lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3336 - Accuracy: 0.6250 - F1: 0.5000
sub_1:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3440 - Accuracy: 0.4375 - F1: 0.4170
sub_1:Test (Best Model) - Loss: 0.3342 - Accuracy: 0.5625 - F1: 0.5152
sub_1:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.5000 - F1: 0.4921
sub_1:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_1:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5000 - F1: 0.4667
sub_1:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3234 - Accuracy: 0.6250 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.3032 - Accuracy: 0.6875 - F1: 0.6863
sub_2:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.6250 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.3304 - Accuracy: 0.6875 - F1: 0.6537
sub_2:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3079 - Accuracy: 0.8750 - F1: 0.8730
sub_2:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8125 - F1: 0.8057
sub_2:Test (Best Model) - Loss: 0.3142 - Accuracy: 0.6875 - F1: 0.6863
sub_2:Test (Best Model) - Loss: 0.2964 - Accuracy: 0.8125 - F1: 0.8118
sub_2:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_2:Test (Best Model) - Loss: 0.3074 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.3212 - Accuracy: 0.6250 - F1: 0.5636
sub_2:Test (Best Model) - Loss: 0.3329 - Accuracy: 0.5625 - F1: 0.5608
sub_2:Test (Best Model) - Loss: 0.3235 - Accuracy: 0.6875 - F1: 0.6537
sub_2:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.6250 - F1: 0.6250
sub_3:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.5466
sub_3:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.5608
sub_3:Test (Best Model) - Loss: 0.3298 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.5152
sub_3:Test (Best Model) - Loss: 0.3340 - Accuracy: 0.5000 - F1: 0.4667
sub_3:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3337 - Accuracy: 0.5625 - F1: 0.3600
sub_3:Test (Best Model) - Loss: 0.3223 - Accuracy: 0.6875 - F1: 0.6863
sub_3:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.6250 - F1: 0.5636
sub_3:Test (Best Model) - Loss: 0.3255 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.5466
sub_4:Test (Best Model) - Loss: 0.3206 - Accuracy: 0.6875 - F1: 0.6537
sub_4:Test (Best Model) - Loss: 0.2987 - Accuracy: 0.6875 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.3167 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3207 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.2533 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.3325 - Accuracy: 0.6250 - F1: 0.5000
sub_4:Test (Best Model) - Loss: 0.3320 - Accuracy: 0.5625 - F1: 0.3600
sub_4:Test (Best Model) - Loss: 0.3232 - Accuracy: 0.7500 - F1: 0.7091
sub_4:Test (Best Model) - Loss: 0.3314 - Accuracy: 0.6250 - F1: 0.6190
sub_4:Test (Best Model) - Loss: 0.3217 - Accuracy: 0.6875 - F1: 0.6135
sub_4:Test (Best Model) - Loss: 0.2909 - Accuracy: 0.7500 - F1: 0.7500
sub_4:Test (Best Model) - Loss: 0.3114 - Accuracy: 0.6875 - F1: 0.6863
sub_4:Test (Best Model) - Loss: 0.3069 - Accuracy: 0.8125 - F1: 0.8118
sub_5:Test (Best Model) - Loss: 0.3590 - Accuracy: 0.1875 - F1: 0.1579
sub_5:Test (Best Model) - Loss: 0.3527 - Accuracy: 0.3125 - F1: 0.3098
sub_5:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.4375 - F1: 0.4170
sub_5:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.2329 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.2784 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.3298 - Accuracy: 0.6875 - F1: 0.6537
sub_5:Test (Best Model) - Loss: 0.3300 - Accuracy: 0.8125 - F1: 0.7922
sub_5:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3468 - Accuracy: 0.5000 - F1: 0.4182
sub_5:Test (Best Model) - Loss: 0.2822 - Accuracy: 0.7500 - F1: 0.7460
sub_5:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5000 - F1: 0.4667
sub_5:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_5:Test (Best Model) - Loss: 0.3978 - Accuracy: 0.5000 - F1: 0.4182
sub_6:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 0.3206 - Accuracy: 0.6875 - F1: 0.6863
sub_6:Test (Best Model) - Loss: 0.3507 - Accuracy: 0.5625 - F1: 0.5608
sub_6:Test (Best Model) - Loss: 0.3417 - Accuracy: 0.6250 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.3433 - Accuracy: 0.6250 - F1: 0.6250
sub_6:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.2853 - Accuracy: 0.7500 - F1: 0.7460
sub_6:Test (Best Model) - Loss: 0.3330 - Accuracy: 0.6250 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3251 - Accuracy: 0.6250 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.3306 - Accuracy: 0.5625 - F1: 0.5152
sub_6:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600
sub_6:Test (Best Model) - Loss: 0.3384 - Accuracy: 0.5000 - F1: 0.4182
sub_6:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3785 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.4375 - F1: 0.4170
sub_7:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3341 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3513 - Accuracy: 0.4375 - F1: 0.3043
sub_7:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3037 - Accuracy: 0.8125 - F1: 0.8057
sub_7:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_7:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3333 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 0.3406 - Accuracy: 0.5625 - F1: 0.5608
