2020-10-31 09:36:13 [INFO] ------------Environment Information------------- platform: Linux-3.10.0_3-0-0-34-x86_64-with-centos-7.5.1804-Core Python: 3.7.9 (default, Aug 31 2020, 12:42:55) [GCC 7.3.0] Paddle compiled with cuda: True NVCC: Cuda compilation tools, release 10.2, V10.2.89 cudnn: 7.6 GPUs used: 4 CUDA_VISIBLE_DEVICES: 0,1,2,3 GPU: ['GPU 0: Tesla V100-SXM2-16GB', 'GPU 1: Tesla V100-SXM2-16GB', 'GPU 2: Tesla V100-SXM2-16GB', 'GPU 3: Tesla V100-SXM2-16GB', 'GPU 4: Tesla V100-SXM2-16GB', 'GPU 5: Tesla V100-SXM2-16GB', 'GPU 6: Tesla V100-SXM2-16GB', 'GPU 7: Tesla V100-SXM2-16GB'] GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-36) PaddlePaddle: 2.0.0-rc0 OpenCV: 4.1.0 ------------------------------------------------ 2020-10-31 09:36:13 [INFO] ---------------Config Information--------------- batch_size: 2 iters: 80000 learning_rate: decay: end_lr: 1.0e-05 power: 0.9 type: poly value: 0.01 loss: coef: - 1 - 0.4 types: - ignore_index: 255 type: CrossEntropyLoss model: backbone: output_stride: 8 pretrained: https://bj.bcebos.com/paddleseg/dygraph/resnet50_vd_ssld_v2.tar.gz type: ResNet50_vd enable_auxiliary_loss: true pretrained: null type: GCNet optimizer: momentum: 0.9 type: sgd weight_decay: 4.0e-05 train_dataset: dataset_root: data/cityscapes mode: train transforms: - max_scale_factor: 2.0 min_scale_factor: 0.5 scale_step_size: 0.25 type: ResizeStepScaling - crop_size: - 1024 - 512 type: RandomPaddingCrop - type: RandomHorizontalFlip - brightness_range: 0.4 contrast_range: 0.4 saturation_range: 0.4 type: RandomDistort - type: Normalize type: Cityscapes val_dataset: dataset_root: data/cityscapes mode: val transforms: - type: Normalize type: Cityscapes ------------------------------------------------ 2020-10-31 09:36:18 [INFO] Loading pretrained model from https://bj.bcebos.com/paddleseg/dygraph/resnet50_vd_ssld_v2.tar.gz 2020-10-31 09:36:19 [INFO] There are 275/275 variables loaded into ResNet_vd. 2020-10-31 09:37:12 [INFO] [TRAIN] epoch=1, iter=100/80000, loss=1.2712, lr=0.009989, batch_cost=0.4706, reader_cost=0.0142 | ETA 10:26:39 2020-10-31 09:37:55 [INFO] [TRAIN] epoch=1, iter=200/80000, loss=0.8818, lr=0.009978, batch_cost=0.4312, reader_cost=0.0010 | ETA 09:33:29 2020-10-31 09:38:39 [INFO] [TRAIN] epoch=1, iter=300/80000, loss=0.6197, lr=0.009966, batch_cost=0.4328, reader_cost=0.0009 | ETA 09:34:56 2020-10-31 09:39:23 [INFO] [TRAIN] epoch=2, iter=400/80000, loss=0.6064, lr=0.009955, batch_cost=0.4410, reader_cost=0.0087 | ETA 09:44:59 2020-10-31 09:40:06 [INFO] [TRAIN] epoch=2, iter=500/80000, loss=0.6449, lr=0.009944, batch_cost=0.4333, reader_cost=0.0004 | ETA 09:34:05 2020-10-31 09:40:49 [INFO] [TRAIN] epoch=2, iter=600/80000, loss=0.5674, lr=0.009933, batch_cost=0.4324, reader_cost=0.0006 | ETA 09:32:11 2020-10-31 09:41:33 [INFO] [TRAIN] epoch=2, iter=700/80000, loss=0.4796, lr=0.009921, batch_cost=0.4361, reader_cost=0.0011 | ETA 09:36:20 2020-10-31 09:42:17 [INFO] [TRAIN] epoch=3, iter=800/80000, loss=0.4999, lr=0.009910, batch_cost=0.4420, reader_cost=0.0086 | ETA 09:43:23 2020-10-31 09:43:01 [INFO] [TRAIN] epoch=3, iter=900/80000, loss=0.6226, lr=0.009899, batch_cost=0.4334, reader_cost=0.0006 | ETA 09:31:22 2020-10-31 09:43:44 [INFO] [TRAIN] epoch=3, iter=1000/80000, loss=0.4442, lr=0.009888, batch_cost=0.4356, reader_cost=0.0010 | ETA 09:33:29 2020-10-31 09:44:28 [INFO] [TRAIN] epoch=3, iter=1100/80000, loss=0.4779, lr=0.009876, batch_cost=0.4356, reader_cost=0.0011 | ETA 09:32:50 2020-10-31 09:45:12 [INFO] [TRAIN] epoch=4, iter=1200/80000, loss=0.4551, lr=0.009865, batch_cost=0.4423, reader_cost=0.0079 | ETA 09:40:50 2020-10-31 09:45:55 [INFO] [TRAIN] epoch=4, iter=1300/80000, loss=0.3957, lr=0.009854, batch_cost=0.4336, reader_cost=0.0008 | ETA 09:28:47 2020-10-31 09:46:39 [INFO] [TRAIN] epoch=4, iter=1400/80000, loss=0.4518, lr=0.009843, batch_cost=0.4343, reader_cost=0.0011 | ETA 09:28:58 2020-10-31 09:47:23 [INFO] [TRAIN] epoch=5, iter=1500/80000, loss=0.4276, lr=0.009831, batch_cost=0.4431, reader_cost=0.0082 | ETA 09:39:46 2020-10-31 09:48:06 [INFO] [TRAIN] epoch=5, iter=1600/80000, loss=0.4384, lr=0.009820, batch_cost=0.4344, reader_cost=0.0007 | ETA 09:27:35 2020-10-31 09:48:50 [INFO] [TRAIN] epoch=5, iter=1700/80000, loss=0.5161, lr=0.009809, batch_cost=0.4335, reader_cost=0.0004 | ETA 09:25:44 2020-10-31 09:49:33 [INFO] [TRAIN] epoch=5, iter=1800/80000, loss=0.4866, lr=0.009798, batch_cost=0.4324, reader_cost=0.0005 | ETA 09:23:31 2020-10-31 09:50:17 [INFO] [TRAIN] epoch=6, iter=1900/80000, loss=0.4361, lr=0.009786, batch_cost=0.4439, reader_cost=0.0084 | ETA 09:37:45 2020-10-31 09:51:01 [INFO] [TRAIN] epoch=6, iter=2000/80000, loss=0.4038, lr=0.009775, batch_cost=0.4337, reader_cost=0.0006 | ETA 09:23:46 2020-10-31 09:51:44 [INFO] [TRAIN] epoch=6, iter=2100/80000, loss=0.4380, lr=0.009764, batch_cost=0.4339, reader_cost=0.0006 | ETA 09:23:23 2020-10-31 09:52:28 [INFO] [TRAIN] epoch=6, iter=2200/80000, loss=0.3858, lr=0.009753, batch_cost=0.4340, reader_cost=0.0005 | ETA 09:22:42 2020-10-31 09:53:12 [INFO] [TRAIN] epoch=7, iter=2300/80000, loss=0.4112, lr=0.009741, batch_cost=0.4419, reader_cost=0.0095 | ETA 09:32:11 2020-10-31 09:53:55 [INFO] [TRAIN] epoch=7, iter=2400/80000, loss=0.4073, lr=0.009730, batch_cost=0.4363, reader_cost=0.0005 | ETA 09:24:16 2020-10-31 09:54:39 [INFO] [TRAIN] epoch=7, iter=2500/80000, loss=0.3702, lr=0.009719, batch_cost=0.4358, reader_cost=0.0008 | ETA 09:22:54 2020-10-31 09:55:22 [INFO] [TRAIN] epoch=7, iter=2600/80000, loss=0.2974, lr=0.009707, batch_cost=0.4345, reader_cost=0.0007 | ETA 09:20:26 2020-10-31 09:56:06 [INFO] [TRAIN] epoch=8, iter=2700/80000, loss=0.3615, lr=0.009696, batch_cost=0.4399, reader_cost=0.0082 | ETA 09:26:48 2020-10-31 09:56:50 [INFO] [TRAIN] epoch=8, iter=2800/80000, loss=0.3683, lr=0.009685, batch_cost=0.4351, reader_cost=0.0004 | ETA 09:19:51 2020-10-31 09:57:33 [INFO] [TRAIN] epoch=8, iter=2900/80000, loss=0.3639, lr=0.009674, batch_cost=0.4343, reader_cost=0.0004 | ETA 09:18:02 2020-10-31 09:58:18 [INFO] [TRAIN] epoch=9, iter=3000/80000, loss=0.2961, lr=0.009662, batch_cost=0.4448, reader_cost=0.0079 | ETA 09:30:46 2020-10-31 09:59:01 [INFO] [TRAIN] epoch=9, iter=3100/80000, loss=0.4496, lr=0.009651, batch_cost=0.4347, reader_cost=0.0006 | ETA 09:17:08 2020-10-31 09:59:45 [INFO] [TRAIN] epoch=9, iter=3200/80000, loss=0.4498, lr=0.009640, batch_cost=0.4353, reader_cost=0.0006 | ETA 09:17:09 2020-10-31 10:00:28 [INFO] [TRAIN] epoch=9, iter=3300/80000, loss=0.3331, lr=0.009628, batch_cost=0.4344, reader_cost=0.0009 | ETA 09:15:16 2020-10-31 10:01:13 [INFO] [TRAIN] epoch=10, iter=3400/80000, loss=0.3073, lr=0.009617, batch_cost=0.4429, reader_cost=0.0081 | ETA 09:25:24 2020-10-31 10:01:56 [INFO] [TRAIN] epoch=10, iter=3500/80000, loss=0.3339, lr=0.009606, batch_cost=0.4367, reader_cost=0.0007 | ETA 09:16:46 2020-10-31 10:02:40 [INFO] [TRAIN] epoch=10, iter=3600/80000, loss=0.3739, lr=0.009595, batch_cost=0.4344, reader_cost=0.0005 | ETA 09:13:11 2020-10-31 10:03:23 [INFO] [TRAIN] epoch=10, iter=3700/80000, loss=0.3432, lr=0.009583, batch_cost=0.4342, reader_cost=0.0005 | ETA 09:12:08 2020-10-31 10:04:08 [INFO] [TRAIN] epoch=11, iter=3800/80000, loss=0.3887, lr=0.009572, batch_cost=0.4449, reader_cost=0.0081 | ETA 09:24:59 2020-10-31 10:04:51 [INFO] [TRAIN] epoch=11, iter=3900/80000, loss=0.3420, lr=0.009561, batch_cost=0.4358, reader_cost=0.0006 | ETA 09:12:46 2020-10-31 10:05:35 [INFO] [TRAIN] epoch=11, iter=4000/80000, loss=0.3401, lr=0.009549, batch_cost=0.4355, reader_cost=0.0005 | ETA 09:11:35 2020-10-31 10:06:19 [INFO] [TRAIN] epoch=12, iter=4100/80000, loss=0.3211, lr=0.009538, batch_cost=0.4426, reader_cost=0.0073 | ETA 09:19:55 2020-10-31 10:07:03 [INFO] [TRAIN] epoch=12, iter=4200/80000, loss=0.3151, lr=0.009527, batch_cost=0.4365, reader_cost=0.0010 | ETA 09:11:27 2020-10-31 10:07:46 [INFO] [TRAIN] epoch=12, iter=4300/80000, loss=0.3634, lr=0.009516, batch_cost=0.4359, reader_cost=0.0009 | ETA 09:09:55 2020-10-31 10:08:30 [INFO] [TRAIN] epoch=12, iter=4400/80000, loss=0.3193, lr=0.009504, batch_cost=0.4377, reader_cost=0.0011 | ETA 09:11:27 2020-10-31 10:09:15 [INFO] [TRAIN] epoch=13, iter=4500/80000, loss=0.3102, lr=0.009493, batch_cost=0.4459, reader_cost=0.0081 | ETA 09:21:02 2020-10-31 10:09:58 [INFO] [TRAIN] epoch=13, iter=4600/80000, loss=0.3432, lr=0.009482, batch_cost=0.4333, reader_cost=0.0003 | ETA 09:04:31 2020-10-31 10:10:41 [INFO] [TRAIN] epoch=13, iter=4700/80000, loss=0.3253, lr=0.009470, batch_cost=0.4345, reader_cost=0.0005 | ETA 09:05:21 2020-10-31 10:11:25 [INFO] [TRAIN] epoch=13, iter=4800/80000, loss=0.3152, lr=0.009459, batch_cost=0.4377, reader_cost=0.0004 | ETA 09:08:32 2020-10-31 10:12:10 [INFO] [TRAIN] epoch=14, iter=4900/80000, loss=0.2860, lr=0.009448, batch_cost=0.4447, reader_cost=0.0076 | ETA 09:16:35 2020-10-31 10:12:53 [INFO] [TRAIN] epoch=14, iter=5000/80000, loss=0.3383, lr=0.009436, batch_cost=0.4361, reader_cost=0.0009 | ETA 09:05:07 2020-10-31 10:13:37 [INFO] [TRAIN] epoch=14, iter=5100/80000, loss=0.3206, lr=0.009425, batch_cost=0.4372, reader_cost=0.0009 | ETA 09:05:47 2020-10-31 10:14:21 [INFO] [TRAIN] epoch=14, iter=5200/80000, loss=0.3232, lr=0.009414, batch_cost=0.4361, reader_cost=0.0009 | ETA 09:03:39 2020-10-31 10:15:05 [INFO] [TRAIN] epoch=15, iter=5300/80000, loss=0.3128, lr=0.009402, batch_cost=0.4421, reader_cost=0.0082 | ETA 09:10:22 2020-10-31 10:15:48 [INFO] [TRAIN] epoch=15, iter=5400/80000, loss=0.3515, lr=0.009391, batch_cost=0.4331, reader_cost=0.0004 | ETA 08:58:28 2020-10-31 10:16:32 [INFO] [TRAIN] epoch=15, iter=5500/80000, loss=0.3854, lr=0.009380, batch_cost=0.4344, reader_cost=0.0003 | ETA 08:59:25 2020-10-31 10:17:16 [INFO] [TRAIN] epoch=16, iter=5600/80000, loss=0.3301, lr=0.009368, batch_cost=0.4446, reader_cost=0.0067 | ETA 09:11:18 2020-10-31 10:18:00 [INFO] [TRAIN] epoch=16, iter=5700/80000, loss=0.3204, lr=0.009357, batch_cost=0.4373, reader_cost=0.0008 | ETA 09:01:31 2020-10-31 10:18:43 [INFO] [TRAIN] epoch=16, iter=5800/80000, loss=0.2981, lr=0.009346, batch_cost=0.4348, reader_cost=0.0005 | ETA 08:57:42 2020-10-31 10:19:27 [INFO] [TRAIN] epoch=16, iter=5900/80000, loss=0.3078, lr=0.009335, batch_cost=0.4373, reader_cost=0.0005 | ETA 09:00:01 2020-10-31 10:20:11 [INFO] [TRAIN] epoch=17, iter=6000/80000, loss=0.3380, lr=0.009323, batch_cost=0.4421, reader_cost=0.0082 | ETA 09:05:16 2020-10-31 10:20:55 [INFO] [TRAIN] epoch=17, iter=6100/80000, loss=0.3001, lr=0.009312, batch_cost=0.4346, reader_cost=0.0003 | ETA 08:55:18 2020-10-31 10:21:38 [INFO] [TRAIN] epoch=17, iter=6200/80000, loss=0.3107, lr=0.009301, batch_cost=0.4366, reader_cost=0.0008 | ETA 08:56:57 2020-10-31 10:22:22 [INFO] [TRAIN] epoch=17, iter=6300/80000, loss=0.2643, lr=0.009289, batch_cost=0.4370, reader_cost=0.0011 | ETA 08:56:49 2020-10-31 10:23:06 [INFO] [TRAIN] epoch=18, iter=6400/80000, loss=0.3200, lr=0.009278, batch_cost=0.4423, reader_cost=0.0085 | ETA 09:02:36 2020-10-31 10:23:50 [INFO] [TRAIN] epoch=18, iter=6500/80000, loss=0.2654, lr=0.009267, batch_cost=0.4345, reader_cost=0.0007 | ETA 08:52:18 2020-10-31 10:24:33 [INFO] [TRAIN] epoch=18, iter=6600/80000, loss=0.3177, lr=0.009255, batch_cost=0.4337, reader_cost=0.0007 | ETA 08:50:35 2020-10-31 10:25:17 [INFO] [TRAIN] epoch=19, iter=6700/80000, loss=0.3328, lr=0.009244, batch_cost=0.4427, reader_cost=0.0077 | ETA 09:00:46 2020-10-31 10:26:01 [INFO] [TRAIN] epoch=19, iter=6800/80000, loss=0.2843, lr=0.009233, batch_cost=0.4338, reader_cost=0.0006 | ETA 08:49:12 2020-10-31 10:26:44 [INFO] [TRAIN] epoch=19, iter=6900/80000, loss=0.3632, lr=0.009221, batch_cost=0.4340, reader_cost=0.0004 | ETA 08:48:44 2020-10-31 10:27:28 [INFO] [TRAIN] epoch=19, iter=7000/80000, loss=0.2743, lr=0.009210, batch_cost=0.4367, reader_cost=0.0005 | ETA 08:51:17 2020-10-31 10:28:12 [INFO] [TRAIN] epoch=20, iter=7100/80000, loss=0.2938, lr=0.009199, batch_cost=0.4431, reader_cost=0.0084 | ETA 08:58:22 2020-10-31 10:28:56 [INFO] [TRAIN] epoch=20, iter=7200/80000, loss=0.3336, lr=0.009187, batch_cost=0.4376, reader_cost=0.0008 | ETA 08:50:57 2020-10-31 10:29:39 [INFO] [TRAIN] epoch=20, iter=7300/80000, loss=0.2854, lr=0.009176, batch_cost=0.4352, reader_cost=0.0006 | ETA 08:47:19 2020-10-31 10:30:23 [INFO] [TRAIN] epoch=20, iter=7400/80000, loss=0.2748, lr=0.009164, batch_cost=0.4335, reader_cost=0.0005 | ETA 08:44:33 2020-10-31 10:31:07 [INFO] [TRAIN] epoch=21, iter=7500/80000, loss=0.2724, lr=0.009153, batch_cost=0.4435, reader_cost=0.0070 | ETA 08:55:51 2020-10-31 10:31:51 [INFO] [TRAIN] epoch=21, iter=7600/80000, loss=0.3218, lr=0.009142, batch_cost=0.4359, reader_cost=0.0005 | ETA 08:46:02 2020-10-31 10:32:34 [INFO] [TRAIN] epoch=21, iter=7700/80000, loss=0.3026, lr=0.009130, batch_cost=0.4342, reader_cost=0.0003 | ETA 08:43:15 2020-10-31 10:33:17 [INFO] [TRAIN] epoch=21, iter=7800/80000, loss=0.2709, lr=0.009119, batch_cost=0.4325, reader_cost=0.0008 | ETA 08:40:27 2020-10-31 10:34:02 [INFO] [TRAIN] epoch=22, iter=7900/80000, loss=0.2614, lr=0.009108, batch_cost=0.4420, reader_cost=0.0078 | ETA 08:51:07 2020-10-31 10:34:45 [INFO] [TRAIN] epoch=22, iter=8000/80000, loss=0.2686, lr=0.009096, batch_cost=0.4371, reader_cost=0.0006 | ETA 08:44:34 2020-10-31 10:34:51 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 10:39:35 [INFO] [EVAL] #Images=500 mIoU=0.6994 Acc=0.9488 Kappa=0.9334 2020-10-31 10:39:35 [INFO] [EVAL] Category IoU: [0.9744 0.8078 0.9005 0.3585 0.5321 0.5728 0.6465 0.7367 0.9143 0.5836 0.9276 0.7853 0.5219 0.9286 0.5996 0.6471 0.5416 0.5648 0.7445] 2020-10-31 10:39:35 [INFO] [EVAL] Category Acc: [0.9864 0.9095 0.9365 0.7849 0.7174 0.8041 0.8077 0.8983 0.9472 0.7863 0.951 0.8598 0.7677 0.9642 0.8791 0.7244 0.6127 0.7475 0.8297] 2020-10-31 10:39:38 [INFO] [EVAL] The model with the best validation mIoU (0.6994) was saved at iter 8000. 