lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.4536 - Accuracy: 0.7812 - F1: 0.7758
sub_1:Test (Best Model) - Loss: 0.3780 - Accuracy: 0.7812 - F1: 0.7793
sub_1:Test (Best Model) - Loss: 0.9322 - Accuracy: 0.7188 - F1: 0.7163
sub_1:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.9062 - F1: 0.9039
sub_1:Test (Best Model) - Loss: 0.9053 - Accuracy: 0.7500 - F1: 0.7091
sub_1:Test (Best Model) - Loss: 0.3912 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 1.1417 - Accuracy: 0.7273 - F1: 0.7102
sub_1:Test (Best Model) - Loss: 1.4161 - Accuracy: 0.7273 - F1: 0.6857
sub_1:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.8182 - F1: 0.8036
sub_1:Test (Best Model) - Loss: 0.5403 - Accuracy: 0.8438 - F1: 0.8424
sub_1:Test (Best Model) - Loss: 0.4793 - Accuracy: 0.8438 - F1: 0.8398
sub_1:Test (Best Model) - Loss: 0.0812 - Accuracy: 0.9375 - F1: 0.9365
sub_1:Test (Best Model) - Loss: 0.2774 - Accuracy: 0.9062 - F1: 0.9015
sub_1:Test (Best Model) - Loss: 0.8758 - Accuracy: 0.8750 - F1: 0.8667
sub_2:Test (Best Model) - Loss: 1.2826 - Accuracy: 0.7273 - F1: 0.7273
sub_2:Test (Best Model) - Loss: 1.6214 - Accuracy: 0.7879 - F1: 0.7806
sub_2:Test (Best Model) - Loss: 2.4202 - Accuracy: 0.6970 - F1: 0.6726
sub_2:Test (Best Model) - Loss: 1.6372 - Accuracy: 0.7273 - F1: 0.6997
sub_2:Test (Best Model) - Loss: 2.1065 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 1.5170 - Accuracy: 0.5312 - F1: 0.4910
sub_2:Test (Best Model) - Loss: 2.4522 - Accuracy: 0.5312 - F1: 0.5308
sub_2:Test (Best Model) - Loss: 1.3536 - Accuracy: 0.6875 - F1: 0.6863
sub_2:Test (Best Model) - Loss: 0.5660 - Accuracy: 0.7188 - F1: 0.7117
sub_2:Test (Best Model) - Loss: 0.8400 - Accuracy: 0.6250 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 1.1282 - Accuracy: 0.6667 - F1: 0.6617
sub_2:Test (Best Model) - Loss: 2.6941 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.8824 - Accuracy: 0.6364 - F1: 0.6360
sub_2:Test (Best Model) - Loss: 1.7198 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.9306 - Accuracy: 0.6970 - F1: 0.6944
sub_3:Test (Best Model) - Loss: 1.8999 - Accuracy: 0.5000 - F1: 0.4459
sub_3:Test (Best Model) - Loss: 1.5122 - Accuracy: 0.6250 - F1: 0.6113
sub_3:Test (Best Model) - Loss: 1.3916 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 1.7254 - Accuracy: 0.6562 - F1: 0.6390
sub_3:Test (Best Model) - Loss: 1.5151 - Accuracy: 0.6250 - F1: 0.6190
sub_3:Test (Best Model) - Loss: 1.2038 - Accuracy: 0.6061 - F1: 0.6002
sub_3:Test (Best Model) - Loss: 1.5220 - Accuracy: 0.6061 - F1: 0.5460
sub_3:Test (Best Model) - Loss: 1.1231 - Accuracy: 0.5455 - F1: 0.5438
sub_3:Test (Best Model) - Loss: 1.3204 - Accuracy: 0.6364 - F1: 0.5696
sub_3:Test (Best Model) - Loss: 1.4127 - Accuracy: 0.4545 - F1: 0.4500
sub_3:Test (Best Model) - Loss: 3.4254 - Accuracy: 0.4848 - F1: 0.4527
sub_3:Test (Best Model) - Loss: 2.7334 - Accuracy: 0.4242 - F1: 0.3660
sub_3:Test (Best Model) - Loss: 2.5817 - Accuracy: 0.4848 - F1: 0.4063
sub_3:Test (Best Model) - Loss: 2.7228 - Accuracy: 0.5455 - F1: 0.5171
sub_3:Test (Best Model) - Loss: 3.1332 - Accuracy: 0.4545 - F1: 0.4417
sub_4:Test (Best Model) - Loss: 1.3583 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.8182 - F1: 0.8139
sub_4:Test (Best Model) - Loss: 0.8820 - Accuracy: 0.7576 - F1: 0.7381
sub_4:Test (Best Model) - Loss: 0.2896 - Accuracy: 0.8788 - F1: 0.8731
sub_4:Test (Best Model) - Loss: 0.7241 - Accuracy: 0.9091 - F1: 0.9060
sub_4:Test (Best Model) - Loss: 1.2044 - Accuracy: 0.6667 - F1: 0.5935
sub_4:Test (Best Model) - Loss: 1.3214 - Accuracy: 0.6970 - F1: 0.6726
sub_4:Test (Best Model) - Loss: 0.8105 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 1.3230 - Accuracy: 0.6364 - F1: 0.6360
sub_4:Test (Best Model) - Loss: 2.8442 - Accuracy: 0.5758 - F1: 0.4978
sub_4:Test (Best Model) - Loss: 0.3797 - Accuracy: 0.8182 - F1: 0.8096
