lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.4545 - F1: 0.3750
sub_1:Test (Best Model) - Loss: 0.4358 - Accuracy: 0.4545 - F1: 0.3750
sub_1:Test (Best Model) - Loss: 0.4333 - Accuracy: 0.3636 - F1: 0.2821
sub_1:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2273 - F1: 0.1042
sub_1:Test (Best Model) - Loss: 0.3682 - Accuracy: 0.4348 - F1: 0.3472
sub_1:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_1:Test (Best Model) - Loss: 0.4277 - Accuracy: 0.3636 - F1: 0.2821
sub_1:Test (Best Model) - Loss: 0.4334 - Accuracy: 0.2727 - F1: 0.1984
sub_1:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_1:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 0.4569 - Accuracy: 0.2609 - F1: 0.1111
sub_2:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_2:Test (Best Model) - Loss: 0.4451 - Accuracy: 0.3636 - F1: 0.3119
sub_2:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 0.4461 - Accuracy: 0.3182 - F1: 0.2159
sub_2:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.2727 - F1: 0.1071
sub_2:Test (Best Model) - Loss: 0.4488 - Accuracy: 0.2273 - F1: 0.0962
sub_2:Test (Best Model) - Loss: 0.4731 - Accuracy: 0.2174 - F1: 0.0893
sub_2:Test (Best Model) - Loss: 0.4491 - Accuracy: 0.2609 - F1: 0.1429
sub_2:Test (Best Model) - Loss: 0.4442 - Accuracy: 0.2609 - F1: 0.2419
sub_2:Test (Best Model) - Loss: 0.4128 - Accuracy: 0.3478 - F1: 0.2500
sub_2:Test (Best Model) - Loss: 0.4645 - Accuracy: 0.3913 - F1: 0.3587
sub_3:Test (Best Model) - Loss: 0.4459 - Accuracy: 0.2727 - F1: 0.2404
sub_3:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_3:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.3913 - F1: 0.2582
sub_3:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.3913 - F1: 0.3492
sub_3:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 0.4500 - Accuracy: 0.3913 - F1: 0.3133
sub_3:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 0.4674 - Accuracy: 0.2174 - F1: 0.1468
sub_3:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_3:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.4348 - F1: 0.3816
sub_4:Test (Best Model) - Loss: 0.4447 - Accuracy: 0.3043 - F1: 0.1929
sub_4:Test (Best Model) - Loss: 0.4444 - Accuracy: 0.3913 - F1: 0.2803
sub_4:Test (Best Model) - Loss: 0.4607 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.4555 - Accuracy: 0.3043 - F1: 0.1736
sub_4:Test (Best Model) - Loss: 0.4352 - Accuracy: 0.4783 - F1: 0.4271
sub_4:Test (Best Model) - Loss: 0.2569 - Accuracy: 0.6957 - F1: 0.6633
sub_4:Test (Best Model) - Loss: 0.4618 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.6087 - F1: 0.5600
sub_4:Test (Best Model) - Loss: 0.4138 - Accuracy: 0.3913 - F1: 0.2517
sub_4:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.2609 - F1: 0.2159
sub_4:Test (Best Model) - Loss: 0.4345 - Accuracy: 0.3913 - F1: 0.2649
sub_4:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_4:Test (Best Model) - Loss: 0.4517 - Accuracy: 0.3913 - F1: 0.3234
sub_5:Test (Best Model) - Loss: 0.4452 - Accuracy: 0.2727 - F1: 0.1111
sub_5:Test (Best Model) - Loss: 0.4377 - Accuracy: 0.3636 - F1: 0.2667
sub_5:Test (Best Model) - Loss: 0.3991 - Accuracy: 0.4545 - F1: 0.3750
sub_5:Test (Best Model) - Loss: 0.4467 - Accuracy: 0.1818 - F1: 0.0769
sub_5:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.5909 - F1: 0.5350
sub_5:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 0.4126 - Accuracy: 0.5000 - F1: 0.4415
sub_5:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 0.4278 - Accuracy: 0.3182 - F1: 0.2111
sub_5:Test (Best Model) - Loss: 0.4240 - Accuracy: 0.2727 - F1: 0.2048
sub_5:Test (Best Model) - Loss: 0.4457 - Accuracy: 0.2273 - F1: 0.1584
