[2024-04-29 15:25:09]

================== Exp 0 ==================
 
[2024-04-29 15:25:20] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------

================== Exp 0 ==================
 
[2024-04-29 15:25:41] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.303368, train acc = 1.0000 train oa = 1.0000, test acc = 0.0578 test oa = 0.0363
Evaluate 1, mean = 0.0578 std = 0.0000
-------------------------
[2024-04-29 15:25:41] iter = 0000, loss = 225.0938
[2024-04-29 15:25:42] iter = 0010, loss = 43.0495
[2024-04-29 15:25:43] iter = 0020, loss = 36.2285
[2024-04-29 15:25:43] iter = 0030, loss = 29.6589
[2024-04-29 15:25:44] iter = 0040, loss = 21.1425

================== Exp 0 ==================
 
[2024-04-29 15:26:03] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------

================== Exp 0 ==================
 
[2024-04-29 15:29:56] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------
[2024-04-29 15:29:56] iter = 0000, loss = 275.1134
[2024-04-29 15:29:56] iter = 0010, loss = 90.9476
[2024-04-29 15:29:57] iter = 0020, loss = 68.7451
[2024-04-29 15:29:58] iter = 0030, loss = 58.3373
[2024-04-29 15:29:59] iter = 0040, loss = 53.5492
[2024-04-29 15:29:59] iter = 0050, loss = 53.1770
[2024-04-29 15:30:00] iter = 0060, loss = 39.2343
[2024-04-29 15:30:01] iter = 0070, loss = 45.1445
[2024-04-29 15:30:01] iter = 0080, loss = 44.8131
[2024-04-29 15:30:02] iter = 0090, loss = 42.5767
[2024-04-29 15:30:14] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.335987, train acc = 0.5867 train oa = 0.5867, test acc = 0.2718 test oa = 0.2474
Evaluate 1, mean = 0.2718 std = 0.0000
-------------------------
[2024-04-29 15:30:14] iter = 0100, loss = 38.5047
[2024-04-29 15:30:15] iter = 0110, loss = 40.6488
[2024-04-29 15:30:15] iter = 0120, loss = 43.0592
[2024-04-29 15:30:16] iter = 0130, loss = 40.2300
[2024-04-29 15:30:17] iter = 0140, loss = 38.5414
[2024-04-29 15:30:18] iter = 0150, loss = 41.3294
[2024-04-29 15:30:18] iter = 0160, loss = 34.3889
[2024-04-29 15:30:19] iter = 0170, loss = 39.0164
[2024-04-29 15:30:20] iter = 0180, loss = 35.4948
[2024-04-29 15:30:21] iter = 0190, loss = 42.7217
[2024-04-29 15:30:33] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 0.815188, train acc = 0.8200 train oa = 0.8200, test acc = 0.3071 test oa = 0.2993
Evaluate 1, mean = 0.3071 std = 0.0000
-------------------------
[2024-04-29 15:30:33] iter = 0200, loss = 36.0883
[2024-04-29 15:30:34] iter = 0210, loss = 34.2148
[2024-04-29 15:30:35] iter = 0220, loss = 39.4512
[2024-04-29 15:30:36] iter = 0230, loss = 42.0647
[2024-04-29 15:30:37] iter = 0240, loss = 38.5291
[2024-04-29 15:30:37] iter = 0250, loss = 36.6649
[2024-04-29 15:30:38] iter = 0260, loss = 37.4537
[2024-04-29 15:30:39] iter = 0270, loss = 41.0356
[2024-04-29 15:30:40] iter = 0280, loss = 32.1208
[2024-04-29 15:30:41] iter = 0290, loss = 35.6711
[2024-04-29 15:30:55] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.852768, train acc = 0.8200 train oa = 0.8200, test acc = 0.3131 test oa = 0.2872
Evaluate 1, mean = 0.3131 std = 0.0000
-------------------------
[2024-04-29 15:30:55] iter = 0300, loss = 38.6485
[2024-04-29 15:30:56] iter = 0310, loss = 33.3243
[2024-04-29 15:30:57] iter = 0320, loss = 33.9643
[2024-04-29 15:30:58] iter = 0330, loss = 35.3028
[2024-04-29 15:30:59] iter = 0340, loss = 34.6115
[2024-04-29 15:31:01] iter = 0350, loss = 36.2754
[2024-04-29 15:31:02] iter = 0360, loss = 37.8360
[2024-04-29 15:31:03] iter = 0370, loss = 31.6312
[2024-04-29 15:31:04] iter = 0380, loss = 39.2145
[2024-04-29 15:31:05] iter = 0390, loss = 37.1289
[2024-04-29 15:31:28] Evaluate_00: epoch = 0300, train time = 21 s, train loss = 0.803354, train acc = 0.8333 train oa = 0.8333, test acc = 0.3224 test oa = 0.2907
Evaluate 1, mean = 0.3224 std = 0.0000
-------------------------
[2024-04-29 15:31:28] iter = 0400, loss = 35.0283
[2024-04-29 15:31:30] iter = 0410, loss = 36.1520

================== Exp 0 ==================
 
[2024-04-29 15:32:07] Evaluate_00: epoch = 0300, train time = 28 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------
[2024-04-29 15:32:07] iter = 0000, loss = 237.3870
[2024-04-29 15:32:10] iter = 0010, loss = 40.5376
[2024-04-29 15:32:14] iter = 0020, loss = 30.6723
[2024-04-29 15:32:19] iter = 0030, loss = 24.7275
[2024-04-29 15:32:23] iter = 0040, loss = 22.1896
[2024-04-29 15:32:27] iter = 0050, loss = 19.1375
[2024-04-29 15:32:29] iter = 0060, loss = 15.3155
[2024-04-29 15:32:33] iter = 0070, loss = 17.5753
[2024-04-29 15:32:38] iter = 0080, loss = 15.8567
[2024-04-29 15:32:42] iter = 0090, loss = 14.4379
[2024-04-29 15:33:34] Evaluate_00: epoch = 0300, train time = 48 s, train loss = 1.215049, train acc = 0.6467 train oa = 0.6467, test acc = 0.3335 test oa = 0.3097
Evaluate 1, mean = 0.3335 std = 0.0000
-------------------------
[2024-04-29 15:33:34] iter = 0100, loss = 16.0685
[2024-04-29 15:33:38] iter = 0110, loss = 15.3184
[2024-04-29 15:33:43] iter = 0120, loss = 13.7912
[2024-04-29 15:33:47] iter = 0130, loss = 14.9205
[2024-04-29 15:33:51] iter = 0140, loss = 14.0347
[2024-04-29 15:33:55] iter = 0150, loss = 12.7279
[2024-04-29 15:34:00] iter = 0160, loss = 12.7527
[2024-04-29 15:34:04] iter = 0170, loss = 13.5308
[2024-04-29 15:34:08] iter = 0180, loss = 14.3838
[2024-04-29 15:34:12] iter = 0190, loss = 12.7999
[2024-04-29 15:35:19] Evaluate_00: epoch = 0300, train time = 62 s, train loss = 1.523941, train acc = 0.5067 train oa = 0.5067, test acc = 0.3097 test oa = 0.3322
Evaluate 1, mean = 0.3097 std = 0.0000
-------------------------
[2024-04-29 15:35:20] iter = 0200, loss = 13.8627
[2024-04-29 15:35:24] iter = 0210, loss = 15.5209

================== Exp 0 ==================
 
[2024-04-29 15:36:13] Evaluate_00: epoch = 0300, train time = 30 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------

================== Exp 0 ==================
 
[2024-04-29 15:38:47] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.236107, train acc = 0.2600 train oa = 0.2600, test acc = 0.0252 test oa = 0.0277
Evaluate 1, mean = 0.0252 std = 0.0000
-------------------------
[2024-04-29 15:38:47] iter = 0000, loss = 231.4126
[2024-04-29 15:38:48] iter = 0010, loss = 34.8464
[2024-04-29 15:38:49] iter = 0020, loss = 23.6107
[2024-04-29 15:38:51] iter = 0030, loss = 18.5371
[2024-04-29 15:38:52] iter = 0040, loss = 14.6013
[2024-04-29 15:38:53] iter = 0050, loss = 13.9964
[2024-04-29 15:38:54] iter = 0060, loss = 9.9972
[2024-04-29 15:38:56] iter = 0070, loss = 12.3295
[2024-04-29 15:38:57] iter = 0080, loss = 10.1314
[2024-04-29 15:38:58] iter = 0090, loss = 9.4988
[2024-04-29 15:39:12] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.300870, train acc = 0.6067 train oa = 0.6067, test acc = 0.3489 test oa = 0.3166
Evaluate 1, mean = 0.3489 std = 0.0000
-------------------------
[2024-04-29 15:39:12] iter = 0100, loss = 9.7904
[2024-04-29 15:39:14] iter = 0110, loss = 9.2820
[2024-04-29 15:39:16] iter = 0120, loss = 9.3161
[2024-04-29 15:39:18] iter = 0130, loss = 10.1395
[2024-04-29 15:39:20] iter = 0140, loss = 8.2371
[2024-04-29 15:39:23] iter = 0150, loss = 8.6777
[2024-04-29 15:39:26] iter = 0160, loss = 8.0270
[2024-04-29 15:39:30] iter = 0170, loss = 8.6155
[2024-04-29 15:39:34] iter = 0180, loss = 8.7913
[2024-04-29 15:39:39] iter = 0190, loss = 8.2313
[2024-04-29 15:40:28] Evaluate_00: epoch = 0300, train time = 46 s, train loss = 1.543224, train acc = 0.5267 train oa = 0.5267, test acc = 0.3357 test oa = 0.3599
Evaluate 1, mean = 0.3357 std = 0.0000
-------------------------
[2024-04-29 15:40:29] iter = 0200, loss = 7.7275
[2024-04-29 15:40:34] iter = 0210, loss = 9.3935
[2024-04-29 15:40:40] iter = 0220, loss = 8.9478
[2024-04-29 15:40:46] iter = 0230, loss = 8.1624
[2024-04-29 15:40:51] iter = 0240, loss = 8.3800
[2024-04-29 15:40:57] iter = 0250, loss = 7.2128
[2024-04-29 15:41:03] iter = 0260, loss = 8.1474
[2024-04-29 15:41:08] iter = 0270, loss = 8.3785
[2024-04-29 15:41:14] iter = 0280, loss = 8.7619
[2024-04-29 15:41:20] iter = 0290, loss = 7.4321
[2024-04-29 15:42:28] Evaluate_00: epoch = 0300, train time = 62 s, train loss = 1.543268, train acc = 0.5267 train oa = 0.5267, test acc = 0.3394 test oa = 0.3391
Evaluate 1, mean = 0.3394 std = 0.0000
-------------------------
[2024-04-29 15:42:29] iter = 0300, loss = 7.6468
[2024-04-29 15:42:34] iter = 0310, loss = 7.1638
[2024-04-29 15:42:40] iter = 0320, loss = 7.5792
[2024-04-29 15:42:45] iter = 0330, loss = 8.0952
[2024-04-29 15:42:51] iter = 0340, loss = 7.5315
[2024-04-29 15:49:21] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.668240, train acc = 0.9600 train oa = 0.9600, test acc = 0.2463 test oa = 0.1990
[2024-04-29 15:49:32] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.831643, train acc = 0.9000 train oa = 0.9000, test acc = 0.2284 test oa = 0.1678
[2024-04-29 15:49:43] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.583659, train acc = 0.9333 train oa = 0.9333, test acc = 0.2550 test oa = 0.1972
[2024-04-29 15:51:05] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.936606, train acc = 0.7933 train oa = 0.7933, test acc = 0.2593 test oa = 0.2180
[2024-04-29 15:51:16] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.031444, train acc = 0.7533 train oa = 0.7533, test acc = 0.2974 test oa = 0.2353
[2024-04-29 15:51:27] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.967062, train acc = 0.7467 train oa = 0.7467, test acc = 0.2799 test oa = 0.2145
[2024-04-29 15:52:58] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.981999, train acc = 0.7800 train oa = 0.7800, test acc = 0.3235 test oa = 0.3062
[2024-04-29 15:53:09] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.093367, train acc = 0.7333 train oa = 0.7333, test acc = 0.3505 test oa = 0.3131
[2024-04-29 15:53:21] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.923865, train acc = 0.8467 train oa = 0.8467, test acc = 0.3146 test oa = 0.2820
[2024-04-29 15:54:51] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.903116, train acc = 0.8267 train oa = 0.8267, test acc = 0.2987 test oa = 0.2509
[2024-04-29 15:55:02] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.826888, train acc = 0.8600 train oa = 0.8600, test acc = 0.2959 test oa = 0.2491
[2024-04-29 15:55:13] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.961849, train acc = 0.8333 train oa = 0.8333, test acc = 0.2868 test oa = 0.2284
[2024-04-29 15:56:44] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.155829, train acc = 0.7000 train oa = 0.7000, test acc = 0.2814 test oa = 0.2249
[2024-04-29 15:56:55] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.941735, train acc = 0.7467 train oa = 0.7467, test acc = 0.2744 test oa = 0.2422
[2024-04-29 15:57:06] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.073379, train acc = 0.7333 train oa = 0.7333, test acc = 0.2539 test oa = 0.2249
[2024-04-29 15:58:51] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.326915, train acc = 0.6600 train oa = 0.6600, test acc = 0.3497 test oa = 0.3287
[2024-04-29 15:59:02] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.463462, train acc = 0.5467 train oa = 0.5467, test acc = 0.3698 test oa = 0.3183
[2024-04-29 15:59:13] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.545268, train acc = 0.5267 train oa = 0.5267, test acc = 0.3233 test oa = 0.2803
[2024-04-29 16:00:35] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.135645, train acc = 0.6800 train oa = 0.6800, test acc = 0.2451 test oa = 0.2215
[2024-04-29 16:00:46] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.126953, train acc = 0.6867 train oa = 0.6867, test acc = 0.2626 test oa = 0.2266
[2024-04-29 16:00:57] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.162930, train acc = 0.6667 train oa = 0.6667, test acc = 0.2240 test oa = 0.2111
[2024-04-29 16:02:15] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.514459, train acc = 0.9400 train oa = 0.9400, test acc = 0.2524 test oa = 0.2059
[2024-04-29 16:02:26] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.523967, train acc = 0.9733 train oa = 0.9733, test acc = 0.2899 test oa = 0.2509
[2024-04-29 16:02:37] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.642577, train acc = 0.9400 train oa = 0.9400, test acc = 0.1773 test oa = 0.1401
[2024-04-29 16:04:08] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.156273, train acc = 0.7133 train oa = 0.7133, test acc = 0.2682 test oa = 0.2595
[2024-04-29 16:04:18] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.267827, train acc = 0.6733 train oa = 0.6733, test acc = 0.2494 test oa = 0.2509
[2024-04-29 16:04:29] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.266407, train acc = 0.6600 train oa = 0.6600, test acc = 0.2349 test oa = 0.2318
[2024-04-29 16:06:13] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.464166, train acc = 0.6000 train oa = 0.6000, test acc = 0.3491 test oa = 0.3097
[2024-04-29 16:06:24] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.591593, train acc = 0.5400 train oa = 0.5400, test acc = 0.3579 test oa = 0.2993
[2024-04-29 16:06:35] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.535444, train acc = 0.4800 train oa = 0.4800, test acc = 0.3318 test oa = 0.3028
[2024-04-29 16:08:22] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.563022, train acc = 0.5200 train oa = 0.5200, test acc = 0.3269 test oa = 0.2958
[2024-04-29 16:08:33] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.516468, train acc = 0.5333 train oa = 0.5333, test acc = 0.3839 test oa = 0.3426
[2024-04-29 16:08:44] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.494578, train acc = 0.5133 train oa = 0.5133, test acc = 0.3282 test oa = 0.2958
[2024-04-29 16:09:58] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.495788, train acc = 0.9800 train oa = 0.9800, test acc = 0.2248 test oa = 0.1920
[2024-04-29 16:10:09] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.582281, train acc = 0.9533 train oa = 0.9533, test acc = 0.2570 test oa = 0.1972
[2024-04-29 16:10:20] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.389142, train acc = 0.9800 train oa = 0.9800, test acc = 0.2567 test oa = 0.1972
[2024-04-29 16:11:38] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.605685, train acc = 0.9533 train oa = 0.9533, test acc = 0.2337 test oa = 0.2076
[2024-04-29 16:11:49] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.746329, train acc = 0.9267 train oa = 0.9267, test acc = 0.2075 test oa = 0.1834
[2024-04-29 16:12:00] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.602386, train acc = 0.9533 train oa = 0.9533, test acc = 0.2463 test oa = 0.2059
[2024-04-29 16:14:06] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.458259, train acc = 0.6000 train oa = 0.6000, test acc = 0.3473 test oa = 0.3858
[2024-04-29 16:14:17] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.388618, train acc = 0.6400 train oa = 0.6400, test acc = 0.3151 test oa = 0.3668
[2024-04-29 16:14:28] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.533262, train acc = 0.5667 train oa = 0.5667, test acc = 0.3248 test oa = 0.3253
[2024-04-29 16:15:45] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.492348, train acc = 0.9667 train oa = 0.9667, test acc = 0.2618 test oa = 0.2076
[2024-04-29 16:15:56] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.523399, train acc = 0.9267 train oa = 0.9267, test acc = 0.2752 test oa = 0.2353
[2024-04-29 16:16:07] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.504233, train acc = 0.9600 train oa = 0.9600, test acc = 0.2467 test oa = 0.2059
[2024-04-29 16:18:05] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.530701, train acc = 0.5600 train oa = 0.5600, test acc = 0.3841 test oa = 0.3979
[2024-04-29 16:18:16] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.376435, train acc = 0.6000 train oa = 0.6000, test acc = 0.3549 test oa = 0.3720
[2024-04-29 16:18:27] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.408905, train acc = 0.6200 train oa = 0.6200, test acc = 0.3712 test oa = 0.3633
[2024-04-29 16:20:34] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.493688, train acc = 0.6067 train oa = 0.6067, test acc = 0.3925 test oa = 0.3460
[2024-04-29 16:20:45] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.321722, train acc = 0.6400 train oa = 0.6400, test acc = 0.3924 test oa = 0.3564
[2024-04-29 16:20:56] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.334359, train acc = 0.6400 train oa = 0.6400, test acc = 0.3736 test oa = 0.3460
[2024-04-29 16:22:14] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.311539, train acc = 0.9867 train oa = 0.9867, test acc = 0.3105 test oa = 0.2630
[2024-04-29 16:22:25] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.296026, train acc = 1.0000 train oa = 1.0000, test acc = 0.2752 test oa = 0.2526
[2024-04-29 16:22:36] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.514944, train acc = 0.9800 train oa = 0.9800, test acc = 0.2492 test oa = 0.2336
[2024-04-29 16:24:44] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.410290, train acc = 0.6600 train oa = 0.6600, test acc = 0.3512 test oa = 0.3616
[2024-04-29 16:24:55] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.189531, train acc = 0.7467 train oa = 0.7467, test acc = 0.3369 test oa = 0.3391
[2024-04-29 16:25:06] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.449157, train acc = 0.6267 train oa = 0.6267, test acc = 0.3651 test oa = 0.3668
[2024-04-29 16:26:32] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 0.448850, train acc = 0.9800 train oa = 0.9800, test acc = 0.2905 test oa = 0.2682
[2024-04-29 16:26:43] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 0.534378, train acc = 0.9533 train oa = 0.9533, test acc = 0.2950 test oa = 0.2785
[2024-04-29 16:26:54] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 0.535546, train acc = 0.9533 train oa = 0.9533, test acc = 0.2353 test oa = 0.2266

================== Exp 0 ==================
 
[2024-04-29 16:35:27] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.912262, train acc = 0.8533 train oa = 0.8533, test acc = 0.0817 test oa = 0.0467
Evaluate 1, mean = 0.0817 std = 0.0000
-------------------------
[2024-04-29 16:35:27] iter = 0000, loss = 275.6609
[2024-04-29 16:35:28] iter = 0010, loss = 51.6318
[2024-04-29 16:35:29] iter = 0020, loss = 31.5045
[2024-04-29 16:35:30] iter = 0030, loss = 23.7811
[2024-04-29 16:35:31] iter = 0040, loss = 19.4695
[2024-04-29 16:35:32] iter = 0050, loss = 17.0175
[2024-04-29 16:35:33] iter = 0060, loss = 15.4447
[2024-04-29 16:35:34] iter = 0070, loss = 15.9665
[2024-04-29 16:35:35] iter = 0080, loss = 12.8202
[2024-04-29 16:35:37] iter = 0090, loss = 12.2861
[2024-04-29 16:35:43] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.023008, train acc = 0.8533 train oa = 0.8533, test acc = 0.0936 test oa = 0.1055
Evaluate 1, mean = 0.0936 std = 0.0000
-------------------------
[2024-04-29 16:35:43] iter = 0100, loss = 14.4235
[2024-04-29 16:35:44] iter = 0110, loss = 13.9746
[2024-04-29 16:35:45] iter = 0120, loss = 14.4731
[2024-04-29 16:35:46] iter = 0130, loss = 14.8900
[2024-04-29 16:35:48] iter = 0140, loss = 12.1444
[2024-04-29 16:35:49] iter = 0150, loss = 12.2997
[2024-04-29 16:35:50] iter = 0160, loss = 11.9028
[2024-04-29 16:35:51] iter = 0170, loss = 12.1719
[2024-04-29 16:35:52] iter = 0180, loss = 12.1170
[2024-04-29 16:35:53] iter = 0190, loss = 12.9749
[2024-04-29 16:36:00] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.156139, train acc = 0.8000 train oa = 0.8000, test acc = 0.1185 test oa = 0.1228
Evaluate 1, mean = 0.1185 std = 0.0000
-------------------------
[2024-04-29 16:36:00] iter = 0200, loss = 11.9194
[2024-04-29 16:36:01] iter = 0210, loss = 14.0842
[2024-04-29 16:36:02] iter = 0220, loss = 11.9485
[2024-04-29 16:36:03] iter = 0230, loss = 12.3411
[2024-04-29 16:36:04] iter = 0240, loss = 12.0212
[2024-04-29 16:36:05] iter = 0250, loss = 10.4204
[2024-04-29 16:36:06] iter = 0260, loss = 10.6725
[2024-04-29 16:36:07] iter = 0270, loss = 11.8896
[2024-04-29 16:36:08] iter = 0280, loss = 12.3532
[2024-04-29 16:36:09] iter = 0290, loss = 11.0857
[2024-04-29 16:36:16] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.087507, train acc = 0.8000 train oa = 0.8000, test acc = 0.1370 test oa = 0.2388
Evaluate 1, mean = 0.1370 std = 0.0000
-------------------------
[2024-04-29 16:36:16] iter = 0300, loss = 11.6794
[2024-04-29 16:36:17] iter = 0310, loss = 11.1174
[2024-04-29 16:36:18] iter = 0320, loss = 12.4982
[2024-04-29 16:36:19] iter = 0330, loss = 10.6539
[2024-04-29 16:36:20] iter = 0340, loss = 10.0010
[2024-04-29 16:36:21] iter = 0350, loss = 12.2870
[2024-04-29 16:36:23] iter = 0360, loss = 13.5939
[2024-04-29 16:36:24] iter = 0370, loss = 11.2949
[2024-04-29 16:36:25] iter = 0380, loss = 10.6043
[2024-04-29 16:36:26] iter = 0390, loss = 11.1413
[2024-04-29 16:36:33] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.191030, train acc = 0.7200 train oa = 0.7200, test acc = 0.1034 test oa = 0.1107
Evaluate 1, mean = 0.1034 std = 0.0000
-------------------------
[2024-04-29 16:36:33] iter = 0400, loss = 11.3213
[2024-04-29 16:36:34] iter = 0410, loss = 10.2346
[2024-04-29 16:36:35] iter = 0420, loss = 10.1531
[2024-04-29 16:36:36] iter = 0430, loss = 10.8515
[2024-04-29 16:36:37] iter = 0440, loss = 12.0629

================== Exp 0 ==================
 
[2024-04-29 16:38:33] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.012135, train acc = 1.0000 train oa = 1.0000, test acc = 0.1126 test oa = 0.1073
Evaluate 1, mean = 0.1126 std = 0.0000
-------------------------
[2024-04-29 16:38:33] iter = 0000, loss = 388.8191
[2024-04-29 16:38:34] iter = 0010, loss = 55.9493
[2024-04-29 16:38:35] iter = 0020, loss = 35.3793
[2024-04-29 16:38:36] iter = 0030, loss = 27.8397
[2024-04-29 16:38:37] iter = 0040, loss = 20.8318
[2024-04-29 16:38:38] iter = 0050, loss = 18.5547
[2024-04-29 16:38:39] iter = 0060, loss = 18.0062
[2024-04-29 16:38:40] iter = 0070, loss = 17.3477
[2024-04-29 16:38:41] iter = 0080, loss = 16.1302
[2024-04-29 16:38:42] iter = 0090, loss = 12.7542
[2024-04-29 16:38:49] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.103211, train acc = 0.7200 train oa = 0.7200, test acc = 0.1057 test oa = 0.0986
Evaluate 1, mean = 0.1057 std = 0.0000
-------------------------
[2024-04-29 16:38:49] iter = 0100, loss = 15.1320
[2024-04-29 16:38:50] iter = 0110, loss = 15.8774
[2024-04-29 16:38:51] iter = 0120, loss = 16.1649
[2024-04-29 16:38:52] iter = 0130, loss = 16.6343
[2024-04-29 16:38:53] iter = 0140, loss = 14.1167
[2024-04-29 16:38:54] iter = 0150, loss = 12.9920
[2024-04-29 16:38:56] iter = 0160, loss = 12.6667
[2024-04-29 16:38:57] iter = 0170, loss = 13.7957
[2024-04-29 16:38:58] iter = 0180, loss = 13.0611
[2024-04-29 16:38:59] iter = 0190, loss = 14.0526
[2024-04-29 16:39:06] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.679089, train acc = 0.9600 train oa = 0.9600, test acc = 0.0718 test oa = 0.0744
Evaluate 1, mean = 0.0718 std = 0.0000
-------------------------
[2024-04-29 16:39:06] iter = 0200, loss = 13.1585
[2024-04-29 16:39:07] iter = 0210, loss = 16.2299
[2024-04-29 16:39:08] iter = 0220, loss = 14.1006
[2024-04-29 16:39:09] iter = 0230, loss = 12.3968
[2024-04-29 16:39:10] iter = 0240, loss = 13.6590
[2024-04-29 16:39:11] iter = 0250, loss = 11.8869
[2024-04-29 16:39:12] iter = 0260, loss = 12.0636
[2024-04-29 16:39:13] iter = 0270, loss = 13.2712
[2024-04-29 16:39:14] iter = 0280, loss = 13.1108
[2024-04-29 16:39:15] iter = 0290, loss = 12.4610
[2024-04-29 16:39:23] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.731693, train acc = 0.9067 train oa = 0.9067, test acc = 0.1541 test oa = 0.2249
Evaluate 1, mean = 0.1541 std = 0.0000
-------------------------
[2024-04-29 16:39:23] iter = 0300, loss = 11.9937
[2024-04-29 16:39:24] iter = 0310, loss = 13.1303
[2024-04-29 16:39:25] iter = 0320, loss = 13.2351
[2024-04-29 16:39:26] iter = 0330, loss = 11.6689
[2024-04-29 16:39:27] iter = 0340, loss = 11.1842
[2024-04-29 16:39:28] iter = 0350, loss = 12.2829
[2024-04-29 16:39:29] iter = 0360, loss = 13.4716
[2024-04-29 16:39:31] iter = 0370, loss = 12.6040
[2024-04-29 16:39:32] iter = 0380, loss = 11.1959
[2024-04-29 16:39:33] iter = 0390, loss = 12.6320
[2024-04-29 16:39:40] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.841441, train acc = 0.8933 train oa = 0.8933, test acc = 0.0977 test oa = 0.1021
Evaluate 1, mean = 0.0977 std = 0.0000
-------------------------
[2024-04-29 16:39:41] iter = 0400, loss = 11.8992
[2024-04-29 16:39:42] iter = 0410, loss = 11.0091
[2024-04-29 16:39:43] iter = 0420, loss = 11.3598
[2024-04-29 16:39:44] iter = 0430, loss = 12.1825
[2024-04-29 16:39:45] iter = 0440, loss = 14.1128
[2024-04-29 16:39:46] iter = 0450, loss = 11.4898
[2024-04-29 16:39:47] iter = 0460, loss = 10.9037
[2024-04-29 16:39:49] iter = 0470, loss = 9.4432
[2024-04-29 16:39:50] iter = 0480, loss = 10.0907
[2024-04-29 16:39:51] iter = 0490, loss = 11.9962
[2024-04-29 16:39:58] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 1.067824, train acc = 0.8133 train oa = 0.8133, test acc = 0.0969 test oa = 0.0986
Evaluate 1, mean = 0.0969 std = 0.0000
-------------------------
[2024-04-29 16:39:59] iter = 0500, loss = 11.2709
[2024-04-29 16:40:00] iter = 0510, loss = 9.6396
[2024-04-29 16:40:01] iter = 0520, loss = 12.5053
[2024-04-29 16:40:02] iter = 0530, loss = 11.3684
[2024-04-29 16:40:04] iter = 0540, loss = 11.0067
[2024-04-29 16:40:05] iter = 0550, loss = 10.4105
[2024-04-29 16:40:06] iter = 0560, loss = 10.4067
[2024-04-29 16:40:07] iter = 0570, loss = 11.1973
[2024-04-29 16:40:08] iter = 0580, loss = 12.7300
[2024-04-29 16:40:09] iter = 0590, loss = 11.2528
[2024-04-29 16:40:17] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.939038, train acc = 0.8667 train oa = 0.8667, test acc = 0.0984 test oa = 0.1125
Evaluate 1, mean = 0.0984 std = 0.0000
-------------------------
[2024-04-29 16:40:17] iter = 0600, loss = 10.2181
[2024-04-29 16:40:19] iter = 0610, loss = 11.0855
[2024-04-29 16:40:20] iter = 0620, loss = 10.0223
[2024-04-29 16:40:21] iter = 0630, loss = 12.3571
[2024-04-29 16:40:23] iter = 0640, loss = 10.2641
[2024-04-29 16:40:24] iter = 0650, loss = 10.9766
[2024-04-29 16:40:25] iter = 0660, loss = 10.6477
[2024-04-29 16:40:26] iter = 0670, loss = 9.7852
[2024-04-29 16:40:27] iter = 0680, loss = 10.7733
[2024-04-29 16:40:28] iter = 0690, loss = 11.6253
[2024-04-29 16:40:36] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.652510, train acc = 0.9600 train oa = 0.9600, test acc = 0.3148 test oa = 0.3547
Evaluate 1, mean = 0.3148 std = 0.0000
-------------------------
[2024-04-29 16:40:37] iter = 0700, loss = 10.8801
[2024-04-29 16:40:38] iter = 0710, loss = 10.3550
[2024-04-29 16:40:39] iter = 0720, loss = 11.3639
[2024-04-29 16:40:40] iter = 0730, loss = 9.3533
[2024-04-29 16:40:42] iter = 0740, loss = 10.6356
[2024-04-29 16:40:43] iter = 0750, loss = 9.0631
[2024-04-29 16:40:44] iter = 0760, loss = 10.1591
[2024-04-29 16:40:45] iter = 0770, loss = 11.0796
[2024-04-29 16:40:47] iter = 0780, loss = 9.6411
[2024-04-29 16:40:48] iter = 0790, loss = 10.1883
[2024-04-29 16:40:56] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.645483, train acc = 0.9733 train oa = 0.9733, test acc = 0.3220 test oa = 0.3010
Evaluate 1, mean = 0.3220 std = 0.0000
-------------------------
[2024-04-29 16:40:56] iter = 0800, loss = 11.2966
[2024-04-29 16:40:57] iter = 0810, loss = 10.6012
[2024-04-29 16:40:59] iter = 0820, loss = 11.4113
[2024-04-29 16:41:00] iter = 0830, loss = 11.5516
[2024-04-29 16:41:01] iter = 0840, loss = 11.5549
[2024-04-29 16:41:02] iter = 0850, loss = 11.1248
[2024-04-29 16:41:04] iter = 0860, loss = 9.6443
[2024-04-29 16:41:05] iter = 0870, loss = 9.9808
[2024-04-29 16:41:06] iter = 0880, loss = 9.1064
[2024-04-29 16:41:08] iter = 0890, loss = 10.9937
[2024-04-29 16:41:16] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.983037, train acc = 0.8533 train oa = 0.8533, test acc = 0.3356 test oa = 0.3651
Evaluate 1, mean = 0.3356 std = 0.0000
-------------------------
[2024-04-29 16:41:16] iter = 0900, loss = 9.6533
[2024-04-29 16:41:17] iter = 0910, loss = 9.9047
[2024-04-29 16:41:18] iter = 0920, loss = 9.6028
[2024-04-29 16:41:19] iter = 0930, loss = 9.2301
[2024-04-29 16:41:21] iter = 0940, loss = 10.4740
[2024-04-29 16:41:22] iter = 0950, loss = 10.5539
[2024-04-29 16:41:23] iter = 0960, loss = 10.7214
[2024-04-29 16:41:25] iter = 0970, loss = 9.2413
[2024-04-29 16:41:26] iter = 0980, loss = 10.5407
[2024-04-29 16:41:27] iter = 0990, loss = 9.9466
[2024-04-29 16:41:35] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 1.085119, train acc = 0.7867 train oa = 0.7867, test acc = 0.3071 test oa = 0.3495
Evaluate 1, mean = 0.3071 std = 0.0000
-------------------------
[2024-04-29 16:41:35] iter = 1000, loss = 9.6918
[2024-05-05 23:13:15] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.048139, train acc = 1.0000 train oa = 1.0000, test acc = 0.3110 test oa = 0.2889
[2024-05-05 23:13:17] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.047705, train acc = 1.0000 train oa = 1.0000, test acc = 0.2833 test oa = 0.2578
[2024-05-05 23:13:19] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.049109, train acc = 1.0000 train oa = 1.0000, test acc = 0.2754 test oa = 0.2543
[2024-05-06 00:10:04] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.023187, train acc = 1.0000 train oa = 1.0000, test acc = 0.2500 test oa = 0.2059
[2024-05-06 00:10:06] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.038623, train acc = 1.0000 train oa = 1.0000, test acc = 0.2605 test oa = 0.2076
[2024-05-06 00:10:07] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.015522, train acc = 1.0000 train oa = 1.0000, test acc = 0.2541 test oa = 0.2215
[2024-05-06 00:13:53] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.048235, train acc = 1.0000 train oa = 1.0000, test acc = 0.3010 test oa = 0.2716
[2024-05-06 00:13:55] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.044834, train acc = 1.0000 train oa = 1.0000, test acc = 0.3028 test oa = 0.2664
[2024-05-06 00:13:56] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.051298, train acc = 1.0000 train oa = 1.0000, test acc = 0.3128 test oa = 0.2647
[2024-05-06 00:20:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.096303, train acc = 1.0000 train oa = 1.0000, test acc = 0.2757 test oa = 0.2491
[2024-05-06 00:20:13] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.100814, train acc = 1.0000 train oa = 1.0000, test acc = 0.2624 test oa = 0.2526
[2024-05-06 00:20:15] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.055393, train acc = 1.0000 train oa = 1.0000, test acc = 0.2421 test oa = 0.2543
[2024-05-06 00:24:42] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.073360, train acc = 1.0000 train oa = 1.0000, test acc = 0.3176 test oa = 0.2509
[2024-05-06 00:24:44] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.093057, train acc = 1.0000 train oa = 1.0000, test acc = 0.2801 test oa = 0.2474
[2024-05-06 00:24:46] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.051767, train acc = 1.0000 train oa = 1.0000, test acc = 0.2692 test oa = 0.2388
[2024-05-06 00:32:58] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.059041, train acc = 1.0000 train oa = 1.0000, test acc = 0.2543 test oa = 0.2163
[2024-05-06 00:33:00] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.062959, train acc = 1.0000 train oa = 1.0000, test acc = 0.2702 test oa = 0.2301
[2024-05-06 00:33:01] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.027540, train acc = 1.0000 train oa = 1.0000, test acc = 0.3035 test oa = 0.2595
[2024-05-06 00:55:51] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.062805, train acc = 1.0000 train oa = 1.0000, test acc = 0.2626 test oa = 0.2284
[2024-05-06 00:55:52] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.030917, train acc = 1.0000 train oa = 1.0000, test acc = 0.2802 test oa = 0.2353
[2024-05-06 00:55:54] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.051192, train acc = 1.0000 train oa = 1.0000, test acc = 0.2553 test oa = 0.2353
[2024-05-06 01:08:27] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.062947, train acc = 1.0000 train oa = 1.0000, test acc = 0.2956 test oa = 0.2578
[2024-05-06 01:08:29] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.060923, train acc = 1.0000 train oa = 1.0000, test acc = 0.2865 test oa = 0.2768
[2024-05-06 01:08:31] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.032438, train acc = 1.0000 train oa = 1.0000, test acc = 0.2780 test oa = 0.2682
[2024-05-06 01:18:48] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.039100, train acc = 1.0000 train oa = 1.0000, test acc = 0.2733 test oa = 0.2474
[2024-05-06 01:18:50] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.076247, train acc = 1.0000 train oa = 1.0000, test acc = 0.2724 test oa = 0.2388
[2024-05-06 01:18:52] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.051732, train acc = 1.0000 train oa = 1.0000, test acc = 0.2985 test oa = 0.2595
[2024-05-06 01:30:23] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.032913, train acc = 1.0000 train oa = 1.0000, test acc = 0.2631 test oa = 0.2682
[2024-05-06 01:30:25] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.094585, train acc = 1.0000 train oa = 1.0000, test acc = 0.2657 test oa = 0.2664
[2024-05-06 01:30:27] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.066911, train acc = 1.0000 train oa = 1.0000, test acc = 0.2772 test oa = 0.2578
[2024-05-06 02:42:38] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.086254, train acc = 1.0000 train oa = 1.0000, test acc = 0.2495 test oa = 0.2249
[2024-05-06 02:42:40] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.100502, train acc = 1.0000 train oa = 1.0000, test acc = 0.2858 test oa = 0.2370
[2024-05-06 02:42:42] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.044810, train acc = 1.0000 train oa = 1.0000, test acc = 0.2453 test oa = 0.2180
[2024-05-06 02:53:59] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.065811, train acc = 1.0000 train oa = 1.0000, test acc = 0.2986 test oa = 0.2664
[2024-05-06 02:54:01] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.087995, train acc = 1.0000 train oa = 1.0000, test acc = 0.3141 test oa = 0.2664
[2024-05-06 02:54:03] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.057869, train acc = 1.0000 train oa = 1.0000, test acc = 0.2573 test oa = 0.2353
[2024-05-06 03:00:08] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.051658, train acc = 1.0000 train oa = 1.0000, test acc = 0.2870 test oa = 0.2820
[2024-05-06 03:00:10] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.054917, train acc = 1.0000 train oa = 1.0000, test acc = 0.2861 test oa = 0.2543
[2024-05-06 03:00:12] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.095448, train acc = 1.0000 train oa = 1.0000, test acc = 0.2988 test oa = 0.2768
[2024-05-06 03:06:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.049161, train acc = 1.0000 train oa = 1.0000, test acc = 0.2169 test oa = 0.1920
[2024-05-06 03:06:28] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.065443, train acc = 1.0000 train oa = 1.0000, test acc = 0.2693 test oa = 0.2284
[2024-05-06 03:06:30] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.097962, train acc = 1.0000 train oa = 1.0000, test acc = 0.2782 test oa = 0.2924
[2024-05-06 03:12:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.028614, train acc = 1.0000 train oa = 1.0000, test acc = 0.2825 test oa = 0.2336
[2024-05-06 03:12:35] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.026512, train acc = 1.0000 train oa = 1.0000, test acc = 0.2548 test oa = 0.2128
[2024-05-06 03:12:37] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.036148, train acc = 1.0000 train oa = 1.0000, test acc = 0.2855 test oa = 0.2509
[2024-05-06 03:18:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.045153, train acc = 1.0000 train oa = 1.0000, test acc = 0.2448 test oa = 0.2180
[2024-05-06 03:18:57] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.141577, train acc = 1.0000 train oa = 1.0000, test acc = 0.3045 test oa = 0.2958
[2024-05-06 03:18:59] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.080466, train acc = 1.0000 train oa = 1.0000, test acc = 0.2757 test oa = 0.2768
[2024-05-06 03:25:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.037231, train acc = 1.0000 train oa = 1.0000, test acc = 0.2675 test oa = 0.2785
[2024-05-06 03:25:04] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.046358, train acc = 1.0000 train oa = 1.0000, test acc = 0.2866 test oa = 0.3201
[2024-05-06 03:25:06] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.093754, train acc = 1.0000 train oa = 1.0000, test acc = 0.2801 test oa = 0.3080
[2024-05-06 03:33:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050907, train acc = 1.0000 train oa = 1.0000, test acc = 0.2841 test oa = 0.2664
[2024-05-06 03:33:28] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.095039, train acc = 1.0000 train oa = 1.0000, test acc = 0.2789 test oa = 0.2457
[2024-05-06 03:33:30] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.029287, train acc = 1.0000 train oa = 1.0000, test acc = 0.2944 test oa = 0.2751
[2024-05-06 03:39:37] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.037231, train acc = 1.0000 train oa = 1.0000, test acc = 0.2675 test oa = 0.2785
[2024-05-06 03:39:39] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.046358, train acc = 1.0000 train oa = 1.0000, test acc = 0.2866 test oa = 0.3201
[2024-05-06 03:39:41] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.093754, train acc = 1.0000 train oa = 1.0000, test acc = 0.2801 test oa = 0.3080
[2024-05-06 03:45:53] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.285925, train acc = 1.0000 train oa = 1.0000, test acc = 0.2639 test oa = 0.2612
[2024-05-06 03:45:55] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.134929, train acc = 1.0000 train oa = 1.0000, test acc = 0.2887 test oa = 0.2716
[2024-05-06 03:45:57] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.120236, train acc = 1.0000 train oa = 1.0000, test acc = 0.2450 test oa = 0.2699
[2024-05-06 04:06:38] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.065811, train acc = 1.0000 train oa = 1.0000, test acc = 0.2986 test oa = 0.2664
[2024-05-06 04:06:40] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.087995, train acc = 1.0000 train oa = 1.0000, test acc = 0.3141 test oa = 0.2664
[2024-05-06 04:06:42] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.057869, train acc = 1.0000 train oa = 1.0000, test acc = 0.2573 test oa = 0.2353
[2024-05-06 04:10:56] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.079829, train acc = 1.0000 train oa = 1.0000, test acc = 0.2535 test oa = 0.2612
[2024-05-06 04:10:57] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.064737, train acc = 1.0000 train oa = 1.0000, test acc = 0.2283 test oa = 0.2543
[2024-05-06 04:10:59] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.084097, train acc = 1.0000 train oa = 1.0000, test acc = 0.2468 test oa = 0.2439
[2024-05-06 04:41:47] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.036554, train acc = 1.0000 train oa = 1.0000, test acc = 0.3047 test oa = 0.2664
[2024-05-06 04:41:49] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.036890, train acc = 1.0000 train oa = 1.0000, test acc = 0.3110 test oa = 0.2872
[2024-05-06 04:41:51] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.066949, train acc = 1.0000 train oa = 1.0000, test acc = 0.3050 test oa = 0.2716
[2024-05-06 04:46:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.053294, train acc = 1.0000 train oa = 1.0000, test acc = 0.2867 test oa = 0.2612
[2024-05-06 04:46:57] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.064652, train acc = 1.0000 train oa = 1.0000, test acc = 0.3070 test oa = 0.2612
[2024-05-06 04:46:59] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.068276, train acc = 1.0000 train oa = 1.0000, test acc = 0.2936 test oa = 0.2630
[2024-05-06 04:58:20] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 1.026106, train acc = 0.9067 train oa = 0.9067, test acc = 0.3010 test oa = 0.2976
[2024-05-06 04:58:29] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 1.299563, train acc = 0.7867 train oa = 0.7867, test acc = 0.3084 test oa = 0.2976
[2024-05-06 04:58:39] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 1.121570, train acc = 0.8133 train oa = 0.8133, test acc = 0.2949 test oa = 0.2751
[2024-05-06 05:10:14] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.081597, train acc = 1.0000 train oa = 1.0000, test acc = 0.2732 test oa = 0.2526
[2024-05-06 05:10:16] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.045917, train acc = 1.0000 train oa = 1.0000, test acc = 0.2829 test oa = 0.2647
[2024-05-06 05:10:18] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.099048, train acc = 1.0000 train oa = 1.0000, test acc = 0.2920 test oa = 0.2664
[2024-05-06 05:16:24] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.114277, train acc = 1.0000 train oa = 1.0000, test acc = 0.2891 test oa = 0.2699
[2024-05-06 05:16:25] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.178565, train acc = 1.0000 train oa = 1.0000, test acc = 0.2624 test oa = 0.2612
[2024-05-06 05:16:27] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.161034, train acc = 1.0000 train oa = 1.0000, test acc = 0.2758 test oa = 0.2491
[2024-05-06 05:44:31] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.162558, train acc = 1.0000 train oa = 1.0000, test acc = 0.2485 test oa = 0.2111
[2024-05-06 05:44:33] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.119420, train acc = 1.0000 train oa = 1.0000, test acc = 0.2567 test oa = 0.2215
[2024-05-06 05:44:35] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.196800, train acc = 1.0000 train oa = 1.0000, test acc = 0.2388 test oa = 0.2266
[2024-05-06 06:06:03] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.055274, train acc = 1.0000 train oa = 1.0000, test acc = 0.2773 test oa = 0.2837
[2024-05-06 06:06:05] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.033636, train acc = 1.0000 train oa = 1.0000, test acc = 0.2636 test oa = 0.2785
[2024-05-06 06:06:07] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.098502, train acc = 1.0000 train oa = 1.0000, test acc = 0.2601 test oa = 0.2630
[2024-05-06 06:12:30] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.029096, train acc = 1.0000 train oa = 1.0000, test acc = 0.2726 test oa = 0.2509
[2024-05-06 06:12:32] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.044292, train acc = 1.0000 train oa = 1.0000, test acc = 0.2776 test oa = 0.3028
[2024-05-06 06:12:34] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.017412, train acc = 1.0000 train oa = 1.0000, test acc = 0.2736 test oa = 0.2889
[2024-05-06 06:16:53] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.079829, train acc = 1.0000 train oa = 1.0000, test acc = 0.2535 test oa = 0.2612
[2024-05-06 06:16:55] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.064737, train acc = 1.0000 train oa = 1.0000, test acc = 0.2283 test oa = 0.2543
[2024-05-06 06:16:56] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.084097, train acc = 1.0000 train oa = 1.0000, test acc = 0.2468 test oa = 0.2439
[2024-05-06 06:17:24] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.041468, train acc = 1.0000 train oa = 1.0000, test acc = 0.2811 test oa = 0.2561
[2024-05-06 06:17:26] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.050317, train acc = 1.0000 train oa = 1.0000, test acc = 0.2906 test oa = 0.2509
[2024-05-06 06:17:27] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.046790, train acc = 1.0000 train oa = 1.0000, test acc = 0.2656 test oa = 0.2439
[2024-05-06 06:47:58] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.759710, train acc = 0.9067 train oa = 0.9067, test acc = 0.3214 test oa = 0.2993
[2024-05-06 06:48:06] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.371042, train acc = 1.0000 train oa = 1.0000, test acc = 0.3545 test oa = 0.3478
[2024-05-06 06:48:15] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.765574, train acc = 0.9333 train oa = 0.9333, test acc = 0.3563 test oa = 0.3322
[2024-05-06 06:47:38] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.045518, train acc = 1.0000 train oa = 1.0000, test acc = 0.3109 test oa = 0.2768
[2024-05-06 06:47:40] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.050542, train acc = 1.0000 train oa = 1.0000, test acc = 0.2833 test oa = 0.2716
[2024-05-06 06:47:42] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.072271, train acc = 1.0000 train oa = 1.0000, test acc = 0.2955 test oa = 0.2734
[2024-05-06 06:48:08] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.045518, train acc = 1.0000 train oa = 1.0000, test acc = 0.3109 test oa = 0.2768
[2024-05-06 06:48:09] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.050542, train acc = 1.0000 train oa = 1.0000, test acc = 0.2833 test oa = 0.2716
[2024-05-06 06:48:11] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.072271, train acc = 1.0000 train oa = 1.0000, test acc = 0.2955 test oa = 0.2734
[2024-05-06 06:54:05] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.049161, train acc = 1.0000 train oa = 1.0000, test acc = 0.2169 test oa = 0.1920
[2024-05-06 06:54:07] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.065443, train acc = 1.0000 train oa = 1.0000, test acc = 0.2693 test oa = 0.2284
[2024-05-06 06:54:09] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.097962, train acc = 1.0000 train oa = 1.0000, test acc = 0.2782 test oa = 0.2924
[2024-05-06 06:54:32] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.285925, train acc = 1.0000 train oa = 1.0000, test acc = 0.2639 test oa = 0.2612
[2024-05-06 06:54:34] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.134929, train acc = 1.0000 train oa = 1.0000, test acc = 0.2887 test oa = 0.2716
[2024-05-06 06:54:36] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.120236, train acc = 1.0000 train oa = 1.0000, test acc = 0.2450 test oa = 0.2699
[2024-05-06 07:02:46] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.104859, train acc = 1.0000 train oa = 1.0000, test acc = 0.2900 test oa = 0.2664
[2024-05-06 07:02:48] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.114748, train acc = 1.0000 train oa = 1.0000, test acc = 0.2839 test oa = 0.2751
[2024-05-06 07:02:50] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.170151, train acc = 1.0000 train oa = 1.0000, test acc = 0.2842 test oa = 0.2699
[2024-05-06 07:03:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050907, train acc = 1.0000 train oa = 1.0000, test acc = 0.2841 test oa = 0.2664
[2024-05-06 07:03:13] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.095039, train acc = 1.0000 train oa = 1.0000, test acc = 0.2789 test oa = 0.2457
[2024-05-06 07:03:15] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.029287, train acc = 1.0000 train oa = 1.0000, test acc = 0.2944 test oa = 0.2751
[2024-05-06 07:34:19] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.105750, train acc = 1.0000 train oa = 1.0000, test acc = 0.2572 test oa = 0.2249
[2024-05-06 07:34:21] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.224044, train acc = 1.0000 train oa = 1.0000, test acc = 0.2211 test oa = 0.1920
[2024-05-06 07:34:23] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.080994, train acc = 1.0000 train oa = 1.0000, test acc = 0.2779 test oa = 0.2526
[2024-05-06 07:35:42] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.078834, train acc = 1.0000 train oa = 1.0000, test acc = 0.2134 test oa = 0.2474
[2024-05-06 07:35:44] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.090724, train acc = 1.0000 train oa = 1.0000, test acc = 0.2276 test oa = 0.2526
[2024-05-06 07:35:46] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.104421, train acc = 1.0000 train oa = 1.0000, test acc = 0.2624 test oa = 0.2751
[2024-05-06 07:39:59] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.140003, train acc = 1.0000 train oa = 1.0000, test acc = 0.2648 test oa = 0.2422
[2024-05-06 07:40:01] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.070726, train acc = 1.0000 train oa = 1.0000, test acc = 0.2696 test oa = 0.2474
[2024-05-06 07:40:03] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.110202, train acc = 1.0000 train oa = 1.0000, test acc = 0.2655 test oa = 0.2664
[2024-05-06 08:05:53] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.068484, train acc = 1.0000 train oa = 1.0000, test acc = 0.2701 test oa = 0.2370
[2024-05-06 08:05:55] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.056248, train acc = 1.0000 train oa = 1.0000, test acc = 0.2601 test oa = 0.2232
[2024-05-06 08:05:57] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.071023, train acc = 1.0000 train oa = 1.0000, test acc = 0.3081 test oa = 0.2751
[2024-05-06 08:44:41] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.031516, train acc = 1.0000 train oa = 1.0000, test acc = 0.2330 test oa = 0.2076
[2024-05-06 08:44:43] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.027193, train acc = 1.0000 train oa = 1.0000, test acc = 0.2465 test oa = 0.2249
[2024-05-06 08:44:45] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.032646, train acc = 1.0000 train oa = 1.0000, test acc = 0.2604 test oa = 0.2284
[2024-05-06 08:49:07] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.015010, train acc = 1.0000 train oa = 1.0000, test acc = 0.2619 test oa = 0.2630
[2024-05-06 08:49:08] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.042179, train acc = 1.0000 train oa = 1.0000, test acc = 0.2391 test oa = 0.2163
[2024-05-06 08:49:10] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.029328, train acc = 1.0000 train oa = 1.0000, test acc = 0.2542 test oa = 0.2370
[2024-05-06 08:57:43] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050309, train acc = 1.0000 train oa = 1.0000, test acc = 0.2515 test oa = 0.2145
[2024-05-06 08:57:45] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.051185, train acc = 1.0000 train oa = 1.0000, test acc = 0.2416 test oa = 0.2215
[2024-05-06 08:57:47] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.074690, train acc = 1.0000 train oa = 1.0000, test acc = 0.2340 test oa = 0.1972
[2024-05-06 09:23:09] Evaluate_00: epoch = 0300, train time = 23 s, train loss = 0.461824, train acc = 0.9867 train oa = 0.9867, test acc = 0.3384 test oa = 0.3114
[2024-05-06 09:23:29] Evaluate_01: epoch = 0300, train time = 20 s, train loss = 0.586058, train acc = 0.9867 train oa = 0.9867, test acc = 0.3495 test oa = 0.3253
[2024-05-06 09:23:51] Evaluate_02: epoch = 0300, train time = 21 s, train loss = 0.558280, train acc = 0.9733 train oa = 0.9733, test acc = 0.3324 test oa = 0.3149
[2024-05-06 09:32:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.008592, train acc = 1.0000 train oa = 1.0000, test acc = 0.2149 test oa = 0.2163
[2024-05-06 09:32:28] Evaluate_01: epoch = 0300, train time = 1 s, train loss = 0.003236, train acc = 1.0000 train oa = 1.0000, test acc = 0.2409 test oa = 0.2215
[2024-05-06 09:32:30] Evaluate_02: epoch = 0300, train time = 1 s, train loss = 0.017928, train acc = 1.0000 train oa = 1.0000, test acc = 0.2200 test oa = 0.1955
[2024-05-06 10:18:25] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.267154, train acc = 0.7867 train oa = 0.7867, test acc = 0.2764 test oa = 0.2682
[2024-05-06 10:18:34] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 1.163368, train acc = 0.8000 train oa = 0.8000, test acc = 0.3205 test oa = 0.2976
[2024-05-06 10:18:44] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 1.144360, train acc = 0.8133 train oa = 0.8133, test acc = 0.3253 test oa = 0.3097
[2024-05-06 11:26:50] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.431699, train acc = 1.0000 train oa = 1.0000, test acc = 0.3506 test oa = 0.3304
[2024-05-06 11:26:56] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.391453, train acc = 1.0000 train oa = 1.0000, test acc = 0.3612 test oa = 0.3253
[2024-05-06 11:27:02] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.462123, train acc = 1.0000 train oa = 1.0000, test acc = 0.3608 test oa = 0.3183
[2024-05-06 12:38:54] Evaluate_00: epoch = 0300, train time = 27 s, train loss = 0.726534, train acc = 0.9467 train oa = 0.9467, test acc = 0.3658 test oa = 0.3460
[2024-05-06 12:39:16] Evaluate_01: epoch = 0300, train time = 22 s, train loss = 0.742750, train acc = 0.9600 train oa = 0.9600, test acc = 0.3440 test oa = 0.3166
[2024-05-06 12:39:37] Evaluate_02: epoch = 0300, train time = 21 s, train loss = 0.696023, train acc = 0.9600 train oa = 0.9600, test acc = 0.3585 test oa = 0.3339
[2024-05-06 13:03:54] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.974575, train acc = 0.8133 train oa = 0.8133, test acc = 0.3193 test oa = 0.3010
[2024-05-06 13:04:02] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.920090, train acc = 0.8800 train oa = 0.8800, test acc = 0.3262 test oa = 0.3253
[2024-05-06 13:04:11] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.112515, train acc = 0.7733 train oa = 0.7733, test acc = 0.3456 test oa = 0.3149
[2024-05-06 13:08:02] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.471167, train acc = 1.0000 train oa = 1.0000, test acc = 0.3396 test oa = 0.3114
[2024-05-06 13:08:08] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.862423, train acc = 0.9600 train oa = 0.9600, test acc = 0.3153 test oa = 0.2820
[2024-05-06 13:08:14] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.839787, train acc = 0.9733 train oa = 0.9733, test acc = 0.3488 test oa = 0.3028
[2024-05-06 13:40:41] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.769377, train acc = 0.9600 train oa = 0.9600, test acc = 0.3338 test oa = 0.3114
[2024-05-06 13:40:47] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.784222, train acc = 0.9600 train oa = 0.9600, test acc = 0.3357 test oa = 0.3010
[2024-05-06 13:40:53] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.660902, train acc = 1.0000 train oa = 1.0000, test acc = 0.3219 test oa = 0.3114
[2024-05-06 15:05:25] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.114235, train acc = 0.7333 train oa = 0.7333, test acc = 0.3213 test oa = 0.3322
[2024-05-06 15:05:31] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.807634, train acc = 0.9200 train oa = 0.9200, test acc = 0.3527 test oa = 0.3478
[2024-05-06 15:05:37] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.801529, train acc = 0.8933 train oa = 0.8933, test acc = 0.3434 test oa = 0.3616
[2024-05-06 15:21:21] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.741664, train acc = 0.9733 train oa = 0.9733, test acc = 0.3400 test oa = 0.3460
[2024-05-06 15:21:30] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.604829, train acc = 0.9867 train oa = 0.9867, test acc = 0.3481 test oa = 0.3322
[2024-05-06 15:21:39] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.852943, train acc = 0.9600 train oa = 0.9600, test acc = 0.3468 test oa = 0.3720
[2024-05-06 15:21:44] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.218585, train acc = 0.7467 train oa = 0.7467, test acc = 0.2975 test oa = 0.2976
[2024-05-06 15:21:50] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.951683, train acc = 0.8533 train oa = 0.8533, test acc = 0.3456 test oa = 0.3270
[2024-05-06 15:21:56] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.915715, train acc = 0.8800 train oa = 0.8800, test acc = 0.3378 test oa = 0.2993
[2024-05-06 16:30:24] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.697288, train acc = 0.9333 train oa = 0.9333, test acc = 0.3701 test oa = 0.3304
[2024-05-06 16:30:30] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.721158, train acc = 0.9733 train oa = 0.9733, test acc = 0.3608 test oa = 0.3460
[2024-05-06 16:30:36] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.765814, train acc = 0.9333 train oa = 0.9333, test acc = 0.3714 test oa = 0.3443
[2024-05-06 16:44:27] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.715382, train acc = 0.9867 train oa = 0.9867, test acc = 0.3527 test oa = 0.3149
[2024-05-06 16:44:33] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.930026, train acc = 0.9333 train oa = 0.9333, test acc = 0.3389 test oa = 0.2941
[2024-05-06 16:44:39] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.638852, train acc = 0.9867 train oa = 0.9867, test acc = 0.3645 test oa = 0.3270
[2024-05-06 17:13:22] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 0.715382, train acc = 0.9867 train oa = 0.9867, test acc = 0.3527 test oa = 0.3149
[2024-05-06 17:13:31] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 0.930026, train acc = 0.9333 train oa = 0.9333, test acc = 0.3389 test oa = 0.2941
[2024-05-06 17:13:40] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 0.638852, train acc = 0.9867 train oa = 0.9867, test acc = 0.3645 test oa = 0.3270
[2024-05-06 17:52:33] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.715382, train acc = 0.9867 train oa = 0.9867, test acc = 0.3527 test oa = 0.3149
[2024-05-06 17:52:39] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.930026, train acc = 0.9333 train oa = 0.9333, test acc = 0.3389 test oa = 0.2941
[2024-05-06 17:52:45] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.638852, train acc = 0.9867 train oa = 0.9867, test acc = 0.3645 test oa = 0.3270
[2024-05-06 20:03:02] Evaluate_00: epoch = 0300, train time = 23 s, train loss = 1.165277, train acc = 0.7733 train oa = 0.7733, test acc = 0.3414 test oa = 0.3235
[2024-05-06 20:03:22] Evaluate_01: epoch = 0300, train time = 19 s, train loss = 1.103872, train acc = 0.8933 train oa = 0.8933, test acc = 0.3448 test oa = 0.3131
[2024-05-06 20:03:44] Evaluate_02: epoch = 0300, train time = 21 s, train loss = 1.026337, train acc = 0.8667 train oa = 0.8667, test acc = 0.3283 test oa = 0.3339
[2024-05-06 20:10:31] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.665217, train acc = 0.9867 train oa = 0.9867, test acc = 0.3508 test oa = 0.3304
[2024-05-06 20:10:37] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.919037, train acc = 0.8800 train oa = 0.8800, test acc = 0.3400 test oa = 0.3183
[2024-05-06 20:10:43] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.566124, train acc = 1.0000 train oa = 1.0000, test acc = 0.3623 test oa = 0.3547
[2024-05-06 21:17:01] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.065282, train acc = 0.8800 train oa = 0.8800, test acc = 0.3223 test oa = 0.3495
[2024-05-06 21:17:07] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.049815, train acc = 0.8533 train oa = 0.8533, test acc = 0.3423 test oa = 0.3599
[2024-05-06 21:17:12] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.013542, train acc = 0.8267 train oa = 0.8267, test acc = 0.3596 test oa = 0.3651
[2024-05-06 21:44:30] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.065282, train acc = 0.8800 train oa = 0.8800, test acc = 0.3223 test oa = 0.3495
[2024-05-06 21:44:39] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.049815, train acc = 0.8533 train oa = 0.8533, test acc = 0.3423 test oa = 0.3599
[2024-05-06 21:44:48] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.013542, train acc = 0.8267 train oa = 0.8267, test acc = 0.3596 test oa = 0.3651
[2024-05-06 21:52:19] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.919283, train acc = 0.9200 train oa = 0.9200, test acc = 0.3550 test oa = 0.3149
[2024-05-06 21:52:25] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.118684, train acc = 0.8133 train oa = 0.8133, test acc = 0.2998 test oa = 0.2595
[2024-05-06 21:52:31] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.961349, train acc = 0.8800 train oa = 0.8800, test acc = 0.3470 test oa = 0.3010
[2024-05-07 00:46:45] Evaluate_00: epoch = 0300, train time = 23 s, train loss = 0.919283, train acc = 0.9200 train oa = 0.9200, test acc = 0.3550 test oa = 0.3149
[2024-05-07 00:47:06] Evaluate_01: epoch = 0300, train time = 21 s, train loss = 1.118684, train acc = 0.8133 train oa = 0.8133, test acc = 0.2998 test oa = 0.2595
[2024-05-07 00:47:27] Evaluate_02: epoch = 0300, train time = 20 s, train loss = 0.961349, train acc = 0.8800 train oa = 0.8800, test acc = 0.3470 test oa = 0.3010
[2024-05-07 00:41:43] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.123492, train acc = 0.7733 train oa = 0.7733, test acc = 0.3271 test oa = 0.3408
[2024-05-07 00:41:49] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.296656, train acc = 0.7067 train oa = 0.7067, test acc = 0.3127 test oa = 0.3114
[2024-05-07 00:41:54] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.366107, train acc = 0.6533 train oa = 0.6533, test acc = 0.2719 test oa = 0.2612
[2024-05-07 01:18:12] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.123492, train acc = 0.7733 train oa = 0.7733, test acc = 0.3271 test oa = 0.3408
[2024-05-07 01:18:18] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.296656, train acc = 0.7067 train oa = 0.7067, test acc = 0.3127 test oa = 0.3114
[2024-05-07 01:18:24] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.366107, train acc = 0.6533 train oa = 0.6533, test acc = 0.2719 test oa = 0.2612
[2024-05-07 02:14:25] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.123492, train acc = 0.7733 train oa = 0.7733, test acc = 0.3271 test oa = 0.3408
[2024-05-07 02:14:34] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.296656, train acc = 0.7067 train oa = 0.7067, test acc = 0.3127 test oa = 0.3114
[2024-05-07 02:14:42] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.366107, train acc = 0.6533 train oa = 0.6533, test acc = 0.2719 test oa = 0.2612
[2024-05-07 03:28:56] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.898801, train acc = 0.9200 train oa = 0.9200, test acc = 0.3245 test oa = 0.3408
[2024-05-07 03:29:02] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.329509, train acc = 0.7200 train oa = 0.7200, test acc = 0.3509 test oa = 0.3183
[2024-05-07 03:29:08] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.832667, train acc = 0.9333 train oa = 0.9333, test acc = 0.3532 test oa = 0.3460
[2024-05-07 04:06:35] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.898801, train acc = 0.9200 train oa = 0.9200, test acc = 0.3245 test oa = 0.3408
[2024-05-07 04:06:42] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.329509, train acc = 0.7200 train oa = 0.7200, test acc = 0.3509 test oa = 0.3183
[2024-05-07 04:06:48] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.832667, train acc = 0.9333 train oa = 0.9333, test acc = 0.3532 test oa = 0.3460
[2024-05-07 05:50:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.898801, train acc = 0.9200 train oa = 0.9200, test acc = 0.3245 test oa = 0.3408
[2024-05-07 05:50:39] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 1.329509, train acc = 0.7200 train oa = 0.7200, test acc = 0.3509 test oa = 0.3183
[2024-05-07 05:50:49] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 0.832667, train acc = 0.9333 train oa = 0.9333, test acc = 0.3532 test oa = 0.3460
[2024-05-07 06:22:07] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.073212, train acc = 0.8267 train oa = 0.8267, test acc = 0.3444 test oa = 0.3218
[2024-05-07 06:22:13] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.770965, train acc = 0.9733 train oa = 0.9733, test acc = 0.3570 test oa = 0.3235
[2024-05-07 06:22:19] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.892313, train acc = 0.8667 train oa = 0.8667, test acc = 0.3286 test oa = 0.3218
[2024-05-07 07:02:28] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.073212, train acc = 0.8267 train oa = 0.8267, test acc = 0.3444 test oa = 0.3218
[2024-05-07 07:02:34] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.770965, train acc = 0.9733 train oa = 0.9733, test acc = 0.3570 test oa = 0.3235
[2024-05-07 07:02:40] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.892313, train acc = 0.8667 train oa = 0.8667, test acc = 0.3286 test oa = 0.3218
[2024-05-07 09:31:02] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.073212, train acc = 0.8267 train oa = 0.8267, test acc = 0.3444 test oa = 0.3218
[2024-05-07 09:31:10] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.770965, train acc = 0.9733 train oa = 0.9733, test acc = 0.3570 test oa = 0.3235
[2024-05-07 09:31:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.892313, train acc = 0.8667 train oa = 0.8667, test acc = 0.3286 test oa = 0.3218
[2024-05-07 09:43:37] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.336521, train acc = 0.6400 train oa = 0.6400, test acc = 0.2772 test oa = 0.2993
[2024-05-07 09:43:43] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.079752, train acc = 0.8267 train oa = 0.8267, test acc = 0.3243 test oa = 0.3460
[2024-05-07 09:43:48] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.145525, train acc = 0.7867 train oa = 0.7867, test acc = 0.3122 test oa = 0.3166
[2024-05-07 09:51:42] Evaluate_00: epoch = 0300, train time = 24 s, train loss = 1.123492, train acc = 0.7733 train oa = 0.7733, test acc = 0.3271 test oa = 0.3408
[2024-05-07 09:52:03] Evaluate_01: epoch = 0300, train time = 20 s, train loss = 1.296656, train acc = 0.7067 train oa = 0.7067, test acc = 0.3127 test oa = 0.3114
[2024-05-07 09:52:24] Evaluate_02: epoch = 0300, train time = 20 s, train loss = 1.366107, train acc = 0.6533 train oa = 0.6533, test acc = 0.2719 test oa = 0.2612
[2024-05-07 10:24:37] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.336521, train acc = 0.6400 train oa = 0.6400, test acc = 0.2772 test oa = 0.2993
[2024-05-07 10:24:44] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.079752, train acc = 0.8267 train oa = 0.8267, test acc = 0.3243 test oa = 0.3460
[2024-05-07 10:24:50] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.145525, train acc = 0.7867 train oa = 0.7867, test acc = 0.3122 test oa = 0.3166
[2024-05-07 13:03:58] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.780937, train acc = 0.9067 train oa = 0.9067, test acc = 0.3335 test oa = 0.3304
[2024-05-07 13:04:04] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.888240, train acc = 0.9067 train oa = 0.9067, test acc = 0.3319 test oa = 0.3287
[2024-05-07 13:04:10] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.069452, train acc = 0.8400 train oa = 0.8400, test acc = 0.3255 test oa = 0.3218
[2024-05-07 13:19:39] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.317086, train acc = 0.6933 train oa = 0.6933, test acc = 0.3277 test oa = 0.3097
[2024-05-07 13:19:45] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.126498, train acc = 0.7867 train oa = 0.7867, test acc = 0.3373 test oa = 0.3443
[2024-05-07 13:19:51] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.327343, train acc = 0.7067 train oa = 0.7067, test acc = 0.3469 test oa = 0.3339
[2024-05-07 13:49:23] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.064264, train acc = 0.8533 train oa = 0.8533, test acc = 0.3056 test oa = 0.3201
[2024-05-07 13:49:32] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.953694, train acc = 0.8667 train oa = 0.8667, test acc = 0.3541 test oa = 0.3270
[2024-05-07 13:49:41] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.997582, train acc = 0.8667 train oa = 0.8667, test acc = 0.3047 test oa = 0.3062
[2024-05-07 15:19:56] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.940501, train acc = 0.8400 train oa = 0.8400, test acc = 0.3272 test oa = 0.3270
[2024-05-07 15:20:02] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.020940, train acc = 0.8400 train oa = 0.8400, test acc = 0.3468 test oa = 0.3149
[2024-05-07 15:20:08] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 1.195845, train acc = 0.7600 train oa = 0.7600, test acc = 0.3454 test oa = 0.3339
[2024-05-07 16:35:58] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.979535, train acc = 0.8800 train oa = 0.8800, test acc = 0.3071 test oa = 0.2889
[2024-05-07 16:36:06] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.829649, train acc = 0.9733 train oa = 0.9733, test acc = 0.3371 test oa = 0.3131
[2024-05-07 16:36:15] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 1.013958, train acc = 0.8800 train oa = 0.8800, test acc = 0.3705 test oa = 0.3685
[2024-05-07 16:41:07] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.064264, train acc = 0.8533 train oa = 0.8533, test acc = 0.3056 test oa = 0.3201
[2024-05-07 16:41:13] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 0.953694, train acc = 0.8667 train oa = 0.8667, test acc = 0.3541 test oa = 0.3270
[2024-05-07 16:41:19] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.997582, train acc = 0.8667 train oa = 0.8667, test acc = 0.3047 test oa = 0.3062
[2024-05-07 17:31:39] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.064264, train acc = 0.8533 train oa = 0.8533, test acc = 0.3056 test oa = 0.3201
[2024-05-07 17:31:46] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.953694, train acc = 0.8667 train oa = 0.8667, test acc = 0.3541 test oa = 0.3270
[2024-05-07 17:31:54] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.997582, train acc = 0.8667 train oa = 0.8667, test acc = 0.3047 test oa = 0.3062
[2024-05-07 19:29:30] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.243742, train acc = 0.7200 train oa = 0.7200, test acc = 0.3015 test oa = 0.2768
[2024-05-07 19:29:36] Evaluate_01: epoch = 0300, train time = 5 s, train loss = 1.055605, train acc = 0.8133 train oa = 0.8133, test acc = 0.3612 test oa = 0.3304
[2024-05-07 19:29:42] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.671695, train acc = 0.9467 train oa = 0.9467, test acc = 0.3692 test oa = 0.3235
[2024-05-07 21:03:07] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.920856, train acc = 0.8933 train oa = 0.8933, test acc = 0.3472 test oa = 0.3391
[2024-05-07 21:03:14] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.860038, train acc = 0.8933 train oa = 0.8933, test acc = 0.3389 test oa = 0.3183
[2024-05-07 21:03:22] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.834628, train acc = 0.9467 train oa = 0.9467, test acc = 0.3563 test oa = 0.3547
[2024-05-07 22:48:43] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.669138, train acc = 0.9733 train oa = 0.9733, test acc = 0.3631 test oa = 0.3824
[2024-05-07 22:48:51] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.823189, train acc = 0.9067 train oa = 0.9067, test acc = 0.3695 test oa = 0.3754
[2024-05-07 22:48:58] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.903510, train acc = 0.8667 train oa = 0.8667, test acc = 0.3572 test oa = 0.3702
[2024-05-08 00:34:15] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.898595, train acc = 0.8933 train oa = 0.8933, test acc = 0.3252 test oa = 0.3028
[2024-05-08 00:34:23] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.999804, train acc = 0.8933 train oa = 0.8933, test acc = 0.3307 test oa = 0.2889
[2024-05-08 00:34:32] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.542159, train acc = 0.9867 train oa = 0.9867, test acc = 0.3535 test oa = 0.3287