sub_4:Test (Best Model) - Loss: 0.5054 - Accuracy: 0.7576 - F1: 0.7462
sub_4:Test (Best Model) - Loss: 0.2958 - Accuracy: 0.8788 - F1: 0.8759
sub_4:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.7879 - F1: 0.7847
sub_4:Test (Best Model) - Loss: 0.7443 - Accuracy: 0.8182 - F1: 0.8180
sub_5:Test (Best Model) - Loss: 2.5105 - Accuracy: 0.5000 - F1: 0.4980
sub_5:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 3.1575 - Accuracy: 0.6562 - F1: 0.6532
sub_5:Test (Best Model) - Loss: 1.8708 - Accuracy: 0.6562 - F1: 0.6559
sub_5:Test (Best Model) - Loss: 1.7356 - Accuracy: 0.5312 - F1: 0.5308
sub_5:Test (Best Model) - Loss: 0.8825 - Accuracy: 0.5625 - F1: 0.5556
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.7812 - F1: 0.7625
sub_5:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.6562 - F1: 0.6476
sub_5:Test (Best Model) - Loss: 0.9523 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 0.7471 - Accuracy: 0.6875 - F1: 0.6761
sub_5:Test (Best Model) - Loss: 1.4384 - Accuracy: 0.6250 - F1: 0.6235
sub_5:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.5625 - F1: 0.5608
sub_5:Test (Best Model) - Loss: 1.9718 - Accuracy: 0.4375 - F1: 0.3766
sub_5:Test (Best Model) - Loss: 1.7541 - Accuracy: 0.5938 - F1: 0.5901
sub_5:Test (Best Model) - Loss: 2.0104 - Accuracy: 0.5938 - F1: 0.5934
sub_6:Test (Best Model) - Loss: 1.5772 - Accuracy: 0.7188 - F1: 0.6811
sub_6:Test (Best Model) - Loss: 1.0327 - Accuracy: 0.7500 - F1: 0.7229
sub_6:Test (Best Model) - Loss: 1.4998 - Accuracy: 0.7500 - F1: 0.7091
sub_6:Test (Best Model) - Loss: 1.0609 - Accuracy: 0.6875 - F1: 0.6761
sub_6:Test (Best Model) - Loss: 0.7721 - Accuracy: 0.6875 - F1: 0.6825
sub_6:Test (Best Model) - Loss: 1.6908 - Accuracy: 0.5758 - F1: 0.5417
sub_6:Test (Best Model) - Loss: 2.7464 - Accuracy: 0.5152 - F1: 0.4261
sub_6:Test (Best Model) - Loss: 2.7073 - Accuracy: 0.5152 - F1: 0.3889
sub_6:Test (Best Model) - Loss: 3.2630 - Accuracy: 0.4848 - F1: 0.4063
sub_6:Test (Best Model) - Loss: 1.6655 - Accuracy: 0.6061 - F1: 0.5926
sub_6:Test (Best Model) - Loss: 0.9099 - Accuracy: 0.7576 - F1: 0.7381
sub_6:Test (Best Model) - Loss: 1.4402 - Accuracy: 0.5758 - F1: 0.5558
sub_6:Test (Best Model) - Loss: 1.1181 - Accuracy: 0.6970 - F1: 0.6827
sub_6:Test (Best Model) - Loss: 1.2153 - Accuracy: 0.7273 - F1: 0.7102
sub_6:Test (Best Model) - Loss: 1.3722 - Accuracy: 0.6667 - F1: 0.6159
sub_7:Test (Best Model) - Loss: 0.9126 - Accuracy: 0.7188 - F1: 0.6946
sub_7:Test (Best Model) - Loss: 1.3955 - Accuracy: 0.5625 - F1: 0.5152
sub_7:Test (Best Model) - Loss: 2.5580 - Accuracy: 0.5312 - F1: 0.5077
sub_7:Test (Best Model) - Loss: 1.5021 - Accuracy: 0.6250 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 1.4767 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 2.6860 - Accuracy: 0.4375 - F1: 0.4375
sub_7:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.4375 - F1: 0.4353
sub_7:Test (Best Model) - Loss: 1.4973 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 2.4117 - Accuracy: 0.4688 - F1: 0.4555
sub_7:Test (Best Model) - Loss: 1.9662 - Accuracy: 0.5000 - F1: 0.4921
sub_7:Test (Best Model) - Loss: 1.2337 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 2.0497 - Accuracy: 0.5000 - F1: 0.4980
sub_7:Test (Best Model) - Loss: 2.3217 - Accuracy: 0.5625 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.9508 - Accuracy: 0.7188 - F1: 0.7117
sub_7:Test (Best Model) - Loss: 1.0842 - Accuracy: 0.6562 - F1: 0.6532
sub_8:Test (Best Model) - Loss: 1.7532 - Accuracy: 0.6250 - F1: 0.5844
sub_8:Test (Best Model) - Loss: 1.8818 - Accuracy: 0.6875 - F1: 0.6364
sub_8:Test (Best Model) - Loss: 1.4799 - Accuracy: 0.6562 - F1: 0.6476
sub_8:Test (Best Model) - Loss: 1.7578 - Accuracy: 0.7812 - F1: 0.7519
sub_8:Test (Best Model) - Loss: 1.6980 - Accuracy: 0.7500 - F1: 0.7229
sub_8:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.8438 - F1: 0.8303
