: 0.3676 - F1: 0.2629
sub_15:Test (Best Model) - Loss: 1.8184 - Accuracy: 0.5294 - F1: 0.4580
sub_13:Test (Best Model) - Loss: 2.1911 - Accuracy: 0.3824 - F1: 0.2930
sub_14:Test (Best Model) - Loss: 2.3498 - Accuracy: 0.3235 - F1: 0.3121
sub_14:Test (Best Model) - Loss: 2.3561 - Accuracy: 0.2794 - F1: 0.2037
sub_13:Test (Best Model) - Loss: 3.7667 - Accuracy: 0.4559 - F1: 0.4608
sub_15:Test (Best Model) - Loss: 1.8147 - Accuracy: 0.5735 - F1: 0.5109
sub_14:Test (Best Model) - Loss: 2.6675 - Accuracy: 0.4265 - F1: 0.4081
sub_15:Test (Best Model) - Loss: 1.8466 - Accuracy: 0.5147 - F1: 0.4628
sub_14:Test (Best Model) - Loss: 1.6333 - Accuracy: 0.4853 - F1: 0.4442
sub_15:Test (Best Model) - Loss: 1.6593 - Accuracy: 0.5441 - F1: 0.4755
sub_14:Test (Best Model) - Loss: 1.4377 - Accuracy: 0.4412 - F1: 0.3762
sub_14:Test (Best Model) - Loss: 1.5327 - Accuracy: 0.5000 - F1: 0.4688
sub_14:Test (Best Model) - Loss: 1.3658 - Accuracy: 0.5000 - F1: 0.4319
sub_16:Test (Best Model) - Loss: 1.4462 - Accuracy: 0.3235 - F1: 0.2257
sub_18:Test (Best Model) - Loss: 1.3776 - Accuracy: 0.4783 - F1: 0.4134
sub_17:Test (Best Model) - Loss: 1.6314 - Accuracy: 0.5072 - F1: 0.4948
sub_18:Test (Best Model) - Loss: 0.9857 - Accuracy: 0.6377 - F1: 0.6254
sub_16:Test (Best Model) - Loss: 1.6394 - Accuracy: 0.5147 - F1: 0.5091
sub_17:Test (Best Model) - Loss: 1.6748 - Accuracy: 0.4928 - F1: 0.4831
sub_18:Test (Best Model) - Loss: 2.1515 - Accuracy: 0.5507 - F1: 0.5151
sub_17:Test (Best Model) - Loss: 2.1071 - Accuracy: 0.4783 - F1: 0.4687
sub_16:Test (Best Model) - Loss: 2.1281 - Accuracy: 0.4853 - F1: 0.4745
sub_17:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.3913 - F1: 0.3818
sub_18:Test (Best Model) - Loss: 1.5639 - Accuracy: 0.4058 - F1: 0.3526
sub_17:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.4638 - F1: 0.4084
sub_16:Test (Best Model) - Loss: 1.7077 - Accuracy: 0.3529 - F1: 0.3396
sub_18:Test (Best Model) - Loss: 1.7681 - Accuracy: 0.5797 - F1: 0.5591
sub_17:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.5217 - F1: 0.4870
sub_17:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.5362 - F1: 0.5416
sub_18:Test (Best Model) - Loss: 2.0885 - Accuracy: 0.5000 - F1: 0.4757
sub_16:Test (Best Model) - Loss: 1.8577 - Accuracy: 0.4853 - F1: 0.4914
sub_17:Test (Best Model) - Loss: 1.2410 - Accuracy: 0.4493 - F1: 0.4213
sub_16:Test (Best Model) - Loss: 1.6636 - Accuracy: 0.4118 - F1: 0.3347
sub_17:Test (Best Model) - Loss: 1.3108 - Accuracy: 0.5942 - F1: 0.5722
sub_18:Test (Best Model) - Loss: 1.2363 - Accuracy: 0.6324 - F1: 0.6191
sub_17:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3623 - F1: 0.2891
sub_16:Test (Best Model) - Loss: 2.6825 - Accuracy: 0.3676 - F1: 0.3379
