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+Abs_Joint/Baseline/wandb/run-20260717_154830-a3ogbmg4/run-a3ogbmg4.wandb filter=lfs diff=lfs merge=lfs -text

Abs_Joint/Baseline/action_space_manifest.json

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Abs_Joint/Baseline/checkpoints/060000/pretrained_model/config.json

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Abs_Joint/Baseline/checkpoints/060000/pretrained_model/policy_postprocessor.json

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Abs_Joint/Baseline/checkpoints/060000/pretrained_model/prompt_manifest.json

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+    "1ext": "Find the arrow guide and open the indicated drawer.",
+    "3b": "Open the door, rotate counter-clockwise and push.",
+    "5b": "Open the bottle in counter-clockwise direction.",
+    "3a": "Open the door, rotate clockwise and push.",
+    "3c": "Open the door, rotate clockwise and pull.",
+    "5h": "Close the bottle in counter-clockwise direction.",
+    "5d": "Close the bottle in clockwise direction.",
+    "3d": "Open the door, rotate counter-clockwise and pull.",
+    "5e": "Close the bottle in counter-clockwise direction.",
+    "5a": "Grip the cap on the sides indicated by the 'squeeze' arrow and open the bottle in counter-clockwise direction.",
+    "5c": "Open the bottle in clockwise direction."
+  }
+}

Abs_Joint/Baseline/checkpoints/060000/pretrained_model/train_config.json

@@ -0,0 +1,258 @@
+{
+    "dataset": {
+        "repo_id": "Whalswp/INSIGHTfixposV4_filtered_multispace_v2",
+        "root": "/home/seonho/INSIGHTfixposV4_filtered_multispace_v2",
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+                    "kwargs": {
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+                            1.2
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+                            0.8,
+                            1.2
+                        ]
+                    }
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+                    "type": "ColorJitter",
+                    "kwargs": {
+                        "saturation": [
+                            0.5,
+                            1.5
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+                    "type": "ColorJitter",
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+                    "type": "SharpnessJitter",
+                    "kwargs": {
+                        "sharpness": [
+                            0.5,
+                            1.5
+                        ]
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+                    "type": "RandomAffine",
+                    "kwargs": {
+                        "degrees": [
+                            -5.0,
+                            5.0
+                        ],
+                        "translate": [
+                            0.05,
+                            0.05
+                        ]
+                    }
+                }
+            }
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+        "use_imagenet_stats": true,
+        "video_backend": "torchcodec",
+        "return_uint8": false,
+        "depth_output_unit": "mm",
+        "streaming": false,
+        "eval_split": 0.0
+    },
+    "env": null,
+    "policy": {
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+        "n_obs_steps": 1,
+        "input_features": {
+            "observation.state": {
+                "type": "STATE",
+                "shape": [
+                    16
+                ]
+            },
+            "observation.images.wrist": {
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+                "shape": [
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+                    224
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+        "max_action_dim": 132,
+        "normalization_mapping": {
+            "VISUAL": "IDENTITY",
+            "STATE": "IDENTITY",
+            "ACTION": "IDENTITY"
+        },
+        "base_model_path": "nvidia/GR00T-N1.7-3B",
+        "action_decode_transform": null,
+        "embodiment_tag": "new_embodiment",
+        "tune_llm": false,
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+        "relative_exclude_joints": [],
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+        "balance_trajectory_weights": true,
+        "dataset_paths": null,
+        "output_dir": "./tmp/gr00t",
+        "save_steps": 1000,
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+        "batch_size": 32,
+        "dataloader_num_workers": 8,
+        "report_to": "wandb",
+        "resume": false
+    },
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+    "output_dir": "/home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline",
+    "job_name": "INSIGHT_RD_baseline",
+    "resume": false,
+    "seed": 42,
+    "cudnn_deterministic": false,
+    "num_workers": 4,
+    "batch_size": 128,
+    "prefetch_factor": 4,
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+    "scheduler": {
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+        "name": "cosine"
+    },
+    "eval": {
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+        "batch_size": 44,
+        "use_async_envs": true,
+        "recording": false,
+        "recording_repo_id": null,
+        "recording_private": false
+    },
+    "wandb": {
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+        "disable_artifact": true,
+        "project": "lerobot",
+        "entity": null,
+        "notes": null,
+        "run_id": "a3ogbmg4",
+        "mode": null,
+        "add_tags": true
+    },
+    "peft": null,
+    "job": {
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+        "image": "huggingface/lerobot-gpu:latest",
+        "timeout": "2d",
+        "detach": false,
+        "tags": []
+    },
+    "save_checkpoint_to_hub": false,
+    "sample_weighting": null,
+    "rename_map": {},
+    "checkpoint_path": null
+}

Abs_Joint/Baseline/checkpoints/060000/prompt_manifest.json

@@ -0,0 +1,40 @@
+{
+  "schema_version": 1,
+  "prompt_set": "detailed",
+  "source_file": "task_prompts.json",
+  "source_sha256": "0ba48fb372da9f49dcfcd7dcc2da8cce6ce991d3661060e664a104778d1ffacc",
+  "mapping_sha256": "f71954786e94cdeceb135dde09fdc6b65db0b87ab3b09d25060129d0f0fde018",
+  "dataset_repo_id": "Whalswp/INSIGHTfixposV4_filtered_multispace_v2",
+  "dataset_revision": "v3.0",
+  "task_count": 13,
+  "task_codes": [
+    "5f",
+    "5g",
+    "1ext",
+    "3b",
+    "5b",
+    "3a",
+    "3c",
+    "5h",
+    "5d",
+    "3d",
+    "5e",
+    "5a",
+    "5c"
+  ],
+  "prompts": {
+    "5f": "Close the bottle in clockwise direction.",
+    "5g": "Grip the cap on the sides indicated by the 'squeeze' arrow and open the bottle in clockwise direction.",
+    "1ext": "Find the arrow guide and open the indicated drawer.",
+    "3b": "Open the door, rotate counter-clockwise and push.",
+    "5b": "Open the bottle in counter-clockwise direction.",
+    "3a": "Open the door, rotate clockwise and push.",
+    "3c": "Open the door, rotate clockwise and pull.",
+    "5h": "Close the bottle in counter-clockwise direction.",
+    "5d": "Close the bottle in clockwise direction.",
+    "3d": "Open the door, rotate counter-clockwise and pull.",
+    "5e": "Close the bottle in counter-clockwise direction.",
+    "5a": "Grip the cap on the sides indicated by the 'squeeze' arrow and open the bottle in counter-clockwise direction.",
+    "5c": "Open the bottle in clockwise direction."
+  }
+}

Abs_Joint/Baseline/checkpoints/060000/resolved_config.yaml

@@ -0,0 +1,24 @@
+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: /home/seonho/INSIGHTfixposV4_filtered_multispace_v2
+policy:
+  type: groot
+  device: cuda
+  chunk_size: 16
+  n_action_steps: 16
+  push_to_hub: false
+  tune_llm: false
+  tune_visual: false
+  tune_top_llm_layers: 0
+  tune_projector: true
+  tune_diffusion_model: true
+  tune_vlln: true
+seed: 42
+batch_size: 128
+steps: 60000
+log_freq: 200
+output_dir: /home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline
+job_name: INSIGHT_RD_baseline
+wandb:
+  enable: true
+  disable_artifact: true

Abs_Joint/Baseline/checkpoints/060000/source_config.yaml

@@ -0,0 +1,63 @@
+# INSIGHT GR00T N1.7 training config
+# INSIGHT wrapper-only fields are stripped before LeRobot config parsing.
+insight:
+  # Options: joint_abs | ee_abs_quat | ee_abs_rot6d | ee_delta
+  action_space: joint_abs
+  # Options: coarse | detailed
+  prompt_set: detailed
+  save_steps: ["60K"]
+
+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: ${HOME}/INSIGHTfixposV4_filtered_multispace_v2
+
+policy:
+  type: groot
+  device: cuda
+  chunk_size: 16
+  n_action_steps: 16
+  push_to_hub: false
+  # Trainable scope. This baseline trains projector, diffusion, and VLLN; LLM/vision stay frozen.
+  # VLM
+  tune_llm: false
+  tune_visual: false
+  tune_top_llm_layers: 0
+  # Action Expert
+  tune_projector: true
+  tune_diffusion_model: true
+  tune_vlln: true
+
+
+seed: 42
+batch_size: 128
+steps: 60000
+log_freq: 200
+output_dir: "${HOME}/groot_insight/train_ckpt/Abs_Joint/Baseline"
+job_name: INSIGHT_RD_baseline
+
+wandb:
+  enable: true
+  disable_artifact: true
+
+# Omitted because these match LeRobot/GR00T defaults or are unused in this setup:
+#
+# dataset:
+#   eval_split: 0.0
+#   image_transforms:
+#     enable: false  # default; set true only for train-image augmentation.
+#
+# policy:
+#   base_model_path: nvidia/GR00T-N1.7-3B
+#   embodiment_tag: new_embodiment
+#   use_relative_actions: false
+#   use_bf16: true
+#   repo_id: Whalswp/INSIGHT  # unused while push_to_hub is false
+#
+# save_checkpoint: true
+# use_policy_training_preset: true
+# eval_steps: 0
+# env_eval_freq: 0
+#
+# insight.prompt_set options:
+# coarse: High-level task text that requires following the visual guide.
+# detailed: Direction- and interaction-specific text, including rotation and push/pull details.

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Abs_Joint/Baseline/checkpoints/060000/training_state/scheduler_state.json

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Abs_Joint/Baseline/checkpoints/060000/training_state/training_step.json

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+    "batch_size": 128
+}

Abs_Joint/Baseline/prompt_manifest.json

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+{
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+  "prompt_set": "detailed",
+  "source_file": "task_prompts.json",
+  "source_sha256": "0ba48fb372da9f49dcfcd7dcc2da8cce6ce991d3661060e664a104778d1ffacc",
+  "mapping_sha256": "f71954786e94cdeceb135dde09fdc6b65db0b87ab3b09d25060129d0f0fde018",
+  "dataset_repo_id": "Whalswp/INSIGHTfixposV4_filtered_multispace_v2",
+  "dataset_revision": "v3.0",
+  "task_count": 13,
+  "task_codes": [
+    "5f",
+    "5g",
+    "1ext",
+    "3b",
+    "5b",
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+    "3c",
+    "5h",
+    "5d",
+    "3d",
+    "5e",
+    "5a",
+    "5c"
+  ],
+  "prompts": {
+    "5f": "Close the bottle in clockwise direction.",
+    "5g": "Grip the cap on the sides indicated by the 'squeeze' arrow and open the bottle in clockwise direction.",
+    "1ext": "Find the arrow guide and open the indicated drawer.",
+    "3b": "Open the door, rotate counter-clockwise and push.",
+    "5b": "Open the bottle in counter-clockwise direction.",
+    "3a": "Open the door, rotate clockwise and push.",
+    "3c": "Open the door, rotate clockwise and pull.",
+    "5h": "Close the bottle in counter-clockwise direction.",
+    "5d": "Close the bottle in clockwise direction.",
+    "3d": "Open the door, rotate counter-clockwise and pull.",
+    "5e": "Close the bottle in counter-clockwise direction.",
+    "5a": "Grip the cap on the sides indicated by the 'squeeze' arrow and open the bottle in counter-clockwise direction.",
+    "5c": "Open the bottle in clockwise direction."
+  }
+}

