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git:
sha: dc8f9ae1ed8cb168a3fe69865e9dc55bfafe177f, status: clean, branch: master
Namespace(name='HS_H05',
model='vit',
backbone='vit_base_patch16_224',
pretrained=True,
aux_layer=-3,
isgap=False,
finalval=False,
seed=0,
random_seed=False,
work_dir='/media/hossein-rahmani/Data1/xinyuyang/space/vocseg',
output_dir=PosixPath('/media/hossein-rahmani/Data1/xinyuyang/space/vocseg/HS_H05'),
device='cuda',
save_per_eval=10,
eval_iters=4000,
turnon_rawcam=False,
fasteval=True,
valfull=False,
eval_threshold_filters=None,
dataset='VOC12',
coco_root=None,
voc12_root='/media/hossein-rahmani/Data1/xinyuyang/data/voc/VOCdevkit/VOC2012',
crop_size=448,
scales=(0.5,
2),
ignore_index=255,
num_classes=21,
batch_size=2,
num_workers=4,
max_iters=32000,
warmup_iters=6000,
lr=6e-05,
min_mult=0.0,
wt_dec=0.01,
cam_weight=0.05,
camloss_version='v1',
seg_weight=0.1,
segfg_alpha=0.5,
reg_weight=0.05,
momentum=0.9994,
pseudo_scales=[1.0,
0.5,
1.5],
high_thre=0.7,
high_thre_aux=0.7,
bkg_thre=0.5,
low_thre=0.2,
low_thre_aux=0.25,
usegmm=False,
usegmmaux=False,
gmmscale=16,
gmmfilter_thre=0.05,
queue_update_ratio=100,
camweight_beta=1.0,
par_downscale=2,
usepar=False,
aux_cam2seg=True,
aux_cam2seg_traditional=True,
aux_cam2seg_alpha=0.5,
aux_seg2cam=False,
aux_seg2cam_alpha=0.5,
seg_softmaxtemp=0.01,
segconf_thre=0.25,
after_softmax=False,
detach='none',
use_cammix=False,
oracle_camloss_version='v1',
oracle_camloss_detach=False,
oracle_camloss_bgmax=True,
rank=0,
world_size=2,
gpu=0,
dist_url='env://',
distributed=True,
dist_backend='nccl')
<dataloaders.voc.VOC12ClsDatasetNew object at 0x7fd503152c20>
dataset name: VOC12SegDataset
length: 1449
split: val
here pretrained
Number of params for Network: 92M
Start training
Iter: 200; Elasped: 0:03:08; ETA: 8:18:12; Itertime: 0.94; LR: 7.960e-06;
overall_loss: 6.4637, cls_loss: 0.4267, cls_acc: 0.334, cls_aux_loss: 6.0371, cls_aux_acc: 0.217, seg_loss: 3.0748, cam_loss: 0.7614, reg_loss: -0.2222 ...
Iter: 400; Elasped: 0:06:11; ETA: 8:08:29; Itertime: 0.92; LR: 1.596e-05;
overall_loss: 0.9836, cls_loss: 0.2422, cls_acc: 0.454, cls_aux_loss: 0.7414, cls_aux_acc: 0.335, seg_loss: 3.0700, cam_loss: 0.7393, reg_loss: -0.2401 ...
Iter: 600; Elasped: 0:09:14; ETA: 8:03:12; Itertime: 0.92; LR: 2.396e-05;
overall_loss: 0.5032, cls_loss: 0.2023, cls_acc: 0.594, cls_aux_loss: 0.3009, cls_aux_acc: 0.437, seg_loss: 3.0679, cam_loss: 0.7511, reg_loss: -0.2285 ...
Iter: 800; Elasped: 0:12:18; ETA: 7:59:42; Itertime: 0.92; LR: 3.196e-05;
overall_loss: 0.4061, cls_loss: 0.1641, cls_acc: 0.765, cls_aux_loss: 0.2420, cls_aux_acc: 0.576, seg_loss: 3.0709, cam_loss: 0.7978, reg_loss: -0.2413 ...
Iter: 1000; Elasped: 0:15:21; ETA: 7:55:51; Itertime: 0.92; LR: 3.996e-05;
overall_loss: 0.3453, cls_loss: 0.1234, cls_acc: 0.867, cls_aux_loss: 0.2219, cls_aux_acc: 0.646, seg_loss: 3.0711, cam_loss: 0.8721, reg_loss: -0.2293 ...
Iter: 1200; Elasped: 0:18:25; ETA: 7:52:41; Itertime: 0.92; LR: 4.796e-05;
overall_loss: 0.3181, cls_loss: 0.1105, cls_acc: 0.872, cls_aux_loss: 0.2076, cls_aux_acc: 0.717, seg_loss: 3.0582, cam_loss: 0.9257, reg_loss: -0.2196 ...
Iter: 1400; Elasped: 0:21:28; ETA: 7:49:12; Itertime: 0.92; LR: 5.596e-05;
overall_loss: 0.2783, cls_loss: 0.0902, cls_acc: 0.908, cls_aux_loss: 0.1881, cls_aux_acc: 0.787, seg_loss: 3.0343, cam_loss: 0.9630, reg_loss: -0.2316 ...
Iter: 1600; Elasped: 0:24:31; ETA: 7:45:49; Itertime: 0.92; LR: 5.729e-05;
overall_loss: 0.2720, cls_loss: 0.0900, cls_acc: 0.915, cls_aux_loss: 0.1820, cls_aux_acc: 0.800, seg_loss: 3.0012, cam_loss: 0.9963, reg_loss: -0.2222 ...
Iter: 1800; Elasped: 0:27:35; ETA: 7:42:47; Itertime: 0.92; LR: 5.696e-05;
overall_loss: 0.2859, cls_loss: 0.0955, cls_acc: 0.904, cls_aux_loss: 0.1904, cls_aux_acc: 0.818, seg_loss: 2.9933, cam_loss: 1.0252, reg_loss: -0.2152 ...
Iter: 2000; Elasped: 0:30:39; ETA: 7:39:45; Itertime: 0.92; LR: 5.662e-05;
overall_loss: 0.2312, cls_loss: 0.0796, cls_acc: 0.919, cls_aux_loss: 0.1516, cls_aux_acc: 0.842, seg_loss: 2.9549, cam_loss: 1.0206, reg_loss: -0.2208 ...
Iter: 2200; Elasped: 0:33:43; ETA: 7:36:42; Itertime: 0.92; LR: 5.628e-05;
overall_loss: 0.2359, cls_loss: 0.0850, cls_acc: 0.920, cls_aux_loss: 0.1509, cls_aux_acc: 0.866, seg_loss: 2.9767, cam_loss: 1.0383, reg_loss: -0.2333 ...
Iter: 2400; Elasped: 0:36:46; ETA: 7:33:27; Itertime: 0.92; LR: 5.594e-05;
overall_loss: 0.2393, cls_loss: 0.0887, cls_acc: 0.900, cls_aux_loss: 0.1507, cls_aux_acc: 0.850, seg_loss: 2.9639, cam_loss: 1.0639, reg_loss: -0.2325 ...
Iter: 2600; Elasped: 0:39:50; ETA: 7:30:25; Itertime: 0.92; LR: 5.560e-05;
overall_loss: 0.3776, cls_loss: 0.1264, cls_acc: 0.813, cls_aux_loss: 0.2512, cls_aux_acc: 0.714, seg_loss: 2.9376, cam_loss: 1.0060, reg_loss: -0.2174 ...
Iter: 2800; Elasped: 0:42:54; ETA: 7:27:23; Itertime: 0.92; LR: 5.526e-05;
overall_loss: 0.2767, cls_loss: 0.0948, cls_acc: 0.890, cls_aux_loss: 0.1819, cls_aux_acc: 0.811, seg_loss: 2.9212, cam_loss: 1.0254, reg_loss: -0.2070 ...
Iter: 3000; Elasped: 0:45:58; ETA: 7:24:20; Itertime: 0.92; LR: 5.491e-05;
overall_loss: 0.2216, cls_loss: 0.0809, cls_acc: 0.911, cls_aux_loss: 0.1407, cls_aux_acc: 0.861, seg_loss: 2.9275, cam_loss: 1.0612, reg_loss: -0.2176 ...
Iter: 3200; Elasped: 0:49:01; ETA: 7:21:09; Itertime: 0.92; LR: 5.457e-05;
overall_loss: 0.2518, cls_loss: 0.0930, cls_acc: 0.888, cls_aux_loss: 0.1588, cls_aux_acc: 0.832, seg_loss: 2.9251, cam_loss: 1.0185, reg_loss: -0.2290 ...
Iter: 3400; Elasped: 0:52:04; ETA: 7:17:58; Itertime: 0.92; LR: 5.423e-05;
overall_loss: 0.2475, cls_loss: 0.0911, cls_acc: 0.903, cls_aux_loss: 0.1565, cls_aux_acc: 0.854, seg_loss: 2.9215, cam_loss: 1.0454, reg_loss: -0.2249 ...
Iter: 3600; Elasped: 0:55:08; ETA: 7:14:56; Itertime: 0.92; LR: 5.389e-05;
overall_loss: 0.1816, cls_loss: 0.0669, cls_acc: 0.933, cls_aux_loss: 0.1147, cls_aux_acc: 0.882, seg_loss: 2.9283, cam_loss: 1.0328, reg_loss: -0.2365 ...
Iter: 3800; Elasped: 0:58:11; ETA: 7:11:46; Itertime: 0.92; LR: 5.355e-05;
overall_loss: 0.1968, cls_loss: 0.0744, cls_acc: 0.931, cls_aux_loss: 0.1224, cls_aux_acc: 0.888, seg_loss: 2.9091, cam_loss: 1.0450, reg_loss: -0.2212 ...
Iter: 4000; Elasped: 1:01:14; ETA: 7:08:38; Itertime: 0.91; LR: 5.321e-05;
overall_loss: 0.1969, cls_loss: 0.0726, cls_acc: 0.932, cls_aux_loss: 0.1244, cls_aux_acc: 0.886, seg_loss: 2.8919, cam_loss: 0.9920, reg_loss: -0.2171 ...
