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Abs_6D/Baseline/checkpoints/050000/action_space_manifest.json

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Abs_6D/Baseline/checkpoints/050000/pretrained_model/action_space_manifest.json

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Abs_6D/Baseline/checkpoints/050000/pretrained_model/config.json

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Abs_6D/Baseline/checkpoints/050000/pretrained_model/policy_postprocessor.json

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Abs_6D/Baseline/checkpoints/050000/pretrained_model/policy_preprocessor.json

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+}

Abs_6D/Baseline/checkpoints/050000/pretrained_model/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",
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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_6D/Baseline/checkpoints/050000/pretrained_model/train_config.json

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+{
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Abs_6D/Baseline/checkpoints/050000/resolved_config.yaml

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+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: /home/ext_minje/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: 64
+steps: 60000
+log_freq: 200
+output_dir: /home/ext_minje/groot_insight/Abs_6D/Baseline
+job_name: INSIGHT_6D_baseline
+wandb:
+  enable: true
+  disable_artifact: true

Abs_6D/Baseline/checkpoints/050000/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: ee_abs_rot6d
+  # Options: coarse | detailed
+  prompt_set: detailed
+  save_steps: ["50K"]
+
+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: 64
+steps: 60000
+log_freq: 200
+output_dir: ${HOME}/groot_insight/Abs_6D/Baseline
+job_name: INSIGHT_6D_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_6D/Baseline/checkpoints/050000/training_state/scheduler_state.json

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Abs_6D/Baseline/checkpoints/050000/training_state/training_step.json

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Abs_6D/Baseline/checkpoints/060000/action_space_manifest.json

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Abs_6D/Baseline/checkpoints/060000/pretrained_model/config.json

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Abs_6D/Baseline/checkpoints/060000/pretrained_model/policy_postprocessor.json

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Abs_6D/Baseline/checkpoints/060000/pretrained_model/policy_preprocessor.json

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Abs_6D/Baseline/checkpoints/060000/pretrained_model/prompt_manifest.json

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+}

Abs_6D/Baseline/checkpoints/060000/pretrained_model/train_config.json

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+}

Abs_6D/Baseline/checkpoints/060000/prompt_manifest.json

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+{
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+    "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."
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Abs_6D/Baseline/checkpoints/060000/resolved_config.yaml

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+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: /home/ext_minje/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: 64
+steps: 60000
+log_freq: 200
+output_dir: /home/ext_minje/groot_insight/Abs_6D/Baseline
+job_name: INSIGHT_6D_baseline
+wandb:
+  enable: true
+  disable_artifact: true

Abs_6D/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: ee_abs_rot6d
+  # Options: coarse | detailed
+  prompt_set: detailed
+  save_steps: ["50K"]
+
+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: 64
+steps: 60000
+log_freq: 200
+output_dir: ${HOME}/groot_insight/Abs_6D/Baseline
+job_name: INSIGHT_6D_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_6D/Baseline/checkpoints/060000/training_state/optimizer_param_groups.json

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Abs_6D/Baseline/checkpoints/060000/training_state/scheduler_state.json

@@ -0,0 +1,18 @@
+{
+    "base_lrs": [
+        0.0001,
+        0.0001
+    ],
+    "last_epoch": 60000,
+    "_step_count": 60001,
+    "_is_initial": false,
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+    "_last_lr": [
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+    "lr_lambdas": [
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+}

Abs_6D/Baseline/checkpoints/060000/training_state/training_step.json

@@ -0,0 +1,5 @@
+{
+    "step": 60000,
+    "num_processes": 1,
+    "batch_size": 64
+}

Abs_6D/Baseline/wandb/debug.log

@@ -0,0 +1,46 @@
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+2026-07-15 14:32:50,279 INFO    MainThread:1450496 [wandb_init.py:setup_run_log_directory():724] Logging internal logs to /home/ext_minje/groot_insight/Abs_6D/Baseline/wandb/run-20260715_143250-1jmjb68j/logs/debug-internal.log
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+2026-07-15 14:32:50,280 INFO    MainThread:1450496 [wandb_init.py:init():771] wandb.init called with sweep_config: {}
+config: {'dataset': {'repo_id': 'Whalswp/INSIGHTfixposV4_filtered_multispace_v2', 'root': '/home/ext_minje/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': {'observation.state': {'type': <FeatureType.STATE: 'STATE'>, 'shape': [16]}, 'observation.images.wrist': {'type': <FeatureType.VISUAL: 'VISUAL'>, 'shape': [3, 224, 224]}, 'observation.images.right_shoulder': {'type': <FeatureType.VISUAL: 'VISUAL'>, 'shape': [3, 224, 224]}, 'observation.images.guide': {'type': <FeatureType.VISUAL: 'VISUAL'>, 'shape': [3, 224, 224]}}, 'output_features': {'action': {'type': <FeatureType.ACTION: 'ACTION'>, 'shape': [10]}}, 'device': 'cuda', 'use_amp': False, 'use_peft': False, 'push_to_hub': False, 'repo_id': None, 'private': None, 'tags': None, 'license': None, 'pretrained_path': '/home/ext_minje/groot_insight/Abs_6D/Baseline/checkpoints/050000/pretrained_model', '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/ext_minje/groot_insight/Abs_6D/Baseline', 'job_name': 'INSIGHT_6D_baseline', 'resume': True, 'seed': 42, 'cudnn_deterministic': False, 'num_workers': 4, 'batch_size': 64, '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': 50, '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': '1jmjb68j', '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': '/home/ext_minje/groot_insight/Abs_6D/Baseline/checkpoints/050000', '_wandb': {}}
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+2026-07-15 19:10:44,422 INFO    wandb-AsyncioManager-main:1450496 [service_client.py:_forward_responses():122] Reached EOF.
+2026-07-15 19:10:44,422 INFO    wandb-AsyncioManager-main:1450496 [mailbox.py:close():154] Closing mailbox, abandoning 2 handles.
+2026-07-15 19:10:44,423 ERROR   wandb-AsyncioManager-main:1450496 [asyncio_manager.py:fn_wrap_exceptions():184] Uncaught exception in run_soon callback.
+Traceback (most recent call last):
+  File "/home/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 90, in loop
+    await asyncio_compat.race(
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/contextlib.py", line 217, in __aexit__
+    await anext(self.gen)
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 180, in _wait_all
+    raise exc
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/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/ext_minje/miniforge3/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