sub_8:Test (Best Model) - Loss: 1.9430 - Accuracy: 0.6875 - F1: 0.6761
sub_8:Test (Best Model) - Loss: 1.1613 - Accuracy: 0.7188 - F1: 0.7046
sub_8:Test (Best Model) - Loss: 1.4664 - Accuracy: 0.7500 - F1: 0.7333
sub_8:Test (Best Model) - Loss: 1.1757 - Accuracy: 0.7188 - F1: 0.6811
sub_8:Test (Best Model) - Loss: 1.1510 - Accuracy: 0.6562 - F1: 0.6559
sub_8:Test (Best Model) - Loss: 0.9757 - Accuracy: 0.6562 - F1: 0.6390
sub_8:Test (Best Model) - Loss: 0.4688 - Accuracy: 0.8125 - F1: 0.8095
sub_8:Test (Best Model) - Loss: 0.9697 - Accuracy: 0.7188 - F1: 0.7185
sub_8:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.8125 - F1: 0.8057
sub_9:Test (Best Model) - Loss: 0.2024 - Accuracy: 0.8750 - F1: 0.8730
sub_9:Test (Best Model) - Loss: 0.8904 - Accuracy: 0.8438 - F1: 0.8303
sub_9:Test (Best Model) - Loss: 0.3940 - Accuracy: 0.8750 - F1: 0.8704
sub_9:Test (Best Model) - Loss: 0.2389 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.9062 - F1: 0.9015
sub_9:Test (Best Model) - Loss: 1.2616 - Accuracy: 0.7812 - F1: 0.7793
sub_9:Test (Best Model) - Loss: 0.9882 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 1.0399 - Accuracy: 0.5938 - F1: 0.5901
sub_9:Test (Best Model) - Loss: 0.9364 - Accuracy: 0.6875 - F1: 0.6825
sub_9:Test (Best Model) - Loss: 0.3213 - Accuracy: 0.8125 - F1: 0.8125
sub_9:Test (Best Model) - Loss: 1.9240 - Accuracy: 0.8438 - F1: 0.8436
sub_9:Test (Best Model) - Loss: 1.1284 - Accuracy: 0.7812 - F1: 0.7758
sub_9:Test (Best Model) - Loss: 1.6738 - Accuracy: 0.7500 - F1: 0.7490
sub_9:Test (Best Model) - Loss: 1.7880 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.8750 - F1: 0.8704
sub_10:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.5312 - F1: 0.4386
sub_10:Test (Best Model) - Loss: 1.5852 - Accuracy: 0.5000 - F1: 0.4182
sub_10:Test (Best Model) - Loss: 0.7264 - Accuracy: 0.7188 - F1: 0.7046
sub_10:Test (Best Model) - Loss: 1.4408 - Accuracy: 0.5625 - F1: 0.5152
sub_10:Test (Best Model) - Loss: 2.0130 - Accuracy: 0.5312 - F1: 0.5271
sub_10:Test (Best Model) - Loss: 1.9320 - Accuracy: 0.5625 - F1: 0.5608
sub_10:Test (Best Model) - Loss: 1.4374 - Accuracy: 0.6562 - F1: 0.6267
sub_10:Test (Best Model) - Loss: 1.6469 - Accuracy: 0.5938 - F1: 0.5901
sub_10:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.5000 - F1: 0.4818
sub_10:Test (Best Model) - Loss: 2.5269 - Accuracy: 0.5312 - F1: 0.5077
sub_10:Test (Best Model) - Loss: 2.0269 - Accuracy: 0.5455 - F1: 0.5438
sub_10:Test (Best Model) - Loss: 2.0636 - Accuracy: 0.5758 - F1: 0.5658
sub_10:Test (Best Model) - Loss: 1.3562 - Accuracy: 0.5758 - F1: 0.5754
sub_10:Test (Best Model) - Loss: 1.5082 - Accuracy: 0.6667 - F1: 0.6553
sub_10:Test (Best Model) - Loss: 1.9138 - Accuracy: 0.5152 - F1: 0.5038
sub_11:Test (Best Model) - Loss: 3.2043 - Accuracy: 0.4848 - F1: 0.4328
sub_11:Test (Best Model) - Loss: 2.8485 - Accuracy: 0.3636 - F1: 0.3541
sub_11:Test (Best Model) - Loss: 2.3084 - Accuracy: 0.3939 - F1: 0.3934
sub_11:Test (Best Model) - Loss: 2.7280 - Accuracy: 0.5152 - F1: 0.5111
sub_11:Test (Best Model) - Loss: 2.2913 - Accuracy: 0.4848 - F1: 0.4527
sub_11:Test (Best Model) - Loss: 1.4887 - Accuracy: 0.6061 - F1: 0.4850
sub_11:Test (Best Model) - Loss: 2.1132 - Accuracy: 0.5758 - F1: 0.4978
sub_11:Test (Best Model) - Loss: 1.3622 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 1.9536 - Accuracy: 0.5152 - F1: 0.4923
sub_11:Test (Best Model) - Loss: 3.2096 - Accuracy: 0.5455 - F1: 0.3529
sub_11:Test (Best Model) - Loss: 2.5288 - Accuracy: 0.4848 - F1: 0.3265
sub_11:Test (Best Model) - Loss: 0.8563 - Accuracy: 0.6667 - F1: 0.6330
sub_11:Test (Best Model) - Loss: 1.6767 - Accuracy: 0.5758 - F1: 0.5227
sub_11:Test (Best Model) - Loss: 1.4097 - Accuracy: 0.6061 - F1: 0.5662
sub_11:Test (Best Model) - Loss: 2.1939 - Accuracy: 0.5758 - F1: 0.4653