Abs_Joint/Baseline/resolved_config.yaml

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+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: /home/seonho/INSIGHTfixposV4_filtered_multispace_v2
+policy:
+  type: groot
+  device: cuda
+  chunk_size: 16
+  n_action_steps: 16
+  push_to_hub: false
+  tune_llm: false
+  tune_visual: false
+  tune_top_llm_layers: 0
+  tune_projector: true
+  tune_diffusion_model: true
+  tune_vlln: true
+seed: 42
+batch_size: 128
+steps: 60000
+log_freq: 200
+output_dir: /home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline
+job_name: INSIGHT_RD_baseline
+wandb:
+  enable: true
+  disable_artifact: true

Abs_Joint/Baseline/source_config.yaml

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+# INSIGHT GR00T N1.7 training config
+# INSIGHT wrapper-only fields are stripped before LeRobot config parsing.
+insight:
+  # Options: joint_abs | ee_abs_quat | ee_abs_rot6d | ee_delta
+  action_space: joint_abs
+  # Options: coarse | detailed
+  prompt_set: detailed
+  save_steps: ["60K"]
+
+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: ${HOME}/INSIGHTfixposV4_filtered_multispace_v2
+
+policy:
+  type: groot
+  device: cuda
+  chunk_size: 16
+  n_action_steps: 16
+  push_to_hub: false
+  # Trainable scope. This baseline trains projector, diffusion, and VLLN; LLM/vision stay frozen.
+  # VLM
+  tune_llm: false
+  tune_visual: false
+  tune_top_llm_layers: 0
+  # Action Expert
+  tune_projector: true
+  tune_diffusion_model: true
+  tune_vlln: true
+
+
+seed: 42
+batch_size: 128
+steps: 60000
+log_freq: 200
+output_dir: "${HOME}/groot_insight/train_ckpt/Abs_Joint/Baseline"
+job_name: INSIGHT_RD_baseline
+
+wandb:
+  enable: true
+  disable_artifact: true
+
+# Omitted because these match LeRobot/GR00T defaults or are unused in this setup:
+#
+# dataset:
+#   eval_split: 0.0
+#   image_transforms:
+#     enable: false  # default; set true only for train-image augmentation.
+#
+# policy:
+#   base_model_path: nvidia/GR00T-N1.7-3B
+#   embodiment_tag: new_embodiment
+#   use_relative_actions: false
+#   use_bf16: true
+#   repo_id: Whalswp/INSIGHT  # unused while push_to_hub is false
+#
+# save_checkpoint: true
+# use_policy_training_preset: true
+# eval_steps: 0
+# env_eval_freq: 0
+#
+# insight.prompt_set options:
+# coarse: High-level task text that requires following the visual guide.
+# detailed: Direction- and interaction-specific text, including rotation and push/pull details.

Abs_Joint/Baseline/wandb/debug.log

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+2026-07-17 15:48:30,894 INFO    MainThread:3896698 [wandb_init.py:init():771] wandb.init called with sweep_config: {}
+config: {'dataset': {'repo_id': 'Whalswp/INSIGHTfixposV4_filtered_multispace_v2', 'root': '/home/seonho/INSIGHTfixposV4_filtered_multispace_v2', 'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'brightness': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'brightness': [0.8, 1.2]}}, 'contrast': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'contrast': [0.8, 1.2]}}, 'saturation': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'saturation': [0.5, 1.5]}}, 'hue': {'weight': 1.0, 'type': 'ColorJitter', 'kwargs': {'hue': [-0.05, 0.05]}}, 'sharpness': {'weight': 1.0, 'type': 'SharpnessJitter', 'kwargs': {'sharpness': [0.5, 1.5]}}, 'affine': {'weight': 1.0, 'type': 'RandomAffine', 'kwargs': {'degrees': [-5.0, 5.0], 'translate': [0.05, 0.05]}}}}, 'revision': None, 'use_imagenet_stats': True, 'video_backend': 'torchcodec', 'return_uint8': False, 'depth_output_unit': 'mm', 'streaming': False, 'eval_split': 0.0}, 'env': None, 'policy': {'type': 'groot', 'n_obs_steps': 1, 'input_features': {}, 'output_features': {}, 'device': 'cuda', 'use_amp': False, 'use_peft': False, 'push_to_hub': False, 'repo_id': None, 'private': None, 'tags': None, 'license': None, 'pretrained_path': None, 'pretrained_revision': None, 'chunk_size': 16, 'n_action_steps': 16, 'max_state_dim': 132, 'max_action_dim': 132, 'normalization_mapping': {'VISUAL': <NormalizationMode.IDENTITY: 'IDENTITY'>, 'STATE': <NormalizationMode.IDENTITY: 'IDENTITY'>, 'ACTION': <NormalizationMode.IDENTITY: 'IDENTITY'>}, 'base_model_path': 'nvidia/GR00T-N1.7-3B', 'action_decode_transform': None, 'embodiment_tag': 'new_embodiment', 'tune_llm': False, 'tune_visual': False, 'tune_projector': True, 'tune_diffusion_model': True, 'tune_vlln': True, 'tune_top_llm_layers': 0, 'num_inference_timesteps': None, 'rtc_ramp_rate': None, 'use_flash_attention': False, 'use_relative_actions': False, 'relative_exclude_joints': [], 'optimizer_lr': 0.0001, 'optimizer_betas': [0.9, 0.999], 'optimizer_eps': 1e-08, 'optimizer_weight_decay': 1e-05, 'warmup_ratio': 0.05, 'use_bf16': True, 'model_params_fp32': True, 'image_size': [256, 256], 'tokenizer_assets_repo': None, 'lora_rank': 0, 'lora_alpha': 16, 'lora_dropout': 0.1, 'lora_full_model': False, 'video_backend': 'decord', 'balance_dataset_weights': True, 'balance_trajectory_weights': True, 'dataset_paths': None, 'output_dir': './tmp/gr00t', 'save_steps': 1000, 'max_steps': 10000, 'batch_size': 32, 'dataloader_num_workers': 8, 'report_to': 'wandb', 'resume': False}, 'reward_model': None, 'output_dir': '/home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline', 'job_name': 'INSIGHT_RD_baseline', 'resume': False, 'seed': 42, 'cudnn_deterministic': False, 'num_workers': 4, 'batch_size': 128, 'prefetch_factor': 4, 'persistent_workers': True, 'steps': 60000, 'env_eval_freq': 20000, 'log_freq': 200, 'eval_steps': 0, 'max_eval_samples': 0, 'tolerance_s': 0.0001, 'save_checkpoint': True, 'save_freq': 20000, 'use_policy_training_preset': True, 'optimizer': {'type': 'adamw', 'lr': 0.0001, 'weight_decay': 1e-05, 'grad_clip_norm': 1.0, 'betas': [0.9, 0.999], 'eps': 1e-08}, 'scheduler': {'type': 'diffuser', 'num_warmup_steps': 500, 'name': 'cosine'}, 'eval': {'n_episodes': 50, 'batch_size': 44, 'use_async_envs': True, 'recording': False, 'recording_repo_id': None, 'recording_private': False}, 'wandb': {'enable': True, 'disable_artifact': True, 'project': 'lerobot', 'entity': None, 'notes': None, 'run_id': None, 'mode': None, 'add_tags': True}, 'peft': None, 'job': {'target': None, 'image': 'huggingface/lerobot-gpu:latest', 'timeout': '2d', 'detach': False, 'tags': []}, 'save_checkpoint_to_hub': False, 'sample_weighting': None, 'rename_map': {}, 'checkpoint_path': None, '_wandb': {}}
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+2026-07-20 02:13:16,832 INFO    wandb-AsyncioManager-main:3896698 [service_client.py:_forward_responses():122] Reached EOF.
+2026-07-20 02:13:16,833 INFO    wandb-AsyncioManager-main:3896698 [mailbox.py:close():154] Closing mailbox, abandoning 2 handles.
+2026-07-20 02:13:16,834 ERROR   wandb-AsyncioManager-main:3896698 [asyncio_manager.py:fn_wrap_exceptions():184] Uncaught exception in run_soon callback.
+Traceback (most recent call last):
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 90, in loop
+    await asyncio_compat.race(
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 278, in race
+    async with open_task_group(race=True) as tg:
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/contextlib.py", line 217, in __aexit__
+    await anext(self.gen)
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 240, in open_task_group
+    await task_group._wait_all(race=race, timeout=exit_timeout)
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 180, in _wait_all
+    raise exc
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 113, in _print_all
+    result = await handle.wait_async(timeout=None)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/mailbox/mailbox_handle.py", line 127, in wait_async
+    response = await self._handle.wait_async(timeout=timeout)
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/mailbox/response_handle.py", line 123, in wait_async
+    raise HandleAbandonedError()
+wandb.sdk.mailbox.mailbox_handle.HandleAbandonedError

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+                    - --batch_size=128
+                codePath: benchmarks/INSIGHT/my_scripts/lerobot_train_yaml.py
+                codePathLocal: my_scripts/lerobot_train_yaml.py
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+                python: CPython 3.12.13
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+                        degrees:
+                            - -5
+                            - 5
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+                            - 0.05
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+        type: diffuser
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+        project: lerobot
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Abs_Joint/Baseline/wandb/run-20260717_154830-a3ogbmg4/files/output.log

