lr: 0.001
sub_13:Test (Best Model) - Loss: 0.2769 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.4374 - Accuracy: 0.8788 - F1: 0.8778
sub_2:Test (Best Model) - Loss: 0.3575 - Accuracy: 0.9394 - F1: 0.9380
sub_20:Test (Best Model) - Loss: 0.2788 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.2996 - Accuracy: 0.9697 - F1: 0.9692
sub_22:Test (Best Model) - Loss: 0.3048 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.3863 - Accuracy: 0.8750 - F1: 0.8667
sub_14:Test (Best Model) - Loss: 0.8363 - Accuracy: 0.4375 - F1: 0.3043
sub_16:Test (Best Model) - Loss: 0.2983 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.2607 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.3331 - Accuracy: 0.9091 - F1: 0.9060
sub_21:Test (Best Model) - Loss: 0.4536 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.3780 - Accuracy: 0.9062 - F1: 0.9015
sub_26:Test (Best Model) - Loss: 0.3068 - Accuracy: 0.9697 - F1: 0.9692
sub_1:Test (Best Model) - Loss: 0.2516 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.2491 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3260 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.2421 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.3331 - Accuracy: 0.9091 - F1: 0.9060
sub_9:Test (Best Model) - Loss: 0.2586 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.2471 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.2933 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5323 - Accuracy: 0.7188 - F1: 0.7185
sub_11:Test (Best Model) - Loss: 0.4135 - Accuracy: 0.8485 - F1: 0.8462
sub_29:Test (Best Model) - Loss: 0.3503 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.3047 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.1604 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.2614 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.2751 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.8868 - Accuracy: 0.4688 - F1: 0.3637
sub_3:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 0.3208 - Accuracy: 0.9394 - F1: 0.9380
sub_21:Test (Best Model) - Loss: 0.4899 - Accuracy: 0.7188 - F1: 0.6946
sub_19:Test (Best Model) - Loss: 0.2044 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.3154 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.2648 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.2836 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.2885 - Accuracy: 0.9394 - F1: 0.9380
sub_1:Test (Best Model) - Loss: 0.2046 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.3158 - Accuracy: 0.9394 - F1: 0.9380
sub_25:Test (Best Model) - Loss: 0.3507 - Accuracy: 0.9091 - F1: 0.9077
sub_16:Test (Best Model) - Loss: 0.2480 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.3154 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.2995 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.3189 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.2377 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.2176 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.9062 - F1: 0.9015
sub_24:Test (Best Model) - Loss: 0.2528 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.3066 - Accuracy: 0.9688 - F1: 0.9680
sub_23:Test (Best Model) - Loss: 0.1958 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.3641 - Accuracy: 0.8788 - F1: 0.8778
sub_18:Test (Best Model) - Loss: 0.2317 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.3803 - Accuracy: 0.9091 - F1: 0.9077
sub_29:Test (Best Model) - Loss: 0.3283 - Accuracy: 0.9375 - F1: 0.9352
sub_21:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.7812 - F1: 0.7703