sub_12:Test (Best Model) - Loss: 0.9220 - Accuracy: 0.7188 - F1: 0.6946
sub_12:Test (Best Model) - Loss: 0.4637 - Accuracy: 0.8750 - F1: 0.8730
sub_12:Test (Best Model) - Loss: 1.0448 - Accuracy: 0.8125 - F1: 0.7922
sub_12:Test (Best Model) - Loss: 0.8146 - Accuracy: 0.7812 - F1: 0.7703
sub_12:Test (Best Model) - Loss: 1.4098 - Accuracy: 0.7812 - F1: 0.7519
sub_12:Test (Best Model) - Loss: 0.9722 - Accuracy: 0.7879 - F1: 0.7664
sub_12:Test (Best Model) - Loss: 1.1795 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.9077 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 0.6619 - Accuracy: 0.7576 - F1: 0.7273
sub_12:Test (Best Model) - Loss: 0.8657 - Accuracy: 0.7273 - F1: 0.6857
sub_12:Test (Best Model) - Loss: 1.3800 - Accuracy: 0.7188 - F1: 0.7046
sub_12:Test (Best Model) - Loss: 1.7114 - Accuracy: 0.6250 - F1: 0.5844
sub_12:Test (Best Model) - Loss: 1.3151 - Accuracy: 0.7188 - F1: 0.7163
sub_12:Test (Best Model) - Loss: 1.5012 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 1.0922 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.3649 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.3249 - Accuracy: 0.9375 - F1: 0.9352
sub_13:Test (Best Model) - Loss: 0.9648 - Accuracy: 0.7500 - F1: 0.7091
sub_13:Test (Best Model) - Loss: 0.1757 - Accuracy: 0.9062 - F1: 0.9039
sub_13:Test (Best Model) - Loss: 0.2047 - Accuracy: 0.9062 - F1: 0.9015
sub_13:Test (Best Model) - Loss: 0.7071 - Accuracy: 0.8788 - F1: 0.8759
sub_13:Test (Best Model) - Loss: 0.4700 - Accuracy: 0.8182 - F1: 0.8139
sub_13:Test (Best Model) - Loss: 0.2421 - Accuracy: 0.8788 - F1: 0.8731
sub_13:Test (Best Model) - Loss: 0.3805 - Accuracy: 0.8788 - F1: 0.8731
sub_13:Test (Best Model) - Loss: 1.3262 - Accuracy: 0.7576 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.4042 - Accuracy: 0.9062 - F1: 0.9062
sub_13:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.8125 - F1: 0.8057
sub_13:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.8750 - F1: 0.8745
sub_13:Test (Best Model) - Loss: 0.4991 - Accuracy: 0.8750 - F1: 0.8745
sub_13:Test (Best Model) - Loss: 0.7204 - Accuracy: 0.8750 - F1: 0.8745
sub_14:Test (Best Model) - Loss: 0.7451 - Accuracy: 0.6875 - F1: 0.6863
sub_14:Test (Best Model) - Loss: 0.9125 - Accuracy: 0.7500 - F1: 0.7333
sub_14:Test (Best Model) - Loss: 0.5857 - Accuracy: 0.8125 - F1: 0.8057
sub_14:Test (Best Model) - Loss: 0.6734 - Accuracy: 0.6875 - F1: 0.6875
sub_14:Test (Best Model) - Loss: 0.1625 - Accuracy: 0.9688 - F1: 0.9685
sub_14:Test (Best Model) - Loss: 0.4919 - Accuracy: 0.7812 - F1: 0.7758
sub_14:Test (Best Model) - Loss: 0.7375 - Accuracy: 0.8125 - F1: 0.8095
sub_14:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.6875 - F1: 0.6667
sub_14:Test (Best Model) - Loss: 0.3831 - Accuracy: 0.8438 - F1: 0.8424
sub_14:Test (Best Model) - Loss: 1.1722 - Accuracy: 0.6250 - F1: 0.5636
sub_14:Test (Best Model) - Loss: 0.9111 - Accuracy: 0.6562 - F1: 0.5594
sub_14:Test (Best Model) - Loss: 1.8130 - Accuracy: 0.6250 - F1: 0.5362
sub_14:Test (Best Model) - Loss: 1.5263 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 1.0857 - Accuracy: 0.6562 - F1: 0.6390
sub_14:Test (Best Model) - Loss: 1.3606 - Accuracy: 0.7812 - F1: 0.7519
sub_15:Test (Best Model) - Loss: 2.7228 - Accuracy: 0.7812 - F1: 0.7625
sub_15:Test (Best Model) - Loss: 1.5059 - Accuracy: 0.7188 - F1: 0.7163
sub_15:Test (Best Model) - Loss: 1.8886 - Accuracy: 0.7500 - F1: 0.7409
sub_15:Test (Best Model) - Loss: 1.7545 - Accuracy: 0.7188 - F1: 0.7185
sub_15:Test (Best Model) - Loss: 1.2065 - Accuracy: 0.7812 - F1: 0.7810
sub_15:Test (Best Model) - Loss: 0.9020 - Accuracy: 0.7812 - F1: 0.7758
sub_15:Test (Best Model) - Loss: 2.6766 - Accuracy: 0.5000 - F1: 0.5000
sub_15:Test (Best Model) - Loss: 2.4202 - Accuracy: 0.5938 - F1: 0.5934
sub_15:Test (Best Model) - Loss: 1.1328 - Accuracy: 0.7812 - F1: 0.7758