Iter: 4200; Elasped: 1:04:17; ETA: 7:05:29; Itertime: 0.91; LR: 5.287e-05;
overall_loss: 0.1880, cls_loss: 0.0700, cls_acc: 0.927, cls_aux_loss: 0.1181, cls_aux_acc: 0.901, seg_loss: 2.9032, cam_loss: 0.9862, reg_loss: -0.2249 ...
Iter: 4400; Elasped: 1:07:20; ETA: 7:02:21; Itertime: 0.92; LR: 5.252e-05;
overall_loss: 0.1948, cls_loss: 0.0751, cls_acc: 0.916, cls_aux_loss: 0.1197, cls_aux_acc: 0.882, seg_loss: 2.9145, cam_loss: 0.9605, reg_loss: -0.2440 ...
Iter: 4600; Elasped: 1:10:24; ETA: 6:59:20; Itertime: 0.92; LR: 5.218e-05;
overall_loss: 0.2043, cls_loss: 0.0801, cls_acc: 0.927, cls_aux_loss: 0.1242, cls_aux_acc: 0.897, seg_loss: 2.8785, cam_loss: 0.9678, reg_loss: -0.2178 ...
Iter: 4800; Elasped: 1:13:27; ETA: 6:56:13; Itertime: 0.92; LR: 5.184e-05;
overall_loss: 0.1766, cls_loss: 0.0666, cls_acc: 0.938, cls_aux_loss: 0.1100, cls_aux_acc: 0.894, seg_loss: 2.9316, cam_loss: 0.9480, reg_loss: -0.2089 ...
Iter: 5000; Elasped: 1:16:30; ETA: 6:53:06; Itertime: 0.92; LR: 5.149e-05;
overall_loss: 0.2024, cls_loss: 0.0815, cls_acc: 0.925, cls_aux_loss: 0.1209, cls_aux_acc: 0.889, seg_loss: 2.9032, cam_loss: 0.9503, reg_loss: -0.2447 ...
Iter: 5200; Elasped: 1:19:33; ETA: 6:49:59; Itertime: 0.91; LR: 5.115e-05;
overall_loss: 0.1941, cls_loss: 0.0762, cls_acc: 0.909, cls_aux_loss: 0.1179, cls_aux_acc: 0.887, seg_loss: 2.9336, cam_loss: 0.9524, reg_loss: -0.2238 ...
Iter: 5400; Elasped: 1:22:36; ETA: 6:46:52; Itertime: 0.92; LR: 5.081e-05;
overall_loss: 0.1757, cls_loss: 0.0724, cls_acc: 0.928, cls_aux_loss: 0.1033, cls_aux_acc: 0.900, seg_loss: 2.9016, cam_loss: 0.9304, reg_loss: -0.2254 ...
Iter: 5600; Elasped: 1:25:40; ETA: 6:43:51; Itertime: 0.92; LR: 5.046e-05;
overall_loss: 0.1735, cls_loss: 0.0702, cls_acc: 0.933, cls_aux_loss: 0.1034, cls_aux_acc: 0.909, seg_loss: 2.9025, cam_loss: 0.9511, reg_loss: -0.2160 ...
Iter: 5800; Elasped: 1:28:42; ETA: 6:40:40; Itertime: 0.91; LR: 5.012e-05;
overall_loss: 0.1480, cls_loss: 0.0609, cls_acc: 0.945, cls_aux_loss: 0.0871, cls_aux_acc: 0.925, seg_loss: 2.8482, cam_loss: 0.9629, reg_loss: -0.2156 ...
Iter: 6000; Elasped: 1:31:46; ETA: 6:37:39; Itertime: 0.92; LR: 4.977e-05;
overall_loss: 0.1948, cls_loss: 0.0810, cls_acc: 0.912, cls_aux_loss: 0.1138, cls_aux_acc: 0.893, seg_loss: 2.8676, cam_loss: 0.9563, reg_loss: -0.2398 ...
Iter: 6200; Elasped: 1:34:49; ETA: 6:34:33; Itertime: 0.92; LR: 4.943e-05;
overall_loss: 0.3591, cls_loss: 0.0836, cls_acc: 0.941, cls_aux_loss: 0.1084, cls_aux_acc: 0.914, seg_loss: 1.7370, cam_loss: 0.9101, reg_loss: -1.0158 ...
Iter: 6400; Elasped: 1:37:52; ETA: 6:31:28; Itertime: 0.92; LR: 4.908e-05;
overall_loss: 0.2486, cls_loss: 0.0666, cls_acc: 0.937, cls_aux_loss: 0.0911, cls_aux_acc: 0.915, seg_loss: 1.1092, cam_loss: 0.8458, reg_loss: -1.2457 ...
Iter: 6600; Elasped: 1:40:56; ETA: 6:28:26; Itertime: 0.92; LR: 4.874e-05;
overall_loss: 0.2394, cls_loss: 0.0703, cls_acc: 0.934, cls_aux_loss: 0.0985, cls_aux_acc: 0.896, seg_loss: 1.0031, cam_loss: 0.8022, reg_loss: -1.3969 ...
Iter: 6800; Elasped: 1:43:58; ETA: 6:25:17; Itertime: 0.91; LR: 4.839e-05;
overall_loss: 0.2472, cls_loss: 0.0737, cls_acc: 0.935, cls_aux_loss: 0.1060, cls_aux_acc: 0.909, seg_loss: 0.9422, cam_loss: 0.7749, reg_loss: -1.3101 ...
Iter: 7000; Elasped: 1:47:01; ETA: 6:22:12; Itertime: 0.91; LR: 4.805e-05;
overall_loss: 0.2329, cls_loss: 0.0727, cls_acc: 0.935, cls_aux_loss: 0.1002, cls_aux_acc: 0.906, seg_loss: 0.9711, cam_loss: 0.7700, reg_loss: -1.5111 ...
Iter: 7200; Elasped: 1:50:04; ETA: 6:19:07; Itertime: 0.92; LR: 4.770e-05;
overall_loss: 0.2096, cls_loss: 0.0743, cls_acc: 0.933, cls_aux_loss: 0.1007, cls_aux_acc: 0.907, seg_loss: 0.9173, cam_loss: 0.7546, reg_loss: -1.8979 ...
Iter: 7400; Elasped: 1:53:08; ETA: 6:16:05; Itertime: 0.92; LR: 4.736e-05;
overall_loss: 0.2127, cls_loss: 0.0742, cls_acc: 0.928, cls_aux_loss: 0.1025, cls_aux_acc: 0.905, seg_loss: 0.8409, cam_loss: 0.7505, reg_loss: -1.7102 ...
Iter: 7600; Elasped: 1:56:11; ETA: 6:13:00; Itertime: 0.92; LR: 4.701e-05;
overall_loss: 0.1676, cls_loss: 0.0646, cls_acc: 0.946, cls_aux_loss: 0.0875, cls_aux_acc: 0.931, seg_loss: 0.6975, cam_loss: 0.7436, reg_loss: -1.8287 ...
Iter: 7800; Elasped: 1:59:14; ETA: 6:09:55; Itertime: 0.92; LR: 4.666e-05;
overall_loss: 0.1515, cls_loss: 0.0716, cls_acc: 0.933, cls_aux_loss: 0.0843, cls_aux_acc: 0.917, seg_loss: 0.7394, cam_loss: 0.7459, reg_loss: -2.3128 ...
Iter: 8000; Elasped: 2:02:17; ETA: 6:06:51; Itertime: 0.92; LR: 4.632e-05;
overall_loss: 0.1469, cls_loss: 0.0625, cls_acc: 0.940, cls_aux_loss: 0.0845, cls_aux_acc: 0.920, seg_loss: 0.6968, cam_loss: 0.7443, reg_loss: -2.1402 ...
Iter: 8200; Elasped: 2:05:21; ETA: 6:03:49; Itertime: 0.92; LR: 4.597e-05;
overall_loss: 0.1075, cls_loss: 0.0569, cls_acc: 0.959, cls_aux_loss: 0.0797, cls_aux_acc: 0.940, seg_loss: 0.5284, cam_loss: 0.7314, reg_loss: -2.3700 ...
Iter: 8400; Elasped: 2:08:24; ETA: 6:00:44; Itertime: 0.92; LR: 4.562e-05;
overall_loss: 0.0954, cls_loss: 0.0523, cls_acc: 0.961, cls_aux_loss: 0.0689, cls_aux_acc: 0.948, seg_loss: 0.5151, cam_loss: 0.7386, reg_loss: -2.2846 ...
Iter: 8600; Elasped: 2:11:27; ETA: 5:57:39; Itertime: 0.92; LR: 4.527e-05;
overall_loss: 0.1082, cls_loss: 0.0624, cls_acc: 0.955, cls_aux_loss: 0.0806, cls_aux_acc: 0.937, seg_loss: 0.5051, cam_loss: 0.7228, reg_loss: -2.4293 ...
Iter: 8800; Elasped: 2:14:30; ETA: 5:54:35; Itertime: 0.92; LR: 4.492e-05;
overall_loss: 0.1006, cls_loss: 0.0583, cls_acc: 0.947, cls_aux_loss: 0.0754, cls_aux_acc: 0.927, seg_loss: 0.4972, cam_loss: 0.7218, reg_loss: -2.3773 ...
Iter: 9000; Elasped: 2:17:34; ETA: 5:51:33; Itertime: 0.92; LR: 4.457e-05;
overall_loss: 0.1009, cls_loss: 0.0638, cls_acc: 0.940, cls_aux_loss: 0.0797, cls_aux_acc: 0.928, seg_loss: 0.4646, cam_loss: 0.7179, reg_loss: -2.4994 ...
Iter: 9200; Elasped: 2:20:37; ETA: 5:48:29; Itertime: 0.92; LR: 4.423e-05;
overall_loss: 0.1059, cls_loss: 0.0628, cls_acc: 0.950, cls_aux_loss: 0.0779, cls_aux_acc: 0.933, seg_loss: 0.4438, cam_loss: 0.7179, reg_loss: -2.3030 ...
Iter: 9400; Elasped: 2:23:40; ETA: 5:45:24; Itertime: 0.92; LR: 4.388e-05;
overall_loss: 0.1014, cls_loss: 0.0545, cls_acc: 0.952, cls_aux_loss: 0.0686, cls_aux_acc: 0.951, seg_loss: 0.3897, cam_loss: 0.7119, reg_loss: -1.9260 ...