sub_22:Test (Best Model) - Loss: 0.3172 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.2733 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.3764 - Accuracy: 0.8750 - F1: 0.8667
sub_14:Test (Best Model) - Loss: 0.9340 - Accuracy: 0.4375 - F1: 0.3043
sub_19:Test (Best Model) - Loss: 0.3215 - Accuracy: 0.9688 - F1: 0.9685
sub_4:Test (Best Model) - Loss: 0.2665 - Accuracy: 0.9394 - F1: 0.9380
sub_6:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.7188 - F1: 0.7185
sub_17:Test (Best Model) - Loss: 0.3376 - Accuracy: 0.9091 - F1: 0.9060
sub_15:Test (Best Model) - Loss: 0.2328 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.2317 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.2756 - Accuracy: 0.9697 - F1: 0.9692
sub_13:Test (Best Model) - Loss: 0.2086 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.2315 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.2207 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.2859 - Accuracy: 0.9688 - F1: 0.9680
sub_16:Test (Best Model) - Loss: 0.2178 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.3376 - Accuracy: 0.9091 - F1: 0.9060
sub_9:Test (Best Model) - Loss: 0.2127 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.3077 - Accuracy: 0.8788 - F1: 0.8778
sub_12:Test (Best Model) - Loss: 0.2950 - Accuracy: 0.9688 - F1: 0.9685
sub_22:Test (Best Model) - Loss: 0.2585 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.1998 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.2729 - Accuracy: 0.9688 - F1: 0.9680
sub_23:Test (Best Model) - Loss: 0.2161 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.4046 - Accuracy: 0.8788 - F1: 0.8759
sub_2:Test (Best Model) - Loss: 0.3346 - Accuracy: 0.9697 - F1: 0.9692
sub_18:Test (Best Model) - Loss: 0.2375 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.2782 - Accuracy: 0.9394 - F1: 0.9380
sub_15:Test (Best Model) - Loss: 0.2808 - Accuracy: 0.9375 - F1: 0.9352
sub_28:Test (Best Model) - Loss: 0.2354 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.4363 - Accuracy: 0.8438 - F1: 0.8303
sub_7:Test (Best Model) - Loss: 0.2133 - Accuracy: 0.9688 - F1: 0.9680
sub_29:Test (Best Model) - Loss: 0.3299 - Accuracy: 0.9062 - F1: 0.9015
sub_6:Test (Best Model) - Loss: 0.5981 - Accuracy: 0.7188 - F1: 0.7185
sub_1:Test (Best Model) - Loss: 0.1914 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.2927 - Accuracy: 0.9375 - F1: 0.9373
sub_26:Test (Best Model) - Loss: 0.2618 - Accuracy: 0.9697 - F1: 0.9692
sub_5:Test (Best Model) - Loss: 0.3228 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.8652 - Accuracy: 0.4375 - F1: 0.3043
sub_9:Test (Best Model) - Loss: 0.2017 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.1696 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.2586 - Accuracy: 0.9375 - F1: 0.9365
sub_22:Test (Best Model) - Loss: 0.3948 - Accuracy: 0.8750 - F1: 0.8667
sub_25:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.8788 - F1: 0.8778
sub_16:Test (Best Model) - Loss: 0.2802 - Accuracy: 0.9375 - F1: 0.9352
sub_10:Test (Best Model) - Loss: 0.1652 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.2749 - Accuracy: 0.9394 - F1: 0.9380
sub_3:Test (Best Model) - Loss: 0.3679 - Accuracy: 0.8750 - F1: 0.8667
sub_18:Test (Best Model) - Loss: 0.2295 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.2998 - Accuracy: 0.9091 - F1: 0.9060
sub_8:Test (Best Model) - Loss: 0.2779 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.2284 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.2072 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.3730 - Accuracy: 0.8788 - F1: 0.8778