Abs_6D/Baseline/wandb/run-20260714_161240-1jmjb68j/files/output.log

@@ -0,0 +1,269 @@
+INFO 2026-07-14 16:12:42 db_utils.py:121 Logs will be synced with wandb.
+INFO 2026-07-14 16:12:42 db_utils.py:122 Track this run --> https://wandb.ai/minje227_hyu-hanyang-university/lerobot/runs/1jmjb68j
+INFO 2026-07-14 16:12:42 ot_train.py:277 Creating dataset
+INFO 2026-07-14 16:12:45 ot_train.py:311 Creating policy
+Fetching 27 files: 100%|██████████| 27/27 [00:00<00:00, 4171.90it/s]
+`torch_dtype` is deprecated! Use `dtype` instead!
+Loading weights: 100%|██████████| 1031/1031 [00:00<00:00, 2241.16it/s]
+INFO 2026-07-14 16:12:51 ot_train.py:384 Creating optimizer and scheduler
+INFO 2026-07-14 16:12:51 ot_train.py:416 Output dir: /home/ext_minje/groot_insight/Abs_6D/Baseline
+INFO 2026-07-14 16:12:51 ot_train.py:423 cfg.steps=60000 (60K)
+INFO 2026-07-14 16:12:51 ot_train.py:424 dataset.num_frames=218367 (218K)
+INFO 2026-07-14 16:12:51 ot_train.py:425 dataset.num_episodes=4930
+INFO 2026-07-14 16:12:51 ot_train.py:428 Effective batch size: 64 x 1 = 64
+INFO 2026-07-14 16:12:51 ot_train.py:429 num_learnable_params=1620515968 (2B)
+INFO 2026-07-14 16:12:51 ot_train.py:430 num_total_params=3144016000 (3B)
+Training:   0%|          | 0/60000 [00:00<?, ?step/s]INFO 2026-07-14 16:12:51 ot_train.py:581 Start offline training on a fixed dataset, with effective batch size: 64
+Training:   0%|          | 200/60000 [04:57<25:13:11,  1.52s/step]INFO 2026-07-14 16:17:48 ot_train.py:625 step:200 smpl:13K ep:289 epch:0.06 loss:0.924 grdn:1.272 lr:2.0e-05 updt_s:0.764 data_s:0.721 smp/s:43 mem_gb:39.61
+Training:   1%|          | 400/60000 [09:47<21:50:42,  1.32s/step]INFO 2026-07-14 16:22:38 ot_train.py:625 step:400 smpl:26K ep:578 epch:0.12 loss:0.258 grdn:1.552 lr:6.0e-05 updt_s:0.734 data_s:0.714 smp/s:44 mem_gb:39.63
+Training:   1%|          | 600/60000 [14:37<22:35:00,  1.37s/step]INFO 2026-07-14 16:27:28 ot_train.py:625 step:600 smpl:38K ep:867 epch:0.18 loss:0.199 grdn:1.034 lr:9.5e-05 updt_s:0.734 data_s:0.711 smp/s:44 mem_gb:39.63
+Training:   1%|▏         | 800/60000 [19:30<23:53:10,  1.45s/step]INFO 2026-07-14 16:32:21 ot_train.py:625 step:800 smpl:51K ep:1K epch:0.23 loss:0.163 grdn:0.780 lr:1.0e-04 updt_s:0.731 data_s:0.731 smp/s:44 mem_gb:39.63
+Training:   2%|▏         | 1000/60000 [24:22<26:08:09,  1.59s/step]INFO 2026-07-14 16:37:13 ot_train.py:625 step:1K smpl:64K ep:1K epch:0.29 loss:0.147 grdn:0.695 lr:1.0e-04 updt_s:0.735 data_s:0.721 smp/s:44 mem_gb:39.63
+Training:   2%|▏         | 1200/60000 [29:14<23:30:02,  1.44s/step]INFO 2026-07-14 16:42:06 ot_train.py:625 step:1K smpl:77K ep:2K epch:0.35 loss:0.132 grdn:0.624 lr:1.0e-04 updt_s:0.741 data_s:0.719 smp/s:44 mem_gb:39.63
+Training:   2%|▏         | 1400/60000 [34:02<22:35:14,  1.39s/step]INFO 2026-07-14 16:46:53 ot_train.py:625 step:1K smpl:90K ep:2K epch:0.41 loss:0.123 grdn:0.569 lr:1.0e-04 updt_s:0.723 data_s:0.712 smp/s:45 mem_gb:39.63
+Training:   3%|▎         | 1600/60000 [38:48<24:19:48,  1.50s/step]INFO 2026-07-14 16:51:40 ot_train.py:625 step:2K smpl:102K ep:2K epch:0.47 loss:0.119 grdn:0.548 lr:1.0e-04 updt_s:0.731 data_s:0.698 smp/s:45 mem_gb:39.63
+Training:   3%|▎         | 1800/60000 [43:34<21:35:33,  1.34s/step]INFO 2026-07-14 16:56:26 ot_train.py:625 step:2K smpl:115K ep:3K epch:0.53 loss:0.115 grdn:0.516 lr:1.0e-04 updt_s:0.728 data_s:0.700 smp/s:45 mem_gb:39.63
+Training:   3%|▎         | 2000/60000 [48:21<22:37:52,  1.40s/step]INFO 2026-07-14 17:01:12 ot_train.py:625 step:2K smpl:128K ep:3K epch:0.59 loss:0.110 grdn:0.486 lr:1.0e-04 updt_s:0.734 data_s:0.697 smp/s:45 mem_gb:39.63
+Training:   4%|▎         | 2200/60000 [53:16<27:27:37,  1.71s/step]INFO 2026-07-14 17:06:07 ot_train.py:625 step:2K smpl:141K ep:3K epch:0.64 loss:0.108 grdn:0.488 lr:1.0e-04 updt_s:0.736 data_s:0.735 smp/s:43 mem_gb:39.63
+Training:   4%|▍         | 2400/60000 [57:52<20:49:34,  1.30s/step]INFO 2026-07-14 17:10:43 ot_train.py:625 step:2K smpl:154K ep:3K epch:0.70 loss:0.104 grdn:0.448 lr:1.0e-04 updt_s:0.722 data_s:0.654 smp/s:47 mem_gb:39.62
+Training:   4%|▍         | 2600/60000 [1:02:13<20:53:12,  1.31s/step]INFO 2026-07-14 17:15:04 ot_train.py:625 step:3K smpl:166K ep:4K epch:0.76 loss:0.105 grdn:0.451 lr:1.0e-04 updt_s:0.684 data_s:0.617 smp/s:49 mem_gb:39.64
+Training:   5%|▍         | 2800/60000 [1:07:04<23:58:13,  1.51s/step]INFO 2026-07-14 17:19:55 ot_train.py:625 step:3K smpl:179K ep:4K epch:0.82 loss:0.100 grdn:0.426 lr:1.0e-04 updt_s:0.736 data_s:0.715 smp/s:44 mem_gb:39.64
+Training:   5%|▌         | 3000/60000 [1:12:20<24:00:49,  1.52s/step]INFO 2026-07-14 17:25:11 ot_train.py:625 step:3K smpl:192K ep:4K epch:0.88 loss:0.099 grdn:0.413 lr:1.0e-04 updt_s:0.772 data_s:0.803 smp/s:41 mem_gb:39.64
+Training:   5%|▌         | 3200/60000 [1:16:55<22:01:57,  1.40s/step]INFO 2026-07-14 17:29:46 ot_train.py:625 step:3K smpl:205K ep:5K epch:0.94 loss:0.098 grdn:0.405 lr:1.0e-04 updt_s:0.708 data_s:0.667 smp/s:47 mem_gb:39.64
+Training:   6%|▌         | 3400/60000 [1:22:12<25:28:17,  1.62s/step]INFO 2026-07-14 17:35:03 ot_train.py:625 step:3K smpl:218K ep:5K epch:1.00 loss:0.095 grdn:0.389 lr:9.9e-05 updt_s:0.767 data_s:0.811 smp/s:41 mem_gb:39.64
+Training:   6%|▌         | 3600/60000 [1:27:35<22:56:31,  1.46s/step]INFO 2026-07-14 17:40:26 ot_train.py:625 step:4K smpl:230K ep:5K epch:1.06 loss:0.094 grdn:0.384 lr:9.9e-05 updt_s:0.778 data_s:0.835 smp/s:40 mem_gb:39.64
+Training:   6%|▋         | 3800/60000 [1:32:56<25:08:26,  1.61s/step]INFO 2026-07-14 17:45:47 ot_train.py:625 step:4K smpl:243K ep:5K epch:1.11 loss:0.094 grdn:0.389 lr:9.9e-05 updt_s:0.780 data_s:0.822 smp/s:40 mem_gb:39.64
+Training:   7%|▋         | 4000/60000 [1:38:22<26:54:50,  1.73s/step]INFO 2026-07-14 17:51:13 ot_train.py:625 step:4K smpl:256K ep:6K epch:1.17 loss:0.093 grdn:0.374 lr:9.9e-05 updt_s:0.792 data_s:0.836 smp/s:39 mem_gb:39.64
+Training:   7%|▋         | 4200/60000 [1:43:51<25:40:34,  1.66s/step]INFO 2026-07-14 17:56:42 ot_train.py:625 step:4K smpl:269K ep:6K epch:1.23 loss:0.090 grdn:0.355 lr:9.9e-05 updt_s:0.785 data_s:0.854 smp/s:39 mem_gb:39.64
+Training:   7%|▋         | 4400/60000 [1:49:18<25:19:11,  1.64s/step]INFO 2026-07-14 18:02:09 ot_train.py:625 step:4K smpl:282K ep:6K epch:1.29 loss:0.090 grdn:0.361 lr:9.9e-05 updt_s:0.788 data_s:0.843 smp/s:39 mem_gb:39.63
+Training:   8%|▊         | 4600/60000 [1:54:41<25:34:40,  1.66s/step]INFO 2026-07-14 18:07:32 ot_train.py:625 step:5K smpl:294K ep:7K epch:1.35 loss:0.090 grdn:0.359 lr:9.9e-05 updt_s:0.777 data_s:0.834 smp/s:40 mem_gb:39.62
+Training:   8%|▊         | 4800/60000 [2:00:00<24:06:01,  1.57s/step]INFO 2026-07-14 18:12:51 ot_train.py:625 step:5K smpl:307K ep:7K epch:1.41 loss:0.089 grdn:0.369 lr:9.9e-05 updt_s:0.769 data_s:0.823 smp/s:40 mem_gb:39.64
+Training:   8%|▊         | 5000/60000 [2:04:54<18:21:51,  1.20s/step]INFO 2026-07-14 18:17:46 ot_train.py:625 step:5K smpl:320K ep:7K epch:1.47 loss:0.089 grdn:0.357 lr:9.9e-05 updt_s:0.745 data_s:0.725 smp/s:44 mem_gb:39.64
+Training:   9%|▊         | 5200/60000 [2:09:11<22:04:04,  1.45s/step]INFO 2026-07-14 18:22:02 ot_train.py:625 step:5K smpl:333K ep:8K epch:1.52 loss:0.086 grdn:0.338 lr:9.9e-05 updt_s:0.688 data_s:0.589 smp/s:50 mem_gb:39.64
+Training:   9%|▉         | 5400/60000 [2:13:52<18:51:33,  1.24s/step]INFO 2026-07-14 18:26:43 ot_train.py:625 step:5K smpl:346K ep:8K epch:1.58 loss:0.084 grdn:0.322 lr:9.8e-05 updt_s:0.728 data_s:0.675 smp/s:46 mem_gb:39.64
+Training:   9%|▉         | 5600/60000 [2:18:31<21:32:04,  1.43s/step]INFO 2026-07-14 18:31:22 ot_train.py:625 step:6K smpl:358K ep:8K epch:1.64 loss:0.085 grdn:0.331 lr:9.8e-05 updt_s:0.719 data_s:0.674 smp/s:46 mem_gb:39.64
+Training:  10%|▉         | 5800/60000 [2:23:00<19:34:55,  1.30s/step]INFO 2026-07-14 18:35:52 ot_train.py:625 step:6K smpl:371K ep:8K epch:1.70 loss:0.085 grdn:0.334 lr:9.8e-05 updt_s:0.702 data_s:0.642 smp/s:48 mem_gb:39.64
+Training:  10%|█         | 6000/60000 [2:27:14<18:52:42,  1.26s/step]INFO 2026-07-14 18:40:05 ot_train.py:625 step:6K smpl:384K ep:9K epch:1.76 loss:0.082 grdn:0.329 lr:9.8e-05 updt_s:0.669 data_s:0.596 smp/s:51 mem_gb:39.63
+Training:  10%|█         | 6200/60000 [2:31:29<18:57:12,  1.27s/step]INFO 2026-07-14 18:44:20 ot_train.py:625 step:6K smpl:397K ep:9K epch:1.82 loss:0.085 grdn:0.346 lr:9.8e-05 updt_s:0.673 data_s:0.600 smp/s:50 mem_gb:39.64
+Training:  11%|█         | 6400/60000 [2:35:43<19:12:50,  1.29s/step]INFO 2026-07-14 18:48:34 ot_train.py:625 step:6K smpl:410K ep:9K epch:1.88 loss:0.084 grdn:0.332 lr:9.8e-05 updt_s:0.670 data_s:0.596 smp/s:51 mem_gb:39.64
+Training:  11%|█         | 6600/60000 [2:39:53<18:06:25,  1.22s/step]INFO 2026-07-14 18:52:45 ot_train.py:625 step:7K smpl:422K ep:10K epch:1.93 loss:0.079 grdn:0.300 lr:9.8e-05 updt_s:0.669 data_s:0.582 smp/s:51 mem_gb:39.64
+Training:  11%|█▏        | 6800/60000 [2:44:06<18:20:51,  1.24s/step]INFO 2026-07-14 18:56:57 ot_train.py:625 step:7K smpl:435K ep:10K epch:1.99 loss:0.080 grdn:0.314 lr:9.7e-05 updt_s:0.665 data_s:0.596 smp/s:51 mem_gb:39.62
+Training:  12%|█▏        | 7000/60000 [2:48:25<18:42:17,  1.27s/step]INFO 2026-07-14 19:01:16 ot_train.py:625 step:7K smpl:448K ep:10K epch:2.05 loss:0.078 grdn:0.316 lr:9.7e-05 updt_s:0.682 data_s:0.609 smp/s:50 mem_gb:39.64
+Training:  12%|█▏        | 7200/60000 [2:52:42<19:19:08,  1.32s/step]INFO 2026-07-14 19:05:33 ot_train.py:625 step:7K smpl:461K ep:10K epch:2.11 loss:0.078 grdn:0.307 lr:9.7e-05 updt_s:0.686 data_s:0.593 smp/s:50 mem_gb:39.64
+Training:  12%|█▏        | 7400/60000 [2:57:04<18:49:23,  1.29s/step]INFO 2026-07-14 19:09:55 ot_train.py:625 step:7K smpl:474K ep:11K epch:2.17 loss:0.077 grdn:0.291 lr:9.7e-05 updt_s:0.693 data_s:0.617 smp/s:49 mem_gb:39.64
+Training:  13%|█▎        | 7600/60000 [3:01:28<18:51:21,  1.30s/step]INFO 2026-07-14 19:14:19 ot_train.py:625 step:8K smpl:486K ep:11K epch:2.23 loss:0.079 grdn:0.329 lr:9.7e-05 updt_s:0.694 data_s:0.621 smp/s:49 mem_gb:39.64
+Training:  13%|█▎        | 7800/60000 [3:05:46<18:19:01,  1.26s/step]INFO 2026-07-14 19:18:38 ot_train.py:625 step:8K smpl:499K ep:11K epch:2.29 loss:0.080 grdn:0.329 lr:9.6e-05 updt_s:0.683 data_s:0.606 smp/s:50 mem_gb:39.64
+Training:  13%|█▎        | 8000/60000 [3:10:03<18:01:27,  1.25s/step]INFO 2026-07-14 19:22:54 ot_train.py:625 step:8K smpl:512K ep:12K epch:2.34 loss:0.081 grdn:0.327 lr:9.6e-05 updt_s:0.686 data_s:0.592 smp/s:50 mem_gb:39.64
+Training:  14%|█▎        | 8200/60000 [3:14:22<18:28:54,  1.28s/step]INFO 2026-07-14 19:27:13 ot_train.py:625 step:8K smpl:525K ep:12K epch:2.40 loss:0.077 grdn:0.301 lr:9.6e-05 updt_s:0.689 data_s:0.604 smp/s:49 mem_gb:39.64
+Training:  14%|█▍        | 8400/60000 [3:18:42<19:26:41,  1.36s/step]INFO 2026-07-14 19:31:34 ot_train.py:625 step:8K smpl:538K ep:12K epch:2.46 loss:0.075 grdn:0.294 lr:9.6e-05 updt_s:0.689 data_s:0.612 smp/s:49 mem_gb:39.64
+Training:  14%|█▍        | 8600/60000 [3:23:03<18:46:25,  1.31s/step]INFO 2026-07-14 19:35:54 ot_train.py:625 step:9K smpl:550K ep:12K epch:2.52 loss:0.076 grdn:0.297 lr:9.6e-05 updt_s:0.687 data_s:0.613 smp/s:49 mem_gb:39.64
+Training:  15%|█▍        | 8800/60000 [3:27:30<18:50:26,  1.32s/step]INFO 2026-07-14 19:40:21 ot_train.py:625 step:9K smpl:563K ep:13K epch:2.58 loss:0.075 grdn:0.305 lr:9.5e-05 updt_s:0.711 data_s:0.622 smp/s:48 mem_gb:39.63
+Training:  15%|█▌        | 9000/60000 [3:31:54<18:56:39,  1.34s/step]INFO 2026-07-14 19:44:45 ot_train.py:625 step:9K smpl:576K ep:13K epch:2.64 loss:0.075 grdn:0.296 lr:9.5e-05 updt_s:0.690 data_s:0.626 smp/s:49 mem_gb:39.64
+Training:  15%|█▌        | 9200/60000 [3:36:15<18:15:36,  1.29s/step]INFO 2026-07-14 19:49:06 ot_train.py:625 step:9K smpl:589K ep:13K epch:2.70 loss:0.072 grdn:0.288 lr:9.5e-05 updt_s:0.686 data_s:0.615 smp/s:49 mem_gb:39.62
+Training:  16%|█▌        | 9400/60000 [3:40:27<17:40:11,  1.26s/step]INFO 2026-07-14 19:53:18 ot_train.py:625 step:9K smpl:602K ep:14K epch:2.75 loss:0.076 grdn:0.331 lr:9.5e-05 updt_s:0.670 data_s:0.587 smp/s:51 mem_gb:39.64
+Training:  16%|█▌        | 9600/60000 [3:44:45<17:53:30,  1.28s/step]INFO 2026-07-14 19:57:36 ot_train.py:625 step:10K smpl:614K ep:14K epch:2.81 loss:0.073 grdn:0.299 lr:9.4e-05 updt_s:0.682 data_s:0.605 smp/s:50 mem_gb:39.64
+Training:  16%|█▋        | 9800/60000 [3:49:05<17:46:19,  1.27s/step]INFO 2026-07-14 20:01:56 ot_train.py:625 step:10K smpl:627K ep:14K epch:2.87 loss:0.075 grdn:0.316 lr:9.4e-05 updt_s:0.682 data_s:0.615 smp/s:49 mem_gb:39.64
+Training:  17%|█▋        | 10000/60000 [3:53:23<17:37:11,  1.27s/step]INFO 2026-07-14 20:06:14 ot_train.py:625 step:10K smpl:640K ep:14K epch:2.93 loss:0.071 grdn:0.292 lr:9.4e-05 updt_s:0.681 data_s:0.609 smp/s:50 mem_gb:39.64
+Training:  17%|█▋        | 10200/60000 [3:57:43<18:16:00,  1.32s/step]INFO 2026-07-14 20:10:34 ot_train.py:625 step:10K smpl:653K ep:15K epch:2.99 loss:0.075 grdn:0.321 lr:9.4e-05 updt_s:0.681 data_s:0.616 smp/s:49 mem_gb:39.63
+Training:  17%|█▋        | 10400/60000 [4:02:02<17:42:10,  1.28s/step]INFO 2026-07-14 20:14:53 ot_train.py:625 step:10K smpl:666K ep:15K epch:3.05 loss:0.072 grdn:0.289 lr:9.3e-05 updt_s:0.679 data_s:0.611 smp/s:50 mem_gb:39.64
+Training:  18%|█▊        | 10600/60000 [4:06:08<16:46:22,  1.22s/step]INFO 2026-07-14 20:19:00 ot_train.py:625 step:11K smpl:678K ep:15K epch:3.11 loss:0.071 grdn:0.282 lr:9.3e-05 updt_s:0.660 data_s:0.571 smp/s:52 mem_gb:39.64
+Training:  18%|█▊        | 10800/60000 [4:10:16<16:44:40,  1.23s/step]INFO 2026-07-14 20:23:07 ot_train.py:625 step:11K smpl:691K ep:16K epch:3.17 loss:0.071 grdn:0.279 lr:9.3e-05 updt_s:0.660 data_s:0.574 smp/s:52 mem_gb:39.63
