kanashi6
/

GiT

Model card Files Files and versions Community

GiT / semseg_base.log

kanashi6

upload training log

8f538aa verified 8 months ago

raw

history blame contribute delete

No virus

227 kB

	2023/11/27 07:35:06 - mmengine - INFO - Iter(train) [ 500/120000] base_lr: 1.9999e-04 lr: 1.9999e-05 eta: 1 day, 8:07:20 time: 0.9677 data_time: 0.0078 memory: 8151 grad_norm: 0.2284 loss: 0.0469 semantic_segmentation_loss_cls: 0.0469
	2023/11/27 07:43:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 07:43:10 - mmengine - INFO - Iter(train) [ 1000/120000] base_lr: 1.9997e-04 lr: 1.9997e-05 eta: 1 day, 7:59:33 time: 0.9678 data_time: 0.0078 memory: 8151 grad_norm: 0.1592 loss: 0.0347 semantic_segmentation_loss_cls: 0.0347
	2023/11/27 07:51:15 - mmengine - INFO - Iter(train) [ 1500/120000] base_lr: 1.9992e-04 lr: 1.9993e-05 eta: 1 day, 7:52:40 time: 0.9684 data_time: 0.0079 memory: 8151 grad_norm: 0.1328 loss: 0.0294 semantic_segmentation_loss_cls: 0.0294
	2023/11/27 07:59:20 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 07:59:20 - mmengine - INFO - Iter(train) [ 2000/120000] base_lr: 1.9986e-04 lr: 1.9988e-05 eta: 1 day, 7:45:03 time: 0.9687 data_time: 0.0079 memory: 8151 grad_norm: 0.1182 loss: 0.0264 semantic_segmentation_loss_cls: 0.0264
	2023/11/27 08:07:24 - mmengine - INFO - Iter(train) [ 2500/120000] base_lr: 1.9979e-04 lr: 1.9981e-05 eta: 1 day, 7:37:08 time: 0.9688 data_time: 0.0079 memory: 8151 grad_norm: 0.1095 loss: 0.0246 semantic_segmentation_loss_cls: 0.0246
	2023/11/27 08:15:29 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 08:15:29 - mmengine - INFO - Iter(train) [ 3000/120000] base_lr: 1.9970e-04 lr: 1.9972e-05 eta: 1 day, 7:29:29 time: 0.9690 data_time: 0.0080 memory: 8151 grad_norm: 0.1027 loss: 0.0231 semantic_segmentation_loss_cls: 0.0231
	2023/11/27 08:23:34 - mmengine - INFO - Iter(train) [ 3500/120000] base_lr: 1.9958e-04 lr: 1.9962e-05 eta: 1 day, 7:21:28 time: 0.9690 data_time: 0.0080 memory: 8151 grad_norm: 0.0977 loss: 0.0221 semantic_segmentation_loss_cls: 0.0221
	2023/11/27 08:31:39 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 08:31:39 - mmengine - INFO - Iter(train) [ 4000/120000] base_lr: 1.9946e-04 lr: 1.9951e-05 eta: 1 day, 7:13:42 time: 0.9692 data_time: 0.0080 memory: 8151 grad_norm: 0.0936 loss: 0.0212 semantic_segmentation_loss_cls: 0.0212
	2023/11/27 08:39:44 - mmengine - INFO - Iter(train) [ 4500/120000] base_lr: 1.9931e-04 lr: 1.9938e-05 eta: 1 day, 7:05:40 time: 0.9694 data_time: 0.0080 memory: 8151 grad_norm: 0.0734 loss: 0.0171 semantic_segmentation_loss_cls: 0.0171
	2023/11/27 08:47:48 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 08:47:48 - mmengine - INFO - Iter(train) [ 5000/120000] base_lr: 1.9915e-04 lr: 1.9923e-05 eta: 1 day, 6:57:34 time: 0.9695 data_time: 0.0080 memory: 8151 grad_norm: 0.0702 loss: 0.0161 semantic_segmentation_loss_cls: 0.0161
	2023/11/27 08:51:03 - mmengine - INFO - per class results:
	2023/11/27 08:51:03 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 73.37 \| 85.57 \|
	\| building \| 78.5 \| 90.31 \|
	\| sky \| 92.37 \| 97.55 \|
	\| floor \| 77.78 \| 88.46 \|
	\| tree \| 71.03 \| 84.78 \|
	\| ceiling \| 79.51 \| 94.7 \|
	\| road \| 75.74 \| 90.89 \|
	\| bed \| 82.5 \| 90.7 \|
	\| windowpane \| 56.34 \| 71.68 \|
	\| grass \| 63.22 \| 73.1 \|
	\| cabinet \| 51.77 \| 77.26 \|
	\| sidewalk \| 55.47 \| 64.69 \|
	\| person \| 76.45 \| 90.55 \|
	\| earth \| 35.11 \| 50.02 \|
	\| door \| 37.59 \| 44.71 \|
	\| table \| 44.78 \| 53.81 \|
	\| mountain \| 41.0 \| 46.27 \|
	\| plant \| 47.48 \| 58.07 \|
	\| curtain \| 68.65 \| 80.91 \|
	\| chair \| 47.85 \| 62.21 \|
	\| car \| 74.84 \| 82.43 \|
	\| water \| 48.58 \| 60.96 \|
	\| painting \| 50.19 \| 52.65 \|
	\| sofa \| 54.42 \| 70.1 \|
	\| shelf \| 34.44 \| 76.35 \|
	\| house \| 42.8 \| 75.35 \|
	\| sea \| 50.78 \| 93.52 \|
	\| mirror \| 53.02 \| 57.6 \|
	\| rug \| 65.63 \| 72.44 \|
	\| field \| 26.94 \| 43.02 \|
	\| armchair \| 31.38 \| 56.26 \|
	\| seat \| 48.76 \| 73.63 \|
	\| fence \| 28.91 \| 42.74 \|
	\| desk \| 24.82 \| 33.58 \|
	\| rock \| 37.34 \| 85.43 \|
	\| wardrobe \| 29.11 \| 32.55 \|
	\| lamp \| 52.48 \| 65.92 \|
	\| bathtub \| 62.36 \| 73.53 \|
	\| railing \| 28.58 \| 37.02 \|
	\| cushion \| 41.82 \| 51.15 \|
	\| base \| 11.77 \| 14.06 \|
	\| box \| 14.77 \| 20.09 \|
	\| column \| 48.3 \| 60.27 \|
	\| signboard \| 30.02 \| 39.51 \|
	\| chest of drawers \| 33.91 \| 48.53 \|
	\| counter \| 19.04 \| 32.45 \|
	\| sand \| 30.02 \| 41.43 \|
	\| sink \| 37.95 \| 39.08 \|
	\| skyscraper \| 50.89 \| 60.68 \|
	\| fireplace \| 65.63 \| 87.89 \|
	\| refrigerator \| 60.64 \| 69.66 \|
	\| grandstand \| 16.86 \| 84.82 \|
	\| path \| 2.56 \| 2.62 \|
	\| stairs \| 22.27 \| 30.25 \|
	\| runway \| 61.83 \| 66.83 \|
	\| case \| 26.17 \| 28.96 \|
	\| pool table \| 54.68 \| 55.4 \|
	\| pillow \| 45.85 \| 67.59 \|
	\| screen door \| 52.49 \| 78.38 \|
	\| stairway \| 23.64 \| 30.15 \|
	\| river \| 9.52 \| 10.86 \|
	\| bridge \| 46.85 \| 53.6 \|
	\| bookcase \| 31.59 \| 40.05 \|
	\| blind \| 36.48 \| 56.09 \|
	\| coffee table \| 50.09 \| 58.25 \|
	\| toilet \| 73.16 \| 85.62 \|
	\| flower \| 26.71 \| 41.73 \|
	\| book \| 38.2 \| 53.44 \|
	\| hill \| 4.89 \| 11.79 \|
	\| bench \| 35.65 \| 47.26 \|
	\| countertop \| 41.85 \| 54.43 \|
	\| stove \| 50.7 \| 77.68 \|
	\| palm \| 33.49 \| 39.45 \|
	\| kitchen island \| 25.34 \| 66.6 \|
	\| computer \| 32.55 \| 39.12 \|
	\| swivel chair \| 35.56 \| 49.0 \|
	\| boat \| 64.22 \| 78.44 \|
	\| bar \| 24.54 \| 33.66 \|
	\| arcade machine \| 20.33 \| 64.2 \|
	\| hovel \| 13.05 \| 29.49 \|
	\| bus \| 50.65 \| 96.65 \|
	\| towel \| 44.89 \| 48.53 \|
	\| light \| 35.21 \| 38.96 \|
	\| truck \| 4.09 \| 4.88 \|
	\| tower \| 27.4 \| 43.64 \|
	\| chandelier \| 52.9 \| 68.33 \|
	\| awning \| 20.52 \| 25.71 \|
	\| streetlight \| 12.26 \| 13.01 \|
	\| booth \| 33.08 \| 33.61 \|
	\| television receiver \| 52.21 \| 63.56 \|
	\| airplane \| 52.6 \| 62.07 \|
	\| dirt track \| 0.0 \| 0.0 \|
	\| apparel \| 24.07 \| 37.1 \|
	\| pole \| 20.43 \| 27.05 \|
	\| land \| 0.0 \| 0.0 \|
	\| bannister \| 10.55 \| 17.49 \|
	\| escalator \| 8.35 \| 10.66 \|
	\| ottoman \| 15.9 \| 16.94 \|
	\| bottle \| 15.95 \| 26.56 \|
	\| buffet \| 41.55 \| 47.7 \|
	\| poster \| 14.43 \| 58.08 \|
	\| stage \| 11.09 \| 13.47 \|
	\| van \| 18.63 \| 23.62 \|
	\| ship \| 54.22 \| 65.59 \|
	\| fountain \| 19.09 \| 19.4 \|
	\| conveyer belt \| 45.92 \| 60.53 \|
	\| canopy \| 23.47 \| 26.87 \|
	\| washer \| 41.97 \| 42.3 \|
	\| plaything \| 13.04 \| 41.46 \|
	\| swimming pool \| 37.85 \| 80.22 \|
	\| stool \| 17.9 \| 19.56 \|
	\| barrel \| 7.99 \| 11.53 \|
	\| basket \| 14.68 \| 17.39 \|
	\| waterfall \| 52.44 \| 66.56 \|
	\| tent \| 77.51 \| 84.68 \|
	\| bag \| 2.41 \| 2.48 \|
	\| minibike \| 37.17 \| 50.45 \|
	\| cradle \| 74.08 \| 92.2 \|
	\| oven \| 20.17 \| 27.69 \|
	\| ball \| 26.59 \| 28.55 \|
	\| food \| 51.4 \| 62.3 \|
	\| step \| 10.82 \| 11.66 \|
	\| tank \| 13.96 \| 14.29 \|
	\| trade name \| 13.08 \| 13.44 \|
	\| microwave \| 32.86 \| 40.26 \|
	\| pot \| 27.84 \| 31.36 \|
	\| animal \| 48.18 \| 51.12 \|
	\| bicycle \| 43.19 \| 57.32 \|
	\| lake \| 2.32 \| 2.82 \|
	\| dishwasher \| 46.75 \| 62.75 \|
	\| screen \| 51.18 \| 75.17 \|
	\| blanket \| 3.35 \| 3.66 \|
	\| sculpture \| 43.53 \| 49.29 \|
	\| hood \| 44.8 \| 51.66 \|
	\| sconce \| 29.96 \| 39.25 \|
	\| vase \| 23.17 \| 34.03 \|
	\| traffic light \| 16.92 \| 21.86 \|
	\| tray \| 5.22 \| 6.37 \|
	\| ashcan \| 24.96 \| 48.21 \|
	\| fan \| 42.42 \| 60.41 \|
	\| pier \| 39.09 \| 48.76 \|
	\| crt screen \| 5.28 \| 27.79 \|
	\| plate \| 33.2 \| 38.39 \|
	\| monitor \| 20.6 \| 60.58 \|
	\| bulletin board \| 8.72 \| 9.57 \|
	\| shower \| 0.0 \| 0.0 \|
	\| radiator \| 28.17 \| 29.01 \|
	\| glass \| 7.78 \| 9.11 \|
	\| clock \| 13.57 \| 19.09 \|
	\| flag \| 31.92 \| 36.94 \|
	+---------------------+-------+-------+
	2023/11/27 08:51:03 - mmengine - INFO - Iter(val) [250/250] aAcc: 78.2500 mIoU: 36.3000 mAcc: 48.0900 data_time: 0.0039 time: 0.7725
	2023/11/27 08:59:08 - mmengine - INFO - Iter(train) [ 5500/120000] base_lr: 1.9898e-04 lr: 1.9907e-05 eta: 1 day, 6:50:01 time: 0.9698 data_time: 0.0084 memory: 8148 grad_norm: 0.0681 loss: 0.0155 semantic_segmentation_loss_cls: 0.0155
	2023/11/27 09:07:12 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 09:07:12 - mmengine - INFO - Iter(train) [ 6000/120000] base_lr: 1.9878e-04 lr: 1.9889e-05 eta: 1 day, 6:41:54 time: 0.9698 data_time: 0.0084 memory: 8148 grad_norm: 0.0667 loss: 0.0150 semantic_segmentation_loss_cls: 0.0150
	2023/11/27 09:15:17 - mmengine - INFO - Iter(train) [ 6500/120000] base_lr: 1.9857e-04 lr: 1.9870e-05 eta: 1 day, 6:33:52 time: 0.9699 data_time: 0.0084 memory: 8148 grad_norm: 0.0649 loss: 0.0144 semantic_segmentation_loss_cls: 0.0144
	2023/11/27 09:19:07 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 09:23:22 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 09:23:22 - mmengine - INFO - Iter(train) [ 7000/120000] base_lr: 1.9834e-04 lr: 1.9849e-05 eta: 1 day, 6:25:50 time: 0.9698 data_time: 0.0084 memory: 8148 grad_norm: 0.0639 loss: 0.0141 semantic_segmentation_loss_cls: 0.0141
	2023/11/27 09:31:27 - mmengine - INFO - Iter(train) [ 7500/120000] base_lr: 1.9810e-04 lr: 1.9827e-05 eta: 1 day, 6:17:47 time: 0.9699 data_time: 0.0084 memory: 8148 grad_norm: 0.0629 loss: 0.0137 semantic_segmentation_loss_cls: 0.0137
	2023/11/27 09:39:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 09:39:32 - mmengine - INFO - Iter(train) [ 8000/120000] base_lr: 1.9784e-04 lr: 1.9803e-05 eta: 1 day, 6:09:41 time: 0.9698 data_time: 0.0084 memory: 8148 grad_norm: 0.0621 loss: 0.0134 semantic_segmentation_loss_cls: 0.0134
	2023/11/27 09:47:37 - mmengine - INFO - Iter(train) [ 8500/120000] base_lr: 1.9756e-04 lr: 1.9778e-05 eta: 1 day, 6:01:38 time: 0.9698 data_time: 0.0084 memory: 8148 grad_norm: 0.0611 loss: 0.0131 semantic_segmentation_loss_cls: 0.0131
	2023/11/27 09:55:41 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 09:55:41 - mmengine - INFO - Iter(train) [ 9000/120000] base_lr: 1.9727e-04 lr: 1.9751e-05 eta: 1 day, 5:53:35 time: 0.9699 data_time: 0.0085 memory: 8148 grad_norm: 0.0604 loss: 0.0128 semantic_segmentation_loss_cls: 0.0128
	2023/11/27 10:03:46 - mmengine - INFO - Iter(train) [ 9500/120000] base_lr: 1.9695e-04 lr: 1.9723e-05 eta: 1 day, 5:45:30 time: 0.9696 data_time: 0.0081 memory: 8148 grad_norm: 0.0596 loss: 0.0125 semantic_segmentation_loss_cls: 0.0125
	2023/11/27 10:11:51 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 10:11:51 - mmengine - INFO - Iter(train) [ 10000/120000] base_lr: 1.9663e-04 lr: 1.9693e-05 eta: 1 day, 5:37:27 time: 0.9697 data_time: 0.0081 memory: 8148 grad_norm: 0.0588 loss: 0.0124 semantic_segmentation_loss_cls: 0.0124
	2023/11/27 10:11:51 - mmengine - INFO - Saving checkpoint at 10000 iterations
	2023/11/27 10:15:14 - mmengine - INFO - per class results:
	2023/11/27 10:15:14 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 72.61 \| 87.92 \|
	\| building \| 79.61 \| 87.57 \|
	\| sky \| 92.8 \| 96.08 \|
	\| floor \| 78.68 \| 88.32 \|
	\| tree \| 72.16 \| 88.91 \|
	\| ceiling \| 79.61 \| 91.66 \|
	\| road \| 82.22 \| 87.6 \|
	\| bed \| 84.52 \| 93.16 \|
	\| windowpane \| 55.48 \| 71.94 \|
	\| grass \| 63.09 \| 72.46 \|
	\| cabinet \| 55.61 \| 70.43 \|
	\| sidewalk \| 63.23 \| 79.67 \|
	\| person \| 77.63 \| 90.61 \|
	\| earth \| 34.37 \| 45.42 \|
	\| door \| 43.09 \| 65.89 \|
	\| table \| 52.6 \| 68.26 \|
	\| mountain \| 50.5 \| 64.54 \|
	\| plant \| 49.53 \| 62.75 \|
	\| curtain \| 68.43 \| 81.73 \|
	\| chair \| 47.89 \| 60.02 \|
	\| car \| 80.51 \| 90.67 \|
	\| water \| 45.07 \| 59.22 \|
	\| painting \| 66.58 \| 85.55 \|
	\| sofa \| 58.45 \| 73.91 \|
	\| shelf \| 37.52 \| 50.61 \|
	\| house \| 44.78 \| 77.97 \|
	\| sea \| 43.65 \| 65.2 \|
	\| mirror \| 58.95 \| 69.39 \|
	\| rug \| 59.51 \| 72.13 \|
	\| field \| 29.94 \| 57.8 \|
	\| armchair \| 35.08 \| 53.83 \|
	\| seat \| 56.39 \| 69.44 \|
	\| fence \| 35.42 \| 65.66 \|
	\| desk \| 31.09 \| 71.87 \|
	\| rock \| 38.22 \| 53.85 \|
	\| wardrobe \| 45.47 \| 55.17 \|
	\| lamp \| 55.13 \| 64.04 \|
	\| bathtub \| 67.52 \| 81.73 \|
	\| railing \| 27.92 \| 38.09 \|
	\| cushion \| 43.16 \| 48.97 \|
	\| base \| 9.81 \| 11.95 \|
	\| box \| 13.2 \| 14.4 \|
	\| column \| 36.83 \| 39.21 \|
	\| signboard \| 33.06 \| 44.18 \|
	\| chest of drawers \| 40.27 \| 44.86 \|
	\| counter \| 24.52 \| 35.31 \|
	\| sand \| 30.15 \| 64.51 \|
	\| sink \| 58.05 \| 64.58 \|
	\| skyscraper \| 49.44 \| 60.39 \|
	\| fireplace \| 49.28 \| 53.24 \|
	\| refrigerator \| 59.69 \| 63.65 \|
	\| grandstand \| 39.78 \| 42.0 \|
	\| path \| 25.74 \| 37.7 \|
	\| stairs \| 36.83 \| 59.78 \|
	\| runway \| 68.9 \| 92.75 \|
	\| case \| 42.0 \| 67.0 \|
	\| pool table \| 90.59 \| 95.35 \|
	\| pillow \| 44.2 \| 63.72 \|
	\| screen door \| 46.21 \| 69.21 \|
	\| stairway \| 29.42 \| 32.92 \|
	\| river \| 6.92 \| 13.64 \|
	\| bridge \| 34.96 \| 42.34 \|
	\| bookcase \| 30.47 \| 40.88 \|
	\| blind \| 32.75 \| 35.87 \|
	\| coffee table \| 56.65 \| 67.86 \|
	\| toilet \| 75.59 \| 86.01 \|
	\| flower \| 27.52 \| 54.05 \|
	\| book \| 43.24 \| 56.16 \|
	\| hill \| 4.2 \| 13.55 \|
	\| bench \| 35.95 \| 40.22 \|
	\| countertop \| 42.66 \| 65.8 \|
	\| stove \| 50.92 \| 56.75 \|
	\| palm \| 40.03 \| 65.15 \|
	\| kitchen island \| 39.63 \| 70.92 \|
	\| computer \| 43.27 \| 50.1 \|
	\| swivel chair \| 34.26 \| 46.95 \|
	\| boat \| 37.72 \| 40.28 \|
	\| bar \| 34.45 \| 39.42 \|
	\| arcade machine \| 49.91 \| 62.64 \|
	\| hovel \| 9.92 \| 14.07 \|
	\| bus \| 69.26 \| 72.04 \|
	\| towel \| 49.56 \| 61.14 \|
	\| light \| 44.73 \| 55.13 \|
	\| truck \| 14.28 \| 18.4 \|
	\| tower \| 27.31 \| 43.31 \|
	\| chandelier \| 56.13 \| 71.06 \|
	\| awning \| 14.9 \| 16.15 \|
	\| streetlight \| 25.97 \| 37.11 \|
	\| booth \| 17.54 \| 18.62 \|
	\| television receiver \| 59.92 \| 71.5 \|
	\| airplane \| 53.27 \| 60.1 \|
	\| dirt track \| 0.0 \| 0.0 \|
	\| apparel \| 24.53 \| 36.11 \|
	\| pole \| 25.65 \| 45.6 \|
	\| land \| 18.35 \| 24.03 \|
	\| bannister \| 8.32 \| 11.29 \|
	\| escalator \| 5.17 \| 5.68 \|
	\| ottoman \| 35.15 \| 44.08 \|
	\| bottle \| 15.0 \| 17.87 \|
	\| buffet \| 22.41 \| 23.76 \|
	\| poster \| 28.13 \| 28.96 \|
	\| stage \| 9.34 \| 14.58 \|
	\| van \| 21.54 \| 35.99 \|
	\| ship \| 21.31 \| 27.79 \|
	\| fountain \| 10.55 \| 11.25 \|
	\| conveyer belt \| 38.04 \| 42.02 \|
	\| canopy \| 11.04 \| 16.46 \|
	\| washer \| 57.3 \| 59.94 \|
	\| plaything \| 24.87 \| 28.37 \|
	\| swimming pool \| 29.91 \| 52.68 \|
	\| stool \| 23.27 \| 26.35 \|
	\| barrel \| 24.99 \| 70.37 \|
	\| basket \| 23.25 \| 31.56 \|
	\| waterfall \| 64.29 \| 91.89 \|
	\| tent \| 83.36 \| 97.68 \|
	\| bag \| 3.94 \| 4.28 \|
	\| minibike \| 55.55 \| 64.02 \|
	\| cradle \| 66.31 \| 80.86 \|
	\| oven \| 33.03 \| 64.24 \|
	\| ball \| 44.98 \| 58.9 \|
	\| food \| 42.03 \| 48.71 \|
	\| step \| 9.59 \| 10.37 \|
	\| tank \| 27.31 \| 30.52 \|
	\| trade name \| 26.05 \| 36.51 \|
	\| microwave \| 32.92 \| 36.44 \|
	\| pot \| 31.83 \| 38.53 \|
	\| animal \| 50.81 \| 54.82 \|
	\| bicycle \| 41.53 \| 60.94 \|
	\| lake \| 28.59 \| 60.64 \|
	\| dishwasher \| 46.11 \| 63.91 \|
	\| screen \| 74.63 \| 81.31 \|
	\| blanket \| 14.46 \| 26.16 \|
	\| sculpture \| 42.88 \| 47.86 \|
	\| hood \| 47.86 \| 50.34 \|
	\| sconce \| 37.23 \| 57.99 \|
	\| vase \| 23.22 \| 29.11 \|
	\| traffic light \| 25.84 \| 37.39 \|
	\| tray \| 4.66 \| 9.45 \|
	\| ashcan \| 28.92 \| 37.02 \|
	\| fan \| 50.68 \| 66.77 \|
	\| pier \| 27.44 \| 80.01 \|
	\| crt screen \| 7.66 \| 28.48 \|
	\| plate \| 39.67 \| 55.47 \|
	\| monitor \| 47.85 \| 54.06 \|
	\| bulletin board \| 27.32 \| 33.83 \|
	\| shower \| 0.41 \| 1.88 \|
	\| radiator \| 38.85 \| 42.25 \|
	\| glass \| 7.54 \| 8.01 \|
	\| clock \| 15.11 \| 19.01 \|
	\| flag \| 27.62 \| 32.29 \|
	+---------------------+-------+-------+
	2023/11/27 10:15:14 - mmengine - INFO - Iter(val) [250/250] aAcc: 79.5400 mIoU: 40.0800 mAcc: 51.7400 data_time: 0.0019 time: 0.7716
	2023/11/27 10:23:19 - mmengine - INFO - Iter(train) [ 10500/120000] base_lr: 1.9628e-04 lr: 1.9662e-05 eta: 1 day, 5:29:29 time: 0.9698 data_time: 0.0083 memory: 8148 grad_norm: 0.0580 loss: 0.0122 semantic_segmentation_loss_cls: 0.0122
	2023/11/27 10:31:24 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 10:31:24 - mmengine - INFO - Iter(train) [ 11000/120000] base_lr: 1.9592e-04 lr: 1.9629e-05 eta: 1 day, 5:21:24 time: 0.9698 data_time: 0.0083 memory: 8148 grad_norm: 0.0573 loss: 0.0120 semantic_segmentation_loss_cls: 0.0120
	2023/11/27 10:39:28 - mmengine - INFO - Iter(train) [ 11500/120000] base_lr: 1.9555e-04 lr: 1.9595e-05 eta: 1 day, 5:13:17 time: 0.9697 data_time: 0.0083 memory: 8148 grad_norm: 0.0566 loss: 0.0118 semantic_segmentation_loss_cls: 0.0118
	2023/11/27 10:47:33 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 10:47:33 - mmengine - INFO - Iter(train) [ 12000/120000] base_lr: 1.9516e-04 lr: 1.9560e-05 eta: 1 day, 5:05:14 time: 0.9698 data_time: 0.0083 memory: 8148 grad_norm: 0.0558 loss: 0.0117 semantic_segmentation_loss_cls: 0.0117
	2023/11/27 10:55:38 - mmengine - INFO - Iter(train) [ 12500/120000] base_lr: 1.9475e-04 lr: 1.9522e-05 eta: 1 day, 4:57:07 time: 0.9697 data_time: 0.0083 memory: 8148 grad_norm: 0.0548 loss: 0.0115 semantic_segmentation_loss_cls: 0.0115
	2023/11/27 11:03:42 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 11:03:42 - mmengine - INFO - Iter(train) [ 13000/120000] base_lr: 1.9432e-04 lr: 1.9484e-05 eta: 1 day, 4:49:02 time: 0.9697 data_time: 0.0083 memory: 8148 grad_norm: 0.0540 loss: 0.0114 semantic_segmentation_loss_cls: 0.0114
	2023/11/27 11:11:47 - mmengine - INFO - Iter(train) [ 13500/120000] base_lr: 1.9388e-04 lr: 1.9444e-05 eta: 1 day, 4:40:58 time: 0.9697 data_time: 0.0083 memory: 8148 grad_norm: 0.0530 loss: 0.0112 semantic_segmentation_loss_cls: 0.0112
	2023/11/27 11:19:52 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 11:19:52 - mmengine - INFO - Iter(train) [ 14000/120000] base_lr: 1.9343e-04 lr: 1.9402e-05 eta: 1 day, 4:32:52 time: 0.9696 data_time: 0.0083 memory: 8148 grad_norm: 0.0522 loss: 0.0109 semantic_segmentation_loss_cls: 0.0109
	2023/11/27 11:27:57 - mmengine - INFO - Iter(train) [ 14500/120000] base_lr: 1.9295e-04 lr: 1.9359e-05 eta: 1 day, 4:24:48 time: 0.9695 data_time: 0.0081 memory: 8148 grad_norm: 0.0516 loss: 0.0107 semantic_segmentation_loss_cls: 0.0107
	2023/11/27 11:36:02 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 11:36:02 - mmengine - INFO - Iter(train) [ 15000/120000] base_lr: 1.9247e-04 lr: 1.9315e-05 eta: 1 day, 4:16:43 time: 0.9695 data_time: 0.0081 memory: 8148 grad_norm: 0.0510 loss: 0.0105 semantic_segmentation_loss_cls: 0.0105
	2023/11/27 11:39:16 - mmengine - INFO - per class results:
	2023/11/27 11:39:16 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 75.47 \| 88.2 \|
	\| building \| 81.23 \| 91.75 \|
	\| sky \| 92.6 \| 96.6 \|
	\| floor \| 80.85 \| 88.15 \|
	\| tree \| 70.93 \| 87.64 \|
	\| ceiling \| 80.9 \| 90.39 \|
	\| road \| 80.52 \| 87.73 \|
	\| bed \| 84.92 \| 94.55 \|
	\| windowpane \| 58.1 \| 76.81 \|
	\| grass \| 67.6 \| 80.56 \|
	\| cabinet \| 54.87 \| 63.84 \|
	\| sidewalk \| 55.98 \| 65.38 \|
	\| person \| 76.19 \| 85.84 \|
	\| earth \| 38.69 \| 61.43 \|
	\| door \| 43.21 \| 52.38 \|
	\| table \| 54.14 \| 76.94 \|
	\| mountain \| 53.1 \| 83.25 \|
	\| plant \| 45.39 \| 54.95 \|
	\| curtain \| 70.08 \| 82.85 \|
	\| chair \| 51.83 \| 70.97 \|
	\| car \| 79.63 \| 90.29 \|
	\| water \| 53.49 \| 71.44 \|
	\| painting \| 64.66 \| 85.94 \|
	\| sofa \| 60.07 \| 72.5 \|
	\| shelf \| 38.7 \| 51.34 \|
	\| house \| 41.39 \| 60.44 \|
	\| sea \| 51.99 \| 74.3 \|
	\| mirror \| 62.88 \| 72.6 \|
	\| rug \| 70.75 \| 76.11 \|
	\| field \| 19.25 \| 22.65 \|
	\| armchair \| 38.19 \| 62.64 \|
	\| seat \| 59.5 \| 77.99 \|
	\| fence \| 39.71 \| 58.87 \|
	\| desk \| 32.93 \| 70.68 \|
	\| rock \| 33.78 \| 45.49 \|
	\| wardrobe \| 55.22 \| 71.93 \|
	\| lamp \| 54.58 \| 76.87 \|
	\| bathtub \| 67.75 \| 72.47 \|
	\| railing \| 31.4 \| 63.18 \|
	\| cushion \| 46.14 \| 59.25 \|
	\| base \| 17.87 \| 24.98 \|
	\| box \| 16.36 \| 21.43 \|
	\| column \| 44.8 \| 68.22 \|
	\| signboard \| 34.87 \| 44.88 \|
	\| chest of drawers \| 39.87 \| 67.66 \|
	\| counter \| 27.76 \| 45.56 \|
	\| sand \| 40.22 \| 45.59 \|
	\| sink \| 60.7 \| 79.09 \|
	\| skyscraper \| 47.94 \| 61.57 \|
	\| fireplace \| 60.86 \| 75.54 \|
	\| refrigerator \| 63.54 \| 71.42 \|
	\| grandstand \| 38.5 \| 66.92 \|
	\| path \| 21.98 \| 31.79 \|
	\| stairs \| 16.52 \| 17.91 \|
	\| runway \| 74.37 \| 75.04 \|
	\| case \| 40.07 \| 53.65 \|
	\| pool table \| 90.61 \| 93.88 \|
	\| pillow \| 50.1 \| 71.96 \|
	\| screen door \| 51.69 \| 61.08 \|
	\| stairway \| 27.14 \| 61.54 \|
	\| river \| 11.69 \| 16.09 \|
	\| bridge \| 35.32 \| 47.39 \|
	\| bookcase \| 20.92 \| 25.87 \|
	\| blind \| 31.37 \| 34.12 \|
	\| coffee table \| 58.09 \| 69.52 \|
	\| toilet \| 78.53 \| 81.44 \|
	\| flower \| 32.99 \| 52.91 \|
	\| book \| 43.85 \| 70.74 \|
	\| hill \| 4.02 \| 4.92 \|
	\| bench \| 34.84 \| 42.68 \|
	\| countertop \| 48.54 \| 58.22 \|
	\| stove \| 67.74 \| 76.28 \|
	\| palm \| 40.71 \| 55.45 \|
	\| kitchen island \| 40.97 \| 68.83 \|
	\| computer \| 50.73 \| 63.0 \|
	\| swivel chair \| 35.97 \| 41.67 \|
	\| boat \| 40.51 \| 43.33 \|
	\| bar \| 27.09 \| 30.83 \|
	\| arcade machine \| 49.15 \| 56.09 \|
	\| hovel \| 7.35 \| 8.29 \|
	\| bus \| 65.58 \| 67.63 \|
	\| towel \| 61.03 \| 67.87 \|
	\| light \| 43.69 \| 50.37 \|
	\| truck \| 17.06 \| 24.9 \|
	\| tower \| 30.31 \| 50.11 \|
	\| chandelier \| 57.68 \| 69.97 \|
	\| awning \| 20.36 \| 22.72 \|
	\| streetlight \| 26.05 \| 30.46 \|
	\| booth \| 41.59 \| 47.31 \|
	\| television receiver \| 63.31 \| 71.7 \|
	\| airplane \| 52.09 \| 61.87 \|
	\| dirt track \| 4.16 \| 18.29 \|
	\| apparel \| 34.53 \| 49.88 \|
	\| pole \| 25.23 \| 34.99 \|
	\| land \| 0.05 \| 0.07 \|
	\| bannister \| 8.16 \| 9.51 \|
	\| escalator \| 6.13 \| 6.23 \|
	\| ottoman \| 38.48 \| 48.85 \|
	\| bottle \| 14.37 \| 17.68 \|
	\| buffet \| 38.13 \| 76.79 \|
	\| poster \| 19.54 \| 24.24 \|
	\| stage \| 15.72 \| 26.98 \|
	\| van \| 10.2 \| 16.01 \|
	\| ship \| 54.4 \| 80.19 \|
	\| fountain \| 8.38 \| 11.93 \|
	\| conveyer belt \| 67.37 \| 83.63 \|
	\| canopy \| 15.59 \| 26.07 \|
	\| washer \| 66.74 \| 74.6 \|
	\| plaything \| 18.16 \| 20.97 \|
	\| swimming pool \| 41.65 \| 50.12 \|
	\| stool \| 35.51 \| 39.94 \|
	\| barrel \| 45.68 \| 47.45 \|
	\| basket \| 22.75 \| 28.57 \|
	\| waterfall \| 57.78 \| 83.42 \|
	\| tent \| 91.63 \| 96.47 \|
	\| bag \| 7.94 \| 9.53 \|
	\| minibike \| 45.62 \| 56.3 \|
	\| cradle \| 62.71 \| 92.97 \|
	\| oven \| 45.59 \| 63.42 \|
	\| ball \| 34.77 \| 40.45 \|
	\| food \| 48.11 \| 54.75 \|
	\| step \| 7.62 \| 9.06 \|
	\| tank \| 42.11 \| 55.69 \|
	\| trade name \| 3.0 \| 3.06 \|
	\| microwave \| 32.22 \| 34.15 \|
	\| pot \| 44.0 \| 56.06 \|
	\| animal \| 50.49 \| 54.28 \|
	\| bicycle \| 45.16 \| 78.34 \|
	\| lake \| 43.8 \| 44.53 \|
	\| dishwasher \| 61.87 \| 65.51 \|
	\| screen \| 58.66 \| 78.55 \|
	\| blanket \| 13.93 \| 15.58 \|
	\| sculpture \| 32.84 \| 57.34 \|
	\| hood \| 42.51 \| 44.87 \|
	\| sconce \| 37.35 \| 56.18 \|
	\| vase \| 30.12 \| 43.31 \|
	\| traffic light \| 24.07 \| 28.87 \|
	\| tray \| 5.17 \| 6.83 \|
	\| ashcan \| 28.82 \| 37.74 \|
	\| fan \| 45.71 \| 54.92 \|
	\| pier \| 6.4 \| 8.57 \|
	\| crt screen \| 10.92 \| 18.71 \|
	\| plate \| 47.76 \| 67.58 \|
	\| monitor \| 15.44 \| 20.12 \|
	\| bulletin board \| 30.76 \| 43.24 \|
	\| shower \| 0.86 \| 4.66 \|
	\| radiator \| 41.7 \| 44.8 \|
	\| glass \| 9.95 \| 10.75 \|
	\| clock \| 16.06 \| 24.46 \|
	\| flag \| 28.03 \| 33.01 \|
	+---------------------+-------+-------+
	2023/11/27 11:39:16 - mmengine - INFO - Iter(val) [250/250] aAcc: 80.6200 mIoU: 41.7700 mAcc: 53.0700 data_time: 0.0019 time: 0.7623