sub_1:Test (Best Model) - Loss: 0.2617 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.5744 - Accuracy: 0.6562 - F1: 0.6559
sub_13:Test (Best Model) - Loss: 0.2759 - Accuracy: 0.9375 - F1: 0.9365
sub_19:Test (Best Model) - Loss: 0.2842 - Accuracy: 0.9688 - F1: 0.9685
sub_2:Test (Best Model) - Loss: 0.2950 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.3392 - Accuracy: 0.9062 - F1: 0.9015
sub_20:Test (Best Model) - Loss: 0.2721 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.2998 - Accuracy: 0.9091 - F1: 0.9060
sub_15:Test (Best Model) - Loss: 0.2646 - Accuracy: 0.9062 - F1: 0.9015
sub_28:Test (Best Model) - Loss: 0.2028 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.2529 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.3494 - Accuracy: 0.8750 - F1: 0.8667
sub_21:Test (Best Model) - Loss: 0.4572 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.2588 - Accuracy: 0.9394 - F1: 0.9380
sub_22:Test (Best Model) - Loss: 0.3117 - Accuracy: 0.9091 - F1: 0.9077
sub_5:Test (Best Model) - Loss: 0.3657 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.2390 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.9720 - Accuracy: 0.4375 - F1: 0.3043
sub_25:Test (Best Model) - Loss: 0.3682 - Accuracy: 0.8485 - F1: 0.8462
sub_12:Test (Best Model) - Loss: 0.3026 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.2342 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.6193 - Accuracy: 0.6562 - F1: 0.6532
sub_3:Test (Best Model) - Loss: 0.2698 - Accuracy: 0.9697 - F1: 0.9692
sub_8:Test (Best Model) - Loss: 0.3432 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.3321 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.2720 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.2330 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.2796 - Accuracy: 0.9697 - F1: 0.9692
sub_2:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9375 - F1: 0.9373
sub_23:Test (Best Model) - Loss: 0.3016 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.3821 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 0.2841 - Accuracy: 0.9688 - F1: 0.9685
sub_16:Test (Best Model) - Loss: 0.2210 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.2437 - Accuracy: 0.9688 - F1: 0.9685
sub_20:Test (Best Model) - Loss: 0.2467 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.2951 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.3252 - Accuracy: 0.9375 - F1: 0.9352
sub_27:Test (Best Model) - Loss: 0.3321 - Accuracy: 0.9091 - F1: 0.9060
sub_5:Test (Best Model) - Loss: 0.3129 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.2282 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.2588 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.2223 - Accuracy: 0.9697 - F1: 0.9692
sub_10:Test (Best Model) - Loss: 0.3711 - Accuracy: 0.8438 - F1: 0.8303
sub_3:Test (Best Model) - Loss: 0.3129 - Accuracy: 0.9394 - F1: 0.9380
sub_26:Test (Best Model) - Loss: 0.2160 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.2578 - Accuracy: 0.9688 - F1: 0.9680
sub_22:Test (Best Model) - Loss: 0.3016 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.2915 - Accuracy: 0.9394 - F1: 0.9380
sub_12:Test (Best Model) - Loss: 0.3824 - Accuracy: 0.8788 - F1: 0.8759
sub_25:Test (Best Model) - Loss: 0.3881 - Accuracy: 0.8788 - F1: 0.8778
sub_11:Test (Best Model) - Loss: 0.3240 - Accuracy: 0.9394 - F1: 0.9380
sub_2:Test (Best Model) - Loss: 0.2803 - Accuracy: 0.9375 - F1: 0.9373
sub_8:Test (Best Model) - Loss: 0.3532 - Accuracy: 0.8750 - F1: 0.8745
sub_21:Test (Best Model) - Loss: 0.2548 - Accuracy: 0.9375 - F1: 0.9352