+Training:  18%|█▊        | 11000/60000 [4:14:24<16:49:58,  1.24s/step]INFO 2026-07-14 20:27:16 ot_train.py:625 step:11K smpl:704K ep:16K epch:3.22 loss:0.067 grdn:0.270 lr:9.3e-05 updt_s:0.663 data_s:0.578 smp/s:52 mem_gb:39.64
+Training:  19%|█▊        | 11200/60000 [4:18:36<16:38:47,  1.23s/step]INFO 2026-07-14 20:31:27 ot_train.py:625 step:11K smpl:717K ep:16K epch:3.28 loss:0.067 grdn:0.274 lr:9.2e-05 updt_s:0.665 data_s:0.592 smp/s:51 mem_gb:39.64
+Training:  19%|█▉        | 11400/60000 [4:22:47<16:26:56,  1.22s/step]INFO 2026-07-14 20:35:38 ot_train.py:625 step:11K smpl:730K ep:16K epch:3.34 loss:0.070 grdn:0.292 lr:9.2e-05 updt_s:0.658 data_s:0.591 smp/s:51 mem_gb:39.62
+Training:  19%|█▉        | 11600/60000 [4:27:00<17:21:50,  1.29s/step]INFO 2026-07-14 20:39:51 ot_train.py:625 step:12K smpl:742K ep:17K epch:3.40 loss:0.067 grdn:0.283 lr:9.2e-05 updt_s:0.667 data_s:0.595 smp/s:51 mem_gb:39.64
+Training:  20%|█▉        | 11800/60000 [4:31:17<16:16:30,  1.22s/step]INFO 2026-07-14 20:44:08 ot_train.py:625 step:12K smpl:755K ep:17K epch:3.46 loss:0.070 grdn:0.290 lr:9.2e-05 updt_s:0.675 data_s:0.608 smp/s:50 mem_gb:39.64
+Training:  20%|██        | 12000/60000 [4:35:26<16:27:26,  1.23s/step]INFO 2026-07-14 20:48:17 ot_train.py:625 step:12K smpl:768K ep:17K epch:3.52 loss:0.071 grdn:0.295 lr:9.1e-05 updt_s:0.657 data_s:0.587 smp/s:51 mem_gb:39.64
+Training:  20%|██        | 12200/60000 [4:39:32<17:11:03,  1.29s/step]INFO 2026-07-14 20:52:23 ot_train.py:625 step:12K smpl:781K ep:18K epch:3.58 loss:0.067 grdn:0.274 lr:9.1e-05 updt_s:0.655 data_s:0.570 smp/s:52 mem_gb:39.64
+Training:  21%|█��        | 12400/60000 [4:43:39<16:03:48,  1.21s/step]INFO 2026-07-14 20:56:30 ot_train.py:625 step:12K smpl:794K ep:18K epch:3.63 loss:0.069 grdn:0.297 lr:9.1e-05 updt_s:0.657 data_s:0.576 smp/s:52 mem_gb:39.64
+Training:  21%|██        | 12600/60000 [4:47:50<16:04:53,  1.22s/step]INFO 2026-07-14 21:00:41 ot_train.py:625 step:13K smpl:806K ep:18K epch:3.69 loss:0.066 grdn:0.270 lr:9.0e-05 updt_s:0.661 data_s:0.591 smp/s:51 mem_gb:39.64
+Training:  21%|██▏       | 12800/60000 [4:52:03<16:09:50,  1.23s/step]INFO 2026-07-14 21:04:54 ot_train.py:625 step:13K smpl:819K ep:18K epch:3.75 loss:0.066 grdn:0.275 lr:9.0e-05 updt_s:0.666 data_s:0.596 smp/s:51 mem_gb:39.64
+Training:  22%|██▏       | 13000/60000 [4:56:17<17:16:44,  1.32s/step]INFO 2026-07-14 21:09:08 ot_train.py:625 step:13K smpl:832K ep:19K epch:3.81 loss:0.067 grdn:0.284 lr:9.0e-05 updt_s:0.673 data_s:0.594 smp/s:50 mem_gb:39.63
+Training:  22%|██▏       | 13200/60000 [5:00:26<16:13:10,  1.25s/step]INFO 2026-07-14 21:13:17 ot_train.py:625 step:13K smpl:845K ep:19K epch:3.87 loss:0.070 grdn:0.306 lr:8.9e-05 updt_s:0.661 data_s:0.583 smp/s:51 mem_gb:39.63
+Training:  22%|██▏       | 13400/60000 [5:04:37<15:56:23,  1.23s/step]INFO 2026-07-14 21:17:29 ot_train.py:625 step:13K smpl:858K ep:19K epch:3.93 loss:0.068 grdn:0.301 lr:8.9e-05 updt_s:0.668 data_s:0.587 smp/s:51 mem_gb:39.64
+Training:  23%|██▎       | 13600/60000 [5:08:44<15:34:44,  1.21s/step]INFO 2026-07-14 21:21:35 ot_train.py:625 step:14K smpl:870K ep:20K epch:3.99 loss:0.067 grdn:0.281 lr:8.9e-05 updt_s:0.652 data_s:0.578 smp/s:52 mem_gb:39.62
+Training:  23%|██▎       | 13800/60000 [5:12:51<16:02:46,  1.25s/step]INFO 2026-07-14 21:25:42 ot_train.py:625 step:14K smpl:883K ep:20K epch:4.04 loss:0.065 grdn:0.268 lr:8.8e-05 updt_s:0.656 data_s:0.575 smp/s:52 mem_gb:39.64
+Training:  23%|██▎       | 14000/60000 [5:17:03<15:27:28,  1.21s/step]INFO 2026-07-14 21:29:54 ot_train.py:625 step:14K smpl:896K ep:20K epch:4.10 loss:0.064 grdn:0.285 lr:8.8e-05 updt_s:0.665 data_s:0.591 smp/s:51 mem_gb:39.64
+Training:  24%|██▎       | 14200/60000 [5:21:15<15:36:13,  1.23s/step]INFO 2026-07-14 21:34:06 ot_train.py:625 step:14K smpl:909K ep:21K epch:4.16 loss:0.066 grdn:0.281 lr:8.8e-05 updt_s:0.659 data_s:0.599 smp/s:51 mem_gb:39.64
+Training:  24%|██▍       | 14400/60000 [5:25:33<16:34:18,  1.31s/step]INFO 2026-07-14 21:38:24 ot_train.py:625 step:14K smpl:922K ep:21K epch:4.22 loss:0.064 grdn:0.272 lr:8.7e-05 updt_s:0.682 data_s:0.605 smp/s:50 mem_gb:39.64
+Training:  24%|██▍       | 14600/60000 [5:29:45<15:40:37,  1.24s/step]INFO 2026-07-14 21:42:36 ot_train.py:625 step:15K smpl:934K ep:21K epch:4.28 loss:0.067 grdn:0.315 lr:8.7e-05 updt_s:0.665 data_s:0.593 smp/s:51 mem_gb:39.63
+Training:  25%|██▍       | 14800/60000 [5:34:00<15:40:37,  1.25s/step]INFO 2026-07-14 21:46:51 ot_train.py:625 step:15K smpl:947K ep:21K epch:4.34 loss:0.064 grdn:0.279 lr:8.7e-05 updt_s:0.671 data_s:0.599 smp/s:50 mem_gb:39.63
+Training:  25%|██▌       | 15000/60000 [5:38:06<15:14:31,  1.22s/step]INFO 2026-07-14 21:50:57 ot_train.py:625 step:15K smpl:960K ep:22K epch:4.40 loss:0.064 grdn:0.267 lr:8.6e-05 updt_s:0.655 data_s:0.572 smp/s:52 mem_gb:39.64
+Training:  25%|██▌       | 15200/60000 [5:42:12<14:50:06,  1.19s/step]INFO 2026-07-14 21:55:03 ot_train.py:625 step:15K smpl:973K ep:22K epch:4.45 loss:0.070 grdn:0.321 lr:8.6e-05 updt_s:0.657 data_s:0.571 smp/s:52 mem_gb:39.64
+Training:  26%|██▌       | 15400/60000 [5:46:20<15:10:47,  1.23s/step]INFO 2026-07-14 21:59:12 ot_train.py:625 step:15K smpl:986K ep:22K epch:4.51 loss:0.064 grdn:0.269 lr:8.5e-05 updt_s:0.660 data_s:0.581 smp/s:52 mem_gb:39.64
+Training:  26%|██▌       | 15600/60000 [5:50:34<15:03:47,  1.22s/step]INFO 2026-07-14 22:03:25 ot_train.py:625 step:16K smpl:998K ep:23K epch:4.57 loss:0.063 grdn:0.274 lr:8.5e-05 updt_s:0.662 data_s:0.604 smp/s:51 mem_gb:39.64
+Training:  26%|██▋       | 15800/60000 [5:54:50<19:01:44,  1.55s/step]INFO 2026-07-14 22:07:42 ot_train.py:625 step:16K smpl:1M ep:23K epch:4.63 loss:0.062 grdn:0.271 lr:8.5e-05 updt_s:0.671 data_s:0.607 smp/s:50 mem_gb:39.62
+Training:  27%|██▋       | 16000/60000 [5:59:04<14:59:09,  1.23s/step]INFO 2026-07-14 22:11:55 ot_train.py:625 step:16K smpl:1M ep:23K epch:4.69 loss:0.061 grdn:0.272 lr:8.4e-05 updt_s:0.674 data_s:0.592 smp/s:51 mem_gb:39.64
+Training:  27%|██▋       | 16200/60000 [6:03:18<15:56:38,  1.31s/step]INFO 2026-07-14 22:16:09 ot_train.py:625 step:16K smpl:1M ep:23K epch:4.75 loss:0.060 grdn:0.258 lr:8.4e-05 updt_s:0.668 data_s:0.598 smp/s:51 mem_gb:39.64
+Training:  27%|██▋       | 16400/60000 [6:07:27<15:43:33,  1.30s/step]INFO 2026-07-14 22:20:19 ot_train.py:625 step:16K smpl:1M ep:24K epch:4.81 loss:0.062 grdn:0.274 lr:8.4e-05 updt_s:0.660 data_s:0.585 smp/s:51 mem_gb:39.64
+Training:  28%|██▊       | 16600/60000 [6:11:43<15:50:06,  1.31s/step]INFO 2026-07-14 22:24:35 ot_train.py:625 step:17K smpl:1M ep:24K epch:4.87 loss:0.060 grdn:0.270 lr:8.3e-05 updt_s:0.677 data_s:0.599 smp/s:50 mem_gb:39.63
+Training:  28%|██▊       | 16800/60000 [6:16:05<15:21:36,  1.28s/step]INFO 2026-07-14 22:28:56 ot_train.py:625 step:17K smpl:1M ep:24K epch:4.92 loss:0.061 grdn:0.254 lr:8.3e-05 updt_s:0.685 data_s:0.618 smp/s:49 mem_gb:39.64
+Training:  28%|██▊       | 17000/60000 [6:20:21<15:33:00,  1.30s/step]INFO 2026-07-14 22:33:12 ot_train.py:625 step:17K smpl:1M ep:25K epch:4.98 loss:0.061 grdn:0.262 lr:8.2e-05 updt_s:0.687 data_s:0.589 smp/s:50 mem_gb:39.64
+Training:  29%|██▊       | 17200/60000 [6:24:31<14:26:42,  1.22s/step]INFO 2026-07-14 22:37:22 ot_train.py:625 step:17K smpl:1M ep:25K epch:5.04 loss:0.063 grdn:0.303 lr:8.2e-05 updt_s:0.676 data_s:0.573 smp/s:51 mem_gb:39.64
+Training:  29%|██▉       | 17400/60000 [6:28:40<14:54:34,  1.26s/step]INFO 2026-07-14 22:41:32 ot_train.py:625 step:17K smpl:1M ep:25K epch:5.10 loss:0.060 grdn:0.271 lr:8.2e-05 updt_s:0.673 data_s:0.571 smp/s:51 mem_gb:39.63
+Training:  29%|██▉       | 17600/60000 [6:32:50<15:00:30,  1.27s/step]INFO 2026-07-14 22:45:41 ot_train.py:625 step:18K smpl:1M ep:25K epch:5.16 loss:0.059 grdn:0.268 lr:8.1e-05 updt_s:0.676 data_s:0.568 smp/s:51 mem_gb:39.64
+Training:  30%|██▉       | 17800/60000 [6:37:01<14:37:09,  1.25s/step]INFO 2026-07-14 22:49:52 ot_train.py:625 step:18K smpl:1M ep:26K epch:5.22 loss:0.060 grdn:0.260 lr:8.1e-05 updt_s:0.670 data_s:0.581 smp/s:51 mem_gb:39.64
+Training:  30%|███       | 18000/60000 [6:41:10<15:23:22,  1.32s/step]INFO 2026-07-14 22:54:01 ot_train.py:625 step:18K smpl:1M ep:26K epch:5.28 loss:0.060 grdn:0.281 lr:8.0e-05 updt_s:0.674 data_s:0.571 smp/s:51 mem_gb:39.64
+Training:  30%|███       | 18200/60000 [6:45:20<14:02:08,  1.21s/step]INFO 2026-07-14 22:58:11 ot_train.py:625 step:18K smpl:1M ep:26K epch:5.33 loss:0.060 grdn:0.265 lr:8.0e-05 updt_s:0.669 data_s:0.577 smp/s:51 mem_gb:39.62
+Training:  31%|███       | 18400/60000 [6:49:43<14:36:21,  1.26s/step]INFO 2026-07-14 23:02:34 ot_train.py:625 step:18K smpl:1M ep:27K epch:5.39 loss:0.057 grdn:0.259 lr:7.9e-05 updt_s:0.701 data_s:0.611 smp/s:49 mem_gb:39.64
+Training:  31%|███       | 18600/60000 [6:54:06<14:11:09,  1.23s/step]INFO 2026-07-14 23:06:57 ot_train.py:625 step:19K smpl:1M ep:27K epch:5.45 loss:0.059 grdn:0.263 lr:7.9e-05 updt_s:0.699 data_s:0.612 smp/s:49 mem_gb:39.63
+Training:  31%|███▏      | 18800/60000 [6:58:35<15:03:04,  1.32s/step]INFO 2026-07-14 23:11:27 ot_train.py:625 step:19K smpl:1M ep:27K epch:5.51 loss:0.058 grdn:0.273 lr:7.9e-05 updt_s:0.712 data_s:0.632 smp/s:48 mem_gb:39.64
+Training:  32%|███▏      | 19000/60000 [7:03:01<14:58:10,  1.31s/step]INFO 2026-07-14 23:15:52 ot_train.py:625 step:19K smpl:1M ep:27K epch:5.57 loss:0.059 grdn:0.265 lr:7.8e-05 updt_s:0.694 data_s:0.631 smp/s:48 mem_gb:39.64
+Training:  32%|███▏      | 19200/60000 [7:07:23<13:38:45,  1.20s/step]INFO 2026-07-14 23:20:15 ot_train.py:625 step:19K smpl:1M ep:28K epch:5.63 loss:0.059 grdn:0.262 lr:7.8e-05 updt_s:0.688 data_s:0.620 smp/s:49 mem_gb:39.64
+Training:  32%|███▏      | 19400/60000 [7:11:17<12:53:09,  1.14s/step]INFO 2026-07-14 23:24:08 ot_train.py:625 step:19K smpl:1M ep:28K epch:5.69 loss:0.058 grdn:0.265 lr:7.7e-05 updt_s:0.626 data_s:0.540 smp/s:55 mem_gb:39.63
+Training:  33%|███▎      | 19600/60000 [7:15:11<14:19:26,  1.28s/step]INFO 2026-07-14 23:28:02 ot_train.py:625 step:20K smpl:1M ep:28K epch:5.74 loss:0.056 grdn:0.261 lr:7.7e-05 updt_s:0.630 data_s:0.535 smp/s:55 mem_gb:39.64
+Training:  33%|███▎      | 19800/60000 [7:19:32<16:27:23,  1.47s/step]INFO 2026-07-14 23:32:23 ot_train.py:625 step:20K smpl:1M ep:29K epch:5.80 loss:0.058 grdn:0.265 lr:7.6e-05 updt_s:0.675 data_s:0.625 smp/s:49 mem_gb:39.64
+Training:  33%|███▎      | 20000/60000 [7:24:10<14:40:40,  1.32s/step]INFO 2026-07-14 23:37:01 ot_train.py:625 step:20K smpl:1M ep:29K epch:5.86 loss:0.058 grdn:0.277 lr:7.6e-05 updt_s:0.723 data_s:0.666 smp/s:46 mem_gb:39.63
+Training:  34%|███▎      | 20200/60000 [7:29:08<17:58:49,  1.63s/step]INFO 2026-07-14 23:41:59 ot_train.py:625 step:20K smpl:1M ep:29K epch:5.92 loss:0.060 grdn:0.285 lr:7.6e-05 updt_s:0.756 data_s:0.732 smp/s:43 mem_gb:39.64
+Training:  34%|███▍      | 20400/60000 [7:34:25<16:39:59,  1.52s/step]INFO 2026-07-14 23:47:16 ot_train.py:625 step:20K smpl:1M ep:29K epch:5.98 loss:0.056 grdn:0.268 lr:7.5e-05 updt_s:0.799 data_s:0.781 smp/s:41 mem_gb:39.62
+Training:  34%|███▍      | 20600/60000 [7:39:43<15:34:50,  1.42s/step]INFO 2026-07-14 23:52:34 ot_train.py:625 step:21K smpl:1M ep:30K epch:6.04 loss:0.055 grdn:0.262 lr:7.5e-05 updt_s:0.797 data_s:0.791 smp/s:40 mem_gb:39.64
+Training:  35%|███▍      | 20800/60000 [7:45:03<18:00:15,  1.65s/step]INFO 2026-07-14 23:57:54 ot_train.py:625 step:21K smpl:1M ep:30K epch:6.10 loss:0.054 grdn:0.258 lr:7.4e-05 updt_s:0.795 data_s:0.801 smp/s:40 mem_gb:39.64
+Training:  35%|███▌      | 21000/60000 [7:50:23<16:51:45,  1.56s/step]INFO 2026-07-15 00:03:14 ot_train.py:625 step:21K smpl:1M ep:30K epch:6.15 loss:0.056 grdn:0.258 lr:7.4e-05 updt_s:0.790 data_s:0.806 smp/s:40 mem_gb:39.64
+Training:  35%|███▌      | 21200/60000 [7:55:39<17:37:43,  1.64s/step]INFO 2026-07-15 00:08:30 ot_train.py:625 step:21K smpl:1M ep:31K epch:6.21 loss:0.054 grdn:0.258 lr:7.3e-05 updt_s:0.785 data_s:0.793 smp/s:41 mem_gb:39.64
+Training:  36%|███▌      | 21400/60000 [8:00:54<17:25:58,  1.63s/step]INFO 2026-07-15 00:13:46 ot_train.py:625 step:21K smpl:1M ep:31K epch:6.27 loss:0.054 grdn:0.258 lr:7.3e-05 updt_s:0.791 data_s:0.784 smp/s:41 mem_gb:39.64
+Training:  36%|███▌      | 21600/60000 [8:06:01<17:31:34,  1.64s/step]INFO 2026-07-15 00:18:52 ot_train.py:625 step:22K smpl:1M ep:31K epch:6.33 loss:0.055 grdn:0.262 lr:7.2e-05 updt_s:0.773 data_s:0.755 smp/s:42 mem_gb:39.63
+Training:  36%|███▋      | 21800/60000 [8:11:19<16:43:14,  1.58s/step]INFO 2026-07-15 00:24:10 ot_train.py:625 step:22K smpl:1M ep:31K epch:6.39 loss:0.054 grdn:0.263 lr:7.2e-05 updt_s:0.794 data_s:0.793 smp/s:40 mem_gb:39.64
+Training:  37%|███▋      | 22000/60000 [8:16:41<17:11:39,  1.63s/step]INFO 2026-07-15 00:29:32 ot_train.py:625 step:22K smpl:1M ep:32K epch:6.45 loss:0.054 grdn:0.269 lr:7.1e-05 updt_s:0.800 data_s:0.806 smp/s:40 mem_gb:39.64
+Training:  37%|███▋      | 22200/60000 [8:21:59<17:04:40,  1.63s/step]INFO 2026-07-15 00:34:51 ot_train.py:625 step:22K smpl:1M ep:32K epch:6.51 loss:0.054 grdn:0.260 lr:7.1e-05 updt_s:0.791 data_s:0.799 smp/s:40 mem_gb:39.64
+Training:  37%|███▋      | 22400/60000 [8:27:18<16:23:29,  1.57s/step]INFO 2026-07-15 00:40:09 ot_train.py:625 step:22K smpl:1M ep:32K epch:6.57 loss:0.057 grdn:0.284 lr:7.0e-05 updt_s:0.791 data_s:0.799 smp/s:40 mem_gb:39.64
+Training:  38%|███▊      | 22600/60000 [8:32:28<15:18:06,  1.47s/step]INFO 2026-07-15 00:45:19 ot_train.py:625 step:23K smpl:1M ep:33K epch:6.62 loss:0.053 grdn:0.251 lr:7.0e-05 updt_s:0.774 data_s:0.770 smp/s:41 mem_gb:39.62
+Training:  38%|███▊      | 22800/60000 [8:36:49<11:38:23,  1.13s/step]INFO 2026-07-15 00:49:40 ot_train.py:625 step:23K smpl:1M ep:33K epch:6.68 loss:0.053 grdn:0.265 lr:6.9e-05 updt_s:0.685 data_s:0.619 smp/s:49 mem_gb:39.64
