lr: 0.001
sub_1:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.3750 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.3946 - Accuracy: 0.5000 - F1: 0.4667
sub_1:Test (Best Model) - Loss: 0.3504 - Accuracy: 0.6875 - F1: 0.6537
sub_1:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.4106 - Accuracy: 0.3750 - F1: 0.2727
sub_1:Test (Best Model) - Loss: 0.3353 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3332 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3317 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3330 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3868 - Accuracy: 0.5000 - F1: 0.4667
sub_1:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3542 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3195 - Accuracy: 0.6250 - F1: 0.6190
sub_2:Test (Best Model) - Loss: 0.3405 - Accuracy: 0.4375 - F1: 0.4353
sub_2:Test (Best Model) - Loss: 0.3089 - Accuracy: 0.7500 - F1: 0.7333
sub_2:Test (Best Model) - Loss: 0.3338 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3323 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.2970 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.2806 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.3968 - Accuracy: 0.5625 - F1: 0.5466
sub_2:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3196 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 0.2237 - Accuracy: 0.8125 - F1: 0.7922
sub_2:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.2813 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.3318 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3440 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.3721 - Accuracy: 0.5000 - F1: 0.4921
sub_3:Test (Best Model) - Loss: 0.4100 - Accuracy: 0.4375 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 0.3531 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3294 - Accuracy: 0.5000 - F1: 0.4182
sub_3:Test (Best Model) - Loss: 0.2957 - Accuracy: 0.6875 - F1: 0.6863
sub_3:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5000 - F1: 0.4921
sub_3:Test (Best Model) - Loss: 0.3329 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3327 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3320 - Accuracy: 0.5625 - F1: 0.5152
sub_3:Test (Best Model) - Loss: 0.3292 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3333 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3615 - Accuracy: 0.5625 - F1: 0.5152
sub_4:Test (Best Model) - Loss: 0.2692 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3361 - Accuracy: 0.6875 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.2831 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3371 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3300 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.2839 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3354 - Accuracy: 0.6250 - F1: 0.5000
sub_4:Test (Best Model) - Loss: 0.2740 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3092 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.3422 - Accuracy: 0.5625 - F1: 0.5608
sub_4:Test (Best Model) - Loss: 0.3009 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.2694 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3151 - Accuracy: 0.5625 - F1: 0.5152
sub_5:Test (Best Model) - Loss: 0.4065 - Accuracy: 0.6250 - F1: 0.6000
sub_5:Test (Best Model) - Loss: 0.2173 - Accuracy: 0.8750 - F1: 0.8750
sub_5:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3433 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3479 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.2330 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.3546 - Accuracy: 0.5625 - F1: 0.4589
sub_5:Test (Best Model) - Loss: 0.2969 - Accuracy: 0.8750 - F1: 0.8730
sub_5:Test (Best Model) - Loss: 0.2901 - Accuracy: 0.6875 - F1: 0.6135
sub_5:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.6250 - F1: 0.6190
sub_5:Test (Best Model) - Loss: 0.3484 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.5000 - F1: 0.4921
sub_6:Test (Best Model) - Loss: 0.3512 - Accuracy: 0.6250 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.3490 - Accuracy: 0.4375 - F1: 0.4170
sub_6:Test (Best Model) - Loss: 0.3427 - Accuracy: 0.5625 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.3857 - Accuracy: 0.3750 - F1: 0.2727
sub_6:Test (Best Model) - Loss: 0.3373 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.2927 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 0.3307 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.6875 - F1: 0.6135
sub_6:Test (Best Model) - Loss: 0.3328 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3314 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3313 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3326 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3282 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3642 - Accuracy: 0.3750 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3900 - Accuracy: 0.3750 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3442 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3474 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3571 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3433 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3479 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3312 - Accuracy: 0.6250 - F1: 0.5636
sub_7:Test (Best Model) - Loss: 0.2718 - Accuracy: 0.7500 - F1: 0.7460
sub_7:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3427 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3173 - Accuracy: 0.6875 - F1: 0.6863
sub_8:Test (Best Model) - Loss: 0.3424 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.5250 - Accuracy: 0.5000 - F1: 0.4921