@@ -0,0 +1,320 @@
+INFO 2026-07-17 15:48:32 db_utils.py:121 Logs will be synced with wandb.
+INFO 2026-07-17 15:48:32 db_utils.py:122 Track this run --> https://wandb.ai/minje227_hyu-hanyang-university/lerobot/runs/a3ogbmg4
+INFO 2026-07-17 15:48:32 ot_train.py:298 Creating dataset
+INFO 2026-07-17 15:48:34 ot_train.py:332 Creating policy
+Fetching 27 files: 100%|██████████| 27/27 [00:00<00:00, 6565.38it/s]
+`torch_dtype` is deprecated! Use `dtype` instead!
+Loading weights: 100%|██████████| 1031/1031 [00:00<00:00, 2551.60it/s]
+INFO 2026-07-17 15:48:38 ot_train.py:405 Creating optimizer and scheduler
+INFO 2026-07-17 15:48:38 ot_train.py:437 Output dir: /home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline
+INFO 2026-07-17 15:48:38 ot_train.py:444 cfg.steps=60000 (60K)
+INFO 2026-07-17 15:48:38 ot_train.py:445 dataset.num_frames=218367 (218K)
+INFO 2026-07-17 15:48:38 ot_train.py:446 dataset.num_episodes=4930
+INFO 2026-07-17 15:48:38 ot_train.py:449 Effective batch size: 128 x 1 = 128
+INFO 2026-07-17 15:48:38 ot_train.py:450 num_learnable_params=1620515968 (2B)
+INFO 2026-07-17 15:48:38 ot_train.py:451 num_total_params=3144016000 (3B)
+Training:   0%|          | 0/60000 [00:00<?, ?step/s]INFO 2026-07-17 15:48:38 ot_train.py:602 Start offline training on a fixed dataset, with effective batch size: 128
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+Training:   7%|▋         | 4200/60000 [4:06:15<55:51:35,  3.60s/step]INFO 2026-07-17 19:54:54 ot_train.py:646 step:4K smpl:538K ep:12K epch:2.46 loss:0.055 grdn:0.263 lr:9.9e-05 updt_s:2.391 data_s:1.171 smp/s:36 mem_gb:52.79
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+Training:   8%|▊         | 5000/60000 [4:53:40<53:22:02,  3.49s/step]INFO 2026-07-17 20:42:19 ot_train.py:646 step:5K smpl:640K ep:14K epch:2.93 loss:0.053 grdn:0.252 lr:9.9e-05 updt_s:2.383 data_s:1.160 smp/s:36 mem_gb:52.79
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+Training:   9%|▉         | 5400/60000 [5:17:06<53:23:36,  3.52s/step]INFO 2026-07-17 21:05:45 ot_train.py:646 step:5K smpl:691K ep:16K epch:3.17 loss:0.052 grdn:0.240 lr:9.8e-05 updt_s:2.371 data_s:1.147 smp/s:36 mem_gb:52.79
+Training:   9%|▉         | 5600/60000 [5:28:48<52:51:47,  3.50s/step]INFO 2026-07-17 21:17:27 ot_train.py:646 step:6K smpl:717K ep:16K epch:3.28 loss:0.051 grdn:0.241 lr:9.8e-05 updt_s:2.363 data_s:1.145 smp/s:36 mem_gb:52.79
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+Training:  10%|█         | 6000/60000 [5:52:12<52:32:43,  3.50s/step]INFO 2026-07-17 21:40:51 ot_train.py:646 step:6K smpl:768K ep:17K epch:3.52 loss:0.053 grdn:0.243 lr:9.8e-05 updt_s:2.357 data_s:1.148 smp/s:37 mem_gb:52.79
+Training:  10%|█         | 6200/60000 [6:03:54<52:55:26,  3.54s/step]INFO 2026-07-17 21:52:33 ot_train.py:646 step:6K smpl:794K ep:18K epch:3.63 loss:0.050 grdn:0.230 lr:9.8e-05 updt_s:2.360 data_s:1.149 smp/s:36 mem_gb:52.79
+Training:  11%|█         | 6400/60000 [6:15:37<52:08:13,  3.50s/step]INFO 2026-07-17 22:04:16 ot_train.py:646 step:6K smpl:819K ep:18K epch:3.75 loss:0.051 grdn:0.240 lr:9.8e-05 updt_s:2.364 data_s:1.151 smp/s:36 mem_gb:52.79
+Training:  11%|█         | 6600/60000 [6:27:19<52:01:01,  3.51s/step]INFO 2026-07-17 22:15:58 ot_train.py:646 step:7K smpl:845K ep:19K epch:3.87 loss:0.052 grdn:0.237 lr:9.8e-05 updt_s:2.359 data_s:1.149 smp/s:36 mem_gb:52.79
+Training:  11%|█▏        | 6800/60000 [6:39:02<53:07:11,  3.59s/step]INFO 2026-07-17 22:27:41 ot_train.py:646 step:7K smpl:870K ep:20K epch:3.99 loss:0.050 grdn:0.230 lr:9.7e-05 updt_s:2.352 data_s:1.157 smp/s:36 mem_gb:52.71
+Training:  12%|█▏        | 7000/60000 [6:50:43<51:53:34,  3.52s/step]INFO 2026-07-17 22:39:22 ot_train.py:646 step:7K smpl:896K ep:20K epch:4.10 loss:0.047 grdn:0.215 lr:9.7e-05 updt_s:2.361 data_s:1.145 smp/s:37 mem_gb:52.79
+Training:  12%|█▏        | 7200/60000 [7:02:26<51:08:34,  3.49s/step]INFO 2026-07-17 22:51:05 ot_train.py:646 step:7K smpl:922K ep:21K epch:4.22 loss:0.048 grdn:0.228 lr:9.7e-05 updt_s:2.363 data_s:1.148 smp/s:36 mem_gb:52.79
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+Training:  13%|█▎        | 8000/60000 [7:49:15<50:28:09,  3.49s/step]INFO 2026-07-17 23:37:54 ot_train.py:646 step:8K smpl:1M ep:23K epch:4.69 loss:0.048 grdn:0.217 lr:9.6e-05 updt_s:2.354 data_s:1.157 smp/s:36 mem_gb:52.71
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+Training:  14%|█▍        | 8400/60000 [8:12:41<50:05:38,  3.49s/step]INFO 2026-07-18 00:01:20 ot_train.py:646 step:8K smpl:1M ep:24K epch:4.92 loss:0.046 grdn:0.211 lr:9.6e-05 updt_s:2.355 data_s:1.150 smp/s:37 mem_gb:52.79
+Training:  14%|█▍        | 8600/60000 [8:24:23<49:56:32,  3.50s/step]INFO 2026-07-18 00:13:02 ot_train.py:646 step:9K smpl:1M ep:25K epch:5.04 loss:0.047 grdn:0.226 lr:9.6e-05 updt_s:2.361 data_s:1.148 smp/s:36 mem_gb:52.79
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+Training:  15%|█▌        | 9000/60000 [8:47:48<50:33:30,  3.57s/step]INFO 2026-07-18 00:36:27 ot_train.py:646 step:9K smpl:1M ep:26K epch:5.28 loss:0.046 grdn:0.214 lr:9.5e-05 updt_s:2.362 data_s:1.149 smp/s:36 mem_gb:52.79
+Training:  15%|█▌        | 9200/60000 [8:59:30<49:39:40,  3.52s/step]INFO 2026-07-18 00:48:09 ot_train.py:646 step:9K smpl:1M ep:27K epch:5.39 loss:0.045 grdn:0.204 lr:9.5e-05 updt_s:2.356 data_s:1.155 smp/s:36 mem_gb:52.71
+Training:  16%|█▌        | 9400/60000 [9:11:13<48:54:27,  3.48s/step]INFO 2026-07-18 00:59:52 ot_train.py:646 step:9K smpl:1M ep:27K epch:5.51 loss:0.045 grdn:0.208 lr:9.5e-05 updt_s:2.367 data_s:1.146 smp/s:36 mem_gb:52.79
+Training:  16%|█▌        | 9600/60000 [9:22:57<49:47:20,  3.56s/step]INFO 2026-07-18 01:11:36 ot_train.py:646 step:10K smpl:1M ep:28K epch:5.63 loss:0.045 grdn:0.202 lr:9.4e-05 updt_s:2.371 data_s:1.146 smp/s:36 mem_gb:52.79
+Training:  16%|█▋        | 9800/60000 [9:34:40<49:08:31,  3.52s/step]INFO 2026-07-18 01:23:19 ot_train.py:646 step:10K smpl:1M ep:28K epch:5.74 loss:0.045 grdn:0.216 lr:9.4e-05 updt_s:2.368 data_s:1.146 smp/s:36 mem_gb:52.79
+Training:  17%|█▋        | 10000/60000 [9:46:23<48:48:18,  3.51s/step]INFO 2026-07-18 01:35:02 ot_train.py:646 step:10K smpl:1M ep:29K epch:5.86 loss:0.044 grdn:0.203 lr:9.4e-05 updt_s:2.369 data_s:1.144 smp/s:36 mem_gb:52.79
+Training:  17%|█▋        | 10200/60000 [9:58:06<48:43:20,  3.52s/step]INFO 2026-07-18 01:46:45 ot_train.py:646 step:10K smpl:1M ep:29K epch:5.98 loss:0.045 grdn:0.216 lr:9.4e-05 updt_s:2.360 data_s:1.153 smp/s:36 mem_gb:52.71
+Training:  17%|█▋        | 10400/60000 [10:09:47<48:17:51,  3.51s/step]INFO 2026-07-18 01:58:26 ot_train.py:646 step:10K smpl:1M ep:30K epch:6.10 loss:0.043 grdn:0.208 lr:9.3e-05 updt_s:2.362 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  18%|█▊        | 10600/60000 [10:21:27<48:35:25,  3.54s/step]INFO 2026-07-18 02:10:06 ot_train.py:646 step:11K smpl:1M ep:31K epch:6.21 loss:0.043 grdn:0.203 lr:9.3e-05 updt_s:2.357 data_s:1.141 smp/s:37 mem_gb:52.79
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+Training:  18%|█▊        | 11000/60000 [10:44:49<47:25:01,  3.48s/step]INFO 2026-07-18 02:33:28 ot_train.py:646 step:11K smpl:1M ep:32K epch:6.45 loss:0.042 grdn:0.202 lr:9.3e-05 updt_s:2.361 data_s:1.146 smp/s:36 mem_gb:52.79
+Training:  19%|█▊        | 11200/60000 [10:56:29<47:43:53,  3.52s/step]INFO 2026-07-18 02:45:08 ot_train.py:646 step:11K smpl:1M ep:32K epch:6.57 loss:0.042 grdn:0.204 lr:9.2e-05 updt_s:2.356 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  19%|█▉        | 11400/60000 [11:08:08<47:23:30,  3.51s/step]INFO 2026-07-18 02:56:47 ot_train.py:646 step:11K smpl:1M ep:33K epch:6.68 loss:0.042 grdn:0.209 lr:9.2e-05 updt_s:2.347 data_s:1.146 smp/s:37 mem_gb:52.71
+Training:  19%|█▉        | 11600/60000 [11:19:49<46:49:30,  3.48s/step]INFO 2026-07-18 03:08:28 ot_train.py:646 step:12K smpl:1M ep:34K epch:6.80 loss:0.041 grdn:0.211 lr:9.2e-05 updt_s:2.358 data_s:1.148 smp/s:37 mem_gb:52.79
+Training:  20%|█▉        | 11800/60000 [11:31:30<47:05:20,  3.52s/step]INFO 2026-07-18 03:20:09 ot_train.py:646 step:12K smpl:2M ep:34K epch:6.92 loss:0.041 grdn:0.202 lr:9.2e-05 updt_s:2.358 data_s:1.145 smp/s:37 mem_gb:52.79
+Training:  20%|██        | 12000/60000 [11:43:11<46:22:08,  3.48s/step]INFO 2026-07-18 03:31:50 ot_train.py:646 step:12K smpl:2M ep:35K epch:7.03 loss:0.041 grdn:0.201 lr:9.1e-05 updt_s:2.361 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  20%|██        | 12200/60000 [11:54:55<46:48:17,  3.53s/step]INFO 2026-07-18 03:43:34 ot_train.py:646 step:12K smpl:2M ep:35K epch:7.15 loss:0.041 grdn:0.209 lr:9.1e-05 updt_s:2.367 data_s:1.148 smp/s:36 mem_gb:52.79
+Training:  21%|██        | 12400/60000 [12:06:35<46:16:20,  3.50s/step]INFO 2026-07-18 03:55:14 ot_train.py:646 step:12K smpl:2M ep:36K epch:7.27 loss:0.042 grdn:0.213 lr:9.1e-05 updt_s:2.355 data_s:1.145 smp/s:37 mem_gb:52.79
+Training:  21%|██        | 12600/60000 [12:18:17<45:44:14,  3.47s/step]INFO 2026-07-18 04:06:56 ot_train.py:646 step:13K smpl:2M ep:36K epch:7.39 loss:0.041 grdn:0.207 lr:9.0e-05 updt_s:2.355 data_s:1.151 smp/s:37 mem_gb:52.71
+Training:  21%|██▏       | 12800/60000 [12:29:59<45:54:30,  3.50s/step]INFO 2026-07-18 04:18:38 ot_train.py:646 step:13K smpl:2M ep:37K epch:7.50 loss:0.040 grdn:0.202 lr:9.0e-05 updt_s:2.366 data_s:1.144 smp/s:36 mem_gb:52.79
+Training:  22%|██▏       | 13000/60000 [12:41:41<45:48:34,  3.51s/step]INFO 2026-07-18 04:30:20 ot_train.py:646 step:13K smpl:2M ep:38K epch:7.62 loss:0.039 grdn:0.203 lr:9.0e-05 updt_s:2.362 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  22%|██▏       | 13200/60000 [12:53:22<45:25:39,  3.49s/step]INFO 2026-07-18 04:42:01 ot_train.py:646 step:13K smpl:2M ep:38K epch:7.74 loss:0.039 grdn:0.200 lr:8.9e-05 updt_s:2.359 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  22%|██▏       | 13400/60000 [13:05:04<45:06:39,  3.48s/step]INFO 2026-07-18 04:53:42 ot_train.py:646 step:13K smpl:2M ep:39K epch:7.85 loss:0.040 grdn:0.198 lr:8.9e-05 updt_s:2.361 data_s:1.147 smp/s:36 mem_gb:52.79