sub_16:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.3088 - F1: 0.1999
sub_17:Test (Best Model) - Loss: 3.3698 - Accuracy: 0.5588 - F1: 0.5587
sub_18:Test (Best Model) - Loss: 1.0831 - Accuracy: 0.6618 - F1: 0.6727
sub_17:Test (Best Model) - Loss: 3.1935 - Accuracy: 0.4559 - F1: 0.4608
sub_16:Test (Best Model) - Loss: 1.6520 - Accuracy: 0.4118 - F1: 0.3489
sub_18:Test (Best Model) - Loss: 1.0994 - Accuracy: 0.5000 - F1: 0.4527
sub_18:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.3676 - F1: 0.3449
sub_17:Test (Best Model) - Loss: 4.1998 - Accuracy: 0.5147 - F1: 0.5062
sub_16:Test (Best Model) - Loss: 1.4595 - Accuracy: 0.3676 - F1: 0.2907
sub_18:Test (Best Model) - Loss: 1.7571 - Accuracy: 0.4706 - F1: 0.3619
sub_16:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2941 - F1: 0.2833
sub_18:Test (Best Model) - Loss: 2.3119 - Accuracy: 0.4265 - F1: 0.3547
sub_17:Test (Best Model) - Loss: 4.1638 - Accuracy: 0.5441 - F1: 0.5488
sub_16:Test (Best Model) - Loss: 1.4051 - Accuracy: 0.3676 - F1: 0.3648
sub_18:Test (Best Model) - Loss: 3.4156 - Accuracy: 0.3676 - F1: 0.3148
sub_16:Test (Best Model) - Loss: 1.7981 - Accuracy: 0.4706 - F1: 0.4579
sub_18:Test (Best Model) - Loss: 3.0029 - Accuracy: 0.3676 - F1: 0.3424
sub_17:Test (Best Model) - Loss: 4.0308 - Accuracy: 0.5588 - F1: 0.5587
sub_16:Test (Best Model) - Loss: 1.4806 - Accuracy: 0.4118 - F1: 0.4009
sub_18:Test (Best Model) - Loss: 5.5573 - Accuracy: 0.3971 - F1: 0.3354
sub_16:Test (Best Model) - Loss: 1.2689 - Accuracy: 0.2794 - F1: 0.1986
sub_21:Test (Best Model) - Loss: 1.9202 - Accuracy: 0.4118 - F1: 0.2813
sub_19:Test (Best Model) - Loss: 3.7667 - Accuracy: 0.3824 - F1: 0.3860
sub_20:Test (Best Model) - Loss: 1.7285 - Accuracy: 0.6618 - F1: 0.6628
sub_20:Test (Best Model) - Loss: 1.1817 - Accuracy: 0.6029 - F1: 0.6035
sub_21:Test (Best Model) - Loss: 5.6839 - Accuracy: 0.5000 - F1: 0.4678
sub_19:Test (Best Model) - Loss: 2.6330 - Accuracy: 0.3529 - F1: 0.3399
sub_20:Test (Best Model) - Loss: 1.0488 - Accuracy: 0.5441 - F1: 0.4896
sub_19:Test (Best Model) - Loss: 1.7124 - Accuracy: 0.2794 - F1: 0.1923
sub_21:Test (Best Model) - Loss: 3.2196 - Accuracy: 0.4412 - F1: 0.4123
sub_20:Test (Best Model) - Loss: 1.0574 - Accuracy: 0.5147 - F1: 0.4394
sub_19:Test (Best Model) - Loss: 1.6484 - Accuracy: 0.2794 - F1: 0.2055
sub_21:Test (Best Model) - Loss: 2.1094 - Accuracy: 0.4706 - F1: 0.4064
sub_19:Test (Best Model) - Loss: 1.9110 - Accuracy: 0.2500 - F1: 0.2017
sub_20:Test (Best Model) - Loss: 1.3209 - Accuracy: 0.6029 - F1: 0.5994
sub_19:Test (Best Model) - Loss: 3.0268 - Accuracy: 0.4559 - F1: 0.4229
sub_21:Test (Best Model) - Loss: 7.9377 - Accuracy: 0.5000 - F1: 0.4787
