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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+wandb/wandb/run-20260507_130026-3lo4j577/run-3lo4j577.wandb filter=lfs diff=lfs merge=lfs -text

trogeo_pi3_eccv_checkpoint.pth.tar

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trogeo_pi3_eccv_model_best.pth.tar

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wandb/wandb/debug.log

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+2026-05-07 13:00:27,101 INFO    MainThread:4596 [wandb_init.py:init():855] wandb.init called with sweep_config: {}
+config: {'config': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/configs/trogeo_pi3_offline.yaml', 'gpu': '0,1,2,3,4,5,6,7', 'num_workers': 3, 'max_epoch': 25, 'lr': 0.0001, 'batch_size': 12, 'emb_size': 768, 'img_size': 518, 'data_root': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/data', 'data_name': 'CVOGL_DroneAerial', 'dataset_type': 'eccv', 'train_json': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/train_all.json', 'val_json': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/val_all.json', 'test_json': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/test_all.json', 'backbone_type': 'pi3', 'pi3_pretrain': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/location_v4/checkpoints_offline/pi3_model.safetensors', 'pi3_decoder_size': 'large', 'freeze_encoder': True, 'freeze_decoder': False, 'pretrain': '', 'resume': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs', 'print_freq': 10, 'savename': 'trogeo_pi3_eccv', 'output_dir': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs', 'seed': 2024, 'beta': 1.0, 'pos_weight': 15.0, 'test': False, 'val': False, 'wandb': True, 'wandb_project': 'CVOS-Code', 'wandb_dir': '/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs/wandb', 'use_amp': True, 'use_tf32': True, 'persistent_workers': True, 'prefetch_factor': 4, 'rank': 0, 'world_size': 8, 'local_rank': 0, 'anchors': '18,20, 36,40, 48,108, 64,64, 96,40, 96,88, 124,140, 198,171, 275,286', 'train_loader_len': 1994, '_wandb': {}}
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wandb/wandb/run-20260507_130026-3lo4j577/files/config.yaml