+Training:  23%|██▎       | 13600/60000 [13:16:45<45:18:36,  3.52s/step]INFO 2026-07-18 05:05:24 ot_train.py:646 step:14K smpl:2M ep:39K epch:7.97 loss:0.039 grdn:0.208 lr:8.9e-05 updt_s:2.353 data_s:1.153 smp/s:37 mem_gb:52.71
+Training:  23%|██▎       | 13800/60000 [13:28:27<44:39:19,  3.48s/step]INFO 2026-07-18 05:17:06 ot_train.py:646 step:14K smpl:2M ep:40K epch:8.09 loss:0.039 grdn:0.197 lr:8.8e-05 updt_s:2.367 data_s:1.144 smp/s:36 mem_gb:52.79
+Training:  23%|██▎       | 14000/60000 [13:40:09<44:26:54,  3.48s/step]INFO 2026-07-18 05:28:48 ot_train.py:646 step:14K smpl:2M ep:40K epch:8.21 loss:0.038 grdn:0.198 lr:8.8e-05 updt_s:2.365 data_s:1.144 smp/s:36 mem_gb:52.79
+Training:  24%|██▎       | 14200/60000 [13:51:51<44:12:47,  3.48s/step]INFO 2026-07-18 05:40:30 ot_train.py:646 step:14K smpl:2M ep:41K epch:8.32 loss:0.039 grdn:0.198 lr:8.8e-05 updt_s:2.361 data_s:1.147 smp/s:36 mem_gb:52.79
+Training:  24%|██▍       | 14400/60000 [14:03:34<44:22:55,  3.50s/step]INFO 2026-07-18 05:52:13 ot_train.py:646 step:14K smpl:2M ep:42K epch:8.44 loss:0.039 grdn:0.205 lr:8.7e-05 updt_s:2.364 data_s:1.145 smp/s:36 mem_gb:52.79
+Training:  24%|██▍       | 14600/60000 [14:15:15<44:40:07,  3.54s/step]INFO 2026-07-18 06:03:54 ot_train.py:646 step:15K smpl:2M ep:42K epch:8.56 loss:0.040 grdn:0.204 lr:8.7e-05 updt_s:2.358 data_s:1.148 smp/s:37 mem_gb:52.79
+Training:  25%|██▍       | 14800/60000 [14:26:55<43:33:40,  3.47s/step]INFO 2026-07-18 06:15:34 ot_train.py:646 step:15K smpl:2M ep:43K epch:8.68 loss:0.038 grdn:0.200 lr:8.7e-05 updt_s:2.345 data_s:1.150 smp/s:37 mem_gb:52.71
+Training:  25%|██▌       | 15000/60000 [14:38:34<43:28:06,  3.48s/step]INFO 2026-07-18 06:27:13 ot_train.py:646 step:15K smpl:2M ep:43K epch:8.79 loss:0.038 grdn:0.207 lr:8.6e-05 updt_s:2.356 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  25%|██▌       | 15200/60000 [14:50:14<43:34:33,  3.50s/step]INFO 2026-07-18 06:38:53 ot_train.py:646 step:15K smpl:2M ep:44K epch:8.91 loss:0.036 grdn:0.192 lr:8.6e-05 updt_s:2.357 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  26%|██▌       | 15400/60000 [15:01:56<43:33:11,  3.52s/step]INFO 2026-07-18 06:50:35 ot_train.py:646 step:15K smpl:2M ep:45K epch:9.03 loss:0.037 grdn:0.195 lr:8.5e-05 updt_s:2.365 data_s:1.142 smp/s:36 mem_gb:52.79
+Training:  26%|██▌       | 15600/60000 [15:13:36<43:15:44,  3.51s/step]INFO 2026-07-18 07:02:15 ot_train.py:646 step:16K smpl:2M ep:45K epch:9.14 loss:0.038 grdn:0.202 lr:8.5e-05 updt_s:2.357 data_s:1.143 smp/s:37 mem_gb:52.79
+Training:  26%|██▋       | 15800/60000 [15:25:16<42:29:26,  3.46s/step]INFO 2026-07-18 07:13:55 ot_train.py:646 step:16K smpl:2M ep:46K epch:9.26 loss:0.037 grdn:0.200 lr:8.5e-05 updt_s:2.354 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  27%|██▋       | 16000/60000 [15:36:57<42:37:05,  3.49s/step]INFO 2026-07-18 07:25:36 ot_train.py:646 step:16K smpl:2M ep:46K epch:9.38 loss:0.036 grdn:0.190 lr:8.4e-05 updt_s:2.355 data_s:1.151 smp/s:37 mem_gb:52.71
+Training:  27%|██▋       | 16200/60000 [15:48:38<42:46:14,  3.52s/step]INFO 2026-07-18 07:37:16 ot_train.py:646 step:16K smpl:2M ep:47K epch:9.50 loss:0.036 grdn:0.194 lr:8.4e-05 updt_s:2.358 data_s:1.143 smp/s:37 mem_gb:52.79
+Training:  27%|██▋       | 16400/60000 [16:00:19<42:08:11,  3.48s/step]INFO 2026-07-18 07:48:58 ot_train.py:646 step:16K smpl:2M ep:47K epch:9.61 loss:0.037 grdn:0.198 lr:8.4e-05 updt_s:2.360 data_s:1.145 smp/s:37 mem_gb:52.79
+Training:  28%|██▊       | 16600/60000 [16:12:00<42:03:53,  3.49s/step]INFO 2026-07-18 08:00:39 ot_train.py:646 step:17K smpl:2M ep:48K epch:9.73 loss:0.036 grdn:0.193 lr:8.3e-05 updt_s:2.361 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  28%|██▊       | 16800/60000 [16:23:42<42:03:45,  3.51s/step]INFO 2026-07-18 08:12:21 ot_train.py:646 step:17K smpl:2M ep:49K epch:9.85 loss:0.036 grdn:0.198 lr:8.3e-05 updt_s:2.363 data_s:1.143 smp/s:37 mem_gb:52.79
+Training:  28%|██▊       | 17000/60000 [16:35:23<41:40:02,  3.49s/step]INFO 2026-07-18 08:24:02 ot_train.py:646 step:17K smpl:2M ep:49K epch:9.96 loss:0.036 grdn:0.210 lr:8.2e-05 updt_s:2.351 data_s:1.152 smp/s:37 mem_gb:52.71
+Training:  29%|██▊       | 17200/60000 [16:47:05<41:25:32,  3.48s/step]INFO 2026-07-18 08:35:44 ot_train.py:646 step:17K smpl:2M ep:50K epch:10.08 loss:0.036 grdn:0.200 lr:8.2e-05 updt_s:2.367 data_s:1.142 smp/s:36 mem_gb:52.79
+Training:  29%|██▉       | 17400/60000 [16:58:46<41:17:48,  3.49s/step]INFO 2026-07-18 08:47:25 ot_train.py:646 step:17K smpl:2M ep:50K epch:10.20 loss:0.035 grdn:0.210 lr:8.2e-05 updt_s:2.364 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  29%|██▉       | 17600/60000 [17:10:28<41:12:14,  3.50s/step]INFO 2026-07-18 08:59:07 ot_train.py:646 step:18K smpl:2M ep:51K epch:10.32 loss:0.034 grdn:0.192 lr:8.1e-05 updt_s:2.368 data_s:1.143 smp/s:36 mem_gb:52.79
+Training:  30%|██▉       | 17800/60000 [17:22:09<40:44:31,  3.48s/step]INFO 2026-07-18 09:10:47 ot_train.py:646 step:18K smpl:2M ep:51K epch:10.43 loss:0.034 grdn:0.189 lr:8.1e-05 updt_s:2.358 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  30%|███       | 18000/60000 [17:33:49<40:46:18,  3.49s/step]INFO 2026-07-18 09:22:28 ot_train.py:646 step:18K smpl:2M ep:52K epch:10.55 loss:0.034 grdn:0.189 lr:8.0e-05 updt_s:2.361 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  30%|███       | 18200/60000 [17:45:30<40:42:39,  3.51s/step]INFO 2026-07-18 09:34:09 ot_train.py:646 step:18K smpl:2M ep:53K epch:10.67 loss:0.034 grdn:0.204 lr:8.0e-05 updt_s:2.357 data_s:1.146 smp/s:37 mem_gb:52.71
+Training:  31%|███       | 18400/60000 [17:57:11<40:20:32,  3.49s/step]INFO 2026-07-18 09:45:50 ot_train.py:646 step:18K smpl:2M ep:53K epch:10.79 loss:0.033 grdn:0.197 lr:7.9e-05 updt_s:2.367 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  31%|███       | 18600/60000 [18:08:52<40:07:55,  3.49s/step]INFO 2026-07-18 09:57:31 ot_train.py:646 step:19K smpl:2M ep:54K epch:10.90 loss:0.033 grdn:0.205 lr:7.9e-05 updt_s:2.365 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  31%|███▏      | 18800/60000 [18:20:32<40:09:57,  3.51s/step]INFO 2026-07-18 10:09:11 ot_train.py:646 step:19K smpl:2M ep:54K epch:11.02 loss:0.034 grdn:0.194 lr:7.9e-05 updt_s:2.359 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  32%|███▏      | 19000/60000 [18:32:12<39:46:27,  3.49s/step]INFO 2026-07-18 10:20:51 ot_train.py:646 step:19K smpl:2M ep:55K epch:11.14 loss:0.033 grdn:0.198 lr:7.8e-05 updt_s:2.356 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  32%|███▏      | 19200/60000 [18:43:53<41:38:00,  3.67s/step]INFO 2026-07-18 10:32:32 ot_train.py:646 step:19K smpl:2M ep:55K epch:11.25 loss:0.033 grdn:0.195 lr:7.8e-05 updt_s:2.353 data_s:1.149 smp/s:37 mem_gb:52.71
+Training:  32%|███▏      | 19400/60000 [18:55:33<39:28:50,  3.50s/step]INFO 2026-07-18 10:44:12 ot_train.py:646 step:19K smpl:2M ep:56K epch:11.37 loss:0.033 grdn:0.204 lr:7.7e-05 updt_s:2.363 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  33%|███▎      | 19600/60000 [19:07:12<38:58:54,  3.47s/step]INFO 2026-07-18 10:55:51 ot_train.py:646 step:20K smpl:3M ep:57K epch:11.49 loss:0.032 grdn:0.200 lr:7.7e-05 updt_s:2.357 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  33%|███▎      | 19800/60000 [19:18:53<39:04:03,  3.50s/step]INFO 2026-07-18 11:07:32 ot_train.py:646 step:20K smpl:3M ep:57K epch:11.61 loss:0.033 grdn:0.203 lr:7.6e-05 updt_s:2.362 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  33%|███▎      | 20000/60000 [19:30:35<38:37:54,  3.48s/step]INFO 2026-07-18 11:19:14 ot_train.py:646 step:20K smpl:3M ep:58K epch:11.72 loss:0.033 grdn:0.201 lr:7.6e-05 updt_s:2.368 data_s:1.140 smp/s:36 mem_gb:52.79
+Training:  34%|███▎      | 20200/60000 [19:42:18<38:39:11,  3.50s/step]INFO 2026-07-18 11:30:57 ot_train.py:646 step:20K smpl:3M ep:58K epch:11.84 loss:0.033 grdn:0.197 lr:7.6e-05 updt_s:2.365 data_s:1.151 smp/s:36 mem_gb:52.79
+Training:  34%|███▍      | 20400/60000 [19:53:57<38:28:49,  3.50s/step]INFO 2026-07-18 11:42:36 ot_train.py:646 step:20K smpl:3M ep:59K epch:11.96 loss:0.032 grdn:0.198 lr:7.5e-05 updt_s:2.351 data_s:1.141 smp/s:37 mem_gb:52.71
+Training:  34%|███▍      | 20600/60000 [20:05:36<38:15:38,  3.50s/step]INFO 2026-07-18 11:54:14 ot_train.py:646 step:21K smpl:3M ep:60K epch:12.08 loss:0.031 grdn:0.198 lr:7.5e-05 updt_s:2.355 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  35%|███▍      | 20800/60000 [20:17:16<38:11:32,  3.51s/step]INFO 2026-07-18 12:05:55 ot_train.py:646 step:21K smpl:3M ep:60K epch:12.19 loss:0.031 grdn:0.194 lr:7.4e-05 updt_s:2.361 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  35%|███▌      | 21000/60000 [20:28:54<37:49:19,  3.49s/step]INFO 2026-07-18 12:17:33 ot_train.py:646 step:21K smpl:3M ep:61K epch:12.31 loss:0.031 grdn:0.195 lr:7.4e-05 updt_s:2.353 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  35%|███▌      | 21200/60000 [20:40:34<37:42:59,  3.50s/step]INFO 2026-07-18 12:29:13 ot_train.py:646 step:21K smpl:3M ep:61K epch:12.43 loss:0.032 grdn:0.196 lr:7.3e-05 updt_s:2.358 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  36%|███▌      | 21400/60000 [20:52:12<37:26:57,  3.49s/step]INFO 2026-07-18 12:40:51 ot_train.py:646 step:21K smpl:3M ep:62K epch:12.54 loss:0.031 grdn:0.195 lr:7.3e-05 updt_s:2.354 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  36%|███▌      | 21600/60000 [21:03:52<36:56:06,  3.46s/step]INFO 2026-07-18 12:52:31 ot_train.py:646 step:22K smpl:3M ep:62K epch:12.66 loss:0.030 grdn:0.196 lr:7.2e-05 updt_s:2.346 data_s:1.149 smp/s:37 mem_gb:52.71
+Training:  36%|███▋      | 21800/60000 [21:15:30<36:55:06,  3.48s/step]INFO 2026-07-18 13:04:09 ot_train.py:646 step:22K smpl:3M ep:63K epch:12.78 loss:0.030 grdn:0.204 lr:7.2e-05 updt_s:2.355 data_s:1.135 smp/s:37 mem_gb:52.79
