lr: 0.001
sub_1:Test (Best Model) - Loss: 4.8805 - Accuracy: 0.2059 - F1: 0.1951
sub_1:Test (Best Model) - Loss: 4.5399 - Accuracy: 0.3088 - F1: 0.3016
sub_1:Test (Best Model) - Loss: 5.3160 - Accuracy: 0.2353 - F1: 0.2300
sub_1:Test (Best Model) - Loss: 4.6014 - Accuracy: 0.3235 - F1: 0.3158
sub_1:Test (Best Model) - Loss: 4.7616 - Accuracy: 0.3382 - F1: 0.3296
sub_1:Test (Best Model) - Loss: 4.8160 - Accuracy: 0.3188 - F1: 0.2895
sub_1:Test (Best Model) - Loss: 4.0018 - Accuracy: 0.2754 - F1: 0.2408
sub_1:Test (Best Model) - Loss: 4.3598 - Accuracy: 0.3333 - F1: 0.2974
sub_1:Test (Best Model) - Loss: 4.7050 - Accuracy: 0.3043 - F1: 0.2502
sub_1:Test (Best Model) - Loss: 4.3759 - Accuracy: 0.2899 - F1: 0.2592
sub_1:Test (Best Model) - Loss: 4.7079 - Accuracy: 0.2353 - F1: 0.2300
sub_1:Test (Best Model) - Loss: 3.4299 - Accuracy: 0.3824 - F1: 0.3826
sub_1:Test (Best Model) - Loss: 3.0603 - Accuracy: 0.3088 - F1: 0.3133
sub_1:Test (Best Model) - Loss: 4.7643 - Accuracy: 0.2794 - F1: 0.2333
sub_1:Test (Best Model) - Loss: 3.9971 - Accuracy: 0.3235 - F1: 0.3202
sub_2:Test (Best Model) - Loss: 5.3606 - Accuracy: 0.3043 - F1: 0.2782
sub_2:Test (Best Model) - Loss: 4.1868 - Accuracy: 0.3478 - F1: 0.3021
sub_2:Test (Best Model) - Loss: 4.3421 - Accuracy: 0.3043 - F1: 0.2822
sub_2:Test (Best Model) - Loss: 4.0019 - Accuracy: 0.2464 - F1: 0.2606
sub_2:Test (Best Model) - Loss: 4.5696 - Accuracy: 0.2464 - F1: 0.2233
sub_2:Test (Best Model) - Loss: 4.4382 - Accuracy: 0.2794 - F1: 0.2064
sub_2:Test (Best Model) - Loss: 3.9600 - Accuracy: 0.2206 - F1: 0.1966
sub_2:Test (Best Model) - Loss: 3.6413 - Accuracy: 0.2794 - F1: 0.2817
sub_2:Test (Best Model) - Loss: 3.2816 - Accuracy: 0.2794 - F1: 0.2771
sub_2:Test (Best Model) - Loss: 3.3340 - Accuracy: 0.3088 - F1: 0.3066
sub_2:Test (Best Model) - Loss: 4.5218 - Accuracy: 0.2899 - F1: 0.2776
sub_2:Test (Best Model) - Loss: 4.0990 - Accuracy: 0.2899 - F1: 0.2764
sub_2:Test (Best Model) - Loss: 3.0583 - Accuracy: 0.3478 - F1: 0.2990
sub_2:Test (Best Model) - Loss: 4.6689 - Accuracy: 0.2754 - F1: 0.2271
sub_2:Test (Best Model) - Loss: 4.6896 - Accuracy: 0.2754 - F1: 0.2266
sub_3:Test (Best Model) - Loss: 5.5688 - Accuracy: 0.2500 - F1: 0.2463
sub_3:Test (Best Model) - Loss: 4.4542 - Accuracy: 0.2206 - F1: 0.2152
sub_3:Test (Best Model) - Loss: 5.0558 - Accuracy: 0.2353 - F1: 0.2330
sub_3:Test (Best Model) - Loss: 5.0408 - Accuracy: 0.1912 - F1: 0.1875
sub_3:Test (Best Model) - Loss: 5.4438 - Accuracy: 0.2353 - F1: 0.2341
sub_3:Test (Best Model) - Loss: 4.1875 - Accuracy: 0.2609 - F1: 0.2282
sub_3:Test (Best Model) - Loss: 5.0247 - Accuracy: 0.1884 - F1: 0.1794
sub_3:Test (Best Model) - Loss: 4.1785 - Accuracy: 0.2174 - F1: 0.2120
sub_3:Test (Best Model) - Loss: 4.3605 - Accuracy: 0.2029 - F1: 0.1888
sub_3:Test (Best Model) - Loss: 3.9128 - Accuracy: 0.2464 - F1: 0.2446
sub_3:Test (Best Model) - Loss: 4.2417 - Accuracy: 0.2319 - F1: 0.2278
sub_3:Test (Best Model) - Loss: 4.8624 - Accuracy: 0.2029 - F1: 0.1978
sub_3:Test (Best Model) - Loss: 5.1742 - Accuracy: 0.2754 - F1: 0.2597
sub_3:Test (Best Model) - Loss: 6.2125 - Accuracy: 0.2319 - F1: 0.2066
sub_3:Test (Best Model) - Loss: 5.3556 - Accuracy: 0.2754 - F1: 0.2714
sub_4:Test (Best Model) - Loss: 4.2087 - Accuracy: 0.3768 - F1: 0.3794
sub_4:Test (Best Model) - Loss: 4.6360 - Accuracy: 0.3188 - F1: 0.3029
sub_4:Test (Best Model) - Loss: 5.3102 - Accuracy: 0.3333 - F1: 0.3149
sub_4:Test (Best Model) - Loss: 3.3537 - Accuracy: 0.3333 - F1: 0.3218
sub_4:Test (Best Model) - Loss: 5.9631 - Accuracy: 0.3333 - F1: 0.3173
sub_4:Test (Best Model) - Loss: 4.6495 - Accuracy: 0.3478 - F1: 0.3296
sub_4:Test (Best Model) - Loss: 3.4892 - Accuracy: 0.2899 - F1: 0.2920
sub_4:Test (Best Model) - Loss: 3.1096 - Accuracy: 0.3043 - F1: 0.3005
sub_4:Test (Best Model) - Loss: 3.2563 - Accuracy: 0.3043 - F1: 0.2888
sub_4:Test (Best Model) - Loss: 3.3447 - Accuracy: 0.2609 - F1: 0.2616