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+_wandb:
+    value:
+        cli_version: 0.26.1
+        e:
+            n66y3yolechf07hvu2i2dxfxcxu3un0q:
+                args:
+                    - --config
+                    - /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/configs/trogeo_pi3_offline.yaml
+                codePath: train.py
+                codePathLocal: train.py
+                cpu_count: 96
+                cpu_count_logical: 184
+                cudaVersion: "12.4"
+                disk:
+                    /:
+                        total: "53687091200"
+                        used: "121737216"
+                email: hycd540@gmail.com
+                executable: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/location_v4/.venv/bin/python
+                git:
+                    commit: 69ac6ce26abfd5b5619ce59bf76b093bbf75f1cc
+                    remote: git@github.com:cipual/CVOS-Code.git
+                gpu: NVIDIA H200
+                gpu_count: 8
+                gpu_nvidia:
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-e691af30-9e76-2280-b5cc-1276df37a4fb
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-1c3e7100-2e19-234c-3046-f07e76b3d684
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-45f60f31-9a59-e99b-da1c-eb7df5e0df4d
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-96df27eb-a35a-2c2f-1024-455553308768
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-d3d78141-29c8-e2ce-ce62-8cb199bbd05e
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-ea15c218-130a-565f-058d-6cadc9ac3aa5
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-76ee9c8e-bad5-8e3c-1766-c891bc14e07a
+                    - architecture: Hopper
+                      cudaCores: 16896
+                      memoryTotal: "150754820096"
+                      name: NVIDIA H200
+                      uuid: GPU-25afd362-e436-a0d2-ad7f-c31a4a73a20f
+                host: psx4524xrlkpndoc-worker-0
+                memory:
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+                os: Linux-5.10.0-218.0.0.mt20250120.565.mt2203sp4.x86_64-x86_64-with-glibc2.32
+                program: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/train.py
+                python: CPython 3.11.14
+                root: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs/wandb
+                startedAt: "2026-05-07T05:00:26.945273Z"
+                writerId: n66y3yolechf07hvu2i2dxfxcxu3un0q
+        m: []
+        python_version: 3.11.14
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+            "13": linux-x86_64
+anchors:
+    value: 18,20, 36,40, 48,108, 64,64, 96,40, 96,88, 124,140, 198,171, 275,286
+backbone_type:
+    value: pi3
+batch_size:
+    value: 12
+beta:
+    value: 1
+config:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/configs/trogeo_pi3_offline.yaml
+data_name:
+    value: CVOGL_DroneAerial
+data_root:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/data
+dataset_type:
+    value: eccv
+emb_size:
+    value: 768
+freeze_decoder:
+    value: false
+freeze_encoder:
+    value: true
+gpu:
+    value: 0,1,2,3,4,5,6,7
+img_size:
+    value: 518
+local_rank:
+    value: 0
+lr:
+    value: 0.0001
+max_epoch:
+    value: 25
+num_workers:
+    value: 3
+output_dir:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs
+persistent_workers:
+    value: true
+pi3_decoder_size:
+    value: large
+pi3_pretrain:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/location_v4/checkpoints_offline/pi3_model.safetensors
+pos_weight:
+    value: 15
+prefetch_factor:
+    value: 4
+pretrain:
+    value: ""
+print_freq:
+    value: 10
+rank:
+    value: 0
+resume:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs
+savename:
+    value: trogeo_pi3_eccv
+seed:
+    value: 2024
+test:
+    value: false
+test_json:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/test_all.json
+train_json:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/train_all.json
+train_loader_len:
+    value: 1994
+use_amp:
+    value: true
+use_tf32:
+    value: true
+val:
+    value: false
+val_json:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CMA-Loc/val_all.json
+wandb:
+    value: true
+wandb_dir:
+    value: /mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/CVOS-Code/outputs/wandb
+wandb_project:
+    value: CVOS-Code
+world_size:
+    value: 8