+Training:  37%|███▋      | 22000/60000 [21:27:09<36:42:26,  3.48s/step]INFO 2026-07-18 13:15:48 ot_train.py:646 step:22K smpl:3M ep:64K epch:12.90 loss:0.031 grdn:0.205 lr:7.1e-05 updt_s:2.356 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  37%|███▋      | 22200/60000 [21:38:49<36:44:20,  3.50s/step]INFO 2026-07-18 13:27:28 ot_train.py:646 step:22K smpl:3M ep:64K epch:13.01 loss:0.030 grdn:0.197 lr:7.1e-05 updt_s:2.359 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  37%|███▋      | 22400/60000 [21:50:29<36:52:05,  3.53s/step]INFO 2026-07-18 13:39:08 ot_train.py:646 step:22K smpl:3M ep:65K epch:13.13 loss:0.030 grdn:0.197 lr:7.0e-05 updt_s:2.362 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  38%|███▊      | 22600/60000 [22:02:09<36:30:25,  3.51s/step]INFO 2026-07-18 13:50:48 ot_train.py:646 step:23K smpl:3M ep:65K epch:13.25 loss:0.029 grdn:0.196 lr:7.0e-05 updt_s:2.351 data_s:1.148 smp/s:37 mem_gb:52.71
+Training:  38%|███▊      | 22800/60000 [22:13:47<36:10:33,  3.50s/step]INFO 2026-07-18 14:02:26 ot_train.py:646 step:23K smpl:3M ep:66K epch:13.36 loss:0.029 grdn:0.198 lr:6.9e-05 updt_s:2.354 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  38%|███▊      | 23000/60000 [22:25:27<35:47:07,  3.48s/step]INFO 2026-07-18 14:14:06 ot_train.py:646 step:23K smpl:3M ep:66K epch:13.48 loss:0.028 grdn:0.191 lr:6.9e-05 updt_s:2.358 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  39%|███▊      | 23200/60000 [22:37:06<35:41:50,  3.49s/step]INFO 2026-07-18 14:25:45 ot_train.py:646 step:23K smpl:3M ep:67K epch:13.60 loss:0.028 grdn:0.198 lr:6.8e-05 updt_s:2.359 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  39%|███▉      | 23400/60000 [22:48:45<35:32:33,  3.50s/step]INFO 2026-07-18 14:37:24 ot_train.py:646 step:23K smpl:3M ep:68K epch:13.72 loss:0.028 grdn:0.192 lr:6.8e-05 updt_s:2.357 data_s:1.136 smp/s:37 mem_gb:52.79
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+Training:  45%|████▌     | 27000/60000 [26:18:40<31:57:35,  3.49s/step]INFO 2026-07-18 18:07:19 ot_train.py:646 step:27K smpl:3M ep:78K epch:15.83 loss:0.026 grdn:0.187 lr:5.9e-05 updt_s:2.364 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  45%|████▌     | 27200/60000 [26:30:20<31:43:29,  3.48s/step]INFO 2026-07-18 18:18:59 ot_train.py:646 step:27K smpl:3M ep:79K epch:15.94 loss:0.025 grdn:0.190 lr:5.8e-05 updt_s:2.356 data_s:1.144 smp/s:37 mem_gb:52.71
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+Training:  46%|████▌     | 27600/60000 [26:53:41<31:22:41,  3.49s/step]INFO 2026-07-18 18:42:19 ot_train.py:646 step:28K smpl:4M ep:80K epch:16.18 loss:0.025 grdn:0.186 lr:5.7e-05 updt_s:2.363 data_s:1.140 smp/s:37 mem_gb:52.79
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+Training:  47%|████▋     | 28000/60000 [27:16:59<31:07:55,  3.50s/step]INFO 2026-07-18 19:05:38 ot_train.py:646 step:28K smpl:4M ep:81K epch:16.41 loss:0.024 grdn:0.193 lr:5.6e-05 updt_s:2.357 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  47%|████▋     | 28200/60000 [27:28:41<30:41:38,  3.47s/step]INFO 2026-07-18 19:17:20 ot_train.py:646 step:28K smpl:4M ep:81K epch:16.53 loss:0.024 grdn:0.193 lr:5.6e-05 updt_s:2.366 data_s:1.142 smp/s:36 mem_gb:52.79
+Training:  47%|████▋     | 28400/60000 [27:40:21<30:36:21,  3.49s/step]INFO 2026-07-18 19:29:00 ot_train.py:646 step:28K smpl:4M ep:82K epch:16.65 loss:0.024 grdn:0.191 lr:5.5e-05 updt_s:2.350 data_s:1.149 smp/s:37 mem_gb:52.71
+Training:  48%|████▊     | 28600/60000 [27:52:01<30:19:17,  3.48s/step]INFO 2026-07-18 19:40:40 ot_train.py:646 step:29K smpl:4M ep:83K epch:16.76 loss:0.023 grdn:0.182 lr:5.5e-05 updt_s:2.357 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  48%|████▊     | 28800/60000 [28:03:41<30:21:29,  3.50s/step]INFO 2026-07-18 19:52:20 ot_train.py:646 step:29K smpl:4M ep:83K epch:16.88 loss:0.023 grdn:0.185 lr:5.4e-05 updt_s:2.354 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  48%|████▊     | 29000/60000 [28:15:21<29:56:06,  3.48s/step]INFO 2026-07-18 20:04:00 ot_train.py:646 step:29K smpl:4M ep:84K epch:17.00 loss:0.023 grdn:0.178 lr:5.4e-05 updt_s:2.359 data_s:1.140 smp/s:37 mem_gb:52.79
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+Training:  49%|████▉     | 29400/60000 [28:38:41<29:39:14,  3.49s/step]INFO 2026-07-18 20:27:20 ot_train.py:646 step:29K smpl:4M ep:85K epch:17.23 loss:0.023 grdn:0.188 lr:5.3e-05 updt_s:2.347 data_s:1.146 smp/s:37 mem_gb:52.71
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+Training:  50%|████▉     | 29800/60000 [29:01:59<29:22:18,  3.50s/step]INFO 2026-07-18 20:50:38 ot_train.py:646 step:30K smpl:4M ep:86K epch:17.47 loss:0.022 grdn:0.184 lr:5.1e-05 updt_s:2.355 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  50%|█████     | 30000/60000 [29:13:39<28:57:38,  3.48s/step]INFO 2026-07-18 21:02:18 ot_train.py:646 step:30K smpl:4M ep:87K epch:17.59 loss:0.022 grdn:0.188 lr:5.1e-05 updt_s:2.358 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  50%|█████     | 30200/60000 [29:25:18<28:59:41,  3.50s/step]INFO 2026-07-18 21:13:57 ot_train.py:646 step:30K smpl:4M ep:87K epch:17.70 loss:0.022 grdn:0.181 lr:5.0e-05 updt_s:2.356 data_s:1.141 smp/s:37 mem_gb:52.79
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+Training:  51%|█████▏    | 30800/60000 [30:00:15<28:14:43,  3.48s/step]INFO 2026-07-18 21:48:54 ot_train.py:646 step:31K smpl:4M ep:89K epch:18.05 loss:0.021 grdn:0.186 lr:4.9e-05 updt_s:2.355 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  52%|█████▏    | 31000/60000 [30:11:55<28:07:42,  3.49s/step]INFO 2026-07-18 22:00:34 ot_train.py:646 step:31K smpl:4M ep:90K epch:18.17 loss:0.021 grdn:0.186 lr:4.8e-05 updt_s:2.357 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  52%|█████▏    | 31200/60000 [30:23:35<27:45:41,  3.47s/step]INFO 2026-07-18 22:12:14 ot_train.py:646 step:31K smpl:4M ep:90K epch:18.29 loss:0.021 grdn:0.184 lr:4.8e-05 updt_s:2.361 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  52%|█████▏    | 31400/60000 [30:35:15<27:36:15,  3.47s/step]INFO 2026-07-18 22:23:54 ot_train.py:646 step:31K smpl:4M ep:91K epch:18.41 loss:0.021 grdn:0.171 lr:4.7e-05 updt_s:2.355 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  53%|█████▎    | 31600/60000 [30:46:54<27:21:09,  3.47s/step]INFO 2026-07-18 22:35:33 ot_train.py:646 step:32K smpl:4M ep:91K epch:18.52 loss:0.021 grdn:0.178 lr:4.7e-05 updt_s:2.357 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  53%|█████▎    | 31800/60000 [30:58:34<28:04:45,  3.58s/step]INFO 2026-07-18 22:47:13 ot_train.py:646 step:32K smpl:4M ep:92K epch:18.64 loss:0.020 grdn:0.178 lr:4.6e-05 updt_s:2.350 data_s:1.145 smp/s:37 mem_gb:52.71
+Training:  53%|█████▎    | 32000/60000 [31:10:13<26:58:01,  3.47s/step]INFO 2026-07-18 22:58:52 ot_train.py:646 step:32K smpl:4M ep:92K epch:18.76 loss:0.020 grdn:0.179 lr:4.6e-05 updt_s:2.358 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  54%|█████▎    | 32200/60000 [31:21:52<26:49:36,  3.47s/step]INFO 2026-07-18 23:10:31 ot_train.py:646 step:32K smpl:4M ep:93K epch:18.87 loss:0.020 grdn:0.174 lr:4.5e-05 updt_s:2.358 data_s:1.134 smp/s:37 mem_gb:52.79
+Training:  54%|█████▍    | 32400/60000 [31:33:30<27:00:58,  3.52s/step]INFO 2026-07-18 23:22:08 ot_train.py:646 step:32K smpl:4M ep:94K epch:18.99 loss:0.020 grdn:0.179 lr:4.5e-05 updt_s:2.352 data_s:1.134 smp/s:37 mem_gb:52.79
+Training:  54%|█████▍    | 32600/60000 [31:45:07<26:24:06,  3.47s/step]INFO 2026-07-18 23:33:46 ot_train.py:646 step:33K smpl:4M ep:94K epch:19.11 loss:0.020 grdn:0.175 lr:4.4e-05 updt_s:2.353 data_s:1.134 smp/s:37 mem_gb:52.79
+Training:  55%|█████▍    | 32800/60000 [31:56:46<26:16:12,  3.48s/step]INFO 2026-07-18 23:45:24 ot_train.py:646 step:33K smpl:4M ep:95K epch:19.23 loss:0.019 grdn:0.165 lr:4.4e-05 updt_s:2.347 data_s:1.142 smp/s:37 mem_gb:52.71
+Training:  55%|█████▌    | 33000/60000 [32:08:25<26:07:07,  3.48s/step]INFO 2026-07-18 23:57:04 ot_train.py:646 step:33K smpl:4M ep:95K epch:19.34 loss:0.019 grdn:0.170 lr:4.3e-05 updt_s:2.361 data_s:1.133 smp/s:37 mem_gb:52.79
+Training:  55%|█████▌    | 33200/60000 [32:20:04<25:50:57,  3.47s/step]INFO 2026-07-19 00:08:42 ot_train.py:646 step:33K smpl:4M ep:96K epch:19.46 loss:0.019 grdn:0.178 lr:4.3e-05 updt_s:2.359 data_s:1.133 smp/s:37 mem_gb:52.79
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+Training:  56%|█████▌    | 33600/60000 [32:43:21<25:34:28,  3.49s/step]INFO 2026-07-19 00:32:00 ot_train.py:646 step:34K smpl:4M ep:97K epch:19.70 loss:0.019 grdn:0.171 lr:4.1e-05 updt_s:2.356 data_s:1.134 smp/s:37 mem_gb:52.79
+Training:  56%|█████▋    | 33800/60000 [32:55:01<25:19:38,  3.48s/step]INFO 2026-07-19 00:43:40 ot_train.py:646 step:34K smpl:4M ep:98K epch:19.81 loss:0.019 grdn:0.177 lr:4.1e-05 updt_s:2.362 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  57%|█████▋    | 34000/60000 [33:06:40<25:51:34,  3.58s/step]INFO 2026-07-19 00:55:19 ot_train.py:646 step:34K smpl:4M ep:98K epch:19.93 loss:0.019 grdn:0.177 lr:4.0e-05 updt_s:2.354 data_s:1.140 smp/s:37 mem_gb:52.71
+Training:  57%|█████▋    | 34200/60000 [33:18:20<25:04:37,  3.50s/step]INFO 2026-07-19 01:06:59 ot_train.py:646 step:34K smpl:4M ep:99K epch:20.05 loss:0.018 grdn:0.162 lr:4.0e-05 updt_s:2.365 data_s:1.135 smp/s:37 mem_gb:52.79
+Training:  57%|█████▋    | 34400/60000 [33:29:59<24:43:44,  3.48s/step]INFO 2026-07-19 01:18:37 ot_train.py:646 step:34K smpl:4M ep:99K epch:20.16 loss:0.018 grdn:0.176 lr:3.9e-05 updt_s:2.358 data_s:1.132 smp/s:37 mem_gb:52.79
+Training:  58%|█████▊    | 34600/60000 [33:41:38<24:38:22,  3.49s/step]INFO 2026-07-19 01:30:17 ot_train.py:646 step:35K smpl:4M ep:100K epch:20.28 loss:0.018 grdn:0.176 lr:3.9e-05 updt_s:2.363 data_s:1.134 smp/s:37 mem_gb:52.79
+Training:  58%|█████▊    | 34800/60000 [33:53:18<24:47:44,  3.54s/step]INFO 2026-07-19 01:41:57 ot_train.py:646 step:35K smpl:4M ep:101K epch:20.40 loss:0.018 grdn:0.175 lr:3.8e-05 updt_s:2.361 data_s:1.135 smp/s:37 mem_gb:52.79
