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3.7.11 (default, Jul 27 2021, 14:32:16)
[GCC 7.5.0]
python exp/s3dis/pointtransformer_repro/train.py --config=config/s3dis/s3dis_pointtransformer_repro.yaml save_path exp/s3dis/pointtransformer_repro
[2021-12-13 16:44:42,539 INFO train.py line 122 16826] arch: pointtransformer_seg_repro
base_lr: 0.5
batch_size: 1
batch_size_test: 1
batch_size_val: 1
classes: 13
data_name: s3dis
data_root: /home/tidop/Documents/dataset/s3dis/trainval_fullarea
dist_backend: nccl
dist_url: tcp://localhost:8888
distributed: False
drop_rate: 0.5
epochs: 100
eval_freq: 1
evaluate: True
fea_dim: 6
ignore_label: 255
loop: 30
manual_seed: 7777
model_path: None
momentum: 0.9
multiplier: 0.1
multiprocessing_distributed: False
names_path: data/s3dis/s3dis_names.txt
ngpus_per_node: 1
print_freq: 1
rank: 0
resume: None
save_folder: None
save_freq: 1
save_path: exp/s3dis/pointtransformer_repro
split: val
start_epoch: 0
step_epoch: 30
sync_bn: False
test_area: 5
test_gpu: [0]
test_list: dataset/s3dis/list/val5.txt
test_list_full: dataset/s3dis/list/val5_full.txt
test_workers: 4
train_gpu: [0]
use_xyz: True
voxel_max: 80000
voxel_size: 0.04
weight: None
weight_decay: 0.0001
workers: 16
world_size: 1
[2021-12-13 16:44:42,539 INFO train.py line 123 16826] => creating model ...
[2021-12-13 16:44:42,539 INFO train.py line 124 16826] Classes: 13
[2021-12-13 16:44:43,903 INFO train.py line 171 16826] train_data samples: '6120'
Totally 204 samples in train set.
Totally 68 samples in val set.
Totally 204 samples in train set.
Totally 68 samples in val set.
[2021-12-13 16:45:34,645 INFO train.py line 351 16826] Epoch: [1/100][16/6120] Data 48.676 (30.415) Batch 50.740 (50.740) Remain 8625:31:06 Loss 2.5989 Accuracy 0.0800.
[2021-12-13 16:46:16,469 INFO train.py line 351 16826] Epoch: [1/100][32/6120] Data 38.717 (24.768) Batch 41.824 (46.282) Remain 7867:29:26 Loss 2.4089 Accuracy 0.2416.
[2021-12-13 16:46:46,773 INFO train.py line 351 16826] Epoch: [1/100][48/6120] Data 28.476 (20.882) Batch 30.304 (40.956) Remain 6961:56:19 Loss 1.9630 Accuracy 0.4504.
[2021-12-13 16:47:25,175 INFO train.py line 351 16826] Epoch: [1/100][64/6120] Data 33.304 (19.131) Batch 38.403 (40.317) Remain 6853:15:24 Loss 2.1831 Accuracy 0.3061.
[2021-12-13 16:48:00,389 INFO train.py line 351 16826] Epoch: [1/100][80/6120] Data 32.626 (18.713) Batch 35.214 (39.297) Remain 6679:35:21 Loss 2.1511 Accuracy 0.3715.
[2021-12-13 16:48:37,170 INFO train.py line 351 16826] Epoch: [1/100][96/6120] Data 36.018 (18.406) Batch 36.781 (38.877) Remain 6608:08:14 Loss 1.8193 Accuracy 0.5068.
[2021-12-13 16:49:12,811 INFO train.py line 351 16826] Epoch: [1/100][112/6120] Data 33.330 (17.872) Batch 35.641 (38.415) Remain 6529:22:21 Loss 2.7529 Accuracy 0.3322.
[2021-12-13 16:50:07,596 INFO train.py line 351 16826] Epoch: [1/100][128/6120] Data 49.772 (18.808) Batch 54.785 (40.461) Remain 6876:58:58 Loss 1.6035 Accuracy 0.4931.
[2021-12-13 16:50:46,487 INFO train.py line 351 16826] Epoch: [1/100][144/6120] Data 35.876 (18.998) Batch 38.892 (40.287) Remain 6847:09:57 Loss 1.8046 Accuracy 0.4813.
[2021-12-13 16:51:26,765 INFO train.py line 351 16826] Epoch: [1/100][160/6120] Data 39.260 (18.701) Batch 40.278 (40.286) Remain 6846:50:00 Loss 1.6752 Accuracy 0.4765.
[2021-12-13 16:52:11,370 INFO train.py line 351 16826] Epoch: [1/100][176/6120] Data 43.742 (18.817) Batch 44.604 (40.679) Remain 6913:22:24 Loss 1.4070 Accuracy 0.5854.
[2021-12-13 16:52:56,727 INFO train.py line 351 16826] Epoch: [1/100][192/6120] Data 42.496 (18.749) Batch 45.358 (41.069) Remain 6979:27:32 Loss 1.4934 Accuracy 0.6135.
[2021-12-13 16:53:41,095 INFO train.py line 351 16826] Epoch: [1/100][208/6120] Data 40.802 (18.890) Batch 44.368 (41.322) Remain 7022:24:33 Loss 1.6988 Accuracy 0.5119.
[2021-12-13 16:54:24,066 INFO train.py line 351 16826] Epoch: [1/100][224/6120] Data 41.582 (19.026) Batch 42.970 (41.440) Remain 7042:13:38 Loss 1.3428 Accuracy 0.6029.
[2021-12-13 16:54:54,232 INFO train.py line 351 16826] Epoch: [1/100][240/6120] Data 25.950 (18.367) Batch 30.167 (40.688) Remain 6914:19:37 Loss 1.0382 Accuracy 0.7158.
[2021-12-13 16:55:37,873 INFO train.py line 351 16826] Epoch: [1/100][256/6120] Data 41.717 (18.818) Batch 43.640 (40.873) Remain 6945:29:48 Loss 1.1284 Accuracy 0.6215.
[2021-12-13 16:56:11,087 INFO train.py line 351 16826] Epoch: [1/100][272/6120] Data 28.175 (18.651) Batch 33.215 (40.422) Remain 6868:46:02 Loss 1.6853 Accuracy 0.4207.
[2021-12-13 16:56:47,828 INFO train.py line 351 16826] Epoch: [1/100][288/6120] Data 33.689 (18.717) Batch 36.741 (40.218) Remain 6833:49:53 Loss 1.6394 Accuracy 0.5484.
[2021-12-13 16:57:29,049 INFO train.py line 351 16826] Epoch: [1/100][304/6120] Data 35.888 (18.559) Batch 41.221 (40.271) Remain 6842:37:30 Loss 1.5381 Accuracy 0.4504.
[2021-12-13 16:57:58,269 INFO train.py line 351 16826] Epoch: [1/100][320/6120] Data 27.945 (18.187) Batch 29.220 (39.718) Remain 6748:33:43 Loss 1.5151 Accuracy 0.3371.
[2021-12-13 16:58:42,324 INFO train.py line 351 16826] Epoch: [1/100][336/6120] Data 42.654 (18.227) Batch 44.055 (39.925) Remain 6783:28:18 Loss 1.6381 Accuracy 0.2925.
[2021-12-13 16:59:31,383 INFO train.py line 351 16826] Epoch: [1/100][352/6120] Data 47.917 (18.428) Batch 49.059 (40.340) Remain 6853:50:13 Loss 1.3267 Accuracy 0.4577.
[2021-12-13 17:00:15,607 INFO train.py line 351 16826] Epoch: [1/100][368/6120] Data 39.239 (18.537) Batch 44.225 (40.509) Remain 6882:21:11 Loss 1.3284 Accuracy 0.6303.
[2021-12-13 17:00:57,025 INFO train.py line 351 16826] Epoch: [1/100][384/6120] Data 38.792 (18.660) Batch 41.418 (40.547) Remain 6888:36:27 Loss 1.4201 Accuracy 0.5770.
[2021-12-13 17:01:40,516 INFO train.py line 351 16826] Epoch: [1/100][400/6120] Data 39.950 (18.683) Batch 43.491 (40.664) Remain 6908:25:56 Loss 1.5162 Accuracy 0.5883.
[2021-12-13 17:02:17,311 INFO train.py line 351 16826] Epoch: [1/100][416/6120] Data 31.794 (18.540) Batch 36.795 (40.516) Remain 6882:58:14 Loss 2.2468 Accuracy 0.4514.
[2021-12-13 17:03:12,607 INFO train.py line 351 16826] Epoch: [1/100][432/6120] Data 51.055 (18.814) Batch 55.296 (41.063) Remain 6975:47:14 Loss 1.8432 Accuracy 0.4355.
[2021-12-13 17:03:50,238 INFO train.py line 351 16826] Epoch: [1/100][448/6120] Data 32.561 (18.662) Batch 37.631 (40.940) Remain 6954:46:58 Loss 1.0591 Accuracy 0.6887.
[2021-12-13 17:04:23,094 INFO train.py line 351 16826] Epoch: [1/100][464/6120] Data 30.464 (18.562) Batch 32.856 (40.662) Remain 6907:14:47 Loss 1.5210 Accuracy 0.5762.
[2021-12-13 17:05:10,086 INFO train.py line 351 16826] Epoch: [1/100][480/6120] Data 41.816 (18.595) Batch 46.992 (40.873) Remain 6942:54:29 Loss 1.8644 Accuracy 0.4728.
[2021-12-13 17:05:53,187 INFO train.py line 351 16826] Epoch: [1/100][496/6120] Data 42.661 (18.680) Batch 43.101 (40.945) Remain 6954:56:04 Loss 1.7939 Accuracy 0.5581.
[2021-12-13 17:06:34,425 INFO train.py line 351 16826] Epoch: [1/100][512/6120] Data 36.491 (18.691) Batch 41.238 (40.954) Remain 6956:18:37 Loss 1.2720 Accuracy 0.6060.
[2021-12-13 17:07:09,485 INFO train.py line 351 16826] Epoch: [1/100][528/6120] Data 32.931 (18.514) Batch 35.060 (40.775) Remain 6925:47:44 Loss 1.4299 Accuracy 0.5642.
[2021-12-13 17:07:51,578 INFO train.py line 351 16826] Epoch: [1/100][544/6120] Data 40.483 (18.585) Batch 42.093 (40.814) Remain 6932:11:49 Loss 1.4432 Accuracy 0.5252.
[2021-12-13 17:08:39,804 INFO train.py line 351 16826] Epoch: [1/100][560/6120] Data 45.977 (18.717) Batch 48.226 (41.026) Remain 6967:59:03 Loss 1.3416 Accuracy 0.5338.
[2021-12-13 17:09:29,343 INFO train.py line 351 16826] Epoch: [1/100][576/6120] Data 44.469 (18.783) Batch 49.539 (41.262) Remain 7007:57:55 Loss 1.6437 Accuracy 0.4672.
[2021-12-13 17:10:10,861 INFO train.py line 351 16826] Epoch: [1/100][592/6120] Data 41.102 (18.699) Batch 41.518 (41.269) Remain 7008:57:24 Loss 1.1894 Accuracy 0.7168.
[2021-12-13 17:11:00,323 INFO train.py line 351 16826] Epoch: [1/100][608/6120] Data 44.142 (18.850) Batch 49.462 (41.485) Remain 7045:23:25 Loss 1.4997 Accuracy 0.7049.
[2021-12-13 17:11:44,467 INFO train.py line 351 16826] Epoch: [1/100][624/6120] Data 41.192 (18.872) Batch 44.144 (41.553) Remain 7056:47:10 Loss 1.5948 Accuracy 0.5181.
[2021-12-13 17:12:20,418 INFO train.py line 351 16826] Epoch: [1/100][640/6120] Data 31.255 (18.752) Batch 35.951 (41.413) Remain 7032:49:01 Loss 0.8114 Accuracy 0.7666.
[2021-12-13 17:12:57,048 INFO train.py line 351 16826] Epoch: [1/100][656/6120] Data 33.571 (18.591) Batch 36.630 (41.296) Remain 7012:49:30 Loss 1.6515 Accuracy 0.4985.
[2021-12-13 17:13:42,045 INFO train.py line 351 16826] Epoch: [1/100][672/6120] Data 41.376 (18.614) Batch 44.997 (41.384) Remain 7027:36:14 Loss 1.5004 Accuracy 0.6100.
[2021-12-13 17:14:15,042 INFO train.py line 351 16826] Epoch: [1/100][688/6120] Data 28.031 (18.525) Batch 32.996 (41.189) Remain 6994:17:43 Loss 1.7442 Accuracy 0.4832.
[2021-12-13 17:14:50,414 INFO train.py line 351 16826] Epoch: [1/100][704/6120] Data 30.318 (18.426) Batch 35.373 (41.057) Remain 6971:39:57 Loss 0.8022 Accuracy 0.7368.
[2021-12-13 17:15:26,156 INFO train.py line 351 16826] Epoch: [1/100][720/6120] Data 33.348 (18.387) Batch 35.741 (40.939) Remain 6951:25:32 Loss 1.4109 Accuracy 0.5784.
[2021-12-13 17:16:04,308 INFO train.py line 351 16826] Epoch: [1/100][736/6120] Data 37.570 (18.458) Batch 38.152 (40.878) Remain 6940:57:27 Loss 1.0811 Accuracy 0.7544.
[2021-12-13 17:16:36,192 INFO train.py line 351 16826] Epoch: [1/100][752/6120] Data 28.931 (18.321) Batch 31.884 (40.687) Remain 6908:16:57 Loss 1.5065 Accuracy 0.4734.
[2021-12-13 17:17:14,813 INFO train.py line 351 16826] Epoch: [1/100][768/6120] Data 38.185 (18.338) Batch 38.621 (40.644) Remain 6900:47:44 Loss 0.9814 Accuracy 0.7171.
[2021-12-13 17:18:07,220 INFO train.py line 351 16826] Epoch: [1/100][784/6120] Data 49.131 (18.456) Batch 52.406 (40.884) Remain 6941:22:15 Loss 1.7090 Accuracy 0.4938.
[2021-12-13 17:18:49,443 INFO train.py line 351 16826] Epoch: [1/100][800/6120] Data 37.854 (18.502) Batch 42.223 (40.911) Remain 6945:44:10 Loss 0.7249 Accuracy 0.8087.
[2021-12-13 17:19:33,268 INFO train.py line 351 16826] Epoch: [1/100][816/6120] Data 42.770 (18.571) Batch 43.826 (40.968) Remain 6955:15:29 Loss 1.1725 Accuracy 0.5520.
[2021-12-13 17:20:14,209 INFO train.py line 351 16826] Epoch: [1/100][832/6120] Data 39.263 (18.603) Batch 40.940 (40.967) Remain 6954:59:08 Loss 1.6840 Accuracy 0.4710.
[2021-12-13 17:20:49,944 INFO train.py line 351 16826] Epoch: [1/100][848/6120] Data 35.224 (18.597) Batch 35.735 (40.869) Remain 6938:02:37 Loss 0.6162 Accuracy 0.8014.
[2021-12-13 17:21:32,827 INFO train.py line 351 16826] Epoch: [1/100][864/6120] Data 40.243 (18.617) Batch 42.884 (40.906) Remain 6944:11:46 Loss 1.5571 Accuracy 0.5317.
[2021-12-13 17:22:15,572 INFO train.py line 351 16826] Epoch: [1/100][880/6120] Data 39.885 (18.636) Batch 42.744 (40.939) Remain 6949:41:20 Loss 1.7178 Accuracy 0.4816.
[2021-12-13 17:22:58,311 INFO train.py line 351 16826] Epoch: [1/100][896/6120] Data 41.916 (18.638) Batch 42.739 (40.972) Remain 6954:57:42 Loss 0.9431 Accuracy 0.6748.
[2021-12-13 17:23:38,344 INFO train.py line 351 16826] Epoch: [1/100][912/6120] Data 37.112 (18.608) Batch 40.034 (40.955) Remain 6951:59:13 Loss 1.3206 Accuracy 0.5979.
[2021-12-13 17:24:15,374 INFO train.py line 351 16826] Epoch: [1/100][928/6120] Data 34.745 (18.588) Batch 37.030 (40.887) Remain 6940:19:06 Loss 1.4153 Accuracy 0.5303.
[2021-12-13 17:25:01,498 INFO train.py line 351 16826] Epoch: [1/100][944/6120] Data 42.114 (18.664) Batch 46.123 (40.976) Remain 6955:11:59 Loss 0.9424 Accuracy 0.7252.
[2021-12-13 17:25:49,745 INFO train.py line 351 16826] Epoch: [1/100][960/6120] Data 47.624 (18.767) Batch 48.247 (41.097) Remain 6975:35:11 Loss 1.2528 Accuracy 0.5062.
[2021-12-13 17:26:25,489 INFO train.py line 351 16826] Epoch: [1/100][976/6120] Data 30.734 (18.728) Batch 35.744 (41.010) Remain 6960:30:35 Loss 0.9570 Accuracy 0.7363.
[2021-12-13 17:27:07,397 INFO train.py line 351 16826] Epoch: [1/100][992/6120] Data 39.535 (18.750) Batch 41.908 (41.024) Remain 6962:47:12 Loss 1.3103 Accuracy 0.5677.
[2021-12-13 17:27:44,768 INFO train.py line 351 16826] Epoch: [1/100][1008/6120] Data 34.436 (18.694) Batch 37.370 (40.966) Remain 6952:45:40 Loss 1.3192 Accuracy 0.5411.
[2021-12-13 17:28:19,127 INFO train.py line 351 16826] Epoch: [1/100][1024/6120] Data 29.361 (18.610) Batch 34.359 (40.863) Remain 6935:03:35 Loss 1.3815 Accuracy 0.5670.
[2021-12-13 17:28:52,153 INFO train.py line 351 16826] Epoch: [1/100][1040/6120] Data 32.413 (18.542) Batch 33.026 (40.742) Remain 6914:25:01 Loss 1.5523 Accuracy 0.4900.
[2021-12-13 17:29:27,202 INFO train.py line 351 16826] Epoch: [1/100][1056/6120] Data 30.050 (18.489) Batch 35.049 (40.656) Remain 6899:35:46 Loss 1.0266 Accuracy 0.6965.
[2021-12-13 17:30:07,291 INFO train.py line 351 16826] Epoch: [1/100][1072/6120] Data 39.427 (18.492) Batch 40.089 (40.648) Remain 6897:58:43 Loss 2.3269 Accuracy 0.3525.
[2021-12-13 17:30:40,783 INFO train.py line 351 16826] Epoch: [1/100][1088/6120] Data 32.074 (18.494) Batch 33.492 (40.542) Remain 6879:56:30 Loss 1.3454 Accuracy 0.5743.
[2021-12-13 17:31:21,681 INFO train.py line 351 16826] Epoch: [1/100][1104/6120] Data 35.924 (18.481) Batch 40.898 (40.547) Remain 6880:38:08 Loss 1.1768 Accuracy 0.7182.
[2021-12-13 17:32:05,381 INFO train.py line 351 16826] Epoch: [1/100][1120/6120] Data 41.257 (18.540) Batch 43.700 (40.593) Remain 6888:05:55 Loss 1.3250 Accuracy 0.5852.
[2021-12-13 17:32:49,231 INFO train.py line 351 16826] Epoch: [1/100][1136/6120] Data 42.624 (18.563) Batch 43.850 (40.638) Remain 6895:42:11 Loss 1.0686 Accuracy 0.6447.
[2021-12-13 17:33:13,892 INFO train.py line 351 16826] Epoch: [1/100][1152/6120] Data 19.692 (18.455) Batch 24.661 (40.416) Remain 6857:52:07 Loss 1.1687 Accuracy 0.5833.
[2021-12-13 17:33:54,722 INFO train.py line 351 16826] Epoch: [1/100][1168/6120] Data 38.229 (18.444) Batch 40.830 (40.422) Remain 6858:39:04 Loss 1.3957 Accuracy 0.5354.
[2021-12-13 17:34:25,699 INFO train.py line 351 16826] Epoch: [1/100][1184/6120] Data 28.262 (18.388) Batch 30.976 (40.295) Remain 6836:48:50 Loss 1.4277 Accuracy 0.5085.
[2021-12-13 17:34:53,448 INFO train.py line 351 16826] Epoch: [1/100][1200/6120] Data 27.541 (18.283) Batch 27.749 (40.127) Remain 6808:15:12 Loss 1.5291 Accuracy 0.5523.
[2021-12-13 17:35:29,050 INFO train.py line 351 16826] Epoch: [1/100][1216/6120] Data 32.836 (18.278) Batch 35.602 (40.068) Remain 6797:58:24 Loss 1.4219 Accuracy 0.5454.
[2021-12-13 17:36:07,319 INFO train.py line 351 16826] Epoch: [1/100][1232/6120] Data 37.735 (18.294) Batch 38.270 (40.044) Remain 6793:50:00 Loss 1.3601 Accuracy 0.6475.
[2021-12-13 17:36:51,141 INFO train.py line 351 16826] Epoch: [1/100][1248/6120] Data 41.049 (18.344) Batch 43.822 (40.093) Remain 6801:52:20 Loss 1.1475 Accuracy 0.6608.
[2021-12-13 17:37:34,991 INFO train.py line 351 16826] Epoch: [1/100][1264/6120] Data 42.567 (18.402) Batch 43.850 (40.140) Remain 6809:45:42 Loss 1.3489 Accuracy 0.5910.
[2021-12-13 17:38:09,704 INFO train.py line 351 16826] Epoch: [1/100][1280/6120] Data 34.408 (18.392) Batch 34.713 (40.072) Remain 6798:04:30 Loss 0.8780 Accuracy 0.8011.
[2021-12-13 17:38:52,981 INFO train.py line 351 16826] Epoch: [1/100][1296/6120] Data 41.138 (18.447) Batch 43.277 (40.112) Remain 6804:36:31 Loss 1.3303 Accuracy 0.5544.
[2021-12-13 17:39:39,862 INFO train.py line 351 16826] Epoch: [1/100][1312/6120] Data 46.129 (18.505) Batch 46.881 (40.195) Remain 6818:25:59 Loss 0.9844 Accuracy 0.7317.
[2021-12-13 17:40:16,552 INFO train.py line 351 16826] Epoch: [1/100][1328/6120] Data 32.291 (18.473) Batch 36.690 (40.152) Remain 6811:05:27 Loss 1.7845 Accuracy 0.4444.
[2021-12-13 17:40:50,258 INFO train.py line 351 16826] Epoch: [1/100][1344/6120] Data 30.756 (18.436) Batch 33.706 (40.076) Remain 6797:53:41 Loss 1.4026 Accuracy 0.6182.
[2021-12-13 17:41:30,489 INFO train.py line 351 16826] Epoch: [1/100][1360/6120] Data 37.660 (18.430) Batch 40.231 (40.077) Remain 6798:01:39 Loss 0.8110 Accuracy 0.7523.
[2021-12-13 17:42:12,901 INFO train.py line 351 16826] Epoch: [1/100][1376/6120] Data 39.703 (18.474) Batch 42.412 (40.105) Remain 6802:27:12 Loss 1.3426 Accuracy 0.5716.
[2021-12-13 17:42:46,039 INFO train.py line 351 16826] Epoch: [1/100][1392/6120] Data 31.139 (18.448) Batch 33.138 (40.025) Remain 6788:41:37 Loss 1.3251 Accuracy 0.6178.
[2021-12-13 17:43:22,776 INFO train.py line 351 16826] Epoch: [1/100][1408/6120] Data 35.819 (18.461) Batch 36.736 (39.987) Remain 6782:10:42 Loss 0.9220 Accuracy 0.7542.
[2021-12-13 17:44:01,851 INFO train.py line 351 16826] Epoch: [1/100][1424/6120] Data 38.552 (18.480) Batch 39.075 (39.977) Remain 6780:15:44 Loss 0.6449 Accuracy 0.7966.
[2021-12-13 17:44:49,127 INFO train.py line 351 16826] Epoch: [1/100][1440/6120] Data 43.929 (18.515) Batch 47.276 (40.058) Remain 6793:50:21 Loss 2.6571 Accuracy 0.2943.
[2021-12-13 17:45:23,075 INFO train.py line 351 16826] Epoch: [1/100][1456/6120] Data 33.648 (18.476) Batch 33.948 (39.991) Remain 6782:16:27 Loss 0.7281 Accuracy 0.6718.
[2021-12-13 17:45:59,771 INFO train.py line 351 16826] Epoch: [1/100][1472/6120] Data 35.912 (18.498) Batch 36.697 (39.955) Remain 6776:01:27 Loss 1.8678 Accuracy 0.3551.
[2021-12-13 17:46:32,543 INFO train.py line 351 16826] Epoch: [1/100][1488/6120] Data 31.116 (18.515) Batch 32.771 (39.878) Remain 6762:44:49 Loss 1.2563 Accuracy 0.6606.
[2021-12-13 17:47:20,343 INFO train.py line 351 16826] Epoch: [1/100][1504/6120] Data 46.802 (18.566) Batch 47.801 (39.962) Remain 6776:51:46 Loss 0.7719 Accuracy 0.8110.
[2021-12-13 17:48:09,233 INFO train.py line 351 16826] Epoch: [1/100][1520/6120] Data 48.312 (18.658) Batch 48.890 (40.056) Remain 6792:37:19 Loss 1.1390 Accuracy 0.6696.
[2021-12-13 17:48:49,556 INFO train.py line 351 16826] Epoch: [1/100][1536/6120] Data 37.752 (18.671) Batch 40.322 (40.059) Remain 6792:54:51 Loss 0.9772 Accuracy 0.6460.
[2021-12-13 17:49:24,811 INFO train.py line 351 16826] Epoch: [1/100][1552/6120] Data 31.257 (18.627) Batch 35.255 (40.009) Remain 6784:20:21 Loss 1.2731 Accuracy 0.6384.
[2021-12-13 17:50:03,493 INFO train.py line 351 16826] Epoch: [1/100][1568/6120] Data 36.500 (18.641) Batch 38.682 (39.996) Remain 6781:51:55 Loss 1.3303 Accuracy 0.6400.
[2021-12-13 17:50:42,647 INFO train.py line 351 16826] Epoch: [1/100][1584/6120] Data 37.929 (18.659) Batch 39.154 (39.987) Remain 6780:14:42 Loss 0.8926 Accuracy 0.7036.
[2021-12-13 17:51:22,129 INFO train.py line 351 16826] Epoch: [1/100][1600/6120] Data 38.691 (18.663) Batch 39.482 (39.982) Remain 6779:12:38 Loss 0.6068 Accuracy 0.6964.
[2021-12-13 17:51:55,121 INFO train.py line 351 16826] Epoch: [1/100][1616/6120] Data 32.468 (18.639) Batch 32.992 (39.913) Remain 6767:17:54 Loss 1.0705 Accuracy 0.6430.
[2021-12-13 17:52:34,740 INFO train.py line 351 16826] Epoch: [1/100][1632/6120] Data 39.225 (18.645) Batch 39.618 (39.910) Remain 6766:37:52 Loss 0.3726 Accuracy 0.8986.