wandb/wandb/run-20260507_130026-3lo4j577/files/output.log

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+('lr', 0.0001)
+Train Epoch 0: 100%|██████████| 1994/1994 [50:15<00:00,  1.51s/it, loss=3.4721, geo=0.1546, cls=2.8872, accu=0.7500, miou=0.6599, accu_c=0.4167, dt=1.496s]  
+Val Epoch 0: 100%|██████████| 125/125 [01:41<00:00,  1.23it/s, accu50=0.4583, accu25=0.5833, miou=0.4058, accu_c=0.2917, dt=0.786s]
+Accu50: 0.48011, Accu25: 0.67026, mIoU: 0.42649, Accu Center: 0.24682
+/mnt/dolphinfs/ssd_pool/docker/user/hadoop-nlp-sh02/hadoop-aipnlp/EVA/yangheqing/workspace/location_v4/.venv/lib/python3.11/site-packages/torch/distributed/distributed_c10d.py:4631: UserWarning: No device id is provided via `init_process_group` or `barrier `. Using the current device set by the user.
+  warnings.warn(  # warn only once
+('lr', 0.0001)
+Train Epoch 1: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=2.9348, geo=0.1290, cls=2.4171, accu=0.8333, miou=0.6097, accu_c=0.5000, dt=1.497s]
+Val Epoch 1: 100%|██████████| 125/125 [01:39<00:00,  1.26it/s, accu50=0.5833, accu25=0.7083, miou=0.4671, accu_c=0.2917, dt=0.787s]
+Accu50: 0.56979, Accu25: 0.74695, mIoU: 0.49041, Accu Center: 0.29969
+('lr', 0.0001)
+Train Epoch 2: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=3.1956, geo=0.1702, cls=2.6621, accu=0.6667, miou=0.5718, accu_c=0.4167, dt=1.497s]
+Val Epoch 2: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.6667, accu25=0.7917, miou=0.5274, accu_c=0.3333, dt=0.786s]
+Accu50: 0.60022, Accu25: 0.77144, mIoU: 0.51186, Accu Center: 0.33191
+('lr', 0.0001)
+Train Epoch 3: 100%|██████████| 1994/1994 [49:52<00:00,  1.50s/it, loss=2.4825, geo=0.1389, cls=2.0033, accu=0.5833, miou=0.5864, accu_c=0.3333, dt=1.496s]
+Val Epoch 3: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.8333, miou=0.5194, accu_c=0.4583, dt=0.786s]
+Accu50: 0.61597, Accu25: 0.78557, mIoU: 0.52427, Accu Center: 0.34767
+('lr', 0.0001)
+Train Epoch 4: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=2.7691, geo=0.0920, cls=2.2314, accu=0.5833, miou=0.4442, accu_c=0.3333, dt=1.497s]
+Val Epoch 4: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.6667, accu25=0.7917, miou=0.5264, accu_c=0.3750, dt=0.787s]
+Accu50: 0.62734, Accu25: 0.79468, mIoU: 0.53739, Accu Center: 0.36622
+('lr', 0.0001)
+Train Epoch 5: 100%|██████████| 1994/1994 [49:52<00:00,  1.50s/it, loss=2.5781, geo=0.0811, cls=1.8582, accu=0.6667, miou=0.6095, accu_c=0.5833, dt=1.497s]
+Val Epoch 5: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5417, accu25=0.7917, miou=0.5327, accu_c=0.4583, dt=0.787s]
+Accu50: 0.64314, Accu25: 0.80759, mIoU: 0.54760, Accu Center: 0.37124
+('lr', 0.0001)
+Train Epoch 6: 100%|██████████| 1994/1994 [49:52<00:00,  1.50s/it, loss=1.3582, geo=0.1030, cls=0.9880, accu=0.7500, miou=0.5849, accu_c=0.8333, dt=1.494s]
+Val Epoch 6: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5383, accu_c=0.3750, dt=0.787s]
+Accu50: 0.65242, Accu25: 0.81566, mIoU: 0.55271, Accu Center: 0.38378
+('lr', 0.0001)
+Train Epoch 7: 100%|██████████| 1994/1994 [49:49<00:00,  1.50s/it, loss=1.6938, geo=0.1253, cls=1.3444, accu=0.7500, miou=0.7229, accu_c=0.5833, dt=1.496s]
+Val Epoch 7: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.6250, accu25=0.8333, miou=0.5236, accu_c=0.2917, dt=0.787s]