sub_20:Test (Best Model) - Loss: 2.1712 - Accuracy: 0.5882 - F1: 0.5663
sub_19:Test (Best Model) - Loss: 1.3339 - Accuracy: 0.5441 - F1: 0.5016
sub_21:Test (Best Model) - Loss: 5.4668 - Accuracy: 0.4412 - F1: 0.4467
sub_20:Test (Best Model) - Loss: 1.2122 - Accuracy: 0.6765 - F1: 0.6475
sub_19:Test (Best Model) - Loss: 1.2734 - Accuracy: 0.5882 - F1: 0.5580
sub_20:Test (Best Model) - Loss: 1.1212 - Accuracy: 0.6912 - F1: 0.6562
sub_21:Test (Best Model) - Loss: 13.7349 - Accuracy: 0.5882 - F1: 0.5797
sub_19:Test (Best Model) - Loss: 1.3759 - Accuracy: 0.5441 - F1: 0.5158
sub_19:Test (Best Model) - Loss: 1.3178 - Accuracy: 0.5294 - F1: 0.5246
sub_20:Test (Best Model) - Loss: 1.5334 - Accuracy: 0.6765 - F1: 0.6577
sub_21:Test (Best Model) - Loss: 8.9074 - Accuracy: 0.6176 - F1: 0.6126
sub_19:Test (Best Model) - Loss: 2.9889 - Accuracy: 0.4853 - F1: 0.4476
sub_20:Test (Best Model) - Loss: 1.4081 - Accuracy: 0.7206 - F1: 0.7141
sub_19:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.4412 - F1: 0.3403
sub_21:Test (Best Model) - Loss: 18.2842 - Accuracy: 0.5735 - F1: 0.5652
sub_19:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.5147 - F1: 0.4671
sub_20:Test (Best Model) - Loss: 1.5120 - Accuracy: 0.6232 - F1: 0.5899
sub_19:Test (Best Model) - Loss: 1.5323 - Accuracy: 0.4706 - F1: 0.4372
sub_21:Test (Best Model) - Loss: 3.5012 - Accuracy: 0.5882 - F1: 0.5923
sub_19:Test (Best Model) - Loss: 1.2617 - Accuracy: 0.4265 - F1: 0.4123
sub_20:Test (Best Model) - Loss: 1.6647 - Accuracy: 0.5942 - F1: 0.5862
sub_21:Test (Best Model) - Loss: 1.3656 - Accuracy: 0.4265 - F1: 0.3462
sub_21:Test (Best Model) - Loss: 1.2600 - Accuracy: 0.2647 - F1: 0.2530
sub_20:Test (Best Model) - Loss: 1.4748 - Accuracy: 0.6957 - F1: 0.6908
sub_20:Test (Best Model) - Loss: 1.4506 - Accuracy: 0.6957 - F1: 0.6742
sub_21:Test (Best Model) - Loss: 1.3242 - Accuracy: 0.5588 - F1: 0.4949
sub_20:Test (Best Model) - Loss: 2.2102 - Accuracy: 0.5652 - F1: 0.5521
sub_21:Test (Best Model) - Loss: 1.3242 - Accuracy: 0.5441 - F1: 0.5149
sub_21:Test (Best Model) - Loss: 1.5315 - Accuracy: 0.5588 - F1: 0.5029
sub_24:Test (Best Model) - Loss: 1.6378 - Accuracy: 0.4118 - F1: 0.3328
sub_23:Test (Best Model) - Loss: 1.4945 - Accuracy: 0.3333 - F1: 0.2489
sub_24:Test (Best Model) - Loss: 2.0399 - Accuracy: 0.3382 - F1: 0.2964
sub_22:Test (Best Model) - Loss: 4.5545 - Accuracy: 0.4706 - F1: 0.3852
sub_24:Test (Best Model) - Loss: 2.1063 - Accuracy: 0.3676 - F1: 0.3411
sub_23:Test (Best Model) - Loss: 1.5758 - Accuracy: 0.4058 - F1: 0.4035
sub_22:Test (Best Model) - Loss: 5.9982 - Accuracy: 0.4706 - F1: 0.3790
sub_24:Test (Best Model) - Loss: 1.9168 - Accuracy: 0.3676 - F1: 0.3337
sub_23:Test (Best Model) - Loss: 1.4619 - Accuracy: 0.4203 - F1: 0.4293