+Training:  38%|███▊      | 23000/60000 [8:41:05<14:19:13,  1.39s/step]INFO 2026-07-15 00:53:56 ot_train.py:625 step:23K smpl:1M ep:33K epch:6.74 loss:0.051 grdn:0.249 lr:6.9e-05 updt_s:0.729 data_s:0.549 smp/s:50 mem_gb:39.64
+Training:  39%|███▊      | 23200/60000 [8:45:41<13:59:08,  1.37s/step]INFO 2026-07-15 00:58:32 ot_train.py:625 step:23K smpl:1M ep:34K epch:6.80 loss:0.052 grdn:0.273 lr:6.8e-05 updt_s:0.806 data_s:0.572 smp/s:46 mem_gb:39.64
+Training:  39%|███▉      | 23400/60000 [8:50:16<13:59:29,  1.38s/step]INFO 2026-07-15 01:03:07 ot_train.py:625 step:23K smpl:1M ep:34K epch:6.86 loss:0.051 grdn:0.266 lr:6.8e-05 updt_s:0.805 data_s:0.569 smp/s:47 mem_gb:39.64
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+Training:  40%|████      | 24000/60000 [9:03:54<13:29:52,  1.35s/step]INFO 2026-07-15 01:16:45 ot_train.py:625 step:24K smpl:2M ep:35K epch:7.03 loss:0.050 grdn:0.265 lr:6.6e-05 updt_s:0.765 data_s:0.576 smp/s:48 mem_gb:39.64
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+Training:  41%|████      | 24400/60000 [9:13:08<13:10:45,  1.33s/step]INFO 2026-07-15 01:25:59 ot_train.py:625 step:24K smpl:2M ep:35K epch:7.15 loss:0.051 grdn:0.262 lr:6.5e-05 updt_s:0.834 data_s:0.569 smp/s:46 mem_gb:39.63
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+Training:  42%|████▏     | 25000/60000 [9:26:59<13:23:54,  1.38s/step]INFO 2026-07-15 01:39:50 ot_train.py:625 step:25K smpl:2M ep:36K epch:7.33 loss:0.051 grdn:0.264 lr:6.4e-05 updt_s:0.813 data_s:0.568 smp/s:46 mem_gb:39.62
+Training:  42%|████▏     | 25200/60000 [9:31:36<12:46:56,  1.32s/step]INFO 2026-07-15 01:44:27 ot_train.py:625 step:25K smpl:2M ep:36K epch:7.39 loss:0.051 grdn:0.309 lr:6.3e-05 updt_s:0.821 data_s:0.559 smp/s:46 mem_gb:39.64
+Training:  42%|████▏     | 25400/60000 [9:36:17<13:28:54,  1.40s/step]INFO 2026-07-15 01:49:08 ot_train.py:625 step:25K smpl:2M ep:37K epch:7.44 loss:0.048 grdn:0.251 lr:6.3e-05 updt_s:0.832 data_s:0.572 smp/s:46 mem_gb:39.64
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+Training:  43%|████▎     | 25800/60000 [9:45:50<14:57:05,  1.57s/step]INFO 2026-07-15 01:58:42 ot_train.py:625 step:26K smpl:2M ep:37K epch:7.56 loss:0.049 grdn:0.269 lr:6.2e-05 updt_s:0.856 data_s:0.607 smp/s:44 mem_gb:39.64
+Training:  43%|████▎     | 26000/60000 [9:51:14<14:39:08,  1.55s/step]INFO 2026-07-15 02:04:05 ot_train.py:625 step:26K smpl:2M ep:38K epch:7.62 loss:0.049 grdn:0.272 lr:6.1e-05 updt_s:0.906 data_s:0.710 smp/s:40 mem_gb:39.64
+Training:  44%|████▎     | 26200/60000 [9:56:34<15:30:28,  1.65s/step]INFO 2026-07-15 02:09:26 ot_train.py:625 step:26K smpl:2M ep:38K epch:7.68 loss:0.049 grdn:0.263 lr:6.1e-05 updt_s:0.885 data_s:0.714 smp/s:40 mem_gb:39.63
+Training:  44%|████▍     | 26400/60000 [10:02:02<14:44:53,  1.58s/step]INFO 2026-07-15 02:14:53 ot_train.py:625 step:26K smpl:2M ep:38K epch:7.74 loss:0.049 grdn:0.266 lr:6.0e-05 updt_s:0.889 data_s:0.746 smp/s:39 mem_gb:39.63
+Training:  44%|████▍     | 26600/60000 [10:07:37<19:16:12,  2.08s/step]INFO 2026-07-15 02:20:28 ot_train.py:625 step:27K smpl:2M ep:38K epch:7.80 loss:0.049 grdn:0.274 lr:6.0e-05 updt_s:0.911 data_s:0.759 smp/s:38 mem_gb:39.64
+Training:  45%|████▍     | 26800/60000 [10:13:10<15:20:56,  1.66s/step]INFO 2026-07-15 02:26:01 ot_train.py:625 step:27K smpl:2M ep:39K epch:7.85 loss:0.050 grdn:0.270 lr:5.9e-05 updt_s:0.884 data_s:0.779 smp/s:38 mem_gb:39.63
+Training:  45%|████▌     | 27000/60000 [10:18:41<15:53:56,  1.73s/step]INFO 2026-07-15 02:31:32 ot_train.py:625 step:27K smpl:2M ep:39K epch:7.91 loss:0.047 grdn:0.259 lr:5.9e-05 updt_s:0.902 data_s:0.752 smp/s:39 mem_gb:39.63
+Training:  45%|████▌     | 27200/60000 [10:24:13<14:53:00,  1.63s/step]INFO 2026-07-15 02:37:04 ot_train.py:625 step:27K smpl:2M ep:39K epch:7.97 loss:0.047 grdn:0.260 lr:5.8e-05 updt_s:0.876 data_s:0.780 smp/s:39 mem_gb:39.62
+Training:  46%|████▌     | 27400/60000 [10:29:44<15:48:54,  1.75s/step]INFO 2026-07-15 02:42:36 ot_train.py:625 step:27K smpl:2M ep:40K epch:8.03 loss:0.047 grdn:0.273 lr:5.8e-05 updt_s:0.888 data_s:0.766 smp/s:39 mem_gb:39.63
+Training:  46%|████▌     | 27600/60000 [10:35:17<15:05:31,  1.68s/step]INFO 2026-07-15 02:48:08 ot_train.py:625 step:28K smpl:2M ep:40K epch:8.09 loss:0.046 grdn:0.258 lr:5.7e-05 updt_s:0.918 data_s:0.740 smp/s:39 mem_gb:39.64
+Training:  46%|████▋     | 27800/60000 [10:40:48<14:24:38,  1.61s/step]INFO 2026-07-15 02:53:39 ot_train.py:625 step:28K smpl:2M ep:40K epch:8.15 loss:0.046 grdn:0.258 lr:5.7e-05 updt_s:0.885 data_s:0.768 smp/s:39 mem_gb:39.64
+Training:  47%|████▋     | 28000/60000 [10:46:18<14:09:46,  1.59s/step]INFO 2026-07-15 02:59:09 ot_train.py:625 step:28K smpl:2M ep:40K epch:8.21 loss:0.045 grdn:0.259 lr:5.6e-05 updt_s:0.906 data_s:0.742 smp/s:39 mem_gb:39.64
+Training:  47%|████▋     | 28200/60000 [10:51:43<15:20:49,  1.74s/step]INFO 2026-07-15 03:04:34 ot_train.py:625 step:28K smpl:2M ep:41K epch:8.26 loss:0.046 grdn:0.271 lr:5.6e-05 updt_s:0.925 data_s:0.696 smp/s:39 mem_gb:39.64
+Training:  47%|████▋     | 28400/60000 [10:57:14<15:10:37,  1.73s/step]INFO 2026-07-15 03:10:05 ot_train.py:625 step:28K smpl:2M ep:41K epch:8.32 loss:0.046 grdn:0.280 lr:5.5e-05 updt_s:0.877 data_s:0.776 smp/s:39 mem_gb:39.64
+Training:  48%|████▊     | 28600/60000 [11:02:46<14:21:58,  1.65s/step]INFO 2026-07-15 03:15:37 ot_train.py:625 step:29K smpl:2M ep:41K epch:8.38 loss:0.046 grdn:0.291 lr:5.5e-05 updt_s:0.909 data_s:0.749 smp/s:39 mem_gb:39.64
+Training:  48%|████▊     | 28800/60000 [11:08:18<14:46:01,  1.70s/step]INFO 2026-07-15 03:21:09 ot_train.py:625 step:29K smpl:2M ep:42K epch:8.44 loss:0.046 grdn:0.272 lr:5.4e-05 updt_s:0.902 data_s:0.752 smp/s:39 mem_gb:39.64
+Training:  48%|████▊     | 29000/60000 [11:13:50<14:15:49,  1.66s/step]INFO 2026-07-15 03:26:41 ot_train.py:625 step:29K smpl:2M ep:42K epch:8.50 loss:0.046 grdn:0.273 lr:5.4e-05 updt_s:0.914 data_s:0.746 smp/s:39 mem_gb:39.64
+Training:  49%|████▊     | 29200/60000 [11:19:24<14:15:17,  1.67s/step]INFO 2026-07-15 03:32:15 ot_train.py:625 step:29K smpl:2M ep:42K epch:8.56 loss:0.046 grdn:0.264 lr:5.3e-05 updt_s:0.879 data_s:0.787 smp/s:38 mem_gb:39.64
+Training:  49%|████▉     | 29400/60000 [11:24:59<14:02:17,  1.65s/step]INFO 2026-07-15 03:37:50 ot_train.py:625 step:29K smpl:2M ep:42K epch:8.62 loss:0.045 grdn:0.278 lr:5.3e-05 updt_s:0.874 data_s:0.796 smp/s:38 mem_gb:39.62
+Training:  49%|████▉     | 29600/60000 [11:30:29<13:54:15,  1.65s/step]INFO 2026-07-15 03:43:20 ot_train.py:625 step:30K smpl:2M ep:43K epch:8.68 loss:0.044 grdn:0.278 lr:5.2e-05 updt_s:0.867 data_s:0.779 smp/s:39 mem_gb:39.64
+Training:  50%|██���█▉     | 29800/60000 [11:36:02<14:42:59,  1.75s/step]INFO 2026-07-15 03:48:53 ot_train.py:625 step:30K smpl:2M ep:43K epch:8.73 loss:0.043 grdn:0.268 lr:5.1e-05 updt_s:0.874 data_s:0.789 smp/s:38 mem_gb:39.64
+Training:  50%|█████     | 30000/60000 [11:41:34<13:52:00,  1.66s/step]INFO 2026-07-15 03:54:25 ot_train.py:625 step:30K smpl:2M ep:43K epch:8.79 loss:0.043 grdn:0.278 lr:5.1e-05 updt_s:0.878 data_s:0.781 smp/s:39 mem_gb:39.64
+Training:  50%|█████     | 30200/60000 [11:47:11<13:44:23,  1.66s/step]INFO 2026-07-15 04:00:02 ot_train.py:625 step:30K smpl:2M ep:44K epch:8.85 loss:0.043 grdn:0.276 lr:5.0e-05 updt_s:0.894 data_s:0.786 smp/s:38 mem_gb:39.64
+Training:  51%|█████     | 30400/60000 [11:52:46<13:39:50,  1.66s/step]INFO 2026-07-15 04:05:37 ot_train.py:625 step:30K smpl:2M ep:44K epch:8.91 loss:0.043 grdn:0.264 lr:5.0e-05 updt_s:0.909 data_s:0.764 smp/s:38 mem_gb:39.64
+Training:  51%|█████     | 30600/60000 [11:58:20<13:32:44,  1.66s/step]INFO 2026-07-15 04:11:11 ot_train.py:625 step:31K smpl:2M ep:44K epch:8.97 loss:0.042 grdn:0.270 lr:4.9e-05 updt_s:0.873 data_s:0.794 smp/s:38 mem_gb:39.64
+Training:  51%|█████▏    | 30800/60000 [12:03:53<13:26:33,  1.66s/step]INFO 2026-07-15 04:16:45 ot_train.py:625 step:31K smpl:2M ep:45K epch:9.03 loss:0.043 grdn:0.267 lr:4.9e-05 updt_s:0.875 data_s:0.789 smp/s:38 mem_gb:39.64
+Training:  52%|█████▏    | 31000/60000 [12:09:29<13:30:18,  1.68s/step]INFO 2026-07-15 04:22:20 ot_train.py:625 step:31K smpl:2M ep:45K epch:9.09 loss:0.042 grdn:0.270 lr:4.8e-05 updt_s:0.901 data_s:0.774 smp/s:38 mem_gb:39.64
+Training:  52%|█████▏    | 31200/60000 [12:15:01<13:14:58,  1.66s/step]INFO 2026-07-15 04:27:52 ot_train.py:625 step:31K smpl:2M ep:45K epch:9.14 loss:0.042 grdn:0.266 lr:4.8e-05 updt_s:0.872 data_s:0.784 smp/s:39 mem_gb:39.64
+Training:  52%|█████▏    | 31400/60000 [12:20:32<12:46:41,  1.61s/step]INFO 2026-07-15 04:33:23 ot_train.py:625 step:31K smpl:2M ep:45K epch:9.20 loss:0.043 grdn:0.267 lr:4.7e-05 updt_s:0.896 data_s:0.757 smp/s:39 mem_gb:39.64
+Training:  53%|█████▎    | 31600/60000 [12:26:06<15:55:47,  2.02s/step]INFO 2026-07-15 04:38:57 ot_train.py:625 step:32K smpl:2M ep:46K epch:9.26 loss:0.042 grdn:0.269 lr:4.7e-05 updt_s:0.900 data_s:0.766 smp/s:38 mem_gb:39.62
+Training:  53%|█████▎    | 31800/60000 [12:31:35<11:47:12,  1.50s/step]INFO 2026-07-15 04:44:26 ot_train.py:625 step:32K smpl:2M ep:46K epch:9.32 loss:0.040 grdn:0.260 lr:4.6e-05 updt_s:0.891 data_s:0.751 smp/s:39 mem_gb:39.64
+Training:  53%|█████▎    | 32000/60000 [12:37:07<12:48:46,  1.65s/step]INFO 2026-07-15 04:49:58 ot_train.py:625 step:32K smpl:2M ep:46K epch:9.38 loss:0.041 grdn:0.275 lr:4.6e-05 updt_s:0.886 data_s:0.771 smp/s:39 mem_gb:39.64
+Training:  54%|█████▎    | 32200/60000 [12:42:41<12:45:47,  1.65s/step]INFO 2026-07-15 04:55:32 ot_train.py:625 step:32K smpl:2M ep:47K epch:9.44 loss:0.041 grdn:0.286 lr:4.5e-05 updt_s:0.889 data_s:0.775 smp/s:38 mem_gb:39.64
+Training:  54%|█████▍    | 32400/60000 [12:48:13<12:43:18,  1.66s/step]INFO 2026-07-15 05:01:04 ot_train.py:625 step:32K smpl:2M ep:47K epch:9.50 loss:0.041 grdn:0.277 lr:4.5e-05 updt_s:0.890 data_s:0.770 smp/s:39 mem_gb:39.63
+Training:  54%|█████▍    | 32600/60000 [12:53:49<12:41:27,  1.67s/step]INFO 2026-07-15 05:06:40 ot_train.py:625 step:33K smpl:2M ep:47K epch:9.55 loss:0.040 grdn:0.277 lr:4.4e-05 updt_s:0.901 data_s:0.774 smp/s:38 mem_gb:39.64
+Training:  55%|█████▍    | 32800/60000 [12:59:16<12:20:59,  1.63s/step]INFO 2026-07-15 05:12:07 ot_train.py:625 step:33K smpl:2M ep:47K epch:9.61 loss:0.040 grdn:0.271 lr:4.4e-05 updt_s:0.922 data_s:0.713 smp/s:39 mem_gb:39.63
+Training:  55%|█████▌    | 33000/60000 [13:04:43<12:14:14,  1.63s/step]INFO 2026-07-15 05:17:34 ot_train.py:625 step:33K smpl:2M ep:48K epch:9.67 loss:0.041 grdn:0.286 lr:4.3e-05 updt_s:0.874 data_s:0.758 smp/s:39 mem_gb:39.63
+Training:  55%|█████▌    | 33200/60000 [13:10:12<12:14:11,  1.64s/step]INFO 2026-07-15 05:23:03 ot_train.py:625 step:33K smpl:2M ep:48K epch:9.73 loss:0.040 grdn:0.286 lr:4.3e-05 updt_s:0.899 data_s:0.742 smp/s:39 mem_gb:39.64
+Training:  56%|█████▌    | 33400/60000 [13:15:41<12:09:56,  1.65s/step]INFO 2026-07-15 05:28:32 ot_train.py:625 step:33K smpl:2M ep:48K epch:9.79 loss:0.040 grdn:0.279 lr:4.2e-05 updt_s:0.895 data_s:0.749 smp/s:39 mem_gb:39.64
+Training:  56%|█████▌    | 33600/60000 [13:21:14<12:40:48,  1.73s/step]INFO 2026-07-15 05:34:05 ot_train.py:625 step:34K smpl:2M ep:49K epch:9.85 loss:0.040 grdn:0.287 lr:4.1e-05 updt_s:0.905 data_s:0.754 smp/s:39 mem_gb:39.64
+Training:  56%|█████▋    | 33800/60000 [13:26:39<11:36:03,  1.59s/step]INFO 2026-07-15 05:39:30 ot_train.py:625 step:34K smpl:2M ep:49K epch:9.91 loss:0.040 grdn:0.281 lr:4.1e-05 updt_s:0.930 data_s:0.691 smp/s:39 mem_gb:39.64
+Training:  57%|█████▋    | 34000/60000 [13:32:14<11:58:23,  1.66s/step]INFO 2026-07-15 05:45:05 ot_train.py:625 step:34K smpl:2M ep:49K epch:9.96 loss:0.038 grdn:0.264 lr:4.0e-05 updt_s:0.932 data_s:0.742 smp/s:38 mem_gb:39.62
+Training:  57%|█████▋    | 34200/60000 [13:37:48<12:17:56,  1.72s/step]INFO 2026-07-15 05:50:39 ot_train.py:625 step:34K smpl:2M ep:49K epch:10.02 loss:0.037 grdn:0.260 lr:4.0e-05 updt_s:0.891 data_s:0.773 smp/s:38 mem_gb:39.64
+Training:  57%|█████▋    | 34400/60000 [13:43:24<12:10:03,  1.71s/step]INFO 2026-07-15 05:56:15 ot_train.py:625 step:34K smpl:2M ep:50K epch:10.08 loss:0.037 grdn:0.274 lr:3.9e-05 updt_s:0.893 data_s:0.786 smp/s:38 mem_gb:39.63
+Training:  58%|█████▊    | 34600/60000 [13:48:56<11:45:11,  1.67s/step]INFO 2026-07-15 06:01:47 ot_train.py:625 step:35K smpl:2M ep:50K epch:10.14 loss:0.037 grdn:0.273 lr:3.9e-05 updt_s:0.899 data_s:0.756 smp/s:39 mem_gb:39.63
+Training:  58%|█████▊    | 34800/60000 [13:54:27<11:31:52,  1.65s/step]INFO 2026-07-15 06:07:18 ot_train.py:625 step:35K smpl:2M ep:50K epch:10.20 loss:0.038 grdn:0.269 lr:3.8e-05 updt_s:0.874 data_s:0.780 smp/s:39 mem_gb:39.64
+Training:  58%|█████▊    | 35000/60000 [13:59:57<11:15:26,  1.62s/step]INFO 2026-07-15 06:12:48 ot_train.py:625 step:35K smpl:2M ep:51K epch:10.26 loss:0.037 grdn:0.277 lr:3.8e-05 updt_s:0.881 data_s:0.763 smp/s:39 mem_gb:39.63
+Training:  59%|█████▊    | 35200/60000 [14:05:28<11:24:17,  1.66s/step]INFO 2026-07-15 06:18:19 ot_train.py:625 step:35K smpl:2M ep:51K epch:10.32 loss:0.037 grdn:0.300 lr:3.7e-05 updt_s:0.896 data_s:0.759 smp/s:39 mem_gb:39.64
+Training:  59%|█████▉    | 35400/60000 [14:11:00<11:26:13,  1.67s/step]INFO 2026-07-15 06:23:51 ot_train.py:625 step:35K smpl:2M ep:51K epch:10.38 loss:0.037 grdn:0.274 lr:3.7e-05 updt_s:0.886 data_s:0.770 smp/s:39 mem_gb:39.64
+Training:  59%|█████▉    | 35600/60000 [14:16:34<11:16:52,  1.66s/step]INFO 2026-07-15 06:29:25 ot_train.py:625 step:36K smpl:2M ep:51K epch:10.43 loss:0.036 grdn:0.276 lr:3.6e-05 updt_s:0.905 data_s:0.763 smp/s:38 mem_gb:39.63
+Training:  60%|█████▉    | 35800/60000 [14:22:04<11:07:28,  1.65s/step]INFO 2026-07-15 06:34:56 ot_train.py:625 step:36K smpl:2M ep:52K epch:10.49 loss:0.036 grdn:0.273 lr:3.6e-05 updt_s:0.896 data_s:0.751 smp/s:39 mem_gb:39.64
