lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.6312 - Accuracy: 0.2647 - F1: 0.2635
sub_1:Test (Best Model) - Loss: 1.8345 - Accuracy: 0.3382 - F1: 0.3241
sub_1:Test (Best Model) - Loss: 1.9681 - Accuracy: 0.2647 - F1: 0.2647
sub_1:Test (Best Model) - Loss: 1.6855 - Accuracy: 0.2794 - F1: 0.2776
sub_1:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.3676 - F1: 0.3587
sub_1:Test (Best Model) - Loss: 1.7791 - Accuracy: 0.3768 - F1: 0.3539
sub_1:Test (Best Model) - Loss: 1.6528 - Accuracy: 0.2609 - F1: 0.2162
sub_1:Test (Best Model) - Loss: 1.7755 - Accuracy: 0.3188 - F1: 0.2932
sub_1:Test (Best Model) - Loss: 1.6930 - Accuracy: 0.3478 - F1: 0.3286
sub_1:Test (Best Model) - Loss: 1.6785 - Accuracy: 0.2899 - F1: 0.2685
sub_1:Test (Best Model) - Loss: 1.5725 - Accuracy: 0.3235 - F1: 0.3148
sub_1:Test (Best Model) - Loss: 1.4407 - Accuracy: 0.3971 - F1: 0.3999
sub_1:Test (Best Model) - Loss: 1.3968 - Accuracy: 0.3529 - F1: 0.3437
sub_1:Test (Best Model) - Loss: 1.9916 - Accuracy: 0.3971 - F1: 0.3766
sub_1:Test (Best Model) - Loss: 1.4582 - Accuracy: 0.3676 - F1: 0.3585
sub_2:Test (Best Model) - Loss: 1.7868 - Accuracy: 0.2899 - F1: 0.2794
sub_2:Test (Best Model) - Loss: 1.8673 - Accuracy: 0.2899 - F1: 0.2537
sub_2:Test (Best Model) - Loss: 1.8808 - Accuracy: 0.2899 - F1: 0.2520
sub_2:Test (Best Model) - Loss: 1.9952 - Accuracy: 0.2319 - F1: 0.2107
sub_2:Test (Best Model) - Loss: 2.1136 - Accuracy: 0.2609 - F1: 0.2460
sub_2:Test (Best Model) - Loss: 1.8529 - Accuracy: 0.2794 - F1: 0.2660
sub_2:Test (Best Model) - Loss: 1.7458 - Accuracy: 0.2941 - F1: 0.2694
sub_2:Test (Best Model) - Loss: 1.6713 - Accuracy: 0.2941 - F1: 0.2804
sub_2:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.3382 - F1: 0.3212
sub_2:Test (Best Model) - Loss: 1.7870 - Accuracy: 0.3088 - F1: 0.3100
sub_2:Test (Best Model) - Loss: 1.9136 - Accuracy: 0.2754 - F1: 0.2429
sub_2:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.2899 - F1: 0.2333
sub_2:Test (Best Model) - Loss: 1.6506 - Accuracy: 0.3188 - F1: 0.2679
sub_2:Test (Best Model) - Loss: 1.8155 - Accuracy: 0.3333 - F1: 0.2916
sub_2:Test (Best Model) - Loss: 1.6787 - Accuracy: 0.3478 - F1: 0.3188
sub_3:Test (Best Model) - Loss: 2.3205 - Accuracy: 0.3088 - F1: 0.2982
sub_3:Test (Best Model) - Loss: 2.0023 - Accuracy: 0.2794 - F1: 0.2735
sub_3:Test (Best Model) - Loss: 2.0466 - Accuracy: 0.2353 - F1: 0.2300
sub_3:Test (Best Model) - Loss: 1.8810 - Accuracy: 0.2206 - F1: 0.2133
sub_3:Test (Best Model) - Loss: 1.8221 - Accuracy: 0.1765 - F1: 0.1760
sub_3:Test (Best Model) - Loss: 1.6951 - Accuracy: 0.2029 - F1: 0.1988
sub_3:Test (Best Model) - Loss: 1.7974 - Accuracy: 0.2029 - F1: 0.2032
sub_3:Test (Best Model) - Loss: 1.6448 - Accuracy: 0.1884 - F1: 0.1787
sub_3:Test (Best Model) - Loss: 1.7432 - Accuracy: 0.2899 - F1: 0.2640
sub_3:Test (Best Model) - Loss: 1.6498 - Accuracy: 0.2174 - F1: 0.2154
sub_3:Test (Best Model) - Loss: 1.9671 - Accuracy: 0.2319 - F1: 0.2323
sub_3:Test (Best Model) - Loss: 1.7347 - Accuracy: 0.2464 - F1: 0.2349
sub_3:Test (Best Model) - Loss: 2.1772 - Accuracy: 0.2609 - F1: 0.2481
sub_3:Test (Best Model) - Loss: 2.0752 - Accuracy: 0.2464 - F1: 0.2319
sub_3:Test (Best Model) - Loss: 1.9410 - Accuracy: 0.3333 - F1: 0.3203
sub_4:Test (Best Model) - Loss: 1.7581 - Accuracy: 0.2464 - F1: 0.2624
sub_4:Test (Best Model) - Loss: 1.7092 - Accuracy: 0.3188 - F1: 0.3299
sub_4:Test (Best Model) - Loss: 2.1518 - Accuracy: 0.3333 - F1: 0.3271
sub_4:Test (Best Model) - Loss: 1.5924 - Accuracy: 0.4058 - F1: 0.3911
sub_4:Test (Best Model) - Loss: 2.0115 - Accuracy: 0.3478 - F1: 0.3323
sub_4:Test (Best Model) - Loss: 1.7042 - Accuracy: 0.3768 - F1: 0.3684
sub_4:Test (Best Model) - Loss: 1.5142 - Accuracy: 0.3478 - F1: 0.3564
sub_4:Test (Best Model) - Loss: 1.4227 - Accuracy: 0.3768 - F1: 0.3787
sub_4:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.3478 - F1: 0.3349
sub_4:Test (Best Model) - Loss: 1.6283 - Accuracy: 0.3478 - F1: 0.3410