sub_5:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_5:Test (Best Model) - Loss: 0.4107 - Accuracy: 0.2727 - F1: 0.2262
sub_6:Test (Best Model) - Loss: 0.4271 - Accuracy: 0.3636 - F1: 0.3053
sub_6:Test (Best Model) - Loss: 0.4442 - Accuracy: 0.3182 - F1: 0.1756
sub_6:Test (Best Model) - Loss: 0.4356 - Accuracy: 0.2727 - F1: 0.1542
sub_6:Test (Best Model) - Loss: 0.4385 - Accuracy: 0.3182 - F1: 0.2500
sub_6:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.3182 - F1: 0.1825
sub_6:Test (Best Model) - Loss: 0.4619 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 0.4322 - Accuracy: 0.5217 - F1: 0.3431
sub_6:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 0.4596 - Accuracy: 0.3478 - F1: 0.2539
sub_6:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_6:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.5217 - F1: 0.3571
sub_6:Test (Best Model) - Loss: 0.3053 - Accuracy: 0.5652 - F1: 0.4244
sub_6:Test (Best Model) - Loss: 0.4512 - Accuracy: 0.3478 - F1: 0.2213
sub_6:Test (Best Model) - Loss: 0.4555 - Accuracy: 0.4783 - F1: 0.4194
sub_6:Test (Best Model) - Loss: 0.4030 - Accuracy: 0.5217 - F1: 0.4949
sub_7:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.2568 - Accuracy: 0.6364 - F1: 0.6000
sub_7:Test (Best Model) - Loss: 0.4166 - Accuracy: 0.4091 - F1: 0.2833
sub_7:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.4239 - Accuracy: 0.3182 - F1: 0.2788
sub_7:Test (Best Model) - Loss: 0.4348 - Accuracy: 0.3182 - F1: 0.1960
sub_7:Test (Best Model) - Loss: 0.4521 - Accuracy: 0.2727 - F1: 0.2065
sub_7:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_7:Test (Best Model) - Loss: 0.4170 - Accuracy: 0.4545 - F1: 0.3250
sub_7:Test (Best Model) - Loss: 0.4325 - Accuracy: 0.3182 - F1: 0.2261
sub_7:Test (Best Model) - Loss: 0.3681 - Accuracy: 0.4545 - F1: 0.3676
sub_7:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.2727 - F1: 0.1200
sub_7:Test (Best Model) - Loss: 0.4347 - Accuracy: 0.4545 - F1: 0.3123
sub_7:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4493 - Accuracy: 0.3636 - F1: 0.2361
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4381 - Accuracy: 0.1364 - F1: 0.0789
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.4545 - F1: 0.4456
sub_8:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4415 - Accuracy: 0.3182 - F1: 0.2247
sub_8:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_8:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4394 - Accuracy: 0.3182 - F1: 0.1970
sub_9:Test (Best Model) - Loss: 0.3886 - Accuracy: 0.4545 - F1: 0.2951
sub_9:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4467 - Accuracy: 0.2273 - F1: 0.1337
sub_9:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.4091 - F1: 0.2917
sub_9:Test (Best Model) - Loss: 0.4144 - Accuracy: 0.5909 - F1: 0.5816
sub_9:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4467 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4188 - Accuracy: 0.5455 - F1: 0.3529
sub_9:Test (Best Model) - Loss: 0.4459 - Accuracy: 0.1818 - F1: 0.1337
sub_9:Test (Best Model) - Loss: 0.4366 - Accuracy: 0.3182 - F1: 0.1917
sub_9:Test (Best Model) - Loss: 0.4398 - Accuracy: 0.2727 - F1: 0.1200
sub_9:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_9:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4442 - Accuracy: 0.2727 - F1: 0.1111
sub_10:Test (Best Model) - Loss: 0.4258 - Accuracy: 0.3636 - F1: 0.2867
sub_10:Test (Best Model) - Loss: 0.3835 - Accuracy: 0.3182 - F1: 0.2536
sub_10:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_10:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_10:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4449 - Accuracy: 0.3913 - F1: 0.3133
sub_11:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4549 - Accuracy: 0.3043 - F1: 0.1736