================== Exp 0 ==================
 
[2024-05-08 10:16:57] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.245829, train acc = 0.9733 train oa = 0.9733, test acc = 0.0779 test oa = 0.0900
Evaluate 1, mean = 0.0779 std = 0.0000
-------------------------
[2024-05-08 10:17:00] iter = 0000, loss = 101.8088
[2024-05-08 10:17:32] iter = 0010, loss = 71.4109
[2024-05-08 10:18:07] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.246149, train acc = 1.0000 train oa = 1.0000, test acc = 0.2813 test oa = 0.2820
Evaluate 1, mean = 0.2813 std = 0.0000
-------------------------
[2024-05-08 10:18:11] iter = 0020, loss = 64.0139
[2024-05-08 10:18:43] iter = 0030, loss = 67.8301
[2024-05-08 10:19:18] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.133592, train acc = 1.0000 train oa = 1.0000, test acc = 0.2981 test oa = 0.2734
Evaluate 1, mean = 0.2981 std = 0.0000
-------------------------
[2024-05-08 10:19:22] iter = 0040, loss = 66.7208
[2024-05-08 10:19:55] iter = 0050, loss = 66.2653
[2024-05-08 10:20:33] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.090020, train acc = 1.0000 train oa = 1.0000, test acc = 0.2916 test oa = 0.2993
Evaluate 1, mean = 0.2916 std = 0.0000
-------------------------
[2024-05-08 10:20:37] iter = 0060, loss = 64.2033
[2024-05-08 10:21:13] iter = 0070, loss = 73.3362
[2024-05-08 10:21:52] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.103465, train acc = 0.9867 train oa = 0.9867, test acc = 0.3578 test oa = 0.3408
Evaluate 1, mean = 0.3578 std = 0.0000
-------------------------
[2024-05-08 10:21:56] iter = 0080, loss = 60.1343
[2024-05-08 10:22:33] iter = 0090, loss = 58.1170
[2024-05-08 10:23:13] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.124767, train acc = 1.0000 train oa = 1.0000, test acc = 0.3500 test oa = 0.3374
Evaluate 1, mean = 0.3500 std = 0.0000
-------------------------
[2024-05-08 10:23:17] iter = 0100, loss = 62.9332
[2024-05-08 10:23:54] iter = 0110, loss = 61.4900
[2024-05-08 10:24:34] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.080816, train acc = 1.0000 train oa = 1.0000, test acc = 0.3247 test oa = 0.3235
Evaluate 1, mean = 0.3247 std = 0.0000
-------------------------
[2024-05-08 10:24:38] iter = 0120, loss = 67.8909
[2024-05-08 10:25:15] iter = 0130, loss = 62.8062
[2024-05-08 10:25:55] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.103807, train acc = 1.0000 train oa = 1.0000, test acc = 0.3419 test oa = 0.3408
Evaluate 1, mean = 0.3419 std = 0.0000
-------------------------
[2024-05-08 10:25:59] iter = 0140, loss = 59.4359
[2024-05-08 10:26:36] iter = 0150, loss = 59.9934
[2024-05-08 10:27:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.137786, train acc = 1.0000 train oa = 1.0000, test acc = 0.3763 test oa = 0.3374
Evaluate 1, mean = 0.3763 std = 0.0000
-------------------------
[2024-05-08 10:27:20] iter = 0160, loss = 54.7009
[2024-05-08 10:27:57] iter = 0170, loss = 59.4536
[2024-05-08 10:28:38] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.101432, train acc = 1.0000 train oa = 1.0000, test acc = 0.3562 test oa = 0.3374
Evaluate 1, mean = 0.3562 std = 0.0000
-------------------------
[2024-05-08 10:28:42] iter = 0180, loss = 62.1913
[2024-05-08 10:29:19] iter = 0190, loss = 66.3594
[2024-05-08 10:29:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.055482, train acc = 1.0000 train oa = 1.0000, test acc = 0.3065 test oa = 0.2958
Evaluate 1, mean = 0.3065 std = 0.0000
-------------------------
[2024-05-08 10:30:03] iter = 0200, loss = 58.8400
[2024-05-08 10:30:40] iter = 0210, loss = 57.4689
[2024-05-08 10:31:21] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.032627, train acc = 1.0000 train oa = 1.0000, test acc = 0.3583 test oa = 0.3339
Evaluate 1, mean = 0.3583 std = 0.0000
-------------------------
[2024-05-08 10:31:25] iter = 0220, loss = 57.9222
[2024-05-08 10:32:02] iter = 0230, loss = 55.0072
[2024-05-08 10:32:43] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.134108, train acc = 1.0000 train oa = 1.0000, test acc = 0.3775 test oa = 0.3564
Evaluate 1, mean = 0.3775 std = 0.0000
-------------------------
[2024-05-08 10:32:46] iter = 0240, loss = 57.8051
[2024-05-08 10:33:23] iter = 0250, loss = 60.7577
[2024-05-08 10:34:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.066445, train acc = 1.0000 train oa = 1.0000, test acc = 0.3498 test oa = 0.3235
Evaluate 1, mean = 0.3498 std = 0.0000
-------------------------
[2024-05-08 10:34:08] iter = 0260, loss = 59.9994
[2024-05-08 10:34:45] iter = 0270, loss = 60.0542
[2024-05-08 10:35:27] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.152891, train acc = 1.0000 train oa = 1.0000, test acc = 0.3382 test oa = 0.3028
Evaluate 1, mean = 0.3382 std = 0.0000
-------------------------
[2024-05-08 10:35:31] iter = 0280, loss = 59.6941
[2024-05-08 10:36:08] iter = 0290, loss = 60.1591
[2024-05-08 10:36:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.104463, train acc = 1.0000 train oa = 1.0000, test acc = 0.3570 test oa = 0.3235
Evaluate 1, mean = 0.3570 std = 0.0000
-------------------------
[2024-05-08 10:36:52] iter = 0300, loss = 54.0127
[2024-05-08 10:37:30] iter = 0310, loss = 58.8437
[2024-05-08 10:38:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.050270, train acc = 1.0000 train oa = 1.0000, test acc = 0.3416 test oa = 0.3478
Evaluate 1, mean = 0.3416 std = 0.0000
-------------------------
[2024-05-08 10:38:15] iter = 0320, loss = 57.5391
[2024-05-08 10:38:52] iter = 0330, loss = 58.6375
[2024-05-08 10:39:33] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.133923, train acc = 0.9867 train oa = 0.9867, test acc = 0.3207 test oa = 0.3028
Evaluate 1, mean = 0.3207 std = 0.0000
-------------------------
[2024-05-08 10:39:37] iter = 0340, loss = 60.5710
[2024-05-08 10:40:14] iter = 0350, loss = 56.1133
[2024-05-08 10:40:55] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.082832, train acc = 1.0000 train oa = 1.0000, test acc = 0.2936 test oa = 0.2664
Evaluate 1, mean = 0.2936 std = 0.0000
-------------------------
[2024-05-08 10:40:59] iter = 0360, loss = 56.8134
[2024-05-08 10:41:36] iter = 0370, loss = 58.3538
[2024-05-08 10:42:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.184925, train acc = 0.9867 train oa = 0.9867, test acc = 0.3501 test oa = 0.3495
Evaluate 1, mean = 0.3501 std = 0.0000
-------------------------
[2024-05-08 10:42:21] iter = 0380, loss = 57.1719
[2024-05-08 10:42:59] iter = 0390, loss = 56.3931
[2024-05-08 10:43:40] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.136157, train acc = 1.0000 train oa = 1.0000, test acc = 0.3220 test oa = 0.3235
Evaluate 1, mean = 0.3220 std = 0.0000
-------------------------
[2024-05-08 10:43:44] iter = 0400, loss = 53.9277
[2024-05-08 10:44:21] iter = 0410, loss = 56.5088
[2024-05-08 10:45:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.173182, train acc = 1.0000 train oa = 1.0000, test acc = 0.3479 test oa = 0.3460
Evaluate 1, mean = 0.3479 std = 0.0000
-------------------------
[2024-05-08 10:45:07] iter = 0420, loss = 54.1863
[2024-05-08 10:45:44] iter = 0430, loss = 56.0119
[2024-05-08 10:46:26] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.107467, train acc = 1.0000 train oa = 1.0000, test acc = 0.3657 test oa = 0.3651
Evaluate 1, mean = 0.3657 std = 0.0000
-------------------------
[2024-05-08 10:46:29] iter = 0440, loss = 53.5000
[2024-05-08 10:47:06] iter = 0450, loss = 59.8526
[2024-05-08 10:47:48] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.142348, train acc = 1.0000 train oa = 1.0000, test acc = 0.3251 test oa = 0.3131
Evaluate 1, mean = 0.3251 std = 0.0000
-------------------------
[2024-05-08 10:47:52] iter = 0460, loss = 57.7792
[2024-05-08 10:48:29] iter = 0470, loss = 57.8420
[2024-05-08 10:49:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.210180, train acc = 1.0000 train oa = 1.0000, test acc = 0.3127 test oa = 0.3028
Evaluate 1, mean = 0.3127 std = 0.0000
-------------------------
[2024-05-08 10:49:14] iter = 0480, loss = 58.5153
[2024-05-08 10:49:52] iter = 0490, loss = 50.0039
[2024-05-08 10:50:33] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.126542, train acc = 1.0000 train oa = 1.0000, test acc = 0.3546 test oa = 0.3495
Evaluate 1, mean = 0.3546 std = 0.0000
-------------------------
[2024-05-08 10:50:37] iter = 0500, loss = 56.2575
[2024-05-08 10:51:15] iter = 0510, loss = 58.7471
[2024-05-08 10:51:56] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.066345, train acc = 1.0000 train oa = 1.0000, test acc = 0.3668 test oa = 0.3599
Evaluate 1, mean = 0.3668 std = 0.0000
-------------------------
[2024-05-08 10:52:00] iter = 0520, loss = 59.3929
[2024-05-08 10:52:38] iter = 0530, loss = 48.4731
[2024-05-08 10:53:19] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.145042, train acc = 1.0000 train oa = 1.0000, test acc = 0.3912 test oa = 0.3616
Evaluate 1, mean = 0.3912 std = 0.0000
-------------------------
[2024-05-08 10:53:23] iter = 0540, loss = 55.0499
[2024-05-08 10:54:01] iter = 0550, loss = 57.9310
[2024-05-08 10:54:42] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.074899, train acc = 0.9867 train oa = 0.9867, test acc = 0.3578 test oa = 0.3201
Evaluate 1, mean = 0.3578 std = 0.0000
-------------------------
[2024-05-08 10:54:46] iter = 0560, loss = 58.9280
[2024-05-08 10:55:24] iter = 0570, loss = 58.6562
[2024-05-08 10:56:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.116444, train acc = 1.0000 train oa = 1.0000, test acc = 0.3386 test oa = 0.3062
Evaluate 1, mean = 0.3386 std = 0.0000
-------------------------
[2024-05-08 10:56:09] iter = 0580, loss = 60.4962
[2024-05-08 10:56:47] iter = 0590, loss = 55.6764
[2024-05-08 10:57:28] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.357586, train acc = 0.9467 train oa = 0.9467, test acc = 0.3624 test oa = 0.3633
Evaluate 1, mean = 0.3624 std = 0.0000
-------------------------
[2024-05-08 10:57:32] iter = 0600, loss = 56.3560
[2024-05-08 10:58:09] iter = 0610, loss = 53.9665
[2024-05-08 10:58:51] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.302809, train acc = 0.9867 train oa = 0.9867, test acc = 0.3137 test oa = 0.2924
Evaluate 1, mean = 0.3137 std = 0.0000
-------------------------
[2024-05-08 10:58:55] iter = 0620, loss = 55.1928
[2024-05-08 10:59:33] iter = 0630, loss = 59.9521
[2024-05-08 11:00:14] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.132087, train acc = 1.0000 train oa = 1.0000, test acc = 0.3118 test oa = 0.2889
Evaluate 1, mean = 0.3118 std = 0.0000
-------------------------
[2024-05-08 11:00:18] iter = 0640, loss = 53.8470
[2024-05-08 11:00:56] iter = 0650, loss = 54.7581
[2024-05-08 11:01:37] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.206694, train acc = 0.9867 train oa = 0.9867, test acc = 0.3561 test oa = 0.2958
Evaluate 1, mean = 0.3561 std = 0.0000
-------------------------
[2024-05-08 11:01:41] iter = 0660, loss = 58.1867
[2024-05-08 11:02:18] iter = 0670, loss = 57.5683
[2024-05-08 11:03:00] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.070837, train acc = 1.0000 train oa = 1.0000, test acc = 0.3370 test oa = 0.3201
Evaluate 1, mean = 0.3370 std = 0.0000
-------------------------
[2024-05-08 11:03:03] iter = 0680, loss = 55.9742
[2024-05-08 11:03:41] iter = 0690, loss = 55.8864
[2024-05-08 11:04:23] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.129231, train acc = 1.0000 train oa = 1.0000, test acc = 0.3447 test oa = 0.2941
Evaluate 1, mean = 0.3447 std = 0.0000
-------------------------
[2024-05-08 11:04:27] iter = 0700, loss = 54.5744
[2024-05-08 11:05:04] iter = 0710, loss = 56.7222
[2024-05-08 11:05:45] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.234656, train acc = 0.9867 train oa = 0.9867, test acc = 0.3248 test oa = 0.3201
Evaluate 1, mean = 0.3248 std = 0.0000
-------------------------
[2024-05-08 11:05:49] iter = 0720, loss = 56.2884
[2024-05-08 11:06:27] iter = 0730, loss = 55.2925
[2024-05-08 11:07:08] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.100435, train acc = 1.0000 train oa = 1.0000, test acc = 0.3203 test oa = 0.2993
Evaluate 1, mean = 0.3203 std = 0.0000
-------------------------
[2024-05-08 11:07:12] iter = 0740, loss = 54.9224
[2024-05-08 11:07:50] iter = 0750, loss = 55.2591
[2024-05-08 11:08:32] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.189925, train acc = 1.0000 train oa = 1.0000, test acc = 0.3403 test oa = 0.3270
Evaluate 1, mean = 0.3403 std = 0.0000
-------------------------
[2024-05-08 11:08:35] iter = 0760, loss = 53.7811
[2024-05-08 11:09:13] iter = 0770, loss = 54.4150
[2024-05-08 11:09:55] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.163687, train acc = 0.9867 train oa = 0.9867, test acc = 0.3572 test oa = 0.3322
Evaluate 1, mean = 0.3572 std = 0.0000
-------------------------
[2024-05-08 11:09:59] iter = 0780, loss = 52.5912
[2024-05-08 11:10:36] iter = 0790, loss = 54.2545
[2024-05-08 11:11:18] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.133191, train acc = 1.0000 train oa = 1.0000, test acc = 0.3287 test oa = 0.2924
Evaluate 1, mean = 0.3287 std = 0.0000
-------------------------
[2024-05-08 11:11:22] iter = 0800, loss = 56.2897
[2024-05-08 11:11:59] iter = 0810, loss = 54.2081
[2024-05-08 11:12:41] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.117639, train acc = 1.0000 train oa = 1.0000, test acc = 0.3690 test oa = 0.3339
Evaluate 1, mean = 0.3690 std = 0.0000
-------------------------
[2024-05-08 11:12:45] iter = 0820, loss = 52.7700
[2024-05-08 11:13:22] iter = 0830, loss = 54.9859
[2024-05-08 11:14:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.379256, train acc = 0.9600 train oa = 0.9600, test acc = 0.3172 test oa = 0.3010
Evaluate 1, mean = 0.3172 std = 0.0000
-------------------------
[2024-05-08 11:14:07] iter = 0840, loss = 54.0126
[2024-05-08 11:14:45] iter = 0850, loss = 55.6697
[2024-05-08 11:15:26] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.107330, train acc = 1.0000 train oa = 1.0000, test acc = 0.3760 test oa = 0.3304
Evaluate 1, mean = 0.3760 std = 0.0000
-------------------------
[2024-05-08 11:15:30] iter = 0860, loss = 54.9011
[2024-05-08 11:16:08] iter = 0870, loss = 53.3493
[2024-05-08 11:16:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.083278, train acc = 1.0000 train oa = 1.0000, test acc = 0.3482 test oa = 0.3287
Evaluate 1, mean = 0.3482 std = 0.0000
-------------------------
[2024-05-08 11:16:53] iter = 0880, loss = 56.1004
[2024-05-08 11:17:30] iter = 0890, loss = 53.6660
[2024-05-08 11:18:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.154370, train acc = 1.0000 train oa = 1.0000, test acc = 0.3472 test oa = 0.3339
Evaluate 1, mean = 0.3472 std = 0.0000
-------------------------
[2024-05-08 11:18:15] iter = 0900, loss = 52.0713
[2024-05-08 11:18:53] iter = 0910, loss = 56.6096
[2024-05-08 11:19:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.147336, train acc = 1.0000 train oa = 1.0000, test acc = 0.3717 test oa = 0.3529
Evaluate 1, mean = 0.3717 std = 0.0000
-------------------------
[2024-05-08 11:19:38] iter = 0920, loss = 55.9924
[2024-05-08 11:20:16] iter = 0930, loss = 56.9197
[2024-05-08 11:20:58] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.206201, train acc = 1.0000 train oa = 1.0000, test acc = 0.3080 test oa = 0.2889
Evaluate 1, mean = 0.3080 std = 0.0000
-------------------------
[2024-05-08 11:21:01] iter = 0940, loss = 53.2166
[2024-05-08 11:21:39] iter = 0950, loss = 56.9370
[2024-05-08 11:22:21] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.115547, train acc = 1.0000 train oa = 1.0000, test acc = 0.3356 test oa = 0.3270
Evaluate 1, mean = 0.3356 std = 0.0000
-------------------------
[2024-05-08 11:22:24] iter = 0960, loss = 53.0098
[2024-05-08 11:23:02] iter = 0970, loss = 52.8810
[2024-05-08 11:23:44] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.195848, train acc = 0.9867 train oa = 0.9867, test acc = 0.3224 test oa = 0.2958
Evaluate 1, mean = 0.3224 std = 0.0000
-------------------------
[2024-05-08 11:23:47] iter = 0980, loss = 52.6165
[2024-05-08 11:24:25] iter = 0990, loss = 54.8963
[2024-05-08 11:25:07] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.232771, train acc = 0.9733 train oa = 0.9733, test acc = 0.3270 test oa = 0.3097
Evaluate 1, mean = 0.3270 std = 0.0000
-------------------------
[2024-05-08 11:25:10] iter = 1000, loss = 50.7000

================== Exp 0 ==================
 
[2024-05-20 21:55:34] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.014367, train acc = 1.0000 train oa = 1.0000, test acc = 0.1017 test oa = 0.0813
Evaluate 1, mean = 0.1017 std = 0.0000
-------------------------
[2024-05-20 21:55:35] iter = 0000, loss = 158.2997
[2024-05-20 21:55:39] iter = 0010, loss = 113.3284

================== Exp 0 ==================
 
[2024-05-20 21:55:44] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050789, train acc = 1.0000 train oa = 1.0000, test acc = 0.2343 test oa = 0.2353
Evaluate 1, mean = 0.2343 std = 0.0000
-------------------------
[2024-05-20 21:55:45] iter = 0020, loss = 127.5617
[2024-05-20 21:55:47] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.863413, train acc = 0.4667 train oa = 0.4667, test acc = 0.0961 test oa = 0.0675
Evaluate 1, mean = 0.0961 std = 0.0000
-------------------------
[2024-05-20 21:55:48] iter = 0030, loss = 129.7004
[2024-05-20 21:55:52] iter = 0000, loss = 108.8079
[2024-05-20 21:55:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.095954, train acc = 1.0000 train oa = 1.0000, test acc = 0.2475 test oa = 0.2163
Evaluate 1, mean = 0.2475 std = 0.0000
-------------------------
[2024-05-20 21:55:54] iter = 0040, loss = 143.8905
[2024-05-20 21:55:58] iter = 0050, loss = 116.0015
[2024-05-20 21:56:04] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.064986, train acc = 1.0000 train oa = 1.0000, test acc = 0.2262 test oa = 0.2145
Evaluate 1, mean = 0.2262 std = 0.0000
-------------------------
[2024-05-20 21:56:04] iter = 0060, loss = 129.7810
[2024-05-20 21:56:08] iter = 0070, loss = 135.8596
[2024-05-20 21:56:13] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.048004, train acc = 1.0000 train oa = 1.0000, test acc = 0.2489 test oa = 0.2318
Evaluate 1, mean = 0.2489 std = 0.0000
-------------------------
[2024-05-20 21:56:14] iter = 0080, loss = 131.3324
[2024-05-20 21:56:17] iter = 0090, loss = 140.6644

================== Exp 0 ==================
 
[2024-05-20 22:02:52] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.014367, train acc = 1.0000 train oa = 1.0000, test acc = 0.1017 test oa = 0.0813
Evaluate 1, mean = 0.1017 std = 0.0000
-------------------------
[2024-05-20 22:02:52] iter = 0000, loss = 158.2997
[2024-05-20 22:02:56] iter = 0010, loss = 113.3284

================== Exp 0 ==================
 
[2024-05-20 22:03:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050789, train acc = 1.0000 train oa = 1.0000, test acc = 0.2343 test oa = 0.2353
Evaluate 1, mean = 0.2343 std = 0.0000
-------------------------
[2024-05-20 22:03:02] iter = 0020, loss = 127.5617
[2024-05-20 22:03:03] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.863413, train acc = 0.4667 train oa = 0.4667, test acc = 0.0961 test oa = 0.0675
Evaluate 1, mean = 0.0961 std = 0.0000
-------------------------
[2024-05-20 22:03:06] iter = 0030, loss = 129.7004
[2024-05-20 22:03:08] iter = 0000, loss = 108.8079
[2024-05-20 22:03:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.095954, train acc = 1.0000 train oa = 1.0000, test acc = 0.2475 test oa = 0.2163
Evaluate 1, mean = 0.2475 std = 0.0000
-------------------------
[2024-05-20 22:03:12] iter = 0040, loss = 143.8905

================== Exp 0 ==================
 
[2024-05-20 22:08:14] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.014367, train acc = 1.0000 train oa = 1.0000, test acc = 0.1017 test oa = 0.0813
Evaluate 1, mean = 0.1017 std = 0.0000
-------------------------
[2024-05-20 22:08:14] iter = 0000, loss = 158.2997
[2024-05-20 22:08:19] iter = 0010, loss = 109.4550
[2024-05-20 22:08:25] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.075454, train acc = 1.0000 train oa = 1.0000, test acc = 0.2268 test oa = 0.2163
Evaluate 1, mean = 0.2268 std = 0.0000
-------------------------
[2024-05-20 22:08:26] iter = 0020, loss = 128.5619

================== Exp 0 ==================
 
[2024-05-20 22:08:30] iter = 0030, loss = 130.5282
[2024-05-20 22:08:35] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.603385, train acc = 0.5733 train oa = 0.5733, test acc = 0.0734 test oa = 0.0554
Evaluate 1, mean = 0.0734 std = 0.0000
-------------------------
[2024-05-20 22:08:35] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.098507, train acc = 1.0000 train oa = 1.0000, test acc = 0.2732 test oa = 0.2595
Evaluate 1, mean = 0.2732 std = 0.0000
-------------------------
[2024-05-20 22:08:36] iter = 0040, loss = 145.1497
[2024-05-20 22:08:40] iter = 0050, loss = 118.8222
[2024-05-20 22:08:40] iter = 0000, loss = 107.5211
[2024-05-20 22:08:45] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.094565, train acc = 1.0000 train oa = 1.0000, test acc = 0.2884 test oa = 0.2837
Evaluate 1, mean = 0.2884 std = 0.0000
-------------------------
[2024-05-20 22:08:46] iter = 0060, loss = 130.6382
[2024-05-20 22:08:50] iter = 0070, loss = 135.8270
[2024-05-20 22:08:55] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.055789, train acc = 1.0000 train oa = 1.0000, test acc = 0.2742 test oa = 0.2647
Evaluate 1, mean = 0.2742 std = 0.0000
-------------------------
[2024-05-20 22:08:56] iter = 0080, loss = 134.0748
[2024-05-20 22:09:00] iter = 0090, loss = 143.8559
[2024-05-20 22:09:06] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.078366, train acc = 1.0000 train oa = 1.0000, test acc = 0.2621 test oa = 0.2284
Evaluate 1, mean = 0.2621 std = 0.0000
-------------------------
[2024-05-20 22:09:06] iter = 0100, loss = 124.8091
[2024-05-20 22:09:10] iter = 0110, loss = 129.6850
[2024-05-20 22:09:16] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.053214, train acc = 1.0000 train oa = 1.0000, test acc = 0.2533 test oa = 0.2751
Evaluate 1, mean = 0.2533 std = 0.0000
-------------------------
[2024-05-20 22:09:16] iter = 0120, loss = 149.1705
[2024-05-20 22:09:20] iter = 0130, loss = 136.1299
[2024-05-20 22:09:26] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.066590, train acc = 1.0000 train oa = 1.0000, test acc = 0.2457 test oa = 0.2837
Evaluate 1, mean = 0.2457 std = 0.0000
-------------------------
[2024-05-20 22:09:26] iter = 0140, loss = 124.7142
[2024-05-20 22:09:30] iter = 0150, loss = 113.7783
[2024-05-20 22:09:32] iter = 0010, loss = 82.2149
[2024-05-20 22:09:36] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.098242, train acc = 1.0000 train oa = 1.0000, test acc = 0.2869 test oa = 0.2837
Evaluate 1, mean = 0.2869 std = 0.0000
-------------------------
[2024-05-20 22:09:36] iter = 0160, loss = 133.0196
[2024-05-20 22:09:40] iter = 0170, loss = 140.9989
[2024-05-20 22:09:46] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.080802, train acc = 1.0000 train oa = 1.0000, test acc = 0.2714 test oa = 0.2526
Evaluate 1, mean = 0.2714 std = 0.0000
-------------------------
[2024-05-20 22:09:46] iter = 0180, loss = 117.0766
[2024-05-20 22:09:50] iter = 0190, loss = 119.8567
[2024-05-20 22:09:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050913, train acc = 1.0000 train oa = 1.0000, test acc = 0.2874 test oa = 0.2837
Evaluate 1, mean = 0.2874 std = 0.0000
-------------------------
[2024-05-20 22:09:56] iter = 0200, loss = 145.0669
[2024-05-20 22:10:00] iter = 0210, loss = 155.5953
[2024-05-20 22:10:05] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.023803, train acc = 1.0000 train oa = 1.0000, test acc = 0.2733 test oa = 0.2578
Evaluate 1, mean = 0.2733 std = 0.0000
-------------------------
[2024-05-20 22:10:06] iter = 0220, loss = 140.1498
[2024-05-20 22:10:10] iter = 0230, loss = 123.6969
[2024-05-20 22:10:15] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.064346, train acc = 1.0000 train oa = 1.0000, test acc = 0.2503 test oa = 0.2820
Evaluate 1, mean = 0.2503 std = 0.0000
-------------------------
[2024-05-20 22:10:16] iter = 0240, loss = 150.7515
[2024-05-20 22:10:20] iter = 0250, loss = 118.9084
[2024-05-20 22:10:24] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.463418, train acc = 0.9600 train oa = 0.9600, test acc = 0.3255 test oa = 0.3045
Evaluate 1, mean = 0.3255 std = 0.0000
-------------------------
[2024-05-20 22:10:25] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.056993, train acc = 1.0000 train oa = 1.0000, test acc = 0.2583 test oa = 0.2284
Evaluate 1, mean = 0.2583 std = 0.0000
-------------------------
[2024-05-20 22:10:26] iter = 0260, loss = 127.3814
[2024-05-20 22:10:30] iter = 0270, loss = 146.6046
[2024-05-20 22:10:30] iter = 0020, loss = 74.5420
[2024-05-20 22:10:35] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.107391, train acc = 1.0000 train oa = 1.0000, test acc = 0.2704 test oa = 0.2526
Evaluate 1, mean = 0.2704 std = 0.0000
-------------------------
[2024-05-20 22:10:36] iter = 0280, loss = 119.3127
[2024-05-20 22:10:39] iter = 0290, loss = 113.6260
[2024-05-20 22:10:45] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.087915, train acc = 1.0000 train oa = 1.0000, test acc = 0.2927 test oa = 0.2716
Evaluate 1, mean = 0.2927 std = 0.0000
-------------------------
[2024-05-20 22:10:45] iter = 0300, loss = 133.2161
[2024-05-20 22:10:49] iter = 0310, loss = 131.3751
[2024-05-20 22:10:54] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.065767, train acc = 1.0000 train oa = 1.0000, test acc = 0.2538 test oa = 0.2284
Evaluate 1, mean = 0.2538 std = 0.0000
-------------------------
[2024-05-20 22:10:55] iter = 0320, loss = 150.5026
[2024-05-20 22:10:59] iter = 0330, loss = 118.4948
[2024-05-20 22:11:04] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.097006, train acc = 1.0000 train oa = 1.0000, test acc = 0.2244 test oa = 0.2647
Evaluate 1, mean = 0.2244 std = 0.0000
-------------------------
[2024-05-20 22:11:05] iter = 0340, loss = 120.4595
[2024-05-20 22:11:09] iter = 0350, loss = 124.3934
[2024-05-20 22:11:14] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.102156, train acc = 1.0000 train oa = 1.0000, test acc = 0.2391 test oa = 0.2145
Evaluate 1, mean = 0.2391 std = 0.0000
-------------------------
[2024-05-20 22:11:15] iter = 0360, loss = 129.6114
[2024-05-20 22:11:19] iter = 0370, loss = 139.0713
[2024-05-20 22:11:22] iter = 0030, loss = 67.2497
[2024-05-20 22:11:25] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.082682, train acc = 1.0000 train oa = 1.0000, test acc = 0.2108 test oa = 0.1817
Evaluate 1, mean = 0.2108 std = 0.0000
-------------------------
[2024-05-20 22:11:25] iter = 0380, loss = 118.1630
[2024-05-20 22:11:29] iter = 0390, loss = 139.9025
[2024-05-20 22:11:35] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.069627, train acc = 1.0000 train oa = 1.0000, test acc = 0.2364 test oa = 0.2024
Evaluate 1, mean = 0.2364 std = 0.0000
-------------------------
[2024-05-20 22:11:36] iter = 0400, loss = 126.8963
[2024-05-20 22:11:39] iter = 0410, loss = 134.5477
[2024-05-20 22:11:46] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.041318, train acc = 1.0000 train oa = 1.0000, test acc = 0.2941 test oa = 0.2785
Evaluate 1, mean = 0.2941 std = 0.0000
-------------------------
[2024-05-20 22:11:46] iter = 0420, loss = 115.3393
[2024-05-20 22:11:50] iter = 0430, loss = 120.6954
[2024-05-20 22:11:57] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.093844, train acc = 1.0000 train oa = 1.0000, test acc = 0.3236 test oa = 0.2803
Evaluate 1, mean = 0.3236 std = 0.0000
-------------------------
[2024-05-20 22:11:57] iter = 0440, loss = 134.0306
[2024-05-20 22:12:01] iter = 0450, loss = 116.8091
[2024-05-20 22:12:08] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.191769, train acc = 1.0000 train oa = 1.0000, test acc = 0.2496 test oa = 0.2682
Evaluate 1, mean = 0.2496 std = 0.0000
-------------------------
[2024-05-20 22:12:08] iter = 0460, loss = 140.6338
[2024-05-20 22:12:12] iter = 0470, loss = 131.3156
[2024-05-20 22:12:21] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 0.040716, train acc = 1.0000 train oa = 1.0000, test acc = 0.2705 test oa = 0.2612
Evaluate 1, mean = 0.2705 std = 0.0000
-------------------------
[2024-05-20 22:12:21] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.937935, train acc = 0.8800 train oa = 0.8800, test acc = 0.2909 test oa = 0.2422
[2024-05-20 22:12:21] iter = 0480, loss = 117.7934
Evaluate 1, mean = 0.2909 std = 0.0000
-------------------------
[2024-05-20 22:12:25] iter = 0490, loss = 130.4479
[2024-05-20 22:12:27] iter = 0040, loss = 64.5045
[2024-05-20 22:12:32] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.035280, train acc = 1.0000 train oa = 1.0000, test acc = 0.2967 test oa = 0.2509
Evaluate 1, mean = 0.2967 std = 0.0000
-------------------------
[2024-05-20 22:12:32] iter = 0500, loss = 128.6415
[2024-05-20 22:12:36] iter = 0510, loss = 130.5882
[2024-05-20 22:12:43] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.048418, train acc = 1.0000 train oa = 1.0000, test acc = 0.2578 test oa = 0.2630
Evaluate 1, mean = 0.2578 std = 0.0000
-------------------------
[2024-05-20 22:12:43] iter = 0520, loss = 130.7238
[2024-05-20 22:12:47] iter = 0530, loss = 146.7842
[2024-05-20 22:12:54] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.053474, train acc = 1.0000 train oa = 1.0000, test acc = 0.2760 test oa = 0.2474
Evaluate 1, mean = 0.2760 std = 0.0000
-------------------------
[2024-05-20 22:12:55] iter = 0540, loss = 118.1979
[2024-05-20 22:12:59] iter = 0550, loss = 117.5265
[2024-05-20 22:13:06] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.056110, train acc = 1.0000 train oa = 1.0000, test acc = 0.2802 test oa = 0.2958
Evaluate 1, mean = 0.2802 std = 0.0000
-------------------------
[2024-05-20 22:13:07] iter = 0560, loss = 115.9644
[2024-05-20 22:13:11] iter = 0570, loss = 136.6115
[2024-05-20 22:13:17] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.106042, train acc = 1.0000 train oa = 1.0000, test acc = 0.2733 test oa = 0.2716
Evaluate 1, mean = 0.2733 std = 0.0000
-------------------------
[2024-05-20 22:13:18] iter = 0580, loss = 138.8057
[2024-05-20 22:13:22] iter = 0590, loss = 126.8689
[2024-05-20 22:13:26] iter = 0050, loss = 64.0250
[2024-05-20 22:13:28] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.100860, train acc = 1.0000 train oa = 1.0000, test acc = 0.3035 test oa = 0.2907
Evaluate 1, mean = 0.3035 std = 0.0000
-------------------------
[2024-05-20 22:13:29] iter = 0600, loss = 151.4564
[2024-05-20 22:13:33] iter = 0610, loss = 125.8220
[2024-05-20 22:13:41] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.083209, train acc = 1.0000 train oa = 1.0000, test acc = 0.2894 test oa = 0.2509
Evaluate 1, mean = 0.2894 std = 0.0000
-------------------------
[2024-05-20 22:13:41] iter = 0620, loss = 124.7213
[2024-05-20 22:13:45] iter = 0630, loss = 127.8869
[2024-05-20 22:13:52] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.074652, train acc = 1.0000 train oa = 1.0000, test acc = 0.2343 test oa = 0.2266
Evaluate 1, mean = 0.2343 std = 0.0000
-------------------------
[2024-05-20 22:13:53] iter = 0640, loss = 123.7191
[2024-05-20 22:13:57] iter = 0650, loss = 124.8349
[2024-05-20 22:14:05] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.052390, train acc = 1.0000 train oa = 1.0000, test acc = 0.2448 test oa = 0.2682
Evaluate 1, mean = 0.2448 std = 0.0000
-------------------------
[2024-05-20 22:14:05] iter = 0660, loss = 102.7409
[2024-05-20 22:14:09] iter = 0670, loss = 127.9458
[2024-05-20 22:14:16] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.184501, train acc = 1.0000 train oa = 1.0000, test acc = 0.2458 test oa = 0.2301
Evaluate 1, mean = 0.2458 std = 0.0000
-------------------------
[2024-05-20 22:14:17] iter = 0680, loss = 129.1482
[2024-05-20 22:14:21] iter = 0690, loss = 152.9528
[2024-05-20 22:14:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.983368, train acc = 0.8133 train oa = 0.8133, test acc = 0.3077 test oa = 0.3183
Evaluate 1, mean = 0.3077 std = 0.0000
-------------------------
[2024-05-20 22:14:30] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 0.104987, train acc = 1.0000 train oa = 1.0000, test acc = 0.2458 test oa = 0.2526
Evaluate 1, mean = 0.2458 std = 0.0000
-------------------------
[2024-05-20 22:14:30] iter = 0700, loss = 114.7266
[2024-05-20 22:14:34] iter = 0710, loss = 127.6763
[2024-05-20 22:14:35] iter = 0060, loss = 64.4087
[2024-05-20 22:14:41] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.076569, train acc = 1.0000 train oa = 1.0000, test acc = 0.2910 test oa = 0.2578
Evaluate 1, mean = 0.2910 std = 0.0000
-------------------------
[2024-05-20 22:14:41] iter = 0720, loss = 147.9753
[2024-05-20 22:14:45] iter = 0730, loss = 114.1599
[2024-05-20 22:14:53] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 0.068794, train acc = 1.0000 train oa = 1.0000, test acc = 0.2824 test oa = 0.2993
Evaluate 1, mean = 0.2824 std = 0.0000
-------------------------
[2024-05-20 22:14:54] iter = 0740, loss = 128.1038
[2024-05-20 22:14:58] iter = 0750, loss = 123.1092
[2024-05-20 22:15:06] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.061750, train acc = 1.0000 train oa = 1.0000, test acc = 0.2505 test oa = 0.2266
Evaluate 1, mean = 0.2505 std = 0.0000
-------------------------
[2024-05-20 22:15:06] iter = 0760, loss = 125.0753
[2024-05-20 22:15:10] iter = 0770, loss = 119.0351
[2024-05-20 22:15:18] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.101541, train acc = 1.0000 train oa = 1.0000, test acc = 0.2594 test oa = 0.2474
Evaluate 1, mean = 0.2594 std = 0.0000
-------------------------
[2024-05-20 22:15:18] iter = 0780, loss = 128.9301
[2024-05-20 22:15:23] iter = 0790, loss = 112.2146
[2024-05-20 22:15:30] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.070754, train acc = 1.0000 train oa = 1.0000, test acc = 0.2502 test oa = 0.2353
Evaluate 1, mean = 0.2502 std = 0.0000
-------------------------
[2024-05-20 22:15:31] iter = 0800, loss = 117.4621
[2024-05-20 22:15:35] iter = 0810, loss = 143.0471
[2024-05-20 22:15:38] iter = 0070, loss = 59.9516
[2024-05-20 22:15:43] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.066907, train acc = 1.0000 train oa = 1.0000, test acc = 0.3062 test oa = 0.2509
Evaluate 1, mean = 0.3062 std = 0.0000
-------------------------
[2024-05-20 22:15:43] iter = 0820, loss = 112.7539
[2024-05-20 22:15:47] iter = 0830, loss = 120.1570
[2024-05-20 22:15:55] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.059510, train acc = 1.0000 train oa = 1.0000, test acc = 0.2755 test oa = 0.2907
Evaluate 1, mean = 0.2755 std = 0.0000
-------------------------
[2024-05-20 22:15:56] iter = 0840, loss = 125.2971
[2024-05-20 22:16:00] iter = 0850, loss = 130.3228
[2024-05-20 22:16:08] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 0.085770, train acc = 1.0000 train oa = 1.0000, test acc = 0.2881 test oa = 0.2837
Evaluate 1, mean = 0.2881 std = 0.0000
-------------------------
[2024-05-20 22:16:09] iter = 0860, loss = 115.8431
[2024-05-20 22:16:13] iter = 0870, loss = 124.3730
[2024-05-20 22:16:21] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.133473, train acc = 1.0000 train oa = 1.0000, test acc = 0.2394 test oa = 0.2180
Evaluate 1, mean = 0.2394 std = 0.0000
-------------------------
[2024-05-20 22:16:21] iter = 0880, loss = 107.7725
[2024-05-20 22:16:25] iter = 0890, loss = 127.3333
[2024-05-20 22:16:33] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.060601, train acc = 1.0000 train oa = 1.0000, test acc = 0.2731 test oa = 0.2734
Evaluate 1, mean = 0.2731 std = 0.0000
-------------------------
[2024-05-20 22:16:33] iter = 0900, loss = 132.5743
[2024-05-20 22:16:38] iter = 0910, loss = 125.4597
[2024-05-20 22:16:41] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.802886, train acc = 0.9200 train oa = 0.9200, test acc = 0.3452 test oa = 0.3253
Evaluate 1, mean = 0.3452 std = 0.0000
-------------------------
[2024-05-20 22:16:45] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.069835, train acc = 1.0000 train oa = 1.0000, test acc = 0.2842 test oa = 0.2647
Evaluate 1, mean = 0.2842 std = 0.0000
-------------------------
[2024-05-20 22:16:46] iter = 0920, loss = 121.1490
[2024-05-20 22:16:48] iter = 0080, loss = 63.4805
[2024-05-20 22:16:50] iter = 0930, loss = 144.5295
[2024-05-20 22:16:57] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.055332, train acc = 1.0000 train oa = 1.0000, test acc = 0.2762 test oa = 0.2716
Evaluate 1, mean = 0.2762 std = 0.0000
-------------------------
[2024-05-20 22:16:58] iter = 0940, loss = 121.6875
[2024-05-20 22:17:02] iter = 0950, loss = 117.3256
[2024-05-20 22:17:09] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.049058, train acc = 1.0000 train oa = 1.0000, test acc = 0.2769 test oa = 0.2907
Evaluate 1, mean = 0.2769 std = 0.0000
-------------------------
[2024-05-20 22:17:10] iter = 0960, loss = 112.8925
[2024-05-20 22:17:14] iter = 0970, loss = 138.2979
[2024-05-20 22:17:22] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.034657, train acc = 1.0000 train oa = 1.0000, test acc = 0.2944 test oa = 0.2682
Evaluate 1, mean = 0.2944 std = 0.0000
-------------------------
[2024-05-20 22:17:22] iter = 0980, loss = 123.7355
[2024-05-20 22:17:27] iter = 0990, loss = 131.1979
[2024-05-20 22:17:34] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.045255, train acc = 1.0000 train oa = 1.0000, test acc = 0.2409 test oa = 0.2076
Evaluate 1, mean = 0.2409 std = 0.0000
-------------------------
[2024-05-20 22:17:34] iter = 1000, loss = 123.1916
[2024-05-20 22:17:50] iter = 0090, loss = 57.0437
[2024-05-20 22:18:54] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.520082, train acc = 1.0000 train oa = 1.0000, test acc = 0.3365 test oa = 0.3131
Evaluate 1, mean = 0.3365 std = 0.0000
-------------------------
[2024-05-20 22:19:00] iter = 0100, loss = 56.2660
[2024-05-20 22:20:01] iter = 0110, loss = 55.2511
[2024-05-20 22:21:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.476988, train acc = 0.9867 train oa = 0.9867, test acc = 0.3514 test oa = 0.2958
Evaluate 1, mean = 0.3514 std = 0.0000
-------------------------
[2024-05-20 22:21:11] iter = 0120, loss = 55.6626
[2024-05-20 22:22:13] iter = 0130, loss = 58.8100
[2024-05-20 22:23:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.410310, train acc = 1.0000 train oa = 1.0000, test acc = 0.3683 test oa = 0.3253
Evaluate 1, mean = 0.3683 std = 0.0000
-------------------------
[2024-05-20 22:23:23] iter = 0140, loss = 55.0701
[2024-05-20 22:24:25] iter = 0150, loss = 55.8106
[2024-05-20 22:25:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.369676, train acc = 1.0000 train oa = 1.0000, test acc = 0.3539 test oa = 0.3235
Evaluate 1, mean = 0.3539 std = 0.0000
-------------------------
[2024-05-20 22:25:35] iter = 0160, loss = 51.7111
[2024-05-20 22:25:57] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.029448, train acc = 1.0000 train oa = 1.0000, test acc = 0.2493 test oa = 0.2093
[2024-05-20 22:25:59] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.013530, train acc = 1.0000 train oa = 1.0000, test acc = 0.2631 test oa = 0.2388
[2024-05-20 22:26:02] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.036005, train acc = 1.0000 train oa = 1.0000, test acc = 0.2381 test oa = 0.2042
[2024-05-20 22:26:37] iter = 0170, loss = 54.2768
[2024-05-20 22:27:42] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.095791, train acc = 0.8267 train oa = 0.8267, test acc = 0.3572 test oa = 0.3547
Evaluate 1, mean = 0.3572 std = 0.0000
-------------------------
[2024-05-20 22:27:49] iter = 0180, loss = 53.6943
[2024-05-20 22:28:53] iter = 0190, loss = 54.0334
[2024-05-20 22:29:59] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.814646, train acc = 0.9200 train oa = 0.9200, test acc = 0.3652 test oa = 0.3391
Evaluate 1, mean = 0.3652 std = 0.0000
-------------------------
[2024-05-20 22:30:06] iter = 0200, loss = 52.3295
[2024-05-20 22:31:09] iter = 0210, loss = 53.2300
[2024-05-20 22:32:14] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.652210, train acc = 1.0000 train oa = 1.0000, test acc = 0.3231 test oa = 0.3045
Evaluate 1, mean = 0.3231 std = 0.0000
-------------------------
[2024-05-20 22:32:20] iter = 0220, loss = 53.1156
[2024-05-20 22:33:24] iter = 0230, loss = 53.3234
[2024-05-20 22:34:28] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.763250, train acc = 0.9733 train oa = 0.9733, test acc = 0.3632 test oa = 0.3374
Evaluate 1, mean = 0.3632 std = 0.0000
-------------------------
[2024-05-20 22:34:35] iter = 0240, loss = 54.4329
[2024-05-20 22:35:37] iter = 0250, loss = 52.6009
[2024-05-20 22:36:41] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.720119, train acc = 0.9600 train oa = 0.9600, test acc = 0.3435 test oa = 0.2958
Evaluate 1, mean = 0.3435 std = 0.0000
-------------------------
[2024-05-20 22:36:47] iter = 0260, loss = 51.4702
[2024-05-20 22:37:49] iter = 0270, loss = 53.2876
[2024-05-20 22:38:53] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.842659, train acc = 0.9067 train oa = 0.9067, test acc = 0.3443 test oa = 0.3443
Evaluate 1, mean = 0.3443 std = 0.0000
-------------------------
[2024-05-20 22:38:59] iter = 0280, loss = 51.1499
[2024-05-20 22:40:01] iter = 0290, loss = 52.7835
[2024-05-20 22:41:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.740064, train acc = 0.9200 train oa = 0.9200, test acc = 0.3178 test oa = 0.2993
Evaluate 1, mean = 0.3178 std = 0.0000
-------------------------
[2024-05-20 22:41:10] iter = 0300, loss = 53.1490
[2024-05-20 22:42:12] iter = 0310, loss = 53.8612
[2024-05-20 22:43:15] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.826994, train acc = 0.9467 train oa = 0.9467, test acc = 0.3353 test oa = 0.3131
Evaluate 1, mean = 0.3353 std = 0.0000
-------------------------
[2024-05-20 22:43:22] iter = 0320, loss = 53.7972
[2024-05-20 22:44:25] iter = 0330, loss = 53.8946
[2024-05-20 22:45:30] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.827164, train acc = 0.9200 train oa = 0.9200, test acc = 0.3524 test oa = 0.3097
Evaluate 1, mean = 0.3524 std = 0.0000
-------------------------
[2024-05-20 22:45:36] iter = 0340, loss = 51.1738
[2024-05-20 22:46:40] iter = 0350, loss = 55.8847
[2024-05-20 22:47:45] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.639306, train acc = 0.9733 train oa = 0.9733, test acc = 0.3843 test oa = 0.3547
Evaluate 1, mean = 0.3843 std = 0.0000
-------------------------
[2024-05-20 22:47:51] iter = 0360, loss = 52.9867
[2024-05-20 22:48:54] iter = 0370, loss = 52.9340
[2024-05-20 22:49:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.660655, train acc = 0.9467 train oa = 0.9467, test acc = 0.3431 test oa = 0.3183
Evaluate 1, mean = 0.3431 std = 0.0000
-------------------------
[2024-05-20 22:50:05] iter = 0380, loss = 53.1699
[2024-05-20 22:51:08] iter = 0390, loss = 53.3074
[2024-05-20 22:52:12] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.567341, train acc = 0.9733 train oa = 0.9733, test acc = 0.3451 test oa = 0.3374
Evaluate 1, mean = 0.3451 std = 0.0000
-------------------------
[2024-05-20 22:52:18] iter = 0400, loss = 53.9184
[2024-05-20 22:53:21] iter = 0410, loss = 54.1086
[2024-05-20 22:54:25] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.519163, train acc = 1.0000 train oa = 1.0000, test acc = 0.3503 test oa = 0.3183
Evaluate 1, mean = 0.3503 std = 0.0000
-------------------------
[2024-05-20 22:54:31] iter = 0420, loss = 50.4429
[2024-05-20 22:54:53] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.041087, train acc = 1.0000 train oa = 1.0000, test acc = 0.2854 test oa = 0.2526
[2024-05-20 22:54:57] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.067799, train acc = 1.0000 train oa = 1.0000, test acc = 0.2825 test oa = 0.2526
[2024-05-20 22:54:59] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.043337, train acc = 1.0000 train oa = 1.0000, test acc = 0.3042 test oa = 0.2647
[2024-05-20 22:55:33] iter = 0430, loss = 51.3417
[2024-05-20 22:56:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.667385, train acc = 0.9467 train oa = 0.9467, test acc = 0.3115 test oa = 0.2803
Evaluate 1, mean = 0.3115 std = 0.0000
-------------------------
[2024-05-20 22:56:41] iter = 0440, loss = 53.2762
[2024-05-20 22:57:42] iter = 0450, loss = 51.3040
[2024-05-20 22:58:44] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.522215, train acc = 0.9867 train oa = 0.9867, test acc = 0.3685 test oa = 0.3685
Evaluate 1, mean = 0.3685 std = 0.0000
-------------------------
[2024-05-20 22:58:50] iter = 0460, loss = 51.4390
[2024-05-20 22:59:51] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.082426, train acc = 1.0000 train oa = 1.0000, test acc = 0.2645 test oa = 0.2336
[2024-05-20 22:59:53] iter = 0470, loss = 53.1177
[2024-05-20 22:59:54] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.050332, train acc = 1.0000 train oa = 1.0000, test acc = 0.2566 test oa = 0.2215
[2024-05-20 22:59:58] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.047956, train acc = 1.0000 train oa = 1.0000, test acc = 0.2397 test oa = 0.1920
[2024-05-20 23:00:58] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.447498, train acc = 1.0000 train oa = 1.0000, test acc = 0.3601 test oa = 0.3495
Evaluate 1, mean = 0.3601 std = 0.0000
-------------------------
[2024-05-20 23:01:04] iter = 0480, loss = 53.5090
[2024-05-20 23:02:07] iter = 0490, loss = 51.2643
[2024-05-20 23:03:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.893215, train acc = 0.9067 train oa = 0.9067, test acc = 0.3553 test oa = 0.3512
Evaluate 1, mean = 0.3553 std = 0.0000
-------------------------
[2024-05-20 23:03:17] iter = 0500, loss = 52.2821
[2024-05-20 23:04:20] iter = 0510, loss = 50.7499
[2024-05-20 23:05:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.642865, train acc = 0.9600 train oa = 0.9600, test acc = 0.3229 test oa = 0.2958
Evaluate 1, mean = 0.3229 std = 0.0000
-------------------------
[2024-05-20 23:05:30] iter = 0520, loss = 55.1070
[2024-05-20 23:06:32] iter = 0530, loss = 51.1957
[2024-05-20 23:07:30] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.066568, train acc = 1.0000 train oa = 1.0000, test acc = 0.2783 test oa = 0.2872
[2024-05-20 23:07:34] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.061137, train acc = 1.0000 train oa = 1.0000, test acc = 0.2738 test oa = 0.2976
[2024-05-20 23:07:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.668778, train acc = 0.9733 train oa = 0.9733, test acc = 0.3380 test oa = 0.3166
Evaluate 1, mean = 0.3380 std = 0.0000
-------------------------
[2024-05-20 23:07:38] Evaluate_02: epoch = 0300, train time = 4 s, train loss = 0.050924, train acc = 1.0000 train oa = 1.0000, test acc = 0.2608 test oa = 0.2993
[2024-05-20 23:07:41] iter = 0540, loss = 52.0761
[2024-05-20 23:08:43] iter = 0550, loss = 53.4909
[2024-05-20 23:09:47] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.821651, train acc = 0.9333 train oa = 0.9333, test acc = 0.3188 test oa = 0.2958
Evaluate 1, mean = 0.3188 std = 0.0000
-------------------------
[2024-05-20 23:09:53] iter = 0560, loss = 50.6175
[2024-05-20 23:10:54] iter = 0570, loss = 49.8856
[2024-05-20 23:11:56] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.409666, train acc = 1.0000 train oa = 1.0000, test acc = 0.3564 test oa = 0.3097
Evaluate 1, mean = 0.3564 std = 0.0000
-------------------------
[2024-05-20 23:12:02] iter = 0580, loss = 52.4613
[2024-05-20 23:12:22] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.073594, train acc = 1.0000 train oa = 1.0000, test acc = 0.2514 test oa = 0.2491
[2024-05-20 23:12:26] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.060635, train acc = 1.0000 train oa = 1.0000, test acc = 0.2367 test oa = 0.2232
[2024-05-20 23:12:30] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.049014, train acc = 1.0000 train oa = 1.0000, test acc = 0.2497 test oa = 0.2301
[2024-05-20 23:13:03] iter = 0590, loss = 50.4846
[2024-05-20 23:14:07] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.907842, train acc = 0.8667 train oa = 0.8667, test acc = 0.3432 test oa = 0.3512
Evaluate 1, mean = 0.3432 std = 0.0000
-------------------------
[2024-05-20 23:14:13] iter = 0600, loss = 50.3507
[2024-05-20 23:15:16] iter = 0610, loss = 50.2905
[2024-05-20 23:16:21] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.585446, train acc = 0.9600 train oa = 0.9600, test acc = 0.3325 test oa = 0.3080
Evaluate 1, mean = 0.3325 std = 0.0000
-------------------------
[2024-05-20 23:16:27] iter = 0620, loss = 51.5757
[2024-05-20 23:17:30] iter = 0630, loss = 51.5803
[2024-05-20 23:18:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.701395, train acc = 0.9200 train oa = 0.9200, test acc = 0.3357 test oa = 0.3183
Evaluate 1, mean = 0.3357 std = 0.0000
-------------------------
[2024-05-20 23:18:41] iter = 0640, loss = 51.3312
[2024-05-20 23:19:44] iter = 0650, loss = 50.5959
[2024-05-20 23:20:48] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.990898, train acc = 0.8800 train oa = 0.8800, test acc = 0.3128 test oa = 0.3408
Evaluate 1, mean = 0.3128 std = 0.0000
-------------------------
[2024-05-20 23:20:55] iter = 0660, loss = 50.5906
[2024-05-20 23:21:57] iter = 0670, loss = 52.0830
[2024-05-20 23:23:01] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.741063, train acc = 0.9867 train oa = 0.9867, test acc = 0.3793 test oa = 0.3460
Evaluate 1, mean = 0.3793 std = 0.0000
-------------------------
[2024-05-20 23:23:07] iter = 0680, loss = 54.1454
[2024-05-20 23:24:09] iter = 0690, loss = 53.0198
[2024-05-20 23:25:13] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.471195, train acc = 0.9867 train oa = 0.9867, test acc = 0.3779 test oa = 0.3495
Evaluate 1, mean = 0.3779 std = 0.0000
-------------------------
[2024-05-20 23:25:19] iter = 0700, loss = 51.8344
[2024-05-20 23:26:21] iter = 0710, loss = 50.7276
[2024-05-20 23:27:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.855254, train acc = 0.9333 train oa = 0.9333, test acc = 0.3138 test oa = 0.3080
Evaluate 1, mean = 0.3138 std = 0.0000
-------------------------
[2024-05-20 23:27:30] iter = 0720, loss = 51.7797
[2024-05-20 23:28:32] iter = 0730, loss = 52.2862
[2024-05-20 23:29:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.206699, train acc = 1.0000 train oa = 1.0000, test acc = 0.3603 test oa = 0.3391
Evaluate 1, mean = 0.3603 std = 0.0000
-------------------------
[2024-05-20 23:29:41] iter = 0740, loss = 52.7907
[2024-05-20 23:30:42] iter = 0750, loss = 54.3951
[2024-05-20 23:31:47] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.837786, train acc = 0.9333 train oa = 0.9333, test acc = 0.3274 test oa = 0.2941
Evaluate 1, mean = 0.3274 std = 0.0000
-------------------------
[2024-05-20 23:31:53] iter = 0760, loss = 53.6491
[2024-05-20 23:32:55] iter = 0770, loss = 52.2585
[2024-05-20 23:34:00] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.309733, train acc = 1.0000 train oa = 1.0000, test acc = 0.3532 test oa = 0.3391
Evaluate 1, mean = 0.3532 std = 0.0000
-------------------------
[2024-05-20 23:34:06] iter = 0780, loss = 51.0479
[2024-05-20 23:35:09] iter = 0790, loss = 52.2033
[2024-05-20 23:35:16] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.000445, train acc = 1.0000 train oa = 1.0000, test acc = 0.1419 test oa = 0.1349
[2024-05-20 23:35:19] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.010505, train acc = 1.0000 train oa = 1.0000, test acc = 0.1473 test oa = 0.1367
[2024-05-20 23:35:22] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.004009, train acc = 1.0000 train oa = 1.0000, test acc = 0.1537 test oa = 0.1886
[2024-05-20 23:36:14] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.888089, train acc = 0.9067 train oa = 0.9067, test acc = 0.3163 test oa = 0.2889
Evaluate 1, mean = 0.3163 std = 0.0000
-------------------------
[2024-05-20 23:36:21] iter = 0800, loss = 52.7936
[2024-05-20 23:37:23] iter = 0810, loss = 52.9379
[2024-05-20 23:38:27] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.717021, train acc = 0.9600 train oa = 0.9600, test acc = 0.3328 test oa = 0.2993
Evaluate 1, mean = 0.3328 std = 0.0000
-------------------------
[2024-05-20 23:38:33] iter = 0820, loss = 53.3046
[2024-05-20 23:39:35] iter = 0830, loss = 50.0323
[2024-05-20 23:40:38] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.471252, train acc = 1.0000 train oa = 1.0000, test acc = 0.3361 test oa = 0.2976
Evaluate 1, mean = 0.3361 std = 0.0000
-------------------------
[2024-05-20 23:40:45] iter = 0840, loss = 50.9918
[2024-05-20 23:41:47] iter = 0850, loss = 54.7672
[2024-05-20 23:42:51] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.756018, train acc = 0.9333 train oa = 0.9333, test acc = 0.3175 test oa = 0.3062
Evaluate 1, mean = 0.3175 std = 0.0000
-------------------------
[2024-05-20 23:42:57] iter = 0860, loss = 48.8853
[2024-05-20 23:43:59] iter = 0870, loss = 52.6760
[2024-05-20 23:45:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.898551, train acc = 0.9200 train oa = 0.9200, test acc = 0.3428 test oa = 0.2924
Evaluate 1, mean = 0.3428 std = 0.0000
-------------------------
[2024-05-20 23:45:09] iter = 0880, loss = 52.3555
[2024-05-20 23:46:11] iter = 0890, loss = 48.6875
[2024-05-20 23:47:15] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.781833, train acc = 0.9600 train oa = 0.9600, test acc = 0.3464 test oa = 0.2993
Evaluate 1, mean = 0.3464 std = 0.0000
-------------------------
[2024-05-20 23:47:21] iter = 0900, loss = 52.0921
[2024-05-20 23:47:33] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.265532, train acc = 0.6067 train oa = 0.6067, test acc = 0.3574 test oa = 0.3166
[2024-05-20 23:47:46] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.285760, train acc = 0.6267 train oa = 0.6267, test acc = 0.3738 test oa = 0.3460
[2024-05-20 23:47:58] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.340723, train acc = 0.6067 train oa = 0.6067, test acc = 0.3540 test oa = 0.3131
[2024-05-20 23:48:24] iter = 0910, loss = 49.4200
[2024-05-20 23:49:29] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.801027, train acc = 0.9333 train oa = 0.9333, test acc = 0.3440 test oa = 0.3114
Evaluate 1, mean = 0.3440 std = 0.0000
-------------------------
[2024-05-20 23:49:35] iter = 0920, loss = 52.2960
[2024-05-20 23:50:39] iter = 0930, loss = 52.5188
[2024-05-20 23:51:45] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.582877, train acc = 0.9867 train oa = 0.9867, test acc = 0.3271 test oa = 0.3045
Evaluate 1, mean = 0.3271 std = 0.0000
-------------------------
[2024-05-20 23:51:51] iter = 0940, loss = 50.2192
[2024-05-20 23:52:54] iter = 0950, loss = 51.8334
[2024-05-20 23:53:42] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.050944, train acc = 1.0000 train oa = 1.0000, test acc = 0.2647 test oa = 0.2370
[2024-05-20 23:53:46] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.058128, train acc = 1.0000 train oa = 1.0000, test acc = 0.2645 test oa = 0.2370
[2024-05-20 23:53:49] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.044713, train acc = 1.0000 train oa = 1.0000, test acc = 0.2934 test oa = 0.2699
[2024-05-20 23:53:58] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.897642, train acc = 0.9067 train oa = 0.9067, test acc = 0.3335 test oa = 0.2941
Evaluate 1, mean = 0.3335 std = 0.0000
-------------------------
[2024-05-20 23:54:04] iter = 0960, loss = 52.2163
[2024-05-20 23:55:07] iter = 0970, loss = 50.8510
[2024-05-20 23:56:12] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.929737, train acc = 0.8800 train oa = 0.8800, test acc = 0.3297 test oa = 0.3270
Evaluate 1, mean = 0.3297 std = 0.0000
-------------------------
[2024-05-20 23:56:18] iter = 0980, loss = 50.4016
[2024-05-20 23:56:36] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.995492, train acc = 0.7667 train oa = 0.7667, test acc = 0.3333 test oa = 0.2976
[2024-05-20 23:56:49] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.279430, train acc = 0.6467 train oa = 0.6467, test acc = 0.3044 test oa = 0.2734
[2024-05-20 23:57:01] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 0.858150, train acc = 0.8267 train oa = 0.8267, test acc = 0.3712 test oa = 0.3547
[2024-05-20 23:57:21] iter = 0990, loss = 49.8827
[2024-05-20 23:58:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.863390, train acc = 0.8933 train oa = 0.8933, test acc = 0.3583 test oa = 0.3478
Evaluate 1, mean = 0.3583 std = 0.0000
-------------------------
[2024-05-20 23:58:31] iter = 1000, loss = 60.9449
[2024-05-21 00:04:30] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.848229, train acc = 0.9067 train oa = 0.9067, test acc = 0.3666 test oa = 0.3287
[2024-05-21 00:04:37] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.018889, train acc = 0.8400 train oa = 0.8400, test acc = 0.3567 test oa = 0.3218
[2024-05-21 00:04:44] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.741227, train acc = 0.9333 train oa = 0.9333, test acc = 0.3842 test oa = 0.3426
[2024-05-21 00:05:31] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.731942, train acc = 1.0000 train oa = 1.0000, test acc = 0.1898 test oa = 0.1799
[2024-05-21 00:05:34] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.376266, train acc = 1.0000 train oa = 1.0000, test acc = 0.1758 test oa = 0.1696
[2024-05-21 00:05:37] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.387622, train acc = 1.0000 train oa = 1.0000, test acc = 0.1838 test oa = 0.1799
[2024-05-21 00:31:32] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.097876, train acc = 1.0000 train oa = 1.0000, test acc = 0.3034 test oa = 0.2612
[2024-05-21 00:31:36] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.100707, train acc = 1.0000 train oa = 1.0000, test acc = 0.2981 test oa = 0.2578
[2024-05-21 00:31:38] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.098803, train acc = 1.0000 train oa = 1.0000, test acc = 0.2795 test oa = 0.2526
[2024-05-21 00:57:26] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.415024, train acc = 0.1867 train oa = 0.1867, test acc = 0.1776 test oa = 0.1730
[2024-05-21 00:57:39] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.419602, train acc = 0.2333 train oa = 0.2333, test acc = 0.1851 test oa = 0.1713
[2024-05-21 00:57:52] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.536224, train acc = 0.2333 train oa = 0.2333, test acc = 0.1427 test oa = 0.1176
[2024-05-21 01:11:54] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.031960, train acc = 1.0000 train oa = 1.0000, test acc = 0.3059 test oa = 0.2803
[2024-05-21 01:11:57] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.063799, train acc = 1.0000 train oa = 1.0000, test acc = 0.2823 test oa = 0.2526
[2024-05-21 01:12:00] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.032082, train acc = 1.0000 train oa = 1.0000, test acc = 0.3231 test oa = 0.2889
[2024-05-21 01:29:07] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.675108, train acc = 0.9333 train oa = 0.9333, test acc = 0.1047 test oa = 0.0813
[2024-05-21 01:29:11] Evaluate_01: epoch = 0300, train time = 4 s, train loss = 0.648228, train acc = 1.0000 train oa = 1.0000, test acc = 0.1353 test oa = 0.1488
[2024-05-21 01:29:15] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.327246, train acc = 1.0000 train oa = 1.0000, test acc = 0.1445 test oa = 0.1332
[2024-05-21 01:59:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.621064, train acc = 0.9867 train oa = 0.9867, test acc = 0.3355 test oa = 0.3304
[2024-05-21 01:59:31] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.688618, train acc = 0.9733 train oa = 0.9733, test acc = 0.3334 test oa = 0.3028
[2024-05-21 01:59:39] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.080394, train acc = 0.8133 train oa = 0.8133, test acc = 0.3183 test oa = 0.2889
[2024-05-21 01:59:58] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.454921, train acc = 0.3067 train oa = 0.3067, test acc = 0.1246 test oa = 0.1263
[2024-05-21 02:00:06] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.977927, train acc = 0.4400 train oa = 0.4400, test acc = 0.1719 test oa = 0.1799
[2024-05-21 02:00:15] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.267756, train acc = 0.3733 train oa = 0.3733, test acc = 0.1602 test oa = 0.1920
[2024-05-21 02:11:19] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.009141, train acc = 1.0000 train oa = 1.0000, test acc = 0.2757 test oa = 0.2578
[2024-05-21 02:11:21] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.008315, train acc = 1.0000 train oa = 1.0000, test acc = 0.3143 test oa = 0.2889
[2024-05-21 02:11:24] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.001493, train acc = 1.0000 train oa = 1.0000, test acc = 0.2544 test oa = 0.2509
[2024-05-21 02:37:56] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.059953, train acc = 1.0000 train oa = 1.0000, test acc = 0.2582 test oa = 0.2353
[2024-05-21 02:38:00] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.060665, train acc = 1.0000 train oa = 1.0000, test acc = 0.2432 test oa = 0.2215
[2024-05-21 02:38:02] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.036545, train acc = 1.0000 train oa = 1.0000, test acc = 0.2471 test oa = 0.2284
[2024-05-21 02:51:19] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.070813, train acc = 1.0000 train oa = 1.0000, test acc = 0.1467 test oa = 0.1851
[2024-05-21 02:51:23] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.071478, train acc = 1.0000 train oa = 1.0000, test acc = 0.1273 test oa = 0.1349
[2024-05-21 02:51:26] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.171863, train acc = 1.0000 train oa = 1.0000, test acc = 0.1534 test oa = 0.1851
[2024-05-21 03:17:50] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.697031, train acc = 0.9600 train oa = 0.9600, test acc = 0.3509 test oa = 0.3253
[2024-05-21 03:17:58] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.582908, train acc = 0.9867 train oa = 0.9867, test acc = 0.3405 test oa = 0.3304
[2024-05-21 03:18:05] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.525308, train acc = 1.0000 train oa = 1.0000, test acc = 0.3759 test oa = 0.3426
[2024-05-21 03:39:25] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.376763, train acc = 0.2933 train oa = 0.2933, test acc = 0.1165 test oa = 0.1107
[2024-05-21 03:39:38] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.468009, train acc = 0.2800 train oa = 0.2800, test acc = 0.1842 test oa = 0.1799
[2024-05-21 03:39:51] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.447960, train acc = 0.2733 train oa = 0.2733, test acc = 0.1561 test oa = 0.1592
[2024-05-21 04:01:55] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.201990, train acc = 1.0000 train oa = 1.0000, test acc = 0.1896 test oa = 0.1799
[2024-05-21 04:01:59] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.150440, train acc = 1.0000 train oa = 1.0000, test acc = 0.1700 test oa = 0.1471
[2024-05-21 04:02:02] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.075904, train acc = 1.0000 train oa = 1.0000, test acc = 0.2109 test oa = 0.2007
[2024-05-21 04:09:28] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.066568, train acc = 1.0000 train oa = 1.0000, test acc = 0.2783 test oa = 0.2872
[2024-05-21 04:09:30] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.061137, train acc = 1.0000 train oa = 1.0000, test acc = 0.2738 test oa = 0.2976
[2024-05-21 04:09:33] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.050924, train acc = 1.0000 train oa = 1.0000, test acc = 0.2608 test oa = 0.2993
[2024-05-21 04:14:43] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.067358, train acc = 1.0000 train oa = 1.0000, test acc = 0.1368 test oa = 0.1522
[2024-05-21 04:14:46] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.028650, train acc = 1.0000 train oa = 1.0000, test acc = 0.1422 test oa = 0.1522
[2024-05-21 04:14:50] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.079695, train acc = 1.0000 train oa = 1.0000, test acc = 0.1172 test oa = 0.1176
[2024-05-21 04:34:39] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.468856, train acc = 0.6400 train oa = 0.6400, test acc = 0.3788 test oa = 0.3685
[2024-05-21 04:34:51] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.711175, train acc = 0.4867 train oa = 0.4867, test acc = 0.3259 test oa = 0.3114
[2024-05-21 04:35:04] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.310927, train acc = 0.6800 train oa = 0.6800, test acc = 0.3857 test oa = 0.3651
[2024-05-21 04:51:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.637961, train acc = 0.9600 train oa = 0.9600, test acc = 0.3474 test oa = 0.3183
[2024-05-21 04:51:31] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.516736, train acc = 0.9867 train oa = 0.9867, test acc = 0.3648 test oa = 0.3443
[2024-05-21 04:51:38] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.507105, train acc = 1.0000 train oa = 1.0000, test acc = 0.3709 test oa = 0.3356
[2024-05-21 05:07:07] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.002314, train acc = 1.0000 train oa = 1.0000, test acc = 0.1909 test oa = 0.2128
[2024-05-21 05:07:10] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.010636, train acc = 1.0000 train oa = 1.0000, test acc = 0.1779 test oa = 0.1834
[2024-05-21 05:07:13] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.002714, train acc = 1.0000 train oa = 1.0000, test acc = 0.1540 test oa = 0.1609
[2024-05-21 05:07:27] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.076020, train acc = 0.3600 train oa = 0.3600, test acc = 0.1722 test oa = 0.1886
[2024-05-21 05:07:35] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.550889, train acc = 0.2667 train oa = 0.2667, test acc = 0.1053 test oa = 0.0917
[2024-05-21 05:07:44] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.543083, train acc = 0.2000 train oa = 0.2000, test acc = 0.0767 test oa = 0.0779
[2024-05-21 05:12:27] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 1.767873, train acc = 0.9333 train oa = 0.9333, test acc = 0.1316 test oa = 0.1298
[2024-05-21 05:12:30] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.603605, train acc = 1.0000 train oa = 1.0000, test acc = 0.1849 test oa = 0.1920
[2024-05-21 05:12:33] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.136611, train acc = 1.0000 train oa = 1.0000, test acc = 0.2133 test oa = 0.2716
[2024-05-21 05:14:38] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.031990, train acc = 1.0000 train oa = 1.0000, test acc = 0.2611 test oa = 0.2474
[2024-05-21 05:14:41] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.032111, train acc = 1.0000 train oa = 1.0000, test acc = 0.2763 test oa = 0.2630
[2024-05-21 05:14:45] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.040537, train acc = 1.0000 train oa = 1.0000, test acc = 0.2700 test oa = 0.2872
[2024-05-21 05:19:29] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.073594, train acc = 1.0000 train oa = 1.0000, test acc = 0.2514 test oa = 0.2491
[2024-05-21 05:19:32] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.060635, train acc = 1.0000 train oa = 1.0000, test acc = 0.2367 test oa = 0.2232
[2024-05-21 05:19:35] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.049014, train acc = 1.0000 train oa = 1.0000, test acc = 0.2497 test oa = 0.2301
[2024-05-21 05:27:00] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.134771, train acc = 1.0000 train oa = 1.0000, test acc = 0.3162 test oa = 0.2699
[2024-05-21 05:27:03] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.097218, train acc = 1.0000 train oa = 1.0000, test acc = 0.2933 test oa = 0.2509
[2024-05-21 05:27:06] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.091824, train acc = 1.0000 train oa = 1.0000, test acc = 0.2838 test oa = 0.2457
[2024-05-21 05:29:41] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.090286, train acc = 0.3533 train oa = 0.3533, test acc = 0.2342 test oa = 0.2543
[2024-05-21 05:29:54] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.173651, train acc = 0.3333 train oa = 0.3333, test acc = 0.1834 test oa = 0.1817
[2024-05-21 05:30:07] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.035772, train acc = 0.3933 train oa = 0.3933, test acc = 0.1882 test oa = 0.1851
[2024-05-21 05:42:47] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.197489, train acc = 1.0000 train oa = 1.0000, test acc = 0.1493 test oa = 0.1349
[2024-05-21 05:42:50] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.538971, train acc = 1.0000 train oa = 1.0000, test acc = 0.1658 test oa = 0.1678
[2024-05-21 05:42:53] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.099484, train acc = 1.0000 train oa = 1.0000, test acc = 0.1994 test oa = 0.2318
[2024-05-21 05:55:12] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.059810, train acc = 1.0000 train oa = 1.0000, test acc = 0.2632 test oa = 0.2336
[2024-05-21 05:55:14] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.060927, train acc = 1.0000 train oa = 1.0000, test acc = 0.2416 test oa = 0.2145
[2024-05-21 05:55:17] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.041929, train acc = 1.0000 train oa = 1.0000, test acc = 0.2759 test oa = 0.2509
[2024-05-21 06:02:36] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.019506, train acc = 1.0000 train oa = 1.0000, test acc = 0.2932 test oa = 0.2958
[2024-05-21 06:02:39] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.031929, train acc = 1.0000 train oa = 1.0000, test acc = 0.3086 test oa = 0.3062
[2024-05-21 06:02:42] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.021362, train acc = 1.0000 train oa = 1.0000, test acc = 0.2994 test oa = 0.2803
[2024-05-21 06:07:14] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.807871, train acc = 0.9333 train oa = 0.9333, test acc = 0.3131 test oa = 0.2682
[2024-05-21 06:07:21] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.838660, train acc = 0.9200 train oa = 0.9200, test acc = 0.3501 test oa = 0.3045
[2024-05-21 06:07:28] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.942330, train acc = 0.8667 train oa = 0.8667, test acc = 0.3498 test oa = 0.3270
[2024-05-21 06:11:51] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 1.830197, train acc = 1.0000 train oa = 1.0000, test acc = 0.1022 test oa = 0.1090
[2024-05-21 06:11:55] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 1.740501, train acc = 0.5333 train oa = 0.5333, test acc = 0.1413 test oa = 0.1090
[2024-05-21 06:11:58] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 1.872908, train acc = 1.0000 train oa = 1.0000, test acc = 0.1201 test oa = 0.1125
[2024-05-21 06:40:46] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.123597, train acc = 1.0000 train oa = 1.0000, test acc = 0.2900 test oa = 0.2543
[2024-05-21 06:40:50] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.058300, train acc = 1.0000 train oa = 1.0000, test acc = 0.2562 test oa = 0.2284
[2024-05-21 06:40:53] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.050607, train acc = 1.0000 train oa = 1.0000, test acc = 0.2799 test oa = 0.2491
[2024-05-21 06:45:50] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.074768, train acc = 1.0000 train oa = 1.0000, test acc = 0.2565 test oa = 0.2232
[2024-05-21 06:45:54] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.068786, train acc = 1.0000 train oa = 1.0000, test acc = 0.2687 test oa = 0.2232
[2024-05-21 06:45:57] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.128089, train acc = 1.0000 train oa = 1.0000, test acc = 0.2602 test oa = 0.2543
[2024-05-21 06:52:06] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.526133, train acc = 0.6667 train oa = 0.6667, test acc = 0.1539 test oa = 0.2093
[2024-05-21 06:52:09] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.256371, train acc = 1.0000 train oa = 1.0000, test acc = 0.1592 test oa = 0.1851
[2024-05-21 06:52:12] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.770386, train acc = 0.6000 train oa = 0.6000, test acc = 0.1701 test oa = 0.2093
[2024-05-21 06:57:20] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.051580, train acc = 1.0000 train oa = 1.0000, test acc = 0.1530 test oa = 0.2111
[2024-05-21 06:57:23] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.062598, train acc = 1.0000 train oa = 1.0000, test acc = 0.2063 test oa = 0.2768
[2024-05-21 06:57:27] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.331428, train acc = 1.0000 train oa = 1.0000, test acc = 0.1926 test oa = 0.1869
[2024-05-21 07:02:39] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.415034, train acc = 1.0000 train oa = 1.0000, test acc = 0.1615 test oa = 0.1678
[2024-05-21 07:02:43] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.503907, train acc = 1.0000 train oa = 1.0000, test acc = 0.2060 test oa = 0.2042
[2024-05-21 07:02:46] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.551746, train acc = 1.0000 train oa = 1.0000, test acc = 0.1779 test oa = 0.1851
[2024-05-21 07:08:02] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.023313, train acc = 1.0000 train oa = 1.0000, test acc = 0.1973 test oa = 0.2837
[2024-05-21 07:08:05] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.160748, train acc = 1.0000 train oa = 1.0000, test acc = 0.1852 test oa = 0.2007
[2024-05-21 07:08:09] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.031136, train acc = 1.0000 train oa = 1.0000, test acc = 0.1777 test oa = 0.2491
[2024-05-21 07:13:26] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.103414, train acc = 1.0000 train oa = 1.0000, test acc = 0.2013 test oa = 0.2266
[2024-05-21 07:13:30] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.462907, train acc = 1.0000 train oa = 1.0000, test acc = 0.2029 test oa = 0.2076
[2024-05-21 07:13:33] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.090283, train acc = 1.0000 train oa = 1.0000, test acc = 0.1659 test oa = 0.2128
[2024-05-21 07:20:40] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.056113, train acc = 1.0000 train oa = 1.0000, test acc = 0.1617 test oa = 0.2630
[2024-05-21 07:20:44] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.450746, train acc = 1.0000 train oa = 1.0000, test acc = 0.1870 test oa = 0.2093
[2024-05-21 07:20:47] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.070320, train acc = 1.0000 train oa = 1.0000, test acc = 0.2112 test oa = 0.2837
[2024-05-21 07:27:11] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.080528, train acc = 1.0000 train oa = 1.0000, test acc = 0.1881 test oa = 0.1903
[2024-05-21 07:27:13] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.092315, train acc = 1.0000 train oa = 1.0000, test acc = 0.2072 test oa = 0.2007
[2024-05-21 07:27:17] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.221134, train acc = 1.0000 train oa = 1.0000, test acc = 0.2107 test oa = 0.1955
[2024-05-21 07:34:32] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.056699, train acc = 1.0000 train oa = 1.0000, test acc = 0.3265 test oa = 0.2768
[2024-05-21 07:34:35] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.097003, train acc = 1.0000 train oa = 1.0000, test acc = 0.2829 test oa = 0.2353
[2024-05-21 07:34:38] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.035128, train acc = 1.0000 train oa = 1.0000, test acc = 0.2834 test oa = 0.2422
[2024-05-21 07:54:19] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.123574, train acc = 0.2867 train oa = 0.2867, test acc = 0.1664 test oa = 0.1574
[2024-05-21 07:54:32] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.472660, train acc = 0.2333 train oa = 0.2333, test acc = 0.1786 test oa = 0.1626
[2024-05-21 07:54:45] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.153835, train acc = 0.3400 train oa = 0.3400, test acc = 0.2289 test oa = 0.2336
[2024-05-21 08:01:47] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.109601, train acc = 1.0000 train oa = 1.0000, test acc = 0.1831 test oa = 0.2457
[2024-05-21 08:01:50] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.368301, train acc = 1.0000 train oa = 1.0000, test acc = 0.1667 test oa = 0.1696
[2024-05-21 08:01:54] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.329280, train acc = 1.0000 train oa = 1.0000, test acc = 0.1726 test oa = 0.1713
[2024-05-21 08:09:12] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.072401, train acc = 0.4000 train oa = 0.4000, test acc = 0.1736 test oa = 0.1678
[2024-05-21 08:09:20] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.066848, train acc = 0.4133 train oa = 0.4133, test acc = 0.1322 test oa = 0.1142
[2024-05-21 08:09:28] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.354995, train acc = 0.3867 train oa = 0.3867, test acc = 0.1637 test oa = 0.1228
[2024-05-21 08:42:45] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.160918, train acc = 0.7000 train oa = 0.7000, test acc = 0.4380 test oa = 0.3945
[2024-05-21 08:42:58] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.014480, train acc = 0.7867 train oa = 0.7867, test acc = 0.3963 test oa = 0.3633
[2024-05-21 08:43:10] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.271191, train acc = 0.7333 train oa = 0.7333, test acc = 0.3824 test oa = 0.3685
[2024-05-21 08:51:22] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.074266, train acc = 1.0000 train oa = 1.0000, test acc = 0.2673 test oa = 0.2457
[2024-05-21 08:51:26] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.056080, train acc = 1.0000 train oa = 1.0000, test acc = 0.2863 test oa = 0.2578
[2024-05-21 08:51:29] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.120189, train acc = 1.0000 train oa = 1.0000, test acc = 0.2374 test oa = 0.2249
[2024-05-21 08:58:30] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.060747, train acc = 1.0000 train oa = 1.0000, test acc = 0.3183 test oa = 0.2907
[2024-05-21 08:58:32] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.099846, train acc = 1.0000 train oa = 1.0000, test acc = 0.2785 test oa = 0.2370
[2024-05-21 08:58:35] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.049999, train acc = 1.0000 train oa = 1.0000, test acc = 0.2918 test oa = 0.2595
[2024-05-21 09:03:20] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.082426, train acc = 1.0000 train oa = 1.0000, test acc = 0.2645 test oa = 0.2336
[2024-05-21 09:03:23] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.050332, train acc = 1.0000 train oa = 1.0000, test acc = 0.2566 test oa = 0.2215
[2024-05-21 09:03:27] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.047956, train acc = 1.0000 train oa = 1.0000, test acc = 0.2397 test oa = 0.1920
[2024-05-21 09:14:39] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.204605, train acc = 0.8000 train oa = 0.8000, test acc = 0.3417 test oa = 0.3287
[2024-05-21 09:14:46] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.852167, train acc = 0.9600 train oa = 0.9600, test acc = 0.3414 test oa = 0.3512
[2024-05-21 09:14:52] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.218096, train acc = 0.8400 train oa = 0.8400, test acc = 0.3374 test oa = 0.3253
[2024-05-21 09:18:58] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.112657, train acc = 1.0000 train oa = 1.0000, test acc = 0.1415 test oa = 0.1471
[2024-05-21 09:19:01] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.892327, train acc = 1.0000 train oa = 1.0000, test acc = 0.1259 test oa = 0.1263
[2024-05-21 09:19:04] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.492296, train acc = 1.0000 train oa = 1.0000, test acc = 0.1331 test oa = 0.1176
[2024-05-21 09:26:12] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.294363, train acc = 1.0000 train oa = 1.0000, test acc = 0.1512 test oa = 0.1471
[2024-05-21 09:26:16] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 1.609296, train acc = 1.0000 train oa = 1.0000, test acc = 0.1212 test oa = 0.1073
[2024-05-21 09:26:20] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.518042, train acc = 0.5333 train oa = 0.5333, test acc = 0.1321 test oa = 0.1298