sub_4:Test (Best Model) - Loss: 1.4961 - Accuracy: 0.3478 - F1: 0.3178
sub_4:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.3478 - F1: 0.3309
sub_4:Test (Best Model) - Loss: 1.5283 - Accuracy: 0.2754 - F1: 0.2886
sub_4:Test (Best Model) - Loss: 1.4657 - Accuracy: 0.2899 - F1: 0.2875
sub_4:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.4493 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 2.1408 - Accuracy: 0.2353 - F1: 0.2136
sub_5:Test (Best Model) - Loss: 2.2186 - Accuracy: 0.2353 - F1: 0.2261
sub_5:Test (Best Model) - Loss: 2.6667 - Accuracy: 0.2794 - F1: 0.2708
sub_5:Test (Best Model) - Loss: 2.1105 - Accuracy: 0.3824 - F1: 0.3694
sub_5:Test (Best Model) - Loss: 2.1955 - Accuracy: 0.2353 - F1: 0.2296
sub_5:Test (Best Model) - Loss: 1.5016 - Accuracy: 0.4412 - F1: 0.4385
sub_5:Test (Best Model) - Loss: 1.4080 - Accuracy: 0.4412 - F1: 0.4384
sub_5:Test (Best Model) - Loss: 1.5132 - Accuracy: 0.3824 - F1: 0.3800
sub_5:Test (Best Model) - Loss: 1.4676 - Accuracy: 0.3971 - F1: 0.3962
sub_5:Test (Best Model) - Loss: 1.5434 - Accuracy: 0.4265 - F1: 0.4339
sub_5:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.3235 - F1: 0.3195
sub_5:Test (Best Model) - Loss: 1.5122 - Accuracy: 0.3235 - F1: 0.2869
sub_5:Test (Best Model) - Loss: 1.5744 - Accuracy: 0.2941 - F1: 0.2739
sub_5:Test (Best Model) - Loss: 1.3914 - Accuracy: 0.3676 - F1: 0.3634
sub_5:Test (Best Model) - Loss: 1.3114 - Accuracy: 0.3676 - F1: 0.3629
sub_6:Test (Best Model) - Loss: 1.4731 - Accuracy: 0.3971 - F1: 0.3870
sub_6:Test (Best Model) - Loss: 1.5609 - Accuracy: 0.3971 - F1: 0.3729
sub_6:Test (Best Model) - Loss: 1.5168 - Accuracy: 0.3382 - F1: 0.3187
sub_6:Test (Best Model) - Loss: 1.4518 - Accuracy: 0.3382 - F1: 0.3272
sub_6:Test (Best Model) - Loss: 1.4632 - Accuracy: 0.3676 - F1: 0.3750
sub_6:Test (Best Model) - Loss: 1.8570 - Accuracy: 0.2464 - F1: 0.1864
sub_6:Test (Best Model) - Loss: 1.6513 - Accuracy: 0.3333 - F1: 0.2728
sub_6:Test (Best Model) - Loss: 1.7780 - Accuracy: 0.3043 - F1: 0.2608
sub_6:Test (Best Model) - Loss: 1.7771 - Accuracy: 0.3188 - F1: 0.2653
sub_6:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.3043 - F1: 0.2464
sub_6:Test (Best Model) - Loss: 1.6827 - Accuracy: 0.2464 - F1: 0.2475
sub_6:Test (Best Model) - Loss: 1.7941 - Accuracy: 0.3333 - F1: 0.3190
sub_6:Test (Best Model) - Loss: 1.8926 - Accuracy: 0.3333 - F1: 0.3160
sub_6:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.3768 - F1: 0.3710
sub_6:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.3478 - F1: 0.3256
sub_7:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.4559 - F1: 0.4095
sub_7:Test (Best Model) - Loss: 1.7008 - Accuracy: 0.3824 - F1: 0.3654
sub_7:Test (Best Model) - Loss: 1.6972 - Accuracy: 0.2794 - F1: 0.2806
sub_7:Test (Best Model) - Loss: 1.4904 - Accuracy: 0.4265 - F1: 0.4081
sub_7:Test (Best Model) - Loss: 1.6685 - Accuracy: 0.4265 - F1: 0.4054
sub_7:Test (Best Model) - Loss: 1.6587 - Accuracy: 0.2647 - F1: 0.2614
sub_7:Test (Best Model) - Loss: 1.6756 - Accuracy: 0.3235 - F1: 0.3341
sub_7:Test (Best Model) - Loss: 1.5515 - Accuracy: 0.3235 - F1: 0.3263
sub_7:Test (Best Model) - Loss: 1.7103 - Accuracy: 0.2794 - F1: 0.2713
sub_7:Test (Best Model) - Loss: 1.6335 - Accuracy: 0.3824 - F1: 0.3747
sub_7:Test (Best Model) - Loss: 1.6302 - Accuracy: 0.3088 - F1: 0.3112
sub_7:Test (Best Model) - Loss: 1.9102 - Accuracy: 0.3529 - F1: 0.3555
sub_7:Test (Best Model) - Loss: 1.7988 - Accuracy: 0.2794 - F1: 0.2796
sub_7:Test (Best Model) - Loss: 1.9677 - Accuracy: 0.3088 - F1: 0.3125
sub_7:Test (Best Model) - Loss: 1.7053 - Accuracy: 0.3088 - F1: 0.3125
sub_8:Test (Best Model) - Loss: 1.9486 - Accuracy: 0.2206 - F1: 0.2233
sub_8:Test (Best Model) - Loss: 2.0009 - Accuracy: 0.2353 - F1: 0.2265
sub_8:Test (Best Model) - Loss: 2.3385 - Accuracy: 0.2500 - F1: 0.2547
sub_8:Test (Best Model) - Loss: 1.9168 - Accuracy: 0.3088 - F1: 0.3014
sub_8:Test (Best Model) - Loss: 1.9882 - Accuracy: 0.2206 - F1: 0.2238