	2023/11/27 11:47:21 - mmengine - INFO - Iter(train) [ 15500/120000] base_lr: 1.9196e-04 lr: 1.9269e-05 eta: 1 day, 4:09:06 time: 0.9706 data_time: 0.0091 memory: 8148 grad_norm: 0.0502 loss: 0.0104 semantic_segmentation_loss_cls: 0.0104
	2023/11/27 11:55:26 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 11:55:26 - mmengine - INFO - Iter(train) [ 16000/120000] base_lr: 1.9144e-04 lr: 1.9222e-05 eta: 1 day, 4:00:58 time: 0.9705 data_time: 0.0091 memory: 8148 grad_norm: 0.0497 loss: 0.0102 semantic_segmentation_loss_cls: 0.0102
	2023/11/27 12:03:30 - mmengine - INFO - Iter(train) [ 16500/120000] base_lr: 1.9091e-04 lr: 1.9173e-05 eta: 1 day, 3:52:52 time: 0.9705 data_time: 0.0091 memory: 8148 grad_norm: 0.0493 loss: 0.0101 semantic_segmentation_loss_cls: 0.0101
	2023/11/27 12:11:35 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 12:11:35 - mmengine - INFO - Iter(train) [ 17000/120000] base_lr: 1.9036e-04 lr: 1.9123e-05 eta: 1 day, 3:44:45 time: 0.9705 data_time: 0.0091 memory: 8148 grad_norm: 0.0488 loss: 0.0100 semantic_segmentation_loss_cls: 0.0100
	2023/11/27 12:19:40 - mmengine - INFO - Iter(train) [ 17500/120000] base_lr: 1.8979e-04 lr: 1.9072e-05 eta: 1 day, 3:36:39 time: 0.9704 data_time: 0.0091 memory: 8148 grad_norm: 0.0489 loss: 0.0099 semantic_segmentation_loss_cls: 0.0099
	2023/11/27 12:27:45 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 12:27:45 - mmengine - INFO - Iter(train) [ 18000/120000] base_lr: 1.8921e-04 lr: 1.9019e-05 eta: 1 day, 3:28:34 time: 0.9704 data_time: 0.0091 memory: 8148 grad_norm: 0.0485 loss: 0.0098 semantic_segmentation_loss_cls: 0.0098
	2023/11/27 12:35:49 - mmengine - INFO - Iter(train) [ 18500/120000] base_lr: 1.8861e-04 lr: 1.8965e-05 eta: 1 day, 3:20:27 time: 0.9703 data_time: 0.0091 memory: 8148 grad_norm: 0.0480 loss: 0.0098 semantic_segmentation_loss_cls: 0.0098
	2023/11/27 12:43:54 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 12:43:54 - mmengine - INFO - Iter(train) [ 19000/120000] base_lr: 1.8800e-04 lr: 1.8909e-05 eta: 1 day, 3:12:21 time: 0.9703 data_time: 0.0091 memory: 8148 grad_norm: 0.0472 loss: 0.0096 semantic_segmentation_loss_cls: 0.0096
	2023/11/27 12:51:58 - mmengine - INFO - Iter(train) [ 19500/120000] base_lr: 1.8738e-04 lr: 1.8853e-05 eta: 1 day, 3:04:14 time: 0.9692 data_time: 0.0081 memory: 8148 grad_norm: 0.0470 loss: 0.0096 semantic_segmentation_loss_cls: 0.0096
	2023/11/27 13:00:03 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 13:00:03 - mmengine - INFO - Iter(train) [ 20000/120000] base_lr: 1.8674e-04 lr: 1.8794e-05 eta: 1 day, 2:56:08 time: 0.9692 data_time: 0.0081 memory: 8148 grad_norm: 0.0462 loss: 0.0095 semantic_segmentation_loss_cls: 0.0095
	2023/11/27 13:00:03 - mmengine - INFO - Saving checkpoint at 20000 iterations
	2023/11/27 13:03:24 - mmengine - INFO - per class results:
	2023/11/27 13:03:24 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 75.4 \| 85.39 \|
	\| building \| 79.36 \| 91.84 \|
	\| sky \| 93.16 \| 97.41 \|
	\| floor \| 78.97 \| 90.44 \|
	\| tree \| 71.06 \| 86.6 \|
	\| ceiling \| 83.38 \| 93.2 \|
	\| road \| 80.35 \| 85.49 \|
	\| bed \| 86.93 \| 93.61 \|
	\| windowpane \| 59.1 \| 78.98 \|
	\| grass \| 62.43 \| 71.51 \|
	\| cabinet \| 58.65 \| 71.76 \|
	\| sidewalk \| 63.59 \| 81.61 \|
	\| person \| 76.49 \| 89.84 \|
	\| earth \| 37.74 \| 55.06 \|
	\| door \| 44.65 \| 59.03 \|
	\| table \| 56.73 \| 77.86 \|
	\| mountain \| 50.31 \| 70.81 \|
	\| plant \| 47.14 \| 56.77 \|
	\| curtain \| 71.36 \| 83.22 \|
	\| chair \| 52.87 \| 70.29 \|
	\| car \| 79.85 \| 90.61 \|
	\| water \| 54.24 \| 72.52 \|
	\| painting \| 66.75 \| 85.0 \|
	\| sofa \| 57.95 \| 70.64 \|
	\| shelf \| 35.07 \| 60.76 \|
	\| house \| 40.91 \| 63.14 \|
	\| sea \| 46.97 \| 68.73 \|
	\| mirror \| 61.88 \| 73.29 \|
	\| rug \| 59.82 \| 62.88 \|
	\| field \| 22.77 \| 36.25 \|
	\| armchair \| 39.86 \| 62.45 \|
	\| seat \| 55.06 \| 74.39 \|
	\| fence \| 36.72 \| 61.83 \|
	\| desk \| 43.81 \| 56.75 \|
	\| rock \| 27.52 \| 39.58 \|
	\| wardrobe \| 50.6 \| 70.63 \|
	\| lamp \| 57.67 \| 71.34 \|
	\| bathtub \| 72.59 \| 74.32 \|
	\| railing \| 29.73 \| 36.3 \|
	\| cushion \| 55.04 \| 70.56 \|
	\| base \| 19.08 \| 26.84 \|
	\| box \| 16.58 \| 20.38 \|
	\| column \| 45.28 \| 53.94 \|
	\| signboard \| 28.37 \| 60.55 \|
	\| chest of drawers \| 39.12 \| 47.43 \|
	\| counter \| 27.75 \| 46.61 \|
	\| sand \| 39.86 \| 48.2 \|
	\| sink \| 57.38 \| 75.71 \|
	\| skyscraper \| 31.87 \| 36.11 \|
	\| fireplace \| 62.72 \| 89.77 \|
	\| refrigerator \| 62.71 \| 69.33 \|
	\| grandstand \| 37.0 \| 74.15 \|
	\| path \| 24.59 \| 31.83 \|
	\| stairs \| 23.13 \| 28.1 \|
	\| runway \| 69.09 \| 87.04 \|
	\| case \| 32.33 \| 69.78 \|
	\| pool table \| 89.32 \| 93.13 \|
	\| pillow \| 53.69 \| 67.7 \|
	\| screen door \| 70.3 \| 74.28 \|
	\| stairway \| 21.69 \| 34.96 \|
	\| river \| 15.85 \| 21.05 \|
	\| bridge \| 34.1 \| 42.27 \|
	\| bookcase \| 30.63 \| 60.28 \|
	\| blind \| 37.47 \| 42.71 \|
	\| coffee table \| 58.71 \| 76.5 \|
	\| toilet \| 77.5 \| 82.8 \|
	\| flower \| 34.03 \| 47.83 \|
	\| book \| 41.95 \| 65.15 \|
	\| hill \| 5.26 \| 10.44 \|
	\| bench \| 38.28 \| 46.31 \|
	\| countertop \| 49.27 \| 58.35 \|
	\| stove \| 64.95 \| 78.02 \|
	\| palm \| 40.0 \| 50.08 \|
	\| kitchen island \| 44.2 \| 66.73 \|
	\| computer \| 57.58 \| 69.48 \|
	\| swivel chair \| 37.98 \| 47.49 \|
	\| boat \| 68.29 \| 77.36 \|
	\| bar \| 17.98 \| 21.99 \|
	\| arcade machine \| 54.07 \| 56.19 \|
	\| hovel \| 0.0 \| 0.0 \|
	\| bus \| 76.38 \| 83.96 \|
	\| towel \| 53.25 \| 75.92 \|
	\| light \| 48.14 \| 60.28 \|
	\| truck \| 28.45 \| 42.57 \|
	\| tower \| 21.49 \| 36.43 \|
	\| chandelier \| 55.03 \| 67.27 \|
	\| awning \| 27.17 \| 36.18 \|
	\| streetlight \| 25.26 \| 34.87 \|
	\| booth \| 38.32 \| 42.96 \|
	\| television receiver \| 57.53 \| 77.47 \|
	\| airplane \| 45.15 \| 66.05 \|
	\| dirt track \| 1.59 \| 6.02 \|
	\| apparel \| 31.55 \| 52.01 \|
	\| pole \| 19.93 \| 26.86 \|
	\| land \| 4.0 \| 4.99 \|
	\| bannister \| 4.72 \| 6.19 \|
	\| escalator \| 23.42 \| 27.0 \|
	\| ottoman \| 15.12 \| 16.3 \|
	\| bottle \| 14.04 \| 18.06 \|
	\| buffet \| 53.71 \| 67.03 \|
	\| poster \| 25.2 \| 39.42 \|
	\| stage \| 13.02 \| 25.9 \|
	\| van \| 21.94 \| 28.21 \|
	\| ship \| 18.0 \| 18.04 \|
	\| fountain \| 9.15 \| 10.26 \|
	\| conveyer belt \| 68.44 \| 86.84 \|
	\| canopy \| 12.49 \| 15.11 \|
	\| washer \| 64.5 \| 70.54 \|
	\| plaything \| 31.5 \| 36.62 \|
	\| swimming pool \| 48.67 \| 61.61 \|
	\| stool \| 39.81 \| 47.2 \|
	\| barrel \| 28.4 \| 29.0 \|
	\| basket \| 19.82 \| 22.62 \|
	\| waterfall \| 30.39 \| 32.42 \|
	\| tent \| 84.32 \| 94.29 \|
	\| bag \| 6.18 \| 7.95 \|
	\| minibike \| 47.69 \| 54.69 \|
	\| cradle \| 71.51 \| 91.42 \|
	\| oven \| 33.36 \| 49.23 \|
	\| ball \| 39.54 \| 54.79 \|
	\| food \| 40.51 \| 51.94 \|
	\| step \| 7.79 \| 9.6 \|
	\| tank \| 29.62 \| 37.27 \|
	\| trade name \| 19.26 \| 21.22 \|
	\| microwave \| 31.96 \| 34.68 \|
	\| pot \| 40.77 \| 47.42 \|
	\| animal \| 47.42 \| 60.23 \|
	\| bicycle \| 33.89 \| 50.06 \|
	\| lake \| 45.89 \| 64.65 \|
	\| dishwasher \| 19.21 \| 19.52 \|
	\| screen \| 64.3 \| 86.29 \|
	\| blanket \| 6.12 \| 6.27 \|
	\| sculpture \| 57.82 \| 67.5 \|
	\| hood \| 57.0 \| 64.23 \|
	\| sconce \| 35.25 \| 43.69 \|
	\| vase \| 25.9 \| 37.22 \|
	\| traffic light \| 28.52 \| 49.24 \|
	\| tray \| 3.52 \| 4.11 \|
	\| ashcan \| 28.63 \| 33.52 \|
	\| fan \| 53.99 \| 70.19 \|
	\| pier \| 43.33 \| 78.74 \|
	\| crt screen \| 4.05 \| 8.1 \|
	\| plate \| 49.76 \| 66.4 \|
	\| monitor \| 32.89 \| 43.98 \|
	\| bulletin board \| 22.16 \| 59.11 \|
	\| shower \| 1.91 \| 11.26 \|
	\| radiator \| 27.63 \| 28.32 \|
	\| glass \| 12.14 \| 13.5 \|
	\| clock \| 15.77 \| 17.72 \|
	\| flag \| 25.68 \| 29.13 \|
	+---------------------+-------+-------+
	2023/11/27 13:03:24 - mmengine - INFO - Iter(val) [250/250] aAcc: 80.5200 mIoU: 41.7000 mAcc: 53.2600 data_time: 0.0019 time: 0.7636
	2023/11/27 13:11:28 - mmengine - INFO - Iter(train) [ 20500/120000] base_lr: 1.8608e-04 lr: 1.8735e-05 eta: 1 day, 2:48:04 time: 0.9694 data_time: 0.0083 memory: 8148 grad_norm: 0.0456 loss: 0.0094 semantic_segmentation_loss_cls: 0.0094
	2023/11/27 13:19:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 13:19:32 - mmengine - INFO - Iter(train) [ 21000/120000] base_lr: 1.8541e-04 lr: 1.8674e-05 eta: 1 day, 2:39:57 time: 0.9693 data_time: 0.0083 memory: 8148 grad_norm: 0.0450 loss: 0.0094 semantic_segmentation_loss_cls: 0.0094
	2023/11/27 13:27:37 - mmengine - INFO - Iter(train) [ 21500/120000] base_lr: 1.8473e-04 lr: 1.8612e-05 eta: 1 day, 2:31:53 time: 0.9694 data_time: 0.0083 memory: 8148 grad_norm: 0.0442 loss: 0.0093 semantic_segmentation_loss_cls: 0.0093
	2023/11/27 13:35:42 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 13:35:42 - mmengine - INFO - Iter(train) [ 22000/120000] base_lr: 1.8403e-04 lr: 1.8548e-05 eta: 1 day, 2:23:46 time: 0.9692 data_time: 0.0083 memory: 8148 grad_norm: 0.0437 loss: 0.0092 semantic_segmentation_loss_cls: 0.0092
	2023/11/27 13:43:47 - mmengine - INFO - Iter(train) [ 22500/120000] base_lr: 1.8332e-04 lr: 1.8483e-05 eta: 1 day, 2:15:42 time: 0.9694 data_time: 0.0083 memory: 8148 grad_norm: 0.0434 loss: 0.0091 semantic_segmentation_loss_cls: 0.0091
	2023/11/27 13:51:51 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 13:51:51 - mmengine - INFO - Iter(train) [ 23000/120000] base_lr: 1.8259e-04 lr: 1.8417e-05 eta: 1 day, 2:07:36 time: 0.9693 data_time: 0.0083 memory: 8148 grad_norm: 0.0429 loss: 0.0090 semantic_segmentation_loss_cls: 0.0090
	2023/11/27 13:59:56 - mmengine - INFO - Iter(train) [ 23500/120000] base_lr: 1.8185e-04 lr: 1.8350e-05 eta: 1 day, 1:59:29 time: 0.9693 data_time: 0.0083 memory: 8148 grad_norm: 0.0426 loss: 0.0090 semantic_segmentation_loss_cls: 0.0090
	2023/11/27 14:08:01 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 14:08:01 - mmengine - INFO - Iter(train) [ 24000/120000] base_lr: 1.8109e-04 lr: 1.8281e-05 eta: 1 day, 1:51:25 time: 0.9694 data_time: 0.0083 memory: 8148 grad_norm: 0.0424 loss: 0.0089 semantic_segmentation_loss_cls: 0.0089
	2023/11/27 14:16:05 - mmengine - INFO - Iter(train) [ 24500/120000] base_lr: 1.8033e-04 lr: 1.8211e-05 eta: 1 day, 1:43:18 time: 0.9692 data_time: 0.0081 memory: 8148 grad_norm: 0.0420 loss: 0.0088 semantic_segmentation_loss_cls: 0.0088
	2023/11/27 14:24:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 14:24:10 - mmengine - INFO - Iter(train) [ 25000/120000] base_lr: 1.7954e-04 lr: 1.8140e-05 eta: 1 day, 1:35:14 time: 0.9694 data_time: 0.0081 memory: 8148 grad_norm: 0.0415 loss: 0.0088 semantic_segmentation_loss_cls: 0.0088
	2023/11/27 14:27:23 - mmengine - INFO - per class results:
	2023/11/27 14:27:23 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 74.68 \| 90.05 \|
	\| building \| 79.6 \| 87.58 \|
	\| sky \| 92.79 \| 96.49 \|
	\| floor \| 79.42 \| 89.34 \|
	\| tree \| 72.63 \| 88.19 \|
	\| ceiling \| 82.59 \| 93.04 \|
	\| road \| 81.36 \| 87.91 \|
	\| bed \| 86.28 \| 94.2 \|
	\| windowpane \| 58.94 \| 72.49 \|
	\| grass \| 65.57 \| 83.22 \|
	\| cabinet \| 58.9 \| 73.16 \|
	\| sidewalk \| 63.59 \| 81.62 \|
	\| person \| 77.39 \| 88.03 \|
	\| earth \| 33.09 \| 41.43 \|
	\| door \| 48.1 \| 68.63 \|
	\| table \| 55.71 \| 71.06 \|
	\| mountain \| 48.32 \| 62.69 \|
	\| plant \| 49.19 \| 58.28 \|
	\| curtain \| 69.06 \| 78.44 \|
	\| chair \| 51.7 \| 61.13 \|
	\| car \| 79.55 \| 90.48 \|
	\| water \| 51.5 \| 66.53 \|
	\| painting \| 68.21 \| 81.55 \|
	\| sofa \| 58.98 \| 79.39 \|
	\| shelf \| 38.6 \| 53.3 \|
	\| house \| 44.36 \| 74.7 \|
	\| sea \| 56.54 \| 81.03 \|
	\| mirror \| 62.02 \| 70.75 \|
	\| rug \| 65.32 \| 72.03 \|
	\| field \| 20.8 \| 34.95 \|
	\| armchair \| 34.59 \| 49.46 \|
	\| seat \| 57.13 \| 70.98 \|
	\| fence \| 42.04 \| 58.83 \|
	\| desk \| 45.3 \| 63.61 \|
	\| rock \| 29.36 \| 42.23 \|
	\| wardrobe \| 44.45 \| 65.62 \|
	\| lamp \| 55.7 \| 63.38 \|
	\| bathtub \| 77.27 \| 82.75 \|
	\| railing \| 26.65 \| 36.65 \|
	\| cushion \| 51.48 \| 63.87 \|
	\| base \| 12.77 \| 20.16 \|
	\| box \| 18.08 \| 28.86 \|
	\| column \| 46.04 \| 56.49 \|
	\| signboard \| 32.84 \| 43.74 \|
	\| chest of drawers \| 35.88 \| 41.58 \|
	\| counter \| 20.02 \| 36.9 \|
	\| sand \| 35.45 \| 45.45 \|
	\| sink \| 65.65 \| 74.76 \|
	\| skyscraper \| 48.35 \| 60.18 \|
	\| fireplace \| 61.48 \| 70.66 \|
	\| refrigerator \| 67.01 \| 74.36 \|
	\| grandstand \| 29.12 \| 64.49 \|
	\| path \| 21.31 \| 29.0 \|
	\| stairs \| 28.51 \| 39.68 \|
	\| runway \| 75.38 \| 80.94 \|
	\| case \| 35.33 \| 46.64 \|
	\| pool table \| 89.72 \| 94.58 \|
	\| pillow \| 49.05 \| 65.12 \|
	\| screen door \| 71.88 \| 82.35 \|
	\| stairway \| 37.84 \| 48.55 \|
	\| river \| 10.24 \| 24.92 \|
	\| bridge \| 66.88 \| 81.67 \|
	\| bookcase \| 34.91 \| 55.51 \|
	\| blind \| 39.06 \| 44.42 \|
	\| coffee table \| 49.67 \| 85.62 \|
	\| toilet \| 81.0 \| 88.72 \|
	\| flower \| 29.39 \| 51.34 \|
	\| book \| 43.21 \| 53.87 \|
	\| hill \| 5.32 \| 15.5 \|
	\| bench \| 39.86 \| 50.05 \|
	\| countertop \| 48.46 \| 62.77 \|
	\| stove \| 65.79 \| 76.97 \|
	\| palm \| 43.39 \| 63.87 \|
	\| kitchen island \| 36.71 \| 50.71 \|
	\| computer \| 49.85 \| 54.27 \|
	\| swivel chair \| 41.73 \| 62.17 \|
	\| boat \| 59.42 \| 68.77 \|
	\| bar \| 23.77 \| 29.36 \|
	\| arcade machine \| 34.74 \| 36.37 \|
	\| hovel \| 18.4 \| 21.29 \|
	\| bus \| 76.2 \| 82.05 \|
	\| towel \| 53.25 \| 77.25 \|
	\| light \| 44.98 \| 51.7 \|
	\| truck \| 21.14 \| 30.71 \|
	\| tower \| 26.88 \| 43.24 \|
	\| chandelier \| 59.79 \| 71.02 \|
	\| awning \| 23.74 \| 44.08 \|
	\| streetlight \| 23.0 \| 27.41 \|
	\| booth \| 36.53 \| 40.55 \|
	\| television receiver \| 61.85 \| 64.37 \|
	\| airplane \| 57.42 \| 64.71 \|
	\| dirt track \| 4.94 \| 19.11 \|
	\| apparel \| 23.91 \| 35.91 \|
	\| pole \| 21.76 \| 35.5 \|
	\| land \| 1.81 \| 2.45 \|
	\| bannister \| 13.06 \| 22.45 \|
	\| escalator \| 20.99 \| 23.32 \|
	\| ottoman \| 42.38 \| 61.7 \|
	\| bottle \| 16.86 \| 20.68 \|
	\| buffet \| 47.43 \| 54.25 \|
	\| poster \| 25.55 \| 41.63 \|
	\| stage \| 16.16 \| 26.18 \|
	\| van \| 24.24 \| 35.77 \|
	\| ship \| 66.84 \| 75.49 \|
	\| fountain \| 16.29 \| 18.85 \|
	\| conveyer belt \| 74.97 \| 87.5 \|
	\| canopy \| 13.7 \| 22.19 \|
	\| washer \| 60.42 \| 66.09 \|
	\| plaything \| 24.6 \| 36.7 \|
	\| swimming pool \| 39.15 \| 50.44 \|
	\| stool \| 40.55 \| 51.66 \|
	\| barrel \| 19.03 \| 60.11 \|
	\| basket \| 24.09 \| 28.07 \|
	\| waterfall \| 36.73 \| 49.98 \|
	\| tent \| 88.44 \| 98.21 \|
	\| bag \| 12.84 \| 16.45 \|
	\| minibike \| 55.2 \| 74.79 \|
	\| cradle \| 73.56 \| 91.63 \|
	\| oven \| 41.91 \| 49.86 \|
	\| ball \| 40.67 \| 47.34 \|
	\| food \| 57.03 \| 77.24 \|
	\| step \| 12.95 \| 18.98 \|
	\| tank \| 38.83 \| 43.78 \|
	\| trade name \| 24.72 \| 31.1 \|
	\| microwave \| 36.62 \| 43.3 \|
	\| pot \| 43.74 \| 54.23 \|
	\| animal \| 42.18 \| 43.45 \|
	\| bicycle \| 52.23 \| 64.31 \|
	\| lake \| 49.64 \| 61.56 \|
	\| dishwasher \| 57.86 \| 63.13 \|
	\| screen \| 66.13 \| 83.1 \|
	\| blanket \| 11.06 \| 12.71 \|
	\| sculpture \| 46.68 \| 53.54 \|
	\| hood \| 58.5 \| 62.24 \|
	\| sconce \| 33.86 \| 42.57 \|
	\| vase \| 31.97 \| 49.03 \|
	\| traffic light \| 22.95 \| 27.07 \|
	\| tray \| 7.89 \| 11.11 \|
	\| ashcan \| 34.3 \| 58.99 \|
	\| fan \| 57.27 \| 68.66 \|
	\| pier \| 68.66 \| 75.7 \|
	\| crt screen \| 9.68 \| 26.09 \|
	\| plate \| 50.06 \| 60.82 \|
	\| monitor \| 4.36 \| 5.02 \|
	\| bulletin board \| 33.49 \| 48.61 \|
	\| shower \| 0.0 \| 0.0 \|
	\| radiator \| 37.3 \| 39.07 \|
	\| glass \| 4.96 \| 5.14 \|
	\| clock \| 18.17 \| 25.29 \|
	\| flag \| 29.22 \| 32.92 \|
	+---------------------+-------+-------+
	2023/11/27 14:27:23 - mmengine - INFO - Iter(val) [250/250] aAcc: 80.7400 mIoU: 43.7200 mAcc: 54.9500 data_time: 0.0018 time: 0.7639
	2023/11/27 14:35:27 - mmengine - INFO - Iter(train) [ 25500/120000] base_lr: 1.7875e-04 lr: 1.8068e-05 eta: 1 day, 1:27:14 time: 0.9697 data_time: 0.0086 memory: 8148 grad_norm: 0.0410 loss: 0.0087 semantic_segmentation_loss_cls: 0.0087
	2023/11/27 14:43:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 14:43:32 - mmengine - INFO - Iter(train) [ 26000/120000] base_lr: 1.7794e-04 lr: 1.7994e-05 eta: 1 day, 1:19:10 time: 0.9699 data_time: 0.0086 memory: 8148 grad_norm: 0.0406 loss: 0.0087 semantic_segmentation_loss_cls: 0.0087
	2023/11/27 14:51:37 - mmengine - INFO - Iter(train) [ 26500/120000] base_lr: 1.7712e-04 lr: 1.7920e-05 eta: 1 day, 1:11:04 time: 0.9697 data_time: 0.0086 memory: 8148 grad_norm: 0.0398 loss: 0.0086 semantic_segmentation_loss_cls: 0.0086
	2023/11/27 14:59:41 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 14:59:41 - mmengine - INFO - Iter(train) [ 27000/120000] base_lr: 1.7628e-04 lr: 1.7844e-05 eta: 1 day, 1:02:58 time: 0.9697 data_time: 0.0086 memory: 8148 grad_norm: 0.0399 loss: 0.0086 semantic_segmentation_loss_cls: 0.0086
	2023/11/27 15:07:46 - mmengine - INFO - Iter(train) [ 27500/120000] base_lr: 1.7543e-04 lr: 1.7767e-05 eta: 1 day, 0:54:54 time: 0.9699 data_time: 0.0086 memory: 8148 grad_norm: 0.0391 loss: 0.0085 semantic_segmentation_loss_cls: 0.0085
	2023/11/27 15:15:51 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 15:15:51 - mmengine - INFO - Iter(train) [ 28000/120000] base_lr: 1.7457e-04 lr: 1.7688e-05 eta: 1 day, 0:46:48 time: 0.9698 data_time: 0.0086 memory: 8148 grad_norm: 0.0387 loss: 0.0085 semantic_segmentation_loss_cls: 0.0085
	2023/11/27 15:23:56 - mmengine - INFO - Iter(train) [ 28500/120000] base_lr: 1.7370e-04 lr: 1.7609e-05 eta: 1 day, 0:38:43 time: 0.9699 data_time: 0.0086 memory: 8148 grad_norm: 0.0385 loss: 0.0084 semantic_segmentation_loss_cls: 0.0084
	2023/11/27 15:32:00 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 15:32:00 - mmengine - INFO - Iter(train) [ 29000/120000] base_lr: 1.7281e-04 lr: 1.7529e-05 eta: 1 day, 0:30:37 time: 0.9698 data_time: 0.0086 memory: 8148 grad_norm: 0.0383 loss: 0.0084 semantic_segmentation_loss_cls: 0.0084
	2023/11/27 15:40:05 - mmengine - INFO - Iter(train) [ 29500/120000] base_lr: 1.7192e-04 lr: 1.7447e-05 eta: 1 day, 0:22:32 time: 0.9694 data_time: 0.0081 memory: 8148 grad_norm: 0.0381 loss: 0.0083 semantic_segmentation_loss_cls: 0.0083
	2023/11/27 15:48:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 15:48:10 - mmengine - INFO - Iter(train) [ 30000/120000] base_lr: 1.7101e-04 lr: 1.7364e-05 eta: 1 day, 0:14:27 time: 0.9693 data_time: 0.0082 memory: 8148 grad_norm: 0.0377 loss: 0.0082 semantic_segmentation_loss_cls: 0.0082
	2023/11/27 15:48:10 - mmengine - INFO - Saving checkpoint at 30000 iterations
	2023/11/27 15:51:31 - mmengine - INFO - per class results:
	2023/11/27 15:51:31 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.17 \| 87.91 \|
	\| building \| 79.99 \| 91.62 \|
	\| sky \| 93.08 \| 97.69 \|
	\| floor \| 80.32 \| 89.06 \|
	\| tree \| 71.72 \| 87.19 \|
	\| ceiling \| 83.4 \| 93.72 \|
	\| road \| 80.62 \| 86.7 \|
	\| bed \| 86.01 \| 94.98 \|
	\| windowpane \| 59.86 \| 76.91 \|
	\| grass \| 64.23 \| 75.29 \|
	\| cabinet \| 56.78 \| 71.59 \|
	\| sidewalk \| 62.46 \| 83.68 \|
	\| person \| 76.74 \| 89.34 \|
	\| earth \| 35.41 \| 46.92 \|
	\| door \| 47.16 \| 63.74 \|
	\| table \| 57.71 \| 75.74 \|
	\| mountain \| 51.57 \| 65.67 \|
	\| plant \| 46.91 \| 61.09 \|
	\| curtain \| 69.92 \| 79.35 \|
	\| chair \| 54.5 \| 69.32 \|
	\| car \| 80.64 \| 89.51 \|
	\| water \| 53.52 \| 65.85 \|
	\| painting \| 66.88 \| 82.65 \|
	\| sofa \| 60.13 \| 72.01 \|
	\| shelf \| 40.67 \| 59.84 \|
	\| house \| 39.63 \| 50.84 \|
	\| sea \| 53.61 \| 85.42 \|
	\| mirror \| 64.09 \| 77.06 \|
	\| rug \| 65.64 \| 78.52 \|
	\| field \| 26.63 \| 44.74 \|
	\| armchair \| 42.58 \| 62.0 \|
	\| seat \| 55.49 \| 72.65 \|
	\| fence \| 43.6 \| 64.07 \|
	\| desk \| 41.76 \| 69.71 \|
	\| rock \| 32.92 \| 47.46 \|
	\| wardrobe \| 47.36 \| 70.39 \|
	\| lamp \| 59.79 \| 75.38 \|
	\| bathtub \| 77.68 \| 80.09 \|
	\| railing \| 34.52 \| 54.22 \|
	\| cushion \| 56.21 \| 71.4 \|
	\| base \| 15.47 \| 21.7 \|
	\| box \| 17.72 \| 25.11 \|
	\| column \| 50.67 \| 57.59 \|
	\| signboard \| 33.49 \| 41.18 \|
	\| chest of drawers \| 40.54 \| 60.72 \|
	\| counter \| 20.25 \| 30.68 \|
	\| sand \| 44.21 \| 66.6 \|
	\| sink \| 66.19 \| 75.38 \|
	\| skyscraper \| 36.77 \| 45.19 \|
	\| fireplace \| 69.01 \| 83.51 \|
	\| refrigerator \| 64.47 \| 69.01 \|
	\| grandstand \| 32.62 \| 60.58 \|
	\| path \| 24.83 \| 32.36 \|
	\| stairs \| 21.9 \| 29.28 \|
	\| runway \| 72.99 \| 83.98 \|
	\| case \| 47.24 \| 66.23 \|
	\| pool table \| 84.84 \| 96.19 \|
	\| pillow \| 51.3 \| 64.92 \|
	\| screen door \| 65.76 \| 68.08 \|
	\| stairway \| 28.23 \| 34.63 \|
	\| river \| 14.63 \| 32.69 \|
	\| bridge \| 21.32 \| 23.0 \|
	\| bookcase \| 35.54 \| 50.43 \|
	\| blind \| 42.76 \| 46.87 \|
	\| coffee table \| 61.16 \| 78.84 \|
	\| toilet \| 81.87 \| 88.02 \|
	\| flower \| 35.42 \| 51.82 \|
	\| book \| 38.82 \| 56.38 \|
	\| hill \| 6.57 \| 13.32 \|
	\| bench \| 40.89 \| 55.9 \|
	\| countertop \| 49.99 \| 58.71 \|
	\| stove \| 69.0 \| 73.43 \|
	\| palm \| 48.32 \| 70.38 \|
	\| kitchen island \| 40.07 \| 51.57 \|
	\| computer \| 56.86 \| 64.9 \|
	\| swivel chair \| 33.89 \| 40.2 \|
	\| boat \| 62.6 \| 75.81 \|
	\| bar \| 34.93 \| 52.49 \|
	\| arcade machine \| 57.03 \| 66.24 \|
	\| hovel \| 6.64 \| 8.5 \|
	\| bus \| 63.24 \| 67.47 \|
	\| towel \| 58.63 \| 69.84 \|
	\| light \| 49.69 \| 58.12 \|
	\| truck \| 28.96 \| 42.17 \|
	\| tower \| 29.34 \| 51.96 \|
	\| chandelier \| 65.22 \| 78.6 \|
	\| awning \| 28.02 \| 36.61 \|
	\| streetlight \| 29.74 \| 38.91 \|
	\| booth \| 47.69 \| 58.82 \|
	\| television receiver \| 65.25 \| 76.17 \|
	\| airplane \| 54.3 \| 62.19 \|
	\| dirt track \| 4.59 \| 17.26 \|
	\| apparel \| 24.13 \| 40.23 \|
	\| pole \| 26.63 \| 39.91 \|
	\| land \| 1.63 \| 1.84 \|
	\| bannister \| 9.12 \| 13.92 \|
	\| escalator \| 6.13 \| 6.21 \|
	\| ottoman \| 33.74 \| 46.83 \|
	\| bottle \| 15.07 \| 16.92 \|
	\| buffet \| 44.38 \| 52.37 \|
	\| poster \| 26.77 \| 32.41 \|
	\| stage \| 13.81 \| 22.27 \|
	\| van \| 31.3 \| 67.72 \|
	\| ship \| 49.26 \| 51.3 \|
	\| fountain \| 23.8 \| 26.81 \|
	\| conveyer belt \| 48.61 \| 88.72 \|
	\| canopy \| 28.17 \| 33.39 \|
	\| washer \| 64.66 \| 66.18 \|
	\| plaything \| 23.42 \| 30.78 \|
	\| swimming pool \| 44.85 \| 72.52 \|
	\| stool \| 42.15 \| 52.86 \|
	\| barrel \| 54.32 \| 72.61 \|
	\| basket \| 23.93 \| 34.47 \|
	\| waterfall \| 47.97 \| 51.81 \|
	\| tent \| 71.18 \| 98.16 \|
	\| bag \| 10.1 \| 13.63 \|
	\| minibike \| 46.38 \| 49.33 \|
	\| cradle \| 66.89 \| 91.21 \|
	\| oven \| 43.13 \| 59.89 \|
	\| ball \| 24.23 \| 28.05 \|
	\| food \| 29.8 \| 30.43 \|
	\| step \| 11.52 \| 12.97 \|
	\| tank \| 21.8 \| 22.68 \|
	\| trade name \| 25.23 \| 28.72 \|
	\| microwave \| 34.45 \| 37.11 \|
	\| pot \| 44.45 \| 51.41 \|
	\| animal \| 50.16 \| 55.68 \|
	\| bicycle \| 38.95 \| 63.04 \|
	\| lake \| 0.0 \| 0.0 \|
	\| dishwasher \| 52.81 \| 54.29 \|
	\| screen \| 75.84 \| 85.31 \|
	\| blanket \| 9.54 \| 11.73 \|
	\| sculpture \| 49.43 \| 78.15 \|
	\| hood \| 52.23 \| 56.72 \|
	\| sconce \| 39.95 \| 47.01 \|
	\| vase \| 30.02 \| 46.86 \|
	\| traffic light \| 29.36 \| 38.48 \|
	\| tray \| 7.14 \| 10.14 \|
	\| ashcan \| 36.26 \| 56.13 \|
	\| fan \| 54.46 \| 68.03 \|
	\| pier \| 44.64 \| 58.44 \|
	\| crt screen \| 8.41 \| 26.44 \|
	\| plate \| 43.23 \| 49.32 \|
	\| monitor \| 3.39 \| 3.93 \|
	\| bulletin board \| 25.94 \| 46.1 \|
	\| shower \| 1.15 \| 2.4 \|
	\| radiator \| 42.96 \| 47.38 \|
	\| glass \| 10.05 \| 10.85 \|
	\| clock \| 17.62 \| 23.6 \|
	\| flag \| 25.83 \| 29.94 \|
	+---------------------+-------+-------+
	2023/11/27 15:51:31 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.1600 mIoU: 43.2800 mAcc: 54.7200 data_time: 0.0019 time: 0.7642