sub_15:Test (Best Model) - Loss: 2.5868 - Accuracy: 0.6250 - F1: 0.6190
sub_15:Test (Best Model) - Loss: 1.2471 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 1.7690 - Accuracy: 0.4062 - F1: 0.4057
sub_15:Test (Best Model) - Loss: 2.1200 - Accuracy: 0.5000 - F1: 0.4921
sub_15:Test (Best Model) - Loss: 1.4249 - Accuracy: 0.6562 - F1: 0.6390
sub_15:Test (Best Model) - Loss: 1.3567 - Accuracy: 0.6250 - F1: 0.6190
sub_16:Test (Best Model) - Loss: 1.3663 - Accuracy: 0.6250 - F1: 0.6250
sub_16:Test (Best Model) - Loss: 1.9020 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.5625 - F1: 0.5625
sub_16:Test (Best Model) - Loss: 1.1103 - Accuracy: 0.6250 - F1: 0.6235
sub_16:Test (Best Model) - Loss: 1.7433 - Accuracy: 0.5625 - F1: 0.5556
sub_16:Test (Best Model) - Loss: 1.5190 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 1.5337 - Accuracy: 0.6875 - F1: 0.6667
sub_16:Test (Best Model) - Loss: 1.9389 - Accuracy: 0.6875 - F1: 0.6863
sub_16:Test (Best Model) - Loss: 1.4548 - Accuracy: 0.6562 - F1: 0.6532
sub_16:Test (Best Model) - Loss: 2.6361 - Accuracy: 0.6875 - F1: 0.6761
sub_16:Test (Best Model) - Loss: 3.5151 - Accuracy: 0.5625 - F1: 0.5333
sub_16:Test (Best Model) - Loss: 1.6356 - Accuracy: 0.5312 - F1: 0.4684
sub_16:Test (Best Model) - Loss: 1.8969 - Accuracy: 0.5938 - F1: 0.4793
sub_16:Test (Best Model) - Loss: 1.6417 - Accuracy: 0.4375 - F1: 0.4170
sub_16:Test (Best Model) - Loss: 1.8643 - Accuracy: 0.5312 - F1: 0.4386
sub_17:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.5758 - F1: 0.5658
sub_17:Test (Best Model) - Loss: 0.9355 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 1.4359 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 2.3576 - Accuracy: 0.6061 - F1: 0.4850
sub_17:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.6364 - F1: 0.6333
sub_17:Test (Best Model) - Loss: 2.2282 - Accuracy: 0.5152 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 2.0302 - Accuracy: 0.5455 - F1: 0.4762
sub_17:Test (Best Model) - Loss: 2.0575 - Accuracy: 0.5152 - F1: 0.5111
sub_17:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.5455 - F1: 0.5171
sub_17:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.5455 - F1: 0.4995
sub_17:Test (Best Model) - Loss: 1.7470 - Accuracy: 0.3438 - F1: 0.3273
sub_17:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.6250 - F1: 0.5844
sub_17:Test (Best Model) - Loss: 2.3578 - Accuracy: 0.4688 - F1: 0.4682
sub_17:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.5625 - F1: 0.5466
sub_17:Test (Best Model) - Loss: 1.8270 - Accuracy: 0.6562 - F1: 0.6102
sub_18:Test (Best Model) - Loss: 0.7220 - Accuracy: 0.7273 - F1: 0.7232
sub_18:Test (Best Model) - Loss: 0.4876 - Accuracy: 0.7879 - F1: 0.7746
sub_18:Test (Best Model) - Loss: 0.5300 - Accuracy: 0.7879 - F1: 0.7879
sub_18:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.7879 - F1: 0.7746
sub_18:Test (Best Model) - Loss: 0.4348 - Accuracy: 0.8182 - F1: 0.8139
sub_18:Test (Best Model) - Loss: 1.0314 - Accuracy: 0.8125 - F1: 0.7922
sub_18:Test (Best Model) - Loss: 0.7949 - Accuracy: 0.6875 - F1: 0.6761
sub_18:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.5887 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.7714 - Accuracy: 0.7812 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.9062 - F1: 0.9015
sub_18:Test (Best Model) - Loss: 1.2224 - Accuracy: 0.6875 - F1: 0.6364
sub_18:Test (Best Model) - Loss: 0.4834 - Accuracy: 0.8438 - F1: 0.8424
sub_18:Test (Best Model) - Loss: 0.9467 - Accuracy: 0.7500 - F1: 0.7490
sub_18:Test (Best Model) - Loss: 0.5529 - Accuracy: 0.8750 - F1: 0.8745
sub_19:Test (Best Model) - Loss: 3.2614 - Accuracy: 0.5312 - F1: 0.3992
sub_19:Test (Best Model) - Loss: 1.4975 - Accuracy: 0.5938 - F1: 0.5135
sub_19:Test (Best Model) - Loss: 1.1322 - Accuracy: 0.6250 - F1: 0.5844
sub_19:Test (Best Model) - Loss: 3.0033 - Accuracy: 0.5938 - F1: 0.4793