sub_11:Test (Best Model) - Loss: 0.4528 - Accuracy: 0.4783 - F1: 0.3810
sub_11:Test (Best Model) - Loss: 0.4539 - Accuracy: 0.3043 - F1: 0.3360
sub_11:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4587 - Accuracy: 0.3043 - F1: 0.2371
sub_11:Test (Best Model) - Loss: 0.4618 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4590 - Accuracy: 0.2174 - F1: 0.1417
sub_11:Test (Best Model) - Loss: 0.4633 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4522 - Accuracy: 0.4348 - F1: 0.3676
sub_11:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_11:Test (Best Model) - Loss: 0.4595 - Accuracy: 0.3913 - F1: 0.3159
sub_12:Test (Best Model) - Loss: 0.3499 - Accuracy: 0.5000 - F1: 0.4519
sub_12:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.2727 - F1: 0.1071
sub_12:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.2727 - F1: 0.1250
sub_12:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.3478 - F1: 0.2540
sub_12:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 0.4612 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_12:Test (Best Model) - Loss: 0.4188 - Accuracy: 0.4091 - F1: 0.3343
sub_12:Test (Best Model) - Loss: 0.4069 - Accuracy: 0.4545 - F1: 0.3750
sub_12:Test (Best Model) - Loss: 0.4359 - Accuracy: 0.4091 - F1: 0.3343
sub_12:Test (Best Model) - Loss: 0.4012 - Accuracy: 0.4545 - F1: 0.3485
sub_12:Test (Best Model) - Loss: 0.4371 - Accuracy: 0.3182 - F1: 0.2532
sub_13:Test (Best Model) - Loss: 0.4452 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4115 - Accuracy: 0.4091 - F1: 0.3393
sub_13:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_13:Test (Best Model) - Loss: 0.4313 - Accuracy: 0.3182 - F1: 0.2708
sub_13:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_13:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 0.4091 - Accuracy: 0.4091 - F1: 0.3467
sub_14:Test (Best Model) - Loss: 0.4261 - Accuracy: 0.5000 - F1: 0.4331
sub_14:Test (Best Model) - Loss: 0.4130 - Accuracy: 0.3636 - F1: 0.3258
sub_14:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 0.4155 - Accuracy: 0.2727 - F1: 0.2274
sub_14:Test (Best Model) - Loss: 0.4291 - Accuracy: 0.2727 - F1: 0.1667
sub_14:Test (Best Model) - Loss: 0.3586 - Accuracy: 0.5455 - F1: 0.4917
sub_14:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.4545 - F1: 0.3095
sub_14:Test (Best Model) - Loss: 0.4190 - Accuracy: 0.4545 - F1: 0.2929
sub_14:Test (Best Model) - Loss: 0.4041 - Accuracy: 0.5455 - F1: 0.3542
sub_14:Test (Best Model) - Loss: 0.4064 - Accuracy: 0.6364 - F1: 0.5979
sub_14:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 0.4090 - Accuracy: 0.5909 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_14:Test (Best Model) - Loss: 0.4141 - Accuracy: 0.5455 - F1: 0.3542
sub_15:Test (Best Model) - Loss: 0.3703 - Accuracy: 0.5000 - F1: 0.5511
sub_15:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.3610 - Accuracy: 0.5455 - F1: 0.5143
sub_15:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.6364 - F1: 0.6208
sub_15:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2273 - F1: 0.0926
sub_15:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.4091 - F1: 0.2604
sub_15:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.4545 - F1: 0.2967
sub_15:Test (Best Model) - Loss: 0.3689 - Accuracy: 0.4545 - F1: 0.3318
sub_15:Test (Best Model) - Loss: 0.2987 - Accuracy: 0.5000 - F1: 0.4980
sub_15:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.4262 - Accuracy: 0.4091 - F1: 0.2843
sub_15:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_15:Test (Best Model) - Loss: 0.4070 - Accuracy: 0.5909 - F1: 0.5417
sub_16:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1111