sub_8:Test (Best Model) - Loss: 1.8077 - Accuracy: 0.3529 - F1: 0.3554
sub_8:Test (Best Model) - Loss: 1.8990 - Accuracy: 0.2059 - F1: 0.2035
sub_8:Test (Best Model) - Loss: 1.5936 - Accuracy: 0.2647 - F1: 0.2545
sub_8:Test (Best Model) - Loss: 1.8713 - Accuracy: 0.1618 - F1: 0.1530
sub_8:Test (Best Model) - Loss: 1.7936 - Accuracy: 0.1912 - F1: 0.1834
sub_8:Test (Best Model) - Loss: 2.0309 - Accuracy: 0.1618 - F1: 0.1277
sub_8:Test (Best Model) - Loss: 2.4690 - Accuracy: 0.2500 - F1: 0.2367
sub_8:Test (Best Model) - Loss: 2.1949 - Accuracy: 0.2794 - F1: 0.2755
sub_8:Test (Best Model) - Loss: 1.9326 - Accuracy: 0.2794 - F1: 0.2737
sub_8:Test (Best Model) - Loss: 1.8679 - Accuracy: 0.2206 - F1: 0.1996
sub_9:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.3382 - F1: 0.3480
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.3971 - F1: 0.4043
sub_9:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.3676 - F1: 0.3962
sub_9:Test (Best Model) - Loss: 1.4875 - Accuracy: 0.3824 - F1: 0.3998
sub_9:Test (Best Model) - Loss: 1.5255 - Accuracy: 0.3235 - F1: 0.3267
sub_9:Test (Best Model) - Loss: 2.4595 - Accuracy: 0.2941 - F1: 0.2944
sub_9:Test (Best Model) - Loss: 2.2571 - Accuracy: 0.3235 - F1: 0.3517
sub_9:Test (Best Model) - Loss: 1.8126 - Accuracy: 0.3529 - F1: 0.3594
sub_9:Test (Best Model) - Loss: 1.6324 - Accuracy: 0.3824 - F1: 0.3828
sub_9:Test (Best Model) - Loss: 1.8866 - Accuracy: 0.3235 - F1: 0.3330
sub_9:Test (Best Model) - Loss: 2.1051 - Accuracy: 0.2500 - F1: 0.2437
sub_9:Test (Best Model) - Loss: 1.8336 - Accuracy: 0.3676 - F1: 0.3771
sub_9:Test (Best Model) - Loss: 1.9528 - Accuracy: 0.2941 - F1: 0.2950
sub_9:Test (Best Model) - Loss: 2.2445 - Accuracy: 0.3382 - F1: 0.3422
sub_9:Test (Best Model) - Loss: 1.9410 - Accuracy: 0.3529 - F1: 0.3702
sub_10:Test (Best Model) - Loss: 1.9783 - Accuracy: 0.2206 - F1: 0.2171
sub_10:Test (Best Model) - Loss: 1.8475 - Accuracy: 0.3235 - F1: 0.3058
sub_10:Test (Best Model) - Loss: 1.7159 - Accuracy: 0.2500 - F1: 0.2404
sub_10:Test (Best Model) - Loss: 1.8120 - Accuracy: 0.2941 - F1: 0.2836
sub_10:Test (Best Model) - Loss: 1.9557 - Accuracy: 0.3088 - F1: 0.3068
sub_10:Test (Best Model) - Loss: 1.8300 - Accuracy: 0.2647 - F1: 0.2463
sub_10:Test (Best Model) - Loss: 2.0396 - Accuracy: 0.2059 - F1: 0.1991
sub_10:Test (Best Model) - Loss: 1.9490 - Accuracy: 0.2353 - F1: 0.2266
sub_10:Test (Best Model) - Loss: 1.6755 - Accuracy: 0.2353 - F1: 0.2335
sub_10:Test (Best Model) - Loss: 1.8155 - Accuracy: 0.2206 - F1: 0.2196
sub_10:Test (Best Model) - Loss: 2.2823 - Accuracy: 0.1884 - F1: 0.1734
sub_10:Test (Best Model) - Loss: 2.0189 - Accuracy: 0.2319 - F1: 0.2315
sub_10:Test (Best Model) - Loss: 1.9462 - Accuracy: 0.2319 - F1: 0.2160
sub_10:Test (Best Model) - Loss: 1.8543 - Accuracy: 0.2754 - F1: 0.2716
sub_10:Test (Best Model) - Loss: 1.8909 - Accuracy: 0.2464 - F1: 0.2282
sub_11:Test (Best Model) - Loss: 1.9601 - Accuracy: 0.2899 - F1: 0.2905
sub_11:Test (Best Model) - Loss: 1.7652 - Accuracy: 0.2899 - F1: 0.2823
sub_11:Test (Best Model) - Loss: 2.0225 - Accuracy: 0.2754 - F1: 0.2733
sub_11:Test (Best Model) - Loss: 1.8216 - Accuracy: 0.2754 - F1: 0.2768
sub_11:Test (Best Model) - Loss: 1.8096 - Accuracy: 0.2754 - F1: 0.2731
sub_11:Test (Best Model) - Loss: 1.8273 - Accuracy: 0.4203 - F1: 0.3699
sub_11:Test (Best Model) - Loss: 1.7239 - Accuracy: 0.3478 - F1: 0.3256
sub_11:Test (Best Model) - Loss: 1.5542 - Accuracy: 0.3188 - F1: 0.3086
sub_11:Test (Best Model) - Loss: 1.8367 - Accuracy: 0.2899 - F1: 0.2838
sub_11:Test (Best Model) - Loss: 1.8288 - Accuracy: 0.3768 - F1: 0.3619
sub_11:Test (Best Model) - Loss: 1.5917 - Accuracy: 0.2899 - F1: 0.2599
sub_11:Test (Best Model) - Loss: 1.9271 - Accuracy: 0.3188 - F1: 0.3166
sub_11:Test (Best Model) - Loss: 1.5456 - Accuracy: 0.3913 - F1: 0.3688
sub_11:Test (Best Model) - Loss: 1.6360 - Accuracy: 0.3188 - F1: 0.2981
sub_11:Test (Best Model) - Loss: 1.6294 - Accuracy: 0.3043 - F1: 0.2856