+Accu50: 0.66282, Accu25: 0.82038, mIoU: 0.56240, Accu Center: 0.38190
+('lr', 0.0001)
+Train Epoch 8: 100%|██████████| 1994/1994 [49:50<00:00,  1.50s/it, loss=2.0382, geo=0.0671, cls=1.6468, accu=0.9167, miou=0.6967, accu_c=0.5833, dt=1.495s]
+Val Epoch 8: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5160, accu_c=0.2917, dt=0.787s]
+Accu50: 0.67828, Accu25: 0.82644, mIoU: 0.57158, Accu Center: 0.38624
+('lr', 0.0001)
+Train Epoch 9: 100%|██████████| 1994/1994 [49:52<00:00,  1.50s/it, loss=0.9196, geo=0.0802, cls=0.7432, accu=0.7500, miou=0.6685, accu_c=0.7500, dt=1.498s]
+Val Epoch 9: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.4583, accu25=0.7917, miou=0.4656, accu_c=0.3750, dt=0.787s]
+Accu50: 0.66199, Accu25: 0.82084, mIoU: 0.56267, Accu Center: 0.39673
+('lr', 1e-05)
+Train Epoch 10: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=1.1155, geo=0.0903, cls=0.8719, accu=1.0000, miou=0.8320, accu_c=0.6667, dt=1.495s]
+Val Epoch 10: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5000, accu25=0.7500, miou=0.4939, accu_c=0.3333, dt=0.785s]
+Accu50: 0.69968, Accu25: 0.84771, mIoU: 0.59382, Accu Center: 0.43033
+('lr', 1e-05)
+Train Epoch 11: 100%|██████████| 1994/1994 [49:50<00:00,  1.50s/it, loss=1.2032, geo=0.0522, cls=1.0270, accu=0.9167, miou=0.7849, accu_c=0.5833, dt=1.494s]
+Val Epoch 11: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5417, accu25=0.7917, miou=0.4995, accu_c=0.2917, dt=0.787s]
+Accu50: 0.70323, Accu25: 0.84938, mIoU: 0.59601, Accu Center: 0.43714
+('lr', 1e-05)
+Train Epoch 12: 100%|██████████| 1994/1994 [49:50<00:00,  1.50s/it, loss=1.0123, geo=0.0635, cls=0.7869, accu=0.9167, miou=0.7628, accu_c=0.5833, dt=1.497s]
+Val Epoch 12: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5105, accu_c=0.3333, dt=0.787s]
+Accu50: 0.70340, Accu25: 0.84959, mIoU: 0.59492, Accu Center: 0.43882
+('lr', 1e-05)
+Train Epoch 13: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=1.5644, geo=0.0697, cls=1.3500, accu=0.8333, miou=0.6840, accu_c=0.4167, dt=1.494s]
+Val Epoch 13: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.4988, accu_c=0.2917, dt=0.786s]
+Accu50: 0.70821, Accu25: 0.85298, mIoU: 0.59926, Accu Center: 0.44007
+('lr', 1e-05)
+Train Epoch 14: 100%|██████████| 1994/1994 [49:48<00:00,  1.50s/it, loss=0.9199, geo=0.1082, cls=0.6514, accu=0.8333, miou=0.6749, accu_c=0.9167, dt=1.495s]
+Val Epoch 14: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5080, accu_c=0.2917, dt=0.786s]
+Accu50: 0.71067, Accu25: 0.85214, mIoU: 0.60067, Accu Center: 0.44270
+('lr', 1e-05)
+Train Epoch 15: 100%|██████████| 1994/1994 [49:51<00:00,  1.50s/it, loss=0.9338, geo=0.0484, cls=0.7569, accu=0.8333, miou=0.7187, accu_c=0.5000, dt=1.495s]
+Val Epoch 15: 100%|██████████| 125/125 [01:40<00:00,  1.25it/s, accu50=0.5417, accu25=0.7917, miou=0.5080, accu_c=0.2917, dt=0.787s]
+Accu50: 0.70583, Accu25: 0.85080, mIoU: 0.59717, Accu Center: 0.44032
+('lr', 1e-05)
+Train Epoch 16: 100%|██████████| 1994/1994 [49:49<00:00,  1.50s/it, loss=0.7115, geo=0.0585, cls=0.4862, accu=0.9167, miou=0.7482, accu_c=0.7500, dt=1.495s]
+Val Epoch 16: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5089, accu_c=0.2917, dt=0.786s]
+Accu50: 0.70449, Accu25: 0.85172, mIoU: 0.59748, Accu Center: 0.44153