+Training:  58%|█████▊    | 35000/60000 [34:04:54<25:18:25,  3.64s/step]INFO 2026-07-19 01:53:33 ot_train.py:646 step:35K smpl:4M ep:101K epch:20.52 loss:0.018 grdn:0.173 lr:3.8e-05 updt_s:2.339 data_s:1.140 smp/s:37 mem_gb:52.71
+Training:  59%|█████▊    | 35200/60000 [34:16:30<23:58:36,  3.48s/step]INFO 2026-07-19 02:05:09 ot_train.py:646 step:35K smpl:5M ep:102K epch:20.63 loss:0.017 grdn:0.169 lr:3.7e-05 updt_s:2.339 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  59%|█████▉    | 35400/60000 [34:28:07<23:45:31,  3.48s/step]INFO 2026-07-19 02:16:46 ot_train.py:646 step:35K smpl:5M ep:102K epch:20.75 loss:0.017 grdn:0.181 lr:3.7e-05 updt_s:2.343 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  59%|█████▉    | 35600/60000 [34:39:43<23:39:48,  3.49s/step]INFO 2026-07-19 02:28:21 ot_train.py:646 step:36K smpl:5M ep:103K epch:20.87 loss:0.017 grdn:0.166 lr:3.6e-05 updt_s:2.340 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  60%|█████▉    | 35800/60000 [34:51:19<23:17:48,  3.47s/step]INFO 2026-07-19 02:39:58 ot_train.py:646 step:36K smpl:5M ep:103K epch:20.98 loss:0.017 grdn:0.165 lr:3.6e-05 updt_s:2.341 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  60%|██████    | 36000/60000 [35:02:54<22:58:22,  3.45s/step]INFO 2026-07-19 02:51:33 ot_train.py:646 step:36K smpl:5M ep:104K epch:21.10 loss:0.017 grdn:0.167 lr:3.5e-05 updt_s:2.338 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  60%|██████    | 36200/60000 [35:14:31<22:57:38,  3.47s/step]INFO 2026-07-19 03:03:10 ot_train.py:646 step:36K smpl:5M ep:105K epch:21.22 loss:0.017 grdn:0.167 lr:3.5e-05 updt_s:2.333 data_s:1.147 smp/s:37 mem_gb:52.71
+Training:  61%|██████    | 36400/60000 [35:26:08<22:43:47,  3.47s/step]INFO 2026-07-19 03:14:47 ot_train.py:646 step:36K smpl:5M ep:105K epch:21.34 loss:0.016 grdn:0.165 lr:3.4e-05 updt_s:2.341 data_s:1.141 smp/s:37 mem_gb:52.79
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+Training:  63%|██████▎   | 37600/60000 [36:35:45<21:37:15,  3.47s/step]INFO 2026-07-19 04:24:24 ot_train.py:646 step:38K smpl:5M ep:109K epch:22.04 loss:0.015 grdn:0.169 lr:3.1e-05 updt_s:2.344 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  63%|██████▎   | 37800/60000 [36:47:22<21:18:32,  3.46s/step]INFO 2026-07-19 04:36:01 ot_train.py:646 step:38K smpl:5M ep:109K epch:22.16 loss:0.016 grdn:0.172 lr:3.1e-05 updt_s:2.340 data_s:1.139 smp/s:37 mem_gb:52.79
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+Training:  64%|██████▎   | 38200/60000 [37:10:32<21:00:52,  3.47s/step]INFO 2026-07-19 04:59:11 ot_train.py:646 step:38K smpl:5M ep:110K epch:22.39 loss:0.016 grdn:0.163 lr:3.0e-05 updt_s:2.339 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  64%|██████▍   | 38400/60000 [37:22:08<20:48:47,  3.47s/step]INFO 2026-07-19 05:10:47 ot_train.py:646 step:38K smpl:5M ep:111K epch:22.51 loss:0.015 grdn:0.168 lr:2.9e-05 updt_s:2.333 data_s:1.146 smp/s:37 mem_gb:52.71
+Training:  64%|██████▍   | 38600/60000 [37:33:45<21:04:44,  3.55s/step]INFO 2026-07-19 05:22:24 ot_train.py:646 step:39K smpl:5M ep:112K epch:22.63 loss:0.015 grdn:0.162 lr:2.9e-05 updt_s:2.347 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  65%|██████▍   | 38800/60000 [37:45:24<20:52:09,  3.54s/step]INFO 2026-07-19 05:34:02 ot_train.py:646 step:39K smpl:5M ep:112K epch:22.74 loss:0.015 grdn:0.172 lr:2.8e-05 updt_s:2.350 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  65%|██████▌   | 39000/60000 [37:57:14<21:16:02,  3.65s/step]INFO 2026-07-19 05:45:53 ot_train.py:646 step:39K smpl:5M ep:113K epch:22.86 loss:0.015 grdn:0.159 lr:2.8e-05 updt_s:2.387 data_s:1.164 smp/s:36 mem_gb:52.79
+Training:  65%|██████▌   | 39200/60000 [38:09:12<21:11:17,  3.67s/step]INFO 2026-07-19 05:57:50 ot_train.py:646 step:39K smpl:5M ep:113K epch:22.98 loss:0.015 grdn:0.165 lr:2.7e-05 updt_s:2.404 data_s:1.179 smp/s:36 mem_gb:52.79
+Training:  66%|██████▌   | 39400/60000 [38:21:07<20:36:15,  3.60s/step]INFO 2026-07-19 06:09:46 ot_train.py:646 step:39K smpl:5M ep:114K epch:23.10 loss:0.014 grdn:0.163 lr:2.7e-05 updt_s:2.396 data_s:1.178 smp/s:36 mem_gb:52.79
+Training:  66%|██████▌   | 39600/60000 [38:33:05<20:00:18,  3.53s/step]INFO 2026-07-19 06:21:44 ot_train.py:646 step:40K smpl:5M ep:114K epch:23.21 loss:0.014 grdn:0.164 lr:2.7e-05 updt_s:2.388 data_s:1.201 smp/s:36 mem_gb:52.71
+Training:  66%|██████▋   | 39800/60000 [38:44:56<20:11:14,  3.60s/step]INFO 2026-07-19 06:33:35 ot_train.py:646 step:40K smpl:5M ep:115K epch:23.33 loss:0.013 grdn:0.156 lr:2.6e-05 updt_s:2.383 data_s:1.169 smp/s:36 mem_gb:52.79
+Training:  67%|██████▋   | 40000/60000 [38:56:44<19:14:46,  3.46s/step]INFO 2026-07-19 06:45:22 ot_train.py:646 step:40K smpl:5M ep:116K epch:23.45 loss:0.014 grdn:0.155 lr:2.6e-05 updt_s:2.373 data_s:1.163 smp/s:36 mem_gb:52.79
+Training:  67%|██████▋   | 40200/60000 [39:08:23<19:07:30,  3.48s/step]INFO 2026-07-19 06:57:02 ot_train.py:646 step:40K smpl:5M ep:116K epch:23.56 loss:0.013 grdn:0.156 lr:2.5e-05 updt_s:2.352 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  67%|██████▋   | 40400/60000 [39:20:21<19:45:19,  3.63s/step]INFO 2026-07-19 07:09:00 ot_train.py:646 step:40K smpl:5M ep:117K epch:23.68 loss:0.014 grdn:0.170 lr:2.5e-05 updt_s:2.419 data_s:1.167 smp/s:36 mem_gb:52.79
+Training:  68%|██████▊   | 40600/60000 [39:32:22<19:50:01,  3.68s/step]INFO 2026-07-19 07:21:01 ot_train.py:646 step:41K smpl:5M ep:117K epch:23.80 loss:0.014 grdn:0.161 lr:2.4e-05 updt_s:2.431 data_s:1.173 smp/s:36 mem_gb:52.79
+Training:  68%|██████▊   | 40800/60000 [39:44:15<19:03:35,  3.57s/step]INFO 2026-07-19 07:32:54 ot_train.py:646 step:41K smpl:5M ep:118K epch:23.92 loss:0.013 grdn:0.171 lr:2.4e-05 updt_s:2.384 data_s:1.180 smp/s:36 mem_gb:52.71
+Training:  68%|██████▊   | 41000/60000 [39:56:10<18:39:17,  3.53s/step]INFO 2026-07-19 07:44:49 ot_train.py:646 step:41K smpl:5M ep:118K epch:24.03 loss:0.013 grdn:0.159 lr:2.3e-05 updt_s:2.393 data_s:1.178 smp/s:36 mem_gb:52.79
+Training:  69%|██████▊   | 41200/60000 [40:08:03<19:01:12,  3.64s/step]INFO 2026-07-19 07:56:42 ot_train.py:646 step:41K smpl:5M ep:119K epch:24.15 loss:0.013 grdn:0.156 lr:2.3e-05 updt_s:2.392 data_s:1.172 smp/s:36 mem_gb:52.79
+Training:  69%|██████▉   | 41400/60000 [40:19:44<18:01:40,  3.49s/step]INFO 2026-07-19 08:08:23 ot_train.py:646 step:41K smpl:5M ep:120K epch:24.27 loss:0.013 grdn:0.164 lr:2.2e-05 updt_s:2.356 data_s:1.147 smp/s:37 mem_gb:52.79
+Training:  69%|██████▉   | 41600/60000 [40:31:21<17:44:00,  3.47s/step]INFO 2026-07-19 08:20:00 ot_train.py:646 step:42K smpl:5M ep:120K epch:24.38 loss:0.013 grdn:0.159 lr:2.2e-05 updt_s:2.338 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  70%|██████▉   | 41800/60000 [40:42:59<17:42:50,  3.50s/step]INFO 2026-07-19 08:31:38 ot_train.py:646 step:42K smpl:5M ep:121K epch:24.50 loss:0.013 grdn:0.154 lr:2.2e-05 updt_s:2.338 data_s:1.154 smp/s:37 mem_gb:52.71
+Training:  70%|███████   | 42000/60000 [40:54:38<17:23:59,  3.48s/step]INFO 2026-07-19 08:43:17 ot_train.py:646 step:42K smpl:5M ep:121K epch:24.62 loss:0.012 grdn:0.151 lr:2.1e-05 updt_s:2.345 data_s:1.145 smp/s:37 mem_gb:52.79
+Training:  70%|███████   | 42200/60000 [41:06:15<17:08:28,  3.47s/step]INFO 2026-07-19 08:54:54 ot_train.py:646 step:42K smpl:5M ep:122K epch:24.74 loss:0.012 grdn:0.154 lr:2.1e-05 updt_s:2.342 data_s:1.144 smp/s:37 mem_gb:52.79
+Training:  71%|███████   | 42400/60000 [41:17:51<17:02:29,  3.49s/step]INFO 2026-07-19 09:06:30 ot_train.py:646 step:42K smpl:5M ep:123K epch:24.85 loss:0.012 grdn:0.156 lr:2.0e-05 updt_s:2.335 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  71%|███████   | 42600/60000 [41:29:29<16:43:06,  3.46s/step]INFO 2026-07-19 09:18:08 ot_train.py:646 step:43K smpl:5M ep:123K epch:24.97 loss:0.012 grdn:0.156 lr:2.0e-05 updt_s:2.346 data_s:1.143 smp/s:37 mem_gb:52.79
+Training:  71%|███████▏  | 42800/60000 [41:41:06<16:37:46,  3.48s/step]INFO 2026-07-19 09:29:45 ot_train.py:646 step:43K smpl:5M ep:124K epch:25.09 loss:0.012 grdn:0.152 lr:1.9e-05 updt_s:2.341 data_s:1.143 smp/s:37 mem_gb:52.79
+Training:  72%|███████▏  | 43000/60000 [41:52:44<16:22:38,  3.47s/step]INFO 2026-07-19 09:41:23 ot_train.py:646 step:43K smpl:6M ep:124K epch:25.21 loss:0.012 grdn:0.158 lr:1.9e-05 updt_s:2.335 data_s:1.150 smp/s:37 mem_gb:52.71
+Training:  72%|███████▏  | 43200/60000 [42:04:21<16:12:44,  3.47s/step]INFO 2026-07-19 09:53:00 ot_train.py:646 step:43K smpl:6M ep:125K epch:25.32 loss:0.012 grdn:0.163 lr:1.9e-05 updt_s:2.346 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  72%|███████▏  | 43400/60000 [42:15:59<16:03:56,  3.48s/step]INFO 2026-07-19 10:04:38 ot_train.py:646 step:43K smpl:6M ep:125K epch:25.44 loss:0.012 grdn:0.152 lr:1.8e-05 updt_s:2.347 data_s:1.139 smp/s:37 mem_gb:52.79
+Training:  73%|███████▎  | 43600/60000 [42:27:38<16:21:51,  3.59s/step]INFO 2026-07-19 10:16:17 ot_train.py:646 step:44K smpl:6M ep:126K epch:25.56 loss:0.011 grdn:0.153 lr:1.8e-05 updt_s:2.351 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  73%|███████▎  | 43800/60000 [42:39:38<16:17:38,  3.62s/step]INFO 2026-07-19 10:28:17 ot_train.py:646 step:44K smpl:6M ep:127K epch:25.67 loss:0.012 grdn:0.157 lr:1.7e-05 updt_s:2.425 data_s:1.171 smp/s:36 mem_gb:52.79
+Training:  73%|███████▎  | 44000/60000 [42:51:37<15:49:05,  3.56s/step]INFO 2026-07-19 10:40:16 ot_train.py:646 step:44K smpl:6M ep:127K epch:25.79 loss:0.011 grdn:0.153 lr:1.7e-05 updt_s:2.422 data_s:1.171 smp/s:36 mem_gb:52.79
+Training:  74%|███████▎  | 44200/60000 [43:03:28<15:37:42,  3.56s/step]INFO 2026-07-19 10:52:07 ot_train.py:646 step:44K smpl:6M ep:128K epch:25.91 loss:0.011 grdn:0.155 lr:1.7e-05 updt_s:2.376 data_s:1.175 smp/s:36 mem_gb:52.71
+Training:  74%|███████▍  | 44400/60000 [43:15:16<15:19:18,  3.54s/step]INFO 2026-07-19 11:03:55 ot_train.py:646 step:44K smpl:6M ep:128K epch:26.03 loss:0.011 grdn:0.158 lr:1.6e-05 updt_s:2.378 data_s:1.163 smp/s:36 mem_gb:52.79