sub_20:Test (Best Model) - Loss: 0.2297 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.2535 - Accuracy: 0.9688 - F1: 0.9680
sub_16:Test (Best Model) - Loss: 0.2870 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.2335 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.2885 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.2150 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.3522 - Accuracy: 0.9091 - F1: 0.9077
sub_23:Test (Best Model) - Loss: 0.4219 - Accuracy: 0.8125 - F1: 0.8118
sub_17:Test (Best Model) - Loss: 0.4765 - Accuracy: 0.7576 - F1: 0.7556
sub_28:Test (Best Model) - Loss: 0.2938 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.3630 - Accuracy: 0.9062 - F1: 0.9015
sub_6:Test (Best Model) - Loss: 0.3535 - Accuracy: 0.8485 - F1: 0.8390
sub_10:Test (Best Model) - Loss: 0.3691 - Accuracy: 0.8750 - F1: 0.8667
sub_1:Test (Best Model) - Loss: 0.2583 - Accuracy: 0.9697 - F1: 0.9692
sub_3:Test (Best Model) - Loss: 0.3277 - Accuracy: 0.9394 - F1: 0.9380
sub_14:Test (Best Model) - Loss: 0.2143 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.2094 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.9394 - F1: 0.9380
sub_4:Test (Best Model) - Loss: 0.1307 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.2762 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.4765 - Accuracy: 0.7576 - F1: 0.7556
sub_11:Test (Best Model) - Loss: 0.3110 - Accuracy: 0.9394 - F1: 0.9380
sub_12:Test (Best Model) - Loss: 0.4214 - Accuracy: 0.8788 - F1: 0.8731
sub_18:Test (Best Model) - Loss: 0.1580 - Accuracy: 0.9688 - F1: 0.9680
sub_16:Test (Best Model) - Loss: 0.4105 - Accuracy: 0.8750 - F1: 0.8745
sub_25:Test (Best Model) - Loss: 0.3700 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.2732 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2358 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4067 - Accuracy: 0.8485 - F1: 0.8479
sub_9:Test (Best Model) - Loss: 0.2889 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.2192 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.1860 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2603 - Accuracy: 0.9375 - F1: 0.9373
sub_28:Test (Best Model) - Loss: 0.4021 - Accuracy: 0.8438 - F1: 0.8303
sub_6:Test (Best Model) - Loss: 0.3716 - Accuracy: 0.9091 - F1: 0.9060
sub_4:Test (Best Model) - Loss: 0.2623 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.2331 - Accuracy: 0.9688 - F1: 0.9680
sub_23:Test (Best Model) - Loss: 0.4486 - Accuracy: 0.8438 - F1: 0.8436
sub_14:Test (Best Model) - Loss: 0.2749 - Accuracy: 0.9688 - F1: 0.9680
sub_3:Test (Best Model) - Loss: 0.3218 - Accuracy: 0.9394 - F1: 0.9380
sub_7:Test (Best Model) - Loss: 0.3496 - Accuracy: 0.9062 - F1: 0.9015
sub_17:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.7273 - F1: 0.7232
sub_26:Test (Best Model) - Loss: 0.2496 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.2271 - Accuracy: 0.9394 - F1: 0.9380
sub_10:Test (Best Model) - Loss: 0.3744 - Accuracy: 0.8438 - F1: 0.8303
sub_18:Test (Best Model) - Loss: 0.2664 - Accuracy: 0.9688 - F1: 0.9680
sub_15:Test (Best Model) - Loss: 0.2970 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.3285 - Accuracy: 0.9062 - F1: 0.9054
sub_25:Test (Best Model) - Loss: 0.4387 - Accuracy: 0.8125 - F1: 0.8118
sub_22:Test (Best Model) - Loss: 0.3110 - Accuracy: 0.9091 - F1: 0.9060
sub_20:Test (Best Model) - Loss: 0.3303 - Accuracy: 0.9062 - F1: 0.9015
sub_12:Test (Best Model) - Loss: 0.4082 - Accuracy: 0.8788 - F1: 0.8731
sub_16:Test (Best Model) - Loss: 0.2796 - Accuracy: 0.9688 - F1: 0.9685
sub_11:Test (Best Model) - Loss: 0.3409 - Accuracy: 0.9394 - F1: 0.9380