+Training:  60%|██████    | 36000/60000 [14:27:41<12:01:42,  1.80s/step]INFO 2026-07-15 06:40:32 ot_train.py:625 step:36K smpl:2M ep:52K epch:10.55 loss:0.037 grdn:0.277 lr:3.5e-05 updt_s:0.890 data_s:0.791 smp/s:38 mem_gb:39.64
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+Training:  62%|██████▏   | 37000/60000 [14:55:40<10:28:31,  1.64s/step]INFO 2026-07-15 07:08:31 ot_train.py:625 step:37K smpl:2M ep:53K epch:10.84 loss:0.034 grdn:0.274 lr:3.3e-05 updt_s:0.899 data_s:0.791 smp/s:38 mem_gb:39.64
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+Training:  63%|██████▎   | 37800/60000 [15:17:54<10:06:55,  1.64s/step]INFO 2026-07-15 07:30:45 ot_train.py:625 step:38K smpl:2M ep:55K epch:11.08 loss:0.034 grdn:0.285 lr:3.1e-05 updt_s:0.894 data_s:0.770 smp/s:38 mem_gb:39.64
+Training:  63%|██████▎   | 38000/60000 [15:23:32<10:56:34,  1.79s/step]INFO 2026-07-15 07:36:23 ot_train.py:625 step:38K smpl:2M ep:55K epch:11.14 loss:0.034 grdn:0.276 lr:3.0e-05 updt_s:0.907 data_s:0.781 smp/s:38 mem_gb:39.63
+Training:  64%|██████▎   | 38200/60000 [15:29:03<10:07:18,  1.67s/step]INFO 2026-07-15 07:41:54 ot_train.py:625 step:38K smpl:2M ep:55K epch:11.20 loss:0.034 grdn:0.279 lr:3.0e-05 updt_s:0.898 data_s:0.757 smp/s:39 mem_gb:39.64
+Training:  64%|██████▍   | 38400/60000 [15:34:41<9:42:31,  1.62s/step]INFO 2026-07-15 07:47:32 ot_train.py:625 step:38K smpl:2M ep:55K epch:11.25 loss:0.034 grdn:0.278 lr:2.9e-05 updt_s:0.893 data_s:0.794 smp/s:38 mem_gb:39.62
+Training:  64%|██████▍   | 38600/60000 [15:40:13<9:58:51,  1.68s/step]INFO 2026-07-15 07:53:04 ot_train.py:625 step:39K smpl:2M ep:56K epch:11.31 loss:0.031 grdn:0.273 lr:2.9e-05 updt_s:0.878 data_s:0.776 smp/s:39 mem_gb:39.64
+Training:  65%|██████▍   | 38800/60000 [15:45:47<9:58:54,  1.70s/step]INFO 2026-07-15 07:58:38 ot_train.py:625 step:39K smpl:2M ep:56K epch:11.37 loss:0.032 grdn:0.269 lr:2.8e-05 updt_s:0.872 data_s:0.794 smp/s:38 mem_gb:39.64
+Training:  65%|██████▌   | 39000/60000 [15:51:21<9:14:08,  1.58s/step]INFO 2026-07-15 08:04:12 ot_train.py:625 step:39K smpl:2M ep:56K epch:11.43 loss:0.032 grdn:0.268 lr:2.8e-05 updt_s:0.876 data_s:0.793 smp/s:38 mem_gb:39.64
+Training:  65%|██████▌   | 39200/60000 [15:56:53<10:02:35,  1.74s/step]INFO 2026-07-15 08:09:44 ot_train.py:625 step:39K smpl:3M ep:57K epch:11.49 loss:0.030 grdn:0.278 lr:2.7e-05 updt_s:0.888 data_s:0.768 smp/s:39 mem_gb:39.64
+Training:  66%|██████▌   | 39400/60000 [16:02:25<9:52:44,  1.73s/step]INFO 2026-07-15 08:15:16 ot_train.py:625 step:39K smpl:3M ep:57K epch:11.55 loss:0.032 grdn:0.276 lr:2.7e-05 updt_s:0.897 data_s:0.761 smp/s:39 mem_gb:39.63
+Training:  66%|██████▌   | 39600/60000 [16:08:00<9:22:03,  1.65s/step]INFO 2026-07-15 08:20:51 ot_train.py:625 step:40K smpl:3M ep:57K epch:11.61 loss:0.032 grdn:0.283 lr:2.7e-05 updt_s:0.891 data_s:0.778 smp/s:38 mem_gb:39.64
+Training:  66%|██████▋   | 39800/60000 [16:13:33<9:25:39,  1.68s/step]INFO 2026-07-15 08:26:24 ot_train.py:625 step:40K smpl:3M ep:58K epch:11.66 loss:0.032 grdn:0.284 lr:2.6e-05 updt_s:0.881 data_s:0.783 smp/s:38 mem_gb:39.64
+Training:  67%|██████▋   | 40000/60000 [16:19:06<9:08:31,  1.65s/step]INFO 2026-07-15 08:31:57 ot_train.py:625 step:40K smpl:3M ep:58K epch:11.72 loss:0.031 grdn:0.275 lr:2.6e-05 updt_s:0.899 data_s:0.763 smp/s:38 mem_gb:39.64
+Training:  67%|██████▋   | 40200/60000 [16:24:36<9:11:55,  1.67s/step]INFO 2026-07-15 08:37:27 ot_train.py:625 step:40K smpl:3M ep:58K epch:11.78 loss:0.032 grdn:0.277 lr:2.5e-05 updt_s:0.888 data_s:0.757 smp/s:39 mem_gb:39.64
+Training:  67%|██████▋   | 40400/60000 [16:30:08<9:18:53,  1.71s/step]INFO 2026-07-15 08:42:59 ot_train.py:625 step:40K smpl:3M ep:58K epch:11.84 loss:0.030 grdn:0.271 lr:2.5e-05 updt_s:0.887 data_s:0.771 smp/s:39 mem_gb:39.64
+Training:  68%|██████▊   | 40600/60000 [16:35:41<9:07:31,  1.69s/step]INFO 2026-07-15 08:48:32 ot_train.py:625 step:41K smpl:3M ep:59K epch:11.90 loss:0.030 grdn:0.292 lr:2.4e-05 updt_s:0.883 data_s:0.777 smp/s:39 mem_gb:39.64
+Training:  68%|██████▊   | 40800/60000 [16:41:13<8:45:21,  1.64s/step]INFO 2026-07-15 08:54:04 ot_train.py:625 step:41K smpl:3M ep:59K epch:11.96 loss:0.029 grdn:0.272 lr:2.4e-05 updt_s:0.898 data_s:0.761 smp/s:39 mem_gb:39.62
+Training:  68%|██████▊   | 41000/60000 [16:46:49<8:40:00,  1.64s/step]INFO 2026-07-15 08:59:40 ot_train.py:625 step:41K smpl:3M ep:59K epch:12.02 loss:0.030 grdn:0.284 lr:2.3e-05 updt_s:0.895 data_s:0.783 smp/s:38 mem_gb:39.64
+Training:  69%|██████▊   | 41200/60000 [16:52:23<8:35:24,  1.64s/step]INFO 2026-07-15 09:05:14 ot_train.py:625 step:41K smpl:3M ep:60K epch:12.08 loss:0.029 grdn:0.289 lr:2.3e-05 updt_s:0.893 data_s:0.770 smp/s:38 mem_gb:39.63
+Training:  69%|██████▉   | 41400/60000 [16:57:54<8:40:07,  1.68s/step]INFO 2026-07-15 09:10:45 ot_train.py:625 step:41K smpl:3M ep:60K epch:12.13 loss:0.029 grdn:0.262 lr:2.2e-05 updt_s:0.888 data_s:0.767 smp/s:39 mem_gb:39.64
+Training:  69%|██████▉   | 41600/60000 [17:03:26<8:20:39,  1.63s/step]INFO 2026-07-15 09:16:17 ot_train.py:625 step:42K smpl:3M ep:60K epch:12.19 loss:0.027 grdn:0.266 lr:2.2e-05 updt_s:0.867 data_s:0.789 smp/s:39 mem_gb:39.64
+Training:  70%|██████▉   | 41800/60000 [17:10:48<20:41:28,  4.09s/step]INFO 2026-07-15 09:23:39 ot_train.py:625 step:42K smpl:3M ep:60K epch:12.25 loss:0.029 grdn:0.273 lr:2.2e-05 updt_s:1.412 data_s:0.794 smp/s:29 mem_gb:39.64
+Training:  70%|███████   | 42000/60000 [17:24:24<20:31:05,  4.10s/step]INFO 2026-07-15 09:37:15 ot_train.py:625 step:42K smpl:3M ep:61K epch:12.31 loss:0.029 grdn:0.269 lr:2.1e-05 updt_s:3.228 data_s:0.847 smp/s:16 mem_gb:39.64
+Training:  70%|███████   | 42200/60000 [17:35:54<12:07:31,  2.45s/step]INFO 2026-07-15 09:48:45 ot_train.py:625 step:42K smpl:3M ep:61K epch:12.37 loss:0.029 grdn:0.271 lr:2.1e-05 updt_s:2.618 data_s:0.831 smp/s:19 mem_gb:39.64
+Training:  71%|███████   | 42400/60000 [17:44:04<11:56:06,  2.44s/step]INFO 2026-07-15 09:56:56 ot_train.py:625 step:42K smpl:3M ep:61K epch:12.43 loss:0.029 grdn:0.279 lr:2.0e-05 updt_s:1.822 data_s:0.627 smp/s:26 mem_gb:39.64
+Training:  71%|███████   | 42600/60000 [17:55:05<18:12:31,  3.77s/step]INFO 2026-07-15 10:07:56 ot_train.py:625 step:43K smpl:3M ep:62K epch:12.49 loss:0.029 grdn:0.269 lr:2.0e-05 updt_s:2.721 data_s:0.578 smp/s:19 mem_gb:39.64
+Training:  71%|███████▏  | 42800/60000 [18:07:29<17:56:14,  3.75s/step]INFO 2026-07-15 10:20:20 ot_train.py:625 step:43K smpl:3M ep:62K epch:12.54 loss:0.029 grdn:0.267 lr:1.9e-05 updt_s:3.151 data_s:0.568 smp/s:17 mem_gb:39.64
+Training:  72%|███████▏  | 43000/60000 [18:16:24<12:50:33,  2.72s/step]INFO 2026-07-15 10:29:15 ot_train.py:625 step:43K smpl:3M ep:62K epch:12.60 loss:0.027 grdn:0.270 lr:1.9e-05 updt_s:2.092 data_s:0.579 smp/s:24 mem_gb:39.62
+Training:  72%|███████▏  | 43200/60000 [18:24:18<11:55:31,  2.56s/step]INFO 2026-07-15 10:37:10 ot_train.py:625 step:43K smpl:3M ep:62K epch:12.66 loss:0.027 grdn:0.273 lr:1.9e-05 updt_s:1.796 data_s:0.575 smp/s:27 mem_gb:39.64
+Training:  72%|███████▏  | 43400/60000 [18:32:45<12:08:05,  2.63s/step]INFO 2026-07-15 10:45:36 ot_train.py:625 step:43K smpl:3M ep:63K epch:12.72 loss:0.028 grdn:0.274 lr:1.8e-05 updt_s:1.957 data_s:0.572 smp/s:25 mem_gb:39.63
+Training:  73%|███████▎  | 43600/60000 [18:41:16<11:03:50,  2.43s/step]INFO 2026-07-15 10:54:07 ot_train.py:625 step:44K smpl:3M ep:63K epch:12.78 loss:0.026 grdn:0.259 lr:1.8e-05 updt_s:1.980 data_s:0.574 smp/s:25 mem_gb:39.64
+Training:  73%|███████▎  | 43800/60000 [18:47:18<8:26:27,  1.88s/step]INFO 2026-07-15 11:00:09 ot_train.py:625 step:44K smpl:3M ep:63K epch:12.84 loss:0.027 grdn:0.273 lr:1.7e-05 updt_s:1.213 data_s:0.592 smp/s:35 mem_gb:39.64
+Training:  73%|███████▎  | 44000/60000 [18:54:49<12:06:04,  2.72s/step]INFO 2026-07-15 11:07:40 ot_train.py:625 step:44K smpl:3M ep:64K epch:12.90 loss:0.027 grdn:0.257 lr:1.7e-05 updt_s:1.629 data_s:0.624 smp/s:28 mem_gb:39.64
+Training:  74%|███████▎  | 44200/60000 [19:03:46<11:36:50,  2.65s/step]INFO 2026-07-15 11:16:37 ot_train.py:625 step:44K smpl:3M ep:64K epch:12.95 loss:0.027 grdn:0.286 lr:1.7e-05 updt_s:2.081 data_s:0.601 smp/s:24 mem_gb:39.64
+Training:  74%|███████▍  | 44400/60000 [19:11:34<11:23:20,  2.63s/step]INFO 2026-07-15 11:24:25 ot_train.py:625 step:44K smpl:3M ep:64K epch:13.01 loss:0.027 grdn:0.281 lr:1.6e-05 updt_s:1.766 data_s:0.572 smp/s:27 mem_gb:39.64
+Training:  74%|███████▍  | 44600/60000 [19:20:07<11:26:35,  2.68s/step]INFO 2026-07-15 11:32:58 ot_train.py:625 step:45K smpl:3M ep:64K epch:13.07 loss:0.026 grdn:0.264 lr:1.6e-05 updt_s:1.982 data_s:0.579 smp/s:25 mem_gb:39.64
+Training:  75%|███████▍  | 44800/60000 [19:27:32<8:00:15,  1.90s/step]INFO 2026-07-15 11:40:23 ot_train.py:625 step:45K smpl:3M ep:65K epch:13.13 loss:0.026 grdn:0.263 lr:1.5e-05 updt_s:1.652 data_s:0.572 smp/s:29 mem_gb:39.64
+Training:  75%|███████▌  | 45000/60000 [19:33:50<5:02:16,  1.21s/step]INFO 2026-07-15 11:46:41 ot_train.py:625 step:45K smpl:3M ep:65K epch:13.19 loss:0.026 grdn:0.264 lr:1.5e-05 updt_s:1.243 data_s:0.641 smp/s:34 mem_gb:39.63
+Training:  75%|███████▌  | 45200/60000 [19:42:45<10:54:27,  2.65s/step]INFO 2026-07-15 11:55:36 ot_train.py:625 step:45K smpl:3M ep:65K epch:13.25 loss:0.026 grdn:0.262 lr:1.5e-05 updt_s:2.077 data_s:0.596 smp/s:24 mem_gb:39.62
+Training:  76%|███████▌  | 45400/60000 [19:51:39<11:06:40,  2.74s/step]INFO 2026-07-15 12:04:30 ot_train.py:625 step:45K smpl:3M ep:66K epch:13.31 loss:0.025 grdn:0.251 lr:1.4e-05 updt_s:2.088 data_s:0.582 smp/s:24 mem_gb:39.64
+Training:  76%|███████▌  | 45600/60000 [19:59:38<10:22:59,  2.60s/step]INFO 2026-07-15 12:12:29 ot_train.py:625 step:46K smpl:3M ep:66K epch:13.36 loss:0.026 grdn:0.295 lr:1.4e-05 updt_s:1.812 data_s:0.578 smp/s:27 mem_gb:39.64
+Training:  76%|███████▋  | 45800/60000 [20:08:05<5:11:53,  1.32s/step]INFO 2026-07-15 12:20:56 ot_train.py:625 step:46K smpl:3M ep:66K epch:13.42 loss:0.025 grdn:0.257 lr:1.4e-05 updt_s:1.964 data_s:0.570 smp/s:25 mem_gb:39.64
+Training:  77%|███████▋  | 46000/60000 [20:14:12<7:11:12,  1.85s/step]INFO 2026-07-15 12:27:03 ot_train.py:625 step:46K smpl:3M ep:66K epch:13.48 loss:0.024 grdn:0.257 lr:1.3e-05 updt_s:1.194 data_s:0.637 smp/s:35 mem_gb:39.63
+Training:  77%|███████▋  | 46200/60000 [20:22:15<10:13:05,  2.67s/step]INFO 2026-07-15 12:35:06 ot_train.py:625 step:46K smpl:3M ep:67K epch:13.54 loss:0.024 grdn:0.258 lr:1.3e-05 updt_s:1.828 data_s:0.582 smp/s:27 mem_gb:39.64
+Training:  77%|███████▋  | 46400/60000 [20:30:14<9:40:57,  2.56s/step]INFO 2026-07-15 12:43:05 ot_train.py:625 step:46K smpl:3M ep:67K epch:13.60 loss:0.024 grdn:0.266 lr:1.3e-05 updt_s:1.821 data_s:0.571 smp/s:27 mem_gb:39.63
+Training:  78%|███████▊  | 46600/60000 [20:37:49<7:04:35,  1.90s/step]INFO 2026-07-15 12:50:40 ot_train.py:625 step:47K smpl:3M ep:67K epch:13.66 loss:0.024 grdn:0.260 lr:1.2e-05 updt_s:1.693 data_s:0.578 smp/s:28 mem_gb:39.64
+Training:  78%|███████▊  | 46800/60000 [20:44:09<7:38:08,  2.08s/step]INFO 2026-07-15 12:57:00 ot_train.py:625 step:47K smpl:3M ep:68K epch:13.72 loss:0.024 grdn:0.256 lr:1.2e-05 updt_s:1.261 data_s:0.638 smp/s:34 mem_gb:39.64
+Training:  78%|███████▊  | 47000/60000 [20:52:10<9:41:08,  2.68s/step]INFO 2026-07-15 13:05:01 ot_train.py:625 step:47K smpl:3M ep:68K epch:13.77 loss:0.024 grdn:0.265 lr:1.1e-05 updt_s:1.825 data_s:0.575 smp/s:27 mem_gb:39.63
+Training:  79%|███████▊  | 47200/60000 [21:00:56<9:30:27,  2.67s/step]INFO 2026-07-15 13:13:47 ot_train.py:625 step:47K smpl:3M ep:68K epch:13.83 loss:0.024 grdn:0.264 lr:1.1e-05 updt_s:2.050 data_s:0.577 smp/s:24 mem_gb:39.63
+Training:  79%|███████▉  | 47400/60000 [21:09:19<4:47:27,  1.37s/step]INFO 2026-07-15 13:22:10 ot_train.py:625 step:47K smpl:3M ep:68K epch:13.89 loss:0.024 grdn:0.276 lr:1.1e-05 updt_s:1.935 data_s:0.580 smp/s:25 mem_gb:39.62
+Training:  79%|███████▉  | 47600/60000 [21:17:27<8:38:29,  2.51s/step]INFO 2026-07-15 13:30:19 ot_train.py:625 step:48K smpl:3M ep:69K epch:13.95 loss:0.023 grdn:0.254 lr:1.0e-05 updt_s:1.870 data_s:0.569 smp/s:26 mem_gb:39.64
+Training:  80%|███████▉  | 47800/60000 [21:26:57<10:57:31,  3.23s/step]INFO 2026-07-15 13:39:48 ot_train.py:625 step:48K smpl:3M ep:69K epch:14.01 loss:0.023 grdn:0.274 lr:1.0e-05 updt_s:2.158 data_s:0.688 smp/s:22 mem_gb:39.63
+Training:  80%|████████  | 48000/60000 [21:35:23<6:19:34,  1.90s/step]INFO 2026-07-15 13:48:14 ot_train.py:625 step:48K smpl:3M ep:69K epch:14.07 loss:0.023 grdn:0.253 lr:9.9e-06 updt_s:1.758 data_s:0.769 smp/s:25 mem_gb:39.63
+Training:  80%|████████  | 48200/60000 [21:40:03<3:53:51,  1.19s/step]INFO 2026-07-15 13:52:54 ot_train.py:625 step:48K smpl:3M ep:70K epch:14.13 loss:0.023 grdn:0.259 lr:9.5e-06 updt_s:0.794 data_s:0.604 smp/s:46 mem_gb:39.64
+Training:  81%|████████  | 48400/60000 [21:44:09<3:56:28,  1.22s/step]INFO 2026-07-15 13:57:00 ot_train.py:625 step:48K smpl:3M ep:70K epch:14.19 loss:0.022 grdn:0.250 lr:9.2e-06 updt_s:0.647 data_s:0.577 smp/s:52 mem_gb:39.63
+Training:  81%|████████  | 48600/60000 [21:48:11<3:45:58,  1.19s/step]INFO 2026-07-15 14:01:02 ot_train.py:625 step:49K smpl:3M ep:70K epch:14.24 loss:0.023 grdn:0.260 lr:8.9e-06 updt_s:0.639 data_s:0.568 smp/s:53 mem_gb:39.64
+Training:  81%|████████▏ | 48800/60000 [21:52:14<3:41:56,  1.19s/step]INFO 2026-07-15 14:05:05 ot_train.py:625 step:49K smpl:3M ep:71K epch:14.30 loss:0.024 grdn:0.253 lr:8.6e-06 updt_s:0.644 data_s:0.572 smp/s:53 mem_gb:39.63
+Training:  82%|████████▏ | 49000/60000 [21:56:15<3:32:43,  1.16s/step]INFO 2026-07-15 14:09:06 ot_train.py:625 step:49K smpl:3M ep:71K epch:14.36 loss:0.023 grdn:0.245 lr:8.3e-06 updt_s:0.643 data_s:0.558 smp/s:53 mem_gb:39.63
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+Training:  83%|████████▎ | 50007/60000 [22:19:28<6:15:26,  2.25s/step] 