sub_12:Test (Best Model) - Loss: 1.5532 - Accuracy: 0.3676 - F1: 0.3452
sub_12:Test (Best Model) - Loss: 1.5374 - Accuracy: 0.3529 - F1: 0.3349
sub_12:Test (Best Model) - Loss: 1.7129 - Accuracy: 0.3529 - F1: 0.3419
sub_12:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.3824 - F1: 0.3647
sub_12:Test (Best Model) - Loss: 1.6649 - Accuracy: 0.3088 - F1: 0.3071
sub_12:Test (Best Model) - Loss: 1.8533 - Accuracy: 0.2899 - F1: 0.2755
sub_12:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.3043 - F1: 0.2975
sub_12:Test (Best Model) - Loss: 1.6392 - Accuracy: 0.2609 - F1: 0.2643
sub_12:Test (Best Model) - Loss: 1.6242 - Accuracy: 0.3188 - F1: 0.3034
sub_12:Test (Best Model) - Loss: 1.6468 - Accuracy: 0.3188 - F1: 0.3254
sub_12:Test (Best Model) - Loss: 1.6204 - Accuracy: 0.3824 - F1: 0.3742
sub_12:Test (Best Model) - Loss: 1.8602 - Accuracy: 0.3235 - F1: 0.2963
sub_12:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.2353 - F1: 0.2222
sub_12:Test (Best Model) - Loss: 1.7224 - Accuracy: 0.2794 - F1: 0.2820
sub_12:Test (Best Model) - Loss: 1.5821 - Accuracy: 0.2941 - F1: 0.2810
sub_13:Test (Best Model) - Loss: 2.1306 - Accuracy: 0.3235 - F1: 0.3162
sub_13:Test (Best Model) - Loss: 2.2538 - Accuracy: 0.2206 - F1: 0.2221
sub_13:Test (Best Model) - Loss: 2.0056 - Accuracy: 0.3235 - F1: 0.3196
sub_13:Test (Best Model) - Loss: 1.8828 - Accuracy: 0.2647 - F1: 0.2662
sub_13:Test (Best Model) - Loss: 1.7932 - Accuracy: 0.3529 - F1: 0.3637
sub_13:Test (Best Model) - Loss: 2.0132 - Accuracy: 0.2609 - F1: 0.2550
sub_13:Test (Best Model) - Loss: 1.7655 - Accuracy: 0.2899 - F1: 0.2634
sub_13:Test (Best Model) - Loss: 1.8582 - Accuracy: 0.2174 - F1: 0.2193
sub_13:Test (Best Model) - Loss: 2.0645 - Accuracy: 0.3043 - F1: 0.3012
sub_13:Test (Best Model) - Loss: 1.7759 - Accuracy: 0.2174 - F1: 0.2014
sub_13:Test (Best Model) - Loss: 1.6565 - Accuracy: 0.2941 - F1: 0.2874
sub_13:Test (Best Model) - Loss: 1.7192 - Accuracy: 0.2647 - F1: 0.2757
sub_13:Test (Best Model) - Loss: 2.0799 - Accuracy: 0.2794 - F1: 0.2777
sub_13:Test (Best Model) - Loss: 1.7947 - Accuracy: 0.2647 - F1: 0.2702
sub_13:Test (Best Model) - Loss: 1.7740 - Accuracy: 0.2941 - F1: 0.2838
sub_14:Test (Best Model) - Loss: 1.7238 - Accuracy: 0.1618 - F1: 0.1663
sub_14:Test (Best Model) - Loss: 1.6728 - Accuracy: 0.3088 - F1: 0.3124
sub_14:Test (Best Model) - Loss: 1.6988 - Accuracy: 0.2206 - F1: 0.2201
sub_14:Test (Best Model) - Loss: 1.8610 - Accuracy: 0.2500 - F1: 0.2339
sub_14:Test (Best Model) - Loss: 1.6945 - Accuracy: 0.2647 - F1: 0.2614
sub_14:Test (Best Model) - Loss: 1.9106 - Accuracy: 0.2353 - F1: 0.2183
sub_14:Test (Best Model) - Loss: 1.9274 - Accuracy: 0.3382 - F1: 0.3375
sub_14:Test (Best Model) - Loss: 1.9369 - Accuracy: 0.3235 - F1: 0.3180
sub_14:Test (Best Model) - Loss: 1.9203 - Accuracy: 0.3088 - F1: 0.3040
sub_14:Test (Best Model) - Loss: 1.9011 - Accuracy: 0.2941 - F1: 0.2847
sub_14:Test (Best Model) - Loss: 1.8000 - Accuracy: 0.3529 - F1: 0.3514
sub_14:Test (Best Model) - Loss: 1.6815 - Accuracy: 0.2941 - F1: 0.2843
sub_14:Test (Best Model) - Loss: 1.7785 - Accuracy: 0.2647 - F1: 0.2555
sub_14:Test (Best Model) - Loss: 1.7071 - Accuracy: 0.2353 - F1: 0.2344
sub_14:Test (Best Model) - Loss: 1.7246 - Accuracy: 0.2353 - F1: 0.2317
sub_15:Test (Best Model) - Loss: 1.9548 - Accuracy: 0.2500 - F1: 0.2592
sub_15:Test (Best Model) - Loss: 2.0334 - Accuracy: 0.3088 - F1: 0.3047
sub_15:Test (Best Model) - Loss: 1.9467 - Accuracy: 0.3235 - F1: 0.3335
sub_15:Test (Best Model) - Loss: 1.8293 - Accuracy: 0.3088 - F1: 0.3218
sub_15:Test (Best Model) - Loss: 1.8936 - Accuracy: 0.3529 - F1: 0.3601
sub_15:Test (Best Model) - Loss: 1.5090 - Accuracy: 0.4118 - F1: 0.4190
sub_15:Test (Best Model) - Loss: 2.0350 - Accuracy: 0.3676 - F1: 0.3771
sub_15:Test (Best Model) - Loss: 1.8140 - Accuracy: 0.4559 - F1: 0.4601
sub_15:Test (Best Model) - Loss: 1.5730 - Accuracy: 0.3529 - F1: 0.3523