sub_4:Test (Best Model) - Loss: 3.7370 - Accuracy: 0.3043 - F1: 0.2791
sub_4:Test (Best Model) - Loss: 3.2744 - Accuracy: 0.3188 - F1: 0.3081
sub_4:Test (Best Model) - Loss: 3.2081 - Accuracy: 0.3043 - F1: 0.3050
sub_4:Test (Best Model) - Loss: 3.3597 - Accuracy: 0.3043 - F1: 0.3007
sub_4:Test (Best Model) - Loss: 3.4005 - Accuracy: 0.3913 - F1: 0.3836
sub_5:Test (Best Model) - Loss: 7.9062 - Accuracy: 0.2353 - F1: 0.2159
sub_5:Test (Best Model) - Loss: 6.8015 - Accuracy: 0.1765 - F1: 0.1629
sub_5:Test (Best Model) - Loss: 8.0854 - Accuracy: 0.2353 - F1: 0.2213
sub_5:Test (Best Model) - Loss: 7.2751 - Accuracy: 0.3529 - F1: 0.3459
sub_5:Test (Best Model) - Loss: 5.7718 - Accuracy: 0.2500 - F1: 0.2384
sub_5:Test (Best Model) - Loss: 3.3072 - Accuracy: 0.2941 - F1: 0.2846
sub_5:Test (Best Model) - Loss: 2.7921 - Accuracy: 0.3971 - F1: 0.3888
sub_5:Test (Best Model) - Loss: 3.3325 - Accuracy: 0.3235 - F1: 0.3270
sub_5:Test (Best Model) - Loss: 2.4782 - Accuracy: 0.3971 - F1: 0.4060
sub_5:Test (Best Model) - Loss: 2.9965 - Accuracy: 0.2941 - F1: 0.3083
sub_5:Test (Best Model) - Loss: 3.5545 - Accuracy: 0.2647 - F1: 0.2651
sub_5:Test (Best Model) - Loss: 4.3438 - Accuracy: 0.2647 - F1: 0.2499
sub_5:Test (Best Model) - Loss: 3.8044 - Accuracy: 0.3235 - F1: 0.3067
sub_5:Test (Best Model) - Loss: 3.7022 - Accuracy: 0.2941 - F1: 0.2839
sub_5:Test (Best Model) - Loss: 2.7339 - Accuracy: 0.4412 - F1: 0.4353
sub_6:Test (Best Model) - Loss: 2.8793 - Accuracy: 0.3235 - F1: 0.3127
sub_6:Test (Best Model) - Loss: 2.9665 - Accuracy: 0.2353 - F1: 0.2250
sub_6:Test (Best Model) - Loss: 3.3868 - Accuracy: 0.3529 - F1: 0.3486
sub_6:Test (Best Model) - Loss: 2.7411 - Accuracy: 0.3088 - F1: 0.2897
sub_6:Test (Best Model) - Loss: 3.0302 - Accuracy: 0.3971 - F1: 0.3841
sub_6:Test (Best Model) - Loss: 6.8072 - Accuracy: 0.2609 - F1: 0.2162
sub_6:Test (Best Model) - Loss: 4.3143 - Accuracy: 0.3768 - F1: 0.3271
sub_6:Test (Best Model) - Loss: 3.8099 - Accuracy: 0.2899 - F1: 0.2379
sub_6:Test (Best Model) - Loss: 4.7312 - Accuracy: 0.2754 - F1: 0.2340
sub_6:Test (Best Model) - Loss: 5.3155 - Accuracy: 0.2609 - F1: 0.2107
sub_6:Test (Best Model) - Loss: 3.9381 - Accuracy: 0.2609 - F1: 0.2423
sub_6:Test (Best Model) - Loss: 4.6795 - Accuracy: 0.3043 - F1: 0.2693
sub_6:Test (Best Model) - Loss: 4.4947 - Accuracy: 0.2754 - F1: 0.2732
sub_6:Test (Best Model) - Loss: 3.6587 - Accuracy: 0.3043 - F1: 0.2785
sub_6:Test (Best Model) - Loss: 3.3676 - Accuracy: 0.3478 - F1: 0.3045
sub_7:Test (Best Model) - Loss: 4.0150 - Accuracy: 0.3529 - F1: 0.3277
sub_7:Test (Best Model) - Loss: 4.8086 - Accuracy: 0.3088 - F1: 0.3024
sub_7:Test (Best Model) - Loss: 5.0325 - Accuracy: 0.2500 - F1: 0.2325
sub_7:Test (Best Model) - Loss: 4.2472 - Accuracy: 0.3529 - F1: 0.3450
sub_7:Test (Best Model) - Loss: 4.8869 - Accuracy: 0.3382 - F1: 0.3196
sub_7:Test (Best Model) - Loss: 4.4510 - Accuracy: 0.2794 - F1: 0.2724
sub_7:Test (Best Model) - Loss: 4.0571 - Accuracy: 0.2794 - F1: 0.2820
sub_7:Test (Best Model) - Loss: 3.6231 - Accuracy: 0.3088 - F1: 0.3163
sub_7:Test (Best Model) - Loss: 3.7150 - Accuracy: 0.3529 - F1: 0.3476
sub_7:Test (Best Model) - Loss: 3.3314 - Accuracy: 0.3382 - F1: 0.3288
sub_7:Test (Best Model) - Loss: 3.9976 - Accuracy: 0.2941 - F1: 0.2916
sub_7:Test (Best Model) - Loss: 4.4951 - Accuracy: 0.3235 - F1: 0.3251
sub_7:Test (Best Model) - Loss: 5.1621 - Accuracy: 0.2647 - F1: 0.2665
sub_7:Test (Best Model) - Loss: 5.1364 - Accuracy: 0.3382 - F1: 0.3295
sub_7:Test (Best Model) - Loss: 4.3052 - Accuracy: 0.3088 - F1: 0.3113
sub_8:Test (Best Model) - Loss: 4.8712 - Accuracy: 0.2059 - F1: 0.2118
sub_8:Test (Best Model) - Loss: 5.5476 - Accuracy: 0.2500 - F1: 0.2358
sub_8:Test (Best Model) - Loss: 5.6037 - Accuracy: 0.2206 - F1: 0.2197
sub_8:Test (Best Model) - Loss: 5.2120 - Accuracy: 0.3088 - F1: 0.3063
sub_8:Test (Best Model) - Loss: 5.2562 - Accuracy: 0.2059 - F1: 0.1968