[2021-12-13 17:53:04,941 INFO train.py line 351 16826] Epoch: [1/100][1648/6120] Data 30.077 (18.609) Batch 30.201 (39.816) Remain 6750:28:21 Loss 0.7888 Accuracy 0.7888.
[2021-12-13 17:53:31,532 INFO train.py line 351 16826] Epoch: [1/100][1664/6120] Data 25.307 (18.526) Batch 26.591 (39.689) Remain 6728:44:15 Loss 0.9832 Accuracy 0.6700.
[2021-12-13 17:54:04,337 INFO train.py line 351 16826] Epoch: [1/100][1680/6120] Data 31.560 (18.497) Batch 32.805 (39.623) Remain 6717:26:45 Loss 0.9933 Accuracy 0.6683.
[2021-12-13 17:54:39,445 INFO train.py line 351 16826] Epoch: [1/100][1696/6120] Data 32.250 (18.443) Batch 35.109 (39.581) Remain 6710:02:57 Loss 1.1629 Accuracy 0.6486.
[2021-12-13 17:55:13,107 INFO train.py line 351 16826] Epoch: [1/100][1712/6120] Data 32.532 (18.416) Batch 33.662 (39.525) Remain 6700:29:45 Loss 0.5442 Accuracy 0.8289.
[2021-12-13 17:55:55,325 INFO train.py line 351 16826] Epoch: [1/100][1728/6120] Data 37.224 (18.416) Batch 42.218 (39.550) Remain 6704:32:51 Loss 1.3674 Accuracy 0.5617.
[2021-12-13 17:56:42,351 INFO train.py line 351 16826] Epoch: [1/100][1744/6120] Data 42.067 (18.464) Batch 47.026 (39.619) Remain 6715:59:53 Loss 0.6695 Accuracy 0.7552.
[2021-12-13 17:57:23,481 INFO train.py line 351 16826] Epoch: [1/100][1760/6120] Data 36.063 (18.475) Batch 41.129 (39.633) Remain 6718:08:59 Loss 1.5727 Accuracy 0.4816.
[2021-12-13 17:57:52,034 INFO train.py line 351 16826] Epoch: [1/100][1776/6120] Data 23.583 (18.414) Batch 28.554 (39.533) Remain 6701:03:19 Loss 1.3436 Accuracy 0.5668.
[2021-12-13 17:58:24,075 INFO train.py line 351 16826] Epoch: [1/100][1792/6120] Data 31.469 (18.382) Batch 32.040 (39.466) Remain 6689:32:26 Loss 1.9993 Accuracy 0.3849.
[2021-12-13 17:59:15,272 INFO train.py line 351 16826] Epoch: [1/100][1808/6120] Data 49.527 (18.424) Batch 51.197 (39.570) Remain 6706:57:44 Loss 1.5009 Accuracy 0.5517.
[2021-12-13 17:59:49,911 INFO train.py line 351 16826] Epoch: [1/100][1824/6120] Data 34.382 (18.384) Batch 34.639 (39.526) Remain 6699:27:18 Loss 2.2595 Accuracy 0.4183.
[2021-12-13 18:00:30,610 INFO train.py line 351 16826] Epoch: [1/100][1840/6120] Data 38.241 (18.388) Batch 40.700 (39.537) Remain 6701:00:32 Loss 0.8930 Accuracy 0.6706.
[2021-12-13 18:01:03,696 INFO train.py line 351 16826] Epoch: [1/100][1856/6120] Data 29.722 (18.357) Batch 33.086 (39.481) Remain 6691:24:28 Loss 1.4929 Accuracy 0.5190.
[2021-12-13 18:01:46,278 INFO train.py line 351 16826] Epoch: [1/100][1872/6120] Data 41.934 (18.399) Batch 42.582 (39.507) Remain 6695:43:29 Loss 1.2494 Accuracy 0.7034.
[2021-12-13 18:02:27,855 INFO train.py line 351 16826] Epoch: [1/100][1888/6120] Data 41.224 (18.418) Batch 41.576 (39.525) Remain 6698:31:13 Loss 1.0120 Accuracy 0.7435.
[2021-12-13 18:03:14,207 INFO train.py line 351 16826] Epoch: [1/100][1904/6120] Data 44.281 (18.453) Batch 46.353 (39.582) Remain 6708:04:05 Loss 1.7046 Accuracy 0.4841.
[2021-12-13 18:03:52,008 INFO train.py line 351 16826] Epoch: [1/100][1920/6120] Data 35.618 (18.468) Batch 37.801 (39.568) Remain 6705:22:37 Loss 1.7214 Accuracy 0.5371.
[2021-12-13 18:04:33,382 INFO train.py line 351 16826] Epoch: [1/100][1936/6120] Data 40.116 (18.501) Batch 41.373 (39.582) Remain 6707:43:48 Loss 1.3225 Accuracy 0.5266.
[2021-12-13 18:05:05,872 INFO train.py line 351 16826] Epoch: [1/100][1952/6120] Data 31.954 (18.481) Batch 32.490 (39.524) Remain 6697:42:10 Loss 0.4422 Accuracy 0.9215.
[2021-12-13 18:05:56,369 INFO train.py line 351 16826] Epoch: [1/100][1968/6120] Data 45.506 (18.532) Batch 50.497 (39.614) Remain 6712:38:39 Loss 1.3921 Accuracy 0.6190.
[2021-12-13 18:06:24,499 INFO train.py line 351 16826] Epoch: [1/100][1984/6120] Data 24.650 (18.498) Batch 28.130 (39.521) Remain 6696:46:31 Loss 1.0022 Accuracy 0.6700.
[2021-12-13 18:07:10,526 INFO train.py line 351 16826] Epoch: [1/100][2000/6120] Data 41.037 (18.522) Batch 46.027 (39.573) Remain 6705:25:07 Loss 2.0355 Accuracy 0.4282.
[2021-12-13 18:07:56,962 INFO train.py line 351 16826] Epoch: [1/100][2016/6120] Data 44.653 (18.564) Batch 46.437 (39.627) Remain 6714:28:23 Loss 1.6378 Accuracy 0.5697.
[2021-12-13 18:08:35,185 INFO train.py line 351 16826] Epoch: [1/100][2032/6120] Data 37.566 (18.561) Batch 38.223 (39.616) Remain 6712:25:22 Loss 1.6181 Accuracy 0.4821.
[2021-12-13 18:09:17,774 INFO train.py line 351 16826] Epoch: [1/100][2048/6120] Data 37.615 (18.569) Batch 42.588 (39.640) Remain 6716:10:51 Loss 1.5373 Accuracy 0.5214.
[2021-12-13 18:09:42,962 INFO train.py line 351 16826] Epoch: [1/100][2064/6120] Data 24.554 (18.512) Batch 25.189 (39.528) Remain 6697:01:29 Loss 1.0718 Accuracy 0.7485.
[2021-12-13 18:10:33,352 INFO train.py line 351 16826] Epoch: [1/100][2080/6120] Data 49.009 (18.562) Batch 50.390 (39.611) Remain 6711:00:20 Loss 1.6125 Accuracy 0.4572.
[2021-12-13 18:11:05,313 INFO train.py line 351 16826] Epoch: [1/100][2096/6120] Data 30.321 (18.525) Batch 31.961 (39.553) Remain 6700:56:08 Loss 1.4013 Accuracy 0.4386.
[2021-12-13 18:11:31,270 INFO train.py line 351 16826] Epoch: [1/100][2112/6120] Data 23.916 (18.470) Batch 25.958 (39.450) Remain 6683:18:40 Loss 1.5298 Accuracy 0.5015.
[2021-12-13 18:12:10,978 INFO train.py line 351 16826] Epoch: [1/100][2128/6120] Data 36.820 (18.464) Batch 39.707 (39.452) Remain 6683:27:50 Loss 1.3371 Accuracy 0.5599.
[2021-12-13 18:12:45,153 INFO train.py line 351 16826] Epoch: [1/100][2144/6120] Data 33.651 (18.460) Batch 34.175 (39.412) Remain 6676:37:06 Loss 0.9417 Accuracy 0.7926.
[2021-12-13 18:13:28,082 INFO train.py line 351 16826] Epoch: [1/100][2160/6120] Data 42.345 (18.483) Batch 42.928 (39.438) Remain 6680:51:19 Loss 1.2027 Accuracy 0.5256.
[2021-12-13 18:14:03,522 INFO train.py line 351 16826] Epoch: [1/100][2176/6120] Data 33.071 (18.453) Batch 35.441 (39.409) Remain 6675:42:02 Loss 1.3758 Accuracy 0.5233.
[2021-12-13 18:14:44,582 INFO train.py line 351 16826] Epoch: [1/100][2192/6120] Data 40.447 (18.455) Batch 41.060 (39.421) Remain 6677:33:59 Loss 1.0156 Accuracy 0.7342.
[2021-12-13 18:15:23,240 INFO train.py line 351 16826] Epoch: [1/100][2208/6120] Data 36.128 (18.453) Batch 38.658 (39.415) Remain 6676:27:17 Loss 1.3288 Accuracy 0.5456.
[2021-12-13 18:16:05,833 INFO train.py line 351 16826] Epoch: [1/100][2224/6120] Data 37.579 (18.458) Batch 42.594 (39.438) Remain 6680:09:08 Loss 1.8930 Accuracy 0.4681.
[2021-12-13 18:16:39,118 INFO train.py line 351 16826] Epoch: [1/100][2240/6120] Data 32.926 (18.451) Batch 33.284 (39.394) Remain 6672:31:53 Loss 1.2435 Accuracy 0.5726.
[2021-12-13 18:17:09,064 INFO train.py line 351 16826] Epoch: [1/100][2256/6120] Data 28.978 (18.413) Batch 29.946 (39.327) Remain 6661:00:25 Loss 0.8040 Accuracy 0.6902.
[2021-12-13 18:17:45,794 INFO train.py line 351 16826] Epoch: [1/100][2272/6120] Data 34.653 (18.429) Batch 36.730 (39.309) Remain 6657:44:03 Loss 1.3264 Accuracy 0.5751.
[2021-12-13 18:18:11,882 INFO train.py line 351 16826] Epoch: [1/100][2288/6120] Data 24.145 (18.375) Batch 26.089 (39.217) Remain 6641:54:05 Loss 1.2339 Accuracy 0.5670.
[2021-12-13 18:18:51,907 INFO train.py line 351 16826] Epoch: [1/100][2304/6120] Data 37.656 (18.382) Batch 40.025 (39.222) Remain 6642:40:40 Loss 1.3329 Accuracy 0.5614.
[2021-12-13 18:19:32,924 INFO train.py line 351 16826] Epoch: [1/100][2320/6120] Data 36.024 (18.382) Batch 41.017 (39.235) Remain 6644:35:57 Loss 0.9873 Accuracy 0.6447.
[2021-12-13 18:20:21,050 INFO train.py line 351 16826] Epoch: [1/100][2336/6120] Data 43.079 (18.410) Batch 48.126 (39.296) Remain 6654:44:17 Loss 1.1059 Accuracy 0.6257.
[2021-12-13 18:20:46,618 INFO train.py line 351 16826] Epoch: [1/100][2352/6120] Data 25.202 (18.362) Batch 25.568 (39.202) Remain 6638:44:56 Loss 0.9966 Accuracy 0.6163.
[2021-12-13 18:21:14,531 INFO train.py line 351 16826] Epoch: [1/100][2368/6120] Data 27.429 (18.323) Batch 27.913 (39.126) Remain 6625:39:28 Loss 1.3820 Accuracy 0.6467.
[2021-12-13 18:21:55,770 INFO train.py line 351 16826] Epoch: [1/100][2384/6120] Data 39.538 (18.336) Batch 41.239 (39.140) Remain 6627:53:10 Loss 0.6601 Accuracy 0.7929.
[2021-12-13 18:22:25,719 INFO train.py line 351 16826] Epoch: [1/100][2400/6120] Data 26.216 (18.311) Batch 29.949 (39.079) Remain 6617:20:10 Loss 1.2766 Accuracy 0.6274.
[2021-12-13 18:23:15,546 INFO train.py line 351 16826] Epoch: [1/100][2416/6120] Data 45.984 (18.342) Batch 49.827 (39.150) Remain 6629:12:57 Loss 2.7334 Accuracy 0.3108.
[2021-12-13 18:23:51,015 INFO train.py line 351 16826] Epoch: [1/100][2432/6120] Data 32.657 (18.313) Batch 35.469 (39.126) Remain 6624:56:28 Loss 1.2770 Accuracy 0.5814.
[2021-12-13 18:24:20,972 INFO train.py line 351 16826] Epoch: [1/100][2448/6120] Data 28.849 (18.298) Batch 29.957 (39.066) Remain 6614:37:15 Loss 1.1516 Accuracy 0.6433.
[2021-12-13 18:25:04,056 INFO train.py line 351 16826] Epoch: [1/100][2464/6120] Data 39.324 (18.311) Batch 43.084 (39.092) Remain 6618:51:54 Loss 1.4689 Accuracy 0.4859.
[2021-12-13 18:25:48,096 INFO train.py line 351 16826] Epoch: [1/100][2480/6120] Data 40.160 (18.337) Batch 44.039 (39.124) Remain 6624:05:44 Loss 1.0797 Accuracy 0.5877.
[2021-12-13 18:26:23,659 INFO train.py line 351 16826] Epoch: [1/100][2496/6120] Data 33.797 (18.328) Batch 35.563 (39.101) Remain 6620:03:27 Loss 1.4637 Accuracy 0.4854.
[2021-12-13 18:27:03,493 INFO train.py line 351 16826] Epoch: [1/100][2512/6120] Data 37.418 (18.313) Batch 39.834 (39.106) Remain 6620:40:26 Loss 1.2121 Accuracy 0.6079.
[2021-12-13 18:27:37,431 INFO train.py line 351 16826] Epoch: [1/100][2528/6120] Data 30.951 (18.304) Batch 33.938 (39.073) Remain 6614:57:47 Loss 1.2787 Accuracy 0.6110.
[2021-12-13 18:28:00,072 INFO train.py line 351 16826] Epoch: [1/100][2544/6120] Data 19.722 (18.250) Batch 22.641 (38.970) Remain 6597:17:37 Loss 1.1141 Accuracy 0.6173.
[2021-12-13 18:28:36,529 INFO train.py line 351 16826] Epoch: [1/100][2560/6120] Data 35.878 (18.248) Batch 36.458 (38.954) Remain 6594:27:44 Loss 1.1224 Accuracy 0.6679.
[2021-12-13 18:29:14,800 INFO train.py line 351 16826] Epoch: [1/100][2576/6120] Data 34.973 (18.222) Batch 38.271 (38.950) Remain 6593:34:16 Loss 1.0919 Accuracy 0.6586.
[2021-12-13 18:29:45,570 INFO train.py line 351 16826] Epoch: [1/100][2592/6120] Data 29.039 (18.191) Batch 30.769 (38.899) Remain 6584:51:00 Loss 0.8201 Accuracy 0.6982.
[2021-12-13 18:30:32,792 INFO train.py line 351 16826] Epoch: [1/100][2608/6120] Data 44.419 (18.237) Batch 47.223 (38.950) Remain 6593:19:17 Loss 1.0765 Accuracy 0.6507.
[2021-12-13 18:31:09,276 INFO train.py line 351 16826] Epoch: [1/100][2624/6120] Data 34.199 (18.237) Batch 36.483 (38.935) Remain 6590:36:07 Loss 1.1116 Accuracy 0.6502.
[2021-12-13 18:31:55,540 INFO train.py line 351 16826] Epoch: [1/100][2640/6120] Data 45.993 (18.260) Batch 46.264 (38.980) Remain 6597:56:52 Loss 0.4232 Accuracy 0.9085.
[2021-12-13 18:32:39,994 INFO train.py line 351 16826] Epoch: [1/100][2656/6120] Data 43.876 (18.294) Batch 44.454 (39.013) Remain 6603:21:24 Loss 0.6914 Accuracy 0.7882.
[2021-12-13 18:33:03,797 INFO train.py line 351 16826] Epoch: [1/100][2672/6120] Data 22.677 (18.252) Batch 23.803 (38.922) Remain 6587:46:03 Loss 1.2941 Accuracy 0.6466.
[2021-12-13 18:33:48,423 INFO train.py line 351 16826] Epoch: [1/100][2688/6120] Data 43.742 (18.295) Batch 44.627 (38.955) Remain 6593:20:32 Loss 0.5801 Accuracy 0.8045.
[2021-12-13 18:34:32,430 INFO train.py line 351 16826] Epoch: [1/100][2704/6120] Data 41.010 (18.307) Batch 44.007 (38.985) Remain 6598:13:39 Loss 1.3013 Accuracy 0.6239.
[2021-12-13 18:35:20,717 INFO train.py line 351 16826] Epoch: [1/100][2720/6120] Data 46.304 (18.339) Batch 48.287 (39.040) Remain 6607:18:54 Loss 1.1885 Accuracy 0.6203.
[2021-12-13 18:36:00,015 INFO train.py line 351 16826] Epoch: [1/100][2736/6120] Data 34.279 (18.335) Batch 39.297 (39.042) Remain 6607:23:46 Loss 1.0174 Accuracy 0.7161.
[2021-12-13 18:36:32,414 INFO train.py line 351 16826] Epoch: [1/100][2752/6120] Data 31.325 (18.336) Batch 32.399 (39.003) Remain 6600:41:13 Loss 0.5718 Accuracy 0.8426.
[2021-12-13 18:37:20,893 INFO train.py line 351 16826] Epoch: [1/100][2768/6120] Data 47.283 (18.377) Batch 48.479 (39.058) Remain 6609:46:59 Loss 1.3774 Accuracy 0.4856.
[2021-12-13 18:38:09,614 INFO train.py line 351 16826] Epoch: [1/100][2784/6120] Data 43.985 (18.390) Batch 48.721 (39.113) Remain 6619:00:27 Loss 1.0604 Accuracy 0.6912.
[2021-12-13 18:38:45,655 INFO train.py line 351 16826] Epoch: [1/100][2800/6120] Data 34.222 (18.358) Batch 36.041 (39.096) Remain 6615:51:46 Loss 1.1707 Accuracy 0.6262.
[2021-12-13 18:39:18,392 INFO train.py line 351 16826] Epoch: [1/100][2816/6120] Data 31.824 (18.353) Batch 32.737 (39.060) Remain 6609:34:32 Loss 1.0287 Accuracy 0.6389.
[2021-12-13 18:39:58,403 INFO train.py line 351 16826] Epoch: [1/100][2832/6120] Data 38.781 (18.375) Batch 40.011 (39.065) Remain 6610:18:42 Loss 1.2201 Accuracy 0.6132.
[2021-12-13 18:40:40,132 INFO train.py line 351 16826] Epoch: [1/100][2848/6120] Data 38.846 (18.383) Batch 41.729 (39.080) Remain 6612:40:15 Loss 1.3760 Accuracy 0.5478.
[2021-12-13 18:41:20,890 INFO train.py line 351 16826] Epoch: [1/100][2864/6120] Data 39.080 (18.387) Batch 40.758 (39.089) Remain 6614:05:00 Loss 0.7654 Accuracy 0.7677.
[2021-12-13 18:41:55,185 INFO train.py line 351 16826] Epoch: [1/100][2880/6120] Data 29.244 (18.360) Batch 34.295 (39.063) Remain 6609:24:09 Loss 1.3541 Accuracy 0.6455.
[2021-12-13 18:42:35,446 INFO train.py line 351 16826] Epoch: [1/100][2896/6120] Data 38.571 (18.349) Batch 40.261 (39.069) Remain 6610:20:56 Loss 1.3913 Accuracy 0.5671.
[2021-12-13 18:43:13,232 INFO train.py line 351 16826] Epoch: [1/100][2912/6120] Data 35.795 (18.332) Batch 37.787 (39.062) Remain 6608:58:59 Loss 1.0080 Accuracy 0.6457.
[2021-12-13 18:43:52,332 INFO train.py line 351 16826] Epoch: [1/100][2928/6120] Data 37.349 (18.336) Batch 39.100 (39.062) Remain 6608:50:39 Loss 0.5475 Accuracy 0.8524.
[2021-12-13 18:44:23,602 INFO train.py line 351 16826] Epoch: [1/100][2944/6120] Data 29.067 (18.318) Batch 31.270 (39.020) Remain 6601:30:18 Loss 1.2094 Accuracy 0.5522.
[2021-12-13 18:44:55,169 INFO train.py line 351 16826] Epoch: [1/100][2960/6120] Data 30.284 (18.297) Batch 31.568 (38.980) Remain 6594:30:59 Loss 1.2023 Accuracy 0.6332.
[2021-12-13 18:45:34,120 INFO train.py line 351 16826] Epoch: [1/100][2976/6120] Data 34.718 (18.296) Batch 38.951 (38.980) Remain 6594:19:02 Loss 2.0292 Accuracy 0.6203.
[2021-12-13 18:46:13,979 INFO train.py line 351 16826] Epoch: [1/100][2992/6120] Data 37.383 (18.305) Batch 39.859 (38.984) Remain 6594:56:22 Loss 1.2039 Accuracy 0.5773.
[2021-12-13 18:46:55,058 INFO train.py line 351 16826] Epoch: [1/100][3008/6120] Data 36.364 (18.313) Batch 41.079 (38.995) Remain 6596:39:03 Loss 1.1469 Accuracy 0.6121.
[2021-12-13 18:47:34,936 INFO train.py line 351 16826] Epoch: [1/100][3024/6120] Data 38.424 (18.304) Batch 39.878 (39.000) Remain 6597:16:02 Loss 1.2403 Accuracy 0.5999.
[2021-12-13 18:48:20,320 INFO train.py line 351 16826] Epoch: [1/100][3040/6120] Data 44.855 (18.308) Batch 45.385 (39.034) Remain 6602:46:40 Loss 0.9941 Accuracy 0.6551.
[2021-12-13 18:49:04,411 INFO train.py line 351 16826] Epoch: [1/100][3056/6120] Data 39.039 (18.300) Batch 44.091 (39.060) Remain 6607:04:58 Loss 1.3603 Accuracy 0.5517.
[2021-12-13 18:49:38,523 INFO train.py line 351 16826] Epoch: [1/100][3072/6120] Data 33.457 (18.302) Batch 34.112 (39.034) Remain 6602:33:00 Loss 1.3040 Accuracy 0.6094.
[2021-12-13 18:50:18,907 INFO train.py line 351 16826] Epoch: [1/100][3088/6120] Data 35.370 (18.292) Batch 40.384 (39.041) Remain 6603:33:33 Loss 1.3250 Accuracy 0.5098.
[2021-12-13 18:50:58,581 INFO train.py line 351 16826] Epoch: [1/100][3104/6120] Data 34.691 (18.303) Batch 39.674 (39.045) Remain 6603:56:14 Loss 1.4448 Accuracy 0.5491.
[2021-12-13 18:51:41,783 INFO train.py line 351 16826] Epoch: [1/100][3120/6120] Data 38.445 (18.305) Batch 43.201 (39.066) Remain 6607:22:08 Loss 1.1706 Accuracy 0.6531.
[2021-12-13 18:52:16,888 INFO train.py line 351 16826] Epoch: [1/100][3136/6120] Data 34.355 (18.292) Batch 35.105 (39.046) Remain 6603:46:40 Loss 1.2603 Accuracy 0.5700.
[2021-12-13 18:53:03,655 INFO train.py line 351 16826] Epoch: [1/100][3152/6120] Data 45.520 (18.314) Batch 46.767 (39.085) Remain 6610:13:59 Loss 1.0654 Accuracy 0.6411.
[2021-12-13 18:53:44,959 INFO train.py line 351 16826] Epoch: [1/100][3168/6120] Data 39.379 (18.326) Batch 41.304 (39.096) Remain 6611:57:17 Loss 1.4541 Accuracy 0.5042.
[2021-12-13 18:54:28,448 INFO train.py line 351 16826] Epoch: [1/100][3184/6120] Data 41.580 (18.338) Batch 43.488 (39.118) Remain 6615:30:49 Loss 1.4013 Accuracy 0.5759.
[2021-12-13 18:55:05,314 INFO train.py line 351 16826] Epoch: [1/100][3200/6120] Data 35.929 (18.340) Batch 36.866 (39.107) Remain 6613:26:08 Loss 0.8786 Accuracy 0.7290.
[2021-12-13 18:55:43,786 INFO train.py line 351 16826] Epoch: [1/100][3216/6120] Data 37.891 (18.349) Batch 38.472 (39.104) Remain 6612:43:39 Loss 0.8556 Accuracy 0.6734.
[2021-12-13 18:56:24,618 INFO train.py line 351 16826] Epoch: [1/100][3232/6120] Data 38.132 (18.353) Batch 40.832 (39.112) Remain 6614:00:01 Loss 1.1789 Accuracy 0.6501.
[2021-12-13 18:57:03,152 INFO train.py line 351 16826] Epoch: [1/100][3248/6120] Data 33.547 (18.332) Batch 38.534 (39.110) Remain 6613:20:41 Loss 0.5138 Accuracy 0.8366.
[2021-12-13 18:57:46,292 INFO train.py line 351 16826] Epoch: [1/100][3264/6120] Data 40.708 (18.350) Batch 43.140 (39.129) Remain 6616:30:41 Loss 1.4644 Accuracy 0.7367.
[2021-12-13 18:58:31,351 INFO train.py line 351 16826] Epoch: [1/100][3280/6120] Data 43.706 (18.366) Batch 45.059 (39.158) Remain 6621:13:43 Loss 0.5266 Accuracy 0.8197.
[2021-12-13 18:59:08,649 INFO train.py line 351 16826] Epoch: [1/100][3296/6120] Data 36.974 (18.360) Batch 37.298 (39.149) Remain 6619:31:39 Loss 0.7742 Accuracy 0.6922.
[2021-12-13 18:59:50,958 INFO train.py line 351 16826] Epoch: [1/100][3312/6120] Data 37.271 (18.356) Batch 42.309 (39.165) Remain 6621:56:03 Loss 1.6407 Accuracy 0.5835.
[2021-12-13 19:00:32,434 INFO train.py line 351 16826] Epoch: [1/100][3328/6120] Data 40.075 (18.355) Batch 41.476 (39.176) Remain 6623:38:21 Loss 1.9059 Accuracy 0.5124.
[2021-12-13 19:01:06,963 INFO train.py line 351 16826] Epoch: [1/100][3344/6120] Data 32.564 (18.343) Batch 34.530 (39.153) Remain 6619:42:24 Loss 1.2701 Accuracy 0.6478.
[2021-12-13 19:01:43,795 INFO train.py line 351 16826] Epoch: [1/100][3360/6120] Data 34.196 (18.345) Batch 36.832 (39.142) Remain 6617:39:48 Loss 1.1777 Accuracy 0.6637.
[2021-12-13 19:02:07,887 INFO train.py line 351 16826] Epoch: [1/100][3376/6120] Data 23.811 (18.312) Batch 24.092 (39.071) Remain 6605:25:49 Loss 0.7778 Accuracy 0.7117.