+Training:  74%|███████▍  | 44600/60000 [43:27:08<15:19:23,  3.58s/step]INFO 2026-07-19 11:15:47 ot_train.py:646 step:45K smpl:6M ep:129K epch:26.14 loss:0.011 grdn:0.156 lr:1.6e-05 updt_s:2.393 data_s:1.165 smp/s:36 mem_gb:52.79
+Training:  75%|███████▍  | 44800/60000 [43:38:51<14:50:54,  3.52s/step]INFO 2026-07-19 11:27:30 ot_train.py:646 step:45K smpl:6M ep:129K epch:26.26 loss:0.011 grdn:0.157 lr:1.5e-05 updt_s:2.368 data_s:1.143 smp/s:36 mem_gb:52.79
+Training:  75%|███████▌  | 45000/60000 [43:50:34<14:40:28,  3.52s/step]INFO 2026-07-19 11:39:13 ot_train.py:646 step:45K smpl:6M ep:130K epch:26.38 loss:0.011 grdn:0.152 lr:1.5e-05 updt_s:2.370 data_s:1.141 smp/s:36 mem_gb:52.79
+Training:  75%|███████▌  | 45200/60000 [44:02:16<14:31:37,  3.53s/step]INFO 2026-07-19 11:50:55 ot_train.py:646 step:45K smpl:6M ep:131K epch:26.49 loss:0.011 grdn:0.154 lr:1.5e-05 updt_s:2.359 data_s:1.152 smp/s:36 mem_gb:52.71
+Training:  76%|███████▌  | 45400/60000 [44:13:57<14:20:39,  3.54s/step]INFO 2026-07-19 12:02:36 ot_train.py:646 step:45K smpl:6M ep:131K epch:26.61 loss:0.011 grdn:0.149 lr:1.4e-05 updt_s:2.361 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  76%|███████▌  | 45600/60000 [44:25:36<14:01:37,  3.51s/step]INFO 2026-07-19 12:14:15 ot_train.py:646 step:46K smpl:6M ep:132K epch:26.73 loss:0.010 grdn:0.148 lr:1.4e-05 updt_s:2.357 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  76%|███████▋  | 45800/60000 [44:37:16<13:53:10,  3.52s/step]INFO 2026-07-19 12:25:55 ot_train.py:646 step:46K smpl:6M ep:132K epch:26.85 loss:0.011 grdn:0.156 lr:1.4e-05 updt_s:2.359 data_s:1.141 smp/s:37 mem_gb:52.79
+Training:  77%|███████▋  | 46000/60000 [44:48:55<13:37:09,  3.50s/step]INFO 2026-07-19 12:37:34 ot_train.py:646 step:46K smpl:6M ep:133K epch:26.96 loss:0.011 grdn:0.153 lr:1.3e-05 updt_s:2.357 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  77%|███████▋  | 46200/60000 [45:00:35<13:21:22,  3.48s/step]INFO 2026-07-19 12:49:14 ot_train.py:646 step:46K smpl:6M ep:134K epch:27.08 loss:0.011 grdn:0.163 lr:1.3e-05 updt_s:2.355 data_s:1.142 smp/s:37 mem_gb:52.79
+Training:  77%|███████▋  | 46400/60000 [45:12:15<13:07:43,  3.48s/step]INFO 2026-07-19 13:00:53 ot_train.py:646 step:46K smpl:6M ep:134K epch:27.20 loss:0.010 grdn:0.149 lr:1.3e-05 updt_s:2.345 data_s:1.151 smp/s:37 mem_gb:52.71
+Training:  78%|███████▊  | 46600/60000 [45:23:54<13:01:30,  3.50s/step]INFO 2026-07-19 13:12:33 ot_train.py:646 step:47K smpl:6M ep:135K epch:27.32 loss:0.010 grdn:0.153 lr:1.2e-05 updt_s:2.357 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  78%|███████▊  | 46800/60000 [45:35:33<12:45:56,  3.48s/step]INFO 2026-07-19 13:24:12 ot_train.py:646 step:47K smpl:6M ep:135K epch:27.43 loss:0.010 grdn:0.146 lr:1.2e-05 updt_s:2.358 data_s:1.138 smp/s:37 mem_gb:52.79
+Training:  78%|███████▊  | 47000/60000 [45:47:14<12:36:07,  3.49s/step]INFO 2026-07-19 13:35:53 ot_train.py:646 step:47K smpl:6M ep:136K epch:27.55 loss:0.010 grdn:0.154 lr:1.1e-05 updt_s:2.364 data_s:1.137 smp/s:37 mem_gb:52.79
+Training:  79%|███████▊  | 47200/60000 [45:58:52<12:20:29,  3.47s/step]INFO 2026-07-19 13:47:31 ot_train.py:646 step:47K smpl:6M ep:136K epch:27.67 loss:0.010 grdn:0.146 lr:1.1e-05 updt_s:2.357 data_s:1.135 smp/s:37 mem_gb:52.79
+Training:  79%|███████▉  | 47400/60000 [46:10:31<12:10:46,  3.48s/step]INFO 2026-07-19 13:59:10 ot_train.py:646 step:47K smpl:6M ep:137K epch:27.78 loss:0.010 grdn:0.145 lr:1.1e-05 updt_s:2.355 data_s:1.136 smp/s:37 mem_gb:52.79
+Training:  79%|███████▉  | 47600/60000 [46:22:09<11:59:36,  3.48s/step]INFO 2026-07-19 14:10:48 ot_train.py:646 step:48K smpl:6M ep:138K epch:27.90 loss:0.010 grdn:0.149 lr:1.0e-05 updt_s:2.345 data_s:1.144 smp/s:37 mem_gb:52.71
+Training:  80%|███████▉  | 47800/60000 [46:33:48<11:44:59,  3.47s/step]INFO 2026-07-19 14:22:27 ot_train.py:646 step:48K smpl:6M ep:138K epch:28.02 loss:0.009 grdn:0.150 lr:1.0e-05 updt_s:2.358 data_s:1.135 smp/s:37 mem_gb:52.79
+Training:  80%|████████  | 48000/60000 [46:45:27<11:40:44,  3.50s/step]INFO 2026-07-19 14:34:06 ot_train.py:646 step:48K smpl:6M ep:139K epch:28.14 loss:0.009 grdn:0.153 lr:9.9e-06 updt_s:2.359 data_s:1.134 smp/s:37 mem_gb:52.79
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+Training:  89%|████████▉ | 53600/60000 [52:11:49<6:11:16,  3.48s/step]INFO 2026-07-19 20:00:28 ot_train.py:646 step:54K smpl:7M ep:155K epch:31.42 loss:0.008 grdn:0.142 lr:2.9e-06 updt_s:2.353 data_s:1.140 smp/s:37 mem_gb:52.79
+Training:  90%|████████▉ | 53800/60000 [52:23:27<5:59:18,  3.48s/step]INFO 2026-07-19 20:12:06 ot_train.py:646 step:54K smpl:7M ep:155K epch:31.54 loss:0.007 grdn:0.147 lr:2.7e-06 updt_s:2.356 data_s:1.135 smp/s:37 mem_gb:52.79
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+Training:  93%|█████████▎| 55600/60000 [54:08:13<4:17:21,  3.51s/step]INFO 2026-07-19 21:56:51 ot_train.py:646 step:56K smpl:7M ep:161K epch:32.59 loss:0.007 grdn:0.143 lr:1.4e-06 updt_s:2.357 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  93%|█████████▎| 55800/60000 [54:19:50<4:03:56,  3.48s/step]INFO 2026-07-19 22:08:29 ot_train.py:646 step:56K smpl:7M ep:161K epch:32.71 loss:0.007 grdn:0.150 lr:1.3e-06 updt_s:2.356 data_s:1.129 smp/s:37 mem_gb:52.79
+Training:  93%|█████████▎| 56000/60000 [54:31:28<3:51:33,  3.47s/step]INFO 2026-07-19 22:20:07 ot_train.py:646 step:56K smpl:7M ep:162K epch:32.83 loss:0.007 grdn:0.140 lr:1.2e-06 updt_s:2.358 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  94%|█████████▎| 56200/60000 [54:43:06<3:40:39,  3.48s/step]INFO 2026-07-19 22:31:44 ot_train.py:646 step:56K smpl:7M ep:162K epch:32.94 loss:0.007 grdn:0.142 lr:1.1e-06 updt_s:2.356 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  94%|█████████▍| 56400/60000 [54:54:44<3:27:34,  3.46s/step]INFO 2026-07-19 22:43:23 ot_train.py:646 step:56K smpl:7M ep:163K epch:33.06 loss:0.007 grdn:0.144 lr:9.5e-07 updt_s:2.360 data_s:1.130 smp/s:37 mem_gb:52.79
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+Training:  95%|█████████▌| 57000/60000 [55:29:36<2:54:47,  3.50s/step]INFO 2026-07-19 23:18:15 ot_train.py:646 step:57K smpl:7M ep:165K epch:33.41 loss:0.007 grdn:0.140 lr:6.7e-07 updt_s:2.356 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  95%|█████████▌| 57200/60000 [55:41:14<2:42:30,  3.48s/step]INFO 2026-07-19 23:29:53 ot_train.py:646 step:57K smpl:7M ep:165K epch:33.53 loss:0.007 grdn:0.143 lr:5.9e-07 updt_s:2.356 data_s:1.132 smp/s:37 mem_gb:52.79
+Training:  96%|█████████▌| 57400/60000 [55:52:52<2:31:23,  3.49s/step]INFO 2026-07-19 23:41:31 ot_train.py:646 step:57K smpl:7M ep:166K epch:33.65 loss:0.007 grdn:0.142 lr:5.1e-07 updt_s:2.358 data_s:1.131 smp/s:37 mem_gb:52.79
+Training:  96%|█████████▌| 57600/60000 [56:04:31<2:20:02,  3.50s/step]INFO 2026-07-19 23:53:10 ot_train.py:646 step:58K smpl:7M ep:166K epch:33.76 loss:0.007 grdn:0.142 lr:4.4e-07 updt_s:2.352 data_s:1.142 smp/s:37 mem_gb:52.71
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+Training:  97%|█████████▋| 58000/60000 [56:27:49<1:56:15,  3.49s/step]INFO 2026-07-20 00:16:28 ot_train.py:646 step:58K smpl:7M ep:168K epch:34.00 loss:0.007 grdn:0.139 lr:3.1e-07 updt_s:2.361 data_s:1.132 smp/s:37 mem_gb:52.79
+Training:  97%|█████████▋| 58200/60000 [56:39:28<1:46:44,  3.56s/step]INFO 2026-07-20 00:28:06 ot_train.py:646 step:58K smpl:7M ep:168K epch:34.12 loss:0.007 grdn:0.133 lr:2.5e-07 updt_s:2.360 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  97%|█████████▋| 58400/60000 [56:51:05<1:32:58,  3.49s/step]INFO 2026-07-20 00:39:44 ot_train.py:646 step:58K smpl:7M ep:169K epch:34.23 loss:0.007 grdn:0.144 lr:2.0e-07 updt_s:2.358 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  98%|█████████▊| 58600/60000 [57:02:44<1:21:35,  3.50s/step]INFO 2026-07-20 00:51:23 ot_train.py:646 step:59K smpl:8M ep:169K epch:34.35 loss:0.007 grdn:0.140 lr:1.6e-07 updt_s:2.360 data_s:1.133 smp/s:37 mem_gb:52.79
+Training:  98%|█████████▊| 58800/60000 [57:14:23<1:09:39,  3.48s/step]INFO 2026-07-20 01:03:02 ot_train.py:646 step:59K smpl:8M ep:170K epch:34.47 loss:0.007 grdn:0.143 lr:1.2e-07 updt_s:2.351 data_s:1.139 smp/s:37 mem_gb:52.71
+Training:  98%|█████████▊| 59000/60000 [57:26:01<58:25,  3.51s/step]INFO 2026-07-20 01:14:40 ot_train.py:646 step:59K smpl:8M ep:170K epch:34.58 loss:0.007 grdn:0.142 lr:8.4e-08 updt_s:2.360 data_s:1.131 smp/s:37 mem_gb:52.79
+Training:  99%|█████████▊| 59200/60000 [57:37:41<47:08,  3.54s/step]INFO 2026-07-20 01:26:20 ot_train.py:646 step:59K smpl:8M ep:171K epch:34.70 loss:0.007 grdn:0.144 lr:5.7e-08 updt_s:2.364 data_s:1.133 smp/s:37 mem_gb:52.79
+Training:  99%|█████████▉| 59400/60000 [57:49:20<34:51,  3.49s/step]INFO 2026-07-20 01:37:59 ot_train.py:646 step:59K smpl:8M ep:172K epch:34.82 loss:0.007 grdn:0.140 lr:3.4e-08 updt_s:2.361 data_s:1.130 smp/s:37 mem_gb:52.79
+Training:  99%|█████████▉| 59600/60000 [58:00:58<23:15,  3.49s/step]INFO 2026-07-20 01:49:37 ot_train.py:646 step:60K smpl:8M ep:172K epch:34.94 loss:0.007 grdn:0.137 lr:1.8e-08 updt_s:2.361 data_s:1.129 smp/s:37 mem_gb:52.79
+Training: 100%|█████████▉| 59800/60000 [58:12:35<11:36,  3.48s/step]INFO 2026-07-20 02:01:14 ot_train.py:646 step:60K smpl:8M ep:173K epch:35.05 loss:0.007 grdn:0.139 lr:6.5e-09 updt_s:2.355 data_s:1.129 smp/s:37 mem_gb:52.79
+Training: 100%|██████████| 60000/60000 [58:24:13<00:00,  3.51s/step]INFO 2026-07-20 02:12:52 ot_train.py:646 step:60K smpl:8M ep:173K epch:35.17 loss:0.007 grdn:0.147 lr:9.2e-10 updt_s:2.349 data_s:1.139 smp/s:37 mem_gb:52.71
+INFO 2026-07-20 02:12:52 ot_train.py:691 Checkpoint policy after step 60000
+INFO 2026-07-20 02:13:16 in_yaml.py:1245 Saved config, action-space, prompt, and phase provenance in /home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline and /home/seonho/groot_insight/train_ckpt/Abs_Joint/Baseline/checkpoints/060000
+Training: 100%|██████████| 60000/60000 [58:24:37<00:00,  3.50s/step]
+INFO 2026-07-20 02:13:16 ot_train.py:777 End of training