Iter: 9600; Elasped: 2:26:44; ETA: 5:42:22; Itertime: 0.92; LR: 4.353e-05;
overall_loss: 0.1253, cls_loss: 0.0655, cls_acc: 0.933, cls_aux_loss: 0.0811, cls_aux_acc: 0.920, seg_loss: 0.4498, cam_loss: 0.7086, reg_loss: -2.0336 ...
Iter: 9800; Elasped: 2:29:47; ETA: 5:39:18; Itertime: 0.92; LR: 4.318e-05;
overall_loss: 0.1426, cls_loss: 0.0677, cls_acc: 0.934, cls_aux_loss: 0.0857, cls_aux_acc: 0.908, seg_loss: 0.4310, cam_loss: 0.7143, reg_loss: -1.7926 ...
Iter: 10000; Elasped: 2:32:50; ETA: 5:36:14; Itertime: 0.92; LR: 4.283e-05;
overall_loss: 0.1170, cls_loss: 0.0610, cls_acc: 0.959, cls_aux_loss: 0.0730, cls_aux_acc: 0.948, seg_loss: 0.3520, cam_loss: 0.7084, reg_loss: -1.7520 ...
Iter: 10200; Elasped: 2:35:53; ETA: 5:33:09; Itertime: 0.92; LR: 4.248e-05;
overall_loss: 0.1409, cls_loss: 0.0652, cls_acc: 0.950, cls_aux_loss: 0.0765, cls_aux_acc: 0.935, seg_loss: 0.3597, cam_loss: 0.7017, reg_loss: -1.4373 ...
Iter: 10400; Elasped: 2:38:57; ETA: 5:30:07; Itertime: 0.92; LR: 4.213e-05;
overall_loss: 0.1394, cls_loss: 0.0618, cls_acc: 0.947, cls_aux_loss: 0.0779, cls_aux_acc: 0.931, seg_loss: 0.3671, cam_loss: 0.7039, reg_loss: -1.4465 ...
Iter: 10600; Elasped: 2:41:59; ETA: 5:27:01; Itertime: 0.91; LR: 4.177e-05;
overall_loss: 0.1589, cls_loss: 0.0656, cls_acc: 0.939, cls_aux_loss: 0.0843, cls_aux_acc: 0.912, seg_loss: 0.4105, cam_loss: 0.7022, reg_loss: -1.3429 ...
Iter: 10800; Elasped: 2:45:03; ETA: 5:23:59; Itertime: 0.92; LR: 4.142e-05;
overall_loss: 0.1499, cls_loss: 0.0651, cls_acc: 0.942, cls_aux_loss: 0.0756, cls_aux_acc: 0.932, seg_loss: 0.3497, cam_loss: 0.7048, reg_loss: -1.2206 ...
Iter: 11000; Elasped: 2:48:06; ETA: 5:20:55; Itertime: 0.92; LR: 4.107e-05;
overall_loss: 0.1319, cls_loss: 0.0562, cls_acc: 0.956, cls_aux_loss: 0.0661, cls_aux_acc: 0.948, seg_loss: 0.2754, cam_loss: 0.7032, reg_loss: -1.0631 ...
Iter: 11200; Elasped: 2:51:09; ETA: 5:17:51; Itertime: 0.92; LR: 4.072e-05;
overall_loss: 0.1104, cls_loss: 0.0474, cls_acc: 0.959, cls_aux_loss: 0.0566, cls_aux_acc: 0.953, seg_loss: 0.2501, cam_loss: 0.7004, reg_loss: -1.0725 ...
Iter: 11400; Elasped: 2:54:12; ETA: 5:14:46; Itertime: 0.92; LR: 4.037e-05;
overall_loss: 0.1353, cls_loss: 0.0560, cls_acc: 0.953, cls_aux_loss: 0.0625, cls_aux_acc: 0.945, seg_loss: 0.3116, cam_loss: 0.7038, reg_loss: -0.9928 ...
Iter: 11600; Elasped: 2:57:16; ETA: 5:11:44; Itertime: 0.92; LR: 4.001e-05;
overall_loss: 0.1414, cls_loss: 0.0566, cls_acc: 0.951, cls_aux_loss: 0.0645, cls_aux_acc: 0.944, seg_loss: 0.3080, cam_loss: 0.7017, reg_loss: -0.9100 ...
Iter: 11800; Elasped: 3:00:19; ETA: 5:08:40; Itertime: 0.91; LR: 3.966e-05;
overall_loss: 0.1564, cls_loss: 0.0608, cls_acc: 0.952, cls_aux_loss: 0.0736, cls_aux_acc: 0.936, seg_loss: 0.3231, cam_loss: 0.6990, reg_loss: -0.9067 ...
Iter: 12000; Elasped: 3:03:22; ETA: 5:05:36; Itertime: 0.91; LR: 3.931e-05;
overall_loss: 0.1385, cls_loss: 0.0539, cls_acc: 0.960, cls_aux_loss: 0.0633, cls_aux_acc: 0.951, seg_loss: 0.2725, cam_loss: 0.7003, reg_loss: -0.8208 ...
Iter: 12200; Elasped: 3:06:25; ETA: 5:02:32; Itertime: 0.92; LR: 3.895e-05;
overall_loss: 0.1723, cls_loss: 0.0670, cls_acc: 0.932, cls_aux_loss: 0.0799, cls_aux_acc: 0.920, seg_loss: 0.3154, cam_loss: 0.6983, reg_loss: -0.8211 ...
Iter: 12400; Elasped: 3:09:28; ETA: 4:59:28; Itertime: 0.92; LR: 3.860e-05;
overall_loss: 0.1348, cls_loss: 0.0488, cls_acc: 0.967, cls_aux_loss: 0.0615, cls_aux_acc: 0.947, seg_loss: 0.2899, cam_loss: 0.7019, reg_loss: -0.7917 ...
Iter: 12600; Elasped: 3:12:32; ETA: 4:56:26; Itertime: 0.92; LR: 3.824e-05;
overall_loss: 0.1341, cls_loss: 0.0518, cls_acc: 0.957, cls_aux_loss: 0.0636, cls_aux_acc: 0.937, seg_loss: 0.2319, cam_loss: 0.6985, reg_loss: -0.7866 ...
Iter: 12800; Elasped: 3:15:35; ETA: 4:53:22; Itertime: 0.92; LR: 3.789e-05;
overall_loss: 0.1415, cls_loss: 0.0539, cls_acc: 0.959, cls_aux_loss: 0.0618, cls_aux_acc: 0.956, seg_loss: 0.2548, cam_loss: 0.6955, reg_loss: -0.6890 ...
Iter: 13000; Elasped: 3:18:38; ETA: 4:50:18; Itertime: 0.92; LR: 3.753e-05;
overall_loss: 0.1701, cls_loss: 0.0647, cls_acc: 0.935, cls_aux_loss: 0.0775, cls_aux_acc: 0.925, seg_loss: 0.2894, cam_loss: 0.6968, reg_loss: -0.7168 ...
Iter: 13200; Elasped: 3:21:41; ETA: 4:47:14; Itertime: 0.92; LR: 3.718e-05;
overall_loss: 0.1507, cls_loss: 0.0542, cls_acc: 0.959, cls_aux_loss: 0.0671, cls_aux_acc: 0.949, seg_loss: 0.2480, cam_loss: 0.6980, reg_loss: -0.6071 ...
Iter: 13400; Elasped: 3:24:44; ETA: 4:44:10; Itertime: 0.92; LR: 3.682e-05;
overall_loss: 0.1315, cls_loss: 0.0494, cls_acc: 0.972, cls_aux_loss: 0.0548, cls_aux_acc: 0.970, seg_loss: 0.2528, cam_loss: 0.6994, reg_loss: -0.6589 ...
Iter: 13600; Elasped: 3:27:48; ETA: 4:41:08; Itertime: 0.92; LR: 3.646e-05;
overall_loss: 0.1221, cls_loss: 0.0448, cls_acc: 0.964, cls_aux_loss: 0.0506, cls_aux_acc: 0.957, seg_loss: 0.2266, cam_loss: 0.6956, reg_loss: -0.6163 ...
Iter: 13800; Elasped: 3:30:51; ETA: 4:38:04; Itertime: 0.92; LR: 3.611e-05;
overall_loss: 0.1279, cls_loss: 0.0499, cls_acc: 0.960, cls_aux_loss: 0.0562, cls_aux_acc: 0.957, seg_loss: 0.1964, cam_loss: 0.6942, reg_loss: -0.6524 ...
Iter: 14000; Elasped: 3:33:54; ETA: 4:35:00; Itertime: 0.92; LR: 3.575e-05;
overall_loss: 0.1358, cls_loss: 0.0515, cls_acc: 0.965, cls_aux_loss: 0.0568, cls_aux_acc: 0.958, seg_loss: 0.2561, cam_loss: 0.6978, reg_loss: -0.6580 ...
Iter: 14200; Elasped: 3:36:58; ETA: 4:31:58; Itertime: 0.92; LR: 3.539e-05;
overall_loss: 0.1384, cls_loss: 0.0504, cls_acc: 0.963, cls_aux_loss: 0.0583, cls_aux_acc: 0.949, seg_loss: 0.2852, cam_loss: 0.6961, reg_loss: -0.6728 ...
Iter: 14400; Elasped: 3:40:01; ETA: 4:28:54; Itertime: 0.92; LR: 3.503e-05;
overall_loss: 0.1403, cls_loss: 0.0528, cls_acc: 0.962, cls_aux_loss: 0.0605, cls_aux_acc: 0.952, seg_loss: 0.2272, cam_loss: 0.6954, reg_loss: -0.6105 ...
Iter: 14600; Elasped: 3:43:04; ETA: 4:25:50; Itertime: 0.91; LR: 3.468e-05;
overall_loss: 0.1475, cls_loss: 0.0525, cls_acc: 0.952, cls_aux_loss: 0.0651, cls_aux_acc: 0.945, seg_loss: 0.2533, cam_loss: 0.6950, reg_loss: -0.6024 ...
Iter: 14800; Elasped: 3:46:07; ETA: 4:22:47; Itertime: 0.91; LR: 3.432e-05;
overall_loss: 0.1532, cls_loss: 0.0552, cls_acc: 0.958, cls_aux_loss: 0.0652, cls_aux_acc: 0.948, seg_loss: 0.2801, cam_loss: 0.6939, reg_loss: -0.5975 ...