================== Exp 0 ==================
 
[2024-05-21 10:00:54] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.335359, train acc = 1.0000 train oa = 1.0000, test acc = 0.0571 test oa = 0.0554
Evaluate 1, mean = 0.0571 std = 0.0000
-------------------------
[2024-05-21 10:01:05] iter = 0000, loss = 97.3355
[2024-05-21 10:03:05] iter = 0010, loss = 73.8268
[2024-05-21 10:05:01] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.475247, train acc = 1.0000 train oa = 1.0000, test acc = 0.3092 test oa = 0.2872
Evaluate 1, mean = 0.3092 std = 0.0000
-------------------------
[2024-05-21 10:05:14] iter = 0020, loss = 70.2868
[2024-05-21 10:07:16] iter = 0030, loss = 69.1683
[2024-05-21 10:09:14] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.635943, train acc = 0.9600 train oa = 0.9600, test acc = 0.3245 test oa = 0.3131
Evaluate 1, mean = 0.3245 std = 0.0000
-------------------------
[2024-05-21 10:09:26] iter = 0040, loss = 65.9715
[2024-05-21 10:11:29] iter = 0050, loss = 64.0619
[2024-05-21 10:13:26] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.749102, train acc = 0.9867 train oa = 0.9867, test acc = 0.3072 test oa = 0.2682
Evaluate 1, mean = 0.3072 std = 0.0000
-------------------------
[2024-05-21 10:13:39] iter = 0060, loss = 59.5938
[2024-05-21 10:15:41] iter = 0070, loss = 56.9886
[2024-05-21 10:17:39] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.855602, train acc = 0.9867 train oa = 0.9867, test acc = 0.3326 test oa = 0.3097
Evaluate 1, mean = 0.3326 std = 0.0000
-------------------------
[2024-05-21 10:17:52] iter = 0080, loss = 55.7411
[2024-05-21 10:19:55] iter = 0090, loss = 55.1761
[2024-05-21 10:21:55] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.930310, train acc = 0.9333 train oa = 0.9333, test acc = 0.3246 test oa = 0.3062
Evaluate 1, mean = 0.3246 std = 0.0000
-------------------------
[2024-05-21 10:22:07] iter = 0100, loss = 59.5767
[2024-05-21 10:24:08] iter = 0110, loss = 54.4128
[2024-05-21 10:25:23] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.062498, train acc = 1.0000 train oa = 1.0000, test acc = 0.2458 test oa = 0.1972
[2024-05-21 10:25:26] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.029705, train acc = 1.0000 train oa = 1.0000, test acc = 0.2021 test oa = 0.1696
[2024-05-21 10:25:30] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.038995, train acc = 1.0000 train oa = 1.0000, test acc = 0.2276 test oa = 0.1851
[2024-05-21 10:26:06] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.983447, train acc = 0.8933 train oa = 0.8933, test acc = 0.3488 test oa = 0.3218
Evaluate 1, mean = 0.3488 std = 0.0000
-------------------------
[2024-05-21 10:26:08] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.322506, train acc = 0.2800 train oa = 0.2800, test acc = 0.1908 test oa = 0.1903
[2024-05-21 10:26:16] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.501675, train acc = 0.3200 train oa = 0.3200, test acc = 0.1433 test oa = 0.1367
[2024-05-21 10:26:18] iter = 0120, loss = 58.2077
[2024-05-21 10:26:25] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.168911, train acc = 0.3067 train oa = 0.3067, test acc = 0.1952 test oa = 0.2076
[2024-05-21 10:28:21] iter = 0130, loss = 54.5078
[2024-05-21 10:30:18] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.937439, train acc = 0.9600 train oa = 0.9600, test acc = 0.3197 test oa = 0.2993
Evaluate 1, mean = 0.3197 std = 0.0000
-------------------------
[2024-05-21 10:30:31] iter = 0140, loss = 54.9456
[2024-05-21 10:32:33] iter = 0150, loss = 53.4956
[2024-05-21 10:34:31] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.003623, train acc = 0.9067 train oa = 0.9067, test acc = 0.3458 test oa = 0.3114
Evaluate 1, mean = 0.3458 std = 0.0000
-------------------------
[2024-05-21 10:34:43] iter = 0160, loss = 56.4950
[2024-05-21 10:36:47] iter = 0170, loss = 56.7626
[2024-05-21 10:37:41] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.132305, train acc = 0.3267 train oa = 0.3267, test acc = 0.2114 test oa = 0.2266
[2024-05-21 10:37:54] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.325522, train acc = 0.2933 train oa = 0.2933, test acc = 0.1691 test oa = 0.1505
[2024-05-21 10:38:07] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.163329, train acc = 0.2800 train oa = 0.2800, test acc = 0.1880 test oa = 0.1869
[2024-05-21 10:38:46] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.958922, train acc = 0.9333 train oa = 0.9333, test acc = 0.3531 test oa = 0.3270
Evaluate 1, mean = 0.3531 std = 0.0000
-------------------------
[2024-05-21 10:38:58] iter = 0180, loss = 56.6062
[2024-05-21 10:41:02] iter = 0190, loss = 53.7800
[2024-05-21 10:43:00] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.023123, train acc = 0.8800 train oa = 0.8800, test acc = 0.3677 test oa = 0.3166
Evaluate 1, mean = 0.3677 std = 0.0000
-------------------------
[2024-05-21 10:43:13] iter = 0200, loss = 56.5430
[2024-05-21 10:45:16] iter = 0210, loss = 57.5392
[2024-05-21 10:47:13] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.032890, train acc = 0.9200 train oa = 0.9200, test acc = 0.3452 test oa = 0.3235
Evaluate 1, mean = 0.3452 std = 0.0000
-------------------------
[2024-05-21 10:47:25] iter = 0220, loss = 54.4846
[2024-05-21 10:49:27] iter = 0230, loss = 54.5688
[2024-05-21 10:51:03] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.003192, train acc = 1.0000 train oa = 1.0000, test acc = 0.2124 test oa = 0.2595
[2024-05-21 10:51:06] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.004599, train acc = 1.0000 train oa = 1.0000, test acc = 0.1810 test oa = 0.1955
[2024-05-21 10:51:10] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.005039, train acc = 1.0000 train oa = 1.0000, test acc = 0.1708 test oa = 0.2024
[2024-05-21 10:51:24] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.027780, train acc = 0.9467 train oa = 0.9467, test acc = 0.3220 test oa = 0.3149
Evaluate 1, mean = 0.3220 std = 0.0000
-------------------------
[2024-05-21 10:51:36] iter = 0240, loss = 52.6483
[2024-05-21 10:53:39] iter = 0250, loss = 55.2455
[2024-05-21 10:55:37] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.017754, train acc = 0.9200 train oa = 0.9200, test acc = 0.3224 test oa = 0.3028
Evaluate 1, mean = 0.3224 std = 0.0000
-------------------------
[2024-05-21 10:55:50] iter = 0260, loss = 55.8020
[2024-05-21 10:57:52] iter = 0270, loss = 52.7590
[2024-05-21 10:59:49] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.108814, train acc = 0.8800 train oa = 0.8800, test acc = 0.3325 test oa = 0.3010
Evaluate 1, mean = 0.3325 std = 0.0000
-------------------------
[2024-05-21 11:00:01] iter = 0280, loss = 55.2493
[2024-05-21 11:02:03] iter = 0290, loss = 54.3402
[2024-05-21 11:03:51] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.043248, train acc = 1.0000 train oa = 1.0000, test acc = 0.2514 test oa = 0.2318
[2024-05-21 11:03:53] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.059255, train acc = 1.0000 train oa = 1.0000, test acc = 0.2318 test oa = 0.2145
[2024-05-21 11:03:56] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.090571, train acc = 1.0000 train oa = 1.0000, test acc = 0.2523 test oa = 0.2301
[2024-05-21 11:03:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.069380, train acc = 0.8800 train oa = 0.8800, test acc = 0.3248 test oa = 0.2941
Evaluate 1, mean = 0.3248 std = 0.0000
-------------------------
[2024-05-21 11:04:12] iter = 0300, loss = 53.9067
[2024-05-21 11:06:15] iter = 0310, loss = 52.9557
[2024-05-21 11:08:13] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.082923, train acc = 0.8667 train oa = 0.8667, test acc = 0.3632 test oa = 0.3253
Evaluate 1, mean = 0.3632 std = 0.0000
-------------------------
[2024-05-21 11:08:25] iter = 0320, loss = 56.1562
[2024-05-21 11:10:29] iter = 0330, loss = 53.9397
[2024-05-21 11:12:27] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.045321, train acc = 0.8800 train oa = 0.8800, test acc = 0.3374 test oa = 0.3149
Evaluate 1, mean = 0.3374 std = 0.0000
-------------------------
[2024-05-21 11:12:39] iter = 0340, loss = 51.6104
[2024-05-21 11:14:40] iter = 0350, loss = 55.8674
[2024-05-21 11:16:37] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.985255, train acc = 0.8800 train oa = 0.8800, test acc = 0.3211 test oa = 0.3080
Evaluate 1, mean = 0.3211 std = 0.0000
-------------------------
[2024-05-21 11:16:49] iter = 0360, loss = 55.4894
[2024-05-21 11:18:51] iter = 0370, loss = 53.1824
[2024-05-21 11:20:48] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.006483, train acc = 0.9200 train oa = 0.9200, test acc = 0.3121 test oa = 0.2958
Evaluate 1, mean = 0.3121 std = 0.0000
-------------------------
[2024-05-21 11:21:00] iter = 0380, loss = 54.2802
[2024-05-21 11:23:03] iter = 0390, loss = 55.6936
[2024-05-21 11:25:02] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.081528, train acc = 0.8933 train oa = 0.8933, test acc = 0.3626 test oa = 0.3426
Evaluate 1, mean = 0.3626 std = 0.0000
-------------------------
[2024-05-21 11:25:14] iter = 0400, loss = 53.1847
[2024-05-21 11:27:16] iter = 0410, loss = 52.8600
[2024-05-21 11:29:12] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.000763, train acc = 0.9200 train oa = 0.9200, test acc = 0.3177 test oa = 0.2993
Evaluate 1, mean = 0.3177 std = 0.0000
-------------------------
[2024-05-21 11:29:24] iter = 0420, loss = 53.2772
[2024-05-21 11:31:26] iter = 0430, loss = 53.9745
[2024-05-21 11:33:08] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.398765, train acc = 1.0000 train oa = 1.0000, test acc = 0.1492 test oa = 0.1747
[2024-05-21 11:33:12] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.366724, train acc = 1.0000 train oa = 1.0000, test acc = 0.1500 test oa = 0.1505
[2024-05-21 11:33:15] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 1.177254, train acc = 1.0000 train oa = 1.0000, test acc = 0.1414 test oa = 0.1696
[2024-05-21 11:33:25] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.057285, train acc = 0.8667 train oa = 0.8667, test acc = 0.3373 test oa = 0.3253
Evaluate 1, mean = 0.3373 std = 0.0000
-------------------------
[2024-05-21 11:33:38] iter = 0440, loss = 53.6522
[2024-05-21 11:35:40] iter = 0450, loss = 53.6297
[2024-05-21 11:37:38] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.036019, train acc = 0.8933 train oa = 0.8933, test acc = 0.3580 test oa = 0.3149
Evaluate 1, mean = 0.3580 std = 0.0000
-------------------------
[2024-05-21 11:37:50] iter = 0460, loss = 54.9727
[2024-05-21 11:39:51] iter = 0470, loss = 51.2951
[2024-05-21 11:41:48] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.976053, train acc = 0.9333 train oa = 0.9333, test acc = 0.3099 test oa = 0.2820
Evaluate 1, mean = 0.3099 std = 0.0000
-------------------------
[2024-05-21 11:42:00] iter = 0480, loss = 54.6972
[2024-05-21 11:44:03] iter = 0490, loss = 58.2687
[2024-05-21 11:46:02] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.073611, train acc = 0.8800 train oa = 0.8800, test acc = 0.3423 test oa = 0.3010
Evaluate 1, mean = 0.3423 std = 0.0000
-------------------------
[2024-05-21 11:46:15] iter = 0500, loss = 54.9278
[2024-05-21 11:48:18] iter = 0510, loss = 52.6060
[2024-05-21 11:50:16] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.043435, train acc = 0.9067 train oa = 0.9067, test acc = 0.3165 test oa = 0.3010
Evaluate 1, mean = 0.3165 std = 0.0000
-------------------------
[2024-05-21 11:50:28] iter = 0520, loss = 56.0855
[2024-05-21 11:52:29] iter = 0530, loss = 53.8409
[2024-05-21 11:54:26] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.090029, train acc = 0.9067 train oa = 0.9067, test acc = 0.3522 test oa = 0.3218
Evaluate 1, mean = 0.3522 std = 0.0000
-------------------------
[2024-05-21 11:54:39] iter = 0540, loss = 55.1599
[2024-05-21 11:56:44] iter = 0550, loss = 56.1676
[2024-05-21 11:58:43] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.074719, train acc = 0.8800 train oa = 0.8800, test acc = 0.3708 test oa = 0.3201
Evaluate 1, mean = 0.3708 std = 0.0000
-------------------------
[2024-05-21 11:58:55] iter = 0560, loss = 56.6790
[2024-05-21 12:00:56] iter = 0570, loss = 53.1646
[2024-05-21 12:02:52] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 1.042131, train acc = 0.8933 train oa = 0.8933, test acc = 0.3439 test oa = 0.3270
Evaluate 1, mean = 0.3439 std = 0.0000
-------------------------
[2024-05-21 12:03:05] iter = 0580, loss = 54.5958
[2024-05-21 12:05:08] iter = 0590, loss = 53.3248
[2024-05-21 12:07:07] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.082168, train acc = 0.9067 train oa = 0.9067, test acc = 0.3632 test oa = 0.3564
Evaluate 1, mean = 0.3632 std = 0.0000
-------------------------
[2024-05-21 12:07:19] iter = 0600, loss = 56.1482
[2024-05-21 12:09:22] iter = 0610, loss = 53.8127
[2024-05-21 12:11:18] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.003651, train acc = 0.9067 train oa = 0.9067, test acc = 0.3500 test oa = 0.3183
Evaluate 1, mean = 0.3500 std = 0.0000
-------------------------
[2024-05-21 12:11:30] iter = 0620, loss = 53.8221
[2024-05-21 12:13:33] iter = 0630, loss = 56.9134
[2024-05-21 12:15:28] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.096384, train acc = 0.8800 train oa = 0.8800, test acc = 0.3699 test oa = 0.3322
Evaluate 1, mean = 0.3699 std = 0.0000
-------------------------
[2024-05-21 12:15:41] iter = 0640, loss = 55.6876

================== Exp 0 ==================
 
[2024-05-21 12:07:37] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.065849, train acc = 0.8000 train oa = 0.8000, test acc = 0.0426 test oa = 0.0415
Evaluate 1, mean = 0.0426 std = 0.0000
-------------------------
[2024-05-21 12:07:42] iter = 0000, loss = 137.4107
[2024-05-21 12:08:35] iter = 0010, loss = 112.8435
[2024-05-21 12:17:41] iter = 0650, loss = 51.9694
[2024-05-21 12:09:29] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.368315, train acc = 0.6000 train oa = 0.6000, test acc = 0.1754 test oa = 0.1661
Evaluate 1, mean = 0.1754 std = 0.0000
-------------------------
[2024-05-21 12:09:35] iter = 0020, loss = 112.0165
[2024-05-21 12:10:28] iter = 0030, loss = 103.5967
[2024-05-21 12:19:41] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.003848, train acc = 0.8933 train oa = 0.8933, test acc = 0.3454 test oa = 0.3183
Evaluate 1, mean = 0.3454 std = 0.0000
-------------------------
[2024-05-21 12:19:53] iter = 0660, loss = 56.7282
[2024-05-21 12:11:22] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.977195, train acc = 0.4667 train oa = 0.4667, test acc = 0.1285 test oa = 0.1315
Evaluate 1, mean = 0.1285 std = 0.0000
-------------------------
[2024-05-21 12:11:27] iter = 0040, loss = 121.2142
[2024-05-21 12:12:21] iter = 0050, loss = 114.5807
[2024-05-21 12:13:15] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.315569, train acc = 0.6800 train oa = 0.6800, test acc = 0.2049 test oa = 0.2180
Evaluate 1, mean = 0.2049 std = 0.0000
-------------------------
[2024-05-21 12:21:55] iter = 0670, loss = 54.1184
[2024-05-21 12:13:21] iter = 0060, loss = 104.2442
[2024-05-21 12:14:15] iter = 0070, loss = 108.7176
[2024-05-21 12:15:09] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 2.097191, train acc = 0.4000 train oa = 0.4000, test acc = 0.1546 test oa = 0.1505
Evaluate 1, mean = 0.1546 std = 0.0000
-------------------------
[2024-05-21 12:15:15] iter = 0080, loss = 105.8343
[2024-05-21 12:23:53] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 1.081245, train acc = 0.9333 train oa = 0.9333, test acc = 0.3416 test oa = 0.3010
Evaluate 1, mean = 0.3416 std = 0.0000
-------------------------
[2024-05-21 12:24:05] iter = 0680, loss = 50.0366
[2024-05-21 12:16:09] iter = 0090, loss = 108.1494
[2024-05-21 12:17:04] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.911757, train acc = 0.4267 train oa = 0.4267, test acc = 0.1463 test oa = 0.1471
Evaluate 1, mean = 0.1463 std = 0.0000
-------------------------
[2024-05-21 12:17:10] iter = 0100, loss = 99.9801
[2024-05-21 12:25:59] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.005620, train acc = 1.0000 train oa = 1.0000, test acc = 0.2114 test oa = 0.1696
[2024-05-21 12:26:02] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.022381, train acc = 1.0000 train oa = 1.0000, test acc = 0.2344 test oa = 0.1920
[2024-05-21 12:26:05] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.009766, train acc = 1.0000 train oa = 1.0000, test acc = 0.2280 test oa = 0.1869
[2024-05-21 12:26:09] iter = 0690, loss = 53.0339
[2024-05-21 12:18:08] iter = 0110, loss = 106.9140
[2024-05-21 12:19:09] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.089609, train acc = 0.3067 train oa = 0.3067, test acc = 0.1494 test oa = 0.1367
Evaluate 1, mean = 0.1494 std = 0.0000
-------------------------
[2024-05-21 12:19:15] iter = 0120, loss = 99.1725
[2024-05-21 12:28:04] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.024364, train acc = 0.9067 train oa = 0.9067, test acc = 0.3477 test oa = 0.3304
Evaluate 1, mean = 0.3477 std = 0.0000
-------------------------
[2024-05-21 12:28:17] iter = 0700, loss = 54.1294
[2024-05-21 12:20:08] iter = 0130, loss = 102.6377
[2024-05-21 12:21:08] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.126312, train acc = 0.4933 train oa = 0.4933, test acc = 0.1573 test oa = 0.1522
Evaluate 1, mean = 0.1573 std = 0.0000
-------------------------
[2024-05-21 12:21:14] iter = 0140, loss = 100.5072
[2024-05-21 12:30:18] iter = 0710, loss = 54.1288
[2024-05-21 12:22:09] iter = 0150, loss = 112.2095
[2024-05-21 12:23:10] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.094470, train acc = 0.3067 train oa = 0.3067, test acc = 0.1529 test oa = 0.1522
Evaluate 1, mean = 0.1529 std = 0.0000
-------------------------
[2024-05-21 12:23:16] iter = 0160, loss = 96.4985
[2024-05-21 12:32:16] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.043526, train acc = 0.9200 train oa = 0.9200, test acc = 0.3506 test oa = 0.3253
Evaluate 1, mean = 0.3506 std = 0.0000
-------------------------
[2024-05-21 12:32:32] iter = 0720, loss = 51.7909
[2024-05-21 12:33:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.366604, train acc = 0.7333 train oa = 0.7333, test acc = 0.3355 test oa = 0.3287
[2024-05-21 12:33:30] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 0.031990, train acc = 1.0000 train oa = 1.0000, test acc = 0.2611 test oa = 0.2474
[2024-05-21 12:33:34] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.032111, train acc = 1.0000 train oa = 1.0000, test acc = 0.2763 test oa = 0.2630
[2024-05-21 12:33:37] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.190906, train acc = 0.8133 train oa = 0.8133, test acc = 0.3410 test oa = 0.3166
[2024-05-21 12:33:41] Evaluate_02: epoch = 0300, train time = 4 s, train loss = 0.040537, train acc = 1.0000 train oa = 1.0000, test acc = 0.2700 test oa = 0.2872
[2024-05-21 12:33:45] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.247851, train acc = 0.7733 train oa = 0.7733, test acc = 0.3522 test oa = 0.3443
[2024-05-21 12:34:33] iter = 0730, loss = 54.0742
[2024-05-21 12:36:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.058988, train acc = 0.8933 train oa = 0.8933, test acc = 0.3191 test oa = 0.3131
Evaluate 1, mean = 0.3191 std = 0.0000
-------------------------
[2024-05-21 12:36:43] iter = 0740, loss = 52.5083
[2024-05-21 12:38:42] iter = 0750, loss = 52.0087
[2024-05-21 12:40:37] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.092955, train acc = 0.9067 train oa = 0.9067, test acc = 0.3611 test oa = 0.3166
Evaluate 1, mean = 0.3611 std = 0.0000
-------------------------
[2024-05-21 12:40:49] iter = 0760, loss = 54.1944
[2024-05-21 12:42:48] iter = 0770, loss = 51.5786
[2024-05-21 12:44:44] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.048653, train acc = 0.8667 train oa = 0.8667, test acc = 0.3457 test oa = 0.3304
Evaluate 1, mean = 0.3457 std = 0.0000
-------------------------
[2024-05-21 12:44:56] iter = 0780, loss = 53.0709
[2024-05-21 12:46:58] iter = 0790, loss = 55.0372
[2024-05-21 12:47:11] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.209303, train acc = 0.3200 train oa = 0.3200, test acc = 0.2021 test oa = 0.2232
[2024-05-21 12:47:24] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.516448, train acc = 0.2400 train oa = 0.2400, test acc = 0.1632 test oa = 0.1384
[2024-05-21 12:47:38] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.268870, train acc = 0.2467 train oa = 0.2467, test acc = 0.2173 test oa = 0.2284
[2024-05-21 12:48:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.969194, train acc = 0.9067 train oa = 0.9067, test acc = 0.3570 test oa = 0.3235
Evaluate 1, mean = 0.3570 std = 0.0000
-------------------------
[2024-05-21 12:49:11] iter = 0800, loss = 52.7254
[2024-05-21 12:51:14] iter = 0810, loss = 53.5387
[2024-05-21 12:51:54] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 1.782561, train acc = 0.8667 train oa = 0.8667, test acc = 0.1110 test oa = 0.0917
[2024-05-21 12:51:58] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 1.922152, train acc = 0.8667 train oa = 0.8667, test acc = 0.1345 test oa = 0.1107
[2024-05-21 12:52:01] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.368210, train acc = 1.0000 train oa = 1.0000, test acc = 0.0982 test oa = 0.1003
[2024-05-21 12:52:20] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.358640, train acc = 0.6400 train oa = 0.6400, test acc = 0.4116 test oa = 0.3841
[2024-05-21 12:52:32] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.309327, train acc = 0.6400 train oa = 0.6400, test acc = 0.3937 test oa = 0.3806
[2024-05-21 12:52:44] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.132109, train acc = 0.7333 train oa = 0.7333, test acc = 0.4039 test oa = 0.3858
[2024-05-21 12:53:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.015985, train acc = 0.9067 train oa = 0.9067, test acc = 0.3176 test oa = 0.2907
Evaluate 1, mean = 0.3176 std = 0.0000
-------------------------
[2024-05-21 12:53:24] iter = 0820, loss = 52.1569
[2024-05-21 12:55:22] iter = 0830, loss = 52.2894
[2024-05-21 12:57:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.102023, train acc = 0.8800 train oa = 0.8800, test acc = 0.3454 test oa = 0.3201
Evaluate 1, mean = 0.3454 std = 0.0000
-------------------------
[2024-05-21 12:57:29] iter = 0840, loss = 55.8706
[2024-05-21 12:59:14] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.056113, train acc = 1.0000 train oa = 1.0000, test acc = 0.1617 test oa = 0.2630
[2024-05-21 12:59:18] Evaluate_01: epoch = 0300, train time = 4 s, train loss = 0.450746, train acc = 1.0000 train oa = 1.0000, test acc = 0.1870 test oa = 0.2093
[2024-05-21 12:59:22] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.070320, train acc = 1.0000 train oa = 1.0000, test acc = 0.2112 test oa = 0.2837
[2024-05-21 12:59:28] iter = 0850, loss = 55.3100
[2024-05-21 13:01:26] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.050592, train acc = 0.9200 train oa = 0.9200, test acc = 0.3570 test oa = 0.3322
Evaluate 1, mean = 0.3570 std = 0.0000
-------------------------
[2024-05-21 13:01:38] iter = 0860, loss = 54.4485
[2024-05-21 13:03:43] iter = 0870, loss = 52.6583
[2024-05-21 13:05:39] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.030410, train acc = 0.8933 train oa = 0.8933, test acc = 0.3591 test oa = 0.3339
Evaluate 1, mean = 0.3591 std = 0.0000
-------------------------
[2024-05-21 13:05:52] iter = 0880, loss = 54.0897
[2024-05-21 13:07:54] iter = 0890, loss = 51.4379

================== Exp 0 ==================
 
[2024-05-21 13:00:04] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.031571, train acc = 1.0000 train oa = 1.0000, test acc = 0.0825 test oa = 0.0796
Evaluate 1, mean = 0.0825 std = 0.0000
-------------------------
[2024-05-21 13:00:04] iter = 0000, loss = 394.3570
[2024-05-21 13:00:05] iter = 0010, loss = 71.2911
[2024-05-21 13:00:06] iter = 0020, loss = 40.2147
[2024-05-21 13:00:07] iter = 0030, loss = 34.9004
[2024-05-21 13:00:08] iter = 0040, loss = 28.3288
[2024-05-21 13:00:08] iter = 0050, loss = 26.4365
[2024-05-21 13:00:09] iter = 0060, loss = 22.2747
[2024-05-21 13:00:10] iter = 0070, loss = 21.2712
[2024-05-21 13:00:11] iter = 0080, loss = 22.1509
[2024-05-21 13:00:12] iter = 0090, loss = 20.4065
[2024-05-21 13:00:18] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.790540, train acc = 0.8800 train oa = 0.8800, test acc = 0.1046 test oa = 0.1038
Evaluate 1, mean = 0.1046 std = 0.0000
-------------------------
[2024-05-21 13:00:18] iter = 0100, loss = 21.9695
[2024-05-21 13:00:19] iter = 0110, loss = 20.3491
[2024-05-21 13:00:20] iter = 0120, loss = 20.3513
[2024-05-21 13:00:20] iter = 0130, loss = 18.3725
[2024-05-21 13:00:21] iter = 0140, loss = 20.2343
[2024-05-21 13:00:22] iter = 0150, loss = 19.2597
[2024-05-21 13:00:23] iter = 0160, loss = 19.1275
[2024-05-21 13:00:24] iter = 0170, loss = 20.9225
[2024-05-21 13:00:25] iter = 0180, loss = 17.1733
[2024-05-21 13:00:25] iter = 0190, loss = 16.1292
[2024-05-21 13:00:32] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.571091, train acc = 0.9733 train oa = 0.9733, test acc = 0.1916 test oa = 0.1799
Evaluate 1, mean = 0.1916 std = 0.0000
-------------------------
[2024-05-21 13:00:32] iter = 0200, loss = 19.2282
[2024-05-21 13:00:33] iter = 0210, loss = 20.4860
[2024-05-21 13:00:34] iter = 0220, loss = 19.3730
[2024-05-21 13:00:34] iter = 0230, loss = 17.5286
[2024-05-21 13:00:35] iter = 0240, loss = 15.3037
[2024-05-21 13:00:36] iter = 0250, loss = 16.8851
[2024-05-21 13:00:37] iter = 0260, loss = 16.4561
[2024-05-21 13:00:38] iter = 0270, loss = 17.5511
[2024-05-21 13:00:38] iter = 0280, loss = 15.3116
[2024-05-21 13:00:39] iter = 0290, loss = 18.9291
[2024-05-21 13:00:46] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.861548, train acc = 0.9200 train oa = 0.9200, test acc = 0.1601 test oa = 0.2336
Evaluate 1, mean = 0.1601 std = 0.0000
-------------------------
[2024-05-21 13:00:46] iter = 0300, loss = 15.4841
[2024-05-21 13:00:46] iter = 0310, loss = 16.5905
[2024-05-21 13:00:47] iter = 0320, loss = 17.5676
[2024-05-21 13:00:48] iter = 0330, loss = 18.1254
[2024-05-21 13:00:49] iter = 0340, loss = 16.9429
[2024-05-21 13:00:50] iter = 0350, loss = 17.4440
[2024-05-21 13:00:51] iter = 0360, loss = 18.0449
[2024-05-21 13:00:51] iter = 0370, loss = 16.3648
[2024-05-21 13:00:52] iter = 0380, loss = 17.6401
[2024-05-21 13:00:53] iter = 0390, loss = 16.7693
[2024-05-21 13:00:59] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 1.055356, train acc = 0.8267 train oa = 0.8267, test acc = 0.1706 test oa = 0.1886
Evaluate 1, mean = 0.1706 std = 0.0000
-------------------------
[2024-05-21 13:01:00] iter = 0400, loss = 18.8726
[2024-05-21 13:01:00] iter = 0410, loss = 16.6768
[2024-05-21 13:01:01] iter = 0420, loss = 16.3554
[2024-05-21 13:01:02] iter = 0430, loss = 15.2146
[2024-05-21 13:01:03] iter = 0440, loss = 16.0506
[2024-05-21 13:01:04] iter = 0450, loss = 14.5187
[2024-05-21 13:01:04] iter = 0460, loss = 14.9030
[2024-05-21 13:01:05] iter = 0470, loss = 14.0676
[2024-05-21 13:01:06] iter = 0480, loss = 15.5529
[2024-05-21 13:01:07] iter = 0490, loss = 17.4241
[2024-05-21 13:01:13] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.850799, train acc = 0.9067 train oa = 0.9067, test acc = 0.2392 test oa = 0.2716
Evaluate 1, mean = 0.2392 std = 0.0000
-------------------------
[2024-05-21 13:01:13] iter = 0500, loss = 15.7357
[2024-05-21 13:01:14] iter = 0510, loss = 16.0992
[2024-05-21 13:09:53] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.004559, train acc = 0.9067 train oa = 0.9067, test acc = 0.3385 test oa = 0.3183
Evaluate 1, mean = 0.3385 std = 0.0000
-------------------------
[2024-05-21 13:01:15] iter = 0520, loss = 16.9785
[2024-05-21 13:01:16] iter = 0530, loss = 15.3483
[2024-05-21 13:01:17] iter = 0540, loss = 16.4695
[2024-05-21 13:01:17] iter = 0550, loss = 14.4565
[2024-05-21 13:01:18] iter = 0560, loss = 16.4897
[2024-05-21 13:01:19] iter = 0570, loss = 18.9817
[2024-05-21 13:01:20] iter = 0580, loss = 16.5533
[2024-05-21 13:01:21] iter = 0590, loss = 17.1712
[2024-05-21 13:01:27] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.875564, train acc = 0.8800 train oa = 0.8800, test acc = 0.2615 test oa = 0.2664
Evaluate 1, mean = 0.2615 std = 0.0000
-------------------------
[2024-05-21 13:10:05] iter = 0900, loss = 54.2448
[2024-05-21 13:01:27] iter = 0600, loss = 14.7399
[2024-05-21 13:01:28] iter = 0610, loss = 16.0022
[2024-05-21 13:01:29] iter = 0620, loss = 15.6176
[2024-05-21 13:01:29] iter = 0630, loss = 15.2971
[2024-05-21 13:01:30] iter = 0640, loss = 14.9083
[2024-05-21 13:01:31] iter = 0650, loss = 17.0792
[2024-05-21 13:01:32] iter = 0660, loss = 14.4583
[2024-05-21 13:01:33] iter = 0670, loss = 13.4170
[2024-05-21 13:01:33] iter = 0680, loss = 13.7593
[2024-05-21 13:01:34] iter = 0690, loss = 14.5799
[2024-05-21 13:01:41] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.677565, train acc = 0.9733 train oa = 0.9733, test acc = 0.3413 test oa = 0.3304
Evaluate 1, mean = 0.3413 std = 0.0000
-------------------------
[2024-05-21 13:01:41] iter = 0700, loss = 14.9335
[2024-05-21 13:01:42] iter = 0710, loss = 15.2167
[2024-05-21 13:01:42] iter = 0720, loss = 16.4907
[2024-05-21 13:01:43] iter = 0730, loss = 15.1823
[2024-05-21 13:01:44] iter = 0740, loss = 17.1470
[2024-05-21 13:01:45] iter = 0750, loss = 16.4461
[2024-05-21 13:01:46] iter = 0760, loss = 15.7466
[2024-05-21 13:01:47] iter = 0770, loss = 18.8792
[2024-05-21 13:01:47] iter = 0780, loss = 14.2019
[2024-05-21 13:01:48] iter = 0790, loss = 15.6297
[2024-05-21 13:01:55] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.669836, train acc = 0.9600 train oa = 0.9600, test acc = 0.3554 test oa = 0.3772
Evaluate 1, mean = 0.3554 std = 0.0000
-------------------------
[2024-05-21 13:01:55] iter = 0800, loss = 17.2270
[2024-05-21 13:01:56] iter = 0810, loss = 15.8699
[2024-05-21 13:01:56] iter = 0820, loss = 15.4358
[2024-05-21 13:01:57] iter = 0830, loss = 15.0800
[2024-05-21 13:01:58] iter = 0840, loss = 15.5430
[2024-05-21 13:01:59] iter = 0850, loss = 17.6051
[2024-05-21 13:02:00] iter = 0860, loss = 13.3855
[2024-05-21 13:02:00] iter = 0870, loss = 15.3243
[2024-05-21 13:02:01] iter = 0880, loss = 15.0944
[2024-05-21 13:02:02] iter = 0890, loss = 14.1528
[2024-05-21 13:02:09] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.827087, train acc = 0.8800 train oa = 0.8800, test acc = 0.3385 test oa = 0.3651
Evaluate 1, mean = 0.3385 std = 0.0000
-------------------------
[2024-05-21 13:02:09] iter = 0900, loss = 13.3925
[2024-05-21 13:02:09] iter = 0910, loss = 13.8845
[2024-05-21 13:02:10] iter = 0920, loss = 15.6628
[2024-05-21 13:02:11] iter = 0930, loss = 14.4402
[2024-05-21 13:02:12] iter = 0940, loss = 15.4685
[2024-05-21 13:02:13] iter = 0950, loss = 15.1129
[2024-05-21 13:02:14] iter = 0960, loss = 14.2233
[2024-05-21 13:02:14] iter = 0970, loss = 12.0361
[2024-05-21 13:02:15] iter = 0980, loss = 14.2371
[2024-05-21 13:02:16] iter = 0990, loss = 14.5297
[2024-05-21 13:02:22] Evaluate_00: epoch = 0300, train time = 5 s, train loss = 0.722264, train acc = 0.9733 train oa = 0.9733, test acc = 0.3522 test oa = 0.3720
Evaluate 1, mean = 0.3522 std = 0.0000
-------------------------
[2024-05-21 13:02:23] iter = 1000, loss = 13.5714

================== Exp 0 ==================
 
[2024-05-21 13:02:40] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000084, train acc = 1.0000 train oa = 1.0000, test acc = 0.0436 test oa = 0.0190
Evaluate 1, mean = 0.0436 std = 0.0000
-------------------------
[2024-05-21 13:02:40] iter = 0000, loss = 726.6176
[2024-05-21 13:02:41] iter = 0010, loss = 162.2273
[2024-05-21 13:02:41] iter = 0020, loss = 113.5908
[2024-05-21 13:02:42] iter = 0030, loss = 99.4451
[2024-05-21 13:02:42] iter = 0040, loss = 86.4228
[2024-05-21 13:02:43] iter = 0050, loss = 81.2981
[2024-05-21 13:02:44] iter = 0060, loss = 80.3639
[2024-05-21 13:02:44] iter = 0070, loss = 76.1418
[2024-05-21 13:02:45] iter = 0080, loss = 81.7118
[2024-05-21 13:02:45] iter = 0090, loss = 76.9502
[2024-05-21 13:02:48] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.021161, train acc = 1.0000 train oa = 1.0000, test acc = 0.2719 test oa = 0.2716
Evaluate 1, mean = 0.2719 std = 0.0000
-------------------------
[2024-05-21 13:02:48] iter = 0100, loss = 77.3877
[2024-05-21 13:02:48] iter = 0110, loss = 73.5739
[2024-05-21 13:02:49] iter = 0120, loss = 73.2596
[2024-05-21 13:02:50] iter = 0130, loss = 64.1309
[2024-05-21 13:02:50] iter = 0140, loss = 66.3802
[2024-05-21 13:02:51] iter = 0150, loss = 71.8087
[2024-05-21 13:02:51] iter = 0160, loss = 70.1153
[2024-05-21 13:02:52] iter = 0170, loss = 72.2836
[2024-05-21 13:02:52] iter = 0180, loss = 71.1031
[2024-05-21 13:02:53] iter = 0190, loss = 71.4072
[2024-05-21 13:02:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024224, train acc = 1.0000 train oa = 1.0000, test acc = 0.2927 test oa = 0.2734
Evaluate 1, mean = 0.2927 std = 0.0000
-------------------------
[2024-05-21 13:02:55] iter = 0200, loss = 69.5986
[2024-05-21 13:02:56] iter = 0210, loss = 70.5120
[2024-05-21 13:02:57] iter = 0220, loss = 63.6347
[2024-05-21 13:02:57] iter = 0230, loss = 67.0890
[2024-05-21 13:02:58] iter = 0240, loss = 65.9394
[2024-05-21 13:02:58] iter = 0250, loss = 64.6719
[2024-05-21 13:02:59] iter = 0260, loss = 66.8715
[2024-05-21 13:02:59] iter = 0270, loss = 69.6175
[2024-05-21 13:03:00] iter = 0280, loss = 64.0838
[2024-05-21 13:03:01] iter = 0290, loss = 67.8771
[2024-05-21 13:03:03] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.025169, train acc = 1.0000 train oa = 1.0000, test acc = 0.2826 test oa = 0.2526
Evaluate 1, mean = 0.2826 std = 0.0000
-------------------------
[2024-05-21 13:03:03] iter = 0300, loss = 67.3533
[2024-05-21 13:03:04] iter = 0310, loss = 65.7244
[2024-05-21 13:03:04] iter = 0320, loss = 67.1042
[2024-05-21 13:03:05] iter = 0330, loss = 72.4269
[2024-05-21 13:03:05] iter = 0340, loss = 67.1009
[2024-05-21 13:03:06] iter = 0350, loss = 68.5994
[2024-05-21 13:03:07] iter = 0360, loss = 71.2119
[2024-05-21 13:03:07] iter = 0370, loss = 65.9746
[2024-05-21 13:03:08] iter = 0380, loss = 54.7322
[2024-05-21 13:03:08] iter = 0390, loss = 65.8655
[2024-05-21 13:03:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.021218, train acc = 1.0000 train oa = 1.0000, test acc = 0.2376 test oa = 0.2215
Evaluate 1, mean = 0.2376 std = 0.0000
-------------------------
[2024-05-21 13:03:11] iter = 0400, loss = 62.4496
[2024-05-21 13:03:11] iter = 0410, loss = 71.2498
[2024-05-21 13:03:12] iter = 0420, loss = 65.8483
[2024-05-21 13:03:12] iter = 0430, loss = 67.2761
[2024-05-21 13:03:13] iter = 0440, loss = 56.4859
[2024-05-21 13:03:14] iter = 0450, loss = 64.9302
[2024-05-21 13:03:14] iter = 0460, loss = 69.4912
[2024-05-21 13:03:15] iter = 0470, loss = 64.9246
[2024-05-21 13:03:15] iter = 0480, loss = 66.8929
[2024-05-21 13:03:16] iter = 0490, loss = 71.1113
[2024-05-21 13:03:18] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.028660, train acc = 1.0000 train oa = 1.0000, test acc = 0.3181 test oa = 0.3149
Evaluate 1, mean = 0.3181 std = 0.0000
-------------------------
[2024-05-21 13:03:18] iter = 0500, loss = 65.2716
[2024-05-21 13:03:19] iter = 0510, loss = 62.8385
[2024-05-21 13:03:20] iter = 0520, loss = 64.0158
[2024-05-21 13:03:20] iter = 0530, loss = 64.5257
[2024-05-21 13:03:21] iter = 0540, loss = 66.7552
[2024-05-21 13:03:21] iter = 0550, loss = 62.6410
[2024-05-21 13:03:22] iter = 0560, loss = 63.2921
[2024-05-21 13:03:22] iter = 0570, loss = 65.3694
[2024-05-21 13:03:23] iter = 0580, loss = 62.2988
[2024-05-21 13:03:24] iter = 0590, loss = 61.7846
[2024-05-21 13:03:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.018804, train acc = 1.0000 train oa = 1.0000, test acc = 0.2860 test oa = 0.2595
Evaluate 1, mean = 0.2860 std = 0.0000
-------------------------
[2024-05-21 13:03:26] iter = 0600, loss = 60.5660
[2024-05-21 13:03:27] iter = 0610, loss = 57.2972
[2024-05-21 13:03:27] iter = 0620, loss = 62.4165
[2024-05-21 13:03:28] iter = 0630, loss = 63.2171
[2024-05-21 13:03:28] iter = 0640, loss = 62.8649
[2024-05-21 13:12:07] iter = 0910, loss = 50.6719
[2024-05-21 13:03:29] iter = 0650, loss = 64.3544
[2024-05-21 13:03:30] iter = 0660, loss = 57.0132
[2024-05-21 13:03:30] iter = 0670, loss = 64.1270
[2024-05-21 13:03:31] iter = 0680, loss = 54.1261
[2024-05-21 13:03:31] iter = 0690, loss = 70.5509
[2024-05-21 13:03:34] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.022119, train acc = 1.0000 train oa = 1.0000, test acc = 0.2932 test oa = 0.2439
Evaluate 1, mean = 0.2932 std = 0.0000
-------------------------
[2024-05-21 13:03:34] iter = 0700, loss = 71.0289
[2024-05-21 13:03:34] iter = 0710, loss = 72.4010
[2024-05-21 13:03:35] iter = 0720, loss = 64.3986
[2024-05-21 13:03:36] iter = 0730, loss = 65.6982
[2024-05-21 13:03:36] iter = 0740, loss = 64.1416
[2024-05-21 13:03:37] iter = 0750, loss = 65.4324
[2024-05-21 13:03:37] iter = 0760, loss = 57.4384
[2024-05-21 13:03:38] iter = 0770, loss = 67.2087
[2024-05-21 13:03:38] iter = 0780, loss = 62.7251
[2024-05-21 13:03:39] iter = 0790, loss = 59.8298
[2024-05-21 13:03:42] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.032487, train acc = 1.0000 train oa = 1.0000, test acc = 0.2560 test oa = 0.2180
Evaluate 1, mean = 0.2560 std = 0.0000
-------------------------
[2024-05-21 13:03:42] iter = 0800, loss = 63.1305
[2024-05-21 13:03:42] iter = 0810, loss = 53.6251
[2024-05-21 13:03:43] iter = 0820, loss = 55.8994
[2024-05-21 13:03:43] iter = 0830, loss = 67.3235
[2024-05-21 13:03:44] iter = 0840, loss = 60.3323
[2024-05-21 13:03:44] iter = 0850, loss = 65.8039
[2024-05-21 13:03:45] iter = 0860, loss = 59.8347
[2024-05-21 13:03:46] iter = 0870, loss = 63.8888
[2024-05-21 13:03:46] iter = 0880, loss = 62.5959
[2024-05-21 13:03:47] iter = 0890, loss = 57.9796
[2024-05-21 13:03:49] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.041489, train acc = 1.0000 train oa = 1.0000, test acc = 0.2883 test oa = 0.2630
Evaluate 1, mean = 0.2883 std = 0.0000
-------------------------
[2024-05-21 13:03:49] iter = 0900, loss = 62.4884
[2024-05-21 13:03:50] iter = 0910, loss = 61.2792
[2024-05-21 13:03:51] iter = 0920, loss = 66.2222
[2024-05-21 13:03:51] iter = 0930, loss = 65.0514
[2024-05-21 13:03:52] iter = 0940, loss = 61.6286
[2024-05-21 13:03:52] iter = 0950, loss = 62.7974
[2024-05-21 13:03:53] iter = 0960, loss = 61.7905
[2024-05-21 13:03:53] iter = 0970, loss = 60.8058
[2024-05-21 13:03:54] iter = 0980, loss = 60.5708
[2024-05-21 13:03:55] iter = 0990, loss = 57.1056
[2024-05-21 13:03:57] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024037, train acc = 1.0000 train oa = 1.0000, test acc = 0.2692 test oa = 0.2215
Evaluate 1, mean = 0.2692 std = 0.0000
-------------------------
[2024-05-21 13:03:57] iter = 1000, loss = 65.3192

================== Exp 0 ==================
 
[2024-05-21 13:04:18] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000084, train acc = 1.0000 train oa = 1.0000, test acc = 0.0436 test oa = 0.0190
Evaluate 1, mean = 0.0436 std = 0.0000
-------------------------
[2024-05-21 13:04:18] iter = 0000, loss = 726.6176
[2024-05-21 13:04:18] iter = 0010, loss = 283.5895
[2024-05-21 13:04:19] iter = 0020, loss = 182.8770
[2024-05-21 13:04:20] iter = 0030, loss = 145.6079
[2024-05-21 13:04:20] iter = 0040, loss = 128.1936
[2024-05-21 13:04:21] iter = 0050, loss = 108.1001
[2024-05-21 13:04:21] iter = 0060, loss = 108.4098
[2024-05-21 13:04:22] iter = 0070, loss = 96.3568
[2024-05-21 13:04:23] iter = 0080, loss = 103.3566
[2024-05-21 13:04:23] iter = 0090, loss = 91.9119
[2024-05-21 13:04:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.011349, train acc = 1.0000 train oa = 1.0000, test acc = 0.2812 test oa = 0.2318
Evaluate 1, mean = 0.2812 std = 0.0000
-------------------------
[2024-05-21 13:04:26] iter = 0100, loss = 91.6016
[2024-05-21 13:04:26] iter = 0110, loss = 84.3912
[2024-05-21 13:04:27] iter = 0120, loss = 82.7865
[2024-05-21 13:04:27] iter = 0130, loss = 72.6603
[2024-05-21 13:04:28] iter = 0140, loss = 71.5575
[2024-05-21 13:04:28] iter = 0150, loss = 82.4388
[2024-05-21 13:04:29] iter = 0160, loss = 74.9601
[2024-05-21 13:04:30] iter = 0170, loss = 79.9046
[2024-05-21 13:04:30] iter = 0180, loss = 77.8738
[2024-05-21 13:04:31] iter = 0190, loss = 77.8197
[2024-05-21 13:04:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.017722, train acc = 1.0000 train oa = 1.0000, test acc = 0.2803 test oa = 0.2561
Evaluate 1, mean = 0.2803 std = 0.0000
-------------------------
[2024-05-21 13:04:33] iter = 0200, loss = 76.0346
[2024-05-21 13:04:34] iter = 0210, loss = 75.0112
[2024-05-21 13:04:35] iter = 0220, loss = 67.8259
[2024-05-21 13:04:35] iter = 0230, loss = 70.4153
[2024-05-21 13:04:36] iter = 0240, loss = 72.4005
[2024-05-21 13:04:36] iter = 0250, loss = 69.7059
[2024-05-21 13:04:37] iter = 0260, loss = 70.9460
[2024-05-21 13:04:37] iter = 0270, loss = 75.0625
[2024-05-21 13:04:38] iter = 0280, loss = 68.3963
[2024-05-21 13:04:39] iter = 0290, loss = 70.5232
[2024-05-21 13:04:41] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.006224, train acc = 1.0000 train oa = 1.0000, test acc = 0.2419 test oa = 0.2197
Evaluate 1, mean = 0.2419 std = 0.0000
-------------------------
[2024-05-21 13:04:41] iter = 0300, loss = 72.9619
[2024-05-21 13:04:42] iter = 0310, loss = 70.7227
[2024-05-21 13:04:42] iter = 0320, loss = 70.8901
[2024-05-21 13:04:43] iter = 0330, loss = 73.7943
[2024-05-21 13:04:44] iter = 0340, loss = 69.9206
[2024-05-21 13:04:44] iter = 0350, loss = 70.4363
[2024-05-21 13:04:45] iter = 0360, loss = 72.6060
[2024-05-21 13:04:45] iter = 0370, loss = 69.1435
[2024-05-21 13:04:46] iter = 0380, loss = 58.2424
[2024-05-21 13:04:47] iter = 0390, loss = 66.9000
[2024-05-21 13:04:49] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.019626, train acc = 1.0000 train oa = 1.0000, test acc = 0.2648 test oa = 0.2042
Evaluate 1, mean = 0.2648 std = 0.0000
-------------------------
[2024-05-21 13:04:49] iter = 0400, loss = 65.1686
[2024-05-21 13:04:50] iter = 0410, loss = 74.3183
[2024-05-21 13:04:50] iter = 0420, loss = 66.6170
[2024-05-21 13:04:51] iter = 0430, loss = 70.2675
[2024-05-21 13:04:51] iter = 0440, loss = 59.7510
[2024-05-21 13:04:52] iter = 0450, loss = 69.4995
[2024-05-21 13:04:53] iter = 0460, loss = 72.9268
[2024-05-21 13:04:53] iter = 0470, loss = 66.4657
[2024-05-21 13:04:54] iter = 0480, loss = 66.2010
[2024-05-21 13:04:54] iter = 0490, loss = 74.1545
[2024-05-21 13:04:57] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.020221, train acc = 1.0000 train oa = 1.0000, test acc = 0.2533 test oa = 0.2353
Evaluate 1, mean = 0.2533 std = 0.0000
-------------------------
[2024-05-21 13:04:57] iter = 0500, loss = 65.8136
[2024-05-21 13:04:58] iter = 0510, loss = 66.1258
[2024-05-21 13:04:58] iter = 0520, loss = 65.9990
[2024-05-21 13:04:59] iter = 0530, loss = 67.1348
[2024-05-21 13:04:59] iter = 0540, loss = 69.1611
[2024-05-21 13:05:00] iter = 0550, loss = 63.4532
[2024-05-21 13:05:00] iter = 0560, loss = 64.2385
[2024-05-21 13:05:01] iter = 0570, loss = 64.6775
[2024-05-21 13:05:02] iter = 0580, loss = 62.3908
[2024-05-21 13:05:02] iter = 0590, loss = 65.1079
[2024-05-21 13:05:05] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.008836, train acc = 1.0000 train oa = 1.0000, test acc = 0.2698 test oa = 0.2370
Evaluate 1, mean = 0.2698 std = 0.0000
-------------------------
[2024-05-21 13:05:05] iter = 0600, loss = 63.5767
[2024-05-21 13:05:05] iter = 0610, loss = 58.6274
[2024-05-21 13:05:06] iter = 0620, loss = 64.9055
[2024-05-21 13:05:07] iter = 0630, loss = 64.8036
[2024-05-21 13:05:07] iter = 0640, loss = 64.9580
[2024-05-21 13:05:08] iter = 0650, loss = 63.7229
[2024-05-21 13:05:08] iter = 0660, loss = 58.9470
[2024-05-21 13:05:09] iter = 0670, loss = 63.7897
[2024-05-21 13:05:10] iter = 0680, loss = 57.9680
[2024-05-21 13:05:10] iter = 0690, loss = 71.3139
[2024-05-21 13:05:13] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024614, train acc = 1.0000 train oa = 1.0000, test acc = 0.2785 test oa = 0.2353
Evaluate 1, mean = 0.2785 std = 0.0000
-------------------------
[2024-05-21 13:05:13] iter = 0700, loss = 72.3272
[2024-05-21 13:05:13] iter = 0710, loss = 73.1752
[2024-05-21 13:05:14] iter = 0720, loss = 65.5441
[2024-05-21 13:05:14] iter = 0730, loss = 65.4403
[2024-05-21 13:05:15] iter = 0740, loss = 66.7980
[2024-05-21 13:05:16] iter = 0750, loss = 65.6795
[2024-05-21 13:05:16] iter = 0760, loss = 57.5433
[2024-05-21 13:05:17] iter = 0770, loss = 67.8921
[2024-05-21 13:05:17] iter = 0780, loss = 64.2650
[2024-05-21 13:05:18] iter = 0790, loss = 60.3822
[2024-05-21 13:05:20] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.014742, train acc = 1.0000 train oa = 1.0000, test acc = 0.2510 test oa = 0.2076
Evaluate 1, mean = 0.2510 std = 0.0000
-------------------------
[2024-05-21 13:05:20] iter = 0800, loss = 62.2097
[2024-05-21 13:05:21] iter = 0810, loss = 55.8074
[2024-05-21 13:05:22] iter = 0820, loss = 56.9998
[2024-05-21 13:05:22] iter = 0830, loss = 68.9366
[2024-05-21 13:05:23] iter = 0840, loss = 61.1142
[2024-05-21 13:05:23] iter = 0850, loss = 68.7070
[2024-05-21 13:05:24] iter = 0860, loss = 61.3357
[2024-05-21 13:05:24] iter = 0870, loss = 64.7666
[2024-05-21 13:05:25] iter = 0880, loss = 63.2129
[2024-05-21 13:05:26] iter = 0890, loss = 57.9976
[2024-05-21 13:14:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.072251, train acc = 0.9200 train oa = 0.9200, test acc = 0.3219 test oa = 0.3062
Evaluate 1, mean = 0.3219 std = 0.0000
-------------------------
[2024-05-21 13:05:28] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.023591, train acc = 1.0000 train oa = 1.0000, test acc = 0.2376 test oa = 0.2042
Evaluate 1, mean = 0.2376 std = 0.0000
-------------------------
[2024-05-21 13:05:28] iter = 0900, loss = 61.1413
[2024-05-21 13:05:29] iter = 0910, loss = 62.7139
[2024-05-21 13:05:29] iter = 0920, loss = 66.8215
[2024-05-21 13:05:30] iter = 0930, loss = 63.9726
[2024-05-21 13:05:30] iter = 0940, loss = 64.8359
[2024-05-21 13:05:31] iter = 0950, loss = 64.4024
[2024-05-21 13:05:32] iter = 0960, loss = 61.1045
[2024-05-21 13:05:32] iter = 0970, loss = 60.9609
[2024-05-21 13:05:33] iter = 0980, loss = 60.6944
[2024-05-21 13:05:33] iter = 0990, loss = 56.2856
[2024-05-21 13:05:36] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.021341, train acc = 1.0000 train oa = 1.0000, test acc = 0.2413 test oa = 0.2336
Evaluate 1, mean = 0.2413 std = 0.0000
-------------------------
[2024-05-21 13:05:36] iter = 1000, loss = 62.2637
[2024-05-21 13:14:17] iter = 0920, loss = 52.2884