sub_16:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4199 - Accuracy: 0.4091 - F1: 0.3071
sub_16:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_16:Test (Best Model) - Loss: 0.4427 - Accuracy: 0.1818 - F1: 0.1497
sub_17:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.4219 - Accuracy: 0.3913 - F1: 0.3292
sub_17:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.4612 - Accuracy: 0.2609 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.5001 - Accuracy: 0.2609 - F1: 0.1889
sub_17:Test (Best Model) - Loss: 0.4607 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_17:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1504
sub_17:Test (Best Model) - Loss: 0.4440 - Accuracy: 0.3182 - F1: 0.1868
sub_17:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 0.3755 - Accuracy: 0.4091 - F1: 0.3393
sub_17:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_17:Test (Best Model) - Loss: 0.4251 - Accuracy: 0.5000 - F1: 0.4415
sub_18:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 0.4350 - Accuracy: 0.3478 - F1: 0.3282
sub_18:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_18:Test (Best Model) - Loss: 0.4767 - Accuracy: 0.2727 - F1: 0.2120
sub_18:Test (Best Model) - Loss: 0.4172 - Accuracy: 0.3636 - F1: 0.4048
sub_18:Test (Best Model) - Loss: 0.4208 - Accuracy: 0.4091 - F1: 0.3343
sub_18:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.4465 - Accuracy: 0.2727 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.4344 - Accuracy: 0.4545 - F1: 0.3750
sub_18:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_18:Test (Best Model) - Loss: 0.4435 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4186 - Accuracy: 0.4091 - F1: 0.3125
sub_19:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.3182 - F1: 0.2811
sub_19:Test (Best Model) - Loss: 0.4341 - Accuracy: 0.1818 - F1: 0.1961
sub_19:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4477 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4441 - Accuracy: 0.2727 - F1: 0.1364
sub_19:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4477 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4159 - Accuracy: 0.4091 - F1: 0.3722
sub_19:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_19:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 0.4198 - Accuracy: 0.4545 - F1: 0.3586
sub_20:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 0.4220 - Accuracy: 0.4545 - F1: 0.3750
sub_20:Test (Best Model) - Loss: 0.4390 - Accuracy: 0.3182 - F1: 0.1759
sub_20:Test (Best Model) - Loss: 0.4465 - Accuracy: 0.2727 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 0.4391 - Accuracy: 0.2727 - F1: 0.1111
sub_20:Test (Best Model) - Loss: 0.3209 - Accuracy: 0.5909 - F1: 0.6057
sub_20:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 0.3859 - Accuracy: 0.4545 - F1: 0.3750
sub_20:Test (Best Model) - Loss: 0.4466 - Accuracy: 0.2273 - F1: 0.0926
sub_20:Test (Best Model) - Loss: 0.3752 - Accuracy: 0.4783 - F1: 0.4652
sub_20:Test (Best Model) - Loss: 0.4567 - Accuracy: 0.2609 - F1: 0.1071
sub_20:Test (Best Model) - Loss: 0.4032 - Accuracy: 0.4783 - F1: 0.4525
sub_20:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_20:Test (Best Model) - Loss: 0.3784 - Accuracy: 0.5652 - F1: 0.5317
sub_21:Test (Best Model) - Loss: 0.4329 - Accuracy: 0.4091 - F1: 0.2614
sub_21:Test (Best Model) - Loss: 0.4248 - Accuracy: 0.4091 - F1: 0.2727
sub_21:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.2761 - Accuracy: 0.5455 - F1: 0.3542
sub_21:Test (Best Model) - Loss: 0.3536 - Accuracy: 0.5000 - F1: 0.3246
sub_21:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1932
sub_21:Test (Best Model) - Loss: 0.4265 - Accuracy: 0.4091 - F1: 0.2750
sub_21:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.4196 - Accuracy: 0.4091 - F1: 0.3131