sub_8:Test (Best Model) - Loss: 3.2606 - Accuracy: 0.3235 - F1: 0.3278
sub_8:Test (Best Model) - Loss: 5.1315 - Accuracy: 0.2206 - F1: 0.2151
sub_8:Test (Best Model) - Loss: 4.4541 - Accuracy: 0.2206 - F1: 0.2170
sub_8:Test (Best Model) - Loss: 4.6137 - Accuracy: 0.1765 - F1: 0.1674
sub_8:Test (Best Model) - Loss: 4.9190 - Accuracy: 0.1618 - F1: 0.1375
sub_8:Test (Best Model) - Loss: 5.9183 - Accuracy: 0.1471 - F1: 0.1358
sub_8:Test (Best Model) - Loss: 6.0899 - Accuracy: 0.1912 - F1: 0.1899
sub_8:Test (Best Model) - Loss: 5.4989 - Accuracy: 0.1912 - F1: 0.1956
sub_8:Test (Best Model) - Loss: 5.1574 - Accuracy: 0.2353 - F1: 0.2294
sub_8:Test (Best Model) - Loss: 4.7398 - Accuracy: 0.2941 - F1: 0.2904
sub_9:Test (Best Model) - Loss: 3.3616 - Accuracy: 0.3676 - F1: 0.3816
sub_9:Test (Best Model) - Loss: 3.0106 - Accuracy: 0.3529 - F1: 0.3410
sub_9:Test (Best Model) - Loss: 3.2808 - Accuracy: 0.3088 - F1: 0.3118
sub_9:Test (Best Model) - Loss: 2.8477 - Accuracy: 0.3382 - F1: 0.3369
sub_9:Test (Best Model) - Loss: 2.6718 - Accuracy: 0.4118 - F1: 0.4082
sub_9:Test (Best Model) - Loss: 5.5066 - Accuracy: 0.2794 - F1: 0.2911
sub_9:Test (Best Model) - Loss: 4.7394 - Accuracy: 0.2941 - F1: 0.3036
sub_9:Test (Best Model) - Loss: 4.3989 - Accuracy: 0.3824 - F1: 0.3934
sub_9:Test (Best Model) - Loss: 3.8952 - Accuracy: 0.3235 - F1: 0.3255
sub_9:Test (Best Model) - Loss: 4.1600 - Accuracy: 0.3235 - F1: 0.3384
sub_9:Test (Best Model) - Loss: 5.1147 - Accuracy: 0.2206 - F1: 0.2167
sub_9:Test (Best Model) - Loss: 3.8470 - Accuracy: 0.3824 - F1: 0.4001
sub_9:Test (Best Model) - Loss: 4.1588 - Accuracy: 0.2353 - F1: 0.2278
sub_9:Test (Best Model) - Loss: 5.1104 - Accuracy: 0.3088 - F1: 0.3060
sub_9:Test (Best Model) - Loss: 4.2427 - Accuracy: 0.4118 - F1: 0.4313
sub_10:Test (Best Model) - Loss: 4.8139 - Accuracy: 0.1765 - F1: 0.1596
sub_10:Test (Best Model) - Loss: 4.6660 - Accuracy: 0.3088 - F1: 0.2917
sub_10:Test (Best Model) - Loss: 4.2374 - Accuracy: 0.2647 - F1: 0.2547
sub_10:Test (Best Model) - Loss: 4.2630 - Accuracy: 0.2353 - F1: 0.2247
sub_10:Test (Best Model) - Loss: 5.3490 - Accuracy: 0.2794 - F1: 0.2702
sub_10:Test (Best Model) - Loss: 5.4730 - Accuracy: 0.2353 - F1: 0.2075
sub_10:Test (Best Model) - Loss: 4.1026 - Accuracy: 0.1912 - F1: 0.1753
sub_10:Test (Best Model) - Loss: 4.9396 - Accuracy: 0.1765 - F1: 0.1650
sub_10:Test (Best Model) - Loss: 4.5400 - Accuracy: 0.2059 - F1: 0.2026
sub_10:Test (Best Model) - Loss: 5.3414 - Accuracy: 0.2353 - F1: 0.2309
sub_10:Test (Best Model) - Loss: 5.6172 - Accuracy: 0.2174 - F1: 0.1779
sub_10:Test (Best Model) - Loss: 5.6948 - Accuracy: 0.2609 - F1: 0.2604
sub_10:Test (Best Model) - Loss: 5.8683 - Accuracy: 0.2899 - F1: 0.2767
sub_10:Test (Best Model) - Loss: 5.5540 - Accuracy: 0.2319 - F1: 0.2198
sub_10:Test (Best Model) - Loss: 5.0611 - Accuracy: 0.2319 - F1: 0.2339
sub_11:Test (Best Model) - Loss: 5.0195 - Accuracy: 0.3043 - F1: 0.2904
sub_11:Test (Best Model) - Loss: 4.4888 - Accuracy: 0.2754 - F1: 0.2500
sub_11:Test (Best Model) - Loss: 4.3087 - Accuracy: 0.2609 - F1: 0.2613
sub_11:Test (Best Model) - Loss: 4.6565 - Accuracy: 0.2754 - F1: 0.2730
sub_11:Test (Best Model) - Loss: 5.1152 - Accuracy: 0.2319 - F1: 0.2021
sub_11:Test (Best Model) - Loss: 4.5816 - Accuracy: 0.3188 - F1: 0.3124
sub_11:Test (Best Model) - Loss: 4.5628 - Accuracy: 0.2754 - F1: 0.2569
sub_11:Test (Best Model) - Loss: 4.1492 - Accuracy: 0.3478 - F1: 0.3339
sub_11:Test (Best Model) - Loss: 5.0998 - Accuracy: 0.2899 - F1: 0.2571
sub_11:Test (Best Model) - Loss: 4.4612 - Accuracy: 0.3623 - F1: 0.3559
sub_11:Test (Best Model) - Loss: 3.5982 - Accuracy: 0.3043 - F1: 0.2574
sub_11:Test (Best Model) - Loss: 3.7843 - Accuracy: 0.3043 - F1: 0.2949
sub_11:Test (Best Model) - Loss: 3.4125 - Accuracy: 0.3913 - F1: 0.3413
sub_11:Test (Best Model) - Loss: 4.4199 - Accuracy: 0.2754 - F1: 0.2315
sub_11:Test (Best Model) - Loss: 3.7127 - Accuracy: 0.2754 - F1: 0.2358