	2023/11/27 15:59:36 - mmengine - INFO - Iter(train) [ 30500/120000] base_lr: 1.7008e-04 lr: 1.7280e-05 eta: 1 day, 0:06:24 time: 0.9696 data_time: 0.0084 memory: 8148 grad_norm: 0.0374 loss: 0.0082 semantic_segmentation_loss_cls: 0.0082
	2023/11/27 16:07:41 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 16:07:41 - mmengine - INFO - Iter(train) [ 31000/120000] base_lr: 1.6915e-04 lr: 1.7195e-05 eta: 23:58:20 time: 0.9697 data_time: 0.0084 memory: 8148 grad_norm: 0.0369 loss: 0.0081 semantic_segmentation_loss_cls: 0.0081
	2023/11/27 16:15:45 - mmengine - INFO - Iter(train) [ 31500/120000] base_lr: 1.6820e-04 lr: 1.7109e-05 eta: 23:50:14 time: 0.9696 data_time: 0.0084 memory: 8148 grad_norm: 0.0368 loss: 0.0080 semantic_segmentation_loss_cls: 0.0080
	2023/11/27 16:23:50 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 16:23:50 - mmengine - INFO - Iter(train) [ 32000/120000] base_lr: 1.6725e-04 lr: 1.7022e-05 eta: 23:42:09 time: 0.9697 data_time: 0.0084 memory: 8148 grad_norm: 0.0364 loss: 0.0079 semantic_segmentation_loss_cls: 0.0079
	2023/11/27 16:31:55 - mmengine - INFO - Iter(train) [ 32500/120000] base_lr: 1.6628e-04 lr: 1.6934e-05 eta: 23:34:04 time: 0.9696 data_time: 0.0084 memory: 8148 grad_norm: 0.0358 loss: 0.0079 semantic_segmentation_loss_cls: 0.0079
	2023/11/27 16:40:00 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 16:40:00 - mmengine - INFO - Iter(train) [ 33000/120000] base_lr: 1.6530e-04 lr: 1.6845e-05 eta: 23:25:59 time: 0.9697 data_time: 0.0084 memory: 8148 grad_norm: 0.0357 loss: 0.0078 semantic_segmentation_loss_cls: 0.0078
	2023/11/27 16:48:04 - mmengine - INFO - Iter(train) [ 33500/120000] base_lr: 1.6431e-04 lr: 1.6755e-05 eta: 23:17:54 time: 0.9697 data_time: 0.0084 memory: 8148 grad_norm: 0.0352 loss: 0.0078 semantic_segmentation_loss_cls: 0.0078
	2023/11/27 16:56:09 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 16:56:09 - mmengine - INFO - Iter(train) [ 34000/120000] base_lr: 1.6330e-04 lr: 1.6664e-05 eta: 23:09:48 time: 0.9696 data_time: 0.0084 memory: 8148 grad_norm: 0.0350 loss: 0.0078 semantic_segmentation_loss_cls: 0.0078
	2023/11/27 17:04:14 - mmengine - INFO - Iter(train) [ 34500/120000] base_lr: 1.6229e-04 lr: 1.6572e-05 eta: 23:01:44 time: 0.9695 data_time: 0.0082 memory: 8148 grad_norm: 0.0349 loss: 0.0078 semantic_segmentation_loss_cls: 0.0078
	2023/11/27 17:12:18 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 17:12:18 - mmengine - INFO - Iter(train) [ 35000/120000] base_lr: 1.6127e-04 lr: 1.6479e-05 eta: 22:53:39 time: 0.9694 data_time: 0.0082 memory: 8148 grad_norm: 0.0344 loss: 0.0077 semantic_segmentation_loss_cls: 0.0077
	2023/11/27 17:15:32 - mmengine - INFO - per class results:
	2023/11/27 17:15:32 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.1 \| 88.86 \|
	\| building \| 81.96 \| 91.25 \|
	\| sky \| 92.98 \| 97.89 \|
	\| floor \| 79.91 \| 89.1 \|
	\| tree \| 72.17 \| 86.15 \|
	\| ceiling \| 83.28 \| 92.74 \|
	\| road \| 80.79 \| 88.87 \|
	\| bed \| 86.94 \| 92.9 \|
	\| windowpane \| 60.1 \| 75.61 \|
	\| grass \| 68.54 \| 83.42 \|
	\| cabinet \| 59.73 \| 74.69 \|
	\| sidewalk \| 63.1 \| 80.7 \|
	\| person \| 76.88 \| 88.72 \|
	\| earth \| 39.48 \| 50.79 \|
	\| door \| 47.59 \| 63.54 \|
	\| table \| 58.88 \| 72.11 \|
	\| mountain \| 53.78 \| 71.02 \|
	\| plant \| 51.11 \| 65.82 \|
	\| curtain \| 72.11 \| 84.7 \|
	\| chair \| 55.41 \| 70.02 \|
	\| car \| 80.34 \| 90.6 \|
	\| water \| 46.7 \| 62.37 \|
	\| painting \| 70.67 \| 84.36 \|
	\| sofa \| 63.61 \| 81.32 \|
	\| shelf \| 40.17 \| 57.89 \|
	\| house \| 44.08 \| 62.42 \|
	\| sea \| 40.39 \| 62.65 \|
	\| mirror \| 63.0 \| 76.13 \|
	\| rug \| 61.66 \| 69.01 \|
	\| field \| 25.39 \| 42.59 \|
	\| armchair \| 42.33 \| 59.46 \|
	\| seat \| 62.4 \| 80.02 \|
	\| fence \| 41.01 \| 53.65 \|
	\| desk \| 38.83 \| 74.29 \|
	\| rock \| 26.34 \| 37.11 \|
	\| wardrobe \| 47.4 \| 55.58 \|
	\| lamp \| 56.66 \| 67.21 \|
	\| bathtub \| 75.65 \| 90.84 \|
	\| railing \| 33.4 \| 44.38 \|
	\| cushion \| 53.87 \| 65.93 \|
	\| base \| 18.16 \| 25.65 \|
	\| box \| 19.81 \| 29.66 \|
	\| column \| 45.73 \| 55.49 \|
	\| signboard \| 32.91 \| 41.38 \|
	\| chest of drawers \| 32.33 \| 46.02 \|
	\| counter \| 23.32 \| 34.02 \|
	\| sand \| 46.29 \| 61.95 \|
	\| sink \| 65.56 \| 75.86 \|
	\| skyscraper \| 49.34 \| 59.54 \|
	\| fireplace \| 71.18 \| 91.98 \|
	\| refrigerator \| 71.04 \| 82.45 \|
	\| grandstand \| 41.04 \| 65.07 \|
	\| path \| 18.4 \| 24.94 \|
	\| stairs \| 29.33 \| 46.82 \|
	\| runway \| 67.64 \| 86.98 \|
	\| case \| 31.0 \| 34.97 \|
	\| pool table \| 91.56 \| 96.03 \|
	\| pillow \| 56.49 \| 75.36 \|
	\| screen door \| 66.02 \| 84.44 \|
	\| stairway \| 18.34 \| 19.5 \|
	\| river \| 14.07 \| 32.99 \|
	\| bridge \| 66.45 \| 81.38 \|
	\| bookcase \| 33.17 \| 59.38 \|
	\| blind \| 39.64 \| 43.55 \|
	\| coffee table \| 63.85 \| 76.74 \|
	\| toilet \| 81.53 \| 87.26 \|
	\| flower \| 34.8 \| 52.11 \|
	\| book \| 44.04 \| 66.1 \|
	\| hill \| 9.36 \| 16.78 \|
	\| bench \| 38.72 \| 45.63 \|
	\| countertop \| 52.87 \| 62.12 \|
	\| stove \| 73.83 \| 78.41 \|
	\| palm \| 44.46 \| 67.38 \|
	\| kitchen island \| 41.07 \| 59.81 \|
	\| computer \| 53.7 \| 62.59 \|
	\| swivel chair \| 44.31 \| 61.17 \|
	\| boat \| 40.74 \| 43.03 \|
	\| bar \| 15.12 \| 18.1 \|
	\| arcade machine \| 61.03 \| 66.93 \|
	\| hovel \| 8.27 \| 9.31 \|
	\| bus \| 78.33 \| 89.19 \|
	\| towel \| 56.26 \| 70.63 \|
	\| light \| 46.8 \| 62.49 \|
	\| truck \| 28.82 \| 43.87 \|
	\| tower \| 39.52 \| 51.8 \|
	\| chandelier \| 50.8 \| 54.62 \|
	\| awning \| 24.1 \| 34.26 \|
	\| streetlight \| 25.14 \| 31.58 \|
	\| booth \| 30.21 \| 36.75 \|
	\| television receiver \| 68.11 \| 83.09 \|
	\| airplane \| 55.2 \| 61.97 \|
	\| dirt track \| 3.67 \| 10.67 \|
	\| apparel \| 30.03 \| 44.85 \|
	\| pole \| 23.96 \| 34.73 \|
	\| land \| 1.46 \| 1.74 \|
	\| bannister \| 15.42 \| 21.89 \|
	\| escalator \| 19.13 \| 20.94 \|
	\| ottoman \| 30.6 \| 37.14 \|
	\| bottle \| 22.87 \| 32.94 \|
	\| buffet \| 44.64 \| 50.1 \|
	\| poster \| 29.47 \| 36.13 \|
	\| stage \| 13.78 \| 26.73 \|
	\| van \| 22.95 \| 26.04 \|
	\| ship \| 64.25 \| 88.91 \|
	\| fountain \| 11.61 \| 12.35 \|
	\| conveyer belt \| 59.13 \| 86.76 \|
	\| canopy \| 12.62 \| 15.96 \|
	\| washer \| 60.08 \| 70.93 \|
	\| plaything \| 15.0 \| 19.74 \|
	\| swimming pool \| 34.87 \| 39.69 \|
	\| stool \| 36.48 \| 49.19 \|
	\| barrel \| 44.71 \| 54.07 \|
	\| basket \| 26.51 \| 38.67 \|
	\| waterfall \| 65.06 \| 69.63 \|
	\| tent \| 91.9 \| 96.84 \|
	\| bag \| 8.95 \| 13.14 \|
	\| minibike \| 59.62 \| 79.77 \|
	\| cradle \| 75.65 \| 96.93 \|
	\| oven \| 51.64 \| 67.37 \|
	\| ball \| 37.49 \| 50.6 \|
	\| food \| 57.95 \| 68.93 \|
	\| step \| 9.41 \| 12.0 \|
	\| tank \| 36.58 \| 37.69 \|
	\| trade name \| 20.71 \| 26.15 \|
	\| microwave \| 36.36 \| 39.7 \|
	\| pot \| 48.34 \| 55.69 \|
	\| animal \| 44.91 \| 46.43 \|
	\| bicycle \| 50.45 \| 64.76 \|
	\| lake \| 42.11 \| 42.24 \|
	\| dishwasher \| 65.75 \| 71.86 \|
	\| screen \| 76.87 \| 85.9 \|
	\| blanket \| 13.74 \| 20.54 \|
	\| sculpture \| 54.03 \| 78.13 \|
	\| hood \| 58.52 \| 64.97 \|
	\| sconce \| 33.22 \| 38.01 \|
	\| vase \| 32.57 \| 52.84 \|
	\| traffic light \| 27.32 \| 53.07 \|
	\| tray \| 7.84 \| 11.56 \|
	\| ashcan \| 38.35 \| 55.2 \|
	\| fan \| 57.41 \| 70.97 \|
	\| pier \| 42.05 \| 46.34 \|
	\| crt screen \| 12.55 \| 33.71 \|
	\| plate \| 46.29 \| 50.72 \|
	\| monitor \| 8.62 \| 9.89 \|
	\| bulletin board \| 36.45 \| 58.03 \|
	\| shower \| 2.34 \| 6.28 \|
	\| radiator \| 47.06 \| 54.11 \|
	\| glass \| 12.79 \| 14.58 \|
	\| clock \| 19.92 \| 29.93 \|
	\| flag \| 28.56 \| 32.4 \|
	+---------------------+-------+-------+
	2023/11/27 17:15:32 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.6400 mIoU: 44.7800 mAcc: 56.0200 data_time: 0.0018 time: 0.7639
	2023/11/27 17:23:37 - mmengine - INFO - Iter(train) [ 35500/120000] base_lr: 1.6024e-04 lr: 1.6385e-05 eta: 22:45:41 time: 0.9702 data_time: 0.0089 memory: 8148 grad_norm: 0.0342 loss: 0.0077 semantic_segmentation_loss_cls: 0.0077
	2023/11/27 17:31:41 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 17:31:41 - mmengine - INFO - Iter(train) [ 36000/120000] base_lr: 1.5919e-04 lr: 1.6290e-05 eta: 22:37:34 time: 0.9701 data_time: 0.0089 memory: 8148 grad_norm: 0.0338 loss: 0.0077 semantic_segmentation_loss_cls: 0.0077
	2023/11/27 17:39:46 - mmengine - INFO - Iter(train) [ 36500/120000] base_lr: 1.5814e-04 lr: 1.6194e-05 eta: 22:29:30 time: 0.9702 data_time: 0.0089 memory: 8148 grad_norm: 0.0336 loss: 0.0076 semantic_segmentation_loss_cls: 0.0076
	2023/11/27 17:47:51 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 17:47:51 - mmengine - INFO - Iter(train) [ 37000/120000] base_lr: 1.5708e-04 lr: 1.6098e-05 eta: 22:21:24 time: 0.9701 data_time: 0.0089 memory: 8148 grad_norm: 0.0334 loss: 0.0076 semantic_segmentation_loss_cls: 0.0076
	2023/11/27 17:55:56 - mmengine - INFO - Iter(train) [ 37500/120000] base_lr: 1.5600e-04 lr: 1.6000e-05 eta: 22:13:19 time: 0.9700 data_time: 0.0089 memory: 8148 grad_norm: 0.0330 loss: 0.0075 semantic_segmentation_loss_cls: 0.0075
	2023/11/27 18:04:01 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 18:04:01 - mmengine - INFO - Iter(train) [ 38000/120000] base_lr: 1.5492e-04 lr: 1.5902e-05 eta: 22:05:15 time: 0.9702 data_time: 0.0089 memory: 8148 grad_norm: 0.0326 loss: 0.0075 semantic_segmentation_loss_cls: 0.0075
	2023/11/27 18:12:06 - mmengine - INFO - Iter(train) [ 38500/120000] base_lr: 1.5383e-04 lr: 1.5803e-05 eta: 21:57:09 time: 0.9701 data_time: 0.0089 memory: 8148 grad_norm: 0.0323 loss: 0.0074 semantic_segmentation_loss_cls: 0.0074
	2023/11/27 18:20:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 18:20:10 - mmengine - INFO - Iter(train) [ 39000/120000] base_lr: 1.5273e-04 lr: 1.5703e-05 eta: 21:49:05 time: 0.9702 data_time: 0.0089 memory: 8148 grad_norm: 0.0322 loss: 0.0074 semantic_segmentation_loss_cls: 0.0074
	2023/11/27 18:28:15 - mmengine - INFO - Iter(train) [ 39500/120000] base_lr: 1.5162e-04 lr: 1.5602e-05 eta: 21:40:59 time: 0.9694 data_time: 0.0082 memory: 8148 grad_norm: 0.0322 loss: 0.0074 semantic_segmentation_loss_cls: 0.0074
	2023/11/27 18:36:20 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_072624
	2023/11/27 18:36:20 - mmengine - INFO - Iter(train) [ 40000/120000] base_lr: 1.5050e-04 lr: 1.5500e-05 eta: 21:32:53 time: 0.9694 data_time: 0.0082 memory: 8148 grad_norm: 0.0324 loss: 0.0073 semantic_segmentation_loss_cls: 0.0073
	2023/11/27 18:36:20 - mmengine - INFO - Saving checkpoint at 40000 iterations
	2023/11/27 18:39:41 - mmengine - INFO - per class results:
	2023/11/27 18:39:41 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 75.77 \| 89.21 \|
	\| building \| 79.72 \| 90.4 \|
	\| sky \| 93.04 \| 97.9 \|
	\| floor \| 80.04 \| 89.41 \|
	\| tree \| 70.43 \| 83.09 \|
	\| ceiling \| 82.85 \| 92.91 \|
	\| road \| 82.38 \| 89.75 \|
	\| bed \| 87.18 \| 92.59 \|
	\| windowpane \| 59.15 \| 77.02 \|
	\| grass \| 61.43 \| 70.8 \|
	\| cabinet \| 58.0 \| 71.11 \|
	\| sidewalk \| 65.25 \| 78.73 \|
	\| person \| 78.08 \| 90.37 \|
	\| earth \| 32.44 \| 39.55 \|
	\| door \| 50.35 \| 65.13 \|
	\| table \| 58.57 \| 75.31 \|
	\| mountain \| 52.68 \| 72.32 \|
	\| plant \| 45.77 \| 61.79 \|
	\| curtain \| 71.19 \| 81.13 \|
	\| chair \| 54.79 \| 70.01 \|
	\| car \| 81.18 \| 89.07 \|
	\| water \| 48.05 \| 62.86 \|
	\| painting \| 68.33 \| 83.92 \|
	\| sofa \| 58.85 \| 66.88 \|
	\| shelf \| 40.0 \| 61.3 \|
	\| house \| 34.69 \| 44.29 \|
	\| sea \| 48.01 \| 81.41 \|
	\| mirror \| 63.33 \| 72.86 \|
	\| rug \| 62.5 \| 72.75 \|
	\| field \| 27.4 \| 59.97 \|
	\| armchair \| 43.27 \| 72.45 \|
	\| seat \| 61.51 \| 80.74 \|
	\| fence \| 38.09 \| 58.8 \|
	\| desk \| 44.37 \| 63.84 \|
	\| rock \| 34.34 \| 43.21 \|
	\| wardrobe \| 46.33 \| 67.41 \|
	\| lamp \| 60.77 \| 69.39 \|
	\| bathtub \| 76.74 \| 81.15 \|
	\| railing \| 31.33 \| 47.72 \|
	\| cushion \| 57.21 \| 71.48 \|
	\| base \| 23.59 \| 33.45 \|
	\| box \| 19.43 \| 24.98 \|
	\| column \| 43.88 \| 66.2 \|
	\| signboard \| 33.78 \| 51.66 \|
	\| chest of drawers \| 36.78 \| 45.8 \|
	\| counter \| 18.74 \| 22.31 \|
	\| sand \| 42.67 \| 67.77 \|
	\| sink \| 68.25 \| 77.23 \|
	\| skyscraper \| 39.45 \| 46.97 \|
	\| fireplace \| 70.0 \| 84.67 \|
	\| refrigerator \| 64.7 \| 71.01 \|
	\| grandstand \| 29.01 \| 68.87 \|
	\| path \| 18.88 \| 30.09 \|
	\| stairs \| 22.56 \| 29.63 \|
	\| runway \| 66.08 \| 80.89 \|
	\| case \| 44.74 \| 55.29 \|
	\| pool table \| 88.69 \| 95.22 \|
	\| pillow \| 52.68 \| 69.98 \|
	\| screen door \| 67.49 \| 73.4 \|
	\| stairway \| 31.83 \| 40.63 \|
	\| river \| 16.22 \| 27.54 \|
	\| bridge \| 34.29 \| 42.43 \|
	\| bookcase \| 32.29 \| 72.97 \|
	\| blind \| 38.58 \| 43.6 \|
	\| coffee table \| 65.15 \| 80.75 \|
	\| toilet \| 82.24 \| 86.89 \|
	\| flower \| 34.67 \| 53.5 \|
	\| book \| 38.28 \| 59.06 \|
	\| hill \| 4.0 \| 6.15 \|
	\| bench \| 45.0 \| 58.06 \|
	\| countertop \| 48.01 \| 65.25 \|
	\| stove \| 67.83 \| 72.25 \|
	\| palm \| 43.94 \| 60.07 \|
	\| kitchen island \| 32.65 \| 38.65 \|
	\| computer \| 56.49 \| 67.26 \|
	\| swivel chair \| 44.9 \| 66.23 \|
	\| boat \| 44.79 \| 48.21 \|
	\| bar \| 11.92 \| 13.29 \|
	\| arcade machine \| 53.73 \| 57.32 \|
	\| hovel \| 7.92 \| 10.44 \|
	\| bus \| 83.62 \| 94.85 \|
	\| towel \| 60.44 \| 68.45 \|
	\| light \| 50.71 \| 62.12 \|
	\| truck \| 22.05 \| 30.68 \|
	\| tower \| 28.0 \| 41.91 \|
	\| chandelier \| 62.92 \| 78.65 \|
	\| awning \| 23.72 \| 26.05 \|
	\| streetlight \| 30.59 \| 52.7 \|
	\| booth \| 32.43 \| 33.34 \|
	\| television receiver \| 55.52 \| 80.59 \|
	\| airplane \| 51.18 \| 62.86 \|
	\| dirt track \| 1.48 \| 2.3 \|
	\| apparel \| 30.09 \| 38.75 \|
	\| pole \| 17.96 \| 22.84 \|
	\| land \| 3.19 \| 4.16 \|
	\| bannister \| 11.66 \| 19.5 \|
	\| escalator \| 24.8 \| 29.5 \|
	\| ottoman \| 43.2 \| 64.02 \|
	\| bottle \| 18.88 \| 25.13 \|
	\| buffet \| 41.5 \| 47.95 \|
	\| poster \| 33.85 \| 44.04 \|
	\| stage \| 12.67 \| 19.91 \|
	\| van \| 41.67 \| 59.64 \|
	\| ship \| 54.17 \| 75.26 \|
	\| fountain \| 6.86 \| 7.32 \|
	\| conveyer belt \| 37.92 \| 91.43 \|
	\| canopy \| 19.1 \| 21.3 \|
	\| washer \| 68.64 \| 70.72 \|
	\| plaything \| 25.03 \| 42.16 \|
	\| swimming pool \| 48.11 \| 74.17 \|
	\| stool \| 41.99 \| 58.99 \|
	\| barrel \| 20.93 \| 71.91 \|
	\| basket \| 28.12 \| 39.79 \|
	\| waterfall \| 46.92 \| 58.57 \|
	\| tent \| 83.47 \| 98.87 \|
	\| bag \| 10.6 \| 11.99 \|
	\| minibike \| 59.49 \| 74.11 \|
	\| cradle \| 71.26 \| 85.52 \|
	\| oven \| 46.37 \| 52.68 \|
	\| ball \| 36.14 \| 42.1 \|
	\| food \| 57.88 \| 76.3 \|
	\| step \| 20.46 \| 26.17 \|
	\| tank \| 33.8 \| 36.4 \|
	\| trade name \| 26.91 \| 31.78 \|
	\| microwave \| 37.84 \| 40.74 \|
	\| pot \| 50.37 \| 56.83 \|
	\| animal \| 49.67 \| 54.61 \|
	\| bicycle \| 46.56 \| 78.46 \|
	\| lake \| 55.87 \| 61.87 \|
	\| dishwasher \| 64.25 \| 74.84 \|
	\| screen \| 67.86 \| 88.32 \|
	\| blanket \| 16.95 \| 18.67 \|
	\| sculpture \| 54.22 \| 75.59 \|
	\| hood \| 61.53 \| 67.31 \|
	\| sconce \| 44.86 \| 64.71 \|
	\| vase \| 32.63 \| 61.73 \|
	\| traffic light \| 31.36 \| 51.08 \|
	\| tray \| 3.81 \| 4.63 \|
	\| ashcan \| 35.85 \| 48.17 \|
	\| fan \| 58.89 \| 68.32 \|
	\| pier \| 59.59 \| 71.92 \|
	\| crt screen \| 8.28 \| 13.26 \|
	\| plate \| 46.38 \| 58.45 \|
	\| monitor \| 23.6 \| 27.16 \|
	\| bulletin board \| 34.35 \| 42.88 \|
	\| shower \| 2.33 \| 7.57 \|
	\| radiator \| 42.04 \| 45.39 \|
	\| glass \| 12.98 \| 14.5 \|
	\| clock \| 17.33 \| 23.05 \|
	\| flag \| 28.25 \| 31.17 \|
	+---------------------+-------+-------+
	2023/11/27 18:39:41 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.0800 mIoU: 44.4400 mAcc: 56.7000 data_time: 0.0020 time: 0.7641
	2023/11/27 20:58:35 - mmengine - INFO - Iter(train) [ 40500/120000] base_lr: 1.4938e-04 lr: 1.5398e-05 eta: 21:13:56 time: 0.9684 data_time: 0.0081 memory: 8153 grad_norm: 0.0323 loss: 0.0073 semantic_segmentation_loss_cls: 0.0073
	2023/11/27 21:06:37 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 21:06:37 - mmengine - INFO - Iter(train) [ 41000/120000] base_lr: 1.4824e-04 lr: 1.5295e-05 eta: 21:06:55 time: 0.9676 data_time: 0.0080 memory: 8153 grad_norm: 0.0319 loss: 0.0072 semantic_segmentation_loss_cls: 0.0072
	2023/11/27 21:14:40 - mmengine - INFO - Iter(train) [ 41500/120000] base_lr: 1.4710e-04 lr: 1.5191e-05 eta: 21:00:36 time: 0.9672 data_time: 0.0079 memory: 8153 grad_norm: 0.0318 loss: 0.0072 semantic_segmentation_loss_cls: 0.0072
	2023/11/27 21:22:43 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 21:22:43 - mmengine - INFO - Iter(train) [ 42000/120000] base_lr: 1.4595e-04 lr: 1.5086e-05 eta: 20:53:23 time: 0.9667 data_time: 0.0078 memory: 8153 grad_norm: 0.0318 loss: 0.0072 semantic_segmentation_loss_cls: 0.0072
	2023/11/27 21:30:46 - mmengine - INFO - Iter(train) [ 42500/120000] base_lr: 1.4479e-04 lr: 1.4981e-05 eta: 20:45:55 time: 0.9663 data_time: 0.0077 memory: 8153 grad_norm: 0.0316 loss: 0.0071 semantic_segmentation_loss_cls: 0.0071
	2023/11/27 21:38:50 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 21:38:50 - mmengine - INFO - Iter(train) [ 43000/120000] base_lr: 1.4362e-04 lr: 1.4875e-05 eta: 20:38:24 time: 0.9660 data_time: 0.0076 memory: 8153 grad_norm: 0.0311 loss: 0.0070 semantic_segmentation_loss_cls: 0.0070
	2023/11/27 21:46:53 - mmengine - INFO - Iter(train) [ 43500/120000] base_lr: 1.4245e-04 lr: 1.4768e-05 eta: 20:30:42 time: 0.9657 data_time: 0.0075 memory: 8153 grad_norm: 0.0304 loss: 0.0070 semantic_segmentation_loss_cls: 0.0070
	2023/11/27 21:54:57 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 21:54:57 - mmengine - INFO - Iter(train) [ 44000/120000] base_lr: 1.4127e-04 lr: 1.4661e-05 eta: 20:22:58 time: 0.9655 data_time: 0.0074 memory: 8153 grad_norm: 0.0299 loss: 0.0070 semantic_segmentation_loss_cls: 0.0070
	2023/11/27 22:03:00 - mmengine - INFO - Iter(train) [ 44500/120000] base_lr: 1.4008e-04 lr: 1.4553e-05 eta: 20:15:04 time: 0.9661 data_time: 0.0074 memory: 8153 grad_norm: 0.0296 loss: 0.0069 semantic_segmentation_loss_cls: 0.0069
	2023/11/27 22:11:04 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 22:11:04 - mmengine - INFO - Iter(train) [ 45000/120000] base_lr: 1.3889e-04 lr: 1.4444e-05 eta: 20:07:10 time: 0.9666 data_time: 0.0074 memory: 8153 grad_norm: 0.0296 loss: 0.0069 semantic_segmentation_loss_cls: 0.0069
	2023/11/27 22:14:18 - mmengine - INFO - per class results:
	2023/11/27 22:14:18 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.71 \| 88.51 \|
	\| building \| 81.45 \| 91.77 \|
	\| sky \| 93.23 \| 98.25 \|
	\| floor \| 79.56 \| 90.9 \|
	\| tree \| 71.87 \| 85.52 \|
	\| ceiling \| 82.8 \| 93.69 \|
	\| road \| 81.39 \| 87.29 \|
	\| bed \| 87.53 \| 94.86 \|
	\| windowpane \| 61.44 \| 76.67 \|
	\| grass \| 64.49 \| 73.84 \|
	\| cabinet \| 57.79 \| 69.32 \|
	\| sidewalk \| 65.83 \| 81.18 \|
	\| person \| 77.36 \| 91.12 \|
	\| earth \| 37.61 \| 60.48 \|
	\| door \| 49.0 \| 61.5 \|
	\| table \| 57.97 \| 70.71 \|
	\| mountain \| 54.54 \| 66.74 \|
	\| plant \| 47.14 \| 53.39 \|
	\| curtain \| 72.62 \| 83.81 \|
	\| chair \| 57.21 \| 72.27 \|
	\| car \| 80.48 \| 88.77 \|
	\| water \| 54.69 \| 72.72 \|
	\| painting \| 69.6 \| 85.44 \|
	\| sofa \| 60.66 \| 80.32 \|
	\| shelf \| 44.37 \| 62.61 \|
	\| house \| 50.26 \| 72.94 \|
	\| sea \| 53.32 \| 72.95 \|
	\| mirror \| 66.48 \| 76.86 \|
	\| rug \| 63.97 \| 75.75 \|
	\| field \| 33.26 \| 58.9 \|
	\| armchair \| 35.9 \| 47.7 \|
	\| seat \| 63.77 \| 72.22 \|
	\| fence \| 38.01 \| 48.17 \|
	\| desk \| 46.33 \| 77.45 \|
	\| rock \| 36.88 \| 53.24 \|
	\| wardrobe \| 50.04 \| 71.25 \|
	\| lamp \| 59.38 \| 71.94 \|
	\| bathtub \| 74.92 \| 79.88 \|
	\| railing \| 32.85 \| 46.21 \|
	\| cushion \| 50.3 \| 57.8 \|
	\| base \| 16.35 \| 20.53 \|
	\| box \| 20.19 \| 25.92 \|
	\| column \| 49.19 \| 60.29 \|
	\| signboard \| 34.02 \| 45.63 \|
	\| chest of drawers \| 43.52 \| 73.47 \|
	\| counter \| 24.73 \| 35.31 \|
	\| sand \| 40.65 \| 51.61 \|
	\| sink \| 69.77 \| 78.85 \|
	\| skyscraper \| 45.86 \| 54.1 \|
	\| fireplace \| 72.2 \| 88.42 \|
	\| refrigerator \| 70.9 \| 86.07 \|
	\| grandstand \| 33.77 \| 72.01 \|
	\| path \| 24.31 \| 39.58 \|
	\| stairs \| 26.42 \| 31.87 \|
	\| runway \| 60.98 \| 66.97 \|
	\| case \| 43.02 \| 61.63 \|
	\| pool table \| 91.15 \| 94.9 \|
	\| pillow \| 53.36 \| 71.94 \|
	\| screen door \| 53.35 \| 56.84 \|
	\| stairway \| 32.53 \| 42.18 \|
	\| river \| 12.95 \| 24.24 \|
	\| bridge \| 33.22 \| 44.58 \|
	\| bookcase \| 39.38 \| 62.69 \|
	\| blind \| 42.59 \| 48.69 \|
	\| coffee table \| 52.88 \| 84.25 \|
	\| toilet \| 83.18 \| 86.48 \|
	\| flower \| 35.6 \| 55.33 \|
	\| book \| 45.87 \| 59.49 \|
	\| hill \| 7.02 \| 18.16 \|
	\| bench \| 43.42 \| 47.0 \|
	\| countertop \| 50.82 \| 63.52 \|
	\| stove \| 74.57 \| 81.75 \|
	\| palm \| 44.86 \| 58.77 \|
	\| kitchen island \| 46.44 \| 75.39 \|
	\| computer \| 61.43 \| 70.65 \|
	\| swivel chair \| 46.01 \| 60.77 \|
	\| boat \| 58.02 \| 62.4 \|
	\| bar \| 23.16 \| 25.42 \|
	\| arcade machine \| 47.25 \| 48.27 \|
	\| hovel \| 14.69 \| 20.55 \|
	\| bus \| 85.34 \| 89.31 \|
	\| towel \| 60.64 \| 70.3 \|
	\| light \| 49.04 \| 58.88 \|
	\| truck \| 28.0 \| 34.88 \|
	\| tower \| 34.02 \| 54.39 \|
	\| chandelier \| 64.06 \| 79.28 \|
	\| awning \| 24.96 \| 27.28 \|
	\| streetlight \| 29.22 \| 37.63 \|
	\| booth \| 43.31 \| 51.47 \|
	\| television receiver \| 57.09 \| 79.7 \|
	\| airplane \| 55.64 \| 63.11 \|
	\| dirt track \| 10.23 \| 25.99 \|
	\| apparel \| 32.89 \| 44.51 \|
	\| pole \| 23.37 \| 30.58 \|
	\| land \| 0.21 \| 0.25 \|
	\| bannister \| 9.19 \| 15.0 \|
	\| escalator \| 4.13 \| 4.26 \|
	\| ottoman \| 35.78 \| 68.58 \|
	\| bottle \| 21.33 \| 28.33 \|
	\| buffet \| 46.07 \| 56.23 \|
	\| poster \| 24.02 \| 28.82 \|
	\| stage \| 15.57 \| 20.06 \|
	\| van \| 33.86 \| 49.92 \|
	\| ship \| 15.21 \| 16.5 \|
	\| fountain \| 1.54 \| 1.56 \|
	\| conveyer belt \| 46.33 \| 82.93 \|
	\| canopy \| 16.42 \| 18.3 \|
	\| washer \| 68.52 \| 71.74 \|
	\| plaything \| 26.39 \| 37.44 \|
	\| swimming pool \| 22.41 \| 22.5 \|
	\| stool \| 43.39 \| 60.94 \|
	\| barrel \| 62.66 \| 72.66 \|
	\| basket \| 25.16 \| 37.5 \|
	\| waterfall \| 47.85 \| 60.51 \|
	\| tent \| 91.21 \| 96.81 \|
	\| bag \| 8.93 \| 10.32 \|
	\| minibike \| 51.01 \| 53.23 \|
	\| cradle \| 67.94 \| 96.76 \|
	\| oven \| 56.75 \| 69.3 \|
	\| ball \| 38.59 \| 44.6 \|
	\| food \| 46.34 \| 55.26 \|
	\| step \| 9.33 \| 9.83 \|
	\| tank \| 45.45 \| 49.43 \|
	\| trade name \| 17.74 \| 19.97 \|
	\| microwave \| 36.99 \| 40.46 \|
	\| pot \| 36.68 \| 40.48 \|
	\| animal \| 52.96 \| 57.95 \|
	\| bicycle \| 43.63 \| 67.6 \|
	\| lake \| 60.05 \| 62.15 \|
	\| dishwasher \| 67.51 \| 74.74 \|
	\| screen \| 52.65 \| 88.91 \|
	\| blanket \| 15.4 \| 18.93 \|
	\| sculpture \| 61.45 \| 75.72 \|
	\| hood \| 61.99 \| 74.99 \|
	\| sconce \| 39.14 \| 44.73 \|
	\| vase \| 31.02 \| 44.22 \|
	\| traffic light \| 31.21 \| 49.41 \|
	\| tray \| 10.52 \| 14.02 \|
	\| ashcan \| 39.29 \| 52.24 \|
	\| fan \| 57.03 \| 64.62 \|
	\| pier \| 39.94 \| 58.93 \|
	\| crt screen \| 6.25 \| 18.16 \|
	\| plate \| 46.45 \| 60.27 \|
	\| monitor \| 5.26 \| 5.88 \|
	\| bulletin board \| 33.47 \| 66.56 \|
	\| shower \| 1.37 \| 7.65 \|
	\| radiator \| 39.53 \| 46.75 \|
	\| glass \| 11.53 \| 12.49 \|
	\| clock \| 20.82 \| 27.96 \|
	\| flag \| 29.81 \| 37.12 \|
	+---------------------+-------+-------+
	2023/11/27 22:14:18 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.7900 mIoU: 44.8100 mAcc: 56.2800 data_time: 0.0048 time: 0.7680
	2023/11/27 22:22:21 - mmengine - INFO - Iter(train) [ 45500/120000] base_lr: 1.3769e-04 lr: 1.4335e-05 eta: 19:59:45 time: 0.9673 data_time: 0.0080 memory: 8153 grad_norm: 0.0293 loss: 0.0069 semantic_segmentation_loss_cls: 0.0069
	2023/11/27 22:30:25 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 22:30:25 - mmengine - INFO - Iter(train) [ 46000/120000] base_lr: 1.3648e-04 lr: 1.4226e-05 eta: 19:51:42 time: 0.9673 data_time: 0.0080 memory: 8153 grad_norm: 0.0288 loss: 0.0068 semantic_segmentation_loss_cls: 0.0068