================== Exp 0 ==================
 
[2024-05-21 13:05:59] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000180, train acc = 1.0000 train oa = 1.0000, test acc = 0.0525 test oa = 0.0467
Evaluate 1, mean = 0.0525 std = 0.0000
-------------------------
[2024-05-21 13:05:59] iter = 0000, loss = 1177.0352
[2024-05-21 13:06:00] iter = 0010, loss = 167.4869
[2024-05-21 13:06:01] iter = 0020, loss = 116.9925
[2024-05-21 13:06:01] iter = 0030, loss = 103.6865
[2024-05-21 13:06:02] iter = 0040, loss = 81.7581
[2024-05-21 13:06:03] iter = 0050, loss = 72.5858
[2024-05-21 13:06:03] iter = 0060, loss = 74.6831
[2024-05-21 13:06:04] iter = 0070, loss = 74.3987
[2024-05-21 13:06:05] iter = 0080, loss = 67.6732
[2024-05-21 13:06:05] iter = 0090, loss = 68.4651
[2024-05-21 13:06:08] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024224, train acc = 1.0000 train oa = 1.0000, test acc = 0.1986 test oa = 0.1817
Evaluate 1, mean = 0.1986 std = 0.0000
-------------------------
[2024-05-21 13:06:08] iter = 0100, loss = 73.1184
[2024-05-21 13:06:09] iter = 0110, loss = 72.7279
[2024-05-21 13:06:09] iter = 0120, loss = 70.5538
[2024-05-21 13:06:10] iter = 0130, loss = 61.6921
[2024-05-21 13:06:11] iter = 0140, loss = 67.5135
[2024-05-21 13:06:11] iter = 0150, loss = 66.5149
[2024-05-21 13:06:12] iter = 0160, loss = 69.1357
[2024-05-21 13:06:12] iter = 0170, loss = 64.4022
[2024-05-21 13:06:13] iter = 0180, loss = 66.8053
[2024-05-21 13:06:14] iter = 0190, loss = 64.7770
[2024-05-21 13:06:16] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.034520, train acc = 1.0000 train oa = 1.0000, test acc = 0.0846 test oa = 0.0865
Evaluate 1, mean = 0.0846 std = 0.0000
-------------------------
[2024-05-21 13:06:16] iter = 0200, loss = 66.2195
[2024-05-21 13:06:17] iter = 0210, loss = 73.7517
[2024-05-21 13:06:18] iter = 0220, loss = 59.1717
[2024-05-21 13:06:18] iter = 0230, loss = 71.4879
[2024-05-21 13:06:19] iter = 0240, loss = 64.8323
[2024-05-21 13:06:20] iter = 0250, loss = 63.5487
[2024-05-21 13:06:20] iter = 0260, loss = 61.2956
[2024-05-21 13:06:21] iter = 0270, loss = 65.0493
[2024-05-21 13:06:22] iter = 0280, loss = 67.7009
[2024-05-21 13:06:22] iter = 0290, loss = 64.9611
[2024-05-21 13:06:25] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.017739, train acc = 1.0000 train oa = 1.0000, test acc = 0.2617 test oa = 0.2405
Evaluate 1, mean = 0.2617 std = 0.0000
-------------------------
[2024-05-21 13:06:25] iter = 0300, loss = 55.6911
[2024-05-21 13:06:26] iter = 0310, loss = 66.5764
[2024-05-21 13:06:26] iter = 0320, loss = 68.2045
[2024-05-21 13:06:27] iter = 0330, loss = 77.0253
[2024-05-21 13:06:27] iter = 0340, loss = 67.8962
[2024-05-21 13:06:28] iter = 0350, loss = 68.4909
[2024-05-21 13:06:29] iter = 0360, loss = 64.4736
[2024-05-21 13:06:29] iter = 0370, loss = 66.2737
[2024-05-21 13:06:30] iter = 0380, loss = 64.7068
[2024-05-21 13:06:31] iter = 0390, loss = 65.7154
[2024-05-21 13:15:09] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.024024, train acc = 1.0000 train oa = 1.0000, test acc = 0.3031 test oa = 0.3045
[2024-05-21 13:06:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.033595, train acc = 1.0000 train oa = 1.0000, test acc = 0.1956 test oa = 0.1903
Evaluate 1, mean = 0.1956 std = 0.0000
-------------------------
[2024-05-21 13:06:33] iter = 0400, loss = 66.6189
[2024-05-21 13:06:34] iter = 0410, loss = 59.6175
[2024-05-21 13:06:34] iter = 0420, loss = 62.6531
[2024-05-21 13:15:12] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.032364, train acc = 1.0000 train oa = 1.0000, test acc = 0.2903 test oa = 0.2976
[2024-05-21 13:06:35] iter = 0430, loss = 60.0222
[2024-05-21 13:06:36] iter = 0440, loss = 57.7672
[2024-05-21 13:06:36] iter = 0450, loss = 65.2078
[2024-05-21 13:06:37] iter = 0460, loss = 61.8421
[2024-05-21 13:15:15] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.045361, train acc = 1.0000 train oa = 1.0000, test acc = 0.2685 test oa = 0.2439
[2024-05-21 13:06:38] iter = 0470, loss = 57.7296
[2024-05-21 13:06:38] iter = 0480, loss = 62.5644
[2024-05-21 13:06:39] iter = 0490, loss = 58.6772
[2024-05-21 13:06:41] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.059320, train acc = 1.0000 train oa = 1.0000, test acc = 0.1940 test oa = 0.1869
Evaluate 1, mean = 0.1940 std = 0.0000
-------------------------
[2024-05-21 13:06:41] iter = 0500, loss = 58.1354
[2024-05-21 13:06:42] iter = 0510, loss = 60.1415
[2024-05-21 13:06:43] iter = 0520, loss = 60.5913
[2024-05-21 13:06:43] iter = 0530, loss = 60.0884
[2024-05-21 13:06:44] iter = 0540, loss = 61.5958
[2024-05-21 13:06:45] iter = 0550, loss = 60.4339
[2024-05-21 13:06:45] iter = 0560, loss = 65.5914
[2024-05-21 13:06:46] iter = 0570, loss = 65.1853
[2024-05-21 13:06:47] iter = 0580, loss = 56.9899
[2024-05-21 13:06:47] iter = 0590, loss = 57.1303
[2024-05-21 13:06:50] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.044577, train acc = 1.0000 train oa = 1.0000, test acc = 0.2795 test oa = 0.2353
Evaluate 1, mean = 0.2795 std = 0.0000
-------------------------
[2024-05-21 13:06:50] iter = 0600, loss = 62.4065
[2024-05-21 13:06:50] iter = 0610, loss = 58.3233
[2024-05-21 13:06:51] iter = 0620, loss = 64.0408
[2024-05-21 13:06:52] iter = 0630, loss = 57.8239
[2024-05-21 13:06:52] iter = 0640, loss = 55.8997
[2024-05-21 13:06:53] iter = 0650, loss = 58.4414
[2024-05-21 13:06:53] iter = 0660, loss = 59.0814
[2024-05-21 13:06:54] iter = 0670, loss = 58.6831
[2024-05-21 13:06:55] iter = 0680, loss = 62.0405
[2024-05-21 13:06:55] iter = 0690, loss = 55.4896
[2024-05-21 13:06:58] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.030436, train acc = 1.0000 train oa = 1.0000, test acc = 0.3046 test oa = 0.2872
Evaluate 1, mean = 0.3046 std = 0.0000
-------------------------
[2024-05-21 13:06:58] iter = 0700, loss = 59.6177
[2024-05-21 13:06:59] iter = 0710, loss = 60.0562
[2024-05-21 13:06:59] iter = 0720, loss = 59.3212
[2024-05-21 13:07:00] iter = 0730, loss = 57.1099
[2024-05-21 13:07:01] iter = 0740, loss = 63.1119
[2024-05-21 13:07:01] iter = 0750, loss = 59.6852
[2024-05-21 13:07:02] iter = 0760, loss = 59.5036
[2024-05-21 13:07:03] iter = 0770, loss = 65.5038
[2024-05-21 13:07:03] iter = 0780, loss = 63.9815
[2024-05-21 13:07:04] iter = 0790, loss = 56.6060
[2024-05-21 13:07:06] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.038324, train acc = 1.0000 train oa = 1.0000, test acc = 0.2894 test oa = 0.2612
Evaluate 1, mean = 0.2894 std = 0.0000
-------------------------
[2024-05-21 13:07:06] iter = 0800, loss = 60.6969
[2024-05-21 13:07:07] iter = 0810, loss = 57.1979
[2024-05-21 13:07:08] iter = 0820, loss = 58.7402
[2024-05-21 13:07:08] iter = 0830, loss = 64.4389
[2024-05-21 13:07:09] iter = 0840, loss = 59.3826
[2024-05-21 13:07:10] iter = 0850, loss = 59.3776
[2024-05-21 13:07:10] iter = 0860, loss = 58.7285
[2024-05-21 13:07:11] iter = 0870, loss = 64.8948
[2024-05-21 13:07:12] iter = 0880, loss = 57.4739
[2024-05-21 13:07:12] iter = 0890, loss = 55.9527
[2024-05-21 13:07:15] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.036439, train acc = 1.0000 train oa = 1.0000, test acc = 0.3241 test oa = 0.2855
Evaluate 1, mean = 0.3241 std = 0.0000
-------------------------
[2024-05-21 13:07:15] iter = 0900, loss = 56.3857
[2024-05-21 13:07:16] iter = 0910, loss = 59.9496
[2024-05-21 13:07:16] iter = 0920, loss = 54.8271
[2024-05-21 13:07:17] iter = 0930, loss = 59.5221
[2024-05-21 13:07:17] iter = 0940, loss = 60.8186
[2024-05-21 13:07:18] iter = 0950, loss = 65.2700
[2024-05-21 13:07:19] iter = 0960, loss = 57.7319
[2024-05-21 13:07:19] iter = 0970, loss = 53.7289
[2024-05-21 13:07:20] iter = 0980, loss = 63.0074
[2024-05-21 13:07:21] iter = 0990, loss = 58.7667
[2024-05-21 13:07:23] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.064930, train acc = 1.0000 train oa = 1.0000, test acc = 0.2958 test oa = 0.2336
Evaluate 1, mean = 0.2958 std = 0.0000
-------------------------
[2024-05-21 13:07:23] iter = 1000, loss = 54.4250
[2024-05-21 13:16:18] iter = 0930, loss = 54.0767

================== Exp 0 ==================
 
[2024-05-21 13:07:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000178, train acc = 1.0000 train oa = 1.0000, test acc = 0.0570 test oa = 0.0398
Evaluate 1, mean = 0.0570 std = 0.0000
-------------------------
[2024-05-21 13:07:54] iter = 0000, loss = 522.7395
[2024-05-21 13:07:55] iter = 0010, loss = 119.4990
[2024-05-21 13:07:55] iter = 0020, loss = 82.0532
[2024-05-21 13:07:56] iter = 0030, loss = 77.0301
[2024-05-21 13:07:56] iter = 0040, loss = 70.9156
[2024-05-21 13:07:57] iter = 0050, loss = 67.4932
[2024-05-21 13:07:58] iter = 0060, loss = 67.1475
[2024-05-21 13:07:58] iter = 0070, loss = 66.0580
[2024-05-21 13:07:59] iter = 0080, loss = 63.1841
[2024-05-21 13:07:59] iter = 0090, loss = 67.3324
[2024-05-21 13:08:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.041180, train acc = 1.0000 train oa = 1.0000, test acc = 0.2232 test oa = 0.1972
Evaluate 1, mean = 0.2232 std = 0.0000
-------------------------
[2024-05-21 13:08:02] iter = 0100, loss = 66.2740
[2024-05-21 13:08:02] iter = 0110, loss = 68.4194
[2024-05-21 13:08:03] iter = 0120, loss = 66.2033
[2024-05-21 13:08:04] iter = 0130, loss = 57.7546
[2024-05-21 13:08:04] iter = 0140, loss = 56.5965
[2024-05-21 13:08:05] iter = 0150, loss = 65.0418
[2024-05-21 13:08:05] iter = 0160, loss = 63.3767
[2024-05-21 13:08:06] iter = 0170, loss = 64.2400
[2024-05-21 13:08:07] iter = 0180, loss = 65.5674
[2024-05-21 13:08:07] iter = 0190, loss = 65.1675
[2024-05-21 13:08:10] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.033197, train acc = 1.0000 train oa = 1.0000, test acc = 0.2263 test oa = 0.1903
Evaluate 1, mean = 0.2263 std = 0.0000
-------------------------
[2024-05-21 13:08:10] iter = 0200, loss = 64.0636
[2024-05-21 13:08:10] iter = 0210, loss = 66.0578
[2024-05-21 13:08:11] iter = 0220, loss = 56.5853
[2024-05-21 13:08:11] iter = 0230, loss = 58.7031
[2024-05-21 13:08:12] iter = 0240, loss = 62.1040
[2024-05-21 13:08:13] iter = 0250, loss = 61.4566
[2024-05-21 13:08:13] iter = 0260, loss = 61.5965
[2024-05-21 13:08:14] iter = 0270, loss = 63.5727
[2024-05-21 13:08:14] iter = 0280, loss = 58.1014
[2024-05-21 13:08:15] iter = 0290, loss = 62.0385
[2024-05-21 13:08:17] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.063776, train acc = 1.0000 train oa = 1.0000, test acc = 0.2766 test oa = 0.2076
Evaluate 1, mean = 0.2766 std = 0.0000
-------------------------
[2024-05-21 13:08:17] iter = 0300, loss = 63.8713
[2024-05-21 13:08:18] iter = 0310, loss = 59.8577
[2024-05-21 13:08:19] iter = 0320, loss = 61.9705
[2024-05-21 13:08:19] iter = 0330, loss = 64.6701
[2024-05-21 13:08:20] iter = 0340, loss = 62.7308
[2024-05-21 13:08:20] iter = 0350, loss = 63.2806
[2024-05-21 13:08:21] iter = 0360, loss = 65.4033
[2024-05-21 13:08:21] iter = 0370, loss = 60.9541
[2024-05-21 13:08:22] iter = 0380, loss = 51.8180
[2024-05-21 13:08:23] iter = 0390, loss = 63.6567
[2024-05-21 13:08:25] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.020472, train acc = 1.0000 train oa = 1.0000, test acc = 0.2517 test oa = 0.2215
Evaluate 1, mean = 0.2517 std = 0.0000
-------------------------
[2024-05-21 13:08:25] iter = 0400, loss = 58.8308
[2024-05-21 13:08:26] iter = 0410, loss = 64.9448
[2024-05-21 13:08:26] iter = 0420, loss = 64.5258
[2024-05-21 13:08:27] iter = 0430, loss = 63.4599
[2024-05-21 13:08:27] iter = 0440, loss = 52.7048
[2024-05-21 13:08:28] iter = 0450, loss = 60.7100
[2024-05-21 13:08:28] iter = 0460, loss = 68.0746
[2024-05-21 13:08:29] iter = 0470, loss = 61.1996
[2024-05-21 13:08:30] iter = 0480, loss = 59.6568
[2024-05-21 13:08:30] iter = 0490, loss = 67.7753
[2024-05-21 13:08:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.047052, train acc = 1.0000 train oa = 1.0000, test acc = 0.2861 test oa = 0.2612
Evaluate 1, mean = 0.2861 std = 0.0000
-------------------------
[2024-05-21 13:08:33] iter = 0500, loss = 61.6540
[2024-05-21 13:08:33] iter = 0510, loss = 57.5229
[2024-05-21 13:08:34] iter = 0520, loss = 60.0621
[2024-05-21 13:08:35] iter = 0530, loss = 61.7590
[2024-05-21 13:08:35] iter = 0540, loss = 65.8253
[2024-05-21 13:08:36] iter = 0550, loss = 60.9975
[2024-05-21 13:08:36] iter = 0560, loss = 61.8435
[2024-05-21 13:08:37] iter = 0570, loss = 64.1558
[2024-05-21 13:08:38] iter = 0580, loss = 58.0255
[2024-05-21 13:08:38] iter = 0590, loss = 60.1990
[2024-05-21 13:08:41] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.021038, train acc = 1.0000 train oa = 1.0000, test acc = 0.2852 test oa = 0.2526
Evaluate 1, mean = 0.2852 std = 0.0000
-------------------------
[2024-05-21 13:08:41] iter = 0600, loss = 55.3047
[2024-05-21 13:08:41] iter = 0610, loss = 53.9807
[2024-05-21 13:08:42] iter = 0620, loss = 61.0346
[2024-05-21 13:08:42] iter = 0630, loss = 60.3876
[2024-05-21 13:08:43] iter = 0640, loss = 59.6787
[2024-05-21 13:08:44] iter = 0650, loss = 63.4384
[2024-05-21 13:08:44] iter = 0660, loss = 55.7038
[2024-05-21 13:08:45] iter = 0670, loss = 63.8346
[2024-05-21 13:08:45] iter = 0680, loss = 51.4674
[2024-05-21 13:08:46] iter = 0690, loss = 66.9748
[2024-05-21 13:08:48] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.048340, train acc = 1.0000 train oa = 1.0000, test acc = 0.2571 test oa = 0.2024
Evaluate 1, mean = 0.2571 std = 0.0000
-------------------------
[2024-05-21 13:08:49] iter = 0700, loss = 66.6545
[2024-05-21 13:08:49] iter = 0710, loss = 68.8658
[2024-05-21 13:08:50] iter = 0720, loss = 60.7644
[2024-05-21 13:08:50] iter = 0730, loss = 59.9194
[2024-05-21 13:08:51] iter = 0740, loss = 60.9909
[2024-05-21 13:08:51] iter = 0750, loss = 62.4742
[2024-05-21 13:08:52] iter = 0760, loss = 54.1051
[2024-05-21 13:08:53] iter = 0770, loss = 64.4356
[2024-05-21 13:08:53] iter = 0780, loss = 59.8579
[2024-05-21 13:08:54] iter = 0790, loss = 57.2720
[2024-05-21 13:08:56] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.037800, train acc = 1.0000 train oa = 1.0000, test acc = 0.2702 test oa = 0.2388
Evaluate 1, mean = 0.2702 std = 0.0000
-------------------------
[2024-05-21 13:08:56] iter = 0800, loss = 58.9521
[2024-05-21 13:08:57] iter = 0810, loss = 51.7358
[2024-05-21 13:08:57] iter = 0820, loss = 54.1623
[2024-05-21 13:08:58] iter = 0830, loss = 67.0834
[2024-05-21 13:08:59] iter = 0840, loss = 57.9440
[2024-05-21 13:08:59] iter = 0850, loss = 63.0656
[2024-05-21 13:09:00] iter = 0860, loss = 57.7123
[2024-05-21 13:09:00] iter = 0870, loss = 60.6740
[2024-05-21 13:09:01] iter = 0880, loss = 60.6321
[2024-05-21 13:09:01] iter = 0890, loss = 55.3766
[2024-05-21 13:09:04] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.050470, train acc = 1.0000 train oa = 1.0000, test acc = 0.2538 test oa = 0.2301
Evaluate 1, mean = 0.2538 std = 0.0000
-------------------------
[2024-05-21 13:09:04] iter = 0900, loss = 59.9664
[2024-05-21 13:09:05] iter = 0910, loss = 60.9312
[2024-05-21 13:09:05] iter = 0920, loss = 62.7300
[2024-05-21 13:09:06] iter = 0930, loss = 62.8802
[2024-05-21 13:09:06] iter = 0940, loss = 61.5248
[2024-05-21 13:09:07] iter = 0950, loss = 58.5117
[2024-05-21 13:09:08] iter = 0960, loss = 61.4901
[2024-05-21 13:09:08] iter = 0970, loss = 57.3075
[2024-05-21 13:09:09] iter = 0980, loss = 59.6132
[2024-05-21 13:09:09] iter = 0990, loss = 55.1193
[2024-05-21 13:09:12] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.042555, train acc = 1.0000 train oa = 1.0000, test acc = 0.2904 test oa = 0.2439
Evaluate 1, mean = 0.2904 std = 0.0000
-------------------------
[2024-05-21 13:09:12] iter = 1000, loss = 60.5423

================== Exp 0 ==================
 
[2024-05-21 13:09:30] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000176, train acc = 1.0000 train oa = 1.0000, test acc = 0.0548 test oa = 0.0554
Evaluate 1, mean = 0.0548 std = 0.0000
-------------------------
[2024-05-21 13:09:30] iter = 0000, loss = 1231.8674
[2024-05-21 13:09:31] iter = 0010, loss = 251.9246
[2024-05-21 13:09:31] iter = 0020, loss = 187.3183
[2024-05-21 13:09:32] iter = 0030, loss = 171.9649
[2024-05-21 13:09:33] iter = 0040, loss = 133.3252
[2024-05-21 13:09:33] iter = 0050, loss = 115.6341
[2024-05-21 13:09:34] iter = 0060, loss = 130.9261
[2024-05-21 13:18:12] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.070188, train acc = 0.8800 train oa = 0.8800, test acc = 0.3324 test oa = 0.3235
Evaluate 1, mean = 0.3324 std = 0.0000
-------------------------
[2024-05-21 13:09:35] iter = 0070, loss = 117.8369
[2024-05-21 13:09:35] iter = 0080, loss = 116.3375
[2024-05-21 13:09:36] iter = 0090, loss = 102.0210
[2024-05-21 13:09:39] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001555, train acc = 1.0000 train oa = 1.0000, test acc = 0.2107 test oa = 0.1955
Evaluate 1, mean = 0.2107 std = 0.0000
-------------------------
[2024-05-21 13:09:39] iter = 0100, loss = 113.5523
[2024-05-21 13:09:39] iter = 0110, loss = 108.9392
[2024-05-21 13:09:40] iter = 0120, loss = 106.1262
[2024-05-21 13:09:41] iter = 0130, loss = 92.8610
[2024-05-21 13:09:41] iter = 0140, loss = 102.1495
[2024-05-21 13:09:42] iter = 0150, loss = 96.8231
[2024-05-21 13:09:43] iter = 0160, loss = 97.7854
[2024-05-21 13:09:43] iter = 0170, loss = 90.2677
[2024-05-21 13:09:44] iter = 0180, loss = 96.5433
[2024-05-21 13:09:44] iter = 0190, loss = 89.3375
[2024-05-21 13:18:24] iter = 0940, loss = 55.0020
[2024-05-21 13:09:47] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001313, train acc = 1.0000 train oa = 1.0000, test acc = 0.2205 test oa = 0.2682
Evaluate 1, mean = 0.2205 std = 0.0000
-------------------------
[2024-05-21 13:09:47] iter = 0200, loss = 94.2003
[2024-05-21 13:09:48] iter = 0210, loss = 103.2782
[2024-05-21 13:09:48] iter = 0220, loss = 82.4833
[2024-05-21 13:09:49] iter = 0230, loss = 93.9298
[2024-05-21 13:09:50] iter = 0240, loss = 92.8229
[2024-05-21 13:09:50] iter = 0250, loss = 79.6831
[2024-05-21 13:09:51] iter = 0260, loss = 78.6924
[2024-05-21 13:09:51] iter = 0270, loss = 83.3100
[2024-05-21 13:09:52] iter = 0280, loss = 85.5624
[2024-05-21 13:09:53] iter = 0290, loss = 86.0970
[2024-05-21 13:09:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.010019, train acc = 1.0000 train oa = 1.0000, test acc = 0.1291 test oa = 0.1280
Evaluate 1, mean = 0.1291 std = 0.0000
-------------------------
[2024-05-21 13:09:55] iter = 0300, loss = 73.4420
[2024-05-21 13:09:56] iter = 0310, loss = 88.2041
[2024-05-21 13:09:57] iter = 0320, loss = 88.3712
[2024-05-21 13:09:57] iter = 0330, loss = 99.6798
[2024-05-21 13:09:58] iter = 0340, loss = 86.8409
[2024-05-21 13:09:58] iter = 0350, loss = 84.6239
[2024-05-21 13:09:59] iter = 0360, loss = 87.2556
[2024-05-21 13:10:00] iter = 0370, loss = 82.3701
[2024-05-21 13:10:00] iter = 0380, loss = 81.5629
[2024-05-21 13:10:01] iter = 0390, loss = 86.5291
[2024-05-21 13:10:03] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.008042, train acc = 1.0000 train oa = 1.0000, test acc = 0.2382 test oa = 0.1903
Evaluate 1, mean = 0.2382 std = 0.0000
-------------------------
[2024-05-21 13:10:04] iter = 0400, loss = 84.3294
[2024-05-21 13:10:04] iter = 0410, loss = 77.5018
[2024-05-21 13:10:05] iter = 0420, loss = 82.8945
[2024-05-21 13:10:05] iter = 0430, loss = 75.5485
[2024-05-21 13:10:06] iter = 0440, loss = 75.1681
[2024-05-21 13:10:07] iter = 0450, loss = 80.4096
[2024-05-21 13:10:07] iter = 0460, loss = 73.8341
[2024-05-21 13:10:08] iter = 0470, loss = 70.4570
[2024-05-21 13:10:09] iter = 0480, loss = 76.9287
[2024-05-21 13:10:09] iter = 0490, loss = 70.3084
[2024-05-21 13:10:12] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.011107, train acc = 1.0000 train oa = 1.0000, test acc = 0.2392 test oa = 0.1955
Evaluate 1, mean = 0.2392 std = 0.0000
-------------------------
[2024-05-21 13:10:12] iter = 0500, loss = 75.0183
[2024-05-21 13:10:12] iter = 0510, loss = 76.8371
[2024-05-21 13:10:13] iter = 0520, loss = 77.6747
[2024-05-21 13:10:14] iter = 0530, loss = 77.4821
[2024-05-21 13:10:14] iter = 0540, loss = 75.1909
[2024-05-21 13:10:15] iter = 0550, loss = 71.8431
[2024-05-21 13:10:16] iter = 0560, loss = 80.8226
[2024-05-21 13:10:16] iter = 0570, loss = 75.0056
[2024-05-21 13:10:17] iter = 0580, loss = 70.8136
[2024-05-21 13:10:18] iter = 0590, loss = 73.2608
[2024-05-21 13:10:20] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.009589, train acc = 1.0000 train oa = 1.0000, test acc = 0.2375 test oa = 0.1920
Evaluate 1, mean = 0.2375 std = 0.0000
-------------------------
[2024-05-21 13:10:20] iter = 0600, loss = 71.4076
[2024-05-21 13:10:21] iter = 0610, loss = 70.2103
[2024-05-21 13:10:22] iter = 0620, loss = 76.2226
[2024-05-21 13:10:22] iter = 0630, loss = 69.9567
[2024-05-21 13:10:23] iter = 0640, loss = 66.6472
[2024-05-21 13:10:24] iter = 0650, loss = 70.8163
[2024-05-21 13:10:24] iter = 0660, loss = 72.3166
[2024-05-21 13:10:25] iter = 0670, loss = 67.2762
[2024-05-21 13:10:26] iter = 0680, loss = 76.0335
[2024-05-21 13:10:26] iter = 0690, loss = 66.5203
[2024-05-21 13:10:29] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.014675, train acc = 1.0000 train oa = 1.0000, test acc = 0.2912 test oa = 0.2595
Evaluate 1, mean = 0.2912 std = 0.0000
-------------------------
[2024-05-21 13:10:29] iter = 0700, loss = 69.5950
[2024-05-21 13:10:30] iter = 0710, loss = 72.3560
[2024-05-21 13:10:30] iter = 0720, loss = 68.9148
[2024-05-21 13:10:31] iter = 0730, loss = 67.4653
[2024-05-21 13:10:31] iter = 0740, loss = 74.3014
[2024-05-21 13:10:32] iter = 0750, loss = 68.2488
[2024-05-21 13:10:33] iter = 0760, loss = 69.4134
[2024-05-21 13:10:33] iter = 0770, loss = 74.3155
[2024-05-21 13:10:34] iter = 0780, loss = 72.2678
[2024-05-21 13:10:35] iter = 0790, loss = 68.4036
[2024-05-21 13:10:37] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.023781, train acc = 1.0000 train oa = 1.0000, test acc = 0.3016 test oa = 0.2837
Evaluate 1, mean = 0.3016 std = 0.0000
-------------------------
[2024-05-21 13:10:37] iter = 0800, loss = 70.8099
[2024-05-21 13:10:38] iter = 0810, loss = 65.9933
[2024-05-21 13:10:39] iter = 0820, loss = 70.0149
[2024-05-21 13:10:39] iter = 0830, loss = 73.9818
[2024-05-21 13:10:40] iter = 0840, loss = 66.8745
[2024-05-21 13:10:41] iter = 0850, loss = 68.3718
[2024-05-21 13:10:41] iter = 0860, loss = 68.6287
[2024-05-21 13:10:42] iter = 0870, loss = 76.4780
[2024-05-21 13:10:43] iter = 0880, loss = 66.0800
[2024-05-21 13:10:43] iter = 0890, loss = 63.7008
[2024-05-21 13:10:46] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.026731, train acc = 1.0000 train oa = 1.0000, test acc = 0.2975 test oa = 0.2993
Evaluate 1, mean = 0.2975 std = 0.0000
-------------------------
[2024-05-21 13:10:46] iter = 0900, loss = 65.5594
[2024-05-21 13:10:46] iter = 0910, loss = 68.7320
[2024-05-21 13:10:47] iter = 0920, loss = 63.2562
[2024-05-21 13:10:48] iter = 0930, loss = 68.4696
[2024-05-21 13:10:48] iter = 0940, loss = 69.2085
[2024-05-21 13:10:49] iter = 0950, loss = 73.9640
[2024-05-21 13:10:50] iter = 0960, loss = 65.5083
[2024-05-21 13:10:50] iter = 0970, loss = 63.6091
[2024-05-21 13:10:51] iter = 0980, loss = 72.2566
[2024-05-21 13:10:52] iter = 0990, loss = 65.4917
[2024-05-21 13:10:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024776, train acc = 1.0000 train oa = 1.0000, test acc = 0.2298 test oa = 0.2024
Evaluate 1, mean = 0.2298 std = 0.0000
-------------------------
[2024-05-21 13:10:54] iter = 1000, loss = 60.3715

================== Exp 0 ==================
 
[2024-05-21 13:11:13] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000336, train acc = 1.0000 train oa = 1.0000, test acc = 0.0922 test oa = 0.1055
Evaluate 1, mean = 0.0922 std = 0.0000
-------------------------
[2024-05-21 13:11:13] iter = 0000, loss = 2183.2773
[2024-05-21 13:11:13] iter = 0010, loss = 675.2224
[2024-05-21 13:11:14] iter = 0020, loss = 574.0903
[2024-05-21 13:11:15] iter = 0030, loss = 544.1489
[2024-05-21 13:11:15] iter = 0040, loss = 475.9970
[2024-05-21 13:11:16] iter = 0050, loss = 411.2908
[2024-05-21 13:11:17] iter = 0060, loss = 448.3637
[2024-05-21 13:11:17] iter = 0070, loss = 392.4021
[2024-05-21 13:11:18] iter = 0080, loss = 417.4314
[2024-05-21 13:11:19] iter = 0090, loss = 355.5633
[2024-05-21 13:11:21] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000220, train acc = 1.0000 train oa = 1.0000, test acc = 0.1005 test oa = 0.0727
Evaluate 1, mean = 0.1005 std = 0.0000
-------------------------
[2024-05-21 13:11:21] iter = 0100, loss = 359.3929
[2024-05-21 13:11:22] iter = 0110, loss = 316.7682
[2024-05-21 13:11:22] iter = 0120, loss = 345.2389
[2024-05-21 13:11:23] iter = 0130, loss = 324.0986
[2024-05-21 13:11:24] iter = 0140, loss = 271.3278
[2024-05-21 13:11:24] iter = 0150, loss = 255.1306
[2024-05-21 13:11:25] iter = 0160, loss = 274.7708
[2024-05-21 13:11:25] iter = 0170, loss = 253.0042
[2024-05-21 13:11:26] iter = 0180, loss = 240.8120
[2024-05-21 13:11:27] iter = 0190, loss = 203.3073
[2024-05-21 13:11:29] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000144, train acc = 1.0000 train oa = 1.0000, test acc = 0.1773 test oa = 0.1505
Evaluate 1, mean = 0.1773 std = 0.0000
-------------------------
[2024-05-21 13:11:29] iter = 0200, loss = 238.1433
[2024-05-21 13:11:30] iter = 0210, loss = 217.7941
[2024-05-21 13:11:31] iter = 0220, loss = 204.5504
[2024-05-21 13:11:31] iter = 0230, loss = 201.0124
[2024-05-21 13:11:32] iter = 0240, loss = 204.0177
[2024-05-21 13:11:33] iter = 0250, loss = 202.2758
[2024-05-21 13:11:33] iter = 0260, loss = 197.9504
[2024-05-21 13:11:34] iter = 0270, loss = 173.1426
[2024-05-21 13:11:34] iter = 0280, loss = 178.6557
[2024-05-21 13:11:35] iter = 0290, loss = 168.4735
[2024-05-21 13:11:38] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000109, train acc = 1.0000 train oa = 1.0000, test acc = 0.1975 test oa = 0.1972
Evaluate 1, mean = 0.1975 std = 0.0000
-------------------------
[2024-05-21 13:11:38] iter = 0300, loss = 156.3710
[2024-05-21 13:11:38] iter = 0310, loss = 169.3654
[2024-05-21 13:11:39] iter = 0320, loss = 170.3290
[2024-05-21 13:11:40] iter = 0330, loss = 190.3912
[2024-05-21 13:11:40] iter = 0340, loss = 159.3893
[2024-05-21 13:11:41] iter = 0350, loss = 161.1857
[2024-05-21 13:11:42] iter = 0360, loss = 161.3192
[2024-05-21 13:11:42] iter = 0370, loss = 153.2533
[2024-05-21 13:11:43] iter = 0380, loss = 153.5822
[2024-05-21 13:20:21] iter = 0950, loss = 53.5646
[2024-05-21 13:11:43] iter = 0390, loss = 170.4709
[2024-05-21 13:11:46] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000060, train acc = 1.0000 train oa = 1.0000, test acc = 0.2062 test oa = 0.1522
Evaluate 1, mean = 0.2062 std = 0.0000
-------------------------
[2024-05-21 13:11:46] iter = 0400, loss = 165.7455
[2024-05-21 13:11:47] iter = 0410, loss = 146.8738
[2024-05-21 13:11:47] iter = 0420, loss = 142.4101
[2024-05-21 13:11:48] iter = 0430, loss = 145.4187
[2024-05-21 13:11:49] iter = 0440, loss = 137.1059
[2024-05-21 13:11:49] iter = 0450, loss = 141.3895
[2024-05-21 13:11:50] iter = 0460, loss = 140.2898
[2024-05-21 13:11:50] iter = 0470, loss = 133.4053
[2024-05-21 13:11:51] iter = 0480, loss = 139.7984
[2024-05-21 13:11:52] iter = 0490, loss = 126.2799
[2024-05-21 13:11:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000072, train acc = 1.0000 train oa = 1.0000, test acc = 0.2295 test oa = 0.2336
Evaluate 1, mean = 0.2295 std = 0.0000
-------------------------
[2024-05-21 13:11:54] iter = 0500, loss = 131.1922
[2024-05-21 13:11:55] iter = 0510, loss = 132.8819
[2024-05-21 13:11:56] iter = 0520, loss = 136.9885
[2024-05-21 13:11:56] iter = 0530, loss = 132.0636
[2024-05-21 13:11:57] iter = 0540, loss = 130.3132
[2024-05-21 13:11:57] iter = 0550, loss = 127.2817
[2024-05-21 13:11:58] iter = 0560, loss = 127.5063
[2024-05-21 13:11:59] iter = 0570, loss = 119.7790
[2024-05-21 13:11:59] iter = 0580, loss = 123.9831
[2024-05-21 13:12:00] iter = 0590, loss = 119.2971
[2024-05-21 13:12:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000588, train acc = 1.0000 train oa = 1.0000, test acc = 0.2043 test oa = 0.1696
Evaluate 1, mean = 0.2043 std = 0.0000
-------------------------
[2024-05-21 13:12:03] iter = 0600, loss = 122.6736
[2024-05-21 13:12:03] iter = 0610, loss = 121.6087
[2024-05-21 13:12:04] iter = 0620, loss = 110.3987
[2024-05-21 13:12:04] iter = 0630, loss = 113.1437
[2024-05-21 13:12:05] iter = 0640, loss = 110.5274
[2024-05-21 13:12:06] iter = 0650, loss = 110.4079
[2024-05-21 13:12:06] iter = 0660, loss = 114.4241
[2024-05-21 13:12:07] iter = 0670, loss = 111.4139
[2024-05-21 13:12:08] iter = 0680, loss = 110.3952
[2024-05-21 13:12:08] iter = 0690, loss = 112.8052
[2024-05-21 13:12:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001115, train acc = 1.0000 train oa = 1.0000, test acc = 0.2603 test oa = 0.2370
Evaluate 1, mean = 0.2603 std = 0.0000
-------------------------
[2024-05-21 13:12:11] iter = 0700, loss = 104.8746
[2024-05-21 13:12:12] iter = 0710, loss = 109.5375
[2024-05-21 13:12:12] iter = 0720, loss = 103.1396
[2024-05-21 13:12:13] iter = 0730, loss = 97.8880
[2024-05-21 13:12:14] iter = 0740, loss = 113.4078
[2024-05-21 13:12:14] iter = 0750, loss = 106.5742
[2024-05-21 13:12:15] iter = 0760, loss = 101.2666
[2024-05-21 13:12:16] iter = 0770, loss = 107.7340
[2024-05-21 13:12:16] iter = 0780, loss = 103.3087
[2024-05-21 13:12:17] iter = 0790, loss = 118.7527
[2024-05-21 13:12:19] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000862, train acc = 1.0000 train oa = 1.0000, test acc = 0.2228 test oa = 0.2163
Evaluate 1, mean = 0.2228 std = 0.0000
-------------------------
[2024-05-21 13:12:19] iter = 0800, loss = 102.8194
[2024-05-21 13:12:20] iter = 0810, loss = 99.0390
[2024-05-21 13:12:21] iter = 0820, loss = 104.2573
[2024-05-21 13:12:21] iter = 0830, loss = 106.1142
[2024-05-21 13:12:22] iter = 0840, loss = 94.1475
[2024-05-21 13:12:23] iter = 0850, loss = 96.2453
[2024-05-21 13:12:23] iter = 0860, loss = 95.5783
[2024-05-21 13:12:24] iter = 0870, loss = 110.0527
[2024-05-21 13:12:24] iter = 0880, loss = 96.6023
[2024-05-21 13:12:25] iter = 0890, loss = 91.6969
[2024-05-21 13:12:28] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.003307, train acc = 1.0000 train oa = 1.0000, test acc = 0.2617 test oa = 0.2370
Evaluate 1, mean = 0.2617 std = 0.0000
-------------------------
[2024-05-21 13:12:28] iter = 0900, loss = 93.2510
[2024-05-21 13:12:28] iter = 0910, loss = 93.5676
[2024-05-21 13:12:29] iter = 0920, loss = 92.8075
[2024-05-21 13:12:30] iter = 0930, loss = 90.0381
[2024-05-21 13:12:30] iter = 0940, loss = 94.1799
[2024-05-21 13:12:31] iter = 0950, loss = 104.1505
[2024-05-21 13:12:32] iter = 0960, loss = 92.9264
[2024-05-21 13:12:32] iter = 0970, loss = 81.9385
[2024-05-21 13:12:33] iter = 0980, loss = 92.4048
[2024-05-21 13:12:34] iter = 0990, loss = 87.8025
[2024-05-21 13:12:36] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.003451, train acc = 1.0000 train oa = 1.0000, test acc = 0.2486 test oa = 0.2232
Evaluate 1, mean = 0.2486 std = 0.0000
-------------------------
[2024-05-21 13:12:36] iter = 1000, loss = 83.2943

================== Exp 0 ==================
 
[2024-05-21 13:12:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000183, train acc = 1.0000 train oa = 1.0000, test acc = 0.0899 test oa = 0.0796
Evaluate 1, mean = 0.0899 std = 0.0000
-------------------------
[2024-05-21 13:12:55] iter = 0000, loss = 796.9383
[2024-05-21 13:12:55] iter = 0010, loss = 228.1622
[2024-05-21 13:12:56] iter = 0020, loss = 156.6722
[2024-05-21 13:12:56] iter = 0030, loss = 138.9366
[2024-05-21 13:12:57] iter = 0040, loss = 122.9261
[2024-05-21 13:12:57] iter = 0050, loss = 115.2093
[2024-05-21 13:12:58] iter = 0060, loss = 108.6384
[2024-05-21 13:12:59] iter = 0070, loss = 106.8645
[2024-05-21 13:12:59] iter = 0080, loss = 116.4939
[2024-05-21 13:13:00] iter = 0090, loss = 107.2252
[2024-05-21 13:13:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.002127, train acc = 1.0000 train oa = 1.0000, test acc = 0.2438 test oa = 0.2388
Evaluate 1, mean = 0.2438 std = 0.0000
-------------------------
[2024-05-21 13:13:02] iter = 0100, loss = 104.1684
[2024-05-21 13:13:03] iter = 0110, loss = 100.2088
[2024-05-21 13:13:03] iter = 0120, loss = 93.8041
[2024-05-21 13:13:04] iter = 0130, loss = 84.8571
[2024-05-21 13:13:05] iter = 0140, loss = 81.7955
[2024-05-21 13:13:05] iter = 0150, loss = 96.8600
[2024-05-21 13:13:06] iter = 0160, loss = 90.2695
[2024-05-21 13:13:06] iter = 0170, loss = 95.9149
[2024-05-21 13:13:07] iter = 0180, loss = 90.0730
[2024-05-21 13:13:08] iter = 0190, loss = 87.8135
[2024-05-21 13:13:10] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000872, train acc = 1.0000 train oa = 1.0000, test acc = 0.2257 test oa = 0.2111
Evaluate 1, mean = 0.2257 std = 0.0000
-------------------------
[2024-05-21 13:13:10] iter = 0200, loss = 86.8246
[2024-05-21 13:13:11] iter = 0210, loss = 82.0177
[2024-05-21 13:13:11] iter = 0220, loss = 77.8374
[2024-05-21 13:13:12] iter = 0230, loss = 76.5762
[2024-05-21 13:13:12] iter = 0240, loss = 77.7428
[2024-05-21 13:13:13] iter = 0250, loss = 76.0425
[2024-05-21 13:13:13] iter = 0260, loss = 76.1192
[2024-05-21 13:13:14] iter = 0270, loss = 80.2695
[2024-05-21 13:13:15] iter = 0280, loss = 76.4467
[2024-05-21 13:13:15] iter = 0290, loss = 75.4041
[2024-05-21 13:13:17] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001487, train acc = 1.0000 train oa = 1.0000, test acc = 0.2832 test oa = 0.2699
Evaluate 1, mean = 0.2832 std = 0.0000
-------------------------
[2024-05-21 13:13:18] iter = 0300, loss = 78.3565
[2024-05-21 13:13:18] iter = 0310, loss = 80.0041
[2024-05-21 13:13:19] iter = 0320, loss = 75.3444
[2024-05-21 13:13:19] iter = 0330, loss = 85.9710
[2024-05-21 13:13:20] iter = 0340, loss = 74.2758
[2024-05-21 13:13:20] iter = 0350, loss = 75.9807
[2024-05-21 13:13:21] iter = 0360, loss = 78.0296
[2024-05-21 13:13:22] iter = 0370, loss = 75.6466
[2024-05-21 13:13:22] iter = 0380, loss = 63.0186
[2024-05-21 13:13:23] iter = 0390, loss = 76.8803
[2024-05-21 13:13:25] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.019418, train acc = 1.0000 train oa = 1.0000, test acc = 0.2343 test oa = 0.2180
Evaluate 1, mean = 0.2343 std = 0.0000
-------------------------
[2024-05-21 13:13:25] iter = 0400, loss = 68.1188
[2024-05-21 13:13:26] iter = 0410, loss = 78.0549
[2024-05-21 13:13:27] iter = 0420, loss = 76.1431
[2024-05-21 13:13:27] iter = 0430, loss = 74.8929
[2024-05-21 13:13:28] iter = 0440, loss = 65.2597
[2024-05-21 13:13:28] iter = 0450, loss = 73.7909
[2024-05-21 13:13:29] iter = 0460, loss = 79.4318
[2024-05-21 13:13:30] iter = 0470, loss = 70.2945
[2024-05-21 13:13:30] iter = 0480, loss = 72.9087
[2024-05-21 13:13:31] iter = 0490, loss = 77.8552
[2024-05-21 13:13:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.009091, train acc = 1.0000 train oa = 1.0000, test acc = 0.2412 test oa = 0.2578
Evaluate 1, mean = 0.2412 std = 0.0000
-------------------------
[2024-05-21 13:13:33] iter = 0500, loss = 70.2411
[2024-05-21 13:13:34] iter = 0510, loss = 67.3146
[2024-05-21 13:13:35] iter = 0520, loss = 68.8451
[2024-05-21 13:13:35] iter = 0530, loss = 68.3202
[2024-05-21 13:13:36] iter = 0540, loss = 73.2137
[2024-05-21 13:13:36] iter = 0550, loss = 68.5243
[2024-05-21 13:13:37] iter = 0560, loss = 70.1855
[2024-05-21 13:13:38] iter = 0570, loss = 70.0739
[2024-05-21 13:13:38] iter = 0580, loss = 69.4395
[2024-05-21 13:22:16] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.017142, train acc = 0.8800 train oa = 0.8800, test acc = 0.3431 test oa = 0.3218
Evaluate 1, mean = 0.3431 std = 0.0000
-------------------------
[2024-05-21 13:13:39] iter = 0590, loss = 70.6708
[2024-05-21 13:13:41] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.011925, train acc = 1.0000 train oa = 1.0000, test acc = 0.2160 test oa = 0.2578
Evaluate 1, mean = 0.2160 std = 0.0000
-------------------------
[2024-05-21 13:13:41] iter = 0600, loss = 66.7545
[2024-05-21 13:13:42] iter = 0610, loss = 64.7786
[2024-05-21 13:13:43] iter = 0620, loss = 67.4530
[2024-05-21 13:13:43] iter = 0630, loss = 68.2429
[2024-05-21 13:13:44] iter = 0640, loss = 69.8399
[2024-05-21 13:13:44] iter = 0650, loss = 69.5999
[2024-05-21 13:13:45] iter = 0660, loss = 65.0498
[2024-05-21 13:13:45] iter = 0670, loss = 68.7374
[2024-05-21 13:13:46] iter = 0680, loss = 62.4311
[2024-05-21 13:13:47] iter = 0690, loss = 78.0051
[2024-05-21 13:22:25] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.062350, train acc = 1.0000 train oa = 1.0000, test acc = 0.3028 test oa = 0.3270
[2024-05-21 13:13:49] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.012010, train acc = 1.0000 train oa = 1.0000, test acc = 0.2589 test oa = 0.2128
Evaluate 1, mean = 0.2589 std = 0.0000
-------------------------
[2024-05-21 13:13:49] iter = 0700, loss = 77.8160
[2024-05-21 13:13:50] iter = 0710, loss = 76.5941
[2024-05-21 13:22:28] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.047175, train acc = 1.0000 train oa = 1.0000, test acc = 0.2544 test oa = 0.2924
[2024-05-21 13:13:50] iter = 0720, loss = 69.2397
[2024-05-21 13:22:28] iter = 0960, loss = 55.7944
[2024-05-21 13:13:51] iter = 0730, loss = 69.6161
[2024-05-21 13:13:51] iter = 0740, loss = 72.6428
[2024-05-21 13:13:52] iter = 0750, loss = 69.8112
[2024-05-21 13:22:30] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.074160, train acc = 1.0000 train oa = 1.0000, test acc = 0.2944 test oa = 0.2993
[2024-05-21 13:13:53] iter = 0760, loss = 61.7836
[2024-05-21 13:13:53] iter = 0770, loss = 71.6779
[2024-05-21 13:13:54] iter = 0780, loss = 65.9184
[2024-05-21 13:13:54] iter = 0790, loss = 65.5462
[2024-05-21 13:13:57] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024432, train acc = 1.0000 train oa = 1.0000, test acc = 0.2614 test oa = 0.2474
Evaluate 1, mean = 0.2614 std = 0.0000
-------------------------
[2024-05-21 13:13:57] iter = 0800, loss = 65.1743
[2024-05-21 13:13:57] iter = 0810, loss = 62.2454
[2024-05-21 13:13:58] iter = 0820, loss = 61.7944
[2024-05-21 13:13:59] iter = 0830, loss = 72.4097
[2024-05-21 13:13:59] iter = 0840, loss = 66.4043
[2024-05-21 13:14:00] iter = 0850, loss = 69.0833
[2024-05-21 13:14:00] iter = 0860, loss = 65.2207
[2024-05-21 13:14:01] iter = 0870, loss = 67.2767
[2024-05-21 13:14:01] iter = 0880, loss = 68.2975
[2024-05-21 13:14:02] iter = 0890, loss = 61.8506
[2024-05-21 13:14:04] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.014295, train acc = 1.0000 train oa = 1.0000, test acc = 0.2411 test oa = 0.2388
Evaluate 1, mean = 0.2411 std = 0.0000
-------------------------
[2024-05-21 13:14:05] iter = 0900, loss = 64.0496
[2024-05-21 13:14:05] iter = 0910, loss = 67.9884
[2024-05-21 13:14:06] iter = 0920, loss = 71.2423
[2024-05-21 13:14:06] iter = 0930, loss = 69.3201
[2024-05-21 13:14:07] iter = 0940, loss = 67.2112
[2024-05-21 13:14:07] iter = 0950, loss = 68.6418
[2024-05-21 13:14:08] iter = 0960, loss = 69.3541
[2024-05-21 13:14:09] iter = 0970, loss = 64.3259
[2024-05-21 13:14:09] iter = 0980, loss = 66.8841
[2024-05-21 13:14:10] iter = 0990, loss = 63.0199
[2024-05-21 13:14:12] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.020445, train acc = 1.0000 train oa = 1.0000, test acc = 0.2559 test oa = 0.2388
Evaluate 1, mean = 0.2559 std = 0.0000
-------------------------
[2024-05-21 13:14:12] iter = 1000, loss = 69.3852

================== Exp 0 ==================
 
[2024-05-21 13:15:03] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000176, train acc = 1.0000 train oa = 1.0000, test acc = 0.0548 test oa = 0.0554
Evaluate 1, mean = 0.0548 std = 0.0000
-------------------------
[2024-05-21 13:15:03] iter = 0000, loss = 1231.8674
[2024-05-21 13:15:04] iter = 0010, loss = 252.0955
[2024-05-21 13:15:05] iter = 0020, loss = 187.8190
[2024-05-21 13:15:05] iter = 0030, loss = 172.6389
[2024-05-21 13:15:06] iter = 0040, loss = 133.2629
[2024-05-21 13:15:07] iter = 0050, loss = 116.7276
[2024-05-21 13:15:07] iter = 0060, loss = 129.0202
[2024-05-21 13:15:08] iter = 0070, loss = 119.0518
[2024-05-21 13:15:09] iter = 0080, loss = 118.1694
[2024-05-21 13:15:09] iter = 0090, loss = 102.6544
[2024-05-21 13:15:12] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001024, train acc = 1.0000 train oa = 1.0000, test acc = 0.2439 test oa = 0.2526
Evaluate 1, mean = 0.2439 std = 0.0000
-------------------------
[2024-05-21 13:15:12] iter = 0100, loss = 115.7715
[2024-05-21 13:15:13] iter = 0110, loss = 111.9356
[2024-05-21 13:15:13] iter = 0120, loss = 109.5831
[2024-05-21 13:15:14] iter = 0130, loss = 95.6860
[2024-05-21 13:15:14] iter = 0140, loss = 103.1577
[2024-05-21 13:15:15] iter = 0150, loss = 97.3656
[2024-05-21 13:15:16] iter = 0160, loss = 98.8863
[2024-05-21 13:15:16] iter = 0170, loss = 90.7230
[2024-05-21 13:15:17] iter = 0180, loss = 94.9359
[2024-05-21 13:15:18] iter = 0190, loss = 88.0456
[2024-05-21 13:15:20] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001171, train acc = 1.0000 train oa = 1.0000, test acc = 0.1767 test oa = 0.2284
Evaluate 1, mean = 0.1767 std = 0.0000
-------------------------
[2024-05-21 13:15:20] iter = 0200, loss = 94.0251
[2024-05-21 13:15:21] iter = 0210, loss = 101.4416
[2024-05-21 13:15:21] iter = 0220, loss = 84.0309
[2024-05-21 13:15:22] iter = 0230, loss = 96.4024
[2024-05-21 13:15:23] iter = 0240, loss = 93.3058
[2024-05-21 13:15:23] iter = 0250, loss = 80.9892
[2024-05-21 13:15:24] iter = 0260, loss = 79.2537
[2024-05-21 13:15:25] iter = 0270, loss = 84.6299
[2024-05-21 13:15:25] iter = 0280, loss = 88.1449
[2024-05-21 13:15:26] iter = 0290, loss = 85.6762
[2024-05-21 13:15:28] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.002678, train acc = 1.0000 train oa = 1.0000, test acc = 0.2172 test oa = 0.2215
Evaluate 1, mean = 0.2172 std = 0.0000
-------------------------
[2024-05-21 13:15:29] iter = 0300, loss = 74.2517
[2024-05-21 13:15:29] iter = 0310, loss = 88.8694
[2024-05-21 13:15:30] iter = 0320, loss = 86.4291
[2024-05-21 13:15:30] iter = 0330, loss = 98.9304
[2024-05-21 13:15:31] iter = 0340, loss = 86.2498
[2024-05-21 13:15:32] iter = 0350, loss = 85.6363
[2024-05-21 13:15:32] iter = 0360, loss = 87.1970
[2024-05-21 13:15:33] iter = 0370, loss = 81.5892
[2024-05-21 13:15:34] iter = 0380, loss = 81.8578
[2024-05-21 13:15:34] iter = 0390, loss = 86.4809
[2024-05-21 13:15:37] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.004108, train acc = 1.0000 train oa = 1.0000, test acc = 0.1160 test oa = 0.1090
Evaluate 1, mean = 0.1160 std = 0.0000
-------------------------
[2024-05-21 13:15:37] iter = 0400, loss = 85.5392
[2024-05-21 13:15:37] iter = 0410, loss = 77.6898
[2024-05-21 13:15:38] iter = 0420, loss = 82.4768
[2024-05-21 13:15:39] iter = 0430, loss = 76.4421
[2024-05-21 13:15:39] iter = 0440, loss = 75.2151
[2024-05-21 13:15:40] iter = 0450, loss = 78.6175
[2024-05-21 13:15:41] iter = 0460, loss = 73.9109
[2024-05-21 13:15:41] iter = 0470, loss = 70.2650
[2024-05-21 13:15:42] iter = 0480, loss = 77.3642
[2024-05-21 13:15:43] iter = 0490, loss = 73.1490
[2024-05-21 13:15:45] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.011642, train acc = 1.0000 train oa = 1.0000, test acc = 0.2325 test oa = 0.1886
Evaluate 1, mean = 0.2325 std = 0.0000
-------------------------
[2024-05-21 13:15:45] iter = 0500, loss = 76.5585
[2024-05-21 13:15:46] iter = 0510, loss = 76.9515
[2024-05-21 13:15:47] iter = 0520, loss = 79.7248
[2024-05-21 13:15:47] iter = 0530, loss = 76.3244
[2024-05-21 13:15:48] iter = 0540, loss = 74.6273
[2024-05-21 13:15:48] iter = 0550, loss = 72.7757
[2024-05-21 13:15:49] iter = 0560, loss = 80.8682
[2024-05-21 13:15:50] iter = 0570, loss = 75.5727
[2024-05-21 13:15:50] iter = 0580, loss = 69.9566
[2024-05-21 13:15:51] iter = 0590, loss = 72.5281
[2024-05-21 13:24:29] iter = 0970, loss = 52.7943
[2024-05-21 13:15:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.013704, train acc = 1.0000 train oa = 1.0000, test acc = 0.2693 test oa = 0.2093
Evaluate 1, mean = 0.2693 std = 0.0000
-------------------------
[2024-05-21 13:15:54] iter = 0600, loss = 71.3700
[2024-05-21 13:15:54] iter = 0610, loss = 71.7200
[2024-05-21 13:15:55] iter = 0620, loss = 75.0507
[2024-05-21 13:15:56] iter = 0630, loss = 69.0267
[2024-05-21 13:15:56] iter = 0640, loss = 68.8088
[2024-05-21 13:15:57] iter = 0650, loss = 69.6516
[2024-05-21 13:15:57] iter = 0660, loss = 71.5821
[2024-05-21 13:15:58] iter = 0670, loss = 66.7212
[2024-05-21 13:15:59] iter = 0680, loss = 76.8880
[2024-05-21 13:15:59] iter = 0690, loss = 66.0235
[2024-05-21 13:16:02] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.022839, train acc = 1.0000 train oa = 1.0000, test acc = 0.2802 test oa = 0.2526
Evaluate 1, mean = 0.2802 std = 0.0000
-------------------------
[2024-05-21 13:16:02] iter = 0700, loss = 69.1669
[2024-05-21 13:16:03] iter = 0710, loss = 72.3049
[2024-05-21 13:16:03] iter = 0720, loss = 68.4566
[2024-05-21 13:16:04] iter = 0730, loss = 67.1413
[2024-05-21 13:16:05] iter = 0740, loss = 74.2037
[2024-05-21 13:16:05] iter = 0750, loss = 68.1205
[2024-05-21 13:16:06] iter = 0760, loss = 69.8580
[2024-05-21 13:16:06] iter = 0770, loss = 74.0028
[2024-05-21 13:16:07] iter = 0780, loss = 72.7466
[2024-05-21 13:16:08] iter = 0790, loss = 69.3532
[2024-05-21 13:16:10] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.017746, train acc = 1.0000 train oa = 1.0000, test acc = 0.2743 test oa = 0.2370
Evaluate 1, mean = 0.2743 std = 0.0000
-------------------------
[2024-05-21 13:16:10] iter = 0800, loss = 71.8653
[2024-05-21 13:16:11] iter = 0810, loss = 65.9922
[2024-05-21 13:16:12] iter = 0820, loss = 69.9340
[2024-05-21 13:16:12] iter = 0830, loss = 73.5366
[2024-05-21 13:16:13] iter = 0840, loss = 67.4299
[2024-05-21 13:16:14] iter = 0850, loss = 67.2979
[2024-05-21 13:16:14] iter = 0860, loss = 68.8695
[2024-05-21 13:16:15] iter = 0870, loss = 78.8909
[2024-05-21 13:16:16] iter = 0880, loss = 67.5354
[2024-05-21 13:16:16] iter = 0890, loss = 64.5215
[2024-05-21 13:16:19] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.016212, train acc = 1.0000 train oa = 1.0000, test acc = 0.2807 test oa = 0.2664
Evaluate 1, mean = 0.2807 std = 0.0000
-------------------------
[2024-05-21 13:16:19] iter = 0900, loss = 65.9376
[2024-05-21 13:16:19] iter = 0910, loss = 68.3331
[2024-05-21 13:16:20] iter = 0920, loss = 64.1454
[2024-05-21 13:16:21] iter = 0930, loss = 68.3572
[2024-05-21 13:16:21] iter = 0940, loss = 70.3926
[2024-05-21 13:16:22] iter = 0950, loss = 74.6342
[2024-05-21 13:16:23] iter = 0960, loss = 66.4624
[2024-05-21 13:16:23] iter = 0970, loss = 63.2553
[2024-05-21 13:16:24] iter = 0980, loss = 73.0991
[2024-05-21 13:16:24] iter = 0990, loss = 66.2566
[2024-05-21 13:16:27] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.019712, train acc = 1.0000 train oa = 1.0000, test acc = 0.2478 test oa = 0.2180
Evaluate 1, mean = 0.2478 std = 0.0000
-------------------------
[2024-05-21 13:16:27] iter = 1000, loss = 61.5378

================== Exp 0 ==================
 
[2024-05-21 13:16:47] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000176, train acc = 1.0000 train oa = 1.0000, test acc = 0.0548 test oa = 0.0554
Evaluate 1, mean = 0.0548 std = 0.0000
-------------------------
[2024-05-21 13:16:47] iter = 0000, loss = 1231.8674
[2024-05-21 13:16:48] iter = 0010, loss = 251.8275
[2024-05-21 13:16:48] iter = 0020, loss = 188.2388
[2024-05-21 13:16:49] iter = 0030, loss = 170.7198
[2024-05-21 13:16:50] iter = 0040, loss = 133.3619
[2024-05-21 13:16:50] iter = 0050, loss = 116.7559
[2024-05-21 13:16:51] iter = 0060, loss = 128.8872
[2024-05-21 13:16:52] iter = 0070, loss = 118.9492
[2024-05-21 13:16:52] iter = 0080, loss = 117.3750
[2024-05-21 13:16:53] iter = 0090, loss = 102.7244
[2024-05-21 13:16:55] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.003572, train acc = 1.0000 train oa = 1.0000, test acc = 0.2225 test oa = 0.2301
Evaluate 1, mean = 0.2225 std = 0.0000
-------------------------
[2024-05-21 13:16:56] iter = 0100, loss = 113.4251
[2024-05-21 13:16:56] iter = 0110, loss = 110.1442
[2024-05-21 13:16:57] iter = 0120, loss = 109.5669
[2024-05-21 13:16:58] iter = 0130, loss = 94.9290
[2024-05-21 13:16:58] iter = 0140, loss = 103.0621
[2024-05-21 13:16:59] iter = 0150, loss = 97.5353
[2024-05-21 13:16:59] iter = 0160, loss = 98.2687
[2024-05-21 13:17:00] iter = 0170, loss = 90.1322
[2024-05-21 13:17:01] iter = 0180, loss = 95.8577
[2024-05-21 13:17:01] iter = 0190, loss = 88.6522
[2024-05-21 13:17:04] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000812, train acc = 1.0000 train oa = 1.0000, test acc = 0.2018 test oa = 0.2370
Evaluate 1, mean = 0.2018 std = 0.0000
-------------------------
[2024-05-21 13:17:04] iter = 0200, loss = 93.8319
[2024-05-21 13:17:05] iter = 0210, loss = 102.7216
[2024-05-21 13:17:05] iter = 0220, loss = 82.9686
[2024-05-21 13:17:06] iter = 0230, loss = 94.1022
[2024-05-21 13:17:07] iter = 0240, loss = 91.0182
[2024-05-21 13:17:07] iter = 0250, loss = 81.1069
[2024-05-21 13:17:08] iter = 0260, loss = 80.2274
[2024-05-21 13:17:09] iter = 0270, loss = 84.0845
[2024-05-21 13:17:09] iter = 0280, loss = 86.1897
[2024-05-21 13:17:10] iter = 0290, loss = 86.1875
[2024-05-21 13:17:12] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.008329, train acc = 1.0000 train oa = 1.0000, test acc = 0.1534 test oa = 0.1747
Evaluate 1, mean = 0.1534 std = 0.0000
-------------------------
[2024-05-21 13:17:13] iter = 0300, loss = 73.9817
[2024-05-21 13:17:13] iter = 0310, loss = 90.0405
[2024-05-21 13:17:14] iter = 0320, loss = 87.4585
[2024-05-21 13:17:15] iter = 0330, loss = 99.3780
[2024-05-21 13:17:15] iter = 0340, loss = 87.2253
[2024-05-21 13:17:16] iter = 0350, loss = 84.4915
[2024-05-21 13:17:16] iter = 0360, loss = 87.0859
[2024-05-21 13:17:17] iter = 0370, loss = 82.5750
[2024-05-21 13:17:18] iter = 0380, loss = 81.8067
[2024-05-21 13:17:18] iter = 0390, loss = 86.1596
[2024-05-21 13:17:21] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001922, train acc = 1.0000 train oa = 1.0000, test acc = 0.2153 test oa = 0.1782
Evaluate 1, mean = 0.2153 std = 0.0000
-------------------------
[2024-05-21 13:17:21] iter = 0400, loss = 84.1256
[2024-05-21 13:17:21] iter = 0410, loss = 77.9055
[2024-05-21 13:17:22] iter = 0420, loss = 82.6753
[2024-05-21 13:17:23] iter = 0430, loss = 76.0439
[2024-05-21 13:17:23] iter = 0440, loss = 74.7672
[2024-05-21 13:17:24] iter = 0450, loss = 78.7462
[2024-05-21 13:17:25] iter = 0460, loss = 74.0289
[2024-05-21 13:17:25] iter = 0470, loss = 70.6633
[2024-05-21 13:17:26] iter = 0480, loss = 77.9531
[2024-05-21 13:17:27] iter = 0490, loss = 71.4787
[2024-05-21 13:17:29] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.004819, train acc = 1.0000 train oa = 1.0000, test acc = 0.2264 test oa = 0.1799
Evaluate 1, mean = 0.2264 std = 0.0000
-------------------------
[2024-05-21 13:17:29] iter = 0500, loss = 75.4682
[2024-05-21 13:17:30] iter = 0510, loss = 76.9848
[2024-05-21 13:17:31] iter = 0520, loss = 78.9310
[2024-05-21 13:17:31] iter = 0530, loss = 75.8999
[2024-05-21 13:17:32] iter = 0540, loss = 75.2268
[2024-05-21 13:17:32] iter = 0550, loss = 72.4787
[2024-05-21 13:17:33] iter = 0560, loss = 80.0879
[2024-05-21 13:17:34] iter = 0570, loss = 75.7406
[2024-05-21 13:17:34] iter = 0580, loss = 70.4504
[2024-05-21 13:17:35] iter = 0590, loss = 72.9853
[2024-05-21 13:17:37] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.025531, train acc = 1.0000 train oa = 1.0000, test acc = 0.2208 test oa = 0.2042
Evaluate 1, mean = 0.2208 std = 0.0000
-------------------------
[2024-05-21 13:17:37] iter = 0600, loss = 71.5597
[2024-05-21 13:17:38] iter = 0610, loss = 71.9206
[2024-05-21 13:17:39] iter = 0620, loss = 74.9106
[2024-05-21 13:17:39] iter = 0630, loss = 69.3080
[2024-05-21 13:17:40] iter = 0640, loss = 67.7636
[2024-05-21 13:17:41] iter = 0650, loss = 70.5397
[2024-05-21 13:17:41] iter = 0660, loss = 71.9993
[2024-05-21 13:17:42] iter = 0670, loss = 66.8936
[2024-05-21 13:17:43] iter = 0680, loss = 77.1716
[2024-05-21 13:17:43] iter = 0690, loss = 65.6490
[2024-05-21 13:17:46] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.012853, train acc = 1.0000 train oa = 1.0000, test acc = 0.2858 test oa = 0.2751
Evaluate 1, mean = 0.2858 std = 0.0000
-------------------------
[2024-05-21 13:17:46] iter = 0700, loss = 68.6881
[2024-05-21 13:17:46] iter = 0710, loss = 72.2321
[2024-05-21 13:17:47] iter = 0720, loss = 68.1599
[2024-05-21 13:17:48] iter = 0730, loss = 67.1896
[2024-05-21 13:17:48] iter = 0740, loss = 74.8220
[2024-05-21 13:17:49] iter = 0750, loss = 68.8368
[2024-05-21 13:17:50] iter = 0760, loss = 69.5815
[2024-05-21 13:17:50] iter = 0770, loss = 74.0584
[2024-05-21 13:17:51] iter = 0780, loss = 72.9264
[2024-05-21 13:26:29] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.074916, train acc = 0.8933 train oa = 0.8933, test acc = 0.3338 test oa = 0.3010
Evaluate 1, mean = 0.3338 std = 0.0000
-------------------------
[2024-05-21 13:17:52] iter = 0790, loss = 69.5154
[2024-05-21 13:17:54] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.022121, train acc = 1.0000 train oa = 1.0000, test acc = 0.2938 test oa = 0.2768
Evaluate 1, mean = 0.2938 std = 0.0000
-------------------------
[2024-05-21 13:17:54] iter = 0800, loss = 71.1712
[2024-05-21 13:17:55] iter = 0810, loss = 66.6513
[2024-05-21 13:17:55] iter = 0820, loss = 70.8313
[2024-05-21 13:17:56] iter = 0830, loss = 74.2586
[2024-05-21 13:17:57] iter = 0840, loss = 67.4157
[2024-05-21 13:17:57] iter = 0850, loss = 67.8590
[2024-05-21 13:17:58] iter = 0860, loss = 68.3629
[2024-05-21 13:17:59] iter = 0870, loss = 77.6621
[2024-05-21 13:17:59] iter = 0880, loss = 67.6049
[2024-05-21 13:18:00] iter = 0890, loss = 64.3497
[2024-05-21 13:18:03] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.014152, train acc = 1.0000 train oa = 1.0000, test acc = 0.2856 test oa = 0.2647
Evaluate 1, mean = 0.2856 std = 0.0000
-------------------------
[2024-05-21 13:18:03] iter = 0900, loss = 66.9008
[2024-05-21 13:18:03] iter = 0910, loss = 68.2226
[2024-05-21 13:26:42] iter = 0980, loss = 52.8791
[2024-05-21 13:18:04] iter = 0920, loss = 64.0743
[2024-05-21 13:18:05] iter = 0930, loss = 68.3268
[2024-05-21 13:18:05] iter = 0940, loss = 71.0277
[2024-05-21 13:18:06] iter = 0950, loss = 74.9662
[2024-05-21 13:18:06] iter = 0960, loss = 67.2064
[2024-05-21 13:18:07] iter = 0970, loss = 63.0550
[2024-05-21 13:18:08] iter = 0980, loss = 73.7343
[2024-05-21 13:18:08] iter = 0990, loss = 66.3829
[2024-05-21 13:18:11] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.029952, train acc = 1.0000 train oa = 1.0000, test acc = 0.2680 test oa = 0.2232
Evaluate 1, mean = 0.2680 std = 0.0000
-------------------------
[2024-05-21 13:18:11] iter = 1000, loss = 61.4689