sub_12:Test (Best Model) - Loss: 3.2905 - Accuracy: 0.3235 - F1: 0.3173
sub_12:Test (Best Model) - Loss: 3.3265 - Accuracy: 0.3529 - F1: 0.3246
sub_12:Test (Best Model) - Loss: 4.2130 - Accuracy: 0.2647 - F1: 0.2505
sub_12:Test (Best Model) - Loss: 3.8727 - Accuracy: 0.3235 - F1: 0.3111
sub_12:Test (Best Model) - Loss: 3.7764 - Accuracy: 0.2794 - F1: 0.2647
sub_12:Test (Best Model) - Loss: 4.5063 - Accuracy: 0.2609 - F1: 0.2502
sub_12:Test (Best Model) - Loss: 4.3423 - Accuracy: 0.2609 - F1: 0.2555
sub_12:Test (Best Model) - Loss: 3.9886 - Accuracy: 0.2609 - F1: 0.2461
sub_12:Test (Best Model) - Loss: 4.1410 - Accuracy: 0.2754 - F1: 0.2651
sub_12:Test (Best Model) - Loss: 3.6133 - Accuracy: 0.3188 - F1: 0.3036
sub_12:Test (Best Model) - Loss: 3.8394 - Accuracy: 0.3382 - F1: 0.3191
sub_12:Test (Best Model) - Loss: 4.8224 - Accuracy: 0.2941 - F1: 0.2703
sub_12:Test (Best Model) - Loss: 4.5007 - Accuracy: 0.2206 - F1: 0.2166
sub_12:Test (Best Model) - Loss: 5.2037 - Accuracy: 0.3088 - F1: 0.2962
sub_12:Test (Best Model) - Loss: 4.0954 - Accuracy: 0.3235 - F1: 0.3134
sub_13:Test (Best Model) - Loss: 4.6376 - Accuracy: 0.2941 - F1: 0.2877
sub_13:Test (Best Model) - Loss: 4.6200 - Accuracy: 0.2941 - F1: 0.2959
sub_13:Test (Best Model) - Loss: 3.9939 - Accuracy: 0.2647 - F1: 0.2751
sub_13:Test (Best Model) - Loss: 5.3642 - Accuracy: 0.2647 - F1: 0.2645
sub_13:Test (Best Model) - Loss: 4.4991 - Accuracy: 0.3382 - F1: 0.3310
sub_13:Test (Best Model) - Loss: 4.7811 - Accuracy: 0.2319 - F1: 0.2312
sub_13:Test (Best Model) - Loss: 4.3829 - Accuracy: 0.2319 - F1: 0.2118
sub_13:Test (Best Model) - Loss: 4.8915 - Accuracy: 0.2464 - F1: 0.2432
sub_13:Test (Best Model) - Loss: 5.3618 - Accuracy: 0.3043 - F1: 0.3078
sub_13:Test (Best Model) - Loss: 4.3029 - Accuracy: 0.2319 - F1: 0.2212
sub_13:Test (Best Model) - Loss: 3.5876 - Accuracy: 0.2500 - F1: 0.2301
sub_13:Test (Best Model) - Loss: 3.9700 - Accuracy: 0.3088 - F1: 0.2946
sub_13:Test (Best Model) - Loss: 4.4879 - Accuracy: 0.2647 - F1: 0.2792
sub_13:Test (Best Model) - Loss: 4.2546 - Accuracy: 0.2500 - F1: 0.2483
sub_13:Test (Best Model) - Loss: 3.9282 - Accuracy: 0.2941 - F1: 0.2736
sub_14:Test (Best Model) - Loss: 4.3354 - Accuracy: 0.2353 - F1: 0.2378
sub_14:Test (Best Model) - Loss: 4.0568 - Accuracy: 0.2353 - F1: 0.2189
sub_14:Test (Best Model) - Loss: 4.7808 - Accuracy: 0.2353 - F1: 0.2358
sub_14:Test (Best Model) - Loss: 3.7285 - Accuracy: 0.2500 - F1: 0.2469
sub_14:Test (Best Model) - Loss: 3.7507 - Accuracy: 0.2500 - F1: 0.2483
sub_14:Test (Best Model) - Loss: 5.2145 - Accuracy: 0.1912 - F1: 0.1668
sub_14:Test (Best Model) - Loss: 4.7943 - Accuracy: 0.2353 - F1: 0.2233
sub_14:Test (Best Model) - Loss: 4.3606 - Accuracy: 0.2500 - F1: 0.2442
sub_14:Test (Best Model) - Loss: 4.8837 - Accuracy: 0.3088 - F1: 0.2845
sub_14:Test (Best Model) - Loss: 4.7088 - Accuracy: 0.2647 - F1: 0.2324
sub_14:Test (Best Model) - Loss: 4.7006 - Accuracy: 0.2206 - F1: 0.2069
sub_14:Test (Best Model) - Loss: 3.9843 - Accuracy: 0.2794 - F1: 0.2658
sub_14:Test (Best Model) - Loss: 4.7334 - Accuracy: 0.2647 - F1: 0.2529
sub_14:Test (Best Model) - Loss: 3.4975 - Accuracy: 0.3088 - F1: 0.2943
sub_14:Test (Best Model) - Loss: 3.5855 - Accuracy: 0.2500 - F1: 0.2409
sub_15:Test (Best Model) - Loss: 4.3924 - Accuracy: 0.3235 - F1: 0.3197
sub_15:Test (Best Model) - Loss: 5.1822 - Accuracy: 0.1912 - F1: 0.1740
sub_15:Test (Best Model) - Loss: 5.8600 - Accuracy: 0.2353 - F1: 0.2389
sub_15:Test (Best Model) - Loss: 4.0224 - Accuracy: 0.2941 - F1: 0.3021
sub_15:Test (Best Model) - Loss: 5.5261 - Accuracy: 0.2794 - F1: 0.2763
sub_15:Test (Best Model) - Loss: 3.7963 - Accuracy: 0.3529 - F1: 0.3618
sub_15:Test (Best Model) - Loss: 4.9464 - Accuracy: 0.3529 - F1: 0.3494
sub_15:Test (Best Model) - Loss: 3.8285 - Accuracy: 0.4118 - F1: 0.4105
sub_15:Test (Best Model) - Loss: 4.7138 - Accuracy: 0.3676 - F1: 0.3708