sub_8:Test (Best Model) - Loss: 0.3954 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3889 - Accuracy: 0.3125 - F1: 0.3098
sub_8:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.4375 - F1: 0.4170
sub_8:Test (Best Model) - Loss: 0.3480 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3585 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.4317 - Accuracy: 0.6250 - F1: 0.6250
sub_9:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.5000 - F1: 0.5000
sub_9:Test (Best Model) - Loss: 0.3405 - Accuracy: 0.6250 - F1: 0.6000
sub_9:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.5608
sub_9:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3418 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3535 - Accuracy: 0.5625 - F1: 0.4589
sub_9:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.4589
sub_9:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.4375 - F1: 0.3043
sub_10:Test (Best Model) - Loss: 0.4390 - Accuracy: 0.3125 - F1: 0.2874
sub_10:Test (Best Model) - Loss: 0.4230 - Accuracy: 0.3125 - F1: 0.2874
sub_10:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3384 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.4212 - Accuracy: 0.3125 - F1: 0.2874
sub_10:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.3125 - F1: 0.3098
sub_10:Test (Best Model) - Loss: 0.3483 - Accuracy: 0.5000 - F1: 0.4182
sub_10:Test (Best Model) - Loss: 0.4573 - Accuracy: 0.3125 - F1: 0.3098
sub_10:Test (Best Model) - Loss: 0.3292 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3174 - Accuracy: 0.6875 - F1: 0.6135
sub_10:Test (Best Model) - Loss: 0.3247 - Accuracy: 0.6250 - F1: 0.5000
sub_10:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.5380 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.3329 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3329 - Accuracy: 0.3750 - F1: 0.2727
sub_11:Test (Best Model) - Loss: 0.3416 - Accuracy: 0.5000 - F1: 0.4182
sub_11:Test (Best Model) - Loss: 0.2950 - Accuracy: 0.6875 - F1: 0.6863
sub_11:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.6250 - F1: 0.6000
sub_11:Test (Best Model) - Loss: 0.3326 - Accuracy: 0.5625 - F1: 0.5608
sub_11:Test (Best Model) - Loss: 0.3496 - Accuracy: 0.6250 - F1: 0.6000
sub_11:Test (Best Model) - Loss: 0.2756 - Accuracy: 0.7500 - F1: 0.7333
sub_11:Test (Best Model) - Loss: 0.3568 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.2993 - Accuracy: 0.6875 - F1: 0.6135
sub_11:Test (Best Model) - Loss: 0.3985 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3260 - Accuracy: 0.6250 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.3316 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3398 - Accuracy: 0.6250 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3424 - Accuracy: 0.5625 - F1: 0.4589
sub_12:Test (Best Model) - Loss: 0.3420 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3406 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3311 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3251 - Accuracy: 0.6250 - F1: 0.6000
sub_12:Test (Best Model) - Loss: 0.3382 - Accuracy: 0.5000 - F1: 0.4667
sub_12:Test (Best Model) - Loss: 0.3318 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.5625 - F1: 0.4589
sub_12:Test (Best Model) - Loss: 0.4098 - Accuracy: 0.3750 - F1: 0.3651
sub_12:Test (Best Model) - Loss: 0.3694 - Accuracy: 0.3750 - F1: 0.2727
sub_12:Test (Best Model) - Loss: 0.3469 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3474 - Accuracy: 0.3750 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.4499 - Accuracy: 0.5000 - F1: 0.4182
sub_13:Test (Best Model) - Loss: 0.3418 - Accuracy: 0.5625 - F1: 0.5608
sub_13:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3421 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3437 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3991 - Accuracy: 0.3125 - F1: 0.2381
sub_13:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3912 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3514 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3848 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3570 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.6875 - F1: 0.6761
sub_13:Test (Best Model) - Loss: 0.3619 - Accuracy: 0.4375 - F1: 0.3766
sub_13:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.6250 - F1: 0.6250
sub_13:Test (Best Model) - Loss: 0.3423 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.4566 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.3483 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.4704 - Accuracy: 0.5000 - F1: 0.4667
sub_14:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3423 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3538 - Accuracy: 0.5000 - F1: 0.4182
sub_14:Test (Best Model) - Loss: 0.3496 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.3410 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3427 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3484 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.4528 - Accuracy: 0.5000 - F1: 0.4182
sub_14:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3420 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.4304 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.4034 - Accuracy: 0.4375 - F1: 0.3043
sub_15:Test (Best Model) - Loss: 0.3427 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3548 - Accuracy: 0.5625 - F1: 0.5152
sub_15:Test (Best Model) - Loss: 0.4263 - Accuracy: 0.3125 - F1: 0.3098
sub_15:Test (Best Model) - Loss: 0.3487 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.4838 - Accuracy: 0.3125 - F1: 0.3098