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Abs_6D/Baseline/wandb/run-20260715_143250-1jmjb68j/files/output.log

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+INFO 2026-07-15 14:32:51 db_utils.py:121 Logs will be synced with wandb.
+INFO 2026-07-15 14:32:51 db_utils.py:122 Track this run --> https://wandb.ai/minje227_hyu-hanyang-university/lerobot/runs/1jmjb68j
+INFO 2026-07-15 14:32:51 ot_train.py:298 Creating dataset
+INFO 2026-07-15 14:32:54 ot_train.py:332 Creating policy
+INFO 2026-07-15 14:32:54 ng_groot.py:191 The Groot policy wraps NVIDIA's GR00T n1.7 model. Loading pretrained model from: /home/ext_minje/groot_insight/Abs_6D/Baseline/checkpoints/050000/pretrained_model
+INFO 2026-07-15 14:32:54 ng_groot.py:225 Detected fine-tuned LeRobot checkpoint, loading with state dict...
+Fetching 27 files: 100%|██████████| 27/27 [00:00<00:00, 1554.62it/s]
+`torch_dtype` is deprecated! Use `dtype` instead!
+Loading weights: 100%|██████████| 1031/1031 [00:00<00:00, 2321.50it/s]
+Loading weights from local directory
+INFO 2026-07-15 14:33:09 ot_train.py:405 Creating optimizer and scheduler
+INFO 2026-07-15 14:33:12 ot_train.py:437 Output dir: /home/ext_minje/groot_insight/Abs_6D/Baseline
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+Training:  76%|███████▌  | 7600/10000 [3:29:49<1:05:33,  1.64s/step]INFO 2026-07-15 18:03:02 ot_train.py:646 step:58K smpl:4M ep:83K epch:16.88 loss:0.019 grdn:0.225 lr:4.4e-07 updt_s:0.899 data_s:0.770 smp/s:38 mem_gb:39.59
+Training:  78%|███████▊  | 7800/10000 [3:35:24<1:00:16,  1.64s/step]INFO 2026-07-15 18:08:37 ot_train.py:646 step:58K smpl:4M ep:84K epch:16.94 loss:0.019 grdn:0.230 lr:3.7e-07 updt_s:0.901 data_s:0.772 smp/s:38 mem_gb:39.59
+Training:  80%|████████  | 8000/10000 [3:41:01<58:47,  1.76s/step]INFO 2026-07-15 18:14:14 ot_train.py:646 step:58K smpl:4M ep:84K epch:17.00 loss:0.019 grdn:0.219 lr:3.1e-07 updt_s:0.915 data_s:0.766 smp/s:38 mem_gb:39.59
+Training:  82%|████████▏ | 8200/10000 [3:46:37<50:06,  1.67s/step]INFO 2026-07-15 18:19:50 ot_train.py:646 step:58K smpl:4M ep:84K epch:17.06 loss:0.020 grdn:0.230 lr:2.5e-07 updt_s:0.910 data_s:0.768 smp/s:38 mem_gb:39.59
+Training:  84%|████████▍ | 8400/10000 [3:52:19<43:53,  1.65s/step]INFO 2026-07-15 18:25:32 ot_train.py:646 step:58K smpl:4M ep:84K epch:17.12 loss:0.020 grdn:0.231 lr:2.0e-07 updt_s:0.936 data_s:0.770 smp/s:38 mem_gb:39.59
+Training:  86%|████████▌ | 8600/10000 [3:57:55<42:26,  1.82s/step]INFO 2026-07-15 18:31:08 ot_train.py:646 step:59K smpl:4M ep:85K epch:17.17 loss:0.019 grdn:0.228 lr:1.6e-07 updt_s:0.953 data_s:0.725 smp/s:38 mem_gb:39.59
+Training:  88%|████████▊ | 8800/10000 [4:03:31<33:19,  1.67s/step]INFO 2026-07-15 18:36:44 ot_train.py:646 step:59K smpl:4M ep:85K epch:17.23 loss:0.020 grdn:0.234 lr:1.2e-07 updt_s:0.902 data_s:0.778 smp/s:38 mem_gb:39.58
+Training:  90%|█████████ | 9000/10000 [4:09:07<30:05,  1.81s/step]INFO 2026-07-15 18:42:20 ot_train.py:646 step:59K smpl:4M ep:85K epch:17.29 loss:0.019 grdn:0.220 lr:8.4e-08 updt_s:0.904 data_s:0.771 smp/s:38 mem_gb:39.59
+Training:  92%|█████████▏| 9200/10000 [4:14:44<23:27,  1.76s/step]INFO 2026-07-15 18:47:57 ot_train.py:646 step:59K smpl:4M ep:86K epch:17.35 loss:0.020 grdn:0.228 lr:5.7e-08 updt_s:0.899 data_s:0.782 smp/s:38 mem_gb:39.59
+Training:  94%|█████████▍| 9400/10000 [4:20:17<16:53,  1.69s/step]INFO 2026-07-15 18:53:30 ot_train.py:646 step:59K smpl:4M ep:86K epch:17.41 loss:0.020 grdn:0.243 lr:3.4e-08 updt_s:0.901 data_s:0.764 smp/s:38 mem_gb:39.59
+Training:  96%|█████████▌| 9600/10000 [4:25:50<10:42,  1.61s/step]INFO 2026-07-15 18:59:03 ot_train.py:646 step:60K smpl:4M ep:86K epch:17.47 loss:0.019 grdn:0.228 lr:1.8e-08 updt_s:0.909 data_s:0.752 smp/s:39 mem_gb:39.59
+Training:  98%|█████████▊| 9800/10000 [4:31:24<05:26,  1.63s/step]INFO 2026-07-15 19:04:37 ot_train.py:646 step:60K smpl:4M ep:86K epch:17.53 loss:0.019 grdn:0.225 lr:6.5e-09 updt_s:0.889 data_s:0.778 smp/s:38 mem_gb:39.59
+Training: 100%|██████████| 10000/10000 [4:37:01<00:00,  1.66s/step]INFO 2026-07-15 19:10:14 ot_train.py:646 step:60K smpl:4M ep:87K epch:17.59 loss:0.019 grdn:0.219 lr:9.2e-10 updt_s:0.909 data_s:0.773 smp/s:38 mem_gb:39.59
+INFO 2026-07-15 19:10:14 ot_train.py:691 Checkpoint policy after step 60000
+INFO 2026-07-15 19:10:44 ain_yaml.py:918 Saved config, action-space, prompt, and phase provenance in /home/ext_minje/groot_insight/Abs_6D/Baseline and /home/ext_minje/groot_insight/Abs_6D/Baseline/checkpoints/060000
+Training: 100%|██████████| 10000/10000 [4:37:31<00:00,  1.67s/step]
+INFO 2026-07-15 19:10:44 ot_train.py:777 End of training

Abs_6D/Baseline/wandb/run-20260715_143250-1jmjb68j/files/requirements.txt

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+  File "/home/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_manager.py", line 182, in fn_wrap_exceptions
+    await fn()
+  File "/home/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/run_messages.py", line 90, in loop
+    await asyncio_compat.race(
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/contextlib.py", line 217, in __aexit__
+    await anext(self.gen)
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/envs/lerobot060_groot/lib/python3.12/site-packages/wandb/sdk/lib/asyncio_compat.py", line 180, in _wait_all
+    raise exc
+  File "/home/ext_minje/miniforge3/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/ext_minje/miniforge3/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/ext_minje/miniforge3/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

Abs_6D/Baseline_gpu3_resume.pid

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Abs_6D/Baseline_gpu3_watcher_status.json

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+  "state": "error",
+  "updated_at": "2026-07-15T14:33:15+09:00"
+}

Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/phase_schedule.json

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+}

Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/pretrained_model/action_space_manifest.json

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Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/pretrained_model/policy_postprocessor.json

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+{
+  "name": "policy_postprocessor",
+  "steps": [
+    {
+      "registry_name": "groot_action_unpack_unnormalize_v2",
+      "config": {
+        "env_action_dim": 10,
+        "normalize_min_max": true,
+        "clip_normalized_action": true,
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+        "libero_gripper_binarize": true
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+      "state_file": "policy_postprocessor_step_0_groot_action_unpack_unnormalize_v2.safetensors"
+    },
+    {
+      "registry_name": "device_processor",
+      "config": {
+        "device": "cpu",
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+      }
+    }
+  ]
+}

Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/pretrained_model/train_config.json

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+{
+    "dataset": {
+        "repo_id": "Whalswp/INSIGHTfixposV4_filtered_multispace_v2",
+        "root": "/home/ext_minje/INSIGHTfixposV4_filtered_multispace_v2",
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+        "lora_rank": 0,
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+        "video_backend": "decord",
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+        "balance_trajectory_weights": true,
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+        "output_dir": "./tmp/gr00t",
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+        "batch_size": 32,
+        "dataloader_num_workers": 8,
+        "report_to": "wandb",
+        "resume": false,
+        "rkd_enabled": true,
+        "rkd_vae_checkpoint": "/home/ext_minje/groot_insight/TimewarpVAE_combo_top8_30k/C8_01_C3_008_beta_5em05_latent_dim_16_granularity_4_decoder_hidden_dim_512/checkpoint-step-30000-epoch-39.11",
+        "rkd_student_pooling": "attention",
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+    "output_dir": "/home/ext_minje/groot_insight/Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K",
+    "job_name": "INSIGHT_6D_RKD_TimewarpVAE_LAPstyle_6K",
+    "resume": false,
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+        "name": "cosine"
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+        "use_async_envs": true,
+        "recording": false,
+        "recording_repo_id": null,
+        "recording_private": false
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+    "wandb": {
+        "enable": true,
+        "disable_artifact": true,
+        "project": "lerobot",
+        "entity": null,
+        "notes": null,
+        "run_id": "pebh9ode",
+        "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_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/resolved_config.yaml

@@ -0,0 +1,34 @@
+dataset:
+  repo_id: Whalswp/INSIGHTfixposV4_filtered_multispace_v2
+  root: /home/ext_minje/INSIGHTfixposV4_filtered_multispace_v2
+policy:
+  type: groot_rkd
+  device: cuda
+  chunk_size: 16
+  n_action_steps: 16
+  push_to_hub: false
+  warmup_steps: 6000
+  tune_llm: false
+  tune_visual: false
+  tune_top_llm_layers: 0
+  tune_projector: true
+  tune_diffusion_model: true
+  tune_vlln: true
+  rkd_enabled: true
+  rkd_vae_checkpoint: /home/ext_minje/groot_insight/TimewarpVAE_combo_top8_30k/C8_01_C3_008_beta_5em05_latent_dim_16_granularity_4_decoder_hidden_dim_512/checkpoint-step-30000-epoch-39.11
+  rkd_student_pooling: attention
+  rkd_student_attention_hidden_dim: 512
+  rkd_student_attention_output_dim: 512
+  rkd_fm_loss_weight: 1.0
+  rkd_loss_weight: 1.0
+  rkd_distance_weight: 1.0
+  rkd_angle_weight: 2.0
+seed: 42
+batch_size: 64
+steps: 60000
+log_freq: 200
+output_dir: /home/ext_minje/groot_insight/Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K
+job_name: INSIGHT_6D_RKD_TimewarpVAE_LAPstyle_6K
+wandb:
+  enable: true
+  disable_artifact: true

Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000/training_state/training_step.json

@@ -0,0 +1,5 @@
+{
+    "step": 60000,
+    "num_processes": 1,
+    "batch_size": 64
+}

Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/wandb/run-20260715_011448-pebh9ode/files/output.log