sub_15:Test (Best Model) - Loss: 3.3847 - Accuracy: 0.3971 - F1: 0.4021
sub_15:Test (Best Model) - Loss: 3.8941 - Accuracy: 0.2794 - F1: 0.2922
sub_15:Test (Best Model) - Loss: 4.0020 - Accuracy: 0.2794 - F1: 0.2882
sub_15:Test (Best Model) - Loss: 3.6871 - Accuracy: 0.2794 - F1: 0.2836
sub_15:Test (Best Model) - Loss: 4.3320 - Accuracy: 0.3382 - F1: 0.3606
sub_15:Test (Best Model) - Loss: 4.5097 - Accuracy: 0.2794 - F1: 0.2992
sub_16:Test (Best Model) - Loss: 4.1215 - Accuracy: 0.2941 - F1: 0.2784
sub_16:Test (Best Model) - Loss: 3.3899 - Accuracy: 0.2353 - F1: 0.2284
sub_16:Test (Best Model) - Loss: 3.7678 - Accuracy: 0.3382 - F1: 0.3312
sub_16:Test (Best Model) - Loss: 4.3280 - Accuracy: 0.2647 - F1: 0.2517
sub_16:Test (Best Model) - Loss: 3.4690 - Accuracy: 0.2059 - F1: 0.2006
sub_16:Test (Best Model) - Loss: 6.0760 - Accuracy: 0.3088 - F1: 0.2964
sub_16:Test (Best Model) - Loss: 6.2700 - Accuracy: 0.3235 - F1: 0.2968
sub_16:Test (Best Model) - Loss: 3.4885 - Accuracy: 0.3676 - F1: 0.3699
sub_16:Test (Best Model) - Loss: 4.5770 - Accuracy: 0.2794 - F1: 0.2796
sub_16:Test (Best Model) - Loss: 6.7848 - Accuracy: 0.2500 - F1: 0.2426
sub_16:Test (Best Model) - Loss: 3.9518 - Accuracy: 0.2647 - F1: 0.2557
sub_16:Test (Best Model) - Loss: 4.0309 - Accuracy: 0.3529 - F1: 0.3396
sub_16:Test (Best Model) - Loss: 3.2826 - Accuracy: 0.2500 - F1: 0.2455
sub_16:Test (Best Model) - Loss: 4.6333 - Accuracy: 0.2353 - F1: 0.2202
sub_16:Test (Best Model) - Loss: 3.0169 - Accuracy: 0.2941 - F1: 0.2768
sub_17:Test (Best Model) - Loss: 3.5421 - Accuracy: 0.3478 - F1: 0.2963
sub_17:Test (Best Model) - Loss: 2.3476 - Accuracy: 0.3623 - F1: 0.3554
sub_17:Test (Best Model) - Loss: 3.6968 - Accuracy: 0.3478 - F1: 0.3382
sub_17:Test (Best Model) - Loss: 2.9113 - Accuracy: 0.3768 - F1: 0.3650
sub_17:Test (Best Model) - Loss: 2.6240 - Accuracy: 0.4638 - F1: 0.4492
sub_17:Test (Best Model) - Loss: 3.6733 - Accuracy: 0.3623 - F1: 0.3260
sub_17:Test (Best Model) - Loss: 4.6512 - Accuracy: 0.3043 - F1: 0.2961
sub_17:Test (Best Model) - Loss: 3.7162 - Accuracy: 0.3768 - F1: 0.3528
sub_17:Test (Best Model) - Loss: 4.1733 - Accuracy: 0.3623 - F1: 0.3323
sub_17:Test (Best Model) - Loss: 4.2367 - Accuracy: 0.3333 - F1: 0.2677
sub_17:Test (Best Model) - Loss: 3.6974 - Accuracy: 0.4706 - F1: 0.4763
sub_17:Test (Best Model) - Loss: 4.2245 - Accuracy: 0.3824 - F1: 0.3786
sub_17:Test (Best Model) - Loss: 3.7218 - Accuracy: 0.3529 - F1: 0.3157
sub_17:Test (Best Model) - Loss: 3.6321 - Accuracy: 0.2794 - F1: 0.2749
sub_17:Test (Best Model) - Loss: 4.8052 - Accuracy: 0.2647 - F1: 0.2678
sub_18:Test (Best Model) - Loss: 4.1673 - Accuracy: 0.3333 - F1: 0.3293
sub_18:Test (Best Model) - Loss: 3.5356 - Accuracy: 0.3478 - F1: 0.3575
sub_18:Test (Best Model) - Loss: 4.0114 - Accuracy: 0.2754 - F1: 0.2745
sub_18:Test (Best Model) - Loss: 4.1344 - Accuracy: 0.2174 - F1: 0.2203
sub_18:Test (Best Model) - Loss: 4.2226 - Accuracy: 0.2319 - F1: 0.2400
sub_18:Test (Best Model) - Loss: 3.6147 - Accuracy: 0.3235 - F1: 0.3128
sub_18:Test (Best Model) - Loss: 4.3501 - Accuracy: 0.3235 - F1: 0.3141
sub_18:Test (Best Model) - Loss: 4.0986 - Accuracy: 0.2647 - F1: 0.2645
sub_18:Test (Best Model) - Loss: 4.0729 - Accuracy: 0.2647 - F1: 0.2916
sub_18:Test (Best Model) - Loss: 4.1231 - Accuracy: 0.2059 - F1: 0.2039
sub_18:Test (Best Model) - Loss: 3.7041 - Accuracy: 0.3088 - F1: 0.3068
sub_18:Test (Best Model) - Loss: 4.5921 - Accuracy: 0.2941 - F1: 0.2961
sub_18:Test (Best Model) - Loss: 4.4164 - Accuracy: 0.2500 - F1: 0.2499
sub_18:Test (Best Model) - Loss: 4.4903 - Accuracy: 0.2500 - F1: 0.2489
sub_18:Test (Best Model) - Loss: 4.1985 - Accuracy: 0.2206 - F1: 0.2226
sub_19:Test (Best Model) - Loss: 3.6998 - Accuracy: 0.2941 - F1: 0.2629
sub_19:Test (Best Model) - Loss: 4.0533 - Accuracy: 0.2647 - F1: 0.1987
sub_19:Test (Best Model) - Loss: 3.9426 - Accuracy: 0.3824 - F1: 0.3507