Abs_Joint/Baseline/wandb/run-20260717_154830-a3ogbmg4/files/requirements.txt

@@ -0,0 +1,117 @@
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+nvidia-nvshmem-cu13==3.4.5
+nvidia-cuda-nvrtc==13.0.88
+nvidia-nvjitlink==13.0.88
+numpy==2.2.6
+shellingham==1.5.4
+pip==26.1.2
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+mypy_extensions==1.1.0
+pillow==12.3.0
+wheel==0.47.0
+cuda-pathfinder==1.5.6
+dm-tree==0.1.10
+hf-xet==1.5.1
+packaging==25.0
+typing-inspect==0.9.0
+nvidia-cuda-runtime==13.0.96
+pyyaml-include==1.4.1
+wrapt==2.2.2
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+2026-07-20 02:13:16,834 ERROR   wandb-AsyncioManager-main:3896698 [asyncio_manager.py:fn_wrap_exceptions():184] Uncaught exception in run_soon callback.
+Traceback (most recent call last):
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 90, in loop
+    await asyncio_compat.race(
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 278, in race
+    async with open_task_group(race=True) as tg:
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/contextlib.py", line 217, in __aexit__
+    await anext(self.gen)
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 240, in open_task_group
+    await task_group._wait_all(race=race, timeout=exit_timeout)
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 180, in _wait_all
+    raise exc
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 113, in _print_all
+    result = await handle.wait_async(timeout=None)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/mailbox/mailbox_handle.py", line 127, in wait_async
+    response = await self._handle.wait_async(timeout=timeout)
+               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/home/seonho/miniconda3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/mailbox/response_handle.py", line 123, in wait_async
+    raise HandleAbandonedError()
+wandb.sdk.mailbox.mailbox_handle.HandleAbandonedError

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