Iter: 15000; Elasped: 3:49:10; ETA: 4:19:43; Itertime: 0.92; LR: 3.396e-05;
overall_loss: 0.1376, cls_loss: 0.0517, cls_acc: 0.962, cls_aux_loss: 0.0581, cls_aux_acc: 0.954, seg_loss: 0.2509, cam_loss: 0.6962, reg_loss: -0.6414 ...
Iter: 15200; Elasped: 3:52:13; ETA: 4:16:39; Itertime: 0.92; LR: 3.360e-05;
overall_loss: 0.1154, cls_loss: 0.0417, cls_acc: 0.972, cls_aux_loss: 0.0450, cls_aux_acc: 0.967, seg_loss: 0.2246, cam_loss: 0.6932, reg_loss: -0.5695 ...
Iter: 15400; Elasped: 3:55:16; ETA: 4:13:35; Itertime: 0.91; LR: 3.324e-05;
overall_loss: 0.1289, cls_loss: 0.0476, cls_acc: 0.963, cls_aux_loss: 0.0545, cls_aux_acc: 0.959, seg_loss: 0.2236, cam_loss: 0.6953, reg_loss: -0.6070 ...
Iter: 15600; Elasped: 3:58:20; ETA: 4:10:33; Itertime: 0.92; LR: 3.288e-05;
overall_loss: 0.1379, cls_loss: 0.0466, cls_acc: 0.960, cls_aux_loss: 0.0575, cls_aux_acc: 0.947, seg_loss: 0.2721, cam_loss: 0.6951, reg_loss: -0.5636 ...
Iter: 15800; Elasped: 4:01:23; ETA: 4:07:29; Itertime: 0.92; LR: 3.252e-05;
overall_loss: 0.1600, cls_loss: 0.0605, cls_acc: 0.954, cls_aux_loss: 0.0686, cls_aux_acc: 0.944, seg_loss: 0.2633, cam_loss: 0.6945, reg_loss: -0.6017 ...
Iter: 16000; Elasped: 4:04:26; ETA: 4:04:26; Itertime: 0.91; LR: 3.216e-05;
overall_loss: 0.1197, cls_loss: 0.0442, cls_acc: 0.973, cls_aux_loss: 0.0513, cls_aux_acc: 0.970, seg_loss: 0.1799, cam_loss: 0.6964, reg_loss: -0.5719 ...
model validating...
current_rank 0
store saving with size: 724 at rank: 0
store loaded with size: 1448
teacher: cls:0.9740016333421033, clsaux: 0.9647201567454549
+--------------+--------+---------+--------+--------+
| Class | CAM | aux_CAM | Seg_ps | Seg_vd |
+==============+========+=========+========+========+
| _background_ | 91.410 | 89.420 | 91.620 | 91.810 |
+--------------+--------+---------+--------+--------+
| aeroplane | 83.030 | 78.470 | 80.520 | 83.890 |
+--------------+--------+---------+--------+--------+
| bicycle | 48.080 | 43.270 | 44.840 | 45.640 |
+--------------+--------+---------+--------+--------+
| bird | 85.970 | 70.100 | 86.550 | 86.710 |
+--------------+--------+---------+--------+--------+
| boat | 58.400 | 61.240 | 53.890 | 54.280 |
+--------------+--------+---------+--------+--------+
| bottle | 73.670 | 66.830 | 74.390 | 74.550 |
+--------------+--------+---------+--------+--------+
| bus | 89.060 | 76.190 | 88 | 88.910 |
+--------------+--------+---------+--------+--------+
| car | 83.220 | 70.320 | 83.050 | 83.260 |
+--------------+--------+---------+--------+--------+
| cat | 85.410 | 84.250 | 88.480 | 89.140 |
+--------------+--------+---------+--------+--------+
| chair | 42.240 | 46.930 | 38.150 | 45.810 |
+--------------+--------+---------+--------+--------+
| cow | 86.570 | 81.830 | 86.330 | 89.190 |
+--------------+--------+---------+--------+--------+
| diningtable | 47.760 | 50 | 49.530 | 51.370 |
+--------------+--------+---------+--------+--------+
| dog | 85.520 | 82.460 | 84.300 | 87.150 |
+--------------+--------+---------+--------+--------+
| horse | 86.570 | 73.190 | 85.930 | 86.790 |
+--------------+--------+---------+--------+--------+
| motorbike | 77.530 | 78.540 | 74.740 | 75.270 |
+--------------+--------+---------+--------+--------+
| person | 80.760 | 82.200 | 84.310 | 84.960 |
+--------------+--------+---------+--------+--------+
| pottedplant | 60.750 | 36.540 | 54.690 | 54.960 |
+--------------+--------+---------+--------+--------+
| sheep | 87.020 | 81.700 | 87.700 | 89.170 |
+--------------+--------+---------+--------+--------+
| sofa | 65.830 | 65.220 | 60.240 | 65.090 |
+--------------+--------+---------+--------+--------+
| train | 63.670 | 60.700 | 60.690 | 60.700 |
+--------------+--------+---------+--------+--------+
| tvmonitor | 59.230 | 63.270 | 51.230 | 51.970 |
+--------------+--------+---------+--------+--------+
| mIoU | 73.414 | 68.699 | 71.866 | 73.363 |
+--------------+--------+---------+--------+--------+
Saving checkpoint to /media/hossein-rahmani/Data1/xinyuyang/space/vocseg/HS_H05
Iter: 16200; Elasped: 4:11:41; ETA: 4:05:28; Itertime: 2.17; LR: 3.179e-05;
overall_loss: 0.1065, cls_loss: 0.0394, cls_acc: 0.969, cls_aux_loss: 0.0420, cls_aux_acc: 0.971, seg_loss: 0.1663, cam_loss: 0.6937, reg_loss: -0.5234 ...
Iter: 16400; Elasped: 4:14:43; ETA: 4:02:17; Itertime: 0.91; LR: 3.143e-05;
overall_loss: 0.1147, cls_loss: 0.0413, cls_acc: 0.969, cls_aux_loss: 0.0484, cls_aux_acc: 0.964, seg_loss: 0.1911, cam_loss: 0.6956, reg_loss: -0.5793 ...
Iter: 16600; Elasped: 4:17:45; ETA: 3:59:07; Itertime: 0.91; LR: 3.107e-05;
overall_loss: 0.1048, cls_loss: 0.0387, cls_acc: 0.978, cls_aux_loss: 0.0429, cls_aux_acc: 0.967, seg_loss: 0.1717, cam_loss: 0.6943, reg_loss: -0.5753 ...
Iter: 16800; Elasped: 4:20:47; ETA: 3:55:56; Itertime: 0.91; LR: 3.070e-05;
overall_loss: 0.1248, cls_loss: 0.0456, cls_acc: 0.971, cls_aux_loss: 0.0481, cls_aux_acc: 0.973, seg_loss: 0.2224, cam_loss: 0.6945, reg_loss: -0.5176 ...
Iter: 17000; Elasped: 4:23:49; ETA: 3:52:46; Itertime: 0.91; LR: 3.034e-05;
overall_loss: 0.1560, cls_loss: 0.0548, cls_acc: 0.956, cls_aux_loss: 0.0666, cls_aux_acc: 0.941, seg_loss: 0.2448, cam_loss: 0.6955, reg_loss: -0.4917 ...
Iter: 17200; Elasped: 4:26:52; ETA: 3:49:37; Itertime: 0.91; LR: 2.998e-05;
overall_loss: 0.1309, cls_loss: 0.0458, cls_acc: 0.953, cls_aux_loss: 0.0537, cls_aux_acc: 0.943, seg_loss: 0.2207, cam_loss: 0.6939, reg_loss: -0.5064 ...
Iter: 17400; Elasped: 4:29:54; ETA: 3:46:28; Itertime: 0.91; LR: 2.961e-05;
overall_loss: 0.1185, cls_loss: 0.0431, cls_acc: 0.968, cls_aux_loss: 0.0507, cls_aux_acc: 0.960, seg_loss: 0.2095, cam_loss: 0.6960, reg_loss: -0.6197 ...
Iter: 17600; Elasped: 4:32:57; ETA: 3:43:19; Itertime: 0.91; LR: 2.925e-05;
overall_loss: 0.1494, cls_loss: 0.0551, cls_acc: 0.948, cls_aux_loss: 0.0666, cls_aux_acc: 0.946, seg_loss: 0.2369, cam_loss: 0.6957, reg_loss: -0.6148 ...
Iter: 17800; Elasped: 4:35:59; ETA: 3:40:09; Itertime: 0.91; LR: 2.888e-05;
overall_loss: 0.1336, cls_loss: 0.0492, cls_acc: 0.967, cls_aux_loss: 0.0557, cls_aux_acc: 0.954, seg_loss: 0.2425, cam_loss: 0.6929, reg_loss: -0.6032 ...
Iter: 18000; Elasped: 4:39:01; ETA: 3:37:00; Itertime: 0.91; LR: 2.851e-05;
overall_loss: 0.1172, cls_loss: 0.0428, cls_acc: 0.963, cls_aux_loss: 0.0462, cls_aux_acc: 0.959, seg_loss: 0.2062, cam_loss: 0.6954, reg_loss: -0.5430 ...
Iter: 18200; Elasped: 4:42:03; ETA: 3:33:51; Itertime: 0.91; LR: 2.815e-05;
overall_loss: 0.1226, cls_loss: 0.0428, cls_acc: 0.961, cls_aux_loss: 0.0504, cls_aux_acc: 0.960, seg_loss: 0.2060, cam_loss: 0.6932, reg_loss: -0.5175 ...
Iter: 18400; Elasped: 4:45:05; ETA: 3:30:42; Itertime: 0.91; LR: 2.778e-05;
overall_loss: 0.1022, cls_loss: 0.0379, cls_acc: 0.983, cls_aux_loss: 0.0411, cls_aux_acc: 0.978, seg_loss: 0.1522, cam_loss: 0.6936, reg_loss: -0.5345 ...
Iter: 18600; Elasped: 4:48:08; ETA: 3:27:34; Itertime: 0.91; LR: 2.741e-05;
overall_loss: 0.1091, cls_loss: 0.0382, cls_acc: 0.969, cls_aux_loss: 0.0421, cls_aux_acc: 0.961, seg_loss: 0.1968, cam_loss: 0.6933, reg_loss: -0.5113 ...