sub_8:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3495 - Accuracy: 0.3125 - F1: 0.2381
sub_8:Test (Best Model) - Loss: 0.3548 - Accuracy: 0.3750 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.3504 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3233 - Accuracy: 0.6875 - F1: 0.6537
sub_8:Test (Best Model) - Loss: 0.3410 - Accuracy: 0.6250 - F1: 0.5000
sub_8:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_8:Test (Best Model) - Loss: 0.3428 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3279 - Accuracy: 0.5625 - F1: 0.5466
sub_9:Test (Best Model) - Loss: 0.3530 - Accuracy: 0.5000 - F1: 0.4667
sub_9:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3426 - Accuracy: 0.5625 - F1: 0.4589
sub_9:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3492 - Accuracy: 0.5000 - F1: 0.4921
sub_9:Test (Best Model) - Loss: 0.3375 - Accuracy: 0.5625 - F1: 0.5152
sub_9:Test (Best Model) - Loss: 0.3495 - Accuracy: 0.1875 - F1: 0.1843
sub_9:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.6250 - F1: 0.5000
sub_9:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3503 - Accuracy: 0.5000 - F1: 0.5000
sub_9:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_9:Test (Best Model) - Loss: 0.3519 - Accuracy: 0.4375 - F1: 0.3766
sub_9:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.6875 - F1: 0.6135
sub_10:Test (Best Model) - Loss: 0.3597 - Accuracy: 0.3125 - F1: 0.2874
sub_10:Test (Best Model) - Loss: 0.3614 - Accuracy: 0.3125 - F1: 0.2874
sub_10:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3447 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3550 - Accuracy: 0.3125 - F1: 0.3098
sub_10:Test (Best Model) - Loss: 0.3726 - Accuracy: 0.3750 - F1: 0.3651
sub_10:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3548 - Accuracy: 0.3750 - F1: 0.3651
sub_10:Test (Best Model) - Loss: 0.3294 - Accuracy: 0.6250 - F1: 0.5636
sub_10:Test (Best Model) - Loss: 0.3378 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 0.3387 - Accuracy: 0.5000 - F1: 0.4667
sub_10:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_10:Test (Best Model) - Loss: 0.3337 - Accuracy: 0.6875 - F1: 0.6135
sub_11:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.4375 - F1: 0.3766
sub_11:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3430 - Accuracy: 0.4375 - F1: 0.3043
sub_11:Test (Best Model) - Loss: 0.3229 - Accuracy: 0.7500 - F1: 0.7500
sub_11:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.7500 - F1: 0.7091
sub_11:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.6250 - F1: 0.5000
sub_11:Test (Best Model) - Loss: 0.3221 - Accuracy: 0.6875 - F1: 0.6537
sub_11:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.6250 - F1: 0.6000
sub_11:Test (Best Model) - Loss: 0.3365 - Accuracy: 0.5000 - F1: 0.4921
sub_11:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3354 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3324 - Accuracy: 0.6875 - F1: 0.6135
sub_11:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.4589
sub_11:Test (Best Model) - Loss: 0.3353 - Accuracy: 0.5625 - F1: 0.3600
sub_11:Test (Best Model) - Loss: 0.3341 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3416 - Accuracy: 0.5000 - F1: 0.4667
sub_12:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3361 - Accuracy: 0.6250 - F1: 0.6000
sub_12:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3341 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3340 - Accuracy: 0.8125 - F1: 0.8057
sub_12:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3339 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3627 - Accuracy: 0.3750 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.3981 - Accuracy: 0.4375 - F1: 0.3766
sub_12:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.2500 - F1: 0.2000
sub_12:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_12:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3486 - Accuracy: 0.5000 - F1: 0.4182
sub_13:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.5625 - F1: 0.5152
sub_13:Test (Best Model) - Loss: 0.3358 - Accuracy: 0.6875 - F1: 0.6135
sub_13:Test (Best Model) - Loss: 0.3576 - Accuracy: 0.3750 - F1: 0.3651
sub_13:Test (Best Model) - Loss: 0.3763 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3512 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3364 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3367 - Accuracy: 0.4375 - F1: 0.3043
sub_13:Test (Best Model) - Loss: 0.3468 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3142 - Accuracy: 0.6250 - F1: 0.6190
sub_13:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.5152
sub_13:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_13:Test (Best Model) - Loss: 0.3424 - Accuracy: 0.6250 - F1: 0.5000
sub_14:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.4667
sub_14:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3452 - 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: 0.3403 - Accuracy: 0.5625 - F1: 0.5152
sub_14:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_14:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3494 - Accuracy: 0.6250 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.4400 - Accuracy: 0.3750 - F1: 0.3651