================== Exp 0 ==================
 
[2024-05-21 13:18:27] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000247, train acc = 1.0000 train oa = 1.0000, test acc = 0.0812 test oa = 0.0952
Evaluate 1, mean = 0.0812 std = 0.0000
-------------------------
[2024-05-21 13:18:27] iter = 0000, loss = 1078.3430
[2024-05-21 13:18:27] iter = 0010, loss = 234.0013
[2024-05-21 13:18:28] iter = 0020, loss = 174.7764
[2024-05-21 13:18:29] iter = 0030, loss = 147.1846
[2024-05-21 13:18:29] iter = 0040, loss = 130.8884
[2024-05-21 13:18:30] iter = 0050, loss = 116.7168
[2024-05-21 13:18:31] iter = 0060, loss = 124.4137
[2024-05-21 13:18:31] iter = 0070, loss = 107.7959
[2024-05-21 13:18:32] iter = 0080, loss = 108.2083
[2024-05-21 13:18:33] iter = 0090, loss = 113.0744
[2024-05-21 13:18:35] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000673, train acc = 1.0000 train oa = 1.0000, test acc = 0.1865 test oa = 0.1817
Evaluate 1, mean = 0.1865 std = 0.0000
-------------------------
[2024-05-21 13:18:35] iter = 0100, loss = 106.9485
[2024-05-21 13:18:36] iter = 0110, loss = 109.5345
[2024-05-21 13:18:36] iter = 0120, loss = 99.8239
[2024-05-21 13:18:37] iter = 0130, loss = 97.0872
[2024-05-21 13:18:38] iter = 0140, loss = 99.4537
[2024-05-21 13:18:38] iter = 0150, loss = 99.9243
[2024-05-21 13:18:39] iter = 0160, loss = 92.9610
[2024-05-21 13:18:40] iter = 0170, loss = 87.9816
[2024-05-21 13:18:40] iter = 0180, loss = 94.7286
[2024-05-21 13:18:41] iter = 0190, loss = 91.1920
[2024-05-21 13:18:43] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001171, train acc = 1.0000 train oa = 1.0000, test acc = 0.1922 test oa = 0.1661
Evaluate 1, mean = 0.1922 std = 0.0000
-------------------------
[2024-05-21 13:18:43] iter = 0200, loss = 97.0203
[2024-05-21 13:18:44] iter = 0210, loss = 84.7215
[2024-05-21 13:18:45] iter = 0220, loss = 77.9489
[2024-05-21 13:18:45] iter = 0230, loss = 85.1923
[2024-05-21 13:18:46] iter = 0240, loss = 82.9892
[2024-05-21 13:18:47] iter = 0250, loss = 74.7716
[2024-05-21 13:18:47] iter = 0260, loss = 73.4298
[2024-05-21 13:18:48] iter = 0270, loss = 77.2094
[2024-05-21 13:18:49] iter = 0280, loss = 73.1764
[2024-05-21 13:18:49] iter = 0290, loss = 81.0402
[2024-05-21 13:18:52] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.021349, train acc = 1.0000 train oa = 1.0000, test acc = 0.0989 test oa = 0.0900
Evaluate 1, mean = 0.0989 std = 0.0000
-------------------------
[2024-05-21 13:18:52] iter = 0300, loss = 80.7168
[2024-05-21 13:18:52] iter = 0310, loss = 79.2584
[2024-05-21 13:18:53] iter = 0320, loss = 80.4077
[2024-05-21 13:18:54] iter = 0330, loss = 74.3668
[2024-05-21 13:18:54] iter = 0340, loss = 76.4583
[2024-05-21 13:18:55] iter = 0350, loss = 75.0933
[2024-05-21 13:18:56] iter = 0360, loss = 77.2133
[2024-05-21 13:18:56] iter = 0370, loss = 72.8840
[2024-05-21 13:18:57] iter = 0380, loss = 68.1512
[2024-05-21 13:18:58] iter = 0390, loss = 72.4425
[2024-05-21 13:19:00] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.013535, train acc = 1.0000 train oa = 1.0000, test acc = 0.2710 test oa = 0.2682
Evaluate 1, mean = 0.2710 std = 0.0000
-------------------------
[2024-05-21 13:19:00] iter = 0400, loss = 75.6602
[2024-05-21 13:19:01] iter = 0410, loss = 73.3374
[2024-05-21 13:19:01] iter = 0420, loss = 74.1594
[2024-05-21 13:19:02] iter = 0430, loss = 69.9923
[2024-05-21 13:19:03] iter = 0440, loss = 72.5103
[2024-05-21 13:19:03] iter = 0450, loss = 70.2944
[2024-05-21 13:19:04] iter = 0460, loss = 73.4252
[2024-05-21 13:19:05] iter = 0470, loss = 76.2682
[2024-05-21 13:19:05] iter = 0480, loss = 71.1748
[2024-05-21 13:19:06] iter = 0490, loss = 72.5739
[2024-05-21 13:19:09] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.020777, train acc = 1.0000 train oa = 1.0000, test acc = 0.2221 test oa = 0.2093
Evaluate 1, mean = 0.2221 std = 0.0000
-------------------------
[2024-05-21 13:19:09] iter = 0500, loss = 72.3799
[2024-05-21 13:19:09] iter = 0510, loss = 70.4627
[2024-05-21 13:19:10] iter = 0520, loss = 67.6233
[2024-05-21 13:19:11] iter = 0530, loss = 71.1818
[2024-05-21 13:19:11] iter = 0540, loss = 63.0773
[2024-05-21 13:19:12] iter = 0550, loss = 69.4747
[2024-05-21 13:19:12] iter = 0560, loss = 66.2136
[2024-05-21 13:19:13] iter = 0570, loss = 61.3811
[2024-05-21 13:19:14] iter = 0580, loss = 66.0526
[2024-05-21 13:19:14] iter = 0590, loss = 62.0360
[2024-05-21 13:19:17] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.027484, train acc = 1.0000 train oa = 1.0000, test acc = 0.3153 test oa = 0.2751
Evaluate 1, mean = 0.3153 std = 0.0000
-------------------------
[2024-05-21 13:19:17] iter = 0600, loss = 73.5135
[2024-05-21 13:19:18] iter = 0610, loss = 66.9401
[2024-05-21 13:19:18] iter = 0620, loss = 72.2819
[2024-05-21 13:19:19] iter = 0630, loss = 69.5356
[2024-05-21 13:19:20] iter = 0640, loss = 68.9874
[2024-05-21 13:19:20] iter = 0650, loss = 68.1615
[2024-05-21 13:19:21] iter = 0660, loss = 72.3899
[2024-05-21 13:19:22] iter = 0670, loss = 70.3380
[2024-05-21 13:19:22] iter = 0680, loss = 59.7819
[2024-05-21 13:19:23] iter = 0690, loss = 63.3044
[2024-05-21 13:19:25] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.028211, train acc = 1.0000 train oa = 1.0000, test acc = 0.3136 test oa = 0.2543
Evaluate 1, mean = 0.3136 std = 0.0000
-------------------------
[2024-05-21 13:19:25] iter = 0700, loss = 73.2135
[2024-05-21 13:19:26] iter = 0710, loss = 67.1596
[2024-05-21 13:19:27] iter = 0720, loss = 66.4225
[2024-05-21 13:19:27] iter = 0730, loss = 68.3835
[2024-05-21 13:19:28] iter = 0740, loss = 64.4849
[2024-05-21 13:19:28] iter = 0750, loss = 67.7612
[2024-05-21 13:19:29] iter = 0760, loss = 68.3391
[2024-05-21 13:19:30] iter = 0770, loss = 64.7579
[2024-05-21 13:19:30] iter = 0780, loss = 60.1681
[2024-05-21 13:19:31] iter = 0790, loss = 68.0585
[2024-05-21 13:19:33] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.065438, train acc = 1.0000 train oa = 1.0000, test acc = 0.2728 test oa = 0.2336
Evaluate 1, mean = 0.2728 std = 0.0000
-------------------------
[2024-05-21 13:19:34] iter = 0800, loss = 62.3721
[2024-05-21 13:19:34] iter = 0810, loss = 60.7164
[2024-05-21 13:19:35] iter = 0820, loss = 64.1332
[2024-05-21 13:19:35] iter = 0830, loss = 59.5879
[2024-05-21 13:19:36] iter = 0840, loss = 62.0264
[2024-05-21 13:19:37] iter = 0850, loss = 66.3115
[2024-05-21 13:19:37] iter = 0860, loss = 70.4960
[2024-05-21 13:19:38] iter = 0870, loss = 61.3703
[2024-05-21 13:19:39] iter = 0880, loss = 74.8488
[2024-05-21 13:19:39] iter = 0890, loss = 69.3541
[2024-05-21 13:19:42] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.043608, train acc = 1.0000 train oa = 1.0000, test acc = 0.2853 test oa = 0.2457
Evaluate 1, mean = 0.2853 std = 0.0000
-------------------------
[2024-05-21 13:19:42] iter = 0900, loss = 64.8445
[2024-05-21 13:19:43] iter = 0910, loss = 62.9197
[2024-05-21 13:19:43] iter = 0920, loss = 61.6167
[2024-05-21 13:19:44] iter = 0930, loss = 65.2111
[2024-05-21 13:19:44] iter = 0940, loss = 65.3197
[2024-05-21 13:19:45] iter = 0950, loss = 67.1051
[2024-05-21 13:19:46] iter = 0960, loss = 65.1796
[2024-05-21 13:19:46] iter = 0970, loss = 65.0558
[2024-05-21 13:19:47] iter = 0980, loss = 69.1296
[2024-05-21 13:19:48] iter = 0990, loss = 69.1120
[2024-05-21 13:19:50] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.027247, train acc = 1.0000 train oa = 1.0000, test acc = 0.2702 test oa = 0.2318
Evaluate 1, mean = 0.2702 std = 0.0000
-------------------------
[2024-05-21 13:19:50] iter = 1000, loss = 71.2008
[2024-05-21 13:28:43] iter = 0990, loss = 52.4530

================== Exp 0 ==================
 
[2024-05-21 13:20:19] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000247, train acc = 1.0000 train oa = 1.0000, test acc = 0.0812 test oa = 0.0952
Evaluate 1, mean = 0.0812 std = 0.0000
-------------------------
[2024-05-21 13:20:19] iter = 0000, loss = 1078.3430
[2024-05-21 13:20:20] iter = 0010, loss = 233.1214
[2024-05-21 13:20:20] iter = 0020, loss = 175.8376
[2024-05-21 13:20:21] iter = 0030, loss = 146.3107
[2024-05-21 13:20:22] iter = 0040, loss = 130.7941
[2024-05-21 13:20:22] iter = 0050, loss = 116.3261
[2024-05-21 13:20:23] iter = 0060, loss = 124.3767
[2024-05-21 13:20:23] iter = 0070, loss = 106.7028
[2024-05-21 13:20:24] iter = 0080, loss = 108.7812
[2024-05-21 13:20:25] iter = 0090, loss = 113.7728
[2024-05-21 13:20:27] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.000307, train acc = 1.0000 train oa = 1.0000, test acc = 0.1574 test oa = 0.1505
Evaluate 1, mean = 0.1574 std = 0.0000
-------------------------
[2024-05-21 13:20:27] iter = 0100, loss = 106.5421
[2024-05-21 13:20:28] iter = 0110, loss = 110.3755
[2024-05-21 13:20:29] iter = 0120, loss = 100.8072
[2024-05-21 13:20:29] iter = 0130, loss = 96.0025
[2024-05-21 13:20:30] iter = 0140, loss = 99.7599
[2024-05-21 13:20:31] iter = 0150, loss = 101.9215
[2024-05-21 13:20:31] iter = 0160, loss = 92.6792
[2024-05-21 13:20:32] iter = 0170, loss = 87.7174
[2024-05-21 13:20:32] iter = 0180, loss = 96.3827
[2024-05-21 13:20:33] iter = 0190, loss = 92.8207
[2024-05-21 13:20:36] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.001591, train acc = 1.0000 train oa = 1.0000, test acc = 0.2340 test oa = 0.2405
Evaluate 1, mean = 0.2340 std = 0.0000
-------------------------
[2024-05-21 13:20:36] iter = 0200, loss = 98.0652
[2024-05-21 13:20:36] iter = 0210, loss = 84.7340
[2024-05-21 13:20:37] iter = 0220, loss = 78.1215
[2024-05-21 13:20:38] iter = 0230, loss = 86.8463
[2024-05-21 13:20:38] iter = 0240, loss = 84.6343
[2024-05-21 13:20:39] iter = 0250, loss = 75.8219
[2024-05-21 13:20:40] iter = 0260, loss = 72.0262
[2024-05-21 13:20:40] iter = 0270, loss = 77.2291
[2024-05-21 13:20:41] iter = 0280, loss = 73.6010
[2024-05-21 13:20:42] iter = 0290, loss = 82.0571
[2024-05-21 13:20:44] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.011565, train acc = 1.0000 train oa = 1.0000, test acc = 0.1319 test oa = 0.1228
Evaluate 1, mean = 0.1319 std = 0.0000
-------------------------
[2024-05-21 13:20:44] iter = 0300, loss = 80.0641
[2024-05-21 13:20:45] iter = 0310, loss = 80.2686
[2024-05-21 13:20:45] iter = 0320, loss = 80.7118
[2024-05-21 13:20:46] iter = 0330, loss = 74.7819
[2024-05-21 13:20:47] iter = 0340, loss = 76.0694
[2024-05-21 13:20:47] iter = 0350, loss = 74.5828
[2024-05-21 13:20:48] iter = 0360, loss = 77.7346
[2024-05-21 13:20:49] iter = 0370, loss = 74.2765
[2024-05-21 13:20:49] iter = 0380, loss = 67.9216
[2024-05-21 13:20:50] iter = 0390, loss = 72.9346
[2024-05-21 13:20:52] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.014670, train acc = 1.0000 train oa = 1.0000, test acc = 0.2243 test oa = 0.2215
Evaluate 1, mean = 0.2243 std = 0.0000
-------------------------
[2024-05-21 13:20:52] iter = 0400, loss = 75.3857
[2024-05-21 13:20:53] iter = 0410, loss = 72.4668
[2024-05-21 13:20:54] iter = 0420, loss = 71.9743
[2024-05-21 13:20:54] iter = 0430, loss = 71.4699
[2024-05-21 13:20:55] iter = 0440, loss = 73.1296
[2024-05-21 13:20:56] iter = 0450, loss = 71.6144
[2024-05-21 13:20:56] iter = 0460, loss = 74.2747
[2024-05-21 13:20:57] iter = 0470, loss = 76.0401
[2024-05-21 13:20:58] iter = 0480, loss = 71.5208
[2024-05-21 13:20:58] iter = 0490, loss = 71.7636
[2024-05-21 13:21:01] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.017680, train acc = 1.0000 train oa = 1.0000, test acc = 0.2470 test oa = 0.2336
Evaluate 1, mean = 0.2470 std = 0.0000
-------------------------
[2024-05-21 13:21:01] iter = 0500, loss = 71.1317
[2024-05-21 13:21:01] iter = 0510, loss = 69.0760
[2024-05-21 13:21:02] iter = 0520, loss = 68.2247
[2024-05-21 13:21:03] iter = 0530, loss = 70.8549
[2024-05-21 13:21:03] iter = 0540, loss = 63.5466
[2024-05-21 13:21:04] iter = 0550, loss = 70.3951
[2024-05-21 13:21:05] iter = 0560, loss = 66.4471
[2024-05-21 13:21:05] iter = 0570, loss = 62.3769
[2024-05-21 13:21:06] iter = 0580, loss = 66.6746
[2024-05-21 13:21:07] iter = 0590, loss = 61.5675
[2024-05-21 13:21:09] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024434, train acc = 1.0000 train oa = 1.0000, test acc = 0.3073 test oa = 0.2734
Evaluate 1, mean = 0.3073 std = 0.0000
-------------------------
[2024-05-21 13:21:09] iter = 0600, loss = 73.2479
[2024-05-21 13:21:10] iter = 0610, loss = 67.0202
[2024-05-21 13:21:11] iter = 0620, loss = 71.1455
[2024-05-21 13:21:11] iter = 0630, loss = 68.9609
[2024-05-21 13:21:12] iter = 0640, loss = 67.5987
[2024-05-21 13:21:13] iter = 0650, loss = 67.6677
[2024-05-21 13:21:13] iter = 0660, loss = 71.2850
[2024-05-21 13:21:14] iter = 0670, loss = 71.4227
[2024-05-21 13:21:15] iter = 0680, loss = 59.5338
[2024-05-21 13:21:15] iter = 0690, loss = 63.7579
[2024-05-21 13:21:18] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.031009, train acc = 1.0000 train oa = 1.0000, test acc = 0.3023 test oa = 0.2509
Evaluate 1, mean = 0.3023 std = 0.0000
-------------------------
[2024-05-21 13:21:18] iter = 0700, loss = 72.8927
[2024-05-21 13:21:18] iter = 0710, loss = 66.9179
[2024-05-21 13:21:19] iter = 0720, loss = 65.8682
[2024-05-21 13:21:20] iter = 0730, loss = 68.6644
[2024-05-21 13:21:20] iter = 0740, loss = 65.3495
[2024-05-21 13:21:21] iter = 0750, loss = 67.4526
[2024-05-21 13:21:22] iter = 0760, loss = 68.4572
[2024-05-21 13:21:22] iter = 0770, loss = 64.9980
[2024-05-21 13:21:23] iter = 0780, loss = 59.4258
[2024-05-21 13:21:24] iter = 0790, loss = 67.4859
[2024-05-21 13:21:26] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.041667, train acc = 1.0000 train oa = 1.0000, test acc = 0.2748 test oa = 0.2370
Evaluate 1, mean = 0.2748 std = 0.0000
-------------------------
[2024-05-21 13:21:26] iter = 0800, loss = 62.5304
[2024-05-21 13:21:27] iter = 0810, loss = 61.7937
[2024-05-21 13:21:27] iter = 0820, loss = 65.2219
[2024-05-21 13:21:28] iter = 0830, loss = 60.2684
[2024-05-21 13:21:29] iter = 0840, loss = 62.2162
[2024-05-21 13:21:29] iter = 0850, loss = 67.0312
[2024-05-21 13:21:30] iter = 0860, loss = 70.7893
[2024-05-21 13:21:31] iter = 0870, loss = 62.0170
[2024-05-21 13:21:31] iter = 0880, loss = 74.6166
[2024-05-21 13:21:32] iter = 0890, loss = 68.6813
[2024-05-21 13:21:35] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.030587, train acc = 1.0000 train oa = 1.0000, test acc = 0.3281 test oa = 0.2820
Evaluate 1, mean = 0.3281 std = 0.0000
-------------------------
[2024-05-21 13:21:35] iter = 0900, loss = 63.9648
[2024-05-21 13:21:35] iter = 0910, loss = 62.1886
[2024-05-21 13:21:36] iter = 0920, loss = 62.1103
[2024-05-21 13:21:37] iter = 0930, loss = 64.6713
[2024-05-21 13:21:37] iter = 0940, loss = 64.7835
[2024-05-21 13:21:38] iter = 0950, loss = 67.0202
[2024-05-21 13:21:39] iter = 0960, loss = 66.2880
[2024-05-21 13:21:39] iter = 0970, loss = 65.9181
[2024-05-21 13:21:40] iter = 0980, loss = 69.8825
[2024-05-21 13:21:41] iter = 0990, loss = 68.1304
[2024-05-21 13:21:43] Evaluate_00: epoch = 0300, train time = 1 s, train loss = 0.024306, train acc = 1.0000 train oa = 1.0000, test acc = 0.2626 test oa = 0.2318
Evaluate 1, mean = 0.2626 std = 0.0000
-------------------------
[2024-05-21 13:21:43] iter = 1000, loss = 69.6942
[2024-05-21 13:30:42] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.989498, train acc = 0.8667 train oa = 0.8667, test acc = 0.3332 test oa = 0.2993
Evaluate 1, mean = 0.3332 std = 0.0000
-------------------------
[2024-05-21 13:30:54] iter = 1000, loss = 54.1606

================== Exp 0 ==================
 
[2024-05-21 13:22:43] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.093517, train acc = 0.3867 train oa = 0.3867, test acc = 0.0850 test oa = 0.0433
Evaluate 1, mean = 0.0850 std = 0.0000
-------------------------
[2024-05-21 13:22:43] iter = 0000, loss = 198.3702
[2024-05-21 13:22:45] iter = 0010, loss = 41.7918
[2024-05-21 13:22:46] iter = 0020, loss = 24.1171
[2024-05-21 13:22:47] iter = 0030, loss = 22.4138
[2024-05-21 13:22:48] iter = 0040, loss = 19.9031
[2024-05-21 13:22:49] iter = 0050, loss = 15.5432
[2024-05-21 13:22:50] iter = 0060, loss = 16.5992
[2024-05-21 13:22:51] iter = 0070, loss = 16.7438
[2024-05-21 13:22:52] iter = 0080, loss = 16.7556
[2024-05-21 13:22:53] iter = 0090, loss = 16.0610
[2024-05-21 13:23:05] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.234135, train acc = 0.6467 train oa = 0.6467, test acc = 0.3160 test oa = 0.2561
Evaluate 1, mean = 0.3160 std = 0.0000
-------------------------
[2024-05-21 13:23:05] iter = 0100, loss = 15.6233
[2024-05-21 13:23:06] iter = 0110, loss = 14.0237
[2024-05-21 13:23:07] iter = 0120, loss = 15.3059
[2024-05-21 13:23:08] iter = 0130, loss = 13.7431
[2024-05-21 13:23:09] iter = 0140, loss = 13.8556
[2024-05-21 13:23:10] iter = 0150, loss = 14.2788
[2024-05-21 13:23:11] iter = 0160, loss = 12.4645
[2024-05-21 13:23:13] iter = 0170, loss = 13.1339
[2024-05-21 13:23:14] iter = 0180, loss = 15.2363
[2024-05-21 13:23:15] iter = 0190, loss = 13.5498
[2024-05-21 13:23:26] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.493972, train acc = 0.5600 train oa = 0.5600, test acc = 0.3638 test oa = 0.3322
Evaluate 1, mean = 0.3638 std = 0.0000
-------------------------
[2024-05-21 13:23:27] iter = 0200, loss = 13.9748
[2024-05-21 13:23:28] iter = 0210, loss = 12.3205
[2024-05-21 13:23:29] iter = 0220, loss = 11.3110
[2024-05-21 13:23:30] iter = 0230, loss = 15.9722
[2024-05-21 13:23:31] iter = 0240, loss = 13.5408
[2024-05-21 13:23:32] iter = 0250, loss = 11.2379
[2024-05-21 13:23:33] iter = 0260, loss = 12.7484
[2024-05-21 13:23:34] iter = 0270, loss = 13.5655
[2024-05-21 13:23:35] iter = 0280, loss = 13.5774
[2024-05-21 13:23:36] iter = 0290, loss = 13.5136
[2024-05-21 13:23:48] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.373977, train acc = 0.6200 train oa = 0.6200, test acc = 0.3599 test oa = 0.3356
Evaluate 1, mean = 0.3599 std = 0.0000
-------------------------
[2024-05-21 13:23:48] iter = 0300, loss = 16.5063
[2024-05-21 13:23:49] iter = 0310, loss = 12.9522
[2024-05-21 13:23:50] iter = 0320, loss = 14.2692
[2024-05-21 13:23:51] iter = 0330, loss = 12.3826
[2024-05-21 13:23:53] iter = 0340, loss = 12.6045
[2024-05-21 13:23:54] iter = 0350, loss = 11.5768
[2024-05-21 13:23:55] iter = 0360, loss = 15.2173
[2024-05-21 13:23:56] iter = 0370, loss = 10.7580
[2024-05-21 13:23:57] iter = 0380, loss = 10.5312
[2024-05-21 13:23:58] iter = 0390, loss = 12.0515
[2024-05-21 13:24:10] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.460125, train acc = 0.5867 train oa = 0.5867, test acc = 0.3327 test oa = 0.3218
Evaluate 1, mean = 0.3327 std = 0.0000
-------------------------
[2024-05-21 13:24:10] iter = 0400, loss = 12.9391
[2024-05-21 13:24:11] iter = 0410, loss = 12.1367
[2024-05-21 13:24:12] iter = 0420, loss = 12.3017
[2024-05-21 13:24:13] iter = 0430, loss = 10.3975
[2024-05-21 13:24:14] iter = 0440, loss = 11.2059
[2024-05-21 13:24:15] iter = 0450, loss = 12.9231
[2024-05-21 13:24:17] iter = 0460, loss = 13.6179
[2024-05-21 13:24:18] iter = 0470, loss = 11.1542
[2024-05-21 13:24:19] iter = 0480, loss = 11.3028
[2024-05-21 13:24:20] iter = 0490, loss = 12.9776

================== Exp 0 ==================
 
[2024-05-21 13:25:05] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 2.165263, train acc = 0.3267 train oa = 0.3267, test acc = 0.0560 test oa = 0.0450
Evaluate 1, mean = 0.0560 std = 0.0000
-------------------------
[2024-05-21 13:25:05] iter = 0000, loss = 227.8366
[2024-05-21 13:25:06] iter = 0010, loss = 41.7898
[2024-05-21 13:25:07] iter = 0020, loss = 31.0650
[2024-05-21 13:25:08] iter = 0030, loss = 23.8549
[2024-05-21 13:25:09] iter = 0040, loss = 19.8462
[2024-05-21 13:25:10] iter = 0050, loss = 20.0260
[2024-05-21 13:25:12] iter = 0060, loss = 16.8444
[2024-05-21 13:25:13] iter = 0070, loss = 18.4557
[2024-05-21 13:25:14] iter = 0080, loss = 17.8776
[2024-05-21 13:25:15] iter = 0090, loss = 13.8844
[2024-05-21 13:25:26] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.471601, train acc = 0.5667 train oa = 0.5667, test acc = 0.2696 test oa = 0.3062
Evaluate 1, mean = 0.2696 std = 0.0000
-------------------------
[2024-05-21 13:25:27] iter = 0100, loss = 16.3695
[2024-05-21 13:25:28] iter = 0110, loss = 16.0079
[2024-05-21 13:25:29] iter = 0120, loss = 16.6949
[2024-05-21 13:25:30] iter = 0130, loss = 13.0075
[2024-05-21 13:25:31] iter = 0140, loss = 15.8013
[2024-05-21 13:25:32] iter = 0150, loss = 13.6391
[2024-05-21 13:25:33] iter = 0160, loss = 12.7165
[2024-05-21 13:25:34] iter = 0170, loss = 13.7057
[2024-05-21 13:25:35] iter = 0180, loss = 14.1776
[2024-05-21 13:25:36] iter = 0190, loss = 12.1884
[2024-05-21 13:25:48] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.557535, train acc = 0.5000 train oa = 0.5000, test acc = 0.2397 test oa = 0.2751
Evaluate 1, mean = 0.2397 std = 0.0000
-------------------------
[2024-05-21 13:25:48] iter = 0200, loss = 15.1923
[2024-05-21 13:25:49] iter = 0210, loss = 16.4333
[2024-05-21 13:25:50] iter = 0220, loss = 14.1716
[2024-05-21 13:25:52] iter = 0230, loss = 13.6697
[2024-05-21 13:25:53] iter = 0240, loss = 12.2927
[2024-05-21 13:25:54] iter = 0250, loss = 11.8666
[2024-05-21 13:25:55] iter = 0260, loss = 13.1680
[2024-05-21 13:25:56] iter = 0270, loss = 17.1911
[2024-05-21 13:25:57] iter = 0280, loss = 13.1184
[2024-05-21 13:25:58] iter = 0290, loss = 13.0683
[2024-05-21 13:26:10] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.602117, train acc = 0.5200 train oa = 0.5200, test acc = 0.1492 test oa = 0.1765
Evaluate 1, mean = 0.1492 std = 0.0000
-------------------------
[2024-05-21 13:26:10] iter = 0300, loss = 12.7201
[2024-05-21 13:26:11] iter = 0310, loss = 14.9189
[2024-05-21 13:26:12] iter = 0320, loss = 14.9576
[2024-05-21 13:26:13] iter = 0330, loss = 14.2391
[2024-05-21 13:26:14] iter = 0340, loss = 11.9763
[2024-05-21 13:26:16] iter = 0350, loss = 14.7531
[2024-05-21 13:26:17] iter = 0360, loss = 13.0381
[2024-05-21 13:26:18] iter = 0370, loss = 12.2325
[2024-05-21 13:26:19] iter = 0380, loss = 13.1395
[2024-05-21 13:26:20] iter = 0390, loss = 11.8252
[2024-05-21 13:26:32] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.409444, train acc = 0.5867 train oa = 0.5867, test acc = 0.2689 test oa = 0.2699
Evaluate 1, mean = 0.2689 std = 0.0000
-------------------------
[2024-05-21 13:26:32] iter = 0400, loss = 13.3737
[2024-05-21 13:26:33] iter = 0410, loss = 13.1900
[2024-05-21 13:26:34] iter = 0420, loss = 11.2769
[2024-05-21 13:26:35] iter = 0430, loss = 12.7912
[2024-05-21 13:26:36] iter = 0440, loss = 12.0540
[2024-05-21 13:26:37] iter = 0450, loss = 15.8205
[2024-05-21 13:26:38] iter = 0460, loss = 11.3530
[2024-05-21 13:26:40] iter = 0470, loss = 11.4451
[2024-05-21 13:26:41] iter = 0480, loss = 11.7138
[2024-05-21 13:26:42] iter = 0490, loss = 15.1034
[2024-05-21 13:26:54] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.610937, train acc = 0.5000 train oa = 0.5000, test acc = 0.2947 test oa = 0.3062
Evaluate 1, mean = 0.2947 std = 0.0000
-------------------------
[2024-05-21 13:26:54] iter = 0500, loss = 14.3406
[2024-05-21 13:26:55] iter = 0510, loss = 13.6491
[2024-05-21 13:26:56] iter = 0520, loss = 12.1799
[2024-05-21 13:26:57] iter = 0530, loss = 12.4975
[2024-05-21 13:26:58] iter = 0540, loss = 12.1275
[2024-05-21 13:26:59] iter = 0550, loss = 10.0065
[2024-05-21 13:27:01] iter = 0560, loss = 13.4572
[2024-05-21 13:27:02] iter = 0570, loss = 16.6203
[2024-05-21 13:27:03] iter = 0580, loss = 13.2548
[2024-05-21 13:27:04] iter = 0590, loss = 10.9943
[2024-05-21 13:27:16] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.253162, train acc = 0.6667 train oa = 0.6667, test acc = 0.2874 test oa = 0.3010
Evaluate 1, mean = 0.2874 std = 0.0000
-------------------------
[2024-05-21 13:27:16] iter = 0600, loss = 13.1884
[2024-05-21 13:27:17] iter = 0610, loss = 10.5529
[2024-05-21 13:27:18] iter = 0620, loss = 12.1795
[2024-05-21 13:27:19] iter = 0630, loss = 11.8053
[2024-05-21 13:27:20] iter = 0640, loss = 11.3490
[2024-05-21 13:27:22] iter = 0650, loss = 13.0043
[2024-05-21 13:27:23] iter = 0660, loss = 9.7465
[2024-05-21 13:27:24] iter = 0670, loss = 10.4264
[2024-05-21 13:27:25] iter = 0680, loss = 9.8493
[2024-05-21 13:27:26] iter = 0690, loss = 10.4241
[2024-05-21 13:27:38] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.623810, train acc = 0.5400 train oa = 0.5400, test acc = 0.2564 test oa = 0.2543
Evaluate 1, mean = 0.2564 std = 0.0000
-------------------------
[2024-05-21 13:27:38] iter = 0700, loss = 12.7195
[2024-05-21 13:27:39] iter = 0710, loss = 11.8748
[2024-05-21 13:27:40] iter = 0720, loss = 14.2065
[2024-05-21 13:27:41] iter = 0730, loss = 12.2832
[2024-05-21 13:27:43] iter = 0740, loss = 11.3447
[2024-05-21 13:27:44] iter = 0750, loss = 10.2255
[2024-05-21 13:27:45] iter = 0760, loss = 10.3131
[2024-05-21 13:27:46] iter = 0770, loss = 14.1709
[2024-05-21 13:27:47] iter = 0780, loss = 9.9243
[2024-05-21 13:27:48] iter = 0790, loss = 12.0247
[2024-05-21 13:28:00] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.427464, train acc = 0.6133 train oa = 0.6133, test acc = 0.3325 test oa = 0.3651
Evaluate 1, mean = 0.3325 std = 0.0000
-------------------------
[2024-05-21 13:28:00] iter = 0800, loss = 11.6413
[2024-05-21 13:28:01] iter = 0810, loss = 9.8211
[2024-05-21 13:28:02] iter = 0820, loss = 11.7725
[2024-05-21 13:28:04] iter = 0830, loss = 11.0090
[2024-05-21 13:28:05] iter = 0840, loss = 11.5338
[2024-05-21 13:28:06] iter = 0850, loss = 14.0770
[2024-05-21 13:28:07] iter = 0860, loss = 10.0766
[2024-05-21 13:28:08] iter = 0870, loss = 10.5811
[2024-05-21 13:28:09] iter = 0880, loss = 11.3718
[2024-05-21 13:28:10] iter = 0890, loss = 10.1375
[2024-05-21 13:28:22] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.191737, train acc = 0.7200 train oa = 0.7200, test acc = 0.3998 test oa = 0.4204
Evaluate 1, mean = 0.3998 std = 0.0000
-------------------------
[2024-05-21 13:28:22] iter = 0900, loss = 9.1932
[2024-05-21 13:28:24] iter = 0910, loss = 9.7893
[2024-05-21 13:28:25] iter = 0920, loss = 12.5587
[2024-05-21 13:28:26] iter = 0930, loss = 11.4469
[2024-05-21 13:28:27] iter = 0940, loss = 11.3437
[2024-05-21 13:28:28] iter = 0950, loss = 13.0276
[2024-05-21 13:28:29] iter = 0960, loss = 10.2470
[2024-05-21 13:28:30] iter = 0970, loss = 11.5019
[2024-05-21 13:28:31] iter = 0980, loss = 10.0460
[2024-05-21 13:28:32] iter = 0990, loss = 10.3838
[2024-05-21 13:28:44] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.446067, train acc = 0.6333 train oa = 0.6333, test acc = 0.3608 test oa = 0.4014
Evaluate 1, mean = 0.3608 std = 0.0000
-------------------------
[2024-05-21 13:28:45] iter = 1000, loss = 11.4467
[2024-05-21 13:38:26] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.826971, train acc = 1.0000 train oa = 1.0000, test acc = 0.1531 test oa = 0.1505
[2024-05-21 13:38:29] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.785208, train acc = 1.0000 train oa = 1.0000, test acc = 0.1693 test oa = 0.1557
[2024-05-21 13:38:33] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.995271, train acc = 0.4000 train oa = 0.4000, test acc = 0.1408 test oa = 0.1038
[2024-05-21 13:36:10] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.097631, train acc = 1.0000 train oa = 1.0000, test acc = 0.1951 test oa = 0.1903
[2024-05-21 13:36:13] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.329083, train acc = 1.0000 train oa = 1.0000, test acc = 0.1959 test oa = 0.1678
[2024-05-21 13:36:17] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 1.154728, train acc = 1.0000 train oa = 1.0000, test acc = 0.1591 test oa = 0.1332
[2024-05-21 13:45:43] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.033747, train acc = 1.0000 train oa = 1.0000, test acc = 0.1896 test oa = 0.3045
[2024-05-21 13:45:46] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.153388, train acc = 1.0000 train oa = 1.0000, test acc = 0.2382 test oa = 0.2716
[2024-05-21 13:45:50] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.040876, train acc = 1.0000 train oa = 1.0000, test acc = 0.2120 test oa = 0.3114
[2024-05-21 13:37:24] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.060630, train acc = 0.3600 train oa = 0.3600, test acc = 0.1964 test oa = 0.2249
[2024-05-21 13:37:33] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.264340, train acc = 0.3733 train oa = 0.3733, test acc = 0.1985 test oa = 0.1799
[2024-05-21 13:37:42] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.098529, train acc = 0.4000 train oa = 0.4000, test acc = 0.2217 test oa = 0.1990
[2024-05-21 13:38:46] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.334994, train acc = 1.0000 train oa = 1.0000, test acc = 0.1485 test oa = 0.1471
[2024-05-21 13:38:49] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.139279, train acc = 1.0000 train oa = 1.0000, test acc = 0.1448 test oa = 0.1401
[2024-05-21 13:38:53] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.778207, train acc = 1.0000 train oa = 1.0000, test acc = 0.1818 test oa = 0.2111
[2024-05-21 13:40:09] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.499925, train acc = 0.2000 train oa = 0.2000, test acc = 0.1186 test oa = 0.1176
[2024-05-21 13:40:18] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.486301, train acc = 0.2933 train oa = 0.2933, test acc = 0.1449 test oa = 0.1505
[2024-05-21 13:40:27] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.108036, train acc = 0.2933 train oa = 0.2933, test acc = 0.1894 test oa = 0.2076
[2024-05-21 13:41:27] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.460371, train acc = 1.0000 train oa = 1.0000, test acc = 0.2003 test oa = 0.2301
[2024-05-21 13:41:30] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 2.226672, train acc = 0.8667 train oa = 0.8667, test acc = 0.0703 test oa = 0.1903
[2024-05-21 13:41:33] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.227613, train acc = 1.0000 train oa = 1.0000, test acc = 0.1176 test oa = 0.1211
[2024-05-21 13:42:53] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.451928, train acc = 0.2667 train oa = 0.2667, test acc = 0.1493 test oa = 0.1505
[2024-05-21 13:43:02] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.310750, train acc = 0.2933 train oa = 0.2933, test acc = 0.1705 test oa = 0.1799
[2024-05-21 13:43:11] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.071909, train acc = 0.4667 train oa = 0.4667, test acc = 0.1781 test oa = 0.2007
[2024-05-21 13:44:06] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.485196, train acc = 1.0000 train oa = 1.0000, test acc = 0.1386 test oa = 0.1332
[2024-05-21 13:44:09] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.794160, train acc = 1.0000 train oa = 1.0000, test acc = 0.1060 test oa = 0.1055
[2024-05-21 13:44:12] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 2.247834, train acc = 0.7333 train oa = 0.7333, test acc = 0.0788 test oa = 0.0433
[2024-05-21 13:52:52] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.125036, train acc = 1.0000 train oa = 1.0000, test acc = 0.1471 test oa = 0.1315
[2024-05-21 13:52:56] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.578471, train acc = 1.0000 train oa = 1.0000, test acc = 0.1586 test oa = 0.1557
[2024-05-21 13:53:00] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.108483, train acc = 1.0000 train oa = 1.0000, test acc = 0.1346 test oa = 0.1419
[2024-05-21 13:45:47] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.988245, train acc = 0.4800 train oa = 0.4800, test acc = 0.2348 test oa = 0.2474
[2024-05-21 13:45:56] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.501628, train acc = 0.2133 train oa = 0.2133, test acc = 0.1423 test oa = 0.1592
[2024-05-21 13:46:05] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.469646, train acc = 0.2667 train oa = 0.2667, test acc = 0.1734 test oa = 0.1592
[2024-05-21 13:46:48] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.462503, train acc = 1.0000 train oa = 1.0000, test acc = 0.1158 test oa = 0.1055
[2024-05-21 13:46:51] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.774294, train acc = 1.0000 train oa = 1.0000, test acc = 0.1488 test oa = 0.1349
[2024-05-21 13:46:54] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.324572, train acc = 1.0000 train oa = 1.0000, test acc = 0.1382 test oa = 0.1401
[2024-05-21 13:48:41] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.923187, train acc = 0.5200 train oa = 0.5200, test acc = 0.2728 test oa = 0.3045
[2024-05-21 13:48:50] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.413942, train acc = 0.3467 train oa = 0.3467, test acc = 0.1419 test oa = 0.1730
[2024-05-21 13:48:59] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.437960, train acc = 0.2800 train oa = 0.2800, test acc = 0.1686 test oa = 0.1817
[2024-05-21 13:49:31] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.115588, train acc = 1.0000 train oa = 1.0000, test acc = 0.1751 test oa = 0.1834
[2024-05-21 13:49:34] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 2.003805, train acc = 0.9333 train oa = 0.9333, test acc = 0.0726 test oa = 0.1938
[2024-05-21 13:49:37] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.218032, train acc = 1.0000 train oa = 1.0000, test acc = 0.1477 test oa = 0.1644
[2024-05-21 13:51:29] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.467376, train acc = 0.1867 train oa = 0.1867, test acc = 0.1518 test oa = 0.1367
[2024-05-21 13:51:38] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.993619, train acc = 0.3467 train oa = 0.3467, test acc = 0.1487 test oa = 0.1488
[2024-05-21 13:51:46] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.300637, train acc = 0.2800 train oa = 0.2800, test acc = 0.1609 test oa = 0.1384
[2024-05-21 13:52:13] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.096233, train acc = 1.0000 train oa = 1.0000, test acc = 0.1812 test oa = 0.1920
[2024-05-21 13:52:16] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.694391, train acc = 1.0000 train oa = 1.0000, test acc = 0.1040 test oa = 0.1246
[2024-05-21 13:52:19] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.084289, train acc = 1.0000 train oa = 1.0000, test acc = 0.1591 test oa = 0.1834
[2024-05-21 13:54:12] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.472363, train acc = 0.1733 train oa = 0.1733, test acc = 0.1516 test oa = 0.1765
[2024-05-21 13:54:21] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.301221, train acc = 0.2933 train oa = 0.2933, test acc = 0.1995 test oa = 0.1799
[2024-05-21 13:54:30] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.317801, train acc = 0.2933 train oa = 0.2933, test acc = 0.1664 test oa = 0.1592
[2024-05-21 13:54:59] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.080877, train acc = 1.0000 train oa = 1.0000, test acc = 0.2233 test oa = 0.2647
[2024-05-21 13:55:02] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.645925, train acc = 1.0000 train oa = 1.0000, test acc = 0.1850 test oa = 0.1817
[2024-05-21 13:55:05] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.103466, train acc = 1.0000 train oa = 1.0000, test acc = 0.1706 test oa = 0.1713
[2024-05-21 13:57:04] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.889673, train acc = 0.5200 train oa = 0.5200, test acc = 0.2746 test oa = 0.3028
[2024-05-21 13:57:13] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.274209, train acc = 0.3067 train oa = 0.3067, test acc = 0.2108 test oa = 0.1886
[2024-05-21 13:57:21] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.251285, train acc = 0.2933 train oa = 0.2933, test acc = 0.2100 test oa = 0.2336
[2024-05-21 13:57:35] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.284691, train acc = 1.0000 train oa = 1.0000, test acc = 0.1593 test oa = 0.1574
[2024-05-21 13:57:38] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.060719, train acc = 1.0000 train oa = 1.0000, test acc = 0.1893 test oa = 0.2059
[2024-05-21 13:57:42] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 1.587689, train acc = 1.0000 train oa = 1.0000, test acc = 0.0864 test oa = 0.0830
[2024-05-21 13:59:59] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.102049, train acc = 0.4000 train oa = 0.4000, test acc = 0.2746 test oa = 0.2993
[2024-05-21 14:00:08] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.465692, train acc = 0.2133 train oa = 0.2133, test acc = 0.1526 test oa = 0.1540
[2024-05-21 14:00:17] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.364687, train acc = 0.2800 train oa = 0.2800, test acc = 0.2265 test oa = 0.2595
[2024-05-21 14:00:25] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.451122, train acc = 1.0000 train oa = 1.0000, test acc = 0.2047 test oa = 0.2128
[2024-05-21 14:00:27] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 1.427461, train acc = 1.0000 train oa = 1.0000, test acc = 0.1208 test oa = 0.1038
[2024-05-21 14:00:31] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.444391, train acc = 1.0000 train oa = 1.0000, test acc = 0.1411 test oa = 0.1298
[2024-05-21 14:09:26] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.799719, train acc = 0.9200 train oa = 0.9200, test acc = 0.3492 test oa = 0.3287
[2024-05-21 14:09:33] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.901594, train acc = 0.9067 train oa = 0.9067, test acc = 0.3378 test oa = 0.3045
[2024-05-21 14:09:40] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.963780, train acc = 0.9067 train oa = 0.9067, test acc = 0.3369 test oa = 0.3045
[2024-05-21 14:02:35] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.149103, train acc = 0.2800 train oa = 0.2800, test acc = 0.1989 test oa = 0.1782
[2024-05-21 14:02:44] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.243165, train acc = 0.3333 train oa = 0.3333, test acc = 0.1622 test oa = 0.1851
[2024-05-21 14:02:52] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.020575, train acc = 0.3200 train oa = 0.3200, test acc = 0.1782 test oa = 0.1817
[2024-05-21 14:03:04] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.200006, train acc = 1.0000 train oa = 1.0000, test acc = 0.1598 test oa = 0.1782
[2024-05-21 14:03:06] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.114561, train acc = 1.0000 train oa = 1.0000, test acc = 0.1590 test oa = 0.1851
[2024-05-21 14:03:09] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 1.895427, train acc = 1.0000 train oa = 1.0000, test acc = 0.0688 test oa = 0.0329
[2024-05-21 14:05:03] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.434098, train acc = 0.2800 train oa = 0.2800, test acc = 0.1629 test oa = 0.1799
[2024-05-21 14:05:09] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.293001, train acc = 0.2533 train oa = 0.2533, test acc = 0.1646 test oa = 0.1644
[2024-05-21 14:05:15] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.425767, train acc = 0.2533 train oa = 0.2533, test acc = 0.1516 test oa = 0.1817
[2024-05-21 14:23:38] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.056497, train acc = 0.4133 train oa = 0.4133, test acc = 0.2118 test oa = 0.2232
[2024-05-21 14:23:47] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.478621, train acc = 0.2533 train oa = 0.2533, test acc = 0.1588 test oa = 0.1419
[2024-05-21 14:23:56] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.368454, train acc = 0.2800 train oa = 0.2800, test acc = 0.1606 test oa = 0.1522
[2024-05-21 14:31:09] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.514284, train acc = 1.0000 train oa = 1.0000, test acc = 0.1276 test oa = 0.1125
[2024-05-21 14:31:12] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.912415, train acc = 1.0000 train oa = 1.0000, test acc = 0.1782 test oa = 0.1920
[2024-05-21 14:31:15] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 2.378888, train acc = 0.2000 train oa = 0.2000, test acc = 0.1209 test oa = 0.0917
[2024-05-21 14:34:09] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 0.995410, train acc = 0.8200 train oa = 0.8200, test acc = 0.4407 test oa = 0.4377
[2024-05-21 14:34:22] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.046802, train acc = 0.7600 train oa = 0.7600, test acc = 0.3971 test oa = 0.4152
[2024-05-21 14:34:34] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 0.955615, train acc = 0.8133 train oa = 0.8133, test acc = 0.4640 test oa = 0.4602
[2024-05-21 14:38:22] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.054829, train acc = 1.0000 train oa = 1.0000, test acc = 0.1655 test oa = 0.2197
[2024-05-21 14:38:25] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.180010, train acc = 1.0000 train oa = 1.0000, test acc = 0.2165 test oa = 0.2111
[2024-05-21 14:38:29] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.080188, train acc = 1.0000 train oa = 1.0000, test acc = 0.1767 test oa = 0.2042
[2024-05-21 14:43:04] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.008126, train acc = 1.0000 train oa = 1.0000, test acc = 0.2343 test oa = 0.1938
[2024-05-21 14:43:07] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.028143, train acc = 1.0000 train oa = 1.0000, test acc = 0.2300 test oa = 0.2163
[2024-05-21 14:43:09] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.049528, train acc = 1.0000 train oa = 1.0000, test acc = 0.1893 test oa = 0.1920
[2024-05-21 14:45:36] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.034233, train acc = 1.0000 train oa = 1.0000, test acc = 0.1998 test oa = 0.2526
[2024-05-21 14:45:39] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.036845, train acc = 1.0000 train oa = 1.0000, test acc = 0.2093 test oa = 0.2630
[2024-05-21 14:45:42] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.051696, train acc = 1.0000 train oa = 1.0000, test acc = 0.1990 test oa = 0.1903
[2024-05-21 14:50:11] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.062350, train acc = 1.0000 train oa = 1.0000, test acc = 0.3028 test oa = 0.3270
[2024-05-21 14:50:15] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.047175, train acc = 1.0000 train oa = 1.0000, test acc = 0.2544 test oa = 0.2924
[2024-05-21 14:50:17] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.074160, train acc = 1.0000 train oa = 1.0000, test acc = 0.2944 test oa = 0.2993
[2024-05-21 14:57:22] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.022738, train acc = 1.0000 train oa = 1.0000, test acc = 0.2716 test oa = 0.2682
[2024-05-21 14:57:26] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.027973, train acc = 1.0000 train oa = 1.0000, test acc = 0.2726 test oa = 0.2958
[2024-05-21 14:57:29] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.024655, train acc = 1.0000 train oa = 1.0000, test acc = 0.2880 test oa = 0.3166
[2024-05-21 15:08:25] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.063582, train acc = 0.3667 train oa = 0.3667, test acc = 0.2225 test oa = 0.2301
[2024-05-21 15:08:38] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.154129, train acc = 0.3333 train oa = 0.3333, test acc = 0.2082 test oa = 0.2336
[2024-05-21 15:08:52] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.264523, train acc = 0.3133 train oa = 0.3133, test acc = 0.2044 test oa = 0.2076
[2024-05-21 15:37:12] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.067707, train acc = 1.0000 train oa = 1.0000, test acc = 0.2776 test oa = 0.2820
[2024-05-21 15:37:15] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.038157, train acc = 1.0000 train oa = 1.0000, test acc = 0.2814 test oa = 0.2872
[2024-05-21 15:37:18] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.045004, train acc = 1.0000 train oa = 1.0000, test acc = 0.2740 test oa = 0.3028
[2024-05-21 15:44:26] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.084863, train acc = 1.0000 train oa = 1.0000, test acc = 0.2428 test oa = 0.2163
[2024-05-21 15:44:29] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.121341, train acc = 1.0000 train oa = 1.0000, test acc = 0.2382 test oa = 0.2111
[2024-05-21 15:44:31] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.113565, train acc = 1.0000 train oa = 1.0000, test acc = 0.2486 test oa = 0.2145
[2024-05-21 16:02:04] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.885964, train acc = 1.0000 train oa = 1.0000, test acc = 0.1237 test oa = 0.1159
[2024-05-21 16:02:07] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 1.290578, train acc = 1.0000 train oa = 1.0000, test acc = 0.1396 test oa = 0.1401
[2024-05-21 16:02:10] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.972737, train acc = 0.9333 train oa = 0.9333, test acc = 0.1328 test oa = 0.1263
[2024-05-21 15:56:11] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.460887, train acc = 0.2533 train oa = 0.2533, test acc = 0.1161 test oa = 0.0917
[2024-05-21 15:56:22] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.051843, train acc = 0.4000 train oa = 0.4000, test acc = 0.2042 test oa = 0.2682
[2024-05-21 15:56:34] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.842946, train acc = 0.4533 train oa = 0.4533, test acc = 0.2461 test oa = 0.2526
[2024-05-21 15:58:20] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.546325, train acc = 0.2400 train oa = 0.2400, test acc = 0.1547 test oa = 0.1540
[2024-05-21 15:58:31] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.515210, train acc = 0.2333 train oa = 0.2333, test acc = 0.1624 test oa = 0.1609
[2024-05-21 15:58:43] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.467142, train acc = 0.2733 train oa = 0.2733, test acc = 0.1492 test oa = 0.1799
[2024-05-21 16:00:31] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.511775, train acc = 0.2067 train oa = 0.2067, test acc = 0.1349 test oa = 0.1626
[2024-05-21 16:09:12] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.383009, train acc = 1.0000 train oa = 1.0000, test acc = 0.2049 test oa = 0.1765
[2024-05-21 16:09:15] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.189692, train acc = 1.0000 train oa = 1.0000, test acc = 0.2147 test oa = 0.2543
[2024-05-21 16:09:19] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 1.896233, train acc = 1.0000 train oa = 1.0000, test acc = 0.1225 test oa = 0.1228
[2024-05-21 16:00:42] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.549183, train acc = 0.1867 train oa = 0.1867, test acc = 0.1331 test oa = 0.1384
[2024-05-21 16:00:54] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.327211, train acc = 0.2533 train oa = 0.2533, test acc = 0.1844 test oa = 0.2076
[2024-05-21 16:02:42] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.575098, train acc = 0.2200 train oa = 0.2200, test acc = 0.1350 test oa = 0.1488

================== Exp 0 ==================
 
[2024-05-21 16:02:47] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.042116, train acc = 1.0000 train oa = 1.0000, test acc = 0.0830 test oa = 0.0813
Evaluate 1, mean = 0.0830 std = 0.0000
-------------------------
[2024-05-21 16:02:47] iter = 0000, loss = 314.6273
[2024-05-21 16:02:48] iter = 0010, loss = 57.7074
[2024-05-21 16:02:49] iter = 0020, loss = 37.5462
[2024-05-21 16:02:49] iter = 0030, loss = 29.8162
[2024-05-21 16:02:50] iter = 0040, loss = 28.7089
[2024-05-21 16:02:50] iter = 0050, loss = 26.0882
[2024-05-21 16:02:51] iter = 0060, loss = 22.8075
[2024-05-21 16:02:51] iter = 0070, loss = 22.5433
[2024-05-21 16:02:52] iter = 0080, loss = 20.9451
[2024-05-21 16:02:52] iter = 0090, loss = 18.0051
[2024-05-21 16:02:53] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.502764, train acc = 0.2467 train oa = 0.2467, test acc = 0.1471 test oa = 0.1471
[2024-05-21 16:02:56] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.654602, train acc = 0.9867 train oa = 0.9867, test acc = 0.2079 test oa = 0.1903
Evaluate 1, mean = 0.2079 std = 0.0000
-------------------------
[2024-05-21 16:02:56] iter = 0100, loss = 22.3782
[2024-05-21 16:02:56] iter = 0110, loss = 21.1387
[2024-05-21 16:02:57] iter = 0120, loss = 21.5042
[2024-05-21 16:02:58] iter = 0130, loss = 19.7982
[2024-05-21 16:02:58] iter = 0140, loss = 19.4307
[2024-05-21 16:02:59] iter = 0150, loss = 16.9032
[2024-05-21 16:02:59] iter = 0160, loss = 17.7638