sub_21:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_21:Test (Best Model) - Loss: 0.4374 - Accuracy: 0.5000 - F1: 0.3246
sub_21:Test (Best Model) - Loss: 0.4216 - Accuracy: 0.5909 - F1: 0.5363
sub_21:Test (Best Model) - Loss: 0.4358 - Accuracy: 0.5455 - F1: 0.3542
sub_21:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4591 - Accuracy: 0.0000 - F1: 0.0000
sub_22:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4598 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 0.4533 - Accuracy: 0.2609 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.3913 - F1: 0.2614
sub_22:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_22:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.2273 - F1: 0.1452
sub_22:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4163 - Accuracy: 0.4091 - F1: 0.3434
sub_22:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_22:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.3182 - F1: 0.2584
sub_23:Test (Best Model) - Loss: 0.4075 - Accuracy: 0.4348 - F1: 0.3095
sub_23:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.3478 - F1: 0.2337
sub_23:Test (Best Model) - Loss: 0.3646 - Accuracy: 0.4783 - F1: 0.4000
sub_23:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 0.4417 - Accuracy: 0.2727 - F1: 0.2298
sub_23:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 0.4236 - Accuracy: 0.3636 - F1: 0.2754
sub_23:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_23:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.5217 - F1: 0.5311
sub_23:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.4783 - F1: 0.4375
sub_23:Test (Best Model) - Loss: 0.4237 - Accuracy: 0.4783 - F1: 0.3512
sub_23:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_23:Test (Best Model) - Loss: 0.4612 - Accuracy: 0.2609 - F1: 0.1250
sub_24:Test (Best Model) - Loss: 0.4408 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4420 - Accuracy: 0.3636 - F1: 0.2344
sub_24:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4421 - Accuracy: 0.3182 - F1: 0.1970
sub_24:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.2727 - F1: 0.1591
sub_24:Test (Best Model) - Loss: 0.4327 - Accuracy: 0.1818 - F1: 0.1382
sub_24:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4502 - Accuracy: 0.3636 - F1: 0.2667
sub_24:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_24:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_25:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.5217 - F1: 0.4060
sub_25:Test (Best Model) - Loss: 0.3811 - Accuracy: 0.5217 - F1: 0.4162
sub_25:Test (Best Model) - Loss: 0.4398 - Accuracy: 0.5652 - F1: 0.4852
sub_25:Test (Best Model) - Loss: 0.3843 - Accuracy: 0.6522 - F1: 0.6320
sub_25:Test (Best Model) - Loss: 0.4497 - Accuracy: 0.3913 - F1: 0.2821
sub_25:Test (Best Model) - Loss: 0.3916 - Accuracy: 0.5909 - F1: 0.5859
sub_25:Test (Best Model) - Loss: 0.4340 - Accuracy: 0.4545 - F1: 0.3665
sub_25:Test (Best Model) - Loss: 0.4288 - Accuracy: 0.4545 - F1: 0.3750
sub_25:Test (Best Model) - Loss: 0.4474 - Accuracy: 0.2727 - F1: 0.1071
sub_25:Test (Best Model) - Loss: 0.4273 - Accuracy: 0.4545 - F1: 0.2951
sub_25:Test (Best Model) - Loss: 0.4213 - Accuracy: 0.3636 - F1: 0.2500
sub_25:Test (Best Model) - Loss: 0.3813 - Accuracy: 0.4091 - F1: 0.2788
sub_25:Test (Best Model) - Loss: 0.3994 - Accuracy: 0.4545 - F1: 0.4311
sub_25:Test (Best Model) - Loss: 0.4202 - Accuracy: 0.4091 - F1: 0.3581
sub_25:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_26:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 0.4594 - Accuracy: 0.2609 - F1: 0.1154
sub_26:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.2609 - F1: 0.1034