sub_15:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.6250 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_15:Test (Best Model) - Loss: 0.3433 - Accuracy: 0.3750 - F1: 0.3333
sub_15:Test (Best Model) - Loss: 0.3491 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 0.3414 - Accuracy: 0.5625 - F1: 0.5466
sub_15:Test (Best Model) - Loss: 0.3516 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3492 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.3426 - Accuracy: 0.5625 - F1: 0.5466
sub_16:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.5000 - F1: 0.4182
sub_16:Test (Best Model) - Loss: 0.3437 - Accuracy: 0.6875 - F1: 0.6135
sub_16:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3522 - Accuracy: 0.5000 - F1: 0.4182
sub_16:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.4375 - F1: 0.3766
sub_16:Test (Best Model) - Loss: 0.3420 - Accuracy: 0.8750 - F1: 0.8730
sub_16:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3316 - Accuracy: 0.8750 - F1: 0.8750
sub_16:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.7500 - F1: 0.7333
sub_16:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.5625 - F1: 0.3600
sub_16:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.6250 - F1: 0.5636
sub_16:Test (Best Model) - Loss: 0.3059 - Accuracy: 0.7500 - F1: 0.7500
sub_16:Test (Best Model) - Loss: 0.3394 - Accuracy: 0.6875 - F1: 0.6135
sub_17:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3327 - Accuracy: 0.6250 - F1: 0.5636
sub_17:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3353 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_17:Test (Best Model) - Loss: 0.3446 - Accuracy: 0.5625 - F1: 0.5608
sub_17:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.4375 - F1: 0.3766
sub_17:Test (Best Model) - Loss: 0.3930 - Accuracy: 0.4375 - F1: 0.3043
sub_17:Test (Best Model) - Loss: 0.3503 - Accuracy: 0.4375 - F1: 0.4353
sub_17:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.3750 - F1: 0.3333
sub_18:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3343 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3448 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3476 - Accuracy: 0.6250 - F1: 0.6250
sub_18:Test (Best Model) - Loss: 0.3588 - Accuracy: 0.4375 - F1: 0.4170
sub_18:Test (Best Model) - Loss: 0.3090 - Accuracy: 0.6875 - F1: 0.6761
sub_18:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3518 - Accuracy: 0.5000 - F1: 0.4182
sub_18:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_18:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3424 - Accuracy: 0.6875 - F1: 0.6761
sub_19:Test (Best Model) - Loss: 0.3474 - Accuracy: 0.5000 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.3418 - Accuracy: 0.6875 - F1: 0.6863
sub_19:Test (Best Model) - Loss: 0.3098 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.2825 - Accuracy: 0.7500 - F1: 0.7091
sub_19:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.6250 - F1: 0.5636
sub_19:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.6250 - F1: 0.5000
sub_19:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3429 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3287 - Accuracy: 0.6875 - F1: 0.6135
sub_19:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5625 - F1: 0.3600
sub_19:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3400 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.5625 - F1: 0.4589
sub_20:Test (Best Model) - Loss: 0.3303 - Accuracy: 0.6875 - F1: 0.6135
sub_20:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3239 - Accuracy: 0.6250 - F1: 0.5000
sub_20:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5000 - F1: 0.4667
sub_20:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3342 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_20:Test (Best Model) - Loss: 0.3422 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3313 - Accuracy: 0.6250 - F1: 0.6000
sub_21:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.6875 - F1: 0.6537
sub_21:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.5000 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.5000 - F1: 0.3333
sub_21:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3500 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 0.3841 - Accuracy: 0.3125 - F1: 0.2381
sub_21:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.6250 - F1: 0.5000
sub_21:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_21:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3498 - Accuracy: 0.4375 - F1: 0.4170
sub_22:Test (Best Model) - Loss: 0.3552 - Accuracy: 0.5000 - F1: 0.4921
sub_22:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.5152
sub_22:Test (Best Model) - Loss: 0.3469 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3457 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3347 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3147 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.5625 - F1: 0.3600
sub_22:Test (Best Model) - Loss: 0.3624 - Accuracy: 0.4375 - F1: 0.4170
sub_22:Test (Best Model) - Loss: 0.2972 - Accuracy: 0.7500 - F1: 0.7500
sub_22:Test (Best Model) - Loss: 0.3425 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.6250 - F1: 0.5000