sub_19:Test (Best Model) - Loss: 4.3437 - Accuracy: 0.3235 - F1: 0.2957
sub_19:Test (Best Model) - Loss: 3.0832 - Accuracy: 0.3676 - F1: 0.3323
sub_19:Test (Best Model) - Loss: 6.4040 - Accuracy: 0.3088 - F1: 0.2842
sub_19:Test (Best Model) - Loss: 4.9391 - Accuracy: 0.2941 - F1: 0.2679
sub_19:Test (Best Model) - Loss: 4.0064 - Accuracy: 0.2353 - F1: 0.2160
sub_19:Test (Best Model) - Loss: 4.5286 - Accuracy: 0.2941 - F1: 0.2752
sub_19:Test (Best Model) - Loss: 5.1227 - Accuracy: 0.2647 - F1: 0.2448
sub_19:Test (Best Model) - Loss: 4.0486 - Accuracy: 0.2647 - F1: 0.2534
sub_19:Test (Best Model) - Loss: 4.9716 - Accuracy: 0.2500 - F1: 0.2455
sub_19:Test (Best Model) - Loss: 3.7411 - Accuracy: 0.2941 - F1: 0.2707
sub_19:Test (Best Model) - Loss: 6.2080 - Accuracy: 0.2206 - F1: 0.2259
sub_19:Test (Best Model) - Loss: 5.4783 - Accuracy: 0.3529 - F1: 0.3453
sub_20:Test (Best Model) - Loss: 3.8683 - Accuracy: 0.3088 - F1: 0.3013
sub_20:Test (Best Model) - Loss: 4.0957 - Accuracy: 0.4118 - F1: 0.4230
sub_20:Test (Best Model) - Loss: 4.8083 - Accuracy: 0.2794 - F1: 0.2793
sub_20:Test (Best Model) - Loss: 3.8022 - Accuracy: 0.2500 - F1: 0.2439
sub_20:Test (Best Model) - Loss: 4.8006 - Accuracy: 0.3529 - F1: 0.3379
sub_20:Test (Best Model) - Loss: 4.3745 - Accuracy: 0.3088 - F1: 0.2842
sub_20:Test (Best Model) - Loss: 3.6948 - Accuracy: 0.3529 - F1: 0.3572
sub_20:Test (Best Model) - Loss: 4.5251 - Accuracy: 0.3529 - F1: 0.3689
sub_20:Test (Best Model) - Loss: 5.5230 - Accuracy: 0.3382 - F1: 0.3279
sub_20:Test (Best Model) - Loss: 4.3725 - Accuracy: 0.3235 - F1: 0.3409
sub_20:Test (Best Model) - Loss: 3.8370 - Accuracy: 0.3913 - F1: 0.4013
sub_20:Test (Best Model) - Loss: 4.4951 - Accuracy: 0.2754 - F1: 0.2693
sub_20:Test (Best Model) - Loss: 4.7641 - Accuracy: 0.4058 - F1: 0.3814
sub_20:Test (Best Model) - Loss: 4.0339 - Accuracy: 0.3478 - F1: 0.3438
sub_20:Test (Best Model) - Loss: 4.3842 - Accuracy: 0.3478 - F1: 0.3523
sub_21:Test (Best Model) - Loss: 4.5029 - Accuracy: 0.3529 - F1: 0.3373
sub_21:Test (Best Model) - Loss: 4.7615 - Accuracy: 0.2500 - F1: 0.2432
sub_21:Test (Best Model) - Loss: 4.8737 - Accuracy: 0.2794 - F1: 0.2638
sub_21:Test (Best Model) - Loss: 4.4013 - Accuracy: 0.3382 - F1: 0.3275
sub_21:Test (Best Model) - Loss: 5.8150 - Accuracy: 0.2794 - F1: 0.2695
sub_21:Test (Best Model) - Loss: 4.4873 - Accuracy: 0.2794 - F1: 0.2820
sub_21:Test (Best Model) - Loss: 5.0032 - Accuracy: 0.2941 - F1: 0.2944
sub_21:Test (Best Model) - Loss: 3.5146 - Accuracy: 0.2941 - F1: 0.2917
sub_21:Test (Best Model) - Loss: 4.1066 - Accuracy: 0.3235 - F1: 0.3187
sub_21:Test (Best Model) - Loss: 4.2730 - Accuracy: 0.2353 - F1: 0.2259
sub_21:Test (Best Model) - Loss: 4.2467 - Accuracy: 0.1471 - F1: 0.1465
sub_21:Test (Best Model) - Loss: 3.9888 - Accuracy: 0.2500 - F1: 0.2543
sub_21:Test (Best Model) - Loss: 4.5617 - Accuracy: 0.2794 - F1: 0.2459
sub_21:Test (Best Model) - Loss: 4.8829 - Accuracy: 0.1765 - F1: 0.1712
sub_21:Test (Best Model) - Loss: 3.5193 - Accuracy: 0.2941 - F1: 0.2894
sub_22:Test (Best Model) - Loss: 5.2388 - Accuracy: 0.2647 - F1: 0.2541
sub_22:Test (Best Model) - Loss: 4.8678 - Accuracy: 0.2941 - F1: 0.2692
sub_22:Test (Best Model) - Loss: 5.8157 - Accuracy: 0.2206 - F1: 0.2174
sub_22:Test (Best Model) - Loss: 4.8940 - Accuracy: 0.2647 - F1: 0.2500
sub_22:Test (Best Model) - Loss: 5.0984 - Accuracy: 0.3235 - F1: 0.3008
sub_22:Test (Best Model) - Loss: 4.1792 - Accuracy: 0.2754 - F1: 0.2475
sub_22:Test (Best Model) - Loss: 3.4464 - Accuracy: 0.3188 - F1: 0.2819
sub_22:Test (Best Model) - Loss: 3.1143 - Accuracy: 0.2899 - F1: 0.2610
sub_22:Test (Best Model) - Loss: 3.3257 - Accuracy: 0.2609 - F1: 0.2607
sub_22:Test (Best Model) - Loss: 3.7396 - Accuracy: 0.2754 - F1: 0.2190
sub_22:Test (Best Model) - Loss: 4.0364 - Accuracy: 0.2941 - F1: 0.3115
sub_22:Test (Best Model) - Loss: 3.9640 - Accuracy: 0.2647 - F1: 0.2633
sub_22:Test (Best Model) - Loss: 3.5618 - Accuracy: 0.2647 - F1: 0.2577