sub_15:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3485 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3396 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3596 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3480 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3426 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3927 - Accuracy: 0.5000 - F1: 0.4182
sub_15:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3951 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.3785 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.3796 - Accuracy: 0.5000 - F1: 0.4921
sub_16:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.5000 - F1: 0.4667
sub_16:Test (Best Model) - Loss: 0.3437 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5625 - F1: 0.5608
sub_16:Test (Best Model) - Loss: 0.4301 - Accuracy: 0.4375 - F1: 0.4353
sub_16:Test (Best Model) - Loss: 0.3069 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 0.3435 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.2321 - Accuracy: 0.8125 - F1: 0.8118
sub_16:Test (Best Model) - Loss: 0.3269 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 0.3420 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.4627 - Accuracy: 0.5625 - F1: 0.5152
sub_16:Test (Best Model) - Loss: 0.3601 - Accuracy: 0.3125 - F1: 0.2874
sub_16:Test (Best Model) - Loss: 0.3279 - Accuracy: 0.6875 - F1: 0.6537
sub_17:Test (Best Model) - Loss: 0.3333 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3386 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3342 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3332 - Accuracy: 0.5625 - F1: 0.4589
sub_17:Test (Best Model) - Loss: 0.3325 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3821 - Accuracy: 0.4375 - F1: 0.3766
sub_17:Test (Best Model) - Loss: 0.3222 - Accuracy: 0.6250 - F1: 0.5000
sub_17:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3336 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.4788 - Accuracy: 0.3125 - F1: 0.3098
sub_17:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3414 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.4375 - F1: 0.4170
sub_18:Test (Best Model) - Loss: 0.3377 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3337 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3473 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3399 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3490 - Accuracy: 0.6250 - F1: 0.6190
sub_18:Test (Best Model) - Loss: 0.3470 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3482 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3385 - Accuracy: 0.6250 - F1: 0.5000
sub_18:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3411 - Accuracy: 0.5000 - F1: 0.4182
sub_19:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3263 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.5289 - Accuracy: 0.5625 - F1: 0.5152
sub_19:Test (Best Model) - Loss: 0.3490 - Accuracy: 0.5625 - F1: 0.5608
sub_19:Test (Best Model) - Loss: 0.3141 - Accuracy: 0.8125 - F1: 0.7922
sub_19:Test (Best Model) - Loss: 0.3246 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.2269 - Accuracy: 0.8125 - F1: 0.7922
sub_19:Test (Best Model) - Loss: 0.3319 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.3468 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3904 - Accuracy: 0.3750 - F1: 0.3651
sub_19:Test (Best Model) - Loss: 0.3360 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3860 - Accuracy: 0.4375 - F1: 0.4353
sub_20:Test (Best Model) - Loss: 0.3685 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 0.3711 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.3300 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.3426 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3437 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.7500 - F1: 0.7091
sub_20:Test (Best Model) - Loss: 0.3145 - Accuracy: 0.6875 - F1: 0.6537
sub_20:Test (Best Model) - Loss: 0.3294 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3407 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.3315 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3291 - Accuracy: 0.6250 - F1: 0.6250
sub_21:Test (Best Model) - Loss: 0.3521 - Accuracy: 0.5000 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.4375 - F1: 0.3043
sub_21:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3264 - Accuracy: 0.6250 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.3400 - Accuracy: 0.6250 - F1: 0.6190
sub_21:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.5000 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.3421 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.4349 - Accuracy: 0.2500 - F1: 0.2500
sub_21:Test (Best Model) - Loss: 0.3442 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3479 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3888 - Accuracy: 0.3750 - F1: 0.3651
sub_22:Test (Best Model) - Loss: 0.4752 - Accuracy: 0.5625 - F1: 0.5466
sub_22:Test (Best Model) - Loss: 0.3635 - Accuracy: 0.5000 - F1: 0.4921
sub_22:Test (Best Model) - Loss: 0.3535 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3423 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3378 - Accuracy: 0.6250 - F1: 0.6000
sub_22:Test (Best Model) - Loss: 0.4003 - Accuracy: 0.5625 - F1: 0.4589
sub_22:Test (Best Model) - Loss: 0.3195 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.3170 - Accuracy: 0.6875 - F1: 0.6135
sub_22:Test (Best Model) - Loss: 0.3328 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3577 - Accuracy: 0.5625 - F1: 0.5608
sub_22:Test (Best Model) - Loss: 0.3262 - Accuracy: 0.9375 - F1: 0.9352
sub_22:Test (Best Model) - Loss: 0.1853 - Accuracy: 0.8750 - F1: 0.8750