sub_13:Test (Best Model) - Loss: 0.3108 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.2509 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.7273 - F1: 0.7232
sub_9:Test (Best Model) - Loss: 0.3031 - Accuracy: 0.9375 - F1: 0.9352
sub_19:Test (Best Model) - Loss: 0.2378 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.3309 - Accuracy: 0.9375 - F1: 0.9365
sub_21:Test (Best Model) - Loss: 0.3055 - Accuracy: 1.0000 - F1: 1.0000
sub_4:Test (Best Model) - Loss: 0.2161 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.2592 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.2873 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.2151 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.2386 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.2401 - Accuracy: 0.9394 - F1: 0.9380
sub_10:Test (Best Model) - Loss: 0.4168 - Accuracy: 0.8438 - F1: 0.8303
sub_28:Test (Best Model) - Loss: 0.3281 - Accuracy: 0.9062 - F1: 0.9015
sub_5:Test (Best Model) - Loss: 0.1906 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.4346 - Accuracy: 0.7500 - F1: 0.7460
sub_8:Test (Best Model) - Loss: 0.3764 - Accuracy: 0.9375 - F1: 0.9365
sub_26:Test (Best Model) - Loss: 0.2043 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3764 - Accuracy: 0.8750 - F1: 0.8704
sub_22:Test (Best Model) - Loss: 0.4228 - Accuracy: 0.8485 - F1: 0.8390
sub_15:Test (Best Model) - Loss: 0.2789 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.4278 - Accuracy: 0.8788 - F1: 0.8731
sub_11:Test (Best Model) - Loss: 0.3339 - Accuracy: 0.8788 - F1: 0.8731
sub_20:Test (Best Model) - Loss: 0.2171 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.5758 - F1: 0.5658
sub_29:Test (Best Model) - Loss: 0.2734 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.2115 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.4782 - Accuracy: 0.8125 - F1: 0.8118
sub_16:Test (Best Model) - Loss: 0.2622 - Accuracy: 0.9688 - F1: 0.9680
sub_9:Test (Best Model) - Loss: 0.3633 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.2701 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.3121 - Accuracy: 0.9062 - F1: 0.9062
sub_21:Test (Best Model) - Loss: 0.2819 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.2273 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.2125 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.2910 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.3682 - Accuracy: 0.8485 - F1: 0.8390
sub_3:Test (Best Model) - Loss: 0.3401 - Accuracy: 0.9091 - F1: 0.9077
sub_10:Test (Best Model) - Loss: 0.3845 - Accuracy: 0.8750 - F1: 0.8667
sub_13:Test (Best Model) - Loss: 0.1574 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2252 - Accuracy: 0.9688 - F1: 0.9685
sub_18:Test (Best Model) - Loss: 0.2505 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.2766 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.2574 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.2227 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.5758 - F1: 0.5658
sub_22:Test (Best Model) - Loss: 0.2951 - Accuracy: 0.9688 - F1: 0.9685
sub_20:Test (Best Model) - Loss: 0.3443 - Accuracy: 0.9394 - F1: 0.9380
sub_11:Test (Best Model) - Loss: 0.3476 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.2044 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.4555 - Accuracy: 0.8485 - F1: 0.8390
sub_17:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.6970 - F1: 0.6944
sub_21:Test (Best Model) - Loss: 0.2511 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.2572 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.1606 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.3091 - Accuracy: 0.9062 - F1: 0.9015