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+INFO 2026-07-15 01:14:49 db_utils.py:121 Logs will be synced with wandb.
+INFO 2026-07-15 01:14:49 db_utils.py:122 Track this run --> https://wandb.ai/minje227_hyu-hanyang-university/lerobot/runs/pebh9ode
+INFO 2026-07-15 01:14:49 ot_train.py:298 Creating dataset
+INFO 2026-07-15 01:14:51 ot_train.py:332 Creating policy
+Fetching 27 files: 100%|██████████| 27/27 [00:00<00:00, 1325.37it/s]
+`torch_dtype` is deprecated! Use `dtype` instead!
+Loading weights: 100%|██████████| 1031/1031 [00:00<00:00, 2096.45it/s]
+INFO 2026-07-15 01:15:00 ot_train.py:405 Creating optimizer and scheduler
+INFO 2026-07-15 01:15:00 ot_train.py:439 Output dir: /home/ext_minje/groot_insight/Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K
+INFO 2026-07-15 01:15:00 ot_train.py:446 cfg.steps=60000 (60K)
+INFO 2026-07-15 01:15:00 ot_train.py:447 dataset.num_frames=218367 (218K)
+INFO 2026-07-15 01:15:00 ot_train.py:448 dataset.num_episodes=4930
+INFO 2026-07-15 01:15:00 ot_train.py:451 Effective batch size: 64 x 1 = 64
+INFO 2026-07-15 01:15:00 ot_train.py:452 num_learnable_params=1622090881 (2B)
+INFO 2026-07-15 01:15:00 ot_train.py:453 num_total_params=3145709729 (3B)
+Training:   0%|          | 0/60000 [00:00<?, ?step/s]INFO 2026-07-15 01:15:00 ot_train.py:604 Start offline training on a fixed dataset, with effective batch size: 64
+Training:   0%|          | 200/60000 [04:46<22:37:09,  1.36s/step]INFO 2026-07-15 01:19:46 ot_train.py:649 step:200 smpl:13K ep:289 epch:0.06 loss:1.345 grdn:0.758 lr:1.7e-06 updt_s:0.833 data_s:0.594 smp/s:45 mem_gb:39.69
+Training:   1%|          | 400/60000 [09:24<22:24:07,  1.35s/step]INFO 2026-07-15 01:24:24 ot_train.py:649 step:400 smpl:26K ep:578 epch:0.12 loss:1.021 grdn:1.398 lr:5.0e-06 updt_s:0.813 data_s:0.574 smp/s:46 mem_gb:39.70
+Training:   1%|          | 600/60000 [14:03<21:52:56,  1.33s/step]INFO 2026-07-15 01:29:03 ot_train.py:649 step:600 smpl:38K ep:867 epch:0.18 loss:0.416 grdn:2.294 lr:8.3e-06 updt_s:0.823 data_s:0.567 smp/s:46 mem_gb:39.70
+Training:   1%|▏         | 800/60000 [18:40<22:47:14,  1.39s/step]INFO 2026-07-15 01:33:40 ot_train.py:649 step:800 smpl:51K ep:1K epch:0.23 loss:0.281 grdn:2.509 lr:1.2e-05 updt_s:0.820 data_s:0.560 smp/s:46 mem_gb:39.70
+Training:   2%|▏         | 1000/60000 [23:17<23:07:02,  1.41s/step]INFO 2026-07-15 01:38:17 ot_train.py:649 step:1K smpl:64K ep:1K epch:0.29 loss:0.236 grdn:2.537 lr:1.5e-05 updt_s:0.819 data_s:0.562 smp/s:46 mem_gb:39.70
+Training:   2%|▏         | 1200/60000 [27:52<21:59:48,  1.35s/step]INFO 2026-07-15 01:42:53 ot_train.py:649 step:1K smpl:77K ep:2K epch:0.35 loss:0.203 grdn:2.252 lr:1.8e-05 updt_s:0.819 data_s:0.553 smp/s:47 mem_gb:39.70
+Training:   2%|▏         | 1400/60000 [32:31<23:02:02,  1.42s/step]INFO 2026-07-15 01:47:31 ot_train.py:649 step:1K smpl:90K ep:2K epch:0.41 loss:0.186 grdn:1.998 lr:2.2e-05 updt_s:0.830 data_s:0.559 smp/s:46 mem_gb:39.70
+Training:   3%|▎         | 1600/60000 [37:09<23:48:13,  1.47s/step]INFO 2026-07-15 01:52:09 ot_train.py:649 step:2K smpl:102K ep:2K epch:0.47 loss:0.173 grdn:1.758 lr:2.5e-05 updt_s:0.827 data_s:0.560 smp/s:46 mem_gb:39.70
+Training:   3%|▎         | 1800/60000 [41:54<22:41:14,  1.40s/step]INFO 2026-07-15 01:56:54 ot_train.py:649 step:2K smpl:115K ep:3K epch:0.53 loss:0.162 grdn:1.516 lr:2.8e-05 updt_s:0.845 data_s:0.576 smp/s:45 mem_gb:39.70
+Training:   3%|▎         | 2000/60000 [47:10<24:14:16,  1.50s/step]INFO 2026-07-15 02:02:10 ot_train.py:649 step:2K smpl:128K ep:3K epch:0.59 loss:0.153 grdn:1.335 lr:3.2e-05 updt_s:0.888 data_s:0.687 smp/s:41 mem_gb:39.70
+Training:   4%|▎         | 2200/60000 [52:28<25:51:23,  1.61s/step]INFO 2026-07-15 02:07:29 ot_train.py:649 step:2K smpl:141K ep:3K epch:0.64 loss:0.147 grdn:1.223 lr:3.5e-05 updt_s:0.876 data_s:0.712 smp/s:40 mem_gb:39.70
+Training:   4%|▍         | 2400/60000 [58:13<26:13:20,  1.64s/step]INFO 2026-07-15 02:13:13 ot_train.py:649 step:2K smpl:154K ep:3K epch:0.70 loss:0.142 grdn:1.103 lr:3.8e-05 updt_s:0.979 data_s:0.739 smp/s:37 mem_gb:39.69
+Training:   4%|▍         | 2600/60000 [1:03:48<27:05:30,  1.70s/step]INFO 2026-07-15 02:18:48 ot_train.py:649 step:3K smpl:166K ep:4K epch:0.76 loss:0.137 grdn:0.987 lr:4.2e-05 updt_s:0.934 data_s:0.737 smp/s:38 mem_gb:39.71
+Training:   5%|▍         | 2800/60000 [1:09:24<25:28:19,  1.60s/step]INFO 2026-07-15 02:24:25 ot_train.py:649 step:3K smpl:179K ep:4K epch:0.82 loss:0.132 grdn:0.912 lr:4.5e-05 updt_s:0.924 data_s:0.754 smp/s:38 mem_gb:39.71
+Training:   5%|▌         | 3000/60000 [1:15:00<26:15:36,  1.66s/step]INFO 2026-07-15 02:30:01 ot_train.py:649 step:3K smpl:192K ep:4K epch:0.88 loss:0.125 grdn:0.805 lr:4.8e-05 updt_s:0.899 data_s:0.775 smp/s:38 mem_gb:39.71
+Training:   5%|▌         | 3200/60000 [1:20:37<26:17:44,  1.67s/step]INFO 2026-07-15 02:35:37 ot_train.py:649 step:3K smpl:205K ep:5K epch:0.94 loss:0.123 grdn:0.761 lr:5.2e-05 updt_s:0.905 data_s:0.774 smp/s:38 mem_gb:39.71
+Training:   6%|▌         | 3400/60000 [1:26:11<26:45:18,  1.70s/step]INFO 2026-07-15 02:41:12 ot_train.py:649 step:3K smpl:218K ep:5K epch:1.00 loss:0.117 grdn:0.685 lr:5.5e-05 updt_s:0.905 data_s:0.762 smp/s:38 mem_gb:39.71
+Training:   6%|▌         | 3600/60000 [1:31:55<26:20:28,  1.68s/step]INFO 2026-07-15 02:46:55 ot_train.py:649 step:4K smpl:230K ep:5K epch:1.06 loss:0.113 grdn:0.646 lr:5.8e-05 updt_s:0.946 data_s:0.766 smp/s:37 mem_gb:39.71
+Training:   6%|▋         | 3800/60000 [1:37:31<25:29:57,  1.63s/step]INFO 2026-07-15 02:52:31 ot_train.py:649 step:4K smpl:243K ep:5K epch:1.11 loss:0.110 grdn:0.636 lr:6.2e-05 updt_s:0.903 data_s:0.773 smp/s:38 mem_gb:39.71
+Training:   7%|▋         | 4000/60000 [1:43:11<25:54:37,  1.67s/step]INFO 2026-07-15 02:58:11 ot_train.py:649 step:4K smpl:256K ep:6K epch:1.17 loss:0.109 grdn:0.590 lr:6.5e-05 updt_s:0.918 data_s:0.777 smp/s:38 mem_gb:39.71
+Training:   7%|▋         | 4200/60000 [1:48:54<26:11:55,  1.69s/step]INFO 2026-07-15 03:03:54 ot_train.py:649 step:4K smpl:269K ep:6K epch:1.23 loss:0.107 grdn:0.556 lr:6.8e-05 updt_s:0.924 data_s:0.785 smp/s:37 mem_gb:39.71
+Training:   7%|▋         | 4400/60000 [1:54:30<26:10:52,  1.70s/step]INFO 2026-07-15 03:09:31 ot_train.py:649 step:4K smpl:282K ep:6K epch:1.29 loss:0.105 grdn:0.524 lr:7.2e-05 updt_s:0.892 data_s:0.786 smp/s:38 mem_gb:39.71
+Training:   8%|▊         | 4600/60000 [2:00:05<25:36:21,  1.66s/step]INFO 2026-07-15 03:15:06 ot_train.py:649 step:5K smpl:294K ep:7K epch:1.35 loss:0.102 grdn:0.504 lr:7.5e-05 updt_s:0.878 data_s:0.791 smp/s:38 mem_gb:39.70
+Training:   8%|▊         | 4800/60000 [2:05:40<24:32:38,  1.60s/step]INFO 2026-07-15 03:20:41 ot_train.py:649 step:5K smpl:307K ep:7K epch:1.41 loss:0.102 grdn:0.516 lr:7.8e-05 updt_s:0.906 data_s:0.765 smp/s:38 mem_gb:39.71
+Training:   8%|▊         | 5000/60000 [2:11:18<26:55:04,  1.76s/step]INFO 2026-07-15 03:26:18 ot_train.py:649 step:5K smpl:320K ep:7K epch:1.47 loss:0.101 grdn:0.469 lr:8.2e-05 updt_s:0.899 data_s:0.783 smp/s:38 mem_gb:39.71
+Training:   9%|▊         | 5200/60000 [2:16:54<24:51:25,  1.63s/step]INFO 2026-07-15 03:31:55 ot_train.py:649 step:5K smpl:333K ep:8K epch:1.52 loss:0.103 grdn:0.472 lr:8.5e-05 updt_s:0.886 data_s:0.793 smp/s:38 mem_gb:39.71
+Training:   9%|▉         | 5400/60000 [2:22:32<25:31:34,  1.68s/step]INFO 2026-07-15 03:37:33 ot_train.py:649 step:5K smpl:346K ep:8K epch:1.58 loss:0.098 grdn:0.447 lr:8.8e-05 updt_s:0.899 data_s:0.786 smp/s:38 mem_gb:39.71
+Training:   9%|▉         | 5600/60000 [2:28:08<25:11:56,  1.67s/step]INFO 2026-07-15 03:43:08 ot_train.py:649 step:6K smpl:358K ep:8K epch:1.64 loss:0.096 grdn:0.432 lr:9.2e-05 updt_s:0.886 data_s:0.789 smp/s:38 mem_gb:39.71
+Training:  10%|▉         | 5800/60000 [2:33:44<25:01:13,  1.66s/step]INFO 2026-07-15 03:48:44 ot_train.py:649 step:6K smpl:371K ep:8K epch:1.70 loss:0.094 grdn:0.417 lr:9.5e-05 updt_s:0.888 data_s:0.786 smp/s:38 mem_gb:39.71
+Training:  10%|█         | 6000/60000 [2:39:21<27:26:41,  1.83s/step]INFO 2026-07-15 03:54:21 ot_train.py:649 step:6K smpl:384K ep:9K epch:1.76 loss:0.095 grdn:0.425 lr:9.8e-05 updt_s:0.889 data_s:0.789 smp/s:38 mem_gb:39.71
+INFO 2026-07-15 03:54:21 ot_train.py:103 INSIGHT phase transition: index=1 name=fm_only range=[6000,60000) trainable_params=1620515968
+Training:  10%|█         | 6200/60000 [2:44:57<25:12:11,  1.69s/step]INFO 2026-07-15 03:59:57 ot_train.py:649 step:6K smpl:397K ep:9K epch:1.82 loss:0.095 grdn:0.411 lr:1.0e-04 updt_s:0.898 data_s:0.778 smp/s:38 mem_gb:39.65
+Training:  11%|█         | 6400/60000 [2:50:33<24:49:56,  1.67s/step]INFO 2026-07-15 04:05:33 ot_train.py:649 step:6K smpl:410K ep:9K epch:1.88 loss:0.092 grdn:0.406 lr:1.0e-04 updt_s:0.888 data_s:0.787 smp/s:38 mem_gb:39.65
+Training:  11%|█         | 6600/60000 [2:56:11<24:40:30,  1.66s/step]INFO 2026-07-15 04:11:11 ot_train.py:649 step:7K smpl:422K ep:10K epch:1.93 loss:0.089 grdn:0.369 lr:1.0e-04 updt_s:0.899 data_s:0.785 smp/s:38 mem_gb:39.65
+Training:  11%|█▏        | 6800/60000 [3:01:48<25:13:44,  1.71s/step]INFO 2026-07-15 04:16:49 ot_train.py:649 step:7K smpl:435K ep:10K epch:1.99 loss:0.092 grdn:0.408 lr:1.0e-04 updt_s:0.889 data_s:0.794 smp/s:38 mem_gb:39.63
+Training:  12%|█▏        | 7000/60000 [3:07:23<24:04:04,  1.63s/step]INFO 2026-07-15 04:22:23 ot_train.py:649 step:7K smpl:448K ep:10K epch:2.05 loss:0.091 grdn:0.374 lr:1.0e-04 updt_s:0.889 data_s:0.779 smp/s:38 mem_gb:39.65
+Training:  12%|█▏        | 7200/60000 [3:12:59<24:30:07,  1.67s/step]INFO 2026-07-15 04:27:59 ot_train.py:649 step:7K smpl:461K ep:10K epch:2.11 loss:0.087 grdn:0.365 lr:1.0e-04 updt_s:0.881 data_s:0.793 smp/s:38 mem_gb:39.65
+Training:  12%|█▏        | 7400/60000 [3:18:36<24:22:07,  1.67s/step]INFO 2026-07-15 04:33:36 ot_train.py:649 step:7K smpl:474K ep:11K epch:2.17 loss:0.089 grdn:0.379 lr:1.0e-04 updt_s:0.888 data_s:0.791 smp/s:38 mem_gb:39.65
+Training:  13%|█▎        | 7600/60000 [3:24:13<24:14:16,  1.67s/step]INFO 2026-07-15 04:39:13 ot_train.py:649 step:8K smpl:486K ep:11K epch:2.23 loss:0.088 grdn:0.358 lr:1.0e-04 updt_s:0.891 data_s:0.791 smp/s:38 mem_gb:39.65
+Training:  13%|█▎        | 7800/60000 [3:29:51<27:32:12,  1.90s/step]INFO 2026-07-15 04:44:51 ot_train.py:649 step:8K smpl:499K ep:11K epch:2.29 loss:0.087 grdn:0.362 lr:1.0e-04 updt_s:0.901 data_s:0.782 smp/s:38 mem_gb:39.65
+Training:  13%|█▎        | 8000/60000 [3:35:26<24:11:18,  1.67s/step]INFO 2026-07-15 04:50:27 ot_train.py:649 step:8K smpl:512K ep:12K epch:2.34 loss:0.089 grdn:0.385 lr:1.0e-04 updt_s:0.870 data_s:0.803 smp/s:38 mem_gb:39.65
+Training:  14%|█▎        | 8200/60000 [3:41:06<23:27:19,  1.63s/step]INFO 2026-07-15 04:56:07 ot_train.py:649 step:8K smpl:525K ep:12K epch:2.40 loss:0.086 grdn:0.358 lr:1.0e-04 updt_s:0.909 data_s:0.787 smp/s:38 mem_gb:39.65
+Training:  14%|█▍        | 8400/60000 [3:46:45<24:59:29,  1.74s/step]INFO 2026-07-15 05:01:45 ot_train.py:649 step:8K smpl:538K ep:12K epch:2.46 loss:0.085 grdn:0.354 lr:1.0e-04 updt_s:0.921 data_s:0.767 smp/s:38 mem_gb:39.65
+Training:  14%|█▍        | 8600/60000 [3:52:23<24:03:08,  1.68s/step]INFO 2026-07-15 05:07:24 ot_train.py:649 step:9K smpl:550K ep:12K epch:2.52 loss:0.083 grdn:0.343 lr:9.9e-05 updt_s:0.906 data_s:0.781 smp/s:38 mem_gb:39.65
+Training:  15%|█▍        | 8800/60000 [3:57:58<23:17:35,  1.64s/step]INFO 2026-07-15 05:12:59 ot_train.py:649 step:9K smpl:563K ep:13K epch:2.58 loss:0.084 grdn:0.336 lr:9.9e-05 updt_s:0.905 data_s:0.766 smp/s:38 mem_gb:39.64
+Training:  15%|█▌        | 9000/60000 [4:03:31<21:07:31,  1.49s/step]INFO 2026-07-15 05:18:32 ot_train.py:649 step:9K smpl:576K ep:13K epch:2.64 loss:0.081 grdn:0.331 lr:9.9e-05 updt_s:0.917 data_s:0.743 smp/s:39 mem_gb:39.65
+Training:  15%|█▌        | 9200/60000 [4:09:07<25:20:25,  1.80s/step]INFO 2026-07-15 05:24:07 ot_train.py:649 step:9K smpl:589K ep:13K epch:2.70 loss:0.084 grdn:0.379 lr:9.9e-05 updt_s:0.894 data_s:0.780 smp/s:38 mem_gb:39.63
+Training:  16%|█▌        | 9400/60000 [4:14:39<23:37:47,  1.68s/step]INFO 2026-07-15 05:29:39 ot_train.py:649 step:9K smpl:602K ep:14K epch:2.75 loss:0.086 grdn:0.377 lr:9.9e-05 updt_s:0.887 data_s:0.767 smp/s:39 mem_gb:39.65
+Training:  16%|█▌        | 9600/60000 [4:20:14<23:28:17,  1.68s/step]INFO 2026-07-15 05:35:15 ot_train.py:649 step:10K smpl:614K ep:14K epch:2.81 loss:0.082 grdn:0.334 lr:9.9e-05 updt_s:0.901 data_s:0.773 smp/s:38 mem_gb:39.65
+Training:  16%|█▋        | 9800/60000 [4:25:54<22:54:59,  1.64s/step]INFO 2026-07-15 05:40:55 ot_train.py:649 step:10K smpl:627K ep:14K epch:2.87 loss:0.080 grdn:0.326 lr:9.9e-05 updt_s:0.914 data_s:0.780 smp/s:38 mem_gb:39.65
+Training:  17%|█▋        | 10000/60000 [4:31:31<23:00:39,  1.66s/step]INFO 2026-07-15 05:46:31 ot_train.py:649 step:10K smpl:640K ep:14K epch:2.93 loss:0.077 grdn:0.322 lr:9.9e-05 updt_s:0.909 data_s:0.770 smp/s:38 mem_gb:39.65
+Training:  17%|█▋        | 10200/60000 [4:37:08<24:14:57,  1.75s/step]INFO 2026-07-15 05:52:08 ot_train.py:649 step:10K smpl:653K ep:15K epch:2.99 loss:0.078 grdn:0.321 lr:9.9e-05 updt_s:0.916 data_s:0.763 smp/s:38 mem_gb:39.65
+Training:  17%|█▋        | 10400/60000 [4:42:38<22:46:01,  1.65s/step]INFO 2026-07-15 05:57:38 ot_train.py:649 step:10K smpl:666K ep:15K epch:3.05 loss:0.078 grdn:0.321 lr:9.8e-05 updt_s:0.944 data_s:0.701 smp/s:39 mem_gb:39.65
+Training:  18%|█▊        | 10600/60000 [4:48:10<23:12:41,  1.69s/step]INFO 2026-07-15 06:03:10 ot_train.py:649 step:11K smpl:678K ep:15K epch:3.11 loss:0.078 grdn:0.328 lr:9.8e-05 updt_s:0.915 data_s:0.739 smp/s:39 mem_gb:39.65
+Training:  18%|█▊        | 10800/60000 [4:53:42<22:32:03,  1.65s/step]INFO 2026-07-15 06:08:43 ot_train.py:649 step:11K smpl:691K ep:16K epch:3.17 loss:0.080 grdn:0.335 lr:9.8e-05 updt_s:0.888 data_s:0.771 smp/s:39 mem_gb:39.65
+Training:  18%|█▊        | 11000/60000 [4:59:14<22:51:50,  1.68s/step]INFO 2026-07-15 06:14:15 ot_train.py:649 step:11K smpl:704K ep:16K epch:3.22 loss:0.076 grdn:0.337 lr:9.8e-05 updt_s:0.892 data_s:0.764 smp/s:39 mem_gb:39.65
+Training:  19%|█▊        | 11200/60000 [5:04:53<22:29:22,  1.66s/step]INFO 2026-07-15 06:19:53 ot_train.py:649 step:11K smpl:717K ep:16K epch:3.28 loss:0.076 grdn:0.318 lr:9.8e-05 updt_s:0.913 data_s:0.775 smp/s:38 mem_gb:39.65
+Training:  19%|█▉        | 11400/60000 [5:10:28<22:43:38,  1.68s/step]INFO 2026-07-15 06:25:29 ot_train.py:649 step:11K smpl:730K ep:16K epch:3.34 loss:0.078 grdn:0.324 lr:9.8e-05 updt_s:0.888 data_s:0.782 smp/s:38 mem_gb:39.63
+Training:  19%|█▉        | 11600/60000 [5:15:58<21:21:23,  1.59s/step]INFO 2026-07-15 06:30:59 ot_train.py:649 step:12K smpl:742K ep:17K epch:3.40 loss:0.075 grdn:0.322 lr:9.7e-05 updt_s:0.947 data_s:0.700 smp/s:39 mem_gb:39.65
+Training:  20%|█▉        | 11800/60000 [5:21:14<21:16:14,  1.59s/step]INFO 2026-07-15 06:36:15 ot_train.py:649 step:12K smpl:755K ep:17K epch:3.46 loss:0.077 grdn:0.333 lr:9.7e-05 updt_s:0.986 data_s:0.588 smp/s:41 mem_gb:39.65
+Training:  20%|██        | 12000/60000 [5:26:27<21:17:46,  1.60s/step]INFO 2026-07-15 06:41:28 ot_train.py:649 step:12K smpl:768K ep:17K epch:3.52 loss:0.074 grdn:0.329 lr:9.7e-05 updt_s:0.982 data_s:0.580 smp/s:41 mem_gb:39.65
+Training:  20%|██        | 12200/60000 [5:31:39<19:50:46,  1.49s/step]INFO 2026-07-15 06:46:39 ot_train.py:649 step:12K smpl:781K ep:18K epch:3.58 loss:0.075 grdn:0.330 lr:9.7e-05 updt_s:0.974 data_s:0.578 smp/s:41 mem_gb:39.65
+Training:  21%|██        | 12400/60000 [5:36:48<19:14:09,  1.45s/step]INFO 2026-07-15 06:51:49 ot_train.py:649 step:12K smpl:794K ep:18K epch:3.63 loss:0.074 grdn:0.313 lr:9.7e-05 updt_s:0.963 data_s:0.581 smp/s:41 mem_gb:39.65
+Training:  21%|██        | 12600/60000 [5:41:57<18:45:17,  1.42s/step]INFO 2026-07-15 06:56:58 ot_train.py:649 step:13K smpl:806K ep:18K epch:3.69 loss:0.074 grdn:0.307 lr:9.6e-05 updt_s:0.954 data_s:0.585 smp/s:42 mem_gb:39.65
+Training:  21%|██▏       | 12800/60000 [5:47:06<20:03:30,  1.53s/step]INFO 2026-07-15 07:02:07 ot_train.py:649 step:13K smpl:819K ep:18K epch:3.75 loss:0.074 grdn:0.307 lr:9.6e-05 updt_s:0.958 data_s:0.582 smp/s:42 mem_gb:39.65
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+Training:  28%|██▊       | 16800/60000 [7:37:16<19:40:27,  1.64s/step]INFO 2026-07-15 08:52:16 ot_train.py:649 step:17K smpl:1M ep:24K epch:4.92 loss:0.067 grdn:0.299 lr:9.1e-05 updt_s:0.888 data_s:0.789 smp/s:38 mem_gb:39.65
+Training:  28%|██▊       | 17000/60000 [7:42:50<20:17:43,  1.70s/step]INFO 2026-07-15 08:57:51 ot_train.py:649 step:17K smpl:1M ep:25K epch:4.98 loss:0.065 grdn:0.289 lr:9.0e-05 updt_s:0.877 data_s:0.791 smp/s:38 mem_gb:39.65
+Training:  29%|██▊       | 17200/60000 [7:48:25<20:13:04,  1.70s/step]INFO 2026-07-15 09:03:26 ot_train.py:649 step:17K smpl:1M ep:25K epch:5.04 loss:0.065 grdn:0.287 lr:9.0e-05 updt_s:0.886 data_s:0.784 smp/s:38 mem_gb:39.65
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+Training:  35%|███▌      | 21000/60000 [9:23:20<14:31:23,  1.34s/step]INFO 2026-07-15 10:38:21 ot_train.py:649 step:21K smpl:1M ep:30K epch:6.15 loss:0.060 grdn:0.282 lr:8.2e-05 updt_s:0.807 data_s:0.537 smp/s:48 mem_gb:39.65
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+Training:  40%|████      | 24000/60000 [10:31:40<13:22:50,  1.34s/step]INFO 2026-07-15 11:46:40 ot_train.py:649 step:24K smpl:2M ep:35K epch:7.03 loss:0.056 grdn:0.278 lr:7.5e-05 updt_s:0.815 data_s:0.612 smp/s:45 mem_gb:39.65
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+Training:  41%|████      | 24600/60000 [10:45:18<13:12:07,  1.34s/step]INFO 2026-07-15 12:00:18 ot_train.py:649 step:25K smpl:2M ep:36K epch:7.21 loss:0.056 grdn:0.262 lr:7.4e-05 updt_s:0.799 data_s:0.546 smp/s:48 mem_gb:39.65
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+Training:  47%|████▋     | 28000/60000 [12:02:55<12:06:08,  1.36s/step]INFO 2026-07-15 13:17:56 ot_train.py:649 step:28K smpl:2M ep:40K epch:8.21 loss:0.051 grdn:0.277 lr:6.5e-05 updt_s:0.799 data_s:0.545 smp/s:48 mem_gb:39.65
+Training:  47%|████▋     | 28200/60000 [12:07:29<12:42:52,  1.44s/step]INFO 2026-07-15 13:22:30 ot_train.py:649 step:28K smpl:2M ep:41K epch:8.26 loss:0.051 grdn:0.272 lr:6.4e-05 updt_s:0.818 data_s:0.547 smp/s:47 mem_gb:39.65
+Training:  47%|████▋     | 28400/60000 [12:11:59<11:39:53,  1.33s/step]INFO 2026-07-15 13:26:59 ot_train.py:649 step:28K smpl:2M ep:41K epch:8.32 loss:0.050 grdn:0.263 lr:6.4e-05 updt_s:0.806 data_s:0.539 smp/s:48 mem_gb:39.65
+Training:  48%|████▊     | 28600/60000 [12:16:37<12:36:49,  1.45s/step]INFO 2026-07-15 13:31:37 ot_train.py:649 step:29K smpl:2M ep:41K epch:8.38 loss:0.051 grdn:0.258 lr:6.3e-05 updt_s:0.826 data_s:0.560 smp/s:46 mem_gb:39.65
+Training:  48%|████▊     | 28800/60000 [12:21:42<13:28:51,  1.56s/step]INFO 2026-07-15 13:36:42 ot_train.py:649 step:29K smpl:2M ep:42K epch:8.44 loss:0.050 grdn:0.272 lr:6.2e-05 updt_s:0.866 data_s:0.655 smp/s:42 mem_gb:39.65
+Training:  48%|████▊     | 29000/60000 [12:27:13<13:55:32,  1.62s/step]INFO 2026-07-15 13:42:13 ot_train.py:649 step:29K smpl:2M ep:42K epch:8.50 loss:0.050 grdn:0.275 lr:6.2e-05 updt_s:0.916 data_s:0.731 smp/s:39 mem_gb:39.65
+Training:  49%|████▊     | 29200/60000 [12:32:43<12:22:14,  1.45s/step]INFO 2026-07-15 13:47:43 ot_train.py:649 step:29K smpl:2M ep:42K epch:8.56 loss:0.050 grdn:0.274 lr:6.1e-05 updt_s:0.876 data_s:0.768 smp/s:39 mem_gb:39.65
+Training:  49%|████▉     | 29400/60000 [12:37:22<11:17:56,  1.33s/step]INFO 2026-07-15 13:52:23 ot_train.py:649 step:29K smpl:2M ep:42K epch:8.62 loss:0.050 grdn:0.279 lr:6.1e-05 updt_s:0.806 data_s:0.588 smp/s:46 mem_gb:39.63
+Training:  49%|████▉     | 29600/60000 [12:41:52<11:13:16,  1.33s/step]INFO 2026-07-15 13:56:53 ot_train.py:649 step:30K smpl:2M ep:43K epch:8.68 loss:0.050 grdn:0.275 lr:6.0e-05 updt_s:0.809 data_s:0.537 smp/s:48 mem_gb:39.65
+Training:  50%|████▉     | 29800/60000 [12:46:20<11:19:38,  1.35s/step]INFO 2026-07-15 14:01:20 ot_train.py:649 step:30K smpl:2M ep:43K epch:8.73 loss:0.048 grdn:0.273 lr:6.0e-05 updt_s:0.801 data_s:0.533 smp/s:48 mem_gb:39.65
+Training:  50%|█████     | 30000/60000 [12:50:49<12:15:53,  1.47s/step]INFO 2026-07-15 14:05:49 ot_train.py:649 step:30K smpl:2M ep:43K epch:8.79 loss:0.048 grdn:0.270 lr:5.9e-05 updt_s:0.806 data_s:0.535 smp/s:48 mem_gb:39.65
+Training:  50%|█████     | 30200/60000 [12:55:22<11:56:13,  1.44s/step]INFO 2026-07-15 14:10:22 ot_train.py:649 step:30K smpl:2M ep:44K epch:8.85 loss:0.048 grdn:0.273 lr:5.8e-05 updt_s:0.811 data_s:0.551 smp/s:47 mem_gb:39.65