sub_22:Test (Best Model) - Loss: 3.6698 - Accuracy: 0.3088 - F1: 0.3117
sub_22:Test (Best Model) - Loss: 3.9066 - Accuracy: 0.3971 - F1: 0.4041
sub_23:Test (Best Model) - Loss: 4.7636 - Accuracy: 0.2609 - F1: 0.2500
sub_23:Test (Best Model) - Loss: 4.3904 - Accuracy: 0.2319 - F1: 0.2248
sub_23:Test (Best Model) - Loss: 4.0059 - Accuracy: 0.3768 - F1: 0.3546
sub_23:Test (Best Model) - Loss: 3.7093 - Accuracy: 0.2754 - F1: 0.2650
sub_23:Test (Best Model) - Loss: 3.9938 - Accuracy: 0.3043 - F1: 0.3001
sub_23:Test (Best Model) - Loss: 4.0483 - Accuracy: 0.3676 - F1: 0.3549
sub_23:Test (Best Model) - Loss: 3.2229 - Accuracy: 0.2500 - F1: 0.2572
sub_23:Test (Best Model) - Loss: 3.8062 - Accuracy: 0.3382 - F1: 0.3251
sub_23:Test (Best Model) - Loss: 3.3391 - Accuracy: 0.2500 - F1: 0.2375
sub_23:Test (Best Model) - Loss: 3.5445 - Accuracy: 0.2941 - F1: 0.2554
sub_23:Test (Best Model) - Loss: 6.1261 - Accuracy: 0.2174 - F1: 0.1862
sub_23:Test (Best Model) - Loss: 6.8533 - Accuracy: 0.2464 - F1: 0.2302
sub_23:Test (Best Model) - Loss: 5.1204 - Accuracy: 0.2464 - F1: 0.2222
sub_23:Test (Best Model) - Loss: 6.7688 - Accuracy: 0.2319 - F1: 0.2233
sub_23:Test (Best Model) - Loss: 6.3033 - Accuracy: 0.3043 - F1: 0.2704
sub_24:Test (Best Model) - Loss: 4.7229 - Accuracy: 0.3529 - F1: 0.3441
sub_24:Test (Best Model) - Loss: 3.8078 - Accuracy: 0.2941 - F1: 0.2851
sub_24:Test (Best Model) - Loss: 4.2518 - Accuracy: 0.2941 - F1: 0.2873
sub_24:Test (Best Model) - Loss: 4.2815 - Accuracy: 0.2353 - F1: 0.2335
sub_24:Test (Best Model) - Loss: 4.1148 - Accuracy: 0.2353 - F1: 0.2287
sub_24:Test (Best Model) - Loss: 3.3758 - Accuracy: 0.2794 - F1: 0.2828
sub_24:Test (Best Model) - Loss: 3.4814 - Accuracy: 0.3676 - F1: 0.3559
sub_24:Test (Best Model) - Loss: 2.6058 - Accuracy: 0.2941 - F1: 0.2908
sub_24:Test (Best Model) - Loss: 3.1495 - Accuracy: 0.3088 - F1: 0.2933
sub_24:Test (Best Model) - Loss: 3.1171 - Accuracy: 0.3088 - F1: 0.3022
sub_24:Test (Best Model) - Loss: 4.6645 - Accuracy: 0.2206 - F1: 0.2134
sub_24:Test (Best Model) - Loss: 3.4948 - Accuracy: 0.2206 - F1: 0.2209
sub_24:Test (Best Model) - Loss: 3.8271 - Accuracy: 0.2500 - F1: 0.2506
sub_24:Test (Best Model) - Loss: 3.9607 - Accuracy: 0.3676 - F1: 0.3666
sub_24:Test (Best Model) - Loss: 4.6626 - Accuracy: 0.2206 - F1: 0.2293
sub_25:Test (Best Model) - Loss: 3.8879 - Accuracy: 0.2754 - F1: 0.2370
sub_25:Test (Best Model) - Loss: 4.8810 - Accuracy: 0.3188 - F1: 0.2768
sub_25:Test (Best Model) - Loss: 4.1948 - Accuracy: 0.2464 - F1: 0.2361
sub_25:Test (Best Model) - Loss: 4.0491 - Accuracy: 0.3478 - F1: 0.3297
sub_25:Test (Best Model) - Loss: 5.0259 - Accuracy: 0.2464 - F1: 0.2326
sub_25:Test (Best Model) - Loss: 3.3326 - Accuracy: 0.3088 - F1: 0.2718
sub_25:Test (Best Model) - Loss: 5.3402 - Accuracy: 0.2353 - F1: 0.2028
sub_25:Test (Best Model) - Loss: 3.4699 - Accuracy: 0.3382 - F1: 0.3350
sub_25:Test (Best Model) - Loss: 3.6792 - Accuracy: 0.3824 - F1: 0.3356
sub_25:Test (Best Model) - Loss: 3.6599 - Accuracy: 0.3235 - F1: 0.2887
sub_25:Test (Best Model) - Loss: 4.0914 - Accuracy: 0.2647 - F1: 0.2447
sub_25:Test (Best Model) - Loss: 4.0936 - Accuracy: 0.2794 - F1: 0.2594
sub_25:Test (Best Model) - Loss: 3.4359 - Accuracy: 0.3971 - F1: 0.3660
sub_25:Test (Best Model) - Loss: 4.3742 - Accuracy: 0.3382 - F1: 0.3194
sub_25:Test (Best Model) - Loss: 4.1989 - Accuracy: 0.3529 - F1: 0.3168
sub_26:Test (Best Model) - Loss: 3.3685 - Accuracy: 0.3043 - F1: 0.2999
sub_26:Test (Best Model) - Loss: 4.0859 - Accuracy: 0.2899 - F1: 0.2867
sub_26:Test (Best Model) - Loss: 4.1061 - Accuracy: 0.3623 - F1: 0.3639
sub_26:Test (Best Model) - Loss: 3.3797 - Accuracy: 0.3043 - F1: 0.3026
sub_26:Test (Best Model) - Loss: 3.9251 - Accuracy: 0.3623 - F1: 0.3510
sub_26:Test (Best Model) - Loss: 4.0683 - Accuracy: 0.1912 - F1: 0.1758
sub_26:Test (Best Model) - Loss: 3.7724 - Accuracy: 0.2941 - F1: 0.2897