	2023/11/27 22:38:28 - mmengine - INFO - Iter(train) [ 46500/120000] base_lr: 1.3527e-04 lr: 1.4115e-05 eta: 19:43:44 time: 0.9674 data_time: 0.0079 memory: 8153 grad_norm: 0.0286 loss: 0.0068 semantic_segmentation_loss_cls: 0.0068
	2023/11/27 22:46:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 22:46:32 - mmengine - INFO - Iter(train) [ 47000/120000] base_lr: 1.3405e-04 lr: 1.4004e-05 eta: 19:35:47 time: 0.9675 data_time: 0.0080 memory: 8153 grad_norm: 0.0286 loss: 0.0068 semantic_segmentation_loss_cls: 0.0068
	2023/11/27 22:54:36 - mmengine - INFO - Iter(train) [ 47500/120000] base_lr: 1.3282e-04 lr: 1.3893e-05 eta: 19:27:51 time: 0.9676 data_time: 0.0079 memory: 8153 grad_norm: 0.0282 loss: 0.0067 semantic_segmentation_loss_cls: 0.0067
	2023/11/27 23:02:40 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 23:02:40 - mmengine - INFO - Iter(train) [ 48000/120000] base_lr: 1.3160e-04 lr: 1.3781e-05 eta: 19:19:52 time: 0.9676 data_time: 0.0079 memory: 8153 grad_norm: 0.0279 loss: 0.0067 semantic_segmentation_loss_cls: 0.0067
	2023/11/27 23:10:44 - mmengine - INFO - Iter(train) [ 48500/120000] base_lr: 1.3036e-04 lr: 1.3669e-05 eta: 19:11:55 time: 0.9678 data_time: 0.0079 memory: 8153 grad_norm: 0.0277 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/27 23:18:48 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 23:18:48 - mmengine - INFO - Iter(train) [ 49000/120000] base_lr: 1.2912e-04 lr: 1.3556e-05 eta: 19:03:55 time: 0.9679 data_time: 0.0079 memory: 8153 grad_norm: 0.0275 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/27 23:26:51 - mmengine - INFO - Iter(train) [ 49500/120000] base_lr: 1.2788e-04 lr: 1.3443e-05 eta: 18:55:53 time: 0.9674 data_time: 0.0073 memory: 8153 grad_norm: 0.0272 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/27 23:34:55 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 23:34:55 - mmengine - INFO - Iter(train) [ 50000/120000] base_lr: 1.2663e-04 lr: 1.3330e-05 eta: 18:47:54 time: 0.9675 data_time: 0.0073 memory: 8153 grad_norm: 0.0273 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/27 23:34:55 - mmengine - INFO - Saving checkpoint at 50000 iterations
	2023/11/27 23:38:17 - mmengine - INFO - per class results:
	2023/11/27 23:38:17 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 75.52 \| 89.22 \|
	\| building \| 81.02 \| 91.83 \|
	\| sky \| 93.25 \| 97.68 \|
	\| floor \| 79.77 \| 90.57 \|
	\| tree \| 73.25 \| 85.53 \|
	\| ceiling \| 82.65 \| 94.72 \|
	\| road \| 83.85 \| 89.95 \|
	\| bed \| 86.31 \| 94.44 \|
	\| windowpane \| 60.03 \| 74.26 \|
	\| grass \| 66.14 \| 83.11 \|
	\| cabinet \| 57.49 \| 67.82 \|
	\| sidewalk \| 64.39 \| 81.2 \|
	\| person \| 78.17 \| 89.74 \|
	\| earth \| 39.03 \| 52.77 \|
	\| door \| 48.67 \| 63.05 \|
	\| table \| 58.71 \| 76.33 \|
	\| mountain \| 51.5 \| 70.15 \|
	\| plant \| 48.56 \| 57.14 \|
	\| curtain \| 72.14 \| 85.52 \|
	\| chair \| 55.54 \| 68.06 \|
	\| car \| 81.65 \| 88.4 \|
	\| water \| 52.86 \| 66.53 \|
	\| painting \| 68.05 \| 87.06 \|
	\| sofa \| 62.03 \| 78.74 \|
	\| shelf \| 39.57 \| 54.38 \|
	\| house \| 34.59 \| 44.04 \|
	\| sea \| 50.83 \| 79.97 \|
	\| mirror \| 64.98 \| 75.89 \|
	\| rug \| 65.53 \| 71.3 \|
	\| field \| 29.05 \| 47.82 \|
	\| armchair \| 38.48 \| 52.19 \|
	\| seat \| 57.36 \| 77.34 \|
	\| fence \| 44.86 \| 66.2 \|
	\| desk \| 45.42 \| 61.98 \|
	\| rock \| 30.62 \| 44.58 \|
	\| wardrobe \| 48.36 \| 69.48 \|
	\| lamp \| 60.5 \| 70.63 \|
	\| bathtub \| 77.65 \| 80.57 \|
	\| railing \| 31.48 \| 40.12 \|
	\| cushion \| 59.38 \| 72.02 \|
	\| base \| 15.91 \| 22.43 \|
	\| box \| 21.29 \| 31.96 \|
	\| column \| 47.67 \| 57.62 \|
	\| signboard \| 34.15 \| 45.1 \|
	\| chest of drawers \| 38.42 \| 53.96 \|
	\| counter \| 24.59 \| 32.33 \|
	\| sand \| 51.96 \| 60.65 \|
	\| sink \| 69.47 \| 76.54 \|
	\| skyscraper \| 46.98 \| 57.95 \|
	\| fireplace \| 74.38 \| 87.71 \|
	\| refrigerator \| 62.23 \| 69.54 \|
	\| grandstand \| 38.43 \| 64.17 \|
	\| path \| 32.31 \| 41.41 \|
	\| stairs \| 30.25 \| 38.82 \|
	\| runway \| 69.29 \| 80.15 \|
	\| case \| 44.05 \| 50.57 \|
	\| pool table \| 90.89 \| 94.99 \|
	\| pillow \| 55.92 \| 71.05 \|
	\| screen door \| 52.48 \| 55.65 \|
	\| stairway \| 29.76 \| 34.11 \|
	\| river \| 14.92 \| 23.88 \|
	\| bridge \| 33.75 \| 44.09 \|
	\| bookcase \| 40.07 \| 62.88 \|
	\| blind \| 35.53 \| 38.21 \|
	\| coffee table \| 63.17 \| 72.88 \|
	\| toilet \| 82.33 \| 87.0 \|
	\| flower \| 34.27 \| 59.26 \|
	\| book \| 42.65 \| 57.52 \|
	\| hill \| 7.76 \| 9.98 \|
	\| bench \| 40.59 \| 46.82 \|
	\| countertop \| 51.53 \| 64.49 \|
	\| stove \| 70.62 \| 74.8 \|
	\| palm \| 48.66 \| 69.62 \|
	\| kitchen island \| 33.68 \| 51.28 \|
	\| computer \| 52.84 \| 59.34 \|
	\| swivel chair \| 41.55 \| 58.03 \|
	\| boat \| 40.48 \| 47.54 \|
	\| bar \| 26.64 \| 30.08 \|
	\| arcade machine \| 58.89 \| 65.94 \|
	\| hovel \| 16.75 \| 18.43 \|
	\| bus \| 84.84 \| 91.94 \|
	\| towel \| 57.95 \| 68.66 \|
	\| light \| 47.33 \| 55.63 \|
	\| truck \| 22.38 \| 29.21 \|
	\| tower \| 24.85 \| 37.46 \|
	\| chandelier \| 62.12 \| 75.49 \|
	\| awning \| 26.7 \| 37.34 \|
	\| streetlight \| 27.82 \| 38.42 \|
	\| booth \| 37.82 \| 42.32 \|
	\| television receiver \| 60.45 \| 76.19 \|
	\| airplane \| 49.61 \| 64.86 \|
	\| dirt track \| 6.03 \| 9.1 \|
	\| apparel \| 20.58 \| 31.43 \|
	\| pole \| 21.54 \| 30.19 \|
	\| land \| 0.25 \| 0.33 \|
	\| bannister \| 10.03 \| 14.64 \|
	\| escalator \| 23.97 \| 28.17 \|
	\| ottoman \| 38.13 \| 53.43 \|
	\| bottle \| 18.3 \| 22.34 \|
	\| buffet \| 39.55 \| 47.18 \|
	\| poster \| 26.9 \| 43.84 \|
	\| stage \| 11.19 \| 24.79 \|
	\| van \| 38.4 \| 55.35 \|
	\| ship \| 56.88 \| 78.15 \|
	\| fountain \| 19.95 \| 21.26 \|
	\| conveyer belt \| 46.11 \| 89.53 \|
	\| canopy \| 12.13 \| 15.43 \|
	\| washer \| 66.08 \| 67.52 \|
	\| plaything \| 22.81 \| 34.49 \|
	\| swimming pool \| 46.65 \| 71.12 \|
	\| stool \| 42.99 \| 57.65 \|
	\| barrel \| 44.59 \| 49.19 \|
	\| basket \| 31.37 \| 43.69 \|
	\| waterfall \| 54.56 \| 63.98 \|
	\| tent \| 92.94 \| 97.6 \|
	\| bag \| 6.66 \| 7.81 \|
	\| minibike \| 42.47 \| 48.1 \|
	\| cradle \| 76.88 \| 90.64 \|
	\| oven \| 47.91 \| 63.13 \|
	\| ball \| 40.08 \| 53.3 \|
	\| food \| 55.08 \| 68.57 \|
	\| step \| 17.39 \| 21.98 \|
	\| tank \| 41.51 \| 49.0 \|
	\| trade name \| 31.8 \| 42.3 \|
	\| microwave \| 38.11 \| 41.44 \|
	\| pot \| 49.14 \| 57.44 \|
	\| animal \| 51.47 \| 56.46 \|
	\| bicycle \| 49.38 \| 72.87 \|
	\| lake \| 60.71 \| 65.33 \|
	\| dishwasher \| 70.74 \| 76.18 \|
	\| screen \| 59.63 \| 86.99 \|
	\| blanket \| 15.43 \| 19.68 \|
	\| sculpture \| 53.59 \| 78.54 \|
	\| hood \| 63.1 \| 68.08 \|
	\| sconce \| 41.16 \| 52.48 \|
	\| vase \| 31.91 \| 45.18 \|
	\| traffic light \| 30.8 \| 55.94 \|
	\| tray \| 14.15 \| 23.61 \|
	\| ashcan \| 39.26 \| 51.03 \|
	\| fan \| 53.62 \| 69.88 \|
	\| pier \| 60.69 \| 80.31 \|
	\| crt screen \| 1.12 \| 1.5 \|
	\| plate \| 49.43 \| 61.61 \|
	\| monitor \| 22.25 \| 28.8 \|
	\| bulletin board \| 36.85 \| 39.4 \|
	\| shower \| 2.35 \| 2.82 \|
	\| radiator \| 45.82 \| 50.8 \|
	\| glass \| 12.04 \| 13.0 \|
	\| clock \| 21.76 \| 27.73 \|
	\| flag \| 29.16 \| 38.58 \|
	+---------------------+-------+-------+
	2023/11/27 23:38:17 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.8100 mIoU: 45.4900 mAcc: 56.5300 data_time: 0.0019 time: 0.7651
	2023/11/27 23:46:21 - mmengine - INFO - Iter(train) [ 50500/120000] base_lr: 1.2537e-04 lr: 1.3216e-05 eta: 18:39:56 time: 0.9677 data_time: 0.0076 memory: 8153 grad_norm: 0.0269 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/27 23:54:25 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/27 23:54:25 - mmengine - INFO - Iter(train) [ 51000/120000] base_lr: 1.2411e-04 lr: 1.3101e-05 eta: 18:31:56 time: 0.9678 data_time: 0.0076 memory: 8153 grad_norm: 0.0268 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/28 00:02:28 - mmengine - INFO - Iter(train) [ 51500/120000] base_lr: 1.2285e-04 lr: 1.2987e-05 eta: 18:23:53 time: 0.9677 data_time: 0.0076 memory: 8153 grad_norm: 0.0268 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/28 00:10:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 00:10:32 - mmengine - INFO - Iter(train) [ 52000/120000] base_lr: 1.2159e-04 lr: 1.2871e-05 eta: 18:15:52 time: 0.9677 data_time: 0.0076 memory: 8153 grad_norm: 0.0267 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/28 00:18:36 - mmengine - INFO - Iter(train) [ 52500/120000] base_lr: 1.2032e-04 lr: 1.2756e-05 eta: 18:07:50 time: 0.9677 data_time: 0.0076 memory: 8153 grad_norm: 0.0266 loss: 0.0066 semantic_segmentation_loss_cls: 0.0066
	2023/11/28 00:26:39 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 00:26:39 - mmengine - INFO - Iter(train) [ 53000/120000] base_lr: 1.1904e-04 lr: 1.2640e-05 eta: 17:59:46 time: 0.9676 data_time: 0.0077 memory: 8153 grad_norm: 0.0260 loss: 0.0065 semantic_segmentation_loss_cls: 0.0065
	2023/11/28 00:34:43 - mmengine - INFO - Iter(train) [ 53500/120000] base_lr: 1.1777e-04 lr: 1.2524e-05 eta: 17:51:44 time: 0.9676 data_time: 0.0077 memory: 8153 grad_norm: 0.0258 loss: 0.0065 semantic_segmentation_loss_cls: 0.0065
	2023/11/28 00:42:47 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 00:42:47 - mmengine - INFO - Iter(train) [ 54000/120000] base_lr: 1.1649e-04 lr: 1.2408e-05 eta: 17:43:40 time: 0.9675 data_time: 0.0077 memory: 8153 grad_norm: 0.0254 loss: 0.0064 semantic_segmentation_loss_cls: 0.0064
	2023/11/28 00:50:51 - mmengine - INFO - Iter(train) [ 54500/120000] base_lr: 1.1521e-04 lr: 1.2292e-05 eta: 17:35:39 time: 0.9675 data_time: 0.0074 memory: 8153 grad_norm: 0.0253 loss: 0.0064 semantic_segmentation_loss_cls: 0.0064
	2023/11/28 00:58:54 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 00:58:54 - mmengine - INFO - Iter(train) [ 55000/120000] base_lr: 1.1392e-04 lr: 1.2175e-05 eta: 17:27:36 time: 0.9674 data_time: 0.0074 memory: 8153 grad_norm: 0.0250 loss: 0.0063 semantic_segmentation_loss_cls: 0.0063
	2023/11/28 01:02:08 - mmengine - INFO - per class results:
	2023/11/28 01:02:08 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.51 \| 88.85 \|
	\| building \| 80.64 \| 92.01 \|
	\| sky \| 93.0 \| 97.95 \|
	\| floor \| 80.68 \| 90.35 \|
	\| tree \| 72.84 \| 86.43 \|
	\| ceiling \| 83.74 \| 93.49 \|
	\| road \| 82.8 \| 91.21 \|
	\| bed \| 87.78 \| 93.55 \|
	\| windowpane \| 58.27 \| 73.1 \|
	\| grass \| 69.26 \| 81.81 \|
	\| cabinet \| 57.33 \| 70.75 \|
	\| sidewalk \| 67.25 \| 77.83 \|
	\| person \| 78.22 \| 90.69 \|
	\| earth \| 37.49 \| 52.44 \|
	\| door \| 48.97 \| 63.51 \|
	\| table \| 57.7 \| 71.91 \|
	\| mountain \| 55.3 \| 70.35 \|
	\| plant \| 48.23 \| 60.36 \|
	\| curtain \| 70.69 \| 82.5 \|
	\| chair \| 55.95 \| 66.45 \|
	\| car \| 81.96 \| 89.07 \|
	\| water \| 45.52 \| 56.45 \|
	\| painting \| 70.39 \| 85.0 \|
	\| sofa \| 60.66 \| 70.16 \|
	\| shelf \| 40.92 \| 57.81 \|
	\| house \| 43.38 \| 61.63 \|
	\| sea \| 51.76 \| 87.09 \|
	\| mirror \| 63.67 \| 71.24 \|
	\| rug \| 65.35 \| 77.17 \|
	\| field \| 31.5 \| 51.08 \|
	\| armchair \| 43.94 \| 67.83 \|
	\| seat \| 58.57 \| 77.38 \|
	\| fence \| 46.0 \| 61.83 \|
	\| desk \| 47.54 \| 64.26 \|
	\| rock \| 36.56 \| 52.98 \|
	\| wardrobe \| 43.8 \| 57.58 \|
	\| lamp \| 60.09 \| 71.91 \|
	\| bathtub \| 76.72 \| 83.17 \|
	\| railing \| 29.13 \| 38.13 \|
	\| cushion \| 57.89 \| 74.3 \|
	\| base \| 24.14 \| 40.69 \|
	\| box \| 16.88 \| 22.29 \|
	\| column \| 48.39 \| 59.64 \|
	\| signboard \| 35.34 \| 47.25 \|
	\| chest of drawers \| 39.36 \| 64.7 \|
	\| counter \| 32.11 \| 53.15 \|
	\| sand \| 49.87 \| 65.39 \|
	\| sink \| 67.89 \| 77.83 \|
	\| skyscraper \| 27.82 \| 31.04 \|
	\| fireplace \| 66.04 \| 91.95 \|
	\| refrigerator \| 65.26 \| 70.64 \|
	\| grandstand \| 35.0 \| 62.45 \|
	\| path \| 27.18 \| 41.29 \|
	\| stairs \| 27.06 \| 37.0 \|
	\| runway \| 68.72 \| 86.21 \|
	\| case \| 39.37 \| 45.47 \|
	\| pool table \| 91.13 \| 95.17 \|
	\| pillow \| 56.49 \| 73.08 \|
	\| screen door \| 59.64 \| 61.46 \|
	\| stairway \| 32.88 \| 39.38 \|
	\| river \| 16.14 \| 28.05 \|
	\| bridge \| 35.42 \| 44.12 \|
	\| bookcase \| 34.24 \| 54.65 \|
	\| blind \| 36.74 \| 41.48 \|
	\| coffee table \| 59.72 \| 84.53 \|
	\| toilet \| 82.9 \| 87.99 \|
	\| flower \| 33.33 \| 48.81 \|
	\| book \| 42.06 \| 63.61 \|
	\| hill \| 5.58 \| 9.75 \|
	\| bench \| 38.89 \| 44.85 \|
	\| countertop \| 53.0 \| 66.42 \|
	\| stove \| 70.82 \| 82.66 \|
	\| palm \| 41.68 \| 57.37 \|
	\| kitchen island \| 40.45 \| 75.61 \|
	\| computer \| 58.36 \| 65.64 \|
	\| swivel chair \| 40.51 \| 54.69 \|
	\| boat \| 41.16 \| 54.45 \|
	\| bar \| 20.4 \| 21.74 \|
	\| arcade machine \| 55.93 \| 62.64 \|
	\| hovel \| 5.65 \| 5.86 \|
	\| bus \| 89.15 \| 95.36 \|
	\| towel \| 58.3 \| 73.58 \|
	\| light \| 47.08 \| 56.64 \|
	\| truck \| 26.21 \| 44.34 \|
	\| tower \| 29.92 \| 48.69 \|
	\| chandelier \| 62.66 \| 71.04 \|
	\| awning \| 23.22 \| 27.24 \|
	\| streetlight \| 28.25 \| 36.2 \|
	\| booth \| 43.02 \| 59.15 \|
	\| television receiver \| 55.25 \| 80.09 \|
	\| airplane \| 56.33 \| 62.53 \|
	\| dirt track \| 4.49 \| 20.89 \|
	\| apparel \| 28.08 \| 42.56 \|
	\| pole \| 21.76 \| 31.45 \|
	\| land \| 0.86 \| 1.14 \|
	\| bannister \| 12.06 \| 15.61 \|
	\| escalator \| 26.03 \| 31.29 \|
	\| ottoman \| 49.27 \| 64.41 \|
	\| bottle \| 19.18 \| 25.01 \|
	\| buffet \| 40.45 \| 48.97 \|
	\| poster \| 32.62 \| 41.03 \|
	\| stage \| 12.51 \| 24.28 \|
	\| van \| 41.08 \| 55.27 \|
	\| ship \| 51.2 \| 80.48 \|
	\| fountain \| 16.42 \| 17.12 \|
	\| conveyer belt \| 62.71 \| 85.95 \|
	\| canopy \| 25.67 \| 28.31 \|
	\| washer \| 68.42 \| 72.25 \|
	\| plaything \| 25.7 \| 32.65 \|
	\| swimming pool \| 35.55 \| 85.58 \|
	\| stool \| 41.23 \| 60.72 \|
	\| barrel \| 30.39 \| 61.05 \|
	\| basket \| 35.66 \| 45.29 \|
	\| waterfall \| 37.3 \| 44.09 \|
	\| tent \| 80.02 \| 98.34 \|
	\| bag \| 8.04 \| 10.15 \|
	\| minibike \| 57.6 \| 70.5 \|
	\| cradle \| 71.18 \| 95.05 \|
	\| oven \| 33.64 \| 41.66 \|
	\| ball \| 39.66 \| 55.09 \|
	\| food \| 55.12 \| 68.41 \|
	\| step \| 8.41 \| 10.14 \|
	\| tank \| 48.69 \| 50.14 \|
	\| trade name \| 20.97 \| 24.23 \|
	\| microwave \| 36.1 \| 37.98 \|
	\| pot \| 49.13 \| 58.93 \|
	\| animal \| 50.4 \| 53.26 \|
	\| bicycle \| 47.99 \| 74.39 \|
	\| lake \| 42.91 \| 57.13 \|
	\| dishwasher \| 62.37 \| 67.71 \|
	\| screen \| 63.45 \| 87.33 \|
	\| blanket \| 10.31 \| 12.14 \|
	\| sculpture \| 51.13 \| 77.53 \|
	\| hood \| 56.33 \| 61.87 \|
	\| sconce \| 44.09 \| 52.28 \|
	\| vase \| 36.78 \| 55.97 \|
	\| traffic light \| 28.94 \| 40.49 \|
	\| tray \| 15.53 \| 21.05 \|
	\| ashcan \| 35.08 \| 46.31 \|
	\| fan \| 57.06 \| 66.12 \|
	\| pier \| 45.57 \| 65.36 \|
	\| crt screen \| 11.52 \| 24.73 \|
	\| plate \| 53.46 \| 67.3 \|
	\| monitor \| 19.92 \| 24.1 \|
	\| bulletin board \| 16.52 \| 16.83 \|
	\| shower \| 2.17 \| 3.36 \|
	\| radiator \| 41.19 \| 46.25 \|
	\| glass \| 15.6 \| 17.78 \|
	\| clock \| 19.62 \| 23.05 \|
	\| flag \| 30.39 \| 33.82 \|
	+---------------------+-------+-------+
	2023/11/28 01:02:08 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.8700 mIoU: 44.9800 mAcc: 57.0600 data_time: 0.0019 time: 0.7654
	2023/11/28 01:10:12 - mmengine - INFO - Iter(train) [ 55500/120000] base_lr: 1.1264e-04 lr: 1.2058e-05 eta: 17:19:44 time: 0.9680 data_time: 0.0080 memory: 8153 grad_norm: 0.0245 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:18:16 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 01:18:16 - mmengine - INFO - Iter(train) [ 56000/120000] base_lr: 1.1135e-04 lr: 1.1941e-05 eta: 17:11:40 time: 0.9679 data_time: 0.0080 memory: 8153 grad_norm: 0.0242 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:26:19 - mmengine - INFO - Iter(train) [ 56500/120000] base_lr: 1.1006e-04 lr: 1.1824e-05 eta: 17:03:36 time: 0.9679 data_time: 0.0081 memory: 8153 grad_norm: 0.0238 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:34:23 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 01:34:23 - mmengine - INFO - Iter(train) [ 57000/120000] base_lr: 1.0877e-04 lr: 1.1706e-05 eta: 16:55:34 time: 0.9680 data_time: 0.0081 memory: 8153 grad_norm: 0.0237 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:42:26 - mmengine - INFO - Iter(train) [ 57500/120000] base_lr: 1.0748e-04 lr: 1.1589e-05 eta: 16:47:28 time: 0.9679 data_time: 0.0081 memory: 8153 grad_norm: 0.0237 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:50:30 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 01:50:30 - mmengine - INFO - Iter(train) [ 58000/120000] base_lr: 1.0618e-04 lr: 1.1471e-05 eta: 16:39:26 time: 0.9680 data_time: 0.0081 memory: 8153 grad_norm: 0.0236 loss: 0.0062 semantic_segmentation_loss_cls: 0.0062
	2023/11/28 01:58:34 - mmengine - INFO - Iter(train) [ 58500/120000] base_lr: 1.0489e-04 lr: 1.1354e-05 eta: 16:31:22 time: 0.9679 data_time: 0.0081 memory: 8153 grad_norm: 0.0234 loss: 0.0061 semantic_segmentation_loss_cls: 0.0061
	2023/11/28 02:06:38 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 02:06:38 - mmengine - INFO - Iter(train) [ 59000/120000] base_lr: 1.0359e-04 lr: 1.1236e-05 eta: 16:23:20 time: 0.9680 data_time: 0.0081 memory: 8153 grad_norm: 0.0231 loss: 0.0061 semantic_segmentation_loss_cls: 0.0061
	2023/11/28 02:14:42 - mmengine - INFO - Iter(train) [ 59500/120000] base_lr: 1.0230e-04 lr: 1.1118e-05 eta: 16:15:17 time: 0.9673 data_time: 0.0075 memory: 8153 grad_norm: 0.0231 loss: 0.0061 semantic_segmentation_loss_cls: 0.0061
	2023/11/28 02:22:46 - mmengine - INFO - Exp name: univision_single_semseg_base_20231127_204948
	2023/11/28 02:22:46 - mmengine - INFO - Iter(train) [ 60000/120000] base_lr: 1.0100e-04 lr: 1.1000e-05 eta: 16:07:13 time: 0.9674 data_time: 0.0075 memory: 8153 grad_norm: 0.0229 loss: 0.0060 semantic_segmentation_loss_cls: 0.0060
	2023/11/28 02:22:46 - mmengine - INFO - Saving checkpoint at 60000 iterations
	2023/11/28 02:26:07 - mmengine - INFO - per class results:
	2023/11/28 02:26:07 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.3 \| 89.48 \|
	\| building \| 81.89 \| 91.32 \|
	\| sky \| 92.92 \| 97.94 \|
	\| floor \| 80.7 \| 90.51 \|
	\| tree \| 73.91 \| 88.35 \|
	\| ceiling \| 83.42 \| 92.88 \|
	\| road \| 82.46 \| 90.56 \|
	\| bed \| 87.59 \| 94.94 \|
	\| windowpane \| 59.75 \| 75.38 \|
	\| grass \| 67.24 \| 78.67 \|
	\| cabinet \| 58.93 \| 68.15 \|
	\| sidewalk \| 67.98 \| 79.1 \|
	\| person \| 77.51 \| 90.6 \|
	\| earth \| 40.3 \| 53.24 \|
	\| door \| 50.08 \| 62.96 \|
	\| table \| 60.62 \| 74.24 \|
	\| mountain \| 55.14 \| 69.69 \|
	\| plant \| 51.98 \| 65.77 \|
	\| curtain \| 70.73 \| 80.79 \|
	\| chair \| 56.72 \| 70.65 \|
	\| car \| 81.52 \| 88.99 \|
	\| water \| 53.9 \| 66.51 \|
	\| painting \| 68.8 \| 84.61 \|
	\| sofa \| 61.98 \| 75.68 \|
	\| shelf \| 46.03 \| 65.91 \|
	\| house \| 45.98 \| 60.64 \|
	\| sea \| 54.44 \| 84.74 \|
	\| mirror \| 64.79 \| 78.53 \|
	\| rug \| 65.63 \| 74.59 \|
	\| field \| 27.81 \| 53.2 \|
	\| armchair \| 43.45 \| 68.83 \|
	\| seat \| 63.36 \| 81.19 \|
	\| fence \| 42.46 \| 58.96 \|
	\| desk \| 44.96 \| 65.44 \|
	\| rock \| 36.9 \| 58.01 \|
	\| wardrobe \| 43.79 \| 60.79 \|
	\| lamp \| 61.21 \| 71.35 \|
	\| bathtub \| 75.23 \| 78.39 \|
	\| railing \| 31.76 \| 43.2 \|
	\| cushion \| 59.17 \| 72.32 \|
	\| base \| 17.27 \| 20.36 \|
	\| box \| 23.67 \| 37.23 \|
	\| column \| 38.47 \| 42.55 \|
	\| signboard \| 35.25 \| 50.83 \|
	\| chest of drawers \| 41.74 \| 60.78 \|
	\| counter \| 9.19 \| 10.6 \|
	\| sand \| 50.62 \| 63.51 \|
	\| sink \| 70.72 \| 80.17 \|
	\| skyscraper \| 47.74 \| 58.87 \|
	\| fireplace \| 66.79 \| 83.88 \|
	\| refrigerator \| 71.49 \| 78.8 \|
	\| grandstand \| 35.79 \| 71.79 \|
	\| path \| 21.67 \| 27.39 \|
	\| stairs \| 28.0 \| 36.82 \|
	\| runway \| 74.58 \| 80.21 \|
	\| case \| 45.27 \| 56.06 \|
	\| pool table \| 91.94 \| 95.6 \|
	\| pillow \| 53.3 \| 64.21 \|
	\| screen door \| 75.2 \| 80.39 \|
	\| stairway \| 31.74 \| 39.72 \|
	\| river \| 15.19 \| 28.46 \|
	\| bridge \| 51.25 \| 63.97 \|
	\| bookcase \| 39.49 \| 54.56 \|
	\| blind \| 32.83 \| 36.1 \|
	\| coffee table \| 64.73 \| 76.16 \|
	\| toilet \| 85.85 \| 89.24 \|
	\| flower \| 36.5 \| 49.61 \|
	\| book \| 45.66 \| 64.05 \|
	\| hill \| 8.69 \| 16.1 \|
	\| bench \| 38.02 \| 48.74 \|
	\| countertop \| 52.34 \| 68.09 \|
	\| stove \| 74.77 \| 79.28 \|
	\| palm \| 41.61 \| 52.07 \|
	\| kitchen island \| 41.44 \| 74.57 \|
	\| computer \| 57.58 \| 66.52 \|
	\| swivel chair \| 33.46 \| 41.1 \|
	\| boat \| 40.03 \| 47.99 \|
	\| bar \| 27.7 \| 32.77 \|
	\| arcade machine \| 42.8 \| 43.74 \|
	\| hovel \| 11.51 \| 23.56 \|
	\| bus \| 87.49 \| 95.57 \|
	\| towel \| 60.42 \| 71.69 \|
	\| light \| 47.73 \| 54.14 \|
	\| truck \| 28.75 \| 44.18 \|
	\| tower \| 24.34 \| 36.67 \|
	\| chandelier \| 66.79 \| 78.84 \|
	\| awning \| 27.8 \| 34.31 \|
	\| streetlight \| 25.63 \| 30.95 \|
	\| booth \| 21.62 \| 49.1 \|
	\| television receiver \| 69.14 \| 75.06 \|
	\| airplane \| 52.55 \| 65.06 \|
	\| dirt track \| 1.42 \| 5.63 \|
	\| apparel \| 27.86 \| 38.02 \|
	\| pole \| 23.47 \| 34.2 \|
	\| land \| 0.9 \| 1.28 \|
	\| bannister \| 11.64 \| 14.33 \|
	\| escalator \| 38.62 \| 52.56 \|
	\| ottoman \| 42.34 \| 54.87 \|
	\| bottle \| 20.06 \| 25.54 \|
	\| buffet \| 56.83 \| 68.35 \|
	\| poster \| 38.64 \| 56.34 \|
	\| stage \| 17.1 \| 37.49 \|
	\| van \| 43.3 \| 65.14 \|
	\| ship \| 58.29 \| 81.3 \|
	\| fountain \| 4.61 \| 4.66 \|
	\| conveyer belt \| 65.32 \| 86.97 \|
	\| canopy \| 25.54 \| 27.63 \|
	\| washer \| 68.52 \| 70.73 \|
	\| plaything \| 24.17 \| 31.56 \|
	\| swimming pool \| 55.84 \| 71.42 \|
	\| stool \| 40.69 \| 59.87 \|
	\| barrel \| 57.47 \| 72.07 \|
	\| basket \| 28.95 \| 36.04 \|
	\| waterfall \| 41.88 \| 52.2 \|
	\| tent \| 88.89 \| 97.23 \|
	\| bag \| 10.68 \| 14.01 \|
	\| minibike \| 63.83 \| 72.62 \|
	\| cradle \| 82.13 \| 95.78 \|
	\| oven \| 50.57 \| 56.19 \|
	\| ball \| 41.41 \| 50.85 \|
	\| food \| 55.39 \| 65.5 \|
	\| step \| 12.41 \| 15.28 \|
	\| tank \| 48.45 \| 54.89 \|
	\| trade name \| 24.77 \| 29.55 \|
	\| microwave \| 36.15 \| 40.04 \|
	\| pot \| 50.53 \| 57.81 \|
	\| animal \| 47.31 \| 51.49 \|
	\| bicycle \| 49.86 \| 69.73 \|
	\| lake \| 25.31 \| 25.76 \|
	\| dishwasher \| 65.87 \| 71.57 \|
	\| screen \| 71.93 \| 88.2 \|
	\| blanket \| 17.27 \| 20.66 \|
	\| sculpture \| 59.54 \| 78.71 \|
	\| hood \| 58.45 \| 64.36 \|
	\| sconce \| 44.98 \| 55.22 \|
	\| vase \| 38.03 \| 51.95 \|
	\| traffic light \| 32.81 \| 56.89 \|
	\| tray \| 12.22 \| 17.7 \|
	\| ashcan \| 37.02 \| 48.86 \|
	\| fan \| 53.95 \| 64.18 \|
	\| pier \| 56.72 \| 71.32 \|
	\| crt screen \| 3.66 \| 12.7 \|
	\| plate \| 50.0 \| 76.6 \|
	\| monitor \| 13.08 \| 16.11 \|
	\| bulletin board \| 32.81 \| 44.54 \|
	\| shower \| 4.1 \| 8.49 \|
	\| radiator \| 40.26 \| 48.32 \|
	\| glass \| 15.61 \| 18.24 \|
	\| clock \| 20.34 \| 26.62 \|
	\| flag \| 30.08 \| 33.38 \|
	+---------------------+-------+-------+
	2023/11/28 02:26:07 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.2500 mIoU: 46.4900 mAcc: 57.6600 data_time: 0.0020 time: 0.7659
	2023/11/28 03:03:38 - mmengine - INFO - Iter(train) [ 60500/120000] base_lr: 9.9707e-05 lr: 1.0882e-05 eta: 15:54:23 time: 0.9668 data_time: 0.0074 memory: 8153 grad_norm: 0.0230 loss: 0.0060 semantic_segmentation_loss_cls: 0.0060
	2023/11/28 03:11:40 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 03:11:40 - mmengine - INFO - Iter(train) [ 61000/120000] base_lr: 9.8411e-05 lr: 1.0765e-05 eta: 15:46:47 time: 0.9662 data_time: 0.0074 memory: 8153 grad_norm: 0.0229 loss: 0.0060 semantic_segmentation_loss_cls: 0.0060
	2023/11/28 03:11:40 - mmengine - INFO - Saving checkpoint at 61000 iterations