Iter: 18800; Elasped: 4:51:10; ETA: 3:24:26; Itertime: 0.91; LR: 2.704e-05;
overall_loss: 0.1033, cls_loss: 0.0378, cls_acc: 0.982, cls_aux_loss: 0.0386, cls_aux_acc: 0.979, seg_loss: 0.1664, cam_loss: 0.6952, reg_loss: -0.4886 ...
Iter: 19000; Elasped: 4:54:12; ETA: 3:21:17; Itertime: 0.91; LR: 2.667e-05;
overall_loss: 0.1004, cls_loss: 0.0343, cls_acc: 0.981, cls_aux_loss: 0.0381, cls_aux_acc: 0.973, seg_loss: 0.1596, cam_loss: 0.6945, reg_loss: -0.4519 ...
Iter: 19200; Elasped: 4:57:14; ETA: 3:18:09; Itertime: 0.91; LR: 2.630e-05;
overall_loss: 0.1215, cls_loss: 0.0451, cls_acc: 0.972, cls_aux_loss: 0.0496, cls_aux_acc: 0.966, seg_loss: 0.2023, cam_loss: 0.6931, reg_loss: -0.5625 ...
Iter: 19400; Elasped: 5:00:16; ETA: 3:15:01; Itertime: 0.91; LR: 2.593e-05;
overall_loss: 0.1236, cls_loss: 0.0444, cls_acc: 0.968, cls_aux_loss: 0.0474, cls_aux_acc: 0.965, seg_loss: 0.2224, cam_loss: 0.6937, reg_loss: -0.5016 ...
Iter: 19600; Elasped: 5:03:18; ETA: 3:11:53; Itertime: 0.91; LR: 2.556e-05;
overall_loss: 0.1121, cls_loss: 0.0417, cls_acc: 0.965, cls_aux_loss: 0.0441, cls_aux_acc: 0.962, seg_loss: 0.1627, cam_loss: 0.6942, reg_loss: -0.4933 ...
Iter: 19800; Elasped: 5:06:21; ETA: 3:08:45; Itertime: 0.91; LR: 2.519e-05;
overall_loss: 0.1109, cls_loss: 0.0411, cls_acc: 0.974, cls_aux_loss: 0.0445, cls_aux_acc: 0.973, seg_loss: 0.1731, cam_loss: 0.6946, reg_loss: -0.5348 ...
Iter: 20000; Elasped: 5:09:23; ETA: 3:05:37; Itertime: 0.91; LR: 2.482e-05;
overall_loss: 0.1068, cls_loss: 0.0371, cls_acc: 0.967, cls_aux_loss: 0.0419, cls_aux_acc: 0.965, seg_loss: 0.1671, cam_loss: 0.6941, reg_loss: -0.4720 ...
model validating...
current_rank 0
store saving with size: 724 at rank: 0
store loaded with size: 1448
teacher: cls:0.9743474853108834, clsaux: 0.9672452597885135
+--------------+--------+---------+--------+--------+
| Class | CAM | aux_CAM | Seg_ps | Seg_vd |
+==============+========+=========+========+========+
| _background_ | 91.650 | 89.730 | 92.500 | 92.690 |
+--------------+--------+---------+--------+--------+
| aeroplane | 85.230 | 80.650 | 82.460 | 85.830 |
+--------------+--------+---------+--------+--------+
| bicycle | 48.310 | 44.530 | 45.820 | 46.870 |
+--------------+--------+---------+--------+--------+
| bird | 87.980 | 77.490 | 88.480 | 88.490 |
+--------------+--------+---------+--------+--------+
| boat | 68.550 | 58.790 | 64.040 | 66.110 |
+--------------+--------+---------+--------+--------+
| bottle | 72.590 | 64.570 | 74.820 | 75.240 |
+--------------+--------+---------+--------+--------+
| bus | 89.140 | 74.600 | 88.950 | 90.050 |
+--------------+--------+---------+--------+--------+
| car | 82.930 | 72.430 | 84.210 | 84.720 |
+--------------+--------+---------+--------+--------+
| cat | 84.040 | 82.970 | 89.190 | 89.810 |
+--------------+--------+---------+--------+--------+
| chair | 40.350 | 45.360 | 37.870 | 48.430 |
+--------------+--------+---------+--------+--------+
| cow | 86.670 | 82.540 | 88.280 | 89.740 |
+--------------+--------+---------+--------+--------+
| diningtable | 47.820 | 52.260 | 51.870 | 54.120 |
+--------------+--------+---------+--------+--------+
| dog | 84.350 | 81.410 | 85.690 | 87.640 |
+--------------+--------+---------+--------+--------+
| horse | 85.230 | 75.870 | 85.570 | 87.670 |
+--------------+--------+---------+--------+--------+
| motorbike | 77.960 | 78.070 | 75.900 | 76.430 |
+--------------+--------+---------+--------+--------+
| person | 77.960 | 82.580 | 85.140 | 85.440 |
+--------------+--------+---------+--------+--------+
| pottedplant | 57.590 | 34.150 | 53.830 | 54.120 |
+--------------+--------+---------+--------+--------+
| sheep | 88.740 | 84.570 | 89.880 | 89.880 |
+--------------+--------+---------+--------+--------+
| sofa | 62.360 | 64.760 | 59.180 | 66.440 |
+--------------+--------+---------+--------+--------+
| train | 67.170 | 59.860 | 63.510 | 63.530 |
+--------------+--------+---------+--------+--------+
| tvmonitor | 66.510 | 60.660 | 60.260 | 61.410 |
+--------------+--------+---------+--------+--------+
| mIoU | 73.959 | 68.945 | 73.688 | 75.460 |
+--------------+--------+---------+--------+--------+
Saving checkpoint to /media/hossein-rahmani/Data1/xinyuyang/space/vocseg/HS_H05
Iter: 20200; Elasped: 5:16:37; ETA: 3:04:57; Itertime: 2.17; LR: 2.445e-05;
overall_loss: 0.1339, cls_loss: 0.0484, cls_acc: 0.950, cls_aux_loss: 0.0527, cls_aux_acc: 0.949, seg_loss: 0.2439, cam_loss: 0.6926, reg_loss: -0.5223 ...
Iter: 20400; Elasped: 5:19:39; ETA: 3:01:45; Itertime: 0.91; LR: 2.407e-05;
overall_loss: 0.1096, cls_loss: 0.0396, cls_acc: 0.971, cls_aux_loss: 0.0451, cls_aux_acc: 0.964, seg_loss: 0.1613, cam_loss: 0.6929, reg_loss: -0.5188 ...
Iter: 20600; Elasped: 5:22:42; ETA: 2:58:34; Itertime: 0.91; LR: 2.370e-05;
overall_loss: 0.1148, cls_loss: 0.0418, cls_acc: 0.972, cls_aux_loss: 0.0460, cls_aux_acc: 0.967, seg_loss: 0.1770, cam_loss: 0.6923, reg_loss: -0.5050 ...
Iter: 20800; Elasped: 5:25:44; ETA: 2:55:23; Itertime: 0.91; LR: 2.333e-05;
overall_loss: 0.1044, cls_loss: 0.0391, cls_acc: 0.964, cls_aux_loss: 0.0394, cls_aux_acc: 0.972, seg_loss: 0.1727, cam_loss: 0.6934, reg_loss: -0.5202 ...
Iter: 21000; Elasped: 5:28:46; ETA: 2:52:12; Itertime: 0.91; LR: 2.295e-05;
overall_loss: 0.1180, cls_loss: 0.0426, cls_acc: 0.971, cls_aux_loss: 0.0480, cls_aux_acc: 0.964, seg_loss: 0.1947, cam_loss: 0.6937, reg_loss: -0.5353 ...
Iter: 21200; Elasped: 5:31:48; ETA: 2:49:01; Itertime: 0.91; LR: 2.258e-05;
overall_loss: 0.1048, cls_loss: 0.0373, cls_acc: 0.984, cls_aux_loss: 0.0398, cls_aux_acc: 0.978, seg_loss: 0.1980, cam_loss: 0.6926, reg_loss: -0.5341 ...
Iter: 21400; Elasped: 5:34:50; ETA: 2:45:51; Itertime: 0.91; LR: 2.220e-05;
overall_loss: 0.1074, cls_loss: 0.0387, cls_acc: 0.980, cls_aux_loss: 0.0387, cls_aux_acc: 0.981, seg_loss: 0.2054, cam_loss: 0.6933, reg_loss: -0.5042 ...
Iter: 21600; Elasped: 5:37:52; ETA: 2:42:40; Itertime: 0.91; LR: 2.182e-05;
overall_loss: 0.0952, cls_loss: 0.0326, cls_acc: 0.979, cls_aux_loss: 0.0370, cls_aux_acc: 0.976, seg_loss: 0.1668, cam_loss: 0.6926, reg_loss: -0.5155 ...
Iter: 21800; Elasped: 5:40:55; ETA: 2:39:30; Itertime: 0.91; LR: 2.144e-05;
overall_loss: 0.1001, cls_loss: 0.0388, cls_acc: 0.971, cls_aux_loss: 0.0408, cls_aux_acc: 0.968, seg_loss: 0.1710, cam_loss: 0.6912, reg_loss: -0.6240 ...
Iter: 22000; Elasped: 5:43:57; ETA: 2:36:20; Itertime: 0.91; LR: 2.106e-05;
overall_loss: 0.0884, cls_loss: 0.0322, cls_acc: 0.979, cls_aux_loss: 0.0327, cls_aux_acc: 0.977, seg_loss: 0.1738, cam_loss: 0.6938, reg_loss: -0.5710 ...
Iter: 22200; Elasped: 5:47:00; ETA: 2:33:10; Itertime: 0.91; LR: 2.069e-05;
overall_loss: 0.1020, cls_loss: 0.0377, cls_acc: 0.971, cls_aux_loss: 0.0384, cls_aux_acc: 0.970, seg_loss: 0.1697, cam_loss: 0.6930, reg_loss: -0.5164 ...
Iter: 22400; Elasped: 5:50:02; ETA: 2:30:00; Itertime: 0.91; LR: 2.030e-05;
overall_loss: 0.1210, cls_loss: 0.0444, cls_acc: 0.975, cls_aux_loss: 0.0492, cls_aux_acc: 0.968, seg_loss: 0.2042, cam_loss: 0.6942, reg_loss: -0.5541 ...