================== Exp 0 ==================
 
[2024-05-21 16:03:00] iter = 0170, loss = 18.5905
[2024-05-21 16:03:01] iter = 0180, loss = 17.4118
[2024-05-21 16:03:01] iter = 0190, loss = 16.1284
[2024-05-21 16:03:04] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.058925, train acc = 1.0000 train oa = 1.0000, test acc = 0.0599 test oa = 0.0588
Evaluate 1, mean = 0.0599 std = 0.0000
-------------------------
[2024-05-21 16:03:04] iter = 0000, loss = 288.6340
[2024-05-21 16:03:05] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.474652, train acc = 0.2267 train oa = 0.2267, test acc = 0.1399 test oa = 0.1644
[2024-05-21 16:03:06] iter = 0010, loss = 54.2094
[2024-05-21 16:03:07] Evaluate_00: epoch = 0300, train time = 4 s, train loss = 1.017519, train acc = 0.8800 train oa = 0.8800, test acc = 0.1755 test oa = 0.1972
Evaluate 1, mean = 0.1755 std = 0.0000
-------------------------
[2024-05-21 16:03:07] iter = 0020, loss = 35.9590
[2024-05-21 16:03:07] iter = 0200, loss = 19.2060
[2024-05-21 16:03:08] iter = 0030, loss = 28.7662
[2024-05-21 16:03:08] iter = 0210, loss = 19.3579
[2024-05-21 16:03:09] iter = 0040, loss = 26.9424
[2024-05-21 16:03:09] iter = 0220, loss = 19.7890
[2024-05-21 16:03:09] iter = 0050, loss = 25.0311
[2024-05-21 16:03:10] iter = 0230, loss = 16.1024
[2024-05-21 16:03:10] iter = 0060, loss = 22.6260
[2024-05-21 16:03:10] iter = 0240, loss = 14.5870
[2024-05-21 16:03:11] iter = 0070, loss = 23.4345
[2024-05-21 16:03:11] iter = 0250, loss = 17.4052
[2024-05-21 16:03:12] iter = 0080, loss = 21.2969
[2024-05-21 16:03:12] iter = 0260, loss = 16.7908
[2024-05-21 16:03:13] iter = 0090, loss = 18.8298
[2024-05-21 16:03:13] iter = 0270, loss = 17.9579
[2024-05-21 16:03:14] iter = 0280, loss = 14.5016
[2024-05-21 16:03:15] iter = 0290, loss = 16.8694
[2024-05-21 16:03:16] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.370261, train acc = 1.0000 train oa = 1.0000, test acc = 0.2298 test oa = 0.1869
Evaluate 1, mean = 0.2298 std = 0.0000
-------------------------
[2024-05-21 16:03:16] iter = 0100, loss = 23.5388
[2024-05-21 16:03:17] iter = 0110, loss = 19.8477
[2024-05-21 16:03:19] iter = 0120, loss = 21.0169
[2024-05-21 16:03:20] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.546320, train acc = 1.0000 train oa = 1.0000, test acc = 0.1354 test oa = 0.1522
Evaluate 1, mean = 0.1354 std = 0.0000
-------------------------
[2024-05-21 16:03:20] iter = 0300, loss = 14.4106
[2024-05-21 16:03:20] iter = 0130, loss = 20.2882
[2024-05-21 16:03:21] iter = 0310, loss = 18.9458
[2024-05-21 16:03:21] iter = 0140, loss = 18.9427
[2024-05-21 16:03:22] iter = 0320, loss = 16.9919
[2024-05-21 16:03:22] iter = 0150, loss = 17.2944
[2024-05-21 16:03:22] iter = 0330, loss = 21.0026
[2024-05-21 16:03:22] iter = 0160, loss = 17.2650
[2024-05-21 16:03:23] iter = 0340, loss = 16.6364
[2024-05-21 16:03:23] iter = 0170, loss = 17.6755
[2024-05-21 16:03:24] iter = 0350, loss = 18.0704
[2024-05-21 16:03:24] iter = 0180, loss = 16.5573
[2024-05-21 16:03:25] iter = 0360, loss = 15.9232
[2024-05-21 16:03:25] iter = 0190, loss = 15.9579
[2024-05-21 16:03:26] iter = 0370, loss = 15.0025
[2024-05-21 16:03:27] iter = 0380, loss = 15.4964
[2024-05-21 16:03:28] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.496458, train acc = 0.9867 train oa = 0.9867, test acc = 0.1652 test oa = 0.2024
Evaluate 1, mean = 0.1652 std = 0.0000
-------------------------
[2024-05-21 16:03:28] iter = 0200, loss = 19.0350
[2024-05-21 16:03:28] iter = 0390, loss = 14.8507
[2024-05-21 16:03:29] iter = 0210, loss = 19.2685
[2024-05-21 16:03:30] iter = 0220, loss = 18.9726
[2024-05-21 16:03:32] iter = 0230, loss = 16.3461
[2024-05-21 16:03:33] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.049945, train acc = 0.7467 train oa = 0.7467, test acc = 0.1782 test oa = 0.1799
Evaluate 1, mean = 0.1782 std = 0.0000
-------------------------
[2024-05-21 16:03:33] iter = 0400, loss = 16.9882
[2024-05-21 16:03:33] iter = 0240, loss = 14.8204
[2024-05-21 16:03:34] iter = 0410, loss = 15.1365
[2024-05-21 16:03:34] iter = 0250, loss = 18.0261
[2024-05-21 16:03:35] iter = 0420, loss = 16.1218
[2024-05-21 16:03:35] iter = 0260, loss = 16.8605
[2024-05-21 16:03:35] iter = 0430, loss = 14.6777
[2024-05-21 16:03:35] iter = 0270, loss = 18.8767
[2024-05-21 16:03:36] iter = 0440, loss = 14.7070
[2024-05-21 16:03:36] iter = 0280, loss = 16.0948
[2024-05-21 16:03:37] iter = 0450, loss = 14.8653
[2024-05-21 16:03:37] iter = 0290, loss = 15.6109
[2024-05-21 16:03:38] iter = 0460, loss = 13.8066
[2024-05-21 16:03:39] iter = 0470, loss = 14.5350
[2024-05-21 16:03:40] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.721162, train acc = 0.9600 train oa = 0.9600, test acc = 0.1475 test oa = 0.1592
Evaluate 1, mean = 0.1475 std = 0.0000
-------------------------
[2024-05-21 16:03:40] iter = 0300, loss = 14.2565
[2024-05-21 16:03:41] iter = 0480, loss = 14.3686
[2024-05-21 16:03:41] iter = 0310, loss = 18.5304
[2024-05-21 16:03:41] iter = 0490, loss = 17.2608
[2024-05-21 16:03:42] iter = 0320, loss = 17.5866
[2024-05-21 16:03:43] iter = 0330, loss = 20.1818
[2024-05-21 16:03:45] iter = 0340, loss = 16.5164
[2024-05-21 16:03:46] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.094937, train acc = 0.7733 train oa = 0.7733, test acc = 0.2908 test oa = 0.2682
Evaluate 1, mean = 0.2908 std = 0.0000
-------------------------
[2024-05-21 16:03:46] iter = 0500, loss = 17.0053
[2024-05-21 16:03:46] iter = 0350, loss = 17.1326
[2024-05-21 16:03:47] iter = 0510, loss = 14.8826
[2024-05-21 16:03:47] iter = 0360, loss = 15.3235
[2024-05-21 16:03:48] iter = 0520, loss = 18.1122
[2024-05-21 16:03:48] iter = 0370, loss = 14.7313
[2024-05-21 16:03:48] iter = 0530, loss = 13.3624
[2024-05-21 16:03:49] iter = 0380, loss = 14.9386
[2024-05-21 16:03:49] iter = 0540, loss = 14.2646
[2024-05-21 16:03:49] iter = 0390, loss = 15.3175
[2024-05-21 16:03:50] iter = 0550, loss = 13.2962
[2024-05-21 16:03:52] iter = 0560, loss = 16.9757
[2024-05-21 16:03:53] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.582818, train acc = 1.0000 train oa = 1.0000, test acc = 0.3066 test oa = 0.2543
Evaluate 1, mean = 0.3066 std = 0.0000
-------------------------
[2024-05-21 16:03:53] iter = 0400, loss = 17.8572
[2024-05-21 16:03:53] iter = 0570, loss = 19.1553
[2024-05-21 16:03:53] iter = 0410, loss = 16.1851
[2024-05-21 16:03:54] iter = 0580, loss = 15.4412
[2024-05-21 16:03:54] iter = 0420, loss = 15.8015
[2024-05-21 16:03:54] iter = 0590, loss = 14.8208
[2024-05-21 16:03:55] iter = 0430, loss = 15.0870
[2024-05-21 16:03:57] iter = 0440, loss = 15.5348
[2024-05-21 16:03:58] iter = 0450, loss = 15.0338
[2024-05-21 16:03:59] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.885408, train acc = 0.9067 train oa = 0.9067, test acc = 0.3262 test oa = 0.2924
Evaluate 1, mean = 0.3262 std = 0.0000
-------------------------
[2024-05-21 16:03:59] iter = 0600, loss = 15.0393
[2024-05-21 16:03:59] iter = 0460, loss = 13.4303
[2024-05-21 16:04:00] iter = 0610, loss = 13.4085
[2024-05-21 16:04:00] iter = 0470, loss = 14.6847
[2024-05-21 16:04:01] iter = 0620, loss = 17.0698
[2024-05-21 16:04:01] iter = 0480, loss = 14.3970
[2024-05-21 16:04:01] iter = 0630, loss = 13.8921
[2024-05-21 16:04:02] iter = 0490, loss = 17.5486
[2024-05-21 16:04:02] iter = 0640, loss = 14.7696
[2024-05-21 16:04:04] iter = 0650, loss = 16.7302
[2024-05-21 16:04:05] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.509929, train acc = 0.9867 train oa = 0.9867, test acc = 0.3183 test oa = 0.2526
Evaluate 1, mean = 0.3183 std = 0.0000
-------------------------
[2024-05-21 16:04:05] iter = 0500, loss = 16.3876
[2024-05-21 16:04:05] iter = 0660, loss = 12.6087
[2024-05-21 16:04:06] iter = 0510, loss = 14.8627
[2024-05-21 16:04:06] iter = 0670, loss = 13.9268
[2024-05-21 16:04:07] iter = 0520, loss = 17.6714
[2024-05-21 16:04:07] iter = 0680, loss = 13.3476
[2024-05-21 16:04:07] iter = 0530, loss = 13.1816
[2024-05-21 16:04:07] iter = 0690, loss = 14.0379
[2024-05-21 16:04:08] iter = 0540, loss = 14.6212
[2024-05-21 16:04:10] iter = 0550, loss = 13.5233
[2024-05-21 16:04:11] iter = 0560, loss = 17.5604
[2024-05-21 16:04:12] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.662736, train acc = 0.9733 train oa = 0.9733, test acc = 0.3416 test oa = 0.3737
Evaluate 1, mean = 0.3416 std = 0.0000
-------------------------
[2024-05-21 16:04:12] iter = 0700, loss = 15.6516
[2024-05-21 16:04:12] iter = 0570, loss = 18.6519
[2024-05-21 16:04:13] iter = 0710, loss = 15.1679
[2024-05-21 16:04:13] iter = 0580, loss = 15.2906
[2024-05-21 16:04:14] iter = 0720, loss = 16.2679
[2024-05-21 16:04:14] iter = 0590, loss = 14.9450
[2024-05-21 16:04:14] iter = 0730, loss = 14.7415
[2024-05-21 16:04:16] iter = 0740, loss = 14.9945
[2024-05-21 16:04:17] iter = 0750, loss = 15.1319
[2024-05-21 16:04:17] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.679745, train acc = 0.9333 train oa = 0.9333, test acc = 0.3559 test oa = 0.3201
Evaluate 1, mean = 0.3559 std = 0.0000
-------------------------
[2024-05-21 16:04:17] iter = 0600, loss = 14.4292
[2024-05-21 16:04:18] iter = 0760, loss = 14.9398
[2024-05-21 16:04:18] iter = 0610, loss = 13.3472
[2024-05-21 16:04:19] iter = 0770, loss = 17.1434
[2024-05-21 16:04:19] iter = 0620, loss = 16.7620
[2024-05-21 16:04:20] iter = 0780, loss = 12.9621
[2024-05-21 16:04:20] iter = 0630, loss = 14.3535
[2024-05-21 16:04:20] iter = 0790, loss = 14.7031
[2024-05-21 16:04:21] iter = 0640, loss = 15.3793
[2024-05-21 16:04:22] iter = 0650, loss = 16.5946
[2024-05-21 16:04:23] iter = 0660, loss = 13.0642
[2024-05-21 16:04:25] iter = 0670, loss = 13.5372
[2024-05-21 16:04:25] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.897563, train acc = 0.8933 train oa = 0.8933, test acc = 0.3762 test oa = 0.3806
Evaluate 1, mean = 0.3762 std = 0.0000
-------------------------
[2024-05-21 16:04:25] iter = 0800, loss = 17.0599
[2024-05-21 16:04:26] iter = 0680, loss = 13.6412
[2024-05-21 16:04:26] iter = 0810, loss = 12.9949
[2024-05-21 16:04:26] iter = 0690, loss = 14.6043
[2024-05-21 16:04:27] iter = 0820, loss = 16.9057
[2024-05-21 16:04:28] iter = 0830, loss = 14.6537
[2024-05-21 16:04:30] iter = 0840, loss = 16.4064
[2024-05-21 16:04:30] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.791480, train acc = 0.8800 train oa = 0.8800, test acc = 0.3874 test oa = 0.3875
Evaluate 1, mean = 0.3874 std = 0.0000
-------------------------
[2024-05-21 16:04:30] iter = 0700, loss = 14.5710
[2024-05-21 16:04:31] iter = 0850, loss = 17.2360
[2024-05-21 16:04:31] iter = 0710, loss = 14.6133
[2024-05-21 16:04:31] iter = 0860, loss = 13.0588
[2024-05-21 16:04:32] iter = 0720, loss = 15.4859
[2024-05-21 16:04:32] iter = 0870, loss = 13.8161
[2024-05-21 16:04:32] iter = 0730, loss = 15.2625
[2024-05-21 16:04:33] iter = 0880, loss = 13.8871
[2024-05-21 16:04:33] iter = 0740, loss = 14.4309
[2024-05-21 16:04:34] iter = 0890, loss = 14.4742
[2024-05-21 16:04:34] iter = 0750, loss = 15.1900
[2024-05-21 16:04:35] iter = 0760, loss = 15.1299
[2024-05-21 16:04:36] iter = 0770, loss = 17.3829
[2024-05-21 16:04:38] iter = 0780, loss = 13.0229
[2024-05-21 16:04:38] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.935998, train acc = 0.8400 train oa = 0.8400, test acc = 0.3729 test oa = 0.3841
Evaluate 1, mean = 0.3729 std = 0.0000
-------------------------
[2024-05-21 16:04:38] iter = 0900, loss = 12.9753
[2024-05-21 16:04:39] iter = 0790, loss = 14.5792
[2024-05-21 16:04:39] iter = 0910, loss = 13.1575
[2024-05-21 16:04:41] iter = 0920, loss = 14.0277
[2024-05-21 16:04:42] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.731565, train acc = 0.9200 train oa = 0.9200, test acc = 0.3661 test oa = 0.3616
Evaluate 1, mean = 0.3661 std = 0.0000
-------------------------
[2024-05-21 16:04:42] iter = 0800, loss = 17.1638
[2024-05-21 16:04:42] iter = 0930, loss = 12.9960
[2024-05-21 16:04:43] iter = 0810, loss = 13.3254
[2024-05-21 16:04:43] iter = 0940, loss = 14.8029
[2024-05-21 16:04:44] iter = 0820, loss = 16.5613
[2024-05-21 16:04:44] iter = 0950, loss = 16.0593
[2024-05-21 16:04:45] iter = 0830, loss = 14.4793
[2024-05-21 16:04:45] iter = 0960, loss = 13.6701
[2024-05-21 16:04:45] iter = 0840, loss = 15.8677
[2024-05-21 16:04:45] iter = 0970, loss = 12.4911
[2024-05-21 16:04:46] iter = 0850, loss = 17.7551
[2024-05-21 16:04:46] iter = 0980, loss = 12.7067
[2024-05-21 16:04:47] iter = 0860, loss = 12.9893
[2024-05-21 16:04:47] iter = 0990, loss = 15.1115
[2024-05-21 16:04:48] iter = 0870, loss = 13.7875
[2024-05-21 16:04:49] iter = 0880, loss = 14.4342
[2024-05-21 16:04:51] iter = 0890, loss = 14.3883
[2024-05-21 16:04:52] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.944023, train acc = 0.8400 train oa = 0.8400, test acc = 0.3953 test oa = 0.4014
Evaluate 1, mean = 0.3953 std = 0.0000
-------------------------
[2024-05-21 16:04:52] iter = 1000, loss = 13.9854
[2024-05-21 16:04:54] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.859298, train acc = 0.8533 train oa = 0.8533, test acc = 0.3968 test oa = 0.3824
Evaluate 1, mean = 0.3968 std = 0.0000
-------------------------
[2024-05-21 16:04:54] iter = 0900, loss = 13.1248
[2024-05-21 16:04:54] iter = 0910, loss = 13.5340
[2024-05-21 16:04:55] iter = 0920, loss = 14.1743
[2024-05-21 16:04:55] iter = 0930, loss = 13.1558
[2024-05-21 16:04:56] iter = 0940, loss = 15.1736
[2024-05-21 16:04:56] iter = 0950, loss = 15.8689
[2024-05-21 16:04:56] iter = 0960, loss = 13.8359
[2024-05-21 16:04:57] iter = 0970, loss = 12.8914
[2024-05-21 16:04:57] iter = 0980, loss = 13.0881
[2024-05-21 16:04:58] iter = 0990, loss = 14.1239
[2024-05-21 16:05:00] Evaluate_00: epoch = 0300, train time = 2 s, train loss = 0.626636, train acc = 0.9733 train oa = 0.9733, test acc = 0.3920 test oa = 0.3945
Evaluate 1, mean = 0.3920 std = 0.0000
-------------------------
[2024-05-21 16:05:00] iter = 1000, loss = 14.4985
[2024-05-21 16:05:09] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.401839, train acc = 0.2933 train oa = 0.2933, test acc = 0.1794 test oa = 0.1626
[2024-05-21 16:05:21] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.972833, train acc = 0.4133 train oa = 0.4133, test acc = 0.2551 test oa = 0.3028
[2024-05-21 16:05:32] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.946033, train acc = 0.4600 train oa = 0.4600, test acc = 0.3067 test oa = 0.3097
[2024-05-21 16:14:32] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.386325, train acc = 0.6267 train oa = 0.6267, test acc = 0.3521 test oa = 0.3322
[2024-05-21 16:14:43] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.279079, train acc = 0.6667 train oa = 0.6667, test acc = 0.3588 test oa = 0.3201
[2024-05-21 16:14:55] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.260817, train acc = 0.6400 train oa = 0.6400, test acc = 0.3653 test oa = 0.3443
[2024-05-21 16:07:34] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.489573, train acc = 0.2933 train oa = 0.2933, test acc = 0.1703 test oa = 0.1384
[2024-05-21 16:07:46] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.263942, train acc = 0.3467 train oa = 0.3467, test acc = 0.2355 test oa = 0.2457
[2024-05-21 16:16:27] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.033747, train acc = 1.0000 train oa = 1.0000, test acc = 0.1896 test oa = 0.3045
[2024-05-21 16:16:30] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.153388, train acc = 1.0000 train oa = 1.0000, test acc = 0.2382 test oa = 0.2716
[2024-05-21 16:16:34] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.040876, train acc = 1.0000 train oa = 1.0000, test acc = 0.2120 test oa = 0.3114
[2024-05-21 16:07:57] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.332755, train acc = 0.3333 train oa = 0.3333, test acc = 0.1793 test oa = 0.1817
[2024-05-21 16:09:45] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.483703, train acc = 0.3133 train oa = 0.3133, test acc = 0.1672 test oa = 0.1661
[2024-05-21 16:09:57] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.543901, train acc = 0.2200 train oa = 0.2200, test acc = 0.1597 test oa = 0.1592
[2024-05-21 16:10:08] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.465257, train acc = 0.3067 train oa = 0.3067, test acc = 0.1695 test oa = 0.1592
[2024-05-21 16:12:17] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.500270, train acc = 0.2067 train oa = 0.2067, test acc = 0.1607 test oa = 0.1505
[2024-05-21 16:12:29] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.395702, train acc = 0.2600 train oa = 0.2600, test acc = 0.1958 test oa = 0.1834
[2024-05-21 16:12:40] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.285761, train acc = 0.3400 train oa = 0.3400, test acc = 0.2357 test oa = 0.2232
[2024-05-21 16:23:40] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 1.125036, train acc = 1.0000 train oa = 1.0000, test acc = 0.1471 test oa = 0.1315
[2024-05-21 16:23:42] Evaluate_01: epoch = 0300, train time = 2 s, train loss = 0.578471, train acc = 1.0000 train oa = 1.0000, test acc = 0.1586 test oa = 0.1557
[2024-05-21 16:23:45] Evaluate_02: epoch = 0300, train time = 2 s, train loss = 0.108483, train acc = 1.0000 train oa = 1.0000, test acc = 0.1346 test oa = 0.1419
[2024-05-21 16:15:22] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.519236, train acc = 0.2333 train oa = 0.2333, test acc = 0.1449 test oa = 0.1246
[2024-05-21 16:15:34] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.345223, train acc = 0.2867 train oa = 0.2867, test acc = 0.2197 test oa = 0.2249
[2024-05-21 16:15:45] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.370533, train acc = 0.3200 train oa = 0.3200, test acc = 0.2013 test oa = 0.1886
[2024-05-21 16:29:29] Evaluate_00: epoch = 0300, train time = 3 s, train loss = 0.128745, train acc = 1.0000 train oa = 1.0000, test acc = 0.1807 test oa = 0.2301
[2024-05-21 16:29:32] Evaluate_01: epoch = 0300, train time = 3 s, train loss = 0.177126, train acc = 1.0000 train oa = 1.0000, test acc = 0.1654 test oa = 0.1990
[2024-05-21 16:29:36] Evaluate_02: epoch = 0300, train time = 3 s, train loss = 0.030811, train acc = 1.0000 train oa = 1.0000, test acc = 0.1617 test oa = 0.2128
[2024-05-21 16:27:53] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.484089, train acc = 0.5733 train oa = 0.5733, test acc = 0.3461 test oa = 0.3201
[2024-05-21 16:28:04] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.571746, train acc = 0.5333 train oa = 0.5333, test acc = 0.3482 test oa = 0.3131
[2024-05-21 16:28:14] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.520675, train acc = 0.5600 train oa = 0.5600, test acc = 0.3302 test oa = 0.2664
[2024-05-21 16:30:11] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.420156, train acc = 0.6333 train oa = 0.6333, test acc = 0.3539 test oa = 0.3253
[2024-05-21 16:30:22] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.400580, train acc = 0.5933 train oa = 0.5933, test acc = 0.3425 test oa = 0.3253
[2024-05-21 16:30:32] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.410318, train acc = 0.6267 train oa = 0.6267, test acc = 0.3913 test oa = 0.3754
[2024-05-21 16:32:15] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.095221, train acc = 0.7000 train oa = 0.7000, test acc = 0.3909 test oa = 0.3685
[2024-05-21 16:32:26] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.370864, train acc = 0.5933 train oa = 0.5933, test acc = 0.3500 test oa = 0.3287
[2024-05-21 16:32:37] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.222142, train acc = 0.6933 train oa = 0.6933, test acc = 0.3735 test oa = 0.3356
[2024-05-21 16:34:21] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.521385, train acc = 0.5600 train oa = 0.5600, test acc = 0.3034 test oa = 0.2699
[2024-05-21 16:34:32] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.567811, train acc = 0.5333 train oa = 0.5333, test acc = 0.3028 test oa = 0.2682
[2024-05-21 16:34:43] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.388000, train acc = 0.6600 train oa = 0.6600, test acc = 0.3722 test oa = 0.3443
[2024-05-21 16:36:26] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.150814, train acc = 0.6867 train oa = 0.6867, test acc = 0.3917 test oa = 0.3806
[2024-05-21 16:36:37] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.345137, train acc = 0.6000 train oa = 0.6000, test acc = 0.3628 test oa = 0.3235
[2024-05-21 16:36:48] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.492641, train acc = 0.5600 train oa = 0.5600, test acc = 0.3432 test oa = 0.3235
[2024-05-21 16:38:47] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.541159, train acc = 0.5933 train oa = 0.5933, test acc = 0.3557 test oa = 0.3183
[2024-05-21 16:38:58] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.493153, train acc = 0.5533 train oa = 0.5533, test acc = 0.3314 test oa = 0.3028
[2024-05-21 16:39:09] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.508747, train acc = 0.5867 train oa = 0.5867, test acc = 0.3356 test oa = 0.3183
[2024-05-21 16:40:52] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.349412, train acc = 0.6333 train oa = 0.6333, test acc = 0.3698 test oa = 0.3426
[2024-05-21 16:41:03] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.450668, train acc = 0.5933 train oa = 0.5933, test acc = 0.3735 test oa = 0.3304
[2024-05-21 16:41:14] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.609005, train acc = 0.5200 train oa = 0.5200, test acc = 0.3263 test oa = 0.2837
[2024-05-21 16:43:13] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.236893, train acc = 0.7067 train oa = 0.7067, test acc = 0.4104 test oa = 0.4135
[2024-05-21 16:43:24] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.399447, train acc = 0.6267 train oa = 0.6267, test acc = 0.3845 test oa = 0.3979
[2024-05-21 16:43:35] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.182201, train acc = 0.7267 train oa = 0.7267, test acc = 0.4120 test oa = 0.4152
[2024-05-21 16:45:42] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.347642, train acc = 0.6667 train oa = 0.6667, test acc = 0.3610 test oa = 0.3564
[2024-05-21 16:45:53] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.570541, train acc = 0.5467 train oa = 0.5467, test acc = 0.3353 test oa = 0.3460
[2024-05-21 16:46:04] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.241949, train acc = 0.7200 train oa = 0.7200, test acc = 0.3996 test oa = 0.3806
[2024-05-21 16:48:14] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.363880, train acc = 0.6333 train oa = 0.6333, test acc = 0.3782 test oa = 0.3443
[2024-05-21 16:48:25] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.326177, train acc = 0.6733 train oa = 0.6733, test acc = 0.3458 test oa = 0.3478
[2024-05-21 16:48:36] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.122257, train acc = 0.7533 train oa = 0.7533, test acc = 0.3904 test oa = 0.3564
[2024-05-21 16:50:33] Evaluate_00: epoch = 0300, train time = 10 s, train loss = 1.311863, train acc = 0.6533 train oa = 0.6533, test acc = 0.3833 test oa = 0.4152
[2024-05-21 16:50:44] Evaluate_01: epoch = 0300, train time = 10 s, train loss = 1.486336, train acc = 0.5733 train oa = 0.5733, test acc = 0.3538 test oa = 0.3772
[2024-05-21 16:50:55] Evaluate_02: epoch = 0300, train time = 10 s, train loss = 1.390177, train acc = 0.6133 train oa = 0.6133, test acc = 0.3958 test oa = 0.3997
[2024-05-21 17:53:02] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.883098, train acc = 0.9600 train oa = 0.9600, test acc = 0.3444 test oa = 0.3547
[2024-05-21 17:53:08] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.974284, train acc = 0.8667 train oa = 0.8667, test acc = 0.3506 test oa = 0.3512
[2024-05-21 17:53:14] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.910586, train acc = 0.9600 train oa = 0.9600, test acc = 0.3300 test oa = 0.3183
[2024-05-21 18:13:17] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 0.648605, train acc = 0.9267 train oa = 0.9267, test acc = 0.3810 test oa = 0.3633
[2024-05-21 18:13:29] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 0.897492, train acc = 0.8000 train oa = 0.8000, test acc = 0.3967 test oa = 0.3737
[2024-05-21 18:13:41] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.133816, train acc = 0.7333 train oa = 0.7333, test acc = 0.3793 test oa = 0.3512
[2024-05-21 18:49:56] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.005341, train acc = 0.3600 train oa = 0.3600, test acc = 0.1808 test oa = 0.1869
[2024-05-21 18:50:03] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.184047, train acc = 0.2933 train oa = 0.2933, test acc = 0.1848 test oa = 0.1869
[2024-05-21 18:50:11] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.437510, train acc = 0.3333 train oa = 0.3333, test acc = 0.1504 test oa = 0.1574
[2024-05-21 19:24:00] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.859924, train acc = 0.9200 train oa = 0.9200, test acc = 0.3403 test oa = 0.3166
[2024-05-21 19:24:07] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.878716, train acc = 0.8933 train oa = 0.8933, test acc = 0.3659 test oa = 0.3339
[2024-05-21 19:24:14] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.829120, train acc = 0.9200 train oa = 0.9200, test acc = 0.3773 test oa = 0.3426
[2024-05-21 19:50:08] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.234710, train acc = 0.2867 train oa = 0.2867, test acc = 0.1932 test oa = 0.2163
[2024-05-21 19:50:21] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.357746, train acc = 0.3067 train oa = 0.3067, test acc = 0.1843 test oa = 0.1869
[2024-05-21 19:50:33] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.159115, train acc = 0.3733 train oa = 0.3733, test acc = 0.2206 test oa = 0.2578
[2024-05-21 20:36:30] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.047564, train acc = 0.3600 train oa = 0.3600, test acc = 0.1721 test oa = 0.1903
[2024-05-21 20:36:38] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.141688, train acc = 0.2667 train oa = 0.2667, test acc = 0.1564 test oa = 0.1211
[2024-05-21 20:36:46] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.003380, train acc = 0.3467 train oa = 0.3467, test acc = 0.1660 test oa = 0.1626
[2024-05-21 21:36:53] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.080118, train acc = 0.7600 train oa = 0.7600, test acc = 0.3798 test oa = 0.3633
[2024-05-21 21:37:05] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.214289, train acc = 0.7400 train oa = 0.7400, test acc = 0.3486 test oa = 0.3512
[2024-05-21 21:37:17] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.136581, train acc = 0.7333 train oa = 0.7333, test acc = 0.3663 test oa = 0.3599
[2024-05-21 22:27:24] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 1.141063, train acc = 0.8000 train oa = 0.8000, test acc = 0.3325 test oa = 0.3131
[2024-05-21 22:27:30] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 1.244003, train acc = 0.7733 train oa = 0.7733, test acc = 0.3465 test oa = 0.3149
[2024-05-21 22:27:37] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.163920, train acc = 0.7867 train oa = 0.7867, test acc = 0.3411 test oa = 0.3166
[2024-05-21 23:23:56] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.787684, train acc = 0.4800 train oa = 0.4800, test acc = 0.2749 test oa = 0.2630
[2024-05-21 23:24:08] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.097134, train acc = 0.3400 train oa = 0.3400, test acc = 0.2041 test oa = 0.1903
[2024-05-21 23:24:21] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.307827, train acc = 0.3400 train oa = 0.3400, test acc = 0.1934 test oa = 0.1903
[2024-05-22 02:04:30] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.086269, train acc = 0.3600 train oa = 0.3600, test acc = 0.1879 test oa = 0.1886
[2024-05-22 02:04:39] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.300514, train acc = 0.2533 train oa = 0.2533, test acc = 0.1750 test oa = 0.1522
[2024-05-22 02:04:47] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.201972, train acc = 0.3067 train oa = 0.3067, test acc = 0.1725 test oa = 0.1592
[2024-05-22 02:48:25] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.236491, train acc = 0.7067 train oa = 0.7067, test acc = 0.3911 test oa = 0.3858
[2024-05-22 02:48:38] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 1.344853, train acc = 0.6667 train oa = 0.6667, test acc = 0.3290 test oa = 0.3270
[2024-05-22 02:48:51] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.324513, train acc = 0.6733 train oa = 0.6733, test acc = 0.3758 test oa = 0.3633
[2024-05-22 03:36:33] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.488745, train acc = 0.2000 train oa = 0.2000, test acc = 0.1211 test oa = 0.1038
[2024-05-22 03:36:35] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.984690, train acc = 0.4133 train oa = 0.4133, test acc = 0.1911 test oa = 0.1990
[2024-05-22 03:36:43] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 2.468463, train acc = 0.2800 train oa = 0.2800, test acc = 0.1532 test oa = 0.1419
[2024-05-22 03:36:43] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.315425, train acc = 0.2933 train oa = 0.2933, test acc = 0.1809 test oa = 0.1730
[2024-05-22 03:36:52] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.428844, train acc = 0.2933 train oa = 0.2933, test acc = 0.1676 test oa = 0.1453
[2024-05-22 03:36:52] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.264177, train acc = 0.2667 train oa = 0.2667, test acc = 0.1843 test oa = 0.1661
[2024-05-22 04:24:36] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.412000, train acc = 0.3467 train oa = 0.3467, test acc = 0.1506 test oa = 0.1696
[2024-05-22 04:24:45] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.297982, train acc = 0.3200 train oa = 0.3200, test acc = 0.1555 test oa = 0.1488
[2024-05-22 04:24:53] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.344800, train acc = 0.3067 train oa = 0.3067, test acc = 0.1515 test oa = 0.1626
[2024-05-22 04:30:34] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.172883, train acc = 0.7733 train oa = 0.7733, test acc = 0.3335 test oa = 0.3287
[2024-05-22 04:30:42] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.839133, train acc = 0.9600 train oa = 0.9600, test acc = 0.3590 test oa = 0.3495
[2024-05-22 04:30:50] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.968154, train acc = 0.9067 train oa = 0.9067, test acc = 0.3660 test oa = 0.3564
[2024-05-22 04:37:29] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.231283, train acc = 0.6800 train oa = 0.6800, test acc = 0.3799 test oa = 0.3633
[2024-05-22 04:37:43] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 0.967687, train acc = 0.7867 train oa = 0.7867, test acc = 0.3793 test oa = 0.3564
[2024-05-22 04:37:56] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 0.940500, train acc = 0.7800 train oa = 0.7800, test acc = 0.4015 test oa = 0.3772
[2024-05-22 05:00:19] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.172883, train acc = 0.7733 train oa = 0.7733, test acc = 0.3335 test oa = 0.3287
[2024-05-22 05:00:28] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.839133, train acc = 0.9600 train oa = 0.9600, test acc = 0.3590 test oa = 0.3495
[2024-05-22 05:00:37] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.968154, train acc = 0.9067 train oa = 0.9067, test acc = 0.3660 test oa = 0.3564
[2024-05-22 05:30:42] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.050204, train acc = 0.4000 train oa = 0.4000, test acc = 0.1880 test oa = 0.1747
[2024-05-22 05:30:51] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.525454, train acc = 0.2667 train oa = 0.2667, test acc = 0.1588 test oa = 0.1453
[2024-05-22 05:30:59] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.746578, train acc = 0.4267 train oa = 0.4267, test acc = 0.1720 test oa = 0.1661
[2024-05-22 05:36:50] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.234710, train acc = 0.2867 train oa = 0.2867, test acc = 0.1932 test oa = 0.2163
[2024-05-22 05:37:04] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.357746, train acc = 0.3067 train oa = 0.3067, test acc = 0.1843 test oa = 0.1869
[2024-05-22 05:37:18] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.159115, train acc = 0.3733 train oa = 0.3733, test acc = 0.2206 test oa = 0.2578
[2024-05-22 05:56:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.399755, train acc = 0.3333 train oa = 0.3333, test acc = 0.1667 test oa = 0.1453
[2024-05-22 05:56:57] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.439211, train acc = 0.3067 train oa = 0.3067, test acc = 0.1438 test oa = 0.1194
[2024-05-22 05:57:06] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.208821, train acc = 0.3333 train oa = 0.3333, test acc = 0.1365 test oa = 0.1263
[2024-05-22 06:08:35] Evaluate_00: epoch = 0300, train time = 15 s, train loss = 2.386418, train acc = 0.2733 train oa = 0.2733, test acc = 0.1466 test oa = 0.1471
[2024-05-22 06:08:50] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.483442, train acc = 0.2467 train oa = 0.2467, test acc = 0.1177 test oa = 0.1159
[2024-05-22 06:09:05] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.177265, train acc = 0.2733 train oa = 0.2733, test acc = 0.1893 test oa = 0.1799
[2024-05-22 06:44:04] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.076020, train acc = 0.3600 train oa = 0.3600, test acc = 0.1722 test oa = 0.1886
[2024-05-22 06:44:12] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.550889, train acc = 0.2667 train oa = 0.2667, test acc = 0.1053 test oa = 0.0917
[2024-05-22 06:44:20] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.543083, train acc = 0.2000 train oa = 0.2000, test acc = 0.0767 test oa = 0.0779
[2024-05-22 06:56:14] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.812159, train acc = 0.8533 train oa = 0.8533, test acc = 0.4144 test oa = 0.3875
[2024-05-22 06:56:27] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.045913, train acc = 0.7733 train oa = 0.7733, test acc = 0.3814 test oa = 0.3685
[2024-05-22 06:56:40] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 0.914627, train acc = 0.8533 train oa = 0.8533, test acc = 0.3988 test oa = 0.3841
[2024-05-22 07:27:02] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.982872, train acc = 0.3867 train oa = 0.3867, test acc = 0.1883 test oa = 0.2076
[2024-05-22 07:27:10] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.752747, train acc = 0.4000 train oa = 0.4000, test acc = 0.2181 test oa = 0.2284
[2024-05-22 07:27:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.253736, train acc = 0.3333 train oa = 0.3333, test acc = 0.1585 test oa = 0.1834
[2024-05-22 08:34:15] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.937469, train acc = 0.8933 train oa = 0.8933, test acc = 0.3308 test oa = 0.3270
[2024-05-22 08:34:24] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.925916, train acc = 0.9067 train oa = 0.9067, test acc = 0.3208 test oa = 0.3045
[2024-05-22 08:34:32] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.329212, train acc = 0.8133 train oa = 0.8133, test acc = 0.2824 test oa = 0.2803
[2024-05-22 08:38:02] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.467931, train acc = 0.3067 train oa = 0.3067, test acc = 0.1125 test oa = 0.1194
[2024-05-22 08:38:11] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.472417, train acc = 0.2933 train oa = 0.2933, test acc = 0.1410 test oa = 0.1332
[2024-05-22 08:38:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.387905, train acc = 0.3733 train oa = 0.3733, test acc = 0.1539 test oa = 0.1419
[2024-05-22 09:33:10] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.937469, train acc = 0.8933 train oa = 0.8933, test acc = 0.3308 test oa = 0.3270
[2024-05-22 09:33:20] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 0.925916, train acc = 0.9067 train oa = 0.9067, test acc = 0.3208 test oa = 0.3045
[2024-05-22 09:33:29] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.329212, train acc = 0.8133 train oa = 0.8133, test acc = 0.2824 test oa = 0.2803
[2024-05-22 10:30:46] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.101510, train acc = 0.2800 train oa = 0.2800, test acc = 0.1733 test oa = 0.1522
[2024-05-22 10:30:55] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.151471, train acc = 0.3200 train oa = 0.3200, test acc = 0.1785 test oa = 0.1869
[2024-05-22 10:31:02] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.807225, train acc = 0.4400 train oa = 0.4400, test acc = 0.2058 test oa = 0.2180
[2024-05-22 10:37:12] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.446733, train acc = 0.3000 train oa = 0.3000, test acc = 0.1832 test oa = 0.1713
[2024-05-22 10:37:26] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.295813, train acc = 0.2867 train oa = 0.2867, test acc = 0.1472 test oa = 0.1453
[2024-05-22 10:37:39] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.331676, train acc = 0.2800 train oa = 0.2800, test acc = 0.1902 test oa = 0.1851
[2024-05-22 11:06:54] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 0.958747, train acc = 0.8133 train oa = 0.8133, test acc = 0.4511 test oa = 0.4291
[2024-05-22 11:07:08] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 0.659698, train acc = 0.9200 train oa = 0.9200, test acc = 0.4360 test oa = 0.4048
[2024-05-22 11:07:21] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.059674, train acc = 0.7667 train oa = 0.7667, test acc = 0.4089 test oa = 0.3979
[2024-05-22 11:13:50] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.101510, train acc = 0.2800 train oa = 0.2800, test acc = 0.1733 test oa = 0.1522
[2024-05-22 11:13:58] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.151471, train acc = 0.3200 train oa = 0.3200, test acc = 0.1785 test oa = 0.1869
[2024-05-22 11:14:06] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.807225, train acc = 0.4400 train oa = 0.4400, test acc = 0.2058 test oa = 0.2180
[2024-05-22 11:31:05] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.446733, train acc = 0.3000 train oa = 0.3000, test acc = 0.1832 test oa = 0.1713
[2024-05-22 11:31:19] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.295813, train acc = 0.2867 train oa = 0.2867, test acc = 0.1472 test oa = 0.1453
[2024-05-22 11:31:34] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.331676, train acc = 0.2800 train oa = 0.2800, test acc = 0.1902 test oa = 0.1851
[2024-05-22 11:56:09] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.090151, train acc = 0.8000 train oa = 0.8000, test acc = 0.3225 test oa = 0.2924
[2024-05-22 11:56:17] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.166968, train acc = 0.7600 train oa = 0.7600, test acc = 0.2845 test oa = 0.2457
[2024-05-22 11:56:25] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.914191, train acc = 0.8667 train oa = 0.8667, test acc = 0.3009 test oa = 0.2682
[2024-05-22 12:20:50] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.411500, train acc = 0.3467 train oa = 0.3467, test acc = 0.1393 test oa = 0.1298
[2024-05-22 12:20:58] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.611044, train acc = 0.5333 train oa = 0.5333, test acc = 0.1706 test oa = 0.1955
[2024-05-22 12:21:06] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.920709, train acc = 0.4267 train oa = 0.4267, test acc = 0.1783 test oa = 0.1782
[2024-05-22 12:24:47] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.144449, train acc = 0.2800 train oa = 0.2800, test acc = 0.1865 test oa = 0.1609
[2024-05-22 12:24:56] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.865796, train acc = 0.4000 train oa = 0.4000, test acc = 0.1799 test oa = 0.1834
[2024-05-22 12:25:04] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.938218, train acc = 0.4400 train oa = 0.4400, test acc = 0.1822 test oa = 0.1626
[2024-05-22 13:03:46] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.460091, train acc = 0.3333 train oa = 0.3333, test acc = 0.1145 test oa = 0.1142
[2024-05-22 13:03:54] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.875587, train acc = 0.4133 train oa = 0.4133, test acc = 0.2103 test oa = 0.1886
[2024-05-22 13:04:02] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.980836, train acc = 0.4267 train oa = 0.4267, test acc = 0.1649 test oa = 0.1505
[2024-05-22 13:10:27] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.036879, train acc = 0.7800 train oa = 0.7800, test acc = 0.4357 test oa = 0.4118
[2024-05-22 13:10:41] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 0.840526, train acc = 0.8800 train oa = 0.8800, test acc = 0.4151 test oa = 0.4118
[2024-05-22 13:10:55] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.056855, train acc = 0.7533 train oa = 0.7533, test acc = 0.4161 test oa = 0.3997
[2024-05-22 13:16:36] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.090151, train acc = 0.8000 train oa = 0.8000, test acc = 0.3225 test oa = 0.2924
[2024-05-22 13:16:45] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.166968, train acc = 0.7600 train oa = 0.7600, test acc = 0.2845 test oa = 0.2457
[2024-05-22 13:16:53] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.914191, train acc = 0.8667 train oa = 0.8667, test acc = 0.3009 test oa = 0.2682
[2024-05-22 14:11:12] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.460091, train acc = 0.3333 train oa = 0.3333, test acc = 0.1145 test oa = 0.1142
[2024-05-22 14:11:21] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 1.875587, train acc = 0.4133 train oa = 0.4133, test acc = 0.2103 test oa = 0.1886
[2024-05-22 14:11:29] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.980836, train acc = 0.4267 train oa = 0.4267, test acc = 0.1649 test oa = 0.1505
[2024-05-22 14:15:52] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.460091, train acc = 0.3333 train oa = 0.3333, test acc = 0.1145 test oa = 0.1142
[2024-05-22 14:16:01] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.875587, train acc = 0.4133 train oa = 0.4133, test acc = 0.2103 test oa = 0.1886
[2024-05-22 14:16:09] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.980836, train acc = 0.4267 train oa = 0.4267, test acc = 0.1649 test oa = 0.1505
[2024-05-22 14:34:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.730914, train acc = 0.5333 train oa = 0.5333, test acc = 0.2181 test oa = 0.2457
[2024-05-22 14:34:11] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.965993, train acc = 0.3867 train oa = 0.3867, test acc = 0.1926 test oa = 0.2007
[2024-05-22 14:34:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.018022, train acc = 0.3733 train oa = 0.3733, test acc = 0.1866 test oa = 0.1747
[2024-05-22 14:56:52] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.967017, train acc = 0.7933 train oa = 0.7933, test acc = 0.4054 test oa = 0.3772
[2024-05-22 14:57:05] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 1.041136, train acc = 0.7467 train oa = 0.7467, test acc = 0.3723 test oa = 0.3616
[2024-05-22 14:57:18] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.014627, train acc = 0.8067 train oa = 0.8067, test acc = 0.4002 test oa = 0.3893
[2024-05-22 15:17:25] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.896276, train acc = 0.8667 train oa = 0.8667, test acc = 0.3509 test oa = 0.3322
[2024-05-22 15:17:32] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.292935, train acc = 0.7200 train oa = 0.7200, test acc = 0.3093 test oa = 0.2768
[2024-05-22 15:17:40] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.909634, train acc = 0.8533 train oa = 0.8533, test acc = 0.3215 test oa = 0.3028
[2024-05-22 15:35:47] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.264852, train acc = 0.2800 train oa = 0.2800, test acc = 0.1624 test oa = 0.1747
[2024-05-22 15:36:01] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.246954, train acc = 0.2867 train oa = 0.2867, test acc = 0.1693 test oa = 0.1713
[2024-05-22 15:36:14] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.192328, train acc = 0.3267 train oa = 0.3267, test acc = 0.1981 test oa = 0.2543
[2024-05-22 16:04:18] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.050169, train acc = 0.4133 train oa = 0.4133, test acc = 0.2032 test oa = 0.2439
[2024-05-22 16:04:26] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.962465, train acc = 0.4000 train oa = 0.4000, test acc = 0.1724 test oa = 0.1886
[2024-05-22 16:04:34] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.909338, train acc = 0.4000 train oa = 0.4000, test acc = 0.2033 test oa = 0.2145
[2024-05-22 16:46:50] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 1.912144, train acc = 0.4667 train oa = 0.4667, test acc = 0.2058 test oa = 0.1920
[2024-05-22 16:47:05] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 1.859552, train acc = 0.4533 train oa = 0.4533, test acc = 0.2518 test oa = 0.2664
[2024-05-22 16:47:19] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.007176, train acc = 0.4200 train oa = 0.4200, test acc = 0.2202 test oa = 0.2612
[2024-05-22 17:13:33] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.072401, train acc = 0.4000 train oa = 0.4000, test acc = 0.1736 test oa = 0.1678
[2024-05-22 17:13:41] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.066848, train acc = 0.4133 train oa = 0.4133, test acc = 0.1322 test oa = 0.1142
[2024-05-22 17:13:49] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.354995, train acc = 0.3867 train oa = 0.3867, test acc = 0.1637 test oa = 0.1228
[2024-05-22 17:18:40] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 2.117414, train acc = 0.3733 train oa = 0.3733, test acc = 0.1335 test oa = 0.1367
[2024-05-22 17:18:48] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.412932, train acc = 0.3067 train oa = 0.3067, test acc = 0.1504 test oa = 0.1488
[2024-05-22 17:18:57] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.490685, train acc = 0.2933 train oa = 0.2933, test acc = 0.1539 test oa = 0.1522
[2024-05-22 17:36:33] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.468002, train acc = 0.3200 train oa = 0.3200, test acc = 0.1253 test oa = 0.1003
[2024-05-22 17:36:41] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.504698, train acc = 0.2933 train oa = 0.2933, test acc = 0.1412 test oa = 0.1003
[2024-05-22 17:36:49] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.139858, train acc = 0.3733 train oa = 0.3733, test acc = 0.1554 test oa = 0.1401
[2024-05-22 17:44:18] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 0.524579, train acc = 0.9733 train oa = 0.9733, test acc = 0.3592 test oa = 0.3581
[2024-05-22 17:44:27] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.345766, train acc = 1.0000 train oa = 1.0000, test acc = 0.3870 test oa = 0.3702
[2024-05-22 17:44:36] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.450105, train acc = 1.0000 train oa = 1.0000, test acc = 0.3469 test oa = 0.3495
[2024-05-22 18:45:15] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.468002, train acc = 0.3200 train oa = 0.3200, test acc = 0.1253 test oa = 0.1003
[2024-05-22 18:45:24] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.504698, train acc = 0.2933 train oa = 0.2933, test acc = 0.1412 test oa = 0.1003
[2024-05-22 18:45:32] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.139858, train acc = 0.3733 train oa = 0.3733, test acc = 0.1554 test oa = 0.1401
[2024-05-22 18:49:54] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.468002, train acc = 0.3200 train oa = 0.3200, test acc = 0.1253 test oa = 0.1003
[2024-05-22 18:50:03] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.504698, train acc = 0.2933 train oa = 0.2933, test acc = 0.1412 test oa = 0.1003
[2024-05-22 18:50:11] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.139858, train acc = 0.3733 train oa = 0.3733, test acc = 0.1554 test oa = 0.1401
[2024-05-22 19:08:23] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.445339, train acc = 0.2400 train oa = 0.2400, test acc = 0.1372 test oa = 0.1384
[2024-05-22 19:08:31] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.540624, train acc = 0.2133 train oa = 0.2133, test acc = 0.1440 test oa = 0.1176
[2024-05-22 19:08:39] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.211364, train acc = 0.2400 train oa = 0.2400, test acc = 0.1881 test oa = 0.2197
[2024-05-22 19:20:02] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.524579, train acc = 0.9733 train oa = 0.9733, test acc = 0.3592 test oa = 0.3581
[2024-05-22 19:20:10] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.345766, train acc = 1.0000 train oa = 1.0000, test acc = 0.3870 test oa = 0.3702
[2024-05-22 19:20:18] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.450105, train acc = 1.0000 train oa = 1.0000, test acc = 0.3469 test oa = 0.3495
[2024-05-22 19:55:33] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.460132, train acc = 0.9867 train oa = 0.9867, test acc = 0.4086 test oa = 0.3979
[2024-05-22 19:55:42] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 0.344405, train acc = 1.0000 train oa = 1.0000, test acc = 0.3935 test oa = 0.3651
[2024-05-22 19:55:51] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.378326, train acc = 1.0000 train oa = 1.0000, test acc = 0.3851 test oa = 0.3772
[2024-05-22 20:16:23] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.527492, train acc = 0.5933 train oa = 0.5933, test acc = 0.3827 test oa = 0.3824
[2024-05-22 20:16:35] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.445339, train acc = 0.2400 train oa = 0.2400, test acc = 0.1372 test oa = 0.1384
[2024-05-22 20:16:36] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 1.039064, train acc = 0.8067 train oa = 0.8067, test acc = 0.4207 test oa = 0.4152
[2024-05-22 20:16:43] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.540624, train acc = 0.2133 train oa = 0.2133, test acc = 0.1440 test oa = 0.1176
[2024-05-22 20:16:50] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.091726, train acc = 0.7800 train oa = 0.7800, test acc = 0.4236 test oa = 0.4239
[2024-05-22 20:16:51] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.211364, train acc = 0.2400 train oa = 0.2400, test acc = 0.1881 test oa = 0.2197
[2024-05-22 20:22:24] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.445339, train acc = 0.2400 train oa = 0.2400, test acc = 0.1372 test oa = 0.1384
[2024-05-22 20:22:33] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.540624, train acc = 0.2133 train oa = 0.2133, test acc = 0.1440 test oa = 0.1176
[2024-05-22 20:22:42] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.211364, train acc = 0.2400 train oa = 0.2400, test acc = 0.1881 test oa = 0.2197
[2024-05-22 20:40:46] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.463700, train acc = 0.2467 train oa = 0.2467, test acc = 0.2134 test oa = 0.1765
[2024-05-22 20:41:00] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.465148, train acc = 0.2333 train oa = 0.2333, test acc = 0.1542 test oa = 0.1228
[2024-05-22 20:41:13] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.507850, train acc = 0.2533 train oa = 0.2533, test acc = 0.1394 test oa = 0.1055
[2024-05-22 21:02:26] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.444401, train acc = 0.9867 train oa = 0.9867, test acc = 0.3700 test oa = 0.3478
[2024-05-22 21:02:34] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.425684, train acc = 1.0000 train oa = 1.0000, test acc = 0.3565 test oa = 0.3253
[2024-05-22 21:02:42] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.381952, train acc = 1.0000 train oa = 1.0000, test acc = 0.3540 test oa = 0.3408
[2024-05-22 21:45:53] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.444401, train acc = 0.9867 train oa = 0.9867, test acc = 0.3700 test oa = 0.3478
[2024-05-22 21:46:02] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.425684, train acc = 1.0000 train oa = 1.0000, test acc = 0.3565 test oa = 0.3253
[2024-05-22 21:46:11] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.381952, train acc = 1.0000 train oa = 1.0000, test acc = 0.3540 test oa = 0.3408
[2024-05-22 22:02:58] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.427664, train acc = 0.5867 train oa = 0.5867, test acc = 0.3673 test oa = 0.3426
[2024-05-22 22:03:10] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.321025, train acc = 0.6667 train oa = 0.6667, test acc = 0.3483 test oa = 0.3270
[2024-05-22 22:03:24] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.440476, train acc = 0.5933 train oa = 0.5933, test acc = 0.3738 test oa = 0.3599
[2024-05-22 22:08:28] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.530453, train acc = 0.2400 train oa = 0.2400, test acc = 0.0929 test oa = 0.0813
[2024-05-22 22:08:36] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.518458, train acc = 0.2800 train oa = 0.2800, test acc = 0.0937 test oa = 0.0952
[2024-05-22 22:08:44] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.403068, train acc = 0.3600 train oa = 0.3600, test acc = 0.1417 test oa = 0.1384
[2024-05-22 22:15:45] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.284961, train acc = 0.2867 train oa = 0.2867, test acc = 0.2023 test oa = 0.1869
[2024-05-22 22:15:59] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.327033, train acc = 0.2667 train oa = 0.2667, test acc = 0.1700 test oa = 0.1592
[2024-05-22 22:16:14] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.285912, train acc = 0.2733 train oa = 0.2733, test acc = 0.1700 test oa = 0.1644
[2024-05-22 22:47:29] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.355141, train acc = 1.0000 train oa = 1.0000, test acc = 0.3751 test oa = 0.3529
[2024-05-22 22:47:37] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.793447, train acc = 0.9467 train oa = 0.9467, test acc = 0.3178 test oa = 0.2855
[2024-05-22 22:47:46] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.731801, train acc = 0.9733 train oa = 0.9733, test acc = 0.3424 test oa = 0.3028
[2024-05-22 23:20:52] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.468182, train acc = 0.2933 train oa = 0.2933, test acc = 0.1154 test oa = 0.1107
[2024-05-22 23:21:01] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.364638, train acc = 0.2533 train oa = 0.2533, test acc = 0.1667 test oa = 0.1453
[2024-05-22 23:21:09] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.939544, train acc = 0.4400 train oa = 0.4400, test acc = 0.2038 test oa = 0.1834
[2024-05-22 23:27:37] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.530453, train acc = 0.2400 train oa = 0.2400, test acc = 0.0929 test oa = 0.0813
[2024-05-22 23:27:45] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.518458, train acc = 0.2800 train oa = 0.2800, test acc = 0.0937 test oa = 0.0952
[2024-05-22 23:27:54] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.403068, train acc = 0.3600 train oa = 0.3600, test acc = 0.1417 test oa = 0.1384
[2024-05-22 23:38:57] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 0.355141, train acc = 1.0000 train oa = 1.0000, test acc = 0.3751 test oa = 0.3529
[2024-05-22 23:39:06] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.793447, train acc = 0.9467 train oa = 0.9467, test acc = 0.3178 test oa = 0.2855
[2024-05-22 23:39:15] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 0.731801, train acc = 0.9733 train oa = 0.9733, test acc = 0.3424 test oa = 0.3028
[2024-05-22 23:59:34] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.353409, train acc = 0.3067 train oa = 0.3067, test acc = 0.1290 test oa = 0.1125
[2024-05-22 23:59:42] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.069887, train acc = 0.4000 train oa = 0.4000, test acc = 0.1386 test oa = 0.1488
[2024-05-22 23:59:50] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.091906, train acc = 0.4133 train oa = 0.4133, test acc = 0.1317 test oa = 0.1159
[2024-05-23 00:12:42] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.523541, train acc = 1.0000 train oa = 1.0000, test acc = 0.3613 test oa = 0.3253
[2024-05-23 00:12:49] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.466726, train acc = 1.0000 train oa = 1.0000, test acc = 0.3623 test oa = 0.3339
[2024-05-23 00:12:58] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.462679, train acc = 1.0000 train oa = 1.0000, test acc = 0.3640 test oa = 0.3391
[2024-05-23 00:24:36] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.309038, train acc = 0.7133 train oa = 0.7133, test acc = 0.3853 test oa = 0.3651
[2024-05-23 00:24:49] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.157066, train acc = 0.7400 train oa = 0.7400, test acc = 0.3816 test oa = 0.3529
[2024-05-23 00:25:02] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.331462, train acc = 0.6667 train oa = 0.6667, test acc = 0.3866 test oa = 0.3737
[2024-05-23 01:11:50] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.353409, train acc = 0.3067 train oa = 0.3067, test acc = 0.1290 test oa = 0.1125
[2024-05-23 01:11:59] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.069887, train acc = 0.4000 train oa = 0.4000, test acc = 0.1386 test oa = 0.1488
[2024-05-23 01:12:07] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.091906, train acc = 0.4133 train oa = 0.4133, test acc = 0.1317 test oa = 0.1159
[2024-05-23 01:20:28] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.353409, train acc = 0.3067 train oa = 0.3067, test acc = 0.1290 test oa = 0.1125
[2024-05-23 01:20:36] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.069887, train acc = 0.4000 train oa = 0.4000, test acc = 0.1386 test oa = 0.1488
[2024-05-23 01:20:45] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.091906, train acc = 0.4133 train oa = 0.4133, test acc = 0.1317 test oa = 0.1159
[2024-05-23 01:32:17] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 0.816197, train acc = 0.9467 train oa = 0.9467, test acc = 0.3299 test oa = 0.2941
[2024-05-23 01:32:27] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 0.610998, train acc = 0.9867 train oa = 0.9867, test acc = 0.3511 test oa = 0.3235
[2024-05-23 01:32:36] Evaluate_02: epoch = 0300, train time = 9 s, train loss = 0.765415, train acc = 0.9200 train oa = 0.9200, test acc = 0.3614 test oa = 0.3339
[2024-05-23 01:47:48] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.284961, train acc = 0.2867 train oa = 0.2867, test acc = 0.2023 test oa = 0.1869
[2024-05-23 01:48:01] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.327033, train acc = 0.2667 train oa = 0.2667, test acc = 0.1700 test oa = 0.1592
[2024-05-23 01:48:02] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.530257, train acc = 0.6267 train oa = 0.6267, test acc = 0.2407 test oa = 0.2491
[2024-05-23 01:48:10] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.484021, train acc = 0.6000 train oa = 0.6000, test acc = 0.1806 test oa = 0.1817
[2024-05-23 01:48:14] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.285912, train acc = 0.2733 train oa = 0.2733, test acc = 0.1700 test oa = 0.1644
[2024-05-23 01:48:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.819023, train acc = 0.4800 train oa = 0.4800, test acc = 0.1717 test oa = 0.1696
[2024-05-23 01:52:36] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.610922, train acc = 0.9733 train oa = 0.9733, test acc = 0.3316 test oa = 0.2803
[2024-05-23 01:52:43] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.385151, train acc = 1.0000 train oa = 1.0000, test acc = 0.3516 test oa = 0.3097
[2024-05-23 01:52:51] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.762421, train acc = 0.9467 train oa = 0.9467, test acc = 0.3424 test oa = 0.2907
[2024-05-23 02:10:36] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 1.127149, train acc = 0.7133 train oa = 0.7133, test acc = 0.3918 test oa = 0.3720
[2024-05-23 02:10:49] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 0.929121, train acc = 0.7933 train oa = 0.7933, test acc = 0.3851 test oa = 0.3772
[2024-05-23 02:11:02] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 0.810433, train acc = 0.8733 train oa = 0.8733, test acc = 0.4168 test oa = 0.4014
[2024-05-23 02:41:43] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.399560, train acc = 0.4000 train oa = 0.4000, test acc = 0.1715 test oa = 0.1799
[2024-05-23 02:41:52] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.864783, train acc = 0.4133 train oa = 0.4133, test acc = 0.1841 test oa = 0.1661
[2024-05-23 02:42:00] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.460651, train acc = 0.6000 train oa = 0.6000, test acc = 0.1766 test oa = 0.1972
[2024-05-23 02:51:08] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.399560, train acc = 0.4000 train oa = 0.4000, test acc = 0.1715 test oa = 0.1799
[2024-05-23 02:51:17] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.864783, train acc = 0.4133 train oa = 0.4133, test acc = 0.1841 test oa = 0.1661
[2024-05-23 02:51:26] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.460651, train acc = 0.6000 train oa = 0.6000, test acc = 0.1766 test oa = 0.1972
[2024-05-23 03:16:22] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.399560, train acc = 0.4000 train oa = 0.4000, test acc = 0.1715 test oa = 0.1799
[2024-05-23 03:16:30] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.864783, train acc = 0.4133 train oa = 0.4133, test acc = 0.1841 test oa = 0.1661
[2024-05-23 03:16:38] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.460651, train acc = 0.6000 train oa = 0.6000, test acc = 0.1766 test oa = 0.1972
[2024-05-23 03:46:34] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.331333, train acc = 0.2733 train oa = 0.2733, test acc = 0.1525 test oa = 0.1246
[2024-05-23 03:46:49] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.088547, train acc = 0.3733 train oa = 0.3733, test acc = 0.2009 test oa = 0.1886
[2024-05-23 03:47:04] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 2.268587, train acc = 0.2733 train oa = 0.2733, test acc = 0.2032 test oa = 0.2197
[2024-05-23 03:47:10] Evaluate_00: epoch = 0300, train time = 9 s, train loss = 0.327028, train acc = 1.0000 train oa = 1.0000, test acc = 0.3912 test oa = 0.3702
[2024-05-23 03:47:19] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.694218, train acc = 0.9867 train oa = 0.9867, test acc = 0.3548 test oa = 0.3408
[2024-05-23 03:47:27] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.537285, train acc = 1.0000 train oa = 1.0000, test acc = 0.3855 test oa = 0.3668
[2024-05-23 03:54:00] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.372158, train acc = 1.0000 train oa = 1.0000, test acc = 0.3634 test oa = 0.3460
[2024-05-23 03:54:09] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 0.599297, train acc = 0.9867 train oa = 0.9867, test acc = 0.3481 test oa = 0.3080
[2024-05-23 03:54:16] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.789203, train acc = 0.9733 train oa = 0.9733, test acc = 0.3443 test oa = 0.3028
[2024-05-23 03:59:52] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.921047, train acc = 0.8133 train oa = 0.8133, test acc = 0.3871 test oa = 0.3702
[2024-05-23 04:00:06] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 1.066513, train acc = 0.7867 train oa = 0.7867, test acc = 0.4057 test oa = 0.3702
[2024-05-23 04:00:19] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 1.015496, train acc = 0.7800 train oa = 0.7800, test acc = 0.4102 test oa = 0.3875
[2024-05-23 04:35:03] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.095471, train acc = 0.4000 train oa = 0.4000, test acc = 0.1497 test oa = 0.1678
[2024-05-23 04:35:13] Evaluate_01: epoch = 0300, train time = 9 s, train loss = 2.446498, train acc = 0.3200 train oa = 0.3200, test acc = 0.1114 test oa = 0.1159
[2024-05-23 04:35:22] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.478510, train acc = 0.2933 train oa = 0.2933, test acc = 0.1472 test oa = 0.1176
[2024-05-23 04:47:17] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.095471, train acc = 0.4000 train oa = 0.4000, test acc = 0.1497 test oa = 0.1678
[2024-05-23 04:47:26] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.446498, train acc = 0.3200 train oa = 0.3200, test acc = 0.1114 test oa = 0.1159
[2024-05-23 04:47:35] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.478510, train acc = 0.2933 train oa = 0.2933, test acc = 0.1472 test oa = 0.1176
[2024-05-23 05:06:57] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.158134, train acc = 0.3867 train oa = 0.3867, test acc = 0.2150 test oa = 0.2024
[2024-05-23 05:07:05] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.558897, train acc = 0.2800 train oa = 0.2800, test acc = 0.1277 test oa = 0.1176
[2024-05-23 05:07:13] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.911288, train acc = 0.4267 train oa = 0.4267, test acc = 0.1863 test oa = 0.1661
[2024-05-23 05:17:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.550937, train acc = 1.0000 train oa = 1.0000, test acc = 0.3489 test oa = 0.3131
[2024-05-23 05:17:13] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.212424, train acc = 1.0000 train oa = 1.0000, test acc = 0.3676 test oa = 0.3356
[2024-05-23 05:17:21] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.469790, train acc = 1.0000 train oa = 1.0000, test acc = 0.3882 test oa = 0.3426
[2024-05-23 05:48:45] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 0.522879, train acc = 0.9533 train oa = 0.9533, test acc = 0.4440 test oa = 0.4377
[2024-05-23 05:48:58] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 0.716810, train acc = 0.9067 train oa = 0.9067, test acc = 0.4108 test oa = 0.4152
[2024-05-23 05:49:11] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 0.830992, train acc = 0.8333 train oa = 0.8333, test acc = 0.4179 test oa = 0.4256
[2024-05-23 06:04:15] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 0.372158, train acc = 1.0000 train oa = 1.0000, test acc = 0.3634 test oa = 0.3460
[2024-05-23 06:04:23] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 0.599297, train acc = 0.9867 train oa = 0.9867, test acc = 0.3481 test oa = 0.3080
[2024-05-23 06:04:32] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 0.789203, train acc = 0.9733 train oa = 0.9733, test acc = 0.3443 test oa = 0.3028
[2024-05-23 06:05:40] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.119393, train acc = 0.4000 train oa = 0.4000, test acc = 0.1940 test oa = 0.1799
[2024-05-23 06:05:49] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.912764, train acc = 0.4000 train oa = 0.4000, test acc = 0.1902 test oa = 0.1592
[2024-05-23 06:05:57] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.964159, train acc = 0.3467 train oa = 0.3467, test acc = 0.1711 test oa = 0.1522
[2024-05-23 06:37:21] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.158301, train acc = 0.3333 train oa = 0.3333, test acc = 0.1800 test oa = 0.1644
[2024-05-23 06:37:29] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.092869, train acc = 0.3067 train oa = 0.3067, test acc = 0.1980 test oa = 0.2145
[2024-05-23 06:37:37] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.911566, train acc = 0.4267 train oa = 0.4267, test acc = 0.1890 test oa = 0.2059
[2024-05-23 06:46:19] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.331333, train acc = 0.2733 train oa = 0.2733, test acc = 0.1525 test oa = 0.1246
[2024-05-23 06:46:33] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.088547, train acc = 0.3733 train oa = 0.3733, test acc = 0.2009 test oa = 0.1886
[2024-05-23 06:46:46] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.268587, train acc = 0.2733 train oa = 0.2733, test acc = 0.2032 test oa = 0.2197
[2024-05-23 07:15:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.565047, train acc = 1.0000 train oa = 1.0000, test acc = 0.3438 test oa = 0.3270
[2024-05-23 07:15:57] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.989872, train acc = 0.8533 train oa = 0.8533, test acc = 0.3275 test oa = 0.3166
[2024-05-23 07:16:04] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.931273, train acc = 0.8800 train oa = 0.8800, test acc = 0.3672 test oa = 0.3304
[2024-05-23 07:35:08] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.158301, train acc = 0.3333 train oa = 0.3333, test acc = 0.1800 test oa = 0.1644
[2024-05-23 07:35:16] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.092869, train acc = 0.3067 train oa = 0.3067, test acc = 0.1980 test oa = 0.2145
[2024-05-23 07:35:24] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.911566, train acc = 0.4267 train oa = 0.4267, test acc = 0.1890 test oa = 0.2059
[2024-05-23 07:54:31] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.069617, train acc = 0.3867 train oa = 0.3867, test acc = 0.2015 test oa = 0.2180
[2024-05-23 07:54:40] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.530131, train acc = 0.2800 train oa = 0.2800, test acc = 0.1325 test oa = 0.1125
[2024-05-23 07:54:48] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.243395, train acc = 0.2533 train oa = 0.2533, test acc = 0.1436 test oa = 0.1125
[2024-05-23 08:14:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 0.565047, train acc = 1.0000 train oa = 1.0000, test acc = 0.3438 test oa = 0.3270
[2024-05-23 08:15:06] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 0.989872, train acc = 0.8533 train oa = 0.8533, test acc = 0.3275 test oa = 0.3166
[2024-05-23 08:15:14] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 0.931273, train acc = 0.8800 train oa = 0.8800, test acc = 0.3672 test oa = 0.3304
[2024-05-23 08:31:56] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.715165, train acc = 0.9733 train oa = 0.9733, test acc = 0.3325 test oa = 0.3201
[2024-05-23 08:32:02] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.768804, train acc = 0.9200 train oa = 0.9200, test acc = 0.3471 test oa = 0.3270
[2024-05-23 08:32:09] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.636407, train acc = 0.9867 train oa = 0.9867, test acc = 0.3865 test oa = 0.3391
[2024-05-23 09:11:42] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.359554, train acc = 0.3000 train oa = 0.3000, test acc = 0.1548 test oa = 0.1540
[2024-05-23 09:11:56] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.343346, train acc = 0.3200 train oa = 0.3200, test acc = 0.1802 test oa = 0.1730
[2024-05-23 09:12:10] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.187540, train acc = 0.3467 train oa = 0.3467, test acc = 0.1898 test oa = 0.2145
[2024-05-23 09:17:19] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.029327, train acc = 0.8200 train oa = 0.8200, test acc = 0.3986 test oa = 0.3772
[2024-05-23 09:17:31] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.151030, train acc = 0.7400 train oa = 0.7400, test acc = 0.3832 test oa = 0.3702
[2024-05-23 09:17:43] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.236026, train acc = 0.7333 train oa = 0.7333, test acc = 0.3811 test oa = 0.3702
[2024-05-23 10:14:14] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.550318, train acc = 0.9733 train oa = 0.9733, test acc = 0.3623 test oa = 0.3426
[2024-05-23 10:14:21] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.785039, train acc = 0.9067 train oa = 0.9067, test acc = 0.3167 test oa = 0.2976
[2024-05-23 10:14:27] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.903982, train acc = 0.8933 train oa = 0.8933, test acc = 0.3536 test oa = 0.3218
[2024-05-23 10:20:33] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.550318, train acc = 0.9733 train oa = 0.9733, test acc = 0.3623 test oa = 0.3426
[2024-05-23 10:20:39] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.785039, train acc = 0.9067 train oa = 0.9067, test acc = 0.3167 test oa = 0.2976
[2024-05-23 10:20:46] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.903982, train acc = 0.8933 train oa = 0.8933, test acc = 0.3536 test oa = 0.3218
[2024-05-23 10:54:32] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.431091, train acc = 0.6267 train oa = 0.6267, test acc = 0.3522 test oa = 0.3564
[2024-05-23 10:54:44] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.313063, train acc = 0.6733 train oa = 0.6733, test acc = 0.3569 test oa = 0.3581
[2024-05-23 10:54:56] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.475931, train acc = 0.5267 train oa = 0.5267, test acc = 0.3497 test oa = 0.3547
[2024-05-23 11:31:00] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.359554, train acc = 0.3000 train oa = 0.3000, test acc = 0.1548 test oa = 0.1540
[2024-05-23 11:31:12] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.343346, train acc = 0.3200 train oa = 0.3200, test acc = 0.1802 test oa = 0.1730
[2024-05-23 11:31:25] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.187540, train acc = 0.3467 train oa = 0.3467, test acc = 0.1898 test oa = 0.2145
[2024-05-23 11:49:19] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.803173, train acc = 0.9333 train oa = 0.9333, test acc = 0.2959 test oa = 0.2612
[2024-05-23 11:49:26] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.749644, train acc = 0.9067 train oa = 0.9067, test acc = 0.3389 test oa = 0.3080
[2024-05-23 11:49:29] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 0.691679, train acc = 0.9333 train oa = 0.9333, test acc = 0.3150 test oa = 0.2855
[2024-05-23 11:49:32] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 0.955781, train acc = 0.8133 train oa = 0.8133, test acc = 0.3471 test oa = 0.3218
[2024-05-23 11:49:36] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 0.277740, train acc = 1.0000 train oa = 1.0000, test acc = 0.3565 test oa = 0.3304
[2024-05-23 11:49:42] Evaluate_02: epoch = 0300, train time = 5 s, train loss = 0.433803, train acc = 1.0000 train oa = 1.0000, test acc = 0.3544 test oa = 0.3287
[2024-05-23 12:48:46] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.011167, train acc = 0.7400 train oa = 0.7400, test acc = 0.4107 test oa = 0.4170
[2024-05-23 12:48:58] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 0.680439, train acc = 0.9067 train oa = 0.9067, test acc = 0.4491 test oa = 0.4412
[2024-05-23 12:49:09] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 0.960437, train acc = 0.7733 train oa = 0.7733, test acc = 0.3928 test oa = 0.4014
[2024-05-23 16:58:21] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.249751, train acc = 0.7200 train oa = 0.7200, test acc = 0.3926 test oa = 0.3651
[2024-05-23 16:58:32] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.049374, train acc = 0.7867 train oa = 0.7867, test acc = 0.4127 test oa = 0.3806
[2024-05-23 16:58:43] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 1.022625, train acc = 0.7933 train oa = 0.7933, test acc = 0.4326 test oa = 0.4031
[2024-05-23 20:07:13] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 0.904305, train acc = 0.8467 train oa = 0.8467, test acc = 0.4348 test oa = 0.4221
[2024-05-23 20:07:25] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 0.770670, train acc = 0.8800 train oa = 0.8800, test acc = 0.4346 test oa = 0.4118
[2024-05-23 20:07:36] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 0.981200, train acc = 0.7867 train oa = 0.7867, test acc = 0.4285 test oa = 0.4204
[2024-05-23 22:27:59] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 0.920627, train acc = 0.8333 train oa = 0.8333, test acc = 0.4171 test oa = 0.4066
[2024-05-23 22:28:10] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.085472, train acc = 0.7600 train oa = 0.7600, test acc = 0.4181 test oa = 0.3893
[2024-05-23 22:28:22] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 0.975115, train acc = 0.8200 train oa = 0.8200, test acc = 0.4010 test oa = 0.3893
[2024-05-24 00:33:22] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.328786, train acc = 0.6733 train oa = 0.6733, test acc = 0.3605 test oa = 0.3443
[2024-05-24 00:33:34] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 0.731714, train acc = 0.9333 train oa = 0.9333, test acc = 0.4106 test oa = 0.3806
[2024-05-24 00:33:45] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 0.702606, train acc = 0.9200 train oa = 0.9200, test acc = 0.4004 test oa = 0.3668
[2024-05-24 00:51:25] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.690184, train acc = 0.5200 train oa = 0.5200, test acc = 0.2115 test oa = 0.2042
[2024-05-24 00:51:32] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.500491, train acc = 0.6133 train oa = 0.6133, test acc = 0.2412 test oa = 0.2491
[2024-05-24 00:51:40] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.596088, train acc = 0.6000 train oa = 0.6000, test acc = 0.1838 test oa = 0.2197
[2024-05-24 00:54:22] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.497444, train acc = 0.2467 train oa = 0.2467, test acc = 0.1011 test oa = 0.0934
[2024-05-24 00:54:37] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.382184, train acc = 0.2733 train oa = 0.2733, test acc = 0.1703 test oa = 0.1540
[2024-05-24 00:54:52] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.509026, train acc = 0.2400 train oa = 0.2400, test acc = 0.1407 test oa = 0.1263
[2024-05-24 01:22:16] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.359200, train acc = 0.2667 train oa = 0.2667, test acc = 0.1439 test oa = 0.1436
[2024-05-24 01:22:25] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.067666, train acc = 0.3200 train oa = 0.3200, test acc = 0.1937 test oa = 0.1920
[2024-05-24 01:22:34] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.894746, train acc = 0.3867 train oa = 0.3867, test acc = 0.2543 test oa = 0.2370
[2024-05-24 01:26:43] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.295183, train acc = 0.2533 train oa = 0.2533, test acc = 0.1933 test oa = 0.1678
[2024-05-24 01:26:55] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.426470, train acc = 0.2533 train oa = 0.2533, test acc = 0.1974 test oa = 0.1661
[2024-05-24 01:27:08] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.476705, train acc = 0.2067 train oa = 0.2067, test acc = 0.1543 test oa = 0.1228
[2024-05-24 01:58:01] Evaluate_00: epoch = 0300, train time = 15 s, train loss = 2.165874, train acc = 0.3133 train oa = 0.3133, test acc = 0.2229 test oa = 0.1834
[2024-05-24 01:58:16] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.118021, train acc = 0.3600 train oa = 0.3600, test acc = 0.1950 test oa = 0.1817
[2024-05-24 01:58:32] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 2.410797, train acc = 0.2733 train oa = 0.2733, test acc = 0.1661 test oa = 0.1419
[2024-05-24 02:07:37] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.055375, train acc = 0.3600 train oa = 0.3600, test acc = 0.1805 test oa = 0.1747
[2024-05-24 02:07:52] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.020583, train acc = 0.3733 train oa = 0.3733, test acc = 0.2176 test oa = 0.2543
[2024-05-24 02:08:08] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 1.657049, train acc = 0.5267 train oa = 0.5267, test acc = 0.2353 test oa = 0.2595
[2024-05-24 02:09:13] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.471527, train acc = 0.2067 train oa = 0.2067, test acc = 0.1621 test oa = 0.1765
[2024-05-24 02:09:26] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.441552, train acc = 0.2000 train oa = 0.2000, test acc = 0.1808 test oa = 0.1626
[2024-05-24 02:09:39] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.269597, train acc = 0.2667 train oa = 0.2667, test acc = 0.1906 test oa = 0.1834
[2024-05-24 02:32:53] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.371468, train acc = 0.6733 train oa = 0.6733, test acc = 0.3755 test oa = 0.3478
[2024-05-24 02:33:06] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.400681, train acc = 0.6067 train oa = 0.6067, test acc = 0.3681 test oa = 0.3339
[2024-05-24 02:33:18] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 1.444808, train acc = 0.6333 train oa = 0.6333, test acc = 0.3872 test oa = 0.3685
[2024-05-24 03:02:39] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.138821, train acc = 0.3600 train oa = 0.3600, test acc = 0.2471 test oa = 0.2301
[2024-05-24 03:02:53] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.225931, train acc = 0.3067 train oa = 0.3067, test acc = 0.2063 test oa = 0.1955
[2024-05-24 03:03:06] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.123500, train acc = 0.3867 train oa = 0.3867, test acc = 0.2026 test oa = 0.2111
[2024-05-24 03:39:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.488745, train acc = 0.2000 train oa = 0.2000, test acc = 0.1211 test oa = 0.1038
[2024-05-24 03:39:24] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.468463, train acc = 0.2800 train oa = 0.2800, test acc = 0.1532 test oa = 0.1419
[2024-05-24 03:39:32] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.264177, train acc = 0.2667 train oa = 0.2667, test acc = 0.1843 test oa = 0.1661
[2024-05-24 03:41:07] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.467931, train acc = 0.3067 train oa = 0.3067, test acc = 0.1125 test oa = 0.1194
[2024-05-24 03:41:15] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.472417, train acc = 0.2933 train oa = 0.2933, test acc = 0.1410 test oa = 0.1332
[2024-05-24 03:41:22] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.387905, train acc = 0.3733 train oa = 0.3733, test acc = 0.1539 test oa = 0.1419
[2024-05-24 04:11:19] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.323744, train acc = 0.2533 train oa = 0.2533, test acc = 0.2128 test oa = 0.2370
[2024-05-24 04:11:33] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.271096, train acc = 0.2867 train oa = 0.2867, test acc = 0.1885 test oa = 0.2197
[2024-05-24 04:11:46] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.487265, train acc = 0.2200 train oa = 0.2200, test acc = 0.1506 test oa = 0.1298
[2024-05-24 04:29:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.738693, train acc = 0.4133 train oa = 0.4133, test acc = 0.2224 test oa = 0.2318
[2024-05-24 04:30:07] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.374552, train acc = 0.2533 train oa = 0.2533, test acc = 0.1657 test oa = 0.1436
[2024-05-24 04:30:14] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.869535, train acc = 0.4000 train oa = 0.4000, test acc = 0.1740 test oa = 0.1990
[2024-05-24 05:03:55] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.984690, train acc = 0.4133 train oa = 0.4133, test acc = 0.1911 test oa = 0.1990
[2024-05-24 05:04:02] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.315425, train acc = 0.2933 train oa = 0.2933, test acc = 0.1809 test oa = 0.1730
[2024-05-24 05:04:10] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.428844, train acc = 0.2933 train oa = 0.2933, test acc = 0.1676 test oa = 0.1453
[2024-05-24 05:16:49] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.335608, train acc = 0.2667 train oa = 0.2667, test acc = 0.1692 test oa = 0.1609
[2024-05-24 05:16:57] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.975503, train acc = 0.4267 train oa = 0.4267, test acc = 0.1751 test oa = 0.1955
[2024-05-24 05:17:06] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.345814, train acc = 0.2667 train oa = 0.2667, test acc = 0.1655 test oa = 0.1592
[2024-05-24 05:25:02] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.180483, train acc = 0.3200 train oa = 0.3200, test acc = 0.1828 test oa = 0.1886
[2024-05-24 05:25:15] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.054339, train acc = 0.3667 train oa = 0.3667, test acc = 0.2334 test oa = 0.2474
[2024-05-24 05:25:28] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.516717, train acc = 0.2400 train oa = 0.2400, test acc = 0.1501 test oa = 0.1419
[2024-05-24 05:52:47] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.804582, train acc = 0.4667 train oa = 0.4667, test acc = 0.2153 test oa = 0.1886
[2024-05-24 05:52:55] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.126305, train acc = 0.3467 train oa = 0.3467, test acc = 0.1890 test oa = 0.1678
[2024-05-24 05:53:02] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.744087, train acc = 0.4800 train oa = 0.4800, test acc = 0.2089 test oa = 0.2128
[2024-05-24 06:07:25] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.112594, train acc = 0.2667 train oa = 0.2667, test acc = 0.2538 test oa = 0.2526
[2024-05-24 06:07:37] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.205047, train acc = 0.3000 train oa = 0.3000, test acc = 0.1982 test oa = 0.1955
[2024-05-24 06:07:50] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.333087, train acc = 0.2867 train oa = 0.2867, test acc = 0.1487 test oa = 0.1332
[2024-05-24 06:15:23] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.543031, train acc = 0.2200 train oa = 0.2200, test acc = 0.1452 test oa = 0.1678
[2024-05-24 06:15:37] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.373221, train acc = 0.2733 train oa = 0.2733, test acc = 0.1817 test oa = 0.1747
[2024-05-24 06:15:50] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.254490, train acc = 0.2533 train oa = 0.2533, test acc = 0.1926 test oa = 0.2007
[2024-05-24 06:23:12] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.546665, train acc = 0.2133 train oa = 0.2133, test acc = 0.1128 test oa = 0.1194
[2024-05-24 06:23:25] Evaluate_01: epoch = 0300, train time = 13 s, train loss = 2.256220, train acc = 0.2667 train oa = 0.2667, test acc = 0.1582 test oa = 0.1799
[2024-05-24 06:23:38] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.447972, train acc = 0.2267 train oa = 0.2267, test acc = 0.1378 test oa = 0.1661
[2024-05-24 06:32:34] Evaluate_00: epoch = 0300, train time = 15 s, train loss = 2.237339, train acc = 0.3067 train oa = 0.3067, test acc = 0.1782 test oa = 0.1938
[2024-05-24 06:32:49] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.388342, train acc = 0.2600 train oa = 0.2600, test acc = 0.1587 test oa = 0.1557
[2024-05-24 06:33:05] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 2.538085, train acc = 0.2000 train oa = 0.2000, test acc = 0.1529 test oa = 0.1384
[2024-05-24 06:41:52] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.176472, train acc = 0.3200 train oa = 0.3200, test acc = 0.1641 test oa = 0.1557
[2024-05-24 06:42:07] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.253728, train acc = 0.2933 train oa = 0.2933, test acc = 0.1808 test oa = 0.1938
[2024-05-24 06:42:22] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.270426, train acc = 0.3200 train oa = 0.3200, test acc = 0.1797 test oa = 0.1903
[2024-05-24 06:59:12] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.338345, train acc = 0.2667 train oa = 0.2667, test acc = 0.1622 test oa = 0.1280
[2024-05-24 06:59:18] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.085834, train acc = 0.3867 train oa = 0.3867, test acc = 0.1971 test oa = 0.1799
[2024-05-24 06:59:25] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.991047, train acc = 0.4133 train oa = 0.4133, test acc = 0.2251 test oa = 0.2163
[2024-05-24 07:00:54] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.543971, train acc = 0.2000 train oa = 0.2000, test acc = 0.1198 test oa = 0.1038
[2024-05-24 07:01:07] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.357072, train acc = 0.2467 train oa = 0.2467, test acc = 0.1841 test oa = 0.1713
[2024-05-24 07:01:20] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.353042, train acc = 0.2400 train oa = 0.2400, test acc = 0.1762 test oa = 0.1609
[2024-05-24 07:43:31] Evaluate_00: epoch = 0300, train time = 15 s, train loss = 2.317780, train acc = 0.2533 train oa = 0.2533, test acc = 0.2117 test oa = 0.1869
[2024-05-24 07:43:46] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.317540, train acc = 0.2867 train oa = 0.2867, test acc = 0.1709 test oa = 0.1747
[2024-05-24 07:44:02] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 2.144229, train acc = 0.3533 train oa = 0.3533, test acc = 0.1557 test oa = 0.1505
[2024-05-24 07:45:11] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.184937, train acc = 0.3333 train oa = 0.3333, test acc = 0.1788 test oa = 0.2007
[2024-05-24 07:45:20] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.299670, train acc = 0.3067 train oa = 0.3067, test acc = 0.1786 test oa = 0.2093
[2024-05-24 07:45:28] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.497873, train acc = 0.2267 train oa = 0.2267, test acc = 0.1248 test oa = 0.1367
[2024-05-24 07:52:21] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.982122, train acc = 0.3733 train oa = 0.3733, test acc = 0.2028 test oa = 0.1920
[2024-05-24 07:52:29] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.547655, train acc = 0.5867 train oa = 0.5867, test acc = 0.1715 test oa = 0.2007
[2024-05-24 07:52:38] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.811966, train acc = 0.4933 train oa = 0.4933, test acc = 0.1980 test oa = 0.1886
[2024-05-24 07:53:01] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.317780, train acc = 0.2533 train oa = 0.2533, test acc = 0.2117 test oa = 0.1869
[2024-05-24 07:53:06] Evaluate_00: epoch = 0300, train time = 15 s, train loss = 2.226874, train acc = 0.2733 train oa = 0.2733, test acc = 0.1572 test oa = 0.1626
[2024-05-24 07:53:14] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.317540, train acc = 0.2867 train oa = 0.2867, test acc = 0.1709 test oa = 0.1747
[2024-05-24 07:53:22] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.265472, train acc = 0.2333 train oa = 0.2333, test acc = 0.1855 test oa = 0.1713
[2024-05-24 07:53:27] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.144229, train acc = 0.3533 train oa = 0.3533, test acc = 0.1557 test oa = 0.1505
[2024-05-24 07:53:37] Evaluate_02: epoch = 0300, train time = 15 s, train loss = 2.015762, train acc = 0.4000 train oa = 0.4000, test acc = 0.2590 test oa = 0.2820
[2024-05-24 07:54:05] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.454921, train acc = 0.3067 train oa = 0.3067, test acc = 0.1246 test oa = 0.1263
[2024-05-24 07:54:12] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.977927, train acc = 0.4400 train oa = 0.4400, test acc = 0.1719 test oa = 0.1799
[2024-05-24 07:54:20] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.267756, train acc = 0.3733 train oa = 0.3733, test acc = 0.1602 test oa = 0.1920
[2024-05-24 07:59:50] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.982122, train acc = 0.3733 train oa = 0.3733, test acc = 0.2028 test oa = 0.1920
[2024-05-24 07:59:58] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.547655, train acc = 0.5867 train oa = 0.5867, test acc = 0.1715 test oa = 0.2007
[2024-05-24 08:00:07] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.811966, train acc = 0.4933 train oa = 0.4933, test acc = 0.1980 test oa = 0.1886
[2024-05-24 08:00:30] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.982122, train acc = 0.3733 train oa = 0.3733, test acc = 0.2028 test oa = 0.1920
[2024-05-24 08:00:38] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.547655, train acc = 0.5867 train oa = 0.5867, test acc = 0.1715 test oa = 0.2007
[2024-05-24 08:00:46] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.811966, train acc = 0.4933 train oa = 0.4933, test acc = 0.1980 test oa = 0.1886
[2024-05-24 08:00:56] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.226874, train acc = 0.2733 train oa = 0.2733, test acc = 0.1572 test oa = 0.1626
[2024-05-24 08:01:09] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.265472, train acc = 0.2333 train oa = 0.2333, test acc = 0.1855 test oa = 0.1713
[2024-05-24 08:01:22] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.015762, train acc = 0.4000 train oa = 0.4000, test acc = 0.2590 test oa = 0.2820
[2024-05-24 09:07:46] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.478354, train acc = 0.2933 train oa = 0.2933, test acc = 0.1438 test oa = 0.1263
[2024-05-24 09:07:54] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.226954, train acc = 0.2667 train oa = 0.2667, test acc = 0.1401 test oa = 0.1401
[2024-05-24 09:08:01] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.421192, train acc = 0.2133 train oa = 0.2133, test acc = 0.1848 test oa = 0.1851
[2024-05-24 09:12:40] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.423533, train acc = 0.2800 train oa = 0.2800, test acc = 0.1209 test oa = 0.1125
[2024-05-24 09:12:48] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.287010, train acc = 0.2400 train oa = 0.2400, test acc = 0.2041 test oa = 0.1799
[2024-05-24 09:12:56] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.159524, train acc = 0.2400 train oa = 0.2400, test acc = 0.1909 test oa = 0.1938
[2024-05-24 09:14:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.482433, train acc = 0.1867 train oa = 0.1867, test acc = 0.1127 test oa = 0.1384
[2024-05-24 09:14:19] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.264369, train acc = 0.2800 train oa = 0.2800, test acc = 0.1707 test oa = 0.1644
[2024-05-24 09:14:26] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.238028, train acc = 0.2800 train oa = 0.2800, test acc = 0.1474 test oa = 0.1557
[2024-05-24 09:17:09] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.405736, train acc = 0.2133 train oa = 0.2133, test acc = 0.1654 test oa = 0.1419
[2024-05-24 09:17:16] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.514402, train acc = 0.2133 train oa = 0.2133, test acc = 0.1334 test oa = 0.1298
[2024-05-24 09:17:23] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.398978, train acc = 0.2133 train oa = 0.2133, test acc = 0.1694 test oa = 0.1713
[2024-05-24 09:19:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.807244, train acc = 0.5333 train oa = 0.5333, test acc = 0.2106 test oa = 0.2457
[2024-05-24 09:19:57] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.259835, train acc = 0.7067 train oa = 0.7067, test acc = 0.2052 test oa = 0.2059
[2024-05-24 09:20:05] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.987148, train acc = 0.4000 train oa = 0.4000, test acc = 0.2324 test oa = 0.2543
[2024-05-24 09:20:49] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.807244, train acc = 0.5333 train oa = 0.5333, test acc = 0.2106 test oa = 0.2457
[2024-05-24 09:20:56] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.259835, train acc = 0.7067 train oa = 0.7067, test acc = 0.2052 test oa = 0.2059
[2024-05-24 09:21:03] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.987148, train acc = 0.4000 train oa = 0.4000, test acc = 0.2324 test oa = 0.2543
[2024-05-24 09:23:35] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.156621, train acc = 0.3200 train oa = 0.3200, test acc = 0.1487 test oa = 0.1644
[2024-05-24 09:23:43] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.829535, train acc = 0.4133 train oa = 0.4133, test acc = 0.1568 test oa = 0.1730
[2024-05-24 09:23:50] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.938887, train acc = 0.4267 train oa = 0.4267, test acc = 0.1721 test oa = 0.1592
[2024-05-24 09:27:02] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.477848, train acc = 0.2267 train oa = 0.2267, test acc = 0.1485 test oa = 0.1401
[2024-05-24 09:27:11] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.504667, train acc = 0.2133 train oa = 0.2133, test acc = 0.1429 test oa = 0.1159
[2024-05-24 09:27:19] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.377974, train acc = 0.3200 train oa = 0.3200, test acc = 0.1754 test oa = 0.2024
[2024-05-24 09:48:21] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.903441, train acc = 0.4267 train oa = 0.4267, test acc = 0.2335 test oa = 0.2561
[2024-05-24 09:48:34] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.190738, train acc = 0.3800 train oa = 0.3800, test acc = 0.1801 test oa = 0.1661
[2024-05-24 09:48:47] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.112654, train acc = 0.3733 train oa = 0.3733, test acc = 0.2026 test oa = 0.1903
[2024-05-24 10:02:11] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.178964, train acc = 0.2933 train oa = 0.2933, test acc = 0.1841 test oa = 0.1799
[2024-05-24 10:02:18] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.218534, train acc = 0.2800 train oa = 0.2800, test acc = 0.1866 test oa = 0.1626
[2024-05-24 10:02:25] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.440440, train acc = 0.2133 train oa = 0.2133, test acc = 0.1393 test oa = 0.1107
[2024-05-24 10:05:32] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.178964, train acc = 0.2933 train oa = 0.2933, test acc = 0.1841 test oa = 0.1799
[2024-05-24 10:05:40] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.218534, train acc = 0.2800 train oa = 0.2800, test acc = 0.1866 test oa = 0.1626
[2024-05-24 10:05:48] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.440440, train acc = 0.2133 train oa = 0.2133, test acc = 0.1393 test oa = 0.1107
[2024-05-24 10:20:57] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.125541, train acc = 0.3200 train oa = 0.3200, test acc = 0.1750 test oa = 0.1471
[2024-05-24 10:21:06] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.419597, train acc = 0.2667 train oa = 0.2667, test acc = 0.1241 test oa = 0.1142
[2024-05-24 10:21:14] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.238727, train acc = 0.3067 train oa = 0.3067, test acc = 0.1694 test oa = 0.1522
[2024-05-24 10:36:00] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.144080, train acc = 0.3133 train oa = 0.3133, test acc = 0.1950 test oa = 0.1765
[2024-05-24 10:36:15] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.041245, train acc = 0.3467 train oa = 0.3467, test acc = 0.1621 test oa = 0.1505
[2024-05-24 10:36:30] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.244159, train acc = 0.3067 train oa = 0.3067, test acc = 0.2033 test oa = 0.1869
[2024-05-24 10:55:07] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.302164, train acc = 0.2533 train oa = 0.2533, test acc = 0.1981 test oa = 0.1869
[2024-05-24 10:55:20] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.989964, train acc = 0.3200 train oa = 0.3200, test acc = 0.2171 test oa = 0.1938
[2024-05-24 10:55:33] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.137610, train acc = 0.3733 train oa = 0.3733, test acc = 0.1903 test oa = 0.1799
[2024-05-24 11:12:39] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.912144, train acc = 0.4667 train oa = 0.4667, test acc = 0.2058 test oa = 0.1920
[2024-05-24 11:12:52] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.859552, train acc = 0.4533 train oa = 0.4533, test acc = 0.2518 test oa = 0.2664
[2024-05-24 11:13:05] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.007176, train acc = 0.4200 train oa = 0.4200, test acc = 0.2202 test oa = 0.2612
[2024-05-24 11:35:46] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 1.977413, train acc = 0.3933 train oa = 0.3933, test acc = 0.2929 test oa = 0.3010
[2024-05-24 11:36:02] Evaluate_01: epoch = 0300, train time = 15 s, train loss = 2.106620, train acc = 0.3333 train oa = 0.3333, test acc = 0.2264 test oa = 0.2197
[2024-05-24 11:36:16] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.085888, train acc = 0.3533 train oa = 0.3533, test acc = 0.2251 test oa = 0.2266
[2024-05-24 11:46:48] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.215342, train acc = 0.2933 train oa = 0.2933, test acc = 0.1663 test oa = 0.1557
[2024-05-24 11:46:56] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.534625, train acc = 0.2667 train oa = 0.2667, test acc = 0.1204 test oa = 0.1540
[2024-05-24 11:47:03] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.517432, train acc = 0.3333 train oa = 0.3333, test acc = 0.1384 test oa = 0.1367
[2024-05-24 12:48:33] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.504809, train acc = 0.2533 train oa = 0.2533, test acc = 0.1846 test oa = 0.1782
[2024-05-24 12:48:41] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.580206, train acc = 0.1867 train oa = 0.1867, test acc = 0.1206 test oa = 0.1349
[2024-05-24 12:48:49] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 2.560852, train acc = 0.1733 train oa = 0.1733, test acc = 0.1420 test oa = 0.1471
[2024-05-24 12:55:36] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.344532, train acc = 0.2800 train oa = 0.2800, test acc = 0.1678 test oa = 0.1522
[2024-05-24 12:55:44] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.974887, train acc = 0.3733 train oa = 0.3733, test acc = 0.2531 test oa = 0.2093
[2024-05-24 12:55:53] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.193056, train acc = 0.2933 train oa = 0.2933, test acc = 0.2321 test oa = 0.2180
[2024-05-24 13:02:45] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.807244, train acc = 0.5333 train oa = 0.5333, test acc = 0.2106 test oa = 0.2457
[2024-05-24 13:02:53] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.259835, train acc = 0.7067 train oa = 0.7067, test acc = 0.2052 test oa = 0.2059
[2024-05-24 13:03:01] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.987148, train acc = 0.4000 train oa = 0.4000, test acc = 0.2324 test oa = 0.2543
[2024-05-24 13:38:02] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.412000, train acc = 0.3467 train oa = 0.3467, test acc = 0.1506 test oa = 0.1696
[2024-05-24 13:38:09] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.297982, train acc = 0.3200 train oa = 0.3200, test acc = 0.1555 test oa = 0.1488
[2024-05-24 13:38:17] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.344800, train acc = 0.3067 train oa = 0.3067, test acc = 0.1515 test oa = 0.1626
[2024-05-24 14:06:30] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.469357, train acc = 0.3067 train oa = 0.3067, test acc = 0.1305 test oa = 0.1194
[2024-05-24 14:06:38] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.507731, train acc = 0.2267 train oa = 0.2267, test acc = 0.1297 test oa = 0.1211
[2024-05-24 14:06:45] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.364843, train acc = 0.2667 train oa = 0.2667, test acc = 0.1399 test oa = 0.1367
[2024-05-24 14:16:17] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.326074, train acc = 0.2800 train oa = 0.2800, test acc = 0.1985 test oa = 0.1955
[2024-05-24 14:16:25] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 2.207395, train acc = 0.3600 train oa = 0.3600, test acc = 0.1940 test oa = 0.1920
[2024-05-24 14:16:33] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.460624, train acc = 0.2000 train oa = 0.2000, test acc = 0.1655 test oa = 0.1592
[2024-05-24 14:23:32] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.807244, train acc = 0.5333 train oa = 0.5333, test acc = 0.2106 test oa = 0.2457
[2024-05-24 14:23:40] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.259835, train acc = 0.7067 train oa = 0.7067, test acc = 0.2052 test oa = 0.2059
[2024-05-24 14:23:48] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.987148, train acc = 0.4000 train oa = 0.4000, test acc = 0.2324 test oa = 0.2543
[2024-05-24 14:39:59] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.243801, train acc = 0.3067 train oa = 0.3067, test acc = 0.1453 test oa = 0.1419
[2024-05-24 14:40:12] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.536679, train acc = 0.1933 train oa = 0.1933, test acc = 0.1470 test oa = 0.1522
[2024-05-24 14:40:25] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.508226, train acc = 0.3200 train oa = 0.3200, test acc = 0.1235 test oa = 0.1280
[2024-05-24 14:46:42] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.326074, train acc = 0.2800 train oa = 0.2800, test acc = 0.1985 test oa = 0.1955
[2024-05-24 14:46:49] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.207395, train acc = 0.3600 train oa = 0.3600, test acc = 0.1940 test oa = 0.1920
[2024-05-24 14:46:57] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.460624, train acc = 0.2000 train oa = 0.2000, test acc = 0.1655 test oa = 0.1592
[2024-05-24 14:53:22] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.477848, train acc = 0.2267 train oa = 0.2267, test acc = 0.1485 test oa = 0.1401
[2024-05-24 14:53:30] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.504667, train acc = 0.2133 train oa = 0.2133, test acc = 0.1429 test oa = 0.1159
[2024-05-24 14:53:37] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.377974, train acc = 0.3200 train oa = 0.3200, test acc = 0.1754 test oa = 0.2024
[2024-05-24 14:59:58] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.114873, train acc = 0.8000 train oa = 0.8000, test acc = 0.2254 test oa = 0.2370
[2024-05-24 15:00:05] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.064943, train acc = 0.8000 train oa = 0.8000, test acc = 0.1778 test oa = 0.1747
[2024-05-24 15:00:12] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.454080, train acc = 0.6933 train oa = 0.6933, test acc = 0.1774 test oa = 0.1799
[2024-05-24 15:00:19] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.734049, train acc = 0.5467 train oa = 0.5467, test acc = 0.2188 test oa = 0.2232
[2024-05-24 15:00:27] Evaluate_01: epoch = 0300, train time = 8 s, train loss = 1.685330, train acc = 0.4667 train oa = 0.4667, test acc = 0.2001 test oa = 0.2301
[2024-05-24 15:00:35] Evaluate_02: epoch = 0300, train time = 8 s, train loss = 1.536779, train acc = 0.4667 train oa = 0.4667, test acc = 0.1964 test oa = 0.2128
[2024-05-24 15:07:25] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 2.200179, train acc = 0.2667 train oa = 0.2667, test acc = 0.1803 test oa = 0.1661
[2024-05-24 15:07:33] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.172072, train acc = 0.3067 train oa = 0.3067, test acc = 0.1870 test oa = 0.1696
[2024-05-24 15:07:41] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.461169, train acc = 0.2133 train oa = 0.2133, test acc = 0.1530 test oa = 0.1713
[2024-05-24 15:14:20] Evaluate_00: epoch = 0300, train time = 8 s, train loss = 1.690184, train acc = 0.5200 train oa = 0.5200, test acc = 0.2115 test oa = 0.2042
[2024-05-24 15:14:28] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.500491, train acc = 0.6133 train oa = 0.6133, test acc = 0.2412 test oa = 0.2491
[2024-05-24 15:14:36] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.596088, train acc = 0.6000 train oa = 0.6000, test acc = 0.1838 test oa = 0.2197
[2024-05-24 15:15:13] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.326074, train acc = 0.2800 train oa = 0.2800, test acc = 0.1985 test oa = 0.1955
[2024-05-24 15:15:21] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.207395, train acc = 0.3600 train oa = 0.3600, test acc = 0.1940 test oa = 0.1920
[2024-05-24 15:15:28] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.460624, train acc = 0.2000 train oa = 0.2000, test acc = 0.1655 test oa = 0.1592
[2024-05-24 15:21:59] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.156621, train acc = 0.3200 train oa = 0.3200, test acc = 0.1487 test oa = 0.1644
[2024-05-24 15:22:06] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.829535, train acc = 0.4133 train oa = 0.4133, test acc = 0.1568 test oa = 0.1730
[2024-05-24 15:22:13] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.938887, train acc = 0.4267 train oa = 0.4267, test acc = 0.1721 test oa = 0.1592
[2024-05-24 15:33:08] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.261765, train acc = 0.2933 train oa = 0.2933, test acc = 0.1779 test oa = 0.1522
[2024-05-24 15:33:15] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.257926, train acc = 0.2400 train oa = 0.2400, test acc = 0.1692 test oa = 0.1401
[2024-05-24 15:33:21] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.380063, train acc = 0.3333 train oa = 0.3333, test acc = 0.1899 test oa = 0.1609
[2024-05-24 15:39:40] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.114873, train acc = 0.8000 train oa = 0.8000, test acc = 0.2254 test oa = 0.2370
[2024-05-24 15:39:47] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.064943, train acc = 0.8000 train oa = 0.8000, test acc = 0.1778 test oa = 0.1747
[2024-05-24 15:39:54] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 1.454080, train acc = 0.6933 train oa = 0.6933, test acc = 0.1774 test oa = 0.1799
[2024-05-24 15:44:22] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.130967, train acc = 0.3867 train oa = 0.3867, test acc = 0.1836 test oa = 0.1938
[2024-05-24 15:44:36] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.353663, train acc = 0.2800 train oa = 0.2800, test acc = 0.1522 test oa = 0.1522
[2024-05-24 15:44:51] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.497344, train acc = 0.2667 train oa = 0.2667, test acc = 0.1752 test oa = 0.1765
[2024-05-24 15:54:56] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.564016, train acc = 0.2000 train oa = 0.2000, test acc = 0.1383 test oa = 0.1246
[2024-05-24 15:55:03] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.521109, train acc = 0.2133 train oa = 0.2133, test acc = 0.1273 test oa = 0.1159
[2024-05-24 15:55:10] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.187243, train acc = 0.2400 train oa = 0.2400, test acc = 0.1681 test oa = 0.1540
[2024-05-24 16:04:43] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.386418, train acc = 0.2733 train oa = 0.2733, test acc = 0.1466 test oa = 0.1471
[2024-05-24 16:04:55] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.483442, train acc = 0.2467 train oa = 0.2467, test acc = 0.1177 test oa = 0.1159
[2024-05-24 16:05:08] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.177265, train acc = 0.2733 train oa = 0.2733, test acc = 0.1893 test oa = 0.1799
[2024-05-24 17:18:55] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.446808, train acc = 0.2600 train oa = 0.2600, test acc = 0.2210 test oa = 0.2093
[2024-05-24 17:19:08] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.248759, train acc = 0.3067 train oa = 0.3067, test acc = 0.2193 test oa = 0.1903
[2024-05-24 17:19:20] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.301247, train acc = 0.2867 train oa = 0.2867, test acc = 0.1826 test oa = 0.2128
[2024-05-24 17:26:41] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.338150, train acc = 0.3000 train oa = 0.3000, test acc = 0.1608 test oa = 0.1349
[2024-05-24 17:26:54] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.087734, train acc = 0.3400 train oa = 0.3400, test acc = 0.2105 test oa = 0.2059
[2024-05-24 17:27:06] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.049936, train acc = 0.3400 train oa = 0.3400, test acc = 0.1971 test oa = 0.1592
[2024-05-24 18:29:52] Evaluate_00: epoch = 0300, train time = 6 s, train loss = 2.468182, train acc = 0.2933 train oa = 0.2933, test acc = 0.1154 test oa = 0.1107
[2024-05-24 18:29:59] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.364638, train acc = 0.2533 train oa = 0.2533, test acc = 0.1667 test oa = 0.1453
[2024-05-24 18:30:06] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 1.939544, train acc = 0.4400 train oa = 0.4400, test acc = 0.2038 test oa = 0.1834
[2024-05-24 18:30:25] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.894840, train acc = 0.4333 train oa = 0.4333, test acc = 0.2831 test oa = 0.2924
[2024-05-24 18:30:38] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.941386, train acc = 0.4200 train oa = 0.4200, test acc = 0.2463 test oa = 0.2457
[2024-05-24 18:30:50] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.198418, train acc = 0.3067 train oa = 0.3067, test acc = 0.2249 test oa = 0.2163
[2024-05-24 19:08:45] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.494170, train acc = 0.2400 train oa = 0.2400, test acc = 0.1460 test oa = 0.1107
[2024-05-24 19:08:52] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.280329, train acc = 0.3333 train oa = 0.3333, test acc = 0.1957 test oa = 0.1730
[2024-05-24 19:08:59] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.560050, train acc = 0.1467 train oa = 0.1467, test acc = 0.1251 test oa = 0.0986
[2024-05-24 19:09:40] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.973183, train acc = 0.4267 train oa = 0.4267, test acc = 0.2462 test oa = 0.2734
[2024-05-24 19:09:52] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.463346, train acc = 0.2333 train oa = 0.2333, test acc = 0.1510 test oa = 0.1315
[2024-05-24 19:10:04] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.093940, train acc = 0.3133 train oa = 0.3133, test acc = 0.2295 test oa = 0.2457
[2024-05-24 19:15:16] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.515942, train acc = 0.2000 train oa = 0.2000, test acc = 0.1464 test oa = 0.1246
[2024-05-24 19:15:24] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 2.292120, train acc = 0.2933 train oa = 0.2933, test acc = 0.1505 test oa = 0.1436
[2024-05-24 19:15:31] Evaluate_02: epoch = 0300, train time = 7 s, train loss = 2.030889, train acc = 0.4000 train oa = 0.4000, test acc = 0.2199 test oa = 0.2232
[2024-05-24 19:22:03] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 2.344532, train acc = 0.2800 train oa = 0.2800, test acc = 0.1678 test oa = 0.1522
[2024-05-24 19:22:11] Evaluate_01: epoch = 0300, train time = 7 s, train loss = 1.974887, train acc = 0.3733 train oa = 0.3733, test acc = 0.2531 test oa = 0.2093
[2024-05-24 19:22:18] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.193056, train acc = 0.2933 train oa = 0.2933, test acc = 0.2321 test oa = 0.2180
[2024-05-24 19:54:08] Evaluate_00: epoch = 0300, train time = 7 s, train loss = 1.896852, train acc = 0.5067 train oa = 0.5067, test acc = 0.2271 test oa = 0.2612
[2024-05-24 19:54:16] Evaluate_01: epoch = 0300, train time = 6 s, train loss = 2.358134, train acc = 0.3467 train oa = 0.3467, test acc = 0.1469 test oa = 0.1453
[2024-05-24 19:54:23] Evaluate_02: epoch = 0300, train time = 6 s, train loss = 2.015358, train acc = 0.2800 train oa = 0.2800, test acc = 0.2338 test oa = 0.2388
[2024-05-24 20:00:02] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.551084, train acc = 0.2400 train oa = 0.2400, test acc = 0.1494 test oa = 0.1263
[2024-05-24 20:00:14] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.455649, train acc = 0.2667 train oa = 0.2667, test acc = 0.1780 test oa = 0.1747
[2024-05-24 20:00:26] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.493226, train acc = 0.2067 train oa = 0.2067, test acc = 0.1536 test oa = 0.1419
[2024-05-24 20:43:12] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.359554, train acc = 0.3000 train oa = 0.3000, test acc = 0.1548 test oa = 0.1540
[2024-05-24 20:43:24] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.343346, train acc = 0.3200 train oa = 0.3200, test acc = 0.1802 test oa = 0.1730
[2024-05-24 20:43:37] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.187540, train acc = 0.3467 train oa = 0.3467, test acc = 0.1898 test oa = 0.2145
[2024-05-24 21:04:19] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.359554, train acc = 0.3000 train oa = 0.3000, test acc = 0.1548 test oa = 0.1540
[2024-05-24 21:04:33] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.343346, train acc = 0.3200 train oa = 0.3200, test acc = 0.1802 test oa = 0.1730
[2024-05-24 21:04:48] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.187540, train acc = 0.3467 train oa = 0.3467, test acc = 0.1898 test oa = 0.2145
[2024-05-24 21:43:22] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.090286, train acc = 0.3533 train oa = 0.3533, test acc = 0.2342 test oa = 0.2543
[2024-05-24 21:43:34] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.173651, train acc = 0.3333 train oa = 0.3333, test acc = 0.1834 test oa = 0.1817
[2024-05-24 21:43:46] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.035772, train acc = 0.3933 train oa = 0.3933, test acc = 0.1882 test oa = 0.1851
[2024-05-24 22:28:17] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.090286, train acc = 0.3533 train oa = 0.3533, test acc = 0.2342 test oa = 0.2543
[2024-05-24 22:28:30] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.173651, train acc = 0.3333 train oa = 0.3333, test acc = 0.1834 test oa = 0.1817
[2024-05-24 22:28:42] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.035772, train acc = 0.3933 train oa = 0.3933, test acc = 0.1882 test oa = 0.1851
[2024-05-24 22:47:13] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.549804, train acc = 0.1800 train oa = 0.1800, test acc = 0.1527 test oa = 0.1401
[2024-05-24 22:47:25] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.417019, train acc = 0.2600 train oa = 0.2600, test acc = 0.1850 test oa = 0.2007
[2024-05-24 22:47:37] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.546661, train acc = 0.2333 train oa = 0.2333, test acc = 0.1316 test oa = 0.1246
[2024-05-24 23:05:04] Evaluate_00: epoch = 0300, train time = 13 s, train loss = 2.090286, train acc = 0.3533 train oa = 0.3533, test acc = 0.2342 test oa = 0.2543
[2024-05-24 23:05:18] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.173651, train acc = 0.3333 train oa = 0.3333, test acc = 0.1834 test oa = 0.1817
[2024-05-24 23:05:32] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.035772, train acc = 0.3933 train oa = 0.3933, test acc = 0.1882 test oa = 0.1851
[2024-05-24 23:33:31] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.549804, train acc = 0.1800 train oa = 0.1800, test acc = 0.1527 test oa = 0.1401
[2024-05-24 23:33:43] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.417019, train acc = 0.2600 train oa = 0.2600, test acc = 0.1850 test oa = 0.2007
[2024-05-24 23:33:56] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.546661, train acc = 0.2333 train oa = 0.2333, test acc = 0.1316 test oa = 0.1246
[2024-05-24 23:51:08] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.325375, train acc = 0.2800 train oa = 0.2800, test acc = 0.1916 test oa = 0.2232
[2024-05-24 23:51:20] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 2.231647, train acc = 0.2800 train oa = 0.2800, test acc = 0.1696 test oa = 0.1696
[2024-05-24 23:51:32] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.242856, train acc = 0.3267 train oa = 0.3267, test acc = 0.2053 test oa = 0.2076
[2024-05-25 00:21:23] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.325375, train acc = 0.2800 train oa = 0.2800, test acc = 0.1916 test oa = 0.2232
[2024-05-25 00:21:38] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.231647, train acc = 0.2800 train oa = 0.2800, test acc = 0.1696 test oa = 0.1696
[2024-05-25 00:21:53] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.242856, train acc = 0.3267 train oa = 0.3267, test acc = 0.2053 test oa = 0.2076
[2024-05-25 00:38:47] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.325375, train acc = 0.2800 train oa = 0.2800, test acc = 0.1916 test oa = 0.2232
[2024-05-25 00:39:00] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.231647, train acc = 0.2800 train oa = 0.2800, test acc = 0.1696 test oa = 0.1696
[2024-05-25 00:39:12] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.242856, train acc = 0.3267 train oa = 0.3267, test acc = 0.2053 test oa = 0.2076
[2024-05-25 00:56:20] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 2.117046, train acc = 0.2533 train oa = 0.2533, test acc = 0.1871 test oa = 0.1644
[2024-05-25 00:56:32] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.450438, train acc = 0.2733 train oa = 0.2733, test acc = 0.1336 test oa = 0.1159
[2024-05-25 00:56:44] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.441539, train acc = 0.2600 train oa = 0.2600, test acc = 0.1725 test oa = 0.1747
[2024-05-25 01:39:36] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.117046, train acc = 0.2533 train oa = 0.2533, test acc = 0.1871 test oa = 0.1644
[2024-05-25 01:39:51] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.450438, train acc = 0.2733 train oa = 0.2733, test acc = 0.1336 test oa = 0.1159
[2024-05-25 01:40:06] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.441539, train acc = 0.2600 train oa = 0.2600, test acc = 0.1725 test oa = 0.1747
[2024-05-25 01:45:13] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.117046, train acc = 0.2533 train oa = 0.2533, test acc = 0.1871 test oa = 0.1644
[2024-05-25 01:45:26] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.450438, train acc = 0.2733 train oa = 0.2733, test acc = 0.1336 test oa = 0.1159
[2024-05-25 01:45:38] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.441539, train acc = 0.2600 train oa = 0.2600, test acc = 0.1725 test oa = 0.1747
[2024-05-25 02:00:31] Evaluate_00: epoch = 0300, train time = 11 s, train loss = 1.739470, train acc = 0.5467 train oa = 0.5467, test acc = 0.2709 test oa = 0.2872
[2024-05-25 02:00:43] Evaluate_01: epoch = 0300, train time = 11 s, train loss = 1.729284, train acc = 0.5067 train oa = 0.5067, test acc = 0.2875 test oa = 0.2976
[2024-05-25 02:00:55] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.092698, train acc = 0.3467 train oa = 0.3467, test acc = 0.2029 test oa = 0.1990
[2024-05-25 03:05:18] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.369992, train acc = 0.2600 train oa = 0.2600, test acc = 0.2018 test oa = 0.1765
[2024-05-25 03:05:31] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.368996, train acc = 0.2200 train oa = 0.2200, test acc = 0.1622 test oa = 0.1661
[2024-05-25 03:05:43] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.321219, train acc = 0.2733 train oa = 0.2733, test acc = 0.1900 test oa = 0.1696
[2024-05-25 03:12:53] Evaluate_00: epoch = 0300, train time = 14 s, train loss = 2.369992, train acc = 0.2600 train oa = 0.2600, test acc = 0.2018 test oa = 0.1765
[2024-05-25 03:13:08] Evaluate_01: epoch = 0300, train time = 14 s, train loss = 2.368996, train acc = 0.2200 train oa = 0.2200, test acc = 0.1622 test oa = 0.1661
[2024-05-25 03:13:22] Evaluate_02: epoch = 0300, train time = 14 s, train loss = 2.321219, train acc = 0.2733 train oa = 0.2733, test acc = 0.1900 test oa = 0.1696
[2024-05-25 03:20:00] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.348439, train acc = 0.2267 train oa = 0.2267, test acc = 0.1998 test oa = 0.1869
[2024-05-25 03:20:12] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.266980, train acc = 0.2800 train oa = 0.2800, test acc = 0.1726 test oa = 0.1574
[2024-05-25 03:20:24] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.305939, train acc = 0.3000 train oa = 0.3000, test acc = 0.1967 test oa = 0.2128
[2024-05-25 04:24:07] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.492168, train acc = 0.2267 train oa = 0.2267, test acc = 0.1164 test oa = 0.1332
[2024-05-25 04:24:19] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.404070, train acc = 0.3000 train oa = 0.3000, test acc = 0.1493 test oa = 0.1367
[2024-05-25 04:24:31] Evaluate_02: epoch = 0300, train time = 11 s, train loss = 2.541081, train acc = 0.1867 train oa = 0.1867, test acc = 0.1344 test oa = 0.1471
[2024-05-25 07:39:56] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.446733, train acc = 0.3000 train oa = 0.3000, test acc = 0.1832 test oa = 0.1713
[2024-05-25 07:40:09] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.295813, train acc = 0.2867 train oa = 0.2867, test acc = 0.1472 test oa = 0.1453
[2024-05-25 07:40:22] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.331676, train acc = 0.2800 train oa = 0.2800, test acc = 0.1902 test oa = 0.1851
[2024-05-25 08:19:06] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.446733, train acc = 0.3000 train oa = 0.3000, test acc = 0.1832 test oa = 0.1713
[2024-05-25 08:19:20] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.295813, train acc = 0.2867 train oa = 0.2867, test acc = 0.1472 test oa = 0.1453
[2024-05-25 08:19:33] Evaluate_02: epoch = 0300, train time = 13 s, train loss = 2.331676, train acc = 0.2800 train oa = 0.2800, test acc = 0.1902 test oa = 0.1851
[2024-05-25 08:46:05] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.995614, train acc = 0.3733 train oa = 0.3733, test acc = 0.1939 test oa = 0.1782
[2024-05-25 08:46:17] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.054867, train acc = 0.3467 train oa = 0.3467, test acc = 0.1828 test oa = 0.1851
[2024-05-25 08:46:30] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.286415, train acc = 0.3200 train oa = 0.3200, test acc = 0.1737 test oa = 0.1419
[2024-05-25 10:40:35] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.893710, train acc = 0.4267 train oa = 0.4267, test acc = 0.2021 test oa = 0.2093
[2024-05-25 10:40:48] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.946971, train acc = 0.4267 train oa = 0.4267, test acc = 0.2460 test oa = 0.2318
[2024-05-25 10:41:01] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.386995, train acc = 0.2800 train oa = 0.2800, test acc = 0.1803 test oa = 0.1678
[2024-05-25 11:00:14] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 1.893710, train acc = 0.4267 train oa = 0.4267, test acc = 0.2021 test oa = 0.2093
[2024-05-25 11:00:27] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.946971, train acc = 0.4267 train oa = 0.4267, test acc = 0.2460 test oa = 0.2318
[2024-05-25 11:00:40] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.386995, train acc = 0.2800 train oa = 0.2800, test acc = 0.1803 test oa = 0.1678
[2024-05-25 11:21:30] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.131295, train acc = 0.3867 train oa = 0.3867, test acc = 0.2660 test oa = 0.2647
[2024-05-25 11:21:43] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.932930, train acc = 0.4200 train oa = 0.4200, test acc = 0.2585 test oa = 0.2457
[2024-05-25 11:21:56] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.007721, train acc = 0.3800 train oa = 0.3800, test acc = 0.2778 test oa = 0.2561
[2024-05-25 11:31:03] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.176472, train acc = 0.3200 train oa = 0.3200, test acc = 0.1641 test oa = 0.1557
[2024-05-25 11:31:16] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.253728, train acc = 0.2933 train oa = 0.2933, test acc = 0.1808 test oa = 0.1938
[2024-05-25 11:31:29] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.270426, train acc = 0.3200 train oa = 0.3200, test acc = 0.1797 test oa = 0.1903
[2024-05-25 11:40:44] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.131295, train acc = 0.3867 train oa = 0.3867, test acc = 0.2660 test oa = 0.2647
[2024-05-25 11:40:56] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 1.932930, train acc = 0.4200 train oa = 0.4200, test acc = 0.2585 test oa = 0.2457
[2024-05-25 11:41:09] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.007721, train acc = 0.3800 train oa = 0.3800, test acc = 0.2778 test oa = 0.2561
[2024-05-25 16:13:12] Evaluate_00: epoch = 0300, train time = 12 s, train loss = 2.284961, train acc = 0.2867 train oa = 0.2867, test acc = 0.2023 test oa = 0.1869
[2024-05-25 16:13:24] Evaluate_01: epoch = 0300, train time = 12 s, train loss = 2.327033, train acc = 0.2667 train oa = 0.2667, test acc = 0.1700 test oa = 0.1592
[2024-05-25 16:13:37] Evaluate_02: epoch = 0300, train time = 12 s, train loss = 2.285912, train acc = 0.2733 train oa = 0.2733, test acc = 0.1700 test oa = 0.1644