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+Training:  51%|█████     | 30600/60000 [13:05:08<11:42:33,  1.43s/step]INFO 2026-07-15 14:20:08 ot_train.py:649 step:31K smpl:2M ep:44K epch:8.97 loss:0.047 grdn:0.260 lr:5.7e-05 updt_s:0.897 data_s:0.630 smp/s:42 mem_gb:39.65
+Training:  51%|█████▏    | 30800/60000 [13:10:31<12:57:37,  1.60s/step]INFO 2026-07-15 14:25:31 ot_train.py:649 step:31K smpl:2M ep:45K epch:9.03 loss:0.047 grdn:0.273 lr:5.7e-05 updt_s:0.909 data_s:0.702 smp/s:40 mem_gb:39.65
+Training:  52%|█████▏    | 31000/60000 [13:15:59<13:18:56,  1.65s/step]INFO 2026-07-15 14:30:59 ot_train.py:649 step:31K smpl:2M ep:45K epch:9.09 loss:0.047 grdn:0.264 lr:5.6e-05 updt_s:0.909 data_s:0.726 smp/s:39 mem_gb:39.65
+Training:  52%|█████▏    | 31200/60000 [13:21:20<11:55:33,  1.49s/step]INFO 2026-07-15 14:36:21 ot_train.py:649 step:31K smpl:2M ep:45K epch:9.14 loss:0.046 grdn:0.265 lr:5.6e-05 updt_s:0.901 data_s:0.704 smp/s:40 mem_gb:39.65
+Training:  52%|█████▏    | 31400/60000 [13:26:38<12:25:35,  1.56s/step]INFO 2026-07-15 14:41:38 ot_train.py:649 step:31K smpl:2M ep:45K epch:9.20 loss:0.049 grdn:0.291 lr:5.5e-05 updt_s:0.927 data_s:0.656 smp/s:40 mem_gb:39.65
+Training:  53%|█████▎    | 31600/60000 [13:32:05<15:29:36,  1.96s/step]INFO 2026-07-15 14:47:06 ot_train.py:649 step:32K smpl:2M ep:46K epch:9.26 loss:0.048 grdn:0.272 lr:5.4e-05 updt_s:0.893 data_s:0.739 smp/s:39 mem_gb:39.63
+Training:  53%|█████▎    | 31800/60000 [13:37:36<12:42:22,  1.62s/step]INFO 2026-07-15 14:52:36 ot_train.py:649 step:32K smpl:2M ep:46K epch:9.32 loss:0.045 grdn:0.267 lr:5.4e-05 updt_s:0.886 data_s:0.761 smp/s:39 mem_gb:39.65
+Training:  53%|█████▎    | 32000/60000 [13:43:08<12:59:36,  1.67s/step]INFO 2026-07-15 14:58:09 ot_train.py:649 step:32K smpl:2M ep:46K epch:9.38 loss:0.045 grdn:0.264 lr:5.3e-05 updt_s:0.891 data_s:0.769 smp/s:39 mem_gb:39.65
+Training:  54%|█████▎    | 32200/60000 [13:48:42<12:49:20,  1.66s/step]INFO 2026-07-15 15:03:42 ot_train.py:649 step:32K smpl:2M ep:47K epch:9.44 loss:0.045 grdn:0.266 lr:5.3e-05 updt_s:0.894 data_s:0.767 smp/s:39 mem_gb:39.65
+Training:  54%|█████▍    | 32400/60000 [13:54:14<13:26:32,  1.75s/step]INFO 2026-07-15 15:09:15 ot_train.py:649 step:32K smpl:2M ep:47K epch:9.50 loss:0.045 grdn:0.270 lr:5.2e-05 updt_s:0.886 data_s:0.771 smp/s:39 mem_gb:39.65
+Training:  54%|█████▍    | 32600/60000 [13:59:44<12:05:42,  1.59s/step]INFO 2026-07-15 15:14:44 ot_train.py:649 step:33K smpl:2M ep:47K epch:9.55 loss:0.045 grdn:0.264 lr:5.1e-05 updt_s:0.891 data_s:0.753 smp/s:39 mem_gb:39.65
+Training:  55%|█████▍    | 32800/60000 [14:05:16<13:15:31,  1.75s/step]INFO 2026-07-15 15:20:16 ot_train.py:649 step:33K smpl:2M ep:47K epch:9.61 loss:0.046 grdn:0.276 lr:5.1e-05 updt_s:0.907 data_s:0.747 smp/s:39 mem_gb:39.65
+Training:  55%|█████▌    | 33000/60000 [14:10:46<12:09:18,  1.62s/step]INFO 2026-07-15 15:25:47 ot_train.py:649 step:33K smpl:2M ep:48K epch:9.67 loss:0.045 grdn:0.270 lr:5.0e-05 updt_s:0.884 data_s:0.765 smp/s:39 mem_gb:39.65
+Training:  55%|█████▌    | 33200/60000 [14:16:19<12:15:16,  1.65s/step]INFO 2026-07-15 15:31:19 ot_train.py:649 step:33K smpl:2M ep:48K epch:9.73 loss:0.044 grdn:0.268 lr:5.0e-05 updt_s:0.901 data_s:0.755 smp/s:39 mem_gb:39.65
+Training:  56%|█████▌    | 33400/60000 [14:21:47<12:15:57,  1.66s/step]INFO 2026-07-15 15:36:48 ot_train.py:649 step:33K smpl:2M ep:48K epch:9.79 loss:0.044 grdn:0.268 lr:4.9e-05 updt_s:0.895 data_s:0.744 smp/s:39 mem_gb:39.65
+Training:  56%|█████▌    | 33600/60000 [14:27:19<12:05:29,  1.65s/step]INFO 2026-07-15 15:42:19 ot_train.py:649 step:34K smpl:2M ep:49K epch:9.85 loss:0.045 grdn:0.280 lr:4.9e-05 updt_s:0.897 data_s:0.756 smp/s:39 mem_gb:39.65
+Training:  56%|█████▋    | 33800/60000 [14:32:50<11:58:31,  1.65s/step]INFO 2026-07-15 15:47:51 ot_train.py:649 step:34K smpl:2M ep:49K epch:9.91 loss:0.045 grdn:0.267 lr:4.8e-05 updt_s:0.900 data_s:0.751 smp/s:39 mem_gb:39.65
+Training:  57%|█████▋    | 34000/60000 [14:38:20<11:58:31,  1.66s/step]INFO 2026-07-15 15:53:21 ot_train.py:649 step:34K smpl:2M ep:49K epch:9.96 loss:0.043 grdn:0.264 lr:4.7e-05 updt_s:0.891 data_s:0.754 smp/s:39 mem_gb:39.63
+Training:  57%|█████▋    | 34200/60000 [14:43:50<11:59:06,  1.67s/step]INFO 2026-07-15 15:58:50 ot_train.py:649 step:34K smpl:2M ep:49K epch:10.02 loss:0.042 grdn:0.266 lr:4.7e-05 updt_s:0.885 data_s:0.757 smp/s:39 mem_gb:39.65
+Training:  57%|█████▋    | 34400/60000 [14:49:21<12:00:19,  1.69s/step]INFO 2026-07-15 16:04:21 ot_train.py:649 step:34K smpl:2M ep:50K epch:10.08 loss:0.042 grdn:0.275 lr:4.6e-05 updt_s:0.918 data_s:0.733 smp/s:39 mem_gb:39.65
+Training:  58%|█████▊    | 34600/60000 [14:54:50<11:54:54,  1.69s/step]INFO 2026-07-15 16:09:50 ot_train.py:649 step:35K smpl:2M ep:50K epch:10.14 loss:0.041 grdn:0.258 lr:4.6e-05 updt_s:0.874 data_s:0.766 smp/s:39 mem_gb:39.65
+Training:  58%|█████▊    | 34800/60000 [15:00:22<11:38:48,  1.66s/step]INFO 2026-07-15 16:15:22 ot_train.py:649 step:35K smpl:2M ep:50K epch:10.20 loss:0.042 grdn:0.265 lr:4.5e-05 updt_s:0.899 data_s:0.756 smp/s:39 mem_gb:39.65
+Training:  58%|█████▊    | 35000/60000 [15:05:53<12:08:58,  1.75s/step]INFO 2026-07-15 16:20:53 ot_train.py:649 step:35K smpl:2M ep:51K epch:10.26 loss:0.042 grdn:0.270 lr:4.4e-05 updt_s:0.883 data_s:0.765 smp/s:39 mem_gb:39.65
+Training:  59%|█████▊    | 35200/60000 [15:11:27<11:40:05,  1.69s/step]INFO 2026-07-15 16:26:27 ot_train.py:649 step:35K smpl:2M ep:51K epch:10.32 loss:0.043 grdn:0.288 lr:4.4e-05 updt_s:0.879 data_s:0.788 smp/s:38 mem_gb:39.65
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+Training:  59%|█████▉    | 35600/60000 [15:22:37<10:43:46,  1.58s/step]INFO 2026-07-15 16:37:37 ot_train.py:649 step:36K smpl:2M ep:51K epch:10.43 loss:0.041 grdn:0.269 lr:4.3e-05 updt_s:0.899 data_s:0.759 smp/s:39 mem_gb:39.65
+Training:  60%|█████▉    | 35800/60000 [15:28:05<11:01:21,  1.64s/step]INFO 2026-07-15 16:43:05 ot_train.py:649 step:36K smpl:2M ep:52K epch:10.49 loss:0.041 grdn:0.279 lr:4.2e-05 updt_s:0.901 data_s:0.734 smp/s:39 mem_gb:39.65
+Training:  60%|██████    | 36000/60000 [15:33:36<10:51:07,  1.63s/step]INFO 2026-07-15 16:48:36 ot_train.py:649 step:36K smpl:2M ep:52K epch:10.55 loss:0.041 grdn:0.275 lr:4.2e-05 updt_s:0.914 data_s:0.735 smp/s:39 mem_gb:39.65
+Training:  60%|██████    | 36200/60000 [15:39:07<11:01:45,  1.67s/step]INFO 2026-07-15 16:54:07 ot_train.py:649 step:36K smpl:2M ep:52K epch:10.61 loss:0.040 grdn:0.273 lr:4.1e-05 updt_s:0.909 data_s:0.741 smp/s:39 mem_gb:39.63
+Training:  61%|██████    | 36400/60000 [15:44:43<11:13:28,  1.71s/step]INFO 2026-07-15 16:59:43 ot_train.py:649 step:36K smpl:2M ep:53K epch:10.67 loss:0.040 grdn:0.275 lr:4.0e-05 updt_s:0.932 data_s:0.742 smp/s:38 mem_gb:39.65
+Training:  61%|██████    | 36600/60000 [15:50:14<10:52:18,  1.67s/step]INFO 2026-07-15 17:05:14 ot_train.py:649 step:37K smpl:2M ep:53K epch:10.73 loss:0.039 grdn:0.279 lr:4.0e-05 updt_s:0.921 data_s:0.729 smp/s:39 mem_gb:39.65
+Training:  61%|██████▏   | 36800/60000 [15:55:53<10:54:37,  1.69s/step]INFO 2026-07-15 17:10:53 ot_train.py:649 step:37K smpl:2M ep:53K epch:10.79 loss:0.038 grdn:0.275 lr:3.9e-05 updt_s:0.927 data_s:0.763 smp/s:38 mem_gb:39.65
+Training:  62%|██████▏   | 37000/60000 [16:01:20<9:57:23,  1.56s/step] INFO 2026-07-15 17:16:21 ot_train.py:649 step:37K smpl:2M ep:53K epch:10.84 loss:0.038 grdn:0.273 lr:3.9e-05 updt_s:0.864 data_s:0.768 smp/s:39 mem_gb:39.65
+Training:  62%|██████▏   | 37200/60000 [16:06:54<10:18:29,  1.63s/step]INFO 2026-07-15 17:21:55 ot_train.py:649 step:37K smpl:2M ep:54K epch:10.90 loss:0.039 grdn:0.273 lr:3.8e-05 updt_s:0.906 data_s:0.760 smp/s:38 mem_gb:39.65
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+Training:  65%|██████▌   | 39000/60000 [16:56:47<8:56:40,  1.53s/step]INFO 2026-07-15 18:11:47 ot_train.py:649 step:39K smpl:2M ep:56K epch:11.43 loss:0.036 grdn:0.277 lr:3.3e-05 updt_s:0.893 data_s:0.763 smp/s:39 mem_gb:39.65
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+Training:  67%|██████▋   | 40400/60000 [17:35:22<8:29:03,  1.56s/step]INFO 2026-07-15 18:50:22 ot_train.py:649 step:40K smpl:3M ep:58K epch:11.84 loss:0.035 grdn:0.289 lr:2.9e-05 updt_s:0.883 data_s:0.762 smp/s:39 mem_gb:39.65
+Training:  68%|██████▊   | 40600/60000 [17:40:51<8:55:50,  1.66s/step]INFO 2026-07-15 18:55:52 ot_train.py:649 step:41K smpl:3M ep:59K epch:11.90 loss:0.036 grdn:0.274 lr:2.9e-05 updt_s:0.880 data_s:0.762 smp/s:39 mem_gb:39.65
+Training:  68%|██████▊   | 40800/60000 [17:46:23<8:22:22,  1.57s/step]INFO 2026-07-15 19:01:23 ot_train.py:649 step:41K smpl:3M ep:59K epch:11.96 loss:0.033 grdn:0.284 lr:2.8e-05 updt_s:0.875 data_s:0.779 smp/s:39 mem_gb:39.63
+Training:  68%|██████▊   | 41000/60000 [17:51:55<8:46:14,  1.66s/step]INFO 2026-07-15 19:06:56 ot_train.py:649 step:41K smpl:3M ep:59K epch:12.02 loss:0.033 grdn:0.279 lr:2.8e-05 updt_s:0.884 data_s:0.773 smp/s:39 mem_gb:39.65
+Training:  69%|██████▊   | 41200/60000 [17:57:29<8:53:16,  1.70s/step]INFO 2026-07-15 19:12:30 ot_train.py:649 step:41K smpl:3M ep:60K epch:12.08 loss:0.033 grdn:0.283 lr:2.7e-05 updt_s:0.890 data_s:0.774 smp/s:38 mem_gb:39.65
+Training:  69%|██████▉   | 41400/60000 [18:03:04<8:42:38,  1.69s/step]INFO 2026-07-15 19:18:04 ot_train.py:649 step:41K smpl:3M ep:60K epch:12.13 loss:0.033 grdn:0.283 lr:2.7e-05 updt_s:0.889 data_s:0.779 smp/s:38 mem_gb:39.65
+Training:  69%|██████▉   | 41600/60000 [18:08:39<9:24:26,  1.84s/step]INFO 2026-07-15 19:23:40 ot_train.py:649 step:42K smpl:3M ep:60K epch:12.19 loss:0.033 grdn:0.278 lr:2.6e-05 updt_s:0.894 data_s:0.780 smp/s:38 mem_gb:39.65
+Training:  70%|██████▉   | 41800/60000 [18:14:12<8:32:23,  1.69s/step]INFO 2026-07-15 19:29:12 ot_train.py:649 step:42K smpl:3M ep:60K epch:12.25 loss:0.033 grdn:0.281 lr:2.6e-05 updt_s:0.868 data_s:0.790 smp/s:39 mem_gb:39.65
+Training:  70%|███████   | 42000/60000 [18:19:51<8:13:53,  1.65s/step]INFO 2026-07-15 19:34:51 ot_train.py:649 step:42K smpl:3M ep:61K epch:12.31 loss:0.033 grdn:0.281 lr:2.5e-05 updt_s:0.895 data_s:0.795 smp/s:38 mem_gb:39.65
+Training:  70%|███████   | 42200/60000 [18:25:24<9:48:29,  1.98s/step]INFO 2026-07-15 19:40:24 ot_train.py:649 step:42K smpl:3M ep:61K epch:12.37 loss:0.033 grdn:0.273 lr:2.5e-05 updt_s:0.910 data_s:0.748 smp/s:39 mem_gb:39.65
+Training:  71%|███████   | 42400/60000 [18:31:00<8:14:29,  1.69s/step]INFO 2026-07-15 19:46:00 ot_train.py:649 step:42K smpl:3M ep:61K epch:12.43 loss:0.033 grdn:0.287 lr:2.4e-05 updt_s:0.908 data_s:0.768 smp/s:38 mem_gb:39.65
+Training:  71%|███████   | 42600/60000 [18:36:31<8:07:33,  1.68s/step]INFO 2026-07-15 19:51:32 ot_train.py:649 step:43K smpl:3M ep:62K epch:12.49 loss:0.033 grdn:0.275 lr:2.4e-05 updt_s:0.865 data_s:0.787 smp/s:39 mem_gb:39.65
+Training:  71%|███████▏  | 42800/60000 [18:42:03<8:02:53,  1.68s/step]INFO 2026-07-15 19:57:03 ot_train.py:649 step:43K smpl:3M ep:62K epch:12.54 loss:0.032 grdn:0.283 lr:2.3e-05 updt_s:0.873 data_s:0.779 smp/s:39 mem_gb:39.65
+Training:  72%|███████▏  | 43000/60000 [18:47:39<8:03:43,  1.71s/step]INFO 2026-07-15 20:02:39 ot_train.py:649 step:43K smpl:3M ep:62K epch:12.60 loss:0.031 grdn:0.270 lr:2.3e-05 updt_s:0.908 data_s:0.768 smp/s:38 mem_gb:39.63
+Training:  72%|███████▏  | 43200/60000 [18:53:13<7:30:45,  1.61s/step]INFO 2026-07-15 20:08:13 ot_train.py:649 step:43K smpl:3M ep:62K epch:12.66 loss:0.030 grdn:0.276 lr:2.2e-05 updt_s:0.894 data_s:0.770 smp/s:38 mem_gb:39.65
+Training:  72%|███████▏  | 43400/60000 [18:58:43<7:25:35,  1.61s/step]INFO 2026-07-15 20:13:43 ot_train.py:649 step:43K smpl:3M ep:63K epch:12.72 loss:0.031 grdn:0.273 lr:2.2e-05 updt_s:0.897 data_s:0.748 smp/s:39 mem_gb:39.65
+Training:  73%|███████▎  | 43600/60000 [19:04:15<7:41:36,  1.69s/step]INFO 2026-07-15 20:19:15 ot_train.py:649 step:44K smpl:3M ep:63K epch:12.78 loss:0.030 grdn:0.278 lr:2.1e-05 updt_s:0.888 data_s:0.769 smp/s:39 mem_gb:39.65
+Training:  73%|███████▎  | 43800/60000 [19:09:46<7:19:43,  1.63s/step]INFO 2026-07-15 20:24:46 ot_train.py:649 step:44K smpl:3M ep:63K epch:12.84 loss:0.030 grdn:0.286 lr:2.1e-05 updt_s:0.880 data_s:0.769 smp/s:39 mem_gb:39.65
+Training:  73%|███████▎  | 44000/60000 [19:15:19<7:19:15,  1.65s/step]INFO 2026-07-15 20:30:20 ot_train.py:649 step:44K smpl:3M ep:64K epch:12.90 loss:0.030 grdn:0.279 lr:2.0e-05 updt_s:0.872 data_s:0.791 smp/s:38 mem_gb:39.65
+Training:  74%|███████▎  | 44200/60000 [19:20:53<7:13:49,  1.65s/step]INFO 2026-07-15 20:35:53 ot_train.py:649 step:44K smpl:3M ep:64K epch:12.95 loss:0.030 grdn:0.272 lr:2.0e-05 updt_s:0.888 data_s:0.777 smp/s:38 mem_gb:39.65
+Training:  74%|███████▍  | 44400/60000 [19:26:25<7:15:33,  1.68s/step]INFO 2026-07-15 20:41:26 ot_train.py:649 step:44K smpl:3M ep:64K epch:13.01 loss:0.030 grdn:0.284 lr:1.9e-05 updt_s:0.887 data_s:0.770 smp/s:39 mem_gb:39.65
+Training:  74%|███████▍  | 44600/60000 [19:31:57<7:00:20,  1.64s/step]INFO 2026-07-15 20:46:57 ot_train.py:649 step:45K smpl:3M ep:64K epch:13.07 loss:0.029 grdn:0.275 lr:1.9e-05 updt_s:0.872 data_s:0.780 smp/s:39 mem_gb:39.65
+Training:  75%|███████▍  | 44800/60000 [19:37:28<6:54:07,  1.63s/step]INFO 2026-07-15 20:52:28 ot_train.py:649 step:45K smpl:3M ep:65K epch:13.13 loss:0.029 grdn:0.265 lr:1.9e-05 updt_s:0.864 data_s:0.786 smp/s:39 mem_gb:39.65
+Training:  75%|███████▌  | 45000/60000 [19:43:01<6:48:42,  1.63s/step]INFO 2026-07-15 20:58:01 ot_train.py:649 step:45K smpl:3M ep:65K epch:13.19 loss:0.030 grdn:0.279 lr:1.8e-05 updt_s:0.884 data_s:0.777 smp/s:39 mem_gb:39.65
+Training:  75%|███████▌  | 45200/60000 [19:48:32<6:52:14,  1.67s/step]INFO 2026-07-15 21:03:33 ot_train.py:649 step:45K smpl:3M ep:65K epch:13.25 loss:0.029 grdn:0.269 lr:1.8e-05 updt_s:0.857 data_s:0.793 smp/s:39 mem_gb:39.63
+Training:  76%|███████▌  | 45400/60000 [19:54:04<6:52:36,  1.70s/step]INFO 2026-07-15 21:09:04 ot_train.py:649 step:45K smpl:3M ep:66K epch:13.31 loss:0.029 grdn:0.282 lr:1.7e-05 updt_s:0.874 data_s:0.779 smp/s:39 mem_gb:39.65
+Training:  76%|███████▌  | 45600/60000 [19:59:37<6:44:32,  1.69s/step]INFO 2026-07-15 21:14:37 ot_train.py:649 step:46K smpl:3M ep:66K epch:13.36 loss:0.028 grdn:0.273 lr:1.7e-05 updt_s:0.885 data_s:0.775 smp/s:39 mem_gb:39.65
+Training:  76%|███████▋  | 45800/60000 [20:05:10<6:27:43,  1.64s/step]INFO 2026-07-15 21:20:10 ot_train.py:649 step:46K smpl:3M ep:66K epch:13.42 loss:0.028 grdn:0.280 lr:1.6e-05 updt_s:0.872 data_s:0.790 smp/s:39 mem_gb:39.65
+Training:  77%|███████▋  | 46000/60000 [20:10:40<6:30:17,  1.67s/step]INFO 2026-07-15 21:25:41 ot_train.py:649 step:46K smpl:3M ep:66K epch:13.48 loss:0.027 grdn:0.278 lr:1.6e-05 updt_s:0.871 data_s:0.775 smp/s:39 mem_gb:39.65
+Training:  77%|███████▋  | 46200/60000 [20:16:12<6:14:10,  1.63s/step]INFO 2026-07-15 21:31:13 ot_train.py:649 step:46K smpl:3M ep:67K epch:13.54 loss:0.028 grdn:0.270 lr:1.5e-05 updt_s:0.882 data_s:0.774 smp/s:39 mem_gb:39.65
+Training:  77%|███████▋  | 46400/60000 [20:21:45<6:42:41,  1.78s/step]INFO 2026-07-15 21:36:45 ot_train.py:649 step:46K smpl:3M ep:67K epch:13.60 loss:0.028 grdn:0.284 lr:1.5e-05 updt_s:0.889 data_s:0.769 smp/s:39 mem_gb:39.65
+Training:  78%|███████▊  | 46600/60000 [20:27:17<5:58:05,  1.60s/step]INFO 2026-07-15 21:42:18 ot_train.py:649 step:47K smpl:3M ep:67K epch:13.66 loss:0.027 grdn:0.278 lr:1.5e-05 updt_s:0.895 data_s:0.762 smp/s:39 mem_gb:39.65
+Training:  78%|███████▊  | 46800/60000 [20:32:42<6:00:52,  1.64s/step]INFO 2026-07-15 21:47:42 ot_train.py:649 step:47K smpl:3M ep:68K epch:13.72 loss:0.027 grdn:0.281 lr:1.4e-05 updt_s:0.924 data_s:0.692 smp/s:40 mem_gb:39.65
+Training:  78%|███████▊  | 47000/60000 [20:38:13<6:04:53,  1.68s/step]INFO 2026-07-15 21:53:13 ot_train.py:649 step:47K smpl:3M ep:68K epch:13.77 loss:0.028 grdn:0.305 lr:1.4e-05 updt_s:0.898 data_s:0.753 smp/s:39 mem_gb:39.65
+Training:  79%|███████▊  | 47200/60000 [20:43:27<5:31:43,  1.55s/step]INFO 2026-07-15 21:58:28 ot_train.py:649 step:47K smpl:3M ep:68K epch:13.83 loss:0.028 grdn:0.278 lr:1.3e-05 updt_s:0.913 data_s:0.654 smp/s:41 mem_gb:39.65
+Training:  79%|███████▉  | 47400/60000 [20:48:42<5:23:56,  1.54s/step]INFO 2026-07-15 22:03:42 ot_train.py:649 step:47K smpl:3M ep:68K epch:13.89 loss:0.027 grdn:0.268 lr:1.3e-05 updt_s:0.970 data_s:0.598 smp/s:41 mem_gb:39.63
+Training:  79%|███████▉  | 47600/60000 [20:53:46<5:00:27,  1.45s/step]INFO 2026-07-15 22:08:46 ot_train.py:649 step:48K smpl:3M ep:69K epch:13.95 loss:0.026 grdn:0.262 lr:1.3e-05 updt_s:0.964 data_s:0.555 smp/s:42 mem_gb:39.65
+Training:  80%|███████▉  | 47800/60000 [20:58:52<5:07:57,  1.51s/step]INFO 2026-07-15 22:13:52 ot_train.py:649 step:48K smpl:3M ep:69K epch:14.01 loss:0.026 grdn:0.267 lr:1.2e-05 updt_s:0.965 data_s:0.561 smp/s:42 mem_gb:39.65
+Training:  80%|████████  | 48000/60000 [21:03:57<5:17:02,  1.59s/step]INFO 2026-07-15 22:18:57 ot_train.py:649 step:48K smpl:3M ep:69K epch:14.07 loss:0.026 grdn:0.275 lr:1.2e-05 updt_s:0.963 data_s:0.559 smp/s:42 mem_gb:39.65
+Training:  80%|████████  | 48200/60000 [21:09:09<5:16:35,  1.61s/step]INFO 2026-07-15 22:24:09 ot_train.py:649 step:48K smpl:3M ep:70K epch:14.13 loss:0.026 grdn:0.273 lr:1.2e-05 updt_s:0.978 data_s:0.578 smp/s:41 mem_gb:39.65
+Training:  81%|████████  | 48400/60000 [21:14:20<4:55:40,  1.53s/step]INFO 2026-07-15 22:29:20 ot_train.py:649 step:48K smpl:3M ep:70K epch:14.19 loss:0.026 grdn:0.267 lr:1.1e-05 updt_s:0.933 data_s:0.617 smp/s:41 mem_gb:39.65
+Training:  81%|████████  | 48600/60000 [21:19:50<5:11:16,  1.64s/step]INFO 2026-07-15 22:34:51 ot_train.py:649 step:49K smpl:3M ep:70K epch:14.24 loss:0.025 grdn:0.260 lr:1.1e-05 updt_s:0.894 data_s:0.754 smp/s:39 mem_gb:39.65
+Training:  81%|████████▏ | 48800/60000 [21:25:23<5:06:32,  1.64s/step]INFO 2026-07-15 22:40:23 ot_train.py:649 step:49K smpl:3M ep:71K epch:14.30 loss:0.026 grdn:0.277 lr:1.0e-05 updt_s:0.866 data_s:0.792 smp/s:39 mem_gb:39.65
+Training:  82%|████████▏ | 49000/60000 [21:30:57<5:02:20,  1.65s/step]INFO 2026-07-15 22:45:57 ot_train.py:649 step:49K smpl:3M ep:71K epch:14.36 loss:0.025 grdn:0.260 lr:1.0e-05 updt_s:0.874 data_s:0.792 smp/s:38 mem_gb:39.65
+Training:  82%|████████▏ | 49200/60000 [21:36:29<5:00:34,  1.67s/step]INFO 2026-07-15 22:51:29 ot_train.py:649 step:49K smpl:3M ep:71K epch:14.42 loss:0.025 grdn:0.268 lr:9.7e-06 updt_s:0.862 data_s:0.794 smp/s:39 mem_gb:39.65
+Training:  82%|████████▏ | 49400/60000 [21:42:02<4:53:06,  1.66s/step]INFO 2026-07-15 22:57:03 ot_train.py:649 step:49K smpl:3M ep:71K epch:14.48 loss:0.025 grdn:0.261 lr:9.4e-06 updt_s:0.862 data_s:0.800 smp/s:39 mem_gb:39.65
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+Training:  97%|█████████▋| 58000/60000 [25:46:17<55:19,  1.66s/step]INFO 2026-07-16 03:01:17 ot_train.py:649 step:58K smpl:4M ep:84K epch:17.00 loss:0.021 grdn:0.243 lr:3.7e-07 updt_s:0.870 data_s:0.783 smp/s:39 mem_gb:39.65
+Training:  97%|█████████▋| 58200/60000 [25:51:50<45:44,  1.52s/step]INFO 2026-07-16 03:06:50 ot_train.py:649 step:58K smpl:4M ep:84K epch:17.06 loss:0.021 grdn:0.232 lr:3.1e-07 updt_s:0.918 data_s:0.743 smp/s:39 mem_gb:39.65
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+Training:  98%|█████████▊| 58600/60000 [26:02:43<36:31,  1.57s/step]INFO 2026-07-16 03:17:44 ot_train.py:649 step:59K smpl:4M ep:85K epch:17.17 loss:0.022 grdn:0.244 lr:1.9e-07 updt_s:0.937 data_s:0.713 smp/s:39 mem_gb:39.65
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+Training:  98%|█████████▊| 59000/60000 [26:13:57<29:22,  1.76s/step]INFO 2026-07-16 03:28:57 ot_train.py:649 step:59K smpl:4M ep:85K epch:17.29 loss:0.022 grdn:0.253 lr:1.0e-07 updt_s:0.871 data_s:0.801 smp/s:38 mem_gb:39.65
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+Training:  99%|█████████▉| 59400/60000 [26:25:06<16:52,  1.69s/step]INFO 2026-07-16 03:40:07 ot_train.py:649 step:59K smpl:4M ep:86K epch:17.41 loss:0.022 grdn:0.244 lr:4.2e-08 updt_s:0.914 data_s:0.752 smp/s:38 mem_gb:39.65
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+Training: 100%|██████████| 60000/60000 [26:41:52<00:00,  1.65s/step]INFO 2026-07-16 03:56:52 ot_train.py:649 step:60K smpl:4M ep:87K epch:17.59 loss:0.021 grdn:0.238 lr:1.1e-09 updt_s:0.878 data_s:0.795 smp/s:38 mem_gb:39.65
+INFO 2026-07-16 03:56:52 ot_train.py:694 Checkpoint policy after step 60000
+INFO 2026-07-16 03:57:25 ain_yaml.py:918 Saved config, action-space, prompt, and phase provenance in /home/ext_minje/groot_insight/Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K and /home/ext_minje/groot_insight/Abs_6D/RKD_TimewarpVAE/LAPstyle_linear_6K/checkpoints/060000
+Training: 100%|██████████| 60000/60000 [26:42:25<00:00,  1.60s/step]
+INFO 2026-07-16 03:57:25 ot_train.py:780 End of training