=== Avatar Training (fire-and-forget) === Script: train_pi0fast.py Started: 2026-03-11 01:43:03 UTC >>> [0/4] Raising file descriptor limit... ulimit -n = 1048576 >>> [1/4] Setting environment... HF_TOKEN set: 37 chars WANDB_API_KEY set: 0 chars >>> [2/4] Logging into HuggingFace... The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `hf`CLI if you want to set the git credential as well. Token is valid (permission: write). The token `avatar` has been saved to /root/.cache/huggingface/stored_tokens Your token has been saved to /root/.cache/huggingface/token Login successful. Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured. ⚠️ Warning: 'huggingface-cli login' is deprecated. Use 'hf auth login' instead. >>> [3/4] Pre-downloading pretrained model... Downloading lerobot/pi0fast-base (default)... Fetching 6 files: 0%| | 0/6 [00:00>> [4/4] Launching accelerate with 1 GPUs... Script: train_pi0fast.py Train args: --dataset fixed_motion_simple --steps 5000 --batch-size 4 --save-freq 1000 --push-to-hub --task-text move\ arm\ back\ and\ forth ============================================================ π₀-FAST Training ============================================================ Dataset: hamidavatar/fixed_motion_simple Pretrained: lerobot/pi0fast-base Model repo: hamidavatar/pi0fast-fixed-motion-simple-b4-20260311-0143 Steps: 5000 Batch/GPU: 4 (eff: 4) Chunk size: 10 LR: 2.5e-05 Save freq: 1000 GPUs: 1 ============================================================ lerobot_train \ --dataset.repo_id=hamidavatar/fixed_motion_simple \ --policy.type=pi0_fast \ --policy.pretrained_path=lerobot/pi0fast-base \ --policy.repo_id=hamidavatar/pi0fast-fixed-motion-simple-b4-20260311-0143 \ --policy.dtype=bfloat16 \ --policy.gradient_checkpointing=true \ --policy.chunk_size=10 \ --policy.n_action_steps=10 \ --policy.max_action_tokens=256 \ --policy.optimizer_lr=2.5e-05 \ --policy.optimizer_weight_decay=0.01 \ --policy.scheduler_warmup_steps=1000 \ --policy.scheduler_decay_steps=5000 \ --policy.scheduler_decay_lr=1e-6 \ --batch_size=4 \ --steps=5000 \ --save_freq=1000 \ --log_freq=100 \ --save_checkpoint=true \ --seed=1000 \ --num_workers=4 \ --output_dir=outputs/train/pi0fast \ --policy.push_to_hub=true \ --policy.private=true \ [Avatar] cudnn.benchmark=True, tf32=True [Avatar] Checkpoint push enabled → hamidavatar/pi0fast-fixed-motion-simple-b4-20260311-0143 (with per-step tags) [Avatar] Dataset task text patched → "move arm back and forth" [Avatar] Installed corrupt-frame retry handler WARNING:lerobot.configs.policies:Device 'None' is not available. Switching to 'cuda'. INFO 2026-03-11 01:43:43 ot_train.py:197 {'batch_size': 4, 'checkpoint_path': None, 'dataset': {'episodes': None, 'image_transforms': {'enable': False, 'max_num_transforms': 3, 'random_order': False, 'tfs': {'affine': {'kwargs': {'degrees': [-5.0, 5.0], 'translate': [0.05, 0.05]}, 'type': 'RandomAffine', 'weight': 1.0}, 'brightness': {'kwargs': {'brightness': [0.8, 1.2]}, 'type': 'ColorJitter', 'weight': 1.0}, 'contrast': {'kwargs': {'contrast': [0.8, 1.2]}, 'type': 'ColorJitter', 'weight': 1.0}, 'hue': {'kwargs': {'hue': [-0.05, 0.05]}, 'type': 'ColorJitter', 'weight': 1.0}, 'saturation': {'kwargs': {'saturation': [0.5, 1.5]}, 'type': 'ColorJitter', 'weight': 1.0}, 'sharpness': {'kwargs': {'sharpness': [0.5, 1.5]}, 'type': 'SharpnessJitter', 'weight': 1.0}}}, 'repo_id': 'hamidavatar/fixed_motion_simple', 'revision': None, 'root': None, 'streaming': False, 'use_imagenet_stats': True, 'video_backend': 'torchcodec'}, 'env': None, 'eval': {'batch_size': 50, 'n_episodes': 50, 'use_async_envs': False}, 'eval_freq': 20000, 'job_name': 'pi0_fast', 'log_freq': 100, 'num_workers': 4, 'optimizer': {'betas': [0.9, 0.95], 'eps': 1e-08, 'grad_clip_norm': 1.0, 'lr': 2.5e-05, 'type': 'adamw', 'weight_decay': 0.01}, 'output_dir': 'outputs/train/pi0fast', 'peft': None, 'policy': {'action_expert_variant': 'gemma_300m', 'action_tokenizer_name': 'physical-intelligence/fast', 'chunk_size': 10, 'compile_mode': 'max-autotune', 'compile_model': False, 'device': 'cuda', 'dtype': 'bfloat16', 'empty_cameras': 0, 'fast_skip_tokens': 128, 'gradient_checkpointing': True, 'image_resolution': [224, 224], 'input_features': {}, 'license': None, 'max_action_dim': 32, 'max_action_tokens': 256, 'max_decoding_steps': 256, 'max_state_dim': 32, 'n_action_steps': 10, 'n_obs_steps': 1, 'normalization_mapping': {'ACTION': , 'STATE': , 'VISUAL': }, 'optimizer_betas': [0.9, 0.95], 'optimizer_eps': 1e-08, 'optimizer_grad_clip_norm': 1.0, 'optimizer_lr': 2.5e-05, 'optimizer_weight_decay': 0.01, 'output_features': {}, 'paligemma_variant': 'gemma_2b', 'pretrained_path': 'lerobot/pi0fast-base', 'private': True, 'push_to_hub': True, 'repo_id': 'hamidavatar/pi0fast-fixed-motion-simple-b4-20260311-0143', 'rtc_config': None, 'scheduler_decay_lr': 1e-06, 'scheduler_decay_steps': 5000, 'scheduler_warmup_steps': 1000, 'tags': None, 'temperature': 0.0, 'text_tokenizer_name': 'google/paligemma-3b-pt-224', 'tokenizer_max_length': 200, 'type': 'pi0_fast', 'use_amp': False, 'use_kv_cache': True, 'use_peft': False, 'validate_action_token_prefix': True}, 'rabc_epsilon': 1e-06, 'rabc_head_mode': 'sparse', 'rabc_kappa': 0.01, 'rabc_progress_path': None, 'rename_map': {}, 'resume': False, 'save_checkpoint': True, 'save_freq': 1000, 'scheduler': {'decay_lr': 1e-06, 'num_decay_steps': 5000, 'num_warmup_steps': 1000, 'peak_lr': 2.5e-05, 'type': 'cosine_decay_with_warmup'}, 'seed': 1000, 'steps': 5000, 'tolerance_s': 0.0001, 'use_policy_training_preset': True, 'use_rabc': False, 'wandb': {'disable_artifact': False, 'enable': False, 'entity': None, 'mode': None, 'notes': None, 'project': 'lerobot', 'run_id': None}} INFO 2026-03-11 01:43:43 ot_train.py:205 Logs will be saved locally. INFO 2026-03-11 01:43:43 ot_train.py:217 Creating dataset Fetching 7 files: 0%| | 0/7 [00:00>> Training finished with exit code 0 Ended: 2026-03-11 02:58:16 UTC >>> Saving training log to HuggingFace...