================== Exp 0 ==================
 
[2024-08-14 13:35:19] iter = 0000, loss = 238.5967
[2024-08-14 13:38:27] iter = 0010, loss = 146.1432
[2024-08-14 13:41:42] iter = 0020, loss = 137.0687
[2024-08-14 13:45:01] iter = 0030, loss = 126.6219
[2024-08-14 13:48:22] iter = 0040, loss = 128.8963
[2024-08-14 13:51:39] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.088003, train acc = 1.0000 train oa = 1.0000, test acc = 0.4204 test oa = 0.4394
Evaluate 1, mean = 0.4204 std = 0.0000
-------------------------
[2024-08-14 13:52:19] iter = 0050, loss = 128.5054
[2024-08-14 13:55:40] iter = 0060, loss = 128.5075
[2024-08-14 13:59:01] iter = 0070, loss = 122.6224
[2024-08-14 14:02:22] iter = 0080, loss = 121.3064
[2024-08-14 14:05:44] iter = 0090, loss = 126.7096
[2024-08-14 14:09:02] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.094674, train acc = 1.0000 train oa = 1.0000, test acc = 0.4425 test oa = 0.4567
Evaluate 1, mean = 0.4425 std = 0.0000
-------------------------
[2024-08-14 14:09:43] iter = 0100, loss = 131.4795
[2024-08-14 14:13:04] iter = 0110, loss = 123.9285
[2024-08-14 14:16:27] iter = 0120, loss = 116.7833
[2024-08-14 14:19:49] iter = 0130, loss = 126.3561
[2024-08-14 14:23:10] iter = 0140, loss = 123.4196
[2024-08-14 14:26:27] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.099300, train acc = 1.0000 train oa = 1.0000, test acc = 0.4433 test oa = 0.4723
Evaluate 1, mean = 0.4433 std = 0.0000
-------------------------
[2024-08-14 14:27:07] iter = 0150, loss = 118.0901
[2024-08-14 14:30:29] iter = 0160, loss = 113.9487
[2024-08-14 14:33:51] iter = 0170, loss = 131.1009
[2024-08-14 14:37:13] iter = 0180, loss = 112.4840
[2024-08-14 14:40:36] iter = 0190, loss = 127.8011
[2024-08-14 14:43:54] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.106378, train acc = 1.0000 train oa = 1.0000, test acc = 0.4163 test oa = 0.4273
Evaluate 1, mean = 0.4163 std = 0.0000
-------------------------
[2024-08-14 14:44:35] iter = 0200, loss = 125.0205

================== Exp 0 ==================
 
[2024-08-14 15:03:52] iter = 0000, loss = 238.5967
[2024-08-14 15:07:09] iter = 0010, loss = 146.1432
[2024-08-14 15:11:12] iter = 0020, loss = 137.0687
[2024-08-14 15:14:47] iter = 0030, loss = 126.6219
[2024-08-14 15:18:14] iter = 0040, loss = 128.8963
[2024-08-14 15:21:32] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.088003, train acc = 1.0000 train oa = 1.0000, test acc = 0.4204 test oa = 0.4394
Evaluate 1, mean = 0.4204 std = 0.0000
-------------------------

================== Exp 0 ==================
 
[2024-08-14 15:22:37] iter = 0000, loss = 263.9257
[2024-08-14 15:24:12] iter = 0010, loss = 158.6304
[2024-08-14 15:25:52] iter = 0020, loss = 139.5027
[2024-08-14 15:27:32] iter = 0030, loss = 136.4854
[2024-08-14 15:29:12] iter = 0040, loss = 128.8280
[2024-08-14 15:31:08] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.087078, train acc = 1.0000 train oa = 1.0000, test acc = 0.4656 test oa = 0.4394
Evaluate 1, mean = 0.4656 std = 0.0000
-------------------------
[2024-08-14 15:31:28] iter = 0050, loss = 126.2604
[2024-08-14 15:33:08] iter = 0060, loss = 119.1128
[2024-08-14 15:34:48] iter = 0070, loss = 126.9661
[2024-08-14 15:36:29] iter = 0080, loss = 133.4498
[2024-08-14 15:38:08] iter = 0090, loss = 122.5238
[2024-08-14 15:40:01] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.098478, train acc = 1.0000 train oa = 1.0000, test acc = 0.3991 test oa = 0.4412
Evaluate 1, mean = 0.3991 std = 0.0000
-------------------------
[2024-08-14 15:40:21] iter = 0100, loss = 118.6829
[2024-08-14 15:42:02] iter = 0110, loss = 123.1646
[2024-08-14 15:43:40] iter = 0120, loss = 121.2150
[2024-08-14 15:45:20] iter = 0130, loss = 120.1655
[2024-08-14 15:47:00] iter = 0140, loss = 112.0779
[2024-08-14 15:48:54] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.092112, train acc = 1.0000 train oa = 1.0000, test acc = 0.4592 test oa = 0.4516
Evaluate 1, mean = 0.4592 std = 0.0000
-------------------------
[2024-08-14 15:49:14] iter = 0150, loss = 116.4919
[2024-08-14 15:50:55] iter = 0160, loss = 116.3953
[2024-08-14 15:52:34] iter = 0170, loss = 110.9719
[2024-08-14 15:54:14] iter = 0180, loss = 117.0151
[2024-08-14 15:55:53] iter = 0190, loss = 116.2298
[2024-08-14 15:57:47] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.082257, train acc = 1.0000 train oa = 1.0000, test acc = 0.4127 test oa = 0.4446
Evaluate 1, mean = 0.4127 std = 0.0000
-------------------------
[2024-08-14 15:58:07] iter = 0200, loss = 115.5474

================== Exp 0 ==================
 
[2024-08-14 16:17:23] iter = 0000, loss = 234.6939
[2024-08-14 16:19:59] iter = 0010, loss = 134.0788
[2024-08-14 16:22:53] iter = 0020, loss = 133.8759
[2024-08-14 16:25:51] iter = 0030, loss = 128.4814
[2024-08-14 16:28:50] iter = 0040, loss = 123.6899
[2024-08-14 16:31:50] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.086425, train acc = 1.0000 train oa = 1.0000, test acc = 0.4478 test oa = 0.4567
Evaluate 1, mean = 0.4478 std = 0.0000
-------------------------
[2024-08-14 16:32:33] iter = 0050, loss = 120.4464
[2024-08-14 16:35:35] iter = 0060, loss = 116.1447
[2024-08-14 16:38:39] iter = 0070, loss = 116.1302
[2024-08-14 16:42:45] iter = 0080, loss = 120.6827
[2024-08-14 16:45:46] iter = 0090, loss = 120.8154
[2024-08-14 16:48:44] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.105903, train acc = 1.0000 train oa = 1.0000, test acc = 0.4049 test oa = 0.4291
Evaluate 1, mean = 0.4049 std = 0.0000
-------------------------
[2024-08-14 16:49:21] iter = 0100, loss = 133.7900
[2024-08-14 16:52:22] iter = 0110, loss = 121.8606
[2024-08-14 16:55:23] iter = 0120, loss = 120.3402
[2024-08-14 16:58:25] iter = 0130, loss = 122.1055
[2024-08-14 17:01:27] iter = 0140, loss = 118.3424
[2024-08-14 17:04:27] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.092504, train acc = 1.0000 train oa = 1.0000, test acc = 0.4297 test oa = 0.4533
Evaluate 1, mean = 0.4297 std = 0.0000
-------------------------
[2024-08-14 17:05:04] iter = 0150, loss = 118.4754
[2024-08-14 17:08:06] iter = 0160, loss = 121.1931
[2024-08-14 17:11:08] iter = 0170, loss = 120.2694
[2024-08-14 17:14:10] iter = 0180, loss = 120.6207
[2024-08-14 17:17:12] iter = 0190, loss = 112.0369
[2024-08-14 17:20:14] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.102339, train acc = 1.0000 train oa = 1.0000, test acc = 0.4456 test oa = 0.4377
Evaluate 1, mean = 0.4456 std = 0.0000
-------------------------
[2024-08-14 17:20:51] iter = 0200, loss = 123.7858

================== Exp 0 ==================
 
[2024-08-14 18:10:34] iter = 0000, loss = 328.2344
[2024-08-14 18:10:41] iter = 0010, loss = 246.6310
[2024-08-14 18:10:48] iter = 0020, loss = 213.6031
[2024-08-14 18:10:55] iter = 0030, loss = 185.6042
[2024-08-14 18:11:01] iter = 0040, loss = 185.5390
[2024-08-14 18:11:33] Evaluate_00: epoch = 0200, train time = 26 s, train loss = 0.131280, train acc = 1.0000 train oa = 1.0000, test acc = 0.3386 test oa = 0.3356
Evaluate 1, mean = 0.3386 std = 0.0000
-------------------------
[2024-08-14 18:11:34] iter = 0050, loss = 179.7694
[2024-08-14 18:11:41] iter = 0060, loss = 165.9911
[2024-08-14 18:11:48] iter = 0070, loss = 174.2116
[2024-08-14 18:11:54] iter = 0080, loss = 153.7410
[2024-08-14 18:12:01] iter = 0090, loss = 154.6280
[2024-08-14 18:12:33] Evaluate_00: epoch = 0200, train time = 26 s, train loss = 0.092912, train acc = 1.0000 train oa = 1.0000, test acc = 0.3594 test oa = 0.3651
Evaluate 1, mean = 0.3594 std = 0.0000
-------------------------
[2024-08-14 18:12:35] iter = 0100, loss = 162.4454
[2024-08-14 18:12:42] iter = 0110, loss = 153.0356
[2024-08-14 18:12:49] iter = 0120, loss = 157.4292
[2024-08-14 18:12:56] iter = 0130, loss = 147.4766
[2024-08-14 18:13:03] iter = 0140, loss = 150.5797
[2024-08-14 18:13:38] Evaluate_00: epoch = 0200, train time = 28 s, train loss = 0.086677, train acc = 1.0000 train oa = 1.0000, test acc = 0.4311 test oa = 0.4221
Evaluate 1, mean = 0.4311 std = 0.0000
-------------------------
[2024-08-14 18:13:40] iter = 0150, loss = 145.5174
[2024-08-14 18:13:47] iter = 0160, loss = 137.5530
[2024-08-14 18:13:55] iter = 0170, loss = 141.7870
[2024-08-14 18:14:03] iter = 0180, loss = 138.6679
[2024-08-14 18:14:10] iter = 0190, loss = 152.4041
[2024-08-14 18:14:46] Evaluate_00: epoch = 0200, train time = 30 s, train loss = 0.101504, train acc = 1.0000 train oa = 1.0000, test acc = 0.4101 test oa = 0.4066
Evaluate 1, mean = 0.4101 std = 0.0000
-------------------------
[2024-08-14 18:14:48] iter = 0200, loss = 138.4508

================== Exp 0 ==================
 
[2024-08-14 18:16:11] iter = 0000, loss = 247.1302
[2024-08-14 18:22:02] iter = 0010, loss = 182.6774
[2024-08-14 18:28:04] iter = 0020, loss = 169.9400
[2024-08-14 18:34:08] iter = 0030, loss = 157.0014
[2024-08-14 18:40:13] iter = 0040, loss = 160.1905

================== Exp 0 ==================
 
[2024-08-14 18:40:33] iter = 0000, loss = 90.1186
[2024-08-14 18:42:09] iter = 0010, loss = 71.5402
[2024-08-14 18:43:47] iter = 0020, loss = 89.5820
[2024-08-14 18:45:25] iter = 0030, loss = 76.1096
[2024-08-14 18:47:04] iter = 0040, loss = 82.6663
[2024-08-14 18:48:41] Evaluate_00: epoch = 0200, train time = 17 s, train loss = 1.566379, train acc = 0.4933 train oa = 0.4933, test acc = 0.3074 test oa = 0.3529
Evaluate 1, mean = 0.3074 std = 0.0000
-------------------------
[2024-08-14 18:48:50] Evaluate_00: epoch = 0200, train time = 106 s, train loss = 0.085264, train acc = 1.0000 train oa = 1.0000, test acc = 0.4547 test oa = 0.4412
Evaluate 1, mean = 0.4547 std = 0.0000
-------------------------
[2024-08-14 18:49:01] iter = 0050, loss = 86.5799
[2024-08-14 18:50:40] iter = 0060, loss = 86.1619
[2024-08-14 18:51:26] iter = 0050, loss = 157.8842
[2024-08-14 18:52:19] iter = 0070, loss = 82.0761
[2024-08-14 18:53:58] iter = 0080, loss = 69.5993
[2024-08-14 18:57:45] iter = 0090, loss = 82.1150
[2024-08-14 18:59:39] Evaluate_00: epoch = 0200, train time = 17 s, train loss = 1.676191, train acc = 0.4900 train oa = 0.4900, test acc = 0.3623 test oa = 0.3599
Evaluate 1, mean = 0.3623 std = 0.0000
-------------------------
[2024-08-14 19:01:25] iter = 0100, loss = 85.7006
[2024-08-14 19:01:27] iter = 0060, loss = 151.4372
[2024-08-14 19:03:57] iter = 0110, loss = 85.0537
[2024-08-14 19:05:35] iter = 0120, loss = 74.3754
[2024-08-14 19:07:14] iter = 0130, loss = 84.9465
[2024-08-14 19:08:53] iter = 0140, loss = 82.1270
[2024-08-14 19:10:30] Evaluate_00: epoch = 0200, train time = 18 s, train loss = 1.694585, train acc = 0.4600 train oa = 0.4600, test acc = 0.3654 test oa = 0.3702
Evaluate 1, mean = 0.3654 std = 0.0000
-------------------------
[2024-08-14 19:10:50] iter = 0150, loss = 70.8052
[2024-08-14 19:12:29] iter = 0160, loss = 74.3076
[2024-08-14 19:13:08] iter = 0070, loss = 152.0564
[2024-08-14 19:14:10] iter = 0170, loss = 70.5989
[2024-08-14 19:15:49] iter = 0180, loss = 94.9964
[2024-08-14 19:17:29] iter = 0190, loss = 91.7306
[2024-08-14 19:19:08] Evaluate_00: epoch = 0200, train time = 18 s, train loss = 1.783003, train acc = 0.4433 train oa = 0.4433, test acc = 0.2837 test oa = 0.3529
Evaluate 1, mean = 0.2837 std = 0.0000
-------------------------
[2024-08-14 19:19:28] iter = 0200, loss = 81.7633
[2024-08-14 19:24:08] iter = 0080, loss = 148.4064
[2024-08-14 19:30:33] iter = 0090, loss = 144.8752
[2024-08-14 19:36:05] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.091664, train acc = 1.0000 train oa = 1.0000, test acc = 0.4083 test oa = 0.4377
Evaluate 1, mean = 0.4083 std = 0.0000
-------------------------
[2024-08-14 19:37:18] iter = 0100, loss = 148.5526
[2024-08-14 19:43:23] iter = 0110, loss = 148.6088
[2024-08-14 19:49:35] iter = 0120, loss = 148.9475
[2024-08-14 19:55:47] iter = 0130, loss = 147.0806
[2024-08-14 20:02:47] iter = 0140, loss = 146.0909
[2024-08-14 20:08:27] Evaluate_00: epoch = 0200, train time = 40 s, train loss = 0.092396, train acc = 1.0000 train oa = 1.0000, test acc = 0.4624 test oa = 0.4792
Evaluate 1, mean = 0.4624 std = 0.0000
-------------------------
[2024-08-14 20:09:43] iter = 0150, loss = 141.4712
[2024-08-14 20:16:04] iter = 0160, loss = 149.3115
[2024-08-14 20:22:28] iter = 0170, loss = 157.5696
[2024-08-14 20:28:56] iter = 0180, loss = 146.6931
[2024-08-14 20:35:26] iter = 0190, loss = 145.0109
[2024-08-14 20:41:16] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.088257, train acc = 1.0000 train oa = 1.0000, test acc = 0.4360 test oa = 0.4775
Evaluate 1, mean = 0.4360 std = 0.0000
-------------------------
[2024-08-14 20:42:32] iter = 0200, loss = 141.7029

================== Exp 0 ==================
 
[2024-08-14 21:12:32] iter = 0000, loss = 234.6939
[2024-08-14 21:15:25] iter = 0010, loss = 134.0788

================== Exp 0 ==================
 
[2024-08-14 21:17:35] iter = 0000, loss = 234.6939
[2024-08-14 21:20:43] iter = 0010, loss = 134.0788
[2024-08-14 21:24:02] iter = 0020, loss = 133.8759
[2024-08-14 21:27:24] iter = 0030, loss = 128.4814
[2024-08-14 21:30:45] iter = 0040, loss = 123.6899
[2024-08-14 21:34:07] Evaluate_00: epoch = 0200, train time = 40 s, train loss = 0.086425, train acc = 1.0000 train oa = 1.0000, test acc = 0.4478 test oa = 0.4567
Evaluate 1, mean = 0.4478 std = 0.0000
-------------------------
[2024-08-14 21:34:48] iter = 0050, loss = 120.4464
[2024-08-14 21:38:10] iter = 0060, loss = 116.1447
[2024-08-14 21:41:34] iter = 0070, loss = 116.1302
[2024-08-14 21:44:57] iter = 0080, loss = 120.6827
[2024-08-14 21:48:23] iter = 0090, loss = 120.8154
[2024-08-14 21:51:49] Evaluate_00: epoch = 0200, train time = 43 s, train loss = 0.105903, train acc = 1.0000 train oa = 1.0000, test acc = 0.4049 test oa = 0.4291
Evaluate 1, mean = 0.4049 std = 0.0000
-------------------------
[2024-08-14 21:52:30] iter = 0100, loss = 133.7900
[2024-08-14 21:55:50] iter = 0110, loss = 121.8606
[2024-08-14 21:59:14] iter = 0120, loss = 120.3402
[2024-08-14 22:02:37] iter = 0130, loss = 122.1055
[2024-08-14 22:06:00] iter = 0140, loss = 118.3424
[2024-08-14 22:09:28] Evaluate_00: epoch = 0200, train time = 43 s, train loss = 0.092504, train acc = 1.0000 train oa = 1.0000, test acc = 0.4297 test oa = 0.4533
Evaluate 1, mean = 0.4297 std = 0.0000
-------------------------
[2024-08-14 22:10:09] iter = 0150, loss = 118.4754
[2024-08-14 22:13:34] iter = 0160, loss = 121.1931
[2024-08-14 22:16:54] iter = 0170, loss = 120.2694
[2024-08-14 22:20:16] iter = 0180, loss = 120.6207
[2024-08-14 22:23:39] iter = 0190, loss = 112.0369
[2024-08-14 22:27:03] Evaluate_00: epoch = 0200, train time = 41 s, train loss = 0.102339, train acc = 1.0000 train oa = 1.0000, test acc = 0.4456 test oa = 0.4377
Evaluate 1, mean = 0.4456 std = 0.0000
-------------------------
[2024-08-14 22:27:44] iter = 0200, loss = 123.7858

================== Exp 0 ==================
 
[2024-08-19 19:27:19] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.412112, train acc = 0.9967 train oa = 0.9967, test acc = 0.0660 test oa = 0.1153
Evaluate 1, mean = 0.0660 std = 0.0000
-------------------------

================== Exp 0 ==================
 
[2024-08-19 19:29:40] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.412112, train acc = 0.9967 train oa = 0.9967, test acc = 0.0660 test oa = 0.1153
Evaluate 1, mean = 0.0660 std = 0.0000
-------------------------
[2024-08-19 19:53:05] iter = 0000, loss = 291.1556
[2024-08-19 19:54:35] iter = 0010, loss = 175.8707
[2024-08-19 19:57:31] iter = 0020, loss = 170.7919
[2024-08-19 19:59:04] iter = 0030, loss = 164.8979
[2024-08-19 20:00:40] iter = 0040, loss = 159.8409
[2024-08-19 20:02:30] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.108303, train acc = 1.0000 train oa = 1.0000, test acc = 0.4269 test oa = 0.4836
Evaluate 1, mean = 0.4269 std = 0.0000
-------------------------
[2024-08-19 20:02:49] iter = 0050, loss = 160.0449
[2024-08-19 20:04:22] iter = 0060, loss = 166.7877
[2024-08-19 20:05:55] iter = 0070, loss = 155.1984
[2024-08-19 20:07:28] iter = 0080, loss = 154.7695
[2024-08-19 20:09:01] iter = 0090, loss = 156.1981
[2024-08-19 20:11:09] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.121300, train acc = 1.0000 train oa = 1.0000, test acc = 0.4424 test oa = 0.4974
Evaluate 1, mean = 0.4424 std = 0.0000
-------------------------
[2024-08-19 20:11:28] iter = 0100, loss = 167.3609
[2024-08-19 20:13:00] iter = 0110, loss = 149.1077
[2024-08-19 20:14:34] iter = 0120, loss = 149.7430
[2024-08-19 20:16:07] iter = 0130, loss = 147.8167
[2024-08-19 20:18:15] iter = 0140, loss = 145.2369
[2024-08-19 20:20:05] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.087619, train acc = 1.0000 train oa = 1.0000, test acc = 0.4685 test oa = 0.5060
Evaluate 1, mean = 0.4685 std = 0.0000
-------------------------
[2024-08-19 20:20:23] iter = 0150, loss = 153.7678
[2024-08-19 20:22:33] iter = 0160, loss = 152.2827
[2024-08-19 20:24:06] iter = 0170, loss = 148.0012
[2024-08-19 20:25:51] iter = 0180, loss = 150.0663
[2024-08-19 20:27:29] iter = 0190, loss = 151.2564
[2024-08-19 20:29:20] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.105391, train acc = 1.0000 train oa = 1.0000, test acc = 0.4945 test oa = 0.5336
Evaluate 1, mean = 0.4945 std = 0.0000
-------------------------
[2024-08-19 20:29:39] iter = 0200, loss = 161.5080
[2024-08-19 21:19:46] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.104631, train acc = 0.9967 train oa = 0.9967, test acc = 0.4969 test oa = 0.5318
[2024-08-19 21:20:24] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.095211, train acc = 1.0000 train oa = 1.0000, test acc = 0.4989 test oa = 0.5387
[2024-08-19 21:21:06] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.107875, train acc = 1.0000 train oa = 1.0000, test acc = 0.4841 test oa = 0.5164
[2024-08-19 21:26:27] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.103124, train acc = 1.0000 train oa = 1.0000, test acc = 0.4845 test oa = 0.5232
[2024-08-19 21:27:09] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.105551, train acc = 1.0000 train oa = 1.0000, test acc = 0.5093 test oa = 0.5456
[2024-08-19 21:27:46] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.113563, train acc = 1.0000 train oa = 1.0000, test acc = 0.4902 test oa = 0.5181
[2024-08-19 21:52:46] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.117784, train acc = 1.0000 train oa = 1.0000, test acc = 0.4852 test oa = 0.5267
[2024-08-19 21:53:26] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.110637, train acc = 1.0000 train oa = 1.0000, test acc = 0.4516 test oa = 0.5250
[2024-08-19 21:54:05] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.103202, train acc = 1.0000 train oa = 1.0000, test acc = 0.4709 test oa = 0.5473
[2024-08-19 22:01:07] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.112125, train acc = 1.0000 train oa = 1.0000, test acc = 0.4888 test oa = 0.5422
[2024-08-19 22:02:14] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.109762, train acc = 1.0000 train oa = 1.0000, test acc = 0.5010 test oa = 0.5422
[2024-08-19 22:02:52] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.114817, train acc = 0.9967 train oa = 0.9967, test acc = 0.5098 test oa = 0.5525
[2024-08-19 22:32:47] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.103073, train acc = 1.0000 train oa = 1.0000, test acc = 0.4856 test oa = 0.5422
[2024-08-19 22:33:25] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.084157, train acc = 1.0000 train oa = 1.0000, test acc = 0.4811 test oa = 0.5318
[2024-08-19 22:34:04] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.099472, train acc = 1.0000 train oa = 1.0000, test acc = 0.5061 test oa = 0.5353
[2024-08-19 23:01:10] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.114459, train acc = 1.0000 train oa = 1.0000, test acc = 0.4470 test oa = 0.5009
[2024-08-19 23:02:05] Evaluate_01: epoch = 0200, train time = 36 s, train loss = 0.121429, train acc = 1.0000 train oa = 1.0000, test acc = 0.4549 test oa = 0.5129
[2024-08-19 23:02:43] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.124766, train acc = 1.0000 train oa = 1.0000, test acc = 0.4665 test oa = 0.5026
[2024-08-20 00:00:19] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.165010, train acc = 1.0000 train oa = 1.0000, test acc = 0.4378 test oa = 0.4750
[2024-08-20 00:00:57] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.136291, train acc = 1.0000 train oa = 1.0000, test acc = 0.4339 test oa = 0.4768
[2024-08-20 00:01:35] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.154037, train acc = 1.0000 train oa = 1.0000, test acc = 0.4461 test oa = 0.4802
[2024-08-20 00:09:52] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.100280, train acc = 1.0000 train oa = 1.0000, test acc = 0.4785 test oa = 0.5198
[2024-08-20 00:10:30] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.103759, train acc = 0.9967 train oa = 0.9967, test acc = 0.4799 test oa = 0.5404
[2024-08-20 00:11:09] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.101371, train acc = 1.0000 train oa = 1.0000, test acc = 0.4722 test oa = 0.5387
[2024-08-20 00:40:24] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.095267, train acc = 1.0000 train oa = 1.0000, test acc = 0.4755 test oa = 0.5250
[2024-08-20 00:41:03] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.083845, train acc = 1.0000 train oa = 1.0000, test acc = 0.4829 test oa = 0.5318
[2024-08-20 00:41:41] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.101834, train acc = 1.0000 train oa = 1.0000, test acc = 0.4593 test oa = 0.5060
[2024-08-20 01:49:11] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.126429, train acc = 1.0000 train oa = 1.0000, test acc = 0.4719 test oa = 0.5146
[2024-08-20 01:49:49] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.114663, train acc = 0.9967 train oa = 0.9967, test acc = 0.4559 test oa = 0.5250
[2024-08-20 01:50:27] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.132373, train acc = 1.0000 train oa = 1.0000, test acc = 0.4569 test oa = 0.5095
[2024-08-20 02:19:26] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.097820, train acc = 1.0000 train oa = 1.0000, test acc = 0.4753 test oa = 0.5387
[2024-08-20 02:20:04] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.090638, train acc = 1.0000 train oa = 1.0000, test acc = 0.4801 test oa = 0.5284
[2024-08-20 02:20:42] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.103481, train acc = 1.0000 train oa = 1.0000, test acc = 0.4572 test oa = 0.5232
[2024-08-20 02:29:40] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.126359, train acc = 1.0000 train oa = 1.0000, test acc = 0.4739 test oa = 0.5232
[2024-08-20 02:30:18] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.110879, train acc = 1.0000 train oa = 1.0000, test acc = 0.4628 test oa = 0.5164
[2024-08-20 02:30:55] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.132281, train acc = 0.9967 train oa = 0.9967, test acc = 0.4551 test oa = 0.5026
[2024-08-20 02:56:13] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.107661, train acc = 1.0000 train oa = 1.0000, test acc = 0.4492 test oa = 0.4940
[2024-08-20 02:56:50] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.098177, train acc = 1.0000 train oa = 1.0000, test acc = 0.4770 test oa = 0.5146
[2024-08-20 02:57:28] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.112620, train acc = 1.0000 train oa = 1.0000, test acc = 0.4434 test oa = 0.4888
[2024-08-20 03:38:14] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.103872, train acc = 1.0000 train oa = 1.0000, test acc = 0.4529 test oa = 0.5095
[2024-08-20 03:38:52] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.111543, train acc = 1.0000 train oa = 1.0000, test acc = 0.4736 test oa = 0.5198
[2024-08-20 03:39:30] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.117953, train acc = 1.0000 train oa = 1.0000, test acc = 0.4510 test oa = 0.5026
[2024-08-20 04:04:32] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.103872, train acc = 1.0000 train oa = 1.0000, test acc = 0.4529 test oa = 0.5095
[2024-08-20 04:05:10] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.111543, train acc = 1.0000 train oa = 1.0000, test acc = 0.4736 test oa = 0.5198
[2024-08-20 04:05:48] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.117953, train acc = 1.0000 train oa = 1.0000, test acc = 0.4510 test oa = 0.5026
[2024-08-20 05:20:19] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.103590, train acc = 1.0000 train oa = 1.0000, test acc = 0.5105 test oa = 0.5491
[2024-08-20 05:20:56] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.110193, train acc = 1.0000 train oa = 1.0000, test acc = 0.4900 test oa = 0.5456
[2024-08-20 05:21:34] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.125765, train acc = 1.0000 train oa = 1.0000, test acc = 0.4905 test oa = 0.5250
[2024-08-20 05:46:09] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.103590, train acc = 1.0000 train oa = 1.0000, test acc = 0.5105 test oa = 0.5491
[2024-08-20 05:46:47] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.110193, train acc = 1.0000 train oa = 1.0000, test acc = 0.4900 test oa = 0.5456
[2024-08-20 05:47:25] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.125765, train acc = 1.0000 train oa = 1.0000, test acc = 0.4905 test oa = 0.5250
[2024-08-20 05:52:54] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.107798, train acc = 1.0000 train oa = 1.0000, test acc = 0.4425 test oa = 0.5077
[2024-08-20 05:53:32] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.110800, train acc = 1.0000 train oa = 1.0000, test acc = 0.4629 test oa = 0.5129
[2024-08-20 05:54:11] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.104541, train acc = 1.0000 train oa = 1.0000, test acc = 0.4537 test oa = 0.5146
[2024-08-20 06:18:36] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.107798, train acc = 1.0000 train oa = 1.0000, test acc = 0.4425 test oa = 0.5077
[2024-08-20 06:19:14] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.110800, train acc = 1.0000 train oa = 1.0000, test acc = 0.4629 test oa = 0.5129
[2024-08-20 06:19:52] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.104541, train acc = 1.0000 train oa = 1.0000, test acc = 0.4537 test oa = 0.5146
[2024-08-20 07:05:54] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.115013, train acc = 1.0000 train oa = 1.0000, test acc = 0.4420 test oa = 0.4905
[2024-08-20 07:06:33] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.107721, train acc = 1.0000 train oa = 1.0000, test acc = 0.4299 test oa = 0.4888
[2024-08-20 07:07:10] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.107182, train acc = 1.0000 train oa = 1.0000, test acc = 0.4628 test oa = 0.4991
[2024-08-20 07:17:56] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.113983, train acc = 1.0000 train oa = 1.0000, test acc = 0.4776 test oa = 0.5250
[2024-08-20 07:18:34] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.109765, train acc = 1.0000 train oa = 1.0000, test acc = 0.4789 test oa = 0.5232
[2024-08-20 07:19:11] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.109524, train acc = 1.0000 train oa = 1.0000, test acc = 0.4959 test oa = 0.5422
[2024-08-20 08:48:12] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.134273, train acc = 1.0000 train oa = 1.0000, test acc = 0.4518 test oa = 0.4819
[2024-08-20 08:48:51] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.143839, train acc = 1.0000 train oa = 1.0000, test acc = 0.4388 test oa = 0.4716
[2024-08-20 08:49:29] Evaluate_02: epoch = 0200, train time = 38 s, train loss = 0.147097, train acc = 1.0000 train oa = 1.0000, test acc = 0.4356 test oa = 0.4854
[2024-08-20 09:00:01] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.134273, train acc = 1.0000 train oa = 1.0000, test acc = 0.4518 test oa = 0.4819
[2024-08-20 09:00:40] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.143839, train acc = 1.0000 train oa = 1.0000, test acc = 0.4388 test oa = 0.4716
[2024-08-20 09:01:16] Evaluate_02: epoch = 0200, train time = 36 s, train loss = 0.147097, train acc = 1.0000 train oa = 1.0000, test acc = 0.4356 test oa = 0.4854
[2024-08-20 09:23:35] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.106538, train acc = 1.0000 train oa = 1.0000, test acc = 0.4527 test oa = 0.5095
[2024-08-20 09:24:34] Evaluate_01: epoch = 0200, train time = 37 s, train loss = 0.102411, train acc = 1.0000 train oa = 1.0000, test acc = 0.4957 test oa = 0.5353
[2024-08-20 09:25:19] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.104686, train acc = 1.0000 train oa = 1.0000, test acc = 0.4557 test oa = 0.5095
[2024-08-20 09:34:52] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.106538, train acc = 1.0000 train oa = 1.0000, test acc = 0.4527 test oa = 0.5095
[2024-08-20 09:35:42] Evaluate_01: epoch = 0200, train time = 36 s, train loss = 0.102411, train acc = 1.0000 train oa = 1.0000, test acc = 0.4957 test oa = 0.5353
[2024-08-20 09:36:42] Evaluate_02: epoch = 0200, train time = 36 s, train loss = 0.104686, train acc = 1.0000 train oa = 1.0000, test acc = 0.4557 test oa = 0.5095

================== Exp 0 ==================
 
[2024-08-20 10:19:01] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.412112, train acc = 0.9967 train oa = 0.9967, test acc = 0.0660 test oa = 0.1153
Evaluate 1, mean = 0.0660 std = 0.0000
-------------------------
[2024-08-20 10:19:06] iter = 0000, loss = 305.5832
[2024-08-20 10:19:54] iter = 0010, loss = 191.7815
[2024-08-20 10:20:43] iter = 0020, loss = 181.8997
[2024-08-20 10:21:57] iter = 0030, loss = 181.6889
[2024-08-20 10:22:47] iter = 0040, loss = 164.9746
[2024-08-20 10:24:06] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.099769, train acc = 1.0000 train oa = 1.0000, test acc = 0.4044 test oa = 0.4647
Evaluate 1, mean = 0.4044 std = 0.0000
-------------------------
[2024-08-20 10:24:20] iter = 0050, loss = 166.1049
[2024-08-20 10:24:30] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.106361, train acc = 1.0000 train oa = 1.0000, test acc = 0.4587 test oa = 0.4940
[2024-08-20 10:25:10] iter = 0060, loss = 150.5200
[2024-08-20 10:25:08] Evaluate_01: epoch = 0200, train time = 38 s, train loss = 0.108387, train acc = 1.0000 train oa = 1.0000, test acc = 0.4647 test oa = 0.4991
[2024-08-20 10:26:04] Evaluate_02: epoch = 0200, train time = 37 s, train loss = 0.112924, train acc = 1.0000 train oa = 1.0000, test acc = 0.4589 test oa = 0.5146
[2024-08-20 10:26:16] iter = 0070, loss = 161.8354
[2024-08-20 10:27:08] iter = 0080, loss = 165.3785
[2024-08-20 10:27:57] iter = 0090, loss = 160.2418
[2024-08-20 10:29:14] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.098042, train acc = 1.0000 train oa = 1.0000, test acc = 0.4510 test oa = 0.5009
Evaluate 1, mean = 0.4510 std = 0.0000
-------------------------
[2024-08-20 10:29:24] iter = 0100, loss = 152.7484
[2024-08-20 10:30:13] iter = 0110, loss = 154.0878
[2024-08-20 10:31:02] iter = 0120, loss = 150.1261
[2024-08-20 10:31:51] iter = 0130, loss = 150.6262
[2024-08-20 10:32:40] iter = 0140, loss = 152.6910
[2024-08-20 10:33:55] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.101453, train acc = 1.0000 train oa = 1.0000, test acc = 0.4652 test oa = 0.5026
Evaluate 1, mean = 0.4652 std = 0.0000
-------------------------
[2024-08-20 10:34:05] iter = 0150, loss = 160.3146
[2024-08-20 10:34:53] iter = 0160, loss = 140.9164
[2024-08-20 10:35:42] iter = 0170, loss = 153.5694
[2024-08-20 10:36:31] iter = 0180, loss = 148.4630
[2024-08-20 10:37:20] iter = 0190, loss = 153.7286
[2024-08-20 10:38:34] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.095322, train acc = 1.0000 train oa = 1.0000, test acc = 0.4987 test oa = 0.5129
Evaluate 1, mean = 0.4987 std = 0.0000
-------------------------
[2024-08-20 10:38:44] iter = 0200, loss = 150.2205
[2024-08-20 14:58:01] Evaluate_00: epoch = 0200, train time = 187 s, train loss = 0.057636, train acc = 0.9973 train oa = 0.9973, test acc = 0.5199 test oa = 0.5559
[2024-08-20 15:01:27] Evaluate_01: epoch = 0200, train time = 206 s, train loss = 0.064574, train acc = 1.0000 train oa = 1.0000, test acc = 0.5159 test oa = 0.5525
[2024-08-20 15:04:51] Evaluate_02: epoch = 0200, train time = 203 s, train loss = 0.059514, train acc = 1.0000 train oa = 1.0000, test acc = 0.5314 test oa = 0.5628