	2023/11/28 03:19:53 - mmengine - INFO - Iter(train) [ 61500/120000] base_lr: 9.7116e-05 lr: 1.0647e-05 eta: 15:46:33 time: 0.9688 data_time: 0.0097 memory: 8153 grad_norm: 0.0224 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 03:27:57 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 03:27:57 - mmengine - INFO - Iter(train) [ 62000/120000] base_lr: 9.5821e-05 lr: 1.0529e-05 eta: 15:37:34 time: 0.9687 data_time: 0.0097 memory: 8153 grad_norm: 0.0221 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 03:27:57 - mmengine - INFO - Saving checkpoint at 62000 iterations
	2023/11/28 03:36:10 - mmengine - INFO - Iter(train) [ 62500/120000] base_lr: 9.4528e-05 lr: 1.0412e-05 eta: 15:32:39 time: 0.9711 data_time: 0.0120 memory: 8153 grad_norm: 0.0220 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 03:44:14 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 03:44:14 - mmengine - INFO - Iter(train) [ 63000/120000] base_lr: 9.3235e-05 lr: 1.0294e-05 eta: 15:23:45 time: 0.9712 data_time: 0.0121 memory: 8153 grad_norm: 0.0219 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 03:44:14 - mmengine - INFO - Saving checkpoint at 63000 iterations
	2023/11/28 03:52:28 - mmengine - INFO - Iter(train) [ 63500/120000] base_lr: 9.1944e-05 lr: 1.0177e-05 eta: 15:17:35 time: 0.9735 data_time: 0.0144 memory: 8153 grad_norm: 0.0218 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 04:00:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 04:00:32 - mmengine - INFO - Iter(train) [ 64000/120000] base_lr: 9.0654e-05 lr: 1.0059e-05 eta: 15:08:46 time: 0.9737 data_time: 0.0144 memory: 8153 grad_norm: 0.0216 loss: 0.0059 semantic_segmentation_loss_cls: 0.0059
	2023/11/28 04:00:32 - mmengine - INFO - Saving checkpoint at 64000 iterations
	2023/11/28 04:08:45 - mmengine - INFO - Iter(train) [ 64500/120000] base_lr: 8.9366e-05 lr: 9.9424e-06 eta: 15:01:56 time: 0.9767 data_time: 0.0167 memory: 8153 grad_norm: 0.0215 loss: 0.0058 semantic_segmentation_loss_cls: 0.0058
	2023/11/28 04:16:49 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 04:16:49 - mmengine - INFO - Iter(train) [ 65000/120000] base_lr: 8.8080e-05 lr: 9.8255e-06 eta: 14:53:08 time: 0.9772 data_time: 0.0167 memory: 8153 grad_norm: 0.0212 loss: 0.0058 semantic_segmentation_loss_cls: 0.0058
	2023/11/28 04:16:49 - mmengine - INFO - Saving checkpoint at 65000 iterations
	2023/11/28 04:20:11 - mmengine - INFO - per class results:
	2023/11/28 04:20:11 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.43 \| 88.44 \|
	\| building \| 80.55 \| 93.61 \|
	\| sky \| 93.51 \| 97.75 \|
	\| floor \| 80.32 \| 88.93 \|
	\| tree \| 73.79 \| 85.64 \|
	\| ceiling \| 83.47 \| 93.79 \|
	\| road \| 80.29 \| 90.37 \|
	\| bed \| 86.52 \| 94.47 \|
	\| windowpane \| 61.17 \| 77.29 \|
	\| grass \| 70.49 \| 81.73 \|
	\| cabinet \| 57.65 \| 73.32 \|
	\| sidewalk \| 64.97 \| 77.38 \|
	\| person \| 78.7 \| 90.76 \|
	\| earth \| 37.74 \| 51.36 \|
	\| door \| 50.13 \| 67.14 \|
	\| table \| 58.9 \| 76.69 \|
	\| mountain \| 52.44 \| 74.06 \|
	\| plant \| 52.23 \| 65.54 \|
	\| curtain \| 70.55 \| 81.26 \|
	\| chair \| 56.27 \| 69.95 \|
	\| car \| 79.7 \| 91.2 \|
	\| water \| 46.64 \| 56.94 \|
	\| painting \| 71.55 \| 85.96 \|
	\| sofa \| 61.3 \| 79.26 \|
	\| shelf \| 42.64 \| 61.37 \|
	\| house \| 24.34 \| 28.61 \|
	\| sea \| 53.46 \| 89.79 \|
	\| mirror \| 65.96 \| 73.12 \|
	\| rug \| 66.39 \| 74.86 \|
	\| field \| 34.02 \| 56.59 \|
	\| armchair \| 39.66 \| 54.61 \|
	\| seat \| 62.63 \| 79.11 \|
	\| fence \| 45.8 \| 60.9 \|
	\| desk \| 43.69 \| 61.31 \|
	\| rock \| 36.09 \| 53.89 \|
	\| wardrobe \| 46.38 \| 66.28 \|
	\| lamp \| 60.97 \| 72.92 \|
	\| bathtub \| 75.91 \| 80.51 \|
	\| railing \| 30.99 \| 40.82 \|
	\| cushion \| 57.54 \| 66.62 \|
	\| base \| 24.05 \| 37.19 \|
	\| box \| 20.13 \| 25.57 \|
	\| column \| 42.71 \| 48.84 \|
	\| signboard \| 34.59 \| 45.77 \|
	\| chest of drawers \| 36.22 \| 51.4 \|
	\| counter \| 18.06 \| 19.65 \|
	\| sand \| 43.36 \| 51.72 \|
	\| sink \| 68.93 \| 82.62 \|
	\| skyscraper \| 46.8 \| 53.1 \|
	\| fireplace \| 71.24 \| 89.41 \|
	\| refrigerator \| 71.15 \| 76.92 \|
	\| grandstand \| 37.37 \| 66.63 \|
	\| path \| 21.42 \| 27.52 \|
	\| stairs \| 26.59 \| 35.92 \|
	\| runway \| 71.52 \| 86.95 \|
	\| case \| 36.32 \| 51.72 \|
	\| pool table \| 91.37 \| 95.96 \|
	\| pillow \| 55.08 \| 67.1 \|
	\| screen door \| 69.54 \| 79.51 \|
	\| stairway \| 30.02 \| 42.48 \|
	\| river \| 16.78 \| 35.9 \|
	\| bridge \| 36.86 \| 48.01 \|
	\| bookcase \| 35.1 \| 47.82 \|
	\| blind \| 37.4 \| 42.67 \|
	\| coffee table \| 60.87 \| 72.64 \|
	\| toilet \| 83.19 \| 86.17 \|
	\| flower \| 38.92 \| 55.65 \|
	\| book \| 46.81 \| 67.0 \|
	\| hill \| 8.44 \| 13.1 \|
	\| bench \| 36.98 \| 43.35 \|
	\| countertop \| 51.6 \| 60.79 \|
	\| stove \| 73.74 \| 80.4 \|
	\| palm \| 48.97 \| 69.55 \|
	\| kitchen island \| 44.59 \| 71.6 \|
	\| computer \| 57.55 \| 65.74 \|
	\| swivel chair \| 36.02 \| 48.55 \|
	\| boat \| 45.25 \| 52.34 \|
	\| bar \| 13.45 \| 15.99 \|
	\| arcade machine \| 49.53 \| 51.51 \|
	\| hovel \| 6.81 \| 8.4 \|
	\| bus \| 86.92 \| 95.08 \|
	\| towel \| 61.35 \| 74.03 \|
	\| light \| 50.13 \| 59.43 \|
	\| truck \| 24.02 \| 40.78 \|
	\| tower \| 19.07 \| 27.89 \|
	\| chandelier \| 66.64 \| 77.24 \|
	\| awning \| 26.4 \| 32.31 \|
	\| streetlight \| 27.33 \| 35.2 \|
	\| booth \| 40.11 \| 41.1 \|
	\| television receiver \| 56.9 \| 78.77 \|
	\| airplane \| 55.18 \| 65.47 \|
	\| dirt track \| 6.67 \| 18.38 \|
	\| apparel \| 26.11 \| 38.79 \|
	\| pole \| 20.15 \| 25.51 \|
	\| land \| 1.89 \| 2.28 \|
	\| bannister \| 16.77 \| 24.91 \|
	\| escalator \| 25.34 \| 30.9 \|
	\| ottoman \| 38.8 \| 60.3 \|
	\| bottle \| 17.95 \| 20.83 \|
	\| buffet \| 41.72 \| 46.19 \|
	\| poster \| 40.18 \| 50.19 \|
	\| stage \| 13.1 \| 24.52 \|
	\| van \| 34.1 \| 43.38 \|
	\| ship \| 21.73 \| 32.31 \|
	\| fountain \| 4.61 \| 4.68 \|
	\| conveyer belt \| 61.18 \| 85.94 \|
	\| canopy \| 13.75 \| 14.6 \|
	\| washer \| 69.36 \| 72.04 \|
	\| plaything \| 24.88 \| 32.22 \|
	\| swimming pool \| 67.84 \| 74.77 \|
	\| stool \| 43.27 \| 56.18 \|
	\| barrel \| 34.0 \| 74.47 \|
	\| basket \| 30.42 \| 46.35 \|
	\| waterfall \| 50.96 \| 54.38 \|
	\| tent \| 89.73 \| 97.44 \|
	\| bag \| 7.5 \| 9.95 \|
	\| minibike \| 43.52 \| 48.47 \|
	\| cradle \| 76.01 \| 95.24 \|
	\| oven \| 43.65 \| 52.35 \|
	\| ball \| 46.53 \| 56.03 \|
	\| food \| 48.92 \| 54.61 \|
	\| step \| 10.9 \| 12.01 \|
	\| tank \| 35.76 \| 41.89 \|
	\| trade name \| 23.36 \| 26.94 \|
	\| microwave \| 38.24 \| 41.35 \|
	\| pot \| 49.89 \| 57.73 \|
	\| animal \| 52.25 \| 57.16 \|
	\| bicycle \| 48.71 \| 74.44 \|
	\| lake \| 51.36 \| 51.88 \|
	\| dishwasher \| 62.81 \| 66.71 \|
	\| screen \| 68.96 \| 86.62 \|
	\| blanket \| 15.39 \| 18.17 \|
	\| sculpture \| 59.9 \| 73.11 \|
	\| hood \| 60.11 \| 63.9 \|
	\| sconce \| 43.13 \| 53.11 \|
	\| vase \| 36.73 \| 55.09 \|
	\| traffic light \| 31.78 \| 53.92 \|
	\| tray \| 12.47 \| 19.45 \|
	\| ashcan \| 38.91 \| 60.33 \|
	\| fan \| 58.53 \| 72.81 \|
	\| pier \| 50.81 \| 68.55 \|
	\| crt screen \| 4.21 \| 6.27 \|
	\| plate \| 51.54 \| 75.37 \|
	\| monitor \| 46.94 \| 57.56 \|
	\| bulletin board \| 29.84 \| 36.51 \|
	\| shower \| 6.95 \| 11.56 \|
	\| radiator \| 49.16 \| 56.04 \|
	\| glass \| 15.33 \| 17.5 \|
	\| clock \| 20.86 \| 25.69 \|
	\| flag \| 29.29 \| 32.46 \|
	+---------------------+-------+-------+
	2023/11/28 04:20:11 - mmengine - INFO - Iter(val) [250/250] aAcc: 81.9500 mIoU: 45.5700 mAcc: 56.5100 data_time: 0.0035 time: 0.7660
	2023/11/28 04:28:15 - mmengine - INFO - Iter(train) [ 65500/120000] base_lr: 8.6797e-05 lr: 9.7088e-06 eta: 14:44:39 time: 0.9751 data_time: 0.0146 memory: 8153 grad_norm: 0.0213 loss: 0.0058 semantic_segmentation_loss_cls: 0.0058
	2023/11/28 04:36:19 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 04:36:19 - mmengine - INFO - Iter(train) [ 66000/120000] base_lr: 8.5516e-05 lr: 9.5923e-06 eta: 14:36:03 time: 0.9751 data_time: 0.0146 memory: 8153 grad_norm: 0.0212 loss: 0.0058 semantic_segmentation_loss_cls: 0.0058
	2023/11/28 04:36:19 - mmengine - INFO - Saving checkpoint at 66000 iterations
	2023/11/28 04:44:33 - mmengine - INFO - Iter(train) [ 66500/120000] base_lr: 8.4237e-05 lr: 9.4761e-06 eta: 14:28:55 time: 0.9753 data_time: 0.0147 memory: 8153 grad_norm: 0.0211 loss: 0.0057 semantic_segmentation_loss_cls: 0.0057
	2023/11/28 04:52:38 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 04:52:38 - mmengine - INFO - Iter(train) [ 67000/120000] base_lr: 8.2961e-05 lr: 9.3601e-06 eta: 14:20:30 time: 0.9755 data_time: 0.0147 memory: 8153 grad_norm: 0.0208 loss: 0.0057 semantic_segmentation_loss_cls: 0.0057
	2023/11/28 04:52:38 - mmengine - INFO - Saving checkpoint at 67000 iterations
	2023/11/28 05:00:52 - mmengine - INFO - Iter(train) [ 67500/120000] base_lr: 8.1689e-05 lr: 9.2444e-06 eta: 14:13:11 time: 0.9756 data_time: 0.0146 memory: 8153 grad_norm: 0.0206 loss: 0.0057 semantic_segmentation_loss_cls: 0.0057
	2023/11/28 05:08:55 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 05:08:55 - mmengine - INFO - Iter(train) [ 68000/120000] base_lr: 8.0419e-05 lr: 9.1290e-06 eta: 14:04:39 time: 0.9755 data_time: 0.0146 memory: 8153 grad_norm: 0.0206 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 05:08:55 - mmengine - INFO - Saving checkpoint at 68000 iterations
	2023/11/28 05:17:09 - mmengine - INFO - Iter(train) [ 68500/120000] base_lr: 7.9153e-05 lr: 9.0140e-06 eta: 13:57:10 time: 0.9757 data_time: 0.0147 memory: 8153 grad_norm: 0.0202 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 05:25:13 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 05:25:13 - mmengine - INFO - Iter(train) [ 69000/120000] base_lr: 7.7891e-05 lr: 8.8992e-06 eta: 13:48:41 time: 0.9757 data_time: 0.0147 memory: 8153 grad_norm: 0.0201 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 05:25:13 - mmengine - INFO - Saving checkpoint at 69000 iterations
	2023/11/28 05:33:27 - mmengine - INFO - Iter(train) [ 69500/120000] base_lr: 7.6633e-05 lr: 8.7848e-06 eta: 13:41:05 time: 0.9778 data_time: 0.0168 memory: 8153 grad_norm: 0.0198 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 05:41:31 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 05:41:31 - mmengine - INFO - Iter(train) [ 70000/120000] base_lr: 7.5379e-05 lr: 8.6709e-06 eta: 13:32:42 time: 0.9780 data_time: 0.0168 memory: 8153 grad_norm: 0.0199 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 05:41:31 - mmengine - INFO - Saving checkpoint at 70000 iterations
	2023/11/28 05:44:53 - mmengine - INFO - per class results:
	2023/11/28 05:44:53 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.86 \| 88.8 \|
	\| building \| 80.5 \| 92.6 \|
	\| sky \| 93.46 \| 97.87 \|
	\| floor \| 81.07 \| 89.82 \|
	\| tree \| 72.74 \| 87.53 \|
	\| ceiling \| 83.93 \| 93.51 \|
	\| road \| 83.4 \| 90.64 \|
	\| bed \| 88.09 \| 95.14 \|
	\| windowpane \| 61.94 \| 75.68 \|
	\| grass \| 68.72 \| 81.63 \|
	\| cabinet \| 61.18 \| 73.8 \|
	\| sidewalk \| 66.61 \| 82.9 \|
	\| person \| 78.71 \| 91.21 \|
	\| earth \| 38.6 \| 53.39 \|
	\| door \| 50.24 \| 61.64 \|
	\| table \| 59.42 \| 75.38 \|
	\| mountain \| 54.66 \| 70.38 \|
	\| plant \| 49.27 \| 57.52 \|
	\| curtain \| 72.34 \| 80.28 \|
	\| chair \| 56.94 \| 69.74 \|
	\| car \| 80.68 \| 90.56 \|
	\| water \| 48.49 \| 63.08 \|
	\| painting \| 69.95 \| 85.11 \|
	\| sofa \| 62.41 \| 74.17 \|
	\| shelf \| 46.19 \| 62.85 \|
	\| house \| 43.12 \| 57.8 \|
	\| sea \| 44.87 \| 72.78 \|
	\| mirror \| 67.38 \| 78.33 \|
	\| rug \| 66.35 \| 78.15 \|
	\| field \| 32.6 \| 52.91 \|
	\| armchair \| 44.72 \| 65.14 \|
	\| seat \| 62.09 \| 78.81 \|
	\| fence \| 41.72 \| 54.61 \|
	\| desk \| 44.6 \| 71.89 \|
	\| rock \| 35.7 \| 51.13 \|
	\| wardrobe \| 53.29 \| 64.32 \|
	\| lamp \| 61.28 \| 72.71 \|
	\| bathtub \| 77.28 \| 81.98 \|
	\| railing \| 32.61 \| 47.61 \|
	\| cushion \| 59.1 \| 74.45 \|
	\| base \| 23.39 \| 33.28 \|
	\| box \| 19.85 \| 26.59 \|
	\| column \| 45.51 \| 54.52 \|
	\| signboard \| 37.63 \| 55.98 \|
	\| chest of drawers \| 36.95 \| 67.5 \|
	\| counter \| 18.41 \| 25.76 \|
	\| sand \| 42.55 \| 55.83 \|
	\| sink \| 68.86 \| 80.34 \|
	\| skyscraper \| 46.0 \| 53.96 \|
	\| fireplace \| 70.98 \| 90.93 \|
	\| refrigerator \| 71.03 \| 78.12 \|
	\| grandstand \| 40.02 \| 67.68 \|
	\| path \| 28.14 \| 33.79 \|
	\| stairs \| 30.45 \| 41.57 \|
	\| runway \| 70.96 \| 87.11 \|
	\| case \| 43.98 \| 54.06 \|
	\| pool table \| 91.95 \| 95.59 \|
	\| pillow \| 54.67 \| 67.39 \|
	\| screen door \| 74.73 \| 80.01 \|
	\| stairway \| 29.91 \| 37.33 \|
	\| river \| 14.01 \| 23.86 \|
	\| bridge \| 35.16 \| 46.1 \|
	\| bookcase \| 42.81 \| 64.63 \|
	\| blind \| 38.73 \| 43.25 \|
	\| coffee table \| 60.74 \| 77.15 \|
	\| toilet \| 82.98 \| 88.25 \|
	\| flower \| 39.95 \| 58.16 \|
	\| book \| 43.63 \| 63.42 \|
	\| hill \| 6.03 \| 8.91 \|
	\| bench \| 37.86 \| 46.86 \|
	\| countertop \| 49.97 \| 68.61 \|
	\| stove \| 74.14 \| 80.68 \|
	\| palm \| 46.56 \| 65.97 \|
	\| kitchen island \| 39.09 \| 82.77 \|
	\| computer \| 54.12 \| 60.91 \|
	\| swivel chair \| 35.09 \| 43.29 \|
	\| boat \| 42.01 \| 48.79 \|
	\| bar \| 19.73 \| 21.49 \|
	\| arcade machine \| 51.55 \| 53.73 \|
	\| hovel \| 6.37 \| 10.99 \|
	\| bus \| 80.92 \| 95.14 \|
	\| towel \| 58.51 \| 77.72 \|
	\| light \| 47.92 \| 55.9 \|
	\| truck \| 27.53 \| 32.99 \|
	\| tower \| 26.42 \| 43.69 \|
	\| chandelier \| 67.34 \| 79.39 \|
	\| awning \| 27.25 \| 34.28 \|
	\| streetlight \| 24.61 \| 29.62 \|
	\| booth \| 45.71 \| 50.78 \|
	\| television receiver \| 61.42 \| 79.06 \|
	\| airplane \| 58.07 \| 63.47 \|
	\| dirt track \| 0.81 \| 1.88 \|
	\| apparel \| 30.52 \| 38.87 \|
	\| pole \| 22.52 \| 28.71 \|
	\| land \| 0.37 \| 0.55 \|
	\| bannister \| 13.0 \| 17.56 \|
	\| escalator \| 34.81 \| 45.0 \|
	\| ottoman \| 40.61 \| 52.91 \|
	\| bottle \| 27.34 \| 35.07 \|
	\| buffet \| 29.62 \| 32.02 \|
	\| poster \| 31.2 \| 37.41 \|
	\| stage \| 11.71 \| 23.98 \|
	\| van \| 34.01 \| 47.2 \|
	\| ship \| 45.94 \| 69.61 \|
	\| fountain \| 16.93 \| 19.27 \|
	\| conveyer belt \| 61.13 \| 88.34 \|
	\| canopy \| 14.93 \| 16.69 \|
	\| washer \| 72.41 \| 75.8 \|
	\| plaything \| 20.27 \| 28.79 \|
	\| swimming pool \| 57.29 \| 65.22 \|
	\| stool \| 43.42 \| 62.59 \|
	\| barrel \| 61.15 \| 68.43 \|
	\| basket \| 35.6 \| 46.28 \|
	\| waterfall \| 51.31 \| 56.5 \|
	\| tent \| 87.25 \| 97.99 \|
	\| bag \| 7.13 \| 7.83 \|
	\| minibike \| 59.53 \| 75.3 \|
	\| cradle \| 78.94 \| 92.67 \|
	\| oven \| 49.52 \| 69.88 \|
	\| ball \| 40.14 \| 52.57 \|
	\| food \| 49.36 \| 60.72 \|
	\| step \| 9.55 \| 11.55 \|
	\| tank \| 51.07 \| 57.25 \|
	\| trade name \| 19.4 \| 22.64 \|
	\| microwave \| 38.1 \| 41.02 \|
	\| pot \| 50.23 \| 57.18 \|
	\| animal \| 49.19 \| 53.02 \|
	\| bicycle \| 51.74 \| 70.14 \|
	\| lake \| 57.04 \| 62.64 \|
	\| dishwasher \| 63.97 \| 70.64 \|
	\| screen \| 59.7 \| 84.35 \|
	\| blanket \| 16.41 \| 19.12 \|
	\| sculpture \| 55.3 \| 74.94 \|
	\| hood \| 62.56 \| 68.29 \|
	\| sconce \| 44.39 \| 53.58 \|
	\| vase \| 36.14 \| 52.86 \|
	\| traffic light \| 35.64 \| 54.06 \|
	\| tray \| 12.72 \| 17.54 \|
	\| ashcan \| 34.38 \| 43.1 \|
	\| fan \| 58.09 \| 68.17 \|
	\| pier \| 41.42 \| 65.77 \|
	\| crt screen \| 3.82 \| 5.48 \|
	\| plate \| 52.78 \| 67.31 \|
	\| monitor \| 53.95 \| 72.74 \|
	\| bulletin board \| 30.75 \| 43.53 \|
	\| shower \| 4.6 \| 16.29 \|
	\| radiator \| 46.19 \| 49.67 \|
	\| glass \| 15.88 \| 18.07 \|
	\| clock \| 19.12 \| 25.01 \|
	\| flag \| 27.52 \| 30.19 \|
	+---------------------+-------+-------+
	2023/11/28 05:44:53 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.3700 mIoU: 46.5000 mAcc: 57.7800 data_time: 0.0021 time: 0.7648
	2023/11/28 05:52:57 - mmengine - INFO - Iter(train) [ 70500/120000] base_lr: 7.4130e-05 lr: 8.5573e-06 eta: 13:24:20 time: 0.9757 data_time: 0.0146 memory: 8153 grad_norm: 0.0197 loss: 0.0056 semantic_segmentation_loss_cls: 0.0056
	2023/11/28 06:01:01 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 06:01:01 - mmengine - INFO - Iter(train) [ 71000/120000] base_lr: 7.2885e-05 lr: 8.4441e-06 eta: 13:15:59 time: 0.9756 data_time: 0.0146 memory: 8153 grad_norm: 0.0197 loss: 0.0055 semantic_segmentation_loss_cls: 0.0055
	2023/11/28 06:01:01 - mmengine - INFO - Saving checkpoint at 71000 iterations
	2023/11/28 06:09:14 - mmengine - INFO - Iter(train) [ 71500/120000] base_lr: 7.1645e-05 lr: 8.3314e-06 eta: 13:08:16 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0195 loss: 0.0055 semantic_segmentation_loss_cls: 0.0055
	2023/11/28 06:17:19 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 06:17:19 - mmengine - INFO - Iter(train) [ 72000/120000] base_lr: 7.0410e-05 lr: 8.2191e-06 eta: 12:59:55 time: 0.9756 data_time: 0.0146 memory: 8153 grad_norm: 0.0194 loss: 0.0055 semantic_segmentation_loss_cls: 0.0055
	2023/11/28 06:17:19 - mmengine - INFO - Saving checkpoint at 72000 iterations
	2023/11/28 06:25:32 - mmengine - INFO - Iter(train) [ 72500/120000] base_lr: 6.9180e-05 lr: 8.1073e-06 eta: 12:52:10 time: 0.9755 data_time: 0.0146 memory: 8153 grad_norm: 0.0193 loss: 0.0055 semantic_segmentation_loss_cls: 0.0055
	2023/11/28 06:33:36 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 06:33:36 - mmengine - INFO - Iter(train) [ 73000/120000] base_lr: 6.7956e-05 lr: 7.9960e-06 eta: 12:43:49 time: 0.9755 data_time: 0.0146 memory: 8153 grad_norm: 0.0193 loss: 0.0055 semantic_segmentation_loss_cls: 0.0055
	2023/11/28 06:33:36 - mmengine - INFO - Saving checkpoint at 73000 iterations
	2023/11/28 06:41:50 - mmengine - INFO - Iter(train) [ 73500/120000] base_lr: 6.6737e-05 lr: 7.8852e-06 eta: 12:36:03 time: 0.9756 data_time: 0.0147 memory: 8153 grad_norm: 0.0191 loss: 0.0054 semantic_segmentation_loss_cls: 0.0054
	2023/11/28 06:49:54 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 06:49:54 - mmengine - INFO - Iter(train) [ 74000/120000] base_lr: 6.5524e-05 lr: 7.7749e-06 eta: 12:27:42 time: 0.9753 data_time: 0.0147 memory: 8153 grad_norm: 0.0188 loss: 0.0054 semantic_segmentation_loss_cls: 0.0054
	2023/11/28 06:49:54 - mmengine - INFO - Saving checkpoint at 74000 iterations
	2023/11/28 06:58:07 - mmengine - INFO - Iter(train) [ 74500/120000] base_lr: 6.4317e-05 lr: 7.6652e-06 eta: 12:19:53 time: 0.9776 data_time: 0.0168 memory: 8153 grad_norm: 0.0188 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:06:11 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 07:06:11 - mmengine - INFO - Iter(train) [ 75000/120000] base_lr: 6.3117e-05 lr: 7.5561e-06 eta: 12:11:32 time: 0.9773 data_time: 0.0167 memory: 8153 grad_norm: 0.0184 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:06:11 - mmengine - INFO - Saving checkpoint at 75000 iterations
	2023/11/28 07:09:32 - mmengine - INFO - per class results:
	2023/11/28 07:09:32 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.58 \| 88.14 \|
	\| building \| 81.8 \| 91.6 \|
	\| sky \| 93.42 \| 97.9 \|
	\| floor \| 80.6 \| 90.96 \|
	\| tree \| 72.92 \| 87.95 \|
	\| ceiling \| 83.01 \| 94.73 \|
	\| road \| 83.29 \| 89.63 \|
	\| bed \| 87.57 \| 94.99 \|
	\| windowpane \| 60.21 \| 78.97 \|
	\| grass \| 67.52 \| 79.68 \|
	\| cabinet \| 62.14 \| 74.76 \|
	\| sidewalk \| 66.83 \| 80.67 \|
	\| person \| 78.4 \| 91.02 \|
	\| earth \| 39.48 \| 56.93 \|
	\| door \| 51.48 \| 63.49 \|
	\| table \| 60.38 \| 75.83 \|
	\| mountain \| 56.74 \| 70.01 \|
	\| plant \| 51.49 \| 65.0 \|
	\| curtain \| 70.92 \| 82.27 \|
	\| chair \| 55.38 \| 67.89 \|
	\| car \| 81.69 \| 90.17 \|
	\| water \| 52.82 \| 70.88 \|
	\| painting \| 70.8 \| 85.52 \|
	\| sofa \| 63.26 \| 79.49 \|
	\| shelf \| 46.34 \| 62.6 \|
	\| house \| 47.6 \| 64.61 \|
	\| sea \| 50.53 \| 69.06 \|
	\| mirror \| 66.61 \| 76.92 \|
	\| rug \| 67.2 \| 76.4 \|
	\| field \| 27.8 \| 44.68 \|
	\| armchair \| 39.52 \| 57.72 \|
	\| seat \| 61.83 \| 79.54 \|
	\| fence \| 41.91 \| 58.32 \|
	\| desk \| 47.65 \| 67.19 \|
	\| rock \| 40.69 \| 58.16 \|
	\| wardrobe \| 53.11 \| 65.93 \|
	\| lamp \| 61.35 \| 73.55 \|
	\| bathtub \| 79.89 \| 83.51 \|
	\| railing \| 31.95 \| 45.2 \|
	\| cushion \| 59.45 \| 69.99 \|
	\| base \| 18.32 \| 24.95 \|
	\| box \| 21.22 \| 26.55 \|
	\| column \| 47.95 \| 62.32 \|
	\| signboard \| 37.95 \| 53.43 \|
	\| chest of drawers \| 39.43 \| 61.26 \|
	\| counter \| 23.16 \| 31.25 \|
	\| sand \| 48.19 \| 60.53 \|
	\| sink \| 70.94 \| 80.28 \|
	\| skyscraper \| 44.97 \| 51.39 \|
	\| fireplace \| 71.48 \| 89.24 \|
	\| refrigerator \| 69.04 \| 79.48 \|
	\| grandstand \| 36.15 \| 67.58 \|
	\| path \| 27.9 \| 36.52 \|
	\| stairs \| 26.4 \| 32.64 \|
	\| runway \| 70.78 \| 84.09 \|
	\| case \| 42.97 \| 56.14 \|
	\| pool table \| 92.03 \| 95.88 \|
	\| pillow \| 56.89 \| 71.75 \|
	\| screen door \| 67.94 \| 72.55 \|
	\| stairway \| 30.63 \| 36.97 \|
	\| river \| 13.74 \| 27.7 \|
	\| bridge \| 48.35 \| 61.99 \|
	\| bookcase \| 40.66 \| 56.26 \|
	\| blind \| 33.15 \| 37.63 \|
	\| coffee table \| 61.41 \| 80.62 \|
	\| toilet \| 84.73 \| 89.17 \|
	\| flower \| 40.39 \| 53.82 \|
	\| book \| 44.51 \| 62.61 \|
	\| hill \| 6.23 \| 8.68 \|
	\| bench \| 41.78 \| 49.03 \|
	\| countertop \| 49.07 \| 66.08 \|
	\| stove \| 74.03 \| 78.64 \|
	\| palm \| 48.46 \| 65.04 \|
	\| kitchen island \| 39.95 \| 84.88 \|
	\| computer \| 61.61 \| 69.35 \|
	\| swivel chair \| 38.11 \| 51.29 \|
	\| boat \| 47.51 \| 52.25 \|
	\| bar \| 22.92 \| 27.42 \|
	\| arcade machine \| 51.71 \| 54.74 \|
	\| hovel \| 10.22 \| 12.74 \|
	\| bus \| 88.91 \| 93.79 \|
	\| towel \| 59.42 \| 71.66 \|
	\| light \| 43.62 \| 50.98 \|
	\| truck \| 28.81 \| 38.26 \|
	\| tower \| 29.33 \| 44.21 \|
	\| chandelier \| 64.1 \| 74.19 \|
	\| awning \| 28.74 \| 35.04 \|
	\| streetlight \| 29.23 \| 39.83 \|
	\| booth \| 41.81 \| 46.95 \|
	\| television receiver \| 57.84 \| 82.7 \|
	\| airplane \| 54.29 \| 64.84 \|
	\| dirt track \| 6.33 \| 18.06 \|
	\| apparel \| 27.41 \| 37.72 \|
	\| pole \| 19.34 \| 23.7 \|
	\| land \| 0.3 \| 0.4 \|
	\| bannister \| 13.47 \| 17.96 \|
	\| escalator \| 20.79 \| 25.7 \|
	\| ottoman \| 47.05 \| 61.86 \|
	\| bottle \| 29.12 \| 40.5 \|
	\| buffet \| 49.1 \| 53.77 \|
	\| poster \| 29.4 \| 34.89 \|
	\| stage \| 16.08 \| 29.48 \|
	\| van \| 41.19 \| 60.07 \|
	\| ship \| 59.6 \| 80.72 \|
	\| fountain \| 2.04 \| 2.16 \|
	\| conveyer belt \| 68.98 \| 87.86 \|
	\| canopy \| 12.17 \| 14.24 \|
	\| washer \| 69.71 \| 73.64 \|
	\| plaything \| 24.28 \| 32.1 \|
	\| swimming pool \| 57.13 \| 61.4 \|
	\| stool \| 45.33 \| 58.52 \|
	\| barrel \| 48.37 \| 54.11 \|
	\| basket \| 31.51 \| 45.51 \|
	\| waterfall \| 42.87 \| 54.75 \|
	\| tent \| 90.54 \| 97.37 \|
	\| bag \| 5.96 \| 6.92 \|
	\| minibike \| 48.34 \| 56.95 \|
	\| cradle \| 77.48 \| 95.35 \|
	\| oven \| 43.14 \| 49.52 \|
	\| ball \| 37.62 \| 51.0 \|
	\| food \| 52.09 \| 61.4 \|
	\| step \| 5.34 \| 6.26 \|
	\| tank \| 45.07 \| 49.21 \|
	\| trade name \| 24.96 \| 30.12 \|
	\| microwave \| 37.64 \| 40.26 \|
	\| pot \| 52.49 \| 61.29 \|
	\| animal \| 50.55 \| 53.55 \|
	\| bicycle \| 52.25 \| 75.85 \|
	\| lake \| 57.62 \| 63.86 \|
	\| dishwasher \| 66.26 \| 71.47 \|
	\| screen \| 51.29 \| 88.26 \|
	\| blanket \| 16.23 \| 18.4 \|
	\| sculpture \| 62.88 \| 75.72 \|
	\| hood \| 59.95 \| 62.8 \|
	\| sconce \| 46.92 \| 57.75 \|
	\| vase \| 35.13 \| 49.08 \|
	\| traffic light \| 36.72 \| 48.04 \|
	\| tray \| 15.0 \| 21.07 \|
	\| ashcan \| 37.45 \| 50.75 \|
	\| fan \| 56.83 \| 65.62 \|
	\| pier \| 59.0 \| 75.72 \|
	\| crt screen \| 1.95 \| 3.13 \|
	\| plate \| 54.35 \| 70.67 \|
	\| monitor \| 48.56 \| 65.83 \|
	\| bulletin board \| 28.12 \| 35.64 \|
	\| shower \| 3.21 \| 6.49 \|
	\| radiator \| 48.48 \| 55.9 \|
	\| glass \| 15.66 \| 17.15 \|
	\| clock \| 21.71 \| 29.25 \|
	\| flag \| 30.08 \| 36.36 \|
	+---------------------+-------+-------+
	2023/11/28 07:09:32 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.5100 mIoU: 46.9300 mAcc: 57.8800 data_time: 0.0019 time: 0.7641