sub_15:Test (Best Model) - Loss: 1.5619 - Accuracy: 0.3824 - F1: 0.3899
sub_15:Test (Best Model) - Loss: 1.5318 - Accuracy: 0.3824 - F1: 0.3903
sub_15:Test (Best Model) - Loss: 1.5413 - Accuracy: 0.3824 - F1: 0.4038
sub_15:Test (Best Model) - Loss: 1.5807 - Accuracy: 0.2941 - F1: 0.3031
sub_15:Test (Best Model) - Loss: 1.6694 - Accuracy: 0.3676 - F1: 0.3802
sub_15:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2941 - F1: 0.3144
sub_16:Test (Best Model) - Loss: 1.6269 - Accuracy: 0.3088 - F1: 0.2643
sub_16:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2941 - F1: 0.2732
sub_16:Test (Best Model) - Loss: 1.6662 - Accuracy: 0.3382 - F1: 0.3282
sub_16:Test (Best Model) - Loss: 1.6226 - Accuracy: 0.2941 - F1: 0.2934
sub_16:Test (Best Model) - Loss: 1.4178 - Accuracy: 0.3529 - F1: 0.3309
sub_16:Test (Best Model) - Loss: 1.7968 - Accuracy: 0.3382 - F1: 0.3469
sub_16:Test (Best Model) - Loss: 1.7596 - Accuracy: 0.3382 - F1: 0.3378
sub_16:Test (Best Model) - Loss: 1.6407 - Accuracy: 0.2794 - F1: 0.2834
sub_16:Test (Best Model) - Loss: 1.6912 - Accuracy: 0.2941 - F1: 0.2975
sub_16:Test (Best Model) - Loss: 2.7379 - Accuracy: 0.2647 - F1: 0.2780
sub_16:Test (Best Model) - Loss: 1.5389 - Accuracy: 0.2941 - F1: 0.2800
sub_16:Test (Best Model) - Loss: 1.5580 - Accuracy: 0.2794 - F1: 0.2593
sub_16:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.2500 - F1: 0.2389
sub_16:Test (Best Model) - Loss: 1.7272 - Accuracy: 0.3088 - F1: 0.3000
sub_16:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.3235 - F1: 0.3127
sub_17:Test (Best Model) - Loss: 1.4925 - Accuracy: 0.5072 - F1: 0.4876
sub_17:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.3768 - F1: 0.3577
sub_17:Test (Best Model) - Loss: 1.4042 - Accuracy: 0.4058 - F1: 0.3979
sub_17:Test (Best Model) - Loss: 1.5308 - Accuracy: 0.4058 - F1: 0.4003
sub_17:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.3913 - F1: 0.3907
sub_17:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.3768 - F1: 0.3505
sub_17:Test (Best Model) - Loss: 1.7024 - Accuracy: 0.2754 - F1: 0.2433
sub_17:Test (Best Model) - Loss: 1.6733 - Accuracy: 0.4058 - F1: 0.3851
sub_17:Test (Best Model) - Loss: 1.6521 - Accuracy: 0.3768 - F1: 0.3670
sub_17:Test (Best Model) - Loss: 1.7820 - Accuracy: 0.3478 - F1: 0.3333
sub_17:Test (Best Model) - Loss: 1.6319 - Accuracy: 0.4412 - F1: 0.4297
sub_17:Test (Best Model) - Loss: 1.6507 - Accuracy: 0.3971 - F1: 0.3728
sub_17:Test (Best Model) - Loss: 1.8319 - Accuracy: 0.3529 - F1: 0.3348
sub_17:Test (Best Model) - Loss: 1.8659 - Accuracy: 0.3824 - F1: 0.3685
sub_17:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.3088 - F1: 0.2934
sub_18:Test (Best Model) - Loss: 1.7518 - Accuracy: 0.2029 - F1: 0.1967
sub_18:Test (Best Model) - Loss: 1.6328 - Accuracy: 0.3333 - F1: 0.3369
sub_18:Test (Best Model) - Loss: 1.7176 - Accuracy: 0.3188 - F1: 0.3140
sub_18:Test (Best Model) - Loss: 1.6401 - Accuracy: 0.2899 - F1: 0.2993
sub_18:Test (Best Model) - Loss: 1.6242 - Accuracy: 0.3333 - F1: 0.3417
sub_18:Test (Best Model) - Loss: 1.6744 - Accuracy: 0.3235 - F1: 0.3348
sub_18:Test (Best Model) - Loss: 1.6170 - Accuracy: 0.3088 - F1: 0.3088
sub_18:Test (Best Model) - Loss: 1.9213 - Accuracy: 0.2647 - F1: 0.2615
sub_18:Test (Best Model) - Loss: 1.7219 - Accuracy: 0.2647 - F1: 0.2695
sub_18:Test (Best Model) - Loss: 1.7260 - Accuracy: 0.2353 - F1: 0.2467
sub_18:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2941 - F1: 0.2857
sub_18:Test (Best Model) - Loss: 1.7541 - Accuracy: 0.3382 - F1: 0.3378
sub_18:Test (Best Model) - Loss: 1.8279 - Accuracy: 0.2353 - F1: 0.2334
sub_18:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.3088 - F1: 0.3101
sub_18:Test (Best Model) - Loss: 1.6241 - Accuracy: 0.2353 - F1: 0.2439
sub_19:Test (Best Model) - Loss: 1.6349 - Accuracy: 0.2941 - F1: 0.2609
sub_19:Test (Best Model) - Loss: 1.5609 - Accuracy: 0.2794 - F1: 0.2502
sub_19:Test (Best Model) - Loss: 1.6918 - Accuracy: 0.2500 - F1: 0.2493