================== Exp 0 ==================
 
[2024-08-20 15:03:51] iter = 0000, loss = 296.1822

================== Exp 0 ==================
 
[2024-08-20 15:04:16] iter = 0000, loss = 293.0203
[2024-08-20 15:05:59] iter = 0010, loss = 182.9520
[2024-08-20 15:07:43] iter = 0020, loss = 180.4117
[2024-08-20 15:09:27] iter = 0030, loss = 168.5798
[2024-08-20 15:11:12] iter = 0040, loss = 147.3529
[2024-08-20 15:13:11] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.556921, train acc = 0.9267 train oa = 0.9267, test acc = 0.3507 test oa = 0.3890
Evaluate 1, mean = 0.3507 std = 0.0000
-------------------------
[2024-08-20 15:13:32] iter = 0050, loss = 157.8609
[2024-08-20 15:15:17] iter = 0060, loss = 182.3112
[2024-08-20 15:17:02] iter = 0070, loss = 165.2874
[2024-08-20 15:18:48] iter = 0080, loss = 163.2531
[2024-08-20 15:20:33] iter = 0090, loss = 156.7254
[2024-08-20 15:22:32] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.419863, train acc = 0.9467 train oa = 0.9467, test acc = 0.3908 test oa = 0.4251
Evaluate 1, mean = 0.3908 std = 0.0000
-------------------------
[2024-08-20 15:22:53] iter = 0100, loss = 178.3854
[2024-08-20 15:24:38] iter = 0110, loss = 166.7993
[2024-08-20 15:26:23] iter = 0120, loss = 183.5196
[2024-08-20 15:28:08] iter = 0130, loss = 168.9558
[2024-08-20 15:29:53] iter = 0140, loss = 163.8258
[2024-08-20 15:31:52] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.503355, train acc = 0.9300 train oa = 0.9300, test acc = 0.3712 test oa = 0.4131
Evaluate 1, mean = 0.3712 std = 0.0000
-------------------------
[2024-08-20 15:32:17] iter = 0150, loss = 163.1649
[2024-08-20 15:34:02] iter = 0160, loss = 192.3656
[2024-08-20 15:35:47] iter = 0170, loss = 152.9223

================== Exp 0 ==================
 
[2024-08-20 15:36:30] iter = 0000, loss = 293.0203
[2024-08-20 15:37:32] iter = 0180, loss = 188.1586
[2024-08-20 15:38:15] iter = 0010, loss = 182.9520
[2024-08-20 15:39:19] iter = 0190, loss = 165.6807
[2024-08-20 15:40:03] iter = 0020, loss = 180.4117
[2024-08-20 15:41:24] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.651481, train acc = 0.8967 train oa = 0.8967, test acc = 0.3902 test oa = 0.3959
Evaluate 1, mean = 0.3902 std = 0.0000
-------------------------
[2024-08-20 15:41:45] iter = 0200, loss = 150.9018
[2024-08-20 15:41:51] iter = 0030, loss = 168.5798
[2024-08-20 15:43:38] iter = 0040, loss = 147.3529
[2024-08-20 15:45:38] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.346515, train acc = 0.9933 train oa = 0.9933, test acc = 0.2756 test oa = 0.3253
Evaluate 1, mean = 0.2756 std = 0.0000
-------------------------
[2024-08-20 15:45:59] iter = 0050, loss = 152.3478
[2024-08-20 15:47:46] iter = 0060, loss = 179.0797

================== Exp 0 ==================
 
[2024-08-20 15:47:58] iter = 0000, loss = 293.0203
[2024-08-20 15:49:33] iter = 0070, loss = 163.2357
[2024-08-20 15:49:43] iter = 0010, loss = 182.9520
[2024-08-20 15:51:20] iter = 0080, loss = 199.6035
[2024-08-20 15:51:30] iter = 0020, loss = 180.4117
[2024-08-20 15:53:07] iter = 0090, loss = 191.4909
[2024-08-20 15:53:19] iter = 0030, loss = 168.5798
[2024-08-20 15:55:08] iter = 0040, loss = 147.3529
[2024-08-20 15:55:11] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.323292, train acc = 0.9967 train oa = 0.9967, test acc = 0.3920 test oa = 0.4165
Evaluate 1, mean = 0.3920 std = 0.0000
-------------------------
[2024-08-20 15:55:35] iter = 0100, loss = 151.6754
[2024-08-20 15:57:23] iter = 0110, loss = 166.3677
[2024-08-20 15:57:15] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.568417, train acc = 0.9367 train oa = 0.9367, test acc = 0.3499 test oa = 0.3941
Evaluate 1, mean = 0.3499 std = 0.0000
-------------------------
[2024-08-20 15:57:51] iter = 0050, loss = 157.8609
[2024-08-20 15:59:18] iter = 0120, loss = 159.0991
[2024-08-20 15:59:40] iter = 0060, loss = 182.3112
[2024-08-20 16:01:05] iter = 0130, loss = 156.3244
[2024-08-20 16:01:30] iter = 0070, loss = 165.2874
[2024-08-20 16:02:53] iter = 0140, loss = 158.0275
[2024-08-20 16:03:17] iter = 0080, loss = 163.2531
[2024-08-20 16:05:05] iter = 0090, loss = 156.7254
[2024-08-20 16:05:15] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.290878, train acc = 0.9967 train oa = 0.9967, test acc = 0.3942 test oa = 0.4200
Evaluate 1, mean = 0.3942 std = 0.0000
-------------------------
[2024-08-20 16:05:37] iter = 0150, loss = 140.2174
[2024-08-20 16:07:12] Evaluate_00: epoch = 0200, train time = 40 s, train loss = 0.394387, train acc = 0.9667 train oa = 0.9667, test acc = 0.3904 test oa = 0.4251
Evaluate 1, mean = 0.3904 std = 0.0000
-------------------------
[2024-08-20 16:07:34] iter = 0100, loss = 178.3854
[2024-08-20 16:07:34] iter = 0160, loss = 162.1635
[2024-08-20 16:09:22] iter = 0110, loss = 166.7993
[2024-08-20 16:09:23] iter = 0170, loss = 137.8041
[2024-08-20 16:11:10] iter = 0120, loss = 183.5196
[2024-08-20 16:11:10] iter = 0180, loss = 162.9389
[2024-08-20 16:12:59] iter = 0190, loss = 176.0432
[2024-08-20 16:12:59] iter = 0130, loss = 168.9558
[2024-08-20 16:14:48] iter = 0140, loss = 163.8258
[2024-08-20 16:15:02] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.314424, train acc = 0.9933 train oa = 0.9933, test acc = 0.3132 test oa = 0.3701
Evaluate 1, mean = 0.3132 std = 0.0000
-------------------------
[2024-08-20 16:15:24] iter = 0200, loss = 175.2957
[2024-08-20 16:16:51] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.506758, train acc = 0.9233 train oa = 0.9233, test acc = 0.3755 test oa = 0.4148
Evaluate 1, mean = 0.3755 std = 0.0000
-------------------------
[2024-08-20 16:17:24] iter = 0150, loss = 163.1649
[2024-08-20 16:19:11] iter = 0160, loss = 192.3656
[2024-08-20 16:20:56] iter = 0170, loss = 152.9223
[2024-08-20 16:23:08] iter = 0180, loss = 188.1586
[2024-08-20 16:31:32] iter = 0190, loss = 165.6807
[2024-08-20 16:33:35] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.665129, train acc = 0.8800 train oa = 0.8800, test acc = 0.3747 test oa = 0.4062
Evaluate 1, mean = 0.3747 std = 0.0000
-------------------------
[2024-08-20 16:33:56] iter = 0200, loss = 150.9018

================== Exp 0 ==================
 
[2024-08-20 16:35:50] iter = 0000, loss = 295.6827
[2024-08-20 16:37:26] iter = 0010, loss = 178.0580

================== Exp 0 ==================
 
[2024-08-20 16:38:15] iter = 0000, loss = 295.6827
[2024-08-20 16:39:04] iter = 0020, loss = 185.8409
[2024-08-20 16:39:54] iter = 0010, loss = 178.0580
[2024-08-20 16:40:44] iter = 0030, loss = 152.7858
[2024-08-20 16:41:33] iter = 0020, loss = 185.8409
[2024-08-20 16:42:25] iter = 0040, loss = 155.9809
[2024-08-20 16:43:14] iter = 0030, loss = 152.7858
[2024-08-20 16:44:25] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.624230, train acc = 0.9133 train oa = 0.9133, test acc = 0.3182 test oa = 0.3546
Evaluate 1, mean = 0.3182 std = 0.0000
-------------------------
[2024-08-20 16:44:46] iter = 0050, loss = 157.0727
[2024-08-20 16:44:55] iter = 0040, loss = 155.9809
[2024-08-20 16:46:27] iter = 0060, loss = 214.0854
[2024-08-20 16:47:13] Evaluate_00: epoch = 0200, train time = 56 s, train loss = 0.332757, train acc = 0.9867 train oa = 0.9867, test acc = 0.3165 test oa = 0.3580
Evaluate 1, mean = 0.3165 std = 0.0000
-------------------------
[2024-08-20 16:47:38] iter = 0050, loss = 168.9698
[2024-08-20 16:48:17] iter = 0070, loss = 157.5568
[2024-08-20 16:51:25] iter = 0080, loss = 147.1073
[2024-08-20 16:51:25] iter = 0060, loss = 154.7817
[2024-08-20 16:53:06] iter = 0090, loss = 216.8235
[2024-08-20 16:53:06] iter = 0070, loss = 153.1781
[2024-08-20 16:54:46] iter = 0080, loss = 157.6502
[2024-08-20 16:55:04] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.638149, train acc = 0.8967 train oa = 0.8967, test acc = 0.3448 test oa = 0.3821
Evaluate 1, mean = 0.3448 std = 0.0000
-------------------------
[2024-08-20 16:55:24] iter = 0100, loss = 208.4366
[2024-08-20 16:56:25] iter = 0090, loss = 162.3556
[2024-08-20 16:58:18] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.286391, train acc = 0.9933 train oa = 0.9933, test acc = 0.3662 test oa = 0.4010
Evaluate 1, mean = 0.3662 std = 0.0000
-------------------------
[2024-08-20 16:58:39] iter = 0100, loss = 147.1374
[2024-08-20 17:20:23] Evaluate_00: epoch = 0200, train time = 69 s, train loss = 0.070822, train acc = 1.0000 train oa = 1.0000, test acc = 0.5408 test oa = 0.5783
[2024-08-20 17:21:40] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.070705, train acc = 0.9987 train oa = 0.9987, test acc = 0.5522 test oa = 0.5869
[2024-08-20 17:22:49] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.070285, train acc = 1.0000 train oa = 1.0000, test acc = 0.5244 test oa = 0.5594

================== Exp 0 ==================
 
[2024-08-20 17:26:55] iter = 0000, loss = 260.2972
[2024-08-20 17:30:33] iter = 0010, loss = 170.2331
[2024-08-20 17:34:09] iter = 0020, loss = 236.0047
[2024-08-20 17:37:44] iter = 0030, loss = 184.5557
[2024-08-20 17:41:19] iter = 0040, loss = 180.4155
[2024-08-20 17:44:45] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.360225, train acc = 0.9933 train oa = 0.9933, test acc = 0.3257 test oa = 0.3735
Evaluate 1, mean = 0.3257 std = 0.0000
-------------------------
[2024-08-20 17:45:28] iter = 0050, loss = 189.4120
[2024-08-20 17:49:02] iter = 0060, loss = 164.3122
[2024-08-20 17:52:37] iter = 0070, loss = 165.8599
[2024-08-20 17:56:11] iter = 0080, loss = 165.8145
[2024-08-20 17:59:54] iter = 0090, loss = 173.4421
[2024-08-20 18:03:19] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.369661, train acc = 0.9767 train oa = 0.9767, test acc = 0.3885 test oa = 0.4165
Evaluate 1, mean = 0.3885 std = 0.0000
-------------------------
[2024-08-20 18:04:15] iter = 0100, loss = 163.4622
[2024-08-20 18:07:50] iter = 0110, loss = 149.9475
[2024-08-20 18:11:26] iter = 0120, loss = 176.1789
[2024-08-20 18:19:03] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.066304, train acc = 1.0000 train oa = 1.0000, test acc = 0.5400 test oa = 0.5783
[2024-08-20 18:15:00] iter = 0130, loss = 154.3512
[2024-08-20 18:20:14] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.066505, train acc = 1.0000 train oa = 1.0000, test acc = 0.5426 test oa = 0.5852
[2024-08-20 18:21:23] Evaluate_02: epoch = 0200, train time = 69 s, train loss = 0.072651, train acc = 1.0000 train oa = 1.0000, test acc = 0.5293 test oa = 0.5749
[2024-08-20 18:18:37] iter = 0140, loss = 159.1994
[2024-08-20 18:22:27] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.282328, train acc = 0.9900 train oa = 0.9900, test acc = 0.3698 test oa = 0.4045
Evaluate 1, mean = 0.3698 std = 0.0000
-------------------------
[2024-08-20 18:23:53] iter = 0150, loss = 164.4380
[2024-08-20 18:27:28] iter = 0160, loss = 163.2861
[2024-08-20 18:31:03] iter = 0170, loss = 160.6532
[2024-08-20 18:34:38] iter = 0180, loss = 186.4082
[2024-08-20 18:38:12] iter = 0190, loss = 171.0694
[2024-08-20 18:41:39] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.482084, train acc = 0.9467 train oa = 0.9467, test acc = 0.2918 test oa = 0.3270
Evaluate 1, mean = 0.2918 std = 0.0000
-------------------------
[2024-08-20 18:42:22] iter = 0200, loss = 172.3338
[2024-08-20 19:33:21] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.072386, train acc = 1.0000 train oa = 1.0000, test acc = 0.5540 test oa = 0.5749
[2024-08-20 19:34:30] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.060600, train acc = 1.0000 train oa = 1.0000, test acc = 0.5463 test oa = 0.5869
[2024-08-20 19:35:39] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.064031, train acc = 1.0000 train oa = 1.0000, test acc = 0.5389 test oa = 0.5921
[2024-08-20 22:57:57] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.072310, train acc = 1.0000 train oa = 1.0000, test acc = 0.5418 test oa = 0.5749
[2024-08-20 22:59:05] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.064512, train acc = 1.0000 train oa = 1.0000, test acc = 0.5532 test oa = 0.5835
[2024-08-20 23:00:14] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.066137, train acc = 1.0000 train oa = 1.0000, test acc = 0.5436 test oa = 0.5783
[2024-08-20 23:46:46] Evaluate_00: epoch = 0200, train time = 270 s, train loss = 0.077938, train acc = 1.0000 train oa = 1.0000, test acc = 0.5347 test oa = 0.5663
[2024-08-20 23:51:56] Evaluate_01: epoch = 0200, train time = 309 s, train loss = 0.079637, train acc = 1.0000 train oa = 1.0000, test acc = 0.5044 test oa = 0.5577
[2024-08-20 23:57:17] Evaluate_02: epoch = 0200, train time = 321 s, train loss = 0.071790, train acc = 1.0000 train oa = 1.0000, test acc = 0.5211 test oa = 0.5714
[2024-08-21 01:14:51] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.076654, train acc = 1.0000 train oa = 1.0000, test acc = 0.5399 test oa = 0.5749
[2024-08-21 01:15:58] Evaluate_01: epoch = 0200, train time = 67 s, train loss = 0.083706, train acc = 1.0000 train oa = 1.0000, test acc = 0.5304 test oa = 0.5766
[2024-08-21 01:17:06] Evaluate_02: epoch = 0200, train time = 67 s, train loss = 0.069060, train acc = 1.0000 train oa = 1.0000, test acc = 0.5400 test oa = 0.5852
[2024-08-21 03:09:12] Evaluate_00: epoch = 0200, train time = 67 s, train loss = 0.111528, train acc = 0.9973 train oa = 0.9973, test acc = 0.4500 test oa = 0.4888
[2024-08-21 03:10:21] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.127464, train acc = 0.9960 train oa = 0.9960, test acc = 0.4643 test oa = 0.5009
[2024-08-21 03:11:29] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.119197, train acc = 0.9987 train oa = 0.9987, test acc = 0.4770 test oa = 0.5043
[2024-08-21 05:14:53] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.113233, train acc = 1.0000 train oa = 1.0000, test acc = 0.4901 test oa = 0.5336
[2024-08-21 05:16:01] Evaluate_01: epoch = 0200, train time = 67 s, train loss = 0.121202, train acc = 0.9973 train oa = 0.9973, test acc = 0.4931 test oa = 0.5404
[2024-08-21 05:17:09] Evaluate_02: epoch = 0200, train time = 67 s, train loss = 0.107868, train acc = 0.9987 train oa = 0.9987, test acc = 0.5029 test oa = 0.5491
[2024-08-21 07:09:20] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.069430, train acc = 1.0000 train oa = 1.0000, test acc = 0.5148 test oa = 0.5611
[2024-08-21 07:10:30] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.073047, train acc = 1.0000 train oa = 1.0000, test acc = 0.5130 test oa = 0.5663
[2024-08-21 07:11:38] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.078559, train acc = 0.9987 train oa = 0.9987, test acc = 0.5310 test oa = 0.5749
[2024-08-21 09:47:22] Evaluate_00: epoch = 0200, train time = 178 s, train loss = 0.118507, train acc = 1.0000 train oa = 1.0000, test acc = 0.5031 test oa = 0.5387
[2024-08-21 09:50:35] Evaluate_01: epoch = 0200, train time = 193 s, train loss = 0.115488, train acc = 1.0000 train oa = 1.0000, test acc = 0.4772 test oa = 0.5009
[2024-08-21 09:53:46] Evaluate_02: epoch = 0200, train time = 190 s, train loss = 0.103186, train acc = 1.0000 train oa = 1.0000, test acc = 0.4926 test oa = 0.5284

================== Exp 0 ==================
 
[2024-08-21 10:42:33] iter = 0000, loss = 250.0477

================== Exp 0 ==================
 
[2024-08-21 10:44:50] iter = 0000, loss = 250.6443
[2024-08-21 10:46:09] iter = 0010, loss = 171.4951
[2024-08-21 10:50:37] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.101628, train acc = 1.0000 train oa = 1.0000, test acc = 0.5032 test oa = 0.5353
[2024-08-21 10:51:45] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.112936, train acc = 0.9987 train oa = 0.9987, test acc = 0.4610 test oa = 0.5215
[2024-08-21 10:48:09] iter = 0010, loss = 161.3974
[2024-08-21 10:52:53] Evaluate_02: epoch = 0200, train time = 67 s, train loss = 0.108300, train acc = 1.0000 train oa = 1.0000, test acc = 0.4539 test oa = 0.5129
[2024-08-21 10:49:49] iter = 0020, loss = 163.0576
[2024-08-21 10:51:32] iter = 0020, loss = 157.7886
[2024-08-21 10:53:27] iter = 0030, loss = 160.7698
[2024-08-21 10:54:55] iter = 0030, loss = 165.0910
[2024-08-21 10:57:06] iter = 0040, loss = 164.2559
[2024-08-21 10:58:17] iter = 0040, loss = 163.3737
[2024-08-21 11:00:38] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.290259, train acc = 0.9967 train oa = 0.9967, test acc = 0.3794 test oa = 0.4045
Evaluate 1, mean = 0.3794 std = 0.0000
-------------------------
[2024-08-21 11:01:23] iter = 0050, loss = 160.5332
[2024-08-21 11:01:36] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.256433, train acc = 0.9967 train oa = 0.9967, test acc = 0.3305 test oa = 0.3563
Evaluate 1, mean = 0.3305 std = 0.0000
-------------------------
[2024-08-21 11:02:16] iter = 0050, loss = 158.7434
[2024-08-21 11:05:37] iter = 0060, loss = 162.8980
[2024-08-21 11:05:01] iter = 0060, loss = 169.1813
[2024-08-21 11:09:17] iter = 0070, loss = 161.1594
[2024-08-21 11:09:33] iter = 0070, loss = 176.0238
[2024-08-21 11:12:40] iter = 0080, loss = 152.3734
[2024-08-21 11:13:26] iter = 0080, loss = 157.8604
[2024-08-21 11:16:01] iter = 0090, loss = 162.7808
[2024-08-21 11:17:05] iter = 0090, loss = 162.6673
[2024-08-21 11:19:20] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.332209, train acc = 0.9933 train oa = 0.9933, test acc = 0.3088 test oa = 0.3528
Evaluate 1, mean = 0.3088 std = 0.0000
-------------------------
[2024-08-21 11:20:01] iter = 0100, loss = 170.3742
[2024-08-21 11:20:37] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.279511, train acc = 0.9933 train oa = 0.9933, test acc = 0.3535 test oa = 0.3873
Evaluate 1, mean = 0.3535 std = 0.0000
-------------------------
[2024-08-21 11:21:21] iter = 0100, loss = 169.1178
[2024-08-21 11:23:23] iter = 0110, loss = 158.9973
[2024-08-21 11:24:59] iter = 0110, loss = 157.0141
[2024-08-21 11:26:44] iter = 0120, loss = 159.4463
[2024-08-21 11:28:38] iter = 0120, loss = 154.9687
[2024-08-21 11:30:06] iter = 0130, loss = 151.8863
[2024-08-21 11:32:16] iter = 0130, loss = 154.6628
[2024-08-21 11:33:28] iter = 0140, loss = 160.8530
[2024-08-21 11:35:55] iter = 0140, loss = 153.7548
[2024-08-21 11:36:47] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.332813, train acc = 0.9867 train oa = 0.9867, test acc = 0.3118 test oa = 0.3752
Evaluate 1, mean = 0.3118 std = 0.0000
-------------------------
[2024-08-21 11:37:27] iter = 0150, loss = 158.1048
[2024-08-21 11:39:26] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.273323, train acc = 0.9900 train oa = 0.9900, test acc = 0.3472 test oa = 0.3855
Evaluate 1, mean = 0.3472 std = 0.0000
-------------------------
[2024-08-21 11:40:10] iter = 0150, loss = 165.8438
[2024-08-21 11:40:49] iter = 0160, loss = 166.3966
[2024-08-21 11:43:49] iter = 0160, loss = 161.6424
[2024-08-21 11:44:12] iter = 0170, loss = 164.4550
[2024-08-21 11:47:27] iter = 0170, loss = 160.7272
[2024-08-21 11:47:33] iter = 0180, loss = 160.3306
[2024-08-21 11:50:55] iter = 0190, loss = 170.6854
[2024-08-21 11:51:06] iter = 0180, loss = 163.9398
[2024-08-21 11:54:14] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.305502, train acc = 1.0000 train oa = 1.0000, test acc = 0.3498 test oa = 0.3890
Evaluate 1, mean = 0.3498 std = 0.0000
-------------------------
[2024-08-21 11:54:47] iter = 0190, loss = 165.0923
[2024-08-21 11:54:55] iter = 0200, loss = 145.9537
[2024-08-21 11:59:35] Evaluate_00: epoch = 0200, train time = 67 s, train loss = 0.054025, train acc = 1.0000 train oa = 1.0000, test acc = 0.5174 test oa = 0.5577
[2024-08-21 12:00:44] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.063214, train acc = 1.0000 train oa = 1.0000, test acc = 0.5341 test oa = 0.5749
[2024-08-21 12:01:53] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.062063, train acc = 1.0000 train oa = 1.0000, test acc = 0.5217 test oa = 0.5594
[2024-08-21 11:58:14] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.326343, train acc = 0.9933 train oa = 0.9933, test acc = 0.3516 test oa = 0.3907
Evaluate 1, mean = 0.3516 std = 0.0000
-------------------------
[2024-08-21 11:58:57] iter = 0200, loss = 170.3032

================== Exp 0 ==================
 
[2024-08-21 12:25:50] iter = 0000, loss = 247.9168
[2024-08-21 12:29:04] iter = 0010, loss = 157.7896
[2024-08-21 12:32:21] iter = 0020, loss = 157.0545
[2024-08-21 12:35:39] iter = 0030, loss = 177.3771
[2024-08-21 12:39:07] iter = 0040, loss = 150.2730
[2024-08-21 12:42:31] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.336853, train acc = 0.9967 train oa = 0.9967, test acc = 0.3888 test oa = 0.4355
Evaluate 1, mean = 0.3888 std = 0.0000
-------------------------
[2024-08-21 12:43:11] iter = 0050, loss = 147.0466
[2024-08-21 12:46:28] iter = 0060, loss = 149.7029
[2024-08-21 12:49:45] iter = 0070, loss = 170.0648
[2024-08-21 12:53:02] iter = 0080, loss = 158.6152
[2024-08-21 12:56:19] iter = 0090, loss = 149.8081
[2024-08-21 13:03:24] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.061164, train acc = 1.0000 train oa = 1.0000, test acc = 0.5147 test oa = 0.5663
[2024-08-21 12:59:31] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.450017, train acc = 0.9833 train oa = 0.9833, test acc = 0.3520 test oa = 0.3804
Evaluate 1, mean = 0.3520 std = 0.0000
-------------------------
[2024-08-21 13:00:10] iter = 0100, loss = 169.4547
[2024-08-21 13:04:34] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.071919, train acc = 1.0000 train oa = 1.0000, test acc = 0.5165 test oa = 0.5508
[2024-08-21 13:05:43] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.064691, train acc = 1.0000 train oa = 1.0000, test acc = 0.5207 test oa = 0.5766
[2024-08-21 13:03:27] iter = 0110, loss = 154.1761
[2024-08-21 13:06:45] iter = 0120, loss = 159.9824
[2024-08-21 13:10:03] iter = 0130, loss = 146.0834
[2024-08-21 13:13:21] iter = 0140, loss = 146.2547
[2024-08-21 13:16:33] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.365602, train acc = 0.9967 train oa = 0.9967, test acc = 0.4206 test oa = 0.4286
Evaluate 1, mean = 0.4206 std = 0.0000
-------------------------
[2024-08-21 13:17:14] iter = 0150, loss = 148.2436
[2024-08-21 13:20:32] iter = 0160, loss = 151.6821
[2024-08-21 13:23:49] iter = 0170, loss = 166.3695
[2024-08-21 13:27:09] iter = 0180, loss = 153.0580
[2024-08-21 13:30:27] iter = 0190, loss = 153.4667
[2024-08-21 13:33:39] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.381073, train acc = 0.9900 train oa = 0.9900, test acc = 0.4006 test oa = 0.4200
Evaluate 1, mean = 0.4006 std = 0.0000
-------------------------
[2024-08-21 13:34:19] iter = 0200, loss = 141.3156

================== Exp 0 ==================
 

================== Exp 0 ==================
 
[2024-08-21 13:40:16] iter = 0000, loss = 250.6687
[2024-08-21 13:44:20] iter = 0010, loss = 167.5047
[2024-08-21 13:48:28] iter = 0020, loss = 169.8085
[2024-08-21 13:52:36] iter = 0030, loss = 168.7193
[2024-08-21 13:56:43] iter = 0040, loss = 177.0456
[2024-08-21 14:00:34] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.336193, train acc = 0.9933 train oa = 0.9933, test acc = 0.3651 test oa = 0.4062
Evaluate 1, mean = 0.3651 std = 0.0000
-------------------------
[2024-08-21 14:01:24] iter = 0050, loss = 177.8787
[2024-08-21 14:05:32] iter = 0060, loss = 159.5443
[2024-08-21 14:09:39] iter = 0070, loss = 199.6892
[2024-08-21 14:13:47] iter = 0080, loss = 169.3621
[2024-08-21 14:17:54] iter = 0090, loss = 163.9910
[2024-08-21 14:21:47] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.335094, train acc = 0.9967 train oa = 0.9967, test acc = 0.3822 test oa = 0.4217
Evaluate 1, mean = 0.3822 std = 0.0000
-------------------------
[2024-08-21 14:22:36] iter = 0100, loss = 159.3147
[2024-08-21 14:26:44] iter = 0110, loss = 203.9353
[2024-08-21 14:30:51] iter = 0120, loss = 175.6119
[2024-08-21 14:34:58] iter = 0130, loss = 158.8436
[2024-08-21 14:39:05] iter = 0140, loss = 156.9358
[2024-08-21 14:42:58] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.365373, train acc = 0.9867 train oa = 0.9867, test acc = 0.3795 test oa = 0.3941
Evaluate 1, mean = 0.3795 std = 0.0000
-------------------------
[2024-08-21 14:43:48] iter = 0150, loss = 150.5029
[2024-08-21 14:47:55] iter = 0160, loss = 155.2985
[2024-08-21 14:52:03] iter = 0170, loss = 164.0962
[2024-08-21 14:56:34] iter = 0180, loss = 155.4074

================== Exp 0 ==================
 
[2024-08-21 15:06:18] iter = 0000, loss = 251.2927
[2024-08-21 15:00:43] iter = 0190, loss = 162.9137
[2024-08-21 15:04:34] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.343536, train acc = 0.9900 train oa = 0.9900, test acc = 0.3990 test oa = 0.4234
Evaluate 1, mean = 0.3990 std = 0.0000
-------------------------
[2024-08-21 15:05:24] iter = 0200, loss = 169.0803

================== Exp 0 ==================
 
[2024-08-21 15:12:43] iter = 0000, loss = 250.6687
[2024-08-21 15:22:31] iter = 0010, loss = 168.5807
[2024-08-21 15:16:48] iter = 0010, loss = 167.5047
[2024-08-21 15:20:56] iter = 0020, loss = 169.8085
[2024-08-21 15:25:04] iter = 0030, loss = 168.7193
[2024-08-21 15:29:12] iter = 0040, loss = 177.0456
[2024-08-21 15:33:05] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.455461, train acc = 0.9733 train oa = 0.9733, test acc = 0.3840 test oa = 0.4200
Evaluate 1, mean = 0.3840 std = 0.0000
-------------------------
[2024-08-21 15:33:55] iter = 0050, loss = 195.9782
[2024-08-21 15:38:03] iter = 0060, loss = 162.3412
[2024-08-21 15:42:10] iter = 0070, loss = 157.9051
[2024-08-21 15:46:36] iter = 0080, loss = 164.4556
[2024-08-21 15:50:44] iter = 0090, loss = 166.9469
[2024-08-21 15:56:00] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.475621, train acc = 0.9533 train oa = 0.9533, test acc = 0.3160 test oa = 0.3821
Evaluate 1, mean = 0.3160 std = 0.0000
-------------------------
[2024-08-21 16:00:08] iter = 0100, loss = 159.8512
[2024-08-21 16:04:15] iter = 0110, loss = 223.0009
[2024-08-21 16:10:45] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.086343, train acc = 1.0000 train oa = 1.0000, test acc = 0.4907 test oa = 0.5422
[2024-08-21 16:10:20] iter = 0120, loss = 158.7427
[2024-08-21 16:11:56] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.080371, train acc = 0.9987 train oa = 0.9987, test acc = 0.5196 test oa = 0.5611
[2024-08-21 16:16:04] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.077321, train acc = 1.0000 train oa = 1.0000, test acc = 0.5033 test oa = 0.5404
[2024-08-21 16:14:47] iter = 0130, loss = 171.4863
[2024-08-21 16:19:55] iter = 0140, loss = 191.2486
[2024-08-21 16:23:49] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.487388, train acc = 0.9600 train oa = 0.9600, test acc = 0.2989 test oa = 0.3150
Evaluate 1, mean = 0.2989 std = 0.0000
-------------------------
[2024-08-21 16:24:41] iter = 0150, loss = 184.7735

================== Exp 0 ==================
 

================== Exp 0 ==================
 

================== Exp 0 ==================
 
[2024-08-21 16:29:07] iter = 0160, loss = 245.8151
[2024-08-21 16:29:15] iter = 0000, loss = 222.5449
[2024-08-21 16:33:16] iter = 0010, loss = 129.6352
[2024-08-21 16:33:20] iter = 0170, loss = 225.9230
[2024-08-21 16:37:56] iter = 0020, loss = 117.8951
[2024-08-21 16:38:08] iter = 0180, loss = 174.2835
[2024-08-21 16:41:59] iter = 0030, loss = 118.5492
[2024-08-21 16:42:24] iter = 0190, loss = 227.2095
[2024-08-21 16:46:00] iter = 0040, loss = 125.0749
[2024-08-21 16:46:25] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 1.064222, train acc = 0.7833 train oa = 0.7833, test acc = 0.3709 test oa = 0.3804
Evaluate 1, mean = 0.3709 std = 0.0000
-------------------------
[2024-08-21 16:47:16] iter = 0200, loss = 176.0477
[2024-08-21 16:49:47] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.347733, train acc = 0.9900 train oa = 0.9900, test acc = 0.4060 test oa = 0.4423
Evaluate 1, mean = 0.4060 std = 0.0000
-------------------------
[2024-08-21 16:50:35] iter = 0050, loss = 121.9709
[2024-08-21 16:54:34] iter = 0060, loss = 109.9473
[2024-08-21 16:58:33] iter = 0070, loss = 125.1169
[2024-08-21 17:02:36] iter = 0080, loss = 121.5408
[2024-08-21 17:06:35] iter = 0090, loss = 107.7345
[2024-08-21 17:10:21] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.355816, train acc = 0.9767 train oa = 0.9767, test acc = 0.4629 test oa = 0.4733
Evaluate 1, mean = 0.4629 std = 0.0000
-------------------------
[2024-08-21 17:11:09] iter = 0100, loss = 113.2012
[2024-08-21 17:15:07] iter = 0110, loss = 121.6016
[2024-08-21 17:19:05] iter = 0120, loss = 119.5325
[2024-08-21 17:23:03] iter = 0130, loss = 118.4228
[2024-08-21 17:30:07] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.073103, train acc = 1.0000 train oa = 1.0000, test acc = 0.5333 test oa = 0.5731
[2024-08-21 17:31:15] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.071161, train acc = 1.0000 train oa = 1.0000, test acc = 0.5284 test oa = 0.5800
[2024-08-21 17:27:02] iter = 0140, loss = 104.0367
[2024-08-21 17:32:23] Evaluate_02: epoch = 0200, train time = 67 s, train loss = 0.066914, train acc = 1.0000 train oa = 1.0000, test acc = 0.5277 test oa = 0.5731
[2024-08-21 17:30:46] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.338597, train acc = 0.9800 train oa = 0.9800, test acc = 0.4319 test oa = 0.4768
Evaluate 1, mean = 0.4319 std = 0.0000
-------------------------
[2024-08-21 17:31:33] iter = 0150, loss = 117.6413
[2024-08-21 17:35:36] iter = 0160, loss = 117.8582
[2024-08-21 17:39:34] iter = 0170, loss = 109.3016
[2024-08-21 17:43:33] iter = 0180, loss = 117.0771
[2024-08-21 17:47:32] iter = 0190, loss = 117.3544
[2024-08-21 17:53:19] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.303833, train acc = 0.9767 train oa = 0.9767, test acc = 0.4188 test oa = 0.4458
Evaluate 1, mean = 0.4188 std = 0.0000
-------------------------
[2024-08-21 17:54:20] iter = 0200, loss = 120.5256

================== Exp 0 ==================
 
[2024-08-21 18:06:20] iter = 0000, loss = 222.5449
[2024-08-21 18:10:17] iter = 0010, loss = 129.6352
[2024-08-21 18:14:27] iter = 0020, loss = 117.8951
[2024-08-21 18:18:42] iter = 0030, loss = 118.5492
[2024-08-21 18:26:46] Evaluate_00: epoch = 0200, train time = 189 s, train loss = 0.111775, train acc = 1.0000 train oa = 1.0000, test acc = 0.4851 test oa = 0.5267
[2024-08-21 18:23:20] iter = 0040, loss = 125.0749
[2024-08-21 18:28:37] Evaluate_00: epoch = 0200, train time = 71 s, train loss = 0.059291, train acc = 1.0000 train oa = 1.0000, test acc = 0.5231 test oa = 0.5680
[2024-08-21 18:29:49] Evaluate_01: epoch = 0200, train time = 71 s, train loss = 0.061467, train acc = 1.0000 train oa = 1.0000, test acc = 0.5377 test oa = 0.5766
[2024-08-21 18:30:10] Evaluate_01: epoch = 0200, train time = 196 s, train loss = 0.110635, train acc = 1.0000 train oa = 1.0000, test acc = 0.4669 test oa = 0.5112
[2024-08-21 18:31:00] Evaluate_02: epoch = 0200, train time = 71 s, train loss = 0.061235, train acc = 1.0000 train oa = 1.0000, test acc = 0.5483 test oa = 0.5800
[2024-08-21 18:27:06] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.347733, train acc = 0.9900 train oa = 0.9900, test acc = 0.4060 test oa = 0.4423
Evaluate 1, mean = 0.4060 std = 0.0000
-------------------------
[2024-08-21 18:27:54] iter = 0050, loss = 121.9709
[2024-08-21 18:33:21] Evaluate_02: epoch = 0200, train time = 190 s, train loss = 0.112856, train acc = 0.9987 train oa = 0.9987, test acc = 0.4855 test oa = 0.5215
[2024-08-21 18:31:52] iter = 0060, loss = 109.9473
[2024-08-21 18:35:49] iter = 0070, loss = 125.1169
[2024-08-21 18:39:48] iter = 0080, loss = 121.5408

================== Exp 0 ==================
 
[2024-08-21 18:42:04] iter = 0000, loss = 228.8700
[2024-08-21 18:46:03] iter = 0010, loss = 136.6535
[2024-08-21 18:50:02] iter = 0020, loss = 128.7372

================== Exp 0 ==================
 
[2024-08-21 18:50:26] iter = 0000, loss = 228.8700
[2024-08-21 18:54:03] iter = 0030, loss = 124.9005
[2024-08-21 18:54:26] iter = 0010, loss = 136.6535
[2024-08-21 18:58:04] iter = 0040, loss = 134.7644
[2024-08-21 18:58:31] iter = 0020, loss = 128.7372
[2024-08-21 19:01:54] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.585693, train acc = 0.8867 train oa = 0.8867, test acc = 0.4282 test oa = 0.4630
Evaluate 1, mean = 0.4282 std = 0.0000
-------------------------
[2024-08-21 19:02:34] iter = 0030, loss = 124.9005
[2024-08-21 19:02:43] iter = 0050, loss = 128.1318
[2024-08-21 19:06:37] iter = 0040, loss = 134.7644
[2024-08-21 19:06:44] iter = 0060, loss = 120.6248
[2024-08-21 19:10:30] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.576442, train acc = 0.8967 train oa = 0.8967, test acc = 0.4439 test oa = 0.4682
Evaluate 1, mean = 0.4439 std = 0.0000
-------------------------
[2024-08-21 19:10:45] iter = 0070, loss = 131.6532
[2024-08-21 19:11:19] iter = 0050, loss = 128.1318
[2024-08-21 19:14:46] iter = 0080, loss = 124.0804
[2024-08-21 19:15:22] iter = 0060, loss = 120.6248
[2024-08-21 19:18:47] iter = 0090, loss = 118.2186
[2024-08-21 19:19:24] iter = 0070, loss = 131.6532
[2024-08-21 19:22:38] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.625100, train acc = 0.8833 train oa = 0.8833, test acc = 0.3898 test oa = 0.4355
Evaluate 1, mean = 0.3898 std = 0.0000
-------------------------
[2024-08-21 19:23:26] iter = 0100, loss = 116.8511
[2024-08-21 19:23:28] iter = 0080, loss = 124.0804
[2024-08-21 19:27:27] iter = 0110, loss = 121.6263
[2024-08-21 19:27:30] iter = 0090, loss = 118.2186
[2024-08-21 19:31:24] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.599548, train acc = 0.9100 train oa = 0.9100, test acc = 0.3946 test oa = 0.4475
Evaluate 1, mean = 0.3946 std = 0.0000
-------------------------
[2024-08-21 19:31:29] iter = 0120, loss = 123.2486
[2024-08-21 19:32:12] iter = 0100, loss = 116.8511
[2024-08-21 19:35:30] iter = 0130, loss = 126.8190
[2024-08-21 19:36:15] iter = 0110, loss = 121.6263
[2024-08-21 19:39:31] iter = 0140, loss = 110.4687
[2024-08-21 19:40:17] iter = 0120, loss = 123.2486
[2024-08-21 19:43:21] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.609537, train acc = 0.9200 train oa = 0.9200, test acc = 0.4313 test oa = 0.4544
Evaluate 1, mean = 0.4313 std = 0.0000
-------------------------
[2024-08-21 19:44:11] iter = 0150, loss = 121.6022
[2024-08-21 19:44:20] iter = 0130, loss = 126.8190
[2024-08-21 19:48:12] iter = 0160, loss = 124.2105
[2024-08-21 19:48:22] iter = 0140, loss = 110.4687
[2024-08-21 19:52:13] iter = 0170, loss = 115.0018
[2024-08-21 19:52:15] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.620934, train acc = 0.9167 train oa = 0.9167, test acc = 0.4275 test oa = 0.4613
Evaluate 1, mean = 0.4275 std = 0.0000
-------------------------
[2024-08-21 19:53:04] iter = 0150, loss = 121.6022
[2024-08-21 19:56:15] iter = 0180, loss = 136.4572
[2024-08-21 19:57:07] iter = 0160, loss = 124.2105
[2024-08-21 20:00:15] iter = 0190, loss = 123.9403
[2024-08-21 20:01:08] iter = 0170, loss = 115.0018
[2024-08-21 20:04:04] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.753745, train acc = 0.8333 train oa = 0.8333, test acc = 0.3991 test oa = 0.4372
Evaluate 1, mean = 0.3991 std = 0.0000
-------------------------
[2024-08-21 20:04:53] iter = 0200, loss = 138.2250
[2024-08-21 20:05:38] iter = 0180, loss = 136.4572
[2024-08-21 20:09:39] iter = 0190, loss = 123.9403
[2024-08-21 20:13:26] Evaluate_00: epoch = 0200, train time = 36 s, train loss = 0.700566, train acc = 0.8700 train oa = 0.8700, test acc = 0.3926 test oa = 0.4337
Evaluate 1, mean = 0.3926 std = 0.0000
-------------------------
[2024-08-21 20:14:14] iter = 0200, loss = 138.2250
[2024-08-21 22:10:01] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.062989, train acc = 1.0000 train oa = 1.0000, test acc = 0.5414 test oa = 0.5731
[2024-08-21 22:11:09] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.066975, train acc = 1.0000 train oa = 1.0000, test acc = 0.5466 test oa = 0.5749
[2024-08-21 22:12:18] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.071121, train acc = 1.0000 train oa = 1.0000, test acc = 0.5423 test oa = 0.5749

================== Exp 0 ==================
 
[2024-08-21 22:42:49] iter = 0000, loss = 222.5449
[2024-08-21 22:46:43] iter = 0010, loss = 129.6352
[2024-08-21 22:50:40] iter = 0020, loss = 117.8951
[2024-08-21 22:54:38] iter = 0030, loss = 118.5492
[2024-08-21 22:58:35] iter = 0040, loss = 125.0749
[2024-08-21 23:02:19] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.347733, train acc = 0.9900 train oa = 0.9900, test acc = 0.4060 test oa = 0.4423
Evaluate 1, mean = 0.4060 std = 0.0000
-------------------------
[2024-08-21 23:03:07] iter = 0050, loss = 121.9709
[2024-08-21 23:07:05] iter = 0060, loss = 109.9473
[2024-08-21 23:11:02] iter = 0070, loss = 125.1169
[2024-08-21 23:14:59] iter = 0080, loss = 121.5408
[2024-08-21 23:18:56] iter = 0090, loss = 107.7345
[2024-08-21 23:22:40] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.355816, train acc = 0.9767 train oa = 0.9767, test acc = 0.4629 test oa = 0.4733
Evaluate 1, mean = 0.4629 std = 0.0000
-------------------------
[2024-08-21 23:23:27] iter = 0100, loss = 113.2012
[2024-08-21 23:27:25] iter = 0110, loss = 121.6016
[2024-08-21 23:31:22] iter = 0120, loss = 119.5325
[2024-08-21 23:35:19] iter = 0130, loss = 118.4228
[2024-08-21 23:39:16] iter = 0140, loss = 104.0367
[2024-08-21 23:42:59] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.338597, train acc = 0.9800 train oa = 0.9800, test acc = 0.4319 test oa = 0.4768
Evaluate 1, mean = 0.4319 std = 0.0000
-------------------------
[2024-08-21 23:43:47] iter = 0150, loss = 117.6413
[2024-08-21 23:47:44] iter = 0160, loss = 117.8582
[2024-08-21 23:51:42] iter = 0170, loss = 109.3016
[2024-08-21 23:55:39] iter = 0180, loss = 117.0771
[2024-08-21 23:59:37] iter = 0190, loss = 117.3544
[2024-08-22 00:03:20] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.303833, train acc = 0.9767 train oa = 0.9767, test acc = 0.4188 test oa = 0.4458
Evaluate 1, mean = 0.4188 std = 0.0000
-------------------------
[2024-08-22 00:04:07] iter = 0200, loss = 120.5256
[2024-08-22 00:38:04] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.064124, train acc = 1.0000 train oa = 1.0000, test acc = 0.5481 test oa = 0.5749
[2024-08-22 00:39:13] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.059009, train acc = 1.0000 train oa = 1.0000, test acc = 0.5584 test oa = 0.5886
[2024-08-22 00:40:22] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.064421, train acc = 1.0000 train oa = 1.0000, test acc = 0.5539 test oa = 0.5783
[2024-08-22 03:06:10] Evaluate_00: epoch = 0200, train time = 69 s, train loss = 0.123704, train acc = 1.0000 train oa = 1.0000, test acc = 0.4433 test oa = 0.4974
[2024-08-22 03:07:19] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.099464, train acc = 1.0000 train oa = 1.0000, test acc = 0.4662 test oa = 0.5181
[2024-08-22 03:08:27] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.109082, train acc = 0.9987 train oa = 0.9987, test acc = 0.4592 test oa = 0.5112
[2024-08-22 04:10:43] Evaluate_00: epoch = 0200, train time = 280 s, train loss = 0.071169, train acc = 1.0000 train oa = 1.0000, test acc = 0.5309 test oa = 0.5663
[2024-08-22 04:14:58] Evaluate_01: epoch = 0200, train time = 254 s, train loss = 0.061321, train acc = 1.0000 train oa = 1.0000, test acc = 0.5519 test oa = 0.5972
[2024-08-22 04:19:38] Evaluate_02: epoch = 0200, train time = 280 s, train loss = 0.067126, train acc = 1.0000 train oa = 1.0000, test acc = 0.5448 test oa = 0.5783
[2024-08-22 04:20:51] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.085591, train acc = 1.0000 train oa = 1.0000, test acc = 0.4861 test oa = 0.5404
[2024-08-22 04:22:00] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.079257, train acc = 1.0000 train oa = 1.0000, test acc = 0.5121 test oa = 0.5525
[2024-08-22 04:23:08] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.081669, train acc = 0.9987 train oa = 0.9987, test acc = 0.5074 test oa = 0.5577
[2024-08-22 08:02:28] Evaluate_00: epoch = 0200, train time = 69 s, train loss = 0.058491, train acc = 1.0000 train oa = 1.0000, test acc = 0.5748 test oa = 0.6024
[2024-08-22 08:03:37] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.067991, train acc = 0.9987 train oa = 0.9987, test acc = 0.5700 test oa = 0.6024
[2024-08-22 08:04:45] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.071624, train acc = 1.0000 train oa = 1.0000, test acc = 0.5593 test oa = 0.5886
[2024-08-22 09:00:36] Evaluate_00: epoch = 0200, train time = 186 s, train loss = 0.085591, train acc = 1.0000 train oa = 1.0000, test acc = 0.4861 test oa = 0.5404
[2024-08-22 09:03:40] Evaluate_01: epoch = 0200, train time = 184 s, train loss = 0.079257, train acc = 1.0000 train oa = 1.0000, test acc = 0.5121 test oa = 0.5525
[2024-08-22 09:06:59] Evaluate_02: epoch = 0200, train time = 199 s, train loss = 0.081669, train acc = 0.9987 train oa = 0.9987, test acc = 0.5074 test oa = 0.5577

================== Exp 0 ==================
 

================== Exp 0 ==================
 
[2024-08-22 10:18:58] iter = 0000, loss = 222.7066
[2024-08-22 10:22:52] iter = 0010, loss = 129.0839
[2024-08-22 10:26:50] iter = 0020, loss = 119.4915
[2024-08-22 10:30:48] iter = 0030, loss = 114.9340
[2024-08-22 10:34:46] iter = 0040, loss = 122.9723
[2024-08-22 10:41:28] Evaluate_00: epoch = 0200, train time = 211 s, train loss = 0.252958, train acc = 0.9900 train oa = 0.9900, test acc = 0.4311 test oa = 0.4509
Evaluate 1, mean = 0.4311 std = 0.0000
-------------------------
[2024-08-22 10:42:56] iter = 0050, loss = 117.3595
[2024-08-22 10:47:04] iter = 0060, loss = 109.7140
[2024-08-22 10:51:02] iter = 0070, loss = 121.7801
[2024-08-22 10:55:05] iter = 0080, loss = 117.4194
[2024-08-22 10:59:03] iter = 0090, loss = 106.5743
[2024-08-22 11:02:48] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.291085, train acc = 0.9967 train oa = 0.9967, test acc = 0.4315 test oa = 0.4682
Evaluate 1, mean = 0.4315 std = 0.0000
-------------------------
[2024-08-22 11:03:36] iter = 0100, loss = 111.4367
[2024-08-22 11:09:18] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.070730, train acc = 1.0000 train oa = 1.0000, test acc = 0.5299 test oa = 0.5749
[2024-08-22 11:10:26] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.064977, train acc = 1.0000 train oa = 1.0000, test acc = 0.5327 test oa = 0.5697
[2024-08-22 11:11:36] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.067921, train acc = 1.0000 train oa = 1.0000, test acc = 0.5334 test oa = 0.5783
[2024-08-22 11:07:43] iter = 0110, loss = 107.2673
[2024-08-22 11:11:41] iter = 0120, loss = 112.2456
[2024-08-22 11:15:38] iter = 0130, loss = 117.7012
[2024-08-22 11:19:37] iter = 0140, loss = 104.8497
[2024-08-22 11:23:21] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.308163, train acc = 0.9900 train oa = 0.9900, test acc = 0.4365 test oa = 0.4527
Evaluate 1, mean = 0.4365 std = 0.0000
-------------------------
[2024-08-22 11:24:08] iter = 0150, loss = 114.7262
[2024-08-22 11:28:06] iter = 0160, loss = 115.7430
[2024-08-22 11:32:03] iter = 0170, loss = 108.2120
[2024-08-22 11:36:01] iter = 0180, loss = 118.7950
[2024-08-22 11:39:59] iter = 0190, loss = 113.3973
[2024-08-22 11:43:43] Evaluate_00: epoch = 0200, train time = 33 s, train loss = 0.303590, train acc = 0.9900 train oa = 0.9900, test acc = 0.4282 test oa = 0.4475
Evaluate 1, mean = 0.4282 std = 0.0000
-------------------------
[2024-08-22 11:44:30] iter = 0200, loss = 121.2659

================== Exp 0 ==================
 
[2024-08-22 13:56:06] iter = 0000, loss = 222.5449
[2024-08-22 14:02:05] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.078534, train acc = 0.9973 train oa = 0.9973, test acc = 0.5322 test oa = 0.5559
[2024-08-22 14:03:28] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.073357, train acc = 1.0000 train oa = 1.0000, test acc = 0.5360 test oa = 0.5663
[2024-08-22 14:00:11] iter = 0010, loss = 129.6352
[2024-08-22 14:05:19] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.071076, train acc = 1.0000 train oa = 1.0000, test acc = 0.5430 test oa = 0.5783
[2024-08-22 14:04:22] iter = 0020, loss = 117.8951
[2024-08-22 14:08:21] iter = 0030, loss = 118.5492
[2024-08-22 14:12:20] iter = 0040, loss = 125.0749
[2024-08-22 14:16:05] Evaluate_00: epoch = 0200, train time = 34 s, train loss = 0.344183, train acc = 0.9833 train oa = 0.9833, test acc = 0.4150 test oa = 0.4389
Evaluate 1, mean = 0.4150 std = 0.0000
-------------------------
[2024-08-22 14:16:53] iter = 0050, loss = 121.9709
[2024-08-22 14:20:50] iter = 0060, loss = 109.9473
[2024-08-22 14:24:49] iter = 0070, loss = 125.1169
[2024-08-22 14:28:51] iter = 0080, loss = 121.5408
[2024-08-22 14:32:48] iter = 0090, loss = 107.7345
[2024-08-22 14:36:34] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.339510, train acc = 0.9833 train oa = 0.9833, test acc = 0.4489 test oa = 0.4613
Evaluate 1, mean = 0.4489 std = 0.0000
-------------------------
[2024-08-22 14:37:21] iter = 0100, loss = 113.2012
[2024-08-22 14:41:19] iter = 0110, loss = 121.6016
[2024-08-22 14:45:16] iter = 0120, loss = 119.5325
[2024-08-22 14:49:14] iter = 0130, loss = 118.4228
[2024-08-22 14:53:12] iter = 0140, loss = 104.0367
[2024-08-22 14:56:58] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.322753, train acc = 0.9833 train oa = 0.9833, test acc = 0.4303 test oa = 0.4664
Evaluate 1, mean = 0.4303 std = 0.0000
-------------------------
[2024-08-22 14:57:45] iter = 0150, loss = 117.6413
[2024-08-22 15:01:43] iter = 0160, loss = 117.8582
[2024-08-22 15:05:41] iter = 0170, loss = 109.3016
[2024-08-22 15:09:38] iter = 0180, loss = 117.0771
[2024-08-22 15:13:36] iter = 0190, loss = 117.3544
[2024-08-22 15:17:21] Evaluate_00: epoch = 0200, train time = 35 s, train loss = 0.322494, train acc = 0.9667 train oa = 0.9667, test acc = 0.4258 test oa = 0.4527
Evaluate 1, mean = 0.4258 std = 0.0000
-------------------------
[2024-08-22 15:18:09] iter = 0200, loss = 120.5256

================== Exp 0 ==================
 
[2024-08-22 17:29:34] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.117291, train acc = 1.0000 train oa = 1.0000, test acc = 0.4805 test oa = 0.5060
[2024-08-22 17:30:42] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.101720, train acc = 1.0000 train oa = 1.0000, test acc = 0.4764 test oa = 0.5232
[2024-08-22 17:31:51] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.112597, train acc = 0.9947 train oa = 0.9947, test acc = 0.4783 test oa = 0.5250
[2024-08-22 17:39:08] Evaluate_00: epoch = 0200, train time = 82 s, train loss = 0.070730, train acc = 1.0000 train oa = 1.0000, test acc = 0.5299 test oa = 0.5749
[2024-08-22 17:40:30] Evaluate_01: epoch = 0200, train time = 81 s, train loss = 0.064977, train acc = 1.0000 train oa = 1.0000, test acc = 0.5327 test oa = 0.5697
[2024-08-22 17:41:53] Evaluate_02: epoch = 0200, train time = 83 s, train loss = 0.067921, train acc = 1.0000 train oa = 1.0000, test acc = 0.5334 test oa = 0.5783

================== Exp 0 ==================
 
[2024-08-22 18:40:55] iter = 0000, loss = 201.2523

================== Exp 0 ==================
 
[2024-08-22 18:41:33] iter = 0000, loss = 201.2523
[2024-08-22 18:46:59] iter = 0010, loss = 128.6853
[2024-08-22 18:47:38] iter = 0010, loss = 128.6853
[2024-08-22 18:53:08] iter = 0020, loss = 131.4277
[2024-08-22 18:53:43] iter = 0020, loss = 131.4277
[2024-08-22 18:59:33] iter = 0030, loss = 127.0927
[2024-08-22 18:59:48] iter = 0030, loss = 127.0927
[2024-08-22 19:05:41] iter = 0040, loss = 129.2807
[2024-08-22 19:05:52] iter = 0040, loss = 129.2807
[2024-08-22 19:11:15] Evaluate_00: epoch = 0200, train time = 40 s, train loss = 0.328670, train acc = 0.9900 train oa = 0.9900, test acc = 0.4479 test oa = 0.4630
Evaluate 1, mean = 0.4479 std = 0.0000
-------------------------
[2024-08-22 19:11:22] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.294500, train acc = 0.9967 train oa = 0.9967, test acc = 0.4348 test oa = 0.4527
Evaluate 1, mean = 0.4348 std = 0.0000
-------------------------
[2024-08-22 19:12:28] iter = 0050, loss = 124.9215
[2024-08-22 19:12:35] iter = 0050, loss = 124.9215
[2024-08-22 19:18:35] iter = 0060, loss = 115.8721
[2024-08-22 19:18:39] iter = 0060, loss = 115.8721
[2024-08-22 19:24:58] iter = 0070, loss = 113.9179
[2024-08-22 19:25:00] iter = 0070, loss = 113.9179
[2024-08-22 19:31:05] iter = 0080, loss = 125.3214
[2024-08-22 19:31:05] iter = 0080, loss = 125.3214
[2024-08-22 19:37:45] iter = 0090, loss = 118.1717
[2024-08-22 19:37:48] iter = 0090, loss = 118.1717
[2024-08-22 19:44:48] Evaluate_00: epoch = 0200, train time = 38 s, train loss = 0.270878, train acc = 0.9967 train oa = 0.9967, test acc = 0.4493 test oa = 0.4750
Evaluate 1, mean = 0.4493 std = 0.0000
-------------------------
[2024-08-22 19:44:52] Evaluate_00: epoch = 0200, train time = 40 s, train loss = 0.310710, train acc = 0.9900 train oa = 0.9900, test acc = 0.4566 test oa = 0.4819
Evaluate 1, mean = 0.4566 std = 0.0000
-------------------------
[2024-08-22 19:46:02] iter = 0100, loss = 121.2074
[2024-08-22 19:46:06] iter = 0100, loss = 121.2074
[2024-08-22 19:52:06] iter = 0110, loss = 117.2607
[2024-08-22 19:52:13] iter = 0110, loss = 117.2607
[2024-08-22 19:58:09] iter = 0120, loss = 129.6799
[2024-08-22 19:58:20] iter = 0120, loss = 129.6799
[2024-08-22 20:04:13] iter = 0130, loss = 121.9397
[2024-08-22 20:08:37] Evaluate_00: epoch = 0200, train time = 82 s, train loss = 0.065809, train acc = 1.0000 train oa = 1.0000, test acc = 0.5252 test oa = 0.5594
[2024-08-22 20:04:26] iter = 0130, loss = 121.9397
[2024-08-22 20:10:00] Evaluate_01: epoch = 0200, train time = 82 s, train loss = 0.063605, train acc = 1.0000 train oa = 1.0000, test acc = 0.5303 test oa = 0.5852
[2024-08-22 20:11:21] Evaluate_02: epoch = 0200, train time = 81 s, train loss = 0.061065, train acc = 1.0000 train oa = 1.0000, test acc = 0.5282 test oa = 0.5611
[2024-08-22 20:10:16] iter = 0140, loss = 111.9527
[2024-08-22 20:10:33] iter = 0140, loss = 111.9527
[2024-08-22 20:15:44] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.263479, train acc = 0.9967 train oa = 0.9967, test acc = 0.4288 test oa = 0.4441
Evaluate 1, mean = 0.4288 std = 0.0000
-------------------------
[2024-08-22 20:16:06] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.322896, train acc = 0.9833 train oa = 0.9833, test acc = 0.4300 test oa = 0.4441
Evaluate 1, mean = 0.4300 std = 0.0000
-------------------------
[2024-08-22 20:16:57] iter = 0150, loss = 119.0354
[2024-08-22 20:17:19] iter = 0150, loss = 119.0354
[2024-08-22 20:23:01] iter = 0160, loss = 123.0326
[2024-08-22 20:23:25] iter = 0160, loss = 123.0326
[2024-08-22 20:29:05] iter = 0170, loss = 120.8448
[2024-08-22 20:29:32] iter = 0170, loss = 120.8448
[2024-08-22 20:35:08] iter = 0180, loss = 113.2237
[2024-08-22 20:35:38] iter = 0180, loss = 113.2237
[2024-08-22 20:41:17] iter = 0190, loss = 116.6572
[2024-08-22 20:41:54] iter = 0190, loss = 116.6572
[2024-08-22 20:46:46] Evaluate_00: epoch = 0200, train time = 37 s, train loss = 0.295540, train acc = 0.9900 train oa = 0.9900, test acc = 0.4266 test oa = 0.4544
Evaluate 1, mean = 0.4266 std = 0.0000
-------------------------
[2024-08-22 20:47:27] Evaluate_00: epoch = 0200, train time = 39 s, train loss = 0.333868, train acc = 0.9833 train oa = 0.9833, test acc = 0.4249 test oa = 0.4441
Evaluate 1, mean = 0.4249 std = 0.0000
-------------------------
[2024-08-22 20:47:59] iter = 0200, loss = 118.7607
[2024-08-22 20:48:41] iter = 0200, loss = 118.7607
[2024-08-23 00:34:47] Evaluate_00: epoch = 0200, train time = 69 s, train loss = 0.262702, train acc = 0.9813 train oa = 0.9813, test acc = 0.4511 test oa = 0.4905
[2024-08-23 00:35:56] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.263932, train acc = 0.9840 train oa = 0.9840, test acc = 0.4182 test oa = 0.4664
[2024-08-23 00:37:05] Evaluate_02: epoch = 0200, train time = 69 s, train loss = 0.261038, train acc = 0.9827 train oa = 0.9827, test acc = 0.4249 test oa = 0.4716
[2024-08-23 03:27:53] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.192934, train acc = 0.9960 train oa = 0.9960, test acc = 0.4814 test oa = 0.5043
[2024-08-23 03:29:01] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.223881, train acc = 0.9893 train oa = 0.9893, test acc = 0.4666 test oa = 0.5026
[2024-08-23 03:30:09] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.229981, train acc = 0.9920 train oa = 0.9920, test acc = 0.4804 test oa = 0.5009
[2024-08-23 05:02:50] Evaluate_00: epoch = 0200, train time = 287 s, train loss = 0.344357, train acc = 0.9693 train oa = 0.9693, test acc = 0.4165 test oa = 0.4475
[2024-08-23 05:07:14] Evaluate_01: epoch = 0200, train time = 264 s, train loss = 0.338374, train acc = 0.9733 train oa = 0.9733, test acc = 0.3827 test oa = 0.4423
[2024-08-23 05:11:01] Evaluate_02: epoch = 0200, train time = 226 s, train loss = 0.362828, train acc = 0.9627 train oa = 0.9627, test acc = 0.4037 test oa = 0.4337
[2024-08-23 05:21:00] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.241795, train acc = 0.9867 train oa = 0.9867, test acc = 0.4724 test oa = 0.4905
[2024-08-23 05:22:08] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.269335, train acc = 0.9813 train oa = 0.9813, test acc = 0.4558 test oa = 0.4785
[2024-08-23 05:23:17] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.264418, train acc = 0.9773 train oa = 0.9773, test acc = 0.4777 test oa = 0.4957
[2024-08-23 06:31:29] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.231396, train acc = 0.9867 train oa = 0.9867, test acc = 0.4584 test oa = 0.4819
[2024-08-23 06:32:38] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.258482, train acc = 0.9867 train oa = 0.9867, test acc = 0.4668 test oa = 0.4854
[2024-08-23 06:33:46] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.237692, train acc = 0.9880 train oa = 0.9880, test acc = 0.4820 test oa = 0.5043
[2024-08-23 08:15:56] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.307220, train acc = 0.9760 train oa = 0.9760, test acc = 0.4368 test oa = 0.4854
[2024-08-23 08:17:04] Evaluate_01: epoch = 0200, train time = 67 s, train loss = 0.270875, train acc = 0.9840 train oa = 0.9840, test acc = 0.4640 test oa = 0.4991
[2024-08-23 08:18:13] Evaluate_02: epoch = 0200, train time = 69 s, train loss = 0.261082, train acc = 0.9787 train oa = 0.9787, test acc = 0.4465 test oa = 0.4819
[2024-08-23 09:26:13] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.250824, train acc = 0.9907 train oa = 0.9907, test acc = 0.4396 test oa = 0.4836
[2024-08-23 09:27:22] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.262745, train acc = 0.9840 train oa = 0.9840, test acc = 0.4440 test oa = 0.4733
[2024-08-23 09:28:31] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.260175, train acc = 0.9867 train oa = 0.9867, test acc = 0.4516 test oa = 0.4785
[2024-08-23 12:07:16] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.243560, train acc = 0.9880 train oa = 0.9880, test acc = 0.4654 test oa = 0.4940
[2024-08-23 12:08:26] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.268165, train acc = 0.9720 train oa = 0.9720, test acc = 0.4780 test oa = 0.4991
[2024-08-23 12:09:34] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.248339, train acc = 0.9827 train oa = 0.9827, test acc = 0.4604 test oa = 0.4905
[2024-08-23 14:59:58] Evaluate_00: epoch = 0200, train time = 69 s, train loss = 0.321001, train acc = 0.9760 train oa = 0.9760, test acc = 0.4434 test oa = 0.4596
[2024-08-23 15:01:07] Evaluate_01: epoch = 0200, train time = 69 s, train loss = 0.361605, train acc = 0.9627 train oa = 0.9627, test acc = 0.4222 test oa = 0.4406
[2024-08-23 15:02:15] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.380489, train acc = 0.9693 train oa = 0.9693, test acc = 0.4043 test oa = 0.4406
[2024-08-23 15:20:27] Evaluate_00: epoch = 0200, train time = 187 s, train loss = 0.219940, train acc = 0.9920 train oa = 0.9920, test acc = 0.4623 test oa = 0.4836
[2024-08-23 15:23:47] Evaluate_01: epoch = 0200, train time = 199 s, train loss = 0.270825, train acc = 0.9840 train oa = 0.9840, test acc = 0.4479 test oa = 0.4802
[2024-08-23 15:27:10] Evaluate_02: epoch = 0200, train time = 203 s, train loss = 0.278786, train acc = 0.9800 train oa = 0.9800, test acc = 0.4573 test oa = 0.4802
[2024-08-23 17:41:08] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.243804, train acc = 0.9840 train oa = 0.9840, test acc = 0.4856 test oa = 0.5060
[2024-08-23 17:42:16] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.214096, train acc = 0.9907 train oa = 0.9907, test acc = 0.4583 test oa = 0.4940
[2024-08-23 17:43:25] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.234123, train acc = 0.9893 train oa = 0.9893, test acc = 0.4631 test oa = 0.4974
[2024-08-23 20:10:49] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.237886, train acc = 0.9893 train oa = 0.9893, test acc = 0.4608 test oa = 0.4888
[2024-08-23 20:11:58] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.257990, train acc = 0.9880 train oa = 0.9880, test acc = 0.4394 test oa = 0.4716
[2024-08-23 20:13:06] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.233975, train acc = 0.9840 train oa = 0.9840, test acc = 0.4511 test oa = 0.4854
[2024-08-23 22:21:08] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.250350, train acc = 0.9853 train oa = 0.9853, test acc = 0.4497 test oa = 0.4802
[2024-08-23 22:22:16] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.286504, train acc = 0.9693 train oa = 0.9693, test acc = 0.4341 test oa = 0.4716
[2024-08-23 22:23:25] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.238623, train acc = 0.9893 train oa = 0.9893, test acc = 0.4461 test oa = 0.4871
[2024-08-24 01:02:46] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.582068, train acc = 0.9133 train oa = 0.9133, test acc = 0.3578 test oa = 0.3924
[2024-08-24 01:03:54] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.552146, train acc = 0.9213 train oa = 0.9213, test acc = 0.3886 test oa = 0.4096
[2024-08-24 01:05:03] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.552409, train acc = 0.9200 train oa = 0.9200, test acc = 0.3634 test oa = 0.4079
[2024-08-24 01:32:11] Evaluate_00: epoch = 0200, train time = 222 s, train loss = nan, train acc = 0.0667 train oa = 0.0667, test acc = 0.0667 test oa = 0.0293
[2024-08-24 01:35:24] Evaluate_01: epoch = 0200, train time = 193 s, train loss = nan, train acc = 0.0667 train oa = 0.0667, test acc = 0.0667 test oa = 0.0293
[2024-08-24 01:39:01] Evaluate_02: epoch = 0200, train time = 216 s, train loss = nan, train acc = 0.0667 train oa = 0.0667, test acc = 0.0667 test oa = 0.0293
[2024-08-24 02:30:29] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.255498, train acc = 0.9800 train oa = 0.9800, test acc = 0.4691 test oa = 0.4923
[2024-08-24 02:31:38] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.261393, train acc = 0.9747 train oa = 0.9747, test acc = 0.4542 test oa = 0.4923
[2024-08-24 02:32:46] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.267798, train acc = 0.9720 train oa = 0.9720, test acc = 0.4647 test oa = 0.5009
[2024-08-24 04:49:15] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.302553, train acc = 0.9827 train oa = 0.9827, test acc = 0.4726 test oa = 0.4802
[2024-08-24 04:50:23] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.271531, train acc = 0.9840 train oa = 0.9840, test acc = 0.4484 test oa = 0.4802
[2024-08-24 04:51:32] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.267710, train acc = 0.9827 train oa = 0.9827, test acc = 0.4791 test oa = 0.4923
[2024-08-24 07:19:32] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.407852, train acc = 0.9533 train oa = 0.9533, test acc = 0.4264 test oa = 0.4561
[2024-08-24 07:20:41] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.474831, train acc = 0.9373 train oa = 0.9373, test acc = 0.4273 test oa = 0.4337
[2024-08-24 07:21:49] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.432076, train acc = 0.9440 train oa = 0.9440, test acc = 0.4371 test oa = 0.4630
[2024-08-24 08:03:30] Evaluate_00: epoch = 0200, train time = 240 s, train loss = 0.255498, train acc = 0.9800 train oa = 0.9800, test acc = 0.4691 test oa = 0.4923
[2024-08-24 08:07:13] Evaluate_01: epoch = 0200, train time = 222 s, train loss = 0.261393, train acc = 0.9747 train oa = 0.9747, test acc = 0.4542 test oa = 0.4923
[2024-08-24 08:10:57] Evaluate_02: epoch = 0200, train time = 223 s, train loss = 0.267798, train acc = 0.9720 train oa = 0.9720, test acc = 0.4647 test oa = 0.5009
[2024-08-24 09:49:29] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.265383, train acc = 0.9840 train oa = 0.9840, test acc = 0.4666 test oa = 0.4905
[2024-08-24 09:50:38] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.305858, train acc = 0.9787 train oa = 0.9787, test acc = 0.4703 test oa = 0.4854
[2024-08-24 09:51:46] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.287645, train acc = 0.9760 train oa = 0.9760, test acc = 0.4643 test oa = 0.4871
[2024-08-24 11:59:40] Evaluate_00: epoch = 0200, train time = 68 s, train loss = 0.526825, train acc = 0.9400 train oa = 0.9400, test acc = 0.3800 test oa = 0.3976
[2024-08-24 12:00:48] Evaluate_01: epoch = 0200, train time = 68 s, train loss = 0.573154, train acc = 0.9280 train oa = 0.9280, test acc = 0.3577 test oa = 0.3804
[2024-08-24 12:01:56] Evaluate_02: epoch = 0200, train time = 68 s, train loss = 0.494820, train acc = 0.9533 train oa = 0.9533, test acc = 0.3623 test oa = 0.3941
[2024-08-24 13:33:19] Evaluate_00: epoch = 0200, train time = 80 s, train loss = 0.265383, train acc = 0.9840 train oa = 0.9840, test acc = 0.4666 test oa = 0.4905
[2024-08-24 13:34:39] Evaluate_01: epoch = 0200, train time = 79 s, train loss = 0.305858, train acc = 0.9787 train oa = 0.9787, test acc = 0.4703 test oa = 0.4854
[2024-08-24 13:36:00] Evaluate_02: epoch = 0200, train time = 80 s, train loss = 0.287645, train acc = 0.9760 train oa = 0.9760, test acc = 0.4643 test oa = 0.4871