[2021-12-13 19:02:47,036 INFO train.py line 351 16826] Epoch: [1/100][3392/6120] Data 37.806 (18.314) Batch 39.149 (39.071) Remain 6605:19:09 Loss 1.1273 Accuracy 0.6328.
[2021-12-13 19:03:28,633 INFO train.py line 351 16826] Epoch: [1/100][3408/6120] Data 40.718 (18.325) Batch 41.597 (39.083) Remain 6607:08:59 Loss 1.6945 Accuracy 0.4043.
[2021-12-13 19:04:12,414 INFO train.py line 351 16826] Epoch: [1/100][3424/6120] Data 41.706 (18.346) Batch 43.781 (39.105) Remain 6610:41:13 Loss 1.3707 Accuracy 0.5568.
[2021-12-13 19:04:50,656 INFO train.py line 351 16826] Epoch: [1/100][3440/6120] Data 33.265 (18.347) Batch 38.242 (39.101) Remain 6609:50:05 Loss 1.0789 Accuracy 0.6413.
[2021-12-13 19:05:38,903 INFO train.py line 351 16826] Epoch: [1/100][3456/6120] Data 45.947 (18.377) Batch 48.247 (39.144) Remain 6616:49:08 Loss 1.4958 Accuracy 0.4597.
[2021-12-13 19:06:27,503 INFO train.py line 351 16826] Epoch: [1/100][3472/6120] Data 47.566 (18.421) Batch 48.600 (39.187) Remain 6624:00:39 Loss 1.4562 Accuracy 0.4897.
[2021-12-13 19:07:09,360 INFO train.py line 351 16826] Epoch: [1/100][3488/6120] Data 36.832 (18.419) Batch 41.857 (39.199) Remain 6625:54:24 Loss 1.0417 Accuracy 0.6667.
[2021-12-13 19:07:36,917 INFO train.py line 351 16826] Epoch: [1/100][3504/6120] Data 27.371 (18.407) Batch 27.557 (39.146) Remain 6616:44:49 Loss 1.7361 Accuracy 0.5508.
[2021-12-13 19:08:21,420 INFO train.py line 351 16826] Epoch: [1/100][3520/6120] Data 41.160 (18.429) Batch 44.502 (39.171) Remain 6620:41:17 Loss 1.4548 Accuracy 0.5246.
[2021-12-13 19:08:56,393 INFO train.py line 351 16826] Epoch: [1/100][3536/6120] Data 33.011 (18.416) Batch 34.974 (39.152) Remain 6617:18:16 Loss 1.4451 Accuracy 0.5044.
[2021-12-13 19:09:42,432 INFO train.py line 351 16826] Epoch: [1/100][3552/6120] Data 43.620 (18.429) Batch 46.038 (39.183) Remain 6622:22:25 Loss 1.8660 Accuracy 0.3473.
[2021-12-13 19:10:15,179 INFO train.py line 351 16826] Epoch: [1/100][3568/6120] Data 32.333 (18.416) Batch 32.747 (39.154) Remain 6617:19:19 Loss 1.0934 Accuracy 0.6476.
[2021-12-13 19:10:50,047 INFO train.py line 351 16826] Epoch: [1/100][3584/6120] Data 32.380 (18.407) Batch 34.868 (39.135) Remain 6613:54:53 Loss 1.2241 Accuracy 0.5867.
[2021-12-13 19:11:30,006 INFO train.py line 351 16826] Epoch: [1/100][3600/6120] Data 39.368 (18.424) Batch 39.959 (39.138) Remain 6614:21:36 Loss 1.1567 Accuracy 0.6350.
[2021-12-13 19:12:04,487 INFO train.py line 351 16826] Epoch: [1/100][3616/6120] Data 33.261 (18.435) Batch 34.481 (39.118) Remain 6610:42:13 Loss 1.2644 Accuracy 0.5260.
[2021-12-13 19:12:40,363 INFO train.py line 351 16826] Epoch: [1/100][3632/6120] Data 32.848 (18.426) Batch 35.876 (39.103) Remain 6608:06:59 Loss 1.2343 Accuracy 0.6029.
[2021-12-13 19:13:17,309 INFO train.py line 351 16826] Epoch: [1/100][3648/6120] Data 36.553 (18.425) Batch 36.946 (39.094) Remain 6606:20:37 Loss 1.0098 Accuracy 0.5688.
[2021-12-13 19:13:49,209 INFO train.py line 351 16826] Epoch: [1/100][3664/6120] Data 31.687 (18.412) Batch 31.899 (39.062) Remain 6600:51:40 Loss 0.7285 Accuracy 0.8796.
[2021-12-13 19:14:27,938 INFO train.py line 351 16826] Epoch: [1/100][3680/6120] Data 34.488 (18.406) Batch 38.729 (39.061) Remain 6600:26:34 Loss 1.2689 Accuracy 0.6045.
[2021-12-13 19:15:05,665 INFO train.py line 351 16826] Epoch: [1/100][3696/6120] Data 36.967 (18.403) Batch 37.727 (39.055) Remain 6599:17:37 Loss 0.5915 Accuracy 0.8405.
[2021-12-13 19:15:40,826 INFO train.py line 351 16826] Epoch: [1/100][3712/6120] Data 31.476 (18.400) Batch 35.161 (39.038) Remain 6596:17:02 Loss 0.9281 Accuracy 0.7522.
[2021-12-13 19:16:21,266 INFO train.py line 351 16826] Epoch: [1/100][3728/6120] Data 38.826 (18.412) Batch 40.439 (39.044) Remain 6597:07:34 Loss 1.3267 Accuracy 0.5984.
[2021-12-13 19:16:57,710 INFO train.py line 351 16826] Epoch: [1/100][3744/6120] Data 31.413 (18.398) Batch 36.444 (39.033) Remain 6595:04:31 Loss 0.7065 Accuracy 0.8165.
[2021-12-13 19:17:38,184 INFO train.py line 351 16826] Epoch: [1/100][3760/6120] Data 38.003 (18.406) Batch 40.474 (39.039) Remain 6595:56:16 Loss 1.2539 Accuracy 0.6318.
[2021-12-13 19:18:19,378 INFO train.py line 351 16826] Epoch: [1/100][3776/6120] Data 38.638 (18.401) Batch 41.193 (39.049) Remain 6597:18:23 Loss 1.3878 Accuracy 0.6190.
[2021-12-13 19:18:57,601 INFO train.py line 351 16826] Epoch: [1/100][3792/6120] Data 37.586 (18.388) Batch 38.224 (39.045) Remain 6596:32:41 Loss 0.7565 Accuracy 0.7963.
[2021-12-13 19:19:44,071 INFO train.py line 351 16826] Epoch: [1/100][3808/6120] Data 43.603 (18.409) Batch 46.470 (39.076) Remain 6601:38:29 Loss 0.5063 Accuracy 0.8026.
[2021-12-13 19:20:18,165 INFO train.py line 351 16826] Epoch: [1/100][3824/6120] Data 33.066 (18.404) Batch 34.094 (39.055) Remain 6597:56:44 Loss 1.9646 Accuracy 0.4419.
[2021-12-13 19:20:39,977 INFO train.py line 351 16826] Epoch: [1/100][3840/6120] Data 20.554 (18.366) Batch 21.812 (38.984) Remain 6585:38:04 Loss 0.6948 Accuracy 0.7733.
[2021-12-13 19:21:09,411 INFO train.py line 351 16826] Epoch: [1/100][3856/6120] Data 28.826 (18.361) Batch 29.435 (38.944) Remain 6578:46:05 Loss 0.5337 Accuracy 0.7660.
[2021-12-13 19:21:50,258 INFO train.py line 351 16826] Epoch: [1/100][3872/6120] Data 39.202 (18.380) Batch 40.846 (38.952) Remain 6579:55:22 Loss 0.8787 Accuracy 0.7421.
[2021-12-13 19:22:26,541 INFO train.py line 351 16826] Epoch: [1/100][3888/6120] Data 35.209 (18.374) Batch 36.283 (38.941) Remain 6577:53:41 Loss 0.9062 Accuracy 0.7477.
[2021-12-13 19:23:08,241 INFO train.py line 351 16826] Epoch: [1/100][3904/6120] Data 41.422 (18.377) Batch 41.700 (38.952) Remain 6579:37:53 Loss 0.8010 Accuracy 0.6505.
[2021-12-13 19:23:50,630 INFO train.py line 351 16826] Epoch: [1/100][3920/6120] Data 39.899 (18.374) Batch 42.390 (38.966) Remain 6581:49:41 Loss 1.0629 Accuracy 0.6493.
[2021-12-13 19:24:30,589 INFO train.py line 351 16826] Epoch: [1/100][3936/6120] Data 38.445 (18.367) Batch 39.959 (38.970) Remain 6582:20:11 Loss 1.4585 Accuracy 0.5490.
[2021-12-13 19:25:22,949 INFO train.py line 351 16826] Epoch: [1/100][3952/6120] Data 47.331 (18.381) Batch 52.360 (39.024) Remain 6591:19:10 Loss 1.6964 Accuracy 0.5193.
[2021-12-13 19:25:58,594 INFO train.py line 351 16826] Epoch: [1/100][3968/6120] Data 35.074 (18.378) Batch 35.645 (39.011) Remain 6588:50:39 Loss 0.6712 Accuracy 0.7929.
[2021-12-13 19:26:53,590 INFO train.py line 351 16826] Epoch: [1/100][3984/6120] Data 53.180 (18.414) Batch 54.996 (39.075) Remain 6599:30:48 Loss 1.0726 Accuracy 0.6194.
[2021-12-13 19:27:25,086 INFO train.py line 351 16826] Epoch: [1/100][4000/6120] Data 30.937 (18.393) Batch 31.496 (39.045) Remain 6594:13:11 Loss 1.1047 Accuracy 0.6302.
[2021-12-13 19:27:55,527 INFO train.py line 351 16826] Epoch: [1/100][4016/6120] Data 28.646 (18.374) Batch 30.440 (39.010) Remain 6588:15:25 Loss 1.4558 Accuracy 0.5484.
[2021-12-13 19:28:29,680 INFO train.py line 351 16826] Epoch: [1/100][4032/6120] Data 33.353 (18.363) Batch 34.153 (38.991) Remain 6584:49:42 Loss 0.8501 Accuracy 0.7329.
[2021-12-13 19:29:10,433 INFO train.py line 351 16826] Epoch: [1/100][4048/6120] Data 35.757 (18.368) Batch 40.753 (38.998) Remain 6585:49:53 Loss 0.6396 Accuracy 0.7728.
[2021-12-13 19:30:01,382 INFO train.py line 351 16826] Epoch: [1/100][4064/6120] Data 48.368 (18.386) Batch 50.949 (39.045) Remain 6593:36:12 Loss 1.1566 Accuracy 0.6483.
[2021-12-13 19:30:38,684 INFO train.py line 351 16826] Epoch: [1/100][4080/6120] Data 34.652 (18.384) Batch 37.302 (39.038) Remain 6592:16:32 Loss 1.2343 Accuracy 0.5820.
[2021-12-13 19:31:09,920 INFO train.py line 351 16826] Epoch: [1/100][4096/6120] Data 30.486 (18.386) Batch 31.236 (39.008) Remain 6586:57:19 Loss 0.6977 Accuracy 0.7157.
[2021-12-13 19:31:52,062 INFO train.py line 351 16826] Epoch: [1/100][4112/6120] Data 37.113 (18.386) Batch 42.142 (39.020) Remain 6588:50:28 Loss 1.2767 Accuracy 0.6118.
[2021-12-13 19:32:35,242 INFO train.py line 351 16826] Epoch: [1/100][4128/6120] Data 39.113 (18.406) Batch 43.181 (39.036) Remain 6591:23:26 Loss 1.1273 Accuracy 0.6386.
[2021-12-13 19:33:25,709 INFO train.py line 351 16826] Epoch: [1/100][4144/6120] Data 49.138 (18.443) Batch 50.467 (39.080) Remain 6598:40:08 Loss 1.0512 Accuracy 0.6315.
[2021-12-13 19:33:58,250 INFO train.py line 351 16826] Epoch: [1/100][4160/6120] Data 28.587 (18.423) Batch 32.541 (39.055) Remain 6594:14:55 Loss 1.3506 Accuracy 0.5453.
[2021-12-13 19:34:40,195 INFO train.py line 351 16826] Epoch: [1/100][4176/6120] Data 40.271 (18.424) Batch 41.945 (39.066) Remain 6595:56:41 Loss 1.1107 Accuracy 0.6615.
[2021-12-13 19:35:30,859 INFO train.py line 351 16826] Epoch: [1/100][4192/6120] Data 48.230 (18.439) Batch 50.664 (39.111) Remain 6603:14:41 Loss 1.1881 Accuracy 0.5857.
[2021-12-13 19:36:06,301 INFO train.py line 351 16826] Epoch: [1/100][4208/6120] Data 31.905 (18.425) Batch 35.441 (39.097) Remain 6600:42:56 Loss 1.1628 Accuracy 0.6914.
[2021-12-13 19:36:32,223 INFO train.py line 351 16826] Epoch: [1/100][4224/6120] Data 24.389 (18.391) Batch 25.922 (39.047) Remain 6592:07:00 Loss 0.6931 Accuracy 0.8650.
[2021-12-13 19:37:18,316 INFO train.py line 351 16826] Epoch: [1/100][4240/6120] Data 41.046 (18.387) Batch 46.093 (39.073) Remain 6596:25:57 Loss 0.9454 Accuracy 0.6904.
[2021-12-13 19:37:56,184 INFO train.py line 351 16826] Epoch: [1/100][4256/6120] Data 32.828 (18.374) Batch 37.868 (39.069) Remain 6595:29:37 Loss 0.9609 Accuracy 0.7247.
[2021-12-13 19:38:37,363 INFO train.py line 351 16826] Epoch: [1/100][4272/6120] Data 40.175 (18.367) Batch 41.179 (39.077) Remain 6596:39:16 Loss 0.7743 Accuracy 0.6854.
[2021-12-13 19:39:10,183 INFO train.py line 351 16826] Epoch: [1/100][4288/6120] Data 31.556 (18.352) Batch 32.821 (39.053) Remain 6592:32:24 Loss 0.9878 Accuracy 0.6317.
[2021-12-13 19:39:57,661 INFO train.py line 351 16826] Epoch: [1/100][4304/6120] Data 47.141 (18.382) Batch 47.477 (39.085) Remain 6597:39:10 Loss 0.7526 Accuracy 0.7956.
[2021-12-13 19:40:35,906 INFO train.py line 351 16826] Epoch: [1/100][4320/6120] Data 35.341 (18.377) Batch 38.246 (39.081) Remain 6596:57:17 Loss 1.1312 Accuracy 0.6127.
[2021-12-13 19:41:06,354 INFO train.py line 351 16826] Epoch: [1/100][4336/6120] Data 27.813 (18.368) Batch 30.448 (39.050) Remain 6591:24:13 Loss 1.3101 Accuracy 0.6153.
[2021-12-13 19:41:41,184 INFO train.py line 351 16826] Epoch: [1/100][4352/6120] Data 34.174 (18.358) Batch 34.830 (39.034) Remain 6588:36:40 Loss 0.4676 Accuracy 0.8831.
[2021-12-13 19:42:23,556 INFO train.py line 351 16826] Epoch: [1/100][4368/6120] Data 37.427 (18.374) Batch 42.372 (39.046) Remain 6590:30:05 Loss 1.1585 Accuracy 0.6853.
[2021-12-13 19:42:55,252 INFO train.py line 351 16826] Epoch: [1/100][4384/6120] Data 29.963 (18.362) Batch 31.696 (39.020) Remain 6585:48:01 Loss 1.4711 Accuracy 0.5488.
[2021-12-13 19:43:25,564 INFO train.py line 351 16826] Epoch: [1/100][4400/6120] Data 27.991 (18.339) Batch 30.311 (38.988) Remain 6580:16:56 Loss 1.2050 Accuracy 0.6267.
[2021-12-13 19:44:10,926 INFO train.py line 351 16826] Epoch: [1/100][4416/6120] Data 42.460 (18.348) Batch 45.363 (39.011) Remain 6584:00:26 Loss 1.0054 Accuracy 0.6874.
[2021-12-13 19:44:53,335 INFO train.py line 351 16826] Epoch: [1/100][4432/6120] Data 41.110 (18.365) Batch 42.409 (39.023) Remain 6585:54:15 Loss 0.5375 Accuracy 0.8855.
[2021-12-13 19:45:31,990 INFO train.py line 351 16826] Epoch: [1/100][4448/6120] Data 38.023 (18.366) Batch 38.655 (39.022) Remain 6585:30:25 Loss 0.4901 Accuracy 0.8596.
[2021-12-13 19:46:09,742 INFO train.py line 351 16826] Epoch: [1/100][4464/6120] Data 33.700 (18.357) Batch 37.752 (39.017) Remain 6584:33:56 Loss 0.8132 Accuracy 0.7278.
[2021-12-13 19:46:51,674 INFO train.py line 351 16826] Epoch: [1/100][4480/6120] Data 40.838 (18.364) Batch 41.932 (39.028) Remain 6586:08:55 Loss 0.4776 Accuracy 0.8691.
[2021-12-13 19:47:36,502 INFO train.py line 351 16826] Epoch: [1/100][4496/6120] Data 42.745 (18.368) Batch 44.828 (39.048) Remain 6589:27:30 Loss 1.4481 Accuracy 0.6266.
[2021-12-13 19:48:27,974 INFO train.py line 351 16826] Epoch: [1/100][4512/6120] Data 50.873 (18.395) Batch 51.472 (39.092) Remain 6596:43:08 Loss 0.8993 Accuracy 0.7113.
[2021-12-13 19:49:06,283 INFO train.py line 351 16826] Epoch: [1/100][4528/6120] Data 37.594 (18.392) Batch 38.309 (39.090) Remain 6596:04:42 Loss 0.7402 Accuracy 0.7709.
[2021-12-13 19:49:47,775 INFO train.py line 351 16826] Epoch: [1/100][4544/6120] Data 40.106 (18.400) Batch 41.492 (39.098) Remain 6597:19:56 Loss 1.1358 Accuracy 0.6395.
[2021-12-13 19:50:25,182 INFO train.py line 351 16826] Epoch: [1/100][4560/6120] Data 36.946 (18.395) Batch 37.406 (39.092) Remain 6596:09:25 Loss 0.5258 Accuracy 0.8046.
[2021-12-13 19:51:09,627 INFO train.py line 351 16826] Epoch: [1/100][4576/6120] Data 43.027 (18.410) Batch 44.446 (39.111) Remain 6599:08:29 Loss 1.1742 Accuracy 0.6634.
[2021-12-13 19:51:46,131 INFO train.py line 351 16826] Epoch: [1/100][4592/6120] Data 35.792 (18.413) Batch 36.503 (39.102) Remain 6597:26:04 Loss 0.5298 Accuracy 0.8917.
[2021-12-13 19:52:26,319 INFO train.py line 351 16826] Epoch: [1/100][4608/6120] Data 38.001 (18.411) Batch 40.188 (39.106) Remain 6597:53:50 Loss 0.8350 Accuracy 0.6887.
[2021-12-13 19:52:56,707 INFO train.py line 351 16826] Epoch: [1/100][4624/6120] Data 29.736 (18.400) Batch 30.388 (39.075) Remain 6592:38:02 Loss 0.8585 Accuracy 0.7126.
[2021-12-13 19:53:35,572 INFO train.py line 351 16826] Epoch: [1/100][4640/6120] Data 38.464 (18.408) Batch 38.866 (39.075) Remain 6592:20:17 Loss 1.9217 Accuracy 0.3634.
[2021-12-13 19:54:09,633 INFO train.py line 351 16826] Epoch: [1/100][4656/6120] Data 33.347 (18.395) Batch 34.061 (39.057) Remain 6589:15:28 Loss 0.7584 Accuracy 0.7009.
[2021-12-13 19:54:45,143 INFO train.py line 351 16826] Epoch: [1/100][4672/6120] Data 33.019 (18.392) Batch 35.510 (39.045) Remain 6587:02:05 Loss 1.2109 Accuracy 0.6451.
[2021-12-13 19:55:35,309 INFO train.py line 351 16826] Epoch: [1/100][4688/6120] Data 45.131 (18.404) Batch 50.165 (39.083) Remain 6593:15:49 Loss 0.6239 Accuracy 0.7911.
[2021-12-13 19:56:17,875 INFO train.py line 351 16826] Epoch: [1/100][4704/6120] Data 41.465 (18.414) Batch 42.567 (39.095) Remain 6595:05:19 Loss 0.6953 Accuracy 0.7849.
[2021-12-13 19:57:01,076 INFO train.py line 351 16826] Epoch: [1/100][4720/6120] Data 41.329 (18.427) Batch 43.201 (39.109) Remain 6597:15:46 Loss 0.7717 Accuracy 0.6165.
[2021-12-13 19:57:36,224 INFO train.py line 351 16826] Epoch: [1/100][4736/6120] Data 31.341 (18.421) Batch 35.148 (39.096) Remain 6594:49:54 Loss 0.7916 Accuracy 0.7472.
[2021-12-13 19:58:19,919 INFO train.py line 351 16826] Epoch: [1/100][4752/6120] Data 42.831 (18.435) Batch 43.694 (39.111) Remain 6597:16:11 Loss 0.8097 Accuracy 0.7433.
[2021-12-13 19:59:01,018 INFO train.py line 351 16826] Epoch: [1/100][4768/6120] Data 39.726 (18.444) Batch 41.100 (39.118) Remain 6598:13:17 Loss 0.5857 Accuracy 0.8174.
[2021-12-13 19:59:43,352 INFO train.py line 351 16826] Epoch: [1/100][4784/6120] Data 40.262 (18.442) Batch 42.333 (39.129) Remain 6599:51:41 Loss 0.7189 Accuracy 0.7238.
[2021-12-13 20:00:22,097 INFO train.py line 351 16826] Epoch: [1/100][4800/6120] Data 36.289 (18.447) Batch 38.745 (39.127) Remain 6599:28:20 Loss 1.8076 Accuracy 0.4812.
[2021-12-13 20:01:04,257 INFO train.py line 351 16826] Epoch: [1/100][4816/6120] Data 38.822 (18.455) Batch 42.160 (39.137) Remain 6600:59:52 Loss 1.6106 Accuracy 0.5212.
[2021-12-13 20:01:43,616 INFO train.py line 351 16826] Epoch: [1/100][4832/6120] Data 34.339 (18.453) Batch 39.359 (39.138) Remain 6600:56:50 Loss 1.4541 Accuracy 0.6097.
[2021-12-13 20:02:23,584 INFO train.py line 351 16826] Epoch: [1/100][4848/6120] Data 34.963 (18.450) Batch 39.968 (39.141) Remain 6601:14:07 Loss 0.5956 Accuracy 0.8156.
[2021-12-13 20:02:55,641 INFO train.py line 351 16826] Epoch: [1/100][4864/6120] Data 27.045 (18.434) Batch 32.057 (39.118) Remain 6597:07:53 Loss 1.2078 Accuracy 0.5251.
[2021-12-13 20:03:38,712 INFO train.py line 351 16826] Epoch: [1/100][4880/6120] Data 41.017 (18.447) Batch 43.071 (39.131) Remain 6599:08:37 Loss 1.2338 Accuracy 0.5495.
[2021-12-13 20:04:28,348 INFO train.py line 351 16826] Epoch: [1/100][4896/6120] Data 46.683 (18.464) Batch 49.636 (39.165) Remain 6604:45:35 Loss 1.5277 Accuracy 0.5310.
[2021-12-13 20:05:17,115 INFO train.py line 351 16826] Epoch: [1/100][4912/6120] Data 47.369 (18.485) Batch 48.767 (39.196) Remain 6609:51:36 Loss 1.3707 Accuracy 0.5200.
[2021-12-13 20:05:41,291 INFO train.py line 351 16826] Epoch: [1/100][4928/6120] Data 23.765 (18.470) Batch 24.176 (39.147) Remain 6601:27:44 Loss 1.2011 Accuracy 0.4221.
[2021-12-13 20:06:17,156 INFO train.py line 351 16826] Epoch: [1/100][4944/6120] Data 35.357 (18.471) Batch 35.864 (39.137) Remain 6599:29:48 Loss 1.0450 Accuracy 0.5795.
[2021-12-13 20:06:58,598 INFO train.py line 351 16826] Epoch: [1/100][4960/6120] Data 38.733 (18.472) Batch 41.442 (39.144) Remain 6600:34:36 Loss 1.2467 Accuracy 0.5265.
[2021-12-13 20:07:41,414 INFO train.py line 351 16826] Epoch: [1/100][4976/6120] Data 42.637 (18.479) Batch 42.816 (39.156) Remain 6602:23:37 Loss 0.6224 Accuracy 0.9111.
[2021-12-13 20:08:16,242 INFO train.py line 351 16826] Epoch: [1/100][4992/6120] Data 33.463 (18.478) Batch 34.828 (39.142) Remain 6599:52:50 Loss 1.1037 Accuracy 0.5766.
[2021-12-13 20:09:06,574 INFO train.py line 351 16826] Epoch: [1/100][5008/6120] Data 49.358 (18.502) Batch 50.332 (39.178) Remain 6605:44:03 Loss 1.2306 Accuracy 0.6111.
[2021-12-13 20:09:45,695 INFO train.py line 351 16826] Epoch: [1/100][5024/6120] Data 34.139 (18.509) Batch 39.121 (39.178) Remain 6605:31:47 Loss 0.9405 Accuracy 0.7445.
[2021-12-13 20:10:17,884 INFO train.py line 351 16826] Epoch: [1/100][5040/6120] Data 30.165 (18.496) Batch 32.190 (39.155) Remain 6601:36:55 Loss 1.5059 Accuracy 0.4928.
[2021-12-13 20:10:58,779 INFO train.py line 351 16826] Epoch: [1/100][5056/6120] Data 39.322 (18.505) Batch 40.895 (39.161) Remain 6602:22:08 Loss 1.2276 Accuracy 0.6019.
[2021-12-13 20:11:26,529 INFO train.py line 351 16826] Epoch: [1/100][5072/6120] Data 26.280 (18.491) Batch 27.750 (39.125) Remain 6596:07:34 Loss 1.1566 Accuracy 0.6318.
[2021-12-13 20:12:17,802 INFO train.py line 351 16826] Epoch: [1/100][5088/6120] Data 46.276 (18.515) Batch 51.274 (39.163) Remain 6602:23:35 Loss 1.8949 Accuracy 0.5139.
[2021-12-13 20:12:51,823 INFO train.py line 351 16826] Epoch: [1/100][5104/6120] Data 29.533 (18.502) Batch 34.021 (39.147) Remain 6599:30:04 Loss 2.0930 Accuracy 0.3922.
[2021-12-13 20:13:33,132 INFO train.py line 351 16826] Epoch: [1/100][5120/6120] Data 36.327 (18.498) Batch 41.309 (39.154) Remain 6600:27:59 Loss 0.9448 Accuracy 0.7064.