sub_24:Test (Best Model) - Loss: 2.3192 - Accuracy: 0.4412 - F1: 0.3988
sub_22:Test (Best Model) - Loss: 5.6808 - Accuracy: 0.3971 - F1: 0.3125
sub_24:Test (Best Model) - Loss: 1.4536 - Accuracy: 0.5147 - F1: 0.4673
sub_22:Test (Best Model) - Loss: 3.3757 - Accuracy: 0.4706 - F1: 0.3970
sub_23:Test (Best Model) - Loss: 2.0658 - Accuracy: 0.4928 - F1: 0.4812
sub_24:Test (Best Model) - Loss: 1.7956 - Accuracy: 0.4265 - F1: 0.3338
sub_22:Test (Best Model) - Loss: 11.7298 - Accuracy: 0.4265 - F1: 0.3433
sub_24:Test (Best Model) - Loss: 1.7545 - Accuracy: 0.4853 - F1: 0.4596
sub_24:Test (Best Model) - Loss: 1.8274 - Accuracy: 0.5294 - F1: 0.4833
sub_23:Test (Best Model) - Loss: 3.5200 - Accuracy: 0.4203 - F1: 0.4202
sub_22:Test (Best Model) - Loss: 1.7694 - Accuracy: 0.4783 - F1: 0.4397
sub_24:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.5441 - F1: 0.5459
sub_22:Test (Best Model) - Loss: 1.0908 - Accuracy: 0.5072 - F1: 0.4927
sub_23:Test (Best Model) - Loss: 18.3960 - Accuracy: 0.5294 - F1: 0.5178
sub_24:Test (Best Model) - Loss: 1.6005 - Accuracy: 0.4265 - F1: 0.3844
sub_22:Test (Best Model) - Loss: 1.1997 - Accuracy: 0.4493 - F1: 0.4015
sub_22:Test (Best Model) - Loss: 1.2029 - Accuracy: 0.4348 - F1: 0.3676
sub_23:Test (Best Model) - Loss: 2.9640 - Accuracy: 0.5735 - F1: 0.5705
sub_22:Test (Best Model) - Loss: 1.2821 - Accuracy: 0.4638 - F1: 0.4090
sub_24:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.3529 - F1: 0.3565
sub_23:Test (Best Model) - Loss: 3.5828 - Accuracy: 0.6176 - F1: 0.6182
sub_24:Test (Best Model) - Loss: 1.3393 - Accuracy: 0.4118 - F1: 0.3746
sub_22:Test (Best Model) - Loss: 9.2233 - Accuracy: 0.3088 - F1: 0.2468
sub_24:Test (Best Model) - Loss: 1.3659 - Accuracy: 0.3676 - F1: 0.2806
sub_23:Test (Best Model) - Loss: 2.4247 - Accuracy: 0.4559 - F1: 0.4471
sub_22:Test (Best Model) - Loss: 3.5361 - Accuracy: 0.3971 - F1: 0.3490
sub_24:Test (Best Model) - Loss: 1.3406 - Accuracy: 0.3971 - F1: 0.4320
sub_23:Test (Best Model) - Loss: 3.7307 - Accuracy: 0.4706 - F1: 0.4660
sub_22:Test (Best Model) - Loss: 2.8128 - Accuracy: 0.3971 - F1: 0.3806
sub_23:Test (Best Model) - Loss: 4.7662 - Accuracy: 0.4058 - F1: 0.3672
sub_22:Test (Best Model) - Loss: 3.6113 - Accuracy: 0.3382 - F1: 0.3005
sub_23:Test (Best Model) - Loss: 2.0938 - Accuracy: 0.4493 - F1: 0.4265
sub_22:Test (Best Model) - Loss: 4.0183 - Accuracy: 0.3382 - F1: 0.3235
sub_23:Test (Best Model) - Loss: 3.1037 - Accuracy: 0.4058 - F1: 0.3786
sub_23:Test (Best Model) - Loss: 1.7781 - Accuracy: 0.4638 - F1: 0.4574
sub_23:Test (Best Model) - Loss: 5.1281 - Accuracy: 0.4348 - F1: 0.4102
sub_26:Test (Best Model) - Loss: 1.2622 - Accuracy: 0.4783 - F1: 0.4235
sub_27:Test (Best Model) - Loss: 1.6314 - Accuracy: 0.5072 - F1: 0.4948