	2023/11/28 07:17:37 - mmengine - INFO - Iter(train) [ 75500/120000] base_lr: 6.1923e-05 lr: 7.4475e-06 eta: 12:03:18 time: 0.9754 data_time: 0.0147 memory: 8153 grad_norm: 0.0184 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:25:41 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 07:25:41 - mmengine - INFO - Iter(train) [ 76000/120000] base_lr: 6.0735e-05 lr: 7.3396e-06 eta: 11:55:00 time: 0.9753 data_time: 0.0147 memory: 8153 grad_norm: 0.0182 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:25:41 - mmengine - INFO - Saving checkpoint at 76000 iterations
	2023/11/28 07:33:54 - mmengine - INFO - Iter(train) [ 76500/120000] base_lr: 5.9555e-05 lr: 7.2323e-06 eta: 11:47:07 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0181 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:41:58 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 07:41:58 - mmengine - INFO - Iter(train) [ 77000/120000] base_lr: 5.8382e-05 lr: 7.1256e-06 eta: 11:38:51 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0179 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:41:58 - mmengine - INFO - Saving checkpoint at 77000 iterations
	2023/11/28 07:50:11 - mmengine - INFO - Iter(train) [ 77500/120000] base_lr: 5.7216e-05 lr: 7.0196e-06 eta: 11:30:57 time: 0.9751 data_time: 0.0145 memory: 8153 grad_norm: 0.0178 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:58:16 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 07:58:16 - mmengine - INFO - Iter(train) [ 78000/120000] base_lr: 5.6057e-05 lr: 6.9143e-06 eta: 11:22:41 time: 0.9753 data_time: 0.0145 memory: 8153 grad_norm: 0.0178 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 07:58:16 - mmengine - INFO - Saving checkpoint at 78000 iterations
	2023/11/28 08:06:29 - mmengine - INFO - Iter(train) [ 78500/120000] base_lr: 5.4906e-05 lr: 6.8097e-06 eta: 11:14:45 time: 0.9751 data_time: 0.0144 memory: 8153 grad_norm: 0.0177 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 08:14:33 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 08:14:33 - mmengine - INFO - Iter(train) [ 79000/120000] base_lr: 5.3764e-05 lr: 6.7058e-06 eta: 11:06:29 time: 0.9752 data_time: 0.0144 memory: 8153 grad_norm: 0.0176 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 08:14:33 - mmengine - INFO - Saving checkpoint at 79000 iterations
	2023/11/28 08:22:46 - mmengine - INFO - Iter(train) [ 79500/120000] base_lr: 5.2629e-05 lr: 6.6026e-06 eta: 10:58:33 time: 0.9771 data_time: 0.0164 memory: 8153 grad_norm: 0.0174 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 08:30:50 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 08:30:50 - mmengine - INFO - Iter(train) [ 80000/120000] base_lr: 5.1502e-05 lr: 6.5002e-06 eta: 10:50:17 time: 0.9771 data_time: 0.0164 memory: 8153 grad_norm: 0.0172 loss: 0.0053 semantic_segmentation_loss_cls: 0.0053
	2023/11/28 08:30:50 - mmengine - INFO - Saving checkpoint at 80000 iterations
	2023/11/28 08:34:11 - mmengine - INFO - per class results:
	2023/11/28 08:34:11 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.43 \| 89.79 \|
	\| building \| 81.06 \| 91.78 \|
	\| sky \| 93.36 \| 97.9 \|
	\| floor \| 80.9 \| 90.58 \|
	\| tree \| 73.0 \| 87.23 \|
	\| ceiling \| 83.59 \| 94.36 \|
	\| road \| 84.32 \| 89.76 \|
	\| bed \| 87.5 \| 94.81 \|
	\| windowpane \| 62.05 \| 75.55 \|
	\| grass \| 66.85 \| 81.52 \|
	\| cabinet \| 61.34 \| 74.62 \|
	\| sidewalk \| 67.47 \| 81.98 \|
	\| person \| 78.61 \| 90.69 \|
	\| earth \| 37.76 \| 52.23 \|
	\| door \| 48.4 \| 57.48 \|
	\| table \| 61.22 \| 75.9 \|
	\| mountain \| 53.57 \| 66.98 \|
	\| plant \| 49.92 \| 62.17 \|
	\| curtain \| 72.12 \| 82.27 \|
	\| chair \| 56.72 \| 69.87 \|
	\| car \| 81.74 \| 90.03 \|
	\| water \| 51.23 \| 67.71 \|
	\| painting \| 72.34 \| 85.58 \|
	\| sofa \| 65.15 \| 80.62 \|
	\| shelf \| 45.7 \| 66.2 \|
	\| house \| 48.79 \| 67.9 \|
	\| sea \| 47.65 \| 71.03 \|
	\| mirror \| 66.39 \| 74.69 \|
	\| rug \| 63.64 \| 69.52 \|
	\| field \| 28.14 \| 49.03 \|
	\| armchair \| 43.69 \| 60.7 \|
	\| seat \| 60.44 \| 78.75 \|
	\| fence \| 42.08 \| 57.3 \|
	\| desk \| 49.97 \| 66.93 \|
	\| rock \| 36.64 \| 52.23 \|
	\| wardrobe \| 51.82 \| 63.84 \|
	\| lamp \| 62.34 \| 72.9 \|
	\| bathtub \| 80.29 \| 84.74 \|
	\| railing \| 32.31 \| 45.49 \|
	\| cushion \| 60.92 \| 74.04 \|
	\| base \| 26.36 \| 34.08 \|
	\| box \| 22.72 \| 30.67 \|
	\| column \| 49.34 \| 59.06 \|
	\| signboard \| 35.85 \| 46.27 \|
	\| chest of drawers \| 37.83 \| 55.54 \|
	\| counter \| 21.54 \| 31.15 \|
	\| sand \| 48.92 \| 60.32 \|
	\| sink \| 69.76 \| 79.74 \|
	\| skyscraper \| 45.45 \| 52.31 \|
	\| fireplace \| 72.9 \| 87.73 \|
	\| refrigerator \| 71.89 \| 80.49 \|
	\| grandstand \| 36.46 \| 66.85 \|
	\| path \| 27.79 \| 40.71 \|
	\| stairs \| 28.42 \| 38.12 \|
	\| runway \| 75.38 \| 86.22 \|
	\| case \| 42.9 \| 55.32 \|
	\| pool table \| 91.63 \| 94.78 \|
	\| pillow \| 56.28 \| 67.41 \|
	\| screen door \| 67.52 \| 70.98 \|
	\| stairway \| 30.18 \| 35.36 \|
	\| river \| 13.36 \| 27.87 \|
	\| bridge \| 34.17 \| 45.47 \|
	\| bookcase \| 38.05 \| 52.09 \|
	\| blind \| 37.85 \| 42.34 \|
	\| coffee table \| 64.07 \| 76.72 \|
	\| toilet \| 85.37 \| 89.52 \|
	\| flower \| 39.41 \| 55.29 \|
	\| book \| 45.9 \| 61.28 \|
	\| hill \| 5.68 \| 8.74 \|
	\| bench \| 39.01 \| 46.75 \|
	\| countertop \| 51.42 \| 66.25 \|
	\| stove \| 77.63 \| 83.73 \|
	\| palm \| 46.14 \| 63.54 \|
	\| kitchen island \| 39.26 \| 75.9 \|
	\| computer \| 65.42 \| 73.35 \|
	\| swivel chair \| 38.87 \| 50.86 \|
	\| boat \| 42.28 \| 51.28 \|
	\| bar \| 25.67 \| 30.19 \|
	\| arcade machine \| 38.32 \| 40.12 \|
	\| hovel \| 6.93 \| 8.1 \|
	\| bus \| 83.53 \| 93.53 \|
	\| towel \| 65.79 \| 74.23 \|
	\| light \| 47.14 \| 54.95 \|
	\| truck \| 30.63 \| 41.1 \|
	\| tower \| 23.84 \| 38.89 \|
	\| chandelier \| 69.19 \| 81.53 \|
	\| awning \| 26.62 \| 30.23 \|
	\| streetlight \| 27.84 \| 35.36 \|
	\| booth \| 48.46 \| 57.35 \|
	\| television receiver \| 57.18 \| 84.66 \|
	\| airplane \| 52.99 \| 63.98 \|
	\| dirt track \| 1.06 \| 2.51 \|
	\| apparel \| 36.78 \| 47.11 \|
	\| pole \| 22.31 \| 28.8 \|
	\| land \| 0.0 \| 0.0 \|
	\| bannister \| 11.81 \| 15.13 \|
	\| escalator \| 35.45 \| 46.6 \|
	\| ottoman \| 46.72 \| 62.52 \|
	\| bottle \| 25.37 \| 31.43 \|
	\| buffet \| 41.7 \| 43.7 \|
	\| poster \| 27.41 \| 32.71 \|
	\| stage \| 14.35 \| 26.72 \|
	\| van \| 38.21 \| 50.17 \|
	\| ship \| 59.25 \| 88.79 \|
	\| fountain \| 7.34 \| 7.7 \|
	\| conveyer belt \| 62.31 \| 88.84 \|
	\| canopy \| 13.69 \| 15.16 \|
	\| washer \| 69.28 \| 73.2 \|
	\| plaything \| 19.93 \| 23.99 \|
	\| swimming pool \| 51.63 \| 54.24 \|
	\| stool \| 45.91 \| 58.8 \|
	\| barrel \| 45.65 \| 85.03 \|
	\| basket \| 33.1 \| 46.12 \|
	\| waterfall \| 42.87 \| 53.43 \|
	\| tent \| 89.66 \| 97.38 \|
	\| bag \| 9.84 \| 12.2 \|
	\| minibike \| 64.33 \| 79.28 \|
	\| cradle \| 79.93 \| 96.25 \|
	\| oven \| 42.37 \| 52.85 \|
	\| ball \| 43.07 \| 57.9 \|
	\| food \| 51.15 \| 62.08 \|
	\| step \| 15.61 \| 18.35 \|
	\| tank \| 46.0 \| 55.75 \|
	\| trade name \| 27.92 \| 34.45 \|
	\| microwave \| 39.15 \| 42.08 \|
	\| pot \| 52.19 \| 59.78 \|
	\| animal \| 49.47 \| 51.95 \|
	\| bicycle \| 55.21 \| 72.89 \|
	\| lake \| 54.33 \| 59.47 \|
	\| dishwasher \| 66.1 \| 72.92 \|
	\| screen \| 69.42 \| 85.63 \|
	\| blanket \| 15.15 \| 17.54 \|
	\| sculpture \| 63.9 \| 74.98 \|
	\| hood \| 60.27 \| 63.52 \|
	\| sconce \| 45.91 \| 54.41 \|
	\| vase \| 39.25 \| 55.99 \|
	\| traffic light \| 30.75 \| 45.47 \|
	\| tray \| 13.35 \| 18.37 \|
	\| ashcan \| 41.52 \| 51.42 \|
	\| fan \| 59.05 \| 69.66 \|
	\| pier \| 43.23 \| 81.25 \|
	\| crt screen \| 4.6 \| 6.14 \|
	\| plate \| 52.27 \| 69.15 \|
	\| monitor \| 49.29 \| 62.59 \|
	\| bulletin board \| 27.79 \| 30.79 \|
	\| shower \| 6.19 \| 12.16 \|
	\| radiator \| 49.5 \| 52.94 \|
	\| glass \| 15.33 \| 17.22 \|
	\| clock \| 21.01 \| 24.63 \|
	\| flag \| 25.02 \| 26.91 \|
	+---------------------+-------+-------+
	2023/11/28 08:34:11 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.5000 mIoU: 47.1100 mAcc: 57.9600 data_time: 0.0018 time: 0.7632
	2023/11/28 08:42:15 - mmengine - INFO - Iter(train) [ 80500/120000] base_lr: 5.0384e-05 lr: 6.3986e-06 eta: 10:42:04 time: 0.9751 data_time: 0.0144 memory: 8153 grad_norm: 0.0170 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 08:50:19 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 08:50:19 - mmengine - INFO - Iter(train) [ 81000/120000] base_lr: 4.9275e-05 lr: 6.2977e-06 eta: 10:33:49 time: 0.9749 data_time: 0.0144 memory: 8153 grad_norm: 0.0169 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 08:50:19 - mmengine - INFO - Saving checkpoint at 81000 iterations
	2023/11/28 08:58:32 - mmengine - INFO - Iter(train) [ 81500/120000] base_lr: 4.8174e-05 lr: 6.1977e-06 eta: 10:25:52 time: 0.9751 data_time: 0.0144 memory: 8153 grad_norm: 0.0169 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 09:06:36 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 09:06:36 - mmengine - INFO - Iter(train) [ 82000/120000] base_lr: 4.7083e-05 lr: 6.0984e-06 eta: 10:17:38 time: 0.9749 data_time: 0.0144 memory: 8153 grad_norm: 0.0165 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 09:06:36 - mmengine - INFO - Saving checkpoint at 82000 iterations
	2023/11/28 09:14:50 - mmengine - INFO - Iter(train) [ 82500/120000] base_lr: 4.6001e-05 lr: 6.0001e-06 eta: 10:09:40 time: 0.9751 data_time: 0.0145 memory: 8153 grad_norm: 0.0164 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 09:22:54 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 09:22:54 - mmengine - INFO - Iter(train) [ 83000/120000] base_lr: 4.4928e-05 lr: 5.9025e-06 eta: 10:01:26 time: 0.9751 data_time: 0.0145 memory: 8153 grad_norm: 0.0163 loss: 0.0052 semantic_segmentation_loss_cls: 0.0052
	2023/11/28 09:22:54 - mmengine - INFO - Saving checkpoint at 83000 iterations
	2023/11/28 09:31:07 - mmengine - INFO - Iter(train) [ 83500/120000] base_lr: 4.3865e-05 lr: 5.8059e-06 eta: 9:53:26 time: 0.9750 data_time: 0.0145 memory: 8153 grad_norm: 0.0162 loss: 0.0051 semantic_segmentation_loss_cls: 0.0051
	2023/11/28 09:39:11 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 09:39:11 - mmengine - INFO - Iter(train) [ 84000/120000] base_lr: 4.2811e-05 lr: 5.7101e-06 eta: 9:45:14 time: 0.9752 data_time: 0.0145 memory: 8153 grad_norm: 0.0163 loss: 0.0051 semantic_segmentation_loss_cls: 0.0051
	2023/11/28 09:39:11 - mmengine - INFO - Saving checkpoint at 84000 iterations
	2023/11/28 09:47:24 - mmengine - INFO - Iter(train) [ 84500/120000] base_lr: 4.1768e-05 lr: 5.6153e-06 eta: 9:37:14 time: 0.9772 data_time: 0.0166 memory: 8153 grad_norm: 0.0163 loss: 0.0051 semantic_segmentation_loss_cls: 0.0051
	2023/11/28 09:55:29 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 09:55:29 - mmengine - INFO - Iter(train) [ 85000/120000] base_lr: 4.0735e-05 lr: 5.5213e-06 eta: 9:29:01 time: 0.9774 data_time: 0.0166 memory: 8153 grad_norm: 0.0162 loss: 0.0051 semantic_segmentation_loss_cls: 0.0051
	2023/11/28 09:55:29 - mmengine - INFO - Saving checkpoint at 85000 iterations
	2023/11/28 09:58:50 - mmengine - INFO - per class results:
	2023/11/28 09:58:50 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.3 \| 89.14 \|
	\| building \| 81.95 \| 92.5 \|
	\| sky \| 93.49 \| 97.92 \|
	\| floor \| 80.9 \| 90.97 \|
	\| tree \| 72.78 \| 87.32 \|
	\| ceiling \| 84.13 \| 94.58 \|
	\| road \| 84.64 \| 91.93 \|
	\| bed \| 86.57 \| 95.66 \|
	\| windowpane \| 62.1 \| 78.91 \|
	\| grass \| 69.16 \| 82.19 \|
	\| cabinet \| 60.19 \| 73.85 \|
	\| sidewalk \| 67.34 \| 77.54 \|
	\| person \| 79.11 \| 91.17 \|
	\| earth \| 39.78 \| 55.17 \|
	\| door \| 50.91 \| 61.68 \|
	\| table \| 59.98 \| 75.51 \|
	\| mountain \| 55.13 \| 70.28 \|
	\| plant \| 49.65 \| 61.14 \|
	\| curtain \| 72.0 \| 83.14 \|
	\| chair \| 56.95 \| 69.43 \|
	\| car \| 81.73 \| 90.91 \|
	\| water \| 52.61 \| 67.58 \|
	\| painting \| 69.48 \| 87.83 \|
	\| sofa \| 64.08 \| 78.6 \|
	\| shelf \| 46.21 \| 63.89 \|
	\| house \| 47.69 \| 64.18 \|
	\| sea \| 49.39 \| 71.02 \|
	\| mirror \| 65.95 \| 75.88 \|
	\| rug \| 64.32 \| 70.02 \|
	\| field \| 30.84 \| 49.63 \|
	\| armchair \| 42.59 \| 60.19 \|
	\| seat \| 60.26 \| 78.45 \|
	\| fence \| 42.55 \| 57.45 \|
	\| desk \| 48.01 \| 67.81 \|
	\| rock \| 33.63 \| 52.96 \|
	\| wardrobe \| 49.63 \| 65.87 \|
	\| lamp \| 61.39 \| 74.33 \|
	\| bathtub \| 79.41 \| 84.0 \|
	\| railing \| 32.94 \| 47.28 \|
	\| cushion \| 60.13 \| 70.99 \|
	\| base \| 22.36 \| 27.83 \|
	\| box \| 25.58 \| 34.39 \|
	\| column \| 47.96 \| 54.29 \|
	\| signboard \| 36.89 \| 48.57 \|
	\| chest of drawers \| 38.73 \| 55.78 \|
	\| counter \| 22.76 \| 33.46 \|
	\| sand \| 47.78 \| 53.86 \|
	\| sink \| 71.94 \| 80.42 \|
	\| skyscraper \| 47.26 \| 54.93 \|
	\| fireplace \| 72.42 \| 92.03 \|
	\| refrigerator \| 69.12 \| 78.32 \|
	\| grandstand \| 43.07 \| 65.99 \|
	\| path \| 29.89 \| 42.07 \|
	\| stairs \| 31.92 \| 41.73 \|
	\| runway \| 77.18 \| 85.7 \|
	\| case \| 45.31 \| 63.4 \|
	\| pool table \| 90.98 \| 95.03 \|
	\| pillow \| 57.53 \| 70.81 \|
	\| screen door \| 63.84 \| 66.68 \|
	\| stairway \| 29.73 \| 35.83 \|
	\| river \| 13.11 \| 28.72 \|
	\| bridge \| 37.02 \| 46.87 \|
	\| bookcase \| 40.26 \| 61.95 \|
	\| blind \| 37.34 \| 40.05 \|
	\| coffee table \| 61.85 \| 79.23 \|
	\| toilet \| 85.53 \| 89.48 \|
	\| flower \| 38.03 \| 53.77 \|
	\| book \| 45.45 \| 59.49 \|
	\| hill \| 6.46 \| 9.89 \|
	\| bench \| 38.64 \| 45.7 \|
	\| countertop \| 50.91 \| 66.57 \|
	\| stove \| 79.65 \| 85.11 \|
	\| palm \| 47.25 \| 67.72 \|
	\| kitchen island \| 40.06 \| 71.64 \|
	\| computer \| 61.41 \| 70.18 \|
	\| swivel chair \| 39.08 \| 51.74 \|
	\| boat \| 44.14 \| 49.2 \|
	\| bar \| 24.07 \| 27.96 \|
	\| arcade machine \| 55.2 \| 58.98 \|
	\| hovel \| 6.23 \| 7.77 \|
	\| bus \| 87.81 \| 91.81 \|
	\| towel \| 64.14 \| 74.29 \|
	\| light \| 49.69 \| 58.88 \|
	\| truck \| 23.18 \| 34.2 \|
	\| tower \| 25.89 \| 38.03 \|
	\| chandelier \| 67.67 \| 79.27 \|
	\| awning \| 26.81 \| 31.15 \|
	\| streetlight \| 31.51 \| 43.24 \|
	\| booth \| 47.38 \| 53.29 \|
	\| television receiver \| 65.34 \| 81.58 \|
	\| airplane \| 56.86 \| 64.21 \|
	\| dirt track \| 7.95 \| 18.56 \|
	\| apparel \| 30.11 \| 40.06 \|
	\| pole \| 22.51 \| 31.19 \|
	\| land \| 0.57 \| 0.7 \|
	\| bannister \| 14.7 \| 18.99 \|
	\| escalator \| 31.51 \| 41.06 \|
	\| ottoman \| 43.67 \| 53.48 \|
	\| bottle \| 26.02 \| 31.69 \|
	\| buffet \| 53.43 \| 58.69 \|
	\| poster \| 11.79 \| 12.63 \|
	\| stage \| 14.51 \| 27.87 \|
	\| van \| 37.2 \| 53.32 \|
	\| ship \| 60.45 \| 85.97 \|
	\| fountain \| 14.99 \| 16.11 \|
	\| conveyer belt \| 52.85 \| 88.07 \|
	\| canopy \| 17.68 \| 19.27 \|
	\| washer \| 70.37 \| 72.83 \|
	\| plaything \| 25.37 \| 30.97 \|
	\| swimming pool \| 68.13 \| 70.7 \|
	\| stool \| 46.43 \| 59.47 \|
	\| barrel \| 51.46 \| 65.68 \|
	\| basket \| 32.64 \| 43.47 \|
	\| waterfall \| 41.95 \| 52.59 \|
	\| tent \| 86.31 \| 97.81 \|
	\| bag \| 9.22 \| 10.86 \|
	\| minibike \| 62.63 \| 72.93 \|
	\| cradle \| 73.58 \| 95.23 \|
	\| oven \| 50.66 \| 59.48 \|
	\| ball \| 39.3 \| 45.6 \|
	\| food \| 46.31 \| 53.25 \|
	\| step \| 7.51 \| 9.26 \|
	\| tank \| 49.32 \| 57.78 \|
	\| trade name \| 23.05 \| 26.03 \|
	\| microwave \| 39.15 \| 42.07 \|
	\| pot \| 50.16 \| 57.65 \|
	\| animal \| 49.53 \| 52.46 \|
	\| bicycle \| 56.57 \| 77.5 \|
	\| lake \| 57.04 \| 65.92 \|
	\| dishwasher \| 68.57 \| 72.54 \|
	\| screen \| 63.79 \| 78.74 \|
	\| blanket \| 11.62 \| 12.87 \|
	\| sculpture \| 61.14 \| 76.81 \|
	\| hood \| 62.01 \| 68.22 \|
	\| sconce \| 46.59 \| 61.47 \|
	\| vase \| 38.33 \| 56.84 \|
	\| traffic light \| 34.1 \| 46.49 \|
	\| tray \| 14.21 \| 19.97 \|
	\| ashcan \| 37.84 \| 51.62 \|
	\| fan \| 59.7 \| 70.7 \|
	\| pier \| 48.57 \| 82.5 \|
	\| crt screen \| 4.0 \| 7.83 \|
	\| plate \| 54.76 \| 69.17 \|
	\| monitor \| 34.82 \| 40.05 \|
	\| bulletin board \| 26.86 \| 31.76 \|
	\| shower \| 9.31 \| 12.41 \|
	\| radiator \| 45.03 \| 49.1 \|
	\| glass \| 15.5 \| 17.14 \|
	\| clock \| 22.78 \| 30.01 \|
	\| flag \| 28.77 \| 33.26 \|
	+---------------------+-------+-------+
	2023/11/28 09:58:50 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.7600 mIoU: 47.3500 mAcc: 58.0600 data_time: 0.0018 time: 0.7636
	2023/11/28 10:06:54 - mmengine - INFO - Iter(train) [ 85500/120000] base_lr: 3.9712e-05 lr: 5.4283e-06 eta: 9:20:50 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0160 loss: 0.0051 semantic_segmentation_loss_cls: 0.0051
	2023/11/28 10:14:58 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 10:14:58 - mmengine - INFO - Iter(train) [ 86000/120000] base_lr: 3.8699e-05 lr: 5.3363e-06 eta: 9:12:37 time: 0.9753 data_time: 0.0146 memory: 8153 grad_norm: 0.0159 loss: 0.0050 semantic_segmentation_loss_cls: 0.0050
	2023/11/28 10:14:58 - mmengine - INFO - Saving checkpoint at 86000 iterations
	2023/11/28 10:23:11 - mmengine - INFO - Iter(train) [ 86500/120000] base_lr: 3.7698e-05 lr: 5.2452e-06 eta: 9:04:36 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0158 loss: 0.0050 semantic_segmentation_loss_cls: 0.0050
	2023/11/28 10:31:15 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 10:31:15 - mmengine - INFO - Iter(train) [ 87000/120000] base_lr: 3.6707e-05 lr: 5.1551e-06 eta: 8:56:24 time: 0.9751 data_time: 0.0146 memory: 8153 grad_norm: 0.0158 loss: 0.0050 semantic_segmentation_loss_cls: 0.0050
	2023/11/28 10:31:15 - mmengine - INFO - Saving checkpoint at 87000 iterations
	2023/11/28 10:39:29 - mmengine - INFO - Iter(train) [ 87500/120000] base_lr: 3.5727e-05 lr: 5.0661e-06 eta: 8:48:23 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0156 loss: 0.0050 semantic_segmentation_loss_cls: 0.0050
	2023/11/28 10:47:33 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 10:47:33 - mmengine - INFO - Iter(train) [ 88000/120000] base_lr: 3.4758e-05 lr: 4.9780e-06 eta: 8:40:11 time: 0.9752 data_time: 0.0147 memory: 8153 grad_norm: 0.0154 loss: 0.0050 semantic_segmentation_loss_cls: 0.0050
	2023/11/28 10:47:33 - mmengine - INFO - Saving checkpoint at 88000 iterations
	2023/11/28 10:55:46 - mmengine - INFO - Iter(train) [ 88500/120000] base_lr: 3.3801e-05 lr: 4.8910e-06 eta: 8:32:10 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0155 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:03:50 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 11:03:50 - mmengine - INFO - Iter(train) [ 89000/120000] base_lr: 3.2855e-05 lr: 4.8050e-06 eta: 8:23:58 time: 0.9751 data_time: 0.0146 memory: 8153 grad_norm: 0.0154 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:03:50 - mmengine - INFO - Saving checkpoint at 89000 iterations
	2023/11/28 11:12:03 - mmengine - INFO - Iter(train) [ 89500/120000] base_lr: 3.1921e-05 lr: 4.7201e-06 eta: 8:15:56 time: 0.9772 data_time: 0.0167 memory: 8153 grad_norm: 0.0153 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:20:08 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 11:20:08 - mmengine - INFO - Iter(train) [ 90000/120000] base_lr: 3.0998e-05 lr: 4.6362e-06 eta: 8:07:45 time: 0.9773 data_time: 0.0167 memory: 8153 grad_norm: 0.0153 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:20:08 - mmengine - INFO - Saving checkpoint at 90000 iterations
	2023/11/28 11:23:29 - mmengine - INFO - per class results:
	2023/11/28 11:23:29 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.79 \| 88.89 \|
	\| building \| 81.56 \| 93.16 \|
	\| sky \| 93.38 \| 98.11 \|
	\| floor \| 80.86 \| 90.26 \|
	\| tree \| 72.82 \| 86.56 \|
	\| ceiling \| 83.86 \| 94.22 \|
	\| road \| 84.78 \| 91.87 \|
	\| bed \| 88.05 \| 94.16 \|
	\| windowpane \| 61.71 \| 78.56 \|
	\| grass \| 68.68 \| 84.24 \|
	\| cabinet \| 60.8 \| 73.42 \|
	\| sidewalk \| 66.83 \| 78.83 \|
	\| person \| 79.11 \| 91.49 \|
	\| earth \| 39.25 \| 53.64 \|
	\| door \| 51.13 \| 61.37 \|
	\| table \| 60.28 \| 75.15 \|
	\| mountain \| 55.08 \| 70.99 \|
	\| plant \| 49.55 \| 59.88 \|
	\| curtain \| 72.53 \| 84.21 \|
	\| chair \| 58.03 \| 71.1 \|
	\| car \| 81.72 \| 90.67 \|
	\| water \| 50.66 \| 65.87 \|
	\| painting \| 71.08 \| 85.78 \|
	\| sofa \| 63.51 \| 75.85 \|
	\| shelf \| 45.81 \| 64.18 \|
	\| house \| 42.73 \| 54.71 \|
	\| sea \| 46.63 \| 73.92 \|
	\| mirror \| 66.12 \| 78.58 \|
	\| rug \| 63.7 \| 74.28 \|
	\| field \| 24.71 \| 36.64 \|
	\| armchair \| 44.97 \| 68.1 \|
	\| seat \| 61.86 \| 81.81 \|
	\| fence \| 44.41 \| 59.82 \|
	\| desk \| 48.37 \| 71.54 \|
	\| rock \| 36.02 \| 57.15 \|
	\| wardrobe \| 52.86 \| 65.87 \|
	\| lamp \| 61.8 \| 73.25 \|
	\| bathtub \| 81.36 \| 85.05 \|
	\| railing \| 33.04 \| 44.61 \|
	\| cushion \| 61.11 \| 73.78 \|
	\| base \| 23.17 \| 29.34 \|
	\| box \| 23.37 \| 29.89 \|
	\| column \| 47.02 \| 53.66 \|
	\| signboard \| 36.55 \| 46.74 \|
	\| chest of drawers \| 37.19 \| 57.9 \|
	\| counter \| 19.42 \| 26.77 \|
	\| sand \| 42.83 \| 54.04 \|
	\| sink \| 68.21 \| 79.98 \|
	\| skyscraper \| 48.92 \| 57.55 \|
	\| fireplace \| 71.35 \| 86.05 \|
	\| refrigerator \| 70.95 \| 80.66 \|
	\| grandstand \| 42.34 \| 70.37 \|
	\| path \| 29.03 \| 40.87 \|
	\| stairs \| 28.73 \| 40.43 \|
	\| runway \| 74.05 \| 87.23 \|
	\| case \| 42.81 \| 57.57 \|
	\| pool table \| 91.41 \| 95.35 \|
	\| pillow \| 59.48 \| 70.54 \|
	\| screen door \| 74.0 \| 78.58 \|
	\| stairway \| 28.91 \| 36.58 \|
	\| river \| 15.66 \| 26.15 \|
	\| bridge \| 33.82 \| 41.74 \|
	\| bookcase \| 37.78 \| 53.58 \|
	\| blind \| 40.62 \| 45.86 \|
	\| coffee table \| 62.85 \| 79.96 \|
	\| toilet \| 84.12 \| 89.71 \|
	\| flower \| 38.14 \| 55.32 \|
	\| book \| 46.65 \| 62.51 \|
	\| hill \| 5.38 \| 7.75 \|
	\| bench \| 37.19 \| 45.52 \|
	\| countertop \| 51.24 \| 64.99 \|
	\| stove \| 78.39 \| 85.46 \|
	\| palm \| 48.74 \| 70.09 \|
	\| kitchen island \| 37.8 \| 76.28 \|
	\| computer \| 64.61 \| 73.49 \|
	\| swivel chair \| 40.0 \| 50.04 \|
	\| boat \| 43.0 \| 50.95 \|
	\| bar \| 15.78 \| 18.06 \|
	\| arcade machine \| 38.87 \| 39.92 \|
	\| hovel \| 6.95 \| 8.32 \|
	\| bus \| 88.81 \| 92.1 \|
	\| towel \| 63.57 \| 77.38 \|
	\| light \| 48.8 \| 55.55 \|
	\| truck \| 24.64 \| 37.66 \|
	\| tower \| 27.61 \| 38.21 \|
	\| chandelier \| 67.54 \| 82.94 \|
	\| awning \| 30.05 \| 35.21 \|
	\| streetlight \| 28.59 \| 37.36 \|
	\| booth \| 44.31 \| 48.55 \|
	\| television receiver \| 63.01 \| 83.59 \|
	\| airplane \| 55.82 \| 64.55 \|
	\| dirt track \| 14.8 \| 22.15 \|
	\| apparel \| 34.11 \| 43.75 \|
	\| pole \| 23.44 \| 29.65 \|
	\| land \| 0.53 \| 0.69 \|
	\| bannister \| 12.58 \| 15.97 \|
	\| escalator \| 36.51 \| 48.38 \|
	\| ottoman \| 48.08 \| 58.41 \|
	\| bottle \| 28.92 \| 37.92 \|
	\| buffet \| 49.51 \| 57.91 \|
	\| poster \| 25.12 \| 29.01 \|
	\| stage \| 13.67 \| 26.85 \|
	\| van \| 38.96 \| 51.89 \|
	\| ship \| 58.36 \| 82.71 \|
	\| fountain \| 3.87 \| 4.21 \|
	\| conveyer belt \| 69.1 \| 86.78 \|
	\| canopy \| 17.96 \| 20.66 \|
	\| washer \| 71.0 \| 74.26 \|
	\| plaything \| 25.54 \| 33.25 \|
	\| swimming pool \| 64.69 \| 72.31 \|
	\| stool \| 45.15 \| 59.74 \|
	\| barrel \| 45.75 \| 74.48 \|
	\| basket \| 32.99 \| 41.81 \|
	\| waterfall \| 41.05 \| 53.43 \|
	\| tent \| 89.34 \| 97.13 \|
	\| bag \| 9.22 \| 11.21 \|
	\| minibike \| 56.86 \| 69.19 \|
	\| cradle \| 76.11 \| 95.27 \|
	\| oven \| 45.53 \| 55.96 \|
	\| ball \| 43.44 \| 57.86 \|
	\| food \| 49.95 \| 59.4 \|
	\| step \| 13.54 \| 18.57 \|
	\| tank \| 44.61 \| 54.19 \|
	\| trade name \| 27.12 \| 32.13 \|
	\| microwave \| 39.01 \| 41.85 \|
	\| pot \| 49.92 \| 57.75 \|
	\| animal \| 48.34 \| 50.76 \|
	\| bicycle \| 55.87 \| 72.85 \|
	\| lake \| 58.91 \| 65.36 \|
	\| dishwasher \| 66.78 \| 70.27 \|
	\| screen \| 61.29 \| 87.18 \|
	\| blanket \| 11.31 \| 12.88 \|
	\| sculpture \| 62.39 \| 75.12 \|
	\| hood \| 60.75 \| 64.56 \|
	\| sconce \| 44.42 \| 50.6 \|
	\| vase \| 34.09 \| 47.33 \|
	\| traffic light \| 35.06 \| 48.44 \|
	\| tray \| 14.82 \| 21.95 \|
	\| ashcan \| 33.42 \| 42.73 \|
	\| fan \| 58.1 \| 66.33 \|
	\| pier \| 44.08 \| 77.13 \|
	\| crt screen \| 3.23 \| 5.6 \|
	\| plate \| 53.69 \| 71.94 \|
	\| monitor \| 36.69 \| 43.55 \|