[2021-12-13 20:14:21,492 INFO train.py line 351 16826] Epoch: [1/100][5136/6120] Data 43.368 (18.511) Batch 48.359 (39.183) Remain 6605:07:36 Loss 1.2038 Accuracy 0.6403.
[2021-12-13 20:15:01,189 INFO train.py line 351 16826] Epoch: [1/100][5152/6120] Data 38.337 (18.514) Batch 39.697 (39.184) Remain 6605:13:19 Loss 0.9784 Accuracy 0.6404.
[2021-12-13 20:15:32,849 INFO train.py line 351 16826] Epoch: [1/100][5168/6120] Data 26.611 (18.497) Batch 31.660 (39.161) Remain 6601:07:16 Loss 0.9591 Accuracy 0.6138.
[2021-12-13 20:16:16,659 INFO train.py line 351 16826] Epoch: [1/100][5184/6120] Data 41.145 (18.492) Batch 43.810 (39.175) Remain 6603:21:57 Loss 1.1717 Accuracy 0.5596.
[2021-12-13 20:17:07,016 INFO train.py line 351 16826] Epoch: [1/100][5200/6120] Data 48.013 (18.509) Batch 50.357 (39.210) Remain 6608:59:27 Loss 1.1978 Accuracy 0.5894.
[2021-12-13 20:17:45,677 INFO train.py line 351 16826] Epoch: [1/100][5216/6120] Data 33.648 (18.500) Batch 38.661 (39.208) Remain 6608:31:59 Loss 1.1508 Accuracy 0.5632.
[2021-12-13 20:18:19,478 INFO train.py line 351 16826] Epoch: [1/100][5232/6120] Data 33.373 (18.492) Batch 33.800 (39.191) Remain 6605:34:18 Loss 1.1851 Accuracy 0.5809.
[2021-12-13 20:18:59,217 INFO train.py line 351 16826] Epoch: [1/100][5248/6120] Data 37.529 (18.489) Batch 39.740 (39.193) Remain 6605:40:45 Loss 1.0764 Accuracy 0.6708.
[2021-12-13 20:19:43,306 INFO train.py line 351 16826] Epoch: [1/100][5264/6120] Data 41.993 (18.491) Batch 44.089 (39.208) Remain 6608:00:47 Loss 1.4665 Accuracy 0.5454.
[2021-12-13 20:20:20,066 INFO train.py line 351 16826] Epoch: [1/100][5280/6120] Data 36.517 (18.488) Batch 36.760 (39.200) Remain 6606:35:19 Loss 0.5229 Accuracy 0.8935.
[2021-12-13 20:20:58,654 INFO train.py line 351 16826] Epoch: [1/100][5296/6120] Data 35.533 (18.487) Batch 38.588 (39.199) Remain 6606:06:09 Loss 1.0285 Accuracy 0.6521.
[2021-12-13 20:21:36,241 INFO train.py line 351 16826] Epoch: [1/100][5312/6120] Data 36.435 (18.486) Batch 37.587 (39.194) Remain 6605:06:37 Loss 1.3687 Accuracy 0.5160.
[2021-12-13 20:22:15,424 INFO train.py line 351 16826] Epoch: [1/100][5328/6120] Data 36.068 (18.487) Batch 39.183 (39.194) Remain 6604:55:50 Loss 1.0366 Accuracy 0.6063.
[2021-12-13 20:22:59,729 INFO train.py line 351 16826] Epoch: [1/100][5344/6120] Data 39.320 (18.496) Batch 44.305 (39.209) Remain 6607:20:07 Loss 1.3535 Accuracy 0.6031.
[2021-12-13 20:23:42,975 INFO train.py line 351 16826] Epoch: [1/100][5360/6120] Data 41.644 (18.511) Batch 43.246 (39.221) Remain 6609:11:29 Loss 1.1100 Accuracy 0.6632.
[2021-12-13 20:24:09,207 INFO train.py line 351 16826] Epoch: [1/100][5376/6120] Data 26.074 (18.489) Batch 26.232 (39.182) Remain 6602:30:12 Loss 0.8598 Accuracy 0.6277.
[2021-12-13 20:24:48,866 INFO train.py line 351 16826] Epoch: [1/100][5392/6120] Data 34.583 (18.484) Batch 39.659 (39.184) Remain 6602:34:02 Loss 3.0272 Accuracy 0.3654.
[2021-12-13 20:25:23,205 INFO train.py line 351 16826] Epoch: [1/100][5408/6120] Data 32.610 (18.476) Batch 34.339 (39.170) Remain 6599:58:40 Loss 1.6183 Accuracy 0.4313.
[2021-12-13 20:26:15,643 INFO train.py line 351 16826] Epoch: [1/100][5424/6120] Data 48.456 (18.493) Batch 52.438 (39.209) Remain 6606:23:55 Loss 1.1065 Accuracy 0.5807.
[2021-12-13 20:26:51,719 INFO train.py line 351 16826] Epoch: [1/100][5440/6120] Data 32.837 (18.494) Batch 36.076 (39.199) Remain 6604:40:20 Loss 1.3769 Accuracy 0.4806.
[2021-12-13 20:27:37,015 INFO train.py line 351 16826] Epoch: [1/100][5456/6120] Data 42.990 (18.499) Batch 45.295 (39.217) Remain 6607:30:35 Loss 1.5855 Accuracy 0.4097.
[2021-12-13 20:28:12,559 INFO train.py line 351 16826] Epoch: [1/100][5472/6120] Data 33.583 (18.490) Batch 35.544 (39.207) Remain 6605:31:34 Loss 1.1612 Accuracy 0.6957.
[2021-12-13 20:28:51,330 INFO train.py line 351 16826] Epoch: [1/100][5488/6120] Data 37.732 (18.497) Batch 38.771 (39.205) Remain 6605:08:17 Loss 0.7339 Accuracy 0.8619.
[2021-12-13 20:29:25,541 INFO train.py line 351 16826] Epoch: [1/100][5504/6120] Data 31.849 (18.484) Batch 34.211 (39.191) Remain 6602:31:03 Loss 1.3095 Accuracy 0.5819.
[2021-12-13 20:30:10,624 INFO train.py line 351 16826] Epoch: [1/100][5520/6120] Data 43.151 (18.494) Batch 45.083 (39.208) Remain 6605:13:14 Loss 1.5173 Accuracy 0.5631.
[2021-12-13 20:30:49,143 INFO train.py line 351 16826] Epoch: [1/100][5536/6120] Data 33.467 (18.491) Batch 38.519 (39.206) Remain 6604:42:40 Loss 1.7255 Accuracy 0.4741.
[2021-12-13 20:31:31,544 INFO train.py line 351 16826] Epoch: [1/100][5552/6120] Data 37.397 (18.495) Batch 42.402 (39.215) Remain 6606:05:17 Loss 1.3310 Accuracy 0.5923.
[2021-12-13 20:32:03,841 INFO train.py line 351 16826] Epoch: [1/100][5568/6120] Data 30.568 (18.490) Batch 32.297 (39.195) Remain 6602:33:54 Loss 1.7692 Accuracy 0.4988.
[2021-12-13 20:32:49,249 INFO train.py line 351 16826] Epoch: [1/100][5584/6120] Data 40.330 (18.486) Batch 45.408 (39.213) Remain 6605:23:21 Loss 1.6867 Accuracy 0.4649.
[2021-12-13 20:33:40,787 INFO train.py line 351 16826] Epoch: [1/100][5600/6120] Data 49.802 (18.506) Batch 51.538 (39.248) Remain 6611:08:49 Loss 1.3531 Accuracy 0.5956.
[2021-12-13 20:34:29,772 INFO train.py line 351 16826] Epoch: [1/100][5616/6120] Data 43.913 (18.515) Batch 48.985 (39.276) Remain 6615:38:41 Loss 1.4148 Accuracy 0.6337.
[2021-12-13 20:35:01,720 INFO train.py line 351 16826] Epoch: [1/100][5632/6120] Data 29.645 (18.504) Batch 31.948 (39.255) Remain 6611:57:49 Loss 1.1943 Accuracy 0.6471.
[2021-12-13 20:35:35,016 INFO train.py line 351 16826] Epoch: [1/100][5648/6120] Data 31.927 (18.504) Batch 33.296 (39.238) Remain 6608:56:45 Loss 0.9025 Accuracy 0.7556.
[2021-12-13 20:36:30,387 INFO train.py line 351 16826] Epoch: [1/100][5664/6120] Data 50.307 (18.521) Batch 55.371 (39.284) Remain 6616:26:50 Loss 0.8572 Accuracy 0.7565.
[2021-12-13 20:37:09,590 INFO train.py line 351 16826] Epoch: [1/100][5680/6120] Data 35.066 (18.523) Batch 39.203 (39.284) Remain 6616:14:03 Loss 1.7375 Accuracy 0.4965.
[2021-12-13 20:37:51,790 INFO train.py line 351 16826] Epoch: [1/100][5696/6120] Data 41.373 (18.529) Batch 42.200 (39.292) Remain 6617:26:21 Loss 1.6721 Accuracy 0.6757.
[2021-12-13 20:38:29,068 INFO train.py line 351 16826] Epoch: [1/100][5712/6120] Data 33.470 (18.524) Batch 37.278 (39.286) Remain 6616:18:53 Loss 1.3878 Accuracy 0.5383.
[2021-12-13 20:39:02,585 INFO train.py line 351 16826] Epoch: [1/100][5728/6120] Data 29.742 (18.514) Batch 33.517 (39.270) Remain 6613:25:35 Loss 1.6341 Accuracy 0.3771.
[2021-12-13 20:39:40,364 INFO train.py line 351 16826] Epoch: [1/100][5744/6120] Data 36.923 (18.516) Batch 37.779 (39.266) Remain 6612:33:08 Loss 1.0812 Accuracy 0.6479.
[2021-12-13 20:40:16,050 INFO train.py line 351 16826] Epoch: [1/100][5760/6120] Data 34.296 (18.511) Batch 35.686 (39.256) Remain 6610:42:11 Loss 1.4470 Accuracy 0.4931.
[2021-12-13 20:40:52,868 INFO train.py line 351 16826] Epoch: [1/100][5776/6120] Data 31.773 (18.503) Batch 36.818 (39.249) Remain 6609:23:29 Loss 1.2719 Accuracy 0.6038.
[2021-12-13 20:41:41,422 INFO train.py line 351 16826] Epoch: [1/100][5792/6120] Data 46.540 (18.515) Batch 48.554 (39.275) Remain 6613:32:43 Loss 1.3230 Accuracy 0.6116.
[2021-12-13 20:42:30,002 INFO train.py line 351 16826] Epoch: [1/100][5808/6120] Data 43.513 (18.525) Batch 48.580 (39.301) Remain 6617:41:13 Loss 1.3688 Accuracy 0.4922.
[2021-12-13 20:43:13,241 INFO train.py line 351 16826] Epoch: [1/100][5824/6120] Data 42.099 (18.528) Batch 43.240 (39.311) Remain 6619:20:04 Loss 1.1212 Accuracy 0.6634.
[2021-12-13 20:43:56,276 INFO train.py line 351 16826] Epoch: [1/100][5840/6120] Data 42.026 (18.544) Batch 43.034 (39.322) Remain 6620:52:38 Loss 0.8970 Accuracy 0.7425.
[2021-12-13 20:44:37,063 INFO train.py line 351 16826] Epoch: [1/100][5856/6120] Data 37.975 (18.540) Batch 40.787 (39.326) Remain 6621:22:35 Loss 1.2378 Accuracy 0.6027.
[2021-12-13 20:45:24,169 INFO train.py line 351 16826] Epoch: [1/100][5872/6120] Data 45.293 (18.552) Batch 47.106 (39.347) Remain 6624:46:17 Loss 0.8250 Accuracy 0.7510.
[2021-12-13 20:46:12,534 INFO train.py line 351 16826] Epoch: [1/100][5888/6120] Data 43.382 (18.566) Batch 48.365 (39.371) Remain 6628:43:21 Loss 1.2476 Accuracy 0.6334.
[2021-12-13 20:46:50,874 INFO train.py line 351 16826] Epoch: [1/100][5904/6120] Data 36.075 (18.568) Batch 38.340 (39.368) Remain 6628:04:37 Loss 1.3079 Accuracy 0.5326.
[2021-12-13 20:47:16,087 INFO train.py line 351 16826] Epoch: [1/100][5920/6120] Data 24.436 (18.547) Batch 25.213 (39.330) Remain 6621:27:39 Loss 0.7334 Accuracy 0.8160.
[2021-12-13 20:48:02,965 INFO train.py line 351 16826] Epoch: [1/100][5936/6120] Data 44.660 (18.563) Batch 46.879 (39.351) Remain 6624:42:41 Loss 1.7996 Accuracy 0.4731.
[2021-12-13 20:48:46,666 INFO train.py line 351 16826] Epoch: [1/100][5952/6120] Data 42.108 (18.571) Batch 43.700 (39.362) Remain 6626:30:18 Loss 1.4842 Accuracy 0.5260.
[2021-12-13 20:49:35,863 INFO train.py line 351 16826] Epoch: [1/100][5968/6120] Data 48.838 (18.588) Batch 49.198 (39.389) Remain 6630:46:08 Loss 0.3851 Accuracy 0.9598.
[2021-12-13 20:50:14,573 INFO train.py line 351 16826] Epoch: [1/100][5984/6120] Data 36.498 (18.589) Batch 38.710 (39.387) Remain 6630:17:18 Loss 1.4523 Accuracy 0.5430.
[2021-12-13 20:50:56,516 INFO train.py line 351 16826] Epoch: [1/100][6000/6120] Data 41.088 (18.584) Batch 41.943 (39.394) Remain 6631:15:39 Loss 0.7965 Accuracy 0.7735.
[2021-12-13 20:51:39,969 INFO train.py line 351 16826] Epoch: [1/100][6016/6120] Data 42.985 (18.600) Batch 43.453 (39.404) Remain 6632:54:10 Loss 0.8989 Accuracy 0.7559.
[2021-12-13 20:52:19,690 INFO train.py line 351 16826] Epoch: [1/100][6032/6120] Data 38.992 (18.602) Batch 39.721 (39.405) Remain 6632:52:09 Loss 0.5514 Accuracy 0.7862.
[2021-12-13 20:53:03,369 INFO train.py line 351 16826] Epoch: [1/100][6048/6120] Data 40.638 (18.611) Batch 43.679 (39.417) Remain 6634:35:50 Loss 1.1829 Accuracy 0.6268.
[2021-12-13 20:53:28,695 INFO train.py line 351 16826] Epoch: [1/100][6064/6120] Data 24.884 (18.594) Batch 25.325 (39.379) Remain 6628:09:50 Loss 1.1730 Accuracy 0.6752.
[2021-12-13 20:54:01,955 INFO train.py line 351 16826] Epoch: [1/100][6080/6120] Data 31.880 (18.587) Batch 33.261 (39.363) Remain 6625:16:44 Loss 0.8473 Accuracy 0.6932.
[2021-12-13 20:54:37,860 INFO train.py line 351 16826] Epoch: [1/100][6096/6120] Data 33.789 (18.586) Batch 35.905 (39.354) Remain 6623:34:33 Loss 1.2073 Accuracy 0.5936.
[2021-12-13 20:55:18,273 INFO train.py line 351 16826] Epoch: [1/100][6112/6120] Data 38.069 (18.587) Batch 40.413 (39.357) Remain 6623:52:03 Loss 1.0998 Accuracy 0.7021.
[2021-12-13 20:55:43,049 INFO train.py line 364 16826] Train result at epoch [1/100]: mIoU/mAcc/allAcc 0.2222/0.2875/0.6016.
[2021-12-13 20:55:43,050 INFO train.py line 370 16826] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>>
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[2021-12-13 20:55:47,121 INFO train.py line 425 16826] Test: [1/68] Data 1.052 (1.052) Batch 4.069 (4.069) Loss 0.8107 (0.8107) Accuracy 0.7034.
[2021-12-13 20:55:49,579 INFO train.py line 425 16826] Test: [2/68] Data 0.000 (0.526) Batch 2.458 (3.264) Loss 0.7152 (0.7652) Accuracy 0.7202.
[2021-12-13 20:55:54,080 INFO train.py line 425 16826] Test: [3/68] Data 0.000 (0.351) Batch 4.501 (3.676) Loss 1.2877 (0.9915) Accuracy 0.6942.
[2021-12-13 20:56:06,768 INFO train.py line 425 16826] Test: [4/68] Data 0.000 (0.263) Batch 12.688 (5.929) Loss 2.8900 (1.8485) Accuracy 0.6297.
[2021-12-13 20:56:14,058 INFO train.py line 425 16826] Test: [5/68] Data 0.000 (0.211) Batch 7.290 (6.201) Loss 1.1870 (1.6767) Accuracy 0.6840.
[2021-12-13 20:57:02,890 INFO train.py line 425 16826] Test: [6/68] Data 0.000 (0.176) Batch 48.831 (13.306) Loss 61.8538 (23.5439) Accuracy 0.4273.
[2021-12-13 20:57:07,372 INFO train.py line 425 16826] Test: [7/68] Data 0.000 (0.150) Batch 4.482 (12.046) Loss 5.5661 (21.5197) Accuracy 0.6705.
[2021-12-13 20:57:09,446 INFO train.py line 425 16826] Test: [8/68] Data 0.000 (0.132) Batch 2.074 (10.799) Loss 0.9861 (20.1027) Accuracy 0.8539.
[2021-12-13 20:57:11,489 INFO train.py line 425 16826] Test: [9/68] Data 0.000 (0.117) Batch 2.043 (9.826) Loss 0.3414 (18.8349) Accuracy 0.9227.
[2021-12-13 20:57:16,612 INFO train.py line 425 16826] Test: [10/68] Data 0.000 (0.105) Batch 5.123 (9.356) Loss 4.9434 (17.5069) Accuracy 0.6703.
[2021-12-13 20:57:18,465 INFO train.py line 425 16826] Test: [11/68] Data 0.000 (0.096) Batch 1.853 (8.674) Loss 0.4779 (16.6217) Accuracy 0.8326.
[2021-12-13 20:57:23,886 INFO train.py line 425 16826] Test: [12/68] Data 0.000 (0.088) Batch 5.421 (8.403) Loss 5.4321 (15.6659) Accuracy 0.6086.
[2021-12-13 20:58:44,726 INFO train.py line 425 16826] Test: [13/68] Data 0.000 (0.081) Batch 80.840 (13.975) Loss 147.9118 (44.9998) Accuracy 0.3023.
[2021-12-13 20:58:49,683 INFO train.py line 425 16826] Test: [14/68] Data 0.000 (0.075) Batch 4.957 (13.331) Loss 3.7697 (42.5425) Accuracy 0.6551.
[2021-12-13 20:58:53,048 INFO train.py line 425 16826] Test: [15/68] Data 0.000 (0.070) Batch 3.364 (12.666) Loss 3.0604 (40.7246) Accuracy 0.6815.
[2021-12-13 20:59:25,938 INFO train.py line 425 16826] Test: [16/68] Data 0.000 (0.066) Batch 32.891 (13.930) Loss 67.0165 (43.6596) Accuracy 0.3926.
[2021-12-13 20:59:29,720 INFO train.py line 425 16826] Test: [17/68] Data 0.000 (0.062) Batch 3.782 (13.333) Loss 6.2395 (42.0920) Accuracy 0.5791.
[2021-12-13 20:59:34,178 INFO train.py line 425 16826] Test: [18/68] Data 0.000 (0.059) Batch 4.457 (12.840) Loss 6.1313 (40.5209) Accuracy 0.5837.
[2021-12-13 20:59:35,146 INFO train.py line 425 16826] Test: [19/68] Data 0.000 (0.056) Batch 0.969 (12.215) Loss 0.3399 (39.7830) Accuracy 0.9129.
[2021-12-13 20:59:39,638 INFO train.py line 425 16826] Test: [20/68] Data 0.000 (0.053) Batch 4.491 (11.829) Loss 5.3733 (38.3602) Accuracy 0.6520.
[2021-12-13 20:59:43,385 INFO train.py line 425 16826] Test: [21/68] Data 0.000 (0.050) Batch 3.748 (11.444) Loss 0.7449 (37.0004) Accuracy 0.7938.
[2021-12-13 20:59:45,869 INFO train.py line 425 16826] Test: [22/68] Data 0.000 (0.048) Batch 2.483 (11.037) Loss 1.6562 (36.0067) Accuracy 0.4989.
[2021-12-13 20:59:48,020 INFO train.py line 425 16826] Test: [23/68] Data 0.000 (0.046) Batch 2.151 (10.651) Loss 1.4436 (35.1339) Accuracy 0.5229.
[2021-12-13 20:59:50,738 INFO train.py line 425 16826] Test: [24/68] Data 0.000 (0.044) Batch 2.718 (10.320) Loss 1.6722 (34.1994) Accuracy 0.4793.
[2021-12-13 20:59:53,372 INFO train.py line 425 16826] Test: [25/68] Data 0.000 (0.042) Batch 2.634 (10.013) Loss 1.4031 (33.3232) Accuracy 0.5347.
[2021-12-13 20:59:57,123 INFO train.py line 425 16826] Test: [26/68] Data 0.000 (0.041) Batch 3.751 (9.772) Loss 1.4847 (32.3230) Accuracy 0.5321.
[2021-12-13 21:00:02,155 INFO train.py line 425 16826] Test: [27/68] Data 0.000 (0.039) Batch 5.031 (9.596) Loss 1.4568 (31.2270) Accuracy 0.5254.
[2021-12-13 21:00:07,862 INFO train.py line 425 16826] Test: [28/68] Data 0.000 (0.038) Batch 5.707 (9.457) Loss 1.3150 (30.1329) Accuracy 0.5965.
[2021-12-13 21:00:09,870 INFO train.py line 425 16826] Test: [29/68] Data 0.000 (0.036) Batch 2.008 (9.201) Loss 0.7374 (29.5362) Accuracy 0.7910.
[2021-12-13 21:00:13,110 INFO train.py line 425 16826] Test: [30/68] Data 0.000 (0.035) Batch 3.241 (9.002) Loss 1.0868 (28.8061) Accuracy 0.5895.
[2021-12-13 21:00:18,426 INFO train.py line 425 16826] Test: [31/68] Data 0.000 (0.034) Batch 5.316 (8.883) Loss 0.8997 (27.8997) Accuracy 0.7602.
[2021-12-13 21:00:26,951 INFO train.py line 425 16826] Test: [32/68] Data 0.000 (0.033) Batch 8.526 (8.872) Loss 1.1426 (26.8247) Accuracy 0.6638.
[2021-12-13 21:00:29,648 INFO train.py line 425 16826] Test: [33/68] Data 0.000 (0.032) Batch 2.696 (8.685) Loss 1.6614 (26.2934) Accuracy 0.4874.
[2021-12-13 21:00:30,713 INFO train.py line 425 16826] Test: [34/68] Data 0.000 (0.031) Batch 1.066 (8.461) Loss 0.9474 (25.9801) Accuracy 0.7182.
[2021-12-13 21:00:43,417 INFO train.py line 425 16826] Test: [35/68] Data 0.000 (0.030) Batch 12.703 (8.582) Loss 1.0654 (24.8520) Accuracy 0.7278.
[2021-12-13 21:00:45,670 INFO train.py line 425 16826] Test: [36/68] Data 0.000 (0.029) Batch 2.253 (8.406) Loss 1.4608 (24.4368) Accuracy 0.5527.
[2021-12-13 21:00:48,489 INFO train.py line 425 16826] Test: [37/68] Data 0.000 (0.029) Batch 2.819 (8.255) Loss 1.5098 (23.9854) Accuracy 0.5459.
[2021-12-13 21:00:57,166 INFO train.py line 425 16826] Test: [38/68] Data 0.000 (0.028) Batch 8.677 (8.266) Loss 1.6757 (23.2085) Accuracy 0.4640.
[2021-12-13 21:00:58,694 INFO train.py line 425 16826] Test: [39/68] Data 0.000 (0.027) Batch 1.528 (8.093) Loss 1.2776 (22.9166) Accuracy 0.5622.
[2021-12-13 21:01:00,769 INFO train.py line 425 16826] Test: [40/68] Data 0.000 (0.026) Batch 2.075 (7.943) Loss 1.3244 (22.5798) Accuracy 0.5298.
[2021-12-13 21:01:02,777 INFO train.py line 425 16826] Test: [41/68] Data 0.000 (0.026) Batch 2.009 (7.798) Loss 1.2182 (22.2582) Accuracy 0.6152.
[2021-12-13 21:01:04,941 INFO train.py line 425 16826] Test: [42/68] Data 0.000 (0.025) Batch 2.164 (7.664) Loss 1.1885 (21.9319) Accuracy 0.5989.
[2021-12-13 21:01:13,655 INFO train.py line 425 16826] Test: [43/68] Data 0.000 (0.025) Batch 8.714 (7.688) Loss 1.4202 (21.2784) Accuracy 0.5330.
[2021-12-13 21:01:15,828 INFO train.py line 425 16826] Test: [44/68] Data 0.000 (0.024) Batch 2.174 (7.563) Loss 1.3793 (20.9836) Accuracy 0.5276.
[2021-12-13 21:01:16,774 INFO train.py line 425 16826] Test: [45/68] Data 0.000 (0.024) Batch 0.946 (7.416) Loss 1.0299 (20.8017) Accuracy 0.6777.
[2021-12-13 21:01:19,194 INFO train.py line 425 16826] Test: [46/68] Data 0.000 (0.023) Batch 2.420 (7.307) Loss 1.6029 (20.5072) Accuracy 0.4973.
[2021-12-13 21:01:21,546 INFO train.py line 425 16826] Test: [47/68] Data 0.000 (0.023) Batch 2.352 (7.202) Loss 1.3262 (20.2224) Accuracy 0.5417.
[2021-12-13 21:01:24,100 INFO train.py line 425 16826] Test: [48/68] Data 0.000 (0.022) Batch 2.555 (7.105) Loss 1.2654 (19.9320) Accuracy 0.6232.
[2021-12-13 21:01:26,963 INFO train.py line 425 16826] Test: [49/68] Data 0.000 (0.022) Batch 2.863 (7.019) Loss 1.5797 (19.6377) Accuracy 0.4972.
[2021-12-13 21:01:29,845 INFO train.py line 425 16826] Test: [50/68] Data 0.000 (0.021) Batch 2.882 (6.936) Loss 1.2913 (19.3475) Accuracy 0.5836.
[2021-12-13 21:01:34,785 INFO train.py line 425 16826] Test: [51/68] Data 0.000 (0.021) Batch 4.940 (6.897) Loss 0.7928 (18.9620) Accuracy 0.7551.
[2021-12-13 21:02:10,421 INFO train.py line 425 16826] Test: [52/68] Data 0.000 (0.020) Batch 35.636 (7.449) Loss 2.9017 (18.2294) Accuracy 0.5090.
[2021-12-13 21:02:51,546 INFO train.py line 425 16826] Test: [53/68] Data 0.000 (0.020) Batch 41.125 (8.085) Loss 5.1538 (17.6174) Accuracy 0.3684.