Iter: 22600; Elasped: 5:53:04; ETA: 2:26:51; Itertime: 0.91; LR: 1.992e-05;
overall_loss: 0.1042, cls_loss: 0.0364, cls_acc: 0.975, cls_aux_loss: 0.0414, cls_aux_acc: 0.972, seg_loss: 0.1839, cam_loss: 0.6925, reg_loss: -0.5323 ...
Iter: 22800; Elasped: 5:56:06; ETA: 2:23:41; Itertime: 0.91; LR: 1.954e-05;
overall_loss: 0.0850, cls_loss: 0.0310, cls_acc: 0.973, cls_aux_loss: 0.0305, cls_aux_acc: 0.976, seg_loss: 0.1357, cam_loss: 0.6921, reg_loss: -0.4938 ...
Iter: 23000; Elasped: 5:59:09; ETA: 2:20:32; Itertime: 0.91; LR: 1.916e-05;
overall_loss: 0.0986, cls_loss: 0.0362, cls_acc: 0.981, cls_aux_loss: 0.0389, cls_aux_acc: 0.974, seg_loss: 0.1716, cam_loss: 0.6929, reg_loss: -0.5663 ...
Iter: 23200; Elasped: 6:02:11; ETA: 2:17:22; Itertime: 0.91; LR: 1.878e-05;
overall_loss: 0.1051, cls_loss: 0.0374, cls_acc: 0.981, cls_aux_loss: 0.0425, cls_aux_acc: 0.973, seg_loss: 0.1702, cam_loss: 0.6940, reg_loss: -0.5313 ...
Iter: 23400; Elasped: 6:05:13; ETA: 2:14:13; Itertime: 0.91; LR: 1.839e-05;
overall_loss: 0.1028, cls_loss: 0.0366, cls_acc: 0.976, cls_aux_loss: 0.0409, cls_aux_acc: 0.975, seg_loss: 0.1641, cam_loss: 0.6922, reg_loss: -0.5157 ...
Iter: 23600; Elasped: 6:08:15; ETA: 2:11:04; Itertime: 0.91; LR: 1.801e-05;
overall_loss: 0.1038, cls_loss: 0.0360, cls_acc: 0.980, cls_aux_loss: 0.0382, cls_aux_acc: 0.973, seg_loss: 0.1911, cam_loss: 0.6936, reg_loss: -0.4848 ...
Iter: 23800; Elasped: 6:11:17; ETA: 2:07:55; Itertime: 0.91; LR: 1.762e-05;
overall_loss: 0.0902, cls_loss: 0.0326, cls_acc: 0.980, cls_aux_loss: 0.0331, cls_aux_acc: 0.980, seg_loss: 0.1554, cam_loss: 0.6925, reg_loss: -0.5139 ...
Iter: 24000; Elasped: 6:14:19; ETA: 2:04:46; Itertime: 0.91; LR: 1.723e-05;
overall_loss: 0.0887, cls_loss: 0.0319, cls_acc: 0.982, cls_aux_loss: 0.0325, cls_aux_acc: 0.982, seg_loss: 0.1380, cam_loss: 0.6912, reg_loss: -0.4796 ...
model validating...
current_rank 0
store saving with size: 724 at rank: 0
store loaded with size: 1448
teacher: cls:0.9735121788125938, clsaux: 0.9637797642650074
+--------------+--------+---------+--------+--------+---------+
| Class | CAM | aux_CAM | Seg_ps | Seg_vd | Seg_crf |
+==============+========+=========+========+========+=========+
| _background_ | 91.190 | 89.640 | 92.670 | 92.850 | 92.950 |
+--------------+--------+---------+--------+--------+---------+
| aeroplane | 82.240 | 81.190 | 83.870 | 85.020 | 85.490 |
+--------------+--------+---------+--------+--------+---------+
| bicycle | 47.930 | 46.520 | 47.210 | 48.110 | 48.590 |
+--------------+--------+---------+--------+--------+---------+
| bird | 86.630 | 67.970 | 88.050 | 88.100 | 88.610 |
+--------------+--------+---------+--------+--------+---------+
| boat | 69.970 | 58.240 | 67.020 | 69.540 | 69.950 |
+--------------+--------+---------+--------+--------+---------+
| bottle | 72.580 | 64.470 | 75.290 | 76.190 | 76.540 |
+--------------+--------+---------+--------+--------+---------+
| bus | 88.460 | 75.460 | 89.460 | 90.270 | 90.360 |
+--------------+--------+---------+--------+--------+---------+
| car | 82.440 | 72.450 | 85.280 | 85.860 | 86.010 |
+--------------+--------+---------+--------+--------+---------+
| cat | 82.310 | 83.630 | 89.330 | 89.740 | 90.050 |
+--------------+--------+---------+--------+--------+---------+
| chair | 32.960 | 45.860 | 32.740 | 46.390 | 46.340 |
+--------------+--------+---------+--------+--------+---------+
| cow | 83.480 | 76.070 | 85.100 | 87.780 | 88.130 |
+--------------+--------+---------+--------+--------+---------+
| diningtable | 43.290 | 51.030 | 49.900 | 52.100 | 52.130 |
+--------------+--------+---------+--------+--------+---------+
| dog | 82.840 | 82.660 | 84.470 | 86.880 | 87.130 |
+--------------+--------+---------+--------+--------+---------+
| horse | 82.960 | 75.630 | 85.810 | 86.800 | 87.130 |
+--------------+--------+---------+--------+--------+---------+
| motorbike | 78.370 | 77.340 | 78.520 | 78.920 | 78.940 |
+--------------+--------+---------+--------+--------+---------+
| person | 74.020 | 81.740 | 84.660 | 84.910 | 85.170 |
+--------------+--------+---------+--------+--------+---------+
| pottedplant | 53.580 | 33.270 | 52.580 | 52.850 | 52.950 |
+--------------+--------+---------+--------+--------+---------+
| sheep | 86.690 | 84.030 | 89.120 | 89.300 | 89.760 |
+--------------+--------+---------+--------+--------+---------+
| sofa | 64.830 | 68.490 | 60.340 | 70.700 | 71.030 |
+--------------+--------+---------+--------+--------+---------+
| train | 67.130 | 58.990 | 64.870 | 64.870 | 65.060 |
+--------------+--------+---------+--------+--------+---------+
| tvmonitor | 69.080 | 63.370 | 61.340 | 63.020 | 63.130 |
+--------------+--------+---------+--------+--------+---------+
| mIoU | 72.523 | 68.479 | 73.697 | 75.724 | 75.974 |
+--------------+--------+---------+--------+--------+---------+
Saving checkpoint to /media/hossein-rahmani/Data1/xinyuyang/space/vocseg/HS_H05
Iter: 24200; Elasped: 6:25:11; ETA: 2:04:09; Itertime: 3.26; LR: 1.684e-05;
overall_loss: 0.0906, cls_loss: 0.0311, cls_acc: 0.984, cls_aux_loss: 0.0304, cls_aux_acc: 0.984, seg_loss: 0.1551, cam_loss: 0.6928, reg_loss: -0.4211 ...
Iter: 24400; Elasped: 6:28:13; ETA: 2:00:55; Itertime: 0.91; LR: 1.646e-05;
overall_loss: 0.0861, cls_loss: 0.0299, cls_acc: 0.976, cls_aux_loss: 0.0301, cls_aux_acc: 0.975, seg_loss: 0.1613, cam_loss: 0.6910, reg_loss: -0.4898 ...
Iter: 24600; Elasped: 6:31:15; ETA: 1:57:41; Itertime: 0.91; LR: 1.606e-05;
overall_loss: 0.0833, cls_loss: 0.0305, cls_acc: 0.980, cls_aux_loss: 0.0300, cls_aux_acc: 0.981, seg_loss: 0.1362, cam_loss: 0.6912, reg_loss: -0.5077 ...
Iter: 24800; Elasped: 6:34:18; ETA: 1:54:28; Itertime: 0.91; LR: 1.567e-05;
overall_loss: 0.0879, cls_loss: 0.0344, cls_acc: 0.978, cls_aux_loss: 0.0330, cls_aux_acc: 0.974, seg_loss: 0.1639, cam_loss: 0.6913, reg_loss: -0.6095 ...
Iter: 25000; Elasped: 6:37:20; ETA: 1:51:15; Itertime: 0.91; LR: 1.528e-05;
overall_loss: 0.0874, cls_loss: 0.0330, cls_acc: 0.986, cls_aux_loss: 0.0303, cls_aux_acc: 0.986, seg_loss: 0.1387, cam_loss: 0.6907, reg_loss: -0.4853 ...
Iter: 25200; Elasped: 6:40:22; ETA: 1:48:02; Itertime: 0.91; LR: 1.489e-05;
overall_loss: 0.0850, cls_loss: 0.0309, cls_acc: 0.981, cls_aux_loss: 0.0323, cls_aux_acc: 0.978, seg_loss: 0.1463, cam_loss: 0.6916, reg_loss: -0.5468 ...
Iter: 25400; Elasped: 6:43:24; ETA: 1:44:49; Itertime: 0.91; LR: 1.449e-05;
overall_loss: 0.0684, cls_loss: 0.0234, cls_acc: 0.989, cls_aux_loss: 0.0231, cls_aux_acc: 0.990, seg_loss: 0.1180, cam_loss: 0.6906, reg_loss: -0.4868 ...
Iter: 25600; Elasped: 6:46:27; ETA: 1:41:36; Itertime: 0.91; LR: 1.410e-05;
overall_loss: 0.0897, cls_loss: 0.0333, cls_acc: 0.980, cls_aux_loss: 0.0344, cls_aux_acc: 0.977, seg_loss: 0.1522, cam_loss: 0.6924, reg_loss: -0.5556 ...
Iter: 25800; Elasped: 6:49:29; ETA: 1:38:24; Itertime: 0.91; LR: 1.370e-05;
overall_loss: 0.0834, cls_loss: 0.0303, cls_acc: 0.986, cls_aux_loss: 0.0308, cls_aux_acc: 0.982, seg_loss: 0.1390, cam_loss: 0.6928, reg_loss: -0.5245 ...