sub_25:Test (Best Model) - Loss: 1.3869 - Accuracy: 0.6667 - F1: 0.6661
sub_26:Test (Best Model) - Loss: 1.0916 - Accuracy: 0.5797 - F1: 0.5817
sub_27:Test (Best Model) - Loss: 1.6748 - Accuracy: 0.4928 - F1: 0.4831
sub_25:Test (Best Model) - Loss: 1.0279 - Accuracy: 0.6232 - F1: 0.6142
sub_27:Test (Best Model) - Loss: 2.1071 - Accuracy: 0.4783 - F1: 0.4687
sub_27:Test (Best Model) - Loss: 1.3098 - Accuracy: 0.3913 - F1: 0.3818
sub_26:Test (Best Model) - Loss: 1.0415 - Accuracy: 0.5942 - F1: 0.6119
sub_25:Test (Best Model) - Loss: 0.8265 - Accuracy: 0.5942 - F1: 0.5917
sub_27:Test (Best Model) - Loss: 1.3149 - Accuracy: 0.4638 - F1: 0.4084
sub_26:Test (Best Model) - Loss: 0.9687 - Accuracy: 0.6232 - F1: 0.6246
sub_27:Test (Best Model) - Loss: 1.3605 - Accuracy: 0.5217 - F1: 0.4870
sub_25:Test (Best Model) - Loss: 0.9854 - Accuracy: 0.6377 - F1: 0.6332
sub_25:Test (Best Model) - Loss: 1.1356 - Accuracy: 0.5942 - F1: 0.5831
sub_27:Test (Best Model) - Loss: 1.3481 - Accuracy: 0.5362 - F1: 0.5416
sub_26:Test (Best Model) - Loss: 1.3280 - Accuracy: 0.6087 - F1: 0.6087
sub_27:Test (Best Model) - Loss: 1.2410 - Accuracy: 0.4493 - F1: 0.4213
sub_25:Test (Best Model) - Loss: 1.2221 - Accuracy: 0.6176 - F1: 0.6217
sub_25:Test (Best Model) - Loss: 1.1737 - Accuracy: 0.6029 - F1: 0.5742
sub_27:Test (Best Model) - Loss: 1.3108 - Accuracy: 0.5942 - F1: 0.5722
sub_26:Test (Best Model) - Loss: 2.3860 - Accuracy: 0.6176 - F1: 0.6031
sub_27:Test (Best Model) - Loss: 1.3568 - Accuracy: 0.3623 - F1: 0.2891
sub_25:Test (Best Model) - Loss: 1.0186 - Accuracy: 0.6324 - F1: 0.6406
sub_25:Test (Best Model) - Loss: 1.0986 - Accuracy: 0.6618 - F1: 0.5963
sub_27:Test (Best Model) - Loss: 3.3698 - Accuracy: 0.5588 - F1: 0.5587
sub_26:Test (Best Model) - Loss: 1.1355 - Accuracy: 0.6176 - F1: 0.6199
sub_27:Test (Best Model) - Loss: 3.1935 - Accuracy: 0.4559 - F1: 0.4608
sub_26:Test (Best Model) - Loss: 1.6527 - Accuracy: 0.5294 - F1: 0.4930
sub_25:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.7500 - F1: 0.7616
sub_26:Test (Best Model) - Loss: 1.5229 - Accuracy: 0.5147 - F1: 0.4819
sub_27:Test (Best Model) - Loss: 4.1998 - Accuracy: 0.5147 - F1: 0.5062
sub_26:Test (Best Model) - Loss: 2.2004 - Accuracy: 0.5294 - F1: 0.4945
sub_25:Test (Best Model) - Loss: 0.9521 - Accuracy: 0.6912 - F1: 0.6906
sub_27:Test (Best Model) - Loss: 4.1638 - Accuracy: 0.5441 - F1: 0.5488
sub_26:Test (Best Model) - Loss: 1.7165 - Accuracy: 0.4265 - F1: 0.3936
sub_25:Test (Best Model) - Loss: 0.9752 - Accuracy: 0.6765 - F1: 0.6789
sub_26:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.4412 - F1: 0.4217
sub_25:Test (Best Model) - Loss: 1.1676 - Accuracy: 0.6176 - F1: 0.6037