[2021-12-13 21:02:54,785 INFO train.py line 425 16826] Test: [54/68] Data 0.000 (0.020) Batch 3.238 (7.995) Loss 0.9230 (17.3707) Accuracy 0.7049.
[2021-12-13 21:02:57,224 INFO train.py line 425 16826] Test: [55/68] Data 0.000 (0.019) Batch 2.439 (7.894) Loss 1.4788 (17.1718) Accuracy 0.5532.
[2021-12-13 21:03:27,721 INFO train.py line 425 16826] Test: [56/68] Data 0.000 (0.019) Batch 30.497 (8.298) Loss 2.7958 (16.6306) Accuracy 0.4969.
[2021-12-13 21:03:34,182 INFO train.py line 425 16826] Test: [57/68] Data 0.000 (0.019) Batch 6.461 (8.265) Loss 1.3226 (16.3247) Accuracy 0.5907.
[2021-12-13 21:03:36,761 INFO train.py line 425 16826] Test: [58/68] Data 0.000 (0.018) Batch 2.580 (8.167) Loss 1.4190 (16.1452) Accuracy 0.5201.
[2021-12-13 21:03:38,812 INFO train.py line 425 16826] Test: [59/68] Data 0.000 (0.018) Batch 2.050 (8.064) Loss 1.1506 (15.9880) Accuracy 0.6574.
[2021-12-13 21:03:40,966 INFO train.py line 425 16826] Test: [60/68] Data 0.000 (0.018) Batch 2.154 (7.965) Loss 1.4679 (15.8330) Accuracy 0.5154.
[2021-12-13 21:03:43,536 INFO train.py line 425 16826] Test: [61/68] Data 0.000 (0.017) Batch 2.570 (7.877) Loss 1.5385 (15.6667) Accuracy 0.4792.
[2021-12-13 21:03:46,408 INFO train.py line 425 16826] Test: [62/68] Data 0.000 (0.017) Batch 2.873 (7.796) Loss 1.6272 (15.4955) Accuracy 0.5001.
[2021-12-13 21:03:48,702 INFO train.py line 425 16826] Test: [63/68] Data 0.000 (0.017) Batch 2.293 (7.709) Loss 1.3021 (15.3441) Accuracy 0.5771.
[2021-12-13 21:03:50,472 INFO train.py line 425 16826] Test: [64/68] Data 0.000 (0.017) Batch 1.770 (7.616) Loss 0.7268 (15.2103) Accuracy 0.7105.
[2021-12-13 21:03:52,182 INFO train.py line 425 16826] Test: [65/68] Data 0.000 (0.016) Batch 1.710 (7.525) Loss 2.9348 (15.1011) Accuracy 0.4533.
[2021-12-13 21:03:54,585 INFO train.py line 425 16826] Test: [66/68] Data 0.000 (0.016) Batch 2.403 (7.447) Loss 2.2090 (14.9638) Accuracy 0.3453.
[2021-12-13 21:03:54,809 INFO train.py line 425 16826] Test: [67/68] Data 0.000 (0.016) Batch 0.224 (7.340) Loss 1.5037 (14.9304) Accuracy 0.5092.
[2021-12-13 21:03:56,696 INFO train.py line 425 16826] Test: [68/68] Data 0.000 (0.016) Batch 1.887 (7.259) Loss 0.9394 (14.8014) Accuracy 0.7108.
[2021-12-13 21:03:56,753 INFO train.py line 434 16826] Val result: mIoU/mAcc/allAcc 0.2107/0.3248/0.5659.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_0 Result: iou/accuracy 0.5344/0.9578.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_1 Result: iou/accuracy 0.7600/0.7698.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_2 Result: iou/accuracy 0.5010/0.6907.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_3 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_4 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_5 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_6 Result: iou/accuracy 0.0894/0.2849.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_7 Result: iou/accuracy 0.4039/0.4823.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_8 Result: iou/accuracy 0.2983/0.7952.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_9 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_10 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_11 Result: iou/accuracy 0.0000/0.0000.
[2021-12-13 21:03:56,753 INFO train.py line 436 16826] Class_12 Result: iou/accuracy 0.1517/0.2414.
[2021-12-13 21:03:56,753 INFO train.py line 437 16826] <<<<<<<<<<<<<<<<< End Evaluation <<<<<<<<<<<<<<<<<
[2021-12-13 21:03:56,754 INFO train.py line 218 16826] Saving checkpoint to: exp/s3dis/pointtransformer_repro/model/model_last.pth
[2021-12-13 21:03:56,906 INFO train.py line 222 16826] Best validation mIoU updated to: 0.2107
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[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-12-13 21:04:49,328 INFO train.py line 351 16826] Epoch: [2/100][16/6120] Data 48.904 (27.877) Batch 52.372 (52.372) Remain 8813:54:04 Loss 0.9165 Accuracy 0.7308.
[2021-12-13 21:05:21,536 INFO train.py line 351 16826] Epoch: [2/100][32/6120] Data 31.001 (21.339) Batch 32.220 (42.296) Remain 7117:57:49 Loss 1.1527 Accuracy 0.6555.
[2021-12-13 21:06:11,378 INFO train.py line 351 16826] Epoch: [2/100][48/6120] Data 48.376 (22.171) Batch 49.842 (44.811) Remain 7541:06:32 Loss 1.1223 Accuracy 0.6586.
[2021-12-13 21:06:44,424 INFO train.py line 351 16826] Epoch: [2/100][64/6120] Data 32.196 (20.777) Batch 33.046 (41.870) Remain 7045:57:00 Loss 0.6756 Accuracy 0.7136.
[2021-12-13 21:07:27,103 INFO train.py line 351 16826] Epoch: [2/100][80/6120] Data 42.491 (21.263) Batch 42.679 (42.032) Remain 7072:59:59 Loss 0.6795 Accuracy 0.7830.
[2021-12-13 21:08:01,286 INFO train.py line 351 16826] Epoch: [2/100][96/6120] Data 29.139 (19.692) Batch 34.182 (40.723) Remain 6852:40:39 Loss 0.7147 Accuracy 0.6947.
[2021-12-13 21:08:44,976 INFO train.py line 351 16826] Epoch: [2/100][112/6120] Data 38.648 (19.504) Batch 43.690 (41.147) Remain 6923:48:50 Loss 1.0784 Accuracy 0.6801.
[2021-12-13 21:09:26,423 INFO train.py line 351 16826] Epoch: [2/100][128/6120] Data 37.927 (19.331) Batch 41.446 (41.185) Remain 6929:55:19 Loss 1.5411 Accuracy 0.5518.
[2021-12-13 21:10:09,638 INFO train.py line 351 16826] Epoch: [2/100][144/6120] Data 38.226 (19.455) Batch 43.215 (41.410) Remain 6967:42:18 Loss 1.2608 Accuracy 0.6477.
[2021-12-13 21:10:53,486 INFO train.py line 351 16826] Epoch: [2/100][160/6120] Data 41.230 (19.119) Batch 43.848 (41.654) Remain 7008:31:39 Loss 1.9773 Accuracy 0.4695.
[2021-12-13 21:11:47,477 INFO train.py line 351 16826] Epoch: [2/100][176/6120] Data 48.939 (19.501) Batch 53.991 (42.776) Remain 7197:02:43 Loss 1.5410 Accuracy 0.5481.
[2021-12-13 21:12:20,156 INFO train.py line 351 16826] Epoch: [2/100][192/6120] Data 31.515 (19.238) Batch 32.679 (41.934) Remain 7055:18:07 Loss 0.4658 Accuracy 0.8797.
[2021-12-13 21:12:59,251 INFO train.py line 351 16826] Epoch: [2/100][208/6120] Data 38.490 (19.261) Batch 39.095 (41.716) Remain 7018:22:01 Loss 1.5540 Accuracy 0.5034.
[2021-12-13 21:13:37,664 INFO train.py line 351 16826] Epoch: [2/100][224/6120] Data 33.409 (19.019) Batch 38.413 (41.480) Remain 6978:29:34 Loss 0.5077 Accuracy 0.8388.
[2021-12-13 21:14:22,307 INFO train.py line 351 16826] Epoch: [2/100][240/6120] Data 42.286 (19.057) Batch 44.643 (41.691) Remain 7013:47:00 Loss 1.2997 Accuracy 0.6565.
[2021-12-13 21:15:09,050 INFO train.py line 351 16826] Epoch: [2/100][256/6120] Data 41.727 (19.316) Batch 46.743 (42.007) Remain 7066:43:12 Loss 1.2697 Accuracy 0.5569.
[2021-12-13 21:15:54,904 INFO train.py line 351 16826] Epoch: [2/100][272/6120] Data 41.796 (19.313) Batch 45.854 (42.233) Remain 7104:36:16 Loss 0.8947 Accuracy 0.6752.
[2021-12-13 21:16:30,053 INFO train.py line 351 16826] Epoch: [2/100][288/6120] Data 33.568 (19.045) Batch 35.149 (41.839) Remain 7038:12:44 Loss 0.8202 Accuracy 0.6758.
[2021-12-13 21:17:16,419 INFO train.py line 351 16826] Epoch: [2/100][304/6120] Data 45.420 (19.212) Batch 46.366 (42.078) Remain 7078:06:01 Loss 0.6173 Accuracy 0.7093.
[2021-12-13 21:17:54,572 INFO train.py line 351 16826] Epoch: [2/100][320/6120] Data 34.733 (19.113) Batch 38.153 (41.881) Remain 7044:54:31 Loss 0.9983 Accuracy 0.6752.
[2021-12-13 21:18:29,036 INFO train.py line 351 16826] Epoch: [2/100][336/6120] Data 32.459 (19.100) Batch 34.464 (41.528) Remain 6985:18:24 Loss 0.6187 Accuracy 0.7732.
[2021-12-13 21:19:12,491 INFO train.py line 351 16826] Epoch: [2/100][352/6120] Data 43.217 (19.368) Batch 43.455 (41.616) Remain 6999:51:20 Loss 0.5906 Accuracy 0.8427.
[2021-12-13 21:19:56,244 INFO train.py line 351 16826] Epoch: [2/100][368/6120] Data 38.691 (19.346) Batch 43.753 (41.709) Remain 7015:18:09 Loss 1.4083 Accuracy 0.5419.
[2021-12-13 21:20:38,040 INFO train.py line 351 16826] Epoch: [2/100][384/6120] Data 40.229 (19.434) Batch 41.796 (41.712) Remain 7015:43:51 Loss 1.2409 Accuracy 0.6185.
[2021-12-13 21:21:18,428 INFO train.py line 351 16826] Epoch: [2/100][400/6120] Data 37.459 (19.401) Batch 40.388 (41.659) Remain 7006:37:59 Loss 1.2823 Accuracy 0.6470.
[2021-12-13 21:22:05,917 INFO train.py line 351 16826] Epoch: [2/100][416/6120] Data 43.468 (19.510) Batch 47.490 (41.884) Remain 7044:09:41 Loss 1.2504 Accuracy 0.6634.
[2021-12-13 21:22:49,898 INFO train.py line 351 16826] Epoch: [2/100][432/6120] Data 38.986 (19.534) Batch 43.981 (41.961) Remain 7057:02:22 Loss 1.3755 Accuracy 0.5957.
[2021-12-13 21:23:20,202 INFO train.py line 351 16826] Epoch: [2/100][448/6120] Data 29.252 (19.282) Batch 30.304 (41.545) Remain 6986:50:11 Loss 0.7028 Accuracy 0.7649.
[2021-12-13 21:24:05,231 INFO train.py line 351 16826] Epoch: [2/100][464/6120] Data 40.016 (19.299) Batch 45.029 (41.665) Remain 7006:51:26 Loss 1.3580 Accuracy 0.6178.
[2021-12-13 21:24:45,057 INFO train.py line 351 16826] Epoch: [2/100][480/6120] Data 37.326 (19.396) Batch 39.825 (41.604) Remain 6996:21:31 Loss 2.5781 Accuracy 0.3461.
[2021-12-13 21:25:23,192 INFO train.py line 351 16826] Epoch: [2/100][496/6120] Data 36.070 (19.306) Batch 38.135 (41.492) Remain 6977:21:31 Loss 1.3500 Accuracy 0.6274.
[2021-12-13 21:26:04,984 INFO train.py line 351 16826] Epoch: [2/100][512/6120] Data 36.577 (19.272) Batch 41.792 (41.501) Remain 6978:45:01 Loss 0.9441 Accuracy 0.6587.
[2021-12-13 21:26:37,855 INFO train.py line 351 16826] Epoch: [2/100][528/6120] Data 32.144 (19.131) Batch 32.871 (41.240) Remain 6934:35:24 Loss 0.6080 Accuracy 0.8938.
[2021-12-13 21:27:26,624 INFO train.py line 351 16826] Epoch: [2/100][544/6120] Data 47.280 (19.252) Batch 48.769 (41.461) Remain 6971:38:45 Loss 0.7388 Accuracy 0.8303.
[2021-12-13 21:27:54,897 INFO train.py line 351 16826] Epoch: [2/100][560/6120] Data 25.761 (19.152) Batch 28.273 (41.084) Remain 6908:06:22 Loss 1.1526 Accuracy 0.7007.
[2021-12-13 21:28:32,156 INFO train.py line 351 16826] Epoch: [2/100][576/6120] Data 34.134 (19.066) Batch 37.259 (40.978) Remain 6890:03:17 Loss 1.1859 Accuracy 0.6257.
[2021-12-13 21:29:14,632 INFO train.py line 351 16826] Epoch: [2/100][592/6120] Data 37.271 (19.033) Batch 42.476 (41.019) Remain 6896:40:46 Loss 1.3757 Accuracy 0.5366.
[2021-12-13 21:29:51,177 INFO train.py line 351 16826] Epoch: [2/100][608/6120] Data 33.178 (18.990) Batch 36.545 (40.901) Remain 6876:42:12 Loss 1.9837 Accuracy 0.3941.
[2021-12-13 21:30:25,822 INFO train.py line 351 16826] Epoch: [2/100][624/6120] Data 33.612 (18.932) Batch 34.645 (40.740) Remain 6849:33:17 Loss 1.1372 Accuracy 0.6508.
[2021-12-13 21:30:57,269 INFO train.py line 351 16826] Epoch: [2/100][640/6120] Data 29.161 (18.798) Batch 31.447 (40.508) Remain 6810:18:40 Loss 1.1268 Accuracy 0.6372.
[2021-12-13 21:31:30,854 INFO train.py line 351 16826] Epoch: [2/100][656/6120] Data 32.986 (18.797) Batch 33.585 (40.339) Remain 6781:44:37 Loss 0.8890 Accuracy 0.7992.
[2021-12-13 21:32:19,811 INFO train.py line 351 16826] Epoch: [2/100][672/6120] Data 44.456 (18.915) Batch 48.957 (40.544) Remain 6816:03:32 Loss 1.8227 Accuracy 0.3089.
[2021-12-13 21:33:13,365 INFO train.py line 351 16826] Epoch: [2/100][688/6120] Data 52.062 (19.127) Batch 53.554 (40.847) Remain 6866:44:17 Loss 0.8890 Accuracy 0.7143.
[2021-12-13 21:33:59,921 INFO train.py line 351 16826] Epoch: [2/100][704/6120] Data 41.503 (19.095) Batch 46.557 (40.977) Remain 6888:22:15 Loss 1.1162 Accuracy 0.6473.
[2021-12-13 21:34:41,567 INFO train.py line 351 16826] Epoch: [2/100][720/6120] Data 39.623 (19.099) Batch 41.646 (40.992) Remain 6890:41:15 Loss 0.9856 Accuracy 0.7062.
[2021-12-13 21:35:22,134 INFO train.py line 351 16826] Epoch: [2/100][736/6120] Data 37.182 (19.087) Batch 40.567 (40.982) Remain 6888:57:12 Loss 1.0830 Accuracy 0.6719.
[2021-12-13 21:35:57,990 INFO train.py line 351 16826] Epoch: [2/100][752/6120] Data 30.798 (18.986) Batch 35.856 (40.873) Remain 6870:26:16 Loss 0.9164 Accuracy 0.7410.
[2021-12-13 21:36:36,778 INFO train.py line 351 16826] Epoch: [2/100][768/6120] Data 35.549 (18.995) Batch 38.788 (40.830) Remain 6862:57:15 Loss 0.9270 Accuracy 0.7525.
[2021-12-13 21:37:17,723 INFO train.py line 351 16826] Epoch: [2/100][784/6120] Data 37.033 (18.916) Batch 40.945 (40.832) Remain 6863:10:05 Loss 1.2355 Accuracy 0.6582.
[2021-12-13 21:37:53,724 INFO train.py line 351 16826] Epoch: [2/100][800/6120] Data 33.264 (18.924) Batch 36.001 (40.736) Remain 6846:44:50 Loss 0.9960 Accuracy 0.6877.
[2021-12-13 21:38:32,378 INFO train.py line 351 16826] Epoch: [2/100][816/6120] Data 37.057 (18.940) Batch 38.653 (40.695) Remain 6839:42:12 Loss 0.9458 Accuracy 0.7313.
[2021-12-13 21:39:15,749 INFO train.py line 351 16826] Epoch: [2/100][832/6120] Data 42.627 (18.936) Batch 43.371 (40.746) Remain 6848:10:21 Loss 0.4305 Accuracy 0.8187.
[2021-12-13 21:39:56,102 INFO train.py line 351 16826] Epoch: [2/100][848/6120] Data 38.977 (18.947) Batch 40.353 (40.739) Remain 6846:44:42 Loss 0.9155 Accuracy 0.7574.
[2021-12-13 21:40:32,746 INFO train.py line 351 16826] Epoch: [2/100][864/6120] Data 32.240 (18.894) Batch 36.644 (40.663) Remain 6833:49:13 Loss 0.8247 Accuracy 0.7581.
[2021-12-13 21:41:12,601 INFO train.py line 351 16826] Epoch: [2/100][880/6120] Data 34.796 (18.866) Batch 39.855 (40.648) Remain 6831:10:14 Loss 1.7141 Accuracy 0.5691.
[2021-12-13 21:41:46,701 INFO train.py line 351 16826] Epoch: [2/100][896/6120] Data 33.124 (18.796) Batch 34.100 (40.531) Remain 6811:20:25 Loss 0.6987 Accuracy 0.7427.
[2021-12-13 21:42:24,692 INFO train.py line 351 16826] Epoch: [2/100][912/6120] Data 36.899 (18.818) Batch 37.990 (40.487) Remain 6803:40:08 Loss 0.8057 Accuracy 0.7113.
[2021-12-13 21:42:54,492 INFO train.py line 351 16826] Epoch: [2/100][928/6120] Data 26.648 (18.712) Batch 29.801 (40.303) Remain 6772:31:42 Loss 1.6079 Accuracy 0.7567.
[2021-12-13 21:43:33,231 INFO train.py line 351 16826] Epoch: [2/100][944/6120] Data 36.442 (18.696) Batch 38.739 (40.276) Remain 6767:53:47 Loss 1.2509 Accuracy 0.5909.
[2021-12-13 21:44:06,406 INFO train.py line 351 16826] Epoch: [2/100][960/6120] Data 32.783 (18.667) Batch 33.175 (40.158) Remain 6747:49:49 Loss 0.9966 Accuracy 0.8037.
[2021-12-13 21:44:33,764 INFO train.py line 351 16826] Epoch: [2/100][976/6120] Data 26.743 (18.558) Batch 27.358 (39.948) Remain 6712:23:36 Loss 0.4934 Accuracy 0.8319.
[2021-12-13 21:45:09,092 INFO train.py line 351 16826] Epoch: [2/100][992/6120] Data 33.550 (18.544) Batch 35.327 (39.873) Remain 6699:41:39 Loss 0.6095 Accuracy 0.7702.
[2021-12-13 21:45:50,204 INFO train.py line 351 16826] Epoch: [2/100][1008/6120] Data 37.796 (18.582) Batch 41.112 (39.893) Remain 6702:49:18 Loss 1.0683 Accuracy 0.6472.
[2021-12-13 21:46:31,559 INFO train.py line 351 16826] Epoch: [2/100][1024/6120] Data 40.130 (18.619) Batch 41.355 (39.916) Remain 6706:28:55 Loss 0.4284 Accuracy 0.8671.
[2021-12-13 21:47:10,667 INFO train.py line 351 16826] Epoch: [2/100][1040/6120] Data 36.749 (18.620) Batch 39.109 (39.903) Remain 6704:13:04 Loss 1.1104 Accuracy 0.6645.
[2021-12-13 21:47:40,944 INFO train.py line 351 16826] Epoch: [2/100][1056/6120] Data 29.252 (18.546) Batch 30.277 (39.758) Remain 6679:32:05 Loss 1.5790 Accuracy 0.5712.
[2021-12-13 21:48:16,874 INFO train.py line 351 16826] Epoch: [2/100][1072/6120] Data 32.842 (18.523) Batch 35.930 (39.700) Remain 6669:45:35 Loss 1.4694 Accuracy 0.5344.
[2021-12-13 21:48:43,211 INFO train.py line 351 16826] Epoch: [2/100][1088/6120] Data 24.448 (18.433) Batch 26.338 (39.504) Remain 6636:34:12 Loss 1.2241 Accuracy 0.6293.
[2021-12-13 21:49:18,561 INFO train.py line 351 16826] Epoch: [2/100][1104/6120] Data 34.748 (18.401) Batch 35.350 (39.444) Remain 6626:16:53 Loss 0.7545 Accuracy 0.7895.
[2021-12-13 21:50:06,824 INFO train.py line 351 16826] Epoch: [2/100][1120/6120] Data 46.237 (18.469) Batch 48.262 (39.570) Remain 6647:16:08 Loss 1.1240 Accuracy 0.6561.
[2021-12-13 21:50:34,613 INFO train.py line 351 16826] Epoch: [2/100][1136/6120] Data 25.266 (18.385) Batch 27.790 (39.404) Remain 6619:13:20 Loss 1.2450 Accuracy 0.5979.
[2021-12-13 21:51:15,787 INFO train.py line 351 16826] Epoch: [2/100][1152/6120] Data 38.187 (18.403) Batch 41.173 (39.428) Remain 6623:10:31 Loss 1.0783 Accuracy 0.6798.
[2021-12-13 21:51:43,816 INFO train.py line 351 16826] Epoch: [2/100][1168/6120] Data 26.300 (18.336) Batch 28.030 (39.272) Remain 6596:46:17 Loss 1.1489 Accuracy 0.6470.
[2021-12-13 21:52:19,391 INFO train.py line 351 16826] Epoch: [2/100][1184/6120] Data 35.217 (18.334) Batch 35.575 (39.222) Remain 6588:12:16 Loss 1.2607 Accuracy 0.6422.
[2021-12-13 21:53:02,159 INFO train.py line 351 16826] Epoch: [2/100][1200/6120] Data 37.774 (18.370) Batch 42.768 (39.270) Remain 6595:58:14 Loss 1.5092 Accuracy 0.4735.
[2021-12-13 21:53:42,806 INFO train.py line 351 16826] Epoch: [2/100][1216/6120] Data 36.408 (18.379) Batch 40.646 (39.288) Remain 6598:50:20 Loss 1.0111 Accuracy 0.6167.
[2021-12-13 21:54:16,819 INFO train.py line 351 16826] Epoch: [2/100][1232/6120] Data 28.995 (18.311) Batch 34.013 (39.219) Remain 6587:09:36 Loss 1.2884 Accuracy 0.5918.
[2021-12-13 21:54:56,835 INFO train.py line 351 16826] Epoch: [2/100][1248/6120] Data 39.546 (18.341) Batch 40.016 (39.229) Remain 6588:42:02 Loss 1.0895 Accuracy 0.6345.
[2021-12-13 21:55:33,361 INFO train.py line 351 16826] Epoch: [2/100][1264/6120] Data 34.496 (18.362) Batch 36.526 (39.195) Remain 6582:46:46 Loss 1.2347 Accuracy 0.6180.
[2021-12-13 21:56:08,466 INFO train.py line 351 16826] Epoch: [2/100][1280/6120] Data 30.153 (18.343) Batch 35.106 (39.144) Remain 6574:01:12 Loss 0.7245 Accuracy 0.7657.
[2021-12-13 21:56:48,368 INFO train.py line 351 16826] Epoch: [2/100][1296/6120] Data 38.844 (18.364) Batch 39.902 (39.153) Remain 6575:25:02 Loss 1.0160 Accuracy 0.6178.
[2021-12-13 21:57:33,015 INFO train.py line 351 16826] Epoch: [2/100][1312/6120] Data 39.687 (18.435) Batch 44.647 (39.220) Remain 6586:29:37 Loss 1.3041 Accuracy 0.6748.
[2021-12-13 21:58:07,970 INFO train.py line 351 16826] Epoch: [2/100][1328/6120] Data 31.993 (18.422) Batch 34.955 (39.169) Remain 6577:41:24 Loss 1.3923 Accuracy 0.5628.
[2021-12-13 21:58:49,830 INFO train.py line 351 16826] Epoch: [2/100][1344/6120] Data 38.569 (18.457) Batch 41.860 (39.201) Remain 6582:53:41 Loss 0.4743 Accuracy 0.8669.
[2021-12-13 21:59:22,169 INFO train.py line 351 16826] Epoch: [2/100][1360/6120] Data 27.401 (18.410) Batch 32.339 (39.120) Remain 6569:09:50 Loss 1.1439 Accuracy 0.6969.
[2021-12-13 22:00:00,120 INFO train.py line 351 16826] Epoch: [2/100][1376/6120] Data 37.631 (18.417) Batch 37.952 (39.107) Remain 6566:42:30 Loss 1.7851 Accuracy 0.3672.
[2021-12-13 22:00:37,668 INFO train.py line 351 16826] Epoch: [2/100][1392/6120] Data 34.353 (18.401) Batch 37.548 (39.089) Remain 6563:31:32 Loss 1.2230 Accuracy 0.5732.
[2021-12-13 22:01:04,341 INFO train.py line 351 16826] Epoch: [2/100][1408/6120] Data 26.294 (18.347) Batch 26.672 (38.948) Remain 6539:39:39 Loss 0.6618 Accuracy 0.8667.
[2021-12-13 22:01:37,966 INFO train.py line 351 16826] Epoch: [2/100][1424/6120] Data 32.258 (18.331) Batch 33.626 (38.888) Remain 6529:26:51 Loss 1.2074 Accuracy 0.5818.
[2021-12-13 22:02:19,324 INFO train.py line 351 16826] Epoch: [2/100][1440/6120] Data 36.351 (18.338) Batch 41.358 (38.915) Remain 6533:52:57 Loss 2.6652 Accuracy 0.3150.
[2021-12-13 22:03:02,037 INFO train.py line 351 16826] Epoch: [2/100][1456/6120] Data 40.639 (18.358) Batch 42.713 (38.957) Remain 6540:43:00 Loss 1.3834 Accuracy 0.4869.
[2021-12-13 22:03:41,544 INFO train.py line 351 16826] Epoch: [2/100][1472/6120] Data 37.619 (18.379) Batch 39.507 (38.963) Remain 6541:32:47 Loss 1.2480 Accuracy 0.5906.