sub_19:Test (Best Model) - Loss: 1.7054 - Accuracy: 0.6250 - F1: 0.5362
sub_19:Test (Best Model) - Loss: 1.8420 - Accuracy: 0.5625 - F1: 0.4909
sub_19:Test (Best Model) - Loss: 1.8715 - Accuracy: 0.5625 - F1: 0.4589
sub_19:Test (Best Model) - Loss: 0.8340 - Accuracy: 0.7188 - F1: 0.6946
sub_19:Test (Best Model) - Loss: 1.3283 - Accuracy: 0.6250 - F1: 0.6000
sub_19:Test (Best Model) - Loss: 1.6893 - Accuracy: 0.5312 - F1: 0.4910
sub_19:Test (Best Model) - Loss: 1.1551 - Accuracy: 0.7188 - F1: 0.7046
sub_19:Test (Best Model) - Loss: 1.8281 - Accuracy: 0.6562 - F1: 0.6532
sub_19:Test (Best Model) - Loss: 1.1647 - Accuracy: 0.5938 - F1: 0.5934
sub_19:Test (Best Model) - Loss: 1.1279 - Accuracy: 0.7500 - F1: 0.7409
sub_19:Test (Best Model) - Loss: 1.5062 - Accuracy: 0.7188 - F1: 0.7046
sub_20:Test (Best Model) - Loss: 2.0281 - Accuracy: 0.6562 - F1: 0.6532
sub_20:Test (Best Model) - Loss: 1.3547 - Accuracy: 0.7188 - F1: 0.6946
sub_20:Test (Best Model) - Loss: 1.7558 - Accuracy: 0.5625 - F1: 0.5556
sub_20:Test (Best Model) - Loss: 1.8886 - Accuracy: 0.6250 - F1: 0.5844
sub_20:Test (Best Model) - Loss: 2.1083 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 2.4408 - Accuracy: 0.5938 - F1: 0.5589
sub_20:Test (Best Model) - Loss: 1.2587 - Accuracy: 0.7500 - F1: 0.7460
sub_20:Test (Best Model) - Loss: 2.0169 - Accuracy: 0.5938 - F1: 0.5836
sub_20:Test (Best Model) - Loss: 1.7403 - Accuracy: 0.6562 - F1: 0.6476
sub_20:Test (Best Model) - Loss: 1.9865 - Accuracy: 0.6562 - F1: 0.6390
sub_20:Test (Best Model) - Loss: 3.0885 - Accuracy: 0.5455 - F1: 0.5299
sub_20:Test (Best Model) - Loss: 3.8355 - Accuracy: 0.5758 - F1: 0.5558
sub_20:Test (Best Model) - Loss: 1.4938 - Accuracy: 0.6667 - F1: 0.6459
sub_20:Test (Best Model) - Loss: 3.1330 - Accuracy: 0.5152 - F1: 0.5111
sub_20:Test (Best Model) - Loss: 2.3648 - Accuracy: 0.7273 - F1: 0.6857
sub_21:Test (Best Model) - Loss: 3.1182 - Accuracy: 0.4062 - F1: 0.4057
sub_21:Test (Best Model) - Loss: 2.8545 - Accuracy: 0.3750 - F1: 0.3725
sub_21:Test (Best Model) - Loss: 3.2406 - Accuracy: 0.4375 - F1: 0.4170
sub_21:Test (Best Model) - Loss: 2.0633 - Accuracy: 0.4375 - F1: 0.3455
sub_21:Test (Best Model) - Loss: 2.2019 - Accuracy: 0.4688 - F1: 0.4640
sub_21:Test (Best Model) - Loss: 2.2669 - Accuracy: 0.4688 - F1: 0.4421
sub_21:Test (Best Model) - Loss: 1.9534 - Accuracy: 0.4062 - F1: 0.3914
sub_21:Test (Best Model) - Loss: 2.1261 - Accuracy: 0.4062 - F1: 0.3764
sub_21:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.5938 - F1: 0.5733
sub_21:Test (Best Model) - Loss: 1.8335 - Accuracy: 0.5625 - F1: 0.5466
sub_21:Test (Best Model) - Loss: 1.8632 - Accuracy: 0.4688 - F1: 0.4555
sub_21:Test (Best Model) - Loss: 2.5571 - Accuracy: 0.5000 - F1: 0.4667
sub_21:Test (Best Model) - Loss: 3.1653 - Accuracy: 0.3750 - F1: 0.3074
sub_21:Test (Best Model) - Loss: 3.1359 - Accuracy: 0.4688 - F1: 0.4682
sub_21:Test (Best Model) - Loss: 2.7918 - Accuracy: 0.4062 - F1: 0.3267
sub_22:Test (Best Model) - Loss: 1.4068 - Accuracy: 0.5938 - F1: 0.5934
sub_22:Test (Best Model) - Loss: 1.5126 - Accuracy: 0.6562 - F1: 0.6267
sub_22:Test (Best Model) - Loss: 0.9750 - Accuracy: 0.7188 - F1: 0.7046
sub_22:Test (Best Model) - Loss: 1.3626 - Accuracy: 0.6875 - F1: 0.6537
sub_22:Test (Best Model) - Loss: 1.0826 - Accuracy: 0.7812 - F1: 0.7758
sub_22:Test (Best Model) - Loss: 1.2381 - Accuracy: 0.7273 - F1: 0.7102
sub_22:Test (Best Model) - Loss: 2.8624 - Accuracy: 0.6061 - F1: 0.4850
sub_22:Test (Best Model) - Loss: 1.1883 - Accuracy: 0.6970 - F1: 0.6726
sub_22:Test (Best Model) - Loss: 1.3366 - Accuracy: 0.6970 - F1: 0.6413
sub_22:Test (Best Model) - Loss: 1.6424 - Accuracy: 0.6364 - F1: 0.5696
sub_22:Test (Best Model) - Loss: 1.7971 - Accuracy: 0.6875 - F1: 0.6135
sub_22:Test (Best Model) - Loss: 0.8574 - Accuracy: 0.8750 - F1: 0.8704