sub_22:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3320 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.2731 - Accuracy: 0.8750 - F1: 0.8667
sub_23:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3254 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3331 - Accuracy: 0.5625 - F1: 0.5608
sub_23:Test (Best Model) - Loss: 0.3454 - Accuracy: 0.4375 - F1: 0.3766
sub_23:Test (Best Model) - Loss: 0.3479 - Accuracy: 0.5000 - F1: 0.4921
sub_23:Test (Best Model) - Loss: 0.3106 - Accuracy: 0.8750 - F1: 0.8730
sub_23:Test (Best Model) - Loss: 0.3415 - Accuracy: 0.6250 - F1: 0.5000
sub_23:Test (Best Model) - Loss: 0.3952 - Accuracy: 0.4375 - F1: 0.3766
sub_23:Test (Best Model) - Loss: 0.3376 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3368 - Accuracy: 0.5625 - F1: 0.3600
sub_23:Test (Best Model) - Loss: 0.3516 - Accuracy: 0.3750 - F1: 0.2727
sub_23:Test (Best Model) - Loss: 0.3355 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3471 - Accuracy: 0.5625 - F1: 0.5152
sub_24:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 0.3445 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3452 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3480 - Accuracy: 0.3750 - F1: 0.3651
sub_24:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.6250 - F1: 0.5636
sub_24:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_24:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3356 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3338 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3434 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.5625 - F1: 0.5466
sub_25:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.6875 - F1: 0.6135
sub_25:Test (Best Model) - Loss: 0.3449 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.5625 - F1: 0.5152
sub_25:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.5000 - F1: 0.4667
sub_25:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_25:Test (Best Model) - Loss: 0.3481 - Accuracy: 0.5000 - F1: 0.4182
sub_26:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3666 - Accuracy: 0.3750 - F1: 0.3651
sub_26:Test (Best Model) - Loss: 0.3363 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3756 - Accuracy: 0.3125 - F1: 0.3098
sub_26:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3455 - 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: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3460 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3463 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3493 - Accuracy: 0.3750 - F1: 0.3333
sub_26:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.3600
sub_26:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3143 - Accuracy: 0.6875 - F1: 0.6135
sub_27:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3350 - 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: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3344 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3330 - Accuracy: 0.6875 - F1: 0.6537
sub_27:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3486 - Accuracy: 0.4375 - F1: 0.4353
sub_27:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_27:Test (Best Model) - Loss: 0.3837 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.3892 - Accuracy: 0.4375 - F1: 0.3043
sub_27:Test (Best Model) - Loss: 0.3453 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3345 - Accuracy: 0.6250 - F1: 0.6250
sub_28:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3626 - Accuracy: 0.5000 - F1: 0.5000
sub_28:Test (Best Model) - Loss: 0.3081 - Accuracy: 0.8125 - F1: 0.8118
sub_28:Test (Best Model) - Loss: 0.3758 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 0.3394 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 0.3465 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3461 - Accuracy: 0.5625 - F1: 0.4589
sub_28:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_28:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.5000 - F1: 0.4921
sub_28:Test (Best Model) - Loss: 0.3603 - Accuracy: 0.5625 - F1: 0.5152
sub_28:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.5000 - F1: 0.3333
sub_28:Test (Best Model) - Loss: 0.3400 - Accuracy: 0.3750 - F1: 0.2727
sub_28:Test (Best Model) - Loss: 0.3462 - Accuracy: 0.5625 - F1: 0.5152
sub_29:Test (Best Model) - Loss: 0.3582 - Accuracy: 0.5000 - F1: 0.4667
sub_29:Test (Best Model) - Loss: 0.3370 - Accuracy: 0.6250 - F1: 0.6190
sub_29:Test (Best Model) - Loss: 0.3458 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3382 - Accuracy: 0.6250 - F1: 0.6000
sub_29:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3197 - Accuracy: 0.7500 - F1: 0.7091
sub_29:Test (Best Model) - Loss: 0.3214 - Accuracy: 0.6250 - F1: 0.6250
sub_29:Test (Best Model) - Loss: 0.3456 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3455 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3370 - Accuracy: 0.5000 - F1: 0.4667
sub_29:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.2933 - Accuracy: 0.6875 - F1: 0.6135
sub_29:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3350 - Accuracy: 0.5625 - F1: 0.3600
sub_29:Test (Best Model) - Loss: 0.3352 - Accuracy: 0.5625 - F1: 0.3600

=== Summary Results ===

acc:   56.91 ± 4.33
F1:    44.80 ± 6.93
acc-in:74.54 ± 5.92
F1-in: 61.88 ± 10.06