[2021-12-13 22:04:25,039 INFO train.py line 351 16826] Epoch: [2/100][1488/6120] Data 38.517 (18.375) Batch 43.496 (39.012) Remain 6549:33:20 Loss 0.9482 Accuracy 0.7507.
[2021-12-13 22:05:14,296 INFO train.py line 351 16826] Epoch: [2/100][1504/6120] Data 47.127 (18.454) Batch 49.256 (39.121) Remain 6567:40:43 Loss 1.5276 Accuracy 0.5315.
[2021-12-13 22:05:53,514 INFO train.py line 351 16826] Epoch: [2/100][1520/6120] Data 38.501 (18.460) Batch 39.219 (39.122) Remain 6567:40:41 Loss 0.9373 Accuracy 0.8021.
[2021-12-13 22:06:30,287 INFO train.py line 351 16826] Epoch: [2/100][1536/6120] Data 31.779 (18.431) Batch 36.773 (39.097) Remain 6563:23:46 Loss 1.3418 Accuracy 0.5546.
[2021-12-13 22:07:20,226 INFO train.py line 351 16826] Epoch: [2/100][1552/6120] Data 44.957 (18.473) Batch 49.939 (39.209) Remain 6581:59:08 Loss 1.0774 Accuracy 0.6489.
[2021-12-13 22:08:08,242 INFO train.py line 351 16826] Epoch: [2/100][1568/6120] Data 43.027 (18.514) Batch 48.015 (39.299) Remain 6596:53:44 Loss 0.8773 Accuracy 0.7635.
[2021-12-13 22:08:43,717 INFO train.py line 351 16826] Epoch: [2/100][1584/6120] Data 33.198 (18.485) Batch 35.475 (39.260) Remain 6590:14:13 Loss 1.1348 Accuracy 0.5971.
[2021-12-13 22:09:13,611 INFO train.py line 351 16826] Epoch: [2/100][1600/6120] Data 26.405 (18.444) Batch 29.894 (39.167) Remain 6574:20:29 Loss 1.4061 Accuracy 0.5675.
[2021-12-13 22:09:51,781 INFO train.py line 351 16826] Epoch: [2/100][1616/6120] Data 36.466 (18.462) Batch 38.170 (39.157) Remain 6572:30:38 Loss 0.9271 Accuracy 0.7002.
[2021-12-13 22:10:28,016 INFO train.py line 351 16826] Epoch: [2/100][1632/6120] Data 34.709 (18.470) Batch 36.236 (39.128) Remain 6567:31:47 Loss 1.2768 Accuracy 0.5583.
[2021-12-13 22:11:01,935 INFO train.py line 351 16826] Epoch: [2/100][1648/6120] Data 29.804 (18.442) Batch 33.919 (39.078) Remain 6558:52:00 Loss 0.9550 Accuracy 0.7159.
[2021-12-13 22:11:38,046 INFO train.py line 351 16826] Epoch: [2/100][1664/6120] Data 32.675 (18.411) Batch 36.111 (39.049) Remain 6553:54:18 Loss 1.0016 Accuracy 0.6977.
[2021-12-13 22:12:16,875 INFO train.py line 351 16826] Epoch: [2/100][1680/6120] Data 33.840 (18.389) Batch 38.829 (39.047) Remain 6553:22:46 Loss 0.7613 Accuracy 0.7091.
[2021-12-13 22:12:59,223 INFO train.py line 351 16826] Epoch: [2/100][1696/6120] Data 40.374 (18.405) Batch 42.349 (39.078) Remain 6558:26:01 Loss 0.9644 Accuracy 0.7101.
[2021-12-13 22:13:40,746 INFO train.py line 351 16826] Epoch: [2/100][1712/6120] Data 37.930 (18.430) Batch 41.523 (39.101) Remain 6562:05:40 Loss 1.8555 Accuracy 0.3895.
[2021-12-13 22:14:20,395 INFO train.py line 351 16826] Epoch: [2/100][1728/6120] Data 37.878 (18.436) Batch 39.649 (39.106) Remain 6562:46:19 Loss 0.9480 Accuracy 0.6811.
[2021-12-13 22:14:57,272 INFO train.py line 351 16826] Epoch: [2/100][1744/6120] Data 33.663 (18.426) Batch 36.877 (39.086) Remain 6559:10:00 Loss 1.0133 Accuracy 0.6832.
[2021-12-13 22:15:32,920 INFO train.py line 351 16826] Epoch: [2/100][1760/6120] Data 32.586 (18.405) Batch 35.648 (39.054) Remain 6553:44:53 Loss 1.5583 Accuracy 0.5511.
[2021-12-13 22:16:06,975 INFO train.py line 351 16826] Epoch: [2/100][1776/6120] Data 33.725 (18.387) Batch 34.055 (39.009) Remain 6546:01:01 Loss 1.2822 Accuracy 0.5340.
[2021-12-13 22:16:30,179 INFO train.py line 351 16826] Epoch: [2/100][1792/6120] Data 22.530 (18.320) Batch 23.204 (38.868) Remain 6522:09:47 Loss 0.8626 Accuracy 0.7712.
[2021-12-13 22:17:09,460 INFO train.py line 351 16826] Epoch: [2/100][1808/6120] Data 34.301 (18.315) Batch 39.281 (38.872) Remain 6522:36:14 Loss 1.0665 Accuracy 0.6989.
[2021-12-13 22:17:43,996 INFO train.py line 351 16826] Epoch: [2/100][1824/6120] Data 33.001 (18.343) Batch 34.536 (38.834) Remain 6516:02:58 Loss 1.6266 Accuracy 0.5556.
[2021-12-13 22:18:27,226 INFO train.py line 351 16826] Epoch: [2/100][1840/6120] Data 41.482 (18.360) Batch 43.230 (38.872) Remain 6522:17:29 Loss 1.8271 Accuracy 0.5575.
[2021-12-13 22:19:09,467 INFO train.py line 351 16826] Epoch: [2/100][1856/6120] Data 37.268 (18.356) Batch 42.241 (38.901) Remain 6526:59:28 Loss 0.7131 Accuracy 0.7009.
[2021-12-13 22:19:53,445 INFO train.py line 351 16826] Epoch: [2/100][1872/6120] Data 41.606 (18.369) Batch 43.978 (38.944) Remain 6534:05:55 Loss 1.2815 Accuracy 0.6229.
[2021-12-13 22:20:30,154 INFO train.py line 351 16826] Epoch: [2/100][1888/6120] Data 36.334 (18.360) Batch 36.709 (38.925) Remain 6530:44:48 Loss 1.6339 Accuracy 0.4332.
[2021-12-13 22:21:23,562 INFO train.py line 351 16826] Epoch: [2/100][1904/6120] Data 49.893 (18.407) Batch 53.408 (39.047) Remain 6550:59:32 Loss 1.0776 Accuracy 0.6438.
[2021-12-13 22:22:09,128 INFO train.py line 351 16826] Epoch: [2/100][1920/6120] Data 44.581 (18.451) Batch 45.566 (39.102) Remain 6559:55:55 Loss 0.5156 Accuracy 0.8793.
[2021-12-13 22:22:46,163 INFO train.py line 351 16826] Epoch: [2/100][1936/6120] Data 36.180 (18.465) Batch 37.035 (39.084) Remain 6556:53:34 Loss 0.6092 Accuracy 0.8107.
[2021-12-13 22:23:22,701 INFO train.py line 351 16826] Epoch: [2/100][1952/6120] Data 35.943 (18.471) Batch 36.538 (39.064) Remain 6553:13:04 Loss 0.8760 Accuracy 0.7650.
[2021-12-13 22:24:05,727 INFO train.py line 351 16826] Epoch: [2/100][1968/6120] Data 37.987 (18.457) Batch 43.026 (39.096) Remain 6558:26:56 Loss 0.5880 Accuracy 0.7785.
[2021-12-13 22:24:46,028 INFO train.py line 351 16826] Epoch: [2/100][1984/6120] Data 39.297 (18.484) Batch 40.301 (39.106) Remain 6559:54:20 Loss 0.5090 Accuracy 0.7599.
[2021-12-13 22:25:30,446 INFO train.py line 351 16826] Epoch: [2/100][2000/6120] Data 44.003 (18.516) Batch 44.418 (39.148) Remain 6566:51:39 Loss 1.2127 Accuracy 0.6408.
[2021-12-13 22:26:04,297 INFO train.py line 351 16826] Epoch: [2/100][2016/6120] Data 28.834 (18.457) Batch 33.851 (39.106) Remain 6559:38:08 Loss 2.6858 Accuracy 0.4771.
[2021-12-13 22:26:38,302 INFO train.py line 351 16826] Epoch: [2/100][2032/6120] Data 32.250 (18.449) Batch 34.005 (39.066) Remain 6552:43:27 Loss 1.3192 Accuracy 0.6383.
[2021-12-13 22:27:14,862 INFO train.py line 351 16826] Epoch: [2/100][2048/6120] Data 34.697 (18.430) Batch 36.560 (39.046) Remain 6549:16:00 Loss 1.5226 Accuracy 0.5726.
[2021-12-13 22:27:58,869 INFO train.py line 351 16826] Epoch: [2/100][2064/6120] Data 39.824 (18.452) Batch 44.007 (39.085) Remain 6555:32:35 Loss 1.5901 Accuracy 0.5209.
[2021-12-13 22:28:41,019 INFO train.py line 351 16826] Epoch: [2/100][2080/6120] Data 41.241 (18.462) Batch 42.150 (39.108) Remain 6559:19:29 Loss 1.2549 Accuracy 0.5687.
[2021-12-13 22:29:14,961 INFO train.py line 351 16826] Epoch: [2/100][2096/6120] Data 33.326 (18.470) Batch 33.942 (39.069) Remain 6552:32:11 Loss 1.0461 Accuracy 0.5619.
[2021-12-13 22:29:56,362 INFO train.py line 351 16826] Epoch: [2/100][2112/6120] Data 38.985 (18.470) Batch 41.401 (39.086) Remain 6555:19:32 Loss 1.2330 Accuracy 0.5819.
[2021-12-13 22:30:33,434 INFO train.py line 351 16826] Epoch: [2/100][2128/6120] Data 34.893 (18.466) Batch 37.072 (39.071) Remain 6552:36:42 Loss 1.1406 Accuracy 0.6451.
[2021-12-13 22:31:10,957 INFO train.py line 351 16826] Epoch: [2/100][2144/6120] Data 36.155 (18.460) Batch 37.523 (39.060) Remain 6550:30:01 Loss 1.2349 Accuracy 0.6107.
[2021-12-13 22:31:42,265 INFO train.py line 351 16826] Epoch: [2/100][2160/6120] Data 29.961 (18.437) Batch 31.308 (39.002) Remain 6540:41:48 Loss 1.1702 Accuracy 0.6445.
[2021-12-13 22:32:18,024 INFO train.py line 351 16826] Epoch: [2/100][2176/6120] Data 32.753 (18.427) Batch 35.760 (38.979) Remain 6536:31:30 Loss 1.1927 Accuracy 0.6323.
[2021-12-13 22:32:52,160 INFO train.py line 351 16826] Epoch: [2/100][2192/6120] Data 32.423 (18.417) Batch 34.136 (38.943) Remain 6530:25:26 Loss 1.2943 Accuracy 0.5515.
[2021-12-13 22:33:26,126 INFO train.py line 351 16826] Epoch: [2/100][2208/6120] Data 32.507 (18.397) Batch 33.967 (38.907) Remain 6524:12:13 Loss 0.8705 Accuracy 0.6731.
[2021-12-13 22:34:04,571 INFO train.py line 351 16826] Epoch: [2/100][2224/6120] Data 33.458 (18.401) Batch 38.445 (38.904) Remain 6523:28:22 Loss 1.3891 Accuracy 0.5987.
[2021-12-13 22:34:44,380 INFO train.py line 351 16826] Epoch: [2/100][2240/6120] Data 37.346 (18.401) Batch 39.809 (38.910) Remain 6524:23:02 Loss 0.7867 Accuracy 0.7478.
[2021-12-13 22:35:30,696 INFO train.py line 351 16826] Epoch: [2/100][2256/6120] Data 41.263 (18.414) Batch 46.317 (38.963) Remain 6533:01:06 Loss 1.0973 Accuracy 0.6447.
[2021-12-13 22:36:16,645 INFO train.py line 351 16826] Epoch: [2/100][2272/6120] Data 44.557 (18.414) Batch 45.948 (39.012) Remain 6541:05:35 Loss 0.9631 Accuracy 0.6811.
[2021-12-13 22:36:57,049 INFO train.py line 351 16826] Epoch: [2/100][2288/6120] Data 38.038 (18.418) Batch 40.405 (39.022) Remain 6542:33:10 Loss 1.2927 Accuracy 0.5970.
[2021-12-13 22:37:30,570 INFO train.py line 351 16826] Epoch: [2/100][2304/6120] Data 33.304 (18.405) Batch 33.521 (38.984) Remain 6535:58:29 Loss 0.5554 Accuracy 0.8434.
[2021-12-13 22:38:07,540 INFO train.py line 351 16826] Epoch: [2/100][2320/6120] Data 35.186 (18.387) Batch 36.969 (38.970) Remain 6533:28:22 Loss 0.9680 Accuracy 0.6361.
[2021-12-13 22:38:48,144 INFO train.py line 351 16826] Epoch: [2/100][2336/6120] Data 40.271 (18.384) Batch 40.605 (38.981) Remain 6535:10:37 Loss 0.2823 Accuracy 0.9467.
[2021-12-13 22:39:22,490 INFO train.py line 351 16826] Epoch: [2/100][2352/6120] Data 32.454 (18.362) Batch 34.346 (38.949) Remain 6529:43:03 Loss 1.4147 Accuracy 0.5749.
[2021-12-13 22:39:51,198 INFO train.py line 351 16826] Epoch: [2/100][2368/6120] Data 27.277 (18.347) Batch 28.708 (38.880) Remain 6517:56:37 Loss 0.7877 Accuracy 0.7067.
[2021-12-13 22:40:35,785 INFO train.py line 351 16826] Epoch: [2/100][2384/6120] Data 40.698 (18.359) Batch 44.587 (38.918) Remain 6524:11:30 Loss 1.0304 Accuracy 0.6803.
[2021-12-13 22:41:10,185 INFO train.py line 351 16826] Epoch: [2/100][2400/6120] Data 32.492 (18.333) Batch 34.400 (38.888) Remain 6518:58:09 Loss 1.3056 Accuracy 0.5572.
[2021-12-13 22:41:43,736 INFO train.py line 351 16826] Epoch: [2/100][2416/6120] Data 28.562 (18.294) Batch 33.551 (38.853) Remain 6512:52:16 Loss 0.7148 Accuracy 0.7257.
[2021-12-13 22:42:15,740 INFO train.py line 351 16826] Epoch: [2/100][2432/6120] Data 31.304 (18.261) Batch 32.004 (38.808) Remain 6505:08:44 Loss 0.9973 Accuracy 0.7090.
[2021-12-13 22:42:53,522 INFO train.py line 351 16826] Epoch: [2/100][2448/6120] Data 34.913 (18.261) Batch 37.783 (38.801) Remain 6503:51:00 Loss 1.2859 Accuracy 0.5192.
[2021-12-13 22:43:37,790 INFO train.py line 351 16826] Epoch: [2/100][2464/6120] Data 39.238 (18.265) Batch 44.268 (38.837) Remain 6509:37:41 Loss 1.4431 Accuracy 0.6784.
[2021-12-13 22:44:19,140 INFO train.py line 351 16826] Epoch: [2/100][2480/6120] Data 39.939 (18.277) Batch 41.349 (38.853) Remain 6512:10:21 Loss 0.9963 Accuracy 0.6555.
[2021-12-13 22:44:56,366 INFO train.py line 351 16826] Epoch: [2/100][2496/6120] Data 35.369 (18.272) Batch 37.226 (38.842) Remain 6510:15:07 Loss 0.9591 Accuracy 0.7128.
[2021-12-13 22:45:43,055 INFO train.py line 351 16826] Epoch: [2/100][2512/6120] Data 46.222 (18.324) Batch 46.689 (38.892) Remain 6518:27:22 Loss 0.7155 Accuracy 0.9502.
[2021-12-13 22:46:18,147 INFO train.py line 351 16826] Epoch: [2/100][2528/6120] Data 34.056 (18.336) Batch 35.091 (38.868) Remain 6514:15:04 Loss 0.8444 Accuracy 0.7177.
[2021-12-13 22:47:02,662 INFO train.py line 351 16826] Epoch: [2/100][2544/6120] Data 43.260 (18.356) Batch 44.516 (38.904) Remain 6520:01:52 Loss 0.9027 Accuracy 0.6891.
[2021-12-13 22:47:40,390 INFO train.py line 351 16826] Epoch: [2/100][2560/6120] Data 36.066 (18.355) Batch 37.728 (38.897) Remain 6518:37:36 Loss 0.8780 Accuracy 0.6733.
[2021-12-13 22:48:25,050 INFO train.py line 351 16826] Epoch: [2/100][2576/6120] Data 39.695 (18.373) Batch 44.660 (38.932) Remain 6524:27:10 Loss 1.4312 Accuracy 0.5394.
[2021-12-13 22:49:11,733 INFO train.py line 351 16826] Epoch: [2/100][2592/6120] Data 44.826 (18.389) Batch 46.683 (38.980) Remain 6532:17:51 Loss 1.1768 Accuracy 0.4898.
[2021-12-13 22:49:49,411 INFO train.py line 351 16826] Epoch: [2/100][2608/6120] Data 35.977 (18.383) Batch 37.677 (38.972) Remain 6530:47:05 Loss 0.6828 Accuracy 0.7791.
[2021-12-13 22:50:25,214 INFO train.py line 351 16826] Epoch: [2/100][2624/6120] Data 34.261 (18.361) Batch 35.803 (38.953) Remain 6527:22:25 Loss 0.7175 Accuracy 0.7899.
[2021-12-13 22:50:55,538 INFO train.py line 351 16826] Epoch: [2/100][2640/6120] Data 27.835 (18.343) Batch 30.325 (38.901) Remain 6518:26:16 Loss 0.9187 Accuracy 0.6632.
[2021-12-13 22:51:29,514 INFO train.py line 351 16826] Epoch: [2/100][2656/6120] Data 28.925 (18.314) Batch 33.975 (38.871) Remain 6513:17:37 Loss 1.4837 Accuracy 0.5913.
[2021-12-13 22:52:22,503 INFO train.py line 351 16826] Epoch: [2/100][2672/6120] Data 47.970 (18.339) Batch 52.989 (38.955) Remain 6527:17:11 Loss 0.9919 Accuracy 0.6745.
[2021-12-13 22:53:07,107 INFO train.py line 351 16826] Epoch: [2/100][2688/6120] Data 42.094 (18.362) Batch 44.604 (38.989) Remain 6532:44:48 Loss 1.2648 Accuracy 0.6031.
[2021-12-13 22:53:36,695 INFO train.py line 351 16826] Epoch: [2/100][2704/6120] Data 29.210 (18.342) Batch 29.588 (38.933) Remain 6523:15:10 Loss 0.4793 Accuracy 0.7882.
[2021-12-13 22:54:15,668 INFO train.py line 351 16826] Epoch: [2/100][2720/6120] Data 37.060 (18.353) Batch 38.973 (38.934) Remain 6523:07:09 Loss 1.3549 Accuracy 0.5823.
[2021-12-13 22:54:58,401 INFO train.py line 351 16826] Epoch: [2/100][2736/6120] Data 39.612 (18.361) Batch 42.733 (38.956) Remain 6526:40:07 Loss 1.0643 Accuracy 0.6181.
[2021-12-13 22:55:40,538 INFO train.py line 351 16826] Epoch: [2/100][2752/6120] Data 38.640 (18.371) Batch 42.136 (38.974) Remain 6529:35:36 Loss 1.1401 Accuracy 0.5980.
[2021-12-13 22:56:12,867 INFO train.py line 351 16826] Epoch: [2/100][2768/6120] Data 31.850 (18.344) Batch 32.329 (38.936) Remain 6522:59:06 Loss 0.4340 Accuracy 0.9019.
[2021-12-13 22:56:46,548 INFO train.py line 351 16826] Epoch: [2/100][2784/6120] Data 33.228 (18.343) Batch 33.681 (38.906) Remain 6517:45:09 Loss 0.8037 Accuracy 0.7404.
[2021-12-13 22:57:28,449 INFO train.py line 351 16826] Epoch: [2/100][2800/6120] Data 40.361 (18.367) Batch 41.901 (38.923) Remain 6520:26:48 Loss 1.2505 Accuracy 0.6074.
[2021-12-13 22:57:58,204 INFO train.py line 351 16826] Epoch: [2/100][2816/6120] Data 27.848 (18.343) Batch 29.756 (38.871) Remain 6511:32:55 Loss 1.1262 Accuracy 0.6449.
[2021-12-13 22:58:41,686 INFO train.py line 351 16826] Epoch: [2/100][2832/6120] Data 39.920 (18.359) Batch 43.481 (38.897) Remain 6515:44:22 Loss 1.2096 Accuracy 0.6261.
[2021-12-13 22:59:14,578 INFO train.py line 351 16826] Epoch: [2/100][2848/6120] Data 32.491 (18.337) Batch 32.892 (38.863) Remain 6509:54:55 Loss 0.1987 Accuracy 0.9698.
[2021-12-13 22:59:54,120 INFO train.py line 351 16826] Epoch: [2/100][2864/6120] Data 34.467 (18.319) Batch 39.542 (38.867) Remain 6510:22:41 Loss 1.0343 Accuracy 0.6812.
[2021-12-13 23:00:25,524 INFO train.py line 351 16826] Epoch: [2/100][2880/6120] Data 26.432 (18.287) Batch 31.404 (38.825) Remain 6503:15:37 Loss 0.6691 Accuracy 0.7724.
[2021-12-13 23:01:08,965 INFO train.py line 351 16826] Epoch: [2/100][2896/6120] Data 40.934 (18.294) Batch 43.442 (38.851) Remain 6507:21:35 Loss 0.9562 Accuracy 0.6600.
[2021-12-13 23:01:49,396 INFO train.py line 351 16826] Epoch: [2/100][2912/6120] Data 35.458 (18.284) Batch 40.430 (38.860) Remain 6508:38:26 Loss 1.0972 Accuracy 0.6058.
[2021-12-13 23:02:23,018 INFO train.py line 351 16826] Epoch: [2/100][2928/6120] Data 30.362 (18.254) Batch 33.622 (38.831) Remain 6503:40:28 Loss 1.1657 Accuracy 0.6326.
[2021-12-13 23:02:51,793 INFO train.py line 351 16826] Epoch: [2/100][2944/6120] Data 27.471 (18.216) Batch 28.775 (38.776) Remain 6494:20:56 Loss 1.0391 Accuracy 0.6332.
[2021-12-13 23:03:32,172 INFO train.py line 351 16826] Epoch: [2/100][2960/6120] Data 38.999 (18.222) Batch 40.379 (38.785) Remain 6495:37:39 Loss 1.0989 Accuracy 0.5958.
[2021-12-13 23:04:04,885 INFO train.py line 351 16826] Epoch: [2/100][2976/6120] Data 31.271 (18.197) Batch 32.713 (38.752) Remain 6489:59:16 Loss 1.0266 Accuracy 0.6190.
[2021-12-13 23:04:40,510 INFO train.py line 351 16826] Epoch: [2/100][2992/6120] Data 34.871 (18.207) Batch 35.625 (38.736) Remain 6487:00:53 Loss 0.9346 Accuracy 0.6965.
[2021-12-13 23:05:23,746 INFO train.py line 351 16826] Epoch: [2/100][3008/6120] Data 38.166 (18.207) Batch 43.236 (38.760) Remain 6490:51:05 Loss 1.6906 Accuracy 0.4360.
[2021-12-13 23:06:07,322 INFO train.py line 351 16826] Epoch: [2/100][3024/6120] Data 40.388 (18.220) Batch 43.576 (38.785) Remain 6494:56:47 Loss 0.9268 Accuracy 0.7034.
[2021-12-13 23:06:45,468 INFO train.py line 351 16826] Epoch: [2/100][3040/6120] Data 36.307 (18.210) Batch 38.146 (38.782) Remain 6494:12:38 Loss 1.3689 Accuracy 0.5223.
[2021-12-13 23:07:22,287 INFO train.py line 351 16826] Epoch: [2/100][3056/6120] Data 36.626 (18.210) Batch 36.819 (38.771) Remain 6492:19:05 Loss 1.0776 Accuracy 0.6230.
[2021-12-13 23:08:03,214 INFO train.py line 351 16826] Epoch: [2/100][3072/6120] Data 39.425 (18.215) Batch 40.927 (38.783) Remain 6494:01:31 Loss 0.5592 Accuracy 0.8304.
[2021-12-13 23:08:44,142 INFO train.py line 351 16826] Epoch: [2/100][3088/6120] Data 37.736 (18.217) Batch 40.928 (38.794) Remain 6495:42:50 Loss 1.2311 Accuracy 0.6202.
[2021-12-13 23:09:32,432 INFO train.py line 351 16826] Epoch: [2/100][3104/6120] Data 43.317 (18.238) Batch 48.291 (38.843) Remain 6503:44:18 Loss 1.0105 Accuracy 0.6801.
[2021-12-13 23:10:11,844 INFO train.py line 351 16826] Epoch: [2/100][3120/6120] Data 35.963 (18.240) Batch 39.412 (38.846) Remain 6504:03:15 Loss 0.9658 Accuracy 0.7746.
[2021-12-13 23:10:57,574 INFO train.py line 351 16826] Epoch: [2/100][3136/6120] Data 44.971 (18.259) Batch 45.730 (38.881) Remain 6509:45:44 Loss 2.2242 Accuracy 0.3774.
[2021-12-13 23:11:49,550 INFO train.py line 351 16826] Epoch: [2/100][3152/6120] Data 47.861 (18.287) Batch 51.976 (38.947) Remain 6520:43:08 Loss 1.1829 Accuracy 0.6016.
[2021-12-13 23:12:27,125 INFO train.py line 351 16826] Epoch: [2/100][3168/6120] Data 35.215 (18.286) Batch 37.575 (38.940) Remain 6519:23:08 Loss 0.8972 Accuracy 0.7013.
[2021-12-13 23:13:13,782 INFO train.py line 351 16826] Epoch: [2/100][3184/6120] Data 43.126 (18.303) Batch 46.657 (38.979) Remain 6525:42:16 Loss 1.4181 Accuracy 0.5589.
[2021-12-13 23:13:55,679 INFO train.py line 351 16826] Epoch: [2/100][3200/6120] Data 38.559 (18.311) Batch 41.896 (38.994) Remain 6527:58:23 Loss 1.0770 Accuracy 0.6585.
[2021-12-13 23:14:31,478 INFO train.py line 351 16826] Epoch: [2/100][3216/6120] Data 31.247 (18.294) Batch 35.799 (38.978) Remain 6525:08:22 Loss 1.2659 Accuracy 0.6289.