sub_26:Test (Best Model) - Loss: 2.7668 - Accuracy: 0.3382 - F1: 0.3325
sub_26:Test (Best Model) - Loss: 3.3486 - Accuracy: 0.3382 - F1: 0.3304
sub_26:Test (Best Model) - Loss: 2.8228 - Accuracy: 0.2941 - F1: 0.2839
sub_26:Test (Best Model) - Loss: 3.7068 - Accuracy: 0.4853 - F1: 0.4857
sub_26:Test (Best Model) - Loss: 5.6199 - Accuracy: 0.4412 - F1: 0.4385
sub_26:Test (Best Model) - Loss: 4.3450 - Accuracy: 0.3382 - F1: 0.3261
sub_26:Test (Best Model) - Loss: 4.6466 - Accuracy: 0.4706 - F1: 0.4621
sub_26:Test (Best Model) - Loss: 4.7108 - Accuracy: 0.3382 - F1: 0.3301
sub_27:Test (Best Model) - Loss: 3.5421 - Accuracy: 0.3478 - F1: 0.2963
sub_27:Test (Best Model) - Loss: 2.3476 - Accuracy: 0.3623 - F1: 0.3554
sub_27:Test (Best Model) - Loss: 3.6968 - Accuracy: 0.3478 - F1: 0.3382
sub_27:Test (Best Model) - Loss: 2.9113 - Accuracy: 0.3768 - F1: 0.3650
sub_27:Test (Best Model) - Loss: 2.6240 - Accuracy: 0.4638 - F1: 0.4492
sub_27:Test (Best Model) - Loss: 3.6733 - Accuracy: 0.3623 - F1: 0.3260
sub_27:Test (Best Model) - Loss: 4.6512 - Accuracy: 0.3043 - F1: 0.2961
sub_27:Test (Best Model) - Loss: 3.7162 - Accuracy: 0.3768 - F1: 0.3528
sub_27:Test (Best Model) - Loss: 4.1733 - Accuracy: 0.3623 - F1: 0.3323
sub_27:Test (Best Model) - Loss: 4.2367 - Accuracy: 0.3333 - F1: 0.2677
sub_27:Test (Best Model) - Loss: 3.6974 - Accuracy: 0.4706 - F1: 0.4763
sub_27:Test (Best Model) - Loss: 4.2245 - Accuracy: 0.3824 - F1: 0.3786
sub_27:Test (Best Model) - Loss: 3.7218 - Accuracy: 0.3529 - F1: 0.3157
sub_27:Test (Best Model) - Loss: 3.6321 - Accuracy: 0.2794 - F1: 0.2749
sub_27:Test (Best Model) - Loss: 4.8052 - Accuracy: 0.2647 - F1: 0.2678
sub_28:Test (Best Model) - Loss: 3.9598 - Accuracy: 0.2353 - F1: 0.2283
sub_28:Test (Best Model) - Loss: 3.6614 - Accuracy: 0.2941 - F1: 0.2800
sub_28:Test (Best Model) - Loss: 4.6393 - Accuracy: 0.2500 - F1: 0.2481
sub_28:Test (Best Model) - Loss: 3.6117 - Accuracy: 0.1912 - F1: 0.1848
sub_28:Test (Best Model) - Loss: 3.7665 - Accuracy: 0.1912 - F1: 0.1915
sub_28:Test (Best Model) - Loss: 7.2251 - Accuracy: 0.2206 - F1: 0.2052
sub_28:Test (Best Model) - Loss: 7.5539 - Accuracy: 0.2647 - F1: 0.2696
sub_28:Test (Best Model) - Loss: 8.4438 - Accuracy: 0.2206 - F1: 0.2289
sub_28:Test (Best Model) - Loss: 6.4809 - Accuracy: 0.2500 - F1: 0.2583
sub_28:Test (Best Model) - Loss: 7.2102 - Accuracy: 0.2794 - F1: 0.2523
sub_28:Test (Best Model) - Loss: 2.8923 - Accuracy: 0.2500 - F1: 0.2414
sub_28:Test (Best Model) - Loss: 2.3105 - Accuracy: 0.3529 - F1: 0.3497
sub_28:Test (Best Model) - Loss: 3.0638 - Accuracy: 0.2353 - F1: 0.2306
sub_28:Test (Best Model) - Loss: 2.8422 - Accuracy: 0.2353 - F1: 0.2199
sub_28:Test (Best Model) - Loss: 2.5489 - Accuracy: 0.2353 - F1: 0.2321
sub_29:Test (Best Model) - Loss: 4.6189 - Accuracy: 0.3824 - F1: 0.3876
sub_29:Test (Best Model) - Loss: 4.8011 - Accuracy: 0.3088 - F1: 0.2823
sub_29:Test (Best Model) - Loss: 3.8633 - Accuracy: 0.4559 - F1: 0.4553
sub_29:Test (Best Model) - Loss: 4.2814 - Accuracy: 0.3088 - F1: 0.3026
sub_29:Test (Best Model) - Loss: 3.3587 - Accuracy: 0.4706 - F1: 0.4856
sub_29:Test (Best Model) - Loss: 4.3781 - Accuracy: 0.3824 - F1: 0.3983
sub_29:Test (Best Model) - Loss: 4.0489 - Accuracy: 0.2353 - F1: 0.2357
sub_29:Test (Best Model) - Loss: 4.3522 - Accuracy: 0.2794 - F1: 0.2907
sub_29:Test (Best Model) - Loss: 3.7027 - Accuracy: 0.4559 - F1: 0.4699
sub_29:Test (Best Model) - Loss: 3.7528 - Accuracy: 0.3088 - F1: 0.3136
sub_29:Test (Best Model) - Loss: 3.8092 - Accuracy: 0.4638 - F1: 0.4679
sub_29:Test (Best Model) - Loss: 4.3581 - Accuracy: 0.3623 - F1: 0.3649
sub_29:Test (Best Model) - Loss: 4.1936 - Accuracy: 0.3623 - F1: 0.3451
sub_29:Test (Best Model) - Loss: 3.4659 - Accuracy: 0.4638 - F1: 0.4747
sub_29:Test (Best Model) - Loss: 3.9400 - Accuracy: 0.3188 - F1: 0.3268

=== Summary Results ===

acc: 29.57 ± 3.71
F1: 28.48 ± 3.82
acc-in: 35.87 ± 3.25
F1-in: 34.30 ± 3.27