sub_22:Test (Best Model) - Loss: 2.0027 - Accuracy: 0.5938 - F1: 0.4793
sub_22:Test (Best Model) - Loss: 0.7962 - Accuracy: 0.8125 - F1: 0.8057
sub_22:Test (Best Model) - Loss: 1.6629 - Accuracy: 0.6875 - F1: 0.6135
sub_23:Test (Best Model) - Loss: 0.6582 - Accuracy: 0.9091 - F1: 0.9077
sub_23:Test (Best Model) - Loss: 1.0022 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.4689 - Accuracy: 0.7879 - F1: 0.7806
sub_23:Test (Best Model) - Loss: 0.8953 - Accuracy: 0.7273 - F1: 0.6857
sub_23:Test (Best Model) - Loss: 0.3852 - Accuracy: 0.8485 - F1: 0.8433
sub_23:Test (Best Model) - Loss: 1.2883 - Accuracy: 0.5312 - F1: 0.5271
sub_23:Test (Best Model) - Loss: 0.9272 - Accuracy: 0.6875 - F1: 0.6863
sub_23:Test (Best Model) - Loss: 0.5746 - Accuracy: 0.7812 - F1: 0.7810
sub_23:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.7188 - F1: 0.7163
sub_23:Test (Best Model) - Loss: 0.5200 - Accuracy: 0.8438 - F1: 0.8359
sub_23:Test (Best Model) - Loss: 1.0789 - Accuracy: 0.8182 - F1: 0.8096
sub_23:Test (Best Model) - Loss: 1.3884 - Accuracy: 0.7879 - F1: 0.7664
sub_23:Test (Best Model) - Loss: 0.3933 - Accuracy: 0.8182 - F1: 0.8180
sub_23:Test (Best Model) - Loss: 0.8025 - Accuracy: 0.8485 - F1: 0.8433
sub_23:Test (Best Model) - Loss: 0.5354 - Accuracy: 0.8182 - F1: 0.8036
sub_24:Test (Best Model) - Loss: 1.1381 - Accuracy: 0.5625 - F1: 0.5466
sub_24:Test (Best Model) - Loss: 2.0235 - Accuracy: 0.4688 - F1: 0.4682
sub_24:Test (Best Model) - Loss: 1.4439 - Accuracy: 0.5000 - F1: 0.4980
sub_24:Test (Best Model) - Loss: 1.3740 - Accuracy: 0.4688 - F1: 0.4421
sub_24:Test (Best Model) - Loss: 2.4444 - Accuracy: 0.5938 - F1: 0.5901
sub_24:Test (Best Model) - Loss: 1.4148 - Accuracy: 0.7188 - F1: 0.7046
sub_24:Test (Best Model) - Loss: 1.2973 - Accuracy: 0.6562 - F1: 0.6559
sub_24:Test (Best Model) - Loss: 1.6537 - Accuracy: 0.6250 - F1: 0.6113
sub_24:Test (Best Model) - Loss: 0.9058 - Accuracy: 0.6250 - F1: 0.6000
sub_24:Test (Best Model) - Loss: 1.4825 - Accuracy: 0.5312 - F1: 0.4910
sub_24:Test (Best Model) - Loss: 2.1397 - Accuracy: 0.4375 - F1: 0.4375
sub_24:Test (Best Model) - Loss: 1.9070 - Accuracy: 0.4375 - F1: 0.4170
sub_24:Test (Best Model) - Loss: 1.6952 - Accuracy: 0.5625 - F1: 0.5608
sub_24:Test (Best Model) - Loss: 2.4561 - Accuracy: 0.5312 - F1: 0.5308
sub_24:Test (Best Model) - Loss: 2.4070 - Accuracy: 0.5000 - F1: 0.4980
sub_25:Test (Best Model) - Loss: 2.1392 - Accuracy: 0.4545 - F1: 0.3543
sub_25:Test (Best Model) - Loss: 1.7113 - Accuracy: 0.4848 - F1: 0.4772
sub_25:Test (Best Model) - Loss: 2.1924 - Accuracy: 0.5152 - F1: 0.4545
sub_25:Test (Best Model) - Loss: 1.8881 - Accuracy: 0.4848 - F1: 0.4527
sub_25:Test (Best Model) - Loss: 2.7643 - Accuracy: 0.4848 - F1: 0.4328
sub_25:Test (Best Model) - Loss: 1.5139 - Accuracy: 0.6250 - F1: 0.5636
sub_25:Test (Best Model) - Loss: 1.1800 - Accuracy: 0.6250 - F1: 0.6235
sub_25:Test (Best Model) - Loss: 1.8378 - Accuracy: 0.5938 - F1: 0.5836
sub_25:Test (Best Model) - Loss: 1.3048 - Accuracy: 0.6875 - F1: 0.6364
sub_25:Test (Best Model) - Loss: 1.3971 - Accuracy: 0.6250 - F1: 0.5000
sub_25:Test (Best Model) - Loss: 1.2170 - Accuracy: 0.7500 - F1: 0.7333
sub_25:Test (Best Model) - Loss: 1.9395 - Accuracy: 0.6250 - F1: 0.6000
sub_25:Test (Best Model) - Loss: 2.1048 - Accuracy: 0.6250 - F1: 0.5636
sub_25:Test (Best Model) - Loss: 1.7465 - Accuracy: 0.5625 - F1: 0.4589
sub_25:Test (Best Model) - Loss: 1.3870 - Accuracy: 0.5625 - F1: 0.5333
sub_26:Test (Best Model) - Loss: 0.8863 - Accuracy: 0.7273 - F1: 0.7263
sub_26:Test (Best Model) - Loss: 1.9208 - Accuracy: 0.7273 - F1: 0.7102
sub_26:Test (Best Model) - Loss: 1.2343 - Accuracy: 0.7879 - F1: 0.7664
sub_26:Test (Best Model) - Loss: 0.8090 - Accuracy: 0.8182 - F1: 0.8036
sub_26:Test (Best Model) - Loss: 0.3510 - Accuracy: 0.9091 - F1: 0.9060
sub_26:Test (Best Model) - Loss: 1.0461 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.9477 - Accuracy: 0.7812 - F1: 0.7793