sub_4:Test (Best Model) - Loss: 0.2307 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.2330 - Accuracy: 1.0000 - F1: 1.0000
sub_26:Test (Best Model) - Loss: 0.3217 - Accuracy: 0.9375 - F1: 0.9352
sub_2:Test (Best Model) - Loss: 0.4338 - Accuracy: 0.8182 - F1: 0.8036
sub_18:Test (Best Model) - Loss: 0.2322 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.3618 - Accuracy: 0.9375 - F1: 0.9373
sub_13:Test (Best Model) - Loss: 0.3012 - Accuracy: 0.9697 - F1: 0.9692
sub_9:Test (Best Model) - Loss: 0.2450 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.5561 - Accuracy: 0.7500 - F1: 0.7500
sub_14:Test (Best Model) - Loss: 0.5030 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 0.2809 - Accuracy: 0.9688 - F1: 0.9680
sub_3:Test (Best Model) - Loss: 0.2385 - Accuracy: 0.9697 - F1: 0.9692
sub_1:Test (Best Model) - Loss: 0.2510 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.1894 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.3218 - Accuracy: 0.9091 - F1: 0.9060
sub_5:Test (Best Model) - Loss: 0.1997 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3381 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.4389 - Accuracy: 0.8485 - F1: 0.8390
sub_20:Test (Best Model) - Loss: 0.3508 - Accuracy: 0.9091 - F1: 0.9060
sub_22:Test (Best Model) - Loss: 0.2726 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.4310 - Accuracy: 0.8438 - F1: 0.8424
sub_27:Test (Best Model) - Loss: 0.5491 - Accuracy: 0.6970 - F1: 0.6944
sub_11:Test (Best Model) - Loss: 0.3262 - Accuracy: 0.9091 - F1: 0.9060
sub_17:Test (Best Model) - Loss: 0.3858 - Accuracy: 0.8788 - F1: 0.8787
sub_18:Test (Best Model) - Loss: 0.2687 - Accuracy: 1.0000 - F1: 1.0000
sub_19:Test (Best Model) - Loss: 0.1959 - Accuracy: 1.0000 - F1: 1.0000
sub_25:Test (Best Model) - Loss: 0.3196 - Accuracy: 0.9375 - F1: 0.9373
sub_4:Test (Best Model) - Loss: 0.2277 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.3842 - Accuracy: 0.8750 - F1: 0.8667
sub_29:Test (Best Model) - Loss: 0.2052 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3321 - Accuracy: 0.9688 - F1: 0.9680
sub_13:Test (Best Model) - Loss: 0.4949 - Accuracy: 0.8125 - F1: 0.8057
sub_23:Test (Best Model) - Loss: 0.4026 - Accuracy: 0.8788 - F1: 0.8731
sub_26:Test (Best Model) - Loss: 0.3157 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.2715 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.1675 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.2297 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.2767 - Accuracy: 0.9697 - F1: 0.9692
sub_1:Test (Best Model) - Loss: 0.2367 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2554 - Accuracy: 0.9394 - F1: 0.9380
sub_24:Test (Best Model) - Loss: 0.2967 - Accuracy: 0.9688 - F1: 0.9680
sub_20:Test (Best Model) - Loss: 0.3391 - Accuracy: 0.9091 - F1: 0.9060
sub_3:Test (Best Model) - Loss: 0.2728 - Accuracy: 0.9697 - F1: 0.9692
sub_5:Test (Best Model) - Loss: 0.2034 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3269 - Accuracy: 0.9688 - F1: 0.9680
sub_18:Test (Best Model) - Loss: 0.2497 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.2358 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.3858 - Accuracy: 0.8788 - F1: 0.8787
sub_25:Test (Best Model) - Loss: 0.3565 - Accuracy: 0.8438 - F1: 0.8303
sub_21:Test (Best Model) - Loss: 0.5279 - Accuracy: 0.7500 - F1: 0.7490
sub_14:Test (Best Model) - Loss: 0.5891 - Accuracy: 0.7812 - F1: 0.7519
sub_16:Test (Best Model) - Loss: 0.4061 - Accuracy: 0.8438 - F1: 0.8303