Iter: 26000; Elasped: 6:52:31; ETA: 1:35:11; Itertime: 0.91; LR: 1.330e-05;
overall_loss: 0.0851, cls_loss: 0.0314, cls_acc: 0.979, cls_aux_loss: 0.0328, cls_aux_acc: 0.979, seg_loss: 0.1499, cam_loss: 0.6924, reg_loss: -0.5741 ...
Iter: 26200; Elasped: 6:55:33; ETA: 1:31:59; Itertime: 0.91; LR: 1.290e-05;
overall_loss: 0.0902, cls_loss: 0.0310, cls_acc: 0.983, cls_aux_loss: 0.0339, cls_aux_acc: 0.982, seg_loss: 0.1561, cam_loss: 0.6929, reg_loss: -0.4981 ...
Iter: 26400; Elasped: 6:58:36; ETA: 1:28:47; Itertime: 0.91; LR: 1.250e-05;
overall_loss: 0.0932, cls_loss: 0.0327, cls_acc: 0.973, cls_aux_loss: 0.0343, cls_aux_acc: 0.968, seg_loss: 0.1578, cam_loss: 0.6920, reg_loss: -0.4848 ...
Iter: 26600; Elasped: 7:01:38; ETA: 1:25:35; Itertime: 0.91; LR: 1.210e-05;
overall_loss: 0.0959, cls_loss: 0.0334, cls_acc: 0.970, cls_aux_loss: 0.0351, cls_aux_acc: 0.974, seg_loss: 0.1592, cam_loss: 0.6914, reg_loss: -0.4620 ...
Iter: 26800; Elasped: 7:04:40; ETA: 1:22:23; Itertime: 0.91; LR: 1.169e-05;
overall_loss: 0.0795, cls_loss: 0.0269, cls_acc: 0.987, cls_aux_loss: 0.0269, cls_aux_acc: 0.988, seg_loss: 0.1406, cam_loss: 0.6922, reg_loss: -0.4617 ...
Iter: 27000; Elasped: 7:07:42; ETA: 1:19:12; Itertime: 0.91; LR: 1.129e-05;
overall_loss: 0.0781, cls_loss: 0.0278, cls_acc: 0.987, cls_aux_loss: 0.0256, cls_aux_acc: 0.989, seg_loss: 0.1666, cam_loss: 0.6934, reg_loss: -0.5336 ...
Iter: 27200; Elasped: 7:10:45; ETA: 1:16:00; Itertime: 0.91; LR: 1.088e-05;
overall_loss: 0.0778, cls_loss: 0.0289, cls_acc: 0.979, cls_aux_loss: 0.0279, cls_aux_acc: 0.979, seg_loss: 0.1087, cam_loss: 0.6909, reg_loss: -0.4870 ...
Iter: 27400; Elasped: 7:13:47; ETA: 1:12:49; Itertime: 0.91; LR: 1.047e-05;
overall_loss: 0.0709, cls_loss: 0.0251, cls_acc: 0.987, cls_aux_loss: 0.0234, cls_aux_acc: 0.992, seg_loss: 0.1434, cam_loss: 0.6914, reg_loss: -0.5298 ...
Iter: 27600; Elasped: 7:16:49; ETA: 1:09:38; Itertime: 0.91; LR: 1.006e-05;
overall_loss: 0.0852, cls_loss: 0.0287, cls_acc: 0.982, cls_aux_loss: 0.0299, cls_aux_acc: 0.982, seg_loss: 0.1518, cam_loss: 0.6918, reg_loss: -0.4636 ...
Iter: 27800; Elasped: 7:19:51; ETA: 1:06:27; Itertime: 0.91; LR: 9.650e-06;
overall_loss: 0.0693, cls_loss: 0.0243, cls_acc: 0.991, cls_aux_loss: 0.0237, cls_aux_acc: 0.989, seg_loss: 0.1344, cam_loss: 0.6914, reg_loss: -0.5354 ...
Iter: 28000; Elasped: 7:22:53; ETA: 1:03:16; Itertime: 0.91; LR: 9.236e-06;
overall_loss: 0.0850, cls_loss: 0.0287, cls_acc: 0.984, cls_aux_loss: 0.0303, cls_aux_acc: 0.976, seg_loss: 0.1583, cam_loss: 0.6923, reg_loss: -0.4888 ...
model validating...
current_rank 0
store saving with size: 724 at rank: 0
store loaded with size: 1448
teacher: cls:0.9716387683065865, clsaux: 0.9661113376946469
+--------------+--------+---------+--------+--------+---------+
| Class | CAM | aux_CAM | Seg_ps | Seg_vd | Seg_crf |
+==============+========+=========+========+========+=========+
| _background_ | 90.720 | 89.410 | 92.480 | 92.690 | 92.780 |
+--------------+--------+---------+--------+--------+---------+
| aeroplane | 79.030 | 82.170 | 81.680 | 84.210 | 84.630 |
+--------------+--------+---------+--------+--------+---------+
| bicycle | 46.670 | 44.570 | 47.640 | 48.130 | 48.610 |
+--------------+--------+---------+--------+--------+---------+
| bird | 86.510 | 70.770 | 87.360 | 87.380 | 87.830 |
+--------------+--------+---------+--------+--------+---------+
| boat | 70.730 | 58.910 | 68.950 | 71.640 | 72.080 |
+--------------+--------+---------+--------+--------+---------+
| bottle | 72.240 | 62.710 | 74.610 | 75.580 | 76.030 |
+--------------+--------+---------+--------+--------+---------+
| bus | 87.210 | 77.080 | 89.290 | 90.310 | 90.370 |
+--------------+--------+---------+--------+--------+---------+
| car | 80.640 | 71.800 | 84.990 | 85.410 | 85.600 |
+--------------+--------+---------+--------+--------+---------+
| cat | 79.690 | 82.860 | 88.520 | 88.720 | 89.040 |
+--------------+--------+---------+--------+--------+---------+
| chair | 32.550 | 45.780 | 36.160 | 47.860 | 47.950 |
+--------------+--------+---------+--------+--------+---------+
| cow | 81.370 | 74.430 | 87.380 | 88.060 | 88.410 |
+--------------+--------+---------+--------+--------+---------+
| diningtable | 42.980 | 51.740 | 48.840 | 50.670 | 50.760 |
+--------------+--------+---------+--------+--------+---------+
| dog | 79.780 | 74.160 | 84.390 | 85.240 | 85.520 |
+--------------+--------+---------+--------+--------+---------+
| horse | 82.440 | 74.160 | 83.540 | 85.680 | 85.920 |
+--------------+--------+---------+--------+--------+---------+
| motorbike | 78.250 | 77.070 | 79.650 | 79.760 | 79.920 |
+--------------+--------+---------+--------+--------+---------+
| person | 72.130 | 80.110 | 84.040 | 84.110 | 84.340 |
+--------------+--------+---------+--------+--------+---------+
| pottedplant | 49.740 | 32.610 | 51.400 | 51.960 | 52.010 |
+--------------+--------+---------+--------+--------+---------+
| sheep | 85.870 | 85.360 | 88.670 | 88.700 | 89.090 |
+--------------+--------+---------+--------+--------+---------+
| sofa | 59.170 | 70.160 | 57.620 | 67.950 | 68.040 |
+--------------+--------+---------+--------+--------+---------+
| train | 66.790 | 58.180 | 64.580 | 64.580 | 64.730 |
+--------------+--------+---------+--------+--------+---------+
| tvmonitor | 70.580 | 61.570 | 65.810 | 67.190 | 67.260 |
+--------------+--------+---------+--------+--------+---------+
| mIoU | 71.195 | 67.886 | 73.695 | 75.516 | 75.758 |
+--------------+--------+---------+--------+--------+---------+
Iter: 28200; Elasped: 7:33:39; ETA: 1:01:07; Itertime: 3.23; LR: 8.819e-06;
overall_loss: 0.0803, cls_loss: 0.0271, cls_acc: 0.981, cls_aux_loss: 0.0255, cls_aux_acc: 0.980, seg_loss: 0.1491, cam_loss: 0.6913, reg_loss: -0.4365 ...
Iter: 28400; Elasped: 7:36:41; ETA: 0:57:53; Itertime: 0.91; LR: 8.400e-06;
overall_loss: 0.0750, cls_loss: 0.0262, cls_acc: 0.980, cls_aux_loss: 0.0261, cls_aux_acc: 0.975, seg_loss: 0.1318, cam_loss: 0.6917, reg_loss: -0.5008 ...
Iter: 28600; Elasped: 7:39:44; ETA: 0:54:39; Itertime: 0.91; LR: 7.979e-06;
overall_loss: 0.0632, cls_loss: 0.0205, cls_acc: 0.990, cls_aux_loss: 0.0214, cls_aux_acc: 0.986, seg_loss: 0.1164, cam_loss: 0.6909, reg_loss: -0.4978 ...
Iter: 28800; Elasped: 7:42:46; ETA: 0:51:25; Itertime: 0.91; LR: 7.556e-06;
overall_loss: 0.0709, cls_loss: 0.0249, cls_acc: 0.991, cls_aux_loss: 0.0238, cls_aux_acc: 0.987, seg_loss: 0.1281, cam_loss: 0.6927, reg_loss: -0.5046 ...
Iter: 29000; Elasped: 7:45:48; ETA: 0:48:11; Itertime: 0.91; LR: 7.129e-06;
overall_loss: 0.0910, cls_loss: 0.0317, cls_acc: 0.974, cls_aux_loss: 0.0324, cls_aux_acc: 0.981, seg_loss: 0.1500, cam_loss: 0.6926, reg_loss: -0.4534 ...
Iter: 29200; Elasped: 7:48:50; ETA: 0:44:57; Itertime: 0.91; LR: 6.700e-06;
overall_loss: 0.0731, cls_loss: 0.0270, cls_acc: 0.984, cls_aux_loss: 0.0250, cls_aux_acc: 0.989, seg_loss: 0.1371, cam_loss: 0.6916, reg_loss: -0.5454 ...
Iter: 29400; Elasped: 7:51:52; ETA: 0:41:43; Itertime: 0.91; LR: 6.268e-06;
overall_loss: 0.0657, cls_loss: 0.0222, cls_acc: 0.988, cls_aux_loss: 0.0201, cls_aux_acc: 0.991, seg_loss: 0.1175, cam_loss: 0.6918, reg_loss: -0.4582 ...