sub_22:Test (Best Model) - Loss: 0.3306 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3311 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.2651 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3129 - Accuracy: 0.6875 - F1: 0.6135
sub_23:Test (Best Model) - Loss: 0.3326 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.4121 - Accuracy: 0.5000 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.3922 - Accuracy: 0.3750 - F1: 0.2727
sub_23:Test (Best Model) - Loss: 0.4485 - Accuracy: 0.3750 - F1: 0.2727
sub_23:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.3396 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.4232 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.3593 - Accuracy: 0.3750 - F1: 0.2727
sub_23:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.3125 - F1: 0.2381
sub_23:Test (Best Model) - Loss: 0.3337 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.3750 - F1: 0.3651
sub_24:Test (Best Model) - Loss: 0.5394 - Accuracy: 0.5000 - F1: 0.4921
sub_24:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.3750 - F1: 0.3333
sub_24:Test (Best Model) - Loss: 0.3640 - Accuracy: 0.5000 - F1: 0.4182
sub_24:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3696 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.3410 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 0.3494 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3402 - Accuracy: 0.6250 - F1: 0.6190
sub_24:Test (Best Model) - Loss: 0.3480 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3444 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3435 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3328 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3359 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.6875 - F1: 0.6135
sub_25:Test (Best Model) - Loss: 0.4831 - Accuracy: 0.4375 - F1: 0.3766
sub_25:Test (Best Model) - Loss: 0.3333 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3867 - Accuracy: 0.5000 - F1: 0.4182
sub_25:Test (Best Model) - Loss: 0.3427 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3417 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3415 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.4550 - Accuracy: 0.3125 - F1: 0.2381
sub_25:Test (Best Model) - Loss: 0.3688 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.3442 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3776 - Accuracy: 0.5625 - F1: 0.5152
sub_26:Test (Best Model) - Loss: 0.3651 - Accuracy: 0.3125 - F1: 0.2381
sub_26:Test (Best Model) - Loss: 0.3384 - Accuracy: 0.3125 - F1: 0.3098
sub_26:Test (Best Model) - Loss: 0.3334 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3328 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3570 - Accuracy: 0.3750 - F1: 0.3651
sub_26:Test (Best Model) - Loss: 0.3471 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3975 - Accuracy: 0.4375 - F1: 0.3043
sub_26:Test (Best Model) - Loss: 0.3442 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3138 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3474 - Accuracy: 0.4375 - F1: 0.4170
sub_26:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3435 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3137 - Accuracy: 0.6250 - F1: 0.6190
sub_27:Test (Best Model) - Loss: 0.3377 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3342 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3071 - Accuracy: 0.6875 - F1: 0.6537
sub_27:Test (Best Model) - Loss: 0.3360 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3322 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.4631 - Accuracy: 0.3750 - F1: 0.2727
sub_27:Test (Best Model) - Loss: 0.3580 - Accuracy: 0.4375 - F1: 0.3766
sub_27:Test (Best Model) - Loss: 0.3386 - Accuracy: 0.6250 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.3410 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3464 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.3435 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3288 - Accuracy: 0.5625 - F1: 0.5608
sub_28:Test (Best Model) - Loss: 0.2827 - Accuracy: 0.7500 - F1: 0.7460
sub_28:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.5625 - F1: 0.4589
sub_28:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.4652 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 0.3733 - Accuracy: 0.5000 - F1: 0.4667
sub_28:Test (Best Model) - Loss: 0.3634 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.3468 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.4259 - Accuracy: 0.3750 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 0.3436 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3603 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3474 - Accuracy: 0.5625 - F1: 0.5152
sub_29:Test (Best Model) - Loss: 0.2467 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.3051 - Accuracy: 0.6875 - F1: 0.6761
sub_29:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3901 - Accuracy: 0.5000 - F1: 0.3333
sub_29:Test (Best Model) - Loss: 0.3581 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3431 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3512 - Accuracy: 0.4375 - F1: 0.3043
sub_29:Test (Best Model) - Loss: 0.4047 - Accuracy: 0.6250 - F1: 0.6000
sub_29:Test (Best Model) - Loss: 0.3551 - Accuracy: 0.5000 - F1: 0.4182
sub_29:Test (Best Model) - Loss: 0.3282 - Accuracy: 0.6250 - F1: 0.5000
sub_29:Test (Best Model) - Loss: 0.2844 - Accuracy: 0.7500 - F1: 0.7333
sub_29:Test (Best Model) - Loss: 0.2334 - Accuracy: 0.8125 - F1: 0.8118
sub_29:Test (Best Model) - Loss: 0.3336 - Accuracy: 0.5625 - F1: 0.3600

=== Summary Results ===

acc:   55.99 ± 4.13
F1:    43.49 ± 5.81
acc-in:73.55 ± 5.14
F1-in: 60.45 ± 8.90