+('lr', 1e-05)
+Train Epoch 17: 100%|██████████| 1994/1994 [49:52<00:00,  1.50s/it, loss=0.8768, geo=0.0600, cls=0.6826, accu=1.0000, miou=0.7404, accu_c=0.7500, dt=1.494s]
+Val Epoch 17: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.6667, accu25=0.8333, miou=0.5421, accu_c=0.3333, dt=0.787s]
+Accu50: 0.71063, Accu25: 0.85135, mIoU: 0.60151, Accu Center: 0.43982
+('lr', 1e-05)
+Train Epoch 18: 100%|██████████| 1994/1994 [49:48<00:00,  1.50s/it, loss=1.0363, geo=0.0552, cls=0.8747, accu=1.0000, miou=0.7751, accu_c=0.6667, dt=1.494s]
+Val Epoch 18: 100%|██████████| 125/125 [01:40<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5135, accu_c=0.3750, dt=0.786s]
+Accu50: 0.70992, Accu25: 0.85164, mIoU: 0.60126, Accu Center: 0.44107
+('lr', 1e-05)
+Train Epoch 19: 100%|██████████| 1994/1994 [49:47<00:00,  1.50s/it, loss=0.8069, geo=0.0419, cls=0.6339, accu=1.0000, miou=0.7871, accu_c=0.6667, dt=1.497s]
+Val Epoch 19: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5045, accu_c=0.2917, dt=0.786s]
+Accu50: 0.70478, Accu25: 0.85097, mIoU: 0.59983, Accu Center: 0.43852
+('lr', 1.0000000000000002e-06)
+Train Epoch 20: 100%|██████████| 1994/1994 [49:48<00:00,  1.50s/it, loss=0.4784, geo=0.0402, cls=0.3337, accu=1.0000, miou=0.8210, accu_c=0.8333, dt=1.498s]
+Val Epoch 20: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5015, accu_c=0.2917, dt=0.786s]
+Accu50: 0.70909, Accu25: 0.85277, mIoU: 0.60155, Accu Center: 0.44283
+('lr', 1.0000000000000002e-06)
+Train Epoch 21: 100%|██████████| 1994/1994 [49:55<00:00,  1.50s/it, loss=0.9288, geo=0.0195, cls=0.8041, accu=1.0000, miou=0.8106, accu_c=0.7500, dt=1.500s]
+Val Epoch 21: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5047, accu_c=0.2917, dt=0.787s]
+Accu50: 0.71155, Accu25: 0.85256, mIoU: 0.60218, Accu Center: 0.44233
+('lr', 1.0000000000000002e-06)
+Train Epoch 22: 100%|██████████| 1994/1994 [49:49<00:00,  1.50s/it, loss=0.8759, geo=0.0302, cls=0.7199, accu=1.0000, miou=0.8106, accu_c=0.6667, dt=1.496s]
+Val Epoch 22: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5057, accu_c=0.2917, dt=0.788s]
+Accu50: 0.71084, Accu25: 0.85318, mIoU: 0.60185, Accu Center: 0.44366
+('lr', 1.0000000000000002e-06)
+Train Epoch 23: 100%|██████████| 1994/1994 [49:50<00:00,  1.50s/it, loss=0.3663, geo=0.0669, cls=0.1929, accu=0.8333, miou=0.7454, accu_c=0.9167, dt=1.496s]
+Val Epoch 23: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5029, accu_c=0.2917, dt=0.787s]
+Accu50: 0.71063, Accu25: 0.85289, mIoU: 0.60239, Accu Center: 0.44437
+('lr', 1.0000000000000002e-06)
+Train Epoch 24: 100%|██████████| 1994/1994 [49:50<00:00,  1.50s/it, loss=0.5847, geo=0.0369, cls=0.3998, accu=0.8333, miou=0.7486, accu_c=0.7500, dt=1.496s]
+Val Epoch 24: 100%|██████████| 125/125 [01:39<00:00,  1.25it/s, accu50=0.5833, accu25=0.7917, miou=0.5022, accu_c=0.2917, dt=0.785s]
+Accu50: 0.71097, Accu25: 0.85285, mIoU: 0.60220, Accu Center: 0.44392
+
+Best Accu: 0.711551

wandb/wandb/run-20260507_130026-3lo4j577/files/requirements.txt

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wandb/wandb/run-20260507_130026-3lo4j577/run-3lo4j577.wandb

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+oid sha256:66c87c9e0521decdb5455f09b6a7c9600049e3f1371db89f4a79b89b9f6452c0
+size 63687309