sub_22:Test (Best Model) - Loss: 0.2211 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.4135 - Accuracy: 0.8750 - F1: 0.8704
sub_4:Test (Best Model) - Loss: 0.2487 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4592 - Accuracy: 0.8125 - F1: 0.8057
sub_12:Test (Best Model) - Loss: 0.3166 - Accuracy: 0.9375 - F1: 0.9352
sub_23:Test (Best Model) - Loss: 0.3932 - Accuracy: 0.8788 - F1: 0.8759
sub_11:Test (Best Model) - Loss: 0.3082 - Accuracy: 0.9091 - F1: 0.9060
sub_8:Test (Best Model) - Loss: 0.2743 - Accuracy: 0.9688 - F1: 0.9680
sub_6:Test (Best Model) - Loss: 0.4399 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.2993 - Accuracy: 0.9062 - F1: 0.9015
sub_10:Test (Best Model) - Loss: 0.2689 - Accuracy: 0.9697 - F1: 0.9692
sub_19:Test (Best Model) - Loss: 0.3893 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.2273 - Accuracy: 1.0000 - F1: 1.0000
sub_28:Test (Best Model) - Loss: 0.4411 - Accuracy: 0.8750 - F1: 0.8667
sub_3:Test (Best Model) - Loss: 0.2952 - Accuracy: 0.9394 - F1: 0.9389
sub_1:Test (Best Model) - Loss: 0.2400 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.3175 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.2778 - Accuracy: 0.9375 - F1: 0.9365
sub_2:Test (Best Model) - Loss: 0.3323 - Accuracy: 0.9091 - F1: 0.9060
sub_16:Test (Best Model) - Loss: 0.3224 - Accuracy: 0.9062 - F1: 0.9015
sub_25:Test (Best Model) - Loss: 0.3207 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.2559 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2339 - Accuracy: 1.0000 - F1: 1.0000
sub_27:Test (Best Model) - Loss: 0.4135 - Accuracy: 0.8750 - F1: 0.8704
sub_21:Test (Best Model) - Loss: 0.4014 - Accuracy: 0.8750 - F1: 0.8750
sub_24:Test (Best Model) - Loss: 0.2225 - Accuracy: 0.9375 - F1: 0.9365
sub_4:Test (Best Model) - Loss: 0.2648 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.5473 - Accuracy: 0.7188 - F1: 0.7185
sub_20:Test (Best Model) - Loss: 0.3394 - Accuracy: 0.8788 - F1: 0.8731
sub_23:Test (Best Model) - Loss: 0.3562 - Accuracy: 0.9091 - F1: 0.9060
sub_18:Test (Best Model) - Loss: 0.1702 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.4610 - Accuracy: 0.7812 - F1: 0.7519
sub_5:Test (Best Model) - Loss: 0.2247 - Accuracy: 0.9688 - F1: 0.9685
sub_12:Test (Best Model) - Loss: 0.2795 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3390 - Accuracy: 0.9062 - F1: 0.9015
sub_19:Test (Best Model) - Loss: 0.3900 - Accuracy: 0.8750 - F1: 0.8667
sub_10:Test (Best Model) - Loss: 0.3162 - Accuracy: 0.9091 - F1: 0.9060
sub_6:Test (Best Model) - Loss: 0.4342 - Accuracy: 0.8182 - F1: 0.8139
sub_8:Test (Best Model) - Loss: 0.2513 - Accuracy: 0.9688 - F1: 0.9680
sub_28:Test (Best Model) - Loss: 0.5584 - Accuracy: 0.8125 - F1: 0.8118
sub_11:Test (Best Model) - Loss: 0.3100 - Accuracy: 0.9091 - F1: 0.9060
sub_16:Test (Best Model) - Loss: 0.3198 - Accuracy: 0.9375 - F1: 0.9352
sub_3:Test (Best Model) - Loss: 0.2678 - Accuracy: 0.9697 - F1: 0.9692
sub_9:Test (Best Model) - Loss: 0.2387 - Accuracy: 1.0000 - F1: 1.0000
sub_22:Test (Best Model) - Loss: 0.2543 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.8125 - F1: 0.8057
sub_7:Test (Best Model) - Loss: 0.2544 - Accuracy: 0.9688 - F1: 0.9680
sub_2:Test (Best Model) - Loss: 0.3080 - Accuracy: 0.9697 - F1: 0.9692
sub_20:Test (Best Model) - Loss: 0.3718 - Accuracy: 0.8788 - F1: 0.8731
sub_13:Test (Best Model) - Loss: 0.4837 - Accuracy: 0.7812 - F1: 0.7793
sub_24:Test (Best Model) - Loss: 0.2741 - Accuracy: 0.9375 - F1: 0.9365
sub_15:Test (Best Model) - Loss: 0.2809 - Accuracy: 0.9062 - F1: 0.9054
sub_1:Test (Best Model) - Loss: 0.1416 - Accuracy: 1.0000 - F1: 1.0000