2020-10-31 10:40:21 [INFO] [TRAIN] epoch=22, iter=8100/80000, loss=0.2795, lr=0.009085, batch_cost=0.4284, reader_cost=0.0003 | ETA 08:33:19 2020-10-31 10:41:05 [INFO] [TRAIN] epoch=23, iter=8200/80000, loss=0.2933, lr=0.009074, batch_cost=0.4409, reader_cost=0.0091 | ETA 08:47:35 2020-10-31 10:41:49 [INFO] [TRAIN] epoch=23, iter=8300/80000, loss=0.2692, lr=0.009062, batch_cost=0.4357, reader_cost=0.0005 | ETA 08:40:39 2020-10-31 10:42:32 [INFO] [TRAIN] epoch=23, iter=8400/80000, loss=0.3282, lr=0.009051, batch_cost=0.4352, reader_cost=0.0009 | ETA 08:39:18 2020-10-31 10:43:16 [INFO] [TRAIN] epoch=23, iter=8500/80000, loss=0.3266, lr=0.009040, batch_cost=0.4358, reader_cost=0.0008 | ETA 08:39:21 2020-10-31 10:44:00 [INFO] [TRAIN] epoch=24, iter=8600/80000, loss=0.2909, lr=0.009028, batch_cost=0.4418, reader_cost=0.0082 | ETA 08:45:44 2020-10-31 10:44:44 [INFO] [TRAIN] epoch=24, iter=8700/80000, loss=0.3203, lr=0.009017, batch_cost=0.4347, reader_cost=0.0004 | ETA 08:36:30 2020-10-31 10:45:27 [INFO] [TRAIN] epoch=24, iter=8800/80000, loss=0.3111, lr=0.009005, batch_cost=0.4378, reader_cost=0.0011 | ETA 08:39:29 2020-10-31 10:46:11 [INFO] [TRAIN] epoch=24, iter=8900/80000, loss=0.2236, lr=0.008994, batch_cost=0.4381, reader_cost=0.0008 | ETA 08:39:11 2020-10-31 10:46:55 [INFO] [TRAIN] epoch=25, iter=9000/80000, loss=0.2516, lr=0.008983, batch_cost=0.4423, reader_cost=0.0086 | ETA 08:43:22 2020-10-31 10:47:39 [INFO] [TRAIN] epoch=25, iter=9100/80000, loss=0.2702, lr=0.008971, batch_cost=0.4324, reader_cost=0.0009 | ETA 08:30:58 2020-10-31 10:48:22 [INFO] [TRAIN] epoch=25, iter=9200/80000, loss=0.2867, lr=0.008960, batch_cost=0.4343, reader_cost=0.0005 | ETA 08:32:29 2020-10-31 10:49:05 [INFO] [TRAIN] epoch=25, iter=9300/80000, loss=0.2671, lr=0.008949, batch_cost=0.4346, reader_cost=0.0007 | ETA 08:32:06 2020-10-31 10:49:50 [INFO] [TRAIN] epoch=26, iter=9400/80000, loss=0.2513, lr=0.008937, batch_cost=0.4454, reader_cost=0.0092 | ETA 08:44:05 2020-10-31 10:50:34 [INFO] [TRAIN] epoch=26, iter=9500/80000, loss=0.2976, lr=0.008926, batch_cost=0.4373, reader_cost=0.0008 | ETA 08:33:48 2020-10-31 10:51:17 [INFO] [TRAIN] epoch=26, iter=9600/80000, loss=0.2728, lr=0.008914, batch_cost=0.4365, reader_cost=0.0005 | ETA 08:32:11 2020-10-31 10:52:01 [INFO] [TRAIN] epoch=27, iter=9700/80000, loss=0.2236, lr=0.008903, batch_cost=0.4403, reader_cost=0.0075 | ETA 08:35:55 2020-10-31 10:52:45 [INFO] [TRAIN] epoch=27, iter=9800/80000, loss=0.2750, lr=0.008892, batch_cost=0.4331, reader_cost=0.0011 | ETA 08:26:44 2020-10-31 10:53:28 [INFO] [TRAIN] epoch=27, iter=9900/80000, loss=0.2821, lr=0.008880, batch_cost=0.4344, reader_cost=0.0005 | ETA 08:27:33 2020-10-31 10:54:12 [INFO] [TRAIN] epoch=27, iter=10000/80000, loss=0.2626, lr=0.008869, batch_cost=0.4355, reader_cost=0.0008 | ETA 08:28:07 2020-10-31 10:54:56 [INFO] [TRAIN] epoch=28, iter=10100/80000, loss=0.2987, lr=0.008857, batch_cost=0.4428, reader_cost=0.0089 | ETA 08:35:52 2020-10-31 10:55:39 [INFO] [TRAIN] epoch=28, iter=10200/80000, loss=0.2493, lr=0.008846, batch_cost=0.4338, reader_cost=0.0010 | ETA 08:24:41 2020-10-31 10:56:23 [INFO] [TRAIN] epoch=28, iter=10300/80000, loss=0.2818, lr=0.008835, batch_cost=0.4355, reader_cost=0.0011 | ETA 08:25:54 2020-10-31 10:57:07 [INFO] [TRAIN] epoch=28, iter=10400/80000, loss=0.2337, lr=0.008823, batch_cost=0.4352, reader_cost=0.0007 | ETA 08:24:52 2020-10-31 10:57:51 [INFO] [TRAIN] epoch=29, iter=10500/80000, loss=0.2595, lr=0.008812, batch_cost=0.4419, reader_cost=0.0079 | ETA 08:31:49 2020-10-31 10:58:34 [INFO] [TRAIN] epoch=29, iter=10600/80000, loss=0.2760, lr=0.008801, batch_cost=0.4345, reader_cost=0.0010 | ETA 08:22:34 2020-10-31 10:59:18 [INFO] [TRAIN] epoch=29, iter=10700/80000, loss=0.3361, lr=0.008789, batch_cost=0.4390, reader_cost=0.0011 | ETA 08:27:00 2020-10-31 11:00:02 [INFO] [TRAIN] epoch=30, iter=10800/80000, loss=0.2378, lr=0.008778, batch_cost=0.4427, reader_cost=0.0087 | ETA 08:30:33 2020-10-31 11:00:46 [INFO] [TRAIN] epoch=30, iter=10900/80000, loss=0.2409, lr=0.008766, batch_cost=0.4330, reader_cost=0.0008 | ETA 08:18:42 2020-10-31 11:01:29 [INFO] [TRAIN] epoch=30, iter=11000/80000, loss=0.2570, lr=0.008755, batch_cost=0.4314, reader_cost=0.0008 | ETA 08:16:07 2020-10-31 11:02:12 [INFO] [TRAIN] epoch=30, iter=11100/80000, loss=0.2277, lr=0.008743, batch_cost=0.4318, reader_cost=0.0005 | ETA 08:15:48 2020-10-31 11:02:56 [INFO] [TRAIN] epoch=31, iter=11200/80000, loss=0.2474, lr=0.008732, batch_cost=0.4433, reader_cost=0.0092 | ETA 08:28:22 2020-10-31 11:03:39 [INFO] [TRAIN] epoch=31, iter=11300/80000, loss=0.2835, lr=0.008721, batch_cost=0.4314, reader_cost=0.0006 | ETA 08:13:57 2020-10-31 11:04:23 [INFO] [TRAIN] epoch=31, iter=11400/80000, loss=0.3113, lr=0.008709, batch_cost=0.4322, reader_cost=0.0005 | ETA 08:14:07 2020-10-31 11:05:06 [INFO] [TRAIN] epoch=31, iter=11500/80000, loss=0.2418, lr=0.008698, batch_cost=0.4306, reader_cost=0.0004 | ETA 08:11:33 2020-10-31 11:05:50 [INFO] [TRAIN] epoch=32, iter=11600/80000, loss=0.3100, lr=0.008686, batch_cost=0.4416, reader_cost=0.0080 | ETA 08:23:26 2020-10-31 11:06:33 [INFO] [TRAIN] epoch=32, iter=11700/80000, loss=0.3109, lr=0.008675, batch_cost=0.4343, reader_cost=0.0008 | ETA 08:14:24 2020-10-31 11:07:17 [INFO] [TRAIN] epoch=32, iter=11800/80000, loss=0.2664, lr=0.008664, batch_cost=0.4380, reader_cost=0.0006 | ETA 08:17:54 2020-10-31 11:08:01 [INFO] [TRAIN] epoch=32, iter=11900/80000, loss=0.2330, lr=0.008652, batch_cost=0.4377, reader_cost=0.0007 | ETA 08:16:48 2020-10-31 11:08:45 [INFO] [TRAIN] epoch=33, iter=12000/80000, loss=0.2560, lr=0.008641, batch_cost=0.4440, reader_cost=0.0079 | ETA 08:23:09 2020-10-31 11:09:29 [INFO] [TRAIN] epoch=33, iter=12100/80000, loss=0.2707, lr=0.008629, batch_cost=0.4335, reader_cost=0.0005 | ETA 08:10:34 2020-10-31 11:10:12 [INFO] [TRAIN] epoch=33, iter=12200/80000, loss=0.2880, lr=0.008618, batch_cost=0.4333, reader_cost=0.0005 | ETA 08:09:34 2020-10-31 11:10:56 [INFO] [TRAIN] epoch=34, iter=12300/80000, loss=0.2199, lr=0.008606, batch_cost=0.4441, reader_cost=0.0084 | ETA 08:21:02 2020-10-31 11:11:40 [INFO] [TRAIN] epoch=34, iter=12400/80000, loss=0.2463, lr=0.008595, batch_cost=0.4364, reader_cost=0.0007 | ETA 08:11:42 2020-10-31 11:12:24 [INFO] [TRAIN] epoch=34, iter=12500/80000, loss=0.2785, lr=0.008584, batch_cost=0.4371, reader_cost=0.0006 | ETA 08:11:42 2020-10-31 11:13:07 [INFO] [TRAIN] epoch=34, iter=12600/80000, loss=0.2231, lr=0.008572, batch_cost=0.4377, reader_cost=0.0004 | ETA 08:11:44 2020-10-31 11:13:51 [INFO] [TRAIN] epoch=35, iter=12700/80000, loss=0.2394, lr=0.008561, batch_cost=0.4400, reader_cost=0.0081 | ETA 08:13:33 2020-10-31 11:14:35 [INFO] [TRAIN] epoch=35, iter=12800/80000, loss=0.2250, lr=0.008549, batch_cost=0.4308, reader_cost=0.0006 | ETA 08:02:27 2020-10-31 11:15:18 [INFO] [TRAIN] epoch=35, iter=12900/80000, loss=0.2430, lr=0.008538, batch_cost=0.4364, reader_cost=0.0007 | ETA 08:07:59 2020-10-31 11:16:02 [INFO] [TRAIN] epoch=35, iter=13000/80000, loss=0.2268, lr=0.008526, batch_cost=0.4360, reader_cost=0.0006 | ETA 08:06:53 2020-10-31 11:16:46 [INFO] [TRAIN] epoch=36, iter=13100/80000, loss=0.2376, lr=0.008515, batch_cost=0.4465, reader_cost=0.0092 | ETA 08:17:53 2020-10-31 11:17:30 [INFO] [TRAIN] epoch=36, iter=13200/80000, loss=0.2211, lr=0.008504, batch_cost=0.4368, reader_cost=0.0008 | ETA 08:06:19 2020-10-31 11:18:14 [INFO] [TRAIN] epoch=36, iter=13300/80000, loss=0.2715, lr=0.008492, batch_cost=0.4364, reader_cost=0.0007 | ETA 08:05:09 2020-10-31 11:18:58 [INFO] [TRAIN] epoch=37, iter=13400/80000, loss=0.2912, lr=0.008481, batch_cost=0.4450, reader_cost=0.0093 | ETA 08:13:56 2020-10-31 11:19:42 [INFO] [TRAIN] epoch=37, iter=13500/80000, loss=0.2888, lr=0.008469, batch_cost=0.4362, reader_cost=0.0010 | ETA 08:03:28 2020-10-31 11:20:26 [INFO] [TRAIN] epoch=37, iter=13600/80000, loss=0.3158, lr=0.008458, batch_cost=0.4376, reader_cost=0.0011 | ETA 08:04:18 2020-10-31 11:21:10 [INFO] [TRAIN] epoch=37, iter=13700/80000, loss=0.2868, lr=0.008446, batch_cost=0.4385, reader_cost=0.0009 | ETA 08:04:33 2020-10-31 11:21:54 [INFO] [TRAIN] epoch=38, iter=13800/80000, loss=0.2277, lr=0.008435, batch_cost=0.4459, reader_cost=0.0103 | ETA 08:12:00 2020-10-31 11:22:37 [INFO] [TRAIN] epoch=38, iter=13900/80000, loss=0.2458, lr=0.008423, batch_cost=0.4328, reader_cost=0.0006 | ETA 07:56:47 2020-10-31 11:23:21 [INFO] [TRAIN] epoch=38, iter=14000/80000, loss=0.2781, lr=0.008412, batch_cost=0.4344, reader_cost=0.0007 | ETA 07:57:47 2020-10-31 11:24:04 [INFO] [TRAIN] epoch=38, iter=14100/80000, loss=0.2327, lr=0.008400, batch_cost=0.4354, reader_cost=0.0006 | ETA 07:58:13 2020-10-31 11:24:48 [INFO] [TRAIN] epoch=39, iter=14200/80000, loss=0.2156, lr=0.008389, batch_cost=0.4405, reader_cost=0.0080 | ETA 08:03:07 2020-10-31 11:25:32 [INFO] [TRAIN] epoch=39, iter=14300/80000, loss=0.3016, lr=0.008378, batch_cost=0.4369, reader_cost=0.0012 | ETA 07:58:24 2020-10-31 11:26:16 [INFO] [TRAIN] epoch=39, iter=14400/80000, loss=0.2631, lr=0.008366, batch_cost=0.4352, reader_cost=0.0005 | ETA 07:55:50 2020-10-31 11:26:59 [INFO] [TRAIN] epoch=39, iter=14500/80000, loss=0.2268, lr=0.008355, batch_cost=0.4366, reader_cost=0.0007 | ETA 07:56:34 2020-10-31 11:27:44 [INFO] [TRAIN] epoch=40, iter=14600/80000, loss=0.2510, lr=0.008343, batch_cost=0.4431, reader_cost=0.0074 | ETA 08:02:56 2020-10-31 11:28:27 [INFO] [TRAIN] epoch=40, iter=14700/80000, loss=0.2630, lr=0.008332, batch_cost=0.4360, reader_cost=0.0006 | ETA 07:54:30 2020-10-31 11:29:11 [INFO] [TRAIN] epoch=40, iter=14800/80000, loss=0.2712, lr=0.008320, batch_cost=0.4366, reader_cost=0.0007 | ETA 07:54:26 2020-10-31 11:29:55 [INFO] [TRAIN] epoch=41, iter=14900/80000, loss=0.2436, lr=0.008309, batch_cost=0.4428, reader_cost=0.0080 | ETA 08:00:28 2020-10-31 11:30:39 [INFO] [TRAIN] epoch=41, iter=15000/80000, loss=0.3085, lr=0.008297, batch_cost=0.4365, reader_cost=0.0009 | ETA 07:52:53 2020-10-31 11:31:22 [INFO] [TRAIN] epoch=41, iter=15100/80000, loss=0.2622, lr=0.008286, batch_cost=0.4362, reader_cost=0.0010 | ETA 07:51:51 2020-10-31 11:32:06 [INFO] [TRAIN] epoch=41, iter=15200/80000, loss=0.2474, lr=0.008274, batch_cost=0.4349, reader_cost=0.0009 | ETA 07:49:44 2020-10-31 11:32:50 [INFO] [TRAIN] epoch=42, iter=15300/80000, loss=0.2291, lr=0.008263, batch_cost=0.4437, reader_cost=0.0081 | ETA 07:58:24 2020-10-31 11:33:34 [INFO] [TRAIN] epoch=42, iter=15400/80000, loss=0.2374, lr=0.008251, batch_cost=0.4364, reader_cost=0.0006 | ETA 07:49:49 2020-10-31 11:34:18 [INFO] [TRAIN] epoch=42, iter=15500/80000, loss=0.2504, lr=0.008240, batch_cost=0.4376, reader_cost=0.0010 | ETA 07:50:24 2020-10-31 11:35:01 [INFO] [TRAIN] epoch=42, iter=15600/80000, loss=0.2306, lr=0.008228, batch_cost=0.4367, reader_cost=0.0013 | ETA 07:48:46 2020-10-31 11:35:45 [INFO] [TRAIN] epoch=43, iter=15700/80000, loss=0.2487, lr=0.008217, batch_cost=0.4401, reader_cost=0.0086 | ETA 07:51:41 2020-10-31 11:36:29 [INFO] [TRAIN] epoch=43, iter=15800/80000, loss=0.2443, lr=0.008205, batch_cost=0.4336, reader_cost=0.0007 | ETA 07:43:59 2020-10-31 11:37:12 [INFO] [TRAIN] epoch=43, iter=15900/80000, loss=0.2376, lr=0.008194, batch_cost=0.4340, reader_cost=0.0003 | ETA 07:43:37 2020-10-31 11:37:57 [INFO] [TRAIN] epoch=44, iter=16000/80000, loss=0.2136, lr=0.008182, batch_cost=0.4436, reader_cost=0.0079 | ETA 07:53:09 2020-10-31 11:38:02 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 11:42:38 [INFO] [EVAL] #Images=500 mIoU=0.7231 Acc=0.9518 Kappa=0.9374 2020-10-31 11:42:38 [INFO] [EVAL] Category IoU: [0.9755 0.8138 0.9106 0.3163 0.5526 0.5871 0.6792 0.7507 0.9158 0.608 0.9392 0.8008 0.5808 0.9303 0.6838 0.7559 0.6216 0.5706 0.7472] 2020-10-31 11:42:38 [INFO] [EVAL] Category Acc: [0.9856 0.9256 0.9421 0.8197 0.6884 0.839 0.8395 0.9042 0.9483 0.7667 0.9638 0.8615 0.7561 0.9752 0.7311 0.8166 0.713 0.8255 0.8176] 2020-10-31 11:42:41 [INFO] [EVAL] The model with the best validation mIoU (0.7231) was saved at iter 16000. 2020-10-31 11:43:24 [INFO] [TRAIN] epoch=44, iter=16100/80000, loss=0.2322, lr=0.008171, batch_cost=0.4310, reader_cost=0.0005 | ETA 07:39:01 2020-10-31 11:44:07 [INFO] [TRAIN] epoch=44, iter=16200/80000, loss=0.2585, lr=0.008159, batch_cost=0.4320, reader_cost=0.0003 | ETA 07:39:18 2020-10-31 11:44:50 [INFO] [TRAIN] epoch=44, iter=16300/80000, loss=0.1982, lr=0.008148, batch_cost=0.4281, reader_cost=0.0004 | ETA 07:34:29 2020-10-31 11:45:34 [INFO] [TRAIN] epoch=45, iter=16400/80000, loss=0.2331, lr=0.008136, batch_cost=0.4412, reader_cost=0.0088 | ETA 07:47:38 2020-10-31 11:46:17 [INFO] [TRAIN] epoch=45, iter=16500/80000, loss=0.2743, lr=0.008125, batch_cost=0.4335, reader_cost=0.0005 | ETA 07:38:48 2020-10-31 11:47:01 [INFO] [TRAIN] epoch=45, iter=16600/80000, loss=0.2361, lr=0.008113, batch_cost=0.4344, reader_cost=0.0004 | ETA 07:39:03 2020-10-31 11:47:44 [INFO] [TRAIN] epoch=45, iter=16700/80000, loss=0.2093, lr=0.008102, batch_cost=0.4325, reader_cost=0.0004 | ETA 07:36:17 2020-10-31 11:48:28 [INFO] [TRAIN] epoch=46, iter=16800/80000, loss=0.2778, lr=0.008090, batch_cost=0.4404, reader_cost=0.0080 | ETA 07:43:55 2020-10-31 11:49:12 [INFO] [TRAIN] epoch=46, iter=16900/80000, loss=0.2569, lr=0.008079, batch_cost=0.4347, reader_cost=0.0006 | ETA 07:37:11 2020-10-31 11:49:55 [INFO] [TRAIN] epoch=46, iter=17000/80000, loss=0.2359, lr=0.008067, batch_cost=0.4305, reader_cost=0.0004 | ETA 07:32:00 2020-10-31 11:50:38 [INFO] [TRAIN] epoch=46, iter=17100/80000, loss=0.2243, lr=0.008056, batch_cost=0.4334, reader_cost=0.0003 | ETA 07:34:21 2020-10-31 11:51:22 [INFO] [TRAIN] epoch=47, iter=17200/80000, loss=0.2704, lr=0.008044, batch_cost=0.4416, reader_cost=0.0067 | ETA 07:42:11 2020-10-31 11:52:05 [INFO] [TRAIN] epoch=47, iter=17300/80000, loss=0.2334, lr=0.008033, batch_cost=0.4323, reader_cost=0.0003 | ETA 07:31:45 2020-10-31 11:52:49 [INFO] [TRAIN] epoch=47, iter=17400/80000, loss=0.2573, lr=0.008021, batch_cost=0.4332, reader_cost=0.0004 | ETA 07:31:56 2020-10-31 11:53:33 [INFO] [TRAIN] epoch=48, iter=17500/80000, loss=0.2061, lr=0.008010, batch_cost=0.4412, reader_cost=0.0086 | ETA 07:39:33 2020-10-31 11:54:16 [INFO] [TRAIN] epoch=48, iter=17600/80000, loss=0.2620, lr=0.007998, batch_cost=0.4312, reader_cost=0.0005 | ETA 07:28:24 2020-10-31 11:55:00 [INFO] [TRAIN] epoch=48, iter=17700/80000, loss=0.2331, lr=0.007987, batch_cost=0.4355, reader_cost=0.0005 | ETA 07:32:09 2020-10-31 11:55:43 [INFO] [TRAIN] epoch=48, iter=17800/80000, loss=0.2328, lr=0.007975, batch_cost=0.4341, reader_cost=0.0009 | ETA 07:30:03 2020-10-31 11:56:27 [INFO] [TRAIN] epoch=49, iter=17900/80000, loss=0.2357, lr=0.007964, batch_cost=0.4444, reader_cost=0.0092 | ETA 07:39:55 2020-10-31 11:57:11 [INFO] [TRAIN] epoch=49, iter=18000/80000, loss=0.2282, lr=0.007952, batch_cost=0.4317, reader_cost=0.0005 | ETA 07:26:05 2020-10-31 11:57:54 [INFO] [TRAIN] epoch=49, iter=18100/80000, loss=0.2456, lr=0.007941, batch_cost=0.4341, reader_cost=0.0009 | ETA 07:27:51 2020-10-31 11:58:38 [INFO] [TRAIN] epoch=49, iter=18200/80000, loss=0.2077, lr=0.007929, batch_cost=0.4363, reader_cost=0.0012 | ETA 07:29:24 2020-10-31 11:59:22 [INFO] [TRAIN] epoch=50, iter=18300/80000, loss=0.2461, lr=0.007918, batch_cost=0.4434, reader_cost=0.0091 | ETA 07:35:56 2020-10-31 12:00:05 [INFO] [TRAIN] epoch=50, iter=18400/80000, loss=0.2305, lr=0.007906, batch_cost=0.4327, reader_cost=0.0006 | ETA 07:24:12 2020-10-31 12:00:49 [INFO] [TRAIN] epoch=50, iter=18500/80000, loss=0.2540, lr=0.007895, batch_cost=0.4361, reader_cost=0.0007 | ETA 07:26:57 2020-10-31 12:01:32 [INFO] [TRAIN] epoch=50, iter=18600/80000, loss=0.2088, lr=0.007883, batch_cost=0.4336, reader_cost=0.0006 | ETA 07:23:40 2020-10-31 12:02:16 [INFO] [TRAIN] epoch=51, iter=18700/80000, loss=0.2013, lr=0.007871, batch_cost=0.4414, reader_cost=0.0082 | ETA 07:30:55 2020-10-31 12:03:00 [INFO] [TRAIN] epoch=51, iter=18800/80000, loss=0.2547, lr=0.007860, batch_cost=0.4362, reader_cost=0.0005 | ETA 07:24:54 2020-10-31 12:03:43 [INFO] [TRAIN] epoch=51, iter=18900/80000, loss=0.2440, lr=0.007848, batch_cost=0.4333, reader_cost=0.0006 | ETA 07:21:16 2020-10-31 12:04:28 [INFO] [TRAIN] epoch=52, iter=19000/80000, loss=0.2234, lr=0.007837, batch_cost=0.4428, reader_cost=0.0080 | ETA 07:30:09 2020-10-31 12:05:11 [INFO] [TRAIN] epoch=52, iter=19100/80000, loss=0.2375, lr=0.007825, batch_cost=0.4358, reader_cost=0.0008 | ETA 07:22:22 2020-10-31 12:05:55 [INFO] [TRAIN] epoch=52, iter=19200/80000, loss=0.2464, lr=0.007814, batch_cost=0.4368, reader_cost=0.0012 | ETA 07:22:38 2020-10-31 12:06:38 [INFO] [TRAIN] epoch=52, iter=19300/80000, loss=0.2225, lr=0.007802, batch_cost=0.4321, reader_cost=0.0006 | ETA 07:17:07 2020-10-31 12:07:22 [INFO] [TRAIN] epoch=53, iter=19400/80000, loss=0.2340, lr=0.007791, batch_cost=0.4438, reader_cost=0.0090 | ETA 07:28:16 2020-10-31 12:08:06 [INFO] [TRAIN] epoch=53, iter=19500/80000, loss=0.2319, lr=0.007779, batch_cost=0.4332, reader_cost=0.0008 | ETA 07:16:47 2020-10-31 12:08:49 [INFO] [TRAIN] epoch=53, iter=19600/80000, loss=0.2503, lr=0.007768, batch_cost=0.4362, reader_cost=0.0008 | ETA 07:19:06 2020-10-31 12:09:33 [INFO] [TRAIN] epoch=53, iter=19700/80000, loss=0.2364, lr=0.007756, batch_cost=0.4375, reader_cost=0.0012 | ETA 07:19:39 2020-10-31 12:10:17 [INFO] [TRAIN] epoch=54, iter=19800/80000, loss=0.2187, lr=0.007744, batch_cost=0.4402, reader_cost=0.0082 | ETA 07:21:39 2020-10-31 12:11:01 [INFO] [TRAIN] epoch=54, iter=19900/80000, loss=0.2075, lr=0.007733, batch_cost=0.4352, reader_cost=0.0004 | ETA 07:15:54 2020-10-31 12:11:44 [INFO] [TRAIN] epoch=54, iter=20000/80000, loss=0.2498, lr=0.007721, batch_cost=0.4371, reader_cost=0.0004 | ETA 07:17:03 2020-10-31 12:12:29 [INFO] [TRAIN] epoch=55, iter=20100/80000, loss=0.2435, lr=0.007710, batch_cost=0.4431, reader_cost=0.0082 | ETA 07:22:20 2020-10-31 12:13:12 [INFO] [TRAIN] epoch=55, iter=20200/80000, loss=0.2011, lr=0.007698, batch_cost=0.4347, reader_cost=0.0003 | ETA 07:13:12 2020-10-31 12:13:56 [INFO] [TRAIN] epoch=55, iter=20300/80000, loss=0.2369, lr=0.007687, batch_cost=0.4355, reader_cost=0.0009 | ETA 07:13:20 2020-10-31 12:14:39 [INFO] [TRAIN] epoch=55, iter=20400/80000, loss=0.2159, lr=0.007675, batch_cost=0.4348, reader_cost=0.0009 | ETA 07:11:53 2020-10-31 12:15:24 [INFO] [TRAIN] epoch=56, iter=20500/80000, loss=0.2250, lr=0.007663, batch_cost=0.4435, reader_cost=0.0087 | ETA 07:19:45 2020-10-31 12:16:07 [INFO] [TRAIN] epoch=56, iter=20600/80000, loss=0.2144, lr=0.007652, batch_cost=0.4379, reader_cost=0.0005 | ETA 07:13:29 2020-10-31 12:16:51 [INFO] [TRAIN] epoch=56, iter=20700/80000, loss=0.2707, lr=0.007640, batch_cost=0.4378, reader_cost=0.0008 | ETA 07:12:39 2020-10-31 12:17:35 [INFO] [TRAIN] epoch=56, iter=20800/80000, loss=0.2099, lr=0.007629, batch_cost=0.4371, reader_cost=0.0006 | ETA 07:11:14 2020-10-31 12:18:19 [INFO] [TRAIN] epoch=57, iter=20900/80000, loss=0.2130, lr=0.007617, batch_cost=0.4462, reader_cost=0.0080 | ETA 07:19:28 2020-10-31 12:19:03 [INFO] [TRAIN] epoch=57, iter=21000/80000, loss=0.2441, lr=0.007606, batch_cost=0.4342, reader_cost=0.0006 | ETA 07:06:57 2020-10-31 12:19:47 [INFO] [TRAIN] epoch=57, iter=21100/80000, loss=0.2297, lr=0.007594, batch_cost=0.4372, reader_cost=0.0005 | ETA 07:09:12 2020-10-31 12:20:30 [INFO] [TRAIN] epoch=57, iter=21200/80000, loss=0.1863, lr=0.007582, batch_cost=0.4363, reader_cost=0.0007 | ETA 07:07:33 2020-10-31 12:21:15 [INFO] [TRAIN] epoch=58, iter=21300/80000, loss=0.2042, lr=0.007571, batch_cost=0.4437, reader_cost=0.0083 | ETA 07:14:06 2020-10-31 12:21:58 [INFO] [TRAIN] epoch=58, iter=21400/80000, loss=0.2093, lr=0.007559, batch_cost=0.4360, reader_cost=0.0009 | ETA 07:05:49 2020-10-31 12:22:42 [INFO] [TRAIN] epoch=58, iter=21500/80000, loss=0.2315, lr=0.007548, batch_cost=0.4350, reader_cost=0.0010 | ETA 07:04:08 2020-10-31 12:23:26 [INFO] [TRAIN] epoch=59, iter=21600/80000, loss=0.2157, lr=0.007536, batch_cost=0.4444, reader_cost=0.0086 | ETA 07:12:32 2020-10-31 12:24:10 [INFO] [TRAIN] epoch=59, iter=21700/80000, loss=0.2077, lr=0.007524, batch_cost=0.4353, reader_cost=0.0008 | ETA 07:02:59 2020-10-31 12:24:53 [INFO] [TRAIN] epoch=59, iter=21800/80000, loss=0.2198, lr=0.007513, batch_cost=0.4355, reader_cost=0.0009 | ETA 07:02:23 2020-10-31 12:25:37 [INFO] [TRAIN] epoch=59, iter=21900/80000, loss=0.2100, lr=0.007501, batch_cost=0.4349, reader_cost=0.0013 | ETA 07:01:10 2020-10-31 12:26:21 [INFO] [TRAIN] epoch=60, iter=22000/80000, loss=0.2225, lr=0.007490, batch_cost=0.4410, reader_cost=0.0087 | ETA 07:06:19 2020-10-31 12:27:04 [INFO] [TRAIN] epoch=60, iter=22100/80000, loss=0.2350, lr=0.007478, batch_cost=0.4344, reader_cost=0.0012 | ETA 06:59:09 2020-10-31 12:27:48 [INFO] [TRAIN] epoch=60, iter=22200/80000, loss=0.2418, lr=0.007466, batch_cost=0.4351, reader_cost=0.0013 | ETA 06:59:08 2020-10-31 12:28:31 [INFO] [TRAIN] epoch=60, iter=22300/80000, loss=0.2595, lr=0.007455, batch_cost=0.4324, reader_cost=0.0011 | ETA 06:55:51 2020-10-31 12:29:15 [INFO] [TRAIN] epoch=61, iter=22400/80000, loss=0.2464, lr=0.007443, batch_cost=0.4416, reader_cost=0.0078 | ETA 07:03:53 2020-10-31 12:29:59 [INFO] [TRAIN] epoch=61, iter=22500/80000, loss=0.2590, lr=0.007432, batch_cost=0.4340, reader_cost=0.0007 | ETA 06:55:52 2020-10-31 12:30:42 [INFO] [TRAIN] epoch=61, iter=22600/80000, loss=0.3105, lr=0.007420, batch_cost=0.4351, reader_cost=0.0009 | ETA 06:56:12 2020-10-31 12:31:26 [INFO] [TRAIN] epoch=62, iter=22700/80000, loss=0.2171, lr=0.007408, batch_cost=0.4440, reader_cost=0.0083 | ETA 07:04:03 2020-10-31 12:32:10 [INFO] [TRAIN] epoch=62, iter=22800/80000, loss=0.2446, lr=0.007397, batch_cost=0.4343, reader_cost=0.0008 | ETA 06:54:04 2020-10-31 12:32:53 [INFO] [TRAIN] epoch=62, iter=22900/80000, loss=0.2377, lr=0.007385, batch_cost=0.4344, reader_cost=0.0009 | ETA 06:53:22 2020-10-31 12:33:37 [INFO] [TRAIN] epoch=62, iter=23000/80000, loss=0.2237, lr=0.007373, batch_cost=0.4348, reader_cost=0.0010 | ETA 06:53:05 2020-10-31 12:34:21 [INFO] [TRAIN] epoch=63, iter=23100/80000, loss=0.2290, lr=0.007362, batch_cost=0.4435, reader_cost=0.0084 | ETA 07:00:37 2020-10-31 12:35:05 [INFO] [TRAIN] epoch=63, iter=23200/80000, loss=0.2039, lr=0.007350, batch_cost=0.4355, reader_cost=0.0005 | ETA 06:52:14 2020-10-31 12:35:48 [INFO] [TRAIN] epoch=63, iter=23300/80000, loss=0.2442, lr=0.007339, batch_cost=0.4337, reader_cost=0.0008 | ETA 06:49:48 2020-10-31 12:36:32 [INFO] [TRAIN] epoch=63, iter=23400/80000, loss=0.2234, lr=0.007327, batch_cost=0.4362, reader_cost=0.0005 | ETA 06:51:29 2020-10-31 12:37:16 [INFO] [TRAIN] epoch=64, iter=23500/80000, loss=0.2120, lr=0.007315, batch_cost=0.4419, reader_cost=0.0079 | ETA 06:56:09 2020-10-31 12:38:00 [INFO] [TRAIN] epoch=64, iter=23600/80000, loss=0.2343, lr=0.007304, batch_cost=0.4371, reader_cost=0.0005 | ETA 06:50:51 2020-10-31 12:38:43 [INFO] [TRAIN] epoch=64, iter=23700/80000, loss=0.2232, lr=0.007292, batch_cost=0.4297, reader_cost=0.0004 | ETA 06:43:10 2020-10-31 12:39:26 [INFO] [TRAIN] epoch=64, iter=23800/80000, loss=0.2246, lr=0.007280, batch_cost=0.4332, reader_cost=0.0004 | ETA 06:45:43 2020-10-31 12:40:10 [INFO] [TRAIN] epoch=65, iter=23900/80000, loss=0.3079, lr=0.007269, batch_cost=0.4385, reader_cost=0.0083 | ETA 06:49:59 2020-10-31 12:40:53 [INFO] [TRAIN] epoch=65, iter=24000/80000, loss=0.2705, lr=0.007257, batch_cost=0.4301, reader_cost=0.0010 | ETA 06:41:24 2020-10-31 12:40:58 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 12:45:34 [INFO] [EVAL] #Images=500 mIoU=0.7441 Acc=0.9526 Kappa=0.9385 2020-10-31 12:45:34 [INFO] [EVAL] Category IoU: [0.9732 0.8083 0.9084 0.4327 0.5541 0.6166 0.6823 0.7682 0.9164 0.6106 0.9372 0.7965 0.5766 0.9429 0.7738 0.8478 0.6321 0.5982 0.7625] 2020-10-31 12:45:34 [INFO] [EVAL] Category Acc: [0.9882 0.8917 0.948 0.7839 0.8 0.7603 0.8017 0.8705 0.9455 0.8494 0.9686 0.8547 0.7219 0.9712 0.8859 0.9199 0.7338 0.7877 0.8528] 2020-10-31 12:45:37 [INFO] [EVAL] The model with the best validation mIoU (0.7441) was saved at iter 24000. 2020-10-31 12:46:20 [INFO] [TRAIN] epoch=65, iter=24100/80000, loss=0.2502, lr=0.007245, batch_cost=0.4329, reader_cost=0.0006 | ETA 06:43:18 2020-10-31 12:47:04 [INFO] [TRAIN] epoch=66, iter=24200/80000, loss=0.2103, lr=0.007234, batch_cost=0.4416, reader_cost=0.0082 | ETA 06:50:40 2020-10-31 12:47:47 [INFO] [TRAIN] epoch=66, iter=24300/80000, loss=0.2271, lr=0.007222, batch_cost=0.4311, reader_cost=0.0004 | ETA 06:40:09 2020-10-31 12:48:31 [INFO] [TRAIN] epoch=66, iter=24400/80000, loss=0.3175, lr=0.007210, batch_cost=0.4337, reader_cost=0.0006 | ETA 06:41:55 2020-10-31 12:49:14 [INFO] [TRAIN] epoch=66, iter=24500/80000, loss=0.2340, lr=0.007199, batch_cost=0.4355, reader_cost=0.0006 | ETA 06:42:49 2020-10-31 12:49:58 [INFO] [TRAIN] epoch=67, iter=24600/80000, loss=0.2012, lr=0.007187, batch_cost=0.4433, reader_cost=0.0072 | ETA 06:49:18 2020-10-31 12:50:42 [INFO] [TRAIN] epoch=67, iter=24700/80000, loss=0.2399, lr=0.007175, batch_cost=0.4338, reader_cost=0.0010 | ETA 06:39:50 2020-10-31 12:51:25 [INFO] [TRAIN] epoch=67, iter=24800/80000, loss=0.2412, lr=0.007164, batch_cost=0.4349, reader_cost=0.0006 | ETA 06:40:06 2020-10-31 12:52:09 [INFO] [TRAIN] epoch=67, iter=24900/80000, loss=0.2109, lr=0.007152, batch_cost=0.4330, reader_cost=0.0003 | ETA 06:37:36 2020-10-31 12:52:53 [INFO] [TRAIN] epoch=68, iter=25000/80000, loss=0.2155, lr=0.007140, batch_cost=0.4418, reader_cost=0.0077 | ETA 06:45:01 2020-10-31 12:53:36 [INFO] [TRAIN] epoch=68, iter=25100/80000, loss=0.1965, lr=0.007129, batch_cost=0.4324, reader_cost=0.0003 | ETA 06:35:37 2020-10-31 12:54:20 [INFO] [TRAIN] epoch=68, iter=25200/80000, loss=0.2557, lr=0.007117, batch_cost=0.4355, reader_cost=0.0003 | ETA 06:37:46 2020-10-31 12:55:04 [INFO] [TRAIN] epoch=69, iter=25300/80000, loss=0.2149, lr=0.007105, batch_cost=0.4428, reader_cost=0.0067 | ETA 06:43:38 2020-10-31 12:55:47 [INFO] [TRAIN] epoch=69, iter=25400/80000, loss=0.1970, lr=0.007094, batch_cost=0.4339, reader_cost=0.0003 | ETA 06:34:48 2020-10-31 12:56:31 [INFO] [TRAIN] epoch=69, iter=25500/80000, loss=0.2224, lr=0.007082, batch_cost=0.4346, reader_cost=0.0003 | ETA 06:34:47 2020-10-31 12:57:14 [INFO] [TRAIN] epoch=69, iter=25600/80000, loss=0.2341, lr=0.007070, batch_cost=0.4349, reader_cost=0.0005 | ETA 06:34:16 2020-10-31 12:57:58 [INFO] [TRAIN] epoch=70, iter=25700/80000, loss=0.2332, lr=0.007059, batch_cost=0.4414, reader_cost=0.0097 | ETA 06:39:26 2020-10-31 12:58:42 [INFO] [TRAIN] epoch=70, iter=25800/80000, loss=0.2065, lr=0.007047, batch_cost=0.4356, reader_cost=0.0011 | ETA 06:33:27 2020-10-31 12:59:25 [INFO] [TRAIN] epoch=70, iter=25900/80000, loss=0.2327, lr=0.007035, batch_cost=0.4338, reader_cost=0.0012 | ETA 06:31:11 2020-10-31 13:00:09 [INFO] [TRAIN] epoch=70, iter=26000/80000, loss=0.1804, lr=0.007024, batch_cost=0.4361, reader_cost=0.0013 | ETA 06:32:26 2020-10-31 13:00:53 [INFO] [TRAIN] epoch=71, iter=26100/80000, loss=0.2238, lr=0.007012, batch_cost=0.4436, reader_cost=0.0082 | ETA 06:38:31 2020-10-31 13:01:37 [INFO] [TRAIN] epoch=71, iter=26200/80000, loss=0.2272, lr=0.007000, batch_cost=0.4343, reader_cost=0.0006 | ETA 06:29:24 2020-10-31 13:02:20 [INFO] [TRAIN] epoch=71, iter=26300/80000, loss=0.2351, lr=0.006989, batch_cost=0.4355, reader_cost=0.0008 | ETA 06:29:45 2020-10-31 13:03:03 [INFO] [TRAIN] epoch=71, iter=26400/80000, loss=0.2169, lr=0.006977, batch_cost=0.4308, reader_cost=0.0006 | ETA 06:24:51 2020-10-31 13:03:48 [INFO] [TRAIN] epoch=72, iter=26500/80000, loss=0.2335, lr=0.006965, batch_cost=0.4437, reader_cost=0.0081 | ETA 06:35:39 2020-10-31 13:04:31 [INFO] [TRAIN] epoch=72, iter=26600/80000, loss=0.2397, lr=0.006954, batch_cost=0.4343, reader_cost=0.0008 | ETA 06:26:31 2020-10-31 13:05:15 [INFO] [TRAIN] epoch=72, iter=26700/80000, loss=0.1993, lr=0.006942, batch_cost=0.4355, reader_cost=0.0004 | ETA 06:26:49 2020-10-31 13:05:59 [INFO] [TRAIN] epoch=73, iter=26800/80000, loss=0.2103, lr=0.006930, batch_cost=0.4429, reader_cost=0.0081 | ETA 06:32:39 2020-10-31 13:06:42 [INFO] [TRAIN] epoch=73, iter=26900/80000, loss=0.2115, lr=0.006918, batch_cost=0.4336, reader_cost=0.0003 | ETA 06:23:44 2020-10-31 13:07:25 [INFO] [TRAIN] epoch=73, iter=27000/80000, loss=0.2269, lr=0.006907, batch_cost=0.4313, reader_cost=0.0003 | ETA 06:21:01 2020-10-31 13:08:09 [INFO] [TRAIN] epoch=73, iter=27100/80000, loss=0.1932, lr=0.006895, batch_cost=0.4339, reader_cost=0.0004 | ETA 06:22:31 2020-10-31 13:08:53 [INFO] [TRAIN] epoch=74, iter=27200/80000, loss=0.2110, lr=0.006883, batch_cost=0.4408, reader_cost=0.0086 | ETA 06:27:54 2020-10-31 13:09:36 [INFO] [TRAIN] epoch=74, iter=27300/80000, loss=0.2331, lr=0.006872, batch_cost=0.4332, reader_cost=0.0003 | ETA 06:20:30 2020-10-31 13:10:20 [INFO] [TRAIN] epoch=74, iter=27400/80000, loss=0.2014, lr=0.006860, batch_cost=0.4345, reader_cost=0.0003 | ETA 06:20:55 2020-10-31 13:11:03 [INFO] [TRAIN] epoch=74, iter=27500/80000, loss=0.1988, lr=0.006848, batch_cost=0.4334, reader_cost=0.0005 | ETA 06:19:15 2020-10-31 13:11:47 [INFO] [TRAIN] epoch=75, iter=27600/80000, loss=0.2093, lr=0.006836, batch_cost=0.4412, reader_cost=0.0078 | ETA 06:25:19 2020-10-31 13:12:31 [INFO] [TRAIN] epoch=75, iter=27700/80000, loss=0.2144, lr=0.006825, batch_cost=0.4338, reader_cost=0.0005 | ETA 06:18:06 2020-10-31 13:13:14 [INFO] [TRAIN] epoch=75, iter=27800/80000, loss=0.2228, lr=0.006813, batch_cost=0.4362, reader_cost=0.0003 | ETA 06:19:31 2020-10-31 13:13:58 [INFO] [TRAIN] epoch=75, iter=27900/80000, loss=0.1953, lr=0.006801, batch_cost=0.4354, reader_cost=0.0004 | ETA 06:18:02 2020-10-31 13:14:42 [INFO] [TRAIN] epoch=76, iter=28000/80000, loss=0.2106, lr=0.006789, batch_cost=0.4428, reader_cost=0.0073 | ETA 06:23:44 2020-10-31 13:15:25 [INFO] [TRAIN] epoch=76, iter=28100/80000, loss=0.2336, lr=0.006778, batch_cost=0.4337, reader_cost=0.0006 | ETA 06:15:08 2020-10-31 13:16:09 [INFO] [TRAIN] epoch=76, iter=28200/80000, loss=0.2175, lr=0.006766, batch_cost=0.4345, reader_cost=0.0006 | ETA 06:15:08 2020-10-31 13:16:53 [INFO] [TRAIN] epoch=77, iter=28300/80000, loss=0.2223, lr=0.006754, batch_cost=0.4420, reader_cost=0.0083 | ETA 06:20:50 2020-10-31 13:17:36 [INFO] [TRAIN] epoch=77, iter=28400/80000, loss=0.2069, lr=0.006743, batch_cost=0.4333, reader_cost=0.0004 | ETA 06:12:38 2020-10-31 13:18:20 [INFO] [TRAIN] epoch=77, iter=28500/80000, loss=0.2210, lr=0.006731, batch_cost=0.4356, reader_cost=0.0007 | ETA 06:13:53 2020-10-31 13:19:03 [INFO] [TRAIN] epoch=77, iter=28600/80000, loss=0.1935, lr=0.006719, batch_cost=0.4330, reader_cost=0.0008 | ETA 06:10:57 2020-10-31 13:19:47 [INFO] [TRAIN] epoch=78, iter=28700/80000, loss=0.1981, lr=0.006707, batch_cost=0.4427, reader_cost=0.0077 | ETA 06:18:29 2020-10-31 13:20:31 [INFO] [TRAIN] epoch=78, iter=28800/80000, loss=0.1900, lr=0.006696, batch_cost=0.4353, reader_cost=0.0005 | ETA 06:11:27 2020-10-31 13:21:14 [INFO] [TRAIN] epoch=78, iter=28900/80000, loss=0.2180, lr=0.006684, batch_cost=0.4332, reader_cost=0.0003 | ETA 06:08:58 2020-10-31 13:21:58 [INFO] [TRAIN] epoch=78, iter=29000/80000, loss=0.1821, lr=0.006672, batch_cost=0.4351, reader_cost=0.0004 | ETA 06:09:51 2020-10-31 13:22:42 [INFO] [TRAIN] epoch=79, iter=29100/80000, loss=0.2220, lr=0.006660, batch_cost=0.4438, reader_cost=0.0076 | ETA 06:16:30 2020-10-31 13:23:26 [INFO] [TRAIN] epoch=79, iter=29200/80000, loss=0.2048, lr=0.006648, batch_cost=0.4357, reader_cost=0.0004 | ETA 06:08:55 2020-10-31 13:24:09 [INFO] [TRAIN] epoch=79, iter=29300/80000, loss=0.2334, lr=0.006637, batch_cost=0.4357, reader_cost=0.0011 | ETA 06:08:09 2020-10-31 13:24:54 [INFO] [TRAIN] epoch=80, iter=29400/80000, loss=0.1912, lr=0.006625, batch_cost=0.4440, reader_cost=0.0091 | ETA 06:14:24 2020-10-31 13:25:37 [INFO] [TRAIN] epoch=80, iter=29500/80000, loss=0.2208, lr=0.006613, batch_cost=0.4325, reader_cost=0.0004 | ETA 06:04:00 2020-10-31 13:26:20 [INFO] [TRAIN] epoch=80, iter=29600/80000, loss=0.2224, lr=0.006601, batch_cost=0.4324, reader_cost=0.0003 | ETA 06:03:12 2020-10-31 13:27:04 [INFO] [TRAIN] epoch=80, iter=29700/80000, loss=0.1985, lr=0.006590, batch_cost=0.4346, reader_cost=0.0004 | ETA 06:04:21 2020-10-31 13:27:48 [INFO] [TRAIN] epoch=81, iter=29800/80000, loss=0.2038, lr=0.006578, batch_cost=0.4428, reader_cost=0.0086 | ETA 06:10:28 2020-10-31 13:28:32 [INFO] [TRAIN] epoch=81, iter=29900/80000, loss=0.2252, lr=0.006566, batch_cost=0.4362, reader_cost=0.0004 | ETA 06:04:13 2020-10-31 13:29:15 [INFO] [TRAIN] epoch=81, iter=30000/80000, loss=0.2074, lr=0.006554, batch_cost=0.4340, reader_cost=0.0004 | ETA 06:01:38 2020-10-31 13:29:58 [INFO] [TRAIN] epoch=81, iter=30100/80000, loss=0.1963, lr=0.006543, batch_cost=0.4342, reader_cost=0.0003 | ETA 06:01:05 2020-10-31 13:30:43 [INFO] [TRAIN] epoch=82, iter=30200/80000, loss=0.2099, lr=0.006531, batch_cost=0.4444, reader_cost=0.0077 | ETA 06:08:49 2020-10-31 13:31:26 [INFO] [TRAIN] epoch=82, iter=30300/80000, loss=0.2067, lr=0.006519, batch_cost=0.4342, reader_cost=0.0008 | ETA 05:59:38 2020-10-31 13:32:10 [INFO] [TRAIN] epoch=82, iter=30400/80000, loss=0.2213, lr=0.006507, batch_cost=0.4345, reader_cost=0.0007 | ETA 05:59:11 2020-10-31 13:32:53 [INFO] [TRAIN] epoch=82, iter=30500/80000, loss=0.1838, lr=0.006495, batch_cost=0.4338, reader_cost=0.0007 | ETA 05:57:54 2020-10-31 13:33:38 [INFO] [TRAIN] epoch=83, iter=30600/80000, loss=0.1869, lr=0.006484, batch_cost=0.4478, reader_cost=0.0102 | ETA 06:08:39 2020-10-31 13:34:22 [INFO] [TRAIN] epoch=83, iter=30700/80000, loss=0.2463, lr=0.006472, batch_cost=0.4368, reader_cost=0.0010 | ETA 05:58:54 2020-10-31 13:35:05 [INFO] [TRAIN] epoch=83, iter=30800/80000, loss=0.2062, lr=0.006460, batch_cost=0.4349, reader_cost=0.0006 | ETA 05:56:34 2020-10-31 13:35:50 [INFO] [TRAIN] epoch=84, iter=30900/80000, loss=0.1933, lr=0.006448, batch_cost=0.4471, reader_cost=0.0078 | ETA 06:05:54 2020-10-31 13:36:33 [INFO] [TRAIN] epoch=84, iter=31000/80000, loss=0.2490, lr=0.006436, batch_cost=0.4337, reader_cost=0.0003 | ETA 05:54:12 2020-10-31 13:37:17 [INFO] [TRAIN] epoch=84, iter=31100/80000, loss=0.2177, lr=0.006425, batch_cost=0.4345, reader_cost=0.0004 | ETA 05:54:05 2020-10-31 13:38:00 [INFO] [TRAIN] epoch=84, iter=31200/80000, loss=0.2059, lr=0.006413, batch_cost=0.4350, reader_cost=0.0005 | ETA 05:53:47 2020-10-31 13:38:44 [INFO] [TRAIN] epoch=85, iter=31300/80000, loss=0.2023, lr=0.006401, batch_cost=0.4427, reader_cost=0.0078 | ETA 05:59:21 2020-10-31 13:39:28 [INFO] [TRAIN] epoch=85, iter=31400/80000, loss=0.2102, lr=0.006389, batch_cost=0.4338, reader_cost=0.0004 | ETA 05:51:21 2020-10-31 13:40:11 [INFO] [TRAIN] epoch=85, iter=31500/80000, loss=0.2207, lr=0.006377, batch_cost=0.4342, reader_cost=0.0007 | ETA 05:50:58 2020-10-31 13:40:55 [INFO] [TRAIN] epoch=85, iter=31600/80000, loss=0.2065, lr=0.006366, batch_cost=0.4333, reader_cost=0.0003 | ETA 05:49:29 2020-10-31 13:41:39 [INFO] [TRAIN] epoch=86, iter=31700/80000, loss=0.2386, lr=0.006354, batch_cost=0.4416, reader_cost=0.0084 | ETA 05:55:30 2020-10-31 13:42:22 [INFO] [TRAIN] epoch=86, iter=31800/80000, loss=0.2024, lr=0.006342, batch_cost=0.4345, reader_cost=0.0006 | ETA 05:49:01 2020-10-31 13:43:06 [INFO] [TRAIN] epoch=86, iter=31900/80000, loss=0.2006, lr=0.006330, batch_cost=0.4347, reader_cost=0.0011 | ETA 05:48:30 2020-10-31 13:43:50 [INFO] [TRAIN] epoch=87, iter=32000/80000, loss=0.2076, lr=0.006318, batch_cost=0.4426, reader_cost=0.0090 | ETA 05:54:06 2020-10-31 13:43:55 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 13:48:30 [INFO] [EVAL] #Images=500 mIoU=0.7540 Acc=0.9540 Kappa=0.9403 2020-10-31 13:48:30 [INFO] [EVAL] Category IoU: [0.9733 0.8161 0.9081 0.3626 0.5291 0.6102 0.6972 0.7719 0.9221 0.6372 0.9442 0.8149 0.6126 0.9441 0.758 0.866 0.7746 0.6134 0.7701] 2020-10-31 13:48:30 [INFO] [EVAL] Category Acc: [0.9897 0.8868 0.9315 0.8491 0.8012 0.827 0.8363 0.9053 0.9565 0.8429 0.9678 0.9043 0.7828 0.9704 0.878 0.9346 0.9158 0.817 0.8492] 2020-10-31 13:48:33 [INFO] [EVAL] The model with the best validation mIoU (0.7540) was saved at iter 32000. 2020-10-31 13:49:16 [INFO] [TRAIN] epoch=87, iter=32100/80000, loss=0.2067, lr=0.006306, batch_cost=0.4288, reader_cost=0.0008 | ETA 05:42:18 2020-10-31 13:50:00 [INFO] [TRAIN] epoch=87, iter=32200/80000, loss=0.2078, lr=0.006295, batch_cost=0.4350, reader_cost=0.0007 | ETA 05:46:34 2020-10-31 13:50:43 [INFO] [TRAIN] epoch=87, iter=32300/80000, loss=0.1889, lr=0.006283, batch_cost=0.4329, reader_cost=0.0007 | ETA 05:44:10 2020-10-31 13:51:27 [INFO] [TRAIN] epoch=88, iter=32400/80000, loss=0.2067, lr=0.006271, batch_cost=0.4424, reader_cost=0.0084 | ETA 05:51:00 2020-10-31 13:52:10 [INFO] [TRAIN] epoch=88, iter=32500/80000, loss=0.2009, lr=0.006259, batch_cost=0.4318, reader_cost=0.0004 | ETA 05:41:48 2020-10-31 13:52:53 [INFO] [TRAIN] epoch=88, iter=32600/80000, loss=0.1981, lr=0.006247, batch_cost=0.4314, reader_cost=0.0004 | ETA 05:40:46 2020-10-31 13:53:37 [INFO] [TRAIN] epoch=88, iter=32700/80000, loss=0.1804, lr=0.006235, batch_cost=0.4351, reader_cost=0.0003 | ETA 05:43:02 2020-10-31 13:54:21 [INFO] [TRAIN] epoch=89, iter=32800/80000, loss=0.2000, lr=0.006224, batch_cost=0.4433, reader_cost=0.0082 | ETA 05:48:42 2020-10-31 13:55:05 [INFO] [TRAIN] epoch=89, iter=32900/80000, loss=0.1961, lr=0.006212, batch_cost=0.4374, reader_cost=0.0004 | ETA 05:43:19 2020-10-31 13:55:49 [INFO] [TRAIN] epoch=89, iter=33000/80000, loss=0.2060, lr=0.006200, batch_cost=0.4352, reader_cost=0.0005 | ETA 05:40:56 2020-10-31 13:56:32 [INFO] [TRAIN] epoch=89, iter=33100/80000, loss=0.2081, lr=0.006188, batch_cost=0.4359, reader_cost=0.0004 | ETA 05:40:41 2020-10-31 13:57:17 [INFO] [TRAIN] epoch=90, iter=33200/80000, loss=0.1925, lr=0.006176, batch_cost=0.4436, reader_cost=0.0078 | ETA 05:46:00 2020-10-31 13:58:00 [INFO] [TRAIN] epoch=90, iter=33300/80000, loss=0.2081, lr=0.006164, batch_cost=0.4346, reader_cost=0.0007 | ETA 05:38:17 2020-10-31 13:58:43 [INFO] [TRAIN] epoch=90, iter=33400/80000, loss=0.2055, lr=0.006152, batch_cost=0.4332, reader_cost=0.0003 | ETA 05:36:28 2020-10-31 13:59:28 [INFO] [TRAIN] epoch=91, iter=33500/80000, loss=0.1739, lr=0.006141, batch_cost=0.4420, reader_cost=0.0081 | ETA 05:42:32 2020-10-31 14:00:11 [INFO] [TRAIN] epoch=91, iter=33600/80000, loss=0.2109, lr=0.006129, batch_cost=0.4342, reader_cost=0.0008 | ETA 05:35:49 2020-10-31 14:00:54 [INFO] [TRAIN] epoch=91, iter=33700/80000, loss=0.2132, lr=0.006117, batch_cost=0.4349, reader_cost=0.0006 | ETA 05:35:36 2020-10-31 14:01:38 [INFO] [TRAIN] epoch=91, iter=33800/80000, loss=0.2014, lr=0.006105, batch_cost=0.4333, reader_cost=0.0003 | ETA 05:33:38 2020-10-31 14:02:22 [INFO] [TRAIN] epoch=92, iter=33900/80000, loss=0.1790, lr=0.006093, batch_cost=0.4434, reader_cost=0.0087 | ETA 05:40:42 2020-10-31 14:03:06 [INFO] [TRAIN] epoch=92, iter=34000/80000, loss=0.2093, lr=0.006081, batch_cost=0.4338, reader_cost=0.0005 | ETA 05:32:33 2020-10-31 14:03:49 [INFO] [TRAIN] epoch=92, iter=34100/80000, loss=0.2001, lr=0.006069, batch_cost=0.4336, reader_cost=0.0009 | ETA 05:31:41 2020-10-31 14:04:32 [INFO] [TRAIN] epoch=92, iter=34200/80000, loss=0.1805, lr=0.006057, batch_cost=0.4327, reader_cost=0.0010 | ETA 05:30:17 2020-10-31 14:05:17 [INFO] [TRAIN] epoch=93, iter=34300/80000, loss=0.1897, lr=0.006046, batch_cost=0.4438, reader_cost=0.0079 | ETA 05:38:00 2020-10-31 14:06:00 [INFO] [TRAIN] epoch=93, iter=34400/80000, loss=0.1811, lr=0.006034, batch_cost=0.4371, reader_cost=0.0008 | ETA 05:32:12 2020-10-31 14:06:44 [INFO] [TRAIN] epoch=93, iter=34500/80000, loss=0.2387, lr=0.006022, batch_cost=0.4366, reader_cost=0.0003 | ETA 05:31:05 2020-10-31 14:07:28 [INFO] [TRAIN] epoch=94, iter=34600/80000, loss=0.1889, lr=0.006010, batch_cost=0.4418, reader_cost=0.0076 | ETA 05:34:17 2020-10-31 14:08:12 [INFO] [TRAIN] epoch=94, iter=34700/80000, loss=0.1947, lr=0.005998, batch_cost=0.4344, reader_cost=0.0005 | ETA 05:27:58 2020-10-31 14:08:55 [INFO] [TRAIN] epoch=94, iter=34800/80000, loss=0.2323, lr=0.005986, batch_cost=0.4360, reader_cost=0.0012 | ETA 05:28:29 2020-10-31 14:09:39 [INFO] [TRAIN] epoch=94, iter=34900/80000, loss=0.1860, lr=0.005974, batch_cost=0.4359, reader_cost=0.0007 | ETA 05:27:38 2020-10-31 14:10:23 [INFO] [TRAIN] epoch=95, iter=35000/80000, loss=0.1732, lr=0.005962, batch_cost=0.4439, reader_cost=0.0097 | ETA 05:32:55 2020-10-31 14:11:06 [INFO] [TRAIN] epoch=95, iter=35100/80000, loss=0.1946, lr=0.005950, batch_cost=0.4337, reader_cost=0.0007 | ETA 05:24:31 2020-10-31 14:11:50 [INFO] [TRAIN] epoch=95, iter=35200/80000, loss=0.2076, lr=0.005938, batch_cost=0.4344, reader_cost=0.0006 | ETA 05:24:21 2020-10-31 14:12:33 [INFO] [TRAIN] epoch=95, iter=35300/80000, loss=0.1778, lr=0.005927, batch_cost=0.4339, reader_cost=0.0012 | ETA 05:23:15 2020-10-31 14:13:18 [INFO] [TRAIN] epoch=96, iter=35400/80000, loss=0.2037, lr=0.005915, batch_cost=0.4435, reader_cost=0.0092 | ETA 05:29:39 2020-10-31 14:14:01 [INFO] [TRAIN] epoch=96, iter=35500/80000, loss=0.2149, lr=0.005903, batch_cost=0.4351, reader_cost=0.0004 | ETA 05:22:41 2020-10-31 14:14:44 [INFO] [TRAIN] epoch=96, iter=35600/80000, loss=0.2060, lr=0.005891, batch_cost=0.4328, reader_cost=0.0005 | ETA 05:20:18 2020-10-31 14:15:27 [INFO] [TRAIN] epoch=96, iter=35700/80000, loss=0.1787, lr=0.005879, batch_cost=0.4299, reader_cost=0.0003 | ETA 05:17:24 2020-10-31 14:16:11 [INFO] [TRAIN] epoch=97, iter=35800/80000, loss=0.2147, lr=0.005867, batch_cost=0.4382, reader_cost=0.0080 | ETA 05:22:49 2020-10-31 14:16:54 [INFO] [TRAIN] epoch=97, iter=35900/80000, loss=0.2016, lr=0.005855, batch_cost=0.4299, reader_cost=0.0004 | ETA 05:15:58 2020-10-31 14:17:37 [INFO] [TRAIN] epoch=97, iter=36000/80000, loss=0.1871, lr=0.005843, batch_cost=0.4311, reader_cost=0.0007 | ETA 05:16:09 2020-10-31 14:18:21 [INFO] [TRAIN] epoch=98, iter=36100/80000, loss=0.1869, lr=0.005831, batch_cost=0.4400, reader_cost=0.0080 | ETA 05:21:54 2020-10-31 14:19:04 [INFO] [TRAIN] epoch=98, iter=36200/80000, loss=0.1886, lr=0.005819, batch_cost=0.4295, reader_cost=0.0005 | ETA 05:13:33 2020-10-31 14:19:48 [INFO] [TRAIN] epoch=98, iter=36300/80000, loss=0.1821, lr=0.005807, batch_cost=0.4318, reader_cost=0.0006 | ETA 05:14:29 2020-10-31 14:20:31 [INFO] [TRAIN] epoch=98, iter=36400/80000, loss=0.2002, lr=0.005795, batch_cost=0.4305, reader_cost=0.0005 | ETA 05:12:50 2020-10-31 14:21:15 [INFO] [TRAIN] epoch=99, iter=36500/80000, loss=0.1957, lr=0.005783, batch_cost=0.4445, reader_cost=0.0101 | ETA 05:22:16 2020-10-31 14:21:59 [INFO] [TRAIN] epoch=99, iter=36600/80000, loss=0.2104, lr=0.005771, batch_cost=0.4354, reader_cost=0.0012 | ETA 05:14:56 2020-10-31 14:22:42 [INFO] [TRAIN] epoch=99, iter=36700/80000, loss=0.2074, lr=0.005760, batch_cost=0.4384, reader_cost=0.0010 | ETA 05:16:23 2020-10-31 14:23:26 [INFO] [TRAIN] epoch=99, iter=36800/80000, loss=0.1812, lr=0.005748, batch_cost=0.4362, reader_cost=0.0007 | ETA 05:14:02 2020-10-31 14:24:10 [INFO] [TRAIN] epoch=100, iter=36900/80000, loss=0.1998, lr=0.005736, batch_cost=0.4418, reader_cost=0.0081 | ETA 05:17:22 2020-10-31 14:24:54 [INFO] [TRAIN] epoch=100, iter=37000/80000, loss=0.1664, lr=0.005724, batch_cost=0.4349, reader_cost=0.0004 | ETA 05:11:40 2020-10-31 14:25:37 [INFO] [TRAIN] epoch=100, iter=37100/80000, loss=0.1982, lr=0.005712, batch_cost=0.4347, reader_cost=0.0004 | ETA 05:10:46 2020-10-31 14:26:20 [INFO] [TRAIN] epoch=100, iter=37200/80000, loss=0.1810, lr=0.005700, batch_cost=0.4330, reader_cost=0.0008 | ETA 05:08:53 2020-10-31 14:27:05 [INFO] [TRAIN] epoch=101, iter=37300/80000, loss=0.1832, lr=0.005688, batch_cost=0.4447, reader_cost=0.0095 | ETA 05:16:29 2020-10-31 14:27:48 [INFO] [TRAIN] epoch=101, iter=37400/80000, loss=0.2004, lr=0.005676, batch_cost=0.4306, reader_cost=0.0004 | ETA 05:05:44 2020-10-31 14:28:32 [INFO] [TRAIN] epoch=101, iter=37500/80000, loss=0.1941, lr=0.005664, batch_cost=0.4369, reader_cost=0.0007 | ETA 05:09:30 2020-10-31 14:29:16 [INFO] [TRAIN] epoch=102, iter=37600/80000, loss=0.1681, lr=0.005652, batch_cost=0.4408, reader_cost=0.0085 | ETA 05:11:30 2020-10-31 14:29:59 [INFO] [TRAIN] epoch=102, iter=37700/80000, loss=0.2054, lr=0.005640, batch_cost=0.4342, reader_cost=0.0005 | ETA 05:06:08 2020-10-31 14:30:43 [INFO] [TRAIN] epoch=102, iter=37800/80000, loss=0.2012, lr=0.005628, batch_cost=0.4366, reader_cost=0.0005 | ETA 05:07:05 2020-10-31 14:31:26 [INFO] [TRAIN] epoch=102, iter=37900/80000, loss=0.1715, lr=0.005616, batch_cost=0.4329, reader_cost=0.0007 | ETA 05:03:46 2020-10-31 14:32:11 [INFO] [TRAIN] epoch=103, iter=38000/80000, loss=0.2161, lr=0.005604, batch_cost=0.4481, reader_cost=0.0085 | ETA 05:13:42 2020-10-31 14:32:55 [INFO] [TRAIN] epoch=103, iter=38100/80000, loss=0.2082, lr=0.005592, batch_cost=0.4363, reader_cost=0.0005 | ETA 05:04:41 2020-10-31 14:33:38 [INFO] [TRAIN] epoch=103, iter=38200/80000, loss=0.1827, lr=0.005580, batch_cost=0.4358, reader_cost=0.0005 | ETA 05:03:35 2020-10-31 14:34:22 [INFO] [TRAIN] epoch=103, iter=38300/80000, loss=0.1772, lr=0.005568, batch_cost=0.4355, reader_cost=0.0003 | ETA 05:02:39 2020-10-31 14:35:06 [INFO] [TRAIN] epoch=104, iter=38400/80000, loss=0.2053, lr=0.005556, batch_cost=0.4464, reader_cost=0.0090 | ETA 05:09:29 2020-10-31 14:35:50 [INFO] [TRAIN] epoch=104, iter=38500/80000, loss=0.1745, lr=0.005544, batch_cost=0.4333, reader_cost=0.0006 | ETA 04:59:40 2020-10-31 14:36:33 [INFO] [TRAIN] epoch=104, iter=38600/80000, loss=0.1817, lr=0.005532, batch_cost=0.4348, reader_cost=0.0005 | ETA 04:59:59 2020-10-31 14:37:18 [INFO] [TRAIN] epoch=105, iter=38700/80000, loss=0.1856, lr=0.005520, batch_cost=0.4444, reader_cost=0.0089 | ETA 05:05:55 2020-10-31 14:38:01 [INFO] [TRAIN] epoch=105, iter=38800/80000, loss=0.1970, lr=0.005508, batch_cost=0.4359, reader_cost=0.0005 | ETA 04:59:19 2020-10-31 14:38:45 [INFO] [TRAIN] epoch=105, iter=38900/80000, loss=0.2165, lr=0.005496, batch_cost=0.4343, reader_cost=0.0004 | ETA 04:57:31 2020-10-31 14:39:28 [INFO] [TRAIN] epoch=105, iter=39000/80000, loss=0.1792, lr=0.005484, batch_cost=0.4338, reader_cost=0.0007 | ETA 04:56:26 2020-10-31 14:40:12 [INFO] [TRAIN] epoch=106, iter=39100/80000, loss=0.1702, lr=0.005472, batch_cost=0.4440, reader_cost=0.0087 | ETA 05:02:38 2020-10-31 14:40:56 [INFO] [TRAIN] epoch=106, iter=39200/80000, loss=0.1769, lr=0.005460, batch_cost=0.4358, reader_cost=0.0012 | ETA 04:56:20 2020-10-31 14:41:40 [INFO] [TRAIN] epoch=106, iter=39300/80000, loss=0.2248, lr=0.005448, batch_cost=0.4366, reader_cost=0.0008 | ETA 04:56:10 2020-10-31 14:42:23 [INFO] [TRAIN] epoch=106, iter=39400/80000, loss=0.1769, lr=0.005436, batch_cost=0.4370, reader_cost=0.0005 | ETA 04:55:41 2020-10-31 14:43:08 [INFO] [TRAIN] epoch=107, iter=39500/80000, loss=0.1835, lr=0.005424, batch_cost=0.4435, reader_cost=0.0084 | ETA 04:59:22 2020-10-31 14:43:51 [INFO] [TRAIN] epoch=107, iter=39600/80000, loss=0.1918, lr=0.005412, batch_cost=0.4366, reader_cost=0.0011 | ETA 04:53:58 2020-10-31 14:44:35 [INFO] [TRAIN] epoch=107, iter=39700/80000, loss=0.1847, lr=0.005400, batch_cost=0.4345, reader_cost=0.0009 | ETA 04:51:50 2020-10-31 14:45:18 [INFO] [TRAIN] epoch=107, iter=39800/80000, loss=0.1815, lr=0.005388, batch_cost=0.4355, reader_cost=0.0007 | ETA 04:51:45 2020-10-31 14:46:03 [INFO] [TRAIN] epoch=108, iter=39900/80000, loss=0.1892, lr=0.005376, batch_cost=0.4439, reader_cost=0.0081 | ETA 04:56:39 2020-10-31 14:46:46 [INFO] [TRAIN] epoch=108, iter=40000/80000, loss=0.1849, lr=0.005364, batch_cost=0.4346, reader_cost=0.0008 | ETA 04:49:42 2020-10-31 14:46:52 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 14:51:32 [INFO] [EVAL] #Images=500 mIoU=0.7604 Acc=0.9584 Kappa=0.9460 2020-10-31 14:51:32 [INFO] [EVAL] Category IoU: [0.9792 0.8448 0.919 0.4339 0.6018 0.6338 0.7061 0.782 0.9248 0.6318 0.9419 0.823 0.6127 0.9475 0.7167 0.8456 0.6954 0.6281 0.7796] 2020-10-31 14:51:32 [INFO] [EVAL] Category Acc: [0.9913 0.9164 0.9465 0.8164 0.7655 0.8206 0.8427 0.9143 0.9546 0.8202 0.9663 0.8884 0.8245 0.9723 0.9136 0.9282 0.7723 0.8599 0.8637] 2020-10-31 14:51:34 [INFO] [EVAL] The model with the best validation mIoU (0.7604) was saved at iter 40000. 