[2021-12-13 23:15:08,053 INFO train.py line 351 16826] Epoch: [2/100][3232/6120] Data 33.911 (18.262) Batch 36.575 (38.966) Remain 6522:58:29 Loss 1.0019 Accuracy 0.6763.
[2021-12-13 23:16:00,056 INFO train.py line 351 16826] Epoch: [2/100][3248/6120] Data 46.978 (18.287) Batch 52.003 (39.030) Remain 6533:33:08 Loss 1.0969 Accuracy 0.6117.
[2021-12-13 23:16:47,903 INFO train.py line 351 16826] Epoch: [2/100][3264/6120] Data 42.817 (18.289) Batch 47.847 (39.073) Remain 6540:36:48 Loss 1.1701 Accuracy 0.6425.
[2021-12-13 23:17:27,267 INFO train.py line 351 16826] Epoch: [2/100][3280/6120] Data 35.679 (18.289) Batch 39.364 (39.075) Remain 6540:40:37 Loss 1.2428 Accuracy 0.5593.
[2021-12-13 23:18:24,417 INFO train.py line 351 16826] Epoch: [2/100][3296/6120] Data 53.172 (18.334) Batch 57.150 (39.162) Remain 6555:11:25 Loss 0.9863 Accuracy 0.6528.
[2021-12-13 23:19:03,244 INFO train.py line 351 16826] Epoch: [2/100][3312/6120] Data 37.939 (18.351) Batch 38.827 (39.161) Remain 6554:44:42 Loss 1.0924 Accuracy 0.6574.
[2021-12-13 23:19:40,201 INFO train.py line 351 16826] Epoch: [2/100][3328/6120] Data 35.185 (18.349) Batch 36.958 (39.150) Remain 6552:47:53 Loss 1.1916 Accuracy 0.5970.
[2021-12-13 23:20:14,321 INFO train.py line 351 16826] Epoch: [2/100][3344/6120] Data 33.589 (18.352) Batch 34.119 (39.126) Remain 6548:35:42 Loss 2.0623 Accuracy 0.4298.
[2021-12-13 23:20:50,288 INFO train.py line 351 16826] Epoch: [2/100][3360/6120] Data 33.386 (18.342) Batch 35.967 (39.111) Remain 6545:54:12 Loss 1.1606 Accuracy 0.5710.
[2021-12-13 23:21:27,047 INFO train.py line 351 16826] Epoch: [2/100][3376/6120] Data 35.545 (18.340) Batch 36.760 (39.100) Remain 6543:51:52 Loss 0.9138 Accuracy 0.6918.
[2021-12-13 23:22:08,111 INFO train.py line 351 16826] Epoch: [2/100][3392/6120] Data 40.687 (18.343) Batch 41.063 (39.109) Remain 6545:14:26 Loss 1.2723 Accuracy 0.5090.
[2021-12-13 23:22:42,216 INFO train.py line 351 16826] Epoch: [2/100][3408/6120] Data 32.735 (18.338) Batch 34.106 (39.086) Remain 6541:08:07 Loss 1.2713 Accuracy 0.5871.
[2021-12-13 23:23:19,332 INFO train.py line 351 16826] Epoch: [2/100][3424/6120] Data 36.258 (18.339) Batch 37.116 (39.077) Remain 6539:25:17 Loss 1.2101 Accuracy 0.4987.
[2021-12-13 23:24:00,734 INFO train.py line 351 16826] Epoch: [2/100][3440/6120] Data 40.688 (18.333) Batch 41.401 (39.087) Remain 6541:03:26 Loss 1.0327 Accuracy 0.5925.
[2021-12-13 23:24:40,412 INFO train.py line 351 16826] Epoch: [2/100][3456/6120] Data 36.946 (18.317) Batch 39.678 (39.090) Remain 6541:20:28 Loss 1.2963 Accuracy 0.6275.
[2021-12-13 23:25:08,146 INFO train.py line 351 16826] Epoch: [2/100][3472/6120] Data 23.492 (18.285) Batch 27.734 (39.038) Remain 6532:24:36 Loss 1.0659 Accuracy 0.5997.
[2021-12-13 23:25:44,851 INFO train.py line 351 16826] Epoch: [2/100][3488/6120] Data 34.424 (18.269) Batch 36.705 (39.027) Remain 6530:26:46 Loss 1.2330 Accuracy 0.6726.
[2021-12-13 23:26:29,500 INFO train.py line 351 16826] Epoch: [2/100][3504/6120] Data 42.043 (18.292) Batch 44.649 (39.053) Remain 6534:34:05 Loss 1.2905 Accuracy 0.5582.
[2021-12-13 23:27:06,996 INFO train.py line 351 16826] Epoch: [2/100][3520/6120] Data 36.232 (18.283) Batch 37.496 (39.046) Remain 6533:12:38 Loss 1.3586 Accuracy 0.5370.
[2021-12-13 23:27:48,968 INFO train.py line 351 16826] Epoch: [2/100][3536/6120] Data 40.305 (18.281) Batch 41.972 (39.059) Remain 6535:15:09 Loss 1.2884 Accuracy 0.5988.
[2021-12-13 23:28:27,318 INFO train.py line 351 16826] Epoch: [2/100][3552/6120] Data 36.035 (18.279) Batch 38.350 (39.056) Remain 6534:32:41 Loss 1.0179 Accuracy 0.6768.
[2021-12-13 23:29:09,273 INFO train.py line 351 16826] Epoch: [2/100][3568/6120] Data 36.880 (18.270) Batch 41.955 (39.069) Remain 6536:32:47 Loss 0.6997 Accuracy 0.7289.
[2021-12-13 23:29:41,345 INFO train.py line 351 16826] Epoch: [2/100][3584/6120] Data 31.364 (18.265) Batch 32.072 (39.037) Remain 6531:08:49 Loss 0.6229 Accuracy 0.8159.
[2021-12-13 23:30:19,258 INFO train.py line 351 16826] Epoch: [2/100][3600/6120] Data 32.849 (18.249) Batch 37.913 (39.033) Remain 6530:08:14 Loss 1.6203 Accuracy 0.5200.
[2021-12-13 23:30:58,774 INFO train.py line 351 16826] Epoch: [2/100][3616/6120] Data 37.565 (18.245) Batch 39.516 (39.035) Remain 6530:19:17 Loss 0.7915 Accuracy 0.8104.
[2021-12-13 23:31:34,520 INFO train.py line 351 16826] Epoch: [2/100][3632/6120] Data 30.672 (18.236) Batch 35.746 (39.020) Remain 6527:43:28 Loss 1.1046 Accuracy 0.6843.
[2021-12-13 23:32:20,100 INFO train.py line 351 16826] Epoch: [2/100][3648/6120] Data 44.131 (18.259) Batch 45.581 (39.049) Remain 6532:21:52 Loss 0.8369 Accuracy 0.7756.
[2021-12-13 23:32:53,770 INFO train.py line 351 16826] Epoch: [2/100][3664/6120] Data 32.877 (18.253) Batch 33.670 (39.025) Remain 6528:15:42 Loss 1.5833 Accuracy 0.4010.
[2021-12-13 23:33:33,552 INFO train.py line 351 16826] Epoch: [2/100][3680/6120] Data 37.892 (18.252) Batch 39.782 (39.029) Remain 6528:38:18 Loss 1.2006 Accuracy 0.6380.
[2021-12-13 23:34:22,161 INFO train.py line 351 16826] Epoch: [2/100][3696/6120] Data 45.393 (18.268) Batch 48.609 (39.070) Remain 6535:24:09 Loss 1.4326 Accuracy 0.5680.
[2021-12-13 23:35:10,465 INFO train.py line 351 16826] Epoch: [2/100][3712/6120] Data 46.358 (18.271) Batch 48.303 (39.110) Remain 6541:53:09 Loss 0.8588 Accuracy 0.7555.
[2021-12-13 23:35:56,905 INFO train.py line 351 16826] Epoch: [2/100][3728/6120] Data 41.435 (18.282) Batch 46.440 (39.141) Remain 6546:58:27 Loss 1.2301 Accuracy 0.6529.
[2021-12-13 23:36:43,192 INFO train.py line 351 16826] Epoch: [2/100][3744/6120] Data 44.871 (18.308) Batch 46.287 (39.172) Remain 6551:54:28 Loss 1.2214 Accuracy 0.5771.
[2021-12-13 23:37:15,334 INFO train.py line 351 16826] Epoch: [2/100][3760/6120] Data 27.140 (18.286) Batch 32.142 (39.142) Remain 6546:43:50 Loss 0.7645 Accuracy 0.7288.
[2021-12-13 23:37:48,286 INFO train.py line 351 16826] Epoch: [2/100][3776/6120] Data 31.719 (18.278) Batch 32.951 (39.116) Remain 6542:10:09 Loss 0.8114 Accuracy 0.7350.
[2021-12-13 23:38:27,880 INFO train.py line 351 16826] Epoch: [2/100][3792/6120] Data 38.236 (18.286) Batch 39.595 (39.118) Remain 6542:20:00 Loss 1.3679 Accuracy 0.5860.
[2021-12-13 23:39:04,568 INFO train.py line 351 16826] Epoch: [2/100][3808/6120] Data 34.292 (18.287) Batch 36.688 (39.108) Remain 6540:27:07 Loss 1.4518 Accuracy 0.6008.
[2021-12-13 23:39:36,995 INFO train.py line 351 16826] Epoch: [2/100][3824/6120] Data 30.484 (18.280) Batch 32.427 (39.080) Remain 6535:36:12 Loss 1.0919 Accuracy 0.6347.
[2021-12-13 23:40:10,974 INFO train.py line 351 16826] Epoch: [2/100][3840/6120] Data 33.513 (18.261) Batch 33.979 (39.058) Remain 6531:52:32 Loss 0.7346 Accuracy 0.7971.
[2021-12-13 23:40:49,796 INFO train.py line 351 16826] Epoch: [2/100][3856/6120] Data 33.758 (18.254) Batch 38.821 (39.057) Remain 6531:32:14 Loss 1.4153 Accuracy 0.5564.
[2021-12-13 23:41:30,239 INFO train.py line 351 16826] Epoch: [2/100][3872/6120] Data 36.915 (18.258) Batch 40.443 (39.063) Remain 6532:19:16 Loss 1.0380 Accuracy 0.6540.
[2021-12-13 23:42:10,520 INFO train.py line 351 16826] Epoch: [2/100][3888/6120] Data 39.079 (18.252) Batch 40.281 (39.068) Remain 6532:59:08 Loss 0.6845 Accuracy 0.8035.
[2021-12-13 23:42:54,023 INFO train.py line 351 16826] Epoch: [2/100][3904/6120] Data 38.432 (18.249) Batch 43.504 (39.086) Remain 6535:51:06 Loss 2.0490 Accuracy 0.4182.
[2021-12-13 23:43:28,057 INFO train.py line 351 16826] Epoch: [2/100][3920/6120] Data 30.792 (18.249) Batch 34.034 (39.066) Remain 6532:13:46 Loss 0.9956 Accuracy 0.6709.
[2021-12-13 23:44:07,816 INFO train.py line 351 16826] Epoch: [2/100][3936/6120] Data 37.408 (18.250) Batch 39.759 (39.069) Remain 6532:31:38 Loss 0.9888 Accuracy 0.6585.
[2021-12-13 23:44:49,956 INFO train.py line 351 16826] Epoch: [2/100][3952/6120] Data 38.884 (18.254) Batch 42.140 (39.081) Remain 6534:25:58 Loss 1.3426 Accuracy 0.5777.
[2021-12-13 23:45:33,353 INFO train.py line 351 16826] Epoch: [2/100][3968/6120] Data 42.652 (18.266) Batch 43.396 (39.098) Remain 6537:10:06 Loss 1.1465 Accuracy 0.6006.
[2021-12-13 23:46:15,535 INFO train.py line 351 16826] Epoch: [2/100][3984/6120] Data 40.187 (18.290) Batch 42.183 (39.111) Remain 6539:03:56 Loss 0.8866 Accuracy 0.7419.
[2021-12-13 23:46:46,666 INFO train.py line 351 16826] Epoch: [2/100][4000/6120] Data 26.147 (18.270) Batch 31.131 (39.079) Remain 6533:33:18 Loss 1.2635 Accuracy 0.5876.
[2021-12-13 23:47:25,400 INFO train.py line 351 16826] Epoch: [2/100][4016/6120] Data 37.412 (18.280) Batch 38.734 (39.078) Remain 6533:09:05 Loss 0.9308 Accuracy 0.6873.
[2021-12-13 23:48:18,756 INFO train.py line 351 16826] Epoch: [2/100][4032/6120] Data 48.362 (18.312) Batch 53.356 (39.134) Remain 6542:27:02 Loss 1.3120 Accuracy 0.5722.
[2021-12-13 23:48:56,238 INFO train.py line 351 16826] Epoch: [2/100][4048/6120] Data 36.781 (18.307) Batch 37.482 (39.128) Remain 6541:11:05 Loss 0.6653 Accuracy 0.7923.
[2021-12-13 23:49:32,047 INFO train.py line 351 16826] Epoch: [2/100][4064/6120] Data 33.923 (18.299) Batch 35.809 (39.115) Remain 6538:49:36 Loss 1.0349 Accuracy 0.6744.
[2021-12-13 23:50:07,893 INFO train.py line 351 16826] Epoch: [2/100][4080/6120] Data 34.756 (18.288) Batch 35.846 (39.102) Remain 6536:30:37 Loss 0.9580 Accuracy 0.7164.
[2021-12-13 23:50:43,483 INFO train.py line 351 16826] Epoch: [2/100][4096/6120] Data 35.017 (18.289) Batch 35.589 (39.088) Remain 6534:02:35 Loss 0.8657 Accuracy 0.7518.
[2021-12-13 23:51:18,203 INFO train.py line 351 16826] Epoch: [2/100][4112/6120] Data 32.487 (18.282) Batch 34.720 (39.071) Remain 6531:01:42 Loss 0.9362 Accuracy 0.6980.
[2021-12-13 23:51:56,914 INFO train.py line 351 16826] Epoch: [2/100][4128/6120] Data 37.045 (18.283) Batch 38.711 (39.070) Remain 6530:37:18 Loss 0.7886 Accuracy 0.7172.
[2021-12-13 23:52:42,730 INFO train.py line 351 16826] Epoch: [2/100][4144/6120] Data 40.760 (18.291) Batch 45.815 (39.096) Remain 6534:48:05 Loss 0.7882 Accuracy 0.7331.
[2021-12-13 23:53:15,821 INFO train.py line 351 16826] Epoch: [2/100][4160/6120] Data 28.044 (18.267) Batch 33.091 (39.073) Remain 6530:46:04 Loss 1.2612 Accuracy 0.6235.
[2021-12-13 23:54:03,272 INFO train.py line 351 16826] Epoch: [2/100][4176/6120] Data 42.627 (18.277) Batch 47.451 (39.105) Remain 6535:57:34 Loss 1.2577 Accuracy 0.6155.
[2021-12-13 23:54:47,998 INFO train.py line 351 16826] Epoch: [2/100][4192/6120] Data 39.649 (18.280) Batch 44.726 (39.126) Remain 6539:22:19 Loss 1.1569 Accuracy 0.6327.
[2021-12-13 23:55:32,786 INFO train.py line 351 16826] Epoch: [2/100][4208/6120] Data 44.206 (18.293) Batch 44.788 (39.148) Remain 6542:47:46 Loss 0.9967 Accuracy 0.7061.
[2021-12-13 23:56:10,998 INFO train.py line 351 16826] Epoch: [2/100][4224/6120] Data 36.895 (18.295) Batch 38.211 (39.144) Remain 6542:01:45 Loss 1.0949 Accuracy 0.6672.
[2021-12-13 23:56:52,582 INFO train.py line 351 16826] Epoch: [2/100][4240/6120] Data 40.223 (18.302) Batch 41.585 (39.153) Remain 6543:23:40 Loss 1.2217 Accuracy 0.5762.
[2021-12-13 23:57:30,295 INFO train.py line 351 16826] Epoch: [2/100][4256/6120] Data 36.566 (18.301) Batch 37.712 (39.148) Remain 6542:18:54 Loss 1.0721 Accuracy 0.7005.
[2021-12-13 23:58:01,190 INFO train.py line 351 16826] Epoch: [2/100][4272/6120] Data 28.009 (18.295) Batch 30.895 (39.117) Remain 6536:58:32 Loss 1.1275 Accuracy 0.6318.
[2021-12-13 23:58:42,499 INFO train.py line 351 16826] Epoch: [2/100][4288/6120] Data 40.421 (18.297) Batch 41.309 (39.125) Remain 6538:10:06 Loss 0.6266 Accuracy 0.8402.
[2021-12-13 23:59:21,710 INFO train.py line 351 16826] Epoch: [2/100][4304/6120] Data 35.581 (18.294) Batch 39.211 (39.126) Remain 6538:02:53 Loss 0.9394 Accuracy 0.6809.
[2021-12-13 23:59:57,125 INFO train.py line 351 16826] Epoch: [2/100][4320/6120] Data 33.308 (18.291) Batch 35.415 (39.112) Remain 6535:34:40 Loss 1.0233 Accuracy 0.6855.
[2021-12-14 00:00:47,925 INFO train.py line 351 16826] Epoch: [2/100][4336/6120] Data 47.769 (18.311) Batch 50.800 (39.155) Remain 6542:36:40 Loss 1.1541 Accuracy 0.6453.
[2021-12-14 00:01:22,721 INFO train.py line 351 16826] Epoch: [2/100][4352/6120] Data 31.776 (18.295) Batch 34.796 (39.139) Remain 6539:45:33 Loss 1.1042 Accuracy 0.6235.
[2021-12-14 00:02:01,778 INFO train.py line 351 16826] Epoch: [2/100][4368/6120] Data 36.650 (18.297) Batch 39.057 (39.139) Remain 6539:32:06 Loss 1.9601 Accuracy 0.4561.
[2021-12-14 00:02:37,870 INFO train.py line 351 16826] Epoch: [2/100][4384/6120] Data 31.095 (18.289) Batch 36.092 (39.127) Remain 6537:30:13 Loss 0.7923 Accuracy 0.7790.
[2021-12-14 00:03:16,922 INFO train.py line 351 16826] Epoch: [2/100][4400/6120] Data 36.133 (18.287) Batch 39.052 (39.127) Remain 6537:17:01 Loss 1.0054 Accuracy 0.6695.
[2021-12-14 00:03:58,399 INFO train.py line 351 16826] Epoch: [2/100][4416/6120] Data 38.910 (18.292) Batch 41.477 (39.136) Remain 6538:31:57 Loss 1.5328 Accuracy 0.4506.
[2021-12-14 00:04:40,904 INFO train.py line 351 16826] Epoch: [2/100][4432/6120] Data 39.086 (18.295) Batch 42.505 (39.148) Remain 6540:23:25 Loss 0.9365 Accuracy 0.7195.
[2021-12-14 00:05:19,299 INFO train.py line 351 16826] Epoch: [2/100][4448/6120] Data 36.558 (18.296) Batch 38.394 (39.145) Remain 6539:45:49 Loss 0.7957 Accuracy 0.8334.
[2021-12-14 00:05:55,435 INFO train.py line 351 16826] Epoch: [2/100][4464/6120] Data 34.756 (18.288) Batch 36.136 (39.134) Remain 6537:47:17 Loss 0.8810 Accuracy 0.7322.
[2021-12-14 00:06:33,698 INFO train.py line 351 16826] Epoch: [2/100][4480/6120] Data 36.155 (18.294) Batch 38.263 (39.131) Remain 6537:05:39 Loss 0.9545 Accuracy 0.6673.
[2021-12-14 00:07:26,723 INFO train.py line 351 16826] Epoch: [2/100][4496/6120] Data 47.998 (18.307) Batch 53.025 (39.181) Remain 6545:10:47 Loss 1.3574 Accuracy 0.7003.
[2021-12-14 00:08:15,208 INFO train.py line 351 16826] Epoch: [2/100][4512/6120] Data 47.379 (18.333) Batch 48.485 (39.214) Remain 6550:31:02 Loss 0.9472 Accuracy 0.7412.
[2021-12-14 00:08:46,395 INFO train.py line 351 16826] Epoch: [2/100][4528/6120] Data 30.344 (18.318) Batch 31.188 (39.185) Remain 6545:36:19 Loss 1.0447 Accuracy 0.6376.
[2021-12-14 00:09:15,146 INFO train.py line 351 16826] Epoch: [2/100][4544/6120] Data 28.229 (18.307) Batch 28.751 (39.149) Remain 6539:17:38 Loss 0.7324 Accuracy 0.7727.
[2021-12-14 00:09:56,085 INFO train.py line 351 16826] Epoch: [2/100][4560/6120] Data 35.935 (18.315) Batch 40.939 (39.155) Remain 6540:10:09 Loss 1.0129 Accuracy 0.7445.
[2021-12-14 00:10:32,442 INFO train.py line 351 16826] Epoch: [2/100][4576/6120] Data 35.671 (18.311) Batch 36.357 (39.145) Remain 6538:21:40 Loss 1.9674 Accuracy 0.4455.
[2021-12-14 00:11:00,206 INFO train.py line 351 16826] Epoch: [2/100][4592/6120] Data 26.788 (18.287) Batch 27.764 (39.105) Remain 6531:33:50 Loss 1.1369 Accuracy 0.7039.
[2021-12-14 00:11:42,907 INFO train.py line 351 16826] Epoch: [2/100][4608/6120] Data 40.413 (18.299) Batch 42.701 (39.118) Remain 6533:28:32 Loss 1.0387 Accuracy 0.6400.
[2021-12-14 00:12:25,998 INFO train.py line 351 16826] Epoch: [2/100][4624/6120] Data 41.774 (18.310) Batch 43.091 (39.132) Remain 6535:35:51 Loss 1.2922 Accuracy 0.6162.
[2021-12-14 00:12:59,677 INFO train.py line 351 16826] Epoch: [2/100][4640/6120] Data 28.621 (18.298) Batch 33.679 (39.113) Remain 6532:17:01 Loss 1.0674 Accuracy 0.6298.
[2021-12-14 00:13:37,299 INFO train.py line 351 16826] Epoch: [2/100][4656/6120] Data 36.293 (18.305) Batch 37.622 (39.108) Remain 6531:15:15 Loss 1.3373 Accuracy 0.5494.
[2021-12-14 00:14:15,928 INFO train.py line 351 16826] Epoch: [2/100][4672/6120] Data 36.963 (18.309) Batch 38.629 (39.106) Remain 6530:48:23 Loss 1.3550 Accuracy 0.5544.
[2021-12-14 00:14:48,724 INFO train.py line 351 16826] Epoch: [2/100][4688/6120] Data 30.452 (18.300) Batch 32.795 (39.085) Remain 6527:02:09 Loss 1.0357 Accuracy 0.6064.
[2021-12-14 00:15:22,697 INFO train.py line 351 16826] Epoch: [2/100][4704/6120] Data 33.683 (18.297) Batch 33.973 (39.067) Remain 6523:57:32 Loss 1.9396 Accuracy 0.3374.
[2021-12-14 00:16:08,911 INFO train.py line 351 16826] Epoch: [2/100][4720/6120] Data 44.929 (18.304) Batch 46.214 (39.091) Remain 6527:49:51 Loss 0.9941 Accuracy 0.7343.
[2021-12-14 00:16:42,077 INFO train.py line 351 16826] Epoch: [2/100][4736/6120] Data 31.565 (18.297) Batch 33.166 (39.071) Remain 6524:18:51 Loss 0.9078 Accuracy 0.7310.
[2021-12-14 00:17:25,736 INFO train.py line 351 16826] Epoch: [2/100][4752/6120] Data 40.419 (18.297) Batch 43.660 (39.087) Remain 6526:43:12 Loss 1.0394 Accuracy 0.6536.
[2021-12-14 00:18:01,568 INFO train.py line 351 16826] Epoch: [2/100][4768/6120] Data 34.308 (18.291) Batch 35.832 (39.076) Remain 6524:43:21 Loss 0.7677 Accuracy 0.7467.
[2021-12-14 00:18:47,909 INFO train.py line 351 16826] Epoch: [2/100][4784/6120] Data 43.076 (18.299) Batch 46.341 (39.100) Remain 6528:36:21 Loss 1.3968 Accuracy 0.5725.
[2021-12-14 00:19:20,047 INFO train.py line 351 16826] Epoch: [2/100][4800/6120] Data 29.937 (18.281) Batch 32.138 (39.077) Remain 6524:33:26 Loss 0.9227 Accuracy 0.6393.
[2021-12-14 00:19:58,068 INFO train.py line 351 16826] Epoch: [2/100][4816/6120] Data 34.601 (18.288) Batch 38.021 (39.073) Remain 6523:47:52 Loss 1.1179 Accuracy 0.6656.
[2021-12-14 00:20:43,666 INFO train.py line 351 16826] Epoch: [2/100][4832/6120] Data 44.226 (18.303) Batch 45.598 (39.095) Remain 6527:13:51 Loss 0.7430 Accuracy 0.8325.
[2021-12-14 00:21:17,584 INFO train.py line 351 16826] Epoch: [2/100][4848/6120] Data 28.935 (18.294) Batch 33.919 (39.078) Remain 6524:12:18 Loss 1.1553 Accuracy 0.6244.
[2021-12-14 00:21:45,763 INFO train.py line 351 16826] Epoch: [2/100][4864/6120] Data 23.162 (18.279) Batch 28.179 (39.042) Remain 6518:02:45 Loss 1.2597 Accuracy 0.5816.
[2021-12-14 00:22:26,721 INFO train.py line 351 16826] Epoch: [2/100][4880/6120] Data 35.891 (18.271) Batch 40.958 (39.048) Remain 6518:55:15 Loss 0.9222 Accuracy 0.6984.
[2021-12-14 00:22:58,537 INFO train.py line 351 16826] Epoch: [2/100][4896/6120] Data 27.093 (18.257) Batch 31.816 (39.025) Remain 6514:48:05 Loss 1.3194 Accuracy 0.5143.
[2021-12-14 00:23:38,902 INFO train.py line 351 16826] Epoch: [2/100][4912/6120] Data 39.462 (18.264) Batch 40.365 (39.029) Remain 6515:21:25 Loss 1.1957 Accuracy 0.5125.
[2021-12-14 00:24:11,587 INFO train.py line 351 16826] Epoch: [2/100][4928/6120] Data 30.780 (18.253) Batch 32.685 (39.009) Remain 6511:44:42 Loss 0.7991 Accuracy 0.7987.
[2021-12-14 00:24:46,227 INFO train.py line 351 16826] Epoch: [2/100][4944/6120] Data 31.780 (18.251) Batch 34.640 (38.994) Remain 6509:12:41 Loss 0.8846 Accuracy 0.7326.
[2021-12-14 00:25:21,647 INFO train.py line 351 16826] Epoch: [2/100][4960/6120] Data 34.846 (18.249) Batch 35.421 (38.983) Remain 6507:06:49 Loss 0.8751 Accuracy 0.7290.