Iter: 29600; Elasped: 7:54:54; ETA: 0:38:30; Itertime: 0.91; LR: 5.833e-06;
overall_loss: 0.0730, cls_loss: 0.0262, cls_acc: 0.981, cls_aux_loss: 0.0249, cls_aux_acc: 0.981, seg_loss: 0.1221, cam_loss: 0.6914, reg_loss: -0.4954 ...
Iter: 29800; Elasped: 7:57:57; ETA: 0:35:17; Itertime: 0.91; LR: 5.394e-06;
overall_loss: 0.0623, cls_loss: 0.0207, cls_acc: 0.990, cls_aux_loss: 0.0191, cls_aux_acc: 0.991, seg_loss: 0.1445, cam_loss: 0.6928, reg_loss: -0.5324 ...
Iter: 30000; Elasped: 8:00:59; ETA: 0:32:03; Itertime: 0.91; LR: 4.950e-06;
overall_loss: 0.0657, cls_loss: 0.0229, cls_acc: 0.990, cls_aux_loss: 0.0212, cls_aux_acc: 0.990, seg_loss: 0.1022, cam_loss: 0.6925, reg_loss: -0.4641 ...
Iter: 30200; Elasped: 8:04:01; ETA: 0:28:50; Itertime: 0.91; LR: 4.503e-06;
overall_loss: 0.0740, cls_loss: 0.0248, cls_acc: 0.985, cls_aux_loss: 0.0244, cls_aux_acc: 0.983, seg_loss: 0.1296, cam_loss: 0.6922, reg_loss: -0.4547 ...
Iter: 30400; Elasped: 8:07:03; ETA: 0:25:38; Itertime: 0.91; LR: 4.050e-06;
overall_loss: 0.0728, cls_loss: 0.0262, cls_acc: 0.988, cls_aux_loss: 0.0244, cls_aux_acc: 0.987, seg_loss: 0.1398, cam_loss: 0.6918, reg_loss: -0.5247 ...
Iter: 30600; Elasped: 8:10:06; ETA: 0:22:25; Itertime: 0.91; LR: 3.592e-06;
overall_loss: 0.0652, cls_loss: 0.0222, cls_acc: 0.990, cls_aux_loss: 0.0211, cls_aux_acc: 0.990, seg_loss: 0.1190, cam_loss: 0.6916, reg_loss: -0.4921 ...
Iter: 30800; Elasped: 8:13:08; ETA: 0:19:12; Itertime: 0.91; LR: 3.127e-06;
overall_loss: 0.0690, cls_loss: 0.0218, cls_acc: 0.988, cls_aux_loss: 0.0241, cls_aux_acc: 0.988, seg_loss: 0.1349, cam_loss: 0.6922, reg_loss: -0.5004 ...
Iter: 31000; Elasped: 8:16:10; ETA: 0:16:00; Itertime: 0.91; LR: 2.654e-06;
overall_loss: 0.0721, cls_loss: 0.0252, cls_acc: 0.984, cls_aux_loss: 0.0246, cls_aux_acc: 0.985, seg_loss: 0.1419, cam_loss: 0.6921, reg_loss: -0.5311 ...
Iter: 31200; Elasped: 8:19:12; ETA: 0:12:48; Itertime: 0.91; LR: 2.172e-06;
overall_loss: 0.0745, cls_loss: 0.0234, cls_acc: 0.992, cls_aux_loss: 0.0231, cls_aux_acc: 0.989, seg_loss: 0.1557, cam_loss: 0.6921, reg_loss: -0.4429 ...
Iter: 31400; Elasped: 8:22:15; ETA: 0:09:35; Itertime: 0.91; LR: 1.677e-06;
overall_loss: 0.0698, cls_loss: 0.0250, cls_acc: 0.990, cls_aux_loss: 0.0234, cls_aux_acc: 0.990, seg_loss: 0.1084, cam_loss: 0.6919, reg_loss: -0.4801 ...
Iter: 31600; Elasped: 8:25:17; ETA: 0:06:23; Itertime: 0.91; LR: 1.165e-06;
overall_loss: 0.0613, cls_loss: 0.0228, cls_acc: 0.989, cls_aux_loss: 0.0202, cls_aux_acc: 0.990, seg_loss: 0.1313, cam_loss: 0.6924, reg_loss: -0.5877 ...
Iter: 31800; Elasped: 8:28:19; ETA: 0:03:11; Itertime: 0.91; LR: 6.257e-07;
overall_loss: 0.0619, cls_loss: 0.0196, cls_acc: 0.993, cls_aux_loss: 0.0187, cls_aux_acc: 0.990, seg_loss: 0.1172, cam_loss: 0.6937, reg_loss: -0.4579 ...
Iter: 32000; Elasped: 8:31:21; ETA: 0:00:00; Itertime: 0.91; LR: 5.291e-09;
overall_loss: 0.0729, cls_loss: 0.0255, cls_acc: 0.987, cls_aux_loss: 0.0249, cls_aux_acc: 0.986, seg_loss: 0.1197, cam_loss: 0.6923, reg_loss: -0.4812 ...
model validating...
current_rank 0
store saving with size: 724 at rank: 0
store loaded with size: 1448
teacher: cls:0.971229336578094, clsaux: 0.9641350738571952
+--------------+--------+---------+--------+--------+---------+
| Class | CAM | aux_CAM | Seg_ps | Seg_vd | Seg_crf |
+==============+========+=========+========+========+=========+
| _background_ | 90.380 | 89.650 | 92.420 | 92.550 | 92.630 |
+--------------+--------+---------+--------+--------+---------+
| aeroplane | 78.230 | 80.680 | 81.990 | 83.650 | 84.040 |
+--------------+--------+---------+--------+--------+---------+
| bicycle | 46.550 | 47.110 | 48.020 | 48.520 | 48.930 |
+--------------+--------+---------+--------+--------+---------+
| bird | 85.840 | 72.210 | 87.260 | 87.470 | 87.880 |
+--------------+--------+---------+--------+--------+---------+
| boat | 71.030 | 62.960 | 70.990 | 73.670 | 74.080 |
+--------------+--------+---------+--------+--------+---------+
| bottle | 73.830 | 64.030 | 75.360 | 76.430 | 76.880 |
+--------------+--------+---------+--------+--------+---------+
| bus | 86.780 | 77.050 | 88.680 | 89.760 | 89.820 |
+--------------+--------+---------+--------+--------+---------+
| car | 79.610 | 73.570 | 84.170 | 84.920 | 85.080 |
+--------------+--------+---------+--------+--------+---------+
| cat | 77.540 | 82.010 | 86.830 | 87.280 | 87.550 |
+--------------+--------+---------+--------+--------+---------+
| chair | 32.870 | 45.840 | 37.420 | 47.170 | 47.240 |
+--------------+--------+---------+--------+--------+---------+
| cow | 82.410 | 76.080 | 88.090 | 88.120 | 88.450 |
+--------------+--------+---------+--------+--------+---------+
| diningtable | 41.380 | 50.580 | 47.630 | 49.230 | 49.240 |
+--------------+--------+---------+--------+--------+---------+
| dog | 78.530 | 75.860 | 83.420 | 84.360 | 84.550 |
+--------------+--------+---------+--------+--------+---------+
| horse | 79.560 | 70.810 | 83.630 | 84.650 | 84.880 |
+--------------+--------+---------+--------+--------+---------+
| motorbike | 75.880 | 75.810 | 78.360 | 78.480 | 78.520 |
+--------------+--------+---------+--------+--------+---------+
| person | 70.630 | 81.810 | 83.890 | 84 | 84.220 |
+--------------+--------+---------+--------+--------+---------+
| pottedplant | 46.920 | 32.900 | 50.510 | 50.840 | 50.940 |
+--------------+--------+---------+--------+--------+---------+
| sheep | 85.340 | 84.660 | 88.460 | 88.460 | 88.730 |
+--------------+--------+---------+--------+--------+---------+
| sofa | 55.370 | 68.050 | 56.750 | 64.530 | 64.550 |
+--------------+--------+---------+--------+--------+---------+
| train | 66.560 | 55.750 | 64.850 | 64.850 | 65.010 |
+--------------+--------+---------+--------+--------+---------+
| tvmonitor | 71.070 | 61.330 | 65.360 | 66.950 | 67.090 |
+--------------+--------+---------+--------+--------+---------+
| mIoU | 70.300 | 68.036 | 73.528 | 75.042 | 75.253 |
+--------------+--------+---------+--------+--------+---------+
Training time 8:39:10 Best val Seg IoU: 75.72
Perform final validation on best model
use pretrained
decoder is LargeFOV
model validating...
current_rank 0
store saving with size: 1449 at rank: 0
Store loaded with size: 1449
Final Model Result:
+--------------+--------+---------+
| Class | Seg_vd | Seg_crf |
+==============+========+=========+
| _background_ | 92.980 | 93.050 |
+--------------+--------+---------+
| aeroplane | 85.230 | 85.520 |
+--------------+--------+---------+
| bicycle | 48.230 | 48.530 |
+--------------+--------+---------+
| bird | 88.400 | 88.700 |
+--------------+--------+---------+
| boat | 69.630 | 69.970 |
+--------------+--------+---------+
| bottle | 77.340 | 77.560 |
+--------------+--------+---------+
| bus | 90.330 | 90.390 |
+--------------+--------+---------+
| car | 86.260 | 86.360 |
+--------------+--------+---------+
| cat | 90.110 | 90.310 |
+--------------+--------+---------+
| chair | 47.160 | 47.190 |
+--------------+--------+---------+
| cow | 88.440 | 88.700 |
+--------------+--------+---------+
| diningtable | 54 | 54.090 |
+--------------+--------+---------+
| dog | 87.130 | 87.290 |
+--------------+--------+---------+
| horse | 86.940 | 87.140 |
+--------------+--------+---------+
| motorbike | 79.590 | 79.620 |
+--------------+--------+---------+
| person | 85.420 | 85.600 |
+--------------+--------+---------+
| pottedplant | 53.090 | 53.190 |
+--------------+--------+---------+
| sheep | 89.560 | 89.860 |
+--------------+--------+---------+
| sofa | 71.680 | 71.870 |
+--------------+--------+---------+
| train | 65.020 | 65.130 |
+--------------+--------+---------+
| tvmonitor | 63.350 | 63.420 |
+--------------+--------+---------+
| mIoU | 76.185 | 76.357 |
+--------------+--------+---------+