sub_19:Test (Best Model) - Loss: 1.4857 - Accuracy: 0.3382 - F1: 0.2963
sub_19:Test (Best Model) - Loss: 1.5105 - Accuracy: 0.4118 - F1: 0.3684
sub_19:Test (Best Model) - Loss: 1.8615 - Accuracy: 0.3824 - F1: 0.3615
sub_19:Test (Best Model) - Loss: 1.6968 - Accuracy: 0.2794 - F1: 0.2569
sub_19:Test (Best Model) - Loss: 1.9204 - Accuracy: 0.3088 - F1: 0.2972
sub_19:Test (Best Model) - Loss: 1.7658 - Accuracy: 0.2647 - F1: 0.2504
sub_19:Test (Best Model) - Loss: 1.8516 - Accuracy: 0.3088 - F1: 0.2784
sub_19:Test (Best Model) - Loss: 1.6665 - Accuracy: 0.2500 - F1: 0.2498
sub_19:Test (Best Model) - Loss: 2.0986 - Accuracy: 0.2059 - F1: 0.2252
sub_19:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.3382 - F1: 0.3334
sub_19:Test (Best Model) - Loss: 1.8444 - Accuracy: 0.2647 - F1: 0.2661
sub_19:Test (Best Model) - Loss: 1.6238 - Accuracy: 0.3824 - F1: 0.3942
sub_20:Test (Best Model) - Loss: 1.8709 - Accuracy: 0.3676 - F1: 0.3614
sub_20:Test (Best Model) - Loss: 1.8966 - Accuracy: 0.4118 - F1: 0.4043
sub_20:Test (Best Model) - Loss: 1.7675 - Accuracy: 0.3235 - F1: 0.3291
sub_20:Test (Best Model) - Loss: 1.7515 - Accuracy: 0.2794 - F1: 0.2704
sub_20:Test (Best Model) - Loss: 2.0364 - Accuracy: 0.3676 - F1: 0.3685
sub_20:Test (Best Model) - Loss: 1.6374 - Accuracy: 0.3529 - F1: 0.3509
sub_20:Test (Best Model) - Loss: 1.8364 - Accuracy: 0.3529 - F1: 0.3613
sub_20:Test (Best Model) - Loss: 1.7524 - Accuracy: 0.2647 - F1: 0.2778
sub_20:Test (Best Model) - Loss: 1.7484 - Accuracy: 0.3235 - F1: 0.3262
sub_20:Test (Best Model) - Loss: 1.9464 - Accuracy: 0.3529 - F1: 0.3574
sub_20:Test (Best Model) - Loss: 1.7474 - Accuracy: 0.3623 - F1: 0.3589
sub_20:Test (Best Model) - Loss: 1.6939 - Accuracy: 0.3333 - F1: 0.3242
sub_20:Test (Best Model) - Loss: 1.8099 - Accuracy: 0.3623 - F1: 0.3577
sub_20:Test (Best Model) - Loss: 1.8436 - Accuracy: 0.3333 - F1: 0.3292
sub_20:Test (Best Model) - Loss: 1.7673 - Accuracy: 0.4058 - F1: 0.3930
sub_21:Test (Best Model) - Loss: 1.6338 - Accuracy: 0.3529 - F1: 0.3399
sub_21:Test (Best Model) - Loss: 1.7561 - Accuracy: 0.3382 - F1: 0.3212
sub_21:Test (Best Model) - Loss: 2.0287 - Accuracy: 0.3382 - F1: 0.3353
sub_21:Test (Best Model) - Loss: 1.9856 - Accuracy: 0.2794 - F1: 0.2729
sub_21:Test (Best Model) - Loss: 1.9500 - Accuracy: 0.2794 - F1: 0.2789
sub_21:Test (Best Model) - Loss: 1.8355 - Accuracy: 0.2206 - F1: 0.2056
sub_21:Test (Best Model) - Loss: 1.7874 - Accuracy: 0.2647 - F1: 0.2610
sub_21:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.2647 - F1: 0.2654
sub_21:Test (Best Model) - Loss: 1.7592 - Accuracy: 0.2941 - F1: 0.2857
sub_21:Test (Best Model) - Loss: 1.6420 - Accuracy: 0.2500 - F1: 0.2460
sub_21:Test (Best Model) - Loss: 1.5990 - Accuracy: 0.2353 - F1: 0.2186
sub_21:Test (Best Model) - Loss: 1.8379 - Accuracy: 0.2941 - F1: 0.2874
sub_21:Test (Best Model) - Loss: 1.6580 - Accuracy: 0.2647 - F1: 0.2515
sub_21:Test (Best Model) - Loss: 1.8408 - Accuracy: 0.2059 - F1: 0.2019
sub_21:Test (Best Model) - Loss: 1.6288 - Accuracy: 0.2500 - F1: 0.2489
sub_22:Test (Best Model) - Loss: 1.8940 - Accuracy: 0.3235 - F1: 0.3353
sub_22:Test (Best Model) - Loss: 1.7491 - Accuracy: 0.3088 - F1: 0.2787
sub_22:Test (Best Model) - Loss: 2.0465 - Accuracy: 0.2647 - F1: 0.2799
sub_22:Test (Best Model) - Loss: 1.7064 - Accuracy: 0.2206 - F1: 0.2140
sub_22:Test (Best Model) - Loss: 1.8071 - Accuracy: 0.2647 - F1: 0.2447
sub_22:Test (Best Model) - Loss: 1.6547 - Accuracy: 0.2754 - F1: 0.2470
sub_22:Test (Best Model) - Loss: 1.4909 - Accuracy: 0.3043 - F1: 0.2929
sub_22:Test (Best Model) - Loss: 1.5215 - Accuracy: 0.3623 - F1: 0.3522
sub_22:Test (Best Model) - Loss: 1.5335 - Accuracy: 0.3043 - F1: 0.3156
sub_22:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2754 - F1: 0.2240
sub_22:Test (Best Model) - Loss: 1.5496 - Accuracy: 0.3382 - F1: 0.3587
sub_22:Test (Best Model) - Loss: 1.4740 - Accuracy: 0.2941 - F1: 0.2901
sub_22:Test (Best Model) - Loss: 1.7453 - Accuracy: 0.3088 - F1: 0.2962