	\| bulletin board \| 32.54 \| 37.91 \|
	\| shower \| 7.46 \| 11.86 \|
	\| radiator \| 49.1 \| 52.55 \|
	\| glass \| 14.45 \| 15.79 \|
	\| clock \| 21.64 \| 26.38 \|
	\| flag \| 28.01 \| 32.02 \|
	+---------------------+-------+-------+
	2023/11/28 11:23:29 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.6700 mIoU: 47.2000 mAcc: 58.0600 data_time: 0.0020 time: 0.7628
	2023/11/28 11:31:33 - mmengine - INFO - Iter(train) [ 90500/120000] base_lr: 3.0088e-05 lr: 4.5534e-06 eta: 7:59:34 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0153 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:39:37 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 11:39:37 - mmengine - INFO - Iter(train) [ 91000/120000] base_lr: 2.9190e-05 lr: 4.4718e-06 eta: 7:51:23 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0152 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:39:37 - mmengine - INFO - Saving checkpoint at 91000 iterations
	2023/11/28 11:47:50 - mmengine - INFO - Iter(train) [ 91500/120000] base_lr: 2.8304e-05 lr: 4.3913e-06 eta: 7:43:20 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0152 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:55:55 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 11:55:55 - mmengine - INFO - Iter(train) [ 92000/120000] base_lr: 2.7430e-05 lr: 4.3119e-06 eta: 7:35:09 time: 0.9753 data_time: 0.0146 memory: 8153 grad_norm: 0.0150 loss: 0.0049 semantic_segmentation_loss_cls: 0.0049
	2023/11/28 11:55:55 - mmengine - INFO - Saving checkpoint at 92000 iterations
	2023/11/28 12:04:08 - mmengine - INFO - Iter(train) [ 92500/120000] base_lr: 2.6570e-05 lr: 4.2336e-06 eta: 7:27:06 time: 0.9752 data_time: 0.0145 memory: 8153 grad_norm: 0.0147 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:12:12 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 12:12:12 - mmengine - INFO - Iter(train) [ 93000/120000] base_lr: 2.5721e-05 lr: 4.1565e-06 eta: 7:18:56 time: 0.9753 data_time: 0.0145 memory: 8153 grad_norm: 0.0148 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:12:12 - mmengine - INFO - Saving checkpoint at 93000 iterations
	2023/11/28 12:20:26 - mmengine - INFO - Iter(train) [ 93500/120000] base_lr: 2.4886e-05 lr: 4.0806e-06 eta: 7:10:52 time: 0.9754 data_time: 0.0146 memory: 8153 grad_norm: 0.0148 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:28:30 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 12:28:30 - mmengine - INFO - Iter(train) [ 94000/120000] base_lr: 2.4064e-05 lr: 4.0058e-06 eta: 7:02:42 time: 0.9752 data_time: 0.0146 memory: 8153 grad_norm: 0.0147 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:28:30 - mmengine - INFO - Saving checkpoint at 94000 iterations
	2023/11/28 12:36:43 - mmengine - INFO - Iter(train) [ 94500/120000] base_lr: 2.3255e-05 lr: 3.9323e-06 eta: 6:54:38 time: 0.9775 data_time: 0.0167 memory: 8153 grad_norm: 0.0147 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:44:47 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 12:44:47 - mmengine - INFO - Iter(train) [ 95000/120000] base_lr: 2.2460e-05 lr: 3.8600e-06 eta: 6:46:28 time: 0.9774 data_time: 0.0167 memory: 8153 grad_norm: 0.0146 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 12:44:47 - mmengine - INFO - Saving checkpoint at 95000 iterations
	2023/11/28 12:48:09 - mmengine - INFO - per class results:
	2023/11/28 12:48:09 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 76.95 \| 89.16 \|
	\| building \| 81.58 \| 92.57 \|
	\| sky \| 93.61 \| 97.95 \|
	\| floor \| 80.71 \| 90.83 \|
	\| tree \| 73.06 \| 87.35 \|
	\| ceiling \| 83.93 \| 94.18 \|
	\| road \| 83.84 \| 91.2 \|
	\| bed \| 88.21 \| 95.48 \|
	\| windowpane \| 61.93 \| 77.39 \|
	\| grass \| 67.45 \| 83.1 \|
	\| cabinet \| 61.77 \| 74.25 \|
	\| sidewalk \| 65.81 \| 79.66 \|
	\| person \| 78.58 \| 91.81 \|
	\| earth \| 38.54 \| 49.56 \|
	\| door \| 51.1 \| 61.53 \|
	\| table \| 60.75 \| 74.21 \|
	\| mountain \| 55.21 \| 71.3 \|
	\| plant \| 49.88 \| 60.74 \|
	\| curtain \| 72.38 \| 83.67 \|
	\| chair \| 58.07 \| 71.36 \|
	\| car \| 81.4 \| 90.59 \|
	\| water \| 40.24 \| 47.61 \|
	\| painting \| 71.63 \| 86.18 \|
	\| sofa \| 64.58 \| 79.4 \|
	\| shelf \| 44.9 \| 62.56 \|
	\| house \| 45.96 \| 62.42 \|
	\| sea \| 47.5 \| 87.94 \|
	\| mirror \| 66.95 \| 77.31 \|
	\| rug \| 62.88 \| 70.97 \|
	\| field \| 30.38 \| 51.17 \|
	\| armchair \| 43.31 \| 62.43 \|
	\| seat \| 61.48 \| 78.4 \|
	\| fence \| 43.06 \| 56.03 \|
	\| desk \| 52.01 \| 70.99 \|
	\| rock \| 34.05 \| 52.54 \|
	\| wardrobe \| 51.96 \| 66.82 \|
	\| lamp \| 62.05 \| 73.63 \|
	\| bathtub \| 80.73 \| 84.4 \|
	\| railing \| 33.35 \| 46.77 \|
	\| cushion \| 60.56 \| 70.81 \|
	\| base \| 23.69 \| 31.29 \|
	\| box \| 23.24 \| 29.36 \|
	\| column \| 47.39 \| 55.3 \|
	\| signboard \| 35.96 \| 46.9 \|
	\| chest of drawers \| 42.15 \| 61.27 \|
	\| counter \| 21.33 \| 30.46 \|
	\| sand \| 47.86 \| 57.59 \|
	\| sink \| 71.47 \| 81.83 \|
	\| skyscraper \| 48.25 \| 57.79 \|
	\| fireplace \| 73.23 \| 90.55 \|
	\| refrigerator \| 72.51 \| 79.97 \|
	\| grandstand \| 42.79 \| 68.31 \|
	\| path \| 29.05 \| 40.28 \|
	\| stairs \| 25.7 \| 34.13 \|
	\| runway \| 70.68 \| 87.13 \|
	\| case \| 42.81 \| 57.12 \|
	\| pool table \| 91.96 \| 95.6 \|
	\| pillow \| 58.68 \| 70.78 \|
	\| screen door \| 73.71 \| 75.3 \|
	\| stairway \| 26.01 \| 36.68 \|
	\| river \| 13.13 \| 30.93 \|
	\| bridge \| 35.39 \| 42.21 \|
	\| bookcase \| 37.07 \| 57.46 \|
	\| blind \| 37.87 \| 41.64 \|
	\| coffee table \| 60.48 \| 78.81 \|
	\| toilet \| 84.93 \| 89.78 \|
	\| flower \| 37.22 \| 53.44 \|
	\| book \| 47.64 \| 65.34 \|
	\| hill \| 6.22 \| 9.44 \|
	\| bench \| 38.4 \| 45.21 \|
	\| countertop \| 53.32 \| 64.28 \|
	\| stove \| 77.65 \| 84.23 \|
	\| palm \| 48.42 \| 68.48 \|
	\| kitchen island \| 37.79 \| 79.7 \|
	\| computer \| 63.5 \| 70.95 \|
	\| swivel chair \| 39.25 \| 50.35 \|
	\| boat \| 41.8 \| 50.68 \|
	\| bar \| 23.6 \| 27.21 \|
	\| arcade machine \| 35.43 \| 36.74 \|
	\| hovel \| 7.12 \| 8.29 \|
	\| bus \| 90.49 \| 94.28 \|
	\| towel \| 64.83 \| 75.33 \|
	\| light \| 50.9 \| 61.23 \|
	\| truck \| 28.78 \| 36.29 \|
	\| tower \| 28.56 \| 42.44 \|
	\| chandelier \| 66.79 \| 76.13 \|
	\| awning \| 28.83 \| 33.02 \|
	\| streetlight \| 30.85 \| 39.29 \|
	\| booth \| 45.96 \| 49.33 \|
	\| television receiver \| 57.76 \| 84.47 \|
	\| airplane \| 57.69 \| 65.26 \|
	\| dirt track \| 12.34 \| 17.11 \|
	\| apparel \| 31.64 \| 41.49 \|
	\| pole \| 24.75 \| 33.62 \|
	\| land \| 0.48 \| 0.62 \|
	\| bannister \| 14.57 \| 18.81 \|
	\| escalator \| 33.25 \| 42.39 \|
	\| ottoman \| 47.74 \| 60.58 \|
	\| bottle \| 28.51 \| 35.28 \|
	\| buffet \| 51.07 \| 57.8 \|
	\| poster \| 34.69 \| 41.1 \|
	\| stage \| 13.1 \| 26.95 \|
	\| van \| 38.93 \| 53.28 \|
	\| ship \| 57.77 \| 84.35 \|
	\| fountain \| 14.32 \| 15.51 \|
	\| conveyer belt \| 70.7 \| 88.9 \|
	\| canopy \| 19.02 \| 21.53 \|
	\| washer \| 71.69 \| 74.36 \|
	\| plaything \| 23.3 \| 30.63 \|
	\| swimming pool \| 50.15 \| 63.81 \|
	\| stool \| 44.49 \| 56.25 \|
	\| barrel \| 23.74 \| 74.84 \|
	\| basket \| 34.56 \| 45.19 \|
	\| waterfall \| 41.59 \| 52.21 \|
	\| tent \| 76.18 \| 97.79 \|
	\| bag \| 9.01 \| 10.62 \|
	\| minibike \| 57.89 \| 67.81 \|
	\| cradle \| 77.89 \| 95.57 \|
	\| oven \| 42.95 \| 54.94 \|
	\| ball \| 44.19 \| 56.75 \|
	\| food \| 48.78 \| 59.09 \|
	\| step \| 6.48 \| 8.24 \|
	\| tank \| 45.98 \| 54.5 \|
	\| trade name \| 31.41 \| 38.79 \|
	\| microwave \| 37.73 \| 40.34 \|
	\| pot \| 51.26 \| 58.46 \|
	\| animal \| 50.89 \| 54.02 \|
	\| bicycle \| 57.6 \| 73.24 \|
	\| lake \| 50.25 \| 60.85 \|
	\| dishwasher \| 66.58 \| 70.0 \|
	\| screen \| 66.07 \| 85.93 \|
	\| blanket \| 12.78 \| 14.94 \|
	\| sculpture \| 60.05 \| 77.7 \|
	\| hood \| 64.25 \| 68.22 \|
	\| sconce \| 47.74 \| 56.75 \|
	\| vase \| 34.69 \| 46.89 \|
	\| traffic light \| 34.51 \| 47.24 \|
	\| tray \| 13.71 \| 19.08 \|
	\| ashcan \| 35.15 \| 45.55 \|
	\| fan \| 58.03 \| 68.83 \|
	\| pier \| 44.13 \| 77.32 \|
	\| crt screen \| 3.66 \| 5.49 \|
	\| plate \| 54.85 \| 69.69 \|
	\| monitor \| 47.02 \| 55.06 \|
	\| bulletin board \| 33.72 \| 41.71 \|
	\| shower \| 6.59 \| 10.52 \|
	\| radiator \| 48.28 \| 51.61 \|
	\| glass \| 14.51 \| 15.52 \|
	\| clock \| 21.3 \| 27.15 \|
	\| flag \| 29.18 \| 33.8 \|
	+---------------------+-------+-------+
	2023/11/28 12:48:09 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.6200 mIoU: 47.1700 mAcc: 58.3500 data_time: 0.0019 time: 0.7629
	2023/11/28 12:56:13 - mmengine - INFO - Iter(train) [ 95500/120000] base_lr: 2.1677e-05 lr: 3.7889e-06 eta: 6:38:18 time: 0.9755 data_time: 0.0147 memory: 8153 grad_norm: 0.0145 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 13:04:17 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 13:04:17 - mmengine - INFO - Iter(train) [ 96000/120000] base_lr: 2.0909e-05 lr: 3.7190e-06 eta: 6:30:08 time: 0.9753 data_time: 0.0147 memory: 8153 grad_norm: 0.0144 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 13:04:17 - mmengine - INFO - Saving checkpoint at 96000 iterations
	2023/11/28 13:12:31 - mmengine - INFO - Iter(train) [ 96500/120000] base_lr: 2.0154e-05 lr: 3.6504e-06 eta: 6:22:04 time: 0.9755 data_time: 0.0147 memory: 8153 grad_norm: 0.0144 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 13:20:34 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 13:20:34 - mmengine - INFO - Iter(train) [ 97000/120000] base_lr: 1.9413e-05 lr: 3.5830e-06 eta: 6:13:54 time: 0.9753 data_time: 0.0148 memory: 8153 grad_norm: 0.0142 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 13:20:34 - mmengine - INFO - Saving checkpoint at 97000 iterations
	2023/11/28 13:28:48 - mmengine - INFO - Iter(train) [ 97500/120000] base_lr: 1.8686e-05 lr: 3.5169e-06 eta: 6:05:50 time: 0.9753 data_time: 0.0148 memory: 8153 grad_norm: 0.0141 loss: 0.0048 semantic_segmentation_loss_cls: 0.0048
	2023/11/28 13:36:52 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 13:36:52 - mmengine - INFO - Iter(train) [ 98000/120000] base_lr: 1.7973e-05 lr: 3.4521e-06 eta: 5:57:40 time: 0.9754 data_time: 0.0148 memory: 8153 grad_norm: 0.0140 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 13:36:52 - mmengine - INFO - Saving checkpoint at 98000 iterations
	2023/11/28 13:45:06 - mmengine - INFO - Iter(train) [ 98500/120000] base_lr: 1.7274e-05 lr: 3.3886e-06 eta: 5:49:35 time: 0.9753 data_time: 0.0148 memory: 8153 grad_norm: 0.0139 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 13:53:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 13:53:10 - mmengine - INFO - Iter(train) [ 99000/120000] base_lr: 1.6590e-05 lr: 3.3264e-06 eta: 5:41:26 time: 0.9755 data_time: 0.0148 memory: 8153 grad_norm: 0.0139 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 13:53:10 - mmengine - INFO - Saving checkpoint at 99000 iterations
	2023/11/28 14:01:23 - mmengine - INFO - Iter(train) [ 99500/120000] base_lr: 1.5920e-05 lr: 3.2655e-06 eta: 5:33:20 time: 0.9774 data_time: 0.0168 memory: 8153 grad_norm: 0.0138 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 14:09:27 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_025431
	2023/11/28 14:09:27 - mmengine - INFO - Iter(train) [100000/120000] base_lr: 1.5265e-05 lr: 3.2059e-06 eta: 5:25:11 time: 0.9774 data_time: 0.0168 memory: 8153 grad_norm: 0.0138 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 14:09:27 - mmengine - INFO - Saving checkpoint at 100000 iterations
	2023/11/28 14:12:50 - mmengine - INFO - per class results:
	2023/11/28 14:12:50 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.31 \| 89.02 \|
	\| building \| 81.36 \| 92.78 \|
	\| sky \| 93.63 \| 97.83 \|
	\| floor \| 80.99 \| 90.46 \|
	\| tree \| 73.09 \| 86.98 \|
	\| ceiling \| 84.55 \| 94.47 \|
	\| road \| 84.5 \| 90.89 \|
	\| bed \| 88.0 \| 95.73 \|
	\| windowpane \| 62.17 \| 77.55 \|
	\| grass \| 68.21 \| 82.64 \|
	\| cabinet \| 60.89 \| 74.16 \|
	\| sidewalk \| 67.44 \| 81.17 \|
	\| person \| 78.86 \| 91.99 \|
	\| earth \| 39.69 \| 53.15 \|
	\| door \| 51.31 \| 62.3 \|
	\| table \| 60.77 \| 75.45 \|
	\| mountain \| 54.85 \| 69.93 \|
	\| plant \| 49.5 \| 60.35 \|
	\| curtain \| 73.3 \| 85.73 \|
	\| chair \| 57.98 \| 71.6 \|
	\| car \| 81.77 \| 90.2 \|
	\| water \| 49.82 \| 64.69 \|
	\| painting \| 70.98 \| 86.75 \|
	\| sofa \| 64.63 \| 77.72 \|
	\| shelf \| 45.53 \| 64.62 \|
	\| house \| 42.65 \| 56.41 \|
	\| sea \| 48.98 \| 80.17 \|
	\| mirror \| 68.16 \| 79.07 \|
	\| rug \| 64.92 \| 74.43 \|
	\| field \| 29.91 \| 49.4 \|
	\| armchair \| 44.71 \| 65.03 \|
	\| seat \| 61.11 \| 79.81 \|
	\| fence \| 44.56 \| 59.38 \|
	\| desk \| 49.16 \| 67.51 \|
	\| rock \| 35.32 \| 54.63 \|
	\| wardrobe \| 51.36 \| 66.31 \|
	\| lamp \| 61.92 \| 73.6 \|
	\| bathtub \| 79.57 \| 82.99 \|
	\| railing \| 33.35 \| 44.98 \|
	\| cushion \| 60.35 \| 73.1 \|
	\| base \| 23.99 \| 31.32 \|
	\| box \| 24.12 \| 30.18 \|
	\| column \| 47.6 \| 55.31 \|
	\| signboard \| 36.93 \| 49.77 \|
	\| chest of drawers \| 38.67 \| 54.67 \|
	\| counter \| 25.28 \| 36.73 \|
	\| sand \| 46.21 \| 53.84 \|
	\| sink \| 68.34 \| 81.74 \|
	\| skyscraper \| 45.67 \| 51.63 \|
	\| fireplace \| 73.06 \| 89.32 \|
	\| refrigerator \| 71.42 \| 81.05 \|
	\| grandstand \| 42.29 \| 72.37 \|
	\| path \| 29.29 \| 41.21 \|
	\| stairs \| 30.9 \| 41.9 \|
	\| runway \| 73.81 \| 86.85 \|
	\| case \| 43.08 \| 53.89 \|
	\| pool table \| 92.2 \| 95.98 \|
	\| pillow \| 58.32 \| 68.28 \|
	\| screen door \| 64.61 \| 68.39 \|
	\| stairway \| 30.11 \| 35.93 \|
	\| river \| 19.16 \| 28.27 \|
	\| bridge \| 42.9 \| 53.05 \|
	\| bookcase \| 38.05 \| 54.59 \|
	\| blind \| 37.23 \| 40.7 \|
	\| coffee table \| 63.35 \| 79.88 \|
	\| toilet \| 84.93 \| 89.58 \|
	\| flower \| 36.92 \| 55.88 \|
	\| book \| 47.89 \| 66.25 \|
	\| hill \| 6.53 \| 10.34 \|
	\| bench \| 37.96 \| 45.3 \|
	\| countertop \| 52.47 \| 64.81 \|
	\| stove \| 76.93 \| 83.69 \|
	\| palm \| 47.59 \| 66.38 \|
	\| kitchen island \| 36.6 \| 75.87 \|
	\| computer \| 64.41 \| 72.57 \|
	\| swivel chair \| 39.15 \| 50.31 \|
	\| boat \| 46.04 \| 51.4 \|
	\| bar \| 18.62 \| 21.63 \|
	\| arcade machine \| 42.77 \| 45.73 \|
	\| hovel \| 7.48 \| 8.17 \|
	\| bus \| 90.95 \| 94.44 \|
	\| towel \| 62.52 \| 75.99 \|
	\| light \| 50.32 \| 59.18 \|
	\| truck \| 24.51 \| 41.92 \|
	\| tower \| 26.32 \| 38.62 \|
	\| chandelier \| 66.09 \| 78.98 \|
	\| awning \| 31.32 \| 36.64 \|
	\| streetlight \| 31.6 \| 42.11 \|
	\| booth \| 46.25 \| 49.66 \|
	\| television receiver \| 65.31 \| 84.94 \|
	\| airplane \| 56.86 \| 65.01 \|
	\| dirt track \| 8.43 \| 18.49 \|
	\| apparel \| 35.52 \| 49.81 \|
	\| pole \| 24.89 \| 35.28 \|
	\| land \| 0.54 \| 0.7 \|
	\| bannister \| 14.25 \| 19.1 \|
	\| escalator \| 34.37 \| 43.79 \|
	\| ottoman \| 51.67 \| 64.32 \|
	\| bottle \| 22.97 \| 29.03 \|
	\| buffet \| 49.46 \| 55.67 \|
	\| poster \| 33.55 \| 39.8 \|
	\| stage \| 14.43 \| 26.64 \|
	\| van \| 38.43 \| 51.66 \|
	\| ship \| 60.73 \| 86.16 \|
	\| fountain \| 6.64 \| 6.98 \|
	\| conveyer belt \| 68.33 \| 89.44 \|
	\| canopy \| 17.72 \| 19.94 \|
	\| washer \| 70.85 \| 73.12 \|
	\| plaything \| 22.94 \| 31.46 \|
	\| swimming pool \| 66.83 \| 69.6 \|
	\| stool \| 43.71 \| 54.81 \|
	\| barrel \| 23.3 \| 66.09 \|
	\| basket \| 36.02 \| 47.92 \|
	\| waterfall \| 41.29 \| 53.45 \|
	\| tent \| 75.74 \| 97.82 \|
	\| bag \| 9.57 \| 13.09 \|
	\| minibike \| 57.4 \| 67.42 \|
	\| cradle \| 77.49 \| 95.18 \|
	\| oven \| 41.7 \| 57.09 \|
	\| ball \| 40.45 \| 59.01 \|
	\| food \| 48.8 \| 58.81 \|
	\| step \| 7.85 \| 10.61 \|
	\| tank \| 41.71 \| 53.62 \|
	\| trade name \| 26.98 \| 32.35 \|
	\| microwave \| 39.41 \| 42.1 \|
	\| pot \| 50.78 \| 56.98 \|
	\| animal \| 50.25 \| 53.62 \|
	\| bicycle \| 56.99 \| 74.16 \|
	\| lake \| 55.57 \| 62.32 \|
	\| dishwasher \| 66.32 \| 73.09 \|
	\| screen \| 66.21 \| 86.22 \|
	\| blanket \| 12.09 \| 14.49 \|
	\| sculpture \| 61.38 \| 76.4 \|
	\| hood \| 63.6 \| 67.66 \|
	\| sconce \| 47.32 \| 55.8 \|
	\| vase \| 36.66 \| 50.39 \|
	\| traffic light \| 34.41 \| 48.57 \|
	\| tray \| 14.03 \| 19.27 \|
	\| ashcan \| 35.49 \| 50.42 \|
	\| fan \| 58.74 \| 67.94 \|
	\| pier \| 45.81 \| 80.65 \|
	\| crt screen \| 3.94 \| 7.11 \|
	\| plate \| 55.31 \| 70.89 \|
	\| monitor \| 36.26 \| 42.4 \|
	\| bulletin board \| 36.33 \| 47.86 \|
	\| shower \| 7.7 \| 12.32 \|
	\| radiator \| 50.16 \| 55.04 \|
	\| glass \| 15.71 \| 17.19 \|
	\| clock \| 20.2 \| 24.34 \|
	\| flag \| 28.18 \| 31.86 \|
	+---------------------+-------+-------+
	2023/11/28 14:12:50 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.8100 mIoU: 47.3700 mAcc: 58.6300 data_time: 0.0019 time: 0.7696
	2023/11/28 15:39:34 - mmengine - INFO - Iter(train) [102500/120000] base_lr: 1.2211e-05 lr: 2.9282e-06 eta: 4:46:50 time: 0.9747 data_time: 0.0123 memory: 8153 grad_norm: 0.0136 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 15:47:47 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 15:47:47 - mmengine - INFO - Iter(train) [103000/120000] base_lr: 1.1645e-05 lr: 2.8768e-06 eta: 4:38:48 time: 0.9767 data_time: 0.0123 memory: 8153 grad_norm: 0.0135 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 15:47:47 - mmengine - INFO - Saving checkpoint at 103000 iterations
	2023/11/28 15:56:11 - mmengine - INFO - Iter(train) [103500/120000] base_lr: 1.1095e-05 lr: 2.8268e-06 eta: 4:32:43 time: 0.9793 data_time: 0.0124 memory: 8153 grad_norm: 0.0136 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:04:24 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 16:04:24 - mmengine - INFO - Iter(train) [104000/120000] base_lr: 1.0560e-05 lr: 2.7782e-06 eta: 4:24:10 time: 0.9818 data_time: 0.0124 memory: 8153 grad_norm: 0.0136 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:04:24 - mmengine - INFO - Saving checkpoint at 104000 iterations
	2023/11/28 16:12:48 - mmengine - INFO - Iter(train) [104500/120000] base_lr: 1.0041e-05 lr: 2.7310e-06 eta: 4:16:43 time: 0.9864 data_time: 0.0146 memory: 8153 grad_norm: 0.0137 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:21:02 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 16:21:02 - mmengine - INFO - Iter(train) [105000/120000] base_lr: 9.5369e-06 lr: 2.6852e-06 eta: 4:08:13 time: 0.9889 data_time: 0.0146 memory: 8153 grad_norm: 0.0137 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 16:21:02 - mmengine - INFO - Saving checkpoint at 105000 iterations
	2023/11/28 16:24:24 - mmengine - INFO - per class results:
	2023/11/28 16:24:24 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.22 \| 89.24 \|
	\| building \| 81.7 \| 92.31 \|
	\| sky \| 93.6 \| 97.96 \|
	\| floor \| 81.08 \| 90.8 \|
	\| tree \| 73.27 \| 87.95 \|
	\| ceiling \| 84.43 \| 94.55 \|
	\| road \| 85.02 \| 91.72 \|
	\| bed \| 87.68 \| 95.44 \|
	\| windowpane \| 62.45 \| 78.43 \|
	\| grass \| 69.4 \| 82.79 \|
	\| cabinet \| 60.69 \| 73.1 \|
	\| sidewalk \| 67.4 \| 79.01 \|
	\| person \| 78.8 \| 91.62 \|
	\| earth \| 39.21 \| 53.4 \|
	\| door \| 51.63 \| 62.6 \|
	\| table \| 61.63 \| 76.9 \|
	\| mountain \| 54.4 \| 70.29 \|
	\| plant \| 50.34 \| 61.93 \|
	\| curtain \| 74.04 \| 85.26 \|
	\| chair \| 57.6 \| 71.03 \|
	\| car \| 82.15 \| 90.96 \|
	\| water \| 50.5 \| 64.75 \|
	\| painting \| 70.87 \| 86.25 \|
	\| sofa \| 65.32 \| 78.07 \|
	\| shelf \| 45.37 \| 63.34 \|
	\| house \| 44.15 \| 58.77 \|
	\| sea \| 50.6 \| 80.63 \|
	\| mirror \| 68.05 \| 78.01 \|
	\| rug \| 65.34 \| 72.91 \|
	\| field \| 32.71 \| 54.61 \|
	\| armchair \| 44.48 \| 65.1 \|
	\| seat \| 61.78 \| 79.76 \|
	\| fence \| 44.45 \| 59.17 \|
	\| desk \| 52.65 \| 72.58 \|
	\| rock \| 32.11 \| 50.09 \|
	\| wardrobe \| 49.63 \| 65.68 \|
	\| lamp \| 61.88 \| 73.03 \|
	\| bathtub \| 80.88 \| 85.09 \|
	\| railing \| 31.84 \| 40.84 \|
	\| cushion \| 62.21 \| 74.48 \|
	\| base \| 25.0 \| 31.67 \|
	\| box \| 24.05 \| 30.49 \|
	\| column \| 48.06 \| 55.47 \|
	\| signboard \| 37.12 \| 49.29 \|
	\| chest of drawers \| 40.7 \| 55.41 \|
	\| counter \| 23.77 \| 33.9 \|
	\| sand \| 45.55 \| 52.06 \|
	\| sink \| 71.22 \| 81.57 \|
	\| skyscraper \| 48.6 \| 55.47 \|
	\| fireplace \| 71.62 \| 86.82 \|
	\| refrigerator \| 71.85 \| 80.97 \|
	\| grandstand \| 41.58 \| 71.06 \|
	\| path \| 28.58 \| 42.38 \|
	\| stairs \| 30.62 \| 41.04 \|
	\| runway \| 73.8 \| 86.25 \|
	\| case \| 44.02 \| 56.18 \|
	\| pool table \| 91.64 \| 95.52 \|
	\| pillow \| 58.75 \| 69.62 \|
	\| screen door \| 67.0 \| 71.54 \|
	\| stairway \| 29.47 \| 35.72 \|
	\| river \| 18.43 \| 29.45 \|
	\| bridge \| 43.44 \| 53.14 \|
	\| bookcase \| 38.21 \| 57.16 \|
	\| blind \| 39.51 \| 43.58 \|
	\| coffee table \| 62.78 \| 81.06 \|
	\| toilet \| 85.08 \| 89.55 \|
	\| flower \| 38.56 \| 53.38 \|
	\| book \| 47.82 \| 66.27 \|
	\| hill \| 6.22 \| 8.8 \|
	\| bench \| 38.15 \| 44.84 \|
	\| countertop \| 51.52 \| 66.9 \|
	\| stove \| 78.87 \| 84.59 \|
	\| palm \| 49.42 \| 66.94 \|
	\| kitchen island \| 39.57 \| 78.96 \|
	\| computer \| 66.8 \| 75.86 \|
	\| swivel chair \| 38.41 \| 48.03 \|
	\| boat \| 44.38 \| 50.79 \|
	\| bar \| 21.73 \| 24.92 \|
	\| arcade machine \| 39.27 \| 40.49 \|
	\| hovel \| 7.89 \| 9.53 \|
	\| bus \| 90.05 \| 93.46 \|
	\| towel \| 62.63 \| 76.12 \|
	\| light \| 48.44 \| 56.71 \|
	\| truck \| 31.93 \| 41.08 \|
	\| tower \| 26.46 \| 38.01 \|
	\| chandelier \| 65.69 \| 78.97 \|
	\| awning \| 28.06 \| 31.98 \|
	\| streetlight \| 30.73 \| 39.71 \|
	\| booth \| 42.86 \| 47.37 \|
	\| television receiver \| 57.92 \| 85.18 \|
	\| airplane \| 56.73 \| 64.42 \|
	\| dirt track \| 9.53 \| 21.96 \|
	\| apparel \| 32.89 \| 40.38 \|
	\| pole \| 24.7 \| 33.32 \|
	\| land \| 0.41 \| 0.52 \|
	\| bannister \| 13.71 \| 18.23 \|
	\| escalator \| 34.43 \| 44.5 \|
	\| ottoman \| 49.83 \| 62.03 \|
	\| bottle \| 29.76 \| 40.17 \|
	\| buffet \| 49.93 \| 57.03 \|
	\| poster \| 31.96 \| 36.64 \|
	\| stage \| 13.37 \| 27.3 \|
	\| van \| 38.2 \| 51.46 \|
	\| ship \| 58.82 \| 82.47 \|
	\| fountain \| 4.76 \| 4.99 \|
	\| conveyer belt \| 70.11 \| 89.0 \|
	\| canopy \| 17.3 \| 19.18 \|
	\| washer \| 71.83 \| 74.84 \|
	\| plaything \| 24.08 \| 29.79 \|
	\| swimming pool \| 59.86 \| 67.42 \|
	\| stool \| 47.09 \| 57.32 \|
	\| barrel \| 37.25 \| 82.84 \|
	\| basket \| 32.45 \| 42.59 \|
	\| waterfall \| 40.56 \| 52.87 \|
	\| tent \| 83.19 \| 97.67 \|
	\| bag \| 8.2 \| 10.23 \|
	\| minibike \| 56.17 \| 64.43 \|
	\| cradle \| 78.73 \| 95.0 \|
	\| oven \| 45.07 \| 58.2 \|
	\| ball \| 39.17 \| 56.73 \|
	\| food \| 50.37 \| 60.26 \|
	\| step \| 11.79 \| 16.58 \|
	\| tank \| 44.55 \| 53.27 \|
	\| trade name \| 27.25 \| 31.84 \|
	\| microwave \| 38.69 \| 41.41 \|
	\| pot \| 51.16 \| 58.69 \|
	\| animal \| 50.1 \| 53.17 \|
	\| bicycle \| 56.77 \| 74.46 \|
	\| lake \| 53.02 \| 60.38 \|
	\| dishwasher \| 69.15 \| 72.39 \|
	\| screen \| 57.0 \| 86.35 \|
	\| blanket \| 14.2 \| 17.11 \|
	\| sculpture \| 60.72 \| 75.46 \|
	\| hood \| 62.0 \| 65.57 \|
	\| sconce \| 47.42 \| 56.22 \|
	\| vase \| 39.67 \| 56.16 \|
	\| traffic light \| 34.72 \| 44.77 \|
	\| tray \| 14.83 \| 20.3 \|
	\| ashcan \| 36.52 \| 48.93 \|
	\| fan \| 57.75 \| 67.74 \|
	\| pier \| 40.6 \| 78.12 \|
	\| crt screen \| 3.79 \| 7.02 \|
	\| plate \| 54.42 \| 71.27 \|
	\| monitor \| 32.95 \| 39.02 \|
	\| bulletin board \| 35.66 \| 43.07 \|
	\| shower \| 7.6 \| 13.03 \|
	\| radiator \| 52.07 \| 56.22 \|
	\| glass \| 16.53 \| 18.3 \|
	\| clock \| 19.94 \| 24.84 \|
	\| flag \| 27.85 \| 31.87 \|
	+---------------------+-------+-------+
	2023/11/28 16:24:24 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.9200 mIoU: 47.5400 mAcc: 58.6200 data_time: 0.0043 time: 0.7691
	2023/11/28 16:32:38 - mmengine - INFO - Iter(train) [105500/120000] base_lr: 9.0488e-06 lr: 2.6408e-06 eta: 3:59:49 time: 0.9892 data_time: 0.0126 memory: 8153 grad_norm: 0.0136 loss: 0.0047 semantic_segmentation_loss_cls: 0.0047