sub_27:Test (Best Model) - Loss: 4.0308 - Accuracy: 0.5588 - F1: 0.5587
sub_26:Test (Best Model) - Loss: 2.5305 - Accuracy: 0.3382 - F1: 0.3195
sub_25:Test (Best Model) - Loss: 0.9271 - Accuracy: 0.6471 - F1: 0.6529
sub_26:Test (Best Model) - Loss: 2.2434 - Accuracy: 0.4118 - F1: 0.4161
sub_25:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.6618 - F1: 0.6515
sub_26:Test (Best Model) - Loss: 1.7783 - Accuracy: 0.4265 - F1: 0.4127
sub_28:Test (Best Model) - Loss: 1.4484 - Accuracy: 0.2353 - F1: 0.1623
sub_29:Test (Best Model) - Loss: 2.7015 - Accuracy: 0.4706 - F1: 0.4562
sub_29:Test (Best Model) - Loss: 4.1094 - Accuracy: 0.5147 - F1: 0.4988
sub_28:Test (Best Model) - Loss: 1.9298 - Accuracy: 0.3529 - F1: 0.3410
sub_28:Test (Best Model) - Loss: 2.0866 - Accuracy: 0.3088 - F1: 0.2996
sub_29:Test (Best Model) - Loss: 5.0491 - Accuracy: 0.5000 - F1: 0.5043
sub_28:Test (Best Model) - Loss: 1.3620 - Accuracy: 0.2500 - F1: 0.1885
sub_29:Test (Best Model) - Loss: 2.8845 - Accuracy: 0.5000 - F1: 0.5052
sub_28:Test (Best Model) - Loss: 1.4444 - Accuracy: 0.2941 - F1: 0.2625
sub_29:Test (Best Model) - Loss: 3.8132 - Accuracy: 0.5147 - F1: 0.5142
sub_29:Test (Best Model) - Loss: 1.8537 - Accuracy: 0.5441 - F1: 0.4765
sub_28:Test (Best Model) - Loss: 20.8042 - Accuracy: 0.3824 - F1: 0.3209
sub_29:Test (Best Model) - Loss: 2.9771 - Accuracy: 0.5441 - F1: 0.4748
sub_28:Test (Best Model) - Loss: 14.6550 - Accuracy: 0.4118 - F1: 0.3764
sub_29:Test (Best Model) - Loss: 2.4414 - Accuracy: 0.6176 - F1: 0.5794
sub_28:Test (Best Model) - Loss: 8.7923 - Accuracy: 0.3971 - F1: 0.3459
sub_29:Test (Best Model) - Loss: 2.8453 - Accuracy: 0.5441 - F1: 0.4852
sub_28:Test (Best Model) - Loss: 12.3283 - Accuracy: 0.4118 - F1: 0.3435
sub_29:Test (Best Model) - Loss: 2.0329 - Accuracy: 0.6176 - F1: 0.5601
sub_28:Test (Best Model) - Loss: 4.6424 - Accuracy: 0.3088 - F1: 0.2381
sub_28:Test (Best Model) - Loss: 3.5516 - Accuracy: 0.3382 - F1: 0.2514
sub_29:Test (Best Model) - Loss: 1.7657 - Accuracy: 0.3768 - F1: 0.3611
sub_29:Test (Best Model) - Loss: 1.7203 - Accuracy: 0.4638 - F1: 0.4851
sub_28:Test (Best Model) - Loss: 12.6894 - Accuracy: 0.2500 - F1: 0.2145
sub_28:Test (Best Model) - Loss: 3.5659 - Accuracy: 0.3235 - F1: 0.2725
sub_29:Test (Best Model) - Loss: 2.2299 - Accuracy: 0.3913 - F1: 0.3617
sub_28:Test (Best Model) - Loss: 2.5091 - Accuracy: 0.2206 - F1: 0.1527
sub_29:Test (Best Model) - Loss: 1.4155 - Accuracy: 0.4203 - F1: 0.4277
sub_28:Test (Best Model) - Loss: 7.9114 - Accuracy: 0.1912 - F1: 0.1794
sub_29:Test (Best Model) - Loss: 1.2412 - Accuracy: 0.4493 - F1: 0.4818

=== Summary Results ===

acc: 48.69 ± 7.49
F1: 45.38 ± 8.28
acc-in: 62.56 ± 6.15
F1-in: 59.26 ± 7.11
runing time: 2383.80 seconds