2020-10-31 14:52:17 [INFO] [TRAIN] epoch=108, iter=40100/80000, loss=0.2365, lr=0.005352, batch_cost=0.4310, reader_cost=0.0006 | ETA 04:46:36 2020-10-31 14:53:02 [INFO] [TRAIN] epoch=109, iter=40200/80000, loss=0.1843, lr=0.005340, batch_cost=0.4425, reader_cost=0.0090 | ETA 04:53:31 2020-10-31 14:53:45 [INFO] [TRAIN] epoch=109, iter=40300/80000, loss=0.1872, lr=0.005327, batch_cost=0.4320, reader_cost=0.0006 | ETA 04:45:51 2020-10-31 14:54:28 [INFO] [TRAIN] epoch=109, iter=40400/80000, loss=0.2068, lr=0.005315, batch_cost=0.4319, reader_cost=0.0003 | ETA 04:45:04 2020-10-31 14:55:11 [INFO] [TRAIN] epoch=109, iter=40500/80000, loss=0.1772, lr=0.005303, batch_cost=0.4346, reader_cost=0.0007 | ETA 04:46:06 2020-10-31 14:55:56 [INFO] [TRAIN] epoch=110, iter=40600/80000, loss=0.1858, lr=0.005291, batch_cost=0.4407, reader_cost=0.0082 | ETA 04:49:23 2020-10-31 14:56:39 [INFO] [TRAIN] epoch=110, iter=40700/80000, loss=0.1971, lr=0.005279, batch_cost=0.4327, reader_cost=0.0003 | ETA 04:43:26 2020-10-31 14:57:22 [INFO] [TRAIN] epoch=110, iter=40800/80000, loss=0.1943, lr=0.005267, batch_cost=0.4323, reader_cost=0.0004 | ETA 04:42:26 2020-10-31 14:58:05 [INFO] [TRAIN] epoch=110, iter=40900/80000, loss=0.2160, lr=0.005255, batch_cost=0.4303, reader_cost=0.0003 | ETA 04:40:24 2020-10-31 14:58:49 [INFO] [TRAIN] epoch=111, iter=41000/80000, loss=0.2174, lr=0.005243, batch_cost=0.4404, reader_cost=0.0086 | ETA 04:46:14 2020-10-31 14:59:32 [INFO] [TRAIN] epoch=111, iter=41100/80000, loss=0.1931, lr=0.005231, batch_cost=0.4337, reader_cost=0.0004 | ETA 04:41:10 2020-10-31 15:00:16 [INFO] [TRAIN] epoch=111, iter=41200/80000, loss=0.2256, lr=0.005219, batch_cost=0.4373, reader_cost=0.0004 | ETA 04:42:46 2020-10-31 15:01:01 [INFO] [TRAIN] epoch=112, iter=41300/80000, loss=0.1889, lr=0.005207, batch_cost=0.4439, reader_cost=0.0094 | ETA 04:46:17 2020-10-31 15:01:44 [INFO] [TRAIN] epoch=112, iter=41400/80000, loss=0.1855, lr=0.005195, batch_cost=0.4331, reader_cost=0.0004 | ETA 04:38:36 2020-10-31 15:02:27 [INFO] [TRAIN] epoch=112, iter=41500/80000, loss=0.2094, lr=0.005183, batch_cost=0.4338, reader_cost=0.0005 | ETA 04:38:22 2020-10-31 15:03:11 [INFO] [TRAIN] epoch=112, iter=41600/80000, loss=0.1717, lr=0.005171, batch_cost=0.4359, reader_cost=0.0011 | ETA 04:38:57 2020-10-31 15:03:55 [INFO] [TRAIN] epoch=113, iter=41700/80000, loss=0.1803, lr=0.005158, batch_cost=0.4381, reader_cost=0.0087 | ETA 04:39:38 2020-10-31 15:04:38 [INFO] [TRAIN] epoch=113, iter=41800/80000, loss=0.1736, lr=0.005146, batch_cost=0.4325, reader_cost=0.0003 | ETA 04:35:21 2020-10-31 15:05:21 [INFO] [TRAIN] epoch=113, iter=41900/80000, loss=0.2079, lr=0.005134, batch_cost=0.4353, reader_cost=0.0006 | ETA 04:36:23 2020-10-31 15:06:05 [INFO] [TRAIN] epoch=113, iter=42000/80000, loss=0.1629, lr=0.005122, batch_cost=0.4368, reader_cost=0.0010 | ETA 04:36:38 2020-10-31 15:06:49 [INFO] [TRAIN] epoch=114, iter=42100/80000, loss=0.1939, lr=0.005110, batch_cost=0.4432, reader_cost=0.0084 | ETA 04:39:57 2020-10-31 15:07:33 [INFO] [TRAIN] epoch=114, iter=42200/80000, loss=0.1901, lr=0.005098, batch_cost=0.4331, reader_cost=0.0008 | ETA 04:32:50 2020-10-31 15:08:16 [INFO] [TRAIN] epoch=114, iter=42300/80000, loss=0.2086, lr=0.005086, batch_cost=0.4344, reader_cost=0.0003 | ETA 04:32:55 2020-10-31 15:08:59 [INFO] [TRAIN] epoch=114, iter=42400/80000, loss=0.1732, lr=0.005074, batch_cost=0.4326, reader_cost=0.0006 | ETA 04:31:07 2020-10-31 15:09:44 [INFO] [TRAIN] epoch=115, iter=42500/80000, loss=0.1776, lr=0.005062, batch_cost=0.4417, reader_cost=0.0089 | ETA 04:36:03 2020-10-31 15:10:27 [INFO] [TRAIN] epoch=115, iter=42600/80000, loss=0.2156, lr=0.005049, batch_cost=0.4345, reader_cost=0.0005 | ETA 04:30:50 2020-10-31 15:11:11 [INFO] [TRAIN] epoch=115, iter=42700/80000, loss=0.1886, lr=0.005037, batch_cost=0.4356, reader_cost=0.0007 | ETA 04:30:46 2020-10-31 15:11:55 [INFO] [TRAIN] epoch=116, iter=42800/80000, loss=0.2083, lr=0.005025, batch_cost=0.4433, reader_cost=0.0082 | ETA 04:34:49 2020-10-31 15:12:38 [INFO] [TRAIN] epoch=116, iter=42900/80000, loss=0.2211, lr=0.005013, batch_cost=0.4344, reader_cost=0.0008 | ETA 04:28:37 2020-10-31 15:13:22 [INFO] [TRAIN] epoch=116, iter=43000/80000, loss=0.2056, lr=0.005001, batch_cost=0.4361, reader_cost=0.0007 | ETA 04:28:54 2020-10-31 15:14:05 [INFO] [TRAIN] epoch=116, iter=43100/80000, loss=0.1658, lr=0.004989, batch_cost=0.4335, reader_cost=0.0011 | ETA 04:26:34 2020-10-31 15:14:49 [INFO] [TRAIN] epoch=117, iter=43200/80000, loss=0.2062, lr=0.004977, batch_cost=0.4407, reader_cost=0.0090 | ETA 04:30:18 2020-10-31 15:15:33 [INFO] [TRAIN] epoch=117, iter=43300/80000, loss=0.1906, lr=0.004964, batch_cost=0.4352, reader_cost=0.0004 | ETA 04:26:10 2020-10-31 15:16:16 [INFO] [TRAIN] epoch=117, iter=43400/80000, loss=0.2023, lr=0.004952, batch_cost=0.4348, reader_cost=0.0007 | ETA 04:25:14 2020-10-31 15:17:00 [INFO] [TRAIN] epoch=117, iter=43500/80000, loss=0.1755, lr=0.004940, batch_cost=0.4338, reader_cost=0.0006 | ETA 04:23:53 2020-10-31 15:17:44 [INFO] [TRAIN] epoch=118, iter=43600/80000, loss=0.1876, lr=0.004928, batch_cost=0.4435, reader_cost=0.0082 | ETA 04:29:04 2020-10-31 15:18:28 [INFO] [TRAIN] epoch=118, iter=43700/80000, loss=0.1849, lr=0.004916, batch_cost=0.4348, reader_cost=0.0004 | ETA 04:23:03 2020-10-31 15:19:11 [INFO] [TRAIN] epoch=118, iter=43800/80000, loss=0.2032, lr=0.004904, batch_cost=0.4345, reader_cost=0.0010 | ETA 04:22:09 2020-10-31 15:19:55 [INFO] [TRAIN] epoch=119, iter=43900/80000, loss=0.1747, lr=0.004891, batch_cost=0.4398, reader_cost=0.0078 | ETA 04:24:38 2020-10-31 15:20:39 [INFO] [TRAIN] epoch=119, iter=44000/80000, loss=0.1553, lr=0.004879, batch_cost=0.4350, reader_cost=0.0003 | ETA 04:20:59 2020-10-31 15:21:22 [INFO] [TRAIN] epoch=119, iter=44100/80000, loss=0.1851, lr=0.004867, batch_cost=0.4340, reader_cost=0.0004 | ETA 04:19:40 2020-10-31 15:22:05 [INFO] [TRAIN] epoch=119, iter=44200/80000, loss=0.1818, lr=0.004855, batch_cost=0.4337, reader_cost=0.0008 | ETA 04:18:45 2020-10-31 15:22:50 [INFO] [TRAIN] epoch=120, iter=44300/80000, loss=0.1800, lr=0.004843, batch_cost=0.4422, reader_cost=0.0086 | ETA 04:23:05 2020-10-31 15:23:33 [INFO] [TRAIN] epoch=120, iter=44400/80000, loss=0.1627, lr=0.004831, batch_cost=0.4345, reader_cost=0.0008 | ETA 04:17:49 2020-10-31 15:24:17 [INFO] [TRAIN] epoch=120, iter=44500/80000, loss=0.1846, lr=0.004818, batch_cost=0.4353, reader_cost=0.0009 | ETA 04:17:31 2020-10-31 15:25:00 [INFO] [TRAIN] epoch=120, iter=44600/80000, loss=0.1612, lr=0.004806, batch_cost=0.4363, reader_cost=0.0007 | ETA 04:17:24 2020-10-31 15:25:44 [INFO] [TRAIN] epoch=121, iter=44700/80000, loss=0.1796, lr=0.004794, batch_cost=0.4423, reader_cost=0.0079 | ETA 04:20:12 2020-10-31 15:26:28 [INFO] [TRAIN] epoch=121, iter=44800/80000, loss=0.1928, lr=0.004782, batch_cost=0.4358, reader_cost=0.0008 | ETA 04:15:38 2020-10-31 15:27:12 [INFO] [TRAIN] epoch=121, iter=44900/80000, loss=0.1903, lr=0.004770, batch_cost=0.4351, reader_cost=0.0007 | ETA 04:14:32 2020-10-31 15:27:55 [INFO] [TRAIN] epoch=121, iter=45000/80000, loss=0.1753, lr=0.004757, batch_cost=0.4340, reader_cost=0.0009 | ETA 04:13:11 2020-10-31 15:28:39 [INFO] [TRAIN] epoch=122, iter=45100/80000, loss=0.1627, lr=0.004745, batch_cost=0.4426, reader_cost=0.0086 | ETA 04:17:26 2020-10-31 15:29:22 [INFO] [TRAIN] epoch=122, iter=45200/80000, loss=0.1883, lr=0.004733, batch_cost=0.4328, reader_cost=0.0008 | ETA 04:11:01 2020-10-31 15:30:06 [INFO] [TRAIN] epoch=122, iter=45300/80000, loss=0.2045, lr=0.004721, batch_cost=0.4331, reader_cost=0.0009 | ETA 04:10:29 2020-10-31 15:30:50 [INFO] [TRAIN] epoch=123, iter=45400/80000, loss=0.1814, lr=0.004709, batch_cost=0.4443, reader_cost=0.0080 | ETA 04:16:11 2020-10-31 15:31:34 [INFO] [TRAIN] epoch=123, iter=45500/80000, loss=0.1708, lr=0.004696, batch_cost=0.4343, reader_cost=0.0009 | ETA 04:09:44 2020-10-31 15:32:17 [INFO] [TRAIN] epoch=123, iter=45600/80000, loss=0.1803, lr=0.004684, batch_cost=0.4377, reader_cost=0.0010 | ETA 04:10:58 2020-10-31 15:33:01 [INFO] [TRAIN] epoch=123, iter=45700/80000, loss=0.1798, lr=0.004672, batch_cost=0.4363, reader_cost=0.0009 | ETA 04:09:23 2020-10-31 15:33:45 [INFO] [TRAIN] epoch=124, iter=45800/80000, loss=0.1820, lr=0.004660, batch_cost=0.4432, reader_cost=0.0082 | ETA 04:12:36 2020-10-31 15:34:29 [INFO] [TRAIN] epoch=124, iter=45900/80000, loss=0.1801, lr=0.004647, batch_cost=0.4370, reader_cost=0.0006 | ETA 04:08:20 2020-10-31 15:35:13 [INFO] [TRAIN] epoch=124, iter=46000/80000, loss=0.1891, lr=0.004635, batch_cost=0.4371, reader_cost=0.0008 | ETA 04:07:42 2020-10-31 15:35:56 [INFO] [TRAIN] epoch=124, iter=46100/80000, loss=0.1701, lr=0.004623, batch_cost=0.4360, reader_cost=0.0009 | ETA 04:06:19 2020-10-31 15:36:40 [INFO] [TRAIN] epoch=125, iter=46200/80000, loss=0.2053, lr=0.004611, batch_cost=0.4412, reader_cost=0.0079 | ETA 04:08:32 2020-10-31 15:37:24 [INFO] [TRAIN] epoch=125, iter=46300/80000, loss=0.1815, lr=0.004598, batch_cost=0.4321, reader_cost=0.0003 | ETA 04:02:41 2020-10-31 15:38:07 [INFO] [TRAIN] epoch=125, iter=46400/80000, loss=0.1913, lr=0.004586, batch_cost=0.4324, reader_cost=0.0003 | ETA 04:02:07 2020-10-31 15:38:50 [INFO] [TRAIN] epoch=125, iter=46500/80000, loss=0.1788, lr=0.004574, batch_cost=0.4338, reader_cost=0.0004 | ETA 04:02:11 2020-10-31 15:39:34 [INFO] [TRAIN] epoch=126, iter=46600/80000, loss=0.1773, lr=0.004562, batch_cost=0.4405, reader_cost=0.0093 | ETA 04:05:11 2020-10-31 15:40:18 [INFO] [TRAIN] epoch=126, iter=46700/80000, loss=0.1816, lr=0.004549, batch_cost=0.4329, reader_cost=0.0005 | ETA 04:00:14 2020-10-31 15:41:01 [INFO] [TRAIN] epoch=126, iter=46800/80000, loss=0.1717, lr=0.004537, batch_cost=0.4307, reader_cost=0.0004 | ETA 03:58:19 2020-10-31 15:41:45 [INFO] [TRAIN] epoch=127, iter=46900/80000, loss=0.1765, lr=0.004525, batch_cost=0.4419, reader_cost=0.0080 | ETA 04:03:46 2020-10-31 15:42:28 [INFO] [TRAIN] epoch=127, iter=47000/80000, loss=0.1834, lr=0.004513, batch_cost=0.4356, reader_cost=0.0004 | ETA 03:59:35 2020-10-31 15:43:12 [INFO] [TRAIN] epoch=127, iter=47100/80000, loss=0.1931, lr=0.004500, batch_cost=0.4354, reader_cost=0.0006 | ETA 03:58:44 2020-10-31 15:43:55 [INFO] [TRAIN] epoch=127, iter=47200/80000, loss=0.1724, lr=0.004488, batch_cost=0.4339, reader_cost=0.0004 | ETA 03:57:11 2020-10-31 15:44:39 [INFO] [TRAIN] epoch=128, iter=47300/80000, loss=0.1822, lr=0.004476, batch_cost=0.4395, reader_cost=0.0079 | ETA 03:59:31 2020-10-31 15:45:23 [INFO] [TRAIN] epoch=128, iter=47400/80000, loss=0.2036, lr=0.004463, batch_cost=0.4332, reader_cost=0.0002 | ETA 03:55:21 2020-10-31 15:46:06 [INFO] [TRAIN] epoch=128, iter=47500/80000, loss=0.1804, lr=0.004451, batch_cost=0.4326, reader_cost=0.0003 | ETA 03:54:19 2020-10-31 15:46:49 [INFO] [TRAIN] epoch=128, iter=47600/80000, loss=0.1680, lr=0.004439, batch_cost=0.4329, reader_cost=0.0004 | ETA 03:53:46 2020-10-31 15:47:33 [INFO] [TRAIN] epoch=129, iter=47700/80000, loss=0.1658, lr=0.004427, batch_cost=0.4411, reader_cost=0.0086 | ETA 03:57:26 2020-10-31 15:48:17 [INFO] [TRAIN] epoch=129, iter=47800/80000, loss=0.1800, lr=0.004414, batch_cost=0.4362, reader_cost=0.0005 | ETA 03:54:04 2020-10-31 15:49:00 [INFO] [TRAIN] epoch=129, iter=47900/80000, loss=0.1963, lr=0.004402, batch_cost=0.4340, reader_cost=0.0005 | ETA 03:52:11 2020-10-31 15:49:45 [INFO] [TRAIN] epoch=130, iter=48000/80000, loss=0.1649, lr=0.004390, batch_cost=0.4429, reader_cost=0.0075 | ETA 03:56:11 2020-10-31 15:49:50 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 15:54:23 [INFO] [EVAL] #Images=500 mIoU=0.7553 Acc=0.9556 Kappa=0.9425 2020-10-31 15:54:23 [INFO] [EVAL] Category IoU: [0.9781 0.8368 0.9154 0.4321 0.5898 0.6407 0.7107 0.7872 0.9203 0.6029 0.9443 0.8223 0.6116 0.9432 0.6467 0.8446 0.6993 0.6472 0.7779] 2020-10-31 15:54:23 [INFO] [EVAL] Category Acc: [0.9906 0.9001 0.9643 0.5105 0.8093 0.7878 0.8434 0.8946 0.9488 0.8495 0.9599 0.8926 0.7275 0.9712 0.9541 0.9322 0.7901 0.8338 0.8626] 2020-10-31 15:54:23 [INFO] [EVAL] The model with the best validation mIoU (0.7604) was saved at iter 40000. 2020-10-31 15:55:06 [INFO] [TRAIN] epoch=130, iter=48100/80000, loss=0.1659, lr=0.004377, batch_cost=0.4311, reader_cost=0.0007 | ETA 03:49:10 2020-10-31 15:55:49 [INFO] [TRAIN] epoch=130, iter=48200/80000, loss=0.1856, lr=0.004365, batch_cost=0.4301, reader_cost=0.0005 | ETA 03:47:56 2020-10-31 15:56:32 [INFO] [TRAIN] epoch=130, iter=48300/80000, loss=0.1649, lr=0.004353, batch_cost=0.4310, reader_cost=0.0009 | ETA 03:47:42 2020-10-31 15:57:16 [INFO] [TRAIN] epoch=131, iter=48400/80000, loss=0.1827, lr=0.004340, batch_cost=0.4399, reader_cost=0.0076 | ETA 03:51:39 2020-10-31 15:57:59 [INFO] [TRAIN] epoch=131, iter=48500/80000, loss=0.1986, lr=0.004328, batch_cost=0.4333, reader_cost=0.0003 | ETA 03:47:28 2020-10-31 15:58:43 [INFO] [TRAIN] epoch=131, iter=48600/80000, loss=0.1782, lr=0.004316, batch_cost=0.4348, reader_cost=0.0005 | ETA 03:47:32 2020-10-31 15:59:26 [INFO] [TRAIN] epoch=131, iter=48700/80000, loss=0.1545, lr=0.004303, batch_cost=0.4340, reader_cost=0.0006 | ETA 03:46:24 2020-10-31 16:00:11 [INFO] [TRAIN] epoch=132, iter=48800/80000, loss=0.2015, lr=0.004291, batch_cost=0.4445, reader_cost=0.0084 | ETA 03:51:07 2020-10-31 16:00:54 [INFO] [TRAIN] epoch=132, iter=48900/80000, loss=0.1907, lr=0.004279, batch_cost=0.4355, reader_cost=0.0004 | ETA 03:45:44 2020-10-31 16:01:38 [INFO] [TRAIN] epoch=132, iter=49000/80000, loss=0.2075, lr=0.004266, batch_cost=0.4403, reader_cost=0.0008 | ETA 03:47:30 2020-10-31 16:02:22 [INFO] [TRAIN] epoch=132, iter=49100/80000, loss=0.1931, lr=0.004254, batch_cost=0.4343, reader_cost=0.0010 | ETA 03:43:39 2020-10-31 16:03:06 [INFO] [TRAIN] epoch=133, iter=49200/80000, loss=0.1720, lr=0.004241, batch_cost=0.4420, reader_cost=0.0081 | ETA 03:46:52 2020-10-31 16:03:49 [INFO] [TRAIN] epoch=133, iter=49300/80000, loss=0.1775, lr=0.004229, batch_cost=0.4360, reader_cost=0.0008 | ETA 03:43:05 2020-10-31 16:04:33 [INFO] [TRAIN] epoch=133, iter=49400/80000, loss=0.1733, lr=0.004217, batch_cost=0.4364, reader_cost=0.0010 | ETA 03:42:35 2020-10-31 16:05:18 [INFO] [TRAIN] epoch=134, iter=49500/80000, loss=0.1636, lr=0.004204, batch_cost=0.4448, reader_cost=0.0092 | ETA 03:46:05 2020-10-31 16:06:01 [INFO] [TRAIN] epoch=134, iter=49600/80000, loss=0.1801, lr=0.004192, batch_cost=0.4345, reader_cost=0.0004 | ETA 03:40:10 2020-10-31 16:06:45 [INFO] [TRAIN] epoch=134, iter=49700/80000, loss=0.1848, lr=0.004180, batch_cost=0.4370, reader_cost=0.0010 | ETA 03:40:40 2020-10-31 16:07:28 [INFO] [TRAIN] epoch=134, iter=49800/80000, loss=0.1735, lr=0.004167, batch_cost=0.4356, reader_cost=0.0006 | ETA 03:39:16 2020-10-31 16:08:13 [INFO] [TRAIN] epoch=135, iter=49900/80000, loss=0.1585, lr=0.004155, batch_cost=0.4437, reader_cost=0.0081 | ETA 03:42:36 2020-10-31 16:08:56 [INFO] [TRAIN] epoch=135, iter=50000/80000, loss=0.1580, lr=0.004142, batch_cost=0.4326, reader_cost=0.0006 | ETA 03:36:18 2020-10-31 16:09:40 [INFO] [TRAIN] epoch=135, iter=50100/80000, loss=0.1894, lr=0.004130, batch_cost=0.4367, reader_cost=0.0007 | ETA 03:37:38 2020-10-31 16:10:23 [INFO] [TRAIN] epoch=135, iter=50200/80000, loss=0.1762, lr=0.004118, batch_cost=0.4351, reader_cost=0.0003 | ETA 03:36:05 2020-10-31 16:11:07 [INFO] [TRAIN] epoch=136, iter=50300/80000, loss=0.1796, lr=0.004105, batch_cost=0.4429, reader_cost=0.0081 | ETA 03:39:15 2020-10-31 16:11:51 [INFO] [TRAIN] epoch=136, iter=50400/80000, loss=0.1738, lr=0.004093, batch_cost=0.4355, reader_cost=0.0014 | ETA 03:34:51 2020-10-31 16:12:34 [INFO] [TRAIN] epoch=136, iter=50500/80000, loss=0.1896, lr=0.004080, batch_cost=0.4341, reader_cost=0.0009 | ETA 03:33:26 2020-10-31 16:13:19 [INFO] [TRAIN] epoch=137, iter=50600/80000, loss=0.1557, lr=0.004068, batch_cost=0.4457, reader_cost=0.0097 | ETA 03:38:23 2020-10-31 16:14:02 [INFO] [TRAIN] epoch=137, iter=50700/80000, loss=0.1841, lr=0.004056, batch_cost=0.4345, reader_cost=0.0006 | ETA 03:32:11 2020-10-31 16:14:46 [INFO] [TRAIN] epoch=137, iter=50800/80000, loss=0.1889, lr=0.004043, batch_cost=0.4364, reader_cost=0.0010 | ETA 03:32:23 2020-10-31 16:15:29 [INFO] [TRAIN] epoch=137, iter=50900/80000, loss=0.1953, lr=0.004031, batch_cost=0.4342, reader_cost=0.0008 | ETA 03:30:35 2020-10-31 16:16:14 [INFO] [TRAIN] epoch=138, iter=51000/80000, loss=0.1586, lr=0.004018, batch_cost=0.4418, reader_cost=0.0085 | ETA 03:33:33 2020-10-31 16:16:57 [INFO] [TRAIN] epoch=138, iter=51100/80000, loss=0.1744, lr=0.004006, batch_cost=0.4344, reader_cost=0.0006 | ETA 03:29:13 2020-10-31 16:17:41 [INFO] [TRAIN] epoch=138, iter=51200/80000, loss=0.1929, lr=0.003993, batch_cost=0.4352, reader_cost=0.0012 | ETA 03:28:52 2020-10-31 16:18:24 [INFO] [TRAIN] epoch=138, iter=51300/80000, loss=0.1493, lr=0.003981, batch_cost=0.4359, reader_cost=0.0007 | ETA 03:28:30 2020-10-31 16:19:09 [INFO] [TRAIN] epoch=139, iter=51400/80000, loss=0.1599, lr=0.003968, batch_cost=0.4447, reader_cost=0.0086 | ETA 03:31:57 2020-10-31 16:19:52 [INFO] [TRAIN] epoch=139, iter=51500/80000, loss=0.1723, lr=0.003956, batch_cost=0.4337, reader_cost=0.0006 | ETA 03:26:00 2020-10-31 16:20:36 [INFO] [TRAIN] epoch=139, iter=51600/80000, loss=0.1906, lr=0.003944, batch_cost=0.4368, reader_cost=0.0009 | ETA 03:26:46 2020-10-31 16:21:19 [INFO] [TRAIN] epoch=139, iter=51700/80000, loss=0.1596, lr=0.003931, batch_cost=0.4353, reader_cost=0.0006 | ETA 03:25:18 2020-10-31 16:22:04 [INFO] [TRAIN] epoch=140, iter=51800/80000, loss=0.1628, lr=0.003919, batch_cost=0.4433, reader_cost=0.0083 | ETA 03:28:21 2020-10-31 16:22:47 [INFO] [TRAIN] epoch=140, iter=51900/80000, loss=0.2002, lr=0.003906, batch_cost=0.4374, reader_cost=0.0009 | ETA 03:24:51 2020-10-31 16:23:31 [INFO] [TRAIN] epoch=140, iter=52000/80000, loss=0.2017, lr=0.003894, batch_cost=0.4366, reader_cost=0.0007 | ETA 03:23:45 2020-10-31 16:24:15 [INFO] [TRAIN] epoch=141, iter=52100/80000, loss=0.1681, lr=0.003881, batch_cost=0.4440, reader_cost=0.0076 | ETA 03:26:26 2020-10-31 16:24:59 [INFO] [TRAIN] epoch=141, iter=52200/80000, loss=0.2009, lr=0.003869, batch_cost=0.4357, reader_cost=0.0004 | ETA 03:21:52 2020-10-31 16:25:42 [INFO] [TRAIN] epoch=141, iter=52300/80000, loss=0.1939, lr=0.003856, batch_cost=0.4351, reader_cost=0.0007 | ETA 03:20:50 2020-10-31 16:26:26 [INFO] [TRAIN] epoch=141, iter=52400/80000, loss=0.1659, lr=0.003844, batch_cost=0.4344, reader_cost=0.0006 | ETA 03:19:48 2020-10-31 16:27:10 [INFO] [TRAIN] epoch=142, iter=52500/80000, loss=0.1698, lr=0.003831, batch_cost=0.4427, reader_cost=0.0086 | ETA 03:22:54 2020-10-31 16:27:54 [INFO] [TRAIN] epoch=142, iter=52600/80000, loss=0.1609, lr=0.003819, batch_cost=0.4368, reader_cost=0.0005 | ETA 03:19:27 2020-10-31 16:28:37 [INFO] [TRAIN] epoch=142, iter=52700/80000, loss=0.1990, lr=0.003806, batch_cost=0.4335, reader_cost=0.0003 | ETA 03:17:14 2020-10-31 16:29:21 [INFO] [TRAIN] epoch=142, iter=52800/80000, loss=0.1582, lr=0.003794, batch_cost=0.4335, reader_cost=0.0004 | ETA 03:16:30 2020-10-31 16:30:05 [INFO] [TRAIN] epoch=143, iter=52900/80000, loss=0.1950, lr=0.003781, batch_cost=0.4446, reader_cost=0.0088 | ETA 03:20:48 2020-10-31 16:30:49 [INFO] [TRAIN] epoch=143, iter=53000/80000, loss=0.1705, lr=0.003769, batch_cost=0.4353, reader_cost=0.0006 | ETA 03:15:53 2020-10-31 16:31:32 [INFO] [TRAIN] epoch=143, iter=53100/80000, loss=0.1889, lr=0.003756, batch_cost=0.4335, reader_cost=0.0008 | ETA 03:14:21 2020-10-31 16:32:16 [INFO] [TRAIN] epoch=144, iter=53200/80000, loss=0.1835, lr=0.003744, batch_cost=0.4445, reader_cost=0.0092 | ETA 03:18:33 2020-10-31 16:33:00 [INFO] [TRAIN] epoch=144, iter=53300/80000, loss=0.1480, lr=0.003731, batch_cost=0.4358, reader_cost=0.0004 | ETA 03:13:55 2020-10-31 16:33:44 [INFO] [TRAIN] epoch=144, iter=53400/80000, loss=0.1798, lr=0.003718, batch_cost=0.4367, reader_cost=0.0003 | ETA 03:13:35 2020-10-31 16:34:27 [INFO] [TRAIN] epoch=144, iter=53500/80000, loss=0.1678, lr=0.003706, batch_cost=0.4363, reader_cost=0.0005 | ETA 03:12:40 2020-10-31 16:35:11 [INFO] [TRAIN] epoch=145, iter=53600/80000, loss=0.1680, lr=0.003693, batch_cost=0.4409, reader_cost=0.0084 | ETA 03:13:59 2020-10-31 16:35:55 [INFO] [TRAIN] epoch=145, iter=53700/80000, loss=0.1690, lr=0.003681, batch_cost=0.4360, reader_cost=0.0009 | ETA 03:11:05 2020-10-31 16:36:39 [INFO] [TRAIN] epoch=145, iter=53800/80000, loss=0.1807, lr=0.003668, batch_cost=0.4365, reader_cost=0.0003 | ETA 03:10:36 2020-10-31 16:37:22 [INFO] [TRAIN] epoch=145, iter=53900/80000, loss=0.1633, lr=0.003656, batch_cost=0.4377, reader_cost=0.0008 | ETA 03:10:23 2020-10-31 16:38:07 [INFO] [TRAIN] epoch=146, iter=54000/80000, loss=0.1654, lr=0.003643, batch_cost=0.4465, reader_cost=0.0100 | ETA 03:13:28 2020-10-31 16:38:51 [INFO] [TRAIN] epoch=146, iter=54100/80000, loss=0.1847, lr=0.003631, batch_cost=0.4363, reader_cost=0.0004 | ETA 03:08:19 2020-10-31 16:39:34 [INFO] [TRAIN] epoch=146, iter=54200/80000, loss=0.1669, lr=0.003618, batch_cost=0.4381, reader_cost=0.0014 | ETA 03:08:22 2020-10-31 16:40:18 [INFO] [TRAIN] epoch=146, iter=54300/80000, loss=0.1517, lr=0.003605, batch_cost=0.4359, reader_cost=0.0011 | ETA 03:06:43 2020-10-31 16:41:02 [INFO] [TRAIN] epoch=147, iter=54400/80000, loss=0.1608, lr=0.003593, batch_cost=0.4425, reader_cost=0.0085 | ETA 03:08:47 2020-10-31 16:41:46 [INFO] [TRAIN] epoch=147, iter=54500/80000, loss=0.1684, lr=0.003580, batch_cost=0.4331, reader_cost=0.0006 | ETA 03:04:03 2020-10-31 16:42:29 [INFO] [TRAIN] epoch=147, iter=54600/80000, loss=0.1960, lr=0.003568, batch_cost=0.4322, reader_cost=0.0003 | ETA 03:02:57 2020-10-31 16:43:13 [INFO] [TRAIN] epoch=148, iter=54700/80000, loss=0.1975, lr=0.003555, batch_cost=0.4394, reader_cost=0.0081 | ETA 03:05:17 2020-10-31 16:43:56 [INFO] [TRAIN] epoch=148, iter=54800/80000, loss=0.2543, lr=0.003542, batch_cost=0.4366, reader_cost=0.0008 | ETA 03:03:21 2020-10-31 16:44:40 [INFO] [TRAIN] epoch=148, iter=54900/80000, loss=0.1826, lr=0.003530, batch_cost=0.4315, reader_cost=0.0004 | ETA 03:00:30 2020-10-31 16:45:23 [INFO] [TRAIN] epoch=148, iter=55000/80000, loss=0.1779, lr=0.003517, batch_cost=0.4350, reader_cost=0.0008 | ETA 03:01:15 2020-10-31 16:46:07 [INFO] [TRAIN] epoch=149, iter=55100/80000, loss=0.1798, lr=0.003504, batch_cost=0.4421, reader_cost=0.0091 | ETA 03:03:28 2020-10-31 16:46:51 [INFO] [TRAIN] epoch=149, iter=55200/80000, loss=0.1897, lr=0.003492, batch_cost=0.4336, reader_cost=0.0011 | ETA 02:59:13 2020-10-31 16:47:34 [INFO] [TRAIN] epoch=149, iter=55300/80000, loss=0.1905, lr=0.003479, batch_cost=0.4352, reader_cost=0.0006 | ETA 02:59:09 2020-10-31 16:48:18 [INFO] [TRAIN] epoch=149, iter=55400/80000, loss=0.1684, lr=0.003467, batch_cost=0.4344, reader_cost=0.0012 | ETA 02:58:05 2020-10-31 16:49:02 [INFO] [TRAIN] epoch=150, iter=55500/80000, loss=0.1586, lr=0.003454, batch_cost=0.4421, reader_cost=0.0079 | ETA 03:00:30 2020-10-31 16:49:45 [INFO] [TRAIN] epoch=150, iter=55600/80000, loss=0.1715, lr=0.003441, batch_cost=0.4346, reader_cost=0.0011 | ETA 02:56:43 2020-10-31 16:50:29 [INFO] [TRAIN] epoch=150, iter=55700/80000, loss=0.1920, lr=0.003429, batch_cost=0.4323, reader_cost=0.0010 | ETA 02:55:03 2020-10-31 16:51:12 [INFO] [TRAIN] epoch=150, iter=55800/80000, loss=0.1737, lr=0.003416, batch_cost=0.4365, reader_cost=0.0012 | ETA 02:56:02 2020-10-31 16:51:56 [INFO] [TRAIN] epoch=151, iter=55900/80000, loss=0.1634, lr=0.003403, batch_cost=0.4432, reader_cost=0.0079 | ETA 02:58:01 2020-10-31 16:52:40 [INFO] [TRAIN] epoch=151, iter=56000/80000, loss=0.1913, lr=0.003391, batch_cost=0.4345, reader_cost=0.0007 | ETA 02:53:48 2020-10-31 16:52:45 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 16:57:20 [INFO] [EVAL] #Images=500 mIoU=0.7639 Acc=0.9593 Kappa=0.9471 2020-10-31 16:57:20 [INFO] [EVAL] Category IoU: [0.9802 0.8465 0.9213 0.4152 0.6193 0.6475 0.7157 0.7927 0.9246 0.6133 0.9439 0.8276 0.6282 0.9508 0.6992 0.8288 0.7056 0.6684 0.7859] 2020-10-31 16:57:20 [INFO] [EVAL] Category Acc: [0.9913 0.9097 0.9503 0.868 0.7913 0.8099 0.8392 0.9047 0.9556 0.8469 0.9616 0.8939 0.7865 0.9735 0.8935 0.8684 0.8988 0.8431 0.8663] 2020-10-31 16:57:23 [INFO] [EVAL] The model with the best validation mIoU (0.7639) was saved at iter 56000. 2020-10-31 16:58:06 [INFO] [TRAIN] epoch=151, iter=56100/80000, loss=0.1752, lr=0.003378, batch_cost=0.4293, reader_cost=0.0006 | ETA 02:50:59 2020-10-31 16:58:50 [INFO] [TRAIN] epoch=152, iter=56200/80000, loss=0.1669, lr=0.003365, batch_cost=0.4402, reader_cost=0.0081 | ETA 02:54:36 2020-10-31 16:59:33 [INFO] [TRAIN] epoch=152, iter=56300/80000, loss=0.2192, lr=0.003353, batch_cost=0.4331, reader_cost=0.0006 | ETA 02:51:04 2020-10-31 17:00:17 [INFO] [TRAIN] epoch=152, iter=56400/80000, loss=0.1899, lr=0.003340, batch_cost=0.4345, reader_cost=0.0009 | ETA 02:50:53 2020-10-31 17:01:00 [INFO] [TRAIN] epoch=152, iter=56500/80000, loss=0.1503, lr=0.003327, batch_cost=0.4336, reader_cost=0.0004 | ETA 02:49:50 2020-10-31 17:01:44 [INFO] [TRAIN] epoch=153, iter=56600/80000, loss=0.1662, lr=0.003314, batch_cost=0.4399, reader_cost=0.0075 | ETA 02:51:33 2020-10-31 17:02:27 [INFO] [TRAIN] epoch=153, iter=56700/80000, loss=0.1989, lr=0.003302, batch_cost=0.4332, reader_cost=0.0005 | ETA 02:48:14 2020-10-31 17:03:10 [INFO] [TRAIN] epoch=153, iter=56800/80000, loss=0.1814, lr=0.003289, batch_cost=0.4307, reader_cost=0.0003 | ETA 02:46:33 2020-10-31 17:03:54 [INFO] [TRAIN] epoch=153, iter=56900/80000, loss=0.1669, lr=0.003276, batch_cost=0.4362, reader_cost=0.0009 | ETA 02:47:57 2020-10-31 17:04:39 [INFO] [TRAIN] epoch=154, iter=57000/80000, loss=0.1712, lr=0.003264, batch_cost=0.4469, reader_cost=0.0098 | ETA 02:51:19 2020-10-31 17:05:22 [INFO] [TRAIN] epoch=154, iter=57100/80000, loss=0.1773, lr=0.003251, batch_cost=0.4368, reader_cost=0.0009 | ETA 02:46:43 2020-10-31 17:06:06 [INFO] [TRAIN] epoch=154, iter=57200/80000, loss=0.1851, lr=0.003238, batch_cost=0.4375, reader_cost=0.0009 | ETA 02:46:15 2020-10-31 17:06:50 [INFO] [TRAIN] epoch=155, iter=57300/80000, loss=0.1948, lr=0.003225, batch_cost=0.4423, reader_cost=0.0084 | ETA 02:47:19 2020-10-31 17:07:34 [INFO] [TRAIN] epoch=155, iter=57400/80000, loss=0.1933, lr=0.003213, batch_cost=0.4344, reader_cost=0.0004 | ETA 02:43:36 2020-10-31 17:08:18 [INFO] [TRAIN] epoch=155, iter=57500/80000, loss=0.1892, lr=0.003200, batch_cost=0.4377, reader_cost=0.0007 | ETA 02:44:07 2020-10-31 17:09:01 [INFO] [TRAIN] epoch=155, iter=57600/80000, loss=0.1638, lr=0.003187, batch_cost=0.4334, reader_cost=0.0004 | ETA 02:41:48 2020-10-31 17:09:45 [INFO] [TRAIN] epoch=156, iter=57700/80000, loss=0.1734, lr=0.003174, batch_cost=0.4426, reader_cost=0.0084 | ETA 02:44:30 2020-10-31 17:10:29 [INFO] [TRAIN] epoch=156, iter=57800/80000, loss=0.1583, lr=0.003162, batch_cost=0.4345, reader_cost=0.0006 | ETA 02:40:45 2020-10-31 17:11:12 [INFO] [TRAIN] epoch=156, iter=57900/80000, loss=0.1969, lr=0.003149, batch_cost=0.4338, reader_cost=0.0008 | ETA 02:39:47 2020-10-31 17:11:55 [INFO] [TRAIN] epoch=156, iter=58000/80000, loss=0.1500, lr=0.003136, batch_cost=0.4342, reader_cost=0.0004 | ETA 02:39:11 2020-10-31 17:12:40 [INFO] [TRAIN] epoch=157, iter=58100/80000, loss=0.1647, lr=0.003123, batch_cost=0.4428, reader_cost=0.0089 | ETA 02:41:38 2020-10-31 17:13:23 [INFO] [TRAIN] epoch=157, iter=58200/80000, loss=0.1769, lr=0.003110, batch_cost=0.4337, reader_cost=0.0006 | ETA 02:37:35 2020-10-31 17:14:07 [INFO] [TRAIN] epoch=157, iter=58300/80000, loss=0.1729, lr=0.003098, batch_cost=0.4366, reader_cost=0.0011 | ETA 02:37:54 2020-10-31 17:14:50 [INFO] [TRAIN] epoch=157, iter=58400/80000, loss=0.1565, lr=0.003085, batch_cost=0.4368, reader_cost=0.0013 | ETA 02:37:15 2020-10-31 17:15:35 [INFO] [TRAIN] epoch=158, iter=58500/80000, loss=0.1440, lr=0.003072, batch_cost=0.4421, reader_cost=0.0078 | ETA 02:38:24 2020-10-31 17:16:18 [INFO] [TRAIN] epoch=158, iter=58600/80000, loss=0.1649, lr=0.003059, batch_cost=0.4319, reader_cost=0.0008 | ETA 02:34:03 2020-10-31 17:17:01 [INFO] [TRAIN] epoch=158, iter=58700/80000, loss=0.1757, lr=0.003046, batch_cost=0.4343, reader_cost=0.0005 | ETA 02:34:11 2020-10-31 17:17:45 [INFO] [TRAIN] epoch=159, iter=58800/80000, loss=0.1502, lr=0.003033, batch_cost=0.4426, reader_cost=0.0088 | ETA 02:36:24 2020-10-31 17:18:29 [INFO] [TRAIN] epoch=159, iter=58900/80000, loss=0.1662, lr=0.003021, batch_cost=0.4360, reader_cost=0.0009 | ETA 02:33:20 2020-10-31 17:19:13 [INFO] [TRAIN] epoch=159, iter=59000/80000, loss=0.1785, lr=0.003008, batch_cost=0.4348, reader_cost=0.0008 | ETA 02:32:11 2020-10-31 17:19:56 [INFO] [TRAIN] epoch=159, iter=59100/80000, loss=0.1656, lr=0.002995, batch_cost=0.4337, reader_cost=0.0006 | ETA 02:31:03 2020-10-31 17:20:40 [INFO] [TRAIN] epoch=160, iter=59200/80000, loss=0.1614, lr=0.002982, batch_cost=0.4445, reader_cost=0.0091 | ETA 02:34:05 2020-10-31 17:21:24 [INFO] [TRAIN] epoch=160, iter=59300/80000, loss=0.1571, lr=0.002969, batch_cost=0.4351, reader_cost=0.0005 | ETA 02:30:06 2020-10-31 17:22:07 [INFO] [TRAIN] epoch=160, iter=59400/80000, loss=0.1733, lr=0.002956, batch_cost=0.4342, reader_cost=0.0003 | ETA 02:29:05 2020-10-31 17:22:51 [INFO] [TRAIN] epoch=160, iter=59500/80000, loss=0.1568, lr=0.002943, batch_cost=0.4338, reader_cost=0.0007 | ETA 02:28:12 2020-10-31 17:23:35 [INFO] [TRAIN] epoch=161, iter=59600/80000, loss=0.1586, lr=0.002931, batch_cost=0.4426, reader_cost=0.0082 | ETA 02:30:28 2020-10-31 17:24:18 [INFO] [TRAIN] epoch=161, iter=59700/80000, loss=0.1634, lr=0.002918, batch_cost=0.4340, reader_cost=0.0004 | ETA 02:26:49 2020-10-31 17:25:02 [INFO] [TRAIN] epoch=161, iter=59800/80000, loss=0.1699, lr=0.002905, batch_cost=0.4347, reader_cost=0.0003 | ETA 02:26:20 2020-10-31 17:25:46 [INFO] [TRAIN] epoch=162, iter=59900/80000, loss=0.1553, lr=0.002892, batch_cost=0.4441, reader_cost=0.0090 | ETA 02:28:47 2020-10-31 17:26:30 [INFO] [TRAIN] epoch=162, iter=60000/80000, loss=0.1580, lr=0.002879, batch_cost=0.4330, reader_cost=0.0006 | ETA 02:24:19 2020-10-31 17:27:13 [INFO] [TRAIN] epoch=162, iter=60100/80000, loss=0.1636, lr=0.002866, batch_cost=0.4312, reader_cost=0.0004 | ETA 02:23:01 2020-10-31 17:27:56 [INFO] [TRAIN] epoch=162, iter=60200/80000, loss=0.1622, lr=0.002853, batch_cost=0.4340, reader_cost=0.0007 | ETA 02:23:13 2020-10-31 17:28:40 [INFO] [TRAIN] epoch=163, iter=60300/80000, loss=0.1578, lr=0.002840, batch_cost=0.4405, reader_cost=0.0080 | ETA 02:24:37 2020-10-31 17:29:24 [INFO] [TRAIN] epoch=163, iter=60400/80000, loss=0.1662, lr=0.002827, batch_cost=0.4342, reader_cost=0.0008 | ETA 02:21:49 2020-10-31 17:30:07 [INFO] [TRAIN] epoch=163, iter=60500/80000, loss=0.1764, lr=0.002814, batch_cost=0.4335, reader_cost=0.0009 | ETA 02:20:53 2020-10-31 17:30:50 [INFO] [TRAIN] epoch=163, iter=60600/80000, loss=0.1553, lr=0.002801, batch_cost=0.4313, reader_cost=0.0010 | ETA 02:19:27 2020-10-31 17:31:34 [INFO] [TRAIN] epoch=164, iter=60700/80000, loss=0.1684, lr=0.002788, batch_cost=0.4400, reader_cost=0.0084 | ETA 02:21:32 2020-10-31 17:32:17 [INFO] [TRAIN] epoch=164, iter=60800/80000, loss=0.1850, lr=0.002776, batch_cost=0.4275, reader_cost=0.0005 | ETA 02:16:48 2020-10-31 17:33:00 [INFO] [TRAIN] epoch=164, iter=60900/80000, loss=0.1854, lr=0.002763, batch_cost=0.4296, reader_cost=0.0012 | ETA 02:16:44 2020-10-31 17:33:43 [INFO] [TRAIN] epoch=164, iter=61000/80000, loss=0.1478, lr=0.002750, batch_cost=0.4284, reader_cost=0.0005 | ETA 02:15:40 2020-10-31 17:34:27 [INFO] [TRAIN] epoch=165, iter=61100/80000, loss=0.1658, lr=0.002737, batch_cost=0.4424, reader_cost=0.0097 | ETA 02:19:22 2020-10-31 17:35:10 [INFO] [TRAIN] epoch=165, iter=61200/80000, loss=0.1860, lr=0.002724, batch_cost=0.4290, reader_cost=0.0006 | ETA 02:14:25 2020-10-31 17:35:53 [INFO] [TRAIN] epoch=165, iter=61300/80000, loss=0.1771, lr=0.002711, batch_cost=0.4286, reader_cost=0.0004 | ETA 02:13:35 2020-10-31 17:36:36 [INFO] [TRAIN] epoch=166, iter=61400/80000, loss=0.1481, lr=0.002698, batch_cost=0.4369, reader_cost=0.0085 | ETA 02:15:25 2020-10-31 17:37:19 [INFO] [TRAIN] epoch=166, iter=61500/80000, loss=0.1763, lr=0.002685, batch_cost=0.4304, reader_cost=0.0008 | ETA 02:12:42 2020-10-31 17:38:03 [INFO] [TRAIN] epoch=166, iter=61600/80000, loss=0.1975, lr=0.002672, batch_cost=0.4323, reader_cost=0.0010 | ETA 02:12:33 2020-10-31 17:38:46 [INFO] [TRAIN] epoch=166, iter=61700/80000, loss=0.1604, lr=0.002659, batch_cost=0.4334, reader_cost=0.0008 | ETA 02:12:10 2020-10-31 17:39:30 [INFO] [TRAIN] epoch=167, iter=61800/80000, loss=0.1618, lr=0.002646, batch_cost=0.4382, reader_cost=0.0081 | ETA 02:12:55 2020-10-31 17:40:13 [INFO] [TRAIN] epoch=167, iter=61900/80000, loss=0.1476, lr=0.002633, batch_cost=0.4342, reader_cost=0.0004 | ETA 02:10:59 2020-10-31 17:40:57 [INFO] [TRAIN] epoch=167, iter=62000/80000, loss=0.1827, lr=0.002619, batch_cost=0.4334, reader_cost=0.0004 | ETA 02:10:00 2020-10-31 17:41:40 [INFO] [TRAIN] epoch=167, iter=62100/80000, loss=0.1459, lr=0.002606, batch_cost=0.4354, reader_cost=0.0005 | ETA 02:09:53 2020-10-31 17:42:24 [INFO] [TRAIN] epoch=168, iter=62200/80000, loss=0.1498, lr=0.002593, batch_cost=0.4400, reader_cost=0.0076 | ETA 02:10:31 2020-10-31 17:43:07 [INFO] [TRAIN] epoch=168, iter=62300/80000, loss=0.1547, lr=0.002580, batch_cost=0.4310, reader_cost=0.0004 | ETA 02:07:08 2020-10-31 17:43:51 [INFO] [TRAIN] epoch=168, iter=62400/80000, loss=0.1868, lr=0.002567, batch_cost=0.4357, reader_cost=0.0002 | ETA 02:07:48 2020-10-31 17:44:35 [INFO] [TRAIN] epoch=169, iter=62500/80000, loss=0.1605, lr=0.002554, batch_cost=0.4392, reader_cost=0.0087 | ETA 02:08:05 2020-10-31 17:45:18 [INFO] [TRAIN] epoch=169, iter=62600/80000, loss=0.1587, lr=0.002541, batch_cost=0.4305, reader_cost=0.0009 | ETA 02:04:49 2020-10-31 17:46:01 [INFO] [TRAIN] epoch=169, iter=62700/80000, loss=0.1859, lr=0.002528, batch_cost=0.4323, reader_cost=0.0007 | ETA 02:04:38 2020-10-31 17:46:44 [INFO] [TRAIN] epoch=169, iter=62800/80000, loss=0.1555, lr=0.002515, batch_cost=0.4326, reader_cost=0.0009 | ETA 02:03:59 2020-10-31 17:47:28 [INFO] [TRAIN] epoch=170, iter=62900/80000, loss=0.1643, lr=0.002502, batch_cost=0.4403, reader_cost=0.0085 | ETA 02:05:29 2020-10-31 17:48:11 [INFO] [TRAIN] epoch=170, iter=63000/80000, loss=0.1885, lr=0.002489, batch_cost=0.4320, reader_cost=0.0004 | ETA 02:02:23 2020-10-31 17:48:54 [INFO] [TRAIN] epoch=170, iter=63100/80000, loss=0.1672, lr=0.002476, batch_cost=0.4286, reader_cost=0.0004 | ETA 02:00:42 2020-10-31 17:49:37 [INFO] [TRAIN] epoch=170, iter=63200/80000, loss=0.1509, lr=0.002462, batch_cost=0.4284, reader_cost=0.0005 | ETA 01:59:56 2020-10-31 17:50:21 [INFO] [TRAIN] epoch=171, iter=63300/80000, loss=0.1605, lr=0.002449, batch_cost=0.4386, reader_cost=0.0081 | ETA 02:02:03 2020-10-31 17:51:04 [INFO] [TRAIN] epoch=171, iter=63400/80000, loss=0.1574, lr=0.002436, batch_cost=0.4301, reader_cost=0.0008 | ETA 01:58:59 2020-10-31 17:51:47 [INFO] [TRAIN] epoch=171, iter=63500/80000, loss=0.1515, lr=0.002423, batch_cost=0.4297, reader_cost=0.0008 | ETA 01:58:10 2020-10-31 17:52:30 [INFO] [TRAIN] epoch=171, iter=63600/80000, loss=0.1642, lr=0.002410, batch_cost=0.4276, reader_cost=0.0003 | ETA 01:56:52 2020-10-31 17:53:14 [INFO] [TRAIN] epoch=172, iter=63700/80000, loss=0.1547, lr=0.002397, batch_cost=0.4407, reader_cost=0.0091 | ETA 01:59:42 2020-10-31 17:53:57 [INFO] [TRAIN] epoch=172, iter=63800/80000, loss=0.1695, lr=0.002383, batch_cost=0.4327, reader_cost=0.0003 | ETA 01:56:49 2020-10-31 17:54:40 [INFO] [TRAIN] epoch=172, iter=63900/80000, loss=0.1867, lr=0.002370, batch_cost=0.4335, reader_cost=0.0010 | ETA 01:56:18 2020-10-31 17:55:24 [INFO] [TRAIN] epoch=173, iter=64000/80000, loss=0.1446, lr=0.002357, batch_cost=0.4383, reader_cost=0.0077 | ETA 01:56:52 2020-10-31 17:55:29 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 17:59:55 [INFO] [EVAL] #Images=500 mIoU=0.7670 Acc=0.9612 Kappa=0.9496 2020-10-31 17:59:55 [INFO] [EVAL] Category IoU: [0.9829 0.8638 0.9232 0.443 0.6216 0.6547 0.7199 0.7979 0.9252 0.6536 0.9451 0.8318 0.6398 0.9527 0.7088 0.8209 0.6272 0.6792 0.7819] 2020-10-31 17:59:55 [INFO] [EVAL] Category Acc: [0.9914 0.9302 0.954 0.8516 0.8116 0.82 0.8453 0.905 0.9526 0.8485 0.9624 0.8995 0.7968 0.9734 0.9314 0.874 0.9605 0.8565 0.8457] 2020-10-31 17:59:57 [INFO] [EVAL] The model with the best validation mIoU (0.7670) was saved at iter 64000. 2020-10-31 18:00:40 [INFO] [TRAIN] epoch=173, iter=64100/80000, loss=0.1925, lr=0.002344, batch_cost=0.4302, reader_cost=0.0004 | ETA 01:54:00 2020-10-31 18:01:23 [INFO] [TRAIN] epoch=173, iter=64200/80000, loss=0.1735, lr=0.002331, batch_cost=0.4301, reader_cost=0.0004 | ETA 01:53:15 2020-10-31 18:02:06 [INFO] [TRAIN] epoch=173, iter=64300/80000, loss=0.1594, lr=0.002317, batch_cost=0.4298, reader_cost=0.0004 | ETA 01:52:27 2020-10-31 18:02:50 [INFO] [TRAIN] epoch=174, iter=64400/80000, loss=0.1409, lr=0.002304, batch_cost=0.4376, reader_cost=0.0092 | ETA 01:53:47 2020-10-31 18:03:33 [INFO] [TRAIN] epoch=174, iter=64500/80000, loss=0.1531, lr=0.002291, batch_cost=0.4278, reader_cost=0.0005 | ETA 01:50:30 2020-10-31 18:04:16 [INFO] [TRAIN] epoch=174, iter=64600/80000, loss=0.1810, lr=0.002278, batch_cost=0.4289, reader_cost=0.0004 | ETA 01:50:05 2020-10-31 18:04:59 [INFO] [TRAIN] epoch=174, iter=64700/80000, loss=0.1462, lr=0.002264, batch_cost=0.4301, reader_cost=0.0006 | ETA 01:49:40 2020-10-31 18:05:43 [INFO] [TRAIN] epoch=175, iter=64800/80000, loss=0.1576, lr=0.002251, batch_cost=0.4386, reader_cost=0.0091 | ETA 01:51:06 2020-10-31 18:06:25 [INFO] [TRAIN] epoch=175, iter=64900/80000, loss=0.1707, lr=0.002238, batch_cost=0.4276, reader_cost=0.0004 | ETA 01:47:36 2020-10-31 18:07:08 [INFO] [TRAIN] epoch=175, iter=65000/80000, loss=0.1701, lr=0.002225, batch_cost=0.4285, reader_cost=0.0002 | ETA 01:47:07 2020-10-31 18:07:51 [INFO] [TRAIN] epoch=175, iter=65100/80000, loss=0.1510, lr=0.002211, batch_cost=0.4285, reader_cost=0.0004 | ETA 01:46:24 2020-10-31 18:08:35 [INFO] [TRAIN] epoch=176, iter=65200/80000, loss=0.1591, lr=0.002198, batch_cost=0.4363, reader_cost=0.0069 | ETA 01:47:37 2020-10-31 18:09:17 [INFO] [TRAIN] epoch=176, iter=65300/80000, loss=0.1592, lr=0.002185, batch_cost=0.4280, reader_cost=0.0002 | ETA 01:44:52 2020-10-31 18:10:00 [INFO] [TRAIN] epoch=176, iter=65400/80000, loss=0.1575, lr=0.002171, batch_cost=0.4296, reader_cost=0.0004 | ETA 01:44:32 2020-10-31 18:10:44 [INFO] [TRAIN] epoch=177, iter=65500/80000, loss=0.1458, lr=0.002158, batch_cost=0.4376, reader_cost=0.0096 | ETA 01:45:45 2020-10-31 18:11:27 [INFO] [TRAIN] epoch=177, iter=65600/80000, loss=0.1609, lr=0.002145, batch_cost=0.4303, reader_cost=0.0004 | ETA 01:43:15 2020-10-31 18:12:10 [INFO] [TRAIN] epoch=177, iter=65700/80000, loss=0.1705, lr=0.002131, batch_cost=0.4306, reader_cost=0.0002 | ETA 01:42:36 2020-10-31 18:12:53 [INFO] [TRAIN] epoch=177, iter=65800/80000, loss=0.1505, lr=0.002118, batch_cost=0.4319, reader_cost=0.0007 | ETA 01:42:13 2020-10-31 18:13:38 [INFO] [TRAIN] epoch=178, iter=65900/80000, loss=0.1470, lr=0.002105, batch_cost=0.4404, reader_cost=0.0092 | ETA 01:43:30 2020-10-31 18:14:21 [INFO] [TRAIN] epoch=178, iter=66000/80000, loss=0.1665, lr=0.002091, batch_cost=0.4339, reader_cost=0.0005 | ETA 01:41:14 2020-10-31 18:15:04 [INFO] [TRAIN] epoch=178, iter=66100/80000, loss=0.1719, lr=0.002078, batch_cost=0.4325, reader_cost=0.0003 | ETA 01:40:11 2020-10-31 18:15:47 [INFO] [TRAIN] epoch=178, iter=66200/80000, loss=0.1563, lr=0.002064, batch_cost=0.4315, reader_cost=0.0006 | ETA 01:39:14 2020-10-31 18:16:31 [INFO] [TRAIN] epoch=179, iter=66300/80000, loss=0.1537, lr=0.002051, batch_cost=0.4387, reader_cost=0.0077 | ETA 01:40:10 2020-10-31 18:17:14 [INFO] [TRAIN] epoch=179, iter=66400/80000, loss=0.1578, lr=0.002038, batch_cost=0.4301, reader_cost=0.0004 | ETA 01:37:29 2020-10-31 18:17:57 [INFO] [TRAIN] epoch=179, iter=66500/80000, loss=0.1588, lr=0.002024, batch_cost=0.4311, reader_cost=0.0004 | ETA 01:36:59 2020-10-31 18:18:41 [INFO] [TRAIN] epoch=180, iter=66600/80000, loss=0.1585, lr=0.002011, batch_cost=0.4373, reader_cost=0.0082 | ETA 01:37:39 2020-10-31 18:19:25 [INFO] [TRAIN] epoch=180, iter=66700/80000, loss=0.1582, lr=0.001997, batch_cost=0.4355, reader_cost=0.0004 | ETA 01:36:31 2020-10-31 18:20:08 [INFO] [TRAIN] epoch=180, iter=66800/80000, loss=0.1728, lr=0.001984, batch_cost=0.4337, reader_cost=0.0006 | ETA 01:35:24 2020-10-31 18:20:51 [INFO] [TRAIN] epoch=180, iter=66900/80000, loss=0.1637, lr=0.001970, batch_cost=0.4334, reader_cost=0.0006 | ETA 01:34:36 2020-10-31 18:21:36 [INFO] [TRAIN] epoch=181, iter=67000/80000, loss=0.1449, lr=0.001957, batch_cost=0.4427, reader_cost=0.0077 | ETA 01:35:54 2020-10-31 18:22:19 [INFO] [TRAIN] epoch=181, iter=67100/80000, loss=0.1486, lr=0.001944, batch_cost=0.4337, reader_cost=0.0003 | ETA 01:33:14 2020-10-31 18:23:02 [INFO] [TRAIN] epoch=181, iter=67200/80000, loss=0.1710, lr=0.001930, batch_cost=0.4335, reader_cost=0.0004 | ETA 01:32:28 2020-10-31 18:23:45 [INFO] [TRAIN] epoch=181, iter=67300/80000, loss=0.1362, lr=0.001917, batch_cost=0.4302, reader_cost=0.0006 | ETA 01:31:03 2020-10-31 18:24:30 [INFO] [TRAIN] epoch=182, iter=67400/80000, loss=0.1564, lr=0.001903, batch_cost=0.4421, reader_cost=0.0096 | ETA 01:32:50 2020-10-31 18:25:13 [INFO] [TRAIN] epoch=182, iter=67500/80000, loss=0.1551, lr=0.001889, batch_cost=0.4342, reader_cost=0.0008 | ETA 01:30:27 2020-10-31 18:25:56 [INFO] [TRAIN] epoch=182, iter=67600/80000, loss=0.1640, lr=0.001876, batch_cost=0.4316, reader_cost=0.0005 | ETA 01:29:11 2020-10-31 18:26:39 [INFO] [TRAIN] epoch=182, iter=67700/80000, loss=0.1414, lr=0.001862, batch_cost=0.4304, reader_cost=0.0004 | ETA 01:28:13 2020-10-31 18:27:23 [INFO] [TRAIN] epoch=183, iter=67800/80000, loss=0.1540, lr=0.001849, batch_cost=0.4404, reader_cost=0.0078 | ETA 01:29:32 2020-10-31 18:28:06 [INFO] [TRAIN] epoch=183, iter=67900/80000, loss=0.1664, lr=0.001835, batch_cost=0.4320, reader_cost=0.0003 | ETA 01:27:07 2020-10-31 18:28:49 [INFO] [TRAIN] epoch=183, iter=68000/80000, loss=0.1565, lr=0.001822, batch_cost=0.4309, reader_cost=0.0003 | ETA 01:26:10 2020-10-31 18:29:33 [INFO] [TRAIN] epoch=184, iter=68100/80000, loss=0.1440, lr=0.001808, batch_cost=0.4388, reader_cost=0.0080 | ETA 01:27:01 2020-10-31 18:30:17 [INFO] [TRAIN] epoch=184, iter=68200/80000, loss=0.1743, lr=0.001794, batch_cost=0.4350, reader_cost=0.0003 | ETA 01:25:33 2020-10-31 18:31:00 [INFO] [TRAIN] epoch=184, iter=68300/80000, loss=0.1632, lr=0.001781, batch_cost=0.4360, reader_cost=0.0004 | ETA 01:25:01 2020-10-31 18:31:44 [INFO] [TRAIN] epoch=184, iter=68400/80000, loss=0.1522, lr=0.001767, batch_cost=0.4335, reader_cost=0.0008 | ETA 01:23:48 2020-10-31 18:32:28 [INFO] [TRAIN] epoch=185, iter=68500/80000, loss=0.1496, lr=0.001754, batch_cost=0.4420, reader_cost=0.0079 | ETA 01:24:43 2020-10-31 18:33:11 [INFO] [TRAIN] epoch=185, iter=68600/80000, loss=0.1535, lr=0.001740, batch_cost=0.4347, reader_cost=0.0005 | ETA 01:22:36 2020-10-31 18:33:55 [INFO] [TRAIN] epoch=185, iter=68700/80000, loss=0.1630, lr=0.001726, batch_cost=0.4343, reader_cost=0.0005 | ETA 01:21:47 2020-10-31 18:34:38 [INFO] [TRAIN] epoch=185, iter=68800/80000, loss=0.1530, lr=0.001713, batch_cost=0.4344, reader_cost=0.0004 | ETA 01:21:04 2020-10-31 18:35:22 [INFO] [TRAIN] epoch=186, iter=68900/80000, loss=0.1869, lr=0.001699, batch_cost=0.4403, reader_cost=0.0079 | ETA 01:21:27 2020-10-31 18:36:06 [INFO] [TRAIN] epoch=186, iter=69000/80000, loss=0.1806, lr=0.001685, batch_cost=0.4381, reader_cost=0.0004 | ETA 01:20:18 2020-10-31 18:36:50 [INFO] [TRAIN] epoch=186, iter=69100/80000, loss=0.1735, lr=0.001672, batch_cost=0.4351, reader_cost=0.0004 | ETA 01:19:02 2020-10-31 18:37:33 [INFO] [TRAIN] epoch=187, iter=69200/80000, loss=0.1600, lr=0.001658, batch_cost=0.4372, reader_cost=0.0087 | ETA 01:18:41 2020-10-31 18:38:16 [INFO] [TRAIN] epoch=187, iter=69300/80000, loss=0.1481, lr=0.001644, batch_cost=0.4277, reader_cost=0.0005 | ETA 01:16:16 2020-10-31 18:38:59 [INFO] [TRAIN] epoch=187, iter=69400/80000, loss=0.1664, lr=0.001630, batch_cost=0.4318, reader_cost=0.0004 | ETA 01:16:16 2020-10-31 18:39:42 [INFO] [TRAIN] epoch=187, iter=69500/80000, loss=0.1564, lr=0.001617, batch_cost=0.4289, reader_cost=0.0007 | ETA 01:15:03 2020-10-31 18:40:26 [INFO] [TRAIN] epoch=188, iter=69600/80000, loss=0.1500, lr=0.001603, batch_cost=0.4385, reader_cost=0.0091 | ETA 01:16:00 2020-10-31 18:41:09 [INFO] [TRAIN] epoch=188, iter=69700/80000, loss=0.1629, lr=0.001589, batch_cost=0.4283, reader_cost=0.0005 | ETA 01:13:31 2020-10-31 18:41:52 [INFO] [TRAIN] epoch=188, iter=69800/80000, loss=0.1707, lr=0.001575, batch_cost=0.4272, reader_cost=0.0003 | ETA 01:12:37 2020-10-31 18:42:34 [INFO] [TRAIN] epoch=188, iter=69900/80000, loss=0.1364, lr=0.001561, batch_cost=0.4271, reader_cost=0.0003 | ETA 01:11:53 2020-10-31 18:43:18 [INFO] [TRAIN] epoch=189, iter=70000/80000, loss=0.1452, lr=0.001548, batch_cost=0.4382, reader_cost=0.0083 | ETA 01:13:01 2020-10-31 18:44:01 [INFO] [TRAIN] epoch=189, iter=70100/80000, loss=0.1397, lr=0.001534, batch_cost=0.4287, reader_cost=0.0008 | ETA 01:10:43 2020-10-31 18:44:44 [INFO] [TRAIN] epoch=189, iter=70200/80000, loss=0.1567, lr=0.001520, batch_cost=0.4290, reader_cost=0.0005 | ETA 01:10:04 2020-10-31 