sub_26:Test (Best Model) - Loss: 0.3618 - Accuracy: 0.5455 - F1: 0.5000
sub_26:Test (Best Model) - Loss: 0.4390 - Accuracy: 0.3636 - F1: 0.2386
sub_26:Test (Best Model) - Loss: 0.4345 - Accuracy: 0.4091 - F1: 0.3343
sub_26:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_26:Test (Best Model) - Loss: 0.3894 - Accuracy: 0.5000 - F1: 0.4276
sub_26:Test (Best Model) - Loss: 0.4317 - Accuracy: 0.5000 - F1: 0.4159
sub_26:Test (Best Model) - Loss: 0.3994 - Accuracy: 0.4091 - F1: 0.3393
sub_26:Test (Best Model) - Loss: 0.4475 - Accuracy: 0.1364 - F1: 0.0882
sub_26:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.2727 - F1: 0.1071
sub_26:Test (Best Model) - Loss: 0.4511 - Accuracy: 0.2273 - F1: 0.1825
sub_27:Test (Best Model) - Loss: 0.4613 - Accuracy: 0.4783 - F1: 0.3137
sub_27:Test (Best Model) - Loss: 0.4333 - Accuracy: 0.3913 - F1: 0.3234
sub_27:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 0.4615 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 0.4614 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 0.4602 - Accuracy: 0.3043 - F1: 0.1920
sub_27:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 0.4507 - Accuracy: 0.3478 - F1: 0.2803
sub_27:Test (Best Model) - Loss: 0.4617 - Accuracy: 0.2609 - F1: 0.1034
sub_27:Test (Best Model) - Loss: 0.4616 - Accuracy: 0.1304 - F1: 0.0682
sub_27:Test (Best Model) - Loss: 0.4448 - Accuracy: 0.2727 - F1: 0.1071
sub_27:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_27:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_27:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_27:Test (Best Model) - Loss: 0.4462 - Accuracy: 0.3182 - F1: 0.1825
sub_28:Test (Best Model) - Loss: 0.4360 - Accuracy: 0.3636 - F1: 0.2338
sub_28:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4428 - Accuracy: 0.1818 - F1: 0.2074
sub_28:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4905 - Accuracy: 0.1818 - F1: 0.1466
sub_28:Test (Best Model) - Loss: 0.4376 - Accuracy: 0.2727 - F1: 0.1200
sub_28:Test (Best Model) - Loss: 0.4820 - Accuracy: 0.2727 - F1: 0.1774
sub_28:Test (Best Model) - Loss: 0.4482 - Accuracy: 0.2727 - F1: 0.1200
sub_28:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.2727 - F1: 0.1200
sub_28:Test (Best Model) - Loss: 0.4476 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4473 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_28:Test (Best Model) - Loss: 0.4445 - Accuracy: 0.2727 - F1: 0.2382
sub_28:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.1818 - F1: 0.0800
sub_29:Test (Best Model) - Loss: 0.4087 - Accuracy: 0.4545 - F1: 0.3247
sub_29:Test (Best Model) - Loss: 0.4344 - Accuracy: 0.4545 - F1: 0.3750
sub_29:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.4091 - F1: 0.3068
sub_29:Test (Best Model) - Loss: 0.4468 - Accuracy: 0.2727 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 0.4464 - Accuracy: 0.2727 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 0.3950 - Accuracy: 0.4091 - F1: 0.3403
sub_29:Test (Best Model) - Loss: 0.3944 - Accuracy: 0.4091 - F1: 0.3343
sub_29:Test (Best Model) - Loss: 0.4280 - Accuracy: 0.3636 - F1: 0.2754
sub_29:Test (Best Model) - Loss: 0.4472 - Accuracy: 0.2727 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 0.4461 - Accuracy: 0.2727 - F1: 0.1071
sub_29:Test (Best Model) - Loss: 0.4314 - Accuracy: 0.3478 - F1: 0.2582
sub_29:Test (Best Model) - Loss: 0.4469 - Accuracy: 0.3913 - F1: 0.3029
sub_29:Test (Best Model) - Loss: 0.4346 - Accuracy: 0.4783 - F1: 0.3750
sub_29:Test (Best Model) - Loss: 0.4540 - Accuracy: 0.3913 - F1: 0.2674
sub_29:Test (Best Model) - Loss: 0.4612 - Accuracy: 0.2609 - F1: 0.1034

=== Summary Results ===

acc:   32.77 ± 5.06
F1:    20.33 ± 6.13
acc‑in:43.90 ± 6.55
F1‑in: 29.14 ± 8.38