sub_22:Test (Best Model) - Loss: 1.6275 - Accuracy: 0.3088 - F1: 0.3132
sub_22:Test (Best Model) - Loss: 1.4834 - Accuracy: 0.3529 - F1: 0.3696
sub_23:Test (Best Model) - Loss: 1.8507 - Accuracy: 0.2174 - F1: 0.2183
sub_23:Test (Best Model) - Loss: 1.6766 - Accuracy: 0.3188 - F1: 0.2986
sub_23:Test (Best Model) - Loss: 1.8490 - Accuracy: 0.2899 - F1: 0.2778
sub_23:Test (Best Model) - Loss: 1.5595 - Accuracy: 0.3623 - F1: 0.3353
sub_23:Test (Best Model) - Loss: 1.7864 - Accuracy: 0.2899 - F1: 0.2783
sub_23:Test (Best Model) - Loss: 1.8033 - Accuracy: 0.2941 - F1: 0.2613
sub_23:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.3088 - F1: 0.3085
sub_23:Test (Best Model) - Loss: 1.6308 - Accuracy: 0.2941 - F1: 0.2875
sub_23:Test (Best Model) - Loss: 1.4591 - Accuracy: 0.2647 - F1: 0.2659
sub_23:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.3235 - F1: 0.2954
sub_23:Test (Best Model) - Loss: 2.5018 - Accuracy: 0.2319 - F1: 0.1845
sub_23:Test (Best Model) - Loss: 2.2786 - Accuracy: 0.2754 - F1: 0.2536
sub_23:Test (Best Model) - Loss: 2.0386 - Accuracy: 0.3043 - F1: 0.2794
sub_23:Test (Best Model) - Loss: 2.3803 - Accuracy: 0.2464 - F1: 0.2269
sub_23:Test (Best Model) - Loss: 2.2692 - Accuracy: 0.3188 - F1: 0.2564
sub_24:Test (Best Model) - Loss: 1.9341 - Accuracy: 0.3382 - F1: 0.3393
sub_24:Test (Best Model) - Loss: 1.7306 - Accuracy: 0.3235 - F1: 0.3221
sub_24:Test (Best Model) - Loss: 1.8652 - Accuracy: 0.2353 - F1: 0.2315
sub_24:Test (Best Model) - Loss: 1.7885 - Accuracy: 0.3088 - F1: 0.2966
sub_24:Test (Best Model) - Loss: 1.8688 - Accuracy: 0.3088 - F1: 0.3087
sub_24:Test (Best Model) - Loss: 1.5898 - Accuracy: 0.2647 - F1: 0.2613
sub_24:Test (Best Model) - Loss: 1.6608 - Accuracy: 0.3235 - F1: 0.3188
sub_24:Test (Best Model) - Loss: 1.4845 - Accuracy: 0.2941 - F1: 0.2934
sub_24:Test (Best Model) - Loss: 1.5544 - Accuracy: 0.3676 - F1: 0.3423
sub_24:Test (Best Model) - Loss: 1.6333 - Accuracy: 0.2647 - F1: 0.2517
sub_24:Test (Best Model) - Loss: 1.8617 - Accuracy: 0.2794 - F1: 0.2943
sub_24:Test (Best Model) - Loss: 1.7653 - Accuracy: 0.2206 - F1: 0.2241
sub_24:Test (Best Model) - Loss: 1.7895 - Accuracy: 0.2500 - F1: 0.2474
sub_24:Test (Best Model) - Loss: 1.8552 - Accuracy: 0.3088 - F1: 0.3136
sub_24:Test (Best Model) - Loss: 1.8611 - Accuracy: 0.2647 - F1: 0.2657
sub_25:Test (Best Model) - Loss: 1.6231 - Accuracy: 0.2609 - F1: 0.2383
sub_25:Test (Best Model) - Loss: 1.8260 - Accuracy: 0.2609 - F1: 0.2418
sub_25:Test (Best Model) - Loss: 1.7726 - Accuracy: 0.3768 - F1: 0.3663
sub_25:Test (Best Model) - Loss: 1.8308 - Accuracy: 0.3333 - F1: 0.3211
sub_25:Test (Best Model) - Loss: 1.9873 - Accuracy: 0.2754 - F1: 0.2460
sub_25:Test (Best Model) - Loss: 1.5080 - Accuracy: 0.3676 - F1: 0.3280
sub_25:Test (Best Model) - Loss: 1.7010 - Accuracy: 0.3088 - F1: 0.2764
sub_25:Test (Best Model) - Loss: 1.5142 - Accuracy: 0.3529 - F1: 0.3389
sub_25:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.4118 - F1: 0.3706
sub_25:Test (Best Model) - Loss: 1.4631 - Accuracy: 0.3824 - F1: 0.3513
sub_25:Test (Best Model) - Loss: 1.6514 - Accuracy: 0.2794 - F1: 0.2999
sub_25:Test (Best Model) - Loss: 1.5615 - Accuracy: 0.3529 - F1: 0.3514
sub_25:Test (Best Model) - Loss: 1.5657 - Accuracy: 0.3529 - F1: 0.3213
sub_25:Test (Best Model) - Loss: 1.6527 - Accuracy: 0.2500 - F1: 0.2288
sub_25:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.3088 - F1: 0.2617
sub_26:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.4058 - F1: 0.4011
sub_26:Test (Best Model) - Loss: 1.7363 - Accuracy: 0.3913 - F1: 0.3773
sub_26:Test (Best Model) - Loss: 1.7081 - Accuracy: 0.3913 - F1: 0.3855
sub_26:Test (Best Model) - Loss: 1.4361 - Accuracy: 0.3768 - F1: 0.3842
sub_26:Test (Best Model) - Loss: 1.5113 - Accuracy: 0.4058 - F1: 0.3904
sub_26:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.3088 - F1: 0.3017
sub_26:Test (Best Model) - Loss: 1.6466 - Accuracy: 0.3529 - F1: 0.3499