[2021-12-14 00:25:58,355 INFO train.py line 351 16826] Epoch: [2/100][4976/6120] Data 35.130 (18.251) Batch 36.708 (38.976) Remain 6505:43:10 Loss 0.7889 Accuracy 0.7920.
[2021-12-14 00:26:36,930 INFO train.py line 351 16826] Epoch: [2/100][4992/6120] Data 37.370 (18.263) Batch 38.575 (38.974) Remain 6505:19:54 Loss 1.3166 Accuracy 0.5956.
[2021-12-14 00:27:26,122 INFO train.py line 351 16826] Epoch: [2/100][5008/6120] Data 45.211 (18.274) Batch 49.193 (39.007) Remain 6510:36:27 Loss 0.7304 Accuracy 0.7915.
[2021-12-14 00:28:04,859 INFO train.py line 351 16826] Epoch: [2/100][5024/6120] Data 37.981 (18.280) Batch 38.737 (39.006) Remain 6510:17:25 Loss 1.7065 Accuracy 0.4059.
[2021-12-14 00:28:57,549 INFO train.py line 351 16826] Epoch: [2/100][5040/6120] Data 47.614 (18.293) Batch 52.691 (39.050) Remain 6517:22:03 Loss 1.0080 Accuracy 0.7288.
[2021-12-14 00:29:32,806 INFO train.py line 351 16826] Epoch: [2/100][5056/6120] Data 33.167 (18.285) Batch 35.257 (39.038) Remain 6515:11:28 Loss 1.0796 Accuracy 0.6605.
[2021-12-14 00:30:17,656 INFO train.py line 351 16826] Epoch: [2/100][5072/6120] Data 39.780 (18.286) Batch 44.850 (39.056) Remain 6518:04:39 Loss 0.9334 Accuracy 0.7341.
[2021-12-14 00:31:00,114 INFO train.py line 351 16826] Epoch: [2/100][5088/6120] Data 39.808 (18.284) Batch 42.458 (39.067) Remain 6519:41:21 Loss 1.0303 Accuracy 0.6781.
[2021-12-14 00:31:35,910 INFO train.py line 351 16826] Epoch: [2/100][5104/6120] Data 31.471 (18.280) Batch 35.797 (39.056) Remain 6517:48:18 Loss 1.2765 Accuracy 0.6390.
[2021-12-14 00:32:12,493 INFO train.py line 351 16826] Epoch: [2/100][5120/6120] Data 33.921 (18.277) Batch 36.582 (39.049) Remain 6516:20:28 Loss 1.3329 Accuracy 0.6488.
[2021-12-14 00:32:58,555 INFO train.py line 351 16826] Epoch: [2/100][5136/6120] Data 42.996 (18.286) Batch 46.062 (39.070) Remain 6519:48:49 Loss 1.4298 Accuracy 0.5353.
[2021-12-14 00:33:38,879 INFO train.py line 351 16826] Epoch: [2/100][5152/6120] Data 37.107 (18.289) Batch 40.324 (39.074) Remain 6520:17:22 Loss 1.0582 Accuracy 0.6320.
[2021-12-14 00:34:14,380 INFO train.py line 351 16826] Epoch: [2/100][5168/6120] Data 34.889 (18.288) Batch 35.501 (39.063) Remain 6518:16:12 Loss 1.0187 Accuracy 0.5740.
[2021-12-14 00:35:05,263 INFO train.py line 351 16826] Epoch: [2/100][5184/6120] Data 48.955 (18.305) Batch 50.883 (39.100) Remain 6524:11:01 Loss 1.0301 Accuracy 0.6733.
[2021-12-14 00:35:45,736 INFO train.py line 351 16826] Epoch: [2/100][5200/6120] Data 40.242 (18.302) Batch 40.472 (39.104) Remain 6524:42:52 Loss 0.6847 Accuracy 0.8089.
[2021-12-14 00:36:38,776 INFO train.py line 351 16826] Epoch: [2/100][5216/6120] Data 50.726 (18.331) Batch 53.041 (39.147) Remain 6531:40:25 Loss 0.8581 Accuracy 0.6757.
[2021-12-14 00:37:21,386 INFO train.py line 351 16826] Epoch: [2/100][5232/6120] Data 41.963 (18.337) Batch 42.610 (39.157) Remain 6533:16:00 Loss 0.6692 Accuracy 0.7637.
[2021-12-14 00:37:48,724 INFO train.py line 351 16826] Epoch: [2/100][5248/6120] Data 26.106 (18.316) Batch 27.338 (39.121) Remain 6527:04:50 Loss 0.9357 Accuracy 0.6374.
[2021-12-14 00:38:30,900 INFO train.py line 351 16826] Epoch: [2/100][5264/6120] Data 38.824 (18.322) Batch 42.176 (39.131) Remain 6528:27:21 Loss 1.1872 Accuracy 0.6678.
[2021-12-14 00:39:06,782 INFO train.py line 351 16826] Epoch: [2/100][5280/6120] Data 33.881 (18.319) Batch 35.882 (39.121) Remain 6526:38:23 Loss 1.0787 Accuracy 0.6472.
[2021-12-14 00:39:49,790 INFO train.py line 351 16826] Epoch: [2/100][5296/6120] Data 39.742 (18.329) Batch 43.008 (39.132) Remain 6528:25:30 Loss 1.3943 Accuracy 0.5582.
[2021-12-14 00:40:23,370 INFO train.py line 351 16826] Epoch: [2/100][5312/6120] Data 30.396 (18.321) Batch 33.580 (39.116) Remain 6525:27:40 Loss 0.8943 Accuracy 0.7613.
[2021-12-14 00:41:07,675 INFO train.py line 351 16826] Epoch: [2/100][5328/6120] Data 42.562 (18.327) Batch 44.305 (39.131) Remain 6527:53:12 Loss 0.6264 Accuracy 0.8098.
[2021-12-14 00:41:50,772 INFO train.py line 351 16826] Epoch: [2/100][5344/6120] Data 42.559 (18.332) Batch 43.097 (39.143) Remain 6529:41:36 Loss 0.8658 Accuracy 0.7599.
[2021-12-14 00:42:29,705 INFO train.py line 351 16826] Epoch: [2/100][5360/6120] Data 33.932 (18.318) Batch 38.933 (39.143) Remain 6529:24:54 Loss 1.3636 Accuracy 0.5443.
[2021-12-14 00:43:09,934 INFO train.py line 351 16826] Epoch: [2/100][5376/6120] Data 39.412 (18.323) Batch 40.228 (39.146) Remain 6529:46:48 Loss 0.6734 Accuracy 0.8321.
[2021-12-14 00:43:50,400 INFO train.py line 351 16826] Epoch: [2/100][5392/6120] Data 39.021 (18.328) Batch 40.466 (39.150) Remain 6530:15:35 Loss 0.8139 Accuracy 0.6996.
[2021-12-14 00:44:27,174 INFO train.py line 351 16826] Epoch: [2/100][5408/6120] Data 34.894 (18.319) Batch 36.774 (39.143) Remain 6528:54:48 Loss 1.0624 Accuracy 0.6274.
[2021-12-14 00:45:08,224 INFO train.py line 351 16826] Epoch: [2/100][5424/6120] Data 37.123 (18.318) Batch 41.050 (39.148) Remain 6529:40:39 Loss 0.8778 Accuracy 0.7284.
[2021-12-14 00:45:44,832 INFO train.py line 351 16826] Epoch: [2/100][5440/6120] Data 36.229 (18.318) Batch 36.609 (39.141) Remain 6528:15:28 Loss 0.9484 Accuracy 0.7136.
[2021-12-14 00:46:15,551 INFO train.py line 351 16826] Epoch: [2/100][5456/6120] Data 29.652 (18.302) Batch 30.719 (39.116) Remain 6523:57:52 Loss 0.6390 Accuracy 0.8011.
[2021-12-14 00:47:04,553 INFO train.py line 351 16826] Epoch: [2/100][5472/6120] Data 44.001 (18.314) Batch 49.002 (39.145) Remain 6528:36:41 Loss 0.5119 Accuracy 0.8136.
[2021-12-14 00:47:41,209 INFO train.py line 351 16826] Epoch: [2/100][5488/6120] Data 33.652 (18.307) Batch 36.656 (39.138) Remain 6527:13:39 Loss 1.1573 Accuracy 0.6533.
[2021-12-14 00:48:22,687 INFO train.py line 351 16826] Epoch: [2/100][5504/6120] Data 40.369 (18.325) Batch 41.478 (39.145) Remain 6528:11:17 Loss 1.1506 Accuracy 0.5708.
[2021-12-14 00:48:59,023 INFO train.py line 351 16826] Epoch: [2/100][5520/6120] Data 35.314 (18.315) Batch 36.336 (39.136) Remain 6526:39:23 Loss 0.7087 Accuracy 0.7763.
[2021-12-14 00:49:38,159 INFO train.py line 351 16826] Epoch: [2/100][5536/6120] Data 34.095 (18.315) Batch 39.136 (39.136) Remain 6526:28:56 Loss 1.0546 Accuracy 0.6537.
[2021-12-14 00:50:19,281 INFO train.py line 351 16826] Epoch: [2/100][5552/6120] Data 40.090 (18.322) Batch 41.122 (39.142) Remain 6527:15:45 Loss 0.4753 Accuracy 0.8985.
[2021-12-14 00:51:05,312 INFO train.py line 351 16826] Epoch: [2/100][5568/6120] Data 42.292 (18.332) Batch 46.031 (39.162) Remain 6530:23:22 Loss 0.5903 Accuracy 0.8404.
[2021-12-14 00:51:42,704 INFO train.py line 351 16826] Epoch: [2/100][5584/6120] Data 32.322 (18.319) Batch 37.392 (39.157) Remain 6529:22:12 Loss 1.0174 Accuracy 0.6629.
[2021-12-14 00:52:19,517 INFO train.py line 351 16826] Epoch: [2/100][5600/6120] Data 33.404 (18.309) Batch 36.812 (39.150) Remain 6528:04:44 Loss 1.0569 Accuracy 0.6898.
[2021-12-14 00:53:09,422 INFO train.py line 351 16826] Epoch: [2/100][5616/6120] Data 44.847 (18.328) Batch 49.905 (39.181) Remain 6533:00:51 Loss 1.4291 Accuracy 0.5641.
[2021-12-14 00:53:44,116 INFO train.py line 351 16826] Epoch: [2/100][5632/6120] Data 32.848 (18.317) Batch 34.694 (39.168) Remain 6530:42:53 Loss 0.8316 Accuracy 0.7407.
[2021-12-14 00:54:22,959 INFO train.py line 351 16826] Epoch: [2/100][5648/6120] Data 33.846 (18.314) Batch 38.843 (39.167) Remain 6530:23:13 Loss 0.7647 Accuracy 0.7376.
[2021-12-14 00:54:55,251 INFO train.py line 351 16826] Epoch: [2/100][5664/6120] Data 31.564 (18.315) Batch 32.292 (39.148) Remain 6526:58:29 Loss 1.1288 Accuracy 0.6318.
[2021-12-14 00:55:39,177 INFO train.py line 351 16826] Epoch: [2/100][5680/6120] Data 39.251 (18.320) Batch 43.926 (39.161) Remain 6529:02:41 Loss 1.1043 Accuracy 0.6416.
[2021-12-14 00:56:18,075 INFO train.py line 351 16826] Epoch: [2/100][5696/6120] Data 37.591 (18.322) Batch 38.899 (39.160) Remain 6528:44:52 Loss 0.5109 Accuracy 0.8608.
[2021-12-14 00:56:59,409 INFO train.py line 351 16826] Epoch: [2/100][5712/6120] Data 39.450 (18.323) Batch 41.333 (39.167) Remain 6529:35:18 Loss 0.8780 Accuracy 0.7147.
[2021-12-14 00:57:42,641 INFO train.py line 351 16826] Epoch: [2/100][5728/6120] Data 41.901 (18.326) Batch 43.232 (39.178) Remain 6531:18:27 Loss 1.0409 Accuracy 0.6356.
[2021-12-14 00:58:37,018 INFO train.py line 351 16826] Epoch: [2/100][5744/6120] Data 49.354 (18.341) Batch 54.377 (39.220) Remain 6538:11:28 Loss 1.3254 Accuracy 0.6317.
[2021-12-14 00:59:12,233 INFO train.py line 351 16826] Epoch: [2/100][5760/6120] Data 32.356 (18.331) Batch 35.215 (39.209) Remain 6536:09:44 Loss 0.6622 Accuracy 0.7736.
[2021-12-14 00:59:59,774 INFO train.py line 351 16826] Epoch: [2/100][5776/6120] Data 42.512 (18.343) Batch 47.541 (39.232) Remain 6539:50:08 Loss 1.4933 Accuracy 0.6556.
[2021-12-14 01:00:33,663 INFO train.py line 351 16826] Epoch: [2/100][5792/6120] Data 32.855 (18.341) Batch 33.889 (39.217) Remain 6537:12:02 Loss 0.7582 Accuracy 0.7000.
[2021-12-14 01:01:10,311 INFO train.py line 351 16826] Epoch: [2/100][5808/6120] Data 33.318 (18.335) Batch 36.648 (39.210) Remain 6535:50:47 Loss 0.8516 Accuracy 0.7389.
[2021-12-14 01:01:41,045 INFO train.py line 351 16826] Epoch: [2/100][5824/6120] Data 28.688 (18.331) Batch 30.734 (39.187) Remain 6531:47:26 Loss 0.7688 Accuracy 0.7282.
[2021-12-14 01:02:05,942 INFO train.py line 351 16826] Epoch: [2/100][5840/6120] Data 23.843 (18.307) Batch 24.897 (39.148) Remain 6525:05:27 Loss 0.8220 Accuracy 0.7494.
[2021-12-14 01:02:44,354 INFO train.py line 351 16826] Epoch: [2/100][5856/6120] Data 36.117 (18.311) Batch 38.412 (39.146) Remain 6524:34:54 Loss 0.9726 Accuracy 0.6909.
[2021-12-14 01:03:22,060 INFO train.py line 351 16826] Epoch: [2/100][5872/6120] Data 36.502 (18.304) Batch 37.706 (39.142) Remain 6523:45:14 Loss 0.9831 Accuracy 0.6366.
[2021-12-14 01:04:00,568 INFO train.py line 351 16826] Epoch: [2/100][5888/6120] Data 36.878 (18.300) Batch 38.508 (39.140) Remain 6523:17:34 Loss 0.6649 Accuracy 0.7650.
[2021-12-14 01:04:38,406 INFO train.py line 351 16826] Epoch: [2/100][5904/6120] Data 36.155 (18.298) Batch 37.838 (39.137) Remain 6522:31:51 Loss 0.7185 Accuracy 0.7663.
[2021-12-14 01:05:19,360 INFO train.py line 351 16826] Epoch: [2/100][5920/6120] Data 39.103 (18.295) Batch 40.954 (39.142) Remain 6523:10:31 Loss 0.8011 Accuracy 0.6879.
[2021-12-14 01:05:47,145 INFO train.py line 351 16826] Epoch: [2/100][5936/6120] Data 24.462 (18.273) Batch 27.785 (39.111) Remain 6517:54:00 Loss 0.9762 Accuracy 0.6662.
[2021-12-14 01:06:24,594 INFO train.py line 351 16826] Epoch: [2/100][5952/6120] Data 35.997 (18.276) Batch 37.449 (39.107) Remain 6516:58:53 Loss 0.6932 Accuracy 0.7570.
[2021-12-14 01:07:08,210 INFO train.py line 351 16826] Epoch: [2/100][5968/6120] Data 40.073 (18.287) Batch 43.616 (39.119) Remain 6518:49:20 Loss 0.9457 Accuracy 0.6758.
[2021-12-14 01:07:55,676 INFO train.py line 351 16826] Epoch: [2/100][5984/6120] Data 42.872 (18.288) Batch 47.467 (39.141) Remain 6522:22:04 Loss 1.1603 Accuracy 0.6019.
[2021-12-14 01:08:38,520 INFO train.py line 351 16826] Epoch: [2/100][6000/6120] Data 37.876 (18.290) Batch 42.843 (39.151) Remain 6523:50:20 Loss 1.1769 Accuracy 0.6860.
[2021-12-14 01:09:25,150 INFO train.py line 351 16826] Epoch: [2/100][6016/6120] Data 41.570 (18.283) Batch 46.630 (39.171) Remain 6526:58:46 Loss 1.0407 Accuracy 0.6668.
[2021-12-14 01:09:59,369 INFO train.py line 351 16826] Epoch: [2/100][6032/6120] Data 31.948 (18.278) Batch 34.220 (39.158) Remain 6524:37:02 Loss 0.7716 Accuracy 0.7426.
[2021-12-14 01:10:34,853 INFO train.py line 351 16826] Epoch: [2/100][6048/6120] Data 33.055 (18.272) Batch 35.484 (39.148) Remain 6522:49:26 Loss 0.7913 Accuracy 0.7392.
[2021-12-14 01:11:18,052 INFO train.py line 351 16826] Epoch: [2/100][6064/6120] Data 40.927 (18.281) Batch 43.199 (39.159) Remain 6524:25:51 Loss 0.9053 Accuracy 0.6674.
[2021-12-14 01:11:56,902 INFO train.py line 351 16826] Epoch: [2/100][6080/6120] Data 38.220 (18.284) Batch 38.850 (39.158) Remain 6524:07:16 Loss 0.6754 Accuracy 0.8365.
[2021-12-14 01:12:25,588 INFO train.py line 351 16826] Epoch: [2/100][6096/6120] Data 23.652 (18.266) Batch 28.686 (39.130) Remain 6519:22:05 Loss 0.9364 Accuracy 0.6976.
[2021-12-14 01:13:07,074 INFO train.py line 351 16826] Epoch: [2/100][6112/6120] Data 39.505 (18.277) Batch 41.486 (39.136) Remain 6520:13:18 Loss 0.8562 Accuracy 0.6555.
[2021-12-14 01:13:18,373 INFO train.py line 364 16826] Train result at epoch [2/100]: mIoU/mAcc/allAcc 0.2708/0.3427/0.6526.
[2021-12-14 01:13:18,374 INFO train.py line 370 16826] >>>>>>>>>>>>>>>> Start Evaluation >>>>>>>>>>>>>>>>
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-12-14 01:13:21,693 INFO train.py line 425 16826] Test: [1/68] Data 1.212 (1.212) Batch 3.317 (3.317) Loss 1.0929 (1.0929) Accuracy 0.7256.
[2021-12-14 01:13:23,206 INFO train.py line 425 16826] Test: [2/68] Data 0.000 (0.606) Batch 1.513 (2.415) Loss 0.9301 (1.0154) Accuracy 0.7164.
[2021-12-14 01:13:26,764 INFO train.py line 425 16826] Test: [3/68] Data 0.000 (0.404) Batch 3.558 (2.796) Loss 1.2426 (1.1138) Accuracy 0.6595.
[2021-12-14 01:13:38,586 INFO train.py line 425 16826] Test: [4/68] Data 0.000 (0.303) Batch 11.822 (5.052) Loss 1.1252 (1.1189) Accuracy 0.6861.
[2021-12-14 01:13:45,893 INFO train.py line 425 16826] Test: [5/68] Data 0.000 (0.243) Batch 7.308 (5.503) Loss 1.1502 (1.1271) Accuracy 0.6458.
[2021-12-14 01:14:34,710 INFO train.py line 425 16826] Test: [6/68] Data 0.000 (0.202) Batch 48.816 (12.722) Loss 13.2498 (5.5322) Accuracy 0.4557.
[2021-12-14 01:14:39,194 INFO train.py line 425 16826] Test: [7/68] Data 0.000 (0.173) Batch 4.484 (11.545) Loss 1.2850 (5.0540) Accuracy 0.7559.
[2021-12-14 01:14:41,280 INFO train.py line 425 16826] Test: [8/68] Data 0.000 (0.152) Batch 2.086 (10.363) Loss 0.4591 (4.7369) Accuracy 0.9218.
[2021-12-14 01:14:43,332 INFO train.py line 425 16826] Test: [9/68] Data 0.000 (0.135) Batch 2.053 (9.440) Loss 0.4239 (4.4602) Accuracy 0.9150.
[2021-12-14 01:14:48,459 INFO train.py line 425 16826] Test: [10/68] Data 0.000 (0.121) Batch 5.127 (9.008) Loss 2.1667 (4.2410) Accuracy 0.6769.
[2021-12-14 01:14:50,319 INFO train.py line 425 16826] Test: [11/68] Data 0.000 (0.110) Batch 1.860 (8.358) Loss 0.9702 (4.0709) Accuracy 0.7426.
[2021-12-14 01:14:55,747 INFO train.py line 425 16826] Test: [12/68] Data 0.000 (0.101) Batch 5.428 (8.114) Loss 3.1738 (3.9943) Accuracy 0.6172.
[2021-12-14 01:16:16,547 INFO train.py line 425 16826] Test: [13/68] Data 0.000 (0.093) Batch 80.800 (13.705) Loss 25.3327 (8.7274) Accuracy 0.3454.
[2021-12-14 01:16:21,531 INFO train.py line 425 16826] Test: [14/68] Data 0.000 (0.087) Batch 4.984 (13.083) Loss 1.1988 (8.2787) Accuracy 0.7711.
[2021-12-14 01:16:24,902 INFO train.py line 425 16826] Test: [15/68] Data 0.000 (0.081) Batch 3.370 (12.435) Loss 1.1149 (7.9489) Accuracy 0.7652.
[2021-12-14 01:16:57,873 INFO train.py line 425 16826] Test: [16/68] Data 0.000 (0.076) Batch 32.972 (13.719) Loss 8.5430 (8.0152) Accuracy 0.4978.
[2021-12-14 01:17:01,686 INFO train.py line 425 16826] Test: [17/68] Data 0.000 (0.072) Batch 3.813 (13.136) Loss 1.4967 (7.7421) Accuracy 0.6838.
[2021-12-14 01:17:06,182 INFO train.py line 425 16826] Test: [18/68] Data 0.000 (0.068) Batch 4.496 (12.656) Loss 1.9608 (7.4896) Accuracy 0.6618.
[2021-12-14 01:17:07,161 INFO train.py line 425 16826] Test: [19/68] Data 0.000 (0.064) Batch 0.979 (12.041) Loss 0.4119 (7.3596) Accuracy 0.9150.
[2021-12-14 01:17:11,700 INFO train.py line 425 16826] Test: [20/68] Data 0.000 (0.061) Batch 4.539 (11.666) Loss 0.8031 (7.0885) Accuracy 0.7853.
[2021-12-14 01:17:15,478 INFO train.py line 425 16826] Test: [21/68] Data 0.000 (0.058) Batch 3.778 (11.291) Loss 0.5430 (6.8519) Accuracy 0.8148.
[2021-12-14 01:17:17,981 INFO train.py line 425 16826] Test: [22/68] Data 0.000 (0.055) Batch 2.503 (10.891) Loss 1.3837 (6.6981) Accuracy 0.5017.
[2021-12-14 01:17:20,144 INFO train.py line 425 16826] Test: [23/68] Data 0.000 (0.053) Batch 2.164 (10.512) Loss 1.4269 (6.5650) Accuracy 0.4664.
[2021-12-14 01:17:22,883 INFO train.py line 425 16826] Test: [24/68] Data 0.000 (0.051) Batch 2.739 (10.188) Loss 1.4079 (6.4210) Accuracy 0.5014.
[2021-12-14 01:17:25,535 INFO train.py line 425 16826] Test: [25/68] Data 0.000 (0.049) Batch 2.652 (9.886) Loss 1.3700 (6.2860) Accuracy 0.4801.
[2021-12-14 01:17:29,314 INFO train.py line 425 16826] Test: [26/68] Data 0.000 (0.047) Batch 3.779 (9.651) Loss 1.2628 (6.1282) Accuracy 0.5362.
[2021-12-14 01:17:34,389 INFO train.py line 425 16826] Test: [27/68] Data 0.000 (0.045) Batch 5.075 (9.482) Loss 1.4099 (5.9607) Accuracy 0.4959.
[2021-12-14 01:17:40,133 INFO train.py line 425 16826] Test: [28/68] Data 0.000 (0.044) Batch 5.744 (9.348) Loss 1.4324 (5.7951) Accuracy 0.5296.
[2021-12-14 01:17:42,157 INFO train.py line 425 16826] Test: [29/68] Data 0.000 (0.042) Batch 2.024 (9.096) Loss 0.8874 (5.6954) Accuracy 0.7351.
[2021-12-14 01:17:45,425 INFO train.py line 425 16826] Test: [30/68] Data 0.000 (0.041) Batch 3.268 (8.902) Loss 1.3889 (5.5849) Accuracy 0.5379.
[2021-12-14 01:17:50,768 INFO train.py line 425 16826] Test: [31/68] Data 0.000 (0.039) Batch 5.343 (8.787) Loss 1.1372 (5.4405) Accuracy 0.6672.
[2021-12-14 01:17:59,327 INFO train.py line 425 16826] Test: [32/68] Data 0.000 (0.038) Batch 8.559 (8.780) Loss 1.0964 (5.2659) Accuracy 0.6694.
[2021-12-14 01:18:02,034 INFO train.py line 425 16826] Test: [33/68] Data 0.000 (0.037) Batch 2.707 (8.596) Loss 1.3659 (5.1836) Accuracy 0.4991.
[2021-12-14 01:18:03,106 INFO train.py line 425 16826] Test: [34/68] Data 0.000 (0.036) Batch 1.072 (8.374) Loss 0.8481 (5.1300) Accuracy 0.6938.
[2021-12-14 01:18:15,875 INFO train.py line 425 16826] Test: [35/68] Data 0.000 (0.035) Batch 12.769 (8.500) Loss 0.8743 (4.9373) Accuracy 0.7167.
[2021-12-14 01:18:18,146 INFO train.py line 425 16826] Test: [36/68] Data 0.000 (0.034) Batch 2.271 (8.327) Loss 1.3762 (4.8741) Accuracy 0.5065.
[2021-12-14 01:18:20,982 INFO train.py line 425 16826] Test: [37/68] Data 0.000 (0.033) Batch 2.837 (8.179) Loss 1.3477 (4.8047) Accuracy 0.5253.
[2021-12-14 01:18:29,702 INFO train.py line 425 16826] Test: [38/68] Data 0.000 (0.032) Batch 8.719 (8.193) Loss 1.8244 (4.7009) Accuracy 0.4880.
[2021-12-14 01:18:31,241 INFO train.py line 425 16826] Test: [39/68] Data 0.000 (0.031) Batch 1.540 (8.022) Loss 1.3537 (4.6563) Accuracy 0.5095.
[2021-12-14 01:18:33,329 INFO train.py line 425 16826] Test: [40/68] Data 0.000 (0.031) Batch 2.088 (7.874) Loss 1.3537 (4.6048) Accuracy 0.5200.
[2021-12-14 01:18:35,349 INFO train.py line 425 16826] Test: [41/68] Data 0.000 (0.030) Batch 2.020 (7.731) Loss 1.1638 (4.5530) Accuracy 0.5712.