18:45:27 [INFO] [TRAIN] epoch=189, iter=70300/80000, loss=0.1595, lr=0.001506, batch_cost=0.4285, reader_cost=0.0004 | ETA 01:09:16 2020-10-31 18:46:11 [INFO] [TRAIN] epoch=190, iter=70400/80000, loss=0.1547, lr=0.001492, batch_cost=0.4394, reader_cost=0.0081 | ETA 01:10:18 2020-10-31 18:46:54 [INFO] [TRAIN] epoch=190, iter=70500/80000, loss=0.1595, lr=0.001478, batch_cost=0.4361, reader_cost=0.0006 | ETA 01:09:03 2020-10-31 18:47:38 [INFO] [TRAIN] epoch=190, iter=70600/80000, loss=0.1666, lr=0.001464, batch_cost=0.4357, reader_cost=0.0004 | ETA 01:08:15 2020-10-31 18:48:22 [INFO] [TRAIN] epoch=191, iter=70700/80000, loss=0.1365, lr=0.001450, batch_cost=0.4442, reader_cost=0.0090 | ETA 01:08:50 2020-10-31 18:49:06 [INFO] [TRAIN] epoch=191, iter=70800/80000, loss=0.1638, lr=0.001436, batch_cost=0.4325, reader_cost=0.0005 | ETA 01:06:18 2020-10-31 18:49:49 [INFO] [TRAIN] epoch=191, iter=70900/80000, loss=0.1577, lr=0.001422, batch_cost=0.4321, reader_cost=0.0008 | ETA 01:05:32 2020-10-31 18:50:32 [INFO] [TRAIN] epoch=191, iter=71000/80000, loss=0.1573, lr=0.001408, batch_cost=0.4347, reader_cost=0.0011 | ETA 01:05:12 2020-10-31 18:51:17 [INFO] [TRAIN] epoch=192, iter=71100/80000, loss=0.1572, lr=0.001394, batch_cost=0.4419, reader_cost=0.0094 | ETA 01:05:33 2020-10-31 18:52:00 [INFO] [TRAIN] epoch=192, iter=71200/80000, loss=0.1462, lr=0.001380, batch_cost=0.4333, reader_cost=0.0003 | ETA 01:03:33 2020-10-31 18:52:44 [INFO] [TRAIN] epoch=192, iter=71300/80000, loss=0.1534, lr=0.001366, batch_cost=0.4393, reader_cost=0.0006 | ETA 01:03:41 2020-10-31 18:53:27 [INFO] [TRAIN] epoch=192, iter=71400/80000, loss=0.1477, lr=0.001352, batch_cost=0.4328, reader_cost=0.0004 | ETA 01:02:01 2020-10-31 18:54:11 [INFO] [TRAIN] epoch=193, iter=71500/80000, loss=0.1484, lr=0.001338, batch_cost=0.4398, reader_cost=0.0084 | ETA 01:02:18 2020-10-31 18:54:54 [INFO] [TRAIN] epoch=193, iter=71600/80000, loss=0.1633, lr=0.001324, batch_cost=0.4293, reader_cost=0.0003 | ETA 01:00:05 2020-10-31 18:55:37 [INFO] [TRAIN] epoch=193, iter=71700/80000, loss=0.1718, lr=0.001310, batch_cost=0.4303, reader_cost=0.0005 | ETA 00:59:31 2020-10-31 18:56:21 [INFO] [TRAIN] epoch=194, iter=71800/80000, loss=0.1470, lr=0.001296, batch_cost=0.4401, reader_cost=0.0095 | ETA 01:00:08 2020-10-31 18:57:04 [INFO] [TRAIN] epoch=194, iter=71900/80000, loss=0.1513, lr=0.001282, batch_cost=0.4310, reader_cost=0.0004 | ETA 00:58:11 2020-10-31 18:57:47 [INFO] [TRAIN] epoch=194, iter=72000/80000, loss=0.1470, lr=0.001268, batch_cost=0.4306, reader_cost=0.0003 | ETA 00:57:24 2020-10-31 18:57:52 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 19:02:14 [INFO] [EVAL] #Images=500 mIoU=0.7912 Acc=0.9630 Kappa=0.9519 2020-10-31 19:02:14 [INFO] [EVAL] Category IoU: [0.9829 0.8634 0.9277 0.5675 0.6319 0.655 0.7222 0.7986 0.928 0.6579 0.9476 0.8315 0.6389 0.9527 0.7841 0.8869 0.7746 0.6923 0.7889] 2020-10-31 19:02:14 [INFO] [EVAL] Category Acc: [0.9915 0.9284 0.9575 0.8422 0.8232 0.82 0.8486 0.9146 0.9566 0.837 0.9686 0.897 0.7672 0.9729 0.9246 0.9432 0.9378 0.8202 0.8748] 2020-10-31 19:02:17 [INFO] [EVAL] The model with the best validation mIoU (0.7912) was saved at iter 72000. 2020-10-31 19:03:00 [INFO] [TRAIN] epoch=194, iter=72100/80000, loss=0.1557, lr=0.001254, batch_cost=0.4341, reader_cost=0.0004 | ETA 00:57:09 2020-10-31 19:03:44 [INFO] [TRAIN] epoch=195, iter=72200/80000, loss=0.1410, lr=0.001239, batch_cost=0.4392, reader_cost=0.0083 | ETA 00:57:05 2020-10-31 19:04:27 [INFO] [TRAIN] epoch=195, iter=72300/80000, loss=0.1445, lr=0.001225, batch_cost=0.4296, reader_cost=0.0005 | ETA 00:55:08 2020-10-31 19:05:10 [INFO] [TRAIN] epoch=195, iter=72400/80000, loss=0.1535, lr=0.001211, batch_cost=0.4299, reader_cost=0.0004 | ETA 00:54:26 2020-10-31 19:05:53 [INFO] [TRAIN] epoch=195, iter=72500/80000, loss=0.1381, lr=0.001197, batch_cost=0.4307, reader_cost=0.0004 | ETA 00:53:49 2020-10-31 19:06:37 [INFO] [TRAIN] epoch=196, iter=72600/80000, loss=0.1457, lr=0.001183, batch_cost=0.4374, reader_cost=0.0084 | ETA 00:53:56 2020-10-31 19:07:20 [INFO] [TRAIN] epoch=196, iter=72700/80000, loss=0.1574, lr=0.001168, batch_cost=0.4275, reader_cost=0.0006 | ETA 00:52:00 2020-10-31 19:08:03 [INFO] [TRAIN] epoch=196, iter=72800/80000, loss=0.1471, lr=0.001154, batch_cost=0.4291, reader_cost=0.0005 | ETA 00:51:29 2020-10-31 19:08:46 [INFO] [TRAIN] epoch=196, iter=72900/80000, loss=0.1433, lr=0.001140, batch_cost=0.4282, reader_cost=0.0005 | ETA 00:50:40 2020-10-31 19:09:29 [INFO] [TRAIN] epoch=197, iter=73000/80000, loss=0.1545, lr=0.001125, batch_cost=0.4388, reader_cost=0.0083 | ETA 00:51:11 2020-10-31 19:10:12 [INFO] [TRAIN] epoch=197, iter=73100/80000, loss=0.1658, lr=0.001111, batch_cost=0.4295, reader_cost=0.0003 | ETA 00:49:23 2020-10-31 19:10:56 [INFO] [TRAIN] epoch=197, iter=73200/80000, loss=0.1546, lr=0.001097, batch_cost=0.4325, reader_cost=0.0007 | ETA 00:49:00 2020-10-31 19:11:40 [INFO] [TRAIN] epoch=198, iter=73300/80000, loss=0.1336, lr=0.001082, batch_cost=0.4412, reader_cost=0.0093 | ETA 00:49:16 2020-10-31 19:12:23 [INFO] [TRAIN] epoch=198, iter=73400/80000, loss=0.1499, lr=0.001068, batch_cost=0.4299, reader_cost=0.0003 | ETA 00:47:17 2020-10-31 19:13:06 [INFO] [TRAIN] epoch=198, iter=73500/80000, loss=0.1671, lr=0.001053, batch_cost=0.4283, reader_cost=0.0003 | ETA 00:46:23 2020-10-31 19:13:49 [INFO] [TRAIN] epoch=198, iter=73600/80000, loss=0.1497, lr=0.001039, batch_cost=0.4290, reader_cost=0.0002 | ETA 00:45:45 2020-10-31 19:14:32 [INFO] [TRAIN] epoch=199, iter=73700/80000, loss=0.1441, lr=0.001025, batch_cost=0.4386, reader_cost=0.0094 | ETA 00:46:03 2020-10-31 19:15:15 [INFO] [TRAIN] epoch=199, iter=73800/80000, loss=0.1405, lr=0.001010, batch_cost=0.4290, reader_cost=0.0004 | ETA 00:44:19 2020-10-31 19:15:58 [INFO] [TRAIN] epoch=199, iter=73900/80000, loss=0.1508, lr=0.000995, batch_cost=0.4293, reader_cost=0.0006 | ETA 00:43:38 2020-10-31 19:16:41 [INFO] [TRAIN] epoch=199, iter=74000/80000, loss=0.1272, lr=0.000981, batch_cost=0.4284, reader_cost=0.0003 | ETA 00:42:50 2020-10-31 19:17:25 [INFO] [TRAIN] epoch=200, iter=74100/80000, loss=0.1541, lr=0.000966, batch_cost=0.4399, reader_cost=0.0092 | ETA 00:43:15 2020-10-31 19:18:08 [INFO] [TRAIN] epoch=200, iter=74200/80000, loss=0.1540, lr=0.000952, batch_cost=0.4295, reader_cost=0.0004 | ETA 00:41:30 2020-10-31 19:18:51 [INFO] [TRAIN] epoch=200, iter=74300/80000, loss=0.1703, lr=0.000937, batch_cost=0.4320, reader_cost=0.0006 | ETA 00:41:02 2020-10-31 19:19:34 [INFO] [TRAIN] epoch=200, iter=74400/80000, loss=0.1499, lr=0.000922, batch_cost=0.4309, reader_cost=0.0006 | ETA 00:40:12 2020-10-31 19:20:18 [INFO] [TRAIN] epoch=201, iter=74500/80000, loss=0.1571, lr=0.000908, batch_cost=0.4409, reader_cost=0.0077 | ETA 00:40:24 2020-10-31 19:21:02 [INFO] [TRAIN] epoch=201, iter=74600/80000, loss=0.1634, lr=0.000893, batch_cost=0.4331, reader_cost=0.0004 | ETA 00:38:58 2020-10-31 19:21:45 [INFO] [TRAIN] epoch=201, iter=74700/80000, loss=0.1556, lr=0.000878, batch_cost=0.4301, reader_cost=0.0004 | ETA 00:37:59 2020-10-31 19:22:29 [INFO] [TRAIN] epoch=202, iter=74800/80000, loss=0.1549, lr=0.000864, batch_cost=0.4382, reader_cost=0.0097 | ETA 00:37:58 2020-10-31 19:23:12 [INFO] [TRAIN] epoch=202, iter=74900/80000, loss=0.1326, lr=0.000849, batch_cost=0.4306, reader_cost=0.0003 | ETA 00:36:36 2020-10-31 19:23:55 [INFO] [TRAIN] epoch=202, iter=75000/80000, loss=0.1662, lr=0.000834, batch_cost=0.4360, reader_cost=0.0003 | ETA 00:36:20 2020-10-31 19:24:38 [INFO] [TRAIN] epoch=202, iter=75100/80000, loss=0.1543, lr=0.000819, batch_cost=0.4329, reader_cost=0.0003 | ETA 00:35:21 2020-10-31 19:25:22 [INFO] [TRAIN] epoch=203, iter=75200/80000, loss=0.1578, lr=0.000804, batch_cost=0.4391, reader_cost=0.0085 | ETA 00:35:07 2020-10-31 19:26:06 [INFO] [TRAIN] epoch=203, iter=75300/80000, loss=0.1560, lr=0.000789, batch_cost=0.4341, reader_cost=0.0007 | ETA 00:34:00 2020-10-31 19:26:49 [INFO] [TRAIN] epoch=203, iter=75400/80000, loss=0.1442, lr=0.000774, batch_cost=0.4365, reader_cost=0.0005 | ETA 00:33:28 2020-10-31 19:27:33 [INFO] [TRAIN] epoch=203, iter=75500/80000, loss=0.1535, lr=0.000759, batch_cost=0.4332, reader_cost=0.0003 | ETA 00:32:29 2020-10-31 19:28:17 [INFO] [TRAIN] epoch=204, iter=75600/80000, loss=0.1598, lr=0.000744, batch_cost=0.4387, reader_cost=0.0090 | ETA 00:32:10 2020-10-31 19:29:00 [INFO] [TRAIN] epoch=204, iter=75700/80000, loss=0.1649, lr=0.000729, batch_cost=0.4350, reader_cost=0.0008 | ETA 00:31:10 2020-10-31 19:29:43 [INFO] [TRAIN] epoch=204, iter=75800/80000, loss=0.1621, lr=0.000714, batch_cost=0.4306, reader_cost=0.0006 | ETA 00:30:08 2020-10-31 19:30:27 [INFO] [TRAIN] epoch=205, iter=75900/80000, loss=0.1472, lr=0.000699, batch_cost=0.4405, reader_cost=0.0081 | ETA 00:30:05 2020-10-31 19:31:10 [INFO] [TRAIN] epoch=205, iter=76000/80000, loss=0.1750, lr=0.000684, batch_cost=0.4311, reader_cost=0.0008 | ETA 00:28:44 2020-10-31 19:31:53 [INFO] [TRAIN] epoch=205, iter=76100/80000, loss=0.1593, lr=0.000669, batch_cost=0.4312, reader_cost=0.0010 | ETA 00:28:01 2020-10-31 19:32:37 [INFO] [TRAIN] epoch=205, iter=76200/80000, loss=0.1601, lr=0.000654, batch_cost=0.4317, reader_cost=0.0008 | ETA 00:27:20 2020-10-31 19:33:21 [INFO] [TRAIN] epoch=206, iter=76300/80000, loss=0.1547, lr=0.000638, batch_cost=0.4402, reader_cost=0.0082 | ETA 00:27:08 2020-10-31 19:34:04 [INFO] [TRAIN] epoch=206, iter=76400/80000, loss=0.1624, lr=0.000623, batch_cost=0.4352, reader_cost=0.0006 | ETA 00:26:06 2020-10-31 19:34:48 [INFO] [TRAIN] epoch=206, iter=76500/80000, loss=0.1652, lr=0.000608, batch_cost=0.4336, reader_cost=0.0007 | ETA 00:25:17 2020-10-31 19:35:31 [INFO] [TRAIN] epoch=206, iter=76600/80000, loss=0.1397, lr=0.000592, batch_cost=0.4313, reader_cost=0.0004 | ETA 00:24:26 2020-10-31 19:36:15 [INFO] [TRAIN] epoch=207, iter=76700/80000, loss=0.1442, lr=0.000577, batch_cost=0.4395, reader_cost=0.0079 | ETA 00:24:10 2020-10-31 19:36:58 [INFO] [TRAIN] epoch=207, iter=76800/80000, loss=0.1581, lr=0.000561, batch_cost=0.4304, reader_cost=0.0006 | ETA 00:22:57 2020-10-31 19:37:41 [INFO] [TRAIN] epoch=207, iter=76900/80000, loss=0.1546, lr=0.000546, batch_cost=0.4300, reader_cost=0.0006 | ETA 00:22:13 2020-10-31 19:38:24 [INFO] [TRAIN] epoch=207, iter=77000/80000, loss=0.1446, lr=0.000530, batch_cost=0.4319, reader_cost=0.0007 | ETA 00:21:35 2020-10-31 19:39:08 [INFO] [TRAIN] epoch=208, iter=77100/80000, loss=0.1708, lr=0.000515, batch_cost=0.4427, reader_cost=0.0115 | ETA 00:21:23 2020-10-31 19:39:51 [INFO] [TRAIN] epoch=208, iter=77200/80000, loss=0.1672, lr=0.000499, batch_cost=0.4310, reader_cost=0.0003 | ETA 00:20:06 2020-10-31 19:40:34 [INFO] [TRAIN] epoch=208, iter=77300/80000, loss=0.1453, lr=0.000483, batch_cost=0.4291, reader_cost=0.0003 | ETA 00:19:18 2020-10-31 19:41:18 [INFO] [TRAIN] epoch=209, iter=77400/80000, loss=0.1491, lr=0.000468, batch_cost=0.4379, reader_cost=0.0077 | ETA 00:18:58 2020-10-31 19:42:01 [INFO] [TRAIN] epoch=209, iter=77500/80000, loss=0.1616, lr=0.000452, batch_cost=0.4319, reader_cost=0.0003 | ETA 00:17:59 2020-10-31 19:42:45 [INFO] [TRAIN] epoch=209, iter=77600/80000, loss=0.1729, lr=0.000436, batch_cost=0.4349, reader_cost=0.0004 | ETA 00:17:23 2020-10-31 19:43:28 [INFO] [TRAIN] epoch=209, iter=77700/80000, loss=0.1387, lr=0.000420, batch_cost=0.4320, reader_cost=0.0004 | ETA 00:16:33 2020-10-31 19:44:12 [INFO] [TRAIN] epoch=210, iter=77800/80000, loss=0.1363, lr=0.000404, batch_cost=0.4416, reader_cost=0.0085 | ETA 00:16:11 2020-10-31 19:44:55 [INFO] [TRAIN] epoch=210, iter=77900/80000, loss=0.1575, lr=0.000388, batch_cost=0.4338, reader_cost=0.0003 | ETA 00:15:11 2020-10-31 19:45:39 [INFO] [TRAIN] epoch=210, iter=78000/80000, loss=0.1656, lr=0.000371, batch_cost=0.4331, reader_cost=0.0007 | ETA 00:14:26 2020-10-31 19:46:22 [INFO] [TRAIN] epoch=210, iter=78100/80000, loss=0.1315, lr=0.000355, batch_cost=0.4312, reader_cost=0.0006 | ETA 00:13:39 2020-10-31 19:47:05 [INFO] [TRAIN] epoch=211, iter=78200/80000, loss=0.1634, lr=0.000339, batch_cost=0.4362, reader_cost=0.0086 | ETA 00:13:05 2020-10-31 19:47:49 [INFO] [TRAIN] epoch=211, iter=78300/80000, loss=0.1596, lr=0.000322, batch_cost=0.4337, reader_cost=0.0004 | ETA 00:12:17 2020-10-31 19:48:32 [INFO] [TRAIN] epoch=211, iter=78400/80000, loss=0.1502, lr=0.000306, batch_cost=0.4327, reader_cost=0.0004 | ETA 00:11:32 2020-10-31 19:49:16 [INFO] [TRAIN] epoch=212, iter=78500/80000, loss=0.1421, lr=0.000289, batch_cost=0.4380, reader_cost=0.0082 | ETA 00:10:57 2020-10-31 19:49:59 [INFO] [TRAIN] epoch=212, iter=78600/80000, loss=0.1506, lr=0.000272, batch_cost=0.4338, reader_cost=0.0005 | ETA 00:10:07 2020-10-31 19:50:43 [INFO] [TRAIN] epoch=212, iter=78700/80000, loss=0.1637, lr=0.000255, batch_cost=0.4332, reader_cost=0.0005 | ETA 00:09:23 2020-10-31 19:51:26 [INFO] [TRAIN] epoch=212, iter=78800/80000, loss=0.1556, lr=0.000238, batch_cost=0.4310, reader_cost=0.0006 | ETA 00:08:37 2020-10-31 19:52:10 [INFO] [TRAIN] epoch=213, iter=78900/80000, loss=0.1550, lr=0.000221, batch_cost=0.4414, reader_cost=0.0099 | ETA 00:08:05 2020-10-31 19:52:53 [INFO] [TRAIN] epoch=213, iter=79000/80000, loss=0.1542, lr=0.000204, batch_cost=0.4318, reader_cost=0.0002 | ETA 00:07:11 2020-10-31 19:53:36 [INFO] [TRAIN] epoch=213, iter=79100/80000, loss=0.1670, lr=0.000186, batch_cost=0.4292, reader_cost=0.0003 | ETA 00:06:26 2020-10-31 19:54:19 [INFO] [TRAIN] epoch=213, iter=79200/80000, loss=0.1576, lr=0.000169, batch_cost=0.4311, reader_cost=0.0004 | ETA 00:05:44 2020-10-31 19:55:03 [INFO] [TRAIN] epoch=214, iter=79300/80000, loss=0.1519, lr=0.000151, batch_cost=0.4391, reader_cost=0.0086 | ETA 00:05:07 2020-10-31 19:55:46 [INFO] [TRAIN] epoch=214, iter=79400/80000, loss=0.1463, lr=0.000132, batch_cost=0.4305, reader_cost=0.0004 | ETA 00:04:18 2020-10-31 19:56:29 [INFO] [TRAIN] epoch=214, iter=79500/80000, loss=0.1512, lr=0.000114, batch_cost=0.4290, reader_cost=0.0008 | ETA 00:03:34 2020-10-31 19:57:12 [INFO] [TRAIN] epoch=214, iter=79600/80000, loss=0.1541, lr=0.000095, batch_cost=0.4279, reader_cost=0.0004 | ETA 00:02:51 2020-10-31 19:57:55 [INFO] [TRAIN] epoch=215, iter=79700/80000, loss=0.1391, lr=0.000076, batch_cost=0.4378, reader_cost=0.0087 | ETA 00:02:11 2020-10-31 19:58:39 [INFO] [TRAIN] epoch=215, iter=79800/80000, loss=0.1545, lr=0.000056, batch_cost=0.4303, reader_cost=0.0003 | ETA 00:01:26 2020-10-31 19:59:22 [INFO] [TRAIN] epoch=215, iter=79900/80000, loss=0.1598, lr=0.000035, batch_cost=0.4312, reader_cost=0.0004 | ETA 00:00:43 2020-10-31 20:00:06 [INFO] [TRAIN] epoch=216, iter=80000/80000, loss=0.1468, lr=0.000010, batch_cost=0.4391, reader_cost=0.0085 | ETA 00:00:00 2020-10-31 20:00:11 [INFO] Start evaluating (total_samples=500, total_iters=500)... 2020-10-31 20:04:31 [INFO] [EVAL] #Images=500 mIoU=0.7950 Acc=0.9629 Kappa=0.9518 2020-10-31 20:04:31 [INFO] [EVAL] Category IoU: [0.982 0.8593 0.9273 0.5629 0.6308 0.6571 0.7244 0.8009 0.9286 0.6471 0.9485 0.8342 0.6447 0.9539 0.8081 0.8964 0.8126 0.6966 0.7902] 2020-10-31 20:04:31 [INFO] [EVAL] Category Acc: [0.9921 0.9198 0.955 0.8667 0.8241 0.8265 0.8387 0.9057 0.9575 0.8619 0.9671 0.8978 0.801 0.9744 0.945 0.9467 0.9239 0.8539 0.8692] 2020-10-31 20:04:33 [INFO] [EVAL] The model with the best validation mIoU (0.7950) was saved at iter 80000.