sub_26:Test (Best Model) - Loss: 1.4250 - Accuracy: 0.3235 - F1: 0.3122
sub_26:Test (Best Model) - Loss: 1.4060 - Accuracy: 0.3971 - F1: 0.3962
sub_26:Test (Best Model) - Loss: 1.5340 - Accuracy: 0.2794 - F1: 0.3019
sub_26:Test (Best Model) - Loss: 1.4350 - Accuracy: 0.4118 - F1: 0.4160
sub_26:Test (Best Model) - Loss: 1.7079 - Accuracy: 0.4265 - F1: 0.4320
sub_26:Test (Best Model) - Loss: 1.6963 - Accuracy: 0.3824 - F1: 0.3804
sub_26:Test (Best Model) - Loss: 1.5508 - Accuracy: 0.4559 - F1: 0.4579
sub_26:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.3824 - F1: 0.4008
sub_27:Test (Best Model) - Loss: 1.4925 - Accuracy: 0.5072 - F1: 0.4876
sub_27:Test (Best Model) - Loss: 1.4023 - Accuracy: 0.3768 - F1: 0.3577
sub_27:Test (Best Model) - Loss: 1.4042 - Accuracy: 0.4058 - F1: 0.3979
sub_27:Test (Best Model) - Loss: 1.5308 - Accuracy: 0.4058 - F1: 0.4003
sub_27:Test (Best Model) - Loss: 1.3918 - Accuracy: 0.3913 - F1: 0.3907
sub_27:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.3768 - F1: 0.3505
sub_27:Test (Best Model) - Loss: 1.7024 - Accuracy: 0.2754 - F1: 0.2433
sub_27:Test (Best Model) - Loss: 1.6733 - Accuracy: 0.4058 - F1: 0.3851
sub_27:Test (Best Model) - Loss: 1.6521 - Accuracy: 0.3768 - F1: 0.3670
sub_27:Test (Best Model) - Loss: 1.7820 - Accuracy: 0.3478 - F1: 0.3333
sub_27:Test (Best Model) - Loss: 1.6319 - Accuracy: 0.4412 - F1: 0.4297
sub_27:Test (Best Model) - Loss: 1.6507 - Accuracy: 0.3971 - F1: 0.3728
sub_27:Test (Best Model) - Loss: 1.8319 - Accuracy: 0.3529 - F1: 0.3348
sub_27:Test (Best Model) - Loss: 1.8659 - Accuracy: 0.3824 - F1: 0.3685
sub_27:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.3088 - F1: 0.2934
sub_28:Test (Best Model) - Loss: 1.8548 - Accuracy: 0.2353 - F1: 0.2319
sub_28:Test (Best Model) - Loss: 1.9475 - Accuracy: 0.2941 - F1: 0.2789
sub_28:Test (Best Model) - Loss: 1.9872 - Accuracy: 0.2647 - F1: 0.2462
sub_28:Test (Best Model) - Loss: 1.7232 - Accuracy: 0.1765 - F1: 0.1708
sub_28:Test (Best Model) - Loss: 1.8041 - Accuracy: 0.2353 - F1: 0.2187
sub_28:Test (Best Model) - Loss: 2.1840 - Accuracy: 0.2500 - F1: 0.2300
sub_28:Test (Best Model) - Loss: 2.4039 - Accuracy: 0.2500 - F1: 0.2435
sub_28:Test (Best Model) - Loss: 2.4888 - Accuracy: 0.2206 - F1: 0.2198
sub_28:Test (Best Model) - Loss: 2.3493 - Accuracy: 0.2647 - F1: 0.2560
sub_28:Test (Best Model) - Loss: 2.2601 - Accuracy: 0.3382 - F1: 0.3312
sub_28:Test (Best Model) - Loss: 1.5506 - Accuracy: 0.2353 - F1: 0.2266
sub_28:Test (Best Model) - Loss: 1.5567 - Accuracy: 0.3529 - F1: 0.3323
sub_28:Test (Best Model) - Loss: 1.4541 - Accuracy: 0.2941 - F1: 0.2793
sub_28:Test (Best Model) - Loss: 1.5580 - Accuracy: 0.3088 - F1: 0.2965
sub_28:Test (Best Model) - Loss: 1.5055 - Accuracy: 0.2353 - F1: 0.2144
sub_29:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.4265 - F1: 0.4501
sub_29:Test (Best Model) - Loss: 1.8724 - Accuracy: 0.3382 - F1: 0.3416
sub_29:Test (Best Model) - Loss: 1.5442 - Accuracy: 0.3824 - F1: 0.3888
sub_29:Test (Best Model) - Loss: 1.6801 - Accuracy: 0.3529 - F1: 0.3661
sub_29:Test (Best Model) - Loss: 1.5508 - Accuracy: 0.4118 - F1: 0.4220
sub_29:Test (Best Model) - Loss: 1.5611 - Accuracy: 0.4118 - F1: 0.4318
sub_29:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.3529 - F1: 0.3438
sub_29:Test (Best Model) - Loss: 1.7175 - Accuracy: 0.3382 - F1: 0.3605
sub_29:Test (Best Model) - Loss: 1.4112 - Accuracy: 0.4118 - F1: 0.4376
sub_29:Test (Best Model) - Loss: 1.4661 - Accuracy: 0.2941 - F1: 0.3067
sub_29:Test (Best Model) - Loss: 1.7122 - Accuracy: 0.3913 - F1: 0.4029
sub_29:Test (Best Model) - Loss: 1.6548 - Accuracy: 0.3478 - F1: 0.3616
sub_29:Test (Best Model) - Loss: 1.7674 - Accuracy: 0.3188 - F1: 0.3107
sub_29:Test (Best Model) - Loss: 1.6388 - Accuracy: 0.4348 - F1: 0.4500
sub_29:Test (Best Model) - Loss: 1.5010 - Accuracy: 0.4638 - F1: 0.4872

=== Summary Results ===

acc: 31.38 ± 4.09
F1: 30.56 ± 4.33
acc-in: 37.34 ± 3.70
F1-in: 35.99 ± 3.81