	2023/11/28 16:40:52 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 16:40:52 - mmengine - INFO - Iter(train) [106000/120000] base_lr: 8.5765e-06 lr: 2.5979e-06 eta: 3:51:25 time: 0.9918 data_time: 0.0125 memory: 8153 grad_norm: 0.0137 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:40:52 - mmengine - INFO - Saving checkpoint at 106000 iterations
	2023/11/28 16:49:16 - mmengine - INFO - Iter(train) [106500/120000] base_lr: 8.1200e-06 lr: 2.5564e-06 eta: 3:43:31 time: 0.9947 data_time: 0.0149 memory: 8153 grad_norm: 0.0136 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:57:30 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 16:57:30 - mmengine - INFO - Iter(train) [107000/120000] base_lr: 7.6794e-06 lr: 2.5163e-06 eta: 3:35:08 time: 0.9952 data_time: 0.0149 memory: 8153 grad_norm: 0.0135 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 16:57:30 - mmengine - INFO - Saving checkpoint at 107000 iterations
	2023/11/28 17:05:53 - mmengine - INFO - Iter(train) [107500/120000] base_lr: 7.2548e-06 lr: 2.4777e-06 eta: 3:27:07 time: 0.9951 data_time: 0.0149 memory: 8153 grad_norm: 0.0134 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:14:07 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 17:14:07 - mmengine - INFO - Iter(train) [108000/120000] base_lr: 6.8462e-06 lr: 2.4406e-06 eta: 3:18:43 time: 0.9951 data_time: 0.0149 memory: 8153 grad_norm: 0.0134 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:14:07 - mmengine - INFO - Saving checkpoint at 108000 iterations
	2023/11/28 17:22:31 - mmengine - INFO - Iter(train) [108500/120000] base_lr: 6.4538e-06 lr: 2.4049e-06 eta: 3:10:38 time: 0.9952 data_time: 0.0149 memory: 8153 grad_norm: 0.0133 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:30:45 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 17:30:45 - mmengine - INFO - Iter(train) [109000/120000] base_lr: 6.0776e-06 lr: 2.3707e-06 eta: 3:02:16 time: 0.9952 data_time: 0.0149 memory: 8153 grad_norm: 0.0133 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:30:45 - mmengine - INFO - Saving checkpoint at 109000 iterations
	2023/11/28 17:39:09 - mmengine - INFO - Iter(train) [109500/120000] base_lr: 5.7176e-06 lr: 2.3380e-06 eta: 2:54:08 time: 0.9974 data_time: 0.0170 memory: 8153 grad_norm: 0.0133 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:47:23 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 17:47:23 - mmengine - INFO - Iter(train) [110000/120000] base_lr: 5.3740e-06 lr: 2.3067e-06 eta: 2:45:46 time: 0.9974 data_time: 0.0170 memory: 8153 grad_norm: 0.0132 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 17:47:23 - mmengine - INFO - Saving checkpoint at 110000 iterations
	2023/11/28 17:50:45 - mmengine - INFO - per class results:
	2023/11/28 17:50:45 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.17 \| 89.29 \|
	\| building \| 82.03 \| 92.21 \|
	\| sky \| 93.56 \| 98.01 \|
	\| floor \| 81.14 \| 90.87 \|
	\| tree \| 72.99 \| 87.34 \|
	\| ceiling \| 84.23 \| 94.3 \|
	\| road \| 85.05 \| 91.14 \|
	\| bed \| 88.28 \| 95.42 \|
	\| windowpane \| 61.96 \| 78.1 \|
	\| grass \| 69.83 \| 83.11 \|
	\| cabinet \| 61.19 \| 74.18 \|
	\| sidewalk \| 67.64 \| 80.98 \|
	\| person \| 78.73 \| 92.02 \|
	\| earth \| 39.97 \| 54.13 \|
	\| door \| 51.3 \| 62.55 \|
	\| table \| 61.34 \| 76.08 \|
	\| mountain \| 54.99 \| 70.66 \|
	\| plant \| 50.61 \| 61.62 \|
	\| curtain \| 73.11 \| 82.57 \|
	\| chair \| 57.37 \| 70.24 \|
	\| car \| 82.05 \| 90.19 \|
	\| water \| 49.73 \| 64.01 \|
	\| painting \| 70.39 \| 86.76 \|
	\| sofa \| 64.75 \| 77.03 \|
	\| shelf \| 45.73 \| 63.86 \|
	\| house \| 46.56 \| 63.84 \|
	\| sea \| 49.96 \| 80.01 \|
	\| mirror \| 67.39 \| 78.59 \|
	\| rug \| 63.73 \| 72.7 \|
	\| field \| 34.68 \| 57.16 \|
	\| armchair \| 44.39 \| 65.83 \|
	\| seat \| 61.45 \| 79.39 \|
	\| fence \| 44.32 \| 58.92 \|
	\| desk \| 50.9 \| 71.56 \|
	\| rock \| 33.77 \| 52.22 \|
	\| wardrobe \| 52.63 \| 67.0 \|
	\| lamp \| 62.2 \| 74.02 \|
	\| bathtub \| 79.75 \| 83.83 \|
	\| railing \| 32.75 \| 43.84 \|
	\| cushion \| 62.12 \| 74.84 \|
	\| base \| 26.62 \| 34.87 \|
	\| box \| 23.5 \| 29.23 \|
	\| column \| 48.11 \| 55.44 \|
	\| signboard \| 36.86 \| 50.16 \|
	\| chest of drawers \| 37.59 \| 48.69 \|
	\| counter \| 24.61 \| 35.72 \|
	\| sand \| 47.79 \| 56.83 \|
	\| sink \| 70.09 \| 81.89 \|
	\| skyscraper \| 49.44 \| 57.11 \|
	\| fireplace \| 71.07 \| 87.25 \|
	\| refrigerator \| 71.79 \| 80.96 \|
	\| grandstand \| 42.72 \| 71.09 \|
	\| path \| 29.6 \| 41.75 \|
	\| stairs \| 30.43 \| 40.71 \|
	\| runway \| 73.9 \| 87.04 \|
	\| case \| 44.04 \| 58.54 \|
	\| pool table \| 91.78 \| 95.97 \|
	\| pillow \| 59.3 \| 70.44 \|
	\| screen door \| 67.5 \| 72.46 \|
	\| stairway \| 29.88 \| 36.19 \|
	\| river \| 16.94 \| 29.11 \|
	\| bridge \| 40.5 \| 50.39 \|
	\| bookcase \| 37.78 \| 55.31 \|
	\| blind \| 36.02 \| 39.36 \|
	\| coffee table \| 62.96 \| 79.81 \|
	\| toilet \| 84.88 \| 89.51 \|
	\| flower \| 39.06 \| 53.83 \|
	\| book \| 48.83 \| 67.27 \|
	\| hill \| 6.34 \| 9.64 \|
	\| bench \| 38.7 \| 44.2 \|
	\| countertop \| 51.58 \| 65.25 \|
	\| stove \| 78.22 \| 85.48 \|
	\| palm \| 48.21 \| 69.11 \|
	\| kitchen island \| 38.87 \| 78.61 \|
	\| computer \| 66.54 \| 74.92 \|
	\| swivel chair \| 39.45 \| 50.59 \|
	\| boat \| 42.28 \| 51.33 \|
	\| bar \| 19.59 \| 22.58 \|
	\| arcade machine \| 38.64 \| 39.73 \|
	\| hovel \| 6.81 \| 8.19 \|
	\| bus \| 90.64 \| 94.53 \|
	\| towel \| 63.79 \| 75.68 \|
	\| light \| 48.64 \| 56.92 \|
	\| truck \| 30.52 \| 39.79 \|
	\| tower \| 26.57 \| 37.16 \|
	\| chandelier \| 66.98 \| 78.4 \|
	\| awning \| 30.41 \| 34.94 \|
	\| streetlight \| 30.05 \| 39.15 \|
	\| booth \| 45.1 \| 49.96 \|
	\| television receiver \| 57.33 \| 84.56 \|
	\| airplane \| 56.04 \| 65.09 \|
	\| dirt track \| 9.4 \| 23.25 \|
	\| apparel \| 33.75 \| 41.91 \|
	\| pole \| 24.38 \| 32.41 \|
	\| land \| 0.45 \| 0.57 \|
	\| bannister \| 14.86 \| 20.11 \|
	\| escalator \| 34.16 \| 44.1 \|
	\| ottoman \| 51.78 \| 63.53 \|
	\| bottle \| 29.69 \| 39.24 \|
	\| buffet \| 48.61 \| 56.39 \|
	\| poster \| 31.68 \| 36.77 \|
	\| stage \| 13.54 \| 26.42 \|
	\| van \| 38.04 \| 52.16 \|
	\| ship \| 60.35 \| 86.7 \|
	\| fountain \| 5.82 \| 6.18 \|
	\| conveyer belt \| 70.76 \| 89.1 \|
	\| canopy \| 17.8 \| 19.94 \|
	\| washer \| 71.45 \| 73.9 \|
	\| plaything \| 23.31 \| 29.95 \|
	\| swimming pool \| 59.73 \| 63.58 \|
	\| stool \| 46.58 \| 57.24 \|
	\| barrel \| 50.94 \| 79.52 \|
	\| basket \| 33.6 \| 44.39 \|
	\| waterfall \| 40.56 \| 53.34 \|
	\| tent \| 83.44 \| 97.74 \|
	\| bag \| 8.29 \| 10.17 \|
	\| minibike \| 60.62 \| 69.73 \|
	\| cradle \| 79.55 \| 95.73 \|
	\| oven \| 42.76 \| 57.91 \|
	\| ball \| 43.71 \| 56.36 \|
	\| food \| 47.62 \| 56.93 \|
	\| step \| 9.18 \| 11.84 \|
	\| tank \| 45.12 \| 55.03 \|
	\| trade name \| 27.16 \| 31.39 \|
	\| microwave \| 38.95 \| 41.64 \|
	\| pot \| 51.34 \| 57.98 \|
	\| animal \| 49.7 \| 53.05 \|
	\| bicycle \| 57.46 \| 74.4 \|
	\| lake \| 55.91 \| 62.2 \|
	\| dishwasher \| 69.68 \| 73.29 \|
	\| screen \| 53.92 \| 85.67 \|
	\| blanket \| 14.93 \| 17.95 \|
	\| sculpture \| 61.8 \| 76.76 \|
	\| hood \| 60.18 \| 64.04 \|
	\| sconce \| 45.86 \| 53.08 \|
	\| vase \| 38.5 \| 52.76 \|
	\| traffic light \| 34.62 \| 46.28 \|
	\| tray \| 14.81 \| 19.48 \|
	\| ashcan \| 36.76 \| 49.63 \|
	\| fan \| 56.78 \| 66.09 \|
	\| pier \| 41.84 \| 83.09 \|
	\| crt screen \| 4.52 \| 6.75 \|
	\| plate \| 54.29 \| 71.54 \|
	\| monitor \| 47.12 \| 56.63 \|
	\| bulletin board \| 33.55 \| 40.5 \|
	\| shower \| 8.1 \| 13.51 \|
	\| radiator \| 48.88 \| 51.73 \|
	\| glass \| 15.6 \| 17.01 \|
	\| clock \| 20.05 \| 24.7 \|
	\| flag \| 28.21 \| 32.03 \|
	+---------------------+-------+-------+
	2023/11/28 17:50:45 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.9400 mIoU: 47.7200 mAcc: 58.7900 data_time: 0.0018 time: 0.7681
	2023/11/28 17:58:59 - mmengine - INFO - Iter(train) [110500/120000] base_lr: 5.0468e-06 lr: 2.2770e-06 eta: 2:37:25 time: 0.9953 data_time: 0.0149 memory: 8153 grad_norm: 0.0132 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:07:13 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 18:07:13 - mmengine - INFO - Iter(train) [111000/120000] base_lr: 4.7360e-06 lr: 2.2487e-06 eta: 2:29:05 time: 0.9952 data_time: 0.0149 memory: 8153 grad_norm: 0.0132 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:07:13 - mmengine - INFO - Saving checkpoint at 111000 iterations
	2023/11/28 18:15:37 - mmengine - INFO - Iter(train) [111500/120000] base_lr: 4.4417e-06 lr: 2.2220e-06 eta: 2:20:54 time: 0.9952 data_time: 0.0148 memory: 8153 grad_norm: 0.0133 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:23:50 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 18:23:50 - mmengine - INFO - Iter(train) [112000/120000] base_lr: 4.1639e-06 lr: 2.1967e-06 eta: 2:12:34 time: 0.9953 data_time: 0.0148 memory: 8153 grad_norm: 0.0133 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:23:50 - mmengine - INFO - Saving checkpoint at 112000 iterations
	2023/11/28 18:32:14 - mmengine - INFO - Iter(train) [112500/120000] base_lr: 3.9028e-06 lr: 2.1730e-06 eta: 2:04:21 time: 0.9951 data_time: 0.0148 memory: 8153 grad_norm: 0.0132 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:40:28 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 18:40:28 - mmengine - INFO - Iter(train) [113000/120000] base_lr: 3.6582e-06 lr: 2.1507e-06 eta: 1:56:01 time: 0.9952 data_time: 0.0148 memory: 8153 grad_norm: 0.0132 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:40:28 - mmengine - INFO - Saving checkpoint at 113000 iterations
	2023/11/28 18:48:51 - mmengine - INFO - Iter(train) [113500/120000] base_lr: 3.4304e-06 lr: 2.1300e-06 eta: 1:47:47 time: 0.9951 data_time: 0.0148 memory: 8153 grad_norm: 0.0131 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 18:57:06 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 18:57:06 - mmengine - INFO - Iter(train) [114000/120000] base_lr: 3.2193e-06 lr: 2.1108e-06 eta: 1:39:28 time: 0.9951 data_time: 0.0148 memory: 8153 grad_norm: 0.0131 loss: 0.0045 semantic_segmentation_loss_cls: 0.0045
	2023/11/28 18:57:06 - mmengine - INFO - Saving checkpoint at 114000 iterations
	2023/11/28 19:05:29 - mmengine - INFO - Iter(train) [114500/120000] base_lr: 3.0249e-06 lr: 2.0932e-06 eta: 1:31:13 time: 0.9972 data_time: 0.0168 memory: 8153 grad_norm: 0.0131 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 19:13:43 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 19:13:43 - mmengine - INFO - Iter(train) [115000/120000] base_lr: 2.8473e-06 lr: 2.0770e-06 eta: 1:22:54 time: 0.9972 data_time: 0.0168 memory: 8153 grad_norm: 0.0130 loss: 0.0045 semantic_segmentation_loss_cls: 0.0045
	2023/11/28 19:13:43 - mmengine - INFO - Saving checkpoint at 115000 iterations
	2023/11/28 19:17:05 - mmengine - INFO - per class results:
	2023/11/28 19:17:05 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.29 \| 89.25 \|
	\| building \| 81.86 \| 92.23 \|
	\| sky \| 93.66 \| 97.9 \|
	\| floor \| 81.13 \| 90.94 \|
	\| tree \| 73.37 \| 87.86 \|
	\| ceiling \| 84.29 \| 94.06 \|
	\| road \| 85.09 \| 91.21 \|
	\| bed \| 88.07 \| 95.45 \|
	\| windowpane \| 61.95 \| 78.02 \|
	\| grass \| 69.19 \| 82.57 \|
	\| cabinet \| 61.26 \| 74.16 \|
	\| sidewalk \| 67.73 \| 80.94 \|
	\| person \| 78.84 \| 91.66 \|
	\| earth \| 40.28 \| 55.37 \|
	\| door \| 52.24 \| 63.8 \|
	\| table \| 61.18 \| 75.82 \|
	\| mountain \| 55.19 \| 70.56 \|
	\| plant \| 50.42 \| 62.13 \|
	\| curtain \| 73.78 \| 84.99 \|
	\| chair \| 57.21 \| 70.36 \|
	\| car \| 81.68 \| 90.25 \|
	\| water \| 49.94 \| 64.14 \|
	\| painting \| 70.44 \| 86.97 \|
	\| sofa \| 65.54 \| 78.53 \|
	\| shelf \| 45.29 \| 63.08 \|
	\| house \| 44.94 \| 61.1 \|
	\| sea \| 49.59 \| 79.72 \|
	\| mirror \| 68.17 \| 77.69 \|
	\| rug \| 64.28 \| 72.24 \|
	\| field \| 33.24 \| 53.06 \|
	\| armchair \| 44.6 \| 65.06 \|
	\| seat \| 62.28 \| 79.3 \|
	\| fence \| 44.4 \| 59.52 \|
	\| desk \| 50.08 \| 69.09 \|
	\| rock \| 34.08 \| 52.22 \|
	\| wardrobe \| 51.11 \| 66.09 \|
	\| lamp \| 62.39 \| 73.33 \|
	\| bathtub \| 80.29 \| 83.98 \|
	\| railing \| 32.93 \| 44.08 \|
	\| cushion \| 61.7 \| 73.42 \|
	\| base \| 25.64 \| 33.1 \|
	\| box \| 23.97 \| 30.21 \|
	\| column \| 48.06 \| 55.26 \|
	\| signboard \| 37.06 \| 50.46 \|
	\| chest of drawers \| 38.11 \| 52.79 \|
	\| counter \| 24.08 \| 34.8 \|
	\| sand \| 45.79 \| 53.75 \|
	\| sink \| 70.43 \| 81.43 \|
	\| skyscraper \| 48.6 \| 55.71 \|
	\| fireplace \| 71.43 \| 87.82 \|
	\| refrigerator \| 71.8 \| 81.04 \|
	\| grandstand \| 42.18 \| 70.57 \|
	\| path \| 29.47 \| 41.18 \|
	\| stairs \| 30.35 \| 41.51 \|
	\| runway \| 74.14 \| 86.88 \|
	\| case \| 44.34 \| 58.68 \|
	\| pool table \| 91.85 \| 95.79 \|
	\| pillow \| 59.45 \| 71.34 \|
	\| screen door \| 67.38 \| 71.69 \|
	\| stairway \| 30.36 \| 36.09 \|
	\| river \| 17.1 \| 29.05 \|
	\| bridge \| 34.98 \| 42.64 \|
	\| bookcase \| 39.02 \| 58.23 \|
	\| blind \| 36.25 \| 39.93 \|
	\| coffee table \| 62.55 \| 80.3 \|
	\| toilet \| 84.72 \| 89.64 \|
	\| flower \| 39.11 \| 54.36 \|
	\| book \| 49.18 \| 67.05 \|
	\| hill \| 6.24 \| 9.43 \|
	\| bench \| 38.57 \| 44.89 \|
	\| countertop \| 52.23 \| 65.75 \|
	\| stove \| 79.11 \| 85.92 \|
	\| palm \| 48.33 \| 68.2 \|
	\| kitchen island \| 37.24 \| 78.0 \|
	\| computer \| 65.62 \| 74.85 \|
	\| swivel chair \| 39.36 \| 50.99 \|
	\| boat \| 44.92 \| 52.0 \|
	\| bar \| 20.49 \| 23.55 \|
	\| arcade machine \| 39.53 \| 40.77 \|
	\| hovel \| 6.82 \| 8.31 \|
	\| bus \| 89.79 \| 94.26 \|
	\| towel \| 61.92 \| 76.24 \|
	\| light \| 48.85 \| 56.68 \|
	\| truck \| 31.06 \| 40.48 \|
	\| tower \| 26.41 \| 36.97 \|
	\| chandelier \| 67.28 \| 79.91 \|
	\| awning \| 31.06 \| 36.29 \|
	\| streetlight \| 30.19 \| 39.9 \|
	\| booth \| 43.8 \| 47.09 \|
	\| television receiver \| 57.23 \| 84.32 \|
	\| airplane \| 56.78 \| 64.59 \|
	\| dirt track \| 11.43 \| 24.97 \|
	\| apparel \| 34.92 \| 45.05 \|
	\| pole \| 22.98 \| 31.51 \|
	\| land \| 0.37 \| 0.48 \|
	\| bannister \| 14.69 \| 19.34 \|
	\| escalator \| 37.04 \| 48.47 \|
	\| ottoman \| 50.7 \| 62.94 \|
	\| bottle \| 28.37 \| 36.12 \|
	\| buffet \| 47.87 \| 54.09 \|
	\| poster \| 31.29 \| 36.64 \|
	\| stage \| 13.35 \| 26.64 \|
	\| van \| 38.97 \| 54.26 \|
	\| ship \| 60.53 \| 84.97 \|
	\| fountain \| 5.12 \| 5.41 \|
	\| conveyer belt \| 73.19 \| 89.2 \|
	\| canopy \| 17.6 \| 19.78 \|
	\| washer \| 70.9 \| 73.37 \|
	\| plaything \| 23.98 \| 30.61 \|
	\| swimming pool \| 59.35 \| 66.68 \|
	\| stool \| 47.06 \| 58.06 \|
	\| barrel \| 34.64 \| 76.95 \|
	\| basket \| 35.1 \| 46.02 \|
	\| waterfall \| 40.07 \| 52.35 \|
	\| tent \| 77.93 \| 97.64 \|
	\| bag \| 8.39 \| 10.5 \|
	\| minibike \| 62.62 \| 72.24 \|
	\| cradle \| 77.38 \| 95.76 \|
	\| oven \| 43.12 \| 58.62 \|
	\| ball \| 43.1 \| 57.27 \|
	\| food \| 48.84 \| 58.62 \|
	\| step \| 11.5 \| 14.9 \|
	\| tank \| 44.26 \| 53.85 \|
	\| trade name \| 28.72 \| 34.28 \|
	\| microwave \| 38.77 \| 41.58 \|
	\| pot \| 51.41 \| 58.24 \|
	\| animal \| 49.66 \| 52.41 \|
	\| bicycle \| 57.38 \| 74.38 \|
	\| lake \| 56.78 \| 62.24 \|
	\| dishwasher \| 69.56 \| 73.93 \|
	\| screen \| 56.57 \| 86.31 \|
	\| blanket \| 13.35 \| 16.32 \|
	\| sculpture \| 60.87 \| 74.95 \|
	\| hood \| 61.46 \| 64.96 \|
	\| sconce \| 46.73 \| 56.11 \|
	\| vase \| 39.27 \| 53.61 \|
	\| traffic light \| 35.54 \| 48.04 \|
	\| tray \| 14.82 \| 19.6 \|
	\| ashcan \| 37.08 \| 49.93 \|
	\| fan \| 56.48 \| 66.57 \|
	\| pier \| 40.63 \| 79.58 \|
	\| crt screen \| 4.34 \| 6.92 \|
	\| plate \| 54.95 \| 71.11 \|
	\| monitor \| 42.4 \| 50.63 \|
	\| bulletin board \| 34.64 \| 42.78 \|
	\| shower \| 8.4 \| 13.65 \|
	\| radiator \| 49.22 \| 53.39 \|
	\| glass \| 16.26 \| 17.87 \|
	\| clock \| 21.06 \| 25.58 \|
	\| flag \| 27.93 \| 32.22 \|
	+---------------------+-------+-------+
	2023/11/28 19:17:05 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.9500 mIoU: 47.6100 mAcc: 58.8200 data_time: 0.0021 time: 0.7683
	2023/11/28 19:25:18 - mmengine - INFO - Iter(train) [115500/120000] base_lr: 2.6865e-06 lr: 2.0624e-06 eta: 1:14:36 time: 0.9949 data_time: 0.0148 memory: 8153 grad_norm: 0.0129 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 19:33:32 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 19:33:32 - mmengine - INFO - Iter(train) [116000/120000] base_lr: 2.5426e-06 lr: 2.0493e-06 eta: 1:06:17 time: 0.9950 data_time: 0.0148 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 19:33:32 - mmengine - INFO - Saving checkpoint at 116000 iterations
	2023/11/28 19:41:56 - mmengine - INFO - Iter(train) [116500/120000] base_lr: 2.4155e-06 lr: 2.0378e-06 eta: 0:58:02 time: 0.9950 data_time: 0.0148 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 19:50:10 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 19:50:10 - mmengine - INFO - Iter(train) [117000/120000] base_lr: 2.3054e-06 lr: 2.0278e-06 eta: 0:49:43 time: 0.9949 data_time: 0.0148 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 19:50:10 - mmengine - INFO - Saving checkpoint at 117000 iterations
	2023/11/28 19:58:34 - mmengine - INFO - Iter(train) [117500/120000] base_lr: 2.2121e-06 lr: 2.0193e-06 eta: 0:41:27 time: 0.9951 data_time: 0.0148 memory: 8153 grad_norm: 0.0131 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:06:48 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 20:06:48 - mmengine - INFO - Iter(train) [118000/120000] base_lr: 2.1358e-06 lr: 2.0123e-06 eta: 0:33:09 time: 0.9949 data_time: 0.0148 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:06:48 - mmengine - INFO - Saving checkpoint at 118000 iterations
	2023/11/28 20:15:11 - mmengine - INFO - Iter(train) [118500/120000] base_lr: 2.0764e-06 lr: 2.0069e-06 eta: 0:24:52 time: 0.9949 data_time: 0.0148 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:23:25 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 20:23:25 - mmengine - INFO - Iter(train) [119000/120000] base_lr: 2.0340e-06 lr: 2.0031e-06 eta: 0:16:34 time: 0.9950 data_time: 0.0148 memory: 8153 grad_norm: 0.0131 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:23:25 - mmengine - INFO - Saving checkpoint at 119000 iterations
	2023/11/28 20:31:48 - mmengine - INFO - Iter(train) [119500/120000] base_lr: 2.0085e-06 lr: 2.0008e-06 eta: 0:08:17 time: 0.9972 data_time: 0.0169 memory: 8153 grad_norm: 0.0131 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:40:02 - mmengine - INFO - Exp name: univision_single_semseg_base_20231128_153007
	2023/11/28 20:40:02 - mmengine - INFO - Iter(train) [120000/120000] base_lr: 2.0000e-06 lr: 2.0000e-06 eta: 0:00:00 time: 0.9972 data_time: 0.0169 memory: 8153 grad_norm: 0.0130 loss: 0.0046 semantic_segmentation_loss_cls: 0.0046
	2023/11/28 20:40:02 - mmengine - INFO - Saving checkpoint at 120000 iterations
	2023/11/28 20:43:25 - mmengine - INFO - per class results:
	2023/11/28 20:43:25 - mmengine - INFO -
	+---------------------+-------+-------+
	\| Class \| IoU \| Acc \|
	+---------------------+-------+-------+
	\| wall \| 77.19 \| 89.46 \|
	\| building \| 81.7 \| 92.61 \|
	\| sky \| 93.67 \| 97.72 \|
	\| floor \| 81.13 \| 90.97 \|
	\| tree \| 73.4 \| 88.13 \|
	\| ceiling \| 84.59 \| 94.05 \|
	\| road \| 85.04 \| 91.11 \|
	\| bed \| 88.17 \| 95.25 \|
	\| windowpane \| 62.19 \| 77.76 \|
	\| grass \| 69.45 \| 83.09 \|
	\| cabinet \| 61.74 \| 74.56 \|
	\| sidewalk \| 67.85 \| 81.26 \|
	\| person \| 78.7 \| 91.74 \|
	\| earth \| 39.83 \| 53.78 \|
	\| door \| 51.98 \| 62.88 \|
	\| table \| 61.64 \| 76.77 \|
	\| mountain \| 55.26 \| 70.45 \|
	\| plant \| 50.71 \| 62.48 \|
	\| curtain \| 73.35 \| 84.54 \|
	\| chair \| 57.25 \| 70.16 \|
	\| car \| 81.58 \| 90.34 \|
	\| water \| 50.88 \| 65.83 \|
	\| painting \| 71.38 \| 86.32 \|
	\| sofa \| 65.24 \| 77.81 \|
	\| shelf \| 45.13 \| 62.4 \|
	\| house \| 44.09 \| 59.13 \|
	\| sea \| 48.54 \| 76.12 \|
	\| mirror \| 66.99 \| 77.79 \|
	\| rug \| 63.7 \| 72.07 \|
	\| field \| 32.82 \| 53.0 \|
	\| armchair \| 44.6 \| 65.91 \|
	\| seat \| 62.08 \| 79.29 \|
	\| fence \| 43.98 \| 58.21 \|
	\| desk \| 50.42 \| 68.51 \|
	\| rock \| 35.47 \| 55.4 \|
	\| wardrobe \| 52.91 \| 66.45 \|
	\| lamp \| 62.08 \| 73.67 \|
	\| bathtub \| 80.37 \| 84.43 \|
	\| railing \| 33.03 \| 43.89 \|
	\| cushion \| 61.88 \| 74.37 \|
	\| base \| 24.53 \| 30.72 \|
	\| box \| 23.01 \| 28.17 \|
	\| column \| 48.9 \| 55.45 \|
	\| signboard \| 36.43 \| 48.75 \|
	\| chest of drawers \| 36.66 \| 50.2 \|
	\| counter \| 23.52 \| 34.16 \|
	\| sand \| 46.28 \| 55.6 \|
	\| sink \| 70.81 \| 81.41 \|
	\| skyscraper \| 48.47 \| 55.48 \|
	\| fireplace \| 71.59 \| 87.6 \|
	\| refrigerator \| 71.68 \| 80.95 \|
	\| grandstand \| 44.52 \| 70.33 \|
	\| path \| 29.84 \| 41.7 \|
	\| stairs \| 30.51 \| 40.7 \|
	\| runway \| 73.99 \| 86.83 \|
	\| case \| 43.72 \| 59.43 \|
	\| pool table \| 91.53 \| 95.32 \|
	\| pillow \| 58.03 \| 69.32 \|
	\| screen door \| 69.11 \| 71.86 \|
	\| stairway \| 30.21 \| 35.72 \|
	\| river \| 15.92 \| 28.79 \|
	\| bridge \| 34.75 \| 42.47 \|
	\| bookcase \| 38.3 \| 56.03 \|
	\| blind \| 38.03 \| 41.72 \|
	\| coffee table \| 63.33 \| 79.91 \|
	\| toilet \| 84.87 \| 89.58 \|
	\| flower \| 39.9 \| 54.11 \|
	\| book \| 49.26 \| 66.58 \|
	\| hill \| 6.1 \| 8.95 \|
	\| bench \| 38.44 \| 44.11 \|
	\| countertop \| 51.81 \| 65.77 \|
	\| stove \| 78.21 \| 84.3 \|
	\| palm \| 47.96 \| 67.17 \|
	\| kitchen island \| 38.78 \| 79.57 \|
	\| computer \| 66.29 \| 74.79 \|
	\| swivel chair \| 39.63 \| 51.07 \|
	\| boat \| 44.76 \| 51.19 \|
	\| bar \| 21.02 \| 24.25 \|
	\| arcade machine \| 40.82 \| 42.28 \|
	\| hovel \| 6.59 \| 8.31 \|
	\| bus \| 89.33 \| 94.25 \|
	\| towel \| 62.77 \| 75.9 \|
	\| light \| 49.15 \| 57.05 \|
	\| truck \| 30.61 \| 40.08 \|
	\| tower \| 25.87 \| 37.28 \|
	\| chandelier \| 66.96 \| 80.72 \|
	\| awning \| 30.01 \| 34.51 \|
	\| streetlight \| 30.77 \| 40.58 \|
	\| booth \| 42.67 \| 47.01 \|
	\| television receiver \| 56.13 \| 84.18 \|
	\| airplane \| 56.38 \| 64.88 \|
	\| dirt track \| 10.81 \| 25.43 \|
	\| apparel \| 34.87 \| 43.43 \|
	\| pole \| 23.92 \| 32.69 \|
	\| land \| 0.28 \| 0.35 \|
	\| bannister \| 14.67 \| 19.6 \|
	\| escalator \| 37.05 \| 49.0 \|
	\| ottoman \| 50.63 \| 61.98 \|
	\| bottle \| 28.43 \| 36.28 \|
	\| buffet \| 49.55 \| 57.92 \|
	\| poster \| 31.24 \| 36.55 \|
	\| stage \| 13.43 \| 26.44 \|
	\| van \| 38.58 \| 53.46 \|
	\| ship \| 60.91 \| 85.4 \|
	\| fountain \| 6.63 \| 7.12 \|
	\| conveyer belt \| 72.28 \| 88.75 \|
	\| canopy \| 15.38 \| 17.32 \|
	\| washer \| 71.01 \| 73.34 \|
	\| plaything \| 24.64 \| 30.97 \|
	\| swimming pool \| 62.47 \| 68.53 \|
	\| stool \| 46.91 \| 57.27 \|
	\| barrel \| 37.95 \| 80.15 \|
	\| basket \| 34.59 \| 46.1 \|
	\| waterfall \| 40.88 \| 53.48 \|
	\| tent \| 82.13 \| 97.48 \|
	\| bag \| 7.71 \| 9.39 \|
	\| minibike \| 59.7 \| 68.79 \|
	\| cradle \| 77.5 \| 95.67 \|
	\| oven \| 43.07 \| 58.45 \|
	\| ball \| 41.56 \| 55.4 \|
	\| food \| 49.26 \| 58.59 \|
	\| step \| 11.26 \| 14.35 \|
	\| tank \| 44.83 \| 54.15 \|
	\| trade name \| 28.3 \| 33.63 \|
	\| microwave \| 38.75 \| 41.52 \|
	\| pot \| 51.26 \| 58.63 \|
	\| animal \| 49.47 \| 52.45 \|
	\| bicycle \| 57.15 \| 73.98 \|
	\| lake \| 56.64 \| 62.02 \|
	\| dishwasher \| 69.53 \| 73.46 \|
	\| screen \| 57.22 \| 85.61 \|
	\| blanket \| 14.1 \| 16.61 \|
	\| sculpture \| 61.21 \| 76.24 \|
	\| hood \| 60.39 \| 63.91 \|
	\| sconce \| 46.01 \| 54.19 \|
	\| vase \| 39.02 \| 53.97 \|
	\| traffic light \| 35.25 \| 46.66 \|
	\| tray \| 14.54 \| 18.55 \|
	\| ashcan \| 36.37 \| 48.68 \|
	\| fan \| 56.74 \| 66.98 \|
	\| pier \| 46.22 \| 80.73 \|
	\| crt screen \| 4.36 \| 7.32 \|
	\| plate \| 54.68 \| 71.26 \|
	\| monitor \| 37.21 \| 46.23 \|
	\| bulletin board \| 32.69 \| 41.45 \|
	\| shower \| 6.71 \| 11.95 \|
	\| radiator \| 50.87 \| 54.02 \|
	\| glass \| 16.08 \| 17.7 \|
	\| clock \| 20.62 \| 25.16 \|
	\| flag \| 29.35 \| 33.62 \|
	+---------------------+-------+-------+
	2023/11/28 20:43:25 - mmengine - INFO - Iter(val) [250/250] aAcc: 82.9700 mIoU: 47.6400 mAcc: 58.6500 data_time: 0.0018 time: 0.7678