sub_26:Test (Best Model) - Loss: 1.0858 - Accuracy: 0.7500 - F1: 0.7490
sub_26:Test (Best Model) - Loss: 1.4118 - Accuracy: 0.7188 - F1: 0.6811
sub_26:Test (Best Model) - Loss: 0.7109 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.1479 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.8695 - Accuracy: 0.7188 - F1: 0.6632
sub_26:Test (Best Model) - Loss: 1.1497 - Accuracy: 0.8125 - F1: 0.7922
sub_26:Test (Best Model) - Loss: 0.2513 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.2840 - Accuracy: 0.9375 - F1: 0.9352
sub_27:Test (Best Model) - Loss: 1.3224 - Accuracy: 0.5758 - F1: 0.5658
sub_27:Test (Best Model) - Loss: 0.9355 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 1.4359 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 2.3576 - Accuracy: 0.6061 - F1: 0.4850
sub_27:Test (Best Model) - Loss: 1.0199 - Accuracy: 0.6364 - F1: 0.6333
sub_27:Test (Best Model) - Loss: 2.2282 - Accuracy: 0.5152 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 2.0302 - Accuracy: 0.5455 - F1: 0.4762
sub_27:Test (Best Model) - Loss: 2.0575 - Accuracy: 0.5152 - F1: 0.5111
sub_27:Test (Best Model) - Loss: 1.2209 - Accuracy: 0.5455 - F1: 0.5171
sub_27:Test (Best Model) - Loss: 1.3275 - Accuracy: 0.5455 - F1: 0.4995
sub_27:Test (Best Model) - Loss: 1.7470 - Accuracy: 0.3438 - F1: 0.3273
sub_27:Test (Best Model) - Loss: 1.3624 - Accuracy: 0.6250 - F1: 0.5844
sub_27:Test (Best Model) - Loss: 2.3578 - Accuracy: 0.4688 - F1: 0.4682
sub_27:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.5625 - F1: 0.5466
sub_27:Test (Best Model) - Loss: 1.8270 - Accuracy: 0.6562 - F1: 0.6102
sub_28:Test (Best Model) - Loss: 0.9506 - Accuracy: 0.6875 - F1: 0.6667
sub_28:Test (Best Model) - Loss: 0.9560 - Accuracy: 0.6250 - F1: 0.6000
sub_28:Test (Best Model) - Loss: 1.6450 - Accuracy: 0.6562 - F1: 0.6532
sub_28:Test (Best Model) - Loss: 2.6919 - Accuracy: 0.5312 - F1: 0.5077
sub_28:Test (Best Model) - Loss: 2.3333 - Accuracy: 0.5312 - F1: 0.5195
sub_28:Test (Best Model) - Loss: 4.0861 - Accuracy: 0.6562 - F1: 0.6390
sub_28:Test (Best Model) - Loss: 5.9218 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 4.5186 - Accuracy: 0.3125 - F1: 0.3016
sub_28:Test (Best Model) - Loss: 4.1965 - Accuracy: 0.4375 - F1: 0.4353
sub_28:Test (Best Model) - Loss: 7.0043 - Accuracy: 0.6562 - F1: 0.6102
sub_28:Test (Best Model) - Loss: 2.2468 - Accuracy: 0.4062 - F1: 0.4010
sub_28:Test (Best Model) - Loss: 1.6657 - Accuracy: 0.5000 - F1: 0.4182
sub_28:Test (Best Model) - Loss: 4.4919 - Accuracy: 0.4062 - F1: 0.2889
sub_28:Test (Best Model) - Loss: 2.0948 - Accuracy: 0.5938 - F1: 0.5934
sub_28:Test (Best Model) - Loss: 3.0513 - Accuracy: 0.3750 - F1: 0.2727
sub_29:Test (Best Model) - Loss: 2.1439 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.9473 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.8368 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 1.4150 - Accuracy: 0.7812 - F1: 0.7519
sub_29:Test (Best Model) - Loss: 0.0240 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.3753 - Accuracy: 0.9062 - F1: 0.9054
sub_29:Test (Best Model) - Loss: 0.1657 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1436 - Accuracy: 0.9375 - F1: 0.9373
sub_29:Test (Best Model) - Loss: 0.3788 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.1194 - Accuracy: 0.9375 - F1: 0.9352
sub_29:Test (Best Model) - Loss: 0.0833 - Accuracy: 0.9697 - F1: 0.9692
sub_29:Test (Best Model) - Loss: 0.3909 - Accuracy: 0.9091 - F1: 0.9060
sub_29:Test (Best Model) - Loss: 0.0840 - Accuracy: 0.9697 - F1: 0.9696
sub_29:Test (Best Model) - Loss: 0.0304 - Accuracy: 0.9697 - F1: 0.9696
sub_29:Test (Best Model) - Loss: 0.0005 - Accuracy: 1.0000 - F1: 1.0000

=== Summary Results ===

acc: 66.60 ± 11.71
F1: 64.32 ± 12.56
acc-in: 74.86 ± 9.04
F1-in: 72.06 ± 10.16