sub_18:Test (Best Model) - Loss: 0.2288 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.2301 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.2847 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.2921 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.3097 - Accuracy: 0.9062 - F1: 0.9015
sub_23:Test (Best Model) - Loss: 0.3743 - Accuracy: 0.9394 - F1: 0.9380
sub_28:Test (Best Model) - Loss: 0.4531 - Accuracy: 0.8125 - F1: 0.8118
sub_19:Test (Best Model) - Loss: 0.3807 - Accuracy: 0.8750 - F1: 0.8667
sub_10:Test (Best Model) - Loss: 0.3002 - Accuracy: 0.9091 - F1: 0.9060
sub_25:Test (Best Model) - Loss: 0.1761 - Accuracy: 0.9375 - F1: 0.9352
sub_9:Test (Best Model) - Loss: 0.2473 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.3990 - Accuracy: 0.8125 - F1: 0.8057
sub_8:Test (Best Model) - Loss: 0.2572 - Accuracy: 0.9688 - F1: 0.9680
sub_14:Test (Best Model) - Loss: 0.5098 - Accuracy: 0.7812 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.2832 - Accuracy: 0.9394 - F1: 0.9393
sub_16:Test (Best Model) - Loss: 0.4017 - Accuracy: 0.8438 - F1: 0.8303
sub_2:Test (Best Model) - Loss: 0.3021 - Accuracy: 0.9394 - F1: 0.9380
sub_11:Test (Best Model) - Loss: 0.3096 - Accuracy: 0.9394 - F1: 0.9380
sub_13:Test (Best Model) - Loss: 0.4587 - Accuracy: 0.8125 - F1: 0.8057
sub_18:Test (Best Model) - Loss: 0.1893 - Accuracy: 1.0000 - F1: 1.0000
sub_15:Test (Best Model) - Loss: 0.3020 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.2173 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.1677 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.2109 - Accuracy: 0.9688 - F1: 0.9680
sub_21:Test (Best Model) - Loss: 0.3015 - Accuracy: 0.9688 - F1: 0.9685
sub_23:Test (Best Model) - Loss: 0.4151 - Accuracy: 0.8788 - F1: 0.8731
sub_24:Test (Best Model) - Loss: 0.2053 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.8750 - F1: 0.8667
sub_28:Test (Best Model) - Loss: 0.5244 - Accuracy: 0.7188 - F1: 0.7185
sub_12:Test (Best Model) - Loss: 0.2467 - Accuracy: 0.9375 - F1: 0.9352
sub_6:Test (Best Model) - Loss: 0.3720 - Accuracy: 0.9091 - F1: 0.9088
sub_25:Test (Best Model) - Loss: 0.2695 - Accuracy: 0.9375 - F1: 0.9352
sub_14:Test (Best Model) - Loss: 0.5200 - Accuracy: 0.7812 - F1: 0.7519
sub_27:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.9062 - F1: 0.9015
sub_6:Test (Best Model) - Loss: 0.3547 - Accuracy: 0.9394 - F1: 0.9380
sub_7:Test (Best Model) - Loss: 0.2810 - Accuracy: 0.9688 - F1: 0.9680
sub_24:Test (Best Model) - Loss: 0.2601 - Accuracy: 0.9688 - F1: 0.9680
sub_5:Test (Best Model) - Loss: 0.2665 - Accuracy: 0.9688 - F1: 0.9685
sub_15:Test (Best Model) - Loss: 0.2121 - Accuracy: 1.0000 - F1: 1.0000
sub_17:Test (Best Model) - Loss: 0.3616 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 0.3829 - Accuracy: 0.8438 - F1: 0.8303
sub_28:Test (Best Model) - Loss: 0.4545 - Accuracy: 0.8125 - F1: 0.8125
sub_25:Test (Best Model) - Loss: 0.3076 - Accuracy: 0.9062 - F1: 0.9015
sub_6:Test (Best Model) - Loss: 0.3410 - Accuracy: 0.9394 - F1: 0.9393
sub_27:Test (Best Model) - Loss: 0.3616 - Accuracy: 0.8750 - F1: 0.8667
sub_5:Test (Best Model) - Loss: 0.2765 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.3762 - Accuracy: 0.9062 - F1: 0.9015
sub_15:Test (Best Model) - Loss: 0.3274 - Accuracy: 0.9062 - F1: 0.9054
sub_28:Test (Best Model) - Loss: 0.4920 - Accuracy: 0.7812 - F1: 0.7810
sub_27:Test (Best Model) - Loss: 0.3762 - Accuracy: 0.9062 - F1: 0.9015
sub_5:Test (Best Model) - Loss: 0.2569 - Accuracy: 0.9688 - F1: 0.9685

=== Summary Results ===

acc: 92.22 ± 5.56
F1: 91.82 ± 6.24
acc-in: 96.01 ± 3.01
F1-in: 95.80 ± 3.22
